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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Tools and Data Services from the NASA Earth Satellite Observations for Climate Applications

Climate science and applications require access to vast amounts of archived high quality data, software tools and services for data manipulation and information extraction. These on the other hand require gaining detailed understanding of the data's internal structure and physical implementation to data reduction, combination and data product production. This time-consuming task must be undertaken before the core investigation can begin and is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets of different formats, structures, and resolutions. In order to address these issues the Goddard Space Flight Center (GSFC) Earth Sciences (GES), Data and Information Service Center (DISC) Distributed Active Archive Center (DAAC) has made great progress in facilitating science and applications research by developing innovative tools and data services applied to the Earth sciences atmospheric and climate data. The GES/DISC/DAAC has successfully implemented and maintained a long-term climate satellite data archive and developed tools and services to a variety of atmospheric science missions including AIRS, AVHRR, MODIS, SeaWiFS, SORCE, TOMS, TOVS, TRMM, and UARS and Aura instruments providing researchers with excellent opportunities to acquire accurate and continuous atmospheric measurements. Since the number of climate science products from these various missions is steadily increasing as a result of more sophisticated sensors and new science algorithms, the main challenge for data centers like the GES/DISC/DAAC is to guide users through the variety of data sets and products, provide tools to visualize and reduce the volume of the data and secure uninterrupted and reliable access to data and related products. This presentation will describe the effort at the GES/DISC/DAAC to build a bridge between multi-sensor data and the effective scientific use of the data, with an emphasis on the heritage satellite observations and science products for climate applications. The intent is to inform users of the existence of this large collection of data and products; suggest starting points for cross-platform science projects and data mining activities and provide data services and tools information. More information about the GES/DISC/DAAC satellite data and products, tools, and services can be found at http://daac.gsfc.nasa.gov.

Vicente, Gilberto A.↗
NASA NTRS2022

Mars Climate Sounder Observations of Gravity Wave Activity throughout Mars’s Lower Atmosphere

Gravity waves are one way Mars’s lower atmospheric weather can affect the circulation and even composition of Mars’s middle and upper atmosphere. A recent study showed how on-planet observations near the center of the 15 micron CO2band by the A3 channel(635–665 cm−1)of the Mars Climate Sounder on board Mars Reconnaissance Orbiter (MRO-MCS) could sense horizontally short, vertically broad gravity waves at≈25 km above the surface by looking at small-scale radiance variability in temperature-sensitive channels. This approach is extended here to two additional channels closer to the wings of the 15 micron CO2band,A1 (595–615 cm−1) and A2 (615–645 cm−1), to sense gravity waves throughout the lower atmosphere. Using information from all three channels demonstrates that gravity wave activity in Mars’s lowermost atmosphere is dominated by orographic sources, particularly over the extremely rough terrain of Valles Marineris. Much of this orographic population is either trapped or filtered in the lowest two scale heights, such that variations in filtering and non-orographic sources shape the gravity wave population observed at 25 km above the surface. During global dust storms, however, gravity wave activity in the first scale height decreases by approximately a factor of two, yet trapping/filtering of what activity remains in the tropics substantially weakens. Exceptionally high radiance variability at night in the tropics during the less dusty part of the year is the result of observing mesospheric clouds rather than gravity waves.

Nicholas G Heavens↗
NASA NTRS2013

Achieving Climate Change Absolute Accuracy in Orbit

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5-50 micron), the spectrum of solar radiation reflected by the Earth and its atmosphere (320-2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a "NIST [National Institute of Standards and Technology] in orbit." CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.

Wielicki, Bruce A.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-19005-DND

Science is an economic investment by the public. We will be managing Earth’s climate until civilization moves elsewhere. We currently have no national or international climate observing system, nor a plan to create one. Should we invest in one? Is it worth it? What is the economic value of an advanced climate observing system? How would you estimate it? We have a few traceable estimates of the economic value of weather prediction for severe storms, hurricanes, floods and droughts. Climate scientists often say that the results from their research “will inform societal decisions with trillion dollar impacts”. But is this statement verified and traceable in any way? How could we quantify an economic value to climate science? Recall that climate change science value exists decades into the future. Its value has to be treated as a risk/benefit economic analysis. A rigorous analysis must take into account the uncertainties in climate science, economic impacts, and policy (see Figure 1 below).

