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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

The Separate Physics and Dynamics Experiment (SPADE) framework for determining resolution awareness: A case study of microphysics

The ability to use multi-resolution dynamical cores for weather and climate modeling is pushing the atmospheric community towards developing scale aware or, more specifically, resolution aware parameterizations that will function properly across a range of grid spacings. Determining the resolution dependence of specific model parameterizations is difficult due to strong resolution dependencies in many pieces of the model. This study presents the Separate Physics and Dynamics Experiment (SPADE) framework that can be used to isolate the resolution dependent behavior of specific parameterizations without conflating resolution dependencies from other portions of the model. To demonstrate the SPADE framework, the resolution dependence of the Morrison microphysics from the Weather Research and Forecasting model and the Morrison-Gettelman microphysics from the Community Atmosphere Model are compared for grid spacings spanning the cloud modeling gray zone. It is shown that the Morrison scheme has stronger resolution dependence than Morrison-Gettelman, and that the ability of Morrison-Gettelman to use partial cloud fractions is not the primary reason for this difference. This study also discusses how to frame the issue of resolution dependence, the meaning of which has often been assumed, but not clearly expressed in the atmospheric modeling community. It is proposed that parameterization resolution dependence can be expressed in terms of "resolution dependence of the first type," RA1, which implies that the parameterization behavior converges towards observations with increasing resolution, or as "resolution dependence of the second type," RA2, which requires that the parameterization reproduces the same behavior across a range of grid spacings when compared at a given coarser resolution. RA2 behavior is considered the ideal, but brings with it serious implications due to limitations of parameterizations to accurately estimate reality with coarse grid spacing. The type of resolution awareness developers should target in their development depends upon the particular modeler’s application.

Gustafson, William I.↗
DOE OSTI2022

Subseasonal Earth System Prediction with CESM2

Abstract Prediction systems to enable Earth system predictability research on the subseasonal time scale have been developed with the Community Earth System Model, version 2 (CESM2) using two configurations that differ in their atmospheric components. One system uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ∼140 km, and it includes fully interactive tropospheric and stratospheric chemistry [CESM2(WACCM6)]. Both systems are utilized to carry out subseasonal reforecasts for the 1999–2020 period following the Subseasonal Experiment’s (SubX) protocol. Subseasonal prediction skill from both systems is compared to those of the National Oceanic and Atmospheric Administration CFSv2 and European Centre for Medium-Range Weather Forecasts (ECMWF) operational models. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-m temperature, precipitation, the Madden–Julian oscillation, and North Atlantic Oscillation to its previous version and to the NOAA CFSv2 model. Overall, skill of CESM2(CAM6) and CESM2(WACCM6) is a little lower than that of the ECMWF system. In addition to typical output provided by subseasonal prediction systems, CESM2 reforecasts provide comprehensive datasets for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region from CESM2(WACCM6). It is shown that sudden stratosphere warming events, and the associated variability in the MLT, can be predicted ∼10 days in advance. Weekly real-time forecasts and reforecasts with CESM2(CAM6) and CESM2(WACCM6) are freely available. Significance Statement We describe here the design and prediction skill of two subseasonal prediction systems based on two configurations of the Community Earth System Model, version 2 (CESM2): CESM2 with the Community Atmosphere Model, version 6 [CESM2(CAM6)] and CESM 2 with Whole Atmosphere Community Climate Model, version 6 [CESM2(WACCM6)] as its atmospheric component. These two systems provide a foundation for community-model based subseasonal prediction research. The CESM2(WACCM6) system provides a novel capability to explore the predictability of the stratosphere, mesosphere, and lower thermosphere. Both CESM2(CAM6) and CESM2(WACCM6) demonstrate subseasonal surface prediction skill comparable to that of the NOAA CFSv2 model, and a little lower than that of the ECMWF forecasting system. CESM2 reforecasts provide a comprehensive dataset for predictability research of multiple aspects of the Earth system, including the whole atmosphere up to 140 km, land, and sea ice. Weekly real-time forecasts, reforecasts, and models are publicly available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

