Continuous versus discontinuous albedo representations in a simple diffusive climate model

NASA Astrophysics Data System (ADS)

Simmons, P. A.; Griffel, D. H.

1988-07-01

A one-dimensional annually and zonally averaged energy-balance model, with diffusive meridional heat transport and including icealbedo feedback, is considered. This type of model is found to be very sensitive to the form of albedo used. The solutions for a discontinuous step-function albedo are compared to those for a more realistic smoothly varying albedo. The smooth albedo gives a closer fit to present conditions, but the discontinuous form gives a better representation of climates in earlier epochs.

Atmospheric Carbon Dioxide and the Global Carbon Cycle: The Key Uncertainties

DOE R&D Accomplishments Database

Peng, T. H.; Post, W. M.; DeAngelis, D. L.; Dale, V. H.; Farrell, M. P.

1987-12-01

The biogeochemical cycling of carbon between its sources and sinks determines the rate of increase in atmospheric CO{sub 2} concentrations. The observed increase in atmospheric CO{sub 2} content is less than the estimated release from fossil fuel consumption and deforestation. This discrepancy can be explained by interactions between the atmosphere and other global carbon reservoirs such as the oceans, and the terrestrial biosphere including soils. Undoubtedly, the oceans have been the most important sinks for CO{sub 2} produced by man. But, the physical, chemical, and biological processes of oceans are complex and, therefore, credible estimates of CO{sub 2} uptake can probably only come from mathematical models. Unfortunately, one- and two-dimensional ocean models do not allow for enough CO{sub 2} uptake to accurately account for known releases. Thus, they produce higher concentrations of atmospheric CO{sub 2} than was historically the case. More complex three-dimensional models, while currently being developed, may make better use of existing tracer data than do one- and two-dimensional models and will also incorporate climate feedback effects to provide a more realistic view of ocean dynamics and CO{sub 2} fluxes. The instability of current models to estimate accurately oceanic uptake of CO{sub 2} creates one of the key uncertainties in predictions of atmospheric CO{sub 2} increases and climate responses over the next 100 to 200 years.

SIMULATED CLIMATE CHANGE EFFECTS ON DISSOLVED OXYGEN CHARACTERISTICS IN ICE-COVERED LAKES. (R824801)

EPA Science Inventory

A deterministic, one-dimensional model is presented which simulates daily dissolved oxygen (DO) profiles and associated water temperatures, ice covers and snow covers for dimictic and polymictic lakes of the temperate zone. The lake parameters required as model input are surface ...

Increased insolation threshold for runaway greenhouse processes on Earth-like planets

NASA Astrophysics Data System (ADS)

Leconte, Jérémy; Forget, Francois; Charnay, Benjamin; Wordsworth, Robin; Pottier, Alizée

2013-12-01

The increase in solar luminosity over geological timescales should warm the Earth's climate, increasing water evaporation, which will in turn enhance the atmospheric greenhouse effect. Above a certain critical insolation, this destabilizing greenhouse feedback can `run away' until the oceans have completely evaporated. Through increases in stratospheric humidity, warming may also cause evaporative loss of the oceans to space before the runaway greenhouse state occurs. The critical insolation thresholds for these processes, however, remain uncertain because they have so far been evaluated using one-dimensional models that cannot account for the dynamical and cloud feedback effects that are key stabilizing features of the Earth's climate. Here we use a three-dimensional global climate model to show that the insolation threshold for the runaway greenhouse state to occur is about 375 W m-2, which is significantly higher than previously thought. Our model is specifically developed to quantify the climate response of Earth-like planets to increased insolation in hot and extremely moist atmospheres. In contrast with previous studies, we find that clouds have a destabilizing feedback effect on the long-term warming. However, subsident, unsaturated regions created by the Hadley circulation have a stabilizing effect that is strong enough to shift the runaway greenhouse limit to higher values of insolation than are inferred from one-dimensional models. Furthermore, because of wavelength-dependent radiative effects, the stratosphere remains sufficiently cold and dry to hamper the escape of atmospheric water, even at large fluxes. This has strong implications for the possibility of liquid water existing on Venus early in its history, and extends the size of the habitable zone around other stars.

Increased insolation threshold for runaway greenhouse processes on Earth-like planets.

PubMed

Leconte, Jérémy; Forget, Francois; Charnay, Benjamin; Wordsworth, Robin; Pottier, Alizée

2013-12-12

The increase in solar luminosity over geological timescales should warm the Earth's climate, increasing water evaporation, which will in turn enhance the atmospheric greenhouse effect. Above a certain critical insolation, this destabilizing greenhouse feedback can 'run away' until the oceans have completely evaporated. Through increases in stratospheric humidity, warming may also cause evaporative loss of the oceans to space before the runaway greenhouse state occurs. The critical insolation thresholds for these processes, however, remain uncertain because they have so far been evaluated using one-dimensional models that cannot account for the dynamical and cloud feedback effects that are key stabilizing features of the Earth's climate. Here we use a three-dimensional global climate model to show that the insolation threshold for the runaway greenhouse state to occur is about 375 W m(-2), which is significantly higher than previously thought. Our model is specifically developed to quantify the climate response of Earth-like planets to increased insolation in hot and extremely moist atmospheres. In contrast with previous studies, we find that clouds have a destabilizing feedback effect on the long-term warming. However, subsident, unsaturated regions created by the Hadley circulation have a stabilizing effect that is strong enough to shift the runaway greenhouse limit to higher values of insolation than are inferred from one-dimensional models. Furthermore, because of wavelength-dependent radiative effects, the stratosphere remains sufficiently cold and dry to hamper the escape of atmospheric water, even at large fluxes. This has strong implications for the possibility of liquid water existing on Venus early in its history, and extends the size of the habitable zone around other stars.

Coupling Climate Models and Forward-Looking Economic Models

NASA Astrophysics Data System (ADS)

Judd, K.; Brock, W. A.

2010-12-01

Authors: Dr. Kenneth L. Judd, Hoover Institution, and Prof. William A. Brock, University of Wisconsin Current climate models range from General Circulation Models (GCM’s) with millions of degrees of freedom to models with few degrees of freedom. Simple Energy Balance Climate Models (EBCM’s) help us understand the dynamics of GCM’s. The same is true in economics with Computable General Equilibrium Models (CGE’s) where some models are infinite-dimensional multidimensional differential equations but some are simple models. Nordhaus (2007, 2010) couples a simple EBCM with a simple economic model. One- and two- dimensional ECBM’s do better at approximating damages across the globe and positive and negative feedbacks from anthroprogenic forcing (North etal. (1981), Wu and North (2007)). A proper coupling of climate and economic systems is crucial for arriving at effective policies. Brock and Xepapadeas (2010) have used Fourier/Legendre based expansions to study the shape of socially optimal carbon taxes over time at the planetary level in the face of damages caused by polar ice cap melt (as discussed by Oppenheimer, 2005) but in only a “one dimensional” EBCM. Economists have used orthogonal polynomial expansions to solve dynamic, forward-looking economic models (Judd, 1992, 1998). This presentation will couple EBCM climate models with basic forward-looking economic models, and examine the effectiveness and scaling properties of alternative solution methods. We will use a two dimensional EBCM model on the sphere (Wu and North, 2007) and a multicountry, multisector regional model of the economic system. Our aim will be to gain insights into intertemporal shape of the optimal carbon tax schedule, and its impact on global food production, as modeled by Golub and Hertel (2009). We will initially have limited computing resources and will need to focus on highly aggregated models. However, this will be more complex than existing models with forward-looking economic modules, and the initial models will help guide the construction of more refined models that can effectively use more powerful computational environments to analyze economic policies related to climate change. REFERENCES Brock, W., Xepapadeas, A., 2010, “An Integration of Simple Dynamic Energy Balance Climate Models and Ramsey Growth Models,” Department of Economics, University of Wisconsin, Madison, and University of Athens. Golub, A., Hertel, T., etal., 2009, “The opportunity cost of land use and the global potential for greenhouse gas mitigation in agriculture and forestry,” RESOURCE AND ENERGY ECONOMICS, 31, 299-319. Judd, K., 1992, “Projection methods for solving aggregate growth models,” JOURNAL OF ECONOMIC THEORY, 58: 410-52. Judd, K., 1998, NUMERICAL METHODS IN ECONOMICS, MIT Press, Cambridge, Mass. Nordhaus, W., 2007, A QUESTION OF BALANCE: ECONOMIC MODELS OF CLIMATE CHANGE, Yale University Press, New Haven, CT. North, G., R., Cahalan, R., Coakely, J., 1981, “Energy balance climate models,” REVIEWS OF GEOPHYSICS AND SPACE PHYSICS, Vol. 19, No. 1, 91-121, February Wu, W., North, G. R., 2007, “Thermal decay modes of a 2-D energy balance climate model,” TELLUS, 59A, 618-626.

Quantifying uncertainty in climate change science through empirical information theory.

PubMed

Majda, Andrew J; Gershgorin, Boris

2010-08-24

Quantifying the uncertainty for the present climate and the predictions of climate change in the suite of imperfect Atmosphere Ocean Science (AOS) computer models is a central issue in climate change science. Here, a systematic approach to these issues with firm mathematical underpinning is developed through empirical information theory. An information metric to quantify AOS model errors in the climate is proposed here which incorporates both coarse-grained mean model errors as well as covariance ratios in a transformation invariant fashion. The subtle behavior of model errors with this information metric is quantified in an instructive statistically exactly solvable test model with direct relevance to climate change science including the prototype behavior of tracer gases such as CO(2). Formulas for identifying the most sensitive climate change directions using statistics of the present climate or an AOS model approximation are developed here; these formulas just involve finding the eigenvector associated with the largest eigenvalue of a quadratic form computed through suitable unperturbed climate statistics. These climate change concepts are illustrated on a statistically exactly solvable one-dimensional stochastic model with relevance for low frequency variability of the atmosphere. Viable algorithms for implementation of these concepts are discussed throughout the paper.

An energy-balance model with multiply-periodic and quasi-chaotic free oscillations. [for climate forecasting

NASA Technical Reports Server (NTRS)

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.

Uncertainty, Sensitivity Analysis, and Causal Identification in the Arctic using a Perturbed Parameter Ensemble of the HiLAT Climate Model

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

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

Coupled climate models have a large number of input parameters that can affect output uncertainty. We conducted a sensitivity analysis of sea ice proper:es and Arc:c related climate variables to 5 parameters in the HiLAT climate model: air-ocean turbulent exchange parameter (C), conversion of water vapor to clouds (cldfrc_rhminl) and of ice crystals to snow (micro_mg_dcs), snow thermal conduc:vity (ksno), and maximum snow grain size (rsnw_mlt). We used an elementary effect (EE) approach to rank their importance for output uncertainty. EE is an extension of one-at-a-time sensitivity analyses, but it is more efficient in sampling multi-dimensional parameter spaces. We lookedmore » for emerging relationships among climate variables across the model ensemble, and used causal discovery algorithms to establish potential pathways for those relationships.« less

3-D Teaching of Climate Change: An innovative professional learning model for K-12 teachers

NASA Astrophysics Data System (ADS)

Stapleton, M.; Wolfson, J.; Sezen-Barrie, A.

2017-12-01

In spite of the presumed controversy over the evidence for climate change, the recently released Next Generation Science Standards (NGSS) for K-12 include a focus on climate literacy and explicitly use the term `climate change.' In addition to the increased focus on climate change, the NGSS are also built upon a new three dimensional framework for teaching and learning science. Three dimensional learning has students engaging in scientific and engineering practices (Dimension 1), while using crosscutting concepts (Dimension 2) to explore and explain natural phenomena using disciplinary core ideas (Dimension 3). The adoption of these new standards in many states across the nation has created a critical need for on-going professional learning as in-service science educators begin to implement both climate change instruction and three dimensional teaching and learning in their classrooms. In response to this need, we developed an innovative professional learning model for preparing teachers to effectively integrate climate change into their new curriculum and engage students in three dimensional learning. Our professional learning model utilized ideas that have emerged from recent science education research and include: a) formative assessment probes for three dimensional learning that monitor students' progress; b) collaboration with scientists with expertise in climate science to understand the domain specific ways of doing science; and c) development of a community of practice for in-service teachers to provide feedback to each other on their implementation. In this poster presentation, we will provide details on the development of this professional learning model and discuss the affordances and challenges of implementing this type of professional learning experience.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, E.; Sokolov, A. P.; Schlosser, C. A.; Scott, J. R.; Gao, X.

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity, with a two-dimensional zonal-mean atmosphere, to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three dimensional atmospheric model; and a statistical downscaling, where a pattern scaling algorithm uses climate-change patterns from 17 climate models. This framework allows for key sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections; climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate); natural variability; and structural uncertainty. Results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also nd that dierent initial conditions lead to dierences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider all sources of uncertainty when modeling climate impacts over Northern Eurasia.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.

An introduction to three-dimensional climate modeling

NASA Technical Reports Server (NTRS)

Washington, W. M.; Parkinson, C. L.

1986-01-01

The development and use of three-dimensional computer models of the earth's climate are discussed. The processes and interactions of the atmosphere, oceans, and sea ice are examined. The basic theory of climate simulation which includes the fundamental equations, models, and numerical techniques for simulating the atmosphere, oceans, and sea ice is described. Simulated wind, temperature, precipitation, ocean current, and sea ice distribution data are presented and compared to observational data. The responses of the climate to various environmental changes, such as variations in solar output or increases in atmospheric carbon dioxide, are modeled. Future developments in climate modeling are considered. Information is also provided on the derivation of the energy equation, the finite difference barotropic forecast model, the spectral transform technique, and the finite difference shallow water waved equation model.

Climate Models

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.

2012-01-01

Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.

Modeling of Greenland outlet glaciers response to future climate change

NASA Astrophysics Data System (ADS)

Beckmann, J.

2017-12-01

Over the past two decades net mass loss from the Greenland ice sheet (GIS) quadrupled, resulting in 25% of the global mean sea level (GMSL) rise. Increased mass loss of the GIS is caused by enhanced surface melting and speedup of the marine-terminating outlet glaciers. This speedup has been related, among other factors, to enhanced submarine melting, which in turn is caused by warming of the surrounding ocean and by increased subglacial, meltwater discharge. Yet, ice-ocean processes are not properly represented in contemporary Greenland Ice Sheet models used to project future changes in the GIS. In this work, we performed numerical experiments with a one-dimensional plume model coupled to a one-dimensional (depth- and width- integrated) ice flow model for several representative outlet glaciers in Greenland. We investigate the dynamic response of the coupled ice-flow plume model to scenarios of future climate change. In particular, we examine the transient response of the outlet glaciers to projected changes in surface melting, ocean temperature and subglacial discharge. With our modeling approach we quantify the amount of the surface and submarine melting and the resulting retreat and mass loss for each individual glacier for the next 100 years.

SENSITIVITY OF THE REGIONAL WATER BALANCE IN THE COLUMBIA RIVER BASIN TO CLIMATE VARIABILITY: APPLICATION OF A SPATIALLY DISTRIBUTED WATER BALANCE MODEL

EPA Science Inventory

A one-dimensional water balance model was developed and used to simulate water balance for the Columbia River Basin. he model was run over a 10 km X 10 km grid for the United State's portion of the basin. he regional water balance was calculated using a monthly time-step for a re...

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Li; Sze, N. D.

1997-01-01

This is the first semi-annual report for NAS5-97039 summarizing work performed for January 1997 through June 1997. Work in this project is related to NAS1-20666, also funded by NASA ACMAP. The work funded in this project also benefits from work at AER associated with the AER three-dimensional isentropic transport model funded by NASA AEAP and the AER two-dimensional climate-chemistry model (co-funded by Department of Energy). The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry.

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

NASA Astrophysics Data System (ADS)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin, particularly for annual maxima of the FWI distribution and spatiotemporal autocorrelation of precipitation fields.

Venus climate stability and volcanic resurfacing rates

NASA Technical Reports Server (NTRS)

Bullock, M. A.; Grinspoon, D. H.; Pollack, J. B.

1994-01-01

The climate of Venus is to a large degree controlled by the radiative properties of its massive atmosphere. In addition, outgassing due to volcanic activity, exospheric escape processes, and surface/atmosphere interactions may all be important in moderating the abundances of atmospheric CO2 and other volatiles. We have developed an evolutionary climate model for Venus using a systems approach that emphasizes feedbacks between elements in the climate system. Modules for atmospheric radiative transfer, surface/atmosphere interactions, tropospheric chemistry, and exospheric escape processes have so far been developed. Climate feedback loops result from interconnections between modules, in the form of the environmental parameters pressure, temperature, and atmospheric mixing ratios. The radiative transfer module has been implemented by using Rosseland mean opacities in a one dimensional grey radiative-convective model. The model has been solved for the static (time independent) case to determine climate equilibrium points. The dynamics of the model have also been explored by employing reaction/diffusion kinetics for possible surface atmosphere heterogeneous reactions over geologic timescales. It was found that under current conditions, the model predicts that the climate of Venus is at or near an unstable equilibrium point. The effects of constant rate volcanism and corresponding exsolution of volatiles on the stability of the climate model were also explored.

A non-equilibrium model for soil heating and moisture transport during extreme surface heating: The soil (heat-moisture-vapor) HMV-Model Version

Treesearch

William Massman

2015-01-01

Increased use of prescribed fire by land managers and the increasing likelihood of wildfires due to climate change require an improved modeling capability of extreme heating of soils during fires. This issue is addressed here by developing and testing the soil (heat-moisture-vapor) HMVmodel, a 1-D (one-dimensional) non-equilibrium (liquid- vapor phase change)...

Assessing the operation rules of a reservoir system based on a detailed modelling-chain

NASA Astrophysics Data System (ADS)

Bruwier, M.; Erpicum, S.; Pirotton, M.; Archambeau, P.; Dewals, B.

2014-09-01

According to available climate change scenarios for Belgium, drier summers and wetter winters are expected. In this study, we focus on two muti-purpose reservoirs located in the Vesdre catchment, which is part of the Meuse basin. The current operation rules of the reservoirs are first analysed. Next, the impacts of two climate change scenarios are assessed and enhanced operation rules are proposed to mitigate these impacts. For this purpose, an integrated model of the catchment was used. It includes a hydrological model, one-dimensional and two-dimensional hydraulic models of the river and its main tributaries, a model of the reservoir system and a flood damage model. Five performance indicators of the reservoir system have been defined, reflecting its ability to provide sufficient drinking, to control floods, to produce hydropower and to reduce low-flow condition. As shown by the results, enhanced operation rules may improve the drinking water potential and the low-flow augmentation while the existing operation rules are efficient for flood control and for hydropower production.

Assessing the operation rules of a reservoir system based on a detailed modelling chain

NASA Astrophysics Data System (ADS)

Bruwier, M.; Erpicum, S.; Pirotton, M.; Archambeau, P.; Dewals, B. J.

2015-03-01

According to available climate change scenarios for Belgium, drier summers and wetter winters are expected. In this study, we focus on two multi-purpose reservoirs located in the Vesdre catchment, which is part of the Meuse basin. The current operation rules of the reservoirs are first analysed. Next, the impacts of two climate change scenarios are assessed and enhanced operation rules are proposed to mitigate these impacts. For this purpose, an integrated model of the catchment was used. It includes a hydrological model, one-dimensional and two-dimensional hydraulic models of the river and its main tributaries, a model of the reservoir system and a flood damage model. Five performance indicators of the reservoir system have been defined, reflecting its ability to provide sufficient drinking water, to control floods, to produce hydropower and to reduce low-flow conditions. As shown by the results, enhanced operation rules may improve the drinking water potential and the low-flow augmentation while the existing operation rules are efficient for flood control and for hydropower production.

A Simple Climate Model Program for High School Education

NASA Astrophysics Data System (ADS)

Dommenget, D.

2012-04-01

The future climate change projections of the IPCC AR4 are based on GCM simulations, which give a distinct global warming pattern, with an arctic winter amplification, an equilibrium land sea contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the IPCC predictions, the conceptual understanding of these predicted structures of climate change are very difficult to reach if only based on these highly complex GCM simulations and they are not accessible for ordinary people. In this study presented here we will introduce a very simple gridded globally resolved energy balance model based on strongly simplified physical processes, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the 1-dimensional energy balance models and the fully coupled 4-dimensional complex GCMs. It runs on standard PC computers computing globally resolved climate simulation with 2yrs per second or 100,000yrs per day. The program can compute typical global warming scenarios in a few minutes on a standard PC. The computer code is only 730 line long with very simple formulations that high school students should be able to understand. The simple model's climate sensitivity and the spatial structure of the warming pattern is within the uncertainties of the IPCC AR4 models simulations. It is capable of simulating the arctic winter amplification, the equilibrium land sea contrast and the inter-hemispheric warming gradient with good agreement to the IPCC AR4 models in amplitude and structure. The program can be used to do sensitivity studies in which students can change something (e.g. reduce the solar radiation, take away the clouds or make snow black) and see how it effects the climate or the climate response to changes in greenhouse gases. This program is available for every one and could be the basis for high school education. Partners for a high school project are wanted!

A multiscale climate emulator for long-term morphodynamics (MUSCLE-morpho)

NASA Astrophysics Data System (ADS)

Antolínez, José Antonio A.; Méndez, Fernando J.; Camus, Paula; Vitousek, Sean; González, E. Mauricio; Ruggiero, Peter; Barnard, Patrick

2016-01-01

Interest in understanding long-term coastal morphodynamics has recently increased as climate change impacts become perceptible and accelerated. Multiscale, behavior-oriented and process-based models, or hybrids of the two, are typically applied with deterministic approaches which require considerable computational effort. In order to reduce the computational cost of modeling large spatial and temporal scales, input reduction and morphological acceleration techniques have been developed. Here we introduce a general framework for reducing dimensionality of wave-driver inputs to morphodynamic models. The proposed framework seeks to account for dependencies with global atmospheric circulation fields and deals simultaneously with seasonality, interannual variability, long-term trends, and autocorrelation of wave height, wave period, and wave direction. The model is also able to reproduce future wave climate time series accounting for possible changes in the global climate system. An application of long-term shoreline evolution is presented by comparing the performance of the real and the simulated wave climate using a one-line model. This article was corrected on 2 FEB 2016. See the end of the full text for details.

Statistical Downscaling in Multi-dimensional Wave Climate Forecast

NASA Astrophysics Data System (ADS)

Camus, P.; Méndez, F. J.; Medina, R.; Losada, I. J.; Cofiño, A. S.; Gutiérrez, J. M.

2009-04-01

Wave climate at a particular site is defined by the statistical distribution of sea state parameters, such as significant wave height, mean wave period, mean wave direction, wind velocity, wind direction and storm surge. Nowadays, long-term time series of these parameters are available from reanalysis databases obtained by numerical models. The Self-Organizing Map (SOM) technique is applied to characterize multi-dimensional wave climate, obtaining the relevant "wave types" spanning the historical variability. This technique summarizes multi-dimension of wave climate in terms of a set of clusters projected in low-dimensional lattice with a spatial organization, providing Probability Density Functions (PDFs) on the lattice. On the other hand, wind and storm surge depend on instantaneous local large-scale sea level pressure (SLP) fields while waves depend on the recent history of these fields (say, 1 to 5 days). Thus, these variables are associated with large-scale atmospheric circulation patterns. In this work, a nearest-neighbors analog method is used to predict monthly multi-dimensional wave climate. This method establishes relationships between the large-scale atmospheric circulation patterns from numerical models (SLP fields as predictors) with local wave databases of observations (monthly wave climate SOM PDFs as predictand) to set up statistical models. A wave reanalysis database, developed by Puertos del Estado (Ministerio de Fomento), is considered as historical time series of local variables. The simultaneous SLP fields calculated by NCEP atmospheric reanalysis are used as predictors. Several applications with different size of sea level pressure grid and with different temporal domain resolution are compared to obtain the optimal statistical model that better represents the monthly wave climate at a particular site. In this work we examine the potential skill of this downscaling approach considering perfect-model conditions, but we will also analyze the suitability of this methodology to be used for seasonal forecast and for long-term climate change scenario projection of wave climate.

A Energy Balance Analysis of the Climate Sensitivity to Variations in the Rate of Upwelling in the World Oceans.

NASA Astrophysics Data System (ADS)

Morantine, Michael Creighton

The climate system of the Earth has been under investigation for many years, and the "Green-House Effect" has introduced a sense of urgency into the effort. The globally averaged temperature of the Earth undergoes what is commonly referred to as natural fluctuations in the climate signal. One effort of climate modellers is to isolate the responses of particular climate forcings in order to better understand each effect. The use of energy balance climate models (EBM's) has been one of the major tools in this respect. Studies conducted on the response of the environment to the "Green-House Effect" predict a warming trend. After experiencing such a trend in the early 1900's, however, the globally averaged temperature of the Earth began to decrease in the 1940's and continued this trend for approximately 20 years before resuming its trend of increase. It will be shown that a reduction of ~10% in the upwelling rate in the oceans could produce a decrease in the globally averaged temperature sufficient to explain this departure from the expected trend. The analysis of paleoclimatic indicators has produced strong evidence that the orbital forcing with periods of approximately 21000, 41000 and 93000 years predicted by the Milankovitch Theory is the primary cause of the glacial cycles known to have occurred on the Earth. However, there is a dynamic interaction between the environment and the ice caps that is not completely understood at this time. The paleoclimatic indicators available for the last deglaciation are abundant and well preserved (relative to the evidence of previous glacial periods), and analysis of the evidence indicates that during the most recent deglaciation a pulsation in the polar front occurred on such a small time scale that Milankovitch forcing is ruled out as a possible cause. It will be shown that an abrupt shutdown in the deep-water formation process which feeds the upwelling in the oceans could produce an influence of appropriate magnitude and time-scale to be the source of the dynamic interaction responsible for this abrupt climatic event. The process employed in the dimension reduction used in the formulation of lower-order EBM's will be illustrated through the development of the equations, pointing out the inherent assumptions which must be made when developing one- and two-dimensional models as they are required. One -, two- and three-dimensional energy balance models will be analyzed and the results of climate sensitivity to upwelling variations will be presented graphically for each case.

A three-dimensional simulation of the equatorial quasi-biennial oscillation

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

Takahashi, M.; Boville, B.A.

1992-06-15

A simulation of the equatorial quasi-biennial oscillation (QBO) has been obtained using a three-dimensional mechanistic model of the stratosphere. The model is a simplified form of the NCAR CCM (Community Climate Model) in which the troposphere has been replaced with a specified geopotential distribution near the tropical tropopause and most of the physical parameterizations have been removed. A Kelvin wave and a Rossby-gravity wave are forced at the bottom boundary as in previous one- and two-dimensional models. The model reproduces most of the principal features of the observed QBO, as do previous models with lower dimensionality. The principal difference betweenmore » the present model and previous QBO models is that the wave propagation is explicitly represented, allowing wave-wave interactions to take place. It is found that these interactions significantly affect the simulated oscillation. The interaction of the Rossby-gravity waves with the Kelvin waves results in about twice as much easterly compared to westerly forcing being required in order to obtain a QBO. 26 refs., 12 figs.« less

Efficient Screening of Climate Model Sensitivity to a Large Number of Perturbed Input Parameters [plus supporting information

DOE PAGES

Covey, Curt; Lucas, Donald D.; Tannahill, John; ...

2013-07-01

Modern climate models contain numerous input parameters, each with a range of possible values. Since the volume of parameter space increases exponentially with the number of parameters N, it is generally impossible to directly evaluate a model throughout this space even if just 2-3 values are chosen for each parameter. Sensitivity screening algorithms, however, can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination.This can aid both model development and the uncertainty quantification (UQ) process. Here we report results from a parameter sensitivity screening algorithm hitherto untested in climate modeling,more » the Morris one-at-a-time (MOAT) method. This algorithm drastically reduces the computational cost of estimating sensitivities in a high dimensional parameter space because the sample size grows linearly rather than exponentially with N. It nevertheless samples over much of the N-dimensional volume and allows assessment of parameter interactions, unlike traditional elementary one-at-a-time (EOAT) parameter variation. We applied both EOAT and MOAT to the Community Atmosphere Model (CAM), assessing CAM’s behavior as a function of 27 uncertain input parameters related to the boundary layer, clouds, and other subgrid scale processes. For radiation balance at the top of the atmosphere, EOAT and MOAT rank most input parameters similarly, but MOAT identifies a sensitivity that EOAT underplays for two convection parameters that operate nonlinearly in the model. MOAT’s ranking of input parameters is robust to modest algorithmic variations, and it is qualitatively consistent with model development experience. Supporting information is also provided at the end of the full text of the article.« less

Investigation of biogeophysical feedback on the African climate using a two-dimensional model

NASA Technical Reports Server (NTRS)

Xue, Yongkang; Liou, Kuo-Nan; Kasahara, Akira

1990-01-01

A numerical scheme is specifically designed to develop a time-dependent climate model to ensure the conservation of mass, momentum, energy, and water vapor, in order to study the biogeophysical feedback for the climate of Africa. A vegetation layer is incorporated in the present two-dimensional climate model. Using the coupled climate-vegetation model, two tests were performed involving the removal and expansion of the Sahara Desert. Results show that variations in the surface conditions produce a significant feedback to the climate system. It is noted that the simulation responses to the temperature and zonal wind in the case of an expanded desert agree with the climatological data for African dry years. Perturbed simulations have also been performed by changing the albedo only, without allowing the variation in the vegetation layer. It is shown that the variation in latent heat release is significant and is related to changes in the vegetation cover. As a result, precipitation and cloud cover are reduced.

The influence of ice sheets on temperature during the past 38 million years inferred from a one-dimensional ice sheet-climate model

NASA Astrophysics Data System (ADS)

Stap, Lennert B.; van de Wal, Roderik S. W.; de Boer, Bas; Bintanja, Richard; Lourens, Lucas J.

2017-09-01

Since the inception of the Antarctic ice sheet at the Eocene-Oligocene transition (˜ 34 Myr ago), land ice has played a crucial role in Earth's climate. Through feedbacks in the climate system, land ice variability modifies atmospheric temperature changes induced by orbital, topographical, and greenhouse gas variations. Quantification of these feedbacks on long timescales has hitherto scarcely been undertaken. In this study, we use a zonally averaged energy balance climate model bidirectionally coupled to a one-dimensional ice sheet model, capturing the ice-albedo and surface-height-temperature feedbacks. Potentially important transient changes in topographic boundary conditions by tectonics and erosion are not taken into account but are briefly discussed. The relative simplicity of the coupled model allows us to perform integrations over the past 38 Myr in a fully transient fashion using a benthic oxygen isotope record as forcing to inversely simulate CO2. Firstly, we find that the results of the simulations over the past 5 Myr are dependent on whether the model run is started at 5 or 38 Myr ago. This is because the relation between CO2 and temperature is subject to hysteresis. When the climate cools from very high CO2 levels, as in the longer transient 38 Myr run, temperatures in the lower CO2 range of the past 5 Myr are higher than when the climate is initialised at low temperatures. Consequently, the modelled CO2 concentrations depend on the initial state. Taking the realistic warm initialisation into account, we come to a best estimate of CO2, temperature, ice-volume-equivalent sea level, and benthic δ18O over the past 38 Myr. Secondly, we study the influence of ice sheets on the evolution of global temperature and polar amplification by comparing runs with ice sheet-climate interaction switched on and off. By passing only albedo or surface height changes to the climate model, we can distinguish the separate effects of the ice-albedo and surface-height-temperature feedbacks. We find that ice volume variability has a strong enhancing effect on atmospheric temperature changes, particularly in the regions where the ice sheets are located. As a result, polar amplification in the Northern Hemisphere decreases towards warmer climates as there is little land ice left to melt. Conversely, decay of the Antarctic ice sheet increases polar amplification in the Southern Hemisphere in the high-CO2 regime. Our results also show that in cooler climates than the pre-industrial, the ice-albedo feedback predominates the surface-height-temperature feedback, while in warmer climates they are more equal in strength.

Interfacing a one-dimensional lake model with a single-column atmospheric model: 2. Thermal response of the deep Lake Geneva, Switzerland under a 2 × CO2 global climate change

NASA Astrophysics Data System (ADS)

Perroud, Marjorie; Goyette, StéPhane

2012-06-01

In the companion to the present paper, the one-dimensional k-ɛ lake model SIMSTRAT is coupled to a single-column atmospheric model, nicknamed FIZC, and an application of the coupled model to the deep Lake Geneva, Switzerland, is described. In this paper, the response of Lake Geneva to global warming caused by an increase in atmospheric carbon dioxide concentration (i.e., 2 × CO2) is investigated. Coupling the models allowed for feedbacks between the lake surface and the atmosphere and produced changes in atmospheric moisture and cloud cover that further modified the downward radiation fluxes. The time evolution of atmospheric variables as well as those of the lake's thermal profile could be reproduced realistically by devising a set of adjustable parameters. In a "control" 1 × CO2 climate experiment, the coupled FIZC-SIMSTRAT model demonstrated genuine skills in reproducing epilimnetic and hypolimnetic temperatures, with annual mean errors and standard deviations of 0.25°C ± 0.25°C and 0.3°C ± 0.15°C, respectively. Doubling the CO2 concentration induced an atmospheric warming that impacted the lake's thermal structure, increasing the stability of the water column and extending the stratified period by 3 weeks. Epilimnetic temperatures were seen to increase by 2.6°C to 4.2°C, while hypolimnion temperatures increased by 2.2°C. Climate change modified components of the surface energy budget through changes mainly in air temperature, moisture, and cloud cover. During summer, reduced cloud cover resulted in an increase in the annual net solar radiation budget. A larger water vapor deficit at the air-water interface induced a cooling effect in the lake.

Using the CLEAN educational resource collection for building three-dimensional lessons to teach the climate system

NASA Astrophysics Data System (ADS)

Gold, A. U.; Sullivan, S. M.; Manning, C. L. B.; Ledley, T. S.; Youngman, E.; Taylor, J.; Niepold, F., III; Kirk, K.; Lockwood, J.; Bruckner, M. Z.; Fox, S.

2017-12-01

The impacts of climate change are a critical societal challenge of the 21st century. Educating students about the globally connected climate system is key in supporting the development of mitigation and adaptation strategies. Systems thinking is required for students to understand the complex, dynamic climate systems and the role that humans play within them. The interdisciplinary nature of climate science challenges educators, who often don't have formal training in climate science, to identify resources that are scientifically accurate before weaving them together into units that teach about the climate system. The Climate Literacy and Energy Awareness Network (CLEAN) supports this work by providing over 700 peer-reviewed, classroom-ready resources on climate and energy topics. The resource collection itself provide only limited instructional guidance, so educators need to weave the resources together to build multi-dimensional lessons that develop systems thinking skills. The Next Generation Science Standards (NGSS) science standards encourage educators to teach science in a 3-dimensional approach that trains students in systems thinking. The CLEAN project strives to help educators design NGSS-style, three-dimensional lessons about the climate system. Two approaches are currently being modeled on the CLEAN web portal. The first is described in the CLEAN NGSS "Get Started Guide" which follows a step-by-step process starting with the Disciplinary Core Idea and then interweaves the Cross-Cutting Concepts (CCC) and the Science and Engineering Practices (SEP) based on the teaching strategy chosen for the lesson or unit topic. The second model uses a climate topic as a starting place and the SEP as the guide through a four-step lesson sequence called "Earth Systems Investigations". Both models use CLEAN reviewed lessons as the core activity but provide the necessary framework for classroom implementation. Sample lessons that were developed following these two approaches are provided on the CLEAN web portal (cleanet.org).

Climate-chemical interactions and greenhouse effects of trace gases

NASA Technical Reports Server (NTRS)

Shi, Guang-Yu; Fan, Xiao-Biao

1994-01-01

A completely coupled one-dimensional radiative-convective (RC) and photochemical-diffusion (PC) model has been developed recently and used to study the climate-chemical interactions. The importance of radiative-chemical interactions within the troposphere and stratosphere has been examined in some detail. We find that increases of radiatively and/or chemically active trace gases such as CO2, CH4 and N2O have both the direct effects and the indirect effects on climate change by changing the atmospheric O3 profile through their interaction with chemical processes in the atmosphere. It is also found that the climatic effect of ozone depends strongly on its vertical distribution throughout the troposphere and stratosphere, as well on its column amount in the atmosphere.

Multi-year global climatic effects of atmospheric dust from large bolide impacts

NASA Technical Reports Server (NTRS)

Thompson, Starley L.

1988-01-01

The global climatic effects of dust generated by the impact of a 10 km-diameter bolide was simulated using a one-dimensional (vertical only) globally-averaged climate model by Pollack et al. The goal of the simulation is to examine the regional climate effects, including the possibility of coastal refugia, generated by a global dust cloud in a model having realistic geographic resolution. The climate model assumes the instantaneous appearance of a global stratospheric dust cloud with initial optical depth of 10,000. The time history of optical depth decreases according to the detailed calculations of Pollack et al., reaching an optical depth of unity at day 160, and subsequently decreasing with an e-folding time of 1 year. The simulation is carried out for three years in order to examine the atmospheric effects and recovery over several seasons. The simulation does not include any effects of NOx, CO2, or wildfire smoke injections that may accompany the creation of the dust cloud. The global distribution of surface temperature changes, freezing events, precipitation and soil moisture effects and sea ice increases will be discussed.

One-dimensional modelling of upper ocean mixing by turbulence due to wave orbital motion

NASA Astrophysics Data System (ADS)

Ghantous, M.; Babanin, A. V.

2014-02-01

Mixing of the upper ocean affects the sea surface temperature by bringing deeper, colder water to the surface. Because even small changes in the surface temperature can have a large impact on weather and climate, accurately determining the rate of mixing is of central importance for forecasting. Although there are several mixing mechanisms, one that has until recently been overlooked is the effect of turbulence generated by non-breaking, wind-generated surface waves. Lately there has been a lot of interest in introducing this mechanism into ocean mixing models, and real gains have been made in terms of increased fidelity to observational data. However, our knowledge of the mechanism is still incomplete. We indicate areas where we believe the existing parameterisations need refinement and propose an alternative one. We use two of the parameterisations to demonstrate the effect on the mixed layer of wave-induced turbulence by applying them to a one-dimensional mixing model and a stable temperature profile. Our modelling experiment suggests a strong effect on sea surface temperature due to non-breaking wave-induced turbulent mixing.

The Future of Planetary Climate Modeling and Weather Prediction

NASA Technical Reports Server (NTRS)

Del Genio, A. D.; Domagal-Goldman, S. D.; Kiang, N. Y.; Kopparapu, R. K.; Schmidt, G. A.; Sohl, L. E.

2017-01-01

Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction

NASA Astrophysics Data System (ADS)

Vrac, Mathieu

2018-06-01

Climate simulations often suffer from statistical biases with respect to observations or reanalyses. It is therefore common to correct (or adjust) those simulations before using them as inputs into impact models. However, most bias correction (BC) methods are univariate and so do not account for the statistical dependences linking the different locations and/or physical variables of interest. In addition, they are often deterministic, and stochasticity is frequently needed to investigate climate uncertainty and to add constrained randomness to climate simulations that do not possess a realistic variability. This study presents a multivariate method of rank resampling for distributions and dependences (R2D2) bias correction allowing one to adjust not only the univariate distributions but also their inter-variable and inter-site dependence structures. Moreover, the proposed R2D2 method provides some stochasticity since it can generate as many multivariate corrected outputs as the number of statistical dimensions (i.e., number of grid cell × number of climate variables) of the simulations to be corrected. It is based on an assumption of stability in time of the dependence structure - making it possible to deal with a high number of statistical dimensions - that lets the climate model drive the temporal properties and their changes in time. R2D2 is applied on temperature and precipitation reanalysis time series with respect to high-resolution reference data over the southeast of France (1506 grid cell). Bivariate, 1506-dimensional and 3012-dimensional versions of R2D2 are tested over a historical period and compared to a univariate BC. How the different BC methods behave in a climate change context is also illustrated with an application to regional climate simulations over the 2071-2100 period. The results indicate that the 1d-BC basically reproduces the climate model multivariate properties, 2d-R2D2 is only satisfying in the inter-variable context, 1506d-R2D2 strongly improves inter-site properties and 3012d-R2D2 is able to account for both. Applications of the proposed R2D2 method to various climate datasets are relevant for many impact studies. The perspectives of improvements are numerous, such as introducing stochasticity in the dependence itself, questioning its stability assumption, and accounting for temporal properties adjustment while including more physics in the adjustment procedures.

Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1

NASA Astrophysics Data System (ADS)

Langenbrunner, B.; Neelin, J. D.

2017-09-01

Global climate models (GCMs) are examples of high-dimensional input-output systems, where model output is a function of many variables, and an update in model physics commonly improves performance in one objective function (i.e., measure of model performance) at the expense of degrading another. Here concepts from multiobjective optimization in the engineering literature are used to investigate parameter sensitivity and optimization in the face of such trade-offs. A metamodeling technique called cut high-dimensional model representation (cut-HDMR) is leveraged in the context of multiobjective optimization to improve GCM simulation of the tropical Pacific climate, focusing on seasonal precipitation, column water vapor, and skin temperature. An evolutionary algorithm is used to solve for Pareto fronts, which are surfaces in objective function space along which trade-offs in GCM performance occur. This approach allows the modeler to visualize trade-offs quickly and identify the physics at play. In some cases, Pareto fronts are small, implying that trade-offs are minimal, optimal parameter value choices are more straightforward, and the GCM is well-functioning. In all cases considered here, the control run was found not to be Pareto-optimal (i.e., not on the front), highlighting an opportunity for model improvement through objectively informed parameter selection. Taylor diagrams illustrate that these improvements occur primarily in field magnitude, not spatial correlation, and they show that specific parameter updates can improve fields fundamental to tropical moist processes—namely precipitation and skin temperature—without significantly impacting others. These results provide an example of how basic elements of multiobjective optimization can facilitate pragmatic GCM tuning processes.

Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model

NASA Technical Reports Server (NTRS)

Hansen, J.; Fung, I.; Lacis, A.; Rind, D.; Lebedeff, S.; Ruedy, R.; Russell, G.

1988-01-01

The global climate effects of time-dependent atmospheric trace gas and aerosol variations are simulated by NASA-Goddard's three-dimensional climate model II, which possesses 8 x 10-deg horizontal resolution, for the cases of a 100-year control run and three different atmospheric composition scenarios in which trace gas growth is respectively a continuation of current exponential trends, a reduced linear growth, and a rapid curtailment of emissions due to which net climate forcing no longer increases after the year 2000. The experiments begin in 1958, run to the present, and encompass measured or estimated changes in CO2, CH4, N2O, chlorofluorocarbons, and stratospheric aerosols. It is shown that the greenhouse warming effect may be clearly identifiable in the 1990s.

Physical effects of thermal pollution in lakes

NASA Astrophysics Data System (ADS)

Râman Vinnâ, Love; Wüest, Alfred; Bouffard, Damien

2017-05-01

Anthropogenic heat emissions into inland waters influence water temperature and affect stratification, heat and nutrient fluxes, deep water renewal, and biota. Given the increased thermal stress on these systems by growing cooling demands of riparian/coastal infrastructures in combination with climate warming, the question arises on how to best monitor and manage these systems. In this study, we investigate local and system-wide physical effects on the medium-sized perialpine Lake Biel (Switzerland), influenced by point-source cooling water emission from an upstream nuclear power plant (heat emission ˜700 MW, ˜18 W m-2 lake wide). We use one-dimensional (SIMSTRAT) and three-dimensional (Delft3D-Flow) hydrodynamic numerical simulations and provide model resolution guidelines for future studies of thermal pollution. The effects on Lake Biel by the emitted excess heat are summarized as: (i) clear seasonal trend in temperature increase, locally up to 3.4°C and system-wide volume mean ˜0.3°C, which corresponds to one decade of regional surface water climate warming; (ii) the majority of supplied thermal pollution (˜60%) leaves this short residence time (˜58 days) system via the main outlet, whereas the remaining heat exits to the atmosphere; (iii) increased length of stratified period due to the stabilizing effects of additional heat; (iv) system-wide effects such as warmer temperature, prolonged stratified period, and river-caused epilimnion flushing are resolved by both models whereas local raised temperature and river short circuiting was only identifiable with the three-dimensional model approach. This model-based method provides an ideal tool to assess man-made impacts on lakes and their downstream outflows.

CO2 condensation and the climate of early Mars.

PubMed

Kasting, J F

1991-01-01

A one-dimensional, radiative-convective climate model was used to reexamine the question of whether early Mars could have been kept warm by the greenhouse effect of a dense, CO2 atmosphere. The new model differs from previous models by considering the influence of CO2 clouds on the convective lapse rate and on the the planetary radiation budget. Condensation of CO2 decreases the lapse rate and, hence, reduces the magnitude of the greenhouse effect. This phenomenon becomes increasingly important at low solar luminosities and may preclude warm (0 degree C), globally averaged surface temperatures prior to approximately 2 billion years ago unless other greenhouse gases were present in addition to CO2 and H2O. Alternative mechanisms for warming early Mars and explaining channel formation are discussed.

Modeling effects of climate change on Yakima River salmonid habitats

USGS Publications Warehouse

Hatten, James R.; Batt, Thomas R.; Connolly, Patrick J.; Maule, Alec G.

2014-01-01

We evaluated the potential effects of two climate change scenarios on salmonid habitats in the Yakima River by linking the outputs from a watershed model, a river operations model, a two-dimensional (2D) hydrodynamic model, and a geographic information system (GIS). The watershed model produced a discharge time series (hydrograph) in two study reaches under three climate scenarios: a baseline (1981–2005), a 1-°C increase in mean air temperature (plus one scenario), and a 2-°C increase (plus two scenario). A river operations model modified the discharge time series with Yakima River operational rules, a 2D model provided spatially explicit depth and velocity grids for two floodplain reaches, while an expert panel provided habitat criteria for four life stages of coho and fall Chinook salmon. We generated discharge-habitat functions for each salmonid life stage (e.g., spawning, rearing) in main stem and side channels, and habitat time series for baseline, plus one (P1) and plus two (P2) scenarios. The spatial and temporal patterns in salmonid habitats differed by reach, life stage, and climate scenario. Seventy-five percent of the 28 discharge-habitat responses exhibited a decrease in habitat quantity, with the P2 scenario producing the largest changes, followed by P1. Fry and spring/summer rearing habitats were the most sensitive to warming and flow modification for both species. Side channels generally produced more habitat than main stem and were more responsive to flow changes, demonstrating the importance of lateral connectivity in the floodplain. A discharge-habitat sensitivity analysis revealed that proactive management of regulated surface waters (i.e., increasing or decreasing flows) might lessen the impacts of climate change on salmonid habitats.

Impact of four-dimensional data assimilation (FDDA) on urban climate analysis

NASA Astrophysics Data System (ADS)

Pan, Linlin; Liu, Yubao; Liu, Yuewei; Li, Lei; Jiang, Yin; Cheng, Will; Roux, Gregory

2015-12-01

This study investigates the impact of four-dimensional data assimilation (FDDA) on urban climate analysis, which employs the NCAR (National Center for Atmospheric Research) WRF (the weather research and forecasting model) based on climate FDDA (CFDDA) technology to develop an urban-scale microclimatology database for the Shenzhen area, a rapidly developing metropolitan located along the southern coast of China, where uniquely high-density observations, including ultrahigh-resolution surface AWS (automatic weather station) network, radio sounding, wind profilers, radiometers, and other weather observation platforms, have been installed. CFDDA is an innovative dynamical downscaling regional climate analysis system that assimilates diverse regional observations; and has been employed to produce a 5 year multiscale high-resolution microclimate analysis by assimilating high-density observations at Shenzhen area. The CFDDA system was configured with four nested-grid domains at grid sizes of 27, 9, 3, and 1 km, respectively. This research evaluates the impact of assimilating high-resolution observation data on reproducing the refining features of urban-scale circulations. Two experiments were conducted with a 5 year run using CFSR (climate forecast system reanalysis) as boundary and initial conditions: one with CFDDA and the other without. The comparisons of these two experiments with observations indicate that CFDDA greatly reduces the model analysis error and is able to realistically analyze the microscale features such as urban-rural-coastal circulation, land/sea breezes, and local-hilly terrain thermal circulations. It is demonstrated that the urbanization can produce 2.5 k differences in 2 m temperatures, delays/speeds up the land/sea breeze development, and interacts with local mountain-valley circulations.

Modeling the seasonal cycle of CO2 on Mars: A fit to the Viking lander pressure curves

NASA Technical Reports Server (NTRS)

Wood, S. E.; Paige, D. A.

1992-01-01

We have constructed a more accurate Mars thermal model, similar to the one used by Leighton and Murray in 1966, which solves radiative, conductive, and latent heat balance at the surface as well as the one-dimensional heat conduction equation for 40 layers to a depth of 15 meters every 1/36 of a Martian day. The planet is divided into 42 latitude bands with a resolution of two degrees near the poles and five degrees at lower latitudes, with elevations relative to the 6.1 mbar reference areoid. This estimate of the Martian zonally averaged topography was derived primarily from radio occultations. We show that a realistic one-dimensional thermal model is able to reproduce the VL1 pressure curve reasonably well without having to invoke complicated atmospheric effects such as dust storms and polar hoods. Although these factors may cause our deduced values for each model parameter to differ from its true value, we believe that this simple model can be used as a platform to study many aspects of the Martian CO2 cycle over seasonal, interannual, and long-term climate timescales.

A Mixed-dimensional Model for Determining the Impact of Permafrost Polygonal Ground Degradation on Arctic Hydrology.

NASA Astrophysics Data System (ADS)

Coon, E.; Jan, A.; Painter, S. L.; Moulton, J. D.; Wilson, C. J.

2017-12-01

Many permafrost-affected regions in the Arctic manifest a polygonal patterned ground, which contains large carbon stores and is vulnerability to climate change as warming temperatures drive melting ice wedges, polygon degradation, and thawing of the underlying carbon-rich soils. Understanding the fate of this carbon is difficult. The system is controlled by complex, nonlinear physics coupling biogeochemistry, thermal-hydrology, and geomorphology, and there is a strong spatial scale separation between microtopograpy (at the scale of an individual polygon) and the scale of landscape change (at the scale of many thousands of polygons). Physics-based models have come a long way, and are now capable of representing the diverse set of processes, but only on individual polygons or a few polygons. Empirical models have been used to upscale across land types, including ecotypes evolving from low-centered (pristine) polygons to high-centered (degraded) polygon, and do so over large spatial extent, but are limited in their ability to discern causal process mechanisms. Here we present a novel strategy that looks to use physics-based models across scales, bringing together multiple capabilities to capture polygon degradation under a warming climate and its impacts on thermal-hydrology. We use fine-scale simulations on individual polygons to motivate a mixed-dimensional strategy that couples one-dimensional columns representing each individual polygon through two-dimensional surface flow. A subgrid model is used to incorporate the effects of surface microtopography on surface flow; this model is described and calibrated to fine-scale simulations. And critically, a subsidence model that tracks volume loss in bulk ice wedges is used to alter the subsurface structure and subgrid parameters, enabling the inclusion of the feedbacks associated with polygon degradation. This combined strategy results in a model that is able to capture the key features of polygon permafrost degradation, but in a simulation across a large spatial extent of polygonal tundra.

Laminar Flow in the Ocean Ekman Layer

NASA Astrophysics Data System (ADS)

Woods, J. T. H.

INTRODUCTION THE EFFECT OF A STABLE DENSITY GRADIENT THE FATAL FLAW FLOW VISUALIZATION THE DISCOVERY OF LAMINAR FLOW FINE STRUCTURE WAVE-INDUCED SHEAR INSTABILITY BILLOW TURBULENCE REVERSE TRANSITION REVISED PARADIGM ONE-DIMENSIONAL MODELLING OF THE UPPER OCEAN DIURNAL VARIATION BUOYANT CONVECTION BILLOW TURBULENCE IN THE DIURNAL THERMOCLINE CONSEQUENCES FOR THE EKMAN CURRENT PROFILE SOLAR RADIATION APPLICATIONS Slippery Seas of Acapulco Pollution Afternoon Effect in Sonar Patchiness Fisheries Climate DISCUSSION CONCLUSION REFERENCES

A Process-based, Climate-Sensitive Model to Derive Methane Emissions from Natural Wetlands: Application to 5 Wetland Sites, Sensitivity to Model Parameters and Climate

NASA Technical Reports Server (NTRS)

Walter, Bernadette P.; Heimann, Martin

1999-01-01

Methane emissions from natural wetlands constitutes the largest methane source at present and depends highly on the climate. In order to investigate the response of methane emissions from natural wetlands to climate variations, a 1-dimensional process-based climate-sensitive model to derive methane emissions from natural wetlands is developed. In the model the processes leading to methane emission are simulated within a 1-dimensional soil column and the three different transport mechanisms diffusion, plant-mediated transport and ebullition are modeled explicitly. The model forcing consists of daily values of soil temperature, water table and Net Primary Productivity, and at permafrost sites the thaw depth is included. The methane model is tested using observational data obtained at 5 wetland sites located in North America, Europe and Central America, representing a large variety of environmental conditions. It can be shown that in most cases seasonal variations in methane emissions can be explained by the combined effect of changes in soil temperature and the position of the water table. Our results also show that a process-based approach is needed, because there is no simple relationship between these controlling factors and methane emissions that applies to a variety of wetland sites. The sensitivity of the model to the choice of key model parameters is tested and further sensitivity tests are performed to demonstrate how methane emissions from wetlands respond to climate variations.

Climate modeling. [for use in understanding earth's radiation budget

NASA Technical Reports Server (NTRS)

1978-01-01

The requirements for radiation measurements suitable for the understanding, improvement, and verification of models used in performing climate research are considered. Both zonal energy balance models and three dimensional general circulation models are considered, and certain problems are identified as common to all models. Areas of emphasis include regional energy balance observations, spectral band observations, cloud-radiation interaction, and the radiative properties of the earth's surface.

LakeMIP Kivu: Evaluating the representation of a large, deep tropical lake by a set of 1-dimensional lake models

NASA Astrophysics Data System (ADS)

Thiery, Wim; Stepanenko, Viktor; Darchambeau, François; Joehnk, Klaus; Martynov, Andrey; Mironov, Dmitrii; Perroud, Marjorie; van Lipzig, Nicole

2013-04-01

The African great lakes are of utmost importance for the local economy (fishing), as well as being essential to the survival of the local people. During the last decades, these lakes experienced fast changes in ecosystem structure and functioning and their future evolution is a major concern. In this study, for the first time a set of one-dimensional lake models are evaluated over East-Africa, in particular over Lake Kivu (2.28 °S; 28.98 °E). The unique limnology of meromictic Lake Kivu, with the importance of salinity and geothermal springs in a tropical high-altitude climate, presents a worthy challenge to the 1D-lake models currently involved in the Lake Model Intercomparison Project (LakeMIP). Furthermore, this experiment will serve as the basis for a future, more complex intercomparison, coupling lake models with atmospheric circulation models to analyse climate change effects on the lake. Meteorological observations from two automatic weather stations, one at Kamembe airport (Rwanda, 2003-2008), the other at ISP Bukavu (DRC, 2003-2011), are used to drive each of these models. For the evaluation, a unique dataset is used which contains over 150 temperature profiles recorded since 2002. The standard LakeMIP protocol is adapted to mirror the limnological conditions in Lake Kivu and to unify model parameters as far as possible. Since some lake models do not account for salinity and its effect upon lake stratification, two sets of simulations are performed with each model: one for the freshwater layer only (60 m) and one for the average lake depth (240 m) including salinity. Therewith, on the one hand it is investigated whether each model is able to reproduce the correct mixing regime in Lake Kivu and captures the controlling of this seasonality by the relative humidity, which constrains evaporation except during summer (JJA). On the other hand, the ability of different models to simulate salinity- and geothermal-induced effects upon deep water stratification is analysed. Finally, different models are tested for their sensitivity to variations in respectively the light extinction coefficient, the geothermal heat flux, the applied wind speed correction and the bottom sediments routine.

Hydrologic Response and Watershed Sensitivity to Climate Warming in California's Sierra Nevada

PubMed Central

Null, Sarah E.; Viers, Joshua H.; Mount, Jeffrey F.

2010-01-01

This study focuses on the differential hydrologic response of individual watersheds to climate warming within the Sierra Nevada mountain region of California. We describe climate warming models for 15 west-slope Sierra Nevada watersheds in California under unimpaired conditions using WEAP21, a weekly one-dimensional rainfall-runoff model. Incremental climate warming alternatives increase air temperature uniformly by 2°, 4°, and 6°C, but leave other climatic variables unchanged from observed values. Results are analyzed for changes in mean annual flow, peak runoff timing, and duration of low flow conditions to highlight which watersheds are most resilient to climate warming within a region, and how individual watersheds may be affected by changes to runoff quantity and timing. Results are compared with current water resources development and ecosystem services in each watershed to gain insight into how regional climate warming may affect water supply, hydropower generation, and montane ecosystems. Overall, watersheds in the northern Sierra Nevada are most vulnerable to decreased mean annual flow, southern-central watersheds are most susceptible to runoff timing changes, and the central portion of the range is most affected by longer periods with low flow conditions. Modeling results suggest the American and Mokelumne Rivers are most vulnerable to all three metrics, and the Kern River is the most resilient, in part from the high elevations of the watershed. Our research seeks to bridge information gaps between climate change modeling and regional management planning, helping to incorporate climate change into the development of regional adaptation strategies for Sierra Nevada watersheds. PMID:20368984

Multi-Decadal Coastal Behavioural States From A Fusion Of Geohistorical Conceptual Modelling With 2-D Morphodynamic Modelling

NASA Astrophysics Data System (ADS)

Goodwin, I. D.; Mortlock, T.

2016-02-01

Geohistorical archives of shoreline and foredune planform geometry provides a unique evidence-based record of the time integral response to coupled directional wave climate and sediment supply variability on annual to multi-decadal time scales. We develop conceptual shoreline modelling from the geohistorical shoreline archive using a novel combination of methods, including: LIDAR DEM and field mapping of coastal geology; a decadal-scale climate reconstruction of sea-level pressure, marine windfields, and paleo-storm synoptic type and frequency, and historical bathymetry. The conceptual modelling allows for the discrimination of directional wave climate shifts and the relative contributions of cross-shore and along-shore sand supply rates at multi-decadal resolution. We present regional examples from south-eastern Australia over a large latitudinal gradient from subtropical Queensland (S 25°) to mid-latitude Bass Strait (S 40°) that illustrate the morphodynamic evolution and reorganization to wave climate change. We then use the conceptual modeling to inform a two-dimensional coupled spectral wave-hydrodynamic-morphodynamic model to investigate the shoreface response to paleo-directional wind and wave climates. Unlike one-line shoreline modelling, this fully dynamical approach allows for the investigation of cumulative and spatial bathymetric change due to wave-induced currents, as well as proxy-shoreline change. The fusion of the two modeling approaches allows for: (i) the identification of the natural range of coastal planform geometries in response to wave climate shifts; and, (ii) the decomposition of the multidecadal coastal change into the cross-shore and along-shore sand supply drivers, according to the best-matching planforms.

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Weisenstein, Debra; Shia, Run-Lie; Sze, N. D.

1998-01-01

The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER 2-dimensional chemistry-transport model, the AER 2-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. We will continue developing our three-wave model so that we can help NASA determine the strength and weakness of the next generation assessment models.

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Lie; Sze, N. D.

1998-01-01

The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. We will continue developing our three-wave model so that we can help NASA determine the strength and weakness of the next generation assessment models.

