An observationally constrained estimate of global dust aerosol optical depth

DOE PAGES

Ridley, David A.; Heald, Colette L.; Kok, Jasper F.; ...

2016-12-06

Here, the role of mineral dust in climate and ecosystems has been largely quantified using global climate and chemistry model simulations of dust emission, transport, and deposition. However, differences between these model simulations are substantial, with estimates of global dust aerosol optical depth (AOD) that vary by over a factor of 5. Here we develop an observationally based estimate of the global dust AOD, using multiple satellite platforms, in situ AOD observations and four state-of-the-science global models over 2004–2008. We estimate that the global dust AOD at 550 nm is 0.030 ± 0.005 (1σ), higher than the AeroCom model medianmore » (0.023) and substantially narrowing the uncertainty. The methodology used provides regional, seasonal dust AOD and the associated statistical uncertainty for key dust regions around the globe with which model dust schemes can be evaluated. Exploring the regional and seasonal differences in dust AOD between our observationally based estimate and the four models in this study, we find that emissions in Africa are often overrepresented at the expense of Asian and Middle Eastern emissions and that dust removal appears to be too rapid in most models.« less

An ensemble-based dynamic Bayesian averaging approach for discharge simulations using multiple global precipitation products and hydrological models

NASA Astrophysics Data System (ADS)

Qi, Wei; Liu, Junguo; Yang, Hong; Sweetapple, Chris

2018-03-01

Global precipitation products are very important datasets in flow simulations, especially in poorly gauged regions. Uncertainties resulting from precipitation products, hydrological models and their combinations vary with time and data magnitude, and undermine their application to flow simulations. However, previous studies have not quantified these uncertainties individually and explicitly. This study developed an ensemble-based dynamic Bayesian averaging approach (e-Bay) for deterministic discharge simulations using multiple global precipitation products and hydrological models. In this approach, the joint probability of precipitation products and hydrological models being correct is quantified based on uncertainties in maximum and mean estimation, posterior probability is quantified as functions of the magnitude and timing of discharges, and the law of total probability is implemented to calculate expected discharges. Six global fine-resolution precipitation products and two hydrological models of different complexities are included in an illustrative application. e-Bay can effectively quantify uncertainties and therefore generate better deterministic discharges than traditional approaches (weighted average methods with equal and varying weights and maximum likelihood approach). The mean Nash-Sutcliffe Efficiency values of e-Bay are up to 0.97 and 0.85 in training and validation periods respectively, which are at least 0.06 and 0.13 higher than traditional approaches. In addition, with increased training data, assessment criteria values of e-Bay show smaller fluctuations than traditional approaches and its performance becomes outstanding. The proposed e-Bay approach bridges the gap between global precipitation products and their pragmatic applications to discharge simulations, and is beneficial to water resources management in ungauged or poorly gauged regions across the world.

Biomes computed from simulated climatologies

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

Claussen, M.; Esch, M.

1994-01-01

The biome model of Prentice et al. is used to predict global patterns of potential natural plant formations, or biomes, from climatologies simulated by ECHAM, a model used for climate simulations at the Max-Planck-Institut fuer Meteorologie. This study undertaken in order to show the advantage of this biome model in diagnosing the performance of a climate model and assessing effects of past and future climate changes predicted by a climate model. Good overall agreement is found between global patterns of biomes computed from observed and simulated data of present climate. But there are also major discrepancies indicated by a differencemore » in biomes in Australia, in the Kalahari Desert, and in the Middle West of North America. These discrepancies can be traced back to in simulated rainfall as well as summer or winter temperatures. Global patterns of biomes computed from an ice age simulation reveal that North America, Europe, and Siberia should have been covered largely by tundra and taiga, whereas only small differences are for the tropical rain forests. A potential northeast shift of biomes is expected from a simulation with enhanced CO{sub 2} concentration according to the IPCC Scenario A. Little change is seen in the tropical rain forest and the Sahara. Since the biome model used is not capable of predicting chances in vegetation patterns due to a rapid climate change, the latter simulation to be taken as a prediction of chances in conditions favourable for the existence of certain biomes, not as a reduction of a future distribution of biomes. 15 refs., 8 figs., 2 tabs.« less

Simulations of Seismic Wave Propagation on Mars

NASA Astrophysics Data System (ADS)

Bozdağ, Ebru; Ruan, Youyi; Metthez, Nathan; Khan, Amir; Leng, Kuangdai; van Driel, Martin; Wieczorek, Mark; Rivoldini, Attilio; Larmat, Carène S.; Giardini, Domenico; Tromp, Jeroen; Lognonné, Philippe; Banerdt, Bruce W.

2017-10-01

We present global and regional synthetic seismograms computed for 1D and 3D Mars models based on the spectral-element method. For global simulations, we implemented a radially-symmetric Mars model with a 110 km thick crust (Sohl and Spohn in J. Geophys. Res., Planets 102(E1):1613-1635, 1997). For this 1D model, we successfully benchmarked the 3D seismic wave propagation solver SPECFEM3D_GLOBE (Komatitsch and Tromp in Geophys. J. Int. 149(2):390-412, 2002a; 150(1):303-318, 2002b) against the 2D axisymmetric wave propagation solver AxiSEM (Nissen-Meyer et al. in Solid Earth 5(1):425-445, 2014) at periods down to 10 s. We also present higher-resolution body-wave simulations with AxiSEM down to 1 s in a model with a more complex 1D crust, revealing wave propagation effects that would have been difficult to interpret based on ray theory. For 3D global simulations based on SPECFEM3D_GLOBE, we superimposed 3D crustal thickness variations capturing the distinct crustal dichotomy between Mars' northern and southern hemispheres, as well as topography, ellipticity, gravity, and rotation. The global simulations clearly indicate that the 3D crust speeds up body waves compared to the reference 1D model, whereas it significantly changes surface waveforms and their dispersive character depending on its thickness. We also perform regional simulations with the solver SES3D (Fichtner et al. Geophys. J. Int. 179:1703-1725, 2009) based on 3D crustal models derived from surface composition, thereby addressing the effects of various distinct crustal features down to 2 s. The regional simulations confirm the strong effects of crustal variations on waveforms. We conclude that the numerical tools are ready for examining more scenarios, including various other seismic models and sources.

A global hydrological simulation to specify the sources of water used by humans

NASA Astrophysics Data System (ADS)

Hanasaki, Naota; Yoshikawa, Sayaka; Pokhrel, Yadu; Kanae, Shinjiro

2018-01-01

Humans abstract water from various sources to sustain their livelihood and society. Some global hydrological models (GHMs) include explicit schemes of human water abstraction, but the representation and performance of these schemes remain limited. We substantially enhanced the water abstraction schemes of the H08 GHM. This enabled us to estimate water abstraction from six major water sources, namely, river flow regulated by global reservoirs (i.e., reservoirs regulating the flow of the world's major rivers), aqueduct water transfer, local reservoirs, seawater desalination, renewable groundwater, and nonrenewable groundwater. In its standard setup, the model covers the whole globe at a spatial resolution of 0.5° × 0.5°, and the calculation interval is 1 day. All the interactions were simulated in a single computer program, and all water fluxes and storage were strictly traceable at any place and time during the simulation period. A global hydrological simulation was conducted to validate the performance of the model for the period of 1979-2013 (land use was fixed for the year 2000). The simulated water fluxes for water abstraction were validated against those reported in earlier publications and showed a reasonable agreement at the global and country level. The simulated monthly river discharge and terrestrial water storage (TWS) for six of the world's most significantly human-affected river basins were compared with gauge observations and the data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. It is found that the simulation including the newly added schemes outperformed the simulation without human activities. The simulated results indicated that, in 2000, of the 3628±75 km3 yr-1 global freshwater requirement, 2839±50 km3 yr-1 was taken from surface water and 789±30 km3 yr-1 from groundwater. Streamflow, aqueduct water transfer, local reservoirs, and seawater desalination accounted for 1786±23, 199±10, 106±5, and 1.8±0 km3 yr-1 of the surface water, respectively. The remaining 747±45 km3 yr-1 freshwater requirement was unmet, or surface water was not available when and where it was needed in our simulation. Renewable and nonrenewable groundwater accounted for 607±11 and 182±26 km3 yr-1 of the groundwater total, respectively. Each source differed in its renewability, economic costs for development, and environmental consequences of usage. The model is useful for performing global water resource assessments by considering the aspects of sustainability, economy, and environment.

Large historical growth in global terrestrial gross primary production

DOE PAGES

Campbell, J. E.; Berry, J. A.; Seibt, U.; ...

2017-04-05

Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including amore » large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.« less

Large historical growth in global terrestrial gross primary production

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

Campbell, J. E.; Berry, J. A.; Seibt, U.

Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including amore » large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.« less

Using DOUBLE STAR and CLUSTER Synoptic Observations to Test Global MHD Simulations of the Large-scale Topology of the Dayside Merging Region

NASA Astrophysics Data System (ADS)

Berchem, J.; Marchaudon, A.; Bosqued, J.; Escoubet, C. P.; Dunlop, M.; Owen, C. J.; Reme, H.; Balogh, A.; Carr, C.; Fazakerley, A. N.; Cao, J. B.

2005-12-01

Synoptic measurements from the DOUBLE STAR and CLUSTER spacecraft offer a unique opportunity to evaluate global models in simulating the complex topology and dynamics of the dayside merging region. We compare observations from the DOUBLE STAR TC-1 and CLUSTER spacecraft on May 8, 2004 with the predictions from a three-dimensional magnetohydrodynamic (MHD) simulation that uses plasma and magnetic field parameters measured upstream of the bow shock by the WIND spacecraft. Results from the global simulation are consistent with the large-scale features observed by CLUSTER and TC-1. We discuss topological changes and plasma flows at the dayside magnetospheric boundary inferred from the simulation results. The simulation shows that the DOUBLE STAR spacecraft passed through the dawn side merging region as the IMF rotated. In particular, the simulation indicates that at times TC-1 was very close to the merging region. In addition, we found that the bifurcation of the merging region in the simulation results is consistent with predictions by the antiparallel merging model. However, because of the draping of the magnetosheath field lines over the magnetopause, the positions and shape of the merging region differ significantly from those predicted by the model.

A THREE-DIMENSIONAL MODEL ASSESSMENT OF THE GLOBAL DISTRIBUTION OF HEXACHLOROBENZENE

EPA Science Inventory

The distributions of persistent organic pollutants (POPs) in the global environment have been studied typically with box/fugacity models with simplified treatments of atmospheric transport processes1. Such models are incapable of simulating the complex three-dimensional mechanis...

Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model

NASA Astrophysics Data System (ADS)

Mann, G. W.; Carslaw, K. S.; Spracklen, D. V.; Ridley, D. A.; Manktelow, P. T.; Chipperfield, M. P.; Pickering, S. J.; Johnson, C. E.

2010-10-01

A new version of the Global Model of Aerosol Processes (GLOMAP) is described, which uses a two-moment pseudo-modal aerosol dynamics approach rather than the original two-moment bin scheme. GLOMAP-mode simulates the multi-component global aerosol, resolving sulfate, sea-salt, dust, black carbon (BC) and particulate organic matter (POM), the latter including primary and biogenic secondary POM. Aerosol processes are simulated in a size-resolved manner including primary emissions, secondary particle formation by binary homogeneous nucleation of sulfuric acid and water, particle growth by coagulation, condensation and cloud-processing and removal by dry deposition, in-cloud and below-cloud scavenging. A series of benchmark observational datasets are assembled against which the skill of the model is assessed in terms of normalised mean bias (b) and correlation coefficient (R). Overall, the model performs well against the datasets in simulating concentrations of aerosol precursor gases, chemically speciated particle mass, condensation nuclei (CN) and cloud condensation nuclei (CCN). Surface sulfate, sea-salt and dust mass concentrations are all captured well, while BC and POM are biased low (but correlate well). Surface CN concentrations compare reasonably well in free troposphere and marine sites, but are underestimated at continental and coastal sites related to underestimation of either primary particle emissions or new particle formation. The model compares well against a compilation of CCN observations covering a range of environments and against vertical profiles of size-resolved particle concentrations over Europe. The simulated global burden, lifetime and wet removal of each of the simulated aerosol components is also examined and each lies close to multi-model medians from the AEROCOM model intercomparison exercise.

Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model

NASA Astrophysics Data System (ADS)

Mann, G. W.; Carslaw, K. S.; Spracklen, D. V.; Ridley, D. A.; Manktelow, P. T.; Chipperfield, M. P.; Pickering, S. J.; Johnson, C. E.

2010-05-01

A new version of the Global Model of Aerosol Processes (GLOMAP) is described, which uses a two-moment modal aerosol scheme rather than the original two-moment bin scheme. GLOMAP-mode simulates the multi-component global aerosol, resolving sulphate, sea-salt, dust, black carbon (BC) and particulate organic matter (POM), the latter including primary and biogenic secondary POM. Aerosol processes are simulated in a size-resolved manner including primary emissions, secondary particle formation by binary homogeneous nucleation of sulphuric acid and water, particle growth by coagulation, condensation and cloud-processing and removal by dry deposition, in-cloud and below-cloud scavenging. A series of benchmark observational datasets are assembled against which the skill of the model is assessed in terms of normalised mean bias (b) and correlation coefficient (R). Overall, the model performs well against the datasets in simulating concentrations of aerosol precursor gases, chemically speciated particle mass, condensation nuclei (CN) and cloud condensation nuclei (CCN). Surface sulphate, sea-salt and dust mass concentrations are all captured well, while BC and POM are biased low (but correlate well). Surface CN concentrations compare reasonably well in free troposphere and marine sites, but are underestimated at continental and coastal sites related to underestimation of either primary particle emissions or new particle formation. The model compares well against a compilation of CCN observations covering a range of environments and against vertical profiles of size-resolved particle concentrations over Europe. The simulated global burden, lifetime and wet removal of each of the simulated aerosol components is also examined and each lies close to multi-model medians from the AEROCOM model intercomparison exercise.

Changes of global terrestrial carbon budget and major drivers in recent 30 years simulated using the remote sensing driven BEPS model

NASA Astrophysics Data System (ADS)

Ju, W.; Chen, J.; Liu, R.; Liu, Y.

2013-12-01

The process-based Boreal Ecosystem Productivity Simulator (BEPS) model was employed in conjunction with spatially distributed leaf area index (LAI), land cover, soil, and climate data to simulate the carbon budget of global terrestrial ecosystems during the period from 1981 to 2008. The BEPS model was first calibrated and validated using gross primary productivity (GPP), net primary productivity (NPP), and net ecosystem productivity (NEP) measured in different ecosystems across the word. Then, four global simulations were conducted at daily time steps and a spatial resolution of 8 km to quantify the global terrestrial carbon budget and to identify the relative contributions of changes in climate, atmospheric CO2 concentration, and LAI to the global terrestrial carbon sink. The long term LAI data used to drive the model was generated through fusing Moderate Resolution Imaging Spectroradiometer (MODIS) and historical Advanced Very High Resolution Radiometer (AVHRR) data pixel by pixel. The meteorological fields were interpolated from the 0.5° global daily meteorological dataset produced by the land surface hydrological research group at Princeton University. The results show that the BEPS model was able to simulate carbon fluxes in different ecosystems. Simulated GPP, NPP, and NEP values and their temporal trends exhibited distinguishable spatial patterns. During the period from 1981 to 2008, global terrestrial ecosystems acted as a carbon sink. The averaged global totals of GPP NPP, and NEP were 122.70 Pg C yr-1, 56.89 Pg C yr-1, and 2.76 Pg C yr-1, respectively. The global totals of GPP and NPP increased greatly, at rates of 0.43 Pg C yr-2 (R2=0.728) and 0.26 Pg C yr-2 (R2=0.709), respectively. Global total NEP did not show an apparent increasing trend (R2= 0.036), averaged 2.26 Pg C yr-1, 3.21 Pg C yr-1, and 2.72 Pg C yr-1 for the periods from 1981 to 1989, from 1990 to 1999, and from 2000 to 2008, respectively. The magnitude and temporal trend of global terrestrial carbon budget were similar to the values recently reported by the Global Carbon Project. The obvious increases in global GPP and NPP were mainly driven by the enhancement of atmospheric CO2 fertilization. The change of LAI played the secondary role. Climate had a small negative impact on global terrestrial carbon sequestration. The relative importance of changes in climate, atmospheric CO2 concentration, and LAI in altering the temporal trend of carbon sequestration differed spatially. During the period from 2000 to 2008, terrestrial carbon sinks mainly existed in the northern region of South America, the western region of middle Africa, Southeast Asia, Southeast China, Southeast United States, and some regions of Eurasia.

Hydrological modelling in forested systems | Science ...

EPA Pesticide Factsheets

This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.

Implementation of the MEGAN (v2.1) biogenic emission model in the ECHAM6-HAMMOZ chemistry climate model

NASA Astrophysics Data System (ADS)

Henrot, Alexandra-Jane; Stanelle, Tanja; Schröder, Sabine; Siegenthaler, Colombe; Taraborrelli, Domenico; Schultz, Martin G.

2017-02-01

A biogenic emission scheme based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 (Guenther et al., 2012) has been integrated into the ECHAM6-HAMMOZ chemistry climate model in order to calculate the emissions from terrestrial vegetation of 32 compounds. The estimated annual global total for the reference simulation is 634 Tg C yr-1 (simulation period 2000-2012). Isoprene is the main contributor to the average emission total, accounting for 66 % (417 Tg C yr-1), followed by several monoterpenes (12 %), methanol (7 %), acetone (3.6 %), and ethene (3.6 %). Regionally, most of the high annual emissions are found to be associated with tropical regions and tropical vegetation types. In order to evaluate the implementation of the biogenic model in ECHAM-HAMMOZ, global and regional biogenic volatile organic compound (BVOC) emissions of the reference simulation were compared to previous published experiment results with MEGAN. Several sensitivity simulations were performed to study the impact of different model input and parameters related to the vegetation cover and the ECHAM6 climate. BVOC emissions obtained here are within the range of previous published estimates. The large range of emission estimates can be attributed to the use of different input data and empirical coefficients within different setups of MEGAN. The biogenic model shows a high sensitivity to the changes in plant functional type (PFT) distributions and associated emission factors for most of the compounds. The global emission impact for isoprene is about -9 %, but reaches +75 % for α-pinene when switching from global emission factor maps to PFT-specific emission factor distributions. The highest sensitivity of isoprene emissions is calculated when considering soil moisture impact, with a global decrease of 12.5 % when the soil moisture activity factor is included in the model parameterization. Nudging ECHAM6 climate towards ERA-Interim reanalysis has an impact on the biogenic emissions, slightly lowering the global total emissions and their interannual variability.

Global simulation of interactions between groundwater and terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Braakhekke, M. C.; Rebel, K.; Dekker, S. C.; Smith, B.; Van Beek, L. P.; Sutanudjaja, E.; van Kampenhout, L.; Wassen, M. J.

2016-12-01

In many places in the world ecosystems are influenced by the presence of a shallow groundwater table. In these regions upward water flux due to capillary rise increases soil moisture availability in the root zone, which has strong positive effect on evapotranspiration. Additionally it has important consequences for vegetation dynamics and fluxes of carbon and nitrogen. Under water limited conditions shallow groundwater stimulates vegetation productivity, and soil organic matter decomposition while under saturated conditions groundwater may have a negative effect on these processes due to lack of oxygen. Furthermore, since plant species differ with respect to their root distribution, preference for moisture conditions, and resistance to oxygen stress, shallow groundwater also influences vegetation type. Finally, processes such as denitrification and methane production occur under strictly anaerobic conditions and are thus strongly influenced by moisture availability. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure and are therefore less suitable to represent effects of groundwater on biogeochemical fluxes. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure and biogeochemical processes. These models are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB. Using this coupled model we aim to study the influence of shallow groundwater on terrestrial ecosystem processes. We will present results of global simulations to demonstrate the effects on C, N, and water fluxes.

Evaluating climate models: Should we use weather or climate observations?

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

Comparison of MADE3-simulated and observed aerosol distributions with a focus on aerosol vertical profiles

NASA Astrophysics Data System (ADS)

Kaiser, Christopher; Hendricks, Johannes; Righi, Mattia; Jöckel, Patrick

2016-04-01

The reliability of aerosol radiative forcing estimates from climate models depends on the accuracy of simulated global aerosol distribution and composition, as well as on the models' representation of the aerosol-cloud and aerosol-radiation interactions. To help improve on previous modeling studies, we recently developed the new aerosol microphysics submodel MADE3 that explicitly tracks particle mixing state in the Aitken, accumulation, and coarse mode size ranges. We implemented MADE3 into the global atmospheric chemistry general circulation model EMAC and evaluated it by comparison of simulated aerosol properties to observations. Compared properties include continental near-surface aerosol component concentrations and size distributions, continental and marine aerosol vertical profiles, and nearly global aerosol optical depth. Recent studies have shown the specific importance of aerosol vertical profiles for determination of the aerosol radiative forcing. Therefore, our focus here is on the evaluation of simulated vertical profiles. The observational data is taken from campaigns between 1990 and 2011 over the Pacific Ocean, over North and South America, and over Europe. The datasets include black carbon and total aerosol mass mixing ratios, as well as aerosol particle number concentrations. Compared to other models, EMAC with MADE3 yields good agreement with the observations - despite a general high bias of the simulated mass mixing ratio profiles. However, BC concentrations are generally overestimated by many models in the upper troposphere. With MADE3 in EMAC, we find better agreement of the simulated BC profiles with HIPPO data than the multi-model average of the models that took part in the AeroCom project. There is an interesting difference between the profiles from individual campaigns and more "climatological" datasets. For instance, compared to spatially and temporally localized campaigns, the model simulates a more continuous decline in both total aerosol and black carbon mass mixing ratio with altitude than found in the observations. In contrast, measured profiles from the HIPPO project are qualitatively captured well. Similar conclusions hold for the comparison of simulated and measured aerosol particle number concentrations. On the one hand, these results exemplify the difficulty in evaluating the representativeness of the simulated global climatological state of the aerosol by means of comparison with individually measured vertical profiles. On the other hand, it highlights the value of aircraft campaigns with large spatial and temporal coverage for model evaluation.

Integrating global socio-economic influences into a regional land use change model for China

NASA Astrophysics Data System (ADS)

Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li

2014-03-01

With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socioeconomic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

Shifts in nitrogen acquisition strategies enable enhanced terrestrial carbon storage under elevated CO2 in a global model

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Brzostek, E. R.; Menge, D.; Malyshev, S.; Shevliakova, E.

2017-12-01

Earth System Model (ESM) projections of terrestrial carbon (C) uptake are critical to understanding the future of the global C cycle. Current ESMs include intricate representations of photosynthetic C fixation in plants, allowing them to simulate the stimulatory effect of increasing atmospheric CO2 levels on photosynthesis. However, they lack sophisticated representations of plant nutrient acquisition, calling into question their ability to project the future land C sink. We conducted simulations using a new model of terrestrial C and nitrogen (N) cycling within the Geophysical Fluid Dynamics Laboratory (GFDL) global land model LM4 that uses a return on investment framework to simulate global patterns of N acquisition via fixation of N2 from the atmosphere, scavenging of inorganic N from soil solution, and mining of organic N from soil organic matter (SOM). We show that these strategies drive divergent C cycle responses to elevated CO2 at the ecosystem scale, with the scavenging strategy leading to N limitation of plant growth and the mining strategy facilitating stimulation of plant biomass accumulation over decadal time scales. In global simulations, shifts in N acquisition from inorganic N scavenging to organic N mining along with increases in N fixation supported long-term acceleration of C uptake under elevated CO2. Our results indicate that the ability of the land C sink to mitigate atmospheric CO2 levels is tightly coupled to the functional diversity of ecosystems and their capacity to change their N acquisition strategies over time. Incorporation of these mechanisms into ESMs is necessary to improve confidence in model projections of the global C cycle.

Modeling spatial-temporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Z.; Zimmermann, N. E.; Poulter, B.

2015-11-01

Simulations of the spatial-temporal dynamics of wetlands are key to understanding the role of wetland biogeochemistry under past and future climate variability. Hydrologic inundation models, such as TOPMODEL, are based on a fundamental parameter known as the compound topographic index (CTI) and provide a computationally cost-efficient approach to simulate wetland dynamics at global scales. However, there remains large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl dynamic global vegetation model (DGVM), and quantifies uncertainties by comparing three digital elevation model products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. In addition, we found that calibrating TOPMODEL with a benchmark wetland dataset can help to successfully delineate the seasonal and interannual variations of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows best accuracy for capturing the spatio-temporal dynamics of wetlands among the three DEM products. The estimate of global wetland potential/maximum is ∼ 10.3 Mkm2 (106 km2), with a mean annual maximum of ∼ 5.17 Mkm2 for 1980-2010. This study demonstrates the feasibility to capture spatial heterogeneity of inundation and to estimate seasonal and interannual variations in wetland by coupling a hydrological module in LSMs with appropriate benchmark datasets. It additionally highlights the importance of an adequate investigation of topographic indices for simulating global wetlands and shows the opportunity to converge wetland estimates across LSMs by identifying the uncertainty associated with existing wetland products.

Integration of Extended MHD and Kinetic Effects in Global Magnetosphere Models

NASA Astrophysics Data System (ADS)

Germaschewski, K.; Wang, L.; Maynard, K. R. M.; Raeder, J.; Bhattacharjee, A.

2015-12-01

Computational models of Earth's geospace environment are an important tool to investigate the science of the coupled solar-wind -- magnetosphere -- ionosphere system, complementing satellite and ground observations with a global perspective. They are also crucial in understanding and predicting space weather, in particular under extreme conditions. Traditionally, global models have employed the one-fluid MHD approximation, which captures large-scale dynamics quite well. However, in Earth's nearly collisionless plasma environment it breaks down on small scales, where ion and electron dynamics and kinetic effects become important, and greatly change the reconnection dynamics. A number of approaches have recently been taken to advance global modeling, e.g., including multiple ion species, adding Hall physics in a Generalized Ohm's Law, embedding local PIC simulations into a larger fluid domain and also some work on simulating the entire system with hybrid or fully kinetic models, the latter however being to computationally expensive to be run at realistic parameters. We will present an alternate approach, ie., a multi-fluid moment model that is derived rigorously from the Vlasov-Maxwell system. The advantage is that the computational cost remains managable, as we are still solving fluid equations. While the evolution equation for each moment is exact, it depends on the next higher-order moment, so that truncating the hiearchy and closing the system to capture the essential kinetic physics is crucial. We implement 5-moment (density, momentum, scalar pressure) and 10-moment (includes pressure tensor) versions of the model, and use local approximations for the heat flux to close the system. We test these closures by local simulations where we can compare directly to PIC / hybrid codes, and employ them in global simulations using the next-generation OpenGGCM to contrast them to MHD / Hall-MHD results and compare with observations.

Challenges in global modeling of wetland extent and wetland methane dynamics

NASA Astrophysics Data System (ADS)

Spahni, R.; Melton, J. R.; Wania, R.; Stocker, B. D.; Zürcher, S.; Joos, F.

2012-12-01

Global wetlands are known to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. Modelling of global wetland extent and wetland CH4 dynamics remains a challenge. Here we present results from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) that investigated our present ability to simulate large scale wetland characteristics (e.g. wetland type, water table, carbon cycling, gas transport, etc.) and corresponding CH4 emissions. Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The WETCHIMP experiments showed that while models disagree in spatial and temporal patterns of simulated CH4 emissions and wetland areal extent, they all do agree on a strong positive response to increased carbon dioxide concentrations. WETCHIMP made clear that we currently lack observation data sets that are adequate to evaluate model CH4 soil-atmosphere fluxes at a spatial scale comparable to model grid cells. Thus there are substantial parameter and structural uncertainties in large-scale CH4 emission models. As an illustration of the implications of CH4 emissions on climate we show results of the LPX-Bern model, as one of the models participating in WETCHIMP. LPX-Bern is forced with observed 20th century climate and climate output from an ensemble of five comprehensive climate models for a low and a high emission scenario till 2100 AD. In the high emission scenario increased substrate availability for methanogenesis due to a strong stimulation of net primary productivity, and faster soil turnover leads to an amplification of CH4 emissions with the sharpest increase in peatlands (+180% compared to present). Combined with prescribed anthropogenic CH4 emissions, simulated atmospheric CH4 concentration reaches ~4500 ppbv by 2100 AD, about 800 ppbv more than in standard IPCC scenarios. This represents a significant contribution to radiative forcing of global climate.

CONSTABLE: A Global Climate Model for Classroom Use.

ERIC Educational Resources Information Center

Cerveny, Randall S.; And Others

1985-01-01

Described is the global climate model CONSTABLE (Climatic One-Dimensional Numerical Simulation of the Annual Balance of Latitudinal Energy), which can be used in undergraduate and graduate level climatology courses. Classroom exercises that can be used with the model are also included. (RM)

Enhancing the water management schemes of H08 global hydrological model to attribute human water use to six major water sources

NASA Astrophysics Data System (ADS)

Hanasaki, N.; Yoshikawa, S.; Pokhrel, Y. N.; Kanae, S.

2017-12-01

Humans abstract water from various sources to sustain their livelihood and society. Some global hydrological models (GHMs) include explicit schemes of human water management, but the representation and performance of these schemes remain limited. We substantially enhanced the human water management schemes of the H08 GHM by incorporating the latest data and techniques. The model enables us to estimate water abstraction from six major water sources, namely, river flow regulated by global reservoirs (i.e., reservoirs regulating the flow of the world's major rivers), aqueduct water transfer, local reservoirs, seawater desalination, renewable groundwater, and nonrenewable groundwater. All the interactions were simulated in a single computer program and the water balance was always strictly closed at any place and time during the simulation period. Using this model, we first conducted a historical global hydrological simulation at a spatial resolution of 0.5 x 0.5 degree to specify the sources of water for humanity. The results indicated that, in 2000, of the 3628 km3yr-1 global freshwater requirement, 2839 km3yr-1 was taken from surface water and 789 km3yr-1 from groundwater. Streamflow, aqueduct water transfer, local reservoirs, and seawater desalination accounted for 1786, 199, 106, and 1.8 km3yr-1 of the surface water, respectively. The remaining 747 km3yr-1 freshwater requirement was unmet, or surface water was not available when and where it was needed in our simulation. Renewable and nonrenewable groundwater accounted for 607 and 182 km3yr-1 of the groundwater total, respectively. Second, we evaluated the water stress using our simulations and contrasted it with earlier global assessments based on empirical water scarcity indicators, namely, the Withdrawal to Availability ratio and the Falkenmark index (annual renewable water resources per capita). We found that inclusion of water infrastructures in our model diminished water stress in some parts of the world, on the other hand, daily evaluation of water supply and demand highlighted the temporal/seasonal water deficit due to their variations. The enhanced model is potentially useful for quantitative understanding of the global hydrological cycles including human activities and advancement of global water resources assessment.

A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1

NASA Astrophysics Data System (ADS)

Rabin, Sam S.; Ward, Daniel S.; Malyshev, Sergey L.; Magi, Brian I.; Shevliakova, Elena; Pacala, Stephen W.

2018-03-01

This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001-2009 (global totals: 0.434×106 and 2.02×106 km2 yr-1 modeled, 0.454×106 and 2.04×106 km2 yr-1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.295 and 0.706 PgC yr-1 modeled, 0.194 and 0.538 PgC yr-1 observed). The non-agricultural fire module underestimates global burned area (1.91×106 km2 yr-1 modeled, 2.44×106 km2 yr-1 observed) and carbon emissions (1.14 PgC yr-1 modeled, 1.84 PgC yr-1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, Central Asia, and Australia, whereas the boreal zone sees underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets. We include an in-depth discussion of the lessons learned from using the Levenberg-Marquardt algorithm in an interactive optimization for a dynamic global vegetation model.

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

NASA Astrophysics Data System (ADS)

McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.

2016-03-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

USGS Publications Warehouse

McDowell, Nathan G.; Williams, A.P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, Sanna; Pangle, R.; Limousin, J.; Plaut, J.J.; Mackay, D.S.; Ogee, J.; Domec, Jean-Christophe; Allen, Craig D.; Fisher, Rosie A.; Jiang, X.; Muss, J.D.; Breshears, D.D.; Rauscher, Sara A.; Koven, C.

2016-01-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Assessing the Influence of Human Activities on Global Water Resources Using an Advanced Land Surface Model

NASA Astrophysics Data System (ADS)

Pokhrel, Y.; Hanasaki, N.; Koirala, S.; Kanae, S.; Oki, T.

2010-12-01

In order to examine the impact of human intervention on the global hydrological cycle, a Land Surface Model was enhanced with schemes to assess the anthropogenic disturbance on the natural water flow at the global scale. Four different schemes namely; reservoir operation, crop growth, environmental flow, and anthropogenic water withdrawal modules from a state-of-the-art global water resources assessment model called H08 were integrated into an offline version of LSM, Minimal Advance Treatment of Surface Interaction and Runoff (MATSIRO). MATSIRO represents majority of the hydrological processes of water and energy exchange between the land surface and the atmosphere on a physical basis and is designed to be coupled with GCM. The integrated model presented here thus has the capability to simulate both natural and anthropogenic flows of water globally at a spatial resolution of 1°x1°, considering dam operation, domestic, industrial and agricultural water withdrawals and environmental flow requirements. The model can also be coupled with climate models to assess the impact of human activities on the climate system. A simple groundwater scheme was also incorporated and the model can be used to assess the change in water table due to groundwater pumping for irrigation. The model was validated by comparing simulated soil moisture, river discharge and Terrestrial Water Storage Anomaly (TWSA) with observations. The model performs well in simulating TWSA as compared to GRACE observation in different river basins ranging from very wet to very dry. Soil moisture cannot be validated globally because of the lack of validation datasets. For Illinois region, where long term soil moisture observations are available, the model captures the seasonal variation quite well. The simulated global potential irrigation demand is about 1100km3/year, which is within the range of previously published estimates based on various water balance models and LSMs. The model has an advanced option to limit water withdrawal from river channels based on water availability and environmental flow requirements. Results showed that about three-fourth of the irrigation demand can be met from surface-water (rivers, small and medium-sized reservoirs). Therefore, one-fourth of the demand must have been supplied by groundwater. Further analysis of modeled groundwater pumping for irrigation is needed to examine the extent of groundwater withdrawal and its impact on water table fluctuations.

Global River Water Temperature Modelling at Hyper-Resolution

NASA Astrophysics Data System (ADS)

Wanders, N.; van Vliet, M. T. H.; Wada, Y.; Van Beek, L. P.

2017-12-01

The temperature of river water plays a crucial role in many physical, chemical and biological aquatic processes. The influence of changing water temperatures is not only felt locally, but also has regional and downstream impacts. Sectors that might be affected by sudden or gradual changes in the water temperature are: energy production, industry and recreation. Although it is very important to have detailed information on this environmental variable, high-resolution simulations of water temperature on a large scale are currently lacking. Here we present a novel hyper-resolution water temperature dataset at the global scale. We developed the 1-D energy routing model WARM, to simulate river temperature for the period 1980-2014 at 10 km and 50 km resolution. The WARM model accounts for surface water abstraction, reservoirs, riverine flooding and formation of ice, therefore enabling a realistic representation of the water temperature. The water temperature simulations have been validated against 358 river monitoring stations globally for the period 1980 to 2014. The results indicate the increase in resolution significantly improves the simulation performance with a decrease in the water temperature RMSE from 3.5°C to 3.0°C and an increase in the mean correlation of the daily discharge simulations, from R=0.4 to 0.6. We find an average global increase in water temperature of 0.22°C per decade between 1960-2014, with increasing trends towards the end of the simulations period. Strong increasing trends in maxima in the Northern Hemisphere (0.62°C per decade) and minima in the Southern Hemisphere (0.45°C per decade). Finally, we show the impact of major heatwaves and drought events on the water temperature and water availability. The high resolution not only improves the model performance; it also positively impacts the relevancy of the simulation for local and regional scale studies and impact assessments. This new global water temperature dataset could help to develop decision-support system related to water quality with increasing precision and accuracy.

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2.

PubMed

Friend, Andrew D; Lucht, Wolfgang; Rademacher, Tim T; Keribin, Rozenn; Betts, Richard; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B; Dankers, Rutger; Falloon, Pete D; Ito, Akihiko; Kahana, Ron; Kleidon, Axel; Lomas, Mark R; Nishina, Kazuya; Ostberg, Sebastian; Pavlick, Ryan; Peylin, Philippe; Schaphoff, Sibyll; Vuichard, Nicolas; Warszawski, Lila; Wiltshire, Andy; Woodward, F Ian

2014-03-04

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510-758 ppm of CO2), vegetation carbon increases by 52-477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2

PubMed Central

Friend, Andrew D.; Lucht, Wolfgang; Rademacher, Tim T.; Keribin, Rozenn; Betts, Richard; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B.; Dankers, Rutger; Falloon, Pete D.; Ito, Akihiko; Kahana, Ron; Kleidon, Axel; Lomas, Mark R.; Nishina, Kazuya; Ostberg, Sebastian; Pavlick, Ryan; Peylin, Philippe; Schaphoff, Sibyll; Vuichard, Nicolas; Warszawski, Lila; Wiltshire, Andy; Woodward, F. Ian

2014-01-01

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510–758 ppm of CO2), vegetation carbon increases by 52–477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended. PMID:24344265

GNAQPMS-Hg v1.0, a global nested atmospheric mercury transport model: model description, evaluation and application to trans-boundary transport of Chinese anthropogenic emissions

NASA Astrophysics Data System (ADS)

Chen, H. S.; Wang, Z. F.; Li, J.; Tang, X.; Ge, B. Z.; Wu, X. L.; Wild, O.; Carmichael, G. R.

2015-09-01

Atmospheric mercury (Hg) is a toxic pollutant and can be transported over the whole globe due to its long lifetime in the atmosphere. For the purpose of assessing Hg hemispheric transport and better characterizing regional Hg pollution, a global nested atmospheric Hg transport model (GNAQPMS-Hg - Global Nested Air Quality Prediction Modeling System for Hg) has been developed. In GNAQPMS-Hg, the gas- and aqueous-phase Hg chemistry representing the transformation among three forms of Hg: elemental mercury (Hg(0)), divalent mercury (Hg(II)), and primary particulate mercury (Hg(P)) are calculated. A detailed description of the model, including mercury emissions, gas- and aqueous-phase chemistry, and dry and wet deposition is given in this study. Worldwide observations including extensive data in China have been collected for model evaluation. Comparison results show that the model reasonably simulates the global mercury budget and the spatiotemporal variation of surface mercury concentrations and deposition. Overall, model predictions of annual total gaseous mercury (TGM) and wet deposition agree with observations within a factor of 2, and within a factor of 5 for oxidized mercury and dry deposition. The model performs significantly better in North America and Europe than in East Asia. This can probably be attributed to the large uncertainties in emission inventories, coarse model resolution and to the inconsistency between the simulation and observation periods in East Asia. Compared to the global simulation, the nested simulation shows improved skill at capturing the high spatial variability of surface Hg concentrations and deposition over East Asia. In particular, the root mean square error (RMSE) of simulated Hg wet deposition over East Asia is reduced by 24 % in the nested simulation. Model sensitivity studies indicate that Chinese primary anthropogenic emissions account for 30 and 62 % of surface mercury concentrations and deposition over China, respectively. Along the rim of the western Pacific, the contributions from Chinese sources are 11 and 15.2 % over the Korean Peninsula, 10.4 and 8.2 % over Southeast Asia, and 5.7 and 5.9 % over Japan. But for North America, Europe and western Asia, the contributions from China are all below 5 %.

A Global Assessment of Dissolved Organic Carbon in Precipitation

NASA Astrophysics Data System (ADS)

Safieddine, Sarah A.; Heald, Colette L.

2017-11-01

Precipitation is the largest physical removal pathway of atmospheric reactive organic carbon in the form of dissolved organic carbon (DOC). We present the first global DOC distribution simulated with a global model. A total of 85 and 188 Tg C yr-1 are deposited to the ocean and the land, respectively, with DOC ranging between 0.1 and 10 mg C L-1 in this GEOS-Chem simulation. We compare the 2010 simulated DOC to a 30 year synthesis of measurements. Despite limited measurements and imperfect temporal matching, the model is able to reproduce much of the spatial variability of DOC (r = 0.63), with a low bias of 35%. We present the global average carbon oxidation state (OSc>¯) as a simple metric for describing the chemical composition. In the atmosphere, -1.8≤OSc>¯≤-0.6, and the increase in solubility upon oxidation leads to a global increase in OSc>¯ in precipitation with -0.6≤OSc>¯DOC≤0.

Cloud evaluation using satellite simulators and cloud changes for global nonhydrostatic simulations with NICAM

NASA Astrophysics Data System (ADS)

Satoh, M.; Noda, A. T.; Kodama, C.; Yamada, Y.; Hashino, T.

2012-12-01

Global cloud distributions and properties simulated by the global nonhydrostatic model, NICAM (Nonhydrostatic Icosahedral Atmospheric Model), are evaluated and their future changes are discussed. First, we evaluated the simulated cloud properties produced by a case study of the 3.5km mesh experiment of NICAM using the satellite simulator package (the Joint-simulator) with cloud microphysics oriented approach (Hashino et al. 2012). Then, we analyzed future cloud changes using various sets of simulations under the present and the future global warming conditions. The results show that the zonal averaged ice water path (IWP) generally decreases or marginally unchanged in the tropics, while IWP in the extra-tropics increases. The upper cloud fraction increases both in the tropics and in the extra-tropics in general. We further analyzed contributions of cloud systems such as cloud clusters, tropical cyclones (TCs), and storm-tracks to these changes. Probability distribution of the larger cloud clusters decreases, while that of the smaller ones increases, consistent with the decrease in the number of tropical cyclones in the future climate. Average liquid water path (LWP) and IWP associated with each tropical cyclone are diagnosed, and it is found that both the associated LWP and IWP increase under the warmer condition. Even though, since the number of the intensive cloud systems decrease, the average IWP decreases. It should be remarked that the change in TC tracks largely contribute to the change in the horizontal distribution of clouds. The NICAM simulations also show that the storm-tracks shift poleward, and the storms become less frequent and stronger in the extra-tropics, similar to the results of other general circulation models. Both LWP and IWP associated with the storms also increase in the warmer climate in the NICAM simulations. This results in increase in the upper clouds under the warmer climate condition, as described by Miura et al. (2005). References: Hashino, T., Satoh, M., Hagihara, Y., Kubota, T., Matsui, T., Nasuno, T., and Okamoto, H. (2012), Evaluating Global Cloud Distribution and Microphysics from the NICAM against CloudSat and CALIPSO, J. Geophys. Res., submitted. Miura, H., Tomita,H., Nasuno,T., Iga, S., Satoh,M., and Matsuno, T. (2005), A climate sensitivity test using a global cloud resolving model under an aqua planet condition, Geophys. Res. Lett., 32, L19717, doi:10.1029/2005GL023672.

Global and Regional Modeling of Long-Range Transport and Intercontinental Source-Receptor Linkages

EPA Science Inventory

In this study, we compare air quality over North America simulated by the C-IFS global model and the CMAQ regional model driven by boundary conditions from C-IFS against surface and upper air observations. Results indicate substantial differences in model performance for surface ...

Space-based Doppler lidar sampling strategies: Algorithm development and simulated observation experiments

NASA Technical Reports Server (NTRS)

Emmitt, G. D.; Wood, S. A.; Morris, M.

1990-01-01

Lidar Atmospheric Wind Sounder (LAWS) Simulation Models (LSM) were developed to evaluate the potential impact of global wind observations on the basic understanding of the Earth's atmosphere and on the predictive skills of current forecast models (GCM and regional scale). Fully integrated top to bottom LAWS Simulation Models for global and regional scale simulations were developed. The algorithm development incorporated the effects of aerosols, water vapor, clouds, terrain, and atmospheric turbulence into the models. Other additions include a new satellite orbiter, signal processor, line of sight uncertainty model, new Multi-Paired Algorithm and wind error analysis code. An atmospheric wind field library containing control fields, meteorological fields, phenomena fields, and new European Center for Medium Range Weather Forecasting (ECMWF) data was also added. The LSM was used to address some key LAWS issues and trades such as accuracy and interpretation of LAWS information, data density, signal strength, cloud obscuration, and temporal data resolution.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

Intraseasonal Variability of the Indian Monsoon as Simulated by a Global Model

NASA Astrophysics Data System (ADS)

Joshi, Sneh; Kar, S. C.

2018-01-01

This study uses the global forecast system (GFS) model at T126 horizontal resolution to carry out seasonal simulations with prescribed sea-surface temperatures. Main objectives of the study are to evaluate the simulated Indian monsoon variability in intraseasonal timescales. The GFS model has been integrated for 29 monsoon seasons with 15 member ensembles forced with observed sea-surface temperatures (SSTs) and additional 16-member ensemble runs have been carried out using climatological SSTs. Northward propagation of intraseasonal rainfall anomalies over the Indian region from the model simulations has been examined. It is found that the model is unable to simulate the observed moisture pattern when the active zone of convection is over central India. However, the model simulates the observed pattern of specific humidity during the life cycle of northward propagation on day - 10 and day + 10 of maximum convection over central India. The space-time spectral analysis of the simulated equatorial waves shows that the ensemble members have varying amount of power in each band of wavenumbers and frequencies. However, variations among ensemble members are more in the antisymmetric component of westward moving waves and maximum difference in power is seen in the 8-20 day mode among ensemble members.

