climate model parameterizations: Topics by Science.gov

Sample records for climate model parameterizations

Collaborative Research: Reducing tropical precipitation biases in CESM — Tests of unified parameterizations with ARM observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Vincent; Gettelman, Andrew; Morrison, Hugh

In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we are creating a climate model that contains a unified cloud parameterization and a unified microphysics parameterization. This model will be used to address the problems of excessive frequency of drizzle in climate models and excessively early onset of deep convection in the Tropics over land.more » The resulting model will be compared with ARM observations.« less
Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-10-20

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less
Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less
Climate and the equilibrium state of land surface hydrology parameterizations

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less
Are Atmospheric Updrafts a Key to Unlocking Climate Forcing and Sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-06-08

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less
Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE PAGES

Berner, Judith; Achatz, Ulrich; Batté, Lauriane; ...

2017-03-31

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less
Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berner, Judith; Achatz, Ulrich; Batté, Lauriane

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less
Final Technical Report for "Reducing tropical precipitation biases in CESM"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Vincent

In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we have created a climate model that contains a unified cloud parameterization (“CLUBB”) and a unified microphysics parameterization (“MG2”). In this model, all cloud types --- including marine stratocumulus, shallow cumulus, and deep cumulus --- are represented with a single equation set. This model improves themore » representation of convection in the Tropics. The model has been compared with ARM observations. The chief benefit of the project is to provide a climate model that is based on a more theoretically rigorous formulation.« less
The effects of surface evaporation parameterizations on climate sensitivity to solar constant variations

NASA Technical Reports Server (NTRS)

Chou, S.-H.; Curran, R. J.; Ohring, G.

1981-01-01

The effects of two different evaporation parameterizations on the sensitivity of simulated climate to solar constant variations are investigated by using a zonally averaged climate model. One parameterization is a nonlinear formulation in which the evaporation is nonlinearly proportional to the sensible heat flux, with the Bowen ratio determined by the predicted vertical temperature and humidity gradients near the earth's surface (model A). The other is the formulation of Saltzman (1968) with the evaporation linearly proportional to the sensible heat flux (model B). The computed climates of models A and B are in good agreement except for the energy partition between sensible and latent heat at the earth's surface. The difference in evaporation parameterizations causes a difference in the response of temperature lapse rate to solar constant variations and a difference in the sensitivity of longwave radiation to surface temperature which leads to a smaller sensitivity of surface temperature to solar constant variations in model A than in model B. The results of model A are qualitatively in agreement with those of the general circulation model calculations of Wetherald and Manabe (1975).
Trends and uncertainties in budburst projections of Norway spruce in Northern Europe.

PubMed

Olsson, Cecilia; Olin, Stefan; Lindström, Johan; Jönsson, Anna Maria

2017-12-01

Budburst is regulated by temperature conditions, and a warming climate is associated with earlier budburst. A range of phenology models has been developed to assess climate change effects, and they tend to produce different results. This is mainly caused by different model representations of tree physiology processes, selection of observational data for model parameterization, and selection of climate model data to generate future projections. In this study, we applied (i) Bayesian inference to estimate model parameter values to address uncertainties associated with selection of observational data, (ii) selection of climate model data representative of a larger dataset, and (iii) ensembles modeling over multiple initial conditions, model classes, model parameterizations, and boundary conditions to generate future projections and uncertainty estimates. The ensemble projection indicated that the budburst of Norway spruce in northern Europe will on average take place 10.2 ± 3.7 days earlier in 2051-2080 than in 1971-2000, given climate conditions corresponding to RCP 8.5. Three provenances were assessed separately (one early and two late), and the projections indicated that the relationship among provenance will remain also in a warmer climate. Structurally complex models were more likely to fail predicting budburst for some combinations of site and year than simple models. However, they contributed to the overall picture of current understanding of climate impacts on tree phenology by capturing additional aspects of temperature response, for example, chilling. Model parameterizations based on single sites were more likely to result in model failure than parameterizations based on multiple sites, highlighting that the model parameterization is sensitive to initial conditions and may not perform well under other climate conditions, whether the change is due to a shift in space or over time. By addressing a range of uncertainties, this study showed that ensemble modeling provides a more robust impact assessment than would a single phenology model run.
Impact of Physics Parameterization Ordering in a Global Atmosphere Model

DOE PAGES

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-02

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less
Impact of Physics Parameterization Ordering in a Global Atmosphere Model

NASA Astrophysics Data System (ADS)

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-01

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.
Impact of Physics Parameterization Ordering in a Global Atmosphere Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donahue, Aaron S.; Caldwell, Peter M.

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less
Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies

NASA Astrophysics Data System (ADS)

Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj

2016-04-01

In climate simulations, the impacts of the sub-grid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the sub-grid variability in a computationally inexpensive manner. This presentation shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition, by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a non-zero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference PD Williams, NJ Howe, JM Gregory, RS Smith, and MM Joshi (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, under revision.
a Physical Parameterization of Snow Albedo for Use in Climate Models.

NASA Astrophysics Data System (ADS)

Marshall, Susan Elaine

The albedo of a natural snowcover is highly variable ranging from 90 percent for clean, new snow to 30 percent for old, dirty snow. This range in albedo represents a difference in surface energy absorption of 10 to 70 percent of incident solar radiation. Most general circulation models (GCMs) fail to calculate the surface snow albedo accurately, yet the results of these models are sensitive to the assumed value of the snow albedo. This study replaces the current simple empirical parameterizations of snow albedo with a physically-based parameterization which is accurate (within +/- 3% of theoretical estimates) yet efficient to compute. The parameterization is designed as a FORTRAN subroutine (called SNOALB) which can be easily implemented into model code. The subroutine requires less then 0.02 seconds of computer time (CRAY X-MP) per call and adds only one new parameter to the model calculations, the snow grain size. The snow grain size can be calculated according to one of the two methods offered in this thesis. All other input variables to the subroutine are available from a climate model. The subroutine calculates a visible, near-infrared and solar (0.2-5 μm) snow albedo and offers a choice of two wavelengths (0.7 and 0.9 mu m) at which the solar spectrum is separated into the visible and near-infrared components. The parameterization is incorporated into the National Center for Atmospheric Research (NCAR) Community Climate Model, version 1 (CCM1), and the results of a five -year, seasonal cycle, fixed hydrology experiment are compared to the current model snow albedo parameterization. The results show the SNOALB albedos to be comparable to the old CCM1 snow albedos for current climate conditions, with generally higher visible and lower near-infrared snow albedos using the new subroutine. However, this parameterization offers a greater predictability for climate change experiments outside the range of current snow conditions because it is physically-based and not tuned to current empirical results.
The QBO in Two GISS Global Climate Models: 1. Generation of the QBO

NASA Technical Reports Server (NTRS)

Rind, David; Jonas, Jeffrey A.; Balachandra, Nambath; Schmidt, Gavin A.; Lean, Judith

2014-01-01

The adjustment of parameterized gravity waves associated with model convection and finer vertical resolution has made possible the generation of the quasi-biennial oscillation (QBO) in two Goddard Institute for Space Studies (GISS) models, GISS Middle Atmosphere Global Climate Model III and a climate/middle atmosphere version of Model E2. Both extend from the surface to 0.002 hPa, with 2deg × 2.5deg resolution and 102 layers. Many realistic features of the QBO are simulated, including magnitude and variability of its period and amplitude. The period itself is affected by the magnitude of parameterized convective gravity wave momentum fluxes and interactive ozone (which also affects the QBO amplitude and variability), among other forcings. Although varying sea surface temperatures affect the parameterized momentum fluxes, neither aspect is responsible for the modeled variation in QBO period. Both the parameterized and resolved waves act to produce the respective easterly and westerly wind descent, although their effect is offset in altitude at each level. The modeled and observed QBO influences on tracers in the stratosphere, such as ozone, methane, and water vapor are also discussed. Due to the link between the gravity wave parameterization and the models' convection, and the dependence on the ozone field, the models may also be used to investigate how the QBO may vary with climate change.
Technical report series on global modeling and data assimilation. Volume 3: An efficient thermal infrared radiation parameterization for use in general circulation models

NASA Technical Reports Server (NTRS)

Suarex, Max J. (Editor); Chou, Ming-Dah

1994-01-01

A detailed description of a parameterization for thermal infrared radiative transfer designed specifically for use in global climate models is presented. The parameterization includes the effects of the main absorbers of terrestrial radiation: water vapor, carbon dioxide, and ozone. While being computationally efficient, the schemes compute very accurately the clear-sky fluxes and cooling rates from the Earth's surface to 0.01 mb. This combination of accuracy and speed makes the parameterization suitable for both tropospheric and middle atmospheric modeling applications. Since no transmittances are precomputed the atmospheric layers and the vertical distribution of the absorbers may be freely specified. The scheme can also account for any vertical distribution of fractional cloudiness with arbitrary optical thickness. These features make the parameterization very flexible and extremely well suited for use in climate modeling studies. In addition, the numerics and the FORTRAN implementation have been carefully designed to conserve both memory and computer time. This code should be particularly attractive to those contemplating long-term climate simulations, wishing to model the middle atmosphere, or planning to use a large number of levels in the vertical.
The cloud-phase feedback in the Super-parameterized Community Earth System Model

NASA Astrophysics Data System (ADS)

Burt, M. A.; Randall, D. A.

2016-12-01

Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.
Objective calibration of regional climate models

NASA Astrophysics Data System (ADS)

Bellprat, O.; Kotlarski, S.; Lüthi, D.; SchäR, C.

2012-12-01

Climate models are subject to high parametric uncertainty induced by poorly confined model parameters of parameterized physical processes. Uncertain model parameters are typically calibrated in order to increase the agreement of the model with available observations. The common practice is to adjust uncertain model parameters manually, often referred to as expert tuning, which lacks objectivity and transparency in the use of observations. These shortcomings often haze model inter-comparisons and hinder the implementation of new model parameterizations. Methods which would allow to systematically calibrate model parameters are unfortunately often not applicable to state-of-the-art climate models, due to computational constraints facing the high dimensionality and non-linearity of the problem. Here we present an approach to objectively calibrate a regional climate model, using reanalysis driven simulations and building upon a quadratic metamodel presented by Neelin et al. (2010) that serves as a computationally cheap surrogate of the model. Five model parameters originating from different parameterizations are selected for the optimization according to their influence on the model performance. The metamodel accurately estimates spatial averages of 2 m temperature, precipitation and total cloud cover, with an uncertainty of similar magnitude as the internal variability of the regional climate model. The non-linearities of the parameter perturbations are well captured, such that only a limited number of 20-50 simulations are needed to estimate optimal parameter settings. Parameter interactions are small, which allows to further reduce the number of simulations. In comparison to an ensemble of the same model which has undergone expert tuning, the calibration yields similar optimal model configurations, but leading to an additional reduction of the model error. The performance range captured is much wider than sampled with the expert-tuned ensemble and the presented methodology is effective and objective. It is argued that objective calibration is an attractive tool and could become standard procedure after introducing new model implementations, or after a spatial transfer of a regional climate model. Objective calibration of parameterizations with regional models could also serve as a strategy toward improving parameterization packages of global climate models.

The effects of ground hydrology on climate sensitivity to solar constant variations

NASA Technical Reports Server (NTRS)

Chou, S. H.; Curran, R. J.; Ohring, G.

1979-01-01

The effects of two different evaporation parameterizations on the climate sensitivity to solar constant variations are investigated by using a zonally averaged climate model. The model is based on a two-level quasi-geostrophic zonally averaged annual mean model. One of the evaporation parameterizations tested is a nonlinear formulation with the Bowen ratio determined by the predicted vertical temperature and humidity gradients near the earth's surface. The other is the linear formulation with the Bowen ratio essentially determined by the prescribed linear coefficient.
Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies

NASA Astrophysics Data System (ADS)

Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj

2017-04-01

In climate simulations, the impacts of the subgrid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the subgrid variability in a computationally inexpensive manner. This study shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a nonzero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference Williams PD, Howe NJ, Gregory JM, Smith RS, and Joshi MM (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, 29, 8763-8781. http://dx.doi.org/10.1175/JCLI-D-15-0746.1
A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

Thayer-Calder, K.; Gettelman, A.; Craig, C.; ...

2015-06-30

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into amore » microphysics scheme.This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less
A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

Thayer-Calder, Katherine; Gettelman, A.; Craig, Cheryl; ...

2015-12-01

Most global climate models parameterize separate cloud types using separate parameterizations.This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysicsmore » scheme. This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. In conclusion, the new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, perceptible water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less
Parameterization Interactions in Global Aquaplanet Simulations

NASA Astrophysics Data System (ADS)

Bhattacharya, Ritthik; Bordoni, Simona; Suselj, Kay; Teixeira, João.

2018-02-01

Global climate simulations rely on parameterizations of physical processes that have scales smaller than the resolved ones. In the atmosphere, these parameterizations represent moist convection, boundary layer turbulence and convection, cloud microphysics, longwave and shortwave radiation, and the interaction with the land and ocean surface. These parameterizations can generate different climates involving a wide range of interactions among parameterizations and between the parameterizations and the resolved dynamics. To gain a simplified understanding of a subset of these interactions, we perform aquaplanet simulations with the global version of the Weather Research and Forecasting (WRF) model employing a range (in terms of properties) of moist convection and boundary layer (BL) parameterizations. Significant differences are noted in the simulated precipitation amounts, its partitioning between convective and large-scale precipitation, as well as in the radiative impacts. These differences arise from the way the subcloud physics interacts with convection, both directly and through various pathways involving the large-scale dynamics and the boundary layer, convection, and clouds. A detailed analysis of the profiles of the different tendencies (from the different physical processes) for both potential temperature and water vapor is performed. While different combinations of convection and boundary layer parameterizations can lead to different climates, a key conclusion of this study is that similar climates can be simulated with model versions that are different in terms of the partitioning of the tendencies: the vertically distributed energy and water balances in the tropics can be obtained with significantly different profiles of large-scale, convection, and cloud microphysics tendencies.
Estimating the Contrail Impact on Climate Using the UK Met Office Model

NASA Astrophysics Data System (ADS)

Rap, A.; Forster, P. M.

2008-12-01

With air travel predicted to increase over the coming century, the emissions associated with air traffic are expected to have a significant warming effect on climate. According to current best estimates, an important contribution comes from contrails. However, as reported by the IPCC fourth assessment report, these current best estimates still have a high uncertainty. The development and validation of contrail parameterizations in global climate models is therefore very important. This current study develops a contrail parameterization within the UK Met Office Climate Model. Using this new parameterization, we estimate that for the 2002 traffic, the global mean annual contrail coverage is approximately 0.11%, a value which in good agreement with several other estimates. The corresponding contrail radiative forcing (RF) is calculated to be approximately 4 and 6 mWm-2 in all-sky and clear-sky conditions, respectively. These values lie within the lower end of the RF range reported by the latest IPCC assessment. The relatively high cloud masking effect on contrails observed by our parameterization compared with other studies is investigated, and a possible cause for this difference is suggested. The effect of the diurnal variations of air traffic on both contrail coverage and contrail RF is also investigated. The new parameterization is also employed in thirty-year slab-ocean model runs in order to give one of the first insights into contrail effects on daily temperature range and the climate impact of contrails.
Radiative flux and forcing parameterization error in aerosol-free clear skies

DOE PAGES

Pincus, Robert; Mlawer, Eli J.; Oreopoulos, Lazaros; ...

2015-07-03

This article reports on the accuracy in aerosol- and cloud-free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present-day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m 2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present-day conditions is essentiallymore » unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. As a result, a dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations.« less
Coordinated Parameterization Development and Large-Eddy Simulation for Marine and Arctic Cloud-Topped Boundary Layers

NASA Technical Reports Server (NTRS)

Bretherton, Christopher S.

2002-01-01

The goal of this project was to compare observations of marine and arctic boundary layers with: (1) parameterization systems used in climate and weather forecast models; and (2) two and three dimensional eddy resolving (LES) models for turbulent fluid flow. Based on this comparison, we hoped to better understand, predict, and parameterize the boundary layer structure and cloud amount, type, and thickness as functions of large scale conditions that are predicted by global climate models. The principal achievements of the project were as follows: (1) Development of a novel boundary layer parameterization for large-scale models that better represents the physical processes in marine boundary layer clouds; and (2) Comparison of column output from the ECMWF global forecast model with observations from the SHEBA experiment. Overall the forecast model did predict most of the major precipitation events and synoptic variability observed over the year of observation of the SHEBA ice camp.
Simulating Aerosol Indirect Effects with Improved Aerosol-Cloud- Precipitation Representations in a Coupled Regional Climate Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yang; Leung, L. Ruby; Fan, Jiwen

This is a collaborative project among North Carolina State University, Pacific Northwest National Laboratory, and Scripps Institution of Oceanography, University of California at San Diego to address the critical need for an accurate representation of aerosol indirect effect in climate and Earth system models. In this project, we propose to develop and improve parameterizations of aerosol-cloud-precipitation feedbacks in climate models and apply them to study the effect of aerosols and clouds on radiation and hydrologic cycle. Our overall objective is to develop, improve, and evaluate parameterizations to enable more accurate simulations of these feedbacks in high resolution regional and globalmore » climate models.« less
Single-Column Modeling, GCM Parameterizations and Atmospheric Radiation Measurement Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Somerville, R.C.J.; Iacobellis, S.F.

2005-03-18

Our overall goal is identical to that of the Atmospheric Radiation Measurement (ARM) Program: the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global and regional models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have first compared single-column model (SCM) output with ARM observations at the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Topical Western Pacific (TWP) sites. We focus on the predicted cloud amounts and on a suite of radiativemore » quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art 3D atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable. We are currently testing the performance of our ARM-based parameterizations in state-of-the--art global and regional models. One fruitful strategy for evaluating advances in parameterizations has turned out to be using short-range numerical weather prediction as a test-bed within which to implement and improve parameterizations for modeling and predicting climate variability. The global models we have used to date are the CAM atmospheric component of the National Center for Atmospheric Research (NCAR) CCSM climate model as well as the National Centers for Environmental Prediction (NCEP) numerical weather prediction model, thus allowing testing in both climate simulation and numerical weather prediction modes. We present detailed results of these tests, demonstrating the sensitivity of model performance to changes in parameterizations.« less
Scale dependency of regional climate modeling of current and future climate extremes in Germany

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.
Cloud-radiation interactions and their parameterization in climate models

NASA Technical Reports Server (NTRS)

1994-01-01

This report contains papers from the International Workshop on Cloud-Radiation Interactions and Their Parameterization in Climate Models met on 18-20 October 1993 in Camp Springs, Maryland, USA. It was organized by the Joint Working Group on Clouds and Radiation of the International Association of Meteorology and Atmospheric Sciences. Recommendations were grouped into three broad areas: (1) general circulation models (GCMs), (2) satellite studies, and (3) process studies. Each of the panels developed recommendations on the themes of the workshop. Explicitly or implicitly, each panel independently recommended observations of basic cloud microphysical properties (water content, phase, size) on the scales resolved by GCMs. Such observations are necessary to validate cloud parameterizations in GCMs, to use satellite data to infer radiative forcing in the atmosphere and at the earth's surface, and to refine the process models which are used to develop advanced cloud parameterizations.
Sensitivity of Glacier Mass Balance Estimates to the Selection of WRF Cloud Microphysics Parameterization in the Indus River Watershed

NASA Astrophysics Data System (ADS)

Johnson, E. S.; Rupper, S.; Steenburgh, W. J.; Strong, C.; Kochanski, A.

2017-12-01

Climate model outputs are often used as inputs to glacier energy and mass balance models, which are essential glaciological tools for testing glacier sensitivity, providing mass balance estimates in regions with little glaciological data, and providing a means to model future changes. Climate model outputs, however, are sensitive to the choice of physical parameterizations, such as those for cloud microphysics, land-surface schemes, surface layer options, etc. Furthermore, glacier mass balance (MB) estimates that use these climate model outputs as inputs are likely sensitive to the specific parameterization schemes, but this sensitivity has not been carefully assessed. Here we evaluate the sensitivity of glacier MB estimates across the Indus Basin to the selection of cloud microphysics parameterizations in the Weather Research and Forecasting Model (WRF). Cloud microphysics parameterizations differ in how they specify the size distributions of hydrometeors, the rate of graupel and snow production, their fall speed assumptions, the rates at which they convert from one hydrometeor type to the other, etc. While glacier MB estimates are likely sensitive to other parameterizations in WRF, our preliminary results suggest that glacier MB is highly sensitive to the timing, frequency, and amount of snowfall, which is influenced by the cloud microphysics parameterization. To this end, the Indus Basin is an ideal study site, as it has both westerly (winter) and monsoonal (summer) precipitation influences, is a data-sparse region (so models are critical), and still has lingering questions as to glacier importance for local and regional resources. WRF is run at a 4 km grid scale using two commonly used parameterizations: the Thompson scheme and the Goddard scheme. On average, these parameterizations result in minimal differences in annual precipitation. However, localized regions exhibit differences in precipitation of up to 3 m w.e. a-1. The different schemes also impact the radiative budgets over the glacierized areas. Our results show that glacier MB estimates can differ by up to 45% depending on the chosen cloud microphysics scheme. These findings highlight the need to better account for uncertainties in meteorological inputs into glacier energy and mass balance models.
Studies in the parameterization of cloudiness in climate models and the analysis of radiation fields in general circulation models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1990-01-01

Broad-band parameterizations for atmospheric radiative transfer were developed for clear and cloudy skies. These were in the shortwave and longwave regions of the spectrum. These models were compared with other models in an international effort called ICRCCM (Intercomparison of Radiation Codes for Climate Models). The radiation package developed was used for simulations of a General Circulation Model (GCM). A synopsis is provided of the research accomplishments in the two areas separately. Details are available in the published literature.
Extensions and applications of a second-order landsurface parameterization

NASA Technical Reports Server (NTRS)

Andreou, S. A.; Eagleson, P. S.

1983-01-01

Extensions and applications of a second order land surface parameterization, proposed by Andreou and Eagleson are developed. Procedures for evaluating the near surface storage depth used in one cell land surface parameterizations are suggested and tested by using the model. Sensitivity analysis to the key soil parameters is performed. A case study involving comparison with an "exact" numerical model and another simplified parameterization, under very dry climatic conditions and for two different soil types, is also incorporated.
Mixing parametrizations for ocean climate modelling

NASA Astrophysics Data System (ADS)

Gusev, Anatoly; Moshonkin, Sergey; Diansky, Nikolay; Zalesny, Vladimir

2016-04-01

The algorithm is presented of splitting the total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF), which is used to parameterize the viscosity and diffusion coefficients in ocean circulation models. The turbulence model equations are split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage, the following schemes are implemented: the explicit-implicit numerical scheme, analytical solution and the asymptotic behavior of the analytical solutions. The experiments were performed with different mixing parameterizations for the modelling of Arctic and the Atlantic climate decadal variability with the eddy-permitting circulation model INMOM (Institute of Numerical Mathematics Ocean Model) using vertical grid refinement in the zone of fully developed turbulence. The proposed model with the split equations for turbulence characteristics is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. Parameterizations with using the split turbulence model make it possible to obtain more adequate structure of temperature and salinity at decadal timescales, compared to the simpler Pacanowski-Philander (PP) turbulence parameterization. Parameterizations with using analytical solution or numerical scheme at the generation-dissipation step of the turbulence model leads to better representation of ocean climate than the faster parameterization using the asymptotic behavior of the analytical solution. At the same time, the computational efficiency left almost unchanged relative to the simple PP parameterization. Usage of PP parametrization in the circulation model leads to realistic simulation of density and circulation with violation of T,S-relationships. This error is majorly avoided with using the proposed parameterizations containing the split turbulence model. The high sensitivity of the eddy-permitting circulation model to the definition of mixing is revealed, which is associated with significant changes of density fields in the upper baroclinic ocean layer over the total considered area. For instance, usage of the turbulence parameterization instead of PP algorithm leads to increasing circulation velocity in the Gulf Stream and North Atlantic Current, as well as the subpolar cyclonic gyre in the North Atlantic and Beaufort Gyre in the Arctic basin are reproduced more realistically. Consideration of the Prandtl number as a function of the Richardson number significantly increases the modelling quality. The research was supported by the Russian Foundation for Basic Research (grant № 16-05-00534) and the Council on the Russian Federation President Grants (grant № MK-3241.2015.5)
ARM - Midlatitude Continental Convective Clouds

DOE Data Explorer

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.
ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

DOE Data Explorer

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-06

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.
Improving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme

NASA Astrophysics Data System (ADS)

Xie, Xin

Microphysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.
A Review on Regional Convection-Permitting Climate Modeling: Demonstrations, Prospects, and Challenges

NASA Astrophysics Data System (ADS)

Prein, A. F.; Langhans, W.; Fosser, G.; Ferrone, A.; Ban, N.; Goergen, K.; Keller, M.; Tölle, M.; Gutjahr, O.; Feser, F.; Brisson, E.; Kollet, S. J.; Schmidli, J.; Van Lipzig, N. P. M.; Leung, L. R.

2015-12-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. We aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges.

PubMed

Prein, Andreas F; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P M; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.
A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges

NASA Astrophysics Data System (ADS)

Prein, Andreas F.; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P. M.; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.
Numerical Study of the Role of Shallow Convection in Moisture Transport and Climate

NASA Technical Reports Server (NTRS)

Seaman, Nelson L.; Stauffer, David R.; Munoz, Ricardo C.

2001-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins of the Southern Great Plains (SGP) using a 3-D mesoscale model, the PSU/NCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. At the beginning of the study, it was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having high-quality parameterizations for the key physical processes controlling the water cycle. These included a detailed land-surface parameterization (the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) sub-model of Wetzel and Boone), an advanced boundary-layer parameterization (the 1.5-order turbulent kinetic energy (TKE) predictive scheme of Shafran et al.), and a more complete shallow convection parameterization (the hybrid-closure scheme of Deng et al.) than are available in most current models. PLACE is a product of researchers working at NASA's Goddard Space Flight Center in Greenbelt, MD. The TKE and shallow-convection schemes are the result of model development at Penn State. The long-range goal is to develop an integrated suite of physical sub-models that can be used for regional and perhaps global climate studies of the water budget. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the SGP. These schemes have been tested extensively through the course of this study and the latter two have been improved significantly as a consequence.
Climate model biases in jet streams, blocking and storm tracks resulting from missing orographic drag

NASA Astrophysics Data System (ADS)

Pithan, Felix; Shepherd, Theodore G.; Zappa, Giuseppe; Sandu, Irina

2016-07-01

State-of-the art climate models generally struggle to represent important features of the large-scale circulation. Common model deficiencies include an equatorward bias in the location of the midlatitude westerlies and an overly zonal orientation of the North Atlantic storm track. Orography is known to strongly affect the atmospheric circulation and is notoriously difficult to represent in coarse-resolution climate models. Yet how the representation of orography affects circulation biases in current climate models is not understood. Here we show that the effects of switching off the parameterization of drag from low-level orographic blocking in one climate model resemble the biases of the Coupled Model Intercomparison Project Phase 5 ensemble: An overly zonal wintertime North Atlantic storm track and less European blocking events, and an equatorward shift in the Southern Hemispheric jet and increase in the Southern Annular Mode time scale. This suggests that typical circulation biases in coarse-resolution climate models may be alleviated by improved parameterizations of low-level drag.
10 Ways to Improve the Representation of MCSs in Climate Models

NASA Astrophysics Data System (ADS)

Schumacher, C.

2017-12-01

1. The first way to improve the representation of mesoscale convective systems (MCSs) in global climate models (GCMs) is to recognize that MCSs are important to climate. That may be obvious to most of the people attending this session, but it cannot be taken for granted in the wider community. The fact that MCSs produce large amounts of the global rainfall and that they dramatically impact the atmosphere via transports of heat, moisture, and momentum must be continuously stressed. 2-4. There has traditionally been three approaches to representing MCSs and/or their impacts in GCMs. The first is to focus on improving cumulus parameterizations by implementing things like cold pools that are assumed to better organize convection. The second is to focus on including mesoscale processes in the cumulus parameterization such as mesoscale vertical motions. The third is to just buy your way out with higher resolution using techniques like super-parameterization or global cloud-resolving model runs. All of these approaches have their pros and cons, but none of them satisfactorily solve the MCS climate modeling problem. 5-10. Looking forward, there is active discussion and new ideas in the modeling community on how to better represent convective organization in models. A number of ideas are a dramatic shift from the traditional plume-based cumulus parameterizations of most GCMs, such as implementing mesoscale parmaterizations based on their physical impacts (e.g., via heating), on empirical relationships based on big data/machine learning, or on stochastic approaches. Regardless of the technique employed, smart evaluation processes using observations are paramount to refining and constraining the inevitable tunable parameters in any parameterization.
Sensitivity of single column model simulations of Arctic springtime clouds to different cloud cover and mixed phase cloud parameterizations

NASA Astrophysics Data System (ADS)

Zhang, Junhua; Lohmann, Ulrike

2003-08-01

The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.
Prototype Mcs Parameterization for Global Climate Models

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.

2017-12-01

Excellent progress has been made with observational, numerical and theoretical studies of MCS processes but the parameterization of those processes remain in a dire state and are missing from GCMs. The perceived complexity of the distribution, type, and intensity of organized precipitation systems has arguably daunted attention and stifled the development of adequate parameterizations. TRMM observations imply links between convective organization and large-scale meteorological features in the tropics and subtropics that are inadequately treated by GCMs. This calls for improved physical-dynamical treatment of organized convection to enable the next-generation of GCMs to reliably address a slew of challenges. The multiscale coherent structure parameterization (MCSP) paradigm is based on the fluid-dynamical concept of coherent structures in turbulent environments. The effects of vertical shear on MCS dynamics implemented as 2nd baroclinic convective heating and convective momentum transport is based on Lagrangian conservation principles, nonlinear dynamical models, and self-similarity. The prototype MCS parameterization, a minimalist proof-of-concept, is applied in the NCAR Community Climate Model, Version 5.5 (CAM 5.5). The MCSP generates convectively coupled tropical waves and large-scale precipitation features notably in the Indo-Pacific warm-pool and Maritime Continent region, a center-of-action for weather and climate variability around the globe.
A stochastic multicloud convective parameterization in the NCEP Climate Forecast System (CFSv2) : implementation and calibration.

NASA Astrophysics Data System (ADS)

Goswami, B. B.; Khouider, B.; Krishna, R. P. M.; Mukhopadhyay, P.; Majda, A.

2017-12-01

A stochastic multicloud (SMCM) cumulus parameterization is implemented in the National Centres for Environmental Predictions (NCEP) Climate Forecast System version 2 (CFSv2) model, named as the CFSsmcm model. We present here results from a systematic attempt to understand the CFSsmcm model's sensitivity to the SMCM parameters. To asses the model-sentivity to the different SMCM parameters, we have analized a set of 14 5-year long climate simulations produced by the CFSsmcm model. The model is found to be resilient to minor changes in the parameter values. The middle tropospheric dryness (MTD) and the stratiform cloud decay timescale are found to be most crucial parameters in the SMCM formulation in the CFSsmcm model.
Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

NASA Astrophysics Data System (ADS)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach), and iii) process-level evaluation at climate time-scales. The advantages and disadvantages of each approach will be identified and discussed, and some thoughts about possible future developments will be given.
Current state of aerosol nucleation parameterizations for air-quality and climate modeling

NASA Astrophysics Data System (ADS)

Semeniuk, Kirill; Dastoor, Ashu

2018-04-01

Aerosol nucleation parameterization models commonly used in 3-D air quality and climate models have serious limitations. This includes classical nucleation theory based variants, empirical models and other formulations. Recent work based on detailed and extensive laboratory measurements and improved quantum chemistry computation has substantially advanced the state of nucleation parameterizations. In terms of inorganic nucleation involving BHN and THN including ion effects these new models should be considered as worthwhile replacements for the old models. However, the contribution of organic species to nucleation remains poorly quantified. New particle formation consists of a distinct post-nucleation growth regime which is characterized by a strong Kelvin curvature effect and is thus dependent on availability of very low volatility organic species or sulfuric acid. There have been advances in the understanding of the multiphase chemistry of biogenic and anthropogenic organic compounds which facilitate to overcome the initial aerosol growth barrier. Implementation of processes influencing new particle formation is challenging in 3-D models and there is a lack of comprehensive parameterizations. This review considers the existing models and recent innovations.
Final Report for “Simulating the Arctic Winter Longwave Indirect Effects. A New Parameterization for Frost Flower Aerosol Salt Emissions” (DESC0006679) for 9/15/2011 through 9/14/2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russell, Lynn M.; Somerville, Richard C.J.; Burrows, Susannah

Description of the Project: This project has improved the aerosol formulation in a global climate model by using innovative new field and laboratory observations to develop and implement a novel wind-driven sea ice aerosol flux parameterization. This work fills a critical gap in the understanding of clouds, aerosol, and radiation in polar regions by addressing one of the largest missing particle sources in aerosol-climate modeling. Recent measurements of Arctic organic and inorganic aerosol indicate that the largest source of natural aerosol during the Arctic winter is emitted from crystal structures, known as frost flowers, formed on a newly frozen seamore » ice surface [Shaw et al., 2010]. We have implemented the new parameterization in an updated climate model making it the first capable of investigating how polar natural aerosol-cloud indirect effects relate to this important and previously unrecognized sea ice source. The parameterization is constrained by Arctic ARM in situ cloud and radiation data. The modified climate model has been used to quantify the potential pan-Arctic radiative forcing and aerosol indirect effects due to this missing source. This research supported the work of one postdoc (Li Xu) for two years and contributed to the training and research of an undergraduate student. This research allowed us to establish a collaboration between SIO and PNNL in order to contribute the frost flower parameterization to the new ACME model. One peer-reviewed publications has already resulted from this work, and a manuscript for a second publication has been completed. Additional publications from the PNNL collaboration are expected to follow.« less
Exploring the potential of machine learning to break deadlock in convection parameterization

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Gentine, P.

2017-12-01

We explore the potential of modern machine learning tools (via TensorFlow) to replace parameterization of deep convection in climate models. Our strategy begins by generating a large ( 1 Tb) training dataset from time-step level (30-min) output harvested from a one-year integration of a zonally symmetric, uniform-SST aquaplanet integration of the SuperParameterized Community Atmosphere Model (SPCAM). We harvest the inputs and outputs connecting each of SPCAM's 8,192 embedded cloud-resolving model (CRM) arrays to its host climate model's arterial thermodynamic state variables to afford 143M independent training instances. We demonstrate that this dataset is sufficiently large to induce preliminary convergence for neural network prediction of desired outputs of SP, i.e. CRM-mean convective heating and moistening profiles. Sensitivity of the machine learning convergence to the nuances of the TensorFlow implementation are discussed, as well as results from pilot tests from the neural network operating inline within the SPCAM as a replacement to the (super)parameterization of convection.
Methods of testing parameterizations: Vertical ocean mixing

NASA Technical Reports Server (NTRS)

Tziperman, Eli

1992-01-01

The ocean's velocity field is characterized by an exceptional variety of scales. While the small-scale oceanic turbulence responsible for the vertical mixing in the ocean is of scales a few centimeters and smaller, the oceanic general circulation is characterized by horizontal scales of thousands of kilometers. In oceanic general circulation models that are typically run today, the vertical structure of the ocean is represented by a few tens of discrete grid points. Such models cannot explicitly model the small-scale mixing processes, and must, therefore, find ways to parameterize them in terms of the larger-scale fields. Finding a parameterization that is both reliable and plausible to use in ocean models is not a simple task. Vertical mixing in the ocean is the combined result of many complex processes, and, in fact, mixing is one of the less known and less understood aspects of the oceanic circulation. In present models of the oceanic circulation, the many complex processes responsible for vertical mixing are often parameterized in an oversimplified manner. Yet, finding an adequate parameterization of vertical ocean mixing is crucial to the successful application of ocean models to climate studies. The results of general circulation models for quantities that are of particular interest to climate studies, such as the meridional heat flux carried by the ocean, are quite sensitive to the strength of the vertical mixing. We try to examine the difficulties in choosing an appropriate vertical mixing parameterization, and the methods that are available for validating different parameterizations by comparing model results to oceanographic data. First, some of the physical processes responsible for vertically mixing the ocean are briefly mentioned, and some possible approaches to the parameterization of these processes in oceanographic general circulation models are described in the following section. We then discuss the role of the vertical mixing in the physics of the large-scale ocean circulation, and examine methods of validating mixing parameterizations using large-scale ocean models.
Comparison of Ice Cloud Particle Sizes Retrieved from Satellite Data Derived from In Situ Measurements

NASA Technical Reports Server (NTRS)

Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M.

1997-01-01

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al.), there is no comparable study for cirrus ice crystals. This study is an effort to supply such a data set.
Understanding and Improving Ocean Mixing Parameterizations for modeling Climate Change

NASA Astrophysics Data System (ADS)

Howard, A. M.; Fells, J.; Clarke, J.; Cheng, Y.; Canuto, V.; Dubovikov, M. S.

2017-12-01

Climate is vital. Earth is only habitable due to the atmosphere&oceans' distribution of energy. Our Greenhouse Gas emissions shift overall the balance between absorbed and emitted radiation causing Global Warming. How much of these emissions are stored in the ocean vs. entering the atmosphere to cause warming and how the extra heat is distributed depends on atmosphere&ocean dynamics, which we must understand to know risks of both progressive Climate Change and Climate Variability which affect us all in many ways including extreme weather, floods, droughts, sea-level rise and ecosystem disruption. Citizens must be informed to make decisions such as "business as usual" vs. mitigating emissions to avert catastrophe. Simulations of Climate Change provide needed knowledge but in turn need reliable parameterizations of key physical processes, including ocean mixing, which greatly impacts transport&storage of heat and dissolved CO2. The turbulence group at NASA-GISS seeks to use physical theory to improve parameterizations of ocean mixing, including smallscale convective, shear driven, double diffusive, internal wave and tidal driven vertical mixing, as well as mixing by submesoscale eddies, and lateral mixing along isopycnals by mesoscale eddies. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. We write our own programs in MATLAB and FORTRAN to visualize and process output of ocean simulations including producing statistics to help judge impacts of different parameterizations on fidelity in reproducing realistic temperatures&salinities, diffusivities and turbulent power. The results can help upgrade the parameterizations. Students are introduced to complex system modeling and gain deeper appreciation of climate science and programming skills, while furthering climate science. We are incorporating climate projects into the Medgar Evers college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293 And NASA Award NNX17AC81G.
The effects of atmospheric cloud radiative forcing on climate

NASA Technical Reports Server (NTRS)

Randall, David A.

1989-01-01

In order to isolate the effects of atmospheric cloud radiative forcing (ACRF) on climate, the general circulation of an ocean-covered earth called 'Seaworld' was simulated using the Colorado State University GCM. Most current climate models, however, do not include an interactive ocean. The key simplifications in 'Seaworld' are the fixed boundary temperature with no land points, the lack of mountains and the zonal uniformity of the boundary conditions. Two 90-day 'perpetual July' simulations were performed and analyzed the last sixty days of each. The first run included all the model's physical parameterizations, while the second omitted the effects of clouds in both the solar and terrestrial radiation parameterizations. Fixed and identical boundary temperatures were set for the two runs, and resulted in differences revealing the direct and indirect effects of the ACRF on the large-scale circulation and the parameterized hydrologic processes.
The sensitivity of Alpine summer convection to surrogate climate change: an intercomparison between convection-parameterizing and convection-resolving models

NASA Astrophysics Data System (ADS)

Keller, Michael; Kröner, Nico; Fuhrer, Oliver; Lüthi, Daniel; Schmidli, Juerg; Stengel, Martin; Stöckli, Reto; Schär, Christoph

2018-04-01

Climate models project an increase in heavy precipitation events in response to greenhouse gas forcing. Important elements of such events are rain showers and thunderstorms, which are poorly represented in models with parameterized convection. In this study, simulations with 12 km horizontal grid spacing (convection-parameterizing model, CPM) and 2 km grid spacing (convection-resolving model, CRM) are employed to investigate the change in the diurnal cycle of convection with warmer climate. For this purpose, simulations of 11 days in June 2007 with a pronounced diurnal cycle of convection are compared with surrogate simulations from the same period. The surrogate climate simulations mimic a future climate with increased temperatures but unchanged relative humidity and similar synoptic-scale circulation. Two temperature scenarios are compared: one with homogeneous warming (HW) using a vertically uniform warming and the other with vertically dependent warming (VW) that enables changes in lapse rate. The two sets of simulations with parameterized and explicit convection exhibit substantial differences, some of which are well known from the literature. These include differences in the timing and amplitude of the diurnal cycle of convection, and the frequency of precipitation with low intensities. The response to climate change is much less studied. We can show that stratification changes have a strong influence on the changes in convection. Precipitation is strongly increasing for HW but decreasing for the VW simulations. For cloud type frequencies, virtually no changes are found for HW, but a substantial reduction in high clouds is found for VW. Further, we can show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences between CPM and CRM are found in terms of the radiative feedbacks, with CRM exhibiting a stronger negative feedback in the top-of-the-atmosphere energy budget.
New Gravity Wave Treatments for GISS Climate Models

NASA Technical Reports Server (NTRS)

Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye

2011-01-01

Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model-resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, the authors introduce a relatively simple and computationally efficient specification of unresolved orographic and nonorographic gravity waves and their interaction with the resolved flow. Comparisons of the GISS model winds and temperatures with no gravity wave parameterization; with only orographic gravity wave parameterization; and with both orographic and nonorographic gravity wave parameterizations are shown to illustrate how the zonal mean winds and temperatures converge toward observations. The authors also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. Then results are presented where the nonorographic gravity wave sources are specified to represent sources from convection in the intertropical convergence zone and spontaneous emission from jet imbalances. Finally, a strategy to include these effects in a climate-dependent manner is suggested.
On the usage of classical nucleation theory in predicting the impact of bacteria on weather and climate

NASA Astrophysics Data System (ADS)

Sahyoun, Maher; Woetmann Nielsen, Niels; Havskov Sørensen, Jens; Finster, Kai; Bay Gosewinkel Karlson, Ulrich; Šantl-Temkiv, Tina; Smith Korsholm, Ulrik

2014-05-01

Bacteria, e.g. Pseudomonas syringae, have previously been found efficient in nucleating ice heterogeneously at temperatures close to -2°C in laboratory tests. Therefore, ice nucleation active (INA) bacteria may be involved in the formation of precipitation in mixed phase clouds, and could potentially influence weather and climate. Investigations into the impact of INA bacteria on climate have shown that emissions were too low to significantly impact the climate (Hoose et al., 2010). The goal of this study is to clarify the reason for finding the marginal impact on climate when INA bacteria were considered, by investigating the usability of ice nucleation rate parameterization based on classical nucleation theory (CNT). For this purpose, two parameterizations of heterogeneous ice nucleation were compared. Both parameterizations were implemented and tested in a 1-d version of the operational weather model (HIRLAM) (Lynch et al., 2000; Unden et al., 2002) in two different meteorological cases. The first parameterization is based on CNT and denoted CH08 (Chen et al., 2008). This parameterization is a function of temperature and the size of the IN. The second parameterization, denoted HAR13, was derived from nucleation measurements of SnomaxTM (Hartmann et al., 2013). It is a function of temperature and the number of protein complexes on the outer membranes of the cell. The fraction of cloud droplets containing each type of IN as percentage in the cloud droplets population were used and the sensitivity of cloud ice production in each parameterization was compared. In this study, HAR13 produces more cloud ice and precipitation than CH08 when the bacteria fraction increases. In CH08, the increase of the bacteria fraction leads to decreasing the cloud ice mixing ratio. The ice production using HAR13 was found to be more sensitive to the change of the bacterial fraction than CH08 which did not show a similar sensitivity. As a result, this may explain the marginal impact of IN bacteria in climate models when CH08 was used. The number of cell fragments containing proteins appears to be a more important parameter to consider than the size of the cell when parameterizing the heterogeneous freezing of bacteria.
Performance assessment and parameterization of the SWAP-WOFOST model for peat soil under agricultural use in northern Europe.

NASA Astrophysics Data System (ADS)

Bertram, Sascha; Bechtold, Michel; Hendriks, Rob; Piayda, Arndt; Regina, Kristiina; Myllys, Merja; Tiemeyer, Bärbel

2017-04-01

Peat soils form a major share of soil suitable for agriculture in northern Europe. Successful agricultural production depends on hydrological and pedological conditions, local climate and agricultural management. Climate change impact assessment on food production and development of mitigation and adaptation strategies require reliable yield forecasts under given emission scenarios. Coupled soil hydrology - crop growth models, driven by regionalized future climate scenarios are a valuable tool and widely used for this purpose. Parameterization on local peat soil conditions and crop breed or grassland specie performance, however, remains a major challenge. The subject of this study is to evaluate the performance and sensitivity of the SWAP-WOFOST coupled soil hydrology and plant growth model with respect to the application on peat soils under different regional conditions across northern Europe. Further, the parameterization of region-specific crop and grass species is discussed. First results of the model application and parameterization at deep peat sites in southern Finland are presented. The model performed very well in reproducing two years of observed, daily ground water level data on four hydrologically contrasting sites. Naturally dry and wet sites could be modelled with the same performance as sites with active water table management by regulated drains in order to improve peat conservation. A simultaneous multi-site calibration scheme was used to estimate plant growth parameters of the local oat breed. Cross-site validation of the modelled yields against two years of observations proved the robustness of the chosen parameter set and gave no indication of possible overparameterization. This study proves the suitability of the coupled SWAP-WOFOST model for the prediction of crop yields and water table dynamics of peat soils in agricultural use under given climate conditions.

Low Cloud Feedback to Surface Warming in the World's First Global Climate Model with Explicit Embedded Boundary Layer Turbulence

NASA Astrophysics Data System (ADS)

Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Wyant, M. C.; Khairoutdinov, M.; Singh, B.

2017-12-01

Biases and parameterization formulation uncertainties in the representation of boundary layer clouds remain a leading source of possible systematic error in climate projections. Here we show the first results of cloud feedback to +4K SST warming in a new experimental climate model, the ``Ultra-Parameterized (UP)'' Community Atmosphere Model, UPCAM. We have developed UPCAM as an unusually high-resolution implementation of cloud superparameterization (SP) in which a global set of cloud resolving arrays is embedded in a host global climate model. In UP, the cloud-resolving scale includes sufficient internal resolution to explicitly generate the turbulent eddies that form marine stratocumulus and trade cumulus clouds. This is computationally costly but complements other available approaches for studying low clouds and their climate interaction, by avoiding parameterization of the relevant scales. In a recent publication we have shown that UP, while not without its own complexity trade-offs, can produce encouraging improvements in low cloud climatology in multi-month simulations of the present climate and is a promising target for exascale computing (Parishani et al. 2017). Here we show results of its low cloud feedback to warming in multi-year simulations for the first time. References: Parishani, H., M. S. Pritchard, C. S. Bretherton, M. C. Wyant, and M. Khairoutdinov (2017), Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000968.
Upgrades, Current Capabilities and Near-Term Plans of the NASA ARC Mars Climate

NASA Technical Reports Server (NTRS)

Hollingsworth, J. L.; Kahre, Melinda April; Haberle, Robert M.; Schaeffer, James R.

2012-01-01

We describe and review recent upgrades to the ARC Mars climate modeling framework, in particular, with regards to physical parameterizations (i.e., testing, implementation, modularization and documentation); the current climate modeling capabilities; selected research topics regarding current/past climates; and then, our near-term plans related to the NASA ARC Mars general circulation modeling (GCM) project.
Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux?

DOE PAGES

Zhu, Qing; Zhuang, Qianlai

2015-12-21

Reliability of terrestrial ecosystem models highly depends on the quantity and quality of thedata that have been used to calibrate the models. Nowadays, in situ observations of carbon fluxes areabundant. However, the knowledge of how much data (data length) and which subset of the time seriesdata (data period) should be used to effectively calibrate the model is still lacking. This study uses theAmeriFlux carbon flux data to parameterize the Terrestrial Ecosystem Model (TEM) with an adjoint-baseddata assimilation technique for various ecosystem types. Parameterization experiments are thus conductedto explore the impact of both data length and data period on the uncertaintymore » reduction of the posteriormodel parameters and the quantification of site and regional carbon dynamics. We find that: the modelis better constrained when it uses two-year data comparing to using one-year data. Further, two-year datais sufficient in calibrating TEM’s carbon dynamics, since using three-year data could only marginallyimprove the model performance at our study sites; the model is better constrained with the data thathave a higher‘‘climate variability’’than that having a lower one. The climate variability is used to measurethe overall possibility of the ecosystem to experience all climatic conditions including drought and extremeair temperatures and radiation; the U.S. regional simulations indicate that the effect of calibration datalength on carbon dynamics is amplified at regional and temporal scales, leading to large discrepanciesamong different parameterization experiments, especially in July and August. Our findings areconditioned on the specific model we used and the calibration sites we selected. The optimal calibrationdata length may not be suitable for other models. However, this study demonstrates that there may exist athreshold for calibration data length and simply using more data would not guarantee a better modelparameterization and prediction. More importantly, climate variability might be an effective indicator ofinformation within the data, which could help data selection for model parameterization. As a result, we believe ourfindings will benefit the ecosystem modeling community in using multiple-year data to improve modelpredictability.« less
Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Qing; Zhuang, Qianlai

Reliability of terrestrial ecosystem models highly depends on the quantity and quality of thedata that have been used to calibrate the models. Nowadays, in situ observations of carbon fluxes areabundant. However, the knowledge of how much data (data length) and which subset of the time seriesdata (data period) should be used to effectively calibrate the model is still lacking. This study uses theAmeriFlux carbon flux data to parameterize the Terrestrial Ecosystem Model (TEM) with an adjoint-baseddata assimilation technique for various ecosystem types. Parameterization experiments are thus conductedto explore the impact of both data length and data period on the uncertaintymore » reduction of the posteriormodel parameters and the quantification of site and regional carbon dynamics. We find that: the modelis better constrained when it uses two-year data comparing to using one-year data. Further, two-year datais sufficient in calibrating TEM’s carbon dynamics, since using three-year data could only marginallyimprove the model performance at our study sites; the model is better constrained with the data thathave a higher‘‘climate variability’’than that having a lower one. The climate variability is used to measurethe overall possibility of the ecosystem to experience all climatic conditions including drought and extremeair temperatures and radiation; the U.S. regional simulations indicate that the effect of calibration datalength on carbon dynamics is amplified at regional and temporal scales, leading to large discrepanciesamong different parameterization experiments, especially in July and August. Our findings areconditioned on the specific model we used and the calibration sites we selected. The optimal calibrationdata length may not be suitable for other models. However, this study demonstrates that there may exist athreshold for calibration data length and simply using more data would not guarantee a better modelparameterization and prediction. More importantly, climate variability might be an effective indicator ofinformation within the data, which could help data selection for model parameterization. As a result, we believe ourfindings will benefit the ecosystem modeling community in using multiple-year data to improve modelpredictability.« less
Parameterization of eddy sensible heat transports in a zonally averaged dynamic model of the atmosphere

NASA Technical Reports Server (NTRS)

Genthon, Christophe; Le Treut, Herve; Sadourny, Robert; Jouzel, Jean

1990-01-01

A Charney-Branscome based parameterization has been tested as a way of representing the eddy sensible heat transports missing in a zonally averaged dynamic model (ZADM) of the atmosphere. The ZADM used is a zonally averaged version of a general circulation model (GCM). The parameterized transports in the ZADM are gaged against the corresponding fluxes explicitly simulated in the GCM, using the same zonally averaged boundary conditions in both models. The Charney-Branscome approach neglects stationary eddies and transient barotropic disturbances and relies on a set of simplifying assumptions, including the linear appoximation, to describe growing transient baroclinic eddies. Nevertheless, fairly satisfactory results are obtained when the parameterization is performed interactively with the model. Compared with noninteractive tests, a very efficient restoring feedback effect between the modeled zonal-mean climate and the parameterized meridional eddy transport is identified.
Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; ...

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less
Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ˜25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.
Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present‐Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

PubMed Central

Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-01-01

Abstract Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large‐scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large‐scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large‐scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large‐scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale‐aware parameterizations, but also reveal unrecognized trade‐offs from the entanglement of precipitation frequency and total amount. PMID:29861837
Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less
Evaluation of a Mesoscale Convective System in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Payne, A. E.; Jablonowski, C.

2017-12-01

Warm season precipitation over the Southern Great Plains (SGP) follows a well observed diurnal pattern of variability, peaking at night-time, due to the eastward propagation of mesoscale convection systems that develop over the eastern slopes of the Rockies in the late afternoon. While most climate models are unable to adequately capture the organization of convection and characteristic pattern of precipitation over this region, models with high enough resolution to explicitly resolve convection show improvement. However, high resolution simulations are computationally expensive and, in the case of regional climate models, are subject to boundary conditions. Newly developed variable resolution global climate models strike a balance between the benefits of high-resolution regional climate models and the large-scale dynamics of global climate models and low computational cost. Recently developed parameterizations that are insensitive to the model grid scale provide a way to improve model performance. Here, we present an evaluation of the newly available Cloud Layers Unified by Binormals (CLUBB) parameterization scheme in a suite of variable-resolution CESM simulations with resolutions ranging from 110 km to 7 km within a regionally refined region centered over the SGP Atmospheric Radiation Measurement (ARM) site. Simulations utilize the hindcast approach developed by the Department of Energy's Cloud-Associated Parameterizations Testbed (CAPT) for the assessment of climate models. We limit our evaluation to a single mesoscale convective system that passed over the region on May 24, 2008. The effects of grid-resolution on the timing and intensity of precipitation, as well as, on the transition from shallow to deep convection are assessed against ground-based observations from the SGP ARM site, satellite observations and ERA-Interim reanalysis.
Impact of Stochastic Parameterization Schemes on Coupled and Uncoupled Climate Simulations with the Community Earth System Model

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Berner, J.; Coleman, D.; Palmer, T.

2015-12-01

Stochastic parameterizations have been used for more than a decade in atmospheric models to represent the variability of unresolved sub-grid processes. They have a beneficial effect on the spread and mean state of medium- and extended-range forecasts (Buizza et al. 1999, Palmer et al. 2009). There is also increasing evidence that stochastic parameterization of unresolved processes could be beneficial for the climate of an atmospheric model through noise enhanced variability, noise-induced drift (Berner et al. 2008), and by enabling the climate simulator to explore other flow regimes (Christensen et al. 2015; Dawson and Palmer 2015). We present results showing the impact of including the Stochastically Perturbed Parameterization Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. The SPPT scheme accounts for uncertainty in the CAM physical parameterization schemes, including the convection scheme, by perturbing the parametrised temperature, moisture and wind tendencies with a multiplicative noise term. SPPT results in a large improvement in the variability of the CAM4 modeled climate. In particular, SPPT results in a significant improvement to the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. References: Berner, J., Doblas-Reyes, F. J., Palmer, T. N., Shutts, G. J., & Weisheimer, A., 2008. Phil. Trans. R. Soc A, 366, 2559-2577 Buizza, R., Miller, M. and Palmer, T. N., 1999. Q.J.R. Meteorol. Soc., 125, 2887-2908. Christensen, H. M., I. M. Moroz & T. N. Palmer, 2015. Clim. Dynam., doi: 10.1007/s00382-014-2239-9 Dawson, A. and T. N. Palmer, 2015. Clim. Dynam., doi: 10.1007/s00382-014-2238-x Palmer, T.N., R. Buizza, F. Doblas-Reyes, et al., 2009, ECMWF technical memorandum 598.
Regionalization of subsurface stormflow parameters of hydrologic models: Up-scaling from physically based numerical simulations at hillslope scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ali, Melkamu; Ye, Sheng; Li, Hongyi

2014-07-19

Subsurface stormflow is an important component of the rainfall-runoff response, especially in steep forested regions. However; its contribution is poorly represented in current generation of land surface hydrological models (LSMs) and catchment-scale rainfall-runoff models. The lack of physical basis of common parameterizations precludes a priori estimation (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global models. This paper is aimed at deriving physically based parameterizations of the storage-discharge relationship relating to subsurface flow. These parameterizations are derived through a two-step up-scaling procedure: firstly, through simulations with a physically based (Darcian) subsurfacemore » flow model for idealized three dimensional rectangular hillslopes, accounting for within-hillslope random heterogeneity of soil hydraulic properties, and secondly, through subsequent up-scaling to the catchment scale by accounting for between-hillslope and within-catchment heterogeneity of topographic features (e.g., slope). These theoretical simulation results produced parameterizations of the storage-discharge relationship in terms of soil hydraulic properties, topographic slope and their heterogeneities, which were consistent with results of previous studies. Yet, regionalization of the resulting storage-discharge relations across 50 actual catchments in eastern United States, and a comparison of the regionalized results with equivalent empirical results obtained on the basis of analysis of observed streamflow recession curves, revealed a systematic inconsistency. It was found that the difference between the theoretical and empirically derived results could be explained, to first order, by climate in the form of climatic aridity index. This suggests a possible codependence of climate, soils, vegetation and topographic properties, and suggests that subsurface flow parameterization needed for ungauged locations must account for both the physics of flow in heterogeneous landscapes, and the co-dependence of soil and topographic properties with climate, including possibly the mediating role of vegetation.« less
A Generalized Simple Formulation of Convective Adjustment Timescale for Cumulus Convection Parameterizations

EPA Science Inventory

Convective adjustment timescale (τ) for cumulus clouds is one of the most influential parameters controlling parameterized convective precipitation in climate and weather simulation models at global and regional scales. Due to the complex nature of deep convection, a pres...
Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0)

NASA Astrophysics Data System (ADS)

Bonan, Gordon B.; Patton, Edward G.; Harman, Ian N.; Oleson, Keith W.; Finnigan, John J.; Lu, Yaqiong; Burakowski, Elizabeth A.

2018-04-01

Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multilayer canopy model (CLM-ml v0) to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at seven forest, two grassland, and three cropland AmeriFlux sites over a range of canopy heights, leaf area indexes, and climates. CLM4.5 has pronounced biases during summer months at forest sites in midday latent heat flux, sensible heat flux, gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. Advances in modeling stomatal conductance and canopy physiology beyond what is in CLM4.5 substantially improve model performance at the forest sites. The signature of the roughness sublayer is most evident in nighttime friction velocity and the diurnal cycle of radiative temperature, but is also seen in sensible heat flux. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin-Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these canopies. The multilayer canopy with the roughness sublayer turbulence improves simulations compared with CLM4.5 while also advancing the theoretical basis for surface flux parameterizations.
Urban Canopy Effects in Regional Climate Simulations - An Inter-Model Comparison

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.; Karlicky, J.

2017-12-01

To assess the impact of cities and urban surfaces on climate, the modeling approach is often used with inclusion of urban parameterization in land-surface interactions. This is especially important when going to higher resolution, which is common trend both in operational weather prediction and regional climate modelling. Model description of urban canopy related meteorological effects can, however, differ largely given especially the underlying surface models and the urban canopy parameterizations, representing a certain uncertainty. To assess this uncertainty is important for adaptation and mitigation measures often applied in the big cities, especially in connection to climate change perspective, which is one of the main task of the new project OP-PPR Proof of Concept UK. In this study we contribute to the estimation of this uncertainty by performing numerous experiments to assess the urban canopy meteorological forcing over central Europe on climate for the decade 2001-2010, using two regional climate models (RegCM4 and WRF) in 10 km resolution driven by ERA-Interim reanalyses, three surface schemes (BATS and CLM4.5 for RegCM4 and Noah for WRF) and five urban canopy parameterizations available: one bulk urban scheme, three single layer and a multilayer urban scheme. Effects of cities on urban and remote areas were evaluated. There are some differences in sensitivity of individual canopy model implementations to the UHI effects, depending on season and size of the city as well. Effect of reducing diurnal temperature range in cities (around 2 °C in summer mean) is noticeable in all simulations, independent to urban parameterization type and model, due to well-known warmer summer city nights. For the adaptation and mitigation purposes, rather than the average urban heat island intensity the distribution of it is more important providing the information on extreme UHI effects, e.g. during heat waves. We demonstrate that for big central European cities this effect can approach 10°C, even for not so big ones these extreme effects can go above 5°C.
Impacts of spectral nudging on the simulated surface air temperature in summer compared with the selection of shortwave radiation and land surface model physics parameterization in a high-resolution regional atmospheric model

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

The impact of a spectral nudging technique for the dynamical downscaling of the summer surface air temperature in a high-resolution regional atmospheric model is assessed. The performance of this technique is measured by comparing 16 analysis-driven simulation sets of physical parameterization combinations of two shortwave radiation and four land surface model schemes of the model, which are known to be crucial for the simulation of the surface air temperature. It is found that the application of spectral nudging to the outermost domain has a greater impact on the regional climate than any combination of shortwave radiation and land surface model physics schemes. The optimal choice of two model physics parameterizations is helpful for obtaining more realistic spatiotemporal distributions of land surface variables such as the surface air temperature, precipitation, and surface fluxes. However, employing spectral nudging adds more value to the results; the improvement is greater than using sophisticated shortwave radiation and land surface model physical parameterizations. This result indicates that spectral nudging applied to the outermost domain provides a more accurate lateral boundary condition to the innermost domain when forced by analysis data by securing the consistency with large-scale forcing over a regional domain. This consequently indirectly helps two physical parameterizations to produce small-scale features closer to the observed values, leading to a better representation of the surface air temperature in a high-resolution downscaled climate.
Improvement of the GEOS-5 AGCM upon Updating the Air-Sea Roughness Parameterization

NASA Technical Reports Server (NTRS)

Garfinkel, C. I.; Molod, A.; Oman, L. D.; Song, I.-S.

2011-01-01

The impact of an air-sea roughness parameterization over the ocean that more closely matches recent observations of air-sea exchange is examined in the NASA Goddard Earth Observing System, version 5 (GEOS-5) atmospheric general circulation model. Surface wind biases in the GEOS-5 AGCM are decreased by up to 1.2m/s. The new parameterization also has implications aloft as improvements extend into the stratosphere. Many other GCMs (both for operational weather forecasting and climate) use a similar class of parameterization for their air-sea roughness scheme. We therefore expect that results from GEOS-5 are relevant to other models as well.
Scientific Overview of Temporal Experiment for Storms and Tropical Systems (TEMPEST) Program

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Reising, S. C.; Kummerow, C. D.; van den Heever, S. C.; Todd, G.; Padmanabhan, S.; Brown, S. T.; Lim, B.; Haddad, Z. S.; Koch, T.; Berg, G.; L'Ecuyer, T.; Munchak, S. J.; Luo, Z. J.; Boukabara, S. A.; Ruf, C. S.

2014-12-01

Over the past decade and a half, we have gained a better understanding of the role of clouds and precipitation on Earth's water cycle, energy budget and climate, from focused Earth science observational satellite missions. However, these missions provide only a snapshot at one point in time of the cloud's development. Processes that govern cloud system development occur primarily on time scales of the order of 5-30 minutes that are generally not observable from low Earth orbiting satellites. Geostationary satellites, in contrast, have higher temporal resolution but at present are limited to visible and infrared wavelengths that observe only the tops of clouds. This observing gap was noted by the National Research Council's Earth Science Decadal Survey in 2007. Uncertainties in global climate models are significantly affected by processes that govern the formation and dissipation of clouds that largely control the global water and energy budgets. Current uncertainties in cloud parameterization within climate models lead to drastically different climate outcomes. With all evidence suggesting that the precipitation onset may be governed by factors such atmospheric stability, it becomes critical to have at least first-order observations globally in diverse climate regimes. Similar arguments are valid for ice processes where more efficient ice formation and precipitation have a tendency to leave fewer ice clouds behind that have different but equally important impacts on the Earth's energy budget and resulting temperature trends. TEMPEST is a unique program that will provide a small constellation of inexpensive CubeSats with millimeter-wave radiometers to address key science needs related to cloud and precipitation processes. Because these processes are most critical in the development of climate models that will soon run at scales that explicitly resolve clouds, the TEMPEST program will directly focus on examining, validating and improving the parameterizations currently used in cloud scale models. The time evolution of cloud and precipitation microphysics is dependent upon parameterized process rates. The outcome of TEMPEST will provide a first-order understanding of how individual assumptions in current cloud model parameterizations behave in diverse climate regimes.
Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Vincent

2016-11-25

The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. Themore » chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.« less
Importance of ensembles in projecting regional climate trends

NASA Astrophysics Data System (ADS)

Arritt, Raymond; Daniel, Ariele; Groisman, Pavel

2016-04-01

We have performed an ensemble of simulations using RegCM4 to examine the ability to reproduce observed trends in precipitation intensity and to project future changes through the 21st century for the central United States. We created a matrix of simulations over the CORDEX North America domain for 1950-2099 by driving the regional model with two different global models (HadGEM2-ES and GFDL-ESM2M, both for RCP8.5), by performing simulations at both 50 km and 25 km grid spacing, and by using three different convective parameterizations. The result is a set of 12 simulations (two GCMs by two resolutions by three convective parameterizations) that can be used to systematically evaluate the influence of simulation design on predicted precipitation. The two global models were selected to bracket the range of climate sensitivity in the CMIP5 models: HadGEM2-ES has the highest ECS of the CMIP5 models, while GFDL-ESM2M has one of the lowestt. Our evaluation metrics differ from many other RCM studies in that we focus on the skill of the models in reproducing past trends rather than the mean climate state. Trends in frequency of extreme precipitation (defined as amounts exceeding 76.2 mm/day) for most simulations are similar to the observed trend but with notable variations depending on RegCM4 configuration and on the driving GCM. There are complex interactions among resolution, choice of convective parameterization, and the driving GCM that carry over into the future climate projections. We also note that biases in the current climate do not correspond to biases in trends. As an example of these points the Emanuel scheme is consistently "wet" (positive bias in precipitation) yet it produced the smallest precipitation increase of the three convective parameterizations when used in simulations driven by HadGEM2-ES. However, it produced the largest increase when driven by GFDL-ESM2M. These findings reiterate that ensembles using multiple RCM configurations and driving GCMs are essential for projecting regional climate change, even when a single RCM is used. This research was sponsored by the U.S. Department of Agriculture National Institute of Food and Agriculture.

Comprehensive assessment of parameterization methods for estimating clear-sky surface downward longwave radiation

NASA Astrophysics Data System (ADS)

Guo, Yamin; Cheng, Jie; Liang, Shunlin

2018-02-01

Surface downward longwave radiation (SDLR) is a key variable for calculating the earth's surface radiation budget. In this study, we evaluated seven widely used clear-sky parameterization methods using ground measurements collected from 71 globally distributed fluxnet sites. The Bayesian model averaging (BMA) method was also introduced to obtain a multi-model ensemble estimate. As a whole, the parameterization method of Carmona et al. (2014) performs the best, with an average BIAS, RMSE, and R 2 of - 0.11 W/m2, 20.35 W/m2, and 0.92, respectively, followed by the parameterization methods of Idso (1981), Prata (Q J R Meteorol Soc 122:1127-1151, 1996), Brunt and Sc (Q J R Meteorol Soc 58:389-420, 1932), and Brutsaert (Water Resour Res 11:742-744, 1975). The accuracy of the BMA is close to that of the parameterization method of Carmona et al. (2014) and comparable to that of the parameterization method of Idso (1981). The advantage of the BMA is that it achieves balanced results compared to the integrated single parameterization methods. To fully assess the performance of the parameterization methods, the effects of climate type, land cover, and surface elevation were also investigated. The five parameterization methods and BMA all failed over land with the tropical climate type, with high water vapor, and had poor results over forest, wetland, and ice. These methods achieved better results over desert, bare land, cropland, and grass and had acceptable accuracies for sites at different elevations, except for the parameterization method of Carmona et al. (2014) over high elevation sites. Thus, a method that can be successfully applied everywhere does not exist.
HPC Aspects of Variable-Resolution Global Climate Modeling using a Multi-scale Convection Parameterization

EPA Science Inventory

High performance computing (HPC) requirements for the new generation variable grid resolution (VGR) global climate models differ from that of traditional global models. A VGR global model with 15 km grids over the CONUS stretching to 60 km grids elsewhere will have about ~2.5 tim...
Subgrid-scale parameterization and low-frequency variability: a response theory approach

NASA Astrophysics Data System (ADS)

Demaeyer, Jonathan; Vannitsem, Stéphane

2016-04-01

Weather and climate models are limited in the possible range of resolved spatial and temporal scales. However, due to the huge space- and time-scale ranges involved in the Earth System dynamics, the effects of many sub-grid processes should be parameterized. These parameterizations have an impact on the forecasts or projections. It could also affect the low-frequency variability present in the system (such as the one associated to ENSO or NAO). An important question is therefore to know what is the impact of stochastic parameterizations on the Low-Frequency Variability generated by the system and its model representation. In this context, we consider a stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed in Wouters and Lucarini (2012). We test this approach in the context of a low-order coupled ocean-atmosphere model, detailed in Vannitsem et al. (2015), for which a part of the atmospheric modes is considered as unresolved. A natural separation of the phase-space into a slow invariant set and its fast complement allows for an analytical derivation of the different terms involved in the parameterization, namely the average, the fluctuation and the long memory terms. Its application to the low-order system reveals that a considerable correction of the low-frequency variability along the invariant subset can be obtained. This new approach of scale separation opens new avenues of subgrid-scale parameterizations in multiscale systems used for climate forecasts. References: Vannitsem S, Demaeyer J, De Cruz L, Ghil M. 2015. Low-frequency variability and heat transport in a low-order nonlinear coupled ocean-atmosphere model. Physica D: Nonlinear Phenomena 309: 71-85. Wouters J, Lucarini V. 2012. Disentangling multi-level systems: averaging, correlations and memory. Journal of Statistical Mechanics: Theory and Experiment 2012(03): P03 003.
Responses of Mixed-Phase Cloud Condensates and Cloud Radiative Effects to Ice Nucleating Particle Concentrations in NCAR CAM5 and DOE ACME Climate Models

NASA Astrophysics Data System (ADS)

Liu, X.; Shi, Y.; Wu, M.; Zhang, K.