Application of empirical and dynamical closure methods to simple climate models

NASA Astrophysics Data System (ADS)

Padilla, Lauren Elizabeth

This dissertation applies empirically- and physically-based methods for closure of uncertain parameters and processes to three model systems that lie on the simple end of climate model complexity. Each model isolates one of three sources of closure uncertainty: uncertain observational data, large dimension, and wide ranging length scales. They serve as efficient test systems toward extension of the methods to more realistic climate models. The empirical approach uses the Unscented Kalman Filter (UKF) to estimate the transient climate sensitivity (TCS) parameter in a globally-averaged energy balance model. Uncertainty in climate forcing and historical temperature make TCS difficult to determine. A range of probabilistic estimates of TCS computed for various assumptions about past forcing and natural variability corroborate ranges reported in the IPCC AR4 found by different means. Also computed are estimates of how quickly uncertainty in TCS may be expected to diminish in the future as additional observations become available. For higher system dimensions the UKF approach may become prohibitively expensive. A modified UKF algorithm is developed in which the error covariance is represented by a reduced-rank approximation, substantially reducing the number of model evaluations required to provide probability densities for unknown parameters. The method estimates the state and parameters of an abstract atmospheric model, known as Lorenz 96, with accuracy close to that of a full-order UKF for 30-60% rank reduction. The physical approach to closure uses the Multiscale Modeling Framework (MMF) to demonstrate closure of small-scale, nonlinear processes that would not be resolved directly in climate models. A one-dimensional, abstract test model with a broad spatial spectrum is developed. The test model couples the Kuramoto-Sivashinsky equation to a transport equation that includes cloud formation and precipitation-like processes. In the test model, three main sources of MMF error are evaluated independently. Loss of nonlinear multi-scale interactions and periodic boundary conditions in closure models were dominant sources of error. Using a reduced order modeling approach to maximize energy content allowed reduction of the closure model dimension up to 75% without loss in accuracy. MMF and a comparable alternative model peformed equally well compared to direct numerical simulation.

The Impact of ARM on Climate Modeling. Chapter 26

NASA Technical Reports Server (NTRS)

Randall, David A.; Del Genio, Anthony D.; Donner, Leo J.; Collins, William D.; Klein, Stephen A.

2016-01-01

Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative envisioning that starts from the intended application and is based on current understanding of how the atmosphere works and the inventory of mathematical methods available.

Weighted Iterative Bayesian Compressive Sensing (WIBCS) for High Dimensional Polynomial Surrogate Construction

NASA Astrophysics Data System (ADS)

Sargsyan, K.; Ricciuto, D. M.; Safta, C.; Debusschere, B.; Najm, H. N.; Thornton, P. E.

2016-12-01

Surrogate construction has become a routine procedure when facing computationally intensive studies requiring multiple evaluations of complex models. In particular, surrogate models, otherwise called emulators or response surfaces, replace complex models in uncertainty quantification (UQ) studies, including uncertainty propagation (forward UQ) and parameter estimation (inverse UQ). Further, surrogates based on Polynomial Chaos (PC) expansions are especially convenient for forward UQ and global sensitivity analysis, also known as variance-based decomposition. However, the PC surrogate construction strongly suffers from the curse of dimensionality. With a large number of input parameters, the number of model simulations required for accurate surrogate construction is prohibitively large. Relatedly, non-adaptive PC expansions typically include infeasibly large number of basis terms far exceeding the number of available model evaluations. We develop Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth and PC surrogate construction leading to a sparse, high-dimensional PC surrogate with a very few model evaluations. The surrogate is then readily employed for global sensitivity analysis leading to further dimensionality reduction. Besides numerical tests, we demonstrate the construction on the example of Accelerated Climate Model for Energy (ACME) Land Model for several output QoIs at nearly 100 FLUXNET sites covering multiple plant functional types and climates, varying 65 input parameters over broad ranges of possible values. This work is supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research, Accelerated Climate Modeling for Energy (ACME) project. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Combined climate and carbon-cycle effects of large-scale deforestation

PubMed Central

Bala, G.; Caldeira, K.; Wickett, M.; Phillips, T. J.; Lobell, D. B.; Delire, C.; Mirin, A.

2007-01-01

The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO2 to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate. PMID:17420463

Combined climate and carbon-cycle effects of large-scale deforestation.

PubMed

Bala, G; Caldeira, K; Wickett, M; Phillips, T J; Lobell, D B; Delire, C; Mirin, A

2007-04-17

The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO(2) to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.

Combined Climate and Carbon-Cycle Effects of Large-Scale Deforestation

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

Bala, G; Caldeira, K; Wickett, M

2006-10-17

The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO{sub 2} to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These are the first such simulations performed using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has amore » net cooling influence on Earth's climate, since the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. While these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.« less

Estimate of temperature change due to ice and snow accretion in the boreal forest regions

NASA Astrophysics Data System (ADS)

Sugiura, K.; Nagai, S.; Suzuki, R.; Eicken, H.; Maximov, T. C.

2016-12-01

Previous research has demonstrated that there is a wide difference between the surface albedo in winter/spring in snow-covered forest regions in various global climate models. If the forest is covered with snow, the surface albedo would increase. In this study, we carried out field observations to monitor the frequency of ice and snow accretion in the boreal forest regions. The time-lapse digital camera was set up on each side of the observation towers at the site located to the north of Fairbanks (USA) and at the site located to the north of Yakutsk (Russia). It was confirmed that both forests were not necessarily covered with snow without a break from the start of continuous snow cover until the end. In addition, the boreal forest at the Yakutsk site is covered with snow in comparison with the boreal forest at the Fairbanks site for a long term such as for about five month. Using a one-dimensional mathematics model about the energy flow including atmospheric multiple scattering, we estimated temperature change due to ice and snow accretion in the boreal forest regions. The result show that the mean surface temperature rises approximately 0.5 [oC] when the boreal forest is not covered with snow. In this presentation, we discuss the snow albedo parameterization in the boreal forest regions and the one-dimensional mathematics model to provide a basis for a better understanding of the role of snow in the climate system.

On determining the point of no return in climate change

NASA Astrophysics Data System (ADS)

van Zalinge, Brenda C.; Feng, Qing Yi; Aengenheyster, Matthias; Dijkstra, Henk A.

2017-08-01

Earth's global mean surface temperature has increased by about 1.0 °C over the period 1880-2015. One of the main causes is thought to be the increase in atmospheric greenhouse gases. If greenhouse gas emissions are not substantially decreased, several studies indicate that there will be a dangerous anthropogenic interference with climate by the end of this century. However, there is no good quantitative measure to determine when it is too late to start reducing greenhouse gas emissions in order to avoid such dangerous interference. In this study, we develop a method for determining a so-called point of no return for several greenhouse gas emission scenarios. The method is based on a combination of aspects of stochastic viability theory and linear response theory; the latter is used to estimate the probability density function of the global mean surface temperature. The innovative element in this approach is the applicability to high-dimensional climate models as demonstrated by the results obtained with the PlaSim model.

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

NASA Astrophysics Data System (ADS)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

Modeling the resilience of Amazonian carbon pools under changing climate

NASA Astrophysics Data System (ADS)

Hajdu, L. H.; Friend, A. D.; Dolman, A. J.

2013-12-01

The rainfall in the Amazon basin is derived from a mixture of moisture convergence from the Atlantic Ocean and local recycling. Changes in the moisture convergence especially during El Nino episodes, strongly influence the interannual climate variability of the basin, potentially having a strong impact on the carbon pools in vegetation and soil, leading to a changes in the ecosystem of the Amazon basin. We used a 0-dimensional model of atmospheric convection (after D'Andrea et al. 2006) to generate realistic timeseries of temperature and precipitation by changing the moisture convergence from the Atlantic Ocean with implications for the stability of Amazonian rainfall. We chose this model because it relies on very few parameters, allowing us to perform numerous sensitivity tests in relatively short time. In this model total rainfall depends on the parameter expressing the external moisture flux and the intensity of convection. Here, two values of moisture convergence were used, one representative of a wet climate (1.4 mm day-1) and one representative of a dry climate (0.54 mm day-1). We also increased the variability of the rainfall in order to investigate its impact on the carbon pools. We used these scenarios for changing precipitation, along with SRES emission scenarios for increasing atmospheric CO2 to force the Land Surface Model Hybrid8. The effects of a changing climate on the simulated soil and vegetation carbon pools have been investigated. Preliminary results show that in our model configuration and under a wet climate, the change in seasonal variability of precipitation does not seem to have a major impact on the carbon pools, which might suggest that the Amazon rainforest is relatively resilient to changes in seasonal precipitation. However, under a dry climate it may decline into a lower carbon system. The coupling of the two models is in progress with promising results for atmosphere-vegetation feedbacks. We will report on any changes in the threshold of precipitation required to change the carbon content of the system due to changed atmospheric CO2 concentrations.

ClimateSpark: An in-memory distributed computing framework for big climate data analytics

NASA Astrophysics Data System (ADS)

Hu, Fei; Yang, Chaowei; Schnase, John L.; Duffy, Daniel Q.; Xu, Mengchao; Bowen, Michael K.; Lee, Tsengdar; Song, Weiwei

2018-06-01

The unprecedented growth of climate data creates new opportunities for climate studies, and yet big climate data pose a grand challenge to climatologists to efficiently manage and analyze big data. The complexity of climate data content and analytical algorithms increases the difficulty of implementing algorithms on high performance computing systems. This paper proposes an in-memory, distributed computing framework, ClimateSpark, to facilitate complex big data analytics and time-consuming computational tasks. Chunking data structure improves parallel I/O efficiency, while a spatiotemporal index is built for the chunks to avoid unnecessary data reading and preprocessing. An integrated, multi-dimensional, array-based data model (ClimateRDD) and ETL operations are developed to address big climate data variety by integrating the processing components of the climate data lifecycle. ClimateSpark utilizes Spark SQL and Apache Zeppelin to develop a web portal to facilitate the interaction among climatologists, climate data, analytic operations and computing resources (e.g., using SQL query and Scala/Python notebook). Experimental results show that ClimateSpark conducts different spatiotemporal data queries/analytics with high efficiency and data locality. ClimateSpark is easily adaptable to other big multiple-dimensional, array-based datasets in various geoscience domains.

Interaction of ice sheets and climate during the past 800 000 years

NASA Astrophysics Data System (ADS)

Stap, L. B.; van de Wal, R. S. W.; de Boer, B.; Bintanja, R.; Lourens, L. J.

2014-12-01

During the Cenozoic, land ice and climate interacted on many different timescales. On long timescales, the effect of land ice on global climate and sea level is mainly set by large ice sheets in North America, Eurasia, Greenland and Antarctica. The climatic forcing of these ice sheets is largely determined by the meridional temperature profile resulting from radiation and greenhouse gas (GHG) forcing. As a response, the ice sheets cause an increase in albedo and surface elevation, which operates as a feedback in the climate system. To quantify the importance of these climate-land ice processes, a zonally averaged energy balance climate model is coupled to five one-dimensional ice sheet models, representing the major ice sheets. In this study, we focus on the transient simulation of the past 800 000 years, where a high-confidence CO2 record from ice core samples is used as input in combination with Milankovitch radiation changes. We obtain simulations of atmospheric temperature, ice volume and sea level that are in good agreement with recent proxy-data reconstructions. We examine long-term climate-ice-sheet interactions by a comparison of simulations with uncoupled and coupled ice sheets. We show that these interactions amplify global temperature anomalies by up to a factor of 2.6, and that they increase polar amplification by 94%. We demonstrate that, on these long timescales, the ice-albedo feedback has a larger and more global influence on the meridional atmospheric temperature profile than the surface-height-temperature feedback. Furthermore, we assess the influence of CO2 and insolation by performing runs with one or both of these variables held constant. We find that atmospheric temperature is controlled by a complex interaction of CO2 and insolation, and both variables serve as thresholds for northern hemispheric glaciation.

Freshwater wetlands: fertile grounds for the invasive Phragmites australis in a climate change context

PubMed Central

Tougas-Tellier, Marie-Andrée; Morin, Jean; Hatin, Daniel; Lavoie, Claude

2015-01-01

Climate change will likely affect flooding regimes, which have a large influence on the functioning of freshwater riparian wetlands. Low water levels predicted for several fluvial systems make wetlands especially vulnerable to the spread of invaders, such as the common reed (Phragmites australis), one of the most invasive species in North America. We developed a model to map the distribution of potential germination grounds of the common reed in freshwater wetlands of the St. Lawrence River (Québec, Canada) under current climate conditions and used this model to predict their future distribution under two climate change scenarios simulated for 2050. We gathered historical and recent (remote sensing) data on the distribution of common reed stands for model calibration and validation purposes, then determined the parameters controlling the species establishment by seed. A two-dimensional model and the identified parameters were used to simulate the current (2010) and future (2050) distribution of germination grounds. Common reed stands are not widespread along the St. Lawrence River (212 ha), but our model suggests that current climate conditions are already conducive to considerable further expansion (>16,000 ha). Climate change may also exacerbate the expansion, particularly if river water levels drop, which will expose large bare areas propitious to seed germination. This phenomenon may be particularly important in one sector of the river, where existing common reed stands could increase their areas by a factor of 100, potentially creating the most extensive reedbed complex in North America. After colonizing salt and brackishwater marshes, the common reed could considerably expand into the freshwater marshes of North America which cover several million hectares. The effects of common reed expansion on biodiversity are difficult to predict, but likely to be highly deleterious given the competitiveness of the invader and the biological richness of freshwater wetlands. PMID:26380675

Impact of 3-D orographic gravity wave parameterisation on stratosphere dynamics

NASA Astrophysics Data System (ADS)

Eichinger, Roland; Garny, Hella; Cai, Duy; Jöckel, Patrick

2017-04-01

Stratosphere dynamics are strongly influenced by gravity waves (GWs) propagating upwards from the troposphere. Some of these GWs are generated through flow over small-scale orography and can not be resolved by common general circulation models (GCMs). Due to computational model designs, their parameterisation usually follows a one dimensional columnar approach that, among other simplifications, neglects the horizontal propagation of GWs on their way up into the Middle Atmosphere. This causes contradictions between models and observations in location and strength of GW drag force through their dissipation and as a consequence, also in stratospheric mean flow. In the EMAC (ECHAM MESSy Atmospheric Chemistry) model, we have found this deficiency to cause a too weak Antarctic polar vortex, which directly impacts stratospheric temperatures and thereby the chemical reactions that determine ozone depletion. For this reason, we adapt a three dimensional parameterisation for orographic GWs, that had been implemented and tested in the MIROC GCM, to the MESSy coding standard. This computationally light scheme can then be used in a modular and flexible way in a cascade of model setups from an idealised version for conceptional process analyses to full climate chemistry simulations for quantitative investigations. This model enhancement can help to reconcile models and observations in wave drag forcing itself, but in consequence, also in Brewer-Dobson Circulation trends across the recent decades. Furthermore, uncertainties in weather and climate predictions as well as in future ozone projections can be reduced.

Coupling Processes between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Lie; Sze, N. D.

1998-01-01

This is the third semi-annual report for NAS5-97039, covering January through June 1998. The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling for this work are the AER 2-dimensional chemistry-transport model, the AER 2-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. We will continue developing our three-wave model so that we can help NASA determine the strengths and weaknesses of the next generation assessment models.

Investigating the impact of diurnal cycle of SST on the intraseasonal and climate variability

NASA Astrophysics Data System (ADS)

Tseng, W. L.; Hsu, H. H.; Chang, C. W. J.; Keenlyside, N. S.; Lan, Y. Y.; Tsuang, B. J.; Tu, C. Y.

2016-12-01

The diurnal cycle is a prominent feature of our climate system and the most familiar example of externally forced variability. Despite this it remains poorly simulated in state-of-the-art climate models. A particular problem is the diurnal cycle in sea surface temperature (SST), which is a key variable in air-sea heat flux exchange. In most models the diurnal cycle in SST is not well resolved, due to insufficient vertical resolution in the upper ocean mixed-layer and insufficiently frequent ocean-atmosphere coupling. Here, we coupled a 1-dimensional ocean model (SIT) to two atmospheric general circulation model (ECHAM5 and CAM5). In particular, we focus on improving the representations of the diurnal cycle in SST in a climate model, and investigate the role of the diurnal cycle in climate and intraseasonal variability.

Comparisons between thermodynamic and one-dimensional combustion models of spark-ignition engines

NASA Technical Reports Server (NTRS)

Ramos, J. I.

1986-01-01

Results from a one-dimensional combustion model employing a constant eddy diffusivity and a one-step chemical reaction are compared with those of one-zone and two-zone thermodynamic models to study the flame propagation in a spark-ignition engine. One-dimensional model predictions are found to be very sensitive to the eddy diffusivity and reaction rate data. The average mixing temperature found using the one-zone thermodynamic model is higher than those of the two-zone and one-dimensional models during the compression stroke, and that of the one-dimensional model is higher than those predicted by both thermodynamic models during the expansion stroke. The one-dimensional model is shown to predict an accelerating flame even when the front approaches the cold cylinder wall.

Reduced nonlinear prognostic model construction from high-dimensional data

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

Construction of a data-driven model of evolution operator using universal approximating functions can only be statistically justified when the dimension of its phase space is small enough, especially in the case of short time series. At the same time in many applications real-measured data is high-dimensional, e.g. it is space-distributed and multivariate in climate science. Therefore it is necessary to use efficient dimensionality reduction methods which are also able to capture key dynamical properties of the system from observed data. To address this problem we present a Bayesian approach to an evolution operator construction which incorporates two key reduction steps. First, the data is decomposed into a set of certain empirical modes, such as standard empirical orthogonal functions or recently suggested nonlinear dynamical modes (NDMs) [1], and the reduced space of corresponding principal components (PCs) is obtained. Then, the model of evolution operator for PCs is constructed which maps a number of states in the past to the current state. The second step is to reduce this time-extended space in the past using appropriate decomposition methods. Such a reduction allows us to capture only the most significant spatio-temporal couplings. The functional form of the evolution operator includes separately linear, nonlinear (based on artificial neural networks) and stochastic terms. Explicit separation of the linear term from the nonlinear one allows us to more easily interpret degree of nonlinearity as well as to deal better with smooth PCs which can naturally occur in the decompositions like NDM, as they provide a time scale separation. Results of application of the proposed method to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Real-Time Climate Simulations in the Interactive 3D Game Universe Sandbox ²

NASA Astrophysics Data System (ADS)

Goldenson, N. L.

2014-12-01

Exploration in an open-ended computer game is an engaging way to explore climate and climate change. Everyone can explore physical models with real-time visualization in the educational simulator Universe Sandbox ² (universesandbox.com/2), which includes basic climate simulations on planets. I have implemented a time-dependent, one-dimensional meridional heat transport energy balance model to run and be adjustable in real time in the midst of a larger simulated system. Universe Sandbox ² is based on the original game - at its core a gravity simulator - with other new physically-based content for stellar evolution, and handling collisions between bodies. Existing users are mostly science enthusiasts in informal settings. We believe that this is the first climate simulation to be implemented in a professionally developed computer game with modern 3D graphical output in real time. The type of simple climate model we've adopted helps us depict the seasonal cycle and the more drastic changes that come from changing the orbit or other external forcings. Users can alter the climate as the simulation is running by altering the star(s) in the simulation, dragging to change orbits and obliquity, adjusting the climate simulation parameters directly or changing other properties like CO2 concentration that affect the model parameters in representative ways. Ongoing visuals of the expansion and contraction of sea ice and snow-cover respond to the temperature calculations, and make it accessible to explore a variety of scenarios and intuitive to understand the output. Variables like temperature can also be graphed in real time. We balance computational constraints with the ability to capture the physical phenomena we wish to visualize, giving everyone access to a simple open-ended meridional energy balance climate simulation to explore and experiment with. The software lends itself to labs at a variety of levels about climate concepts including seasons, the Greenhouse effect, reservoirs and flows, albedo feedback, Snowball Earth, climate sensitivity, and model experiment design. Climate calculations are extended to Mars with some modifications to the Earth climate component, and could be used in lessons about the Mars atmosphere, and exploring scenarios of Mars climate history.

Baby, it's cold outside: Climate model simulations of the effects of the asteroid impact at the end of the Cretaceous

NASA Astrophysics Data System (ADS)

Brugger, Julia; Feulner, Georg; Petri, Stefan

2017-01-01

Sixty-six million years ago, the end-Cretaceous mass extinction ended the reign of the dinosaurs. Flood basalt eruptions and an asteroid impact are widely discussed causes, yet their contributions remain debated. Modeling the environmental changes after the Chicxulub impact can shed light on this question. Existing studies, however, focused on the effect of dust or used one-dimensional, noncoupled atmosphere models. Here we explore the longer-lasting cooling due to sulfate aerosols using a coupled climate model. Depending on aerosol stratospheric residence time, global annual mean surface air temperature decreased by at least 26°C, with 3 to 16 years subfreezing temperatures and a recovery time larger than 30 years. The surface cooling triggered vigorous ocean mixing which could have resulted in a plankton bloom due to upwelling of nutrients. These dramatic environmental changes suggest a pivotal role of the impact in the end-Cretaceous extinction.

On the appropriate definition of soil profile configuration and initial conditions for land surface-hydrology models in cold regions

NASA Astrophysics Data System (ADS)

Sapriza-Azuri, Gonzalo; Gamazo, Pablo; Razavi, Saman; Wheater, Howard S.

2018-06-01

Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land surface models (LSMs) that represent the lower boundary condition of general circulation models (GCMs) and regional climate models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 m, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this gap, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian Land Surface Scheme), as embedded in the MESH (Modélisation Environmentale Communautaire - Surface and Hydrology) modelling system, to (1) characterize the effect of soil profile depth under different climate conditions and in the presence of parameter uncertainty; (2) assess the effect of including or excluding the geothermal flux in the LSM at the bottom of the soil column; and (3) develop a methodology for temperature profile initialization in permafrost regions, where the system has an extended memory, by the use of paleo-records and bootstrapping. Our study area is in Norman Wells, Northwest Territories of Canada, where measurements of soil temperature profiles and historical reconstructed climate data are available. Our results demonstrate a dominant role for parameter uncertainty, that is often neglected in LSMs. Considering such high sensitivity to parameter values and dependency on the climate condition, we show that a minimum depth of 20 m is essential to adequately represent the temperature dynamics. We further show that our proposed initialization procedure is effective and robust to uncertainty in paleo-climate reconstructions and that more than 300 years of reconstructed climate time series are needed for proper model initialization.

The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model

NASA Technical Reports Server (NTRS)

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.

Topographic signatures and a general transport law for deep-seated landslides in a landscape evolution model

NASA Astrophysics Data System (ADS)

Booth, Adam M.; Roering, Josh J.; Rempel, Alan W.

2013-06-01

A fundamental goal of studying earth surface processes is to disentangle the complex web of interactions among baselevel, tectonics, climate, and rock properties that generate characteristic landforms. Mechanistic geomorphic transport laws can quantitatively address this goal, but no widely accepted law for landslides exists. Here we propose a transport law for deep-seated landslides in weathered bedrock and demonstrate its utility using a two-dimensional numerical landscape evolution model informed by study areas in the Waipaoa catchment, New Zealand, and the Eel River catchment, California. We define a non-dimensional landslide number, which is the ratio of the horizontal landslide flux to the vertical tectonic flux, that characterizes three distinct landscape types. One is dominated by stochastic landsliding, whereby discrete landslide events episodically erode material at rates exceeding the long-term uplift rate. Another is characterized by steady landsliding, in which the landslide flux at any location remains constant through time and is greatest at the steepest locations in the catchment. The third is not significantly affected by landsliding. In both the "stochastic landsliding" and "steady landsliding" regimes, increases in the non-dimensional landslide number systematically reduce catchment relief and widen valley spacing, producing long, low angle hillslopes despite high uplift rates. The stochastic landsliding regime captures the frequent observation that deep-seated landslides produce large sediment fluxes from small areal extents while being active only a fraction of the time. We suggest that this model is adaptable to a wide range of geologic settings and is useful for interpreting climate-driven changes in landslide behavior.

Exploring the Causes of Mid-Holocene Drought in the Rocky Mountains Using Hydrologic Forward Models

NASA Astrophysics Data System (ADS)

Meador, E.; Morrill, C.

2017-12-01

We present a quantitative model-data comparison for mid-Holocene (6 ka) lake levels in the Rocky Mountains, with the goals of assessing the skill coupled climate models and hydrologic forward models in simulating climate change and improving our understanding of the factors causing past changes in water resources. The mid-Holocene climate in this area may in some ways be similar to expected future climate, thus improved understanding of the factors causing past changes in water resources have the potential to aid in the process of water allocation for large areas that share a relatively small water source. This project focuses on Little Windy Hill Pond in the Medicine Bow Forest in the Rocky Mountains in southern Wyoming. We first calibrated the Variable Infiltration Capacity (VIC) catchment hydrologic model and the one-dimensional Hostetler Bartlein lake energy-balance model to modern observations, using U.S. Geological Survey stream discharge data and Snow Telemetry (SNOTEL) data to ensure appropriate selection of model parameters. Once the models were calibrated to modern conditions, we forced them with output from eight mid-Holocene coupled climate model simulations completed as part of the Coupled Model Intercomparison Project, Phase 5. Forcing from nearly all of the CMIP5 models generates intense, short-lived droughts for the mid-Holocene that are more severe than any we modeled for the past six decades. The severity of the mid-Holocene droughts could be sufficient, depending on sediment processes in the lake, to account for low lake levels recorded by loss-on-ignition in sediment cores. Our preliminary analysis of model output indicates that the combined effects of decreased snowmelt runoff and increased summer lake evaporation cause low mid-Holocene lake levels. These factors are also expected to be important in the future under anthropogenic climate change.

A Dynamical Downscaling study over the Great Lakes Region Using WRF-Lake: Historical Simulation

NASA Astrophysics Data System (ADS)

Xiao, C.; Lofgren, B. M.

2014-12-01

As the largest group of fresh water bodies on Earth, the Laurentian Great Lakes have significant influence on local and regional weather and climate through their unique physical features compared with the surrounding land. Due to the limited spatial resolution and computational efficiency of general circulation models (GCMs), the Great Lakes are geometrically ignored or idealized into several grid cells in GCMs. Thus, the nested regional climate modeling (RCM) technique, known as dynamical downscaling, serves as a feasible solution to fill the gap. The latest Weather Research and Forecasting model (WRF) is employed to dynamically downscale the historical simulation produced by the Geophysical Fluid Dynamics Laboratory-Coupled Model (GFDL-CM3) from 1970-2005. An updated lake scheme originated from the Community Land Model is implemented in the latest WRF version 3.6. It is a one-dimensional mass and energy balance scheme with 20-25 model layers, including up to 5 snow layers on the lake ice, 10 water layers, and 10 soil layers on the lake bottom. The lake scheme is used with actual lake points and lake depth. The preliminary results show that WRF-Lake model, with a fine horizontal resolution and realistic lake representation, provides significantly improved hydroclimates, in terms of lake surface temperature, annual cycle of precipitation, ice content, and lake-effect snowfall. Those improvements suggest that better resolution of the lakes and the mesoscale process of lake-atmosphere interaction are crucial to understanding the climate and climate change in the Great Lakes region.

Assessing organizational climate: psychometric properties of the CLIOR Scale.

PubMed

Peña-Suárez, Elsa; Muñiz, José; Campillo-Álvarez, Angela; Fonseca-Pedrero, Eduardo; García-Cueto, Eduardo

2013-02-01

Organizational climate is the set of perceptions shared by workers who occupy the same workplace. The main goal of this study is to develop a new organizational climate scale and to determine its psychometric properties. The sample consisted of 3,163 Health Service workers. A total of 88.7% of participants worked in hospitals, and 11.3% in primary care; 80% were women and 20% men, with a mean age of 51.9 years (SD= 6.28). The proposed scale consists of 50 Likert-type items, with an alpha coefficient of 0.97, and an essentially one-dimensional structure. The discrimination indexes of the items are greater than 0.40, and the items show no differential item functioning in relation to participants' sex. A short version of the scale was developed, made up of 15 items, with discrimination indexes higher than 0.40, an alpha coefficient of 0.94, and its structure was clearly one-dimensional. These results indicate that the new scale has adequate psychometric properties, allowing a reliable and valid assessment of organizational climate.

An investigation of the Archean climate using the NCAR CCm

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

Jenkins, G.S.

1991-01-01

The Archean (2.5 to 3.8 billion years ago) is of interest climatically, because of the 'Faint-Young Sun Paradox', which can be characterized by the Sun's reduced energy output. This lower energy output leads to a frozen planet if the climate existed as it does today. But, the geologic record shows that water was flowing at the earth's surface 3.8 billion years ago. Energy Balance Models (EBMs) and one-dimensional radiative-convective (1DRC) models predict a frozen planet for this time period, unless large carbon dioxide (CO2) concentrations exist in the Archean atmosphere. The goal is to explore the Archean climate with themore » National Center for Atmospheric Research (NCAR), Community Climate Model (CCM). The search for negative feedbacks to explain the 'Faint-Young Sun Paradox' is the thrust of this study. This study undertakes a series of sensitivity simulations which first explores individual factors that may be important for the Archean. They include rotation rate, lower solar luminosity, and land fraction. Then, these climatic factors along with higher CO2 concentrations are combined into a set of experiments. A faster rotation rate may have existed in the Archean. The faster rotation rate simulations show warmer globally averaged surface temperatures that are caused by a 20 percent decrease in the total cloud fraction. The smaller cloud fraction is brought about by dynamical changes. A global ocean is a possibility for the Archean. A global ocean simulation predicts 4 K increase in global mean surface temperatures compared to the present-day climate control.« less

The satellite power system - Assessment of the environmental impact on middle atmosphere composition and on climate

NASA Technical Reports Server (NTRS)

Whitten, R. C.; Borucki, W. J.; Park, C.; Pfister, L.; Woodward, H. T.; Turco, R. P.; Capone, L. A.; Riegel, C. A.; Kropp, T.

1982-01-01

Numerical models were developed to calculate the total deposition of watervapor, hydrogen, CO2, CO, SO2, and NO in the middle atmosphere from operation of heavy lift launch vehicles (HLLV) used to build a satellite solar power system (SPS). The effects of the contaminants were examined for their effects on the upper atmosphere. One- and two-dimensional models were formulated for the photochemistry of the upper atmosphere and for rocket plumes and reentry. An SPS scenario of 400 launches per year for 10 yr was considered. The build-up of the contaminants in the atmosphere was projected to have no significant effects, even at the launch latitude. Neither would there by any dangerous ozone depletion. It was found that H, OH, and HO2 species would double in the thermosphere. No measurable changes in climate were foreseen.

Severe environmental effects of Chicxulub impact imply key role in end-Cretaceous mass extinction

NASA Astrophysics Data System (ADS)

Brugger, Julia; Feulner, Georg; Petri, Stefan

2017-04-01

66 million years ago, during the most recent of the five severe mass extinctions in Earth's history, non-avian dinosaurs and many other organisms became extinct. The cause of this end-Cretaceous mass extinction is seen in either flood-basalt eruptions or an asteroid impact. Modeling the climatic changes after the Chicxulub asteroid impact allow to assess its contribution to the extinction event and to analyze the short-term and long-term response of the climate and the biosphere to the impact. Existing studies either investigated the effect of dust, which is now believed to play a minor role, or used one-dimensional, non-coupled models. In contrast, we use a coupled climate model to explore the longer lasting cooling due to sulfate aerosols. Based on data from geophysical impact modeling, we set up simulations with different stratospheric residence times for sulfate aerosols. Depending on this residence time, global surface air temperature decreased by at least 26°C, with 3 to 16 years subfreezing temperatures and a recovery time larger than 30 years. Vigorous ocean mixing, caused by the fast cooling of the surface ocean, might have perturbed marine ecosystems by the upwelling of nutrients. The dramatic climatic changes seen in our simulations imply severe environmental effects and therefore a significant contribution of the impact in the end-Cretaceous mass extinction.

Geoarchaeology, the four dimensional (4D) fluvial matrix and climatic causality

NASA Astrophysics Data System (ADS)

Brown, A. G.

2008-10-01

Geoarchaeology is the application of geological and geomorphological techniques to archaeology and the study of the interactions of hominins with the natural environment at a variety of temporal and spatial scales. Geoarchaeology in the UK over the last twenty years has flourished largely because it has gone beyond technological and scientific applications. Over the same period our ability to reconstruct the 3-dimensional stratigraphy of fluvial deposits and the matrix of fluvial sites has increased dramatically because of a number of technological advances. These have included the use of LiDAR (laser imaging) and radar to produce high-resolution digital surface models, the use of geophysics, particularly ground penetrating radar and electrical resistivity, to produce sediment depth models, and the use of GIS and data visualisation techniques to manipulate and display the data. These techniques along with more systematic and detailed sedimentological recording of exposed sections have allowed the construction of more precise 3-dimensional (volumetric) models of the matrix of artefacts within fluvial deposits. Additionally a revolution in dating techniques, particularly direct sediment dating by luminescence methods, has enabled the creation of 4-dimensional models of the creation and preservation of these sites. These 4-dimensional models have the ability to provide far more information about the processes of site creation, preservation and even destruction, and also allow the integration of these processes with independent data sources concerning cultural evolution and climatic change. All improvements in the precision of dating fluvial deposits have archaeological importance in our need to translate events from a sequential or geological timeframe to human timescales. This allows geoarchaeology to make a more direct contribution to cultural history through the recognition of agency at the individual or group level. This data can then form a component of biocomplexity or agent-based modelling which is becoming increasingly used in the natural sciences, particularly ecology and geomorphology and which can be used to test scenarios including the impact on, and response of, hominins to abrupt or catastrophic environmental change. Whilst catastrophic events clearly represent the atypical they can be illuminating in revealing cognitive processes resulting in abandonment, coping, mitigation and innovation. These points are exemplified using two in-depth case studies: one from the Holocene geoarchaeological record of the River Trent in Central England and the other from the Palaeolithic record from rivers in South West Britain. In the former the interaction between climate change and human activity is illustrated at the year to century timescale whilst in the other the timescale is millennial. These case studies have deliberately been chosen to be as different as possible in temporal and spatial scale with the aim of examining the applicability of methodological and theoretical aspects of geoarchaeology. Lastly the paper considers the problem of scale in geoarchaeology and concludes it is process-dependency, which ultimately affects the questions we can ask, and that questions of human response to climate change are fundamentally a product of materiality and cognitive processes. This demands an in-depth contextual approach to such questions rather than database-driven assertions of causality.

Modeling approaches to describe H2O and CO2 exchange in mare ecosystems

NASA Astrophysics Data System (ADS)

Olchev, A.; Novenko, E.; Volkova, E.

2012-04-01

The modern climatic conditions is strongly influenced by both internal variability of climatic system, and various external natural and anthropogenic factors (IPCC 2007). Significant increase of concentration of greenhouse gases in the atmosphere and especially the growth of atmospheric CO2 due to human activity are considered as the main factors that are responsible for global warming and climate changes. A significant part of anthropogenic CO2 is absorbed from the atmosphere by land biota and especially by vegetation cover. However, it is still not completely clear what is the role of different land ecosystems and especially forests and mares in global cycles of H2O and CO2 and what is a sensitivity of these ecosystems to climate changes. Within the frameworks of this study the spatial and temporal variability of H2O and CO2 fluxes in different types of mare ecosystems of the forest-steppe zone in European part of Russia was described using modeling approaches and results of field measurements. For this modeling and experimental study the mare ecosystems of Tula region were selected. The Tula region is located mostly in the forest-steppe zone and it is unique area for such studies because almost all existed types of mare ecosystems of Northern Eurasia distinguished by a geomorphological position, water and mineral supply can be found there. Most mares in Tula region have a relatively small size and surrounded by very heterogeneous forests that make not possible an application of the classical measuring and modeling approaches e.g. an eddy covariance technique or one-dimensional H2O and CO2 exchange models for flux estimation in such sites. In our study to describe the radiation, sensible heat, H2O and CO2 exchange between such heterogeneous mare ecosystems and the atmosphere a three-dimensional model Forbog-3D and one-dimensional Mixfor-SVAT were applied. The main concept used in the Forbog-3D and Mixfor-SVAT models is an aggregated description of physical and biological processes at various hierarchical levels of forest and mire ecosystems: from a single leaf to a tree and an entire ecosystem. The models consist of the several closely coupled sub-models describing: transfer of direct and diffuse solar radiation; turbulent exchange of sensible heat, H2O and CO2 within and above a vegetation cover; transpiration, photosynthesis and respiration of vegetation and soil; heat and moisture transfer in different soil layers. The models were validated and applied to describe the H2O and CO2 exchange processes in various mare ecosystems with different relief position, type of water and mineral supply as well as vegetation composition. Selected mares are located in different parts of the Tula region (both in forest and forest-steppe zones) and characterized by different microclimatic conditions. The study was supported by grants (11-04-97538-r_center_a, 11-04-01622-a and 11-05-00557-a) of the Russian Foundation for Basic Research (RFBR) and by grant of Government of Russian Federation N 11.G34.31.0079.

Assessing the impact of sea level rise due to climate change on seawater intrusion in Mekong Delta, Vietnam.

PubMed

Vu, D T; Yamada, T; Ishidaira, H

2018-03-01

In the context of climate change, salinity intrusion into rivers has been, and will be, one of the most important issues for coastal water resources management. A combination of changes, including increased temperature, change in regional rainfall, especially sea level rise (SLR) related to climate change, will have significant impacts on this phenomenon. This paper presents the outcomes of a study conducted in the Mekong Delta of Vietnam (MKD) for evaluating the effect of sea water intrusion under a new SLR scenario. Salinity intrusion was simulated by one-dimensional (1D) modeling. The relative sea level projection was constructed corresponding to the RCP 6.0 emission scenario for MKD based on the statistical downscaling method. The sea level in 2050 is projected to increase from 25 cm to 30 cm compared to the baseline period (in 2000). Furthermore, the simulated results suggested that salinity greater than 4 g/l, which affects rice yield, will intrude up to 50-60 km into the river. Approximately 30,000 ha of agricultural area will be affected if the sea level rise is 30 cm.

Topographic evolution of orogens: The long term perspective

NASA Astrophysics Data System (ADS)

Robl, Jörg; Hergarten, Stefan; Prasicek, Günther

2017-04-01

The landscape of mountain ranges reflects the competition of tectonics and climate, that build up and destroy topography, respectively. While there is a broad consensus on the acting processes, there is a vital debate whether the topography of individual orogens reflects stages of growth, steady-state or decay. This debate is fuelled by the million-year time scales hampering direct observations on landscape evolution in mountain ranges, the superposition of various process patterns and the complex interactions among different processes. In this presentation we focus on orogen-scale landscape evolution based on time-dependent numerical models and explore model time series to constrain the development of mountain range topography during an orogenic cycle. The erosional long term response of rivers and hillslopes to uplift can be mathematically formalised by the stream power and mass diffusion equations, respectively, which enables us to describe the time-dependent evolution of topography in orogens. Based on a simple one-dimensional model consisting of two rivers separated by a watershed we explain the influence of uplift rate and rock erodibility on steady-state channel profiles and show the time-dependent development of the channel - drainage divide system. The effect of dynamic drainage network reorganization adds additional complexity and its effect on topography is explored on the basis of two-dimensional models. Further complexity is introduced by coupling a mechanical model (thin viscous sheet approach) describing continental collision, crustal thickening and topography formation with a stream power-based landscape evolution model. Model time series show the impact of crustal deformation on drainage networks and consequently on the evolution of mountain range topography (Robl et al., in review). All model outcomes, from simple one-dimensional to coupled two dimensional models are presented as movies featuring a high spatial and temporal resolution. Robl, J., S. Hergarten, and G. Prasicek (in review), The topographic state of mountain ranges, Earth Science Reviews.

Climate models with delay differential equations

NASA Astrophysics Data System (ADS)

Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M.

2017-11-01

A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

Climate models with delay differential equations.

PubMed

Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M

2017-11-01

A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

Aerosol Retrievals Using Channel 1 and 2 AVHRR Data

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.

1999-01-01

The effect of tropospheric aerosols on global climate via the direct and indirect radiative forcings is one of the largest remaining uncertainties in climate change studies. Current assessments of the direct aerosol radiative effect mainly focus on sulfate aerosols. It has become clear, however, that other aerosol types like soil dust and smoke from biomass burning are also likely to be important climate forcing factors. The magnitude and even the sign of the climate forcing caused by these aerosol types is still unknown. General circulation models (GCMs) can be used to estimate the climatic effect of the direct radiative forcing by tropospheric and stratospheric aerosols. Aerosol optical properties are already parameterized in the Goddard Institute for Space Studies GCM. Once the global distribution of aerosol properties (optical thickness, size distribution, and chemical composition) is available, the calculation of the direct aerosol forcing is rather straighfforward. However, estimates of the indirect aerosol effect require additional knowledge of the physics and chemistry of aerosol-cloud interactions which are still poorly understood. One of the main objectives of the Global Aerosol Climatology Project, established in 1998 as a joint initiative of NASA's Radiation Science Program and GEWEX, is to infer the global distribution of aerosols, their properties, and their seasonal and interannual variations for the full period of available satellite data. This will be accomplished primarily through a systematic application of multichannel aerosol retrieval algorithms to existing satellite data and advanced 3-dimensional aerosol chemistry/transport models. In this paper we outline the methodology of analyzing channel 1 and 2 AVHRR radiance data over the oceans and describe preliminary retrieval results.

Impacts of Climate Change on Stream Temperatures in the Clearwater River, Idaho

NASA Astrophysics Data System (ADS)

Yearsley, J. R.; Chegwidden, O.; Nijssen, B.

2016-12-01

Dworshak Dam in northern Idaho impounds the waters of the North Fork of the Clearwater River, creating a reservoir of approximately 4.278 km3 at full pool elevation. The dam's primary purpose is for flood control and hydroelectric power generation. It also provides important water quality benefits by releasing cold water into the Clearwater River during the summer when conditions become critical for migrating endangered species of salmon. Changes in the climate may have an impact on the ability of Dworshak Dam and Reservoir to provide these benefits. To investigate the potential for extreme outcomes that would limit cold water releases from Dworshak Reservoir and compromise the fishery, we implemented a system of hydrologic and water temperature models that simulate daily-averaged water temperatures in both the riverine and reservoir environments. We used the macroscale hydrologic model, VIC, to simulate land surface water and energy fluxes, the one-dimensional, time-dependent stream temperature model, RBM, to simulate river temperatures and a modified version of CEQUAL-W2 to simulate water temperatures in Dworshak Reservoir. A long-term hydrologically based gridded data set of meteorological forcing provided the input for comparing model results with available observations of flow and water temperature. For purposes of investigating the impacts of climate change, we used the results from ten of the most recent Climate Model Intercomparison Project (CMIP5) climate change models scenarios in conjunction with the estimates of anthropogenic inputs of climate change gases from two representative concentration pathways (RCP). We compared the simulated results associated with a range of outcomes at critical river locations from the climate scenarios with existing conditions assuming that the reservoir would be operated under a rule curve based on the average reservoir elevation for the period 2006-2015 rule curve and for power demands represented by that same period.

A Synergistic Approach to Interpreting Planetary Atmospheres

NASA Astrophysics Data System (ADS)

Batalha, Natasha E.

We will soon have the technological capability to measure the atmospheric composition of temperate Earth-sized planets orbiting nearby stars. Interpreting these atmospheric signals poses a new challenge to planetary science. In contrast to jovian-like atmospheres, whose bulk compositions consist of hydrogen and helium, terrestrial planet atmospheres are likely comprised of high mean molecular weight secondary atmospheres, which have gone through a high degree of evolution. For example, present-day Mars has a frozen surface with a thin tenuous atmosphere, but 4 billion years ago it may have been warmed by a thick greenhouse atmosphere. Several processes contribute to a planet's atmospheric evolution: stellar evolution, geological processes, atmospheric escape, biology, etc. Each of these individual processes affects the planetary system as a whole and therefore they all must be considered in the modeling of terrestrial planets. In order to demonstrate the intricacies in modeling terrestrial planets, I use early Mars as a case study. I leverage a combination of one-dimensional climate, photochemical and energy balance models in order to create one self-consistent model that closely matches currently available climate data. One-dimensional models can address several processes: the influence of greenhouse gases on heating, the effect of the planet's geological processes (i.e. volcanoes and the carbonatesilicate cycle) on the atmosphere, the effect of rainfall on atmospheric composition and the stellar irradiance. After demonstrating the number of assumptions required to build a model, I look towards what exactly we can learn from remote observations of temperate Earths and Super Earths. However, unlike in-situ observations from our own solar system, remote sensing techniques need to be developed and understood in order to accurately characterize exo-atmospheres. I describe the models used to create synthetic transit transmission observations, which includes models of transit spectroscopy and instrumental noise. Using these, I lay the framework for an information content-based approach to optimize our observations and maximize the retrievable information from exoatmospheres. First I test the method on observing strategies of the well-studied, low-mean-molecular weight atmospheres of warm-Neptunes and hot Jupiters. Upon verifying the methodology, I finally address optimal observing strategies for temperate, high-mean-molecular weight atmospheres (Earths/super-Earths). iv.

A Comparison of One-Dimensional Hydrologic Models Using Soil Moisture Observations under Urban Irrigation in a Desert Climate

NASA Astrophysics Data System (ADS)

Volo, T. J.; Vivoni, E. R.; Martin, C. A.; Wang, Z.; Ruddell, B.

2012-12-01

Through the past several decades, rapid population growth in the arid American Southwest has dramatically changed patterns of plant-available water through municipal and residential irrigation systems that provide supplemental water to designed and managed urban landscape vegetation. Urban irrigation, including diversion of rainwater and addition of imported water, has thereby enabled the transformation of areas once covered by bare soil and low water-use, native desert plant species to large tracts of exotic, high water-use turf grass and shade trees. Despite the large percentage of residential water appropriated to irrigation purposes, models of urban hydrology often fail to include the impact that this anthropogenic input has on water, energy, and biomass conditions. This study utilizes two one-dimensional soil moisture models to examine the importance of representing different processes in a quantitative urban ecohydrology model under irrigation scenarios. Such processes include sub-daily energy fluxes, vertical redistribution of soil moisture, saturation- and infiltration-excess runoff mechanisms, seasonally variable irrigation scheduling, and soil moisture control on evapotranspiration rates. The analysis is informed by soil moisture observations from an experimental sensor network in the Phoenix, Arizona metropolitan area. The network includes data from several different landscape and irrigation treatments representative of pre- and post-development conditions in the region. By interpreting soil moisture levels in terms of plant water stress, this study analyzes the effectiveness of urban irrigation practices in arid climates. Furthermore, by identifying the necessary hydrologic processes to represent in an urban ecohydrology model, our results inform future work in adapting a distributed hydrologic model to desert urban settings where irrigation plays a significant role in minimizing plant water stress. An appropriate model of water and energy balances, calibrated using local meteorological forcing, can facilitate discussions with water managers and homeowners regarding optimal irrigation frequency, volume, duration, and seasonality for individual landscapes, while also aiding in water-efficient landscape design for growing cities in desert regions.

Modeling glacial climates

NASA Technical Reports Server (NTRS)

North, G. R.; Crowley, T. J.

1984-01-01

Mathematical climate modelling has matured as a discipline to the point that it is useful in paleoclimatology. As an example a new two dimensional energy balance model is described and applied to several problems of current interest. The model includes the seasonal cycle and the detailed land-sea geographical distribution. By examining the changes in the seasonal cycle when external perturbations are forced upon the climate system it is possible to construct hypotheses about the origin of midlatitude ice sheets and polar ice caps. In particular the model predicts a rather sudden potential for glaciation over large areas when the Earth's orbital elements are only slightly altered. Similarly, the drift of continents or the change of atmospheric carbon dioxide over geological time induces radical changes in continental ice cover. With the advance of computer technology and improved understanding of the individual components of the climate system, these ideas will be tested in far more realistic models in the near future.

Comparison of two-dimensional and quasi-one-dimensional scramjet models by the example of VAG experiment

NASA Astrophysics Data System (ADS)

Seleznev, R. K.

2017-02-01

In the paper two-dimensional and quasi-one dimensional models for scramjet combustion chamber are described. Comparison of the results of calculations for the two-dimensional and quasi-one dimensional code by the example of VAG experiment are presented.

Large-scale water resources management within the framework of GLOWA-Danube. Part A: The groundwater model

NASA Astrophysics Data System (ADS)

Barthel, Roland; Rojanschi, Vlad; Wolf, Jens; Braun, Juergen

The research project GLOWA-Danube, financed by the German Federal Government, is investigating long-term changes in the water cycle of the upper Danube river basin (77,000 km 2) in light of global climatic change. Its aim is to build a fully integrated decision-support tool “DANUBIA” that combines the competence of 11 different research institutes in domains covering all major aspects governing the water cycle-from the formation of clouds, to groundwater flow patterns, to the behaviour of the water consumer. Both the influence of natural changes in the ecosystem, such as climate change, and changes in human behaviour, such as changes in land use or water consumption, are considered. DANUBIA is comprised of 15 individual disciplinary models that are connected via customized interfaces that facilitate network-based parallel calculations. The strictly object-oriented DANUBIA architecture was developed using the graphical notation tool UML (Unified Modeling Language) and has been implemented in Java code. All models use the same spatial discretisation for the exchange of data (1 × 1 km grid cells) but are using different time steps. The representation of a vast number of relevant physical and social processes that occur at different spatial and temporal scales is a very demanding task. Newly developed up- and downscaling procedures [Rojanschi, V., 2001. Effects of upscaling for a finite-difference flow model. Master’s Thesis, Institut für Wasserbau, Universität Stuttgart, Stuttgart, Germany] and a sophisticated time controller developed by the computer sciences group [Hennicker, R., Barth, M., Kraus, A., Ludwig, M., 2002. DANUBIA: A Web-based modelling and decision support system for integrative global change research in the upper Danube basin. In: GSF (Ed.), GLOWA, German Program on Global Change in the Hydrological Cycle Status Report 2002. GSF, Munich, pp. 35-38; Kraus, A., Ludwig, M., 2003. GLOWA-Danube Papers Technical Release No. 002 (Danubia Framework), Software-Release No.: 0.9.2, Documentation Version: 0.10, Release Date: 27 March 2003] are required to solve the emerging problems. After a first successful public demonstration of the DANUBIA package (nine models) in May 2002 [Mauser, W., Stolz, R., Colgan, A., 2002. GLOWA-Danube: integrative techniques, scenarios and strategies regarding global change of the water cycle. In: GSF (Ed.), GLOWA, German Program on Global Change in the Hydrological Cycle (Phase I, 2000-2003) Status Report 2002. GSF, Munich, pp. 31-34], the research consortium is now preparing a first validation run of DANUBIA for the period 1995-1999 with all 15 models. After successful completion of the validation, a scenario run based on IPCC climate scenarios [IPCC, 2001. Climate Change 2001: Synthesis Report. In: Watson, R.T., Core Writing Team (Eds.), A Contribution of Working Groups I, II, and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USA, 398pp] for a five year period between 2025 and 2040 will follow at the end of 2003. The research group “Groundwater and Water Resources Management” at the Institute of Hydraulic Engineering, Universität Stuttgart, is contributing both a three-dimensional groundwater flow model of the catchment and an agent-based model for simulating water supply and distribution. This paper gives a general overview of the GLOWA-Danube project and describes the groundwater modeling segment. Nickel et al. deal with the water supply model in a second contribution to this special issue. A three-dimensional numerical groundwater flow model consisting of four main layers has been developed and is in a continual state of refinement (MODFLOW, [McDonald, M.G., Harbaugh, A.W., 1988. A modular three-dimensional finite-difference ground-water flow model: US Geological Survey Techniques of Water-Resources Investigations, Washington, USA (book 6, Chapter A1)]). One main research focus has been on the investigation of upscaling techniques to meet the requirement of a fixed 1 × 1 km cell size. This cell size is compulsory for all models in DANUBIA in order to facilitate a one to one parameter exchange. In a second stage, a transport model (nitrogen) will be added (MT3D: [Zheng, C., Hathaway, D.-L., 1991. MT3D: a new modular three-dimensional transport model and its application in predicting the persistence and transport of dissolved compounds from a gasoline spill, with implications for remediation. Association of Ground Water Scientists and Engineers Annual Meeting on Innovative Ground Water Technologies for the ’90s, National Ground Water Association, Westerville, Ohio, USA. Ground Water 29 (5)].

Multi-level emulation of complex climate model responses to boundary forcing data

NASA Astrophysics Data System (ADS)

Tran, Giang T.; Oliver, Kevin I. C.; Holden, Philip B.; Edwards, Neil R.; Sóbester, András; Challenor, Peter

2018-04-01

Climate model components involve both high-dimensional input and output fields. It is desirable to efficiently generate spatio-temporal outputs of these models for applications in integrated assessment modelling or to assess the statistical relationship between such sets of inputs and outputs, for example, uncertainty analysis. However, the need for efficiency often compromises the fidelity of output through the use of low complexity models. Here, we develop a technique which combines statistical emulation with a dimensionality reduction technique to emulate a wide range of outputs from an atmospheric general circulation model, PLASIM, as functions of the boundary forcing prescribed by the ocean component of a lower complexity climate model, GENIE-1. Although accurate and detailed spatial information on atmospheric variables such as precipitation and wind speed is well beyond the capability of GENIE-1's energy-moisture balance model of the atmosphere, this study demonstrates that the output of this model is useful in predicting PLASIM's spatio-temporal fields through multi-level emulation. Meaningful information from the fast model, GENIE-1 was extracted by utilising the correlation between variables of the same type in the two models and between variables of different types in PLASIM. We present here the construction and validation of several PLASIM variable emulators and discuss their potential use in developing a hybrid model with statistical components.

Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

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

Zabaras, Nicolas J.

2016-11-08

Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

Advantages of 3D FEM numerical modeling over 2D, analyzed in a case study of transient thermal-hydraulic groundwater utilization

NASA Astrophysics Data System (ADS)

Fuchsluger, Martin; Götzl, Gregor

2014-05-01

In general most aquifers have a much larger lateral extent than vertical. This fact leads to the application of the Dupuit-Forchheimer assumptions to many groundwater problems, whereas a two dimensional simulation is considered sufficient. By coupling transient fluid flow modeling with heat transport the 2D aquifer approximation is in many cases insufficient as it does not consider effects of the subjacent and overlying aquitards on heat propagation as well as the impact of surface climatic effects on shallow aquifers. A shallow Holocene aquifer in Vienna served as a case study to compare different modeling approaches in two and three dimensions in order to predict the performance and impact of a thermal aquifer utilization for heating (1.3 GWh) and cooling (1.4 GWh) of a communal building. With the assumption of a 6 doublets well field, the comparison was realized in three steps: At first a two dimensional model for unconfined flow was set up, assuming a varying hydraulic conductivity as well as a varying top and bottom elevation of the aquifer (gross - thickness). The model area was chosen along constant hydraulic head at steady state conditions. A second model was made by mapping solely the aquifer in three dimensions using the same subdomain and boundary conditions as defined in step one. The third model consists of a complete three dimensional geological build-up including the aquifer as well as the overlying and subjacent layers and additionally an annually variable climatic boundary condition at the surface. The latter was calibrated with measured water temperature at a nearby water gauge. For all three models the same annual operating mode of the 6 hydraulic doublets was assumed. Furthermore a limited maximal groundwater temperature at a range between 8 and 18 °C as well as a constrained well flow rate has been given. Finally a descriptive comparison of the three models concerning the extracted thermal power, drawdown, temperature distribution and Darcy flow has been realized. In addition the effects of the basement of the building to the groundwater flow have been analyzed. The results of the 2D model show an underestimation of more than 10 % of the performance of the groundwater utilization facility and a considerable smaller groundwater table drawdown compared to the 3D simulations. This is due to the possibility of 3D modeling to consider (i) the heat distribution and storage in the adjacent layers, (ii) the climatic surface effect and (iii) vertical groundwater flow.

a Novel Methodology for Developing Inundation Maps Under Climate Change Scenarios Using One-Dimensional Model

NASA Astrophysics Data System (ADS)

Vu, M. T.; Liong, S. Y.; Raghavan, V. S.; Liew, S. C.

2011-07-01

Climate change is expected to cause increases in extreme climatic events such as heavy rainstorms and rising tidal level. Heavy rainstorms are known to be serious causes of flooding problems in big cities. Thus, high density residential and commercial areas along the rivers are facing risks of being flooded. For that reason, inundated area determination is now being considered as one of the most important areas of research focus in flood forecasting. In such a context, this paper presents the development of a floodmap in determining flood-prone areas and its volumes. The areas and volumes of flood are computed by the inundated level using the existing digital elevation model (DEM) of a hypothetical catchment chosen for study. The study focuses on the application of Flood Early Warning System (Delft — FEWS, Deltares), which is designated to work with the SOBEK (Delft) to simulate the extent of stormwater on the ground surface. The results from FEWS consist of time-series of inundation maps in Image file format (PNG) and ASCII format, which are subsequently imported to ArcGIS for further calculations. In addition, FEWS results provide options to export the video clip of water spreading out over the catchment. Consequently, inundated area and volume will be determined by the water level on the ground. Final floodmap is displayed in colors created by ArcGIS. Various flood map results corresponding to climate change scenarios will be displayed in the main part of the paper.

Investigation of the effects of the macrophysical and microphysical properties of cirrus clouds on the retrieval of optical properties: Results for FIRE 2

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Stephens, Graeme L.

1993-01-01

Due to the prevalence and persistence of cirrus cloudiness across the globe, cirrus clouds are believed to have an important effect on the climate. Stephens et al., (1990) among others have shown that the important factor determining how cirrus clouds modulate the climate is the balance between the albedo and emittance effect of the cloud systems. This factor was shown to depend in part upon the effective sizes of the cirrus cloud particles. Since effective sizes of cirrus cloud microphysical distributions are used as a basis of parameterizations in climate models, it is crucial that the relationships between effective sizes and radiative properties be clearly established. In this preliminary study, the retrieval of cirrus cloud effective sizes are examined using a two dimensional radiative transfer model for a cirrus cloud case sampled during FIRE Cirrus 11. The purpose of this paper is to present preliminary results from the SHSG model demonstrating the sensitivity of the bispectral relationships of reflected radiances and thus the retrieval of effective sizes to phase function and dimensionality.

Exploring load, velocity, and surface disorder dependence of friction with one-dimensional and two-dimensional models.

PubMed

Dagdeviren, Omur E

2018-08-03

The effect of surface disorder, load, and velocity on friction between a single asperity contact and a model surface is explored with one-dimensional and two-dimensional Prandtl-Tomlinson (PT) models. We show that there are fundamental physical differences between the predictions of one-dimensional and two-dimensional models. The one-dimensional model estimates a monotonic increase in friction and energy dissipation with load, velocity, and surface disorder. However, a two-dimensional PT model, which is expected to approximate a tip-sample system more realistically, reveals a non-monotonic trend, i.e. friction is inert to surface disorder and roughness in wearless friction regime. The two-dimensional model discloses that the surface disorder starts to dominate the friction and energy dissipation when the tip and the sample interact predominantly deep into the repulsive regime. Our numerical calculations address that tracking the minimum energy path and the slip-stick motion are two competing effects that determine the load, velocity, and surface disorder dependence of friction. In the two-dimensional model, the single asperity can follow the minimum energy path in wearless regime; however, with increasing load and sliding velocity, the slip-stick movement dominates the dynamic motion and results in an increase in friction by impeding tracing the minimum energy path. Contrary to the two-dimensional model, when the one-dimensional PT model is employed, the single asperity cannot escape to the minimum energy minimum due to constraint motion and reveals only a trivial dependence of friction on load, velocity, and surface disorder. Our computational analyses clarify the physical differences between the predictions of the one-dimensional and two-dimensional models and open new avenues for disordered surfaces for low energy dissipation applications in wearless friction regime.