The critical role of the routing scheme in simulating peak river discharge in global hydrological models

NASA Astrophysics Data System (ADS)

Zhao, F.; Veldkamp, T.; Frieler, K.; Schewe, J.; Ostberg, S.; Willner, S. N.; Schauberger, B.; Gosling, S.; Mueller Schmied, H.; Portmann, F. T.; Leng, G.; Huang, M.; Liu, X.; Tang, Q.; Hanasaki, N.; Biemans, H.; Gerten, D.; Satoh, Y.; Pokhrel, Y. N.; Stacke, T.; Ciais, P.; Chang, J.; Ducharne, A.; Guimberteau, M.; Wada, Y.; Kim, H.; Yamazaki, D.

2017-12-01

Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge—which is crucial in flood simulations—has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971-2010) within the ISIMIP2a project. The runoff simulations were used as input for the global river routing model CaMa-Flood. The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about 2/3 of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.

Global dynamic modeling of a transmission system

NASA Technical Reports Server (NTRS)

Choy, F. K.; Qian, W.

1993-01-01

The work performed on global dynamic simulation and noise correlation of gear transmission systems at the University of Akron is outlined. The objective is to develop a comprehensive procedure to simulate the dynamics of the gear transmission system coupled with the effects of gear box vibrations. The developed numerical model is benchmarked with results from experimental tests at NASA Lewis Research Center. The modal synthesis approach is used to develop the global transient vibration analysis procedure used in the model. Modal dynamic characteristics of the rotor-gear-bearing system are calculated by the matrix transfer method while those of the gear box are evaluated by the finite element method (NASTRAN). A three-dimensional, axial-lateral coupled bearing model is used to couple the rotor vibrations with the gear box motion. The vibrations between the individual rotor systems are coupled through the nonlinear gear mesh interactions. The global equations of motion are solved in modal coordinates and the transient vibration of the system is evaluated by a variable time-stepping integration scheme. The relationship between housing vibration and resulting noise of the gear transmission system is generated by linear transfer functions using experimental data. A nonlinear relationship of the noise components to the fundamental mesh frequency is developed using the hypercoherence function. The numerically simulated vibrations and predicted noise of the gear transmission system are compared with the experimental results from the gear noise test rig at NASA Lewis Research Center. Results of the comparison indicate that the global dynamic model developed can accurately simulate the dynamics of a gear transmission system.

Contribution of energy values to the analysis of global searching molecular dynamics simulations of transmembrane helical bundles.

PubMed Central

Torres, Jaume; Briggs, John A G; Arkin, Isaiah T

2002-01-01

Molecular interactions between transmembrane alpha-helices can be explored using global searching molecular dynamics simulations (GSMDS), a method that produces a group of probable low energy structures. We have shown previously that the correct model in various homooligomers is always located at the bottom of one of various possible energy basins. Unfortunately, the correct model is not necessarily the one with the lowest energy according to the computational protocol, which has resulted in overlooking of this parameter in favor of experimental data. In an attempt to use energetic considerations in the aforementioned analysis, we used global searching molecular dynamics simulations on three homooligomers of different sizes, the structures of which are known. As expected, our results show that even when the conformational space searched includes the correct structure, taking together simulations using both left and right handedness, the correct model does not necessarily have the lowest energy. However, for the models derived from the simulation that uses the correct handedness, the lowest energy model is always at, or very close to, the correct orientation. We hypothesize that this should also be true when simulations are performed using homologous sequences, and consequently lowest energy models with the right handedness should produce a cluster around a certain orientation. In contrast, using the wrong handedness the lowest energy structures for each sequence should appear at many different orientations. The rationale behind this is that, although more than one energy basin may exist, basins that do not contain the correct model will shift or disappear because they will be destabilized by at least one conservative (i.e. silent) mutation, whereas the basin containing the correct model will remain. This not only allows one to point to the possible handedness of the bundle, but can be used to overcome ambiguities arising from the use of homologous sequences in the analysis of global searching molecular dynamics simulations. In addition, because clustering of lowest energy models arising from homologous sequences only happens when the estimation of the helix tilt is correct, it may provide a validation for the helix tilt estimate. PMID:12023229

Mapping the spatial distribution of Aedes aegypti and Aedes albopictus.

PubMed

Ding, Fangyu; Fu, Jingying; Jiang, Dong; Hao, Mengmeng; Lin, Gang

2018-02-01

Mosquito-borne infectious diseases, such as Rift Valley fever, Dengue, Chikungunya and Zika, have caused mass human death with the transnational expansion fueled by economic globalization. Simulating the distribution of the disease vectors is of great importance in formulating public health planning and disease control strategies. In the present study, we simulated the global distribution of Aedes aegypti and Aedes albopictus at a 5×5km spatial resolution with high-dimensional multidisciplinary datasets and machine learning methods Three relatively popular and robust machine learning models, including support vector machine (SVM), gradient boosting machine (GBM) and random forest (RF), were used. During the fine-tuning process based on training datasets of A. aegypti and A. albopictus, RF models achieved the highest performance with an area under the curve (AUC) of 0.973 and 0.974, respectively, followed by GBM (AUC of 0.971 and 0.972, respectively) and SVM (AUC of 0.963 and 0.964, respectively) models. The simulation difference between RF and GBM models was not statistically significant (p>0.05) based on the validation datasets, whereas statistically significant differences (p<0.05) were observed for RF and GBM simulations compared with SVM simulations. From the simulated maps derived from RF models, we observed that the distribution of A. albopictus was wider than that of A. aegypti along a latitudinal gradient. The discriminatory power of each factor in simulating the global distribution of the two species was also analyzed. Our results provided fundamental information for further study on disease transmission simulation and risk assessment. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of Diagnostic CO2 Flux and Transport Modeling in NU-WRF and GEOS-5

NASA Astrophysics Data System (ADS)

Kawa, S. R.; Collatz, G. J.; Tao, Z.; Wang, J. S.; Ott, L. E.; Liu, Y.; Andrews, A. E.; Sweeney, C.

2015-12-01

We report on recent diagnostic (constrained by observations) model simulations of atmospheric CO2 flux and transport using a newly developed facility in the NASA Unified-Weather Research and Forecast (NU-WRF) model. The results are compared to CO2 data (ground-based, airborne, and GOSAT) and to corresponding simulations from a global model that uses meteorology from the NASA GEOS-5 Modern Era Retrospective analysis for Research and Applications (MERRA). The objective of these intercomparisons is to assess the relative strengths and weaknesses of the respective models in pursuit of an overall carbon process improvement at both regional and global scales. Our guiding hypothesis is that the finer resolution and improved land surface representation in NU-WRF will lead to better comparisons with CO2 data than those using global MERRA, which will, in turn, inform process model development in global prognostic models. Initial intercomparison results, however, have generally been mixed: NU-WRF is better at some sites and times but not uniformly. We are examining the model transport processes in detail to diagnose differences in the CO2 behavior. These comparisons are done in the context of a long history of simulations from the Parameterized Chemistry and Transport Model, based on GEOS-5 meteorology and Carnegie Ames-Stanford Approach-Global Fire Emissions Database (CASA-GFED) fluxes, that capture much of the CO2 variation from synoptic to seasonal to global scales. We have run the NU-WRF model using unconstrained, internally generated meteorology within the North American domain, and with meteorological 'nudging' from Global Forecast System and North American Regional Reanalysis (NARR) in an effort to optimize the CO2 simulations. Output results constrained by NARR show the best comparisons to data. Discrepancies, of course, may arise either from flux or transport errors and compensating errors are possible. Resolving their interplay is also important to using the data in inverse models. Recent analysis is focused on planetary boundary depth, which can be significantly different between MERRA and NU-WRF, along with subgrid transport differences. Characterization of transport differences between the models will allow us to better constrain the CO2 fluxes, which is the major objective of this work.

The importance of vertical resolution in the free troposphere for modeling intercontinental plumes

NASA Astrophysics Data System (ADS)

Zhuang, Jiawei; Jacob, Daniel J.; Eastham, Sebastian D.

2018-05-01

Chemical plumes in the free troposphere can preserve their identity for more than a week as they are transported on intercontinental scales. Current global models cannot reproduce this transport. The plumes dilute far too rapidly due to numerical diffusion in sheared flow. We show how model accuracy can be limited by either horizontal resolution (Δx) or vertical resolution (Δz). Balancing horizontal and vertical numerical diffusion, and weighing computational cost, implies an optimal grid resolution ratio (Δx / Δz)opt ˜ 1000 for simulating the plumes. This is considerably higher than current global models (Δx / Δz ˜ 20) and explains the rapid plume dilution in the models as caused by insufficient vertical resolution. Plume simulations with the Geophysical Fluid Dynamics Laboratory Finite-Volume Cubed-Sphere Dynamical Core (GFDL-FV3) over a range of horizontal and vertical grid resolutions confirm this limiting behavior. Our highest-resolution simulation (Δx ≈ 25 km, Δz ≈ 80 m) preserves the maximum mixing ratio in the plume to within 35 % after 8 days in strongly sheared flow, a drastic improvement over current models. Adding free tropospheric vertical levels in global models is computationally inexpensive and would also improve the simulation of water vapor.

Dynamics of global vegetation biomass simulated by the integrated Earth System Model

NASA Astrophysics Data System (ADS)

Mao, J.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.; Piao, S.; Yang, X.; Truesdale, J. E.; Bond-Lamberty, B. P.; Chini, L. P.; Thomson, A. M.; Hurtt, G. C.; Collins, W.; Edmonds, J.

2014-12-01

The global vegetation biomass stores huge amounts of carbon and is thus important to the global carbon budget (Pan et al., 2010). For the past few decades, different observation-based estimates and modeling of biomass in the above- and below-ground vegetation compartments have been comprehensively conducted (Saatchi et al., 2011; Baccini et al., 2012). However, uncertainties still exist, in particular for the simulation of biomass magnitude, tendency, and the response of biomass to climatic conditions and natural and human disturbances. The recently successful coupling of the integrated Earth System Model (iESM) (Di Vittorio et al., 2014; Bond-Lamberty et al., 2014), which links the Global Change Assessment Model (GCAM), Global Land-use Model (GLM), and Community Earth System Model (CESM), offers a great opportunity to understand the biomass-related dynamics in a fully-coupled natural and human modeling system. In this study, we focus on the systematic analysis and evaluation of the iESM simulated historical (1850-2005) and future (2006-2100) biomass changes and the response of the biomass dynamics to various impact factors, in particular the human-induced Land Use/Land Cover Change (LULCC). By analyzing the iESM simulations with and without the interactive LULCC feedbacks, we further study how and where the climate feedbacks affect socioeconomic decisions and LULCC, such as to alter vegetation carbon storage. References Pan Y et. al: A large and persistent carbon sink in the World's forests. Science 2011, 333:988-993. Saatchi SS et al: Benchmark map of forest carbon stocks in tropical regions across three continents. Proc Natl Acad Sci 2011, 108:9899-9904. Baccini A et al: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Clim Change 2012, 2:182-185. Di Vittorio AV et al: From land use to land cover: restoring the afforestation signal in a coupled integrated assessment-earth system model and the implications for CMIP5 RCP simulations. Biogeosciences Discuss 2014, 11:7151-7188. Bond-Lamberty, B et al: Coupling earth system and integrated assessment models: The problem of steady state. Geosci. Model Dev. Discuss 2014, 7: 1499-1524, doi:10.5194/gmdd-7-1499-2014.

Southwestern Pine Forests Likely to Disappear

ScienceCinema

McDowell, Nathan

2018-01-16

A new study, led by Los Alamos National Laboratory's Nathan McDowell, suggests that widespread loss of a major forest type, the pine-juniper woodlands of the Southwestern U.S., could be wiped out by the end of this century due to climate change, and that conifers throughout much of the Northern Hemisphere may be on a similar trajectory. New results, reported in the journal Nature Climate Change, suggest that global models may underestimate predictions of forest death. McDowell and his large international team strove to provide the missing pieces of understanding tree death at three levels: plant, regional and global. The team rigorously developed and evaluated multiple process-based and empirical models against experimental results, and then compared these models to results from global vegetation models to examine independent simulations. They discovered that the global models simulated mortality throughout the Northern Hemisphere that was of similar magnitude, but much broader spatial scale, as the evaluated ecosystem models predicted for in the Southwest.

Southwestern Pine Forests Likely to Disappear

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

McDowell, Nathan

A new study, led by Los Alamos National Laboratory's Nathan McDowell, suggests that widespread loss of a major forest type, the pine-juniper woodlands of the Southwestern U.S., could be wiped out by the end of this century due to climate change, and that conifers throughout much of the Northern Hemisphere may be on a similar trajectory. New results, reported in the journal Nature Climate Change, suggest that global models may underestimate predictions of forest death. McDowell and his large international team strove to provide the missing pieces of understanding tree death at three levels: plant, regional and global. The teammore » rigorously developed and evaluated multiple process-based and empirical models against experimental results, and then compared these models to results from global vegetation models to examine independent simulations. They discovered that the global models simulated mortality throughout the Northern Hemisphere that was of similar magnitude, but much broader spatial scale, as the evaluated ecosystem models predicted for in the Southwest.« less

Performance and Evaluation of the Global Modeling and Assimilation Office Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, Nikki; Errico, R. M.; Carvalho, D.

2018-01-01

The National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) has spent more than a decade developing and implementing a global Observing System Simulation Experiment framework for use in evaluting both new observation types as well as the behavior of data assimilation systems. The NASA/GMAO OSSE has constantly evolved to relect changes in the Gridpoint Statistical Interpolation data assimiation system, the Global Earth Observing System model, version 5 (GEOS-5), and the real world observational network. Software and observational datasets for the GMAO OSSE are publicly available, along with a technical report. Substantial modifications have recently been made to the NASA/GMAO OSSE framework, including the character of synthetic observation errors, new instrument types, and more sophisticated atmospheric wind vectors. These improvements will be described, along with the overall performance of the current OSSE. Lessons learned from investigations into correlated errors and model error will be discussed.

Research Review, 1983

NASA Technical Reports Server (NTRS)

1984-01-01

The Global Modeling and Simulation Branch (GMSB) of the Laboratory for Atmospheric Sciences (GLAS) is engaged in general circulation modeling studies related to global atmospheric and oceanographic research. The research activities discussed are organized into two disciplines: Global Weather/Observing Systems and Climate/Ocean-Air Interactions. The Global Weather activities are grouped in four areas: (1) Analysis and Forecast Studies, (2) Satellite Observing Systems, (3) Analysis and Model Development, (4) Atmospheric Dynamics and Diagnostic Studies. The GLAS Analysis/Forecast/Retrieval System was applied to both FGGE and post FGGE periods. The resulting analyses have already been used in a large number of theoretical studies of atmospheric dynamics, forecast impact studies and development of new or improved algorithms for the utilization of satellite data. Ocean studies have focused on the analysis of long-term global sea surface temperature data, for use in the study of the response of the atmosphere to sea surface temperature anomalies. Climate research has concentrated on the simulation of global cloudiness, and on the sensitivities of the climate to sea surface temperature and ground wetness anomalies.

Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model

USDA-ARS?s Scientific Manuscript database

Studies of global hydrologic cycles, carbon cycles and climate change are greatly facilitated when global estimates of evapotranspiration (E) are available. We have developed an air-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balance, and e...

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE PAGES

Xi, Maolong; Lu, Dan; Gui, Dongwei; ...

2016-11-27

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

NASA Astrophysics Data System (ADS)

Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan

2017-01-01

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

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

Xi, Maolong; Lu, Dan; Gui, Dongwei

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5

NASA Astrophysics Data System (ADS)

Zhao, Wenjie; Peng, Yiran; Wang, Bin; Yi, Bingqi; Lin, Yanluan; Li, Jiangnan

2018-05-01

A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.

High resolution global flood hazard map from physically-based hydrologic and hydraulic models.

NASA Astrophysics Data System (ADS)

Begnudelli, L.; Kaheil, Y.; McCollum, J.

2017-12-01

The global flood map published online at http://www.fmglobal.com/research-and-resources/global-flood-map at 90m resolution is being used worldwide to understand flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs. The modeling system is based on a physically-based hydrologic model to simulate river discharges, and 2D shallow-water hydrodynamic model to simulate inundation. The model can be applied to large-scale flood hazard mapping thanks to several solutions that maximize its efficiency and the use of parallel computing. The hydrologic component of the modeling system is the Hillslope River Routing (HRR) hydrologic model. HRR simulates hydrological processes using a Green-Ampt parameterization, and is calibrated against observed discharge data from several publicly-available datasets. For inundation mapping, we use a 2D Finite-Volume Shallow-Water model with wetting/drying. We introduce here a grid Up-Scaling Technique (UST) for hydraulic modeling to perform simulations at higher resolution at global scale with relatively short computational times. A 30m SRTM is now available worldwide along with higher accuracy and/or resolution local Digital Elevation Models (DEMs) in many countries and regions. UST consists of aggregating computational cells, thus forming a coarser grid, while retaining the topographic information from the original full-resolution mesh. The full-resolution topography is used for building relationships between volume and free surface elevation inside cells and computing inter-cell fluxes. This approach almost achieves computational speed typical of the coarse grids while preserving, to a significant extent, the accuracy offered by the much higher resolution available DEM. The simulations are carried out along each river of the network by forcing the hydraulic model with the streamflow hydrographs generated by HRR. Hydrographs are scaled so that the peak corresponds to the return period corresponding to the hazard map being produced (e.g. 100 years, 500 years). Each numerical simulation models one river reach, except for the longest reaches which are split in smaller parts. Here we show results for selected river basins worldwide.

Impacts of Canadian and global black carbon shipping emissions on Arctic climate

NASA Astrophysics Data System (ADS)

Shrestha, R.; von Salzen, K.

2017-12-01

Shipping activities have increased across the Arctic and are projected to continue to increase in the future. In this study we compare the climate impacts of Canadian and global shipping black carbon (BC) emissions on the Arctic using the Canadian Center for Climate Modelling and Analysis Earth System Model (CanESM4.1). The model simulations are performed with and without shipping emissions at T63 (128 x 64) spectral resolution. Results indicate that shipping activities enhance BC concentrations across the area close to the shipping emissions, which causes increased absorption of solar radiation (direct effect). An impact of shipping on temperatures is simulated across the entire Arctic, with maximum warming in fall and winter seasons. Although global mean temperature changes are very similar between the two simulations, increase in Canadian BC shipping emissions cause warmer Arctic land surface temperature in summer due to the direct radiative effects of aerosol.

Challenges and needs in fire management: A landscape simulation modeling perspective [chapter 4

Treesearch

Robert E. Keane; Geoffrey J. Cary; Mike D. Flannigan

2011-01-01

Fire management will face many challenges in the future from global climate change to protecting people, communities, and values at risk. Simulation modeling will be a vital tool for addressing these challenges but the next generation of simulation models must be spatially explicit to address critical landscape ecology relationships and they must use mechanistic...

Global hydrodynamic modelling of flood inundation in continental rivers: How can we achieve it?

NASA Astrophysics Data System (ADS)

Yamazaki, D.

2016-12-01

Global-scale modelling of river hydrodynamics is essential for understanding global hydrological cycle, and is also required in interdisciplinary research fields . Global river models have been developed continuously for more than two decades, but modelling river flow at a global scale is still a challenging topic because surface water movement in continental rivers is a multi-spatial-scale phenomena. We have to consider the basin-wide water balance (>1000km scale), while hydrodynamics in river channels and floodplains is regulated by much smaller-scale topography (<100m scale). For example, heavy precipitation in upstream regions may later cause flooding in farthest downstream reaches. In order to realistically simulate the timing and amplitude of flood wave propagation for a long distance, consideration of detailed local topography is unavoidable. I have developed the global hydrodynamic model CaMa-Flood to overcome this scale-discrepancy of continental river flow. The CaMa-Flood divides river basins into multiple "unit-catchments", and assumes the water level is uniform within each unit-catchment. One unit-catchment is assigned to each grid-box defined at the typical spatial resolution of global climate models (10 100 km scale). Adopting a uniform water level in a >10km river segment seems to be a big assumption, but it is actually a good approximation for hydrodynamic modelling of continental rivers. The number of grid points required for global hydrodynamic simulations is largely reduced by this "unit-catchment assumption". Alternative to calculating 2-dimensional floodplain flows as in regional flood models, the CaMa-Flood treats floodplain inundation in a unit-catchment as a sub-grid physics. The water level and inundated area in each unit-catchment are diagnosed from water volume using topography parameters derived from high-resolution digital elevation models. Thus, the CaMa-Flood is at least 1000 times computationally more efficient compared to regional flood inundation models while the reality of simulated flood dynamics is kept. I will explain in detail how the CaMa-Flood model has been constructed from high-resolution topography datasets, and how the model can be used for various interdisciplinary applications.

On the influence of simulated SST warming on rainfall projections in the Indo-Pacific domain: an AGCM study

NASA Astrophysics Data System (ADS)

Zhang, Huqiang; Zhao, Y.; Moise, A.; Ye, H.; Colman, R.; Roff, G.; Zhao, M.

2018-02-01

Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20-25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying SST forcing.

Octree-based Global Earthquake Simulations

NASA Astrophysics Data System (ADS)

Ramirez-Guzman, L.; Juarez, A.; Bielak, J.; Salazar Monroy, E. F.

2017-12-01

Seismological research has motivated recent efforts to construct more accurate three-dimensional (3D) velocity models of the Earth, perform global simulations of wave propagation to validate models, and also to study the interaction of seismic fields with 3D structures. However, traditional methods for seismogram computation at global scales are limited by computational resources, relying primarily on traditional methods such as normal mode summation or two-dimensional numerical methods. We present an octree-based mesh finite element implementation to perform global earthquake simulations with 3D models using topography and bathymetry with a staircase approximation, as modeled by the Carnegie Mellon Finite Element Toolchain Hercules (Tu et al., 2006). To verify the implementation, we compared the synthetic seismograms computed in a spherical earth against waveforms calculated using normal mode summation for the Preliminary Earth Model (PREM) for a point source representation of the 2014 Mw 7.3 Papanoa, Mexico earthquake. We considered a 3 km-thick ocean layer for stations with predominantly oceanic paths. Eigen frequencies and eigen functions were computed for toroidal, radial, and spherical oscillations in the first 20 branches. Simulations are valid at frequencies up to 0.05 Hz. Matching among the waveforms computed by both approaches, especially for long period surface waves, is excellent. Additionally, we modeled the Mw 9.0 Tohoku-Oki earthquake using the USGS finite fault inversion. Topography and bathymetry from ETOPO1 are included in a mesh with more than 3 billion elements; constrained by the computational resources available. We compared estimated velocity and GPS synthetics against observations at regional and teleseismic stations of the Global Seismological Network and discuss the differences among observations and synthetics, revealing that heterogeneity, particularly in the crust, needs to be considered.

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

DOE PAGES

Kim, John B.; Monier, Erwan; Sohngen, Brent; ...

2017-03-28

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomesmore » of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO 2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Finally, our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO 2 fertilization effects may considerably reduce the range of projections.« less

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

NASA Astrophysics Data System (ADS)

Kim, John B.; Monier, Erwan; Sohngen, Brent; Pitts, G. Stephen; Drapek, Ray; McFarland, James; Ohrel, Sara; Cole, Jefferson

2017-04-01

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomes of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO2 fertilization effects may considerably reduce the range of projections.

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

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

Kim, John B.; Monier, Erwan; Sohngen, Brent

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomesmore » of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO 2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Finally, our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO 2 fertilization effects may considerably reduce the range of projections.« less

Simulated effects of nitrogen saturation on the global carbon budget using the IBIS model

PubMed Central

Lu, Xuehe; Jiang, Hong; Liu, Jinxun; Zhang, Xiuying; Jin, Jiaxin; Zhu, Qiuan; Zhang, Zhen; Peng, Changhui

2016-01-01

Over the past 100 years, human activity has greatly changed the rate of atmospheric N (nitrogen) deposition in terrestrial ecosystems, resulting in N saturation in some regions of the world. The contribution of N saturation to the global carbon budget remains uncertain due to the complicated nature of C-N (carbon-nitrogen) interactions and diverse geography. Although N deposition is included in most terrestrial ecosystem models, the effect of N saturation is frequently overlooked. In this study, the IBIS (Integrated BIosphere Simulator) was used to simulate the global-scale effects of N saturation during the period 1961–2009. The results of this model indicate that N saturation reduced global NPP (Net Primary Productivity) and NEP (Net Ecosystem Productivity) by 0.26 and 0.03 Pg C yr−1, respectively. The negative effects of N saturation on carbon sequestration occurred primarily in temperate forests and grasslands. In response to elevated CO2 levels, global N turnover slowed due to increased biomass growth, resulting in a decline in soil mineral N. These changes in N cycling reduced the impact of N saturation on the global carbon budget. However, elevated N deposition in certain regions may further alter N saturation and C-N coupling. PMID:27966643

Evaluation of Boreal Summer Monsoon Intraseasonal Variability in the GASS-YOTC Multi-Model Physical Processes Experiment

NASA Astrophysics Data System (ADS)

Mani, N. J.; Waliser, D. E.; Jiang, X.

2014-12-01

While the boreal summer monsoon intraseasonal variability (BSISV) exerts profound influence on the south Asian monsoon, the capability of present day dynamical models in simulating and predicting the BSISV is still limited. The global model evaluation project on vertical structure and diabatic processes of the Madden Julian Oscillations (MJO) is a joint venture, coordinated by the Working Group on Numerical Experimentation (WGNE) MJO Task Force and GEWEX Atmospheric System Study (GASS) program, for assessing the model deficiencies in simulating the ISV and for improving our understanding of the underlying processes. In this study the simulation of the northward propagating BSISV is investigated in 26 climate models with special focus on the vertical diabatic heating structure and clouds. Following parallel lines of inquiry as the MJO Task Force has done with the eastward propagating MJO, we utilize previously proposed and newly developed model performance metrics and process diagnostics and apply them to the global climate model simulations of BSISV.

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

NASA Technical Reports Server (NTRS)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.;

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

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

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climatemore » change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.« less

Response of the North Pacific Oscillation to global warming in the models of the Intergovernmental Panel on Climate Change Fourth Assessment Report

NASA Astrophysics Data System (ADS)

Chen, Zheng; Gan, Bolan; Wu, Lixin

2017-09-01

Based on 22 of the climate models from phase 3 of the Coupled Model Intercomparison Project, we investigate the ability of the models to reproduce the spatiotemporal features of the wintertime North Pacific Oscillation (NPO), which is the second most important factor determining the wintertime sea level pressure field in simulations of the pre-industrial control climate, and evaluate the NPO response to the future most reasonable global warming scenario (the A1B scenario). We reveal that while most models simulate the geographic distribution and amplitude of the NPO pattern satisfactorily, only 13 models capture both features well. However, the temporal variability of the simulated NPO could not be significantly correlated with the observations. Further analysis indicates the weakened NPO intensity for a scenario of strong global warming is attributable to the reduced lower-tropospheric baroclinicity at mid-latitudes, which is anticipated to disrupt large-scale and low-frequency atmospheric variability, resulting in the diminished transfer of energy to the NPO, together with its northward shift.

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC.

PubMed

Mukhtar, Hussnain; Lin, Yu-Pin; Shipin, Oleg V; Petway, Joy R

2017-07-12

This study presents an approach for obtaining realization sets of parameters for nitrogen removal in a pilot-scale waste stabilization pond (WSP) system. The proposed approach was designed for optimal parameterization, local sensitivity analysis, and global uncertainty analysis of a dynamic simulation model for the WSP by using the R software package Flexible Modeling Environment (R-FME) with the Markov chain Monte Carlo (MCMC) method. Additionally, generalized likelihood uncertainty estimation (GLUE) was integrated into the FME to evaluate the major parameters that affect the simulation outputs in the study WSP. Comprehensive modeling analysis was used to simulate and assess nine parameters and concentrations of ON-N, NH₃-N and NO₃-N. Results indicate that the integrated FME-GLUE-based model, with good Nash-Sutcliffe coefficients (0.53-0.69) and correlation coefficients (0.76-0.83), successfully simulates the concentrations of ON-N, NH₃-N and NO₃-N. Moreover, the Arrhenius constant was the only parameter sensitive to model performances of ON-N and NH₃-N simulations. However, Nitrosomonas growth rate, the denitrification constant, and the maximum growth rate at 20 °C were sensitive to ON-N and NO₃-N simulation, which was measured using global sensitivity.

Spread in the magnitude of climate model interdecadal global temperature variability traced to disagreements over high-latitude oceans

NASA Astrophysics Data System (ADS)

Brown, Patrick T.; Li, Wenhong; Jiang, Jonathan H.; Su, Hui

2016-12-01

Unforced variability in global mean surface air temperature can obscure or exaggerate global warming on interdecadal time scales; thus, understanding both the magnitude and generating mechanisms of such variability is of critical importance for both attribution studies as well as decadal climate prediction. Coupled atmosphere-ocean general circulation models (climate models) simulate a wide range of magnitudes of unforced interdecadal variability in global mean surface air temperature (UITglobal), hampering efforts to quantify the influence of UITglobal on contemporary global temperature trends. Recently, a preliminary consensus has emerged that unforced interdecadal variability in local surface temperatures (UITlocal) over the tropical Pacific Ocean is particularly influential on UITglobal. Therefore, a reasonable hypothesis might be that the large spread in the magnitude of UITglobal across climate models can be explained by the spread in the magnitude of simulated tropical Pacific UITlocal. Here we show that this hypothesis is mostly false. Instead, the spread in the magnitude of UITglobal is linked much more strongly to the spread in the magnitude of UITlocal over high-latitude regions characterized by significant variability in oceanic convection, sea ice concentration, and energy flux at both the surface and the top of the atmosphere. Thus, efforts to constrain the climate model produced range of UITglobal magnitude would be best served by focusing on the simulation of air-sea interaction at high latitudes.

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Global variability of cloud condensation nuclei concentrations

NASA Astrophysics Data System (ADS)

Makkonen, Risto; Krüger, Olaf

2017-04-01

Atmospheric aerosols can influence cloud optical and dynamical processes by acting as cloud condensation nuclei (CCN). Globally, these indirect aerosol effects are significant to the radiative budget as well as a source of high uncertainty in anthropogenic radiative forcing. While historically many global climate models have fixed CCN concentrations to a certain level, most state-of-the-art models calculate aerosol-cloud interactions with sophisticated methodologies based on interactively simulated aerosol size distributions. However, due to scarcity of atmospheric observations simulated global CCN concentrations remain poorly constrained. Here we assess global CCN variability with a climate model, and attribute potential trends during 2000-2010 to changes in emissions and meteorological fields. Here we have used ECHAM5.5-HAM2 with model M7 microphysical aerosol model. The model has been upgraded with a secondary organic aerosol (SOA) scheme including ELVOCs. Dust and sea salt emissions are calculated online, based on wind speed and hydrology. Each experiment is 11 years, analysed after a 6-month spin-up period. The MODIS CCN product (Terra platform) is used to evaluate model performance throughout 2000-2010. While optical remote observation of CCN column includes several deficiencies, the products serves as a proxy for changes during the simulation period. In our analysis we utilize the observed and simulated vertical column integrated CCN concentration, and limit our analysis only over marine regions. Simulated annual CCN column densities reach 2ṡ108 cm-2 near strong source regions in central Africa, Arabian Sea, Bay of Bengal and China sea. The spatial concentration gradient in CCN(0.2%) is steep, and column densities drop to <50% a few hundred kilometers away from the coasts. While the spatial distribution of CCN at 0.2% supersaturation is closer to that of MODIS proxy, as opposed to 1.0% supersaturation, the overall column integrated CCN are too low. Still, we can compare the relative response of CCN to emission and meteorological variability. Most evident pattern of high temporal correlation is found over North Atlantic ocean, extending throughout Europe and up to Gulf of Mexico. All of these regions show a generally decreasing trend throughout the decade in control simulations and MODIS CCN, and the simulations including the emission trends clearly improve the simulations with climatological emissions. In regions where the observed intra-annual cycle correlates well with sea-spray emissions, the long-term annual correlation usually remains poor. This could indicate that the model is unable to capture the natural variability in marine aerosol emissions.

Xanthos – A Global Hydrologic Model

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

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM). Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resourcesmore » in the form of total runoff.« less

Xanthos – A Global Hydrologic Model

DOE PAGES

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

2017-09-11

Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM). Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resourcesmore » in the form of total runoff.« less

A Simple Model of Global Aerosol Indirect Effects

NASA Technical Reports Server (NTRS)

Ghan, Steven J.; Smith, Steven J.; Wang, Minghuai; Zhang, Kai; Pringle, Kirsty; Carslaw, Kenneth; Pierce, Jeffrey; Bauer, Susanne; Adams, Peter

2013-01-01

Most estimates of the global mean indirect effect of anthropogenic aerosol on the Earth's energy balance are from simulations by global models of the aerosol lifecycle coupled with global models of clouds and the hydrologic cycle. Extremely simple models have been developed for integrated assessment models, but lack the flexibility to distinguish between primary and secondary sources of aerosol. Here a simple but more physically based model expresses the aerosol indirect effect (AIE) using analytic representations of cloud and aerosol distributions and processes. Although the simple model is able to produce estimates of AIEs that are comparable to those from some global aerosol models using the same global mean aerosol properties, the estimates by the simple model are sensitive to preindustrial cloud condensation nuclei concentration, preindustrial accumulation mode radius, width of the accumulation mode, size of primary particles, cloud thickness, primary and secondary anthropogenic emissions, the fraction of the secondary anthropogenic emissions that accumulates on the coarse mode, the fraction of the secondary mass that forms new particles, and the sensitivity of liquid water path to droplet number concentration. Estimates of present-day AIEs as low as 5 W/sq m and as high as 0.3 W/sq m are obtained for plausible sets of parameter values. Estimates are surprisingly linear in emissions. The estimates depend on parameter values in ways that are consistent with results from detailed global aerosol-climate simulation models, which adds to understanding of the dependence on AIE uncertainty on uncertainty in parameter values.

Comparison of predictive estimates of high-latitude electrodynamics with observations of global-scale Birkeland currents

NASA Astrophysics Data System (ADS)

Anderson, Brian J.; Korth, Haje; Welling, Daniel T.; Merkin, Viacheslav G.; Wiltberger, Michael J.; Raeder, Joachim; Barnes, Robin J.; Waters, Colin L.; Pulkkinen, Antti A.; Rastaetter, Lutz

2017-02-01

Two of the geomagnetic storms for the Space Weather Prediction Center Geospace Environment Modeling challenge occurred after data were first acquired by the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). We compare Birkeland currents from AMPERE with predictions from four models for the 4-5 April 2010 and 5-6 August 2011 storms. The four models are the Weimer (2005b) field-aligned current statistical model, the Lyon-Fedder-Mobarry magnetohydrodynamic (MHD) simulation, the Open Global Geospace Circulation Model MHD simulation, and the Space Weather Modeling Framework MHD simulation. The MHD simulations were run as described in Pulkkinen et al. (2013) and the results obtained from the Community Coordinated Modeling Center. The total radial Birkeland current, ITotal, and the distribution of radial current density, Jr, for all models are compared with AMPERE results. While the total currents are well correlated, the quantitative agreement varies considerably. The Jr distributions reveal discrepancies between the models and observations related to the latitude distribution, morphologies, and lack of nightside current systems in the models. The results motivate enhancing the simulations first by increasing the simulation resolution and then by examining the relative merits of implementing more sophisticated ionospheric conductance models, including ionospheric outflows or other omitted physical processes. Some aspects of the system, including substorm timing and location, may remain challenging to simulate, implying a continuing need for real-time specification.

Test of High-resolution Global and Regional Climate Model Projections

NASA Astrophysics Data System (ADS)

Stenchikov, Georgiy; Nikulin, Grigory; Hansson, Ulf; Kjellström, Erik; Raj, Jerry; Bangalath, Hamza; Osipov, Sergey

2014-05-01

In scope of CORDEX project we have simulated the past (1975-2005) and future (2006-2050) climates using the GFDL global high-resolution atmospheric model (HIRAM) and the Rossby Center nested regional model RCA4 for the Middle East and North Africa (MENA) region. Both global and nested runs were performed with roughly the same spatial resolution of 25 km in latitude and longitude, and were driven by the 2°x2.5°-resolution fields from GFDL ESM2M IPCC AR5 runs. The global HIRAM simulations could naturally account for interaction of regional processes with the larger-scale circulation features like Indian Summer Monsoon, which is lacking from regional model setup. Therefore in this study we specifically address the consistency of "global" and "regional" downscalings. The performance of RCA4, HIRAM, and ESM2M is tested based on mean, extreme, trends, seasonal and inter-annual variability of surface temperature, precipitation, and winds. The impact of climate change on dust storm activity, extreme precipitation and water resources is specifically addressed. We found that the global and regional climate projections appear to be quite consistent for the modeled period and differ more significantly from ESM2M than between each other.

Modeling spatiotemporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Zhen; Zimmermann, Niklaus E.; Kaplan, Jed O.; Poulter, Benjamin

2016-03-01

Simulations of the spatiotemporal dynamics of wetlands are key to understanding the role of wetland biogeochemistry under past and future climate. Hydrologic inundation models, such as the TOPography-based hydrological model (TOPMODEL), are based on a fundamental parameter known as the compound topographic index (CTI) and offer a computationally cost-efficient approach to simulate wetland dynamics at global scales. However, there remains a large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl (Lund-Potsdam-Jena Wald Schnee und Landschaft version) Dynamic Global Vegetation Model (DGVM) and quantifies uncertainties by comparing three digital elevation model (DEM) products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. In addition, we found that calibrating TOPMODEL with a benchmark wetland data set can help to successfully delineate the seasonal and interannual variation of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows the best accuracy for capturing the spatiotemporal dynamics of wetlands among the three DEM products. The estimate of global wetland potential/maximum is ˜ 10.3 Mkm2 (106 km2), with a mean annual maximum of ˜ 5.17 Mkm2 for 1980-2010. When integrated with wetland methane emission submodule, the uncertainty of global annual CH4 emissions from topography inputs is estimated to be 29.0 Tg yr-1. This study demonstrates the feasibility of TOPMODEL to capture spatial heterogeneity of inundation at a large scale and highlights the significance of correcting maximum wetland extent to improve modeling of interannual variations in wetland area. It additionally highlights the importance of an adequate investigation of topographic indices for simulating global wetlands and shows the opportunity to converge wetland estimates across LSMs by identifying the uncertainty associated with existing wetland products.

Ventilation tube insertion simulation: a literature review and validity assessment of five training models.

PubMed

Mahalingam, S; Awad, Z; Tolley, N S; Khemani, S

2016-08-01

The objective of this study was to identify and investigate the face and content validity of ventilation tube insertion (VTI) training models described in the literature. A review of literature was carried out to identify articles describing VTI simulators. Feasible models were replicated and assessed by a group of experts. Postgraduate simulation centre. Experts were defined as surgeons who had performed at least 100 VTI on patients. Seventeen experts were participated ensuring sufficient statistical power for analysis. A standardised 18-item Likert-scale questionnaire was used. This addressed face validity (realism), global and task-specific content (suitability of the model for teaching) and curriculum recommendation. The search revealed eleven models, of which only five had associated validity data. Five models were found to be feasible to replicate. None of the tested models achieved face or global content validity. Only one model achieved task-specific validity, and hence, there was no agreement on curriculum recommendation. The quality of simulation models is moderate and there is room for improvement. There is a need for new models to be developed or existing ones to be refined in order to construct a more realistic training platform for VTI simulation. © 2015 John Wiley & Sons Ltd.

Realism of Indian Summer Monsoon Simulation in a Quarter Degree Global Climate Model

NASA Astrophysics Data System (ADS)

Salunke, P.; Mishra, S. K.; Sahany, S.; Gupta, K.

2017-12-01

This study assesses the fidelity of Indian Summer Monsoon (ISM) simulations using a global model at an ultra-high horizontal resolution (UHR) of 0.25°. The model used was the atmospheric component of the Community Earth System Model version 1.2.0 (CESM 1.2.0) developed at the National Center for Atmospheric Research (NCAR). Precipitation and temperature over the Indian region were analyzed for a wide range of space and time scales to evaluate the fidelity of the model under UHR, with special emphasis on the ISM simulations during the period of June-through-September (JJAS). Comparing the UHR simulations with observed data from the India Meteorological Department (IMD) over the Indian land, it was found that 0.25° resolution significantly improved spatial rainfall patterns over many regions, including the Western Ghats and the South-Eastern peninsula as compared to the standard model resolution. Convective and large-scale rainfall components were analyzed using the European Centre for Medium Range Weather Forecast (ECMWF) Re-Analysis (ERA)-Interim (ERA-I) data and it was found that at 0.25° resolution, there was an overall increase in the large-scale component and an associated decrease in the convective component of rainfall as compared to the standard model resolution. Analysis of the diurnal cycle of rainfall suggests a significant improvement in the phase characteristics simulated by the UHR model as compared to the standard model resolution. Analysis of the annual cycle of rainfall, however, failed to show any significant improvement in the UHR model as compared to the standard version. Surface temperature analysis showed small improvements in the UHR model simulations as compared to the standard version. Thus, one may conclude that there are some significant improvements in the ISM simulations using a 0.25° global model, although there is still plenty of scope for further improvement in certain aspects of the annual cycle of rainfall.

Assessing modeled Greenland surface mass balance in the GISS Model E2 and its sensitivity to surface albedo

NASA Astrophysics Data System (ADS)

Alexander, Patrick; LeGrande, Allegra N.; Koenig, Lora S.; Tedesco, Marco; Moustafa, Samiah E.; Ivanoff, Alvaro; Fischer, Robert P.; Fettweis, Xavier

2016-04-01

The surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) plays an important role in global sea level change. Regional Climate Models (RCMs) such as the Modèle Atmosphérique Régionale (MAR) have been employed at high spatial resolution with relatively complex physics to simulate ice sheet SMB. Global climate models (GCMs) incorporate less sophisticated physical schemes and provide outputs at a lower spatial resolution, but have the advantage of modeling the interaction between different components of the earth's oceans, climate, and land surface at a global scale. Improving the ability of GCMs to represent ice sheet SMB is important for making predictions of future changes in global sea level. With the ultimate goal of improving SMB simulated by the Goddard Institute for Space Studies (GISS) Model E2 GCM, we compare simulated GrIS SMB against the outputs of the MAR model and radar-derived estimates of snow accumulation. In order to reproduce present-day climate variability in the Model E2 simulation, winds are constrained to match the reanalysis datasets used to force MAR at the lateral boundaries. We conduct a preliminary assessment of the sensitivity of the simulated Model E2 SMB to surface albedo, a parameter that is known to strongly influence SMB. Model E2 albedo is set to a fixed value of 0.8 over the entire ice sheet in the initial configuration of the model (control case). We adjust this fixed value in an ensemble of simulations over a range of 0.4 to 0.8 (roughly the range of observed summer GrIS albedo values) to examine the sensitivity of ice-sheet-wide SMB to albedo. We prescribe albedo from the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A3 v6 to examine the impact of a more realistic spatial and temporal variations in albedo. An age-dependent snow albedo parameterization is applied, and its impact on SMB relative to observations and the RCM is assessed.

Atmospheric Sulfur Cycle Simulated in The Global Model GOCART: Model Description and Global Properties

NASA Technical Reports Server (NTRS)

Chin, Mian; Rood, Richard B.; Lin, Shian-Jiann; Mueller, Jean-Francois; Thompson, Anne M.

2000-01-01

The Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model is used to simulate the atmospheric sulfur cycle. The model uses the simulated meteorological data from the Goddard Earth Observing System Data Assimilation System (GEOS DAS). Global sulfur budgets from a 6-year simulation for SO2, sulfate, dimethylsulfide (DMS), and methanesulfonic acid (MSA) are presented in this paper. In a normal year without major volcanic perturbations, about 20% of the sulfate precursor emission is from natural sources (biogenic and volcanic) and 80% is anthropogenic: the same sources contribute 339% and 67% respectively to the total sulfate burden. A sulfate production efficiency of 0.41 - 0.42 is estimated in the model, an efficiency which is defined as a ratio of the amount oi sulfate produced to the total amount of SO2 emitted and produced in the atmosphere. This value indicates that less than half of the SO2 entering the atmosphere contributes to the sulfate production, the rest being removed by dry and wet depositions. In a simulation for 1990, we estimate a total sulfate production of 39 Tg S /yr with 36% and 64% respectively from in-air and in-cloud oxidation of SO2. We also demonstrate that major volcanic eruptions, such as the Mt. Pinatubo eruption in 1991, can significantly change the sulfate formation pathways, distributions, abundance, and lifetime. Comparison with other models shows that the parameterizations for wet removal or wet production of sulfate are the most critical factors in determining the burdens of SO2 and sulfate. Therefore, a priority for future research should be to reduce the large uncertainties associated with the wet physical and chemical processes.

On the use of tower-flux measurements to assess the performance of global ecosystem models

NASA Astrophysics Data System (ADS)

El Maayar, M.; Kucharik, C.