Bruce A Wielicki↗
DOE OSTI2023

Ship-based Observations and Climate Model Simulations of Cloud Phase over the Southern Ocean

The Southern Ocean (SO) clouds exert a significant influence on the Earth’s radiation budget. Here we analyzed ship-based remote sensing observations of SO clouds over a five-month long DOE ARM Measurements of Aerosols, Radiation and Clouds over the Southern Oceans (MARCUS) field campaign to better understand cloud phase variability. We developed a method to classify eight categories of hydrometeors (ice, liquid, mixed phase, rain, drizzle, snow, aerosols, and clear sky) based on measurements of lidar, radar and radiosondes. Cloud thermodynamic phases (liquid, ice and mixed phase) at coarser scales were further derived to compare with the DOE Energy Exascale Earth System Model version 1 (E3SMv1) simulation and the Earth Model Column Collaboratory (EMC 2 ) instrument simulator. For a scale-aware comparison with climate model simulations, we found that spatially averaging the raw remote sensing data (e.g., backscatter, reflectivity) results in increased cloud cover and cloud liquid, whereas, directly averaging cloud phase from higher to lower resolution maintains clear air regions and is thus recommended for in-cloud frequency comparisons. For cloud thermodynamic phases in stratiform clouds, the E3SM underestimates cloud ice and overestimates cloud liquid at temperatures between -40 and 0°C. When latitudes increase, both observations and simulations show a transition of dominant phase from liquid to ice for cloud tops as well as for the entire cloud columns, but the model underestimation of ice phase is more severe at higher latitudes. Such model bias is unlikely caused by spatial scale differences or lack of heterogeneity in cloud vertical structure in the simulation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Comparisons of observed seasonal climate features with a winter and summer numerical simulation produced with the GLAS general circulation model

Results are presented from numerical simulations performed with the general circulation model (GCM) for winter and summer. The monthly mean simulated fields for each integration are compared with observed geographical distributions and zonal averages. In general, the simulated sea level pressure and upper level geopotential height field agree well with the observations. Well simulated features are the winter Aleutian and Icelandic lows, the summer southwestern U.S. low, the summer and winter oceanic subtropical highs in both hemispheres, and the summer upper level Tibetan high and Atlantic ridge. The surface and upper air wind fields in the low latitudes are in good agreement with the observations. The geographical distirbutions of the Earth-atmosphere radiation balance and of the precipitation rates over the oceans are well simulated, but not all of the intensities of these features are correct. Other comparisons are shown for precipitation along the ITCZ, rediation balance, zonally averaged temperatures and zonal winds, and poleward transports of momentum and sensible heat.

Halem, M.↗
NASA NTRS2016

The Habitability of Proxima Centauri b II. Possible Climates and Observability

Radial velocity monitoring has found the signature of a M sin i = 1.3 M(sub ⨁) planet located within the habitable zone (HZ) of Proxima Centauri. Despite a hotter past and an active host star, the planet Proxima b could have retained enough volatiles to sustain surface habitability. Here we use a 3D Global Climate Model (GCM) to simulate the atmosphere and water cycle of Proxima b for its two likely rotation modes (1:1 and 3:2 spin-orbit resonances), while varying the unconstrained surface water inventory and atmospheric greenhouse effect. Any low-obliquity, low-eccentricity planet within the HZ of its star should be in one of the climate regimes discussed here. We find that a broad range of atmospheric compositions allow surface liquid water. On a tidally locked planet with sufficient surface water inventory, liquid water is always present, at least in the substellar region. With a non-synchronous rotation, this requires a minimum greenhouse warming (~10 mbar of CO2 and 1 bar of N2). If the planet is dryer, ~0.5 bar or 1.5 bars of CO2 (for asynchronous or synchronous rotation, respectively) suffice to prevent the trapping of any arbitrary, small water inventory into polar or nightside ice caps. We produce reflection and emission spectra and phase curves for the simulated climates. We find that atmospheric characterization will be possible via direct imaging with forthcoming large telescopes. The angular separation of 7 λ/D at 1 μm (with the E-ELT) and a contrast of ~10(exp -7) will enable high-resolution spectroscopy and the search for molecular signatures, including H2O, O2, and CO2. The observation of thermal phase curves can be attempted with the James Webb Space Telescope, thanks to a contrast of 2 × 10(exp -5) at 10 μm. Proxima b will also be an exceptional target for future IR interferometers. Within a decade it will be possible to image Proxima b and possibly determine whether the surface of this exoplanet is habitable.