[Review on HSPF model for simulation of hydrology and water quality processes].

PubMed

Li, Zhao-fu; Liu, Hong-Yu; Li, Yan

2012-07-01

Hydrological Simulation Program-FORTRAN (HSPF), written in FORTRAN, is one ol the best semi-distributed hydrology and water quality models, which was first developed based on the Stanford Watershed Model. Many studies on HSPF model application were conducted. It can represent the contributions of sediment, nutrients, pesticides, conservatives and fecal coliforms from agricultural areas, continuously simulate water quantity and quality processes, as well as the effects of climate change and land use change on water quantity and quality. HSPF consists of three basic application components: PERLND (Pervious Land Segment) IMPLND (Impervious Land Segment), and RCHRES (free-flowing reach or mixed reservoirs). In general, HSPF has extensive application in the modeling of hydrology or water quality processes and the analysis of climate change and land use change. However, it has limited use in China. The main problems with HSPF include: (1) some algorithms and procedures still need to revise, (2) due to the high standard for input data, the accuracy of the model is limited by spatial and attribute data, (3) the model is only applicable for the simulation of well-mixed rivers, reservoirs and one-dimensional water bodies, it must be integrated with other models to solve more complex problems. At present, studies on HSPF model development are still undergoing, such as revision of model platform, extension of model function, method development for model calibration, and analysis of parameter sensitivity. With the accumulation of basic data and imorovement of data sharing, the HSPF model will be applied more extensively in China.

Applicability of WRF-Lake System in Studying Reservoir-Induced Impacts on Local Climate: Case Study of Two Reservoirs with Contrasting Characteristics

NASA Astrophysics Data System (ADS)

Wang, F.; Zhu, D.; Ni, G.; Sun, T.

2017-12-01

Large reservoirs play a key role in regional hydrological cycles as well as in modulating the local climate. The emerging large reservoirs in concomitant with rapid hydropower exploitation in southwestern China warrant better understanding of their impacts on local and regional climates. One of the crucial pathways through which reservoirs impact the climate is lake-atmospheric interaction. Although such interactions have been widely studied with numeric weather prediction (NWP) models, an outstanding limitation across various NWPs resides on the poor thermodynamic representation of lakes. The recent version of Weather Research and Forecasting (WRF) system has been equipped with a one-dimensional lake model to better represent the thermodynamics of large water body and has been shown to enhance the its predication skill in the lake-atmospheric interaction. In this study, we further explore the applicability of the WRF-Lake system in two reservoirs with contrasting characteristics: Miyun Reservoir with an average depth of 30 meters in North China Plain, and Nuozhadu Reservoir with an average depth of 200 meters in the Tibetan Plateau Region. Driven by the high spatiotemporal resolution meteorological forcing data, the WRF-Lake system is used to simulate the water temperature and surface energy budgets of the two reservoirs after the evaluation against temperature observations. The simulated results show the WRF-Lake model can well predict the vertical profile of water temperature in Miyun Reservoir, but underestimates deep water temperature and overestimates surface temperature in the deeper Nuozhadu Reservoir. In addition, sensitivity analysis indicates the poor performance of the WRF-Lake system in Nuozhadu Reservoir could be attributed to the weak vertical mixing in the model, which can be improved by tuning the eddy diffusion coefficient ke . Keywords: reservoir-induced climatic impact; lake-atmospheric interaction; WRF-Lake system; hydropower exploitation

Simulating the carbon, water, energy budgets and greenhouse gas emissions of arctic soils with the ISBA land surface model

NASA Astrophysics Data System (ADS)

Morel, Xavier; Decharme, Bertrand; Delire, Christine

2017-04-01

Permafrost soils and boreal wetlands represent an important challenge for future climate simulations. Our aim is to be able to correctly represent the most important thermal, hydrologic and carbon cycle related processes in boreal areas with our land surface model ISBA (Masson et al, 2013). This is particularly important since ISBA is part of the CNRM-CM Climate Model (Voldoire et al, 2012), that is used for projections of future climate changes. To achieve this goal, we replaced the one layer original soil carbon module based on the CENTURY model (Parton et al, 1987) by a multi-layer soil carbon module that represents C pools and fluxes (CO2 and CH4), organic matter decomposition, gas diffusion (Khvorostyanov et al., 2008), CH4 ebullition and plant-mediated transport, and cryoturbation (Koven et al., 2009). The carbon budget of the new model is closed. The soil carbon module is tightly coupled to the ISBA energy and water budget module that solves the one-dimensional Fourier law and the mixed-form of the Richards equation explicitly to calculate the time evolution of the soil energy and water budgets (Boone et al., 2000; Decharme et al. 2011). The carbon, energy and water modules are solved using the same vertical discretization. Snowpack processes are represented by a multi-layer snow model (Decharme et al, 2016). We test this new model on a pair of monitoring sites in Greenland, one in a permafrost area (Zackenberg Ecological Research Operations, Jensen et al, 2014) and the other in a region without permafrost (Nuuk Ecological Research Operations, Jensen et al, 2013); both sites are established within the GeoBasis part of the Greenland Ecosystem Monitoring (GEM) program. The site of Chokurdakh, in a permafrost area of Siberia is is our third studied site. We test the model's ability to represent the physical variables (soil temperature and water profiles, snow height), the energy and water fluxes as well as the carbon dioxyde and methane fluxes. We also test the model behaviour in the case of a flooded fen, hence giving a first insight of the sensitivity of greenhouse gas emissions with respect to surface hydrology. Comparing the model results on these three climatically distinct sites also gives a first insight on the model sensitivity to the forcing climate variables, and show that the model is generic enough to reasonably model methane and carbon dioxyde emission behaviour from different types of boreal ecosystems.

Long-term simulations of dissolved oxygen concentrations in Lake Trout lakes

NASA Astrophysics Data System (ADS)

Jabbari, A.; Boegman, L.; MacKay, M.; Hadley, K.; Paterson, A.; Jeziorski, A.; Nelligan, C.; Smol, J. P.

2016-02-01

Lake Trout are a rare and valuable natural resource that are threatened by multiple environmental stressors. With the added threat of climate warming, there is growing concern among resource managers that increased thermal stratification will reduce the habitat quality of deep-water Lake Trout lakes through enhanced oxygen depletion. To address this issue, a three-part study is underway, which aims to: analyze sediment cores to understand the past, develop empirical formulae to model the present and apply computational models to forecast the future. This presentation reports on the computational modeling efforts. To this end, a simple dissolved oxygen sub-model has been embedded in the one-dimensional bulk mixed-layer thermodynamic Canadian Small Lake Model (CSLM). This model is currently being incorporated into the Canadian Land Surface Scheme (CLASS), the primary land surface component of Environment Canada's global and regional climate modelling systems. The oxygen model was calibrated and validated by hind-casting temperature and dissolved oxygen profiles from two Lake Trout lakes on the Canadian Shield. These data sets include 5 years of high-frequency (10 s to 10 min) data from Eagle Lake and 30 years of bi-weekly data from Harp Lake. Initial results show temperature and dissolved oxygen was predicted with root mean square error <1.5 °C and <3 mgL-1, respectively. Ongoing work is validating the model, over climate-change relevant timescales, against dissolved oxygen reconstructions from the sediment cores and predicting future deep-water temperature and dissolved oxygen concentrations in Canadian Lake Trout lakes under future climate change scenarios. This model will provide a useful tool for managers to ensure sustainable fishery resources for future generations.

Modeling of the Global Water Cycle - Analytical Models

Treesearch

Yongqiang Liu; Roni Avissar

2005-01-01

Both numerical and analytical models of coupled atmosphere and its underlying ground components (land, ocean, ice) are useful tools for modeling the global and regional water cycle. Unlike complex three-dimensional climate models, which need very large computing resources and involve a large number of complicated interactions often difficult to interpret, analytical...

The implementation and validation of improved land-surface hydrology in an atmospheric general circulation model

NASA Technical Reports Server (NTRS)

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.

Pinatubo Emulation in Multiple Models (POEMs): co-ordinated experiments in the ISA-MIP model intercomparison activity component of the SPARC Stratospheric Sulphur and it's Role in Climate initiative (SSiRC)

NASA Astrophysics Data System (ADS)

Lee, Lindsay; Mann, Graham; Carslaw, Ken; Toohey, Matthew; Aquila, Valentina

2016-04-01

The World Climate Research Program's SPARC initiative has a new international activity "Stratospheric Sulphur and its Role in Climate" (SSiRC) to better understand changes in stratospheric aerosol and precursor gaseous sulphur species. One component of SSiRC involves an intercomparison "ISA-MIP" of composition-climate models that simulate the stratospheric aerosol layer interactively. Within PoEMS each modelling group will run a "perturbed physics ensemble" (PPE) of interactive stratospheric aerosol (ISA) simulations of the Pinatubo eruption, varying several uncertain parameters associated with the eruption's SO2 emissions and model processes. A powerful new technique to quantify and attribute sources of uncertainty in complex global models is described by Lee et al. (2011, ACP). The analysis uses Gaussian emulation to derive a probability density function (pdf) of predicted quantities, essentially interpolating the PPE results in multi-dimensional parameter space. Once trained on the ensemble, a Monte Carlo simulation with the fast Gaussian emulator enabling a full variance-based sensitivity analysis. The approach has already been used effectively by Carslaw et al., (2013, Nature) to quantify the uncertainty in the cloud albedo effect forcing from a 3D global aerosol-microphysics model allowing to compare the sensitivy of different predicted quantities to uncertainties in natural and anthropogenic emissions types, and structural parameters in the models. Within ISA-MIP, each group will carry out a PPE of runs, with the subsequent analysis with the emulator assessing the uncertainty in the volcanic forcings predicted by each model. In this poster presentation we will give an outline of the "PoEMS" analysis, describing the uncertain parameters to be varied and the relevance to further understanding differences identified in previous international stratospheric aerosol assessments.

Modeling soil temperature change in Seward Peninsula, Alaska

NASA Astrophysics Data System (ADS)

Debolskiy, M. V.; Nicolsky, D.; Romanovsky, V. E.; Muskett, R. R.; Panda, S. K.

2017-12-01

Increasing demand for assessment of climate change-induced permafrost degradation and its consequences promotes creation of high-resolution modeling products of soil temperature changes. This is especially relevant for areas with highly vulnerable warm discontinuous permafrost in the Western Alaska. In this study, we apply ecotype-based modeling approach to simulate high-resolution permafrost distribution and its temporal dynamics in Seward Peninsula, Alaska. To model soil temperature dynamics, we use a transient soil heat transfer model developed at the Geophysical Institute Permafrost Laboratory (GIPL-2). The model solves one dimensional nonlinear heat equation with phase change. The developed model is forced with combination of historical climate and different future scenarios for 1900-2100 with 2x2 km resolution prepared by Scenarios Network for Alaska and Arctic Planning (2017). Vegetation, snow and soil properties are calibrated by ecotype and up-scaled by using Alaska Existing Vegetation Type map for Western Alaska (Flemming, 2015) with 30x30 m resolution provided by Geographic Information Network of Alaska (UAF). The calibrated ecotypes cover over 75% of the study area. We calibrate the model using a data assimilation technique utilizing available observations of air, surface and sub-surface temperatures and snow cover collected by various agencies and research groups (USGS, Geophysical Institute, USDA). The calibration approach takes into account a natural variability between stations in the same ecotype and finds an optimal set of model parameters (snow and soil properties) within the study area. This approach allows reduction in microscale heterogeneity and aggregated soil temperature data from shallow boreholes which is highly dependent on local conditions. As a result of this study we present a series of preliminary high resolution maps for the Seward Peninsula showing changes in the active layer depth and ground temperatures for the current climate and future climate change scenarios.

The evolution of extreme precipitations in high resolution scenarios over France

NASA Astrophysics Data System (ADS)

Colin, J.; Déqué, M.; Somot, S.

2009-09-01

Over the past years, improving the modelling of extreme events and their variability at climatic time scales has become one of the challenging issue raised in the regional climate research field. This study shows the results of a high resolution (12 km) scenario run over France with the limited area model (LAM) ALADIN-Climat, regarding the representation of extreme precipitations. The runs were conducted in the framework of the ANR-SCAMPEI national project on high resolution scenarios over French mountains. As a first step, we attempt to quantify one of the uncertainties implied by the use of LAM : the size of the area on which the model is run. In particular, we address the issue of whether a relatively small domain allows the model to create its small scale process. Indeed, high resolution scenarios cannot be run on large domains because of the computation time. Therefore one needs to answer this preliminary question before producing and analyzing such scenarios. To do so, we worked in the framework of a « big brother » experiment. We performed a 23-year long global simulation in present-day climate (1979-2001) with the ARPEGE-Climat GCM, at a resolution of approximately 50 km over Europe (stretched grid). This first simulation, named ARP50, constitutes the « big brother » reference of our experiment. It has been validated in comparison with the CRU climatology. Then we filtered the short waves (up to 200 km) from ARP50 in order to obtain the equivalent of coarse resolution lateral boundary conditions (LBC). We have carried out three ALADIN-Climat simulations at a 50 km resolution with these LBC, using different configurations of the model : * FRA50, run over a small domain (2000 x 2000 km, centered over France), * EUR50, run over a larger domain (5000 x 5000 km, centered over France as well), * EUR50-SN, run over the large domain (using spectral nudging). Considering the facts that ARPEGE-Climat and ALADIN-Climat models share the same physics and dynamics and that both regional and global simulations were run at the same resolution, ARP50 can be regarded as a reference with which FRA50, EUR50 and EUR50-SN should each be compared. After an analysis of the differences between the regional simulations and ARP50 in annual and seasonal mean, we focus on the representation of rainfall extremes comparing two dimensional fields of various index inspired from STARDEX and quantile-quantile plots. The results show a good agreement with the ARP50 reference for all three regional simulations and little differences are found between them. This result indicates that the use of small domains is not significantly detrimental to the modelling of extreme precipitation events. It also shows that the spectral nudging technique has no detrimental effect on the extreme precipitation. Therefore, high resolution scenarios performed on a relatively small domain such as the ones run for SCAMPEI, can be regarded as good tools to explore their possible evolution in the future climate. Preliminary results on the response of precipitation extremes over South-East France are given.

A New Time-varying Concept of Risk in a Changing Climate.

PubMed

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P

2016-10-20

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

Chemistry-Climate Models of the Stratosphere

NASA Technical Reports Server (NTRS)

Austin, J.; Shindell, D.; Bruehl, C.; Dameris, M.; Manzini, E.; Nagashima, T.; Newman, P.; Pawson, S.; Pitari, G.; Rozanov, E.;

Evaluating Transient Global and Regional Model Simulations: Bridging the Model/Observations Information Gap

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Karl, T. R.; Easterling, D. R.; Buja, L.; Stouffer, R.; Alpert, J.

2001-05-01

A major transition in our ability to evaluate transient Global Climate Model (GCM) simulations is occurring. Real-time and retrospective numerical weather prediction analysis, model runs, climate simulations and assessments are proliferating from a handful of national centers to dozens of groups across the world. It is clear that it is no longer sufficient for any one national center to develop its data services alone. The comparison of transient GCM results with the observational climate record is difficult for several reasons. One limitation is that the global distributions of a number of basic climate quantities, such as precipitation, are not well known. Similarly, observational limitations exist with model re-analysis data. Both the NCEP/NCAR, and the ECMWF, re-analysis eliminate the problems of changing analysis systems but observational data also contain time-dependant biases. These changes in input data are blended with the natural variability making estimates of true variability uncertain. The need for data homogeneity is critical to study questions related to the ability to evaluate simulation of past climate. One approach to correct for time-dependant biases and data sparse regions is the development and use of high quality 'reference' data sets. The primary U.S. National responsibility for the archive and service of weather and climate data rests with the National Climatic Data Center (NCDC). However, as supercomputers increase the temporal and spatial resolution of both Numerical Weather Prediction (NWP) and GCM models, the volume and varied formats of data presented for archive at NCDC, using current communications technologies and data management techniques is limiting the scientific access of these data. To address this ever expanding need for climate and NWP information, NCDC along with the National Center's for Environmental Prediction (NCEP) have initiated the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS is a collaboration between the Center for Ocean-Land-Atmosphere studies (COLA); the Geophysical Fluid Dynamics Laboratory (GFDL); the George Mason University (GMU); the National Center for Atmospheric Research (NCAR); the NCDC; NCEP; the Pacific Marine Environmental Laboratory (PMEL); and the University of Washington. The objective of the NOMADS is to preserve and provide retrospective access to GCM's and reference quality long-term observational and high volume three dimensional data as well as NCEP NWP models and re-start and re-analysis information. The creation of the NOMADS features a data distribution, format independent, methodology enabling scientific collaboration between researchers. The NOMADS configuration will allow a researcher to transparently browse, extract and intercompare retrospective observational and model data products from any of the participating centers. NOMADS will provide the ability to easily initialize and compare the results of ongoing climate model assessments and NWP output. Beyond the ingest and access capability soon to be implemented with NOMADS is the challenge of algorithm development for the inter-comparison of large-array data (e.g., satellite and radar) with surface, upper-air, and sub-surface ocean observational data. The implementation of NOMADS should foster the development of new quality control processes by taking advantage of distributed data access.

Development of thermal models of footwear using finite element analysis.

PubMed

Covill, D; Guan, Z W; Bailey, M; Raval, H

2011-03-01

Thermal comfort is increasingly becoming a crucial factor to be considered in footwear design. The climate inside a shoe is controlled by thermal and moisture conditions and is crucial to attain comfort. Research undertaken has shown that thermal conditions play a dominant role in shoe climate. Development of thermal models that are capable of predicting in-shoe temperature distributions is an effective way forward to undertake extensive parametric studies to assist optimized design. In this paper, two-dimensional and three-dimensional thermal models of in-shoe climate were developed using finite element analysis through commercial code Abaqus. The thermal material properties of the upper shoe, sole, and air were considered. Dry heat flux from the foot was calculated on the basis of typical blood flow in the arteries on the foot. Using the thermal models developed, in-shoe temperatures were predicted to cover various locations for controlled ambient temperatures of 15, 25, and 35 degrees C respectively. The predicted temperatures were compared with multipoint measured temperatures through microsensor technology. Reasonably good correlation was obtained, with averaged errors of 6, 2, and 1.5 per cent, based on the averaged in-shoe temperature for the above three ambient temperatures. The models can be further used to help design shoes with optimized thermal comfort.

A spectral nudging method for the ACCESS1.3 atmospheric model

NASA Astrophysics Data System (ADS)

Uhe, P.; Thatcher, M.

2015-06-01

A convolution-based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow for flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10-30 times compared with a version using a two-dimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge.

A spectral nudging method for the ACCESS1.3 atmospheric model

NASA Astrophysics Data System (ADS)

Uhe, P.; Thatcher, M.

2014-10-01

A convolution based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10 to 30 times compared with a version using a two-dimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge.

Three-dimensional nonhydrostatic simulations of summer thunderstorms in the humid subtropics versus High Plains

NASA Astrophysics Data System (ADS)

Lin, Hsin-mu; Wang, Pao K.; Schlesinger, Robert E.

2005-11-01

This article presents a detailed comparison of cloud microphysical evolution among six warm-season thunderstorm simulations using a time-dependent three-dimensional model WISCDYMM. The six thunderstorms chosen for this study consist of three apiece from two contrasting climate zones, the US High Plains (one supercell and two multicells) and the humid subtropics (two in Florida, US and one in Taipei, Taiwan, all multicells). The primary goal of this study is to investigate the differences among thunderstorms in different climate regimes in terms of their microphysical structures and how differently these structures evolve in time. A subtropical case is used as an example to illustrate the general contents of a simulated storm, and two examples of the simulated storms, one humid subtropical and one northern High Plains case, are used to describe in detail the microphysical histories. The simulation results are compared with the available observational data, and the agreement between the two is shown to be at least fairly close overall. The analysis, synthesis and implications of the simulation results are then presented. The microphysical histories of the six simulated storms in terms of the domain-integrated masses of all five hydrometeor classes (cloud water, cloud ice, rain, snow, graupel/hail), along with the individual sources (and sinks) of the three precipitating hydrometeor classes (rain, snow, graupel/hail) are analyzed in detail. These analyses encompass both the absolute magnitudes and their percentage contributions to the totals, for the condensate mass and their precipitation production (and depletion) rates, respectively. Comparisons between the hydrometeor mass partitionings for the High Plains versus subtropical thunderstorms show that, in a time-averaged sense, ice hydrometeors (cloud ice, snow, graupel/hail) account for ˜ 70-80% of the total hydrometeor mass for the High Plains storms but only ˜ 50% for the subtropical storms, after the systems have reached quasi-steady mature states. This demonstrates that ice processes are highly important even in thunderstorms occurring in warm climatic regimes. The dominant rain sources are two of the graupel/hail sinks, shedding and melting, in both High Plains and subtropical storms, while the main rain sinks are accretion by hail and evaporation. The dominant graupel/hail sources are accretion of rain, snow and cloud water, while its main sinks are shedding and melting. The dominant snow sources are the Bergeron-Findeisen process and accretion of cloud water, while the main sinks are accretion by graupel/hail and sublimation. However, the rankings of the leading production and depletion mechanisms differ somewhat in different storm cases, especially for graupel/hail. The model results indicate that the same hydrometeor types in the different climates have their favored microphysical sources and sinks. These findings not only prove that thunderstorm structure depends on local dynamic and thermodynamic atmospheric conditions that are generally climate-dependent, but also provide information about the partitioning of hydrometeors in the storms. Such information is potentially useful for convective parameterization in large-scale models.

Predicted aircraft effects on stratospheric ozone

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Wofsy, Steve; Kley, Dieter; Zhadin, Evgeny A.; Johnson, Colin; Weisenstein, Debra; Prather, Michael J.; Wuebbles, Donald J.

1991-01-01

The possibility that the current fleet of subsonic aircraft may already have caused detectable changes in both the troposphere and stratosphere has raised concerns about the impact of such operations on stratospheric ozone and climate. Recent interest in the operation of supersonic aircraft in the lower stratosphere has heightened such concerns. Previous assessments of impacts from proposed supersonic aircraft were based mostly on one-dimensional model results although a limited number of multidimensional models were used. In the past 15 years, our understanding of the processes that control the atmospheric concentrations of trace gases has changed dramatically. This better understanding was achieved through accumulation of kinetic data and field observations as well as development of new models. It would be beneficial to start examining the impact of subsonic aircraft to identify opportunities to study and validate the mechanisms that were proposed to explain the ozone responses. The two major concerns are the potential for a decrease in the column abundance of ozone leading to an increase in ultraviolet radiation at the ground, and redistribution of ozone in the lower stratosphere and upper troposphere leading to changes in the Earth's climate. Two-dimensional models were used extensively for ozone assessment studies, with a focus on responses to chlorine perturbations. There are problems specific to the aircraft issues that are not adequately addressed by the current models. This chapter reviews the current status of the research on aircraft impact on ozone with emphasis on immediate model improvements necessary for extending our understanding. The discussion will be limited to current and projected commercial aircraft that are equipped with air-breathing engines using conventional jet fuel. The impacts are discussed in terms of the anticipated fuel use at cruise altitude.

The effects of climate downscaling technique and observational data set on modeled ecological responses

Treesearch

Afshin Pourmokhtarian; Charles T. Driscoll; John L. Campbell; Katharine Hayhoe; Anne M. K. Stoner

2016-01-01

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training...

Minimizers with Bounded Action for the High-Dimensional Frenkel-Kontorova Model

NASA Astrophysics Data System (ADS)

Miao, Xue-Qing; Wang, Ya-Nan; Qin, Wen-Xin

In Aubry-Mather theory for monotone twist maps or for one-dimensional Frenkel-Kontorova (FK) model with nearest neighbor interactions, each global minimizer (minimal energy configuration) is naturally Birkhoff. However, this is not true for the one-dimensional FK model with non-nearest neighbor interactions or for the high-dimensional FK model. In this paper, we study the Birkhoff property of minimizers with bounded action for the high-dimensional FK model.

Data needs and data bases for climate studies

NASA Technical Reports Server (NTRS)

Matthews, Elaine

1986-01-01

Two complementary global digital data bases of vegetation and land use, compiled at 1 deg resolution from published sources for use in climate studies, are discussed. The data bases were implemented, in several individually tailored formulations, in a series of climate related applications including: land-surface prescriptions in three-dimensional general circulation models, global biogeochemical cycles (CO2, methane), critical-area mapping for satellite monitoring of land-cover change, and large-scale remote sensing of surface reflectance. The climate applications are discussed with reference to data needs, and data availability from traditional and remote sensing sources.

A climate model with cryodynamics and geodynamics

NASA Technical Reports Server (NTRS)

Ghil, M.; Le Treut, H.

1981-01-01

A simplified, zero-dimensional model of the climatic system is presented which attempts to incorporate mechanisms important on the time scale of glaciation cycles: 10,000 to 100,000 years. The ocean-atmosphere radiation balance, continental ice sheet plastic flow, and upper mantle viscous flow are taken into account, with stress on the interaction between the ice sheets and the upper mantle. The model exhibits free, self-sustained oscillations of an amplitude and period comparable to those found in the paleoclimatic record of glaciations, offering mild support for the idea that unforced oscillations can actually exist in the real climatic system itself. The careful study of the interplay between internal mechanisms and external forcing is held to represent an interesting challenge to the theory of ice ages.

Partial spline models for the inclusion of tropopause and frontal boundary information in otherwise smooth two- and three-dimensional objective analysis

NASA Technical Reports Server (NTRS)

Shiau, Jyh-Jen; Wahba, Grace; Johnson, Donald R.

1986-01-01

A new method, based on partial spline models, is developed for including specified discontinuities in otherwise smooth two- and three-dimensional objective analyses. The method is appropriate for including tropopause height information in two- and three-dimensinal temperature analyses, using the O'Sullivan-Wahba physical variational method for analysis of satellite radiance data, and may in principle be used in a combined variational analysis of observed, forecast, and climate information. A numerical method for its implementation is described and a prototype two-dimensional analysis based on simulated radiosonde and tropopause height data is shown. The method may also be appropriate for other geophysical problems, such as modeling the ocean thermocline, fronts, discontinuities, etc.

The Effect of Climate Change on Ozone Depletion through Changes in Stratospheric Water Vapour

NASA Technical Reports Server (NTRS)

Kirk-Davidoff, Daniel B.; Hintsa, Eric J.; Anderson, James G.; Keith, David W.

1999-01-01

Several studies have predicted substantial increases in Arctic ozone depletion due to the stratospheric cooling induced by increasing atmospheric CO2 concentrations. But climate change may additionally influence Arctic ozone depletion through changes in the water vapor cycle. Here we investigate this possibility by combining predictions of tropical tropopause temperatures from a general circulation model with results from a one-dimensional radiative convective model, recent progress in understanding the stratospheric water vapor budget, modelling of heterogeneous reaction rates and the results of a general circulation model on the radiative effect of increased water vapor. Whereas most of the stratosphere will cool as greenhouse-gas concentrations increase, the tropical tropopause may become warmer, resulting in an increase of the mean saturation mixing ratio of water vapor and hence an increased transport of water vapor from the troposphere to the stratosphere. Stratospheric water vapor concentration in the polar regions determines both the critical temperature below which heterogeneous reactions on cold aerosols become important (the mechanism driving enhanced ozone depletion) and the temperature of the Arctic vortex itself. Our results indicate that ozone loss in the later winter and spring Arctic vortex depends critically on water vapor variations which are forced by sea surface temperature changes in the tropics. This potentially important effect has not been taken into account in previous scenarios of Arctic ozone loss under climate change conditions.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

Using simple chaotic models to interpret climate under climate change: Implications for probabilistic climate prediction

NASA Astrophysics Data System (ADS)

Daron, Joseph

2010-05-01

Exploring the reliability of model based projections is an important pre-cursor to evaluating their societal relevance. In order to better inform decisions concerning adaptation (and mitigation) to climate change, we must investigate whether or not our models are capable of replicating the dynamic nature of the climate system. Whilst uncertainty is inherent within climate prediction, establishing and communicating what is plausible as opposed to what is likely is the first step to ensuring that climate sensitive systems are robust to climate change. Climate prediction centers are moving towards probabilistic projections of climate change at regional and local scales (Murphy et al., 2009). It is therefore important to understand what a probabilistic forecast means for a chaotic nonlinear dynamic system that is subject to changing forcings. It is in this context that we present the results of experiments using simple models that can be considered analogous to the more complex climate system, namely the Lorenz 1963 and Lorenz 1984 models (Lorenz, 1963; Lorenz, 1984). Whilst the search for a low-dimensional climate attractor remains illusive (Fraedrich, 1986; Sahay and Sreenivasan, 1996) the characterization of the climate system in such terms can be useful for conceptual and computational simplicity. Recognising that a change in climate is manifest in a change in the distribution of a particular climate variable (Stainforth et al., 2007), we first establish the equilibrium distributions of the Lorenz systems for certain parameter settings. Allowing the parameters to vary in time, we investigate the dependency of such distributions to initial conditions and discuss the implications for climate prediction. We argue that the role of chaos and nonlinear dynamic behaviour ought to have more prominence in the discussion of the forecasting capabilities in climate prediction. References: Fraedrich, K. Estimating the dimensions of weather and climate attractors. J. Atmos. Sci, 43, 419-432, 1986. Lorenz, E. N. Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130-141, 1963. Lorenz, E. N. Irregularity: a fundamental property of the atmosphere. Tellus, 36A, 98-110, 1984. Murphy, J. M., D. M. H. Sexton, G. J. Jenkins, B. B. B. Booth, C. C. Brown, R. T. Clark, M. Collins, G. R. Harris, E. J. Kendon, R. A. Betts, S. J. Brown, P. Boorman, T. P. Howard, K. A. Humphrey, M. P. McCarthy, R. E. McDonald, A. Stephens, C. Wallace, R. Warren, R. Wilby, and R. A. Wood. Uk climate projections science report: Climate change projections. 2009. Sahay, A. and K. R. Sreenivasan. The search for a low-dimensional characterization of a local climate system. Phil. Trans. R. Soc. A., 354, 1715-1750, 1996. Stainforth, D. A., M. R. Allen, E. R. Tredger, and L. A. Smith. Confidence, uncertainty and decision-support relevance in climate predictions. Phil. Trans. R. Soc. A, 365, 2145-2161, 2007.

Global off-line evaluation of the ISBA-TRIP continental hydrological system used in the CNRM-CM6 climate model for the next CMIP6 exercise

NASA Astrophysics Data System (ADS)

Decharme, Bertrand; Vergnes, Jean-Pierre; Minvielle, Marie; Colin, Jeanne; Delire, Christine

2016-04-01

The land surface hydrology represents an active component of the climate system. It is likely to influence the water and energy exchanges at the land surface, the ocean salinity and temperature at the mouth of the largest rivers, and the climate at least at the regional scale. In climate models, the continental hydrology is simulated via Land Surface Models (LSM), which compute water and energy budgets at the surface, coupled to River Routing Model (RRM), which convert the runoff simulated by the LSMs into river discharge in order to transfer the continental fresh water into the oceans and then to close the global hydrological cycle. Validating these Continental Hydrological Systems (CHS) at the global scale is therefore a crucial task, which requires off-line simulations driven by realistic atmospheric fluxes to avoid the systematic biases commonly found in the atmospheric models. In the CNRM-CM6 climate model of Météo-France, that will be used for the next Coupled Climate Intercomparison Project phase 6 (CMIP6) exercise, the land surface hydrology is simulated using the ISBA-TRIP CHS coupled via the OASIS-MCT coupler. The ISBA LSM solves explicitly the one dimensional Fourier law for soil temperature and the mixed form of the Richards equation for soil moisture using a 14-layers discretization over 12m depths. For the snowpack, a discretization using 12 layers allows the explicit representation of some snow key processes as its viscosity, its compaction due to wind, its age and its albedo on the visible and near infrared spectra. The TRIP RRM uses a global river channel network at 0.5° resolution. It is based on a three prognostic equations for the surface stream water, the seasonal floodplains, and the groundwater. The streamflow velocity is computed using the Maning's formula. The floodplain reservoir fills when the river height exceeds the river bankfull height and vice-versa. The flood interacts with the ISBA soil hydrology through infiltration and with the overlying atmosphere through precipitation interception and free water surface evaporation. Finally, the groundwater scheme is based on the two-dimensional groundwater flow equation for the piezometric head. Its coupling with ISBA permits to account for the presence of a water table under the soil moisture column allowing upward capillarity fluxes into the soil. In this study, we will present the off-line evaluation at the global scale of the ISBA-TRIP CHS over a recent period (1979-2010). The system will be compared to observations such as GRACE (Gravity Recovery and Climate Experiment) terrestrial water storage data, snow and permafrost extents from NSIDC (National Snow and Ice Data Center), or in-situ river discharge measurements from several sources. In addition we will also explore the impacts on the simulated water budget to account for some processes such as upward capillarity fluxes from groundwaters or seasonal floodplains. At last, it is envisaged to discuss some results about land/atmosphere interactions induced by these processes in the CNRM-CM6 climate model.

One-dimensional transport equation models for sound energy propagation in long spaces: theory.

PubMed

Jing, Yun; Larsen, Edward W; Xiang, Ning

2010-04-01

In this paper, a three-dimensional transport equation model is developed to describe the sound energy propagation in a long space. Then this model is reduced to a one-dimensional model by approximating the solution using the method of weighted residuals. The one-dimensional transport equation model directly describes the sound energy propagation in the "long" dimension and deals with the sound energy in the "short" dimensions by prescribed functions. Also, the one-dimensional model consists of a coupled set of N transport equations. Only N=1 and N=2 are discussed in this paper. For larger N, although the accuracy could be improved, the calculation time is expected to significantly increase, which diminishes the advantage of the model in terms of its computational efficiency.

Feedbacks between climate change and biosphere integrity

NASA Astrophysics Data System (ADS)

Lade, Steven; Anderies, J. Marty; Donges, Jonathan; Steffen, Will; Rockström, Johan; Richardson, Katherine; Cornell, Sarah; Norberg, Jon; Fetzer, Ingo

2017-04-01

The terrestrial and marine biospheres sink substantial fractions of human fossil fuel emissions. How the biosphere's capacity to sink carbon depends on biodiversity and other measures of biosphere integrity is however poorly understood. Here, we (1): review assumptions from literature regarding the relationships between the carbon cycle and the terrestrial and marine biospheres; and (2) explore the consequences of these different assumptions for climate feedbacks using the stylised carbon cycle model PB-INT. We find that: terrestrial biodiversity loss could significantly dampen climate-carbon cycle feedbacks; direct biodiversity effects, if they exist, could rival temperature increases from low-emission trajectories; and the response of the marine biosphere is critical for longer term climate change. Simple, low-dimensional climate models such as PB-INT can help assess the importance of still unknown or controversial earth system processes such as biodiversity loss for climate feedbacks. This study constitutes the first detailed study of the interactions between climate change and biosphere integrity, two of the 'planetary boundaries'.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

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

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

DOE PAGES

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare; ...

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Metrics for the Diurnal Cycle of Precipitation: Toward Routine Benchmarks for Climate Models

DOE PAGES

Covey, Curt; Gleckler, Peter J.; Doutriaux, Charles; ...

2016-06-08

In this paper, metrics are proposed—that is, a few summary statistics that condense large amounts of data from observations or model simulations—encapsulating the diurnal cycle of precipitation. Vector area averaging of Fourier amplitude and phase produces useful information in a reasonably small number of harmonic dial plots, a procedure familiar from atmospheric tide research. The metrics cover most of the globe but down-weight high-latitude wintertime ocean areas where baroclinic waves are most prominent. This enables intercomparison of a large number of climate models with observations and with each other. The diurnal cycle of precipitation has features not encountered in typicalmore » climate model intercomparisons, notably the absence of meaningful “average model” results that can be displayed in a single two-dimensional map. Displaying one map per model guides development of the metrics proposed here by making it clear that land and ocean areas must be averaged separately, but interpreting maps from all models becomes problematic as the size of a multimodel ensemble increases. Global diurnal metrics provide quick comparisons with observations and among models, using the most recent version of the Coupled Model Intercomparison Project (CMIP). This includes, for the first time in CMIP, spatial resolutions comparable to global satellite observations. Finally, consistent with earlier studies of resolution versus parameterization of the diurnal cycle, the longstanding tendency of models to produce rainfall too early in the day persists in the high-resolution simulations, as expected if the error is due to subgrid-scale physics.« less

Metrics for the Diurnal Cycle of Precipitation: Toward Routine Benchmarks for Climate Models

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

Covey, Curt; Gleckler, Peter J.; Doutriaux, Charles

In this paper, metrics are proposed—that is, a few summary statistics that condense large amounts of data from observations or model simulations—encapsulating the diurnal cycle of precipitation. Vector area averaging of Fourier amplitude and phase produces useful information in a reasonably small number of harmonic dial plots, a procedure familiar from atmospheric tide research. The metrics cover most of the globe but down-weight high-latitude wintertime ocean areas where baroclinic waves are most prominent. This enables intercomparison of a large number of climate models with observations and with each other. The diurnal cycle of precipitation has features not encountered in typicalmore » climate model intercomparisons, notably the absence of meaningful “average model” results that can be displayed in a single two-dimensional map. Displaying one map per model guides development of the metrics proposed here by making it clear that land and ocean areas must be averaged separately, but interpreting maps from all models becomes problematic as the size of a multimodel ensemble increases. Global diurnal metrics provide quick comparisons with observations and among models, using the most recent version of the Coupled Model Intercomparison Project (CMIP). This includes, for the first time in CMIP, spatial resolutions comparable to global satellite observations. Finally, consistent with earlier studies of resolution versus parameterization of the diurnal cycle, the longstanding tendency of models to produce rainfall too early in the day persists in the high-resolution simulations, as expected if the error is due to subgrid-scale physics.« less

Sparse Polynomial Chaos Surrogate for ACME Land Model via Iterative Bayesian Compressive Sensing

NASA Astrophysics Data System (ADS)

Sargsyan, K.; Ricciuto, D. M.; Safta, C.; Debusschere, B.; Najm, H. N.; Thornton, P. E.

2015-12-01

For computationally expensive climate models, Monte-Carlo approaches of exploring the input parameter space are often prohibitive due to slow convergence with respect to ensemble size. To alleviate this, we build inexpensive surrogates using uncertainty quantification (UQ) methods employing Polynomial Chaos (PC) expansions that approximate the input-output relationships using as few model evaluations as possible. However, when many uncertain input parameters are present, such UQ studies suffer from the curse of dimensionality. In particular, for 50-100 input parameters non-adaptive PC representations have infeasible numbers of basis terms. To this end, we develop and employ Weighted Iterative Bayesian Compressive Sensing to learn the most important input parameter relationships for efficient, sparse PC surrogate construction with posterior uncertainty quantified due to insufficient data. Besides drastic dimensionality reduction, the uncertain surrogate can efficiently replace the model in computationally intensive studies such as forward uncertainty propagation and variance-based sensitivity analysis, as well as design optimization and parameter estimation using observational data. We applied the surrogate construction and variance-based uncertainty decomposition to Accelerated Climate Model for Energy (ACME) Land Model for several output QoIs at nearly 100 FLUXNET sites covering multiple plant functional types and climates, varying 65 input parameters over broad ranges of possible values. This work is supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research, Accelerated Climate Modeling for Energy (ACME) project. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Summary of mathematical models for a conventional and vertical junction photoconverter

NASA Technical Reports Server (NTRS)

Heinbockel, J. H.

1986-01-01

The geometry and computer programming for mathematical models of a one-dimensional conventional photoconverter, a one-dimensional vertical junction photoconverter, a three-dimensional conventinal photoconverter, and a three-dimensional vertical junction solar cell are discussed.

Scales of variability of black carbon plumes and their dependence on resolution of ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Weigum, Natalie; Stier, Philip; Schutgens, Nick; Kipling, Zak

2015-04-01

Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. The aim of this study is to understand how a global climate model's (GCM) inability to resolve sub-grid scale variability affects simulations of important aerosol features. This problem is addressed by comparing observed black carbon (BC) plume scales from the HIPPO aircraft campaign to those simulated by ECHAM-HAM GCM, and testing how model resolution affects these scales. This study additionally investigates how model resolution affects BC variability in remote and near-source regions. These issues are examined using three different approaches: comparison of observed and simulated along-flight-track plume scales, two-dimensional autocorrelation analysis, and 3-dimensional plume analysis. We find that the degree to which GCMs resolve variability can have a significant impact on the scales of BC plumes, and it is important for models to capture the scales of aerosol plume structures, which account for a large degree of aerosol variability. In this presentation, we will provide further results from the three analysis techniques along with a summary of the implication of these results on future aerosol model development.

Modeling the Thickness of Perennial Ice Covers on Stratified Lakes of the Taylor Valley, Antarctica

NASA Technical Reports Server (NTRS)

Obryk, M. K.; Doran, P. T.; Hicks, J. A.; McKay, C. P.; Priscu, J. C.

2016-01-01

A one-dimensional ice cover model was developed to predict and constrain drivers of long term ice thickness trends in chemically stratified lakes of Taylor Valley, Antarctica. The model is driven by surface radiative heat fluxes and heat fluxes from the underlying water column. The model successfully reproduced 16 years (between 1996 and 2012) of ice thickness changes for west lobe of Lake Bonney (average ice thickness = 3.53 m; RMSE = 0.09 m, n = 118) and Lake Fryxell (average ice thickness = 4.22 m; RMSE = 0.21 m, n = 128). Long-term ice thickness trends require coupling with the thermal structure of the water column. The heat stored within the temperature maximum of lakes exceeding a liquid water column depth of 20 m can either impede or facilitate ice thickness change depending on the predominant climatic trend (temperature cooling or warming). As such, shallow (< 20 m deep water columns) perennially ice-covered lakes without deep temperature maxima are more sensitive indicators of climate change. The long-term ice thickness trends are a result of surface energy flux and heat flux from the deep temperature maximum in the water column, the latter of which results from absorbed solar radiation.

Multi-annual modes in the 20th century temperature variability in reanalyses and CMIP5 models

NASA Astrophysics Data System (ADS)

Järvinen, Heikki; Seitola, Teija; Silén, Johan; Räisänen, Jouni

2016-11-01

A performance expectation is that Earth system models simulate well the climate mean state and the climate variability. To test this expectation, we decompose two 20th century reanalysis data sets and 12 CMIP5 model simulations for the years 1901-2005 of the monthly mean near-surface air temperature using randomised multi-channel singular spectrum analysis (RMSSA). Due to the relatively short time span, we concentrate on the representation of multi-annual variability which the RMSSA method effectively captures as separate and mutually orthogonal spatio-temporal components. This decomposition is a unique way to separate statistically significant quasi-periodic oscillations from one another in high-dimensional data sets.The main results are as follows. First, the total spectra for the two reanalysis data sets are remarkably similar in all timescales, except that the spectral power in ERA-20C is systematically slightly higher than in 20CR. Apart from the slow components related to multi-decadal periodicities, ENSO oscillations with approximately 3.5- and 5-year periods are the most prominent forms of variability in both reanalyses. In 20CR, these are relatively slightly more pronounced than in ERA-20C. Since about the 1970s, the amplitudes of the 3.5- and 5-year oscillations have increased, presumably due to some combination of forced climate change, intrinsic low-frequency climate variability, or change in global observing network. Second, none of the 12 coupled climate models closely reproduce all aspects of the reanalysis spectra, although some models represent many aspects well. For instance, the GFDL-ESM2M model has two nicely separated ENSO periods although they are relatively too prominent as compared with the reanalyses. There is an extensive Supplement and YouTube videos to illustrate the multi-annual variability of the data sets.

A monthly global paleo-reanalysis of the atmosphere from 1600 to 2005 for studying past climatic variations

PubMed Central

Franke, Jörg; Brönnimann, Stefan; Bhend, Jonas; Brugnara, Yuri

2017-01-01

Climatic variations at decadal scales such as phases of accelerated warming or weak monsoons have profound effects on society and economy. Studying these variations requires insights from the past. However, most current reconstructions provide either time series or fields of regional surface climate, which limit our understanding of the underlying dynamics. Here, we present the first monthly paleo-reanalysis covering the period 1600 to 2005. Over land, instrumental temperature and surface pressure observations, temperature indices derived from historical documents and climate sensitive tree-ring measurements were assimilated into an atmospheric general circulation model ensemble using a Kalman filtering technique. This data set combines the advantage of traditional reconstruction methods of being as close as possible to observations with the advantage of climate models of being physically consistent and having 3-dimensional information about the state of the atmosphere for various variables and at all points in time. In contrast to most statistical reconstructions, centennial variability stems from the climate model and its forcings, no stationarity assumptions are made and error estimates are provided. PMID:28585926

Incorporating water table dynamics in climate modeling: 1. Water table observations and equilibrium water table simulations

NASA Astrophysics Data System (ADS)

Fan, Ying; Miguez-Macho, Gonzalo; Weaver, Christopher P.; Walko, Robert; Robock, Alan

2007-05-01

Soil moisture is a key participant in land-atmosphere interactions and an important determinant of terrestrial climate. In regions where the water table is shallow, soil moisture is coupled to the water table. This paper is the first of a two-part study to quantify this coupling and explore its implications in the context of climate modeling. We examine the observed water table depth in the lower 48 states of the United States in search of salient spatial and temporal features that are relevant to climate dynamics. As a means to interpolate and synthesize the scattered observations, we use a simple two-dimensional groundwater flow model to construct an equilibrium water table as a result of long-term climatic and geologic forcing. Model simulations suggest that the water table depth exhibits spatial organization at watershed, regional, and continental scales, which may have implications for the spatial organization of soil moisture at similar scales. The observations suggest that water table depth varies at diurnal, event, seasonal, and interannual scales, which may have implications for soil moisture memory at these scales.

Modelling of upper ocean mixing by wave-induced turbulence

NASA Astrophysics Data System (ADS)

Ghantous, Malek; Babanin, Alexander

2013-04-01

Mixing of the upper ocean affects the sea surface temperature by bringing deeper, colder water to the surface. Because even small changes in the surface temperature can have a large impact on weather and climate, accurately determining the rate of mixing is of central importance for forecasting. Although there are several mixing mechanisms, one that has until recently been overlooked is the effect of turbulence generated by non-breaking, wind-generated surface waves. Lately there has been a lot of interest in introducing this mechanism into models, and real gains have been made in terms of increased fidelity to observational data. However our knowledge of the mechanism is still incomplete. We indicate areas where we believe the existing models need refinement and propose an alternative model. We use two of the models to demonstrate the effect on the mixed layer of wave-induced turbulence by applying them to a one-dimensional mixing model and a stable temperature profile. Our modelling experiment suggests a strong effect on sea surface temperature due to non-breaking wave-induced turbulent mixing.

Variability of temperature and chlorophyll of the Iberian Peninsula near costal ecosystem during an upwelling event for the present climate and a future climate scenario

NASA Astrophysics Data System (ADS)

Lopes, José Fortes; Ferreira, Juan A.; Cardoso, Ana Cristina; Rocha, Alfredo C.

2014-01-01

Understanding the importance and the implication of the climate changes on coastal areas may be one of the major issues for this and next centuries. Climate changes may, indeed, impact the nearshore marine ecosystem, as coastal areas are very sensitive to the strength and the variability of the meteorological forcings. The main purpose of this work is to study temperature and phytoplankton distributions along the Portuguese near coastal zone during upwelling events in the present climate conditions and in a future climate scenario. The SRES-A2 IPCC scenario has been considered. We have used a three-dimensional model for coastal and shelf seas, including the following sub-models: hydrodynamical/physical, biological, sediment and contaminant. The forcings are provided by the interactions at the air-sea, considering the wind intensity and direction with the help of the WRF model (Weather Research and Forecast Model) and the coupled atmosphere-ocean model ECHAM5/MPI-OM. Results show that, for the future climate scenario, there is a reinforcement of the southward wind. The responses of the coastal ecosystem corresponds to the reinforcement of both, the southward (up to 10 cm/s) and the westward (up to 6 cm/s) induced upwelling currents. This, in turn generates an enlargement of the near coast upwelled cold layer, extending up to 60 km, as well as the rise of the warm layer temperature (up to 2.0 °C) and the spreading of the phytoplankton offshore. Significant changes in both the Chl-a vertical and the horizontal distribution patterns have been observed, as the nutrient supply to the upper layers depends on the strength of the upwelling, the bottom topography and orography of the coastal. These results confirm that changes in the strength and eventually the frequency of the upwelling favourable wind impact the phytoplankton distribution, which can have significant effect in the distribution and population of the upper level of the trophic chain of the coastal ecosystem.

Regular network model for the sea ice-albedo feedback in the Arctic.

PubMed

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.

Uncertainty Quantification and Sensitivity Analysis in the CICE v5.1 Sea Ice Model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, J. R.; Urban, N. M.

2015-12-01

Changes in the high latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with mid latitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. In this work we characterize parametric uncertainty in Los Alamos Sea Ice model (CICE) and quantify the sensitivity of sea ice area, extent and volume with respect to uncertainty in about 40 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one-at-a-time, this study uses a global variance-based approach in which Sobol sequences are used to efficiently sample the full 40-dimensional parameter space. This approach requires a very large number of model evaluations, which are expensive to run. A more computationally efficient approach is implemented by training and cross-validating a surrogate (emulator) of the sea ice model with model output from 400 model runs. The emulator is used to make predictions of sea ice extent, area, and volume at several model configurations, which are then used to compute the Sobol sensitivity indices of the 40 parameters. A ranking based on the sensitivity indices indicates that model output is most sensitive to snow parameters such as conductivity and grain size, and the drainage of melt ponds. The main effects and interactions among the most influential parameters are also estimated by a non-parametric regression technique based on generalized additive models. It is recommended research to be prioritized towards more accurately determining these most influential parameters values by observational studies or by improving existing parameterizations in the sea ice model.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-01

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.

Linearized Flux Evolution (LiFE): A technique for rapidly adapting fluxes from full-physics radiative transfer models

NASA Astrophysics Data System (ADS)

Robinson, Tyler D.; Crisp, David

2018-05-01

Solar and thermal radiation are critical aspects of planetary climate, with gradients in radiative energy fluxes driving heating and cooling. Climate models require that radiative transfer tools be versatile, computationally efficient, and accurate. Here, we describe a technique that uses an accurate full-physics radiative transfer model to generate a set of atmospheric radiative quantities which can be used to linearly adapt radiative flux profiles to changes in the atmospheric and surface state-the Linearized Flux Evolution (LiFE) approach. These radiative quantities describe how each model layer in a plane-parallel atmosphere reflects and transmits light, as well as how the layer generates diffuse radiation by thermal emission and by scattering light from the direct solar beam. By computing derivatives of these layer radiative properties with respect to dynamic elements of the atmospheric state, we can then efficiently adapt the flux profiles computed by the full-physics model to new atmospheric states. We validate the LiFE approach, and then apply this approach to Mars, Earth, and Venus, demonstrating the information contained in the layer radiative properties and their derivatives, as well as how the LiFE approach can be used to determine the thermal structure of radiative and radiative-convective equilibrium states in one-dimensional atmospheric models.

Laser range profile of cones

NASA Astrophysics Data System (ADS)

Zhou, Wenzhen; Gong, Yanjun; Wang, Mingjun; Gong, Lei

2016-10-01

technology. Laser one-dimensional range profile can reflect the characteristics of the target shape and surface material. These techniques were motivated by applications of laser radar to target discrimination in ballistic missile defense. The radar equation of pulse laser about cone is given in this paper. This paper demonstrates the analytical model of laser one-dimensional range profile of cone based on the radar equation of the pulse laser. Simulations results of laser one-dimensional range profiles of some cones are given. Laser one-dimensional range profiles of cone, whose surface material with diffuse lambertian reflectance, is given in this paper. Laser one-dimensional range profiles of cone, whose surface mater with diffuse materials whose retroreflectance can be modeled closely with an exponential term that decays with increasing incidence angles, is given in this paper. Laser one-dimensional range profiles of different pulse width of cone is given in this paper. The influences of surface material, pulse width, attitude on the one-dimensional range are analyzed. The laser two-dimensional range profile is two-dimensional scattering imaging of pulse laser of target. The two-dimensional range profile of roughness target can provide range resolved information. An analytical model of two-dimensional laser range profile of cone is proposed. The simulations of two-dimensional laser range profiles of some cones are given. Laser two-dimensional range profiles of cone, whose surface mater with diffuse lambertian reflectance, is given in this paper. Laser two-dimensional range profiles of cone, whose surface mater with diffuse materials whose retroreflectance can be modeled closely with an exponential term that decays with increasing incidence angles, is given in this paper. The influence of pulse width, surface material on laser two-dimensional range profile is analyzed. Laser one-dimensional range profile and laser two-dimensional range profile are called as laser range profile (LRP).

Current status of one- and two-dimensional numerical models: Successes and limitations

NASA Technical Reports Server (NTRS)

Schwartz, R. J.; Gray, J. L.; Lundstrom, M. S.

1985-01-01

The capabilities of one and two-dimensional numerical solar cell modeling programs (SCAP1D and SCAP2D) are described. The occasions when a two-dimensional model is required are discussed. The application of the models to design, analysis, and prediction are presented along with a discussion of problem areas for solar cell modeling.

A 3D thermal model to analyze the temperature changes of digits during cold stress and predict the danger of frostbite in human fingers.

PubMed

Fallahi, Amir; Reza Salimpour, Mohammad; Shirani, Ebrahim

2017-04-01

The existing computational models of frostbite injury are limited to one and two dimensional schemes. In this study, a coupled thermo-fluid model is applied to simulate a finger exposed to cold weather. The spatial variability of finger-tip temperature is compared to experimental ones to validate the model. A semi-realistic 3D model for tissue and blood vessels is used to analyze the transient heat transfer through the finger. The effect of heat conduction, metabolic heat generation, heat transport by blood perfusion, heat exchange between tissues and large vessels are considered in energy balance equations. The current model was then tested in different temperatures and air speeds to predict the danger of frostbite in humans for different gloves. Two prevalent gloves which are commonly used in cold climate are considered for investigation. The endurance time and the fraction of necrotic tissues are two main factors suggested for obtaining the response of digit tissues to different environmental conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of surface wave breaking on the oceanic boundary layer

NASA Astrophysics Data System (ADS)

He, Hailun; Chen, Dake

2011-04-01

Existing laboratory studies suggest that surface wave breaking may exert a significant impact on the formation and evolution of oceanic surface boundary layer, which plays an important role in the ocean-atmosphere coupled system. However, present climate models either neglect the effects of wave breaking or treat them implicitly through some crude parameterization. Here we use a one-dimensional ocean model (General Ocean Turbulence Model, GOTM) to investigate the effects of wave breaking on the oceanic boundary layer on diurnal to seasonal time scales. First a set of idealized experiments are carried out to demonstrate the basic physics and the necessity to include wave breaking. Then the model is applied to simulating observations at the northern North Sea and the Ocean Weather Station Papa, which shows that properly accounting for wave breaking effects can improve model performance and help it to successfully capture the observed upper ocean variability.

Continued development and validation of the AER two-dimensional interactive model

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Sze, N. D.; Shia, R. L.; Mackay, M.; Weisenstein, D. K.; Zhou, S. T.

1996-01-01

Results from two-dimensional chemistry-transport models have been used to predict the future behavior of ozone in the stratosphere. Since the transport circulation, temperature, and aerosol surface area are fixed in these models, they cannot account for the effects of changes in these quantities, which could be modified because of ozone redistribution and/or other changes in the troposphere associated with climate changes. Interactive two-dimensional models, which calculate the transport circulation and temperature along with concentrations of the chemical species, could provide answers to complement the results from three-dimension model calculations. In this project, we performed the following tasks in pursuit of the respective goals: (1) We continued to refine the 2-D chemistry-transport model; (2) We developed a microphysics model to calculate the aerosol loading and its size distribution; (3) The treatment of physics in the AER 2-D interactive model were refined in the following areas--the heating rate in the troposphere, and wave-forcing from propagation of planetary waves.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

DTIC Science & Technology

2012-09-30

characterization of extratropical storms and extremes and link these to LFV modes. Mingfang Ting, Yochanan Kushnir, Andrew W. Robertson...simulating and predicting a wide range of climate phenomena including ENSO, tropical Atlantic sea surface temperatures (SSTs), storm track variability...into empirical prediction models. Use observations to improve low-order dynamical MJO models. Adam Sobel, Daehyun Kim. Extratropical variability

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

Cowan, Nicolas B.; Voigt, Aiko; Abbot, Dorian S., E-mail: n-cowan@nortwestern.edu

In order to understand the climate on terrestrial planets orbiting nearby Sun-like stars, one would like to know their thermal inertia. We use a global climate model to simulate the thermal phase variations of Earth analogs and test whether these data could distinguish between planets with different heat storage and heat transport characteristics. In particular, we consider a temperate climate with polar ice caps (like the modern Earth) and a snowball state where the oceans are globally covered in ice. We first quantitatively study the periodic radiative forcing from, and climatic response to, rotation, obliquity, and eccentricity. Orbital eccentricity andmore » seasonal changes in albedo cause variations in the global-mean absorbed flux. The responses of the two climates to these global seasons indicate that the temperate planet has 3 Multiplication-Sign the bulk heat capacity of the snowball planet due to the presence of liquid water oceans. The obliquity seasons in the temperate simulation are weaker than one would expect based on thermal inertia alone; this is due to cross-equatorial oceanic and atmospheric energy transport. Thermal inertia and cross-equatorial heat transport have qualitatively different effects on obliquity seasons, insofar as heat transport tends to reduce seasonal amplitude without inducing a phase lag. For an Earth-like planet, however, this effect is masked by the mixing of signals from low thermal inertia regions (sea ice and land) with that from high thermal inertia regions (oceans), which also produces a damped response with small phase lag. We then simulate thermal light curves as they would appear to a high-contrast imaging mission (TPF-I/Darwin). In order of importance to the present simulations, which use modern-Earth orbital parameters, the three drivers of thermal phase variations are (1) obliquity seasons, (2) diurnal cycle, and (3) global seasons. Obliquity seasons are the dominant source of phase variations for most viewing angles. A pole-on observer would measure peak-to-trough amplitudes of 13% and 47% for the temperate and snowball climates, respectively. Diurnal heating is important for equatorial observers ({approx}5% phase variations), because the obliquity effects cancel to first order from that vantage. Finally, we compare the prospects of optical versus thermal direct imaging missions for constraining the climate on exoplanets and conclude that while zero- and one-dimensional models are best served by thermal measurements, second-order models accounting for seasons and planetary thermal inertia would require both optical and thermal observations.« less

The seasonal effect in one-dimensional Daisyworld.

