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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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NASA NTRS2016

Synoptic Traveling Weather Systems on Mars: Effects of Radiatively-Active Water Ice Clouds

Atmospheric aerosols on Mars are critical in determining the nature of its thermal structure, its large-scale circulation, and hence the overall climate of the planet. We conduct multi-annual simulations with the latest version of the NASA Ames Mars global climate model (GCM), gcm2.3+, that includes a modernized radiative-transfer package and complex water-ice cloud microphysics package which permit radiative effects and interactions of suspended atmospheric aerosols (e.g., water ice clouds, water vapor, dust, and mutual interactions) to influence the net diabatic heating. Results indicate that radiatively active water ice clouds profoundly affect the seasonal and annual mean climate. The mean thermal structure and balanced circulation patterns are strongly modified near the surface and aloft. Warming of the subtropical atmosphere at altitude and cooling of the high latitude atmosphere at low levels takes place, which increases the mean pole-to-equator temperature contrast (i.e., "baroclinicity"). With radiatively active water ice clouds (RAC) compared to radiatively inert water ice clouds (nonRAC), significant changes in the intensity of the mean state and forced stationary Rossby modes occur, both of which affect the vigor and intensity of traveling, synoptic period weather systems. Such weather systems not only act as key agents in the transport of heat and momentum beyond the extent of the Hadley circulation, but also the transport of trace species such as water vapor, water ice-clouds, dust and others. The northern hemisphere (NH) forced Rossby waves and resultant wave train are augmented in the RAC case: the modes are more intense and the wave train is shifted equatorward. Significant changes also occur within the subtropics and tropics. The Rossby wave train sets up, combined with the traveling synoptic-period weather systems (i.e., cyclones and anticyclones), the geographic extent of storm zones (or storm tracks) within the NH. A variety of circulation features will be presented which indicate contrasts between the RAC and nonRAC cases, and which highlight key effects radiatively-active clouds have on physical and dynamical processes active in the current climate of Mars.

NASA Ames Mars global climate model (GCM)↗
NASA NTRSDate not supplied

Model Performance in Simulating the Mid-Holocene Green Sahara

The Green Sahara Period, spanning about 11,500 to 5,000 years ago, offers an opportunity to test the ability of climate models to simulate large-scale changes in northern African climate through the strengthening of the West African Monsoon. In this study, we evaluate the performance of four models in simulating the mid-Holocene (6,000 BP), namely – EC-Earth, iCESM, CCSM4-Toronto, and the GISS ModelE2.1-G. Two scenarios are considered for each model – a standard PMIP scenario simulated with the mid-Holocene orbital parameters and greenhouse gas concentrations with vegetation prescribed to pre-industrial conditions, as well as a Green-Sahara scenario which additionally considers factors such as enhanced vegetation, reduced dust, presence of lakes, and land and soil feedbacks. All mid-Holocene scenarios capture an increase in monsoonal precipitation in northern Africa. However, a comparison of the two mid-Holocene scenarios reveals significantly higher precipitation in northern Africa for all the Green-Sahara scenarios relative to the PMIP scenarios – an observation consistent across all models. Accompanied by a strengthened Saharan Heat Low, these changes in the West African Monsoon are also linked to polar amplification, a stronger Indian Summer Monsoon and alterations to the Walker circulation. Model results are in agreement with pollen-based SAT records, multi-proxy SST records and African lake level records. This comparison indicates that a realistic simulation of the mid-Holocene Green Sahara requires consideration of multiple factors in addition to orbital and greenhouse gas forcings.

Green Sahara Period↗
NASA NTRS2001

Technical Report Series on Global Modeling and Data Assimilation: The Climate of the FVCCM-3 Model - Volume 20

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.

