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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Matching Observations to Model Resolution for Future Weather and Climate Applications

High spatial resolution sounding observations will improve initialization and assimilation into the next generation forecast models and validation of the next generation of climate models. One such advanced sounder concept for low earth orbit is the Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) which proposes to provide highvspatial hyperspectral resolution observations in the mid to longwave infrared. This paper explores the effects of spatial resolution on the errors expected from the combined use of models and observations for representing scene information. We calculate the frequency response of the instrument and model and determine the error at any given spatial frequency. The results show that it is vital to have observations match the spatial resolution of models to minimize the uncertainty in the representation of the scene contents.

spatial resolution↗
NASA NTRS2005

Revealing Relationships among Relevant Climate Variables with Information Theory

The primary objective of the NASA Earth-Sun Exploration Technology Office is to understand the observed Earth climate variability, thus enabling the determination and prediction of the climate's response to both natural and human-induced forcing. We are currently developing a suite of computational tools that will allow researchers to calculate, from data, a variety of information-theoretic quantities such as mutual information, which can be used to identify relationships among climate variables, and transfer entropy, which indicates the possibility of causal interactions. Our tools estimate these quantities along with their associated error bars, the latter of which is critical for describing the degree of uncertainty in the estimates. This work is based upon optimal binning techniques that we have developed for piecewise-constant, histogram-style models of the underlying density functions. Two useful side benefits have already been discovered. The first allows a researcher to determine whether there exist sufficient data to estimate the underlying probability density. The second permits one to determine an acceptable degree of round-off when compressing data for efficient transfer and storage. We also demonstrate how mutual information and transfer entropy can be applied so as to allow researchers not only to identify relations among climate variables, but also to characterize and quantify their possible causal interactions.

Knuth, Kevin H.↗
NASA NTRS1980

Guidelines for the air-sea interaction special study: An element of the NASA climate research program, JPL/SIO workshop report

A program in the area of air sea interactions is introduced. A space capability is discussed for global observations of climate parameters which will contribute to the understanding of the processes which influence climate and its predictability. The following recommendations are some of the suggestions made for air sea interaction studies: (1) a major effort needs to be devoted to the preparation of space based climatic data sets; (2) NASA should create a group or center for climatic data analysis due to the substantial long term effort that is needed in research and development; (3) funding for the analyses of existing data sets should be augmented and continued beyond the termination of present programs; (4) NASA should fund studies in universities, research institutions and governments' centers; and (5) the planning for an air sea interaction mission should be an early task.

Source record↗
NASA NTRS2012

Mars Atmospheric CO2 Condensation Above the North and South Poles as Revealed by Radio Occultation, Climate Sounder, and Laser Ranging Observations

We study the condensation of CO2 in Mars atmosphere using temperature profilesretrieved from radio occultation measurements from Mars Global Surveyor (MGS) as wellas the climate sounding instrument onboard the Mars Reconnaissance Orbiter (MRO),and detection of reflective clouds by the MGS Mars Orbiter Laser Altimeter (MOLA). Wefind 11 events in 1999 where MGS temperature profiles indicate CO2 condensation andMOLA simultaneously detects reflective clouds. We thus provide causal evidence thatMOLA non-ground returns are associated with CO2 condensation, which strongly indicatestheir nature being CO2 clouds. The MGS and MRO temperature profiles together revealthe seasonal expansion and shrinking of the area and the vertical extent of atmosphericsaturation. The occurrence rate of atmospheric saturation is maximized at high latitudes inthe middle of winter. The atmospheric saturation in the northern polar region exhibits moreintense seasonal variation than in the southern polar region. In particular, a shrinking ofsaturation area and thickness from LS 270 to 300 in 2007 is found; this is probablyrelated to a planet-encircling dust storm. Furthermore, we integrate the condensation areaand the condensation occurrence rate to estimate cumulative masses of CO2 condensatesdeposited onto the northern and southern seasonal polar caps. The precipitation flux isapproximated by the particle settling flux which is estimated using the impulse responses ofMOLA filter channels. With our approach, the total atmospheric condensation mass canbe estimated from these observational data sets with average particle size as the onlyfree parameter. By comparison with the seasonal polar cap masses inferred from thetime-varying gravity of Mars, our estimates indicate that the average condensate particleradius is 822 mm in the northern hemisphere and 413 mm in the southern hemisphere.Our multi-instrument data analysis provides new constraints on modeling the global climateof Mars.