PubMed

Biton, Eli; Gildor, Hezi

2012-12-07

We have studied the effects of seasonal Solar Radiation Forcing (SRF) on the climate self-regulatory capability of life, using a latitudinal-dependent Daisyworld model. Because the seasonal polarity of SRF increases poleward, habitable conditions exist in the equatorial regions year round, whereas, in the high latitudes, harsh winters cause annual extinction of life, and only the summers are inhabited or regulated by life. Seasonality affects climate regulation by two major mechanisms: (1) the cold winter conditions in the high latitudes reduce the global temperature below the optimal temperature; (2) during summer, life experiences higher SRF anomalies and, therefore, shifts to higher albedo when compared to annual mean SRF. In turn, a full capacity for temperature regulation is reached at lower SRF, and the range of SRF over which life regulates climate is significantly reduced. Lastly, initiation/extinction of life at low/highly-perturbed SRF occurs at the poles. Therefore, an irreversible global extinction occurs once life passes its regulatory capacity in the poles. We conduct extensive sensitivity analyses on various model parameters (latitudinal heat diffusion, heat capacity, and population death rate), strengthening the generality/robustness of the above net seasonal effects. Applications to other SRF fluctuation, as Milankovitch cycles are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Can Increased CO2 Levels Trigger a Runaway Greenhouse on the Earth?

NASA Astrophysics Data System (ADS)

Ramirez, R.

2014-04-01

Recent one-dimensional (globally averaged) climate model calculations suggest that increased atmospheric CO2 could conceivably trigger a runaway greenhouse if CO2 concentrations were approximately 100 times higher than today. The new prediction runs contrary to previous calculations, which indicated that CO2 increases could not trigger a runaway, even at Venus-like CO2 concentrations. Goldblatt et al. argue that this different behavior is a consequence of updated absorption coefficients for H2O that make a runaway more likely. Here, we use a 1-D cloud-free climate model with similar, up-to-date absorption coefficients, but with a self-consistent methodology, to demonstrate that CO2 increases cannot induce a runaway greenhouse on the modern Earth. However, these initial calculations do not include cloud feedback, which may be positive at higher temperatures, destabilizing Earth's climate. We then show new calculations demonstrating that cirrus clouds cannot trigger a runaway, even in the complete absence of low clouds. Thus, the habitability of an Earth-like planet at Earth's distance appears to be ensured, irrespective of the sign of cloud feedback. Our results are of importance to Earth-like planets that receive similar insolation levels as does the Earth and to the ongoing question about cloud response at higher temperatures.

Modelling the response of shallow groundwater levels to combined climate and water-diversion scenarios in Beijing-Tianjin-Hebei Plain, China

NASA Astrophysics Data System (ADS)

Li, Xue; Ye, Si-Yuan; Wei, Ai-Hua; Zhou, Peng-Peng; Wang, Li-Heng

2017-09-01

A three-dimensional groundwater flow model was implemented to quantify the temporal variation of shallow groundwater levels in response to combined climate and water-diversion scenarios over the next 40 years (2011-2050) in Beijing-Tianjin-Hebei (Jing-Jin-Ji) Plain, China. Groundwater plays a key role in the water supply, but the Jing-Jin-Ji Plain is facing a water crisis. Groundwater levels have declined continuously over the last five decades (1961-2010) due to extensive pumping and climate change, which has resulted in decreased recharge. The implementation of the South-to-North Water Diversion Project (SNWDP) will provide an opportunity to restore the groundwater resources. The response of groundwater levels to combined climate and water-diversion scenarios has been quantified using a groundwater flow model. The impacts of climate change were based on the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset for future high (A2), medium (A1B), and low (B1) greenhouse gas scenarios; precipitation data from CMIP3 were applied in the model. The results show that climate change will slow the rate of decrease of the shallow groundwater levels under three climate-change scenarios over the next 40 years compared to the baseline scenario; however, the shallow groundwater levels will rise significantly (maximum of 6.71 m) when considering scenarios that combine climate change and restrictions on groundwater exploitation. Restrictions on groundwater exploitation for water resource management are imperative to control the decline of levels in the Jing-Jin-Ji area.

Runaway and moist greenhouse atmospheres and the evolution of earth and Venus

NASA Technical Reports Server (NTRS)

Kasting, James F.

1988-01-01

For the case of fully moisture-saturated and cloud-free conditions, the present one-dimensional climate model for the response of an earthlike atmosphere to large solar flux increases notes the critical solar flux at which runaway greenhouse (total evaporation of oceans) occurs to be 1.4 times the present flux at the earth's orbit, almost independently of the CO2 content of the atmophere. The value is, however, sensitive to the H2O absorption coefficient in the 8-12 micron window. Venus oceans may have been lost early on due to rapid water vapor photodissociation, followed by hydrogen escape into space.

Limit cycles at the outer edge of the habitable zone

NASA Astrophysics Data System (ADS)

Haqq-Misra, J. D.; Kopparapu, R.; Batalha, N. E.; Harman, C.; Kasting, J. F.

2016-12-01

The liquid water habitable zone (HZ) describes the orbital distance at which a terrestrial planet can maintain above-freezing conditions through regulation by the carbonate-silicate cycle. Calculations with one-dimensional climate models predict that the inner edge of the HZ is limited by water loss through a runaway greenhouse, while the outer edge of the HZ is bounded by the maximum greenhouse effect of carbon dioxide. This classic picture of the HZ continues to guide interpretation of exoplanet discoveries; however, recent calculations have shown that terrestrial planets near the outer edge of the HZ may exhibit other behaviors that affect their habitability. Here I discuss results from a hierarchy of climate models to understand the stellar environments most likely to support a habitable planet. I present energy balance climate model calculations showing the conditions under which planets in the outer regions of the habitable zone should oscillate between long, globally glaciated states and shorter periods of climatic warmth, known as `limit cycles.' Such conditions would be inimical to the development of complex land life, including intelligent life. Limit cycles may also provide an explanation for fluvial features on early Mars, although this requires additional greenhouse warming by hydrogen. These calculations show that the net volcanic outgassing rate and the propensity for plant life to sequester carbon dioxide are critical factors that determine the susceptibility of a planet to limit cycling. I argue that planets orbiting mid G- to mid K-type stars offer more opportunity for supporting advanced life than do planets around F-type stars or M-type stars.

Sulfur Chemistry in the Early and Present Atmosphere of Mars

NASA Technical Reports Server (NTRS)

Levine, Joel S.; Summers, M. E.

2011-01-01

Atmospheric sulfur species resulting from volcanic emissions impact the composition and chemistry of the atmosphere, impact the climate, and hence, the habitability of Mars and impact the mineralogy and composition of the surface of Mars. The geochemical/ photochemical cycling of sulfur species between the interior (via volcanism), the atmosphere (atmospheric photochemical and chemical processes) and the deposition of sulfuric acid on the surface of Mars is an important, but as yet poorly understood geochemical/ photochemical cycle on Mars. There is no observational evidence to indicate that Mars is volcanically active at the present time, however, there is strong evidence that volcanism was an important and widespread process on early Mars. The chemistry and photochemistry of sulfur species in the early and present atmosphere of Mars will be assessed using a one-dimensional photochemical model. Since it is generally assumed that the atmosphere of early Mars was significantly denser than the present 6-millibar atmosphere, photochemical calculations were performed for the present atmosphere and for the atmosphere of early Mars with assumed surface pressures of 60 and 350-millibars, where higher surface pressure resulted from enhanced atmospheric concentrations of carbon dioxide (CO2). The following sections include the results of earlier modeling studies, a summary of the one-dimensional photochemical model used in this study, a summary of the photochemistry and chemistry of sulfur species in the atmosphere of Mars and some of the results of the calculations.

Detection and attribution of climate change at regional scale: case study of Karkheh river basin in the west of Iran

NASA Astrophysics Data System (ADS)

Zohrabi, Narges; Goodarzi, Elahe; Massah Bavani, Alireza; Najafi, Husain

2017-11-01

This research aims at providing a statistical framework for detection and attribution of climate variability and change at regional scale when at least 30 years of observation data are available. While extensive research has been done on detecting significant observed trends in hydroclimate variables and attribution to anthropogenic greenhouse gas emissions in large continents, less attention has been paid for regional scale analysis. The latter is mainly important for adaptation to climate change in different sectors including but not limited to energy, agriculture, and water resources planning and management, and it is still an open discussion in many countries including the West Asian ones. In the absence of regional climate models, an informative framework is suggested providing useful insights for policymakers. It benefits from general flexibility, not being computationally expensive, and applying several trend tests to analyze temporal variations in temperature and precipitation (gradual and step changes). The framework is implemented for a very important river basin in the west of Iran. In general, some increasing and decreasing trends of the interannual precipitation and temperature have been detected. For precipitation annual time series, a reducing step was seen around 1996 compared with the gradual change in most of the stations, which have not experience a dramatical change. The range of natural forcing is found to be ±76 % for precipitation and ±1.4 °C for temperature considering a two-dimensional diagram of precipitation and temperature anomalies from 1000-year control run of global climate model (GCM). Findings out of applying the proposed framework may provide useful insights into how to approach structural and non-structural climate change adaptation strategies from central governments.

Comparison of entrainment rates from a tank experiment with results using the one-dimensional turbulence model.

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

Kerstein, Alan R.; Sayler, B. J.; Wunsch, S.

2010-05-01

Recent work suggests that cloud effects remain one of the largest sources of uncertainty in model-based estimates of climate sensitivity. In particular, the entrainment rate in stratocumulus-topped mixed layers needs better models. More than thirty years ago a clever laboratory experiment was conducted by McEwan and Paltridge to examine an analog of the entrainment process at the top of stratiform clouds. Sayler and Breidenthal extended this pioneering work and determined the effect of the Richardson number on the dimensionless entrainment rate. The experiments gave hints that the interaction between molecular effects and the one-sided turbulence seems to be crucial formore » understanding entrainment. From the numerical point of view large-eddy simulation (LES) does not allow explicitly resolving all the fine scale processes at the entrainment interface. Direct numerical simulation (DNS) is limited due to the Reynolds number and is not the tool of choice for parameter studies. Therefore it is useful to investigate new modeling strategies, such as stochastic turbulence models which allow sufficient resolution at least in one dimension while having acceptable run times. We will present results of the One-Dimensional Turbulence stochastic simulation model applied to the experimental setup of Sayler and Breidenthal. The results on radiatively induced entrainment follow quite well the scaling of the entrainment rate with the Richardson number that was experimentally found for a set of trials. Moreover, we investigate the influence of molecular effects, the fluids optical properties, and the artifact of parasitic turbulence experimentally observed in the laminar layer. In the simulations the parameters are varied systematically for even larger ranges than in the experiment. Based on the obtained results a more complex parameterization of the entrainment rate than currently discussed in the literature seems to be necessary.« less

A regional groundwater-flow model for sustainable groundwater-resource management in the south Asian megacity of Dhaka, Bangladesh

NASA Astrophysics Data System (ADS)

Islam, Md Bayzidul; Firoz, A. B. M.; Foglia, Laura; Marandi, Andres; Khan, Abidur Rahman; Schüth, Christoph; Ribbe, Lars

2017-05-01

The water resources that supply most of the megacities in the world are under increased pressure because of land transformation, population growth, rapid urbanization, and climate-change impacts. Dhaka, in Bangladesh, is one of the largest of 22 growing megacities in the world, and it depends on mainly groundwater for all kinds of water needs. The regional groundwater-flow model MODFLOW-2005 was used to simulate the interaction between aquifers and rivers in steady-state and transient conditions during the period 1981-2013, to assess the impact of development and climate change on the regional groundwater resources. Detailed hydro-stratigraphic units are described according to 150 lithology logs, and a three-dimensional model of the upper 400 m of the Greater Dhaka area was constructed. The results explain how the total abstraction (2.9 million m3/d) in the Dhaka megacity, which has caused regional cones of depression, is balanced by recharge and induced river leakage. The simulated outcome shows the general trend of groundwater flow in the sedimentary Holocene aquifers under a variety of hydrogeological conditions, which will assist in the future development of a rational and sustainable management approach.

An Empirical Assessment of the Effects of Affective Response in the Measurement of Organizational Climate.

ERIC Educational Resources Information Center

Schnake, Mel E.

1983-01-01

Examined whether an affective response affects the dimensionality of perceptual measures of organizational climate, in a study of 8,938 employees who completed an organizational climate questionnaire and a measure of job satisfaction. Results suggested that partialing job satisfaction out of responses improved the dimensionality of the climate…

Selection of optimal complexity for ENSO-EMR model by minimum description length principle

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Mukhina, A.; Gavrilov, A.; Kondrashov, D. A.; Feigin, A. M.

2012-12-01

One of the main problems arising in modeling of data taken from natural system is finding a phase space suitable for construction of the evolution operator model. Since we usually deal with strongly high-dimensional behavior, we are forced to construct a model working in some projection of system phase space corresponding to time scales of interest. Selection of optimal projection is non-trivial problem since there are many ways to reconstruct phase variables from given time series, especially in the case of a spatio-temporal data field. Actually, finding optimal projection is significant part of model selection, because, on the one hand, the transformation of data to some phase variables vector can be considered as a required component of the model. On the other hand, such an optimization of a phase space makes sense only in relation to the parametrization of the model we use, i.e. representation of evolution operator, so we should find an optimal structure of the model together with phase variables vector. In this paper we propose to use principle of minimal description length (Molkov et al., 2009) for selection models of optimal complexity. The proposed method is applied to optimization of Empirical Model Reduction (EMR) of ENSO phenomenon (Kravtsov et al. 2005, Kondrashov et. al., 2005). This model operates within a subset of leading EOFs constructed from spatio-temporal field of SST in Equatorial Pacific, and has a form of multi-level stochastic differential equations (SDE) with polynomial parameterization of the right-hand side. Optimal values for both the number of EOF, the order of polynomial and number of levels are estimated from the Equatorial Pacific SST dataset. References: Ya. Molkov, D. Mukhin, E. Loskutov, G. Fidelin and A. Feigin, Using the minimum description length principle for global reconstruction of dynamic systems from noisy time series, Phys. Rev. E, Vol. 80, P 046207, 2009 Kravtsov S, Kondrashov D, Ghil M, 2005: Multilevel regression modeling of nonlinear processes: Derivation and applications to climatic variability. J. Climate, 18 (21): 4404-4424. D. Kondrashov, S. Kravtsov, A. W. Robertson and M. Ghil, 2005. A hierarchy of data-based ENSO models. J. Climate, 18, 4425-4444.

Analysis of the Three-Dimensional Vector FAÇADE Model Created from Photogrammetric Data

NASA Astrophysics Data System (ADS)

Kamnev, I. S.; Seredovich, V. A.

2017-12-01

The results of the accuracy assessment analysis for creation of a three-dimensional vector model of building façade are described. In the framework of the analysis, analytical comparison of three-dimensional vector façade models created by photogrammetric and terrestrial laser scanning data has been done. The three-dimensional model built from TLS point clouds was taken as the reference one. In the course of the experiment, the three-dimensional model to be analyzed was superimposed on the reference one, the coordinates were measured and deviations between the same model points were determined. The accuracy estimation of the three-dimensional model obtained by using non-metric digital camera images was carried out. Identified façade surface areas with the maximum deviations were revealed.

Coupling Processes between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Weisenstein, Debra K.; Shia, Run-Lie; Scott, Courtney J.; Sze, Nien Dak

1998-01-01

This is the fourth semi-annual report for NAS5-97039, covering the time period July through December 1998. The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the Atmospheric and Environmental Research (AER) two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. For this six month period, we report on a modeling study of new rate constant which modify the NOx/NOy ratio in the lower stratosphere; sensitivity to changes in stratospheric water vapor in the future atmosphere; a study of N2O and CH4 observations which has allowed us to adjust diffusion in the 2-D CTM in order to obtain appropriate polar vortex isolation; a study of SF6 and age of air with comparisons of models and measurements; and a report on the Models and Measurements II effort.

The Arctic-Subarctic Sea Ice System is Entering a Seasonal Regime: Implications for Future Arctic Amplication

NASA Astrophysics Data System (ADS)

Haine, T. W. N.; Martin, T.

2017-12-01

The loss of Arctic sea ice is a conspicuous example of climate change. Climate models project ice-free conditions during summer this century under realistic emission scenarios, reflecting the increase in seasonality in ice cover. To quantify the increased seasonality in the Arctic-Subarctic sea ice system, we define a non-dimensional seasonality number for sea ice extent, area, and volume from satellite data and realistic coupled climate models. We show that the Arctic-Subarctic, i.e. the northern hemisphere, sea ice now exhibits similar levels of seasonality to the Antarctic, which is in a seasonal regime without significant change since satellite observations began in 1979. Realistic climate models suggest that this transition to the seasonal regime is being accompanied by a maximum in Arctic amplification, which is the faster warming of Arctic latitudes compared to the global mean, in the 2010s. The strong link points to a peak in sea-ice-related feedbacks that occurs long before the Arctic becomes ice-free in summer.

A mixed model for the relationship between climate and human cranial form.

PubMed

Katz, David C; Grote, Mark N; Weaver, Timothy D

2016-08-01

We expand upon a multivariate mixed model from quantitative genetics in order to estimate the magnitude of climate effects in a global sample of recent human crania. In humans, genetic distances are correlated with distances based on cranial form, suggesting that population structure influences both genetic and quantitative trait variation. Studies controlling for this structure have demonstrated significant underlying associations of cranial distances with ecological distances derived from climate variables. However, to assess the biological importance of an ecological predictor, estimates of effect size and uncertainty in the original units of measurement are clearly preferable to significance claims based on units of distance. Unfortunately, the magnitudes of ecological effects are difficult to obtain with distance-based methods, while models that produce estimates of effect size generally do not scale to high-dimensional data like cranial shape and form. Using recent innovations that extend quantitative genetics mixed models to highly multivariate observations, we estimate morphological effects associated with a climate predictor for a subset of the Howells craniometric dataset. Several measurements, particularly those associated with cranial vault breadth, show a substantial linear association with climate, and the multivariate model incorporating a climate predictor is preferred in model comparison. Previous studies demonstrated the existence of a relationship between climate and cranial form. The mixed model quantifies this relationship concretely. Evolutionary questions that require population structure and phylogeny to be disentangled from potential drivers of selection may be particularly well addressed by mixed models. Am J Phys Anthropol 160:593-603, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

A new general circulation model of Jupiter's atmosphere based on the UKMO Unified Model: Three-dimensional evolution of isolated vortices and zonal jets in mid-latitudes

NASA Astrophysics Data System (ADS)

Yamazaki, Y. H.; Skeet, D. R.; Read, P. L.

2004-04-01

We have been developing a new three-dimensional general circulation model for the stratosphere and troposphere of Jupiter based on the dynamical core of a portable version of the Unified Model of the UK Meteorological Office. Being one of the leading terrestrial GCMs, employed for operational weather forecasting and climate research, the Unified Model has been thoroughly tested and performance tuned for both vector and parallel computers. It is formulated as a generalized form of the standard primitive equations to handle a thick atmosphere, using a scaled pressure as the vertical coordinate. It is able to accurately simulate the dynamics of a three-dimensional fully compressible atmosphere on the whole or a part of a spherical shell at high spatial resolution in all three directions. Using the current version of the GCM, we examine the characteristics of the Jovian winds in idealized configurations based on the observed vertical structure of temperature. Our initial focus is on the evolution of isolated eddies in the mid-latitudes. Following a brief theoretical investigation of the vertical structure of the atmosphere, limited-area cyclic channel domains are used to numerically investigate the nonlinear evolution of the mid-latitude winds. First, the evolution of deep and shallow cyclones and anticyclones are tested in the atmosphere at rest to identify a preferred horizontal and vertical structure of the vortices. Then, the dependency of the migration characteristics of the vortices are investigated against modelling parameters to find that it is most sensitive to the horizontal diffusion. We also examine the hydrodynamical stability of observed subtropical jets in both northern and southern hemispheres in the three-dimensional nonlinear model as initial value problems. In both cases, it was found that the prominent jets are unstable at various scales and that vorteces of various sizes are generated including those comparable to the White Ovals and the Great Red Spot.

Transient Stress Wave Propagation in One-Dimensional Micropolar Bodies

DTIC Science & Technology

2009-02-01

based on Biot’s theory of poro- elasticity. Two compressional waves were then observed in the resulting one-dimensional model of a poroelastic column...Lisina, S., Potapov, A., Nesterenko, V., 2001. A nonlinear granular medium with particle rotation: a one-dimensional model . Acoustical Physics 47 (5...zones in failed ceramics, may be modeled using continuum theories incorporating additional kinematic degrees of freedom beyond the scope of classical

Limit Properties of One Dimensional Periodic Hopping Model

NASA Astrophysics Data System (ADS)

Zhang, Yun-xin

2010-02-01

One dimensional periodic hopping model is useful to understand the motion of microscopic particles in thermal noise environment. In this research, by formal calculation and based on detailed balance, the explicit expressions of the limits of mean velocity and diffusion constant of this model as the number of internal mechanochemical sates tend to infinity are obtained. These results will be helpful to understand the limit of the one dimensional hopping model. At the same time, the work can be used to get more useful results in continuous form from the corresponding ones obtained by discrete models.

Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

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.

Estimation of effective hydrologic properties of soils from observations of vegetation density

NASA Technical Reports Server (NTRS)

Tellers, T. E.; Eagleson, P. S.

1980-01-01

A one-dimensional model of the annual water balance is reviewed. Improvements are made in the method of calculating the bare soil component of evaporation, and in the way surface retention is handled. A natural selection hypothesis, which specifies the equilibrium vegetation density for a given, water limited, climate soil system, is verified through comparisons with observed data. Comparison of CDF's of annual basin yield derived using these soil properties with observed CDF's provides verification of the soil-selection procedure. This method of parameterization of the land surface is useful with global circulation models, enabling them to account for both the nonlinearity in the relationship between soil moisture flux and soil moisture concentration, and the variability of soil properties from place to place over the Earth's surface.

Three-Dimensional Water and Carbon Cycle Modeling at High Spatial-Temporal Resolutions

NASA Astrophysics Data System (ADS)

Liao, C.; Zhuang, Q.

2017-12-01

Terrestrial ecosystems in cryosphere are very sensitive to the global climate change due to the presence of snow covers, mountain glaciers and permafrost, especially when the increase in near surface air temperature is almost twice as large as the global average. However, few studies have investigated the water and carbon cycle dynamics using process-based hydrological and biogeochemistry modeling approach. In this study, we used three-dimensional modeling approach at high spatial-temporal resolutions to investigate the water and carbon cycle dynamics for the Tanana Flats Basin in interior Alaska with emphases on dissolved organic carbon (DOC) dynamics. The results have shown that: (1) lateral flow plays an important role in water and carbon cycle, especially in dissolved organic carbon (DOC) dynamics. (2) approximately 2.0 × 104 kg C yr-1 DOC is exported to the hydrological networks and it compromises 1% and 0.01% of total annual gross primary production (GPP) and total organic carbon stored in soil, respectively. This study has established an operational and flexible framework to investigate and predict the water and carbon cycle dynamics under the changing climate.

One-dimensional GIS-based model compared with a two-dimensional model in urban floods simulation.

PubMed

Lhomme, J; Bouvier, C; Mignot, E; Paquier, A

2006-01-01

A GIS-based one-dimensional flood simulation model is presented and applied to the centre of the city of Nîmes (Gard, France), for mapping flow depths or velocities in the streets network. The geometry of the one-dimensional elements is derived from the Digital Elevation Model (DEM). The flow is routed from one element to the next using the kinematic wave approximation. At the crossroads, the flows in the downstream branches are computed using a conceptual scheme. This scheme was previously designed to fit Y-shaped pipes junctions, and has been modified here to fit X-shaped crossroads. The results were compared with the results of a two-dimensional hydrodynamic model based on the full shallow water equations. The comparison shows that good agreements can be found in the steepest streets of the study zone, but differences may be important in the other streets. Some reasons that can explain the differences between the two models are given and some research possibilities are proposed.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

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

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

DOE PAGES

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-27

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

Fluctuations of a Greenlandic tidewater glacier driven by changes in atmospheric forcing: observations and modelling of Kangiata Nunaata Sermia, 1859-present

NASA Astrophysics Data System (ADS)

Lea, J. M.; Mair, D. W. F.; Nick, F. M.; Rea, B. R.; van As, D.; Morlighem, M.; Nienow, P. W.; Weidick, A.

2014-11-01

Many tidewater glaciers in Greenland are known to have undergone significant retreat during the last century following their Little Ice Age maxima. Where it is possible to reconstruct glacier change over this period, they provide excellent records for comparison to climate records, as well as calibration/validation for numerical models. These glacier change records therefore allow for tests of numerical models that seek to simulate tidewater glacier behaviour over multi-decadal to centennial timescales. Here we present a detailed record of behaviour from Kangiata Nunaata Sermia (KNS), SW Greenland, between 1859 and 2012, and compare it against available oceanographic and atmospheric temperature data between 1871 and 2012. We also use these records to evaluate the ability of a well-established one-dimensional flow-band model to replicate behaviour for the observation period. The record of terminus change demonstrates that KNS has advanced/retreated in phase with atmosphere and ocean climate anomalies averaged over multi-annual to decadal timescales. Results from an ensemble of model runs demonstrate that observed dynamics can be replicated. Model runs that provide a reasonable match to observations always require a significant atmospheric forcing component, but do not necessarily require an oceanic forcing component. Although the importance of oceanic forcing cannot be discounted, these results demonstrate that changes in atmospheric forcing are likely to be a primary driver of the terminus fluctuations of KNS from 1859 to 2012. We propose that the detail and length of the record presented makes KNS an ideal site for model validation exercises investigating links between climate, calving rates, and tidewater glacier dynamics.

Quantifying conditional risks for water and energy systems using climate information

NASA Astrophysics Data System (ADS)

Lall, U.

2016-12-01

There has been a growing recognition of the multi-scale spatio-temporal organization of climate dynamics, and its implications for predictable, structured risk exposure to populations and infrastructure systems. At the most base level is an understanding that there are some identifiable climate modes, such as ENSO, that are associated with such outcomes. This has led to the emergence of a small cottage industry of analysts who relate different "climate indices" to specific regional outcomes. Such efforts and the associated media interest in these simplified "stories" have led to an increasing appreciation of the phenomenon, and some formal and informal efforts at decision making using such information. However, as was demonstrated through the 2014-16 El Nino forecasting season, many climate scientists over-emphasized the potential risks, while others cautioned the media as to the caveats and uncertainties associated with assuming that the forecasts of ENSO and the expected teleconnections may pan out. At least in certain sectors and regions, significant efforts or expectations as to outcomes were put in place, and some were beneficial, while others failed to manifest. Climate informed predictions for water and energy systems can be thought of as efforts to infer conditional distributions of specific outcomes given information on climate state. Invariably, the climate state may be presented as a very high dimensional spatial set of variables, with limited temporal sampling, while the water and energy attributes may be regional and constitute a much smaller dimension. One may, of course, be interested in the fact that the same climate state may lead to synchronous positive and negative effects across many locations, as may be expected under mid-latitude stationary and transient wave interaction. In this talk, I will provide examples of a few modern statistical and machine learning tools that allow a decomposition of the high dimensional climate state and its relation to specific regional or hemispheric outcomes that inform terrestrial water and energy (wind as well as hydropower) futures. The focus will be on how one can frame the mathematical problem of robustly estimating relevant conditional distributions and their uncertainty, to inform risk management applications in these sectors.

Response of the pelagic system of the Pacific Ocean off Baja California Peninsula to the projected effects of climate change: insights from a numerical model.

NASA Astrophysics Data System (ADS)

Arellano, B.; Rivas, D.

2015-12-01

The response of the physical and biological dynamics of the Pacific Ocean off Baja California to the projected effects of climate change are studied using numerical simulations. This region is part of the California Current System, which is a highly productive ecosystem due to the seasonal upwelling, supporting all the trophic levels and important fisheries. The response of the ecosystem to the effects of climate change is uncertain and the information generated by models could be useful to predict future conditions. A three-dimensional hydrodinamical model is coupled to a Nitrate-Phytoplankton-Zooplankton-Detritus (NPZD) trophic model, and it is forced by the GFDL 3.0 model outputs. Monthly climatologies of variables such as temperature, nutrients, wind, and ocean circulation patterns during the historical period 1985-2005 are compared to the available observed data in order to assess the model's ability to reproduce the observed patterns. The system's response to a high-emission scenario proposed by the Intergovernmental Panel of Climate Change (IPCC) is also studied. The experiments are carried out using data correspondig to the RCP 6.0 scenario during the period 2006-2050.

Ocean Modeling and Visualization on Massively Parallel Computer

NASA Technical Reports Server (NTRS)

Chao, Yi; Li, P. Peggy; Wang, Ping; Katz, Daniel S.; Cheng, Benny N.

1997-01-01

Climate modeling is one of the grand challenges of computational science, and ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change.

Underwater striling engine design with modified one-dimensional model

NASA Astrophysics Data System (ADS)

Li, Daijin; Qin, Kan; Luo, Kai

2015-09-01

Stirling engines are regarded as an efficient and promising power system for underwater devices. Currently, many researches on one-dimensional model is used to evaluate thermodynamic performance of Stirling engine, but in which there are still some aspects which cannot be modeled with proper mathematical models such as mechanical loss or auxiliary power. In this paper, a four-cylinder double-acting Stirling engine for Unmanned Underwater Vehicles (UUVs) is discussed. And a one-dimensional model incorporated with empirical equations of mechanical loss and auxiliary power obtained from experiments is derived while referring to the Stirling engine computer model of National Aeronautics and Space Administration (NASA). The P-40 Stirling engine with sufficient testing results from NASA is utilized to validate the accuracy of this one-dimensional model. It shows that the maximum error of output power of theoretical analysis results is less than 18% over testing results, and the maximum error of input power is no more than 9%. Finally, a Stirling engine for UUVs is designed with Schmidt analysis method and the modified one-dimensional model, and the results indicate this designed engine is capable of showing desired output power.

Multi-Scale Analysis for Characterizing Near-Field Constituent Concentrations in the Context of a Macro-Scale Semi-Lagrangian Numerical Model

NASA Astrophysics Data System (ADS)

Yearsley, J. R.

2017-12-01

The semi-Lagrangian numerical scheme employed by RBM, a model for simulating time-dependent, one-dimensional water quality constituents in advection-dominated rivers, is highly scalable both in time and space. Although the model has been used at length scales of 150 meters and time scales of three hours, the majority of applications have been at length scales of 1/16th degree latitude/longitude (about 5 km) or greater and time scales of one day. Applications of the method at these scales has proven successful for characterizing the impacts of climate change on water temperatures in global rivers and on the vulnerability of thermoelectric power plants to changes in cooling water temperatures in large river systems. However, local effects can be very important in terms of ecosystem impacts, particularly in the case of developing mixing zones for wastewater discharges with pollutant loadings limited by regulations imposed by the Federal Water Pollution Control Act (FWPCA). Mixing zone analyses have usually been decoupled from large-scale watershed influences by developing scenarios that represent critical scenarios for external processes associated with streamflow and weather conditions . By taking advantage of the particle-tracking characteristics of the numerical scheme, RBM can provide results at any point in time within the model domain. We develop a proof of concept for locations in the river network where local impacts such as mixing zones may be important. Simulated results from the semi-Lagrangian numerical scheme are treated as input to a finite difference model of the two-dimensional diffusion equation for water quality constituents such as water temperature or toxic substances. Simulations will provide time-dependent, two-dimensional constituent concentration in the near-field in response to long-term basin-wide processes. These results could provide decision support to water quality managers for evaluating mixing zone characteristics.

Analysis and Experimental Investigation of Optimum Design of Thermoelectric Cooling/Heating System for Car Seat Climate Control (CSCC)

NASA Astrophysics Data System (ADS)

Elarusi, Abdulmunaem; Attar, Alaa; Lee, HoSung

2018-02-01

The optimum design of a thermoelectric system for application in car seat climate control has been modeled and its performance evaluated experimentally. The optimum design of the thermoelectric device combining two heat exchangers was obtained by using a newly developed optimization method based on the dimensional technique. Based on the analytical optimum design results, commercial thermoelectric cooler and heat sinks were selected to design and construct the climate control heat pump. This work focuses on testing the system performance in both cooling and heating modes to ensure accurate analytical modeling. Although the analytical performance was calculated using the simple ideal thermoelectric equations with effective thermoelectric material properties, it showed very good agreement with experiment for most operating conditions.

Controls on the Archean climate system investigated with a global climate model.

PubMed

Wolf, E T; Toon, O B

2014-03-01

The most obvious means of resolving the faint young Sun paradox is to invoke large quantities of greenhouse gases, namely, CO2 and CH4. However, numerous changes to the Archean climate system have been suggested that may have yielded additional warming, thus easing the required greenhouse gas burden. Here, we use a three-dimensional climate model to examine some of the factors that controlled Archean climate. We examine changes to Earth's rotation rate, surface albedo, cloud properties, and total atmospheric pressure following proposals from the recent literature. While the effects of increased planetary rotation rate on surface temperature are insignificant, plausible changes to the surface albedo, cloud droplet number concentrations, and atmospheric nitrogen inventory may each impart global mean warming of 3-7 K. While none of these changes present a singular solution to the faint young Sun paradox, a combination can have a large impact on climate. Global mean surface temperatures at or above 288 K could easily have been maintained throughout the entirety of the Archean if plausible changes to clouds, surface albedo, and nitrogen content occurred.

Simulation of Water-Surface Elevations and Velocity Distributions at the U.S. Highway 13 Bridge over the Tar River at Greenville, North Carolina, Using One- and Two-Dimensional Steady-State Hydraulic Models

USGS Publications Warehouse

Wagner, Chad R.

2007-01-01

The use of one-dimensional hydraulic models currently is the standard method for estimating velocity fields through a bridge opening for scour computations and habitat assessment. Flood-flow contraction through bridge openings, however, is hydrodynamically two dimensional and often three dimensional. Although there is awareness of the utility of two-dimensional models to predict the complex hydraulic conditions at bridge structures, little guidance is available to indicate whether a one- or two-dimensional model will accurately estimate the hydraulic conditions at a bridge site. The U.S. Geological Survey, in cooperation with the North Carolina Department of Transportation, initiated a study in 2004 to compare one- and two-dimensional model results with field measurements at complex riverine and tidal bridges in North Carolina to evaluate the ability of each model to represent field conditions. The field data consisted of discharge and depth-averaged velocity profiles measured with an acoustic Doppler current profiler and surveyed water-surface profiles for two high-flow conditions. For the initial study site (U.S. Highway 13 over the Tar River at Greenville, North Carolina), the water-surface elevations and velocity distributions simulated by the one- and two-dimensional models showed appreciable disparity in the highly sinuous reach upstream from the U.S. Highway 13 bridge. Based on the available data from U.S. Geological Survey streamgaging stations and acoustic Doppler current profiler velocity data, the two-dimensional model more accurately simulated the water-surface elevations and the velocity distributions in the study reach, and contracted-flow magnitudes and direction through the bridge opening. To further compare the results of the one- and two-dimensional models, estimated hydraulic parameters (flow depths, velocities, attack angles, blocked flow width) for measured high-flow conditions were used to predict scour depths at the U.S. Highway 13 bridge by using established methods. Comparisons of pier-scour estimates from both models indicated that the scour estimates from the two-dimensional model were as much as twice the depth of the estimates from the one-dimensional model. These results can be attributed to higher approach velocities and the appreciable flow angles at the piers simulated by the two-dimensional model and verified in the field. Computed flood-frequency estimates of the 10-, 50-, 100-, and 500-year return-period floods on the Tar River at Greenville were also simulated with both the one- and two-dimensional models. The simulated water-surface profiles and velocity fields of the various return-period floods were used to compare the modeling approaches and provide information on what return-period discharges would result in road over-topping and(or) pressure flow. This information is essential in the design of new and replacement structures. The ability to accurately simulate water-surface elevations and velocity magnitudes and distributions at bridge crossings is essential in assuring that bridge plans balance public safety with the most cost-effective design. By compiling pertinent bridge-site characteristics and relating them to the results of several model-comparison studies, the framework for developing guidelines for selecting the most appropriate model for a given bridge site can be accomplished.

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

Steiner, J.L.; Lime, J.F.; Elson, J.S.

One dimensional TRAC transient calculations of the process inherent ultimate safety (PIUS) advanced reactor design were performed for a pump-trip SCRAM. The TRAC calculations showed that the reactor power response and shutdown were in qualitative agreement with the one-dimensional analyses presented in the PIUS Preliminary Safety Information Document (PSID) submitted by Asea Brown Boveri (ABB) to the US Nuclear Regulatory Commission for preapplication safety review. The PSID analyses were performed with the ABB-developed RIGEL code. The TRAC-calculated phenomena and trends were also similar to those calculated with another one-dimensional PIUS model, the Brookhaven National Laboratory developed PIPA code. A TRACmore » pump-trip SCRAM transient has also been calculated with a TRAC model containing a multi-dimensional representation of the PIUS intemal flow structures and core region. The results obtained using the TRAC fully one-dimensional PIUS model are compared to the RIGEL, PIPA, and TRAC multi-dimensional results.« less

The ARM Climate Research Facility - New Capabilities and the Expected Impacts on Climate Science and Modeling

NASA Astrophysics Data System (ADS)

Voyles, J.; Mather, J. H.

2010-12-01

The ARM Climate Research Facility is a Department of Energy national scientific user facility. Research sites include fixed and mobile facilities, which collect research quality data for climate research. Through the American Recovery and Reinvestment Act of 2009, the U.S. Department of Energy’s Office of Science allocated $60 million to the ARM Climate Research Facility for the purchase of instruments and improvement of research sites. With these funds, ARM is in the process of deploying a broad variety of new instruments that will greatly enhance the measurement capabilities of the facility. New instruments being purchased include dual-frequency scanning cloud radars, scanning precipitation radars, Doppler lidars, a mobile Aerosol Observing System and many others. A list of instruments being purchased is available at http://www.arm.gov/about/recovery-act. Orders for all instruments have now been placed and activities are underway to integrate these new systems with our research sites. The overarching goal is to provide instantaneous and statistical measurements of the climate that can be used to advance the physical understanding and predictive performance of climate models. The Recovery Act investments enable the ARM Climate Research Facility to enhance existing and add new measurements, which enable a more complete understanding of the 3-dimensional evolution of cloud processes and related atmospheric properties. Understanding cloud processes are important globally, to reduce climate-modeling uncertainties and help improve our nation’s ability to manage climate impacts. Domer Plot of W-Band Reflectivity

Effects of Implementing Subgrid-Scale Cloud-Radiation Interactions in a Regional Climate Model

NASA Astrophysics Data System (ADS)

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.

The effect of the solar rotational irradiance variation on the middle and upper atmosphere calculated by a three-dimensional chemistry-climate model

NASA Astrophysics Data System (ADS)

Gruzdev, A. N.; Schmidt, H.; Brasseur, G. P.

2009-01-01

This paper analyzes the effects of the solar rotational (27-day) irradiance variations on the chemical composition and temperature of the stratosphere, mesosphere and lower thermosphere as simulated by the three-dimensional chemistry-climate model HAMMONIA. Different methods are used to analyze the model results, including high resolution spectral and cross-spectral techniques. To force the simulations, an idealized irradiance variation with a constant period of 27 days (apparent solar rotation period) and with constant amplitude is used. While the calculated thermal and chemical responses are very distinct and permanent in the upper atmosphere, the responses in the stratosphere and mesosphere vary considerably in time despite the constant forcing. The responses produced by the model exhibit a non-linear behavior: in general, the response sensitivities (not amplitudes) decrease with increasing amplitude of the forcing. In the extratropics the responses are, in general, seasonally dependent with frequently stronger sensitivities in winter than in summer. Amplitude and phase lag of the ozone response in the tropical stratosphere and lower mesosphere are in satisfactory agreement with available observations. The agreement between the calculated and observed temperature response is generally worse than in the case of ozone.

A new method for probabilistic assessment of regional climate impacts in dependence of cumulative GHG emission budgets

NASA Astrophysics Data System (ADS)

Frieler, Katja; Meinshausen, Malte; Braun, Nadine; Hare, Bill

2010-05-01

Given the expected and already observed impacts of climate change there is growing agreement that global mean temperature rise should be limited to below 2 or 1.5 degrees. The translation of such a temperature target into guidelines for global emission reduction over the coming decades has become one of the most important and urgent tasks. In fact, there are four recent studies (Meinshausen et al. 2009, Allen et al. 2009, Matthews et al. 2009 and Zickfeld et al. 2009) which take a very comprehensive approach to quantifying the current uncertainties related to the question of what are the "allowed amounts" of global emissions given specific limits of global warming. Here, we present an extension of this budget approach allowing to focus on specific regional impacts. The method is based on probabilistic projections of regional temperature and precipitation changes providing the input for available impact functions. Using the example of Greenland's surface mass balance (Gregory et al., 2006) we will demonstrate how the probability of specific impacts can be described in dependence of global GHG emission budgets taking into account the uncertainty of global mean temperature projections as well as uncertainties of regional climate patterns varying from AOGCM to AOGCM. The method utilizes the AOGCM based linear relation between global mean temperature changes and regionally averaged changes in temperature and precipitation. It allows to handle the variations of regional climate projections from AR4 AOGCM runs independent of the uncertainties of global mean temperature change that are estimated by a simple climate model (Meinshausen et al., 2009). While the linearity of this link function is already established for temperature and to a lesser degree (depending on the region) also for precipitation (Santer et al. 1990; Mitchell et al. 1999; Giorgi et al., 2008; Solomon et al., 2009), we especially focus on the quantification of the uncertainty (in particularly the inter-AOGCM variations) of the associated scaling coefficients. Our approach is based on a linear mixed effects model (e.g. Bates and Pinheiro, 2001). In comparison to other scaling approaches we do not fit separate models for the temperature and precipitation data but we apply a two-dimensional model, i.e., we explicitly account for the fact that models (scenarios or runs) showing an especially high temperature increase may also show high precipitation increases or vice versa. Coupling the two-dimensional distribution of the scaling coefficients with the uncertainty distributions of global mean temperature change given different GHG emission trajectories finally provides time series of two dimensional uncertainty distributions of regional changes in temperature and precipitation, where both components might be correlated. These samples provide the input for regional specific impact functions. In case of Greenland we use a function by Gregory et al., 2006 that allows us to calculate changes in sea level rise due to changes in Greenland's surface mass balance in dependence of regionally averaged changes in temperature and precipitation. The precipitation signal turns out to be relatively strong for Greenland with AOGCMs consistently showing increasing precipitation with increasing global mean temperature. In addition, temperature and precipitation increases turned out to be highly correlated for Greenland: Models showing an especially high temperature increase also show high precipitation increases reflected by a correlation coefficient of 0.88 for the inter-model variations of both components of the scaling coefficients. Taking these correlations into account is especially important because the surface mass balance of the Greenland ice sheet critically depends on the interaction of the temperature and precipitation component of climate change: Increasing precipitation may at least partly balance the loss due to increasing temperatures.

Entanglement Area Law in Disordered Free Fermion Anderson Model in One, Two, and Three Dimensions

DOE PAGES

Pouranvari, Mohammad; Zhang, Yuhui; Yang, Kun

2015-01-01

We calculate numerically the entanglement entropy of free fermion ground states in one-, two-, and three-dimensional Anderson models and find that it obeys the area law as long as the linear size of the subsystem is sufficiently larger than the mean free path. This result holds in the metallic phase of the three-dimensional Anderson model, where the mean free path is finite although the localization length is infinite. Relation between the present results and earlier ones on area law violation in special one-dimensional models that support metallic phases is discussed.

Entanglement Area Law in Disordered Free Fermion Anderson Model in One, Two, and Three Dimensions

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

Pouranvari, Mohammad; Zhang, Yuhui; Yang, Kun

We calculate numerically the entanglement entropy of free fermion ground states in one-, two-, and three-dimensional Anderson models and find that it obeys the area law as long as the linear size of the subsystem is sufficiently larger than the mean free path. This result holds in the metallic phase of the three-dimensional Anderson model, where the mean free path is finite although the localization length is infinite. Relation between the present results and earlier ones on area law violation in special one-dimensional models that support metallic phases is discussed.

A new two-Dimensional Physical Basis for the Complementary Relation Between Terrestrial and pan Evaporation

NASA Astrophysics Data System (ADS)

Pettijohn, J. C.; Salvucci, G. D.

2008-12-01

Archived global measurements of water loss from evaporation pans constitute an important indirect measure of evaporative flux. Historical data from evaporation pans shows a decreasing trend over the last half century, but the relationship between pan evaporation and moisture-limited terrestrial evaporation is complex, leading to ambiguities in the interpretation of this data. Under energy-limited conditions, pan evaporation (Epan) and moisture-limited terrestrial evaporation (E) increase or decrease together, while in moisture- limited conditions these fluxes form a complementary relation in which increases in one rate accompany decreases in the other. This has lead to debate about the meaning of the observed trends in the context of changing climate. Here a two-dimensional numerical model of a wet pan in a drying landscape is used to demonstrate that, over a wide range of realistic atmospheric and surface conditions, the influence that changes in E have on Epan (1) are complementary and linear, (2) do not depend upon surface wind speed, and (3) are strikingly asymmetrical, in that a unit decrease in E causes approximately a five-fold increase in Epan, as found in a recent analysis of daily evaporation from US grasslands (Kahler and Brutsaert, 2006). Previous attempts to explain the CR have been based on one dimensional diffusion and energy balance arguments, leading to analytic solutions based on Penman-type bulk difference equations. But without acknowledging the spatially complex multidimensional humidity and temperature field around the pan, and specifically how these fields change as the contrast between the wet pan and the drying land surface increases, such integrated bulk difference equations are a priori incomplete (they ignore important divergence terms), and thus these explanations must be considered physically incomplete. Results of the present study improve the theoretical foundation of the CR, thus increasing the reliability with which it can be applied to estimate water balance and to understand the pan evaporation record of climate change.

Ab initio quantum mechanical calculation of the reaction probability for the Cl-+PH2Cl→ClPH2+Cl- reaction

NASA Astrophysics Data System (ADS)

Farahani, Pooria; Lundberg, Marcus; Karlsson, Hans O.

2013-11-01

The SN2 substitution reactions at phosphorus play a key role in organic and biological processes. Quantum molecular dynamics simulations have been performed to study the prototype reaction Cl-+PH2Cl→ClPH2+Cl-, using one and two-dimensional models. A potential energy surface, showing an energy well for a transition complex, was generated using ab initio electronic structure calculations. The one-dimensional model is essentially reflection free, whereas the more realistic two-dimensional model displays involved resonance structures in the reaction probability. The reaction rate is almost two orders of magnitude smaller for the two-dimensional compared to the one-dimensional model. Energetic errors in the potential energy surface is estimated to affect the rate by only a factor of two. This shows that for these types of reactions it is more important to increase the dimensionality of the modeling than to increase the accuracy of the electronic structure calculation.

The impacts of oceanic deep temperature perturbations in the North Atlantic on decadal climate variability and predictability

NASA Astrophysics Data System (ADS)

Germe, Agathe; Sévellec, Florian; Mignot, Juliette; Fedorov, Alexey; Nguyen, Sébastien; Swingedouw, Didier

2017-12-01

Decadal climate predictability in the North Atlantic is largely related to ocean low frequency variability, whose sensitivity to initial conditions is not very well understood. Recently, three-dimensional oceanic temperature anomalies optimally perturbing the North Atlantic Mean Temperature (NAMT) have been computed via an optimization procedure using a linear adjoint to a realistic ocean general circulation model. The spatial pattern of the identified perturbations, localized in the North Atlantic, has the largest magnitude between 1000 and 4000 m depth. In the present study, the impacts of these perturbations on NAMT, on the Atlantic meridional overturning circulation (AMOC), and on climate in general are investigated in a global coupled model that uses the same ocean model as was used to compute the three-dimensional optimal perturbations. In the coupled model, these perturbations induce AMOC and NAMT anomalies peaking after 5 and 10 years, respectively, generally consistent with the ocean-only linear predictions. To further understand their impact, their magnitude was varied in a broad range. For initial perturbations with a magnitude comparable to the internal variability of the coupled model, the model response exhibits a strong signature in sea surface temperature and precipitation over North America and the Sahel region. The existence and impacts of these ocean perturbations have important implications for decadal prediction: they can be seen either as a source of predictability or uncertainty, depending on whether the current observing system can detect them or not. In fact, comparing the magnitude of the imposed perturbations with the uncertainty of available ocean observations such as Argo data or ocean state estimates suggests that only the largest perturbations used in this study could be detectable. This highlights the importance for decadal climate prediction of accurate ocean density initialisation in the North Atlantic at intermediate and greater depths.

Theoretical constraints on oxygen and carbon dioxide concentrations in the Precambrian atmosphere

NASA Technical Reports Server (NTRS)

Kasting, J. F.

1987-01-01

Simple (one-dimensional) climate models suggest that carbon dioxide concentrations during the Archean must have been at least 100-1000 times the present level to keep the Earth's surface temperature above freezing in the face of decreased solar luminosity. Such models provide only lower bounds on CO2, so it is possible that CO2 levels were substantially higher than this and that the Archean climate was much warmer than today. Periods of extensive glaciation during the early and late Proterozoic, on the other hand, indicate that the climate at these times was relatively cool. To be consistent with climate models CO2 partial pressures must have declined from approximately 0.03 to 0.3 bar around 2.5 Ga ago to between 10(-3) and 10(-2) bar at 0.8 Ga ago. This steep decrease in carbon dioxide concentrations may be inconsistent with paleosol data, which implies that pCO2 did not change appreciably during that time. Oxygen was essentially absent from the Earth's atmosphere and oceans prior to the emergence of a photosynthetic source, probably during the late Archean. During the early Proterozoic the atmosphere and surface ocean were apparently oxidizing, while the deep ocean remained reducing. An upper limit of 6 x 10(-3) bar for pO2 at this time can be derived by balancing the burial rate of organic carbon with the rate of oxidation of ferrous iron in the deep ocean. The establishment of oxidizing conditions in the deep ocean, marked by the disappearance of banded iron formations approximately 1.7 Ga ago, permitted atmospheric oxygen to climb to its present level. O2 concentrations may have remained substantially lower than today, however, until well into the Phanerozoic.

A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier

NASA Astrophysics Data System (ADS)

Strigaro, Daniele; Moretti, Massimiliano; Mattavelli, Matteo; Frigerio, Ivan; Amicis, Mattia De; Maggi, Valter

2016-09-01

The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model, is developed in a GRASS GIS (GRASS Development Team, 2016) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change.

A large-scale simulation of climate change effects on flood regime - A case study for the Alabama-Coosa-Tallapoosa River Basin

NASA Astrophysics Data System (ADS)

Dullo, T. T.; Gangrade, S.; Marshall, R.; Islam, S. R.; Ghafoor, S. K.; Kao, S. C.; Kalyanapu, A. J.

2017-12-01

The damage and cost of flooding are continuously increasing due to climate change and variability, which compels the development and advance of global flood hazard models. However, due to computational expensiveness, evaluation of large-scale and high-resolution flood regime remains a challenge. The objective of this research is to use a coupled modeling framework that consists of a dynamically downscaled suite of eleven Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models, a distributed hydrologic model called DHSVM, and a computational-efficient 2-dimensional hydraulic model called Flood2D-GPU to study the impacts of climate change on flood regime in the Alabama-Coosa-Tallapoosa (ACT) River Basin. Downscaled meteorologic forcings for 40 years in the historical period (1966-2005) and 40 years in the future period (2011-2050) were used as inputs to drive the calibrated DHSVM to generate annual maximum flood hydrographs. These flood hydrographs along with 30-m resolution digital elevation and estimated surface roughness were then used by Flood2D-GPU to estimate high-resolution flood depth, velocities, duration, and regime. Preliminary results for the Conasauga river basin (an upper subbasin within ACT) indicate that seven of the eleven climate projections show an average increase of 25 km2 in flooded area (between historic and future projections). Future work will focus on illustrating the effects of climate change on flood duration and area for the entire ACT basin.

Simple energy balance model resolving the seasons and the continents - Application to the astronomical theory of the ice ages

NASA Technical Reports Server (NTRS)

North, G. R.; Short, D. A.; Mengel, J. G.

1983-01-01

An analysis is undertaken of the properties of a one-level seasonal energy balance climate model having explicit, two-dimensional land-sea geography, where land and sea surfaces are strictly distinguished by the local thermal inertia employed and transport is governed by a smooth, latitude-dependent diffusion mechanism. Solutions of the seasonal cycle for the cases of both ice feedback exclusion and inclusion yield good agreements with real data, using minimal turning of the adjustable parameters. Discontinuous icecap growth is noted for both a solar constant that is lower by a few percent and a change of orbital elements to favor cool Northern Hemisphere summers. This discontinuous sensitivity is discussed in the context of the Milankovitch theory of the ice ages, and the associated branch structure is shown to be analogous to the 'small ice cap' instability of simpler models.

Modelling of Titan's middle atmosphere with the IPSL climate model

NASA Astrophysics Data System (ADS)

Vatant d'Ollone, Jan; Lebonnois, Sébastien; Guerlet, Sandrine

2017-04-01

Titan's 3-dimensional Global Climate Model developed at the Institute Pierre-Simon Laplace has already demonstrated its efficiency to reproduce and interpret many features of the Saturnian moon's climate (e.g. Lebonnois et al., 2012). However, it suffered from limits at the top of the model, with temperatures far warmer than the observations and no stratopause simulated. To interpret Cassini's overall observations of seasonal effects in the middle atmosphere (e.g. Vinatier et al., 2015), a satisfying modelling of the temperature profile in this region was first required. Latest developments in the GCM now enable a correct modelling of the temperature profile in the middle atmosphere. In particular, a new, more flexible, radiative transfer scheme based on correlated-k method has been set up, using up-to-date spectroscopic data. Special emphasis is put on the too warm upper stratospheric temperatures in the former model that were due to the absence of the infrared ν4 methane line (7.7 μm) in the radiative transfer. While it was usually neglected in the tropospheric radiative models, this line has a strong cooling effect in Titan's stratospheric conditions and cannot be neglected. In this new version of the GCM, the microphysical model is temporarily switched off and we use a mean profile for haze opacity (Lavvas et al., 2010). The circulation in the middle atmosphere is significantly improved by this new radiative transfer. The new 3-D simulations also show an interesting feature in the modeled vertical profile of the zonal wind as the minimum in low stratosphere is now closer to the observations. Works in progress such as the vertical extension and the computation of the radiative effect of the seasonal variations of trace components will also be presented. - Lavvas P. et al., 2010. Titan's vertical aerosol structure at the Huygens landing site: Constraints on particle size, density, charge, and refractive index. Icarus 210, 832-842. - Lebonnois S. et al., 2012. Titan Global Climate Model: new 3-dimensional version of the IPSL Titan GCM. Icarus 218, 707-722. - Vinatier S. et al., 2015. Seasonal variations in Titan's middle atmosphere during the northern spring derived from Cassini/CIRS observations. Icarus 250, 95-115.

An aerobic scope-based habitat suitability index for predicting the effects of multi-dimensional climate change stressors on marine teleosts

NASA Astrophysics Data System (ADS)

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.

Forecasting the forest and the trees: consequences of drought in competitive forests

NASA Astrophysics Data System (ADS)

Clark, J. S.

2015-12-01

Models that translate individual tree responses to distribution and abundance of competing populations are needed to understand forest vulnerability to drought. Currently, biodiversity predictions rely on one scale or the other, but do not combine them. Synthesis is accomplished here by modeling data together, each with their respective scale-dependent connections to the scale needed for prediction—landscape to regional biodiversity. The approach we summarize integrates three scales, i) individual growth, reproduction, and survival, ii) size-species structure of stands, and iii) regional forest biomass. Data include 24,347 USDA Forest Inventory and Analysis (FIA) plots and 135 Long-term Forest Demography plots. Climate, soil moisture, and competitive interactions are predictors. We infer and predict the four-dimensional size/species/space/time (SSST) structure of forests, where all demographic rates respond to winter temperature, growing season length, moisture deficits, local moisture status, and competition. Responses to soil moisture are highly non-linear and not strongly related to responses to climatic moisture deficits over time. In the Southeast the species that are most sensitive to drought on dry sites are not the same as those that are most sensitive on moist sites. Those that respond most to spatial moisture gradients are not the same as those that respond most to regional moisture deficits. There is little evidence of simple tradeoffs in responses. Direct responses to climate constrain the ranges of few tree species, north or south; there is little evidence that range limits are defined by fecundity or survival responses to climate. By contrast, recruitment and the interactions between competition and drought that affect growth and survival are predicted to limit ranges of many species. Taken together, results suggest a rich interaction involving demographic responses at all size classes to neighbors, landscape variation in moisture, and regional climate change.

Does The Earth Have an Adaptive Infrared Iris?

NASA Technical Reports Server (NTRS)

Lindzen, Richard S.; Chou, Ming-Dah; Hou, Arthur

2000-01-01

Observations and analyses of water vapor and clouds in the tropics over the past decade suggest a different approach to radiative climate feedbacks: namely, that high clouds and high free-tropospheric relative humidity are largely tied to each other, and that the main feedback consists in changing the relative areas of cloudy/moist regions vis a vis clear/dry regions in response to the surface temperature of the cloudy/moist regions - as opposed to altering the humidity in either of the regions. This is an intrinsically 2-dimensional (horizontal and vertical) effect which does not readily enter simple 1-dimensional (vertical) radiative-convective schemes which emphasize average humidity, etc. Preliminary analyses of cloud data for the eastern part of the Western Pacific from the Japanese GMS-5(Geostationary Meteorological Satellite), are supportive of this suggestion - pointing to a 15% reduction in cloudy/moist area for a 1C increase of the sea surface temperature as measured by the cloud-weighted SST (sea surface temperature). The implication of this result is examined using a simple 2-dimensional radiative-convective model. The calculations show that such a change in the tropics would lead to a strong negative feedback in the global climate, with a feedback factor of about -1.7, which, if correct, would easily dominate the positive water vapor feedback found in current models. This new feedback mechanism, in effect, constitutes an adaptive infrared iris that opens and closes in order to control the OLR (outgoing longwave radiation) in response to changes in surface temperature in a manner similar to the way in which an eye's iris opens and closes in response to changing light levels. The climate sensitivity resulting from this thermostatic mechanism is consistent with the independent determination by Lindzen and Giannitisis (1998). Preliminary attempts to replicate observations with GCMs (General Circulation Models) suggest that models lack such a negative cloud/moist areal feedback.

A flexible climate model for use in integrated assessments

NASA Astrophysics Data System (ADS)

Sokolov, A. P.; Stone, P. H.

Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model's sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO2 are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM for a variety of transient forcing scenarios. Both surface warming and sea level rise due to thermal expansion of the deep ocean in response to a gradually increasing forcing are reasonably reproduced on time scales of 100-150 y. However a wide range of diffusion coefficients is needed to match the behavior of different AOGCMs. We use results of simulations with the 2-D model to show that the impact on climate change of the implied uncertainty in the rate of heat penetration into the deep ocean is comparable with that of other significant uncertainties.

Examining the Performance of Statistical Downscaling Methods: Toward Matching Applications to Data Products

NASA Astrophysics Data System (ADS)

Dixon, K. W.; Lanzante, J. R.; Adams-Smith, D.

