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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

MARCI-observed clouds in the Hellas Basin during northern hemisphere summer on Mars: Interpretation with the NASA/Ames Legacy Mars Global Climate Model

We present a study that is motivated by a population of water ice clouds in the Hellas Basin that has been observed by the MARs Color Imager (MARCI) instrument on the Mars Reconnaissance Orbiter (MRO) to persist throughout the majority of Northern Hemisphere (NH) summer. Although water ice clouds are present in Hellas at very low opacities throughout NH spring, they noticeably thicken after L(sub s) 60° and continue to do so until their peak optical thickness is attained at L(sub s) ~120°. They dissipate rapidly from L(sub s) 120° to 150°, and by L(sub s) 150°, the only clouds in Hellas are on the southern side of the basin and are indistinguishable from the polar hood clouds. We use the NASA/Ames Legacy Mars Global Climate Model (GCM), which is supported by the Agency’s Mars Climate Modeling Center, to investigate the dynamical and microphysical mechanisms that control the formation and evolution of Hellas water ice clouds. We show that water is transported from the North Polar Residual Cap (NPRC) southward across the equator and into the Hellas region. Water vapor is confined down low by cloud formation in the aphelion cloud belt, thus limiting the effectiveness of transport by the zonal mean overturning circulation (i.e., the Hadley cell). Thus, contrary to the commonly held conceptual understanding that the Hadley cell controls cross-equatorial water transport during this season, we show that the southward transport of water is done primarily in the vapor phase by stationary eddies at nearly all latitudes, including across the equator. Clouds form near the surface in the basin as moist air mixes with cold polar air on the western side of Hellas and are subsequently transported clockwise around the north side of the basin by the low-level cyclonic circulation. The simulated Hellas clouds have small particle sizes (~3–5 μm), are very low, and exist as long as the NPRC is exposed.

M. A. Kahre↗
NASA NTRS2013

Tropospheric Ozone Changes, Radiative Forcing and Attribution to Emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

Ozone (O3) from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has been used to calculate tropospheric ozone radiative forcings (RFs). All models applied a common set of anthropogenic emissions, which are better constrained for the present-day than the past. Future anthropogenic emissions follow the four Representative Concentration Pathway (RCP) scenarios, which define a relatively narrow range of possible air pollution emissions. We calculate a value for the pre-industrial (1750) to present-day (2010) tropospheric ozone RF of 410 mW m−2. The model range of pre-industrial to present-day changes in O3 produces a spread (+/-1 standard deviation) in RFs of +/-17%. Three different radiation schemes were used - we find differences in RFs between schemes (for the same ozone fields) of +/-10 percent. Applying two different tropopause definitions gives differences in RFs of +/-3 percent. Given additional (unquantified) uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of +/-30 percent for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (44+/-12 percent), nitrogen oxides (31 +/- 9 percent), carbon monoxide (15 +/- 3 percent) and non-methane volatile organic compounds (9 +/- 2 percent); earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 42 mW m(−2) DU(−1), a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (mW m(−2); relative to 1750) for the four future scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) of 350, 420, 370 and 460 (in 2030), and 200, 300, 280 and 600 (in 2100). Models show some coherent responses of ozone to climate change: decreases in the tropical lower troposphere, associated with increases in water vapour; and increases in the sub-tropical to mid-latitude upper troposphere, associated with increases in lightning and stratosphere-to-troposphere transport. Climate change has relatively small impacts on global mean tropospheric ozone RF.

climate change↗
NASA NTRS1991

Positive water vapour feedback in climate models confirmed by satellite data

It has recently been suggested that GCMs used to evaluate climate change overestimate the greenhouse effect due to increased concentrations of trace gases in the atmosphere. Here, new satellite-generated water vapor data are used to compare summer and winter moisture values in regions of the middle and upper troposphere that have previously been difficult to observe with confidence. It is found that, as the hemispheres warm, increased convection leads to increased water vapor above 500 mbar in approximate quantitative agreement with results from current climate models. The same conclusion is reached by comparing the tropical western and eastern Pacific regions. Thus, water vapor feedback is not overestimated in models and should amplify the climate response to increased trace-gas concentrations.

Rind, D.↗
NASA NTRS1974

Wave climate model of the Mid-Atlantic shelf and shoreline (Virginian Sea): Model development, shelf geomorphology, and preliminary results

A computerized wave climate model is developed that applies linear wave theory and shelf depth information to predict wave behavior as they pass over the continental shelf as well as the resulting wave energy distributions along the coastline. Reviewed are also the geomorphology of the Mid-Atlantic Continental Shelf, wave computations resulting from 122 wave input conditions, and a preliminary analysis of these data.