2017-12-01

Mixed-phase clouds frequently observed in the Arctic and mid-latitude storm tracks have the substantial impacts on the surface energy budget, precipitation and climate. In this study, we first implement the two empirical parameterizations (Niemand et al. 2012 and DeMott et al. 2015) of heterogeneous ice nucleation for mixed-phase clouds in the NCAR Community Atmosphere Model Version 5 (CAM5) and DOE Accelerated Climate Model for Energy Version 1 (ACME1). Model simulated ice nucleating particle (INP) concentrations based on Niemand et al. and DeMott et al. are compared with those from the default ice nucleation parameterization based on the classical nucleation theory (CNT) in CAM5 and ACME, and with in situ observations. Significantly higher INP concentrations (by up to a factor of 5) are simulated from Niemand et al. than DeMott et al. and CNT especially over the dust source regions in both CAM5 and ACME. Interestingly the ACME model simulates higher INP concentrations than CAM5, especially in the Polar regions. This is also the case when we nudge the two models' winds and temperature towards the same reanalysis, indicating more efficient transport of aerosols (dust) to the Polar regions in ACME. Next, we examine the responses of model simulated cloud liquid water and ice water contents to different INP concentrations from three ice nucleation parameterizations (Niemand et al., DeMott et al., and CNT) in CAM5 and ACME. Changes in liquid water path (LWP) reach as much as 20% in the Arctic regions in ACME between the three parameterizations while the LWP changes are smaller and limited in the Northern Hemispheric mid-latitudes in CAM5. Finally, the impacts on cloud radiative forcing and dust indirect effects on mixed-phase clouds are quantified with the three ice nucleation parameterizations in CAM5 and ACME.
Simulating North American mesoscale convective systems with a convection-permitting climate model

NASA Astrophysics Data System (ADS)

Prein, Andreas F.; Liu, Changhai; Ikeda, Kyoko; Bullock, Randy; Rasmussen, Roy M.; Holland, Greg J.; Clark, Martyn

2017-10-01

Deep convection is a key process in the climate system and the main source of precipitation in the tropics, subtropics, and mid-latitudes during summer. Furthermore, it is related to high impact weather causing floods, hail, tornadoes, landslides, and other hazards. State-of-the-art climate models have to parameterize deep convection due to their coarse grid spacing. These parameterizations are a major source of uncertainty and long-standing model biases. We present a North American scale convection-permitting climate simulation that is able to explicitly simulate deep convection due to its 4-km grid spacing. We apply a feature-tracking algorithm to detect hourly precipitation from Mesoscale Convective Systems (MCSs) in the model and compare it with radar-based precipitation estimates east of the US Continental Divide. The simulation is able to capture the main characteristics of the observed MCSs such as their size, precipitation rate, propagation speed, and lifetime within observational uncertainties. In particular, the model is able to produce realistically propagating MCSs, which was a long-standing challenge in climate modeling. However, the MCS frequency is significantly underestimated in the central US during late summer. We discuss the origin of this frequency biases and suggest strategies for model improvements.
Climate Process Team "Representing calving and iceberg dynamics in global climate models"

NASA Astrophysics Data System (ADS)

Sergienko, O. V.; Adcroft, A.; Amundson, J. M.; Bassis, J. N.; Hallberg, R.; Pollard, D.; Stearns, L. A.; Stern, A. A.

2016-12-01

Iceberg calving accounts for approximately 50% of the ice mass loss from the Greenland and Antarctic ice sheets. By changing a glacier's geometry, calving can also significantly perturb the glacier's stress-regime far upstream of the grounding line. This process can enhance discharge of ice across the grounding line. Once calved, icebergs drift into the open ocean where they melt, injecting freshwater to the ocean and affecting the large-scale ocean circulation. The spatial redistribution of the freshwater flux have strong impact on sea-ice formation and its spatial variability. A Climate Process Team "Representing calving and iceberg dynamics in global climate models" was established in the fall 2014. The major objectives of the CPT are: (1) develop parameterizations of calving processes that are suitable for continental-scale ice-sheet models that simulate the evolution of the Antarctic and Greenland ice sheets; (2) compile the data sets of the glaciological and oceanographic observations that are necessary to test, validate and constrain the developed parameterizations and models; (3) develop a physically based iceberg component for inclusion in the large-scale ocean circulation model. Several calving parameterizations based suitable for various glaciological settings have been developed and implemented in a continental-scale ice sheet model. Simulations of the present-day Antarctic and Greenland ice sheets show that the ice-sheet geometric configurations (thickness and extent) are sensitive to the calving process. In order to guide the development as well as to test calving parameterizations, available observations (of various kinds) have been compiled and organized into a database. Monthly estimates of iceberg distribution around the coast of Greenland have been produced with a goal of constructing iceberg size distribution and probability functions for iceberg occurrence in particular regions. A physically based iceberg model component was used in a GFDL global climate model. The simulation results show that the Antarctic iceberg calving-size distribution affects iceberg trajectories, determines where iceberg meltwater enters the ocean and the increased ice-berg freshwater transport leads to increased sea-ice growth around much of the East Antarctic coastline.
On the usage of classical nucleation theory in quantification of the impact of bacterial INP on weather and climate

NASA Astrophysics Data System (ADS)

Sahyoun, Maher; Wex, Heike; Gosewinkel, Ulrich; Šantl-Temkiv, Tina; Nielsen, Niels W.; Finster, Kai; Sørensen, Jens H.; Stratmann, Frank; Korsholm, Ulrik S.

2016-08-01

Bacterial ice-nucleating particles (INP) are present in the atmosphere and efficient in heterogeneous ice-nucleation at temperatures up to -2 °C in mixed-phase clouds. However, due to their low emission rates, their climatic impact was considered insignificant in previous modeling studies. In view of uncertainties about the actual atmospheric emission rates and concentrations of bacterial INP, it is important to re-investigate the threshold fraction of cloud droplets containing bacterial INP for a pronounced effect on ice-nucleation, by using a suitable parameterization that describes the ice-nucleation process by bacterial INP properly. Therefore, we compared two heterogeneous ice-nucleation rate parameterizations, denoted CH08 and HOO10 herein, both of which are based on classical-nucleation-theory and measurements, and use similar equations, but different parameters, to an empirical parameterization, denoted HAR13 herein, which considers implicitly the number of bacterial INP. All parameterizations were used to calculate the ice-nucleation probability offline. HAR13 and HOO10 were implemented and tested in a one-dimensional version of a weather-forecast-model in two meteorological cases. Ice-nucleation-probabilities based on HAR13 and CH08 were similar, in spite of their different derivation, and were higher than those based on HOO10. This study shows the importance of the method of parameterization and of the input variable, number of bacterial INP, for accurately assessing their role in meteorological and climatic processes.
Ice-nucleating particle emissions from photochemically aged diesel and biodiesel exhaust

NASA Astrophysics Data System (ADS)

Schill, G. P.; Jathar, S. H.; Kodros, J. K.; Levin, E. J. T.; Galang, A. M.; Friedman, B.; Link, M. F.; Farmer, D. K.; Pierce, J. R.; Kreidenweis, S. M.; DeMott, P. J.

2016-05-01

Immersion-mode ice-nucleating particle (INP) concentrations from an off-road diesel engine were measured using a continuous-flow diffusion chamber at -30°C. Both petrodiesel and biodiesel were utilized, and the exhaust was aged up to 1.5 photochemically equivalent days using an oxidative flow reactor. We found that aged and unaged diesel exhaust of both fuels is not likely to contribute to atmospheric INP concentrations at mixed-phase cloud conditions. To explore this further, a new limit-of-detection parameterization for ice nucleation on diesel exhaust was developed. Using a global-chemical transport model, potential black carbon INP (INPBC) concentrations were determined using a current literature INPBC parameterization and the limit-of-detection parameterization. Model outputs indicate that the current literature parameterization likely overemphasizes INPBC concentrations, especially in the Northern Hemisphere. These results highlight the need to integrate new INPBC parameterizations into global climate models as generalized INPBC parameterizations are not valid for diesel exhaust.
Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.
Analyses of the stratospheric dynamics simulated by a GCM with a stochastic nonorographic gravity wave parameterization

NASA Astrophysics Data System (ADS)

Serva, Federico; Cagnazzo, Chiara; Riccio, Angelo

2016-04-01

The effects of the propagation and breaking of atmospheric gravity waves have long been considered crucial for their impact on the circulation, especially in the stratosphere and mesosphere, between heights of 10 and 110 km. These waves, that in the Earth's atmosphere originate from surface orography (OGWs) or from transient (nonorographic) phenomena such as fronts and convective processes (NOGWs), have horizontal wavelengths between 10 and 1000 km, vertical wavelengths of several km, and frequencies spanning from minutes to hours. Orographic and nonorographic GWs must be accounted for in climate models to obtain a realistic simulation of the stratosphere in both hemispheres, since they can have a substantial impact on circulation and temperature, hence an important role in ozone chemistry for chemistry-climate models. Several types of parameterization are currently employed in models, differing in the formulation and for the values assigned to parameters, but the common aim is to quantify the effect of wave breaking on large-scale wind and temperature patterns. In the last decade, both global observations from satellite-borne instruments and the outputs of very high resolution climate models provided insight on the variability and properties of gravity wave field, and these results can be used to constrain some of the empirical parameters present in most parameterization scheme. A feature of the NOGW forcing that clearly emerges is the intermittency, linked with the nature of the sources: this property is absent in the majority of the models, in which NOGW parameterizations are uncoupled with other atmospheric phenomena, leading to results which display lower variability compared to observations. In this work, we analyze the climate simulated in AMIP runs of the MAECHAM5 model, which uses the Hines NOGW parameterization and with a fine vertical resolution suitable to capture the effects of wave-mean flow interaction. We compare the results obtained with two version of the model, the default and a new stochastic version, in which the value of the perturbation field at launching level is not constant and uniform, but extracted at each time-step and grid-point from a given PDF. With this approach we are trying to add further variability to the effects given by the deterministic NOGW parameterization: the impact on the simulated climate will be assessed focusing on the Quasi-Biennial Oscillation of the equatorial stratosphere (known to be driven also by gravity waves) and on the variability of the mid-to-high latitudes atmosphere. The different characteristics of the circulation will be compared with recent reanalysis products in order to determine the advantages of the stochastic approach over the traditional deterministic scheme.
Parameterization of Rocket Dust Storms on Mars in the LMD Martian GCM: Modeling Details and Validation

NASA Astrophysics Data System (ADS)

Wang, Chao; Forget, François; Bertrand, Tanguy; Spiga, Aymeric; Millour, Ehouarn; Navarro, Thomas

2018-04-01

The origin of the detached dust layers observed by the Mars Climate Sounder aboard the Mars Reconnaissance Orbiter is still debated. Spiga et al. (2013, https://doi.org/10.1002/jgre.20046) revealed that deep mesoscale convective "rocket dust storms" are likely to play an important role in forming these dust layers. To investigate how the detached dust layers are generated by this mesoscale phenomenon and subsequently evolve at larger scales, a parameterization of rocket dust storms to represent the mesoscale dust convection is designed and included into the Laboratoire de Météorologie Dynamique (LMD) Martian Global Climate Model (GCM). The new parameterization allows dust particles in the GCM to be transported to higher altitudes than in traditional GCMs. Combined with the horizontal transport by large-scale winds, the dust particles spread out and form detached dust layers. During the Martian dusty seasons, the LMD GCM with the new parameterization is able to form detached dust layers. The formation, evolution, and decay of the simulated dust layers are largely in agreement with the Mars Climate Sounder observations. This suggests that mesoscale rocket dust storms are among the key factors to explain the observed detached dust layers on Mars. However, the detached dust layers remain absent in the GCM during the clear seasons, even with the new parameterization. This implies that other relevant atmospheric processes, operating when no dust storms are occurring, are needed to explain the Martian detached dust layers. More observations of local dust storms could improve the ad hoc aspects of this parameterization, such as the trigger and timing of dust injection.
Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

NASA Technical Reports Server (NTRS)

DeBoer, G.; Bauer, S. E.; Toto, T.; Menon, Surabi; Vogelmann, A. M.

2013-01-01

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another.
A cloudy planetary boundary layer oscillation arising from the coupling of turbulence with precipitation in climate simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, X.; Klein, S. A.; Ma, H. -Y.

The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals (CLUBB) scheme and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled subgrid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud.more » Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: (1) a parameterized relationship between rain evaporation and CLUBB's subgrid spatial variance of moisture and heat that induces an extra cooling in the lower PBL and (2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.« less
A cloudy planetary boundary layer oscillation arising from the coupling of turbulence with precipitation in climate simulations

DOE PAGES

Zheng, X.; Klein, S. A.; Ma, H. -Y.; ...

2017-08-24

The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals (CLUBB) scheme and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled subgrid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud.more » Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: (1) a parameterized relationship between rain evaporation and CLUBB's subgrid spatial variance of moisture and heat that induces an extra cooling in the lower PBL and (2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.« less
The interactions between vegetation and climate seasonality, topography on different time scales under the Budyko framework: case study in China's Loess Plateau

NASA Astrophysics Data System (ADS)

Liu, W.; Ning, T.; Shen, H.; Li, Z.

2017-12-01

Vegetation, climate seasonality and topography are the main impact factors controlling the water and heat balance over a catchment, and they are usually empirically formulated into the controlling parameter in Budyko model. However, their interactions on different time scales have not been fully addressed. Taking 30 catchments in China's Loess Plateau as an example, on annual scale, vegetation coverage was found poorly correlated with climate seasonality index; therefore, they could be both parameterized into the Budyko model. On the long-term scale, vegetation coverage tended to have close relationships with topographic conditions and climate seasonality, which was confirmed by the multi-collinearity problems; in that sense, vegetation information could fit the controlling parameter exclusively. Identifying the dominant controlling factors over different time scales, this study simplified the empirical parameterization of the Budyko formula. Though the above relationships further investigation over the other regions/catchments.
Assessing and Upgrading Ocean Mixing for the Study of Climate Change

NASA Astrophysics Data System (ADS)

Howard, A. M.; Fells, J.; Lindo, F.; Tulsee, V.; Canuto, V.; Cheng, Y.; Dubovikov, M. S.; Leboissetier, A.

2016-12-01

Climate is critical. Climate variability affects us all; Climate Change is a burning issue. Droughts, floods, other extreme events, and Global Warming's effects on these and problems such as sea-level rise and ecosystem disruption threaten lives. Citizens must be informed to make decisions concerning climate such as "business as usual" vs. mitigating emissions to keep warming within bounds. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. To make useful predictions we must realistically model each component of the climate system, including the ocean, whose critical role includes transporting&storing heat and dissolved CO2. We need physically based parameterizations of key ocean processes that can't be put explicitly in a global climate model, e.g. vertical&lateral mixing. The NASA-GISS turbulence group uses theory to model mixing including: 1) a comprehensive scheme for small scale vertical mixing, including convection&shear, internal waves & double-diffusion, and bottom tides 2) a new parameterization for the lateral&vertical mixing by mesoscale eddies. For better understanding we write our own programs. To assess the modelling MATLAB programs visualize and calculate statistics, including means, standard deviations and correlations, on NASA-GISS OGCM output with different mixing schemes and help us study drift from observations. We also try to upgrade the schemes, e.g. the bottom tidal mixing parameterizations' roughness, calculated from high resolution topographic data using Gaussian weighting functions with cut-offs. We study the effects of their parameters to improve them. A FORTRAN program extracts topography data subsets of manageable size for a MATLAB program, tested on idealized cases, to visualize&calculate roughness on. Students are introduced to modeling a complex system, gain a deeper appreciation of climate science, programming skills and familiarity with MATLAB, while furthering climate science by improving our mixing schemes. We are incorporating climate research into our college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293.
Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

Treesearch

Shiyuan Zhong; Xiuping Li; Xindi Bian; Warren E. Heilman; L. Ruby Leung; William I. Jr. Gustafson

2012-01-01

The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990-1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-...
Collaborative Project. 3D Radiative Transfer Parameterization Over Mountains/Snow for High-Resolution Climate Models. Fast physics and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liou, Kuo-Nan

2016-02-09

Under the support of the aforementioned DOE Grant, we have made two fundamental contributions to atmospheric and climate sciences: (1) Develop an efficient 3-D radiative transfer parameterization for application to intense and intricate inhomogeneous mountain/snow regions. (2) Innovate a stochastic parameterization for light absorption by internally mixed black carbon and dust particles in snow grains for understanding and physical insight into snow albedo reduction in climate models. With reference to item (1), we divided solar fluxes reaching mountain surfaces into five components: direct and diffuse fluxes, direct- and diffuse-reflected fluxes, and coupled mountain-mountain flux. “Exact” 3D Monte Carlo photon tracingmore » computations can then be performed for these solar flux components to compare with those calculated from the conventional plane-parallel (PP) radiative transfer program readily available in climate models. Subsequently, Parameterizations of the deviations of 3D from PP results for five flux components are carried out by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. We derived five regression equations with high statistical correlations for flux deviations and successfully incorporated this efficient parameterization into WRF model, which was used as the testbed in connection with the Fu-Liou-Gu PP radiation scheme that has been included in the WRF physics package. Incorporating this 3D parameterization program, we conducted simulations of WRF and CCSM4 to understand and evaluate the mountain/snow effect on snow albedo reduction during seasonal transition and the interannual variability for snowmelt, cloud cover, and precipitation over the Western United States presented in the final report. With reference to item (2), we developed in our previous research a geometric-optics surface-wave approach (GOS) for the computation of light absorption and scattering by complex and inhomogeneous particles for application to aggregates and snow grains with external and internal mixing structures. We demonstrated that a small black (BC) particle on the order of 1 μm internally mixed with snow grains could effectively reduce visible snow albedo by as much as 5–10%. Following this work and within the context of DOE support, we have made two key accomplishments presented in the attached final report.« less
Inclusion of Solar Elevation Angle in Land Surface Albedo Parameterization Over Bare Soil Surface.

PubMed

Zheng, Zhiyuan; Wei, Zhigang; Wen, Zhiping; Dong, Wenjie; Li, Zhenchao; Wen, Xiaohang; Zhu, Xian; Ji, Dong; Chen, Chen; Yan, Dongdong

2017-12-01

Land surface albedo is a significant parameter for maintaining a balance in surface energy. It is also an important parameter of bare soil surface albedo for developing land surface process models that accurately reflect diurnal variation characteristics and the mechanism behind the solar spectral radiation albedo on bare soil surfaces and for understanding the relationships between climate factors and spectral radiation albedo. Using a data set of field observations, we conducted experiments to analyze the variation characteristics of land surface solar spectral radiation and the corresponding albedo over a typical Gobi bare soil underlying surface and to investigate the relationships between the land surface solar spectral radiation albedo, solar elevation angle, and soil moisture. Based on both solar elevation angle and soil moisture measurements simultaneously, we propose a new two-factor parameterization scheme for spectral radiation albedo over bare soil underlying surfaces. The results of numerical simulation experiments show that the new parameterization scheme can more accurately depict the diurnal variation characteristics of bare soil surface albedo than the previous schemes. Solar elevation angle is one of the most important factors for parameterizing bare soil surface albedo and must be considered in the parameterization scheme, especially in arid and semiarid areas with low soil moisture content. This study reveals the characteristics and mechanism of the diurnal variation of bare soil surface solar spectral radiation albedo and is helpful in developing land surface process models, weather models, and climate models.
Parameterizing deep convection using the assumed probability density function method

DOE PAGES

Storer, R. L.; Griffin, B. M.; Höft, J.; ...

2014-06-11

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Storer, R. L.; Griffin, B. M.; Höft, J.

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.more » The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less
Parameterizing deep convection using the assumed probability density function method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Storer, R. L.; Griffin, B. M.; Hoft, Jan

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. Themore » same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less
The importance of the terrestrial weathering feedback for multimillennial coral reef habitat recovery

NASA Astrophysics Data System (ADS)

Meissner, Katrin J.; McNeil, Ben I.; Eby, Michael; Wiebe, Edward C.

2012-09-01

Modern-day coral reefs have well defined environmental envelopes for light, sea surface temperature (SST) and seawater aragonite saturation state (Ωarag). We examine the changes in global coral reef habitat on multimillennial timescales with regard to SST and Ωaragusing a climate model including a three-dimensional ocean general circulation model, a fully coupled carbon cycle, and six different parameterizations for continental weathering (the UVic Earth System Climate Model). The model is forced with emission scenarios ranging from 1,000 Pg C to 5,000 Pg C total emissions. We find that the long-term climate change response is independent of the rate at which CO2 is emitted over the next few centuries. On millennial timescales, the weathering feedback introduces a significant uncertainty even for low emission scenarios. Weathering parameterizations based on atmospheric CO2 only display a different transient response than weathering parameterizations that are dependent on temperature. Although environmental conditions for SST and Ωaragstay globally hostile for coral reefs for millennia for our high emission scenarios, some weathering parameterizations induce a near-complete recovery of coral reef habitat to current conditions after 10,000 years, while others result in a collapse of coral reef habitat throughout our simulations. We find that the multimillennial response in sea surface temperature (SST) substantially lags the aragonite saturation recovery in all configurations. This implies that if corals can naturally adapt over millennia by selecting thermally tolerant species to match warmer ocean temperatures, prospects for long-term recovery of coral reefs are better since Ωarag recovers more quickly than SST.
Investigation of tropical diurnal convection biases in a climate model using TWP-ICE observations and convection-permitting simulations

NASA Astrophysics Data System (ADS)

Lin, W.; Xie, S.; Jackson, R. C.; Endo, S.; Vogelmann, A. M.; Collis, S. M.; Golaz, J. C.

2017-12-01

Climate models are known to have difficulty in simulating tropical diurnal convections that exhibit distinct characteristics over land and open ocean. While the causes are rooted in deficiencies in convective parameterization in general, lack of representations of mesoscale dynamics in terms of land-sea breeze, convective organization, and propagation of convection-induced gravity waves also play critical roles. In this study, the problem is investigated at the process-level with the U.S. Department of Energy Accelerated Climate Modeling for Energy (ACME) model in short-term hindcast mode using the Cloud Associated Parameterization Testbed (CAPT) framework. Convective-scale radar retrievals and observation-driven convection-permitting simulations for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) cases are used to guide the analysis of the underlying processes. The emphasis will be on linking deficiencies in representation of detailed process elements to the model biases in diurnal convective properties and their contrast among inland, coastal and open ocean conditions.
The Impact of Parameterized Convection on Climatological Precipitation in Atmospheric Global Climate Models

NASA Astrophysics Data System (ADS)

Maher, Penelope; Vallis, Geoffrey K.; Sherwood, Steven C.; Webb, Mark J.; Sansom, Philip G.

2018-04-01

Convective parameterizations are widely believed to be essential for realistic simulations of the atmosphere. However, their deficiencies also result in model biases. The role of convection schemes in modern atmospheric models is examined using Selected Process On/Off Klima Intercomparison Experiment simulations without parameterized convection and forced with observed sea surface temperatures. Convection schemes are not required for reasonable climatological precipitation. However, they are essential for reasonable daily precipitation and constraining extreme daily precipitation that otherwise develops. Systematic effects on lapse rate and humidity are likewise modest compared with the intermodel spread. Without parameterized convection Kelvin waves are more realistic. An unexpectedly large moist Southern Hemisphere storm track bias is identified. This storm track bias persists without convection schemes, as does the double Intertropical Convergence Zone and excessive ocean precipitation biases. This suggests that model biases originate from processes other than convection or that convection schemes are missing key processes.
Evaluation of Surface Flux Parameterizations with Long-Term ARM Observations

DOE PAGES

Liu, Gang; Liu, Yangang; Endo, Satoshi

2013-02-01

Surface momentum, sensible heat, and latent heat fluxes are critical for atmospheric processes such as clouds and precipitation, and are parameterized in a variety of models ranging from cloud-resolving models to large-scale weather and climate models. However, direct evaluation of the parameterization schemes for these surface fluxes is rare due to limited observations. This study takes advantage of the long-term observations of surface fluxes collected at the Southern Great Plains site by the Department of Energy Atmospheric Radiation Measurement program to evaluate the six surface flux parameterization schemes commonly used in the Weather Research and Forecasting (WRF) model and threemore » U.S. general circulation models (GCMs). The unprecedented 7-yr-long measurements by the eddy correlation (EC) and energy balance Bowen ratio (EBBR) methods permit statistical evaluation of all six parameterizations under a variety of stability conditions, diurnal cycles, and seasonal variations. The statistical analyses show that the momentum flux parameterization agrees best with the EC observations, followed by latent heat flux, sensible heat flux, and evaporation ratio/Bowen ratio. The overall performance of the parameterizations depends on atmospheric stability, being best under neutral stratification and deteriorating toward both more stable and more unstable conditions. Further diagnostic analysis reveals that in addition to the parameterization schemes themselves, the discrepancies between observed and parameterized sensible and latent heat fluxes may stem from inadequate use of input variables such as surface temperature, moisture availability, and roughness length. The results demonstrate the need for improving the land surface models and measurements of surface properties, which would permit the evaluation of full land surface models.« less
Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

NASA Astrophysics Data System (ADS)

Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei

2018-04-01

Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.
Using Field and Satellite Measurements to Improve Snow and Riming Processes in Cloud Resolving Models

NASA Technical Reports Server (NTRS)

Colle, Brian A.; Molthan, Andrew L.

2013-01-01

The representation of clouds in climate and weather models is a driver in forecast uncertainty. Cloud microphysics parameterizations are challenged by having to represent a diverse range of ice species. Key characteristics of predicted ice species include habit and fall speed, and complex interactions that result from mixed-phased processes like riming. Our proposed activity leverages Global Precipitation Measurement (GPM) Mission ground validation studies to improve parameterizations
Land surface hydrology parameterization for atmospheric general circulation models including subgrid scale spatial variability

NASA Technical Reports Server (NTRS)

Entekhabi, D.; Eagleson, P. S.

1989-01-01

Parameterizations are developed for the representation of subgrid hydrologic processes in atmospheric general circulation models. Reasonable a priori probability density functions of the spatial variability of soil moisture and of precipitation are introduced. These are used in conjunction with the deterministic equations describing basic soil moisture physics to derive expressions for the hydrologic processes that include subgrid scale variation in parameters. The major model sensitivities to soil type and to climatic forcing are explored.
Anisotropic shear dispersion parameterization for ocean eddy transport

NASA Astrophysics Data System (ADS)

Reckinger, Scott; Fox-Kemper, Baylor

2015-11-01

The effects of mesoscale eddies are universally treated isotropically in global ocean general circulation models. However, observations and simulations demonstrate that the mesoscale processes that the parameterization is intended to represent, such as shear dispersion, are typified by strong anisotropy. We extend the Gent-McWilliams/Redi mesoscale eddy parameterization to include anisotropy and test the effects of varying levels of anisotropy in 1-degree Community Earth System Model (CESM) simulations. Anisotropy has many effects on the simulated climate, including a reduction of temperature and salinity biases, a deepening of the southern ocean mixed-layer depth, impacts on the meridional overturning circulation and ocean energy and tracer uptake, and improved ventilation of biogeochemical tracers, particularly in oxygen minimum zones. A process-based parameterization to approximate the effects of unresolved shear dispersion is also used to set the strength and direction of anisotropy. The shear dispersion parameterization is similar to drifter observations in spatial distribution of diffusivity and high-resolution model diagnosis in the distribution of eddy flux orientation.
Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.
Development and Testing of Coupled Land-surface, PBL and Shallow/Deep Convective Parameterizations within the MM5

NASA Technical Reports Server (NTRS)

Stauffer, David R.; Seaman, Nelson L.; Munoz, Ricardo C.

2000-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins using a 3-D mesoscale model, the PSUINCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. It was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having a detailed land-surface parameterization, an advanced boundary-layer parameterization, and a more complete shallow convection parameterization than are available in most current models. The methodology was based on the application in the MM5 of new or recently improved parameterizations covering these three physical processes. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the Southern Great Plains (SGP): (1) the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) described by Wetzel and Boone; (2) the 1.5-order turbulent kinetic energy (TKE)-predicting scheme of Shafran et al.; and (3) the hybrid-closure sub-grid shallow convection parameterization of Deng. Each of these schemes has been tested extensively through this study and the latter two have been improved significantly to extend their capabilities.
Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagener, Thorsten; Mann, Michael; Crane, Robert

2014-04-29

This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach tomore » establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.« less
Gravity Waves Generated by Convection: A New Idealized Model Tool and Direct Validation with Satellite Observations

NASA Astrophysics Data System (ADS)

Alexander, M. Joan; Stephan, Claudia

2015-04-01

In climate models, gravity waves remain too poorly resolved to be directly modelled. Instead, simplified parameterizations are used to include gravity wave effects on model winds. A few climate models link some of the parameterized waves to convective sources, providing a mechanism for feedback between changes in convection and gravity wave-driven changes in circulation in the tropics and above high-latitude storms. These convective wave parameterizations are based on limited case studies with cloud-resolving models, but they are poorly constrained by observational validation, and tuning parameters have large uncertainties. Our new work distills results from complex, full-physics cloud-resolving model studies to essential variables for gravity wave generation. We use the Weather Research Forecast (WRF) model to study relationships between precipitation, latent heating/cooling and other cloud properties to the spectrum of gravity wave momentum flux above midlatitude storm systems. Results show the gravity wave spectrum is surprisingly insensitive to the representation of microphysics in WRF. This is good news for use of these models for gravity wave parameterization development since microphysical properties are a key uncertainty. We further use the full-physics cloud-resolving model as a tool to directly link observed precipitation variability to gravity wave generation. We show that waves in an idealized model forced with radar-observed precipitation can quantitatively reproduce instantaneous satellite-observed features of the gravity wave field above storms, which is a powerful validation of our understanding of waves generated by convection. The idealized model directly links observations of surface precipitation to observed waves in the stratosphere, and the simplicity of the model permits deep/large-area domains for studies of wave-mean flow interactions. This unique validated model tool permits quantitative studies of gravity wave driving of regional circulation and provides a new method for future development of realistic convective gravity wave parameterizations.
Winter and summer simulations with the GLAS climate model

NASA Technical Reports Server (NTRS)

Shukla, J.; Straus, D.; Randall, D.; Sud, Y.; Marx, L.

1981-01-01

The GLAS climate model is a general circulation model based on the primitive equations in sigma coordinates on a global domain in the presence of orography. The model incorporates parameterizations of the effects of radiation, convection, large scale latent heat release, turbulent and boundary layer fluxes, and ground hydrology. Winter and summer simulations were carried out with this model, and the resulting data are compared to observations.
A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges

DOE PAGES

Prein, Andreas; Langhans, Wolfgang; Fosser, Giorgia; ...

2015-05-27

Regional climate modeling using convection permitting models (CPMs) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs). CPMs do not use convection parameterization schemes, known as a major source of errors and uncertainties, and have more accurate surface and orography elds. The drawback of CPMs is their high demand on computational resources. For this reason, the CPM climate simulations only appeared a decade ago. In this study we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic.more » The most important components in CPM, such as physical parameterizations and dynamical formulations are discussed, and an outlook on required future developments and computer architectures that would support the application of CPMs is given. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Most improvements are found for processes related to deep convection (e.g., precipitation during summer), for mountainous regions, and for the soil-vegetation-atmosphere interactions. The climate change signals of CPM simulations reveal increases in short and extreme rainfall events and an increased ratio of liquid precipitation at the surface (a decrease of hail) potentially leading to more frequent ash oods. Concluding, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to assess their full potential and support their development.« less
Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

NASA Astrophysics Data System (ADS)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

2016-04-01

The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).
Multi-Scale Modeling and the Eddy-Diffusivity/Mass-Flux (EDMF) Parameterization

NASA Astrophysics Data System (ADS)

Teixeira, J.

2015-12-01

Turbulence and convection play a fundamental role in many key weather and climate science topics. Unfortunately, current atmospheric models cannot explicitly resolve most turbulent and convective flow. Because of this fact, turbulence and convection in the atmosphere has to be parameterized - i.e. equations describing the dynamical evolution of the statistical properties of turbulence and convection motions have to be devised. Recently a variety of different models have been developed that attempt at simulating the atmosphere using variable resolution. A key problem however is that parameterizations are in general not explicitly aware of the resolution - the scale awareness problem. In this context, we will present and discuss a specific approach, the Eddy-Diffusivity/Mass-Flux (EDMF) parameterization, that not only is in itself a multi-scale parameterization but it is also particularly well suited to deal with the scale-awareness problems that plague current variable-resolution models. It does so by representing small-scale turbulence using a classic Eddy-Diffusivity (ED) method, and the larger-scale (boundary layer and tropospheric-scale) eddies as a variety of plumes using the Mass-Flux (MF) concept.
Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model

NASA Astrophysics Data System (ADS)

O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.

2015-12-01

Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.
A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

NASA Technical Reports Server (NTRS)

Geller, Marvin A.; Alexadner, M. Joan; Love, Peter T.; Bacmeister, Julio; Ern, Manfred; Hertzog, Albert; Manzini, Elisa; Preusse, Peter; Sato, Kaoru; Scaife, Adam A.;

2013-01-01

For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

National Centers for Environmental Prediction

Science.gov Websites

: Influence of convective parameterization on the systematic errors of Climate Forecast System (CFS) model ; Climate Dynamics, 41, 45-61, 2013. Saha, S., S. Pokhrel and H. S. Chaudhari : Influence of Eurasian snow Organization Search Enter text Search Navigation Bar End Cap Search EMC Go Branches Global Climate and Weather
The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations

NASA Astrophysics Data System (ADS)

Zhang, K.; O'Donnell, D.; Kazil, J.; Stier, P.; Kinne, S.; Lohmann, U.; Ferrachat, S.; Croft, B.; Quaas, J.; Wan, H.; Rast, S.; Feichter, J.

2012-03-01

This paper introduces and evaluates the second version of the global aerosol-climate model ECHAM-HAM. Major changes have been brought into the model, including new parameterizations for aerosol nucleation and water uptake, an explicit treatment of secondary organic aerosols, modified emission calculations for sea salt and mineral dust, the coupling of aerosol microphysics to a two-moment stratiform cloud microphysics scheme, and alternative wet scavenging parameterizations. These revisions extend the model's capability to represent details of the aerosol lifecycle and its interaction with climate. Sensitivity experiments are carried out to analyse the effects of these improvements in the process representation on the simulated aerosol properties and global distribution. The new parameterizations that have largest impact on the global mean aerosol optical depth and radiative effects turn out to be the water uptake scheme and cloud microphysics. The former leads to a significant decrease of aerosol water contents in the lower troposphere, and consequently smaller optical depth; the latter results in higher aerosol loading and longer lifetime due to weaker in-cloud scavenging. The combined effects of the new/updated parameterizations are demonstrated by comparing the new model results with those from the earlier version, and against observations. Model simulations are evaluated in terms of aerosol number concentrations against measurements collected from twenty field campaigns as well as from fixed measurement sites, and in terms of optical properties against the AERONET measurements. Results indicate a general improvement with respect to the earlier version. The aerosol size distribution and spatial-temporal variance simulated by HAM2 are in better agreement with the observations. Biases in the earlier model version in aerosol optical depth and in the Ångström parameter have been reduced. The paper also points out the remaining model deficiencies that need to be addressed in the future.
Cloud-System Resolving Models: Status and Prospects

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncreiff, Mitch

2008-01-01

Cloud-system resolving models (CRM), which are based on the nonhydrostatic equations of motion and typically have a grid-spacing of about a kilometer, originated as cloud-process models in the 1970s. This paper reviews the status and prospects of CRMs across a wide range of issues, such as microphysics and precipitation; interaction between clouds and radiation; and the effects of boundary-layer and surface-processes on cloud systems. Since CRMs resolve organized convection, tropical waves and the large-scale circulation, there is the prospect for several advances in both basic knowledge of scale-interaction requisite to parameterizing mesoscale processes in climate models. In superparameterization, CRMs represent convection, explicitly replacing many of the assumptions necessary in contemporary parameterization. Global CRMs have been run on an experimental basis, giving prospect to a new generation of climate weather prediction in a decade, and climate models due course. CRMs play a major role in the retrieval of surface-rain and latent heating from satellite measurements. Finally, enormous wide dynamic ranges of CRM simulations present new challenges for model validation against observations.
Process-oriented Observational Metrics for CMIP6 Climate Model Assessments

NASA Astrophysics Data System (ADS)

Jiang, J. H.; Su, H.

2016-12-01

Observational metrics based on satellite observations have been developed and effectively applied during post-CMIP5 model evaluation and improvement projects. As new physics and parameterizations continue to be included in models for the upcoming CMIP6, it is important to continue objective comparisons between observations and model results. This talk will summarize the process-oriented observational metrics and methodologies for constraining climate models with A-Train satellite observations and support CMIP6 model assessments. We target parameters and processes related to atmospheric clouds and water vapor, which are critically important for Earth's radiative budget, climate feedbacks, and water and energy cycles, and thus reduce uncertainties in climate models.
Research into the influence of spatial variability and scale on the parameterization of hydrological processes

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The objectives of the research were as follows: (1) Extend the Representative Elementary Area (RE) concept, first proposed and developed in Wood et al, (1988), to the water balance fluxes of the interstorm period (redistribution, evapotranspiration and baseflow) necessary for the analysis of long-term water balance processes. (2) Derive spatially averaged water balance model equations for spatially variable soil, topography and vegetation, over A RANGE OF CLIMATES. This is a necessary step in our goal to derive consistent hydrologic results up to GCM grid scales necessary for global climate modeling. (3) Apply the above macroscale water balance equations with remotely sensed data and begin to explore the feasibility of parameterizing the water balance constitutive equations at GCM grid scale.
Sensitivity of U.S. summer precipitation to model resolution and convective parameterizations across gray zone resolutions

NASA Astrophysics Data System (ADS)

Gao, Yang; Leung, L. Ruby; Zhao, Chun; Hagos, Samson

2017-03-01

Simulating summer precipitation is a significant challenge for climate models that rely on cumulus parameterizations to represent moist convection processes. Motivated by recent advances in computing that support very high-resolution modeling, this study aims to systematically evaluate the effects of model resolution and convective parameterizations across the gray zone resolutions. Simulations using the Weather Research and Forecasting model were conducted at grid spacings of 36 km, 12 km, and 4 km for two summers over the conterminous U.S. The convection-permitting simulations at 4 km grid spacing are most skillful in reproducing the observed precipitation spatial distributions and diurnal variability. Notable differences are found between simulations with the traditional Kain-Fritsch (KF) and the scale-aware Grell-Freitas (GF) convection schemes, with the latter more skillful in capturing the nocturnal timing in the Great Plains and North American monsoon regions. The GF scheme also simulates a smoother transition from convective to large-scale precipitation as resolution increases, resulting in reduced sensitivity to model resolution compared to the KF scheme. Nonhydrostatic dynamics has a positive impact on precipitation over complex terrain even at 12 km and 36 km grid spacings. With nudging of the winds toward observations, we show that the conspicuous warm biases in the Southern Great Plains are related to precipitation biases induced by large-scale circulation biases, which are insensitive to model resolution. Overall, notable improvements in simulating summer rainfall and its diurnal variability through convection-permitting modeling and scale-aware parameterizations suggest promising venues for improving climate simulations of water cycle processes.
New Directions: Understanding Interactions of Air Quality and Climate Change at Regional Scales

EPA Science Inventory

The estimates of the short-lived climate forcers’ (SLCFs) impacts and mitigation effects on the radiation balance have large uncertainty because the current global model set-ups and simulations contain simplified parameterizations and do not completely cover the full range of air...
Ensemble projections of wildfire activity and carbonaceous aerosol concentrations over the western United States in the mid-21st century

PubMed Central

Yue, Xu; Mickley, Loretta J.; Logan, Jennifer A.; Kaplan, Jed O.

2013-01-01

We estimate future wildfire activity over the western United States during the mid-21st century (2046–2065), based on results from 15 climate models following the A1B scenario. We develop fire prediction models by regressing meteorological variables from the current and previous years together with fire indexes onto observed regional area burned. The regressions explain 0.25–0.60 of the variance in observed annual area burned during 1980–2004, depending on the ecoregion. We also parameterize daily area burned with temperature, precipitation, and relative humidity. This approach explains ~0.5 of the variance in observed area burned over forest ecoregions but shows no predictive capability in the semi-arid regions of Nevada and California. By applying the meteorological fields from 15 climate models to our fire prediction models, we quantify the robustness of our wildfire projections at mid-century. We calculate increases of 24–124% in area burned using regressions and 63–169% with the parameterization. Our projections are most robust in the southwestern desert, where all GCMs predict significant (p<0.05) meteorological changes. For forested ecoregions, more GCMs predict significant increases in future area burned with the parameterization than with the regressions, because the latter approach is sensitive to hydrological variables that show large inter-model variability in the climate projections. The parameterization predicts that the fire season lengthens by 23 days in the warmer and drier climate at mid-century. Using a chemical transport model, we find that wildfire emissions will increase summertime surface organic carbon aerosol over the western United States by 46–70% and black carbon by 20–27% at midcentury, relative to the present day. The pollution is most enhanced during extreme episodes: above the 84th percentile of concentrations, OC increases by ~90% and BC by ~50%, while visibility decreases from 130 km to 100 km in 32 Federal Class 1 areas in Rocky Mountains Forest. PMID:24015109
Infrared radiation parameterizations for the minor CO2 bands and for several CFC bands in the window region

NASA Technical Reports Server (NTRS)

Kratz, David P.; Chou, Ming-Dah; Yan, Michael M.-H.

1993-01-01

Fast and accurate parameterizations have been developed for the transmission functions of the CO2 9.4- and 10.4-micron bands, as well as the CFC-11, CFC-12, and CFC-22 bands located in the 8-12-micron region. The parameterizations are based on line-by-line calculations of transmission functions for the CO2 bands and on high spectral resolution laboratory measurements of the absorption coefficients for the CFC bands. Also developed are the parameterizations for the H2O transmission functions for the corresponding spectral bands. Compared to the high-resolution calculations, fluxes at the tropopause computed with the parameterizations are accurate to within 10 percent when overlapping of gas absorptions within a band is taken into account. For individual gas absorption, the accuracy is of order 0-2 percent. The climatic effects of these trace gases have been studied using a zonally averaged multilayer energy balance model, which includes seasonal cycles and a simplified deep ocean. With the trace gas abundances taken to follow the Intergovernmental Panel on Climate Change Low Emissions 'B' scenario, the transient response of the surface temperature is simulated for the period 1900-2060.
Benefits of explicit urban parameterization in regional climate modeling to study climate and city interactions

NASA Astrophysics Data System (ADS)

Daniel, M.; Lemonsu, Aude; Déqué, M.; Somot, S.; Alias, A.; Masson, V.

2018-06-01

Most climate models do not explicitly model urban areas and at best describe them as rock covers. Nonetheless, the very high resolutions reached now by the regional climate models may justify and require a more realistic parameterization of surface exchanges between urban canopy and atmosphere. To quantify the potential impact of urbanization on the regional climate, and evaluate the benefits of a detailed urban canopy model compared with a simpler approach, a sensitivity study was carried out over France at a 12-km horizontal resolution with the ALADIN-Climate regional model for 1980-2009 time period. Different descriptions of land use and urban modeling were compared, corresponding to an explicit modeling of cities with the urban canopy model TEB, a conventional and simpler approach representing urban areas as rocks, and a vegetated experiment for which cities are replaced by natural covers. A general evaluation of ALADIN-Climate was first done, that showed an overestimation of the incoming solar radiation but satisfying results in terms of precipitation and near-surface temperatures. The sensitivity analysis then highlighted that urban areas had a significant impact on modeled near-surface temperature. A further analysis on a few large French cities indicated that over the 30 years of simulation they all induced a warming effect both at daytime and nighttime with values up to + 1.5 °C for the city of Paris. The urban model also led to a regional warming extending beyond the urban areas boundaries. Finally, the comparison to temperature observations available for Paris area highlighted that the detailed urban canopy model improved the modeling of the urban heat island compared with a simpler approach.
The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna

NASA Technical Reports Server (NTRS)

Molod, Andrea; Takacs, Lawrence; Suarez, Max; Bacmeister, Julio; Song, In-Sun; Eichmann, Andrew

2012-01-01

This report is a documentation of the Fortuna version of the GEOS-5 Atmospheric General Circulation Model (AGCM). The GEOS-5 AGCM is currently in use in the NASA Goddard Modeling and Assimilation Office (GMAO) for simulations at a wide range of resolutions, in atmosphere only, coupled ocean-atmosphere, and data assimilation modes. The focus here is on the development subsequent to the version that was used as part of NASA s Modern-Era Retrospective Analysis for Research and Applications (MERRA). We present here the results of a series of 30-year atmosphere-only simulations at different resolutions, with focus on the behavior of the 1-degree resolution simulation. The details of the changes in parameterizations subsequent to the MERRA model version are outlined, and results of a series of 30-year, atmosphere-only climate simulations at 2-degree resolution are shown to demonstrate changes in simulated climate associated with specific changes in parameterizations. The GEOS-5 AGCM presented here is the model used for the GMAO s atmosphere-only and coupled CMIP-5 simulations.
Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE PAGES

Cai, X.; Yang, Z. -L.; Fisher, J. B.; ...

2016-01-15

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less
Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, X.; Yang, Z. -L.; Fisher, J. B.

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less
Intercomparison of land-surface parameterizations launched

NASA Astrophysics Data System (ADS)

Henderson-Sellers, A.; Dickinson, R. E.

One of the crucial tasks for climatic and hydrological scientists over the next several years will be validating land surface process parameterizations used in climate models. There is not, necessarily, a unique set of parameters to be used. Different scientists will want to attempt to capture processes through various methods “for example, Avissar and Verstraete, 1990”. Validation of some aspects of the available (and proposed) schemes' performance is clearly required. It would also be valuable to compare the behavior of the existing schemes [for example, Dickinson et al., 1991; Henderson-Sellers, 1992a].The WMO-CAS Working Group on Numerical Experimentation (WGNE) and the Science Panel of the GEWEX Continental-Scale International Project (GCIP) [for example, Chahine, 1992] have agreed to launch the joint WGNE/GCIP Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS). The principal goal of this project is to achieve greater understanding of the capabilities and potential applications of existing and new land-surface schemes in atmospheric models. It is not anticipated that a single “best” scheme will emerge. Rather, the aim is to explore alternative models in ways compatible with their authors' or exploiters' goals and to increase understanding of the characteristics of these models in the scientific community.
Sensitivity of a global climate model to the critical Richardson number in the boundary layer parameterization

DOE PAGES

Zhang, Ning; Liu, Yangang; Gao, Zhiqiu; ...

2015-04-27

The critical bulk Richardson number (Ri cr) is an important parameter in planetary boundary layer (PBL) parameterization schemes used in many climate models. This paper examines the sensitivity of a Global Climate Model, the Beijing Climate Center Atmospheric General Circulation Model, BCC_AGCM to Ri cr. The results show that the simulated global average of PBL height increases nearly linearly with Ri cr, with a change of about 114 m for a change of 0.5 in Ri cr. The surface sensible (latent) heat flux decreases (increases) as Ri cr increases. The influence of Ri cr on surface air temperature and specificmore » humidity is not significant. The increasing Ri cr may affect the location of the Westerly Belt in the Southern Hemisphere. Further diagnosis reveals that changes in Ri cr affect stratiform and convective precipitations differently. Increasing Ri cr leads to an increase in the stratiform precipitation but a decrease in the convective precipitation. Significant changes of convective precipitation occur over the inter-tropical convergence zone, while changes of stratiform precipitation mostly appear over arid land such as North Africa and Middle East.« less
New Gravity Wave Treatments for GISS Climate Models

NASA Technical Reports Server (NTRS)

Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye

2010-01-01

Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, we introduce a relatively simple and computationally efficient specification of unresolved orographic and non-orographic gravity waves and their interaction with the resolved flow. We show comparisons of the GISS model winds and temperatures with no gravity wave parametrization; with only orographic gravity wave parameterization; and with both orographic and non-orographic gravity wave parameterizations to illustrate how the zonal mean winds and temperatures converge toward observations. We also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. We then show results where the non-orographic gravity wave sources are specified to represent sources from convection in the Intertropical Convergence Zone and spontaneous emission from jet imbalances. Finally, we suggest a strategy to include these effects in a climate dependent manner.
Convection-Resolving Climate Change Simulations: Intensification of Heavy Hourly Precipitation Events

NASA Astrophysics Data System (ADS)

Ban, N.; Schmidli, J.; Schar, C.

2014-12-01

Reliable climate-change projections of extreme precipitation events are of great interest to decision makers, due to potentially important hydrological impacts such as floods, land slides and debris flows. Low-resolution climate models generally project increases of heavy precipitation events with climate change, but there are large uncertainties related to the limited spatial resolution and the parameterized representation of atmospheric convection. Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Comparison between 12 and 2km resolutions with parameterized and explicit convection, respectively, reveals close agreement in terms of mean summer precipitation amounts (decrease by 30%), and regarding slight increases of heavy day-long events (amounting to 15% for 90th-percentile for wet-day precipitation). However, the different resolutions yield large differences regarding extreme hourly precipitation, with the 2km version projecting substantially faster increases of heavy hourly precipitation events (about 30% increases for 90th-percentile hourly events). Ban, N., J. Schmidli and C. Schӓr (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478
An investigation of the astronomical theory of the ice ages using a simple climate-ice sheet model

NASA Technical Reports Server (NTRS)

Pollard, D.

1978-01-01

The astronomical theory of the Quaternary ice ages is incorporated into a simple climate model for global weather; important features of the model include the albedo feedback, topography and dynamics of the ice sheets. For various parameterizations of the orbital elements, the model yields realistic assessments of the northern ice sheet. Lack of a land-sea heat capacity contrast represents one of the chief difficulties of the model.
Global model comparison of heterogeneous ice nucleation parameterizations in mixed phase clouds

NASA Astrophysics Data System (ADS)

Yun, Yuxing; Penner, Joyce E.

2012-04-01

A new aerosol-dependent mixed phase cloud parameterization for deposition/condensation/immersion (DCI) ice nucleation and one for contact freezing are compared to the original formulations in a coupled general circulation model and aerosol transport model. The present-day cloud liquid and ice water fields and cloud radiative forcing are analyzed and compared to observations. The new DCI freezing parameterization changes the spatial distribution of the cloud water field. Significant changes are found in the cloud ice water fraction and in the middle cloud fractions. The new DCI freezing parameterization predicts less ice water path (IWP) than the original formulation, especially in the Southern Hemisphere. The smaller IWP leads to a less efficient Bergeron-Findeisen process resulting in a larger liquid water path, shortwave cloud forcing, and longwave cloud forcing. It is found that contact freezing parameterizations have a greater impact on the cloud water field and radiative forcing than the two DCI freezing parameterizations that we compared. The net solar flux at top of atmosphere and net longwave flux at the top of the atmosphere change by up to 8.73 and 3.52 W m-2, respectively, due to the use of different DCI and contact freezing parameterizations in mixed phase clouds. The total climate forcing from anthropogenic black carbon/organic matter in mixed phase clouds is estimated to be 0.16-0.93 W m-2using the aerosol-dependent parameterizations. A sensitivity test with contact ice nuclei concentration in the original parameterization fit to that recommended by Young (1974) gives results that are closer to the new contact freezing parameterization.
Cloud Radiation Forcings and Feedbacks: General Circulation Model Tests and Observational Validation

NASA Technical Reports Server (NTRS)

Lee,Wan-Ho; Iacobellis, Sam F.; Somerville, Richard C. J.

1997-01-01

Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.

Regional Climate Modeling over the Glaciated Regions of the Canadian High Arctic

NASA Astrophysics Data System (ADS)

Gready, Benjamin P.

The Canadian Arctic Islands (CAI) contain the largest concentration of terrestrial ice outside of the continental ice sheets. Mass loss from this region has recently increased sharply due to above average summer temperatures. Thus, increasing the understanding of the mechanisms responsible for mass loss from this region is critical. Previously, Regional Climate Models (RCMs) have been utilized to estimate climatic balance over Greenland and Antarctica. This method offers the opportunity to study a full suite of climatic variables over extensive spatially distributed grids. However, there are doubts of the applicability of such models to the CAI, given the relatively complex topography of the CAI. To test RCMs in the CAI, the polar version of the regional climate model MM5 was run at high resolution over Devon Ice Cap. At low altitudes, residuals (computed through comparisons with in situ measurements) in the net radiation budget were driven primarily by residuals in net shortwave (NSW) radiation. Residuals in NSW are largely due to inaccuracies in modeled cloud cover and modeled albedo. Albedo on glaciers and ice sheets is oversimplified in Polar MM5 and its successor, the Polar version of the Weather Research and Forecast model (Polar WRF), and is an obvious place for model improvement. Subsequently, an inline parameterization of albedo for Polar WRF was developed as a function of the depth, temperature and age of snow. The parameterization was able to reproduce elevation gradients of seasonal mean albedo derived from satellite albedo measurements (MODIS MOD10A1 daily albedo), on the western slope of the Greenland Ice Sheet for three years. Feedbacks between modelled albedo and modelled surface energy budget components were identified. The shortwave radiation flux feeds back positively with changes to albedo, whereas the longwave, turbulent and ground energy fluxes all feed back negatively, with a maximum combined magnitude of two thirds of the shortwave feedback magnitude. These strong feedbacks demonstrate that an accurate albedo parameterization must be run inline within an RCM, to accurately quantify the net surface energy budget of an ice sheet. Finally, Polar WRF, with the improved albedo parameterization, was used to simulate climatic balance over the Queen Elizabeth Islands for the summers of 2001 to 2008. Climatic balance was derived from the output using energy balance and temperature index melt models. Regional mass balance was calculated by combining climatic balance with estimates of iceberg discharge. Mass balance estimates from the model agreed, within the bounds of uncertainty, with estimates from previous studies, thus supporting the assertion that mass loss from the QEI accelerated during the first decade of the 21st century. Melt rates on the seven major icecaps of the QEI became more correlated to one another during the period 2001-2008. However, precipitation became less correlated from 2003-2008. These observations are coincident with dramatic increases in melt on all of the ice caps, and it is speculated that both are caused by decreases in the scale of disturbances delivering precipitation to the region over time.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Prein, Andreas; Langhans, Wolfgang; Fosser, Giorgia

Regional climate modeling using convection permitting models (CPMs) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs). CPMs do not use convection parameterization schemes, known as a major source of errors and uncertainties, and have more accurate surface and orography elds. The drawback of CPMs is their high demand on computational resources. For this reason, the CPM climate simulations only appeared a decade ago. In this study we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic.more » The most important components in CPM, such as physical parameterizations and dynamical formulations are discussed, and an outlook on required future developments and computer architectures that would support the application of CPMs is given. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Most improvements are found for processes related to deep convection (e.g., precipitation during summer), for mountainous regions, and for the soil-vegetation-atmosphere interactions. The climate change signals of CPM simulations reveal increases in short and extreme rainfall events and an increased ratio of liquid precipitation at the surface (a decrease of hail) potentially leading to more frequent ash oods. Concluding, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to assess their full potential and support their development.« less
Bias Reduction as Guidance for Developing Convection and Cloud Parameterization in GFDL AM4/CM4

NASA Astrophysics Data System (ADS)

Zhao, M.; Held, I.; Golaz, C.

2016-12-01

The representations of moist convection and clouds are challenging in global climate models and they are known to be important to climate simulations at all spatial and temporal scales. Many climate simulation biases can be traced to deficiencies in convection and cloud parameterizations. I will present some key biases that we are concerned about and the efforts that we have made to reduce the biases during the development of NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) new generation global climate model AM4/CM4. In particular, I will present a modified version of the moist convection scheme that is based on the University of Washington Shallow Cumulus scheme (UWShCu, Bretherton et. al 2004). The new scheme produces marked improvement in simulation of the Madden-Julian Oscillation (MJO) and the El Niño-Southern Oscillation (ENSO) compared to that used in AM3 and HIRAM. AM4/CM4 also produces high quality simulation of global distribution of cloud radiative effects and the precipitation with realistic mean climate state. This differs from models of improved MJO but with a much deteriorated mean state. The modifications to the UWShCu include an additional bulk plume for representing deep convection. The entrainment rate in the deep plume is parameterized to be a function of column-integrated relative humidity. The deep convective closure is based on relaxation of the convective available potential energy (CAPE) or cloud work function. The plumes' precipitation efficiency is optimized for better simulations of the cloud radiative effects. Precipitation re-evaporation is included in both shallow and deep plumes. In addition, a parameterization of convective gustiness is included with an energy source driven by cold pool derived from precipitation re-evaporation within the boundary layer and energy sink due to dissipation. I will present the motivations of these changes which are driven by reducing some aspects of the AM4/CM4 biases. Finally, I will also present the biases in current AM4/CM4 and challenges to further reduce them.
Flexible climate modeling systems: Lessons from Snowball Earth, Titan and Mars

NASA Astrophysics Data System (ADS)

Pierrehumbert, R. T.

2007-12-01

Climate models are only useful to the extent that real understanding can be extracted from them. Most leading- edge problems in climate change, paleoclimate and planetary climate require a high degree of flexibility in terms of incorporating model physics -- for example in allowing methane or CO2 to be a condensible substance instead of water vapor. This puts a premium on model design that allows easy modification, and on physical parameterizations that are close to fundamentals with as little empirical ad-hoc formulation as possible. I will provide examples from two approaches to this problem we have been using at the University of Chicago. The first is the FOAM general circulation model, which is a clean single-executable Fortran-77/c code supported by auxiliary applications in Python and Java. The second is a new approach based on using Python as a shell for assembling building blocks in compiled-code into full models. Applications to Snowball Earth, Titan and Mars, as well as pedagogical uses, will be discussed. One painful lesson we have learned is that Fortran-95 is a major impediment to portability and cross-language interoperability; in this light the trend toward Fortran-95 in major modelling groups is seen as a significant step backwards. In this talk, I will focus on modeling projects employing a full representation of atmospheric fluid dynamics, rather than "intermediate complexity" models in which the associated transports are parameterized.
Domain-averaged snow depth over complex terrain from flat field measurements

NASA Astrophysics Data System (ADS)

Helbig, Nora; van Herwijnen, Alec

2017-04-01

Snow depth is an important parameter for a variety of coarse-scale models and applications, such as hydrological forecasting. Since high-resolution snow cover models are computational expensive, simplified snow models are often used. Ground measured snow depth at single stations provide a chance for snow depth data assimilation to improve coarse-scale model forecasts. Snow depth is however commonly recorded at so-called flat fields, often in large measurement networks. While these ground measurement networks provide a wealth of information, various studies questioned the representativity of such flat field snow depth measurements for the surrounding topography. We developed two parameterizations to compute domain-averaged snow depth for coarse model grid cells over complex topography using easy to derive topographic parameters. To derive the two parameterizations we performed a scale dependent analysis for domain sizes ranging from 50m to 3km using highly-resolved snow depth maps at the peak of winter from two distinct climatic regions in Switzerland and in the Spanish Pyrenees. The first, simpler parameterization uses a commonly applied linear lapse rate. For the second parameterization, we first removed the obvious elevation gradient in mean snow depth, which revealed an additional correlation with the subgrid sky view factor. We evaluated domain-averaged snow depth derived with both parameterizations using flat field measurements nearby with the domain-averaged highly-resolved snow depth. This revealed an overall improved performance for the parameterization combining a power law elevation trend scaled with the subgrid parameterized sky view factor. We therefore suggest the parameterization could be used to assimilate flat field snow depth into coarse-scale snow model frameworks in order to improve coarse-scale snow depth estimates over complex topography.
Influence of ecohydrologic feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

NASA Astrophysics Data System (ADS)

van Walsum, P. E. V.; Supit, I.

2012-06-01

Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated hydrologic simulation provides a valuable addition for hydrologic modelling as well as for crop modelling.
Strategy for long-term 3D cloud-resolving simulations over the ARM SGP site and preliminary results

NASA Astrophysics Data System (ADS)

Lin, W.; Liu, Y.; Song, H.; Endo, S.

2011-12-01

Parametric representations of cloud/precipitation processes continue having to be adopted in climate simulations with increasingly higher spatial resolution or with emerging adaptive mesh framework; and it is only becoming more critical that such parameterizations have to be scale aware. Continuous cloud measurements at DOE's ARM sites have provided a strong observational basis for novel cloud parameterization research at various scales. Despite significant progress in our observational ability, there are important cloud-scale physical and dynamical quantities that are either not currently observable or insufficiently sampled. To complement the long-term ARM measurements, we have explored an optimal strategy to carry out long-term 3-D cloud-resolving simulations over the ARM SGP site using Weather Research and Forecasting (WRF) model with multi-domain nesting. The factors that are considered to have important influences on the simulated cloud fields include domain size, spatial resolution, model top, forcing data set, model physics and the growth of model errors. The hydrometeor advection that may play a significant role in hydrological process within the observational domain but is often lacking, and the limitations due to the constraint of domain-wide uniform forcing in conventional cloud system-resolving model simulations, are at least partly accounted for in our approach. Conventional and probabilistic verification approaches are employed first for selected cases to optimize the model's capability of faithfully reproducing the observed mean and statistical distributions of cloud-scale quantities. This then forms the basis of our setup for long-term cloud-resolving simulations over the ARM SGP site. The model results will facilitate parameterization research, as well as understanding and dissecting parameterization deficiencies in climate models.
Importance of biophysical effects on climate warming mitigation potential of biofuel crops over the conterminous United States

USDA-ARS?s Scientific Manuscript database

Current quantification of Climate Warming Mitigation Potential (CWMP) of biomass-derived energy has focused primarily on its biogeochemical effects. This study used site-level observations of carbon, water, and energy fluxes of biofuel crops to parameterize and evaluate the Community Land Model (CLM...
Sensitivity of Pacific Cold Tongue and Double-ITCZ Bias to Convective Parameterization

NASA Astrophysics Data System (ADS)

Woelfle, M.; Bretherton, C. S.; Pritchard, M. S.; Yu, S.

2016-12-01

Many global climate models struggle to accurately simulate annual mean precipitation and sea surface temperature (SST) fields in the tropical Pacific basin. Precipitation biases are dominated by the double intertropical convergence zone (ITCZ) bias where models exhibit precipitation maxima straddling the equator while only a single Northern Hemispheric maximum exists in observations. The major SST bias is the enhancement of the equatorial cold tongue. A series of coupled model simulations are used to investigate the sensitivity of the bias development to convective parameterization. Model components are initialized independently prior to coupling to allow analysis of the transient response of the system directly following coupling. These experiments show precipitation and SST patterns to be highly sensitive to convective parameterization. Simulations in which the deep convective parameterization is disabled forcing all convection to be resolved by the shallow convection parameterization showed a degradation in both the cold tongue and double-ITCZ biases as precipitation becomes focused into off-equatorial regions of local SST maxima. Simulations using superparameterization in place of traditional cloud parameterizations showed a reduced cold tongue bias at the expense of additional precipitation biases. The equatorial SST responses to changes in convective parameterization are driven by changes in near equatorial zonal wind stress. The sensitivity of convection to SST is important in determining the precipitation and wind stress fields. However, differences in convective momentum transport also play a role. While no significant improvement is seen in these simulations of the double-ITCZ, the system's sensitivity to these changes reaffirm that improved convective parameterizations may provide an avenue for improving simulations of tropical Pacific precipitation and SST.
Evaluation of Multiple Mechanistic Hypotheses of Leaf Photosynthesis and Stomatal Conductance against Diurnal and Seasonal Data from Two Contrasting Panamanian Tropical Forests

NASA Astrophysics Data System (ADS)

Serbin, S.; Walker, A. P.; Wu, J.; Ely, K.; Rogers, A.; Wolfe, B.

2017-12-01

Tropical forests play a key role in regulating the global carbon (C), water, and energy cycles and stores, as well as influence climate through the exchanges of mass and energy with the atmosphere. However, projected changes in temperature and precipitation patterns are expected to impact the tropics and the strength of the tropical C sink, likely resulting in significant climate feedbacks. Moreover, the impact of stronger, longer, and more extensive droughts not well understood. Critical for the accurate modeling of the tropical C and water cycle in Earth System Models (ESMs) is the representation of the coupled photosynthetic and stomatal conductance processes and how these processes are impacted by environmental and other drivers. Moreover, the parameterization and representation of these processes is an important consideration for ESM projections. We use a novel model framework, the Multi-Assumption Architecture and Testbed (MAAT), together with the open-source bioinformatics toolbox, the Predictive Ecosystem Analyzer (PEcAn), to explore the impact of the multiple mechanistic hypotheses of coupled photosynthesis and stomatal conductance as well as the additional uncertainty related to model parameterization. Our goal was to better understand how model choice and parameterization influences diurnal and seasonal modeling of leaf-level photosynthesis and stomatal conductance. We focused on the 2016 ENSO period and starting in February, monthly measurements of diurnal photosynthesis and conductance were made on 7-9 dominant species at the two Smithsonian canopy crane sites. This benchmark dataset was used to test different representations of stomatal conductance and photosynthetic parameterizations with the MAAT model, running within PEcAn. The MAAT model allows for the easy selection of competing hypotheses to test different photosynthetic modeling approaches while PEcAn provides the ability to explore the uncertainties introduced through parameterization. We found that stomatal choice can play a large role in model-data mismatch and observational constraints can be used to reduce simulated model spread, but can also result in large model disagreements with measurements. These results will be used to help inform the modeling of photosynthesis in tropical systems for the larger ESM community.
Energy-balance climate models

NASA Technical Reports Server (NTRS)

North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

1980-01-01

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.
Energy balance climate models

NASA Technical Reports Server (NTRS)

North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

1981-01-01

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.
A consistent prescription of stratospheric aerosol for both radiation and chemistry in the Community Earth System Model (CESM1)

DOE PAGES

Neely, III, Ryan Reynolds; Conley, Andrew J.; Vitt, Francis; ...

2016-07-25

Here we describe an updated parameterization for prescribing stratospheric aerosol in the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1). The need for a new parameterization is motivated by the poor response of the CESM1 (formerly referred to as the Community Climate System Model, version 4, CCSM4) simulations contributed to the Coupled Model Intercomparison Project 5 (CMIP5) to colossal volcanic perturbations to the stratospheric aerosol layer (such as the 1991 Pinatubo eruption or the 1883 Krakatau eruption) in comparison to observations. In particular, the scheme used in the CMIP5 simulations by CESM1 simulated a global mean surface temperature decreasemore » that was inconsistent with the GISS Surface Temperature Analysis (GISTEMP), NOAA's National Climatic Data Center, and the Hadley Centre of the UK Met Office (HADCRUT4). The new parameterization takes advantage of recent improvements in historical stratospheric aerosol databases to allow for variations in both the mass loading and size of the prescribed aerosol. An ensemble of simulations utilizing the old and new schemes shows CESM1's improved response to the 1991 Pinatubo eruption. Most significantly, the new scheme more accurately simulates the temperature response of the stratosphere due to local aerosol heating. Here, results also indicate that the new scheme decreases the global mean temperature response to the 1991 Pinatubo eruption by half of the observed temperature change, and modelled climate variability precludes statements as to the significance of this change.« less
Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

NASA Astrophysics Data System (ADS)

Schneider, Tapio; Lan, Shiwei; Stuart, Andrew; Teixeira, João.