2017-12-01

Several challenges exist when seeking to use future climate model projections in a climate impacts study. A not uncommon approach is to utilize climate projection data sets derived from more than one future emissions scenario and from multiple global climate models (GCMs). The range of future climate responses represented in the set is sometimes taken to be indicative of levels of uncertainty in the projections. Yet, GCM outputs are deemed to be unsuitable for direct use in many climate impacts applications. GCM grids typically are viewed as being too coarse. Additionally, regional or local-scale biases in a GCM's simulation of the contemporary climate that may not be problematic from a global climate modeling perspective may be unacceptably large for a climate impacts application. Statistical downscaling (SD) of climate projections - a type of post-processing that uses observations to inform the refinement of GCM projections - is often used in an attempt to account for GCM biases and to provide additional spatial detail. "What downscaled climate projection is the best one to use" is a frequently asked question, but one that is not always easy to answer, as it can be dependent on stakeholder needs and expectations. Here we present results from a perfect model experimental design illustrating how SD method performance can vary not only by SD method, but how performance can also vary by location, season, climate variable of interest, amount of projected climate change, SD configuration choices, and whether one is interested in central tendencies or the tails of the distribution. Awareness of these factors can be helpful when seeking to determine the suitability of downscaled climate projections for specific climate impacts applications. It also points to the potential value of considering more than one SD data product in a study, so as to acknowledge uncertainties associated with the strengths and weaknesses of different downscaling methods.

The Role of Remote Sensing Displays in Earth Climate and Planetary Atmospheric Research

NASA Technical Reports Server (NTRS)

DelGenio, Anthony D.; Hansen, James E. (Technical Monitor)

2001-01-01

The communities of scientists who study the Earth's climate and the atmospheres of the other planets barely overlap, but the types of questions they pose and the resulting implications for the use and interpretation of remote sensing data sets have much in common. Both seek to determine the characteristic behavior of three-dimensional fluids that also evolve in time. Climate researchers want to know how and why the general patterns that define our climate today might be different in the next century. Planetary scientists try to understand why circulation patterns and clouds on Mars, Venus, or Jupiter are different from those on Earth. Both disciplines must aggregate large amounts of data covering long time periods and several altitudes to have a representative picture of the rapidly changing atmosphere they are studying. This emphasis separates climate scientists from weather forecasters, who focus at any one time on a limited number of images. Likewise, it separates planetary atmosphere researchers from planetary geologists, who rely primarily on single images (or mosaics of images covering the globe) to study two-dimensional planetary surfaces that are mostly static over the duration of a spacecraft mission yet reveal dynamic processes acting over thousands to millions of years. Remote sensing displays are usually two-dimensional projections that capture an atmosphere at an instant in time. How scientists manipulate and display such data, how they interpret what they see, and how they thereby understand the physical processes that cause what they see, are the challenges I discuss in this chapter. I begin by discussing differences in how novices and experts in the field relate displays of data to the real world. This leads to a discussion of the use and abuse of image enhancement and color in remote sensing displays. I then show some examples of techniques used by scientists in climate and planetary research to both convey information and design research strategies using remote sensing displays.

Simple relationship between the virial-route hypernetted-chain and the compressibility-route Percus-Yevick values of the fourth virial coefficient.

PubMed

Santos, Andrés; Manzano, Gema

2010-04-14

As is well known, approximate integral equations for liquids, such as the hypernetted chain (HNC) and Percus-Yevick (PY) theories, are in general thermodynamically inconsistent in the sense that the macroscopic properties obtained from the spatial correlation functions depend on the route followed. In particular, the values of the fourth virial coefficient B(4) predicted by the HNC and PY approximations via the virial route differ from those obtained via the compressibility route. Despite this, it is shown in this paper that the value of B(4) obtained from the virial route in the HNC theory is exactly three halves the value obtained from the compressibility route in the PY theory, irrespective of the interaction potential (whether isotropic or not), the number of components, and the dimensionality of the system. This simple relationship is confirmed in one-component systems by analytical results for the one-dimensional penetrable-square-well model and the three-dimensional penetrable-sphere model, as well as by numerical results for the one-dimensional Lennard-Jones model, the one-dimensional Gaussian core model, and the three-dimensional square-well model.

A one-dimensional with three-dimensional velocity space hybrid-PIC model of the discharge plasma in a Hall thruster

NASA Astrophysics Data System (ADS)

Shashkov, Andrey; Lovtsov, Alexander; Tomilin, Dmitry

2017-04-01

According to present knowledge, countless numerical simulations of the discharge plasma in Hall thrusters were conducted. However, on the one hand, adequate two-dimensional (2D) models require a lot of time to carry out numerical research of the breathing mode oscillations or the discharge structure. On the other hand, existing one-dimensional (1D) models are usually too simplistic and do not take into consideration such important phenomena as neutral-wall collisions, magnetic field induced by Hall current and double, secondary, and stepwise ionizations together. In this paper a one-dimensional with three-dimensional velocity space (1D3V) hybrid-PIC model is presented. The model is able to incorporate all the phenomena mentioned above. A new method of neutral-wall collisions simulation in described space was developed and validated. Simulation results obtained for KM-88 and KM-60 thrusters are in a good agreement with experimental data. The Bohm collision coefficient was the same for both thrusters. Neutral-wall collisions, doubly charged ions, and induced magnetic field were proved to stabilize the breathing mode oscillations in a Hall thruster under some circumstances.

The Effect of Host Star Spectral Energy Distribution and Ice-Albedo Feedback on the Climate of Extrasolar Planets

PubMed Central

Meadows, Victoria S.; Bitz, Cecilia M.; Pierrehumbert, Raymond T.; Joshi, Manoj M.; Robinson, Tyler D.

2013-01-01

Abstract Planetary climate can be affected by the interaction of the host star spectral energy distribution with the wavelength-dependent reflectivity of ice and snow. In this study, we explored this effect with a one-dimensional (1-D), line-by-line, radiative transfer model to calculate broadband planetary albedos as input to a seasonally varying, 1-D energy balance climate model. A three-dimensional (3-D) general circulation model was also used to explore the atmosphere's response to changes in incoming stellar radiation, or instellation, and surface albedo. Using this hierarchy of models, we simulated planets covered by ocean, land, and water-ice of varying grain size, with incident radiation from stars of different spectral types. Terrestrial planets orbiting stars with higher near-UV radiation exhibited a stronger ice-albedo feedback. We found that ice extent was much greater on a planet orbiting an F-dwarf star than on a planet orbiting a G-dwarf star at an equivalent flux distance, and that ice-covered conditions occurred on an F-dwarf planet with only a 2% reduction in instellation relative to the present instellation on Earth, assuming fixed CO2 (present atmospheric level on Earth). A similar planet orbiting the Sun at an equivalent flux distance required an 8% reduction in instellation, while a planet orbiting an M-dwarf star required an additional 19% reduction in instellation to become ice-covered, equivalent to 73% of the modern solar constant. The reduction in instellation must be larger for planets orbiting cooler stars due in large part to the stronger absorption of longer-wavelength radiation by icy surfaces on these planets in addition to stronger absorption by water vapor and CO2 in their atmospheres, which provides increased downwelling longwave radiation. Lowering the IR and visible-band surface ice and snow albedos for an M-dwarf planet increased the planet's climate stability against changes in instellation and slowed the descent into global ice coverage. The surface ice-albedo feedback effect becomes less important at the outer edge of the habitable zone, where atmospheric CO2 could be expected to be high such that it maintains clement conditions for surface liquid water. We showed that ∼3–10 bar of CO2 will entirely mask the climatic effect of ice and snow, leaving the outer limits of the habitable zone unaffected by the spectral dependence of water ice and snow albedo. However, less CO2 is needed to maintain open water for a planet orbiting an M-dwarf star than would be the case for hotter main-sequence stars. Key Words: Extrasolar planets—M stars—Habitable zone—Snowball Earth. Astrobiology 13, 715–739. PMID:23855332

The effect of host star spectral energy distribution and ice-albedo feedback on the climate of extrasolar planets.

PubMed

Shields, Aomawa L; Meadows, Victoria S; Bitz, Cecilia M; Pierrehumbert, Raymond T; Joshi, Manoj M; Robinson, Tyler D

2013-08-01

Planetary climate can be affected by the interaction of the host star spectral energy distribution with the wavelength-dependent reflectivity of ice and snow. In this study, we explored this effect with a one-dimensional (1-D), line-by-line, radiative transfer model to calculate broadband planetary albedos as input to a seasonally varying, 1-D energy balance climate model. A three-dimensional (3-D) general circulation model was also used to explore the atmosphere's response to changes in incoming stellar radiation, or instellation, and surface albedo. Using this hierarchy of models, we simulated planets covered by ocean, land, and water-ice of varying grain size, with incident radiation from stars of different spectral types. Terrestrial planets orbiting stars with higher near-UV radiation exhibited a stronger ice-albedo feedback. We found that ice extent was much greater on a planet orbiting an F-dwarf star than on a planet orbiting a G-dwarf star at an equivalent flux distance, and that ice-covered conditions occurred on an F-dwarf planet with only a 2% reduction in instellation relative to the present instellation on Earth, assuming fixed CO(2) (present atmospheric level on Earth). A similar planet orbiting the Sun at an equivalent flux distance required an 8% reduction in instellation, while a planet orbiting an M-dwarf star required an additional 19% reduction in instellation to become ice-covered, equivalent to 73% of the modern solar constant. The reduction in instellation must be larger for planets orbiting cooler stars due in large part to the stronger absorption of longer-wavelength radiation by icy surfaces on these planets in addition to stronger absorption by water vapor and CO(2) in their atmospheres, which provides increased downwelling longwave radiation. Lowering the IR and visible-band surface ice and snow albedos for an M-dwarf planet increased the planet's climate stability against changes in instellation and slowed the descent into global ice coverage. The surface ice-albedo feedback effect becomes less important at the outer edge of the habitable zone, where atmospheric CO(2) could be expected to be high such that it maintains clement conditions for surface liquid water. We showed that ∼3-10 bar of CO(2) will entirely mask the climatic effect of ice and snow, leaving the outer limits of the habitable zone unaffected by the spectral dependence of water ice and snow albedo. However, less CO(2) is needed to maintain open water for a planet orbiting an M-dwarf star than would be the case for hotter main-sequence stars.

Dynamic colloidal assembly pathways via low dimensional models

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

Yang, Yuguang; Bevan, Michael A., E-mail: mabevan@jhu.edu; Thyagarajan, Raghuram

2016-05-28

Here we construct a low-dimensional Smoluchowski model for electric field mediated colloidal crystallization using Brownian dynamic simulations, which were previously matched to experiments. Diffusion mapping is used to infer dimensionality and confirm the use of two order parameters, one for degree of condensation and one for global crystallinity. Free energy and diffusivity landscapes are obtained as the coefficients of a low-dimensional Smoluchowski equation to capture the thermodynamics and kinetics of microstructure evolution. The resulting low-dimensional model quantitatively captures the dynamics of different assembly pathways between fluid, polycrystal, and single crystals states, in agreement with the full N-dimensional data as characterizedmore » by first passage time distributions. Numerical solution of the low-dimensional Smoluchowski equation reveals statistical properties of the dynamic evolution of states vs. applied field amplitude and system size. The low-dimensional Smoluchowski equation and associated landscapes calculated here can serve as models for predictive control of electric field mediated assembly of colloidal ensembles into two-dimensional crystalline objects.« less

Photosynthetic Control of Atmospheric Carbonyl Sulfide during the Growing Season

NASA Technical Reports Server (NTRS)

Campbell, J. Elliott; Carmichael, Gregory R.; Chai, T.; Mena-Carrasco, M.; Tang, Y.; Blake, D. R.; Blake, N. J.; Vay, Stephanie A.; Collatz, G. James; Baker, I.;

VALIDITY OF A TWO-DIMENSIONAL MODEL FOR VARIABLE-DENSITY HYDRODYNAMIC CIRCULATION

EPA Science Inventory

A three-dimensional model of temperatures and currents has been formulated to assist in the analysis and interpretation of the dynamics of stratified lakes. In this model, nonlinear eddy coefficients for viscosity and conductivities are included. A two-dimensional model (one vert...

Applying machine learning methods for characterization of hexagonal prisms from their 2D scattering patterns - an investigation using modelled scattering data

NASA Astrophysics Data System (ADS)

Salawu, Emmanuel Oluwatobi; Hesse, Evelyn; Stopford, Chris; Davey, Neil; Sun, Yi

2017-11-01

Better understanding and characterization of cloud particles, whose properties and distributions affect climate and weather, are essential for the understanding of present climate and climate change. Since imaging cloud probes have limitations of optical resolution, especially for small particles (with diameter < 25 μm), instruments like the Small Ice Detector (SID) probes, which capture high-resolution spatial light scattering patterns from individual particles down to 1 μm in size, have been developed. In this work, we have proposed a method using Machine Learning techniques to estimate simulated particles' orientation-averaged projected sizes (PAD) and aspect ratio from their 2D scattering patterns. The two-dimensional light scattering patterns (2DLSP) of hexagonal prisms are computed using the Ray Tracing with Diffraction on Facets (RTDF) model. The 2DLSP cover the same angular range as the SID probes. We generated 2DLSP for 162 hexagonal prisms at 133 orientations for each. In a first step, the 2DLSP were transformed into rotation-invariant Zernike moments (ZMs), which are particularly suitable for analyses of pattern symmetry. Then we used ZMs, summed intensities, and root mean square contrast as inputs to the advanced Machine Learning methods. We created one random forests classifier for predicting prism orientation, 133 orientation-specific (OS) support vector classification models for predicting the prism aspect-ratios, 133 OS support vector regression models for estimating prism sizes, and another 133 OS Support Vector Regression (SVR) models for estimating the size PADs. We have achieved a high accuracy of 0.99 in predicting prism aspect ratios, and a low value of normalized mean square error of 0.004 for estimating the particle's size and size PADs.

A conceptual model of oceanic heat transport in the Snowball Earth scenario

NASA Astrophysics Data System (ADS)

Comeau, Darin; Kurtze, Douglas A.; Restrepo, Juan M.

2016-12-01

Geologic evidence suggests that the Earth may have been completely covered in ice in the distant past, a state known as Snowball Earth. This is still the subject of controversy, and has been the focus of modeling work from low-dimensional models up to state-of-the-art general circulation models. In our present global climate, the ocean plays a large role in redistributing heat from the equatorial regions to high latitudes, and as an important part of the global heat budget, its role in the initiation a Snowball Earth, and the subsequent climate, is of great interest. To better understand the role of oceanic heat transport in the initiation of Snowball Earth, and the resulting global ice covered climate state, the goal of this inquiry is twofold: we wish to propose the least complex model that can capture the Snowball Earth scenario as well as the present-day climate with partial ice cover, and we want to determine the relative importance of oceanic heat transport. To do this, we develop a simple model, incorporating thermohaline dynamics from traditional box ocean models, a radiative balance from energy balance models, and the more contemporary "sea glacier" model to account for viscous flow effects of extremely thick sea ice. The resulting model, consisting of dynamic ocean and ice components, is able to reproduce both Snowball Earth and present-day conditions through reasonable changes in forcing parameters. We find that including or neglecting oceanic heat transport may lead to vastly different global climate states, and also that the parameterization of under-ice heat transfer in the ice-ocean coupling plays a key role in the resulting global climate state, demonstrating the regulatory effect of dynamic ocean heat transport.

Simulation of the June 11, 2010, flood along the Little Missouri River near Langley, Arkansas, using a hydrologic model coupled to a hydraulic model

USGS Publications Warehouse

Westerman, Drew A.; Clark, Brian R.

2013-01-01

The results from the precipitation-runoff hydrologic model, the one-dimensional unsteady-state hydraulic model, and a separate two-dimensional model developed as part of a coincident study, each complement the other in terms of streamflow timing, water-surface elevations, and velocities propagated by the June 11, 2010, flood event. The simulated grids for water depth and stream velocity from each model were directly compared by subtracting the one-dimensional hydraulic model grid from the two-dimensional model grid. The absolute mean difference for the simulated water depth was 0.9 foot. Additionally, the absolute mean difference for the simulated stream velocity was 1.9 feet per second.

STABILIZING CLOUD FEEDBACK DRAMATICALLY EXPANDS THE HABITABLE ZONE OF TIDALLY LOCKED PLANETS

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

Yang Jun; Abbot, Dorian S.; Cowan, Nicolas B., E-mail: abbot@uchicago.edu

2013-07-10

The habitable zone (HZ) is the circumstellar region where a planet can sustain surface liquid water. Searching for terrestrial planets in the HZ of nearby stars is the stated goal of ongoing and planned extrasolar planet surveys. Previous estimates of the inner edge of the HZ were based on one-dimensional radiative-convective models. The most serious limitation of these models is the inability to predict cloud behavior. Here we use global climate models with sophisticated cloud schemes to show that due to a stabilizing cloud feedback, tidally locked planets can be habitable at twice the stellar flux found by previous studies.more » This dramatically expands the HZ and roughly doubles the frequency of habitable planets orbiting red dwarf stars. At high stellar flux, strong convection produces thick water clouds near the substellar location that greatly increase the planetary albedo and reduce surface temperatures. Higher insolation produces stronger substellar convection and therefore higher albedo, making this phenomenon a stabilizing climate feedback. Substellar clouds also effectively block outgoing radiation from the surface, reducing or even completely reversing the thermal emission contrast between dayside and nightside. The presence of substellar water clouds and the resulting clement surface conditions will therefore be detectable with the James Webb Space Telescope.« less

One- and Two-dimensional Solitary Wave States in the Nonlinear Kramers Equation with Movement Direction as a Variable

NASA Astrophysics Data System (ADS)

Sakaguchi, Hidetsugu; Ishibashi, Kazuya

2018-06-01

We study self-propelled particles by direct numerical simulation of the nonlinear Kramers equation for self-propelled particles. In our previous paper, we studied self-propelled particles with velocity variables in one dimension. In this paper, we consider another model in which each particle exhibits directional motion. The movement direction is expressed with a variable ϕ. We show that one-dimensional solitary wave states appear in direct numerical simulations of the nonlinear Kramers equation in one- and two-dimensional systems, which is a generalization of our previous result. Furthermore, we find two-dimensionally localized states in the case that each self-propelled particle exhibits rotational motion. The center of mass of the two-dimensionally localized state exhibits circular motion, which implies collective rotating motion. Finally, we consider a simple one-dimensional model equation to qualitatively understand the formation of the solitary wave state.

Integral formulae of the canonical correlation functions for the one dimensional transverse Ising model

NASA Astrophysics Data System (ADS)

Inoue, Makoto

2017-12-01

Some new formulae of the canonical correlation functions for the one dimensional quantum transverse Ising model are found by the ST-transformation method using a Morita's sum rule and its extensions for the two dimensional classical Ising model. As a consequence we obtain a time-independent term of the dynamical correlation functions. Differences of quantum version and classical version of these formulae are also discussed.

Integrated surface/subsurface permafrost thermal hydrology: Model formulation and proof-of-concept simulations

DOE PAGES

Painter, Scott L.; Coon, Ethan T.; Atchley, Adam L.; ...

2016-08-11

The need to understand potential climate impacts and feedbacks in Arctic regions has prompted recent interest in modeling of permafrost dynamics in a warming climate. A new fine-scale integrated surface/subsurface thermal hydrology modeling capability is described and demonstrated in proof-of-concept simulations. The new modeling capability combines a surface energy balance model with recently developed three-dimensional subsurface thermal hydrology models and new models for nonisothermal surface water flows and snow distribution in the microtopography. Surface water flows are modeled using the diffusion wave equation extended to include energy transport and phase change of ponded water. Variation of snow depth in themore » microtopography, physically the result of wind scour, is also modeled heuristically with a diffusion wave equation. The multiple surface and subsurface processes are implemented by leveraging highly parallel community software. Fully integrated thermal hydrology simulations on the tilted open book catchment, an important test case for integrated surface/subsurface flow modeling, are presented. Fine-scale 100-year projections of the integrated permafrost thermal hydrological system on an ice wedge polygon at Barrow Alaska in a warming climate are also presented. Finally, these simulations demonstrate the feasibility of microtopography-resolving, process-rich simulations as a tool to help understand possible future evolution of the carbon-rich Arctic tundra in a warming climate.« less

Modeling the defrost process in complex geometries - Part 1: Development of a one-dimensional defrost model

NASA Astrophysics Data System (ADS)

van Buren, Simon; Hertle, Ellen; Figueiredo, Patric; Kneer, Reinhold; Rohlfs, Wilko

2017-11-01

Frost formation is a common, often undesired phenomenon in heat exchanges such as air coolers. Thus, air coolers have to be defrosted periodically, causing significant energy consumption. For the design and optimization, prediction of defrosting by a CFD tool is desired. This paper presents a one-dimensional transient model approach suitable to be used as a zero-dimensional wall-function in CFD for modeling the defrost process at the fin and tube interfaces. In accordance to previous work a multi stage defrost model is introduced (e.g. [1, 2]). In the first instance the multi stage model is implemented and validated using MATLAB. The defrost process of a one-dimensional frost segment is investigated. Fixed boundary conditions are provided at the frost interfaces. The simulation results verify the plausibility of the designed model. The evaluation of the simulated defrost process shows the expected convergent behavior of the three-stage sequence.

Progress Report on SAM Reduced-Order Model Development for Thermal Stratification and Mixing during Reactor Transients

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

Hu, R.

This report documents the initial progress on the reduced-order flow model developments in SAM for thermal stratification and mixing modeling. Two different modeling approaches are pursued. The first one is based on one-dimensional fluid equations with additional terms accounting for the thermal mixing from both flow circulations and turbulent mixing. The second approach is based on three-dimensional coarse-grid CFD approach, in which the full three-dimensional fluid conservation equations are modeled with closure models to account for the effects of turbulence.

Exact solution of three-dimensional transport problems using one-dimensional models. [in semiconductor devices

NASA Technical Reports Server (NTRS)

Misiakos, K.; Lindholm, F. A.

1986-01-01

Several parameters of certain three-dimensional semiconductor devices including diodes, transistors, and solar cells can be determined without solving the actual boundary-value problem. The recombination current, transit time, and open-circuit voltage of planar diodes are emphasized here. The resulting analytical expressions enable determination of the surface recombination velocity of shallow planar diodes. The method involves introducing corresponding one-dimensional models having the same values of these parameters.

Quantifying the role of ocean initial conditions in decadal prediction

NASA Astrophysics Data System (ADS)

Matei, D.; Pohlmann, H.; Müller, W.; Haak, H.; Jungclaus, J.; Marotzke, J.

2009-04-01

The forecast skill of decadal climate predictions is investigated using two different initialization strategies. First we apply an assimilation of ocean synthesis data provided by the GECCO project (Köhl and Stammer 2008) as initial conditions for the coupled model ECHAM5/MPI-OM. The results show promising skill up to decadal time scales particularly over the North Atlantic (see also Pohlmann et al. 2009). However, mismatches between the ocean climates of GECCO and the MPI-OM model may lead to inconsistencies in the representation of water masses. Therefore, we pursue an alternative approach to the representation of the observed North Atlantic climate for the period 1948-2007. Using the same MPI-OM ocean model as in the coupled system, we perform an ensemble of four NCEP integrations. The ensemble mean temperature and salinity anomalies are then nudged into the coupled model, followed by hindcast/forecast experiments. The model gives dynamically consistent three-dimensional temperature and salinity fields, thereby avoiding the problems of model drift that were encountered when the assimilation experiment was only driven by reconstructed SSTs (Keenlyside et al. 2008, Pohlmann et al. 2009). Differences between the two assimilation approaches are discussed by comparing them with the observational data in key regions and processes, such as North Atlantic and Tropical Pacific climate, MOC variability, Subpolar Gyre variability.

A Numerical Study of Tropical Sea-Air Interactions Using a Cloud Resolving Model Coupled with an Ocean Mixed-Layer Model

NASA Technical Reports Server (NTRS)

Shie, Chung-Lin; Tao, Wei-Kuo; Johnson, Dan; Simpson, Joanne; Li, Xiaofan; Sui, Chung-Hsiung; Einaudi, Franco (Technical Monitor)

2001-01-01

Coupling a cloud resolving model (CRM) with an ocean mixed layer (OML) model can provide a powerful tool for better understanding impacts of atmospheric precipitation on sea surface temperature (SST) and salinity. The objective of this study is twofold. First, by using the three dimensional (3-D) CRM-simulated (the Goddard Cumulus Ensemble model, GCE) diabatic source terms, radiation (longwave and shortwave), surface fluxes (sensible and latent heat, and wind stress), and precipitation as input for the OML model, the respective impact of individual component on upper ocean heat and salt budgets are investigated. Secondly, a two-way air-sea interaction between tropical atmospheric climates (involving atmospheric radiative-convective processes) and upper ocean boundary layer is also examined using a coupled two dimensional (2-D) GCE and OML model. Results presented here, however, only involve the first aspect. Complete results will be presented at the conference.

Phylogeny and adaptation shape the teeth of insular mice

PubMed Central

Ledevin, Ronan; Chevret, Pascale; Ganem, Guila; Britton-Davidian, Janice; Hardouin, Emilie A.; Chapuis, Jean-Louis; Pisanu, Benoit; da Luz Mathias, Maria; Schlager, Stefan; Auffray, Jean-Christophe; Renaud, Sabrina

2016-01-01

By accompanying human travels since prehistorical times, the house mouse dispersed widely throughout the world, and colonized many islands. The origin of the travellers determined the phylogenetic source of the insular mice, which encountered diverse ecological and environmental conditions on the various islands. Insular mice are thus an exceptional model to disentangle the relative role of phylogeny, ecology and climate in evolution. Molar shape is known to vary according to phylogeny and to respond to adaptation. Using for the first time a three-dimensional geometric morphometric approach, compared with a classical two-dimensional quantification, the relative effects of size variation, phylogeny, climate and ecology were investigated on molar shape diversity across a variety of islands. Phylogeny emerged as the factor of prime importance in shaping the molar. Changes in competition level, mostly driven by the presence or absence of the wood mouse on the different islands, appeared as the second most important effect. Climate and size differences accounted for slight shape variation. This evidences a balanced role of random differentiation related to history of colonization, and of adaptation possibly related to resource exploitation. PMID:26842576

Phylogeny and adaptation shape the teeth of insular mice.

PubMed

Ledevin, Ronan; Chevret, Pascale; Ganem, Guila; Britton-Davidian, Janice; Hardouin, Emilie A; Chapuis, Jean-Louis; Pisanu, Benoit; da Luz Mathias, Maria; Schlager, Stefan; Auffray, Jean-Christophe; Renaud, Sabrina

2016-02-10

By accompanying human travels since prehistorical times, the house mouse dispersed widely throughout the world, and colonized many islands. The origin of the travellers determined the phylogenetic source of the insular mice, which encountered diverse ecological and environmental conditions on the various islands. Insular mice are thus an exceptional model to disentangle the relative role of phylogeny, ecology and climate in evolution. Molar shape is known to vary according to phylogeny and to respond to adaptation. Using for the first time a three-dimensional geometric morphometric approach, compared with a classical two-dimensional quantification, the relative effects of size variation, phylogeny, climate and ecology were investigated on molar shape diversity across a variety of islands. Phylogeny emerged as the factor of prime importance in shaping the molar. Changes in competition level, mostly driven by the presence or absence of the wood mouse on the different islands, appeared as the second most important effect. Climate and size differences accounted for slight shape variation. This evidences a balanced role of random differentiation related to history of colonization, and of adaptation possibly related to resource exploitation. © 2016 The Author(s).

Model simulations of the competing climatic effects of SO2 and CO2

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Chou, Ming-Dah

1993-01-01

Sulfur dioxide-derived cloud condensation nuclei are expected to enhance the planetary albedo, thereby cooling the planet. This effect might counteract the global warming expected from enhanced greenhouse gases. A detailed treatment of the relationship between fossil fuel burning and the SO2 effect on cloud albedo is implemented in a two-dimensional model for assessing the climate impact. Using a conservative approach, results show that the cooling induced by the SO2 emission can presently counteract 50 percent of the CO2 greenhouse warming. Since 1980, a strong warming trend has been predicted by the model: 0.15 C during the 1980-1990 period alone. The model predicts that by the year 2060 the SO2 cooling reduces climate warming by 0.5 C or 25 percent for the Intergovernmental Panel on Climate Change (IPCC) business as usual (BAU) scenario and 0.2 C or 20 percent for scenario D (for a slow pace of fossil fuel burning). The hypothesis is examined that the different responses between the Northern Hemisphere and the Southern Hemisphere can be used to validate the presence of the SO2-induced cooling.

Two-dimensional Mathematical Model of Oil-bearing Materials in Extrusion-type Transportation over Rectangular Screw Core

NASA Astrophysics Data System (ADS)

Gukasyan, A. V.; Koshevoy, E. P.; Kosachev, V. S.

2018-05-01

A comparative analysis of alternative models for plastic flow in extrusive transportation of oil-bearing materials was conducted; the research was directed at determining the function describing the screw core throughput capacity of the press (extruder). Transition from a one-dimensional model to a two-dimensional model significantly improves the mathematical model and allows using two-dimensional rheological models determining the throughput of the screw core.

Potential climatic impacts and reliability of very large-scale wind farms

NASA Astrophysics Data System (ADS)

Wang, C.; Prinn, R. G.

2010-02-01

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled substantial interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1 °C over land installations. In contrast, surface cooling exceeding 1 °C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

Potential climatic impacts and reliability of very large-scale wind farms

NASA Astrophysics Data System (ADS)

Wang, C.; Prinn, R. G.

2009-09-01

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled legitimate interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1°C over land installations. In contrast, surface cooling exceeding 1°C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

Particle orbits in two-dimensional equilibrium models for the magnetotail

NASA Technical Reports Server (NTRS)

Karimabadi, H.; Pritchett, P. L.; Coroniti, F. V.

1990-01-01

Assuming that there exist an equilibrium state for the magnetotail, particle orbits are investigated in two-dimensional kinetic equilibrium models for the magnetotail. Particle orbits in the equilibrium field are compared with those calculated earlier with one-dimensional models, where the main component of the magnetic field (Bx) was approximated as either a hyperbolic tangent or a linear function of z with the normal field (Bz) assumed to be a constant. It was found that the particle orbits calculated with the two types of models are significantly different, mainly due to the neglect of the variation of Bx with x in the one-dimensional fields.

The relationship between organizational climate and quality of chronic disease management.

PubMed

Benzer, Justin K; Young, Gary; Stolzmann, Kelly; Osatuke, Katerine; Meterko, Mark; Caso, Allison; White, Bert; Mohr, David C

2011-06-01

To test the utility of a two-dimensional model of organizational climate for explaining variation in diabetes care between primary care clinics. Secondary data were obtained from 223 primary care clinics in the Department of Veterans Affairs health care system. Organizational climate was defined using the dimensions of task and relational climate. The association between primary care organizational climate and diabetes processes and intermediate outcomes were estimated for 4,539 patients in a cross-sectional study. All data were collected from administrative datasets. The climate data were drawn from the 2007 VA All Employee Survey, and the outcomes data were collected as part of the VA External Peer Review Program. Climate data were aggregated to the facility level of analysis and merged with patient-level data. Relational climate was related to an increased likelihood of diabetes care process adherence, with significant but small effects for adherence to intermediate outcomes. Task climate was generally not shown to be related to adherence. The role of relational climate in predicting the quality of chronic care was supported. Future research should examine the mediators and moderators of relational climate and further investigate task climate. © Health Research and Educational Trust.

The Long Decay Model of One-Dimensional Projectile Motion

ERIC Educational Resources Information Center

Lattery, Mark Joseph

2008-01-01

This article introduces a research study on student model formation and development in introductory mechanics. As a point of entry, I present a detailed analysis of the Long Decay Model of one-dimensional projectile motion. This model has been articulated by Galileo ("in De Motu") and by contemporary students. Implications for instruction are…

Application of a one-dimensional model to explore the drivers and lability of carbon in the northern Gulf of Mexico

EPA Science Inventory

A one-dimensional water quality model, Gulf of Mexico Dissolved Oxygen Model (GoMDOM-1D), was developed to simulate phytoplankton, carbon, nutrients, and dissolved oxygen in Gulf of Mexico. The model was calibrated and corroborated against a comprehensive set of field observation...

Development of a numerical model to simulate groundwater flow in the shallow aquifer system of Assateague Island, Maryland and Virginia

USGS Publications Warehouse

Masterson, John P.; Fienen, Michael N.; Gesch, Dean B.; Carlson, Carl S.

2013-01-01

A three-dimensional groundwater-flow model was developed for Assateague Island in eastern Maryland and Virginia to simulate both groundwater flow and solute (salt) transport to evaluate the groundwater system response to sea-level rise. The model was constructed using geologic and spatial information to represent the island geometry, boundaries, and physical properties and was calibrated using an inverse modeling parameter-estimation technique. An initial transient solute-transport simulation was used to establish the freshwater-saltwater boundary for a final calibrated steady-state model of groundwater flow. This model was developed as part of an ongoing investigation by the U.S. Geological Survey Climate and Land Use Change Research and Development Program to improve capabilities for predicting potential climate-change effects and provide the necessary tools for adaptation and mitigation of potentially adverse impacts.

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.

Integration of Local Observations into the One Dimensional Fog Model PAFOG

NASA Astrophysics Data System (ADS)

Thoma, Christina; Schneider, Werner; Masbou, Matthieu; Bott, Andreas

2012-05-01

The numerical prediction of fog requires a very high vertical resolution of the atmosphere. Owing to a prohibitive computational effort of high resolution three dimensional models, operational fog forecast is usually done by means of one dimensional fog models. An important condition for a successful fog forecast with one dimensional models consists of the proper integration of observational data into the numerical simulations. The goal of the present study is to introduce new methods for the consideration of these data in the one dimensional radiation fog model PAFOG. First, it will be shown how PAFOG may be initialized with observed visibilities. Second, a nudging scheme will be presented for the inclusion of measured temperature and humidity profiles in the PAFOG simulations. The new features of PAFOG have been tested by comparing the model results with observations of the German Meteorological Service. A case study will be presented that reveals the importance of including local observations in the model calculations. Numerical results obtained with the modified PAFOG model show a distinct improvement of fog forecasts regarding the times of fog formation, dissipation as well as the vertical extent of the investigated fog events. However, model results also reveal that a further improvement of PAFOG might be possible if several empirical model parameters are optimized. This tuning can only be realized by comprehensive comparisons of model simulations with corresponding fog observations.

The Inhabitance Paradox: how habitability and inhabitancy are inseparable

NASA Astrophysics Data System (ADS)

Goldblatt, C.

2015-12-01

The dominant paradigm in assigning "habitability" to terrestrial planets is to define a circumstellar habitable zone: the locus of orbital radii in which the planet is neither too hot nor too cold for life as we know it. One dimensional climate models have put theoretically impressive boundaries on this: a runaway greenhouse or water loss at the inner edge (Venus), and low-latitude glaciation followed by formation of CO2 clouds at the outer edge. A cottage industry now exists to "refine" the definition of these boundaries each year to the third decimal place of an AU. Using exactly that kind of model, I'll show that the different climate states can overlap very substantially and that "snowball Earth", temperate climate and a post-runaway climate can all be stable under the same solar flux. Furthermore, the radial extent of the temperature climate band is very narrow for pure water atmospheres. The width of the habitable zone is determined by the atmospheric inventories of di-nitrogen and carbon dioxide. Yet Earth teaches us that these abundances are very heavily influenced (perhaps even controlled) by biology. This is paradoxical: the habitable zone seeks to define the region a planet should be capable of harbouring life; yet whether the planet is inhabited will determine whether the climate may be habitable at any given distance from the star. This matters, because future life detection missions may use habitable zone boundaries in mission design. A historical view of solar system exploration helps frame the problem; robotic exploration of the outer solar system revealed the un-imagined nature of the Jovian and Saturnian moons, whilst showing that the Venusian jungle died long ago. Prediction will fall to data but the unexpected may emerge. To soften that fall we should revise the paradigm of habitability to acknowledge that habitability depends on inhabitance; for life as we know it is a planetary scale--and planet dominating--phenomenon.

Reducing Our Carbon Footprint: Frontiers in Climate Forecasting (LBNL Science at the Theater)

ScienceCinema

Collins, Bill [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2018-06-07

Bill Collins directs Berkeley Lab's research dedicated to atmospheric and climate science. Previously, he headed the development of one of the leading climate models used in international studies of global warming. His work has confirmed that man-made greenhouse gases are probably the main culprits of recent warming and future warming poses very real challenges for the environment and society. A lead author of the most recent assessment of the science of climate change by the United Nations' Intergovernmental Panel on Climate Change, Collins wants to create a new kind of climate model, one that will integrate cutting-edge climate science with accurate predictions people can use to plan their lives

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.

ParCAT: A Parallel Climate Analysis Toolkit

NASA Astrophysics Data System (ADS)

Haugen, B.; Smith, B.; Steed, C.; Ricciuto, D. M.; Thornton, P. E.; Shipman, G.

2012-12-01

Climate science has employed increasingly complex models and simulations to analyze the past and predict the future of our climate. The size and dimensionality of climate simulation data has been growing with the complexity of the models. This growth in data is creating a widening gap between the data being produced and the tools necessary to analyze large, high dimensional data sets. With single run data sets increasing into 10's, 100's and even 1000's of gigabytes, parallel computing tools are becoming a necessity in order to analyze and compare climate simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools that efficiently use parallel computing techniques to narrow the gap between data set size and analysis tools. ParCAT was created as a collaborative effort between climate scientists and computer scientists in order to provide efficient parallel implementations of the computing tools that are of use to climate scientists. Some of the basic functionalities included in the toolkit are the ability to compute spatio-temporal means and variances, differences between two runs and histograms of the values in a data set. ParCAT is designed to facilitate the "heavy lifting" that is required for large, multidimensional data sets. The toolkit does not focus on performing the final visualizations and presentation of results but rather, reducing large data sets to smaller, more manageable summaries. The output from ParCAT is provided in commonly used file formats (NetCDF, CSV, ASCII) to allow for simple integration with other tools. The toolkit is currently implemented as a command line utility, but will likely also provide a C library for developers interested in tighter software integration. Elements of the toolkit are already being incorporated into projects such as UV-CDAT and CMDX. There is also an effort underway to implement portions of the CCSM Land Model Diagnostics package using ParCAT in conjunction with Python and gnuplot. ParCAT is implemented in C to provide efficient file IO. The file IO operations in the toolkit use the parallel-netcdf library; this enables the code to use the parallel IO capabilities of modern HPC systems. Analysis that currently requires an estimated 12+ hours with the traditional CCSM Land Model Diagnostics Package can now be performed in as little as 30 minutes on a single desktop workstation and a few minutes for relatively small jobs completed on modern HPC systems such as ORNL's Jaguar.

An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

NASA Astrophysics Data System (ADS)

Velázquez, J. A.; Schmid, J.; Ricard, S.; Muerth, M. J.; Gauvin St-Denis, B.; Minville, M.; Chaumont, D.; Caya, D.; Ludwig, R.; Turcotte, R.

2012-06-01

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs' members over a reference (1971-2000) and a future (2041-2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows.

Higher-order gravity in higher dimensions: geometrical origins of four-dimensional cosmology?

NASA Astrophysics Data System (ADS)

Troisi, Antonio

2017-03-01

Determining the cosmological field equations is still very much debated and led to a wide discussion around different theoretical proposals. A suitable conceptual scheme could be represented by gravity models that naturally generalize Einstein theory like higher-order gravity theories and higher-dimensional ones. Both of these two different approaches allow one to define, at the effective level, Einstein field equations equipped with source-like energy-momentum tensors of geometrical origin. In this paper, the possibility is discussed to develop a five-dimensional fourth-order gravity model whose lower-dimensional reduction could provide an interpretation of cosmological four-dimensional matter-energy components. We describe the basic concepts of the model, the complete field equations formalism and the 5-D to 4-D reduction procedure. Five-dimensional f( R) field equations turn out to be equivalent, on the four-dimensional hypersurfaces orthogonal to the extra coordinate, to an Einstein-like cosmological model with three matter-energy tensors related with higher derivative and higher-dimensional counter-terms. By considering the gravity model with f(R)=f_0R^n the possibility is investigated to obtain five-dimensional power law solutions. The effective four-dimensional picture and the behaviour of the geometrically induced sources are finally outlined in correspondence to simple cases of such higher-dimensional solutions.

The PRISM (Pliocene Palaeoclimate) reconstruction: Time for a paradigm shift

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Stoll, Danielle K.; Foley, Kevin M.; Johnson, Andrew L. A.; Williams, Mark; Riesselman, Christina

2013-01-01

Global palaeoclimate reconstructions have been invaluable to our understanding of the causes and effects of climate change, but single-temperature representations of the oceanic mixed layer for data–model comparisons are outdated, and the time for a paradigm shift in marine palaeoclimate reconstruction is overdue. The new paradigm in marine palaeoclimate reconstruction stems the loss of valuable climate information and instead presents a holistic and nuanced interpretation of multi-dimensional oceanographic processes and responses. A wealth of environmental information is hidden within the US Geological Survey's Pliocene Research,Interpretation and Synoptic Mapping (PRISM) marine palaeoclimate reconstruction, and we introduce here a plan to incorporate all valuable climate data into the next generation of PRISM products. Beyond the global approach and focus, we plan to incorporate regional climate dynamics with emphasis on processes, integrating multiple environmental proxies wherever available in order to better characterize the mixed layer, and developing a finer time slice within the Mid-Piacenzian Age of the Pliocene, complemented by underused proxies that offer snapshots into environmental conditions. The result will be a proxy-rich, temporally nested, process-oriented approach in a digital format - a relational database with geographic information system capabilities comprising a three-dimensional grid representing the surface layer, with a plethora of data in each cell.

Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

NASA Astrophysics Data System (ADS)

Guerrero, José-Luis; Pernica, Patricia; Wheater, Howard; Mackay, Murray; Spence, Chris

2017-12-01

Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere - heat-exchange fluxes - is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue - different parameter-value combinations yielding equivalent results - the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.

The Southern Ocean's role in ocean circulation and climate transients

NASA Astrophysics Data System (ADS)

Thompson, A. F.; Stewart, A.; Hines, S.; Adkins, J. F.

2017-12-01

The ventilation of deep and intermediate density classes at the surface of the Southern Ocean impacts water mass modification and the air-sea exchange of heat and trace gases, which in turn influences the global overturning circulation and Earth's climate. Zonal variability occurs along the Antarctic Circumpolar Current and the Antarctic margins related to flow-topography interactions, variations in surface boundary conditions, and exchange with northern basins. Information about these zonal variations, and their impact on mass and tracer transport, are suppressed when the overturning is depicted as a two-dimensional (depth-latitude) streamfunction. Here we present an idealized, multi-basin, time-dependent circulation model that applies residual circulation theory in the Southern Ocean and allows for zonal water mass transfer between different ocean basins. This model efficiently determines the temporal evolution of the ocean's stratification, ventilation and overturning strength in response to perturbations in the external forcing. With this model we explore the dynamics that lead to transitions in the circulation structure between multiple, isolated cells and a three-dimensional, "figure-of-eight," circulation in which traditional upper and lower cells are interleaved. The transient model is also used to support a mechanistic explanation of the hemispheric asymmetry and phase lag associated with Dansgaard-Oeschger (DO) events during the last glacial period. In particular, the 200 year lag in southern hemisphere temperatures, following a perturbation in North Atlantic deep water formation, depends critically on the migration of Southern Ocean isopycnal outcropping in response to low-latitude stratification changes. Our results provide a self-consistent dynamical framework to explain various ocean overturning transitions that have occurred over the Earth's last 100,000 years, and motivate an exploration of these mechanisms in more sophisticated climate models.

FeynArts model file for MSSM transition counterterms from DREG to DRED

NASA Astrophysics Data System (ADS)

Stöckinger, Dominik; Varšo, Philipp

2012-02-01

The FeynArts model file MSSMdreg2dred implements MSSM transition counterterms which can convert one-loop Green functions from dimensional regularization to dimensional reduction. They correspond to a slight extension of the well-known Martin/Vaughn counterterms, specialized to the MSSM, and can serve also as supersymmetry-restoring counterterms. The paper provides full analytic results for the counterterms and gives one- and two-loop usage examples. The model file can simplify combining MS¯-parton distribution functions with supersymmetric renormalization or avoiding the renormalization of ɛ-scalars in dimensional reduction. Program summaryProgram title:MSSMdreg2dred.mod Catalogue identifier: AEKR_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKR_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: LGPL-License [1] No. of lines in distributed program, including test data, etc.: 7600 No. of bytes in distributed program, including test data, etc.: 197 629 Distribution format: tar.gz Programming language: Mathematica, FeynArts Computer: Any, capable of running Mathematica and FeynArts Operating system: Any, with running Mathematica, FeynArts installation Classification: 4.4, 5, 11.1 Subprograms used: Cat Id Title Reference ADOW_v1_0 FeynArts CPC 140 (2001) 418 Nature of problem: The computation of one-loop Feynman diagrams in the minimal supersymmetric standard model (MSSM) requires regularization. Two schemes, dimensional regularization and dimensional reduction are both common but have different pros and cons. In order to combine the advantages of both schemes one would like to easily convert existing results from one scheme into the other. Solution method: Finite counterterms are constructed which correspond precisely to the one-loop scheme differences for the MSSM. They are provided as a FeynArts [2] model file. Using this model file together with FeynArts, the (ultra-violet) regularization of any MSSM one-loop Green function is switched automatically from dimensional regularization to dimensional reduction. In particular the counterterms serve as supersymmetry-restoring counterterms for dimensional regularization. Restrictions: The counterterms are restricted to the one-loop level and the MSSM. Running time: A few seconds to generate typical Feynman graphs with FeynArts.

Climate impacts on human livelihoods at 1.5° and 2° of warming

NASA Astrophysics Data System (ADS)

Lissner, Tabea

2017-04-01

The measurement of impacts of climate change on socio-economic systems remains challenging and especially multi-dimensional outcome measures remain scarce. Climate impacts can directly affect many dimensions of human livelihoods, which cannot be addressed by monetary assessments alone. Multi-dimensional measures are essential in order to understand the full range of consequences of climate change and to understand the costs that higher levels of warming may have, not only in economic terms, but also in terms of non-market impacts on human livelihood. The AHEAD framework aims at measuring "Adequate Human livelihood conditions for wEll-being And Development" in a multi-dimensional framework, allowing to focus on resources and conditions which are a requirement to attain well-being. In this contribution we build on previous implementations of AHEAD and focus on differences in climate impacts at 1.5° and 2° of warming in order to improve our understanding of the societal consequences of these different warming levels.

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

PubMed

Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

2018-05-01

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

Assessment of the Effect of Climate Change on Grain Yields in China

NASA Astrophysics Data System (ADS)

Chou, J.

2006-12-01

The paper elaborates the social background and research background; makes clear what the key scientific issues need to be resolved and where the difficulties are. In the research area of parasailing the grain yield change caused by climate change, massive works have been done both in the domestic and in the foreign. It is our upcoming work to evaluate how our countrywide climate change information provided by this pattern influence our economic and social development; and how to make related policies and countermeasures. the main idea in this paper is that the grain yield change is by no means the linear composition of social economy function effect and the climatic change function effect. This paper identifies the economic evaluation object, proposes one new concept - climate change output. The grain yields change affected by the social factors and the climatic change working together. Climate change influences the grain yields by the non ¨C linear function from both climate change and social factor changes, not only by climate change itself. Therefore, in my paper, the appraisal object is defined as: The social factors change based on actual social changing situations; under the two kinds of climate change situation, the invariable climate change situation and variable climate change situation; the difference of grain yield outputs is called " climate change output ", In order to solve this problem, we propose a method to analyze and imitate on the historical materials. Giving the condition that the climate is invariable, the social economic factor changes cause the grain yield change. However, this grain yield change is a tentative quantity index, not an actual quantity number. So we use the existing historical materials to exam the climate change output, based on the characteristic that social factor changes greater in year than in age, but the climate factor changes greater in age than in year. The paper proposes and establishes one economy - climate model (C-D-C model) to appraise the grain yield change caused by the climatic change. Also the preliminary test on this model has been done. In selection of the appraisal methods, we take the C-D production function model, which has been proved more mature in the economic research, as our fundamental model. Then, we introduce climate index (arid index) to the C-D model to develop one new model. This new model utilizes the climatic change factor in the economical model to appraise how the climatic change influence the grain yield change. The new way of appraise should have the better application prospect. The economy - climate model (The C-D-C model) has been applied on the eight Chinese regions that we divide; it has been proved satisfactory in its feasibility, rationality and the application prospect. So we can provide the theoretical fundamentals for policy-making under the more complex and uncertain climate change. Therefore, we open a new possible channel for the global climate change research moving toward the actual social, economic life.

EFDC1D - A ONE DIMENSIONAL HYDRODYNAMIC AND SEDIMENT TRANSPORT MODEL FOR RIVER AND STREAM NETWORKS: MODEL THEORY AND USERS GUIDE

EPA Science Inventory

This technical report describes the new one-dimensional (1D) hydrodynamic and sediment transport model EFDC1D. This model that can be applied to stream networks. The model code and two sample data sets are included on the distribution CD. EFDC1D can simulate bi-directional unstea...

A one-dimensional model of subsurface hillslope flow

Treesearch

Jason C. Fisher

1997-01-01

Abstract - A one-dimensional, finite difference model of saturated subsurface flow within a hillslope was developed. The model uses rainfall, elevation data, a hydraulic conductivity, and a storage coefficient to predict the saturated thickness in time and space. The model was tested against piezometric data collected in a swale located in the headwaters of the North...

More than the sum of the parts: forest climate response from joint species distribution models

Treesearch

James S. Clark; Alan E. Gelfand; Christopher W. Woodall; Kai Zhu

2014-01-01

The perceived threat of climate change is often evaluated from species distribution models that are fitted to many species independently and then added together. This approach ignores the fact that species are jointly distributed and limit one another. Species respond to the same underlying climatic variables, and the abundance of any one species can be constrained by...

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

NASA Astrophysics Data System (ADS)

Way, M. J.; Aleinov, I.; Amundsen, David S.; Chandler, M. A.; Clune, T. L.; Del Genio, A. D.; Fujii, Y.; Kelley, M.; Kiang, N. Y.; Sohl, L.; Tsigaridis, K.

2017-07-01

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a three-dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of solar system and exoplanetary terrestrial planets. Its parent model, known as ModelE2, is used to simulate modern Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions, including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (from slower to more rapid than modern Earth’s, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the solar system such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn’s moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents, we can then further expand its capabilities to those exoplanetary rocky worlds that have been discovered in the past, as well as those to be discovered in the future. We also discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

NASA Technical Reports Server (NTRS)

Way, M. J.; Aleinov, I.; Amundsen, David S.; Chandler, M. A.; Clune, T. L.; Del Genio, A.; Fujii, Y.; Kelley, M.; Kiang, N. Y.; Sohl, L.;

Optimization of the lithium/thionyl chloride battery

NASA Technical Reports Server (NTRS)

White, Ralph E.

1987-01-01

The progress which has been made in modeling the lithium/thionyl chloride cell over the past year and proposed research for the coming year are discussed. A one-dimensional mathematical model for a lithium/thionyl chloride cell has been developed and used to investigate methods of improving cell performance. During the course of the work a problem was detected with the banded solver being used. It was replaced with one more reliable. Future work may take one of two directions. The one-dimensional model could be augmented to include additional features and to investigate in more detail the cell temperature behavior, or a simplified two-dimensional model for the spirally wound design of this battery could be developed to investigate the heat flow within the cell.

One-Dimensional Harmonic Model for Biomolecules

PubMed Central

Krizan, John E.

1973-01-01

Following in spirit a paper by Rosen, we propose a one-dimensional harmonic model for biomolecules. Energy bands with gaps of the order of semi-conductor gaps are found. The method is discussed for general symmetric and periodic potential functions. PMID:4709518

Possible implications of global climate change on global lightning distributions and frequencies

NASA Technical Reports Server (NTRS)

Price, Colin; Rind, David

1994-01-01

The Goddard Institute for Space Studies (GISS) general circulation model (GCM) is used to study the possible implications of past and future climate change on global lightning frequencies. Two climate change experiments were conducted: one for a 2 x CO2 climate (representing a 4.2 degs C global warming) and one for a 2% decrease in the solar constant (representing a 5.9 degs C global cooling). The results suggest at 30% increase in global lightning activity for the warmer climate and a 24% decrease in global lightning activity for the colder climate. This implies an approximate 5-6% change in global lightning frequencies for every 1 degs C global warming/cooling. Both intracloud and cloud-to-ground frequencies are modeled, with cloud-to-ground lightning frequencies showing larger sensitivity to climate change than intracloud frequencies. The magnitude of the modeled lightning changes depends on season, location, and even time of day.

3DHYDROGEOCHEM: A 3-DIMENSIONAL MODEL OF DENSITY-DEPENDENT SUBSURFACE FLOW AND THERMAL MULTISPECIES-MULTICOMPONENT HYDROGEOCHEMICAL TRANSPORT

EPA Science Inventory

This report presents a three-dimensional finite-element numerical model designed to simulate chemical transport in subsurface systems with temperature effect taken into account. The three-dimensional model is developed to provide (1) a tool of application, with which one is able...

Determing Credibility of Regional Simulations of Future Climate

NASA Astrophysics Data System (ADS)

Mearns, L. O.

2009-12-01

Climate models have been evaluated or validated ever since they were first developed. Establishing that a climate model can reproduce (some) aspects of the current climate of the earth on various spatial and temporal scales has long been a standard procedure for providing confidence in the model's ability to simulate future climate. However, direct links between the successes and failures of models in reproducing the current climate with regard to what future climates the models simulate has been largely lacking. This is to say that the model evaluation process has been largely divorced from the projections of future climate that the models produce. This is evidenced in the separation in the Intergovernmental Panel on Climate Change (IPCC) WG1 report of the chapter on evaluation of models from the chapter on future climate projections. There has also been the assumption of 'one model, one vote, that is, that each model projection is given equal weight in any multi-model ensemble presentation of the projections of future climate. There have been various attempts at determing measures of credibility that would avoid the 'ultrademocratic' assumption of the IPCC. Simple distinctions between models were made by research such as in Giorgi and Mearns (2002), Tebaldi et al., (2005), and Greene et al., (2006). But the metrics used were rather simplistic. More ambitous means of discriminating among the quality of model simulations have been made through the production of complex multivariate metrics, but insufficent work has been produced to verify that the metrics successfully discriminate in meaningful ways. Indeed it has been suggested that we really don't know what a model must successfully model to establish confidence in its regional-scale projections (Gleckler et al., 2008). Perhaps a more process oriented regional expert judgment approach is needed to understand which errors in climate models really matter for the model's response to future forcing. Such an approach is being attempted in the North American Climate Change Assessment Program (NARCCAP) whereby multiple global models are used to drive multiple regional models for the current period and the mid-21st century over the continent. Progress in this endeavor will be reported.

The role of gap edge instabilities in setting the depth of planet gaps in protoplanetary discs

NASA Astrophysics Data System (ADS)

Hallam, P. D.; Paardekooper, S.-J.

2017-08-01

It is known that an embedded massive planet will open a gap in a protoplanetary disc via angular momentum exchange with the disc material. The resulting surface density profile of the disc is investigated for one-dimensional and two-dimensional disc models and, in agreement with previous work, it is found that one-dimensional gaps are significantly deeper than their two-dimensional counterparts for the same initial conditions. We find, by applying one-dimensional torque density distributions to two-dimensional discs containing no planet, that the excitement of the Rossby wave instability and the formation of Rossby vortices play a critical role in setting the equilibrium depth of the gap. Being a two-dimensional instability, this is absent from one-dimensional simulations and does not limit the equilibrium gap depth there. We find similar gap depths between two-dimensional gaps formed by torque density distributions, in which the Rossby wave instability is present, and two-dimensional planet gaps, in which no Rossby wave instability is present. This can be understood if the planet gap is maintained at marginal stability, even when there is no obvious Rossby wave instability present. Further investigation shows the final equilibrium gap depth is very sensitive to the form of the applied torque density distribution, and using improved one-dimensional approximations from three-dimensional simulations can go even further towards reducing the discrepancy between one- and two-dimensional models, especially for lower mass planets. This behaviour is found to be consistent across discs with varying parameters.

Changes in U.S. Regional-Scale Air Quality at 2030 Simulated Using RCP 6.0

NASA Astrophysics Data System (ADS)

Nolte, C. G.; Otte, T.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.

2012-12-01

Recent improvements in air quality in the United States have been due to significant reductions in emissions of ozone and particulate matter (PM) precursors, and these downward emissions trends are expected to continue in the next few decades. To ensure that planned air quality regulations are robust under a range of possible future climates and to consider possible policy actions to mitigate climate change, it is important to characterize and understand the effects of climate change on air quality. Recent work by several research groups using global and regional models has demonstrated that there is a "climate penalty," in which climate change leads to increases in surface ozone levels in polluted continental regions. One approach to simulating future air quality at the regional scale is via dynamical downscaling, in which fields from a global climate model are used as input for a regional climate model, and these regional climate data are subsequently used for chemical transport modeling. However, recent studies using this approach have encountered problems with the downscaled regional climate fields, including unrealistic surface temperatures and misrepresentation of synoptic pressure patterns such as the Bermuda High. We developed a downscaling methodology and showed that it now reasonably simulates regional climate by evaluating it against historical data. In this work, regional climate simulations created by downscaling the NASA/GISS Model E2 global climate model are used as input for the Community Multiscale Air Quality (CMAQ) model. CMAQ simulations over the continental United States are conducted for two 11-year time slices, one representing current climate (1995-2005) and one following Representative Concentration Pathway 6.0 from 2025-2035. Anthropogenic emissions of ozone and PM precursors are held constant at year 2006 levels for both the current and future periods. In our presentation, we will examine the changes in ozone and PM concentrations, with particular focus on exceedances of the current U.S. air quality standards, and attempt to relate the changes in air quality to the projected changes in regional climate.

Radiation transfer in plant canopies - Transmission of direct solar radiation and the role of leaf orientation

NASA Technical Reports Server (NTRS)

Verstraete, Michel M.

1987-01-01

Understanding the details of the interaction between the radiation field and plant structures is important climatically because of the influence of vegetation on the surface water and energy balance, but also biologically, since solar radiation provides the energy necessary for photosynthesis. The problem is complex because of the extreme variety of vegetation forms in space and time, as well as within and across plant species. This one-dimensional vertical multilayer model describes the transfer of direct solar radiation through a leaf canopy, accounting explicitly for the vertical inhomogeneities of a plant stand and leaf orientation, as well as heliotropic plant behavior. This model reproduces observational results on homogeneous canopies, but it is also well adapted to describe vertically inhomogeneous canopies. Some of the implications of leaf orientation and plant structure as far as light collection is concerned are briefly reviewed.

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.

Persistence in a Two-Dimensional Moving-Habitat Model.

PubMed

Phillips, Austin; Kot, Mark

2015-11-01

Environmental changes are forcing many species to track suitable conditions or face extinction. In this study, we use a two-dimensional integrodifference equation to analyze whether a population can track a habitat that is moving due to climate change. We model habitat as a simple rectangle. Our model quickly leads to an eigenvalue problem that determines whether the population persists or declines. After surveying techniques to solve the eigenvalue problem, we highlight three findings that impact conservation efforts such as reserve design and species risk assessment. First, while other models focus on habitat length (parallel to the direction of habitat movement), we show that ignoring habitat width (perpendicular to habitat movement) can lead to overestimates of persistence. Dispersal barriers and hostile landscapes that constrain habitat width greatly decrease the population's ability to track its habitat. Second, for some long-distance dispersal kernels, increasing habitat length improves persistence without limit; for other kernels, increasing length is of limited help and has diminishing returns. Third, it is not always best to orient the long side of the habitat in the direction of climate change. Evidence suggests that the kurtosis of the dispersal kernel determines whether it is best to have a long, wide, or square habitat. In particular, populations with platykurtic dispersal benefit more from a wide habitat, while those with leptokurtic dispersal benefit more from a long habitat. We apply our model to the Rocky Mountain Apollo butterfly (Parnassius smintheus).