Goldsmith, V.↗
NASA NTRS1984

An energy balance climate model with cloud feedbacks

The present two-level global climate model, which is based on the atmosphere-surface energy balance, includes physically based parameterizations for the exchange of heat and moisture across latitude belts and between the surface and the atmosphere, precipitation and cloud formation, and solar and IR radiation. The model field predictions obtained encompass surface and atmospheric temperature, precipitation, relative humidity, and cloudiness. In the model integrations presented, it is noted that cloudiness is generally constant with changing temperature at low latitudes. High altitude cloudiness increases with temperature, although the cloud feedback effect on the radiation field remains small because of compensating effects on thermal and solar radiation. The net global feedback by the cloud field is negative, but small.

Roads, J. O.↗
NASA NTRS2018

Large-Scale Tropospheric Transport in the Chemistry-Climate Model Initiative (CCMI) Simulations

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI). Specifically, we find up to 40% differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

Orbe, Clara↗
NASA NTRS2008

Performance of Versions 1,2 and 3 of the Goddard Earth Observing System (GEOS) Chemistry-Climate Model (CCM)

Version 1 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) was used in the first CCMVa1 model evaluation and forms the basis for several studies of links between ozone and the circulation. That version of the CCM was based on the GEOS-4 GCM. Versions 2 and 3 of the GEOS CCM are based on the GEOS-5 GCM, which retains the "Lin-Rood" dynamical core but has a totally different set of physical parameterizatiOns to GEOS-4. In Version 2 of the GEOS CCM the Goddard stratospheric chemistry module is retained. Difference between Versions 1 and 2 thus reflect the physics changes of the underlying GCMs. Several comparisons between these two models are made, several of which reveal improvements in Version 2 (including a more realistic representation of the interannual variability of the Antarctic vortex). In Version 3 of the GEOS CCM, the stratospheric chemistry mechanism is replaced by the "GMI COMBO" code that includes tropospheric chemistry and different computational approaches. An advantage of this model version. is the reduction of high ozone biases that prevail at low chlorine loadings in Versions 1 and 2. This poster will compare and contrast various aspects of the three model versions that are relevant for understanding interactions between ozone and climate.

Pawson, Steven↗
NASA NTRS1994

Continental-scale river flow in climate models

The hydrologic cycle is a major part of the global climate system. There is an atmospheric flux of water from the ocean surface to the continents. The cycle is closed by return flow in rivers. In this paper a river routing model is developed to use with grid box climate models for the whole earth. The routing model needs an algorithm for the river mass flow and a river direction file, which has been compiled for 4 deg x 5 deg and 2 deg x 2.5 deg resolutions. River basins are defined by the direction files. The river flow leaving each grid box depends on river and lake mass, downstream distance, and an effective flow speed that depends on topography. As input the routing model uses monthly land source runoff from a 5-yr simulation of the NASA/GISS atmospheric climate model (Hansen et al.). The land source runoff from the 4 deg x 5 deg resolution model is quartered onto a 2 deg x 2.5 deg grid, and the effect of grid resolution is examined. Monthly flow at the mouth of the world's major rivers is compared with observations, and a global error function for river flow is used to evaluate the routing model and its sensitivity to physical parameters. Three basinwide parameters are introduced: the river length weighted by source runoff, the turnover rate, and the basinwide speed. Although the values of these parameters depend on the resolution at which the rivers are defined, the values should converge as the grid resolution becomes finer. When the routing scheme described here is coupled with a climate model's source runoff, it provides the basis for closing the hydrologic cycle in coupled atmosphere-ocean models by realistically allowing water to return to the ocean at the correct location and with the proper magnitude and timing.

Miller, James R.↗
DOE OSTI2024

Droughts in Wind and Solar Power: Assessing Climate Model Simulations for a Net‐Zero Energy Future

Abstract Understanding and predicting “droughts” in wind and solar power availability can help the electric grid operator planning and operation toward deep renewable penetration. We assess climate models' ability to simulate these droughts at different horizontal resolutions, ∼100 and ∼25 km, over Western North America and Texas. We find that these power droughts are associated with the high/low pressure systems. The simulated wind and solar power variabilities and their corresponding droughts during historical periods are more sensitive to the model bias than to the model resolution. Future climate simulations reveal varied future change of these droughts across different regions. Although model resolution does not affect the simulation of historical droughts, it does impact the simulated future changes. This suggests that regional response to future warming can vary considerably in high‐ and low‐resolution models. These insights have important implications for adapting power system planning and operations to the changing climate.

Liu, Xue [Department of Oceanography Texas A&amp,M↗
NASA NTRS2000

The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.