2017-12-01

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.
Introducing Subrid-scale Cloud Feedbacks to Radiation for Regional Meteorological and Cllimate Modeling

EPA Science Inventory

Convection systems and associated cloudiness directly influence regional and local radiation budgets, and dynamics and thermodynamics through feedbacks. However, most subgrid-scale convective parameterizations in regional weather and climate models do not consider cumulus cloud ...
Historical and projected carbon balance of mature black spruce ecosystems across north america: The role of carbon-nitrogen interactions

USGS Publications Warehouse

Clein, Joy S.; McGuire, A.D.; Zhang, X.; Kicklighter, D.W.; Melillo, J.M.; Wofsy, S.C.; Jarvis, P.G.; Massheder, J.M.

2002-01-01

The role of carbon (C) and nitrogen (N) interactions on sequestration of atmospheric CO2 in black spruce ecosystems across North America was evaluated with the Terrestrial Ecosystem Model (TEM) by applying parameterizations of the model in which C-N dynamics were either coupled or uncoupled. First, the performance of the parameterizations, which were developed for the dynamics of black spruce ecosystems at the Bonanza Creek Long-Term Ecological Research site in Alaska, were evaluated by simulating C dynamics at eddy correlation tower sites in the Boreal Ecosystem Atmosphere Study (BOREAS) for black spruce ecosystems in the northern study area (northern site) and the southern study area (southern site) with local climate data. We compared simulated monthly growing season (May to September) estimates of gross primary production (GPP), total ecosystem respiration (RESP), and net ecosystem production (NEP) from 1994 to 1997 to available field-based estimates at both sites. At the northern site, monthly growing season estimates of GPP and RESP for the coupled and uncoupled simulations were highly correlated with the field-based estimates (coupled: R2= 0.77, 0.88 for GPP and RESP; uncoupled: R2 = 0.67, 0.92 for GPP and RESP). Although the simulated seasonal pattern of NEP generally matched the field-based data, the correlations between field-based and simulated monthly growing season NEP were lower (R2 = 0.40, 0.00 for coupled and uncoupled simulations, respectively) in comparison to the correlations between field-based and simulated GPP and RESP. The annual NEP simulated by the coupled parameterization fell within the uncertainty of field-based estimates in two of three years. On the other hand, annual NEP simulated by the uncoupled parameterization only fell within the field-based uncertainty in one of three years. At the southern site, simulated NEP generally matched field-based NEP estimates, and the correlation between monthly growing season field-based and simulated NEP (R2 = 0.36, 0.20 for coupled and uncoupled simulations, respectively) was similar to the correlations at the northern site. To evaluate the role of N dynamics in C balance of black spruce ecosystems across North America, we simulated historical and projected C dynamics from 1900 to 2100 with a global-based climatology at 0.5?? resolution (latitude ?? longitude) with both the coupled and uncoupled parameterizations of TEM. From analyses at the northern site, several consistent patterns emerge. There was greater inter-annual variability in net primary production (NPP) simulated by the uncoupled parameterization as compared to the coupled parameterization, which led to substantial differences in inter-annual variability in NEP between the parameterizations. The divergence between NPP and heterotrophic respiration was greater in the uncoupled simulation, resulting in more C sequestration during the projected period. These responses were the result of fundamentally different responses of the coupled and uncoupled parameterizations to changes in CO2 and climate. Across North American black spruce ecosystems, the range of simulated decadal changes in C storage was substantially greater for the uncoupled parameterization than for the coupled parameterization. Analysis of the spatial variability in decadal responses of C dynamics revealed that C fluxes simulated by the coupled and uncoupled parameterizations have different sensitivities to climate and that the climate sensitivities of the fluxes change over the temporal scope of the simulations. The results of this study suggest that uncertainties can be reduced through (1) factorial studies focused on elucidating the role of C and N interactions in the response of mature black spruce ecosystems to manipulations of atmospheric CO2 and climate, (2) establishment of a network of continuous, long-term measurements of C dynamics across the range of mature black spruce ecosystems in North America, and (3) ancillary measureme
The Milankovitch theory and climate sensitivity. I - Equilibrium climate model solutions for the present surface conditions. II - Interaction between the Northern Hemisphere ice sheets and the climate system

NASA Technical Reports Server (NTRS)

Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

1988-01-01

A seasonal climate model was developed to test the climate sensitivity and, in particular, the Milankovitch (1941) theory. Four climate model versions were implemented to investigate the range of uncertainty in the parameterizations of three basic feedback mechanisms: the ice albedo-temperature, the outgoing long-wave radiation-temperature, and the eddy transport-meridional temperature gradient. It was found that the differences between the simulation of the present climate by the four versions were generally small, especially for annually averaged results. The climate model was also used to study the effect of growing/shrinking of a continental ice sheet, bedrock sinking/uplifting, and sea level changes on the climate system, taking also into account the feedback effects on the climate of the building of the ice caps.
Recent Advances in High-Resolution Regional Climate Modeling at the U.S. Environmental Protection Agency

NASA Astrophysics Data System (ADS)

Alapaty, Kiran; Bullock, O. Russell; Herwehe, Jerold; Spero, Tanya; Nolte, Christopher; Mallard, Megan

2014-05-01

The Regional Climate Modeling Team at the U.S. Environmental Protection Agency has been improving the quality of regional climate fields generated by the Weather Research and Forecasting (WRF) model. Active areas of research include improving core physics within the WRF model and adapting the physics for regional climate applications, improving the representation of inland lakes that are unresolved by the driving fields, evaluating nudging strategies, and devising techniques to demonstrate value added by dynamical downscaling. These research efforts have been conducted using reanalysis data as driving fields, and then their results have been applied to downscale data from global climate models. The goals of this work are to equip environmental managers and policy/decision makers in the U.S. with science, tools, and data to inform decisions related to adapting to and mitigating the potential impacts of climate change on air quality, ecosystems, and human health. Our presentation will focus mainly on one area of the Team's research: Development and testing of a seamless convection parameterization scheme. For the continental U.S., one of the impediments to high-resolution (~3 to 15 km) climate modeling is related to the lack of a seamless convection parameterization that works across many scales. Since many convection schemes are not developed to work at those "gray scales", they often lead to excessive precipitation during warm periods (e.g., summer). The Kain-Fritsch (KF) convection parameterization in the WRF model has been updated such that it can be used seamlessly across spatial scales down to ~1 km grid spacing. First, we introduced subgrid-scale cloud and radiation interactions that had not been previously considered in the KF scheme. Then, a scaling parameter was developed to introduce scale-dependency in the KF scheme for use with various processes. In addition, we developed new formulations for: (1) convective adjustment timescale; (2) entrainment of environmental air; (3) impacts of convective updraft on grid-scale vertical velocity; (4) convective cloud microphysics; (5) stabilizing capacity; (6) elimination of double counting of precipitation; and (7) estimation of updraft mass flux at the lifting condensation level. Some of these scale-dependent formulations make the KF scheme operable at all scales up to about sub-kilometer grid resolution. In this presentation, regional climate simulations using the WRF model will be presented to demonstrate the effects of these changes to the KF scheme. Additionally, we briefly present results obtained from the improved representation of inland lakes, various nudging strategies, and added value of dynamical downscaling of regional climate. Requesting for a plenary talk for the session: "Regional climate modeling, including CORDEX" (session number CL6.4) at the EGU 2014 General Assembly, to be held 27 April - 2 May 2014 in Vienna, Austria.
WRF model sensitivity to land surface model and cumulus parameterization under short-term climate extremes over the southern Great Plains of the United States

Treesearch

Lisi Pei; Nathan Moore; Shiyuan Zhong; Lifeng Luo; David W. Hyndman; Warren E. Heilman; Zhiqiu Gao

2014-01-01

Extreme weather and climate events, especially short-term excessive drought and wet periods over agricultural areas, have received increased attention. The Southern Great Plains (SGP) is one of the largest agricultural regions in North America and features the underlying Ogallala-High Plains Aquifer system worth great economic value in large part due to production...
The Double ITCZ Syndrome in GCMs: A Coupled Problem among Convection, Atmospheric and Ocean Circulations

NASA Astrophysics Data System (ADS)

Zhang, G. J.; Song, X.

2017-12-01

The double ITCZ bias has been a long-standing problem in coupled atmosphere-ocean models. A previous study indicates that uncertainty in the projection of global warming due to doubling of CO2 is closely related to the double ITCZ biases in global climate models. Thus, reducing the double ITCZ biases is not only important to getting the current climate features right, but also important to narrowing the uncertainty in future climate projection. In this work, we will first review the possible factors contributing to the ITCZ problem. Then, we will focus on atmospheric convection, presenting recent progress in alleviating the double ITCZ problem and its sensitivity to details of convective parameterization, including trigger conditions for convection onset, convective memory, entrainment rate, updraft model and closure in the NCAR CESM1. These changes together can result in dramatic improvements in the simulation of ITCZ. Results based on both atmospheric only and coupled simulations with incremental changes of convection scheme will be shown to demonstrate the roles of convection parameterization and coupled interaction between convection, atmospheric circulation and ocean circulation in the simulation of ITCZ.

The Stochastic Parcel Model: A deterministic parameterization of stochastically entraining convection

DOE PAGES

Romps, David M.

2016-03-01

Convective entrainment is a process that is poorly represented in existing convective parameterizations. By many estimates, convective entrainment is the leading source of error in global climate models. As a potential remedy, an Eulerian implementation of the Stochastic Parcel Model (SPM) is presented here as a convective parameterization that treats entrainment in a physically realistic and computationally efficient way. Drawing on evidence that convecting clouds comprise air parcels subject to Poisson-process entrainment events, the SPM calculates the deterministic limit of an infinite number of such parcels. For computational efficiency, the SPM groups parcels at each height by their purity, whichmore » is a measure of their total entrainment up to that height. This reduces the calculation of convective fluxes to a sequence of matrix multiplications. The SPM is implemented in a single-column model and compared with a large-eddy simulation of deep convection.« less
Short-term Time Step Convergence in a Climate Model

DOE PAGES

Wan, Hui; Rasch, Philip J.; Taylor, Mark; ...

2015-02-11

A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to themore » expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.« less
A physically-based approach of treating dust-water cloud interactions in climate models

NASA Astrophysics Data System (ADS)

Kumar, P.; Karydis, V.; Barahona, D.; Sokolik, I. N.; Nenes, A.

2011-12-01

All aerosol-cloud-climate assessment studies to date assume that the ability of dust (and other insoluble species) to act as a Cloud Condensation Nuclei (CCN) is determined solely by their dry size and amount of soluble material. Recent evidence however clearly shows that dust can act as efficient CCN (even if lacking appreciable amounts of soluble material) through adsorption of water vapor onto the surface of the particle. This "inherent" CCN activity is augmented as the dust accumulates soluble material through atmospheric aging. A comprehensive treatment of dust-cloud interactions therefore requires including both of these sources of CCN activity in atmospheric models. This study presents a "unified" theory of CCN activity that considers both effects of adsorption and solute. The theory is corroborated and constrained with experiments of CCN activity of mineral aerosols generated from clays, calcite, quartz, dry lake beds and desert soil samples from Northern Africa, East Asia/China, and Northern America. The unified activation theory then is included within the mechanistic droplet activation parameterization of Kumar et al. (2009) (including the giant CCN correction of Barahona et al., 2010), for a comprehensive treatment of dust impacts on global CCN and cloud droplet number. The parameterization is demonstrated with the NASA Global Modeling Initiative (GMI) Chemical Transport Model using wind fields computed with the Goddard Institute for Space Studies (GISS) general circulation model. References Barahona, D. et al. (2010) Comprehensively Accounting for the Effect of Giant CCN in Cloud Activation Parameterizations, Atmos.Chem.Phys., 10, 2467-2473 Kumar, P., I.N. Sokolik, and A. Nenes (2009), Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN, Atmos.Chem.Phys., 9, 2517- 2532
Utilization of Short-Simulations for Tuning High-Resolution Climate Model

NASA Astrophysics Data System (ADS)

Lin, W.; Xie, S.; Ma, P. L.; Rasch, P. J.; Qian, Y.; Wan, H.; Ma, H. Y.; Klein, S. A.

2016-12-01

Many physical parameterizations in atmospheric models are sensitive to resolution. Tuning the models that involve a multitude of parameters at high resolution is computationally expensive, particularly when relying primarily on multi-year simulations. This work describes a complementary set of strategies for tuning high-resolution atmospheric models, using ensembles of short simulations to reduce the computational cost and elapsed time. Specifically, we utilize the hindcast approach developed through the DOE Cloud Associated Parameterization Testbed (CAPT) project for high-resolution model tuning, which is guided by a combination of short (< 10 days ) and longer ( 1 year) Perturbed Parameters Ensemble (PPE) simulations at low resolution to identify model feature sensitivity to parameter changes. The CAPT tests have been found to be effective in numerous previous studies in identifying model biases due to parameterized fast physics, and we demonstrate that it is also useful for tuning. After the most egregious errors are addressed through an initial "rough" tuning phase, longer simulations are performed to "hone in" on model features that evolve over longer timescales. We explore these strategies to tune the DOE ACME (Accelerated Climate Modeling for Energy) model. For the ACME model at 0.25° resolution, it is confirmed that, given the same parameters, major biases in global mean statistics and many spatial features are consistent between Atmospheric Model Intercomparison Project (AMIP)-type simulations and CAPT-type hindcasts, with just a small number of short-term simulations for the latter over the corresponding season. The use of CAPT hindcasts to find parameter choice for the reduction of large model biases dramatically improves the turnaround time for the tuning at high resolution. Improvement seen in CAPT hindcasts generally translates to improved AMIP-type simulations. An iterative CAPT-AMIP tuning approach is therefore adopted during each major tuning cycle, with the former to survey the likely responses and narrow the parameter space, and the latter to verify the results in climate context along with assessment in greater detail once an educated set of parameter choice is selected. Limitations on using short-term simulations for tuning climate model are also discussed.
Linking Global to Regional Models to Assess Future Climate Impacts on Surface Ozone Concentrations in the United States

EPA Science Inventory

The UCD sectional aerosol model has been coupled to the CMAQ air quality model and used to simulate air quality in Tampa, Florida. Sea salt emissions are parameterized as a function of modeled wind speed and relative humidity. Modeled aerosol sulfate, nitrate, ammonium, sodium,...
Impact of Improvements in Volcanic Implementation on Atmospheric Chemistry and Climate in the GISS-E2 Model

NASA Technical Reports Server (NTRS)

Tsigaridis, Kostas; LeGrande, Allegra; Bauer, Susanne

2015-01-01

The representation of volcanic eruptions in climate models introduces some of the largest errors when evaluating historical simulations, partly due to the crude model parameterizations. We will show preliminary results from the Goddard Institute for Space Studies (GISS)-E2 model comparing traditional highly parameterized volcanic implementation (specified Aerosol Optical Depth, Effective Radius) to deploying the full aerosol microphysics module MATRIX and directly emitting SO2 allowing us the prognosically determine the chemistry and climate impact. We show a reasonable match in aerosol optical depth, effective radius, and forcing between the full aerosol implementation and reconstructions/observations of the Mt. Pinatubo 1991 eruption, with a few areas as targets for future improvement. This allows us to investigate not only the climate impact of the injection of volcanic aerosols, but also influences on regional water vapor, O3, and OH distributions. With the skill of the MATRIX volcano implementation established, we explore (1) how the height of the injection column of SO2 influence atmospheric chemistry and climate response, (2) how the initial condition of the atmosphere influences the climate and chemistry impact of the eruption with a particular focus on how ENSO and QBO and (3) how the coupled chemistry could mitigate the climate signal for much larger eruptions (i.e. the 1258 eruption, reconstructed to be approximately 10x Pinatubo). During each sensitivity experiment we assess the impact on profiles of water vapor, O3, and OH, and assess how the eruption impacts the budget of each.
The seasonal CO2 cycle on Mars - An application of an energy balance climate model

NASA Technical Reports Server (NTRS)

James, P. B.; North, G. R.

1982-01-01

Energy balance climate models of the Budyko-Sellers variety are applied to the carbon-dioxide cycle on Mars. Recent data available from the Viking mission, in particular the seasonal pressure variations measured by Viking landers, are used to constrain the models. No set of parameters was found for which a one-dimensional model parameterized in terms of ground temperature gave an adequate fit to the observed pressure variations. A modified, two-dimensional model including the effects of dust storms and the polar hood reasonably reproduces the pressure curve, however. The implications of these results for Martian climate changes are discussed.
Applying an economical scale-aware PDF-based turbulence closure model in NOAA NCEP GCMs

NASA Astrophysics Data System (ADS)

Belochitski, A.; Krueger, S. K.; Moorthi, S.; Bogenschutz, P.; Pincus, R.

2016-12-01

A novel unified representation of sub-grid scale (SGS) turbulence, cloudiness, and shallow convection is being implemented into the NOAA NCEP Global Forecasting System (GFS) general circulation model. The approach, known as Simplified High Order Closure (SHOC), is based on predicting a joint PDF of SGS thermodynamic variables and vertical velocity and using it to diagnose turbulent diffusion coefficients, SGS fluxes, condensation and cloudiness. Unlike other similar methods, only one new prognostic variable, turbulent kinetic energy (TKE), needs to be intoduced, making the technique computationally efficient.SHOC is now incorporated into a version of GFS, as well as into the next generation of the NCEP global model - NOAA Environmental Modeling System (NEMS). Turbulent diffusion coefficients computed by SHOC are now used in place of those produced by the boundary layer turbulence and shallow convection parameterizations. Large scale microphysics scheme is no longer used to calculate cloud fraction or the large-scale condensation/deposition. Instead, SHOC provides these variables. Radiative transfer parameterization uses cloudiness computed by SHOC.Outstanding problems include high level tropical cloud fraction being too high in SHOC runs, possibly related to the interaction of SHOC with condensate detrained from deep convection.Future work will consist of evaluating model performance and tuning the physics if necessary, by performing medium-range NWP forecasts with prescribed initial conditions, and AMIP-type climate tests with prescribed SSTs. Depending on the results, the model will be tuned or parameterizations modified. Next, SHOC will be implemented in the NCEP CFS, and tuned and evaluated for climate applications - seasonal prediction and long coupled climate runs. Impact of new physics on ENSO, MJO, ISO, monsoon variability, etc will be examined.
Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE PAGES

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.; ...

2017-09-14

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less
Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less
Examining Chaotic Convection with Super-Parameterization Ensembles

NASA Astrophysics Data System (ADS)

Jones, Todd R.

This study investigates a variety of features present in a new configuration of the Community Atmosphere Model (CAM) variant, SP-CAM 2.0. The new configuration (multiple-parameterization-CAM, MP-CAM) changes the manner in which the super-parameterization (SP) concept represents physical tendency feedbacks to the large-scale by using the mean of 10 independent two-dimensional cloud-permitting model (CPM) curtains in each global model column instead of the conventional single CPM curtain. The climates of the SP and MP configurations are examined to investigate any significant differences caused by the application of convective physical tendencies that are more deterministic in nature, paying particular attention to extreme precipitation events and large-scale weather systems, such as the Madden-Julian Oscillation (MJO). A number of small but significant changes in the mean state climate are uncovered, and it is found that the new formulation degrades MJO performance. Despite these deficiencies, the ensemble of possible realizations of convective states in the MP configuration allows for analysis of uncertainty in the small-scale solution, lending to examination of those weather regimes and physical mechanisms associated with strong, chaotic convection. Methods of quantifying precipitation predictability are explored, and use of the most reliable of these leads to the conclusion that poor precipitation predictability is most directly related to the proximity of the global climate model column state to atmospheric critical points. Secondarily, the predictability is tied to the availability of potential convective energy, the presence of mesoscale convective organization on the CPM grid, and the directive power of the large-scale.
Representations of the Stratospheric Polar Vortices in Versions 1 and 2 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM)

NASA Technical Reports Server (NTRS)

Pawson, S.; Stolarski, R.S.; Nielsen, J.E.; Perlwitz, J.; Oman, L.; Waugh, D.

2009-01-01

This study will document the behavior of the polar vortices in two versions of the GEOS CCM. Both versions of the model include the same stratospheric chemistry, They differ in the underlying circulation model. Version 1 of the GEOS CCM is based on the Goddard Earth Observing System, Version 4, general circulation model which includes the finite-volume (Lin-Rood) dynamical core and physical parameterizations from Community Climate Model, Version 3. GEOS CCM Version 2 is based on the GEOS-5 GCM that includes a different tropospheric physics package. Baseline simulations of both models, performed at two-degree spatial resolution, show some improvements in Version 2, but also some degradation, In the Antarctic, both models show an over-persistent stratospheric polar vortex with late breakdown, but the year-to-year variations that are overestimated in Version I are more realistic in Version 2. The implications of this for the interactions with tropospheric climate, the Southern Annular Mode, will be discussed. In the Arctic both model versions show a dominant dynamically forced variabi;ity, but Version 2 has a persistent warm bias in the low stratosphere and there are seasonal differences in the simulations. These differences will be quantified in terms of climate change and ozone loss. Impacts of model resolution, using simulations at one-degree and half-degree, and changes in physical parameterizations (especially the gravity wave drag) will be discussed.
On the physical air-sea fluxes for climate modeling

NASA Astrophysics Data System (ADS)

Bonekamp, J. G.

2001-02-01

At the sea surface, the atmosphere and the ocean exchange momentum, heat and freshwater. Mechanisms for the exchange are wind stress, turbulent mixing, radiation, evaporation and precipitation. These surface fluxes are characterized by a large spatial and temporal variability and play an important role in not only the mean atmospheric and oceanic circulation, but also in the generation and sustainment of coupled climate fluctuations such as the El Niño/La Niña phenomenon. Therefore, a good knowledge of air-sea fluxes is required for the understanding and prediction of climate changes. As part of long-term comprehensive atmospheric reanalyses with `Numerical Weather Prediction/Data assimilation' systems, data sets of global air-sea fluxes are generated. A good example is the 15-year atmospheric reanalysis of the European Centre for Medium--Range Weather Forecasts (ECMWF). Air-sea flux data sets from these reanalyses are very beneficial for climate research, because they combine a good spatial and temporal coverage with a homogeneous and consistent method of calculation. However, atmospheric reanalyses are still imperfect sources of flux information due to shortcomings in model variables, model parameterizations, assimilation methods, sampling of observations, and quality of observations. Therefore, assessments of the errors and the usefulness of air-sea flux data sets from atmospheric (re-)analyses are relevant contributions to the quantitative study of climate variability. Currently, much research is aimed at assessing the quality and usefulness of the reanalysed air-sea fluxes. Work in this thesis intends to contribute to this assessment. In particular, it attempts to answer three relevant questions. The first question is: What is the best parameterization of the momentum flux? A comparison is made of the wind stress parameterization of the ERA15 reanalysis, the currently generated ERA40 reanalysis and the wind stress measurements over the open ocean. The comparison reveals some clear differences in the mean drag coefficient. In addition, this study has indicated that progress has been made from the ERA15 to the ERA40 reanalyses by replacing the model parameterization with a constant Charnock parameter with one which depends on the sea state. The second research question is whether comparison of the response of an ocean model with ocean observations can be exploited to assess the quality of air-sea fluxes of the ERA15 reanalysis. To answer this question in a systematic way an inverse modeling approach is adopted using a four-dimensional variational data assimilation (4DVAR) scheme. Firstly, the functioning of the 4DVAR system is demonstrated from identical twin experiments. These experiments reveal that in the equatorial Pacific, a large reduction in wind-stress and upper-ocean temperature misfits can be achieved using an assimilation time window of eight weeks. It is concluded that the usefulness of inverse ocean modeling technique for global surface flux assessment is limited. The main merit of the developed ocean 4DVAR scheme will be to diagnose errors in the ocean analyses of the ocean model. The last research question is: are the ERA15 fluxes useful for the study of regional patterns of climate variability? The climate mode of consideration is the Antarctic Circumpolar Wave. This study stresses the importance to have the right climatological forcing conditions to assess time scales of climate variability and it confirms the usefulness of ERA15 air-sea fluxes as ocean model forcing fields to study climate variability on the interannual time scale.
Hydrological model parameterization using NDVI values to account for the effects of land-cover change on the rainfall-runoff response

USDA-ARS?s Scientific Manuscript database

Classic rainfall-runoff models usually use historical data to estimate model parameters and mean values of parameters are considered for predictions. However, due to climate changes and human effects, the parameters of model change temporally. To overcome this problem, Normalized Difference Vegetati...
Parameterization of the ACRU model for estimating biophysical and climatological change impacts, Beaver Creek, Alberta

NASA Astrophysics Data System (ADS)

Forbes, K. A.; Kienzle, S. W.; Coburn, C. A.; Byrne, J. M.

2006-12-01

Multiple threats, including intensification of agricultural production, non-renewable resource extraction and climate change, are threatening Southern Alberta's water supply. The objective of this research is to calibrate/evaluate the Agricultural Catchments Research Unit (ACRU) agrohydrological model; with the end goal of forecasting the impacts of a changing environment on water quantity. The strength of this model is the intensive multi-layered soil water budgeting routine that integrates water movement between the surface and atmosphere. The ACRU model was parameterized using data from Environment Canada's climate database for a twenty year period (1984-2004) and was used to simulate streamflow for Beaver Creek. The simulated streamflow was compared to Environment Canada's historical streamflow database to validate the model output. The Beaver Creek Watershed, located in the Porcupine Hills southwestern Alberta, Canada contains a heterogeneous cover of deciduous, coniferous, native prairie grasslands and forage crops. In a catchment with highly diversified land cover, canopy architecture cannot be overlooked in rainfall interception parameterization. Preliminary testing of ACRU suggests that streamflows were sensitive to varied levels of leaf area index (LAI), a representative fraction of canopy foliage. Further testing using remotely sensed LAI's will provide a more accurate representation of canopy foliage and ultimately best represent this important element of the hydrological cycle and the associated processes which govern the natural hydrology of the Beaver Creek watershed.
Climate model biases in seasonality of continental water storage revealed by satellite gravimetry

USGS Publications Warehouse

Swenson, Sean; Milly, P.C.D.

2006-01-01

Satellite gravimetric observations of monthly changes in continental water storage are compared with outputs from five climate models. All models qualitatively reproduce the global pattern of annual storage amplitude, and the seasonal cycle of global average storage is reproduced well, consistent with earlier studies. However, global average agreements mask systematic model biases in low latitudes. Seasonal extrema of low‐latitude, hemispheric storage generally occur too early in the models, and model‐specific errors in amplitude of the low‐latitude annual variations are substantial. These errors are potentially explicable in terms of neglected or suboptimally parameterized water stores in the land models and precipitation biases in the climate models.
Impact of a Stochastic Parameterization Scheme on El Nino-Southern Oscillation in the Community Climate System Model

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Berner, J.; Sardeshmukh, P. D.

