Simulation of modern climate with the new version of the INM RAS climate model
NASA Astrophysics Data System (ADS)
Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykosov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Yakovlev, N. G.
2017-03-01
The INMCM5.0 numerical model of the Earth's climate system is presented, which is an evolution from the previous version, INMCM4.0. A higher vertical resolution for the stratosphere is applied in the atmospheric block. Also, we raised the upper boundary of the calculating area, added the aerosol block, modified parameterization of clouds and condensation, and increased the horizontal resolution in the ocean block. The program implementation of the model was also updated. We consider the simulation of the current climate using the new version of the model. Attention is focused on reducing systematic errors as compared to the previous version, reproducing phenomena that could not be simulated correctly in the previous version, and modeling the problems that remain unresolved.
NASA Technical Reports Server (NTRS)
Pawson, S.; Stolarski, R.S.; Nielsen, J.E.; Perlwitz, J.; Oman, L.; Waugh, D.
2009-01-01
This study will document the behavior of the polar vortices in two versions of the GEOS CCM. Both versions of the model include the same stratospheric chemistry, They differ in the underlying circulation model. Version 1 of the GEOS CCM is based on the Goddard Earth Observing System, Version 4, general circulation model which includes the finite-volume (Lin-Rood) dynamical core and physical parameterizations from Community Climate Model, Version 3. GEOS CCM Version 2 is based on the GEOS-5 GCM that includes a different tropospheric physics package. Baseline simulations of both models, performed at two-degree spatial resolution, show some improvements in Version 2, but also some degradation, In the Antarctic, both models show an over-persistent stratospheric polar vortex with late breakdown, but the year-to-year variations that are overestimated in Version I are more realistic in Version 2. The implications of this for the interactions with tropospheric climate, the Southern Annular Mode, will be discussed. In the Arctic both model versions show a dominant dynamically forced variabi;ity, but Version 2 has a persistent warm bias in the low stratosphere and there are seasonal differences in the simulations. These differences will be quantified in terms of climate change and ozone loss. Impacts of model resolution, using simulations at one-degree and half-degree, and changes in physical parameterizations (especially the gravity wave drag) will be discussed.
NASA Astrophysics Data System (ADS)
Wilhelm, C.; Rechid, D.; Jacob, D.
2013-05-01
The main objective of this study is the coupling of the regional climate model REMO to a 3rd generation land surface scheme and the evaluation of the new model version of REMO, called REMO with interactive MOsaic-based VEgetation: REMO-iMOVE. Attention is paid to the documentation of the technical aspects of the new model constituents and the coupling mechanism. We compare simulation results of REMO-iMOVE and of the reference version REMO2009, to investigate the sensitivity of the regional model to the new land surface scheme. An 11 yr climate model run (1995-2005), forced with ECMWF ERA-Interim lateral boundary conditions, over Europe in 0.44° resolution of both model versions was carried out, to represent present day European climate. The result of these experiments are compared to multiple temperature, precipitation, heat flux and leaf area index observation data, to determine the differences in the model versions. The new model version has further the ability to model net primary productivity for the given plant functional types. This new feature is thoroughly evaluated by literature values of net primary productivity of different plant species in European climatic regions. The new model version REMO-iMOVE is able to model the European climate in the same quality as the parent model version REMO2009 does. The differences in the results of the two model versions stem from the differences in the dynamics of vegetation cover and density and can be distinct in some regions, due to the influences of these parameters to the surface heat and moisture fluxes. The modeled inter-annual variability in the phenology as well as the net primary productivity lays in the range of observations and literature values for most European regions. This study also reveals the need for a more sophisticated soil moisture representation in the newly developed model version REMO-iMOVE to be able to treat the differences in plant functional types. This gets especially important if the model will be used in dynamic vegetation studies.
Climate Sensitivity of the Community Climate System Model, Version 4
Bitz, Cecilia M.; Shell, K. M.; Gent, P. R.; ...
2012-05-01
Equilibrium climate sensitivity of the Community Climate System Model Version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. We use the radiative kernel technique to show that from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude, and the shortwave cloud feedback increases. These twomore » warming effects are partially canceled by cooling due to slight decreases in the global mean water-vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed-layer, slab ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab ocean model version for both CCSM3 and CCSM4. We argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.« less
NASA Technical Reports Server (NTRS)
Pawson, Steven; Stolarski, Richard S.; Nielsen, J. Eric; Duncan, Bryan N.
2008-01-01
Version 1 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) was used in the first CCMVa1 model evaluation and forms the basis for several studies of links between ozone and the circulation. That version of the CCM was based on the GEOS-4 GCM. Versions 2 and 3 of the GEOS CCM are based on the GEOS-5 GCM, which retains the "Lin-Rood" dynamical core but has a totally different set of physical parameterizatiOns to GEOS-4. In Version 2 of the GEOS CCM the Goddard stratospheric chemistry module is retained. Difference between Versions 1 and 2 thus reflect the physics changes of the underlying GCMs. Several comparisons between these two models are made, several of which reveal improvements in Version 2 (including a more realistic representation of the interannual variability of the Antarctic vortex). In Version 3 of the GEOS CCM, the stratospheric chemistry mechanism is replaced by the "GMI COMBO" code that includes tropospheric chemistry and different computational approaches. An advantage of this model version. is the reduction of high ozone biases that prevail at low chlorine loadings in Versions 1 and 2. This poster will compare and contrast various aspects of the three model versions that are relevant for understanding interactions between ozone and climate.
Steele, Madeline O.; Chang, Heejun; Reusser, Deborah A.; Brown, Cheryl A.; Jung, Il-Won
2012-01-01
As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on Climate Change. With these climate-forcing outputs, we derived the mean change in flow from the period encompassing the 1980s (1971-1995) to the period encompassing the 2050s (2041-2065). Specifically, we calculated percent change in mean monthly flow rate, coefficient of variation, top 5 percent of flow, and 7-day low flow. The trends with the most agreement among climate models and among watersheds were increases in autumn mean monthly flows, especially in October and November, decreases in summer monthly mean flow, and increases in the top 5 percent of flow. We also estimated variance in PRMS outputs owing to parameter uncertainty and the selection of climate model using Latin hypercube sampling. This analysis showed that PRMS low-flow simulations are more uncertain than medium or high flow simulations, and that variation among climate models was a larger source of uncertainty than the hydrological model parameters. These results improve our understanding of how climate change may affect the saltwater-freshwater balance in Pacific Northwest estuaries, with implications for their sensitive ecosystems.
EPA's announced the availability of the final report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Version 2). This update furthered land change modeling by providing nationwide housing developmen...
NASA Technical Reports Server (NTRS)
Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.
1988-01-01
A seasonal climate model was developed to test the climate sensitivity and, in particular, the Milankovitch (1941) theory. Four climate model versions were implemented to investigate the range of uncertainty in the parameterizations of three basic feedback mechanisms: the ice albedo-temperature, the outgoing long-wave radiation-temperature, and the eddy transport-meridional temperature gradient. It was found that the differences between the simulation of the present climate by the four versions were generally small, especially for annually averaged results. The climate model was also used to study the effect of growing/shrinking of a continental ice sheet, bedrock sinking/uplifting, and sea level changes on the climate system, taking also into account the feedback effects on the climate of the building of the ice caps.
The Community Climate System Model.
NASA Astrophysics Data System (ADS)
Blackmon, Maurice; Boville, Byron; Bryan, Frank; Dickinson, Robert; Gent, Peter; Kiehl, Jeffrey; Moritz, Richard; Randall, David; Shukla, Jagadish; Solomon, Susan; Bonan, Gordon; Doney, Scott; Fung, Inez; Hack, James; Hunke, Elizabeth; Hurrell, James; Kutzbach, John; Meehl, Jerry; Otto-Bliesner, Bette; Saravanan, R.; Schneider, Edwin K.; Sloan, Lisa; Spall, Michael; Taylor, Karl; Tribbia, Joseph; Washington, Warren
2001-11-01
The Community Climate System Model (CCSM) has been created to represent the principal components of the climate system and their interactions. Development and applications of the model are carried out by the U.S. climate research community, thus taking advantage of both wide intellectual participation and computing capabilities beyond those available to most individual U.S. institutions. This article outlines the history of the CCSM, its current capabilities, and plans for its future development and applications, with the goal of providing a summary useful to present and future users. The initial version of the CCSM included atmosphere and ocean general circulation models, a land surface model that was grafted onto the atmosphere model, a sea-ice model, and a flux coupler that facilitates information exchanges among the component models with their differing grids. This version of the model produced a successful 300-yr simulation of the current climate without artificial flux adjustments. The model was then used to perform a coupled simulation in which the atmospheric CO2 concentration increased by 1% per year. In this version of the coupled model, the ocean salinity and deep-ocean temperature slowly drifted away from observed values. A subsequent correction to the roughness length used for sea ice significantly reduced these errors. An updated version of the CCSM was used to perform three simulations of the twentieth century's climate, and several pro-jections of the climate of the twenty-first century. The CCSM's simulation of the tropical ocean circulation has been significantly improved by reducing the background vertical diffusivity and incorporating an anisotropic horizontal viscosity tensor. The meridional resolution of the ocean model was also refined near the equator. These changes have resulted in a greatly improved simulation of both the Pacific equatorial undercurrent and the surface countercurrents. The interannual variability of the sea surface temperature in the central and eastern tropical Pacific is also more realistic in simulations with the updated model. Scientific challenges to be addressed with future versions of the CCSM include realistic simulation of the whole atmosphere, including the middle and upper atmosphere, as well as the troposphere; simulation of changes in the chemical composition of the atmosphere through the incorporation of an integrated chemistry model; inclusion of global, prognostic biogeochemical components for land, ocean, and atmosphere; simulations of past climates, including times of extensive continental glaciation as well as times with little or no ice; studies of natural climate variability on seasonal-to-centennial timescales; and investigations of anthropogenic climate change. In order to make such studies possible, work is under way to improve all components of the model. Plans call for a new version of the CCSM to be released in 2002. Planned studies with the CCSM will require much more computer power than is currently available.
Thermosphere-Ionosphere-Mesosphere Modeling Using the TIME-GCM
2014-09-30
respectively. The CCM3 is the NCAR Community Climate Model, Version 3.6, a GCM of the troposphere and stratosphere. All models include self-consistent...middle atmosphere version of the NCAR Community Climate Model, (2) the NCAR TIME-GCM, and (3) the Model for Ozone and Related Chemical Tracers (MOZART... troposphere , but the impacts of such events extend well into the mesosphere. The coupled NCAR thermosphere-ionosphere-mesosphere- electrodynamics general
The seasonal-cycle climate model
NASA Technical Reports Server (NTRS)
Marx, L.; Randall, D. A.
1981-01-01
The seasonal cycle run which will become the control run for the comparison with runs utilizing codes and parameterizations developed by outside investigators is discussed. The climate model currently exists in two parallel versions: one running on the Amdahl and the other running on the CYBER 203. These two versions are as nearly identical as machine capability and the requirement for high speed performance will allow. Developmental changes are made on the Amdahl/CMS version for ease of testing and rapidity of turnaround. The changes are subsequently incorporated into the CYBER 203 version using vectorization techniques where speed improvement can be realized. The 400 day seasonal cycle run serves as a control run for both medium and long range climate forecasts alsensitivity studies.
EPA announced the availability of the draft report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) for a 30-day public comment period. The ICLUS version 2 (v2) modeling tool furthered land change mod...
PRMS-IV, the precipitation-runoff modeling system, version 4
Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.
2015-01-01
Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.
NASA Astrophysics Data System (ADS)
Noël, Brice; van de Berg, Willem Jan; Melchior van Wessem, J.; van Meijgaard, Erik; van As, Dirk; Lenaerts, Jan T. M.; Lhermitte, Stef; Kuipers Munneke, Peter; Smeets, C. J. P. Paul; van Ulft, Lambertus H.; van de Wal, Roderik S. W.; van den Broeke, Michiel R.
2018-03-01
We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 (1958-2016). The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of cloud condensate into precipitation have been tuned to correct inland snowfall underestimation: snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves the spatial patterns and temporal variability of SMB compared with the previous model version, notably in the north-east, south-east and along the K-transect in south-western Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS present-day climate and SMB, and will be used for projections of the GrIS climate and SMB in response to a future climate scenario in a forthcoming study.
High-resolution dynamic downscaling of CMIP5 output over the Tropical Andes
NASA Astrophysics Data System (ADS)
Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki
2015-04-01
Our project is targeted towards making robust predictions of future changes in climate over the tropical part of the South American Andes. This goal is challenging, since tropical lowlands, steep mountains, and snow covered subarctic surfaces meet over relatively short distances, leading to distinct climate regimes within the same domain and pronounced spatial gradients in virtually every climate quantity. We use an innovative approach to solve this problem, including several quadruple nested versions of WRF, a systematic validation strategy to find the version of WRF that best fits our study region, spatial resolutions at the kilometer scale, 20-year-long simulation periods, and bias-corrected output from various CMIP5 simulations that also include the multi-model mean of all CMIP5 models. We show that the simulated changes in climate are consistent with the results from the global climate models and also consistent with two different versions of WRF. We also discuss the expected changes in snow and ice, derived from off-line coupling the regional simulations to a carefully calibrated snow and ice model.
Future climate change under RCP emission scenarios with GISS ModelE2
Nazarenko, L.; Schmidt, G. A.; Miller, R. L.; ...
2015-02-24
We examine the anthropogenically forced climate response for the 21st century representative concentration pathway (RCP) emission scenarios and their extensions for the period 2101–2500. The experiments were performed with ModelE2, a new version of the NASA Goddard Institute for Space Sciences (GISS) coupled general circulation model that includes three different versions for the atmospheric composition components: a noninteractive version (NINT) with prescribed composition and a tuned aerosol indirect effect (AIE), the TCAD version with fully interactive aerosols, whole-atmosphere chemistry, and the tuned AIE, and the TCADI version which further includes a parameterized first indirect aerosol effect on clouds. Each atmosphericmore » version is coupled to two different ocean general circulation models: the Russell ocean model (GISS-E2-R) and HYCOM (GISS-E2-H). By 2100, global mean warming in the RCP scenarios ranges from 1.0 to 4.5° C relative to 1850–1860 mean temperature in the historical simulations. In the RCP2.6 scenario, the surface warming in all simulations stays below a 2 °C threshold at the end of the 21st century. For RCP8.5, the range is 3.5–4.5° C at 2100. Decadally averaged sea ice area changes are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with a larger sensitivity during winter months. By the year 2500, there are complete recoveries of the globally averaged surface air temperature for all versions of the GISS climate model in the low-forcing scenario RCP2.6. TCADI simulations show enhanced warming due to greater sensitivity to CO₂, aerosol effects, and greater methane feedbacks, and recovery is much slower in RCP2.6 than with the NINT and TCAD versions. All coupled models have decreases in the Atlantic overturning stream function by 2100. In RCP2.6, there is a complete recovery of the Atlantic overturning stream function by the year 2500 while with scenario RCP8.5, the E2-R climate model produces a complete shutdown of deep water formation in the North Atlantic.« less
Projecting Future Water Levels of the Laurentian Great Lakes
NASA Astrophysics Data System (ADS)
Bennington, V.; Notaro, M.; Holman, K.
2013-12-01
The Laurentian Great Lakes are the largest freshwater system on Earth, containing 84% of North America's freshwater. The lakes are a valuable economic and recreational resource, valued at over 62 billion in annual wages and supporting a 7 billion fishery. Shipping, recreation, and coastal property values are significantly impacted by water level variability, with large economic consequences. Great Lakes water levels fluctuate both seasonally and long-term, responding to natural and anthropogenic climate changes. Due to the integrated nature of water levels, a prolonged small change in any one of the net basin supply components: over-lake precipitation, watershed runoff, or evaporation from the lake surface, may result in important trends in water levels. We utilize the Abdus Salam International Centre for Theoretical Physics's Regional Climate Model Version 4.5.6 to dynamically downscale three global global climate models that represent a spread of potential future climate change for the region to determine whether the climate models suggest a robust response of the Laurentian Great Lakes to anthropogenic climate change. The Model for Interdisciplinary Research on Climate Version 5 (MIROC5), the National Centre for Meteorological Research Earth system model (CNRM-CM5), and the Community Climate System Model Version 4 (CCSM4) project different regional temperature increases and precipitation change over the next century and are used as lateral boundary conditions. We simulate the historical (1980-2000) and late-century periods (2080-2100). Upon model evaluation we will present dynamically downscaled projections of net basin supply changes for each of the Laurentian Great Lakes.
NASA Astrophysics Data System (ADS)
Melchior van Wessem, Jan; van de Berg, Willem Jan; Noël, Brice P. Y.; van Meijgaard, Erik; Amory, Charles; Birnbaum, Gerit; Jakobs, Constantijn L.; Krüger, Konstantin; Lenaerts, Jan T. M.; Lhermitte, Stef; Ligtenberg, Stefan R. M.; Medley, Brooke; Reijmer, Carleen H.; van Tricht, Kristof; Trusel, Luke D.; van Ulft, Lambertus H.; Wouters, Bert; Wuite, Jan; van den Broeke, Michiel R.
2018-04-01
We evaluate modelled Antarctic ice sheet (AIS) near-surface climate, surface mass balance (SMB) and surface energy balance (SEB) from the updated polar version of the regional atmospheric climate model, RACMO2 (1979-2016). The updated model, referred to as RACMO2.3p2, incorporates upper-air relaxation, a revised topography, tuned parameters in the cloud scheme to generate more precipitation towards the AIS interior and modified snow properties reducing drifting snow sublimation and increasing surface snowmelt. Comparisons of RACMO2 model output with several independent observational data show that the existing biases in AIS temperature, radiative fluxes and SMB components are further reduced with respect to the previous model version. The model-integrated annual average SMB for the ice sheet including ice shelves (minus the Antarctic Peninsula, AP) now amounts to 2229 Gt y-1, with an interannual variability of 109 Gt y-1. The largest improvement is found in modelled surface snowmelt, which now compares well with satellite and weather station observations. For the high-resolution ( ˜ 5.5 km) AP simulation, results remain comparable to earlier studies. The updated model provides a new, high-resolution data set of the contemporary near-surface climate and SMB of the AIS; this model version will be used for future climate scenario projections in a forthcoming study.
The Mars Climate Database (MCD version 5.2)
NASA Astrophysics Data System (ADS)
Millour, E.; Forget, F.; Spiga, A.; Navarro, T.; Madeleine, J.-B.; Montabone, L.; Pottier, A.; Lefevre, F.; Montmessin, F.; Chaufray, J.-Y.; Lopez-Valverde, M. A.; Gonzalez-Galindo, F.; Lewis, S. R.; Read, P. L.; Huot, J.-P.; Desjean, M.-C.; MCD/GCM development Team
2015-10-01
The Mars Climate Database (MCD) is a database of meteorological fields derived from General Circulation Model (GCM) numerical simulations of the Martian atmosphere and validated using available observational data. The MCD includes complementary post-processing schemes such as high spatial resolution interpolation of environmental data and means of reconstructing the variability thereof. We have just completed (March 2015) the generation of a new version of the MCD, MCD version 5.2
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dickinson, R.E.; Henderson-Sellers, A.; Kennedy, P.J.
A comprehensive model of land-surface processes has been under development suitable for use with various National Center for Atmospheric Research (NCAR) General Circulation Models (GCMs). Special emphasis has been given to describing properly the role of vegetation in modifying the surface moisture and energy budgets. The result of these efforts has been incorporated into a boundary package, referred to as the Biosphere-Atmosphere Transfer Scheme (BATS). The current frozen version, BATS1e is a piece of software about four thousand lines of code that runs as an offline version or coupled to the Community Climate Model (CCM).
NASA Technical Reports Server (NTRS)
Chandler, M. A.; Sohl, L. E.; Jonas, J. A.; Dowsett, H. J.; Kelley, M.
2013-01-01
The mid-Pliocene Warm Period (mPWP) bears many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change (IPCC, 2007). Both marine and terrestrial data point to high-latitude temperature amplification, including large decreases in sea ice and land ice, as well as expansion of warmer climate biomes into higher latitudes. Here we present our most recent simulations of the mid-Pliocene climate using the CMIP5 version of the NASAGISS Earth System Model (ModelE2-R). We describe the substantial impact associated with a recent correction made in the implementation of the Gent-McWilliams ocean mixing scheme (GM), which has a large effect on the simulation of ocean surface temperatures, particularly in the North Atlantic Ocean. The effect of this correction on the Pliocene climate results would not have been easily determined from examining its impact on the preindustrial runs alone, a useful demonstration of how the consequences of code improvements as seen in modern climate control runs do not necessarily portend the impacts in extreme climates.Both the GM-corrected and GM-uncorrected simulations were contributed to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasize features in the ModelE2-R simulations that are unlike the ensemble means. The corrected version yields results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene, especially the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea, which in the new simulation appears to be far more realistic than previously found with older versions of the GISS model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterisations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.
NASA Technical Reports Server (NTRS)
Ding, Feng; Fang, Fan; Hearty, Thomas J.; Theobald, Michael; Vollmer, Bruce; Lynnes, Christopher
2014-01-01
The Atmospheric Infrared Sounder (AIRS) mission is entering its 13th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing long-wave radiation, cloud properties, and trace gases. Thus AIRS data have been widely used, among other things, for short-term climate research and observational component for model evaluation. One instance is the fifth phase of the Coupled Model Intercomparison Project (CMIP5) which uses AIRS version 5 data in the climate model evaluation. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the AIRS mission. The GES DISC, in collaboration with the AIRS Project, released data from the version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. The ongoing Earth System Grid for next generation climate model research project, a collaborative effort of GES DISC and NASA JPL, will bring temperature and humidity profiles from AIRS version 6. The AIRS version 6 product adds a new "TqJoint" data group, which contains data for a common set of observations across water vapor and temperature at all atmospheric levels and is suitable for climate process studies. How different may the monthly temperature and humidity profiles in "TqJoint" group be from the "Standard" group where temperature and water vapor are not always valid at the same time? This study aims to answer the question by comprehensively comparing the temperature and humidity profiles from the "TqJoint" group and the "Standard" group. The comparison includes mean differences at different levels globally and over land and ocean. We are also working on examining the sampling differences between the "TqJoint" and "Standard" group using MERRA data.
NASA Astrophysics Data System (ADS)
Nazarenko, L.; Rind, D. H.; Bauer, S.; Del Genio, A. D.
2015-12-01
Simulations of aerosols, clouds and their interaction contribute to the major source of uncertainty in predicting the changing Earth's energy and in estimating future climate. Anthropogenic contribution of aerosols affects the properties of clouds through aerosol indirect effects. Three different versions of NASA GISS global climate model are presented for simulation of the twentieth century climate change. All versions have fully interactive tracers of aerosols and chemistry in both the troposphere and stratosphere. All chemical species are simulated prognostically consistent with atmospheric physics in the model and the emissions of short-lived precursors [Shindell et al., 2006]. One version does not include the aerosol indirect effect on clouds. The other two versions include a parameterization of the interactive first indirect aerosol effect on clouds following Menon et al. [2010]. One of these two models has the Multiconfiguration Aerosol Tracker of Mixing state (MATRIX) that permits detailed treatment of aerosol mixing state, size, and aerosol-cloud activation. The main purpose of this study is evaluation of aerosol-clouds interactions and feedbacks, as well as cloud and aerosol radiative forcings, for the twentieth century climate under different assumptions and parameterizations for aerosol, clouds and their interactions in the climate models. The change of global surface air temperature based on linear trend ranges from +0.8°C to +1.2°C between 1850 and 2012. Water cloud optical thickness increases with increasing temperature in all versions with the largest increase in models with interactive indirect effect of aerosols on clouds, which leads to the total (shortwave and longwave) cloud radiative cooling trend at the top of the atmosphere. Menon, S., D. Koch, G. Beig, S. Sahu, J. Fasullo, and D. Orlikowski (2010), Black carbon aerosols and the third polar ice cap, Atmos. Chem. Phys., 10,4559-4571, doi:10.5194/acp-10-4559-2010. Shindell, D., G. Faluvegi, N. Unger, E. Aguilar, G.A. Schmidt, D.M. Koch, S.E. Bauer, and J.R. Miller (2006), Simulations of preindustrial, present-day, and 2100 conditions in the NASA GISS composition and climate model G-PUCCINI, Atmos. Chem. Phys., 6, 4427-4459.
Representation of the Great Lakes in the Coupled Model Intercomparison Project Version 5
NASA Astrophysics Data System (ADS)
Briley, L.; Rood, R. B.
2017-12-01
The U.S. Great Lakes play a significant role in modifying regional temperatures and precipitation, and as the lakes change in response to a warming climate (i.e., warmer surface water temperatures, decreased ice cover, etc) lake-land-atmosphere dynamics are affected. Because the lakes modify regional weather and are a driver of regional climate change, understanding how they are represented in climate models is important to the reliability of model based information for the region. As part of the Great Lakes Integrated Sciences + Assessments (GLISA) Ensemble project, a major effort is underway to evaluate the Coupled Model Intercomparison Project version (CMIP) 5 global climate models for how well they physically represent the Great Lakes and lake-effects. The CMIP models were chosen because they are a primary source of information in many products developed for decision making (i.e., National Climate Assessment, downscaled future climate projections, etc.), yet there is very little description of how well they represent the lakes. This presentation will describe the results of our investigation of if and how the Great Lakes are represented in the CMIP5 models.
Present-day Antarctic climatology of the NCAR Community Climate Model Version 1
NASA Technical Reports Server (NTRS)
Tzeng, Ren-Yow; Bromwich, David H.; Parish, Thomas R.
1993-01-01
The ability of the NCAR Community Climate Model Version 1 (CCM1) with R 15 resolution to simulate the present-day climate of Antarctica was evaluated using the five-year seasonal cycle output produced by the CCM1 and comparing the model results with observed horizontal syntheses and point data. The results showed that the CCM1 with R 15 resolution can simulate to some extent the dynamics of Antarctic climate on the synoptic scale as well as some mesoscale features. The model can also simulate the phase and the amplitude of the annual and semiannual variation of the temperature, sea level pressure, and zonally averaged zonal (E-W) wind. The main shortcomings of the CCM1 model are associated with the model's anomalously large precipitation amounts at high latitudes, due to the tendency of the scheme to suppress negative moisture values.
weather@home 2: validation of an improved global-regional climate modelling system
NASA Astrophysics Data System (ADS)
Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.
2017-05-01
Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.
Psychometric Properties of the Abbreviated Perceived Motivational Climate in Exercise Questionnaire
ERIC Educational Resources Information Center
Moore, E. Whitney G.; Brown, Theresa C.; Fry, Mary D.
2015-01-01
The purpose of this study was to develop an abbreviated version of the Perceived Motivational Climate in Exercise Questionnaire (PMCEQ-A) to provide a more practical instrument for use in applied exercise settings. In the calibration step, two shortened versions' measurement and latent model values were compared to each other and the original…
The GEOS Chemistry Climate Model: Implications of Climate Feedbacks on Ozone Depletion and Recovery
NASA Technical Reports Server (NTRS)
Stolarski, Richard S.; Pawson, Steven; Douglass, Anne R.; Newman, Paul A.; Kawa, S. Randy; Nielsen, J. Eric; Rodriquez, Jose; Strahan, Susan; Oman, Luke; Waugh, Darryn
2008-01-01
The Goddard Earth Observing System Chemistry Climate Model (GEOS CCM) has been developed by combining the atmospheric chemistry and transport modules developed over the years at Goddard and the GEOS general circulation model, also developed at Goddard. The first version of the model was used in the CCMVal intercomparison exercises that contributed to the 2006 WMO/UNEP Ozone Assessment. The second version incorporates the updated version of the GCM (GEOS 5) and will be used for the next round of CCMVal evaluations and the 2010 Ozone Assessment. The third version, now under development, incorporates the combined stratosphere and troposphere chemistry package developed under the Global Modeling Initiative (GMI). We will show comparison to past observations that indicate that we represent the ozone trends over the past 30 years. We will also show the basic temperature, composition, and dynamical structure of the simulations. We will further show projections into the future. We will show results from an ensemble of transient and time-slice simulations, including simulations with fixed 1960 chlorine, simulations with a best guess scenario (Al), and simulations with extremely high chlorine loadings. We will discuss planned extensions of the model to include emission-based boundary conditions for both anthropogenic and biogenic compounds.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wan, Hui; Rasch, Philip J.; Zhang, Kai
2013-06-26
The purpose of this paper is to draw attention to the need for appropriate numerical techniques to represent process interactions in climate models. In two versions of the ECHAM-HAM model, different time integration methods are used to solve the sulfuric acid (H2SO4) gas evolution equation, which lead to substantially different results in the H2SO4 gas concentration and the aerosol nucleation rate. Using convergence tests and sensitivity simulations performed with various time stepping schemes, it is confirmed that numerical errors in the second model version are significantly smaller than those in version one. The use of sequential operator splitting in combinationmore » with long time step is identified as the main reason for the large systematic biases in the old model. The remaining errors in version two in the nucleation rate, related to the competition between condensation and nucleation, have a clear impact on the simulated concentration of cloud condensation nuclei in the lower troposphere. These errors can be significantly reduced by employing an implicit solver that handles production, condensation and nucleation at the same time. Lessons learned in this work underline the need for more caution when treating multi-time-scale problems involving compensating and competing processes, a common occurrence in current climate models.« less
NASA Astrophysics Data System (ADS)
Quéguiner, Solen; Martin, Eric; Lafont, Sébastien; Calvet, Jean-Christophe; Faroux, Stéphanie
2010-05-01
In the framework of the assessment of the impact of climate change, the uncertainty associated to the direct effect of CO2 on plant physiology was seldom addressed, while some other sources of uncertainties have been more studied, such as those related to climate modeling or the downscaling method. A few studies are available at global or continental scale. The purpose of this study is to quantify this effect in a regional study focussed on the Mediterranean area of France. The Safran-Isba-Modcou chain was used. This chain is composed of a meteorological analysis system (SAFRAN), a land surface model describing the exchange with the atmosphere (ISBA) and a hydrogeological model (MODCOU), and has already been used in many studies in France. The present study focuses on the uncertainties related to the representation of carbon cycle and the photosynthesis in the surface model. Two versions of ISBA were used and compared. The standard version simulates the mass and energy exchanges between the continental surface (including vegetation and snow) and the atmosphere. In this version, the LAI (Leaf Area Index) is provided by the ECOCLIMAP2 database and the vegetation is divided into 12 types. The A-gs version accounts for the process of photosynthesis taking into account the vegetation assimilation of atmospheric CO2 concentration, and simulates the evolution of the biomass and the LAI. The domain studied is the French mediterranean basin, in which a sub domain was defined (latitude < 45 °N et height < 1000m) in order to identify the low land area pertaining to a Mediterranean climate. The study focuses on the impact of the climate change on the surface variables (LAI, water balance) and the discharges. The periods chosen to compare the changes are the end of the 20th century (1995-2005) and the end of the 21st century (2090-2099). A first comparison is made for the present climate between the versions of model and the observations of discharges, using two type of meteorological forcing : SAFRAN and data from a continuous high resolution climate scenario, based on the scenario A2, with a coupled atmosphere-mediterranean sea GCM. This scenario was further downscaled to the resolution of the study (a grid mesh of 8x8 km), using a quantile-quantile correction method. Concerning the present climate, the comparison shows a delay of the development of the vegetation simulated by ISBA-A-gs causing an underestimation of evaporation and an overestimation of discharges in the spring compared to the observations and the standard version of ISBA. In future climate, the explicit response of vegetation to the CO2 concentration of the ISBA A-gs version gives an different answer on the surface water budget and flow from the standard version of ISBA. This difference is especially visible in the southern area, the impact on the flow is increased and impact on evaporation is decreased, showing the interest of using a CO2 responsive version of ISBA for impact studies.
Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0
NASA Astrophysics Data System (ADS)
Melton, J. R.; Arora, V. K.
2015-06-01
The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.
Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0
NASA Astrophysics Data System (ADS)
Melton, J. R.; Arora, V. K.
2016-01-01
The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.
CMIP5 Historical Simulations (1850-2012) with GISS ModelE2
NASA Technical Reports Server (NTRS)
Miller, Ronald Lindsay; Schmidt, Gavin A.; Nazarenko, Larissa S.; Tausnev, Nick; Bauer, Susanne E.; DelGenio, Anthony D.; Kelley, Max; Lo, Ken K.; Ruedy, Reto; Shindell, Drew T.;
2014-01-01
Observations of climate change during the CMIP5 extended historical period (1850-2012) are compared to trends simulated by six versions of the NASA Goddard Institute for Space Studies ModelE2 Earth System Model. The six models are constructed from three versions of the ModelE2 atmospheric general circulation model, distinguished by their treatment of atmospheric composition and the aerosol indirect effect, combined with two ocean general circulation models, HYCOM and Russell. Forcings that perturb the model climate during the historical period are described. Five-member ensemble averages from each of the six versions of ModelE2 simulate trends of surface air temperature, atmospheric temperature, sea ice and ocean heat content that are in general agreement with observed trends, although simulated warming is slightly excessive within the past decade. Only simulations that include increasing concentrations of long-lived greenhouse gases match the warming observed during the twentieth century. Differences in twentieth-century warming among the six model versions can be attributed to differences in climate sensitivity, aerosol and ozone forcing, and heat uptake by the deep ocean. Coupled models with HYCOM export less heat to the deep ocean, associated with reduced surface warming in regions of deepwater formation, but greater warming elsewhere at high latitudes along with reduced sea ice. All ensembles show twentieth-century annular trends toward reduced surface pressure at southern high latitudes and a poleward shift of the midlatitude westerlies, consistent with observations.
Description of the NCAR Community Climate Model (CCM3). Technical note
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kiehl, J.T.; Hack, J.J.; Bonan, G.B.
This repor presents the details of the governing equations, physical parameterizations, and numerical algorithms defining the version of the NCAR Community Climate Model designated CCM3. The material provides an overview of the major model components, and the way in which they interact as the numerical integration proceeds. This version of the CCM incorporates significant improvements to the physic package, new capabilities such as the incorporation of a slab ocean component, and a number of enhancements to the implementation (e.g., the ability to integrate the model on parallel distributed-memory computational platforms).
Time variation of effective climate sensitivity in GCMs
NASA Astrophysics Data System (ADS)
Williams, K. D.; Ingram, W. J.; Gregory, J. M.
2009-04-01
Effective climate sensitivity is often assumed to be constant (if uncertain), but some previous studies of General Circulation Model (GCM) simulations have found it varying as the simulation progresses. This complicates the fitting of simple models to such simulations, as well as having implications for the estimation of climate sensitivity from observations. This study examines the evolution of the feedbacks determining the climate sensitivity in GCMs submitted to the Coupled Model Intercomparison Project. Apparent centennial-timescale variations of effective climate sensitivity during stabilisation to a forcing can be considered an artefact of using conventional forcings which only allow for instantaneous effects and stratospheric adjustment. If the forcing is adjusted for processes occurring on timescales which are short compared to the climate stabilisation timescale then there is little centennial timescale evolution of effective climate sensitivity in any of the GCMs. We suggest that much of the apparent variation in effective climate sensitivity identified in previous studies is actually due to the comparatively fast forcing adjustment. Persistent differences are found in the strength of the feedbacks between the coupled atmosphere - ocean (AO) versions and their atmosphere - mixed-layer ocean (AML) counterparts, (the latter are often assumed to give the equilibrium climate sensitivity of the AOGCM). The AML model can typically only estimate the equilibrium climate sensitivity of the parallel AO version to within about 0.5K. The adjustment to the forcing to account for comparatively fast processes varies in magnitude and sign between GCMs, as well as differing between AO and AML versions of the same model. There is evidence from one AOGCM that the forcing adjustment may take a couple of decades, with implications for observationally based estimates of equilibrium climate sensitivity. We suggest that at least some of the spread in 21st century global temperature predictions between GCMs is due to differing adjustment processes, hence work to understand these differences should be a priority.
Evaluation of CESM1 (WACCM) with Observations of Stratospheric Composition
NASA Astrophysics Data System (ADS)
Kinnison, Doug; Froidevaux, Lucien; Garcia, Rolando; Fuller, Ryan
2017-04-01
The Community Earth System Model version 1 (CESM1) Whole Atmosphere Community Climate Model (WACCM) is used in this study. CESM1 (WACCM) includes a detailed representation of tropospheric through lower thermospheric chemistry and physical processes. Simulations for this work were based on scenarios defined by the Chemistry Climate Model Initiative (CCMI). These scenarios included both free-running (FR) and specified-dynamics versions (SD) of CESM1 (WACCM). Comparisons were made with global monthly zonal mean stratospheric data records from satellite-based remote measurements created by the Global Ozone Chemistry and Related Trace gas Data Records for the Stratosphere (GOZCARDS) project. These data records were drawn from high quality measurements of stratospheric composition starting in 1979 for ozone and in the early 1990s for other species. We discuss stratospheric variability and trends through analyses of observed time series of ozone (O3), hydrogen chloride (HCl), nitrous oxide (N2O), nitric acid (HNO3), and water vapor (H2O), and we contrast the fits from the FR and SD model versions. Conclusions from this work have aided in the development of a new version of CESM (WACCM) that will be used in the next Intergovernmental Panel on Climate Change (IPCC) Coupled Model Intercomparison Project Phase 6 (CMIP6) assessment.
NASA Astrophysics Data System (ADS)
Servonnat, Jérôme; Găinuşă-Bogdan, Alina; Braconnot, Pascale
2017-09-01
Turbulent momentum and heat (sensible heat and latent heat) fluxes at the air-sea interface are key components of the whole energetic of the Earth's climate. The evaluation of these fluxes in the climate models is still difficult because of the large uncertainties associated with the reference products. In this paper we present an objective metric accounting for reference uncertainties to evaluate the annual cycle of the low latitude turbulent fluxes of a suite of IPSL climate models. This metric consists in a Hotelling T 2 test between the simulated and observed field in a reduce space characterized by the dominant modes of variability that are common to both the model and the reference, taking into account the observational uncertainty. The test is thus more severe when uncertainties are small as it is the case for sea surface temperature (SST). The results of the test show that for almost all variables and all model versions the model-reference differences are not zero. It is not possible to distinguish between model versions for sensible heat and meridional wind stress, certainly due to the large observational uncertainties. All model versions share similar biases for the different variables. There is no improvement between the reference versions of the IPSL model used for CMIP3 and CMIP5. The test also reveals that the higher horizontal resolution fails to improve the representation of the turbulent surface fluxes compared to the other versions. The representation of the fluxes is further degraded in a version with improved atmospheric physics with an amplification of some of the biases in the Indian Ocean and in the intertropical convergence zone. The ranking of the model versions for the turbulent fluxes is not correlated with the ranking found for SST. This highlights that despite the fact that SST gradients are important for the large-scale atmospheric circulation patterns, other factors such as wind speed, and air-sea temperature contrast play an important role in the representation of turbulent fluxes.
Development of the GEOS-5 Atmospheric General Circulation Model: Evolution from MERRA to MERRA2.
NASA Technical Reports Server (NTRS)
Molod, Andrea; Takacs, Lawrence; Suarez, Max; Bacmeister, Julio
2014-01-01
The Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) version of the GEOS-5 (Goddard Earth Observing System Model - 5) Atmospheric General Circulation Model (AGCM) is currently in use in the NASA Global Modeling and Assimilation Office (GMAO) at a wide range of resolutions for a variety of applications. Details of the changes in parameterizations subsequent to the version in the original MERRA reanalysis are presented here. Results of a series of atmosphere-only sensitivity studies are shown to demonstrate changes in simulated climate associated with specific changes in physical parameterizations, and the impact of the newly implemented resolution-aware behavior on simulations at different resolutions is demonstrated. The GEOS-5 AGCM presented here is the model used as part of the GMAO's MERRA2 reanalysis, the global mesoscale "nature run", the real-time numerical weather prediction system, and for atmosphere-only, coupled ocean-atmosphere and coupled atmosphere-chemistry simulations. The seasonal mean climate of the MERRA2 version of the GEOS-5 AGCM represents a substantial improvement over the simulated climate of the MERRA version at all resolutions and for all applications. Fundamental improvements in simulated climate are associated with the increased re-evaporation of frozen precipitation and cloud condensate, resulting in a wetter atmosphere. Improvements in simulated climate are also shown to be attributable to changes in the background gravity wave drag, and to upgrades in the relationship between the ocean surface stress and the ocean roughness. The series of "resolution aware" parameters related to the moist physics were shown to result in improvements at higher resolutions, and result in AGCM simulations that exhibit seamless behavior across different resolutions and applications.
The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna
NASA Technical Reports Server (NTRS)
Molod, Andrea; Takacs, Lawrence; Suarez, Max; Bacmeister, Julio; Song, In-Sun; Eichmann, Andrew
2012-01-01
This report is a documentation of the Fortuna version of the GEOS-5 Atmospheric General Circulation Model (AGCM). The GEOS-5 AGCM is currently in use in the NASA Goddard Modeling and Assimilation Office (GMAO) for simulations at a wide range of resolutions, in atmosphere only, coupled ocean-atmosphere, and data assimilation modes. The focus here is on the development subsequent to the version that was used as part of NASA s Modern-Era Retrospective Analysis for Research and Applications (MERRA). We present here the results of a series of 30-year atmosphere-only simulations at different resolutions, with focus on the behavior of the 1-degree resolution simulation. The details of the changes in parameterizations subsequent to the MERRA model version are outlined, and results of a series of 30-year, atmosphere-only climate simulations at 2-degree resolution are shown to demonstrate changes in simulated climate associated with specific changes in parameterizations. The GEOS-5 AGCM presented here is the model used for the GMAO s atmosphere-only and coupled CMIP-5 simulations.
Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM)
NASA Astrophysics Data System (ADS)
Cao, Jian; Wang, Bin; Xiang, Baoqiang; Li, Juan; Wu, Tianjie; Fu, Xiouhua; Wu, Liguang; Min, Jinzhong
2015-05-01
A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model's major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model's assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.
Weather and seasonal climate prediction for South America using a multi-model superensemble
NASA Astrophysics Data System (ADS)
Chaves, Rosane R.; Ross, Robert S.; Krishnamurti, T. N.
2005-11-01
This work examines the feasibility of weather and seasonal climate predictions for South America using the multi-model synthetic superensemble approach for climate, and the multi-model conventional superensemble approach for numerical weather prediction, both developed at Florida State University (FSU). The effect on seasonal climate forecasts of the number of models used in the synthetic superensemble is investigated. It is shown that the synthetic superensemble approach for climate and the conventional superensemble approach for numerical weather prediction can reduce the errors over South America in seasonal climate prediction and numerical weather prediction.For climate prediction, a suite of 13 models is used. The forecast lead-time is 1 month for the climate forecasts, which consist of precipitation and surface temperature forecasts. The multi-model ensemble is comprised of four versions of the FSU-Coupled Ocean-Atmosphere Model, seven models from the Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction (DEMETER), a version of the Community Climate Model (CCM3), and a version of the predictive Ocean Atmosphere Model for Australia (POAMA). The results show that conditions over South America are appropriately simulated by the Florida State University Synthetic Superensemble (FSUSSE) in comparison to observations and that the skill of this approach increases with the use of additional models in the ensemble. When compared to observations, the forecasts are generally better than those from both a single climate model and the multi-model ensemble mean, for the variables tested in this study.For numerical weather prediction, the conventional Florida State University Superensemble (FSUSE) is used to predict the mass and motion fields over South America. Predictions of mean sea level pressure, 500 hPa geopotential height, and 850 hPa wind are made with a multi-model superensemble comprised of six global models for the period January, February, and December of 2000. The six global models are from the following forecast centers: FSU, Bureau of Meteorology Research Center (BMRC), Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP), Naval Research Laboratory (NRL), and Recherche en Prevision Numerique (RPN). Predictions of precipitation are made for the period January, February, and December of 2001 with a multi-analysis-multi-model superensemble where, in addition to the six forecast models just mentioned, five additional versions of the FSU model are used in the ensemble, each with a different initialization (analysis) based on different physical initialization procedures. On the basis of observations, the results show that the FSUSE provides the best forecasts of the mass and motion field variables to forecast day 5, when compared to both the models comprising the ensemble and the multi-model ensemble mean during the wet season of December-February over South America. Individual case studies show that the FSUSE provides excellent predictions of rainfall for particular synoptic events to forecast day 3. Copyright
NASA Astrophysics Data System (ADS)
Karl, Thomas R.; Wang, Wei-Chyung; Schlesinger, Michael E.; Knight, Richard W.; Portman, David
1990-10-01
Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model's internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between the output of a ten-year GCM control run and the surface-based observations are often smaller than the differences between the observations of two ten-year periods. Such positive results suggest that GCMs may already contain important climatological information that can be used to infer the local climate.
NASA Technical Reports Server (NTRS)
Li, Feng; Vikhliaev, Yury V.; Newman, Paul A.; Pawson, Steven; Perlwitz, Judith; Waugh, Darryn W.; Douglass, Anne R.
2016-01-01
Stratospheric ozone depletion plays a major role in driving climate change in the Southern Hemisphere. To date, many climate models prescribe the stratospheric ozone layer's evolution using monthly and zonally averaged ozone fields. However, the prescribed ozone underestimates Antarctic ozone depletion and lacks zonal asymmetries. In this study we investigate the impact of using interactive stratospheric chemistry instead of prescribed ozone on climate change simulations of the Antarctic and Southern Ocean. Two sets of 1960-2010 ensemble transient simulations are conducted with the coupled ocean version of the Goddard Earth Observing System Model, version 5: one with interactive stratospheric chemistry and the other with prescribed ozone derived from the same interactive simulations. The model's climatology is evaluated using observations and reanalysis. Comparison of the 1979-2010 climate trends between these two simulations reveals that interactive chemistry has important effects on climate change not only in the Antarctic stratosphere, troposphere, and surface, but also in the Southern Ocean and Antarctic sea ice. Interactive chemistry causes stronger Antarctic lower stratosphere cooling and circumpolar westerly acceleration during November-December-January. It enhances stratosphere-troposphere coupling and leads to significantly larger tropospheric and surface westerly changes. The significantly stronger surface wind stress trends cause larger increases of the Southern Ocean Meridional Overturning Circulation, leading to year-round stronger ocean warming near the surface and enhanced Antarctic sea ice decrease.
NASA Technical Reports Server (NTRS)
Suarez, Max J. (Editor); Chang, Yehui; Schubert, Siegfried D.; Lin, Shian-Jiann; Nebuda, Sharon; Shen, Bo-Wen
2001-01-01
This document describes the climate of version 1 of the NASA-NCAR model developed at the Data Assimilation Office (DAO). The model consists of a new finite-volume dynamical core and an implementation of the NCAR climate community model (CCM-3) physical parameterizations. The version of the model examined here was integrated at a resolution of 2 degrees latitude by 2.5 degrees longitude and 32 levels. The results are based on assimilation that was forced with observed sea surface temperature and sea ice for the period 1979-1995, and are compared with NCEP/NCAR reanalyses and various other observational data sets. The results include an assessment of seasonal means, subseasonal transients including the Madden Julian Oscillation, and interannual variability. The quantities include zonal and meridional winds, temperature, specific humidity, geopotential height, stream function, velocity potential, precipitation, sea level pressure, and cloud radiative forcing.
Simulating post-wildfire forest trajectories under alternative climate and management scenarios
Alicia Azpeleta Tarancon; Peter Z. Fule; Kristen L. Shive; Carolyn H. Sieg; Andrew Sanchez Meador; Barbara Strom
2014-01-01
Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned...
VEMAP vs VINCERA: a DGVM sensitivity to differences in climate scenarios
Dominique Bachelet; James Lenihan; Ray Drapek; Ronald Neilson
2008-01-01
The MCI DGVM has been used in two international model comparison projects, VEMAP (Vegetation Ecosystem Modeling and Analysis Project) and VINCERA (Vulnerability and Impacts of North American forests to Climate Change: Ecosystem Responses and Adaptation). The latest version of MC1 was run on both VINCERA and VEMAP climate and soil input data to document how a change in...
E. A. H. Smithwick; M. G. Ryan; D. M. Kashian; W. H. Romme; D. B. Tinker; M. G. Turner
2009-01-01
The interaction between disturbance and climate change and resultant effects on ecosystem carbon (C) and nitrogen (N) fluxes are poorly understood. Here, we model (using CENTURY version 4.5) how climate change may affect C and N fluxes among mature and regenerating lodgepole pine (Pinus contorta var. latifolia Engelm. ex S.Wats.)...
NASA Astrophysics Data System (ADS)
Pietikäinen, Joni-Pekka; Markkanen, Tiina; Sieck, Kevin; Jacob, Daniela; Korhonen, Johanna; Räisänen, Petri; Gao, Yao; Ahola, Jaakko; Korhonen, Hannele; Laaksonen, Ari; Kaurola, Jussi
2018-04-01
The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied in a set of 35-year hindcast simulations. Additionally, sensitivity tests related to the parameterization of snow albedo were conducted. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation, but the downside is that an existing wintertime cold bias in the model is enhanced. The lake surface water temperature, ice depth and ice season length were analyzed in detail for 10 Finnish, 4 Swedish and 2 Russian lakes and 1 Estonian lake. The results show that the model can reproduce these characteristics with reasonably high accuracy. The cold bias during winter causes overestimation of ice layer thickness, for example, at several of the studied lakes, but overall the values from the model are realistic and represent the lake physics well in a long-term simulation. We also analyzed the snow depth on ice from 10 Finnish lakes and vertical temperature profiles from 5 Finnish lakes and the model results are realistic.
Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system
NASA Astrophysics Data System (ADS)
Dong, J.; Ek, M. B.; Wei, H.; Meng, J.
2017-12-01
Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN).
Effects of the Bering Strait closure on AMOC and global climate under different background climates
NASA Astrophysics Data System (ADS)
Hu, Aixue; Meehl, Gerald A.; Han, Weiqing; Otto-Bliestner, Bette; Abe-Ouchi, Ayako; Rosenbloom, Nan
2015-03-01
Previous studies have suggested that the status of the Bering Strait may have a significant influence on global climate variability on centennial, millennial, and even longer time scales. Here we use multiple versions of the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM, versions 2 and 3) to investigate the influence of the Bering Strait closure/opening on the Atlantic Meridional Overturning Circulation (AMOC) and global mean climate under present-day, 15 thousand-year before present (kyr BP), and 112 kyr BP climate boundary conditions. Our results show that regardless of the version of the model used or the widely different background climates, the Bering Strait's closure produces a robust result of a strengthening of the AMOC, and an increase in the northward meridional heat transport in the Atlantic. As a consequence, the climate becomes warmer in the North Atlantic and the surrounding regions, but cooler in the North Pacific, leading to a seesaw-like climate change between these two basins. For the first time it is noted that the absence of the Bering Strait throughflow causes a slower motion of Arctic sea ice, a reduced upper ocean water exchange between the Arctic and North Atlantic, reduced sea ice export and less fresh water in the North Atlantic. These changes contribute positively to the increased upper ocean density there, thus strengthening the AMOC. Potentially these changes in the North Atlantic could have a significant effect on the ice sheets both upstream and downstream in ice age climate, and further influence global sea level changes.
NASA Astrophysics Data System (ADS)
Rowland, L.; Harper, A.; Christoffersen, B. O.; Galbraith, D. R.; Imbuzeiro, H. M. A.; Powell, T. L.; Doughty, C.; Levine, N. M.; Malhi, Y.; Saleska, S. R.; Moorcroft, P. R.; Meir, P.; Williams, M.
2015-04-01
Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model - CLM3.5-DGVM; Ecosystem Demography model version 2 - ED2; the Joint UK Land Environment Simulator version 2.1 - JULES; Simple Biosphere model version 3 - SiB3; and the soil-plant-atmosphere model - SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model-data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in An with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest that even up to fairly extreme temperature increases from ambient levels (+6 °C), simulated photosynthesis becomes increasingly sensitive to gs and remains less sensitive to biochemical changes. To improve the reliability of simulations of the response of Amazonian rainforest to climate change, the mechanistic underpinnings of vegetation models need to be validated at both leaf- and canopy-scales to improve accuracy and consistency in the quantification of processes within and across an ecosystem.
Upgrades to the REA method for producing probabilistic climate change projections
NASA Astrophysics Data System (ADS)
Xu, Ying; Gao, Xuejie; Giorgi, Filippo
2010-05-01
We present an augmented version of the Reliability Ensemble Averaging (REA) method designed to generate probabilistic climate change information from ensembles of climate model simulations. Compared to the original version, the augmented one includes consideration of multiple variables and statistics in the calculation of the performance-based weights. In addition, the model convergence criterion previously employed is removed. The method is applied to the calculation of changes in mean and variability for temperature and precipitation over different sub-regions of East Asia based on the recently completed CMIP3 multi-model ensemble. Comparison of the new and old REA methods, along with the simple averaging procedure, and the use of different combinations of performance metrics shows that at fine sub-regional scales the choice of weighting is relevant. This is mostly because the models show a substantial spread in performance for the simulation of precipitation statistics, a result that supports the use of model weighting as a useful option to account for wide ranges of quality of models. The REA method, and in particular the upgraded one, provides a simple and flexible framework for assessing the uncertainty related to the aggregation of results from ensembles of models in order to produce climate change information at the regional scale. KEY WORDS: REA method, Climate change, CMIP3
NASA Astrophysics Data System (ADS)
Nageswararao, M. M.; Mohanty, U. C.; Nair, Archana; Ramakrishna, S. S. V. S.
2016-06-01
The precipitation during winter (December through February) over India is highly variable in terms of time and space. Maximum precipitation occurs over the Himalaya region, which is important for water resources and agriculture sectors over the region and also for the economy of the country. Therefore, in the present global warming era, the realistic prediction of winter precipitation over India is important for planning and implementing agriculture and water management strategies. The National Centers for Environmental Prediction (NCEP) issued the operational prediction of climatic variables in monthly to seasonal scale since 2004 using their first version of fully coupled global climate model known as Climate Forecast System (CFSv1). In 2011, a new version of CFS (CFSv2) was introduced with the incorporation of significant changes in older version of CFS (CFSv1). The new version of CFS is required to compare in detail with the older version in the context of simulating the winter precipitation over India. Therefore, the current study presents a detailed analysis on the performance of CFSv2 as compared to CFSv1 for the winter precipitation over India. The hindcast runs of both CFS versions from 1982 to 2008 with November initial conditions are used and the model's precipitation is evaluated with that of India Meteorological Department (IMD). The models simulated wind and geopotential height against the National Center for Atmospheric Research (NCEP-NCAR) reanalysis-2 (NNRP2) and remote response patterns of SST against Extended Reconstructed Sea Surface Temperatures version 3b (ERSSTv3b) are examined for the same period. The analyses of winter precipitation revealed that both the models are able to replicate the patterns of observed climatology; interannual variability and coefficient of variation. However, the magnitude is lesser than IMD observation that can be attributed to the model's inability to simulate the observed remote response of sea surface temperatures to all India winter precipitation. Of the two, CFSv1 is appreciable in capturing year-to-year variations in observed winter precipitation while CFSv2 failed in simulating the same. CFSv1 has accounted for less mean bias and RMSE errors along with good correlations and index of agreements than CFSv2 for predicting winter precipitation over India. In addition, the CFSv1 is also having a high probability of detection in predicting different categories (normal, excess and deficit) of observed winter precipitation over India.
NASA Astrophysics Data System (ADS)
Stanfield, Ryan Evan
Global circulation/climate models (GCMs) remain as an invaluable tool to predict future potential climate change. To best advise policy makers, assessing and increasing the accuracy of climate models is paramount. The treatment of clouds, radiation and precipitation in climate models and their associated feedbacks have long been one of the largest sources of uncertainty in predicting any potential future climate changes. Three versions of the NASA GISS ModelE GCM (the frozen CMIP5 version [C5], a post-CMIP5 version with modifications to cumulus and boundary layer turbulence parameterizations [P5], and the most recent version of the GCM which builds on the post-CMIP5 version with further modifications to convective cloud ice and cold pool parameterizations [E5]) have been compared with various satellite observations to analyze how recent modifications to the GCM has impacted cloud, radiation, and precipitation properties. In addition to global comparisons, two areas are showcased in regional analyses: the Eastern Pacific Northern ITCZ (EP-ITCZ), and Indonesia and the Western Pacific (INDO-WP). Changes to the cumulus and boundary layer turbulence parameterizations in the P5 version of the GCM have improved cloud and radiation estimations in areas of descending motion, such as the Southern Mid-Latitudes. Ice particle size and fall speed modifications in the E5 version of the GCM have decreased ice cloud water contents and cloud fractions globally while increasing precipitable water vapor in the model. Comparisons of IWC profiles show that the GCM simulated IWCs increase with height and peak in the upper portions of the atmosphere, while 2C-ICE observations peak in the lower levels of the atmosphere and decrease with height, effectively opposite of each other. Profiles of CF peak at lower heights in the E5 simulation, which will potentially increase outgoing longwave radiation due to higher cloud top temperatures, which will counterbalance the decrease in reflected shortwave associated with lower CFs and the thinner optical depths associated with decreased IWC and LWC in the E5 simulation. Vertical motion within the newest E5 simulation is greatly weakened over the EP-ITCZ region, potentially due to atmospheric loading from enhanced ice particle fall speeds. Comparatively, E5 simulated upward motion in the INDO-WP is stronger than its predecessors. Changes in the E5 simulation have resulted in stronger/weaker upward motion over the ocean/land in the INDO-WP region in comparison with both the C5 and P5 predecessors. Multimodel precipitation analysis shows that most of the GCMs tend to produce a wider ITCZ with stronger precipitation compared to GPCP and TRMM precipitation products. E5-simulated precipitation decreases and shifts Southward over the Easter Pacific ITCZ, which warrants further investigation into meridional heat transport and radiation fields.
NASA Astrophysics Data System (ADS)
Zhang, K.; O'Donnell, D.; Kazil, J.; Stier, P.; Kinne, S.; Lohmann, U.; Ferrachat, S.; Croft, B.; Quaas, J.; Wan, H.; Rast, S.; Feichter, J.
2012-03-01
This paper introduces and evaluates the second version of the global aerosol-climate model ECHAM-HAM. Major changes have been brought into the model, including new parameterizations for aerosol nucleation and water uptake, an explicit treatment of secondary organic aerosols, modified emission calculations for sea salt and mineral dust, the coupling of aerosol microphysics to a two-moment stratiform cloud microphysics scheme, and alternative wet scavenging parameterizations. These revisions extend the model's capability to represent details of the aerosol lifecycle and its interaction with climate. Sensitivity experiments are carried out to analyse the effects of these improvements in the process representation on the simulated aerosol properties and global distribution. The new parameterizations that have largest impact on the global mean aerosol optical depth and radiative effects turn out to be the water uptake scheme and cloud microphysics. The former leads to a significant decrease of aerosol water contents in the lower troposphere, and consequently smaller optical depth; the latter results in higher aerosol loading and longer lifetime due to weaker in-cloud scavenging. The combined effects of the new/updated parameterizations are demonstrated by comparing the new model results with those from the earlier version, and against observations. Model simulations are evaluated in terms of aerosol number concentrations against measurements collected from twenty field campaigns as well as from fixed measurement sites, and in terms of optical properties against the AERONET measurements. Results indicate a general improvement with respect to the earlier version. The aerosol size distribution and spatial-temporal variance simulated by HAM2 are in better agreement with the observations. Biases in the earlier model version in aerosol optical depth and in the Ångström parameter have been reduced. The paper also points out the remaining model deficiencies that need to be addressed in the future.
RCCM2-BATS model over tropical South America: Applications to tropical deforestation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hahmann, A.N.; Dickinson, R.E.
A multiyear simulation of the global climate uses a revised version of the National Center for Atmospheric Research (NCAR) Community Climate Model Version 2 (CCM2) coupled to the Biosphere-Atmosphere Transfer Scheme (BATS). It is compared with global and rain gauge precipitation climatologies to evaluate precipitation fields and European Centre for Medium-Range Forecasts analyses to evaluate the atmospheric circulation. The near-surface climate is compared with data from Amazonian field campaigns. The model simulation of the South American climate agrees closely with the observational record and is much improved from past simulations with previous versions of the NCAR Community Climate model overmore » this portion of the Tropics. The model is then used to study the local and regional response to tropical deforestation over Amazonia. In addition to the standard deforestation forcing, consisting mainly of increased albedo and decreased roughness length, two additional sensitivity experiments were conducted to assess the individual contributions from these forcings to the deforestation changes. The standard deforestation simulation shows slight increases in annually averaged surface temperature (+1{degrees}C) and reductions in annually averaged precipitation and evaporation (-363 and -149 mm yr{sup -1}, respectively). As expected, increases in surface albedo over Amazonia produce a reduction in net downward solar radiation at the surface and consequently a reduction in net surface radiation and surface latent heat flux. The roughness decrease, on the other hand, reduces the surface latent heat fluxes through decreases in the surface drag coefficient. The regional changes in moisture convergence and precipitation during the Amazonian wet season display a shift in the area of maximum precipitation rather than an overall decrease over the deforested area. 45 refs., 16 figs., 4 tabs.« less
Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.
2016-01-01
Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.
SRT Status and Plans for Version-7
NASA Technical Reports Server (NTRS)
Susskind, Joel; Blaisdell, John; Iredell, Lena; Kouvaris, Louis
2015-01-01
The AIRS Science Team Version-6 retrieval algorithm is currently producing level-3 Climate Data Records (CDRs) from AIRS that have been proven useful to scientists in understanding climate processes. CDRs are gridded level-3 products which include all cases passing AIRS Climate QC. SRT has made significant further improvements to AIRS Version-6. Research is continuing at SRT toward the development of AIRS Version-7. At the last Science Team Meeting, we described results using SRT AIRS Version-6.19. SRT Version-6.19 is now an official build at JPL called 6.2. SRTs latest version is AIRS Version-6.22. We have also adapted AIRS Version-6.22 to run with CrISATMS. AIRS Version-6.22 and CrIS Version- 6.22 both run now on JPL computers, but are not yet official builds. The main reason for finalization of Version-7, and using it in the relatively near future for the future processing and reprocessing of old AIRS data, is to produce even better CDRs for use by climate scientists. For this reason all results shown in this talk use only AIRS Climate QC.
NASA Astrophysics Data System (ADS)
Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.
2013-12-01
This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.
The integrated Earth system model version 1: formulation and functionality
Collins, W. D.; Craig, A. P.; Truesdale, J. E.; ...
2015-07-23
The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less
Inequality, climate impacts on the future poor, and carbon prices.
Dennig, Francis; Budolfson, Mark B; Fleurbaey, Marc; Siebert, Asher; Socolow, Robert H
2015-12-29
Integrated assessment models of climate and the economy provide estimates of the social cost of carbon and inform climate policy. We create a variant of the Regional Integrated model of Climate and the Economy (RICE)-a regionally disaggregated version of the Dynamic Integrated model of Climate and the Economy (DICE)-in which we introduce a more fine-grained representation of economic inequalities within the model's regions. This allows us to model the common observation that climate change impacts are not evenly distributed within regions and that poorer people are more vulnerable than the rest of the population. Our results suggest that this is important to the social cost of carbon-as significant, potentially, for the optimal carbon price as the debate between Stern and Nordhaus on discounting.
Variability along the Atlantic water pathway in the forced Norwegian Earth System Model
NASA Astrophysics Data System (ADS)
Langehaug, H. R.; Sandø, A. B.; Årthun, M.; Ilıcak, M.
2018-03-01
The growing attention on mechanisms that can provide predictability on interannual-to-decadal time scales, makes it necessary to identify how well climate models represent such mechanisms. In this study we use a high (0.25° horizontal grid) and a medium (1°) resolution version of a forced global ocean-sea ice model, utilising the Norwegian Earth System Model, to assess the impact of increased ocean resolution. Our target is the simulation of temperature and salinity anomalies along the pathway of warm Atlantic water in the subpolar North Atlantic and the Nordic Seas. Although the high resolution version has larger biases in general at the ocean surface, the poleward propagation of thermohaline anomalies is better resolved in this version, i.e., the time for an anomaly to travel northward is more similar to observation based estimates. The extent of these anomalies can be rather large in both model versions, as also seen in observations, e.g., stretching from Scotland to northern Norway. The easternmost branch into the Nordic and Barents Seas, carrying warm Atlantic water, is also improved by higher resolution, both in terms of mean heat transport and variability in thermohaline properties. A more detailed assessment of the link between the North Atlantic Ocean circulation and the thermohaline anomalies at the entrance of the Nordic Seas reveals that the high resolution is more consistent with mechanisms that are previously published. This suggests better dynamics and variability in the subpolar region and the Nordic Seas in the high resolution compared to the medium resolution. This is most likely due a better representation of the mean circulation in the studied region when using higher resolution. As the poleward propagation of ocean heat anomalies is considered to be a key source of climate predictability, we recommend that similar methodology presented herein should be performed on coupled climate models that are used for climate prediction.
Psychometric properties of the Persian version of the “Hospital Ethical Climate Survey”
Khalesi, Nader; Arabloo, Jalal; Khosravizadeh, Omid; Taghizadeh, Sanaz; Heyrani, Ali; Ebrahimian, Abbasali
2014-01-01
In order to improve the ethical climate in health care organizations, it is important to apply a valid measure. This study aimed to investigate the psychometric properties of the Persian version of the Hospital Ethical Climate Survey (HECS) and to assess nurses’ perceptions of the ethical climate in teaching hospitals of Iran. A cross-sectional study of randomly selected nurses (n = 187) was conducted in three teaching general hospitals of Tehran, capital of Iran. Olson’s Hospital Ethical Climate Survey (HECS), a self-administered questionnaire, was used to assess the nurses’ perceptions of the hospital ethical climate. Descriptive statistics, confirmatory factor analysis (CFA), internal consistency, and correlation were used to analyze the data. CFA showed acceptable model fit: an standardized root mean square residual (SRMR) of 0.064, an non-normalized fit index (NNFI) of 0.96, a comparative fit index (CFI) of 0.96, and an root mean square error of approximation (RMSEA) of 0.075. The Cronbach’s alpha values were acceptable and ranging from 0.69 to 0.85. The overall Cronbach’s alpha coefficient was 0.94. The factor loadings for all ethical climate items were between 0.50 and 0.80, which revealed good structure of the Persian version of the HECS. Survey findings showed that the “managers” subscale had the highest score and the subscale of “doctors” had the lowest score. This study shows that the Persian version of the HECS is a valid and reliable instrument for measuring nurses’ perceptions of the ethical climate in hospitals of Iran PMID:25512834
Representation of the West African Monsoon System in the aerosol-climate model ECHAM6-HAM2
NASA Astrophysics Data System (ADS)
Stanelle, Tanja; Lohmann, Ulrike; Bey, Isabelle
2017-04-01
The West African Monsoon (WAM) is a major component of the global monsoon system. The temperature contrast between the Saharan land surface in the North and the sea surface temperature in the South dominates the WAM formation. The West African region receives most of its precipitation during the monsoon season between end of June and September. Therefore the existence of the monsoon is of major social and economic importance. We discuss the ability of the climate model ECHAM6 as well as the coupled aerosol climate model ECHAM6-HAM2 to simulate the major features of the WAM system. The north-south temperature gradient is reproduced by both model versions but all model versions fail in reproducing the precipitation amount south of 10° N. A special focus is on the representation of the nocturnal low level jet (NLLJ) and the corresponding enhancement of low level clouds (LLC) at the Guinea Coast, which are a crucial factor for the regional energy budget. Most global climate models have difficulties to represent these features. The pure climate model ECHAM6 is able to simulate the existence of the NLLJ and LLC, but the model does not represent the pronounced diurnal cycle. Overall, the representation of LLC is worse in the coupled model. We discuss the model behaviors on the basis of outputted temperature and humidity tendencies and try to identify potential processes responsible for the model deficiencies.
NASA Astrophysics Data System (ADS)
Guenet, B.; Moyano, F. E.; Vuichard, N.; Kirk, G. J. D.; Bellamy, P. H.; Zaehle, S.; Ciais, P.
