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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Modeling Climate Change Impacts on an Arctic Polygonal Tundra: 2. Changes in CO 2 and CH 4 Exchange Depend on Rates of Permafrost Thaw as Affected by Changes in Vegetation and Drainage

Model projections of future CO 2 and CH 4 exchange in Arctic tundra diverge widely. Here we used ecosys to examine how climate change will affect CO 2 and CH 4 exchange in troughs, rims, and centers of a coastal polygonal tundra landscape at Barrow, AK. The model was shown to simulate diurnal and seasonal variation in CO 2 and CH 4 fluxes associated with those in air and soil temperatures ( T a and T s ) and soil water contents (θ) under current climate in 2014 and 2015. During RCP 8.5 climate change from 2015 to 2085, rising T a , atmospheric CO 2 concentrations ( C a ), and precipitation ( P ) increased net primary productivity (NPP) from 50–150 g C m -2 y -1 , consistent with current biometric estimates, to 200–250 g C m -2 y -1 . Concurrent increases in heterotrophic respiration ( R h ) were slightly smaller, so that net CO 2 exchange rose from values of -25 (net emission) to +50 (net uptake) g C m -2 y -1 to ones of -10 to +65 g C m -2 y -1 . Increases in net CO 2 uptake were largely offset by increases in CH 4 emissions from 0–6 to 1–20 g C m -2 y -1 , reducing gains in net ecosystem productivity. As a result, these increases in net CO 2 uptake and CH 4 emissions were modeled with hydrological boundary conditions that were assumed not to change with climate. Both these increases were smaller if boundary conditions were gradually altered to increase landscape drainage during model runs with climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

On the limitations of General Circulation Climate Models

General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change.

Stone, Peter H.↗
NASA NTRS2003

The Polar Regions and Martian Climate: Studies with a Global Climate Model

Much of the interest in the polar regions centers on the fact that they likely contain the best record of Martian climate change on time scales from years to eons. This expectation is based upon the observed occurrence of weathering product deposits and volatile reservoirs that are coupled to the climate. Interpretation and understanding of these records requires understanding of the mechanisms that involve the exchange of dust, water, and carbon dioxide between the surface and atmosphere, and the atmospheric redistribution of these species. We will summarize our use of the GFDL Mars general circulation model (MGCM), to exploration aspects of the interaction between the global climate and the polar regions. For example, our studies have shown that while the northern polar cap is the dominant seasonal source for water, it can act as a net annual source or sink for water, depending upon the cap temperatures and the bulk humidity of the atmosphere. This behavior regulates the annual and global average humidity of the atmosphere, as the cap acts as a sink if the atmosphere is too wet and a source if it is too dry. We will then focus our presentation on the ability of the MGCM to simulate the observed diurnal variations of surface temperature. We are particularly interested in assessing the influence of dust aerosol and water ice clouds on simulated surface temperature and the comparison with observations. Surface thermal inertia and albedo are critical boundary inputs for MGCM simulations. Thermal inertia is also of intrinsic interest as it may be related to properties of the surface such as particle size and surface character.

Wilson, R. J.↗
NASA NTRS1995

The role of sea ice in 2 x CO2 climate model sensitivity. Part 1: The total influence of sea ice thickness and extent

As a first step in investigating the effects of sea ice changes on the climate sensitivity to doubled atmospheric CO2, the authors use a standard simple sea ice model while varying the sea ice distributions and thicknesses in the control run. Thinner ice amplifies the atmospheric temperature senstivity in these experiments by about 15% (to a warming of 4.8 C), because it is easier for the thinner ice to be removed as the climate warms. Thus, its impact on sensitivity is similar to that of greater sea ice extent in the control run, which provides more opportunity for sea ice reduction. An experiment with sea ice not allowed to change between the control and doubled CO2 simulations illustrates that the total effect of sea ice on surface air temperature changes, including cloud cover and water vapor feedbacks that arise in response to sea ice variations, amounts to 37% of the temperature sensitivity to the CO2 doubling, accounting for 1.56 C of the 4.17 C global warming. This is about four times larger than the sea ice impact when no feedbacks are allowed. The different experiments produce a range of results for southern high latitudes with the hydrologic budget over Antarctica implying sea level increases of varying magnitude or no change. These results highlight the importance of properly constraining the sea ice response to climate perturbations, necessitating the use of more realistic sea ice and ocean models.