Suarez, Max J.↗
NASA NTRS2010

Regional Model Nesting Within GFS Daily Forecasts Over West Africa

The study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (CCSR/GISS). The paper evaluates 30 48-hour RM3 weather forecasts over West Africa during September 2006 made on a 0.5 grid nested within 1 Global Forecast System (GFS) global forecasts. September 2006 was the Special Observing Period #3 of the African Monsoon Multidisciplinary Analysis (AMMA). Archived GFS initial conditions and lateral boundary conditions for the simulations from the US National Weather Service, National Oceanographic and Atmospheric Administration were interpolated four times daily. Results for precipitation forecasts are validated against Tropical Rainfall Measurement Mission (TRMM) satellite estimates and data from the Famine Early Warning System (FEWS), which includes rain gauge measurements, and forecasts of circulation are compared to reanalysis 2. Performance statistics for the precipitation forecasts include bias, root-mean-square errors and spatial correlation coefficients. The nested regional model forecasts are compared to GFS forecasts to gauge whether nesting provides additional realistic information. They are also compared to RM3 simulations driven by reanalysis 2, representing high potential skill forecasts, to gauge the sensitivity of results to lateral boundary conditions. Nested RM3/GFS forecasts generate excessive moisture advection toward West Africa, which in turn causes prodigious amounts of model precipitation. This problem is corrected by empirical adjustments in the preparation of lateral boundary conditions and initial conditions. The resulting modified simulations improve on the GFS precipitation forecasts, achieving time-space correlations with TRMM of 0.77 on the first day and 0.63 on the second day. One realtime RM3/GFS precipitation forecast made at and posted by the African Centre of Meteorological Application for Development (ACMAD) in Niamey, Niger is shown.

Druyan, Leonard M.↗
DOE OSTI2024

Science Area 1: Standard Award: Model-Data Fusion to Examine Multiscale Dynamical Controls on Snow Cover and Critical Zone Moisture Inputs (Final Report)

In many mountain watersheds of the world, seasonal snowpacks play an important role as natural reservoirs of water. Seasonal snowpacks accumulate water during cold, wet winter months that subsequently melts. Downstream communities depend on water from melting seasonal snowpacks to support agricultural, industrial, and municipal water needs. Rapidly melting snowpacks can also present a flooding hazard, particularly if snowpacks melt at rates faster than anticipated and where adequate reservoir capacity is unavailable to buffer river flows associated with melt. The spatial and temporal dynamics of snow accumulation and melt also play an important role in supporting upland ecosystems in mountain landscapes. Snowmelt provides soil moisture that enable terrestrial ecosystem productivity and exert control on soil microorganisms that play important roles in global carbon cycles. Climate warming is gradually decreasing the amount of precipitation in mountain watersheds arriving as snow, presenting potentially profound disruptions to mountain ecosystems, as well as downstream delivery of water. The overarching goal of this project was to understand how interactions between the near-surface atmosphere and surface topography control the input, accumulation, retention, and release of water from mountain snowpacks. Over a 5-year period, this project pursued an approach combining high-resolution regional climate modeling, satellite and airborne remote sensing data, and ground-based observations to develop and analyze benchmark datasets to address overarching science questions and hypotheses. Key products include a continuous, long-term, high spatiotemporal resolution (1 km/1 hr) dataset characterizing key climate variables in the Upper Colorado River Basin. The dataset included historical estimates of precipitation, temperature, humidity, solar and longwave radiation, and wind speeds. Additionally, the project developed a 20+ year long, 30 m spatial, daily temporal multi-sensor dataset characterizing snow presence/absence in the East/Taylor River watersheds in the Central Rocky Mountains of Colorado. The project supported training of 1 postdoctoral scholar, 1 Ph.D. student, and 1 M.S. student.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

The Role of Internal Variability and Feedbacks Controlling AMOC Stability

A bi-stable mode of the Atlantic Meridional Overturning Circulation (AMOC) is found in a 10-member ensemble simulation of the SSP2-4.5 scenario using the NASA GISS-E2-1-G climate model. Local feedbacks in the subpolar North Atlantic region in conjunction with internal variability in sea-ice transport and melt play a critical role in causing the divergent behavior of the AMOC in the ensemble members. While other fully coupled models have demonstrated the important role of surface freshening in leading to AMOC shutdown, either through hosing experiments or increased precipitation and greenhouse gas warming at high latitudes, in the GISS simulations, there are no external freshwater perturbations. This is the first time that a CMIP-class model has shown such a bifurcation across an initial condition ensemble.