2013-12-01
A widespread decrease of the topsoil carbon content was observed over England and Wales during the period 1978-2003 in the National Soil Inventory (NSI), amounting to a carbon loss of 4.44 Tg yr-1 over 141 550 km2. Subsequent modelling studies have shown that changes in temperature and precipitation could only account for a small part of the observed decrease, and therefore that changes in land use and management and resulting changes in heterotrophic respiration or net primary productivity were the main causes. So far, all the models used to reproduce the NSI data have not accounted for plant-soil interactions and have only been soil carbon models with carbon inputs forced by data. Here, we use three different versions of a process-based coupled soil-vegetation model called ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems), in order to separate the effect of trends in soil carbon input from soil carbon mineralization induced by climate trends over 1978-2003. The first version of the model (ORCHIDEE-AR5), used for IPCC-AR5 CMIP5 Earth System simulations, is based on three soil carbon pools defined with first-order decomposition kinetics, as in the CENTURY model. The second version (ORCHIDEE-AR5-PRIM) built for this study includes a relationship between litter carbon and decomposition rates, to reproduce a priming effect on decomposition. The last version (O-CN) takes into account N-related processes. Soil carbon decomposition in O-CN is based on CENTURY, but adds N limitations on litter decomposition. We performed regional gridded simulations with these three versions of the ORCHIDEE model over England and Wales. None of the three model versions was able to reproduce the observed NSI soil carbon trend. This suggests either that climate change is not the main driver for observed soil carbon losses or that the ORCHIDEE model even with priming or N effects on decomposition lacks the basic mechanisms to explain soil carbon change in response to climate, which would raise a caution flag about the ability of this type of model to project soil carbon changes in response to future warming. A third possible explanation could be that the NSI measurements made on the topsoil are not representative of the total soil carbon losses integrated over the entire soil depth, and thus cannot be compared with the model output.
NASA Astrophysics Data System (ADS)
Guenet, B.; Moyano, F. E.; Vuichard, N.; Kirk, G. J. D.; Bellamy, P. H.; Zaehle, S.; Ciais, P.
2013-07-01
A widespread decrease of the top soil carbon content was observed over England and Wales during the period 1978-2003 in the National Soil Inventory (NSI), amounting to a carbon loss of 4.44 Tg yr-1 over 141 550 km2. Subsequent modelling studies have shown that changes in temperature and precipitation could only account for a small part of the observed decrease, and therefore that changes in land use and management and resulting changes in soil respiration or primary production were the main causes. So far, all the models used to reproduce the NSI data did not account for plant-soil interactions and were only soil carbon models with carbon inputs forced by data. Here, we use three different versions of a process-based coupled soil-vegetation model called ORCHIDEE, in order to separate the effect of trends in soil carbon input, and soil carbon mineralisation induced by climate trends over 1978-2003. The first version of the model (ORCHIDEE-AR5) used for IPCC-AR5 CMIP5 Earth System simulations, is based on three soil carbon pools defined with first order decomposition kinetics, as in the CENTURY model. The second version (ORCHIDEE-AR5-PRIM) built for this study includes a relationship between litter carbon and decomposition rates, to reproduce a priming effect on decomposition. The last version (O-CN) takes into account N-related processes. Soil carbon decomposition in O-CN is based on CENTURY, but adds N limitations on litter decomposition. We performed regional gridded simulations with these three versions of the ORCHIDEE model over England and Wales. None of the three model versions was able to reproduce the observed NSI soil carbon trend. This suggests that either climate change is not the main driver for observed soil carbon losses, or that the ORCHIDEE model even with priming or N-effects on decomposition lacks the basic mechanisms to explain soil carbon change in response to climate, which would raise a caution flag about the ability of this type of model to project soil carbon changes in response to future warming. A third possible explanation could be that the NSI measurements made on the topsoil are not representative of the total soil carbon losses integrated over the entire soil depth, and thus cannot be compared with the model output.
How does the sensitivity of climate affect stratospheric solar radiation management?
NASA Astrophysics Data System (ADS)
Ricke, K.; Rowlands, D. J.; Ingram, W.; Keith, D.; Morgan, M. G.
2011-12-01
If implementation of proposals to engineer the climate through solar radiation management (SRM) ever occurs, it is likely to be contingent upon climate sensitivity. Despite this, no modeling studies have examined how the effectiveness of SRM forcings differs between the typical Atmosphere-Ocean General Circulation Models (AOGCMs) with climate sensitivities close to the Coupled Model Intercomparison Project (CMIP) mean and ones with high climate sensitivities. Here, we use a perturbed physics ensemble modeling experiment to examine variations in the response of climate to SRM under different climate sensitivities. When SRM is used as a substitute for mitigation its ability to maintain the current climate state gets worse with increased climate sensitivity and with increased concentrations of greenhouse gases. However, our results also demonstrate that the potential of SRM to slow climate change, even at the regional level, grows with climate sensitivity. On average, SRM reduces regional rates of temperature change by more than 90 percent and rates of precipitation change by more than 50 percent in these higher sensitivity model configurations. To investigate how SRM might behave in models with high climate sensitivity that are also consistent with recent observed climate change we perform a "perturbed physics" ensemble (PPE) modelling experiment with the climateprediction.net (cpdn) version of the HadCM3L AOGCM. Like other perturbed physics climate modelling experiments, we simulate past and future climate scenarios using a wide range of model parameter combinations that both reproduce past climate within a specified level of accuracy and simulate future climates with a wide range of climate sensitivities. We chose 43 members ("model versions") from a subset of the 1,550 from the British Broadcasting Corporation (BBC) climateprediction.net project that have data that allow restarts. We use our results to explore how much assessments of SRM that use best-estimate models, and so near-median climate sensitivity, may be ignoring important contingencies associated with implementing SRM in reality. A primary motivation for studying SRM via the injection of aerosols in the stratosphere is to evaluate its potential effectiveness as "insurance" in the case of higher-than-expected climate response to global warming. We find that this is precisely when SRM appears to be least effective in returning regional climates to their baseline states and reducing regional rates of precipitation change. On the other hand, given the very high regional temperature anomalies associated with rising greenhouse gas concentrations in high sensitivity models, it is also where SRM is most effective in reducing rates of change relative to a no SRM alternative.
NASA Astrophysics Data System (ADS)
Melton, Joe; Arora, Vivek
2015-04-01
The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the earth system modelling framework of the Canadian Centre for Climate Modelling and Analysis (CCCma). In its current framework, CTEM uses prescribed fractional coverage of plant functional types (PFTs) in each grid cell. In reality, vegetation cover is continually adjusting to changes in climate, atmospheric composition, and anthropogenic forcing, for example, through human-caused fires and CO2 fertilization. These changes in vegetation spatial patterns occur over timescales of years to centuries as tree migration is a slow process and vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM that includes a representation of competition between PFTs through a modified version of the Lotka-Volterra (L-V) predator-prey equations. The simulated areal extents of CTEM's seven non-crop PFTs are compared with available observation-based estimates, and simulations using unmodified L-V equations (similar to other models like TRIFFID), to demonstrate that the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. Differences remain, however, since representing the multitude of plant species with just seven non-crop PFTs only allows the large scale climatic controls on the distributions of PFTs to be captured. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model and the corresponding driving climate or the limited number of PFTs used to model the terrestrial ecosystem processes. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably with each other and observation-based estimates. These results illustrate that the parametrization of competition between PFTs in CTEM behaves in a reasonably realistic manner while the use of unmodified L-V equations results in unrealistic plant distributions.
iTree-Hydro: Snow hydrology update for the urban forest hydrology model
Yang Yang; Theodore A. Endreny; David J. Nowak
2011-01-01
This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest EffectsâHydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...
Climatic Change and the Classroom: A Teaching Aid to Understanding.
ERIC Educational Resources Information Center
Sanders, C. Gerald
Equable climates with mild winters and summers are more likely to maintain snow or ice cover in high latitudes than extreme climates having colder winters and hotter summers. A simplified version of the Milankovitch cycles can be used to develop a model instructors can use in their classes to illustrate the orbital variations producing either…
NASA Technical Reports Server (NTRS)
Suarez, Max J. (Editor); Takacs, Lawrence L.; Molod, Andrea; Wang, Tina
1994-01-01
This technical report documents Version 1 of the Goddard Earth Observing System (GEOS) General Circulation Model (GCM). The GEOS-1 GCM is being used by NASA's Data Assimilation Office (DAO) to produce multiyear data sets for climate research. This report provides a documentation of the model components used in the GEOS-1 GCM, a complete description of model diagnostics available, and a User's Guide to facilitate GEOS-1 GCM experiments.
A prognostic pollen emissions model for climate models (PECM1.0)
NASA Astrophysics Data System (ADS)
Wozniak, Matthew C.; Steiner, Allison L.
2017-11-01
We develop a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1) a taxa-specific land cover database, phenology, and emission potential, and (2) a plant functional type (PFT) land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.
Inequality, climate impacts on the future poor, and carbon prices
Dennig, Francis; Budolfson, Mark B.; Fleurbaey, Marc; Siebert, Asher; Socolow, Robert H.
2015-01-01
Integrated assessment models of climate and the economy provide estimates of the social cost of carbon and inform climate policy. We create a variant of the Regional Integrated model of Climate and the Economy (RICE)—a regionally disaggregated version of the Dynamic Integrated model of Climate and the Economy (DICE)—in which we introduce a more fine-grained representation of economic inequalities within the model’s regions. This allows us to model the common observation that climate change impacts are not evenly distributed within regions and that poorer people are more vulnerable than the rest of the population. Our results suggest that this is important to the social cost of carbon—as significant, potentially, for the optimal carbon price as the debate between Stern and Nordhaus on discounting. PMID:26644560
Earth Futures: a General Education Sustainability Course at the Pennsylvania State University
NASA Astrophysics Data System (ADS)
Bralower, T. J.; Bice, D. M.; Barron, E. J.
2012-12-01
Earth in the Future: Predicting Climate Change and Its Impacts Over the Next Century has been taught at The Pennsylvania State University since 2000. The course is a general education course designed to give a broad survey of the science underlying climate change as well as the impacts on natural and human systems. The course has three major goals: (1) to provide an understanding of climate science and of the possible scenarios of how climate may change in the future; (2) to analyze the linkages between climate and major human and natural systems, including agriculture, water, ocean circulation, and coastal ecosystems, necessary to assess the potential impacts of climate change; and (3) to understand the potential responses to climate change, including both adaptation to, and mitigation of change. The general education course is the entry point for a new BS-degree program, Earth System Science and Policy (ESSP). Initially the course was taught face to face on a yearly basis. Recently we have developed an on-line version of the course, and, in Fall semester, 2012, we are teaching a revised version of the course face-to-face and on-line. Both versions of the course are being assessed using survey instruments developed for InTeGrate courses. The simultaneous instruction provides a unique opportunity to compare the strengths and weaknesses of the two different modes of education. From its beginning, the course has included laboratory exercises designed to enhance the student's understanding of climate science. The revised course includes laboratory exercises in every module, including STELLA-based model experiments. These exercises form an essential part of the on-line version of the course, however, the identical exercises are involved in the face-to-face version. In our presentation, we provide preliminary comparison of the two instructional modes as well as their effectiveness in recruiting students to the ESSP major.
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.
Aerosol-cloud interactions in a multi-scale modeling framework
NASA Astrophysics Data System (ADS)
Lin, G.; Ghan, S. J.
2017-12-01
Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.
The climate4impact platform: Providing, tailoring and facilitating climate model data access
NASA Astrophysics Data System (ADS)
Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael
2017-04-01
One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European contribution to ESGF and contributes to the ESGF open source effort, notably through the development of search, monitoring, quality control, and metadata services. In its second phase, IS-ENES2 supports the implementation of regional climate model results from the international Coordinated Regional Downscaling Experiments (CORDEX). These services were extended within the European FP7 Climate Information Portal for Copernicus (CLIPC) project, and some could be later integrated into the European Copernicus platform.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tribbia, Joseph
NCAR brought the latest version of the Community Earth System Model (version 1, CESM1) into the mix of models in the NMME effort. This new version uses our newest atmospheric model CAM5 and produces a coupled climate and ENSO that are generally as good or better than those of the Community Climate System Model version 4 (CCSM4). Compared to CCSM4, the new coupled model has a superior climate response with respect to low clouds in both the subtropical stratus regimes and the Arctic. However, CESM1 has been run to date using a prognostic aerosol model that more than doubles itsmore » computational cost. We are currently evaluating a version of the new model using prescribed aerosols and expect it will be ready for integrations in summer 2012. Because of this NCAR has not been able to complete the hindcast integrations using the NCAR loosely-coupled ensemble Kalman filter assimilation method nor has it contributed to the current (Stage I) NMME operational utilization. The expectation is that this model will be included in the NMME in late 2012 or early 2013. The initialization method will utilize the Ensemble Kalman Filter Assimilation methods developed at NCAR using the Data Assimilation Research Testbed (DART) in conjunction with Jeff Anderson’s team in CISL. This methodology has been used in our decadal prediction contributions to CMIP5. During the course of this project, NCAR has setup and performed all the needed hindcast and forecast simulations and provide the requested fields to our collaborators. In addition, NCAR researchers have participated fully in research themes (i) and (ii). Specifically, i) we have begun to evaluate and optimize our system in hindcast mode, focusing on the optimal number of ensemble members, methodologies to recalibrate individual dynamical models, and accessing our forecasts across multiple time scales, i.e., beyond two weeks, and ii) we have begun investigation of the role of different ocean initial conditions in seasonal forecasts. The completion of the calibration hindcasts for Seasonal to Interannual (SI) predictions and the maintenance of the data archive associated with the NCAR portion of this effort has been the responsibility of the Project Scientist I (Alicia Karspeck) that was partially supported on this project.« less
Intercomparison of four regional climate models for the German State of Saxonia
NASA Astrophysics Data System (ADS)
Kreienkamp, F.; Spekat, A.; Enke, W.
2009-09-01
Results from four regional climate models which focus on Central Europe are presented: CCLM, the climate version of the German Weather Service's Local Model - REMO, the regional dynamic model from the Max Planck Institute for Meteorology in Hamburg - STAR, the statistical model developed at the PIK Potsdam Institute and WETTREG, the statistic-dynamic model developed by the company CEC Potsdam. For the area of the German State of Saxonia a host of properties and indicators were analyzed aiming to show the models' abilities to reconstruct the current climate and compare climate model scenarios. These include a group of thermal indicators, such as the number of ice, frost, summer and hot days, the number of tropical nights; then there are hydrometeorological indicators such as the exceedance of low and high precipitation thresholds; humidity, cloudiness and wind indicators complement the array. A selection of them showing similarities and differences of the models investigated will be presented.
Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; ...
2016-09-26
Changes in the character of rainfall are assessed using a holistic set of statistics based on rainfall frequency and amount distributions in climate change experiments with three conventional and superparameterized versions of the Community Atmosphere Model (CAM and SPCAM). Previous work has shown that high-order statistics of present-day rainfall intensity are significantly improved with superparameterization, especially in regions of tropical convection. Globally, the two modeling approaches project a similar future increase in mean rainfall, especially across the Inter-Tropical Convergence Zone (ITCZ) and at high latitudes, but over land, SPCAM predicts a smaller mean change than CAM. Changes in high-order statisticsmore » are similar at high latitudes in the two models but diverge at lower latitudes. In the tropics, SPCAM projects a large intensification of moderate and extreme rain rates in regions of organized convection associated with the Madden Julian Oscillation, ITCZ, monsoons, and tropical waves. In contrast, this signal is missing in all versions of CAM, which are found to be prone to predicting increases in the amount but not intensity of moderate rates. Predictions from SPCAM exhibit a scale-insensitive behavior with little dependence on horizontal resolution for extreme rates, while lower resolution (~2°) versions of CAM are not able to capture the response simulated with higher resolution (~1°). Furthermore, moderate rain rates analyzed by the “amount mode” and “amount median” are found to be especially telling as a diagnostic for evaluating climate model performance and tracing future changes in rainfall statistics to tropical wave modes in SPCAM.« less
Huang, Francis L; Cornell, Dewey G; Konold, Timothy; Meyer, Joseph P; Lacey, Anna; Nekvasil, Erin K; Heilbrun, Anna; Shukla, Kathan D
2015-12-01
School climate is well recognized as an important influence on student behavior and adjustment to school, but there is a need for theory-guided measures that make use of teacher perspectives. Authoritative school climate theory hypothesizes that a positive school climate is characterized by high levels of disciplinary structure and student support. A teacher version of the Authoritative School Climate Survey (ASCS) was administered to a statewide sample of 9099 7th- and 8th-grade teachers from 366 schools. The study used exploratory and multilevel confirmatory factor analyses (MCFA) that accounted for the nested data structure and allowed for the modeling of the factor structures at 2 levels. Multilevel confirmatory factor analyses conducted on both an exploratory (N = 4422) and a confirmatory sample (N = 4677) showed good support for the factor structures investigated. Factor correlations at 2 levels indicated that schools with greater levels of disciplinary structure and student support had higher student engagement, less teasing and bullying, and lower student aggression toward teachers. The teacher version of the ASCS can be used to assess 2 key domains of school climate and associated measures of student engagement and aggression toward peers and teachers. © 2015, American School Health Association.
Reference aquaplanet climate in the Community Atmosphere Model, Version 5
Medeiros, Brian; Williamson, David L.; Olson, Jerry G.
2016-03-18
In this study, fundamental characteristics of the aquaplanet climate simulated by the Community Atmosphere Model, Version 5.3 (CAM5.3) are presented. The assumptions and simplifications of the configuration are described. A 16 year long, perpetual equinox integration with prescribed SST using the model’s standard 18 grid spacing is presented as a reference simulation. Statistical analysis is presented that shows similar aquaplanet configurations can be run for about 2 years to obtain robust climatological structures, including global and zonal means, eddy statistics, and precipitation distributions. Such a simulation can be compared to the reference simulation to discern differences in the climate, includingmore » an assessment of confidence in the differences. To aid such comparisons, the reference simulation has been made available via earthsystemgrid.org. Examples are shown comparing the reference simulation with simulations from the CAM5 series that make different microphysical assumptions and use a different dynamical core.« less
NASA Technical Reports Server (NTRS)
Youngblut, C.
1984-01-01
Orography and geographically fixed heat sources which force a zonally asymmetric motion field are examined. An extensive space-time spectral analysis of the GLAS climate model (D130) response and observations are compared. An updated version of the model (D150) showed a remarkable improvement in the simulation of the standing waves. The main differences in the model code are an improved boundary layer flux computation and a more realistic specification of the global boundary conditions.
Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)
NASA Astrophysics Data System (ADS)
Frigola, Amanda; Prange, Matthias; Schulz, Michael
2018-04-01
The Middle Miocene Climate Transition was characterized by major Antarctic ice sheet expansion and global cooling during the interval ˜ 15-13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry, and vegetation. Additionally, Antarctic ice volume and geometry, sea level, and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The MMCO and MMG boundary conditions have been successfully applied to the Community Climate System Model version 3 (CCSM3) to provide evidence of their suitability for global climate modeling. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.
Ching-Teng Lee; Ming-Chin Wu; Shyh-Chin Chen
2005-01-01
The National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) version 97 was used to investigate the regional summertime climate over Taiwan and adjacent areas for June-July-August of 1990 through 2000. The simulated sea-level-pressure and wind fields of RSM1 with 50-km grid space are similar to the reanalysis, but the strength of the...
NASA Astrophysics Data System (ADS)
Peña, M.; Saha, S.; Wu, X.; Wang, J.; Tripp, P.; Moorthi, S.; Bhattacharjee, P.
2016-12-01
The next version of the operational Climate Forecast System (version 3, CFSv3) will be a fully coupled six-components system with diverse applications to earth system modeling, including weather and climate predictions. This system will couple the earth's atmosphere, land, ocean, sea-ice, waves and aerosols for both data assimilation and modeling. It will also use the NOAA Environmental Modeling System (NEMS) software super structure to couple these components. The CFSv3 is part of the next Unified Global Coupled System (UGCS), which will unify the global prediction systems that are now operational at NCEP. The UGCS is being developed through the efforts of dedicated research and engineering teams and through coordination across many CPO/MAPP and NGGPS groups. During this development phase, the UGCS is being tested for seasonal purposes and undergoes frequent revisions. Each new revision is evaluated to quickly discover, isolate and solve problems that negatively impact its performance. In the UGCS-seasonal model, components (e.g., ocean, sea-ice, atmosphere, etc.) are coupled through a NEMS-based "mediator". In this numerical infrastructure, model diagnostics and forecast validation are carried out, both component by component, and as a whole. The next stage, model optimization, will require enhanced performance diagnostics tools to help prioritize areas of numerical improvements. After the technical development of the UGCS-seasonal is completed, it will become the first realization of the CFSv3. All future development of this system will be carried out by the climate team at NCEP, in scientific collaboration with the groups that developed the individual components, as well as the climate community. A unique challenge to evaluate this unified weather-climate system is the large number of variables, which evolve over a wide range of temporal and spatial scales. A small set of performance measures and scorecard displays are been created, and collaboration and software contributions from research and operational centers are being incorporated. A status of the CFSv3/UGCS-seasonal development and examples of its performance and measuring tools will be presented.
Kutzbach, J.-E.; Bartlein, P.J.; Foley, J.A.; Harrison, S.P.; Hosteller, S.W.; Liu, Z.; Prentice, I.C.; Webb, T.
1996-01-01
Previous climate model simulations have shown that the configuration of the Earth's orbit during the early to mid-Holocene (approximately 10-5 kyr) can account for the generally warmer-than-present conditions experienced by the high latitudes of the northern hemisphere. New simulations for 6 kyr with two atmospheric/mixed-layer ocean models (Community Climate Model, version 1, CCM1, and Global ENvironmental and Ecological Simulation of Interactive Systems, version 2, GENESIS 2) are presented here and compared with results from two previous simulations with GENESIS 1 that were obtained with and without the albedo feedback due to climate-induced poleward expansion of the boreal forest. The climate model results are summarized in the form of potential vegetation maps obtained with the global BIOME model, which facilitates visual comparisons both among models and with pollen and plant macrofossil data recording shifts of the forest-tundra boundary. A preliminary synthesis shows that the forest limit was shifted 100-200 km north in most sectors. Both CCM1 and GENESIS 2 produced a shift of this magnitude. GENESIS 1 however produced too small a shift, except when the boreal forest albedo feedback was included. The feedback in this case was estimated to have amplified forest expansion by approximately 50%. The forest limit changes also show meridional patterns (greatest expansion in central Siberia and little or none in Alaska and Labrador) which have yet to be reproduced by models. Further progress in understanding of the processes involved in the response of climate and vegetation to orbital forcing will require both the deployment of coupled atmosphere-biosphere-ocean models and the development of more comprehensive observational data sets.
NASA Technical Reports Server (NTRS)
Rosenzweig, Cynthia E.; Jones, James W.; Hatfield, Jerry; Antle, John; Ruane, Alex; Boote, Ken; Thorburn, Peter; Valdivia, Roberto; Porter, Cheryl; Janssen, Sander;
2015-01-01
The purpose of this handbook is to describe recommended methods for a trans-disciplinary, systems-based approach for regional-scale (local to national scale) integrated assessment of agricultural systems under future climate, bio-physical and socio-economic conditions. An earlier version of this Handbook was developed and used by several AgMIP Regional Research Teams (RRTs) in Sub-Saharan Africa (SSA) and South Asia (SA)(AgMIP handbook version 4.2, www.agmip.org/regional-integrated-assessments-handbook/). In contrast to the earlier version, which was written specifically to guide a consistent set of integrated assessments across SSA and SA, this version is intended to be more generic such that the methods can be applied to any region globally. These assessments are the regional manifestation of research activities described by AgMIP in its online protocols document (available at www.agmip.org). AgMIP Protocols were created to guide climate, crop modeling, economics, and information technology components of its projects.
Climate Change Impacts at Department of Defense Installations
2017-06-16
locations. The ease of use of this method and its flexibility have led to a wide variety of applications for assessing impacts of climate change 4...versions of these statistical methods to provide the basis for regional climate assessments for various states, regions, and government agencies...averaging (REA) method proposed by Giorgi and Mearns (2002). This method assigns reliability classifications for the multi-model ensemble simulation by
Buttenfield, B.P.; Stanislawski, L.V.; Brewer, C.A.
2011-01-01
This paper reports on generalization and data modeling to create reduced scale versions of the National Hydrographic Dataset (NHD) for dissemination through The National Map, the primary data delivery portal for USGS. Our approach distinguishes local differences in physiographic factors, to demonstrate that knowledge about varying terrain (mountainous, hilly or flat) and varying climate (dry or humid) can support decisions about algorithms, parameters, and processing sequences to create generalized, smaller scale data versions which preserve distinct hydrographic patterns in these regions. We work with multiple subbasins of the NHD that provide a range of terrain and climate characteristics. Specifically tailored generalization sequences are used to create simplified versions of the high resolution data, which was compiled for 1:24,000 scale mapping. Results are evaluated cartographically and metrically against a medium resolution benchmark version compiled for 1:100,000, developing coefficients of linear and areal correspondence.
Psychometric assessment of the Spiritual Climate Scale Arabic version for nurses in Saudi Arabia.
Cruz, Jonas Preposi; Albaqawi, Hamdan Mohammad; Alharbi, Sami Melbes; Alicante, Jerico G; Vitorino, Luciano M; Abunab, Hamzeh Y
2017-12-07
To assess the psychometric properties of the Spiritual Climate Scale Arabic version for Saudi nurses. Evidence showed that a high level of spiritual climate in the workplace is associated with increased productivity and performance, enhanced emotional intelligence, organisational commitment and job satisfaction among nurses. A convenient sample of 165 Saudi nurses was surveyed in this descriptive, cross-sectional study. Cronbach's α and intraclass correlation coefficient of the 2 week test-retest scores were computed to establish reliability. Exploratory factor analysis was performed to support the validity of the Spiritual Climate Scale Arabic version. The Spiritual Climate Scale Arabic version manifested excellent content validity. Exploratory factor analysis supported a single factor with an explained variance of 73.2%. The Cronbach's α values of the scale ranged from .79 to .88, while the intraclass correlation coefficient value was .90. The perceived spiritual climate was associated with the respondents' hospital, gender, age and years of experience. Findings of this study support the sound psychometric properties of the Spiritual Climate Scale Arabic version. The Spiritual Climate Scale Arabic version can be used by nurse managers to assess the nurses' perception of the spiritual climate in any clinical area. This process can lead to spiritually centred interventions, thereby ensuring a clinical climate that accepts and respects different spiritual beliefs and practices. © 2017 John Wiley & Sons Ltd.
Impact of Amazon deforestation on climate simulations using the NCAR CCM2/BATS model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hahmann, A.N.; Dickinson, R.E.
Model validation and results are briefly presented for a simulation of deforestation of the Amazon rainforest. This initial study is made using assumptions regarding deforestation similar to those in earlier studies with several versions of the NCAR Community Climate Model (CCM) couples to the Biosphere-Atmosphere Transfer Scheme (BATS). The model used is a revised version of the NCAR CCM Version 2 coupled to BATS Version 1e. This paper discusses the portion of validation dealing with the distribution of precipitation; the simulation displays very good agreement with observed rainfall rates for the austral summer. Preliminary results from an 8-year simulation ofmore » deforestation are similar to that of previous studies. Annual precipitation and evaporation are reduced, while surface air temperatures show a slight increase. A substantial bimodal pattern appears in the results, with the Amazon decrease of precipitation and temperature increase accompanied by changes in the opposite sign to the southeast of the Amazon. Similar patterns have occurred in other studies, but not always in exactly the same locations. Evidently, how much of the region of rainfall increase occurs in the deforested area over the Amazon strongly affects the inferred statistics. It is likely that this pattern depends on the model control climatology and possibly other features. 16 refs., 2 figs., 2 tabs.« less
NASA Astrophysics Data System (ADS)
Zarzycki, C. M.; Gettelman, A.; Callaghan, P.
2017-12-01
Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.
NASA Astrophysics Data System (ADS)
Julianto, E. A.; Suntoro, W. A.; Dewi, W. S.; Partoyo
2018-03-01
Climate change has been reported to exacerbate land resources degradation including soil fertility decline. The appropriate validity use on soil fertility evaluation could reduce the risk of climate change effect on plant cultivation. This study aims to assess the validity of a Soil Fertility Evaluation Model using a graphical approach. The models evaluated were the Indonesian Soil Research Center (PPT) version model, the FAO Unesco version model, and the Kyuma version model. Each model was then correlated with rice production (dry grain weight/GKP). The goodness of fit of each model can be tested to evaluate the quality and validity of a model, as well as the regression coefficient (R2). This research used the Eviews 9 programme by a graphical approach. The results obtained three curves, namely actual, fitted, and residual curves. If the actual and fitted curves are widely apart or irregular, this means that the quality of the model is not good, or there are many other factors that are still not included in the model (large residual) and conversely. Indeed, if the actual and fitted curves show exactly the same shape, it means that all factors have already been included in the model. Modification of the standard soil fertility evaluation models can improve the quality and validity of a model.
Simulation of the present-day climate with the climate model INMCM5
NASA Astrophysics Data System (ADS)
Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykossov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Iakovlev, N. G.
2017-12-01
In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions. Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979-2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings.
Impacts of Residential Biofuel Emissions on Air Quality and Climate
NASA Astrophysics Data System (ADS)
Huang, Y.; Unger, N.; Harper, K.; Storelvmo, T.
2016-12-01
The residential biofuel sector is defined as fuelwood, agricultural residues and dung used for household cooking and heating. Aerosol emissions from this human activity play an important role affecting local, regional and global air quality, climate and public health. However, there are only few studies available that evaluate the net impacts and large uncertainties persist. Here we use the Community Atmosphere Model version 5.3 (CAM v5.3) within the Community Earth System Model version 1.2.2, to quantify the impacts of cook-stove biofuel emissions on air quality and climate. The model incorporates a novel advanced treatment of black carbon (BC) effects on mixed-phase/ice clouds. We update the global anthropogenic emission inventory in CAM v5.3 to a state-of-the-art emission inventory from the Greenhouse Gas-Air Pollution Interactions and Synergies integrated assessment model. Global in-situ and aircraft campaign observations for BC and organic carbon are used to evaluate and validate the model performance. Sensitivity simulations are employed to assess the impacts of residential biofuel emissions on regional and global direct and indirect radiative forcings in the contemporary world. We focus the analyses on several key regions including India, China and Sub-Saharan Africa.
Climate-methane cycle feedback in global climate model model simulations forced by RCP scenarios
NASA Astrophysics Data System (ADS)
Eliseev, Alexey V.; Denisov, Sergey N.; Arzhanov, Maxim M.; Mokhov, Igor I.
2013-04-01
Methane cycle module of the global climate model of intermediate complexity developed at the A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM) is extended by coupling with a detailed module for thermal and hydrological processes in soil (Deep Soil Simulator, (Arzhanov et al., 2008)). This is an important improvement with respect with the earlier IAP RAS CM version (Eliseev et al., 2008) which has employed prescribed soil hydrology to simulate CH4 emissions from soil. Geographical distribution of water inundated soil in the model was also improved by replacing the older Olson's ecosystem data base by the data based on the SCIAMACHY retrievals (Bergamaschi et al., 2007). New version of the IAP RAS CM module for methane emissions from soil is validated by using the simulation protocol adopted in the WETCHIMP (Wetland and Wetland CH4 Inter-comparison of Models Project). In addition, atmospheric part of the IAP RAS CM methane cycle is extended by temperature dependence of the methane life-time in the atmosphere in order to mimic the respective dependence of the atmospheric methane chemistry (Denisov et al., 2012). The IAP RAS CM simulations are performed for the 18th-21st centuries according with the CMIP5 protocol taking into account natural and anthropogenic forcings. The new IAP RAS CM version realistically reproduces pre-industrial and present-day characteristics of the global methane cycle including CH4 concentration qCH4 in the atmosphere and CH4 emissions from soil. The latter amounts 150 - 160 TgCH4-yr for the late 20th century and increases to 170 - 230 TgCH4-yr in the late 21st century. Atmospheric methane concentration equals 3900 ppbv under the most aggressive anthropogenic scenario RCP 8.5 and 1850 - 1980 ppbv under more moderate scenarios RCP 6.0 and RCP 4.5. Under the least aggressive scenario RCP 2.6 qCH4 reaches maximum 1730 ppbv in 2020s and declines afterwards. Climate change impact on the methane emissions from soil enhances build up of the methane stock in the atmosphere by 10 - 25% depending on anthropogenic scenario and time instant. In turn, decrease of methane life-time in the atmosphere suppresses this build up by 5 - 40%. The net effect is uncertain but small in terms of resulting additional greenhouse radiative forcing. This smallness is reflected in small additional (relative to the model version with both methane emissions from soil and methane life-time in the atmosphere fixed at their preindustrial values) near-surface warming which globally is not larger than 1 K, i.e, ˜ 4% of warming exhibited by the model version neglecting climate-methane cycle interaction. References [1] M.M. Arzhanov, P.F. Demchenko, A.V. Eliseev, and I.I. Mokhov. Simulation of characteristics of thermal and hydrologic soil regimes in equilibrium numerical experiments with a climate model of intermediate complexity. Izvestiya, Atmos. Ocean. Phys., 44(5):279-287, 2008. doi: 10.1134/S0001433808050022. [2] P. Bergamaschi, C. Frankenberg, J.F. Meirink, M. Krol, F. Dentener, T. Wagner, U. Platt, J.O. Kaplan, S. Körner, M. Heimann, E.J. Dlugokencky, and A. Goede. Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: 2. Evaluation based on inverse model simulations. J. Geophys. Res., 112(D2):D02304, 2007. doi: 10.1029/2006JD007268. [3] S.N. Denisov, A.V. Eliseev, and I.I. Mokhov. Climate change in the IAP RAS global model with interactive methane cycle under RCP anthropogenic scenarios. Rus. Meteorol. Hydrol., 2012. [submitted]. [4] A.V. Eliseev, I.I. Mokhov, M.M. Arzhanov, P.F. Demchenko, and S.N. Denisov. Interaction of the methane cycle and processes in wetland ecosystems in a climate model of intermediate complexity. Izvestiya, Atmos. Ocean. Phys., 44(2):139-152, 2008. doi: 10.1134/S0001433808020011.
Impact of Physics Parameterization Ordering in a Global Atmosphere Model
Donahue, Aaron S.; Caldwell, Peter M.
2018-02-02
Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less
Impact of Physics Parameterization Ordering in a Global Atmosphere Model
NASA Astrophysics Data System (ADS)
Donahue, Aaron S.; Caldwell, Peter M.
2018-02-01
Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.
Impact of Physics Parameterization Ordering in a Global Atmosphere Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Donahue, Aaron S.; Caldwell, Peter M.
Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less
NASA Astrophysics Data System (ADS)
Astitha, M.; Lelieveld, J.; Abdel Kader, M.; Pozzer, A.; de Meij, A.
2012-11-01
Airborne desert dust influences radiative transfer, atmospheric chemistry and dynamics, as well as nutrient transport and deposition. It directly and indirectly affects climate on regional and global scales. Two versions of a parameterization scheme to compute desert dust emissions are incorporated into the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry). One uses a globally uniform soil particle size distribution, whereas the other explicitly accounts for different soil textures worldwide. We have tested these two versions and investigated the sensitivity to input parameters, using remote sensing data from the Aerosol Robotic Network (AERONET) and dust concentrations and deposition measurements from the AeroCom dust benchmark database (and others). The two versions are shown to produce similar atmospheric dust loads in the N-African region, while they deviate in the Asian, Middle Eastern and S-American regions. The dust outflow from Africa over the Atlantic Ocean is accurately simulated by both schemes, in magnitude, location and seasonality. Approximately 70% of the modelled annual deposition data and 70-75% of the modelled monthly aerosol optical depth (AOD) in the Atlantic Ocean stations lay in the range 0.5 to 2 times the observations for all simulations. The two versions have similar performance, even though the total annual source differs by ~50%, which underscores the importance of transport and deposition processes (being the same for both versions). Even though the explicit soil particle size distribution is considered more realistic, the simpler scheme appears to perform better in several locations. This paper discusses the differences between the two versions of the dust emission scheme, focusing on their limitations and strengths in describing the global dust cycle and suggests possible future improvements.
NASA Astrophysics Data System (ADS)
Hardiman, Steven C.; Butchart, Neal; O'Connor, Fiona M.; Rumbold, Steven T.
2017-03-01
Free-running and nudged versions of a Met Office chemistry-climate model are evaluated and used to investigate the impact of dynamics versus transport and chemistry within the model on the simulated evolution of stratospheric ozone. Metrics of the dynamical processes relevant for simulating stratospheric ozone are calculated, and the free-running model is found to outperform the previous model version in 10 of the 14 metrics. In particular, large biases in stratospheric transport and tropical tropopause temperature, which existed in the previous model version, are substantially reduced, making the current model more suitable for the simulation of stratospheric ozone. The spatial structure of the ozone hole, the area of polar stratospheric clouds, and the increased ozone concentrations in the Northern Hemisphere winter stratosphere following sudden stratospheric warmings, were all found to be sensitive to the accuracy of the dynamics and were better simulated in the nudged model than in the free-running model. Whilst nudging can, in general, provide a useful tool for removing the influence of dynamical biases from the evolution of chemical fields, this study shows that issues can remain in the climatology of nudged models. Significant biases in stratospheric vertical velocities, age of air, water vapour, and total column ozone still exist in the Met Office nudged model. Further, these can lead to biases in the downward flux of ozone into the troposphere.
NASA Astrophysics Data System (ADS)
Liu, X.; Ma, P.-L.; Wang, H.; Tilmes, S.; Singh, B.; Easter, R. C.; Ghan, S. J.; Rasch, P. J.
2016-02-01
Atmospheric carbonaceous aerosols play an important role in the climate system by influencing the Earth's radiation budgets and modifying the cloud properties. Despite the importance, their representations in large-scale atmospheric models are still crude, which can influence model simulated burden, lifetime, physical, chemical and optical properties, and the climate forcing of carbonaceous aerosols. In this study, we improve the current three-mode version of the Modal Aerosol Module (MAM3) in the Community Atmosphere Model version 5 (CAM5) by introducing an additional primary carbon mode to explicitly account for the microphysical ageing of primary carbonaceous aerosols in the atmosphere. Compared to MAM3, the four-mode version of MAM (MAM4) significantly increases the column burdens of primary particulate organic matter (POM) and black carbon (BC) by up to 40 % in many remote regions, where in-cloud scavenging plays an important role in determining the aerosol concentrations. Differences in the column burdens for other types of aerosol (e.g., sulfate, secondary organic aerosols, mineral dust, sea salt) are less than 1 %. Evaluating the MAM4 simulation against in situ surface and aircraft observations, we find that MAM4 significantly improves the simulation of seasonal variation of near-surface BC concentrations in the polar regions, by increasing the BC concentrations in all seasons and particularly in cold seasons. However, it exacerbates the overestimation of modeled BC concentrations in the upper troposphere in the Pacific regions. The comparisons suggest that, to address the remaining model POM and BC biases, future improvements are required related to (1) in-cloud scavenging and vertical transport in convective clouds and (2) emissions of anthropogenic and biomass burning aerosols.
Liu, X.; Ma, P. -L.; Wang, H.; ...
2016-02-08
Atmospheric carbonaceous aerosols play an important role in the climate system by influencing the Earth's radiation budgets and modifying the cloud properties. Despite the importance, their representations in large-scale atmospheric models are still crude, which can influence model simulated burden, lifetime, physical, chemical and optical properties, and the climate forcing of carbonaceous aerosols. In this study, we improve the current three-mode version of the Modal Aerosol Module (MAM3) in the Community Atmosphere Model version 5 (CAM5) by introducing an additional primary carbon mode to explicitly account for the microphysical ageing of primary carbonaceous aerosols in the atmosphere. Compared to MAM3,more » the four-mode version of MAM (MAM4) significantly increases the column burdens of primary particulate organic matter (POM) and black carbon (BC) by up to 40 % in many remote regions, where in-cloud scavenging plays an important role in determining the aerosol concentrations. Differences in the column burdens for other types of aerosol (e.g., sulfate, secondary organic aerosols, mineral dust, sea salt) are less than 1 %. Evaluating the MAM4 simulation against in situ surface and aircraft observations, we find that MAM4 significantly improves the simulation of seasonal variation of near-surface BC concentrations in the polar regions, by increasing the BC concentrations in all seasons and particularly in cold seasons. However, it exacerbates the overestimation of modeled BC concentrations in the upper troposphere in the Pacific regions. As a result, the comparisons suggest that, to address the remaining model POM and BC biases, future improvements are required related to (1) in-cloud scavenging and vertical transport in convective clouds and (2) emissions of anthropogenic and biomass burning aerosols.« less
NASA Astrophysics Data System (ADS)
Goswami, B. B.; Khouider, B.; Krishna, R. P. M.; Mukhopadhyay, P.; Majda, A.
2017-12-01
A stochastic multicloud (SMCM) cumulus parameterization is implemented in the National Centres for Environmental Predictions (NCEP) Climate Forecast System version 2 (CFSv2) model, named as the CFSsmcm model. We present here results from a systematic attempt to understand the CFSsmcm model's sensitivity to the SMCM parameters. To asses the model-sentivity to the different SMCM parameters, we have analized a set of 14 5-year long climate simulations produced by the CFSsmcm model. The model is found to be resilient to minor changes in the parameter values. The middle tropospheric dryness (MTD) and the stratiform cloud decay timescale are found to be most crucial parameters in the SMCM formulation in the CFSsmcm model.
NASA Technical Reports Server (NTRS)
Regonda, Satish K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Rodell, Matthew
2016-01-01
Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.
NASA Astrophysics Data System (ADS)
Liu, Bo; Zhao, Guijie; Huang, Gang; Wang, Pengfei; Yan, Bangliang
2017-08-01
The authors present results for El Niño-Southern Oscillation (ENSO) and East Asian-western North Pacific climate variability simulated in a new version high-resolution coupled model (ICM.V2) developed at the Center for Monsoon System Research of the Institute of Atmospheric Physics (CMSR, IAP), Chinese Academy of Sciences. The analyses are based on the last 100-year output of a 1000-year simulation. Results are compared to an earlier version of the same coupled model (ICM.V1), reanalysis, and observations. The two versions of ICM have similar physics but different atmospheric resolution. The simulated climatological mean states show marked improvement over many regions, especially the tropics in ICM.V2 compared to those in ICM.V1. The common bias in the cold tongue has reduced, and the warm biases along the ocean boundaries have improved as well. With improved simulation of ENSO, including its period and strength, the ENSO-related western North Pacific summer climate variability becomes more realistic compared to the observations. The simulated East Asian summer monsoon anomalies in the El Niño decaying summer are substantially more realistic in ICM.V2, which might be related to a better simulation of the Indo-Pacific Ocean capacitor (IPOC) effect and Pacific decadal oscillation (PDO).
Coupled model simulations of climate changes in the 20th century and beyond
NASA Astrophysics Data System (ADS)
Yu, Yongqiang; Zhi, Hai; Wang, Bin; Wan, Hui; Li, Chao; Liu, Hailong; Li, Wei; Zheng, Weipeng; Zhou, Tianjun
2008-07-01
Several scenario experiments of the IPCC 4th Assessment Report (AR4) are performed by version g1.0 of a Flexible coupled Ocean-Atmosphere-Land System Model (FGOALS) developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), including the “Climate of the 20th century experiment”, “CO2 1% increase per year to doubling experiment” and two separate IPCC greenhouse gases emission scenarios A1B and B1 experiments. To distinguish between the different impacts of natural variations and human activities on the climate change, three-member ensemble runs are performed for each scenario experiment. The coupled model simulations show: (1) from 1900 to 2000, the global mean temperature increases about 0.5°C and the major increase occurs during the later half of the 20th century, which is in consistent with the observations that highlights the coupled model’s ability to reproduce the climate changes since the industrial revolution; (2) the global mean surface air temperature increases about 1.6°C in the CO2 doubling experiment and 1.5°C and 2.4°C in the A1B and B1 scenarios, respectively. The global warming is indicated by not only the changes of the surface temperature and precipitation but also the temperature increase in the deep ocean. The thermal expansion of the sea water would induce the rise of the global mean sea level. Both the control run and the 20th century climate change run are carried out again with version g1.1 of FGOALS, in which the cold biases in the high latitudes were removed. They are then compared with those from version g1.0 of FGOALS in order to distinguish the effect of the model biases on the simulation of global warming.
A Decade-long Continental-Scale Convection-Resolving Climate Simulation on GPUs
NASA Astrophysics Data System (ADS)
Leutwyler, David; Fuhrer, Oliver; Lapillonne, Xavier; Lüthi, Daniel; Schär, Christoph
2016-04-01
The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. Using horizontal grid spacings of O(1km), they allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer-designs that involve conventional multicore CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation using the GPU-enabled COSMO version. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss the performance of the convection-resolving modeling approach on the European scale. Specifically we focus on the annual cycle of convection in Europe, on the organization of convective clouds and on the verification of hourly rainfall with various high resolution datasets.
A Decade-Long European-Scale Convection-Resolving Climate Simulation on GPUs
NASA Astrophysics Data System (ADS)
Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.
2016-12-01
Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer designs that involve conventional multi-core CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation over Europe using the GPU-enabled COSMO version on a computational domain with 1536x1536x60 gridpoints. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss some of the advantages and prospects from using GPUs, and focus on the performance of the convection-resolving modeling approach on the European scale. Specifically we investigate the organization of convective clouds and on validate hourly rainfall distributions with various high-resolution data sets.
Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations.
Braconnot, Pascale; Kageyama, Masa
2015-11-13
Simulations of the climates of the Last Glacial Maximum (LGM), 21 000 years ago, and of the Mid-Holocene (MH), 6000 years ago, allow an analysis of climate feedbacks in climate states that are radically different from today. The analyses of cloud and surface albedo feedbacks show that the shortwave cloud feedback is a major driver of differences between model results. Similar behaviours appear when comparing the LGM and MH simulated changes, highlighting the fingerprint of model physics. Even though the different feedbacks show similarities between the different climate periods, the fact that their relative strength differs from one climate to the other prevents a direct comparison of past and future climate sensitivity. The land-surface feedback also shows large disparities among models even though they all produce positive sea-ice and snow feedbacks. Models have very different sensitivities when considering the vegetation feedback. This feedback has a regional pattern that differs significantly between models and depends on their level of complexity and model biases. Analyses of the MH climate in two versions of the IPSL model provide further indication on the possibilities to assess the role of model biases and model physics on simulated climate changes using past climates for which observations can be used to assess the model results. © 2015 The Author(s).
NASA Technical Reports Server (NTRS)
Suarez, Max J. (Editor); daSilva, Arlindo; Dee, Dick; Bloom, Stephen; Bosilovich, Michael; Pawson, Steven; Schubert, Siegfried; Wu, Man-Li; Sienkiewicz, Meta; Stajner, Ivanka
2005-01-01
This document describes the structure and validation of a frozen version of the Goddard Earth Observing System Data Assimilation System (GEOS DAS): GEOS-4.0.3. Significant features of GEOS-4 include: version 3 of the Community Climate Model (CCM3) with the addition of a finite volume dynamical core; version two of the Community Land Model (CLM2); the Physical-space Statistical Analysis System (PSAS); and an interactive retrieval system (iRET) for assimilating TOVS radiance data. Upon completion of the GEOS-4 validation in December 2003, GEOS-4 became operational on 15 January 2004. Products from GEOS-4 have been used in supporting field campaigns and for reprocessing several years of data for CERES.
Spatial and Temporal Variation in the Effects of Climatic Variables on Dugong Calf Production.
Fuentes, Mariana M P B; Delean, Steven; Grayson, Jillian; Lavender, Sally; Logan, Murray; Marsh, Helene
2016-01-01
Knowledge of the relationships between environmental forcing and demographic parameters is important for predicting responses from climatic changes and to manage populations effectively. We explore the relationships between the proportion of sea cows (Dugong dugon) classified as calves and four climatic drivers (rainfall anomaly, Southern Oscillation El Niño Index [SOI], NINO 3.4 sea surface temperature index, and number of tropical cyclones) at a range of spatially distinct locations in Queensland, Australia, a region with relatively high dugong density. Dugong and calf data were obtained from standardized aerial surveys conducted along the study region. A range of lagged versions of each of the focal climatic drivers (1 to 4 years) were included in a global model containing the proportion of calves in each population crossed with each of the lagged versions of the climatic drivers to explore relationships. The relative influence of each predictor was estimated via Gibbs variable selection. The relationships between the proportion of dependent calves and the climatic drivers varied spatially and temporally, with climatic drivers influencing calf counts at sub-regional scales. Thus we recommend that the assessment of and management response to indirect climatic threats on dugongs should also occur at sub-regional scales.
W. Devine; C. Aubry; J. Miller; K. Potter; A. Bower
2012-01-01
This guide provides a step-by-step description of the methodology used to apply the Forest Tree Genetic Risk Assessment System (ForGRAS; Potter and Crane 2010) to the tree species of the Pacific Northwest in a recent climate change vulnerability assessment (Devine et al. 2012). We describe our modified version of the ForGRAS model, and we review the modelâs basic...
NASA Astrophysics Data System (ADS)
Harper, A.; Denning, A. S.; Baker, I.; Randall, D.; Dazlich, D.
2008-12-01
Several climate models have predicted an increase in long-term droughts in tropical South America due to increased greenhouse gases in the atmosphere. Although the Amazon rainforest is resilient to seasonal drought, multi-year droughts pose a definite problem for the ecosystem's health. Furthermore, drought- stressed vegetation participates in feedbacks with the atmosphere that can exacerbate drought. Namely, reduced evapotranspiration further dries out the atmosphere and affects the regional climate. Trees in the rainforest survive seasonal drought by using deep roots to access adequate stores of soil moisture. We investigate the climatic impacts of deep roots and soil moisture by coupling the Simple Biosphere (SiB3) model to Colorado State University's general circulation model (BUGS5). We compare two versions of SiB3 in the GCM during years with anomalously low rainfall. The first has strong vegetative stress due to soil moisture limitations. The second experiences less stress and has more realistic representations of surface biophysics. In the model, basin-wide reductions in soil moisture stress result in increased evapotranspiration, precipitation, and moisture recycling in the Amazon basin. In the savannah region of southeastern Brazil, the unstressed version of SiB3 produces decreased precipitation and weaker moisture flux, which is more in-line with observations. The improved simulation of precipitation and evaporation also produces a more realistic Bolivian high and Nordeste low. These changes highlight the importance of subsurface biophysics for the Amazonian climate. The presence of deep roots and soil moisture will become even more important if climate change brings more frequent droughts to this region in the future.
The NASA Modern Era Reanalysis for Research and Applications, Version-2 (MERRA-2)
NASA Astrophysics Data System (ADS)
Gelaro, R.; McCarty, W.; Molod, A.; Suarez, M.; Takacs, L.; Todling, R.
2014-12-01
The NASA Modern Era Reanalysis for Research Applications Version-2 (MERRA-2) is a reanalysis for the satellite era using an updated version of the Goddard Earth Observing System Data Assimilation System Version-5 (GEOS-5) produced by the Global Modeling and Assimilation Office (GMAO). MERRA-2 will assimilate meteorological and aerosol observations not available to MERRA and includes improvements to the GEOS-5 model and analysis scheme so as to provide an ongoing climate analysis beyond MERRA's terminus. MERRA-2 will also serve as a development milestone for a future GMAO coupled Earth system analysis. Production of MERRA-2 began in June 2014 in four processing streams, with convergence to a single near-real time climate analysis expected by early 2015. This talk provides an overview of the MERRA-2 system developments and key science results. For example, compared with MERRA, MERRA-2 exhibits a well-balanced relationship between global precipitation and evaporation, with significantly reduced sensitivity to changes in the global observing system through time. Other notable improvements include reduced biases in the tropical middle- and upper-tropospheric wind and near-surface temperature over continents.
The urban energy balance of a lightweight low-rise neighborhood in Andacollo, Chile
NASA Astrophysics Data System (ADS)
Crawford, Ben; Krayenhoff, E. Scott; Cordy, Paul
2018-01-01
Worldwide, the majority of rapidly growing neighborhoods are found in the Global South. They often exhibit different building construction and development patterns than the Global North, and urban climate research in many such neighborhoods has to date been sparse. This study presents local-scale observations of net radiation ( Q * ) and sensible heat flux ( Q H ) from a lightweight low-rise neighborhood in the desert climate of Andacollo, Chile, and compares observations with results from a process-based urban energy-balance model (TUF3D) and a local-scale empirical model (LUMPS) for a 14-day period in autumn 2009. This is a unique neighborhood-climate combination in the urban energy-balance literature, and results show good agreement between observations and models for Q * and Q H . The unmeasured latent heat flux ( Q E ) is modeled with an updated version of TUF3D and two versions of LUMPS (a forward and inverse application). Both LUMPS implementations predict slightly higher Q E than TUF3D, which may indicate a bias in LUMPS parameters towards mid-latitude, non-desert climates. Overall, the energy balance is dominated by sensible and storage heat fluxes with mean daytime Bowen ratios of 2.57 (observed Q H /LUMPS Q E )-3.46 (TUF3D). Storage heat flux ( ΔQ S ) is modeled with TUF3D, the empirical objective hysteresis model (OHM), and the inverse LUMPS implementation. Agreement between models is generally good; the OHM-predicted diurnal cycle deviates somewhat relative to the other two models, likely because OHM coefficients are not specified for the roof and wall construction materials found in this neighborhood. New facet-scale and local-scale OHM coefficients are developed based on modeled ΔQ S and observed Q * . Coefficients in the empirical models OHM and LUMPS are derived from observations in primarily non-desert climates in European/North American neighborhoods and must be updated as measurements in lightweight low-rise (and other) neighborhoods in various climates become available.
Projected climate change impacts in rainfall erosivity over Brazil.
Almagro, André; Oliveira, Paulo Tarso S; Nearing, Mark A; Hagemann, Stefan
2017-08-15
The impacts of climate change on soil erosion may bring serious economic, social and environmental problems. However, few studies have investigated these impacts on continental scales. Here we assessed the influence of climate change on rainfall erosivity across Brazil. We used observed rainfall data and downscaled climate model output based on Hadley Center Global Environment Model version 2 (HadGEM2-ES) and Model for Interdisciplinary Research On Climate version 5 (MIROC5), forced by Representative Concentration Pathway 4.5 and 8.5, to estimate and map rainfall erosivity and its projected changes across Brazil. We estimated mean values of 10,437 mm ha -1 h -1 year -1 for observed data (1980-2013) and 10,089 MJ mm ha -1 h -1 year -1 and 10,585 MJ mm ha -1 h -1 year -1 for HadGEM2-ES and MIROC5, respectively (1961-2005). Our analysis suggests that the most affected regions, with projected rainfall erosivity increases ranging up to 109% in the period 2007-2040, are northeastern and southern Brazil. Future decreases of as much as -71% in the 2071-2099 period were estimated for the southeastern, central and northwestern parts of the country. Our results provide an overview of rainfall erosivity in Brazil that may be useful for planning soil and water conservation, and for promoting water and food security.
Influence of surface nudging on climatological mean and ENSO feedbacks in a coupled model
NASA Astrophysics Data System (ADS)
Zhu, Jieshun; Kumar, Arun
2018-01-01
Studies have suggested that surface nudging could be an efficient way to reconstruct the subsurface ocean variability, and thus a useful method for initializing climate predictions (e.g., seasonal and decadal predictions). Surface nudging is also the basis for climate models with flux adjustments. In this study, however, some negative aspects of surface nudging on climate simulations in a coupled model are identified. Specifically, a low-resolution version of the NCEP Climate Forecast System, version 2 (CFSv2L) is used to examine the influence of nudging on simulations of climatological mean and on the coupled feedbacks during ENSO. The effect on ENSO feedbacks is diagnosed following a heat budget analysis of mixed layer temperature anomalies. Diagnostics of the climatological mean state indicates that, even though SST biases in all ocean basins, as expected, are eliminated, the fidelity of climatological precipitation, surface winds and subsurface temperature (or the thermocline depth) could be highly ocean basin dependent. This is exemplified by improvements in the climatology of these variables in the tropical Atlantic, but degradations in the tropical Pacific. Furthermore, surface nudging also distorts the dynamical feedbacks during ENSO. For example, while the thermocline feedback played a critical role during the evolution of ENSO in a free simulation, it only played a minor role in the nudged simulation. These results imply that, even though the simulation of surface temperature could be improved in a climate model with surface nudging, the physics behind might be unrealistic.
NASA Astrophysics Data System (ADS)
Simpson, I.
2015-12-01
A long standing bias among global climate models (GCMs) is their incorrect representation of the wintertime circulation of the North Atlantic region. Specifically models tend to exhibit a North Atlantic jet (and associated storm track) that is too zonal, extending across central Europe, when it should tilt northward toward Scandinavia. GCM's consistently predict substantial changes in the large scale circulation in this region, consisting of a localized anti-cyclonic circulation, centered over the Mediterranean and accompanied by increased aridity there and increased storminess over Northern Europe.Here, we present preliminary results from experiments that are designed to address the question of what the impact of the climatological circulation biases might be on this predicted future response. Climate change experiments will be compared in two versions of the Community Earth System Model: the first is a free running version of the model, as typically used in climate prediction; the second is a bias corrected version of the model in which a seasonally varying cycle of bias correction tendencies are applied to the wind and temperature fields. These bias correction tendencies are designed to account for deficiencies in the fast parameterized processes, with an aim to push the model toward a more realistic climatology.While these experiments come with the caveat that they assume the bias correction tendencies will remain constant with time, they allow for an initial assessment, through controlled experiments, of the impact that biases in the climatological circulation can have on future predictions in this region. They will also motivate future work that can make use of the bias correction tendencies to understand the underlying physical processes responsible for the incorrect tilt of the jet.
NASA Astrophysics Data System (ADS)
Collow, Thomas W.; Wang, Wanqiu; Kumar, Arun; Zhang, Jinlun
2017-09-01
The capability of a numerical model to simulate the statistical characteristics of the summer sea ice date of retreat (DOR) and the winter date of advance (DOA) is investigated using sea ice concentration output from the Climate Forecast System Version 2 model (CFSv2). Two model configurations are tested, the operational setting (CFSv2CFSR) which uses initial data from the Climate Forecast System Reanalysis, and a modified version (CFSv2PIOMp) which ingests sea ice thickness initialization data from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) and includes physics modifications for a more realistic representation of heat fluxes at the sea ice top and bottom. First, a method to define DOR and DOA is presented. Then, DOR and DOA are determined from the model simulations and observational sea ice concentration from the National Aeronautics and Space Administration (NASA). Means, trends, and detrended standard deviations of DOR and DOA are compared, along with DOR/DOA rates in the Arctic Ocean. It is found that the statistics are generally similar between the model and observations, although some regional biases exist. In addition, regions of new ice retreat in recent years are represented well in CFSv2PIOMp over the Arctic Ocean, in terms of both spatial extent and timing. Overall, CFSv2PIOMp shows a reduction in error throughout the Arctic. Based on results, it is concluded that the model produces a reasonable representation of the climatology and variability statistics of DOR and DOA in most regions. This assessment serves as a prerequisite for future predictability experiments.
Using a Very Large Ensemble to Examine the Role of the Ocean in Recent Warming Trends.
NASA Astrophysics Data System (ADS)
Sparrow, S. N.; Millar, R.; Otto, A.; Yamazaki, K.; Allen, M. R.
2014-12-01
Results from a very large (~10,000 member) perturbed physics and perturbed initial condition ensemble are presented for the period 1980 to present. A set of model versions that can shadow recent surface and upper ocean observations are identified and the range of uncertainty in the Atlantic Meridional Overturning Circulation (AMOC) assessed. This experiment uses the Met Office Hadley Centre Coupled Model version 3 (HadCM3), a coupled model with fully dynamic atmosphere and ocean components as part of the climateprediction.net distributive computing project. Parameters are selected so that the model has good top of atmosphere radiative balance and simulations are run without flux adjustments that "nudge" the climate towards a realistic state, but have an adverse effect on important ocean processes. This ensemble provides scientific insights on the possible role of the AMOC, among other factors, in climate trends, or lack thereof, over the past 20 years. This ensemble is also used to explore how the occurrence of hiatus events of different durations varies for models with different transient climate response (TCR). We show that models with a higher TCR are less likely to produce a 15-year warming hiatus in global surface temperature than those with a lower TCR.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kay, Jennifer E.; Wall, Casey; Yettella, Vineel
Here, a large, long-standing, and pervasive climate model bias is excessive absorbed shortwave radiation (ASR) over the midlatitude oceans, especially the Southern Ocean. This study investigates both the underlying mechanisms for and climate impacts of this bias within the Community Earth System Model, version 1, with the Community Atmosphere Model, version 5 [CESM1(CAM5)]. Excessive Southern Ocean ASR in CESM1(CAM5) results in part because low-level clouds contain insufficient amounts of supercooled liquid. In a present-day atmosphere-only run, an observationally motivated modification to the shallow convection detrainment increases supercooled cloud liquid, brightens low-level clouds, and substantially reduces the Southern Ocean ASR bias.more » Tuning to maintain global energy balance enables reduction of a compensating tropical ASR bias. In the resulting preindustrial fully coupled run with a brighter Southern Ocean and dimmer tropics, the Southern Ocean cools and the tropics warm. As a result of the enhanced meridional temperature gradient, poleward heat transport increases in both hemispheres (especially the Southern Hemisphere), and the Southern Hemisphere atmospheric jet strengthens. Because northward cross-equatorial heat transport reductions occur primarily in the ocean (80%), not the atmosphere (20%), a proposed atmospheric teleconnection linking Southern Ocean ASR bias reduction and cooling with northward shifts in tropical precipitation has little impact. In summary, observationally motivated supercooled liquid water increases in shallow convective clouds enable large reductions in long-standing climate model shortwave radiation biases. Of relevance to both model bias reduction and climate dynamics, quantifying the influence of Southern Ocean cooling on tropical precipitation requires a model with dynamic ocean heat transport.« less
Kay, Jennifer E.; Wall, Casey; Yettella, Vineel; ...
2016-06-10
Here, a large, long-standing, and pervasive climate model bias is excessive absorbed shortwave radiation (ASR) over the midlatitude oceans, especially the Southern Ocean. This study investigates both the underlying mechanisms for and climate impacts of this bias within the Community Earth System Model, version 1, with the Community Atmosphere Model, version 5 [CESM1(CAM5)]. Excessive Southern Ocean ASR in CESM1(CAM5) results in part because low-level clouds contain insufficient amounts of supercooled liquid. In a present-day atmosphere-only run, an observationally motivated modification to the shallow convection detrainment increases supercooled cloud liquid, brightens low-level clouds, and substantially reduces the Southern Ocean ASR bias.more » Tuning to maintain global energy balance enables reduction of a compensating tropical ASR bias. In the resulting preindustrial fully coupled run with a brighter Southern Ocean and dimmer tropics, the Southern Ocean cools and the tropics warm. As a result of the enhanced meridional temperature gradient, poleward heat transport increases in both hemispheres (especially the Southern Hemisphere), and the Southern Hemisphere atmospheric jet strengthens. Because northward cross-equatorial heat transport reductions occur primarily in the ocean (80%), not the atmosphere (20%), a proposed atmospheric teleconnection linking Southern Ocean ASR bias reduction and cooling with northward shifts in tropical precipitation has little impact. In summary, observationally motivated supercooled liquid water increases in shallow convective clouds enable large reductions in long-standing climate model shortwave radiation biases. Of relevance to both model bias reduction and climate dynamics, quantifying the influence of Southern Ocean cooling on tropical precipitation requires a model with dynamic ocean heat transport.« less
Surface Water and Energy Budgets for Sub-Saharan Africa in GFDL Coupled Climate Model
NASA Astrophysics Data System (ADS)
Tian, D.; Wood, E. F.; Vecchi, G. A.; Jia, L.; Pan, M.
2015-12-01
This study compare surface water and energy budget variables from the Geophysical Fluid Dynamics Laboratory (GFDL) FLOR models with the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), Princeton University Global Meteorological Forcing Dataset (PGF), and PGF-driven Variable Infiltration Capacity (VIC) model outputs, as well as available observations over the sub-Saharan Africa. The comparison was made for four configurations of the FLOR models that included FLOR phase 1 (FLOR-p1) and phase 2 (FLOR-p2) and two phases of flux adjusted versions (FLOR-FA-p1 and FLOR-FA-p2). Compared to p1, simulated atmospheric states in p2 were nudged to the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. The seasonal cycle and annual mean of major surface water (precipitation, evapotranspiration, runoff, and change of storage) and energy variables (sensible heat, ground heat, latent heat, net solar radiation, net longwave radiation, and skin temperature) over a 34-yr period during 1981-2014 were compared in different regions in sub-Saharan Africa (West Africa, East Africa, and Southern Africa). In addition to evaluating the means in three sub-regions, empirical orthogonal functions (EOFs) analyses were conducted to compare both spatial and temporal characteristics of water and energy budget variables from four versions of GFDL FLOR, NCEP CFSR, PGF, and VIC outputs. This presentation will show how well each coupled climate model represented land surface physics and reproduced spatiotemporal characteristics of surface water and energy budget variables. We discuss what caused differences in surface water and energy budgets in land surface components of coupled climate model, climate reanalysis, and reanalysis driven land surface model. The comparisons will reveal whether flux adjustment and nudging would improve depiction of the surface water and energy budgets in coupled climate models.
NASA Astrophysics Data System (ADS)
Zhao, Chun; Huang, Maoyi; Fast, Jerome D.; Berg, Larry K.; Qian, Yun; Guenther, Alex; Gu, Dasa; Shrivastava, Manish; Liu, Ying; Walters, Stacy; Pfister, Gabriele; Jin, Jiming; Shilling, John E.; Warneke, Carsten
2016-05-01
Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhao, Chun; Huang, Maoyi; Fast, Jerome D.
Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model withmore » chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.« less
NASA Technical Reports Server (NTRS)
McGalliard, James
2008-01-01
This viewgraph presentation details the science and systems environments that NASA High End computing program serves. Included is a discussion of the workload that is involved in the processing for the Global Climate Modeling. The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models integrated using the Earth System Modeling Framework (ESMF). The GEOS-5 system was used for the Benchmark tests, and the results of the tests are shown and discussed. Tests were also run for the Cubed Sphere system, results for these test are also shown.
Beaulieu, Marie-Dominique; Dragieva, Nataliya; Del Grande, Claudio; Dawson, Jeremy; Haggerty, Jeannie L.; Barnsley, Jan; Hogg, William E.; Tousignant, Pierre; West, Michael A.
2014-01-01
Purpose: Evaluate the psychometric properties of the French version of the short 19-item Team Climate Inventory (TCI) and explore the contributions of individual and organizational characteristics to perceived team effectiveness. Method: The TCI was completed by 471 of the 618 (76.2%) healthcare professionals and administrative staff working in a random sample of 37 primary care practices in the province of Quebec. Results: Exploratory factor analysis confirmed the original four-factor model. Cronbach's alphas were excellent (from 0.88 to 0.93). Latent class analysis revealed three-class response structure. Respondents in practices with professional governance had a higher probability of belonging to the “High TCI” class than did practices with community governance (36.7% vs. 19.1%). Administrative staff tended to fall into the “Suboptimal TCI” class more frequently than did physicians (36.5% vs. 19.0%). Conclusion: Results confirm the validity of our French version of the short TCI. The association between professional governance and better team climate merits further exploration. PMID:24726073
An Online Approach for Training International Climate Scientists to Use Computer Models
NASA Astrophysics Data System (ADS)
Yarker, M. B.; Mesquita, M. D.; Veldore, V.