A commentary on the Atlantic meridional overturning circulation stability in climate models

NASA Astrophysics Data System (ADS)

Gent, Peter R.

2018-02-01

The stability of the Atlantic meridional overturning circulation (AMOC) in ocean models depends quite strongly on the model formulation, especially the vertical mixing, and whether it is coupled to an atmosphere model. A hysteresis loop in AMOC strength with respect to freshwater forcing has been found in several intermediate complexity climate models and in one fully coupled climate model that has very coarse resolution. Over 40% of modern climate models are in a bistable AMOC state according to the very frequently used simple stability criterion which is based solely on the sign of the AMOC freshwater transport across 33° S. In a recent freshwater hosing experiment in a climate model with an eddy-permitting ocean component, the change in the gyre freshwater transport across 33° S is larger than the AMOC freshwater transport change. This casts very strong doubt on the usefulness of this simple AMOC stability criterion. If a climate model uses large surface flux adjustments, then these adjustments can interfere with the atmosphere-ocean feedbacks, and strongly change the AMOC stability properties. AMOC can be shut off for many hundreds of years in modern fully coupled climate models if the hosing or carbon dioxide forcing is strong enough. However, in one climate model the AMOC recovers after between 1000 and 1400 years. Recent 1% increasing carbon dioxide runs and RCP8.5 future scenario runs have shown that the AMOC reduction is smaller using an eddy-resolving ocean component than in the comparable standard 1° ocean climate models.

High resolution climate scenarios for snowmelt modelling in small alpine catchments

NASA Astrophysics Data System (ADS)

Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

2017-12-01

Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire Switzerland was used to verify snow distribution patterns at coarser spatial and temporal scale. The ability of the model chain to reproduce current climate conditions in small alpine catchments makes this model combination an outstanding candidate to produce high resolution climate scenarios of snowmelt in small alpine catchments.

On some structure-turbulence interaction problems

NASA Technical Reports Server (NTRS)

Maekawa, S.; Lin, Y. K.

1976-01-01

The interactions between a turbulent flow structure; responding to its excitation were studied. The turbulence was typical of those associated with a boundary layer, having a cross-spectral density indicative of convection and statistical decay. A number of structural models were considered. Among the one-dimensional models were an unsupported infinite beam and a periodically supported infinite beam. The fuselage construction of an aircraft was then considered. For the two-dimensional case a simple membrane was used to illustrate the type of formulation applicable to most two-dimensional structures. Both the one-dimensional and two-dimensional structures studied were backed by a cavity filled with an initially quiescent fluid to simulate the acoustic environment when the structure forms one side of a cabin of a sea vessel or aircraft.

One-Dimensional Collision Carts Computer Model and Its Design Ideas for Productive Experiential Learning

ERIC Educational Resources Information Center

Wee, Loo Kang

2012-01-01

We develop an Easy Java Simulation (EJS) model for students to experience the physics of idealized one-dimensional collision carts. The physics model is described and simulated by both continuous dynamics and discrete transition during collision. In designing the simulations, we discuss briefly three pedagogical considerations namely (1) a…

Climate change hotspots in the CMIP5 global climate model ensemble.

PubMed

Diffenbaugh, Noah S; Giorgi, Filippo

2012-01-10

We use a statistical metric of multi-dimensional climate change to quantify the emergence of global climate change hotspots in the CMIP5 climate model ensemble. Our hotspot metric extends previous work through the inclusion of extreme seasonal temperature and precipitation, which exert critical influence on climate change impacts. The results identify areas of the Amazon, the Sahel and tropical West Africa, Indonesia, and the Tibetan Plateau as persistent regional climate change hotspots throughout the 21 st century of the RCP8.5 and RCP4.5 forcing pathways. In addition, areas of southern Africa, the Mediterranean, the Arctic, and Central America/western North America also emerge as prominent regional climate change hotspots in response to intermediate and high levels of forcing. Comparisons of different periods of the two forcing pathways suggest that the pattern of aggregate change is fairly robust to the level of global warming below approximately 2°C of global warming (relative to the late-20 th -century baseline), but not at the higher levels of global warming that occur in the late-21 st -century period of the RCP8.5 pathway, with areas of southern Africa, the Mediterranean, and the Arctic exhibiting particular intensification of relative aggregate climate change in response to high levels of forcing. Although specific impacts will clearly be shaped by the interaction of climate change with human and biological vulnerabilities, our identification of climate change hotspots can help to inform mitigation and adaptation decisions by quantifying the rate, magnitude and causes of the aggregate climate response in different parts of the world.

Multimodel Estimates of Atmospheric Lifetimes of Long-lived Ozone-Depleting Substances: Present and Future

NASA Technical Reports Server (NTRS)

Chipperfield, M. P.; Liang, Q.; Strahan, S. E.; Morgenstern, O.; Dhomse, S. S.; Abraham, N. L.; Archibald, A. T.; Bekki, S.; Braesicke, P.; Di Genova, G.;

Multimodel Estimates of Atmospheric Lifetimes of Long-Lived Ozone-Depleting Substances: Present and Future

NASA Technical Reports Server (NTRS)

Chipperfield, M. P.; Liang, Q.; Strahan, S. E.; Morgenstern, O.; Dhomse, S. S.; Abraham, N. L.; Archibald, A. T.; Bekki, S.; Braesicke, P.; Di Genova, G.;

Sampling design for groundwater solute transport: Tests of methods and analysis of Cape Cod tracer test data

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.; Garabedian, Stephen P.

1991-01-01

Tests of a one-dimensional sampling design methodology on measurements of bromide concentration collected during the natural gradient tracer test conducted by the U.S. Geological Survey on Cape Cod, Massachusetts, demonstrate its efficacy for field studies of solute transport in groundwater and the utility of one-dimensional analysis. The methodology was applied to design of sparse two-dimensional networks of fully screened wells typical of those often used in engineering practice. In one-dimensional analysis, designs consist of the downstream distances to rows of wells oriented perpendicular to the groundwater flow direction and the timing of sampling to be carried out on each row. The power of a sampling design is measured by its effectiveness in simultaneously meeting objectives of model discrimination, parameter estimation, and cost minimization. One-dimensional models of solute transport, differing in processes affecting the solute and assumptions about the structure of the flow field, were considered for description of tracer cloud migration. When fitting each model using nonlinear regression, additive and multiplicative error forms were allowed for the residuals which consist of both random and model errors. The one-dimensional single-layer model of a nonreactive solute with multiplicative error was judged to be the best of those tested. Results show the efficacy of the methodology in designing sparse but powerful sampling networks. Designs that sample five rows of wells at five or fewer times in any given row performed as well for model discrimination as the full set of samples taken up to eight times in a given row from as many as 89 rows. Also, designs for parameter estimation judged to be good by the methodology were as effective in reducing the variance of parameter estimates as arbitrary designs with many more samples. Results further showed that estimates of velocity and longitudinal dispersivity in one-dimensional models based on data from only five rows of fully screened wells each sampled five or fewer times were practically equivalent to values determined from moments analysis of the complete three-dimensional set of 29,285 samples taken during 16 sampling times.

Ice Floe Breaking in Contemporary Third Generation Operational Wave Models

NASA Astrophysics Data System (ADS)

Sévigny, C.; Baudry, J.; Gauthier, J. C.; Dumont, D.

2016-02-01

The dynamical zone observed at the edge of the consolidated ice area where are found the wave-fractured floes (i.e. marginal ice zone or MIZ) has become an important topic in ocean modeling. As both operational and climate ocean models now seek to reproduce the complex atmosphere-ice-ocean system with realistic coupling processes, many theoretical and numerical studies have focused on understanding and modeling this zone. Few attempts have been made to embed wave-ice interactions specific to the MIZ within a two-dimensional model, giving the possibility to calculate both the attenuation of surface waves by sea ice and the concomitant breaking of the sea ice-cover into smaller floes. One of the first challenges consists in improving the parameterization of wave-ice dynamics in contemporary third generation operational wave models. A simple waves-in-ice model (WIM) similar to the one proposed by Williams et al. (2013a,b) was implemented in WAVEWATCH III. This WIM considers ice floes as floating elastic plates and predicts the dimensionless attenuation coefficient by the use of a lookup-table-based, wave scattering scheme. As in Dumont et al. (2011), the different frequencies are treated individually and floe breaking occurs for a particular frequency when the expected wave amplitude exceeds the allowed strain amplitude, which considers ice floes properties and wavelength in ice field. The model is here further refined and tested in idealized two-dimensional cases, giving preliminary results of the performance and sensitivity of the parameterization to initial wave and ice conditions. The effects of the wave-ice coupling over the incident wave spectrum are analyzed as well as the resulting floe size distribution. The model gives prognostic values of the lateral extent of the marginal ice zone with maximum ice floe diameter that progressively increases with distance from the ice edge.

Panel summary report

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

Gutjahr, A.L.; Kincaid, C.T.; Mercer, J.W.

1987-04-01

The objective of this report is to summarize the various modeling approaches that were used to simulate solute transport in a variably saturated emission. In particular, the technical strengths and weaknesses of each approach are discussed, and conclusions and recommendations for future studies are made. Five models are considered: (1) one-dimensional analytical and semianalytical solutions of the classical deterministic convection-dispersion equation (van Genuchten, Parker, and Kool, this report ); (2) one-dimensional simulation using a continuous-time Markov process (Knighton and Wagenet, this report); (3) one-dimensional simulation using the time domain method and the frequency domain method (Duffy and Al-Hassan, this report);more » (4) one-dimensional numerical approach that combines a solution of the classical deterministic convection-dispersion equation with a chemical equilibrium speciation model (Cederberg, this report); and (5) three-dimensional numerical solution of the classical deterministic convection-dispersion equation (Huyakorn, Jones, Parker, Wadsworth, and White, this report). As part of the discussion, the input data and modeling results are summarized. The models were used in a data analysis mode, as opposed to a predictive mode. Thus, the following discussion will concentrate on the data analysis aspects of model use. Also, all the approaches were similar in that they were based on a convection-dispersion model of solute transport. Each discussion addresses the modeling approaches in the order listed above.« less

Environmental influences on speleothem growth in southwestern Oregon during the last 380, 000 years

USGS Publications Warehouse

Ersek, Vasile; Hostetler, Steven W.; Cheng, Hai; Clark, Peter U.; Anslow, Faron S.; Mix, Alan C.; Edwards, R. Lawrence

2009-01-01

The growth of carbonate formations in caves (speleothems) is sensitive to changes in environmental conditions at the surface (temperature, precipitation and vegetation) and can provide useful paleoclimatic and paleoenvironmental information. We use 73 230Th dates from speleothems collected from a cave in southwestern Oregon (USA) to constrain speleothem growth for the past 380 000 years. Most speleothem growth occurred during interglacial periods, whereas little growth occurred during glacial intervals. To evaluate potential environmental controls on speleothem growth we use two new modeling approaches: i) a one-dimensional thermal advection–diffusion model to estimate cave temperatures during the last glacial cycle, and ii) a regional climate model simulation for the Last Glacial Maximum (21 000 years before present) that assesses a range of potential controls on speleothem growth under peak glacial conditions. The two models are mutually consistent in indicating that permafrost formation did not influence speleothem growth during glacial periods. Instead, the regional climate model simulation combined with proxy data suggest that the influence of the Laurentide and Cordilleran ice sheets on atmospheric circulation induced substantial changes in water balance in the Pacific Northwest and affected speleothem growth at our location. The overall drier conditions during glacial intervals and associated periods of frozen topsoil at times of maximum surface runoff likely induced drastic changes in cave recharge and limited speleothem growth. This mechanism could have affected speleothem growth in other mid-latitude caves without requiring the presence of permafrost.

Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

PubMed Central

Yuan, Naiming; Fu, Zuntao; Liu, Shida

2014-01-01

Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

On The Impact of Climate Change to Agricultural Productivity in East Java

NASA Astrophysics Data System (ADS)

Kuswanto, Heri; Salamah, Mutiah; Mumpuni Retnaningsih, Sri; Dwi Prastyo, Dedy

2018-03-01

Many researches showed that climate change has significant impact on agricultural sector, which threats the food security especially in developing countries. It has been observed also that the climate change increases the intensity of extreme events. This research investigated the impact climate to the agricultural productivity in East Java, as one of the main rice producers in Indonesia. Standard regression as well as panel regression models have been performed in order to find the best model which is able to describe the climate change impact. The analysis found that the fixed effect model of panel regression outperforms the others showing that climate change had negatively impacted the rice productivity in East Java. The effect in Malang and Pasuruan were almost the same, while the impact in Sumenep was the least one compared to other districts.

Estimating the impact of internal climate variability on ice sheet model simulations

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2016-12-01

Rising sea level threatens human societies and coastal habitats and melting ice sheets are a major contributor to sea level rise (SLR). Thus, understanding uncertainty of both forcing and variability within the climate system is essential for assessing long-term risk of SLR given their impact on ice sheet evolution. The predictability of polar climate is limited by uncertainties from the given forcing, the climate model response to this forcing, and the internal variability from feedbacks within the fully coupled climate system. Among those sources of uncertainty, the impact of internal climate variability on ice sheet changes has not yet been robustly assessed. Here we investigate how internal variability affects ice sheet projections using climate fields from two Community Earth System Model (CESM) large-ensemble (LE) experiments to force a three-dimensional ice sheet model. Each ensemble member in an LE experiment undergoes the same external forcings but with unique initial conditions. We find that for both LEs, 2m air temperature variability over Greenland ice sheet (GrIS) can lead to significantly different ice sheet responses. Our results show that the internal variability from two fully coupled CESM LEs can cause about 25 35 mm differences of GrIS's contribution to SLR in 2100 compared to present day (about 20% of the total change), and 100m differences of SLR in 2300. Moreover, only using ensemble-mean climate fields as the forcing in ice sheet model can significantly underestimate the melt of GrIS. As the Arctic region becomes warmer, the role of internal variability is critical given the complex nonlinear interactions between surface temperature and ice sheet. Our results demonstrate that internal variability from coupled atmosphere-ocean general circulation model can affect ice sheet simulations and the resulting sea-level projections. This study highlights an urgent need to reassess associated uncertainties of projecting ice sheet loss over the next few centuries to obtain robust estimates of the contribution of ice sheet melt to SLR.

Optimal one-dimensional inversion and bounding of magnetotelluric apparent resistivity and phase measurements

NASA Astrophysics Data System (ADS)

Parker, Robert L.; Booker, John R.

1996-12-01

The properties of the log of the admittance in the complex frequency plane lead to an integral representation for one-dimensional magnetotelluric (MT) apparent resistivity and impedance phase similar to that found previously for complex admittance. The inverse problem of finding a one-dimensional model for MT data can then be solved using the same techniques as for complex admittance, with similar results. For instance, the one-dimensional conductivity model that minimizes the χ2 misfit statistic for noisy apparent resistivity and phase is a series of delta functions. One of the most important applications of the delta function solution to the inverse problem for complex admittance has been answering the question of whether or not a given set of measurements is consistent with the modeling assumption of one-dimensionality. The new solution allows this test to be performed directly on standard MT data. Recently, it has been shown that induction data must pass the same one-dimensional consistency test if they correspond to the polarization in which the electric field is perpendicular to the strike of two-dimensional structure. This greatly magnifies the utility of the consistency test. The new solution also allows one to compute the upper and lower bounds permitted on phase or apparent resistivity at any frequency given a collection of MT data. Applications include testing the mutual consistency of apparent resistivity and phase data and placing bounds on missing phase or resistivity data. Examples presented demonstrate detection and correction of equipment and processing problems and verification of compatibility with two-dimensional B-polarization for MT data after impedance tensor decomposition and for continuous electromagnetic profiling data.

Hydrologic response of the Crow Wing Watershed, Minnesota, to mid-Holocene climate change

USGS Publications Warehouse

Person, M.; Roy, P.; Wright, H.; Gutowski, W.; Ito, E.; Winter, T.; Rosenberry, D.; Cohen, D.

2007-01-01

In this study, we have integrated a suite of Holocene paleoclimatic proxies with mathematical modeling in an attempt to obtain a comprehensive picture of how watersheds respond to past climate change. A three-dimensional surface-water-groundwater model was developed to assess the effects of mid-Holocene climate change on water resources within the Crow Wing Watershed, Upper Mississippi Basin in north central Minnesota. The model was first calibrated to a 50 yr historical record of average annual surface-water discharge, monthly groundwater levels, and lake-level fluctuations. The model was able to reproduce reasonably well long-term historical records (1949-1999) of water-table and lake-level fluctuations across the watershed as well as stream discharge near the watershed outlet. The calibrated model was then used to reproduce paleogroundwater and lake levels using climate reconstructions based on pollen-transfer functions from Williams Lake just outside the watershed. Computed declines in mid-Holocene lake levels for two lakes at opposite ends of the watershed were between 6 and 18 m. Simulated streamflow near the outlet of the watershed decreased to 70% of modern average annual discharge after ???200 yr. The area covered by wetlands for the entire watershed was reduced by ???16%. The mid-Holocene hydrologic changes indicated by these model results and corroborated by several lake-core records across the Crow Wing Watershed may serve as a useful proxy of the hydrologic response to future warm, dry climatic forecasts (ca. 2050) made by some atmospheric general-circulation models for the glaciated Midwestern United States. ?? 2007 Geological Society of America.

Linking climate change projections for an Alaskan watershed to future coho salmon production.

PubMed

Leppi, Jason C; Rinella, Daniel J; Wilson, Ryan R; Loya, Wendy M

2014-06-01

Climate change is predicted to dramatically change hydrologic processes across Alaska, but estimates of how these impacts will influence specific watersheds and aquatic species are lacking. Here, we linked climate, hydrology, and habitat models within a coho salmon (Oncorhynchus kisutch) population model to assess how projected climate change could affect survival at each freshwater life stage and, in turn, production of coho salmon smolts in three subwatersheds of the Chuitna (Chuit) River watershed, Alaska. Based on future climate scenarios and projections from a three-dimensional hydrology model, we simulated coho smolt production over a 20-year span at the end of the century (2080-2100). The direction (i.e., positive vs. negative) and magnitude of changes in smolt production varied substantially by climate scenario and subwatershed. Projected smolt production decreased in all three subwatersheds under the minimum air temperature and maximum precipitation scenario due to elevated peak flows and a resulting 98% reduction in egg-to-fry survival. In contrast, the maximum air temperature and minimum precipitation scenario led to an increase in smolt production in all three subwatersheds through an increase in fry survival. Other climate change scenarios led to mixed responses, with projected smolt production increasing and decreasing in different subwatersheds. Our analysis highlights the complexity inherent in predicting climate-change-related impacts to salmon populations and demonstrates that population effects may depend on interactions between the relative magnitude of hydrologic and thermal changes and their interactions with features of the local habitat. © 2013 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

Slow-Slip Phenomena Represented by the One-Dimensional Burridge-Knopoff Model of Earthquakes

NASA Astrophysics Data System (ADS)

Kawamura, Hikaru; Yamamoto, Maho; Ueda, Yushi

2018-05-01

Slow-slip phenomena, including afterslips and silent earthquakes, are studied using a one-dimensional Burridge-Knopoff model that obeys the rate-and-state dependent friction law. By varying only a few model parameters, this simple model allows reproducing a variety of seismic slips within a single framework, including main shocks, precursory nucleation processes, afterslips, and silent earthquakes.

Linking climate change and karst hydrology to evaluate species vulnerability: The Edwards and Madison aquifers (Invited)

NASA Astrophysics Data System (ADS)

Mahler, B. J.; Long, A. J.; Stamm, J. F.; Poteet, M.; Symstad, A.

2013-12-01

Karst aquifers present an extreme case of flow along structurally variable pathways, making them highly dynamic systems and therefore likely to respond rapidly to climate change. In turn, many biological communities and ecosystems associated with karst are sensitive to hydrologic changes. We explored how three sites in the Edwards aquifer (Texas) and two sites in the Madison aquifer (South Dakota) might respond to projected climate change from 2011 to 2050. Ecosystems associated with these karst aquifers support federally listed endangered and threatened species and state-listed species of concern, including amphibians, birds, insects, and plants. The vulnerability of selected species associated with projected climate change was assessed. The Advanced Research Weather and Research Forecasting (WRF) model was used to simulate projected climate at a 36-km grid spacing for three weather stations near the study sites, using boundary and initial conditions from the global climate model Community Climate System Model (CCSM3) and an A2 emissions scenario. Daily temperature and precipitation projections from the WRF model were used as input for the hydrologic Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model and the Climate Change Vulnerability Index (CCVI) model. RRAWFLOW is a lumped-parameter model that simulates hydrologic response at a single site, combining the responses of quick and slow flow that commonly characterize karst aquifers. CCVI uses historical and projected climate and hydrologic metrics to determine the vulnerability of selected species on the basis of species exposure to climate change, sensitivity to factors associated with climate change, and capacity to adapt to climate change. An upward trend in temperature was projected for 2011-2050 at all three weather stations; there was a trend (downward) in annual precipitation only for the weather station in Texas. A downward trend in mean annual spring flow or groundwater level was projected for all of the Edwards sites, but there was no significant trend for the Madison sites. Of 16 Edwards aquifer species evaluated (four amphibians, six arthropods, one fish, one mollusk, and four plants), 12 were scored as highly or moderately vulnerable under the projected climate change scenario. In contrast, all of the 8 Madison aquifer species evaluated (two mammals, one bird, one mollusk, and four plants) were scored as moderately vulnerable, stable, or intermediate between the two. The inclusion of hydrologic projections in the vulnerability assessment was essential for interpreting the effects of climate change on aquatic species of conservations concern, such as endemic salamanders. The linkage of climate, hydrologic, and vulnerability models provided a bridge to project the effects of global climate change on local karst aquifer and stream systems and selected species.

Using Clustering to Establish Climate Regimes from PCM Output

NASA Technical Reports Server (NTRS)

Oglesby, Robert; Arnold, James E. (Technical Monitor); Hoffman, Forrest; Hargrove, W. W.; Erickson, D.

2002-01-01

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Impact of climate change on persistent turbidity in the water supply system of a Metropolitan Area

NASA Astrophysics Data System (ADS)

Chung, S. W.; Park, H. S.; Lim, K. J.; Kang, B.

2016-12-01

Persistent turbidity, a long-term resuspension of fine particles in aquatic system, is one of the major water quality concerns for the sustainable management of water supply systems in metropolitan areas. Turbid water has undesirable aesthetic and recreational appeal and may have harmful effect on ecosystem health, in addition to increasing water treatment costs in drinking water supply systems. These concerns have been more intensified as the strength and frequency of rainfall events increase by climate change in the Asian monsoon climate region, including Korea. The aim of this study was to assess the impact of potential climate change on the persistent turbidity of the Han River systems that supplies drinking water to approximately 25 million consumers dwelling in the Seoul Metropolitan areas. A comprehensive numerical and statistical modeling suit has been developed and applied to the systems for the projection of future climate, responding hydrological and soil erosion processes in the watershed, and sediment transport processes in the rivers and reservoirs systems. The down-scaled 100 years of climatic data from General Circulation Model (HadGEM2-AO) based on the IPCC's greenhouse-gas emissions scenario RCP4.5 were used for the forcing data of the watershed and river-reservoir models. As the results, an extreme flood event that may incur significant persistent turbidity was projected to be occurred five times in the future. The threshold of a flood event that is classified as an extreme event was based on the historical flood event that occurred on July of 2006 when turbid water had persisted within the Soyang Reservoir and discharged to the downstream of the Han River systems over the year until May of the following year. A two-dimensional river and reservoir model simulated the transport and dynamics of suspended sediments in Soyang Reservoir, and routed the discharged turbid water to the downstream of Paldang Reservoir, in which most of the drinking water offtake facilities are located. The statistical features of the extreme flood events, their impact on the persistent turbidity on the downstream rivers and reservoirs, and consequently on the water supply system of the Seoul Metropolitan areas will be presented in the special session.

Determination of the spatial variability of temperature and moisture near a tropical Pacific island with MTI satellite images

NASA Astrophysics Data System (ADS)

Kurzeja, Robert J.; O'Steen, Byron L.; Pendergast, Malcolm M.

2002-01-01

The Tropical Pacific Island of Nauru is a US DOE ARM observation site that monitors tropical climate and atmospheric radiation. This observation site is ideal for validating MTI images because of the extensive deployment of continuously operating instruments. MTI images are also useful in assessing the effect of the island on the ocean climate and on the ARM data. An MTI image has been used to determine the spatial distribution of water vapor and sea-surface temperature near the island. The results are compared with a three-dimensional numerical model simulation.

On numerical modeling of one-dimensional geothermal histories

USGS Publications Warehouse

Haugerud, R.A.

1989-01-01

Numerical models of one-dimensional geothermal histories are one way of understanding the relations between tectonics and transient thermal structure in the crust. Such models can be powerful tools for interpreting geochronologic and thermobarometric data. A flexible program to calculate these models on a microcomputer is available and examples of its use are presented. Potential problems with this approach include the simplifying assumptions that are made, limitations of the numerical techniques, and the neglect of convective heat transfer. ?? 1989.

Decomposing the uncertainty in climate impact projections of Dynamic Vegetation Models: a test with the forest models LANDCLIM and FORCLIM

NASA Astrophysics Data System (ADS)

Cailleret, Maxime; Snell, Rebecca; von Waldow, Harald; Kotlarski, Sven; Bugmann, Harald

2015-04-01

Different levels of uncertainty should be considered in climate impact projections by Dynamic Vegetation Models (DVMs), particularly when it comes to managing climate risks. Such information is useful to detect the key processes and uncertainties in the climate model - impact model chain and may be used to support recommendations for future improvements in the simulation of both climate and biological systems. In addition, determining which uncertainty source is dominant is an important aspect to recognize the limitations of climate impact projections by a multi-model ensemble mean approach. However, to date, few studies have clarified how each uncertainty source (baseline climate data, greenhouse gas emission scenario, climate model, and DVM) affects the projection of ecosystem properties. Focusing on one greenhouse gas emission scenario, we assessed the uncertainty in the projections of a forest landscape model (LANDCLIM) and a stand-scale forest gap model (FORCLIM) that is caused by linking climate data with an impact model. LANDCLIM was used to assess the uncertainty in future landscape properties of the Visp valley in Switzerland that is due to (i) the use of different 'baseline' climate data (gridded data vs. data from weather stations), and (ii) differences in climate projections among 10 GCM-RCM chains. This latter point was also considered for the projections of future forest properties by FORCLIM at several sites along an environmental gradient in Switzerland (14 GCM-RCM chains), for which we also quantified the uncertainty caused by (iii) the model chain specific statistical properties of the climate time-series, and (iv) the stochasticity of the demographic processes included in the model, e.g., the annual number of saplings that establish, or tree mortality. Using methods of variance decomposition analysis, we found that (i) The use of different baseline climate data strongly impacts the prediction of forest properties at the lowest and highest, but not so much at medium elevations. (ii) Considering climate change, the variability that is due to the GCM-RCM chains is much greater than the variability induced by the uncertainty in the initial climatic conditions. (iii) The uncertainties caused by the intrinsic stochasticity in the DVMs and by the random generation of the climate time-series are negligible. Overall, our results indicate that DVMs are quite sensitive to the climate data, highlighting particularly (1) the limitations of using one single multi-model average climate change scenario in climate impact studies and (2) the need to better consider the uncertainty in climate model outputs for projecting future vegetation changes.

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.; Baker, Noel C.

2015-01-01

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Effective control of complex turbulent dynamical systems through statistical functionals.

PubMed

Majda, Andrew J; Qi, Di

2017-05-30

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.

Uncertainty Quantification in Climate Modeling and Projection

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

Qian, Yun; Jackson, Charles; Giorgi, Filippo

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change informationmore » for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.« less

Effect of the fiber-matrix interphase on the transverse tensile strength of the unidirectional composite material

NASA Technical Reports Server (NTRS)

Tsai, H. C.; Arocho, A. M.

1992-01-01

A simple one-dimensional fiber-matrix interphase model has been developed and analytical results obtained correlated well with available experimental data. It was found that by including the interphase between the fiber and matrix in the model, much better local stress results were obtained than with the model without the interphase. A more sophisticated two-dimensional micromechanical model, which included the interphase properties was also developed. Both one-dimensional and two-dimensional models were used to study the effect of the interphase properties on the local stresses at the fiber, interphase and matrix. From this study, it was found that interphase modulus and thickness have significant influence on the transverse tensile strength and mode of failure in fiber reinforced composites.

Professional Development Design Considerations in Climate Change Education: Teacher Enactment and Student Learning

ERIC Educational Resources Information Center

Drewes, Andrea; Henderson, Joseph; Mouza, Chrystalla

2018-01-01

Climate change is one of the most pressing challenges facing society, and climate change educational models are emerging in response. This study investigates the implementation and enactment of a climate change professional development (PD) model for science educators and its impact on student learning. Using an intrinsic case study methodology,…

Expansion of the Lyme Disease Vector Ixodes scapularis in Canada inferred from CMIP5 Climate Projections

NASA Astrophysics Data System (ADS)

McPherson, Michelle Yvonne; García-García, Almudena; José Cuesta-Valero, Francisco; Beltrami, Hugo; Hansen-Ketchum, Patti; MacDougall, Donna; Hume Ogden, Nicholas

2017-04-01

A number of studies have assessed possible climate change impacts on the Lyme disease vector, Ixodes scapularis. However, most have used surface air temperature from only one climate model simulation and/or one emission scenario, representing only one possible climate future. We quantified effects of different Representative Concentration Pathway (RCP) and climate model outputs on the projected future changes in the basic reproduction number (R0) of I. scapularis to explore uncertainties in future R0 estimates. We used surface air temperature generated by a complete set of General Circulation Models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to hindcast historical and forecast future effects of climate change on the R0 of I. scapularis. As in previous studies, R0 of I. scapularis increased with a warming climate under future projected climate. Increases in the multi-model mean R0 values showed significant changes over time under all RCP scenarios, however; only the estimated R0 mean values between RCP6.0 and RCP8.5 showed statistically significant differences. Our results highlight the potential for climate change to have an effect on future Lyme disease risk in Canada even if the Paris Agreement's goal to keep global warming below 2°C is achieved, although mitigation reducing emissions from RCP8.5 levels to those of RCP6.0 or less would be expected to slow tick invasion after the 2030s. On-going planning is needed to inform and guide adaptation in light of the projected range of possible futures.

Path Dependence of Regional Climate Change

NASA Astrophysics Data System (ADS)

Herrington, Tyler; Zickfeld, Kirsten

2013-04-01

Path dependence of the climate response to CO2 forcing has been investigated from a global mean perspective, with evidence suggesting that long-term global mean temperature and precipitation changes are proportional to cumulative CO2 emissions, and independent of emissions pathway. Little research, however, has been done on path dependence of regional climate changes, particularly in areas that could be affected by tipping points. Here, we utilize the UVic Earth System Climate Model version 2.9, an Earth System Model of Intermediate Complexity. It consists of a 3-dimensional ocean general circulation model, coupled with a dynamic-thermodynamic sea ice model, and a thermodynamic energy-moisture balance model of the atmosphere. This is then coupled with a terrestrial carbon cycle model and an ocean carbon-cycle model containing an inorganic carbon and marine ecosystem component. Model coverage is global with a zonal resolution of 3.6 degrees and meridional resolution of 1.8 degrees. The model is forced with idealized emissions scenarios across five cumulative emission groups (1300 GtC, 2300 GtC, 3300 GtC, 4300 GtC, and 5300 GtC) to explore the path dependence of (and the possibility of hysteresis in) regional climate changes. Emission curves include both fossil carbon emissions and emissions from land use changes, and span a variety of peak and decline scenarios with varying emission rates, as well as overshoot and instantaneous pulse scenarios. Tipping points being explored include those responsible for the disappearance of summer Arctic sea-ice, the irreversible melt of the Greenland Ice Sheet, the collapse of the Atlantic Thermohaline Circulation, and the dieback of the Amazonian Rainforest. Preliminary results suggest that global mean climate change after cessation of CO2 emissions is independent of the emissions pathway, only varying with total cumulative emissions, in accordance with results from earlier studies. Forthcoming analysis will investigate path dependence of regional climate change. Some evidence exists to support the idea of hysteresis in the Greenland Ice Sheet, and since tipping points represent non-linear elements of the climate system, we suspect that the other tipping points might also show path dependence.

The Relationship between Organizational Climate and Quality of Chronic Disease Management

PubMed Central

Benzer, Justin K; Young, Gary; Stolzmann, Kelly; Osatuke, Katerine; Meterko, Mark; Caso, Allison; White, Bert; Mohr, David C

2011-01-01

Objective To test the utility of a two-dimensional model of organizational climate for explaining variation in diabetes care between primary care clinics. Data Sources/Study Setting Secondary data were obtained from 223 primary care clinics in the Department of Veterans Affairs health care system. Study Design Organizational climate was defined using the dimensions of task and relational climate. The association between primary care organizational climate and diabetes processes and intermediate outcomes were estimated for 4,539 patients in a cross-sectional study. Data Collection/Extraction Methods All data were collected from administrative datasets. The climate data were drawn from the 2007 VA All Employee Survey, and the outcomes data were collected as part of the VA External Peer Review Program. Climate data were aggregated to the facility level of analysis and merged with patient-level data. Principal Findings Relational climate was related to an increased likelihood of diabetes care process adherence, with significant but small effects for adherence to intermediate outcomes. Task climate was generally not shown to be related to adherence. Conclusions The role of relational climate in predicting the quality of chronic care was supported. Future research should examine the mediators and moderators of relational climate and further investigate task climate. PMID:21210799

Convergence and Divergence in a Multi-Model Ensemble of Terrestrial Ecosystem Models in North America

NASA Astrophysics Data System (ADS)

Dungan, J. L.; Wang, W.; Hashimoto, H.; Michaelis, A.; Milesi, C.; Ichii, K.; Nemani, R. R.

2009-12-01

In support of NACP, we are conducting an ensemble modeling exercise using the Terrestrial Observation and Prediction System (TOPS) to evaluate uncertainties among ecosystem models, satellite datasets, and in-situ measurements. The models used in the experiment include public-domain versions of Biome-BGC, LPJ, TOPS-BGC, and CASA, driven by a consistent set of climate fields for North America at 8km resolution and daily/monthly time steps over the period of 1982-2006. The reference datasets include MODIS Gross Primary Production (GPP) and Net Primary Production (NPP) products, Fluxnet measurements, and other observational data. The simulation results and the reference datasets are consistently processed and systematically compared in the climate (temperature-precipitation) space; in particular, an alternative to the Taylor diagram is developed to facilitate model-data intercomparisons in multi-dimensional space. The key findings of this study indicate that: the simulated GPP/NPP fluxes are in general agreement with observations over forests, but are biased low (underestimated) over non-forest types; large uncertainties of biomass and soil carbon stocks are found among the models (and reference datasets), often induced by seemingly “small” differences in model parameters and implementation details; the simulated Net Ecosystem Production (NEP) mainly responds to non-respiratory disturbances (e.g. fire) in the models and therefore is difficult to compare with flux data; and the seasonality and interannual variability of NEP varies significantly among models and reference datasets. These findings highlight the problem inherent in relying on only one modeling approach to map surface carbon fluxes and emphasize the pressing necessity of expanded and enhanced monitoring systems to narrow critical structural and parametrical uncertainties among ecosystem models.

Topographic signatures of deep-seated landslides and a general landscape evolution model

NASA Astrophysics Data System (ADS)

Booth, A. M.; Roering, J. J.; Rempel, A. W.

2012-12-01

A fundamental goal of studying earth surface processes is to disentangle the complex web of interactions among baselevel, climate, and rock properties that generate characteristic landforms. Mechanistic geomorphic transport laws can quantitatively address this goal, but no widely accepted law for landslides exists. Here, we propose a transport law for deep-seated landslides and demonstrate its utility using a two-dimensional numerical landscape evolution model informed by study areas in the Waipaoa catchment, New Zealand and the Eel River catchment, California. We define a non-dimensional landslide number, which is the ratio of uplift to landslide flow time scales, that predicts three distinct landscape types. The first is dominated by stochastic landsliding, whereby discrete landslide events episodically erode material at rates far exceeding the long term uplift rate. The second is characterized by steady landsliding, in which the landslide flux at any location remains constant through time and is largest at the steepest locations in the catchment. The third is not significantly affected by landsliding. In both the "stochastic landsliding" and "steady landsliding" regimes, increases in the non-dimensional landslide number systematically reduce catchment relief and widen valley spacing, producing long, quasi-planar, low angle hillslopes despite high uplift rates. The stochastic landsliding regime best captures the frequent observation that deep-seated landslides produce a large sediment flux from a small aerial extent while being active only a fraction of the time. We suggest that this model is adaptable to a wide range of geologic settings and may be useful for interpreting climate-driven changes in landslide behavior.

Investigating the Greenland ice sheet evolution under changing climate using a three-dimensional full-Stokes model

NASA Astrophysics Data System (ADS)

Seddik, H.; Greve, R.; Zwinger, T.; Gillet-Chaulet, F.; Gagliardini, O.

2010-12-01

A three-dimensional, thermo-mechanically coupled model is applied to the Greenland ice sheet. The model implements the full-Stokes equations for the ice dynamics, and the system is solved with the finite-element method (FEM) using the open source multi-physics package Elmer (http://www.csc.fi/elmer/). The finite-element mesh for the computational domain has been created using the Greenland surface and bedrock DEM data with a spatial resolution of 5 km (SeaRise community effort, based on Bamber and others, 2001). The study is particularly aimed at better understanding the ice dynamics near the major Greenland ice streams. The meshing procedure starts with the bedrock footprint where a mesh with triangle elements and a resolution of 5 km is constructed. Since the resulting mesh is unnecessarily dense in areas with slow ice dynamics, an anisotropic mesh adaptation procedure has been introduced. Using the measured surface velocities to evaluate the Hessian matrix of the velocities, a metric tensor is computed at the mesh vertices in order to define the adaptation scheme. The resulting meshed footprint obtained with the automatic tool YAMS shows a high density of elements in the vicinities of the North-East Greenland Ice Stream (NEGIS), the Jakobshavn ice stream (JIS) and the Kangerdlugssuaq (KL) and Helheim (HH) glaciers. On the other hand, elements with a coarser resolution are generated away from the ice streams and domain margins. The final three-dimensional mesh is obtained by extruding the 2D footprint with 21 vertical layers, so that the resulting mesh contains 400860 wedge elements and 233583 nodes. The numerical solution of the Stokes and the heat transfer equations involves direct and iterative solvers depending on the simulation case, and both methods are coupled with stabilization procedures. The boundary conditions are such that the temperature at the surface uses the present-day mean annual air temperature given by a parameterization or directly from the available data, the geothermal heat flux at the bedrock is prescribed as spatially constant and the lateral sides are open boundaries. A non-linear Weertman law is used for the basal sliding. The project goal is to better assess the effects of dynamical changes of the Greenland ice sheet on sea level rise under global-warming conditions. Hence, the simulations have been conducted in order to investigate the ice sheet evolution using the climate forcing experiments defined in the SeaRISE project. For that purpose, four different experiments have been conducted, (i) constant climate control run beginning at present (epoch 2004-1-1 0:0:0) and running up to 500 years holding the climate constant to its present state, (ii) constant climate forcing with increased basal lubrication, (iii) AR4 climate run forced by anomalies derived from results given in the IPCC 4th Assessment Report (AR4) for the A1B emission scenario, (iv) AR4 climate run with increased basal lubrication.

What Controls ENSO-Amplitude Diversity in Climate Models?

NASA Astrophysics Data System (ADS)

Wengel, C.; Dommenget, D.; Latif, M.; Bayr, T.; Vijayeta, A.

2018-02-01

Climate models depict large diversity in the strength of the El Niño/Southern Oscillation (ENSO) (ENSO amplitude). Here we investigate ENSO-amplitude diversity in the Coupled Model Intercomparison Project Phase 5 (CMIP5) by means of the linear recharge oscillator model, which reduces ENSO dynamics to a two-dimensional problem in terms of eastern equatorial Pacific sea surface temperature anomalies (T) and equatorial Pacific upper ocean heat content anomalies (h). We find that a large contribution to ENSO-amplitude diversity originates from stochastic forcing. Further, significant interactions exist between the stochastic forcing and the growth rates of T and h with competing effects on ENSO amplitude. The joint consideration of stochastic forcing and growth rates explains more than 80% of the ENSO-amplitude variance within CMIP5. Our results can readily explain the lack of correlation between the Bjerknes Stability index, a measure of the growth rate of T, and ENSO amplitude in a multimodel ensemble.

Atmospheric carbon dioxide concentrations before 2.2 billion years ago

NASA Technical Reports Server (NTRS)

Rye, R.; Kuo, P. H.; Holland, H. D.

1995-01-01

The composition of the Earth's early atmosphere is a subject of continuing debate. In particular, it has been suggested that elevated concentrations of atmospheric carbon dioxide would have been necessary to maintain normal surface temperatures in the face of lower solar luminosity in early Earth history. Fossil weathering profiles, known as palaeosols, have provided semi-quantitative constraints on atmospheric oxygen partial pressure (pO2) before 2.2 Gyr ago. Here we use the same well studied palaeosols to constrain atmospheric pCO2 between 2.75 and 2.2 Gyr ago. The observation that iron lost from the tops of these profiles was reprecipitated lower down as iron silicate minerals, rather than as iron carbonate, indicates that atmospheric pCO2 must have been less than 10(-1.4) atm--about 100 times today's level of 360 p.p.m., and at least five times lower than that required in one-dimensional climate models to compensate for lower solar luminosity at 2.75 Gyr. Our results suggest that either the Earth's early climate was much more sensitive to increases in pCO2 than has been thought, or that one or more greenhouse gases other than CO2 contributed significantly to the atmosphere's radiative balance during the late Archaean and early Proterozoic eons.

The influence of initial and surface boundary conditions on a model-generated January climatology

NASA Technical Reports Server (NTRS)

Wu, K. F.; Spar, J.

1981-01-01

The influence on a model-generated January climate of various surface boundary conditions, as well as initial conditions, was studied by using the GISS coarse-mesh climate model. Four experiments - two with water planets, one with flat continents, and one with mountains - were used to investigate the effects of initial conditions, and the thermal and dynamical effects of the surface on the model generated-climate. However, climatological mean zonal-symmetric sea surface temperature is used in all four runs over the model oceans. Moreover, zero ground wetness and uniform ground albedo except for snow are used in the last experiments.

The meaning and measurement of implementation climate

PubMed Central

2011-01-01

Background Climate has a long history in organizational studies, but few theoretical models integrate the complex effects of climate during innovation implementation. In 1996, a theoretical model was proposed that organizations could develop a positive climate for implementation by making use of various policies and practices that promote organizational members' means, motives, and opportunities for innovation use. The model proposes that implementation climate--or the extent to which organizational members perceive that innovation use is expected, supported, and rewarded--is positively associated with implementation effectiveness. The implementation climate construct holds significant promise for advancing scientific knowledge about the organizational determinants of innovation implementation. However, the construct has not received sufficient scholarly attention, despite numerous citations in the scientific literature. In this article, we clarify the meaning of implementation climate, discuss several measurement issues, and propose guidelines for empirical study. Discussion Implementation climate differs from constructs such as organizational climate, culture, or context in two important respects: first, it has a strategic focus (implementation), and second, it is innovation-specific. Measuring implementation climate is challenging because the construct operates at the organizational level, but requires the collection of multi-dimensional perceptual data from many expected innovation users within an organization. In order to avoid problems with construct validity, assessments of within-group agreement of implementation climate measures must be carefully considered. Implementation climate implies a high degree of within-group agreement in climate perceptions. However, researchers might find it useful to distinguish implementation climate level (the average of implementation climate perceptions) from implementation climate strength (the variability of implementation climate perceptions). It is important to recognize that the implementation climate construct applies most readily to innovations that require collective, coordinated behavior change by many organizational members both for successful implementation and for realization of anticipated benefits. For innovations that do not possess these attributes, individual-level theories of behavior change could be more useful in explaining implementation effectiveness. Summary This construct has considerable value in implementation science, however, further debate and development is necessary to refine and distinguish the construct for empirical use. PMID:21781328

ONE-DIMENSIONAL HYDRODYNAMIC/SEDIMENT TRANSPORT MODEL FOR STREAM NETWORKS: TECHNICAL REPORT

EPA Science Inventory

This technical report describes a new sediment transport model and the supporting post-processor, and sampling procedures for sediments in streams. Specifically, the following items are described herein:

EFDC1D - This is a new one-dimensional hydrodynamic and sediment tr...

Pressure distribution under flexible polishing tools. II - Cylindrical (conical) optics

NASA Astrophysics Data System (ADS)

Mehta, Pravin K.

1990-10-01

A previously developed eigenvalue model is extended to determine polishing pressure distribution by rectangular tools with unequal stiffness in two directions on cylindrical optics. Tool misfit is divided into two simplified one-dimensional problems and one simplified two-dimensional problem. Tools with nonuniform cross-sections are treated with a new one-dimensional eigenvalue algorithm, permitting evaluation of tool designs where the edge is more flexible than the interior. This maintains edge pressure variations within acceptable parameters. Finite element modeling is employed to resolve upper bounds, which handle pressure changes in the two-dimensional misfit element. Paraboloids and hyperboloids from the NASA AXAF system are treated with the AXAFPOD software for this method, and are verified with NASTRAN finite element analyses. The maximum deviation from the one-dimensional azimuthal pressure variation is predicted to be 10 percent and 20 percent for paraboloids and hyperboloids, respectively.

Predicting Nitrate Transport under Future Climate Scenarios beneath the Nebraska Management Systems Evaluation Area (MSEA) site

NASA Astrophysics Data System (ADS)

Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.

2017-12-01

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.

Predicting Nitrate Transport under Future Climate Scenarios beneath the Nebraska Management Systems Evaluation Area (MSEA) site

NASA Astrophysics Data System (ADS)

Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.

2016-12-01

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.

A new space-time characterization of Northern Hemisphere drought in model simulations of the past and future as compared to the paleoclimate record

NASA Astrophysics Data System (ADS)

Coats, S.; Smerdon, J. E.; Stevenson, S.; Fasullo, J.; Otto-Bliesner, B. L.

2017-12-01

The observational record, which provides only limited sampling of past climate variability, has made it difficult to quantitatively analyze the complex spatio-temporal character of drought. To provide a more complete characterization of drought, machine learning based methods that identify drought in three-dimensional space-time are applied to climate model simulations of the last millennium and future, as well as tree-ring based reconstructions of hydroclimate over the Northern Hemisphere extratropics. A focus is given to the most persistent and severe droughts of the past 1000 years. Analyzing reconstructions and simulations in this context allows for a validation of the spatio-temporal character of persistent and severe drought in climate model simulations. Furthermore, the long records provided by the reconstructions and simulations, allows for sufficient sampling to constrain projected changes to the spatio-temporal character of these features using the reconstructions. Along these lines, climate models suggest that there will be large increases in the persistence and severity of droughts over the coming century, but little change in their spatial extent. These models, however, exhibit biases in the spatio-temporal character of persistent and severe drought over parts of the Northern Hemisphere, which may undermine their usefulness for future projections. Despite these limitations, and in contrast to previous claims, there are no systematic changes in the character of persistent and severe droughts in simulations of the historical interval. This suggests that climate models are not systematically overestimating the hydroclimate response to anthropogenic forcing over this period, with critical implications for confidence in hydroclimate projections.

Two-dimensional signal processing with application to image restoration

NASA Technical Reports Server (NTRS)

Assefi, T.

1974-01-01

A recursive technique for modeling and estimating a two-dimensional signal contaminated by noise is presented. A two-dimensional signal is assumed to be an undistorted picture, where the noise introduces the distortion. Both the signal and the noise are assumed to be wide-sense stationary processes with known statistics. Thus, to estimate the two-dimensional signal is to enhance the picture. The picture representing the two-dimensional signal is converted to one dimension by scanning the image horizontally one line at a time. The scanner output becomes a nonstationary random process due to the periodic nature of the scanner operation. Procedures to obtain a dynamical model corresponding to the autocorrelation function of the scanner output are derived. Utilizing the model, a discrete Kalman estimator is designed to enhance the image.

Bicylindrical model of Herschel-Quincke tube-duct system: theory and comparison with experiment and finite element method.

PubMed

Poirier, B; Ville, J M; Maury, C; Kateb, D

2009-09-01

An analytical three dimensional bicylindrical model is developed in order to take into account the effects of the saddle-shaped area for the interface of a n-Herschel-Quincke tube system with the main duct. Results for the scattering matrix of this system deduced from this model are compared, in the plane wave frequency domain, versus experimental and numerical data and a one dimensional model with and without tube length correction. The results are performed with a two-Herschel-Quincke tube configuration having the same diameter as the main duct. In spite of strong assumptions on the acoustic continuity conditions at the interfaces, this model is shown to improve the nonperiodic amplitude variations and the frequency localization of the minima of the transmission and reflection coefficients with respect to one dimensional model with length correction and a three dimensional model.

Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments.

PubMed

Tao, Fulu; Rötter, Reimund P; Palosuo, Taru; Gregorio Hernández Díaz-Ambrona, Carlos; Mínguez, M Inés; Semenov, Mikhail A; Kersebaum, Kurt Christian; Nendel, Claas; Specka, Xenia; Hoffmann, Holger; Ewert, Frank; Dambreville, Anaelle; Martre, Pierre; Rodríguez, Lucía; Ruiz-Ramos, Margarita; Gaiser, Thomas; Höhn, Jukka G; Salo, Tapio; Ferrise, Roberto; Bindi, Marco; Cammarano, Davide; Schulman, Alan H

2018-03-01

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources. © 2017 John Wiley & Sons Ltd.

A New Attempt of 2-D Numerical Ice Flow Model to Reconstruct Paleoclimate from Mountain Glaciers

NASA Astrophysics Data System (ADS)

Candaş, Adem; Akif Sarıkaya, Mehmet

2017-04-01

A new two dimensional (2D) numerical ice flow model is generated to simulate the steady-state glacier extent for a wide range of climate conditions. The simulation includes the flow of ice enforced by the annual mass balance gradient of a valley glacier. The annual mass balance is calculated by the difference of the net accumulation and ablation of snow and (or) ice. The generated model lets users to compare the simulated and field observed ice extent of paleoglaciers. As a result, model results provide the conditions about the past climates since simulated ice extent is a function of predefined climatic conditions. To predict the glacier shape and distribution in two dimension, time dependent partial differential equation (PDE) is solved. Thus, a 2D glacier flow model code is constructed in MATLAB and a finite difference method is used to solve this equation. On the other hand, Parallel Ice Sheet Model (PISM) is used to regenerate paleoglaciers in the same area where the MATLAB code is applied. We chose the Mount Dedegöl, an extensively glaciated mountain in SW Turkey, to apply both models. Model results will be presented and discussed in this presentation. This study was supported by TÜBİTAK 114Y548 project.

An analysis of the physical, chemical, optical, and historical impacts of the 1908 Tunguska meteor fall

NASA Technical Reports Server (NTRS)

Turco, R. P.; Toon, O. B.; Park, C.; Whitten, R. C.; Pollack, J. B.; Noerdlinger, P.

1982-01-01

An analysis is presented of the physical characteristics and photochemical aftereffects of the 1908 Tunguska explosive cometary meteor, whose physical manifestations are consistent with a five million ton object's entry into the earth's atmosphere at 40 km/sec. Aerodynamic calculations indicate that the shock waves emanating from the falling meteor could have generated up to 30 million tons of nitric oxide in the stratosphere and mesosphere. A fully interactive one-dimensional chemical-kinetics model of atmospheric trace constituents is used to estimate the photochemical consequences of such a large NO injection. The 35-45% hemispherical ozone depletion predicted by the model is in keeping with the 30 + or - 15% ozone variation reported for the first year after the Tunguska fall. Attention is also given to the optical anomalies which followed the event for indications of NO(x)-O(x) chemiluminescent emissions, NO2 solar absorption, and meteoric dust turbidity, along with possible climate changes due to the nearly one million tons of pulverized dust deposited in the mesosphere and stratosphere by the meteor.

Coupling records of fluvial activity from the last interglacial-glacial cycle with climate forcing using both geochronology and numerical modelling

NASA Astrophysics Data System (ADS)

Briant, Rebecca; Mottram, Gareth; Wainwright, John

2010-05-01

River systems are a critical component of the landscape. An understanding of their response to variations in the Earth's climate is vital in light of the expected changes in global climate (e.g. 1.8 to 4.8°C temperature rise) that are forecast to occur over the next c. 100 years. Over the longer term, it becomes increasingly likely that the changes we will see may even be of a magnitude for which the most appropriate analogue we have is the glacial-interglacial scale (c. 10°C temperature change) and other climate changes typical of the Quaternary period (last 2 million years). Therefore it is crucial to apply our understanding of climate-driven changes during the Quaternary to future projections of both climate and landscape change, especially since landscape instability is a key characteristic of the Quaternary. Linking river activity to climate requires both the recognition of potentially climate-driven changes within the fluvial sedimentary record and the linkage of these to external climate records using various geochronological techniques. To this end, this paper firstly presents results from the Welland catchment, Fenland Basin where climatically-driven phases of river activity have been identified using detailed sedimentological analysis and palaeontological environmental reconstruction. Dating of these using radiocarbon and optically-stimulated luminescence dating has shown broad correspondence to external climate fluctuations at a marine isotope substage scale over the last interglacial-glacial cycle (MIS 5d onwards). The precision and accuracy of the two different age techniques varies in different parts of this time period and this will be discussed. Limitations in the precision of these geochronological techniques have prompted the use of a further, complementary to improve understanding of these sequences, i.e. ensemble numerical modeling. The rationale behind this approach is that river response to climate can be traced within the model and validated against the known geological record. If the known geological record can be replicated, then the detailed linkages between climate and river activity shown in the model can be used understand to the relationships between climate change and river activity more clearly. This paper will present the results of three-dimensional cellular automata modeling of the Welland catchment, compare them to the geological record, and draw out what this means for our understanding of earth surface processes.

An Interactive Multi-Model for Consensus on Climate Change

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

Kocarev, Ljupco

This project purports to develop a new scheme for forming consensus among alternative climate models, that give widely divergent projections as to the details of climate change, that is more intelligent than simply averaging the model outputs, or averaging with ex post facto weighting factors. The method under development effectively allows models to assimilate data from one another in run time with weights that are chosen in an adaptive training phase using 20th century data, so that the models synchronize with one another as well as with reality. An alternate approach that is being explored in parallel is the automatedmore » combination of equations from different models in an expert-system-like framework.« less

3DHYDROGEOCHEM: A 3-DIMENSIONAL MODEL OF DENSITY-DEPENDENT SUBSURFACE FLOW AND THERMAL MULTISPECIES-MULTICOMPONENT HYDROGEOCHEMICAL TRANSPORT (EPA/600/SR-98/159)

EPA Science Inventory

This report presents a three-dimensional finite-element numerical model designed to simulate chemical transport in subsurface systems with temperature effect taken into account. The three-dimensional model is developed to provide (1) a tool of application, with which one is able ...

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

NASA Astrophysics Data System (ADS)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

Thermal Pollution Math Model. Volume 1. Thermal Pollution Model Package Verification and Transfer. [environment impact of thermal discharges from power plants

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.

1980-01-01

Two three dimensional, time dependent models, one free surface, the other rigid lid, were verified at Anclote Anchorage and Lake Keowee respectively. The first site is a coastal site in northern Florida; the other is a man-made lake in South Carolina. These models describe the dispersion of heated discharges from power plants under the action of ambient conditions. A one dimensional, horizontally-averaged model was also developed and verified at Lake Keowee. The data base consisted of archival in situ measurements and data collected during field missions. The field missions were conducted during winter and summer conditions at each site. Each mission consisted of four infrared scanner flights with supporting ground truth and in situ measurements. At Anclote, special care was taken to characterize the complete tidal cycle. The three dimensional model results compared with IR data for thermal plumes on an average within 1 C root mean square difference. The one dimensional model performed satisfactorily in simulating the 1971-1979 period.

Collaborative Project: Development of an Isotope-Enabled CESM for Testing Abrupt Climate Changes

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

Liu, Zhengyu

One of the most important validations for a state-of-art Earth System Model (ESM) with respect to climate changes is the simulation of the climate evolution and abrupt climate change events in the Earth’s history of the last 21,000 years. However, one great challenge for model validation is that ESMs usually do not directly simulate geochemical variables that can be compared directly with past proxy records. In this proposal, we have met this challenge by developing the simulation capability of major isotopes in a state-of-art ESM, the Community Earth System Model (CESM), enabling us to make direct model-data comparison by comparingmore » the model directly against proxy climate records. Our isotope-enabled ESM incorporates the capability of simulating key isotopes and geotracers, notably δ 18O, δD, δ 14C, and δ 13C, Nd and Pa/Th. The isotope-enabled ESM have been used to perform some simulations for the last 21000 years. The direct comparison of these simulations with proxy records has shed light on the mechanisms of important climate change events.« less

Integration of remote sensing based surface information into a three-dimensional microclimate model

NASA Astrophysics Data System (ADS)

Heldens, Wieke; Heiden, Uta; Esch, Thomas; Mueller, Andreas; Dech, Stefan

2017-03-01

Climate change urges cities to consider the urban climate as part of sustainable planning. Urban microclimate models can provide knowledge on the climate at building block level. However, very detailed information on the area of interest is required. Most microclimate studies therefore make use of assumptions and generalizations to describe the model area. Remote sensing data with area wide coverage provides a means to derive many parameters at the detailed spatial and thematic scale required by urban climate models. This study shows how microclimate simulations for a series of real world urban areas can be supported by using remote sensing data. In an automated process, surface materials, albedo, LAI/LAD and object height have been derived and integrated into the urban microclimate model ENVI-met. Multiple microclimate simulations have been carried out both with the dynamic remote sensing based input data as well as with manual and static input data to analyze the impact of the RS-based surface information and the suitability of the applied data and techniques. A valuable support of the integration of the remote sensing based input data for ENVI-met is the use of an automated processing chain. This saves tedious manual editing and allows for fast and area wide generation of simulation areas. The analysis of the different modes shows the importance of high quality height data, detailed surface material information and albedo.

A two-dimensional kinematic dynamo model of the ionospheric magnetic field at Venus

NASA Technical Reports Server (NTRS)

Cravens, T. E.; Wu, D.; Shinagawa, H.

1990-01-01

The results of a high-resolution, two-dimensional, time dependent, kinematic dynamo model of the ionospheric magnetic field of Venus are presented. Various one-dimensional models are considered and the two-dimensional model is then detailed. In this model, the two-dimensional magnetic induction equation, the magnetic diffusion-convection equation, is numerically solved using specified plasma velocities. Origins of the vertical velocity profile and of the horizontal velocities are discussed. It is argued that the basic features of the vertical magnetic field profile remain unaltered by horizontal flow effects and also that horizontal plasma flow can strongly affect the magnetic field for altitudes above 300 km.

Cold spray nozzle mach number limitation

NASA Astrophysics Data System (ADS)

Jodoin, B.

2002-12-01

The classic one-dimensional isentropic flow approach is used along with a two-dimensional axisymmetric numerical model to show that the exit Mach number of a cold spray nozzle should be limited due to two factors. To show this, the two-dimensional model is validated with experimental data. Although both models show that the stagnation temperature is an important limiting factor, the one-dimensional approach fails to show how important the shock-particle interactions are at limiting the nozzle Mach number. It is concluded that for an air nozzle spraying solid powder particles, the nozzle Mach number should be set between 1.5 and 3 to limit the negative effects of the high stagnation temperature and of the shock-particle interactions.