The Impact of Emission and Climate Change on Ozone in the United States under Representative Concentration Pathways (RCPs)

Dynamical downscaling was applied in this study to link the global climate-chemistry model Community Atmosphere Model (CAM-Chem) with the regional models: Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality (CMAQ). Two Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) were used to evaluate the climate impact on ozone concentrations in 2050s. Ozone concentrations in the lower-mid troposphere (surface to ~300 hPa), from mid- to high latitudes in the Northern Hemisphere (NH), show decreasing trends in RCP 4.5 between 2000s and 2050s, with the largest decrease of 4-10 ppbv occurring in the summer and the fall; and increasing trends (2-12 ppbv) in RCP 8.5 resulting from the increased methane emissions. In RCP 8.5, methane emissions increase by ~60% by the end of 2050s, accounting for more than 90% of ozone increases in summer and fall, and 60-80% in spring and winter. Under the RCP 4.5 scenario, in the summer when photochemical reactions are the most active, the large ozone precursor emissions reduction leads to the greatest decrease of downscaled surface ozone concentrations, ranging from 6 to 10 ppbv. However, a few major cities show ozone increases of 3 to 7 ppbv due to weakened NO titration. Under the RCP 8.5 scenario, in winter, downscaled ozone concentrations increase across nearly the entire continental US in winter, ranging from 3 to 10 ppbv due to increased methane emissions and enhanced stratosphere-troposphere exchange (STE). More intense heat waves are projected to occur by the end of 2050s in RCP 8.5, leading to more than 8 ppbv of the maximum daily 8-hour daily average (MDA8) ozone during the heat wave days than other days; this indicates the dramatic impact heat waves exert on high frequency ozone events.

climate↗
DOE OSTI2017

Model simulations of aerosol effects on clouds and precipitation in comparison with ARM data

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 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 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.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Why do general circulation models overestimate the aerosol cloud lifetime effect? A case study comparing CAM5 and a CRM

Abstract. 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.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Evaluating Model Performance of an Ensemble-based Chemical Data Assimilation System During INTEX-B Field Mission

We present a global chemical data assimilation system using a global atmosphere model, the Community Atmosphere Model (CAM3) with simplified chemistry and the Data Assimilation Research Testbed (DART) assimilation package. DART is a community software facility for assimilation studies using the ensemble Kalman filter approach. Here, we apply the assimilation system to constrain global tropospheric carbon monoxide (CO) by assimilating meteorological observations of temperature and horizontal wind velocity and satellite CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument. We verify the system performance using independent CO observations taken on board the NSFINCAR C-130 and NASA DC-8 aircrafts during the April 2006 part of the Intercontinental Chemical Transport Experiment (INTEX-B). Our evaluations show that MOPITT data assimilation provides significant improvements in terms of capturing the observed CO variability relative to no MOPITT assimilation (i.e. the correlation improves from 0.62 to 0.71, significant at 99% confidence). The assimilation provides evidence of median CO loading of about 150 ppbv at 700 hPa over the NE Pacific during April 2006. This is marginally higher than the modeled CO with no MOPITT assimilation (-140 ppbv). Our ensemble-based estimates of model uncertainty also show model overprediction over the source region (i.e. China) and underprediction over the NE Pacific, suggesting model errors that cannot be readily explained by emissions alone. These results have important implications for improving regional chemical forecasts and for inverse modeling of CO sources and further demonstrate the utility of the assimilation system in comparing non-coincident measurements, e.g. comparing satellite retrievals of CO with in-situ aircraft measurements. The work described above also brought to light several short-comings of the data assimilation approach for CO profiles. Because of the limited vertical resolution of the measurement, the retrievals at different altitudes are correlated which can lead to problems with numerical error and overall efficiency. This has resulted in a manuscript that is about to be submitted to JGR:

Arellano, A. F., Jr.↗
DOE OSTI2019

Capability of CAM5.1 in simulating maximum air temperature patterns over West Africa during boreal spring