2003-04-01

Global ecosystem models are important tools for the study of biospheric processes and their responses to environmental changes. Such models typically translate knowledge, gained from local observations, into estimates of regional or even global outcomes of ecosystem processes. A typical test of ecosystem models consists of comparing their output against tower-flux measurements of land surface-atmosphere exchange of heat and mass. To perform such tests, models are typically run using detailed information on soil properties (texture, carbon content,...) and vegetation structure observed at the experimental site (e.g., vegetation height, vegetation phenology, leaf photosynthetic characteristics,...). In global simulations, however, earth's vegetation is typically represented by a limited number of plant functional types (PFT; group of plant species that have similar physiological and ecological characteristics). For each PFT (e.g., temperate broadleaf trees, boreal conifer evergreen trees,...), which can cover a very large area, a set of typical physiological and physical parameters are assigned. Thus, a legitimate question arises: How does the performance of a global ecosystem model run using detailed site-specific parameters compare with the performance of a less detailed global version where generic parameters are attributed to a group of vegetation species forming a PFT? To answer this question, we used a multiyear dataset, measured at two forest sites with contrasting environments, to compare seasonal and interannual variability of surface-atmosphere exchange of water and carbon predicted by the Integrated BIosphere Simulator-Dynamic Global Vegetation Model. Two types of simulations were, thus, performed: a) Detailed runs: observed vegetation characteristics (leaf area index, vegetation height,...) and soil carbon content, in addition to climate and soil type, are specified for model run; and b) Generic runs: when only observed climates and soil types at the measurement sites are used to run the model. The generic runs were performed for the number of years equal to the current age of the forests, initialized with no vegetation and a soil carbon density equal to zero.

The influence of spectral nudging on typhoon formation in regional climate models

NASA Astrophysics Data System (ADS)

Feser, Frauke; Barcikowska, Monika

2012-03-01

Regional climate models can successfully simulate tropical cyclones and typhoons. This has been shown and was evaluated for hindcast studies of the past few decades. But often global and regional weather phenomena are not simulated at the observed location, or occur too often or seldom even though the regional model is driven by global reanalysis data which constitute a near-realistic state of the global atmosphere. Therefore, several techniques have been developed in order to make the regional model follow the global state more closely. One is spectral nudging, which is applied for horizontal wind components with increasing strength for higher model levels in this study. The aim of this study is to show the influence that this method has on the formation of tropical cyclones (TC) in regional climate models. Two ensemble simulations (each with five simulations) were computed for Southeast Asia and the Northwestern Pacific for the typhoon season 2004, one with spectral nudging and one without. First of all, spectral nudging reduced the overall TC number by about a factor of 2. But the number of tracks which are similar to observed best track data (BTD) was greatly increased. Also, spatial track density patterns were found to be more similar when using spectral nudging. The tracks merge after a short time for the spectral nudging simulations and then follow the BTD closely; for the no nudge cases the similarity is greatly reduced. A comparison of seasonal precipitation, geopotential height, and temperature fields at several height levels with observations and reanalysis data showed overall a smaller ensemble spread, higher pattern correlations and reduced root mean square errors and biases for the spectral nudged simulations. Vertical temperature profiles for selected TCs indicate that spectral nudging is not inhibiting TC development at higher levels. Both the Madden-Julian Oscillation and monsoonal precipitation are reproduced realistically by the regional model, with results slightly closer to reanalysis data for the spectral nudged simulations. On the basis of this regional climate model hindcast study of a single typhoon season, spectral nudging seems to be favourable since it has mostly positive effects on typhoon formation, location and general circulation patterns in the generation areas of TCs.

Process-Oriented Diagnostics of Tropical Cyclones in Global Climate Models

NASA Astrophysics Data System (ADS)

Moon, Y.; Kim, D.; Camargo, S. J.; Wing, A. A.; Sobel, A. H.; Bosilovich, M. G.; Murakami, H.; Reed, K. A.; Vecchi, G. A.; Wehner, M. F.; Zarzycki, C. M.; Zhao, M.

2017-12-01

Simulating tropical cyclone (TC) activity with global climate models (GCMs) remains a challenging problem. While some GCMs are able to simulate TC activity that is in good agreement with the observations, many other models exhibit strong biases. Decreasing horizontal grid spacing of the GCM simulations tends to improve the characteristics of simulated TCs, but this enhancement alone does not necessarily lead to greater skill in simulating TC activity. This study uses process-based diagnostics to identify model characteristics that could explain why some GCM simulations are able to produce more realistic TC activity than others. The diagnostics examine how convection, moisture, clouds and related processes are coupled at individual grid points, which yields useful information into how convective parameterizations interact with resolved model dynamics. These diagnostics share similarities with those originally developed to examine the Madden-Julian Oscillations in climate models. This study will examine TCs in eight different GCM simulations performed at NOAA/GFDL, NCAR and NASA that have different horizontal resolutions and ocean coupling. Preliminary results suggest that stronger TCs are closely associated with greater rainfall - thus greater diabatic heating - in the inner-core regions of the storms, which is consistent with previous theoretical studies. Other storm characteristics that can be used to infer why GCM simulations with comparable horizontal grid spacings produce different TC activity will be examined.

Plasma sheet low-entropy flow channels and dipolarization fronts from macro to micro scales: Global MHD and PIC simulations

NASA Astrophysics Data System (ADS)

Merkin, V. G.; Wiltberger, M. J.; Sitnov, M. I.; Lyon, J.

2016-12-01

Observations show that much of plasma and magnetic flux transport in the magnetotail occurs in the form of discrete activations such as bursty bulk flows (BBFs). These flow structures are typically associated with strong peaks of the Z-component of the magnetic field normal to the magnetotail current sheet (dipolarization fronts, DFs), as well as density and flux tube entropy depletions also called plasma bubbles. Extensive observational analysis of these structures has been carried out using data from Geotail spacecraft and more recently from Cluster, THEMIS, and MMS multi-probe missions. Global magnetohydrodynamic (MHD) simulations of the magnetosphere reveal similar plasma sheet flow bursts, in agreement with regional MHD and particle-in-cell (PIC) models. We present results of high-resolution simulations using the Lyon-Fedder-Mobarry (LFM) global MHD model and analyze the properties of the bursty flows including their structure and evolution as they propagate from the mid-tail region into the inner magnetosphere. We highlight similarities and differences with the corresponding observations and discuss comparative properties of plasma bubbles and DFs in our global MHD simulations with their counterparts in 3D PIC simulations.

Dynamical downscaling of historical climate over CORDEX East Asia domain: A comparison of regional ocean-atmosphere coupled model to stand-alone RCM simulations

NASA Astrophysics Data System (ADS)

Zou, Liwei; Zhou, Tianjun; Peng, Dongdong

2016-02-01

The FROALS (flexible regional ocean-atmosphere-land system) model, a regional ocean-atmosphere coupled model, has been applied to the Coordinated Regional Downscaling Experiment (CORDEX) East Asia domain. Driven by historical simulations from a global climate system model, dynamical downscaling for the period from 1980 to 2005 has been conducted at a uniform horizontal resolution of 50 km. The impacts of regional air-sea couplings on the simulations of East Asian summer monsoon rainfall have been investigated, and comparisons have been made to corresponding simulations performed using a stand-alone regional climate model (RCM). The added value of the FROALS model with respect to the driving global climate model was evident in terms of both climatology and the interannual variability of summer rainfall over East China by the contributions of both the high horizontal resolution and the reasonably simulated convergence of the moisture fluxes. Compared with the stand-alone RCM simulations, the spatial pattern of the simulated low-level monsoon flow over East Asia and the western North Pacific was improved in the FROALS model due to its inclusion of regional air-sea coupling. The results indicated that the simulated sea surface temperature (SSTs) resulting from the regional air-sea coupling were lower than those derived directly from the driving global model over the western North Pacific north of 15°N. These colder SSTs had both positive and negative effects. On the one hand, they strengthened the western Pacific subtropical high, which improved the simulation of the summer monsoon circulation over East Asia. On the other hand, the colder SSTs suppressed surface evaporation and favored weaker local interannual variability in the SST, which led to less summer rainfall and weaker interannual rainfall variability over the Korean Peninsula and Japan. Overall, the reference simulation performed using the FROALS model is reasonable in terms of rainfall over the land area of East Asia and will become the basis for the generation of climate change scenarios for the CORDEX East Asia domain that will be described in future reports.

Importance of a Global Approach to Using Regional Models in the Assessment of Source-Receptor Relationships of Mercury

EPA Science Inventory

Regional atmospheric models simulate their pertinent processes over a limited portion of the global atmosphere. This portion of the atmosphere can be a large fraction, as in the case of continental-scale modeling, or small fraction, as in the case of urban-scale modeling. Regio...

GEM-AQ, an On-line Global Multiscale Chemical Weather System: Model Description and Evaluation of Gas Phase Chemistry Processes

NASA Astrophysics Data System (ADS)

Neary, L.; Kaminski, J. W.; Struzewska, J.; Ainslie, B.; McConnell, J. C.

2007-12-01

Tropospheric chemistry and air quality processes were implemented on-line in the Global Environmental Multiscale model. The integrated model, GEM-AQ, has been developed as a platform to investigate chemical weather at scales from global to urban. On the global scale, the model was exercised for five years (2001-2005) to evaluate its ability to simulate seasonal variations and regional distributions of trace gases such as ozone, nitrogen dioxide and carbon monoxide. The model results are compared with observations from satellites, aircraft measurement campaigns and balloon sondes. The same model has also been evaluated on the regional (~15km resolution) and urban scale (~3km resolution). A simulation of the formation and transport of photooxidants during the European heat wave of 2006 was performed and compared with surface observations throughout central and eastern Europe. The complex topographic region of the Lower Fraser Valley in British Columbia was the focus of another model evaluation during the PACIFIC 2001 field campaign. Comparison of model results with observations during this period will be shown.

Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model

USGS Publications Warehouse

Swain, Eric; Stefanova, Lydia; Smith, Thomas

2014-01-01

Precipitation data from Global Climate Models have been downscaled to smaller regions. Adapting this downscaled precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The downscaled rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.

A review on vegetation models and applicability to climate simulations at regional scale

NASA Astrophysics Data System (ADS)

Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

2011-11-01

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

Seasonal Variation of the Indonesian Throughflow in Makassar Strait

DTIC Science & Technology

2012-07-01

HYCOM). Twenty-eight years (1981–2008) of 1/38 Indo-Pacific basin HYCOM simulations and three years (2004–06) from a 1/128 global HYCOM simulation are...eight years (1981?2008) of 1/ 38 Indo-Pacific basin HYCOM simulations and three years (2004?06) from a 1/ 128 global HYCOM simulation are analyzed...Wyrtki 1973) and the propa- gation of Kelvin waves along the coasts of Sumatra and Java, such as observed and modeled during May 1997 (Sprintall et

A Model-Model and Data-Model Comparison for the Early Eocene Hydrological Cycle

NASA Technical Reports Server (NTRS)

Carmichael, Matthew J.; Lunt, Daniel J.; Huber, Matthew; Heinemann, Malte; Kiehl, Jeffrey; LeGrande, Allegra; Loptson, Claire A.; Roberts, Chris D.; Sagoo, Navjit; Shields, Christine

2016-01-01

A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP=dT ) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.

Simulations and Evaluation of Mesoscale Convective Systems in a Multi-scale Modeling Framework (MMF)

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.

2017-12-01

It is well known that the mesoscale convective systems (MCS) produce more than 50% of rainfall in most tropical regions and play important roles in regional and global water cycles. Simulation of MCSs in global and climate models is a very challenging problem. Typical MCSs have horizontal scale of a few hundred kilometers. Models with a domain of several hundred kilometers and fine enough resolution to properly simulate individual clouds are required to realistically simulate MCSs. The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has shown some capabilities of simulating organized MCS-like storm signals and propagations. However, its embedded CRMs typically have small domain (less than 128 km) and coarse resolution ( 4 km) that cannot realistically simulate MCSs and individual clouds. In this study, a series of simulations were performed using the Goddard MMF. The impacts of the domain size and model grid resolution of the embedded CRMs on simulating MCSs are examined. The changes of cloud structure, occurrence, and properties such as cloud types, updraft and downdraft, latent heating profile, and cold pool strength in the embedded CRMs are examined in details. The simulated MCS characteristics are evaluated against satellite measurements using the Goddard Satellite Data Simulator Unit. The results indicate that embedded CRMs with large domain and fine resolution tend to produce better simulations compared to those simulations with typical MMF configuration (128 km domain size and 4 km model grid spacing).

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

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

Unger, N.; Harper, K.; Zheng, Y.

2013-10-22

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar/Ball- Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the ratemore » of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present day climatic state that uses plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R 2 = 64-96 %) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr -1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.« less

Photosynthesis-dependent Isoprene Emission from Leaf to Planet in a Global Carbon-chemistry-climate Model

NASA Technical Reports Server (NTRS)

Unger, N.; Harper, K.; Zeng, Y.; Kiang, N. Y.; Alienov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.;

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

NASA Astrophysics Data System (ADS)

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.; McKinney, K. A.; Misztal, P.; Potosnak, M.; Rinne, J.; Pressley, S.; Schoon, N.; Serça, D.

2013-10-01

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar-Ball-Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64-96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

NASA Astrophysics Data System (ADS)

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.; McKinney, K. A.; Misztal, P.; Potosnak, M.; Rinne, J.; Pressley, S.; Schoon, N.; Serça, D.

2013-07-01

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar/Ball-Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2= 64-96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 Tg C yr-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

NASA Astrophysics Data System (ADS)

Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

2016-09-01

Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

Using Multivariate Adaptive Regression Spline and Artificial Neural Network to Simulate Urbanization in Mumbai, India

NASA Astrophysics Data System (ADS)

Ahmadlou, M.; Delavar, M. R.; Tayyebi, A.; Shafizadeh-Moghadam, H.

2015-12-01

Land use change (LUC) models used for modelling urban growth are different in structure and performance. Local models divide the data into separate subsets and fit distinct models on each of the subsets. Non-parametric models are data driven and usually do not have a fixed model structure or model structure is unknown before the modelling process. On the other hand, global models perform modelling using all the available data. In addition, parametric models have a fixed structure before the modelling process and they are model driven. Since few studies have compared local non-parametric models with global parametric models, this study compares a local non-parametric model called multivariate adaptive regression spline (MARS), and a global parametric model called artificial neural network (ANN) to simulate urbanization in Mumbai, India. Both models determine the relationship between a dependent variable and multiple independent variables. We used receiver operating characteristic (ROC) to compare the power of the both models for simulating urbanization. Landsat images of 1991 (TM) and 2010 (ETM+) were used for modelling the urbanization process. The drivers considered for urbanization in this area were distance to urban areas, urban density, distance to roads, distance to water, distance to forest, distance to railway, distance to central business district, number of agricultural cells in a 7 by 7 neighbourhoods, and slope in 1991. The results showed that the area under the ROC curve for MARS and ANN was 94.77% and 95.36%, respectively. Thus, ANN performed slightly better than MARS to simulate urban areas in Mumbai, India.

Modal simulation of gearbox vibration with experimental correlation

NASA Technical Reports Server (NTRS)

Choy, Fred K.; Ruan, Yeefeng F.; Zakrajsek, James J.; Oswald, Fred B.

1992-01-01

A newly developed global dynamic model was used to simulate the dynamics of a gear noise rig at NASA Lewis Research Center. Experimental results from the test rig were used to verify the analytical model. In this global dynamic model, the number of degrees of freedom of the system are reduced by transforming the system equations of motion into modal coordinates. The vibration of the individual gear-shaft system are coupled through the gear mesh forces. A three-dimensional, axial-lateral coupled, bearing model was used to couple the casing structural vibration to the gear-rotor dynamics. The coupled system of modal equations is solved to predict the resulting vibration at several locations on the test rig. Experimental vibration data was compared to the predictions of the global dynamic model. There is excellent agreement between the vibration results from analysis and experiment.

Does extreme precipitation intensity depend on the emissions scenario?

NASA Astrophysics Data System (ADS)

Pendergrass, Angeline; Lehner, Flavio; Sanderson, Benjamin; Xu, Yangyang

2016-04-01

The rate of increase of global-mean precipitation per degree surface temperature increase differs for greenhouse gas and aerosol forcings, and therefore depends on the change in composition of the emissions scenario used to drive climate model simulations for the remainder of the century. We investigate whether or not this is also the case for extreme precipitation simulated by a multi-model ensemble driven by four realistic emissions scenarios. In most models, the rate of increase of maximum annual daily rainfall per degree global warming in the multi-model ensemble is statistically indistinguishable across the four scenarios, whether this extreme precipitation is calculated globally, over all land, or over extra-tropical land. These results indicate that, in most models, extreme precipitation depends on the total amount of warming and does not depend on emissions scenario, in contrast to mean precipitation.

A satellite and model based flood inundation climatology of Australia

NASA Astrophysics Data System (ADS)

Schumann, G.; Andreadis, K.; Castillo, C. J.

2013-12-01

To date there is no coherent and consistent database on observed or simulated flood event inundation and magnitude at large scales (continental to global). The only compiled data set showing a consistent history of flood inundation area and extent at a near global scale is provided by the MODIS-based Dartmouth Flood Observatory. However, MODIS satellite imagery is only available from 2000 and is hampered by a number of issues associated with flood mapping using optical images (e.g. classification algorithms, cloud cover, vegetation). Here, we present for the first time a proof-of-concept study in which we employ a computationally efficient 2-D hydrodynamic model (LISFLOOD-FP) complemented with a sub-grid channel formulation to generate a complete flood inundation climatology of the past 40 years (1973-2012) for the entire Australian continent. The model was built completely from freely available SRTM-derived data, including channel widths, bank heights and floodplain topography, which was corrected for vegetation canopy height using a global ICESat canopy dataset. Channel hydraulics were resolved using actual channel data and bathymetry was estimated within the model using hydraulic geometry. On the floodplain, the model simulated the flow paths and inundation variables at a 1 km resolution. The developed model was run over a period of 40 years and a floodplain inundation climatology was generated and compared to satellite flood event observations. Our proof-of-concept study demonstrates that this type of model can reliably simulate past flood events with reasonable accuracies both in time and space. The Australian model was forced with both observed flow climatology and VIC-simulated flows in order to assess the feasibility of a model-based flood inundation climatology at the global scale.

Mechanism of ENSO influence on the South Asian monsoon rainfall in global model simulations

NASA Astrophysics Data System (ADS)

Joshi, Sneh; Kar, Sarat C.

2018-02-01

Coupled ocean atmosphere global climate models are increasingly being used for seasonal scale simulation of the South Asian monsoon. In these models, sea surface temperatures (SSTs) evolve as coupled air-sea interaction process. However, sensitivity experiments with various SST forcing can only be done in an atmosphere-only model. In this study, the Global Forecast System (GFS) model at T126 horizontal resolution has been used to examine the mechanism of El Niño-Southern Oscillation (ENSO) forcing on the monsoon circulation and rainfall. The model has been integrated (ensemble) with observed, climatological and ENSO SST forcing to document the mechanism on how the South Asian monsoon responds to basin-wide SST variations in the Indian and Pacific Oceans. The model simulations indicate that the internal variability gets modulated by the SSTs with warming in the Pacific enhancing the ensemble spread over the monsoon region as compared to cooling conditions. Anomalous easterly wind anomalies cover the Indian region both at 850 and 200 hPa levels during El Niño years. The locations and intensity of Walker and Hadley circulations are altered due to ENSO SST forcing. These lead to reduction of monsoon rainfall over most parts of India during El Niño events compared to La Niña conditions. However, internally generated variability is a major source of uncertainty in the model-simulated climate.

Land cover change or land-use intensification: simulating land system change with a global-scale land change model.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2013-12-01

Land-use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land-use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land systems that are characterized by their land cover mosaic, the agricultural management intensity, and livestock. Land system changes are simulated by the model, driven by regional demand for goods and influenced by local factors that either constrain or promote land system conversion. A characteristic of the new model is the endogenous simulation of intensification of agricultural management versus expansion of arable land, and urban versus rural settlements expansion based on land availability in the neighborhood of the location. Model results for the OECD Environmental Outlook scenario show that allocation of increased agricultural production by either management intensification or area expansion varies both among and within world regions, providing useful insight into the land sparing versus land sharing debate. The land system approach allows the inclusion of different types of demand for goods and services from the land system as a driving factor of land system change. Simulation results are compared to observed changes over the 1970-2000 period and projections of other global and regional land change models. © 2013 John Wiley & Sons Ltd.

Comparison of Solar and Other Influences on Long-term Climate

NASA Technical Reports Server (NTRS)

Hansen, James E.; Lacis, Andrew A.; Ruedy, Reto A.

1990-01-01

Examples are shown of climate variability, and unforced climate fluctuations are discussed, as evidenced in both model simulations and observations. Then the author compares different global climate forcings, a comparison which by itself has significant implications. Finally, the author discusses a new climate simulation for the 1980s and 1990s which incorporates the principal known global climate forcings. The results indicate a likelihood of rapid global warming in the early 1990s.

GNAQPMS-Hg v1.0, a global nested atmospheric mercury transport model: model description, evaluation and application to trans-boundary transport of Chinese anthropogenic emissions

NASA Astrophysics Data System (ADS)

Chen, H. S.; Wang, Z. F.; Li, J.; Tang, X.; Ge, B. Z.; Wu, X. L.; Wild, O.; Carmichael, G. R.

2014-10-01

Atmospheric mercury (Hg) is a toxic pollutant and can be transported over the whole globe due to its long lifetime in the atmosphere. For the purpose of assessing Hg hemispheric transport and better characterizing regional Hg pollution, a global nested atmospheric Hg transport model (GNAQPMS-Hg) has been developed. In GNAQPMS-Hg, the gas and aqueous phase Hg chemistry representing the transformation among three forms of Hg: elemental mercury (Hg(0)), divalent mercury (Hg(II)), and primary particulate mercury (Hg(P)) are calculated. A detailed description of the model, including mercury emissions, gas and aqueous phase chemistry, and dry and wet deposition is given in this study. Worldwide observations including extensive data in China have been collected for model evaluation. Comparison results show that the model reasonably simulates the global mercury budget and the spatial-temporal variation of surface mercury concentrations and deposition. Overall, model predictions of annual total gaseous mercury (TGM) and wet deposition agree with observations within a factor of two, and within a factor of five for oxidized mercury and dry deposition. The model performs significantly better in North America and Europe than in East Asia. This can probably be attributed to the large uncertainties in emission inventories, coarse model resolution and to the inconsistency between the simulation and observation periods in East Asia. Compared to the global simulation, the nested simulation shows improved skill at capturing the high spatial variability of Hg concentrations and deposition over East Asia. In particular, the root mean square error (RMSE) of simulated Hg wet deposition over East Asia is reduced by 24% in the nested simulation. Model sensitivity studies indicate that Chinese primary anthropogenic emissions account for 30 and 62% of surface mercury concentrations and deposition over China, respectively. Along the rim of the western Pacific, the contributions from Chinese sources are 11 and 15.2% over the Korean Peninsula, 10.4 and 8.2% over Southeast Asia, and 5.7 and 5.9% over Japan. But for North America, Europe and West Asia, the contributions from China are all below 5%.

Global climate simulations at 3000-year intervals for the last 21 000 years with the GENMOM coupled atmosphere–ocean model

USGS Publications Warehouse

Alder, Jay R.; Hostetler, Steven W.

2015-01-01

We apply GENMOM, a coupled atmosphere–ocean climate model, to simulate eight equilibrium time slices at 3000-year intervals for the past 21 000 years forced by changes in Earth–Sun geometry, atmospheric greenhouse gases (GHGs), continental ice sheets, and sea level. Simulated global cooling during the Last Glacial Maximum (LGM) is 3.8 ◦C and the rate of post-glacial warming is in overall agreement with recently published temperature reconstructions. The greatest rate of warming occurs between 15 and 12 ka (2.4 ◦C over land, 0.7 ◦C over oceans, and 1.4 ◦C globally) in response to changes in radiative forcing from the diminished extent of the Northern Hemisphere (NH) ice sheets and increases in GHGs and NH summer insolation. The modeled LGM and 6 ka temperature and precipitation climatologies are generally consistent with proxy reconstructions, the PMIP2 and PMIP3 simulations, and other paleoclimate data–model analyses. The model does not capture the mid-Holocene “thermal maximum” and gradual cooling to preindustrial (PI) global temperature found in the data. Simulated monsoonal precipitation in North Africa peaks between 12 and 9 ka at values ∼ 50 % greater than those of the PI, and Indian monsoonal precipitation peaks at 12 and 9 ka at values ∼ 45 % greater than the PI. GENMOM captures the reconstructed LGM extent of NH and Southern Hemisphere (SH) sea ice. The simulated present-day Antarctica Circumpolar Current (ACC) is ∼ 48 % weaker than the observed (62 versus 119 Sv). The simulated present-day Atlantic Meridional Overturning Circulation (AMOC) of 19.3 ± 1.4 Sv on the Bermuda Rise (33◦ N) is comparable with observed value of 18.7 ± 4.8 Sv. AMOC at 33◦ N is reduced by ∼ 15 % during the LGM, and the largest post-glacial increase (∼ 11 %) occurs during the 15 ka time slice.

Isoprene emission response to drought and the impact on global atmospheric chemistry

NASA Astrophysics Data System (ADS)

Jiang, Xiaoyan; Guenther, Alex; Potosnak, Mark; Geron, Chris; Seco, Roger; Karl, Thomas; Kim, Saewung; Gu, Lianhong; Pallardy, Stephen

2018-06-01

Biogenic isoprene emissions play a very important role in atmospheric chemistry. These emissions are strongly dependent on various environmental conditions, such as temperature, solar radiation, plant water stress, ambient ozone and CO2 concentrations, and soil moisture. Current biogenic emission models (i.e., Model of Emissions of Gases and Aerosols from Nature, MEGAN) can simulate emission responses to some of the major driving variables, such as short-term variations in temperature and solar radiation, but the other factors are either missing or poorly represented. In this paper, we propose a new modelling approach that considers the physiological effects of drought stress on plant photosynthesis and isoprene emissions for use in the MEGAN3 biogenic emission model. We test the MEGAN3 approach by integrating the algorithm into the existing MEGAN2.1 biogenic emission model framework embedded into the global Community Land Model of the Community Earth System Model (CLM4.5/CESM1.2). Single-point simulations are compared against available field measurements at the Missouri Ozarks AmeriFlux (MOFLUX) field site. The modelling results show that the MEGAN3 approach of using of a photosynthesis parameter (Vcmax) and soil wetness factor (βt) to determine the drought activity factor leads to better simulated isoprene emissions in non-drought and drought periods. The global simulation with the MEGAN3 approach predicts a 17% reduction in global annual isoprene emissions, in comparison to the value predicted using the default CLM4.5/MEGAN2.1 without any drought effect. This reduction leads to changes in surface ozone and oxidants in the areas where the reduction of isoprene emissions is observed. Based on the results presented in this study, we conclude that it is important to simulate the drought-induced response of biogenic isoprene emission accurately in the coupled Earth System model.

Isotopic source signatures: Impact of regional variability on the δ13CH4 trend and spatial distribution

NASA Astrophysics Data System (ADS)

Feinberg, Aryeh I.; Coulon, Ancelin; Stenke, Andrea; Schwietzke, Stefan; Peter, Thomas

2018-02-01

The atmospheric methane growth rate has fluctuated over the past three decades, signifying variations in methane sources and sinks. Methane isotopic ratios (δ13CH4) differ between emission categories, and can therefore be used to distinguish which methane sources have changed. However, isotopic modelling studies have mainly focused on uncertainties in methane emissions rather than uncertainties in isotopic source signatures. We simulated atmospheric δ13CH4 for the period 1990-2010 using the global chemistry-climate model SOCOL. Empirically-derived regional variability in the isotopic signatures was introduced in a suite of sensitivity simulations. These simulations were compared to a baseline simulation with commonly used global mean isotopic signatures. We investigated coal, natural gas/oil, wetland, livestock, and biomass burning source signatures to determine whether regional variations impact the observed isotopic trend and spatial distribution. Based on recently published source signature datasets, our calculated global mean isotopic signatures are in general lighter than the commonly used values. Trends in several isotopic signatures were also apparent during the period 1990-2010. Tropical livestock emissions grew during the 2000s, introducing isotopically heavier livestock emissions since tropical livestock consume more C4 vegetation than midlatitude livestock. Chinese coal emissions, which are isotopically heavy compared to other coals, increase during the 2000s leading to higher global values of δ13CH4 for coal emissions. EDGAR v4.2 emissions disagree with the observed atmospheric isotopic trend for almost all simulations, confirming past doubts about this emissions inventory. The agreement between the modelled and observed δ13CH4 interhemispheric differences improves when regional source signatures are used. Even though the simulated results are highly dependent on the choice of methane emission inventories, they emphasize that the commonly used global mean signatures are inadequate. Regional isotopic signatures should be employed in modelling studies that try to constrain methane emission inventories.

Quasi-decadal Oscillation in the CMIP5 and CMIP3 Climate Model Simulations: California Case

NASA Astrophysics Data System (ADS)

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

2014-12-01

The ongoing three drought years in California are reminding us of two other historical long drought periods: 1987-1992 and 1928-1934. This kind of interannual variability is corresponding to the dominating 7-15 yr quasi-decadal oscillation in precipitation and streamflow in California. When using global climate model projections to assess the climate change impact on water resources planning in California, it is natural to ask if global climate models are able to reproduce the observed interannual variability like 7-15 yr quasi-decadal oscillation. Further spectral analysis to tree ring retrieved precipitation and historical precipitation record proves the existence of 7-15 yr quasi-decadal oscillation in California. But while implementing spectral analysis to all the CMIP5 and CMIP3 global climate model historical simulations using wavelet analysis approach, it was found that only two models in CMIP3 , CGCM 2.3.2a of MRI and NCAP PCM1.0, and only two models in CMIP5, MIROC5 and CESM1-WACCM, have statistically significant 7-15 yr quasi-decadal oscillations in California. More interesting, the existence of 7-15 yr quasi-decadal oscillation in the global climate model simulation is also sensitive to initial conditions. 12-13 yr quasi-decadal oscillation occurs in one ensemble run of CGCM 2.3.2a of MRI but does not exist in the other four ensemble runs.

Dynamics of delayed pathogen infection models with pathogenic and cellular infections and immune impairment

NASA Astrophysics Data System (ADS)

Elaiw, A. M.; Raezah, A. A.; Alofi, B. S.

2018-02-01

We study the global dynamics of delayed pathogen infection models with immune impairment. Both pathogen-to-susceptible and infected-to-susceptible transmissions have been considered. Bilinear and saturated incidence rates are considered in the first and second model, respectively. We drive the basic reproduction parameter R0 which determines the global dynamics of models. Using Lyapunov method, we established the global stability of the models' steady states. The theoretical results are confirmed by numerical simulations.

Present-day constraint for tropical Pacific precipitation changes due to global warming in CMIP5 models

NASA Astrophysics Data System (ADS)

Ham, Yoo-Geun; Kug, Jong-Seong

2016-11-01

The sensitivity of the precipitation responses to greenhouse warming can depend on the present-day climate. In this study, a robust linkage between the present-day precipitation climatology and precipitation change owing to global warming is examined in inter-model space. A model with drier climatology in the present-day simulation tends to simulate an increase in climatological precipitation owing to global warming. Moreover, the horizontal gradient of the present-day precipitation climatology plays an important role in determining the precipitation changes. On the basis of these robust relationships, future precipitation changes are calibrated by removing the impact of the present-day precipitation bias in the climate models. To validate this result, the perfect model approach is adapted, which treats a particular model's precipitation change as an observed change. The results suggest that the precipitation change pattern can be generally improved by applying the present statistical approach.

Real-Time Global Nonlinear Aerodynamic Modeling for Learn-To-Fly

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2016-01-01

Flight testing and modeling techniques were developed to accurately identify global nonlinear aerodynamic models for aircraft in real time. The techniques were developed and demonstrated during flight testing of a remotely-piloted subscale propeller-driven fixed-wing aircraft using flight test maneuvers designed to simulate a Learn-To-Fly scenario. Prediction testing was used to evaluate the quality of the global models identified in real time. The real-time global nonlinear aerodynamic modeling algorithm will be integrated and further tested with learning adaptive control and guidance for NASA Learn-To-Fly concept flight demonstrations.

Modeling Modern Methane Emissions from Natural Wetlands. 1; Model Description and Results

NASA Technical Reports Server (NTRS)

Walter, Bernadette P.; Heimann, Martin; Matthews, Elaine

2001-01-01

Methane is an important greenhouse gas which contributes about 22 percent to the present greenhouse effect. Natural wetlands currently constitute the biggest methane source and were the major source in preindustrial times. Wetland emissions depend highly on the climate, i.e., on soil temperature and water table. To investigate the response of methane emissions from natural wetlands to climate variations, a process-based model that derives methane emissions from natural wetlands as a function of soil temperature, water table, and net primary productivity is used. For its application on the global scale, global data sets for all model parameters are generated. In addition, a simple hydrologic model is developed in order to simulate the position of the water table in wetlands. The hydrologic model is tested against data from different wetland sites, and the sensitivity of the hydrologic model to changes in precipitation is examined. The global methane­ hydrology model constitutes a tool to study temporal and spatial variations in methane emissions from natural wetlands. The model is applied using high-frequency atmospheric forcing fields from European Center for Medium-range Weather Forecasts (ECMWF) re-analyses of the period from 1982 to 1993. We calculate global annual methane emissions from wetlands to be 260 teragrams per year. Twenty-five percent of these methane emissions originate from wetlands north of 30 degrees North Latitude. Only 60 percent of the produced methane is emitted, while the rest is re-oxidized. A comparison of zonal integrals of simulated global wetland emissions and results obtained by an inverse modeling approach shows good agreement. In a test with data from two wetlands the seasonality of simulated and observed methane emissions agrees well.

A Global Model Simulation of Aerosol Effects of Surface Radiation Budget- Toward Understanding of the "Dimming to Brightening" Transition

NASA Technical Reports Server (NTRS)

Chin, Mian; Diehl, Thomas; Bian, Huisheng; Yu, Hongbin

2008-01-01

We present a global model study on the role aerosols play in the change of solar radiation at Earth's surface that transitioned from a decreasing (dimming) trend to an increasing (brightening) trend. Our primary objective is to understand the relationship between the long-term trends of aerosol emission, atmospheric burden, and surface solar radiation. More specifically, we use the recently compiled comprehensive global emission datasets of aerosols and precursors from fuel combustion, biomass burning, volcanic eruptions and other sources from 1980 to 2006 to simulate long-term variations of aerosol distributions and optical properties, and then calculate the multi-decadal changes of short-wave radiative fluxes at the surface and at the top of the atmosphere by coupling the GOCART model simulated aerosols with the Goddard radiative transfer model. The model results are compared with long-term observational records from ground-based networks and satellite data. We will address the following critical questions: To what extent can the observed surface solar radiation trends, known as the transition from dimming to brightening, be explained by the changes of anthropogenic and natural aerosol loading on global and regional scales? What are the relative contributions of local emission and long-range transport to the surface radiation budget and how do these contributions change with time?

The Ozone Budget in the Upper Troposphere from Global Modeling Initiative (GMI)Simulations

NASA Technical Reports Server (NTRS)

Rodriquez, J.; Duncan, Bryan N.; Logan, Jennifer A.

2006-01-01

Ozone concentrations in the upper troposphere are influenced by in-situ production, long-range tropospheric transport, and influx of stratospheric ozone, as well as by photochemical removal. Since ozone is an important greenhouse gas in this region, it is particularly important to understand how it will respond to changes in anthropogenic emissions and changes in stratospheric ozone fluxes.. This response will be determined by the relative balance of the different production, loss and transport processes. Ozone concentrations calculated by models will differ depending on the adopted meteorological fields, their chemical scheme, anthropogenic emissions, and treatment of the stratospheric influx. We performed simulations using the chemical-transport model from the Global Modeling Initiative (GMI) with meteorological fields from (It)h e NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM), (2) the atmospheric GCM from NASA's Global Modeling and Assimilation Office(GMAO), and (3) assimilated winds from GMAO . These simulations adopt the same chemical mechanism and emissions, and adopt the Synthetic Ozone (SYNOZ) approach for treating the influx of stratospheric ozone -. In addition, we also performed simulations for a coupled troposphere-stratosphere model with a subset of the same winds. Simulations were done for both 4degx5deg and 2degx2.5deg resolution. Model results are being tested through comparison with a suite of atmospheric observations. In this presentation, we diagnose the ozone budget in the upper troposphere utilizing the suite of GMI simulations, to address the sensitivity of this budget to: a) the different meteorological fields used; b) the adoption of the SYNOZ boundary condition versus inclusion of a full stratosphere; c) model horizontal resolution. Model results are compared to observations to determine biases in particular simulations; by examining these comparisons in conjunction with the derived budgets, we may pinpoint deficiencies in the representation of chemical/dynamical processes.

Robust Spring Drying in the Southwestern U.S. and Seasonal Migration of Wet/Dry Patterns in a Warmer Climate

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

Gao, Yang; Leung, Lai-Yung R.; Lu, Jian

2014-03-16

This study compares climate simulations over the United States produced by a regional climate model with the driving global climate simulations as well as a large multi-model ensemble of global climate simulations to investigate robust changes in water availability (precipitation (P) – evapotranspiration (E)). A robust spring dry signal across multiple models is identified in the Southwest that results from a decrease in P and an increase in E in the future. In the boreal winter and summer, the prominent changes in P – E are associated with a north – south dipole pattern, while in spring, the prominent changesmore » in P – E appear as an east – west dipole pattern. The progression of the north – south and east – west dipole patterns through the seasons manifests clearly as a seasonal “clockwise” migration of wet/dry patterns, which is shown to be a robust feature of water availability changes in the US consistent across regional and global climate simulations.« less

Global Modeling of Tropospheric Chemistry with Assimilated Meteorology: Model Description and Evaluation

NASA Technical Reports Server (NTRS)

Bey, Isabelle; Jacob, Daniel J.; Yantosca, Robert M.; Logan, Jennifer A.; Field, Brendan D.; Fiore, Arlene M.; Li, Qin-Bin; Liu, Hong-Yu; Mickley, Loretta J.; Schultz, Martin G.

2001-01-01

We present a first description and evaluation of GEOS-CHEM, a global three-dimensional (3-D) model of tropospheric chemistry driven by assimilated meteorological observations from the Goddard Earth Observing System (GEOS) of the NASA Data Assimilation Office (DAO). The model is applied to a 1-year simulation of tropospheric ozone-NOx-hydrocarbon chemistry for 1994, and is evaluated with observations both for 1994 and for other years. It reproduces usually to within 10 ppb the concentrations of ozone observed from the worldwide ozonesonde data network. It simulates correctly the seasonal phases and amplitudes of ozone concentrations for different regions and altitudes, but tends to underestimate the seasonal amplitude at northern midlatitudes. Observed concentrations of NO and peroxyacetylnitrate (PAN) observed in aircraft campaigns are generally reproduced to within a factor of 2 and often much better. Concentrations of HNO3 in the remote troposphere are overestimated typically by a factor of 2-3, a common problem in global models that may reflect a combination of insufficient precipitation scavenging and gas-aerosol partitioning not resolved by the model. The model yields an atmospheric lifetime of methylchloroform (proxy for global OH) of 5.1 years, as compared to a best estimate from observations of 5.5 plus or minus 0.8 years, and simulates H2O2 concentrations observed from aircraft with significant regional disagreements but no global bias. The OH concentrations are approximately 20% higher than in our previous global 3-D model which included an UV-absorbing aerosol. Concentrations of CO tend to be underestimated by the model, often by 10-30 ppb, which could reflect a combination of excessive OH (a 20% decrease in model OH could be accommodated by the methylchloroform constraint) and an underestimate of CO sources (particularly biogenic). The model underestimates observed acetone concentrations over the South Pacific in fall by a factor of 3; a missing source from the ocean may be implicated.

Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.

Automated parameterization of intermolecular pair potentials using global optimization techniques

NASA Astrophysics Data System (ADS)

Krämer, Andreas; Hülsmann, Marco; Köddermann, Thorsten; Reith, Dirk

2014-12-01

In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters' influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task.

Overview of Experimental Capabilities - Supersonics

NASA Technical Reports Server (NTRS)

Banks, Daniel W.

2007-01-01

This viewgraph presentation gives an overview of experimental capabilities applicable to the area of supersonic research. The contents include: 1) EC Objectives; 2) SUP.11: Elements; 3) NRA; 4) Advanced Flight Simulator Flexible Aircraft Simulation Studies; 5) Advanced Flight Simulator Flying Qualities Guideline Development for Flexible Supersonic Transport Aircraft; 6) Advanced Flight Simulator Rigid/Flex Flight Control; 7) Advanced Flight Simulator Rapid Sim Model Exchange; 8) Flight Test Capabilities Advanced In-Flight Infrared (IR) Thermography; 9) Flight Test Capabilities In-Flight Schlieren; 10) Flight Test Capabilities CLIP Flow Calibration; 11) Flight Test Capabilities PFTF Flowfield Survey; 12) Ground Test Capabilities Laser-Induced Thermal Acoustics (LITA); 13) Ground Test Capabilities Doppler Global Velocimetry (DGV); 14) Ground Test Capabilities Doppler Global Velocimetry (DGV); and 15) Ground Test Capabilities EDL Optical Measurement Capability (PIV) for Rigid/Flexible Decelerator Models.

A Scoping Review: Conceptualizations and Pedagogical Models of Learning in Nursing Simulation

ERIC Educational Resources Information Center

Poikela, Paula; Teräs, Marianne

2015-01-01

Simulations have been implemented globally in nursing education for years with diverse conceptual foundations. The aim of this scoping review is to examine the literature regarding the conceptualizations of learning and pedagogical models in nursing simulations. A scoping review of peer-reviewed articles published between 2000 and 2013 was…

Monte Carlo computer simulations of Venus equilibrium and global resurfacing models

NASA Technical Reports Server (NTRS)

Dawson, D. D.; Strom, R. G.; Schaber, G. G.

1992-01-01

Two models have been proposed for the resurfacing history of Venus: (1) equilibrium resurfacing and (2) global resurfacing. The equilibrium model consists of two cases: in case 1, areas less than or equal to 0.03 percent of the planet are spatially randomly resurfaced at intervals of less than or greater than 150,000 yr to produce the observed spatially random distribution of impact craters and average surface age of about 500 m.y.; and in case 2, areas greater than or equal to 10 percent of the planet are resurfaced at intervals of greater than or equal to 50 m.y. The global resurfacing model proposes that the entire planet was resurfaced about 500 m.y. ago, destroying the preexisting crater population and followed by significantly reduced volcanism and tectonism. The present crater population has accumulated since then with only 4 percent of the observed craters having been embayed by more recent lavas. To test the equilibrium resurfacing model we have run several Monte Carlo computer simulations for the two proposed cases. It is shown that the equilibrium resurfacing model is not a valid model for an explanation of the observed crater population characteristics or Venus' resurfacing history. The global resurfacing model is the most likely explanation for the characteristics of Venus' cratering record. The amount of resurfacing since that event, some 500 m.y. ago, can be estimated by a different type of Monte Carolo simulation. To date, our initial simulation has only considered the easiest case to implement. In this case, the volcanic events are randomly distributed across the entire planet and, therefore, contrary to observation, the flooded craters are also randomly distributed across the planet.

Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

2005-12-01

Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.

Coupled Climate Model Simulations to Bracket the Impacts of Increasing Asian Aerosols Emissions and Aggressive Future Clean Air Policies

NASA Astrophysics Data System (ADS)

Dubey, M. K.; Zhang, Y.; Sun, S.; Olsen, S.; Dean, S.; Bleck, R.; Chylek, P.; Lohmann, U.

2007-12-01

We report ensemble simulations of the climatic impacts of changing anthropogenic aerosols (sulfate, organic and black carbon), which bracket two policy scenarios: increased emissions over China and India by a factor of three over current levels and a global reduction of aerosols by a factor of ten, using the NCAR-CCSM3 and NASA- GISS coupled ocean atmosphere models. Tripling the anthropogenic aerosols over China and India has a small cooling effect (about -0.12°C) on the global mean surface air temperature with a slight reduction in global mean precipitation by ~ -0.8%. On the other hand, global reduction of anthropogenic aerosols by a factor of ten would warm the global surface temperatures by 0.4 °C - 0.8 °C in less than 10 years after the reduction takes place as well as an increase in global precipitation by 3.0% - 3.3%. Comparisons of NCAR and NASA model simulations also suggest that the indirect effects of aerosols are about 1-2 times the direct effects of aerosols. Tripling Asian anthropogenic aerosols results in regional cooling and a reduction in precipitation primarily in Asia, with cooling (warming) also noted over the high latitudes of Northern (Southern) Hemisphere. Warming and increase in precipitation in the case of global reduction of aerosols are concentrated mainly over polluted land areas in both hemispheres. Tropical regions experience large changes in precipitation in both scenarios. We provide new insights into the climate model sensitivities of global mean temperatures and rainfall to aerosol forcing. Our results underscore the urgency of reducing greenhouse gas accumulation rates as the world reduces air pollution to improve human health and that potential increased Asian pollution, offsets only a small fraction of the warming by greenhouse gases.