2017-12-01

Stochastic parameterizations have been used for more than a decade in atmospheric models. They provide a way to represent model uncertainty through representing the variability of unresolved sub-grid processes, and have been shown to have a beneficial effect on the spread and mean state for medium- and extended-range forecasts. There is increasing evidence that stochastic parameterization of unresolved processes can improve the bias in mean and variability, e.g. by introducing a noise-induced drift (nonlinear rectification), and by changing the residence time and structure of flow regimes. We present results showing the impact of including the Stochastically Perturbed Parameterization Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. SPPT results in a significant improvement in the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. We use a Linear Inverse Modelling framework to gain insight into the mechanisms by which SPPT has improved ENSO-variability.
Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.Plain Language SummaryProbabilistic weather forecasts, especially for tropical weather, is still a significant challenge for global weather forecasting systems. Expressing uncertainty along with weather forecasts is important for informed decision making. Hence, we explore the use of a relatively new approach in using super-parameterization, where a cloud resolving model is embedded within a global model, in probabilistic tropical weather forecasts at medium range. We show that this approach helps improve modeling uncertainty in forecasts of certain features such as precipitation magnitude and location better, but forecasts of tropical winds are not necessarily improved. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H33D0903C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H33D0903C">A blueprint for using climate change predictions in an eco-hydrological study</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Caporali, E.; Fatichi, S.; Ivanov, V. Y. 2009-12-01 There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for uncertainties in projections of future climate is discussed and a methodology for propagating these uncertainties into the probability density functions of changes in eco-hydrological variables is presented. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A31E2238C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A31E2238C">The influence of Cloud Longwave Scattering together with a state-of-the-art Ice Longwave Optical Parameterization in Climate Model Simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chen, Y. H.; Kuo, C. P.; Huang, X.; Yang, P. 2017-12-01 Clouds play an important role in the Earth's radiation budget, and thus realistic and comprehensive treatments of cloud optical properties and cloud-sky radiative transfer are crucial for simulating weather and climate. However, most GCMs neglect LW scattering effects by clouds and tend to use inconsistent cloud SW and LW optical parameterizations. Recently, co-authors of this study have developed a new LW optical properties parameterization for ice clouds, which is based on ice cloud particle statistics from MODIS measurements and state-of-the-art scattering calculation. A two-stream multiple-scattering scheme has also been implemented into the RRTMG_LW, a widely used longwave radiation scheme by climate modeling centers. This study is to integrate both the new LW cloud-radiation scheme for ice clouds and the modified RRTMG_LW with scattering capability into the NCAR CESM to improve the cloud longwave radiation treatment. A number of single column model (SCM) simulations using the observation from the ARM SGP site on July 18 to August 4 in 1995 are carried out to assess the impact of new LW optical properties of clouds and scattering-enabled radiation scheme on simulated radiation budget and cloud radiative effect (CRE). The SCM simulation allows interaction between cloud and radiation schemes with other parameterizations, but the large-scale forcing is prescribed or nudged. Comparing to the results from the SCM of the standard CESM, the new ice cloud optical properties alone leads to an increase of LW CRE by 26.85 W m-2 in average, as well as an increase of the downward LW flux at surface by 6.48 W m-2. Enabling LW cloud scattering further increases the LW CRE by another 3.57 W m-2 and the downward LW flux at the surface by 0.2 W m-2. The change of LW CRE is mainly due to an increase of cloud top height, which enhances the LW CRE. A long-term simulation of CESM will be carried out to further understand the impact of such changes on simulated climates. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active">9</li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active">10</li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JAMES...9...39T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JAMES...9...39T">The "Grey Zone" cold air outbreak global model intercomparison: A cross evaluation using large-eddy simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tomassini, Lorenzo; Field, Paul R.; Honnert, Rachel; Malardel, Sylvie; McTaggart-Cowan, Ron; Saitou, Kei; Noda, Akira T.; Seifert, Axel 2017-03-01 A stratocumulus-to-cumulus transition as observed in a cold air outbreak over the North Atlantic Ocean is compared in global climate and numerical weather prediction models and a large-eddy simulation model as part of the Working Group on Numerical Experimentation "Grey Zone" project. The focus of the project is to investigate to what degree current convection and boundary layer parameterizations behave in a scale-adaptive manner in situations where the model resolution approaches the scale of convection. Global model simulations were performed at a wide range of resolutions, with convective parameterizations turned on and off. The models successfully simulate the transition between the observed boundary layer structures, from a well-mixed stratocumulus to a deeper, partly decoupled cumulus boundary layer. There are indications that surface fluxes are generally underestimated. The amount of both cloud liquid water and cloud ice, and likely precipitation, are under-predicted, suggesting deficiencies in the strength of vertical mixing in shear-dominated boundary layers. But also regulation by precipitation and mixed-phase cloud microphysical processes play an important role in the case. With convection parameterizations switched on, the profiles of atmospheric liquid water and cloud ice are essentially resolution-insensitive. This, however, does not imply that convection parameterizations are scale-aware. Even at the highest resolutions considered here, simulations with convective parameterizations do not converge toward the results of convection-off experiments. Convection and boundary layer parameterizations strongly interact, suggesting the need for a unified treatment of convective and turbulent mixing when addressing scale-adaptivity. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016MAP...128...73B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016MAP...128...73B">Sensitivity analysis with the regional climate model COSMO-CLM over the CORDEX-MENA domain</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bucchignani, E.; Cattaneo, L.; Panitz, H.-J.; Mercogliano, P. 2016-02-01 The results of a sensitivity work based on ERA-Interim driven COSMO-CLM simulations over the Middle East-North Africa (CORDEX-MENA) domain are presented. All simulations were performed at 0.44° spatial resolution. The purpose of this study was to ascertain model performances with respect to changes in physical and tuning parameters which are mainly related to surface, convection, radiation and cloud parameterizations. Evaluation was performed for the whole CORDEX-MENA region and six sub-regions, comparing a set of 26 COSMO-CLM runs against a combination of available ground observations, satellite products and reanalysis data to assess temperature, precipitation, cloud cover and mean sea level pressure. The model proved to be very sensitive to changes in physical parameters. The optimized configuration allows COSMO-CLM to improve the simulated main climate features of this area. Its main characteristics consist in the new parameterization of albedo, based on Moderate Resolution Imaging Spectroradiometer data, and the new parameterization of aerosol, based on NASA-GISS AOD distributions. When applying this configuration, Mean Absolute Error values for the considered variables are as follows: about 1.2 °C for temperature, about 15 mm/month for precipitation, about 9 % for total cloud cover, and about 0.6 hPa for mean sea level pressure. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170011698','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170011698">Improved Intraseasonal Variability in the NASA GEOS AGCM with 2-moment Microphysics and a Shallow Cumulus Parameterization</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Arnold, Nathan; Barahona, Donifan; Achuthavarier, Deepthi 2017-01-01 Weather and climate models have long struggled to realistically simulate the Madden-Julian Oscillation (MJO). Here we present a significant improvement in MJO simulation in NASA's GEOS atmospheric model with the implementation of 2-moment microphysics and the UW shallow cumulus parameterization. Comparing ten-year runs (2007-2016) with the old (1mom) and updated (2mom+shlw) model physics, the updated model has increased intra-seasonal variance with increased coherence. Surface fluxes and OLR are found to vary more realistically with precipitation, and a moisture budget suggests that changes in rain reevaporation and the cloud longwave feedback help support heavy precipitation. Preliminary results also show improved MJO hindcast skill. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19920024901','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19920024901">Remote sensing technology research and instrumentation platform design</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 1992-01-01 An instrumented pallet concept and definition of an aircraft with performance and payload capability to meet NASA's airborne turbulent flux measurement needs for advanced multiple global climate research and field experiments is presented. The report addresses airborne measurement requirements for general circulation model sub-scale parameterization research, specifies instrumentation capable of making these measurements, and describes a preliminary support pallet design. Also, a review of aircraft types and a recommendation of a manned and an unmanned aircraft capable of meeting flux parameterization research needs is given. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013ThCFD..27..133D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013ThCFD..27..133D">Stochastic parameterization of shallow cumulus convection estimated from high-resolution model data</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dorrestijn, Jesse; Crommelin, Daan T.; Siebesma, A. Pier.; Jonker, Harm J. J. 2013-02-01 In this paper, we report on the development of a methodology for stochastic parameterization of convective transport by shallow cumulus convection in weather and climate models. We construct a parameterization based on Large-Eddy Simulation (LES) data. These simulations resolve the turbulent fluxes of heat and moisture and are based on a typical case of non-precipitating shallow cumulus convection above sea in the trade-wind region. Using clustering, we determine a finite number of turbulent flux pairs for heat and moisture that are representative for the pairs of flux profiles observed in these simulations. In the stochastic parameterization scheme proposed here, the convection scheme jumps randomly between these pre-computed pairs of turbulent flux profiles. The transition probabilities are estimated from the LES data, and they are conditioned on the resolved-scale state in the model column. Hence, the stochastic parameterization is formulated as a data-inferred conditional Markov chain (CMC), where each state of the Markov chain corresponds to a pair of turbulent heat and moisture fluxes. The CMC parameterization is designed to emulate, in a statistical sense, the convective behaviour observed in the LES data. The CMC is tested in single-column model (SCM) experiments. The SCM is able to reproduce the ensemble spread of the temperature and humidity that was observed in the LES data. Furthermore, there is a good similarity between time series of the fractions of the discretized fluxes produced by SCM and observed in LES. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1454817-goamazon2014-campaign-points-deep-inflow-approach-deep-convection-across-scales','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1454817-goamazon2014-campaign-points-deep-inflow-approach-deep-convection-across-scales">GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Schiro, Kathleen A.; Ahmed, Fiaz; Giangrande, Scott E.; ... 2018-04-17 Representations of strongly precipitating deep-convective systems in climate models are among the most important factors in their simulation. Parameterizations of these motions face the dual challenge of unclear pathways to including mesoscale organization and high sensitivity of convection to approximations of turbulent entrainment of environmental air. Ill-constrained entrainment processes can even affect global average climate sensitivity under global warming. Multiinstrument observations from the Department of Energy GoAmazon2014/5 field campaign suggest that an alternative formulation from radar-derived dominant updraft structure yields a strong relationship of precipitation to buoyancy in both mesoscale and smaller-scale convective systems. This simultaneously provides a key stepmore » toward representing the influence of mesoscale convection in climate models and sidesteps a problematic dependence on traditional entrainment rates. A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Lastly, deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1454817-goamazon2014-campaign-points-deep-inflow-approach-deep-convection-across-scales','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1454817-goamazon2014-campaign-points-deep-inflow-approach-deep-convection-across-scales">GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Schiro, Kathleen A.; Ahmed, Fiaz; Giangrande, Scott E. Representations of strongly precipitating deep-convective systems in climate models are among the most important factors in their simulation. Parameterizations of these motions face the dual challenge of unclear pathways to including mesoscale organization and high sensitivity of convection to approximations of turbulent entrainment of environmental air. Ill-constrained entrainment processes can even affect global average climate sensitivity under global warming. Multiinstrument observations from the Department of Energy GoAmazon2014/5 field campaign suggest that an alternative formulation from radar-derived dominant updraft structure yields a strong relationship of precipitation to buoyancy in both mesoscale and smaller-scale convective systems. This simultaneously provides a key stepmore » toward representing the influence of mesoscale convection in climate models and sidesteps a problematic dependence on traditional entrainment rates. A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Lastly, deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1132211-assessing-cam5-physics-suite-wrf-chem-model-implementation-resolution-sensitivity-first-evaluation-regional-case-study','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1132211-assessing-cam5-physics-suite-wrf-chem-model-implementation-resolution-sensitivity-first-evaluation-regional-case-study">Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Ma, Po-Lun; Rasch, Philip J.; Fast, Jerome D. A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 whenmore » the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN21D0068S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN21D0068S">Development of a Cloud Resolving Model for Heterogeneous Supercomputers</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sreepathi, S.; Norman, M. R.; Pal, A.; Hannah, W.; Ponder, C. 2017-12-01 A cloud resolving climate model is needed to reduce major systematic errors in climate simulations due to structural uncertainty in numerical treatments of convection - such as convective storm systems. This research describes the porting effort to enable SAM (System for Atmosphere Modeling) cloud resolving model on heterogeneous supercomputers using GPUs (Graphical Processing Units). We have isolated a standalone configuration of SAM that is targeted to be integrated into the DOE ACME (Accelerated Climate Modeling for Energy) Earth System model. We have identified key computational kernels from the model and offloaded them to a GPU using the OpenACC programming model. Furthermore, we are investigating various optimization strategies intended to enhance GPU utilization including loop fusion/fission, coalesced data access and loop refactoring to a higher abstraction level. We will present early performance results, lessons learned as well as optimization strategies. The computational platform used in this study is the Summitdev system, an early testbed that is one generation removed from Summit, the next leadership class supercomputer at Oak Ridge National Laboratory. The system contains 54 nodes wherein each node has 2 IBM POWER8 CPUs and 4 NVIDIA Tesla P100 GPUs. This work is part of a larger project, ACME-MMF component of the U.S. Department of Energy(DOE) Exascale Computing Project. The ACME-MMF approach addresses structural uncertainty in cloud processes by replacing traditional parameterizations with cloud resolving "superparameterization" within each grid cell of global climate model. Super-parameterization dramatically increases arithmetic intensity, making the MMF approach an ideal strategy to achieve good performance on emerging exascale computing architectures. The goal of the project is to integrate superparameterization into ACME, and explore its full potential to scientifically and computationally advance climate simulation and prediction. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3718207','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3718207">Improving ecophysiological simulation models to predict the impact of elevated atmospheric CO2 concentration on crop productivity</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Yin, Xinyou 2013-01-01 Background Process-based ecophysiological crop models are pivotal in assessing responses of crop productivity and designing strategies of adaptation to climate change. Most existing crop models generally over-estimate the effect of elevated atmospheric [CO2], despite decades of experimental research on crop growth response to [CO2]. Analysis A review of the literature indicates that the quantitative relationships for a number of traits, once expressed as a function of internal plant nitrogen status, are altered little by the elevated [CO2]. A model incorporating these nitrogen-based functional relationships and mechanisms simulated photosynthetic acclimation to elevated [CO2], thereby reducing the chance of over-estimating crop response to [CO2]. Robust crop models to have small parameterization requirements and yet generate phenotypic plasticity under changing environmental conditions need to capture the carbon–nitrogen interactions during crop growth. Conclusions The performance of the improved models depends little on the type of the experimental facilities used to obtain data for parameterization, and allows accurate projections of the impact of elevated [CO2] and other climatic variables on crop productivity. PMID:23388883 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A23D2394H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A23D2394H">Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D. 2017-12-01 Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A24D..04D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A24D..04D">High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2): Large Eddy Simulation Study Over Germany</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dipankar, A.; Stevens, B. B.; Zängl, G.; Pondkule, M.; Brdar, S. 2014-12-01 The effect of clouds on large scale dynamics is represented in climate models through parameterization of various processes, of which the parameterization of shallow and deep convection are particularly uncertain. The atmospheric boundary layer, which controls the coupling to the surface, and which defines the scale of shallow convection, is typically 1 km in depth. Thus, simulations on a O(100 m) grid largely obviate the need for such parameterizations. By crossing this threshold of O(100m) grid resolution one can begin thinking of large-eddy simulation (LES), wherein the sub-grid scale parameterization have a sounder theoretical foundation. Substantial initiatives have been taken internationally to approach this threshold. For example, Miura et al., 2007 and Mirakawa et al., 2014 approach this threshold by doing global simulations, with (gradually) decreasing grid resolution, to understand the effect of cloud-resolving scales on the general circulation. Our strategy, on the other hand, is to take a big leap forward by fixing the resolution at O(100 m), and gradually increasing the domain size. We believe that breaking this threshold would greatly help in improving the parameterization schemes and reducing the uncertainty in climate predictions. To take this forward, the German Federal Ministry of Education and Research has initiated a project on HD(CP)2 that aims for a limited area LES at resolution O(100 m) using the new unified modeling system ICON (Zängl et al., 2014). In the talk, results from the HD(CP)2 evaluation simulation will be shown that targets high resolution simulation over a small domain around Jülich, Germany. This site is chosen because high resolution HD(CP)2 Observational Prototype Experiment took place in this region from 1.04.2013 to 31.05.2013, in order to critically evaluate the model. Nesting capabilities of ICON is used to gradually increase the resolution from the outermost domain, which is forced from the COSMO-DE data, to the innermost and finest resolution domain centered around Jülich (see Fig. 1 top panel). Furthermore, detailed analyses of the simulation results against the observation data will be presented. A reprsentative figure showing time series of column integrated water vapor (IWV) for both model and observation on 24.04.2013 is shown in bottom panel of Fig. 1. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1335565','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1335565">Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Wang, Zhien Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentrationmore » retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations of mixed-phase cloud simulations by CAM5 were performed. Measurement results indicate that ice concentrations control stratiform mixed-phase cloud properties. The improvement of ice concentration parameterization in the CAM5 was done in close collaboration with Dr. Xiaohong Liu, PNNL (now at University of Wyoming).« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26747843','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26747843">Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C 2016-01-01 Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1365568','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1365568">Collaborative Research: Quantifying the Uncertainties of Aerosol Indirect Effects and Impacts on Decadal-Scale Climate Variability in NCAR CAM5 and CESM1</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Nenes, Athanasios The goal of this proposed project is to assess the climatic importance and sensitivity of aerosol indirect effect (AIE) to cloud and aerosol processes and feedbacks, which include organic aerosol hygroscopicity, cloud condensation nuclei (CCN) activation kinetics, Giant CCN, cloud-scale entrainment, ice nucleation in mixed-phase and cirrus clouds, and treatment of subgrid variability of vertical velocity. A key objective was to link aerosol, cloud microphysics and dynamics feedbacks in CAM5 with a suite of internally consistent and integrated parameterizations that provide the appropriate degrees of freedom to capture the various aspects of the aerosol indirect effect. The proposal integrated newmore » parameterization elements into the cloud microphysics, moist turbulence and aerosol modules used by the NCAR Community Atmospheric Model version 5 (CAM5). The CAM5 model was then used to systematically quantify the uncertainties of aerosol indirect effects through a series of sensitivity tests with present-day and preindustrial aerosol emissions. New parameterization elements were developed as a result of these efforts, and new diagnostic tools & methodologies were also developed to quantify the impacts of aerosols on clouds and climate within fully coupled models. Observations were used to constrain key uncertainties in the aerosol-cloud links. Advanced sensitivity tools were developed and implements to probe the drivers of cloud microphysical variability with unprecedented temporal and spatial scale. All these results have been published in top and high impact journals (or are in the final stages of publication). This proposal has also supported a number of outstanding graduate students.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC53F..04I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC53F..04I">Modeling global yield growth of major crops under multiple socioeconomic pathways</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Iizumi, T.; Kim, W.; Zhihong, S.; Nishimori, M. 2016-12-01 Global gridded crop models (GGCMs) are a key tool in deriving global food security scenarios under climate change. However, it is difficult for GGCMs to reproduce the reported yield growth patterns—rapid growth, yield stagnation and yield collapse. Here, we propose a set of parameterizations for GGCMs to capture the contributions to yield from technological improvements at the national and multi-decadal scales. These include country annual per capita gross domestic product (GDP)-based parameterizations for the nitrogen application rate and crop tolerance to stresses associated with high temperature, low temperature, water deficit and water excess. Using a GGCM combined with the parameterizations, we present global 140-year (1961-2100) yield growth simulations for maize, soybean, rice and wheat under multiple shared socioeconomic pathways (SSPs) and no climate change. The model reproduces the major characteristics of reported global and country yield growth patterns over the 1961-2013 period. Under the most rapid developmental pathway SSP5, the simulated global yields for 2091-2100, relative to 2001-2010, are the highest (1.21-1.82 times as high, with variations across the crops), followed by SSP1 (1.14-1.56 times as high), SSP2 (1.12-1.49 times as high), SSP4 (1.08-1.38 times as high) and SSP3 (1.08-1.36 times as high). Future country yield growth varies substantially by income level as well as by crop and by SSP. These yield pathways offer a new baseline for addressing the interdisciplinary questions related to global agricultural development, food security and climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ACP....18.7961R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ACP....18.7961R">On the representation of aerosol activation and its influence on model-derived estimates of the aerosol indirect effect</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rothenberg, Daniel; Avramov, Alexander; Wang, Chien 2018-06-01 Interactions between aerosol particles and clouds contribute a great deal of uncertainty to the scientific community's understanding of anthropogenic climate forcing. Aerosol particles serve as the nucleation sites for cloud droplets, establishing a direct linkage between anthropogenic particulate emissions and clouds in the climate system. To resolve this linkage, the community has developed parameterizations of aerosol activation which can be used in global climate models to interactively predict cloud droplet number concentrations (CDNCs). However, different activation schemes can exhibit different sensitivities to aerosol perturbations in different meteorological or pollution regimes. To assess the impact these different sensitivities have on climate forcing, we have coupled three different core activation schemes and variants with the CESM-MARC (two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC) coupled with the National Center for Atmospheric Research's (NCAR) Community Earth System Model (CESM; version 1.2)). Although the model produces a reasonable present-day CDNC climatology when compared with observations regardless of the scheme used, ΔCDNCs between the present and preindustrial era regionally increase by over 100 % in zonal mean when using the most sensitive parameterization. These differences in activation sensitivity may lead to a different evolution of the model meteorology, and ultimately to a spread of over 0.8 W m-2 in global average shortwave indirect effect (AIE) diagnosed from the model, a range which is as large as the inter-model spread from the AeroCom intercomparison. Model-derived AIE strongly scales with the simulated preindustrial CDNC burden, and those models with the greatest preindustrial CDNC tend to have the smallest AIE, regardless of their ΔCDNC. This suggests that present-day evaluations of aerosol-climate models may not provide useful constraints on the magnitude of the AIE, which will arise from differences in model estimates of the preindustrial aerosol and cloud climatology. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1094907-separate-physics-dynamics-experiment-spade-framework-determining-resolution-awareness-case-study-microphysics','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1094907-separate-physics-dynamics-experiment-spade-framework-determining-resolution-awareness-case-study-microphysics">The Separate Physics and Dynamics Experiment (SPADE) framework for determining resolution awareness: A case study of microphysics</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Gustafson, William I.; Ma, Po-Lun; Xiao, Heng 2013-08-29 The ability to use multi-resolution dynamical cores for weather and climate modeling is pushing the atmospheric community towards developing scale aware or, more specifically, resolution aware parameterizations that will function properly across a range of grid spacings. Determining the resolution dependence of specific model parameterizations is difficult due to strong resolution dependencies in many pieces of the model. This study presents the Separate Physics and Dynamics Experiment (SPADE) framework that can be used to isolate the resolution dependent behavior of specific parameterizations without conflating resolution dependencies from other portions of the model. To demonstrate the SPADE framework, the resolution dependencemore » of the Morrison microphysics from the Weather Research and Forecasting model and the Morrison-Gettelman microphysics from the Community Atmosphere Model are compared for grid spacings spanning the cloud modeling gray zone. It is shown that the Morrison scheme has stronger resolution dependence than Morrison-Gettelman, and that the ability of Morrison-Gettelman to use partial cloud fractions is not the primary reason for this difference. This study also discusses how to frame the issue of resolution dependence, the meaning of which has often been assumed, but not clearly expressed in the atmospheric modeling community. It is proposed that parameterization resolution dependence can be expressed in terms of "resolution dependence of the first type," RA1, which implies that the parameterization behavior converges towards observations with increasing resolution, or as "resolution dependence of the second type," RA2, which requires that the parameterization reproduces the same behavior across a range of grid spacings when compared at a given coarser resolution. RA2 behavior is considered the ideal, but brings with it serious implications due to limitations of parameterizations to accurately estimate reality with coarse grid spacing. The type of resolution awareness developers should target in their development depends upon the particular modeler’s application.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005JCli...18.1227M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005JCli...18.1227M">Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan 2005-04-01 The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain-Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases could only be improved by implementing spectral nudging of the large-scale (wavelength of 2500 km) dynamics in RAMS. This corrected for circulation errors produced by interactions and reflection of the internal domain dynamics with the lateral boundaries where the model was forced by the reanalysis. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017IzAOP..53..142V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017IzAOP..53..142V">Simulation of modern climate with the new version of the INM RAS climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykosov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Yakovlev, N. G. 2017-03-01 The INMCM5.0 numerical model of the Earth's climate system is presented, which is an evolution from the previous version, INMCM4.0. A higher vertical resolution for the stratosphere is applied in the atmospheric block. Also, we raised the upper boundary of the calculating area, added the aerosol block, modified parameterization of clouds and condensation, and increased the horizontal resolution in the ocean block. The program implementation of the model was also updated. We consider the simulation of the current climate using the new version of the model. Attention is focused on reducing systematic errors as compared to the previous version, reproducing phenomena that could not be simulated correctly in the previous version, and modeling the problems that remain unresolved. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active">10</li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active">11</li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B53E0229B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B53E0229B">Developing Remote Sensing Products for Monitoring and Modeling Great Lakes Coastal Wetland Vulnerability to Climate Change and Land Use</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bourgeau-Chavez, L. L.; Miller, M. E.; Battaglia, M.; Banda, E.; Endres, S.; Currie, W. S.; Elgersma, K. J.; French, N. H. F.; Goldberg, D. E.; Hyndman, D. W. 2014-12-01 Spread of invasive plant species in the coastal wetlands of the Great Lakes is degrading wetland habitat, decreasing biodiversity, and decreasing ecosystem services. An understanding of the mechanisms of invasion is crucial to gaining control of this growing threat. To better understand the effects of land use and climatic drivers on the vulnerability of coastal zones to invasion, as well as to develop an understanding of the mechanisms of invasion, research is being conducted that integrates field studies, process-based ecosystem and hydrological models, and remote sensing. Spatial data from remote sensing is needed to parameterize the hydrological model and to test the outputs of the linked models. We will present several new remote sensing products that are providing important physiological, biochemical, and landscape information to parameterize and verify models. This includes a novel hybrid radar-optical technique to delineate stands of invasives, as well as natural wetland cover types; using radar to map seasonally inundated areas not hydrologically connected; and developing new algorithms to estimate leaf area index (LAI) using Landsat. A coastal map delineating wetland types including monocultures of the invaders (Typha spp. and Phragmites austrailis) was created using satellite radar (ALOS PALSAR, 20 m resolution) and optical data (Landsat 5, 30 m resolution) fusion from multiple dates in a Random Forests classifier. These maps provide verification of the integrated model showing areas at high risk of invasion. For parameterizing the hydrological model, maps of seasonal wetness are being developed using spring (wet) imagery and differencing that with summer (dry) imagery to detect the seasonally wet areas. Finally, development of LAI remote sensing high resolution algorithms for uplands and wetlands is underway. LAI algorithms for wetlands have not been previously developed due to the difficulty of a water background. These products are being used to improve the hydrological model through higher resolution products and parameterization of variables that have previously been largely unknown. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C13B0955H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C13B0955H">Impact of Snow Grain Shape and Internal Mixing with Black Carbon Aerosol on Snow Optical Properties for use in Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> He, C.; Liou, K. N.; Takano, Y.; Yang, P.; Li, Q.; Chen, F. 2017-12-01 A set of parameterizations is developed for spectral single-scattering properties of clean and black carbon (BC)-contaminated snow based on geometric-optic surface-wave (GOS) computations, which explicitly resolves BC-snow internal mixing and various snow grain shapes. GOS calculations show that, compared with nonspherical grains, volume-equivalent snow spheres show up to 20% larger asymmetry factors and hence stronger forward scattering, particularly at wavelengths <1 mm. In contrast, snow grain sizes have a rather small impact on the asymmetry factor at wavelengths <1 mm, whereas size effects are important at longer wavelengths. The snow asymmetry factor is parameterized as a function of effective size, aspect ratio, and shape factor, and shows excellent agreement with GOS calculations. According to GOS calculations, the single-scattering coalbedo of pure snow is predominantly affected by grain sizes, rather than grain shapes, with higher values for larger grains. The snow single-scattering coalbedo is parameterized in terms of the effective size that combines shape and size effects, with an accuracy of >99%. Based on GOS calculations, BC-snow internal mixing enhances the snow single-scattering coalbedo at wavelengths <1 mm, but it does not alter the snow asymmetry factor. The BC-induced enhancement ratio of snow single-scattering coalbedo, independent of snow grain size and shape, is parameterized as a function of BC concentration with an accuracy of >99%. Overall, in addition to snow grain size, both BC-snow internal mixing and snow grain shape play critical roles in quantifying BC effects on snow optical properties. The present parameterizations can be conveniently applied to snow, land surface, and climate models including snowpack radiative transfer processes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017OcMod.113...95L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017OcMod.113...95L">Statistical models of global Langmuir mixing</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Li, Qing; Fox-Kemper, Baylor; Breivik, Øyvind; Webb, Adrean 2017-05-01 The effects of Langmuir mixing on the surface ocean mixing may be parameterized by applying an enhancement factor which depends on wave, wind, and ocean state to the turbulent velocity scale in the K-Profile Parameterization. Diagnosing the appropriate enhancement factor online in global climate simulations is readily achieved by coupling with a prognostic wave model, but with significant computational and code development expenses. In this paper, two alternatives that do not require a prognostic wave model, (i) a monthly mean enhancement factor climatology, and (ii) an approximation to the enhancement factor based on the empirical wave spectra, are explored and tested in a global climate model. Both appear to reproduce the Langmuir mixing effects as estimated using a prognostic wave model, with nearly identical and substantial improvements in the simulated mixed layer depth and intermediate water ventilation over control simulations, but significantly less computational cost. Simpler approaches, such as ignoring Langmuir mixing altogether or setting a globally constant Langmuir number, are found to be deficient. Thus, the consequences of Stokes depth and misaligned wind and waves are important. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19920004258','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19920004258">The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S. 1991-01-01 Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015OcMod..86..141B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015OcMod..86..141B">Modeling the interplay between sea ice formation and the oceanic mixed layer: Limitations of simple brine rejection parameterizations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Barthélemy, Antoine; Fichefet, Thierry; Goosse, Hugues; Madec, Gurvan 2015-02-01 The subtle interplay between sea ice formation and ocean vertical mixing is hardly represented in current large-scale models designed for climate studies. Convective mixing caused by the brine release when ice forms is likely to prevail in leads and thin ice areas, while it occurs in models at the much larger horizontal grid cell scale. Subgrid-scale parameterizations have hence been developed to mimic the effects of small-scale convection using a vertical distribution of the salt rejected by sea ice within the mixed layer, instead of releasing it in the top ocean layer. Such a brine rejection parameterization is included in the global ocean-sea ice model NEMO-LIM3. Impacts on the simulated mixed layers and ocean temperature and salinity profiles, along with feedbacks on the sea ice cover, are then investigated in both hemispheres. The changes are overall relatively weak, except for mixed layer depths, which are in general excessively reduced compared to observation-based estimates. While potential model biases prevent a definitive attribution of this vertical mixing underestimation to the brine rejection parameterization, it is unlikely that the latter can be applied in all conditions. In that case, salt rejections do not play any role in mixed layer deepening, which is unrealistic. Applying the parameterization only for low ice-ocean relative velocities improves model results, but introduces additional parameters that are not well constrained by observations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9581B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9581B">Modelling the interplay between sea ice formation and the oceanic mixed layer: limitations of simple brine rejection parameterizations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Barthélemy, Antoine; Fichefet, Thierry; Goosse, Hugues; Madec, Gurvan 2015-04-01 The subtle interplay between sea ice formation and ocean vertical mixing is hardly represented in current large-scale models designed for climate studies. Convective mixing caused by the brine release when ice forms is likely to prevail in leads and thin ice areas, while it occurs in models at the much larger horizontal grid cell scale. Subgrid-scale parameterizations have hence been developed to mimic the effects of small-scale convection using a vertical distribution of the salt rejected by sea ice within the mixed layer, instead of releasing it in the top ocean layer. Such a brine rejection parameterization is included in the global ocean--sea ice model NEMO-LIM3. Impacts on the simulated mixed layers and ocean temperature and salinity profiles, along with feedbacks on the sea ice cover, are then investigated in both hemispheres. The changes are overall relatively weak, except for mixed layer depths, which are in general excessively reduced compared to observation-based estimates. While potential model biases prevent a definitive attribution of this vertical mixing underestimation to the brine rejection parameterization, it is unlikely that the latter can be applied in all conditions. In that case, salt rejections do not play any role in mixed layer deepening, which is unrealistic. Applying the parameterization only for low ice--ocean relative velocities improves model results, but introduces additional parameters that are not well constrained by observations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020081016&hterms=cloud+computing&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dcloud%2Bcomputing','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020081016&hterms=cloud+computing&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dcloud%2Bcomputing">Parameterization of Shortwave Cloud Optical Properties for a Mixture of Ice Particle Habits for use in Atmospheric Models</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Chou, Ming-Dah; Lee, Kyu-Tae; Yang, Ping; Lau, William K. M. (Technical Monitor) 2002-01-01 Based on the single-scattering optical properties pre-computed with an improved geometric optics method, the bulk absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the effective particle size of a mixture of ice habits, the ice water amount, and spectral band. The parameterization has been applied to computing fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. It is found that flux calculations are not overly sensitive to the assumed particle habits if the definition of the effective particle size is consistent with the particle habits that the parameterization is based. Otherwise, the error in the flux calculations could reach a magnitude unacceptable for climate studies. Different from many previous studies, the parameterization requires only an effective particle size representing all ice habits in a cloud layer, but not the effective size of individual ice habits. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GBioC..32..565B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GBioC..32..565B">Dynamic Biological Functioning Important for Simulating and Stabilizing Ocean Biogeochemistry</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Buchanan, P. J.; Matear, R. J.; Chase, Z.; Phipps, S. J.; Bindoff, N. L. 2018-04-01 The biogeochemistry of the ocean exerts a strong influence on the climate by modulating atmospheric greenhouse gases. In turn, ocean biogeochemistry depends on numerous physical and biological processes that change over space and time. Accurately simulating these processes is fundamental for accurately simulating the ocean's role within the climate. However, our simulation of these processes is often simplistic, despite a growing understanding of underlying biological dynamics. Here we explore how new parameterizations of biological processes affect simulated biogeochemical properties in a global ocean model. We combine 6 different physical realizations with 6 different biogeochemical parameterizations (36 unique ocean states). The biogeochemical parameterizations, all previously published, aim to more accurately represent the response of ocean biology to changing physical conditions. We make three major findings. First, oxygen, carbon, alkalinity, and phosphate fields are more sensitive to changes in the ocean's physical state. Only nitrate is more sensitive to changes in biological processes, and we suggest that assessment protocols for ocean biogeochemical models formally include the marine nitrogen cycle to assess their performance. Second, we show that dynamic variations in the production, remineralization, and stoichiometry of organic matter in response to changing environmental conditions benefit the simulation of ocean biogeochemistry. Third, dynamic biological functioning reduces the sensitivity of biogeochemical properties to physical change. Carbon and nitrogen inventories were 50% and 20% less sensitive to physical changes, respectively, in simulations that incorporated dynamic biological functioning. These results highlight the importance of a dynamic biology for ocean properties and climate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JAMES...9.1721G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JAMES...9.1721G">Implementation and calibration of a stochastic multicloud convective parameterization in the NCEP Climate Forecast System (CFSv2)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Goswami, B. B.; Khouider, B.; Phani, R.; Mukhopadhyay, P.; Majda, A. J. 2017-07-01 A comparative analysis of fourteen 5 year long climate simulations produced by the National Centers for Environmental Predictions (NCEP) Climate Forecast System version 2 (CFSv2), in which a stochastic multicloud (SMCM) cumulus parameterization is implemented, is presented here. These 5 year runs are made with different sets of parameters in order to figure out the best model configuration based on a suite of state-of-the-art metrics. This analysis is also a systematic attempt to understand the model sensitivity to the SMCM parameters. The model is found to be resilient to minor changes in the parameters used implying robustness of the SMCM formulation. The model is found to be most sensitive to the midtropospheric dryness parameter (MTD) and to the stratiform cloud decay timescale (τ30). MTD is more effective in controlling the global mean precipitation and its distribution while τ30 has more effect on the organization of convection as noticed in the simulation of the Madden-Julian oscillation (MJO). This is consistent with the fact that in the SMCM formulation, midtropospheric humidity controls the deepening of convection and stratiform clouds control the backward tilt of tropospheric heating and the strength of unsaturated downdrafts which cool and dry the boundary layer and trigger the propagation of organized convection. Many other studies have also found midtropospheric humidity to be a key factor in the capacity of a global climate model to simulate organized convection on the synoptic and intraseasonal scales. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110013131','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110013131">Evaluation of Convective Transport in the GEOS-5 Chemistry and Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Pickering, Kenneth E.; Ott, Lesley E.; Shi, Jainn J.; Tao. Wei-Kuo; Mari, Celine; Schlager, Hans 2011-01-01 The NASA Goddard Earth Observing System (GEOS-5) Chemistry and Climate Model (CCM) consists of a global atmospheric general circulation model and the combined stratospheric and tropospheric chemistry package from the NASA Global Modeling Initiative (GMI) chemical transport model. The subgrid process of convective tracer transport is represented through the Relaxed Arakawa-Schubert parameterization in the GEOS-5 CCM. However, substantial uncertainty for tracer transport is associated with this parameterization, as is the case with all global and regional models. We have designed a project to comprehensively evaluate this parameterization from the point of view of tracer transport, and determine the most appropriate improvements that can be made to the GEOS-5 convection algorithm, allowing improvement in our understanding of the role of convective processes in determining atmospheric composition. We first simulate tracer transport in individual observed convective events with a cloud-resolving model (WRF). Initial condition tracer profiles (CO, CO2, O3) are constructed from aircraft data collected in undisturbed air, and the simulations are evaluated using aircraft data taken in the convective anvils. A single-column (SCM) version of the GEOS-5 GCM with online tracers is then run for the same convective events. SCM output is evaluated based on averaged tracer fields from the cloud-resolving model. Sensitivity simulations with adjusted parameters will be run in the SCM to determine improvements in the representation of convective transport. The focus of the work to date is on tropical continental convective events from the African Monsoon Multidisciplinary Analyses (AMMA) field mission in August 2006 that were extensively sampled by multiple research aircraft. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3761614','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3761614">Enhanced basal lubrication and the contribution of the Greenland ice sheet to future sea-level rise</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Shannon, Sarah R.; Payne, Antony J.; Bartholomew, Ian D.; van den Broeke, Michiel R.; Edwards, Tamsin L.; Fettweis, Xavier; Gagliardini, Olivier; Gillet-Chaulet, Fabien; Goelzer, Heiko; Hoffman, Matthew J.; Huybrechts, Philippe; Mair, Douglas W. F.; Nienow, Peter W.; Perego, Mauro; Price, Stephen F.; Smeets, C. J. P. Paul; Sole, Andrew J.; van de Wal, Roderik S. W.; Zwinger, Thomas 2013-01-01 We assess the effect of enhanced basal sliding on the flow and mass budget of the Greenland ice sheet, using a newly developed parameterization of the relation between meltwater runoff and ice flow. A wide range of observations suggest that water generated by melt at the surface of the ice sheet reaches its bed by both fracture and drainage through moulins. Once at the bed, this water is likely to affect lubrication, although current observations are insufficient to determine whether changes in subglacial hydraulics will limit the potential for the speedup of flow. An uncertainty analysis based on our best-fit parameterization admits both possibilities: continuously increasing or bounded lubrication. We apply the parameterization to four higher-order ice-sheet models in a series of experiments forced by changes in both lubrication and surface mass budget and determine the additional mass loss brought about by lubrication in comparison with experiments forced only by changes in surface mass balance. We use forcing from a regional climate model, itself forced by output from the European Centre Hamburg Model (ECHAM5) global climate model run under scenario A1B. Although changes in lubrication generate widespread effects on the flow and form of the ice sheet, they do not affect substantial net mass loss; increase in the ice sheet’s contribution to sea-level rise from basal lubrication is projected by all models to be no more than 5% of the contribution from surface mass budget forcing alone. PMID:23940337 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23940337','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23940337">Enhanced basal lubrication and the contribution of the Greenland ice sheet to future sea-level rise.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Shannon, Sarah R; Payne, Antony J; Bartholomew, Ian D; van den Broeke, Michiel R; Edwards, Tamsin L; Fettweis, Xavier; Gagliardini, Olivier; Gillet-Chaulet, Fabien; Goelzer, Heiko; Hoffman, Matthew J; Huybrechts, Philippe; Mair, Douglas W F; Nienow, Peter W; Perego, Mauro; Price, Stephen F; Smeets, C J P Paul; Sole, Andrew J; van de Wal, Roderik S W; Zwinger, Thomas 2013-08-27 We assess the effect of enhanced basal sliding on the flow and mass budget of the Greenland ice sheet, using a newly developed parameterization of the relation between meltwater runoff and ice flow. A wide range of observations suggest that water generated by melt at the surface of the ice sheet reaches its bed by both fracture and drainage through moulins. Once at the bed, this water is likely to affect lubrication, although current observations are insufficient to determine whether changes in subglacial hydraulics will limit the potential for the speedup of flow. An uncertainty analysis based on our best-fit parameterization admits both possibilities: continuously increasing or bounded lubrication. We apply the parameterization to four higher-order ice-sheet models in a series of experiments forced by changes in both lubrication and surface mass budget and determine the additional mass loss brought about by lubrication in comparison with experiments forced only by changes in surface mass balance. We use forcing from a regional climate model, itself forced by output from the European Centre Hamburg Model (ECHAM5) global climate model run under scenario A1B. Although changes in lubrication generate widespread effects on the flow and form of the ice sheet, they do not affect substantial net mass loss; increase in the ice sheet's contribution to sea-level rise from basal lubrication is projected by all models to be no more than 5% of the contribution from surface mass budget forcing alone. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A11E0098S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A11E0098S">Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Simmer, C. 2015-12-01 An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1377781-cosp-satellite-simulation-software-model-assessment','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1377781-cosp-satellite-simulation-software-model-assessment">COSP: Satellite simulation software for model assessment</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Bodas-Salcedo, A.; Webb, M. J.; Bony, S.; ... 2011-08-01 Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibilitymore » of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This thus permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. Here we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100033542','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100033542">Characterization of Cloud Water-Content Distribution</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Lee, Seungwon 2010-01-01 The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19790049850&hterms=Free+energy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DFree%2Benergy','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19790049850&hterms=Free+energy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DFree%2Benergy">An energy-balance model with multiply-periodic and quasi-chaotic free oscillations. [for climate forecasting</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Bhattacharya, K.; Ghil, M. 1979-01-01 A slightly modified version of the one-dimensional time-dependent energy-balance climate model of Ghil and Bhattacharya (1978) is presented. The albedo-temperature parameterization has been reformulated and the smoothing of the temperature distribution in the tropics has been eliminated. The model albedo depends on time-lagged temperature in order to account for finite growth and decay time of continental ice sheets. Two distinct regimes of oscillatory behavior which depend on the value of the albedo-temperature time lag are considered. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AtmRe.197....1T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AtmRe.197....1T">Global precipitation measurements for validating climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tapiador, F. J.; Navarro, A.; Levizzani, V.; García-Ortega, E.; Huffman, G. J.; Kidd, C.; Kucera, P. A.; Kummerow, C. D.; Masunaga, H.; Petersen, W. A.; Roca, R.; Sánchez, J.-L.; Tao, W.-K.; Turk, F. J. 2017-11-01 The advent of global precipitation data sets with increasing temporal span has made it possible to use them for validating climate models. In order to fulfill the requirement of global coverage, existing products integrate satellite-derived retrievals from many sensors with direct ground observations (gauges, disdrometers, radars), which are used as reference for the satellites. While the resulting product can be deemed as the best-available source of quality validation data, awareness of the limitations of such data sets is important to avoid extracting wrong or unsubstantiated conclusions when assessing climate model abilities. This paper provides guidance on the use of precipitation data sets for climate research, including model validation and verification for improving physical parameterizations. The strengths and limitations of the data sets for climate modeling applications are presented, and a protocol for quality assurance of both observational databases and models is discussed. The paper helps elaborating the recent IPCC AR5 acknowledgment of large observational uncertainties in precipitation observations for climate model validation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1169523','SCIGOV-DOEDE'); return false;" href="https://www.osti.gov/servlets/purl/1169523">CCPP-ARM Parameterization Testbed Model Forecast Data</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/dataexplorer">DOE Data Explorer</a> Klein, Stephen 2008-01-15 Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/940966','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/940966">Final Technical Report for Project "Improving the Simulation of Arctic Clouds in CCSM3"</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Stephen J. Vavrus 2008-11-15 This project has focused on the simulation of Arctic clouds in CCSM3 and how the modeled cloud amount (and climate) can be improved substantially by altering the parameterized low cloud fraction. The new formula, dubbed 'freeezedry', alleviates the bias of excessive low clouds during polar winter by reducing the cloud amount under very dry conditions. During winter, freezedry decreases the low cloud amount over the coldest regions in high latitudes by over 50% locally and more than 30% averaged across the Arctic (Fig. 1). The cloud reduction causes an Arctic-wide drop of 15 W m{sup -2} in surface cloud radiativemore » forcing (CRF) during winter and about a 50% decrease in mean annual Arctic CRF. Consequently, wintertime surface temperatures fall by up to 4 K on land and 2-8 K over the Arctic Ocean, thus significantly reducing the model's pronounced warm bias (Fig. 1). While improving the polar climate simulation in CCSM3, freezedry has virtually no influence outside of very cold regions (Fig. 2) or during summer (Fig. 3), which are space and time domains that were not targeted. Furthermore, the simplicity of this parameterization allows it to be readily incorporated into other GCMs, many of which also suffer from excessive wintertime polar cloudiness, based on the results from the CMIP3 archive (Vavrus et al., 2008). Freezedry also affects CCSM3's sensitivity to greenhouse forcing. In a transient-CO{sub 2} experiment, the model version with freezedry warms up to 20% less in the North Polar and South Polar regions (1.5 K and 0.5 K smaller warming, respectively) (Fig. 4). Paradoxically, the muted high-latitude response occurs despite a much larger increase in cloud amount with freezedry during non-summer months (when clouds warm the surface), apparently because of the colder modern reference climate. These results of the freezedry parameterization have recently been published (Vavrus and D. Waliser, 2008: An improved parameterization for simulating Arctic cloud amount in the CCSM3 climate model. J. Climate, 21, 5673-5687.). The article also provides a novel synthesis of surface- and satellite-based Arctic cloud observations that show how much the new freezedry parameterization improves the simulated cloud amount in high latitudes (Fig. 3). Freezedry has been incorporated into the CCSM3.5 version, in which it successfully limits the excessive polar clouds, and may be used in CCSM4. Material from this work is also appearing in a synthesis article on future Arctic cloud changes (Vavrus, D. Waliser, J. Francis, and A. Schweiger, 'Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4', accepted in Climate Dynamics) and was used in a collaborative paper on Arctic cloud-sea ice coupling (Schweiger, A., R. Lindsay, S. Vavrus, and J. Francis, 2008: Relationships between Arctic sea ice and clouds during autumn. J. Climate, 21, 4799-4810.). This research was presented at the 2007 CCSM Annual Workshop, as well as the CCSM's 2007 Atmospheric Model Working Group and Polar Working Group Meetings. The findings were also shown at the 2007 Climate Change Prediction Program's Science Team Meeting. In addition, I served as an instructor at the International Arctic Research Center's (IARC) Summer School on Arctic Climate Modeling in Fairbanks this summer, where I presented on the challenges and techniques used in simulating polar clouds. I also contributed to the development of a new Arctic System Model by attending a workshop in Colorado this summer on this fledgling project. Finally, an outreach activity for the general public has been the development of an interactive web site (<http://ccr.aos.wisc.edu/model/visualization/ipcc/>) that displays Arctic cloud amount in the CMIP3 climate model archive under present and future scenarios. This site allows users to make polar and global maps of a variety of climate variables to investigate the individual and ensemble-mean GCM response to greenhouse warming and the extent to which models adequately represent Arctic clouds in the modern climate. This site was used extensively in the IARC summer school projects. This work has also led to a collaboration this year during a 4-month visit I made to NCAR through its Faculty Fellowship Program. I worked with scientists Marika Holland, David Bailey, Andrew Gettleman, and Jen Kay, who are researching polar climate and/or clouds. I met with this group frequently during my visit, leading to some fruitful interactions. This work led to the discovery of a tightly coupled response of clouds and sea ice during intervals of rapid sea ice loss in greenhouse simulations, as well as advising on the evolving CCSM3.5 to CCSM4 model development. This involvement with NCAR also led to a longer-term connection, as I have recently begun a two-year stint on the SSC for CCSM.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A14F..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A14F..01S">High-resolution RCMs as pioneers for future GCMs</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Schar, C.; Ban, N.; Arteaga, A.; Charpilloz, C.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Leutwyler, D.; Lüthi, D.; Piaget, N.; Ruedisuehli, S.; Schlemmer, L.; Schulthess, T. C.; Wernli, H. 2017-12-01 Currently large efforts are underway to refine the horizontal resolution of global and regional climate models to O(1 km), with the intent to represent convective clouds explicitly rather than using semi-empirical parameterizations. This refinement will move the governing equations closer to first principles and is expected to reduce the uncertainties of climate models. High resolution is particularly attractive in order to better represent critical cloud feedback processes (e.g. related to global climate sensitivity and extratropical summer convection) and extreme events (such as heavy precipitation events, floods, and hurricanes). The presentation will be illustrated using decade-long simulations at 2 km horizontal grid spacing, some of these covering the European continent on a computational mesh with 1536x1536x60 grid points. To accomplish such simulations, use is made of emerging heterogeneous supercomputing architectures, using a version of the COSMO limited-area weather and climate model that is able to run entirely on GPUs. Results show that kilometer-scale resolution dramatically improves the simulation of precipitation in terms of the diurnal cycle and short-term extremes. The modeling framework is used to address changes of precipitation scaling with climate change. It is argued that already today, modern supercomputers would in principle enable global atmospheric convection-resolving climate simulations, provided appropriately refactored codes were available, and provided solutions were found to cope with the rapidly growing output volume. A discussion will be provided of key challenges affecting the design of future high-resolution climate models. It is suggested that km-scale RCMs should be exploited to pioneer this terrain, at a time when GCMs are not yet available at such resolutions. Areas of interest include the development of new parameterization schemes adequate for km-scale resolution, the exploration of new validation methodologies and data sets, the assessment of regional-scale climate feedback processes, and the development of alternative output analysis methodologies. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active">11</li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active">12</li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910031763&hterms=climate+facts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dclimate%2Bfacts','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910031763&hterms=climate+facts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dclimate%2Bfacts">On the limitations of General Circulation Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Stone, Peter H.; Risbey, James S. 1990-01-01 General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918834H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918834H">An inter-model comparison of urban canopy effects on climate</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Halenka, Tomas; Karlicky, Jan; Huszar, Peter; Belda, Michal; Bardachova, Tatsiana 2017-04-01 The role of cities is increasing and will continue to increase in future, as the population within the urban areas is growing faster, with the estimate for Europe of about 84% living in urban areas in about mid of 21st century. To assess the impact of cities and, in general, urban surfaces on climate, using of modeling approach is well appropriate. Moreover, with higher resolution, urban areas becomes to be better resolved in the regional models and their relatively significant impacts should not be neglected. Model descriptions of urban canopy related meteorological effects can, however, differ largely given the odds in the driving models, the underlying surface models and the urban canopy parameterizations, representing a certain uncertainty. In this study we try to contribute to the estimation of this uncertainty by performing numerous experiments to assess the urban canopy meteorological forcing over central Europe on climate for the decade 2001-2010, using two driving models (RegCM4 and WRF) in 10 km resolution driven by ERA-Interim reanalyses, three surface schemes (BATS and CLM4.5 for RegCM4 and Noah for WRF) and five urban canopy parameterizations available: one bulk urban scheme, three single layer and a multilayer urban scheme. Actually, in RegCM4 we used our implementation of the Single Layer Urban Canopy Model (SLUCM) in BATS scheme and CLM4.5 option with urban parameterization based on SLUCM concept as well, in WRF we used all the three options, i.e. bulk, SLUCM and more complex and sophisticated Building Environment Parameterization (BEP) connected with Building Energy Model (BEM). As a reference simulations, runs with no urban areas and with no urban parameterizations were performed. Effects of cities on urban and rural areas were evaluated. Effect of reducing diurnal temperature range in cities (around 2 °C in summer) is noticeable in all simulation, independent to urban parameterization type and model. Also well-known warmer summer city nights appear in all simulations. Further, winter boundary layer increase by 100-200 m, together with wind reduction, is visible in all simulations. The spatial distribution of the night-time temperature response of models to urban canopy forcing is rather similar in each set-up, showing temperature increases up to 3°C in summer. In general, much lower increase are modeled for day-time conditions, which can be even slightly negative due to dominance of shadowing in urban canyons, especially in the morning hours. The winter temperature response, driven mainly by anthropogenic heat (AH) is strong in urban schemes where the building-street energy exchange is more resolved and is smaller, where AH is simply prescribed as additive flux to the sensible heat. Somewhat larger differences between the models are encountered for the response of wind and the height of planetary boundary layer (ZPBL), with dominant increases from a few 10 m up to 250 m depending on the model. The comparison of observation of diurnal temperature amplitude from ECAD data with model results and hourly data from Prague with model hourly values show improvement when urban effects are considered. Larger spread encountered for wind and turbulence (as ZPBL) should be considered when choices of urban canopy schemes are made, especially in connection with modeling transport of pollutants within/from cities. Another conclusion is that choosing more complex urban schemes does not necessary improves model performance and using simpler and computationally less demanding (e.g. single layer) urban schemes, is often sufficient. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..4312520F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..4312520F">Effect of a sheared flow on iceberg motion and melting</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> FitzMaurice, A.; Straneo, F.; Cenedese, C.; Andres, M. 2016-12-01 Icebergs account for approximately half the freshwater flux into the ocean from the Greenland and Antarctic ice sheets and play a major role in the distribution of meltwater into the ocean. Global climate models distribute this freshwater by parameterizing iceberg motion and melt, but these parameterizations are presently informed by limited observations. Here we present a record of speed and draft for 90 icebergs from Sermilik Fjord, southeastern Greenland, collected in conjunction with wind and ocean velocity data over an 8 month period. It is shown that icebergs subject to strongly sheared flows predominantly move with the vertical average of the ocean currents. If, as typical in iceberg parameterizations, only the surface ocean velocity is taken into account, iceberg speed and basal melt may have errors in excess of 60%. These results emphasize the need for parameterizations to consider ocean properties over the entire iceberg draft. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160013898&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsoil','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160013898&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsoil">Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Rasool, Quazi Z.; Zhang, Rui; Lash, Benjamin; Cohan, Daniel S.; Cooter, Ellen J.; Bash, Jesse O.; Lamsal, Lok N. 2016-01-01 Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A13J3309T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A13J3309T">An Eddy-Diffusivity Mass-flux (EDMF) closure for the unified representation of cloud and convective processes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tan, Z.; Schneider, T.; Teixeira, J.; Lam, R.; Pressel, K. G. 2014-12-01 Sub-grid scale (SGS) closures in current climate models are usually decomposed into several largely independent parameterization schemes for different cloud and convective processes, such as boundary layer turbulence, shallow convection, and deep convection. These separate parameterizations usually do not converge as the resolution is increased or as physical limits are taken. This makes it difficult to represent the interactions and smooth transition among different cloud and convective regimes. Here we present an eddy-diffusivity mass-flux (EDMF) closure that represents all sub-grid scale turbulent, convective, and cloud processes in a unified parameterization scheme. The buoyant updrafts and precipitative downdrafts are parameterized with a prognostic multiple-plume mass-flux (MF) scheme. The prognostic term for the mass flux is kept so that the life cycles of convective plumes are better represented. The interaction between updrafts and downdrafts are parameterized with the buoyancy-sorting model. The turbulent mixing outside plumes is represented by eddy diffusion, in which eddy diffusivity (ED) is determined from a turbulent kinetic energy (TKE) calculated from a TKE balance that couples the environment with updrafts and downdrafts. Similarly, tracer variances are decomposed consistently between updrafts, downdrafts and the environment. The closure is internally coupled with a probabilistic cloud scheme and a simple precipitation scheme. We have also developed a relatively simple two-stream radiative scheme that includes the longwave (LW) and shortwave (SW) effects of clouds, and the LW effect of water vapor. We have tested this closure in a single-column model for various regimes spanning stratocumulus, shallow cumulus, and deep convection. The model is also run towards statistical equilibrium with climatologically relevant large-scale forcings. These model tests are validated against large-eddy simulation (LES) with the same forcings. The comparison of results verifies the capacity of this closure to realistically represent different cloud and convective processes. Implementation of the closure in an idealized GCM allows us to study cloud feedbacks to climate change and to study the interactions between clouds, convections, and the large-scale circulation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9092R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9092R">Carbon fluxes in tropical forest ecosystems: the value of Eddy-covariance data for individual-based dynamic forest gap models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Roedig, Edna; Cuntz, Matthias; Huth, Andreas 2015-04-01 The effects of climatic inter-annual fluctuations and human activities on the global carbon cycle are uncertain and currently a major issue in global vegetation models. Individual-based forest gap models, on the other hand, model vegetation structure and dynamics on a small spatial (<100 ha) and large temporal scale (>1000 years). They are well-established tools to reproduce successions of highly-diverse forest ecosystems and investigate disturbances as logging or fire events. However, the parameterizations of the relationships between short-term climate variability and forest model processes are often uncertain in these models (e.g. daily variable temperature and gross primary production (GPP)) and cannot be constrained from forest inventories. We addressed this uncertainty and linked high-resolution Eddy-covariance (EC) data with an individual-based forest gap model. The forest model FORMIND was applied to three diverse tropical forest sites in the Amazonian rainforest. Species diversity was categorized into three plant functional types. The parametrizations for the steady-state of biomass and forest structure were calibrated and validated with different forest inventories. The parameterizations of relationships between short-term climate variability and forest model processes were evaluated with EC-data on a daily time step. The validations of the steady-state showed that the forest model could reproduce biomass and forest structures from forest inventories. The daily estimations of carbon fluxes showed that the forest model reproduces GPP as observed by the EC-method. Daily fluctuations of GPP were clearly reflected as a response to daily climate variability. Ecosystem respiration remains a challenge on a daily time step due to a simplified soil respiration approach. In the long-term, however, the dynamic forest model is expected to estimate carbon budgets for highly-diverse tropical forests where EC-measurements are rare. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B21I..08M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B21I..08M">PyrE, an interactive fire module within the NASA-GISS Earth System Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mezuman, K.; Bauer, S. E.; Tsigaridis, K. 2017-12-01 Fires directly affect the composition of the atmosphere and Earth's radiation balance by emitting a suite of reactive gases and particles. Having an interactive fire module in an Earth System Model allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of biomass burning in different time periods. To do so we have developed PyrE, the NASA-GISS interactive fire emissions model. PyrE uses the flammability, ignition, and suppression parameterization proposed by Pechony and Shindell (2009), and is coupled to a burned area and surface recovery parameterization. The burned area calculation follows CLM's approach (Li et al., 2012), paired with an offline recovery scheme based on Ent's Terrestrial Biosphere Model (Ent TBM) carbon pool turnover time. PyrE is driven by environmental variables calculated by climate simulations, population density data, MODIS fire counts and LAI retrievals, as well as GFED4s emissions. Since the model development required extensive use of reference datasets, in addition to comparing it to GFED4s BA, we evaluate it by studying the effect of fires on atmospheric composition and climate. Our results show good agreement globally, with some regional differences. Finally, we quantify the present day fire radiative forcing. The development of PyrE allowed us for the first time to interactively simulate climate and fire activity with GISS-ModelE3 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H24F..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H24F..04S">Estimating the relative contributions of human withdrawals and climate variability to changes in groundwater</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Swenson, S. C.; Lawrence, D. M. 2014-12-01 Estimating the relative contributions of human withdrawals and climate variability to changes in groundwater is a challenging task at present. One method that has been used recently is a model-data synthesis combining GRACE total water storage estimates with simulated water storage estimates from land surface models. In this method, water storage changes due to natural climate variations simulated by a model are removed from total water storage changes observed by GRACE; the residual is then interpreted as anthropogenic groundwater change. If the modeled water storage estimate contains systematic errors, these errors will also be present in the residual groundwater estimate. For example, simulations performed with the Community Land Model (CLM; the land component of the Community Earth System Model) generally show a weak (as much as 50% smaller) seasonal cycle of water storage in semi-arid regions when compared to GRACE satellite water storage estimates. This bias propagates into GRACE-CLM anthropogenic groundwater change estimates, which then exhibit unphysical seasonal variability. The CLM bias can be traced to the parameterization of soil evaporative resistance. Incorporating a new soil resistance parameterization in CLM greatly reduces the seasonal bias with respect to GRACE. In this study, we compare the improved CLM water storage estimates to GRACE and discuss the implications for estimates of anthropogenic groundwater withdrawal, showing examples for the Middle East and Southwestern United States. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=302542','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=302542">Evaluation of CSM-CROPGRO-Cotton for simulating effects of management and climate change on cotton growth and evapotranspiration in an arid environment</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Originally developed for simulating soybean growth and development, the CROPGRO model was recently re-parameterized for cotton. However, further efforts are necessary to evaluate the model's performance against field measurements for new environments and management options. The objective of this stu... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19910018381','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19910018381">Atmospheric water vapor transport: Estimation of continental precipitation recycling and parameterization of a simple climate model. M.S. Thesis</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Brubaker, Kaye L.; Entekhabi, Dara; Eagleson, Peter S. 1991-01-01 The advective transport of atmospheric water vapor and its role in global hydrology and the water balance of continental regions are discussed and explored. The data set consists of ten years of global wind and humidity observations interpolated onto a regular grid by objective analysis. Atmospheric water vapor fluxes across the boundaries of selected continental regions are displayed graphically. The water vapor flux data are used to investigate the sources of continental precipitation. The total amount of water that precipitates on large continental regions is supplied by two mechanisms: (1) advection from surrounding areas external to the region; and (2) evaporation and transpiration from the land surface recycling of precipitation over the continental area. The degree to which regional precipitation is supplied by recycled moisture is a potentially significant climate feedback mechanism and land surface-atmosphere interaction, which may contribute to the persistence and intensification of droughts. A simplified model of the atmospheric moisture over continents and simultaneous estimates of regional precipitation are employed to estimate, for several large continental regions, the fraction of precipitation that is locally derived. In a separate, but related, study estimates of ocean to land water vapor transport are used to parameterize an existing simple climate model, containing both land and ocean surfaces, that is intended to mimic the dynamics of continental climates. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A23D2378M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A23D2378M">Improving the Representation of Mediterranean Heavy Precipitating Events over Land in a Regional Climate System Model.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mazoyer, M.; Roehrig, R.; Nuissier, O.; Duffourg, F.; Somot, S. 2017-12-01 Most regional climate models (RCSMs) face difficulties in representing a reasonable pre-cipitation probability density function in the Mediterranean area and especially over land.Small amounts of rain are too frequent, preventing any realistic representation of droughts orheat waves, while the intensity of heavy precipitating events is underestimated and not welllocated by most state-of-the-art RCSMs using parameterized convection (resolution from10 to 50 km). Convective parameterization is a key point for the representation of suchevents and recently, the new physics implemented in the CNRM-RCSM has been shown toremarkably improve it, even at a 50-km scale.The present study seeks to further analyse the representation of heavy precipitating eventsby this new version of CNRM-RCSM using a process oriented approach. We focus on oneparticular event in the south-east of France, over the Cévennes. Two hindcast experimentswith the CNRM-RCSM (12 and 50 km) are performed and compared with a simulationbased on the convection-permitting model Meso-NH, which makes use of a very similarsetup as CNRM-RCSM hindcasts. The role of small-scale features of the regional topogra-phy and its interaction with the impinging large-scale flow in triggering the convective eventare investigated. This study provides guidance in the ongoing implementation and use of aspecific parameterization dedicated to account for subgrid-scale orography in the triggeringand closure conditions of the CNRM-RCSM convection scheme. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A41E2339L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A41E2339L">Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y. 2017-12-01 The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks, RNVCF shows significant overestimation in summer, perhaps due to RNVCF ignores the growing characteristics of vegetation (mainly grass) in these two regions. Our results demonstrate that VCF schemes have significant influence on LSM performance, and indicate that it is important to consider vegetation growing characteristics in VCF schemes for different LCs. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017APS..DFDF32009M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017APS..DFDF32009M">On the use of infrasound for constraining global climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Millet, Christophe; Ribstein, Bruno; Lott, Francois; Cugnet, David 2017-11-01 Numerical prediction of infrasound is a complex issue due to constantly changing atmospheric conditions and to the random nature of small-scale flows. Although part of the upward propagating wave is refracted at stratospheric levels, where gravity waves significantly affect the temperature and the wind, yet the process by which the gravity wave field changes the infrasound arrivals remains poorly understood. In the present work, we use a stochastic parameterization to represent the subgrid scale gravity wave field from the atmospheric specifications provided by the European Centre for Medium-Range Weather Forecasts. It is shown that regardless of whether the gravity wave field possesses relatively small or large features, the sensitivity of acoustic waveforms to atmospheric disturbances can be extremely different. Using infrasound signals recorded during campaigns of ammunition destruction explosions, a new set of tunable parameters is proposed which more accurately predicts the small-scale content of gravity wave fields in the middle atmosphere. Climate simulations are performed using the updated parameterization. Numerical results demonstrate that a network of ground-based infrasound stations is a promising technology for dynamically tuning the gravity wave parameterization. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/442361-description-ncar-community-climate-model-ccm3-technical-note','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/442361-description-ncar-community-climate-model-ccm3-technical-note">Description of the NCAR Community Climate Model (CCM3). Technical note</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Kiehl, J.T.; Hack, J.J.; Bonan, G.B. This repor presents the details of the governing equations, physical parameterizations, and numerical algorithms defining the version of the NCAR Community Climate Model designated CCM3. The material provides an overview of the major model components, and the way in which they interact as the numerical integration proceeds. This version of the CCM incorporates significant improvements to the physic package, new capabilities such as the incorporation of a slab ocean component, and a number of enhancements to the implementation (e.g., the ability to integrate the model on parallel distributed-memory computational platforms). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMGC53A0700P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMGC53A0700P">Northern African and Indian Precipitation at the end of the 21st Century: An Integrated Application of Regional and Global Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Patricola, C. M.; Cook, K. H. 2008-12-01 As greenhouse warming continues there is growing concern about the future climate of both Africa, which is highlighted by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) as exceptionally vulnerable to climate change, and India. Precipitation projections from the AOGCMs of the IPCC AR4 are relatively consistent over India, but not over northern Africa. Inconsistencies can be related to the model's inability to capture climate process correctly, deficiencies in physical parameterizations, different SST projections, or horizontal atmospheric resolution that is too coarse to realistically represent the tight gradients over West Africa and complex topography of East Africa and India. Treatment of the land surface in a model may also be an issue over West Africa and India where land-surface/atmosphere interactions are very important. Here a method for simulating future climate is developed and applied using a high-resolution regional model in conjunction with output from a suite of AOGCMs, drawing on the advantages of both the regional and global modeling approaches. Integration by the regional model allows for finer horizontal resolution and regionally appropriate selection of parameterizations and land-surface model. AOGCM output is used to provide SST projections and lateral boundary conditions to constrain the regional model. The control simulation corresponds to 1981-2000, and eight future simulations representing 2081-2100 are conducted, each constrained by a different AOGCM and forced by CO2 concentrations from the SRES A2 emissions scenario. After model spin-up, May through October remain for investigation. Analysis is focused on climate change parameters important for impacts on agriculture and water resource management, and is presented in a format compatible with the IPCC reports. Precipitation projections simulated by the regional model are quite consistent, with 75% or more ensemble members agreeing on the sign of the anomaly over vast regions of Africa and India. Over West Africa, where the regional model provides the greatest improvement over the AOGCMs in consistency of ensemble members, precipitation at the end of the century is generally projected to increase during May and decrease in June and July. Wetter conditions are simulated during August though October, with the exception of drying close to the Guinean Coast in August. In late summer, high rainfall rates are simulated more frequently in the future, indicating the possibility for increases in flooding events. The regional model's projections over India are in stark contrast to the AOGCM's, producing intense and generally widespread drying in August and September. The very promising method developed here is young and further potential developments are recognized, including the addition of ocean, vegetation, and dust models. Ensembles which employ other regional models, sets of parameterizations, and emissions scenarios should also be explored. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140000877','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140000877">Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Yao, Mao-Sung; Cheng, Ye 2013-01-01 The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5).Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A51G3117F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A51G3117F">Impact of Variable-Resolution Meshes on Regional Climate Simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fowler, L. D.; Skamarock, W. C.; Bruyere, C. L. 2014-12-01 The Model for Prediction Across Scales (MPAS) is currently being used for seasonal-scale simulations on globally-uniform and regionally-refined meshes. Our ongoing research aims at analyzing simulations of tropical convective activity and tropical cyclone development during one hurricane season over the North Atlantic Ocean, contrasting statistics obtained with a variable-resolution mesh against those obtained with a quasi-uniform mesh. Analyses focus on the spatial distribution, frequency, and intensity of convective and grid-scale precipitations, and their relative contributions to the total precipitation as a function of the horizontal scale. Multi-month simulations initialized on May 1st 2005 using ERA-Interim re-analyses indicate that MPAS performs satisfactorily as a regional climate model for different combinations of horizontal resolutions and transitions between the coarse and refined meshes. Results highlight seamless transitions for convection, cloud microphysics, radiation, and land-surface processes between the quasi-uniform and locally- refined meshes, despite the fact that the physics parameterizations were not developed for variable resolution meshes. Our goal of analyzing the performance of MPAS is twofold. First, we want to establish that MPAS can be successfully used as a regional climate model, bypassing the need for nesting and nudging techniques at the edges of the computational domain as done in traditional regional climate modeling. Second, we want to assess the performance of our convective and cloud microphysics parameterizations as the horizontal resolution varies between the lower-resolution quasi-uniform and higher-resolution locally-refined areas of the global domain. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A42D..05F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A42D..05F">Impact of Variable-Resolution Meshes on Regional Climate Simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fowler, L. D.; Skamarock, W. C.; Bruyere, C. L. 2013-12-01 The Model for Prediction Across Scales (MPAS) is currently being used for seasonal-scale simulations on globally-uniform and regionally-refined meshes. Our ongoing research aims at analyzing simulations of tropical convective activity and tropical cyclone development during one hurricane season over the North Atlantic Ocean, contrasting statistics obtained with a variable-resolution mesh against those obtained with a quasi-uniform mesh. Analyses focus on the spatial distribution, frequency, and intensity of convective and grid-scale precipitations, and their relative contributions to the total precipitation as a function of the horizontal scale. Multi-month simulations initialized on May 1st 2005 using NCEP/NCAR re-analyses indicate that MPAS performs satisfactorily as a regional climate model for different combinations of horizontal resolutions and transitions between the coarse and refined meshes. Results highlight seamless transitions for convection, cloud microphysics, radiation, and land-surface processes between the quasi-uniform and locally-refined meshes, despite the fact that the physics parameterizations were not developed for variable resolution meshes. Our goal of analyzing the performance of MPAS is twofold. First, we want to establish that MPAS can be successfully used as a regional climate model, bypassing the need for nesting and nudging techniques at the edges of the computational domain as done in traditional regional climate modeling. Second, we want to assess the performance of our convective and cloud microphysics parameterizations as the horizontal resolution varies between the lower-resolution quasi-uniform and higher-resolution locally-refined areas of the global domain. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC51B0806L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC51B0806L">Climate Impacts of Fire-Induced Land-Surface Changes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Liu, Y.; Hao, X.; Qu, J. J. 2017-12-01 One of the consequences of wildfires is the changes in land-surface properties such as removal of vegetation. This will change local and regional climate through modifying the land-air heat and water fluxes. This study investigates mechanism by developing and a parameterization of fire-induced land-surface property changes and applying it to modeling of the climate impacts of large wildfires in the United States. Satellite remote sensing was used to quantitatively evaluate the land-surface changes from large fires provided from the Monitoring Trends in Burning Severity (MTBS) dataset. It was found that the changes in land-surface properties induced by fires are very complex, depending on vegetation type and coverage, climate type, season and time after fires. The changes in LAI are remarkable only if the actual values meet a threshold. Large albedo changes occur in winter for fires in cool climate regions. The signs are opposite between the first post-fire year and the following years. Summer day-time temperature increases after fires, while nigh-time temperature changes in various patterns. The changes are larger in forested lands than shrub / grassland lands. In the parameterization scheme, the detected post-fire changes are decomposed into trends using natural exponential functions and fluctuations of periodic variations with the amplitudes also determined by natural exponential functions. The final algorithm is a combination of the trends, periods, and amplitude functions. This scheme is used with Earth system models to simulate the local and regional climate effects of wildfires. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A23E0364B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A23E0364B">Dynamical Downscaling of Global Circulation Models With the Weather Research and Forecast Model in the Northern Great Plains</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Burtch, D.; Mullendore, G. L.; Kennedy, A. D.; Simms, M.; Kirilenko, A.; Coburn, J. 2015-12-01 Understanding the impacts of global climate change on regional scales is crucial for accurate decision-making by state and local governments. This is especially true in North Dakota, where climate change can have significant consequences on agriculture, its traditionally strongest economic sector. This region of the country shows a high variability in precipitation, especially in the summer months and so the focus of this study is on warm season processes over decadal time scales. The Weather Research and Forecast (WRF) model is used to dynamically downscale two Global Circulation Models (GCMs) from the CMIP5 ensemble in order to determine the microphysical parameterization and nudging techniques (spectral or analysis) best suited for this region. The downscaled domain includes the entirety of North Dakota at a horizontal resolution of 5 km. In addition, smaller domains of 1 km horizontal resolution are centered over regions of focused hydrological importance. The dynamically downscaled simulations are compared with both gridded observational data and statistically downscaled data to evaluate the performance of the simulations. Preliminary results have shown a marked difference between the two downscaled GCMs in terms of temperature and precipitation bias. Choice of microphysical parameterization has not shown to create any significant differences in the temperature fields. However, the precipitation fields do appear to be most affected by the microphysical parameterization, regardless of the choice of GCM. Implications on the unique water resource challenges faced in this region will also be discussed. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active">12</li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active">13</li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.H53K..01F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.H53K..01F">Parameterizing a Large-scale Water Balance Model in Regions with Sparse Data: The Tigris-Euphrates River Basins as an Example</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Flint, A. L.; Flint, L. E. 2010-12-01 The characterization of hydrologic response to current and future climates is of increasing importance to many countries around the world that rely heavily on changing and uncertain water supplies. Large-scale models that can calculate a spatially distributed water balance and elucidate groundwater recharge and surface water flows for large river basins provide a basis of estimates of changes due to future climate projections. Unfortunately many regions in the world have very sparse data for parameterization or calibration of hydrologic models. For this study, the Tigris and Euphrates River basins were used for the development of a regional water balance model at 180-m spatial scale, using the Basin Characterization Model, to estimate historical changes in groundwater recharge and surface water flows in the countries of Turkey, Syria, Iraq, Iran, and Saudi Arabia. Necessary input parameters include precipitation, air temperature, potential evapotranspiration (PET), soil properties and thickness, and estimates of bulk permeability from geologic units. Data necessary for calibration includes snow cover, reservoir volumes (from satellite data and historic, pre-reservoir elevation data) and streamflow measurements. Global datasets for precipitation, air temperature, and PET were available at very large spatial scales (50 km) through the world scale databases, finer scale WorldClim climate data, and required downscaling to fine scales for model input. Soils data were available through world scale soil maps but required parameterization on the basis of textural data to estimate soil hydrologic properties. Soil depth was interpreted from geomorphologic interpretation and maps of quaternary deposits, and geologic materials were categorized from generalized geologic maps of each country. Estimates of bedrock permeability were made on the basis of literature and data on driller’s logs and adjusted during calibration of the model to streamflow measurements where available. Results of historical water balance calculations throughout the Tigris and Euphrates River basins will be shown along with details of processing input data to provide spatial continuity and downscaling. Basic water availability analysis for recharge and runoff is readily available from a determinisitic solar radiation energy balance model and a global potential evapotranspiration model and global estimates of precipitation and air temperature. Future climate estimates can be readily applied to the same water and energy balance models to evaluate future water availability for countries around the globe. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150000805','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150000805">Development of the GEOS-5 Atmospheric General Circulation Model: Evolution from MERRA to MERRA2.