2013-12-01
With the mounting evidence by the work of IPCC (2007), climate change has been acknowledged as a significant challenge to Sustainable Development by the international community. It is important that scientists in developing countries have access to knowledge and tools so that well-informed decisions can be made about the mitigation and adaptation of climate change. However, training researchers to use climate modeling techniques and data analysis has become a challenge, because current capacity building approaches train researchers to use climate models through short-term workshops, which requires a large amount of funding. It has also been observed that many participants who recently completed capacity building courses still view climate and weather models as a metaphorical 'black box', where data goes in and results comes out; and there is evidence that these participants lack a basic understanding of the climate system. Both of these issues limit the ability of some scientists to go beyond running a model based on rote memorization of the process. As a result, they are unable to solve problems regarding run-time errors, thus cannot determine whether or not their model simulation is reasonable. Current research in the field of science education indicates that there are effective strategies to teach learners about science models. They involve having the learner work with, experiment with, modify, and apply models in a way that is significant and informative to the learner. It has also been noted that in the case of computational models, the installation and set up process alone can be time consuming and confusing for new users, which can hinder their ability to concentrate on using, experimenting with, and applying the model to real-world scenarios. Therefore, developing an online version of capacity building is an alternative approach to the workshop training programs, which makes use of new technologies and it allows for a long-term educational process in a way that engages the learners with the subject matter, in a way that is meaningful for their region. A number of science-education courses are being conducted online within a capacity building project called 'The Future of Climate Extremes in the Caribbean (XCUBE)'. If accepted, this presentation will explore a case study related to the online training courses provided via the website m2lab.org for the XCUBE project: 'Regional Climate Modeling using WRF'. The course relates to teaching participants how to run WRF for climate simulations using a special version of the model called e-WRF (WRF for Educational purposes). This version of WRF does not require installation so that student learning can be focused on using the model itself. In order to explore the effectiveness of the course, data will be collected from the participants as they complete it. There are currently over 200 participants registered for the course and are made up of graduate students, professors, and researchers from many different science fields. Preliminary results indicate that many students enrolled in this course have previously taken a WRF tutorial, but do not feel confident enough to use it. Despite having taken a tutorial previously, for some participants the basic design of the model was a new concept to them. If accepted, a statistical analysis will be performed as more students complete the course.
The 1997/98 El Nino: A Test for Climate Models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, R; Dong, B; Cess, R D
Version 3 of the Hadley Centre Atmospheric Model (HadAM3) has been used to demonstrate one means of comparing a general circulation model with observations for a specific climate perturbation, namely the strong 1997/98 El Nino. This event was characterized by the collapse of the tropical Pacific's Walker circulation, caused by the lack of a zonal sea surface temperature gradient during the El Nino. Relative to normal years, cloud altitudes were lower in the western portion of the Pacific and higher in the eastern portion. HadAM3 likewise produced the observed collapse of the Walker circulation, and it did a reasonable jobmore » of reproducing the west/east cloud structure changes. This illustrates that the 1997/98 El Nino serves as a useful means of testing cloud-climate interactions in climate models.« less
Predicting the Impacts of Climate Change on Central American Agriculture
NASA Astrophysics Data System (ADS)
Winter, J. M.; Ruane, A. C.; Rosenzweig, C.
2011-12-01
Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.
The MIT IGSM-CAM framework for uncertainty studies in global and regional climate change
NASA Astrophysics Data System (ADS)
Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.
2011-12-01
The MIT Integrated Global System Model (IGSM) version 2.3 is an intermediate complexity fully coupled earth system model that allows simulation of critical feedbacks among its various components, including the atmosphere, ocean, land, urban processes and human activities. A fundamental feature of the IGSM2.3 is the ability to modify its climate parameters: climate sensitivity, net aerosol forcing and ocean heat uptake rate. As such, the IGSM2.3 provides an efficient tool for generating probabilistic distribution functions of climate parameters using optimal fingerprint diagnostics. A limitation of the IGSM2.3 is its zonal-mean atmosphere model that does not permit regional climate studies. For this reason, the MIT IGSM2.3 was linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM) version 3 and new modules were developed and implemented in CAM in order to modify its climate sensitivity and net aerosol forcing to match that of the IGSM. The IGSM-CAM provides an efficient and innovative framework to study regional climate change where climate parameters can be modified to span the range of uncertainty and various emissions scenarios can be tested. This paper presents results from the cloud radiative adjustment method used to modify CAM's climate sensitivity. We also show results from 21st century simulations based on two emissions scenarios (a median "business as usual" scenario where no policy is implemented after 2012 and a policy scenario where greenhouse-gas are stabilized at 660 ppm CO2-equivalent concentrations by 2100) and three sets of climate parameters. The three values of climate sensitivity chosen are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the observed 20th century climate change with simulations by the IGSM with a wide range of climate parameters values. The associated aerosol forcing values were chosen to ensure a good agreement of the simulations with the observed climate change over the 20th century. Because the concentrations of sulfate aerosols significantly decrease over the 21st century in both emissions scenarios, climate changes obtained in these six simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.
NASA Astrophysics Data System (ADS)
Jöckel, Patrick; Tost, Holger; Pozzer, Andrea; Kunze, Markus; Kirner, Oliver; Brenninkmeijer, Carl A. M.; Brinkop, Sabine; Cai, Duy S.; Dyroff, Christoph; Eckstein, Johannes; Frank, Franziska; Garny, Hella; Gottschaldt, Klaus-Dirk; Graf, Phoebe; Grewe, Volker; Kerkweg, Astrid; Kern, Bastian; Matthes, Sigrun; Mertens, Mariano; Meul, Stefanie; Neumaier, Marco; Nützel, Matthias; Oberländer-Hayn, Sophie; Ruhnke, Roland; Runde, Theresa; Sander, Rolf; Scharffe, Dieter; Zahn, Andreas
2016-03-01
Three types of reference simulations, as recommended by the Chemistry-Climate Model Initiative (CCMI), have been performed with version 2.51 of the European Centre for Medium-Range Weather Forecasts - Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model: hindcast simulations (1950-2011), hindcast simulations with specified dynamics (1979-2013), i.e. nudged towards ERA-Interim reanalysis data, and combined hindcast and projection simulations (1950-2100). The manuscript summarizes the updates of the model system and details the different model set-ups used, including the on-line calculated diagnostics. Simulations have been performed with two different nudging set-ups, with and without interactive tropospheric aerosol, and with and without a coupled ocean model. Two different vertical resolutions have been applied. The on-line calculated sources and sinks of reactive species are quantified and a first evaluation of the simulation results from a global perspective is provided as a quality check of the data. The focus is on the intercomparison of the different model set-ups. The simulation data will become publicly available via CCMI and the Climate and Environmental Retrieval and Archive (CERA) database of the German Climate Computing Centre (DKRZ). This manuscript is intended to serve as an extensive reference for further analyses of the Earth System Chemistry integrated Modelling (ESCiMo) simulations.
Update of the Polar SWIFT model for polar stratospheric ozone loss (Polar SWIFT version 2)
NASA Astrophysics Data System (ADS)
Wohltmann, Ingo; Lehmann, Ralph; Rex, Markus
2017-07-01
The Polar SWIFT model is a fast scheme for calculating the chemistry of stratospheric ozone depletion in polar winter. It is intended for use in global climate models (GCMs) and Earth system models (ESMs) to enable the simulation of mutual interactions between the ozone layer and climate. To date, climate models often use prescribed ozone fields, since a full stratospheric chemistry scheme is computationally very expensive. Polar SWIFT is based on a set of coupled differential equations, which simulate the polar vortex-averaged mixing ratios of the key species involved in polar ozone depletion on a given vertical level. These species are O3, chemically active chlorine (ClOx), HCl, ClONO2 and HNO3. The only external input parameters that drive the model are the fraction of the polar vortex in sunlight and the fraction of the polar vortex below the temperatures necessary for the formation of polar stratospheric clouds. Here, we present an update of the Polar SWIFT model introducing several improvements over the original model formulation. In particular, the model is now trained on vortex-averaged reaction rates of the ATLAS Chemistry and Transport Model, which enables a detailed look at individual processes and an independent validation of the different parameterizations contained in the differential equations. The training of the original Polar SWIFT model was based on fitting complete model runs to satellite observations and did not allow for this. A revised formulation of the system of differential equations is developed, which closely fits vortex-averaged reaction rates from ATLAS that represent the main chemical processes influencing ozone. In addition, a parameterization for the HNO3 change by denitrification is included. The rates of change of the concentrations of the chemical species of the Polar SWIFT model are purely chemical rates of change in the new version, whereas in the original Polar SWIFT model, they included a transport effect caused by the original training on satellite data. Hence, the new version allows for an implementation into climate models in combination with an existing stratospheric transport scheme. Finally, the model is now formulated on several vertical levels encompassing the vertical range in which polar ozone depletion is observed. The results of the Polar SWIFT model are validated with independent Microwave Limb Sounder (MLS) satellite observations and output from the original detailed chemistry model of ATLAS.
Future Effects of Southern Hemisphere Stratospheric Zonal Asymmetries on Climate
NASA Astrophysics Data System (ADS)
Stone, K.; Solomon, S.; Kinnison, D. E.; Fyfe, J. C.
2017-12-01
Stratospheric zonal asymmetries in the Southern Hemisphere have been shown to have significant influences on both stratospheric and tropospheric dynamics and climate. Accurate representation of stratospheric ozone in particular is important for realistic simulation of the polar vortex strength and temperature trends. This is therefore also important for stratospheric ozone change's effect on the troposphere, both through modulation of the Southern Annular Mode (SAM), and more localized climate. Here, we characterization the impact of future changes in Southern Hemisphere zonal asymmetry on tropospheric climate, including changes to future tropospheric temperature, and precipitation. The separate impacts of increasing GHGs and ozone recovery on the zonal asymmetric influence on the surface are also investigated. For this purpose, we use a variety of models, including Chemistry Climate Model Initiative simulations from the Community Earth System Model, version 1, with the Whole Atmosphere Community Climate Model (CESM1(WACCM)) and the Australian Community Climate and Earth System Simulator-Chemistry Climate Model (ACCESS-CCM). These models have interactive chemistry and can therefore more accurately represent the zonally asymmetric nature of the stratosphere. The CESM1(WACCM) and ACCESS-CCM models are also compared to simulations from the Canadian Can2ESM model and CESM-Large Ensemble Project (LENS) that have prescribed ozone to further investigate the importance of simulating stratospheric zonal asymmetry.
NASA Technical Reports Server (NTRS)
Bhattacharya, K.; Ghil, M.
1979-01-01
A slightly modified version of the one-dimensional time-dependent energy-balance climate model of Ghil and Bhattacharya (1978) is presented. The albedo-temperature parameterization has been reformulated and the smoothing of the temperature distribution in the tropics has been eliminated. The model albedo depends on time-lagged temperature in order to account for finite growth and decay time of continental ice sheets. Two distinct regimes of oscillatory behavior which depend on the value of the albedo-temperature time lag are considered.
Semiannual progress report, April - September 1991
NASA Technical Reports Server (NTRS)
1991-01-01
Research conducted during the past year in the climate and modeling programs has concentrated on the development of appropriate atmospheric and upper ocean models, and preliminary applications of these models. Principal models are a one-dimensional radiative-convective model, a three dimensional global climate model, and an upper ocean model. Principal applications have been the study of the impact of CO2, aerosols, and the solar constant on climate. Progress was made in the 3-D model development towards physically realistic treatment of these processes. In particular, a map of soil classifications on 1 degree by 1 degree resolution has now been digitized, and soil properties have been assigned to each soil type. Using this information about soil properties, a method has been developed to simulate the hydraulic behavior of the soils of the world. This improved treatment of soil hydrology, together with the seasonally varying vegetation cover, will provide a more realistic study of the role of the terrestrial biota in climate change. A new version of the climate model was created which follows the isotopes of water and sources of water throughout the planet.
Manifestation of remote response over the equatorial Pacific in a climate model
NASA Astrophysics Data System (ADS)
Misra, Vasubandhu; Marx, L.
2007-10-01
In this paper we examine the simulations over the tropical Pacific Ocean from long-term simulations of two different versions of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled climate model that have a different global distribution of the inversion clouds. We find that subtle changes made to the numerics of an empirical parameterization of the inversion clouds can result in a significant change in the coupled climate of the equatorial Pacific Ocean. In one coupled simulation of this study we enforce a simple linear spatial filtering of the diagnostic inversion clouds to ameliorate its spatial incoherency (as a result of the Gibbs effect) while in the other we conduct no such filtering. It is found from the comparison of these two simulations that changing the distribution of the shallow inversion clouds prevalent in the subsidence region of the subtropical high over the eastern oceans in this manner has a direct bearing on the surface wind stress through surface pressure modifications. The SST in the warm pool region responds to this modulation of the wind stress, thus affecting the convective activity over the warm pool region and also the large-scale Walker and Hadley circulation. The interannual variability of SST in the eastern equatorial Pacific Ocean is also modulated by this change to the inversion clouds. Consequently, this sensitivity has a bearing on the midlatitude height response. The same set of two experiments were conducted with the respective versions of the atmosphere general circulation model uncoupled to the ocean general circulation model but forced with observed SST to demonstrate that this sensitivity of the mean climate of the equatorial Pacific Ocean is unique to the coupled climate model where atmosphere, ocean and land interact. Therefore a strong case is made for adopting coupled ocean-land-atmosphere framework to develop climate models as against the usual practice of developing component models independent of each other.
NASA Astrophysics Data System (ADS)
Shukla, Shraddhanand; Arsenault, Kristi R.; Getirana, Augusto; Kumar, Sujay V.; Roningen, Jeanne; Zaitchik, Ben; McNally, Amy; Koster, Randal D.; Peters-Lidard, Christa
2017-04-01
Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. A seamless and effective monitoring and early warning system is needed by regional/national stakeholders. Such system should support a proactive drought management approach and mitigate the socio-economic losses up to the extent possible. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of the LIS models used for drought and water availability monitoring in the region. The second part will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the monitoring and forecasting products through NASA's web-services. The water deficit forecasting system thus far incorporates NOAA's Noah land surface model (LSM), version 3.3, the Variable Infiltration Capacity (VIC) model, version 4.12, NASA GMAO's Catchment LSM, and the Noah Multi-Physics (MP) LSM (the latter two incorporate prognostic water table schemes). In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. The LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. The LIS software framework integrates these forcing datasets and drives the four LSMs and HyMAP. The Land Verification Toolkit (LVT) is used for the evaluation of the LSMs, as it provides model ensemble metrics and the ability to compare against a variety of remotely sensed measurements, like different evapotranspiration (ET) and soil moisture products, and other reanalysis datasets that are available for this region. Comparison of the models' energy and hydrological budgets will be shown for this region (and sub-basin level, e.g., Blue Nile River) and time period (1981-2015), along with evaluating ET, streamflow, groundwater storage and soil moisture, using evaluation metrics (e.g., anomaly correlation, RMSE, etc.). The system uses seasonal climate forecasts from NASA's GMAO (the Goddard Earth Observing System Model, version 5) and NCEP's Climate Forecast System, version 2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region.
The sensitivity of a general circulation model to Saharan dust heating
NASA Technical Reports Server (NTRS)
Randall, D. A.; Carlson, T.; Mintz, Y.
1984-01-01
During the Northern summer, sporadic outbreaks of wind borne Saharan dust are carried out over the Atlantic by the tropical easterlies. Optical depths due to the dust can reach 3 near the African coast, and the dust cloud can be detected as far west as the Caribbean Sea (Carlson, 1979). In order to obtain insight into the possible effects of Saharan dust on the weather and climate of North Africa and the tropical Atlantic Ocean, simulation experiments have been performed with the Climate Model of the Goddard Laboratory for Atmospheric Sciences. The most recent version of the model is described by Randall (1982). The model produces realistic simulations of many aspects of the observed climate and its seasonal variation.
Online Impact Prioritization of Essential Climate Variables on Climate Change
NASA Astrophysics Data System (ADS)
Forsythe-Newell, S. P.; Barkstrom, B. B.; Roberts, K. P.
2007-12-01
The National Oceanic & Atmospheric Administration (NOAA)'s NCDC Scientific Data Stewardship (SDS) Team has developed an online prototype that is capable of displaying the "big picture" perspective of all Essential Climate Variable (ECV) impacts on society and value to the IPCC. This prototype ECV-Model provides the ability to visualize global ECV information with options to drill down in great detail. It offers a quantifiable prioritization of ECV impacts that potentially may significantly enhance collaboration with respect to dealing effectively with climate change. The ECV-Model prototype assures anonymity and provides an online input mechanism for subject matter experts and decision makers to access, review and submit: (1) ranking of ECV"s, (2) new ECV's and associated impact categories and (3) feedback about ECV"s, satellites, etc. Input and feedback are vetted by experts before changes or additions are implemented online. The SDS prototype also provides an intuitive one-stop web site that displays past, current and planned launches of satellites; and general as well as detailed information in conjunction with imagery. NCDC's version 1.0 release will be available to the public and provide an easy "at-a-glance" interface to rapidly identify gaps and overlaps of satellites and associated instruments monitoring climate change ECV's. The SDS version 1.1 will enhance depiction of gaps and overlaps with instruments associated with In-Situ and Satellites related to ECVs. NOAA's SDS model empowers decision makers and the scientific community to rapidly identify weaknesses and strengths in monitoring climate change ECV's and potentially significantly enhance collaboration.
Spatial and Temporal Variation in the Effects of Climatic Variables on Dugong Calf Production
Fuentes, Mariana M. P. B.; Delean, Steven; Grayson, Jillian; Lavender, Sally; Logan, Murray; Marsh, Helene
2016-01-01
Knowledge of the relationships between environmental forcing and demographic parameters is important for predicting responses from climatic changes and to manage populations effectively. We explore the relationships between the proportion of sea cows (Dugong dugon) classified as calves and four climatic drivers (rainfall anomaly, Southern Oscillation El Niño Index [SOI], NINO 3.4 sea surface temperature index, and number of tropical cyclones) at a range of spatially distinct locations in Queensland, Australia, a region with relatively high dugong density. Dugong and calf data were obtained from standardized aerial surveys conducted along the study region. A range of lagged versions of each of the focal climatic drivers (1 to 4 years) were included in a global model containing the proportion of calves in each population crossed with each of the lagged versions of the climatic drivers to explore relationships. The relative influence of each predictor was estimated via Gibbs variable selection. The relationships between the proportion of dependent calves and the climatic drivers varied spatially and temporally, with climatic drivers influencing calf counts at sub-regional scales. Thus we recommend that the assessment of and management response to indirect climatic threats on dugongs should also occur at sub-regional scales. PMID:27355367
Noh, Yoon Goo; Jung, Myun Sook
2016-12-01
The purpose of this study was to analyze the paths of influence that a hospital's ethical climate exerts on nurses' organizational commitment and organizational citizenship behavior, with supervisor trust as the mediating factor, and verify compatibility of the models in hospital nurses. The sample consisted of 374 nurses recruited from four hospitals in 3 cities in Korea. The measurements included the Ethical Climate Questionnaire, Supervisor Trust Questionnaire, Organizational Commitment Questionnaire and Organizational Citizenship Behavior Questionnaire. Ethical Climate Questionnaire consisted of 6 factors; benevolence, personal morality, company rules and procedures, laws and professional codes, self-interest and efficiency. Data were analysed using SPSS version 18.0 and AMOS version 18.0. Supervisor trust was explained by benevolence and self-interest (29.8%). Organizational commitment was explained by benevolence, supervisor trust, personal morality, and rules and procedures (40.4%). Organizational citizenship behavior was explained by supervisor trust, laws and codes, and benevolence (21.8%). Findings indicate that managers need to develop a positive hospital ethical climate in order to improve nurses' trust in supervisors, organizational commitment and organizational citizenship behavior.
Development of a system emulating the global carbon cycle in Earth system models
NASA Astrophysics Data System (ADS)
Tachiiri, K.; Hargreaves, J. C.; Annan, J. D.; Oka, A.; Abe-Ouchi, A.; Kawamiya, M.
2010-08-01
Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO2 concentration scenario. By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO2 stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).
NASA Astrophysics Data System (ADS)
Jung, H. C.; Moon, B. K.; Wie, J.; Park, H. S.; Kim, K. Y.; Lee, J.; Byun, Y. H.
2017-12-01
This research is motivated by a need to develop a new coupled ocean-biogeochemistry model, a key tool for climate projections. The Modular Ocean Model (MOM5) is a global ocean/ice model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) in the US, and it incorporates Tracers of Phytoplankton with Allometric Zooplankton (TOPAZ), which simulates the marine biota associated with carbon cycles. We isolated TOPAZ from MOM5 into a stand-alone version (TOPAZ-SA), and had it receive initial data and ocean physical fields required. Then, its reliability was verified by comparing the simulation results from the TOPAZ-SA with the MOM5/TOPAZ. This stand-alone version of TOPAZ is to be coupled to the Nucleus for European Modelling of the Ocean (NEMO). Here we present the preliminary results. Acknowledgements This research was supported by the project "Research and Development for KMA Weather, Climate, and Earth system Services" (NIMS-2016-3100) of the National Institute of Meteorological Sciences/Korea Meteorological Administration.
Representation of Clear and Cloudy Boundary Layers in Climate Models. Chapter 14
NASA Technical Reports Server (NTRS)
Randall, D. A.; Shao, Q.; Branson, M.
1997-01-01
The atmospheric general circulation models which are being used as components of climate models rely on their boundary layer parameterizations to produce realistic simulations of the surface turbulent fluxes of sensible heat. moisture. and momentum: of the boundary-layer depth over which these fluxes converge: of boundary layer cloudiness: and of the interactions of the boundary layer with the deep convective clouds that grow upwards from it. Two current atmospheric general circulation models are used as examples to show how these requirements are being addressed: these are version 3 of the Community Climate Model. which has been developed at the U.S. National Center for Atmospheric Research. and the Colorado State University atmospheric general circulation model. The formulations and results of both models are discussed. Finally, areas for future research are suggested.
The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0
NASA Astrophysics Data System (ADS)
Valdes, Paul J.; Armstrong, Edward; Badger, Marcus P. S.; Bradshaw, Catherine D.; Bragg, Fran; Crucifix, Michel; Davies-Barnard, Taraka; Day, Jonathan J.; Farnsworth, Alex; Gordon, Chris; Hopcroft, Peter O.; Kennedy, Alan T.; Lord, Natalie S.; Lunt, Dan J.; Marzocchi, Alice; Parry, Louise M.; Pope, Vicky; Roberts, William H. G.; Stone, Emma J.; Tourte, Gregory J. L.; Williams, Jonny H. T.
2017-10-01
Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing with observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Veneziani, Carmela
Two sets of simulations were performed within this allocation: 1) a 12-year fully-coupled experiment in preindustrial conditions, using the CICE4 version of the sea-ice model; 2) a set of multi-decadal ocean-ice-only experiments, forced with CORE-I atmospheric fields and using the CICE5 version of the sea-ice model. Results from simulation 1) are presented in Figures 1-3, and specific results from a simulation in 2) with tracer releases are presented in Figure 4.
The use of perturbed physics ensembles and emulation in palaeoclimate reconstruction (Invited)
NASA Astrophysics Data System (ADS)
Edwards, T. L.; Rougier, J.; Collins, M.
2010-12-01
Climate is a coherent process, with correlations and dependencies across space, time, and climate variables. However, reconstructions of palaeoclimate traditionally consider individual pieces of information independently, rather than making use of this covariance structure. Such reconstructions are at risk of being unphysical or at least implausible. Climate simulators such as General Circulation Models (GCMs), on the other hand, contain climate system theory in the form of dynamical equations describing physical processes, but are imperfect and computationally expensive. These two datasets - pointwise palaeoclimate reconstructions and climate simulator evaluations - contain complementary information, and a statistical synthesis can produce a palaeoclimate reconstruction that combines them while not ignoring their limitations. We use an ensemble of simulators with perturbed parameterisations, to capture the uncertainty about the simulator variant, and our method also accounts for structural uncertainty. The resulting reconstruction contains a full expression of climate uncertainty, not just pointwise but also jointly over locations. Such joint information is crucial in determining spatially extensive features such as isotherms, or the location of the tree-line. A second outcome of the statistical analysis is a refined distribution for the simulator parameters. In this way, information from palaeoclimate observations can be used directly in quantifying uncertainty in future climate projections. The main challenge is the expense of running a large scale climate simulator: each evaluation of an atmosphere-ocean GCM takes several months of computing time. The solution is to interpret the ensemble of evaluations within an 'emulator', which is a statistical model of the simulator. This technique has been used fruitfully in the statistical field of Computer Models for two decades, and has recently been applied in estimating uncertainty in future climate predictions in the UKCP09 (http://ukclimateprojections.defra.gov.uk). But only in the last couple of years has it developed to the point where it can be applied to large-scale spatial fields. We construct an emulator for the mid-Holocene (6000 calendar years BP) temperature anomaly over North America, at the resolution of our simulator (2.5° latitude by 3.75° longitude). This allows us to explore the behaviour of simulator variants that we could not afford to evaluate directly. We introduce the technique of 'co-emulation' of two versions of the climate simulator: the coupled atmosphere-ocean model HadCM3, and an equivalent with a simplified ocean, HadSM3. Running two different versions of a simulator is a powerful tool for increasing the information yield from a fixed budget of computer time, but the results must be combined statistically to account for the reduced fidelity of the quicker version. Emulators provide the appropriate framework.
Dynamical variability in the modelling of chemistry-climate interactions.
Pyle, J A; Braesicke, P; Zeng, G
2005-01-01
We have used a version of the Met Office's climate model, into which we have introduced schemes for atmospheric chemistry, to study chemistry-dynamics-climate interactions. We have considered the variability of the stratospheric polar vortex, whose behaviour influences stratospheric ozone loss and will affect ozone recovery. In particular, we analyse the dynamical control of high latitude ozone in a model version which includes an assimilation of the equatorial quasi-biennial oscillation (QBO), demonstrating the stability of the linear relation between vortex strength and high latitude ozone. We discuss the effect of interactive model ozone on polar stratospheric cloud (PSC) area/volume and winter-spring stratospheric ozone loss in the northern hemisphere. In general we find larger polar ozone losses calculated in those model integrations in which modelled ozone is used interactively in the radiation scheme, even though we underestimate the slope of the ozone loss per PSC volume relation derived from observations. We have also looked at the influence of changing stratosphere-to-troposphere exchange on the tropospheric oxidizing capacity and, in particular, have considered the variability of tropospheric composition under different climate regimes (El Niño/La Niña, etc.). Focusing on the UT/LS, we show the response of ozone to El Niño in two different model set-ups (tropospheric/ stratospheric). In the stratospheric model set-up we find a distinct signal in the lower tropical stratosphere, which shows an anti-correlation between the Niño 3 index and the ozone column amount. In contrast ozone generally increases in the upper troposphere of the tropospheric model set-up after an El Niño. Understanding future trends in stratospheric ozone and tropospheric oxidizing capacity requires an understanding of natural variability, which we explore here.
NASA Technical Reports Server (NTRS)
1990-01-01
The research conducted during the past year in the climate and atmospheric modeling programs concentrated on the development of appropriate atmospheric and upper ocean models, and preliminary applications of these models. Principal models are a one-dimensional radiative-convective model, a three-dimensional global climate model, and an upper ocean model. Principal applications have been the study of the impact of CO2, aerosols and the solar 'constant' on climate. Progress was made in the 3-D model development towards physically realistic treatment of these processes. In particular, a map of soil classifications on 1 degree x 1 degree resolution has been digitized, and soil properties have been assigned to each soil type. Using this information about soil properties, a method was developed to simulate the hydraulic behavior of soils of the world. This improved treatment of soil hydrology, together with the seasonally varying vegetation cover, will provide a more realistic study of the role of the terrestrial biota in climate change. A new version of the climate model was created which follows the isotopes of water and sources of water (or colored water) throughout the planet. Each isotope or colored water source is a fraction of the climate model's water. It participates in condensation and surface evaporation at different fractionation rates and is transported by the dynamics. A major benefit of this project has been to improve the programming techniques and physical simulation of the water vapor budget of the climate model.
Effects of cumulus entrainment and multiple cloud types on a January global climate model simulation
NASA Technical Reports Server (NTRS)
Yao, Mao-Sung; Del Genio, Anthony D.
1989-01-01
An improved version of the GISS Model II cumulus parameterization designed for long-term climate integrations is used to study the effects of entrainment and multiple cloud types on the January climate simulation. Instead of prescribing convective mass as a fixed fraction of the cloud base grid-box mass, it is calculated based on the closure assumption that the cumulus convection restores the atmosphere to a neutral moist convective state at cloud base. This change alone significantly improves the distribution of precipitation, convective mass exchanges, and frequencies in the January climate. The vertical structure of the tropical atmosphere exhibits quasi-equilibrium behavior when this closure is used, even though there is no explicit constraint applied above cloud base.
Evaluation of a new CNRM-CM6 model version for seasonal climate predictions
NASA Astrophysics Data System (ADS)
Volpi, Danila; Ardilouze, Constantin; Batté, Lauriane; Dorel, Laurant; Guérémy, Jean-François; Déqué, Michel
2017-04-01
This work presents the quality assessment of a new version of the Météo-France coupled climate prediction system, which has been developed in the EU COPERNICUS Climate Change Services framework to carry out seasonal forecast. The system is based on the CNRM-CM6 model, with Arpege-Surfex 6.2.2 as atmosphere/land component and Nemo 3.2 as ocean component, which has directly embedded the sea-ice component Gelato 6.0. In order to have a robust diagnostic, the experiment is composed by 60 ensemble members generated with stochastic dynamic perturbations. The experiment has been performed over a 37-year re-forecast period from 1979 to 2015, with two start dates per year, respectively in May 1st and November 1st. The evaluation of the predictive skill of the model is shown under two perspectives: on the one hand, the ability of the model to faithfully respond to positive or negative ENSO, NAO and QBO events, independently of the predictability of these events. Such assessment is carried out through a composite analysis, and shows that the model succeeds in reproducing the main patterns for 2-meter temperature, precipitation and geopotential height at 500 hPa during the winter season. On the other hand, the model predictive skill of the same events (positive and negative ENSO, NAO and QBO) is evaluated.
Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco
2014-01-01
Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required beacause of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied. PMID:25285917
Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco
2014-01-01
Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required because of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.
NASA Technical Reports Server (NTRS)
Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Kovats, R. Sari;
2016-01-01
This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decisionmakers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs (observational datasets) and indicated user needs for the gridding and processing of model output.
NASA Astrophysics Data System (ADS)
Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Sari Kovats, R.; Lotze, Heike K.; Mearns, Linda O.; Navarra, Antonio; Ojima, Dennis S.; Riahi, Keywan; Rosenzweig, Cynthia; Themessl, Matthias; Vincent, Katharine
2016-09-01
This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output.
Models of Solar Irradiance Variability and the Instrumental Temperature Record
NASA Technical Reports Server (NTRS)
Marcus, S. L.; Ghil, M.; Ide, K.
1998-01-01
The effects of decade-to-century (Dec-Cen) variations in total solar irradiance (TSI) on global mean surface temperature Ts during the pre-Pinatubo instrumental era (1854-1991) are studied by using two different proxies for TSI and a simplified version of the IPCC climate model.
NASA Astrophysics Data System (ADS)
Pattnayak, K. C.; Panda, S. K.; Saraswat, Vaishali; Dash, S. K.
2018-04-01
This study assess the performance of two versions of Regional Climate Model (RegCM) in simulating the Indian summer monsoon over South Asia for the period 1998 to 2003 with an aim of conducting future climate change simulations. Two sets of experiments were carried out with two different versions of RegCM (viz. RegCM4.2 and RegCM4.3) with the lateral boundary forcings provided from European Center for Medium Range Weather Forecast Reanalysis (ERA-interim) at 50 km horizontal resolution. The major updates in RegCM4.3 in comparison to the older version RegCM4.2 are the inclusion of measured solar irradiance in place of hardcoded solar constant and additional layers in the stratosphere. The analysis shows that the Indian summer monsoon rainfall, moisture flux and surface net downward shortwave flux are better represented in RegCM4.3 than that in the RegCM4.2 simulations. Excessive moisture flux in the RegCM4.2 simulation over the northern Arabian Sea and Peninsular India resulted in an overestimation of rainfall over the Western Ghats, Peninsular region as a result of which the all India rainfall has been overestimated. RegCM4.3 has performed well over India as a whole as well as its four rainfall homogenous zones in reproducing the mean monsoon rainfall and inter-annual variation of rainfall. Further, the monsoon onset, low-level Somali Jet and the upper level tropical easterly jet are better represented in the RegCM4.3 than RegCM4.2. Thus, RegCM4.3 has performed better in simulating the mean summer monsoon circulation over the South Asia. Hence, RegCM4.3 may be used to study the future climate change over the South Asia.
Hydrological and Climatic Significance of Martian Deltas
NASA Astrophysics Data System (ADS)
Di Achille, G.; Vaz, D. A.
2017-10-01
We a) review the geomorphology, sedimentology, and mineralogy of the martian deltas record and b) present the results of a quantitative study of the hydrology and sedimentology of martian deltas using modified version of terrestrial model Sedflux.
The CESM Large Ensemble Project: Inspiring New Ideas and Understanding
NASA Astrophysics Data System (ADS)
Kay, J. E.; Deser, C.
2016-12-01
While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920-2100) 40+ times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 2000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Examples of scientists and stakeholders that are using the CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change will be highlighted the presentation.
An assessment of climate change impacts on maize yields in Hebei Province of China.
Chen, Yongfu; Han, Xinru; Si, Wei; Wu, Zhigang; Chien, Hsiaoping; Okamoto, Katsuo
2017-03-01
The climate change impacts on maize yields are quantified in this paper using statistical models with panel data from 3731 farmers' observations across nine sample villages in Hebei Province of China. The marginal impacts of climate change and the simulated impacts on maize yields based on scenarios of Representative Concentration Pathways 2.6, 4.5, 6.0, and 8.5 from the global climate models of Model for Interdisciplinary Research on Climate version 5 (MIROC5) and Meteorological Research Institute Coupled General Circulation Model version 3 (MRI-CGCM3) were then calculated, analyzed, and explained. The results indicate that, first, the most important finding was that climate change impacts on maize yields were significant and a 1°C warming or a 1mm decrease in precipitation resulted in a 150.255kg or a 1.941kg loss in maize yields per hectare, respectively. Second, villages with latitudes of less than 39.832 and longitudes of more than 114.839 in Hebei province suffered losses due to warm weather. Third, the simulated impacts for the full sample are all negative based on scenarios from MIROC5, and their magnitudes are more than those of MRI-CGCM3 are. Based on scenarios in the 2050s, the biggest loss for maize yields per hectare for the full sample accounts for about one-tenth of the mean maize yield from 2004 to 2010, and all of the villages are impacted. Hence, it is important to help farms adopt an adaptation strategy to tackle the risk of loss for maize yields from climate change, and it is necessary to develop agricultural synthesis services as a public adaptation policy at the village level to interact with the adaptation strategy at the farm level. Copyright © 2016 Elsevier B.V. All rights reserved.
Simulations of the effect of a warmer climate on atmospheric humidity
NASA Technical Reports Server (NTRS)
Del Genio, Anthony D.; Lacis, Andrew A.; Ruedy, Reto A.
1991-01-01
Increases in the concentration of water vapor constitute the single largest positive feedback in models of global climate warming caused by greenhouse gases. It has been suggested that sinking air in the regions surrounding deep cumulus clouds will dry the upper troposphere and eliminate or reverse the direction of water vapor feedback. This hypothesis has been tested by performing an idealized simulation of climate change with two different versions of a climate model which both incorporate drying due to subsidence of clear air but differ in their parameterization of moist convection and stratiform clouds. Despite increased drying of the upper troposphere by cumulus clouds, upper-level humidity increases in the warmer climate because of enhanced upward moisture transport by the general circulation and increased accumulation of water vapor and ice at cumulus cloud tops.
The Latest Mars Climate Database (MCD v5.1)
NASA Astrophysics Data System (ADS)
Millour, Ehouarn; Forget, Francois; Spiga, Aymeric; Navarro, Thomas; Madeleine, Jean-Baptiste; Pottier, Alizée; Montabone, Luca; Kerber, Laura; Lefèvre, Franck; Montmessin, Franck; Chaufray, Jean-Yves; López-Valverde, Miguel; González-Galindo, Francisco; Lewis, Stephen; Read, Peter; Huot, Jean-Paul; Desjean, Marie-Christine; the MCD/GCM development Team
2014-05-01
For many years, several teams around the world have developed GCMs (General Circulation Model or Global Climate Model) to simulate the environment on Mars. The GCM developed at the Laboratoire de Météorologie Dynamique in collaboration with several teams in Europe (LATMOS, France, University of Oxford, The Open University, the Instituto de Astrofisica de Andalucia), and with the support of ESA and CNES is currently used for many applications. Its outputs have also regularly been compiled to build a Mars Climate Database, a freely available tool useful for the scientific and engineering communities. The Mars Climate Database (MCD) has over the years been distributed to more than 150 teams around the world. Following the recent improvements inthe GCM, a new series of reference simulations have been run and compiled into a new version (version5.1) of the Mars Climate Database, released in the first half of 2014. To summarize, MCD v5.1 provides: - Climatologies over a series of dust scenarios: standard year, cold (ie: low dust), warm (ie: dusty atmosphere) and dust storm, all topped by various cases of Extreme UV solar inputs (low, mean or maximum). These scenarios differ from those of previous versions of the MCD (version 4.x) as they have been derived from home-made, instrument-derived (TES, THEMIS, MCS, MERs), dust climatology of the last 8 Martian years. - Mean values and statistics of main meteorological variables (atmospheric temperature, density, pressure and winds), as well as surface pressure and temperature, CO2 ice cover, thermal and solar radiative fluxes, dust column opacity and mixing ratio, [H20] vapor and ice columns, concentrations of many species: [CO], [O2], [O], [N2], [H2], [O3], ... - A high resolution mode which combines high resolution (32 pixel/degree) MOLA topography records and Viking Lander 1 pressure records with raw lower resolution GCM results to yield, within the restriction of the procedure, high resolution values of atmospheric variables. - The possibility to reconstruct realistic conditions by combining the provided climatology with additional large scale and small scale perturbations schemes. At EGU, we will report on the latest improvements in the Mars Climate Database, with comparisons with available measurements from orbit (e.g.: TES, MCS) or landers (Viking, Phoenix, MSL).
NASA Astrophysics Data System (ADS)
Servonnat, Jerome; Braconnot, Pascale; Gainusa-Bogdan, Alina
2015-04-01
Turbulent momentum and heat (sensible and latent) fluxes at the air-sea interface are key components of the whole energetic of the Earth's climate and their good representation in climate models is of prime importance. In this work, we use the methodology developed by Braconnot & Frankignoul (1993) to perform a Hotelling T2 test on spatio-temporal fields (annual cycles). This statistic provides a quantitative measure accounting for an estimate of the observational uncertainty for the evaluation of low-latitude turbulent air-sea fluxes in a suite of IPSL model versions. The spread within the observational ensemble of turbulent flux data products assembled by Gainusa-Bogdan et al (submitted) is used as an estimate of the observational uncertainty for the different turbulent fluxes. The methodology holds on a selection of a small number of dominating variability patterns (EOFs) that are common to both the model and the observations for the comparison. Consequently it focuses on the large-scale variability patterns and avoids the possibly noisy smaller scales. The results show that different versions of the IPSL couple model share common large scale model biases, but also that there the skill on sea surface temperature is not necessarily directly related to the skill in the representation of the different turbulent fluxes. Despite the large error bars on the observations the test clearly distinguish the different merits of the different model version. The analyses of the common EOF patterns and related time series provide guidance on the major differences with the observations. This work is a first attempt to use such statistic on the evaluation of the spatio-temporal variability of the turbulent fluxes, accounting for an observational uncertainty, and represents an efficient tool for systematic evaluation of simulated air-seafluxes, considering both the fluxes and the related atmospheric variables. References Braconnot, P., and C. Frankignoul (1993), Testing Model Simulations of the Thermocline Depth Variability in the Tropical Atlantic from 1982 through 1984, J. Phys. Oceanogr., 23(4), 626-647 Gainusa-Bogdan A., Braconnot P. and Servonnat J. (submitted), Using an ensemble data set of turbulent air-sea fluxes to evaluate the IPSL climate model in tropical regions, Journal of Geophysical Research Atmosphere, 2014JD022985
A transient fully coupled climate-ice-sheet simulation of the last glacial inception
NASA Astrophysics Data System (ADS)
Lofverstrom, M.; Otto-Bliesner, B. L.; Lipscomb, W. H.; Fyke, J. G.; Marshall, S.; Sacks, B.; Brady, E. C.
2017-12-01
The last glacial inception occurred around 115 ka, following a relative minimum in the Northern Hemisphere summer insolation. It is believed that small and spatially separated ice caps initially formed in the high elevation regions of northern Canada, Scandinavia, and along the Siberian Arctic coast. These ice caps subsequently migrated down in the valleys where they coalesced and formed the initial seeds of the large coherent ice masses that covered the northern parts of the North American and Eurasian continents over most of the last glacial cycle. Sea level records show that the initial growth period lasted for about 10 kyrs, and the resulting ice sheets may have lowered the global sea level by as much as 30 to 50 meters. Here we examine the transient climate system evolution over the period between 118 and 110 ka, using the fully coupled Community Earth System Model, version 2 (CESM2). This model features a two-way coupled high-resolution (4x4 km) ice-sheet component (Community Ice Sheet model, version 2; CISM2) that simulates ice sheets as an interactive component of the climate system. We impose a transient forcing protocol where the greenhouse gas concentrations and the orbital parameters follow the nominal year in the simulation; the model topography is also dynamically evolving in order to reflect changes in ice elevation throughout the simulation. The analysis focuses on how the climate system evolves over this time interval, with a special focus on glacial inception in the high-latitude continents. Results will highlight how the evolving ice sheets compare to data and previous model based reconstructions.
NASA Astrophysics Data System (ADS)
Loikith, Paul C.; Waliser, Duane E.; Kim, Jinwon; Ferraro, Robert
2017-08-01
Cool season precipitation event characteristics are evaluated across a suite of downscaled climate models over the northeastern US. Downscaled hindcast simulations are produced by dynamically downscaling the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) using the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (WRF) regional climate model (RCM) and the Goddard Earth Observing System Model, Version 5 (GEOS-5) global climate model. NU-WRF RCM simulations are produced at 24, 12, and 4-km horizontal resolutions using a range of spectral nudging schemes while the MERRA2 global downscaled run is provided at 12.5-km. All model runs are evaluated using four metrics designed to capture key features of precipitation events: event frequency, event intensity, even total, and event duration. Overall, the downscaling approaches result in a reasonable representation of many of the key features of precipitation events over the region, however considerable biases exist in the magnitude of each metric. Based on this evaluation there is no clear indication that higher resolution simulations result in more realistic results in general, however many small-scale features such as orographic enhancement of precipitation are only captured at higher resolutions suggesting some added value over coarser resolution. While the differences between simulations produced using nudging and no nudging are small, there is some improvement in model fidelity when nudging is introduced, especially at a cutoff wavelength of 600 km compared to 2000 km. Based on the results of this evaluation, dynamical regional downscaling using NU-WRF results in a more realistic representation of precipitation event climatology than the global downscaling of MERRA2 using GEOS-5.
Enhanced marine sulphur emissions offset global warming and impact rainfall.
Grandey, B S; Wang, C
2015-08-21
Artificial fertilisation of the ocean has been proposed as a possible geoengineering method for removing carbon dioxide from the atmosphere. The associated increase in marine primary productivity may lead to an increase in emissions of dimethyl sulphide (DMS), the primary source of sulphate aerosol over remote ocean regions, potentially causing direct and cloud-related indirect aerosol effects on climate. This pathway from ocean fertilisation to aerosol induced cooling of the climate may provide a basis for solar radiation management (SRM) geoengineering. In this study, we investigate the transient climate impacts of two emissions scenarios: an RCP4.5 (Representative Concentration Pathway 4.5) control; and an idealised scenario, based on RCP4.5, in which DMS emissions are substantially enhanced over ocean areas. We use mini-ensembles of a coupled atmosphere-ocean configuration of CESM1(CAM5) (Community Earth System Model version 1, with the Community Atmosphere Model version 5). We find that the cooling effect associated with enhanced DMS emissions beneficially offsets greenhouse gas induced warming across most of the world. However, the rainfall response may adversely affect water resources, potentially impacting human livelihoods. These results demonstrate that changes in marine phytoplankton activity may lead to a mixture of positive and negative impacts on the climate.
Enhanced marine sulphur emissions offset global warming and impact rainfall
Grandey, B. S.; Wang, C.
2015-01-01
Artificial fertilisation of the ocean has been proposed as a possible geoengineering method for removing carbon dioxide from the atmosphere. The associated increase in marine primary productivity may lead to an increase in emissions of dimethyl sulphide (DMS), the primary source of sulphate aerosol over remote ocean regions, potentially causing direct and cloud-related indirect aerosol effects on climate. This pathway from ocean fertilisation to aerosol induced cooling of the climate may provide a basis for solar radiation management (SRM) geoengineering. In this study, we investigate the transient climate impacts of two emissions scenarios: an RCP4.5 (Representative Concentration Pathway 4.5) control; and an idealised scenario, based on RCP4.5, in which DMS emissions are substantially enhanced over ocean areas. We use mini-ensembles of a coupled atmosphere-ocean configuration of CESM1(CAM5) (Community Earth System Model version 1, with the Community Atmosphere Model version 5). We find that the cooling effect associated with enhanced DMS emissions beneficially offsets greenhouse gas induced warming across most of the world. However, the rainfall response may adversely affect water resources, potentially impacting human livelihoods. These results demonstrate that changes in marine phytoplankton activity may lead to a mixture of positive and negative impacts on the climate. PMID:26293204
Enhanced marine sulphur emissions offset global warming and impact rainfall
NASA Astrophysics Data System (ADS)
Grandey, B. S.; Wang, C.
2015-08-01
Artificial fertilisation of the ocean has been proposed as a possible geoengineering method for removing carbon dioxide from the atmosphere. The associated increase in marine primary productivity may lead to an increase in emissions of dimethyl sulphide (DMS), the primary source of sulphate aerosol over remote ocean regions, potentially causing direct and cloud-related indirect aerosol effects on climate. This pathway from ocean fertilisation to aerosol induced cooling of the climate may provide a basis for solar radiation management (SRM) geoengineering. In this study, we investigate the transient climate impacts of two emissions scenarios: an RCP4.5 (Representative Concentration Pathway 4.5) control; and an idealised scenario, based on RCP4.5, in which DMS emissions are substantially enhanced over ocean areas. We use mini-ensembles of a coupled atmosphere-ocean configuration of CESM1(CAM5) (Community Earth System Model version 1, with the Community Atmosphere Model version 5). We find that the cooling effect associated with enhanced DMS emissions beneficially offsets greenhouse gas induced warming across most of the world. However, the rainfall response may adversely affect water resources, potentially impacting human livelihoods. These results demonstrate that changes in marine phytoplankton activity may lead to a mixture of positive and negative impacts on the climate.
Comparison of In-Person vs. Digital Climate Education Program
NASA Astrophysics Data System (ADS)
Anderson, R. K.; Flora, J. A.; Saphir, M.
2017-12-01
In 2014, ACE (Alliance for Climate Education) evaluated the impact of its 45-minute live climate edutainment education program on the knowledge, attitudes and behavior of high school students with respect to climate change. The results showed gains in knowledge, increased engagement, as well as increased communication about climate change with number of students reporting talking about climate change with friends and family more than doubling. In 2016, ACE launched a digital version of its in-person edutainment education program, a 40-minute video version of the live program. This digital version, Our Climate Our Future (OCOF), has now been used by nearly 4,000 teachers nationwide and viewed by over 150,000 students. We experimentally tested the impact of the digital program (OCOF) compared to the live program and a control group. The experiment was conducted with 709 students in 27 classes at two North Carolina public high schools. Classes were assigned to one of three conditions: digital, live and control. In the digital version, students watched the 40-minute OCOF video featuring the same educator that presented the live program. In the live version, students received an identical 40-minute live presentation by an ACE staff educator The control group received neither treatment. When compared to controls, both programs were effective in positively increasing climate change knowledge, climate justice knowledge, perceived self-efficacy to make climate-friendly behavior changes, and beliefs about climate change (all statistically significant at or above P<.01). In the areas of hope that people can solve climate change and intent to change behavior, only the live program showed significant increases. In these two areas, it may be that an in-person experience is key to affecting change. In light of these positive results, ACE plans to increase the use of OCOF in schools across the country to assist teachers in their efforts to teach about climate change.
Comparison of In-Person vs. Digital Climate Education Program
NASA Astrophysics Data System (ADS)
Anbar, A. D.; Elkins-Tanton, L. T.; Klug Boonstra, S.; Ben-Naim, D.
2016-12-01
In 2014, ACE (Alliance for Climate Education) evaluated the impact of its 45-minute live climate edutainment education program on the knowledge, attitudes and behavior of high school students with respect to climate change. The results showed gains in knowledge, increased engagement, as well as increased communication about climate change with number of students reporting talking about climate change with friends and family more than doubling. In 2016, ACE launched a digital version of its in-person edutainment education program, a 40-minute video version of the live program. This digital version, Our Climate Our Future (OCOF), has now been used by nearly 4,000 teachers nationwide and viewed by over 150,000 students. We experimentally tested the impact of the digital program (OCOF) compared to the live program and a control group. The experiment was conducted with 709 students in 27 classes at two North Carolina public high schools. Classes were assigned to one of three conditions: digital, live and control. In the digital version, students watched the 40-minute OCOF video featuring the same educator that presented the live program. In the live version, students received an identical 40-minute live presentation by an ACE staff educator The control group received neither treatment. When compared to controls, both programs were effective in positively increasing climate change knowledge, climate justice knowledge, perceived self-efficacy to make climate-friendly behavior changes, and beliefs about climate change (all statistically significant at or above P<.01). In the areas of hope that people can solve climate change and intent to change behavior, only the live program showed significant increases. In these two areas, it may be that an in-person experience is key to affecting change. In light of these positive results, ACE plans to increase the use of OCOF in schools across the country to assist teachers in their efforts to teach about climate change.
NASA Astrophysics Data System (ADS)
Benedict, James J.; Medeiros, Brian; Clement, Amy C.; Pendergrass, Angeline G.
2017-06-01
Precipitation distributions and extremes play a fundamental role in shaping Earth's climate and yet are poorly represented in many global climate models. Here, a suite of idealized Community Atmosphere Model (CAM) aquaplanet simulations is examined to assess the aquaplanet's ability to reproduce hydroclimate statistics of real-Earth configurations and to investigate sensitivities of precipitation distributions and extremes to model physics, horizontal grid resolution, and ocean type. Little difference in precipitation statistics is found between aquaplanets using time-constant sea-surface temperatures and those implementing a slab ocean model with a 50 m mixed-layer depth. In contrast, CAM version 5.3 (CAM5.3) produces more time mean, zonally averaged precipitation than CAM version 4 (CAM4), while CAM4 generates significantly larger precipitation variance and frequencies of extremely intense precipitation events. The largest model configuration-based precipitation sensitivities relate to choice of horizontal grid resolution in the selected range 1-2°. Refining grid resolution has significant physics-dependent effects on tropical precipitation: for CAM4, time mean zonal mean precipitation increases along the Equator and the intertropical convergence zone (ITCZ) narrows, while for CAM5.3 precipitation decreases along the Equator and the twin branches of the ITCZ shift poleward. Increased grid resolution also reduces light precipitation frequencies and enhances extreme precipitation for both CAM4 and CAM5.3 resulting in better alignment with observational estimates. A discussion of the potential implications these hydrologic cycle sensitivities have on the interpretation of precipitation statistics in future climate projections is also presented.
NASA Technical Reports Server (NTRS)
Suarez, Max J. (Editor); Takacs, Lawrence L.
1995-01-01
A detailed description of the numerical formulation of Version 2 of the ARIES/GEOS 'dynamical core' is presented. This code is a nearly 'plug-compatible' dynamics for use in atmospheric general circulation models (GCMs). It is a finite difference model on a staggered latitude-longitude C-grid. It uses second-order differences for all terms except the advection of vorticity by the rotation part of the flow, which is done at fourth-order accuracy. This dynamical core is currently being used in the climate (ARIES) and data assimilation (GEOS) GCMs at Goddard.
Progress Towards AIRS Science Team Version-7 at SRT
NASA Technical Reports Server (NTRS)
Susskind, Joel; Blaisdell, John; Iredell, Lena; Kouvaris, Louis
2016-01-01
The AIRS Science Team Version-6 retrieval algorithm is currently producing level-3 Climate Data Records (CDRs) from AIRS that have been proven useful to scientists in understanding climate processes. CDRs are gridded level-3 products which include all cases passing AIRS Climate QC. SRT has made significant further improvements to AIRS Version-6. At the last Science Team Meeting, we described results using SRT AIRS Version-6.22. SRT Version-6.22 is now an official build at JPL called 6.2.4. Version-6.22 results are significantly improved compared to Version-6, especially with regard to water vapor and ozone profiles. We have adapted AIRS Version-6.22 to run with CrIS/ATMS, at the Sounder SIPS which processed CrIS/ATMS data for August 2014. JPL AIRS Version-6.22 uses the Version-6 AIRS tuning coefficients. AIRS Version-6.22 has at least two limitations which must be improved before finalization of Version-7: Version-6.22 total O3 has spurious high values in the presence of Saharan dust over the ocean; and Version-6.22 retrieved upper stratospheric temperatures are very poor in polar winter. SRT Version-6.28 addresses the first concern. John Blaisdell ran the analog of AIRS Version-6.28 in his own sandbox at JPL for the 14th and 15th of every month in 2014 and all of July and October for 2014. AIRS Version-6.28a is hot off the presses and addresses the second concern.
Testing the sensitivity of past climates to the indirect effects of dust
NASA Astrophysics Data System (ADS)
Sagoo, Navjit; Storelvmo, Trude
2017-06-01
Mineral dust particles are important ice nuclei (IN) and as such indirectly impact Earth's radiative balance via the properties of cold clouds. Using the Community Earth System Model version 1.0.6, and Community Atmosphere Model version 5.1, and a new empirical parameterization for ice nucleation on dust particles, we investigate the radiative forcing induced by dust IN for different dust loadings. Dust emissions are representative of global conditions for the Last Glacial Maximum and the mid-Pliocene Warm Period. Increased dust leads to smaller and more numerous ice crystals in mixed phase clouds, impacting cloud opacity, lifetime, and precipitation. This increases the shortwave cloud radiative forcing, resulting in significant surface temperature cooling and polar amplification—which is underestimated in existing studies relative to paleoclimate archives. Large hydrological changes occur and are linked to an enhanced dynamical response. We conclude that dust indirect effects could potentially have a significant impact on the model-data mismatch that exists for paleoclimates.
Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; ...
2016-02-01
This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super-Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual-mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double-ITCZ bias. However, unfolding intensity distributions reveal several improvementsmore » in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden-Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM’s low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved-scale processes in CAM, few differences discriminate the rainfall properties of the two models. Lastly, these results are discussed in light of their implication for future rainfall changes in response to climate forcing.« less
NASA Astrophysics Data System (ADS)
Winska, M.
2016-12-01
The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here.
Selecting climate simulations for impact studies based on multivariate patterns of climate change.
Mendlik, Thomas; Gobiet, Andreas
In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.
Improving Subtropical Boundary Layer Cloudiness in the 2011 NCEP GFS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fletcher, J. K.; Bretherton, Christopher S.; Xiao, Heng
2014-09-23
The current operational version of National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) shows significant low cloud bias. These biases also appear in the Coupled Forecast System (CFS), which is developed from the GFS. These low cloud biases degrade seasonal and longer climate forecasts, particularly of short-wave cloud radiative forcing, and affect predicted sea surface temperature. Reducing this bias in the GFS will aid the development of future CFS versions and contributes to NCEP's goal of unified weather and climate modelling. Changes are made to the shallow convection and planetary boundary layer parameterisations to make them more consistentmore » with current knowledge of these processes and to reduce the low cloud bias. These changes are tested in a single-column version of GFS and in global simulations with GFS coupled to a dynamical ocean model. In the single-column model, we focus on changing parameters that set the following: the strength of shallow cumulus lateral entrainment, the conversion of updraught liquid water to precipitation and grid-scale condensate, shallow cumulus cloud top, and the effect of shallow convection in stratocumulus environments. Results show that these changes improve the single-column simulations when compared to large eddy simulations, in particular through decreasing the precipitation efficiency of boundary layer clouds. These changes, combined with a few other model improvements, also reduce boundary layer cloud and albedo biases in global coupled simulations.« less
Impact of Land Cover Characterization and Properties on Snow Albedo in Climate Models
NASA Astrophysics Data System (ADS)
Wang, L.; Bartlett, P. A.; Chan, E.; Montesano, P.
2017-12-01
The simulation of winter albedo in boreal and northern environments has been a particular challenge for land surface modellers. Assessments of output from CMIP3 and CMIP5 climate models have revealed that many simulations are characterized by overestimation of albedo in the boreal forest. Recent studies suggest that inaccurate representation of vegetation distribution, improper simulation of leaf area index, and poor treatment of canopy-snow processes are the primary causes of albedo errors. While several land cover datasets are commonly used to derive plant functional types (PFT) for use in climate models, new land cover and vegetation datasets with higher spatial resolution have become available in recent years. In this study, we compare the spatial distribution of the dominant PFTs and canopy cover fractions based on different land cover datasets, and present results from offline simulations of the latest version Canadian Land Surface Scheme (CLASS) over the northern Hemisphere land. We discuss the impact of land cover representation and surface properties on winter albedo simulations in climate models.
The CNRM-CM5.1 global climate model: description and basic evaluation
NASA Astrophysics Data System (ADS)
Voldoire, A.; Sanchez-Gomez, E.; Salas y Mélia, D.; Decharme, B.; Cassou, C.; Sénési, S.; Valcke, S.; Beau, I.; Alias, A.; Chevallier, M.; Déqué, M.; Deshayes, J.; Douville, H.; Fernandez, E.; Madec, G.; Maisonnave, E.; Moine, M.-P.; Planton, S.; Saint-Martin, D.; Szopa, S.; Tyteca, S.; Alkama, R.; Belamari, S.; Braun, A.; Coquart, L.; Chauvin, F.
2013-05-01
A new version of the general circulation model CNRM-CM has been developed jointly by CNRM-GAME (Centre National de Recherches Météorologiques—Groupe d'études de l'Atmosphère Météorologique) and Cerfacs (Centre Européen de Recherche et de Formation Avancée) in order to contribute to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The purpose of the study is to describe its main features and to provide a preliminary assessment of its mean climatology. CNRM-CM5.1 includes the atmospheric model ARPEGE-Climat (v5.2), the ocean model NEMO (v3.2), the land surface scheme ISBA and the sea ice model GELATO (v5) coupled through the OASIS (v3) system. The main improvements since CMIP3 are the following. Horizontal resolution has been increased both in the atmosphere (from 2.8° to 1.4°) and in the ocean (from 2° to 1°). The dynamical core of the atmospheric component has been revised. A new radiation scheme has been introduced and the treatments of tropospheric and stratospheric aerosols have been improved. Particular care has been devoted to ensure mass/water conservation in the atmospheric component. The land surface scheme ISBA has been externalised from the atmospheric model through the SURFEX platform and includes new developments such as a parameterization of sub-grid hydrology, a new freezing scheme and a new bulk parameterisation for ocean surface fluxes. The ocean model is based on the state-of-the-art version of NEMO, which has greatly progressed since the OPA8.0 version used in the CMIP3 version of CNRM-CM. Finally, the coupling between the different components through OASIS has also received a particular attention to avoid energy loss and spurious drifts. These developments generally lead to a more realistic representation of the mean recent climate and to a reduction of drifts in a preindustrial integration. The large-scale dynamics is generally improved both in the atmosphere and in the ocean, and the bias in mean surface temperature is clearly reduced. However, some flaws remain such as significant precipitation and radiative biases in many regions, or a pronounced drift in three dimensional salinity.
Person-centred ward climate as experienced by mentally lucid residents in long-term care facilities.
Bergland, Ådel; Hofoss, Dag; Kirkevold, Marit; Vassbø, Tove; Edvardsson, David
2015-02-01
To assess the content validity and reliability of the Person-centred Climate Questionnaire-Patient version in long-term care facilities, to describe residents' perceptions of the extent to which their ward climate was person-centred and to explore whether person-centredness was associated with facility and resident characteristics, such as facility and ward size, having a sensory garden and having a primary caregiver. The importance of the physical environment to persons with dementia has been investigated. However, research is lacking regarding the extent to which mentally lucid residents experience their physical and psycho-social ward climate as person-centred and the factors influencing their experience. Cross-sectional survey design. The Person-centred Climate Questionnaire-Patient version was translated into Norwegian with forward and backward translation. The content validity index for scales was assessed. The Person-centred Climate Questionnaire -Patient version was completed by 145 mentally lucid residents in 17 Norwegian long-term care facilities. Reliability was assessed by Cronbach's α and item-total correlations. Test-retest reliability was assessed by paired samples t-test and Spearman's correlation. To explore differences based on facility and resident characteristics, independent-samples t-test and one-way anova were used. The content validity index for scales was satisfactory. The Person-centred Climate Questionnaire-Patient version was internally consistent and had satisfactory test-retest reliability. The climate was experienced as highly person-centred. No significant differences were found, except that residents in larger facilities experienced the climate as more person-centred in relation to everyday activities (subscale 2) than residents in smaller facilities. The Norwegian version of the Person-centred Climate Questionnaire-Patient version can be regarded as reliable in a long-term care facility context. Perceived degree of person-centredness was not associated with facility or resident characteristics, such as the number of residents, having a sensory garden or knowing that one has a primary caregiver. A person-centred climate can be attained in different kinds of long-term care facilities. © 2014 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Schimmel, A.; Rammer, W.; Lexer, M. J.
2012-04-01
The PICUS model is a hybrid ecosystem model which is based on a 3D patch model and a physiological stand level production model. The model includes, among others, a submodel of bark beetle disturbances in Norway spruce and a management module allowing any silvicultural treatment to be mimicked realistically. It has been tested intensively for its ability to realistically reproduce tree growth and stand dynamics in complex structured mixed and mono-species temperate forest ecosystems. In several applications the models capacity to generate relevant forest related attributes which were subsequently fed into indicator systems to assess sustainable forest management under current and future climatic conditions has been proven. However, the relatively coarse monthly temporal resolution of the driving climate data as well as the process resolution of the major water relations within the simulated ecosystem hampered the inclusion of more detailed physiologically based assessments of drought conditions and water provisioning ecosystem services. In this contribution we present the improved model version PICUS v1.6 focusing on the newly implemented logic for the water cycle calculations. Transpiration, evaporation from leave surfaces and the forest floor, snow cover and snow melt as well as soil water dynamics in several soil horizons are covered. In enhancing the model overarching goal was to retain the large-scale applicability by keeping the input requirements to a minimum while improving the physiological foundation of water related ecosystem processes. The new model version is tested against empirical time series data. Future model applications are outlined.
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
Climate Prediction Center: ENSO Diagnostic Discussion
: English Version Spanish Version Adobe PDF Reader (Click icon for Adobe PDF Reader) Word: English Version Spanish Version MS Word Viewer (Click icon for MS Word Viewer) HTML: English Version Spanish Version NOAA
NASA Astrophysics Data System (ADS)
Khodayari, Arezoo; Wuebbles, Donald J.; Olsen, Seth C.; Fuglestvedt, Jan S.; Berntsen, Terje; Lund, Marianne T.; Waitz, Ian; Wolfe, Philip; Forster, Piers M.; Meinshausen, Malte; Lee, David S.; Lim, Ling L.
2013-08-01
This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air-sea and air-biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.
Cloud Radiation Forcings and Feedbacks: General Circulation Model Tests and Observational Validation
NASA Technical Reports Server (NTRS)
Lee,Wan-Ho; Iacobellis, Sam F.; Somerville, Richard C. J.
1997-01-01
Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.
The key role of dry days in changing regional climate and precipitation regimes
Polade, Suraj; Pierce, David W.; Cayan, Daniel R.; Gershunov, Alexander; Dettinger, Michael D.
2014-01-01
Future changes in the number of dry days per year can either reinforce or counteract projected increases in daily precipitation intensity as the climate warms. We analyze climate model projected changes in the number of dry days using 28 coupled global climate models from the Coupled Model Intercomparison Project, version 5 (CMIP5). We find that the Mediterranean Sea region, parts of Central and South America, and western Indonesia could experience up to 30 more dry days per year by the end of this century. We illustrate how changes in the number of dry days and the precipitation intensity on precipitating days combine to produce changes in annual precipitation, and show that over much of the subtropics the change in number of dry days dominates the annual changes in precipitation and accounts for a large part of the change in interannual precipitation variability.
2017-07-01
2017 to incorporate revised factors from the DEOMI Organizational Climate Survey (DEOCS) version 4.0 to version 4.1. This update primarily effects...begins with a survey , such as the DEOMI Organizational Climate Survey (DEOCS). Once survey themes, indicators, or concerns are identified, other...climate assessment to verify indicators and concerns identified through other assessment methods ( surveys , observations, and interviews
Psychometric Support for an Abbreviated Version of the California School Climate and Safety Survey
ERIC Educational Resources Information Center
Rebelez, Jennica L.; Furlong, Michael J.
2013-01-01
The California School Climate and Safety Survey-Short Form (CSCSS-SF) was developed as a streamlined version (54 items) of the original CSCSS (102 items) for school safety teams to gather information regarding student perceptions of campus climate, safety, and experience of victimization. Using a longitudinal dataset, this study implemented…
NASA Astrophysics Data System (ADS)
Zelazowski, Przemyslaw; Huntingford, Chris; Mercado, Lina M.; Schaller, Nathalie
2018-02-01
Global circulation models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in the rate of warming over land and across the globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper, we present a climate pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy-balance model that calculates the amount of global warming. The set, available for download, is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for the CMIP5 and forthcoming CMIP6 ensemble. Critically, it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impact studies. Across models, the presented climate patterns represent consistent global mean trends, with a maximum of 4 (out of 22) GCMs exhibiting the opposite sign to the global trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and have decreased relative humidity. Overall, when averaging individual performance across all variables, and without considering co-variance, the patterns explain one-third of regional change in decadal averages (mean percentage variance explained, PVE, 34.25 ± 5.21), but the signal in some models exhibits much more linearity (e.g. MIROC3.2(hires): 41.53) than in others (GISS_ER: 22.67). The two most often considered variables, near-surface temperature and precipitation, have a PVE of 85.44 ± 4.37 and 14.98 ± 4.61, respectively. We also provide an example assessment of a terrestrial impact (changes in mean runoff) and compare projections by the IMOGEN system, which has one land surface model, against direct GCM outputs, which all have alternative representations of land functioning. The latter is noted as an additional source of uncertainty. Finally, current and potential future applications of the IMOGEN version 2.0 modelling system in the areas of ecosystem modelling and climate change impact assessment are presented and discussed.
ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation Value-Added Product
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Chengzhu; Xie, Shaocheng
A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstratedmore » in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Min; Zhuang, Qianlai; Cook, D.
2011-08-31
Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. We first modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenologymore » and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000-2005 at a 0.05-0.05 spatial resolution. We find that the new version of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 PgC yr{sup -1} and net primary production (NPP) ranges from 3.81 to 4.38 Pg Cyr{sup -1} and net ecosystem production (NEP) varies within 0.08- 0.73 PgC yr{sup -1} over the period 2000-2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 PgC yr{sup -1} for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.« less
Göras, Camilla; Wallentin, Fan Yang; Nilsson, Ulrica; Ehrenberg, Anna
2013-03-19
Tens of millions of patients worldwide suffer from avoidable disabling injuries and death every year. Measuring the safety climate in health care is an important step in improving patient safety. The most commonly used instrument to measure safety climate is the Safety Attitudes Questionnaire (SAQ). The aim of the present study was to establish the validity and reliability of the translated version of the SAQ. The SAQ was translated and adapted to the Swedish context. The survey was then carried out with 374 respondents in the operating room (OR) setting. Data was received from three hospitals, a total of 237 responses. Cronbach's alpha and confirmatory factor analysis (CFA) was used to evaluate the reliability and validity of the instrument. The Cronbach's alpha values for each of the factors of the SAQ ranged between 0.59 and 0.83. The CFA and its goodness-of-fit indices (SRMR 0.055, RMSEA 0.043, CFI 0.98) showed good model fit. Intercorrelations between the factors safety climate, teamwork climate, job satisfaction, perceptions of management, and working conditions showed moderate to high correlation with each other. The factor stress recognition had no significant correlation with teamwork climate, perception of management, or job satisfaction. Therefore, the Swedish translation and psychometric testing of the SAQ (OR version) has good construct validity. However, the reliability analysis suggested that some of the items need further refinement to establish sound internal consistency. As suggested by previous research, the SAQ is potentially a useful tool for evaluating safety climate. However, further psychometric testing is required with larger samples to establish the psychometric properties of the instrument for use in Sweden.