This study classifies maximum air temperature patterns over West Africa into six groups and evaluates the capability of a global climate model (Community Atmospheric Model version 5.1; CAM) to simulate them. We analyzed 45-year (1961–2005) multi-ensemble (50 members) simulations from CAM and compared the results with those of the Climate Research Unit (CRU) and the twentieth Century Reanalysis data sets. Using Self Organizing Map algorithm to classify the spatial patterns of maximum air temperature during boreal spring, the study reveals the temperature patterns that CAM can simulate well and those the model struggles to reproduce. The results show that the best agreements between the composites of observation and CAM occur in the first temperature pattern group (which features positive temperatures anomalies over the Sahel) and Node 2 (which features near-normal temperature) pattern of the third group. CAM succeeded in reproducing some of the associated regional atmospheric dynamics and thermodynamic features in winds (horizontal and vertical), temperature fields, the cloud fractions, and the mean sea-level pressure. Although CAM struggles to capture the relationship between air temperature patterns and tele-connection indices during the boreal spring season over West Africa, it agrees with observations that temperature patterns over the sub-region cannot be associated with a single climate index. An ensemble member (SIM48) captures the inter-annual variation of the observed temperaure patterns with high sycronization (η > 44%), much better than that of ensembles mean (η < 30%). SIM48 also captures adequately four of the spatial patterns in comparison to three captured by the ensembles mean. This indicates that, for better seasonal forecasts and more reliable future climate projections, the practice whereby an ensemble mean is based on uniformly averaging the members rather than the performance of individual ensemble members needs to be reviewed. Finally, the results of the study may be used to improve the perfomance of CAM over West Africa, thereby strengthening the on-going efforts to include CAM as part of multi-model forecasting system over West Africa.

Lawal, Kamoru A. (ORCID:0000000281988844)↗
DOE OSTI2022

Megadrought: A Series of Unfortunate La Niña Events?

Megadroughts are multidecadal periods of aridity more persistent than most droughts during the instrumental period. Paleoclimate evidence suggests that megadroughts occur in many parts of the world, including North America, Central America, western Europe, eastern Asia, and northern Africa. It remains unclear to what extent such megadroughts require external forcing or whether they can arise from internal climate variability alone. A novel statistical–dynamical approach is used to evaluate the possibility that such events arise solely as a function of interannual tropical sea surface temperature (SST) variations. A statistical emulator of tropical SST variations is constructed by using an empirical moving-blocks bootstrap approach that randomly samples multiyear sequences of the observational SST record. This approach preserves the power spectrum, seasonal cycle, and spatial pattern of El Niño-Southern Oscillation (ENSO) but removes longer timescale fluctuations embedded in the observational record. These resampled SST anomalies are then used to force an atmospheric model (the Community Atmosphere Model Version 5). As megadroughts emerge in this run, they should, therefore, be solely a consequence of La Niña sequences combined with internal atmospheric variability and persistence driven by soil moisture storage and other land-surface processes. We indeed find that megadroughts in this simulation have an amplitude-duration rate that is generally indistinguishable from the rate documented in paleoclimate records of the western United States. Our findings support the idea that megadroughts may occur randomly when the unforced climate system evolves freely over a sufficiently long period of time, implying that an unforced unusual but statistically plausible series of La Niña events may be sufficient to generate megadrought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

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

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

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Investigation of short-term effective radiative forcing of fire aerosols over North America using nudged hindcast ensembles