Parkinson, Claire L.↗
NASA NTRS1985

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

Thiele, O.↗
NASA NTRS2023

Sensitivity of the MAR Regional Climate Model Snowpack to the Parameterization of the Assimilation of Satellite-Derived Wet-Snow Masks on the Antarctic Peninsula

Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production (+66.7 % on average, or +95 Gt), along with a small decrease in surface mass balance (SMB) (−4.5 % on average, or −20 Gt) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will enable the identification of potential issues in modeling near-surface snowpack processes, paving the way for more accurate simulations of snow processes in model projections.

regional climate models↗
NASA NTRSDate not supplied

Exploring the Climatic Impact of Bi-Modal Dust Particle Size Distributions During the MY34/2018 Global Dust Storm with the NASA Ames Mars Global Climate Model.

We have implemented a bi-modal dust lifting scheme in the NASA Ames Mars Global Climate Model (GCM) and investigated the climatic impact on the MY34/2018 Global Dust Storm (GDS). We found that the climate is measurably responsive to the inclusion of a second, smaller dust mode. Dust tends to be lifted through a deeper column in the atmosphere, which is reflected in the climate as changes to atmospheric temperature, tide amplitudes, and surface temperatures. Adding a modest fraction of a smaller dust mode improves simulations during the GDS compared to Curiosity semi-diurnal tide observations as well as Mars Climate Sounder (MCS) T15 brightness temperatures

R A Urata↗
NASA NTRS1983

Efficient three-dimensional global models for climate studies - Models I and II

Climate modeling based on numerical solution of the fundamental equations for atmospheric structure and motion permits the explicit modeling of physical processes in the climate system and the natural treatment of interactions and feedbacks among parts of the system. The main difficulty concerning this approach is related to the computational requirements. The present investigation is concerned with the development of a grid-point model which is programmed so that both horizontal and vertical resolutions can easily be changed. Attention is given to a description of Model I, the performance of sensitivity experiments by varying parameters, the definition of an improved Model II, and a study of the dependence of climate simulation on resolution with Model II. It is shown that the major features of global climate can be simulated reasonably well with a horizontal resolution as coarse as 1000 km. Such a resolution allows the possibility of long-range climate studies with moderate computer resources.

Russel, G.↗
NASA NTRS2001

Importance of the Annual Cycles of SST and Solar Irradiance for Circulation and Rainfall: A Climate Model Simulation Study

Annual cycle of climate and precipitation is related to annual cycle of sunshine and sea-surface temperatures. Understanding its behavior is important for the welfare of humans worldwide. For example, failure of Asian monsoons can cause widespread famine and grave economic disaster in the subtropical regions. For centuries meteorologists have struggled to understand the importance of the summer sunshine and associated heating and the annual cycle of sea-surface temperatures (SSTs) on rainfall in the subtropics. Because the solar income is pretty steady from year to year, while SSTs depict large interannual variability as consequence of the variability of ocean dynamics, the influence of SSTs on the monsoons are better understood through observational and modeling studies whereas the relationship of annual rainfall to sunshine remains elusive. However, using NASA's state of the art climate model(s) that can generate realistic climate in a computer simulation, one can answer such questions. We asked the question: if there was no annual cycle of the sunshine (and its associated land-heating) or the SST and its associated influence on global circulation, what will happen to the annual cycle of monsoon rains? By comparing the simulation of a 4-year integration of a baseline Control case with two parallel anomaly experiments: 1) with annual mean solar and 2) with annual mean sea-surface temperatures, we were able to draw the following conclusions: (1) Tropical convergence zone and rainfall which moves with the Sun into the northern and southern hemispheres, specifically over the Indian, African, South American and Australian regions, is strongly modulated by the annual cycles of SSTs as well as solar forcings. The influence of the annual cycle of solar heating over land, however, is much stronger than the corresponding SST influence for almost all regions, particularly the subtropics; (2) The seasonal circulation patterns over the vast land-masses of the Northern Hemisphere at mid and high latitudes also get strongly influenced by the annual cycles of solar heating. The SST influence is largely limited to the oceanic regions of these latitudes; (3) The annual mode of precipitation over Amazonia has an equatorial regime revealing a maxima in the month of March associated with SST, and another maxima in the month of January associated with the solar annual cycles, respectively. The baseline simulation, which has both annual cycles, depicts both annual modes and its rainfall is virtually equal to the sum of those two modes; (4) Rainfall over Sahelian-Africa is significantly reduced (increased) in simulations lacking (invoking) solar irradiation with (without) the annual cycle. In fact, the dominant influence of solar irradiation emerges in almost all monsoonal-land regions: India, Southeast Asia, as well as Australia. The only exception is the Continental United States, where solar annual cycle shows only a relatively minor influence on the annual mode of rainfall.