Rind, D.↗
NASA NTRS2012

Modeling Climate Responses to Spectral Solar Forcing on Centennial and Decadal Time Scales

We report a series of experiments to explore clima~ responses to two types of solar spectral forcing on decadal and centennial time scales - one based on prior reconstructions, and another implied by recent observations from the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral 1rradiance Monitor). We apply these forcings to the Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM). that couples atmosphere with ocean, and has a model top near the mesopause, allowing us to examine the full response to the two solar forcing scenarios. We show different climate responses to the two solar forCing scenarios on decadal time scales and also trends on centennial time scales. Differences between solar maximum and solar minimum conditions are highlighted, including impacts of the time lagged reSponse of the lower atmosphere and ocean. This contrasts with studies that assume separate equilibrium conditions at solar maximum and minimum. We discuss model feedback mechanisms involved in the solar forced climate variations.

Wen, G.↗
DOE OSTI2023

Efficient Super-Resolution of Near-Surface Climate Modeling Using the Fourier Neural Operator

Downscaling methods are critical in efficiently generating high-resolution atmospheric data. However, state-of-the-art statistical or dynamical downscaling techniques either suffer from the high computational cost of running a physical model or require high-resolution data to develop a downscaling tool. Here, we demonstrate a recently proposed zero-shot super-resolution method, the Fourier neural operator (FNO), to efficiently perform downscaling without the need for high-resolution data. Because the FNO learns dynamics in Fourier space, FNO is a resolution-invariant emulator; it can be trained at a coarse resolution and produces emulation at any high resolution. We applied FNO to downscale a 4-km resolution Weather Research and Forecasting (WRF) Model simulation of near-surface heat-related variables over the Great Lakes region. The FNO is driven by the atmospheric forcings, and topographic features used in the WRF model at the same resolution. We incorporated a physics-constrained loss in FNO by using the Clausius-Clapeyron relation to better constrain the relations among the emulated states. Trained on merely 600 WRF snapshots at 4-km resolution, the FNO shows comparable performance with a widely used convolutional network, U-Net, achieving averaged modified Kling-Gupta Efficiency of 0.88 and 0.94 on the test dataset for temperature and pressure, respectively. We then employed the FNO to produce 1-km emulations to reproduce the fine climate features. Further, by taking the WRF simulation as ground truth, we show consistent performances at the two resolutions, suggesting the reliability of FNO in producing high-resolution dynamics. Our study demonstrates the potential of using FNO for zero-shot super-resolution in generating first-order estimation on atmospheric modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Analyzing Seasonal Forcing Mechanisms of the Martian Polar Warming with the NASA Ames Mars Global Climate Model

The meridional transport of heat, momentum, water, dust, trace species and gases is critical for the control of Mars’ climate. Though the nature and structure of the mean meridional circulation has been previously studied, questions remain regarding the seasonal forcing mechanisms, and the implications on the combined thermal and dynamical response for Mars’ climate. A useful diagnostic of the mean meridional circulation and transport in the middle atmosphere is polar warming.

Brecht, A. S.↗
DOE OSTI2019

Accelerated Climate Model for Energy (Final Report)

The E3SM (formerly ACME) project utilizes the netCDF Operator (NCO) toolkit to generate, regrid, and split climate datasets for pre- and post-processing analysis. NCO tools are themselves embedded in the E3SM-unified, E3SM-diags, A-Prime, MPAS-Analysis, Processflow, and LIVVkit diagnostic suites, and so improve and leverage the analysis and diagnostics capabilities of the E3SM Science and Infrastructure teams. In this project, the UCI team extended and customized NCO features used standalone and by the diagnostic suites to accelerate and ease analysis and distribution of E3SM experiments. With supplementary funding, the UCI team also contributed physical improvements to the treatment of snow in the E3SM land, land-ice, and sea-ice model components.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Changes in Precipitation and Air Temperature Contribute Comparably to Permafrost Degradation in a Warmer Climate: Modeling Archive

The dataset contains "ecosys" model outputs reported in Mekonnen et al. (2021) to examine the importance of heat transfer from precipitation on permafrost degradation. The study highlighted the importance of mechanistically representing this process in earth system models (ESMs) and demonstrated that precipitation is as important an environmental control on permafrost degradation as surface air temperature. Included are (1) the modeled spatially averaged annual active layer depth (ALD) and daily maximum soil temperature across the North Slope of Alaska from 1980 to 2100, and (2) 25 km resolution modeled ALD for averaged for two time intervals, 2006 - 2010 and 2096 - 2100. The results are provided for two "ecosys" simulations: S1 with precipitation heat transfer and S2 without precipitation heat transfer across the North Slope of Alaska. These data are available in a NetCDF and csv data formats. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Drivers of coupled climate model biases in representing Labrador Sea convection