</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Molod, Andrea; Takacs, Lawrence; Suarez, Max; Bacmeister, Julio 2014-01-01 The Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) version of the GEOS-5 (Goddard Earth Observing System Model - 5) Atmospheric General Circulation Model (AGCM) is currently in use in the NASA Global Modeling and Assimilation Office (GMAO) at a wide range of resolutions for a variety of applications. Details of the changes in parameterizations subsequent to the version in the original MERRA reanalysis are presented here. Results of a series of atmosphere-only sensitivity studies are shown to demonstrate changes in simulated climate associated with specific changes in physical parameterizations, and the impact of the newly implemented resolution-aware behavior on simulations at different resolutions is demonstrated. The GEOS-5 AGCM presented here is the model used as part of the GMAO's MERRA2 reanalysis, the global mesoscale "nature run", the real-time numerical weather prediction system, and for atmosphere-only, coupled ocean-atmosphere and coupled atmosphere-chemistry simulations. The seasonal mean climate of the MERRA2 version of the GEOS-5 AGCM represents a substantial improvement over the simulated climate of the MERRA version at all resolutions and for all applications. Fundamental improvements in simulated climate are associated with the increased re-evaporation of frozen precipitation and cloud condensate, resulting in a wetter atmosphere. Improvements in simulated climate are also shown to be attributable to changes in the background gravity wave drag, and to upgrades in the relationship between the ocean surface stress and the ocean roughness. The series of "resolution aware" parameters related to the moist physics were shown to result in improvements at higher resolutions, and result in AGCM simulations that exhibit seamless behavior across different resolutions and applications. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007ACPD....7.1655C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007ACPD....7.1655C">A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Cariolle, D.; Teyssèdre, H. 2007-01-01 This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory works. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the resolution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000-2004. Overall, the results show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small. The model also reproduces fairly well the polar ozone variability, with notably the formation of "ozone holes" in the southern hemisphere with amplitudes and seasonal evolutions that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone contents inside the polar vortex of the southern hemisphere over longer periods in spring time. It is concluded that for the study of climatic scenarios or the assimilation of ozone data, the present parameterization gives an interesting alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JGRD..114.0A21W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JGRD..114.0A21W">Cloud ice: A climate model challenge with signs and expectations of progress</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Waliser, Duane E.; Li, Jui-Lin F.; Woods, Christopher P.; Austin, Richard T.; Bacmeister, Julio; Chern, Jiundar; Del Genio, Anthony; Jiang, Jonathan H.; Kuang, Zhiming; Meng, Huan; Minnis, Patrick; Platnick, Steve; Rossow, William B.; Stephens, Graeme L.; Sun-Mack, Szedung; Tao, Wei-Kuo; Tompkins, Adrian M.; Vane, Deborah G.; Walker, Christopher; Wu, Dong 2009-04-01 Present-day shortcomings in the representation of upper tropospheric ice clouds in general circulation models (GCMs) lead to errors in weather and climate forecasts as well as account for a source of uncertainty in climate change projections. An ongoing challenge in rectifying these shortcomings has been the availability of adequate, high-quality, global observations targeting ice clouds and related precipitating hydrometeors. In addition, the inadequacy of the modeled physics and the often disjointed nature between model representation and the characteristics of the retrieved/observed values have hampered GCM development and validation efforts from making effective use of the measurements that have been available. Thus, even though parameterizations in GCMs accounting for cloud ice processes have, in some cases, become more sophisticated in recent years, this development has largely occurred independently of the global-scale measurements. With the relatively recent addition of satellite-derived products from Aura/Microwave Limb Sounder (MLS) and CloudSat, there are now considerably more resources with new and unique capabilities to evaluate GCMs. In this article, we illustrate the shortcomings evident in model representations of cloud ice through a comparison of the simulations assessed in the Intergovernmental Panel on Climate Change Fourth Assessment Report, briefly discuss the range of global observational resources that are available, and describe the essential components of the model parameterizations that characterize their "cloud" ice and related fields. Using this information as background, we (1) discuss some of the main considerations and cautions that must be taken into account in making model-data comparisons related to cloud ice, (2) illustrate present progress and uncertainties in applying satellite cloud ice (namely from MLS and CloudSat) to model diagnosis, (3) show some indications of model improvements, and finally (4) discuss a number of remaining questions and suggestions for pathways forward. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24132912','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24132912">Simulating effects of changing climate and CO(2) emissions on soil carbon pools at the Hubbard Brook experimental forest.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Dib, Alain E; Johnson, Chris E; Driscoll, Charles T; Fahey, Timothy J; Hayhoe, Katharine 2014-05-01 Carbon (C) sequestration in forest biomass and soils may help decrease regional C footprints and mitigate future climate change. The efficacy of these practices must be verified by monitoring and by approved calculation methods (i.e., models) to be credible in C markets. Two widely used soil organic matter models - CENTURY and RothC - were used to project changes in SOC pools after clear-cutting disturbance, as well as under a range of future climate and atmospheric carbon dioxide (CO(2) ) scenarios. Data from the temperate, predominantly deciduous Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, were used to parameterize and validate the models. Clear-cutting simulations demonstrated that both models can effectively simulate soil C dynamics in the northern hardwood forest when adequately parameterized. The minimum postharvest SOC predicted by RothC occurred in postharvest year 14 and was within 1.5% of the observed minimum, which occurred in year 8. CENTURY predicted the postharvest minimum SOC to occur in year 45, at a value 6.9% greater than the observed minimum; the slow response of both models to disturbance suggests that they may overestimate the time required to reach new steady-state conditions. Four climate change scenarios were used to simulate future changes in SOC pools. Climate-change simulations predicted increases in SOC by as much as 7% at the end of this century, partially offsetting future CO(2) emissions. This sequestration was the product of enhanced forest productivity, and associated litter input to the soil, due to increased temperature, precipitation and CO(2) . The simulations also suggested that considerable losses of SOC (8-30%) could occur if forest vegetation at HBEF does not respond to changes in climate and CO(2) levels. Therefore, the source/sink behavior of temperate forest soils likely depends on the degree to which forest growth is stimulated by new climate and CO(2) conditions. © 2013 John Wiley & Sons Ltd. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990064064&hterms=Change+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DChange%2Bclimate','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990064064&hterms=Change+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DChange%2Bclimate">Predicting Decade-to-Century Climate Change: Prospects for Improving Models</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Somerville, Richard C. J. 1999-01-01 Recent research has led to a greatly increased understanding of the uncertainties in today's climate models. In attempting to predict the climate of the 21st century, we must confront not only computer limitations on the affordable resolution of global models, but also a lack of physical realism in attempting to model key processes. Until we are able to incorporate adequate treatments of critical elements of the entire biogeophysical climate system, our models will remain subject to these uncertainties, and our scenarios of future climate change, both anthropogenic and natural, will not fully meet the requirements of either policymakers or the public. The areas of most-needed model improvements are thought to include air-sea exchanges, land surface processes, ice and snow physics, hydrologic cycle elements, and especially the role of aerosols and cloud-radiation interactions. Of these areas, cloud-radiation interactions are known to be responsible for much of the inter-model differences in sensitivity to greenhouse gases. Recently, we have diagnostically evaluated several current and proposed model cloud-radiation treatments against extensive field observations. Satellite remote sensing provides an indispensable component of the observational resources. Cloud-radiation parameterizations display a strong sensitivity to vertical resolution, and we find that vertical resolutions typically used in global models are far from convergence. We also find that newly developed advanced parameterization schemes with explicit cloud water budgets and interactive cloud radiative properties are potentially capable of matching observational data closely. However, it is difficult to evaluate the realism of model-produced fields of cloud extinction, cloud emittance, cloud liquid water content and effective cloud droplet radius until high-quality measurements of these quantities become more widely available. Thus, further progress will require a combination of theoretical and modeling research, together with intensified emphasis on both in situ and space-based remote sensing observations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19910001211','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19910001211">Dependence of marine stratocumulus reflectivities on liquid water paths</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Coakley, James A., Jr.; Snider, Jack B. 1990-01-01 Simple parameterizations that relate cloud liquid water content to cloud reflectivity are often used in general circulation climate models to calculate the effect of clouds in the earth's energy budget. Such parameterizations have been developed by Stephens (1978) and by Slingo and Schrecker (1982) and others. Here researchers seek to verify the parametric relationship through the use of simultaneous observations of cloud liquid water content and cloud reflectivity. The column amount of cloud liquid was measured using a microwave radiometer on San Nicolas Island following techniques described by Hogg et al., (1983). Cloud reflectivity was obtained through spatial coherence analysis of Advanced Very High Resolution Radiometer (AVHRR) imagery data (Coakley and Beckner, 1988). They present the dependence of the observed reflectivity on the observed liquid water path. They also compare this empirical relationship with that proposed by Stephens (1978). Researchers found that by taking clouds to be isotropic reflectors, the observed reflectivities and observed column amounts of cloud liquid water are related in a manner that is consistent with simple parameterizations often used in general circulation climate models to determine the effect of clouds on the earth's radiation budget. Attempts to use the results of radiative transfer calculations to correct for the anisotropy of the AVHRR derived reflectivities resulted in a greater scatter of the points about the relationship expected between liquid water path and reflectivity. The anisotropy of the observed reflectivities proved to be small, much smaller than indicated by theory. To critically assess parameterizations, more simultaneous observations of cloud liquid water and cloud reflectivities and better calibration of the AVHRR sensors are needed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC51A0795S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC51A0795S">Future Wildfire and Managed Fire Interactions in the Lake Tahoe Basin</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Scheller, R.; Kretchun, A. 2017-12-01 Managing large forested landscape in the context of a changing climate and altered disturbance regimes presents new challenges and require integrated assessments of forest disturbance, management, succession, and the carbon cycle. Successful management under these circumstances will require information about trade-offs among multiple objectives and opportunities for spatially optimized landscape-scale management. Improved information about the effects of climate on forest communities, disturbance feedbacks, and the effectiveness of mitigation strategies enables actionable options for landscape managers. We evaluated the effects of fire suppression, wildfires, and forest fuel (thinning) treatments on the long-term carbon storage potential for Lake Tahoe Basin (LTB) forests under various climate futures. We simulated management scenarios that encompass fuel treatments across the larger landscape, beyond the Wildland Urban Interface. We improved upon current fire modeling under climate change via an integrated fire modeling module that, a) explicitly captures the influence of climate, fuels, topography, active fire management (e.g., fire suppression), and fuel treatments, and b) can be parameterized from available data, e.g., remote sensing, field reporting, fire databases, expert opinion. These improvements increase geographic flexibility and decrease reliance on broad historical fire regime statistics - imperfect targets for a no analog future and require minimal parameterization and calibration. We assessed the interactions among fuel treatments, prescribe fire, fire suppression, and stochastically recurring wildfires. Predicted changes in climate and ignition patterns in response to future climatic conditions, vegetation dynamics, and fuel treatments indicate larger potential long-term effects on C emissions, forest structure, and forest composition than prior studies. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1147169','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1147169">Final report on "Modeling Diurnal Variations of California Land Biosphere CO2 Fluxes"</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Fung, Inez In Mediterranean climates, the season of water availability (winter) is out of phase with the season of light availability and atmospheric demand for moisture (summer). Multi-year half-hourly observations of sap flow velocities in 26 evergreen trees in a small watershed in Northern California show that different species of evergreen trees have different seasonalities of transpiration: Douglas-firs respond immediately to the first winter rain, while Pacific madrones have peak transpiration in the dry summer. Using these observations, we have derived species-specific parameterization of normalized sap flow velocities in terms of insolation, vapor pressure deficit and near-surface soil moisture. A simple 1-Dmore » boundary layer model showed that afternoon temperatures may be higher by 1 degree Celsius in an area with Douglas-firs than with Pacific madrones. The results point to the need to develop a new representation of subsurface moisture, in particular pools beneath the organic soil mantle and the vadose zone. Our ongoing and future work includes coupling our new parameterization of transpiration with new representation of sub-surface moisture in saprolite and weathered bedrock. The results will be implemented in a regional climate model to explore vegetation-climate feedbacks, especially in the dry season.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN41A1385C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN41A1385C">Test Driven Development of a Parameterized Ice Sheet Component</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Clune, T. 2011-12-01 Test driven development (TDD) is a software development methodology that offers many advantages over traditional approaches including reduced development and maintenance costs, improved reliability, and superior design quality. Although TDD is widely accepted in many software communities, the suitability to scientific software is largely undemonstrated and warrants a degree of skepticism. Indeed, numerical algorithms pose several challenges to unit testing in general, and TDD in particular. Among these challenges are the need to have simple, non-redundant closed-form expressions to compare against the results obtained from the implementation as well as realistic error estimates. The necessity for serial and parallel performance raises additional concerns for many scientific applicaitons. In previous work I demonstrated that TDD performed well for the development of a relatively simple numerical model that simulates the growth of snowflakes, but the results were anecdotal and of limited relevance to far more complex software components typical of climate models. This investigation has now been extended by successfully applying TDD to the implementation of a substantial portion of a new parameterized ice sheet component within a full climate model. After a brief introduction to TDD, I will present techniques that address some of the obstacles encountered with numerical algorithms. I will conclude with some quantitative and qualitative comparisons against climate components developed in a more traditional manner. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150002122','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150002122">Natural Air-Sea Flux of CO2 in Simulations of the NASA-GISS Climate Model: Sensitivity to the Physical Ocean Model Formulation</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Romanou, A.; Gregg, Watson W.; Romanski, J.; Kelley, M.; Bleck, R.; Healy, R.; Nazarenko, L.; Russell, G.; Schmidt, G. A.; Sun, S.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20150002122'); toggleEditAbsImage('author_20150002122_show'); toggleEditAbsImage('author_20150002122_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20150002122_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20150002122_hide"> 2013-01-01 Results from twin control simulations of the preindustrial CO2 gas exchange (natural flux of CO2) between the ocean and the atmosphere are presented here using the NASA-GISS climate model, in which the same atmospheric component (modelE2) is coupled to two different ocean models, the Russell ocean model and HYCOM. Both incarnations of the GISS climate model are also coupled to the same ocean biogeochemistry module (NOBM) which estimates prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2. Model intercomparison is carried out at equilibrium conditions and model differences are contrasted with biases from present day climatologies. Although the models agree on the spatial patterns of the air-sea flux of CO2, they disagree on the strength of the North Atlantic and Southern Ocean sinks mainly because of kinematic (winds) and chemistry (pCO2) differences rather than thermodynamic (SST) ones. Biology/chemistry dissimilarities in the models stem from the different parameterizations of advective and diffusive processes, such as overturning, mixing and horizontal tracer advection and to a lesser degree from parameterizations of biogeochemical processes such as gravitational settling and sinking. The global meridional overturning circulation illustrates much of the different behavior of the biological pump in the two models, together with differences in mixed layer depth which are responsible for different SST, DIC and nutrient distributions in the two models and consequently different atmospheric feedbacks (in the wind, net heat and freshwater fluxes into the ocean). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=313964','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=313964">Using satellite-based estimates of evapotranspiration and groundwater changes to determine anthropogenic water fluxes in land surface models</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Irrigation is a widely used water management practice that is often poorly parameterized in land surface and climate models. Previous studies have addressed this issue via use of irrigation area, applied water inventory data, or soil moisture content. These approaches have a variety of drawbacks i... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=308471&keyword=Scheme&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=308471&keyword=Scheme&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50">Grid-scale Indirect Radiative Forcing of Climate due to aerosols over the northern hemisphere simulated by the integrated WRF-CMAQ model: Preliminary results</a> <a target="_blank" rel="noopener noreferrer" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a> In this study, indirect aerosol effects on grid-scale clouds were implemented in the integrated WRF3.3-CMAQ5.0 modeling system by including parameterizations for both cloud droplet and ice number concentrations calculated from the CMAQ-predicted aerosol particles. The resulting c... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020080868','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020080868">Confronting Models with Data: The GEWEX Cloud Systems Study</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Randall, David; Curry, Judith; Duynkerke, Peter; Krueger, Steven; Moncrieff, Mitchell; Ryan, Brian; Starr, David OC.; Miller, Martin; Rossow, William; Tselioudis, George 2002-01-01 The GEWEX Cloud System Study (GCSS; GEWEX is the Global Energy and Water Cycle Experiment) was organized to promote development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. The strategy of GCSS is to use two distinct kinds of models to analyze and understand observations of the behavior of several different types of clouds systems. Cloud-system-resolving models (CSRMs) have high enough spatial and temporal resolutions to represent individual cloud elements, but cover a wide enough range of space and time scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the surgically extracted column physics of atmospheric general circulation models. SCMs are used to test cloud parameterizations in an un-coupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data is collected in various field programs and provided to the CSRM Community, which uses the data to "certify" the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM Community. We report here the results of a re-thinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, and an explicit recognition of the importance of data integration. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70168360','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70168360">Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel 2016-01-01 Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160003594&hterms=neither+deep+shallow&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dneither%2Bdeep%2Bshallow','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160003594&hterms=neither+deep+shallow&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dneither%2Bdeep%2Bshallow">RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; Fridlind, Ann; Endo, Satoshi; Song, Hua; Feng, Sha; Toto, Tami; Li, Zhijin; Zhang, Minghua 2015-01-01 Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1201337-racoro-continental-boundary-layer-cloud-investigations-separation-parameterization-biases-single-column-model-cam5-simulations-shallow-cumulus','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1201337-racoro-continental-boundary-layer-cloud-investigations-separation-parameterization-biases-single-column-model-cam5-simulations-shallow-cumulus">RACORO continental boundary layer cloud investigations. 3. Separation of parameterization biases in single-column model CAM5 simulations of shallow cumulus</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; ... 2015-06-19 Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) project has constructed case studies from the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only amore » relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMGC51A0665A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMGC51A0665A">An Investigation of Bomb Cyclogenesis in NCEP's CFS Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Alvarez, F. M.; Eichler, T.; Gottschalck, J. 2008-12-01 With the concerns, impacts and consequences of climate change increasing, the need for climate models to simulate daily weather is very important. Given the improvements in resolution and physical parameterizations, climate models are becoming capable of resolving extreme weather events. A particular type of extreme event which has large impacts on transportation, industry and the general public is a rapidly intensifying cyclone referred to as a "bomb." In this study, bombs are investigated using the National Center for Environmental Prediction's (NCEP) Climate Forecast System (CFS) model. We generate storm tracks based on 6-hourly sea-level pressure (SLP) from long-term climate runs of the CFS model. Investigation of this dataset has revealed that the CFS model is capable of producing bombs. We show a case study of a bomb in the CFS model and demonstrate that it has characteristics similar to the observed. Since the CFS model is capable of producing bombs, future work will focus on trends in their frequency and intensity so that an assessment of the potential role of the bomb in climate change can be assessed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930064881&hterms=balance+general&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dbalance%2Bgeneral','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930064881&hterms=balance+general&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dbalance%2Bgeneral">The implementation and validation of improved land-surface hydrology in an atmospheric general circulation model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S. 1993-01-01 New land-surface hydrologic parameterizations are implemented into the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: 1) runoff and evapotranspiration functions that include the effects of subgrid-scale spatial variability and use physically based equations of hydrologic flux at the soil surface and 2) a realistic soil moisture diffusion scheme for the movement of water and root sink in the soil column. A one-dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three-dimensional GCM. Results of the final simulation with the GISS GCM and the new land-surface hydrology indicate that the runoff rate, especially in the tropics, is significantly improved. As a result, the remaining components of the heat and moisture balance show similar improvements when compared to observations. The validation of model results is carried from the large global (ocean and land-surface) scale to the zonal, continental, and finally the regional river basin scales. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19890064717&hterms=climate+exchange&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dclimate%2Bexchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19890064717&hterms=climate+exchange&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dclimate%2Bexchange">Effects of cumulus entrainment and multiple cloud types on a January global climate model simulation</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Yao, Mao-Sung; Del Genio, Anthony D. 1989-01-01 An improved version of the GISS Model II cumulus parameterization designed for long-term climate integrations is used to study the effects of entrainment and multiple cloud types on the January climate simulation. Instead of prescribing convective mass as a fixed fraction of the cloud base grid-box mass, it is calculated based on the closure assumption that the cumulus convection restores the atmosphere to a neutral moist convective state at cloud base. This change alone significantly improves the distribution of precipitation, convective mass exchanges, and frequencies in the January climate. The vertical structure of the tropical atmosphere exhibits quasi-equilibrium behavior when this closure is used, even though there is no explicit constraint applied above cloud base. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active">13</li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active">14</li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/15536131','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/15536131">The influence of large-scale wind power on global climate.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Keith, David W; Decarolis, Joseph F; Denkenberger, David C; Lenschow, Donald H; Malyshev, Sergey L; Pacala, Stephen; Rasch, Philip J 2004-11-16 Large-scale use of wind power can alter local and global climate by extracting kinetic energy and altering turbulent transport in the atmospheric boundary layer. We report climate-model simulations that address the possible climatic impacts of wind power at regional to global scales by using two general circulation models and several parameterizations of the interaction of wind turbines with the boundary layer. We find that very large amounts of wind power can produce nonnegligible climatic change at continental scales. Although large-scale effects are observed, wind power has a negligible effect on global-mean surface temperature, and it would deliver enormous global benefits by reducing emissions of CO(2) and air pollutants. Our results may enable a comparison between the climate impacts due to wind power and the reduction in climatic impacts achieved by the substitution of wind for fossil fuels. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A54B..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A54B..04B">A stochastic parameterization for deep convection using cellular automata</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J. 2012-12-01 Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in large-scale variables in regions where convective activity is large. A two month extended evaluation of the deterministic behaviour of the scheme indicate a neutral impact on forecast skill. References: Bengtsson, L., H. Körnich, E. Källén, and G. Svensson, 2011: Large-scale dynamical response to sub-grid scale organization provided by cellular automata. Journal of the Atmospheric Sciences, 68, 3132-3144. Frenkel, Y., A. Majda, and B. Khouider, 2011: Using the stochastic multicloud model to improve tropical convective parameterization: A paradigm example. Journal of the Atmospheric Sciences, doi: 10.1175/JAS-D-11-0148.1. Huang, X.-Y., 1988: The organization of moist convection by internal 365 gravity waves. Tellus A, 42, 270-285. Khouider, B., J. Biello, and A. Majda, 2010: A Stochastic Multicloud Model for Tropical Convection. Comm. Math. Sci., 8, 187-216. Palmer, T., 2011: Towards the Probabilistic Earth-System Simulator: A Vision for the Future of Climate and Weather Prediction. Quarterly Journal of the Royal Meteorological Society 138 (2012) 841-861 Plant, R. and G. Craig, 2008: A stochastic parameterization for deep convection based on equilibrium statistics. J. Atmos. Sci., 65, 87-105. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A43G0366B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A43G0366B">Explicit modeling of marine biogeochemical influence on primary sea spray aerosol composition, and cloud impacts</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Burrows, S. M.; Elliott, S.; Liu, X.; Ogunro, O. O.; Easter, R. C.; Rasch, P. J. 2013-12-01 Aerosol concentrations and their cloud nucleation activity in remote ocean regions represent an important uncertainty in current models of global climate. In particular, the impact of marine biological activity on the primary submicron sea spray aerosol is not yet fully understood, and existing knowledge has not yet been fully integrated into climate modeling efforts. We present recent results addressing two aspects of this problem. First, we present an estimate of the concentrations of ice-nucleation active particles derived from ocean biological material, and show that these may dominate IN concentrations in the remote marine boundary layer, particularly over the Southern Ocean. (Burrows et al., ACP, 2013a) Second, we present a novel framework for parameterizing the fractionation of marine organic matter into sea spray. The framework models aerosol organic enrichment as resulting from Langmuir adsorption of surface-active macromolecules at the surface of bursting bubbles. Distributions of macromolecular classes are estimated using output from a global marine biogeochemistry model (Burrows et al., in prep, 2013b; Elliott et al., submitted, 2013). The proposed parameterization independently produces relationships between chlorophyll-a and the sea spray organic mass fraction that are similar to existing empirical parameterizations in highly productive bloom regions, but which differ between seasons and ocean regions as a function of ocean biogeochemical variables. Future work should focus on further evaluating and improving the parameterization based on laboratory and field experiments, as well as on further investigation of the atmospheric implications of the predicted sea spray aerosol chemistry. Field experiments in the Southern Ocean and other remote ocean locations would be especially valuable in evaluating and improving these parameterizations. Burrows, S. M., Hoose, C., Pöschl, U., and Lawrence, M. G.: Ice nuclei in marine air: biogenic particles or dust?, Atmos. Chem. Phys., 13, 245-267, doi:10.5194/acp-13-245-2013, 2013a. Burrows, S. M., Elliott, S., Ogunro, O. and Rasch, P.: A framework for modeling the organic fractionation of the sea spray aerosol, in prep., 2013b. Elliott, S., S. Burrows, C. Deal, X. Liu, M. Long, O. Oluwaseun, L. Russell, and O. Wingenter, Prospects for the simulation of macromolecular surfactant chemistry in the ocean-atmosphere, submitted, 2013b. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010080472','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010080472">Representation of Clear and Cloudy Boundary Layers in Climate Models. Chapter 14</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Randall, D. A.; Shao, Q.; Branson, M. 1997-01-01 The atmospheric general circulation models which are being used as components of climate models rely on their boundary layer parameterizations to produce realistic simulations of the surface turbulent fluxes of sensible heat. moisture. and momentum: of the boundary-layer depth over which these fluxes converge: of boundary layer cloudiness: and of the interactions of the boundary layer with the deep convective clouds that grow upwards from it. Two current atmospheric general circulation models are used as examples to show how these requirements are being addressed: these are version 3 of the Community Climate Model. which has been developed at the U.S. National Center for Atmospheric Research. and the Colorado State University atmospheric general circulation model. The formulations and results of both models are discussed. Finally, areas for future research are suggested. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20010050985&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsimulation%2Bprocesses','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20010050985&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsimulation%2Bprocesses">Tropical Oceanic Precipitation Processes Over Warm Pool: 2D and 3D Cloud Resolving Model Simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Tao, W.-K.; Johnson, D.; Simpson, J.; Einaudi, Franco (Technical Monitor) 2001-01-01 Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA.....4984B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA.....4984B">Towards a community Earth System Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Blackmon, M. 2003-04-01 The Community Climate System Model, version 2 (CCSM2), was released in June 2002. CCSM2 has several new components and features, which I will discuss briefly. I will also show a few results from a multi-century equilibrium run with this model, emphasizing the improvements over the earlier simulation using the original CSM. A few flaws and inadequacies in CCSM2 have been identified. I will also discuss briefly work underway to improve the model and present results, if available. CCSM2, with improvements, will be the basis for the development of a Community Earth System Model (CESM). The highest priority for expansion of the model involves incorporation of biogeosciences into the coupled model system, with emphasis given to the carbon, nitrogen and iron cycles. The overall goal of the biogeosciences project within CESM is to understand the regulation of planetary energetics, planetary ecology, and planetary metabolism through exchanges of energy, momentum, and materials among atmosphere, land, and ocean, and the response of the climate system through these processes to changes in land cover and land use. In particular, this research addresses how biogeochemical coupling of carbon, nitrogen, and iron cycles affects climate and how human perturbations of these cycles alter climate. To accomplish these goals, the Community Land Model, the land component of CCSM2, is being developed to include river routing, carbon and nitrogen cycles, emissions of mineral aerosols and biogenic volatile organic compounds, dry deposition of various gases, and vegetation dynamics. The carbon and nitrogen cycles are being implemented using parameterizations developed as part of a state-of-the-art ecosystem biogeochemistry model. The primary goal of this research is to provide an accurate net flux of CO2 between the land and the atmosphere so that CESM can be used to study the dynamics of the coupled climate-carbon system. Emissions of biogenic volatile organic compounds are also based on a state-of-the-art emissions model and depend on plant type, leaf area index, photosynthetically active radiation, and leaf temperature. Dust emissions and deposition are being developed to implement a fully coupled dust cycle in CCSM, including the radiative effects of dust and carbon feedbacks related to fertilization of ocean and terrestrial ecosystems. Dust mobilization depends on surface wind speed, soil moisture, plant cover, and soil texture. Dust dry deposition processes include sedimentation and turbulent mix-out. A major research focus is how natural and human-mediated changes in land cover and ecosystem functions alter surface energy fluxes, the hydrological cycle, and biogeochemical cycles. Human land uses include conversion of natural vegetation to cropland, soil degradation, and urbanization. Climate feedbacks associated with natural changes in land cover are being assessed by developing and implementing a model of natural vegetation dynamics for use with the Community Land Model. Development of a marine ecosystem model is also underway. The ecosystem model is based on the global, mixed-layer marine ecosystem model of Moore et al., which includes parameterizations for such things as iron limitation and scavenging, zooplankton grazing, nitrogen fixation, calcification, and ballast-based remineralization. A series of experiments is being planned to assess the coupling of the ecology to the biogeochemistry, to adequately tune some of the model parameters that are poorly constrained by data, to explore new parameterizations and processes (e.g., riverine and atmospheric inputs of nutrients), and to conduct uncoupled application studies (e.g., deliberate carbon sequestration, retrospective historical simulations, iron-dust deposition response). Longer term plans include investigating biogeochemical processes in the coastal zone and how to incorporate these processes into a global ocean model, either through subgrid-scale parameterizations or model nesting. A Whole Atmosphere Community Climate Model(WACCM) is being developed. The vertical extent of the model is 150 km at present, but extension to 500 km is eventually expected. Interactive chemistry is being incorporated. This model will be used as the atmospheric component of CESM for some experiments. One expected application is the study of solar variability and its impact on climate variability in the troposphere and at the atmosphere, ocean, land interface. Preliminary results using some of these model components will be shown. A timeline for development and use of the models will be given. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080039447','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080039447">A Goddard Multi-Scale Modeling System with Unified Physics</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20080039447'); toggleEditAbsImage('author_20080039447_show'); toggleEditAbsImage('author_20080039447_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20080039447_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20080039447_hide"> 2008-01-01 Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite simulator has been developed at GSFC, which is designed to fully utilize the multi-scale modeling system. A brief review of the multi-scale modeling system with unified physics/simulator and examples is presented in this article. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatCC...7..774D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatCC...7..774D">Quantifying the economic risks of climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Diaz, Delavane; Moore, Frances 2017-11-01 Understanding the value of reducing greenhouse-gas emissions matters for policy decisions and climate risk management, but quantification is challenging because of the complex interactions and uncertainties in the Earth and human systems, as well as normative ethical considerations. Current modelling approaches use damage functions to parameterize a simplified relationship between climate variables, such as temperature change, and economic losses. Here we review and synthesize the limitations of these damage functions and describe how incorporating impacts, adaptation and vulnerability research advances and empirical findings could substantially improve damage modelling and the robustness of social cost of carbon values produced. We discuss the opportunities and challenges associated with integrating these research advances into cost-benefit integrated assessment models, with guidance for future work. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.8337B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.8337B">The Effect of an Increased Convective Entrainment Rate on Indian Monsoon Biases in the Met Office Unified Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bush, Stephanie; Turner, Andrew; Woolnough, Steve; Martin, Gill 2013-04-01 Global circulation models (GCMs) are a key tool for understanding and predicting monsoon rainfall, now and under future climate change. However, many GCMs show significant, systematic biases in their simulation of monsoon rainfall and dynamics that spin up over very short time scales and persist in the climate mean state. We describe several of these biases as simulated in the Met Office Unified Model and show they are sensitive to changes in the convective parameterization's entrainment rate. To improve our understanding of the biases and inform efforts to improve convective parameterizations, we explore the reasons for this sensitivity. We show the results of experiments where we increase the entrainment rate in regions of especially large bias: the western equatorial Indian Ocean, western north Pacific and India itself. We use the results to determine whether improvements in biases are due to the local increase in entrainment or are the remote response of the entrainment increase elsewhere in the GCM. We find that feedbacks usually strengthen the local response, but the local response leads to a different mean state change in different regions. We also show results from experiments which demonstrate the spin-up of the local response, which we use to further understand the response in complex regions such as the Western North Pacific. Our work demonstrates that local application of parameterization changes is a powerful tool for understanding their global impact. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013DyAtO..61...14B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013DyAtO..61...14B">A diapycnal diffusivity model for stratified environmental flows</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bouffard, Damien; Boegman, Leon 2013-06-01 The vertical diffusivity of density, Kρ, regulates ocean circulation, climate and coastal water quality. Kρ is difficult to measure and model in these stratified turbulent flows, resulting in the need for the development of Kρ parameterizations from more readily measurable flow quantities. Typically, Kρ is parameterized from turbulent temperature fluctuations using the Osborn-Cox model or from the buoyancy frequency, N, kinematic viscosity, ν, and the rate of dissipation of turbulent kinetic energy, ɛ, using the Osborn model. More recently, Shih et al. (2005, J. Fluid Mech. 525: 193-214) proposed a laboratory scale parameterization for Kρ, at Prandtl number (ratio of the viscosity over the molecular diffusivity) Pr = 0.7, in terms of the turbulence intensity parameter, Re=ɛ/(νN), which is the ratio between the destabilizing effect of turbulence to the stabilizing effects of stratification and viscosity. In the present study, we extend the SKIF parameterization, against extensive sets of published data, over 0.7 < Pr < 700 and validate it at field scale. Our results show that the SKIF model must be modified to include a new Buoyancy-controlled mixing regime, between the Molecular and Transitional regimes, where Kρ is captured using the molecular diffusivity and Osborn model, respectively. The Buoyancy-controlled regime occurs over 10Pr<Re<(3, where K=0.1/Prν Re is Pr dependent. This range is shown to be characteristic to lakes and oceans and both the Osborn and Osborn-Cox models systematically underestimate Kρ in this regime. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1711640G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1711640G">Regional Climate Model sesitivity to different parameterizations schemes with WRF over Spain</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> García-Valdecasas Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Hidalgo-Muñoz, Jose Manuel; Argüeso, Daniel; Castro-Díez, Yolanda; Jesús Esteban-Parra, María 2015-04-01 The ability of the Weather Research and Forecasting (WRF) model to simulate the regional climate depends on the selection of an adequate combination of parameterization schemes. This study assesses WRF sensitivity to different parameterizations using six different runs that combined three cumulus, two microphysics and three surface/planetary boundary layer schemes in a topographically complex region such as Spain, for the period 1995-1996. Each of the simulations spanned a period of two years, and were carried out at a spatial resolution of 0.088° over a domain encompassing the Iberian Peninsula and nested in the coarser EURO-CORDEX domain (0.44° resolution). The experiments were driven by Interim ECMWF Re-Analysis (ERA-Interim) data. In addition, two different spectral nudging configurations were also analysed. The simulated precipitation and maximum and minimum temperatures from WRF were compared with Spain02 version 4 observational gridded datasets. The comparison was performed at different time scales with the purpose of evaluating the model capability to capture mean values and high-order statistics. ERA-Interim data was also compared with observations to determine the improvement obtained using dynamical downscaling with respect to the driving data. For this purpose, several parameters were analysed by directly comparing grid-points. On the other hand, the observational gridded data were grouped using a multistep regionalization to facilitate the comparison in term of monthly annual cycle and the percentiles of daily values analysed. The results confirm that no configuration performs best, but some combinations that produce better results could be chosen. Concerning temperatures, WRF provides an improvement over ERA-Interim. Overall, model outputs reduce the biases and the RMSE for monthly-mean maximum and minimum temperatures and are higher correlated with observations than ERA-Interim. The analysis shows that the Yonsei University planetary boundary layer scheme is the most appropriate parameterization in term of temperatures because it better describes monthly minimum temperatures and seems to perform well for maximum temperatures. Regarding precipitation, ERA-Interim time series are slightly higher correlated with observations than WRF, but the bias and the RMSE are largely worse. These results also suggest that CAM V.5.1 2-moment 5-class microphysics schemes should not be used due to the computational cost with no apparent gain with respect to simpler schemes such as WRF single-moment 3-class. For the convection scheme, this study suggests that Betts-Miller-Janjic scheme is an appropriate choice due to its robustness and Kain-Fritsch cumulus scheme should not be used over this region. KEY WORDS: Regional climate modelling, physics schemes, parameterizations, WRF. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=272577&Lab=NCER&keyword=climate+AND+change+AND+colorado+AND+effects&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=272577&Lab=NCER&keyword=climate+AND+change+AND+colorado+AND+effects&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50">QUANTIFYING THE CLIMATE, AIR QUALITY AND HEALTH BENEFITS OF IMPROVED COOKSTOVES: AN INTEGRATED LABORATORY, FIELD AND MODELING STUDY</a> <a target="_blank" rel="noopener noreferrer" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a> Expected results and outputs include: extensive dataset of in-field and laboratory emissions data for traditional and improved cookstoves; parameterization to predict cookstove emissions from drive cycle data; indoor and personal exposure data for traditional and improved cook... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27465689','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27465689">High sensitivity of Indian summer monsoon to Middle East dust absorptive properties.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Jin, Qinjian; Yang, Zong-Liang; Wei, Jiangfeng 2016-07-28 The absorptive properties of dust aerosols largely determine the magnitude of their radiative impacts on the climate system. Currently, climate models use globally constant values of dust imaginary refractive index (IRI), a parameter describing the dust absorption efficiency of solar radiation, although it is highly variable. Here we show with model experiments that the dust-induced Indian summer monsoon (ISM) rainfall differences (with dust minus without dust) change from -9% to 23% of long-term climatology as the dust IRI is changed from zero to the highest values used in the current literature. A comparison of the model results with surface observations, satellite retrievals, and reanalysis data sets indicates that the dust IRI values used in most current climate models are too low, tending to significantly underestimate dust radiative impacts on the ISM system. This study highlights the necessity for developing a parameterization of dust IRI for climate studies. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020080729','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020080729">Tropical Cumulus Convection and Upward Propagating Waves in Middle Atmospheric GCMs</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Horinouchi, T.; Pawson, S.; Shibata, K.; Langematz, U.; Manzini, E.; Giorgetta, M. A.; Sassi, F.; Wilson, R. J.; Hamilton, K. P.; deGranpre, J.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20020080729'); toggleEditAbsImage('author_20020080729_show'); toggleEditAbsImage('author_20020080729_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20020080729_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20020080729_hide"> 2002-01-01 It is recognized that the resolved tropical wave spectrum can vary considerably between general circulation models (GCMs) and that these differences can have an important impact on the simulated climate. A comprehensive comparison of the waves is presented for the December-January-February period using high-frequency (three-hourly) data archives from eight GCMs and one simple model participating in the GCM Reality Intercomparison Project for SPARC (GRIPS). Quantitative measures of the structure and causes of the wavenumber-frequency structure of resolved waves and their impacts on the climate are given. Space-time spectral analysis reveals that the wave spectrum throughout the middle atmosphere is linked to variability of convective precipitation, which is determined by the parameterized convection. The variability of the precipitation spectrum differs by more than an order of magnitude between the models, with additional changes in the spectral distribution (especially the frequency). These differences can be explained primarily by the choice of different, cumulus par amet erizations: quasi-equilibrium mass-flux schemes tend to produce small variability, while the moist-convective adjustment scheme is most active. Comparison with observational estimates of precipitation variability suggests that the model values are scattered around the truth. This result indicates that a significant portion of the forcing of the equatorial quasi-biennial oscillation (QBO) is provided by waves with scales that are not resolved in present-day GCMs, since only the moist convective adjustment scheme (which has the largest transient variability) can force a QBO in models that have no parameterization of non-stationary gravity waves. Parameterized cumulus convection also impacts the nonmigrating tides in the equatorial region. In most of the models, momentum transport by diurnal nonmigrating tides in the mesosphere is larger than that by Kelvin waves, being more significant than has been thought. It is shown that the equatorial semi-annual oscillation in the models examined is driven mainly by gravity waves with periods shorter than three days, with at least some contribution from parameterized gravity waves; the contribution from the ultra-fast zonal wavenumber-1 Kelvin waves is negligible. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19970023383','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19970023383">Comparison of Ice Cloud Particle Sizes Retrieved From Satellite Data Derived From In Situ Measurements</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M. 1997-01-01 Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al. 1994), there is no comparable study for cirrus ice crystals. In this paper a near-global survey of cirrus ice crystal sizes is conducted using ISCCP satellite data analysis. The retrieval scheme uses phase functions based upon hexagonal crystals calculated by a ray tracing technique. The results show that global mean values of D(e) are about 60 micro-m. This study also investigates the possible reasons for the significant difference between satellite retrieved effective radii (approx. 60 micro-m) and aircraft measured particle sizes (approx. 200 micro-m) during the FIRE I IFO experiment. They are (1) vertical inhomogeneity of cirrus particle sizes; (2) lower limit of the instrument used in aircraft measurements; (3) different definitions of effective particle sizes; and (4) possible inappropriate phase functions used in satellite retrieval. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1198411-global-model-simulation-radiative-transfer-impact-surface-hydrology-over-sierra-nevada-rocky-mountains','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1198411-global-model-simulation-radiative-transfer-impact-surface-hydrology-over-sierra-nevada-rocky-mountains">A global model simulation for 3-D radiative transfer impact on surface hydrology over the Sierra Nevada and Rocky Mountains</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Lee, W. -L.; Gu, Y.; Liou, K. N. 2015-05-19 We investigate 3-D mountain effects on solar flux distributions and their impact on surface hydrology over the western United States, specifically the Rocky Mountains and the Sierra Nevada, using the global CCSM4 (Community Climate System Model version 4; Community Atmosphere Model/Community Land Model – CAM4/CLM4) with a 0.23° × 0.31° resolution for simulations over 6 years. In a 3-D radiative transfer parameterization, we have updated surface topography data from a resolution of 1 km to 90 m to improve parameterization accuracy. In addition, we have also modified the upward-flux deviation (3-D–PP (plane-parallel)) adjustment to ensure that the energy balance atmore » the surface is conserved in global climate simulations based on 3-D radiation parameterization. We show that deviations in the net surface fluxes are not only affected by 3-D mountains but also influenced by feedbacks of cloud and snow in association with the long-term simulations. Deviations in sensible heat and surface temperature generally follow the patterns of net surface solar flux. The monthly snow water equivalent (SWE) deviations show an increase in lower elevations due to reduced snowmelt, leading to a reduction in cumulative runoff. Over higher-elevation areas, negative SWE deviations are found because of increased solar radiation available at the surface. Simulated precipitation increases for lower elevations, while it decreases for higher elevations, with a minimum in April. Liquid runoff significantly decreases at higher elevations after April due to reduced SWE and precipitation.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810021159','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810021159">Calculation of surface temperature and surface fluxes in the GLAS GOM</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Sud, Y. C.; Abeles, J. A. 1981-01-01 Because the GLAS model's surface fluxes of sensible and latent heat exhibit strong 2 delta t oscillations at the individual grid points as well as in the zonal hemispheric averages and because a basic weakness of the GLAS model lower evaporation over oceans and higher evaporation over land in a typical monthly simulation, the GLAS model PBL parameterization was changed to calculate the mixed layer temperature gradient by solution of a quadratic equation for a stable PBL and by a curve fit relation for an unstable PBL. The new fluxes without any 2 delta t oscillation. Also, the geographical distributions of the surface fluxes are improved. The parameterization presented is incorporated into the new GLAS climate model. Some results which compare the evaporation over land and ocean between old and new calculations are appended. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005JCli...18..237S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005JCli...18..237S">Cloud Feedbacks in the Climate System: A Critical Review.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stephens, Graeme L. 2005-01-01 This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earth-atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910055075&hterms=increase+humidity&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dincrease%2Bhumidity','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910055075&hterms=increase+humidity&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dincrease%2Bhumidity">Simulations of the effect of a warmer climate on atmospheric humidity</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Del Genio, Anthony D.; Lacis, Andrew A.; Ruedy, Reto A. 1991-01-01 Increases in the concentration of water vapor constitute the single largest positive feedback in models of global climate warming caused by greenhouse gases. It has been suggested that sinking air in the regions surrounding deep cumulus clouds will dry the upper troposphere and eliminate or reverse the direction of water vapor feedback. This hypothesis has been tested by performing an idealized simulation of climate change with two different versions of a climate model which both incorporate drying due to subsidence of clear air but differ in their parameterization of moist convection and stratiform clouds. Despite increased drying of the upper troposphere by cumulus clouds, upper-level humidity increases in the warmer climate because of enhanced upward moisture transport by the general circulation and increased accumulation of water vapor and ice at cumulus cloud tops. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H23O..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H23O..06S">The integrated effects of future climate and hydrologic uncertainty on sustainable flood risk management</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Steinschneider, S.; Wi, S.; Brown, C. M. 2013-12-01 Flood risk management performance is investigated within the context of integrated climate and hydrologic modeling uncertainty to explore system robustness. The research question investigated is whether structural and hydrologic parameterization uncertainties are significant relative to other uncertainties such as climate change when considering water resources system performance. Two hydrologic models are considered, a conceptual, lumped parameter model that preserves the water balance and a physically-based model that preserves both water and energy balances. In the conceptual model, parameter and structural uncertainties are quantified and propagated through the analysis using a Bayesian modeling framework with an innovative error model. Mean climate changes and internal climate variability are explored using an ensemble of simulations from a stochastic weather generator. The approach presented can be used to quantify the sensitivity of flood protection adequacy to different sources of uncertainty in the climate and hydrologic system, enabling the identification of robust projects that maintain adequate performance despite the uncertainties. The method is demonstrated in a case study for the Coralville Reservoir on the Iowa River, where increased flooding over the past several decades has raised questions about potential impacts of climate change on flood protection adequacy. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active">14</li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active">15</li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017SPIE10466E..57I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017SPIE10466E..57I">Influence of the vertical mixing parameterization on the modeling results of the Arctic Ocean hydrology</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Iakshina, D. F.; Golubeva, E. N. 2017-11-01 The vertical distribution of the hydrological characteristics in the upper ocean layer is mostly formed under the influence of turbulent and convective mixing, which are not resolved in the system of equations for large-scale ocean. Therefore it is necessary to include additional parameterizations of these processes into the numerical models. In this paper we carry out a comparative analysis of the different vertical mixing parameterizations in simulations of climatic variability of the Arctic water and sea ice circulation. The 3D regional numerical model for the Arctic and North Atlantic developed in the ICMMG SB RAS (Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the Russian Academy of Science) and package GOTM (General Ocean Turbulence Model1,2, http://www.gotm.net/) were used as the numerical instruments . NCEP/NCAR reanalysis data were used for determination of the surface fluxes related to ice and ocean. The next turbulence closure schemes were used for the vertical mixing parameterizations: 1) Integration scheme based on the Richardson criteria (RI); 2) Second-order scheme TKE with coefficients Canuto-A3 (CANUTO); 3) First-order scheme TKE with coefficients Schumann and Gerz4 (TKE-1); 4) Scheme KPP5 (KPP). In addition we investigated some important characteristics of the Arctic Ocean state including the intensity of Atlantic water inflow, ice cover state and fresh water content in Beaufort Sea. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A41L..08M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A41L..08M">Linking Aerosol Optical Properties Between Laboratory, Field, and Model Studies</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Murphy, S. M.; Pokhrel, R. P.; Foster, K. A.; Brown, H.; Liu, X. 2017-12-01 The optical properties of aerosol emissions from biomass burning have a significant impact on the Earth's radiative balance. Based on measurements made during the Fourth Fire Lab in Missoula Experiment, our group published a series of parameterizations that related optical properties (single scattering albedo and absorption due to brown carbon at multiple wavelengths) to the elemental to total carbon ratio of aerosols emitted from biomass burning. In this presentation, the ability of these parameterizations to simulate the optical properties of ambient aerosol is assessed using observations collected in 2017 from our mobile laboratory chasing wildfires in the Western United States. The ambient data includes measurements of multi-wavelength absorption, scattering, and extinction, size distribution, chemical composition, and volatility. In addition to testing the laboratory parameterizations, this combination of measurements allows us to assess the ability of core-shell Mie Theory to replicate observations and to assess the impact of brown carbon and mixing state on optical properties. Finally, both laboratory and ambient data are compared to the optical properties generated by a prominent climate model (Community Earth System Model (CESM) coupled with the Community Atmosphere Model (CAM 5)). The discrepancies between lab observations, ambient observations and model output will be discussed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1613287F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1613287F">Simulating carbon, water and energy fluxes of a rainforest and an oil palm plantation using the Community Land Model (CLM4.5)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fan, Yuanchao; Bernoux, Martial; Roupsard, Olivier; Panferov, Oleg; Le Maire, Guerric; Tölle, Merja; Knohl, Alexander 2014-05-01 Deforestation and forest degradation driven by the expansion of oil palm (Elaeis guineensis) plantations has become the major source of GHG emission in Indonesia. Changes of land surface properties (e.g. vegetation composition, soil property, surface albedo) associated with rainforest to oil palm conversion might alter the patterns of land-atmosphere energy, water and carbon cycles and therefore affect local or regional climate. Land surface modeling has been widely used to characterize the two-way interactions between climate and human disturbances on land surface. The Community Land Model (CLM) is a third-generation land model that simulates a wide range of biogeophysical and biogeochemical processes. This project utilizes the land-cover/land-use change (LCLUC) capability of the latest CLM versions 4/4.5 to characterize quantitatively how anthropogenic land surface dynamics in Indonesia affect land-atmosphere carbon, water and energy fluxes. Before simulating land use changes, the first objective is to parameterize and validate the CLM model at local rainforest and oil palm plantation sites through separate point simulations. This entails creation and parameterization of a new plant functional type (PFT) for oil palm, as well as sensitivity analysis and adaptation of model parameters for the rainforest PFTs. CLM modelled fluxes for the selected sites are to be compared with field observations from eddy covariance (EC) flux towers (e.g. a rainforest site in Bariri, Sulawesi; an oil palm site in Jambi, Sumatra). After validation, the project will proceed to parameterize land-use transformation system using remote sensing data and to simulate the impacts of historical LUCs on carbon, water and energy fluxes. Last but not least, the effects of future LUCs in Indonesia on the fluxes and carbon sequestration capacity will be investigated through scenario study. Historical land cover changes, especially oil palm coverage, are retrieved from Landsat or MODIS archival images. Oil palm concession boundaries are used to define and project future land use scenarios. Initial results include outputs from a single-point simulation for the Bariri rainforest site forced with locally measured meteorological data which already showed significant advantage over global forcing data in predicting net ecosystem exchange and latent and sensible heat fluxes. Modeled fluxes are being compared with EC flux observations and with Mixfor-SVAT model outputs from another project at the same site. In the next few months, focus will be on sensitivity analyses of model parameters including PFT optical, morphological and physiological parameters that are necessary to configure the new oil palm PFT and represent rainforest to oil palm conversion. The new parameterization will contribute to the development of the CLM model and its implementation in the modelling of LUC effects in tropical regions will help understanding land-climate interactions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912459L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912459L">Improving microphysics in a convective parameterization: possibilities and limitations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Labbouz, Laurent; Heikenfeld, Max; Stier, Philip; Morrison, Hugh; Milbrandt, Jason; Protat, Alain; Kipling, Zak 2017-04-01 The convective cloud field model (CCFM) is a convective parameterization implemented in the climate model ECHAM6.1-HAM2.2. It represents a population of clouds within each ECHAM-HAM model column, simulating up to 10 different convective cloud types with individual radius, vertical velocities and microphysical properties. Comparisons between CCFM and radar data at Darwin, Australia, show that in order to reproduce both the convective cloud top height distribution and the vertical velocity profile, the effect of aerodynamic drag on the rising parcel has to be considered, along with a reduced entrainment parameter. A new double-moment microphysics (the Predicted Particle Properties scheme, P3) has been implemented in the latest version of CCFM and is compared to the standard single-moment microphysics and the radar retrievals at Darwin. The microphysical process rates (autoconversion, accretion, deposition, freezing, …) and their response to changes in CDNC are investigated and compared to high resolution CRM WRF simulations over the Amazon region. The results shed light on the possibilities and limitations of microphysics improvements in the framework of CCFM and in convective parameterizations in general. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014APS..DFDH23003R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014APS..DFDH23003R">Anisotropic mesoscale eddy transport in ocean general circulation models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Reckinger, Scott; Fox-Kemper, Baylor; Bachman, Scott; Bryan, Frank; Dennis, John; Danabasoglu, Gokhan 2014-11-01 In modern climate models, the effects of oceanic mesoscale eddies are introduced by relating subgrid eddy fluxes to the resolved gradients of buoyancy or other tracers, where the proportionality is, in general, governed by an eddy transport tensor. The symmetric part of the tensor, which represents the diffusive effects of mesoscale eddies, is universally treated isotropically. However, the diffusive processes that the parameterization approximates, such as shear dispersion and potential vorticity barriers, typically have strongly anisotropic characteristics. Generalizing the eddy diffusivity tensor for anisotropy extends the number of parameters from one to three: major diffusivity, minor diffusivity, and alignment. The Community Earth System Model (CESM) with the anisotropic eddy parameterization is used to test various choices for the parameters, which are motivated by observations and the eddy transport tensor diagnosed from high resolution simulations. Simply setting the ratio of major to minor diffusivities to a value of five globally, while aligning the major axis along the flow direction, improves biogeochemical tracer ventilation and reduces temperature and salinity biases. These effects can be improved by parameterizing the oceanic anisotropic transport mechanisms. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980200853','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980200853">Trade-Wind Cloudiness and Climate</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Randall, David A. 1997-01-01 Closed Mesoscale Cellular Convection (MCC) consists of mesoscale cloud patches separated by narrow clear regions. Strong radiative cooling occurs at the cloud top. A dry two-dimensional Bousinesq model is used to study the effects of cloud-top cooling on convection. Wide updrafts and narrow downdrafts are used to indicate the asymmetric circulations associated with the mesoscale cloud patches. Based on the numerical results, a conceptual model was constructed to suggest a mechanism for the formation of closed MCC over cool ocean surfaces. A new method to estimate the radioative and evaporative cooling in the entrainment layer of a stratocumulus-topped boundary layer has been developed. The method was applied to a set of Large-Eddy Simulation (LES) results and to a set of tethered-balloon data obtained during FIRE. We developed a statocumulus-capped marine mixed layer model which includes a parameterization of drizzle based on the use of a predicted Cloud Condensation Nuclei (CCN) number concentration. We have developed, implemented, and tested a very elaborate new stratiform cloudiness parameterization for use in GCMs. Finally, we have developed a new, mechanistic parameterization of the effects of cloud-top cooling on the entrainment rate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.A23E..04T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.A23E..04T">GCSS/WGNE Pacific Cross-section Intercomparison: Tropical and Subtropical Cloud Transitions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Teixeira, J. 2008-12-01 In this presentation I will discuss the role of the GEWEX Cloud Systems Study (GCSS) working groups in paving the way for substantial improvements in cloud parameterization in weather and climate models. The GCSS/WGNE Pacific Cross-section Intercomparison (GPCI) is an extension of GCSS and is a different type of model evaluation where climate models are analyzed along a Pacific Ocean transect from California to the equator. This approach aims at complementing the more traditional efforts in GCSS by providing a simple framework for the evaluation of models that encompasses several fundamental cloud regimes such as stratocumulus, shallow cumulus and deep cumulus, as well as the transitions between them. Currently twenty four climate and weather prediction models are participating in GPCI. We will present results of the comparison between models and recent satellite data. In particular, we will explore in detail the potential of the Atmospheric Infrared Sounder (AIRS) and CloudSat data for the evaluation of the representation of clouds and convection in climate models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.9031X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.9031X">Climate Simulations from Super-parameterized and Conventional General Circulation Models with a Third-order Turbulence Closure</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Xu, Kuan-Man; Cheng, Anning 2014-05-01 A high-resolution cloud-resolving model (CRM) embedded in a general circulation model (GCM) is an attractive alternative for climate modeling because it replaces all traditional cloud parameterizations and explicitly simulates cloud physical processes in each grid column of the GCM. Such an approach is called "Multiscale Modeling Framework." MMF still needs to parameterize the subgrid-scale (SGS) processes associated with clouds and large turbulent eddies because circulations associated with planetary boundary layer (PBL) and in-cloud turbulence are unresolved by CRMs with horizontal grid sizes on the order of a few kilometers. A third-order turbulence closure (IPHOC) has been implemented in the CRM component of the super-parameterized Community Atmosphere Model (SPCAM). IPHOC is used to predict (or diagnose) fractional cloudiness and the variability of temperature and water vapor at scales that are not resolved on the CRM's grid. This model has produced promised results, especially for low-level cloud climatology, seasonal variations and diurnal variations (Cheng and Xu 2011, 2013a, b; Xu and Cheng 2013a, b). Because of the enormous computational cost of SPCAM-IPHOC, which is 400 times of a conventional CAM, we decided to bypass the CRM and implement the IPHOC directly to CAM version 5 (CAM5). IPHOC replaces the PBL/stratocumulus, shallow convection, and cloud macrophysics parameterizations in CAM5. Since there are large discrepancies in the spatial and temporal scales between CRM and CAM5, IPHOC used in CAM5 has to be modified from that used in SPCAM. In particular, we diagnose all second- and third-order moments except for the fluxes. These prognostic and diagnostic moments are used to select a double-Gaussian probability density function to describe the SGS variability. We also incorporate a diagnostic PBL height parameterization to represent the strong inversion above PBL. The goal of this study is to compare the simulation of the climatology from these three models (CAM5, CAM5-IPHOC and SPCAM-IPHOC), with emphasis on low-level clouds and precipitation. Detailed comparisons of scatter diagrams among the monthly-mean low-level cloudiness, PBL height, surface relative humidity and lower tropospheric stability (LTS) reveal the relative strengths and weaknesses for five coastal low-cloud regions among the three models. Observations from CloudSat and CALIPSO and ECMWF Interim reanalysis are used as the truths for the comparisons. We found that the standard CAM5 underestimates cloudiness and produces small cloud fractions at low PBL heights that contradict with observations. CAM5-IPHOC tends to overestimate low clouds but the ranges of LTS and PBL height variations are most realistic. SPCAM-IPHOC seems to produce most realistic results with relatively consistent results from one region to another. Further comparisons with other atmospheric environmental variables will be helpful to reveal the causes of model deficiencies so that SPCAM-IPHOC results will provide guidance to the other two models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1011224','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1011224">Uncertainty quantification of US Southwest climate from IPCC projections.</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Boslough, Mark Bruce Elrick 2011-01-01 The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) made extensive use of coordinated simulations by 18 international modeling groups using a variety of coupled general circulation models (GCMs) with different numerics, algorithms, resolutions, physics models, and parameterizations. These simulations span the 20th century and provide forecasts for various carbon emissions scenarios in the 21st century. All the output from this panoply of models is made available to researchers on an archive maintained by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at LLNL. I have downloaded this data and completed the first steps toward a statisticalmore » analysis of these ensembles for the US Southwest. This constitutes the final report for a late start LDRD project. Complete analysis will be the subject of a forthcoming report.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/46838','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/46838">Parameterization of the 3-PG model for Pinus elliottii stands using alternative methods to estimate fertility rating, biomass partitioning and canopy closure</a> <a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Carlos A. Gonzalez-Benecke; Eric J. Jokela; Wendell P. Cropper; Rosvel Bracho; Daniel J. Leduc 2014-01-01 The forest simulation model, 3-PG, has been widely applied as a useful tool for predicting growth of forest species in many countries. The model has the capability to estimate the effects of management, climate and site characteristics on many stand attributes using easily available data. Currently, there is an increasing interest in estimating biomass and assessing... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H52C..02R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H52C..02R">Towards a more efficient and robust representation of subsurface hydrological processes in Earth System Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rosolem, R.; Rahman, M.; Kollet, S. J.; Wagener, T. 2017-12-01 Understanding the impacts of land cover and climate changes on terrestrial hydrometeorology is important across a range of spatial and temporal scales. Earth System Models (ESMs) provide a robust platform for evaluating these impacts. However, current ESMs lack the representation of key hydrological processes (e.g., preferential water flow, and direct interactions with aquifers) in general. The typical "free drainage" conceptualization of land models can misrepresent the magnitude of those interactions, consequently affecting the exchange of energy and water at the surface as well as estimates of groundwater recharge. Recent studies show the benefits of explicitly simulating the interactions between subsurface and surface processes in similar models. However, such parameterizations are often computationally demanding resulting in limited application for large/global-scale studies. Here, we take a different approach in developing a novel parameterization for groundwater dynamics. Instead of directly adding another complex process to an established land model, we examine a set of comprehensive experimental scenarios using a very robust and establish three-dimensional hydrological model to develop a simpler parameterization that represents the aquifer to land surface interactions. The main goal of our developed parameterization is to simultaneously maximize the computational gain (i.e., "efficiency") while minimizing simulation errors in comparison to the full 3D model (i.e., "robustness") to allow for easy implementation in ESMs globally. Our study focuses primarily on understanding both the dynamics for groundwater recharge and discharge, respectively. Preliminary results show that our proposed approach significantly reduced the computational demand while model deviations from the full 3D model are considered to be small for these processes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.6369M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.6369M">Splitting turbulence algorithm for mixing parameterization embedded in the ocean climate model. Examples of data assimilation and Prandtl number variations.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Moshonkin, Sergey; Gusev, Anatoly; Zalesny, Vladimir; Diansky, Nikolay 2017-04-01 Series of experiments were performed with a three-dimensional, free surface, sigma coordinate eddy-permitting ocean circulation model for Atlantic (from 30°S) - Arctic and Bering sea domain (0.25 degrees resolution, Institute of Numerical Mathematics Ocean Model or INMOM) using vertical grid refinement in the zone of fully developed turbulence (40 sigma-levels). The model variables are horizontal velocity components, potential temperature, and salinity as well as free surface height. For parameterization of viscosity and diffusivity, the original splitting turbulence algorithm (STA) is used when total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF) split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage the analytical solution was obtained for TKE and TDF as functions of the buoyancy and velocity shift frequencies (BF and VSF). The proposed model with STA is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. For mixing simulation in the zone of turbulence decay, the two kind numerical experiments were carried out, as with assimilation of annual mean climatic buoyancy frequency, as with variation of Prandtl number function dependence upon the BF, VSF, TKE and TDF. The CORE-II data for 1948-2009 were used for experiments. Quality of temperature T and salinity S structure simulation is estimated by the comparison of model monthly profiles T and S averaged for 1980-2009, with T and S monthly data from the World Ocean Atlas 2013. Form of coefficients in equations for TKE and TDF on the generation-dissipation stage makes it possible to assimilate annual mean climatic buoyancy frequency in a varying degree that cardinally improves adequacy of model results to climatic data in all analyzed model domain. The numerical experiments with modified Prandtl number presents possibility for essential improvement of the TKE attenuation with depth and more realistic water entrainment from pycnocline into the mixed layer. The high sensitivity is revealed of the eddy-permitting circulation stable model solution to the change of the used above mixing parameterizations. This sensitivity is connected with significant changes of density fields in the upper baroclinic ocean layer over the total considered area. For instance, assimilation of annual mean climatic buoyancy frequency in equations for TKE and TDF leads to more realistic circulation in the North Atlantic. Variations of Prandtl number made it possible to simulate intense circulation in Beaufort Gyre owing to steric effect during the whole period under consideration. The research was supported by the Russian Foundation for Basic Research (grants №16-05-00534 and 15-05-00557). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A51N0274N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A51N0274N">Role of clouds, aerosols, and aerosol-cloud interaction in 20th century simulations with GISS ModelE2</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Nazarenko, L.; Rind, D. H.; Bauer, S.; Del Genio, A. D. 2015-12-01 Simulations of aerosols, clouds and their interaction contribute to the major source of uncertainty in predicting the changing Earth's energy and in estimating future climate. Anthropogenic contribution of aerosols affects the properties of clouds through aerosol indirect effects. Three different versions of NASA GISS global climate model are presented for simulation of the twentieth century climate change. All versions have fully interactive tracers of aerosols and chemistry in both the troposphere and stratosphere. All chemical species are simulated prognostically consistent with atmospheric physics in the model and the emissions of short-lived precursors [Shindell et al., 2006]. One version does not include the aerosol indirect effect on clouds. The other two versions include a parameterization of the interactive first indirect aerosol effect on clouds following Menon et al. [2010]. One of these two models has the Multiconfiguration Aerosol Tracker of Mixing state (MATRIX) that permits detailed treatment of aerosol mixing state, size, and aerosol-cloud activation. The main purpose of this study is evaluation of aerosol-clouds interactions and feedbacks, as well as cloud and aerosol radiative forcings, for the twentieth century climate under different assumptions and parameterizations for aerosol, clouds and their interactions in the climate models. The change of global surface air temperature based on linear trend ranges from +0.8°C to +1.2°C between 1850 and 2012. Water cloud optical thickness increases with increasing temperature in all versions with the largest increase in models with interactive indirect effect of aerosols on clouds, which leads to the total (shortwave and longwave) cloud radiative cooling trend at the top of the atmosphere. Menon, S., D. Koch, G. Beig, S. Sahu, J. Fasullo, and D. Orlikowski (2010), Black carbon aerosols and the third polar ice cap, Atmos. Chem. Phys., 10,4559-4571, doi:10.5194/acp-10-4559-2010. Shindell, D., G. Faluvegi, N. Unger, E. Aguilar, G.A. Schmidt, D.M. Koch, S.E. Bauer, and J.R. Miller (2006), Simulations of preindustrial, present-day, and 2100 conditions in the NASA GISS composition and climate model G-PUCCINI, Atmos. Chem. Phys., 6, 4427-4459. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ACP....14.9403V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ACP....14.9403V">Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Vihma, T.; Pirazzini, R.; Fer, I.; Renfrew, I. A.; Sedlar, J.; Tjernström, M.; Lüpkes, C.; Nygård, T.; Notz, D.; Weiss, J.; Marsan, D.; Cheng, B.; Birnbaum, G.; Gerland, S.; Chechin, D.; Gascard, J. C. 2014-09-01 The Arctic climate system includes numerous highly interactive small-scale physical processes in the atmosphere, sea ice, and ocean. During and since the International Polar Year 2007-2009, significant advances have been made in understanding these processes. Here, these recent advances are reviewed, synthesized, and discussed. In atmospheric physics, the primary advances have been in cloud physics, radiative transfer, mesoscale cyclones, coastal, and fjordic processes as well as in boundary layer processes and surface fluxes. In sea ice and its snow cover, advances have been made in understanding of the surface albedo and its relationships with snow properties, the internal structure of sea ice, the heat and salt transfer in ice, the formation of superimposed ice and snow ice, and the small-scale dynamics of sea ice. For the ocean, significant advances have been related to exchange processes at the ice-ocean interface, diapycnal mixing, double-diffusive convection, tidal currents and diurnal resonance. Despite this recent progress, some of these small-scale physical processes are still not sufficiently understood: these include wave-turbulence interactions in the atmosphere and ocean, the exchange of heat and salt at the ice-ocean interface, and the mechanical weakening of sea ice. Many other processes are reasonably well understood as stand-alone processes but the challenge is to understand their interactions with and impacts and feedbacks on other processes. Uncertainty in the parameterization of small-scale processes continues to be among the greatest challenges facing climate modelling, particularly in high latitudes. Further improvements in parameterization require new year-round field campaigns on the Arctic sea ice, closely combined with satellite remote sensing studies and numerical model experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013ACPD...1332703V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013ACPD...1332703V">Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Vihma, T.; Pirazzini, R.; Renfrew, I. A.; Sedlar, J.; Tjernström, M.; Nygård, T.; Fer, I.; Lüpkes, C.; Notz, D.; Weiss, J.; Marsan, D.; Cheng, B.; Birnbaum, G.; Gerland, S.; Chechin, D.; Gascard, J. C. 2013-12-01 The Arctic climate system includes numerous highly interactive small-scale physical processes in the atmosphere, sea ice, and ocean. During and since the International Polar Year 2007-2008, significant advances have been made in understanding these processes. Here these advances are reviewed, synthesized and discussed. In atmospheric physics, the primary advances have been in cloud physics, radiative transfer, mesoscale cyclones, coastal and fjordic processes, as well as in boundary-layer processes and surface fluxes. In sea ice and its snow cover, advances have been made in understanding of the surface albedo and its relationships with snow properties, the internal structure of sea ice, the heat and salt transfer in ice, the formation of super-imposed ice and snow ice, and the small-scale dynamics of sea ice. In the ocean, significant advances have been related to exchange processes at the ice-ocean interface, diapycnal mixing, tidal currents and diurnal resonance. Despite this recent progress, some of these small-scale physical processes are still not sufficiently understood: these include wave-turbulence interactions in the atmosphere and ocean, the exchange of heat and salt at the ice-ocean interface, and the mechanical weakening of sea ice. Many other processes are reasonably well understood as stand-alone processes but challenge is to understand their interactions with, and impacts and feedbacks on, other processes. Uncertainty in the parameterization of small-scale processes continues to be among the largest challenges facing climate modeling, and nowhere is this more true than in the Arctic. Further improvements in parameterization require new year-round field campaigns on the Arctic sea ice, closely combined with satellite remote sensing studies and numerical model experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020061380','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020061380">Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Tao, W. K.; Wang, Y.; Qian, J.; Shie, C. -L.; Lau, W. K. -M.; Kakar, R.; Starr, David O' C. (Technical Monitor) 2002-01-01 The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100015393','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100015393">High-Latitude Stratospheric Sensitivity to QBO Width in a Chemistry-Climate Model with Parameterized Ozone Chemistry</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hurwitz, M. M.; Braesicke, P.; Pyle, J. A. 2010-01-01 In a pair of idealized simulations with a simplified chemistry-climate model, the sensitivity of the wintertime Arctic stratosphere to variability in the width of the quasi-biennial oscillation (QBO) is assessed. The width of the QBO appears to have equal influence on the Arctic stratosphere as does the phase (i.e. the Holton-Tan mechanism). In the model, a wider QBO acts like a preferential shift toward the easterly phase of the QBO, where zonal winds at 60 N tend to be relatively weaker, while 50 hPa geopotential heights and polar ozone values tend to be higher. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007ACP.....7.2183C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007ACP.....7.2183C">A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Cariolle, D.; Teyssèdre, H. 2007-05-01 This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2-D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory work. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the solution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000-2004. Overall, the results from the two versions show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small, of the order of 10%. The model also reproduces fairly well the polar ozone variability, notably the formation of "ozone holes" in the Southern Hemisphere with amplitudes and a seasonal evolution that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone content inside the polar vortex of the Southern Hemisphere over longer periods in spring time. It is concluded that for the study of climate scenarios or the assimilation of ozone data, the present parameterization gives a valuable alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20080722','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20080722">High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Majda, Andrew J; Abramov, Rafail; Gershgorin, Boris 2010-01-12 Climate change science focuses on predicting the coarse-grained, planetary-scale, longtime changes in the climate system due to either changes in external forcing or internal variability, such as the impact of increased carbon dioxide. The predictions of climate change science are carried out through comprehensive, computational atmospheric, and oceanic simulation models, which necessarily parameterize physical features such as clouds, sea ice cover, etc. Recently, it has been suggested that there is irreducible imprecision in such climate models that manifests itself as structural instability in climate statistics and which can significantly hamper the skill of computer models for climate change. A systematic approach to deal with this irreducible imprecision is advocated through algorithms based on the Fluctuation Dissipation Theorem (FDT). There are important practical and computational advantages for climate change science when a skillful FDT algorithm is established. The FDT response operator can be utilized directly for multiple climate change scenarios, multiple changes in forcing, and other parameters, such as damping and inverse modelling directly without the need of running the complex climate model in each individual case. The high skill of FDT in predicting climate change, despite structural instability, is developed in an unambiguous fashion using mathematical theory as guidelines in three different test models: a generic class of analytical models mimicking the dynamical core of the computer climate models, reduced stochastic models for low-frequency variability, and models with a significant new type of irreducible imprecision involving many fast, unstable modes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70022396','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70022396">Modelling carbon responses of tundra ecosystems to historical and projected climate: A comparison of a plot- and a global-scale ecosystem model to identify process-based uncertainties</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Clein, Joy S.; Kwiatkowski, B.L.; McGuire, A.D.; Hobbie, J.E.; Rastetter, E.B.; Melillo, J.M.; Kicklighter, D.W. 2000-01-01 We are developing a process-based modelling approach to investigate how carbon (C) storage of tundra across the entire Arctic will respond to projected climate change. To implement the approach, the processes that are least understood, and thus have the most uncertainty, need to be identified and studied. In this paper, we identified a key uncertainty by comparing the responses of C storage in tussock tundra at one site between the simulations of two models - one a global-scale ecosystem model (Terrestrial Ecosystem Model, TEM) and one a plot-scale ecosystem model (General Ecosystem Model, GEM). The simulations spanned the historical period (1921-94) and the projected period (1995-2100). In the historical period, the model simulations of net primary production (NPP) differed in their sensitivity to variability in climate. However, the long-term changes in C storage were similar in both simulations, because the dynamics of heterotrophic respiration (RH) were similar in both models. In contrast, the responses of C storage in the two model simulations diverged during the projected period. In the GEM simulation for this period, increases in RH tracked increases in NPP, whereas in the TEM simulation increases in RH lagged increases in NPP. We were able to make the long-term C dynamics of the two simulations agree by parameterizing TEM to the fast soil C pools of GEM. We concluded that the differences between the long-term C dynamics of the two simulations lay in modelling the role of the recalcitrant soil C. These differences, which reflect an incomplete understanding of soil processes, lead to quite different projections of the response of pan-Arctic C storage to global change. For example, the reference parameterization of TEM resulted in an estimate of cumulative C storage of 2032 g C m-2 for moist tundra north of 50??N, which was substantially higher than the 463 g C m-2 estimated for a parameterization of fast soil C dynamics. This uncertainty in the depiction of the role of recalcitrant soil C in long-term ecosystem C dynamics resulted from our incomplete understanding of controls over C and N transformations in Arctic soils. Mechanistic studies of these issues are needed to improve our ability to model the response of Arctic ecosystems to global change. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active">15</li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active">16</li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3527538','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3527538">Projecting Range Limits with Coupled Thermal Tolerance - Climate Change Models: An Example Based on Gray Snapper (Lutjanus griseus) along the U.S. East Coast</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Hare, Jonathan A.; Wuenschel, Mark J.; Kimball, Matthew E. 2012-01-01 We couple a species range limit hypothesis with the output of an ensemble of general circulation models to project the poleward range limit of gray snapper. Using laboratory-derived thermal limits and statistical downscaling from IPCC AR4 general circulation models, we project that gray snapper will shift northwards; the magnitude of this shift is dependent on the magnitude of climate change. We also evaluate the uncertainty in our projection and find that statistical uncertainty associated with the experimentally-derived thermal limits is the largest contributor (∼ 65%) to overall quantified uncertainty. This finding argues for more experimental work aimed at understanding and parameterizing the effects of climate change and variability on marine species. PMID:23284974 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=335441&keyword=cmaq&acttype=product&timstype=journal&timssubtypeid=+&deid=&epanumber=&ntisid=&archivestatus=both&ombcat=any&datebegincreated=&dateendcreated=&datebeginpublishedpresented=&dateendpublishedpresented=&datebeginupdated=&dateendupdated=&datebegincompleted=&dateendcompleted=&view=citation%20&personid=&role=any&journalid=&publisherid=&sortby=fy&count=25&cfid=77182256&cftoken=94527145','PESTICIDES'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=335441&keyword=cmaq&acttype=product&timstype=journal&timssubtypeid=+&deid=&epanumber=&ntisid=&archivestatus=both&ombcat=any&datebegincreated=&dateendcreated=&datebeginpublishedpresented=&dateendpublishedpresented=&datebeginupdated=&dateendupdated=&datebegincompleted=&dateendcompleted=&view=citation%20&personid=&role=any&journalid=&publisherid=&sortby=fy&count=25&cfid=77182256&cftoken=94527145">Enhanced representation of soil NO emissions in the ...</a> <a target="_blank" rel="noopener noreferrer" href="http://www.epa.gov/pesticides/search.htm">EPA Pesticide Factsheets</a> Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19840051365&hterms=climate+exchange&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dclimate%2Bexchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19840051365&hterms=climate+exchange&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dclimate%2Bexchange">An energy balance climate model with cloud feedbacks</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Roads, J. O.; Vallis, G. K. 1984-01-01 The present two-level global climate model, which is based on the atmosphere-surface energy balance, includes physically based parameterizations for the exchange of heat and moisture across latitude belts and between the surface and the atmosphere, precipitation and cloud formation, and solar and IR radiation. The model field predictions obtained encompass surface and atmospheric temperature, precipitation, relative humidity, and cloudiness. In the model integrations presented, it is noted that cloudiness is generally constant with changing temperature at low latitudes. High altitude cloudiness increases with temperature, although the cloud feedback effect on the radiation field remains small because of compensating effects on thermal and solar radiation. The net global feedback by the cloud field is negative, but small. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18853818','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18853818">Parametric assessment of climate change impacts of automotive material substitution.