Sud, Yogesh C.↗
NASA NTRS2010

On the Relationship Between the Brewer-Dobson Circulation and the Southern Annular Mode During Austral Summer in Couple Chemistry-Climate Model Simulations

The Brewer-Dobson circulation (BDC) is the mean transport circulation in the stratosphere. It consists of an upwelling branch in the tropics, poleward flows from the tropics to the extratropics, and downward flows in the extratropics. The BDC plays a crucial role in the distribution of important stratospheric trace gases, such as ozone and water vapor. Therefore changes in the strength of the BDC under global warming could have significant impact on stratospheric ozone depletion and recovery. For example, all climate models that are used by the World Meteorological Organization to predict ozone evolution in the 21 st century project a strengthening of the BDC that leads to ozone superrecovery in the mid-latitudes. On the other hand, ozone changes could also affect the strength of the BDC. This work investigates an outstanding question: whether and how changes in the Brewer-Dobson circulation are connected to climate change in the troposphere, in particular, the annular modes. The annular modes are the leading variability in the extratropical troposphere, which describes a seesaw pattern of circulation fluctuations between the polar and middle latitudes. Using simulations from the Goddard Earth Observing System Coupled Chemistry Climate Model (GEOS CCM), we found the strengthening of the BDC in the summer Southern Hemisphere is strongly correlated with a shift of the Southern Hemisphere Annular Mode (SAM) toward its positive phase for the last 4 decades of the 20th century. This relationship is only present in model runs that simulate the stratospheric ozone depletion. Therefore it is concluded that the BDC-SAM relationship is driven by Antarctic ozone depletion. The ozone hole significantly cools the Antarctic stratosphere in late spring/early summer, which leads to a delayed breakdown of the polar vortex: strong circumpolar eastward flows that usually shift to westward winds in late spring. The prolonged persistence of stratospheric eastward flow enhances upward propagation of tropospheric waves into the stratosphere and strengthens the BDC. The increased wave flux in the stratosphere in turn drives a SAM trend toward its positive phase. Our results also show that the BDC-SAM relationship is robust on the interannual timescale

Li, Feng↗
NASA NTRS1987

An earth outgoing longwave radiation climate model. I - Clear sky radiation

An earth outgoing longwave radiation (OLWR) climate model is presented. The model uses the upward radiative transfer parameterization of Thompson and Warren (1982) for radiation calculations, and a climatologic dataset from Crutcher and Meserve (1970) and Taljaard et al. (1969) to provide data on temperature, dewpoint, and geopotential height for various altitudes. Using the model for a monthly average radiation budget study, clear sky cases of OLWR were calculated for the global average, zonal averages, and global distributions. The regional results on North and South America were compared with GOES data and were found to agree well. The clear sky case shows that the OLWR field is highly modulated by water vapor, especially in the tropics, where the strongest longitudinal variations in OLWR occur. In the high latitudes, where cold air contains less water vapor, OLWR is basically modulated by the surface temperature.

Yang, Shi-Keng↗
NASA NTRS2005

Evaluation of the Simulation of Arctic and Antarctic Sea Ice Coverages by Eleven Major Global Climate Models

Comparison of polar sea ice results from 11 major global climate models and satellite-derived observations for 1979-2004 reveals that each of the models is simulating seasonal cycles that are phased at least approximately correctly in both hemispheres. Each is also simulating various key aspects of the observed ice cover distributions, such as winter ice not only throughout the central Arctic basin but also throughout Hudson Bay, despite its relatively low latitudes. However, some of the models simulate too much ice, others too little ice (in some cases varying depending on hemisphere and/or season), and some match the observations better in one season versus another. Several models do noticeably better in the Northern Hemisphere than in the Southern Hemisphere, and one does noticeably better in the Southern Hemisphere. In the Northern Hemisphere all simulate monthly average ice extents to within +/-5.1 x 10(exp 6)sq km of the observed ice extent throughout the year; and in the Southern Hemisphere all except one simulate the monthly averages to within +/-6.3 x 10(exp 6) sq km of the observed values. All the models properly simulate a lack of winter ice to the west of Norway; however, most do not obtain as much absence of ice immediately north of Norway as the observations show, suggesting an under simulation of the North Atlantic Current. The spread in monthly averaged ice extents amongst the 11 model simulations is greater in the Southern Hemisphere than in the Northern Hemisphere and greatest in the Southern Hemisphere winter and spring.

Parksinson, Claire↗