Face aging effect simulation model based on multilayer representation and shearlet transform

NASA Astrophysics Data System (ADS)

Li, Yuancheng; Li, Yan

2017-09-01

In order to extract detailed facial features, we build a face aging effect simulation model based on multilayer representation and shearlet transform. The face is divided into three layers: the global layer of the face, the local features layer, and texture layer, which separately establishes the aging model. First, the training samples are classified according to different age groups, and we use active appearance model (AAM) at the global level to obtain facial features. The regression equations of shape and texture with age are obtained by fitting the support vector machine regression, which is based on the radial basis function. We use AAM to simulate the aging of facial organs. Then, for the texture detail layer, we acquire the significant high-frequency characteristic components of the face by using the multiscale shearlet transform. Finally, we get the last simulated aging images of the human face by the fusion algorithm. Experiments are carried out on the FG-NET dataset, and the experimental results show that the simulated face images have less differences from the original image and have a good face aging simulation effect.

Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties

NASA Astrophysics Data System (ADS)

Exbrayat, Jean-François; Bloom, A. Anthony; Falloon, Pete; Ito, Akihiko; Smallman, T. Luke; Williams, Mathew

2018-02-01

Multi-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used extensively in climate and hydrological sciences, but they have not been used to constrain projected plant productivity responses to climate change, which is a major uncertainty in Earth system modelling. Here, we use three global observationally orientated estimates of current net primary productivity (NPP) to perform a reliability ensemble averaging (REA) method using 30 global simulations of the 21st century change in NPP based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) business as usual emissions scenario. We find that the three REA methods support an increase in global NPP by the end of the 21st century (2095-2099) compared to 2001-2005, which is 2-3 % stronger than the ensemble ISIMIP mean value of 24.2 Pg C y-1. Using REA also leads to a 45-68 % reduction in the global uncertainty of 21st century NPP projection, which strengthens confidence in the resilience of the CO2 fertilization effect to climate change. This reduction in uncertainty is especially clear for boreal ecosystems although it may be an artefact due to the lack of representation of nutrient limitations on NPP in most models. Conversely, the large uncertainty that remains on the sign of the response of NPP in semi-arid regions points to the need for better observations and model development in these regions.

Significant uncertainty in global scale hydrological modeling from precipitation data errors

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

2015-10-01

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.

Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, Cynthia; Ruane, Alex C.; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S.; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M.; Sands, Ronald D.; Schleussner, Carl-Friedrich; Valdivia, Roberto O.; Valin, Hugo; Wiebe, Keith

2018-05-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate. This article is part of the theme issue `The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments.

PubMed

Rosenzweig, Cynthia; Ruane, Alex C; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M; Sands, Ronald D; Schleussner, Carl-Friedrich; Valdivia, Roberto O; Valin, Hugo; Wiebe, Keith

2018-05-13

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO 2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'. © 2018 The Authors.

Variability in modeled cloud feedback tied to differences in the climatological spatial pattern of clouds

NASA Astrophysics Data System (ADS)

Siler, Nicholas; Po-Chedley, Stephen; Bretherton, Christopher S.

2018-02-01

Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO_2 (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud contribution to albedo (α) in simulations of the current climate: high-feedback models exhibit lower (higher) α in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean α as temperatures rise and warm regions expand. The spatial pattern of α is found to be strongly predictive (r=0.84) of a model's global cloud feedback, with satellite observations indicating a most-likely value of 0.58± 0.31 Wm^{-2} K^{-1} (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 Wm^{-2} K^{-1}, with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate.

Modeling extreme (Carrington-type) space weather events using three-dimensional MHD code simulations

NASA Astrophysics Data System (ADS)

Ngwira, C. M.; Pulkkinen, A. A.; Kuznetsova, M. M.; Glocer, A.

2013-12-01

There is growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure and systems. In the last two decades, significant progress has been made towards the modeling of space weather events. Three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, and have played a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for existing global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events that have a ground footprint comparable (or larger) to the Carrington superstorm. Results are presented for an initial simulation run with ``very extreme'' constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated ground induced geoelectric field to such extreme driving conditions. We also discuss the results and what they might mean for the accuracy of the simulations. The model is further tested using input data for an observed space weather event to verify the MHD model consistence and to draw guidance for future work. This extreme space weather MHD model is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in earth conductors such as power transmission grids.

Evaluation of rainfall simulations over West Africa in dynamically downscaled CMIP5 global circulation models

NASA Astrophysics Data System (ADS)

Akinsanola, A. A.; Ajayi, V. O.; Adejare, A. T.; Adeyeri, O. E.; Gbode, I. E.; Ogunjobi, K. O.; Nikulin, G.; Abolude, A. T.

2018-04-01

This study presents evaluation of the ability of Rossby Centre Regional Climate Model (RCA4) driven by nine global circulation models (GCMs), to skilfully reproduce the key features of rainfall climatology over West Africa for the period of 1980-2005. The seasonal climatology and annual cycle of the RCA4 simulations were assessed over three homogenous subregions of West Africa (Guinea coast, Savannah, and Sahel) and evaluated using observed precipitation data from the Global Precipitation Climatology Project (GPCP). Furthermore, the model output was evaluated using a wide range of statistical measures. The interseasonal and interannual variability of the RCA4 were further assessed over the subregions and the whole of the West Africa domain. Results indicate that the RCA4 captures the spatial and interseasonal rainfall pattern adequately but exhibits a weak performance over the Guinea coast. Findings from the interannual rainfall variability indicate that the model performance is better over the larger West Africa domain than the subregions. The largest difference across the RCA4 simulated annual rainfall was found in the Sahel. Result from the Mann-Kendall test showed no significant trend for the 1980-2005 period in annual rainfall either in GPCP observation data or in the model simulations over West Africa. In many aspects, the RCA4 simulation driven by the HadGEM2-ES perform best over the region. The use of the multimodel ensemble mean has resulted to the improved representation of rainfall characteristics over the study domain.

The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

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

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the conceptmore » of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are difficult for the CloudSat radar to detect due to surface contamination (Mace et al. 2007; Marchand et al. 2008). Therefore, the ARM ground-based cloud observations can provide important observations of clouds that complement measurements from space.« less

Cloud radiative effects and changes simulated by the Coupled Model Intercomparison Project Phase 5 models

NASA Astrophysics Data System (ADS)

Shin, Sun-Hee; Kim, Ok-Yeon; Kim, Dongmin; Lee, Myong-In

2017-07-01

Using 32 CMIP5 (Coupled Model Intercomparison Project Phase 5) models, this study examines the veracity in the simulation of cloud amount and their radiative effects (CREs) in the historical run driven by observed external radiative forcing for 1850-2005, and their future changes in the RCP (Representative Concentration Pathway) 4.5 scenario runs for 2006-2100. Validation metrics for the historical run are designed to examine the accuracy in the representation of spatial patterns for climatological mean, and annual and interannual variations of clouds and CREs. The models show large spread in the simulation of cloud amounts, specifically in the low cloud amount. The observed relationship between cloud amount and the controlling large-scale environment are also reproduced diversely by various models. Based on the validation metrics, four models—ACCESS1.0, ACCESS1.3, HadGEM2-CC, and HadGEM2-ES—are selected as best models, and the average of the four models performs more skillfully than the multimodel ensemble average. All models project global-mean SST warming at the increase of the greenhouse gases, but the magnitude varies across the simulations between 1 and 2 K, which is largely attributable to the difference in the change of cloud amount and distribution. The models that simulate more SST warming show a greater increase in the net CRE due to reduced low cloud and increased incoming shortwave radiation, particularly over the regions of marine boundary layer in the subtropics. Selected best-performing models project a significant reduction in global-mean cloud amount of about -0.99% K-1 and net radiative warming of 0.46 W m-2 K-1, suggesting a role of positive feedback to global warming.

Development and initial test of the University of Wisconsin global isentropic-sigma model

NASA Technical Reports Server (NTRS)

Zapotocny, Tom H.; Johnson, Donald R.; Reames, Fred M.

1994-01-01

The description of a global version of the University of Wisconsin (UW) hybrid isentropic-sigma (theta-sigma) model and the results from an initial numerical weather prediction experiment are presented in this paper. The main objectives of this initial test are to (1) discuss theta-sigma model development and computer requirements, (2) demonstrate the ability of the UW theta-sigma model for global numerical weather prediction using realistic orography and parameterized physical processes, and (3) compare the transport of an inert trace constituent against a nominally 'identical' sigma coordinate model. Initial and verifying data for the 5-day simulations presented in this work were supplied by the Goddard Earth Observing System (GEOS-1) data assimilation system. The time period studied is 1-6 February 1985. This validation experiment demonstrates that the global UW theta-sigma model produces a realistic 5-day simulation of the mass and momentum distributions when compared to both the identical sigma model and GEOS-1 verification. Root-mean-square errors demonstrate that the theta-sigma model is slightly more accurate than the nominally identical sigma model with respect to standard synoptic variables. Of particular importance, the UW theta-sigma model displays a distinct advantage over the conventional sigma model with respect to the prognostic simulation of inert trace constituent transport in amplifying baroclinic waves of the extratropics. This is especially true in the upper troposphere and stratosphere where the spatial integrity and conservation of an inert trace constituent is severely compromised in the sigma model compared to the theta-sigma model.

Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes

USDA-ARS?s Scientific Manuscript database

A reasonable representation of crop phenology and biophysical processes in land surface models is necessary to accurately simulate energy, water and carbon budgets at the field, regional, and global scales. However, the evaluation of crop models that can be coupled to earth system models is relative...

Insights into low-latitude cloud feedbacks from high-resolution models.

PubMed

Bretherton, Christopher S

2015-11-13

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes. © 2015 The Author(s).

Numerical simulation of a two-sex human papillomavirus (HPV) vaccination model

NASA Astrophysics Data System (ADS)

Suryani, I.; Adi-Kusumo, F.

2014-02-01

Human Papillomavirus (HPV) is a major cause of cervical cancer, precancerous lesions, cancer and other disease. HPV is the most common sexually transmitted infection. Although HPV virus primarily affects woman but it can also affects man because it cause of cancer of the anus, vulva, vagina, penis and some other cancers. HPV vaccines now used to prevent cervical cancer and genital warts because the vaccine protect against four types of HPV that most commonly cause disease are types 6, 11, 16, and 18. This paper is sequel work of Elbasha (2008). Difference with Elbasha (2008) are give alternative proof global stability, numerical simulation and interpretation. Global stability of the equilibrium on the model of a two-sex HPV vaccination were explored by using Lyapunov. Although we use the same lyapunov function, we use the largest invariant set to proof the global stability. The result show that the global stability of the equilibrium depends on the effective reproduction number (R). If R < 1 then the infection-free equilibrium is asymptotically stable globally. If R > 1 then endemic equilibrium have globally asymptotically stable properties. Then equilibrium proceed with the interpretation of numerical simulation.

Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model.

PubMed

Sato, Yousuke; Goto, Daisuke; Michibata, Takuro; Suzuki, Kentaroh; Takemura, Toshihiko; Tomita, Hirofumi; Nakajima, Teruyuki

2018-03-07

Aerosols affect climate by modifying cloud properties through their role as cloud condensation nuclei or ice nuclei, called aerosol-cloud interactions. In most global climate models (GCMs), the aerosol-cloud interactions are represented by empirical parameterisations, in which the mass of cloud liquid water (LWP) is assumed to increase monotonically with increasing aerosol loading. Recent satellite observations, however, have yielded contradictory results: LWP can decrease with increasing aerosol loading. This difference implies that GCMs overestimate the aerosol effect, but the reasons for the difference are not obvious. Here, we reproduce satellite-observed LWP responses using a global simulation with explicit representations of cloud microphysics, instead of the parameterisations. Our analyses reveal that the decrease in LWP originates from the response of evaporation and condensation processes to aerosol perturbations, which are not represented in GCMs. The explicit representation of cloud microphysics in global scale modelling reduces the uncertainty of climate prediction.

Trans-Pacific transport and evolution of aerosols: evaluation of quasi-global WRF-Chem simulation with multiple observations

NASA Astrophysics Data System (ADS)

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; Leung, L. Ruby; Qian, Yun; Yu, Hongbin; Huang, Lei; Kalashnikova, Olga V.

2016-05-01

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010-2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols. The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010-2014 averaged over three Pacific sub-regions. The evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.

A database and tool for boundary conditions for regional air quality modeling: description and evaluation

NASA Astrophysics Data System (ADS)

Henderson, B. H.; Akhtar, F.; Pye, H. O. T.; Napelenok, S. L.; Hutzell, W. T.

2013-09-01

Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available observations are too sparse vertically to provide boundary information, particularly for ozone precursors, but global simulations can be used to generate spatially and temporally varying Lateral Boundary Conditions (LBC). This study presents a public database of global simulations designed and evaluated for use as LBC for air quality models (AQMs). The database covers the contiguous United States (CONUS) for the years 2000-2010 and contains hourly varying concentrations of ozone, aerosols, and their precursors. The database is complimented by a tool for configuring the global results as inputs to regional scale models (e.g., Community Multiscale Air Quality or Comprehensive Air quality Model with extensions). This study also presents an example application based on the CONUS domain, which is evaluated against satellite retrieved ozone vertical profiles. The results show performance is largely within uncertainty estimates for the Tropospheric Emission Spectrometer (TES) with some exceptions. The major difference shows a high bias in the upper troposphere along the southern boundary in January. This publication documents the global simulation database, the tool for conversion to LBC, and the fidelity of concentrations on the boundaries. This documentation is intended to support applications that require representation of long-range transport of air pollutants.

Assessing Climate Change Risks Using a Multi-Model Approach

NASA Astrophysics Data System (ADS)

Knorr, W.; Scholze, M.; Prentice, C.

2007-12-01

We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from the IPCC AR4 data archive using 16 climate models and mapping the proportions of model runs showing exceedance of natural variability in wildfire frequency and freshwater supply or shifts in vegetation cover. Our analysis does not assign probabilities to scenarios. Instead, we consider the distribution of outcomes within three sets of model runs grouped according to the amount of global warming they simulate: < 2 degree C (including committed climate change simulations), 2-3 degree C, and >3 degree C. Here, we are contrasting two different methods for calculating the risks: first we use an equal weighting approach giving every model within one of the three sets the same weight, and second, we weight the models according to their ability to model ENSO. The differences are underpinning the need for the development of more robust performance metrics for global climate models.

Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

NASA Astrophysics Data System (ADS)

Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.

2017-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

Global two dimensional chemistry model and simulation of atmospheric chemical composition

NASA Astrophysics Data System (ADS)

Zhang, Renjian; Wang, Mingxing; Zeng, Qingcun

2000-03-01

A global two-dimensional zonally averaged chemistry model is developed to study the chemi-cal composition of atmosphere. The region of the model is from 90°S to 90°N and from the ground to the altitude of 20 km with a resolution of 5° x 1 km. The wind field is residual circulation calcu-lated from diabatic rate. 34 species and 104 chemical and photochemical reactions are considered in the model. The sources of CH4, CO and NOx, which are divided into seasonal sources and non-seasonal sources, are parameterized as a function of latitude and time. The chemical composi-tion of atmosphere was simulated with emission level of CH4, CO and NOx in 1990. The results are compared with observations and other model results, showing that the model is successful to simu-late the atmospheric chemical composition and distribution of CH4.

Global Mean Temperature Timeseries Projections from GCMs: The Implications of Rebasing

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2017-12-01

Global climate models are assessed by comparison with observations through several benchmarks. One highlighted by the InterGovernmental Panel on Climate Change (IPCC) is their ability to reproduce "general features of the global and annual mean surface temperature changes over the historical period" [1,2] and to simulate "a trend in global-mean surface temperature from 1951 to 2012 that agrees with the observed trend" [3]. These aspects of annual mean global mean temperature (GMT) change are presented as one feature demonstrating the relevance of these models for climate projections. Here we consider a formal interpretation of "general features" and discuss the implications of this approach to model assessment and intercomparison, for the interpretation of GCM projections. Following the IPCC, we interpret a major element of "general features" as being the slow timescale response to external forcings. (Shorter timescale behaviour such as the response to volcanic eruptions are also elements of "general features" but are not considered here.) Also following the IPCC, we consider only GMT anomalies. The models have absolute temperatures which range over about 3K so this means their timeseries (and the observations) are rebased. We show that rebasing in combination with general agreement, implies a separation of scales which limits the degree to which sub-global behaviour can feedback on the global response. It also implies a degree of linearity in the GMT slow timescale response. For each individual model these implications only apply over the range of absolute temperatures simulated by the model in historic simulations. Taken together, however, they imply consequences over a wider range of GMTs. [1] IPCC, Fifth Assessment Report, Working Group 1, Technical Summary: Stocker et al. 2013. [2] IPCC, Fifth Assessment Report, Working Group 1, Chapter 9 - "Evaluation of Climate Models": Flato et al. 2013. [3] IPCC, Fifth Assessment Report, Working Group 1, Summary for Policy Makers: IPCC, 2013.

Constraints Pb-210 and Be-7 on Wet Deposition and Transport in a Global Three-Dimensional Chemical Tracer Model Driven by Assimilated Meteorological Fields

NASA Technical Reports Server (NTRS)

Liu, Hong-Yu; Jacob, Daniel J.; Bey, Isabelle; Yantosca, Robert M.

2001-01-01

The atmospheric distributions of the aerosol tracers Pb-210 and Be-7 are simulated with a global three-dimensional model driven by assimilated meteorological observations for 1991-1996 from the NASA Goddard Earth Observing System (GEOSl). The combination of terrigenic Pb-210 and cosmogenic Be-7 provides a sensitive test of wet deposition and vertical transport in the model. Our simulation of moist transport and removal includes scavenging in wet convective updrafts (40% scavenging efficiency per kilometer of updraft), midlevel entrainment and detrainment, first-order rainout and washout from both convective anvils and large-scale precipitation, and cirrus precipitation. Observations from surface sites in specific years are compared to model results for the corresponding meteorological years, and observations from aircraft missions over the Pacific are compared to model results for the days of the flights. Initial simulation of Be-7 showed that cross-tropopause transport in the GEOSl meteorological fields is too fast by a factor of 3-4. We adjusted the stratospheric Be-7 source to correct the tropospheric simulation. Including this correction, we find that the model gives a good simulation of observed Pb-210 and Be-7 concentrations and deposition fluxes at surface sites worldwide, with no significant global bias and with significant success in reproducing the observed latitudinal and seasonal distributions. We achieve several improvements over previous models; in particular, we reproduce the observed Be-7 minimum in the tropics and show that its simulation is sensitive to rainout from convective anvils. Comparisons with aircraft observations up to 12-km altitude suggest that cirrus precipitation could be important for explaining the low concentrations in the middle and upper troposphere.

Computer simulations of space-borne meteorological systems on the CYBER 205

NASA Technical Reports Server (NTRS)

Halem, M.

1984-01-01

Because of the extreme expense involved in developing and flight testing meteorological instruments, an extensive series of numerical modeling experiments to simulate the performance of meteorological observing systems were performed on CYBER 205. The studies compare the relative importance of different global measurements of individual and composite systems of the meteorological variables needed to determine the state of the atmosphere. The assessments are made in terms of the systems ability to improve 12 hour global forecasts. Each experiment involves the daily assimilation of simulated data that is obtained from a data set called nature. This data is obtained from two sources: first, a long two-month general circulation integration with the GLAS 4th Order Forecast Model and second, global analysis prepared by the National Meteorological Center, NOAA, from the current observing systems twice daily.

The global nonmethane reactive organic carbon budget: A modeling perspective

NASA Astrophysics Data System (ADS)

Safieddine, Sarah A.; Heald, Colette L.; Henderson, Barron H.

2017-04-01

The cycling of reactive organic carbon (ROC) is central to tropospheric chemistry. We characterize the global tropospheric ROC budget as simulated with the GEOS-Chem model. We expand the standard simulation by including new emissions and gas-phase chemistry, an expansion of dry and wet removal, and a mass tracking of all ROC species to achieve carbon closure. The resulting global annual mean ROC burden is 16 Tg C, with sources from methane oxidation and direct emissions contributing 415 and 935 Tg C yr-1. ROC is lost from the atmosphere via physical deposition (460 Tg C yr-1), and oxidation to CO/CO2 (875 Tg C yr-1). Ketones, alkanes, alkenes, and aromatic hydrocarbons dominate the ROC burden, whereas aldehydes and isoprene dominate the ROC global mean surface OH reactivity. Simulated OH reactivities are between 0.8-1 s-1, 3-14 s-1, and 12-34 s-1 over selected regions in the remote ocean, continental midlatitudes, and the tropics, respectively, and are consistent with observational constraints.

Evaluation of methodology for detecting/predicting migration of forest species

Treesearch

Dale S. Solomon; William B. Leak

1996-01-01

Available methods for analyzing migration of forest species are evaluated, including simulation models, remeasured plots, resurveys, pollen/vegetation analysis, and age/distance trends. Simulation models have provided some of the most drastic estimates of species changes due to predicted changes in global climate. However, these models require additional testing...

: “Developing Regional Modeling Techniques Applicable for Simulating Future Climate Conditions in the Carolinas”

EPA Science Inventory

Global climate models (GCMs) are currently used to obtain information about future changes in the large-scale climate. However, such simulations are typically done at coarse spatial resolutions, with model grid boxes on the order of 100 km on a horizontal side. Therefore, techniq...

Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation modelORCHIDEE - Part 1: Simulating historical global burned area and fire regimes

Treesearch

C. Yue; P. Ciais; P. Cadule; K. Thonicke; S. Archibald; B. Poulter; W. M. Hao; S. Hantson; F. Mouillot; P. Friedlingstein; F. Maignan; N. Viovy

2014-01-01

Fire is an important global ecological process that influences the distribution of biomes, with consequences for carbon, water, and energy budgets. Therefore it is impossible to appropriately model the history and future of the terrestrial ecosystems and the climate system without including fire. This study incorporates the process-based prognostic fire module SPITFIRE...

A high resolution global scale groundwater model

NASA Astrophysics Data System (ADS)

de Graaf, Inge; Sutanudjaja, Edwin; van Beek, Rens; Bierkens, Marc

2014-05-01

As the world's largest accessible source of freshwater, groundwater plays a vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and supplies water for agricultural and industrial activities. During times of drought, groundwater storage provides a large natural buffer against water shortage and sustains flows to rivers and wetlands, supporting ecosystem habitats and biodiversity. Yet, the current generation of global scale hydrological models (GHMs) do not include a groundwater flow component, although it is a crucial part of the hydrological cycle. Thus, a realistic physical representation of the groundwater system that allows for the simulation of groundwater head dynamics and lateral flows is essential for GHMs that increasingly run at finer resolution. In this study we present a global groundwater model with a resolution of 5 arc-minutes (approximately 10 km at the equator) using MODFLOW (McDonald and Harbaugh, 1988). With this global groundwater model we eventually intend to simulate the changes in the groundwater system over time that result from variations in recharge and abstraction. Aquifer schematization and properties of this groundwater model were developed from available global lithological maps and datasets (Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moosdorf, 2013), combined with our estimate of aquifer thickness for sedimentary basins. We forced the groundwater model with the output from the global hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the net groundwater recharge and average surface water levels derived from routed channel discharge. For the parameterization, we relied entirely on available global datasets and did not calibrate the model so that it can equally be expanded to data poor environments. Based on our sensitivity analysis, in which we run the model with various hydrogeological parameter settings, we observed that most variance in groundwater depth is explained by variation in saturated conductivity, and, for the sediment basins, also by variation in recharge. We validated simulated groundwater heads with piezometer heads (available from www.glowasis.eu), resulting in a coefficient of determination for sedimentary basins of 0.92 with regression constant of 0.8. This shows the used method is suitable to build a global groundwater model using best available global information, and estimated water table depths are within acceptable accuracy in many parts of the world.

Applications of New Surrogate Global Optimization Algorithms including Efficient Synchronous and Asynchronous Parallelism for Calibration of Expensive Nonlinear Geophysical Simulation Models.

NASA Astrophysics Data System (ADS)

Shoemaker, C. A.; Pang, M.; Akhtar, T.; Bindel, D.

2016-12-01

New parallel surrogate global optimization algorithms are developed and applied to objective functions that are expensive simulations (possibly with multiple local minima). The algorithms can be applied to most geophysical simulations, including those with nonlinear partial differential equations. The optimization does not require simulations be parallelized. Asynchronous (and synchronous) parallel execution is available in the optimization toolbox "pySOT". The parallel algorithms are modified from serial to eliminate fine grained parallelism. The optimization is computed with open source software pySOT, a Surrogate Global Optimization Toolbox that allows user to pick the type of surrogate (or ensembles), the search procedure on surrogate, and the type of parallelism (synchronous or asynchronous). pySOT also allows the user to develop new algorithms by modifying parts of the code. In the applications here, the objective function takes up to 30 minutes for one simulation, and serial optimization can take over 200 hours. Results from Yellowstone (NSF) and NCSS (Singapore) supercomputers are given for groundwater contaminant hydrology simulations with applications to model parameter estimation and decontamination management. All results are compared with alternatives. The first results are for optimization of pumping at many wells to reduce cost for decontamination of groundwater at a superfund site. The optimization runs with up to 128 processors. Superlinear speed up is obtained for up to 16 processors, and efficiency with 64 processors is over 80%. Each evaluation of the objective function requires the solution of nonlinear partial differential equations to describe the impact of spatially distributed pumping and model parameters on model predictions for the spatial and temporal distribution of groundwater contaminants. The second application uses an asynchronous parallel global optimization for groundwater quality model calibration. The time for a single objective function evaluation varies unpredictably, so efficiency is improved with asynchronous parallel calculations to improve load balancing. The third application (done at NCSS) incorporates new global surrogate multi-objective parallel search algorithms into pySOT and applies it to a large watershed calibration problem.

An Integrated Modeling Suite for Simulating the Core Induction and Kinetic Effects in Mercury's Magnetosphere

NASA Astrophysics Data System (ADS)

Jia, X.; Slavin, J.; Chen, Y.; Poh, G.; Toth, G.; Gombosi, T.

2018-05-01

We present results from state-of-the-art global models of Mercury's space environment capable of self-consistently simulating the induction effect at the core and resolving kinetic physics important for magnetic reconnection.

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC

PubMed Central

Mukhtar, Hussnain; Lin, Yu-Pin; Shipin, Oleg V.; Petway, Joy R.

2017-01-01

This study presents an approach for obtaining realization sets of parameters for nitrogen removal in a pilot-scale waste stabilization pond (WSP) system. The proposed approach was designed for optimal parameterization, local sensitivity analysis, and global uncertainty analysis of a dynamic simulation model for the WSP by using the R software package Flexible Modeling Environment (R-FME) with the Markov chain Monte Carlo (MCMC) method. Additionally, generalized likelihood uncertainty estimation (GLUE) was integrated into the FME to evaluate the major parameters that affect the simulation outputs in the study WSP. Comprehensive modeling analysis was used to simulate and assess nine parameters and concentrations of ON-N, NH3-N and NO3-N. Results indicate that the integrated FME-GLUE-based model, with good Nash–Sutcliffe coefficients (0.53–0.69) and correlation coefficients (0.76–0.83), successfully simulates the concentrations of ON-N, NH3-N and NO3-N. Moreover, the Arrhenius constant was the only parameter sensitive to model performances of ON-N and NH3-N simulations. However, Nitrosomonas growth rate, the denitrification constant, and the maximum growth rate at 20 °C were sensitive to ON-N and NO3-N simulation, which was measured using global sensitivity. PMID:28704958

The global distribution of ecosystems in a world without fire.

PubMed

Bond, W J; Woodward, F I; Midgley, G F

2005-02-01

This paper is the first global study of the extent to which fire determines global vegetation patterns by preventing ecosystems from achieving the potential height, biomass and dominant functional types expected under the ambient climate (climate potential). To determine climate potential, we simulated vegetation without fire using a dynamic global-vegetation model. Model results were tested against fire exclusion studies from different parts of the world. Simulated dominant growth forms and tree cover were compared with satellite-derived land- and tree-cover maps. Simulations were generally consistent with results of fire exclusion studies in southern Africa and elsewhere. Comparison of global 'fire off' simulations with landcover and treecover maps show that vast areas of humid C(4) grasslands and savannas, especially in South America and Africa, have the climate potential to form forests. These are the most frequently burnt ecosystems in the world. Without fire, closed forests would double from 27% to 56% of vegetated grid cells, mostly at the expense of C(4) plants but also of C(3) shrubs and grasses in cooler climates. C(4) grasses began spreading 6-8 Ma, long before human influence on fire regimes. Our results suggest that fire was a major factor in their spread into forested regions, splitting biotas into fire tolerant and intolerant taxa.

Effects of data assimilation on the global aerosol key optical properties simulations

NASA Astrophysics Data System (ADS)

Yin, Xiaomei; Dai, Tie; Schutgens, Nick A. J.; Goto, Daisuke; Nakajima, Teruyuki; Shi, Guangyu

2016-09-01

We present the one month results of global aerosol optical properties for April 2006, using the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) coupled with the Non-hydrostatic ICosahedral Atmospheric Model (NICAM), by assimilating Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) with Local Ensemble Transform Kalman Filter (LETKF). The simulated AOD, Ångström Exponent (AE) and single scattering albedo (SSA) are validated by independent Aerosol Robotic Network (AERONET) observations over the global sites. The data assimilation has the strongest positive effect on the AOD simulation and slight positive influences on the AE and SSA simulations. For the time-averaged globally spatial distribution, the data assimilation increases the model skill score (S) of AOD, AE, and SSA from 0.55, 0.92, and 0.75 to 0.79, 0.94, and 0.80, respectively. Over the North Africa (NAF) and Middle East region where the aerosol composition is simple (mainly dust), the simulated AODs are best improved by the data assimilation, indicating the assimilation correctly modifies the wrong dust burdens caused by the uncertainties of the dust emission parameterization. Assimilation also improves the simulation of the temporal variations of the aerosol optical properties over the AERONET sites, with improved S at 60 (62%), 45 (55%) and 11 (50%) of 97, 82 and 22 sites for AOD, AE and SSA. By analyzing AOD and AE at five selected sites with best S improvement, this study further indicates that the assimilation can reproduce short duration events and ratios between fine and coarse aerosols more accurately.

COMPUTATION OF GLOBAL PHOTOCHEMISTRY WITH SMVGEAR II (R823186)

EPA Science Inventory

A computer model was developed to simulate global gas-phase photochemistry. The model solves chemical equations with SMVGEAR II, a sparse-matrix, vectorized Gear-type code. To obtain SMVGEAR II, the original SMVGEAR code was modified to allow computation of different sets of chem...

Link-prediction to tackle the boundary specification problem in social network surveys

PubMed Central

De Wilde, Philippe; Buarque de Lima-Neto, Fernando

2017-01-01

Diffusion processes in social networks often cause the emergence of global phenomena from individual behavior within a society. The study of those global phenomena and the simulation of those diffusion processes frequently require a good model of the global network. However, survey data and data from online sources are often restricted to single social groups or features, such as age groups, single schools, companies, or interest groups. Hence, a modeling approach is required that extrapolates the locally restricted data to a global network model. We tackle this Missing Data Problem using Link-Prediction techniques from social network research, network generation techniques from the area of Social Simulation, as well as a combination of both. We found that techniques employing less information may be more adequate to solve this problem, especially when data granularity is an issue. We validated the network models created with our techniques on a number of real-world networks, investigating degree distributions as well as the likelihood of links given the geographical distance between two nodes. PMID:28426826

Multimodel comparison of the ionosphere variability during the 2009 sudden stratosphere warming

NASA Astrophysics Data System (ADS)

Pedatella, N. M.; Fang, T.-W.; Jin, H.; Sassi, F.; Schmidt, H.; Chau, J. L.; Siddiqui, T. A.; Goncharenko, L.

2016-07-01

A comparison of different model simulations of the ionosphere variability during the 2009 sudden stratosphere warming (SSW) is presented. The focus is on the equatorial and low-latitude ionosphere simulated by the Ground-to-topside model of the Atmosphere and Ionosphere for Aeronomy (GAIA), Whole Atmosphere Model plus Global Ionosphere Plasmasphere (WAM+GIP), and Whole Atmosphere Community Climate Model eXtended version plus Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (WACCMX+TIMEGCM). The simulations are compared with observations of the equatorial vertical plasma drift in the American and Indian longitude sectors, zonal mean F region peak density (NmF2) from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites, and ground-based Global Positioning System (GPS) total electron content (TEC) at 75°W. The model simulations all reproduce the observed morning enhancement and afternoon decrease in the vertical plasma drift, as well as the progression of the anomalies toward later local times over the course of several days. However, notable discrepancies among the simulations are seen in terms of the magnitude of the drift perturbations, and rate of the local time shift. Comparison of the electron densities further reveals that although many of the broad features of the ionosphere variability are captured by the simulations, there are significant differences among the different model simulations, as well as between the simulations and observations. Additional simulations are performed where the neutral atmospheres from four different whole atmosphere models (GAIA, HAMMONIA (Hamburg Model of the Neutral and Ionized Atmosphere), WAM, and WACCMX) provide the lower atmospheric forcing in the TIME-GCM. These simulations demonstrate that different neutral atmospheres, in particular, differences in the solar migrating semidiurnal tide, are partly responsible for the differences in the simulated ionosphere variability in GAIA, WAM+GIP, and WACCMX+TIMEGCM.

Gap models and their individual-based relatives in the assessment of the consequences of global change

NASA Astrophysics Data System (ADS)

Shugart, Herman H.; Wang, Bin; Fischer, Rico; Ma, Jianyong; Fang, Jing; Yan, Xiaodong; Huth, Andreas; Armstrong, Amanda H.

2018-03-01

Individual-based models (IBMs) of complex systems emerged in the 1960s and early 1970s, across diverse disciplines from astronomy to zoology. Ecological IBMs arose with seemingly independent origins out of the tradition of understanding the ecosystems dynamics of ecosystems from a ‘bottom-up’ accounting of the interactions of the parts. Individual trees are principal among the parts of forests. Because these models are computationally demanding, they have prospered as the power of digital computers has increased exponentially over the decades following the 1970s. This review will focus on a class of forest IBMs called gap models. Gap models simulate the changes in forests by simulating the birth, growth and death of each individual tree on a small plot of land. The summation of these plots comprise a forest (or set of sample plots on a forested landscape or region). Other, more aggregated forest IBMs have been used in global applications including cohort-based models, ecosystem demography models, etc. Gap models have been used to provide the parameters for these bulk models. Currently, gap models have grown from local-scale to continental-scale and even global-scale applications to assess the potential consequences of climate change on natural forests. Modifications to the models have enabled simulation of disturbances including fire, insect outbreak and harvest. Our objective in this review is to provide the reader with an overview of the history, motivation and applications, including theoretical applications, of these models. In a time of concern over global changes, gap models are essential tools to understand forest responses to climate change, modified disturbance regimes and other change agents. Development of forest surveys to provide the starting points for simulations and better estimates of the behavior of the diversity of tree species in response to the environment are continuing needs for improvement for these and other IBMs.

Climate downscaling over South America for 1971-2000: application in SMAP rainfall-runoff model for Grande River Basin

NASA Astrophysics Data System (ADS)

da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio

2018-03-01

This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate model and that data from regional models must be bias-corrected so as to improve their results.

Solar wind interaction with Venus and Mars in a parallel hybrid code

NASA Astrophysics Data System (ADS)

Jarvinen, Riku; Sandroos, Arto

2013-04-01

We discuss the development and applications of a new parallel hybrid simulation, where ions are treated as particles and electrons as a charge-neutralizing fluid, for the interaction between the solar wind and Venus and Mars. The new simulation code under construction is based on the algorithm of the sequential global planetary hybrid model developed at the Finnish Meteorological Institute (FMI) and on the Corsair parallel simulation platform also developed at the FMI. The FMI's sequential hybrid model has been used for studies of plasma interactions of several unmagnetized and weakly magnetized celestial bodies for more than a decade. Especially, the model has been used to interpret in situ particle and magnetic field observations from plasma environments of Mars, Venus and Titan. Further, Corsair is an open source MPI (Message Passing Interface) particle and mesh simulation platform, mainly aimed for simulations of diffusive shock acceleration in solar corona and interplanetary space, but which is now also being extended for global planetary hybrid simulations. In this presentation we discuss challenges and strategies of parallelizing a legacy simulation code as well as possible applications and prospects of a scalable parallel hybrid model for the solar wind interactions of Venus and Mars.

The Impacts of a 2-Degree Rise in Global Temperatures upon Gas-Phase Air Pollutants in Europe

NASA Astrophysics Data System (ADS)

Watson, Laura; Josse, Béatrice; Marecal, Virginie; Lacressonnière, Gwendoline; Vautard, Robert; Gauss, Michael; Engardt, Magnuz; Nyiri, Agnes; Siour, Guillaume

2014-05-01

The 15th session of the Conference of Parties (COP 15) in 2009 ratified the Copenhagen Accord, which "recognises the scientific view that" global temperature rise should be held below 2 degrees C above pre-industrial levels in order to limit the impacts of climate change. Due to the fact that a 2-degree limit has been frequently referred to by policy makers in the context of the Copenhagen Accord and many other high-level policy statements, it is important that the impacts of this 2-degree increase in temperature are adequately analysed. To this end, the European Union sponsored the project IMPACT2C, which uses a multi-disciplinary international team to assess a wide variety of impacts of a 2-degree rise in global temperatures. For example, this future increase in temperature is expected to have a significant influence upon meteorological conditions such as temperature, precipitation, and wind direction and intensity; which will in turn affect the production, deposition, and distribution of air pollutants. For the first part of the air quality analysis within the IMPACT2C project, the impact of meteorological forcings on gas phase air pollutants over Europe was studied using four offline atmospheric chemistry transport models. Two sets of meteorological forcings were used for each model: reanalysis of past observation data and global climate model output. Anthropogenic emissions of ozone precursors for the year 2005 were used for all simulations in order to isolate the impact of meteorology and assess the robustness of the results across the different models. The differences between the simulations that use reanalysis of past observation data and the simulations that use global climate model output show how global climate models modify climate hindcasts by boundary conditions inputs: information that is necessary in order to interpret simulations of future climate. The baseline results were assessed by comparison with AirBase (Version 7) measurement data, and were then used as a reference for an analysis of future climate scenarios upon European air quality. The future scenarios included two types of emission data for the year 2050: one set of emission data corresponding to a current legislation scenario and another corresponding to a scenario with a maximum feasible reduction in emissions. The future scenarios were run for the time period that corresponds to a 2-degree increase in global temperatures; a time period that varies depending on which global climate model is used. In order to calculate the effect of climate change on emission reduction scenarios, the "climate penalty", the future simulations were compared to a simulation using the same future emissions but with current (2005) climate. Results show that climate change will have consequential impacts with regards to the production and geographical distribution of ozone and nitrogen oxides.

Bringing global gyrokinetic turbulence simulations to the transport timescale using a multiscale approach

NASA Astrophysics Data System (ADS)

Parker, Jeffrey B.; LoDestro, Lynda L.; Told, Daniel; Merlo, Gabriele; Ricketson, Lee F.; Campos, Alejandro; Jenko, Frank; Hittinger, Jeffrey A. F.

2018-05-01

The vast separation dividing the characteristic times of energy confinement and turbulence in the core of toroidal plasmas makes first-principles prediction on long timescales extremely challenging. Here we report the demonstration of a multiple-timescale method that enables coupling global gyrokinetic simulations with a transport solver to calculate the evolution of the self-consistent temperature profile. This method, which exhibits resiliency to the intrinsic fluctuations arising in turbulence simulations, holds potential for integrating nonlocal gyrokinetic turbulence simulations into predictive, whole-device models.

The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less

Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models

NASA Astrophysics Data System (ADS)

Kim, Go-Un; Seo, Kyong-Hwan

2018-01-01

A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

Resolving the Kinetic Reconnection Length Scale in Global Magnetospheric Simulations with MHD-EPIC

NASA Astrophysics Data System (ADS)

Toth, G.; Chen, Y.; Cassak, P.; Jordanova, V.; Peng, B.; Markidis, S.; Gombosi, T. I.

2016-12-01

We have recently developed a new modeling capability: the Magnetohydrodynamics with Embedded Particle-in-Cell (MHD-EPIC) algorithm with support from Los Alamos SHIELDS and NSF INSPIRE grants. We have implemented MHD-EPIC into the Space Weather Modeling Framework (SWMF) using the implicit Particle-in-Cell (iPIC3D) and the BATS-R-US extended magnetohydrodynamic codes. The MHD-EPIC model allows two-way coupled simulations in two and three dimensions with multiple embedded PIC regions. Both BATS-R-US and iPIC3D are massively parallel codes. The MHD-EPIC approach allows global magnetosphere simulations with embedded kinetic simulations. For small magnetospheres, like Ganymede or Mercury, we can easily resolve the ion scales around the reconnection sites. Modeling the Earth magnetosphere is very challenging even with our efficient MHD-EPIC model due to the large separation between the global and ion scales. On the other hand the large separation of scales may be exploited: the solution may not be sensitive to the ion inertial length as long as it is small relative to the global scales. The ion inertial length can be varied by changing the ion mass while keeping the MHD mass density, the velocity, and pressure the same for the initial and boundary conditions. Our two-dimensional MHD-EPIC simulations for the dayside reconnection region show in fact, that the overall solution is not sensitive to ion inertial length. The shape, size and frequency of flux transfer events are very similar for a wide range of ion masses. Our results mean that 3D MHD-EPIC simulations for the Earth and other large magnetospheres can be made computationally affordable by artificially increasing the ion mass: the required grid resolution and time step in the PIC model are proportional to the ion inertial length. Changing the ion mass by a factor of 4, for example, speeds up the PIC code by a factor of 256. In fact, this approach allowed us to perform an hour-long 3D MHD-EPIC simulations for the Earth magnetosphere.

Land cover maps, BVOC emissions, and SOA burden in a global aerosol-climate model

NASA Astrophysics Data System (ADS)

Stanelle, Tanja; Henrot, Alexandra; Bey, Isaelle

2015-04-01

It has been reported that different land cover representations influence the emission of biogenic volatile organic compounds (BVOC) (e.g. Guenther et al., 2006). But the land cover forcing used in model simulations is quite uncertain (e.g. Jung et al., 2006). As a consequence the simulated emission of BVOCs depends on the applied land cover map. To test the sensitivity of global and regional estimates of BVOC emissions on the applied land cover map we applied 3 different land cover maps into our global aerosol-climate model ECHAM6-HAM2.2. We found a high sensitivity for tropical regions. BVOCs are a very prominent precursor for the production of Secondary Organic Aerosols (SOA). Therefore the sensitivity of BVOC emissions on land cover maps impacts the SOA burden in the atmosphere. With our model system we are able to quantify that impact. References: Guenther et al. (2006), Estimates of global terrestrial isoprene emissions using MEGAN, Atmos. Chem. Phys., 6, 3181-3210, doi:10.5194/acp-6-3181-2006. Jung et al. (2006), Exploiting synergies of global land cover products for carbon cycle modeling, Rem. Sens. Environm., 101, 534-553, doi:10.1016/j.rse.2006.01.020.

Deep water tsunami simulation at global scale using an elastoacoustic approach

NASA Astrophysics Data System (ADS)

Salazar Monroy, E. F.; Ramirez-Guzman, L.; Bielak, J.; Sanchez-Sesma, F. J.

2017-12-01

In this work, we present the results for the first stage of a tsunami global simulation project using an elastoacoustic approach. The solid-fluid interaction, which is only valid on a global scale and far distances from the coast, is modelled using a finite element scheme for a 2D geometry. Comparing analytic and numerical solutions, we observe a good fit for a homogeneous domain - with an extension of 20 km - using 15 points per wavelength. Subsequently, we performed 2D realizations taking a section from a global 3D model and projecting the Tohoku-Oki source obtained by the USGS. The 3D Global model uses the ETOPO1 and the Preliminary Reference Earth Model (Dziewonski and Anderson, 1981). We analysed 3 cross sections, defined using DART buoys as a reference for each section (i.e., initial and final profile point). Surface water elevation obtained with this coupling strategy is constrained at low frequencies (0.2 Hz). We expect that this coupling strategy could approximate the model to high frequencies and realistic scenarios considering other geometries (i.e., 3D) and a complete domain (i.e., surface and deep).

Modeling CO 2 emissions from Arctic lakes: Model development and site-level study

DOE PAGES

Tan, Zeli; Zhuang, Qianlai; Shurpali, Narasinha J.; ...

2017-09-14

Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one-dimensional process-based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO 2 fluxes from the study Arctic lakes. The simulated area-weighted CO 2 fluxes from yedoma thermokarst lakes, nonyedoma thermokarst lakes, and glacial lakes aremore » 29.5, 13.0, and 21.4 g C m -2 yr -1, respectively, close to the observed values (31.2, 17.2, and 16.5 ± 7.7 g C m -2 yr -1, respectively). The simulations show that the high CO 2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight-induced organic carbon degradation is more important for shallow nonyedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM can simulate the whole-lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.« less

Modelling water use in global hydrological models: review, challenges and directions

NASA Astrophysics Data System (ADS)

Bierkens, M. F.; de Graaf, I.; Wada, Y.; Wanders, N.; Van Beek, L. P.

2017-12-01

During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments using regional statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand for agriculture, industry and households. In this talk we review the evolution of human impact modelling in global land models with a focus on global water resources, touching upon developments of the last 15 years: i.e. calculating human water scarcity; estimating groundwater depletion; adding dams and reservoirs; fully integrating water use (demand, withdrawal, consumption, return flow) in the hydrology; simulating the effects of land use change. We show example studies for each of these steps. We identify We identify major challenges that hamper the further development of integrated water resources modelling. Examples of these are: 1) simulating reservoir operations; 2) including local infrastructure and redistribution; 3) using the correct allocations rules; 4) projecting future water demand and water use. For each of these challenges we signify promising directions for further research.

