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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

The GEOS-Chemistry-Climate Model (CCM), Versions 1,2 and 3

This paper examines evolution of key ozone and climate aspects in our range of Goddard Earth Observing System Models, Versions 1-3. Version 1 (Pawson et al., 2008; )GR) used GSFC stratospheric ozone chemistry in GEOS-4 GCM. A chronic high bias in polar ozone at low chlorine loading persisted into Version 2, which used the GEQS-5 GCM and the same chemistry. This is much improved in Version 3, which uses the GMI-COMBO stratosphere-troposphere chemistry. A dynamical problem with Version 1, the overactive nature of the Antarctic polar vortex, is corrected in Versions 2 and 3, when GEQS-5 replaces GEO5-4. Other changes between the various model versions will be documented.

Pawson, Steven↗
DOE OSTI2017

Using ARM Observations to Evaluate Climate Model Simulations of Land-Atmosphere Coupling on the U.S. Southern Great Plains

Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land-atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operated in both a free-running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free-running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. Lastly, these results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AMOC Variability in Climate Models and Its Dependence on the Mean State

Abstract Understanding internal variability of the climate system is critical when isolating internal and anthropogenically forced signals. Here, we investigate the modes of Atlantic Meridional Overturning Circulation ( AMOC ) variability using perturbation experiments with the Institut Pierre‐Simon Laplace's (IPSL) coupled model and compare them to Coupled Model Intercomparison Project Phase 6 (CMIP6) pre‐industrial control simulations. We identify two characteristic modes of variability—decadal‐to‐multidecadal ( DMD var ) and centennial ( CEN var ). The former is driven largely by temperature anomalies in the subpolar North Atlantic, while the latter is driven by salinity in the western subpolar North Atlantic. The amplitude of each mode scales linearly with the mean AMOC strength in the IPSL experiments. The DMD var amplitude correlates well with the AMOC mean strength across CMIP6 models, while the CEN var mode does not. These findings suggest that the strength of DMD var depends robustly on the North Atlantic mean state, while the CEN var mode may be model‐dependent.

Ferster, Brady S. [LOCEAN‐IPSL Sorbonne Université↗
NASA NTRS2012

Satellite Contributions to the Quantitative Characterization of Biomass Burning for Climate Modeling

Characterization of biomass burning from space has been the subject of an extensive body of literature published over the last few decades. Given the importance of this topic, we review how satellite observations contribute toward improving the representation of biomass burning quantitatively in climate and air-quality modeling and assessment. Satellite observations related to biomass burning may be classified into five broad categories: (i) active fire location and energy release, (ii) burned areas and burn severity, (iii) smoke plume physical disposition, (iv) aerosol distribution and particle properties, and (v) trace gas concentrations. Each of these categories involves multiple parameters used in characterizing specific aspects of the biomass-burning phenomenon. Some of the parameters are merely qualitative, whereas others are quantitative, although all are essential for improving the scientific understanding of the overall distribution (both spatial and temporal) and impacts of biomass burning. Some of the qualitative satellite datasets, such as fire locations, aerosol index, and gas estimates have fairly long-term records. They date back as far as the 1970s, following the launches of the DMSP, Landsat, NOAA, and Nimbus series of earth observation satellites. Although there were additional satellite launches in the 1980s and 1990s, space-based retrieval of quantitative biomass burning data products began in earnest following the launch of Terra in December 1999. Starting in 2000, fire radiative power, aerosol optical thickness and particle properties over land, smoke plume injection height and profile, and essential trace gas concentrations at improved resolutions became available. The 2000s also saw a large list of other new satellite launches, including Aqua, Aura, Envisat, Parasol, and CALIPSO, carrying a host of sophisticated instruments providing high quality measurements of parameters related to biomass burning and other phenomena. These improved data products have enabled significant progress in the study of biomass burning from space. However, appreciable uncertainty remains in many of the measurements that still needs to be addressed. Nevertheless, climate and other atmospheric models are

Ichoku, Charles↗
NASA NTRS1989

Effects of cumulus entrainment and multiple cloud types on a January global climate model simulation

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.

Yao, Mao-Sung↗
NASA NTRSDate not supplied

Planning Satellite Swarm Measurements for Climate Models: Comparing Dynamic Constraint Processing and MILP Methods

We present D-SHIELD, a challenging climate science application to plan coordinated measurements (observations) for a constellation of satellites, each containing two different sensors, each with 61 pointing angle options. The L-band and P-band radar sensors collect data fed into a soil moisture model which tracks and predicts soil moisture across 1.67 million Ground Positions (GP). Soil moisture is an important predictor of wildfires, and then a predictor of floods, landslides and debris flow after a fire. Each measurement covers multiple GP due to the sensor footprint. Each GP has a "model error" which represents the uncertainty of the the soil moisture state prediction. Model error changes at different rates for each GP as the time since last observation increases and after significant events like rain. The planner's goal is to select measurements which maximize soil moisture model improvement (reduce model uncertainty). This problem is combinatorically explosive, involving many degrees of freedom for planner choices. Good domain heuristics can find solutions within a reasonable time for our application needs but cannot be proven optimal. In this paper we compare two different planning approaches to this problem: Dynamic Constraint Processing (DCP) and Mixed Integer Linear Programming (MILP). We match inputs and metrics for both DCP and MILP algorithms to enable a direct apples-to-apples comparison. We demonstrate and discuss the trades between DCP flexibility and performance vs. MILP's promise of provable optimality.

Rich Levinson↗
DOE OSTI2022

Annual Mean Arctic Amplification 1970–2020: Observed and Simulated by CMIP6 Climate Models

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the “best” CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step-like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Objective tropical cyclone extratropical transition detection in high-resolution reanalysis and climate model data

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high-resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable-resolution Community Atmosphere Model (CAM) at two different resolutions (DX 55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, DX 38 km), and the ERA-Interim Reanalysis (ERA-I, DX 80 km). The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA-I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold-core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.

54 ENVIRONMENTAL SCIENCES↗
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↗