A new framework for the analysis of continental-scale convection-resolving climate simulations
NASA Astrophysics Data System (ADS)
Leutwyler, D.; Charpilloz, C.; Arteaga, A.; Ban, N.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Schulthess, T. C.; Christoph, S.
2017-12-01
High-resolution climate simulations at horizontal resolution of O(1-4 km) allow explicit treatment of deep convection (thunderstorms and rain showers). Explicitly treating convection by the governing equations reduces uncertainties associated with parametrization schemes and allows a model formulation closer to physical first principles [1,2]. But kilometer-scale climate simulations with long integration periods and large computational domains are expensive and data storage becomes unbearably voluminous. Hence new approaches to perform analysis are required. In the crCLIM project we propose a new climate modeling framework that allows scientists to conduct analysis at high spatial and temporal resolution. We tackle the computational cost by using the largest available supercomputers such as hybrid CPU-GPU architectures. For this the COSMO model has been adapted to run on such architectures [2]. We then alleviate the I/O-bottleneck by employing a simulation data-virtualizer (SDaVi) that allows to trade-off storage (space) for computational effort (time). This is achieved by caching the simulation outputs and efficiently launching re-simulations in case of cache misses. All this is done transparently from the analysis applications [3]. For the re-runs this approach requires a bit-reproducible version of COSMO. That is to say a model that produces identical results on different architectures to ensure coherent recomputation of the requested data [4]. In this contribution we present a version of SDaVi, a first performance model, and a strategy to obtain bit-reproducibility across hardware architectures.[1] N. Ban, J. Schmidli, C. Schär. Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos., 7889-7907, 2014.[2] D. Leutwyler, O. Fuhrer, X. Lapillonne, D. Lüthi, C. Schär. Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19. Geosci. Model Dev, 3393-3412, 2016.[3] S. Di Girolamo, P. Schmid, T. Schulthess, T. Hoefler. Virtualized Big Data: Reproducing Simulation Output on Demand. Submit. to the 23rd ACM Symposium on PPoPP 18, Vienna, Austria.[4] A. Arteaga, O. Fuhrer, T. Hoefler. Designing Bit-Reproducible Portable High-Performance Applications. IEEE 28th IPDPS, 2014.
WRF-Cordex simulations for Europe: mean and extreme precipitation for present and future climates
NASA Astrophysics Data System (ADS)
Cardoso, Rita M.; Soares, Pedro M. M.; Miranda, Pedro M. A.
2013-04-01
The Weather Research and Forecast (WRF-ARW) model, version 3.3.1, was used to perform the European domain Cordex simulations, at 50km resolution. A first simulation, forced by ERA-Interim (1989-2009), was carried out to evaluate the models performance to represent the mean and extreme precipitation in present European climate. This evaluation is based in the comparison of WRF results against the ECAD regular gridded dataset of daily precipitation. Results are comparable to recent studies with other models for the European region, at this resolution. For the same domain a control and a future scenario (RCP8.5) simulation was performed to assess the climate change impact on the mean and extreme precipitation. These regional simulations were forced by EC-EARTH model results, and, encompass the periods from 1960-2006 and 2006-2100, respectively.
[Short Spanish version of Team Climate Inventory (TCI-14): development and psychometric properties].
Boada-Grau, Joan; de Diego-Vallejo, Raúl; de Llanos-Serra, Emma; Vigil-Colet, Andreu
2011-04-01
The aim of the present paper was to develop a Spanish adaptation of the reduced, 14-item version of the Team Climate Inventory (TCI-14), a questionnaire developed to evaluate team climate. To this end the English version was adapted and applied to a sample of 360 employees from Castilla-León and Catalonia (44.4% men and 55.6% women). The results indicated that the TCI-14 has the same structure as the original version, and confirmatory factor analysis was used to verify the existence of the factors Vision, Participative Safety, Task Orientation and Support for Innovation. The TCI-14 also presented good reliability coefficients considering the low number of items on each scale (alphas ranged between .75 and .82). The TCI-14 is a potentially useful instrument for evaluating the climate of work teams. It could be used by future research as a screening tool in conjunction with other instruments.
NASA Astrophysics Data System (ADS)
Asay-Davis, Xylar; Price, Stephen; Petersen, Mark; Wolfe, Jonathan
2017-04-01
The capability for simulating sub-ice shelf circulation and submarine melting and freezing has recently been added to the U.S. Department of Energy's Accelerated Climate Model for Energy (ACME). With this new capability, we use an eddy permitting ocean model to conduct two sets of simulations in the spirit of Spence et al. (GRL, 41, 2014), who demonstrate increased warm water upwelling along the Antarctic coast in response to poleward shifting and strengthening of Southern Ocean westerly winds. These characteristics, symptomatic of a positive Southern Annular Mode (SAM), are projected to continue into the 21st century under anthropogenic climate change (Fyfe et al., J. Clim., 20, 2007). In our first simulation, we force the climate model using the standard CORE interannual forcing dataset (Large and Yeager; Clim. Dyn., 33, 2009). In our second simulation, we force our climate model using an altered version of CORE interannual forcing, based on the latter half of the full time series, which we take as a proxy for a future climate state biased towards a positive SAM. We compare ocean model states and sub-ice shelf melt rates with observations, exploring sources of model biases as well as the effects of the two forcing scenarios.
NASA Astrophysics Data System (ADS)
Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier
2015-04-01
At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.
NASA Astrophysics Data System (ADS)
Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Huntingford, C.; Cox, P. M.
2011-09-01
The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.
On the stability of the Atlantic meridional overturning circulation.
Hofmann, Matthias; Rahmstorf, Stefan
2009-12-08
One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC.
The Community Earth System Model-Polar Climate Working Group and the status of CESM2.
NASA Astrophysics Data System (ADS)
Bailey, D. A.; Holland, M. M.; DuVivier, A. K.
2017-12-01
The Polar Climate Working Group (PCWG) is a consortium of scientists who are interested in modeling and understanding the climate in the Arctic and the Antarctic, and how polar climate processes interact with and influence climate at lower latitudes. Our members come from universities and laboratories, and our interests span all elements of polar climate, from the ocean depths to the top of the atmosphere. In addition to conducting scientific modeling experiments, we are charged with contributing to the development and maintenance of the state-of-the-art sea ice model component (CICE) used in the Community Earth System Model (CESM). A recent priority for the PCWG has been to come up with innovative ways to bring the observational and modeling communities together. This will allow for more robust validation of climate model simulations, the development and implementation of more physically-based model parameterizations, improved data assimilation capabilities, and the better use of models to design and implement field experiments. These have been informed by topical workshops and scientific visitors that we have hosted in these areas. These activities will be discussed and information on how the better integration of observations and models has influenced the new version of the CESM, which is due to be released in late 2017, will be provided. Additionally, we will address how enhanced interactions with the observational community will contribute to model developments and validation moving forward.
Dunne, John P.; John, Jasmin G.; Adcroft, Alistair J.; Griffies, Stephen M.; Hallberg, Robert W.; Shevalikova, Elena; Stouffer, Ronald J.; Cooke, William; Dunne, Krista A.; Harrison, Matthew J.; Krasting, John P.; Malyshev, Sergey L.; Milly, P.C.D.; Phillipps, Peter J.; Sentman, Lori A.; Samuels, Bonita L.; Spelman, Michael J.; Winton, Michael; Wittenberg, Andrew T.; Zadeh, Niki
2012-01-01
We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
LaRow, Timothy
The SSTs used in our study come from the Community Climate System Model version 4 (CCSM4) (Gent et al 2011) and from the Canadian Centre for Climate Modeling and Analysis (CanESM2) (Chylek et al20ll) climate models from the fifth Coupled Model Intercomparison Project (CMIP5) (Taylor et al2012). We've examined the tropical cyclones using both the historical simulation that employs volcanic and aerosol forcing as well as the representative concentration pathway 4.5 (RCP4.5). In addition, we've compared the present day North Atlantic tropical cyclone metrics from a previous study (LaRow, 2013) to these climate change experiments. The experimental setup is shownmore » in Table 1. We considered the CMIP5 experiment number '3.2 historical' (Taylor et al,201l), which provides simulations of the recent past (1850-2005). The second set of CMIP5 SSTs is the RCp4.5 experiment where the radiative forcing stabilizes at 45W m-2 after 2100 (experiment number 4.1 in Taylor etal2}ll).« less
A CLIMATE VERSION OF THE REGIONAL ATMOSPHERIC MODELING SYSTEM. (R824993)
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...
NASA Astrophysics Data System (ADS)
Ban, N.; Schmidli, J.; Schar, C.
2014-12-01
Reliable climate-change projections of extreme precipitation events are of great interest to decision makers, due to potentially important hydrological impacts such as floods, land slides and debris flows. Low-resolution climate models generally project increases of heavy precipitation events with climate change, but there are large uncertainties related to the limited spatial resolution and the parameterized representation of atmospheric convection. Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Comparison between 12 and 2km resolutions with parameterized and explicit convection, respectively, reveals close agreement in terms of mean summer precipitation amounts (decrease by 30%), and regarding slight increases of heavy day-long events (amounting to 15% for 90th-percentile for wet-day precipitation). However, the different resolutions yield large differences regarding extreme hourly precipitation, with the 2km version projecting substantially faster increases of heavy hourly precipitation events (about 30% increases for 90th-percentile hourly events). Ban, N., J. Schmidli and C. Schӓr (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478
Estimation of the global climate effect of brown carbon
NASA Astrophysics Data System (ADS)
Zhang, A.; Wang, Y.; Zhang, Y.; Weber, R. J.; Song, Y.
2017-12-01
Carbonaceous aerosols significantly affect global radiative forcing and climate through absorption and scattering of sunlight. Black carbon (BC) and brown carbon (BrC) are light-absorbing carbonaceous aerosols. The global distribution and climate effect of BrC is uncertain. A recent study suggests that BrC absorption is comparable to BC in the upper troposphere over biomass burning region and that the resulting heating tends to stabilize the atmosphere. Yet current climate models do not include proper treatments of BrC. In this study, we derived a BrC global biomass burning emission inventory from Global Fire Emissions Database 4 (GFED4) and developed a BrC module in the Community Atmosphere Model version 5 (CAM5) of Community Earth System Model (CESM) model. The model simulations compared well to BrC observations of the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry Project (DC-3) campaigns and includes BrC bleaching. Model results suggested that BrC in the upper troposphere due to convective transport is as important an absorber as BC globally. Upper tropospheric BrC radiative forcing is particularly significant over the tropics, affecting the atmosphere stability and Hadley circulation.
Version 2 Goddard Satellite-Based Surface Turbulent Fluxes (GSSTF2)
NASA Technical Reports Server (NTRS)
Chou, Shu-Hsien; Nelkin, Eric; Ardizzone, Joe; Atlas, Robert M.; Shie, Chung-Lin; Starr, David O'C. (Technical Monitor)
2002-01-01
Information on the turbulent fluxes of momentum, moisture, and heat at the air-sea interface is essential in improving model simulations of climate variations and in climate studies. We have derived a 13.5-year (July 1987-December 2000) dataset of daily surface turbulent fluxes over global oceans from the Special Sensor Mcrowave/Imager (SSM/I) radiance measurements. This dataset, version 2 Goddard Satellite-based Surface Turbulent Fluxes (GSSTF2), has a spatial resolution of 1 degree x 1 degree latitude-longitude and a temporal resolution of 1 day. Turbulent fluxes are derived from the SSM/I surface winds and surface air humidity, as well as the 2-m air and sea surface temperatures (SST) of the NCEP/NCAR reanalysis, using a bulk aerodynamic algorithm based on the surface layer similarity theory.
Multi-centennial upper-ocean heat content reconstruction using online data assimilation
NASA Astrophysics Data System (ADS)
Perkins, W. A.; Hakim, G. J.
2017-12-01
The Last Millennium Reanalysis (LMR) provides an advanced paleoclimate ensemble data assimilation framework for multi-variate climate field reconstructions over the Common Era. Although reconstructions in this framework with full Earth system models remain prohibitively expensive, recent work has shown improved ensemble reconstruction validation using computationally inexpensive linear inverse models (LIMs). Here we leverage these techniques in pursuit of a new multi-centennial field reconstruction of upper-ocean heat content (OHC), synthesizing model dynamics with observational constraints from proxy records. OHC is an important indicator of internal climate variability and responds to planetary energy imbalances. Therefore, a consistent extension of the OHC record in time will help inform aspects of low-frequency climate variability. We use the Community Climate System Model version 4 (CCSM4) and Max Planck Institute (MPI) last millennium simulations to derive the LIMs, and the PAGES2K v.2.0 proxy database to perform annually resolved reconstructions of upper-OHC, surface air temperature, and wind stress over the last 500 years. Annual OHC reconstructions and uncertainties for both the global mean and regional basins are compared against observational and reanalysis data. We then investigate differences in dynamical behavior at decadal and longer time scales between the reconstruction and simulations in the last-millennium Coupled Model Intercomparison Project version 5 (CMIP5). Preliminary investigation of 1-year forecast skill for an OHC-only LIM shows largely positive spatial grid point local anomaly correlations (LAC) with a global average LAC of 0.37. Compared to 1-year OHC persistence forecast LAC (global average LAC of 0.30), the LIM outperforms the persistence forecasts in the tropical Indo-Pacific region, the equatorial Atlantic, and in certain regions near the Antarctic Circumpolar Current. In other regions, the forecast correlations are less than the persistence case but still positive overall.
Assessment of the Breakup of the Antarctic Polar Vortex in Two New Chemistry-Climate Models
NASA Technical Reports Server (NTRS)
Hurwitz, M. M.; Newman, P. A.; Oman, L. D.; Li, F.; Morgenstern, O.; Braesicke, P.; Pyle, J. A.
2010-01-01
Successful simulation of the breakup of the Antarctic polar vortex depends on the representation of tropospheric stationary waves at Southern Hemisphere middle latitudes. This paper assesses the vortex breakup in two new chemistry-climate models (CCMs). The stratospheric version of the UK Chemistry and Aerosols model is able to reproduce the observed timing of the vortex breakup. Version 2 of the Goddard Earth Observing System (GEOS V2) model is typical of CCMs in that the Antarctic polar vortex breaks up too late; at 10 hPa, the mean transition to easterlies at 60 S is delayed by 12-13 days as compared with the ERA-40 and National Centers for Environmental Prediction reanalyses. The two models' skill in simulating planetary wave driving during the October-November period accounts for differences in their simulation of the vortex breakup, with GEOS V2 unable to simulate the magnitude and tilt of geopotential height anomalies in the troposphere and thus underestimating the wave driving. In the GEOS V2 CCM the delayed breakup of the Antarctic vortex biases polar temperatures and trace gas distributions in the upper stratosphere in November and December.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nair, Shyam; Hartley, Damon S; Hays, Ross D
LEAF Version 2.0 is a framework comprising of three models RUSLE2, WEPS, and AGNPS. The framework can predict row crop, crop residue, and energy crop yields at a sub-field resolutions for various combinations of soil, climate and crop management and residue harvesting practices. It estimates the loss of soil, carbon, and nutrients to the atmosphere, to the groundwater, and to runoff. It also models the overland flow of water and washed-off sediments, nutrients and other chemicals to provide estimates of sediment, nutrient, and chemical loadings to water bodies within a watershed. AGNPS model and wash-off calculations are the new additionsmore » to this version of LEAF. Development of LEAF software is supported by DOE's BETO program.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hoffman, Forrest M; Randerson, James T; Thornton, Peter E
2009-12-01
The need to capture important climate feedbacks in general circulation models (GCMs) has resulted in efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, called Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results (Friedlingstein et al., 2006). This work suggests that a more rigorous set of global offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are needed. The Carbon-Land Model Intercomparison Projectmore » (C-LAMP) was designed to meet this need by providing a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). Recently, a similar effort in Europe, called the International Land Model Benchmark (ILAMB) Project, was begun to assess the performance of European land surface models. These two projects will now serve as prototypes for a proposed international land-biosphere model benchmarking activity for those models participating in the IPCC Fifth Assessment Report (AR5). Initially used for model validation for terrestrial biogeochemistry models in the NCAR Community Land Model (CLM), C-LAMP incorporates a simulation protocol for both offline and partially coupled simulations using a prescribed historical trajectory of atmospheric CO2 concentrations. Models are confronted with data through comparisons against AmeriFlux site measurements, MODIS satellite observations, NOAA Globalview flask records, TRANSCOM inversions, and Free Air CO2 Enrichment (FACE) site measurements. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the CLM version 3 in the Community Climate System Model version 3 (CCSM3): the CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons of the CLM3 offline results against observational datasets have been performed and are described in Randerson et al. (2009). CLM version 4 has been evaluated using C-LAMP, showing improvement in many of the metrics. Efforts are now underway to initiate a Nitrogen-Land Model Intercomparison Project (N-LAMP) to better constrain the effects of the nitrogen cycle in biosphere models. Presented will be new results from C-LAMP for CLM4, initial N-LAMP developments, and the proposed land-biosphere model benchmarking activity.« less
NASA Technical Reports Server (NTRS)
Putnam, WilliamM.
2011-01-01
In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.
Surface Winds and Dust Biases in Climate Models
NASA Astrophysics Data System (ADS)
Evan, A. T.
2018-01-01
An analysis of North African dust from models participating in the Fifth Climate Models Intercomparison Project (CMIP5) suggested that, when forced by observed sea surface temperatures, these models were unable to reproduce any aspects of the observed year-to-year variability in dust from North Africa. Consequently, there would be little reason to have confidence in the models' projections of changes in dust over the 21st century. However, no subsequent study has elucidated the root causes of the disagreement between CMIP5 and observed dust. Here I develop an idealized model of dust emission and then use this model to show that, over North Africa, such biases in CMIP5 models are due to errors in the surface wind fields and not due to the representation of dust emission processes. These results also suggest that because the surface wind field over North Africa is highly spatially autocorrelated, intermodel differences in the spatial structure of dust emission have little effect on the relative change in year-to-year dust emission over the continent. I use these results to show that similar biases in North African dust from the NASA Modern Era Retrospective analysis for Research and Applications (MERRA) version 2 surface wind field biases but that these wind biases were not present in the first version of MERRA.
Dominique Bachelet; James M. Lenihan; Christopher Daly; Ronald P. Neilson; Dennis S. Ojima; William J. Parton
2001-01-01
Assessments of vegetation response to climate change have generally been made only by equilibrium vegetation models that predict vegetation composition under steady-state conditions. These models do not simulate either ecosystem biogeochemical processes or changes in ecosystem structure that may, in turn, act as feedbacks in determining the dynamics of vegetation...
Response of the tropical Pacific to abrupt climate change 8,200 years ago
NASA Astrophysics Data System (ADS)
Atwood, A. R.; Battisti, D.; Bitz, C. M.; Sachs, J. P.
2017-12-01
The relatively stable climate of the Holocene epoch was punctuated by a period of large and abrupt climate change ca. 8,200 yr BP, when an outburst of glacial meltwater into the Labrador Sea drove large and abrupt climate changes across the globe. However, little is known about the response of the tropical Pacific to this event. We present the first evidence for large perturbations to the eastern tropical Pacific climate, based on sedimentary biomarker and hydrogen isotopic records from a freshwater lake in the Galápagos Islands. We inform these reconstructions with freshwater forcing simulations performed with the Community Climate System Model version 4. Together, the biomarker records and model simulations provide evidence for a mechanistic link between (1) a southward shift of the Intertropical Convergence Zone in the eastern equatorial Pacific and (2) decreased frequency and/or intensity of Eastern Pacific El Niño events during the 8,200 BP event. While climate theory and modeling studies support a southward shift of the ITCZ in response to a weakened AMOC, the dynamical drivers for the observed change in ENSO variability are less well developed. To explore these linkages, we perform simulations with an intermediate complexity model of the tropical Pacific. These results provide valuable insight into the controls of tropical Pacific climate variability and the mechanisms behind the global response to abrupt climate change.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Prather, Michael
This proposal seeks to maintain the DOE-ACME (offshoot of CESM) as one of the leading CCMs to evaluate near-term climate mitigation. It will implement, test, and optimize the new UCI photolysis codes within CESM CAM5 and new CAM versions in ACME. Fast-J is a high-order-accuracy (8 stream) code for calculating solar scattering and absorption in a single column atmosphere containing clouds, aerosols, and gases that was developed at UCI and implemented in CAM5 under the previous BER/SciDAC grant.
Increasing water cycle extremes in California and relation to ENSO cycle under global warming
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yoon, Jin -Ho; Wang, S. -Y. Simon; Gillies, Robert R.
California has experienced its most severe drought in recorded history since the winter of 2013-2014. The long duration of drought has stressed statewide water resources and the economy, while fueling an extraordinary increase in wildfires. The effects of global warming on the regional climate include a hotter and drier climate, as well as earlier snowmelt, both of which exacerbate drought conditions. However, connections between a changing climate and how climate oscillations modulate regional water cycle extremes are not well understood. Here we analyze large-ensemble simulations of future climate change in California using the Community Earth System Model version 1 (CESM1)more » and multiple climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both intense drought and excessive flooding are projected to increase by at least 50% toward the end of the 21st century. Furthermore, the projected increase in water cycle extremes is associated with tighter relation to El Niño and Southern Oscillation (ENSO), particularly extreme El Niño and La Niña events, which modulates California’s climate not only through its warm and cold phases, but also ENSO’s precursor patterns.« less
Increasing water cycle extremes in California and relation to ENSO cycle under global warming
Yoon, Jin -Ho; Wang, S. -Y. Simon; Gillies, Robert R.; ...
2015-10-21
California has experienced its most severe drought in recorded history since the winter of 2013-2014. The long duration of drought has stressed statewide water resources and the economy, while fueling an extraordinary increase in wildfires. The effects of global warming on the regional climate include a hotter and drier climate, as well as earlier snowmelt, both of which exacerbate drought conditions. However, connections between a changing climate and how climate oscillations modulate regional water cycle extremes are not well understood. Here we analyze large-ensemble simulations of future climate change in California using the Community Earth System Model version 1 (CESM1)more » and multiple climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both intense drought and excessive flooding are projected to increase by at least 50% toward the end of the 21st century. Furthermore, the projected increase in water cycle extremes is associated with tighter relation to El Niño and Southern Oscillation (ENSO), particularly extreme El Niño and La Niña events, which modulates California’s climate not only through its warm and cold phases, but also ENSO’s precursor patterns.« less
NASA Astrophysics Data System (ADS)
Goderniaux, Pascal; BrouyèRe, Serge; Blenkinsop, Stephen; Burton, Aidan; Fowler, Hayley J.; Orban, Philippe; Dassargues, Alain
2011-12-01
Several studies have highlighted the potential negative impact of climate change on groundwater reserves, but additional work is required to help water managers plan for future changes. In particular, existing studies provide projections for a stationary climate representative of the end of the century, although information is demanded for the near future. Such time-slice experiments fail to account for the transient nature of climatic changes over the century. Moreover, uncertainty linked to natural climate variability is not explicitly considered in previous studies. In this study we substantially improve upon the state-of-the-art by using a sophisticated transient weather generator in combination with an integrated surface-subsurface hydrological model (Geer basin, Belgium) developed with the finite element modeling software "HydroGeoSphere." This version of the weather generator enables the stochastic generation of large numbers of equiprobable climatic time series, representing transient climate change, and used to assess impacts in a probabilistic way. For the Geer basin, 30 equiprobable climate change scenarios from 2010 to 2085 have been generated for each of six different regional climate models (RCMs). Results show that although the 95% confidence intervals calculated around projected groundwater levels remain large, the climate change signal becomes stronger than that of natural climate variability by 2085. Additionally, the weather generator's ability to simulate transient climate change enabled the assessment of the likely time scale and associated uncertainty of a specific impact, providing managers with additional information when planning further investment. This methodology constitutes a real improvement in the field of groundwater projections under climate change conditions.
Water Isotopes in the GISS GCM: History, Applications and Potential
NASA Astrophysics Data System (ADS)
Schmidt, G. A.; LeGrande, A. N.; Field, R. D.; Nusbaumer, J. M.
2017-12-01
Water isotopes have been incorporated in the GISS GCMs since the pioneering work of Jean Jouzel in the 1980s. Since 2005, this functionality has been maintained within the master branch of the development code and has been usable (and used) in all subsequent versions. This has allowed a wide variety of applications, across multiple time-scales and interests, to be tackled coherently. Water isotope tracers have been used to debug the atmospheric model code, tune parameterisations of moist processes, assess the isotopic fingerprints of multiple climate drivers, produce forward models for remotely sensed isotope products, and validate paleo-climate interpretations from the last millennium to the Eocene. We will present an overview of recent results involving isotope tracers, including improvements in models for the isotopic fractionation processes themselves, and demonstrate the potential for using these tracers and models more systematically in paleo-climate reconstructions and investigations of the modern hydrological cycle.
Impacts of Climate Change on Biofuels Production
DOE Office of Scientific and Technical Information (OSTI.GOV)
Melillo, Jerry M.
2014-04-30
The overall goal of this research project was to improve and use our biogeochemistry model, TEM, to simulate the effects of climate change and other environmental changes on the production of biofuel feedstocks. We used the improved version of TEM that is coupled with the economic model, EPPA, a part of MIT’s Earth System Model, to explore how alternative uses of land, including land for biofuels production, can help society meet proposed climate targets. During the course of this project, we have made refinements to TEM that include development of a more mechanistic plant module, with improved ecohydrology and considerationmore » of plant-water relations, and a more detailed treatment of soil nitrogen dynamics, especially processes that add or remove nitrogen from ecosystems. We have documented our changes to TEM and used the model to explore the effects on production in land ecosystems, including changes in biofuels production.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.
Changes in the character of rainfall are assessed using a holistic set of statistics based on rainfall frequency and amount distributions in climate change experiments with three conventional and superparameterized versions of the Community Atmosphere Model (CAM and SPCAM). Previous work has shown that high-order statistics of present-day rainfall intensity are significantly improved with superparameterization, especially in regions of tropical convection. Globally, the two modeling approaches project a similar future increase in mean rainfall, especially across the Inter-Tropical Convergence Zone (ITCZ) and at high latitudes, but over land, SPCAM predicts a smaller mean change than CAM. Changes in high-order statisticsmore » are similar at high latitudes in the two models but diverge at lower latitudes. In the tropics, SPCAM projects a large intensification of moderate and extreme rain rates in regions of organized convection associated with the Madden Julian Oscillation, ITCZ, monsoons, and tropical waves. In contrast, this signal is missing in all versions of CAM, which are found to be prone to predicting increases in the amount but not intensity of moderate rates. Predictions from SPCAM exhibit a scale-insensitive behavior with little dependence on horizontal resolution for extreme rates, while lower resolution (~2°) versions of CAM are not able to capture the response simulated with higher resolution (~1°). Furthermore, moderate rain rates analyzed by the “amount mode” and “amount median” are found to be especially telling as a diagnostic for evaluating climate model performance and tracing future changes in rainfall statistics to tropical wave modes in SPCAM.« less
Updates to the Demographic and Spatial Allocation Models to ...
EPA's announced the availability of the final report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Version 2). This update furthered land change modeling by providing nationwide housing development scenarios up to 2100. This newest version includes updated population and land use data sets and addresses limitations identified in ICLUS v1 in both the migration and spatial allocation models. The companion user guide (Final Report) describes the development of ICLUS v2 and the updates that were made to the original data sets and the demographic and spatial allocation models. The GIS tool enables users to run SERGoM with the population projections developed for the ICLUS project and allows users to modify the spatial allocation housing density across the landscape.
Regional climate modeling over the Maritime Continent: Assessment of RegCM3-BATS1e and RegCM3-IBIS
NASA Astrophysics Data System (ADS)
Gianotti, R. L.; Zhang, D.; Eltahir, E. A.
2010-12-01
Despite its importance to global rainfall and circulation processes, the Maritime Continent remains a region that is poorly simulated by climate models. Relatively few studies have been undertaken using a model with fine enough resolution to capture the small-scale spatial heterogeneity of this region and associated land-atmosphere interactions. These studies have shown that even regional climate models (RCMs) struggle to reproduce the climate of this region, particularly the diurnal cycle of rainfall. This study builds on previous work by undertaking a more thorough evaluation of RCM performance in simulating the timing and intensity of rainfall over the Maritime Continent, with identification of major sources of error. An assessment was conducted of the Regional Climate Model Version 3 (RegCM3) used in a coupled system with two land surface schemes: Biosphere Atmosphere Transfer System Version 1e (BATS1e) and Integrated Biosphere Simulator (IBIS). The model’s performance in simulating precipitation was evaluated against the 3-hourly TRMM 3B42 product, with some validation provided of this TRMM product against ground station meteorological data. It is found that the model suffers from three major errors in the rainfall histogram: underestimation of the frequency of dry periods, overestimation of the frequency of low intensity rainfall, and underestimation of the frequency of high intensity rainfall. Additionally, the model shows error in the timing of the diurnal rainfall peak, particularly over land surfaces. These four errors were largely insensitive to the choice of boundary conditions, convective parameterization scheme or land surface scheme. The presence of a wet or dry bias in the simulated volumes of rainfall was, however, dependent on the choice of convection scheme and boundary conditions. This study also showed that the coupled model system has significant error in overestimation of latent heat flux and evapotranspiration from the land surface, and specifically overestimation of interception loss with concurrent underestimation of transpiration, irrespective of the land surface scheme used. Discussion of the origin of these errors is provided, with some suggestions for improvement.
Fong, Ted Chun-tat; Ng, Siu-man
2012-09-01
Work engagement is a positive work-related state of fulfillment characterized by vigor, dedication, and absorption. Previous studies have operationalized the construct through development of the Utrecht Work Engagement Scale. Apart from the original three-factor 17-item version of the instrument (UWES-17), there exists a nine-item shortened revised version (UWES-9). The current study explored the psychometric properties of the Chinese version of the Utrecht Work Engagement Scale in terms of factorial validity, scale reliability, descriptive statistics, and construct validity. A cross-sectional questionnaire survey was conducted in 2009 among 992 workers from over 30 elderly service units in Hong Kong. Confirmatory factor analyses revealed a better fit for the three-factor model of the UWES-9 than the UWES-17 and the one-factor model of the UWES-9. The three factors showed acceptable internal consistency and strong correlations with factors in the original versions. Engagement was negatively associated with perceived stress and burnout while positively with age and holistic care climate. The UWES-9 demonstrates adequate psychometric properties, supporting its use in future research in the Chinese context.
A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models
NASA Technical Reports Server (NTRS)
Geller, Marvin A.; Alexadner, M. Joan; Love, Peter T.; Bacmeister, Julio; Ern, Manfred; Hertzog, Albert; Manzini, Elisa; Preusse, Peter; Sato, Kaoru; Scaife, Adam A.;
2013-01-01
For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.
Simulation of tropospheric ozone with MOZART-2: An evaluation study over East Asia
NASA Astrophysics Data System (ADS)
Liu, Qianxia; Zhang, Meigen; Wang, Bin
2005-07-01
Climate changes induced by human activities have attracted a great amount of attention. With this, a coupling system of an atmospheric chemistry model and a climate model is greatly needed in China for better understanding the interaction between atmospheric chemical components and the climate. As the first step to realize this coupling goal, the three-dimensional global atmospheric chemistry transport model MOZART-2 (the global Model of Ozone and Related Chemical Tracers, version 2) coupled with CAM2 (the Community Atmosphere Model, version 2) is set up and the model results are compared against observations obtained in East Asia in order to evaluate the model performance. Comparison of simulated ozone mixing ratios with ground level observations at Minamitorishima and Ryori and with ozonesonde data at Naha and Tateno in Japan shows that the observed ozone concentrations can be reproduced reasonably well at Minamitorishima but they tend to be slightly overestimated in winter and autumn while underestimated a little in summer at Ryori. The model also captures the general features of surface CO seasonal variations quite well, while it underestimates CO levels at both Minamitorishima and Ryori. The underestimation is primarily associated with the emission inventory adopted in this study. Compared with the ozonesonde data, the simulated vertical gradient and magnitude of ozone can be reasonably well simulated with a little overestimation in winter, especially in the upper troposphere. The model also generally captures the seasonal, latitudinal and altitudinal variations in ozone concentration. Analysis indicates that the underestimation of tropopause height in February contributes to the overestimation of winter ozone in the upper and middle troposphere at Tateno.
NASA Astrophysics Data System (ADS)
Booth, B.; Collins, M.; Harris, G.; Chris, H.; Jones, C.
2007-12-01
A number of recent studies have highlighted the risk of abrupt dieback of the Amazon Rain Forest as the result of climate changes over the next century. The recent 2005 Amazon drought brought wider acceptance of the idea that that climate drivers will play a significant role in future rain forest stability, yet that stability is still subject to considerable degree of uncertainty. We present a study which seeks to explore some of the underlying uncertainties both in the climate drivers of dieback and in the terrestrial land surface formulation used in GCMs. We adopt a perturbed physics approach which forms part of a wider project which is covered in an accompanying abstract submitted to the multi-model ensembles session. We first couple the same interactive land surface model to a number of different versions of the Hadley Centre atmosphere-ocean model that exhibit a wide range of different physical climate responses in the future. The rainforest extent is shown to collapse in all model cases but the timing of the collapse is dependent on the magnitude of the climate drivers. In the second part, we explore uncertainties in the terrestrial land surface model using the perturbed physics ensemble approach, perturbing uncertain parameters which have an important role in the vegetation and soil response. Contrasting the two approaches enables a greater understanding of the relative importance of climatic and land surface model uncertainties in Amazon dieback.
Flexible Environments for Grand-Challenge Simulation in Climate Science
NASA Astrophysics Data System (ADS)
Pierrehumbert, R.; Tobis, M.; Lin, J.; Dieterich, C.; Caballero, R.
2004-12-01
Current climate models are monolithic codes, generally in Fortran, aimed at high-performance simulation of the modern climate. Though they adequately serve their designated purpose, they present major barriers to application in other problems. Tailoring them to paleoclimate of planetary simulations, for instance, takes months of work. Theoretical studies, where one may want to remove selected processes or break feedback loops, are similarly hindered. Further, current climate models are of little value in education, since the implementation of textbook concepts and equations in the code is obscured by technical detail. The Climate Systems Center at the University of Chicago seeks to overcome these limitations by bringing modern object-oriented design into the business of climate modeling. Our ultimate goal is to produce an end-to-end modeling environment capable of configuring anything from a simple single-column radiative-convective model to a full 3-D coupled climate model using a uniform, flexible interface. Technically, the modeling environment is implemented as a Python-based software component toolkit: key number-crunching procedures are implemented as discrete, compiled-language components 'glued' together and co-ordinated by Python, combining the high performance of compiled languages and the flexibility and extensibility of Python. We are incrementally working towards this final objective following a series of distinct, complementary lines. We will present an overview of these activities, including PyOM, a Python-based finite-difference ocean model allowing run-time selection of different Arakawa grids and physical parameterizations; CliMT, an atmospheric modeling toolkit providing a library of 'legacy' radiative, convective and dynamical modules which can be knitted into dynamical models, and PyCCSM, a version of NCAR's Community Climate System Model in which the coupler and run-control architecture are re-implemented in Python, augmenting its flexibility and adaptability.
William Massman
2015-01-01
Increased use of prescribed fire by land managers and the increasing likelihood of wildfires due to climate change require an improved modeling capability of extreme heating of soils during fires. This issue is addressed here by developing and testing the soil (heat-moisture-vapor) HMVmodel, a 1-D (one-dimensional) non-equilibrium (liquid- vapor phase change)...
Potential climatic impacts of vegetation change: A regional modeling study
NASA Astrophysics Data System (ADS)
Copeland, Jeffrey H.; Pielke, Roger A.; Kittel, Timothy G. F.
1996-03-01
The human species has been modifying the landscape long before the development of modern agrarian techniques. Much of the land area of the conterminous United States is currently used for agricultural production. In certain regions this change in vegetative cover from its natural state may have led to local climatic change. A regional climate version of the Colorado State University Regional Atmospheric Modeling System was used to assess the impact of a natural versus current vegetation distribution on the weather and climate of July 1989. The results indicate that coherent regions of substantial changes, of both positive and negative sign, in screen height temperature, humidity, wind speed, and precipitation are a possible consequence of land use change throughout the United States. The simulated changes in the screen height quantities were closely related to changes in the vegetation parameters of albedo, roughness length, leaf area index, and fractional coverage.
Potential climatic impacts of vegetation change: A regional modeling study
Copeland, J.H.; Pielke, R.A.; Kittel, T.G.F.
1996-01-01
The human species has been modifying the landscape long before the development of modern agrarian techniques. Much of the land area of the conterminous United States is currently used for agricultural production. In certain regions this change in vegetative cover from its natural state may have led to local climatic change. A regional climate version of the Colorado State University Regional Atmospheric Modeling System was used to assess the impact of a natural versus current vegetation distribution on the weather and climate of July 1989. The results indicate that coherent regions of substantial changes, of both positive and negative sign, in screen height temperature, humidity, wind speed, and precipitation are a possible consequence of land use change throughout the United States. The simulated changes in the screen height quantities were closely related to changes in the vegetation parameters of albedo, roughness length, leaf area index, and fractional coverage. Copyright 1996 by the American Geophysical Union.
Psychometric evaluation of the Arabic language person-centred climate questionnaire-staff version.
Aljuaid, Mohammed; Elmontsri, Mustafa; Edvardsson, David; Rawaf, Salman; Majeed, Azeem
2018-05-01
To evaluate the psychometric properties of the Arabic language person-centred climate questionnaire-staff version. There have been increasing calls for a person-centred rather than a disease-centred approach to health care. A limited number of tools measure the extent to which care is delivered in a person-centred manner, and none of these tools have been validated for us in Arab settings. The validated form of the person-centred climate questionnaire-staff version was translated into Arabic and distributed to 152 health care staff in teaching and non-teaching hospitals in Saudi Arabia. Statistical estimates of validity and reliability were used for psychometric evaluation. Items on the Arabic form of the person-centred climate questionnaire-staff version had high reliability (Cronbach's alpha .98). Cronbach's alpha values for the three sub-scales (safety, everydayness and community), were .96, .97 and .95 respectively. Internal consistency was also high and measures of validity were very good. Arabic form of the person-centred climate questionnaire-staff version provides a valid and reliable way to measure the degree of perceived person-centredness. The tool can be used for comparing levels of person-centredness between wards, units, and public and private hospitals. The tool can also be used to measure the extent of person-centredness in health care settings in other Arab countries. © 2017 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Varentsov, Mikhail; Wouters, Hendrik; Trusilova, Kristina; Samsonov, Timofey; Konstantinov, Pavel
2017-04-01
In this study we present the application of the regional climate model COSMO-CLM to simulate urban heat island (UHI) phenomenon for Moscow megacity, which is the biggest agglomeration in Europe (with modern population of more than 17 million people). Significant differences of Moscow from the cities of Western Europe are related with much more continental climate with higher diurnal and annual temperature variations, and with specific building features such as its high density and almost total predominance of high-rise and low-rise blocks of flats on the private low-rise houses. Because of these building and climate features, the UHI of Moscow megacity is stronger than UHIs of many other cities of the similar size, with a mean intensity is about 2 °C and maximum intensity reaching up to 13 °C (Lokoschenko, 2014). Such a pronounced UHI together with the existence of an extensive observation network (more than 50 weather and air quality monitoring stations and few microwave temperature profilers) within the city and its surrounding make Moscow an especially interesting place for urban climate researches and good testbed for urban canopy models. In our numerical experiments, regional climate model firstly was adapted for investigated region with aim to improve quality of its simulations of rural areas. Then, to take into account urban canopy effects on thermal regime of the urbanized areas, we used two different versions of COSMO-CLM model. First is coupled with TEB (Town Energy Balance) single layer urban canopy model (Trusilova, 2013), and second is extended with bulk urban canopy scheme TERRA_URB using the Semi-empircal URban-canopY dependency parametriation SURY (Wouters et. al, 2016). Numerical experiments with these two versions of the model were run with spatial resolution about 1 km for several summer and winter months. To provide specific parameters, required for urban parameterizations, such as urban fraction, building height and street canyon aspect ratio, we used originally technology of GIS-based processing of realistic OpenStreetMap data, which includes size and shape of the most of the in the city (Samsonov et al., 2015). Our testbed allows to make more detailed comparison between the modelling approaches, and also reveals the importance of correct definition of the of turbulent mixing in the ABL in the atmospheric model, and the realistic specification of the building morphology parameters and anthropogenic heat fluxes. In addition, strong seasonal variation of the importance of different factors, responsible for UHI appearance, was shown. Moreover, the framework allows to identify and solve issues regarding the different model approaches: detailed analysis of spatial and temporal variations of modelled urban temperature anomalies and their vertical extent has shown that version of COSMO-CLM model with TERRA-URB scheme simulate UHI effect in more realistic way. Research was supported by Russian Foundation for Basic Research (RFBR) and Russian Geographic Society (RGS): RFBR projects № 16-35-00474, 15-35-21129 and 16-05-00704 A, RGS-RFBR project № 13-05-41306. References: 1. Lokoshchenko, M. A. (2014). Urban 'heat island' in Moscow. Urban Climate, 10, 550-562. 2. Samsonov, T. E., Konstantinov, P. I., & Varentsov, M. I. (2015). Object-oriented approach to urban canyon analysis and its applications in meteorological modeling. Urban Climate, 13, 122-139. 3. Trusilova K., Früh, B., Brienen, S., Walter, A., Masson, V., Pigeon, G., Becker, P. Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM// Journal of Applied Meteorology and Climatology. 2013. Vol. 52. P. 2296-2311. 4. Wouters, H., Demuzere, M., Blahak, U., Fortuniak, K., Maiheu, B., Camps, J., & van Lipzig, N. P. (2016). The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer. Geoscientific Model Development, 9(9), 3027-3054.
Assessment of the simulated climate in two versions of the RegT-Band
NASA Astrophysics Data System (ADS)
da Rocha, Rosmeri; Reboita, Michelle; Llopart, Marta
2017-04-01
This study evaluates two simulations carried out with the tropical band version of the Regional Climate Model (RegT-Band). The purpose was to compare the performance of the RegCM 4.4.5 and 4.6 versions (RegT4.4.5 and RegT4.6). The domain used in the simulations extends from 45° S to 45° N and covers all tropical longitudes, with grid spacing of 39 km, 18 sigma-pressure vertical levels. The initial and boundary conditions for the simulations were provided by ERA-Interim reanalysis and the analyzed period is from January 2005 to December 2008. Regarding the physical parameterizations schemes were used the Emanuel scheme to solve cumulus convection and Community Land Model version 4.5 (CLM4.5) to surface-atmosphere interactions. Seasonal simulated precipitation was compared with Global Precipitation Climatology Project (GPCP) while 2 meters air temperature with ERA-Interim reanalysis. The main results of this study are that RegT4.6 reduces the wet bias over the oceans and the cold bias over the continents compared with RegT4.4.5. In austral summer, RegT4.6 improves the simulation reducing the precipitation amounts mainly over Indian Ocean, Indonesia and eastern northeastern Brazil. However, both versions underestimate the precipitation over the South America Convergence Zone (SACZ). During the austral winter, RegT4.6 simulates the precipitation similar to GPCP over India and it reduces the cold bias over this country compared with RegT4.4.5. However, over the South of Africa, Australia and central-southeast South America, RegT4.6 simulates a strong warm bias.
NASA Astrophysics Data System (ADS)
Yu, Jianjun; Berry, Pam
2017-04-01
The drought and heat stress has alerted the composition, structure and biogeography of forests globally, whilst the projected severe and widespread droughts are potentially increasing. This challenges the sustainable forest management to better cope with future climate and maintain the forest ecosystem functions and services. Many studies have investigated the climate change impacts on forest ecosystem but less considered the climate extremes like drought. In this study, we implement a dynamic ecosystem model based on a version of LPJ-GUESS parameterized with European tree species and apply to Great Britain at a finer spatial resolution of 5*5 km. The model runs for the baseline from 1961 to 2011 and projects to the latter 21st century using 100 climate scenarios generated from MaRIUS project to tackle the climate model uncertainty. We will show the potential impacts of climate change on forest ecosystem and vegetation transition in Great Britain by comparing the modelled conditions in the 2030s and the 2080s relative to the baseline. In particular, by analyzing the modelled tree mortality, we will show the tree dieback patterns in response to drought for various species, and assess their drought vulnerability across Great Britain. We also use species distribution modelling to project the suitable climate space for selected tree species using the same climate scenarios. Aided by these two modelling approaches and based on the corresponding modelling results, we will discuss the implications for adaptation strategy for forest management, especially in extreme drought conditions. The gained knowledge and lessons for Great Britain are considered to be transferable in many other regions.
Climate change projections for Greek viticulture as simulated by a regional climate model
NASA Astrophysics Data System (ADS)
Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos
2017-07-01
Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production.
A Generalized Framework for Non-Stationary Extreme Value Analysis
NASA Astrophysics Data System (ADS)
Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.
2017-12-01
Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA accessible to a broader audience.
NASA Astrophysics Data System (ADS)
Legget, J.; Pepper, W.; Sankovski, A.; Smith, J.; Tol, R.; Wigley, T.
2003-04-01
Potential risks of human-induced climate change are subject to a three-fold uncertainty associated with: the extent of future anthropogenic and natural GHG emissions; global and regional climatic responses to emissions; and impacts of climatic changes on economies and the biosphere. Long-term analyses are also subject to uncertainty regarding how humans will respond to actual or perceived changes, through adaptation or mitigation efforts. Explicitly addressing these uncertainties is a high priority in the scientific and policy communities Probabilistic modeling is gaining momentum as a technique to quantify uncertainties explicitly and use decision analysis techniques that take advantage of improved risk information. The Climate Change Risk Assessment Framework (CCRAF) presented here a new integrative tool that combines the probabilistic approaches developed in population, energy and economic sciences with empirical data and probabilistic results of climate and impact models. The main CCRAF objective is to assess global climate change as a risk management challenge and to provide insights regarding robust policies that address the risks, by mitigating greenhouse gas emissions and by adapting to climate change consequences. The CCRAF endogenously simulates to 2100 or beyond annual region-specific changes in population; GDP; primary (by fuel) and final energy (by type) use; a wide set of associated GHG emissions; GHG concentrations; global temperature change and sea level rise; economic, health, and biospheric impacts; costs of mitigation and adaptation measures and residual costs or benefits of climate change. Atmospheric and climate components of CCRAF are formulated based on the latest version of Wigley's and Raper's MAGICC model and impacts are simulated based on a modified version of Tol's FUND model. The CCRAF is based on series of log-linear equations with deterministic and random components and is implemented using a Monte-Carlo method with up to 5000 variants per set of fixed input parameters. The shape and coefficients of CCRAF equations are derived from regression analyses of historic data and expert assessments. There are two types of random components in CCRAF - one reflects a year-to-year fluctuations around the expected value of a given variable (e.g., standard error of the annual GDP growth) and another is fixed within each CCRAF variant and represents some essential constants within a "world" represented by that variant (e.g., the value of climate sensitivity). Both types of random components are drawn from pre-defined probability distributions functions developed based on historic data or expert assessments. Preliminary CCRAF results emphasize the relative importance of uncertainties associated with the conversion of GHG and particulate emissions into radiative forcing and quantifying climate change effects at the regional level. A separates analysis involves an "adaptive decision-making", which optimizes the expected future policy effects given the estimated probabilistic uncertainties. As uncertainty for some variables evolve over the time steps, the decisions also adapt. This modeling approach is feasible only with explicit modeling of uncertainties.
Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J
2013-10-28
Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.
GFDL's CM2 global coupled climate models. Part I: Formulation and simulation characteristics
Delworth, T.L.; Broccoli, A.J.; Rosati, A.; Stouffer, R.J.; Balaji, V.; Beesley, J.A.; Cooke, W.F.; Dixon, K.W.; Dunne, J.; Dunne, K.A.; Durachta, J.W.; Findell, K.L.; Ginoux, P.; Gnanadesikan, A.; Gordon, C.T.; Griffies, S.M.; Gudgel, R.; Harrison, M.J.; Held, I.M.; Hemler, R.S.; Horowitz, L.W.; Klein, S.A.; Knutson, T.R.; Kushner, P.J.; Langenhorst, A.R.; Lee, H.-C.; Lin, S.-J.; Lu, J.; Malyshev, S.L.; Milly, P.C.D.; Ramaswamy, V.; Russell, J.; Schwarzkopf, M.D.; Shevliakova, E.; Sirutis, J.J.; Spelman, M.J.; Stern, W.F.; Winton, M.; Wittenberg, A.T.; Wyman, B.; Zeng, F.; Zhang, R.
2006-01-01
The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved. Tw o versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2?? latitude ?? 2.5?? longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1?? in latitude and longitude, with meridional resolution equatorward of 30?? becoming progressively finer, such that the meridional resolution is 1/3?? at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments. The co ntrol simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic. Both models have be en used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO2. The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/). ?? 2006 American Meteorological Society.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.
This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 x 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmentalmore » Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation’s performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.« less
Compressing climate model simulations: reducing storage burden while preserving information
NASA Astrophysics Data System (ADS)
Hammerling, Dorit; Baker, Allison; Xu, Haiying; Clyne, John; Li, Samuel
2017-04-01
Climate models, which are run at high spatial and temporal resolutions, generate massive quantities of data. As our computing capabilities continue to increase, storing all of the generated data is becoming a bottleneck, which negatively affects scientific progress. It is thus important to develop methods for representing the full datasets by smaller compressed versions, which still preserve all the critical information and, as an added benefit, allow for faster read and write operations during analysis work. Traditional lossy compression algorithms, as for example used for image files, are not necessarily ideally suited for climate data. While visual appearance is relevant, climate data has additional critical features such as the preservation of extreme values and spatial and temporal gradients. Developing alternative metrics to quantify information loss in a manner that is meaningful to climate scientists is an ongoing process still in its early stages. We will provide an overview of current efforts to develop such metrics to assess existing algorithms and to guide the development of tailored compression algorithms to address this pressing challenge.
Intensified Indian Ocean climate variability during the Last Glacial Maximum
NASA Astrophysics Data System (ADS)
Thirumalai, K.; DiNezro, P.; Tierney, J. E.; Puy, M.; Mohtadi, M.
2017-12-01
Climate models project increased year-to-year climate variability in the equatorial Indian Ocean in response to greenhouse gas warming. This response has been attributed to changes in the mean climate of the Indian Ocean associated with the zonal sea-surface temperature (SST) gradient. According to these studies, air-sea coupling is enhanced due to a stronger SST gradient driving anomalous easterlies that shoal the thermocline in the eastern Indian Ocean. We propose that this relationship between the variability and the zonal SST gradient is consistent across different mean climate states. We test this hypothesis using simulations of past and future climate performed with the Community Earth System Model Version 1 (CESM1). We constrain the realism of the model for the Last Glacial Maximum (LGM) where CESM1 simulates a mean climate consistent with a stronger SST gradient, agreeing with proxy reconstructions. CESM1 also simulates a pronounced increase in seasonal and interannual variability. We develop new estimates of climate variability on these timescales during the LGM using δ18O analysis of individual foraminifera (IFA). IFA data generated from four different cores located in the eastern Indian Ocean indicate a marked increase in δ18O-variance during the LGM as compared to the late Holocene. Such a significant increase in the IFA-δ18O variance strongly supports the modeling simulations. This agreement further supports the dynamics linking year-to-year variability and an altered SST gradient, increasing our confidence in model projections.
On the Frozen Soil Scheme for High Latitude Regions
NASA Astrophysics Data System (ADS)
Ganji, A.; Sushama, L.
2014-12-01
Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the frozen scheme in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. Interflow is also included in these experiments presented in this study to better explain the steamflows after snow melt season. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations, performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA-Interim), for the 1990-2001 period, over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept, compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS, over most of the study domain. The simulated spring peaks and their timing in this simulation is also in better agreement to those observed.
On improving cold region hydrological processes in the Canadian Land Surface Scheme
NASA Astrophysics Data System (ADS)
Ganji, Arman; Sushama, Laxmi; Verseghy, Diana; Harvey, Richard
2017-01-01
Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the treatment of frozen water in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis (ERA-Interim) for the 1990-2001 period over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration and therefore soil moisture during the snowmelt season for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS over most of the study domain. The simulated spring peaks and their timing in this simulation are also in better agreement to those observed. This study thus demonstrates the importance of treatment of frozen water for realistic simulation of streamflows.
An overview of CERES-Sorghum as implemented in the cropping systems model version 4.5
USDA-ARS?s Scientific Manuscript database
Sorghum [Sorghum bicolor (L.) Moench] is the fifth most important grain crop globally. It stands out for its diversity of plant types, end-uses, and roles in cropping systems. This diversity presents opportunities but also complicates evaluation of production options, especially under climate uncert...
Spatio-temporal dynamic climate model for Neoleucinodes elegantalis using CLIMEX
NASA Astrophysics Data System (ADS)
da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; da Silva, Ezio Marques; da Silva Galdino, Tarcisio Visintin; Picanço, Marcelo Coutinho
2017-05-01
Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for Neoleucinodes elegantalis (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of N. elegantalis for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for N. elegantalis and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for N. elegantalis. In this study, we ensure that the simulation results are valid through our verification using field data.
The Impact of ENSO on Trace Gas Composition in the Upper Troposphere to Lower Stratosphere
NASA Technical Reports Server (NTRS)
Oman, Luke; Douglass, Anne; Ziemke, Jerry; Waugh, Darryn Warwick
2016-01-01
The El Nino-Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical troposphere and its effects extend well into the stratosphere. Its impact on atmospheric dynamics and chemistry cause important changes to trace gas constituent distributions. A comprehensive suite of satellite observations, reanalyses, and chemistry climate model simulations are illuminating our understanding of processes like ENSO. Analyses of more than a decade of observations from NASAs Aura and Aqua satellites, combined with simulations from the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) and other Chemistry Climate Modeling Initiative (CCMI) models, and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis have provided key insights into the response of atmospheric composition to ENSO. While we will primarily focus on ozone and water vapor responses in the upper troposphere to lower stratosphere, the effects of ENSO ripple through many important trace gas species throughout the atmosphere. The very large 2015-2016 El Nino event provides an opportunity to closely examine these impacts with unprecedented observational breadth. An improved quantification of natural climate variations, like those from ENSO, is needed to detect and quantify anthropogenic climate changes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Collins, William D.; Craig, Anthony P.; Truesdale, John E.
The integrated Earth System Model (iESM) has been developed as a new tool for pro- jecting the joint human/climate system. The iESM is based upon coupling an Integrated Assessment Model (IAM) and an Earth System Model (ESM) into a common modeling in- frastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species, land use and land cover change, and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human dimension modeling of an IAM and a fully coupled ESM within a sin- gle simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore- omitted feedbacks between natural and societal drivers, we can improve scientific under- standing of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper de- scribes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Collins, W. D.; Craig, A. P.; Truesdale, J. E.
The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less
NASA Technical Reports Server (NTRS)
Cullather, Richard; Bosilovich, Michael
2017-01-01
The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) is a global atmospheric reanalysis produced by the NASA Global Modeling and Assimilation Office (GMAO). It spans the satellite observing era from 1980 to the present. The goals of MERRA-2 are to provide a regularly-gridded, homogeneous record of the global atmosphere, and to incorporate additional aspects of the climate system including trace gas constituents (stratospheric ozone), and improved land surface representation, and cryospheric processes. MERRA-2 is also the first satellite-era global reanalysis to assimilate space-based observations of aerosols and represent their interactions with other physical processes in the climate system. The inclusion of these additional components are consistent with the overall objectives of an Integrated Earth System Analysis (IESA). MERRA-2 is intended to replace the original MERRA product, and reflects recent advances in atmospheric modeling and data assimilation. Modern hyperspectral radiance and microwave observations, along with GPS-Radio Occultation and NASA ozone datasets are now assimilated in MERRA-2. Much of the structure of the data files remains the same in MERRA-2. While the original MERRA data format was HDF-EOS, the MERRA-2 supplied binary data format is now NetCDF4 (with lossy compression to save space).
On the stability of the Atlantic meridional overturning circulation
Hofmann, Matthias; Rahmstorf, Stefan
2009-01-01
One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC. PMID:19897722
NASA Technical Reports Server (NTRS)
Boville, Byron A.; Baumhefner, David P.
1990-01-01
Using an NCAR community climate model, Version I, the forecast error growth and the climate drift resulting from the omission of the upper stratosphere are investigated. In the experiment, the control simulation is a seasonal integration of a medium horizontal general circulation model with 30 levels extending from the surface to the upper mesosphere, while the main experiment uses an identical model, except that only the bottom 15 levels (below 10 mb) are retained. It is shown that both random and systematic errors develop rapidly in the lower stratosphere with some local propagation into the troposphere in the 10-30-day time range. The random growth rate in the troposphere in the case of the altered upper boundary was found to be slightly faster than that for the initial-condition uncertainty alone. However, this is not likely to make a significant impact in operational forecast models, because the initial-condition uncertainty is very large.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Penner, Joyce E.; Zhou, Cheng
Observation-based studies have shown that the aerosol cloud lifetime effect or the increase of cloud liquid water path (LWP) with increased aerosol loading may have been overestimated in climate models. Here, we simulate shallow warm clouds on 05/27/2011 at the Southern Great Plains (SGP) measurement site established by Department of Energy's Atmospheric Radiation Measurement (ARM) Program using a single column version of a global climate model (Community Atmosphere Model or CAM) and a cloud resolving model (CRM). The LWP simulated by CAM increases substantially with aerosol loading while that in the CRM does not. The increase of LWP in CAMmore » is caused by a large decrease of the autoconversion rate when cloud droplet number increases. In the CRM, the autoconversion rate is also reduced, but this is offset or even outweighed by the increased evaporation of cloud droplets near cloud top, resulting in an overall decrease in LWP. Our results suggest that climate models need to include the dependence of cloud top growth and the evaporation/condensation process on cloud droplet number concentrations.« less
Influence of land-surface evapotranspiration on the earth's climate
NASA Technical Reports Server (NTRS)
Shukla, J.; Mintz, Y.
1982-01-01
Land-surface evapotranspiration is shown to strongly influence global fields of rainfall, temperature and motion by calculations using a numerical model of the atmosphere, confirming the general belief in the importance of evapotranspiration-producing surface vegetation for the earth's climate. The current version of the Goddard Laboratory atmospheric general circulation model is used in the present experiment, in which conservation equations for mass, momentum, moisture and energy are expressed in finite-difference form for a spherical grid to calculate (1) surface pressure field evolution, and (2) the wind, temperature, and water vapor fields at nine levels between the surface and a 20 km height.
A Coupled Surface Nudging Scheme for use in Retrospective ...
A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem modeling. This scheme is known as the flux-adjusting surface data assimilation system (FASDAS) developed by Alapaty et al. (2008). This scheme provides continuous adjustments for soil moisture and temperature (via indirect nudging) and for surface air temperature and water vapor mixing ratio (via direct nudging). The simultaneous application of indirect and direct nudging maintains greater consistency between the soil temperature–moisture and the atmospheric surface layer mass-field variables. The new method, FASDAS, consistently improved the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as well as for high resolution regional climate predictions. This new capability has been released in WRF Version 3.8 as option grid_sfdda = 2. This new capability increased the accuracy of atmospheric inputs for use air quality, hydrology, and ecosystem modeling research to improve the accuracy of respective end-point research outcome. IMPACT: A new method, FASDAS, was implemented into the WRF model to consistently improve the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as wel
Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley
2002-01-01
We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0â30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huerta, Gabriel
The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projectionsmore » of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta at the University of New Mexico is responsible for developing statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. This report reflects the main activities at the University of New Mexico where the PI (Huerta) and the Postdocs (Nosedal, Hattab and Karki) worked on the project.« less
Chen, M.; Zhuang, Q.; Cook, D. R.; ...
2011-09-21
Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. First we modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenologymore » and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000–2005 at a 0.05° × 0.05° spatial resolution. We find that the new version of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 PgC yr -1 and net primary production (NPP) ranges from 3.81 to 4.38 Pg Cyr -1 and net ecosystem production (NEP) varies within 0.08– 0.73 PgC yr -1 over the period 2000–2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 PgC yr -1 for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Lastly, our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, M.; Zhuang, Q.; Cook, D. R.
Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. First we modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenologymore » and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000–2005 at a 0.05° × 0.05° spatial resolution. We find that the new version of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 PgC yr -1 and net primary production (NPP) ranges from 3.81 to 4.38 Pg Cyr -1 and net ecosystem production (NEP) varies within 0.08– 0.73 PgC yr -1 over the period 2000–2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 PgC yr -1 for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Lastly, our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.« less
A flexible climate model for use in integrated assessments
NASA Astrophysics Data System (ADS)
Sokolov, A. P.; Stone, P. H.
Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model's sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO2 are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM for a variety of transient forcing scenarios. Both surface warming and sea level rise due to thermal expansion of the deep ocean in response to a gradually increasing forcing are reasonably reproduced on time scales of 100-150 y. However a wide range of diffusion coefficients is needed to match the behavior of different AOGCMs. We use results of simulations with the 2-D model to show that the impact on climate change of the implied uncertainty in the rate of heat penetration into the deep ocean is comparable with that of other significant uncertainties.
NASA Astrophysics Data System (ADS)
Yu, Tianlei; Guo, Pinwen; Cheng, Jun; Hu, Aixue; Lin, Pengfei; Yu, Yongqiang
2018-03-01
Previous studies show a close relationship between the East Asian Summer Monsoon (EASM) and Southern Hemisphere (SH) circulation on interannual timescales. In this study, we investigate whether this close relationship will change under intensive greenhouse-gas effect by analyzing simulations under two different climate background states: preindustrial era and Representative Concentration Pathway (RCP) 8.5 stabilization from the Community Climate System Model Version 4 (CCSM4). Results show a significantly reduced relationship under stabilized RCP8.5 climate state, such a less correlated EASM with the sea level pressure in the southern Indian Ocean and the SH branch of local Hadley Cell. Further analysis suggests that the collapse of the Atlantic Meridional Overturning Circulation (AMOC) due to this warming leads to a less vigorous northward meridional heat transport, a decreased intertropical temperature contrast in boreal summer, which produces a weaker cross-equatorial Hadley Cell in the monsoonal region and a reduced Interhemispheric Mass Exchange (IME). Since the monsoonal IME acts as a bridge connecting EASM and SH circulation, the reduced IME weakens this connection. By performing freshwater hosing experiment using the Flexible Global Ocean—Atmosphere—Land System model, Grid-point Version 2 (FGOALS-g2), we show a weakened relationship between the EASM and SH circulation as in CCSM4 when AMOC collapses. Our results suggest that a substantially weakened AMOC is the main driver leading to the EASM, which is less affected by SH circulation in the future warmer climate.
Parameterization Interactions in Global Aquaplanet Simulations
NASA Astrophysics Data System (ADS)
Bhattacharya, Ritthik; Bordoni, Simona; Suselj, Kay; Teixeira, João.
2018-02-01
Global climate simulations rely on parameterizations of physical processes that have scales smaller than the resolved ones. In the atmosphere, these parameterizations represent moist convection, boundary layer turbulence and convection, cloud microphysics, longwave and shortwave radiation, and the interaction with the land and ocean surface. These parameterizations can generate different climates involving a wide range of interactions among parameterizations and between the parameterizations and the resolved dynamics. To gain a simplified understanding of a subset of these interactions, we perform aquaplanet simulations with the global version of the Weather Research and Forecasting (WRF) model employing a range (in terms of properties) of moist convection and boundary layer (BL) parameterizations. Significant differences are noted in the simulated precipitation amounts, its partitioning between convective and large-scale precipitation, as well as in the radiative impacts. These differences arise from the way the subcloud physics interacts with convection, both directly and through various pathways involving the large-scale dynamics and the boundary layer, convection, and clouds. A detailed analysis of the profiles of the different tendencies (from the different physical processes) for both potential temperature and water vapor is performed. While different combinations of convection and boundary layer parameterizations can lead to different climates, a key conclusion of this study is that similar climates can be simulated with model versions that are different in terms of the partitioning of the tendencies: the vertically distributed energy and water balances in the tropics can be obtained with significantly different profiles of large-scale, convection, and cloud microphysics tendencies.
Yao, Shuai-Lei; Luo, Jing-Jia; Huang, Gang
2016-01-01
Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.
CORDEX.be: COmbining Regional climate Downscaling EXpertise in Belgium
NASA Astrophysics Data System (ADS)
Termonia, P.
2015-12-01
The main objective of the ongoing project CORDEX.be, "COmbining Regional Downscaling EXpertise in Belgium: CORDEX and Beyond", is to gather existing and ongoing Belgian research activities in the domain of climate modelling to create a coherent scientific basis for future climate services in Belgium. The project regroups 8 Belgian Institutes under a single research program of the Belgian Science Policy (BELSPO). The project involves three regional climate models: the ALARO model, the COSMO-CLM model and the MAR model running according to the guidelines of the CORDEX project and at convection permitting resolution on small domains over Belgium. The project creates a framework to address four objectives/challenges. First, this projects aims to contribute to the EURO-CORDEX project. Secondly, RCP simulations are executed at convection-permitting resolutions (3 to 5 km) on small domains. Thirdly, the output of the atmospheric models is used to drive land surface models (the SURFEX model and the Urbclim model) with urban modules, a crop model (REGCROP), a tides and storm model (COHERENS) and the MEGAN-MOHYCAN model that simulates the fluxes emitted by vegetation. Finally, one work package will translate the uncertainty present in the CORDEX database to the high-resolution output of the CORDEX.be project. The organization of the project will be presented and first results will be shown, demonstrating that convection-permitting models can add extra skill to the mesoscale version of the regional climate models, in particular regarding the extreme value statistics and the diurnal cycle.
CORDEX.be: COmbining Regional climate Downscaling EXpertise in Belgium
NASA Astrophysics Data System (ADS)
Termonia, Piet; Van Schaeybroeck, Bert; De Ridder, Koen; Fettweis, Xavier; Gobin, Anne; Luyten, Patrick; Marbaix, Philippe; Pottiaux, Eric; Stavrakou, Trissevgeni; Van Lipzig, Nicole; van Ypersele, Jean-Pascal; Willems, Patrick
2016-04-01
The main objective of the ongoing project CORDEX.be, "COmbining Regional Downscaling EXpertise in Belgium: CORDEX and Beyond" is to gather existing and ongoing Belgian research activities in the domain of climate modelling to create a coherent scientific basis for future climate services in Belgium. The project regroups eight Belgian Institutes under a single research program of the Belgian Science Policy (BELSPO). The project involves three regional climate models: the ALARO model, the COSMO-CLM model and the MAR model running according to the guidelines of the CORDEX project and at convection permitting resolution on small domains over Belgium. The project creates a framework to address four objectives/challenges. First, this projects aims to contribute to the EURO-CORDEX project. Secondly, RCP simulations are executed at convection-permitting resolutions (3 to 5 km) on small domains. Thirdly, the output of the atmospheric models is used to drive land surface models (the SURFEX model and the Urbclim model) with urban modules, a crop model (REGCROP), a tides and storm model (COHERENS) and the MEGAN-MOHYCAN model that simulates the fluxes emitted by vegetation. Finally, one work package will translate the uncertainty present in the CORDEX database to the high-resolution output of the CORDEX.be project. The organization of the project will be presented and first results will be shown, demonstrating that convection-permitting models can add extra skill to the mesoscale version of the regional climate models, in particular regarding the extreme value statistics and the diurnal cycle.