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change

PubMed Central

Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

2016-01-01

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one. PMID:27015274

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change.

PubMed

Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

2016-01-01

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

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

Way, M. J.; Aleinov, I.; Amundsen, David S.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a three-dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of solar system and exoplanetary terrestrial planets. Its parent model, known as ModelE2, is used to simulate modern Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions, including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (from slower tomore » more rapid than modern Earth’s, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the solar system such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn’s moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents, we can then further expand its capabilities to those exoplanetary rocky worlds that have been discovered in the past, as well as those to be discovered in the future. We also discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.« less

Numerically exploring the 1D-2D dimensional crossover on spin dynamics in the doped Hubbard model

DOE PAGES

Kung, Y. F.; Bazin, C.; Wohlfeld, K.; ...

2017-11-02

Using determinant quantum Monte Carlo (DQMC) simulations, we systematically study the doping dependence of the crossover from one to two dimensions and its impact on the magnetic properties of the Hubbard model. A square lattice of chains is used, in which the dimensionality can be tuned by varying the interchain coupling t ⊥. The dynamical spin structure factor and static quantities, such as the static spin susceptibility and nearest-neighbor spin correlation function, are characterized in the one- and two-dimensional limits as a benchmark. When the dimensionality is tuned between these limits, the magnetic properties, while evolving smoothly from one tomore » two dimensions, drastically change regardless of the doping level. This suggests that the spin excitations in the two-dimensional Hubbard model, even in the heavily doped case, cannot be explained using the spinon picture known from one dimension. In conclusion, the DQMC calculations are complemented by cluster perturbation theory studies to form a more complete picture of how the crossover occurs as a function of doping and how doped holes impact magnetic order.« less

Effects of Variable Eccentricity on the Climate of an Earth-like World

NASA Astrophysics Data System (ADS)

Way, M. J.; Georgakarakos, Nikolaos

2017-01-01

The Kepler era of exoplanetary discovery has presented the astronomical community with a cornucopia of planetary systems that are very different from the one that we inhabit. It has long been known that Jupiter plays a major role in the orbital parameters of Mars and its climate, but there is also a long-standing belief that Jupiter would play a similar role for Earth if not for the Moon. Using a three-dimensional general circulation model (3D GCM) with a fully coupled ocean, we simulate what would happen to the climate of an Earth-like world if Mars did not exist, but a Jupiter-like planet was much closer to Earth’s orbit. We investigate two scenarios that involve the evolution of the Earth-like planet’s orbital eccentricity from 0 to 0.283 over 6500 years, and from 0 to 0.066 on a timescale of 4500 years. In both cases we discover that they would maintain relatively temperate climates over the timescales simulated. More Earth-like planets in multi-planet systems will be discovered as we continue to survey the skies and the results herein show that the proximity of large gas giant planets may play an important role in the habitability of these worlds. These are the first such 3D GCM simulations using a fully coupled ocean with a planetary orbit that evolves over time due to the presence of a giant planet.

Bare soil respiration in a temperate climate: multiyear evaluation of a coupled CO2 transport and carbon turnover model

NASA Astrophysics Data System (ADS)

Herbst, M.; Hellebrand, H. J.; Bauer, J.; Vanderborght, J.; Vereecken, H.

2006-12-01

The modelling of soil respiration plays an important role in the prediction of climate change. Soil respiration is usually divided in autotrophic and heterotrophic fractions orginating from root respiration and microbial decomposition of soil organic carbon, respectively. We report on the coupling of a one dimensional water, heat and CO2 flux model (SOILCO2) with a model of carbon turnover (RothC) for the prediction of soil heterotrophic respiration. The coupled model was tested using soil temperature, soil moisture, and CO2 flux measurements in a bare soil experimental plot located in Bornim, Germany. A seven year record of soil and CO2 measurements covering a broad range of atmospheric and soil conditions was availabe to evaluate the model performance. After calibrating the decomposition rate constant of the humic fraction pool, the overall model performance on CO2 efflux prediction was acceptable. The root mean square error for the CO2 efflux prediction was 0.12 cm ³/cm ²/d. During the severe summer draught of 2003 very high CO2 efluxes were measured, which could not be explained by the model. Those high fluxes were attributed to a pressure pumping effect. The soil temperature dependency of CO2 production was well described by th e model, whereas the biggest opportunity for improvement is seen in a better description of the soil moisture dependency of CO2 production. The calibration of the humus decomposition rate constant revealed a value of 0.09 1/d, which is higher than the original value suggested by the RothC model developers but within the range of literature values.

Simple One-Dimensional Quantum-Mechanical Model for a Particle Attached to a Surface

ERIC Educational Resources Information Center

Fernandez, Francisco M.

2010-01-01

We present a simple one-dimensional quantum-mechanical model for a particle attached to a surface. It leads to the Schrodinger equation for a harmonic oscillator bounded on one side that we solve in terms of Weber functions and discuss the behaviour of the eigenvalues and eigenfunctions. We derive the virial theorem and other exact relationships…

Finite Volume Numerical Methods for Aeroheating Rate Calculations from Infrared Thermographic Data

NASA Technical Reports Server (NTRS)

Daryabeigi, Kamran; Berry, Scott A.; Horvath, Thomas J.; Nowak, Robert J.

2003-01-01

The use of multi-dimensional finite volume numerical techniques with finite thickness models for calculating aeroheating rates from measured global surface temperatures on hypersonic wind tunnel models was investigated. Both direct and inverse finite volume techniques were investigated and compared with the one-dimensional semi -infinite technique. Global transient surface temperatures were measured using an infrared thermographic technique on a 0.333-scale model of the Hyper-X forebody in the Langley Research Center 20-Inch Mach 6 Air tunnel. In these tests the effectiveness of vortices generated via gas injection for initiating hypersonic transition on the Hyper-X forebody were investigated. An array of streamwise orientated heating striations were generated and visualized downstream of the gas injection sites. In regions without significant spatial temperature gradients, one-dimensional techniques provided accurate aeroheating rates. In regions with sharp temperature gradients due to the striation patterns two-dimensional heat transfer techniques were necessary to obtain accurate heating rates. The use of the one-dimensional technique resulted in differences of 20% in the calculated heating rates because it did not account for lateral heat conduction in the model.

Climatic effects due to halogenated compounds in the earth's atmosphere

NASA Technical Reports Server (NTRS)

Wang, W.-C.; Pinto, J. P.; Yung, Y. L.

1980-01-01

Using a one-dimensional radiative-convective model, a sensitivity study is performed of the effect of ozone depletion in the stratosphere on the surface temperature. There could be a cooling of the surface temperature by approximately 0.2 K due to chlorofluoromethane-induced ozone depletion at steady state (assuming 1973 release rates). This cooling reduces significantly the greenhouse effect due to the presence of chlorofluoromethanes. Carbon tetrafluoride has a strong nu sub 3 band at 7.8 microns, and the atmospheric greenhouse effect is shown to be 0.07 and 0.12 K/ppbv with and without taking into account overlap with CH4 and N2O bands. At concentrations higher than 1 ppbv, absorption by the nu sub 3 band starts to saturate and the greenhouse effect becomes less efficient.

One-Dimensional Modeling Studies of the Gaseous Electronics Conference RF Reference Cell

PubMed Central

Govindan, T. R.; Meyyappan, M.

1995-01-01

A review of the one-dimensional modeling studies in the literature of the Gaseous Electronics Conference (GEC) reference plasma reactor is presented. Most of the studies are based on the fluid model description of the discharge and some utilize hybrid fluid-kinetic schemes. Both models are discussed here briefly. The models provide a basic understanding of the discharge mechanisms and reproduce several critical discharge features observed experimentally. PMID:29151755

More robust regional precipitation projection from selected CMIP5 models based on multiple-dimensional metrics

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, L.; Leung, L. R.; Lin, G.; Lu, J.; Gao, Y.; Zhang, Y.

2017-12-01

Projecting precipitation changes is challenging because of incomplete understanding of the climate system and biases and uncertainty in climate models. In East Asia where summer precipitation is dominantly influenced by the monsoon circulation and the global models from Coupled Model Intercomparison Project Phase 5 (CMIP5), however, give various projection of precipitation change for 21th century. It is critical for community to know which models' projection are more reliable in response to natural and anthropogenic forcings. In this study we defined multiple-dimensional metrics, measuring the model performance in simulating the present-day of large-scale circulation, regional precipitation and relationship between them. The large-scale circulation features examined in this study include the lower tropospheric southwesterly winds, the western North Pacific subtropical high, the South China Sea Subtropical High, and the East Asian westerly jet in the upper troposphere. Each of these circulation features transport moisture to East Asia, enhancing the moist static energy and strengthening the Meiyu moisture front that is the primary mechanism for precipitation generation in eastern China. Based on these metrics, 30 models in CMIP5 ensemble are classified into three groups. Models in the top performing group projected regional precipitation patterns that are more similar to each other than the bottom or middle performing group and consistently projected statistically significant increasing trends in two of the large-scale circulation indices and precipitation. In contrast, models in the bottom or middle performing group projected small drying or no trends in precipitation. We also find the models that only reasonably reproduce the observed precipitation climatology does not guarantee more reliable projection of future precipitation because good simulation skill could be achieved through compensating errors from multiple sources. Herein the potential for more robust projections of precipitation changes at regional scale is demonstrated through the use of discriminating metric to subsample the multi-model ensemble. The results from this study provides insights for how to select models from CMIP ensemble to project regional climate and hydrological cycle changes.

An analytical approach to thermal modeling of Bridgman type crystal growth: One dimensional analysis. Computer program users manual

NASA Technical Reports Server (NTRS)

Cothran, E. K.

1982-01-01

The computer program written in support of one dimensional analytical approach to thermal modeling of Bridgman type crystal growth is presented. The program listing and flow charts are included, along with the complete thermal model. Sample problems include detailed comments on input and output to aid the first time user.

Testing FASST a One-Dimensional Hydrological Model for Soil Moisture Studies at the Little River Watershed, Tifton, Georgia

USDA-ARS?s Scientific Manuscript database

The FASST (Fast All Season Strength model, US Army Corps of Engineers), one-dimensional hydrologic model was used to evaluate soil moisture across the USDA-ARS-SEWRL Little River Watershed in south Georgia US. The ultimate goal of this research is to assess the spatial variation of soil moisture acr...

Inferring time-varying recharge from inverse analysis of long-term water levels

NASA Astrophysics Data System (ADS)

Dickinson, Jesse E.; Hanson, R. T.; Ferré, T. P. A.; Leake, S. A.

2004-07-01

Water levels in aquifers typically vary in response to time-varying rates of recharge, suggesting the possibility of inferring time-varying recharge rates on the basis of long-term water level records. Presumably, in the southwestern United States (Arizona, Nevada, New Mexico, southern California, and southern Utah), rates of mountain front recharge to alluvial aquifers depend on variations in precipitation rates due to known climate cycles such as the El Niño-Southern Oscillation index and the Pacific Decadal Oscillation. This investigation examined the inverse application of a one-dimensional analytical model for periodic flow described by Lloyd R. Townley in 1995 to estimate periodic recharge variations on the basis of variations in long-term water level records using southwest aquifers as the case study. Time-varying water level records at various locations along the flow line were obtained by simulation of forward models of synthetic basins with applied sinusoidal recharge of either a single period or composite of multiple periods of length similar to known climate cycles. Periodic water level components, reconstructed using singular spectrum analysis (SSA), were used to calibrate the analytical model to estimate each recharge component. The results demonstrated that periodic recharge estimates were most accurate in basins with nearly uniform transmissivity and the accuracy of the recharge estimates depends on monitoring well location. A case study of the San Pedro Basin, Arizona, is presented as an example of calibrating the analytical model to real data.

Selected topics in high energy physics: Flavon, neutrino and extra-dimensional models

NASA Astrophysics Data System (ADS)

Dorsner, Ilja

There is already significant evidence, both experimental and theoretical, that the Standard Model of elementary particle physics is just another effective physical theory. Thus, it is crucial (a) to anticipate the experiments in search for signatures of the physics beyond the Standard Model, and (b) whether some theoretically preferred structure can reproduce the low-energy signature of the Standard Model. This work pursues these two directions by investigating various extensions of the Standard Model. One of them is a simple flavon model that accommodates the observed hierarchy of the charged fermion masses and mixings. We show that flavor changing and CP violating signatures of this model are equally near the present experimental limits. We find that, for a significant range of parameters, mu-e conversion can be the most sensitive place to look for such signatures. We then propose two variants of an SO(10) model in five-dimensional framework. The first variant demonstrates that one can embed a four-dimensional flipped SU(5) model into a five-dimensional SO(10) model. This allows one to maintain the advantages of flipped SU(5) while avoiding its well-known drawbacks. The second variant shows that exact unification of the gauge couplings is possible even in the higher dimensional setting. This unification yields low-energy values of the gauge couplings that are in a perfect agreement with experimental values. We show that the corrections to the usual four-dimensional running, due to the Kaluza-Klein towers of states, can be unambiguously and systematically evaluated. We also consider the various main types of models of neutrino masses and mixings from the point of view of how naturally they give the large mixing angle MSW solution to the solar neutrino problem. Special attention is given to one particular "lopsided" SU(5) model, which is then analyzed in a completely statistical manner. We suggest that this sort of statistical analysis should be applicable to other models of neutrino mixing.

Climate Change Impact Study with CMIP5 and Comparison with CMIP3

NASA Astrophysics Data System (ADS)

Wang, J.; Yin, H.; Reyes, E.; Chung, F. I.

2016-12-01

One of significant uncertainties in climate change impact study is the selection of climate model projection including the choosing of greenhouse gas emission scenarios. With the new generation of climate model projection, CMIP5, coming into use, CCTAG selected 11 climate models and two RCPs (rcp4.5 and rcp8.5) for California. Previous DWR climate change study was based on 6 CMIP3 climate models and two emission scenarios (SRES A2 and B1) which were selected by CAT. It is an unanswered question that how the selection of these climate model projections and emission scenarios affect the assessment of climate change impact on future water supply of California CVP/SWP project. This work will run the water planning model CalSim in DWR with 44 CMIP5 and 12 CMIP3 climate model projections to investigate the sensitivity of climate model impact study on future water supply in the CVP/SWP region to the section of climate model projection. It was found that in 2060 CMIP5 projects the wetting trend in Northern California while CMIP3 projects the drying trend in the entire California on the average. And CMIP5 projects about half-degree more warming than CMIP3. As a result, Sacramento River rim inflow increases by 8% for CMIP5 and reduces by 3% for CMIP3. In spite of this difference in rim inflow, north of Delta carryover storage will be reduced both under CMIP5 (14%) and under CMIP3 (23%) in 2060. And south Delta export will be reduced both for CMIP5 (8%) and for CMIP3 (15%). Thus, The CC impact uncertainty caused by the selection of climate model projection (CMIP3 vs CMIP5) is about 7% in terms of Delta export and about 9% in terms of north of Delta carryover storage. This uncertainty is more than the one caused by the selection of sea level rise in that the climate change impact uncertainty caused by the selection of sea level rise (Zero vs 1.5ft SLR) is about 5% in terms of Delta export and about 4-5% in terms of North of Delta carryover storage.

The faint young sun-climate paradox - Volcanic influences

NASA Technical Reports Server (NTRS)

Schatten, K. H.; Endal, A. S.

1982-01-01

It has been suggested that the early earth may have frozen over as a result of a fainter early sun (see Ulrich, 1975). If this had happened, climate models suggest the earth would have remained frozen through the present epoch and into the distant future. We suggest that volcanic influences could allow a passage from the frozen branch into the unfrozen branch of climate models should conditions on earth be suitable for the latter climate change. A broad equatorial belt of volcanic ash is one scenario which would allow a transfer from the frozen earth state into the unfrozen one.

Impact of Climate Change Effects on Contamination of Cereal Grains with Deoxynivalenol

PubMed Central

Van der Fels-Klerx, H. J.; van Asselt, Esther D.; Madsen, Marianne S.; Olesen, Jørgen E.

2013-01-01

Climate change is expected to aggravate feed and food safety problems of crops; however, quantitative estimates are scarce. This study aimed to estimate impacts of climate change effects on deoxynivalenol contamination of wheat and maize grown in the Netherlands by 2040. Quantitative modelling was applied, considering both direct effects of changing climate on toxin contamination and indirect effects via shifts in crop phenology. Climate change projections for the IPCC A1B emission scenario were used for the scenario period 2031-2050 relative to the baseline period of 1975-1994. Climatic data from two different global and regional climate model combinations were used. A weather generator was applied for downscaling climate data to local conditions. Crop phenology models and prediction models for DON contamination used, each for winter wheat and grain maize. Results showed that flowering and full maturity of both wheat and maize will advance with future climate. Flowering advanced on average 5 and 11 days for wheat, and 7 and 14 days for maize (two climate model combinations). Full maturity was on average 10 and 17 days earlier for wheat, and 19 and 36 days earlier for maize. On the country level, contamination of wheat with deoxynivalenol decreased slightly, but not significantly. Variability between regions was large, and individual regions showed a significant increase in deoxynivalenol concentrations. For maize, an overall decrease in deoxynivalenol contamination was projected, which was significant for one climate model combination, but not significant for the other one. In general, results disagree with previous reported expectations of increased feed and food safety hazards under climate change. This study illustrated the relevance of using quantitative models to estimate the impacts of climate change effects on food safety, and of considering both direct and indirect effects when assessing climate change impacts on crops and related food safety hazards. PMID:24066059

Variational asymptotic modeling of composite dimensionally reducible structures

NASA Astrophysics Data System (ADS)

Yu, Wenbin

A general framework to construct accurate reduced models for composite dimensionally reducible structures (beams, plates and shells) was formulated based on two theoretical foundations: decomposition of the rotation tensor and the variational asymptotic method. Two engineering software systems, Variational Asymptotic Beam Sectional Analysis (VABS, new version) and Variational Asymptotic Plate and Shell Analysis (VAPAS), were developed. Several restrictions found in previous work on beam modeling were removed in the present effort. A general formulation of Timoshenko-like cross-sectional analysis was developed, through which the shear center coordinates and a consistent Vlasov model can be obtained. Recovery relations are given to recover the asymptotic approximations for the three-dimensional field variables. A new version of VABS has been developed, which is a much improved program in comparison to the old one. Numerous examples are given for validation. A Reissner-like model being as asymptotically correct as possible was obtained for composite plates and shells. After formulating the three-dimensional elasticity problem in intrinsic form, the variational asymptotic method was used to systematically reduce the dimensionality of the problem by taking advantage of the smallness of the thickness. The through-the-thickness analysis is solved by a one-dimensional finite element method to provide the stiffnesses as input for the two-dimensional nonlinear plate or shell analysis as well as recovery relations to approximately express the three-dimensional results. The known fact that there exists more than one theory that is asymptotically correct to a given order is adopted to cast the refined energy into a Reissner-like form. A two-dimensional nonlinear shell theory consistent with the present modeling process was developed. The engineering computer code VAPAS was developed and inserted into DYMORE to provide an efficient and accurate analysis of composite plates and shells. Numerical results are compared with the exact solutions, and the excellent agreement proves that one can use VAPAS to analyze composite plates and shells efficiently and accurately. In conclusion, rigorous modeling approaches were developed for composite beams, plates and shells within a general framework. No such consistent and general treatment is found in the literature. The associated computer programs VABS and VAPAS are envisioned to have many applications in industry.

Climate Envelope Modeling and Dispersal Simulations Show Little Risk of Range Extension of the Shipworm, Teredo navalis (L.), in the Baltic Sea

PubMed Central

Appelqvist, Christin; Al-Hamdani, Zyad K.; Jonsson, Per R.; Havenhand, Jon N.

2015-01-01

The shipworm, Teredo navalis, is absent from most of the Baltic Sea. In the last 20 years, increased frequency of T. navalis has been reported along the southern Baltic Sea coasts of Denmark, Germany, and Sweden, indicating possible range-extensions into previously unoccupied areas. We evaluated the effects of historical and projected near-future changes in salinity, temperature, and oxygen on the risk of spread of T. navalis in the Baltic. Specifically, we developed a simple, GIS-based, mechanistic climate envelope model to predict the spatial distribution of favourable conditions for adult reproduction and larval metamorphosis of T. navalis, based on published environmental tolerances to these factors. In addition, we used a high-resolution three-dimensional hydrographic model to simulate the probability of spread of T. navalis larvae within the study area. Climate envelope modeling showed that projected near-future climate change is not likely to change the overall distribution of T. navalis in the region, but will prolong the breeding season and increase the risk of shipworm establishment at the margins of the current range. Dispersal simulations indicated that the majority of larvae were philopatric, but those that spread over a wider area typically spread to areas unfavourable for their survival. Overall, therefore, we found no substantive evidence for climate-change related shifts in the distribution of T. navalis in the Baltic Sea, and no evidence for increased risk of spread in the near-future. PMID:25768305

Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2013-09-01

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

Impact of climate change on global malaria distribution.

PubMed

Caminade, Cyril; Kovats, Sari; Rocklov, Joacim; Tompkins, Adrian M; Morse, Andrew P; Colón-González, Felipe J; Stenlund, Hans; Martens, Pim; Lloyd, Simon J

2014-03-04

Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution.

Impact of climate change on global malaria distribution

PubMed Central

Caminade, Cyril; Kovats, Sari; Rocklov, Joacim; Tompkins, Adrian M.; Morse, Andrew P.; Colón-González, Felipe J.; Stenlund, Hans; Martens, Pim; Lloyd, Simon J.

2014-01-01

Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution. PMID:24596427

Assessing the impacts of sea-level rise and precipitation change on the surficial aquifer in the low-lying coastal alluvial plains and barrier islands, east-central Florida (USA)

NASA Astrophysics Data System (ADS)

Xiao, Han; Wang, Dingbao; Hagen, Scott C.; Medeiros, Stephen C.; Hall, Carlton R.

2016-11-01

A three-dimensional variable-density groundwater flow and salinity transport model is implemented using the SEAWAT code to quantify the spatial variation of water-table depth and salinity of the surficial aquifer in Merritt Island and Cape Canaveral Island in east-central Florida (USA) under steady-state 2010 hydrologic and hydrogeologic conditions. The developed model is referred to as the `reference' model and calibrated against field-measured groundwater levels and a map of land use and land cover. Then, five prediction/projection models are developed based on modification of the boundary conditions of the calibrated `reference' model to quantify climate change impacts under various scenarios of sea-level rise and precipitation change projected to 2050. Model results indicate that west Merritt Island will encounter lowland inundation and saltwater intrusion due to its low elevation and flat topography, while climate change impacts on Cape Canaveral Island and east Merritt Island are not significant. The SEAWAT models developed for this study are useful and effective tools for water resources management, land use planning, and climate-change adaptation decision-making in these and other low-lying coastal alluvial plains and barrier island systems.

Three-dimensional finite element modelling of muscle forces during mastication.

PubMed

Röhrle, Oliver; Pullan, Andrew J

2007-01-01

This paper presents a three-dimensional finite element model of human mastication. Specifically, an anatomically realistic model of the masseter muscles and associated bones is used to investigate the dynamics of chewing. A motion capture system is used to track the jaw motion of a subject chewing standard foods. The three-dimensional nonlinear deformation of the masseter muscles are calculated via the finite element method, using the jaw motion data as boundary conditions. Motion-driven muscle activation patterns and a transversely isotropic material law, defined in a muscle-fibre coordinate system, are used in the calculations. Time-force relationships are presented and analysed with respect to different tasks during mastication, e.g. opening, closing, and biting, and are also compared to a more traditional one-dimensional model. The results strongly suggest that, due to the complex arrangement of muscle force directions, modelling skeletal muscles as conventional one-dimensional lines of action might introduce a significant source of error.

Unsteady free surface flow in porous media: One-dimensional model equations including vertical effects and seepage face

NASA Astrophysics Data System (ADS)

Di Nucci, Carmine

2018-05-01

This note examines the two-dimensional unsteady isothermal free surface flow of an incompressible fluid in a non-deformable, homogeneous, isotropic, and saturated porous medium (with zero recharge and neglecting capillary effects). Coupling a Boussinesq-type model for nonlinear water waves with Darcy's law, the two-dimensional flow problem is solved using one-dimensional model equations including vertical effects and seepage face. In order to take into account the seepage face development, the system equations (given by the continuity and momentum equations) are completed by an integral relation (deduced from the Cauchy theorem). After testing the model against data sets available in the literature, some numerical simulations, concerning the unsteady flow through a rectangular dam (with an impermeable horizontal bottom), are presented and discussed.

Role of dimensionality in Axelrod's model for the dissemination of culture

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; Miguel, Maxi San

2003-09-01

We analyze a model of social interaction in one- and two-dimensional lattices for a moderate number of features. We introduce an order parameter as a function of the overlap between neighboring sites. In a one-dimensional chain, we observe that the dynamics is consistent with a second-order transition, where the order parameter changes continuously and the average domain diverges at the transition point. However, in a two-dimensional lattice the order parameter is discontinuous at the transition point characteristic of a first-order transition between an ordered and a disordered state.

Thermoelastic damping in thin microrings with two-dimensional heat conduction

NASA Astrophysics Data System (ADS)

Fang, Yuming; Li, Pu

2015-05-01

Accurate determination of thermoelastic damping (TED) is very challenging in the design of micro-resonators. Microrings are widely used in many micro-resonators. In the past, to model the TED effect on the microrings, some analytical models have been developed. However, in the previous works, the heat conduction within the microring is modeled by using the one-dimensional approach. The governing equation for heat conduction is solved only for the one-dimensional heat conduction along the radial thickness of the microring. This paper presents a simple analytical model for TED in microrings. The two-dimensional heat conduction over the thermoelastic temperature gradients along the radial thickness and the circumferential direction are considered in the present model. A two-dimensional heat conduction equation is developed. The solution of the equation is represented by the product of an assumed sine series along the radial thickness and an assumed trigonometric series along the circumferential direction. The analytical results obtained by the present 2-D model show a good agreement with the numerical (FEM) results. The limitations of the previous 1-D model are assessed.

Limitations of one-dimensional mesoscale PBL parameterizations in reproducing mountain-wave flows

DOE PAGES

Munoz-Esparza, Domingo; Sauer, Jeremy A.; Linn, Rodman R.; ...

2015-12-08

In this study, mesoscale models are considered to be the state of the art in modeling mountain-wave flows. Herein, we investigate the role and accuracy of planetary boundary layer (PBL) parameterizations in handling the interaction between large-scale mountain waves and the atmospheric boundary layer. To that end, we use recent large-eddy simulation (LES) results of mountain waves over a symmetric two-dimensional bell-shaped hill [Sauer et al., J. Atmos. Sci. (2015)], and compare them to four commonly used PBL schemes. We find that one-dimensional PBL parameterizations produce reasonable agreement with the LES results in terms of vertical wavelength, amplitude of velocitymore » and turbulent kinetic energy distribution in the downhill shooting flow region. However, the assumption of horizontal homogeneity in PBL parameterizations does not hold in the context of these complex flow configurations. This inappropriate modeling assumption results in a vertical wavelength shift producing errors of ≈ 10 m s–1 at downstream locations due to the presence of a coherent trapped lee wave that does not mix with the atmospheric boundary layer. In contrast, horizontally-integrated momentum flux derived from these PBL schemes displays a realistic pattern. Therefore results from mesoscale models using ensembles of one-dimensional PBL schemes can still potentially be used to parameterize drag effects in general circulation models. Nonetheless, three-dimensional PBL schemes must be developed in order for mesoscale models to accurately represent complex-terrain and other types of flows where one-dimensional PBL assumptions are violated.« less

The Effects of Climate Model Similarity on Local, Risk-Based Adaptation Planning

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Brown, C. M.

2014-12-01

The climate science community has recently proposed techniques to develop probabilistic projections of climate change from ensemble climate model output. These methods provide a means to incorporate the formal concept of risk, i.e., the product of impact and probability, into long-term planning assessments for local systems under climate change. However, approaches for pdf development often assume that different climate models provide independent information for the estimation of probabilities, despite model similarities that stem from a common genealogy. Here we utilize an ensemble of projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to develop probabilistic climate information, with and without an accounting of inter-model correlations, and use it to estimate climate-related risks to a local water utility in Colorado, U.S. We show that the tail risk of extreme climate changes in both mean precipitation and temperature is underestimated if model correlations are ignored. When coupled with impact models of the hydrology and infrastructure of the water utility, the underestimation of extreme climate changes substantially alters the quantification of risk for water supply shortages by mid-century. We argue that progress in climate change adaptation for local systems requires the recognition that there is less information in multi-model climate ensembles than previously thought. Importantly, adaptation decisions cannot be limited to the spread in one generation of climate models.

Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)

USGS Publications Warehouse

Hay, Lauren E.; LaFontaine, Jacob H.; Markstrom, Steven

2014-01-01

The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.

Identification of Atmospheric Blocking Events and its Influence on Temperature and Precipitation Extremes in Europe

NASA Astrophysics Data System (ADS)

Richling, Andy; Rust, Henning W.; Bissolli, Peter; Ulbrich, Uwe

2017-04-01

Atmospheric blocking plays a crucial role in climate variability in the mid-latitudes. Especially meteorological extremes like heatwaves, cold spells and droughts are often related to persistent and stationary blocking events. For climate monitoring it is important to identify and characterise such blocking events as well as to analyse the relationship between blockings and meteorological extremes in a quantitative way. In this study we identify atmospheric blocking events and analyse the influence on temperature and precipitation extremes with statistical models. For the detection of atmospheric blocking events, we apply modified 2-dimensional versions of commonly used blocking indices suggested by Tibaldi and Molteni (1990) as well as Masato et al. (2013) on daily fields of 500hPa geopotential heights of the Era-Interim reanalysis dataset. A result is a list of blocking events with a multidimensional index characterising area, intensity, location and duration and maps of these parameters, which are intended to be used operationally for regular climate diagnostics at the German Meteorological Service. In addition, relationships between grid-point-base blocking frequency, intensity and location parameters and the number of daily temperature/precipitation extremes based on the E-OBS gridded dataset are investigated using general linear models on a monthly time scale. The number of counts as well as probabilities of occurrence of daily extremes within a certain calendar month will be analysed in this framework. G. Masato, B. J. Hoskins, and T. Woollings. Winter and Summer Northern Hemisphere Blocking in CMIP5 Models. J. Climate, 26:7044-7059, 2013a. doi: http://dx.doi.org/10.1175/JCLI-D- 12-00466.1. G. Masato, B. J. Hoskins, and T. Woollings. Wave-Breaking Characteristics of Northern Hemi- sphere Winter Blocking: A Two-Dimensional Approach. J. Climate, 26:4535-4549, 2013b. doi: http://dx.doi.org/10.1175/JCLI-D-12-00240.1. S. Tibaldi and F. Molteni. On the operational predictability of blocking. Tellus, 42A:343-365, 1990. doi: 10.1034/j.1600-0870.1990.t01-2-00003.x.

Separation of the atmospheric variability into non-Gaussian multidimensional sources by projection pursuit techniques

NASA Astrophysics Data System (ADS)

Pires, Carlos A. L.; Ribeiro, Andreia F. S.

2017-02-01

We develop an expansion of space-distributed time series into statistically independent uncorrelated subspaces (statistical sources) of low-dimension and exhibiting enhanced non-Gaussian probability distributions with geometrically simple chosen shapes (projection pursuit rationale). The method relies upon a generalization of the principal component analysis that is optimal for Gaussian mixed signals and of the independent component analysis (ICA), optimized to split non-Gaussian scalar sources. The proposed method, supported by information theory concepts and methods, is the independent subspace analysis (ISA) that looks for multi-dimensional, intrinsically synergetic subspaces such as dyads (2D) and triads (3D), not separable by ICA. Basically, we optimize rotated variables maximizing certain nonlinear correlations (contrast functions) coming from the non-Gaussianity of the joint distribution. As a by-product, it provides nonlinear variable changes `unfolding' the subspaces into nearly Gaussian scalars of easier post-processing. Moreover, the new variables still work as nonlinear data exploratory indices of the non-Gaussian variability of the analysed climatic and geophysical fields. The method (ISA, followed by nonlinear unfolding) is tested into three datasets. The first one comes from the Lorenz'63 three-dimensional chaotic model, showing a clear separation into a non-Gaussian dyad plus an independent scalar. The second one is a mixture of propagating waves of random correlated phases in which the emergence of triadic wave resonances imprints a statistical signature in terms of a non-Gaussian non-separable triad. Finally the method is applied to the monthly variability of a high-dimensional quasi-geostrophic (QG) atmospheric model, applied to the Northern Hemispheric winter. We find that quite enhanced non-Gaussian dyads of parabolic shape, perform much better than the unrotated variables in which concerns the separation of the four model's centroid regimes (positive and negative phases of the Arctic Oscillation and of the North Atlantic Oscillation). Triads are also likely in the QG model but of weaker expression than dyads due to the imposed shape and dimension. The study emphasizes the existence of nonlinear dyadic and triadic nonlinear teleconnections.

Mixing Regimes in a Spatially Confined, Two-Dimensional, Supersonic Shear Layer

DTIC Science & Technology

1992-07-31

MODEL ................................... 3 THE MODEL PROBLEMS .............................................. 6 THE ONE-DIMENSIONAL PROBLEM...the effects of the numerical diffusion on the spectrum. Guirguis et al.ś and Farouk et al."’ have studied spatially evolving mixing layers for equal...approximations. Physical and Numerical Model General Formulation We solve the time-dependent, two-dimensional, compressible, Navier-Stokes equations for a

Effects of climate change on aerosol concentrations in Europe

NASA Astrophysics Data System (ADS)

Megaritis, Athanasios G.; Fountoukis, Christos; Pandis, Spyros N.

2013-04-01

High concentrations of particulate matter less than 2.5 μm in size (PM2.5), ozone and other major constituents of air pollution, have adverse effects on human health, visibility and ecosystems (Seinfeld and Pandis, 2006), and are strongly influenced by meteorology. Emissions control policy is currently made assuming that climate will remain constant in the future. However, climate change over the next decades is expected to be significant (IPCC, 2007) and may impact local and regional air quality. Determining the sensitivity of the concentrations of air pollutants to climate change is an important step toward estimating future air quality. In this study we applied PMCAMx (Fountoukis et al., 2011), a three dimensional chemical transport model, over Europe, in order to quantify the individual effects of various meteorological parameters on fine particulate matter (PM2.5) concentrations. A suite of perturbations in various meteorological factors, such as temperature, wind speed, absolute humidity and precipitation were imposed separately on base case conditions to determine the sensitivities of PM2.5 concentrations and composition to these parameters. Different simulation periods (summer, autumn 2008 and winter 2009) are used to examine also the seasonal dependence of the air quality - climate interactions. The results of these sensitivity simulations suggest that there is an important link between changes in meteorology and PM2.5 levels. We quantify through separate sensitivity simulations the processes which are mainly responsible for the final predicted changes in PM2.5 concentration and composition. The predicted PM2.5 response to those meteorology perturbations was found to be quite variable in space and time. These results suggest that, the changes in concentrations caused by changes in climate should be taken into account in long-term air quality planning. References Fountoukis C., Racherla P. N., Denier van der Gon H. A. C., Polymeneas P., Charalampidis P. E., Pilinis C., Wiedensohler A., Dall'Osto M., O'Dowd C., and S. N. Pandis: Evaluation of a three-dimensional chemical transport model (PMCAMx) in the European domain during the EUCAARI May 2008 campaign, Atmos. Chem. Phys., 11, 10331-10347, 2011. Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report: Summary for Policymakers, 2007. Seinfeld, J. H., and Pandis, S. N.: Atmospheric chemistry and physics: From air pollution to climate change, 2nd ed.; John Wiley and Sons, Hoboken, NJ, 2006.

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

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

Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.

2013-12-01

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less

The Social Network of Tracer Variations and O(100) Uncertain Photochemical Parameters in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Labute, M.; Chowdhary, K.; Debusschere, B.; Cameron-Smith, P. J.

2014-12-01

Simulating the atmospheric cycles of ozone, methane, and other radiatively important trace gases in global climate models is computationally demanding and requires the use of 100's of photochemical parameters with uncertain values. Quantitative analysis of the effects of these uncertainties on tracer distributions, radiative forcing, and other model responses is hindered by the "curse of dimensionality." We describe efforts to overcome this curse using ensemble simulations and advanced statistical methods. Uncertainties from 95 photochemical parameters in the trop-MOZART scheme were sampled using a Monte Carlo method and propagated through 10,000 simulations of the single column version of the Community Atmosphere Model (CAM). The variance of the ensemble was represented as a network with nodes and edges, and the topology and connections in the network were analyzed using lasso regression, Bayesian compressive sensing, and centrality measures from the field of social network theory. Despite the limited sample size for this high dimensional problem, our methods determined the key sources of variation and co-variation in the ensemble and identified important clusters in the network topology. Our results can be used to better understand the flow of photochemical uncertainty in simulations using CAM and other climate models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC).

Numerical Modeling of One-Dimensional Steady-State Flow and Contaminant Transport in a Horizontally Heterogeneous Unconfined Aquifer with an Uneven Base

EPA Science Inventory

Algorithms and a short description of the D1_Flow program for numerical modeling of one-dimensional steady-state flow in horizontally heterogeneous aquifers with uneven sloping bases are presented. The algorithms are based on the Dupuit-Forchheimer approximations. The program per...

Markov-switching multifractal models as another class of random-energy-like models in one-dimensional space

NASA Astrophysics Data System (ADS)

Saakian, David B.

2012-03-01

We map the Markov-switching multifractal model (MSM) onto the random energy model (REM). The MSM is, like the REM, an exactly solvable model in one-dimensional space with nontrivial correlation functions. According to our results, four different statistical physics phases are possible in random walks with multifractal behavior. We also introduce the continuous branching version of the model, calculate the moments, and prove multiscaling behavior. Different phases have different multiscaling properties.

Thermal model development and validation for rapid filling of high pressure hydrogen tanks

DOE PAGES

Johnson, Terry A.; Bozinoski, Radoslav; Ye, Jianjun; ...

2015-06-30

This paper describes the development of thermal models for the filling of high pressure hydrogen tanks with experimental validation. Two models are presented; the first uses a one-dimensional, transient, network flow analysis code developed at Sandia National Labs, and the second uses the commercially available CFD analysis tool Fluent. These models were developed to help assess the safety of Type IV high pressure hydrogen tanks during the filling process. The primary concern for these tanks is due to the increased susceptibility to fatigue failure of the liner caused by the fill process. Thus, a thorough understanding of temperature changes ofmore » the hydrogen gas and the heat transfer to the tank walls is essential. The effects of initial pressure, filling time, and fill procedure were investigated to quantify the temperature change and verify the accuracy of the models. In this paper we show that the predictions of mass averaged gas temperature for the one and three-dimensional models compare well with the experiment and both can be used to make predictions for final mass delivery. Furthermore, due to buoyancy and other three-dimensional effects, however, the maximum wall temperature cannot be predicted using one-dimensional tools alone which means that a three-dimensional analysis is required for a safety assessment of the system.« less

The importance of terrestrial weathering for climate system modelling on extended timescales: a study with the UVic ESCM

NASA Astrophysics Data System (ADS)

Brault, Marc-Olivier; Matthews, Damon; Mysak, Lawrence

2016-04-01

The chemical erosion of carbonate and silicate rocks is a key process in the global carbon cycle and, through its coupling with calcium carbonate deposition in the ocean, is the primary sink of carbon on geologic timescales. The dynamic interdependence of terrestrial weathering rates with atmospheric temperature and carbon dioxide concentrations is crucial to the regulation of Earth's climate over multi-millennial timescales. However any attempts to develop a modeling context for terrestrial weathering as part of a dynamic climate system are limited, mostly because of the difficulty in adapting the multi-millennial timescales of the implied negative feedback mechanism with those of the atmosphere and ocean. Much of the earlier work on this topic is therefore based on box-model approaches, abandoning spatial variability for the sake of computational efficiency and the possibility to investigate the impact of weathering on climate change over time frames much longer than those allowed by traditional climate system models. As a result we still have but a rudimentary understanding of the chemical weathering feedback mechanism and its effects on ocean biogeochemistry and atmospheric CO2. Here, we introduce a spatially-explicit, rock weathering model into the University of Victoria Earth System Climate Model (UVic ESCM). We use a land map which takes into account a number of different rock lithologies, changes in sea level, as well as an empirical model of the temperature and NPP dependency of weathering rates for the different rock types. We apply this new model to the last deglacial period (c. 21000BP to 13000BP) as well as a future climate change scenario (c. 1800AD to 6000AD+), comparing the results of our 2-D version of the weathering feedback mechanism to simulations using only the box-model parameterizations of Meissner et al. [2012]. These simulations reveal the importance of two-dimensional factors (i.e., changes in sea level and rock type distribution) in the role of the weathering negative feedback mechanism on multi-millennial timescales.

Semiclassical description of resonance-assisted tunneling in one-dimensional integrable models

NASA Astrophysics Data System (ADS)

Le Deunff, Jérémy; Mouchet, Amaury; Schlagheck, Peter

2013-10-01

Resonance-assisted tunneling is investigated within the framework of one-dimensional integrable systems. We present a systematic recipe, based on Hamiltonian normal forms, to construct one-dimensional integrable models that exhibit resonance island chain structures with accurately controlled sizes and positions of the islands. Using complex classical trajectories that evolve along suitably defined paths in the complex time domain, we construct a semiclassical theory of the resonance-assisted tunneling process. This semiclassical approach yields a compact analytical expression for tunnelling-induced level splittings which is found to be in very good agreement with the exact splittings obtained through numerical diagonalization.

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Starr, David (Technical Monitor)

2002-01-01

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.

Explicit Convection over the Western Pacific Warm Pool in the Community Atmospheric Model.

NASA Astrophysics Data System (ADS)

Ziemiaski, Micha Z.; Grabowski, Wojciech W.; Moncrieff, Mitchell W.

2005-05-01

This paper reports on the application of the cloud-resolving convection parameterization (CRCP) to the Community Atmospheric Model (CAM), the atmospheric component of the Community Climate System Model (CCSM). The cornerstone of CRCP is the use of a two-dimensional zonally oriented cloud-system-resolving model to represent processes on mesoscales at the subgrid scale of a climate model. Herein, CRCP is applied at each climate model column over the tropical western Pacific warm pool, in a domain spanning 10°S-10°N, 150°-170°E. Results from the CRCP simulation are compared with CAM in its standard configuration.The CRCP simulation shows significant improvements of the warm pool climate. The cloud condensate distribution is much improved as well as the bias of the tropopause height. More realistic structure of the intertropical convergence zone (ITCZ) during the boreal winter and better representation of the variability of convection are evident. In particular, the diurnal cycle of precipitation has phase and amplitude in good agreement with observations. Also improved is the large-scale organization of the tropical convection, especially superclusters associated with Madden-Julian oscillation (MJO)-like systems. Location and propagation characteristics, as well as lower-tropospheric cyclonic and upper-tropospheric anticyclonic gyres, are more realistic than in the standard CAM. Finally, the simulations support an analytic theory of dynamical coupling between organized convection and equatorial beta-plane vorticity dynamics associated with MJO-like systems.

Tropical rainforest response to marine sky brightening climate engineering

NASA Astrophysics Data System (ADS)

Muri, Helene; Niemeier, Ulrike; Kristjánsson, Jón Egill

2015-04-01

Tropical forests represent a major atmospheric carbon dioxide sink. Here the gross primary productivity (GPP) response of tropical rainforests to climate engineering via marine sky brightening under a future scenario is investigated in three Earth system models. The model response is diverse, and in two of the three models, the tropical GPP shows a decrease from the marine sky brightening climate engineering. Partial correlation analysis indicates precipitation to be important in one of those models, while precipitation and temperature are limiting factors in the other. One model experiences a reversal of its Amazon dieback under marine sky brightening. There, the strongest partial correlation of GPP is to temperature and incoming solar radiation at the surface. Carbon fertilization provides a higher future tropical rainforest GPP overall, both with and without climate engineering. Salt damage to plants and soils could be an important aspect of marine sky brightening.

Impacts of Large-Scale Circulation on Convection: A 2-D Cloud Resolving Model Study

NASA Technical Reports Server (NTRS)

Li, X; Sui, C.-H.; Lau, K.-M.

1999-01-01

Studies of impacts of large-scale circulation on convection, and the roles of convection in heat and water balances over tropical region are fundamentally important for understanding global climate changes. Heat and water budgets over warm pool (SST=29.5 C) and cold pool (SST=26 C) were analyzed based on simulations of the two-dimensional cloud resolving model. Here the sensitivity of heat and water budgets to different sizes of warm and cold pools is examined.

Climate and smoke - An appraisal of nuclear winter

NASA Technical Reports Server (NTRS)

Turco, R. P.; Toon, O. B.; Pollack, J. B.; Ackerman, T. P.; Sagan, C.

1990-01-01

A reevaluation is presented of the 'nuclear winter' scenario of Turco et al. (1983). New pertinent data have emerged from laboratory studies, field experiments, and numerical models on the smoke-plume, mesoscale, and global scales. A full-scale nuclear exchange's probable soot injections lead, in three-dimensional climate simulations, to midsummer land temperature decreases averaging 10-20 C in northern midlatitudes, with local cooling of as much as 35 C. Anomalous circulation patterns due to solar heating of the soot could stabilize the upper atmosphere against overturning, thereby prolonging the soot's residence time in the atmosphere. Monsoon disruptions and severe ozone layer depletion are also foreseen.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Decadal shifts of East Asian summer monsoon in a climate model free of explicit GHGs and aerosols

NASA Astrophysics Data System (ADS)

Lin, Renping; Zhu, Jiang; Zheng, Fei

2016-12-01

The East Asian summer monsoon (EASM) experienced decadal transitions over the past few decades, and the associated "wetter-South-drier-North" shifts in rainfall patterns in China significantly affected the social and economic development in China. Two viewpoints stand out to explain these decadal shifts, regarding the shifts either a result of internal variability of climate system or that of external forcings (e.g. greenhouse gases (GHGs) and anthropogenic aerosols). However, most climate models, for example, the Atmospheric Model Intercomparison Project (AMIP)-type simulations and the Coupled Model Intercomparison Project (CMIP)-type simulations, fail to simulate the variation patterns, leaving the mechanisms responsible for these shifts still open to dispute. In this study, we conducted a successful simulation of these decadal transitions in a coupled model where we applied ocean data assimilation in the model free of explicit aerosols and GHGs forcing. The associated decadal shifts of the three-dimensional spatial structure in the 1990s, including the eastward retreat, the northward shift of the western Pacific subtropical high (WPSH), and the south-cool-north-warm pattern of the upper-level tropospheric temperature, were all well captured. Our simulation supports the argument that the variations of the oceanic fields are the dominant factor responsible for the EASM decadal transitions.

Decadal shifts of East Asian summer monsoon in a climate model free of explicit GHGs and aerosols

PubMed Central

Lin, Renping; Zhu, Jiang; Zheng, Fei

2016-01-01

The East Asian summer monsoon (EASM) experienced decadal transitions over the past few decades, and the associated "wetter-South-drier-North" shifts in rainfall patterns in China significantly affected the social and economic development in China. Two viewpoints stand out to explain these decadal shifts, regarding the shifts either a result of internal variability of climate system or that of external forcings (e.g. greenhouse gases (GHGs) and anthropogenic aerosols). However, most climate models, for example, the Atmospheric Model Intercomparison Project (AMIP)-type simulations and the Coupled Model Intercomparison Project (CMIP)-type simulations, fail to simulate the variation patterns, leaving the mechanisms responsible for these shifts still open to dispute. In this study, we conducted a successful simulation of these decadal transitions in a coupled model where we applied ocean data assimilation in the model free of explicit aerosols and GHGs forcing. The associated decadal shifts of the three-dimensional spatial structure in the 1990s, including the eastward retreat, the northward shift of the western Pacific subtropical high (WPSH), and the south-cool-north-warm pattern of the upper-level tropospheric temperature, were all well captured. Our simulation supports the argument that the variations of the oceanic fields are the dominant factor responsible for the EASM decadal transitions. PMID:27934933

Fast chemical reaction in two-dimensional Navier-Stokes flow: initial regime.

PubMed

Ait-Chaalal, Farid; Bourqui, Michel S; Bartello, Peter

2012-04-01

This paper studies an infinitely fast bimolecular chemical reaction in a two-dimensional biperiodic Navier-Stokes flow. The reactants in stoichiometric quantities are initially segregated by infinite gradients. The focus is placed on the initial stage of the reaction characterized by a well-defined one-dimensional material contact line between the reactants. Particular attention is given to the effect of the diffusion κ of the reactants. This study is an idealized framework for isentropic mixing in the lower stratosphere and is motivated by the need to better understand the effect of resolution on stratospheric chemistry in climate-chemistry models. Adopting a Lagrangian straining theory approach, we relate theoretically the ensemble mean of the length of the contact line, of the gradients along it, and of the modulus of the time derivative of the space-average reactant concentrations (here called the chemical speed) to the joint probability density function of the finite-time Lyapunov exponent λ with two times τ and τ[over ̃]. The time 1/λ measures the stretching time scale of a Lagrangian parcel on a chaotic orbit up to a finite time t, while τ measures it in the recent past before t, and τ[over ̃] in the early part of the trajectory. We show that the chemical speed scales like κ(1/2) and that its time evolution is determined by rare large events in the finite-time Lyapunov exponent distribution. The case of smooth initial gradients is also discussed. The theoretical results are tested with an ensemble of direct numerical simulations (DNSs) using a pseudospectral model.

TPSLVM: a dimensionality reduction algorithm based on thin plate splines.

PubMed

Jiang, Xinwei; Gao, Junbin; Wang, Tianjiang; Shi, Daming

2014-10-01

Dimensionality reduction (DR) has been considered as one of the most significant tools for data analysis. One type of DR algorithms is based on latent variable models (LVM). LVM-based models can handle the preimage problem easily. In this paper we propose a new LVM-based DR model, named thin plate spline latent variable model (TPSLVM). Compared to the well-known Gaussian process latent variable model (GPLVM), our proposed TPSLVM is more powerful especially when the dimensionality of the latent space is low. Also, TPSLVM is robust to shift and rotation. This paper investigates two extensions of TPSLVM, i.e., the back-constrained TPSLVM (BC-TPSLVM) and TPSLVM with dynamics (TPSLVM-DM) as well as their combination BC-TPSLVM-DM. Experimental results show that TPSLVM and its extensions provide better data visualization and more efficient dimensionality reduction compared to PCA, GPLVM, ISOMAP, etc.

Calibration and validation of a one-dimensional complex marine biogeochemical flux model in different areas of the northern Adriatic shelf

NASA Astrophysics Data System (ADS)

Vichi, M.; Oddo, P.; Zavatarelli, M.; Coluccelli, A.; Coppini, G.; Celio, M.; Fonda Umani, S.; Pinardi, N.

2003-01-01

In this paper we show results from numerical simulations carried out with a complex biogeochemical fluxes model coupled with a one-dimensional high-resolution hydrodynamical model and implemented at three different locations of the northern Adriatic shelf. One location is directly affected by the Po River influence, one has more open-sea characteristics and one is located in the Gulf of Trieste with an intermediate behavior; emphasis is put on the comparison with observations and on the functioning of the northern Adriatic ecosystem in the three areas. The work has been performed in a climatological context and has to be considered as preliminary to the development of three-dimensional numerical simulations. Biogeochemical model parameterizations have been ameliorated with a detailed description of bacterial substrate utilization associated with the quality of the dissolved organic matter (DOM), in order to improve the models capability in capturing the observed DOM dynamics in the basin. The coupled model has been calibrated and validated at the three locations by means of climatological data sets. Results show satisfactory model behavior in simulating local seasonal dynamics in the limit of the available boundary conditions and the one-dimensional implementation. Comparisons with available measurements of primary and bacterial production and bacterial abundances have been performed in all locations. Model simulated rates and bacterial dynamics are in the same order of magnitude of observations and show a qualitatively correct time evolution. The importance of temperature as a factor controlling bacteria efficiency is investigated with sensitivity experiments on the model parameterizations.

Beyond Sexual Assault Surveys: A Model for Comprehensive Campus Climate Assessments

ERIC Educational Resources Information Center

McMahon, Sarah; Stepleton, Kate; Cusano, Julia; O'Connor, Julia; Gandhi, Khushbu; McGinty, Felicia

2018-01-01

The White House Task Force to Protect Students from Sexual Assault identified campus climate surveys as "the first step" for addressing campus sexual violence. Through a process case study, this article presents one model for engaging in a comprehensive, action-focused campus climate assessment process. Rooted in principles of…

Effects of convective ice evaporation on interannual variability of tropical tropopause layer water vapor

NASA Astrophysics Data System (ADS)

Ye, Hao; Dessler, Andrew E.; Yu, Wandi

2018-04-01

Water vapor interannual variability in the tropical tropopause layer (TTL) is investigated using satellite observations and model simulations. We break down the influences of the Brewer-Dobson circulation (BDC), the quasi-biennial oscillation (QBO), and the tropospheric temperature (ΔT) on TTL water vapor as a function of latitude and longitude using a two-dimensional multivariate linear regression. This allows us to examine the spatial distribution of the impact of each process on TTL water vapor. In agreement with expectations, we find that the impacts from the BDC and QBO act on TTL water vapor by changing TTL temperature. For ΔT, we find that TTL temperatures alone cannot explain the influence. We hypothesize a moistening role for the evaporation of convective ice from increased deep convection as the troposphere warms. Tests using a chemistry-climate model, the Goddard Earth Observing System Chemistry Climate Model (GEOSCCM), support this hypothesis.

A Catchment-Based Approach to Modeling Land Surface Processes in a GCM. Part 1; Model Structure

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, Max J.; Ducharne, Agnes; Stieglitz, Marc; Kumar, Praveen

2000-01-01

A new strategy for modeling the land surface component of the climate system is described. The strategy is motivated by an arguable deficiency in most state-of-the-art land surface models (LSMs), namely the disproportionately higher emphasis given to the formulation of one-dimensional, vertical physics relative to the treatment of horizontal heterogeneity in surface properties -- particularly subgrid soil moisture variability and its effects on runoff generation. The new strategy calls for the partitioning of the continental surface into a mosaic of hydrologic catchments, delineated through analysis of high-resolution surface elevation data. The effective "grid" used for the land surface is therefore not specified by the overlying atmospheric grid. Within each catchment, the variability of soil moisture is related to characteristics of the topography and to three bulk soil moisture variables through a well-established model of catchment processes. This modeled variability allows the partitioning of the catchment into several areas representing distinct hydrological regimes, wherein distinct (regime-specific) evaporation and runoff parameterizations are applied. Care is taken to ensure that the deficiencies of the catchment model in regions of little to moderate topography are minimized.

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.

Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099

USGS Publications Warehouse

Wood, Tamara M.; Wherry, Susan A.; Piccolroaz, Sebastiano; Girdner, Scott F

2016-05-04

The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.

Coupled Atmosphere-Surface Modeling of Lake Levels of the North American Great Lakes under Climate Change

NASA Astrophysics Data System (ADS)

Lofgren, B. M.; Xiao, C.

2016-12-01

The influence of projected climate change on the water levels of the Great Lakes is subject to considerable uncertainty, and methods that have long been used to determine this sensitivity have been discredited. A strong candidate, albeit expensive, to replace problematic methods is to use outputs that result from dynamical downscaling of future climate simulations, focused on the hydroclimate of the Great Lakes basin. We have produced initial estimates of Great Lakes water levels in the mid- and late 21st century using the Weather Research and Forecasting (WRF) model, including its lake module, driven by lateral boundary conditions from the Geophysical Fluid Dynamics Lab Climate Model version 3.0 (GFDL CM3), under RCP4.5 and 8.5 scenarios. Future lake levels are influenced by the balance between projected general increases in precipitation and increases in evapotranspiration from both land and lake in the basin, driven primarily by the surface radiative energy budget and secondarily by air temperature. The net result was drops in lake level of up to 15 cm, in contrast to the results from much-used older methods, which often projected drops exceeding 1 m. Future plans include increased detail in the simulation of water flow overland and in river channels using WRF-Hydro, and full coupling of regional atmospheric systems with 3-dimensional dynamical lake implementation of the Finite Volume Community Ocean Model (FVCOM).

Quasi-one-dimensional Hall physics in the Harper–Hofstadter–Mott model

NASA Astrophysics Data System (ADS)

Kozarski, Filip; Hügel, Dario; Pollet, Lode

2018-04-01

We study the ground-state phase diagram of the strongly interacting Harper–Hofstadter–Mott model at quarter flux on a quasi-one-dimensional lattice consisting of a single magnetic flux quantum in y-direction. In addition to superfluid phases with various density patterns, the ground-state phase diagram features quasi-one-dimensional analogs of fractional quantum Hall phases at fillings ν = 1/2 and 3/2, where the latter is only found thanks to the hopping anisotropy and the quasi-one-dimensional geometry. At integer fillings—where in the full two-dimensional system the ground-state is expected to be gapless—we observe gapped non-degenerate ground-states: at ν = 1 it shows an odd ‘fermionic’ Hall conductance, while the Hall response at ν = 2 consists of the transverse transport of a single particle–hole pair, resulting in a net zero Hall conductance. The results are obtained by exact diagonalization and in the reciprocal mean-field approximation.

On the dynamics of the Ising model of cooperative phenomena

PubMed Central

Montroll, Elliott W.

1981-01-01

A two-dimensional (and to some degree three-dimensional) version of Glauber's one-dimensional spin relaxation model is described. The model is constructed to yield the Ising model of cooperative phenomena at equilibrium. A complete hierarchy of differential equations for multispin correlation functions is constructed. Some remarks are made concerning the solution of them for the initial value problem of determining the relaxation of an initial set of spin distributions. PMID:16592955

Development of a Three Dimensional Wireless Sensor Network for Terrain-Climate Research in Remote Mountainous Environments

NASA Astrophysics Data System (ADS)

Kavanagh, K.; Davis, A.; Gessler, P.; Hess, H.; Holden, Z.; Link, T. E.; Newingham, B. A.; Smith, A. M.; Robinson, P.

2011-12-01

Developing sensor networks that are robust enough to perform in the world's remote regions is critical since these regions serve as important benchmarks compared to human-dominated areas. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. We aim to overcome these challenges by developing a three-dimensional sensor network arrayed across a topoclimatic gradient (1100-1800 meters) in a wilderness area in central Idaho. Development of this sensor array builds upon advances in sensing, networking, and power supply technologies coupled with experiences of the multidisciplinary investigators in conducting research in remote mountainous locations. The proposed gradient monitoring network will provide near real-time data from a three-dimensional (3-D) array of sensors measuring biophysical parameters used in ecosystem process models. The network will monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, tree stem growth and leaf wetness at time intervals ranging from seconds to days. The long-term goal of this project is to realize a transformative integration of smart sensor networks adaptively communicating data in real-time to ultimately achieve a 3-D visualization of ecosystem processes within remote mountainous regions. Process models will be the interface between the visualization platforms and the sensor network. This will allow us to better predict how non-human dominated terrestrial and aquatic ecosystems function and respond to climate dynamics. Access to the data will be ensured as part of the Northwest Knowledge Network being developed at the University of Idaho, through ongoing Idaho NSF-funded cyber infrastructure initiatives, and existing data management systems funded by NSF, such as the CUAHSI Hydrologic Information System (HIS). These efforts will enhance cross-disciplinary understanding of natural and anthropogenic influences on ecosystem function and ultimately inform decision-making.