Abstract This study investigates the representation of ocean convection in the Labrador Sea in seven Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 5 and 6 datasets. The relative role of the oceanic and atmospheric biases in the subpolar North Atlantic gyre are explored using regional ocean simulations where the atmospheric forcing or the ocean initial and boundary conditions are replaced by reanalysis data in the absence of interactive air-sea coupling. Commonalities and differences among model behaviors are discussed with the objective of finding a pathway forward to improve the representation of the ocean mean state and variability in a region of fundamental importance for climate variability and change. Results highlight that an improved representation of ocean stratification in the North Atlantic subpolar gyre is urgently needed to constrain future climate change projections. While improving the ocean model resolution in the North Atlantic alone may contribute a better representation of both boundary currents and propagation of heat and freshwater anomalies into the Labrador Sea, it may not be sufficient. Addressing the atmospheric heat flux bias with better resolution in the atmosphere and land topography may allow for deep convection to occur in the Labrador Sea in some of the models that miss it entirely, but the greatest priority remains improving the representation of ocean stratification.

Liu, Guangpeng↗
DOE OSTI2025

Impacts of Resolution on Heavy‐Precipitating Storms in Climate Model Hindcasts

The present study investigates the impact of horizontal resolutions on heavy‐precipitating storms using the Energy Exascale Earth System Model version2 (E3SMv2) at low (∼100 km, LR) and high (∼25 km, HR) resolutions through short‐range hindcasts. The short‐range hindcast approach ensures a faithful comparison of model resolution in simulating the same storm events under a controlled large‐scale environment. Using a phenomenon‐based framework, we attribute precipitation to specific storm types: tropical cyclones (TCs), extratropical cyclones, atmospheric rivers, and mesoscale convective systems (MCSs). Our findings show that E3SM hindcasts with both HR and LR configurations significantly underestimate storm‐associated precipitation intensity but overestimate precipitation from other sources. Furthermore, both HR and LR hindcasts face significant challenges in accurately simulating extreme precipitation events, particularly over MCS hotspots. Nevertheless, HR simulations capture more detailed and intense precipitation patterns with an improved representation of storm dynamics. HR hindcasts produce 16% more storm precipitation compared to LR. For precipitation extremes, HR simulates a 33% higher 99th percentile precipitation magnitudes compared to LR, and most of the increment comes from these four heavy‐precipitating storm types. The increase in precipitation mainly comes from stratiform precipitation rather than convective precipitation. The improvement in HR simulations varies across different storm types with TC showing the largest improvement. The phenomenon‐based approach provides important insights into precipitation simulations especially for extremes. Our results emphasize the need for further refinement in high‐resolution models to improve the accuracy of precipitation predictions, which is crucial for better understanding and mitigating climate change impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Altimeter-era emergence of the patterns of forced sea-level rise in climate models and implications for the future

The satellite altimeter record has provided an unprecedented database for understanding sea-level rise and has recently reached a major milestone at 25 years in length. A challenge now exists in understanding its broader significance and its consequences for sea-level rise in the coming decades and beyond. A key question is whether the pattern of altimeter-era change is representative of longer-term trends driven by anthropogenic forcing. In this work, two multimember climate ensembles, the Community Earth System Model (CESM) and the Earth System Model Version 2M (ESM2M), are used to estimate patterns of forced change [also known as the forced response (FR)] and their magnitudes relative to internal variability. It is found that the spatial patterns of 1993–2018 trends in the ensembles correlate significantly with the contemporaneous FRs (0.55 ± 0.10 in the CESM and 0.61 ± 0.09 in the ESM2M) and the 1950–2100 FRs (0.43 ± 0.10 in the CESM and 0.51 ± 0.11 in the ESM2M). Unforced runs for each model show such correlations to be extremely unlikely to have arisen by chance, indicating an emergence of both the altimeter-era and long-term FRs and suggesting a similar emergence in nature. Projected patterns of the FR over the coming decades resemble those simulated during the altimeter era, suggesting a continuation of the forced pattern of change in nature in the coming decades. Notably, elevated rates of rise are projected to continue in regions that are susceptible to tropical cyclones, exacerbating associated impacts in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Resolution matters when modeling climate change in headwaters of the Colorado River