A Global Perspective: NASA's Prediction of Worldwide Energy Resources (POWER) Project
NASA Technical Reports Server (NTRS)
Zhang, Taiping; Stackhouse, Paul W., Jr.; Chandler, William S.; Hoell, James M.; Westberg, David; Whitlock, Charles H.
2007-01-01
The Prediction of the Worldwide Energy Resources (POWER) Project, initiated under the NASA Science Mission Directorate Applied Science Energy Management Program, synthesizes and analyzes data on a global scale that are invaluable to the renewable energy industries, especially to the solar and wind energy sectors. The POWER project derives its data primarily from NASA's World Climate Research Programme (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Version 2.9) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (Version 4). The latest development of the NASA POWER Project and its plans for the future are presented in this paper.
Henrique F. Duarte; Brett M. Raczka; Daniel M. Ricciuto; John C. Lin; Charles D. Koven; Peter E. Thornton; David R. Bowling; Chun-Ta Lai; Kenneth J. Bible; James R. Ehleringer
2017-01-01
Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest...
Modelling of Titan's middle atmosphere with the IPSL climate model
NASA Astrophysics Data System (ADS)
Vatant d'Ollone, Jan; Lebonnois, Sébastien; Guerlet, Sandrine
2017-04-01
Titan's 3-dimensional Global Climate Model developed at the Institute Pierre-Simon Laplace has already demonstrated its efficiency to reproduce and interpret many features of the Saturnian moon's climate (e.g. Lebonnois et al., 2012). However, it suffered from limits at the top of the model, with temperatures far warmer than the observations and no stratopause simulated. To interpret Cassini's overall observations of seasonal effects in the middle atmosphere (e.g. Vinatier et al., 2015), a satisfying modelling of the temperature profile in this region was first required. Latest developments in the GCM now enable a correct modelling of the temperature profile in the middle atmosphere. In particular, a new, more flexible, radiative transfer scheme based on correlated-k method has been set up, using up-to-date spectroscopic data. Special emphasis is put on the too warm upper stratospheric temperatures in the former model that were due to the absence of the infrared ν4 methane line (7.7 μm) in the radiative transfer. While it was usually neglected in the tropospheric radiative models, this line has a strong cooling effect in Titan's stratospheric conditions and cannot be neglected. In this new version of the GCM, the microphysical model is temporarily switched off and we use a mean profile for haze opacity (Lavvas et al., 2010). The circulation in the middle atmosphere is significantly improved by this new radiative transfer. The new 3-D simulations also show an interesting feature in the modeled vertical profile of the zonal wind as the minimum in low stratosphere is now closer to the observations. Works in progress such as the vertical extension and the computation of the radiative effect of the seasonal variations of trace components will also be presented. - Lavvas P. et al., 2010. Titan's vertical aerosol structure at the Huygens landing site: Constraints on particle size, density, charge, and refractive index. Icarus 210, 832-842. - Lebonnois S. et al., 2012. Titan Global Climate Model: new 3-dimensional version of the IPSL Titan GCM. Icarus 218, 707-722. - Vinatier S. et al., 2015. Seasonal variations in Titan's middle atmosphere during the northern spring derived from Cassini/CIRS observations. Icarus 250, 95-115.
Assessment of bias correction under transient climate change
NASA Astrophysics Data System (ADS)
Van Schaeybroeck, Bert; Vannitsem, Stéphane
2015-04-01
Calibration of climate simulations is necessary since large systematic discrepancies are generally found between the model climate and the observed climate. Recent studies have cast doubt upon the common assumption of the bias being stationary when the climate changes. This led to the development of new methods, mostly based on linear sensitivity of the biases as a function of time or forcing (Kharin et al. 2012). However, recent studies uncovered more fundamental problems using both low-order systems (Vannitsem 2011) and climate models, showing that the biases may display complicated non-linear variations under climate change. This last analysis focused on biases derived from the equilibrium climate sensitivity, thereby ignoring the effect of the transient climate sensitivity. Based on the linear response theory, a general method of bias correction is therefore proposed that can be applied on any climate forcing scenario. The validity of the method is addressed using twin experiments with a climate model of intermediate complexity LOVECLIM (Goosse et al., 2010). We evaluate to what extent the bias change is sensitive to the structure (frequency) of the applied forcing (here greenhouse gases) and whether the linear response theory is valid for global and/or local variables. To answer these question we perform large-ensemble simulations using different 300-year scenarios of forced carbon-dioxide concentrations. Reality and simulations are assumed to differ by a model error emulated as a parametric error in the wind drag or in the radiative scheme. References [1] H. Goosse et al., 2010: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603-633. [2] S. Vannitsem, 2011: Bias correction and post-processing under climate change, Nonlin. Processes Geophys., 18, 911-924. [3] V.V. Kharin, G. J. Boer, W. J. Merryfield, J. F. Scinocca, and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate, Geophys. Res. Lett., 39, L19705.
Challenges in the development of very high resolution Earth System Models for climate science
NASA Astrophysics Data System (ADS)
Rasch, Philip J.; Xie, Shaocheng; Ma, Po-Lun; Lin, Wuyin; Wan, Hui; Qian, Yun
2017-04-01
The authors represent the 20+ members of the ACME atmosphere development team. The US Department of Energy (DOE) has, like many other organizations around the world, identified the need for an Earth System Model capable of rapid completion of decade to century length simulations at very high (vertical and horizontal) resolution with good climate fidelity. Two years ago DOE initiated a multi-institution effort called ACME (Accelerated Climate Modeling for Energy) to meet this an extraordinary challenge, targeting a model eventually capable of running at 10-25km horizontal and 20-400m vertical resolution through the troposphere on exascale computational platforms at speeds sufficient to complete 5+ simulated years per day. I will outline the challenges our team has encountered in development of the atmosphere component of this model, and the strategies we have been using for tuning and debugging a model that we can barely afford to run on today's computational platforms. These strategies include: 1) evaluation at lower resolutions; 2) ensembles of short simulations to explore parameter space, and perform rough tuning and evaluation; 3) use of regionally refined versions of the model for probing high resolution model behavior at less expense; 4) use of "auto-tuning" methodologies for model tuning; and 5) brute force long climate simulations.
Surface Mass Balance of the Greenland Ice Sheet Derived from Paleoclimate Reanalysis
NASA Astrophysics Data System (ADS)
Badgeley, J.; Steig, E. J.; Hakim, G. J.; Anderson, J.; Tardif, R.
2017-12-01
Modeling past ice-sheet behavior requires independent knowledge of past surface mass balance. Though models provide useful insight into ice-sheet response to climate forcing, if past climate is unknown, then ascertaining the rate and extent of past ice-sheet change is limited to geological and geophysical constraints. We use a novel data-assimilation framework developed under the Last Millennium Reanalysis Project (Hakim et al., 2016) to reconstruct past climate over ice sheets with the intent of creating an independent surface mass balance record for paleo ice-sheet modeling. Paleoclimate data assimilation combines the physics of climate models and the time series evidence of proxy records in an offline, ensemble-based approach. This framework allows for the assimilation of numerous proxy records and archive types while maintaining spatial consistency with known climate dynamics and physics captured by the models. In our reconstruction, we use the Community Climate System Model version 4, CMIP5 last millennium simulation (Taylor et al., 2012; Landrum et al., 2013) and a nearly complete database of ice core oxygen isotope records to reconstruct Holocene surface temperature and precipitation over the Greenland Ice Sheet on a decadal timescale. By applying a seasonality to this reconstruction (from the TraCE-21ka simulation; Liu et al., 2009), our reanalysis can be used in seasonally-based surface mass balance models. Here we discuss the methods behind our reanalysis and the performance of our reconstruction through prediction of unassimilated proxy records and comparison to paleoclimate reconstructions and reanalysis products.
NASA Astrophysics Data System (ADS)
Cook, E. R.
2007-05-01
The North American Drought Atlas describes a detailed reconstruction of drought variability from tree rings over most of North America for the past 500-1000 years. The first version of it, produced over three years ago, was based on a network of 835 tree-ring chronologies and a 286-point grid of instrumental Palmer Drought Severity Indices (PDSI). These gridded PDSI reconstructions have been used in numerous published studies now that range from modeling fire in the American West, to the impact of drought on palaeo-Indian societies, and to the determination of the primary causes of drought over North America through climate modeling experiments. Some examples of these applications will be described to illustrate the scientific value of these large-scale reconstructions of drought. Since the development and free public release of Version 1 of the North American Drought Atlas (see http:iridl.ldeo.columbia.edu/SOURCES/.LDEO/.TRL/.NADA2004/.pdsi-atlas.html), great improvements have been made in the critical tree-ring network used to reconstruct PDSI at each grid point. This network has now been enlarged to 1743 annual tree-ring chronologies, which greatly improves the density of tree-ring records in certain parts of the grid, especially in Canada and Mexico. In addition, the number of tree-ring records that extend back before AD 1400 has been substantially increased. These developments justify the creation of Version 2 of the North American Drought Atlas. In this talk I will describe this new version of the drought atlas and some of its properties that make it a significant improvement over the previous version. The new product provides enhanced resolution of the spatial and temporal variability of prolonged drought such as the late 16th century event that impacted regions of both Mexico and the United States. I will also argue for the North American Drought Atlas being used as a template for the development of large-scale drought reconstructions in other land areas of the Northern Hemisphere where sufficient tree-ring data exist. By doing so, the importance of this product to the modeling community will be significantly enhanced.
NASA Astrophysics Data System (ADS)
Gusev, Anatoly; Fomin, Vladimir; Diansky, Nikolay; Korshenko, Evgeniya
2017-04-01
In this paper, we present the improved version of the ocean general circulation sigma-model developed in the Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS). The previous version referred to as INMOM (Institute of Numerical Mathematics Ocean Model) is used as the oceanic component of the IPCC climate system model INMCM (Institute of Numerical Mathematics Climate Model (Volodin et al 2010,2013). Besides, INMOM as the only sigma-model was used for simulations according to CORE-II scenario (Danabasoglu et al. 2014,2016; Downes et al. 2015; Farneti et al. 2015). In general, INMOM results are comparable to ones of other OGCMs and were used for investigation of climatic variations in the North Atlantic (Gusev and Diansky 2014). However, detailed analysis of some CORE-II INMOM results revealed some disadvantages of the INMOM leading to considerable errors in reproducing some ocean characteristics. So, the mass transport in the Antarctic Circumpolar Current (ACC) was overestimated. As well, there were noticeable errors in reproducing thermohaline structure of the ocean. After analysing the previous results, the new version of the OGCM was developed. It was decided to entitle is INMSOM (Institute of Numerical Mathematics Sigma Ocean Model). The new title allows one to distingwish the new model, first, from its older version, and second, from another z-model developed in the INM RAS and referred to as INMIO (Institute of Numerical Mathematics and Institute of Oceanology ocean model) (Ushakov et al. 2016). There were numerous modifications in the model, some of them are as follows. 1) Formulation of the ocean circulation problem in terms of full free surface with taking into account water amount variation. 2) Using tensor form of lateral viscosity operator invariant to rotation. 3) Using isopycnal diffusion including Gent-McWilliams mixing. 4) Using atmospheric forcing computation according to NCAR methodology (Large and Yeager 2009). 5) Improvement river runoff algorithm accounting the total amount of discharged water. 6) Using explicit leapfrog time scheme for all lateral operators and implicit Euler scheme for vertical diffusion and viscosity. The INMSOM is tested by reproducing World Ocean circulation and thermohaline characteristics using the well-proved CORE dataset. The presentation is devoted to the analysis of new INMSOM simulation results, estimation of their quality and comparison to the ones previously obtained with the INMOM. The main aim of the INMSOM development is using it as the oceanic component of the next version of INMCM. The work was supported by the Russian Foundation for Basic Research (grants № 16-05-00534 and № 15-05-07539) References 1. Danabasoglu, G., Yeager S.G., Bailey D., et al., 2014: North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states. Ocean Modelling, 73, 76-107. 2. Danabasoglu, G., Yeager S.G., Kim W.M. et al., 2016: North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part II: Inter-annual to decadal variability. Ocean Modelling, 97, 65-90. 3. Downes S.M., Farneti R., Uotila P. et al. An assessment of Southern Ocean water masses and sea ice during 1988-2007 in a suite of interannual CORE-II simulations. Ocean Modelling (2015), 94, 67-94. 4. Farneti R., Downes S.M., Griffies S.M. et al. An assessment of Antarctic Circumpolar Current and Southern Ocean Meridional Overturning Circulation during 1958-2007 in a suite of interannual CORE-II simulations, Ocean Modelling (2015), 93, 84-120. 5. Gusev A.V. and Diansky N.A. Numerical simulation of the World ocean circulation and its climatic variability for 1948-2007 using the INMOM. Izvestiya, Atmospheric and Oceanic Physics, 2014, V. 50, N. 1, P. 1-12 6. Large, W., Yeager, S., 2009. The global climatology of an interannually varying air-sea flux data set. Clim Dyn, V. 33, P. 341-364. 7. Ushakov K.V., Grankina T.B., Ibraev R.A. Modeling the water circulation in the North Atlantic in the scope of the CORE-II experiment. Izvestiya, Atmospheric and Oceanic Physics. 2016. V. 52, № 4, P. 365-375
NASA Astrophysics Data System (ADS)
van Walsum, P. E. V.; Supit, I.
2012-06-01
Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated hydrologic simulation provides a valuable addition for hydrologic modelling as well as for crop modelling.
NASA Astrophysics Data System (ADS)
Hember, R. A.; Kurz, W. A.; Coops, N. C.; Black, T. A.
2010-12-01
Temperate-maritime forests of coastal British Columbia store large amounts of carbon (C) in soil, detritus, and trees. To better understand the sensitivity of these C stocks to climate variability, simulations were conducted using a hybrid version of the model, Physiological Principles Predicting Growth (3-PG), combined with algorithms from the Carbon Budget Model of the Canadian Forest Sector - version 3 (CBM-CFS3) to account for full ecosystem C dynamics. The model was optimized based on a combination of monthly CO2 and H2O flux measurements derived from three eddy-covariance systems and multi-annual stemwood growth (Gsw) and mortality (Msw) derived from 1300 permanent sample plots by means of Markov chain Monte Carlo sampling. The calibrated model serves as an unbiased estimator of stemwood C with enhanced precision over that of strictly-empirical models, minimized reliance on local prescriptions, and the flexibility to study impacts of environmental change on regional C stocks. We report the contribution of each dataset in identifying key physiological parameters and the posterior uncertainty in predictions of net ecosystem production (NEP). The calibrated model was used to spin up pre-industrial C pools and estimate the sensitivity of regional net carbon balance to a gradient of temperature changes, λ=ΔC/ΔT, during three 62-year harvest rotations, spanning 1949-2135. Simulations suggest that regional net primary production, tree mortality, and heterotrophic respiration all began increasing, while NEP began decreasing in response to warming following the 1976 shift in northeast-Pacific climate. We quantified the uncertainty of λ and how it was mediated by initial dead C, tree mortality, precipitation change, and the time horizon in which it was calculated.
NASA Astrophysics Data System (ADS)
Beranová, Romana; Kyselý, Jan; Hanel, Martin
2018-04-01
The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.
NASA Astrophysics Data System (ADS)
Sutanudjaja, Edwin; van Beek, Rens; Winsemius, Hessel; Ward, Philip; Bierkens, Marc
2017-04-01
The Aqueduct Global Flood Analyzer, launched in 2015, is an open-access and free-of-charge web-based interactive platform which assesses and visualises current and future projections of river flood impacts across the globe. One of the key components in the Analyzer is a set of river flood inundation hazard maps derived from the global hydrological model simulation of PCR-GLOBWB. For the current version of the Analyzer, accessible on http://floods.wri.org/#/, the early generation of PCR-GLOBWB 1.0 was used and simulated at 30 arc-minute ( 50 km at the equator) resolution. In this presentation, we will show the new version of these hazard maps. This new version is based on the latest version of PCR-GLOBWB 2.0 (https://github.com/UU-Hydro/PCR-GLOBWB_model, Sutanudjaja et al., 2016, doi:10.5281/zenodo.60764) simulated at 5 arc-minute ( 10 km at the equator) resolution. The model simulates daily hydrological and water resource fluxes and storages, including the simulation of overbank volume that ends up on the floodplain (if flooding occurs). The simulation was performed for the present day situation (from 1960) and future climate projections (until 2099) using the climate forcing created in the ISI-MIP project. From the simulated flood inundation volume time series, we then extract annual maxima for each cell, and fit these maxima to a Gumbel extreme value distribution. This allows us to derive flood volume maps of any hazard magnitude (ranging from 2-year to 1000-year flood events) and for any time period (e.g. 1960-1999, 2010-2049, 2030-2069, and 2060-2099). The derived flood volumes (at 5 arc-minute resolution) are then spread over the high resolution terrain model using an updated GLOFRIS downscaling module (Winsemius et al., 2013, doi:10.5194/hess-17-1871-2013). The updated version performs a volume spreading sequentially from more upstream basins to downstream basins, hence enabling a better inclusion of smaller streams, and takes into account spreading of water over diverging deltaic regions. This results in a set of high resolution hazard maps of flood inundation depth at 30 arc-second ( 1 km at the equator) resolution. Together with many other updates and new features, the resulting flood hazard maps will be used in the next generation of the Aqueduct Global Flood Analyzer.
New and Improved GLDAS Data Sets and Data Services at NASA GES DISC
NASA Technical Reports Server (NTRS)
Rui, Hualan; Beaudoing, Hiroko; Teng, William; Vollmer, Bruce; Rodell, Matthew; Lei, Guang-Dih
2012-01-01
The goal of a Land Data Assimilation System (LDAS) is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes data and, thereby, facilitate hydrology and climate modeling, research, and forecast. With the motivation of creating more climatologically consistent data sets, NASA GSFC's Hydrological Sciences Laboratory has generated more than 60 years (Jan. 1948-- Dec. 2008) of Global LDAS Version 2 (GLDAS-2) data, by using the Princeton Forcing Data Set and upgraded versions of Land Surface Models (LSMs). GLDAS data and data services are provided at NASA GES DISC Hydrology Data and Information Services Center (HDISC), in collaboration with HSL and LDAS.
The path to CAM6: coupled simulations with CAM5.4 and CAM5.5
NASA Astrophysics Data System (ADS)
Bogenschutz, Peter A.; Gettelman, Andrew; Hannay, Cecile; Larson, Vincent E.; Neale, Richard B.; Craig, Cheryl; Chen, Chih-Chieh
2018-01-01
This paper documents coupled simulations of two developmental versions of the Community Atmosphere Model (CAM) towards CAM6. The configuration called CAM5.4 introduces new microphysics, aerosol, and ice nucleation changes, among others to CAM. The CAM5.5 configuration represents a more radical departure, as it uses an assumed probability density function (PDF)-based unified cloud parameterization to replace the turbulence, shallow convection, and warm cloud macrophysics in CAM. This assumed PDF method has been widely used in the last decade in atmosphere-only climate simulations but has never been documented in coupled mode. Here, we compare the simulated coupled climates of CAM5.4 and CAM5.5 and compare them to the control coupled simulation produced by CAM5.3. We find that CAM5.5 has lower cloud forcing biases when compared to the control simulations. Improvements are also seen in the simulated amplitude of the Niño-3.4 index, an improved representation of the diurnal cycle of precipitation, subtropical surface wind stresses, and double Intertropical Convergence Zone biases. Degradations are seen in Amazon precipitation as well as slightly colder sea surface temperatures and thinner Arctic sea ice. Simulation of the 20th century results in a credible simulation that ends slightly colder than the control coupled simulation. The authors find this is due to aerosol indirect effects that are slightly stronger in the new version of the model and propose a solution to ameliorate this. Overall, in these early coupled simulations, CAM5.5 produces a credible climate that is appropriate for science applications and is ready for integration into the National Center for Atmospheric Research's (NCAR's) next-generation climate model.
Evaluation of uncertainties in the CRCM-simulated North American climate
NASA Astrophysics Data System (ADS)
de Elía, Ramón; Caya, Daniel; Côté, Hélène; Frigon, Anne; Biner, Sébastien; Giguère, Michel; Paquin, Dominique; Harvey, Richard; Plummer, David
2008-02-01
This work is a first step in the analysis of uncertainty sources in the RCM-simulated climate over North America. Three main sets of sensitivity studies were carried out: the first estimates the magnitude of internal variability, which is needed to evaluate the significance of changes in the simulated climate induced by any model modification. The second is devoted to the role of CRCM configuration as a source of uncertainty, in particular the sensitivity to nesting technique, domain size, and driving reanalysis. The third study aims to assess the relative importance of the previously estimated sensitivities by performing two additional sensitivity experiments: one, in which the reanalysis driving data is replaced by data generated by the second generation Coupled Global Climate Model (CGCM2), and another, in which a different CRCM version is used. Results show that the internal variability, triggered by differences in initial conditions, is much smaller than the sensitivity to any other source. Results also show that levels of uncertainty originating from liberty of choices in the definition of configuration parameters are comparable among themselves and are smaller than those due to the choice of CGCM or CRCM version used. These results suggest that uncertainty originated by the CRCM configuration latitude (freedom of choice among domain sizes, nesting techniques and reanalysis dataset), although important, does not seem to be a major obstacle to climate downscaling. Finally, with the aim of evaluating the combined effect of the different uncertainties, the ensemble spread is estimated for a subset of the analysed simulations. Results show that downscaled surface temperature is in general more uncertain in the northern regions, while precipitation is more uncertain in the central and eastern US.
Design for and efficient dynamic climate model with realistic geography
NASA Technical Reports Server (NTRS)
Suarez, M. J.; Abeles, J.
1984-01-01
The long term climate sensitivity which include realistic atmospheric dynamics are severely restricted by the expense of integrating atmospheric general circulation models are discussed. Taking as an example models used at GSFC for this dynamic model is an alternative which is of much lower horizontal or vertical resolution. The model of Heid and Suarez uses only two levels in the vertical and, although it has conventional grid resolution in the meridional direction, horizontal resolution is reduced by keeping only a few degrees of freedom in the zonal wavenumber spectrum. Without zonally asymmetric forcing this model simulates a day in roughly 1/2 second on a CRAY. The model under discussion is a fully finite differenced, zonally asymmetric version of the Heid-Suarez model. It is anticipated that speeds can be obtained a few seconds a day roughly 50 times faster than moderate resolution, multilayer GCM's.
NASA Technical Reports Server (NTRS)
Hurwitz, M. M.; Newman, P. A.
2010-01-01
This study examines trends in Antarctic temperature and APSC, a temperature proxy for the area of polar stratospheric clouds, in an ensemble of Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) simulations of the 21st century. A selection of greenhouse gas, ozone-depleting substance, and sea surface temperature scenarios is used to test the trend sensitivity to these parameters. One scenario is used to compare temperature trends in two versions of the GEOS CCM. An extended austral winter season is examined in detail. In May, June, and July, the expected future increase in CO2-related radiative cooling drives temperature trends in the Antarctic lower stratosphere. At 50 hPa, a 1.3 K cooling is expected between 2000 and 2100. Ozone levels increase, despite this robust cooling signal and the consequent increase in APSC, suggesting the enhancement of stratospheric transport in future. In the lower stratosphere, the choice of climate change scenarios does not affect the magnitude of the early winter cooling. Midwinter temperature trends are generally small. In October, APSC trends have the same sign as the prescribed halogen trends. That is, there are negative APSC trends in "grealistic future" simulations, where halogen loading decreases in accordance with the Montreal Protocol and CO2 continues to increase. In these simulations, the speed of ozone recovery is not influenced by either the choice of sea surface temperature and greenhouse gas scenarios or by the model version.
NASA Astrophysics Data System (ADS)
Xu, L.; Peng, Y.; Ram, K.
2017-12-01
The presence of absorbing component of organic carbon in atmospheric aerosols (Brown Carbon, BrC) has recently received much attention to the scientific community because of its absorbing nature, especially in the UV and Visible region. Attempts to account for BrC in radiative forcing calculations in climate model are rather scarce, primarily due to observational constrain as well as its incorporation in the model-based studies. Due to non-treatment of BrC in the off-line models, there exists a large discrepancy between model- and observational- based estimate of direct radiative effect of carbonaceous aerosols. In this study, we have included BrC absorption and optical characteristics in the fifth version of Community Atmospheric Model (CAM5) for the better understanding of radiative impact of BrC over northern India, also for improving the performance of aerosol radiative calculation in climate model. We have used the inputs of aerosol chemical composition measurements conducted at an urban site, Kanpur, in the Indo-Gangetic Plain (IGP) during 2007-2008 to construct the optical properties of BrC in CAM5 model. Model radiative simulations of sensitive tests showed good agreement with observations. Effects of varying imaginary part of BrC refractive index, relative mass ratio of BrC to organic aerosol in combination with core-shell mixing style of BrC with other anthropogenic aerosols are also analyzed for understanding BrC impact on simulated aerosol absorption in model.
NASA Astrophysics Data System (ADS)
Tulich, S. N.
2015-06-01
This paper describes a general method for the treatment of convective momentum transport (CMT) in large-scale dynamical solvers that use a cyclic, two-dimensional (2-D) cloud-resolving model (CRM) as a "superparameterization" of convective-system-scale processes. The approach is similar in concept to traditional parameterizations of CMT, but with the distinction that both the scalar transport and diagnostic pressure gradient force are calculated using information provided by the 2-D CRM. No assumptions are therefore made concerning the role of convection-induced pressure gradient forces in producing up or down-gradient CMT. The proposed method is evaluated using a new superparameterized version of the Weather Research and Forecast model (SP-WRF) that is described herein for the first time. Results show that the net effect of the formulation is to modestly reduce the overall strength of the large-scale circulation, via "cumulus friction." This statement holds true for idealized simulations of two types of mesoscale convective systems, a squall line, and a tropical cyclone, in addition to real-world global simulations of seasonal (1 June to 31 August) climate. In the case of the latter, inclusion of the formulation is found to improve the depiction of key synoptic modes of tropical wave variability, in addition to some aspects of the simulated time-mean climate. The choice of CRM orientation is also found to importantly affect the simulated time-mean climate, apparently due to changes in the explicit representation of wide-spread shallow convective regions.
Multi-model approach to assess the impact of climate change on runoff
NASA Astrophysics Data System (ADS)
Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.
2015-10-01
The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a decrease of the lowest flows, except for the SWAT model with the mean hydrological impact climate change scenario. The results of this study indicate that besides the uncertainty introduced by the climate change scenarios also the hydrological model structure uncertainty should be taken into account in the assessment of climate change impacts on hydrology. To make it more straightforward and transparent to include model structural uncertainty in hydrological impact studies, there is a need for hydrological modelling tools that allow flexible structures and methods to validate model structures in their ability to assess impacts under unobserved future climatic conditions.
Interactive Nature of Climate Change and Aerosol Forcing
NASA Technical Reports Server (NTRS)
Nazarenko, L.; Rind, D.; Tsigaridis, K.; Del Genio, A. D.; Kelley, M.; Tausnev, N.
2017-01-01
The effect of changing cloud cover on climate, based on cloud-aerosol interactions, is one of the major unknowns for climate forcing and climate sensitivity. It has two components: (1) the impact of aerosols on clouds and climate due to in-situ interactions (i.e., rapid response); and (2) the effect of aerosols on the cloud feedback that arises as climate changes - climate feedback response. We examine both effects utilizing the NASA GISS ModelE2 to assess the indirect effect, with both mass-based and microphysical aerosol schemes, in transient twentieth-century simulations. We separate the rapid response and climate feedback effects by making simulations with a coupled version of the model as well as one with no sea surface temperature or sea ice response (atmosphere-only simulations). We show that the indirect effect of aerosols on temperature is altered by the climate feedbacks following the ocean response, and this change differs depending upon which aerosol model is employed. Overall the effective radiative forcing (ERF) for the direct effect of aerosol-radiation interaction (ERFari) ranges between -0.2 and -0.6 W/sq m for atmosphere-only experiments while the total effective radiative forcing, including the indirect effect (ERFari+aci) varies between about -0.4 and -1.1 W/sq m for atmosphere-only simulations; both ranges are in agreement with those given in IPCC (2013). Including the full feedback of the climate system lowers these ranges to -0.2 to -0.5 W/sq m for ERFari, and -0.3 to -0.74 W/sq m for ERFari+aci. With both aerosol schemes, the climate change feedbacks have reduced the global average indirect radiative effect of atmospheric aerosols relative to what the emission changes would have produced, at least partially due to its effect on tropical upper tropospheric clouds.
Validation of the Dutch language version of the Safety Attitudes Questionnaire (SAQ-NL).
Haerkens, Marck Htm; van Leeuwen, Wouter; Sexton, J Bryan; Pickkers, Peter; van der Hoeven, Johannes G
2016-08-15
As the first objective of caring for patients is to do no harm, patient safety is a priority in delivering clinical care. An essential component of safe care in a clinical department is its safety climate. Safety climate correlates with safety-specific behaviour, injury rates, and accidents. Safety climate in healthcare can be assessed by the Safety Attitudes Questionnaire (SAQ), which provides insight by scoring six dimensions: Teamwork Climate, Job Satisfaction, Safety Climate, Stress Recognition, Working Conditions and Perceptions of Management. The objective of this study was to assess the psychometric properties of the Dutch language version of the SAQ in a variety of clinical departments in Dutch hospitals. The Dutch version (SAQ-NL) of the SAQ was back translated, and analyzed for semantic characteristics and content. From October 2010 to November 2015 SAQ-NL surveys were carried out in 17 departments in two university and seven large non-university teaching hospitals in the Netherlands, prior to a Crew Resource Management human factors intervention. Statistical analyses were used to examine response patterns, mean scores, correlations, internal consistency reliability and model fit. Cronbach's α's and inter-item correlations were calculated to examine internal consistency reliability. One thousand three hundred fourteen completed questionnaires were returned from 2113 administered to health care workers, resulting in a response rate of 62 %. Confirmatory Factor Analysis revealed the 6-factor structure fit the data adequately. Response patterns were similar for professional positions, departments, physicians and nurses, and university and non-university teaching hospitals. The SAQ-NL showed strong internal consistency (α = .87). Exploratory analysis revealed differences in scores on the SAQ dimensions when comparing different professional positions, when comparing physicians to nurses and when comparing university to non-university hospitals. The SAQ-NL demonstrated good psychometric properties and is therefore a useful instrument to measure patient safety climate in Dutch clinical work settings. As removal of one item resulted in an increased reliability of the Working Conditions dimension, revision or deletion of this item should be considered. The results from this study provide researchers and practitioners with insight into safety climate in a variety of departments and functional positions in Dutch hospitals.
gpuPOM: a GPU-based Princeton Ocean Model
NASA Astrophysics Data System (ADS)
Xu, S.; Huang, X.; Zhang, Y.; Fu, H.; Oey, L.-Y.; Xu, F.; Yang, G.
2014-11-01
Rapid advances in the performance of the graphics processing unit (GPU) have made the GPU a compelling solution for a series of scientific applications. However, most existing GPU acceleration works for climate models are doing partial code porting for certain hot spots, and can only achieve limited speedup for the entire model. In this work, we take the mpiPOM (a parallel version of the Princeton Ocean Model) as our starting point, design and implement a GPU-based Princeton Ocean Model. By carefully considering the architectural features of the state-of-the-art GPU devices, we rewrite the full mpiPOM model from the original Fortran version into a new Compute Unified Device Architecture C (CUDA-C) version. We take several accelerating methods to further improve the performance of gpuPOM, including optimizing memory access in a single GPU, overlapping communication and boundary operations among multiple GPUs, and overlapping input/output (I/O) between the hybrid Central Processing Unit (CPU) and the GPU. Our experimental results indicate that the performance of the gpuPOM on a workstation containing 4 GPUs is comparable to a powerful cluster with 408 CPU cores and it reduces the energy consumption by 6.8 times.
The evaluation and development of the Met Office Unified Model using surface and space borne radar.
NASA Astrophysics Data System (ADS)
Petch, J.
2012-12-01
The Met Office Unified Model is used for the prediction of weather and climate on time scales of hours through to centuries. Therefore, the parametrizations in that model need to work on weather and climate timescale, and with grid-lengths from hundres of meters through to several hundred kilometres. Focusing on the development of the cloud and radiation schemes I will discuss how we are using ground-based remote-sensing observations from Chilbolton (England) and a combination of Cloudsat and Calipso data to evaluate and improve the performance of the model. I will show how the prediction of the clouds has improved since the AR5 version of the model and how we have developed an improved cloud generator to rebresent the sub-grid variability of clouds for radiative transfer.
NASA Astrophysics Data System (ADS)
Aouade, Ghizlane; Jarlan, Lionel; Ezzahar, Jamal; Er-raki, Salah; Napoly, Adrien; Benkaddour, Abdelfettah; Khabba, Said; Boulet, Gilles; Chehbouni, Abdelghani; Boone, Aaron
2016-04-01
The Haouz region, typical of southern Mediterranean basins, is characterized by a semi-arid climate, with average annual rainfall of 250, whilst evaporative demand is about 1600 mm per year. Under these conditions, crop irrigation is inevitable for growth and development. Irrigated agriculture currently consumes the majority of total available water (up to 85%), making it critical for more efficient water use. Flood irrigation is widely practiced by the majority of the farmers (more than 85 %) with an efficiency which does not exceed 50%. In this context, a good knowledge of the partitioning of evapotranspiration (ET) into soil evaporation and plant transpiration is of crucial need for improving the irrigation scheduling and thus water use efficiency. In this study, the ISBA (Interactions Soil-Biosphere-Atmosphere) model was used for estimating ET and its partition over an olive orchard and a wheat field located near to the Marrakech City (Centre of Morocco). Two versions were evaluated: standard version which simulates a single energy balance for the soil and vegetation and the recently developed multiple energy balance (MEB) version which solves a separate energy balance for each of the two sources. Eddy covariance system, which provides the sensible and latent heat fluxes and meteorological instruments were operated during years 2003-2004 for the Olive Orchard and during years 2013 for wheat. The transpiration component was measured using a Sap flow system during summer over the wheat crop and stable isotope samples were gathered over wheat. The comparison between ET estimated by ISBA model and that measured by the Eddy covariance system showed that MEB version yielded a remarkable improvement compared to the standard version. The root mean square error (RMSE) and the correlation coefficient (R²) were about 45wm-2 and 0.8 for MEB version. By contrast, for the standard version, the RMSE and R² were about 60wm-2 and 0.7, respectively. The result also showed that MEB version simulates more accurately the crop transpiration compared to the standard version. The RMSE and R² were about 0.79 mm and 0.67 for MEB and 1.37mm and 0.65 for standard version. An in-depth analysis of the results points out : (1) a deficiency of the standard version in simulating soil evaporation, in particular after an irrigation event, that directly impact the latent heat fluxes prediction because of two much energy reaching the soil and (2) a significant improvement of the surface temperature predictions with the double energy balance version; an interesting feature in the context of data assimilation; (3) a poor parameterization of the stomatal conductance in the A-gs photosynthetic module that is corrected thanks to a stochastic parameter identification approach. Results have direct implication for the prediction of evapotranspiration and its partition over irrigated crops in semi-arid areas of the South Mediterranean region.
NASA Astrophysics Data System (ADS)
Zhou, Cheng; Penner, Joyce E.
2017-01-01
Observation-based studies have shown that the aerosol cloud lifetime effect or the increase of cloud liquid water path (LWP) with increased aerosol loading may have been overestimated in climate models. Here, we simulate shallow warm clouds on 27 May 2011 at the southern Great Plains (SGP) measurement site established by the Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) program using a single-column version of a global climate model (Community Atmosphere Model or CAM) and a cloud resolving model (CRM). The LWP simulated by CAM increases substantially with aerosol loading while that in the CRM does not. The increase of LWP in CAM is caused by a large decrease of the autoconversion rate when cloud droplet number increases. In the CRM, the autoconversion rate is also reduced, but this is offset or even outweighed by the increased evaporation of cloud droplets near the cloud top, resulting in an overall decrease in LWP. Our results suggest that climate models need to include the dependence of cloud top growth and the evaporation/condensation process on cloud droplet number concentrations.
NASA Astrophysics Data System (ADS)
Quiquet, Aurélien; Roche, Didier M.; Dumas, Christophe; Paillard, Didier
2018-02-01
This paper presents the inclusion of an online dynamical downscaling of temperature and precipitation within the model of intermediate complexity iLOVECLIM v1.1. We describe the following methodology to generate temperature and precipitation fields on a 40 km × 40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is not grid specific and conserves energy and moisture in the same way as the original climate model. We show that we are able to generate a high-resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Although the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature include the improvement of ice sheet model coupling and high-resolution land surface models.
NASA Astrophysics Data System (ADS)
McInerney, J. M.; Liu, H.; Marsh, D. R.; Solomon, S. C.; Vitt, F.; Conley, A. J.
2017-12-01
The total solar eclipse of August 21, 2017 transited the entire continental United States. This presented an opportunity for model simulation of eclipse effects on the lower atmosphere, upper atmosphere, and ionosphere. The Community Earth System Model (CESM), v2.0, now includes a functional version of the Whole Atmosphere Community Climate Model - eXtended (WACCM-X) that has a fully interactive ionosphere and thermosphere. WACCM-X, with a model top up to 700 kilometers, is an atmospheric component of CESM and is being developed at the National Center for Atmospheric Research in Boulder, Colorado. Here we present results from simulations using this model during a total solar eclipse. This not only gives insights into the effects of the eclipse through the entire atmosphere from the surface through the ionosphere/thermosphere, but also serves as a validation tool for the model.
CIM-EARTH: Community Integrated Model of Economic and Resource Trajectories for Humankind
NASA Astrophysics Data System (ADS)
Foster, I.; Elliott, J.; Munson, T.; Judd, K.; Moyer, E. J.; Sanstad, A. H.
2010-12-01
We report here on the development of an open source software framework termed CIM-EARTH that is intended to aid decision-making in climate and energy policy. Numerical modeling in support of evaluating policies to address climate change is difficult not only because of inherent uncertainties but because of the differences in scale and modeling approach required for various subcomponents of the system. Economic and climate models are structured quite differently, and while climate forcing can be assumed to be roughly global, climate impacts and the human response to them occur on small spatial scales. Mitigation policies likewise can be applied on scales ranging from the better part of a continent (e.g. a carbon cap-and-trade program for the entire U.S.) to a few hundred km (e.g. statewide renewable portfolio standards and local gasoline taxes). Both spatial and time resolution requirements can be challenging for global economic models. CIM-EARTH is a modular framework based around dynamic general equilibrium models. It is designed as a community tool that will enable study of the environmental benefits, transition costs, capitalization effects, and other consequences of both mitigation policies and unchecked climate change. Modularity enables both integration of highly resolved component sub-models for energy and other key systems and also user-directed choice of tradeoffs between e.g. spatial, sectoral, and time resolution. This poster describes the framework architecture, the current realized version, and plans for future releases. As with other open-source models familiar to the climate community (e.g. CCSM), deliverables will be made publicly available on a regular schedule, and community input is solicited for development of new features and modules.
NASA Technical Reports Server (NTRS)
Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue
2009-01-01
We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.
Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies
NASA Astrophysics Data System (ADS)
Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj
2016-04-01
In climate simulations, the impacts of the sub-grid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the sub-grid variability in a computationally inexpensive manner. This presentation shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition, by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a non-zero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference PD Williams, NJ Howe, JM Gregory, RS Smith, and MM Joshi (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, under revision.
Evaluation of Probable Maximum Precipitation and Flood under Climate Change in the 21st Century
NASA Astrophysics Data System (ADS)
Gangrade, S.; Kao, S. C.; Rastogi, D.; Ashfaq, M.; Naz, B. S.; Kabela, E.; Anantharaj, V. G.; Singh, N.; Preston, B. L.; Mei, R.
2016-12-01
Critical infrastructures are potentially vulnerable to extreme hydro-climatic events. Under a warming environment, the magnitude and frequency of extreme precipitation and flood are likely to increase enhancing the needs to more accurately quantify the risks due to climate change. In this study, we utilized an integrated modeling framework that includes the Weather Research Forecasting (WRF) model and a high resolution distributed hydrology soil vegetation model (DHSVM) to simulate probable maximum precipitation (PMP) and flood (PMF) events over Alabama-Coosa-Tallapoosa River Basin. A total of 120 storms were selected to simulate moisture maximized PMP under different meteorological forcings, including historical storms driven by Climate Forecast System Reanalysis (CFSR) and baseline (1981-2010), near term future (2021-2050) and long term future (2071-2100) storms driven by Community Climate System Model version 4 (CCSM4) under Representative Concentrations Pathway 8.5 emission scenario. We also analyzed the sensitivity of PMF to various antecedent hydrologic conditions such as initial soil moisture conditions and tested different compulsive approaches. Overall, a statistical significant increase is projected for future PMP and PMF, mainly attributed to the increase of background air temperature. The ensemble of simulated PMP and PMF along with their sensitivity allows us to better quantify the potential risks associated with hydro-climatic extreme events on critical energy-water infrastructures such as major hydropower dams and nuclear power plants.
ICLUS v1.3 Population Projections
Climate and land-use change are major components of global environmental change with feedbacks between these components. The consequences of these interactions show that land use may exacerbate or alleviate climate change effects. Based on these findings it is important to use land-use scenarios that are consistent with the specific assumptions underlying climate-change scenarios. The Integrated Climate and Land-Use Scenarios (ICLUS) project developed land-use outputs that are based on a downscaled version of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines. ICLUS outputs are derived from a pair of models. A demographic model generates county-level population estimates that are distributed by a spatial allocation model (SERGoM v3) as housing density across the landscape. Land-use outputs were developed for the four main SRES storylines and a baseline (base case). The model is run for the conterminous USA and output is available for each scenario by decade to 2100. In addition to housing density at a 1 hectare spatial resolution, this project also generated estimates of impervious surface at a resolution of 1 square kilometer. This shapefile holds population data for all counties of the conterminous USA for all decades (2010-2100) and SRES population growth scenarios (A1, A2, B1, B2), as well as a 'base case' (BC) scenario, for use in the Integrated Climate and Land Use
NASA Astrophysics Data System (ADS)
Leung, Kinson He Yin
Ground-level ozone (O3) is perhaps one of the most familiar pollutants in Ontario, Canada because it is associated with most smog alerts in the province. O3 varies on a number of spatial and temporal scales, primarily due to meteorological variability and the impact of long-range transport of its precursors on the photochemical processes. The goal of this thesis is to project the change in the probability of occurrence of future Extreme Ground-level Ozone Events (EGLOEs) due to changes in atmospheric conditions as a result of climate change for cities located in the southern, eastern and northern parts of Ontario, Canada by using a combination of General Circulation / Global Climate Models (GCMs) and statistical downscaling. These Ontario cities are Toronto, Windsor, London, Kingston, Ottawa, Thunder Bay, Sudbury and North Bay. The successful downscaling method used in this research to generate city-specific climate change scenarios was the Statistical DownScaling Model (SDSM) version 4.2.2, which is a hybrid of regression-based and stochastic weather-generator downscaling methods. The results indicate that the mean values of the daily maximum ground-level ozone concentrations could increase by up to 12-17% in Southern Ontario, 8-16% in Eastern Ontario and 1.5-9% in Northern Ontario by the end of the century due largely to changes in long-range transport. Three important themes emerge from the results: 1) the research successfully model O3 concentration in a region where long-range transport plays a substantial role. 2) The clear confirmation regarding the role of long-range transport in determining O 3 concentration in most areas of Ontario. 3) The projected increase of ozone in Ontario, due largely to an increase of long-range transport, caused by shifting atmospheric dynamics rather than a direct temperature effect on ozone production. Moreover, the results indicate that the future Southern, Eastern and Northern Ontario's EGLOEs with the O3 concentration ≥ 80 ppb (the current Ontario 1-hour Ambient Air Quality criterion for extreme ozone concentration) will have an increase of over 60%, 50% and 62% respectively by the year of 2100 under the different future scenarios in the third version of the Coupled Global Climate Model (CGCM3) and the Hadley Centre's Climate Model (HadCM3).
Costa Rica Rainfall in Future Climate Change Scenarios
NASA Astrophysics Data System (ADS)
Castillo Rodriguez, R. A., Sr.; Amador, J. A.; Duran-Quesada, A. M.
2017-12-01
Studies of intraseasonal and annual cycles of meteorological variables, using projections of climate change, are nowadays extremely important to improve regional socio-economic planning for countries. This is particularly true in Costa Rica, as Central America has been identified as a climate change hot spot. Today many of the economic activities in the region, especially those related to agriculture, tourism and hydroelectric power generation are linked to the seasonal cycle of precipitation. Changes in rainfall (mm/day) and in the diurnal temperature range (°C) for the periods 1950-2005 and 2006-2100 were investigated using the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) constructed using the CMIP5 (Coupled Model Intercomparison Project version 5) data. Differences between the multi-model ensembles of the two prospective scenarios (RCP 4.5 and RCP 8.5) and the retrospective baseline scenario were computed. This study highlights Costa Rica as an inflexion point of the climate change in the region and also suggests future drying conditions.
Upper Blue Nile basin water budget from a multi-model perspective
NASA Astrophysics Data System (ADS)
Jung, Hahn Chul; Getirana, Augusto; Policelli, Frederick; McNally, Amy; Arsenault, Kristi R.; Kumar, Sujay; Tadesse, Tsegaye; Peters-Lidard, Christa D.
2017-12-01
Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.
NASA Technical Reports Server (NTRS)
Da Silva, A. M.; Randles, C. A.; Buchard, V.; Darmenov, A.; Colarco, P. R.; Govindaraju, R.
2015-01-01
This document describes the gridded output files produced by the Goddard Earth Observing System version 5 (GEOS-5) Goddard Aerosol Assimilation System (GAAS) from July 2002 through December 2014. The MERRA Aerosol Reanalysis (MERRAero) is produced with the hydrostatic version of the GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), ozone, carbon monoxide and carbon dioxide. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic emission sources. Meteorology is replayed from the MERRA Reanalysis.
ERIC Educational Resources Information Center
Huang, Francis L.; Cornell, Dewey G.
2016-01-01
Although school climate has long been recognized as an important factor in the school improvement process, there are few psychometrically supported measures based on teacher perspectives. The current study replicated and extended the factor structure, concurrent validity, and test-retest reliability of the teacher version of the Authoritative…
Glaciological reconstruction of Holocene ice margins in northwestern Greenland
NASA Astrophysics Data System (ADS)
Birkel, S. D.; Osterberg, E. C.; Kelly, M. A.; Axford, Y.
2014-12-01
The past few decades of climate warming have brought overall margin retreat to the Greenland Ice Sheet. In order to place recent and projected changes in context, we are undertaking a collaborative field-modeling study that aims to reconstruct the Holocene history of ice-margin fluctuation near Thule (~76.5°N, 68.7°W), and also along the North Ice Cap (NIC) in the Nunatarssuaq region (~76.7°N, 67.4°W). Fieldwork reported by Kelly et al. (2013) reveals that ice in the study areas was less extensive than at present ca. 4700 (GIS) and ca. 880 (NIC) cal. years BP, presumably in response to a warmer climate. We are now exploring Holocene ice-climate coupling using the University of Maine Ice Sheet Model (UMISM). Our approach is to first test what imposed climate anomalies can afford steady state ice margins in accord with field data. A second test encompasses transient simulation of the Holocene, with climate boundary conditions supplied by existing paleo runs of the Community Climate System Model version 4 (CCSM4), and a climate forcing signal derived from Greenland ice cores. In both cases, the full ice sheet is simulated at 10 km resolution with nested domains at 0.5 km for the study areas. UMISM experiments are underway, and results will be reported at the meeting.
New Gravity Wave Treatments for GISS Climate Models
NASA Technical Reports Server (NTRS)
Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye
2011-01-01
Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model-resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, the authors introduce a relatively simple and computationally efficient specification of unresolved orographic and nonorographic gravity waves and their interaction with the resolved flow. Comparisons of the GISS model winds and temperatures with no gravity wave parameterization; with only orographic gravity wave parameterization; and with both orographic and nonorographic gravity wave parameterizations are shown to illustrate how the zonal mean winds and temperatures converge toward observations. The authors also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. Then results are presented where the nonorographic gravity wave sources are specified to represent sources from convection in the intertropical convergence zone and spontaneous emission from jet imbalances. Finally, a strategy to include these effects in a climate-dependent manner is suggested.
Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?
NASA Astrophysics Data System (ADS)
Ban, Nikolina; Schmidli, Juerg; Schär, Christoph
2015-02-01
Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6-7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that subdaily (e.g., hourly) precipitation extremes may increase at about twice this rate. Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parametrize convective precipitation (i.e., thunderstorms and rain showers). Here we employ a convection-resolving model using a horizontal grid spacing of 2.2 km across an extended region covering the Alps and its larger-scale surrounding from northern Italy to northern Germany. Consistent with previous results, projections using a Representative Concentration Pathways version 8.5 greenhouse gas scenario reveal a significant decrease of mean summer precipitation. However, unlike previous studies, we find that both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation. Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day precipitation scaling into the future.
NASA Technical Reports Server (NTRS)
Dudek, Michael P.; Wang, Wei-Chyung; Liang, Xin-Zhong; Li, Zhu
1994-01-01
The total ozone mapping spectrometer (TOMS) and stratospheric aerosol and gas experiment (SAGE) measurements show a significant reduction in the stratospheric ozone over the middle and high latitudes of both hemispheres between the years 1979 and 1991 (WMO, 1992). This change in ozone will effect both the solar and longwave radiation with climate implications. However, recent studies (Ramaswamy et al., 1992; WMO, 1992) indicate that the net effect depends not only on latitudes and seasons, but also on the response of the lower stratospheric temperature. In this study we use a general circulation model (GCM) to calculate the climatic effect due to stratospheric ozone depletion and compare the effect with that due to observed increases of trace gases CO2, CH4, N2O, and CFC's for the period 1980-1990. In the simulations, we use the observed changes in ozone derived from the TOMS data. The GCM used is a version of the NCAR community climate model referenced in Wang et al. (1991). For the present study we run the model in perpetual January and perpetual July modes in which the incoming solar radiation and climatological sea surface temperatures are held constant.
New Gravity Wave Treatments for GISS Climate Models
NASA Technical Reports Server (NTRS)
Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye
2010-01-01
Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, we introduce a relatively simple and computationally efficient specification of unresolved orographic and non-orographic gravity waves and their interaction with the resolved flow. We show comparisons of the GISS model winds and temperatures with no gravity wave parametrization; with only orographic gravity wave parameterization; and with both orographic and non-orographic gravity wave parameterizations to illustrate how the zonal mean winds and temperatures converge toward observations. We also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. We then show results where the non-orographic gravity wave sources are specified to represent sources from convection in the Intertropical Convergence Zone and spontaneous emission from jet imbalances. Finally, we suggest a strategy to include these effects in a climate dependent manner.
Development of ALARO-Climate regional climate model for a very high resolution
NASA Astrophysics Data System (ADS)
Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan
2013-04-01
ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main features of the RCM ALARO-Climate and results of the first model simulations on longer time-scales (1961-1990). The model was driven by the ERA-40/Interim re-analyses and run on the large pan-European integration domain ("ENSEMBLES / Euro-Cordex domain") with spatial resolution of 25 km. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version 7 dataset. The validation of the first ERA-40 simulation has revealed significant cold biases in all seasons (between -4 and -2 °C) and overestimation of precipitation on 20% to 60% in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The consequent adaptations in the model and their effect on the simulated properties of climate variables are illustrated. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).
Nitrogen attenuation of terrestrial carbon cycle response to global environmental factors
Atul Jain; Xiaojuan Yang; Haroon Kheshgi; A. David McGuire; Wilfred Post; David Kicklighter
2009-01-01
Nitrogen cycle dynamics have the capacity to attenuate the magnitude of global terrestrial carbon sinks and sources driven by CO2 fertilization and changes in climate. In this study, two versions of the terrestrial carbon and nitrogen cycle components of the Integrated Science Assessment Model (ISAM) are used to evaluate how variation in nitrogen...
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."
Different types of drifts in two seasonal forecast systems and their dependence on ENSO
NASA Astrophysics Data System (ADS)
Hermanson, L.; Ren, H.-L.; Vellinga, M.; Dunstone, N. D.; Hyder, P.; Ineson, S.; Scaife, A. A.; Smith, D. M.; Thompson, V.; Tian, B.; Williams, K. D.
2017-11-01
Seasonal forecasts using coupled ocean-atmosphere climate models are increasingly employed to provide regional climate predictions. For the quality of forecasts to improve, regional biases in climate models must be diagnosed and reduced. The evolution of biases as initialized forecasts drift away from the observations is poorly understood, making it difficult to diagnose the causes of climate model biases. This study uses two seasonal forecast systems to examine drifts in sea surface temperature (SST) and precipitation, and compares them to the long-term bias in the free-running version of each model. Drifts are considered from daily to multi-annual time scales. We define three types of drift according to their relation with the long-term bias in the free-running model: asymptoting, overshooting and inverse drift. We find that precipitation almost always has an asymptoting drift. SST drifts on the other hand, vary between forecasting systems, where one often overshoots and the other often has an inverse drift. We find that some drifts evolve too slowly to have an impact on seasonal forecasts, even though they are important for climate projections. The bias found over the first few days can be very different from that in the free-running model, so although daily weather predictions can sometimes provide useful information on the causes of climate biases, this is not always the case. We also find that the magnitude of equatorial SST drifts, both in the Pacific and other ocean basins, depends on the El Niño Southern Oscillation (ENSO) phase. Averaging over all hindcast years can therefore hide the details of ENSO state dependent drifts and obscure the underlying physical causes. Our results highlight the need to consider biases across a range of timescales in order to understand their causes and develop improved climate models.
Forest-stressing climate factors on the US West Coast as simulated by CMIP5
NASA Astrophysics Data System (ADS)
Rupp, D. E.; Buotte, P.; Hicke, J. A.; Law, B. E.; Mote, P.; Sharp, D.; Zhenlin, Y.
2013-12-01
The rate of forest mortality has increased significantly in western North America since the 1970s. Causes include insect attacks, fire, and soil water deficit, all of which are interdependent. We first identify climate factors that stress forests by reducing photosynthesis and hydraulic conductance, and by promoting bark beetle infestation and wildfire. Examples of such factors may be two consecutive years of extreme summer precipitation deficit, or prolonged vapor pressure deficit exceeding some threshold. Second, we quantify the frequency and magnitude of these climate factors in 20th and 21st century climates, as simulated by global climate models (GCMs) in Coupled Model Intercomparison Project phase 5 (CMIP5), of Washington, Oregon, and California in the western US. Both ';raw' (i.e., original spatial resolution) and statistically downscaled simulations are considered, the latter generated using the Multivariate Adaptive Constructed Analogs (MACA) method. CMIP5 models that most faithfully reproduce the observed historical statistics of these climate factors are identified. Furthermore, significant changes in the statistics between the 20th and 21st centuries are reported. A subsequent task will be to use a selected subset of MACA-downscaled CMIP5 simulations to force the Community Land Model, version 4.5 (CLM 4.5). CLM 4.5 will be modified to better simulate forest mortality and to couple CLM with an economic model. The ultimate goal of this study is to understand the interactions and the feedbacks by which the market and the forest ecosystem influence each other.
NASA Astrophysics Data System (ADS)
Ivanovic, Ruza F.; Gregoire, Lauren J.; Kageyama, Masa; Roche, Didier M.; Valdes, Paul J.; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev
2016-07-01
The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21-9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Long, M. S.; Keene, W. C.; Easter, Richard C.
2013-02-22
A coupled atmospheric chemistry and climate system model was developed using the modal aerosol version of the National Center for Atmospheric Research Community Atmosphere Model (modal-CAM; v3.6.33) and the Max Planck Institute for Chemistry’s Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA; v2.5) to provide enhanced resolution of multiphase processes, particularly those involving inorganic halogens, and associated impacts on atmospheric composition and climate. Three Rosenbrock solvers (Ros-2, Ros-3, RODAS-3) were tested in conjunction with the basic load-balancing options available to modal-CAM (1) to establish an optimal configuration of the implicitly-solved multiphase chemistry module that maximizes both computational speed andmore » repeatability of Ros- 2 and RODAS-3 results versus Ros-3, and (2) to identify potential implementation strategies for future versions of this and similar coupled systems. RODAS-3 was faster than Ros-2 and Ros-3 with good reproduction of Ros-3 results, while Ros-2 was both slower and substantially less reproducible relative to Ros-3 results. Modal-CAM with MECCA chemistry was a factor of 15 slower than modal-CAM using standard chemistry. MECCA chemistry integration times demonstrated a systematic frequency distribution for all three solvers, and revealed that the change in run-time performance was due to a change in the frequency distribution of chemical integration times; the peak frequency was similar for all solvers. This suggests that efficient chemistry-focused load-balancing schemes can be developed that rely on the parameters of this frequency distribution.« less
Significant Advances in the AIRS Science Team Version-6 Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Susskind, Joel; Blaisdell, John; Iredell, Lena; Molnar, Gyula
2012-01-01
AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. The Goddard DISC has analyzed AIRS/AMSU observations, covering the period September 2002 until the present, using the AIRS Science Team Version-S retrieval algorithm. These products have been used by many researchers to make significant advances in both climate and weather applications. The AIRS Science Team Version-6 Retrieval, which will become operation in mid-20l2, contains many significant theoretical and practical improvements compared to Version-5 which should further enhance the utility of AIRS products for both climate and weather applications. In particular, major changes have been made with regard to the algOrithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the retrieval procedure; 3) compute Outgoing Longwave Radiation; and 4) determine Quality Control. This paper will describe these advances found in the AIRS Version-6 retrieval algorithm and demonstrate the improvement of AIRS Version-6 products compared to those obtained using Version-5,
Importance of Winds and Soil Moistures to the US Summertime Drought of 1988: A GCM Simulation Study
NASA Technical Reports Server (NTRS)
Mocko, David M.; Sud, Y. C.; Lau, William K. M. (Technical Monitor)
2001-01-01
The climate version of NASA's GEOS 2 GCM did not simulate a realistic 1988 summertime drought in the central United States (Mocko et al., 1999). Despite several new upgrades to the model's parameterizations, as well as finer grid spacing from 4x5 degrees to 2x2.5 degrees, no significant improvements were noted in the model's simulation of the U.S. drought.
Personal, Role, Structural, Alternative and Affective Correlates of Organizational Commitment.
1982-01-01
relationships (p. 79). Farrell and Rusbult (1981) seek to integrate the commitment literature through a model based on the social psychological exchange theory...permits testing a number of the components of the Farrell and Rusbult model . Hypotheses Drawing on the recent reviews and conceptual developments of... Climate Questionnalre (OCQ), (Porter et al., 1974) and the short version of the Job Diagnostic Survey (JDS), (Hackman and Oldham, 1975). The JDS scales
NASA Astrophysics Data System (ADS)
Passow, Christian; Donner, Reik
2017-04-01
Quantile mapping (QM) is an established concept that allows to correct systematic biases in multiple quantiles of the distribution of a climatic observable. It shows remarkable results in correcting biases in historical simulations through observational data and outperforms simpler correction methods which relate only to the mean or variance. Since it has been shown that bias correction of future predictions or scenario runs with basic QM can result in misleading trends in the projection, adjusted, trend preserving, versions of QM were introduced in the form of detrended quantile mapping (DQM) and quantile delta mapping (QDM) (Cannon, 2015, 2016). Still, all previous versions and applications of QM based bias correction rely on the assumption of time-independent quantiles over the investigated period, which can be misleading in the context of a changing climate. Here, we propose a novel combination of linear quantile regression (QR) with the classical QM method to introduce a consistent, time-dependent and trend preserving approach of bias correction for historical and future projections. Since QR is a regression method, it is possible to estimate quantiles in the same resolution as the given data and include trends or other dependencies. We demonstrate the performance of the new method of linear regression quantile mapping (RQM) in correcting biases of temperature and precipitation products from historical runs (1959 - 2005) of the COSMO model in climate mode (CCLM) from the Euro-CORDEX ensemble relative to gridded E-OBS data of the same spatial and temporal resolution. A thorough comparison with established bias correction methods highlights the strengths and potential weaknesses of the new RQM approach. References: A.J. Cannon, S.R. Sorbie, T.Q. Murdock: Bias Correction of GCM Precipitation by Quantile Mapping - How Well Do Methods Preserve Changes in Quantiles and Extremes? Journal of Climate, 28, 6038, 2015 A.J. Cannon: Multivariate Bias Correction of Climate Model Outputs - Matching Marginal Distributions and Inter-variable Dependence Structure. Journal of Climate, 29, 7045, 2016
Domínguez, Evelia; Martín, Patricia; Martín-Albo, José; Núñez, Juan L; León, Jaime
2010-11-01
The aim of the present research was to translate and to analyze the psychometric properties of the Spanish version of the Satisfaction of Psychological Needs Scale, using a sample of 284 athletes (204 male and 78 female). Results of the confirmatory factor analysis confirmed the correlated three-factor structure of the scale. Furthermore, the results showed evidence of convergence validity with the Basic Psychological Needs in Exercise Scale. The predictive validity was tested using a structural equation model in which task orientation climate predicted the three basic psychological needs and these, in turn, intrinsic motivation. Likewise, we documented evidence of reliability, analyzed as internal consistency and temporal stability. Results partially support the use of the Spanish version of the scale in sports.
The Norwegian Earth System Model, NorESM1-M - Part 2: Climate response and scenario projections
NASA Astrophysics Data System (ADS)
Iversen, T.; Bentsen, M.; Bethke, I.; Debernard, J. B.; Kirkevåg, A.; Seland, Ø.; Drange, H.; Kristjansson, J. E.; Medhaug, I.; Sand, M.; Seierstad, I. A.
2013-03-01
NorESM is a generic name of the Norwegian earth system model. The first version is named NorESM1, and has been applied with medium spatial resolution to provide results for CMIP5 (http://cmip-pcmdi.llnl.gov/cmip5/index.html) without (NorESM1-M) and with (NorESM1-ME) interactive carbon-cycling. Together with the accompanying paper by Bentsen et al. (2012), this paper documents that the core version NorESM1-M is a valuable global climate model for research and for providing complementary results to the evaluation of possible anthropogenic climate change. NorESM1-M is based on the model CCSM4 operated at NCAR, but the ocean model is replaced by a modified version of MICOM and the atmospheric model is extended with online calculations of aerosols, their direct effect and their indirect effect on warm clouds. Model validation is presented in the companion paper (Bentsen et al., 2012). NorESM1-M is estimated to have equilibrium climate sensitivity of ca. 2.9 K and a transient climate response of ca. 1.4 K. This sensitivity is in the lower range amongst the models contributing to CMIP5. Cloud feedbacks dampen the response, and a strong AMOC reduces the heat fraction available for increasing near-surface temperatures, for evaporation and for melting ice. The future projections based on RCP scenarios yield a global surface air temperature increase of almost one standard deviation lower than a 15-model average. Summer sea-ice is projected to decrease considerably by 2100 and disappear completely for RCP8.5. The AMOC is projected to decrease by 12%, 15-17%, and 32% for the RCP2.6, 4.5, 6.0, and 8.5, respectively. Precipitation is projected to increase in the tropics, decrease in the subtropics and in southern parts of the northern extra-tropics during summer, and otherwise increase in most of the extra-tropics. Changes in the atmospheric water cycle indicate that precipitation events over continents will become more intense and dry spells more frequent. Extra-tropical storminess in the Northern Hemisphere is projected to shift northwards. There are indications of more frequent occurrence of spring and summer blocking in the Euro-Atlantic sector, while the amplitude of ENSO events weakens although they tend to appear more frequently. These indications are uncertain because of biases in the model's representation of present-day conditions. Positive phase PNA and negative phase NAO both appear less frequently under the RCP8.5 scenario, but also this result is considered uncertain. Single-forcing experiments indicate that aerosols and greenhouse gases produce similar geographical patterns of response for near-surface temperature and precipitation. These patterns tend to have opposite signs, although with important exceptions for precipitation at low latitudes. The asymmetric aerosol effects between the two hemispheres lead to a southward displacement of ITCZ. Both forcing agents, thus, tend to reduce Northern Hemispheric subtropical precipitation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Busuioc, A.; Storch, H. von; Schnur, R.
Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). Themore » climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in time-slice mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 x CO{sub 2} GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is concluded that the downscaling technique is adequate for describing climatically changing regional and local conditions, at least for precipitation in Romania during winter.« less
Possible climate change over Eurasia under different emission scenarios
NASA Astrophysics Data System (ADS)
Sokolov, A. P.; Monier, E.; Scott, J. R.; Forest, C. E.; Schlosser, C. A.
2011-12-01
In an attempt to evaluate possible climate change over EURASIA, we analyze results of six AMIP type simulations with CAM version 3 (CAM3) at 2x2.5 degree resolution. CAM3 is driven by time series of sea surface temperatures (SSTs) and sea ice obtained by running the MIT IGSM2.3, which consists of a 3D ocean GCM coupled to a zonally-averaged atmospheric climate-chemistry model. In addition to changes in SSTs, CAM3 is forced by changes in greenhouse gases and ozone concentrations, sulfate aerosol forcing and black carbon loading calculated by the IGSM2.3. An essential feature of the IGSM is the possibility to vary its climate sensitivity (using a cloud adjustment technique) and the strength of the aerosol forcing. For consistency, new modules were developed in CAM3 to modify its climate sensitivity and aerosol forcing to match those used in the simulations with the IGSM2.3. The simulations presented in this paper were carried out for two emission scenarios, a "Business as usual" scenario and a 660 ppm of CO2-EQ stabilization, which are similar to the RCP8.5 and RCP4.5 scenarios, respectively. Values of climate sensitivity used in the simulations within the IGSM-CAM framework are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the 20th century climate simulated by different versions of the IGSM with observations. The associated strength of the aerosol forcing was chosen to ensure a good agreement with the observed climate change over the 20th century. Because the concentration of sulfate aerosol significantly decreases over the 21st century in both emissions scenarios, climate changes obtained in these simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.
Possible climate change over Eurasia under different emission scenarios
NASA Astrophysics Data System (ADS)
Sokolov, A. P.; Monier, E.; Gao, X.
2012-12-01
In an attempt to evaluate possible climate change over EURASIA, we analyze results of six AMIP type simulations with CAM version 3 (CAM3) at 2x2.5 degree resolution. CAM3 is driven by time series of sea surface temperatures (SSTs) and sea ice obtained by running the MIT IGSM2.3, which consists of a 3D ocean GCM coupled to a zonally-averaged atmospheric climate-chemistry model. In addition to changes in SSTs, CAM3 is forced by changes in greenhouse gases and ozone concentrations, sulfate aerosol forcing and black carbon loading calculated by the IGSM2.3. An essential feature of the IGSM is the possibility to vary its climate sensitivity (using a cloud adjustment technique) and the strength of the aerosol forcing. For consistency, new modules were developed in CAM3 to modify its climate sensitivity and aerosol forcing to match those used in the simulations with the IGSM2.3. The simulations presented in this paper were carried out for two emission scenarios, a "Business as usual" scenario and a 660 ppm of CO2-EQ stabilization, which are similar to the RCP8.5 and RCP4.5 scenarios, respectively. Values of climate sensitivity used in the simulations within the IGSM-CAM framework are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the 20th century climate simulated by different versions of the IGSM with observations. The associated strength of the aerosol forcing was chosen to ensure a good agreement with the observed climate change over the 20th century. Because the concentration of sulfate aerosol significantly decreases over the 21st century in both emissions scenarios, climate changes obtained in these simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.
The QBO in Two GISS Global Climate Models: 1. Generation of the QBO
NASA Technical Reports Server (NTRS)
Rind, David; Jonas, Jeffrey A.; Balachandra, Nambath; Schmidt, Gavin A.; Lean, Judith
2014-01-01
The adjustment of parameterized gravity waves associated with model convection and finer vertical resolution has made possible the generation of the quasi-biennial oscillation (QBO) in two Goddard Institute for Space Studies (GISS) models, GISS Middle Atmosphere Global Climate Model III and a climate/middle atmosphere version of Model E2. Both extend from the surface to 0.002 hPa, with 2deg × 2.5deg resolution and 102 layers. Many realistic features of the QBO are simulated, including magnitude and variability of its period and amplitude. The period itself is affected by the magnitude of parameterized convective gravity wave momentum fluxes and interactive ozone (which also affects the QBO amplitude and variability), among other forcings. Although varying sea surface temperatures affect the parameterized momentum fluxes, neither aspect is responsible for the modeled variation in QBO period. Both the parameterized and resolved waves act to produce the respective easterly and westerly wind descent, although their effect is offset in altitude at each level. The modeled and observed QBO influences on tracers in the stratosphere, such as ozone, methane, and water vapor are also discussed. Due to the link between the gravity wave parameterization and the models' convection, and the dependence on the ozone field, the models may also be used to investigate how the QBO may vary with climate change.