Evaluating the Credibility of Transport Processes in the Global Modeling Initiative 3D Model Simulations of Ozone Recovery

NASA Technical Reports Server (NTRS)

Strahan, Susan E.; Douglass, Anne R.

2003-01-01

The Global Modeling Initiative has integrated two 35-year simulations of an ozone recovery scenario with an offline chemistry and transport model using two different meteorological inputs. Physically based diagnostics, derived from satellite and aircraft data sets, are described and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barrier formation in the subtropics and polar regions, and extratropical wave-driven transport. Some diagnostics are especially relevant to simulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of meteorological fields have near climatological values at all latitudes and seasons at 30 hPa and below. Both simulations showed weakness in upper stratospheric wave driving. The simulation using input from a general circulation model (GMI(sub GCM)) showed a very good residual circulation in the tropics and northern hemisphere. The simulation with input from a data assimilation system (GMI(sub DAS)) performed better in the midlatitudes than at high latitudes. Neither simulation forms a realistic barrier at the vortex edge, leading to uncertainty in the fate of ozone-depleted vortex air. Overall, tracer transport in the offline GMI(sub GCM) has greater fidelity throughout the stratosphere than the GMI(sub DAS).

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE PAGES

Dai, Heng; Ye, Ming; Walker, Anthony P.; ...

2017-03-28

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

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

Dai, Heng; Ye, Ming; Walker, Anthony P.

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Impacts of global warming on boreal larch forest in East Siberia: simulations with a coupled carbon cycle and fire regime model

NASA Astrophysics Data System (ADS)

Ito, A.

2005-12-01

Boreal forest is one of the focal areas in the study of global warming and carbon cycle. In this study, a coupled carbon cycle and fire regime model was developed and applied to a larch forest in East Siberia, near Yakutsk. Fire regime is simulated with a cellular automaton (20 km x 20 km), in which fire ignition, propagation, and extinction are parameterized in a stochastic manner, including the effects of fuel accumulation and weather condition. For each grid, carbon cycle is simulated with a 10-box scheme, in which net biome production by photosynthesis, respiration, decomposition, and biomass burning are calculated explicitly. Model parameters were calibrated with field data of biomass, litter stock, and fire statistics; the carbon cycle scheme was examined with flux measurement data. As a result, the model successfully captured average carbon stocks, productivity, fire frequency, and biomass burning. To assess the effects of global warming, a series of simulations were performed using climatic projections based on the IPCC-SRES emission scenarios from 1990 to 2100. The range of uncertainty among the different climate models and emission scenarios was assessed by using multi-model projection data by CCCma, CCSR/NIES, GFDL, and HCCPR corresponding to the SRES A2 and B2 scenarios. The model simulations showed that global warming in the 21st century would considerably enhance the fire regime (e.g., cumulative burnt area increased by 80 to 120 percent), leading to larger carbon emission by biomass burning. The effect was so strong that growth enhancement by elevated atmospheric CO2 concentration and elongated growing period was cancelled out at landscape scale. In many cases, the larch forest was estimated to act as net carbon sources of 2 to 5 kg C m_|2 by the end of the 21st century, underscoring the importance of forest fire monitoring and management in this region.

GMMIP (v1.0) contribution to CMIP6: Global Monsoons Model Inter-comparison Project

NASA Astrophysics Data System (ADS)

Zhou, Tianjun; Turner, Andrew G.; Kinter, James L.; Wang, Bin; Qian, Yun; Chen, Xiaolong; Wu, Bo; Wang, Bin; Liu, Bo; Zou, Liwei; He, Bian

2016-10-01

The Global Monsoons Model Inter-comparison Project (GMMIP) has been endorsed by the panel of Coupled Model Inter-comparison Project (CMIP) as one of the participating model inter-comparison projects (MIPs) in the sixth phase of CMIP (CMIP6). The focus of GMMIP is on monsoon climatology, variability, prediction and projection, which is relevant to four of the "Grand Challenges" proposed by the World Climate Research Programme. At present, 21 international modeling groups are committed to joining GMMIP. This overview paper introduces the motivation behind GMMIP and the scientific questions it intends to answer. Three tiers of experiments, of decreasing priority, are designed to examine (a) model skill in simulating the climatology and interannual-to-multidecadal variability of global monsoons forced by the sea surface temperature during historical climate period; (b) the roles of the Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation in driving variations of the global and regional monsoons; and (c) the effects of large orographic terrain on the establishment of the monsoons. The outputs of the CMIP6 Diagnostic, Evaluation and Characterization of Klima experiments (DECK), "historical" simulation and endorsed MIPs will also be used in the diagnostic analysis of GMMIP to give a comprehensive understanding of the roles played by different external forcings, potential improvements in the simulation of monsoon rainfall at high resolution and reproducibility at decadal timescales. The implementation of GMMIP will improve our understanding of the fundamental physics of changes in the global and regional monsoons over the past 140 years and ultimately benefit monsoons prediction and projection in the current century.

Impact of Assimilation on Heavy Rainfall Simulations Using WRF Model: Sensitivity of Assimilation Results to Background Error Statistics

NASA Astrophysics Data System (ADS)

Rakesh, V.; Kantharao, B.

2017-03-01

Data assimilation is considered as one of the effective tools for improving forecast skill of mesoscale models. However, for optimum utilization and effective assimilation of observations, many factors need to be taken into account while designing data assimilation methodology. One of the critical components that determines the amount and propagation observation information into the analysis, is model background error statistics (BES). The objective of this study is to quantify how BES in data assimilation impacts on simulation of heavy rainfall events over a southern state in India, Karnataka. Simulations of 40 heavy rainfall events were carried out using Weather Research and Forecasting Model with and without data assimilation. The assimilation experiments were conducted using global and regional BES while the experiment with no assimilation was used as the baseline for assessing the impact of data assimilation. The simulated rainfall is verified against high-resolution rain-gage observations over Karnataka. Statistical evaluation using several accuracy and skill measures shows that data assimilation has improved the heavy rainfall simulation. Our results showed that the experiment using regional BES outperformed the one which used global BES. Critical thermo-dynamic variables conducive for heavy rainfall like convective available potential energy simulated using regional BES is more realistic compared to global BES. It is pointed out that these results have important practical implications in design of forecast platforms while decision-making during extreme weather events

Spectral decomposition of internal gravity wave sea surface height in global models

NASA Astrophysics Data System (ADS)

Savage, Anna C.; Arbic, Brian K.; Alford, Matthew H.; Ansong, Joseph K.; Farrar, J. Thomas; Menemenlis, Dimitris; O'Rourke, Amanda K.; Richman, James G.; Shriver, Jay F.; Voet, Gunnar; Wallcraft, Alan J.; Zamudio, Luis

2017-10-01

Two global ocean models ranging in horizontal resolution from 1/12° to 1/48° are used to study the space and time scales of sea surface height (SSH) signals associated with internal gravity waves (IGWs). Frequency-horizontal wavenumber SSH spectral densities are computed over seven regions of the world ocean from two simulations of the HYbrid Coordinate Ocean Model (HYCOM) and three simulations of the Massachusetts Institute of Technology general circulation model (MITgcm). High wavenumber, high-frequency SSH variance follows the predicted IGW linear dispersion curves. The realism of high-frequency motions (>0.87 cpd) in the models is tested through comparison of the frequency spectral density of dynamic height variance computed from the highest-resolution runs of each model (1/25° HYCOM and 1/48° MITgcm) with dynamic height variance frequency spectral density computed from nine in situ profiling instruments. These high-frequency motions are of particular interest because of their contributions to the small-scale SSH variability that will be observed on a global scale in the upcoming Surface Water and Ocean Topography (SWOT) satellite altimetry mission. The variance at supertidal frequencies can be comparable to the tidal and low-frequency variance for high wavenumbers (length scales smaller than ˜50 km), especially in the higher-resolution simulations. In the highest-resolution simulations, the high-frequency variance can be greater than the low-frequency variance at these scales.

Impact of global warming on tropical cyclone genesis in coupled and forced simulations: role of SST spatial anomalies

NASA Astrophysics Data System (ADS)

Royer, Jean-François; Chauvin, Fabrice; Daloz, Anne-Sophie

2010-05-01

The response of tropical cyclones (TC) activity to global warming has not yet reached a clear consensus in the Fourth Assessment Report (AR4) published by the Intergovernmental Panel on Climate Change (IPCC, 2007) or in the recent scientific literature. Observed series are neither long nor reliable enough for a statistically significant detection and attribution of past TC trends, and coupled climate models give widely divergent results for the future evolution of TC activity in the different ocean basins. The potential importance of the spatial structure of the future SST warming has been pointed out by Chauvin et al. (2006) in simulations performed at CNRM with the ARPEGE-Climat GCM. The current presentation describes a new set of simulations that have been performed with the ARPEGE-Climat model to try to understand the possible role of SST patterns in the TC cyclogenesis response in 15 CMIP3 coupled simulations analysed by Royer et al (2009). The new simulations have been performed with the atmospheric component of the ARPEGE-Climat GCM forced in 10 year simulations by the SST patterns from each of 15 CMIP3 simulations with different climate model at the end of the 21st century according to scenario A2. The TC analysis is based on the computation of a Convective Yearly Genesis Parameter (CYGP) and the Genesis Potential Index (GPI). The computed genesis indices for each of the ARPEGE-Climat forced simulations is compared with the indices computed directly from the initial coupled simulation. The influence of SST patterns can then be more easily assessed since all the ARPEGE-Climat simulations are performed with the same atmospheric model, whereas the original simulations used models with different parameterization and resolutions. The analysis shows that CYGP or GPI anomalies obtained with ARPEGE are as variable between each other as those obtained originally by the different IPCC models. The variety of SST patterns used to force ARPEGE explains a large part of the dispersion, though for a given SST pattern, ARPEGE does not necessarily reproduce the anomaly produced originally by the IPCC model which produced the SST anomaly. Many factors can contribute to this discrepancy, but the most prominent seems to be the absence of coupling between the forced atmospheric ARPEGE simulation and the underlying ocean. When the atmospheric model is forced by prescribed SST anomalies some retroactions between cyclogenesis and ocean are missing. There are however areas over the globe were models agree about the CYGP or GPI anomalies induced by global warming, such as the Indian Ocean that shows a better coherency in the coupled and forced responses. This could be an indication that interaction between ocean and atmosphere is not as strong there as in the other basins. Details of the results for all the other ocean basins will be presented. References: Chauvin F. and J.-F. Royer and M. Déqué , 2006: Response of hurricane-type vortices to global warming as simulated by ARPEGE-Climat at high resolution. Climate Dynamics 27(4), 377-399. IPCC [Intergovernmental Panel for Climate Change], Climate change 2007: The physical science basis, in: S. Solomon et al. (eds.), Cambridge University Press. Royer JF, F Chauvin, 2009: Response of tropical cyclogenesis to global warming in an IPCC AR-4 scenario assessed by a modified yearly genesis parameter. "Hurricanes and Climate Change", J. B. Elsner and T. H. Jagger (Eds.), Springer, ISBN: 978-0-387-09409-0, pp 213-234.

Co-variation of Temperature and Precipitation in CMIP5 Models and Satellite Observations

NASA Technical Reports Server (NTRS)

Liu, Chunlei; Allan, Richard P.; Huffman, George J.

2013-01-01

Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled (CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates.There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5)simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 % K for simulations and 3-4 % K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Nio Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (greater than or equal to 75 precipitation percentile), the precipitation response is 13-15%K for GPCP and 5%K for models while trends in P are 2.4% decade for GPCP, 0.6% decade for CMIP5 and 0.9decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

NASA Astrophysics Data System (ADS)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D. M. H.

2013-04-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10-90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

Development and application of process-based simulation models for cotton production: A review of past, present, and future directions

USDA-ARS?s Scientific Manuscript database

The development and application of cropping system simulation models for cotton production has a long and rich history, beginning in the southeast United States in the 1960's and now expanded to major cotton production regions globally. This paper briefly reviews the history of cotton simulation mo...

Simulating global and local surface temperature changes due to Holocene anthropogenic land cover change

NASA Astrophysics Data System (ADS)

He, F.; Vavrus, S. J.; Kutzbach, J. E.; Ruddiman, W. F.; Kaplan, J. O.; Krumhardt, K. M.

2015-12-01

Surface albedo changes from anthropogenic land cover change (ALCC) represent the second-largest negative radiative forcing behind aerosol during the industrial era. Using a new reconstruction of ALCC during the Holocene era by Kaplan et al. [2011], we quantify the local and global temperature response induced by Holocene ALCC in the Community Climate System Model, version 4 (CCSM4). With 1-degree resolution of the CCSM4 slab-ocean model,we find that Holocene ALCC cause a global cooling of 0.17 °C due to the biogeophysical effects of land-atmosphere exchange of momentum, moisture, radiative and heat fluxes. On the global scale, the biogeochemical effects of Holocene ALCC from carbon emissions dominate the biogeophysical effects by causing 0.9 °C global warming. The net effects of Holocene ALCC amount to a global warming of 0.73 °C during the pre-industrial era, which is comparable to the ~0.8 °C warming during industrial times. On local to regional scales, such as parts of Europe, North America and Asia, the biogeophysical effects of Holocene ALCC are significant and comparable to the biogeochemical effect. The lack of ocean dynamics in the 1° CCSM4 slab-ocean simulations could underestimate the climate sensitivity because of the lack of feedbacks from ocean heat transport [Kutzbach et al., 2013; Manabe and Bryan, 1985]. In 1° CCSM4 fully coupled simulations, the climate sensitivity is ~65% larger than the 1° CCSM4 slab-ocean simulations during the Holocene (5.3 °C versus 3.2 °C) [Kutzbach et al., 2013]. With this greater climate sensitivity, the biogeochemical effects of Holocene ALCC could have caused a global warming of ~1.5 °C, and the net biogeophysical and biogeochemical effects of Holocene ALCC could cause a global warming of 1.2 °C during the preindustrial era in our simulations, which is 50% higher than the global warming of ~0.8 °C during industrial times.

Next Generation Vehicle Positioning and Simulation Solutions : Using GPS and Advanced Simulation Tools to Improve Highway Safety

DOT National Transportation Integrated Search

2013-06-03

"Integrated Global Positioning System and Inertial Navigation Unit (GPS/INU) Simulator for Enhanced Traffic Safety," is a project awarded to Ohio State University to integrate different simulation models to accurately study the relationship between v...

Evaluation of preindustrial to present-day black carbon and its albedo forcing from Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

NASA Technical Reports Server (NTRS)

Lee, Y. H.; Lamarque, J.-F.; Flanner, M. G.; Jiao, C.; Shindell, D. T.; Bernsten, T.; Bisiaux, M. M.; Cao, J.; Collins, W. J.; Curran, M.;

The UK Earth System Model project

NASA Astrophysics Data System (ADS)

Tang, Yongming

2016-04-01

In this talk we will describe the development and current status of the UK Earth System Model (UKESM). This project is a NERC/Met Office collaboration and has two objectives; to develop and apply a world-leading Earth System Model, and to grow a community of UK Earth System Model scientists. We are building numerical models that include all the key components of the global climate system, and contain the important process interactions between global biogeochemistry, atmospheric chemistry and the physical climate system. UKESM will be used to make key CMIP6 simulations as well as long-time (e.g. millennium) simulations, large ensemble experiments and investigating a range of future carbon emission scenarios.

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

Sakaguchi, Koichi; Leung, Lai-Yung R.; Zhao, Chun

This study presents a diagnosis of a multi-resolution approach using the Model for Prediction Across Scales - Atmosphere (MPAS-A) for simulating regional climate. Four AMIP experiments are conducted for 1999-2009. In the first two experiments, MPAS-A is configured using global quasi-uniform grids at 120 km and 30 km grid spacing. In the other two experiments, MPAS-A is configured using variable-resolution (VR) mesh with local refinement at 30 km over North America and South America embedded inside a quasi-uniform domain at 120 km elsewhere. Precipitation and related fields in the four simulations are examined to determine how well the VR simulationsmore » reproduce the features simulated by the globally high-resolution model in the refined domain. In previous analyses of idealized aqua-planet simulations, the characteristics of the global high-resolution simulation in moist processes only developed near the boundary of the refined region. In contrast, the AMIP simulations with VR grids are able to reproduce the high-resolution characteristics across the refined domain, particularly in South America. This indicates the importance of finely resolved lower-boundary forcing such as topography and surface heterogeneity for the regional climate, and demonstrates the ability of the MPAS-A VR to replicate the large-scale moisture transport as simulated in the quasi-uniform high-resolution model. Outside of the refined domain, some upscale effects are detected through large-scale circulation but the overall climatic signals are not significant at regional scales. Our results provide support for the multi-resolution approach as a computationally efficient and physically consistent method for modeling regional climate.« less

Modeling the spatial spread of infectious diseases: the GLobal Epidemic and Mobility computational model

PubMed Central

Balcan, Duygu; Gonçalves, Bruno; Hu, Hao; Ramasco, José J.; Colizza, Vittoria

2010-01-01

Here we present the Global Epidemic and Mobility (GLEaM) model that integrates sociodemographic and population mobility data in a spatially structured stochastic disease approach to simulate the spread of epidemics at the worldwide scale. We discuss the flexible structure of the model that is open to the inclusion of different disease structures and local intervention policies. This makes GLEaM suitable for the computational modeling and anticipation of the spatio-temporal patterns of global epidemic spreading, the understanding of historical epidemics, the assessment of the role of human mobility in shaping global epidemics, and the analysis of mitigation and containment scenarios. PMID:21415939

Different Mechanisms of Soil Microbial Response to Global Change Result in Different Outcomes in the MIMICS-CN Model

NASA Astrophysics Data System (ADS)

Kyker-Snowman, E.; Wieder, W. R.; Grandy, S.

2017-12-01

Microbial-explicit models of soil carbon (C) and nitrogen (N) cycling have improved upon simulations of C and N stocks and flows at site-to-global scales relative to traditional first-order linear models. However, the response of microbial-explicit soil models to global change factors depends upon which parameters and processes in a model are altered by those factors. We used the MIcrobial-MIneral Carbon Stabilization Model with coupled N cycling (MIMICS-CN) to compare modeled responses to changes in temperature and plant inputs at two previously-modeled sites (Harvard Forest and Kellogg Biological Station). We spun the model up to equilibrium, applied each perturbation, and evaluated 15 years of post-perturbation C and N pools and fluxes. To model the effect of increasing temperatures, we independently examined the impact of decreasing microbial C use efficiency (CUE), increasing the rate of microbial turnover, and increasing Michaelis-Menten kinetic rates of litter decomposition, plus several combinations of the three. For plant inputs, we ran simulations with stepwise increases in metabolic litter, structural litter, whole litter (structural and metabolic), or labile soil C. The cumulative change in soil C or N varied in both sign and magnitude across simulations. For example, increasing kinetic rates of litter decomposition resulted in net releases of both C and N from soil pools, while decreasing CUE produced short-term increases in respiration but long-term accumulation of C in litter pools and shifts in soil C:N as microbial demand for C increased and biomass declined. Given that soil N cycling constrains the response of plant productivity to global change and that soils generate a large amount of uncertainty in current earth system models, microbial-explicit models are a critical opportunity to advance the modeled representation of soils. However, microbial-explicit models must be improved by experiments to isolate the physiological and stoichiometric parameters of soil microbes that shift under global change.

For how long can we predict the weather? - Insights into atmospheric predictability from global convection-allowing simulations

NASA Astrophysics Data System (ADS)

Judt, Falko

2017-04-01

A tremendous increase in computing power has facilitated the advent of global convection-resolving numerical weather prediction (NWP) models. Although this technological breakthrough allows for the seamless prediction of weather from local to global scales, the predictability of multiscale weather phenomena in these models is not very well known. To address this issue, we conducted a global high-resolution (4-km) predictability experiment using the Model for Prediction Across Scales (MPAS), a state-of-the-art global NWP model developed at the National Center for Atmospheric Research. The goals of this experiment are to investigate error growth from convective to planetary scales and to quantify the intrinsic, scale-dependent predictability limits of atmospheric motions. The globally uniform resolution of 4 km allows for the explicit treatment of organized deep moist convection, alleviating grave limitations of previous predictability studies that either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. Error growth is analyzed within the context of an "identical twin" experiment setup: the error is defined as the difference between a 20-day long "nature run" and a simulation that was perturbed with small-amplitude noise, but is otherwise identical. It is found that in convectively active regions, errors grow by several orders of magnitude within the first 24 h ("super-exponential growth"). The errors then spread to larger scales and begin a phase of exponential growth after 2-3 days when contaminating the baroclinic zones. After 16 days, the globally averaged error saturates—suggesting that the intrinsic limit of atmospheric predictability (in a general sense) is about two weeks, which is in line with earlier estimates. However, error growth rates differ between the tropics and mid-latitudes as well as between the troposphere and stratosphere, highlighting that atmospheric predictability is a complex problem. The comparatively slower error growth in the tropics and in the stratosphere indicates that certain weather phenomena could potentially have longer predictability than currently thought.

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

NASA Technical Reports Server (NTRS)

Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.;

Simulated and Observed Circulation in the Indonesian Seas: 1/12 degree Global HYCOM and the INSTANT Observations

DTIC Science & Technology

2010-01-01

Circulation in the Indonesian Seas: 1/12 degree Global HYCOM and the INSTANT Observations 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...SUPPLEMENTARY NOTES 14. ABSTRACT A l/l 2 global version of the HYbrid Coordinate Ocean Model (HYCOM) using 3-hourly atmospheric forcing is analyzed and...TERMS Indonesian Throughflow, global HYCOM, INSTANT, Inter-ocean exchange, ocean modeling 16. SECURITY CLASSIFICATION OF: a. REPORT Unclassified b

Concurrent Simulation of the Eddying General Circulation and Tides in a Global Ocean Model

DTIC Science & Technology

2010-01-01

Eddying General Circulation and Tides in a Global Ocean Model 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 0602435N 6...STATEMENT Approved for public release, distribution is unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT This paper presents a five-year global ...running 25-h average to approximately separate tidal and non-tidal components of the near-bottom flow. In contrast to earlier high-resolution global

Spatial Variability in Column CO2 Inferred from High Resolution GEOS-5 Global Model Simulations: Implications for Remote Sensing and Inversions

NASA Technical Reports Server (NTRS)

Ott, L.; Putman, B.; Collatz, J.; Gregg, W.

2012-01-01

Column CO2 observations from current and future remote sensing missions represent a major advancement in our understanding of the carbon cycle and are expected to help constrain source and sink distributions. However, data assimilation and inversion methods are challenged by the difference in scale of models and observations. OCO-2 footprints represent an area of several square kilometers while NASA s future ASCENDS lidar mission is likely to have an even smaller footprint. In contrast, the resolution of models used in global inversions are typically hundreds of kilometers wide and often cover areas that include combinations of land, ocean and coastal areas and areas of significant topographic, land cover, and population density variations. To improve understanding of scales of atmospheric CO2 variability and representativeness of satellite observations, we will present results from a global, 10-km simulation of meteorology and atmospheric CO2 distributions performed using NASA s GEOS-5 general circulation model. This resolution, typical of mesoscale atmospheric models, represents an order of magnitude increase in resolution over typical global simulations of atmospheric composition allowing new insight into small scale CO2 variations across a wide range of surface flux and meteorological conditions. The simulation includes high resolution flux datasets provided by NASA s Carbon Monitoring System Flux Pilot Project at half degree resolution that have been down-scaled to 10-km using remote sensing datasets. Probability distribution functions are calculated over larger areas more typical of global models (100-400 km) to characterize subgrid-scale variability in these models. Particular emphasis is placed on coastal regions and regions containing megacities and fires to evaluate the ability of coarse resolution models to represent these small scale features. Additionally, model output are sampled using averaging kernels characteristic of OCO-2 and ASCENDS measurement concepts to create realistic pseudo-datasets. Pseudo-data are averaged over coarse model grid cell areas to better understand the ability of measurements to characterize CO2 distributions and spatial gradients on both short (daily to weekly) and long (monthly to seasonal) time scales

A global model for steady state and transient S.I. engine heat transfer studies

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

Bohac, S.V.; Assanis, D.N.; Baker, D.M.

1996-09-01

A global, systems-level model which characterizes the thermal behavior of internal combustion engines is described in this paper. Based on resistor-capacitor thermal networks, either steady-state or transient thermal simulations can be performed. A two-zone, quasi-dimensional spark-ignition engine simulation is used to determine in-cylinder gas temperature and convection coefficients. Engine heat fluxes and component temperatures can subsequently be predicted from specification of general engine dimensions, materials, and operating conditions. Emphasis has been placed on minimizing the number of model inputs and keeping them as simple as possible to make the model practical and useful as an early design tool. The successmore » of the global model depends on properly scaling the general engine inputs to accurately model engine heat flow paths across families of engine designs. The development and validation of suitable, scalable submodels is described in detail in this paper. Simulation sub-models and overall system predictions are validated with data from two spark ignition engines. Several sensitivity studies are performed to determine the most significant heat transfer paths within the engine and exhaust system. Overall, it has been shown that the model is a powerful tool in predicting steady-state heat rejection and component temperatures, as well as transient component temperatures.« less

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

Tan, Zeli; Zhuang, Qianlai; Shurpali, Narasinha J.

Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one-dimensional process-based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO 2 fluxes from the study Arctic lakes. The simulated area-weighted CO 2 fluxes from yedoma thermokarst lakes, nonyedoma thermokarst lakes, and glacial lakes aremore » 29.5, 13.0, and 21.4 g C m -2 yr -1, respectively, close to the observed values (31.2, 17.2, and 16.5 ± 7.7 g C m -2 yr -1, respectively). The simulations show that the high CO 2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight-induced organic carbon degradation is more important for shallow nonyedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM can simulate the whole-lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.« less

A Multiscale Simulation Framework to Investigate Hydrobiogeochemical Processes in the Groundwater-Surface Water Interaction Zone

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Yang, X.; Song, X.; Chen, X.; Hammond, G. E.; Song, H. S.; Hou, Z.; Murray, C. J.; Tartakovsky, A. M.; Tartakovsky, G.; Yang, X.; Zachara, J. M.

2016-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

An Exospheric Temperature Model Based On CHAMP Observations and TIEGCM Simulations

NASA Astrophysics Data System (ADS)

Ruan, Haibing; Lei, Jiuhou; Dou, Xiankang; Liu, Siqing; Aa, Ercha

2018-02-01

In this work, thermospheric densities from the accelerometer measurement on board the CHAMP satellite during 2002-2009 and the simulations from the National Center for Atmospheric Research Thermosphere Ionosphere Electrodynamics General Circulation Model (NCAR-TIEGCM) are employed to develop an empirical exospheric temperature model (ETM). The two-dimensional basis functions of the ETM are first provided from the principal component analysis of the TIEGCM simulations. Based on the exospheric temperatures derived from CHAMP thermospheric densities, a global distribution of the exospheric temperatures is reconstructed. A parameterization is conducted for each basis function amplitude as a function of solar-geophysical and seasonal conditions. Thus, the ETM can be utilized to model the thermospheric temperature and mass density under a specified condition. Our results showed that the averaged standard deviation of the ETM is generally less than 10% than approximately 30% in the MSIS model. Besides, the ETM reproduces the global thermospheric evolutions including the equatorial thermosphere anomaly.

Evaluating the accuracy of climate change pattern emulation for low warming targets

NASA Astrophysics Data System (ADS)

Tebaldi, Claudia; Knutti, Reto

2018-05-01

Global climate policy is increasingly debating the value of very low warming targets, yet not many experiments conducted with global climate models in their fully coupled versions are currently available to help inform studies of the corresponding impacts. This raises the question whether a map of warming or precipitation change in a world 1.5 °C warmer than preindustrial can be emulated from existing simulations that reach higher warming targets, or whether entirely new simulations are required. Here we show that also for this type of low warming in strong mitigation scenarios, climate change signals are quite linear as a function of global temperature. Therefore, emulation techniques amounting to linear rescaling on the basis of global temperature change ratios (like simple pattern scaling) provide a viable way forward. The errors introduced are small relative to the spread in the forced response to a given scenario that we can assess from a multi-model ensemble. They are also small relative to the noise introduced into the estimates of the forced response by internal variability within a single model, which we can assess from either control simulations or initial condition ensembles. Challenges arise when scaling inadvertently reduces the inter-model spread or suppresses the internal variability, both important sources of uncertainty for impact assessment, or when the scenarios have very different characteristics in the composition of the forcings. Taking advantage of an available suite of coupled model simulations under low-warming and intermediate scenarios, we evaluate the accuracy of these emulation techniques and show that they are unlikely to represent a substantial contribution to the total uncertainty.

Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

NASA Astrophysics Data System (ADS)

Singh, U. K.; Singh, G. P.; Singh, Vikas

2015-04-01

The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread among the ensemble members of individual model, strong teleconnection (correlation analysis) with SST, coefficient of variation, inter-annual variability, analysis of Taylor diagram, etc. suggest that there is a need to improve coupled model instead of uncoupled model for the development of a better dynamical seasonal forecast system.

Tradeoffs in Acceleration and Initialization of Superparameterized Global Atmospheric Models for MJO and Climate Science

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Bretherton, C. S.; DeMott, C. A.

2014-12-01

New trade-offs are discussed in the cloud superparameterization approach to explicitly representing deep convection in global climate models. Intrinsic predictability tests show that the memory of cloud-resolving-scale organization is not critical for producing desired modes of organized convection such as the Madden-Julian Oscillation (MJO). This has implications for the feasibility of data assimilation and real-world initialization for superparameterized weather forecasting. Climate simulation sensitivity tests demonstrate that 400% acceleration of cloud superparameterization is possible by restricting the 32-128 km scale regime without deteriorating the realism of the simulated MJO but the number of cloud resolving model grid columns is discovered to constrain the efficiency of vertical mixing, with consequences for the simulated liquid cloud climatology. Tuning opportunities for next generation accelerated superparameterized climate models are discussed.

Updates on Modeling the Water Cycle with the NASA Ames Mars Global Climate Model

NASA Technical Reports Server (NTRS)

Kahre, M. A.; Haberle, R. M.; Hollingsworth, J. L.; Montmessin, F.; Brecht, A. S.; Urata, R.; Klassen, D. R.; Wolff, M. J.

2017-01-01

Global Circulation Models (GCMs) have made steady progress in simulating the current Mars water cycle. It is now widely recognized that clouds are a critical component that can significantly affect the nature of the simulated water cycle. Two processes in particular are key to implementing clouds in a GCM: the microphysical processes of formation and dissipation, and their radiative effects on heating/ cooling rates. Together, these processes alter the thermal structure, change the dynamics, and regulate inter-hemispheric transport. We have made considerable progress representing these processes in the NASA Ames GCM, particularly in the presence of radiatively active water ice clouds. We present the current state of our group's water cycle modeling efforts, show results from selected simulations, highlight some of the issues, and discuss avenues for further investigation.­

Changes in yields and their variability at different levels of global warming

NASA Astrophysics Data System (ADS)

Childers, Katelin

2015-04-01

An assessment of climate change impacts at different levels of global warming is crucial to inform the political discussion about mitigation targets as well as for the inclusion of climate change impacts in Integrated Assessment Models (IAMs) that generally only provide global mean temperature change as an indicator of climate change. While there is a well-established framework for the scalability of regional temperature and precipitation changes with global mean temperature change we provide an assessment of the extent to which impacts such as crop yield changes can also be described in terms of global mean temperature changes without accounting for the specific underlying emissions scenario. Based on multi-crop-model simulations of the four major cereal crops (maize, rice, soy, and wheat) on a 0.5 x 0.5 degree global grid generated within ISI-MIP, we show the average spatial patterns of projected crop yield changes at one half degree warming steps. We find that emissions scenario dependence is a minor component of the overall variance of projected yield changes at different levels of global warming. Furthermore, scenario dependence can be reduced by accounting for the direct effects of CO2 fertilization in each global climate model (GCM)/impact model combination through an inclusion of the global atmospheric CO2 concentration as a second predictor. The choice of GCM output used to force the crop model simulations accounts for a slightly larger portion of the total yield variance, but the greatest contributor to variance in both global and regional crop yields and at all levels of warming, is the inter-crop-model spread. The unique multi impact model ensemble available with ISI-MIP data also indicates that the overall variability of crop yields is projected to increase in conjunction with increasing global mean temperature. This result is consistent throughout the ensemble of impact models and across many world regions. Such a hike in yield volatility could have significant policy implications by affecting food prices and supplies.

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Multi-criteria Evaluation of Discharge Simulation in Dynamic Global Vegetation Models

NASA Astrophysics Data System (ADS)

Yang, H.; Piao, S.; Zeng, Z.; Ciais, P.; Yin, Y.; Friedlingstein, P.; Sitch, S.; Ahlström, A.; Guimberteau, M.; Huntingford, C.; Levis, S.; Levy, P. E.; Huang, M.; Li, Y.; Li, X.; Lomas, M.; Peylin, P. P.; Poulter, B.; Viovy, N.; Zaehle, S.; Zeng, N.; Zhao, F.; Wang, L.

2015-12-01

In this study, we assessed the performance of discharge simulations by coupling the runoff from seven Dynamic Global Vegetation Models (DGVMs; LPJ, ORCHIDEE, Sheffield-DGVM, TRIFFID, LPJ-GUESS, CLM4CN, and OCN) to one river routing model for 16 large river basins. The results show that the seasonal cycle of river discharge is generally modelled well in the low and mid latitudes, but not in the high latitudes, where the peak discharge (due to snow and ice melting) is underestimated. For the annual mean discharge, the DGVMs chained with the routing model show an underestimation. Furthermore the 30-year trend of discharge is also under-estimated. For the inter-annual variability of discharge, a skill score based on overlapping of probability density functions (PDFs) suggests that most models correctly reproduce the observed variability (correlation coefficient higher than 0.5; i.e. models account for 50% of observed inter-annual variability) except for the Lena, Yenisei, Yukon, and the Congo river basins. In addition, we compared the simulated runoff from different simulations where models were forced with either fixed or varying land use. This suggests that both seasonal and annual mean runoff has been little affected by land use change, but that the trend itself of runoff is sensitive to land use change. None of the models when considered individually show significantly better performances than any other and in all basins. This suggests that based on current modelling capability, a regional-weighted average of multi-model ensemble projections might be appropriate to reduce the bias in future projection of global river discharge.

An anatomically sound surgical simulation model for myringotomy and tympanostomy tube insertion.

PubMed

Hong, Paul; Webb, Amanda N; Corsten, Gerard; Balderston, Janet; Haworth, Rebecca; Ritchie, Krista; Massoud, Emad

2014-03-01

Myringotomy and tympanostomy tube insertion (MT) is a common surgical procedure. Although surgical simulation has proven to be an effective training tool, an anatomically sound simulation model for MT is lacking. We developed such a model and assessed its impact on the operating room performance of senior medical students. Prospective randomized trial. A randomized single-blind controlled study of simulation training with the MT model versus no simulation training. Each participant was randomized to either the simulation model group or control group, after performing an initial MT procedure. Within two weeks of the first procedure, the students performed a second MT. All procedures were performed on real patients and rated with a Global Rating Scale by two attending otolaryngologists. Time to complete the MT was also recorded. Twenty-four senior medical students were enrolled. Control and intervention groups did not differ at baseline on their Global Rating Scale score or time to complete the MT procedure. Following simulation training, the study group received significantly higher scores (P=.005) and performed the MT procedure in significantly less time (P=.034). The control group did not improve their performance scores (P>.05) or the time to complete the procedure (P>.05). Our surgical simulation model shows promise for being a valuable teaching tool for MT for senior medical students. Such anatomically appropriate physical simulators may benefit teaching of junior trainees. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

An integrated model for the assessment of global water resources Part 2: Applications and assessments

NASA Astrophysics Data System (ADS)

Hanasaki, N.; Kanae, S.; Oki, T.; Masuda, K.; Motoya, K.; Shirakawa, N.; Shen, Y.; Tanaka, K.

2008-07-01

To assess global water resources from the perspective of subannual variation in water availability and water use, an integrated water resources model was developed. In a companion report, we presented the global meteorological forcing input used to drive the model and six modules, namely, the land surface hydrology module, the river routing module, the crop growth module, the reservoir operation module, the environmental flow requirement module, and the anthropogenic withdrawal module. Here, we present the results of the model application and global water resources assessments. First, the timing and volume of simulated agriculture water use were examined because agricultural use composes approximately 85% of total consumptive water withdrawal in the world. The estimated crop calendar showed good agreement with earlier reports for wheat, maize, and rice in major countries of production. In major countries, the error in the planting date was ±1 mo, but there were some exceptional cases. The estimated irrigation water withdrawal also showed fair agreement with country statistics, but tended to be underestimated in countries in the Asian monsoon region. The results indicate the validity of the model and the input meteorological forcing because site-specific parameter tuning was not used in the series of simulations. Finally, global water resources were assessed on a subannual basis using a newly devised index. This index located water-stressed regions that were undetected in earlier studies. These regions, which are indicated by a gap in the subannual distribution of water availability and water use, include the Sahel, the Asian monsoon region, and southern Africa. The simulation results show that the reservoir operations of major reservoirs (>1 km3) and the allocation of environmental flow requirements can alter the population under high water stress by approximately -11% to +5% globally. The integrated model is applicable to assessments of various global environmental projections such as climate change.

A new synoptic scale resolving global climate simulation using the Community Earth System Model

NASA Astrophysics Data System (ADS)

Small, R. Justin; Bacmeister, Julio; Bailey, David; Baker, Allison; Bishop, Stuart; Bryan, Frank; Caron, Julie; Dennis, John; Gent, Peter; Hsu, Hsiao-ming; Jochum, Markus; Lawrence, David; Muñoz, Ernesto; diNezio, Pedro; Scheitlin, Tim; Tomas, Robert; Tribbia, Joseph; Tseng, Yu-heng; Vertenstein, Mariana

2014-12-01

High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of "present-day" simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about two simulated years per day on the NCAR-Wyoming supercomputer "Yellowstone."

Climate Impact of a Regional Nuclear Weapons Exchange: An Improved Assessment Based On Detailed Source Calculations

NASA Astrophysics Data System (ADS)

Reisner, Jon; D'Angelo, Gennaro; Koo, Eunmo; Even, Wesley; Hecht, Matthew; Hunke, Elizabeth; Comeau, Darin; Bos, Randall; Cooley, James

2018-03-01

We present a multiscale study examining the impact of a regional exchange of nuclear weapons on global climate. Our models investigate multiple phases of the effects of nuclear weapons usage, including growth and rise of the nuclear fireball, ignition and spread of the induced firestorm, and comprehensive Earth system modeling of the oceans, land, ice, and atmosphere. This study follows from the scenario originally envisioned by Robock, Oman, Stenchikov, et al. (2007, https://doi.org/10.5194/acp-7-2003-2007), based on the analysis of Toon et al. (2007, https://doi.org/10.5194/acp-7-1973-2007), which assumes a regional exchange between India and Pakistan of fifty 15 kt weapons detonated by each side. We expand this scenario by modeling the processes that lead to production of black carbon, in order to refine the black carbon forcing estimates of these previous studies. When the Earth system model is initiated with 5 × 109 kg of black carbon in the upper troposphere (approximately from 9 to 13 km), the impact on climate variables such as global temperature and precipitation in our simulations is similar to that predicted by previously published work. However, while our thorough simulations of the firestorm produce about 3.7 × 109 kg of black carbon, we find that the vast majority of the black carbon never reaches an altitude above weather systems (approximately 12 km). Therefore, our Earth system model simulations conducted with model-informed atmospheric distributions of black carbon produce significantly lower global climatic impacts than assessed in prior studies, as the carbon at lower altitudes is more quickly removed from the atmosphere. In addition, our model ensembles indicate that statistically significant effects on global surface temperatures are limited to the first 5 years and are much smaller in magnitude than those shown in earlier works. None of the simulations produced a nuclear winter effect. We find that the effects on global surface temperatures are not uniform and are concentrated primarily around the highest arctic latitudes, dramatically reducing the global impact on human health and agriculture compared with that reported by earlier studies. Our analysis demonstrates that the probability of significant global cooling from a limited exchange scenario as envisioned in previous studies is highly unlikely, a conclusion supported by examination of natural analogs, such as large forest fires and volcanic eruptions.

Climate impact of a regional nuclear weapons exchange: An improved assessment based on detailed source calculations

DOE PAGES

Reisner, Jon Michael; D'Angelo, Gennaro; Koo, Eunmo; ...

2018-02-13

In this paper, we present a multi-scale study examining the impact of a regional exchange of nuclear weapons on global climate. Our models investigate multiple phases of the effects of nuclear weapons usage, including growth and rise of the nuclear fireball, ignition and spread of the induced firestorm, and comprehensive Earth system modeling of the oceans, land, ice, and atmosphere. This study follows from the scenario originally envisioned by Robock et al. (2007a), based on the analysis of Toon et al. (2007), which assumes a regional exchange between India and Pakistan of fifty 15-kiloton weapons detonated by each side. Wemore » expand this scenario by modeling the processes that lead to production of black carbon, in order to refine the black carbon forcing estimates of these previous studies. When the Earth system model is initiated with 5 × 10 9 kg of black carbon in the upper troposphere (approximately 9 to 13 km), the impact on climate variables such as global temperature and precipitation in our simulations is similar to that predicted by previously published work. However, while our thorough simulations of the firestorm produce about 3.7 × 10 9 kg of black carbon, we find that the vast majority of the black carbon never reaches an altitude above weather systems (approximately 12 km). Therefore, our Earth system model simulations conducted with model-informed atmospheric distributions of black carbon produce significantly lower global climatic impacts than assessed in prior studies, as the carbon at lower altitudes is more quickly removed from the atmosphere. In addition, our model ensembles indicate that statistically significant effects on global surface temperatures are limited to the first 5 years and are much smaller in magnitude than those shown in earlier works. None of the simulations produced a nuclear winter effect. We find that the effects on global surface temperatures are not uniform and are concentrated primarily around the highest arctic latitudes, dramatically reducing the global impact on human health and agriculture compared with that reported by earlier studies. Lastly, our analysis demonstrates that the probability of significant global cooling from a limited exchange scenario as envisioned in the previous studies is highly unlikely, a conclusion supported by examination of natural analogs, such as large forest fires and volcanic eruptions.« less

Climate impact of a regional nuclear weapons exchange: An improved assessment based on detailed source calculations

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

Reisner, Jon Michael; D'Angelo, Gennaro; Koo, Eunmo

In this paper, we present a multi-scale study examining the impact of a regional exchange of nuclear weapons on global climate. Our models investigate multiple phases of the effects of nuclear weapons usage, including growth and rise of the nuclear fireball, ignition and spread of the induced firestorm, and comprehensive Earth system modeling of the oceans, land, ice, and atmosphere. This study follows from the scenario originally envisioned by Robock et al. (2007a), based on the analysis of Toon et al. (2007), which assumes a regional exchange between India and Pakistan of fifty 15-kiloton weapons detonated by each side. Wemore » expand this scenario by modeling the processes that lead to production of black carbon, in order to refine the black carbon forcing estimates of these previous studies. When the Earth system model is initiated with 5 × 10 9 kg of black carbon in the upper troposphere (approximately 9 to 13 km), the impact on climate variables such as global temperature and precipitation in our simulations is similar to that predicted by previously published work. However, while our thorough simulations of the firestorm produce about 3.7 × 10 9 kg of black carbon, we find that the vast majority of the black carbon never reaches an altitude above weather systems (approximately 12 km). Therefore, our Earth system model simulations conducted with model-informed atmospheric distributions of black carbon produce significantly lower global climatic impacts than assessed in prior studies, as the carbon at lower altitudes is more quickly removed from the atmosphere. In addition, our model ensembles indicate that statistically significant effects on global surface temperatures are limited to the first 5 years and are much smaller in magnitude than those shown in earlier works. None of the simulations produced a nuclear winter effect. We find that the effects on global surface temperatures are not uniform and are concentrated primarily around the highest arctic latitudes, dramatically reducing the global impact on human health and agriculture compared with that reported by earlier studies. Lastly, our analysis demonstrates that the probability of significant global cooling from a limited exchange scenario as envisioned in the previous studies is highly unlikely, a conclusion supported by examination of natural analogs, such as large forest fires and volcanic eruptions.« less

Consequences of 1.5 °C and 2 °C global warming levels for temperature and precipitation changes over Central Africa

NASA Astrophysics Data System (ADS)

Pokam Mba, Wilfried; Longandjo, Georges-Noel T.; Moufouma-Okia, Wilfran; Bell, Jean-Pierre; James, Rachel; Vondou, Derbetini A.; Haensler, Andreas; Fotso-Nguemo, Thierry C.; Merlin Guenang, Guy; Djiotang Tchotchou, Angennes Lucie; Kamsu-Tamo, Pierre H.; Takong, Ridick R.; Nikulin, Grigory; Lennard, Christopher J.; Dosio, Alessandro

2018-05-01

Discriminating climate impacts between 1.5 °C and 2 °C warming levels is particularly important for Central Africa, a vulnerable region where multiple biophysical, political, and socioeconomic stresses interact to constrain the region’s adaptive capacity. This study uses an ensemble of 25 transient Regional Climate Model (RCM) simulations from the CORDEX initiative, forced with the Representative Concentration Pathway (RCP) 8.5, to investigate the potential temperature and precipitation changes in Central Africa corresponding to 1.5 °C and 2 °C global warming levels. Global climate model simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to drive the RCMs and determine timing of the targeted global warming levels. The regional warming differs over Central Africa between 1.5 °C and 2 °C global warming levels. Whilst there are large uncertainties associated with projections at 1.5 °C and 2 °C, the 0.5 °C increase in global temperature is associated with larger regional warming response. Compared to changes in temperature, changes in precipitation are more heterogeneous and climate model simulations indicate a lack of consensus across the region, though there is a tendency towards decreasing seasonal precipitation in March–May, and a reduction of consecutive wet days. As a drought indicator, a significant increase in consecutive dry days was found. Consistent changes of maximum 5 day rainfall are also detected between 1.5 °C vs. 2 °C global warming levels.