MOLA↗
NASA NTRS2017

Atmospheric Water Balance and Variability in the MERRA-2 Reanalysis

Closing and balancing Earths global water cycle remains a challenge for the climate community. Observations are limited in duration, global coverage, and frequency, and not all water cycle terms are adequately observed. Reanalyses aim to fill the gaps through the assimilation of as many atmospheric water vapor observations as possible. Former generations of reanalyses have demonstrated a number of systematic problems that have limited their use in climate studies, especially regarding low-frequency trends. This study characterizes the NASA Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) water cycle relative to contemporary reanalyses and observations. MERRA-2 includes measures intended to minimize the spurious global variations related to in homogeneity in the observational record. The global balance and cycling of water from ocean to land is presented, with special attention given to the water vapor analysis increment and the effects of the changing observing system. While some systematic regional biases can be identified,MERRA-2 produces temporally consistent time series of total column water and transport of water from ocean to land. However, the interannual variability of ocean evaporation is affected by the changing surface-wind-observing system, and precipitation variability is closely related to the evaporation. The surface energy budget is also strongly influenced by the interannual variability of the ocean evaporation. Furthermore, evaluating the relationship of temperature and water vapor indicates that the variations of water vapor with temperature are weaker in satellite data reanalyses, not just MERRA-2, than determined by observations, atmospheric models, or reanalyses without water vapor assimilation.

MERRA-2↗
DOE OSTI2023

Large Ensemble Particle Filter for Spatial Climate Reconstructions Using a Linear Inverse Model

Proxy records that document the last 2000 years of climate provide evidence for the wide range of the natural climate variability from inter-annual to secular timescales not captured by the short window of recent direct observations. Assessing climate models ability to reproduce such natural variations is crucial to understand climate sensitivity and impacts of future climate change. Paleoclimate data assimilation (PDA) offers a powerful way to extend the short instrumental period by optimally combining the physics described by General Circulation Climate Models (GCMs) with information from available proxy records while taking into account their uncertainties. Here we present a new PDA approach based on a sequential importance resampling (SIR) Particle filter (PF) that uses Linear Inverse Modeling (LIM) as an emulator of several CMIP-class GCMs. We examine in a perfect-model framework the skill of the various LIMs to forecast the dynamics of the surface temperatures and provide spatial field reconstructions over the last millennium in a SIR PF. Our results show that the LIMs allow for skillful ensemble forecasts at 1-year lead-time based on GCMs dynamical knowledge with best prediction in the tropics and the North Atlantic. The PDA further provides a set of physically consistent spatial fields allowing robust uncertainty quantification related to climate models biases and proxy spatial sampling. Our results indicate that the LIM yields dynamical memory improving climate variability reconstructions and support the use of the LIM as a GCM-emulator in real reconstruction to propagate large ensembles of particles at low cost in SIR PF.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

Interannual variability and climatic noise in satellite-observed outgoing longwave radiation

Upwelling-IR observations of the North Pacific by polar orbiters NOAA 3, 4, 5, and 6 and TIROS-N from 1974 to 1981 are analyzed statistically in terms of interannual variability (IAV) in monthly averages and climatic noise due to short-term weather fluctuations. It is found that although the daily variance in the observations is the same in summer and winter months, and although IAV in winter is smaller than that in summer, the climatic noise in winter is so much smaller that a greater fraction of winter anomalies are statistically significant. The smaller winter climatic noise level is shown to be due to shorter autocorrelation times. It is demonstrated that increasing averaging area does not reduce the climatic noise level, suggesting that continuing collection of high-resolution satellite IR data on a global basis is necessary if better models of short-term variability are to be constructed.

Short, D. A.↗
NASA NTRS2013

Detection and Attribution of Anthropogenic Climate Change Impacts

Human-influenced climate change is an observed phenomenon affecting physical and biological systems across the globe. The majority of observed impacts are related to temperature changes and are located in the northern high- and midlatitudes. However, new evidence is emerging that demonstrates that impacts are related to precipitation changes as well as temperature, and that climate change is impacting systems and sectors beyond the Northern Hemisphere. In this paper, we highlight some of this new evidence-focusing on regions and sectors that the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) noted as under-represented-in the context of observed climate change impacts, direct and indirect drivers of change (including carbon dioxide itself), and methods of detection. We also present methods and studies attributing observed impacts to anthropogenic forcing. We argue that the expansion of methods of detection (in terms of a broader array of climate variables and data sources, inclusion of the major modes of climate variability, and incorporation of other drivers of change) is key to discerning the climate sensitivities of sectors and systems in regions where the impacts of climate change currently remain elusive. Attributing such changes to human forcing of the climate system, where possible, is important for development of effective mitigation and adaptation. Current challenges in documenting adaptation and the role of indigenous knowledge in detection and attribution are described.