NASA Astrophysics Data System (ADS)
Stanfield, R. E.; Dong, X.; Xi, B.; Del Genio, A. D.; Minnis, P.; Doelling, D.; Loeb, N. G.
2011-12-01
To better advise policymakers, it is necessary for climate models to provide credible predictions of future climates. Meeting this goal requires climate models to successfully simulate the present and past climates. The past, current and future Earth climate has been simulated by the NASA GISS ModelE climate model and has been summarized by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, AR4, 2007). New simulations from the updated AR5 version of the NASA GISS ModelE GCM have been released to the public community and will be included in the IPCC AR5 ensemble of simulations. Due to the recent nature of these simulations, however, they have yet to be extensively validated against observations. To evaluate the GISS AR5 simulated global clouds and TOA radiation budgets, we have collected and processed the NASA CERES and MODIS observations during the period 2000-2005. In detail, the 1ox1o resolution monthly averaged SYN1 product has been used with combined observations from both Terra and Aqua satellites, and degraded to a 2ox2.5o grid box to match the GCM spatial resolution. These observations are temporally interpolated and fit to data from geostationary satellites to provide time continuity. The GISS AR5 products were downloaded from the CMIP5 (Coupled Model Intercomparison Project Phase 5) for the IPCC-AR5. Preliminary comparisons between GISS AR5 simulations and CERES-MODIS observations have shown that although their annual and seasonal mean CFs agree within a few percent, there are significant differences in several climatic regions. For example, the modeled CFs have positive biases in the Arctic, Antarctic, Tropics, and Sahara Desert, but negative biases over the southern middle latitudes (30-65 oS). The OLR, albedo and NET radiation comparisons are similar to the CF comparison.
NASA Astrophysics Data System (ADS)
Goswami, B. B.; Khouider, B.; Phani, R.; Mukhopadhyay, P.; Majda, A.
2017-01-01
To better represent organized convection in the Climate Forecast System version 2 (CFSv2), a stochastic multicloud model (SMCM) parameterization is adopted and a 15 year climate run is made. The last 10 years of simulations are analyzed here. While retaining an equally good mean state (if not better) as the parent model, the CFS-SMCM simulation shows significant improvement in the synoptic and intraseasonal variability. The CFS-SMCM provides a better account of convectively coupled equatorial waves and the Madden-Julian oscillation. The CFS-SMCM exhibits improvements in northward and eastward propagation of intraseasonal oscillation of convection including the MJO propagation beyond the maritime continent barrier, which is the Achilles Heel for coarse-resolution global climate models (GCMs). The distribution of precipitation events is better simulated in CFSsmcm and spreads naturally toward high-precipitation events. Deterministic GCMs tend to simulate a narrow distribution with too much drizzling precipitation and too little high-precipitation events.
A Transient Initialization Routine of the Community Ice Sheet Model for the Greenland Ice Sheet
NASA Astrophysics Data System (ADS)
van der Laan, Larissa; van den Broeke, Michiel; Noël, Brice; van de Wal, Roderik
2017-04-01
The Community Ice Sheet Model (CISM) is to be applied in future simulations of the Greenland Ice Sheet under a range of climate change scenarios, determining the sensitivity of the ice sheet to individual climatic forcings. In order to achieve reliable results regarding ice sheet stability and assess the probability of future occurrence of tipping points, a realistic initial ice sheet geometry is essential. The current work describes and evaluates the development of a transient initialization routine, using NGRIP 18O isotope data to create a temperature anomaly field. Based on the latter, surface mass balance components runoff and precipitation are perturbed for the past 125k years. The precipitation and runoff fields originate from a downscaled 1 km resolution version of the regional climate model RACMO2.3 for the period 1961-1990. The result of the initialization routine is a present-day ice sheet with a transient memory of the last glacial-interglacial cycle, which will serve as the future runs' initial condition.
Regional Climate Modeling over the Glaciated Regions of the Canadian High Arctic
NASA Astrophysics Data System (ADS)
Gready, Benjamin P.
The Canadian Arctic Islands (CAI) contain the largest concentration of terrestrial ice outside of the continental ice sheets. Mass loss from this region has recently increased sharply due to above average summer temperatures. Thus, increasing the understanding of the mechanisms responsible for mass loss from this region is critical. Previously, Regional Climate Models (RCMs) have been utilized to estimate climatic balance over Greenland and Antarctica. This method offers the opportunity to study a full suite of climatic variables over extensive spatially distributed grids. However, there are doubts of the applicability of such models to the CAI, given the relatively complex topography of the CAI. To test RCMs in the CAI, the polar version of the regional climate model MM5 was run at high resolution over Devon Ice Cap. At low altitudes, residuals (computed through comparisons with in situ measurements) in the net radiation budget were driven primarily by residuals in net shortwave (NSW) radiation. Residuals in NSW are largely due to inaccuracies in modeled cloud cover and modeled albedo. Albedo on glaciers and ice sheets is oversimplified in Polar MM5 and its successor, the Polar version of the Weather Research and Forecast model (Polar WRF), and is an obvious place for model improvement. Subsequently, an inline parameterization of albedo for Polar WRF was developed as a function of the depth, temperature and age of snow. The parameterization was able to reproduce elevation gradients of seasonal mean albedo derived from satellite albedo measurements (MODIS MOD10A1 daily albedo), on the western slope of the Greenland Ice Sheet for three years. Feedbacks between modelled albedo and modelled surface energy budget components were identified. The shortwave radiation flux feeds back positively with changes to albedo, whereas the longwave, turbulent and ground energy fluxes all feed back negatively, with a maximum combined magnitude of two thirds of the shortwave feedback magnitude. These strong feedbacks demonstrate that an accurate albedo parameterization must be run inline within an RCM, to accurately quantify the net surface energy budget of an ice sheet. Finally, Polar WRF, with the improved albedo parameterization, was used to simulate climatic balance over the Queen Elizabeth Islands for the summers of 2001 to 2008. Climatic balance was derived from the output using energy balance and temperature index melt models. Regional mass balance was calculated by combining climatic balance with estimates of iceberg discharge. Mass balance estimates from the model agreed, within the bounds of uncertainty, with estimates from previous studies, thus supporting the assertion that mass loss from the QEI accelerated during the first decade of the 21st century. Melt rates on the seven major icecaps of the QEI became more correlated to one another during the period 2001-2008. However, precipitation became less correlated from 2003-2008. These observations are coincident with dramatic increases in melt on all of the ice caps, and it is speculated that both are caused by decreases in the scale of disturbances delivering precipitation to the region over time.
Climate-FVS Version 2: Content, users guide, applications, and behavior
Nicholas L. Crookston
2014-01-01
Climate change in the 21st Century is projected to cause widespread changes in forest ecosystems. Climate-FVS is a modification to the Forest Vegetation Simulator designed to take climate change into account when predicting forest dynamics at decadal to century time scales. Individual tree climate viability scores measure the likelihood that the climate at a given...
Upper-Level Mediterranean Oscillation index and seasonal variability of rainfall and temperature
NASA Astrophysics Data System (ADS)
Redolat, Dario; Monjo, Robert; Lopez-Bustins, Joan A.; Martin-Vide, Javier
2018-02-01
The need for early seasonal forecasts stimulates continuous research in climate teleconnections. The large variability of the Mediterranean climate presents a greater difficulty in predicting climate anomalies. This article reviews teleconnection indices commonly used for the Mediterranean basin and explores possible extensions of one of them, the Mediterranean Oscillation index (MOi). In particular, the anomalies of the geopotential height field at 500 hPa are analyzed using segmentation of the Mediterranean basin in seven spatial windows: three at eastern and four at western. That is, different versions of an Upper-Level Mediterranean Oscillation index (ULMOi) were calculated, and monthly and annual variability of precipitation and temperature were analyzed for 53 observatories from 1951 to 2015. Best versions were selected according to the Pearson correlation, its related p value, and two measures of standardized error. The combination of the Balearic Sea and Libya/Egypt windows was the best for precipitation and temperature, respectively. The ULMOi showed the highest predictive ability in combination with the Atlantic Multidecadal Oscillation index (AMOi) for the annual temperature throughout the Mediterranean basin. The best model built from the indices presented a final mean error between 15 and 25% in annual precipitation for most of the studied area.
A spectral nudging method for the ACCESS1.3 atmospheric model
NASA Astrophysics Data System (ADS)
Uhe, P.; Thatcher, M.
2015-06-01
A convolution-based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow for flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10-30 times compared with a version using a two-dimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge.
A spectral nudging method for the ACCESS1.3 atmospheric model
NASA Astrophysics Data System (ADS)
Uhe, P.; Thatcher, M.
2014-10-01
A convolution based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10 to 30 times compared with a version using a two-dimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge.
NASA Astrophysics Data System (ADS)
Kemp, E. M.; Putman, W. M.; Gurganus, J.; Burns, R. W.; Damon, M. R.; McConaughy, G. R.; Seablom, M. S.; Wojcik, G. S.
2009-12-01
We present a regional downscaling system (RDS) suitable for high-resolution weather and climate simulations in multiple supercomputing environments. The RDS is built on the NASA Workflow Tool, a software framework for configuring, running, and managing computer models on multiple platforms with a graphical user interface. The Workflow Tool is used to run the NASA Goddard Earth Observing System Model Version 5 (GEOS-5), a global atmospheric-ocean model for weather and climate simulations down to 1/4 degree resolution; the NASA Land Information System Version 6 (LIS-6), a land surface modeling system that can simulate soil temperature and moisture profiles; and the Weather Research and Forecasting (WRF) community model, a limited-area atmospheric model for weather and climate simulations down to 1-km resolution. The Workflow Tool allows users to customize model settings to user needs; saves and organizes simulation experiments; distributes model runs across different computer clusters (e.g., the DISCOVER cluster at Goddard Space Flight Center, the Cray CX-1 Desktop Supercomputer, etc.); and handles all file transfers and network communications (e.g., scp connections). Together, the RDS is intended to aid researchers by making simulations as easy as possible to generate on the computer resources available. Initial conditions for LIS-6 and GEOS-5 are provided by Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis data stored on DISCOVER. The LIS-6 is first run for 2-4 years forced by MERRA atmospheric analyses, generating initial conditions for the WRF soil physics. GEOS-5 is then initialized from MERRA data and run for the period of interest. Large-scale atmospheric data, sea-surface temperatures, and sea ice coverage from GEOS-5 are used as boundary conditions for WRF, which is run for the same period of interest. Multiply nested grids are used for both LIS-6 and WRF, with the innermost grid run at a resolution sufficient for typical local weather features (terrain, convection, etc.) All model runs, restarts, and file transfers are coordinated by the Workflow Tool. Two use cases are being pursued. First, the RDS generates regional climate simulations down to 4-km for the Chesapeake Bay region, with WRF output provided as input to more specialized models (e.g., ocean/lake, hydrological, marine biology, and air pollution). This will allow assessment of climate impact on local interests (e.g., changes in Bay water levels and temperatures, innundation, fish kills, etc.) Second, the RDS generates high-resolution hurricane simulations in the tropical North Atlantic. This use case will support Observing System Simulation Experiments (OSSEs) of dynamically-targeted lidar observations as part of the NASA Sensor Web Simulator project. Sample results will be presented at the AGU Fall Meeting.
An update to the Surface Ocean CO2 Atlas (SOCAT version 2)
NASA Astrophysics Data System (ADS)
Bakker, D. C. E.; Pfeil, B.; Smith, K.; Hankin, S.; Olsen, A.; Alin, S. R.; Cosca, C.; Harasawa, S.; Kozyr, A.; Nojiri, Y.; O'Brien, K. M.; Schuster, U.; Telszewski, M.; Tilbrook, B.; Wada, C.; Akl, J.; Barbero, L.; Bates, N.; Boutin, J.; Cai, W.-J.; Castle, R. D.; Chavez, F. P.; Chen, L.; Chierici, M.; Currie, K.; de Baar, H. J. W.; Evans, W.; Feely, R. A.; Fransson, A.; Gao, Z.; Hales, B.; Hardman-Mountford, N.; Hoppema, M.; Huang, W.-J.; Hunt, C. W.; Huss, B.; Ichikawa, T.; Johannessen, T.; Jones, E. M.; Jones, S. D.; Jutterström, S.; Kitidis, V.; Körtzinger, A.; Landschtzer, P.; Lauvset, S. K.; Lefèvre, N.; Manke, A. B.; Mathis, J. T.; Merlivat, L.; Metzl, N.; Murata, A.; Newberger, T.; Ono, T.; Park, G.-H.; Paterson, K.; Pierrot, D.; Ríos, A. F.; Sabine, C. L.; Saito, S.; Salisbury, J.; Sarma, V. V. S. S.; Schlitzer, R.; Sieger, R.; Skjelvan, I.; Steinhoff, T.; Sullivan, K.; Sun, H.; Sutton, A. J.; Suzuki, T.; Sweeney, C.; Takahashi, T.; Tjiputra, J.; Tsurushima, N.; van Heuven, S. M. A. C.; Vandemark, D.; Vlahos, P.; Wallace, D. W. R.; Wanninkhof, R.; Watson, A. J.
2013-08-01
The Surface Ocean CO2 Atlas (SOCAT) is an effort by the international marine carbon research community. It aims to improve access to carbon dioxide measurements in the surface oceans by regular releases of quality controlled and fully documented synthesis and gridded fCO2 (fugacity of carbon dioxide) products. SOCAT version 2 presented here extends the data set for the global oceans and coastal seas by four years and has 10.1 million surface water fCO2 values from 2660 cruises between 1968 and 2011. The procedures for creating version 2 have been comparable to those for version 1. The SOCAT website (http://www.socat.info/) provides access to the individual cruise data files, as well as to the synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Scientific users can also retrieve the data as downloadable files or via Ocean Data View. Version 2 enables carbon specialists to expand their studies until 2011. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longer-term variation, as well as initialisation or validation of ocean carbon models and coupled-climate carbon models.
Arctic climate response to geoengineering with stratospheric sulfate aerosols
NASA Astrophysics Data System (ADS)
McCusker, K. E.; Battisti, D. S.; Bitz, C. M.
2010-12-01
Recent warming and record summer sea-ice area minimums have spurred expressions of concern for arctic ecosystems, permafrost, and polar bear populations, among other things. Geoengineering by stratospheric sulfate aerosol injections to deliberately cancel the anthropogenic temperature rise has been put forth as a possible solution to restoring Arctic (and global) climate to modern conditions. However, climate is particularly sensitive in the northern high latitudes, responding easily to radiative forcing changes. To that end, we explore the extent to which tropical injections of stratospheric sulfate aerosol can accomplish regional cancellation in the Arctic. We use the Community Climate System Model version 3 global climate model to execute simulations with combinations of doubled CO2 and imposed stratospheric sulfate burdens to investigate the effects on high latitude climate. We further explore the sensitivity of the polar climate to ocean dynamics by running a suite of simulations with and without ocean dynamics, transiently and to equilibrium respectively. We find that, although annual, global mean temperature cancellation is accomplished, there is over-cooling on land in Arctic summer, but residual warming in Arctic winter, which is largely due to atmospheric circulation changes. Furthermore, the spatial extent of these features and their concurrent impacts on sea-ice properties are modified by the inclusion of ocean dynamical feedbacks.
Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5
NASA Astrophysics Data System (ADS)
Dufresne, J.-L.; Foujols, M.-A.; Denvil, S.; Caubel, A.; Marti, O.; Aumont, O.; Balkanski, Y.; Bekki, S.; Bellenger, H.; Benshila, R.; Bony, S.; Bopp, L.; Braconnot, P.; Brockmann, P.; Cadule, P.; Cheruy, F.; Codron, F.; Cozic, A.; Cugnet, D.; de Noblet, N.; Duvel, J.-P.; Ethé, C.; Fairhead, L.; Fichefet, T.; Flavoni, S.; Friedlingstein, P.; Grandpeix, J.-Y.; Guez, L.; Guilyardi, E.; Hauglustaine, D.; Hourdin, F.; Idelkadi, A.; Ghattas, J.; Joussaume, S.; Kageyama, M.; Krinner, G.; Labetoulle, S.; Lahellec, A.; Lefebvre, M.-P.; Lefevre, F.; Levy, C.; Li, Z. X.; Lloyd, J.; Lott, F.; Madec, G.; Mancip, M.; Marchand, M.; Masson, S.; Meurdesoif, Y.; Mignot, J.; Musat, I.; Parouty, S.; Polcher, J.; Rio, C.; Schulz, M.; Swingedouw, D.; Szopa, S.; Talandier, C.; Terray, P.; Viovy, N.; Vuichard, N.
2013-05-01
We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.
NASA Technical Reports Server (NTRS)
Lunt, Daniel J.; Huber, Matthew; Anagnostou, Eleni; Baatsen, Michiel L. J.; Caballero, Rodrigo; DeConto, Rob; Dijkstra, Henk A.; Donnadieu, Yannick; Evans, David; Feng, Ran;
2017-01-01
Past warm periods provide an opportunity to evaluate climate models under extreme forcing scenarios, in particular high ( greater than 800 ppmv) atmospheric CO2 concentrations. Although a post hoc intercomparison of Eocene (approximately 50 Ma) climate model simulations and geological data has been carried out previously, models of past high-CO2 periods have never been evaluated in a consistent framework. Here, we present an experimental design for climate model simulations of three warm periods within the early Eocene and the latest Paleocene (the EECO, PETM, and pre-PETM). Together with the CMIP6 pre-industrial control and abrupt 4(times) CO2 simulations, and additional sensitivity studies, these form the first phase of DeepMIP - the Deep-time Model Intercomparison Project, itself a group within the wider Paleoclimate Modeling Intercomparison Project (PMIP). The experimental design specifies and provides guidance on boundary conditions associated with palaeogeography, greenhouse gases, astronomical configuration, solar constant, land surface processes, and aerosols. Initial conditions, simulation length, and output variables are also specified. Finally, we explain how the geological data sets, which will be used to evaluate the simulations, will be developed.
Simulating land use changes in the Upper Narew catchment using the RegCM model
NASA Astrophysics Data System (ADS)
Liszewska, Malgorzata; Osuch, Marzena; Romanowicz, Renata
2010-05-01
Catchment hydrology is influenced by climate forcing in the form of precipitation, temperature, evapotranspiration and human interactions such as land use and water management practices. The difficulty in separating different causes of change in a hydrological regime results from the complexity of interactions between those three factors and catchment responses and the uncertainty and scarcity of available observations. This paper describes an application of a regional climate model to simulate the variability in precipitation, temperature, evaporation and discharge under different land use parameterizations, using the Upper Narew catchment (north-east Poland) as a case study. We use RegCM3 model, developed at the International Centre for Theoretical Physics, Trieste, Italy. The model's dynamic core is based on the hydrostatic version of the NCAR/PSU Mesoscale Model version 5 (primitive equations, hydrostatic, compressible, sigma-vertical coordinate). The physical input includes radiation transfer, large-scale and convective precipitation, Planetary Boundary Layer, biosphere. The RegCM3 model has options to interface with a variety of re-analyses and GCM boundary conditions, and can thus be used for scenario assessments. The variability of hydrological conditions in response to regional climate model projections is modeled using an integrated Data Based Mechanistic (DBM) rainfall-flow/flow-routing model of the Upper River Narew catchment. The modelling tool developed is formulated in the MATLAB-SIMULINK language. The basic system structure includes rainfall-flow and flow routing modules, based on a Stochastic Transfer Function (STF) approach combined with a nonlinear transformation of rainfall into effective rainfall. We analyse the signal resulting from modified land use in a given region. 10 month-long runs have been performed from February to November for the period of 1991-2000 based on the NCEP re-analyses. The land use data have been taken from the GLCC dataset and the Corine Land Cover programme (http://dataservice.eea.europa.eu/, GIOS, Poland). Simulations taking into account land use modifications in the catchment are compared with the reference simulations under no change in land use in the region. In the second part of the paper we discuss the application of the RegCM3 model in two climate change scenarios (SRES A2 and B1). The study is a contribution to the LUWR programme (http://luwr.igf.edu.pl).
Impacts of Stratospheric Sulfate Geoengineering on PM2.5
NASA Astrophysics Data System (ADS)
Robock, A.; Xia, L.; Tilmes, S.; Mills, M. J.; Richter, J.; Kravitz, B.; MacMartin, D.
2017-12-01
Particulate matter (PM) includes sulfate, nitrate, organic carbon, elemental carbon, soil dust, and sea salt. The first four components are mostly present near the ground as fine particulate matter with a diameter less than 2.5 µm (PM2.5), and these are of the most concern for human health. PM is efficiently scavenged by precipitation, which is its main atmospheric sink. Here we examine the impact of stratospheric climate engineering on this important pollutant and health risk, taking advantage of two sets of climate model simulations conducted at the National Center for Atmospheric Research. We use the full tropospheric and stratospheric chemistry version of the Community Earth System Model - Community Atmospheric Model 4 (CESM CAM4-chem) with a horizontal resolution of 0.9° x 1.25° lat-lon to simulate a stratospheric sulfate injection climate intervention of 8 Tg SO2 yr-1 combined with an RCP6.0 global warming forcing, the G4 Specified Stratospheric Aerosol (G4SSA) scenario. We also analyze the output from a 20-member ensemble of Community Earth System Model, version 1 with the Whole Atmosphere Community Climate Model as its atmospheric component (CESM1(WACCM)) simulations, also at 0.9° x 1.25° lat-lon resolution, with sulfur dioxide injection at 15°N, 15°S, 30°N, and 30°S varying in time to balance RCP8.5 forcing. While the CESM CAM4-chem model has full tropospheric and stratospheric chemistry, CESM1(WACCM) has an internally generated quasi-biennial oscillation and a comprehensive tropospheric and stratospheric sulfate aerosol treatment, but only stratospheric chemistry. For G4SSA, there are a global temperature reduction of 0.8 K and global averaged precipitation decrease of 3% relative to RCP6.0. The global averaged surface PM2.5 reduces about 1% compared with RCP6.0, mainly over Eurasian and East Asian regions in Northern Hemisphere winter. The PM2.5 concentration change is a combination of effects from tropospheric chemistry and precipitation changes. We compare those changes to the impacts from the CESM1(WACCM) simulations.
Updates to the Demographic and Spatial Allocation Models to ...
EPA announced the availability of the draft report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) for a 30-day public comment period. The ICLUS version 2 (v2) modeling tool furthered land change modeling by providing nationwide housing development scenarios up to 2100. ICLUS V2 includes updated population and land use data sets and addressing limitations identified in ICLUS v1 in both the migration and spatial allocation models. The companion user guide describes the development of ICLUS v2 and the updates that were made to the original data sets and the demographic and spatial allocation models. [2017 UPDATE] Get the latest version of ICLUS and stay up-to-date by signing up to the ICLUS mailing list. The GIS tool enables users to run SERGoM with the population projections developed for the ICLUS project and allows users to modify the spatial allocation housing density across the landscape.
Emissions pathways, climate change, and impacts on California
Hayhoe, K.; Cayan, D.; Field, C.B.; Frumhoff, P.C.; Maurer, E.P.; Miller, N.L.; Moser, S.C.; Schneider, S.H.; Cahill, K.N.; Cleland, E.E.; Dale, L.; Drapek, R.; Hanemann, R.M.; Kalkstein, L.S.; Lenihan, J.; Lunch, C.K.; Neilson, R.P.; Sheridan, S.C.; Verville, J.H.
2004-01-01
The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50-75%; and Sierra snowpack is reduced 30-70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75-90%; and snowpack declines 73-90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades.
NASA Technical Reports Server (NTRS)
Smith, Laura D.; Vonder Haar, Thomas H.
1991-01-01
Simultaneously conducted observations of the earth radiation budget and the cloud amount estimates, taken during the June 1979 - May 1980 Nimbus 7 mission were used to show interactions between the cloud amount and raidation and to verify a long-term climate simulation obtained with the latest version of the NCAR Community Climate Model (CCM). The parameterization of the radiative, dynamic, and thermodynamic processes produced the mean radiation and cloud quantities that were in reasonable agreement with satellite observations, but at the expense of simulating their short-term fluctuations. The results support the assumption that the inclusion of the cloud liquid water (ice) variable would be the best mean to reduce the blinking of clouds in NCAR CCM.
GLEAM version 3: Global Land Evaporation Datasets and Model
NASA Astrophysics Data System (ADS)
Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.
2015-12-01
Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ observations. It is also shown that the performance of the revised model is higher compared to the original one.
Update of global TC simulations using a variable resolution non-hydrostatic model
NASA Astrophysics Data System (ADS)
Park, S. H.
2017-12-01
Using in a variable resolution meshes in MPAS during 2017 summer., Tropical cyclone (TC) forecasts are simulated. Two physics suite are tested to explore performance and bias of each physics suite for TC forecasting. A WRF physics suite is selected from experience on weather forecasting and CAM (Community Atmosphere Model) physics is taken from a AMIP type climate simulation. Based on the last year results from CAM5 physical parameterization package and comparing with WRF physics, we investigated a issue with intensity bias using updated version of CAM physics (CAM6). We also compared these results with coupled version of TC simulations. During this talk, TC structure will be compared specially around of boundary layer and investigate their relationship between TC intensity and different physics package.
Projecting climate-driven increases in North American fire activity
NASA Astrophysics Data System (ADS)
Wang, D.; Morton, D. C.; Collatz, G. J.
2013-12-01
Climate regulates fire activity through controls on vegetation productivity (fuels), lightning ignitions, and conditions governing fire spread. In many regions of the world, human management also influences the timing, duration, and extent of fire activity. These coupled interactions between human and natural systems make fire a complex component of the Earth system. Satellite data provide valuable information on the spatial and temporal dynamics of recent fire activity, as active fires, burned area, and land cover information can be combined to separate wildfires from intentional burning for agriculture and forestry. Here, we combined satellite-derived burned area data with land cover and climate data to assess fire-climate relationships in North America between 2000-2012. We used the latest versions of the Global Fire Emissions Database (GFED) burned area product and Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate data to develop regional relationships between burned area and potential evaporation (PE), an integrated dryness metric. Logistic regression models were developed to link burned area with PE and individual climate variables during and preceding the fire season, and optimal models were selected based on Akaike Information Criterion (AIC). Overall, our model explained 85% of the variance in burned area since 2000 across North America. Fire-climate relationships from the era of satellite observations provide a blueprint for potential changes in fire activity under scenarios of climate change. We used that blueprint to evaluate potential changes in fire activity over the next 50 years based on twenty models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). All models suggest an increase of PE under low and high emissions scenarios (Representative Concentration Pathways (RCP) 4.5 and 8.5, respectively), with largest increases in projected burned area across the western US and central Canada. Overall, near-term climate projections point to pronounced changes in fire season length, total burned area, and the frequency of extreme events across North America by 2050.
Toward Seasonal Forecasting of Global Droughts: Evaluation over USA and Africa
NASA Astrophysics Data System (ADS)
Wood, Eric; Yuan, Xing; Roundy, Joshua; Sheffield, Justin; Pan, Ming
2013-04-01
Extreme hydrologic events in the form of droughts are significant sources of social and economic damage. In the United States according to the National Climatic Data Center, the losses from drought exceed US210 billion during 1980-2011, and account for about 24% of all losses from major weather disasters. Internationally, especially for the developing world, drought has had devastating impacts on local populations through food insecurity and famine. Providing reliable drought forecasts with sufficient early warning will help the governments to move from the management of drought crises to the management of drought risk. After working on drought monitoring and forecasting over the USA for over 10 years, the Princeton land surface hydrology group is now developing a global drought monitoring and forecasting system using a dynamical seasonal climate-hydrologic LSM-model (CHM) approach. Currently there is an active debate on the merits of the CHM-based seasonal hydrologic forecasts as compared to Ensemble Streamflow Prediction (ESP). We use NCEP's operational forecast system, the Climate Forecast System version 2 (CFSv2) and its previous version CFSv1, to investigate the value of seasonal climate model forecasts by conducting a set of 27-year seasonal hydrologic hindcasts over the USA. Through Bayesian downscaling, climate models have higher squared correlation (R2) and smaller error than ESP for monthly precipitation averaged over major river basins across the USA, and the forecasts conditional on ENSO show further improvements (out to four months) over river basins in the southern USA. All three approaches have plausible predictions of soil moisture drought frequency over central USA out to six months because of strong soil moisture memory, and seasonal climate models provide better results over central and eastern USA. The R2 of drought extent is higher for arid basins and for the forecasts initiated during dry seasons, but significant improvements from CFSv2 occur in different seasons for different basins. The R2 of drought severity accumulated over USA is higher during winter, and climate models present added value especially at long leads. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the realtime data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for estimating a climatology against which current conditions can be compared. Based on our established experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML), we use the downscaled CFSv2 climate forcings to drive the re-calibrated VIC model and produce 6-month, 20-member ensemble hydrologic forecasts over Africa starting on the 1st of each calendar month during 1982-2007. Our CHM-based seasonal hydrologic forecasts are now being analyzed for its skill in predicting short-term soil moisture droughts over Africa. Besides relying on a single seasonal climate model or a single drought index, preliminary forecast results will be presented using multiple seasonal climate models based on the NOAA-supported National Multi-Model Ensemble (NMME) project, and with multiple drought indices. Results will be presented for the USA NIDIS test beds such as Southeast US and Colorado NIDIS (National Integrated Drought Information System) test beds, and potentially for other regions of the globe.
NASA Astrophysics Data System (ADS)
Zhang, Y.; Chen, W.; Li, J.
2013-12-01
Climate change may alter the spatial distribution, composition, structure, and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate solar radiation absorbed by individual plants for understanding and predicting their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the analytical solutions of random distributions of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and is suitable for ecological models to simulate long-term transient responses of plant communities to climate change.
Extratropical Respones to Amazon Deforestation
NASA Astrophysics Data System (ADS)
Badger, A.; Dirmeyer, P.
2014-12-01
Land-use change (LUC) is known to impact local climate conditions through modifications of land-atmosphere interactions. Large-scale LUC, such as Amazon deforestation, could have a significant effect on the local and regional climates. The question remains as to what the global impact of large-scale LUC could be, as previous modeling studies have shown non-local responses due to Amazon deforestation. A common shortcoming in many previous modeling studies is the use of prescribed ocean conditions, which can act as a boundary condition to dampen the global response with respect to changes in the mean and variability. Using fully coupled modeling simulations with the Community Earth System Model version 1.2.0, the Amazon rainforest has been replaced with a distribution of representative tropical crops. Through the modifications of local land-atmosphere interactions, a significant change in the region, both at the surface and throughout the atmosphere, can be quantified. Accompanying these local changes are significant changes to the atmospheric circulation across all scales, thus modifying regional climates in other locales. Notable impacts include significant changes in precipitation, surface fluxes, basin-wide sea surface temperatures and ENSO behavior.
NASA Astrophysics Data System (ADS)
Hempelmann, Nils; Ehbrecht, Carsten; Alvarez-Castro, Carmen; Brockmann, Patrick; Falk, Wolfgang; Hoffmann, Jörg; Kindermann, Stephan; Koziol, Ben; Nangini, Cathy; Radanovics, Sabine; Vautard, Robert; Yiou, Pascal
2018-01-01
Analyses of extreme weather events and their impacts often requires big data processing of ensembles of climate model simulations. Researchers generally proceed by downloading the data from the providers and processing the data files ;at home; with their own analysis processes. However, the growing amount of available climate model and observation data makes this procedure quite awkward. In addition, data processing knowledge is kept local, instead of being consolidated into a common resource of reusable code. These drawbacks can be mitigated by using a web processing service (WPS). A WPS hosts services such as data analysis processes that are accessible over the web, and can be installed close to the data archives. We developed a WPS named 'flyingpigeon' that communicates over an HTTP network protocol based on standards defined by the Open Geospatial Consortium (OGC), to be used by climatologists and impact modelers as a tool for analyzing large datasets remotely. Here, we present the current processes we developed in flyingpigeon relating to commonly-used processes (preprocessing steps, spatial subsets at continent, country or region level, and climate indices) as well as methods for specific climate data analysis (weather regimes, analogues of circulation, segetal flora distribution, and species distribution models). We also developed a novel, browser-based interactive data visualization for circulation analogues, illustrating the flexibility of WPS in designing custom outputs. Bringing the software to the data instead of transferring the data to the code is becoming increasingly necessary, especially with the upcoming massive climate datasets.
Simulating post-wildfire forest trajectories under alternative climate and management scenarios.
Tarancón, Alicia Azpeleta; Fulé, Peter Z; Shive, Kristen L; Sieg, Carolyn H; Meador, Andrew Sánchez; Strom, Barbara
Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned multispecies forest of Arizona, USA. The incorporation of seven combinations of General Circulation Models (GCM) and emissions scenarios altered long-term (100 years) predictions of future forest condition compared to a No Climate Change (NCC) scenario, which forecast a gradual increase to high levels of forest density and carbon stock. In contrast, emissions scenarios that included continued high greenhouse gas releases led to near-complete deforestation by 2111. GCM-emissions scenario combinations that were less severe reduced forest structure and carbon stock relative to NCC. Fuel reduction treatments that had been applied prior to the severe wildfire did have persistent effects, especially under NCC, but were overwhelmed by increasingly severe climate change. We tested six management strategies aimed at sustaining future forests: prescribed burning at 5, 10, or 20-year intervals, thinning 40% or 60% of stand basal area, and no treatment. Severe climate change led to deforestation under all management regimes, but important differences emerged under the moderate scenarios: treatments that included regular prescribed burning fostered low density, wildfire-resistant forests composed of the naturally dominant species, ponderosa pine. Non-fire treatments under moderate climate change were forecast to become dense and susceptible to severe wildfire, with a shift to dominance by sprouting species. Current U.S. forest management requires modeling of future scenarios but does not mandate consideration of climate change effects. However, this study showed substantial differences in model outputs depending on climate and management actions. Managers should incorporate climate change into the process of analyzing the environmental effects of alternative actions.
NASA Astrophysics Data System (ADS)
Liu, X.; Shi, Y.; Wu, M.; Zhang, K.
2017-12-01
Mixed-phase clouds frequently observed in the Arctic and mid-latitude storm tracks have the substantial impacts on the surface energy budget, precipitation and climate. In this study, we first implement the two empirical parameterizations (Niemand et al. 2012 and DeMott et al. 2015) of heterogeneous ice nucleation for mixed-phase clouds in the NCAR Community Atmosphere Model Version 5 (CAM5) and DOE Accelerated Climate Model for Energy Version 1 (ACME1). Model simulated ice nucleating particle (INP) concentrations based on Niemand et al. and DeMott et al. are compared with those from the default ice nucleation parameterization based on the classical nucleation theory (CNT) in CAM5 and ACME, and with in situ observations. Significantly higher INP concentrations (by up to a factor of 5) are simulated from Niemand et al. than DeMott et al. and CNT especially over the dust source regions in both CAM5 and ACME. Interestingly the ACME model simulates higher INP concentrations than CAM5, especially in the Polar regions. This is also the case when we nudge the two models' winds and temperature towards the same reanalysis, indicating more efficient transport of aerosols (dust) to the Polar regions in ACME. Next, we examine the responses of model simulated cloud liquid water and ice water contents to different INP concentrations from three ice nucleation parameterizations (Niemand et al., DeMott et al., and CNT) in CAM5 and ACME. Changes in liquid water path (LWP) reach as much as 20% in the Arctic regions in ACME between the three parameterizations while the LWP changes are smaller and limited in the Northern Hemispheric mid-latitudes in CAM5. Finally, the impacts on cloud radiative forcing and dust indirect effects on mixed-phase clouds are quantified with the three ice nucleation parameterizations in CAM5 and ACME.
NASA Astrophysics Data System (ADS)
Abramoff, R. Z.; Torn, M. S.; Georgiou, K.; Tang, J.; Riley, W. J.
2017-12-01
Researchers use spatial gradients to estimate long-term ecosystem responses to perturbations. This approach is commonly applied to soil organic carbon (SOC) stocks which change slowly but store the majority of terrestrial carbon. Climate warming may reduce SOC stocks if higher temperatures increase decomposition rates. Yet, it is uncertain how vulnerable SOC is to warming, and whether the same factors - such as organo-mineral associations, climate, or plant inputs - determine SOC stocks across space and time. In order to test the "space for time" concept, we developed two versions of the Substrate-Mineral-Microbe Soil (SuMMS) model - one with microbial temperature acclimation and one without - to analyze observed SOC stocks at 24 sites spanning a wide range of soil types and climate. Both model predictions of SOC were strongly correlated with observations (R2 > 0.9), because mineral sorption capacity was the dominant control over steady-state SOC stock as determined by a Random Forest model. However, the two model versions made fundamentally different predictions of the change in SOC following 5°C soil warming from 2016 to 2100 because the initial mean annual temperature (MAT) was the dominant control over the SOC response. The model with microbial acclimation predicted that SOC would decline 10% at all sites along the transect, while the model with no acclimation predicted large surface SOC losses at high latitude sites and SOC gains at low latitude sites where microbial exoenzymes were already at or near their temperature optimum. These simulations suggest that gradient studies cannot be used to infer site-level responses to warming, because the dominant controls on SOC at steady state (i.e., mineral sorption capacity) are different than the dominant controls on the SOC response to a warming perturbation (i.e., initial MAT, capacity for acclimation).
The role of updraft velocity in temporal variability of cloud hydrometeor number
NASA Astrophysics Data System (ADS)
Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros
2016-04-01
Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a tool of understanding for hydrometer variability can be instrumental for understanding the source of differences between models used for aerosol-cloud-climate interaction studies.
NASA Astrophysics Data System (ADS)
Naudts, Kim; Ryder, James; McGrath, Matthew J.; Otto, Juliane; Chen, Yiying; Valade, Aude; Bellasen, Valentin; Ghattas, Josefine; Haverd, Vanessa; MacBean, Natasha; Maignan, Fabienne; Peylin, Philippe; Pinty, Bernard; Solyga, Didier; Vuichard, Nicolas; Luyssaert, Sebastiaan
2015-04-01
Since 70% of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land surface models used in Earth system models, and therefore none of today's predictions of future climate, account for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrizing a version of the land surface model ORCHIDEE to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new model called ORCHIDEE-CAN and the standard version of ORCHIDEE are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes towards a better process representation occurred for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrization was revisited after introducing twelve new parameter sets that represent specific tree species or genera rather than a group of unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, GPP, albedo and evapotranspiration over Europe. For all tested variables ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92% chance to reproduce the spatial and temporal variability of the validation data.
NASA Astrophysics Data System (ADS)
Walton, P.; Yarker, M. B.; Mesquita, M. D. S.; Otto, F. E. L.
2014-12-01
There is a clear role for climate science in supporting decision making at a range of scales and in a range of contexts: from Global to local, from Policy to Industry. However, clear a role climate science can play, there is also a clear discrepancy in the understanding of how to use the science and associated tools (such as climate models). Despite there being a large body of literature on the science there is clearly a need to provide greater support in how to apply appropriately. However, access to high quality professional development courses can be problematic, due to geographic, financial and time constraints. In attempt to address this gap we independently developed two online professional courses that focused on helping participants use and apply two regional climate models, WRF and PRECIS. Both courses were designed to support participants' learning through tutor led programs that covered the basic climate scientific principles of regional climate modeling and how to apply model outputs. The fundamental differences between the two courses are: 1) the WRF modeling course expected participants to design their own research question that was then run on a version of the model, whereas 2) the PRECIS course concentrated on the principles of regional modeling and how the climate science informed the modeling process. The two courses were developed to utilise the cost and time management benefits associated with eLearning, with the recognition that this mode of teaching can also be accessed internationally, providing professional development courses in countries that may not be able to provide their own. The development teams saw it as critical that the courses reflected sound educational theory, to ensure that participants had the maximum opportunity to learn successfully. In particular, the role of reflection is central to both course structures to help participants make sense of the science in relation to their own situation. This paper details the different structures of both courses, evaluating the advantages and disadvantages of each, along with the educational approaches used. We conclude by proposing a framework for the develop of educationally robust online professional development programs that actively supports decision makers in understanding, developing and applying regional climate models.
Using a Global Climate Model in an On-line Climate Change Course
NASA Astrophysics Data System (ADS)
Randle, D. E.; Chandler, M. A.; Sohl, L. E.
2012-12-01
Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that arise are due to a lack of computer literacy amongst participants and we have found, through iterative improvements in the materials, that breaking assignments into discrete, well-supported tasks has been key to the success.
Can decadal climate predictions be improved by ocean ensemble dispersion filtering?
NASA Astrophysics Data System (ADS)
Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.
2017-12-01
Decadal predictions by Earth system models aim to capture the state and phase of the climate several years inadvance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-termweather forecasts represent an initial value problem and long-term climate projections represent a boundarycondition problem, the decadal climate prediction falls in-between these two time scales. The ocean memorydue to its heat capacity holds big potential skill on the decadal scale. In recent years, more precise initializationtechniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions.Ensembles are another important aspect. Applying slightly perturbed predictions results in an ensemble. Insteadof using and evaluating one prediction, but the whole ensemble or its ensemble average, improves a predictionsystem. However, climate models in general start losing the initialized signal and its predictive skill from oneforecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improvedby a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. Wefound that this procedure, called ensemble dispersion filter, results in more accurate results than the standarddecadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions showan increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with largerensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from oceanensemble dispersion filtering toward the ensemble mean. This study is part of MiKlip (fona-miklip.de) - a major project on decadal climate prediction in Germany.We focus on the Max-Planck-Institute Earth System Model using the low-resolution version (MPI-ESM-LR) andMiKlip's basic initialization strategy as in 2017 published decadal climate forecast: http://www.fona-miklip.de/decadal-forecast-2017-2026/decadal-forecast-for-2017-2026/ More informations about this study in JAMES:DOI: 10.1002/2016MS000787
PALM-USM v1.0: A new urban surface model integrated into the PALM large-eddy simulation model
NASA Astrophysics Data System (ADS)
Resler, Jaroslav; Krč, Pavel; Belda, Michal; Juruš, Pavel; Benešová, Nina; Lopata, Jan; Vlček, Ondřej; Damašková, Daša; Eben, Kryštof; Derbek, Přemysl; Maronga, Björn; Kanani-Sühring, Farah
2017-10-01
Urban areas are an important part of the climate system and many aspects of urban climate have direct effects on human health and living conditions. This implies that reliable tools for local urban climate studies supporting sustainable urban planning are needed. However, a realistic implementation of urban canopy processes still poses a serious challenge for weather and climate modelling for the current generation of numerical models. To address this demand, a new urban surface model (USM), describing the surface energy processes for urban environments, was developed and integrated as a module into the PALM large-eddy simulation model. The development of the presented first version of the USM originated from modelling the urban heat island during summer heat wave episodes and thus implements primarily processes important in such conditions. The USM contains a multi-reflection radiation model for shortwave and longwave radiation with an integrated model of absorption of radiation by resolved plant canopy (i.e. trees, shrubs). Furthermore, it consists of an energy balance solver for horizontal and vertical impervious surfaces, and thermal diffusion in ground, wall, and roof materials, and it includes a simple model for the consideration of anthropogenic heat sources. The USM was parallelized using the standard Message Passing Interface and performance testing demonstrates that the computational costs of the USM are reasonable on typical clusters for the tested configurations. The module was fully integrated into PALM and is available via its online repository under the GNU General Public License (GPL). The USM was tested on a summer heat-wave episode for a selected Prague crossroads. The general representation of the urban boundary layer and patterns of surface temperatures of various surface types (walls, pavement) are in good agreement with in situ observations made in Prague. Additional simulations were performed in order to assess the sensitivity of the results to uncertainties in the material parameters, the domain size, and the general effect of the USM itself. The first version of the USM is limited to the processes most relevant to the study of summer heat waves and serves as a basis for ongoing development which will address additional processes of the urban environment and lead to improvements to extend the utilization of the USM to other environments and conditions.
NASA Astrophysics Data System (ADS)
Millar, R.; Ingram, W.; Allen, M. R.; Lowe, J.
2013-12-01
Temperature and precipitation patterns are the climate variables with the greatest impacts on both natural and human systems. Due to the small spatial scales and the many interactions involved in the global hydrological cycle, in general circulation models (GCMs) representations of precipitation changes are subject to considerable uncertainty. Quantifying and understanding the causes of uncertainty (and identifying robust features of predictions) in both global and local precipitation change is an essential challenge of climate science. We have used the huge distributed computing capacity of the climateprediction.net citizen science project to examine parametric uncertainty in an ensemble of 20,000 perturbed-physics versions of the HadCM3 general circulation model. The ensemble has been selected to have a control climate in top-of-atmosphere energy balance [Yamazaki et al. 2013, J.G.R.]. We force this ensemble with several idealised climate-forcing scenarios including carbon dioxide step and transient profiles, solar radiation management geoengineering experiments with stratospheric aerosols, and short-lived climate forcing agents. We will present the results from several of these forcing scenarios under GCM parametric uncertainty. We examine the global mean precipitation energy budget to understand the robustness of a simple non-linear global precipitation model [Good et al. 2012, Clim. Dyn.] as a better explanation of precipitation changes in transient climate projections under GCM parametric uncertainty than a simple linear tropospheric energy balance model. We will also present work investigating robust conclusions about precipitation changes in a balanced ensemble of idealised solar radiation management scenarios [Kravitz et al. 2011, Atmos. Sci. Let.].
Estimating the numerical diapycnal mixing in an eddy-permitting ocean model
NASA Astrophysics Data System (ADS)
Megann, Alex
2018-01-01
Constant-depth (or "z-coordinate") ocean models such as MOM4 and NEMO have become the de facto workhorse in climate applications, having attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes, and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimates have been made of the typical magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is a recent ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre. It forms the ocean component of the GC2 climate model, and is closely related to the ocean component of the UKESM1 Earth System Model, the UK's contribution to the CMIP6 model intercomparison. GO5.0 uses version 3.4 of the NEMO model, on the ORCA025 global tripolar grid. An approach to quantifying the numerical diapycnal mixing in this model, based on the isopycnal watermass analysis of Lee et al. (2002), is described, and the estimates thereby obtained of the effective diapycnal diffusivity in GO5.0 are compared with the values of the explicit diffusivity used by the model. It is shown that the effective mixing in this model configuration is up to an order of magnitude higher than the explicit mixing in much of the ocean interior, implying that mixing in the model below the mixed layer is largely dominated by numerical mixing. This is likely to have adverse consequences for the representation of heat uptake in climate models intended for decadal climate projections, and in particular is highly relevant to the interpretation of the CMIP6 class of climate models, many of which use constant-depth ocean models at ¼° resolution
Federal Register 2010, 2011, 2012, 2013, 2014
2010-04-08
... opportunity to submit comments to the draft fifth National Communication on U.S. climate change actions for the United Nations Framework Convention on Climate Change (UNFCCC). In June 1992, the United States... addressing climate change. See SUPPLEMENTARY INFORMATION for instructions on accessing the electronic version...
The Meriden School Climate Survey-Student Version: Preliminary Evidence of Reliability and Validity
ERIC Educational Resources Information Center
Gage, Nicholas A.; Larson, Alvin; Chafouleas, Sandra M.
2016-01-01
School climate has been linked with myriad positive student outcomes and the measurement of school climate is widely advocated at the national and state level. However, districts have little guidance about how to define and measure school climate. This study examines the psychometric properties of a district-developed school climate measure that…
Zhou, Cheng; Penner, Joyce E.
2017-01-02
Observation-based studies have shown that the aerosol cloud lifetime effect or the increase of cloud liquid water path (LWP) with increased aerosol loading may have been overestimated in climate models. Here, we simulate shallow warm clouds on 27 May 2011 at the southern Great Plains (SGP) measurement site established by the Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) program using a single-column version of a global climate model (Community Atmosphere Model or CAM) and a cloud resolving model (CRM). The LWP simulated by CAM increases substantially with aerosol loading while that in the CRM does not. The increase of LWP inmore » CAM is caused by a large decrease of the autoconversion rate when cloud droplet number increases. In the CRM, the autoconversion rate is also reduced, but this is offset or even outweighed by the increased evaporation of cloud droplets near the cloud top, resulting in an overall decrease in LWP. Lastly, our results suggest that climate models need to include the dependence of cloud top growth and the evaporation/condensation process on cloud droplet number concentrations.« less
McFarland, James; Zhou, Yuyu; Clarke, Leon; ...
2015-06-10
The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Fewer studies have explored the physical impacts of climate change on the power sector. Our present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effectsmore » of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. Moreover, the increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhou, Cheng; Penner, Joyce E.
Observation-based studies have shown that the aerosol cloud lifetime effect or the increase of cloud liquid water path (LWP) with increased aerosol loading may have been overestimated in climate models. Here, we simulate shallow warm clouds on 27 May 2011 at the southern Great Plains (SGP) measurement site established by the Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) program using a single-column version of a global climate model (Community Atmosphere Model or CAM) and a cloud resolving model (CRM). The LWP simulated by CAM increases substantially with aerosol loading while that in the CRM does not. The increase of LWP inmore » CAM is caused by a large decrease of the autoconversion rate when cloud droplet number increases. In the CRM, the autoconversion rate is also reduced, but this is offset or even outweighed by the increased evaporation of cloud droplets near the cloud top, resulting in an overall decrease in LWP. Lastly, our results suggest that climate models need to include the dependence of cloud top growth and the evaporation/condensation process on cloud droplet number concentrations.« less
Accelerating Climate and Weather Simulations through Hybrid Computing
NASA Technical Reports Server (NTRS)
Zhou, Shujia; Cruz, Carlos; Duffy, Daniel; Tucker, Robert; Purcell, Mark
2011-01-01
Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.
NASA Technical Reports Server (NTRS)
Colarco, Peter; daSilva, Arlindo; Chin, Mian; Diehl, Thomas
2010-01-01
We have implemented a module for tropospheric aerosols (GO CART) online in the NASA Goddard Earth Observing System version 4 model and simulated global aerosol distributions for the period 2000-2006. The new online system offers several advantages over the previous offline version, providing a platform for aerosol data assimilation, aerosol-chemistry-climate interaction studies, and short-range chemical weather forecasting and climate prediction. We introduce as well a methodology for sampling model output consistently with satellite aerosol optical thickness (AOT) retrievals to facilitate model-satellite comparison. Our results are similar to the offline GOCART model and to the models participating in the AeroCom intercomparison. The simulated AOT has similar seasonal and regional variability and magnitude to Aerosol Robotic Network (AERONET), Moderate Resolution Imaging Spectroradiometer, and Multiangle Imaging Spectroradiometer observations. The model AOT and Angstrom parameter are consistently low relative to AERONET in biomass-burning-dominated regions, where emissions appear to be underestimated, consistent with the results of the offline GOCART model. In contrast, the model AOT is biased high in sulfate-dominated regions of North America and Europe. Our model-satellite comparison methodology shows that diurnal variability in aerosol loading is unimportant compared to sampling the model where the satellite has cloud-free observations, particularly in sulfate-dominated regions. Simulated sea salt burden and optical thickness are high by a factor of 2-3 relative to other models, and agreement between model and satellite over-ocean AOT is improved by reducing the model sea salt burden by a factor of 2. The best agreement in both AOT magnitude and variability occurs immediately downwind of the Saharan dust plume.
Free boundary models for mosquito range movement driven by climate warming.
Bao, Wendi; Du, Yihong; Lin, Zhigui; Zhu, Huaiping
2018-03-01
As vectors, mosquitoes transmit numerous mosquito-borne diseases. Among the many factors affecting the distribution and density of mosquitoes, climate change and warming have been increasingly recognized as major ones. In this paper, we make use of three diffusive logistic models with free boundary in one space dimension to explore the impact of climate warming on the movement of mosquito range. First, a general model incorporating temperature change with location and time is introduced. In order to gain insights of the model, a simplified version of the model with the change of temperature depending only on location is analyzed theoretically, for which the dynamical behavior is completely determined and presented. The general model can be modified into a more realistic one of seasonal succession type, to take into account of the seasonal changes of mosquito movements during each year, where the general model applies only for the time period of the warm seasons of the year, and during the cold season, the mosquito range is fixed and the population is assumed to be in a hibernating status. For both the general model and the seasonal succession model, our numerical simulations indicate that the long-time dynamical behavior is qualitatively similar to the simplified model, and the effect of climate warming on the movement of mosquitoes can be easily captured. Moreover, our analysis reveals that hibernating enhances the chances of survival and successful spreading of the mosquitoes, but it slows down the spreading speed.
A Web-Based Modelling Platform for Interactive Exploration of Regional Responses to Global Change
NASA Astrophysics Data System (ADS)
Holman, I.
2014-12-01
Climate change adaptation is a complex human-environmental problem that is framed by the uncertainty in impacts and the adaptation choices available, but is also bounded by real-world constraints such as future resource availability and environmental and institutional capacities. Educating the next generation of informed decision-makers that will be able to make knowledgeable responses to global climate change impacts requires them to have access to information that is credible, accurate, easy to understand, and appropriate. However, available resources are too often produced by inaccessible models for scenario simulations chosen by researchers hindering exploration and enquiry. This paper describes the interactive exploratory web-based CLIMSAVE Integrated Assessment (IA) Platform (www.climsave.eu/iap) that aims to democratise climate change impacts, adaptation and vulnerability modelling. The regional version of the Platform contain linked simulation models (of the urban, agriculture, forestry, water and biodiversity sectors), probabilistic climate scenarios and socio-economic scenarios, that enable users to select their inputs (climate and socioeconomic), rapidly run the models using their input variable settings and view their chosen outputs. The interface of the CLIMSAVE IA Platform is designed to facilitate a two-way iterative process of dialogue and exploration of "what if's" to enable a wide range of users to improve their understanding surrounding impacts, adaptation responses and vulnerability of natural resources and ecosystem services under uncertain futures. This paper will describe the evolution of the Platform and demonstrate how using its holistic framework (multi sector / ecosystem service; cross-sectoral, climate and socio-economic change) will help to assist learning around the challenging concepts of responding to global change.
The NASA/MSFC Global Reference Atmospheric Model: 1999 Version (GRAM-99)
NASA Technical Reports Server (NTRS)
Justus, C. G.; Johnson, D. L.
1999-01-01
The latest version of Global Reference Atmospheric Model (GRAM-99) is presented and discussed. GRAM-99 uses either (binary) Global Upper Air Climatic Atlas (GUACA) or (ASCII) Global Gridded Upper Air Statistics (GGUAS) CD-ROM data sets, for 0-27 km altitudes. As with earlier versions, GRAM-99 provides complete geographical and altitude coverage for each month of the year. GRAM-99 uses a specially-developed data set, based on Middle Atmosphere Program (MAP) data, for 20-120 km altitudes, and NASA's 1999 version Marshall Engineering Thermosphere (MET-99) model for heights above 90 km. Fairing techniques assure smooth transition in overlap height ranges (20-27 km and 90-120 km). GRAM-99 includes water vapor and 11 other atmospheric constituents (O3, N2O, CO, CH4, CO2, N2, O2, O, A, He and H). A variable-scale perturbation model provides both large-scale (wave) and small-scale (stochastic) deviations from mean values for thermodynamic variables and horizontal and vertical wind components. The small-scale perturbation model includes improvements in representing intermittency ("patchiness"). A major new feature is an option to substitute Range Reference Atmosphere (RRA) data for conventional GRAM climatology when a trajectory passes sufficiently near any RRA site. A complete user's guide for running the program, plus sample input and output, is provided. An example is provided for how to incorporate GRAM-99 as subroutines in other programs (e.g., trajectory codes).
Untangling climatic and autogenic signals in peat records
NASA Astrophysics Data System (ADS)
Morris, Paul J.; Baird, Andrew J.; Young, Dylan M.; Swindles, Graeme T.
2016-04-01
Raised bogs contain potentially valuable information about Holocene climate change. However, autogenic processes may disconnect peatland hydrological behaviour from climate, and overwrite and degrade climatic signals in peat records. How can genuine climate signals be separated from autogenic changes? What level of detail of climatic information should we expect to be able to recover from peat-based reconstructions? We used an updated version of the DigiBog model to simulate peatland development and response to reconstructed Holocene rainfall and temperature reconstructions. The model represents key processes that are influential in peatland development and climate signal preservation, and includes a network of feedbacks between peat accumulation, decomposition, hydraulic structure and hydrological processes. It also incorporates the effects of temperature upon evapotranspiration, plant (litter) productivity and peat decomposition. Negative feedbacks in the model cause simulated water-table depths and peat humification records to exhibit homeostatic recovery from prescribed changes in rainfall, chiefly through changes in drainage. However, the simulated bogs show less resilience to changes in temperature, which cause lasting alterations to peatland structure and function and may therefore be more readily detectable in peat records. The network of feedbacks represented in DigiBog also provide both high- and low-pass filters for climatic information, meaning that the fidelity with which climate signals are preserved in simulated peatlands is determined by both the magnitude and the rate of climate change. Large-magnitude climatic events of an intermediate frequency (i.e., multi-decadal to centennial) are best preserved in the simulated bogs. We found that simulated humification records are further degraded by a phenomenon known as secondary decomposition. Decomposition signals are consistently offset from the climatic events that generate them, and decomposition records of dry-wet-dry climate sequences appear to be particularly vulnerable to overwriting. Our findings have direct implications not only for the interpretation of peat-based records of past climates, but also for understanding the likely vulnerability of peatland ecosystems and carbon stocks to future climate change.
Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States
NASA Astrophysics Data System (ADS)
Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; Kotamarthi, V. Rao
2018-02-01
This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 × 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmental Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation's performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.
NASA Astrophysics Data System (ADS)
Abdel-Lathif, Ahmat Younous; Roehrig, Romain; Beau, Isabelle; Douville, Hervé
2018-03-01
A single-column model (SCM) approach is used to assess the CNRM climate model (CNRM-CM) version 6 ability to represent the properties of the apparent heat source (Q1) and moisture sink (Q2) as observed during the 3 month CINDY2011/DYNAMO field campaign, over its Northern Sounding Array (NSA). The performance of the CNRM SCM is evaluated in a constrained configuration in which the latent and sensible heat surface fluxes are prescribed, as, when forced by observed sea surface temperature, the model is strongly limited by the underestimate of the surface fluxes, most probably related to the SCM forcing itself. The model exhibits a significant cold bias in the upper troposphere, near 200 hPa, and strong wet biases close to the surface and above 700 hPa. The analysis of the Q1 and Q2 profile distributions emphasizes the properties of the convective parameterization of the CNRM-CM physics. The distribution of the Q2 profile is particularly challenging. The model strongly underestimates the frequency of occurrence of the deep moistening profiles, which likely involve misrepresentation of the shallow and congestus convection. Finally, a statistical approach is used to objectively define atmospheric regimes and construct a typical convection life cycle. A composite analysis shows that the CNRM SCM captures the general transition from bottom-heavy to mid-heavy to top-heavy convective heating. Some model errors are shown to be related to the stratiform regimes. The moistening observed during the shallow and congestus convection regimes also requires further improvements of this CNRM-CM physics.
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis; Iredell, Lena
2016-01-01
The AIRS Science Team Version 6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRSAMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.
Results from CrIS/ATMS Obtained Using an "AIRS Version-6 Like" Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis; Iredell, Lena
2015-01-01
A main objective of AIRS/AMSU on EOS is to provide accurate sounding products that are used to generate climate data sets. Suomi NPP carries CrIS/ATMS that were designed as follow-ons to AIRS/AMSU. Our objective is to generate a long term climate data set of products derived from CrIS/ATMS to serve as a continuation of the AIRS/AMSU products. We have modified an improved version of the operational AIRS Version-6 retrieval algorithm for use with CrIS/ATMS. CrIS/ATMS products are of very good quality, and are comparable to, and consistent with, those of AIRS.
NASA Astrophysics Data System (ADS)
Reboita, Michelle Simões; Amaro, Tatiana Rocha; de Souza, Marcelo Rodrigues
2017-09-01
Since wind is an important source of renewable energy, it has attracted attention worldwide. Several studies have been developed in order to know favorable areas where wind farms can be implemented. Therefore, the purpose of this study is to project changes in wind intensity and in wind power density (PD), at 100 m high, over South America and adjacent oceans, by downscaling and ensemble techniques. Regional climate model version 4 (RegCM4) was nested in the output of three global climate models, considering the RCP8.5 scenario. RegCM4 ensemble in the present climate (1979-2005) was validated through comparisons with ERA-Interim reanalysis. The ensemble represents well the spatial pattern of the winds, but there are some differences in relation to the wind intensity registered by ERA-Interim, mainly in center-east Brazil and Patagonia. The comparison between the future climate (2020-2050 and 2070-2098) and the present one shows that there is an increase in wind intensity and PD on the north of SA, center-east Brazil (except in summer) and latitudes higher than 50°S. Such increase is more intense in the period 2070-2098.
ERIC Educational Resources Information Center
Ng, Carmen K. M.; Yuen, Mantak
2011-01-01
This article describes the use of the Chinese translation of the revised Inviting School Survey (ISS-R; Smith, 2005; Smith & Bernard, 2004) to measure the invitational climate of seven invitational secondary schools in Hong Kong. The five subscales of Chinese version of ISS-R were found to be valid and reliable in a sample of 706 Grade 11…
Improved Decadal Climate Prediction in the North Atlantic using EnOI-Assimilated Initial Condition
NASA Astrophysics Data System (ADS)
Li, Q.; Xin, X.; Wei, M.; Zhou, W.
2017-12-01
Decadal prediction experiments of Beijing Climate Center climate system model version 1.1(BCC-CSM1.1) participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation (SODA) reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature (SST) of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation (EnOI). Then a suite of decadal re-forecasts launched annually over the period 1961-2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal Oscillation (AMO), which is consistent with the better skill of Atlantic meridional overturning circulation (AMOC) predicted by the re-forecasts. We conclude that the EnOI assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.
Double-moment cloud microphysics scheme for the deep convection parameterization in the GFDL AM3
NASA Astrophysics Data System (ADS)
Belochitski, A.; Donner, L.
2014-12-01
A double-moment cloud microphysical scheme originally developed by Morrision and Gettelman (2008) for the stratiform clouds and later adopted for the deep convection by Song and Zhang (2011) has been implemented in to the Geophysical Fluid Dynamics Laboratory's atmospheric general circulation model AM3. The scheme treats cloud drop, cloud ice, rain, and snow number concentrations and mixing ratios as diagnostic variables and incorporates processes of autoconversion, self-collection, collection between hydrometeor species, sedimentation, ice nucleation, drop activation, homogeneous and heterogeneous freezing, and the Bergeron-Findeisen process. Such detailed representation of microphysical processes makes the scheme suitable for studying the interactions between aerosols and convection, as well as aerosols' indirect effects on clouds and their roles in climate change. The scheme is first tested in the single column version of the GFDL AM3 using forcing data obtained at the U.S. Department of Energy Atmospheric Radiation Measurment project's Southern Great Planes site. Scheme's impact on SCM simulations is discussed. As the next step, runs of the full atmospheric GCM incorporating the new parameterization are compared to the unmodified version of GFDL AM3. Global climatological fields and their variability are contrasted with those of the original version of the GCM. Impact on cloud radiative forcing and climate sensitivity is investigated.
NASA Technical Reports Server (NTRS)
Susskind, Joel; Molnar, Gyula; Iredell, Lena; Rosenberg, Robert
2012-01-01
AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. These observations, covering the period September 2002 until the present, have been analyzed using the AIRS Science Team Version-5 retrieval algorithm. AIRS is a high spectral resolution infrared grating spectrometer with spect,ral coverage from 650 per centimeter extending to 2660 per centimeter, with low noise and a spectral resolving power of 2400. A brief overview of the AIRS Version-5 retrieval procedure will be presented, including the AIRS channels used in different steps in the retrieval process. Many researchers have used these products to make significant advances in both climate and weather applications. Recent significant results of these experiments will be presented, including results showing that 1) assimilation of AIRS Quality Controlled temperature profiles into a General Circulation Model (GCM) significantly improves the ability to predict storm tracks of intense precipitation events; and 2) anomaly time-series of Outgoing Longwave Radiation (OLR) computed using AIRS sounding products closely match those determined from the CERES instrument, and furthermore explain that the phenomenon that global and especially tropical mean OLR have been decreasing since September 2002 is a result of El Nino/La Nina oscillations during this period.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hoffman, Forrest M; Randerson, Jim; Thornton, Peter E
2009-01-01
The need to capture important climate feebacks in general circulation models (GCMs) has resulted in new efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, now often referred to as Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results, suggesting that a more rigorous set of offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are warranted. The Carbon-Land Model Intercomparison Project (C-LAMP) providesmore » a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). C-LAMP provides feedback to the modeling community regarding model improvements and to the measurement community by suggesting new observational campaigns. C-LAMP Experiment 1 consists of a set of uncoupled simulations of terrestrial carbon models specifically designed to examine the ability of the models to reproduce surface carbon and energy fluxes at multiple sites and to exhibit the influence of climate variability, prescribed atmospheric carbon dioxide (CO{sub 2}), nitrogen (N) deposition, and land cover change on projections of terrestrial carbon fluxes during the 20th century. Experiment 2 consists of partially coupled simulations of the terrestrial carbon model with an active atmosphere model exchanging energy and moisture fluxes. In all experiments, atmospheric CO{sub 2} follows the prescribed historical trajectory from C{sup 4}MIP. In Experiment 2, the atmosphere model is forced with prescribed sea surface temperatures (SSTs) and corresponding sea ice concentrations from the Hadley Centre; prescribed CO{sub 2} is radiatively active; and land, fossil fuel, and ocean CO{sub 2} fluxes are advected by the model. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the Community Land Model version 3 (CLM3) in the Community Climate System Model version 3 (CCSM3): The CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons against Ameriflus site measurements, MODIS satellite observations, NOAA flask records, TRANSCOM inversions, and Free Air CO{sub 2} Enrichment (FACE) site measurements, and other datasets have been performed and are described in Randerson et al. (2009). The C-LAMP diagnostics package was used to validate improvements to CASA and CN for use in the next generation model, CLM4. It is hoped that this effort will serve as a prototype for an international carbon-cycle model benchmarking activity for models being used for the Inter-governmental Panel on Climate Change (IPCC) Fifth Assessment Report. More information about C-LAMP, the experimental protocol, performance metrics, output standards, and model-data comparisons from the CLM3-CASA and CLM3-CN models are available at http://www.climatemodeling.org/c-lamp.« less
An increase in aerosol burden due to the land-sea warming contrast
NASA Astrophysics Data System (ADS)
Hassan, T.; Allen, R.; Randles, C. A.
2017-12-01
Climate models simulate an increase in most aerosol species in response to warming, particularly over the tropics and Northern Hemisphere midlatitudes. This increase in aerosol burden is related to a decrease in wet removal, primarily due to reduced large-scale precipitation. Here, we show that the increase in aerosol burden, and the decrease in large-scale precipitation, is related to a robust climate change phenomenon—the land/sea warming contrast. Idealized simulations with two state of the art climate models, the National Center for Atmospheric Research Community Atmosphere Model version 5 (NCAR CAM5) and the Geophysical Fluid Dynamics Laboratory Atmospheric Model 3 (GFDL AM3), show that muting the land-sea warming contrast negates the increase in aerosol burden under warming. This is related to smaller decreases in near-surface relative humidity over land, and in turn, smaller decreases in large-scale precipitation over land—especially in the NH midlatitudes. Furthermore, additional idealized simulations with an enhanced land/sea warming contrast lead to the opposite result—larger decreases in relative humidity over land, larger decreases in large-scale precipitation, and larger increases in aerosol burden. Our results, which relate the increase in aerosol burden to the robust climate projection of enhanced land warming, adds confidence that a warmer world will be associated with a larger aerosol burden.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Li; Pierce, David W.; Russell, Lynn M.