The continued growth of Southwestern cities depends on reliable water export from Rocky Mountain headwaters, which provide ~85% of Colorado River Basin (CRB) streamflow. Despite being more sensitive to warming temperatures, alpine systems are simplified in the regional-scale models currently in use to plan for future water supply. We used an integrated hydrologic model that couples groundwater and surface water with snow and vegetation processes to examine the effect of topographic simplifications as a result of grid coarsening in a representative CRB headwater basin. High-resolution (100 m) simulations predicted headwater streamflow losses of 16% by 2050 while coarse-resolution (1 km) simulations predict only 12%, suggesting that regional-scale models (coarser than 1 km) likely overestimate future Colorado River Basin water supplies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Basin-Scale River Runoff Estimation from GRACE Gravity Satellites, Climate Models and In Situ Observations: a Case Study in the Amazon Basin

River runoff is estimated as a water budget residual using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage time series, ERA5 reanalysis data, and precipitation observations for January 2003 through December 2015 for the Obidos upstream drainage basin and for the entire Amazon basin. Estimated runoff based on the water budget agrees remarkably well with in situgauge observations at Obidos, especially at seasonal time scales, with nearly perfect phase agreementbut slightly larger seasonal amplitude. The discrepancy in the seasonal amplitude maybe attributed to underestimation of river gauge runoff during the wet season when water overflows the riverbanks. The ERA5 model appears to overestimate long-term mean evapotranspiration in the Amazon by ~2 cm/monthb ased on comparisons with precipitation and runoff observations. Using precipitation data based on satellites and gauge observations relative to gauge observations alone improved agreement between water budget runoff estimates and in situ runoff observations. Seasonal variations in ERA5 simulated runoff are about twice as large as those from in situobservations and show a large phase lag as well. Water budget based runoff for the entire Amazon (~ 7,200 km3averaged 29over the 13 yr period) is significantly larger than observed runoff (~5,700 km3) at notably larger than previous estimates for the entire Amazon. These differences may be partly related to submarine runoff from the Amazon basin that cannot be captured by surface gauges.

Jianli Chen↗
NASA NTRS2003

A One Billion Year Martian Climate Model: The Importance of Seasonally Resolved Polar Caps and the Role of Wind

Wind deflation and deposition are powerful agents of surface change in the present Mars climate regime. Recent studies indicate that, while the distribution of regions of potential deflation (or erosion) and deposition is remarkably insensitive to changes in orbital parameters (obliquity, timing of perihelion passage, etc.), rates of aeolian surface modification may be highly sensitive to these parameters even if the atmospheric mass remains constant. But previous work suggested the atmospheric mass is likely to be sensitive to obliquity, especially if a significant mass of carbon dioxide can be stored in the regolith or deposited in the form of massive polar caps. Deflation and erosion are highly sensitive to surface pressure, so feedback between orbit variations and surface pressure can greatly enhance the sensitivity of aeolian modification rates to orbital parameters. We used statistics derived from a 1 Gyr orbital integration of the spin axis of Mars, coupled with 3D general circulation models (GCMs) at a variety of orbital conditions and pressures, to explore this feedback. We also employed a seasonally resolved 1D energy balance model to illuminate the gross characteristics of the longterm atmospheric evolution, wind erosion and deposition over one billion years. We find that seasonal polar cycles have a critical influence on the ability for the regolith to release CO2 at high obliquities, and find that the atmospheric CO2 actually decreases at high obliquities due to the cooling effect of polar deposits at latitudes where seasonal caps form. At low obliquity, the formation of massive, permanent polar caps depends critically on the values of the frost albedo, A(sub frost), and frost emissivity, E(sub frost). Using our 1D model with values of A(sub frost) = 0.67 and E(sub frost) = 0.55, matched to the NASA Ames GCM results, we find that permanent caps only form at low obliquities (< 10 degrees). Thus, contrary to expectations, the Martian atmospheric pressure is remarkable static over time, and decreases both at high and low obliquity. Also, from our one billion year orbital model, we present new results on the fraction of time Mars is expected to experience periods of high and low obliquity. Finally, using GCM runs at a variety of pressures, we examine the likely role of wind erosion under an early more massive Martian atmosphere.

J C Armstrong↗
DOE OSTI2025

WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions

Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.

54 ENVIRONMENTAL SCIENCES↗