Simulation and Correction of Triana-Viewed Earth Radiation Budget with ERBE/ISCCP Data

NASA Technical Reports Server (NTRS)

Huang, Jian-Ping; Minnis, Patrick; Doelling, David R.; Valero, Francisco P. J.

2002-01-01

This paper describes the simulation of the earth radiation budget (ERB) as viewed by Triana and the development of correction models for converting Trianaviewed radiances into a complete ERB. A full range of Triana views and global radiation fields are simulated using a combination of datasets from ERBE (Earth Radiation Budget Experiment) and ISCCP (International Satellite Cloud Climatology Project) and analyzed with a set of empirical correction factors specific to the Triana views. The results show that the accuracy of global correction factors to estimate ERB from Triana radiances is a function of the Triana position relative to the Lagrange-1 (L1) or the Sun location. Spectral analysis of the global correction factor indicates that both shortwave (SW; 0.2 - 5.0 microns) and longwave (LW; 5 -50 microns) parameters undergo seasonal and diurnal cycles that dominate the periodic fluctuations. The diurnal cycle, especially its amplitude, is also strongly dependent on the seasonal cycle. Based on these results, models are developed to correct the radiances for unviewed areas and anisotropic emission and reflection. A preliminary assessment indicates that these correction models can be applied to Triana radiances to produce the most accurate global ERB to date.

The use of NASA GEOS Global Analysis in MM5/WRF Initialization: Current Studies and Future Applications

NASA Technical Reports Server (NTRS)

Pu, Zhao-Xia; Tao, Wei-Kuo

2004-01-01

An effort has been made at NASA/GSFC to use the Goddard Earth Observing system (GEOS) global analysis in generating the initial and boundary conditions for MM5/WRF simulation. This linkage between GEOS global analysis and MM5/WRF models has made possible for a few useful applications. As one of the sample studies, a series of MM5 simulations were conducted to test the sensitivity of initial and boundary conditions to MM5 simulated precipitation over the eastern; USA. Global analyses horn different operational centers (e.g., NCEP, ECMWF, I U ASA/GSFCj were used to provide first guess field and boundary conditions for MM5. Numerical simulations were performed for one- week period over the eastern coast areas of USA. the distribution and quantities of MM5 simulated precipitation were compared. Results will be presented in the workshop. In addition,other applications from recent and future studies will also be addressed.

Geoengineering by stratospheric SO2 injection: results from the Met Office HadGEM2 climate model and comparison with the Goddard Institute for Space Studies ModelE

NASA Astrophysics Data System (ADS)

Jones, A.; Haywood, J.; Boucher, O.; Kravitz, B.; Robock, A.

2010-03-01

We examine the response of the Met Office Hadley Centre's HadGEM2-AO climate model to simulated geoengineering by continuous injection of SO2 into the lower stratosphere, and compare the results with those from the Goddard Institute for Space Studies ModelE. The HadGEM2 simulations suggest that the SO2 injection rate considered here (5 Tg[SO2] yr-1) could defer the amount of global warming predicted under the Intergovernmental Panel on Climate Change's A1B scenario by approximately 30-35 years, although both models indicate rapid warming if geoengineering is not sustained. We find a broadly similar geographic distribution of the response to geoengineering in both models in terms of near-surface air temperature and mean June-August precipitation. The simulations also suggest that significant changes in regional climate would be experienced even if geoengineering was successful in maintaining global-mean temperature near current values.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, G.; Thornton, Patti; Collatz, G. J.

2012-01-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Astrophysics Data System (ADS)

Koster, R. D.; Walker, G.; Thornton, P. E.; Collatz, G. J.

2012-12-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if somewhat biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Forest product trade impacts of an invasive species: modeling structure and intervention trade-offs

Treesearch

Jeffrey Prestemon; Shushuai Zhu; James A. Turner; Joseph Buongiorno; Ruhong Li

2006-01-01

Asian gypsy and nun moth introductions into the United States, possibly arriving on imported Siberian coniferous logs, threaten domestic forests and product markers and could have global market consequences. We simulate, using the Global Forest Products Model (a spatial equilibrium model of the world forest sector), the consequences under current policies of a...

Evaluating the Contribution of Natural Variability and Climate Model Response to Uncertainty in Projections of Climate Change Impacts on U.S. Air Quality

EPA Science Inventory

We examine the effects of internal variability and model response in projections of climate impacts on U.S. ground-level ozone across the 21st century using integrated global system modeling and global atmospheric chemistry simulations. The impact of climate change on air polluti...

Validation of a Global Hydrodynamic Flood Inundation Model

NASA Astrophysics Data System (ADS)

Bates, P. D.; Smith, A.; Sampson, C. C.; Alfieri, L.; Neal, J. C.

2014-12-01

In this work we present first validation results for a hyper-resolution global flood inundation model. We use a true hydrodynamic model (LISFLOOD-FP) to simulate flood inundation at 1km resolution globally and then use downscaling algorithms to determine flood extent and depth at 90m spatial resolution. Terrain data are taken from a custom version of the SRTM data set that has been processed specifically for hydrodynamic modelling. Return periods of flood flows along the entire global river network are determined using: (1) empirical relationships between catchment characteristics and index flood magnitude in different hydroclimatic zones derived from global runoff data; and (2) an index flood growth curve, also empirically derived. Bankful return period flow is then used to set channel width and depth, and flood defence impacts are modelled using empirical relationships between GDP, urbanization and defence standard of protection. The results of these simulations are global flood hazard maps for a number of different return period events from 1 in 5 to 1 in 1000 years. We compare these predictions to flood hazard maps developed by national government agencies in the UK and Germany using similar methods but employing detailed local data, and to observed flood extent at a number of sites including St. Louis, USA and Bangkok in Thailand. Results show that global flood hazard models can have considerable skill given careful treatment to overcome errors in the publicly available data that are used as their input.

ALM-FATES: Using dynamic vegetation and demography to capture changes in forest carbon cycling and competition at the global scale

NASA Astrophysics Data System (ADS)

Holm, J. A.; Knox, R. G.; Koven, C.; Riley, W. J.; Bisht, G.; Fisher, R.; Christoffersen, B. O.; Dietze, M.; Chambers, J. Q.

2017-12-01

The inclusion of dynamic vegetation demography in Earth System Models (ESMs) has been identified as a critical step in moving ESMs towards more realistic representations of plant ecology and the processes that govern climatically important fluxes of carbon, energy, and water. Successful application of dynamic vegetation models, and process-based approaches to simulate plant demography, succession, and response to disturbances without climate envelopes at the global scale is a challenging endeavor. We integrated demographic processes using the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) in the newly developed ACME Land Model (ALM). We then use an ALM-FATES globally gridded simulation for the first time to investigate plant functional type (PFT) distributions and dynamic turnover rates. Initial global simulations successfully include six interacting and competing PFTs (ranging from tropical to boreal, evergreen, deciduous, needleleaf and broadleaf); including more PFTs is planned. Global maps of net primary productivity, leaf area index, and total vegetation biomass by ALM-FATES matched patterns and values when compared to CLM4.5-BGC and MODIS estimates. We also present techniques for PFT parameterization based on the Predictive Ecosystem Analyzer (PEcAn), field based turnover rates, improved PFT groupings based on trait-tradeoffs, and improved representation of multiple canopy positions. Finally, we applied the improved ALM-FATES model at a central Amazon tropical and western U.S. temperate sites and demonstrate improvements in predicted PFT size- and age-structure and regional distribution. Results from the Amazon tropical site investigate the ability and magnitude of a tropical forest to act as a carbon sink by 2100 with a doubling of CO2, while results from the temperate sites investigate the response of forest mortality with increasing droughts.

Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts

NASA Astrophysics Data System (ADS)

Zaherpour, Jamal; Gosling, Simon N.; Mount, Nick; Müller Schmied, Hannes; Veldkamp, Ted I. E.; Dankers, Rutger; Eisner, Stephanie; Gerten, Dieter; Gudmundsson, Lukas; Haddeland, Ingjerd; Hanasaki, Naota; Kim, Hyungjun; Leng, Guoyong; Liu, Junguo; Masaki, Yoshimitsu; Oki, Taikan; Pokhrel, Yadu; Satoh, Yusuke; Schewe, Jacob; Wada, Yoshihide

2018-06-01

Global-scale hydrological models are routinely used to assess water scarcity, flood hazards and droughts worldwide. Recent efforts to incorporate anthropogenic activities in these models have enabled more realistic comparisons with observations. Here we evaluate simulations from an ensemble of six models participating in the second phase of the Inter-Sectoral Impact Model Inter-comparison Project (ISIMIP2a). We simulate monthly runoff in 40 catchments, spatially distributed across eight global hydrobelts. The performance of each model and the ensemble mean is examined with respect to their ability to replicate observed mean and extreme runoff under human-influenced conditions. Application of a novel integrated evaluation metric to quantify the models’ ability to simulate timeseries of monthly runoff suggests that the models generally perform better in the wetter equatorial and northern hydrobelts than in drier southern hydrobelts. When model outputs are temporally aggregated to assess mean annual and extreme runoff, the models perform better. Nevertheless, we find a general trend in the majority of models towards the overestimation of mean annual runoff and all indicators of upper and lower extreme runoff. The models struggle to capture the timing of the seasonal cycle, particularly in northern hydrobelts, while in southern hydrobelts the models struggle to reproduce the magnitude of the seasonal cycle. It is noteworthy that over all hydrological indicators, the ensemble mean fails to perform better than any individual model—a finding that challenges the commonly held perception that model ensemble estimates deliver superior performance over individual models. The study highlights the need for continued model development and improvement. It also suggests that caution should be taken when summarising the simulations from a model ensemble based upon its mean output.

Evaluation of NCAR CAM5 Simulated Marine Boundary Layer Cloud Properties Using a Combination of Satellite and Surface Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Song, H.; Wang, M.; Ghan, S. J.; Dong, X.

2016-12-01

he main objective of this study is to systematically evaluate the MBL cloud properties simulated in CAM5 family models using a combination of satellite-based CloudSat/MODIS observations and ground-based observations from the ARM Azores site, with a special focus on MBL cloud microphysics and warm rain process. First, we will present a global evaluation based on satellite observations and retrievals. We will compare global cloud properties (e.g., cloud fraction, cloud vertical structure, cloud CER, COT, and LWP, as well as drizzle frequency and intensity diagnosed using the CAM5-COSP instrumental simulators) simulated in the CAM5 models with the collocated CloudSat and MODIS observations. We will also present some preliminary results from a regional evaluation based mainly on ground observations from ARM Azores site. We will compare MBL cloud properties simulated in CAM5 models over the ARM Azores site with collocated satellite (MODIS and CloudSat) and ground-based observations from the ARM site.

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model.

PubMed

Turner, Sean W D; Ng, Jia Yi; Galelli, Stefano

2017-07-15

An important and plausible impact of a changing global climate is altered power generation from hydroelectric dams. Here we project 21st century global hydropower production by forcing a coupled, global hydrological and dam model with three General Circulation Model (GCM) projections run under two emissions scenarios. Dams are simulated using a detailed model that accounts for plant specifications, storage dynamics, reservoir bathymetry and realistic, optimized operations. We show that the inclusion of these features can have a non-trivial effect on the simulated response of hydropower production to changes in climate. Simulation results highlight substantial uncertainty in the direction of change in globally aggregated hydropower production (~-5 to +5% change in mean global production by the 2080s under a high emissions scenario, depending on GCM). Several clearly impacted hotspots are identified, the most prominent of which encompasses the Mediterranean countries in southern Europe, northern Africa and the Middle East. In this region, hydropower production is projected to be reduced by approximately 40% on average by the end of the century under a high emissions scenario. After accounting for each country's dependence on hydropower for meeting its current electricity demands, the Balkans countries emerge as the most vulnerable (~5-20% loss in total national electricity generation depending on country). On the flipside, a handful of countries in Scandinavia and central Asia are projected to reap a significant increase in total electrical production (~5-15%) without investing in new power generation facilities. Copyright © 2017 Elsevier B.V. All rights reserved.

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model

DOE PAGES

Turner, Sean W. D.; Ng, Jia Yi; Galelli, Stefano

2017-03-07

Here, an important and plausible impact of a changing global climate is altered power generation from hydroelectric dams. Here we project 21st century global hydropower production by forcing a coupled, global hydrological and dam model with three General Circulation Model (GCM) projections run under two emissions scenarios. Dams are simulated using a detailed model that accounts for plant specifications, storage dynamics, reservoir bathymetry and realistic, optimized operations. We show that the inclusion of these features can have a non-trivial effect on the simulated response of hydropower production to changes in climate. Simulation results highlight substantial uncertainty in the direction ofmore » change in globally aggregated hydropower production (~–5 to + 5% change in mean global production by the 2080s under a high emissions scenario, depending on GCM). Several clearly impacted hotspots are identified, the most prominent of which encompasses the Mediterranean countries in southern Europe, northern Africa and the Middle East. In this region, hydropower production is projected to be reduced by approximately 40% on average by the end of the century under a high emissions scenario. After accounting for each country's dependence on hydropower for meeting its current electricity demands, the Balkans countries emerge as the most vulnerable (~ 5–20% loss in total national electricity generation depending on country). On the flipside, a handful of countries in Scandinavia and central Asia are projected to reap a significant increase in total electrical production (~ 5–15%) without investing in new power generation facilities.« less

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model

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

Turner, Sean W. D.; Ng, Jia Yi; Galelli, Stefano

Here, an important and plausible impact of a changing global climate is altered power generation from hydroelectric dams. Here we project 21st century global hydropower production by forcing a coupled, global hydrological and dam model with three General Circulation Model (GCM) projections run under two emissions scenarios. Dams are simulated using a detailed model that accounts for plant specifications, storage dynamics, reservoir bathymetry and realistic, optimized operations. We show that the inclusion of these features can have a non-trivial effect on the simulated response of hydropower production to changes in climate. Simulation results highlight substantial uncertainty in the direction ofmore » change in globally aggregated hydropower production (~–5 to + 5% change in mean global production by the 2080s under a high emissions scenario, depending on GCM). Several clearly impacted hotspots are identified, the most prominent of which encompasses the Mediterranean countries in southern Europe, northern Africa and the Middle East. In this region, hydropower production is projected to be reduced by approximately 40% on average by the end of the century under a high emissions scenario. After accounting for each country's dependence on hydropower for meeting its current electricity demands, the Balkans countries emerge as the most vulnerable (~ 5–20% loss in total national electricity generation depending on country). On the flipside, a handful of countries in Scandinavia and central Asia are projected to reap a significant increase in total electrical production (~ 5–15%) without investing in new power generation facilities.« less

The Jena Diversity Model: Towards a Richer Representation of the Terrestrial Biosphere for Earth System Modelling

NASA Astrophysics Data System (ADS)

Pavlick, R.; Reu, B.; Bohn, K.; Dyke, J.; Kleidon, A.

2010-12-01

The terrestrial biosphere is a complex, self-organizing system which is continually both adapting to and altering its global environment. It also exhibits a vast diversity of vegetation forms and functioning. However, the terrestrial biosphere components within current state-of-the-art Earth System Models abstract this diversity in to a handful of relatively static plant functional types. These coarse and static representations of functional diversity might contribute to overly pessimistic projections regarding terrestrial ecosystem responses to scenarios of global change (e.g. Amazonian and boreal forest diebacks). In the Jena Diversity (JeDi) model, we introduce a new approach to vegetation modelling with a richer representation of functional diversity, based not on plant functional types, but on unavoidable plant ecophysiological trade-offs, which we hypothesize should be more stable in time. The JeDi model tests a large number of plant growth strategies. Each growth strategy is simulated using a set of randomly generated parameter values, which characterize its functioning in terms of carbon allocation, ecophysiology, and phenology, which are then linked to the growing conditions at the land surface. The model is constructed in such a way that these parameters inherently lead to ecophysiological trade-offs, which determine whether a growth strategy is able to survive and reproduce under the prevalent climatic conditions. Kleidon and Mooney (2000) demonstrated that this approach is capable of reproducing the geographic distribution of species richness. More recently, we have shown the JeDi model can explain other biogeographical phenomena including the present-day global pattern of biomes (Reu et al., accepted), ecosystem evenness (Kleidon et al. 2009), and possible mechanisms for biome shifts and biodiversity changes under scenarios of global warming (Reu et al., submitted). We have also evaluated the simulated biogeochemical fluxes from JeDi against a variety of site, field, and satellite observations (Pavlick et al., submitted) following a protocol established by the Carbon-Land Model Intercomparison Project (Randerson et al. 2009). We found that the global patterns of biogeochemical fluxes and land surface properties are reasonably well simulated using this bottom-up trade-off approach and compare favorably with other state of the art terrestrial biosphere models. Here, we present some results from JeDi simulations, wherein we varied the modelled functional diversity to quantify its impact on terrestrial biogeochemical fluxes under both present-day conditions and projected scenarios of global change. We also present results from a set of simulations wherein we vary the ability of the modelled ecosystems to adapt through changes in functional composition, leading to different projection responses of the carbon cycle to global warming. This plant functional tradeoff approach sets the foundation for many applications, including exploring the emergence and climatic impacts of major vegetation transitions throughout the last 400 million years as well as quantifying the significance of preserving functional diversity to hedge against uncertain climates in the future.

Towards Better Simulation of US Maize Yield Responses to Climate in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Peng, B.; Guan, K.; Chen, M.; Lawrence, D. M.; Jin, Z.; Bernacchi, C.; Ainsworth, E. A.; DeLucia, E. H.; Lombardozzi, D. L.; Lu, Y.

2017-12-01

Global food security is undergoing continuing pressure from increased population and climate change despites the potential advancement in breeding and management technologies. Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Here we developed an improved maize representation within the Community Earth System Model (CESM) by combining the strengths of both the Community Land Model version 4.5 (CLM4.5) and the Agricultural Production Systems sIMulator (APSIM) models. Specifically, we modified the maize planting scheme, incorporated the phenology scheme adopted from the APSIM model, added a new carbon allocation scheme into CLM4.5, and improved the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number and grain size. We conducted a regional simulation of this new model over the US Corn Belt during 1990 to 2010. The simulated maize yield as well as its responses to climate (growing season mean temperature and precipitation) are benchmarked with data from UADA NASS statistics. Our results show that the CLM-APSIM model outperforms the CLM4.5 in simulating county-level maize yield production and reproduces more realistic yield responses to climate variations than CLM4.5. However, some critical processes (such as crop failure due to frost and inundation and suboptimal growth condition due to biotic stresses) are still missing in both CLM-APSIM and CLM4.5, making the simulated yield responses to climate slightly deviate from the reality. Our results demonstrate that with improved paramterization of crop growth, the ESMs can be powerful tools for realistically simulating agricultural production, which is gaining increasing interests and critical to study of global food security and food-energy-water nexus.

Contributions of Lower Atmospheric Drivers to the Semiannual Oscillation in Thermospheric Global Mass Density

NASA Astrophysics Data System (ADS)

Jones, M., Jr.; Emmert, J. T.; Drob, D. P.; Siskind, D. E.

2016-12-01

The thermosphere exhibits intra-annual variations (IAV) in globally averaged mass density that noticeably impact the drag environment of satellites in low Earth orbit. Particularly, the annual and semiannual oscillations (AO and SAO) are collectively the second largest component, after solar variability, of thermospheric global mass density variations. Several mechanisms have been proposed to explain the oscillations, but they have yet to be reproduced by first-principles modeling simulations. Recent studies have focused on estimating the SAO in eddy diffusion required to explain the thermospheric SAO in mass density. Less attention has been paid to the effect of lower and middle atmospheric drivers on the lower boundary of the thermosphere. In this study, we utilize the National Center for Atmospheric Research Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (TIME-GCM), to elucidate how the different lower atmospheric drivers influence IAV, and in particular the SAO of globally-averaged thermospheric mass density. We performed numerical simulations of a continuous calendar year assuming constant solar forcing, manipulating the lower atmospheric tidal forcing and gravity wave parameterization in order to quantify the SAO in thermospheric mass density attributable to different lower atmospheric drivers. The prominent initial results are as follows: (1) The "standard" TIME-GCM is capable of simulating the SAO in globally-averaged mass density at 400 km from first-principles, and its amplitude and phase compare well with empirical models; (2) The simulations suggest that seasonally varying Kzz driven by breaking GWs is not the primary driver of the SAO in upper thermospheric globally averaged mass density; (3) Preliminary analysis suggests that the SAO in the upper thermospheric mass density could be a by-product of dynamical wave transport in the mesopause region.

Reconstructing a lost Eocene paradise: Part I. Simulating the change in global floral distribution at the initial Eocene thermal maximum

NASA Astrophysics Data System (ADS)

Shellito, Cindy J.; Sloan, Lisa C.

2006-02-01

This study utilizes the NCAR Land Surface Model (LSM1.2) integrated with dynamic global vegetation to recreate the early Paleogene global distribution of vegetation and to examine the response of the vegetation distribution to changes in climate at the Paleocene-Eocene boundary (˜ 55 Ma). We run two simulations with Eocene geography driven by climatologies generated in two atmosphere global modeling experiments: one with atmospheric pCO 2 at 560 ppm, and another at 1120 ppm. In both scenarios, the model produces the best match with fossil flora in the low latitudes. A comparison of model output from the two scenarios suggests that the greatest impact of climate on vegetation will occur in the high latitudes, in the Arctic Circle and in Antarctica. In these regions, greater accumulated summertime warmth in the 1120 ppm simulation allows temperate plant functional types to expand further poleward. Additionally, the high pCO 2 scenario produces a greater abundance of trees over grass at these high latitudes. In the middle and low latitudes, the general distribution of plant functional types is similar in both pCO 2 scenarios. Likely, a greater increment of greenhouse gases is necessary to produce the type of change evident in the mid-latitude paleobotanical record. Overall, differences between model output and fossil flora are greatest at high latitudes.

Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

NASA Astrophysics Data System (ADS)

Qi, W.; Zhang, C.; Fu, G.; Sweetapple, C.; Zhou, H.

2016-02-01

The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

Mars Global Reference Atmospheric Model (Mars-GRAM): Release No. 2 - Overview and applications

NASA Technical Reports Server (NTRS)

James, B.; Johnson, D.; Tyree, L.

1993-01-01

The Mars Global Reference Atmospheric Model (Mars-GRAM), a science and engineering model for empirically parameterizing the temperature, pressure, density, and wind structure of the Martian atmosphere, is described with particular attention to the model's newest version, Mars-GRAM, Release No. 2 and to the improvements incorporated into the Release No. 2 model as compared with the Release No. 1 version. These improvements include (1) an addition of a new capability to simulate local-scale Martian dust storms and the growth and decay of these storms; (2) an addition of the Zurek and Haberle (1988) wave perturbation model, for simulating tidal perturbation effects; and (3) a new modular version of Mars-GRAM, for incorporation as a subroutine into other codes.

Effects of Kinetic Processes in Shaping Io's Global Plasma Environment: A 3D Hybrid Model

NASA Technical Reports Server (NTRS)

Lipatov, Alexander S.; Combi, Michael R.

2004-01-01

The global dynamics of the ionized and neutral components in the environment of Io plays an important role in the interaction of Jupiter's corotating magnetospheric plasma with Io. The stationary simulation of this problem was done in the MHD and the electrodynamics approaches. One of the main significant results from the simplified two-fluid model simulations was a production of the structure of the double-peak in the magnetic field signature of the I0 flyby that could not be explained by standard MHD models. In this paper, we develop a method of kinetic ion simulation. This method employs the fluid description for electrons and neutrals whereas for ions multilevel, drift-kinetic and particle, approaches are used. We also take into account charge-exchange and photoionization processes. Our model provides much more accurate description for ion dynamics and allows us to take into account the realistic anisotropic ion distribution that cannot be done in fluid simulations. The first results of such simulation of the dynamics of ions in the Io's environment are discussed in this paper.

A new look at the multi-G model for organic carbon degradation in surface marine sediments for coupled benthic-pelagic simulations of the global ocean

NASA Astrophysics Data System (ADS)

Stolpovsky, Konstantin; Dale, Andrew W.; Wallmann, Klaus

2018-06-01

The kinetics of particulate organic carbon (POC) mineralization in marine surface sediments is not well constrained. This creates considerable uncertainties when benthic processes are considered in global biogeochemical or Earth system circulation models to simulate climate-ocean interactions and biogeochemical tracer distributions in the ocean. In an attempt to improve our understanding of the rate and depth distribution of organic carbon mineralization in bioturbated (0-20 cm) sediments at the global scale, we parameterized a 1-D diagenetic model that simulates the mineralization of three discrete POC pools (a multi-G model). The rate constants of the three reactive classes (highly reactive, reactive, refractory) are fixed and determined to be 70, 0.5 and ˜ 0.001 yr-1, respectively, based on the Martin curve model for pelagic POC degradation. In contrast to previous approaches, however, the reactivity of the organic material degraded in the seafloor is continuous with, and set by, the apparent reactivity of material sinking through the water column. Despite the simplifications of describing POC remineralization using G-type approaches, the model is able to simulate a global database (185 stations) of benthic oxygen and nitrate fluxes across the sediment-water interface in addition to porewater oxygen and nitrate distributions and organic carbon burial efficiencies. It is further consistent with degradation experiments using fresh phytoplankton reported in a previous study. We propose that an important yet mostly overlooked consideration in upscaling approaches is the proportion of the reactive POC classes reaching the seafloor in addition to their reactivity. The approach presented is applicable to both steady-state and non-steady state scenarios, and links POC degradation kinetics in sedimentary environments to water depth and the POC rain rate to the seafloor.

Detection and Attribution of Regional Climate Change

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

Bala, G; Mirin, A

2007-01-19

We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and oceanmore » circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.« less

Variations of total electron content during geomagnetic disturbances: A model/observation comparison

NASA Technical Reports Server (NTRS)

Roble, G. Lu X. Pi A. D. Richmond R. G.

1997-01-01

This paper studies the ionospheric response to major geomagnetic storm of October 18-19, 1995, using the thermosphere-ionosphere electrodynamic general circulation model (TIE-GCM) simulations and the global ionospheric maps (GIM) of total electron content (TEC) observations from the Global Positioning System (GPS) worldwide network.

The uncertainty of crop yield projections is reduced by improved temperature response functions.

PubMed

Wang, Enli; Martre, Pierre; Zhao, Zhigan; Ewert, Frank; Maiorano, Andrea; Rötter, Reimund P; Kimball, Bruce A; Ottman, Michael J; Wall, Gerard W; White, Jeffrey W; Reynolds, Matthew P; Alderman, Phillip D; Aggarwal, Pramod K; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andrew J; De Sanctis, Giacomo; Doltra, Jordi; Fereres, Elias; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A; Izaurralde, Roberto C; Jabloun, Mohamed; Jones, Curtis D; Kersebaum, Kurt C; Koehler, Ann-Kristin; Liu, Leilei; Müller, Christoph; Naresh Kumar, Soora; Nendel, Claas; O'Leary, Garry; Olesen, Jørgen E; Palosuo, Taru; Priesack, Eckart; Eyshi Rezaei, Ehsan; Ripoche, Dominique; Ruane, Alex C; Semenov, Mikhail A; Shcherbak, Iurii; Stöckle, Claudio; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wallach, Daniel; Wang, Zhimin; Wolf, Joost; Zhu, Yan; Asseng, Senthold

2017-07-17

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

The Uncertainty of Crop Yield Projections Is Reduced by Improved Temperature Response Functions

NASA Technical Reports Server (NTRS)

Wang, Enli; Martre, Pierre; Zhao, Zhigan; Ewert, Frank; Maiorano, Andrea; Rotter, Reimund P.; Kimball, Bruce A.; Ottman, Michael J.; White, Jeffrey W.; Reynolds, Matthew P.;

Multicriteria evaluation of discharge simulation in Dynamic Global Vegetation Models

NASA Astrophysics Data System (ADS)

Yang, Hui; Piao, Shilong; Zeng, Zhenzhong; Ciais, Philippe; Yin, Yi; Friedlingstein, Pierre; Sitch, Stephen; Ahlström, Anders; Guimberteau, Matthieu; Huntingford, Chris; Levis, Sam; Levy, Peter E.; Huang, Mengtian; Li, Yue; Li, Xiran; Lomas, Mark R.; Peylin, Philippe; Poulter, Ben; Viovy, Nicolas; Zaehle, Soenke; Zeng, Ning; Zhao, Fang; Wang, Lei

2015-08-01

In this study, we assessed the performance of discharge simulations by coupling the runoff from seven Dynamic Global Vegetation Models (DGVMs; LPJ, ORCHIDEE, Sheffield-DGVM, TRIFFID, LPJ-GUESS, CLM4CN, and OCN) to one river routing model for 16 large river basins. The results show that the seasonal cycle of river discharge is generally modeled well in the low and middle latitudes but not in the high latitudes, where the peak discharge (due to snow and ice melting) is underestimated. For the annual mean discharge, the DGVMs chained with the routing model show an underestimation. Furthermore, the 30 year trend of discharge is also underestimated. For the interannual variability of discharge, a skill score based on overlapping of probability density functions (PDFs) suggests that most models correctly reproduce the observed variability (correlation coefficient higher than 0.5; i.e., models account for 50% of observed interannual variability) except for the Lena, Yenisei, Yukon, and the Congo river basins. In addition, we compared the simulated runoff from different simulations where models were forced with either fixed or varying land use. This suggests that both seasonal and annual mean runoff has been little affected by land use change but that the trend itself of runoff is sensitive to land use change. None of the models when considered individually show significantly better performances than any other and in all basins. This suggests that based on current modeling capability, a regional-weighted average of multimodel ensemble projections might be appropriate to reduce the bias in future projection of global river discharge.

The "Grey Zone" cold air outbreak global model intercomparison: A cross evaluation using large-eddy simulations

NASA Astrophysics Data System (ADS)

Tomassini, Lorenzo; Field, Paul R.; Honnert, Rachel; Malardel, Sylvie; McTaggart-Cowan, Ron; Saitou, Kei; Noda, Akira T.; Seifert, Axel

2017-03-01

A stratocumulus-to-cumulus transition as observed in a cold air outbreak over the North Atlantic Ocean is compared in global climate and numerical weather prediction models and a large-eddy simulation model as part of the Working Group on Numerical Experimentation "Grey Zone" project. The focus of the project is to investigate to what degree current convection and boundary layer parameterizations behave in a scale-adaptive manner in situations where the model resolution approaches the scale of convection. Global model simulations were performed at a wide range of resolutions, with convective parameterizations turned on and off. The models successfully simulate the transition between the observed boundary layer structures, from a well-mixed stratocumulus to a deeper, partly decoupled cumulus boundary layer. There are indications that surface fluxes are generally underestimated. The amount of both cloud liquid water and cloud ice, and likely precipitation, are under-predicted, suggesting deficiencies in the strength of vertical mixing in shear-dominated boundary layers. But also regulation by precipitation and mixed-phase cloud microphysical processes play an important role in the case. With convection parameterizations switched on, the profiles of atmospheric liquid water and cloud ice are essentially resolution-insensitive. This, however, does not imply that convection parameterizations are scale-aware. Even at the highest resolutions considered here, simulations with convective parameterizations do not converge toward the results of convection-off experiments. Convection and boundary layer parameterizations strongly interact, suggesting the need for a unified treatment of convective and turbulent mixing when addressing scale-adaptivity.

Microbial processes in marine ecosystem models: state of the art and future prospective

NASA Astrophysics Data System (ADS)

Polimene, L.; Butenschon, M.; Blackford, J.; Allen, I.

2012-12-01

Heterotrophic bacteria play a key role in the marine biogeochemistry being the main consumer of dissolved organic matter (DOM) and the main producer of carbon dioxide (CO2) by respiration. Quantifying the carbon and energy fluxes within bacteria (i.e. production, respiration, overflow metabolism etc.) is therefore crucial for the assessment of the global ocean carbon and nutrient cycles. Consequently, the description of bacteria dynamic in ecosystem models is a key (although challenging) issue which cannot be overlooked if we want to properly simulate the marine environment. We present an overview of the microbial processes described in the European Sea Regional Ecosystem Model (ERSEM), a state of the art biogeochemical model resolving carbon and nutrient cycles (N, P, Si and Fe) within the low trophic levels (up to mesozooplankton) of the marine ecosystem. The description of the theoretical assumptions and philosophy underpinning the ERSEM bacteria sub-model will be followed by the presentation of some case studies highlighting the relevance of resolving microbial processes in the simulation of ecosystem dynamics at a local scale. Recent results concerning the implementation of ERSEM on a global ocean domain will be also presented. This latter exercise includes a comparison between simulations carried out with the full bacteria sub-model and simulations carried out with an implicit parameterization of bacterial activity. The results strongly underline the importance of explicitly resolved bacteria in the simulation of global carbon fluxes. Finally, a summary of the future developments along with issues still open on the topic will be presented and discussed.

Sensitivity of Tropospheric Chemical Composition to Halogen-Radical Chemistry Using a Fully Coupled Size-Resolved Multiphase Chemistry-Global Climate System: Halogen Distributions, Aerosol Composition, and Sensitivity of Climate-Relevant Gases

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

Long, M.; Keene, W. C.; Easter, Richard C.

Observations and model studies suggest a significant but highly non-linear role for halogens, primarily Cl and Br, in multiphase atmospheric processes relevant to tropospheric chemistry and composition, aerosol evolution, radiative transfer, weather, and climate. The sensitivity of global atmospheric chemistry to the production of marine aerosol and the associated activation and cycling of inorganic Cl and Br was tested using a size-resolved multiphase coupled chemistry/global climate model (National Center for Atmospheric Research’s Community Atmosphere Model (CAM); v3.6.33). Simulation results showed strong meridional and vertical gradients in Cl and Br species. The simulation reproduced most available observations with reasonable confidence permittingmore » the formulation of potential mechanisms for several previously unexplained halogen phenomena including the enrichment of Br- in submicron aerosol, and the presence of a BrO maximum in the polar free troposphere. However, simulated total volatile Br mixing ratios were generally high in the troposphere. Br in the stratosphere was lower than observed due to the lack of long-lived organobromine species in the simulation. Comparing simulations using chemical mechanisms with and without reactive Cl and Br species demonstrated a significant temporal and spatial sensitivity of primary atmospheric oxidants (O3, HOx, NOx), CH4, and non-methane hydrocarbons (NMHC’s) to halogen cycling. Simulated O3 and NOx were globally lower (65% and 35%, respectively, less in the planetary boundary layer based on median values) in simulations that included halogens. Globally, little impact was seen in SO2 and non-sea-salt SO42- processing due to halogens. Significant regional differences were evident: The lifetime of nss-SO42- was extended downwind of large sources of SO2. The burden and lifetime of DMS (and its oxidation products) were lower by a factor of 5 in simulations that included halogens, versus those without, leading to a 20% reduction in nss-SO42- in the southern hemisphere planetary boundary layer based on median values.« less

Sensitivity of summer ensembles of fledgling superparameterized U.S. mesoscale convective systems to cloud resolving model microphysics and grid configuration

DOE PAGES

Elliott, Elizabeth J.; Yu, Sungduk; Kooperman, Gabriel J.; ...

2016-05-01

The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-likemore » events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. Furthermore, these results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.« less

Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

NASA Technical Reports Server (NTRS)

Koster, Randal Dean; Walker, Gregory K.; Collatz, George J.; Thornton, Peter E.

2013-01-01

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

Modulation of Heavy Rainfall in the Middle East and North Africa by Madden-Julian Oscillation Using High Resolution Atmospheric General Circulation Model

NASA Astrophysics Data System (ADS)

Deng, L.; Stenchikov, G. L.; McCabe, M. F.; Bangalath, H. K.

2014-12-01

Recently, the modulation of subtropical rainfall by the dominant tropical intraseasonal signal of the Madden-Julian Oscillation (MJO), has been explored through the discussion of the MJO-convection-induced Kelvin and Rossby wave related teleconnection patterns. Our study focuses on characterizing the modulation of heavy rainfall in the Middle East and North Africa (MENA) region by the MJO, using the Geophysical Fluid Dynamics Laboratory (GFDL) global High Resolution Atmospheric Model (HIRAM) simulations (25-km; 1979-2012) and a combination of available atmospheric products from satellite, in-situ and reanalysis data. The observed Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) and the simulated SST from GFDL's global coupled carbon-climate Earth System Models (ESM2M) are employed in HIRAM to investigate the sensitivity of the simulated heavy rainfall and MJO to SST. The future trend of the extreme rainfalls and their links to the MJO response to climate change are examined using HIRAM simulations of 2012-2050 with the RCP4.5 and RCP 8.5 scenarios to advance the possibility of characterization and forecasting of future extreme rainfall events in the MENA region.

Does air-sea coupling influence model projections of the effects of the Paris Agreement?

NASA Astrophysics Data System (ADS)

Klingaman, Nicholas; Suckling, Emma; Sutton, Rowan; Dong, Buwen

2017-04-01

The 2015 Paris Agreement includes the long-term goal to hold global-mean temperature to "well below 2°C above pre-industrial levels", with the further stated aim of limiting the global-mean warming to 1.5°C, in the belief that this would "significantly reduce the risks and impacts of climate change". However, it is not clear which risks and impacts would be avoided, or reduced, by achieving a 1.5°C warming instead of a 2.0°C warming. Initial efforts to quantify changes in risk have focused on analysis of existing CMIP5 simulations at levels of global-mean warming close to 1.5°C or 2.0°C, by taking averages over ≈20 year periods. This framework suffers from several drawbacks, however, including the effect of model internal multi-decadal variability, the influence of coupled-model systematic errors on regional circulation patterns, and the presence of a warming trend across the averaging period (i.e., the model is not in steady state). To address these issues, the "Half a degree Additional warming, Prognosis and Projected Impacts" (HAPPI) project is performing large ensembles of atmosphere-only experiments with prescribed sea-surface temperatures (SSTs) for present-day and 1.5°C and 2.0°C scenarios. While these experiments reduce the complications from a limited dataset and coupled-model systematic errors, the use of atmosphere-only models neglects feedbacks between the atmosphere and ocean, which may have substantial effects on the representation of local and regional extremes, and hence on the response of these extremes to global-mean warming. We introduce a set of atmosphere-ocean coupled simulations that incorporate much of the HAPPI experiment design, yet retain a representation of air-sea feedbacks. We use the Met Office Unified Model Global Ocean Mixed Layer (MetUM-GOML) model, which comprises the MetUM atmospheric model coupled to many columns of the one-dimensional K Profile Parameterization mixed-layer ocean. Critically, the MetUM-GOML ocean mean state can be controlled by prescribed, seasonally varying corrections to temperature and salinity, which substantially reduce SST biases without damping variability. This allows the present-day MetUM-GOML experiment to have a ocean mean state very close to the observed climatology (global RMSE ≈ 0.25°C). We perform three 150-year experiments with MetUM-GOML for (a) present-day (1976-2005 climatology) and for future scenarios with global-mean temperatures (b) 1.5°C and (c) 2.0°C above pre-industrial levels. For (b) and (c), we achieve these warming levels by increasing the CO2 concentrations in MetUM-GOML, as well as by adjusting the prescribed sea ice using change factors derived from a transient simulation with the fully coupled Met Office model. We analyse projected global and regional changes in temperature, precipitation and atmospheric circulation in our MetUM-GOML simulations, focusing on seasonal means, multi-annual persistence of seasonal extremes (e.g., the probability of consecutive wet summers) and intra-seasonal extremes (e.g., heatwaves, droughts, floods). To identify the influence of air-sea coupling on these projections, we compare the MetUM-GOML simulations to 150-year atmosphere-only simulations with prescribed daily SSTs from the corresponding MetUM-GOML runs. This comparison demonstrates whether atmosphere-ocean feedbacks influence the projections of changes hydro-meteorological extremes in a warmer world, as well as whether these feedbacks affect the assessment of the impacts avoided by limiting global-mean temperature change to 1.5°C. Our results will inform the choice of model framework for, and hence the experiment design of, further efforts to characterise the response to a fixed global-mean temperature increase, as well as future climate-change attribution experiments.

Climatic Consequences and Agricultural Impact of Regional Nuclear Conflict

NASA Astrophysics Data System (ADS)

Toon, O. B.; Robock, A.; Mills, M. J.; Xia, L.

2013-05-01

A nuclear war between India and Pakistan, with each country using 50 Hiroshima-sized atom bombs as airbursts on urban areas, would inject smoke from the resulting fires into the stratosphere.This could produce climate change unprecedented in recorded human history and global-scale ozone depletion, with enhanced ultraviolet (UV) radiation reaching the surface.Simulations with the Whole Atmosphere Community Climate Model (WACCM), run at higher vertical and horizontal resolution than a previous simulation with the NASA Goddard Institute for Space Studies ModelE, and incorporating ozone chemistry for the first time, show a longer stratospheric residence time for smoke and hence a longer-lasting climate response, with global average surface air temperatures still 1.1 K below normal and global average precipitation 4% below normal after a decade.The erythemal dose from the enhanced UV radiation would greatly increase, in spite of enhanced absorption by the remaining smoke, with the UV index more than 3 units higher in the summer midlatitudes, even after a decade. Scenarios of changes in temperature, precipitation, and downward shortwave radiation from the ModelE and WACCM simulations, applied to the Decision Support System for Agrotechnology Transfer crop model for winter wheat, rice, soybeans, and maize by perturbing observed time series with anomalies from the regional nuclear war simulations, produce decreases of 10-50% in yield averaged over a decade, with larger decreases in the first several years, over the midlatitudes of the Northern Hemisphere. The impact of the nuclear war simulated here, using much less than 1% of the global nuclear arsenal, would be devastating to world agricultural production and trade, possibly sentencing a billion people now living marginal existences to starvation.The continued environmental threat of the use of even a small number of nuclear weapons must be considered in nuclear policy deliberations in Russia, the U.S., and the rest of the world.

Climatic Consequences and Agricultural Impact of Regional Nuclear Conflict

NASA Astrophysics Data System (ADS)

Robock, Alan; Mills, Michael; Toon, Owen Brian; Xia, Lili

2013-04-01

A nuclear war between India and Pakistan, with each country using 50 Hiroshima-sized atom bombs as airbursts on urban areas, would inject smoke from the resulting fires into the stratosphere. This could produce climate change unprecedented in recorded human history and global-scale ozone depletion, with enhanced ultraviolet (UV) radiation reaching the surface. Simulations with the NCAR Whole Atmosphere Community Climate Model (WACCM), run at higher vertical and horizontal resolution than a previous simulation with the NASA Goddard Institute for Space Studies ModelE, and incorporating ozone chemistry for the first time, show a longer stratospheric residence time for smoke and hence a longer-lasting climate response, with global average surface air temperatures still 1.1 K below normal and global average precipitation 4% below normal after a decade. The erythemal dose from the enhanced UV radiation would greatly increase, in spite of enhanced absorption by the remaining smoke, with the UV index more than 3 units higher in the summer midlatitudes, even after a decade. Scenarios of changes in temperature, precipitation, and downward shortwave radiation from the ModelE and WACCM simulations, applied to the Decision Support System for Agrotechnology Transfer crop model for winter wheat, rice, soybeans, and maize by perturbing observed time series with anomalies from the regional nuclear war simulations, produce decreases of 10-50% in yield averaged over a decade, with larger decreases in the first several years, over several regions in the midlatitudes of the Northern Hemisphere. The impact of the nuclear war simulated here, using much less than 1% of the global nuclear arsenal, would be devastating to world agricultural production and trade, possibly sentencing a billion people now living marginal existences to starvation. The continued environmental threat of the use of even a small number of nuclear weapons must be considered in nuclear policy deliberations in Russia, the U.S., and the rest of the world

Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

NASA Astrophysics Data System (ADS)

Hogrefe, Christian; Liu, Peng; Pouliot, George; Mathur, Rohit; Roselle, Shawn; Flemming, Johannes; Lin, Meiyun; Park, Rokjin J.

2018-03-01

This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry - Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated surface ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

Evaluation of the Simulation of Arctic and Antarctic Sea Ice Coverages by Eleven Major Global Climate Models

NASA Technical Reports Server (NTRS)

Parksinson, Claire; Vinnikov, Konstantin Y.; Cavalieri, Donald J.