This study examines multi-year climate variability associated with sea salt aerosols and their contribution to the variability of shortwave cloud forcing (SWCF) using a 150-year simulation for pre-industrial conditions of the Community Earth System Model version 1.0 (CESM1). The results suggest that changes in sea salt and related cloud and radiative properties on interannual timescales are dominated by the ENSO cycle. Sea salt variability on longer (interdecadal) timescales is associated with low-frequency Pacific ocean variability similar to the interdecadal Pacific Oscillation (IPO), but does not show a statistically significant spectral peak. A multivariate regression suggests that sea salt aerosol variabilitymore » may contribute to SWCF variability in the tropical Pacific, explaining up to 25-35% of the variance in that region. Elsewhere, there is only a small aerosol influence on SWCF through modifying cloud droplet number and liquid water path that contributes to the change of cloud effective radius and cloud optical depth (and hence cloud albedo), producing a multi-year aerosol-cloud-wind interaction.« less
The Global Climate Dashboard: a Software Interface to Stream Comprehensive Climate Data
NASA Astrophysics Data System (ADS)
Gardiner, N.; Phillips, M.; NOAA Climate Portal Dashboard
2011-12-01
The Global Climate Dashboard is an integral component of NOAA's web portal to climate data, services, and value-added content for decision-makers, teachers, and the science-attentive public (www.clmate.gov). The dashboard provides a rapid view of observational data that demonstrate climate change and variability, as well as outputs from the Climate Model Intercomparison Project version 3, which was built to support the Intergovernmental Panel on Climate Change fourth assessment. The data shown in the dashboard therefore span a range of climate science disciplines with applications that serve audiences with diverse needs. The dashboard is designed with reusable software components that allow it to be implemented incrementally on a wide range of platforms including desktops, tablet devices, and mobile phones. The underlying software components support live streaming of data and provide a way of encapsulating graph sytles and other presentation details into a device-independent standard format that results in a common visual look and feel across all platforms. Here we describe the pedagogical objectives, technical implementation, and the deployment of the dashboard through climate.gov and partner web sites and describe plans to develop a mobile application using the same framework.
Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations
Glantz, Paul; Bourassa, Adam; Herber, Andreas; Iversen, Trond; Karlsson, Johannes; Kirkevåg, Alf; Maturilli, Marion; Seland, Øyvind; Stebel, Kerstin; Struthers, Hamish; Tesche, Matthias; Thomason, Larry
2014-01-01
In this study Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua retrievals of aerosol optical thickness (AOT) at 555 nm are compared to Sun photometer measurements from Svalbard for a period of 9 years. For the 642 daily coincident measurements that were obtained, MODIS AOT generally varies within the predicted uncertainty of the retrieval over ocean (ΔAOT = ±0.03 ± 0.05 · AOT). The results from the remote sensing have been used to examine the accuracy in estimates of aerosol optical properties in the Arctic, generated by global climate models and from in situ measurements at the Zeppelin station, Svalbard. AOT simulated with the Norwegian Earth System Model/Community Atmosphere Model version 4 Oslo global climate model does not reproduce the observed seasonal variability of the Arctic aerosol. The model overestimates clear-sky AOT by nearly a factor of 2 for the background summer season, while tending to underestimate the values in the spring season. Furthermore, large differences in all-sky AOT of up to 1 order of magnitude are found for the Coupled Model Intercomparison Project phase 5 model ensemble for the spring and summer seasons. Large differences between satellite/ground-based remote sensing of AOT and AOT estimated from dry and humidified scattering coefficients are found for the subarctic marine boundary layer in summer. Key Points Remote sensing of AOT is very useful in validation of climate models PMID:25821664
The tropical climate and vegetation response to Heinrich Event 1
NASA Astrophysics Data System (ADS)
Handiani, D. N.; Paul, A.; Prange, M.; Merkel, U.; Dupont, L. M.; Zhang, X.
2013-12-01
Past abrupt climate change associated with Heinrich Event 1 (HE1, ca. 17.5 ka BP) is thought to be connected to a slowdown of the Atlantic Meridional Overturning Circulation (AMOC). The accompanying abrupt climate changes affect not only the ocean, but also the continents. Furthermore, a strong impact on vegetation patterns during this event is registered both at high latitudes of the Northern Hemisphere and in the tropics. Pollen data from the tropical regions around the Atlantic Ocean (in our study from Angola and Brazil) suggest an effect on tropical vegetation through a southward shift of the rainbelt. However, the response appears to be very different in eastern South America and western Africa. To understand the different climate and vegetation pattern responses in the terrestrial tropics and to gain deeper insight into high-low-latitude climate interactions, we studied the climate and vegetation changes during the HE1 by using two different global climate models: the University of Victoria Earth System-Climate Model (UVic ESCM) and the Community Climate System Model version 3 (CCSM3). In both models, we simulated a similar HE1-like climate state. To facilitate the comparison between the model results and the available pollen records, we generated a distribution of biomes from the simulated plant functional type (PFT) coverage and climate parameters in the models. The UVic ESCM and the CCSM3 showed a slowdown of the AMOC accompanied by a seesaw temperature pattern between the Northern and Southern Hemispheres, as well as a southward shift of the tropical rainbelt. The response of the tropical vegetation pattern around the Atlantic Ocean was more pronounced in the CCSM3 than in the UVic ESCM simulation. In tropical South America, opposite changes in tree and grass cover were found only in CCSM3. In tropical Africa, the tree cover decreased and grass cover increased around 15°N in the UVic ESCM and around 10°N in CCSM3. Changes in tree and grass cover in tropical Southeast Asia were found only in the CCSM3 model, suggesting that the abrupt climate change during the HE1 also influenced remote tropical regions. Moreover, the biome distributions derived from both models corroborate findings from pollen records in southwestern and equatorial western Africa as well as northeastern Brazil.
The SATIRE-S model and why getting solar cycle spectral irradiance trends correct is so important
NASA Astrophysics Data System (ADS)
Ball, William; Haigh, Joanna; Krivova, Natalie; Unruh, Yvonne; Solanki, Sami
2014-05-01
There is currently a wide range of potential spectral solar irradiance (SSI) solar cycle (SC) amplitudes suggested by observations and models. Therefore, SSI SC changes are still not fully understood. The magnitude of the SC flux changes has a direct impact upon the temperature and chemistry of the Earth's atmosphere. To contribute to an understanding of the solar-climate connection, it is critical that we, as the solar community, communicate effectively with the climate community, providing uncertainties in SSI data and assessments of possible SSI options. We present the SATIRE-S reconstruction in the context of these SSI datasets. SATIRE-S is a physically based, consistent SSI reconstruction over the last three solar cycles. It shows different SC spectral variability at all wavelengths compared to the NRLSSI model, widely used in climate research. Most-importantly, SC changes in the ultra-violet (UV) can be twice as large in SATIRE-S as NRLSSI. Typically NRLSSI provides a lower limit of SC SSI UV variability. SORCE satellite observations provide SC magnitudes at the upper limit of variability, exceeding that of SATIRE-S by a factor of three at some UV wavelengths. There is currently no way to be certain if any of these three SSI datasets, or others, is correct. We also present the SSI datasets in terms of their impact on stratospheric ozone, within a 2D atmospheric model, as an example of why it is important to get SC changes correct. Using NRLSSI results in the 2D atmospheric model, we see a decrease in ozone concentration at all altitudes from solar maximum to minimum. SATIRE-S and SORCE/SOLSTICE observations instead show an increase in ozone concentration in the mesosphere. The magnitude of the increase in the mesosphere when using SOLSTICE also depends greatly upon the version of the data, which means that studies using different data versions of SOLSTICE may lead to different conclusions. These results highlight why an accurate understanding of SC SSI changes, and their uncertainties, are essential for the climate community that uses our work.
NASA Astrophysics Data System (ADS)
Lauer, Axel; Jones, Colin; Eyring, Veronika; Evaldsson, Martin; Hagemann, Stefan; Mäkelä, Jarmo; Martin, Gill; Roehrig, Romain; Wang, Shiyu
2018-01-01
The performance of updated versions of the four earth system models (ESMs) CNRM, EC-Earth, HadGEM, and MPI-ESM is assessed in comparison to their predecessor versions used in Phase 5 of the Coupled Model Intercomparison Project. The Earth System Model Evaluation Tool (ESMValTool) is applied to evaluate selected climate phenomena in the models against observations. This is the first systematic application of the ESMValTool to assess and document the progress made during an extensive model development and improvement project. This study focuses on the South Asian monsoon (SAM) and the West African monsoon (WAM), the coupled equatorial climate, and Southern Ocean clouds and radiation, which are known to exhibit systematic biases in present-day ESMs. The analysis shows that the tropical precipitation in three out of four models is clearly improved. Two of three updated coupled models show an improved representation of tropical sea surface temperatures with one coupled model not exhibiting a double Intertropical Convergence Zone (ITCZ). Simulated cloud amounts and cloud-radiation interactions are improved over the Southern Ocean. Improvements are also seen in the simulation of the SAM and WAM, although systematic biases remain in regional details and the timing of monsoon rainfall. Analysis of simulations with EC-Earth at different horizontal resolutions from T159 up to T1279 shows that the synoptic-scale variability in precipitation over the SAM and WAM regions improves with higher model resolution. The results suggest that the reasonably good agreement of modeled and observed mean WAM and SAM rainfall in lower-resolution models may be a result of unrealistic intensity distributions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tilmes, Simone; Lamarque, Jean -Francois; Emmons, Louisa K.
The Community Earth System Model (CESM1) CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low-top model that reaches up to approximately 40 km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. We summarize the performance ofmore » the three reference simulations suggested by CCMI, with a focus on the last 15 years of the simulation when most observations are available. Comparisons with selected data sets are employed to demonstrate the general performance of the model. We highlight new data sets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20 % of values from available observations for most regions. In particular, the trend and magnitude of surface ozone is much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. In conclusion, all experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.« less
Tilmes, Simone; Lamarque, Jean -Francois; Emmons, Louisa K.; ...
2016-05-20
The Community Earth System Model (CESM1) CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low-top model that reaches up to approximately 40 km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. We summarize the performance ofmore » the three reference simulations suggested by CCMI, with a focus on the last 15 years of the simulation when most observations are available. Comparisons with selected data sets are employed to demonstrate the general performance of the model. We highlight new data sets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20 % of values from available observations for most regions. In particular, the trend and magnitude of surface ozone is much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. In conclusion, all experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.« less
Gutiérrez, Melchor; Ruiz, Luis-Miguel; López, Esther
2010-11-01
This study examined the relationship among pupils' perceptions of the motivational climate, pupils' perceptions of teachers' strategies to maintain discipline and pupils' intrinsic motivation in physical education. A sample of 2189 Spanish adolescents, ages 13 to 17 years, completed Spanish versions of the EPCM, SSDS, and IMI. Confirmatory factor analyses were carried out to confirm the factorial validity of the scales. Then, the relationship among the variables was explored through Structural Equation Modelling. The most important predictors of pupils' intrinsic motivation were the perceived mastery climate, and perceived teachers' emphasis on intrinsic reasons to maintain discipline. Perceived performance climate and perceived teachers' strategies to maintain discipline based on introjected reasons and indifference, predicted pupils' tension-pressure. Results are discussed in the context of theoretical propositions of self-determination theory and practical issues of enhancing adolescents' motivation in physical education.
The Community Climate System Model Version 4
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gent, Peter R.; Danabasoglu, Gokhan; Donner, Leo J.
The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all the CCSM components, and documents fully coupled pre-industrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1{sup o} results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4{sup o} resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in the CCSM4 producing El Nino/Southern Oscillation variability with a much more realistic frequency distribution than themore » CCSM3, although the amplitude is too large compared to observations. They also improve the representation of the Madden-Julian Oscillation, and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the deep ocean density structure, especially in the North Atlantic. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than the CCSM3, and the Arctic sea ice concentration is improved in the CCSM4. An ensemble of 20th century simulations runs produce an excellent match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally-averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4 C. This is consistent with the fact that the CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of short-wave and long-wave cloud forcings.« less
NASA Astrophysics Data System (ADS)
Sprintall, J.; Cowley, R.; Palmer, M. D.; Domingues, C. M.; Suzuki, T.; Ishii, M.; Boyer, T.; Goni, G. J.; Gouretski, V. V.; Macdonald, A. M.; Thresher, A.; Good, S. A.; Diggs, S. C.
2016-02-01
Historical ocean temperature profile observations provide a critical element for a host of ocean and climate research activities. These include providing initial conditions for seasonal-to-decadal prediction systems, evaluating past variations in sea level and Earth's energy imbalance, ocean state estimation for studying variability and change, and climate model evaluation and development. The International Quality controlled Ocean Database (IQuOD) initiative represents a community effort to create the most globally complete temperature profile dataset, with (intelligent) metadata and assigned uncertainties. With an internationally coordinated effort organized by oceanographers, with data and ocean instrumentation expertise, and in close consultation with end users (e.g., climate modelers), the IQuOD initiative will assess and maximize the potential of an irreplaceable collection of ocean temperature observations (tens of millions of profiles collected at a cost of tens of billions of dollars, since 1772) to fulfil the demand for a climate-quality global database that can be used with greater confidence in a vast range of climate change related research and services of societal benefit. Progress towards version 1 of the IQuOD database, ongoing and future work will be presented. More information on IQuOD is available at www.iquod.org.
Quantifying uncertainties of permafrost carbon-climate feedbacks
NASA Astrophysics Data System (ADS)
Burke, Eleanor J.; Ekici, Altug; Huang, Ye; Chadburn, Sarah E.; Huntingford, Chris; Ciais, Philippe; Friedlingstein, Pierre; Peng, Shushi; Krinner, Gerhard
2017-06-01
The land surface models JULES (Joint UK Land Environment Simulator, two versions) and ORCHIDEE-MICT (Organizing Carbon and Hydrology in Dynamic Ecosystems), each with a revised representation of permafrost carbon, were coupled to the Integrated Model Of Global Effects of climatic aNomalies (IMOGEN) intermediate-complexity climate and ocean carbon uptake model. IMOGEN calculates atmospheric carbon dioxide (CO2) and local monthly surface climate for a given emission scenario with the land-atmosphere CO2 flux exchange from either JULES or ORCHIDEE-MICT. These simulations include feedbacks associated with permafrost carbon changes in a warming world. Both IMOGEN-JULES and IMOGEN-ORCHIDEE-MICT were forced by historical and three alternative future-CO2-emission scenarios. Those simulations were performed for different climate sensitivities and regional climate change patterns based on 22 different Earth system models (ESMs) used for CMIP3 (phase 3 of the Coupled Model Intercomparison Project), allowing us to explore climate uncertainties in the context of permafrost carbon-climate feedbacks. Three future emission scenarios consistent with three representative concentration pathways were used: RCP2.6, RCP4.5 and RCP8.5. Paired simulations with and without frozen carbon processes were required to quantify the impact of the permafrost carbon feedback on climate change. The additional warming from the permafrost carbon feedback is between 0.2 and 12 % of the change in the global mean temperature (ΔT) by the year 2100 and 0.5 and 17 % of ΔT by 2300, with these ranges reflecting differences in land surface models, climate models and emissions pathway. As a percentage of ΔT, the permafrost carbon feedback has a greater impact on the low-emissions scenario (RCP2.6) than on the higher-emissions scenarios, suggesting that permafrost carbon should be taken into account when evaluating scenarios of heavy mitigation and stabilization. Structural differences between the land surface models (particularly the representation of the soil carbon decomposition) are found to be a larger source of uncertainties than differences in the climate response. Inertia in the permafrost carbon system means that the permafrost carbon response depends on the temporal trajectory of warming as well as the absolute amount of warming. We propose a new policy-relevant metric - the frozen carbon residence time (FCRt) in years - that can be derived from these complex land surface models and used to quantify the permafrost carbon response given any pathway of global temperature change.
Wave Climate and Wave Mixing in the Marginal Ice Zones of Arctic Seas, Observations and Modelling
2015-09-30
ababanin.com/ LONG-TERM GOALS The long-term goals of the present project are two: wind/wave climatology for the Arctic Seas, and their current...OBJECTIVES The wind/wave climatology for the Arctic Seas will be developed based on altimeter observations. It will have a major scientific and...applied significance as presently there is no reference climatology for this region of the ocean available. The new versions of wave models for the
Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies
NASA Astrophysics Data System (ADS)
Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj
2017-04-01
In climate simulations, the impacts of the subgrid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the subgrid variability in a computationally inexpensive manner. This study shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a nonzero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference Williams PD, Howe NJ, Gregory JM, Smith RS, and Joshi MM (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, 29, 8763-8781. http://dx.doi.org/10.1175/JCLI-D-15-0746.1
NASA Astrophysics Data System (ADS)
Kageyama, Masa; Braconnot, Pascale; Bopp, Laurent; Mariotti, Véronique; Roy, Tilla; Woillez, Marie-Noëlle; Caubel, Arnaud; Foujols, Marie-Alice; Guilyardi, Eric; Khodri, Myriam; Lloyd, James; Lombard, Fabien; Marti, Olivier
2013-05-01
The climates of the mid-Holocene (MH, 6,000 years ago) and the Last Glacial Maximum (LGM, 21,000 years ago) have been extensively documented and as such, have become targets for the evaluation of climate models for climate contexts very different from the present. In Part 1 of the present work, we have studied the MH and LGM simulations performed with the last two versions of the IPSL model: IPSL_CM4, run for the PMIP2/CMIP3 (Coupled Model Intercomparion Project) projects and IPSL_CM5A, run for the most recent PMIP3/CMIP5 projets. We have shown that not only are these models different in their simulations of the PI climate, but also in their simulations of the climatic anomalies for the MH and LGM. In the Part 2 of this paper, we first examine whether palaeo-data can help discriminate between the model performances. This is indeed the case for the African monsoon for the MH or for North America south of the Laurentide ice sheet, the South Atlantic or the southern Indian ocean for the LGM. For the LGM, off-line vegetation modelling appears to offer good opportunities to distinguish climate model results because glacial vegetation proves to be very sensitive to even small differences in LGM climate. For other cases such as the LGM North Atlantic or the LGM equatorial Pacific, the large uncertainty on the SST reconstructions, prevents model discrimination. We have examined the use of other proxy-data for model evaluation, which has become possible with the inclusion of the biogeochemistry morel PISCES in the IPSL_CM5A model. We show a broad agreement of the LGM-PI export production changes with reconstructions. These changes are related to the mixed layer depth in most regions and to sea-ice variations in the high latitudes. We have also modelled foraminifer abundances with the FORAMCLIM model and shown that the changes in foraminifer abundance in the equatorial Pacific are mainly forced by changes in SSTs, hence confirming the SST-foraminifer abundance relationship. Yet, this is not the case in all regions in the North Atlantic, where food availability can have a strong impact of foraminifer abundances. Further work will be needed to exhaustively examine the role of factors other than climate in piloting changes in palaeo-indicators.
NASA Astrophysics Data System (ADS)
Rothenberg, Daniel; Avramov, Alexander; Wang, Chien
2018-06-01
Interactions between aerosol particles and clouds contribute a great deal of uncertainty to the scientific community's understanding of anthropogenic climate forcing. Aerosol particles serve as the nucleation sites for cloud droplets, establishing a direct linkage between anthropogenic particulate emissions and clouds in the climate system. To resolve this linkage, the community has developed parameterizations of aerosol activation which can be used in global climate models to interactively predict cloud droplet number concentrations (CDNCs). However, different activation schemes can exhibit different sensitivities to aerosol perturbations in different meteorological or pollution regimes. To assess the impact these different sensitivities have on climate forcing, we have coupled three different core activation schemes and variants with the CESM-MARC (two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC) coupled with the National Center for Atmospheric Research's (NCAR) Community Earth System Model (CESM; version 1.2)). Although the model produces a reasonable present-day CDNC climatology when compared with observations regardless of the scheme used, ΔCDNCs between the present and preindustrial era regionally increase by over 100 % in zonal mean when using the most sensitive parameterization. These differences in activation sensitivity may lead to a different evolution of the model meteorology, and ultimately to a spread of over 0.8 W m-2 in global average shortwave indirect effect (AIE) diagnosed from the model, a range which is as large as the inter-model spread from the AeroCom intercomparison. Model-derived AIE strongly scales with the simulated preindustrial CDNC burden, and those models with the greatest preindustrial CDNC tend to have the smallest AIE, regardless of their ΔCDNC. This suggests that present-day evaluations of aerosol-climate models may not provide useful constraints on the magnitude of the AIE, which will arise from differences in model estimates of the preindustrial aerosol and cloud climatology.
NASA Technical Reports Server (NTRS)
Molnar, Gyula; Susskind, Joel
2008-01-01
The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.
Land-atmosphere coupling and climate prediction over the U.S. Southern Great Plains
NASA Astrophysics Data System (ADS)
Williams, Ian N.; Lu, Yaqiong; Kueppers, Lara M.; Riley, William J.; Biraud, Sebastien C.; Bagley, Justin E.; Torn, Margaret S.
2016-10-01
Biases in land-atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land-atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single-column version of the National Center for Atmospheric Research Community Earth System Model (CESM1.2.2) and an off-line Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. To estimate the impacts of these errors on climate prediction, we modified CLM4.5 by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications improved the predicted soil moisture-evaporative fraction (EF) and LAI-EF correlations in off-line CLM4.5 and reduced the root-mean-square error in summer 2 m air temperature and precipitation in the coupled model. The modifications had the largest effect on prediction during a drought in summer 2006, when a warm bias in daytime 2 m air temperature was reduced from +6°C to a smaller cold bias of -1.3°C, and a corresponding dry bias in precipitation was reduced from -111 mm to -23 mm. The role of vegetation in droughts and heat waves is underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.
NASA Astrophysics Data System (ADS)
Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.
2016-12-01
Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.
NASA Astrophysics Data System (ADS)
Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Cox, P. M.
2011-03-01
The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Past studies with JULES have demonstrated the important role of the land surface in the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of separately changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. There was a need to consolidate these and other advances into a single model code so as to be able to study interactions in a consistent manner. This paper describes the consolidation of these advances into the modelling of carbon fluxes and stores, in the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.
NASA Astrophysics Data System (ADS)
Nijssen, B.; Hamman, J.; Bohn, T. J.
2015-12-01
The Variable Infiltration Capacity (VIC) model is a macro-scale semi-distributed hydrologic model. VIC development began in the early 1990s and it has been used extensively, applied from basin to global scales. VIC has been applied in a many use cases, including the construction of hydrologic data sets, trend analysis, data evaluation and assimilation, forecasting, coupled climate modeling, and climate change impact analysis. Ongoing applications of the VIC model include the University of Washington's drought monitor and forecast systems, and NASA's land data assimilation systems. The development of VIC version 5.0 focused on reconfiguring the legacy VIC source code to support a wider range of modern modeling applications. The VIC source code has been moved to a public Github repository to encourage participation by the model development community-at-large. The reconfiguration has separated the physical core of the model from the driver, which is responsible for memory allocation, pre- and post-processing and I/O. VIC 5.0 includes four drivers that use the same physical model core: classic, image, CESM, and Python. The classic driver supports legacy VIC configurations and runs in the traditional time-before-space configuration. The image driver includes a space-before-time configuration, netCDF I/O, and uses MPI for parallel processing. This configuration facilitates the direct coupling of streamflow routing, reservoir, and irrigation processes within VIC. The image driver is the foundation of the CESM driver; which couples VIC to CESM's CPL7 and a prognostic atmosphere. Finally, we have added a Python driver that provides access to the functions and datatypes of VIC's physical core from a Python interface. This presentation demonstrates how reconfiguring legacy source code extends the life and applicability of a research model.
An update to the Surface Ocean CO2 Atlas (SOCAT version 2)
NASA Astrophysics Data System (ADS)
Bakker, D. C. E.; Pfeil, B.; Smith, K.; Hankin, S.; Olsen, A.; Alin, S. R.; Cosca, C.; Harasawa, S.; Kozyr, A.; Nojiri, Y.; O'Brien, K. M.; Schuster, U.; Telszewski, M.; Tilbrook, B.; Wada, C.; Akl, J.; Barbero, L.; Bates, N. R.; Boutin, J.; Bozec, Y.; Cai, W.-J.; Castle, R. D.; Chavez, F. P.; Chen, L.; Chierici, M.; Currie, K.; de Baar, H. J. W.; Evans, W.; Feely, R. A.; Fransson, A.; Gao, Z.; Hales, B.; Hardman-Mountford, N. J.; Hoppema, M.; Huang, W.-J.; Hunt, C. W.; Huss, B.; Ichikawa, T.; Johannessen, T.; Jones, E. M.; Jones, S. D.; Jutterström, S.; Kitidis, V.; Körtzinger, A.; Landschützer, P.; Lauvset, S. K.; Lefèvre, N.; Manke, A. B.; Mathis, J. T.; Merlivat, L.; Metzl, N.; Murata, A.; Newberger, T.; Omar, A. M.; Ono, T.; Park, G.-H.; Paterson, K.; Pierrot, D.; Ríos, A. F.; Sabine, C. L.; Saito, S.; Salisbury, J.; Sarma, V. V. S. S.; Schlitzer, R.; Sieger, R.; Skjelvan, I.; Steinhoff, T.; Sullivan, K. F.; Sun, H.; Sutton, A. J.; Suzuki, T.; Sweeney, C.; Takahashi, T.; Tjiputra, J.; Tsurushima, N.; van Heuven, S. M. A. C.; Vandemark, D.; Vlahos, P.; Wallace, D. W. R.; Wanninkhof, R.; Watson, A. J.
2014-03-01
The Surface Ocean CO2 Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO2 (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO2 values) and extended data coverage (from 1968-2007 to 1968-2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longerterm variation, as well as initialisation or validation of ocean carbon models and coupled climate-carbon models. Data coverage Repository-References: Individual data set files and synthesis product: doi:10.1594/PANGAEA.811776 Gridded products: doi:10.3334/CDIAC/OTG.SOCAT_V2_GRID Available at: http://www.socat.info/ Coverage: 79° S to 90° N; 180° W to 180° E Location Name: Global Oceans and Coastal Seas Date/Time Start: 16 November 1968 ate/Time End: 26 December 2011
S. A. Covert; P. R. Robichaud; W. J. Elliot; T. E. Link
2005-01-01
This study evaluates runoff predictions generated by GeoWEPP (Geo-spatial interface to the Water Erosion Prediction Project) and a modified version of WEPP v98.4 for forest soils. Three small (2 to 9 ha) watersheds in the mountains of the interior Northwest were monitored for several years following timber harvest and prescribed fires. Observed climate variables,...
NASA Astrophysics Data System (ADS)
Pascoe, Stephen; Cinquini, Luca; Lawrence, Bryan
2010-05-01
The Phase 5 Coupled Model Intercomparison Project (CMIP5) will produce a petabyte scale archive of climate data relevant to future international assessments of climate science (e.g., the IPCC's 5th Assessment Report scheduled for publication in 2013). The infrastructure for the CMIP5 archive must meet many challenges to support this ambitious international project. We describe here the distributed software architecture being deployed worldwide to meet these challenges. The CMIP5 architecture extends the Earth System Grid (ESG) distributed architecture of Datanodes, providing data access and visualisation services, and Gateways providing the user interface including registration, search and browse services. Additional features developed for CMIP5 include a publication workflow incorporating quality control and metadata submission, data replication, version control, update notification and production of citable metadata records. Implementation of these features have been driven by the requirements of reliable global access to over 1Pb of data and consistent citability of data and metadata. Central to the implementation is the concept of Atomic Datasets that are identifiable through a Data Reference Syntax (DRS). Atomic Datasets are immutable to allow them to be replicated and tracked whilst maintaining data consistency. However, since occasional errors in data production and processing is inevitable, new versions can be published and users notified of these updates. As deprecated datasets may be the target of existing citations they can remain visible in the system. Replication of Atomic Datasets is designed to improve regional access and provide fault tolerance. Several datanodes in the system are designated replicating nodes and hold replicas of a portion of the archive expected to be of broad interest to the community. Gateways provide a system-wide interface to users where they can track the version history and location of replicas to select the most appropriate location for download. In addition to meeting the immediate needs of CMIP5 this architecture provides a basis for the Earth System Modeling e-infrastructure being further developed within the EU FP7 IS-ENES project.
NASA's climate data system primer, version 1.2
NASA Technical Reports Server (NTRS)
Closs, James W.; Reph, Mary G.; Olsen, Lola M.
1989-01-01
This is a beginner's manual for NASA's Climate Data System (NCDS), an interactive scientific information management system that allows one to locate, access, manipulate, and display climate-research data. Additional information on the use of the system is available from the system itself.
NASA Astrophysics Data System (ADS)
Prinn, R. G.
2013-12-01
The world is facing major challenges that create tensions between human development and environmental sustenance. In facing these challenges, computer models are invaluable tools for addressing the need for probabilistic approaches to forecasting. To illustrate this, I use the MIT Integrated Global System Model framework (IGSM; http://globalchange.mit.edu ). The IGSM consists of a set of coupled sub-models of global economic and technological development and resultant emissions, and physical, dynamical and chemical processes in the atmosphere, land, ocean and ecosystems (natural and managed). Some of the sub-models have both complex and simplified versions available, with the choice of which version to use being guided by the questions being addressed. Some sub-models (e.g.urban air pollution) are reduced forms of complex ones created by probabilistic collocation with polynomial chaos bases. Given the significant uncertainties in the model components, it is highly desirable that forecasts be probabilistic. We achieve this by running 400-member ensembles (Latin hypercube sampling) with different choices for key uncertain variables and processes within the human and natural system model components (pdfs of inputs estimated by model-observation comparisons, literature surveys, or expert elicitation). The IGSM has recently been used for probabilistic forecasts of climate, each using 400-member ensembles: one ensemble assumes no explicit climate mitigation policy and others assume increasingly stringent policies involving stabilization of greenhouse gases at various levels. These forecasts indicate clearly that the greatest effect of these policies is to lower the probability of extreme changes. The value of such probability analyses for policy decision-making lies in their ability to compare relative (not just absolute) risks of various policies, which are less affected by the earth system model uncertainties. Given the uncertainties in forecasts, it is also clear that we need to evaluate policies based on their ability to lower risk, and to re-evaluate decisions over time as new knowledge is gained. Reference: R. G. Prinn, Development and Application of Earth System Models, Proceedings, National Academy of Science, June 15, 2012, http://www.pnas.org/cgi/doi/10.1073/pnas.1107470109.
AmeriFlux US-MRf Mary's River (Fir) site
DOE Office of Scientific and Technical Information (OSTI.GOV)
Law, Bev
This is the AmeriFlux version of the carbon flux data for the site US-MRf Mary's River (Fir) site. Site Description - The Marys River Fir site is part of the "Synthesis of Remote Sensing and Field Observations to Model and Understand Disturbance and Climate Effects on the Carbon Balance of Oregon and Northern California (ORCA)". Located in the western region of Oregon the Marys River site represents the western extent of the climate gradient that spans eastward into the semi-arid basin of central Oregon. The sites that make up the eastern extent of the ORCA climate gradient is the Metoliusmore » site network (US-Me1, US-ME2, US-ME4, US-Me5) all of which are part of the TERRA PNW project at Oregon State University.« less
Lee, Chang-Hun; Song, Juyoung
2012-08-01
This study uses an ecological systems theory to understand bullying behavior. Emphasis is given to overcome limitations found in the literature, such as very little empirical research on functions of parental involvement and the impacts of school climate on bullying as an outcome variable. Two functions of parental involvement investigated are (a) bridging the negative experiences within the family with bullying behaviors at schools, and (b) influencing school climate. Bullying behaviors were measured by a modified Korean version of Olweus' bully/victim questionnaire (reliability range: .78-.84) from 1,238 randomly selected Korean middle school students in 2007. Findings from structural equation modeling (SEM) analyses showed that (a) individual traits are one of the most important influence on bullying, (b) negative experiences in the family do not have direct influence on bullying behaviors at school, (c) parental involvement influences school climate, and (d) positive school climate was negatively related to bullying behaviors.
NASA Technical Reports Server (NTRS)
Li, Peng; Chou, Ming-Dah; Arking, Albert
1987-01-01
The transient response of the climate to increasing CO2 is studied using a modified version of the multilayer energy balance model of Peng et al. (1982). The main characteristics of the model are described. Latitudinal and seasonal distributions of planetary albedo, latitude-time distributions of zonal mean temperatures, and latitudinal distributions of evaporation, water vapor transport, and snow cover generated from the model and derived from actual observations are analyzed and compared. It is observed that in response to an atmospheric doubling of CO2, the model reaches within 1/e of the equilibrium response of global mean surface temperature in 9-35 years for the probable range of vertical heat diffusivity in the ocean. For CO2 increases projected by the National Research Council (1983), the model's transient response in annually and globally averaged surface temperatures is 60-75 percent of the corresponding equilibrium response, and the disequilibrium increases with increasing heat diffusivity of the ocean.
NASA Astrophysics Data System (ADS)
Wang, W.; Dungan, J. L.; Hashimoto, H.; Michaelis, A.; Milesi, C.; Ichii, K.; Nemani, R. R.
2009-12-01
We are conducting an ensemble modeling exercise using the Terrestrial Observation and Prediction System (TOPS) to characterize structural uncertainty in carbon fluxes and stocks estimates from different ecosystem models. The experiment uses public-domain versions of Biome-BGC, LPJ, TOPS-BGC, and CASA, driven by a consistent set of climate fields for North America at 8km resolution and daily/monthly time steps over the period of 1982-2006. A set of diagnostics is developed to characterize the behavior of the models in the climate (temperature-precipitation) space, and to evaluate the simulated carbon cycle in an integrated way. The key findings of this study include that: (relative) optimal primary production is generally found in climate regions where the relationship between annual temperature (T, oC) and precipitation (P, mm) is defined by P = 50*T+500; the ratios between NPP and GPP are close to 50% on average, yet can vary between models and in different climate regions; the allocation of carbon to leaf growth represents a positive feedback to the primary production, and different approaches to constrain this process have significant impacts on the simulated carbon cycle; substantial differences in biomass stocks may be induced by small differences in the tissue turnover rate and the plant mortality; the mean residence time of soil carbon pools is strongly influenced by schemes of temperature regulations; non-respiratory disturbances (e.g., fires) are the main driver for NEP, yet its magnitudes vary between models. Overall, these findings indicate that although the structures of the models are similar, the uncertainties among them can be large, highlighting the problem inherent in relying on only one modeling approach to map surface carbon fluxes or to assess vegetation-climate interactions.
Emissions pathways, climate change, and impacts on California
Hayhoe, Katharine; Cayan, Daniel; Field, Christopher B.; Frumhoff, Peter C.; Maurer, Edwin P.; Miller, Norman L.; Moser, Susanne C.; Schneider, Stephen H.; Cahill, Kimberly Nicholas; Cleland, Elsa E.; Dale, Larry; Drapek, Ray; Hanemann, R. Michael; Kalkstein, Laurence S.; Lenihan, James; Lunch, Claire K.; Neilson, Ronald P.; Sheridan, Scott C.; Verville, Julia H.
2004-01-01
The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50–75%; and Sierra snowpack is reduced 30–70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75–90%; and snowpack declines 73–90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades. PMID:15314227
Zhang, Qian; Ge, Yan; Qu, Weina; Zhang, Kan; Sun, Xianghong
2018-04-01
Traffic safety climate is defined as road users' attitudes and perceptions of traffic in a specific context at a given point in time. The current study aimed to validate the Chinese version of the Traffic Climate Scale (TCS) and to explore its relation to drivers' personality and dangerous driving behavior. A sample of 413 drivers completed the Big Five Inventory (BFI), the Chinese version of the TCS, the Dula Dangerous Driving Index (DDDI) and a demographic questionnaire. Exploratory factor analysis and confirmatory factor analysis were performed to confirm a three-factor (external affective demands, internal requirements and functionality) solution of the TCS. The reliability and validity of the Chinese version of TCS were verified. More importantly, the results showed that the effect of personality on dangerous driving behavior was mediated by traffic climate. Specifically, the functionality of the TCS mediated the effect of neuroticism on negative cognitive/emotional driving and drunk driving, while openness had an indirect impact on aggressive driving, risky driving and drunk driving based on the internal requirements of the TCS. Additionally, agreeableness had a negative direct impact on four factors of the DDDI, while neuroticism had a positive direct impact on negative cognitive/emotional driving, drunk driving and risky driving. In conclusion, the Chinese version of the TCS will be useful to evaluate drivers' attitudes towards and perceptions of the requirements of traffic environment in which they participate and will also be valuable for comparing traffic cultures and environments in different countries. Copyright © 2018 Elsevier Ltd. All rights reserved.
Development of ALARO-Climate regional climate model for a very high resolution
NASA Astrophysics Data System (ADS)
Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan
2014-05-01
ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main results of the RCM ALARO-Climate model simulations in 25 and 6.25 km resolutions on the longer time-scale (1961-1990). The model was driven by the ERA-40 re-analyses and run on the integration domain of ~ 2500 x 2500 km size covering the central Europe. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version dataset 8. Other simulated parameters (e.g., cloudiness, radiation or components of water cycle) were compared to the ERA-40 re-analyses. The validation of the first ERA-40 simulation in both, 25 km and 6.25 km resolutions, revealed significant cold biases in all seasons and overestimation of precipitation in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The differences between these simulations were small and thus revealed a robustness of the model's physical parameterization on the resolution change. The series of 25 km resolution simulations with several model adaptations was carried out to study their effect on the simulated properties of climate variables and thus possibly identify a source of major errors in the simulated climate. The current investigation suggests the main reason for biases is related to the model physic. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).
NASA Astrophysics Data System (ADS)
Eliseev, A. V.; Mokhov, I. I.; Chernokulsky, A. V.
2017-01-01
A module for simulating of natural fires (NFs) in the climate model of the A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM), is extended with respect to the influence of lightning activity and population density on the ignition frequency and fire suppression. The IAP RAS CM is used to perform numerical experiments in accordance with the conditions of the project that intercompares climate models, CMIP5 (Coupled Models Intercomparison Project, phase 5). The frequency of lightning flashes was assigned in accordance with the LIS/OTD satellite data. In the calculations performed, anthropogenic ignitions play an important role in NF occurrences, except for regions at subpolar latitudes and, to a lesser degree, tropical and subtropical regions. Taking into account the dependence of fire frequency on lightning activity and population density intensifies the influence of characteristics of natural fires on the climate changes in tropics and subtropics as compared to the version of the IAP RAS CM that does not take the influence of ignition sources on the large-scale characteristics of NFs into consideration.
Path Dependence of Regional Climate Change
NASA Astrophysics Data System (ADS)
Herrington, Tyler; Zickfeld, Kirsten
2013-04-01
Path dependence of the climate response to CO2 forcing has been investigated from a global mean perspective, with evidence suggesting that long-term global mean temperature and precipitation changes are proportional to cumulative CO2 emissions, and independent of emissions pathway. Little research, however, has been done on path dependence of regional climate changes, particularly in areas that could be affected by tipping points. Here, we utilize the UVic Earth System Climate Model version 2.9, an Earth System Model of Intermediate Complexity. It consists of a 3-dimensional ocean general circulation model, coupled with a dynamic-thermodynamic sea ice model, and a thermodynamic energy-moisture balance model of the atmosphere. This is then coupled with a terrestrial carbon cycle model and an ocean carbon-cycle model containing an inorganic carbon and marine ecosystem component. Model coverage is global with a zonal resolution of 3.6 degrees and meridional resolution of 1.8 degrees. The model is forced with idealized emissions scenarios across five cumulative emission groups (1300 GtC, 2300 GtC, 3300 GtC, 4300 GtC, and 5300 GtC) to explore the path dependence of (and the possibility of hysteresis in) regional climate changes. Emission curves include both fossil carbon emissions and emissions from land use changes, and span a variety of peak and decline scenarios with varying emission rates, as well as overshoot and instantaneous pulse scenarios. Tipping points being explored include those responsible for the disappearance of summer Arctic sea-ice, the irreversible melt of the Greenland Ice Sheet, the collapse of the Atlantic Thermohaline Circulation, and the dieback of the Amazonian Rainforest. Preliminary results suggest that global mean climate change after cessation of CO2 emissions is independent of the emissions pathway, only varying with total cumulative emissions, in accordance with results from earlier studies. Forthcoming analysis will investigate path dependence of regional climate change. Some evidence exists to support the idea of hysteresis in the Greenland Ice Sheet, and since tipping points represent non-linear elements of the climate system, we suspect that the other tipping points might also show path dependence.
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis; Iredell, Lena
2016-01-01
The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.
CrIS/ATMS Retrievals Using the Latest AIRS/AMSU Retrieval Methodology
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis C.; Blaisdell, John; Iredell, Lena
2015-01-01
This research is being done under the NPP Science Team Proposal: Analysis of CrISATMS Using an AIRS Version 6-like Retrieval Algorithm Objective: Generate a long term CrISATMS level-3 data set that is consistent with that of AIRSAMSU Approach: Adapt the currently operational AIRS Science Team Version-6 Retrieval Algorithm, or an improved version of it, for use with CrISATMS data. Metric: Generate monthly mean level-3 CrISATMS climate data sets and evaluate the results by comparison of monthly mean AIRSAMSU and CrISATMS products, and more significantly, their inter-annual differences and, eventually, anomaly time series. The goal is consistency between the AIRSAMSU and CrISATMS climate data sets.
Multimodel ensemble projection of precipitation in eastern China under A1B emission scenario
NASA Astrophysics Data System (ADS)
Niu, Xiaorui; Wang, Shuyu; Tang, Jianping; Lee, Dong-Kyou; Gao, Xuejie; Wu, Jia; Hong, Songyou; Gutowski, William J.; McGregor, John
2015-10-01
As part of the Regional Climate Model Intercomparison Project for Asia, future precipitation projection in China is constructed using five regional climate models (RCMs) driven by the same global climate model (GCM) of European Centre/Hamburg version 5. The simulations cover both the control climate (1978-2000) and future projection (2041-2070) under the Intergovernmental Panel on Climate Change emission scenario A1B. For the control climate, the RCMs have an advantage over the driving GCM in reproducing the summer mean precipitation distribution and the annual cycle. The biases in simulating summer precipitation mainly are caused by the deficiencies in reproducing the low-level circulation, such as the western Pacific subtropical high. In addition, large inter-RCM differences exist in the summer precipitation simulations. For the future climate, consistent and inconsistent changes in precipitation between the driving GCM and the nested RCMs are observed. Similar changes in summer precipitation are projected by RCMs over western China, but model behaviors are quite different over eastern China, which is dominated by the Asian monsoon system. The inter-RCM difference of rainfall changes is more pronounced in spring over eastern China. North China and the southern part of South China are very likely to experience less summer rainfall in multi-RCM mean (MRM) projection, while limited credibility in increased summer rainfall MRM projection over the lower reaches of the Yangtze River Basin. The inter-RCM variability is the main contributor to the total uncertainty for the lower reaches of the Yangtze River Basin and South China during 2041-2060, while lowest for Northeast China, being less than 40%.
ERIC Educational Resources Information Center
Huang, Francis L.; Cornell, Dewey G.; Konold, Timothy; Meyer, Joseph P.; Lacey, Anna; Nekvasil, Erin K.; Heilbrun, Anna; Shukla, Kathan D.
2015-01-01
Background: School climate is well recognized as an important influence on student behavior and adjustment to school, but there is a need for theory-guided measures that make use of teacher perspectives. Authoritative school climate theory hypothesizes that a positive school climate is characterized by high levels of disciplinary structure and…
NASA Astrophysics Data System (ADS)
Zhang, Y.; Chen, W.; Li, J.
2014-07-01
Climate change may alter the spatial distribution, composition, structure and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate the solar radiation absorbed by individual plants in order to understand and predict their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming that crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the results of random distribution of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and can be included in vegetation models to simulate long-term transient responses of plant communities to climate change. The code and a user's manual are provided as Supplement of the paper.
A Dynamical Downscaling study over the Great Lakes Region Using WRF-Lake: Historical Simulation
NASA Astrophysics Data System (ADS)
Xiao, C.; Lofgren, B. M.
2014-12-01
As the largest group of fresh water bodies on Earth, the Laurentian Great Lakes have significant influence on local and regional weather and climate through their unique physical features compared with the surrounding land. Due to the limited spatial resolution and computational efficiency of general circulation models (GCMs), the Great Lakes are geometrically ignored or idealized into several grid cells in GCMs. Thus, the nested regional climate modeling (RCM) technique, known as dynamical downscaling, serves as a feasible solution to fill the gap. The latest Weather Research and Forecasting model (WRF) is employed to dynamically downscale the historical simulation produced by the Geophysical Fluid Dynamics Laboratory-Coupled Model (GFDL-CM3) from 1970-2005. An updated lake scheme originated from the Community Land Model is implemented in the latest WRF version 3.6. It is a one-dimensional mass and energy balance scheme with 20-25 model layers, including up to 5 snow layers on the lake ice, 10 water layers, and 10 soil layers on the lake bottom. The lake scheme is used with actual lake points and lake depth. The preliminary results show that WRF-Lake model, with a fine horizontal resolution and realistic lake representation, provides significantly improved hydroclimates, in terms of lake surface temperature, annual cycle of precipitation, ice content, and lake-effect snowfall. Those improvements suggest that better resolution of the lakes and the mesoscale process of lake-atmosphere interaction are crucial to understanding the climate and climate change in the Great Lakes region.
Extending the Confrontation of Weather and Climate Models from Soil Moisture to Surface Flux Data
NASA Astrophysics Data System (ADS)
Dirmeyer, P.; Chen, L.; Wu, J.
2016-12-01
The atmosphere and land components of weather and climate models are typically developed separately and coupled as a last step before new model versions are released. Separate testing of land surface models (LSMs) and atmospheric models is often quite extensive in the development phase, but validation of coupled land-atmosphere behavior is often minimal if performed at all. This is partly because of this piecemeal model development approach and partly because the necessary in situ data to confront coupled land-atmosphere models (LAMs) has been meager until quite recently. Over the past 10-20 years there has been a growing number of networks of measurements of land surface states, surface fluxes, radiation and near-surface meteorology, although they have been largely uncoordinated and frequently incomplete across the range of variables necessary to validate LAMs. We extend recent work "confronting" a variety of LSMs and LAMs with in situ observations of soil moisture from cross-standardized networks to comparisons with measurements of surface latent and sensible heat fluxes at FLUXNET sites in a variety of climate regimes around the world. The motivation is to determine how well LSMs represent observed statistics of variability and co-variability, how much models differ from one another, and how those statistics change when the LSMs are coupled to atmospheric models. Furthermore, comparisons are made to several LAMs in both open-loop (free running) and reanalysis configurations. This shows to what extent data assimilation can constrain the processes involved in flux variability, and helps illuminate model development pathways to improve coupled land-atmosphere interactions in weather and climate models.
A model for evaluating stream temperature response to climate change scenarios in Wisconsin
Westenbroek, Stephen M.; Stewart, Jana S.; Buchwald, Cheryl A.; Mitro, Matthew G.; Lyons, John D.; Greb, Steven
2010-01-01
Global climate change is expected to alter temperature and flow regimes for streams in Wisconsin over the coming decades. Stream temperature will be influenced not only by the predicted increases in average air temperature, but also by changes in baseflow due to changes in precipitation patterns and amounts. In order to evaluate future stream temperature and flow regimes in Wisconsin, we have integrated two existing models in order to generate a water temperature time series at a regional scale for thousands of stream reaches where site-specific temperature observations do not exist. The approach uses the US Geological Survey (USGS) Soil-Water-Balance (SWB) model, along with a recalibrated version of an existing artificial neural network (ANN) stream temperature model. The ANN model simulates stream temperatures on the basis of landscape variables such as land use and soil type, and also includes climate variables such as air temperature and precipitation amounts. The existing ANN model includes a landscape variable called DARCY designed to reflect the potential for groundwater recharge in the contributing area for a stream segment. SWB tracks soil-moisture and potential recharge at a daily time step, providing a way to link changing climate patterns and precipitation amounts over time to baseflow volumes, and presumably to stream temperatures. The recalibrated ANN incorporates SWB-derived estimates of potential recharge to supplement the static estimates of groundwater flow potential derived from a topographically based model (DARCY). SWB and the recalibrated ANN will be supplied with climate drivers from a suite of general circulation models and emissions scenarios, enabling resource managers to evaluate possible changes in stream temperature regimes for Wisconsin.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wan, Hui; Rasch, Philip J.; Zhang, Kai
2014-09-08
This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivitymore » of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.« less
NASA Astrophysics Data System (ADS)
Naudts, K.; Ryder, J.; McGrath, M. J.; Otto, J.; Chen, Y.; Valade, A.; Bellasen, V.; Berhongaray, G.; Bönisch, G.; Campioli, M.; Ghattas, J.; De Groote, T.; Haverd, V.; Kattge, J.; MacBean, N.; Maignan, F.; Merilä, P.; Penuelas, J.; Peylin, P.; Pinty, B.; Pretzsch, H.; Schulze, E. D.; Solyga, D.; Vuichard, N.; Yan, Y.; Luyssaert, S.
2015-07-01
Since 70 % of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land-surface models used in Earth system models, and therefore none of today's predictions of future climate, accounts for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrising a version of the ORCHIDEE land-surface model to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes were introduced towards a better process representation for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrisation was revisited after introducing 12 new parameter sets that represent specific tree species or genera rather than a group of often distantly related or even unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, gross primary production (GPP), albedo and evapotranspiration over Europe. For all tested variables, ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92 % chance to reproduce the spatial and temporal variability of the validation data.
Simulation of tropospheric chemistry and aerosols with the climate model EC-Earth
NASA Astrophysics Data System (ADS)
van Noije, T. P. C.; Le Sager, P.; Segers, A. J.; van Velthoven, P. F. J.; Krol, M. C.; Hazeleger, W.
2014-03-01
We have integrated the atmospheric chemistry and transport model TM5 into the global climate model EC-Earth version 2.4. We present an overview of the TM5 model and the two-way data exchange between TM5 and the integrated forecasting system (IFS) model from the European Centre for Medium-Range Weather Forecasts (ECMWF), the atmospheric general circulation model of EC-Earth. In this paper we evaluate the simulation of tropospheric chemistry and aerosols in a one-way coupled configuration. We have carried out a decadal simulation for present-day conditions and calculated chemical budgets and climatologies of tracer concentrations and aerosol optical depth. For comparison we have also performed offline simulations driven by meteorological fields from ECMWF's ERA-Interim reanalysis and output from the EC-Earth model itself. Compared to the offline simulations, the online-coupled system produces more efficient vertical mixing in the troposphere, which likely reflects an improvement of the treatment of cumulus convection. The chemistry in the EC-Earth simulations is affected by the fact that the current version of EC-Earth produces a cold bias with too dry air in large parts of the troposphere. Compared to the ERA-Interim driven simulation, the oxidizing capacity in EC-Earth is lower in the tropics and higher in the extratropics. The methane lifetime is 7% higher in EC-Earth, but remains well within the range reported in the literature. We evaluate the model by comparing the simulated climatologies of surface carbon monoxide, tropospheric and surface ozone, and aerosol optical depth against observational data. The work presented in this study is the first step in the development of EC-Earth into an Earth system model with fully interactive atmospheric chemistry and aerosols.
Effects of ENSO-induced extremes on terrestrial ecosystems
NASA Astrophysics Data System (ADS)
Xu, M.; Hoffman, F. M.
2017-12-01
The El Niño Southern Oscillation (ENSO) with its warm (El Niño) and cold phase (La Niña) has well-known global impacts on the Earth system through the mechanism of teleconnections. Not only the global mean temperature and precipitation distributions will be changed but also the climate extremes will be enhanced during ENSO events. In this study, the advanced Earth System Model ACME version 0.3 was used to simulate terrestrial biogeochemistry and global climate from 1982 to 2020 with prescribed Sea Surface Temperature (SST) from data fusions of the NOAA high resolution daily Optimum Interpolation SST (OISST), CFS v2 9-month seasonal forecast and data reconstructions. We investigated how ENSO-induced climate extremes affect land carbon dynamics both regionally and globally and the implications for the functioning of different vegetated ecosystems under the influence of climate extremes. The results show that the ENSO-induced climate extremes, especially drought and heat waves, have significant impacts on the terrestrial carbon cycle. The responses to ENSO-induced climate extremes are divergent among different vegetation types.
NASA Astrophysics Data System (ADS)
Zsolt Torma, Csaba; Giorgi, Filippo
2014-05-01
A set of regional climate model (RCM) simulations applying dynamical downscaling of global climate model (GCM) simulations over the Mediterranean domain specified by the international initiative Coordinated Regional Downscaling Experiment (CORDEX) were completed with the Regional Climate Model RegCM, version RegCM4.3. Two GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the RegCM: HadGEM2-ES (HadGEM) and MPI-ESM-MR (MPI). The simulations consist of an ensemble including multiple physics configurations and different "Reference Concentration Pathways" (RCP4.5 and RCP8.5). In total 15 simulations were carried out with 7 model physics configurations with varying convection and land surface schemes. The horizontal grid spacing of the RCM simulations is 50 km and the simulated period in all cases is 1970-2100 (1970-2099 in case of HadGEM driven simulations). This ensemble includes a combination of experiments in which different model components are changed individually and in combination, and thus lends itself optimally to the application of the Factor Separation (FS) method. This study applies the FS method to investigate the contributions of different factors, along with their synergy, on a set of regional climate model (RCM) projections for the Mediterranean region. The FS method is applied to 6 projections for the period 1970-2100 performed with the regional model RegCM4.3 over the Med-CORDEX domain. Two different sets of factors are intercompared, namely the driving global climate model (HadGEM and MPI) boundary conditions against two model physics settings (convection scheme and irrigation). We find that both the GCM driving conditions and the model physics provide important contributions, depending on the variable analyzed (surface air temperature and precipitation), season (winter vs. summer) and time horizon into the future, while the synergy term mostly tends to counterbalance the contributions of the individual factors. We demonstrate the usefulness of the FS method to assess different sources of uncertainty in RCM-based regional climate projections.
NASA Technical Reports Server (NTRS)
Leslie, Fred W.; Justus, C. G.
2008-01-01
Engineering models of the atmosphere are used extensively by the aerospace community for design issues related to vehicle ascent and descent. The Earth Global Reference Atmosphere Model version 2007 (Earth-GRAM07) is the latest in this series and includes a number of new features. Like previous versions, Earth-GRAM07 provides both mean values and perturbations for density, temperature, pressure, and winds, as well as monthly- and geographically-varying trace constituent concentrations. From 0 km to 27 km, thermodynamics and winds are based on the National Oceanic and Atmospheric Administration Global Upper Air Climatic Atlas (GUACA) climatology. For altitudes between 20 km and 120 km, the model uses data from the Middle Atmosphere Program (MAP). Above 120 km, EarthGRAM07 now provides users with a choice of three thermosphere models: the Marshall Engineering Thermosphere (MET-2007) model; the Jacchia-Bowman 2006 thermosphere model (JB2006); and the Naval Research Labs Mass Spectrometer, Incoherent Scatter Radar Extended Model (NRL MSIS E-OO) with the associated Harmonic Wind Model (HWM-93). In place of these datasets, Earth-GRAM07 has the option of using the new 2006 revised Range Reference Atmosphere (RRA) data, the earlier (1983) RRA data, or the user may also provide their own data as an auxiliary profile. Refinements of the perturbation model are also discussed which include wind shears more similar to those observed at the Kennedy Space Center than the previous version Earth-GRAM99.
Climate drift of AMOC, North Atlantic salinity and arctic sea ice in CFSv2 decadal predictions
NASA Astrophysics Data System (ADS)
Huang, Bohua; Zhu, Jieshun; Marx, Lawrence; Wu, Xingren; Kumar, Arun; Hu, Zeng-Zhen; Balmaseda, Magdalena A.; Zhang, Shaoqing; Lu, Jian; Schneider, Edwin K.; Kinter, James L., III
2015-01-01
There are potential advantages to extending operational seasonal forecast models to predict decadal variability but major efforts are required to assess the model fidelity for this task. In this study, we examine the North Atlantic climate simulated by the NCEP Climate Forecast System, version 2 (CFSv2), using a set of ensemble decadal hindcasts and several 30-year simulations initialized from realistic ocean-atmosphere states. It is found that a substantial climate drift occurs in the first few years of the CFSv2 hindcasts, which represents a major systematic bias and may seriously affect the model's fidelity for decadal prediction. In particular, it is noted that a major reduction of the upper ocean salinity in the northern North Atlantic weakens the Atlantic meridional overturning circulation (AMOC) significantly. This freshening is likely caused by the excessive freshwater transport from the Arctic Ocean and weakened subtropical water transport by the North Atlantic Current. A potential source of the excessive freshwater is the quick melting of sea ice, which also causes unrealistically thin ice cover in the Arctic Ocean. Our sensitivity experiments with adjusted sea ice albedo parameters produce a sustainable ice cover with realistic thickness distribution. It also leads to a moderate increase of the AMOC strength. This study suggests that a realistic freshwater balance, including a proper sea ice feedback, is crucial for simulating the North Atlantic climate and its variability.
NASA Astrophysics Data System (ADS)
Zhang, Wenxin; Miller, Paul A.; Smith, Benjamin; Wania, Rita; Koenigk, Torben; Döscher, Ralf
2013-09-01
One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model-downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961-1990) agreed well with a composite map of actual arctic vegetation. In the future (2051-2080), a poleward advance of the forest-tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH4 emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH4, may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux.
King, David A.; Bachelet, Dominique M.; Symstad, Amy J.
2013-01-01
Since the initial application of MC1 to a small portion of WICA (Bachelet et al. 2000), the model has been altered to improve model performance with the inclusion of dynamic fire. Applying this improved version to WICA required substantial recalibration, during which we have made a number of improvements to MC1 that will be incorporated as permanent changes. In this report we document these changes and our calibration procedure following a brief overview of the model. We compare the projections of current vegetation to the current state of the park and present projections of vegetation dynamics under future climates downscaled from three GCMs selected to represent the existing range in available GCM projections. In doing so, we examine the consequences of different management options regarding fire and grazing, major aspects of biotic management at Wind Cave.
NASA Astrophysics Data System (ADS)
Xue, L.; Newman, A. J.; Ikeda, K.; Rasmussen, R.; Clark, M. P.; Monaghan, A. J.
2016-12-01
A high-resolution (a 1.5 km grid spacing domain nested within a 4.5 km grid spacing domain) 10-year regional climate simulation over the entire Hawaiian archipelago is being conducted at the National Center for Atmospheric Research (NCAR) using the Weather Research and Forecasting (WRF) model version 3.7.1. Numerical sensitivity simulations of the Hawaiian Rainband Project (HaRP, a filed experiment from July to August in 1990) showed that the simulated precipitation properties are sensitive to initial and lateral boundary conditions, sea surface temperature (SST), land surface models, vertical resolution and cloud droplet concentration. The validations of model simulated statistics of the trade wind inversion, temperature, wind field, cloud cover, and precipitation over the islands against various observations from soundings, satellites, weather stations and rain gauges during the period from 2003 to 2012 will be presented at the meeting.
NASA Astrophysics Data System (ADS)
Morris, Chloe; Coulthard, Tom; Parsons, Daniel R.; Manson, Susan; Barkwith, Andrew
2017-04-01
Landscape Evolution Models (LEMs) are proven to be useful tools in understanding the morphodynamics of coast and estuarine systems. However, perhaps owing to the lack of research in this area, current models are not capable of simulating the dynamic interactions between these systems and their co-evolution at the meso-scale. Through a novel coupling of numerical models, this research is designed to explore coupled coastal-estuarine interactions, controls on system behaviour and the influence that environmental change could have. This will contribute to the understanding of the morphodynamics of these systems and how they may behave and evolve over the next century in response to climate changes, with the aim of informing management practices. This goal is being achieved through the modification and coupling of the one-line Coastline Evolution Model (CEM) with the hydrodynamic LEM CAESAR-Lisflood (C-L). The major issues faced with coupling these programs are their differing complexities and the limited graphical visualisations produced by the CEM that hinder the dissemination of results. The work towards overcoming these issues and reported here, include a new version of the CEM that incorporates a range of more complex geomorphological processes and boasts a graphical user interface that guides users through model set-up and projects a live output during model runs. The improved version is a stand-alone tool that can be used for further research projects and for teaching purposes. A sensitivity analysis using the Morris method has been completed to identify which key variables, including wave climate, erosion and weathering values, dominate the control of model behaviour. The model is being applied and tested using the evolution of the Holderness Coast, Humber Estuary and Spurn Point on the east coast of England (UK), which possess diverse geomorphologies and complex, co-evolving sediment pathways. Simulations using the modified CEM are currently being completed to ascertain the processes influential to the morphodynamics and evolution of these systems; presently this includes increasing sea levels and changing wave climate patterns. Outputs and findings from these runs will be presented and discussed, with the aid of the improved graphical visualisations and animations that illustrate the evolution of simulated environments.
Reconstruction of the Eemian climate using a fully coupled Earth system model
NASA Astrophysics Data System (ADS)
Rybak, Oleg; Volodin, Evgeny; Morozova, Polina; Huybrechts, Philippe
2017-04-01
Climate of the Last Interglacial (LIG) between ca. 130 and 115 kyr BP is thought to be a good analogue for future climate warming. Though the driving mechanisms of the past and current climate evolution differ, analysis of the LIG climate may provide important insights for projections of future environmental changes. We do not know properly what was spatial distribution and magnitude of surface air temperature and precipitation anomalies with respect to present. Sparse proxy data are attributed mostly to the continental margins, internal areas of ice sheets and particular regions of the World Ocean. Combining mathematical modeling and indirect evidence can help to identify driving mechanisms and feed-backs which formed climatic conditions of the LIG. In order to reproduce the LIG climate, we carried out transient numerical experiments using a fully coupled Earth System Model (ESM) consisting of an AO GCM, which includes decription of the biosphere, atmospheric and oceanic chemistry ets. (INMCM), developed in the Institute of Numerical Mathematics (Moscow, Russia) and the models of Greenland and Antarctic ice sheets (GrISM and AISM, Vrije Uninersiteit Brussel, Belgium). Though the newest version of the INMCM has rather high spatial resolution, it canot be used in long transient numerical experimemts because of high computational demand. Coupling of the GrISM and AISM to the low resolution version of the INMCM is complicated by essential differences in spatial and temporal scales of cryospheric, atmosphere and the ocean components of the ESM (spatial resolution 5˚×4˚, 21 vertical layers in the atmospheric block, 2.5°×2°, 6 min. temporal resolution; 33 vertical layers in the oceanic block; 20×20 km, 51 vertical layers and 1 yr temporal resolution in the GrISM and AISM). We apply two different coupling strategies. AISM is incorporated into the ESM via using procedures of resampling and interpolation of the input fields of annually averaged air surface temperatures and precipitation fields generated by the INMCM. To provide interactive coupling of the INMCM and the GrISM, we employ a special energy- and water balance model (EWBM-G), which serves as a buffer providing effective data exchange between sub-models. EWBM-G operates in a rectangle domain including Greenland and calculates annual surface mass balance (further transferred as an external forcing to the GrISM) and fresh water flux (transferred to the oceanic block of the INMCM). Orbital parameters of the LIG were set with 1 kyr step with further interpolation to 100 years. Assuming concentrations of greenhouse gases during the LIG were not very much different from the preindustrial values, this potential forcing was neglected. Climatic block of the ESM was called every 100 model years to follow changes in orbital forcing. AISM and GrISM were asynchronously coupled to sub-models of the atmosphere and the ocean with the ratio of model years as 100 to 1. Obtained fields of deviations of air surface temperature from preindustrial values correspond in general to the estimates made in earlier studies. Evaluated contribution of the Greenland ice sheet to the global sea level rise (approximately 2 m) supports the newest estimates based on model results and proxy data analysis.
NASA Astrophysics Data System (ADS)
Senatore, Alfonso; Hejabi, Somayeh; Mendicino, Giuseppe; Bazrafshan, Javad; Irannejad, Parviz
2018-03-01
Climate change projections were evaluated over both the whole Iran and six zones having different precipitation regimes considering the CORDEX South Asia dataset, for assessing space-time distribution of drought occurrences in the future period 2070-2099 under RCP4.5 scenario. Initially, the performances of eight available CORDEX South Asia Regional Climate Models (RCMs) were assessed for the baseline period 1970-2005 through the GPCC v.7 precipitation dataset and the CFSR temperature dataset, which were previously selected as the most reliable within a set of five global datasets compared to 41 available synoptic stations. Though the CCLM RCM driven by the MPI-ESM-LR General Circulation Model is in general the most suitable for temperature and, together with the REMO 2009 RCM also driven by MPI-ESM-LR, for precipitation, their performances do not overwhelm other models for every season and zone in which Iranian territory was divided according to a principal component analysis approach. Hence, a weighting approach was tested and adopted to take into account useful information from every RCM in each of the six zones. The models resulting more reliable compared to current climate show a strong precipitation decrease. Weighted average predicts an overall yearly precipitation decrease of about 20%. Temperature projections provide a mean annual increase of 2.4 °C. Future drought scenarios were depicted by means of the self-calibrating version of the Palmer drought severity index (SC-PDSI) model. Weighted average predicts a sharp drying that can be configured as a real shift in mean climate conditions, drastically affecting water resources of the country.
Acidification at the Surface in the East Sea: A Coupled Climate-carbon Cycle Model Study
NASA Astrophysics Data System (ADS)
Park, Young-Gyu; Seol, Kyung-Hee; Boo, Kyung-On; Lee, Johan; Cho, Chunho; Byun, Young-Hwa; Seo, Seongbong
2018-05-01
This modeling study investigates the impacts of increasing atmospheric CO2 concentration on acidification in the East Sea. A historical simulation for the past three decades (1980 to 2010) was performed using the Hadley Centre Global Environmental Model (version 2), a coupled climate model with atmospheric, terrestrial and ocean cycles. As the atmospheric CO2 concentration increased, acidification progressed in the surface waters of the marginal sea. The acidification was similar in magnitude to observations and models of acidification in the global ocean. However, in the global ocean, the acidification appears to be due to increased in-situ oceanic CO2 uptake, whereas local processes had stronger effects in the East Sea. pH was lowered by surface warming and by the influx of water with higher dissolved inorganic carbon (DIC) from the northwestern Pacific. Due to the enhanced advection of DIC, the partial pressure of CO2 increased faster than in the overlying air; consequently, the in-situ oceanic uptake of CO2 decreased.
High-resolution RCMs as pioneers for future GCMs
NASA Astrophysics Data System (ADS)
Schar, C.; Ban, N.; Arteaga, A.; Charpilloz, C.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Leutwyler, D.; Lüthi, D.; Piaget, N.; Ruedisuehli, S.; Schlemmer, L.; Schulthess, T. C.; Wernli, H.
2017-12-01
Currently large efforts are underway to refine the horizontal resolution of global and regional climate models to O(1 km), with the intent to represent convective clouds explicitly rather than using semi-empirical parameterizations. This refinement will move the governing equations closer to first principles and is expected to reduce the uncertainties of climate models. High resolution is particularly attractive in order to better represent critical cloud feedback processes (e.g. related to global climate sensitivity and extratropical summer convection) and extreme events (such as heavy precipitation events, floods, and hurricanes). The presentation will be illustrated using decade-long simulations at 2 km horizontal grid spacing, some of these covering the European continent on a computational mesh with 1536x1536x60 grid points. To accomplish such simulations, use is made of emerging heterogeneous supercomputing architectures, using a version of the COSMO limited-area weather and climate model that is able to run entirely on GPUs. Results show that kilometer-scale resolution dramatically improves the simulation of precipitation in terms of the diurnal cycle and short-term extremes. The modeling framework is used to address changes of precipitation scaling with climate change. It is argued that already today, modern supercomputers would in principle enable global atmospheric convection-resolving climate simulations, provided appropriately refactored codes were available, and provided solutions were found to cope with the rapidly growing output volume. A discussion will be provided of key challenges affecting the design of future high-resolution climate models. It is suggested that km-scale RCMs should be exploited to pioneer this terrain, at a time when GCMs are not yet available at such resolutions. Areas of interest include the development of new parameterization schemes adequate for km-scale resolution, the exploration of new validation methodologies and data sets, the assessment of regional-scale climate feedback processes, and the development of alternative output analysis methodologies.