Atlantic Meridional Overturning Circulation↗
NASA NTRS2014

Reconciling Warming Trends

Climate models projected stronger warming over the past 15 years than has been seen in observations. Conspiring factors of errors in volcanic and solar inputs, representations of aerosols, and El NiNo evolution, may explain most of the discrepancy.

Climate models↗
DOE OSTI2025

ORBIT-2 Dataset for Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling

This dataset release corresponds to the work conducted in ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling, where large-scale AI methods were applied to improve climate and weather resolution. The collection integrates four widely used, publicly available datasets: ERA5, PRISM, DAYMET, and IMERG. To prepare the data for ORBIT-2 model training and evaluation, we applied a preprocessing pipeline that generates paired low-resolution and high-resolution samples, enabling supervised downscaling experiments. The transformation from coarse to fine scales was performed using bilinear regridding, consistent with the procedures described in WeatherBench2, a community benchmark for weather and climate AI models. This dataset supports the development and evaluation of foundation models designed for weather and climate downscaling at exascale. Additional details on methodology and applications can be found in Wang et al., ORBIT-2 (arXiv:2505.04802, 2025).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Intercomparison of Dynamically and Statistically Downscaled Climate Change Projections over the Midwest and Great Lakes Region

Downscaling of global climate model (GCMs) simulations is a key element of regional-to-local-scale climate change projections that can inform impact assessments, long-term planning, and resource management in different sectors. Here, we conduct an intercomparison between statistically and dynamically downscaled GCMs simulations using the hybrid delta (HD) and the Weather Research and Forecast (WRF) Model, respectively, over the Midwest and Great Lakes region to 1) validate their performance in reproducing extreme daily precipitation (P) and daily maximum temperature (T max ) for summer and winter and 2) evaluate projections of extremes in the future. Our results show the HD statistical downscaling approach, which includes large-scale bias correction of GCM inputs, can reproduce observed extreme P and T max reasonably well for both summer and winter. However, raw historical WRF simulations show significant bias in both extreme P and T max for both seasons. Interestingly, the convection-permitting WRF simulation at 4-km grid spacing does not produce better results for seasonal extremes than the WRF simulation at 12 km using a parameterized convection scheme. Despite a broad similarity for winter extreme P projections, the projected changes in the future summer storms are quite different between downscaling methods; WRF simulations show substantial increases in summer extreme precipitation, while the changes projected by the HD approach exhibit moderate decreases overall. The WRF simulations at 4 km also show a pronounced decoupling effect between seasonal totals and extreme daily P for summer, which suggests that there could be more intense summer extremes at two different time scales, with more severe individual convective storms combined with longer summer droughts at the end of the twenty-first century.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Solar constant secular changes

A recent model for solar constant secular changes is used to calculate a 'proxy' solar constant for: (1) the past four centuries, based upon the sunspot record, (2) the past nine centuries, based upon C-14 observations and their relation to solar activity, and (3) the next decade, based upon a dynamo theory model for the solar cycle. The proxy solar constant data is tabulated as it may be useful for climate modelers studying global climate changes.

Schatten, Kenneth H.↗
NASA NTRS2019

Inter-annual variation of tropical cyclones simulated by GEOS-5 AGCM with modified convection scheme

The Goddard Earth Observing System version 5 (GEOS-5) global climate model with a 50-km horizontal resolution is forced by observed sea surface temperature (SST) to examine the fidelity of the seasonal-mean and inter-annual variation of tropical cyclones (TCs) in the western North Pacific (WNP) and the North Atlantic (NATL). The standard Relaxed Arakawa Schubert (RAS) deep convection scheme is modified to improve the representation of TCs, where the scheme implements a stochastic limit of the cumulus entrainment rate. The modification drives mid- and upper-tropospheric cooling and low- to mid-tropospheric drying in the background state, which tends to increase atmospheric instability. This enables the model to increase convective variability on an intra-seasonal timescale and improve the simulation of intense storms. Five-member ensemble runs with the modified RAS scheme for 12 years (1998–2009) exhibit realistic spatial distributions in the climatological-mean TC development area and their pathways over WNP and NATL. The GCM is able to reproduce the inter-annual variation of accumulated cyclone energy (ACE) by prescribing yearly varying observed SST even though the individual TC intensity is still underpredicted. A sensitivity of TC activity to El Niño–Southern Oscillation (ENSO) phase is also reproduced realistically over WNP in terms of the spatial pattern changes in the main development region and TC pathways. However, the model exhibits a notable deficiency in NATL in reproducing the observed inter-annual variation of TC activity and the sensitivity to the ENSO.