2005-01-01

Comparison of polar sea ice results from 11 major global climate models and satellite-derived observations for 1979-2004 reveals that each of the models is simulating seasonal cycles that are phased at least approximately correctly in both hemispheres. Each is also simulating various key aspects of the observed ice cover distributions, such as winter ice not only throughout the central Arctic basin but also throughout Hudson Bay, despite its relatively low latitudes. However, some of the models simulate too much ice, others too little ice (in some cases varying depending on hemisphere and/or season), and some match the observations better in one season versus another. Several models do noticeably better in the Northern Hemisphere than in the Southern Hemisphere, and one does noticeably better in the Southern Hemisphere. In the Northern Hemisphere all simulate monthly average ice extents to within +/-5.1 x 10(exp 6)sq km of the observed ice extent throughout the year; and in the Southern Hemisphere all except one simulate the monthly averages to within +/-6.3 x 10(exp 6) sq km of the observed values. All the models properly simulate a lack of winter ice to the west of Norway; however, most do not obtain as much absence of ice immediately north of Norway as the observations show, suggesting an under simulation of the North Atlantic Current. The spread in monthly averaged ice extents amongst the 11 model simulations is greater in the Southern Hemisphere than in the Northern Hemisphere and greatest in the Southern Hemisphere winter and spring.

A global carbon assimilation system based on a dual optimization method

NASA Astrophysics Data System (ADS)

Zheng, H.; Li, Y.; Chen, J. M.; Wang, T.; Huang, Q.; Huang, W. X.; Wang, L. H.; Li, S. M.; Yuan, W. P.; Zheng, X.; Zhang, S. P.; Chen, Z. Q.; Jiang, F.

2015-02-01

Ecological models are effective tools for simulating the distribution of global carbon sources and sinks. However, these models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) to an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state simultaneously. We use GCAS-DOM to estimate the global distribution of the CO2 flux on 1° × 1° grid cells for the period from 2001 to 2007. Results show that land and ocean absorb -3.63 ± 0.50 and -1.82 ± 0.16 Pg C yr-1, respectively. North America, Europe and China contribute -0.98 ± 0.15, -0.42 ± 0.08 and -0.20 ± 0.29 Pg C yr-1, respectively. The uncertainties in the flux after optimization by GCAS-DOM have been remarkably reduced by more than 60%. Through parameter optimization, GCAS-DOM can provide improved estimates of the carbon flux for each PFT. Coniferous forest (-0.97 ± 0.27 Pg C yr-1) is the largest contributor to the global carbon sink. Fluxes of once-dominant deciduous forest generated by the Boreal Ecosystems Productivity Simulator (BEPS) are reduced to -0.78 ± 0.23 Pg C yr-1, the third largest carbon sink.

Global O3-CO correlations in a chemistry and transport model during July-August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions

NASA Astrophysics Data System (ADS)

Choi, Hyun-Deok; Liu, Hongyu; Crawford, James H.; Considine, David B.; Allen, Dale J.; Duncan, Bryan N.; Horowitz, Larry W.; Rodriguez, Jose M.; Strahan, Susan E.; Zhang, Lin; Liu, Xiong; Damon, Megan R.; Steenrod, Stephen D.

2017-07-01

We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618 hPa) ozone-carbon monoxide (O3-CO) correlations determined by the measurements from the Tropospheric Emission Spectrometer (TES) aboard NASA's Aura satellite during boreal summer (July-August). The model is driven by three meteorological data sets (finite-volume General Circulation Model (fvGCM) with sea surface temperature for 1995, Goddard Earth Observing System Data Assimilation System Version 4 (GEOS-4 DAS) for 2005, and Modern-Era Retrospective Analysis for Research and Applications (MERRA) for 2005), allowing us to examine the sensitivity of model O3-CO correlations to input meteorological data. Model simulations of radionuclide tracers (222Rn, 210Pb, and 7Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O3 values are evaluated with climatological profiles from ozonesonde measurements and satellite tropospheric O3 columns. Despite the fact that the three simulations show significantly different global and regional distributions of O3 and CO concentrations, they show similar patterns of O3-CO correlations on a global scale. All model simulations sampled along the TES orbit track capture the observed positive O3-CO correlations in the Northern Hemisphere midlatitude continental outflow and the Southern Hemisphere subtropics. While all simulations show strong negative correlations over the Tibetan Plateau, northern Africa, the subtropical eastern North Pacific, and the Caribbean, TES O3 and CO concentrations at 618 hPa only show weak negative correlations over much narrower areas (i.e., the Tibetan Plateau and northern Africa). Discrepancies in regional O3-CO correlation patterns in the three simulations may be attributed to differences in convective transport, stratospheric influence, and subsidence, among other processes. To understand how various emissions drive global O3-CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O3 and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NOx emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O3-CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O3-CO correlations than other emissions but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O3 is consumed and CO generated during the atmospheric oxidation process of isoprene under low-NOx conditions. We find that lightning NOx emissions degrade both positive correlations at mid- and high latitudes and negative correlations in the tropics because ozone production downwind of lightning NOx emissions is not directly related to the emission and transport of CO. Our study concludes that O3-CO correlations may be used effectively to constrain the sources of regional tropospheric O3 in global 3-D models, especially for those regions where convective transport of pollution plays an important role.

GLOFRIM - A globally applicable framework for integrated hydrologic-hydrodynamic inundation modelling

NASA Astrophysics Data System (ADS)

Hoch, J. M.; Neal, J. C.; Baart, F.; Van Beek, L. P.; Winsemius, H.; Bates, P. D.; Bierkens, M. F.

2017-12-01

Currently, many approaches to provide detailed flood hazard and risk estimates are built upon specific hydrologic or hydrodynamic model routines. By applying these routines in stand-alone mode important processes can however not accurately be described. For instance, global hydrologic models run at coarse spatial resolution, not supporting the detailed simulation of flood hazard. Hydrodynamic models excel in the computations of open water flow dynamics, but dependent on specific runoff or observed discharge as input. In most cases hydrodynamic models are forced at the boundaries and thus cannot account for water sources within the model domain, limiting the simulation of inundation dynamics to reaches fed by upstream boundaries. Recently, Hoch et al. (HESS, 2017) coupled PCR-GLOBWB (PCR) with the hydrodynamic model Delft3D Flexible Mesh (DFM). By means of the Basic Model Interface both models were connected on a cell-by-cell basis, allowing for spatially explicit coupling. Model results showed that discharge simulations can profit from model coupling compared to stand-alone runs. As model results of a coupled simulation depend on the quality of the models, it would be worthwhile to allow a suite of models to be coupled. To facilitate this, we present GLOFRIM, a globally applicable framework for integrated hydrologic-hydrodynamic inundation modelling. In the current version coupling between PCR and both DFM and LISFLOOD-FP (LFP) can be established (Hoch et al., GMDD, 2017). First results show that differences between both hydrodynamic models are present in the timing of peak discharge which is most likely due to differences in channel-floodplain interactions and bathymetry processing. Having benchmarked inundation extent, LFP and DFM agree for around half of the inundated area which is attributable to variations in grid size. Results also indicate that, despite using identical boundary conditions and forcing, the schematization itself as well as internal processes can still greatly influence results. In general, the application of GLOFRIM brings several advantages. For example, with PCR being a global model, it is possible to reduce the dependency of observation data for discharge boundaries, and benchmarking of hydrodynamic models is greatly facilitated by employing identical hydrologic forcing.

Drivers and uncertainties of future global marine primary production in marine ecosystem models

NASA Astrophysics Data System (ADS)

Laufkötter, C.; Vogt, M.; Gruber, N.; Aita-Noguchi, M.; Aumont, O.; Bopp, L.; Buitenhuis, E.; Doney, S. C.; Dunne, J.; Hashioka, T.; Hauck, J.; Hirata, T.; John, J.; Le Quéré, C.; Lima, I. D.; Nakano, H.; Seferian, R.; Totterdell, I.; Vichi, M.; Völker, C.

2015-12-01

Past model studies have projected a global decrease in marine net primary production (NPP) over the 21st century, but these studies focused on the multi-model mean rather than on the large inter-model differences. Here, we analyze model-simulated changes in NPP for the 21st century under IPCC's high-emission scenario RCP8.5. We use a suite of nine coupled carbon-climate Earth system models with embedded marine ecosystem models and focus on the spread between the different models and the underlying reasons. Globally, NPP decreases in five out of the nine models over the course of the 21st century, while three show no significant trend and one even simulates an increase. The largest model spread occurs in the low latitudes (between 30° S and 30° N), with individual models simulating relative changes between -25 and +40 %. Of the seven models diagnosing a net decrease in NPP in the low latitudes, only three simulate this to be a consequence of the classical interpretation, i.e., a stronger nutrient limitation due to increased stratification leading to reduced phytoplankton growth. In the other four, warming-induced increases in phytoplankton growth outbalance the stronger nutrient limitation. However, temperature-driven increases in grazing and other loss processes cause a net decrease in phytoplankton biomass and reduce NPP despite higher growth rates. One model projects a strong increase in NPP in the low latitudes, caused by an intensification of the microbial loop, while NPP in the remaining model changes by less than 0.5 %. While models consistently project increases NPP in the Southern Ocean, the regional inter-model range is also very substantial. In most models, this increase in NPP is driven by temperature, but it is also modulated by changes in light, macronutrients and iron as well as grazing. Overall, current projections of future changes in global marine NPP are subject to large uncertainties and necessitate a dedicated and sustained effort to improve the models and the concepts and data that guide their development.

A reduction in the asymmetry of ENSO amplitude due to global warming: The role of atmospheric feedback

NASA Astrophysics Data System (ADS)

Ham, Yoo-Geun

2017-08-01

This study analyzes a reduction in the asymmetry of El Niño Southern-Oscillation (ENSO) amplitude due to global warming in Coupled Model Intercomparison Project Phase 5 models. The multimodel-averaged Niño3 skewness during December-February season decreased approximately 40% in the RCP4.5 scenario compared to that in the historical simulation. The change in the nonlinear relationship between sea surface temperature (SST) and precipitation is a key factor for understanding the reduction in ENSO asymmetry due to global warming. In the historical simulations, the background SST leading to the greatest precipitation sensitivity (SST for Maximum Precipitation Sensitivity, SST_MPS) occurs when the positive SST anomaly is located over the equatorial central Pacific. Therefore, an increase in climatological SST due to global warming weakens the atmospheric response during El Niño over the central Pacific. However, the climatological SST over this region in the historical simulation is still lower than the SST_MPS for the negative SST anomaly; therefore, a background SST increase due to global warming can further increase precipitation sensitivity. The atmospheric feedbacks during La Niña are enhanced and increase the La Niña amplitude due to global warming.

Evaluation of UTLS Carbon Monoxide Simulations in GMI and GEOS-Chem Chemical Transport Models using Aura MLS Observations

NASA Technical Reports Server (NTRS)

Huang, Lei; Jiang, Jonathan H.; Murray, Lee T.; Damon, Megan R.; Su, Hui; Livesey, Nathaniel J.

2016-01-01

This study evaluates the distribution and variation of carbon monoxide (CO) in the upper troposphere and lower stratosphere (UTLS) during 2004-2012 as simulated by two chemical transport models, using the latest version of Aura Microwave Limb Sounder (MLS) observations. The simulated spatial distributions, temporal variations and vertical transport of CO in the UTLS region are compared with those observed by MLS. We also investigate the impact of surface emissions and deep convection on CO concentrations in the UTLS over different regions, using both model simulations and MLS observations. Global Modeling Initiative (GMI) and GEOS-Chem simulations of UTLS CO both show similar spatial distributions to observations. The global mean CO values simulated by both models agree with MLS observations at 215 and 147 hPa, but are significantly underestimated by more than 40% at 100 hPa. In addition, the models underestimate the peak CO values by up to 70% at 100 hPa, 60% at 147 hPa and 40% at 215 hPa, with GEOS-Chem generally simulating more CO at 100 hPa and less CO at 215 hPa than GMI. The seasonal distributions of CO simulated by both models are in better agreement with MLS in the Southern Hemisphere (SH) than in the Northern Hemisphere (NH), with disagreements between model and observations over enhanced CO regions such as southern Africa. The simulated vertical transport of CO shows better agreement with MLS in the tropics and the SH subtropics than the NH subtropics. We also examine regional variations in the relationships among surface CO emission, convection and UTLS CO concentrations. The two models exhibit emission-convection- CO relationships similar to those observed by MLS over the tropics and some regions with enhanced UTLS CO.

Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

NASA Technical Reports Server (NTRS)

Beaudoing, Hiroko Kato; Rodell, Matthew; Ozdogan, Mutlu

2010-01-01

Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections

NASA Technical Reports Server (NTRS)

Little, Christopher M.; Horton, Radley M.; Kopp, Robert E.; Oppenheimer, Michael; Yip, Stan

2015-01-01

The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere-ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.

Global change and terrestrial hydrology - A review

NASA Technical Reports Server (NTRS)

Dickinson, Robert E.

1991-01-01

This paper reviews the role of terrestrial hydrology in determining the coupling between the surface and atmosphere. Present experience with interactive numerical simulation is discussed and approaches to the inclusion of land hydrology in global climate models ae considered. At present, a wide range of answers as to expected changes in surface hydrology is given by nominally similar models. Studies of the effects of tropical deforestation and global warming illustrate this point.

Watershed scale response to climate change--Yampa River Basin, Colorado

USGS Publications Warehouse

Hay, Lauren E.; Battaglin, William A.; Markstrom, Steven L.

2012-01-01

General Circulation Model simulations of future climate through 2099 project a wide range of possible scenarios. To determine the sensitivity and potential effect of long-term climate change on the freshwater resources of the United States, the U.S. Geological Survey Global Change study, "An integrated watershed scale response to global change in selected basins across the United States" was started in 2008. The long-term goal of this national study is to provide the foundation for hydrologically based climate change studies across the nation. Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Yampa River Basin at Steamboat Springs, Colorado.

Regional scaling of annual mean precipitation and water availability with global temperature change

NASA Astrophysics Data System (ADS)

Greve, Peter; Gudmundsson, Lukas; Seneviratne, Sonia I.

2018-03-01

Changes in regional water availability belong to the most crucial potential impacts of anthropogenic climate change, but are highly uncertain. It is thus of key importance for stakeholders to assess the possible implications of different global temperature thresholds on these quantities. Using a subset of climate model simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), we derive here the sensitivity of regional changes in precipitation and in precipitation minus evapotranspiration to global temperature changes. The simulations span the full range of available emission scenarios, and the sensitivities are derived using a modified pattern scaling approach. The applied approach assumes linear relationships on global temperature changes while thoroughly addressing associated uncertainties via resampling methods. This allows us to assess the full distribution of the simulations in a probabilistic sense. Northern high-latitude regions display robust responses towards wetting, while subtropical regions display a tendency towards drying but with a large range of responses. Even though both internal variability and the scenario choice play an important role in the overall spread of the simulations, the uncertainty stemming from the climate model choice usually accounts for about half of the total uncertainty in most regions. We additionally assess the implications of limiting global mean temperature warming to values below (i) 2 K or (ii) 1.5 K (as stated within the 2015 Paris Agreement). We show that opting for the 1.5 K target might just slightly influence the mean response, but could substantially reduce the risk of experiencing extreme changes in regional water availability.

Effects of a transient sea surface temperature anomaly on the energetics of the Mintz-Arakawa model atmosphere

NASA Technical Reports Server (NTRS)

Chow, S. H.

1974-01-01

The possible response of the atmosphere, as simulated by the two level Mintz-Arakawa global general circulation model, to a transient North Pacific sea surface temperature anomaly is investigated in terms of the energetics both in the spatial and wave number domains. Results indicate that the transient SST variations of reasonable magnitude in the North Pacific Ocean can induce a disturbing effect on the global energetics both in the spatial and wave number domains. The ability of the two level Mintz-Arakawa model to simulate the atmospheric energetics is also examined. Except in the tropics, the model exhibits a reasonable and realistic energy budget.

Multi-millennia simulation of Greenland deglaciation from the Max-Plank-Institute Model (MPI-ISM) 2xCO2 simulation

NASA Astrophysics Data System (ADS)

Cabot, Vincent; Vizcaino, Miren; Mikolajewicz, Uwe

2016-04-01

Long-term ice sheet and climate coupled simulations are of great interest since they assess how the Greenland Ice Sheet (GrIS) will respond to global warming and how GrIS changes will impact on the climate system. We have run the Max-Plank-Institute Earth System Model coupled with an Ice Sheet Model (SICOPOLIS) over a time period of 10500 years under two times CO2 forcing. This is a coupled atmosphere (ECHAM5T31), ocean (MPI-OM), dynamic vegetation (LPJ), and ice sheet (SICOPOLIS, 10 km horizontal resolution) model. Given the multi-millennia simulation, the horizontal spatial resolution of the atmospheric component is relatively coarse (3.75°). A time-saving technique (asynchronous coupling) is used once the global climate reaches quasi-equilibrium. In our doubling-CO2 simulation, the GrIS is expected to break up into two pieces (one ice cap in the far north on one ice sheet in the south and east) after 3000 years. During the first 500 simulation years, the GrIS climate and surface mass balance (SMB) are mainly affected by the greenhouse effect-forced climate change. After the simulated year 500, the global climate reaches quasi-equilibrium. Henceforth Greenland climate change is mainly due to ice sheet decay. GrIS albedo reduction enhances melt and acts as a powerful feedback for deglaciation. Due to increased cloudiness in the Arctic region as a result of global climate change, summer incoming shortwave radiation is substantially reduced over Greenland, reducing deglaciation rates. At the end of the simulation, Greenland becomes green with forest growing over the newly deglaciated regions. References: Helsen, M. M., van de Berg, W. J., van de Wal, R. S. W., van den Broeke, M. R., and Oerlemans, J. (2013), Coupled regional climate-ice-sheet simulation shows limited Greenland ice loss during the Eemian, Climate of the Past, 9, 1773-1788, doi: 10.5194/cp-9-1773-2013 Helsen, M. M., van de Wal, R. S. W., van den Broeke, M. R., van de Berg, W. J., and Oerlemans, J. (2015), Coupling of climate models and ice sheet models by the surface mass balance gradients: application to the Greenland Ice Sheet, The Cryosphere, 6, 255-272, doi: 10.5194/tc-6-255-2012 Robinson, A., Calov, R., and Ganopolski, A. (2011), Greenland ice sheet model parameters constrained using simulations of the Eemian Interglacial, Climate of the Past, 7, 381-396, doi: 10.5194/cp-7-381-2011 Vizcaino, M., Mikolajewicz, U., Ziemen, F., Rodehacke, C. B., Greve, R., and van den Broeke, M. R. (2015), Coupled simulations of Greenland Ice Sheet and climate change up to A.D. 2300, Geophysical Research Letters, 42, doi: 10.1002/2014GL061142

The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM

NASA Technical Reports Server (NTRS)

Parkinson, Claire L.; Rind, David; Healy, Richard J.; Martinson, Douglas G.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.

The impact of biogenic, anthropogenic, and biomass burning volatile organic compound emissions on regional and seasonal variations in secondary organic aerosol

NASA Astrophysics Data System (ADS)

Kelly, Jamie M.; Doherty, Ruth M.; O'Connor, Fiona M.; Mann, Graham W.

2018-05-01

The global secondary organic aerosol (SOA) budget is highly uncertain, with global annual SOA production rates, estimated from global models, ranging over an order of magnitude and simulated SOA concentrations underestimated compared to observations. In this study, we use a global composition-climate model (UKCA) with interactive chemistry and aerosol microphysics to provide an in-depth analysis of the impact of each VOC source on the global SOA budget and its seasonality. We further quantify the role of each source on SOA spatial distributions, and evaluate simulated seasonal SOA concentrations against a comprehensive set of observations. The annual global SOA production rates from monoterpene, isoprene, biomass burning, and anthropogenic precursor sources is 19.9, 19.6, 9.5, and 24.6 Tg (SOA) a-1, respectively. When all sources are included, the SOA production rate from all sources is 73.6 Tg (SOA) a-1, which lies within the range of estimates from previous modelling studies. SOA production rates and SOA burdens from biogenic and biomass burning SOA sources peak during Northern Hemisphere (NH) summer. In contrast, the anthropogenic SOA production rate is fairly constant all year round. However, the global anthropogenic SOA burden does have a seasonal cycle which is lowest during NH summer, which is probably due to enhanced wet removal. Inclusion of the new SOA sources also accelerates the ageing by condensation of primary organic aerosol (POA), making it more hydrophilic, leading to a reduction in the POA lifetime. With monoterpene as the only source of SOA, simulated SOA and total organic aerosol (OA) concentrations are underestimated by the model when compared to surface and aircraft measurements. Model agreement with observations improves with all new sources added, primarily due to the inclusion of the anthropogenic source of SOA, although a negative bias remains. A further sensitivity simulation was performed with an increased anthropogenic SOA reaction yield, corresponding to an annual global SOA production rate of 70.0 Tg (SOA) a-1. Whilst simulated SOA concentrations improved relative to observations, they were still underestimated in urban environments and overestimated further downwind and in remote environments. In contrast, the inclusion of SOA from isoprene and biomass burning did not improve model-observations biases substantially except at one out of two tropical locations. However, these findings may reflect the very limited availability of observations to evaluate the model, which are primarily located in the NH mid-latitudes where anthropogenic emissions are high. Our results highlight that, within the current uncertainty limits in SOA sources and reaction yields, over the NH mid-latitudes, a large anthropogenic SOA source results in good agreement with observations. However, more observations are needed to establish the importance of biomass burning and biogenic sources of SOA in model agreement with observations.

Adding ecosystem function to agent-based land use models

USDA-ARS?s Scientific Manuscript database

The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeoche...

Simulation of the West African monsoon onset using the HadGEM3-RA regional climate model

NASA Astrophysics Data System (ADS)

Diallo, Ismaïla; Bain, Caroline L.; Gaye, Amadou T.; Moufouma-Okia, Wilfran; Niang, Coumba; Dieng, Mame D. B.; Graham, Richard

2014-08-01

The performance of the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) in simulating the West African monsoon (WAM) is investigated. We focus on performance for monsoon onset timing and for rainfall totals over the June-July-August (JJA) season and on the model's representation of the underlying dynamical processes. Experiments are driven by the ERA-Interim reanalysis and follow the CORDEX experimental protocol. Simulations with the HadGEM3 global model, which shares a common physical formulation with HadGEM3-RA, are used to gain insight into the causes of HadGEM3-RA simulation errors. It is found that HadGEM3-RA simulations of monsoon onset timing are realistic, with an error in mean onset date of two pentads. However, the model has a dry bias over the Sahel during JJA of 15-20 %. Analysis suggests that this is related to errors in the positioning of the Saharan heat low, which is too far south in HadGEM3-RA and associated with an insufficient northward reach of the south-westerly low-level monsoon flow and weaker moisture convergence over the Sahel. Despite these biases HadGEM3-RA's representation of the general rainfall distribution during the WAM appears superior to that of ERA-Interim when using Global Precipitation Climatology Project or Tropical Rain Measurement Mission data as reference. This suggests that the associated dynamical features seen in HadGEM3-RA can complement the physical picture available from ERA-Interim. This approach is supported by the fact that the global HadGEM3 model generates realistic simulations of the WAM without the benefit of pseudo-observational forcing at the lateral boundaries; suggesting that the physical formulation shared with HadGEM3-RA, is able to represent the driving processes. HadGEM3-RA simulations confirm previous findings that the main rainfall peak near 10°N during June-August is maintained by a region of mid-tropospheric ascent located, latitudinally, between the cores of the African Easterly Jet and Tropical Easterly Jet that intensifies around the time of onset. This region of ascent is weaker and located further south near 5°N in the driving ERA-Interim reanalysis, for reasons that may be related to the coarser resolution or the physics of the underlying model, and this is consistent with a less realistic latitudinal rainfall profile than found in the HadGEM3-RA simulations.

Representation of fine scale atmospheric variability in a nudged limited area quasi-geostrophic model: application to regional climate modelling

NASA Astrophysics Data System (ADS)

Omrani, H.; Drobinski, P.; Dubos, T.

2009-09-01

In this work, we consider the effect of indiscriminate nudging time on the large and small scales of an idealized limited area model simulation. The limited area model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by its « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. Compared to a previous study by Salameh et al. (2009) who investigated the existence of an optimal nudging time minimizing the error on both large and small scale in a linear model, we here use a fully non-linear model which allows us to represent the chaotic nature of the atmosphere: given the perfect quasi-geostrophic model, errors in the initial conditions, concentrated mainly in the smaller scales of motion, amplify and cascade into the larger scales, eventually resulting in a prediction with low skill. To quantify the predictability of our quasi-geostrophic model, we measure the rate of divergence of the system trajectories in phase space (Lyapunov exponent) from a set of simulations initiated with a perturbation of a reference initial state. Predictability of the "global", periodic model is mostly controlled by the beta effect. In the LAM, predictability decreases as the domain size increases. Then, the effect of large-scale nudging is studied by using the "perfect model” approach. Two sets of experiments were performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic LAM where the size of the LAM domain comes into play in addition to the first set of simulations. In the two sets of experiments, the best spatial correlation between the nudge simulation and the reference is observed with a nudging time close to the predictability time.

JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

NASA Astrophysics Data System (ADS)

Osborne, T.; Gornall, J.; Hooker, J.; Williams, K.; Wiltshire, A.; Betts, R.; Wheeler, T.

2014-10-01

Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soy bean, maize and rice is presented. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soy bean at the global level, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index and canopy height better than in standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an earth system and crop yield model perspective is encouraging however, more effort is needed to develop the parameterisation of the model for specific applications. Key future model developments identified include the specification of the yield gap to enable better representation of the spatial variability in yield.

Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models: Global and Arctic Black Carbon Processes

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

Mahmood, Rashed; von Salzen, Knut; Flanner, Mark

2016-06-22

This study quantifies black carbon (BC) processes in three global climate models and one chemistry transport model, with focus on the seasonality of BC transport, emissions, wet and dry deposition in the Arctic. In the models, transport of BC to the Arctic from lower latitudes is the major BC source for this region while Arctic emissions are very small. All models simulated a similar annual cycle of BC transport from lower latitudes to the Arctic, with maximum transport occurring in July. Substantial differences were found in simulated BC burdens and vertical distributions, with CanAM (NorESM) producing the strongest (weakest) seasonalmore » cycle. CanAM also has the shortest annual mean residence time for BC in the Arctic followed by SMHI-MATCH, CESM and NorESM. The relative contribution of wet and dry deposition rates in removing BC varies seasonally and is one of the major factors causing seasonal variations in BC burdens in the Arctic. Overall, considerable differences in wet deposition efficiencies in the models exist and are a leading cause of differences in simulated BC burdens. Results from model sensitivity experiments indicate that scavenging of BC in convective clouds acts to substantially increase the overall efficiency of BC wet deposition in the Arctic, which leads to low BC burdens and a more pronounced seasonal cycle compared to simulations without convective BC scavenging. In contrast, the simulated seasonality of BC concentrations in the upper troposphere is only weakly influenced by wet deposition in stratiform (layer) clouds whereas lower tropospheric concentrations are highly sensitive.« less

Orographic precipitation at global and regional scales: Observational uncertainty and evaluation of 25-km global model simulations

NASA Astrophysics Data System (ADS)

Schiemann, Reinhard; Roberts, Charles J.; Bush, Stephanie; Demory, Marie-Estelle; Strachan, Jane; Vidale, Pier Luigi; Mizielinski, Matthew S.; Roberts, Malcolm J.

2015-04-01

Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean precipitation/evaporation may be up to 10 Wm-2 (about 0.35 mm day-1) larger than the estimate obtained from GPCP. While the main part of this discrepancy is thought to be due to the underestimation of remotely-sensed ocean precipitation, there is also considerable uncertainty about 'unobserved' precipitation over land, in particular in the form of snow in regions of high latitude/altitude. We aim to contribute to this discussion, at least at a qualitative level, by considering case studies of how area-averaged mountain precipitation is represented in different observational datasets and by HadGEM3-GA3 at different resolutions. Our results show that the AGCM simulates considerably more orographic precipitation at higher resolution. We find this at the global scale both for the winter and summer hemispheres, as well as in several case studies in mid-latitude regions. Gridded observations based on gauge measurements generally capture the mesoscale spatial variability of precipitation, but differ strongly from one another in the magnitude of area-averaged precipitation, so that they are of very limited use for evaluating this aspect of the modelled climate. We are currently conducting a sensitivity experiment (coarse-grained orography in high-resolution HadGEM3) to further investigate the resolution sensitivity seen in the model.

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

DOE PAGES

Blanc, Élodie

2017-01-26

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather,more » especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments.« less

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

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

Blanc, Élodie

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather,more » especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments.« less

Parameter estimation of a pulp digester model with derivative-free optimization strategies

NASA Astrophysics Data System (ADS)

Seiça, João C.; Romanenko, Andrey; Fernandes, Florbela P.; Santos, Lino O.; Fernandes, Natércia C. P.

2017-07-01

The work concerns the parameter estimation in the context of the mechanistic modelling of a pulp digester. The problem is cast as a box bounded nonlinear global optimization problem in order to minimize the mismatch between the model outputs with the experimental data observed at a real pulp and paper plant. MCSFilter and Simulated Annealing global optimization methods were used to solve the optimization problem. While the former took longer to converge to the global minimum, the latter terminated faster at a significantly higher value of the objective function and, thus, failed to find the global solution.

An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems

Treesearch

Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun

2002-01-01

Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...

Solar irradiance reduction to counteract radiative forcing from a quadrupling of CO2: climate responses simulated by four earth system models

NASA Astrophysics Data System (ADS)

Schmidt, H.; Alterskjær, K.; Karam, D. Bou; Boucher, O.; Jones, A.; Kristjánsson, J. E.; Niemeier, U.; Schulz, M.; Aaheim, A.; Benduhn, F.; Lawrence, M.; Timmreck, C.

2012-06-01

In this study we compare the response of four state-of-the-art Earth system models to climate engineering under scenario G1 of two model intercomparison projects: GeoMIP (Geoengineering Model Intercomparison Project) and IMPLICC (EU project "Implications and risks of engineering solar radiation to limit climate change"). In G1, the radiative forcing from an instantaneous quadrupling of the CO2 concentration, starting from the preindustrial level, is balanced by a reduction of the solar constant. Model responses to the two counteracting forcings in G1 are compared to the preindustrial climate in terms of global means and regional patterns and their robustness. While the global mean surface air temperature in G1 remains almost unchanged compared to the control simulation, the meridional temperature gradient is reduced in all models. Another robust response is the global reduction of precipitation with strong effects in particular over North and South America and northern Eurasia. In comparison to the climate response to a quadrupling of CO2 alone, the temperature responses are small in experiment G1. Precipitation responses are, however, in many regions of comparable magnitude but globally of opposite sign.

Estimation of wetland methane emissions in a biogeochemical model integrated in CESM: sensitivity analysis and comparison against surface and atmospheric measurements

NASA Astrophysics Data System (ADS)

Meng, L.; Mahowald, N. M.; Hess, P. G.; Yavitt, J. B.; Riley, W. J.; Subin, Z. M.; Lawrence, D. M.; Swenson, S. C.; Jauhiainen, J.; Fuka, D. R.

2012-12-01

Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources is still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al. 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model because there are large differences between simulated fractional inundation and satellite observations and thus we do not use CLM4 simulated inundated area. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993-2004 were 256 Tg CH4 y-1 (including the soil sink). Tropical wetlands contributed 201 Tg CH4 y-1, or 78% of the global wetland flux. Northern latitude (>50N) systems contributed 12 Tg CH4 y-1. Our sensitivity studies show a large range (150-346 Tg CH4 y-1) in predicted global methane emissions. In order to evaluate our methane emissions on the regional and global scales against atmospheric measurements, we conducted simulations with the Community Atmospheric Model with chemistry (CAM-chem) forced with our baseline simulation of wetland and rice paddy emissions along with other methane sources (e.g. anthropogenic, fire, and termite emissions) and compared model simulations against measured atmospheric concentrations obtained from the World Data Centre for Greenhouse Gases (WDCGG) at http://ds.data.jma.go.jp/gmd/wdcgg/. Overall, using our estimated wetland and rice paddy emissions, CAM-chem model can produce seasonal and interannual variations of observed atmospheric concentration performs well. Thus, within the current level of uncertainty, our emissions appear to be reasonable.

Influence of Transport on Two-Dimensional Model Simulation: 2. Stratospheric Aircraft Perturbations. 2; Stratospheric Aircraft Perturbations

NASA Technical Reports Server (NTRS)

Fleming, Eric L.; Jackman, Charles H.; Considine, David B.

1999-01-01

We have adopted the transport scenarios used in Part 1 to examine the sensitivity of stratospheric aircraft perturbations to transport changes in our 2-D model. Changes to the strength of the residual circulation in the upper troposphere and stratosphere and changes to the lower stratospheric K(sub zz) had similar effects in that increasing the transport rates decreased the overall stratospheric residence time and reduced the magnitude of the negative perturbation response in total ozone. Increasing the stratospheric K(sub yy) increased the residence time and enhanced the global scale negative total ozone response. However, increasing K(sub yy) along with self-consistent increases in the corresponding planetary wave drive, which leads to a stronger residual circulation, more than compensates for the K(sub yy)-effect, and results in a significantly weaker perturbation response, relative to the base case, throughout the stratosphere. We found a relatively minor model perturbation response sensitivity to the magnitude of K(sub yy) in the tropical stratosphere, and only a very small sensitivity to the magnitude of the horizontal mixing across the tropopause and to the strength of the mesospheric gravity wave drag and diffusion. These transport simulations also revealed a generally strong correlation between passive NO(sub y) accumulation and age of air throughout the stratosphere, such that faster transport rates resulted in a younger mean age and a smaller NO(y) mass accumulation. However, specific variations in K(sub yy) and mesospheric gravity wave strength exhibited very little NO(sub y)-age correlation in the lower stratosphere, similar to 3-D model simulations performed in the recent NASA "Models and Measurements" II analysis. The base model transport, which gives the most favorable overall comparison with inert tracer observations, simulated a global/annual mean total ozone response of -0.59%, with only a slightly larger response in the northern compared to the southern hemisphere. For transport scenarios which gave tracer simulations within some agreement with measurements, the annual/globally averaged total ozone response ranged from -0.45% to -0.70%. Our previous 1995 model exhibited overly fast transport rates, resulting in a global/annually averaged perturbation total ozone response of -0.25%, which is significantly weaker compared to the 1999 model. This illustrates how transport deficiencies can bias model simulations of stratospheric aircraft.

Evaluation of tropical channel refinement using MPAS-A aquaplanet simulations

DOE PAGES

Martini, Matus N.; Gustafson, Jr., William I.; O'Brien, Travis A.; ...

2015-09-13

Climate models with variable-resolution grids offer a computationally less expensive way to provide more detailed information at regional scales and increased accuracy for processes that cannot be resolved by a coarser grid. This study uses the Model for Prediction Across Scales–Atmosphere (MPAS22A), consisting of a nonhydrostatic dynamical core and a subset of Advanced Research Weather Research and Forecasting (ARW-WRF) model atmospheric physics that have been modified to include the Community Atmosphere Model version 5 (CAM5) cloud fraction parameterization, to investigate the potential benefits of using increased resolution in an tropical channel. The simulations are performed with an idealized aquaplanet configurationmore » using two quasi-uniform grids, with 30 km and 240 km grid spacing, and two variable-resolution grids spanning the same grid spacing range; one with a narrow (20°S–20°N) and one with a wide (30°S–30°N) tropical channel refinement. Results show that increasing resolution in the tropics impacts both the tropical and extratropical circulation. Compared to the quasi-uniform coarse grid, the narrow-channel simulation exhibits stronger updrafts in the Ferrel cell as well as in the middle of the upward branch of the Hadley cell. The wider tropical channel has a closer correspondence to the 30 km quasi-uniform simulation. However, the total atmospheric poleward energy transports are similar in all simulations. The largest differences are in the low-level cloudiness. The refined channel simulations show improved tropical and extratropical precipitation relative to the global 240 km simulation when compared to the global 30 km simulation. All simulations have a single ITCZ. Furthermore, the relatively small differences in mean global and tropical precipitation rates among the simulations are a promising result, and the evidence points to the tropical channel being an effective method for avoiding the extraneous numerical artifacts seen in earlier studies that only refined portion of the tropics.« less

Numerical Uncertainties in the Simulation of Reversible Isentropic Processes and Entropy Conservation.

NASA Astrophysics Data System (ADS)

Johnson, Donald R.; Lenzen, Allen J.; Zapotocny, Tom H.; Schaack, Todd K.

2000-11-01

A challenge common to weather, climate, and seasonal numerical prediction is the need to simulate accurately reversible isentropic processes in combination with appropriate determination of sources/sinks of energy and entropy. Ultimately, this task includes the distribution and transport of internal, gravitational, and kinetic energies, the energies of water substances in all forms, and the related thermodynamic processes of phase changes involved with clouds, including condensation, evaporation, and precipitation processes.All of the processes noted above involve the entropies of matter, radiation, and chemical substances, conservation during transport, and/or changes in entropies by physical processes internal to the atmosphere. With respect to the entropy of matter, a means to study a model's accuracy in simulating internal hydrologic processes is to determine its capability to simulate the appropriate conservation of potential and equivalent potential temperature as surrogates of dry and moist entropy under reversible adiabatic processes in which clouds form, evaporate, and precipitate. In this study, a statistical strategy utilizing the concept of `pure error' is set forth to assess the numerical accuracies of models to simulate reversible processes during 10-day integrations of the global circulation corresponding to the global residence time of water vapor. During the integrations, the sums of squared differences between equivalent potential temperature e numerically simulated by the governing equations of mass, energy, water vapor, and cloud water and a proxy equivalent potential temperature te numerically simulated as a conservative property are monitored. Inspection of the differences of e and te in time and space and the relative frequency distribution of the differences details bias and random errors that develop from nonlinear numerical inaccuracies in the advection and transport of potential temperature and water substances within the global atmosphere.A series of nine global simulations employing various versions of Community Climate Models CCM2 and CCM3-all Eulerian spectral numerics, all semi-Lagrangian numerics, mixed Eulerian spectral, and semi-Lagrangian numerics-and the University of Wisconsin-Madison (UW) isentropic-sigma gridpoint model provides an interesting comparison of numerical accuracies in the simulation of reversibility. By day 10, large bias and random differences were identified in the simulation of reversible processes in all of the models except for the UW isentropic-sigma model. The CCM2 and CCM3 simulations yielded systematic differences that varied zonally, vertically, and temporally. Within the comparison, the UW isentropic-sigma model was superior in transporting water vapor and cloud water/ice and in simulating reversibility involving the conservation of dry and moist entropy. The only relative frequency distribution of differences that appeared optimal, in that the distribution remained unbiased and equilibrated with minimal variance as it remained statistically stationary, was the distribution from the UW isentropic-sigma model. All other distributions revealed nonstationary characteristics with spreading and/or shifting of the maxima as the biases and variances of the numerical differences of e and te amplified.

GMMIP (v1.0) contribution to CMIP6: Global Monsoons Model Inter-comparison Project

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

Zhou, Tianjun; Turner, Andrew G.; Kinter, James L.

The Global Monsoons Model Inter-comparison Project (GMMIP) has been endorsed by the panel of Coupled Model Inter-comparison Project (CMIP) as one of the participating model inter-comparison projects (MIPs) in the sixth phase of CMIP (CMIP6). The focus of GMMIP is on monsoon climatology, variability, prediction and projection, which is relevant to four of the “Grand Challenges” proposed by the World Climate Research Programme. At present, 21 international modeling groups are committed to joining GMMIP. This overview paper introduces the motivation behind GMMIP and the scientific questions it intends to answer. Three tiers of experiments, of decreasing priority, are designed to examinemore » (a) model skill in simulating the climatology and interannual-to-multidecadal variability of global monsoons forced by the sea surface temperature during historical climate period; (b) the roles of the Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation in driving variations of the global and regional monsoons; and (c) the effects of large orographic terrain on the establishment of the monsoons. The outputs of the CMIP6 Diagnostic, Evaluation and Characterization of Klima experiments (DECK), “historical” simulation and endorsed MIPs will also be used in the diagnostic analysis of GMMIP to give a comprehensive understanding of the roles played by different external forcings, potential improvements in the simulation of monsoon rainfall at high resolution and reproducibility at decadal timescales. The implementation of GMMIP will improve our understanding of the fundamental physics of changes in the global and regional monsoons over the past 140 years and ultimately benefit monsoons prediction and projection in the current century.« less

Scale-dependent performances of CMIP5 earth system models in simulating terrestrial vegetation carbon

NASA Astrophysics Data System (ADS)

Jiang, L.; Luo, Y.; Yan, Y.; Hararuk, O.

2013-12-01

Mitigation of global changes will depend on reliable projection for the future situation. As the major tools to predict future climate, Earth System Models (ESMs) used in Coupled Model Intercomparison Project Phase 5 (CMIP5) for the IPCC Fifth Assessment Report have incorporated carbon cycle components, which account for the important fluxes of carbon between the ocean, atmosphere, and terrestrial biosphere carbon reservoirs; and therefore are expected to provide more detailed and more certain projections. However, ESMs are never perfect; and evaluating the ESMs can help us to identify uncertainties in prediction and give the priorities for model development. In this study, we benchmarked carbon in live vegetation in the terrestrial ecosystems simulated by 19 ESMs models from CMIP5 with an observationally estimated data set of global carbon vegetation pool 'Olson's Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: An Updated Database Using the GLC2000 Land Cover Product' by Gibbs (2006). Our aim is to evaluate the ability of ESMs to reproduce the global vegetation carbon pool at different scales and what are the possible causes for the bias. We found that the performance CMIP5 ESMs is very scale-dependent. While CESM1-BGC, CESM1-CAM5, CESM1-FASTCHEM and CESM1-WACCM, and NorESM1-M and NorESM1-ME (they share the same model structure) have very similar global sums with the observation data but they usually perform poorly at grid cell and biome scale. In contrast, MIROC-ESM and MIROC-ESM-CHEM simulate the best on at grid cell and biome scale but have larger differences in global sums than others. Our results will help improve CMIP5 ESMs for more reliable prediction.

Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources

NASA Astrophysics Data System (ADS)

Wada, Y.; Wisser, D.; Bierkens, M. F. P.

2014-01-01

To sustain growing food demand and increasing standard of living, global water withdrawal and consumptive water use have been increasing rapidly. To analyze the human perturbation on water resources consistently over large scales, a number of macro-scale hydrological models (MHMs) have been developed in recent decades. However, few models consider the interaction between terrestrial water fluxes, and human activities and associated water use, and even fewer models distinguish water use from surface water and groundwater resources. Here, we couple a global water demand model with a global hydrological model and dynamically simulate daily water withdrawal and consumptive water use over the period 1979-2010, using two re-analysis products: ERA-Interim and MERRA. We explicitly take into account the mutual feedback between supply and demand, and implement a newly developed water allocation scheme to distinguish surface water and groundwater use. Moreover, we include a new irrigation scheme, which works dynamically with a daily surface and soil water balance, and incorporate the newly available extensive Global Reservoir and Dams data set (GRanD). Simulated surface water and groundwater withdrawals generally show good agreement with reported national and subnational statistics. The results show a consistent increase in both surface water and groundwater use worldwide, with a more rapid increase in groundwater use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and interannual variability. This alteration is particularly large over heavily regulated basins such as the Colorado and the Columbia, and over the major irrigated basins such as the Mississippi, the Indus, and the Ganges. Including human water use and associated reservoir operations generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Global Modeling of Withdrawal, Allocation and Consumptive Use of Surface Water and Groundwater Resources

NASA Astrophysics Data System (ADS)

Wada, Y.; Wisser, D.; Bierkens, M. F.

2014-12-01

To sustain growing food demand and increasing standard of living, global water withdrawal and consumptive water use have been increasing rapidly. To analyze the human perturbation on water resources consistently over large scales, a number of macro-scale hydrological models (MHMs) have been developed in recent decades. However, few models consider the interaction between terrestrial water fluxes, and human activities and associated water use, and even fewer models distinguish water use from surface water and groundwater resources. Here, we couple a global water demand model with a global hydrological model and dynamically simulate daily water withdrawal and consumptive water use over the period 1979-2010, using two re-analysis products: ERA-Interim and MERRA. We explicitly take into account the mutual feedback between supply and demand, and implement a newly developed water allocation scheme to distinguish surface water and groundwater use. Moreover, we include a new irrigation scheme, which works dynamically with a daily surface and soil water balance, and incorporate the newly available extensive global reservoir data set (GRanD). Simulated surface water and groundwater withdrawals generally show good agreement with reported national and sub-national statistics. The results show a consistent increase in both surface water and groundwater use worldwide, with a more rapid increase in groundwater use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and inter-annual variability. This alteration is particularly large over heavily regulated basins such as the Colorado and the Columbia, and over the major irrigated basins such as the Mississippi, the Indus, and the Ganges. Including human water use and associated reservoir operations generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Online Simulations and Forecasts of the Global Aerosol Distribution in the NASA GEOS-5 Model

NASA Technical Reports Server (NTRS)

Colarco, Peter

2006-01-01

We present an analysis of simulations of the global aerosol system in the NASA GEOS-5 transport, radiation, and chemistry model. The model includes representations of all major tropospheric aerosol species, including dust, sea salt, black carbon, particulate organic matter, and sulfates. The aerosols are run online for the period 2000 through 2005 in a simulation driven by assimilated meteorology from the NASA Goddard Data Assimilation System. Aerosol surface mass concentrations are compared with existing long-term surface measurement networks. Aerosol optical thickness is compared with ground-based AERONET sun photometry and space-based retrievals from MODIS, MISR, and OMI. Particular emphasis is placed here on consistent sampling of model and satellite aerosol optical thickness to account for diurnal variations in aerosol optical properties. Additionally, we illustrate the use of this system for providing chemical weather forecasts in support of various NASA and community field missions.