An Estimation of the Climatic Effects of Stratospheric Ozone Losses during the 1980s. Appendix K
NASA Technical Reports Server (NTRS)
MacKay, Robert M.; Ko, Malcolm K. W.; Shia, Run-Lie; Yang, Yajaing; Zhou, Shuntai; Molnar, Gyula
1997-01-01
In order to study the potential climatic effects of the ozone hole more directly and to assess the validity of previous lower resolution model results, the latest high spatial resolution version of the Atmospheric and Environmental Research, Inc., seasonal radiative dynamical climate model is used to simulate the climatic effects of ozone changes relative to the other greenhouse gases. The steady-state climatic effect of a sustained decrease in lower stratospheric ozone, similar in magnitude to the observed 1979-90 decrease, is estimated by comparing three steady-state climate simulations: 1) 1979 greenhouse gas concentrations and 1979 ozone, II) 1990 greenhouse gas concentrations with 1979 ozone, and III) 1990 greenhouse gas concentrations with 1990 ozone. The simulated increase in surface air temperature resulting from nonozone greenhouse gases is 0.272 K. When changes in lower stratospheric ozone are included, the greenhouse warming is 0.165 K, which is approximately 39% lower than when ozone is fixed at the 1979 concentrations. Ozone perturbations at high latitudes result in a cooling of the surface-troposphere system that is greater (by a factor of 2.8) than that estimated from the change in radiative forcing resulting from ozone depiction and the model's 2 x CO, climate sensitivity. The results suggest that changes in meridional heat transport from low to high latitudes combined with the decrease in the infrared opacity of the lower stratosphere are very important in determining the steady-state response to high latitude ozone losses. The 39% compensation in greenhouse warming resulting from lower stratospheric ozone losses is also larger than the 28% compensation simulated previously by the lower resolution model. The higher resolution model is able to resolve the high latitude features of the assumed ozone perturbation, which are important in determining the overall climate sensitivity to these perturbations.
Aerosol specification in single-column Community Atmosphere Model version 5
Lebassi-Habtezion, B.; Caldwell, P. M.
2015-03-27
Single-column model (SCM) capability is an important tool for general circulation model development. In this study, the SCM mode of version 5 of the Community Atmosphere Model (CAM5) is shown to handle aerosol initialization and advection improperly, resulting in aerosol, cloud-droplet, and ice crystal concentrations which are typically much lower than observed or simulated by CAM5 in global mode. This deficiency has a major impact on stratiform cloud simulations but has little impact on convective case studies because aerosol is currently not used by CAM5 convective schemes and convective cases are typically longer in duration (so initialization is less important).more » By imposing fixed aerosol or cloud-droplet and crystal number concentrations, the aerosol issues described above can be avoided. Sensitivity studies using these idealizations suggest that the Meyers et al. (1992) ice nucleation scheme prevents mixed-phase cloud from existing by producing too many ice crystals. Microphysics is shown to strongly deplete cloud water in stratiform cases, indicating problems with sequential splitting in CAM5 and the need for careful interpretation of output from sequentially split climate models. Droplet concentration in the general circulation model (GCM) version of CAM5 is also shown to be far too low (~ 25 cm −3) at the southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site.« less
Evaluation of improved land use and canopy representation in ...
Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data are based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for 2002–2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emission estimates are used in Community Multiscale Air Quality (CMAQ) Model simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterp
A Web-Based Polar Firn Model to Motivate Interest in Climate Change
NASA Astrophysics Data System (ADS)
Harris, P. D.; Lundin, J.; Stevens, C.; Leahy, W.; Waddington, E. D.
2013-12-01
How long would you have to dig straight down in Greenland before you reached solid ice? This is one of many questions that could be answered by a typical high school student using our online firn model. Firn is fallen snow that compacts under its own weight and eventually turns into glacial ice. The Herron and Langway (1980) firn model describes this process. An important component of predicting future climate change is researching past climate change. Some details of our past climate are discovered by analyzing polar ice and the firn process. Firn research can also be useful for understanding how changes in ice surface levels reflect changes in the ice mass. We have produced an online version of the Herron and Langway model that provides a simple way for students to learn how polar snow turns into ice. As a user, you can enter some climatic conditions (accumulation rate, temperature, and surface density) into our graphical user interface and press 'Submit'. We take the numbers you enter in your internet browser, send them to the model written in Python that is running on our server, and provide links to your results, all within seconds. The model produces firn depth, density, and age data. The results appear on the webpage in both text and graphical format. We have developed an example lesson plan appropriate for a high-school physics or environmental science class. The online model offers students an opportunity to apply their scientific knowledge in order to understand real-world physical processes. Additionally, students learn about scientific research and the tools scientists use to conduct it. The model can be used as a standalone lesson or as a part of a larger climate-science unit. The online model was created with funding from the Washington NASA Space Grant Consortium and the National Science Foundation's Partnerships for International Research and Education program.
Towards a regional climate model coupled to a comprehensive hydrological model
NASA Astrophysics Data System (ADS)
Rasmussen, S. H.; Drews, M.; Christensen, J. H.; Butts, M. B.; Jensen, K. H.; Refsgaard, J.; Hydrological ModellingAssessing Climate Change Impacts At Different Scales (Hyacints)
2010-12-01
When planing new ground water abstractions wells, building areas, roads or other land use activities information about expected future groundwater table location for the lifetime of the construction may be critical. The life time of an abstraction well can be expected to be more than 50 years, while if for buildings may be up to 100 years or more. The construction of an abstraction well is expensive and it is important to know if clean groundwater is available for its expected life time. The future groundwater table is depending on the future climate. With climate change the hydrology is expected to change as well. Traditionally, this assessment has been done by driving hydrological models with output from a climate model. In this way feedback between the groundwater hydrology and the climate is neglected. Neglecting this feedback can lead to imprecise or wrong results. The goal of this work is to couple the regional climate model HIRHAM (Christensen et al. 2006) to the hydrological model MIKE SHE (Graham and Butts, 2006). The coupling exploits the new OpenMI technology that provides a standardized interface to define, describe and transfer data on a time step basis between software components that run simultaneously (Gregersen et al., 2007). HIRHAM runs on a UNIX platform whereas MIKE SHE and OpenMI are under WINDOWS. Therefore the first critical task has been to develop an effective communication link between the platforms. The first step towards assessing the coupled models performance are addressed by looking at simulated land-surface atmosphere feedback through variables such as evapotranspiration, sensible heat flux and soil moisture content. Christensen, O.B., Drews, M., Christensen, J.H., Dethloff, K., Ketelsen, K., Hebestadt, I. and Rinke, A. (2006) The HIRHAM Regional Climate Model. Version 5; DMI Scientific Report 0617. Danish Meteorological Institute. Graham, D.N. and Butts, M.B. (2005) Flexible, integrated watershed modelling with MIKE SHE, In Watershed Models, (Eds. V.P. Singh & D.K. Frevert) CRC Press. Pages 245-272, ISBN: 0849336090. Gregersen, J.B., Gijsbers, P.J.A. and Westen, S.J.P. (2007) OpenMI: Open modelling interface. Journal of Hydroinformatics, 09.3, 175191. doi: 10.2166/hydro.2007.023.
Impacts of boundary condition changes on regional climate projections over West Africa
NASA Astrophysics Data System (ADS)
Kim, Jee Hee; Kim, Yeonjoo; Wang, Guiling
2017-06-01
Future projections using regional climate models (RCMs) are driven with boundary conditions (BCs) typically derived from global climate models. Understanding the impact of the various BCs on regional climate projections is critical for characterizing their robustness and uncertainties. In this study, the International Center for Theoretical Physics Regional Climate Model Version 4 (RegCM4) is used to investigate the impact of different aspects of boundary conditions, including lateral BCs and sea surface temperature (SST), on projected future changes of regional climate in West Africa, and BCs from the coupled European Community-Hamburg Atmospheric Model 5/Max Planck Institute Ocean Model are used as an example. Historical, future, and several sensitivity experiments are conducted with various combinations of BCs and CO2 concentration, and differences among the experiments are compared to identify the most important drivers for RCMs. When driven by changes in all factors, the RegCM4-produced future climate changes include significantly drier conditions in Sahel and wetter conditions along the Guinean coast. Changes in CO2 concentration within the RCM domain alone or changes in wind vectors at the domain boundaries alone have minor impact on projected future climate changes. Changes in the atmospheric humidity alone at the domain boundaries lead to a wetter Sahel due to the northward migration of rain belts during summer. This impact, although significant, is offset and dominated by changes of other BC factors (primarily temperature) that cause a drying signal. Future changes of atmospheric temperature at the domain boundaries combined with SST changes over oceans are sufficient to cause a future climate that closely resembles the projection that accounts for all factors combined. Therefore, climate variability and changes simulated by RCMs depend primarily on the variability and change of temperature aspects of the RCM BCs. Moreover, it is found that the response of the RCM climate to different climate change factors is roughly linear in that the projected changes driven by combined factors are close to the sum of projected changes due to each individual factor alone at least for long-term averages. Findings from this study are important for understanding the source(s) of uncertainties in regional climate projections and for designing innovative approaches to climate downscaling and impact assessment.
UNSAT-H Version 2. 0: Unsaturated soil water and heat flow model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fayer, M.J.; Jones, T.L.
1990-04-01
This report documents UNSAT-H Version 2.0, a model for calculating water and heat flow in unsaturated media. The documentation includes the bases for the conceptual model and its numerical implementation, benchmark test cases, example simulations involving layered soils and plant transpiration, and the code listing. Waste management practices at the Hanford Site have included disposal of low-level wastes by near-surface burial. Predicting the future long-term performance of any such burial site in terms of migration of contaminants requires a model capable of simulating water flow in the unsaturated soils above the buried waste. The model currently used to meet thismore » need is UNSAT-H. This model was developed at Pacific Northwest Laboratory to assess water dynamics of near-surface, waste-disposal sites at the Hanford Site. The code is primarily used to predict deep drainage as a function of such environmental conditions as climate, soil type, and vegetation. UNSAT-H is also used to simulate the effects of various practices to enhance isolation of wastes. 66 refs., 29 figs., 7 tabs.« less
A Revised Thermosphere for the Mars Global Reference Atmospheric Model (Mars-GRAM Version 3.4)
NASA Technical Reports Server (NTRS)
Justus, C. G.; Johnson, D. L.; James, B. F.
1996-01-01
This report describes the newly-revised model thermosphere for the Mars Global Reference Atmospheric Model (Mars-GRAM, Version 3.4). It also provides descriptions of other changes made to the program since publication of the programmer's guide for Mars-GRAM Version 3.34. The original Mars-GRAM model thermosphere was based on the global-mean model of Stewart. The revised thermosphere is based largely on parameterizations derived from output data from the three-dimensional Mars Thermospheric Global Circulation Model (MTGCM). The new thermospheric model includes revised dependence on the 10.7 cm solar flux for the global means of exospheric temperature, temperature of the base of the thermosphere, and scale height for the thermospheric temperature variations, as well as revised dependence on orbital position for global mean height of the base of the thermosphere. Other features of the new thermospheric model are: (1) realistic variations of temperature and density with latitude and time of day, (2) more realistic wind magnitudes, based on improved estimates of horizontal pressure gradients, and (3) allowance for user-input adjustments to the model values for mean exospheric temperature and for height and temperature at the base of the thermosphere. Other new features of Mars-GRAM 3.4 include: (1) allowance for user-input values of climatic adjustment factors for temperature profiles from the surface to 75 km, and (2) a revised method for computing the sub-solar longitude position in the 'ORBIT' subroutine.
Thermosphere Extension of the Whole Atmosphere Community Climate Model
2010-12-04
tropospheric ozone and related tracers: Description and evaluation of MOZART, version 2, J. Geophys. Res., 108(D24), 4784, doi:10.1029/2002JD002853. Immel, T... troposphere to the upper thermosphere and their variability on interannual, seasonal, and daily scales. These quantities are compared with observational and...gravity waves are excited by tropospheric processes. As their amplitudes grow exponen- tially with altitude, they will cause larger variability
Performance of a TKE diffusion scheme in ECMWF IFS Single Column Model
NASA Astrophysics Data System (ADS)
Svensson, Jacob; Bazile, Eric; Sandu, Irina; Svensson, Gunilla
2015-04-01
Numerical Weather Prediction models (NWP) as well as climate models are used for decision making on all levels in society and their performance and accuracy are of great importance for both economical and safety reasons. Today's extensive use of weather apps and websites that directly uses model output even more highlights the importance of realistic output parameters. The turbulent atmospheric boundary layer (ABL) includes many physical processes which occur on a subgrid scale and need to be parameterized. As the absolute major part of the biosphere is located in the ABL, it is of great importance that these subgrid processes are parametrized so that they give realistic values of e.g. temperature and wind on the levels close to the surface. GEWEX (Global Energy and Water Exchange Project) Atmospheric Boundary Layer Study (GABLS), has the overall objective to improve the understanding and the representation of the atmospheric boundary layers in climate models. The study has pointed out that there is a need for a better understanding and representation of stable atmospheric boundary layers (SBL). Therefore four test cases have been designed to highlight the performance of and differences between a number of climate models and NWP:s in SBL. In the experiments, most global NWP and climate models have shown to be too diffusive in stable conditions and thus give too weak temperature gradients, too strong momentum mixing and too weak ageostrophic Ekman flow. The reason for this is that the models need enhanced diffusion to create enough friction for the large scale weather systems, which otherwise would be too fast and too active. In the GABLS test cases, turbulence schemes that use Turbulent Kinetic Energy (TKE) have shown to be more skilful than schemes that only use stability and gradients. TKE as a prognostic variable allows for advection both vertically and horizontally and gives a "memory" from previous time steps. Therefore, e.g. the ECMWF-GABLS workshop in 2011 recommended a move for global NWP models towards a TKE scheme. Here a comparison between a TKE diffusion scheme (based on the implementation in the ARPEGE model by Meteo France) is compared to ECMWF:s IFS operational first-order scheme and to a less diffusive version, using a single column version of ECMWF:s IFS model. Results from the test cases GABLS 1, 3 and 4 together with the Diurnal land/atmosphere coupling experiment (DICE) are presented.
Improvements of the Eastward Propagation of the MJO in MIROC6
NASA Astrophysics Data System (ADS)
Hirota, N.; Ogura, T.; Shiogama, H.; Kimoto, M.; Watanabe, M.; Tatebe, H.
2016-12-01
A new version of the atmosphere-ocean general circulation model cooperatively produced by the Japanese research community, known as the Model for Interdisciplinary Research on Climate (MIROC6), has recently been developed. Many aspects of the Madden Julian Oscillation (MJO) simulations are improved compared with its previous version MIROC5. For example, MJO amplitudes underestimated in MIROC5 are enhanced; the MJO convective envelopes over the Indian Ocean, which often decays too early around the Maritime Continent in MIROC5, propagate farther to the Central Pacific; the vertical structure of the MJO related humidity shows more realistic stepwise moistening associated with the transition from shallow convection to deep convection. Our preliminary analyses indicate that these improvements are associated with a newly implemented shallow convection scheme. The shallow convection in MIROC6 transports the boundary layer moisture to the lower free troposphere, mitigating dry biases around 800hPa over the Western Pacific. MIROC6 also shows improvements in climatological mean precipitation. The coupling strength between convection and the free tropospheric humidity, that are consider to have large impacts on the reproducibility of the MJO and the mean states, will also be discussed. Acknowledgment: This work was supported by the Program for Risk Information on Climate Change (SOUSEI program) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.
The conditional resampling model STARS: weaknesses of the modeling concept and development
NASA Astrophysics Data System (ADS)
Menz, Christoph
2016-04-01
The Statistical Analogue Resampling Scheme (STARS) is based on a modeling concept of Werner and Gerstengarbe (1997). The model uses a conditional resampling technique to create a simulation time series from daily observations. Unlike other time series generators (such as stochastic weather generators) STARS only needs a linear regression specification of a single variable as the target condition for the resampling. Since its first implementation the algorithm was further extended in order to allow for a spatially distributed trend signal, to preserve the seasonal cycle and the autocorrelation of the observation time series (Orlovsky, 2007; Orlovsky et al., 2008). This evolved version was successfully used in several climate impact studies. However a detaild evaluation of the simulations revealed two fundamental weaknesses of the utilized resampling technique. 1. The restriction of the resampling condition on a single individual variable can lead to a misinterpretation of the change signal of other variables when the model is applied to a mulvariate time series. (F. Wechsung and M. Wechsung, 2014). As one example, the short-term correlations between precipitation and temperature (cooling of the near-surface air layer after a rainfall event) can be misinterpreted as a climatic change signal in the simulation series. 2. The model restricts the linear regression specification to the annual mean time series, refusing the specification of seasonal varying trends. To overcome these fundamental weaknesses a redevelopment of the whole algorithm was done. The poster discusses the main weaknesses of the earlier model implementation and the methods applied to overcome these in the new version. Based on the new model idealized simulations were conducted to illustrate the enhancement.
Perturbations and gradients as fundamental tests for modeling the soil carbon cycle
NASA Astrophysics Data System (ADS)
Bond-Lamberty, B. P.; Bailey, V. L.; Becker, K.; Fansler, S.; Hinkle, C.; Liu, C.
2013-12-01
An important step in matching process-level knowledge to larger-scale measurements and model results is to challenge those models with site-specific perturbations and/or changing environmental conditions. Here we subject modified versions of an ecosystem process model to two stringent tests: replicating a long-term climate change dryland experiment (Rattlesnake Mountain) and partitioning the carbon fluxes of a soil drainage gradient in the northern Everglades (Disney Wilderness Preserve). For both sites, on-site measurements were supplemented by laboratory incubations of soil columns. We used a parameter-space search algorithm to optimize, within observational limits, the model's influential inputs, so that the spun-up carbon stocks and fluxes matched observed values. Modeled carbon fluxes (net primary production and net ecosystem exchange) agreed with measured values, within observational error limits, but the model's partitioning of soil fluxes (autotrophic versus heterotrophic), did not match laboratory measurements from either site. Accounting for site heterogeneity at DWP, modeled carbon exchange was reasonably consistent with values from eddy covariance. We discuss the implications of this work for ecosystem- to global scale modeling of ecosystems in a changing climate.
NASA Astrophysics Data System (ADS)
Bal, Prasanta Kumar; Ramachandran, A.; Geetha, R.; Bhaskaran, B.; Thirumurugan, P.; Indumathi, J.; Jayanthi, N.
2016-02-01
In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments.
Impacts of Climate Change on Stream Temperatures in the Clearwater River, Idaho
NASA Astrophysics Data System (ADS)
Yearsley, J. R.; Chegwidden, O.; Nijssen, B.
2016-12-01
Dworshak Dam in northern Idaho impounds the waters of the North Fork of the Clearwater River, creating a reservoir of approximately 4.278 km3 at full pool elevation. The dam's primary purpose is for flood control and hydroelectric power generation. It also provides important water quality benefits by releasing cold water into the Clearwater River during the summer when conditions become critical for migrating endangered species of salmon. Changes in the climate may have an impact on the ability of Dworshak Dam and Reservoir to provide these benefits. To investigate the potential for extreme outcomes that would limit cold water releases from Dworshak Reservoir and compromise the fishery, we implemented a system of hydrologic and water temperature models that simulate daily-averaged water temperatures in both the riverine and reservoir environments. We used the macroscale hydrologic model, VIC, to simulate land surface water and energy fluxes, the one-dimensional, time-dependent stream temperature model, RBM, to simulate river temperatures and a modified version of CEQUAL-W2 to simulate water temperatures in Dworshak Reservoir. A long-term hydrologically based gridded data set of meteorological forcing provided the input for comparing model results with available observations of flow and water temperature. For purposes of investigating the impacts of climate change, we used the results from ten of the most recent Climate Model Intercomparison Project (CMIP5) climate change models scenarios in conjunction with the estimates of anthropogenic inputs of climate change gases from two representative concentration pathways (RCP). We compared the simulated results associated with a range of outcomes at critical river locations from the climate scenarios with existing conditions assuming that the reservoir would be operated under a rule curve based on the average reservoir elevation for the period 2006-2015 rule curve and for power demands represented by that same period.
Climate Change, the Energy-water-food Nexus, and the "New" Colorado River Basin
NASA Astrophysics Data System (ADS)
Middleton, R. S.; Bennett, K. E.; Solander, K.; Hopkins, E.
2017-12-01
Climate change, extremes, and climate-driven disturbances are anticipated to have substantial impacts on regional water resources, particularly in the western and southwestern United States. These unprecedented conditions—a no-analog future—will result in challenges to adaptation, mitigation, and resilience planning for the energy-water-food nexus. We have analyzed the impact of climate change on Colorado River flows for multiple climate and disturbance scenarios: 12 global climate models and two CO2 emission scenarios (RCP 4.5 and RCP 8.5) from the Intergovernmental Panel on Climate Change's Coupled Model Intercomparison Study, version 5, and multiple climate-driven forest disturbance scenarios including temperature-drought vegetation mortality and insect infestations. Results indicate a wide range of potential streamflow projections and the potential emergence of a "new" Colorado River basin. Overall, annual streamflow tends to increase under the majority of modeled scenarios due to projected increases in precipitation across the basin, though a significant number of scenarios indicate moderate and potentially substantial reductions in water availability. However, all scenarios indicate severe changes in seasonality of flows and strong variability across headwater systems. This leads to increased fall and winter streamflow, strong reductions in spring and summer flows, and a shift towards earlier snowmelt timing. These impacts are further exacerbated in headwater systems, which are key to driving Colorado River streamflow and hence water supply for both internal and external basin needs. These results shed a new and important slant on the Colorado River basin, where an emergent streamflow pattern may result in difficulties to adjust to these new regimes, resulting in increased stress to the energy-water-food nexus.
A Semi-empirical Model of the Stratosphere in the Climate System
NASA Astrophysics Data System (ADS)
Sodergren, A. H.; Bodeker, G. E.; Kremser, S.; Meinshausen, M.; McDonald, A.
2014-12-01
Chemistry climate models (CCMs) currently used to project changes in Antarctic ozone are extremely computationally demanding. CCM projections are uncertain due to lack of knowledge of future emissions of greenhouse gases (GHGs) and ozone depleting substances (ODSs), as well as parameterizations within the CCMs that have weakly constrained tuning parameters. While projections should be based on an ensemble of simulations, this is not currently possible due to the complexity of the CCMs. An inexpensive but realistic approach to simulate changes in stratospheric ozone, and its coupling to the climate system, is needed as a complement to CCMs. A simple climate model (SCM) can be used as a fast emulator of complex atmospheric-ocean climate models. If such an SCM includes a representation of stratospheric ozone, the evolution of the global ozone layer can be simulated for a wide range of GHG and ODS emissions scenarios. MAGICC is an SCM used in previous IPCC reports. In the current version of the MAGICC SCM, stratospheric ozone changes depend only on equivalent effective stratospheric chlorine (EESC). In this work, MAGICC is extended to include an interactive stratospheric ozone layer using a semi-empirical model of ozone responses to CO2and EESC, with changes in ozone affecting the radiative forcing in the SCM. To demonstrate the ability of our new, extended SCM to generate projections of global changes in ozone, tuning parameters from 19 coupled atmosphere-ocean general circulation models (AOGCMs) and 10 carbon cycle models (to create an ensemble of 190 simulations) have been used to generate probability density functions of the dates of return of stratospheric column ozone to 1960 and 1980 levels for different latitudes.
NASA Astrophysics Data System (ADS)
Day, Jonathan J.; Tietsche, Steffen; Collins, Mat; Goessling, Helge F.; Guemas, Virginie; Guillory, Anabelle; Hurlin, William J.; Ishii, Masayoshi; Keeley, Sarah P. E.; Matei, Daniela; Msadek, Rym; Sigmond, Michael; Tatebe, Hiroaki; Hawkins, Ed
2016-06-01
Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño-Southern Oscillation.
Implications of Climate Change for Glaciated Watersheds in western Canada
NASA Astrophysics Data System (ADS)
Schnorbus, M.; Menounos, B.; Schoeneberg (Werner), A. T.; Anslow, F. S.; Jost, G.; Moore, R. D.
2017-12-01
The cryosphere is particularly vulnerable to changes in climate. For many catchments, glaciers provide water to streams, especially during summer and early autumn when seasonal snow packs have been depleted. Increased concentrations of greenhouse gasses will promote further warming in the decades ahead leading to strong mass loss and a continuation of the rapid retreat of alpine glaciers. Understanding how the contribution of glacier runoff may change in future has important implications for a variety of water resources issues ranging from the impacts of higher water temperatures and lower summer flows on aquatic habitat to the effects of seasonal changes in runoff on hydropower generation. Consequently, there is a need to increase understanding of the influence of glacier storage changes on runoff and streamflow in mountainous watersheds. We developed a modeling system that explicitly simulates ice dynamics, glacier mass balance and runoff. The modelling system employs an upgraded version of the Variable Infiltration Capacity (VIC) hydrology model (which now includes glacier mass balance) coupled to a glacier dynamics model (UBC Regional Glaciation Model) that will be used to assess potential future hydrologic changes in glaciated drainages throughout western Canada. Our presentation will focus on the application of this new model to simulate climate change effects on inflows for several hydropower reservoirs located in heavily glaciated basins in British Columbia, Canada.
NASA Astrophysics Data System (ADS)
Washington, Warren M.; Meehl, Gerald A.; Verplank, Lynda; Bettge, Thomas W.
1994-05-01
We have developed an improved version of a world ocean model with the intention of coupling to an atmospheric model. This article documents the simulation capability of this 1° global ocean model, shows improvements over our earlier 5° version, and compares it to features simulated with a 0.5° model. These experiments use a model spin-up methodology whereby the ocean model can subsequently be coupled to an atmospheric model and used for order 100-year coupled model integrations. With present-day computers, 1° is a reasonable compromise in resolution that allows for century-long coupled experiments. The 1° ocean model is derived from a 0.5°-resolution model developed by A. Semtner (Naval Postgraduate School) and R. Chervin (National Center for Atmospheric Research) for studies of the global eddy-resolving world ocean circulation. The 0.5° bottom topography and continental outlines have been altered to be compatible with the 1° resolution, and the Arctic Ocean has been added. We describe the ocean simulation characteristics of the 1° version and compare the result of weakly constraining (three-year time scale) the three-dimensional temperature and salinity fields to the observations below the thermocline (710 m) with the model forced only at the top of the ocean by observed annual mean wind stress, temperature, and salinity. The 1° simulations indicate that major ocean circulation patterns are greatly improved compared to the 5° version and are qualitatively reproduced in comparison to the 0.5° version. Using the annual mean top forcing alone in a 100-year simulation with the 1° version preserves the general features of the major observed temperature and salinity structure with most climate drift occurring mainly beneath the thermocline in the first 50 75 years. Because the thermohaline circulation in the 1° version is relatively weak with annual mean forcing, we demonstrate the importance of the seasonal cycle by performing two sensitivity experiments. Results show a dramatic intensification of the meridional overturning circulation (order of magnitude) with perpetual winter surface temperature forcing in the North Atlantic and strong intensification (factor of three) with perpetual early winter temperatures in that region. These effects are felt throughout the Atlantic (particularly an intensified and northward-shifted Gulf Stream outflow). In the Pacific, the temperature gradient strengthens in the thermocline, thus helping counter the systematic error of a thermocline that is too diffuse.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.
2013-12-01
With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less
Quantile Mapping Bias correction for daily precipitation over Vietnam in a regional climate model
NASA Astrophysics Data System (ADS)
Trinh, L. T.; Matsumoto, J.; Ngo-Duc, T.
2017-12-01
In the past decades, Regional Climate Models (RCMs) have been developed significantly, allowing climate simulation to be conducted at a higher resolution. However, RCMs often contained biases when comparing with observations. Therefore, statistical correction methods were commonly employed to reduce/minimize the model biases. In this study, outputs of the Regional Climate Model (RegCM) version 4.3 driven by the CNRM-CM5 global products were evaluated with and without the Quantile Mapping (QM) bias correction method. The model domain covered the area from 90oE to 145oE and from 15oS to 40oN with a horizontal resolution of 25km. The QM bias correction processes were implemented by using the Vietnam Gridded precipitation dataset (VnGP) and the outputs of RegCM historical run in the period 1986-1995 and then validated for the period 1996-2005. Based on the statistical quantity of spatial correlation and intensity distributions, the QM method showed a significant improvement in rainfall compared to the non-bias correction method. The improvements both in time and space were recognized in all seasons and all climatic sub-regions of Vietnam. Moreover, not only the rainfall amount but also some extreme indices such as R10m, R20mm, R50m, CDD, CWD, R95pTOT, R99pTOT were much better after the correction. The results suggested that the QM correction method should be taken into practice for the projections of the future precipitation over Vietnam.
Land-atmosphere coupling and climate prediction over the U.S. Southern Great Plains
NASA Astrophysics Data System (ADS)
Williams, I. N.; Lu, Y.; Kueppers, L. M.; Riley, W. J.; Biraud, S.; Bagley, J. E.; Torn, M. S.
2016-12-01
Biases in land-atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land-atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single-column version of the NCAR Community Earth System Model (CESM1.2.2) and an offline Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. These correlations were improved by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications reduced the root mean squared error (RMSE) in daytime 2 m air temperature from 3.6 C to 2 C in summer (JJA), and reduced RMSE in total JJA precipitation from 133 to 84 mm. The modifications had the largest effect on prediction of summer drought in 2006, when a warm bias in daytime 2 m air temperature was reduced from +6 C to a smaller cold bias of -1.3 C, and a corresponding dry bias in total JJA precipitation was reduced from -111 mm to -23 mm. Thus, the role of vegetation in droughts and heat waves is likely underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.
Zhao, M.; Golaz, J.-C.; Held, I. M.; Guo, H.; Balaji, V.; Benson, R.; Chen, J.-H.; Chen, X.; Donner, L. J.; Dunne, J. P.; Dunne, Krista A.; Durachta, J.; Fan, S.-M.; Freidenreich, S. M.; Garner, S. T.; Ginoux, P.; Harris, L. M.; Horowitz, L. W.; Krasting, J. P.; Langenhorst, A. R.; Liang, Z.; Lin, P.; Lin, S.-J.; Malyshev, S. L.; Mason, E.; Milly, Paul C.D.; Ming, Y.; Naik, V.; Paulot, F.; Paynter, D.; Phillipps, P.; Radhakrishnan, A.; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, C. J.; Shevliakova, E.; Shen, Z.; Shin, H.; Silvers, L.; Wilson, J. R.; Winton, M.; Wittenberg, A. T.; Wyman, B.; Xiang, B.
2018-01-01
In this two‐part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed sea surface temperatures (SSTs) and sea‐ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top‐of‐atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhao, Ming; Golaz, J. -C.; Held, I. M.
In this two–part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed seamore » surface temperatures (SSTs) and sea–ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. Here, the model's Cess sensitivity (response in the top–of–atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.« less
Zhao, Ming; Golaz, J. -C.; Held, I. M.; ...
2018-02-19
In this two–part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed seamore » surface temperatures (SSTs) and sea–ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. Here, the model's Cess sensitivity (response in the top–of–atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.« less
NASA Astrophysics Data System (ADS)
Zhao, M.; Golaz, J.-C.; Held, I. M.; Guo, H.; Balaji, V.; Benson, R.; Chen, J.-H.; Chen, X.; Donner, L. J.; Dunne, J. P.; Dunne, K.; Durachta, J.; Fan, S.-M.; Freidenreich, S. M.; Garner, S. T.; Ginoux, P.; Harris, L. M.; Horowitz, L. W.; Krasting, J. P.; Langenhorst, A. R.; Liang, Z.; Lin, P.; Lin, S.-J.; Malyshev, S. L.; Mason, E.; Milly, P. C. D.; Ming, Y.; Naik, V.; Paulot, F.; Paynter, D.; Phillipps, P.; Radhakrishnan, A.; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, C. J.; Shevliakova, E.; Shen, Z.; Shin, H.; Silvers, L. G.; Wilson, J. R.; Winton, M.; Wittenberg, A. T.; Wyman, B.; Xiang, B.
2018-03-01
In this two-part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a "light" chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed sea surface temperatures (SSTs) and sea-ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top-of-atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.
Preliminary development of a revised version of the School Climate Measure.
Zullig, Keith J; Collins, Rani; Ghani, Nadia; Hunter, Amy A; Patton, Jon M; Huebner, E Scott; Zhang, Jianjun
2015-09-01
The School Climate Measure (SCM) was developed and preliminarily validated in 2010 and extended upon in 2013 in response to a dearth of psychometrically sound school climate instruments. This study sought to further validate the SCM on a large diverse sample of Arizona public school adolescents (N = 1,643) with two new domains. The eight original SCM domains (Positive Student-Teacher Relationships, School Connectedness, Academic Support, Order and Discipline, Physical Environment, Social Environment, Perceived Exclusion, and Academic Satisfaction) and two newly developed domains (Parental Involvement and Opportunities for Student Engagement) were subjected to psychometric analysis. The sample was randomly split into exploratory and confirmatory halves and subjected to factor analytic and structural equation modeling techniques. Factor analysis confirmed a 10-factor solution (loadings with absolute values > .40). Item factor loadings ranged from .47 to .95. Coefficient alphas ranged from .70 to .92. Fit statistics indicated a good fitting model (χ2 = 1452.67 [df = 734, p < .01], CFI = .94, TLI = .93, RMSEA = .039). This process eliminated some original SCM items, but the overall SCM increased only from 39 to 42 items with the newly developed domains. This investigation adds to the existing evidence for the SCM and offers support for a more comprehensive version of the SCM. The addition of the Parental Involvement and Opportunities for Student Engagement domains should further enhance the usefulness of the SCM. The SCM can facilitate data-driven decisions and may be incorporated into evidenced-based processes designed to improve important student learning and well-being outcomes. (c) 2015 APA, all rights reserved.
NASA Technical Reports Server (NTRS)
Stackhouse, Paul W., Jr.; Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping
2015-01-01
Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.
Hofmann, Marco; Lux, Robert; Schultz, Hans R.
2014-01-01
Grapes for wine production are a highly climate sensitive crop and vineyard water budget is a decisive factor in quality formation. In order to conduct risk assessments for climate change effects in viticulture models are needed which can be applied to complete growing regions. We first modified an existing simplified geometric vineyard model of radiation interception and resulting water use to incorporate numerical Monte Carlo simulations and the physical aspects of radiation interactions between canopy and vineyard slope and azimuth. We then used four regional climate models to assess for possible effects on the water budget of selected vineyard sites up 2100. The model was developed to describe the partitioning of short-wave radiation between grapevine canopy and soil surface, respectively, green cover, necessary to calculate vineyard evapotranspiration. Soil water storage was allocated to two sub reservoirs. The model was adopted for steep slope vineyards based on coordinate transformation and validated against measurements of grapevine sap flow and soil water content determined down to 1.6 m depth at three different sites over 2 years. The results showed good agreement of modeled and observed soil water dynamics of vineyards with large variations in site specific soil water holding capacity (SWC) and viticultural management. Simulated sap flow was in overall good agreement with measured sap flow but site-specific responses of sap flow to potential evapotranspiration were observed. The analyses of climate change impacts on vineyard water budget demonstrated the importance of site-specific assessment due to natural variations in SWC. The improved model was capable of describing seasonal and site-specific dynamics in soil water content and could be used in an amended version to estimate changes in the water budget of entire grape growing areas due to evolving climatic changes. PMID:25540646
NASA Astrophysics Data System (ADS)
Kunwar, S.; Bowden, J.; Milly, G.; Previdi, M. J.; Fiore, A. M.; West, J. J.
2017-12-01
In the coming decades, anthropogenically induced climate change will likely impact PM2.5 through both changing meteorology and feedback in natural emissions. A major goal of our project is to assess changes in PM2.5 levels over the continental US due to climate variability and change for the period 2005-2065. We will achieve this by using regional models to dynamically downscale coarse resolution (20 × 20) meteorology and air chemistry from a global model to finer spatial resolution (12 km), improving air quality projections for regions and subregions of the US (NE, SE, SW, NW, Midwest, Intermountain West). We downscale from GFDL CM3 simulations of the RCP8.5 scenario for the years 2006-2100 with aerosol and ozone precursor emissions fixed at 2005 levels. We carefully select model years from the global simulations that sample the range of PM2.5 distributions for different US regions at mid 21st century (2050-2065). Here we will show results for the meteorological downscaling (using WRF version 3.8.1) for this project, including a performance evaluation for meteorological variables with respect to the global model. In the future, the downscaled meteorology presented here will be used to drive air quality downscaling in CMAQ (version 5.2). Analysis of the resulting PM2.5 statistics for US regions, as well as the drivers for PM2.5 changes, will be important in supporting informed policies for air quality (also health and visibility) planning for different US regions for the next five decades.
NASA Astrophysics Data System (ADS)
Lofgren, B. M.; Xiao, C.
2016-12-01
The influence of projected climate change on the water levels of the Great Lakes is subject to considerable uncertainty, and methods that have long been used to determine this sensitivity have been discredited. A strong candidate, albeit expensive, to replace problematic methods is to use outputs that result from dynamical downscaling of future climate simulations, focused on the hydroclimate of the Great Lakes basin. We have produced initial estimates of Great Lakes water levels in the mid- and late 21st century using the Weather Research and Forecasting (WRF) model, including its lake module, driven by lateral boundary conditions from the Geophysical Fluid Dynamics Lab Climate Model version 3.0 (GFDL CM3), under RCP4.5 and 8.5 scenarios. Future lake levels are influenced by the balance between projected general increases in precipitation and increases in evapotranspiration from both land and lake in the basin, driven primarily by the surface radiative energy budget and secondarily by air temperature. The net result was drops in lake level of up to 15 cm, in contrast to the results from much-used older methods, which often projected drops exceeding 1 m. Future plans include increased detail in the simulation of water flow overland and in river channels using WRF-Hydro, and full coupling of regional atmospheric systems with 3-dimensional dynamical lake implementation of the Finite Volume Community Ocean Model (FVCOM).
Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)
Sakaguchi, K.; Zeng, X.; Leung, L. R.; ...
2016-12-21
Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less
Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sakaguchi, K.; Zeng, X.; Leung, L. R.
Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less
The impact of forest structure and light utilization on carbon cycling in tropical forests
NASA Astrophysics Data System (ADS)
Morton, D. C.; Longo, M.; Leitold, V.; Keller, M. M.
2015-12-01
Light competition is a fundamental organizing principle of forest ecosystems, and interactions between forest structure and light availability provide an important constraint on forest productivity. Tropical forests maintain a dense, multi-layered canopy, based in part on abundant diffuse light reaching the forest understory. Climate-driven changes in light availability, such as more direct illumination during drought conditions, therefore alter the potential productivity of forest ecosystems during such events. Here, we used multi-temporal airborne lidar data over a range of Amazon forest conditions to explore the influence of forest structure on gross primary productivity (GPP). Our analysis combined lidar-based observations of canopy illumination and turnover in the Ecosystem Demography model (ED, version 2.2). The ED model was updated to specifically account for regional differences in canopy and understory illumination using lidar-derived measures of canopy light environments. Model simulations considered the influence of forest structure on GPP over seasonal to decadal time scales, including feedbacks from differential productivity between illuminated and shaded canopy trees on mortality rates and forest composition. Finally, we constructed simple scenarios with varying diffuse and direct illumination to evaluate the potential for novel plant-climate interactions under scenarios of climate change. Collectively, the lidar observations and model simulations underscore the need to account for spatial heterogeneity in the vertical structure of tropical forests to constrain estimates of tropical forest productivity under current and future climate conditions.
Estimating the Numerical Diapycnal Mixing in the GO5.0 Ocean Model
NASA Astrophysics Data System (ADS)
Megann, A.; Nurser, G.
2014-12-01
Constant-depth (or "z-coordinate") ocean models such as MOM4 and NEMO have become the de facto workhorse in climate applications, and have attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes, and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimations have been made of the magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is the latest ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre (Megann et al, 2014), and forms part of the GC1 and GC2 climate models. It uses version 3.4 of the NEMO model, on the ORCA025 ¼° global tripolar grid. We describe various approaches to quantifying the numerical diapycnal mixing in this model, and present results from analysis of the GO5.0 model based on the isopycnal watermass analysis of Lee et al (2002) that indicate that numerical mixing does indeed form a significant component of the watermass transformation in the ocean interior.
Reducing uncertainty in Climate Response Time Scale by Bayesian Analysis of the 8.2 ka event
NASA Astrophysics Data System (ADS)
Lorenz, A.; Held, H.; Bauer, E.; Schneider von Deimling, T.
2009-04-01
We analyze the possibility of uncertainty reduction in Climate Response Time Scale by utilizing Greenland ice-core data that contain the 8.2 ka event within a Bayesian model-data intercomparison with the Earth system model of intermediate complexity, CLIMBER-2.3. Within a stochastic version of the model it has been possible to mimic the 8.2 ka event within a plausible experimental setting and with relatively good accuracy considering the timing of the event in comparison to other modeling exercises [1]. The simulation of the centennial cold event is effectively determined by the oceanic cooling rate which depends largely on the ocean diffusivity described by diffusion coefficients of relatively wide uncertainty ranges. The idea now is to discriminate between the different values of diffusivities according to their likelihood to rightly represent the duration of the 8.2 ka event and thus to exploit the paleo data to constrain uncertainty in model parameters in analogue to [2]. Implementing this inverse Bayesian Analysis with this model the technical difficulty arises to establish the related likelihood numerically in addition to the uncertain model parameters: While mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study [3] the Bayesian Analysis showed a reduction of uncertainty in vertical ocean diffusivity parameters of factor 2 compared to prior knowledge. This learning effect on the model parameters is propagated to other model outputs of interest; e.g. the inverse ocean heat capacity, which is important for the dominant time scale of climate response to anthropogenic forcing which, in combination with climate sensitivity, strongly influences the climate systems reaction for the near- and medium-term future. 1 References [1] E. Bauer, A. Ganopolski, M. Montoya: Simulation of the cold climate event 8200 years ago by meltwater outburst from lake Agassiz. Paleoceanography 19:PA3014, (2004) [2] T. Schneider von Deimling, H. Held, A. Ganopolski, S. Rahmstorf, Climate sensitivity estimated from ensemble simulations of glacial climates, Climate Dynamics 27, 149-163, DOI 10.1007/s00382-006-0126-8 (2006). [3] A. Lorenz, Diploma Thesis, U Potsdam (2007).
The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Chonggang; Christoffersen, Bradley
The Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) is a vegetation model for use in Earth system models (ESMs). The model includes a size- and age-structured representation of tree dynamics, competition between functionally diverse plant functional types, and the biophysics underpinning plant growth, competition, mortality, as well as the carbon, water, and energy exchange with the atmosphere. The FATES model is designed as a modular vegetation model that can be integrated within a host land model for inclusion in ESMs. The model is designed for use in global change studies to understand and project the responses and feedbacks between terrestrial ecosystems andmore » the Earth system under changing climate and other forcings.« less
Climate Change Impacts on Crop Production in Nigeria
NASA Astrophysics Data System (ADS)
Mereu, V.; Gallo, A.; Carboni, G.; Spano, D.
2011-12-01
The agricultural sector in Nigeria is particularly important for the country's food security, natural resources, and growth agenda. The cultivable areas comprise more than 70% of the total area; however, the cultivated area is about the 35% of the total area. The most important components in the food basket of the nation are cereals and tubers, which include rice, maize, corn, millet, sorghum, yam, and cassava. These crops represent about 80% of the total agricultural product in Nigeria (from NPAFS). The major crops grown in the country can be divided into food crops (produced for consumption) and export products. Despite the importance of the export crops, the primary policy of agriculture is to make Nigeria self-sufficient in its food and fiber requirements. The projected impacts of future climate change on agriculture and water resources are expected to be adverse and extensive in these area. This implies the need for actions and measures to adapt to climate change impacts, and especially as they affect agriculture, the primary sector for Nigerian economy. In the framework of the Project Climate Risk Analysis in Nigeria (founded by World Bank Contract n.7157826), a study was made to assess the potential impact of climate change on the main crops that characterize Nigerian agriculture. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT are tools that simulate physiological processes of crop growth, development and production by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were calibrated to evaluate climate change impacts on crop production. The climate data used for the analysis are derived by the Regional Circulation Model COSMO-CLM, from 1971 to 2065, at 8 km of spatial resolution. The RCM model output was "perturbed" with 10 Global Climate Models to have a wide variety of possible climate projections for the impact analysis. Multiple combinations of soil and climate conditions and crop management and varieties were considered for each Agro-Ecological Zone (AEZ) of Nigeria. A sensitivity analysis was made to evaluate the model response to changes in precipitation and temperature. The climate impact assessment was made by comparing the yield obtained with the climate data for the present period and the yield obtainable under future climate conditions. The results were analyzed at state, AEZ and country levels. The analysis shows a general reduction in crop yields in particular in the dryer regions of northern Nigeria.
NASA Astrophysics Data System (ADS)
Kay, Jennifer E.; Bourdages, Line; Miller, Nathaniel B.; Morrison, Ariel; Yettella, Vineel; Chepfer, Helene; Eaton, Brian
2016-04-01
Spaceborne lidar observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite are used to evaluate cloud amount and cloud phase in the Community Atmosphere Model version 5 (CAM5), the atmospheric component of a widely used state-of-the-art global coupled climate model (Community Earth System Model). By embedding a lidar simulator within CAM5, the idiosyncrasies of spaceborne lidar cloud detection and phase assignment are replicated. As a result, this study makes scale-aware and definition-aware comparisons between model-simulated and observed cloud amount and cloud phase. In the global mean, CAM5 has insufficient liquid cloud and excessive ice cloud when compared to CALIPSO observations. Over the ice-covered Arctic Ocean, CAM5 has insufficient liquid cloud in all seasons. Having important implications for projections of future sea level rise, a liquid cloud deficit contributes to a cold bias of 2-3°C for summer daily maximum near-surface air temperatures at Summit, Greenland. Over the midlatitude storm tracks, CAM5 has excessive ice cloud and insufficient liquid cloud. Storm track cloud phase biases in CAM5 maximize over the Southern Ocean, which also has larger-than-observed seasonal variations in cloud phase. Physical parameter modifications reduce the Southern Ocean cloud phase and shortwave radiation biases in CAM5 and illustrate the power of the CALIPSO observations as an observational constraint. The results also highlight the importance of using a regime-based, as opposed to a geographic-based, model evaluation approach. More generally, the results demonstrate the importance and value of simulator-enabled comparisons of cloud phase in models used for future climate projection.
A Simplified Biosphere Model for Global Climate Studies.
NASA Astrophysics Data System (ADS)
Xue, Y.; Sellers, P. J.; Kinter, J. L.; Shukla, J.
1991-03-01
The Simple Biosphere Model (SiB) as described in Sellers et al. is a bio-physically based model of land surface-atmosphere interaction. For some general circulation model (GCM) climate studies, further simplifications are desirable to have greater computation efficiency, and more important, to consolidate the parametric representation. Three major reductions in the complexity of SiB have been achieved in the present study.The diurnal variation of surface albedo is computed in SiB by means of a comprehensive yet complex calculation. Since the diurnal cycle is quite regular for each vegetation type, this calculation can be simplified considerably. The effect of root zone soil moisture on stomatal resistance is substantial, but the computation in SiB is complicated and expensive. We have developed approximations, which simulate the effects of reduced soil moisture more simply, keeping the essence of the biophysical concepts used in SiB.The surface stress and the fluxes of heat and moisture between the top of the vegetation canopy and an atmospheric reference level have been parameterized in an off-line version of SiB based upon the studies by Businger et al. and Paulson. We have developed a linear relationship between Richardson number and aero-dynamic resistance. Finally, the second vegetation layer of the original model does not appear explicitly after simplification. Compared to the model of Sellers et al., we have reduced the number of input parameters from 44 to 21. A comparison of results using the reduced parameter biosphere with those from the original formulation in a GCM and a zero-dimensional model shows the simplified version to reproduce the original results quite closely. After simplification, the computational requirement of SiB was reduced by about 55%.
NASA Astrophysics Data System (ADS)
GABA, C. O. U.; Alamou, E.; Afouda, A.; Diekkrüger, B.
2016-12-01
Assessing water resources is still an important challenge especially in the context of climatic changes. Although numerous hydrological models exist, new approaches are still under investigation. In this context, we investigate a new modelling approach based on the Physics Principle of Least Action which was first applied to the Bétérou catchment in Benin and gave very good results. The study presents new hypotheses to go further in the model development with a view of widening its application. The improved version of the model MODHYPMA was applied to sixteen (16) subcatchments in Bénin, West Africa. Its performance was compared to two well-known lumped conceptual models, the GR4J and HBV models. The model was successfully calibrated and validated and showed a good performance in most catchments. The analysis revealed that the three models have similar performance and timing errors. But in contrary to other models, MODHYMA is subject to a less loss of performance from calibration to validation. In order to evaluate the usefulness of our model for the prediction of runoff in ungauged basins, model parameters were estimated from the physical catchments characteristics. We relied on statistical methods applied on calibrated model parameters to deduce relationships between parameters and physical catchments characteristics. These relationships were further tested and validated on gauged basins that were considered ungauged. This regionalization was also performed for GR4J model.We obtained NSE values greater than 0.7 for MODHYPMA while the NSE values for GR4J were inferior to 0.5. In the presented study, the effects of climate change on water resources in the Ouémé catchment at the outlet of Savè (about 23 500 km2) are quantified. The output of a regional climate model was used as input to the hydrological models.Computed within the GLOWA-IMPETUS project, the future climate projections (describing a rainfall reduction of up to 15%) are derived from the regional climate model REMO driven by the global ECHAM model.The results reveal a significant decrease in future water resources (of -66% to -53% for MODHYPMA and of -59% to -46% for GR4J) for the IPCC climate scenarios A1B and B1.
NASA Astrophysics Data System (ADS)
Traore, Abdoul Khadre; Ciais, Philippe; Vuichard, Nicolas; Poulter, Benjamin; Viovy, Nicolas; Guimberteau, Matthieu; Jung, Martin; Myneni, Ranga; Fisher, Joshua B.
2014-08-01
Few studies have evaluated land surface models for African ecosystems. Here we evaluate the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based model for the interannual variability (IAV) of the fraction of absorbed active radiation, the gross primary productivity (GPP), soil moisture, and evapotranspiration (ET). Two ORCHIDEE versions are tested, which differ by their soil hydrology parameterization, one with a two-layer simple bucket and the other a more complex 11-layer soil-water diffusion. In addition, we evaluate the sensitivity of climate forcing data, atmospheric CO2, and soil depth. Beside a very generic vegetation parameterization, ORCHIDEE simulates rather well the IAV of GPP and ET (0.5 < r < 0.9 interannual correlation) over Africa except in forestlands. The ORCHIDEE 11-layer version outperforms the two-layer version for simulating IAV of soil moisture, whereas both versions have similar performance of GPP and ET. Effects of CO2 trends, and of variable soil depth on the IAV of GPP, ET, and soil moisture are small, although these drivers influence the trends of these variables. The meteorological forcing data appear to be quite important for faithfully reproducing the IAV of simulated variables, suggesting that in regions with sparse weather station data, the model uncertainty is strongly related to uncertain meteorological forcing. Simulated variables are positively and strongly correlated with precipitation but negatively and weakly correlated with temperature and solar radiation. Model-derived and observation-based sensitivities are in agreement for the driving role of precipitation. However, the modeled GPP is too sensitive to precipitation, suggesting that processes such as increased water use efficiency during drought need to be incorporated in ORCHIDEE.
Scanza, R. A.; Mahowald, N.; Ghan, S.; ...
2014-07-02
The mineralogy of desert dust is important due to its effect on radiation, clouds and biogeochemical cycling of trace nutrients. This study presents the simulation of dust radiative forcing as a function of both mineral composition and size at the global scale using mineral soil maps for estimating emissions. Externally mixed mineral aerosols in the bulk aerosol module in the Community Atmosphere Model version 4 (CAM4) and internally mixed mineral aerosols in the modal aerosol module in the Community Atmosphere Model version 5.1 (CAM5) embedded in the Community Earth System Model version 1.0.5 (CESM) are speciated into common mineral componentsmore » in place of total dust. The simulations with mineralogy are compared to available observations of mineral atmospheric distribution and deposition along with observations of clear-sky radiative forcing efficiency. Based on these simulations, we estimate the all-sky direct radiative forcing at the top of the atmosphere as +0.05 W m −2 for both CAM4 and CAM5 simulations with mineralogy and compare this both with simulations of dust in release versions of CAM4 and CAM5 (+0.08 and +0.17 W m −2) and of dust with optimized optical properties, wet scavenging and particle size distribution in CAM4 and CAM5, −0.05 and −0.17 W m −2, respectively. The ability to correctly include the mineralogy of dust in climate models is hindered by its spatial and temporal variability as well as insufficient global in-situ observations, incomplete and uncertain source mineralogies and the uncertainties associated with data retrieved from remote sensing methods.« less
Scanza, Rachel; Mahowald, N.; Ghan, Steven J.; ...
2015-01-01
The mineralogy of desert dust is important due to its effect on radiation, clouds and biogeochemical cycling of trace nutrients. This study presents the simulation of dust radiative forcing as a function of both mineral composition and size at the global scale, using mineral soil maps for estimating emissions. Externally mixed mineral aerosols in the bulk aerosol module in the Community Atmosphere Model version 4 (CAM4) and internally mixed mineral aerosols in the modal aerosol module in the Community Atmosphere Model version 5.1 (CAM5) embedded in the Community Earth System Model version 1.0.5 (CESM) are speciated into common mineral componentsmore » in place of total dust. The simulations with mineralogy are compared to available observations of mineral atmospheric distribution and deposition along with observations of clear-sky radiative forcing efficiency. Based on these simulations, we estimate the all-sky direct radiative forcing at the top of the atmosphere as + 0.05 Wm⁻² for both CAM4 and CAM5 simulations with mineralogy. We compare this to the radiative forcing from simulations of dust in release versions of CAM4 and CAM5 (+0.08 and +0.17 Wm⁻²) and of dust with optimized optical properties, wet scavenging and particle size distribution in CAM4 and CAM5, -0.05 and -0.17 Wm⁻², respectively. The ability to correctly include the mineralogy of dust in climate models is hindered by its spatial and temporal variability as well as insufficient global in situ observations, incomplete and uncertain source mineralogies and the uncertainties associated with data retrieved from remote sensing methods.« less
Westerly wind bursts simulated in CAM4 and CCSM4
NASA Astrophysics Data System (ADS)
Lian, Tao; Tang, Youmin; Zhou, Lei; Islam, Siraj Ul; Zhang, Chan; Li, Xiaojing; Ling, Zheng
2018-02-01
The equatorial westerly wind bursts (WWBs) play an important role in modulating and predicting the El Niño-Southern Oscillation (ENSO). In this study, the ability of the Community Atmospheric Model version 4 (CAM4) and the Community Climate System Model version 4 (CCSM4) in simulating WWBs is systematically evaluated. Many characteristics of WWBs, including their longitude distributions, durations, zonal extensions, variabilities at seasonal, intraseasonal, and interannual timescales, as well as their relations with the Madden-Julian Oscillation (MJO) and ENSO, are discussed. Generally speaking, these characteristics of WWBs can be successfully reproduced by CAM4, owning to the improvement of the deep convection in the model. In CCSM4, significant bias such as the lack of the equatorial Pacific WWBs in boreal spring season and the weak modulation by a strong MJO are found. Our findings confirm the fact that the WWBs are greatly modulated by the surface temperature. It's also suggested that improving the air-sea coupling in CCSM4 may improve model performance in simulating WWBs, and may further improve the predictability of ENSO in the coupled model.
NASA Astrophysics Data System (ADS)
Brault, Marc-Olivier; Matthews, Damon; Mysak, Lawrence
2016-04-01
The chemical erosion of carbonate and silicate rocks is a key process in the global carbon cycle and, through its coupling with calcium carbonate deposition in the ocean, is the primary sink of carbon on geologic timescales. The dynamic interdependence of terrestrial weathering rates with atmospheric temperature and carbon dioxide concentrations is crucial to the regulation of Earth's climate over multi-millennial timescales. However any attempts to develop a modeling context for terrestrial weathering as part of a dynamic climate system are limited, mostly because of the difficulty in adapting the multi-millennial timescales of the implied negative feedback mechanism with those of the atmosphere and ocean. Much of the earlier work on this topic is therefore based on box-model approaches, abandoning spatial variability for the sake of computational efficiency and the possibility to investigate the impact of weathering on climate change over time frames much longer than those allowed by traditional climate system models. As a result we still have but a rudimentary understanding of the chemical weathering feedback mechanism and its effects on ocean biogeochemistry and atmospheric CO2. Here, we introduce a spatially-explicit, rock weathering model into the University of Victoria Earth System Climate Model (UVic ESCM). We use a land map which takes into account a number of different rock lithologies, changes in sea level, as well as an empirical model of the temperature and NPP dependency of weathering rates for the different rock types. We apply this new model to the last deglacial period (c. 21000BP to 13000BP) as well as a future climate change scenario (c. 1800AD to 6000AD+), comparing the results of our 2-D version of the weathering feedback mechanism to simulations using only the box-model parameterizations of Meissner et al. [2012]. These simulations reveal the importance of two-dimensional factors (i.e., changes in sea level and rock type distribution) in the role of the weathering negative feedback mechanism on multi-millennial timescales.
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.
Fire in the Earth System: Bridging data and modeling research
Hantson, Srijn; Kloster, Silvia; Coughlan, Michael; Daniau, Anne-Laure; Vanniere, Boris; Bruecher, Tim; Kehrwald, Natalie; Magi, Brian I.
2016-01-01
Significant changes in wildfire occurrence, extent, and severity in areas such as western North America and Indonesia in 2015 have made the issue of fire increasingly salient in both the public and scientific spheres. Biomass combustion rapidly transforms land cover, smoke pours into the atmosphere, radiative heat from fires initiates dramatic pyrocumulus clouds, and the repeated ecological and atmospheric effects of fire can even impact regional and global climate. Furthermore, fires have a significant impact on human health, livelihoods, and social and economic systems.Modeling and databased methods to understand fire have rapidly coevolved over the past decade. Satellite and ground-based data about present-day fire are widely available for applications in research and fire management. Fire modeling has developed in part because of the evolution in vegetation and Earth system modeling efforts, but parameterizations and validation are largely focused on the present day because of the availability of satellite data. Charcoal deposits in sediment cores have emerged as a powerful method to evaluate trends in biomass burning extending back to the Last Glacial Maximum and beyond, and these records provide a context for present-day fire. The Global Charcoal Database version 3 compiled about 700 charcoal records and more than 1,000 records are expected for the future version 4. Together, these advances offer a pathway to explore how the strengths of fire data and fire modeling could address the weaknesses in the overall understanding of human-climate–fire linkages.A community of researchers studying fire in the Earth system with individual expertise that included paleoecology, paleoclimatology, modern ecology, archaeology, climate, and Earth system modeling, statistics, geography, biogeochemistry, and atmospheric science met at an intensive workshop in Massachusetts to explore new research directions and initiate new collaborations. Research themes, which emerged from the workshop participants via preworkshop surveys, focused on addressing the following questions: What are the climatic, ecological, and human drivers of fire regimes, both past and future? What is the role of humans in shaping historical fire regimes? How does fire ecology affect land cover changes, biodiversity, carbon storage, and human land uses? What are the historical fire trends and their impacts across biomes? Are their impacts local and/or regional? Are the fire trends in the last two decades unprecedented from a historical perspective? The workshop1 aimed to develop testable hypotheses about fire, climate, vegetation, and human interactions by leveraging the confluence of proxy, observational, and model data related to decadal- to millennial-scale fire activity on our planet. New research directions focused on broad interdisciplinary approaches to highlight how knowledge about past fire activity could provide a more complete understanding of the predictive capacity of fire models and inform fire policy in the face of our changing climate.
Meeting the Next Generation Science Standards Through "Rediscovered" Climate Model Experiments
NASA Astrophysics Data System (ADS)
Sohl, L. E.; Chandler, M. A.; Zhou, J.
2013-12-01
Since the Educational Global Climate Model (EdGCM) Project made its debut in January 2005, over 150 institutions have employed EdGCM software for a variety of uses ranging from short lab exercises to semester-long and year-long thesis projects. The vast majority of these EdGCM adoptees have been at the undergraduate and graduate levels, with few users at the K-12 level. The K-12 instructors who have worked with EdGCM in professional development settings have commented that, although EdGCM can be used to illustrate a number of the Disciplinary Core Ideas and connects to many of the Common Core State Standards across subjects and grade levels, significant hurdles preclude easy integration of EdGCM into their curricula. Time constraints, a scarcity of curriculum materials, and classroom technology are often mentioned as obstacles in providing experiences to younger grade levels in realistic climate modeling research. Given that the NGSS incorporates student performance expectations relating to Earth System Science, and to climate science and the human dimension in particular, we feel that a streamlined version of EdGCM -- one that eliminates the need to run the climate model on limited computing resources, and provides a more guided climate modeling experience -- would be highly beneficial for the K-12 community. This new tool currently under development, called EzGCM, functions through a browser interface, and presents "rediscovery experiments" that allow students to do their own exploration of model output from published climate experiments, or from sensitivity experiments designed to illustrate how climate models as well as the climate system work. The experiments include background information and sample questions, with more extensive notes for instructors so that the instructors can design their own reflection questions or follow-on activities relating to physical or human impacts, as they choose. An added benefit of the EzGCM tool is that, like EdGCM, it helps illustrate the process of doing research on a complex topic, in a way that builds upon earlier experiences in inquiry-based learning. By having students work through a multi-stage process that requires them to plan several steps ahead, through data processing, analysis and interpretation, they learn how to do research in addition to improving their understanding of climate change.
NASA Astrophysics Data System (ADS)
Sakaguchi, Koichi; Zeng, Xubin; Christoffersen, Bradley J.; Restrepo-Coupe, Natalia; Saleska, Scott R.; Brando, Paulo M.
2011-03-01
Recent development of general circulation models involves biogeochemical cycles: flows of carbon and other chemical species that circulate through the Earth system. Such models are valuable tools for future projections of climate, but still bear large uncertainties in the model simulations. One of the regions with especially high uncertainty is the Amazon forest where large-scale dieback associated with the changing climate is predicted by several models. In order to better understand the capability and weakness of global-scale land-biogeochemical models in simulating a tropical ecosystem under the present day as well as significantly drier climates, we analyzed the off-line simulations for an east central Amazon forest by the Community Land Model version 3.5 of the National Center for Atmospheric Research and its three independent biogeochemical submodels (CASA', CN, and DGVM). Intense field measurements carried out under Large Scale Biosphere-Atmosphere Experiment in Amazonia, including forest response to drought from a throughfall exclusion experiment, are utilized to evaluate the whole spectrum of biogeophysical and biogeochemical aspects of the models. Our analysis shows reasonable correspondence in momentum and energy turbulent fluxes, but it highlights three processes that are not in agreement with observations: (1) inconsistent seasonality in carbon fluxes, (2) biased biomass size and allocation, and (3) overestimation of vegetation stress to short-term drought but underestimation of biomass loss from long-term drought. Without resolving these issues the modeled feedbacks from the biosphere in future climate projections would be questionable. We suggest possible directions for model improvements and also emphasize the necessity of more studies using a variety of in situ data for both driving and evaluating land-biogeochemical models.
Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)
NASA Astrophysics Data System (ADS)
Akperov, Mirseid; Rinke, Annette; Mokhov, Igor I.; Matthes, Heidrun; Semenov, Vladimir A.; Adakudlu, Muralidhar; Cassano, John; Christensen, Jens H.; Dembitskaya, Mariya A.; Dethloff, Klaus; Fettweis, Xavier; Glisan, Justin; Gutjahr, Oliver; Heinemann, Günther; Koenigk, Torben; Koldunov, Nikolay V.; Laprise, René; Mottram, Ruth; Nikiéma, Oumarou; Scinocca, John F.; Sein, Dmitry; Sobolowski, Stefan; Winger, Katja; Zhang, Wenxin
2018-03-01
The ability of state-of-the-art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic-CORDEX initiative. Some models employ large-scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA-Interim, National Centers for Environmental Prediction-Climate Forecast System Reanalysis, National Aeronautics and Space Administration-Modern-Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency-Japanese 55-year reanalysis) in winter and summer for 1981-2010 period. In addition, we compare cyclone statistics between ERA-Interim and the Arctic System Reanalysis reanalyses for 2000-2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large-scale spectral nudging show a better agreement with ERA-Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.
Towards Systematic Benchmarking of Climate Model Performance
NASA Astrophysics Data System (ADS)
Gleckler, P. J.
2014-12-01
The process by which climate models are evaluated has evolved substantially over the past decade, with the Coupled Model Intercomparison Project (CMIP) serving as a centralizing activity for coordinating model experimentation and enabling research. Scientists with a broad spectrum of expertise have contributed to the CMIP model evaluation process, resulting in many hundreds of publications that have served as a key resource for the IPCC process. For several reasons, efforts are now underway to further systematize some aspects of the model evaluation process. First, some model evaluation can now be considered routine and should not require "re-inventing the wheel" or a journal publication simply to update results with newer models. Second, the benefit of CMIP research to model development has not been optimal because the publication of results generally takes several years and is usually not reproducible for benchmarking newer model versions. And third, there are now hundreds of model versions and many thousands of simulations, but there is no community-based mechanism for routinely monitoring model performance changes. An important change in the design of CMIP6 can help address these limitations. CMIP6 will include a small set standardized experiments as an ongoing exercise (CMIP "DECK": ongoing Diagnostic, Evaluation and Characterization of Klima), so that modeling groups can submit them at any time and not be overly constrained by deadlines. In this presentation, efforts to establish routine benchmarking of existing and future CMIP simulations will be described. To date, some benchmarking tools have been made available to all CMIP modeling groups to enable them to readily compare with CMIP5 simulations during the model development process. A natural extension of this effort is to make results from all CMIP simulations widely available, including the results from newer models as soon as the simulations become available for research. Making the results from routine performance tests readily accessible will help advance a more transparent model evaluation process.
NASA Astrophysics Data System (ADS)
Cronin, T.; Tziperman, E.; Li, H.
2015-12-01
High latitude continents have warmed much more rapidly in recent decades than the rest of the globe, especially in winter, and the maintenance of warm, frost-free conditions in continental interiors in winter has been a long-standing problem of past equable climates. It has also been found that the high-latitude lapse rate feedback plays an important role in Arctic amplification of climate change in climate model simulations, but we have little understanding of why lapse rates at high latitudes change so strongly with warming. To better understand these problems, we study Arctic air formation - the process by which a high-latitude maritime air mass is advected over a continent during polar night, cooled at the surface by radiation, and transformed into a much colder continental polar air mass - and its sensitivity to climate warming. We use a single-column version of the WRF model to conduct two-week simulations of the cooling process across a wide range of initial temperature profiles and microphysics schemes, and find that a low cloud feedback suppresses Arctic air formation in warmer climates. This cloud feedback consists of an increase in low cloud amount with warming, which shields the surface from radiative cooling, and increases the continental surface air temperature by roughly two degrees for each degree increase of the initial maritime surface air temperature. The time it takes for the surface air temperature to drop below freezing increases nonlinearly to ~10 days for initial maritime surface air temperatures of 20 oC. Given that this is about the time it takes an air mass starting over the Pacific to traverse the north American continent, this suggests that optically thick stratus cloud decks could help to maintain frost-free winter continental interiors in equable climates. We find that CMIP5 climate model runs show large increases in cloud water path and surface cloud longwave forcing in warmer climates, consistent with the proposed low-cloud feedback. The suppression of Arctic air formation with warming may act as a significant amplifier of climate change at high latitudes, and offers a mechanistic perspective on the high-latitude "lapse rate feedback" diagnosed in climate models.