detection↗
DOE OSTI2021

Explaining the trends and variability in the United States tornado records using climate teleconnections and shifts in observational practices

The annual frequency of tornadoes during 1950–2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefficients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other States, thereby reducing their uncertainty. The influence of the anthropogenic factors and the large-scale climate variables are modeled in a nested framework to unravel secular trend from cyclical variability. Population density explains the long-term trend in Dixie Alley. The step-increase induced due to the installation of the Doppler Radar systems explains the long-term trend in Tornado Alley. NAO and the interplay between NAO and ENSO explained the interannual to multi-decadal variability in Tornado Alley. PDO and AMO are also contributing to this multi-time scale variability. SOI and AO explain the cyclical variability in Dixie Alley. This improved understanding of the variability and trends in tornadoes should be of immense value to public planners, businesses, and insurance-based risk management agencies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

An EOF Iteration Approach for Obtaining Homogeneous Radiative Fluxes from Satellites Observations

Conventional observations of climate parameters are sparse in space and/or in time and the representativeness of such information needs to be optimized. Observations from satellites provide improved spatial coverage than point observations however they pose new challenges for obtaining homogeneous coverage. Surface radiative fluxes, the forcing functions of the hydrologic cycle and biogeophysical processes, are now becoming available from global scale satellite observations. They are derived from independent satellite platforms and sensors that differ in temporal and spatial resolution and in the size of the footprint from which information is derived. Data gaps, degraded spatial resolution near boundaries of geostationary satellites, and different viewing geometries in areas of satellite overlap, could result in biased estimates of radiative fluxes. In this study, discussed will be issues related to the sources of inhomogeneity in surface radiative fluxes as derived from satellites; development of an approach to obtain homogeneous data sets; and application of the methodology to the widely used International Satellite Cloud Climatology Project (ISCCP) data that currently serve as a source of information for deriving estimates of surface and top of the atmosphere radiative fluxes. Introduced is an Empirical Orthogonal Function (EOF) iteration scheme for homogenizing the fluxes. The scheme is evaluated in several ways including comparison of the inferred radiative fluxes against ground observations, both before and after the EOF approach is applied. On the average, the latter reduces the rms error by about 2-3 W/m2.

Zhang, Banglin↗
DOE OSTI2021

Observations of greenhouse gases as climate indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO<:sub>2 GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Observations of Greenhouse Gases as Climate Indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO2GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

greenhouse gases↗
NASA NTRS2015

The Coupled Mars Dust and Water Cycles: Understanding How Clouds Affect the Vertical Distribution and Meridional Transport of Dust and Water.

The dust and water cycles are crucial to the current Martian climate, and they are coupled through cloud formation. Dust strongly impacts the thermal structure of the atmosphere and thus greatly affects atmospheric circulation, while clouds provide radiative forcing and control the hemispheric exchange of water through the modification of the vertical distributions of water and dust. Recent improvements in the quality and sophistication of both observations and climate models allow for a more comprehensive understanding of how the interaction between the dust and water cycles (through cloud formation) affects the dust and water cycles individually. We focus here on the effects of clouds on the vertical distribution of dust and water, and how those vertical distributions control the net meridional transport of water. For this study, we utilize observations of temperature, dust and water ice from the Mars Climate Sounder (MCS) on the Mars Reconnaissance Orbiter (MRO) combined with the NASA ARC Mars Global Climate Model (MGCM). We demonstrate that the magnitude and nature of the net meridional transport of water between the northern and southern hemispheres during NH summer is sensitive to the vertical structure of the simulated aphelion cloud belt. We further examine how clouds influence the atmospheric thermal structure and thus the vertical structure of the cloud belt. Our goal is to identify and understand the importance of radiative/dynamic feedbacks due to the physical processes involved with cloud formation and evolution on the current climate of Mars.