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

Elliott, Elizabeth J.; Yu, Sungduk; Kooperman, Gabriel J.

The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-likemore » events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. Furthermore, these results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.« less

Effects of Drake Passage on a strongly eddying global ocean

NASA Astrophysics Data System (ADS)

Viebahn, Jan; von der Heydt, Anna S.; Dijkstra, Henk A.

2015-04-01

During the past 65 Million (Ma) years, Earth's climate has undergone a major change from warm 'greenhouse' to colder 'icehouse' conditions with extensive ice sheets in the polar regions of both hemispheres. The Eocene-Oligocene (~34 Ma) and Oligocene-Miocene (~23 Ma) boundaries reflect major transitions in Cenozoic global climate change. Proposed mechanisms of these transitions include reorganization of ocean circulation due to critical gateway opening/deepening, changes in atmospheric CO2-concentration, and feedback mechanisms related to land-ice formation. Drake Passage (DP) is an intensively studied gateway because it plays a central role in closing the transport pathways of heat and chemicals in the ocean. The climate response to a closed DP has been explored with a variety of general circulation models, however, all of these models employ low model-grid resolutions such that the effects of subgrid-scale fluctuations ('eddies') are parameterized. We present results of the first high-resolution (0.1° horizontally) realistic global ocean model simulation with a closed DP in which the eddy field is largely resolved. The simulation extends over more than 200 years such that the strong transient adjustment process is passed and a near-equilibrium ocean state is reached. The effects of DP are diagnosed by comparing with both an open DP high-resolution control simulation (of same length) and corresponding low-resolution simulations. By focussing on the heat/tracer transports we demonstrate that the results are twofold: Considering spatially integrated transports the overall response to a closed DP is well captured by low-resolution simulations. However, looking at the actual spatial distributions drastic differences appear between far-scattered high-resolution and laminar-uniform low-resolution fields. We conclude that sparse and highly localized tracer proxy observations have to be interpreted carefully with the help of high-resolution model simulations.

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

Simulated cold bias being improved by using MODIS time-varying albedo in the Tibetan Plateau in WRF model

NASA Astrophysics Data System (ADS)

Meng, X.; Lyu, S.; Zhang, T.; Zhao, L.; Li, Z.; Han, B.; Li, S.; Ma, D.; Chen, H.; Ao, Y.; Luo, S.; Shen, Y.; Guo, J.; Wen, L.

2018-04-01

Systematic cold biases exist in the simulation for 2 m air temperature in the Tibetan Plateau (TP) when using regional climate models and global atmospheric general circulation models. We updated the albedo in the Weather Research and Forecasting (WRF) Model lower boundary condition using the Global LAnd Surface Satellite Moderate-Resolution Imaging Spectroradiometer albedo products and demonstrated evident improvement for cold temperature biases in the TP. It is the large overestimation of albedo in winter and spring in the WRF model that resulted in the large cold temperature biases. The overestimated albedo was caused by the simulated precipitation biases and over-parameterization of snow albedo. Furthermore, light-absorbing aerosols can result in a large reduction of albedo in snow and ice cover. The results suggest the necessity of developing snow albedo parameterization using observations in the TP, where snow cover and melting are very different from other low-elevation regions, and the influence of aerosols should be considered as well. In addition to defining snow albedo, our results show an urgent call for improving precipitation simulation in the TP.

Composite Study Of Aerosol Long-Range Transport Events From East Asia And North America

NASA Astrophysics Data System (ADS)

Jiang, X.; Waliser, D. E.; Guan, B.; Xavier, P.; Petch, J.; Klingaman, N. P.; Woolnough, S.

2011-12-01

While the Madden-Julian Oscillation (MJO) exerts pronounced influences on global climate and weather systems, current general circulation models (GCMs) exhibit rather limited capability in representing this prominent tropical variability mode. Meanwhile, the fundamental physics of the MJO are still elusive. Given the central role of the diabatic heating for prevailing MJO theories and demands for reducing the model deficiencies in simulating the MJO, a global model inter-comparison project on diabatic processes and vertical heating structure associated with the MJO has been coordinated through a joint effort by the WCRP-WWRP/THORPEX YOTC MJO Task Force and GEWEX GASS Program. In this presentation, progress of this model inter-comparison project will be reported, with main focus on climate simulations from about 27 atmosphere-only and coupled GCMs. Vertical structures of heating and diabatic processes associated with the MJO based on multi-model simulations will be presented along with their reanalysis and satellite estimate counterparts. Key processes possibly responsible for a realistic simulation of the MJO, including moisture-convection interaction, gross moist stability, ocean coupling, and surface heat flux, will be discussed.

Assessment and simulation of global terrestrial latent heat flux by synthesis of CMIP5 climate models and surface eddy covariance observations

Treesearch

Yunjun Yao; Shunlin Liang; Xianglan Li; Shaomin Liu; Jiquan Chen; Xiaotong Zhang; Kun Jia; Bo Jiang; Xianhong Xie; Simon Munier; Meng Liu; Jian Yu; Anders Lindroth; Andrej Varlagin; Antonio Raschi; Asko Noormets; Casimiro Pio; Georg Wohlfahrt; Ge Sun; Jean-Christophe Domec; Leonardo Montagnani; Magnus Lund; Moors Eddy; Peter D. Blanken; Thomas Grunwald; Sebastian Wolf; Vincenzo Magliulo

2016-01-01

The latent heat flux (LE) between the terrestrial biosphere and atmosphere is a major driver of the globalhydrological cycle. In this study, we evaluated LE simulations by 45 general circulation models (GCMs)in the Coupled Model Intercomparison Project Phase 5 (CMIP5) by a comparison...

The role of atmospheric nuclear explosions on the stagnation of global warming in the mid 20th century

NASA Astrophysics Data System (ADS)

Fujii, Yoshiaki

2011-04-01

This study suggests that the cause of the stagnation in global warming in the mid 20th century was the atmospheric nuclear explosions detonated between 1945 and 1980. The estimated GST drop due to fine dust from the actual atmospheric nuclear explosions based on the published simulation results by other researchers (a single column model and Atmosphere-Ocean General Circulation Model) has served to explain the stagnation in global warming. Atmospheric nuclear explosions can be regarded as full-scale in situ tests for nuclear winter. The non-negligible amount of GST drop from the actual atmospheric explosions suggests that nuclear winter is not just a theory but has actually occurred, albeit on a small scale. The accuracy of the simulations of GST by IPCC would also be improved significantly by introducing the influence of fine dust from the actual atmospheric nuclear explosions into their climate models; thus, global warming behavior could be more accurately predicted.

The Pilot Phase of the Global Soil Wetness Project Phase 3

NASA Astrophysics Data System (ADS)

Kim, H.; Oki, T.

2015-12-01

After the second phase of the Global Soil Wetness Project (GSWP2) as an early global continuous gridded multi-model analysis, a comprehensive set of land surface fluxes and state variables became available. It has been broadly utilized in the hydrology community, and its success has evolved to take advantages of recent scientific progress and to extend the relatively short time span (1986-1995) of the previous project. In the third phase proposed here (GSWP3), an extensive set of quantities for hydro-energy-eco systems will be produced to investigate their long-term (1901-2010) changes. The energy-water-carbon cycles and their interactions are also examined subcomponent-wise with appropriate model verifications in ensemble land simulations. In this study, the preliminary results and problems found from the first round analysis of the GSWP3 pilot study are shown. Also, it is discussed how the global offline simulation activity contributes to wider communities and a bigger scope such as Climate Model Intercomparison Project Phase 6 (CMIP6).

Simulations of Highway Traffic With Various Degrees of Automation

DOT National Transportation Integrated Search

1996-01-01

A traffic simulator to study highway traffic under various degrees of automation is being developed at Argonne National Laboratory. The key components of this simulator include a global and a local Expert Driver Model, a human factor study and a grap...

Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model

NASA Technical Reports Server (NTRS)

Putnam, Williama

2011-01-01

The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.

Trans-Pacific transport and evolution of aerosols: Evaluation of quasi-global WRF-Chem simulation with multiple observations

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

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010–2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols.more » The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010–2014 averaged over three Pacific sub-regions. Furthermore, the evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.« less

Trans-Pacific transport and evolution of aerosols: Evaluation of quasi-global WRF-Chem simulation with multiple observations

DOE PAGES

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; ...

2016-05-10

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010–2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols.more » The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010–2014 averaged over three Pacific sub-regions. Furthermore, the evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.« less

Simulation services and analysis tools at the CCMC to study multi-scale structure and dynamics of Earth's magnetopause

NASA Astrophysics Data System (ADS)

Kuznetsova, M. M.; Liu, Y. H.; Rastaetter, L.; Pembroke, A. D.; Chen, L. J.; Hesse, M.; Glocer, A.; Komar, C. M.; Dorelli, J.; Roytershteyn, V.

2016-12-01

The presentation will provide overview of new tools, services and models implemented at the Community Coordinated Modeling Center (CCMC) to facilitate MMS dayside results analysis. We will provide updates on implementation of Particle-in-Cell (PIC) simulations at the CCMC and opportunities for on-line visualization and analysis of results of PIC simulations of asymmetric magnetic reconnection for different guide fields and boundary conditions. Fields, plasma parameters, particle distribution moments as well as particle distribution functions calculated in selected regions of the vicinity of reconnection sites can be analyzed through the web-based interactive visualization system. In addition there are options to request distribution functions in user selected regions of interest and to fly through simulated magnetic reconnection configurations and a map of distributions to facilitate comparisons with observations. A broad collection of global magnetosphere models hosted at the CCMC provide opportunity to put MMS observations and local PIC simulations into global context. We recently implemented the RECON-X post processing tool (Glocer et al, 2016) which allows users to determine the location of separator surface around closed field lines and between open field lines and solar wind field lines. The tool also finds the separatrix line where the two surfaces touch and positions of magnetic nulls. The surfaces and the separatrix line can be visualized relative to satellite positions in the dayside magnetosphere using an interactive HTML-5 visualization for each time step processed. To validate global magnetosphere models' capability to simulate locations of dayside magnetosphere boundaries we will analyze the proximity of MMS to simulated separatrix locations for a set of MMS diffusion region crossing events.

ESiWACE: A Center of Excellence for HPC applications to support cloud resolving earth system modelling

NASA Astrophysics Data System (ADS)

Biercamp, Joachim; Adamidis, Panagiotis; Neumann, Philipp

2017-04-01

With the exa-scale era approaching, length and time scales used for climate research on one hand and numerical weather prediction on the other hand blend into each other. The Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) represents a European consortium comprising partners from climate, weather and HPC in their effort to address key scientific challenges that both communities have in common. A particular challenge is to reach global models with spatial resolutions that allow simulating convective clouds and small-scale ocean eddies. These simulations would produce better predictions of trends and provide much more fidelity in the representation of high-impact regional events. However, running such models in operational mode, i.e with sufficient throughput in ensemble mode clearly will require exa-scale computing and data handling capability. We will discuss the ESiWACE initiative and relate it to work-in-progress on high-resolution simulations in Europe. We present recent strong scalability measurements from ESiWACE to demonstrate current computability in weather and climate simulation. A special focus in this particular talk is on the Icosahedal Nonhydrostatic (ICON) model used for a comparison of high resolution regional and global simulations with high quality observation data. We demonstrate that close-to-optimal parallel efficiency can be achieved in strong scaling global resolution experiments on Mistral/DKRZ, e.g. 94% for 5km resolution simulations using 36k cores on Mistral/DKRZ. Based on our scalability and high-resolution experiments, we deduce and extrapolate future capabilities for ICON that are expected for weather and climate research at exascale.

Effects of including electrojet turbulence in LFM-RCM simulations of geospace storms

NASA Astrophysics Data System (ADS)

Oppenheim, M. M.; Wiltberger, M. J.; Merkin, V. G.; Zhang, B.; Toffoletto, F.; Wang, W.; Lyon, J.; Liu, J.; Dimant, Y. S.

2016-12-01

Global geospace system simulations need to incorporate nonlinear and small-scale physical processes in order to accurately model storms and other intense events. During times of strong magnetospheric disturbances, large-amplitude electric fields penetrate from the Earth's magnetosphere to the E-region ionosphere where they drive Farley-Buneman instabilities (FBI) that create small-scale plasma density turbulence. This induces nonlinear currents and leads to anomalous electron heating. Current global Magnetosphere-Ionosphere-Thermosphere (MIT) models disregard these effects by assuming simple laminar ionospheric currents. This paper discusses the effects of incorporating accurate turbulent conductivities into MIT models. Recently, we showed in Liu et al. (2016) that during storm-time, turbulence increases the electron temperatures and conductivities more than precipitation. In this talk, we present the effect of adding these effects to the combined Lyon-Fedder-Mobarry (LFM) global MHD magnetosphere simulator and the Rice Convection Model (RCM). The LFM combines a magnetohydrodynamic (MHD) simulation of the magnetosphere with a 2D electrostatic solution of the ionosphere. The RCM uses drift physics to accurately model the inner magnetosphere, including a storm enhanced ring current. The LFM and coupled LFM-RCM simulations have previously shown unrealistically high cross-polar-cap potentials during strong solar wind driving conditions. We have recently implemented an LFM module that modifies the ionospheric conductivity to account for FBI driven anomalous electron heating and non-linear cross-field current enhancements as a function of the predicted ionospheric electric field. We have also improved the LFM-RCM code by making it capable of handling dipole tilts and asymmetric ionospheric solutions. We have tested this new LFM version by simulating the March 17, 2013 geomagnetic storm. These simulations showed a significant reduction in the cross-polar-cap potential during the strongest driving conditions, significant increases in the ionospheric conductivity in the auroral oval, and better agreement with DMSP observations of sub-auroral polarization streams. We conclude that accurate MIT simulations of geospace storms require the inclusion of turbulent conductivities.

Simulating the Agulhas system in global ocean models - nesting vs. multi-resolution unstructured meshes

NASA Astrophysics Data System (ADS)

Biastoch, Arne; Sein, Dmitry; Durgadoo, Jonathan V.; Wang, Qiang; Danilov, Sergey

2018-01-01

Many questions in ocean and climate modelling require the combined use of high resolution, global coverage and multi-decadal integration length. For this combination, even modern resources limit the use of traditional structured-mesh grids. Here we compare two approaches: A high-resolution grid nested into a global model at coarser resolution (NEMO with AGRIF) and an unstructured-mesh grid (FESOM) which allows to variably enhance resolution where desired. The Agulhas system around South Africa is used as a testcase, providing an energetic interplay of a strong western boundary current and mesoscale dynamics. Its open setting into the horizontal and global overturning circulations also requires global coverage. Both model configurations simulate a reasonable large-scale circulation. Distribution and temporal variability of the wind-driven circulation are quite comparable due to the same atmospheric forcing. However, the overturning circulation differs, owing each model's ability to represent formation and spreading of deep water masses. In terms of regional, high-resolution dynamics, all elements of the Agulhas system are well represented. Owing to the strong nonlinearity in the system, Agulhas Current transports of both configurations and in comparison with observations differ in strength and temporal variability. Similar decadal trends in Agulhas Current transport and Agulhas leakage are linked to the trends in wind forcing.

Forecasting of global solar radiation using anfis and armax techniques

NASA Astrophysics Data System (ADS)

Muhammad, Auwal; Gaya, M. S.; Aliyu, Rakiya; Aliyu Abdulkadir, Rabi'u.; Dauda Umar, Ibrahim; Aminu Yusuf, Lukuman; Umar Ali, Mudassir; Khairi, M. T. M.

2018-01-01

Procurement of measuring device, maintenance cost coupled with calibration of the instrument contributed to the difficulty in forecasting of global solar radiation in underdeveloped countries. Most of the available regressional and mathematical models do not capture well the behavior of the global solar radiation. This paper presents the comparison of Adaptive Neuro Fuzzy Inference System (ANFIS) and Autoregressive Moving Average with eXogenous term (ARMAX) in forecasting global solar radiation. Full-Scale (experimental) data of Nigerian metrological agency, Sultan Abubakar III international airport Sokoto was used to validate the models. The simulation results demonstrated that the ANFIS model having achieved MAPE of 5.34% outperformed the ARMAX model. The ANFIS could be a valuable tool for forecasting the global solar radiation.

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

NASA Astrophysics Data System (ADS)

Porada, Philipp; Lenton, Tim; Pohl, Alexandre; Weber, Bettina; Mander, Luke; Donnadieu, Yannick; Beer, Christian; Pöschl, Ulrich; Kleidon, Axel

2017-04-01

Early non-vascular vegetation in the Late Ordovician may have strongly increased chemical weathering rates of surface rocks at the global scale. This could have led to a drawdown of atmospheric CO2 and, consequently, a decrease in global temperature and an interval of glaciations. Under current climatic conditions, usually field or laboratory experiments are used to quantify enhancement of chemical weathering rates by non-vascular vegetation. However, these experiments are constrained to a small spatial scale and a limited number of species. This complicates the extrapolation to the global scale, even more so for the geological past, where physiological properties of non-vascular vegetation may have differed from current species. Here we present a spatially explicit modelling approach to simulate large-scale chemical weathering by non-vascular vegetation in the Late Ordovician. For this purpose, we use a process-based model of lichens and bryophytes, since these organisms are probably the closest living analogue to Late Ordovician vegetation. The model explicitly represents multiple physiological strategies, which enables the simulated vegetation to adapt to Ordovician climatic conditions. We estimate productivity of Ordovician vegetation with the model, and relate it to chemical weathering by assuming that the organisms dissolve rocks to extract phosphorus for the production of new biomass. Thereby we account for limits on weathering due to reduced supply of unweathered rock material in shallow regions, as well as decreased transport capacity of runoff for dissolved weathered material in dry areas. We simulate a potential global weathering flux of 2.8 km3 (rock) per year, which we define as volume of primary minerals affected by chemical transformation. Our estimate is around 3 times larger than today's global chemical weathering flux. Furthermore, chemical weathering rates simulated by our model are highly sensitive to atmospheric CO2 concentration, which implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate.

Predictive optimal control of sewer networks using CORAL tool: application to Riera Blanca catchment in Barcelona.

PubMed

Puig, V; Cembrano, G; Romera, J; Quevedo, J; Aznar, B; Ramón, G; Cabot, J

2009-01-01

This paper deals with the global control of the Riera Blanca catchment in the Barcelona sewer network using a predictive optimal control approach. This catchment has been modelled using a conceptual modelling approach based on decomposing the catchments in subcatchments and representing them as virtual tanks. This conceptual modelling approach allows real-time model calibration and control of the sewer network. The global control problem of the Riera Blanca catchment is solved using a optimal/predictive control algorithm. To implement the predictive optimal control of the Riera Blanca catchment, a software tool named CORAL is used. The on-line control is simulated by interfacing CORAL with a high fidelity simulator of sewer networks (MOUSE). CORAL interchanges readings from the limnimeters and gate commands with MOUSE as if it was connected with the real SCADA system. Finally, the global control results obtained using the predictive optimal control are presented and compared against the results obtained using current local control system. The results obtained using the global control are very satisfactory compared to those obtained using the local control.

GMI Capabilities

NASA Technical Reports Server (NTRS)

Strode, Sarah; Rodriguez, Jose; Steenrod, Steve; Liu, Junhua; Strahan, Susan; Nielsen, Eric

2015-01-01

We describe the capabilities of the Global Modeling Initiative (GMI) chemical transport model (CTM) with a special focus on capabilities related to the Atmospheric Tomography Mission (ATom). Several science results based on GMI hindcast simulations and preliminary results from the ATom simulations are highlighted. We also discuss the relationship between GMI and GEOS-5.

Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

NASA Astrophysics Data System (ADS)

Huang, Danqing; Yan, Peiwen; Zhu, Jian; Zhang, Yaocun; Kuang, Xueyuan; Cheng, Jing

2018-04-01

The uncertainty of global summer precipitation simulated by the 23 CMIP5 CGCMs and the possible impacts of model resolutions are investigated in this study. Large uncertainties exist over the tropical and subtropical regions, which can be mainly attributed to convective precipitation simulation. High-resolution models (HRMs) and low-resolution models (LRMs) are further investigated to demonstrate their different contributions to the uncertainties of the ensemble mean. It shows that the high-resolution model ensemble means (HMME) and low-resolution model ensemble mean (LMME) mitigate the biases between the MME and observation over most continents and oceans, respectively. The HMME simulates more precipitation than the LMME over most oceans, but less precipitation over some continents. The dominant precipitation category in the HRMs (LRMs) is the heavy precipitation (moderate precipitation) over the tropic regions. The combinations of convective and stratiform precipitation are also quite different: the HMME has much higher ratio of stratiform precipitation while the LMME has more convective precipitation. Finally, differences in precipitation between the HMME and LMME can be traced to their differences in the SST simulations via the local and remote air-sea interaction.

Regime-based evaluation of cloudiness in CMIP5 models

NASA Astrophysics Data System (ADS)

Jin, Daeho; Oreopoulos, Lazaros; Lee, Dongmin

2017-01-01

The concept of cloud regimes (CRs) is used to develop a framework for evaluating the cloudiness of 12 fifth Coupled Model Intercomparison Project (CMIP5) models. Reference CRs come from existing global International Satellite Cloud Climatology Project (ISCCP) weather states. The evaluation is made possible by the implementation in several CMIP5 models of the ISCCP simulator generating in each grid cell daily joint histograms of cloud optical thickness and cloud top pressure. Model performance is assessed with several metrics such as CR global cloud fraction (CF), CR relative frequency of occurrence (RFO), their product [long-term average total cloud amount (TCA)], cross-correlations of CR RFO maps, and a metric of resemblance between model and ISCCP CRs. In terms of CR global RFO, arguably the most fundamental metric, the models perform unsatisfactorily overall, except for CRs representing thick storm clouds. Because model CR CF is internally constrained by our method, RFO discrepancies yield also substantial TCA errors. Our results support previous findings that CMIP5 models underestimate cloudiness. The multi-model mean performs well in matching observed RFO maps for many CRs, but is still not the best for this or other metrics. When overall performance across all CRs is assessed, some models, despite shortcomings, apparently outperform Moderate Resolution Imaging Spectroradiometer cloud observations evaluated against ISCCP like another model output. Lastly, contrasting cloud simulation performance against each model's equilibrium climate sensitivity in order to gain insight on whether good cloud simulation pairs with particular values of this parameter, yields no clear conclusions.

Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

DOE PAGES

Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; ...

2014-12-02

Soil organic carbon (SOC) plays a key role in the global carbon cycle that is important for decadal-to-century climate prediction. Estimation of soil organic carbon stock using model-based methods typically requires spin-up (time marching transient simulation) of the carbon-nitrogen (CN) models by performing hundreds to thousands years long simulations until the carbon-nitrogen pools reach dynamic steady-state. This has become a bottleneck for global modeling and analysis, especially when testing new physical and/or chemical mechanisms and evaluating parameter sensitivity. Here we report a new numerical approach to estimate global soil carbon stock that can avoid the long term spin-up of themore » CN model. The approach uses canopy leaf area index (LAI) from satellite data and takes advantage of a reaction-based biogeochemical module NGBGC (Next Generation BioGeoChemical Module) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as used in CLM4CN, it can be easily configured to run prognostic or steady state simulations. In this approach, monthly LAI from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to calculate potential annual average gross primary production (GPP) and leaf carbon for the period of the atmospheric forcing. The calculated potential annual average GPP and leaf C are then used by NGBGC to calculate the steady-state distributions of carbon and nitrogen in different vegetation and soil pools by solving the steady-state reaction-network in NGBGC using the Newton-Raphson method. The new approach was applied at point and global scales and compared with SOC derived from long spin-up by running NGBGC in prognostic mode, and SOC from the empirical data of the Harmonized World Soil Database (HWSD). The steady-state solution is comparable to the spin-up value when the MODIS LAI is close to the LAI from the spin-up solution, and largely captured the variability of the HWSD SOC across the different dominant plant functional types (PFTs) at global scale. The numerical correlation between the calculated and HWSD SOC was, however, weak at both point and global scales, suggesting that the models used in describing biogeochemical processes in CLM needs improvements and/or HWSD needs updating as suggested by other studies. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, such as NPP, GPP, total vegetation C etc., which makes the developed approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare different aspects simulated by different CN mechanisms in the model.« less

The internal gravity wave spectrum in two high-resolution global ocean models

NASA Astrophysics Data System (ADS)

Arbic, B. K.; Ansong, J. K.; Buijsman, M. C.; Kunze, E. L.; Menemenlis, D.; Müller, M.; Richman, J. G.; Savage, A.; Shriver, J. F.; Wallcraft, A. J.; Zamudio, L.

2016-02-01

We examine the internal gravity wave (IGW) spectrum in two sets of high-resolution global ocean simulations that are forced concurrently by atmospheric fields and the astronomical tidal potential. We analyze global 1/12th and 1/25th degree HYCOM simulations, and global 1/12th, 1/24th, and 1/48th degree simulations of the MITgcm. We are motivated by the central role that IGWs play in ocean mixing, by operational considerations of the US Navy, which runs HYCOM as an ocean forecast model, and by the impact of the IGW continuum on the sea surface height (SSH) measurements that will be taken by the planned NASA/CNES SWOT wide-swath altimeter mission. We (1) compute the IGW horizontal wavenumber-frequency spectrum of kinetic energy, and interpret the results with linear dispersion relations computed from the IGW Sturm-Liouville problem, (2) compute and similarly interpret nonlinear spectral kinetic energy transfers in the IGW band, (3) compute and similarly interpret IGW contributions to SSH variance, (4) perform comparisons of modeled IGW kinetic energy frequency spectra with moored current meter observations, and (5) perform comparisons of modeled IGW kinetic energy vertical wavenumber-frequency spectra with moored observations. This presentation builds upon our work in Muller et al. (2015, GRL), who performed tasks (1), (2), and (4) in 1/12th and 1/25th degree HYCOM simulations, for one region of the North Pacific. New for this presentation are tasks (3) and (5), the inclusion of MITgcm solutions, and the analysis of additional ocean regions.

Modeling spatial-temporal dynamics of global wetlands: Comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Z.; Zimmermann, N. E.; Poulter, B.

2015-12-01

Simulations of the spatial-temporal dynamics of wetlands is key to understanding the role of wetland biogeochemistry under past and future climate variability. Hydrologic inundation models, such as TOPMODEL, are based on a fundamental parameter known as the compound topographic index (CTI) and provide a computationally cost-efficient approach to simulate global wetland dynamics. However, there remains large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl DGVM, and quantifies uncertainties by comparing three digital elevation model products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. We found that calibrating TOPMODEL with a benchmark dataset can help to successfully predict the seasonal and interannual variations of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows best accuracy for capturing the spatio-temporal dynamics of wetland among three DEM products. This study demonstrates the feasibility to capture spatial heterogeneity of inundation and to estimate seasonal and interannual variations in wetland by coupling a hydrological module in LSMs with appropriate benchmark datasets. It additionally highlight the importance of an adequate understanding of topographic indices for simulating global wetlands and show the opportunity to converge wetland estimations in LSMs by identifying the uncertainty associated with existing wetland products.

A modeling study of coastal inundation induced by storm surge, sea-level rise, and subsidence in the Gulf of Mexico

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

Yang, Zhaoqing; Wang, Taiping; Leung, Lai-Yung R.

The northern coasts of the Gulf of Mexico are highly vulnerable to the direct threats of climate change, such as hurricane-induced storm surge, and such risks can be potentially exacerbated by land subsidence and global sea level rise. This paper presents an application of a coastal storm surge model to study the coastal inundation process induced by tide and storm surge, and its response to the effects of land subsidence and sea level rise in the northern Gulf coast. An unstructured-grid Finite Volume Coastal Ocean Model was used to simulate tides and hurricane-induced storm surges in the Gulf of Mexico.more » Simulated distributions of co-amplitude and co-phase of semi-diurnal and diurnal tides are in good agreement with previous modeling studies. The storm surges induced by four historical hurricanes (Rita, Katrina, Ivan and Dolly) were simulated and compared to observed water levels at National Oceanic and Atmospheric Administration tide stations. Effects of coastal subsidence and future global sea level rise on coastal inundation in the Louisiana coast were evaluated using a parameter “change of inundation depth” through sensitivity simulations that were based on a projected future subsidence scenario and 1-m global sea level rise by the end of the century. Model results suggested that hurricane-induced storm surge height and coastal inundation could be exacerbated by future global sea level rise and subsidence, and that responses of storm surge and coastal inundation to the effects of sea level rise and subsidence are highly nonlinear and vary on temporal and spatial scales.« less

Present and Future Projections of Habitat Suitability of the Asian Tiger Mosquito, a Vector of Viral Pathogens, from Global Climate Simulations.

NASA Astrophysics Data System (ADS)

Proestos, Y.; Christophides, G.; Erguler, K.; Tanarhte, M.; Waldock, J.; Lelieveld, J.

2014-12-01

Climate change can influence the transmission of vector borne diseases (VBDs) through altering the habitat suitability of insect vectors. Here we present global climate model simulations and evaluate the associated uncertainties in view of the main meteorological factors that may affect the distribution of the Asian Tiger mosquito (Aedes albopictus), which can transmit pathogens that cause Chikungunya, Dengue fever, yellow fever and various encephalitides. Using a general circulation model (GCM) at 50 km horizontal resolution to simulate mosquito survival variables including temperature, precipitation and relative humidity, we present both global and regional projections of the habitat suitability up to the middle of the 21st century. The model resolution of 50 km allows evaluation against previous projections for Europe and provides a basis for comparative analyses with other regions. Model uncertainties and performance are addressed in light of the recent CMIP5 ensemble climate model simulations for the RCP8.5 concentration pathway and using meteorological re-analysis data (ERA-Interim/ECMWF) for the recent past. Uncertainty ranges associated with the thresholds of meteorological variables that may affect the distribution of Ae. albopictus are diagnosed using fuzzy-logic methodology, notably to assess the influence of selected meteorological criteria and combinations of criteria that influence mosquito habitat suitability. From the climate projections for 2050, and adopting a habitat suitability index larger than 70%, we estimate that about 2.4 billion individuals in a land area of nearly 20 million square kilometres will potentially be exposed to Ae. albopictus. The synthesis of fuzzy-logic based on mosquito biology and climate change analysis provides new insights into the regional and global spreading of VBDs to support disease control and policy making.

Lightning NOx Production and Its Consequences for Tropospheric Chemistry

NASA Technical Reports Server (NTRS)

Pickering, Kenneth E.

2005-01-01

Cloud-resolving case-study simulations of convective transport and lightning NO production have yielded results which are directly applicable to the design of lightning parameterizations for global chemical transport models. In this work we have used cloud-resolving models (the Goddard Cumulus Ensemble Model (GCE) and MMS) to drive an off-line cloud-scale chemical transport model (CSCTM). The CSCTM, in conjunction with aircraft measurements of NO x in thunderstorms and ground-l;>ased lightning observations, has been used to constrain the amount of NO produced per flash. Cloud and chemistry simulations for several case studies of storms in different environments will be presented. Observed lightning flash rates have been incorporated into the CSCTM, and several scenarios of NO production per intracloud (IC) and per cloud-to-ground (CG) flash have been tested for each storm. The resulting NOx mixing ratios are compared with aircraft measurements taken within the storm (typically the anvil region) to determine the most likely NO production scenario. The range of values of NO production per flash (or per meter of lightning channel length) that have been deduced from the model will be shown and compared with values of production in the literature that have been deduced from observed NO spikes and from anvil flux calculations. Results show that on a per flash basis, IC flashes are nearly as productive of NO as CG flashes. This result simplifies the lightning parameterization for global models (ie., an algorithm for estimating the IC/CG ratio is not necessary). Vertical profiles of lightning NOx mass at the end of the 3-D storm simulations have been summarized to yield suggested profiles for use in global models. Estimates of mean NO production per flash vary by a factor of three from one simulated storm to another. When combined with the global flash rate of 44 flashes per second from NASA's Optical Transient Detector (OTD) measurements, these estimates and the results from other techniques yield global NO production rates of2-9 TgN/year. Simulations of the photochemistry over the 24 hours following a storm has been performed to determine the additional ozone production which can be attributed to lightning NO. Convective transport of HOx precursors leads to the generation of a HOx plume which substantially aids the downstream ozone production.

A comparative study of two approaches to analyse groundwater recharge, travel times and nitrate storage distribution at a regional scale

NASA Astrophysics Data System (ADS)

Turkeltaub, T.; Ascott, M.; Gooddy, D.; Jia, X.; Shao, M.; Binley, A. M.

2017-12-01

Understanding deep percolation, travel time processes and nitrate storage in the unsaturated zone at a regional scale is crucial for sustainable management of many groundwater systems. Recently, global hydrological models have been developed to quantify the water balance at such scales and beyond. However, the coarse spatial resolution of the global hydrological models can be a limiting factor when analysing regional processes. This study compares simulations of water flow and nitrate storage based on regional and global scale approaches. The first approach was applied over the Loess Plateau of China (LPC) to investigate the water fluxes and nitrate storage and travel time to the LPC groundwater system. Using raster maps of climate variables, land use data and soil parameters enabled us to determine fluxes by employing Richards' equation and the advection - dispersion equation. These calculations were conducted for each cell on the raster map in a multiple 1-D column approach. In the second approach, vadose zone travel times and nitrate storage were estimated by coupling groundwater recharge (PCR-GLOBWB) and nitrate leaching (IMAGE) models with estimates of water table depth and unsaturated zone porosity. The simulation results of the two methods indicate similar spatial groundwater recharge, nitrate storage and travel time distribution. Intensive recharge rates are located mainly at the south central and south west parts of the aquifer's outcrops. Particularly low recharge rates were simulated in the top central area of the outcrops. However, there are significant discrepancies between the simulated absolute recharge values, which might be related to the coarse scale that is used in the PCR-GLOBWB model, leading to smoothing of the recharge estimations. Both models indicated large nitrate inventories in the south central and south west parts of the aquifer's outcrops and the shortest travel times in the vadose zone are in the south central and east parts of the outcrops. Our results suggest that, for the LPC at least, global scale models might be useful for highlighting the locations with higher recharge rates potential and nitrate contamination risk. Global modelling simulations appear ideal as a primary step in recognizing locations which require investigations at the plot, field and local scales.

Development of absorbing aerosol index simulator based on TM5-M7

NASA Astrophysics Data System (ADS)

Sun, Jiyunting; van Velthoven, Peter; Veefkind, Pepijn

2017-04-01

Aerosols alter the Earth's radiation budget directly by scattering and absorbing solar and thermal radiation, or indirectly by perturbing clouds formation and lifetime. These mechanisms offset the positive radiative forcing ascribed to greenhouse gases. In particular, absorbing aerosols such as black carbon and dust strongly enhance global warming. To quantify the impact of absorbing aerosol on global radiative forcing is challenging. In spite of wide spatial and temporal coverage space-borne instruments (we will use the Ozone Monitoring Instrument, OMI) are unable to derive complete information on aerosol distribution, composition, etc. The retrieval of aerosol optical properties also partly depends on additional information derived from other measurements or global atmospheric chemistry models. Common quantities of great interest presenting the amount of absorbing aerosol are AAOD (absorbing aerosol optical depth), the extinction due to absorption of aerosols under cloud free conditions; and AAI (absorbing aerosol index), a measure of aerosol absorption more directly derivable from UV band observations than AAOD. When comparing model simulations and satellite observations, resemblance is good in terms of the spatial distribution of both parameters. However, the quantitative discrepancy is considerable, indicating possible underestimates of simulated AAI by a factor of 2 to 3. Our research, hence, has started by evaluating to what extent aerosol models, such as our TM5-M7 model, represent the satellite measurements and by identifying the reasons for discrepancies. As a next step a transparent methodology for the comparison between model simulations and satellite observations is under development in the form of an AAI simulator based on TM5-M7.

Parametric uncertainties in global model simulations of black carbon column mass concentration

NASA Astrophysics Data System (ADS)

Pearce, Hana; Lee, Lindsay; Reddington, Carly; Carslaw, Ken; Mann, Graham

2016-04-01

Previous studies have deduced that the annual mean direct radiative forcing from black carbon (BC) aerosol may regionally be up to 5 W m-2 larger than expected due to underestimation of global atmospheric BC absorption in models. We have identified the magnitude and important sources of parametric uncertainty in simulations of BC column mass concentration from a global aerosol microphysics model (GLOMAP-Mode). A variance-based uncertainty analysis of 28 parameters has been performed, based on statistical emulators trained on model output from GLOMAP-Mode. This is the largest number of uncertain model parameters to be considered in a BC uncertainty analysis to date and covers primary aerosol emissions, microphysical processes and structural parameters related to the aerosol size distribution. We will present several recommendations for further research to improve the fidelity of simulated BC. In brief, we find that the standard deviation around the simulated mean annual BC column mass concentration varies globally between 2.5 x 10-9 g cm-2 in remote marine regions and 1.25 x 10-6 g cm-2 near emission sources due to parameter uncertainty Between 60 and 90% of the variance over source regions is due to uncertainty associated with primary BC emission fluxes, including biomass burning, fossil fuel and biofuel emissions. While the contributions to BC column uncertainty from microphysical processes, for example those related to dry and wet deposition, are increased over remote regions, we find that emissions still make an important contribution in these areas. It is likely, however, that the importance of structural model error, i.e. differences between models, is greater than parametric uncertainty. We have extended our analysis to emulate vertical BC profiles at several locations in the mid-Pacific Ocean and identify the parameters contributing to uncertainty in the vertical distribution of black carbon at these locations. We will present preliminary comparisons of emulated BC vertical profiles from the AeroCom multi-model ensemble and Hiaper Pole-to-Pole (HIPPO) observations.

Defining metrics of the Quasi-Biennial Oscillation in global climate models

NASA Astrophysics Data System (ADS)

Schenzinger, Verena; Osprey, Scott; Gray, Lesley; Butchart, Neal

2017-06-01

As the dominant mode of variability in the tropical stratosphere, the Quasi-Biennial Oscillation (QBO) has been subject to extensive research. Though there is a well-developed theory of this phenomenon being forced by wave-mean flow interaction, simulating the QBO adequately in global climate models still remains difficult. This paper presents a set of metrics to characterize the morphology of the QBO using a number of different reanalysis datasets and the FU Berlin radiosonde observation dataset. The same metrics are then calculated from Coupled Model Intercomparison Project 5 and Chemistry-Climate Model Validation Activity 2 simulations which included a representation of QBO-like behaviour to evaluate which aspects of the QBO are well captured by the models and which ones remain a challenge for future model development.

Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

NASA Astrophysics Data System (ADS)

Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

Characterizing uncertainties in recent trends of global terrestrial net primary production through ensemble modeling

NASA Astrophysics Data System (ADS)

Wang, W.; Hashimoto, H.; Ganguly, S.; Votava, P.; Nemani, R. R.; Myneni, R. B.

2010-12-01

Large uncertainties exist in our understanding of the trends and variability in global net primary production (NPP) and its controls. This study attempts to address this question through a multi-model ensemble experiment. In particular, we drive ecosystem models including CASA, LPJ, Biome-BGC, TOPS-BGC, and BEAMS with a long-term climate dataset (i.e., CRU-NCEP) to estimate global NPP from 1901 to 2009 at a spatial resolution of 0.5 x 0.5 degree. We calculate the trends of simulated NPP during different time periods and test their sensitivities to climate variables of solar radiation, air temperature, precipitation, vapor pressure deficit (VPD), and atmospheric CO2 levels. The results indicate a large diversity among the simulated NPP trends over the past 50 years, ranging from nearly no trend to an increasing trend of ~0.1 PgC/yr. Spatial patterns of the NPP generally show positive trends in boreal forests, induced mainly by increasing temperatures in these regions; they also show negative trends in the tropics, although the spatial patterns are more diverse. These diverse trends result from different climatic sensitivities of NPP among the tested models. Depending the ecological processes (e.g., photosynthesis or respiration) a model emphasizes, it can be more or less responsive to changes in solar radiation, temperatures, water, or atmospheric CO2 levels. Overall, these results highlight the limit of current ecosystem models in simulating NPP, which cannot be easily observed. They suggest that the traditional single-model approach is not ideal for characterizing trends and variability in global carbon cycling.

Can global hydrological models reproduce large scale river flood regimes?

NASA Astrophysics Data System (ADS)

Eisner, Stephanie; Flörke, Martina

2013-04-01

River flooding remains one of the most severe natural hazards. On the one hand, major flood events pose a serious threat to human well-being, causing deaths and considerable economic damage. On the other hand, the periodic occurrence of flood pulses is crucial to maintain the functioning of riverine floodplains and wetlands, and to preserve the ecosystem services the latter provide. In many regions, river floods reveal a distinct seasonality, i.e. they occur at a particular time during the year. This seasonality is related to regionally dominant flood generating processes which can be expressed in river flood types. While in data-rich regions (esp. Europe and North America) the analysis of flood regimes can be based on observed river discharge time series, this data is sparse or lacking in many other regions of the world. This gap of knowledge can be filled by global modeling approaches. However, to date most global modeling studies have focused on mean annual or monthly water availability and their change over time while simulating discharge extremes, both floods and droughts, still remains a challenge for large scale hydrological models. This study will explore the ability of the global hydrological model WaterGAP3 to simulate the large scale patterns of river flood regimes, represented by seasonal pattern and the dominant flood type. WaterGAP3 simulates the global terrestrial water balance on a 5 arc minute spatial grid (excluding Greenland and Antarctica) at a daily time step. The model accounts for human interference on river flow, i.e. water abstraction for various purposes, e.g. irrigation, and flow regulation by large dams and reservoirs. Our analysis will provide insight in the general ability of global hydrological models to reproduce river flood regimes and thus will promote the creation of a global map of river flood regimes to provide a spatially inclusive and comprehensive picture. Understanding present-day flood regimes can support both flood risk analysis and the assessment of potential regional impacts of climate change on river flooding.

Climate change effects on landslides in southern B.C.

NASA Astrophysics Data System (ADS)

Jakob, M.

2009-04-01

Two mechanisms that contribute to the temporal occurrence of landslides in coastal British Columbia are ante¬cedent rainfall and short-term intense rainfall. These two quantities can be extracted from the precipitation regimes simulated by climate models. This makes such models an attractive tool for use in the investigation of the effect of global warming on landslide fre¬quencies. In order to provide some measure of the reliability of models used to address the landslide question, the present-day simulation of the antecedent precipitation and short- term rainfall using the daily data from the Canadian Centre for Climate Modelling and Analysis model (CGCM) is compared to observations along the south coast of British Colum¬bia. This evaluation showed that the model was reasonably successful in simulating sta¬tistics of the antecedent rainfall but was less successful in simulating the short-term rainfall. The monthly mean precipitation data from an ensemble of 19 of the world's global climate models were available to study potential changes in landslide frequencies with global warming. Most of the models were used to produce simulations with three scenar¬ios with different levels of prescribed greenhouse gas concentrations during the twenty-first century. The changes in the antecedent precipitation were computed from the resulting monthly and seasonal means. In order to deal with models' suspected difficulties in sim¬ulating the short-term precipitation and lack of daily data, a statistical procedure was used to relate the short-term precipitation to the monthly means. The qualitative model results agree reasonably well, and when averaged over all models and the three scenarios, the change in the antecedent precipitation is predicted to be about 10% and the change in the short-term precipitation about 6%. Because the antecedent precipitation and the short-term precipitation contribute to the occurrence of landslides, the results of this study support the prediction of increased landslide frequency along the British Columbia south coast during the twenty-first century.

Future projections of temperature and precipitation climatology for CORDEX-MENA domain using RegCM4.4

NASA Astrophysics Data System (ADS)

Ozturk, Tugba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent

2018-07-01

In this study, we investigate changes in seasonal temperature and precipitation climatology of CORDEX Middle East and North Africa (MENA) region for three periods of 2010-2040, 2040-2070 and 2070-2100 with respect to the control period of 1970-2000 by using regional climate model simulations. Projections of future climate conditions are modeled by forcing Regional Climate Model, RegCM4.4 of the International Centre for Theoretical Physics (ICTP) with two different CMIP5 global climate models. HadGEM2-ES global climate model of the Met Office Hadley Centre and MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology were used to generate 50 km resolution data for the Coordinated Regional Climate Downscaling Experiment (CORDEX) Region 13. We test the seasonal time-scale performance of RegCM4.4 in simulating the observed climatology over domain of the MENA by using the output of two different global climate models. The projection results show relatively high increase of average temperatures from 3 °C up to 9 °C over the domain for far future (2070-2100). A strong decrease in precipitation is projected in almost all parts of the domain according to the output of the regional model forced by scenario outputs of two global models. Therefore, warmer and drier than present climate conditions are projected to occur more intensely over the CORDEX-MENA domain.

Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century

NASA Astrophysics Data System (ADS)

Kravtsov, Sergey

2017-06-01

Identification and dynamical attribution of multidecadal climate undulations to either variations in external forcings or to internal sources is one of the most important topics of modern climate science, especially in conjunction with the issue of human-induced global warming. Here we utilize ensembles of twentieth century climate simulations to isolate the forced signal and residual internal variability in a network of observed and modeled climate indices. The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether absent in model simulations. This single mode explains a major fraction of model-data differences over the entire climate index network considered; it may reflect either biases in the models' forced response or models' lack of requisite internal dynamics, or a combination of both.