accumulated cyclone energy↗
DOE OSTI2021

Mesoscale Convective Systems in a Superparameterized E3SM Simulation at High Resolution

Accurately representing mesoscale convective systems (MCSs) is crucial to simulating the energy and water cycles in global climate models. Using a novel MCS identification and tracking algorithm applied to observations and model simulations, we evaluate how well the Energy Exascale Earth System Model simulates MCSs over the central US. Simulations performed by E3SM at 25 km grid spacing with (SP-E3SM) and without (E3SM) superparameterization are compared and evaluated against observations using multiple metrics highlighting important MCS characteristics. Compared to E3SM, SP-E3SM better simulates MCS number and MCS precipitation amount, diurnal cycle, propagation, and the probability distribution of precipitation rate in both spring and summer. The improvement from SP is partly contributed by improvement in simulating the large-scale environments, featuring enhanced atmospheric low-level moisture and larger moisture transport to the central US relative to E3SM. However, SP-E3SM still underestimates MCS precipitation amount, particularly in summer. This underestimation is closely related to the negative bias in MCS precipitation intensity, although the drier environments simulated during summer also contributes to underestimation of MCS frequency. Without SP, the larger bias in MCS precipitation amount is closely related to the negative bias in MCS frequency, while the substantial dry bias in the large-scale environments also contributes to underestimation of MCS intensity. Our results suggest that SP improves MCS simulation by improving modeling of the large-scale environments and convection initiation, which are both major limiting factors in E3SM even at 25 km grid spacing where deep convection is represented by a cumulus parameterization.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

The Staring OBservations of the Atmosphere (SOBA) Mission Concept

The Staring OBservations of the Atmosphere (SOBA) Mission is a concept that was developed and matured under the guidance of the NASA Ames Project EXellence (APEX) program. If funded, it will provide an unprecedented opportunity to improve ash transport forecasts and climate model simulations associated with volcanic eruptions. NASA and National science objectives require a better understanding of volcanic aerosol and trace gas emissions, transport, chemical transformation, and deposition, since they impact Earth's climate and atmospheric composition, human health, and aviation safety. Natural hazards such as the 2010 eruption of the Eyjafjallajökull volcano in Iceland demonstrated how existing remote-sensing assets were inadequate for individual volcanic event monitoring. During this eruption, available instruments were unable to provide data necessary to initialize volcanic plume transport models so that they could accurately predict the quantity and location of volcanic ash. As a result, thousands of flights around the world were grounded unnecessarily, at great expense. Volcanoes can also play a large role in regulation of the Earth's climate, so SOBA observations will also be used to evaluate and improve volcanic aerosol and trace gas simulation in chemical transport models (CTMs) and global climate models (GCMs). We propose the development of an airborne remote sensing concept and field campaign that will respond to an eruption and provide near real time observations of a volcanic plume, specifically ash injection height, transport, aerosol microphysical physical properties, and the location and concentration of sulfur dioxide (SO2) (sulfate (SO42-) aerosol precursor). This airborne system will utilize a depolarization sensitive, downward looking Light Detection And Ranging (lidar) instrument and an ultraviolet (UV) imaging spectrometer, and will provide data to be ingested by volcanic ash advisory models. Furthermore, the lessons learned in the development of this system could eventually guide regular deployment of similar systems by NASA or other government agencies.