Aerosols from fire emissions can potentially have large impact on clouds and radiation. However, fire aerosol sources are often intermittent, and their effect on weather and climate is difficult to quantify. Here we investigated the short-term effective radiative forcing of fire aerosols using the global aerosol–climate model Community Atmosphere Model version 5 (CAM5). Different from previous studies, we used nudged hindcast ensembles to quantify the forcing uncertainty due to the chaotic response to small perturbations in the atmosphere state. Daily mean emissions from three fire inventories were used to consider the uncertainty in emission strength and injection heights. The simulated aerosol optical depth (AOD) and mass concentrations were evaluated against in situ measurements and reanalysis data. Overall, the results show the model has reasonably good predicting skills. Short (10-day) nudged ensemble simulations were then performed with and without fire emissions to estimate the effective radiative forcing. Results show fire aerosols have large effects on both liquid and ice clouds over the two selected regions in April 2009. Ensemble mean results show strong negative shortwave cloud radiative effect (SCRE) over almost the entirety of southern Mexico, with a 10-day regional mean value of −3.0 W m −2 . Over the central US, the SCRE is positive in the north but negative in the south, and the regional mean SCRE is small (−0.56 W m −2 ). For the 10-day average, we found a large ensemble spread of regional mean shortwave cloud radiative effect over southern Mexico (15.6 % of the corresponding ensemble mean) and the central US (64.3 %), despite the regional mean AOD time series being almost indistinguishable during the 10-day period. Moreover, the ensemble spread is much larger when using daily averages instead of 10-day averages. This demonstrates the importance of using a large ensemble of simulations to estimate the short-term aerosol effective radiative forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Source attribution of Arctic black carbon and sulfate aerosols and associated Arctic surface warming during 1980–2018

Observations show that the concentrations of Arctic sulfate and black carbon (BC) aerosols have declined since the early 1980s. Previous studies have reported that reducing sulfate aerosols potentially contributed to the recent rapid Arctic warming. In this study, a global aerosol–climate model (Community Atmosphere Model, version 5) equipped with Explicit Aerosol Source Tagging (CAM5-EAST) is applied to quantify the source apportionment of aerosols in the Arctic from 16 source regions and the role of aerosol variations in affecting changes in the Arctic surface temperature from 1980 to 2018. The CAM5-EAST simulated surface concentrations of sulfate and BC in the Arctic had a decrease of 43% and 23%, respectively, in 2014–2018 relative to 1980–1984 mainly due to the reduction of emissions from Europe, Russia and local Arctic sources. Increases in emissions from South and East Asia led to positive trends in Arctic sulfate and BC in the upper troposphere. All aerosol radiative impacts are considered including aerosol–radiation and aerosol–cloud interactions, as well as black carbon deposition on snow- and ice-covered surfaces. Within the Arctic, sulfate reductions caused a top-of-atmosphere (TOA) warming of 0.11 and 0.25 W m -2 through aerosol–radiation and aerosol–cloud interactions, respectively. While the changes in Arctic atmospheric BC has little impact on local radiative forcing, the decrease in BC in snow and ice led to a net cooling of 0.05 W m -2 . By applying climate sensitivity factors for different latitudinal bands, global changes in sulfate and BC during 2014–2018 (with respect to 1980–1984) exerted a +0.088 and 0.057 K Arctic surface warming, respectively, through aerosol–radiation interactions. Through aerosol–cloud interactions, the sulfate reduction caused an Arctic warming of +0.193 K between the two time periods. The weakened BC effect on snow–ice albedo led to an Arctic surface cooling of -0.041 K. The changes in atmospheric sulfate and BC outside the Arctic produced a total Arctic warming of +0.25 K, the majority of which is due to the midlatitude changes in radiative forcing. Our results suggest that changes in aerosols over the midlatitudes of the Northern Hemisphere have a larger impact on Arctic temperature than other regions through enhanced poleward heat transport. The combined total effects of sulfate and BC produced an Arctic surface warming of +0.297 K, explaining approximately 20% of the observed Arctic warming since the early 1980s.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

CAM5 physics suite↗
DOE OSTI2015

Collaborative Project. A Flexible Atmospheric Modeling Framework for the Community Earth System Model (CESM)

In this project we have been upgrading the Multiscale Modeling Framework (MMF) in the Community Atmosphere Model (CAM), also known as Super-Parameterized CAM (SP-CAM). This has included a major effort to update the coding standards and interface with CAM so that it can be placed on the main development trunk. It has also included development of a new software structure for CAM to be able to handle sub-grid column information. These efforts have formed the major thrust of the work.

54 ENVIRONMENTAL SCIENCES↗