Proxima Cen↗
NASA NTRS2003

Obliquity, Ice Sheets, and Layered Sediments on Mars: What Spacecraft Observations and Climate Models are Telling Us

The Mars Odyssey Gamma-Ray Spectrometer (GRS) data present a quandary: On the one hand, large deposits of (inferred) water ice are located where thermal models suggest they would form and best be protected, e.g., if deposited during periods of higher obliquity. On the other hand, the volume mixing ratios (approx. 70%) are so high that diffusive deposition of water in regolith pore space (which is the process assumed by these models) cannot be the primary formation mechanism. Furthermore, given that the water is inferred to be so close to the surface (less than a few 10's of cm's), it must be in communication with the atmosphere on time scales that are geologically relatively short (10(exp 3)-10(exp 6) years); therefore the water cannot be archaic. Considering the GRS data, images of mantled, fretted, and disaggregated terrain, and new climate modeling of Mars orbital cycles, we are led to an alternate conclusion about the ice deposits: that they form as subaerial ice sheets. This scenario not only provides a simple explanation for these observations, but may also help explain the formation of globally distributed, sedimentary layered deposits.

Richardson, M. I.↗
DOE OSTI2024

Autocalibration of the E3SM Version 2 Atmosphere Model Using a PCA-Based Surrogate for Spatial Fields

Global Climate Model tuning (calibration) is a tedious and time-consuming process, with high-dimensional input and output fields. Experts typically tune by iteratively running climate simulations with hand-picked values of tuning parameters. Many, in both the statistical and climate literature, have proposed alternative calibration methods, but most are impractical or difficult to implement. We present a practical, robust, and rigorous calibration approach on the atmosphere-only model of the Department of Energy's Energy Exascale Earth System Model (E3SM) version 2. Our approach can be summarized into two main parts: (a) the training of a surrogate that predicts E3SM output in a fraction of the time compared to running E3SM, and (b) gradient-based parameter optimization. To train the surrogate, we generate a set of designed ensemble runs that span our input parameter space and use polynomial chaos expansions on a reduced output space to fit the E3SM output. We use this surrogate in an optimization scheme to identify values of the input parameters for which our model best matches gridded spatial fields of climate observations. To validate our choice of parameters, we run E3SMv2 with the optimal parameter values and compare prediction results to expertly-tuned simulations across 45 different output fields. This flexible, robust, and automated approach is straightforward to implement, and we demonstrate that the resulting model output matches present day climate observations as well or better than the corresponding output from expert tuned parameter values, while considering high-dimensional output and operating in a fraction of the time.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Roberts, Yolanda↗
NASA NTRS2006

Offshore Radiation Observations for Climate Research at the CERES Ocean Validation Experiment

When radiometers on a satellite are pointed towards the planet with the goal of understanding a phenomenon quantitatively, rather than just creating a pleasing image, the task at hand is often problematic. The signal at the detector can be affected by scattering, absorption, and emission; and these can be due to atmospheric constituents (gases, clouds, and aerosols), the earth's surface, and subsurface features. When targeting surface phenomena, the remote sensing algorithm needs to account for the radiation associated with the atmospheric constituents. Likewise, one needs to correct for the radiation leaving the surface, when atmospheric phenomena are of interest. Rigorous validation of such remote sensing products is a real challenge. In visible and near infrared wavelengths, the jumble of effects on atmospheric radiation are best accomplished over dark surfaces with fairly uniform reflective properties (spatial homogeneity) in the satellite instrument's field of view (FOV). The ocean's surface meets this criteria; land surfaces - which are brighter, more spatially inhomogeneous, and more changeable with time - generally do not. NASA's Clouds and the Earth's Radiant Energy System (CERES) project has used this backdrop to establish a radiation monitoring site in Virginia's coastal Atlantic Ocean. The project, called the CERES Ocean Validation Experiment (COVE), is located on a rigid ocean platform allowing the accurate measurement of radiation parameters that require precise leveling and pointing unavailable from ships or buoys. The COVE site is an optimal location for verifying radiative transfer models and remote sensing algorithms used in climate research; because of the platform's small size, there are no island wake effects; and suites of sensors can be simultaneously trained both on the sky and directly on ocean itself. This paper describes the site, the types of measurements made, multiple years of atmospheric and ocean surface radiation observations, and satellite validation results.