Aerosols↗
DOE OSTI2022

The Role of the North Atlantic Oscillation for Projections of Winter Mean Precipitation in Europe

Climate models generally project an increase in the winter North Atlantic Oscillation (NAO) index under a future high-emissions scenario, alongside an increase in winter precipitation in northern Europe and a decrease in southern Europe. The extent to which future forced NAO trends are important for European winter precipitation trends and their uncertainty remains unclear. We show using the Multimodel Large Ensemble Archive that the NAO plays a small role in northern European mean winter precipitation projections for 2080–2099. Conversely, half of the model uncertainty in southern European mean winter precipitation projections is potentially reducible through improved understanding of the NAO projections. Extreme positive NAO winters increase in frequency in most models as a consequence of mean NAO changes. These extremes also have more severe future precipitation impacts, largely because of mean precipitation changes. This has implications for future resilience to extreme positive NAO winters, which frequently have severe societal impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Numerical wave modeling for operational and survival analyses of wave energy converters at the US Navy Wave Energy Test Site in Hawaii

The US Navy Wave Energy Test Site (WETS) is currently operating three grid-connected berths off Marine Corps Base Hawaii in support of technological development through scaled-model testing and pre-commercial prototyping. The location on the east shore of Oahu is open to year-round wind waves and seasonal north swells as well as severe seas from subtropical systems and hurricanes. We have assembled a spectral wave model system comprising WAVEWATCH III and SWAN on a hierarchy of global, regional, and nearshore computational grids. With wind forcing from global forecast and rean-alysis datasets as well as their regional downscaling, the system produces operational 7-day wave forecasts and a long-term hindcast. The daily forecasts, validated with real-time buoy measurements, facilitate safe deployment, operation, and retrieval of wave energy converters (WECs). The wave hindcast from 1979 to 2017 defines the intra- and inter-annual variations for statistical analysis of sea states and energy resources. Due to limited occurrences of hurricanes in Hawaii waters, their wind forcing is determined parametrically with simulated tracks from climate model downscaling. Finally, systematic analysis of the hindcast and simulation datasets provides significant wave heights from trade winds, swells, subtropical systems, and hurricanes with return periods up to 100 years for WECs survival analysis.

16 TIDAL AND WAVE POWER↗
NASA NTRS2016

How Will Sea Ice Loss Affect the Greenland Ice Sheet? On the Puzzling Features of Greenland Ice-Core Isotopic Composition

The modern cryosphere, Earth's frozen water regime, is in fast transition. Greenland ice cores show how fast theses changes can be, presenting evidence of up to 15 C warming events over timescales of less than a decade. These events, called Dansgaard/Oeschger (D/O) events, are believed to be associated with rapid changes in Arctic sea ice, although the underlying mechanisms are still unclear. The modern demise of Arctic sea ice may, in turn, instigate abrupt changes on the Greenland Ice Sheet. The Arctic Sea Ice and Greenland Ice Sheet Sensitivity (Ice2Ice Chttps://ice2ice.b.uib.noD) initiative, sponsored by the European Research Council, seeks to quantify these past rapid changes to improve our understanding of what the future may hold for the Arctic. Twenty scientists gathered in Copenhagen as part of this initiative to discuss the most recent observational, technological, and model developments toward quantifying the mechanisms behind past climate changes in Greenland. Much of the discussion focused on the causes behind the changes in stable water isotopes recorded in ice cores. The participants discussed sources of variability for stable water isotopes and framed ways that new studies could improve understanding of modern climate. The participants also discussed how climate models could provide insights into the relative roles of local and nonlocal processes in affecting stable water isotopes within the Greenland Ice Sheet. Presentations of modeling results showed how a change in the source or seasonality of precipitation could occur not only between glacial and modern climates but also between abrupt events. Recent fieldwork campaigns illustrate an important role of stable isotopes in atmospheric vapor and diffusion in the final stable isotope signal in ice. Further, indications from recent fieldwork campaigns illustrate an important role of stable isotopes in atmospheric vapor and diffusion in the final stable isotope signal in ice. This feature complicates the quantitative interpretation of ice core signals but also makes the stable ice isotope signal a more robust regional indicator of climate, speakers noted. Meeting participants agreed that to further our understanding of these relationships, we need more process-focused field and laboratory campaigns.

Greenland↗
DOE OSTI2022

Exploratory Precipitation Metrics: Spatiotemporal Characteristics, Process-Oriented, and Phenomena-Based

Abstract Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.

54 ENVIRONMENTAL SCIENCES↗