Middle School Improvement and Reform: Development and Validation of a School-Level Assessment of Climate, Cultural Pluralism, and School Safety.

ERIC Educational Resources Information Center

Brand, Stephen; Felner, Robert; Shim, Minsuk; Seitsinger, Anne; Dumas, Thaddeus

2003-01-01

Examines the structure of perceived school climate and the relationship of climate dimensions to adaptation of students who attend middle-grade-level schools. The climate scales exhibited a stable dimensional structure, high levels of internal consistency, and moderate levels of stability. Ratings of multiple climate dimensions were associated…

Orbital Noise in the Earth System and Climate Fluctuations

NASA Technical Reports Server (NTRS)

Liu, Han-Shou; Smith, David E. (Technical Monitor)

2001-01-01

Frequency noise in the variations of the Earth's obliquity (tilt) can modulate the insolation signal for climate change. Including this frequency noise effect on the incoming solar radiation, we have applied an energy balance climate model to calculate the climate fluctuations for the past one million years. Model simulation results are in good agreement with the geologically observed paleoclimate data. We conclude that orbital noise in the Earth system may be the major cause of the climate fluctuation cycles.

Intraseasonal and Interannual Variability of Mars Present Climate

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1996-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to investigate the nature of intraseasonal and interannual variability of Mars'present climate. We have applied a three-dimensional climate model based on the full hydrostatic primitive equations to determine the spatial, but primarily, the temporal structures of the planet's large-scale circulation as it evolves during a given seasonal advance, and, over multi-annual cycles. The particular climate model applies simplified physical parameterizations and is computationally efficient. It could thus easily be integrated in a perpetual season or advancing season configuration, as well as over many Mars years. We have assessed both high and low-frequency components of the circulation (i.e., motions having periods of Omicron(2-10 days) or greater than Omicron(10 days), respectively). Results from this investigation have explored the basic issue whether Mars' climate system is naturally 'chaotic' associated with nonlinear interactions of the large-scale circulation-regardless of any allowance for year-to-year variations in external forcing mechanisms. Titles of papers presented at scientific conferences and a manuscript to be submitted to the scientific literature are provided. An overview of a areas for further investigation is also presented.

SysSon: A Sonification Platform for Climate Data

NASA Astrophysics Data System (ADS)

Visda, Goudarzi; Hanns Holger, Rutz; Katharina, Vogt

2014-05-01

Climate data provide a challenging working basis for sonification. Both model data and measured data are assessed in collaboration with the Wegener Center for Climate and Global Change. The multi dimensionality and multi variety of climate data has a great potential for auditory displays. Furthermore, there is consensus on global climate change and the necessity of intensified climate research today in the scientific community and general public. Sonification provides a new means to communicate scientific results and inform a wider audience. SysSon is a user centered auditory platform for climate scientists to analyze data. It gives scientists broader insights by extracting hidden patterns and features from data that is not possible using a single modal visual interface. A variety of soundscapes to chose from lessens the fatigue that comes with repeated and sustained listening to long streams of data. Initial needs assessments and user tests made the work procedures and the terminology of climate scientists clear and informed the architecture of our system. Furthermore, experiments evaluated the sound design which led to a more advanced soundscape and improvement of the auditory display. We present a novel interactive sonification tool which combines a workspace for the scientists with a development environment for sonification models. The tool runs on different operating systems and is released as open source. In the standalone desktop application, multiple data sources can be imported, navigated and manipulated either via text or a graphical interface, including traditional plotting facilities. Sound models are built from unit generator graphs which are enhanced with matrix manipulation functions. They allow us to systematically experiment with elements known from the visual domain, such as range selections, scaling, thresholding, markers and labels. The models are organized in an extensible library, from which the user can choose and parametrize. Importance is given to the persistence of all configurations, in order to faithfully reproduce sonification instances. Finally, the platform is prepared to allow the composition of interactive sound installations, transitioning between the scientific lab and the gallery space.

A VLSI implementation for synthetic aperture radar image processing

NASA Technical Reports Server (NTRS)

Premkumar, A.; Purviance, J.

1990-01-01

A simple physical model for the Synthetic Aperture Radar (SAR) is presented. This model explains the one dimensional and two dimensional nature of the received SAR signal in the range and azimuth directions. A time domain correlator, its algorithm, and features are explained. The correlator is ideally suited for VLSI implementation. A real time SAR architecture using these correlators is proposed. In the proposed architecture, the received SAR data is processed using one dimensional correlators for determining the range while two dimensional correlators are used to determine the azimuth of a target. The architecture uses only three different types of custom VLSI chips and a small amount of memory.

Impact of Wall Shear Stress and Pressure Variation on the Stability of Atherosclerotic Plaque

NASA Astrophysics Data System (ADS)

Taviani, V.; Li, Z. Y.; Sutcliffe, M.; Gillard, J.

Rupture of vulnerable atheromatous plaque in the carotid and coronary arteries often leads to stroke and heart attack respectively. The mechanism of blood flow and plaque rupture in stenotic arteries is still not fully understood. A three dimensional rigid wall model was solved under steady and unsteady conditions assuming a time-varying inlet velocity profile to investigate the relative importance of axial forces and pressure drops in arteries with asymmetric stenosis. Flow-structure interactions were investigated for the same geometry and the results were compared with those retrieved with the corresponding one dimensional models. The Navier-Stokes equations were used as the governing equations for the fluid. The tube wall was assumed linearly elastic, homogeneous isotropic. The analysis showed that wall shear stress is small (less than 3.5%) with respect to pressure drop throughout the cycle even for severe stenosis. On the contrary, the three dimensional behavior of velocity, pressure and wall shear stress is in general very different from that predicted by one dimensional models. This suggests that the primary source of mistakes in one dimensional studies comes from neglecting the three dimensional geometry of the plaque. Neglecting axial forces only involves minor errors.

Airborne Particles: What We Have Learned About Their Role in Climate from Remote Sensing, and Prospects for Future Advances

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2013-01-01

Desert dust, wildfire smoke, volcanic ash, biogenic and urban pollution particles, all affect the regional-scale climate of Earth in places and at times; some have global-scale impacts on the column radiation balance, cloud properties, atmospheric stability structure, and circulation patterns. Remote sensing has played a central role in identifying the sources and transports of airborne particles, mapping their three-dimensional distribution and variability, quantifying their amount, and constraining aerosol air mass type. The measurements obtained from remote sensing have strengths and limitations, and their value for characterizing Earths environment is enhanced immensely when they are combined with direct, in situ observations, and used to constrain aerosol transport and climate models. A similar approach has been taken to study the role particles play in determining the climate of Mars, though based on far fewer observations. This presentation will focus what we have learned from remote sensing about the impacts aerosol have on Earths climate; a few points about how aerosols affect the climate of Mars will also be introduced, in the context of how we might assess aerosol-climate impacts more generally on other worlds.

Programmers manual for a one-dimensional Lagrangian transport model

USGS Publications Warehouse

Schoellhamer, D.H.; Jobson, H.E.

1986-01-01

A one-dimensional Lagrangian transport model for simulating water-quality constituents such as temperature, dissolved oxygen , and suspended sediment in rivers is presented in this Programmers Manual. Lagrangian transport modeling techniques, the model 's subroutines, and the user-written decay-coefficient subroutine are discussed in detail. Appendices list the program codes. The Programmers Manual is intended for the model user who needs to modify code either to adapt the model to a particular need or to use reaction kinetics not provided with the model. (Author 's abstract)

Effects of adjusting cropping systems on utilization efficiency of climatic resources in Northeast China under future climate scenarios

NASA Astrophysics Data System (ADS)

Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian

Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize, respectively. Additionally, compared with spring maize, the average utilization efficiencies of thermal resources of winter wheat and summer maize dramatically increased by 9.2%, 12.1% and 12.0%, respectively. The increases in the average utilization efficiencies of precipitation resources of winter wheat and summer maize were 1.78 kg hm-2 mm-1, 2.07 kg hm-2 mm-1 and 1.92 kg hm-2 mm-1 during 2011-2040, 2041-2070 and 2071-2100, respectively. Our findings highlight that adjusting cropping systems can dominantly contribute to utilization efficiency increases of agricultural climatic resources in Northeast China in the future.

A one-dimensional model of solid-earth electrical resistivity beneath Florida

USGS Publications Warehouse

Blum, Cletus; Love, Jeffrey J.; Pedrie, Kolby; Bedrosian, Paul A.; Rigler, E. Joshua

2015-11-19

An estimated one-dimensional layered model of electrical resistivity beneath Florida was developed from published geological and geophysical information. The resistivity of each layer is represented by plausible upper and lower bounds as well as a geometric mean resistivity. Corresponding impedance transfer functions, Schmucker-Weidelt transfer functions, apparent resistivity, and phase responses are calculated for inducing geomagnetic frequencies ranging from 10−5 to 100 hertz. The resulting one-dimensional model and response functions can be used to make general estimates of time-varying electric fields associated with geomagnetic storms such as might represent induction hazards for electric-power grid operation. The plausible upper- and lower-bound resistivity structures show the uncertainty, giving a wide range of plausible time-varying electric fields.

Assessing the impacts of climate change on future water resources: a methodological approach based on equiratio CDF-matching and vine copula

NASA Astrophysics Data System (ADS)

Pham, Minh Tu; Vernieuwe, Hilde; De Baets, Bernard; Verhoest, Niko E. C.

2016-04-01

In this study, the impacts of climate change on future river discharge are evaluated using equiratio CDF-matching and a stochastic copula-based evapotranspiration generator. In recent years, much effort has been dedicated to improve the performances of RCMs outputs, i.e. the downscaled precipitation and temperature, to use in regional studies. However, these outputs usually suffer from bias due to the fact that many important small-scale processes, e.g. the representations of clouds and convection, are not represented explicitly within the models. To solve this problem, several bias correction techniques are developed. In this study, an advanced quantile bias approach called equiratio cumulative distribution function matching (EQCDF) is applied for the outputs from three RCMs for central Belgium, i.e. daily precipitation, temperature and evapotranspiration, for the current (1961-1990) and future climate (2071-2100). The rescaled precipitation and temperature are then used to simulate evapotranspiration via a stochastic copula-based model in which the statistical dependence between evapotranspiration, temperature and precipitation is described by a three-dimensional vine copula. The simulated precipitation and stochastic evapotranspiration are then used to model discharge under present and future climate. To validate, the observations of daily precipitation, temperature and evapotranspiration during 1961 - 1990 in Uccle, Belgium are used. It is found that under current climate, the basic properties of discharge, e.g. mean and frequency distribution, are well modelled; however there is an overestimation of the extreme discharges with return periods higher than 10 years. For the future climate change, compared with historical events, a considerable increase of the discharge magnitude and the number of extreme events is estimated for the studied area in the time period of 2071-2100.

Proceedings of the Advanced Seminar on one-dimensional, open-channel Flow and transport modeling

USGS Publications Warehouse

Schaffranek, Raymond W.

1989-01-01

In view of the increased use of mathematical/numerical simulation models, of the diversity of both model investigations and informational project objectives, and of the technical demands of complex model applications by U.S. Geological Survey personnel, an advanced seminar on one-dimensional open-channel flow and transport modeling was organized and held on June 15-18, 1987, at the National Space Technology Laboratory, Bay St. Louis, Mississippi. Principal emphasis in the Seminar was on one-dimensional flow and transport model-implementation techniques, operational practices, and application considerations. The purposes of the Seminar were to provide a forum for the exchange of information, knowledge, and experience among model users, as well as to identify immediate and future needs with respect to model development and enhancement, user support, training requirements, and technology transfer. The Seminar program consisted of a mix of topical and project presentations by Geological Survey personnel. This report is a compilation of short papers that summarize the presentations made at the Seminar.

Influence of landscape heterogeneity on water available to tropical forests in an Amazonian catchment and implications for modeling drought response: Water Available to Tropical Forest

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

Fang, Yilin; Leung, L. Ruby; Duan, Zhuoran

The Amazon basin experienced periodic droughts in the past, and climate models projected more intense and frequent droughts in the future. How tropical forests respond to drought may depend on water availability, which is modulated by landscape heterogeneity. Using the one-dimensional ACME Land Model (ALM) and the three-dimensional ParFlow variably saturated flow model, a series of numerical experiments were performed for the Asu catchment in central Amazon to elucidate processes that influence water available for plant use and provide insights for improving Earth system models. Results from ParFlow show that topography has a dominant influence on groundwater table and runoffmore » through lateral flow. Without any representations of lateral processes, ALM simulates very different seasonal variations in groundwater table and runoff compared to ParFlow even if it is able to reproduce the long-term spatial average groundwater table of ParFlow through simple parameter calibration. In the ParFlow simulations, the groundwater table is evidently deeper and the soil saturation is lower in the plateau compared to the valley. However, even in the plateau during the dry season in the drought year of 2005, plant transpiration is not water stressed in the ParFlow simulations as the soil saturation is still sufficient to maintain a soil matric potential for the stomata to be fully open. This finding is insensitive to uncertainty in atmospheric forcing and soil parameters, but the empirical wilting formulation used in the models is an important factor that should be addressed using observations and modeling of coupled plant hydraulics-soil hydrology processes in future studies.« less

Continuum modeling of catastrophic collisions

NASA Technical Reports Server (NTRS)

Ryan, Eileen V.; Aspaug, Erik; Melosh, H. J.

1991-01-01

A two dimensional hydrocode based on 2-D SALE was modified to include strength effects and fragmentation equations for fracture resulting from tensile stress in one dimension. Output from this code includes a complete fragmentation summary for each cell of the modeled object: fragment size (mass) distribution, vector velocities of particles, peak values of pressure and tensile stress, and peak strain rates associated with fragmentation. Contour plots showing pressure and temperature at given times within the object are also produced. By invoking axial symmetry, three dimensional events can be modeled such as zero impact parameter collisions between asteroids. The code was tested against the one dimensional model and the analytical solution for a linearly increasing tensile stress under constant strain rate.

Recurrence relations in one-dimensional Ising models.

PubMed

da Conceição, C M Silva; Maia, R N P

2017-09-01

The exact finite-size partition function for the nonhomogeneous one-dimensional (1D) Ising model is found through an approach using algebra operators. Specifically, in this paper we show that the partition function can be computed through a trace from a linear second-order recurrence relation with nonconstant coefficients in matrix form. A relation between the finite-size partition function and the generalized Lucas polynomials is found for the simple homogeneous model, thus establishing a recursive formula for the partition function. This is an important property and it might indicate the possible existence of recurrence relations in higher-dimensional Ising models. Moreover, assuming quenched disorder for the interactions within the model, the quenched averaged magnetic susceptibility displays a nontrivial behavior due to changes in the ferromagnetic concentration probability.

Programming a hillslope water movement model on the MPP

NASA Technical Reports Server (NTRS)

Devaney, J. E.; Irving, A. R.; Camillo, P. J.; Gurney, R. J.

1987-01-01

A physically based numerical model was developed of heat and moisture flow within a hillslope on a parallel architecture computer, as a precursor to a model of a complete catchment. Moisture flow within a catchment includes evaporation, overland flow, flow in unsaturated soil, and flow in saturated soil. Because of the empirical evidence that moisture flow in unsaturated soil is mainly in the vertical direction, flow in the unsaturated zone can be modeled as a series of one dimensional columns. This initial version of the hillslope model includes evaporation and a single column of one dimensional unsaturated zone flow. This case has already been solved on an IBM 3081 computer and is now being applied to the massively parallel processor architecture so as to make the extension to the one dimensional case easier and to check the problems and benefits of using a parallel architecture machine.

Spline models of contemporary, 2030, 2060, and 2090 climates for Mexico and their use in understanding climate-change impacts on the vegetation

Treesearch

Cuauhtemoc Saenz-Romero; Gerald E. Rehfeldt; Nicholas L. Crookston; Pierre Duval; Remi St-Amant; Jean Beaulieu; Bryce A. Richardson

2010-01-01

Spatial climate models were developed for Mexico and its periphery (southern USA, Cuba, Belize and Guatemala) for monthly normals (1961-1990) of average, maximum and minimum temperature and precipitation using thin plate smoothing splines of ANUSPLIN software on ca. 3,800 observations. The fit of the model was generally good: the signal was considerably less than one-...

Expert judgement and uncertainty quantification for climate change

NASA Astrophysics Data System (ADS)

Oppenheimer, Michael; Little, Christopher M.; Cooke, Roger M.

2016-05-01

Expert judgement is an unavoidable element of the process-based numerical models used for climate change projections, and the statistical approaches used to characterize uncertainty across model ensembles. Here, we highlight the need for formalized approaches to unifying numerical modelling with expert judgement in order to facilitate characterization of uncertainty in a reproducible, consistent and transparent fashion. As an example, we use probabilistic inversion, a well-established technique used in many other applications outside of climate change, to fuse two recent analyses of twenty-first century Antarctic ice loss. Probabilistic inversion is but one of many possible approaches to formalizing the role of expert judgement, and the Antarctic ice sheet is only one possible climate-related application. We recommend indicators or signposts that characterize successful science-based uncertainty quantification.

Predictive Modeling of Rice Yellow Stem Borer Population Dynamics under Climate Change Scenarios in Indramayu

NASA Astrophysics Data System (ADS)

Nurhayati, E.; Koesmaryono, Y.; Impron

2017-03-01

Rice Yellow Stem Borer (YSB) is one of the major insect pests in rice plants that has high attack intensity in rice production center areas, especially in West Java. This pest is consider as holometabola insects that causes rice damage in the vegetative phase (deadheart) as well as generative phase (whitehead). Climatic factor is one of the environmental factors influence the pattern of dynamics population. The purpose of this study was to develop a predictive modeling of YSB pest dynamics population under climate change scenarios (2016-2035 period) using Dymex Model in Indramayu area, West Java. YSB modeling required two main components, namely climate parameters and YSB development lower threshold of temperature (To) to describe YSB life cycle in every phase. Calibration and validation test of models showed the coefficient of determination (R2) between the predicted results and observations of the study area were 0.74 and 0.88 respectively, which was able to illustrate the development, mortality, transfer of individuals from one stage to the next life also fecundity and YSB reproduction. On baseline climate condition, there was a tendency of population abundance peak (outbreak) occured when a change of rainfall intensity in the rainy season transition to dry season or the opposite conditions was happen. In both of application of climate change scenarios, the model outputs were generated well and able to predict the pattern of YSB population dynamics with a the increasing trend of specific population numbers, generation numbers per season and also shifting pattern of populations abundance peak in the future climatic conditions. These results can be adopted as a tool to predict outbreak and to give early warning to control YSB pest more effectively.

Configuration memory in patchwork dynamics for low-dimensional spin glasses

NASA Astrophysics Data System (ADS)

Yang, Jie; Middleton, A. Alan

2017-12-01

A patchwork method is used to study the dynamics of loss and recovery of an initial configuration in spin glass models in dimensions d =1 and d =2 . The patchwork heuristic is used to accelerate the dynamics to investigate how models might reproduce the remarkable memory effects seen in experiment. Starting from a ground-state configuration computed for one choice of nearest-neighbor spin couplings, the sample is aged up to a given scale under new random couplings, leading to the partial erasure of the original ground state. The couplings are then restored to the original choice and patchwork coarsening is again applied, in order to assess the recovery of the original state. Eventual recovery of the original ground state upon coarsening is seen in two-dimensional Ising spin glasses and one-dimensional clock models, while one-dimensional Ising spin systems neither lose nor gain overlap with the ground state during the recovery stage. The recovery for the two-dimensional Ising spin glasses suggests scaling relations that lead to a recovery length scale that grows as a power of the aging length scale.

Steady-state solutions of a diffusive energy-balance climate model and their stability

NASA Technical Reports Server (NTRS)

Ghil, M.

1975-01-01

A diffusive energy-balance climate model, governed by a nonlinear parabolic partial differential equation, was studied. Three positive steady-state solutions of this equation are found; they correspond to three possible climates of our planet: an interglacial (nearly identical to the present climate), a glacial, and a completely ice-covered earth. Models similar to the main one are considered, and the number of their steady states was determined. All the models have albedo continuously varying with latitude and temperature, and entirely diffusive horizontal heat transfer. The stability under small perturbations of the main model's climates was investigated. A stability criterion is derived, and its application shows that the present climate and the deep freeze are stable, whereas the model's glacial is unstable. The dependence was examined of the number of steady states and of their stability on the average solar radiation.

Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Cess, R. D.; Potter, G. L.; Blanchet, J. P.; Boer, G. J.; Del Genio, A. D.

1990-01-01

The present study provides an intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. This intercomparison uses sea surface temperature change as a surrogate for climate change. The interpretation of cloud-climate interactions is given special attention. A roughly threefold variation in one measure of global climate sensitivity is found among the 19 models. The important conclusion is that most of this variation is attributable to differences in the models' depiction of cloud feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as reliable climate predictors. It is further emphazied that cloud feedback is the consequence of all interacting physical and dynamical processes in a general circulation model. The result of these processes is to produce changes in temperature, moisture distribution, and clouds which are integrated into the radiative response termed cloud feedback.

A Bayesian partition modelling approach to resolve spatial variability in climate records from borehole temperature inversion

NASA Astrophysics Data System (ADS)

Hopcroft, Peter O.; Gallagher, Kerry; Pain, Christopher C.

2009-08-01

Collections of suitably chosen borehole profiles can be used to infer large-scale trends in ground-surface temperature (GST) histories for the past few hundred years. These reconstructions are based on a large database of carefully selected borehole temperature measurements from around the globe. Since non-climatic thermal influences are difficult to identify, representative temperature histories are derived by averaging individual reconstructions to minimize the influence of these perturbing factors. This may lead to three potentially important drawbacks: the net signal of non-climatic factors may not be zero, meaning that the average does not reflect the best estimate of past climate; the averaging over large areas restricts the useful amount of more local climate change information available; and the inversion methods used to reconstruct the past temperatures at each site must be mathematically identical and are therefore not necessarily best suited to all data sets. In this work, we avoid these issues by using a Bayesian partition model (BPM), which is computed using a trans-dimensional form of a Markov chain Monte Carlo algorithm. This then allows the number and spatial distribution of different GST histories to be inferred from a given set of borehole data by partitioning the geographical area into discrete partitions. Profiles that are heavily influenced by non-climatic factors will be partitioned separately. Conversely, profiles with climatic information, which is consistent with neighbouring profiles, will then be inferred to lie in the same partition. The geographical extent of these partitions then leads to information on the regional extent of the climatic signal. In this study, three case studies are described using synthetic and real data. The first demonstrates that the Bayesian partition model method is able to correctly partition a suite of synthetic profiles according to the inferred GST history. In the second, more realistic case, a series of temperature profiles are calculated using surface air temperatures of a global climate model simulation. In the final case, 23 real boreholes from the United Kingdom, previously used for climatic reconstructions, are examined and the results compared with a local instrumental temperature series and the previous estimate derived from the same borehole data. The results indicate that the majority (17) of the 23 boreholes are unsuitable for climatic reconstruction purposes, at least without including other thermal processes in the forward model.

A New Non-gaussian Turbulent Wind Field Generator to Estimate Design-Loads of Wind-Turbines

NASA Astrophysics Data System (ADS)

Schaffarczyk, A. P.; Gontier, H.; Kleinhans, D.; Friedrich, R.

Climate change and finite fossil fuel resources make it urgent to turn into electricity generation from mostly renewable energies. One major part will play wind-energy supplied by wind-turbines of rated power up to 10 MW. For their design and development wind field models have to be used. The standard models are based on the empirical spectra, for example by von Karman or Kaimal. From investigation of measured data it is clear that gusts are underrepresented in such models. Based on some fundamental discoveries of the nature of turbulence by Friedrich [1] derived from the Navier-Stokes equation directly, we used the concept of Continuous Time Random Walks to construct three dimensional wind fields obeying non-Gaussian statistics. These wind fields were used to estimate critical fatigue loads necessary within the certification process. Calculations are carried out with an implementation of a beam-model (FLEX5) for two types of state-of-the-art wind turbines The authors considered the edgewise and flapwise blade-root bending moments as well as tilt moment at tower top due to the standard wind field models and our new non-Gaussian wind field model. Clear differences in the loads were found.

Modeling methane emissions from Arctic lakes under warming conditions

NASA Astrophysics Data System (ADS)

Zhuang, Qianlai; Tan, Zeli

2014-05-01

To investigate the response of methane emissions from arctic lakes, a process-based climate-sensitive lake methane model is developed. The processes of methane production, oxidation and transport are modeled within a one-dimensional water and sediment column. Dynamics of point-source ebullition seeps are explicitly modeled. The model was calibrated and verified using observational data in the region. The model was further used to estimate the lake methane emissions from the Arctic from 2002 to 2004. We estimate that the total amount of methane emissions is 24.9 Tg CH4 yr-1, which is consistent with a recent estimation of 24±10 Tg CH4 yr-1 and two-fold of methane emissions from natural wetlands in the north of 60 oN. The methane emission rate of lakes spatially varies over high latitudes from 170.5 mg CH4 m-2 day-1 in northern Siberia to only 10.1 mg CH4 m-2 day-1 in northern Europe. A projection assuming 2-7.5oC warming and 15-25% expansion of lake coverage shows that the total amount of methane emitted from Arctic lakes will increase to 29.8-35.6 Tg CH4 yr-1.

Modeling Three-Dimensional Flow in Confined Aquifers by Superposition of Both Two- and Three-Dimensional Analytic Functions

NASA Astrophysics Data System (ADS)

Haitjema, Henk M.

1985-10-01

A technique is presented to incorporate three-dimensional flow in a Dupuit-Forchheimer model. The method is based on superposition of approximate analytic solutions to both two- and three-dimensional flow features in a confined aquifer of infinite extent. Three-dimensional solutions are used in the domain of interest, while farfield conditions are represented by two-dimensional solutions. Approximate three- dimensional solutions have been derived for a partially penetrating well and a shallow creek. Each of these solutions satisfies the condition that no flow occurs across the confining layers of the aquifer. Because of this condition, the flow at some distance of a three-dimensional feature becomes nearly horizontal. Consequently, remotely from a three-dimensional feature, its three-dimensional solution is replaced by a corresponding two-dimensional one. The latter solution is trivial as compared to its three-dimensional counterpart, and its use greatly enhances the computational efficiency of the model. As an example, the flow is modeled between a partially penetrating well and a shallow creek that occur in a regional aquifer system.

Fate of classical solitons in one-dimensional quantum systems.

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

Pustilnik, M.; Matveev, K. A.

We study one-dimensional quantum systems near the classical limit described by the Korteweg-de Vries (KdV) equation. The excitations near this limit are the well-known solitons and phonons. The classical description breaks down at long wavelengths, where quantum effects become dominant. Focusing on the spectra of the elementary excitations, we describe analytically the entire classical-to-quantum crossover. We show that the ultimate quantum fate of the classical KdV excitations is to become fermionic quasiparticles and quasiholes. We discuss in detail two exactly solvable models exhibiting such crossover, the Lieb-Liniger model of bosons with weak contact repulsion and the quantum Toda model, andmore » argue that the results obtained for these models are universally applicable to all quantum one-dimensional systems with a well-defined classical limit described by the KdV equation.« less

Effects of three-dimensional velocity structure on the seismicity of the 1984 Morgan Hill, California, aftershock sequence

USGS Publications Warehouse

Michael, A.J.

1988-01-01

A three-dimensional velocity model for the area surrounding the 24 April 1984 Morgan Hill earthquake has been developed by simultaneously inverting local earthquake and refraction arrival-time data. This velocity model corresponds well to the surface geology of the region, predominantly showing a low-velocity region associated with the sedimentary sequence to the south-west of the Madrone Springs fault. The focal mechanisms were also determined for 946 earthquakes using both the one-dimensional and three-dimensional earth models. Both earth models yield similar focal mechanisms for these earthquakes. -from Author

Signal to noise quantification of regional climate projections

NASA Astrophysics Data System (ADS)

Li, S.; Rupp, D. E.; Mote, P.

2016-12-01

One of the biggest challenges in interpreting climate model outputs for impacts studies and adaptation planning is understanding the sources of disagreement among models (which is often used imperfectly as a stand-in for system uncertainty). Internal variability is a primary source of uncertainty in climate projections, especially for precipitation, for which models disagree about even the sign of changes in large areas like the continental US. Taking advantage of a large initial-condition ensemble of regional climate simulations, this study quantifies the magnitude of changes forced by increasing greenhouse gas concentrations relative to internal variability. Results come from a large initial-condition ensemble of regional climate model simulations generated by weather@home, a citizen science computing platform, where the western United States climate was simulated for the recent past (1985-2014) and future (2030-2059) using a 25-km horizontal resolution regional climate model (HadRM3P) nested in global atmospheric model (HadAM3P). We quantify grid point level signal-to-noise not just in temperature and precipitation responses, but also the energy and moisture flux terms that are related to temperature and precipitation responses, to provide important insights regarding uncertainty in climate change projections at local and regional scales. These results will aid modelers in determining appropriate ensemble sizes for different climate variables and help users of climate model output with interpreting climate model projections.

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.

FireStem2D — A two-dimensional heat transfer model for simulating tree stem injury in fires

Treesearch

Efthalia K. Chatziefstratiou; Gil Bohrer; Anthony S. Bova; Ravishankar Subramanian; Renato P.M. Frasson; Amy Scherzer; Bret W. Butler; Matthew B. Dickinson

2013-01-01

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by...

Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations.

PubMed

Braconnot, Pascale; Kageyama, Masa

2015-11-13

Simulations of the climates of the Last Glacial Maximum (LGM), 21 000 years ago, and of the Mid-Holocene (MH), 6000 years ago, allow an analysis of climate feedbacks in climate states that are radically different from today. The analyses of cloud and surface albedo feedbacks show that the shortwave cloud feedback is a major driver of differences between model results. Similar behaviours appear when comparing the LGM and MH simulated changes, highlighting the fingerprint of model physics. Even though the different feedbacks show similarities between the different climate periods, the fact that their relative strength differs from one climate to the other prevents a direct comparison of past and future climate sensitivity. The land-surface feedback also shows large disparities among models even though they all produce positive sea-ice and snow feedbacks. Models have very different sensitivities when considering the vegetation feedback. This feedback has a regional pattern that differs significantly between models and depends on their level of complexity and model biases. Analyses of the MH climate in two versions of the IPSL model provide further indication on the possibilities to assess the role of model biases and model physics on simulated climate changes using past climates for which observations can be used to assess the model results. © 2015 The Author(s).

Theory of one-dimensional hopping motion of a heavy particle interacting with phonons by different couplings

NASA Astrophysics Data System (ADS)

Itai, K.

1987-02-01

Two models which describe one-dimensional hopping motion of a heavy particle interacting with phonons are discussed. Model A corresponds to hopping in 1D metals or to the polaron problem. In model B the momentum dependence of the particle-phonon coupling is proportional to k-1/2. The scaling equations show that only in model B does localization occur for a coupling larger than a critical value. In the localization region this model shows close analogy to the Caldeira-Leggett model for macroscopic quantum tunneling.

Simulation of climate-change effects on streamflow, lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin

USGS Publications Warehouse

Hunt, Randall J.; Walker, John F.; Selbig, William R.; Westenbroek, Stephen M.; Regan, R. Steve

2013-01-01

Although groundwater and surface water are considered a single resource, historically hydrologic simulations have not accounted for feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system. Simulations that iteratively couple the surface-water and groundwater systems, however, are characterized by long run times and calibration challenges. In this study, calibrated, uncoupled transient surface-water and steady-state groundwater models were used to construct one coupled transient groundwater/surface-water model for the Trout Lake Watershed in north-central Wisconsin, USA. The computer code GSFLOW (Ground-water/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil-zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, stream, and lake budgets. The coupled GSFLOW model was calibrated by using heads, streamflows, lake levels, actual evapotranspiration rates, solar radiation, and snowpack measurements collected during water years 1998–2007; calibration was performed by using advanced features present in the PEST parameter estimation software suite. Simulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model to simulate daily stream temperature in selected tributaries in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2002. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the period extending to the year 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the period 2010–2100 showed increases in maximum and minimum temperature over the scenario period. Scenarios of future precipitation did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased over time for both temperature and precipitation. Separate calibration of the uncoupled groundwater and surface-water models did not provide a representative initial parameter set for coupled model calibration. A sequentially linked calibration, in which the uncoupled models were linked by means of utility software, provided a starting parameter set suitable for coupled model calibration. Even with sequentially linked calibration, however, transmissivity of the lower part of the aquifer required further adjustment during coupled model calibration to attain reasonable parameter values for evaporation rates off a small seepage lake (a lake with no appreciable surface-water outlets) with a long history of study. The resulting coupled model was well calibrated to most types of observed time-series data used for calibration. Daily stream temperatures measured during 2002 were successfully simulated with SNTEMP; the model fit was acceptable for a range of groundwater inflow rates into the streams. Forecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snow-melt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions in rainfed wetlands and uplands, in contrast to less drying in groundwater-fed systems. Seepage lakes showed larger forecast stage declines related to climate change than did drainage lakes (lakes with outlet streams). Seepage lakes higher in the watershed (nearer to groundwater divides) had less groundwater inflow and thus had larger forecast declines in lake stage; however, ground-water inflow to seepage lakes in general tended to increase as a fraction of the lake budgets with lake-stage decline because inward hydraulic gradients increased. Drainage lakes were characterized by less simulated stage decline as reductions in outlet streamflow of set losses to other water flows. Net groundwater inflow tended to decrease in drainage lakes over the scenario period. Simulated stream temperatures increased appreciably with climate change. The estimated increase in annual average temperature ranged from approximately 1 to 2 degrees Celsius by 2100 in the stream characterized by a high groundwater inflow rate and 2 to 3 degrees Celsius in the stream with a lower rate. The climate drivers used for the climate-change scenarios had appreciable variation between the General Circulation Model and emission scenario selected; this uncertainty was reflected in hydrologic flow and temperature model results. Thus, as with all forecasts of this type, the results are best considered to approximate potential outcomes of climate change.

Climate and climate variability of the wind power resources in the Great Lakes region of the United States

Treesearch

X. Li; S. Zhong; X. Bian; W.E. Heilman

2010-01-01

The climate and climate variability of low-level winds over the Great Lakes region of the United States is examined using 30 year (1979-2008) wind records from the recently released North American Regional Reanalysis (NARR), a three-dimensional, high-spatial and temporal resolution, and dynamically consistent climate data set. The analyses focus on spatial distribution...

Surrogate-Based Optimization of Biogeochemical Transport Models

NASA Astrophysics Data System (ADS)

Prieß, Malte; Slawig, Thomas

2010-09-01

First approaches towards a surrogate-based optimization method for a one-dimensional marine biogeochemical model of NPZD type are presented. The model, developed by Oschlies and Garcon [1], simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean circulation data. A key issue is to minimize the misfit between the model output and given observational data. Our aim is to reduce the overall optimization cost avoiding expensive function and derivative evaluations by using a surrogate model replacing the high-fidelity model in focus. This in particular becomes important for more complex three-dimensional models. We analyse a coarsening in the discretization of the model equations as one way to create such a surrogate. Here the numerical stability crucially depends upon the discrete stepsize in time and space and the biochemical terms. We show that for given model parameters the level of grid coarsening can be choosen accordingly yielding a stable and satisfactory surrogate. As one example of a surrogate-based optimization method we present results of the Aggressive Space Mapping technique (developed by John W. Bandler [2, 3]) applied to the optimization of this one-dimensional biogeochemical transport model.

Influence of feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

NASA Astrophysics Data System (ADS)

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.

NASTRAN analysis for the Airmass Sunburst model 'C' Ultralight Aircraft

NASA Technical Reports Server (NTRS)

Verbestel, John; Smith, Howard W.

1993-01-01

The purpose of this project was to create a three dimensional NASTRAN model of the Airmass Sunburst Ultralight comparable to one made for finite element analysis. A two dimensional sample problem will be calculated by hand and by NASTRAN to make sure that NASTRAN finds similar results. A three dimensional model, similar to the one analyzed by the finite element program, will be run on NASTRAN. A comparison will be done between the NASTRAN results and the finite element program results. This study will deal mainly with the aerodynamic loads on the wing and surrounding support structure at an attack angle of 10 degrees.

Modelling large-scale ice-sheet-climate interactions at the last glacial inception

NASA Astrophysics Data System (ADS)

Browne, O. J. H.; Gregory, J. M.; Payne, A. J.; Ridley, J. K.; Rutt, I. C.

2010-05-01

In order to investigate the interactions between coevolving climate and ice-sheets on multimillenial timescales, a low-resolution atmosphere-ocean general circulation model (AOGCM) has been coupled to a three-dimensional thermomechanical ice-sheet model. We use the FAMOUS AOGCM, which is almost identical in formulation to the widely used HadCM3 AOGCM, but on account of its lower resolution (7.5° longitude × 5° latitude in the atmosphere, 3.75°× 2.5° in the ocean) it runs about ten times faster. We use the community ice-sheet model Glimmer at 20 km resolution, with the shallow ice approximation and an annual degree-day scheme for surface mass balance. With the FAMOUS-Glimmer coupled model, we have simulated the growth of the Laurentide and Fennoscandian ice sheets at the last glacial inception, under constant orbital forcing and atmospheric composition for 116 ka BP. Ice grows in both regions, totalling 5.8 m of sea-level equivalent in 10 ka, slower than proxy records suggest. Positive climate feedbacks reinforce this growth at local scales (order hundreds of kilometres), where changes are an order of magnitude larger than on the global average. The albedo feedback (higher local albedo means a cooler climate) is important in the initial expansion of the ice-sheet area. The topography feedback (higher surface means a cooler climate) affects ice-sheet thickness and is not noticeable for the first 1 ka. These two feedbacks reinforce each other. Without them, the ice volume is ~90% less after 10 ka. In Laurentia, ice expands initially on the Canadian Arctic islands. The glaciation of the islands eventually cools the nearby mainland climate sufficiently to produce a positive mass balance there. Adjacent to the ice-sheets, cloud feedbacks tend to reduce the surface mass balance and restrain ice growth; this is an example of a local feedback whose simulation requires a model that includes detailed atmospheric physics.

Improving Streamflow Forecasts Using Predefined Sea Surface Temperature

NASA Astrophysics Data System (ADS)

Kalra, A.; Ahmad, S.

2011-12-01

With the increasing evidence of climate variability, water resources managers in the western United States are faced with greater challenges of developing long range streamflow forecast. This is further aggravated by the increases in climate extremes such as floods and drought caused by climate variability. Over the years, climatologists have identified several modes of climatic variability and their relationship with streamflow. These climate modes have the potential of being used as predictor in models for improving the streamflow lead time. With this as the motivation, the current research focuses on increasing the streamflow lead time using predefine climate indices. A data driven model i.e. Support Vector Machine (SVM) based on the statistical learning theory is used to predict annual streamflow volume 3-year in advance. The SVM model is a learning system that uses a hypothesis space of linear functions in a Kernel induced higher dimensional feature space, and is trained with a learning algorithm from the optimization theory. Annual oceanic-atmospheric indices, comprising of Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), El Niño-Southern Oscillations (ENSO), and a new Sea Surface Temperature (SST) data set of "Hondo" Region for a period of 1906-2005 are used to generate annual streamflow volumes. The SVM model is applied to three gages i.e. Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the western United States. Based on the performance measures the model shows very good forecasts, and the forecast are in good agreement with measured streamflow volumes. Previous research has identified NAO and ENSO as main drivers for extending streamflow forecast lead-time in the UCRB. Inclusion of "Hondo Region" SST information further improve the model's forecasting ability. The overall results of this study revealed that the annual streamflow of the UCRB is significantly influenced by predefine climate modes and the proposed SVM modeling technique incorporating oceanic-atmospheric oscillations is expected to be useful to water managers in the long-term management of the water resources within the UCRB.

System and method for representing and manipulating three-dimensional objects on massively parallel architectures

DOEpatents

Karasick, Michael S.; Strip, David R.

1996-01-01

A parallel computing system is described that comprises a plurality of uniquely labeled, parallel processors, each processor capable of modelling a three-dimensional object that includes a plurality of vertices, faces and edges. The system comprises a front-end processor for issuing a modelling command to the parallel processors, relating to a three-dimensional object. Each parallel processor, in response to the command and through the use of its own unique label, creates a directed-edge (d-edge) data structure that uniquely relates an edge of the three-dimensional object to one face of the object. Each d-edge data structure at least includes vertex descriptions of the edge and a description of the one face. As a result, each processor, in response to the modelling command, operates upon a small component of the model and generates results, in parallel with all other processors, without the need for processor-to-processor intercommunication.

Development of a Localized Low-Dimensional Approach to Turbulence Simulation

NASA Astrophysics Data System (ADS)

Juttijudata, Vejapong; Rempfer, Dietmar; Lumley, John

2000-11-01

Our previous study has shown that the localized low-dimensional model derived from a projection of Navier-Stokes equations onto a set of one-dimensional scalar POD modes, with boundary conditions at y^+=40, can predict wall turbulence accurately for short times while failing to give a stable long-term solution. The structures obtained from the model and later studies suggest our boundary conditions from DNS are not consistent with the solution from the localized model resulting in an injection of energy at the top boundary. In the current study, we develop low-dimensional models using one-dimensional scalar POD modes derived from an explicitly filtered DNS. This model problem has exact no-slip boundary conditions at both walls while the locality of the wall layer is still retained. Furthermore, the interaction between wall and core region is attenuated via an explicit filter which allows us to investigate the quality of the model without requiring complicated modeling of the top boundary conditions. The full-channel model gives reasonable wall turbulence structures as well as long-term turbulent statistics while still having difficulty with the prediction of the mean velocity profile farther from the wall. We also consider a localized model with modified boundary conditions in the last part of our study.

HABITABLE ZONES OF POST-MAIN SEQUENCE STARS

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

Ramirez, Ramses M.; Kaltenegger, Lisa

Once a star leaves the main sequence and becomes a red giant, its Habitable Zone (HZ) moves outward, promoting detectable habitable conditions at larger orbital distances. We use a one-dimensional radiative-convective climate and stellar evolutionary models to calculate post-MS HZ distances for a grid of stars from 3700 to 10,000 K (∼M1 to A5 stellar types) for different stellar metallicities. The post-MS HZ limits are comparable to the distances of known directly imaged planets. We model the stellar as well as planetary atmospheric mass loss during the Red Giant Branch (RGB) and Asymptotic Giant Branch (AGB) phases for super-Moons tomore » super-Earths. A planet can stay between 200 million years up to 9 Gyr in the post-MS HZ for our hottest and coldest grid stars, respectively, assuming solar metallicity. These numbers increase for increased stellar metallicity. Total atmospheric erosion only occurs for planets in close-in orbits. The post-MS HZ orbital distances are within detection capabilities of direct imaging techniques.« less

Effects of high CO2 levels on surface temperature and atmospheric oxidation state of the early earth

NASA Technical Reports Server (NTRS)

Kasting, J. F.; Pollack, J. B.; Crisp, D.

1984-01-01

One-dimensional radiative and photochemical models are used to determine how much CO2 must have been present to maintain a temperate early climate and to examine the consequences that are implied for the controls on atmospheric oxidation state. It is shown that CO2 concentrations of the order of 1000 PAL are required to keep the average surface temperature close to the present value, if albedo changes and heating by reduced greenhouse gases were relatively unimportant. The oxidation state of such a high-CO2, prebiotic atmosphere should have been largely determined by the balance between the H2O2 rainout rate and the rate at which hydrogen escaped to space, with only a weak dependence on the volcanic outgassing rate or on other speculative sources of H2. The implied upper limit on the ground-level O2 mixing ratio is approximately 10 to the -11th and is subject to less uncertainty than the results of previous models.

Estimation of effective hydrologic properties of soils from observations of vegetation density. M.S. Thesis; [water balance of watersheds in Clinton, Maine and Santa Paula, California

NASA Technical Reports Server (NTRS)

Tellers, T. E.

1980-01-01

An existing one-dimensional model of the annual water balance is reviewed. Slight improvements are made in the method of calculating the bare soil component of evaporation, and in the way surface retention is handled. A natural selection hypothesis, which specifies the equilibrium vegetation density for a given, water limited, climate-soil system, is verified through comparisons with observed data and is employed in the annual water balance of watersheds in Clinton, Ma., and Santa Paula, Ca., to estimate effective areal average soil properties. Comparison of CDF's of annual basin yield derived using these soil properties with observed CDF's provides excellent verification of the soil-selection procedure. This method of parameterization of the land surface should be useful with present global circulation models, enabling them to account for both the non-linearity in the relationship between soil moisture flux and soil moisture concentration, and the variability of soil properties from place to place over the Earth's surface.

Sensitivity of worst-case strom surge considering influence of climate change

NASA Astrophysics Data System (ADS)

Takayabu, Izuru; Hibino, Kenshi; Sasaki, Hidetaka; Shiogama, Hideo; Mori, Nobuhito; Shibutani, Yoko; Takemi, Tetsuya

2016-04-01

There are two standpoints when assessing risk caused by climate change. One is how to prevent disaster. For this purpose, we get probabilistic information of meteorological elements, from enough number of ensemble simulations. Another one is to consider disaster mitigation. For this purpose, we have to use very high resolution sophisticated model to represent a worst case event in detail. If we could use enough computer resources to drive many ensemble runs with very high resolution model, we can handle these all themes in one time. However resources are unfortunately limited in most cases, and we have to select the resolution or the number of simulations if we design the experiment. Applying PGWD (Pseudo Global Warming Downscaling) method is one solution to analyze a worst case event in detail. Here we introduce an example to find climate change influence on the worst case storm-surge, by applying PGWD to a super typhoon Haiyan (Takayabu et al, 2015). 1 km grid WRF model could represent both the intensity and structure of a super typhoon. By adopting PGWD method, we can only estimate the influence of climate change on the development process of the Typhoon. Instead, the changes in genesis could not be estimated. Finally, we drove SU-WAT model (which includes shallow water equation model) to get the signal of storm surge height. The result indicates that the height of the storm surge increased up to 20% owing to these 150 years climate change.

Anomaly in the band centre of the one-dimensional Anderson model

NASA Astrophysics Data System (ADS)

Kappus, M.; Wegner, F.

1981-03-01

We calculate the density of states and various characteristic lengths of the one-dimensional Anderson model in the limit of weak disorder. All these quantities show anomalous fluctuations near the band centre. This has already been observed for the density of states in a different model by Gorkov and Dorokhov, and is in close agreement with a Monte-Carlo calculation for the localization length by Czycholl, Kramer and Mac-Kinnon.

Mixed-order phase transition in a one-dimensional model.

PubMed

Bar, Amir; Mukamel, David

2014-01-10

We introduce and analyze an exactly soluble one-dimensional Ising model with long range interactions that exhibits a mixed-order transition, namely a phase transition in which the order parameter is discontinuous as in first order transitions while the correlation length diverges as in second order transitions. Such transitions are known to appear in a diverse classes of models that are seemingly unrelated. The model we present serves as a link between two classes of models that exhibit a mixed-order transition in one dimension, namely, spin models with a coupling constant that decays as the inverse distance squared and models of depinning transitions, thus making a step towards a unifying framework.

DNA denaturation through a model of the partition points on a one-dimensional lattice

NASA Astrophysics Data System (ADS)

Mejdani, R.; Huseini, H.

1994-08-01

We have shown that by using a model of the partition points gas on a one-dimensional lattice, we can study, besides the saturation curves obtained before for the enzyme kinetics, also the denaturation process, i.e. the breaking of the hydrogen bonds connecting the two strands, under treatment by heat of DNA. We think that this model, as a very simple model and mathematically transparent, can be advantageous for pedagogic goals or other theoretical investigations in chemistry or modern biology.

Three Dimensional Distribution of Sensitive Field and Stress Field Inversion of Force Sensitive Materials under Constant Current Excitation.

PubMed

Zhao, Shuanfeng; Liu, Min; Guo, Wei; Zhang, Chuanwei

2018-02-28

Force sensitive conductive composite materials are functional materials which can be used as the sensitive material of force sensors. However, the existing sensors only use one-dimensional electrical properties of force sensitive conductive materials. Even in tactile sensors, the measurement of contact pressure is achieved by large-scale arrays and the units of a large-scale array are also based on the one-dimensional electrical properties of force sensitive materials. The main contribution of this work is to study the three-dimensional electrical properties and the inversion method of three-dimensional stress field of a force sensitive material (conductive rubber), which pushes the application of force sensitive material from one dimensional to three-dimensional. First, the mathematical model of the conductive rubber current field distribution under a constant force is established by the effective medium theory, and the current field distribution model of conductive rubber with different geometry, conductive rubber content and conductive rubber relaxation parameters is deduced. Secondly, the inversion method of the three-dimensional stress field of conductive rubber is established, which provides a theoretical basis for the design of a new tactile sensor, three-dimensional stress field and space force based on force sensitive materials.

Majorana zero modes in the hopping-modulated one-dimensional p-wave superconducting model.

PubMed

Gao, Yi; Zhou, Tao; Huang, Huaixiang; Huang, Ran

2015-11-20

We investigate the one-dimensional p-wave superconducting model with periodically modulated hopping and show that under time-reversal symmetry, the number of the Majorana zero modes (MZMs) strongly depends on the modulation period. If the modulation period is odd, there can be at most one MZM. However if the period is even, the number of the MZMs can be zero, one and two. In addition, the MZMs will disappear as the chemical potential varies. We derive the condition for the existence of the MZMs and show that the topological properties in this model are dramatically different from the one with periodically modulated potential.

One-dimensional simulation of temperature and moisture in atmospheric and soil boundary layers

NASA Technical Reports Server (NTRS)

Bornstein, R. D.; Santhanam, K.

1981-01-01

Meteorologists are interested in modeling the vertical flow of heat and moisture through the soil in order to better simulate the vertical and temporal variations of the atmospheric boundary layer. The one dimensional planetary boundary layer model of is modified by the addition of transport equations to be solved by a finite difference technique to predict soil moisture.

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.

Water Availability in Indus River at the Upper Indus Basin under Different Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Khan, Firdos; Pilz, Jürgen

2015-04-01

The last decade of the 20th century and the first decade of the 21st century showed that climate change or global warming is happening and the latter one is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C on May 26, 2010. The changing climate has impact on various areas including agriculture, water, health, among others. There are two main forces which have central role in changing climate: one is natural variability and the other one is human evoked changes, increasing the density of green house gases. The elements in the bunch of Energy-Food-Water are interlinked with one another and among them water plays a crucial role for the existence of the other two parts. This nexus is the central environmental issue around the globe generally, and is of particular importance in the developing countries. The study evaluated the importance and the availability of water in Indus River under different emission scenarios. Four emission scenarios are included, that is, the A2, B2, RCP4.5 and RCP8.5. One way coupling of regional climate models (RCMs) and Hydrological model have been implemented in this study. The PRECIS (Providing Regional Climate for Impact Studies) and CCAM (Conformal-Cubic Atmospheric Model) climate models and UBCWM (University of British Columbia Watershed Model) hydrological model are used for this purpose. It is observed that Indus River contributes 80 % of the hydro-power generation and contributes 44 % to available water annually in Pakistan. It is further investigated whether sufficient water will be available in the Indus River under climate change scenarios. Toward this goal, Tarbela Reservoir is used as a measurement tool using the parameters of the reservoir like maximum operating storage, dead level storage, discharge capacity of tunnels and spillways. The results of this study are extremely important for the economy of Pakistan in various key areas like agriculture, energy, industries and ecosystem. The analyses show that there will be much more water available in future under the considered emission scenarios but in some months there will be scarcity of water. However, by proper management and optimum utilization of the available water, the scarcity of water can be minimized considerably. Finally, a meta-analysis has been performed to present a combined picture of all scenarios considered in this study. One way to avoid water scarcity is to upgrade and install new reservoirs and water storage capacities to reserve the extra water during high river flow in Indus River, which will then be utilized during low river flow. __________________________________________________________________________________ KEY WORDS: Agriculture, Climate Change, Hydro-power, Indus River, Tarbela Reservoir, Upper Indus Basin, Meta-analysis, Hydrological model.

Relationships between Student, Staff, and Administrative Measures of School Climate and Student Health and Academic Outcomes

PubMed Central

Gase, Lauren Nichol; Gomez, Louis M.; Kuo, Tony; Glenn, Beth A.; Inkelas, Moira; Ponce, Ninez A.

2018-01-01

BACKGROUND School climate is an integral part of a comprehensive approach to improving the wellbeing of students; however, little is known about the relationships between its different domains and measures. This study examined the relationships between student, staff, and administrative measures of school climate in order to understand the extent to which they were related to each other and student outcomes. METHODS The sample included 33,572 secondary school students from 121 schools in Los Angeles County during the 2014–2015 academic year. A multilevel regression model was constructed to examine the association between the domains and measures of school climate and five outcomes of student wellbeing: depressive symptoms or suicidal ideation, tobacco use, alcohol use, marijuana use, and grades. RESULTS Student, staff, and administrative measures of school climate were weakly correlated. Strong associations were found between student outcomes and student reports of engagement and safety, while school staff reports and administrative measures of school climate showed limited associations with student outcomes. CONCLUSIONS As schools seek to measure and implement interventions aimed at improving school climate, consideration should be given to grounding these efforts in a multi-dimensional conceptualization of climate that values student perspectives and includes elements of both engagement and safety. PMID:28382671

Web-based Data Visualization of the MGClimDeX Climate Model Output: An Integrated Perspective of Climate Change Impact on Natural Resources in Highly Vulnerable Regions.

NASA Astrophysics Data System (ADS)

Martinez-Rey, J.; Brockmann, P.; Cadule, P.; Nangini, C.

2016-12-01

Earth System Models allow us to understand the interactions between climate and biogeological processes. These models generate a very large amount of data. These data are usually reduced to a few number of static figures shown in highly specialized scientific publications. However, the potential impacts of climate change demand a broader perspective regarding the ways in which climate model results of this kind are disseminated, particularly in the amount and variety of data, and the target audience. This issue is of great importance particularly for scientific projects that seek a large broadcast with different audiences on their key results. The MGClimDeX project, which assesses the climate change impact on La Martinique island in the Lesser Antilles, will provide tools and means to help the key stakeholders -responsible for addressing the critical social, economic, and environmental issues- to take the appropriate adaptation and mitigation measures in order to prevent future risks associated with climate variability and change, and its role on human activities. The MGClimDeX project will do so by using model output and data visualization techniques within the next year, showing the cross-connected impacts of climate change on various sectors (agriculture, forestry, ecosystems, water resources and fisheries). To address this challenge of representing large sets of data from model output, we use back-end data processing and front-end web-based visualization techniques, going from the conventional netCDF model output stored on hub servers to highly interactive web-based data-powered visualizations on browsers. We use the well-known javascript library D3.js extended with DC.js -a dimensional charting library for all the front-end interactive filtering-, in combination with Bokeh, a Python library to synthesize the data, all framed in the essential HTML+CSS scripts. The resulting websites exist as standalone information units or embedded into journals or scientific-related information hubs. These visualizations encompass all the relevant findings, allowing individual model intercomparisons in the context of observations and socioeconomic references. In this way, the full spectrum of results of the MGClimDeX project is available to the public in general and policymakers in particular.

Climatic consequences of very high CO2 levels in Earth's early atmosphere

NASA Technical Reports Server (NTRS)

Kasting, J. F.

1985-01-01

Earth has approximately 60 bars of carbon dioxide tied up in carbonate rocks, or roughly 2/3 the amount of CO2 of Venus' atmosphere. Two different lines of evidence, one based on thermodynamics and the other on geochemical cycles, indicate that a substantial fraction of this CO2 may have resulted in the atmosphere during the first few hundred million years of the Earth's history. A natural question which arises concerning this hypothesis is whether this would have resulted in a runaway greenhouse affect. One-dimensional radiative/convective model calculations show that the surface temperature of a hypothetical primitive atmosphere containing 20 bars of CO2 would have been less than 100C and no runaway greenhouse should have occurred. The climatic stability of the early atmosphere is a consequence of three factors: (1) reduced solar luminosity at that time; (2) an increase in planetary albedo caused by Rayleigh scattering by CO2; and (3) the stabilizing effects of moist convection. The latter two factors are sufficient to prevent a CO2-induced runaway greenhouse on the present Earth and for CO2 levels up to 100 bars. It is determined whether a runaway greenhouse could have occurred during the latter stages of the accretion process and, if so, whether it would have collapsed once the influx of material slowed down.

Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

NASA Astrophysics Data System (ADS)

Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

2017-04-01

Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

Global meta-analysis of leaf area index in wetlands indicates uncertainties in understanding of their ecosystem function

NASA Astrophysics Data System (ADS)

Dronova, I.; Taddeo, S.; Foster, K.

2017-12-01

Projecting ecosystem responses to global change relies on the accurate understanding of properties governing their functions in different environments. An important variable in models of ecosystem function is canopy leaf area index (LAI; leaf area per unit ground area) declared as one of the Essential Climate Variables in the Global Climate Observing System and extensively measured in terrestrial landscapes. However, wetlands have been largely under-represented in these efforts, which globally limits understanding of their contribution to carbon sequestration, climate regulation and resilience to natural and anthropogenic disturbances. This study provides a global synthesis of >350 wetland-specific LAI observations from 182 studies and compares LAI among wetland ecosystem and vegetation types, biomes and measurement approaches. Results indicate that most wetland types and even individual locations show a substantial local dispersion of LAI values (average coefficient of variation 65%) due to heterogeneity of environmental properties and vegetation composition. Such variation indicates that mean LAI values may not sufficiently represent complex wetland environments, and the use of this index in ecosystem function models needs to incorporate within-site variation in canopy properties. Mean LAI did not significantly differ between direct and indirect measurement methods on a pooled global sample; however, within some of the specific biomes and wetland types significant contrasts between these approaches were detected. These contrasts highlight unique aspects of wetland vegetation physiology and canopy structure affecting measurement principles that need to be considered in generalizing canopy properties in ecosystem models. Finally, efforts to assess wetland LAI using remote sensing strongly indicate the promise of this technology for cost-effective regional-scale modeling of canopy properties similar to terrestrial systems. However, such efforts urgently require more rigorous corrections for three-dimensional contributions of non-canopy material and non-vegetated surfaces to wetland canopy reflectance.

Improving the Use of Species Distribution Models in Conservation Planning and Management under Climate Change

PubMed Central

Porfirio, Luciana L.; Harris, Rebecca M. B.; Lefroy, Edward C.; Hugh, Sonia; Gould, Susan F.; Lee, Greg; Bindoff, Nathaniel L.; Mackey, Brendan

2014-01-01

Choice of variables, climate models and emissions scenarios all influence the results of species distribution models under future climatic conditions. However, an overview of applied studies suggests that the uncertainty associated with these factors is not always appropriately incorporated or even considered. We examine the effects of choice of variables, climate models and emissions scenarios can have on future species distribution models using two endangered species: one a short-lived invertebrate species (Ptunarra Brown Butterfly), and the other a long-lived paleo-endemic tree species (King Billy Pine). We show the range in projected distributions that result from different variable selection, climate models and emissions scenarios. The extent to which results are affected by these choices depends on the characteristics of the species modelled, but they all have the potential to substantially alter conclusions about the impacts of climate change. We discuss implications for conservation planning and management, and provide recommendations to conservation practitioners on variable selection and accommodating uncertainty when using future climate projections in species distribution models. PMID:25420020

Decadal climate predictions improved by ocean ensemble dispersion filtering

NASA Astrophysics Data System (ADS)

Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

2017-06-01

Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.