Rutledge, Charles K.↗
NASA NTRS2010

Solar Radiation Transport in the Cloudy Atmosphere: A 3D Perspective on Observations and Climate Impacts

The interplay of sunlight with clouds is a ubiquitous and often pleasant visual experience, but it conjures up major challenges for weather, climate, environmental science and beyond. Those engaged in the characterization of clouds (and the clear air nearby) by remote sensing methods are even more confronted. The problem comes, on the one hand, from the spatial complexity of real clouds and, on the other hand, from the dominance of multiple scattering in the radiation transport. The former ingredient contrasts sharply with the still popular representation of clouds as homogeneous plane-parallel slabs for the purposes of radiative transfer computations. In typical cloud scenes the opposite asymptotic transport regimes of diffusion and ballistic propagation coexist. We survey the three-dimensional (3D) atmospheric radiative transfer literature over the past 50 years and identify three concurrent and intertwining thrusts: first, how to assess the damage (bias) caused by 3D effects in the operational 1D radiative transfer models? Second, how to mitigate this damage? Finally, can we exploit 3D radiative transfer phenomena to innovate observation methods and technologies? We quickly realize that the smallest scale resolved computationally or observationally may be artificial but is nonetheless a key quantity that separates the 3D radiative transfer solutions into two broad and complementary classes: stochastic and deterministic. Both approaches draw on classic and contemporary statistical, mathematical and computational physics.

Davis, Anthony B.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-20735-DND

Higher than normal accuracy is required to rigorously observe decadal climate change. But what level is needed? How can this be quantified? This presentation will summarize a new more rigorous and quantitative approach to determining the required accuracy for climate change observations (Wielicki et al., 2013, BAMS). Most current global satellite observations cannot meet this accuracy level. A proposed new satellite mission to resolve this challenge is CLARREO (Climate Absolute Radiance and Refractivity Observatory). CLARREO is designed to achieve advances of a factor of 10 for reflected solar spectra and a factor of 3 to 5 for thermal infrared spectra (Wielicki et al., Oct. 2013 BAMS). The CLARREO spectrometers are designed to serve as SI traceable benchmarks for the Global Satellite Intercalibration System (GSICS) and to greatly improve the utility of a wide range of LEO and GEO infrared and reflected solar passive satellite sensors for climate change observations (e.g. CERES, MODIS, VIIIRS, CrIS, IASI, Landsat, SPOT, etc). Providing more accurate decadal change trends can in turn lead to more rapid narrowing of key climate science uncertainties such as cloud feedback and climate sensitivity. A study has been carried out to quantify the economic benefits of such an advance as part of a rigorous and complete climate observing system. The study concludes that the economic value is ~ $12 Trillion U.S. dollars in Net Present Value for a nominal discount rate of 3% (Cooke et al. 2013, J. Env. Sys. Dec.). A brief summary of these two studies and their implications for the future of climate science will be presented.

Bruce Wielicki↗
DOE OSTI2021

Combining artificial intelligence, Earth observations, and climate models to improve predictability of ice-biogeochemistry interactions

Focal Area: Predictive Modeling. We describe how artificial intelligence (AI) can be combined with state-of-the-science Earth system models to better predict future regional climate responses. To demonstrate, we describe a case study in biogeochemical interactions with sea ice. Science Challenge: Biogeochemical models are poorly constrained for high latitude systems. Machine learning methods and edge computing can be combined with Earth system models, such as the Energy Exascale Earth System Model (E3SM), to gain insight into ice-biogeochemical interactions and improve sea ice extent prediction.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Aerosol observations for climate studies

The Stratospheric Aerosol Measurement II and Stratospheric Aerosol and Gas Experiment satellite systems have provided to date more than five years and almost three years, respectively, of data on atmospheric aerosol profiles on a near-global scale. Studies with these unique data sets are developing a global aerosol climatology for the first time and have shown the existence and quantification of polar stratospheric clouds and tropical stratospheric cirrus. In addition, a tropospheric cirrus climatology is evolving. Since these two experiments were launched, a series of large volcanic eruptions have occurred which have greatly impacted the stratospheric aerosol loading. The aerosol layer produced by the eruption of El Chichon, for example, increased the 30 mb temperatures in the northern tropics by as much as 4 C for six months after the eruption. This paper describes in detail, from a climate perspective, the evolving aerosol and cloud climatologies as a function of space and time, and shows the stratospheric dynamics of volcanic injections and their enhancements on stratospheric optical depth and mass loading.

Mccormick, M. P.↗
NASA NTRS1995

Workshop on Satellite and In situ Observations for Climate Prediction

Participants in this workshop, which convened in Venice, Italy, 6-8 May 1993, met to consider the current state of climate monitoring programs and instrumentation for the purpose of climatological prediction on short-term (seasonal to interannual) timescales. Data quality and coverage requirements for definition of oceanographic heat and momentum fluxes, scales of inter- and intra-annual variability, and land-ocean-atmosphere exchange processes were examined. Advantages and disadvantages of earth-based and spaceborne monitoring systems were considered, as were the structures for future monitoring networks, research programs, and modeling studies.

Acker, James G.↗
NASA NTRS2016

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

uncertainty↗