Martian climate↗
NASA NTRS1992

Atmosphere and climate studies of Mars using the Mars Observer pressure modulator infrared radiometer

Studies of the climate and atmosphere of Mars are limited at present by a lack of meteorological data having systematic global coverage with good horizontal and vertical resolution. The Mars Observer spacecraft in a low, nearly circular, polar orbit will provide an excellent platform for acquiring the data needed to advance significantly our understanding of the Martian atmosphere and its remarkable variability. The Mars Observer pressure modulator infrared radiometer (PMIRR) is a nine-channel limb and nadir scanning atmospheric sounder which will observe the atmosphere of Mars globally from 0 to 80 km for a full Martian year. PMIRR employs narrow-band radiometric channels and two pressure modulation cells to measure atmospheric and surface emission in the thermal infrared. PMIRR infrared and visible measurements will be combined to determine the radiative balance of the polar regions, where a sizeable fraction of the global atmospheric mass annually condenses onto and sublimes from the surface. Derived meteorological fields, including diabatic heating and cooling and the vertical variation of horizontal winds, are computed from the globally mapped fields retrieved from PMIRR data.

Mccleese, D. J.↗
DOE OSTI2025

Exploring Causal Relationships and Adjustment Timescales of Aerosol-Cloud Interactions in Geostationary Satellite Observations and CAM6 Using Wavelet Phase Coherence Analysis

We present for the first time within the cloud physics context, the application of wavelet phase coherence analysis to disentangle counteracting physical processes associated with the lead-lag phase difference between cloud-proxy liquid water path (LWP) and aerosol-proxy cloud droplet number concentration ( N d ) in an Eulerian framework using satellite-based observations and climate model outputs. This approach allows us to identify the causality and dominant adjustment timescales governing the correlation between LWP and N d . Satellite observations indicate a more prevalent positive correlation between daytime LWP and N d regardless of whether LWP leads or lags N d . The positive cloud water response, associated with precipitation processes, typically occurs within 1 hr, while the negative response resulting from entrainment drying, usually takes 2–4 hr. CAM6 displays excessively rapid negative responses along with overly strong negative cloud water response and insufficient positive response, leading to a more negative correlation between LWP and N d compared to observations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

CMIP5 Historical Simulations (1850-2012) with GISS ModelE2

Observations of climate change during the CMIP5 extended historical period (1850-2012) are compared to trends simulated by six versions of the NASA Goddard Institute for Space Studies ModelE2 Earth System Model. The six models are constructed from three versions of the ModelE2 atmospheric general circulation model, distinguished by their treatment of atmospheric composition and the aerosol indirect effect, combined with two ocean general circulation models, HYCOM and Russell. Forcings that perturb the model climate during the historical period are described. Five-member ensemble averages from each of the six versions of ModelE2 simulate trends of surface air temperature, atmospheric temperature, sea ice and ocean heat content that are in general agreement with observed trends, although simulated warming is slightly excessive within the past decade. Only simulations that include increasing concentrations of long-lived greenhouse gases match the warming observed during the twentieth century. Differences in twentieth-century warming among the six model versions can be attributed to differences in climate sensitivity, aerosol and ozone forcing, and heat uptake by the deep ocean. Coupled models with HYCOM export less heat to the deep ocean, associated with reduced surface warming in regions of deepwater formation, but greater warming elsewhere at high latitudes along with reduced sea ice. All ensembles show twentieth-century annular trends toward reduced surface pressure at southern high latitudes and a poleward shift of the midlatitude westerlies, consistent with observations.

ocean heat content↗
NASA NTRS2009

Phytoplankton and Climate

Ocean phytoplankton supply about half of the oxygen that humans utilize to sustain life. In this lecture, we will explore how phytoplankton plays a critical role in modulating the Earth's climate. These tiny organisms are the base of the Ocean's food web. They can modulate the rate at which solar heat is absorbed by the ocean, either through direct absorption or through production of highly scattering cellular coverings. They take up and help sequester carbon dioxide, a key greenhouse gas that modulated the Earth's climate. They are the source of cloud nucleation gases that are key to cloud formation/processes. They are also able to modify the nutrient budgets of the ocean through active uptake of inert atmospheric nitrogen. Climate variations have a pronounced impact on phytoplankton dynamics. Long term variations in the climate have been studied through geological interpretations on its influence on phytoplankton populations. The presentation will focus on presenting the numerous linkages that have been observed between climate and phytoplankton and further discuss how present climate change scenarios are likely to impact phytoplankton populations as well as present findings from several studies that have tried to understand how the climate might react to the feedbacks from these numerous climate-phytop|ankton linkages.

Moisan, John R.↗