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Geyer, Roland 2008-09-15 Quantifying the net climate change impact of automotive material substitution is not a trivial task. It requires the assessment of the mass reduction potential of automotive materials, the greenhouse gas (GHG) emissions from their production and recycling, and their impact on GHG emissions from vehicle use. The model presented in this paper is based on life cycle assessment (LCA) and completely parameterized, i.e., its computational structure is separated from the required input data, which is not traditionally done in LCAs. The parameterization increases scientific rigor and transparency of the assessment methodology, facilitates sensitivity and uncertainty analysis of the results, and also makes it possible to compare different studies and explain their disparities. The state of the art of the modeling methodology is reviewed and advanced. Assessment of the GHG emission impacts of material recycling through consequential system expansion shows that our understanding of this issue is still incomplete. This is a critical knowledge gap since a case study shows thatfor materials such as aluminum, the GHG emission impacts of material production and recycling are both of the same size as the use phase savings from vehicle mass reduction. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A13B0327G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A13B0327G">Biases in field measurements of ice nuclei concentrations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Garimella, S.; Voigtländer, J.; Kulkarni, G.; Stratmann, F.; Cziczo, D. J. 2015-12-01 Ice nuclei (IN) play an important role in the climate system by influencing cloud properties, precipitation, and radiative transfer. Despite their importance, there are significant uncertainties in estimating IN concentrations because of the complexities of atmospheric ice nucleation processes. Field measurements of IN concentrations with Continuous Flow Diffusion Chamber (CFDC) IN counters have been vital to constrain IN number concentrations and have led to various parameterizations of IN number vs. temperature and particle concentration. These parameterizations are used in many global climate models, which are very sensitive to the treatment of cloud microphysics. However, due to non-idealities in CFDC behavior, especially at high relative humidity, many of these measurements are likely biased too low. In this study, the extent of this low bias is examined with laboratory experiments at a variety of instrument conditions using the SPectrometer for Ice Nucleation, a commercially-available CFDC-style chamber. These laboratory results are compared to theoretical calculations and computational fluid dynamics models to map the variability of this bias as a function of chamber temperature and relative humidity. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010110948','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010110948">Technical Report Series on Global Modeling and Data Assimilation. Volume 20; The Climate of the FVCCM-3 Model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Suarez, Max J. (Editor); Chang, Yehui; Schubert, Siegfried D.; Lin, Shian-Jiann; Nebuda, Sharon; Shen, Bo-Wen 2001-01-01 This document describes the climate of version 1 of the NASA-NCAR model developed at the Data Assimilation Office (DAO). The model consists of a new finite-volume dynamical core and an implementation of the NCAR climate community model (CCM-3) physical parameterizations. The version of the model examined here was integrated at a resolution of 2 degrees latitude by 2.5 degrees longitude and 32 levels. The results are based on assimilation that was forced with observed sea surface temperature and sea ice for the period 1979-1995, and are compared with NCEP/NCAR reanalyses and various other observational data sets. The results include an assessment of seasonal means, subseasonal transients including the Madden Julian Oscillation, and interannual variability. The quantities include zonal and meridional winds, temperature, specific humidity, geopotential height, stream function, velocity potential, precipitation, sea level pressure, and cloud radiative forcing. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H23C1668D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H23C1668D">Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dong, J.; Ek, M. B.; Wei, H.; Meng, J. 2017-12-01 Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1226494','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1226494">Final Report Collaborative Project. Improving the Representation of Coastal and Estuarine Processes in Earth System Models</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Bryan, Frank; Dennis, John; MacCready, Parker This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. Tomore » develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900032299&hterms=Hogg&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DHogg','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900032299&hterms=Hogg&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DHogg">Observed reflectivities and liquid water content for marine stratocumulus</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Coakley, J. A., Jr.; Snider, J. B. 1989-01-01 Simultaneous observations of cloud liquid water content and cloud reflectivity are used to verify their parametric relationship in a manner consistent with simple parameterizations often used in general-circulation climate models. The column amount of cloud liquid water was measured with a microwave radiometer on San Nicolas Island as described by Hogg et al., (1983). Cloud reflectivity was obtained through spatial coherence analysis of AVHRR imagery data as per Coakley and Baldwin (1984) and Coakley and Beckner (1988). The dependence of the observed reflectivity on the observed liquid water is discussed, and this empirical relationship is compared with the parameterization proposed by Stephens (1978). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC23F0978B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC23F0978B">Robust Emergent Climate Phenomena Associated with the High-Sensitivity Tail</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Boslough, M.; Levy, M.; Backus, G. 2010-12-01 Because the potential effects of climate change are more severe than had previously been thought, increasing focus on uncertainty quantification is required for risk assessment needed by policy makers. Current scientific efforts focus almost exclusively on establishing best estimates of future climate change. However, the greatest consequences occur in the extreme tail of the probability density functions for climate sensitivity (the “high-sensitivity tail”). To this end, we are exploring the impacts of newly postulated, highly uncertain, but high-consequence physical mechanisms to better establish the climate change risk. We define consequence in terms of dramatic change in physical conditions and in the resulting socioeconomic impact (hence, risk) on populations. Although we are developing generally applicable risk assessment methods, we have focused our initial efforts on uncertainty and risk analyses for the Arctic region. Instead of focusing on best estimates, requiring many years of model parameterization development and evaluation, we are focusing on robust emergent phenomena (those that are not necessarily intuitive and are insensitive to assumptions, subgrid-parameterizations, and tunings). For many physical systems, under-resolved models fail to generate such phenomena, which only develop when model resolution is sufficiently high. Our ultimate goal is to discover the patterns of emergent climate precursors (those that cannot be predicted with lower-resolution models) that can be used as a "sensitivity fingerprint" and make recommendations for a climate early warning system that would use satellites and sensor arrays to look for the various predicted high-sensitivity signatures. Our initial simulations are focused on the Arctic region, where underpredicted phenomena such as rapid loss of sea ice are already emerging, and because of major geopolitical implications associated with increasing Arctic accessibility to natural resources, shipping routes, and strategic locations. We anticipate that regional climate will be strongly influenced by feedbacks associated with a seasonally ice-free Arctic, but with unknown emergent phenomena. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE-AC04-94AL85000. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1091952','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1091952"></a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Mitchell, David L. It is well known that cirrus clouds play a major role in regulating the earth’s climate, but the details of how this works are just beginning to be understood. This project targeted the main property of cirrus clouds that influence climate processes; the ice fall speed. That is, this project improves the representation of the mass-weighted ice particle fall velocity, V m, in climate models, used to predict future climate on global and regional scales. Prior to 2007, the dominant sizes of ice particles in cirrus clouds were poorly understood, making it virtually impossible to predict how cirrus clouds interactmore » with sunlight and thermal radiation. Due to several studies investigating the performance of optical probes used to measure the ice particle size distribution (PSD), as well as the remote sensing results from our last ARM project, it is now well established that the anomalously high concentrations of small ice crystals often reported prior to 2007 were measurement artifacts. Advances in the design and data processing of optical probes have greatly reduced these ice artifacts that resulted from the shattering of ice particles on the probe tips and/or inlet tube, and PSD measurements from one of these improved probes (the 2-dimensional Stereo or 2D-S probe) are utilized in this project to parameterize V m for climate models. Our original plan in the proposal was to parameterize the ice PSD (in terms of temperature and ice water content) and ice particle mass and projected area (in terms of mass- and area-dimensional power laws or m-D/A-D expressions) since these are the microphysical properties that determine V m, and then proceed to calculate V m from these parameterized properties. But the 2D-S probe directly measures ice particle projected area and indirectly estimates ice particle mass for each size bin. It soon became apparent that the original plan would introduce more uncertainty in the V m calculations than simply using the 2D-S measurements to directly calculate V m. By calculating V m directly from the measured PSD, ice particle projected area and estimated mass, more accurate estimates of V m are obtained. These V m values were then parameterized for climate models by relating them to (1) sampling temperature and ice water content (IWC) and (2) the effective diameter (D e) of the ice PSD. Parameterization (1) is appropriate for climate models having single-moment microphysical schemes whereas (2) is appropriate for double-moment microphysical schemes and yields more accurate V m estimates. These parameterizations were developed for tropical cirrus clouds, Arctic cirrus, mid-latitude synoptic cirrus and mid-latitude anvil cirrus clouds based on field campaigns in these regions. An important but unexpected result of this research was the discovery of microphysical evidence indicating the mechanisms by which ice crystals are produced in cirrus clouds. This evidence, derived from PSD measurements, indicates that homogeneous freezing ice nucleation dominates in mid-latitude synoptic cirrus clouds, whereas heterogeneous ice nucleation processes dominate in mid-latitude anvil cirrus. Based on these findings, D e was parameterized in terms of temperature (T) for conditions dominated by (1) homo- and (2) heterogeneous ice nucleation. From this, an experiment was designed for global climate models (GCMs). The net radiative forcing from cirrus clouds may be affected by the means ice is produced (homo- or heterogeneously), and this net forcing contributes to climate sensitivity (i.e. the change in mean global surface temperature resulting from a doubling of CO 2). The objective of this GCM experiment was to determine how a change in ice nucleation mode affects the predicted global radiation balance. In the first simulation (Run 1), the D e-T relationship for homogeneous nucleation is used at all latitudes, while in the second simulation (Run 2), the D e-T relationship for heterogeneous nucleation is used at all latitudes. For both runs, V m is calculated from D e. Two GCMs were used; the Community Atmosphere Model version 5 (CAM5) and a European GCM known as ECHAM5 (thanks to our European colleagues who collaborated with us). Similar results were obtained from both GCMs in the Northern Hemisphere mid-latitudes, with a net cooling of ~ 1.0 W m -2 due to heterogeneous nucleation, relative to Run 1. The mean global net cooling was 2.4 W m -2 for the ECHAM5 GCM while CAM5 produced a mean global net cooling of about 0.8 W m -2. This dependence of the radiation balance on nucleation mode is substantial when one considers the direct radiative forcing from a CO 2 doubling is 4 W m -2. The differences between GCMs in mean global net cooling estimates may demonstrate a need for improving the representation of cirrus clouds in GCMs, including the coupling between microphysical and radiative properties. Unfortunately, after completing this GCM experiment, we learned from the company that provided the 2D-S microphysical data that the data was corrupted due to a computer program coding problem. Therefore the microphysical data had to be reprocessed and reanalyzed, and the GCM experiments were redone under our current ASR project but using an improved experimental design.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29666237','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29666237">GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Schiro, Kathleen A; Ahmed, Fiaz; Giangrande, Scott E; Neelin, J David 2018-05-01 A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014-2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation-buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1810017V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1810017V">A review on regional convection permitting climate modeling</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin 2016-04-01 With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing <4 km, is that they better resolve complex orography and land use. The regional climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies are addressed in future research. Coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs. Brisson, E., K. Van Weverberg, M. Demuzere, A. Devis, S. Saeed, M. Stengel, N.P.M. van Lipzig, 2016. How well can a convection-permitting climate model reproduce 1 decadal statistics of precipitation, temperature and cloud characteristics? Clim. Dyn. (minor revisions). Prein, Andreas F., Wolfgang Langhans, Giorgia Fosser, Andrew Ferrone, Nikolina Ban, Klaus Goergen, Michael Keller, Merja Tölle, Oliver Gutjahr, Frauke Feser, Erwan Brisson, Stefan Kollet, Juerg Schmidli, Nicole P. M. van Lipzig, Ruby Leung. (2015) A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of Geophysics 53:10.1002/rog.v53.2, 323-361 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESSD...810151V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESSD...810151V">Influence of feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> van Walsum, P. E. V. 2011-11-01 Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a good soil or from capillary rise. With good supply of moisture, the dynamic model simulates up to 10% less actual evapotranspiration than the static one in the example. This can lead to cases where the dynamic model predicts a slight increase of the recharge in a climate scenario, where the static model predicts a decrease. The use of a dynamic model also affects the simulated demand for surface water from external sources; especially the timing is affected. The proposed modelling approach uses postulated relationships that require validation with controlled field trials. In the Netherlands there is a lack of experimental facilities for performing such validations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/859951-future-sulfur-dioxide-emissions','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/859951-future-sulfur-dioxide-emissions">Future Sulfur Dioxide Emissions</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Smith, Steven J.; Pitcher, Hugh M.; Wigley, Tom M. 2005-12-01 The importance of sulfur dioxide emissions for climate change is now established, although substantial uncertainties remain. This paper presents projections for future sulfur dioxide emissions using the MiniCAM integrated assessment model. A new income-based parameterization for future sulfur dioxide emissions controls is developed based on purchasing power parity (PPP) income estimates and historical trends related to the implementation of sulfur emissions limitations. This parameterization is then used to produce sulfur dioxide emissions trajectories for the set of scenarios developed for the Special Report on Emission Scenarios (SRES). We use the SRES methodology to produce harmonized SRES scenarios using the latestmore » version of the MiniCAM model. The implications, and requirements, for IA modeling of sulfur dioxide emissions are discussed. We find that sulfur emissions eventually decline over the next century under a wide set of assumptions. These emission reductions result from a combination of emission controls, the adoption of advanced electric technologies, and a shift away from the direct end use of coal with increasing income levels. Only under a scenario where incomes in developing regions increase slowly do global emission levels remain at close to present levels over the next century. Under a climate policy that limits emissions of carbon dioxide, sulfur dioxide emissions fall in a relatively narrow range. In all cases, the relative climatic effect of sulfur dioxide emissions decreases dramatically to a point where sulfur dioxide is only a minor component of climate forcing by the end of the century. Ecological effects of sulfur dioxide, however, could be significant in some developing regions for many decades to come.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C44A..07D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C44A..07D">Bayesian prediction of future ice sheet volume using local approximation Markov chain Monte Carlo methods</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Davis, A. D.; Heimbach, P.; Marzouk, Y. 2017-12-01 We develop a Bayesian inverse modeling framework for predicting future ice sheet volume with associated formal uncertainty estimates. Marine ice sheets are drained by fast-flowing ice streams, which we simulate using a flowline model. Flowline models depend on geometric parameters (e.g., basal topography), parameterized physical processes (e.g., calving laws and basal sliding), and climate parameters (e.g., surface mass balance), most of which are unknown or uncertain. Given observations of ice surface velocity and thickness, we define a Bayesian posterior distribution over static parameters, such as basal topography. We also define a parameterized distribution over variable parameters, such as future surface mass balance, which we assume are not informed by the data. Hyperparameters are used to represent climate change scenarios, and sampling their distributions mimics internal variation. For example, a warming climate corresponds to increasing mean surface mass balance but an individual sample may have periods of increasing or decreasing surface mass balance. We characterize the predictive distribution of ice volume by evaluating the flowline model given samples from the posterior distribution and the distribution over variable parameters. Finally, we determine the effect of climate change on future ice sheet volume by investigating how changing the hyperparameters affects the predictive distribution. We use state-of-the-art Bayesian computation to address computational feasibility. Characterizing the posterior distribution (using Markov chain Monte Carlo), sampling the full range of variable parameters and evaluating the predictive model is prohibitively expensive. Furthermore, the required resolution of the inferred basal topography may be very high, which is often challenging for sampling methods. Instead, we leverage regularity in the predictive distribution to build a computationally cheaper surrogate over the low dimensional quantity of interest (future ice sheet volume). Continual surrogate refinement guarantees asymptotic sampling from the predictive distribution. Directly characterizing the predictive distribution in this way allows us to assess the ice sheet's sensitivity to climate variability and change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A21H2252W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A21H2252W">The effect of different spectral shape parameterizations of cloud droplet size distribution on first and second aerosol indirect effects in NACR CAM5 and evaluation with satellite data</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, M.; Peng, Y.; Xie, X.; Liu, Y. 2017-12-01 Aerosol cloud interaction continues to constitute one of the most significant uncertainties for anthropogenic climate perturbations. The parameterization of cloud droplet size distribution and autoconversion process from large scale cloud to rain can influence the estimation of first and second aerosol indirect effects in global climate models. We design a series of experiments focusing on the microphysical cloud scheme of NCAR CAM5 (Community Atmospheric Model Version 5) in transient historical run with realistic sea surface temperature and sea ice. We investigate the effect of three empirical, two semi-empirical and one analytical expressions for droplet size distribution on cloud properties and explore the statistical relationships between aerosol optical thickness (AOT) and simulated cloud variables, including cloud top droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP). We also introduce the droplet spectral shape parameter into the autoconversion process to incorporate the effect of droplet size distribution on second aerosol indirect effect. Three satellite datasets (MODIS Terra/ MODIS Aqua/ AVHRR) are used to evaluate the simulated aerosol indirect effect from the model. Evident CDER decreasing with significant AOT increasing is found in the east coast of China to the North Pacific Ocean and the east coast of USA to the North Atlantic Ocean. Analytical and semi-empirical expressions for spectral shape parameterization show stronger first aerosol indirect effect but weaker second aerosol indirect effect than empirical expressions because of the narrower droplet size distribution. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70159196','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70159196">Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Wildhaber, Mark L.; Wikle, Christopher K.; Moran, Edward H.; Anderson, Christopher J.; Franz, Kristie J.; Dey, Rima 2017-01-01 We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere – ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, cli- mate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation and can account for spatio-temporal variability in the intervening stages. The goal is a framework to determine whether, given uncertainties in the climate models and the biological response, meaningful inference can still be made. The non-linear downscaling of climate information to the river scale requires that one realistically account for spatial and temporal variability across scale. Our down- scaling procedure includes the use of fixed/calibrated hydrological flow and temperature models coupled with a stochastically parameterized sturgeon bioenergetics model. We show that, although there is a large amount of uncertainty associated with both the climate model output and the fish growth process, one can establish significant differences in fish growth distributions between models, and between future and current climates for a given model. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70146562','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70146562">Projection of wave conditions in response to climate change: A community approach to global and regional wave downscaling</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Erikson, Li H.; Hemer, M.; Lionello, Piero; Mendez, Fernando J.; Mori, Nobuhito; Semedo, Alvaro; Wang, Xiaolan; Wolf, Judith 2015-01-01 Future changes in wind-wave climate have broad implications for coastal geomorphology and management. General circulation models (GCM) are now routinely used for assessing climatological parameters, but generally do not provide parameterizations of ocean wind-waves. To fill this information gap, a growing number of studies use GCM outputs to independently downscale wave conditions to global and regional levels. To consolidate these efforts and provide a robust picture of projected changes, we present strategies from the community-derived multi-model ensemble of wave climate projections (COWCLIP) and an overview of regional contributions. Results and strategies from one contributing regional study concerning changes along the eastern North Pacific coast are presented. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19820017703&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dseasonal%2Bforecast','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19820017703&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dseasonal%2Bforecast">The seasonal-cycle climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Marx, L.; Randall, D. A. 1981-01-01 The seasonal cycle run which will become the control run for the comparison with runs utilizing codes and parameterizations developed by outside investigators is discussed. The climate model currently exists in two parallel versions: one running on the Amdahl and the other running on the CYBER 203. These two versions are as nearly identical as machine capability and the requirement for high speed performance will allow. Developmental changes are made on the Amdahl/CMS version for ease of testing and rapidity of turnaround. The changes are subsequently incorporated into the CYBER 203 version using vectorization techniques where speed improvement can be realized. The 400 day seasonal cycle run serves as a control run for both medium and long range climate forecasts alsensitivity studies. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active">16</li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active">17</li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.2213A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.2213A">Assessment of two physical parameterization schemes for desert dust emissions in an atmospheric chemistry general circulation model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Astitha, M.; Abdel Kader, M.; Pozzer, A.; Lelieveld, J. 2012-04-01 Atmospheric particulate matter and more specific desert dust has been the topic of numerous research studies in the past due to the wide range of impacts in the environment and climate and the uncertainty of characterizing and quantifying these impacts in a global scale. In this work we present two physical parameterizations of the desert dust production that have been incorporated in the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry). The scope of this work is to assess the impact of the two physical parameterizations in the global distribution of desert dust and highlight the advantages and disadvantages of using either technique. The dust concentration and deposition has been evaluated using the AEROCOM dust dataset for the year 2000 and data from the MODIS and MISR satellites as well as sun-photometer data from the AERONET network was used to compare the modelled aerosol optical depth with observations. The implementation of the two parameterizations and the simulations using relatively high spatial resolution (T106~1.1deg) has highlighted the large spatial heterogeneity of the dust emission sources as well as the importance of the input parameters (soil size and texture, vegetation, surface wind speed). Also, sensitivity simulations with the nudging option using reanalysis data from ECMWF and without nudging have showed remarkable differences for some areas. Both parameterizations have revealed the difficulty of simulating all arid regions with the same assumptions and mechanisms. Depending on the arid region, each emission scheme performs more or less satisfactorily which leads to the necessity of treating each desert differently. Even though this is a quite different task to accomplish in a global model, some recommendations are given and ideas for future improvements. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27594725','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27594725">Climate Shocks and Migration: An Agent-Based Modeling Approach.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Entwisle, Barbara; Williams, Nathalie E; Verdery, Ashton M; Rindfuss, Ronald R; Walsh, Stephen J; Malanson, George P; Mucha, Peter J; Frizzelle, Brian G; McDaniel, Philip M; Yao, Xiaozheng; Heumann, Benjamin W; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree 2016-09-01 This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19897722','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19897722">On the stability of the Atlantic meridional overturning circulation.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Hofmann, Matthias; Rahmstorf, Stefan 2009-12-08 One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5004973','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5004973">Climate Shocks and Migration: An Agent-Based Modeling Approach</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree 2016-01-01 This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21456825','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21456825">Regular network model for the sea ice-albedo feedback in the Arctic.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Müller-Stoffels, Marc; Wackerbauer, Renate 2011-03-01 The Arctic Ocean and sea ice form a feedback system that plays an important role in the global climate. The complexity of highly parameterized global circulation (climate) models makes it very difficult to assess feedback processes in climate without the concurrent use of simple models where the physics is understood. We introduce a two-dimensional energy-based regular network model to investigate feedback processes in an Arctic ice-ocean layer. The model includes the nonlinear aspect of the ice-water phase transition, a nonlinear diffusive energy transport within a heterogeneous ice-ocean lattice, and spatiotemporal atmospheric and oceanic forcing at the surfaces. First results for a horizontally homogeneous ice-ocean layer show bistability and related hysteresis between perennial ice and perennial open water for varying atmospheric heat influx. Seasonal ice cover exists as a transient phenomenon. We also find that ocean heat fluxes are more efficient than atmospheric heat fluxes to melt Arctic sea ice. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21K3182L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21K3182L">A Comparison of Parameterizations of Secondary Organic Aerosol Production: Global Budget and Spatiotemporal Variability</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Liu, J.; Chen, Z.; Horowitz, L. W.; Carlton, A. M. G.; Fan, S.; Cheng, Y.; Ervens, B.; Fu, T. M.; He, C.; Tao, S. 2014-12-01 Secondary organic aerosols (SOA) have a profound influence on air quality and climate, but large uncertainties exist in modeling SOA on the global scale. In this study, five SOA parameterization schemes, including a two-product model (TPM), volatility basis-set (VBS) and three cloud SOA schemes (Ervens et al. (2008, 2014), Fu et al. (2008) , and He et al. (2013)), are implemented into the global chemical transport model (MOZART-4). For each scheme, model simulations are conducted with identical boundary and initial conditions. The VBS scheme produces the highest global annual SOA production (close to 35 Tg·y-1), followed by three cloud schemes (26-30 Tg·y-1) and TPM (23 Tg·y-1). Though sharing a similar partitioning theory to the TPM scheme, the VBS approach simulates the chemical aging of multiple generations of VOCs oxidation products, resulting in a much larger SOA source, particularly from aromatic species, over Europe, the Middle East and Eastern America. The formation of SOA in VBS, which represents the net partitioning of semi-volatile organic compounds from vapor to condensed phase, is highly sensitivity to the aging and wet removal processes of vapor-phase organic compounds. The production of SOA from cloud processes (SOAcld) is constrained by the coincidence of liquid cloud water and water-soluble organic compounds. Therefore, all cloud schemes resolve a fairly similar spatial pattern over the tropical and the mid-latitude continents. The spatiotemporal diversity among SOA parameterizations is largely driven by differences in precursor inputs. Therefore, a deeper understanding of the evolution, wet removal, and phase partitioning of semi-volatile organic compounds, particularly above remote land and oceanic areas, is critical to better constrain the global-scale distribution and related climate forcing of secondary organic aerosols. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRD..11717108D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRD..11717108D">Exploring a new method for the retrieval of urban thermophysical properties using thermal infrared remote sensing and deterministic modeling</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> De Ridder, K.; Bertrand, C.; Casanova, G.; Lefebvre, W. 2012-09-01 Increasingly, mesoscale meteorological and climate models are used to predict urban weather and climate. Yet, large uncertainties remain regarding values of some urban surface properties. In particular, information concerning urban values for thermal roughness length and thermal admittance is scarce. In this paper, we present a method to estimate values for thermal admittance in combination with an optimal scheme for thermal roughness length, based on METEOSAT-8/SEVIRI thermal infrared imagery in conjunction with a deterministic atmospheric model containing a simple urbanized land surface scheme. Given the spatial resolution of the SEVIRI sensor, the resulting parameter values are applicable at scales of the order of 5 km. As a study case we focused on the city of Paris, for the day of 29 June 2006. Land surface temperature was calculated from SEVIRI thermal radiances using a new split-window algorithm specifically designed to handle urban conditions, as described inAppendix A, including a correction for anisotropy effects. Land surface temperature was also calculated in an ensemble of simulations carried out with the ARPS mesoscale atmospheric model, combining different thermal roughness length parameterizations with a range of thermal admittance values. Particular care was taken to spatially match the simulated land surface temperature with the SEVIRI field of view, using the so-called point spread function of the latter. Using Bayesian inference, the best agreement between simulated and observed land surface temperature was obtained for the Zilitinkevich (1970) and Brutsaert (1975) thermal roughness length parameterizations, the latter with the coefficients obtained by Kanda et al. (2007). The retrieved thermal admittance values associated with either thermal roughness parameterization were, respectively, 1843 ± 108 J m-2 s-1/2 K-1 and 1926 ± 115 J m-2 s-1/2 K-1. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B31G0556F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B31G0556F">Improving predictions of carbon fluxes in the tropics undre climatic changes using ED2</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Feng, X.; Uriarte, M. 2016-12-01 Tropical forests play a critical role in the exchange of carbon between land and atmosphere, highlighting the urgency of understanding the effects of climate change on these ecosystems. The most optimistic predictions of climate models indicate that global mean temperatures will increase by up to 2 0C with some tropical regions experiencing extreme heat. Drought and heat-induced tree mortality will accelerate the release of carbon to the atmosphere creating a positive feedback that greatly exacerbates global warming. Thus, under a warmer and drier climate, tropical forests may become net sources, rather than sinks, of carbon. Earth system models have not reached a consensus on the magnitude and direction of climate change impacts on tropical forests, calling into question the reliability of their predictions. Thus, there is an immediate need to improve the representation of tropical forests in earth system models to make robust predictions. The goal of our study is to quantify the responses of tropical forests to climate variability and improve the predictive capacity of terrestrial ecosystem models. We have collected species-specific physiological and functional trait data from 144 tree species in a Puerto Rican rainforest to parameterize the Ecosystem Demography model (ED2). The large amount of data generated by this research will lead to better validation and lowering the uncertainty in future model predictions. To best represent the forest landscape in ED2, all the trees have been assigned to three plant functional types (PFTs): early, mid, and late successional species. Trait data for each PFT were synthesized in a Bayesian meta-analytical model and posterior distributions of traits were used to parameterize the ED2 model. Model predictions show that biomass production of late successional PFT (118.89 ton/ha) was consistently higher than mid (71.33 ton/ha) and early (13.21 ton/ha) PFTs. However, mid successional PFT had the highest contributions to NPP for the modeled period. Tropical forest biomass reduces by 30% under future drought scenario turning the tropics into carbon sources. Ensemble runs were conducted to construct error estimates around model forecasts, to compare modeled and observed aboveground biomass, and to identify which processes and tree species need further study. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A31H..07Q','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A31H..07Q">Effects of Cumulus Parameterization on the U.S. Summer Precipitation Prediction by the Regional Climate-Weather Research and Forecasting Model (CWRF)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Qiao, F.; Liang, X. 2011-12-01 Accurate prediction of U.S. summer precipitation, including its geographic distribution, the occurrence frequency and intensity, and diurnal cycle, has been a long-standing problem for most climate and weather models. This study employs the Climate-Weather Research and Forecasting model (CWRF) to investigate the effects of cumulus parameterization on prediction of these key precipitation features during the summers of 1993 and 2008 when severe floods occurred over the U.S. Midwest. Among the 12 widely-used cumulus schemes incorporated in the CWRF, the Ensemble Cumulus Parameterization modified from G3 (ECP) scheme and the Zhang-McFarland cumulus scheme modified by Liang (ZML) well reproduce the geographic distributions of observed 1993 and 2008 floods, albeit both slightly underestimating the maximum amount. However, the ZML scheme greatly overestimates the rainfall amount over the North American Monsoon region and Southeast U.S. while the ECP scheme has a better performance over the entire U.S. Compared to global general circulations models that tend to produce too frequent rainy events at reduced intensity, the CWRF better captures both frequency and intensity of extreme events (heavy rainfall and dry bells). However, most existing cumulus schemes in the CWRF are likely to convert atmospheric moisture into rainfall too fast, leading to less rainy days and stronger heavy rainfall events. A few cumulus schemes can depict the diurnal characteristics in certain but not all the regions over the U.S. For example, the Grell scheme shows its superiority in reproducing the eastward diurnal phase transition and the nocturnal peaks over the Great Plains, whereas the other schemes all fail in capturing this feature. By investigating the critical trigger function(s) that enable these cumulus schemes to capture the observed features, it provides opportunity to better understand the underlying mechanisms that drive the diurnal variation, and thus significantly improves the U.S. summer rainfall diurnal cycle prediction. These will be discussed. For an oral presentation at AGU Fall Meeting 2011 A15: Cloud, Convection, Precipitation, and Radiation: Observations and Modeling, San Francisco, California, USA, 5-9 December 2011. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940019904','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940019904">GEWEX Cloud Systems Study (GCSS)</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Moncrieff, Mitch 1993-01-01 The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..558..266D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..558..266D">Impact of climate seasonality on catchment yield: A parameterization for commonly-used water balance formulas</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> de Lavenne, Alban; Andréassian, Vazken 2018-03-01 This paper examines the hydrological impact of the seasonality of precipitation and maximum evaporation: seasonality is, after aridity, a second-order determinant of catchment water yield. Based on a data set of 171 French catchments (where aridity ranged between 0.2 and 1.2), we present a parameterization of three commonly-used water balance formulas (namely, Turc-Mezentsev, Tixeront-Fu and Oldekop formulas) to account for seasonality effects. We quantify the improvement of seasonality-based parameterization in terms of the reconstitution of both catchment streamflow and water yield. The significant improvement obtained (reduction of RMSE between 9 and 14% depending on the formula) demonstrates the importance of climate seasonality in the determination of long-term catchment water balance. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A12E..03R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A12E..03R">Anisotropic Mesoscale Eddy Transport in Ocean General Circulation Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Reckinger, S. J.; Fox-Kemper, B.; Bachman, S.; Bryan, F.; Dennis, J.; Danabasoglu, G. 2014-12-01 Modern climate models are limited to coarse-resolution representations of large-scale ocean circulation that rely on parameterizations for mesoscale eddies. The effects of eddies are typically introduced by relating subgrid eddy fluxes to the resolved gradients of buoyancy or other tracers, where the proportionality is, in general, governed by an eddy transport tensor. The symmetric part of the tensor, which represents the diffusive effects of mesoscale eddies, is universally treated isotropically in general circulation models. Thus, only a single parameter, namely the eddy diffusivity, is used at each spatial and temporal location to impart the influence of mesoscale eddies on the resolved flow. However, the diffusive processes that the parameterization approximates, such as shear dispersion, potential vorticity barriers, oceanic turbulence, and instabilities, typically have strongly anisotropic characteristics. Generalizing the eddy diffusivity tensor for anisotropy extends the number of parameters to three: a major diffusivity, a minor diffusivity, and the principal axis of alignment. The Community Earth System Model (CESM) with the anisotropic eddy parameterization is used to test various choices for the newly introduced parameters, which are motivated by observations and the eddy transport tensor diagnosed from high resolution simulations. Simply setting the ratio of major to minor diffusivities to a value of five globally, while aligning the major axis along the flow direction, improves biogeochemical tracer ventilation and reduces global temperature and salinity biases. These effects can be improved even further by parameterizing the anisotropic transport mechanisms in the ocean. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MsT.........37B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MsT.........37B">Implementation of a Brown Carbon Parameterization in the Community Earth System Model (CESM): Model Validation, Estimation of Brown Carbon Radiative Effect, and Climate Impact</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brown, Hunter Y. A recent development in the representation of aerosols in climate models is the realization that some components of organic carbon (OC), emitted from biomass and biofuel burning, can have a significant contribution to short-wave radiation absorption in the atmosphere. The absorbing fraction of OC is referred to as brown carbon (BrC). This study introduces one of the first implementations of BrC into the Community Earth System Model (CESM), using a parameterization for BrC absorption described in Saleh et al. (2014). 9-year experiments are run (2003-2011) with prescribed emissions and sea surface temperatures to analyze the effect of BrC in the atmosphere. Model validation is conducted via model comparison to single-scatter albedo (SSA) and aerosol optical depth from the Aerosol Robotic Network (AERONET), as well as comparison with a laboratory derived parameterization for SSA dependent on the (black carbon (BC))/(BC+OC) ratio in biomass burning emissions. These comparisons reveal a model underestimation of SSA in biomass burning regions for both default and BrC model runs. Global annual average radiative effects are calculated due to aerosol-radiation interactions (REari; 0.13+/-0.021 W m -2), aerosol-cloud interactions (REaci; 0.07+/-0.056 W m -2), and surface albedo change (REsac; -0.06+/-0.035 W m -2). REari is similar to other studies' estimations of BrC direct radiative effect, while REaci indicates a global reduction in low clouds due to the BrC semi-direct effect. REsac suggests increased surface albedo with BrC implementation due to modified snowfall, but does not take into account the warming effect of BrC on snow. Lastly, comparisons of BrC implementation approaches find that this implementation may do a better job of estimating BrC radiative effect in the Arctic regions than previous studies with CESM. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ACP....18.7217O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ACP....18.7217O">Large-scale tropospheric transport in the Chemistry-Climate Model Initiative (CCMI) simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Orbe, Clara; Yang, Huang; Waugh, Darryn W.; Zeng, Guang; Morgenstern, Olaf; Kinnison, Douglas E.; Lamarque, Jean-Francois; Tilmes, Simone; Plummer, David A.; Scinocca, John F.; Josse, Beatrice; Marecal, Virginie; Jöckel, Patrick; Oman, Luke D.; Strahan, Susan E.; Deushi, Makoto; Tanaka, Taichu Y.; Yoshida, Kohei; Akiyoshi, Hideharu; Yamashita, Yousuke; Stenke, Andreas; Revell, Laura; Sukhodolov, Timofei; Rozanov, Eugene; Pitari, Giovanni; Visioni, Daniele; Stone, Kane A.; Schofield, Robyn; Banerjee, Antara 2018-05-01 Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry-Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GMDD....8.3791Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GMDD....8.3791Z">An automatic and effective parameter optimization method for model tuning</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X. 2015-05-01 Physical parameterizations in General Circulation Models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A51N..03A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A51N..03A">Future changes in large-scale transport and stratosphere-troposphere exchange</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Abalos, M.; Randel, W. J.; Kinnison, D. E.; Garcia, R. R. 2017-12-01 Future changes in large-scale transport are investigated in long-term (1955-2099) simulations of the Community Earth System Model - Whole Atmosphere Community Climate Model (CESM-WACCM) under an RCP6.0 climate change scenario. We examine artificial passive tracers in order to isolate transport changes from future changes in emissions and chemical processes. The model suggests enhanced stratosphere-troposphere exchange in both directions (STE), with decreasing tropospheric and increasing stratospheric tracer concentrations in the troposphere. Changes in the different transport processes are evaluated using the Transformed Eulerian Mean continuity equation, including parameterized convective transport. Dynamical changes associated with the rise of the tropopause height are shown to play a crucial role on future transport trends. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812633P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812633P">Climate Change in Nicaragua: a dynamical downscaling of precipitation and temperature.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Porras, Ignasi; Domingo-Dalmau, Anna; Sole, Josep Maria; Arasa, Raul; Picanyol, Miquel; Ángeles Gonzalez-Serrano, M.°; Masdeu, Marta 2016-04-01 Climate Change affects weather patterns and modifies meteorological extreme events like tropical cyclones, heavy rainfalls, dry events, extreme temperatures, etc. The aim of this study is to show the Climate Change projections over Nicaragua for the period 2010-2040 focused on precipitation and temperature. In order to obtain the climate change signal, the results obtained by modelling a past period (1980-2009) were compared with the ones obtained by modelling a future period (2010-2040). The modelling method was based on a dynamical downscaling, coupling global and regional models. The MPI-ESM-MR global climate model was selected due to the better performance over Nicaragua. Moreover, a detailed sensitivity analysis for different parameterizations and schemes of the Weather Research and Forecast (WRF-ARW) model was made to minimize the model uncertainty. To evaluate and validate the methodology, a comparison between model outputs and satellite measurements data was realized. The results show an expected increment of the temperature and an increment of the number of days per year with temperatures higher than 35°C. Monthly precipitation patterns will change although annual total precipitation will be similar. In addition, number of dry days are expected to increase. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GMD....11.1665F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GMD....11.1665F">Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fuhrer, Oliver; Chadha, Tarun; Hoefler, Torsten; Kwasniewski, Grzegorz; Lapillonne, Xavier; Leutwyler, David; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph; Schulthess, Thomas C.; Vogt, Hannes 2018-05-01 The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain-specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmospheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an energy consumption of 596 MWh per simulated year. Furthermore, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth - the dominant bottleneck of climate codes - is being used. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11D..05H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11D..05H">An Investigation of the Radiative Effects and Climate Feedbacks of Sea Ice Sources of Sea Salt Aerosol</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Horowitz, H. M.; Alexander, B.; Bitz, C. M.; Jaegle, L.; Burrows, S. M. 2017-12-01 In polar regions, sea ice is a major source of sea salt aerosol through lofting of saline frost flowers or blowing saline snow from the sea ice surface. Under continued climate warming, an ice-free Arctic in summer with only first-year, more saline sea ice in winter is likely. Previous work has focused on climate impacts in summer from increasing open ocean sea salt aerosol emissions following complete sea ice loss in the Arctic, with conflicting results suggesting no net radiative effect or a negative climate feedback resulting from a strong first aerosol indirect effect. However, the radiative forcing from changes to the sea ice sources of sea salt aerosol in a future, warmer climate has not previously been explored. Understanding how sea ice loss affects the Arctic climate system requires investigating both open-ocean and sea ice sources of sea-salt aerosol and their potential interactions. Here, we implement a blowing snow source of sea salt aerosol into the Community Earth System Model (CESM) dynamically coupled to the latest version of the Los Alamos sea ice model (CICE5). Snow salinity is a key parameter affecting blowing snow sea salt emissions and previous work has assumed constant regional snow salinity over sea ice. We develop a parameterization for dynamic snow salinity in the sea ice model and examine how its spatial and temporal variability impacts the production of sea salt from blowing snow. We evaluate and constrain the snow salinity parameterization using available observations. Present-day coupled CESM-CICE5 simulations of sea salt aerosol concentrations including sea ice sources are evaluated against in situ and satellite (CALIOP) observations in polar regions. We then quantify the present-day radiative forcing from the addition of blowing snow sea salt aerosol with respect to aerosol-radiation and aerosol-cloud interactions. The relative contributions of sea ice vs. open ocean sources of sea salt aerosol to radiative forcing in polar regions is discussed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8030B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8030B">An improved ice cloud formation parameterization in the EMAC model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bacer, Sara; Pozzer, Andrea; Karydis, Vlassis; Tsimpidi, Alexandra; Tost, Holger; Sullivan, Sylvia; Nenes, Athanasios; Barahona, Donifan; Lelieveld, Jos 2017-04-01 Cirrus clouds cover about 30% of the Earth's surface and are an important modulator of the radiative energy budget of the atmosphere. Despite their importance in the global climate system, there are still large uncertainties in understanding the microphysical properties and interactions with aerosols. Ice crystal formation is quite complex and a variety of mechanisms exists for ice nucleation, depending on aerosol characteristics and environmental conditions. Ice crystals can be formed via homogeneous nucleation or heterogeneous nucleation of ice-nucleating particles in different ways (contact, immersion, condensation, deposition). We have implemented the computationally efficient cirrus cloud formation parameterization by Barahona and Nenes (2009) into the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model in order to improve the representation of ice clouds and aerosol-cloud interactions. The parameterization computes the ice crystal number concentration from precursor aerosols and ice-nucleating particles accounting for the competition between homogeneous and heterogeneous nucleation and among different freezing modes. Our work shows the differences and the improvements obtained after the implementation with respect to the previous version of EMAC. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active">17</li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active">18</li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1198147-climate-simulations-projections-super-parameterized-climate-model','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1198147-climate-simulations-projections-super-parameterized-climate-model">Climate simulations and projections with a super-parameterized climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Stan, Cristiana; Xu, Li 2014-07-01 The mean climate and its variability are analyzed in a suite of numerical experiments with a fully coupled general circulation model in which subgrid-scale moist convection is explicitly represented through embedded 2D cloud-system resolving models. Control simulations forced by the present day, fixed atmospheric carbon dioxide concentration are conducted using two horizontal resolutions and validated against observations and reanalyses. The mean state simulated by the higher resolution configuration has smaller biases. Climate variability also shows some sensitivity to resolution but not as uniform as in the case of mean state. The interannual and seasonal variability are better represented in themore » simulation at lower resolution whereas the subseasonal variability is more accurate in the higher resolution simulation. The equilibrium climate sensitivity of the model is estimated from a simulation forced by an abrupt quadrupling of the atmospheric carbon dioxide concentration. The equilibrium climate sensitivity temperature of the model is 2.77 °C, and this value is slightly smaller than the mean value (3.37 °C) of contemporary models using conventional representation of cloud processes. As a result, the climate change simulation forced by the representative concentration pathway 8.5 scenario projects an increase in the frequency of severe droughts over most of the North America.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1423054','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1423054">Environmental limitation mapping of potential biomass resources across the conterminous United States</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Daly, Christopher; Halbleib, Michael D.; Hannaway, David B. Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1423054-environmental-limitation-mapping-potential-biomass-resources-across-conterminous-united-states','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1423054-environmental-limitation-mapping-potential-biomass-resources-across-conterminous-united-states">Environmental limitation mapping of potential biomass resources across the conterminous United States</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.; ... 2017-12-22 Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.4475L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.4475L">Can Regional Climate Modeling Capture the Observed Changes in Spatial Organization of Extreme Storms at Higher Temperatures?</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Li, J.; Wasko, C.; Johnson, F.; Evans, J. P.; Sharma, A. 2018-05-01 The spatial extent and organization of extreme storm events has important practical implications for flood forecasting. Recently, conflicting evidence has been found on the observed changes of storm spatial extent with increasing temperatures. To further investigate this question, a regional climate model assessment is presented for the Greater Sydney region, in Australia. Two regional climate models were considered: the first a convection-resolving simulation at 2-km resolution, the second a resolution of 10 km with three different convection parameterizations. Both the 2- and the 10-km resolutions that used the Betts-Miller-Janjic convective scheme simulate decreasing storm spatial extent with increasing temperatures for 1-hr duration precipitation events, consistent with the observation-based study in Australia. However, other observed relationships of extreme rainfall with increasing temperature were not well represented by the models. Improved methods for considering storm organization are required to better understand potential future changes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.4231T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.4231T">Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tariku, Tebikachew Betru; Gan, Thian Yew 2018-06-01 Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional climate of NRB over 1980-2001 which include a combination of wet and dry years of the NRB. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..525T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..525T">Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tariku, Tebikachew Betru; Gan, Thian Yew 2017-08-01 Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional climate of NRB over 1980-2001 which include a combination of wet and dry years of the NRB. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1425466','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1425466">Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S. Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (~14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.more » Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1425466-toward-low-cloud-permitting-cloud-superparameterization-explicit-boundary-layer-turbulence','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1425466-toward-low-cloud-permitting-cloud-superparameterization-explicit-boundary-layer-turbulence">Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; ... 2017-06-19 Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (~14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.more » Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1171311-regionalization-subsurface-stormflow-parameters-hydrologic-models-derivation-from-regional-analysis-streamflow-recession-curves','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1171311-regionalization-subsurface-stormflow-parameters-hydrologic-models-derivation-from-regional-analysis-streamflow-recession-curves">Regionalization of subsurface stormflow parameters of hydrologic models: Derivation from regional analysis of streamflow recession curves</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Ye, Sheng; Li, Hongyi; Huang, Maoyi 2014-07-21 Subsurface stormflow is an important component of the rainfall–runoff response, especially in steep terrain. Its contribution to total runoff is, however, poorly represented in the current generation of land surface models. The lack of physical basis of these common parameterizations precludes a priori estimation of the stormflow (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global land surface models. This paper is aimed at deriving regionalized parameterizations of the storage–discharge relationship relating to subsurface stormflow from a top–down empirical data analysis of streamflow recession curves extracted from 50 eastern United Statesmore » catchments. Detailed regression analyses were performed between parameters of the empirical storage–discharge relationships and the controlling climate, soil and topographic characteristics. The regression analyses performed on empirical recession curves at catchment scale indicated that the coefficient of the power-law form storage–discharge relationship is closely related to the catchment hydrologic characteristics, which is consistent with the hydraulic theory derived mainly at the hillslope scale. As for the exponent, besides the role of field scale soil hydraulic properties as suggested by hydraulic theory, it is found to be more strongly affected by climate (aridity) at the catchment scale. At a fundamental level these results point to the need for more detailed exploration of the co-dependence of soil, vegetation and topography with climate.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017APJAS..53..511C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017APJAS..53..511C">Satellite bulk tropospheric temperatures as a metric for climate sensitivity</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Christy, John R.; McNider, Richard T. 2017-11-01 We identify and remove the main natural perturbations (e.g. volcanic activity, ENSOs) from the global mean lower tropospheric temperatures ( T LT ) over January 1979 - June 2017 to estimate the underlying, potentially human-forced trend. The unaltered value is +0.155 K dec-1 while the adjusted trend is +0.096 K dec-1, related primarily to the removal of volcanic cooling in the early part of the record. This is essentially the same value we determined in 1994 (+0.09 K dec-1, Christy and McNider, 1994) using only 15 years of data. If the warming rate of +0.096 K dec-1 represents the net T LT response to increasing greenhouse radiative forcings, this implies that the T LT tropospheric transient climate response (Δ T LT at the time CO2 doubles) is +1.10 ± 0.26 K which is about half of the average of the IPCC AR5 climate models of 2.31 ± 0.20 K. Assuming that the net remaining unknown internal and external natural forcing over this period is near zero, the mismatch since 1979 between observations and CMIP-5 model values suggests that excessive sensitivity to enhanced radiative forcing in the models can be appreciable. The tropical region is mainly responsible for this discrepancy suggesting processes that are the likely sources of the extra sensitivity are (a) the parameterized hydrology of the deep atmosphere, (b) the parameterized heat-partitioning at the oceanatmosphere interface and/or (c) unknown natural variations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JAMES...9.1542P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JAMES...9.1542P">Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; Wyant, Matthew C.; Khairoutdinov, Marat 2017-07-01 Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called "ultraparameterization" (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (˜14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers. Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AtmEn.113..135K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AtmEn.113..135K">Aviation NOx-induced CH4 effect: Fixed mixing ratio boundary conditions versus flux boundary conditions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Khodayari, Arezoo; Olsen, Seth C.; Wuebbles, Donald J.; Phoenix, Daniel B. 2015-07-01 Atmospheric chemistry-climate models are often used to calculate the effect of aviation NOx emissions on atmospheric ozone (O3) and methane (CH4). Due to the long (∼10 yr) atmospheric lifetime of methane, model simulations must be run for long time periods, typically for more than 40 simulation years, to reach steady-state if using CH4 emission fluxes. Because of the computational expense of such long runs, studies have traditionally used specified CH4 mixing ratio lower boundary conditions (BCs) and then applied a simple parameterization based on the change in CH4 lifetime between the control and NOx-perturbed simulations to estimate the change in CH4 concentration induced by NOx emissions. In this parameterization a feedback factor (typically a value of 1.4) is used to account for the feedback of CH4 concentrations on its lifetime. Modeling studies comparing simulations using CH4 surface fluxes and fixed mixing ratio BCs are used to examine the validity of this parameterization. The latest version of the Community Earth System Model (CESM), with the CAM5 atmospheric model, was used for this study. Aviation NOx emissions for 2006 were obtained from the AEDT (Aviation Environmental Design Tool) global commercial aircraft emissions. Results show a 31.4 ppb change in CH4 concentration when estimated using the parameterization and a 1.4 feedback factor, and a 28.9 ppb change when the concentration was directly calculated in the CH4 flux simulations. The model calculated value for CH4 feedback on its own lifetime agrees well with the 1.4 feedback factor. Systematic comparisons between the separate runs indicated that the parameterization technique overestimates the CH4 concentration by 8.6%. Therefore, it is concluded that the estimation technique is good to within ∼10% and decreases the computational requirements in our simulations by nearly a factor of 8. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A44D..02R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A44D..02R">The climate impacts of absorbing aerosols on and within the Arctic</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rasch, P.; Wang, H.; Ma, P.; Fast, J. D.; Wang, M.; Easter, R. C.; Liu, X.; Qian, Y.; Flanner, M. G.; Ghan, S.; Singh, B. 2011-12-01 Absorbing aerosols are receiving increasing attention as forcing agents in the climate system. By scattering and absorbing light they can reduce planetary albedo, particularly over bright surfaces (clouds, snow and ice). They also act as cloud condensation and/or ice nuclei, influencing the brightness, lifetime and precipitation properties of clouds. Atmospheric stability and primary circulation features respond to the changing vertical and horizontal patterns of heating, cooling, and surface fluxes produced by the aerosols, clouds and surface properties. These changes in meteorology have further impacts on aerosols and clouds producing a complex interplay between transport, forcings, and feedbacks involving absorbing aerosols and climate. The complexity of the processes and the interactions between them make it very challenging to represent aerosols realistically in large scale (global and regional) climate models. Simulations of important features of aerosols still contain easily identifiable biases. I will describe our efforts to identify the processes responsible for some of those biases and the deficiencies in model formulations that impede progress in treating aerosols and understanding their role in polar climate. I plan to summarize some studies performed with the NCAR CESM (global) and WRF-Chem (regional) Community models that examine the simulation sensitivity to treatments of physics, chemistry, and meteorology. Some of these simulations were allowed to evolve freely; others were strongly constrained to agree with observed meteorological fields. We have also altered the formulation of a number of the processes in the model to improve fidelity in the aerosol distributions. The parameterizations used in our global model have also been transferred to the regional model, allowing comparisons to be made between the simpler formulations used in the global model with more elaborate and costly formulations available in the regional model. The regional model can be run at higher resolution in order to explore the resolution dependence of the parameterizations and make comparisons to field experiments more straightforward. Aerosols sources have also been tagged by sector and geographic region to help in attribution and interpretation. The many variations mentioned here help in understanding how aerosols reach the arctic and how they produce changes in radiative forcing and Arctic climate. I will provide a brief overview of these studies, with more detail available in presentations submitted to this session and elsewhere. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A54B..07C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A54B..07C">Surface ozone seasonality under global change: Influence from dry deposition and isoprene emissions at northern mid-latitudes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Clifton, O.; Paulot, F.; Fiore, A. M.; Horowitz, L. W.; Malyshev, S.; Shevliakova, E.; Correa, G. J. P.; Lin, M. 2017-12-01 Identifying the contributions of nonlinear chemistry and transport to observed surface ozone seasonal cycles over land using global models relies on an accurate representation of ozone uptake by vegetation (dry deposition). It is well established that in the absence of ozone precursor emission changes, a warming climate will increase surface ozone in polluted regions, and that a rise in temperature-dependent isoprene emissions would exacerbate this "climate penalty". However, the influence of changes in ozone dry deposition, expected to evolve with climate and land use, is often overlooked in air quality projections. With a new scheme that represents dry deposition within the NOAA GFDL dynamic vegetation land model (LM3) coupled to the NOAA GFDL atmospheric chemistry-climate model (AM3), we simulate the impact of 21st century climate and land use on ozone dry deposition and isoprene emissions. This dry deposition parameterization is a version of the Wesely scheme, but uses parameters explicitly calculated by LM3 that respond to climate and land use (e.g., stomatal conductance, canopy interception of water, leaf area index). The parameterization includes a nonstomatal deposition dependence on humidity. We evaluate climatological present-day seasonal cycles of ozone deposition velocities and abundances with those observed at northern mid-latitude sites. With a set of 2010s and 2090s decadal simulations under a high climate warming scenario (RCP8.5) and a sensitivity simulation with well-mixed greenhouse gases following RCP8.5 but air pollutants held at 2010 levels (RCP8.5_WMGG), we examine changes in surface ozone seasonal cycles. We build on our previous findings, which indicate that strong reductions in anthropogenic NOx emissions under RCP8.5 cause the surface ozone seasonal cycle over the NE USA to reverse, shifting from a summer peak at present to a winter peak by 2100. Under RCP8.5_WMGG, we parse the separate effects of climate and land use on ozone dry deposition vs. isoprene emissions to quantify the impact of each process on surface ozone seasonal cycles and compare to the changes induced by declining anthropogenic NOx emissions (RCP8.5). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1612307R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1612307R">Value of eddy-covariance data for individual-based, forest gap models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Roedig, Edna; Cuntz, Matthias; Huth, Andreas 2014-05-01 Individual-based forest gap models simulate tree growth and carbon fluxes on large time scales. They are a well established tool to predict forest dynamics and successions. However, the effect of climatic variables on processes of such individual-based models is uncertain (e.g. the effect of temperature or soil moisture on the gross primary production (GPP)). Commonly, functional relationships and parameter values that describe the effect of climate variables on the model processes are gathered from various vegetation models of different spatial scales. Though, their accuracies and parameter values have not been validated for the specific model scales of individual-based forest gap models. In this study, we address this uncertainty by linking Eddy-covariance (EC) data and a forest gap model. The forest gap model FORMIND is applied on the Norwegian spruce monoculture forest at Wetzstein in Thuringia, Germany for the years 2003-2008. The original parameterizations of climatic functions are adapted according to the EC-data. The time step of the model is reduced to one day in order to adapt to the high resolution EC-data. The FORMIND model uses functional relationships on an individual level, whereas the EC-method measures eco-physiological responses at the ecosystem level. However, we assume that in homogeneous stands as in our study, functional relationships for both methods are comparable. The model is then validated at the spruce forest Waldstein, Germany. Results show that the functional relationships used in the model, are similar to those observed with the EC-method. The temperature reduction curve is well reflected in the EC-data, though parameter values differ from the originally expected values. For example at the freezing point, the observed GPP is 30% higher than predicted by the forest gap model. The response of observed GPP to soil moisture shows that the permanent wilting point is 7 vol-% lower than the value derived from the literature. The light response curve, integrated over the canopy and the forest stand, is underestimated compared to the measured data. The EC-method measures a yearly carbon balance of 13 mol(CO2)m-2 for the Wetzstein site. The model with the original parameterization overestimates the yearly carbon balance by nearly 5 mol(CO2)m-2 while the model with an EC-based parameterization fits the measured data very well. The parameter values derived from EC-data are applied on the spruce forest Waldstein and clearly improve estimates of the carbon balance. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990110694','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990110694">Longwave Radiative Flux Calculations in the TOVS Pathfinder Path A Data Set</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Mehta, Amita; Susskind, Joel 1999-01-01 A radiative transfer model developed to calculate outgoing longwave radiation (OLR) and downwelling longwave, surface flux (DSF) from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder Path A retrieval products is described. The model covers the spectral range of 2 to 2800 cm in 14 medium medium spectral bands. For each band, transmittances are parameterized as a function of temperature, water vapor, and ozone profiles. The form of the band transmittance parameterization is a modified version of the approach we use to model channel transmittances for the High Resolution Infrared Sounder 2 (HIRS2) instrument. We separately derive effective zenith angle for each spectral band such that band-averaged radiance calculated at that angle best approximates directionally integrated radiance for that band. We develop the transmittance parameterization at these band-dependent effective zenith angles to incorporate directional integration of radiances required in the calculations of OLR and DSF. The model calculations of OLR and DSF are accurate and differ by less than 1% from our line-by-line calculations. Also, the model results are within 1% range of other line-by-line calculations provided by the Intercomparison of Radiation Codes in Climate Models (ICRCCM) project for clear-sky and cloudy conditions. The model is currently used to calculate global, multiyear (1985-1998) OLR and DSF from the TOVS Pathfinder Path A Retrievals. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A42C..02S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A42C..02S">CALIOP-based Biomass Burning Smoke Plume Injection Height</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Soja, A. J.; Choi, H. D.; Fairlie, T. D.; Pouliot, G.; Baker, K. R.; Winker, D. M.; Trepte, C. R.; Szykman, J. 2017-12-01 Carbon and aerosols are cycled between terrestrial and atmosphere environments during fire events, and these emissions have strong feedbacks to near-field weather, air quality, and longer-term climate systems. Fire severity and burned area are under the control of weather and climate, and fire emissions have the potential to alter numerous land and atmospheric processes that, in turn, feedback to and interact with climate systems (e.g., changes in patterns of precipitation, black/brown carbon deposition on ice/snow, alteration in landscape and atmospheric/cloud albedo). If plume injection height is incorrectly estimated, then the transport and deposition of those emissions will also be incorrect. The heights to which smoke is injected governs short- or long-range transport, which influences surface pollution, cloud interaction (altered albedo), and modifies patterns of precipitation (cloud condensation nuclei). We are working with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) science team and other stakeholder agencies, primarily the Environmental Protection Agency and regional partners, to generate a biomass burning (BB) plume injection height database using multiple platforms, sensors and models (CALIOP, MODIS, NOAA HMS, Langley Trajectory Model). These data have the capacity to provide enhanced smoke plume injection height parameterization in regional, national and international scientific and air quality models. Statistics that link fire behavior and weather to plume rise are crucial for verifying and enhancing plume rise parameterization in local-, regional- and global-scale models used for air quality, chemical transport and climate. Specifically, we will present: (1) a methodology that links BB injection height and CALIOP air parcels to specific fires; (2) the daily evolution of smoke plumes for specific fires; (3) plumes transport and deposited on the Greenland Ice Sheet; and (4) compare CALIOP-derived smoke plume injection to CMAQ modeled smoke plume injection. These results have the potential to provide value to national and international modeling communities (scientific and air quality) and to public land, fire, and air quality management and regulations communities. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ESSD...10.1031Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ESSD...10.1031Z">Analysis of soil hydraulic and thermal properties for land surface modeling over the Tibetan Plateau</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhao, Hong; Zeng, Yijian; Lv, Shaoning; Su, Zhongbo 2018-06-01 Soil information (e.g., soil texture and porosity) from existing soil datasets over the Tibetan Plateau (TP) is claimed to be inadequate and even inaccurate for determining soil hydraulic properties (SHP) and soil thermal properties (STP), hampering the understanding of the land surface process over TP. As the soil varies across three dominant climate zones (i.e., arid, semi-arid and subhumid) over the TP, the associated SHP and STP are expected to vary correspondingly. To obtain an explicit insight into the soil hydrothermal properties over the TP, in situ and laboratory measurements of over 30 soil property profiles were obtained across the climate zones. Results show that porosity and SHP and STP differ across the climate zones and strongly depend on soil texture. In particular, it is proposed that gravel impact on porosity and SHP and STP are both considered in the arid zone and in deep layers of the semi-arid zone. Parameterization schemes for porosity, SHP and STP are investigated and compared with measurements taken. To determine the SHP, including soil water retention curves (SWRCs) and hydraulic conductivities, the pedotransfer functions (PTFs) developed by Cosby et al. (1984) (for the Clapp-Hornberger model) and the continuous PTFs given by Wösten et al. (1999) (for the Van Genuchten-Mualem model) are recommended. The STP parameterization scheme proposed by Farouki (1981) based on the model of De Vries (1963) performed better across the TP than other schemes. Using the parameterization schemes mentioned above, the uncertainties of five existing regional and global soil datasets and their derived SHP and STP over the TP are quantified through comparison with in situ and laboratory measurements. The measured soil physical properties dataset is available at <a href="https://data.4tu.nl/repository/uuid:c712717c-6ac0-47ff-9d58-97f88082ddc0" target="_blank">https://data.4tu.nl/repository/uuid:c712717c-6ac0-47ff-9d58-97f88082ddc0</a>. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C22B..05W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C22B..05W">Physics-based distributed snow models in the operational arena: Current and future challenges</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Winstral, A. H.; Jonas, T.; Schirmer, M.; Helbig, N. 2017-12-01 The demand for modeling tools robust to climate change and weather extremes along with coincident increases in computational capabilities have led to an increase in the use of physics-based snow models in operational applications. Current operational applications include the WSL-SLF's across Switzerland, ASO's in California, and USDA-ARS's in Idaho. While the physics-based approaches offer many advantages there remain limitations and modeling challenges. The most evident limitation remains computation times that often limit forecasters to a single, deterministic model run. Other limitations however remain less conspicuous amidst the assumptions that these models require little to no calibration based on their foundation on physical principles. Yet all energy balance snow models seemingly contain parameterizations or simplifications of processes where validation data are scarce or present understanding is limited. At the research-basin scale where many of these models were developed these modeling elements may prove adequate. However when applied over large areas, spatially invariable parameterizations of snow albedo, roughness lengths and atmospheric exchange coefficients - all vital to determining the snowcover energy balance - become problematic. Moreover as we apply models over larger grid cells, the representation of sub-grid variability such as the snow-covered fraction adds to the challenges. Here, we will demonstrate some of the major sensitivities of distributed energy balance snow models to particular model constructs, the need for advanced and spatially flexible methods and parameterizations, and prompt the community for open dialogue and future collaborations to further modeling capabilities. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ClDy...43.1693P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ClDy...43.1693P">On the use of nudging techniques for regional climate modeling: application for tropical convection</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pohl, Benjamin; Crétat, Julien 2014-09-01 Using a large set of WRF ensemble simulations at 70-km horizontal resolution over a domain encompassing the Warm Pool region and its surroundings [45°N-45°S, 10°E-240°E], this study aims at quantifying how nudging techniques can modify the simulation of deep atmospheric convection. Both seasonal mean climate, transient variability at intraseasonal timescales, and the respective weight of internal (stochastic) and forced (reproducible) variability are considered. Sensitivity to a large variety of nudging settings (nudged variables and layers and nudging strength) and to the model physics (using 3 convective parameterizations) is addressed. Integrations are carried out during a 7-month season characterized by neutral background conditions and strong intraseasonal variability. Results show that (1) the model responds differently to the nudging from one parameterization to another. Biases are decreased by ~50 % for Betts-Miller-Janjic convection against 17 % only for Grell-Dévényi, the scheme producing yet the largest biases; (2) relaxing air temperature is the most efficient way to reduce biases, while nudging the wind increases most co-variability with daily observations; (3) the model's internal variability is drastically reduced and mostly depends on the nudging strength and nudged variables; (4) interrupting the relaxation before the end of the simulations leads to an abrupt convergence towards the model's natural solution, with no clear effects on the simulated climate after a few days. The usefulness and limitations of the approach are finally discussed through the example of the Madden-Julian Oscillation, that the model fails at simulating and that can be artificially and still imperfectly reproduced in relaxation experiments. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active">18</li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active">19</li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A31K..01D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A31K..01D">Challenges in Parameterizing the Lifecycle of Cumulus Convection in Global Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Del Genio, A. D. 2012-12-01 Moist convection exerts a strong influence on Earth's general circulation, energy cycle, and water cycle and has long been considered among the most difficult processes to represent in global climate models. Historically, convection has been portrayed in models as a collection of individual cells, and most of the attention has focused on deep precipitating convection that adjusts quickly to large-scale processes that destabilize the atmosphere. Only in the past decade has the need to represent the full convective lifecycle been recognized by the global climate modeling community, although many of the relevant features have been observed in field experiments for decades. Progress has accelerated in recent years with the aid of insights gained from cloud-resolving models and new satellite and surface remote sensing datasets. There has also been a welcome trend away from emphasis on the mean state and toward understanding of major modes of convective variability such as the Madden-Julian Oscillation and the continental diurnal cycle. On one end of the lifecycle, the need to capture the gradual transition from shallow to congestus to deep convection has renewed interest in understanding the process of entrainment and the previously underappreciated sensitivity of convection to the humidity of the free troposphere. On the other end, the tendency for convection to organize on the mesoscale in favorable humidity and shear conditions is only now beginning to receive attention in the parameterization community. Approaches to representing downdraft cold pools, which stimulate further convection and trigger organization, are now being implemented in GCMs. The subsequent evolution from convective cells to organized clusters with stratiform precipitation, which shifts the heating profile upward, extends the lifetime of convective systems, and can change the sign of convective momentum transport, remains a challenge, especially as model resolution increases. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.9110A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.9110A">An analysis of MM5 sensitivity to different parameterizations for high-resolution climate simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Argüeso, D.; Hidalgo-Muñoz, J. M.; Gámiz-Fortis, S. R.; Esteban-Parra, M. J.; Castro-Díez, Y. 2009-04-01 An evaluation of MM5 mesoscale model sensitivity to different parameterizations schemes is presented in terms of temperature and precipitation for high-resolution integrations over Andalusia (South of Spain). As initial and boundary conditions ERA-40 Reanalysis data are used. Two domains were used, a coarse one with dimensions of 55 by 60 grid points with spacing of 30 km and a nested domain of 48 by 72 grid points grid spaced 10 km. Coarse domain fully covers Iberian Peninsula and Andalusia fits loosely in the finer one. In addition to parameterization tests, two dynamical downscaling techniques have been applied in order to examine the influence of initial conditions on RCM long-term studies. Regional climate studies usually employ continuous integration for the period under survey, initializing atmospheric fields only at the starting point and feeding boundary conditions regularly. An alternative approach is based on frequent re-initialization of atmospheric fields; hence the simulation is divided in several independent integrations. Altogether, 20 simulations have been performed using varying physics options, of which 4 were fulfilled applying the re-initialization technique. Surface temperature and accumulated precipitation (daily and monthly scale) were analyzed for a 5-year period covering from 1990 to 1994. Results have been compared with daily observational data series from 110 stations for temperature and 95 for precipitation Both daily and monthly average temperatures are generally well represented by the model. Conversely, daily precipitation results present larger deviations from observational data. However, noticeable accuracy is gained when comparing with monthly precipitation observations. There are some especially conflictive subregions where precipitation is scarcely captured, such as the Southeast of the Iberian Peninsula, mainly due to its extremely convective nature. Regarding parameterization schemes performance, every set provides very similar results either for temperature or precipitation and no configuration seems to outperform the others both for the whole region and for every season. Nevertheless, some marked differences between areas within the domain appear when analyzing certain physics options, particularly for precipitation. Some of the physics options, such as radiation, have little impact on model performance with respect to precipitation and results do not vary when the scheme is modified. On the other hand, cumulus and boundary layer parameterizations are responsible for most of the differences obtained between configurations. Acknowledgements: The Spanish Ministry of Science and Innovation, with additional support from the European Community Funds (FEDER), project CGL2007-61151/CLI, and the Regional Government of Andalusia project P06-RNM-01622, have financed this study. The "Centro de Servicios de Informática y Redes de Comunicaciones" (CSIRC), Universidad de Granada, has provided the computing time. Key words: MM5 mesoscale model, parameterizations schemes, temperature and precipitation, South of Spain. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020060666&hterms=drought&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Ddrought','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020060666&hterms=drought&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Ddrought">Importance of Winds and Soil Moistures to the US Summertime Drought of 1988: A GCM Simulation Study</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Mocko, David M.; Sud, Y. C.; Lau, William K. M. (Technical Monitor) 2001-01-01 The climate version of NASA's GEOS 2 GCM did not simulate a realistic 1988 summertime drought in the central United States (Mocko et al., 1999). Despite several new upgrades to the model's parameterizations, as well as finer grid spacing from 4x5 degrees to 2x2.5 degrees, no significant improvements were noted in the model's simulation of the U.S. drought. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H14D..07F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H14D..07F">Soil Structure - A Neglected Component of Land-Surface Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R. 2017-12-01 Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity are less significant but they can reach up to 10% in specific locations. Significance for land-surface and hydrological modeling and implications for distributed domains are discussed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000GBioC..14.1035D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000GBioC..14.1035D">Testing the Hole-in-the-Pipe Model of nitric and nitrous oxide emissions from soils using the TRAGNET Database</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Davidson, Eric A.; Verchot, Louis V. 2000-12-01 Because several soil properties and processes affect emissions of nitric oxide (NO) and nitrous oxide (N2O) from soils, it has been difficult to develop effective and robust algorithms to predict emissions of these gases in biogeochemical models. The conceptual "hole-in-the-pipe" (HIP) model has been used effectively to interpret results of numerous studies, but the ranges of climatic conditions and soil properties are often relatively narrow for each individual study. The Trace Gas Network (TRAGNET) database offers a unique opportunity to test the validity of one manifestation of the HIP model across a broad range of sites, including temperate and tropical climates, grasslands and forests, and native vegetation and agricultural crops. The logarithm of the sum of NO + N2O emissions was positively and significantly correlated with the logarithm of the sum of extractable soil NH4+ + NO3-. The logarithm of the ratio of NO:N2O emissions was negatively and significantly correlated with water-filled pore space (WFPS). These analyses confirm the applicability of the HIP model concept, that indices of soil N availability correlate with the sum of NO+N2O emissions, while soil water content is a strong and robust controller of the ratio of NO:N2O emissions. However, these parameterizations have only broad-brush accuracy because of unaccounted variation among studies in the soil depths where gas production occurs, where soil N and water are measured, and other factors. Although accurate predictions at individual sites may still require site-specific parameterization of these empirical functions, the parameterizations presented here, particularly the one for WFPS, may be appropriate for global biogeochemical modeling. Moreover, this integration of data sets demonstrates the broad ranging applicability of the HIP conceptual approach for understanding soil emissions of NO and N2O. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..43.5450K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..43.5450K">New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L. 2016-05-01 Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ThApC.129.1263P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ThApC.129.1263P">Dynamical downscaling of regional climate over eastern China using RSM with multiple physics scheme ensembles</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Peishu, Zong; Jianping, Tang; Shuyu, Wang; Lingyun, Xie; Jianwei, Yu; Yunqian, Zhu; Xiaorui, Niu; Chao, Li 2017-08-01 The parameterization of physical processes is one of the critical elements to properly simulate the regional climate over eastern China. It is essential to conduct detailed analyses on the effect of physical parameterization schemes on regional climate simulation, to provide more reliable regional climate change information. In this paper, we evaluate the 25-year (1983-2007) summer monsoon climate characteristics of precipitation and surface air temperature by using the regional spectral model (RSM) with different physical schemes. The ensemble results using the reliability ensemble averaging (REA) method are also assessed. The result shows that the RSM model has the capacity to reproduce the spatial patterns, the variations, and the temporal tendency of surface air temperature and precipitation over eastern China. And it tends to predict better climatology characteristics over the Yangtze River basin and the South China. The impact of different physical schemes on RSM simulations is also investigated. Generally, the CLD3 cloud water prediction scheme tends to produce larger precipitation because of its overestimation of the low-level moisture. The systematic biases derived from the KF2 cumulus scheme are larger than those from the RAS scheme. The scale-selective bias correction (SSBC) method improves the simulation of the temporal and spatial characteristics of surface air temperature and precipitation and advances the circulation simulation capacity. The REA ensemble results show significant improvement in simulating temperature and precipitation distribution, which have much higher correlation coefficient and lower root mean square error. The REA result of selected experiments is better than that of nonselected experiments, indicating the necessity of choosing better ensemble samples for ensemble. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRD..119.7616L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRD..119.7616L">Stochastic parameterization for light absorption by internally mixed BC/dust in snow grains for application to climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Liou, K. N.; Takano, Y.; He, C.; Yang, P.; Leung, L. R.; Gu, Y.; Lee, W. L. 2014-06-01 A stochastic approach has been developed to model the positions of BC (black carbon)/dust internally mixed with two snow grain types: hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine BC/dust single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), the action of internal mixing absorbs substantially more light than external mixing. The snow grain shape effect on absorption is relatively small, but its effect on asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions of BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2-5 µm) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 µm, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo substantially more than external mixing and that the snow grain shape plays a critical role in snow albedo calculations through its forward scattering strength. Also, multiple inclusion of BC/dust significantly reduces snow albedo as compared to an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization involving contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountain/snow topography. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1172450-stochastic-parameterization-light-absorption-internally-mixed-bc-dust-snow-grains-application-climate-models','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1172450-stochastic-parameterization-light-absorption-internally-mixed-bc-dust-snow-grains-application-climate-models">Stochastic Parameterization for Light Absorption by Internally Mixed BC/dust in Snow Grains for Application to Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Liou, K. N.; Takano, Y.; He, Cenlin 2014-06-27 A stochastic approach to model the positions of BC/dust internally mixed with two snow-grain types has been developed, including hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine their single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), internal mixing absorbs more light than external mixing. The snow-grain shape effect on absorption is relatively small, but its effect on the asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions ofmore » BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2 – 5 um) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 um, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo more than external mixing and that the snow-grain shape plays a critical role in snow albedo calculations through the asymmetry factor. Also, snow albedo reduces more in the case of multiple inclusion of BC/dust compared to that of an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization containing contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountains/snow topography.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014BGeo...11.1137R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014BGeo...11.1137R">Natural ocean carbon cycle sensitivity to parameterizations of the recycling in a climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Romanou, A.; Romanski, J.; Gregg, W. W. 2014-02-01 Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10%) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34%, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which eventually resurfaces with the global thermohaline circulation especially in the Southern Ocean. Because of the reduced primary production and carbon export in GISSEH compared to GISSER, the biological pump efficiency, i.e., the ratio of primary production and carbon export at 75 m, is half in the GISSEH of that in GISSER, The Southern Ocean emerges as a key region where the CO2 flux is as sensitive to biological parameterizations as it is to physical parameterizations. The fidelity of ocean mixing in the Southern Ocean compared to observations is shown to be a good indicator of the magnitude of the biological pump efficiency regardless of physical model choice. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150002124','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150002124">Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Romanou, A.; Romanski, J.; Gregg, W. W. 2014-01-01 Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which eventually resurfaces with the global thermohaline circulation especially in the Southern Ocean. Because of the reduced primary production and carbon export in GISSEH compared to GISSER, the biological pump efficiency, i.e., the ratio of primary production and carbon export at 75 m, is half in the GISSEH of that in GISSER, The Southern Ocean emerges as a key region where the CO2 flux is as sensitive to biological parameterizations as it is to physical parameterizations. The fidelity of ocean mixing in the Southern Ocean compared to observations is shown to be a good indicator of the magnitude of the biological pump efficiency regardless of physical model choice. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A51I0198T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A51I0198T">Structural uncertainty of downscaled climate model output in a difficult-to-resolve environment: data sparseness and parameterization error contribution to statistical and dynamical downscaling output in the U.S. Caribbean region</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Terando, A. J.; Grade, S.; Bowden, J.; Henareh Khalyani, A.; Wootten, A.; Misra, V.; Collazo, J.; Gould, W. A.; Boyles, R. 2016-12-01 Sub-tropical island nations may be particularly vulnerable to anthropogenic climate change because of predicted changes in the hydrologic cycle that would lead to significant drying in the future. However, decision makers in these regions have seen their adaptation planning efforts frustrated by the lack of island-resolving climate model information. Recently, two investigations have used statistical and dynamical downscaling techniques to develop climate change projections for the U.S. Caribbean region (Puerto Rico and U.S. Virgin Islands). We compare the results from these two studies with respect to three commonly downscaled CMIP5 global climate models (GCMs). The GCMs were dynamically downscaled at a convective-permitting scale using two different regional climate models. The statistical downscaling approach was conducted at locations with long-term climate observations and then further post-processed using climatologically aided interpolation (yielding two sets of projections). Overall, both approaches face unique challenges. The statistical approach suffers from a lack of observations necessary to constrain the model, particularly at the land-ocean boundary and in complex terrain. The dynamically downscaled model output has a systematic dry bias over the island despite ample availability of moisture in the atmospheric column. Notwithstanding these differences, both approaches are consistent in projecting a drier climate that is driven by the strong global-scale anthropogenic forcing. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25265281','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25265281">Impacts of land cover data selection and trait parameterisation on dynamic modelling of species' range expansion.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Heikkinen, Risto K; Bocedi, Greta; Kuussaari, Mikko; Heliölä, Janne; Leikola, Niko; Pöyry, Juha; Travis, Justin M J 2014-01-01 Dynamic models for range expansion provide a promising tool for assessing species' capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina) and one generalist (Issoria lathonia). Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity), with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840024877','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840024877">Science support for the Earth radiation budget sensor on the Nimbus-7 spacecraft</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Ingersoll, A. P. 1982-01-01 Experimental data supporting the Earth radiation budget sensor on the Nimbus 7 Satellite is given. The data deals with the empirical relations between radiative flux, cloudiness, and other meteorological parameters; response of a zonal climate ice sheet model to the orbital perturbations during the quaternary ice ages; and a simple parameterization for ice sheet ablation rate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=336619&keyword=water&subject=water%20research&showcriteria=2&fed_org_id=111&datebeginpublishedpresented=03/04/2012&dateendpublishedpresented=03/04/2017&sortby=pubdateyear','PESTICIDES'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=336619&keyword=water&subject=water%20research&showcriteria=2&fed_org_id=111&datebeginpublishedpresented=03/04/2012&dateendpublishedpresented=03/04/2017&sortby=pubdateyear">A Generalized Simple Formulation of Convective Adjustment ...</a> <a target="_blank" rel="noopener noreferrer" href="http://www.epa.gov/pesticides/search.htm">EPA Pesticide Factsheets</a> Convective adjustment timescale (τ) for cumulus clouds is one of the most influential parameters controlling parameterized convective precipitation in climate and weather simulation models at global and regional scales. Due to the complex nature of deep convection, a prescribed value or ad hoc representation of τ is used in most global and regional climate/weather models making it a tunable parameter and yet still resulting in uncertainties in convective precipitation simulations. In this work, a generalized simple formulation of τ for use in any convection parameterization for shallow and deep clouds is developed to reduce convective precipitation biases at different grid spacing. Unlike existing other methods, our new formulation can be used with field campaign measurements to estimate τ as demonstrated by using data from two different special field campaigns. Then, we implemented our formulation into a regional model (WRF) for testing and evaluation. Results indicate that our simple τ formulation can give realistic temporal and spatial variations of τ across continental U.S. as well as grid-scale and subgrid scale precipitation. We also found that as the grid spacing decreases (e.g., from 36 to 4-km grid spacing), grid-scale precipitation dominants over subgrid-scale precipitation. The generalized τ formulation works for various types of atmospheric conditions (e.g., continental clouds due to heating and large-scale forcing over la </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN23E..06M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN23E..06M">Performance Analysis of GFDL's GCM Line-By-Line Radiative Transfer Model on GPU and MIC Architectures</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Menzel, R.; Paynter, D.; Jones, A. L. 2017-12-01 Due to their relatively low computational cost, radiative transfer models in global climate models (GCMs) run on traditional CPU architectures generally consist of shortwave and longwave parameterizations over a small number of wavelength bands. With the rise of newer GPU and MIC architectures, however, the performance of high resolution line-by-line radiative transfer models may soon approach those of the physical parameterizations currently employed in GCMs. Here we present an analysis of the current performance of a new line-by-line radiative transfer model currently under development at GFDL. Although originally designed to specifically exploit GPU architectures through the use of CUDA, the radiative transfer model has recently been extended to include OpenMP in an effort to also effectively target MIC architectures such as Intel's Xeon Phi. Using input data provided by the upcoming Radiative Forcing Model Intercomparison Project (RFMIP, as part of CMIP 6), we compare model results and performance data for various model configurations and spectral resolutions run on both GPU and Intel Knights Landing architectures to analogous runs of the standard Oxford Reference Forward Model on traditional CPUs. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1343540','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1343540"></a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Allen, Melissa R.; Aziz, H. M. Abdul; Coletti, Mark A. Changing human activity within a geographical location may have significant influence on the global climate, but that activity must be parameterized in such a way as to allow these high-resolution sub-grid processes to affect global climate within that modeling framework. Additionally, we must have tools that provide decision support and inform local and regional policies regarding mitigation of and adaptation to climate change. The development of next-generation earth system models, that can produce actionable results with minimum uncertainties, depends on understanding global climate change and human activity interactions at policy implementation scales. Unfortunately, at best we currently have only limitedmore » schemes for relating high-resolution sectoral emissions to real-time weather, ultimately to become part of larger regions and well-mixed atmosphere. Moreover, even our understanding of meteorological processes at these scales is imperfect. This workshop addresses these shortcomings by providing a forum for discussion of what we know about these processes, what we can model, where we have gaps in these areas and how we can rise to the challenge to fill these gaps.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170002266&hterms=Wrf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DWrf','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170002266&hterms=Wrf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DWrf">NASA Downscaling Project: Final Report</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Ferraro, Robert; Waliser, Duane; Peters-Lidard, Christa 2017-01-01 A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA - 2 reanalyses were used to drive the NU - WRF regional climate model and a GEOS - 5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000 - 2010. The results of these experiments were compared to observational datasets to evaluate the output. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170006916','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170006916">NASA Downscaling Project</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Ferraro, Robert; Waliser, Duane; Peters-Lidard, Christa 2017-01-01 A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA-2 reanalyses were used to drive the NU-WRF regional climate model and a GEOS-5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000-2010. The results of these experiments were compared to observational datasets to evaluate the output. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhDT.......203S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhDT.......203S">A Comprehensive Analysis of Clouds, Radiation, and Precipitation in the North Pacific ITCZ in the NASA GISS ModelE GCM and Satellite Observations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stanfield, Ryan Evan Global circulation/climate models (GCMs) remain as an invaluable tool to predict future potential climate change. To best advise policy makers, assessing and increasing the accuracy of climate models is paramount. The treatment of clouds, radiation and precipitation in climate models and their associated feedbacks have long been one of the largest sources of uncertainty in predicting any potential future climate changes. Three versions of the NASA GISS ModelE GCM (the frozen CMIP5 version [C5], a post-CMIP5 version with modifications to cumulus and boundary layer turbulence parameterizations [P5], and the most recent version of the GCM which builds on the post-CMIP5 version with further modifications to convective cloud ice and cold pool parameterizations [E5]) have been compared with various satellite observations to analyze how recent modifications to the GCM has impacted cloud, radiation, and precipitation properties. In addition to global comparisons, two areas are showcased in regional analyses: the Eastern Pacific Northern ITCZ (EP-ITCZ), and Indonesia and the Western Pacific (INDO-WP). Changes to the cumulus and boundary layer turbulence parameterizations in the P5 version of the GCM have improved cloud and radiation estimations in areas of descending motion, such as the Southern Mid-Latitudes. Ice particle size and fall speed modifications in the E5 version of the GCM have decreased ice cloud water contents and cloud fractions globally while increasing precipitable water vapor in the model. Comparisons of IWC profiles show that the GCM simulated IWCs increase with height and peak in the upper portions of the atmosphere, while 2C-ICE observations peak in the lower levels of the atmosphere and decrease with height, effectively opposite of each other. Profiles of CF peak at lower heights in the E5 simulation, which will potentially increase outgoing longwave radiation due to higher cloud top temperatures, which will counterbalance the decrease in reflected shortwave associated with lower CFs and the thinner optical depths associated with decreased IWC and LWC in the E5 simulation. Vertical motion within the newest E5 simulation is greatly weakened over the EP-ITCZ region, potentially due to atmospheric loading from enhanced ice particle fall speeds. Comparatively, E5 simulated upward motion in the INDO-WP is stronger than its predecessors. Changes in the E5 simulation have resulted in stronger/weaker upward motion over the ocean/land in the INDO-WP region in comparison with both the C5 and P5 predecessors. Multimodel precipitation analysis shows that most of the GCMs tend to produce a wider ITCZ with stronger precipitation compared to GPCP and TRMM precipitation products. E5-simulated precipitation decreases and shifts Southward over the Easter Pacific ITCZ, which warrants further investigation into meridional heat transport and radiation fields. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active">19</li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active">20</li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JAMES...7.2012G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JAMES...7.2012G">Complex functionality with minimal computation: Promise and pitfalls of reduced-tracer ocean biogeochemistry models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Galbraith, Eric D.; Dunne, John P.; Gnanadesikan, Anand; Slater, Richard D.; Sarmiento, Jorge L.; Dufour, Carolina O.; de Souza, Gregory F.; Bianchi, Daniele; Claret, Mariona; Rodgers, Keith B.; Marvasti, Seyedehsafoura Sedigh 2015-12-01 Earth System Models increasingly include ocean biogeochemistry models in order to predict changes in ocean carbon storage, hypoxia, and biological productivity under climate change. However, state-of-the-art ocean biogeochemical models include many advected tracers, that significantly increase the computational resources required, forcing a trade-off with spatial resolution. Here, we compare a state-of-the art model with 30 prognostic tracers (TOPAZ) with two reduced-tracer models, one with 6 tracers (BLING), and the other with 3 tracers (miniBLING). The reduced-tracer models employ parameterized, implicit biological functions, which nonetheless capture many of the most important processes resolved by TOPAZ. All three are embedded in the same coupled climate model. Despite the large difference in tracer number, the absence of tracers for living organic matter is shown to have a minimal impact on the transport of nutrient elements, and the three models produce similar mean annual preindustrial distributions of macronutrients, oxygen, and carbon. Significant differences do exist among the models, in particular the seasonal cycle of biomass and export production, but it does not appear that these are necessary consequences of the reduced tracer number. With increasing CO2, changes in dissolved oxygen and anthropogenic carbon uptake are very similar across the different models. Thus, while the reduced-tracer models do not explicitly resolve the diversity and internal dynamics of marine ecosystems, we demonstrate that such models are applicable to a broad suite of major biogeochemical concerns, including anthropogenic change. These results are very promising for the further development and application of reduced-tracer biogeochemical models that incorporate "sub-ecosystem-scale" parameterizations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28001290','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28001290">Reconciling inconsistencies in precipitation-productivity relationships: implications for climate change.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Knapp, Alan K; Ciais, Philippe; Smith, Melinda D 2017-04-01 Contents 41 I. 41 II. 42 III. 43 IV. 44 V. 45 Acknowledgements 46 References 46 SUMMARY: Precipitation (PPT) is a primary climatic determinant of plant growth and aboveground net primary production (ANPP) over much of the globe. Thus, PPT-ANPP relationships are important both ecologically and to land-atmosphere models that couple terrestrial vegetation to the global carbon cycle. Empirical PPT-ANPP relationships derived from long-term site-based data are almost always portrayed as linear, but recent evidence has accumulated that is inconsistent with an underlying linear relationship. We review, and then reconcile, these inconsistencies with a nonlinear model that incorporates observed asymmetries in PPT-ANPP relationships. Although data are currently lacking for parameterization, this new model highlights research needs that, when met, will improve our understanding of carbon cycle dynamics, as well as forecasts of ecosystem responses to climate change. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT.......129P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT.......129P">Application of advanced data assimilation techniques to the study of cloud and precipitation feedbacks in the tropical climate system</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Posselt, Derek J. The research documented in this study centers around two topics: evaluation of the response of precipitating cloud systems to changes in the tropical climate system, and assimilation of cloud and precipitation information from remote-sensing platforms. The motivation for this work proceeds from the following outstanding problems: (1) Use of models to study the response of clouds to perturbations in the climate system is hampered by uncertainties in cloud microphysical parameterizations. (2) Though there is an ever-growing set of available observations, cloud and precipitation assimilation remains a difficult problem, particularly in the tropics. (3) Though it is widely acknowledged that cloud and precipitation processes play a key role in regulating the Earth's response to surface warming, the response of the tropical hydrologic cycle to climate perturbations remains largely unknown. The above issues are addressed in the following manner. First, Markov chain Monte Carlo (MCMC) methods are used to quantify the sensitivity of the NASA Goddard Cumulus Ensemble (GCE) cloud resolving model (CRM) to changes in its cloud odcrnpbymiC8l parameters. TRMM retrievals of precipitation rate, cloud properties, and radiative fluxes and heating rates over the South China Sea are then assimilated into the GCE model to constrain cloud microphysical parameters to values characteristic of convection in the tropics, and the resulting observation-constrained model is used to assess the response of the tropical hydrologic cycle to surface warming. The major findings of this study are the following: (1) MCMC provides an effective tool with which to evaluate both model parameterizations and the assumption of Gaussian statistics used in optimal estimation procedures. (2) Statistics of the tropical radiation budget and hydrologic cycle can be used to effectively constrain CRM cloud microphysical parameters. (3) For 2D CRM simulations run with and without shear, the precipitation efficiency of cloud systems increases with increasing sea surface temperature, while the high cloud fraction and outgoing shortwave radiation decrease. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15..812R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15..812R">Modeling surface response of the Greenland Ice Sheet to interglacial climate</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rau, Dominik; Rogozhina, Irina 2013-04-01 We present a new parameterization of surface mass balance (SMB) of the Greenland Ice Sheet (GIS) under interglacial climate conditions validated against recent satellite observations on a regional scale. Based on detailed analysis of the modeled surface melting and refreezing rates, we conclude that the existing SMB parameterizations fail to capture either spatial pattern or amplitude of the observed surface response of the GIS. This is due to multiple simplifying assumptions adopted by the majority of modeling studies within the frame of the positive degree day method. Modeled spatial distribution of surface melting is found to be highly sensitive to a choice of daily temperature standard deviation (SD) and degree-day factors, which are generally assumed to have uniform distribution across the entire Greenland region. However, the use of uniform SD distribution and the range of commonly used SD values are absolutely unsupported by the ERA-40 and ERA-Interim climate data. In this region, SD distribution is highly inhomogeneous and characterized by low amplitudes during the summer months in the areas where most surface ice melting occurs. In addition, the use of identical degree day factors on both the eastern and western slopes of the GIS results in overestimation of surface runoff along the western coast of Greenland and significant underestimation along its eastern coast. Our approach is to make use of (i) spatially and seasonally variable SDs derived from ERA-40 and ERA-Interim time series, and (ii) spatially variable degree-day factors, measured across Greenland, Arctic Canada, Norway, Spitsbergen and Iceland. We demonstrate that the new approach is extremely efficient for modeling the evolution of the GIS during the observational period and the entire Holocene interglacial. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1818220B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1818220B">A Simple Model Framework to Explore the Deeply Uncertain, Local Sea Level Response to Climate Change. A Case Study on New Orleans, Louisiana</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bakker, Alexander; Louchard, Domitille; Keller, Klaus 2016-04-01 Sea-level rise threatens many coastal areas around the world. The integrated assessment of potential adaptation and mitigation strategies requires a sound understanding of the upper tails and the major drivers of the uncertainties. Global warming causes sea-level to rise, primarily due to thermal expansion of the oceans and mass loss of the major ice sheets, smaller ice caps and glaciers. These components show distinctly different responses to temperature changes with respect to response time, threshold behavior, and local fingerprints. Projections of these different components are deeply uncertain. Projected uncertainty ranges strongly depend on (necessary) pragmatic choices and assumptions; e.g. on the applied climate scenarios, which processes to include and how to parameterize them, and on error structure of the observations. Competing assumptions are very hard to objectively weigh. Hence, uncertainties of sea-level response are hard to grasp in a single distribution function. The deep uncertainty can be better understood by making clear the key assumptions. Here we demonstrate this approach using a relatively simple model framework. We present a mechanistically motivated, but simple model framework that is intended to efficiently explore the deeply uncertain sea-level response to anthropogenic climate change. The model consists of 'building blocks' that represent the major components of sea-level response and its uncertainties, including threshold behavior. The framework's simplicity enables the simulation of large ensembles allowing for an efficient exploration of parameter uncertainty and for the simulation of multiple combined adaptation and mitigation strategies. The model framework can skilfully reproduce earlier major sea level assessments, but due to the modular setup it can also be easily utilized to explore high-end scenarios and the effect of competing assumptions and parameterizations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GMD....11.1321P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GMD....11.1321P">The regional climate model REMO (v2015) coupled with the 1-D freshwater lake model FLake (v1): Fenno-Scandinavian climate and lakes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pietikäinen, Joni-Pekka; Markkanen, Tiina; Sieck, Kevin; Jacob, Daniela; Korhonen, Johanna; Räisänen, Petri; Gao, Yao; Ahola, Jaakko; Korhonen, Hannele; Laaksonen, Ari; Kaurola, Jussi 2018-04-01 The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied in a set of 35-year hindcast simulations. Additionally, sensitivity tests related to the parameterization of snow albedo were conducted. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation, but the downside is that an existing wintertime cold bias in the model is enhanced. The lake surface water temperature, ice depth and ice season length were analyzed in detail for 10 Finnish, 4 Swedish and 2 Russian lakes and 1 Estonian lake. The results show that the model can reproduce these characteristics with reasonably high accuracy. The cold bias during winter causes overestimation of ice layer thickness, for example, at several of the studied lakes, but overall the values from the model are realistic and represent the lake physics well in a long-term simulation. We also analyzed the snow depth on ice from 10 Finnish lakes and vertical temperature profiles from 5 Finnish lakes and the model results are realistic. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010JGRC..11511005D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010JGRC..11511005D">Climate impacts of parameterized Nordic Sea overflows</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Danabasoglu, Gokhan; Large, William G.; Briegleb, Bruce P. 2010-11-01 A new overflow parameterization (OFP) of density-driven flows through ocean ridges via narrow, unresolved channels has been developed and implemented in the ocean component of the Community Climate System Model version 4. It represents exchanges from the Nordic Seas and the Antarctic shelves, associated entrainment, and subsequent injection of overflow product waters into the abyssal basins. We investigate the effects of the parameterized Denmark Strait (DS) and Faroe Bank Channel (FBC) overflows on the ocean circulation, showing their impacts on the Atlantic Meridional Overturning Circulation and the North Atlantic climate. The OFP is based on the Marginal Sea Boundary Condition scheme of Price and Yang (1998), but there are significant differences that are described in detail. Two uncoupled (ocean-only) and two fully coupled simulations are analyzed. Each pair consists of one case with the OFP and a control case without this parameterization. In both uncoupled and coupled experiments, the parameterized DS and FBC source volume transports are within the range of observed estimates. The entrainment volume transports remain lower than observational estimates, leading to lower than observed product volume transports. Due to low entrainment, the product and source water properties are too similar. The DS and FBC overflow temperature and salinity properties are in better agreement with observations in the uncoupled case than in the coupled simulation, likely reflecting surface flux differences. The most significant impact of the OFP is the improved North Atlantic Deep Water penetration depth, leading to a much better comparison with the observational data and significantly reducing the chronic, shallow penetration depth bias in level coordinate models. This improvement is due to the deeper penetration of the southward flowing Deep Western Boundary Current. In comparison with control experiments without the OFP, the abyssal ventilation rates increase in the North Atlantic. In the uncoupled simulation with the OFP, the warm bias of the control simulation in the deep North Atlantic is substantially reduced along with salinity bias reductions in the northern North Atlantic. There are similar but more modest bias reductions in the deep temperature and salinity distributions especially in the northern North Atlantic in the coupled OFP case. In coupled simulations, there are noticeable impacts of the OFP on climate. The sea surface temperatures (SSTs) are warmer by more than 5°C off the North American coast and by more than 1°C in the Nordic Sea with the OFP. The surface heat fluxes mostly act to diminish these SST changes. There are related changes in the sea level pressure, leading to about 15% weaker westerly wind stress in the northern North Atlantic. In response to the warmer Nordic Sea SSTs, there are reductions in the sea ice extent, improving comparisons with observations. Although the OFP cases improve many aspects of the simulations compared to observations, some significant biases remain, more in coupled than in uncoupled simulations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ACP....12.5077G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ACP....12.5077G">Uncertainties of parameterized surface downward clear-sky shortwave and all-sky longwave radiation.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gubler, S.; Gruber, S.; Purves, R. S. 2012-06-01 As many environmental models rely on simulating the energy balance at the Earth's surface based on parameterized radiative fluxes, knowledge of the inherent model uncertainties is important. In this study we evaluate one parameterization of clear-sky direct, diffuse and global shortwave downward radiation (SDR) and diverse parameterizations of clear-sky and all-sky longwave downward radiation (LDR). In a first step, SDR is estimated based on measured input variables and estimated atmospheric parameters for hourly time steps during the years 1996 to 2008. Model behaviour is validated using the high quality measurements of six Alpine Surface Radiation Budget (ASRB) stations in Switzerland covering different elevations, and measurements of the Swiss Alpine Climate Radiation Monitoring network (SACRaM) in Payerne. In a next step, twelve clear-sky LDR parameterizations are calibrated using the ASRB measurements. One of the best performing parameterizations is elected to estimate all-sky LDR, where cloud transmissivity is estimated using measured and modeled global SDR during daytime. In a last step, the performance of several interpolation methods is evaluated to determine the cloud transmissivity in the night. We show that clear-sky direct, diffuse and global SDR is adequately represented by the model when using measurements of the atmospheric parameters precipitable water and aerosol content at Payerne. If the atmospheric parameters are estimated and used as a fix value, the relative mean bias deviance (MBD) and the relative root mean squared deviance (RMSD) of the clear-sky global SDR scatter between between -2 and 5%, and 7 and 13% within the six locations. The small errors in clear-sky global SDR can be attributed to compensating effects of modeled direct and diffuse SDR since an overestimation of aerosol content in the atmosphere results in underestimating the direct, but overestimating the diffuse SDR. Calibration of LDR parameterizations to local conditions reduces MBD and RMSD strongly compared to using the published values of the parameters, resulting in relative MBD and RMSD of less than 5% respectively 10% for the best parameterizations. The best results to estimate cloud transmissivity during nighttime were obtained by linearly interpolating the average of the cloud transmissivity of the four hours of the preceeding afternoon and the following morning. Model uncertainty can be caused by different errors such as code implementation, errors in input data and in estimated parameters, etc. The influence of the latter (errors in input data and model parameter uncertainty) on model outputs is determined using Monte Carlo. Model uncertainty is provided as the relative standard deviation σrel of the simulated frequency distributions of the model outputs. An optimistic estimate of the relative uncertainty σrel resulted in 10% for the clear-sky direct, 30% for diffuse, 3% for global SDR, and 3% for the fitted all-sky LDR. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008cosp...37..218B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008cosp...37..218B">Sensitivity of the mesosphere to the Lorenz energy cycle of the troposphere</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Becker, Erich The sensitivity of the mesosphere and lower thermosphere (MLT) to climate variability in the troposphere is largely controlled by the generation, propagation, and dissipation of gravity waves (GWs). Conventional climate models cannot fully describe this sensitivity since GWs must be parameterized by invoking strong assumptions. In particular, a fixed GW source at a single level in the troposphere is often assumed. Since the Eliassen-Palm flux (EPF) of low-frequency inertia GWs tends to vanish, the main contribution to the EPF divergence at high latitudes of the MLT is due to midand high-frequency GWs with periods of a few hours or less. In order to resolve at least a good portion of these waves in a GCM, a high spatial resolution from the boundary layer to the lower thermosphere is required. Furthermore, both the generation and dissipation of resolved GWs is expected to depend strongly on the details of the parameterization of turbulence. The present study proposes a new formulation of a mechanistic GCM with high spatial resolution and a sophisticated parameterization of turbulence. This model explicitly simulates the wave drag of the MLT that results from the dynamical GW sources in the troposphere. The Smagorinsky-type horizontal and vertical diffusion coefficients are scaled by the Richardson criterion such that no sponge layer is required for the GWs to dissipate in the MLT. A sensitivity experiment shows that a reduced static stability in the lower troposphere, which may be associated with climate change, leads to a stronger Lorenz energy cycle. The intensification of the tropospheric heat engine is accompanied by enhanced GW acitivity in the upper troposphere at middle latitudes. These changes induce the following remote effects in the summer MLT: downshift of the residual circulation, as well as stronger dissipation, lower temperatures, and reduced easterlies below the mesopause. The simulated sensitivity is consistent with enhanced turbulent diffusion at lower altitudes resulting from stronger GW amplitudes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990087335&hterms=Animation+reading&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DAnimation%2Breading','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990087335&hterms=Animation+reading&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DAnimation%2Breading">Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Cahalan, R. F.; Morcrette, J. J. 1999-01-01 Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015BGD....1215947R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015BGD....1215947R">Estimate of changes in agricultural terrestrial nitrogen pathways and ammonia emissions from 1850 to present in the Community Earth System Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Riddick, S. N.; Ward, D. S.; Hess, P.; Mahowald, N.; Massad, R. S.; Holland, E. A. 2015-09-01 Nitrogen applied to the surface of the land for agricultural purposes represents a significant source of reactive nitrogen (Nr) that can be emitted as a gaseous Nr species, be denitrified to atmospheric nitrogen (N2), run-off during rain events or form plant useable nitrogen in the soil. To investigate the magnitude, temporal variability and spatial heterogeneity of nitrogen pathways on a global scale from sources of animal manure and synthetic fertilizer, we developed a mechanistic parameterization of these pathways within a global terrestrial model. The parameterization uses a climate dependent approach whereby the relationships between meteorological variables and biogeochemical processes are used to calculate the volatilization of ammonia (NH3), nitrification and run-off of Nr following manure or fertilizer application. For the year 2000, we estimate global NH3 emission and Nr dissolved during rain events from manure at 21 and 11 Tg N yr-1, respectively; for synthetic fertilizer we estimate the NH3 emission and Nr run-off during rain events at 12 and 5 Tg N yr-1, respectively. The parameterization was implemented in the Community Land Model from 1850 to 2000 using a transient simulation which predicted that, even though absolute values of all nitrogen pathways are increasing with increased manure and synthetic fertilizer application, partitioning of nitrogen to NH3 emissions from manure is increasing on a percentage basis, from 14 % of nitrogen applied (3 Tg NH3 yr-1) in 1850 to 18 % of nitrogen applied in 2000 (22 Tg NH3 yr-1). While the model confirms earlier estimates of nitrogen fluxes made in a range of studies, its key purpose is to provide a theoretical framework that can be employed within a biogeochemical model, that can explicitly respond to climate and that can evolve and improve with further observation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040027505&hterms=heating+global&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dheating%2Bglobal','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040027505&hterms=heating+global&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dheating%2Bglobal">Tropical Diabatic Heating and the Role of Convective Processes as Represented in Several Contemporary Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Robertson, Franklin R.; Roads, John; Oglesby, Robert; Marshall, Susan 2004-01-01 One of the most fundamental properties of the global heat balance is the net heat input into the tropical atmosphere that helps drive the planetary atmospheric circulation. Although broadly understood in terms of its gross structure and balance of source / sink terms, incorporation of the relevant processes in predictive models is still rather poor. The work reported here examines the tropical radiative and water cycle behavior as produced by four contemporary climate models. Among these are the NSIPP-2 (NASA Seasonal to Interannual Prediction Project) which uses the RAS convective parameterization; the FVCCM, a code using finite volume numerics and the CCM3.6 physics; FVCCM-MCRAS again having the finite volume numerics, but MCRAS convective parameterization and a different radiation treatment; and, finally, the NCEP GSM which uses the RAS. Using multi-decadal integrations with specified SSTs we examine the statistics of radiative / convective processes and associated energy transports, and then estimate model energy flux sensitivities to SST changes. In particular the behavior of the convective parameterizations is investigated. Additional model integrations are performed specifically to assess the importance representing convective inhibition in regulating convective cloud-top structure and moisture detrainment as well as controlling surface energy fluxes. To evaluate the results of these experiments, a number of satellite retrievals are used: TRMM retrievals of vertical reflectivity structure, rainfall rate, and inferred diabatic heating are analyzed to show both seasonal and interannual variations in vertical structure of latent heat release. Top-of-atmosphere radiative fluxes from ERBS and CERES are used to examine shortwave and longwave cloud forcing and to deduce required seasonal energy transports. Retrievals of cloud properties from ISCCP and water vapor variations from SSM/T-2 are also used to understand behavior of the humidity fields. These observations are supplemented with output form the DOE Reanalysis-2. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21B1118B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21B1118B">The Community Earth System Model-Polar Climate Working Group and the status of CESM2.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bailey, D. A.; Holland, M. M.; DuVivier, A. K. 2017-12-01 The Polar Climate Working Group (PCWG) is a consortium of scientists who are interested in modeling and understanding the climate in the Arctic and the Antarctic, and how polar climate processes interact with and influence climate at lower latitudes. Our members come from universities and laboratories, and our interests span all elements of polar climate, from the ocean depths to the top of the atmosphere. In addition to conducting scientific modeling experiments, we are charged with contributing to the development and maintenance of the state-of-the-art sea ice model component (CICE) used in the Community Earth System Model (CESM). A recent priority for the PCWG has been to come up with innovative ways to bring the observational and modeling communities together. This will allow for more robust validation of climate model simulations, the development and implementation of more physically-based model parameterizations, improved data assimilation capabilities, and the better use of models to design and implement field experiments. These have been informed by topical workshops and scientific visitors that we have hosted in these areas. These activities will be discussed and information on how the better integration of observations and models has influenced the new version of the CESM, which is due to be released in late 2017, will be provided. Additionally, we will address how enhanced interactions with the observational community will contribute to model developments and validation moving forward. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1358118-microphysical-explanation-rh-dependent-water-affinity-biogenic-organic-aerosol-its-importance-climate','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1358118-microphysical-explanation-rh-dependent-water-affinity-biogenic-organic-aerosol-its-importance-climate">Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; ... 2017-04-28 A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient datamore » with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.5167R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.5167R">Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; Ma, J.; Song, M.; Partridge, D. G.; Kirkevâg, A.; Leong, Y.; Hu, W. W.; Taylor, N. F.; Lambe, A.; Cerully, K.; Bougiatioti, A.; Liu, P.; Krejci, R.; Petäjä, T.; Percival, C.; Davidovits, P.; Worsnop, D. R.; Ekman, A. M. L.; Nenes, A.; Martin, S.; Jimenez, J. L.; Collins, D. R.; Topping, D. O.; Bertram, A. K.; Zuend, A.; Virtanen, A.; Riipinen, I. 2017-05-01 A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28781391','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28781391">Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Rastak, N; Pajunoja, A; Acosta Navarro, J C; Ma, J; Song, M; Partridge, D G; Kirkevåg, A; Leong, Y; Hu, W W; Taylor, N F; Lambe, A; Cerully, K; Bougiatioti, A; Liu, P; Krejci, R; Petäjä, T; Percival, C; Davidovits, P; Worsnop, D R; Ekman, A M L; Nenes, A; Martin, S; Jimenez, J L; Collins, D R; Topping, D O; Bertram, A K; Zuend, A; Virtanen, A; Riipinen, I 2017-05-28 A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5518298','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5518298">Microphysical explanation of the RH‐dependent water affinity of biogenic organic aerosol and its importance for climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; Ma, J.; Song, M.; Partridge, D. G.; Kirkevåg, A.; Leong, Y.; Hu, W. W.; Taylor, N. F.; Lambe, A.; Cerully, K.; Bougiatioti, A.; Liu, P.; Krejci, R.; Petäjä, T.; Percival, C.; Davidovits, P.; Worsnop, D. R.; Ekman, A. M. L.; Nenes, A.; Martin, S.; Jimenez, J. L.; Collins, D. R.; Topping, D.O.; Bertram, A. K.; Zuend, A.; Virtanen, A. 2017-01-01 Abstract A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH‐dependent SOA water‐uptake with solubility and phase separation; (2) show that laboratory data on IP‐ and MT‐SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single‐parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources. PMID:28781391 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1358118-microphysical-explanation-rh-dependent-water-affinity-biogenic-organic-aerosol-its-importance-climate','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1358118-microphysical-explanation-rh-dependent-water-affinity-biogenic-organic-aerosol-its-importance-climate">Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C. A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient datamore » with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AtmRe.190..128V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AtmRe.190..128V">Objective calibration of numerical weather prediction models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P. 2017-07-01 Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017Ocgy...57..784D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017Ocgy...57..784D">Modeling of Long-Term Evolution of Hydrophysical Fields of the Black Sea</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dorofeyev, V. L.; Sukhikh, L. I. 2017-11-01 The long-term evolution of the Black Sea dynamics (1980-2020) is reconstructed by numerical simulation. The model of the Black Sea circulation has 4.8 km horizontal spatial resolution and 40 levels in z-coordinates. The mixing processes in the upper layer are parameterized by Mellor-Yamada turbulent model. For the sea surface boundary conditions, atmospheric forcing functions were used, provided for the Black Sea region by the Euro mediterranean Center on Climate Change (CMCC) from the COSMO-CLM regional climate model. These data have a spatial resolution of 14 km and a daily temporal resolution. To evaluate the quality of the hydrodynamic fields derived from the simulation, they were compared with in-situ hydrological measurements and similar results from physical reanalysis of the Black Sea. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active">20</li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active">21</li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GMD.....8.3579Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GMD.....8.3579Z">An automatic and effective parameter optimization method for model tuning</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X. 2015-11-01 Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.6046B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.6046B">Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ban, Nikolina; Schmidli, Juerg; Schär, Christoph 2015-04-01 Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6-7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that sub-daily (e.g. hourly) precipitation extremes may increase at about twice this rate (referred to as super-adiabatic scaling). Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parameterize convective precipitation (i.e. thunderstorms and rain showers). Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with environmental temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Consistent with previous results, projections reveal a significant decrease of mean summer precipitation (by 30%). However, unlike previous studies, we find that increase in both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation in 2km simulation (Ban et al. 2015). Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day super-adiabatic precipitation scaling into the future. The applicability of the Clausius-Clapeyron scaling across the whole event spectrum is a potentially useful result for climate impact adaptation. Ban, N., J. Schmidli and C. Schär (2015): Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster? Submitted to GRL. Ban, N., J. Schmidli and C. Schär (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913356J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913356J">Assessing the impact of aerosol-atmosphere interactions in convection-permitting regional climate simulations: the Rolf medicane in 2011</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> José Gómez-Navarro, Juan; María López-Romero, José; Palacios-Peña, Laura; Montávez, Juan Pedro; Jiménez-Guerrero, Pedro 2017-04-01 A critical challenge for assessing regional climate change projections relies on improving the estimate of atmospheric aerosol impact on clouds and reducing the uncertainty associated with the use of parameterizations. In this sense, the horizontal grid spacing implemented in state-of-the-art regional climate simulations is typically 10-25 kilometers, meaning that very important processes such as convective precipitation are smaller than a grid box, and therefore need to be parameterized. This causes large uncertainties, as closure assumptions and a number of parameters have to be established by model tuning. Convection is a physical process that may be strongly conditioned by atmospheric aerosols, although the solution of aerosol-cloud interactions in warm convective clouds remains nowadays a very important scientific challenge, rendering parametrization of these complex processes an important bottleneck that is responsible from a great part of the uncertainty in current climate change projections. Therefore, the explicit simulation of convective processes might improve the quality and reliability of the simulations of the aerosol-cloud interactions in a wide range of atmospheric phenomena. Particularly over the Mediterranean, the role of aerosol particles is very important, being this a crossroad that fuels the mixing of particles from different sources (sea-salt, biomass burning, anthropogenic, Saharan dust, etc). Still, the role of aerosols in extreme events in this area such as medicanes has been barely addressed. This work aims at assessing the role of aerosol-atmosphere interaction in medicanes with the help of the regional chemistry/climate on-line coupled model WRF-CHEM run at a convection-permitting resolution. The analysis is exemplary based on the "Rolf" medicane (6-8 November 2011). Using this case study as reference, four sets of simulations are run with two spatial resolutions: one at a convection-permitting configuration of 4 km, and other at the lower resolution of 12 km, in whose case the convection has to be parameterized. Each configuration is used to produce two simulations, including and not including aerosol-radiation-cloud interactions. The comparison of the simulated output at different scales allows to evaluate the impact of sub-grid scale mixing of precursors on aerosol production. By focusing on these processes at different resolutions, the differences between convection-permitting models running at resolutions of 4 km to 12 km can be explored. Preliminary results indicate that the inclusion of aerosol effects may indeed impact the severity of this simulated medicane, especially sea salt aerosols, and leads to important spatial shifts and differences in intensity of surface precipitation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29923606','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29923606">Major challenges for correlational ecological niche model projections to future climate conditions.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Peterson, A Townsend; Cobos, Marlon E; Jiménez-García, Daniel 2018-06-20 Species-level forecasts of distributional potential and likely distributional shifts, in the face of changing climates, have become popular in the literature in the past 20 years. Many refinements have been made to the methodology over the years, and the result has been an approach that considers multiple sources of variation in geographic predictions, and how that variation translates into both specific predictions and uncertainty in those predictions. Although numerous previous reviews and overviews of this field have pointed out a series of assumptions and caveats associated with the methodology, three aspects of the methodology have important impacts but have not been treated previously in detail. Here, we assess those three aspects: (1) effects of niche truncation on model transfers to future climate conditions, (2) effects of model selection procedures on future-climate transfers of ecological niche models, and (3) relative contributions of several factors (replicate samples of point data, general circulation models, representative concentration pathways, and alternative model parameterizations) to overall variance in model outcomes. Overall, the view is one of caution: although resulting predictions are fascinating and attractive, this paradigm has pitfalls that may bias and limit confidence in niche model outputs as regards the implications of climate change for species' geographic distributions. © 2018 New York Academy of Sciences. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791639','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791639">On the stability of the Atlantic meridional overturning circulation</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Hofmann, Matthias; Rahmstorf, Stefan 2009-01-01 One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC. PMID:19897722 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41G1538B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41G1538B">Parameterization of Nitrogen Limitation for a Dynamic Ecohydrological Model: a Case Study from the Luquillo Critical Zone Observatory</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bastola, S.; Bras, R. L. 2017-12-01 Feedbacks between vegetation and the soil nutrient cycle are important in ecosystems where nitrogen limits plant growth, and consequently influences the carbon balance in the plant-soil system. However, many biosphere models do not include such feedbacks, because interactions between carbon and the nitrogen cycle can be complex, and remain poorly understood. In this study we coupled a nitrogen cycle model with an eco-hydrological model by using the concept of carbon cost economics. This concept accounts for different "costs" to the plant of acquiring nitrogen via different pathways. This study builds on tRIBS-VEGGIE, a spatially explicit hydrological model coupled with a model of photosynthesis, stomatal resistance, and energy balance, by combining it with a model of nitrogen recycling. Driven by climate and spatially explicit data of soils, vegetation and topography, the model (referred to as tRIBS-VEGGIE-CN) simulates the dynamics of carbon and nitrogen in the soil-plant system; the dynamics of vegetation; and different components of the hydrological cycle. The tRIBS-VEGGIE-CN is applied in a humid tropical watershed at the Luquillo Critical Zone Observatory (LCZO). The region is characterized by high availability and cycling of nitrogen, high soil respiration rates, and large carbon stocks.We drive the model under contemporary CO2 and hydro-climatic forcing and compare results to a simulation under doubling CO2 and a range of future climate scenarios. The results with parameterization of nitrogen limitation based on carbon cost economics show that the carbon cost of the acquisition of nitrogen is 14% of the net primary productivity (NPP) and the N uptake cost for different pathways vary over a large range depending on leaf nitrogen content, turnover rates of carbon in soil and nitrogen cycling processes. Moreover, the N fertilization simulation experiment shows that the application of N fertilizer does not significantly change the simulated NPP. Furthermore, an experiment with doubling of the CO2 concentration level shows a significant increase of the NPP and turnover of plant tissues. The simulation with future climate scenarios shows consistent decrease in NPP but the uncertainties in projected NPP arising from selection of climate model and scenario is large. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A41A0041L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A41A0041L">Effects of Planetary Boundary Layer Parameterizations on CWRF Regional Climate Simulation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Liu, S.; Liang, X. 2011-12-01 Planetary Boundary Layer (PBL) parameterizations incorporated in CWRF (Climate extension of the Weather Research and Forecasting model) are first evaluated by comparing simulated PBL heights with observations. Among the 10 evaluated PBL schemes, 2 (CAM, UW) are new in CWRF while the other 8 are original WRF schemes. MYJ, QNSE and UW determine the PBL heights based on turbulent kinetic energy (TKE) profiles, while others (YSU, ACM, GFS, CAM, TEMF) are from bulk Richardson criteria. All TKE-based schemes (MYJ, MYNN, QNSE, UW, Boulac) substantially underestimate convective or residual PBL heights from noon toward evening, while others (ACM, CAM, YSU) well capture the observed diurnal cycle except for the GFS with systematic overestimation. These differences among the schemes are representative over most areas of the simulation domain, suggesting systematic behaviors of the parameterizations. Lower PBL heights simulated by the QNSE and MYJ are consistent with their smaller Bowen ratios and heavier rainfalls, while higher PBL tops by the GFS correspond to warmer surface temperatures. Effects of PBL parameterizations on CWRF regional climate simulation are then compared. The QNSE PBL scheme yields systematically heavier rainfall almost everywhere and throughout the year; this is identified with a much greater surface Bowen ratio (smaller sensible versus larger latent heating) and wetter soil moisture than other PBL schemes. Its predecessor MYJ scheme shares the same deficiency to a lesser degree. For temperature, the performance of the QNSE and MYJ schemes remains poor, having substantially larger rms errors in all seasons. GFS PBL scheme also produces large warm biases. Pronounced sensitivities are also found to the PBL schemes in winter and spring over most areas except the southern U.S. (Southeast, Gulf States, NAM); excluding the outliers (QNSE, MYJ, GFS) that cause extreme biases of -6 to +3°C, the differences among the schemes are still visible (±2°C), where the CAM is generally more realistic. QNSE, MYJ, GFS and BouLac PBL parameterizations are identified as obvious outliers of overall performance in representing precipitation, surface air temperature or PBL height variations. Their poor performance may result from deficiencies in physical formulations, dependences on applicable scales, or trouble numerical implementations, requiring future detailed investigation to isolate the actual cause. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012CliPa...8.1339S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012CliPa...8.1339S">Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium - Part 1: Theory</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sundberg, R.; Moberg, A.; Hind, A. 2012-08-01 A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C41C1229S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C41C1229S">Simulating Ice Dynamics in the Amundsen Sea Sector</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Schwans, E.; Parizek, B. R.; Morlighem, M.; Alley, R. B.; Pollard, D.; Walker, R. T.; Lin, P.; St-Laurent, P.; LaBirt, T.; Seroussi, H. L. 2017-12-01 Thwaites and Pine Island Glaciers (TG; PIG) exhibit patterns of dynamic retreat forced from their floating margins, and could act as gateways for destabilization of deep marine basins in the West Antarctic Ice Sheet (WAIS). Poorly constrained basal conditions can cause model predictions to diverge. Thus, there is a need for efficient simulations that account for shearing within the ice column, and include adequate basal sliding and ice-shelf melting parameterizations. To this end, UCI/NASA JPL's Ice Sheet System Model (ISSM) with coupled SSA/higher-order physics is used in the Amundsen Sea Embayment (ASE) to examine threshold behavior of TG and PIG, highlighting areas particularly vulnerable to retreat from oceanic warming and ice-shelf removal. These moving-front experiments will aid in targeting critical areas for additional data collection in ASE as well as for weighting accuracy in further melt parameterization development. Furthermore, a sub-shelf melt parameterization, resulting from Regional Ocean Modeling System (ROMS; St-Laurent et al., 2015) and coupled ISSM-Massachusetts Institute of Technology general circulation model (MITgcm; Seroussi et al., 2017) output, is incorporated and initially tested in ISSM. Data-guided experiments include variable basal conditions and ice hardness, and are also forced with constant modern climate in ISSM, providing valuable insight into i) effects of different basal friction parameterizations on ice dynamics, illustrating the importance of constraining the variable bed character beneath TG and PIG; ii) the impact of including vertical shear in ice flow models of outlet glaciers, confirming its role in capturing complex feedbacks proximal to the grounding zone; and iii) ASE's sensitivity to sub-shelf melt and ice-front retreat, possible thresholds, and how these affect ice-flow evolution. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ACP....15.5773H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ACP....15.5773H">Modeling the formation and aging of secondary organic aerosols in Los Angeles during CalNex 2010</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hayes, P. L.; Carlton, A. G.; Baker, K. R.; Ahmadov, R.; Washenfelder, R. A.; Alvarez, S.; Rappengluck, B.; Gilman, J. B.; Kuster, W. C.; de Gouw, J. A.; Zotter, P.; Prevot, A. S. H.; Szidat, S.; Kleindienst, T. E.; Offenberg, J. H.; Ma, P. K.; Jimenez, J. L. 2015-05-01 Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle- and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA that formed only from the oxidation of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model-measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate-volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model-measurement agreement for mass concentration. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (~ 3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16-27, 35-61, and 19-35%, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(±3) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μg m-3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies and which is higher on weekends. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr-1 of SOA globally, or 17% of global SOA, one-third of which is likely to be non-fossil. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20100002098&hterms=standard+model+physics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dstandard%2Bmodel%2Bphysics','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20100002098&hterms=standard+model+physics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dstandard%2Bmodel%2Bphysics">Demonstration of Effects on Tropical Cyclone Forecasts with a High Resolution Global Model from Variation in Cumulus Convection Parameterization</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Miller, Timothy L.; Robertson, Franklin R.; Cohen, Charles; Mackaro, Jessica 2009-01-01 The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models that have been developed at Goddard Space Flight Center to support NASA's earth science research in data analysis, observing system modeling and design, climate and weather prediction, and basic research. The work presented used GEOS-5 with 0.25o horizontal resolution and 72 vertical levels (up to 0.01 hP) resolving both the troposphere and stratosphere, with closer packing of the levels close to the surface. The model includes explicit (grid-scale) moist physics, as well as convective parameterization schemes. Results will be presented that will demonstrate strong dependence in the results of modeling of a strong hurricane on the type of convective parameterization scheme used. The previous standard (default) option in the model was the Relaxed Arakawa-Schubert (RAS) scheme, which uses a quasi-equilibrium closure. In the cases shown, this scheme does not permit the efficient development of a strong storm in comparison with observations. When this scheme is replaced by a modified version of the Kain-Fritsch scheme, which was originally developed for use on grids with intervals of order 25 km such as the present one, the storm is able to develop to a much greater extent, closer to that of reality. Details of the two cases will be shown in order to elucidate the differences in the two modeled storms. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H43P..02R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H43P..02R">High Resolution Climate Modeling of the Water Cycle over the Western United States Including Potential Climate Change Impacts</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rasmussen, R.; Liu, C.; Ikeda, K. 2016-12-01 The NCAR Water System program strives to improve the full representation of the water cycle in both regional and global models. Our previous high-resolution simulations using the WRF model over the Rocky Mountains revealed that proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing (< 6 km horizontal) and parameterizations. The climate sensitivity experiment consistent with expected climate change showed an altered hydrological cycle with increased fraction of rain versus snow, increased snowfall at high altitudes, earlier melting of snowpack, and decreased total runoff. In order to investigate regional differences between the Rockies and other major mountain barriers and to study climate change impacts over other regions of the contiguous U.S. (CONUS), we have expanded our prior CO Headwaters modeling study to encompass most of North America at a horizontal grid spacing of 4 km (see figure below). A domain expansion provides the opportunity to assess changes in orographic precipitation across different mountain ranges in the western USA. This study will examine the water cycle over Western U.S. seven U.S. mountain ranges, including likely changes to amount of snowpack and spring melt-off, critical to agriculture in the western U.S. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1711175B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1711175B">Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier 2015-04-01 At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ACPD...1418541H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ACPD...1418541H">Regional climate model assessment of the urban land-surface forcing over central Europe</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Huszar, P.; Halenka, T.; Belda, M.; Zak, M.; Sindelarova, K.; Miksovsky, J. 2014-07-01 For the purpose of qualifying and quantifying the climate impact of cities and urban surfaces in general on climate of central Europe, the surface parameterization in regional climate model RegCM4 has been extended with the Single Layer Urban Canopy Model (SLUCM). A set of experiments was performed over the period of 2005-2009 for central Europe, either without considering urban surfaces or with the SLUCM treatment. Results show a statistically significant impact of urbanized surfaces on temperature (up to 1.5 K increase in summer) as well as on the boundary layer height (increases up to 50 m). Urbanization further influences surface wind with a winter decrease up to -0.6 m s-1, though both increases and decreases were detected in summer depending on the location relative to the cities and daytime (changes up to 0.3 m s-1). Urban surfaces significantly reduce evaporation and thus the humidity over the surface. This impacts the simulated summer precipitation rate, showing decrease over cities up to -2 mm day-1. Significant temperature increases are simulated over higher elevations as well, not only within the urban canopy layer. With the urban parameterization, the climate model better describes the diurnal temperature variation, reducing the cold afternoon and evening bias of RegCM4. Sensitivity experiments were carried out to quantify the response of the meteorological conditions to changes in the parameters specific to the urban environment such as street width, building height, albedo of the roofs and anthropogenic heat release. The results proved to be rather robust and the choice of the key SLUCM parameters impacts them only slightly (mainly temperature, boundary layer height and wind velocity). Statistically significant impacts are modeled not only over large urbanized areas, but the influence of the cities is also evident over rural areas without major urban surfaces. It is shown that this is the result of the combined effect of the distant influence of the cities and the influence of the minor local urban surface coverage. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ACP....1412393H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ACP....1412393H">Regional climate model assessment of the urban land-surface forcing over central Europe</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Huszar, P.; Halenka, T.; Belda, M.; Zak, M.; Sindelarova, K.; Miksovsky, J. 2014-11-01 For the purpose of qualifying and quantifying the climate impact of cities and urban surfaces in general on climate of central Europe, the surface parameterization in regional climate model RegCM4 has been extended with the Single-layer Urban Canopy Model (SLUCM). A set of experiments was performed over the period of 2005-2009 for central Europe, either without considering urban surfaces or with the SLUCM treatment. Results show a statistically significant impact of urbanized surfaces on temperature (up to 1.5 K increase in summer) as well as on the boundary layer height (increases up to 50 m). Urbanization further influences surface wind with a winter decrease up to -0.6 m s-1, though both increases and decreases were detected in summer depending on the location relative to the cities and daytime (changes up to 0.3 m s-1). Urban surfaces significantly reduce the humidity over the surface. This impacts the simulated summer precipitation rate, showing a decrease over cities of up to -2 mm day-1. Significant temperature increases are simulated over higher altitudes as well, not only within the urban canopy layer. With the urban parameterization, the climate model better describes the diurnal temperature variation, reducing the cold afternoon and evening bias of RegCM4. Sensitivity experiments were carried out to quantify the response of the meteorological conditions to changes in the parameters specific to the urban environment, such as street width, building height, albedo of the roofs and anthropogenic heat release. The results proved to be rather robust and the choice of the key SLUCM parameters impacts them only slightly (mainly temperature, boundary layer height and wind velocity). Statistically significant impacts are modelled not only over large urbanized areas, but the influence of the cities is also evident over rural areas without major urban surfaces. It is shown that this is the result of the combined effect of the distant influence of the cities and the influence of the minor local urban surface coverage. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010072848','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010072848">A Thermal Infrared Radiation Parameterization for Atmospheric Studies</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Chou, Ming-Dah; Suarez, Max J.; Liang, Xin-Zhong; Yan, Michael M.-H.; Cote, Charles (Technical Monitor) 2001-01-01 This technical memorandum documents the longwave radiation parameterization developed at the Climate and Radiation Branch, NASA Goddard Space Flight Center, for a wide variety of weather and climate applications. Based on the 1996-version of the Air Force Geophysical Laboratory HITRAN data, the parameterization includes the absorption due to major gaseous absorption (water vapor, CO2, O3) and most of the minor trace gases (N2O, CH4, CFCs), as well as clouds and aerosols. The thermal infrared spectrum is divided into nine bands. To achieve a high degree of accuracy and speed, various approaches of computing the transmission function are applied to different spectral bands and gases. The gaseous transmission function is computed either using the k-distribution method or the table look-up method. To include the effect of scattering due to clouds and aerosols, the optical thickness is scaled by the single-scattering albedo and asymmetry factor. The parameterization can accurately compute fluxes to within 1% of the high spectral-resolution line-by-line calculations. The cooling rate can be accurately computed in the region extending from the surface to the 0.01-hPa level. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140001045','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140001045">Climate Impacts of Ice Nucleation</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Gettelman, Andrew; Liu, Xiaohong; Barahona, Donifan; Lohmann, Ulrike; Chen, Celia 2012-01-01 Several different ice nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of ice nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of ice microphysical states that are consistent with the spread of observations, but many simulations have higher present-day ice crystal number concentrations than in-situ observations. These different states result from different parameterizations of ice cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (0.06 Wm(exp-2) and not statistically significant AIE when included as ice nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting ice AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous ice nucleation. Regional effects can reach several Wm2. Indirect effects are slightly larger for those states with less homogeneous nucleation and lower ice number concentration in the base state. The total ice AIE is estimated at 0.27 +/- 0.10 Wm(exp-2) (1 sigma uncertainty). This represents a 20% offset of the simulated total shortwave AIE for ice and liquid clouds of 1.6 Wm(sup-2). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.7371L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.7371L">Evaluating hourly rainfall characteristics over the U.S. Great Plains in dynamically downscaled climate model simulations using NASA-Unified WRF</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lee, Huikyo; Waliser, Duane E.; Ferraro, Robert; Iguchi, Takamichi; Peters-Lidard, Christa D.; Tian, Baijun; Loikith, Paul C.; Wright, Daniel B. 2017-07-01 Accurate simulation of extreme precipitation events remains a challenge in climate models. This study utilizes hourly precipitation data from ground stations and satellite instruments to evaluate rainfall characteristics simulated by the NASA-Unified Weather Research and Forecasting (NU-WRF) regional climate model at horizontal resolutions of 4, 12, and 24 km over the Great Plains of the United States. We also examined the sensitivity of the simulated precipitation to different spectral nudging approaches and the cumulus parameterizations. The rainfall characteristics in the observations and simulations were defined as an hourly diurnal cycle of precipitation and a joint probability distribution function (JPDF) between duration and peak intensity of precipitation events over the Great Plains in summer. We calculated a JPDF for each data set and the overlapping area between observed and simulated JPDFs to measure the similarity between the two JPDFs. Comparison of the diurnal precipitation cycles between observations and simulations does not reveal the added value of high-resolution simulations. However, the performance of NU-WRF simulations measured by the JPDF metric strongly depends on horizontal resolution. The simulation with the highest resolution of 4 km shows the best agreement with the observations in simulating duration and intensity of wet spells. Spectral nudging does not affect the JPDF significantly. The effect of cumulus parameterizations on the JPDFs is considerable but smaller than that of horizontal resolution. The simulations with lower resolutions of 12 and 24 km show reasonable agreement but only with the high-resolution observational data that are aggregated into coarse resolution and spatially averaged. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A41I0103H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A41I0103H">Effects of Implementing Subgrid-Scale Cloud-Radiation Interactions in a Regional Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Herwehe, J. A.; Alapaty, K.; Otte, T.; Nolte, C. G. 2012-12-01 Interactions between atmospheric radiation, clouds, and aerosols are the most important processes that determine the climate and its variability. In regional scale models, when used at relatively coarse spatial resolutions (e.g., larger than 1 km), convective cumulus clouds need to be parameterized as subgrid-scale clouds. Like many groups, our regional climate modeling group at the EPA uses the Weather Research & Forecasting model (WRF) as a regional climate model (RCM). One of the findings from our RCM studies is that the summertime convective systems simulated by the WRF model are highly energetic, leading to excessive surface precipitation. We also found that the WRF model does not consider the interactions between convective clouds and radiation, thereby omitting an important process that drives the climate. Thus, the subgrid-scale cloudiness associated with convective clouds (from shallow cumuli to thunderstorms) does not exist and radiation passes through the atmosphere nearly unimpeded, potentially leading to overly energetic convection. This also has implications for air quality modeling systems that are dependent upon cloud properties from the WRF model, as the failure to account for subgrid-scale cloudiness can lead to problems such as the underrepresentation of aqueous chemistry processes within clouds and the overprediction of ozone from overactive photolysis. In an effort to advance the climate science of the cloud-aerosol-radiation (CAR) interactions in RCM systems, as a first step we have focused on linking the cumulus clouds with the radiation processes. To this end, our research group has implemented into WRF's Kain-Fritsch (KF) cumulus parameterization a cloudiness formulation that is widely used in global earth system models (e.g., CESM/CAM5). Estimated grid-scale cloudiness and associated condensate are adjusted to account for the subgrid clouds and then passed to WRF's Rapid Radiative Transfer Model - Global (RRTMG) radiation schemes to affect the shortwave and longwave radiative processes. To evaluate the effects of implementing the subgrid-scale cloud-radiation interactions on WRF regional climate simulations, a three-year study period (1988-1990) was simulated over the CONUS using two-way nested domains with 108 km and 36 km horizontal grid spacing, without and with the cumulus feedbacks to radiation, and without and with some form of four dimensional data assimilation (FDDA). Initial and lateral boundary conditions (as well as data for the FDDA, when enabled) were supplied from downscaled NCEP-NCAR Reanalysis II (R2) data sets. Evaluation of the simulation results will be presented comparing regional surface precipitation and temperature statistics with North American Regional Reanalysis (NARR) data and Climate Forecast System Reanalysis (CFSR) data, respectively, as well as comparison with available surface radiation (SURFRAD) and satellite (CERES) observations. This research supports improvements in the EPA's WRF-CMAQ modeling system, leading to better predictions of present and future air quality and climate interactions in order to protect human health and the environment. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A54F..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A54F..01S">Intercomparison Project on Parameterizations of Large-Scale Dynamics for Simulations of Tropical Convection</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sobel, A. H.; Wang, S.; Bellon, G.; Sessions, S. L.; Woolnough, S. 2013-12-01 Parameterizations of large-scale dynamics have been developed in the past decade for studying the interaction between tropical convection and large-scale dynamics, based on our physical understanding of the tropical atmosphere. A principal advantage of these methods is that they offer a pathway to attack the key question of what controls large-scale variations of tropical deep convection. These methods have been used with both single column models (SCMs) and cloud-resolving models (CRMs) to study the interaction of deep convection with several kinds of environmental forcings. While much has been learned from these efforts, different groups' efforts are somewhat hard to compare. Different models, different versions of the large-scale parameterization methods, and experimental designs that differ in other ways are used. It is not obvious which choices are consequential to the scientific conclusions drawn and which are not. The methods have matured to the point that there is value in an intercomparison project. In this context, the Global Atmospheric Systems Study - Weak Temperature Gradient (GASS-WTG) project was proposed at the Pan-GASS meeting in September 2012. The weak temperature gradient approximation is one method to parameterize large-scale dynamics, and is used in the project name for historical reasons and simplicity, but another method, the damped gravity wave (DGW) method, will also be used in the project. The goal of the GASS-WTG project is to develop community understanding of the parameterization methods currently in use. Their strengths, weaknesses, and functionality in models with different physics and numerics will be explored in detail, and their utility to improve our understanding of tropical weather and climate phenomena will be further evaluated. This presentation will introduce the intercomparison project, including background, goals, and overview of the proposed experimental design. Interested groups will be invited to join (it will not be too late), and preliminary results will be presented. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active">21</li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active">22</li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21H3130P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21H3130P">The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pincus, R.; Stevens, B. B.; Forster, P.; Collins, W.; Ramaswamy, V. 2014-12-01 The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies An enormous amount of attention has been paid to the diversity of responses in the CMIP and other multi-model ensembles. This diversity is normally interpreted as a distribution in climate sensitivity driven by some distribution of feedback mechanisms. Identification of these feedbacks relies on precise identification of the forcing to which each model is subject, including distinguishing true error from model diversity. The Radiative Forcing Model Intercomparison Project (RFMIP) aims to disentangle the role of forcing from model sensitivity as determinants of varying climate model response by carefully characterizing the radiative forcing to which such models are subject and by coordinating experiments in which it is specified. RFMIP consists of four activities: 1) An assessment of accuracy in flux and forcing calculations for greenhouse gases under past, present, and future climates, using off-line radiative transfer calculations in specified atmospheres with climate model parameterizations and reference models 2) Characterization and assessment of model-specific historical forcing by anthropogenic aerosols, based on coordinated diagnostic output from climate models and off-line radiative transfer calculations with reference models 3) Characterization of model-specific effective radiative forcing, including contributions of model climatology and rapid adjustments, using coordinated climate model integrations and off-line radiative transfer calculations with a single fast model 4) Assessment of climate model response to precisely-characterized radiative forcing over the historical record, including efforts to infer true historical forcing from patterns of response, by direct specification of non-greenhouse-gas forcing in a series of coordinated climate model integrations This talk discusses the rationale for RFMIP, provides an overview of the four activities, and presents preliminary motivating results. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1208877-using-field-observations-inform-thermal-hydrology-models-permafrost-dynamics-ats-v0','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1208877-using-field-observations-inform-thermal-hydrology-models-permafrost-dynamics-ats-v0">Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Atchley, A. L.; Painter, S. L.; Harp, D. R.; ... 2015-04-14 Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurementsmore » to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050177236','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050177236">GLACE: The Global Land-Atmosphere Coupling Experiment Part 2: Analysis</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Guo, Zhichang; Dirmeyer, Paul A.; Koster, Randal D.; Bonan, Gordon; Chan, Edmond; Cox, Peter; Gordon, C. T.; Kanae, Shinjiro; Kowalczyk, Eva; Lawrence, David 2005-01-01 The twelve weather and climate models participating in the Global Land-Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land-atmosphere coupling and some intriguing commonalities. In this paper, we address the causes of variations in coupling strength - both the geographic variations within a given model and the model-to-model differences. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage - an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation-precipitation connection, however, also play a key role. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19950013363','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19950013363">Assessment of climate variability of the Greenland Ice Sheet: Integration of in situ and satellite data</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Steffen, K.; Abdalati, W.; Stroeve, J.; Key, J. 1994-01-01 The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. Operational satellite sensors are calibrated based on ground measurements and atmospheric modeling prior to large scale analysis to ensure the quality of the satellite data. Further, several satellite sensors of different spatial and spectral resolution are intercompared to access the parameter accuracy. Proposed parameterization schemes to derive key component of the energy balance from satellite data are validated. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface are monitored for the parameterization and interpretation of the satellite data. The expected results include several baseline data sets of albedo, surface temperature, radiative fluxes, and different snow types of the entire Greenland Ice Sheet. These climatological data sets will be of potential use for climate sensitivity studies in the context of future climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27849059','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27849059">Overlooked Role of Mesoscale Winds in Powering Ocean Diapycnal Mixing.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Jing, Zhao; Wu, Lixin; Ma, Xiaohui; Chang, Ping 2016-11-16 Diapycnal mixing affects the uptake of heat and carbon by the ocean as well as plays an important role in global ocean circulations and climate. In the thermocline, winds provide an important energy source for furnishing diapycnal mixing primarily through the generation of near-inertial internal waves. However, this contribution is largely missing in the current generation of climate models. In this study, it is found that mesoscale winds at scales of a few hundred kilometers account for more than 65% of near-inertial energy flux into the North Pacific basin and 55% of turbulent kinetic dissipation rate in the thermocline, suggesting their dominance in powering diapycnal mixing in the thermocline. Furthermore, a new parameterization of wind-driven diapycnal mixing in the ocean interior for climate models is proposed, which, for the first time, successfully captures both temporal and spatial variations of wind-driven diapycnal mixing in the thermocline. It is suggested that as mesoscale winds are not resolved by the climate models participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) due to insufficient resolutions, the diapycnal mixing is likely poorly represented, raising concerns about the accuracy and robustness of climate change simulations and projections. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5111103','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5111103">Overlooked Role of Mesoscale Winds in Powering Ocean Diapycnal Mixing</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Jing, Zhao; Wu, Lixin; Ma, Xiaohui; Chang, Ping 2016-01-01 Diapycnal mixing affects the uptake of heat and carbon by the ocean as well as plays an important role in global ocean circulations and climate. In the thermocline, winds provide an important energy source for furnishing diapycnal mixing primarily through the generation of near-inertial internal waves. However, this contribution is largely missing in the current generation of climate models. In this study, it is found that mesoscale winds at scales of a few hundred kilometers account for more than 65% of near-inertial energy flux into the North Pacific basin and 55% of turbulent kinetic dissipation rate in the thermocline, suggesting their dominance in powering diapycnal mixing in the thermocline. Furthermore, a new parameterization of wind-driven diapycnal mixing in the ocean interior for climate models is proposed, which, for the first time, successfully captures both temporal and spatial variations of wind-driven diapycnal mixing in the thermocline. It is suggested that as mesoscale winds are not resolved by the climate models participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) due to insufficient resolutions, the diapycnal mixing is likely poorly represented, raising concerns about the accuracy and robustness of climate change simulations and projections. PMID:27849059 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005JGRD..11010201D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005JGRD..11010201D">Statistical properties of the normalized ice particle size distribution</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Delanoë, Julien; Protat, Alain; Testud, Jacques; Bouniol, Dominique; Heymsfield, A. J.; Bansemer, A.; Brown, P. R. A.; Forbes, R. M. 2005-05-01 Testud et al. (2001) have recently developed a formalism, known as the "normalized particle size distribution (PSD)", which consists in scaling the diameter and concentration axes in such a way that the normalized PSDs are independent of water content and mean volume-weighted diameter. In this paper we investigate the statistical properties of the normalized PSD for the particular case of ice clouds, which are known to play a crucial role in the Earth's radiation balance. To do so, an extensive database of airborne in situ microphysical measurements has been constructed. A remarkable stability in shape of the normalized PSD is obtained. The impact of using a single analytical shape to represent all PSDs in the database is estimated through an error analysis on the instrumental (radar reflectivity and attenuation) and cloud (ice water content, effective radius, terminal fall velocity of ice crystals, visible extinction) properties. This resulted in a roughly unbiased estimate of the instrumental and cloud parameters, with small standard deviations ranging from 5 to 12%. This error is found to be roughly independent of the temperature range. This stability in shape and its single analytical approximation implies that two parameters are now sufficient to describe any normalized PSD in ice clouds: the intercept parameter N*0 and the mean volume-weighted diameter Dm. Statistical relationships (parameterizations) between N*0 and Dm have then been evaluated in order to reduce again the number of unknowns. It has been shown that a parameterization of N*0 and Dm by temperature could not be envisaged to retrieve the cloud parameters. Nevertheless, Dm-T and mean maximum dimension diameter -T parameterizations have been derived and compared to the parameterization of Kristjánsson et al. (2000) currently used to characterize particle size in climate models. The new parameterization generally produces larger particle sizes at any temperature than the Kristjánsson et al. (2000) parameterization. These new parameterizations are believed to better represent particle size at global scale, owing to a better representativity of the in situ microphysical database used to derive it. We then evaluated the potential of a direct N*0-Dm relationship. While the model parameterized by temperature produces strong errors on the cloud parameters, the N*0-Dm model parameterized by radar reflectivity produces accurate cloud parameters (less than 3% bias and 16% standard deviation). This result implies that the cloud parameters can be estimated from the estimate of only one parameter of the normalized PSD (N*0 or Dm) and a radar reflectivity measurement. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A24F..02L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A24F..02L">Aerosol-cloud interactions in a multi-scale modeling framework</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lin, G.; Ghan, S. J. 2017-12-01 Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1228314-modeling-formation-aging-secondary-organic-aerosols-los-angeles-during-calnex','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1228314-modeling-formation-aging-secondary-organic-aerosols-los-angeles-during-calnex">Modeling the formation and aging of secondary organic aerosols in Los Angeles during CalNex 2010</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Hayes, P. L.; Carlton, A. G.; Baker, K. R.; ... 2015-05-26 Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle- and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA that formed only from the oxidationmore » of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model–measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate-volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model–measurement agreement for mass concentration. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (≈ 3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16–27, 35–61, and 19–35%, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(±3) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μg m −3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies and which is higher on weekends. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr −1 of SOA globally, or 17% of global SOA, one-third of which is likely to be non-fossil.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PApGe.173.3141K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PApGe.173.3141K">Importance of Chemical Composition of Ice Nuclei on the Formation of Arctic Ice Clouds</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Keita, Setigui Aboubacar; Girard, Eric 2016-09-01 Ice clouds play an important role in the Arctic weather and climate system but interactions between aerosols, clouds and radiation remain poorly understood. Consequently, it is essential to fully understand their properties and especially their formation process. Extensive measurements from ground-based sites and satellite remote sensing reveal the existence of two Types of Ice Clouds (TICs) in the Arctic during the polar night and early spring. TICs-1 are composed by non-precipitating small (radar-unseen) ice crystals of less than 30 μm in diameter. The second type, TICs-2, are detected by radar and are characterized by a low concentration of large precipitating ice crystals ice crystals (>30 μm). To explain these differences, we hypothesized that TIC-2 formation is linked to the acidification of aerosols, which inhibits the ice nucleating properties of ice nuclei (IN). As a result, the IN concentration is reduced in these regions, resulting to a lower concentration of larger ice crystals. Water vapor available for deposition being the same, these crystals reach a larger size. Current weather and climate models cannot simulate these different types of ice clouds. This problem is partly due to the parameterizations implemented for ice nucleation. Over the past 10 years, several parameterizations of homogeneous and heterogeneous ice nucleation on IN of different chemical compositions have been developed. These parameterizations are based on two approaches: stochastic (that is nucleation is a probabilistic process, which is time dependent) and singular (that is nucleation occurs at fixed conditions of temperature and humidity and time-independent). The best approach remains unclear. This research aims to better understand the formation process of Arctic TICs using recently developed ice nucleation parameterizations. For this purpose, we have implemented these ice nucleation parameterizations into the Limited Area version of the Global Multiscale Environmental Model (GEM-LAM) and use them to simulate ice clouds observed during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in Alaska. Simulation results of the TICs-2 observed on April 15th and 25th (acidic cases) and TICs-1 observed on April 5th (non-acidic cases) are presented. Our results show that the stochastic approach based on the classical nucleation theory with the appropriate contact angle is better. Parameterizations of ice nucleation based on the singular approach tend to overestimate the ice crystal concentration in TICs-1 and TICs-2. The classical nucleation theory using the appropriate contact angle is the best approach to use to simulate the ice clouds investigated in this research. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C31C..01D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C31C..01D">Scenarios of Earth system change in western Canada: Conceptual understanding and process insights from the Changing Cold Regions Network</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> DeBeer, C. M.; Wheater, H. S.; Pomeroy, J. W.; Stewart, R. E.; Turetsky, M. R.; Baltzer, J. L.; Pietroniro, A.; Marsh, P.; Carey, S.; Howard, A.; Barr, A.; Elshamy, M. 2017-12-01 The interior of western Canada has been experiencing rapid, widespread, and severe hydroclimatic change in recent decades, and this is projected to continue in the future. To better assess future hydrological, cryospheric and ecological states and fluxes under future climates, a regional hydroclimate project was formed under the auspices of the Global Energy and Water Exchanges (GEWEX) project of the World Climate Research Programme; the Changing Cold Regions Network (CCRN; www.ccrnetwork.ca) aims to understand, diagnose, and predict interactions among the changing Earth system components at multiple spatial scales over the Mackenzie and Saskatchewan River basins of western Canada. A particular challenge is in applying land surface and hydrological models under future climates, as system changes and cold regions process interactions are not often straightforward, and model structures and parameterizations based on historical observations and understanding of contemporary system functioning may not adequately capture these complexities. To address this and provide guidance and direction to the modelling community, CCRN has drawn insights from a multi-disciplinary perspective on the process controls and system trajectories to develop a set of feasible scenarios of change for the 21st century across the region. This presentation will describe CCRN's efforts towards formalizing these insights and applying them in a large-scale modelling context. This will address what are seen as the most critical processes and key drivers affecting hydrological, cryospheric and ecological change, how these will most likely evolve in the coming decades, and how these are parameterized and incorporated as future scenarios for terrestrial ecology, hydrological functioning, permafrost state, glaciers, agriculture, and water management. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A52C..05G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A52C..05G">The evaluation of GCMs and a new cloud parameterisation using satellite and in-situ data as part of a Climate Process Team</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Grosvenor, D. P.; Wood, R. 2012-12-01 As part of one of the Climate Process Teams (CPTs) we have been testing the implementation of a new cloud parameterization into the CAM5 and AM3 GCMs. The CLUBB parameterization replaces all but the deep convection cloud scheme and uses an innovative PDF based approach to diagnose cloud water content and turbulence. We have evaluated the base models and the CLUBB parameterization in the SE Pacific stratocumulus region using a suite of satellite observation metrics including: Liquid Water Path (LWP) measurements from AMSRE; cloud fractions from CloudSat/CALIPSO; droplet concentrations (Nd) and Cloud Top Temperatures from MODIS; CloudSat precipitation; and relationships between Estimated Inversion Strength (calculated from AMSRE SSTs, Cloud Top Temperatures from MODIS and ECMWF re-analysis fields) and cloud fraction. This region has the advantage of an abundance of in-situ aircraft observations taken during the VOCALS campaign, which is facilitating the diagnosis of the model problems highlighted by the model evaluation. This data has also been recently used to demonstrate the reliability of MODIS Nd estimates. The satellite data needs to be filtered to ensure accurate retrievals and we have been careful to apply the same screenings to the model fields. For example, scenes with high cloud fractions and with output times near to the satellite overpass times can be extracted from the model for a fair comparison with MODIS Nd estimates. To facilitate this we have been supplied with instantaneous model output since screening would not be possible based on time averaged data. We also have COSP satellite simulator output, which allows a fairer comparison between satellite and model. For example, COSP cloud fraction is based upon the detection threshold of the satellite instrument in question. These COSP fields are also used for the model output filtering just described. The results have revealed problems with both the base models and the versions with the CLUBB parameterization. The CAM5 model produces realistic near-coast cloud cover, but too little further west in the stratocumulus to cumulus regions. The implementation of CLUBB has vastly improved this situation with cloud cover that is very similar to that observed. CLUBB also improves the Nd field in CAM5 by producing realistic near-coast increases and by removing high Nd values associated with the detrainment of droplets by cumulus clouds. AM3 has a lack of stratocumulus cloud near the South American coast and has much lower droplet concentrations than observed. VOCALS measurements showed that sulfate mass loadings were generally too high in both base models, whereas CCN concentrations were too low. This suggests a problem with the mass distribution partitioning of sulfate that is being investigated. Diurnal and seasonal comparisons have been very illuminating. CLUBB produces very little diurnal variation in LWP, but large variations in precipitation rates. This is likely to point to problems that are now being addressed by the modeling part of the CPT team, creating an iterative workflow process between the model developers and the model testers, which should facilitate efficient parameterization improvement. We will report on the latest developments of this process. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120008825','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120008825">High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Putnam, WilliamM. 2011-01-01 In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GMD....10.2671W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GMD....10.2671W">Update of the Polar SWIFT model for polar stratospheric ozone loss (Polar SWIFT version 2)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wohltmann, Ingo; Lehmann, Ralph; Rex, Markus 2017-07-01 The Polar SWIFT model is a fast scheme for calculating the chemistry of stratospheric ozone depletion in polar winter. It is intended for use in global climate models (GCMs) and Earth system models (ESMs) to enable the simulation of mutual interactions between the ozone layer and climate. To date, climate models often use prescribed ozone fields, since a full stratospheric chemistry scheme is computationally very expensive. Polar SWIFT is based on a set of coupled differential equations, which simulate the polar vortex-averaged mixing ratios of the key species involved in polar ozone depletion on a given vertical level. These species are O3, chemically active chlorine (ClOx), HCl, ClONO2 and HNO3. The only external input parameters that drive the model are the fraction of the polar vortex in sunlight and the fraction of the polar vortex below the temperatures necessary for the formation of polar stratospheric clouds. Here, we present an update of the Polar SWIFT model introducing several improvements over the original model formulation. In particular, the model is now trained on vortex-averaged reaction rates of the ATLAS Chemistry and Transport Model, which enables a detailed look at individual processes and an independent validation of the different parameterizations contained in the differential equations. The training of the original Polar SWIFT model was based on fitting complete model runs to satellite observations and did not allow for this. A revised formulation of the system of differential equations is developed, which closely fits vortex-averaged reaction rates from ATLAS that represent the main chemical processes influencing ozone. In addition, a parameterization for the HNO3 change by denitrification is included. The rates of change of the concentrations of the chemical species of the Polar SWIFT model are purely chemical rates of change in the new version, whereas in the original Polar SWIFT model, they included a transport effect caused by the original training on satellite data. Hence, the new version allows for an implementation into climate models in combination with an existing stratospheric transport scheme. Finally, the model is now formulated on several vertical levels encompassing the vertical range in which polar ozone depletion is observed. The results of the Polar SWIFT model are validated with independent Microwave Limb Sounder (MLS) satellite observations and output from the original detailed chemistry model of ATLAS. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1228314-modeling-formation-aging-secondary-organic-aerosols-los-angeles-during-calnex','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1228314-modeling-formation-aging-secondary-organic-aerosols-los-angeles-during-calnex"></a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Hayes, P. L.; Carlton, A. G.; Baker, K. R. Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle- and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA that formed only from the oxidationmore » of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model–measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate-volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model–measurement agreement for mass concentration. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (≈ 3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16–27, 35–61, and 19–35%, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(±3) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μg m −3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies and which is higher on weekends. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr −1 of SOA globally, or 17% of global SOA, one-third of which is likely to be non-fossil.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.5084Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.5084Y">Approaches for Subgrid Parameterization: Does Scaling Help?</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yano, Jun-Ichi 2016-04-01 Arguably the scaling behavior is a well-established fact in many geophysical systems. There are already many theoretical studies elucidating this issue. However, the scaling law is slow to be introduced in "operational" geophysical modelling, notably for weather forecast as well as climate projection models. The main purpose of this presentation is to ask why, and try to answer this question. As a reference point, the presentation reviews the three major approaches for traditional subgrid parameterization: moment, PDF (probability density function), and mode decomposition. The moment expansion is a standard method for describing the subgrid-scale turbulent flows both in the atmosphere and the oceans. The PDF approach is intuitively appealing as it directly deals with a distribution of variables in subgrid scale in a more direct manner. The third category, originally proposed by Aubry et al (1988) in context of the wall boundary-layer turbulence, is specifically designed to represent coherencies in compact manner by a low--dimensional dynamical system. Their original proposal adopts the proper orthogonal decomposition (POD, or empirical orthogonal functions, EOF) as their mode-decomposition basis. However, the methodology can easily be generalized into any decomposition basis. The mass-flux formulation that is currently adopted in majority of atmospheric models for parameterizing convection can also be considered a special case of the mode decomposition, adopting the segmentally-constant modes for the expansion basis. The mode decomposition can, furthermore, be re-interpreted as a type of Galarkin approach for numerically modelling the subgrid-scale processes. Simple extrapolation of this re-interpretation further suggests us that the subgrid parameterization problem may be re-interpreted as a type of mesh-refinement problem in numerical modelling. We furthermore see a link between the subgrid parameterization and downscaling problems along this line. The mode decomposition approach would also be the best framework for linking between the traditional parameterizations and the scaling perspectives. However, by seeing the link more clearly, we also see strength and weakness of introducing the scaling perspectives into parameterizations. Any diagnosis under a mode decomposition would immediately reveal a power-law nature of the spectrum. However, exploiting this knowledge in operational parameterization would be a different story. It is symbolic to realize that POD studies have been focusing on representing the largest-scale coherency within a grid box under a high truncation. This problem is already hard enough. Looking at differently, the scaling law is a very concise manner for characterizing many subgrid-scale variabilities in systems. We may even argue that the scaling law can provide almost complete subgrid-scale information in order to construct a parameterization, but with a major missing link: its amplitude must be specified by an additional condition. The condition called "closure" in the parameterization problem, and known to be a tough problem. We should also realize that the studies of the scaling behavior tend to be statistical in the sense that it hardly provides complete information for constructing a parameterization: can we specify the coefficients of all the decomposition modes by a scaling law perfectly when the first few leading modes are specified? Arguably, the renormalization group (RNG) is a very powerful tool for reducing a system with a scaling behavior into a low dimension, say, under an appropriate mode decomposition procedure. However, RNG is analytical tool: it is extremely hard to apply it to real complex geophysical systems. It appears that it is still a long way to go for us before we can begin to exploit the scaling law in order to construct operational subgrid parameterizations in effective manner. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.5600B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.5600B">Effect of climate change and CO2 inhibition on isoprene emissions in Europe calculated using the ALARO-0 regional climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bauwens, Maite; Müller, Jean-François; Stavrakou, Trisevgeni; De Cruz, Lesley; Van Schaeybroeck, Bert; Termonia, Piet; De Troch, Rozemien; Berckmans, Julie; Hamdi, Rafiq 2017-04-01 Isoprene is the dominant biogenic hydrocarbon emitted in the atmosphere, with global annual emissions estimated at ca. 400-600 Tg (Guenther et al. 2006). It plays a key role in the atmospheric composition because of its influence on tropospheric ozone formation in polluted environments and its contribution to particulate matter. Its emissions depend on the type and abundance of plants, and are modulated by meteorological parameters. Climate changes therefore affect the spatiotemporal and interannual variation of these emissions. In this study we estimate the isoprene fluxes emitted by vegetation in past and future climate over the European (EURO-CORDEX) domain using the MEGAN-MOHYCAN model (Müller et al. 2008, Stavrakou et al. 2014).We first calculate isoprene emissions over 1979-2012 based on the ECMWF ERA-Interim reanalysis data, we compare with available isoprene flux measurements, and we investigate the sensitivity to solar radiation changes observed at European stations. The interannual variability and emission trends on regional and country level are derived and discussed. Next, we perform simulations using the output of the ALARO-0 regional climate model (Giot et al., 2015) forced by the RCP2.6, RCP4.5 and RCP8.5 scenarios over 2071-2099, and compare with the historical emissions over 1976-2005 derived by the same model. Furthermore, we incorporate the inhibition of isoprene emissions to the enhanced CO2 levels of the climate projections through two different parameterizations. The future climate scenarios result in higher isoprene emissions over the European domain increased by 6%, 33% and 82% for the RCP2.6, RCP4.5 and RCP8.5 scenario respectively. However, the CO2 inhibition effect results in an overall decrease of isoprene emissions relative to the standard future simulation, even though this decrease is strongly sensitive to the parameterization used. The different CO2 inhibition simulations in this study show that future isoprene emission are between 11% lower and 26% higher than the present isoprene emissions over Europe. Giot, O. et al.: Validation of the ALARO-0 model within the EURO-CORDEX framework, Geosci. Model Dev. Discuss., 8, 8387-8409, 2015. Guenther, A. et al.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181-3210, 2006. Müller, J.-F. et al.: Global isoprene emissions estimated using MEGAN, ECMWF analyses and a detailed canopy environmental model, Atmos. Chem. Phys., 8, 1329-1341, 2008 Stavrakou, T. et al.: Isoprene emissions over Asia 1979-2012 : impact of climate and land use changes, Atmos. Chem. Phys., 14, 4587-4605, 2014. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20010085343&hterms=lesson+plans&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dlesson%2Bplans','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20010085343&hterms=lesson+plans&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dlesson%2Bplans">Improving Global Modeling and Data Analysis Using Remotely-Sensed Rainfall Data: Lessons From TRMM and Plans for GPM</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hou, Arthur Y.; Einaudi, Franco (Technical Monitor) 2001-01-01 I will discuss the need for accurate rainfall observations to improve our ability to model the earth's climate and improve short-range weather forecasts. I will give an overview of the recent progress in using of rainfall data provided by TRMM and other microwave instruments in data assimilation to improve global analyses and diagnose state-dependent systematic errors in physical parameterizations. I will outline the current and future research strategies in preparation for the Global Precipitation Mission. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990098413&hterms=climate+exchange&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dclimate%2Bexchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990098413&hterms=climate+exchange&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dclimate%2Bexchange">Tropical Convection and Climate Processes in a Cumulus Ensemble Model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Sui, Chung-Hsiung 1999-01-01 Local convective-radiative equilibrium states of the tropical atmosphere are determined by the following external forcing: 1) Insolation, 2) Surface heat and moisture exchanges (primarily radiation and evaporation), 3) Heating and moistening induced by large-scale circulation. Understanding the equilibrium states of the tropical atmosphere in different external forcing conditions is of vital importance for studying cumulus parameterization, climate feedbacks, and climate changes. We extend our previous study using the Goddard Cumulus Ensemble (GCE) Model which resolves convective-radiative processes more explicitly than global climate models do. Several experiments are carried out under fixed insolation and sea surface temperature. The prescribed SST consists of a uniform warm pool (29C) surrounded by uniform cold SST (26C). The model produces "Walker"-type circulation with the ascending branch of the model atmosphere more humid than the descending part, but the vertically integrated temperature does not show a horizontal gradient. The results are compared with satellite measured moisture by SSM/I (Special Sensor Microwave/Imager) and temperature by MSU in the ascending and descending tropical atmosphere. The vertically integrated temperature and humidity in the two model regimes are comparable to the observed values in the tropics. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A11A0018W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A11A0018W">Evaluating Lightning-generated NOx (LNOx) Parameterization based on Cloud Top Height at Resolutions with Partially-resolved Convection for Upper Tropospheric Chemistry Studies</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wong, J.; Barth, M. C.; Noone, D. C. 2012-12-01 Lightning-generated nitrogen oxides (LNOx) is an important precursor to tropospheric ozone production. With a meteorological time-scale variability similar to that of the ozone chemical lifetime, it can nonlinearly perturb tropospheric ozone concentration. Coupled with upper-air circulation patterns, LNOx can accumulate in significant amount in the upper troposphere with other precursors, thus enhancing ozone production (see attached figure). While LNOx emission has been included and tuned extensively in global climate models, its inclusions in regional chemistry models are seldom tested. Here we present a study that evaluates the frequently used Price and Rind parameterization based on cloud-top height at resolutions that partially resolve deep convection using the Weather Research and Forecasting model with Chemistry (WRF-Chem) over the contiguous United States. With minor modifications, the parameterization is shown to generate integrated flash counts close to those observed. However, the modeled frequency distribution of cloud-to-ground flashes do not represent well for storms with high flash rates, bringing into question the applicability of the intra-cloud/ground partitioning (IC:CG) formulation of Price and Rind in some studies. Resolution dependency also requires attention when sub-grid cloud-tops are used instead of the originally intended grid-averaged cloud-top. LNOx passive tracers being gathered by monsoonal upper tropospheric anticyclone. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active">22</li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active">23</li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017SPIE10405E..0DK','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017SPIE10405E..0DK">Effects of microphysics parameterization on simulations of summer heavy precipitation in the Yangtze-Huaihe Region, China</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kan, Yu; Chen, Bo; Shen, Tao; Liu, Chaoshun; Qiao, Fengxue 2017-09-01 It has been a longstanding problem for current weather/climate models to accurately predict summer heavy precipitation over the Yangtze-Huaihe Region (YHR) which is the key flood-prone area in China with intensive population and developed economy. Large uncertainty has been identified with model deficiencies in representing precipitation processes such as microphysics and cumulus parameterizations. This study focuses on examining the effects of microphysics parameterization on the simulation of different type of heavy precipitation over the YHR taking into account two different cumulus schemes. All regional persistent heavy precipitation events over the YHR during 2008-2012 are classified into three types according to their weather patterns: the type I associated with stationary front, the type II directly associated with typhoon or with its spiral rain band, and the type III associated with strong convection along the edge of the Subtropical High. Sixteen groups of experiments are conducted for three selected cases with different types and a local short-time rainstorm in Shanghai, using the WRF model with eight microphysics and two cumulus schemes. Results show that microphysics parameterization has large but different impacts on the location and intensity of regional heavy precipitation centers. The Ferrier (microphysics) -BMJ (cumulus) scheme and Thompson (microphysics) - KF (cumulus) scheme most realistically simulates the rain-bands with the center location and intensity for type I and II respectively. For type III, the Lin microphysics scheme shows advantages in regional persistent cases over YHR, while the WSM5 microphysics scheme is better in local short-term case, both with the BMJ cumulus scheme. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1239491-improved-hindcast-approach-evaluation-diagnosis-physical-processes-global-climate-models','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1239491-improved-hindcast-approach-evaluation-diagnosis-physical-processes-global-climate-models">An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Ma, H. -Y.; Chuang, C. C.; Klein, S. A.; ... 2015-11-06 Here, we present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge onlymore » the model horizontal velocities towards operational analysis/reanalysis values, given a 6-hour relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an offline land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a “Core” integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modelled cloud-associated processes relative to observations.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JAMES...7.1810M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JAMES...7.1810M">An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ma, H.-Y.; Chuang, C. C.; Klein, S. A.; Lo, M.-H.; Zhang, Y.; Xie, S.; Zheng, X.; Ma, P.-L.; Zhang, Y.; Phillips, T. J. 2015-12-01 We present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature, and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge only the model horizontal velocities toward operational analysis/reanalysis values, given a 6 h relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature, and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an off-line land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a "Core" integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modeled cloud-associated processes relative to observations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5016774','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5016774">Short‐term time step convergence in a climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Rasch, Philip J.; Taylor, Mark A.; Jablonowski, Christiane 2015-01-01 Abstract This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid‐scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full‐physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid‐scale physical parameterizations, the stratiform cloud schemes are associated with the largest time‐stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time‐stepping errors and identify the related model sensitivities. PMID:27660669 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PhDT........52E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PhDT........52E">High Resolution Hydro-climatological Projections for Western Canada</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Erler, Andre Richard Accurate identification of the impact of global warming on water resources and hydro-climatic extremes represents a significant challenge to the understanding of climate change on the regional scale. Here an analysis of hydro-climatic changes in western Canada is presented, with specific focus on the Fraser and Athabasca River basins and on changes in hydro-climatic extremes. The analysis is based on a suite of simulations designed to characterize internal variability, as well as model uncertainty. A small ensemble of Community Earth System Model version 1 (CESM1) simulations was employed to generate global climate projections, which were downscaled to 10 km resolution using the Weather Research and Forecasting model (WRF V3.4.1) with several sets of physical parameterizations. Downscaling was performed for a historical validation period and a mid- and end-21st-century projection period, using the RCP8.5 greenhouse gas trajectory. Daily station observations and monthly gridded datasets were used for validation. Changes in hydro-climatic extremes are characterized using Extreme Value Analysis. A novel method of aggregating data from climatologically similar stations was employed to increase the statistical power of the analysis. Changes in mean and extreme precipitation are found to differ strongly between seasons and regions, but (relative) changes in extremes generally follow changes in the (seasonal) mean. At the end of the 21st century, precipitation and precipitation extremes are projected to increase by 30% at the coast in fall and land-inwards in winter, while the projected increase in summer precipitation is smaller and changes in extremes are often not statistically significant. Reasons for the differences between seasons, the role of precipitation recycling in atmospheric water transport, and the sensitivity to physics parameterizations are discussed. Major changes are projected for the Fraser River basin, including earlier snowmelt and a 50% reduction in peak runoff. Combined with higher evapotranspiration, a significant increase in late summer drought risk is likely, but increasing fall precipitation might also increase the risk of moderate flooding. In the Athabasca River basin, increasing winter precipitation and snowmelt is balanced by increasing evapotranspiration in summer and no significant change in flood or drought risk is projected. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC12B..05D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC12B..05D">Quantified Objectives for Assessing the Contribution of Low Clouds to Climate Sensitivity and Variability</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Del Genio, A. D.; Platnick, S. E.; Bennartz, R.; Klein, S. A.; Marchand, R.; Oreopoulos, L.; Pincus, R.; Wood, R. 2016-12-01 Low clouds are central to leading-order questions in climate and subseasonal weather predictability, and are key to the NRC panel report's goals "to understand the signals of the Earth system under a changing climate" and "for improved models and model projections." To achieve both goals requires a mix of continuity observations to document the components of the changing climate and improvements in retrievals of low cloud and boundary layer dynamical/thermodynamic properties to ensure process-oriented observations that constrain the parameterized physics of the models. We discuss four climate/weather objectives that depend sensitively on understanding the behavior of low clouds: 1. Reduce uncertainty in GCM-inferred climate sensitivity by 50% by constraining subtropical low cloud feedbacks. 2. Eliminate the GCM Southern Ocean shortwave flux bias and its effect on cloud feedback and the position of the midlatitude storm track. 3. Eliminate the double Intertropical Convergence Zone bias in GCMs and its potential effects on tropical precipitation over land and the simulation and prediction of El Niño. 4. Increase the subseasonal predictability of tropical warm pool precipitation from 20 to 30 days. We envision advances in three categories of observations that would be highly beneficial for reaching these goals: 1. More accurate observations will facilitate more thorough evaluation of clouds in GCMs. 2. Better observations of the links between cloud properties and the environmental state will be used as the foundation for parameterization improvements. 3. Sufficiently long and higher quality records of cloud properties and environmental state will constrain low cloud feedback purely observationally. To accomplish this, the greatest need is to replace A-Train instruments, which are nearing end-of-life, with enhanced versions. The requirements are sufficient horizontal and vertical resolution to capture boundary layer cloud and thermodynamic spatial structure; more accurate determination of cloud condensate profiles and optical properties; near-coincident observations to permit multi-instrument retrievals and association with dynamic and thermodynamic structure; global coverage; and, for long-term monitoring, measurement and orbit stability and sufficient mission duration. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JCoPh.361..331P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JCoPh.361..331P">Computation at a coordinate singularity</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Prusa, Joseph M. 2018-05-01 Coordinate singularities are sometimes encountered in computational problems. An important example involves global atmospheric models used for climate and weather prediction. Classical spherical coordinates can be used to parameterize the manifold - that is, generate a grid for the computational spherical shell domain. This particular parameterization offers significant benefits such as orthogonality and exact representation of curvature and connection (Christoffel) coefficients. But it also exhibits two polar singularities and at or near these points typical continuity/integral constraints on dependent fields and their derivatives are generally inadequate and lead to poor model performance and erroneous results. Other parameterizations have been developed that eliminate polar singularities, but problems of weaker singularities and enhanced grid noise compared to spherical coordinates (away from the poles) persist. In this study reparameterization invariance of geometric objects (scalars, vectors and the forms generated by their covariant derivatives) is utilized to generate asymptotic forms for dependent fields of interest valid in the neighborhood of a pole. The central concept is that such objects cannot be altered by the metric structure of a parameterization. The new boundary conditions enforce symmetries that are required for transformations of geometric objects. They are implemented in an implicit polar filter of a structured grid, nonhydrostatic global atmospheric model that is simulating idealized Held-Suarez flows. A series of test simulations using different configurations of the asymptotic boundary conditions are made, along with control simulations that use the default model numerics with no absorber, at three different grid sizes. Typically the test simulations are ∼ 20% faster in wall clock time than the control-resulting from a decrease in noise at the poles in all cases. In the control simulations adverse numerical effects from the polar singularity are observed to increase with grid resolution. In contrast, test simulations demonstrate robust polar behavior independent of grid resolution. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29293851','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29293851">Multisite Evaluation of APEX for Water Quality: II. Regional Parameterization.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Nelson, Nathan O; Baffaut, Claire; Lory, John A; Anomaa Senaviratne, G M M M; Bhandari, Ammar B; Udawatta, Ranjith P; Sweeney, Daniel W; Helmers, Matt J; Van Liew, Mike W; Mallarino, Antonio P; Wortmann, Charles S 2017-11-01 Phosphorus (P) Index assessment requires independent estimates of long-term average annual P loss from fields, representing multiple climatic scenarios, management practices, and landscape positions. Because currently available measured data are insufficient to evaluate P Index performance, calibrated and validated process-based models have been proposed as tools to generate the required data. The objectives of this research were to develop a regional parameterization for the Agricultural Policy Environmental eXtender (APEX) model to estimate edge-of-field runoff, sediment, and P losses in restricted-layer soils of Missouri and Kansas and to assess the performance of this parameterization using monitoring data from multiple sites in this region. Five site-specific calibrated models (SSCM) from within the region were used to develop a regionally calibrated model (RCM), which was further calibrated and validated with measured data. Performance of the RCM was similar to that of the SSCMs for runoff simulation and had Nash-Sutcliffe efficiency (NSE) > 0.72 and absolute percent bias (|PBIAS|) < 18% for both calibration and validation. The RCM could not simulate sediment loss (NSE < 0, |PBIAS| > 90%) and was particularly ineffective at simulating sediment loss from locations with small sediment loads. The RCM had acceptable performance for simulation of total P loss (NSE > 0.74, |PBIAS| < 30%) but underperformed the SSCMs. Total P-loss estimates should be used with caution due to poor simulation of sediment loss. Although we did not attain our goal of a robust regional parameterization of APEX for estimating sediment and total P losses, runoff estimates with the RCM were acceptable for P Index evaluation. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20090042915&hterms=process+validation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dprocess%2Bvalidation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20090042915&hterms=process+validation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dprocess%2Bvalidation">Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J. 2009-01-01 Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4063477','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4063477">Predicting future coexistence in a North American ant community</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Bewick, Sharon; Stuble, Katharine L; Lessard, Jean-Phillipe; Dunn, Robert R; Adler, Frederick R; Sanders, Nathan J 2014-01-01 Global climate change will remodel ecological communities worldwide. However, as a consequence of biotic interactions, communities may respond to climate change in idiosyncratic ways. This makes predictive models that incorporate biotic interactions necessary. We show how such models can be constructed based on empirical studies in combination with predictions or assumptions regarding the abiotic consequences of climate change. Specifically, we consider a well-studied ant community in North America. First, we use historical data to parameterize a basic model for species coexistence. Using this model, we determine the importance of various factors, including thermal niches, food discovery rates, and food removal rates, to historical species coexistence. We then extend the model to predict how the community will restructure in response to several climate-related changes, such as increased temperature, shifts in species phenology, and altered resource availability. Interestingly, our mechanistic model suggests that increased temperature and shifts in species phenology can have contrasting effects. Nevertheless, for almost all scenarios considered, we find that the most subordinate ant species suffers most as a result of climate change. More generally, our analysis shows that community composition can respond to climate warming in nonintuitive ways. For example, in the context of a community, it is not necessarily the most heat-sensitive species that are most at risk. Our results demonstrate how models that account for niche partitioning and interspecific trade-offs among species can be used to predict the likely idiosyncratic responses of local communities to climate change. PMID:24963378 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1334768','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1334768">Using ARM Measurements to Understand and Reduce the Double ITCZ Biases in the Community Atmospheric Model</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Zhang, Minghua 1. Understanding of the observed variability of ITCZ in the equatorial eastern Pacific. The annual mean precipitation in the eastern Pacific has a maximum zonal band north of the equator in the ITCZ where the maximum SST is located. During the boreal spring (referring to February, March, and April throughout the present paper), because of the accumulated solar radiation heating and oceanic heat transport, a secondary maximum of SST exists in the southeastern equatorial Pacific. Associated with this warm SST is also a seasonal transitional maximum of precipitation in the same region in boreal spring, exhibited as a weak doublemore » ITCZ pattern in the equatorial eastern Pacific. This climatological seasonal variation, however, varies greatly from year to year: double ITCZ in the boreal spring occurs in some years but not in other years; when there a single ITCZ, it can appear either north, south or at the equator. Understanding this observed variability is critical to find the ultimate cause of the double ITCZ in climate models. Seasonal variation of ITCZ south of the eastern equatorial Pacific: By analyzing data from satellites, field measurements and atmospheric reanalysis, we have found that in the region where spurious ITCZ in models occurs, there is a “seasonal cloud transition” — from stratocumulus to shallow cumulus and eventually to deep convection —in the South Equatorial Pacific (SEP) from September to April that is similar to the spatial cloud transition from the California coast to the equator. This seasonal transition is associated with increasing sea surface temperature (SST), decreasing lower tropospheric stability and large-scale subsidence. This finding of seasonal cloud transition points to the same source of model errors in the ITCZ simulations as in simulation of stratocumulus-cumulus-deep convection transition. It provides a test for climate models to simulate the relationships between clouds and large-scale atmospheric fields in a region that features a spurious double Inter-tropical Convergence Zone (ITCZ) in most models. This work is recently published in Yu et al. (2016). Interannual variation of ITCZ south of the eastern equatorial Pacific: By analyzing data from satellites, field measurements and atmospheric reanalysis, we have characterized the interannual variation of boreal spring precipitation in the eastern tropical Pacific and found the cause of the observed interannual variability. We have shown that ITCZ in this region can occur as a single ITCZ along the Equator, single ITCZ north of the Equator, single ITCZ south of the Equator, and double ITCZ on both sides of the Equator. We have found that convective instability only plays a secondary role in the ITCZ interannual variability. Instead, the remote impact of the Pacific basin-wide SST on the horizontal gradient of surface pressure and wind convergence is the primary driver of this interannual variability. Results point to the need to include moisture convergence in convection schemes to improve the simulation of precipitation in the eastern tropical Pacific. This result has been recently submitted for publication (Yu and Zhang 2016). 2. Improvement of model parameterizations to reduce the double ITCZ bias We analyzed the current status of climate model performance in simulating precipitation in the equatorial Pacific. We have found that the double ITCZ bias has not been reduced in CMIP5 models relative to CMIP4 models. We have characterized the dynamic structure of the common bias by using precipitation, sea surface temperature, surface winds and sea-level. Results are published in Zhang et al. (2015): Since cumulus convection plays a significant role in the double ITCZ behavior in models, we have used measurements from ARM and other sources to carry out a systematic analysis of the roles of shallow and deep convection in the CAM. We found that in both CAM4 and CAM5, when the intensity of deep convection decreases as a result of parameterization change, the intensity of shallow convection increases, leading to very different changes in precipitation partitions but little change in the total precipitation. The different precipitation partition however can manifest themselves in other measures of model performances including temperature and humidity. This study points to the need to treat model physical parameterizations as integrated system rather than individual components. Results from this study are published in Wang and Zhang (2013). Since shallow convection interacts with the deep convection scheme and surface turbulence to trigger the double ITCZ, we studied methods to improve the shallow convection scheme in climate models. We investigated the bulk budgets of the vertical velocity and its parameterization in convective cores, convective updrafts, and clouds by using large-eddy simulation (LES) of four shallow convection cases including one from ARM. We proposed optimal forms of the Simpson and Wiggert equation to calculate the vertical velocity in bulk mass flux convection schemes for convective cores, convective updrafts, and convective clouds as parameterization schemes. The new scheme is published in Wang and Zhang (2014). By using long-term radar-based ground measurements from ARM, we derived a scale-aware inhomogeneity parameterization of cloud liquid water in climate models. We found a relationship between the inhomogeneity parameter and the model grid size as well as atmospheric stability. This relationship is implemented in the CESM to describe the subgrid-scale cloud inhomogeneity. Relative to the default CESM with the finite-volume dynamic core at 2-degree resolution, the new parameterization leads to smaller cloud inhomogeneity and larger cloud liquid-water path in high latitudes, and the opposite effect in low latitudes, with the regional impact on shortwave cloud radiation effect of up to 10 W/m 2. This is due to both the smaller (larger) grid size in high (low) latitudes in the longitude-latitude grid setting of CESM and the more stable (unstable) atmosphere. This parameterization is expected lead to more realistic simulation of tropical precipitation in high-resolution models. Results from this study are reported in Xie and Zhang (2015).« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50..391K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50..391K">Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kim, Go-Un; Seo, Kyong-Hwan 2018-01-01 A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B24D..05S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B24D..05S">Understanding and quantifying foliar temperature acclimation for Earth System Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Smith, N. G.; Dukes, J. 2015-12-01 Photosynthesis and respiration on land are the two largest carbon fluxes between the atmosphere and Earth's surface. The parameterization of these processes represent major uncertainties in the terrestrial component of the Earth System Models used to project future climate change. Research has shown that much of this uncertainty is due to the parameterization of the temperature responses of leaf photosynthesis and autotrophic respiration, which are typically based on short-term empirical responses. Here, we show that including longer-term responses to temperature, such as temperature acclimation, can help to reduce this uncertainty and improve model performance, leading to drastic changes in future land-atmosphere carbon feedbacks across multiple models. However, these acclimation formulations have many flaws, including an underrepresentation of many important global flora. In addition, these parameterizations were done using multiple studies that employed differing methodology. As such, we used a consistent methodology to quantify the short- and long-term temperature responses of maximum Rubisco carboxylation (Vcmax), maximum rate of Ribulos-1,5-bisphosphate regeneration (Jmax), and dark respiration (Rd) in multiple species representing each of the plant functional types used in global-scale land surface models. Short-term temperature responses of each process were measured in individuals acclimated for 7 days at one of 5 temperatures (15-35°C). The comparison of short-term curves in plants acclimated to different temperatures were used to evaluate long-term responses. Our analyses indicated that the instantaneous response of each parameter was highly sensitive to the temperature at which they were acclimated. However, we found that this sensitivity was larger in species whose leaves typically experience a greater range of temperatures over the course of their lifespan. These data indicate that models using previous acclimation formulations are likely incorrectly simulating leaf carbon exchange responses to future warming. Therefore, our data, if used to parameterize large-scale models, are likely to provide an even greater improvement in model performance, resulting in more reliable projections of future carbon-clime feedbacks. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1235486-complex-functionality-minimal-computation-promise-pitfalls-reduced-tracer-ocean-biogeochemistry-models','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1235486-complex-functionality-minimal-computation-promise-pitfalls-reduced-tracer-ocean-biogeochemistry-models">Complex functionality with minimal computation. Promise and pitfalls of reduced-tracer ocean biogeochemistry models</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Galbraith, Eric D.; Dunne, John P.; Gnanadesikan, Anand; ... 2015-12-21 Earth System Models increasingly include ocean biogeochemistry models in order to predict changes in ocean carbon storage, hypoxia, and biological productivity under climate change. However, state-of-the-art ocean biogeochemical models include many advected tracers, that significantly increase the computational resources required, forcing a trade-off with spatial resolution. Here, we compare a state-of the art model with 30 prognostic tracers (TOPAZ) with two reduced-tracer models, one with 6 tracers (BLING), and the other with 3 tracers (miniBLING). The reduced-tracer models employ parameterized, implicit biological functions, which nonetheless capture many of the most important processes resolved by TOPAZ. All three are embedded inmore » the same coupled climate model. Despite the large difference in tracer number, the absence of tracers for living organic matter is shown to have a minimal impact on the transport of nutrient elements, and the three models produce similar mean annual preindustrial distributions of macronutrients, oxygen, and carbon. Significant differences do exist among the models, in particular the seasonal cycle of biomass and export production, but it does not appear that these are necessary consequences of the reduced tracer number. With increasing CO2, changes in dissolved oxygen and anthropogenic carbon uptake are very similar across the different models. Thus, while the reduced-tracer models do not explicitly resolve the diversity and internal dynamics of marine ecosystems, we demonstrate that such models are applicable to a broad suite of major biogeochemical concerns, including anthropogenic change. Lastly, these results are very promising for the further development and application of reduced-tracer biogeochemical models that incorporate ‘‘sub-ecosystem-scale’’ parameterizations.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC43E1208E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC43E1208E">Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D. 2016-12-01 Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27185925','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27185925">Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Medeiros, Brian; Nuijens, Louise 2016-05-31 Trade wind regions cover most of the tropical oceans, and the prevailing cloud type is shallow cumulus. These small clouds are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these clouds in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that clouds in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados Cloud Observatory are relevant to clouds across the tropics. The same methods are applied to climate models to evaluate the simulated clouds. The models generally capture the cloud radiative effect, but underestimate cloud cover and show an array of cloud vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of cloud and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to cloud feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4896687','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4896687">Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Nuijens, Louise 2016-01-01 Trade wind regions cover most of the tropical oceans, and the prevailing cloud type is shallow cumulus. These small clouds are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these clouds in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that clouds in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados Cloud Observatory are relevant to clouds across the tropics. The same methods are applied to climate models to evaluate the simulated clouds. The models generally capture the cloud radiative effect, but underestimate cloud cover and show an array of cloud vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of cloud and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to cloud feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection. PMID:27185925 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1981JAtS...38.2327G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1981JAtS...38.2327G">On Diffusive Climatological Models.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Griffel, D. H.; Drazin, P. G. 1981-11-01 A simple, zonally and annually averaged, energy-balance climatological model with diffusive heat transport and nonlinear albedo feedback is solved numerically. Some parameters of the model are varied, one by one, to find the resultant effects on the steady solution representing the climate. In particular, the outward radiation flux, the insulation distribution and the albedo parameterization are varied. We have found an accurate yet simple analytic expression for the mean annual insolation as a function of latitude and the obliquity of the Earth's rotation axis; this has enabled us to consider the effects of the oscillation of the obliquity. We have used a continuous albedo function which fits the observed values; it considerably reduces the sensitivity of the model. Climatic cycles, calculated by solving the time-dependent equation when parameters change slowly and periodically, are compared qualitatively with paleoclimatic records. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A43G0370Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A43G0370Z">Impact of anthropogenic aerosols on regional climate change in Beijing, China</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhao, B.; Liou, K. N.; He, C.; Lee, W. L.; Gu, Y.; Li, Q.; Leung, L. R. 2015-12-01 Anthropogenic aerosols affect regional climate significantly through radiative (direct and semi-direct) and indirect effects, but the magnitude of these effects over megacities are subject to large uncertainty. In this study, we evaluated the effects of anthropogenic aerosols on regional climate change in Beijing, China using the online-coupled Weather Research and Forecasting/Chemistry Model (WRF/Chem) with the Fu-Liou-Gu radiation scheme and a spatial resolution of 4km. We further updated this radiation scheme with a geometric-optics surface-wave (GOS) approach for the computation of light absorption and scattering by black carbon (BC) particles in which aggregation shape and internal mixing properties are accounted for. In addition, we incorporated in WRF/Chem a 3D radiative transfer parameterization in conjunction with high-resolution digital data for city buildings and landscape to improve the simulation of boundary-layer, surface solar fluxes and associated sensible/latent heat fluxes. Preliminary simulated meteorological parameters, fine particles (PM2.5) and their chemical components agree well with observational data in terms of both magnitude and spatio-temporal variations. The effects of anthropogenic aerosols, including BC, on radiative forcing, surface temperature, wind speed, humidity, cloud water path, and precipitation are quantified on the basis of simulation results. With several preliminary sensitivity runs, we found that meteorological parameters and aerosol radiative effects simulated with the incorporation of improved BC absorption and 3-D radiation parameterizations deviate substantially from simulation results using the conventional homogeneous/core-shell configuration for BC and the plane-parallel model for radiative transfer. Understanding of the aerosol effects on regional climate change over megacities must consider the complex shape and mixing state of aerosol aggregates and 3D radiative transfer effects over city landscape. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ERL....13d4028M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ERL....13d4028M">Simulated cold bias being improved by using MODIS time-varying albedo in the Tibetan Plateau in WRF model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Meng, X.; Lyu, S.; Zhang, T.; Zhao, L.; Li, Z.; Han, B.; Li, S.; Ma, D.; Chen, H.; Ao, Y.; Luo, S.; Shen, Y.; Guo, J.; Wen, L. 2018-04-01 Systematic cold biases exist in the simulation for 2 m air temperature in the Tibetan Plateau (TP) when using regional climate models and global atmospheric general circulation models. We updated the albedo in the Weather Research and Forecasting (WRF) Model lower boundary condition using the Global LAnd Surface Satellite Moderate-Resolution Imaging Spectroradiometer albedo products and demonstrated evident improvement for cold temperature biases in the TP. It is the large overestimation of albedo in winter and spring in the WRF model that resulted in the large cold temperature biases. The overestimated albedo was caused by the simulated precipitation biases and over-parameterization of snow albedo. Furthermore, light-absorbing aerosols can result in a large reduction of albedo in snow and ice cover. The results suggest the necessity of developing snow albedo parameterization using observations in the TP, where snow cover and melting are very different from other low-elevation regions, and the influence of aerosols should be considered as well. In addition to defining snow albedo, our results show an urgent call for improving precipitation simulation in the TP. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active">23</li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active">24</li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFM.A52C0807W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFM.A52C0807W">Evaluation of WRF Model Against Satellite and Field Measurements During ARM March 2000 IOP</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wu, J.; Zhang, M. 2003-12-01 Meso-scale WRF model is employed to simulate the organization of clouds related with the cyclogenesis occurred during March 1-4, 2000 over ARM SGP CART site. Qualitative comparisons of simulated clouds with GOES8 satellite images show that the WRF model can capture the main features of clouds related with the cyclogenesis. The simulated precipitation patterns also match the Radar reflectivity images well. Further evaluation of the simulated features on GCM grid-scale is conducted against ARM field measurements. The evaluation shows that the evolutions of the simulated state fields such as temperature and moisture, the simulated wind fields and the derived large-scale temperature and moisture tendencies closely follow the observed patterns. These results encourages us to use meso-scale WRF model as a tool to verify the performance of GCMs in simulating cloud feedback processes related with the frontal clouds such that we can test and validate the current cloud parameterizations in climate models, and make possible improvements to different components of current cloud parameterizations in GCMs. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/946355-generalized-subsurface-flow-parameterization-considering-subgrid-spatial-variability-recharge-topography','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/946355-generalized-subsurface-flow-parameterization-considering-subgrid-spatial-variability-recharge-topography">A Generalized Subsurface Flow Parameterization Considering Subgrid Spatial Variability of Recharge and Topography</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Huang, Maoyi; Liang, Xu; Leung, Lai R. 2008-12-05 Subsurface flow is an important hydrologic process and a key component of the water budget, especially in humid regions. In this study, a new subsurface flow formulation is developed that incorporates spatial variability of both topography and recharge. It is shown through theoretical derivation and case studies that the power law and exponential subsurface flow parameterizations and the parameterization proposed by Woods et al.[1997] are all special cases of the new formulation. The subsurface flows calculated using the new formulation compare well with values derived from observations at the Tulpehocken Creek and Walnut Creek watersheds. Sensitivity studies show that whenmore » the spatial variability of topography or recharge, or both is increased, the subsurface flows increase at the two aforementioned sites and the Maimai hillslope. This is likely due to enhancement of interactions between the groundwater table and the land surface that reduce the flow path. An important conclusion of this study is that the spatial variability of recharge alone, and/or in combination with the spatial variability of topography can substantially alter the behaviors of subsurface flows. This suggests that in macroscale hydrologic models or land surface models, subgrid variations of recharge and topography can make significant contributions to the grid mean subsurface flow and must be accounted for in regions with large surface heterogeneity. This is particularly true for regions with humid climate and relatively shallow groundwater table where the combined impacts of spatial variability of recharge and topography are shown to be more important. For regions with arid climate and relatively deep groundwater table, simpler formulations, especially the power law, for subsurface flow can work well, and the impacts of subgrid variations of recharge and topography may be ignored.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016HESS...20.2811O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016HESS...20.2811O">Using dry and wet year hydroclimatic extremes to guide future hydrologic projections</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Oni, Stephen; Futter, Martyn; Ledesma, Jose; Teutschbein, Claudia; Buttle, Jim; Laudon, Hjalmar 2016-07-01 There are growing numbers of studies on climate change impacts on forest hydrology, but limited attempts have been made to use current hydroclimatic variabilities to constrain projections of future climatic conditions. Here we used historical wet and dry years as a proxy for expected future extreme conditions in a boreal catchment. We showed that runoff could be underestimated by at least 35 % when dry year parameterizations were used for wet year conditions. Uncertainty analysis showed that behavioural parameter sets from wet and dry years separated mainly on precipitation-related parameters and to a lesser extent on parameters related to landscape processes, while uncertainties inherent in climate models (as opposed to differences in calibration or performance metrics) appeared to drive the overall uncertainty in runoff projections under dry and wet hydroclimatic conditions. Hydrologic model calibration for climate impact studies could be based on years that closely approximate anticipated conditions to better constrain uncertainty in projecting extreme conditions in boreal and temperate regions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22816320','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22816320">Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Shaw, Ruth G; Etterson, Julie R 2012-09-01 Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910038929&hterms=balance+general&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dbalance%2Bgeneral','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910038929&hterms=balance+general&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dbalance%2Bgeneral">Clouds-radiation interactions in a general circulation model - Impact upon the planetary radiation balance</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Smith, Laura D.; Vonder Haar, Thomas H. 1991-01-01 Simultaneously conducted observations of the earth radiation budget and the cloud amount estimates, taken during the June 1979 - May 1980 Nimbus 7 mission were used to show interactions between the cloud amount and raidation and to verify a long-term climate simulation obtained with the latest version of the NCAR Community Climate Model (CCM). The parameterization of the radiative, dynamic, and thermodynamic processes produced the mean radiation and cloud quantities that were in reasonable agreement with satellite observations, but at the expense of simulating their short-term fluctuations. The results support the assumption that the inclusion of the cloud liquid water (ice) variable would be the best mean to reduce the blinking of clouds in NCAR CCM. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A21F0138P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A21F0138P">Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M. 2016-12-01 Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B13E0662S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B13E0662S">Abiotic and biotic determinants of leaf carbon exchange capacity from tropical to high boreal biomes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Smith, N. G.; Dukes, J. S. 2016-12-01 Photosynthesis and respiration on land represent the two largest fluxes of carbon dioxide between the atmosphere and the Earth's surface. As such, the Earth System Models that are used to project climate change are high sensitive to these processes. Studies have found that much of this uncertainty is due to the formulation and parameterization of plant photosynthetic and respiratory capacity. Here, we quantified the abiotic and biotic factors that determine photosynthetic and respiratory capacity at large spatial scales. Specifically, we measured the maximum rate of Rubisco carboxylation (Vcmax), the maximum rate of Ribulose-1,5-bisphosphate regeneration (Jmax), and leaf dark respiration (Rd) in >600 individuals of 98 plant species from the tropical to high boreal biomes of Northern and Central America. We also measured a bevy of covariates including plant functional type, leaf nitrogen content, short- and long-term climate, leaf water potential, plant size, and leaf mass per area. We found that plant functional type and leaf nitrogen content were the primary determinants of Vcmax, Jmax, and Rd. Mean annual temperature and mean annual precipitation were not significant predictors of these rates. However, short-term climatic variables, specifically soil moisture and air temperature over the previous 25 days, were significant predictors and indicated that heat and soil moisture deficits combine to reduce photosynthetic capacity and increase respiratory capacity. Finally, these data were used as a model benchmarking tool for the Community Land Model version 4.5 (CLM 4.5). The benchmarking analyses determined errors in the leaf nitrogen allocation scheme of CLM 4.5. Under high leaf nitrogen levels within a plant type the model overestimated Vcmax and Jmax. This result suggested that plants were altering their nitrogen allocation patterns when leaf nitrogen levels were high, an effect that was not being captured by the model. These data, taken with models in mind, provide paths forward for improving model structure and parameterization of leaf carbon exchange at large spatial scales. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AIPC.1100..611C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AIPC.1100..611C">Incorporation of UK Met Office's radiation scheme into CPTEC's global model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chagas, Júlio C. S.; Barbosa, Henrique M. J. 2009-03-01 Current parameterization of radiation in the CPTEC's (Center for Weather Forecast and Climate Studies, Cachoeira Paulista, SP, Brazil) operational AGCM has its origins in the work of Harshvardhan et al. (1987) and uses the formulation of Ramaswamy and Freidenreich (1992) for the short-wave absorption by water vapor. The UK Met Office's radiation code (Edwards and Slingo, 1996) was incorporated into CPTEC's global model, initially for short-wave only, and some impacts of that were shown by Chagas and Barbosa (2006). Current paper presents some impacts of the complete incorporation (both short-wave and long-wave) of UK Met Office's scheme. Selected results from off-line comparisons with line-by-line benchmark calculations are shown. Impacts on the AGCM's climate are assessed by comparing output of climate runs of current and modified AGCM with products from GEWEX/SRB (Surface Radiation Budget) project. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70113710','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70113710">Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C. 1993-01-01 Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015DSRII.113..280D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015DSRII.113..280D">An aerobic scope-based habitat suitability index for predicting the effects of multi-dimensional climate change stressors on marine teleosts</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Del Raye, Gen; Weng, Kevin C. 2015-03-01 Climate change will expose many marine ecosystems to temperature, oxygen and CO2 conditions that have not been experienced for millennia. Predicting the impact of these changes on marine fishes is difficult due to the complexity of these disparate stressors and the inherent non-linearity of physiological systems. Aerobic scope (the difference between maximum and minimum aerobic metabolic rates) is a coherent, unifying physiological framework that can be used to examine all of the major environmental changes expected to occur in the oceans during this century. Using this framework, we develop a physiology-based habitat suitability model to forecast the response of marine fishes to simultaneous ocean acidification, warming and deoxygenation, including interactions between all three stressors. We present an example of the model parameterized for Thunnus albacares (yellowfin tuna), an important fisheries species that is likely to be affected by climate change. We anticipate that if embedded into multispecies ecosystem models, our model could help to more precisely forecast climate change impacts on the distribution and abundance of other high value species. Finally, we show how our model may indicate the potential for, and limits of, adaptation to chronic stressors. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A11N0269L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A11N0269L">The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lucas, S. E.; Todd, J. F. 2015-12-01 The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability - DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C31C..08L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C31C..08L">Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Li, Y.; Kurkute, S.; Chen, L. 2017-12-01 Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUFMSF31A0714P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUFMSF31A0714P">Flexible Environments for Grand-Challenge Simulation in Climate Science</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pierrehumbert, R.; Tobis, M.; Lin, J.; Dieterich, C.; Caballero, R. 2004-12-01 Current climate models are monolithic codes, generally in Fortran, aimed at high-performance simulation of the modern climate. Though they adequately serve their designated purpose, they present major barriers to application in other problems. Tailoring them to paleoclimate of planetary simulations, for instance, takes months of work. Theoretical studies, where one may want to remove selected processes or break feedback loops, are similarly hindered. Further, current climate models are of little value in education, since the implementation of textbook concepts and equations in the code is obscured by technical detail. The Climate Systems Center at the University of Chicago seeks to overcome these limitations by bringing modern object-oriented design into the business of climate modeling. Our ultimate goal is to produce an end-to-end modeling environment capable of configuring anything from a simple single-column radiative-convective model to a full 3-D coupled climate model using a uniform, flexible interface. Technically, the modeling environment is implemented as a Python-based software component toolkit: key number-crunching procedures are implemented as discrete, compiled-language components 'glued' together and co-ordinated by Python, combining the high performance of compiled languages and the flexibility and extensibility of Python. We are incrementally working towards this final objective following a series of distinct, complementary lines. We will present an overview of these activities, including PyOM, a Python-based finite-difference ocean model allowing run-time selection of different Arakawa grids and physical parameterizations; CliMT, an atmospheric modeling toolkit providing a library of 'legacy' radiative, convective and dynamical modules which can be knitted into dynamical models, and PyCCSM, a version of NCAR's Community Climate System Model in which the coupler and run-control architecture are re-implemented in Python, augmenting its flexibility and adaptability. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B13E0649P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B13E0649P">Forecasting Brassica rapa: Merging climate models with genotype specific process models for evaluation whole species response to climate change.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pleban, J. R.; Mackay, D. S.; Ewers, B. E.; Weinig, C.; Guadagno, C. L. 2016-12-01 Human society has modified agriculture management practices and utilized a variety of breeding approaches to adapt to changing environments. Presently a dual pronged challenge has emerged as environmental change is occurring more rapidly while the demand of population growth on food supply is rising. Knowledge of how current agricultural practices will respond to these challenges can be informed through crafted prognostic modeling approaches. Amongst the uncertainties associated with forecasting agricultural production in a changing environment is evaluation of the responses across the existing genotypic diversity of crop species. Mechanistic models of plant productivity provide a means of genotype level parameterization allowing for a prognostic evaluation of varietal performance under changing climate. Brassica rapa represents an excellent species for this type of investigation because of its wide cultivation as well as large morphological and physiological diversity. We incorporated genotypic parameterization of B. rapa genotypes based on unique CO2 assimilation strategies, vulnerabilities to cavitation, and root to leaf area relationships into the TREES model. Three climate drivers, following the "business-as-usual" greenhouse gas emissions scenario (RCP 8.5) from Coupled Model Intercomparison Project, Phase 5 (CMIP5) were considered: temperature (T) along with associated changes in vapor pressure deficit (VPD), increasing CO2, as well as alternatives in irrigation regime across a temporal scale of present day to 2100. Genotypic responses to these drivers were evaluated using net primary productivity (NPP) and percent loss hydraulic conductance (PLC) as a measure of tolerance for a particular watering regime. Genotypic responses to T were witnessed as water demand driven by increases in VPD at 2050 and 2100 drove some genotypes to greater PLC and in a subset of these saw periodic decreases in NPP during a growing season. Genotypes able to withstand the greater water demand showed lower NPP yields relative to hydraulically aggressive genotypes but saw limited PLC. Expansion of this analysis to large recombinant inbred populations may inform breeders in identification of trait combinations needed to meet the coupled challenge of rapid environmental change and increase food demand. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912431Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912431Y">Potential Effects of Drought on Tree Dieback in Great Britain and Implications for Forest Management in Adaptation to Climate Change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yu, Jianjun; Berry, Pam 2017-04-01 The drought and heat stress has alerted the composition, structure and biogeography of forests globally, whilst the projected severe and widespread droughts are potentially increasing. This challenges the sustainable forest management to better cope with future climate and maintain the forest ecosystem functions and services. Many studies have investigated the climate change impacts on forest ecosystem but less considered the climate extremes like drought. In this study, we implement a dynamic ecosystem model based on a version of LPJ-GUESS parameterized with European tree species and apply to Great Britain at a finer spatial resolution of 5*5 km. The model runs for the baseline from 1961 to 2011 and projects to the latter 21st century using 100 climate scenarios generated from MaRIUS project to tackle the climate model uncertainty. We will show the potential impacts of climate change on forest ecosystem and vegetation transition in Great Britain by comparing the modelled conditions in the 2030s and the 2080s relative to the baseline. In particular, by analyzing the modelled tree mortality, we will show the tree dieback patterns in response to drought for various species, and assess their drought vulnerability across Great Britain. We also use species distribution modelling to project the suitable climate space for selected tree species using the same climate scenarios. Aided by these two modelling approaches and based on the corresponding modelling results, we will discuss the implications for adaptation strategy for forest management, especially in extreme drought conditions. The gained knowledge and lessons for Great Britain are considered to be transferable in many other regions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1227900-using-field-observations-inform-thermal-hydrology-models-permafrost-dynamics-ats-v0','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1227900-using-field-observations-inform-thermal-hydrology-models-permafrost-dynamics-ats-v0">Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Atchley, Adam L.; Painter, Scott L.; Harp, Dylan R.; ... 2015-09-01 Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. Thus, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth system models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth system models challenge validation and parameterization of hydrothermal models. A recently developed surface–subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurementsmore » to achieve the goals of constructing a process-rich model based on plausible parameters and to identify fine-scale controls of ALT in ice-wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze–thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g., troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1415347','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1415347"></a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Hinzman, Larry D.; Bolton, William Robert; Young-Robertson, Jessica This project improves meso-scale hydrologic modeling in the boreal forest by: (1) demonstrating the importance of capturing the heterogeneity of the landscape using small scale datasets for parameterization for both small and large basins; (2) demonstrating that in drier parts of the landscape and as the boreal forest dries with climate change, modeling approaches must consider the sensitivity of simulations to soil hydraulic parameters - such as residual water content - that are usually held constant. Thus, variability / flexibility in residual water content must be considered for accurate simulation of hydrologic processes in the boreal forest; (3) demonstrating thatmore » assessing climate change impacts on boreal forest hydrology through multiple model integration must account for direct effects of climate change (temperature and precipitation), and indirect effects from climate impacts on landscape characteristics (permafrost and vegetation distribution). Simulations demonstrated that climate change will increase runoff, but will increase ET to a greater extent and result in a drying of the landscape; and (4) vegetation plays a significant role in boreal hydrologic processes in permafrost free areas that have deciduous trees. This landscape type results in a decoupling of ET and precipitation, a tight coupling of ET and temperature, low runoff, and overall soil drying.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014E%26ES...17a2013Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014E%26ES...17a2013Y">Improving Calculation Accuracies of Accumulation-Mode Fractions Based on Spectral of Aerosol Optical Depths</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ying, Zhang; Zhengqiang, Li; Yan, Wang 2014-03-01 Anthropogenic aerosols are released into the atmosphere, which cause scattering and absorption of incoming solar radiation, thus exerting a direct radiative forcing on the climate system. Anthropogenic Aerosol Optical Depth (AOD) calculations are important in the research of climate changes. Accumulation-Mode Fractions (AMFs) as an anthropogenic aerosol parameter, which are the fractions of AODs between the particulates with diameters smaller than 1μm and total particulates, could be calculated by AOD spectral deconvolution algorithm, and then the anthropogenic AODs are obtained using AMFs. In this study, we present a parameterization method coupled with an AOD spectral deconvolution algorithm to calculate AMFs in Beijing over 2011. All of data are derived from AErosol RObotic NETwork (AERONET) website. The parameterization method is used to improve the accuracies of AMFs compared with constant truncation radius method. We find a good correlation using parameterization method with the square relation coefficient of 0.96, and mean deviation of AMFs is 0.028. The parameterization method could also effectively solve AMF underestimate in winter. It is suggested that the variations of Angstrom indexes in coarse mode have significant impacts on AMF inversions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A13L..06K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A13L..06K">A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A. 2016-12-01 Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70043241','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70043241">Combining surface reanalysis and remote sensing data for monitoring evapotranspiration</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W. 2012-01-01 Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active">24</li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active">25</li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC14C..06A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC14C..06A">Use of NARCCAP data to characterize regional climate uncertainty in the impact of global climate change on large river fish population: Missouri River sturgeon example</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Anderson, C. J.; Wildhaber, M. L.; Wikle, C. K.; Moran, E. H.; Franz, K. J.; Dey, R. 2012-12-01 Climate change operates over a broad range of spatial and temporal scales. Understanding the effects of change on ecosystems requires accounting for the propagation of information and uncertainty across these scales. For example, to understand potential climate change effects on fish populations in riverine ecosystems, climate conditions predicted by course-resolution atmosphere-ocean global climate models must first be translated to the regional climate scale. In turn, this regional information is used to force watershed models, which are used to force river condition models, which impact the population response. A critical challenge in such a multiscale modeling environment is to quantify sources of uncertainty given the highly nonlinear nature of interactions between climate variables and the individual organism. We use a hierarchical modeling approach for accommodating uncertainty in multiscale ecological impact studies. This framework allows for uncertainty due to system models, model parameter settings, and stochastic parameterizations. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. We use NARCCAP data to determine confidence the capability of climate models to simulate relevant processes and to quantify regional climate variability within the context of the hierarchical model of uncertainty quantification. By confidence, we mean the ability of the regional climate model to replicate observed mechanisms. We use the NCEP-driven simulations for this analysis. This provides a base from which regional change can be categorized as either a modification of previously observed mechanisms or emergence of new processes. The management implications for these categories of change are significantly different in that procedures to address impacts from existing processes may already be known and need adjustment; whereas, an emergent processes may require new management strategies. The results from hierarchical analysis of uncertainty are used to study the relative change in weights of the endangered Missouri River pallid sturgeon (Scaphirhynchus albus) under a 21st century climate scenario. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25752508','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25752508">Phenological plasticity will not help all species adapt to climate change.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Duputié, Anne; Rutschmann, Alexis; Ronce, Ophélie; Chuine, Isabelle 2015-08-01 Concerns are rising about the capacity of species to adapt quickly enough to climate change. In long-lived organisms such as trees, genetic adaptation is slow, and how much phenotypic plasticity can help them cope with climate change remains largely unknown. Here, we assess whether, where and when phenological plasticity is and will be adaptive in three major European tree species. We use a process-based species distribution model, parameterized with extensive ecological data, and manipulate plasticity to suppress phenological variations due to interannual, geographical and trend climate variability, under current and projected climatic conditions. We show that phenological plasticity is not always adaptive and mostly affects fitness at the margins of the species' distribution and climatic niche. Under current climatic conditions, phenological plasticity constrains the northern range limit of oak and beech and the southern range limit of pine. Under future climatic conditions, phenological plasticity becomes strongly adaptive towards the trailing edges of beech and oak, but severely constrains the range and niche of pine. Our results call for caution when interpreting geographical variation in trait means as adaptive, and strongly point towards species distribution models explicitly taking phenotypic plasticity into account when forecasting species distribution under climate change scenarios. © 2015 John Wiley & Sons Ltd. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1251713-relationships-among-cloud-cover-mixed-phase-partitioning-planetary-albedo-gcms','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1251713-relationships-among-cloud-cover-mixed-phase-partitioning-planetary-albedo-gcms">On the relationships among cloud cover, mixed-phase partitioning, and planetary albedo in GCMs</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> McCoy, Daniel T.; Tan, Ivy; Hartmann, Dennis L.; ... 2016-05-06 In this study, it is shown that CMIP5 global climate models (GCMs) that convert supercooled water to ice at relatively warm temperatures tend to have a greater mean-state cloud fraction and more negative cloud feedback in the middle and high latitude Southern Hemisphere. We investigate possible reasons for these relationships by analyzing the mixed-phase parameterizations in 26 GCMs. The atmospheric temperature where ice and liquid are equally prevalent (T5050) is used to characterize the mixed-phase parameterization in each GCM. Liquid clouds have a higher albedo than ice clouds, so, all else being equal, models with more supercooled liquid water wouldmore » also have a higher planetary albedo. The lower cloud fraction in these models compensates the higher cloud reflectivity and results in clouds that reflect shortwave radiation (SW) in reasonable agreement with observations, but gives clouds that are too bright and too few. The temperature at which supercooled liquid can remain unfrozen is strongly anti-correlated with cloud fraction in the climate mean state across the model ensemble, but we know of no robust physical mechanism to explain this behavior, especially because this anti-correlation extends through the subtropics. A set of perturbed physics simulations with the Community Atmospheric Model Version 4 (CAM4) shows that, if its temperature-dependent phase partitioning is varied and the critical relative humidity for cloud formation in each model run is also tuned to bring reflected SW into agreement with observations, then cloud fraction increases and liquid water path (LWP) decreases with T5050, as in the CMIP5 ensemble.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.2427M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.2427M">Mapping (un)certainties in the sign of hydrological projections</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Melsen, Lieke; Addor, Nans; Mizukami, Naoki; Newman, Andrew; Torfs, Paul; Clark, Martyn; Uijlenhoet, Remko; Teuling, Ryan 2017-04-01 While hydrological projections are of vital importance, particularly for water infrastructure design and food production, they are also prone to different sources of uncertainty. Using a multi-model set-up we investigated the uncertainty in hydrological projections for the period 2070-2100 associated with the parameterization of hydrological models, hydrological model structure, and General Circulation Models (GCMs) needed to force the hydrological model, for 605 basins throughout the contiguous United States. The use of such a large sample of basins gave us the opportunity to recognize spatial patterns in the results, and to attribute the uncertainty to particular hydrological processes. We investigated the sign of the projected change in mean annual runoff. The parameterization influenced the sign of change in 5 to 34% of the basins, depending on the hydrological model and GCM forcing. The hydrological model structure led to uncertainty in the sign of the change in 13 to 26% of the basins, depending on GCM forcing. This uncertainty could largely be attributed to the conceptualization of snow processes in the hydrological models. In 14% of the basins, none of the hydrological models was behavioural, which could be related to catchments with high aridity and intermittent flow behaviour. In 41 to 69% of the basins, the sign of the change was uncertain due to GCM forcing, which could be attributed to disagreement among the climate models regarding the projected change in precipitation. The results demonstrate that even the sign of change in mean annual runoff is highly uncertain in the majority of the investigated basins. If we want to use hydrological projections for water management purposes, including the design of water infrastructure, we clearly need to increase our understanding of climate and hydrological processes and their feedbacks. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20110008164&hterms=past+year+papers&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dpast%2Byear%2Bpapers','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20110008164&hterms=past+year+papers&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dpast%2Byear%2Bpapers">Multiscale Cloud System Modeling</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Tao, Wei-Kuo; Moncrieff, Mitchell W. 2009-01-01 The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.1104G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.1104G">Improving synoptic and intraseasonal variability in CFSv2 via stochastic representation of organized convection</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Goswami, B. B.; Khouider, B.; Phani, R.; Mukhopadhyay, P.; Majda, A. 2017-01-01 To better represent organized convection in the Climate Forecast System version 2 (CFSv2), a stochastic multicloud model (SMCM) parameterization is adopted and a 15 year climate run is made. The last 10 years of simulations are analyzed here. While retaining an equally good mean state (if not better) as the parent model, the CFS-SMCM simulation shows significant improvement in the synoptic and intraseasonal variability. The CFS-SMCM provides a better account of convectively coupled equatorial waves and the Madden-Julian oscillation. The CFS-SMCM exhibits improvements in northward and eastward propagation of intraseasonal oscillation of convection including the MJO propagation beyond the maritime continent barrier, which is the Achilles Heel for coarse-resolution global climate models (GCMs). The distribution of precipitation events is better simulated in CFSsmcm and spreads naturally toward high-precipitation events. Deterministic GCMs tend to simulate a narrow distribution with too much drizzling precipitation and too little high-precipitation events. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1027165-quantification-terrestrial-ecosystem-carbon-dynamics-conterminous-united-states-combining-process-based-biogeochemical-model-modis-ameriflux-data','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1027165-quantification-terrestrial-ecosystem-carbon-dynamics-conterminous-united-states-combining-process-based-biogeochemical-model-modis-ameriflux-data">Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Chen, Min; Zhuang, Qianlai; Cook, D. 2011-08-31 Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. We first modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenologymore » and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000-2005 at a 0.05-0.05 spatial resolution. We find that the new version of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 PgC yr{sup -1} and net primary production (NPP) ranges from 3.81 to 4.38 Pg Cyr{sup -1} and net ecosystem production (NEP) varies within 0.08- 0.73 PgC yr{sup -1} over the period 2000-2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 PgC yr{sup -1} for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B21B0438S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B21B0438S">Partitioning sources of uncertainty in projecting the impact of future climate extremes on site to regional ecosystem carbon cycling</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Simkins, J.; Desai, A. R.; Cowdery, E.; Dietze, M.; Rollinson, C. 2016-12-01 The terrestrial biosphere assimilates nearly one fourth of anthropogenic carbon dioxide emissions, providing a significant ecosystem service. Anthropogenic climate changes that influence the distribution and frequency of weather extremes and can have a momentous impact on this useful function that ecosystems provide. However, most analyses of the impact of extreme events on ecosystem carbon uptake do not integrate across the wide range of structural, parametric, and driver uncertainty that needs to be taken into account to estimate probability of changes to ecosystem function under shifts in climate patterns. In order to improve ecosystem model forecasts, we integrated and estimated these sources of uncertainty using an open-sourced informatics workflow, the Predictive ECosystem Analyzer (PEcAn, http://pecanproject.org). PEcAn allows any researcher to parameterize and run multiple ecosystem models and automate extraction of meteorological forcing and estimation of its uncertainty. Trait databases and a uniform protocol for parameterizing and driving models were used to test parametric and structural uncertainty. In order to sample the uncertainty in future projected meteorological drivers, we developed automated extraction routines to acquire site-level three-hourly Coupled Model Intercomparison Project 5 (CMIP5) forcing data from the Geophysical Fluid Dynamics Laboratory general circulation models (CM3, ESM2M, and ESM2G) across the r1i1p1, r3i1p1 and r5i1p1 ensembles and AR5 emission scenarios. We also implemented a site-level high temporal resolution downscaling technique for these forcings calibrated against half-hourly eddy covariance flux tower observations. Our hypothesis claims that parametric and driver uncertainty dominate over the model structural uncertainty. In order to test this, we partition the uncertainty budget on the ChEAS regional network of towers in Northern Wisconsin, USA where each tower is located in forest and wetland ecosystems. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A33G0249H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A33G0249H">Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B. 2015-12-01 Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013GMD.....6.1157L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013GMD.....6.1157L">Failure analysis of parameter-induced simulation crashes in climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y. 2013-08-01 Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.3064D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.3064D">Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dethloff, Klaus; Rex, Markus; Shupe, Matthew 2016-04-01 The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) is an international initiative under the International Arctic Science Committee (IASC) umbrella that aims to improve numerical model representations of sea ice, weather, and climate processes through coupled system observations and modeling activities that link the central Arctic atmosphere, sea ice, ocean, and the ecosystem. Observations of many critical parameters such as cloud properties, surface energy fluxes, atmospheric aerosols, small-scale sea-ice and oceanic processes, biological feedbacks with the sea-ice ice and ocean, and others have never been made in the central Arctic in all seasons, and certainly not in a coupled system fashion. The primary objective of MOSAiC is to develop a better understanding of these important coupled-system processes so they can be more accurately represented in regional- and global-scale weather- and climate models. Such enhancements will contribute to improved modeling of global climate and weather, and Arctic sea-ice predictive capabilities. The MOSAiC observations are an important opportunity to gather the high quality and comprehensive observations needed to improve numerical modeling of critical, scale-dependent processes impacting Arctic predictability given diminished sea ice coverage and increased model complexity. Model improvements are needed to understand the effects of a changing Arctic on mid-latitude weather and climate. MOSAiC is specifically designed to provide the multi-parameter, coordinated observations needed to improve sub-grid scale model parameterizations especially with respect to thinner ice conditions. To facilitate, evaluate, and develop the needed model improvements, MOSAiC will employ a hierarchy of modeling approaches ranging from process model studies, to regional climate model intercomparisons, to operational forecasts and assimilation of real-time observations. Model evaluations prior to the field program will be used to identify specific gaps and parameterization needs. Preliminary modeling and operational forecasting will also be necessary to directly guide field planning and optimal implementation of field resources, and to support the safety of the project. The MOSAiC Observatory will be deployed in, and drift with, the Arctic sea-ice pack for at least a full annual cycle, starting in fall 2019 and ending in autumn 2020. Initial plans are for the drift to start in the newly forming autumn sea-ice in, or near, the East Siberian Sea. The specific location will be selected to allow for the observatory to follow the Transpolar Drift towards the North Pole and on to the Fram Strait. IASC has adopted MOSAiC as a key international activity, the German Alfred Wegener Institute has made the huge contribution of the icebreaker Polarstern to serve as the central drifting observatory for this year long endeavor, and the US Department of Energy has committed a comprehensive atmospheric measurement suite. Many other nations and agencies have expressed interest in participation and in gaining access to this unprecedented observational dataset. International coordination is needed to support this groundbreaking endeavor. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160009263','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160009263">Application of the CERES Flux-by-Cloud Type Simulator to GCM Output</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Eitzen, Zachary; Su, Wenying; Xu, Kuan-Man; Loeb, Norman G.; Sun, Moguo; Doelling, David R.; Bodas-Salcedo, Alejandro 2016-01-01 The CERES Flux By CloudType data product produces CERES top-of-atmosphere (TOA) fluxes by region and cloud type. Here, the cloud types are defined by cloud optical depth (t) and cloud top pressure (pc), with bins similar to those used by ISCCP (International Satellite Cloud Climatology Project). This data product has the potential to be a powerful tool for the evaluation of the clouds produced by climate models by helping to identify which physical parameterizations have problems (e.g., boundary-layer parameterizations, convective clouds, processes that affect surface albedo). Also, when the flux-by-cloud type and frequency of cloud types are simultaneously used to evaluate a model, the results can determine whether an unrealistically large or small occurrence of a given cloud type has an important radiative impact for a given region. A simulator of the flux-by-cloud type product has been applied to three-hourly data from the year 2008 from the UK Met Office HadGEM2-A model using the Langley Fu-Lour radiative transfer model to obtain TOA SW and LW fluxes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAr42.3..967L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAr42.3..967L">Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y. 2018-04-01 Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.1947S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.1947S">A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Skaugen, Thomas; Weltzien, Ingunn H. 2016-09-01 Snow is an important and complicated element in hydrological modelling. The traditional catchment hydrological model with its many free calibration parameters, also in snow sub-models, is not a well-suited tool for predicting conditions for which it has not been calibrated. Such conditions include prediction in ungauged basins and assessing hydrological effects of climate change. In this study, a new model for the spatial distribution of snow water equivalent (SWE), parameterized solely from observed spatial variability of precipitation, is compared with the current snow distribution model used in the operational flood forecasting models in Norway. The former model uses a dynamic gamma distribution and is called Snow Distribution_Gamma, (SD_G), whereas the latter model has a fixed, calibrated coefficient of variation, which parameterizes a log-normal model for snow distribution and is called Snow Distribution_Log-Normal (SD_LN). The two models are implemented in the parameter parsimonious rainfall-runoff model Distance Distribution Dynamics (DDD), and their capability for predicting runoff, SWE and snow-covered area (SCA) is tested and compared for 71 Norwegian catchments. The calibration period is 1985-2000 and validation period is 2000-2014. Results show that SDG better simulates SCA when compared with MODIS satellite-derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" and giving spurious positive trends in SWE, typical for SD_LN, is prevented. The precision of runoff simulations using SDG is slightly inferior, with a reduction in Nash-Sutcliffe and Kling-Gupta efficiency criterion of 0.01, but it is shown that the high precision in runoff prediction using SD_LN is accompanied with erroneous simulations of SWE. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1232664','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1232664">LES ARM Symbiotic Simulation and Observation (LASSO) Implementation Strategy</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Gustafson Jr., WI; Vogelmann, AM 2015-09-01 This document illustrates the design of the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) workflow to provide a routine, high-resolution modeling capability to augment the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s high-density observations. LASSO will create a powerful new capability for furthering ARM’s mission to advance understanding of cloud, radiation, aerosol, and land-surface processes. The combined observational and modeling elements will enable a new level of scientific inquiry by connecting processes and context to observations and providing needed statistics for details that cannot be measured. The result will be improved process understandingmore » that facilitates concomitant improvements in climate model parameterizations. The initial LASSO implementation will be for ARM’s Southern Great Plains site in Oklahoma and will focus on shallow convection, which is poorly simulated by climate models due in part to clouds’ typically small spatial scale compared to model grid spacing, and because the convection involves complicated interactions of microphysical and boundary layer processes.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A41D0095R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A41D0095R">High Resolution Climate Modeling of the Water Cycle over the Contiguous United States Including Potential Climate Change Scenarios</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rasmussen, R.; Ikeda, K.; Liu, C.; Gochis, D.; Chen, F.; Barlage, M. J.; Dai, A.; Dudhia, J.; Clark, M. P.; Gutmann, E. D.; Li, Y. 2015-12-01 The NCAR Water System program strives to improve the full representation of the water cycle in both regional and global models. Our previous high-resolution simulations using the WRF model over the Rocky Mountains revealed that proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing (< 6 km horizontal) and parameterizations. The climate sensitivity experiment consistent with expected climate change showed an altered hydrological cycle with increased fraction of rain versus snow, increased snowfall at high altitudes, earlier melting of snowpack, and decreased total runoff. In order to investigate regional differences between the Rockies and other major mountain barriers and to study climate change impacts over other regions of the contiguous U.S. (CONUS), we have expanded our prior CO Headwaters modeling study to encompass most of North America at a horizontal grid spacing of 4 km. A domain expansion provides the opportunity to assess changes in orographic precipitation across different mountain ranges in the western USA, as well as the very dominant role of convection in the eastern half of the USA. The high resolution WRF-downscaled climate change data will also become a valuable community resource for many university groups who are interested in studying regional climate changes and impacts but unable to perform such long-duration and high-resolution WRF-based downscaling simulations of their own. The scientific goals and details of the model dataset will be presented including some preliminary results. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C13G..07J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C13G..07J">Modelling and parameterizing the influence of tides on ice-shelf melt rates</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Jourdain, N.; Molines, J. M.; Le Sommer, J.; Mathiot, P.; de Lavergne, C.; Gurvan, M.; Durand, G. 2017-12-01 Significant Antarctic ice sheet thinning is observed in several sectors of Antarctica, in particular in the Amundsen Sea sector, where warm circumpolar deep waters affect basal melting. The later has the potential to trigger marine ice sheet instabilities, with an associated potential for rapid sea level rise. It is therefore crucial to simulate and understand the processes associated with ice-shelf melt rates. In particular, the absence of tides representation in ocean models remains a caveat of numerous ocean hindcasts and climate projections. In the Amundsen Sea, tides are relatively weak and the melt-induced circulation is stronger than the tidal circulation. Using a regional 1/12° ocean model of the Amundsen Sea, we nonetheless find that tides can increase melt rates by up to 36% in some ice-shelf cavities. Among the processes that can possibly affect melt rates, the most important is an increased exchange at the ice/ocean interface resulting from the presence of strong tidal currents along the ice drafts. Approximately a third of this effect is compensated by a decrease in thermal forcing along the ice draft, which is related to an enhanced vertical mixing in the ocean interior in presence of tides. Parameterizing the effect of tides is an alternative to the representation of explicit tides in an ocean model, and has the advantage not to require any filtering of ocean model outputs. We therefore explore different ways to parameterize the effects of tides on ice shelf melt. First, we compare several methods to impose tidal velocities along the ice draft. We show that getting a realistic spatial distribution of tidal velocities in important, and can be deduced from the barotropic velocities of a tide model. Then, we explore several aspects of parameterized tidal mixing to reproduce the tide-induced decrease in thermal forcing along the ice drafts. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990060930','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990060930">A Solar Radiation Parameterization for Atmospheric Studies. Volume 15</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Chou, Ming-Dah; Suarez, Max J. (Editor) 1999-01-01 The solar radiation parameterization (CLIRAD-SW) developed at the Goddard Climate and Radiation Branch for application to atmospheric models are described. It includes the absorption by water vapor, O3, O2, CO2, clouds, and aerosols and the scattering by clouds, aerosols, and gases. Depending upon the nature of absorption, different approaches are applied to different absorbers. In the ultraviolet and visible regions, the spectrum is divided into 8 bands, and single O3 absorption coefficient and Rayleigh scattering coefficient are used for each band. In the infrared, the spectrum is divided into 3 bands, and the k-distribution method is applied for water vapor absorption. The flux reduction due to O2 is derived from a simple function, while the flux reduction due to CO2 is derived from precomputed tables. Cloud single-scattering properties are parameterized, separately for liquid drops and ice, as functions of water amount and effective particle size. A maximum-random approximation is adopted for the overlapping of clouds at different heights. Fluxes are computed using the Delta-Eddington approximation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1243064-mean-state-acceleration-cloud-resolving-models-large-eddy-simulations','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1243064-mean-state-acceleration-cloud-resolving-models-large-eddy-simulations">Mean-state acceleration of cloud-resolving models and large eddy simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Jones, C. R.; Bretherton, C. S.; Pritchard, M. S. 2015-10-29 In this study, large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate themore » evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2–16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H13P..07E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H13P..07E">Understanding the Impact of Ground Water Treatment and Evapotranspiration Parameterizations in the NCEP Climate Forecast System (CFS) on Warm Season Predictions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ek, M. B.; Yang, R. 2016-12-01 Skillful short-term weather forecasts, which rely heavily on quality atmospheric initial conditions, have a fundamental limit of about two weeks owing to the chaotic nature of the atmosphere. Useful forecasts at sub-seasonal to seasonal time scales, on the other hand, require well-simulated large-scale atmospheric response to slowly varying lower boundary forcings from both the ocean and land surface. The critical importance of ocean has been recognized, where the ocean indices have been used in a variety of climate applications. In contrast, the impact of land surface anomalies, especially soil moisture and associated evaporation, has been proven notably difficult to demonstrate. The Noah Land Surface Model (LSM) is the land component of NCEP CFS version 2 (CFSv2) used for seasonal predictions. The Noah LSM originates from the Oregon State University (OSU) LSM. The evaporation control in the Noah LSM is based on the Penman-Monteith equation, which takes into account the solar radiation, relative humidity, air temperature, and soil moisture effects. The Noah LSM is configured with four soil layers with a fixed depth of 2 meters and free drainage at the bottom soil layer. This treatment assumes that the soil water table depth is well within the specified range, and also potentially misrepresents the soil moisture memory effects at seasonal time scales. To overcome the limitation, an unconfined aquifer is attached to the bottom of the soil to allow the water table to move freely up and down. In addition, in conjunction with the water table, an alternative Ball-Berry photosynthesis-based evaporation parameterization is examined to evaluate the impact from using a different evaporation control methodology. Focusing on the 2011 and 2012 intense summer droughts in the central US, seasonal ensemble forecast experiments with early May initial conditions are carried out for the two years using an enhanced version of CFSv2, where the atmospheric component of the CFSv2 is coupled to the Noah Multiple-Parameterization (Noah-MP) land model. The Noah-MP has different options for ground water and evaporation control parameterizations. 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