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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Data management support for selected climate data sets using the climate data access system

The functional capabilities of the Goddard Space Flight Center (GSFC) Climate Data Access System (CDAS), an interactive data storage and retrieval system, and the archival data sets which this system manages are discussed. The CDAS manages several climate-related data sets, such as the First Global Atmospheric Research Program (GARP) Global Experiment (FGGE) Level 2-b and Level 3-a data tapes. CDAS data management support consists of three basic functions: (1) an inventory capability which allows users to search or update a disk-resident inventory describing the contents of each tape in a data set, (2) a capability to depict graphically the spatial coverage of a tape in a data set, and (3) a data set selection capability which allows users to extract portions of a data set using criteria such as time, location, and data source/parameter and output the data to tape, user terminal, or system printer. This report includes figures that illustrate menu displays and output listings for each CDAS function.

Reph, M. G.↗
NASA NTRS1992

Uncertainties in climate data sets

Climate diagnostics are constructed from either analyzed fields or from observational data sets. Those that have been commonly used are normally considered ground truth. However, in most of these collections, errors and uncertainties exist which are generally ignored due to the consistency of usage over time. Examples of uncertainties and errors are described in NMC and ECMWF analyses and in satellite observational sets-OLR, TOVS, and SMMR. It is suggested that these errors can be large, systematic, and not negligible in climate analysis.

Mcguirk, James P.↗
DOE OSTI2014

Parallel analysis tools and new visualization techniques for ultra-large climate data set

ParVis was a project funded under LAB 10-05: “Earth System Modeling: Advanced Scientific Visualization of Ultra-Large Climate Data Sets”. Argonne was the lead lab with partners at PNNL, SNL, NCAR and UC-Davis. This report covers progress from January 1st, 2013 through Dec 1st, 2014. Two previous reports covered the period from Summer, 2010, through September 2011 and October 2011 through December 2012, respectively. While the project was originally planned to end on April 30, 2013, personnel and priority changes allowed many of the institutions to continue work through FY14 using existing funds. A primary focus of ParVis was introducing parallelism to climate model analysis to greatly reduce the time-to-visualization for ultra-large climate data sets. Work in the first two years was conducted on two tracks with different time horizons: one track to provide immediate help to climate scientists already struggling to apply their analysis to existing large data sets and another focused on building a new data-parallel library and tool for climate analysis and visualization that will give the field a platform for performing analysis and visualization on ultra-large datasets for the foreseeable future. In the final 2 years of the project, we focused mostly on the new data-parallel library and associated tools for climate analysis and visualization.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Information Theoretic Approaches to Rapid Discovery of Relationships in Large Climate Data Sets

Mutual information as the asymptotic Bayesian measure of independence is an excellent starting point for investigating the existence of possible relationships among climate-relevant variables in large data sets, As mutual information is a nonlinear function of of its arguments, it is not beholden to the assumption of a linear relationship between the variables in question and can reveal features missed in linear correlation analyses. However, as mutual information is symmetric in its arguments, it only has the ability to reveal the probability that two variables are related. it provides no information as to how they are related; specifically, causal interactions or a relation based on a common cause cannot be detected. For this reason we also investigate the utility of a related quantity called the transfer entropy. The transfer entropy can be written as a difference between mutual informations and has the capability to reveal whether and how the variables are causally related. The application of these information theoretic measures is rested on some familiar examples using data from the International Satellite Cloud Climatology Project (ISCCP) to identify relation between global cloud cover and other variables, including equatorial pacific sea surface temperature (SST), over seasonal and El Nino Southern Oscillation (ENSO) cycles.

Knuth, Kevin H.↗
NASA NTRS1987

Nimbus 7 earth radiation budget wide field of view climate data set improvement. II - Deconvolution of earth radiation budget products and consideration of 1982-1983 El Nino event

A deconvolution technique is employed that permits recovery of daily averaged earth radiation budget (ERB) parameters at the top of the atmosphere from a set of the Nimbus 7 ERB wide field of view (WFOV) measurements. Improvements in both the spatial resolution of the resultant fields and in the fidelity of the time averages is obtained. The algorithm is evaluated on a set of months during the period 1980-1983. The albedo, outgoing long-wave radiation, and net radiation parameters are analyzed. The amplitude and phase of the quasi-stationary patterns that appear in the spatially deconvolved fields describe the radiation budget components for 'normal' as well as the El Nino/Southern Oscillation (ENSO) episode years. They delineate the seasonal development of large-scale features inherent in the earth's radiation budget as well as the natural variability of interannual differences. These features are underscored by the powerful emergence of the 1982-1983 ENSO event in the fields displayed. The conclusion is that with this type of resolution enhancement, WFOV radiometers provide a useful tool for the observation of the contemporary climate and its variability.

Ardanuy, Phillip E.↗
NASA NTRS1986

Defining the minimum temporal and spatial scales available from a new 72-month Nimbus-7 Earth Radiation Budget climate data set

Scale factors and assumptions which were applied in calculations of global radiation budget parameters based on ERB data are discussed. The study was performed to examine the relationship between the composite global ERB map that can be generated every six days using all available data and the actual average global ERB. The wide field of view ERB instrument functioned for the first 19 months of the Nimbus-7 life, and furnished sufficient data for calculating actual ERB averages. The composite was most accurate in regions with the least variation in radiation budget.

Randel, D. L.↗
NASA NTRS1987

Nimbus 7 earth radiation budget wide field of view climate data set improvement. I - The earth albedo from deconvolution of shortwave measurements

A deconvolution method for extracting the top of the atmosphere (TOA) mean, daily albedo field from a set of wide-FOV (WFOV) shortwave radiometer measurements is proposed. The method is based on constructing a synthetic measurement for each satellite observation. The albedo field is represented as a truncated series of spherical harmonic functions, and these linear equations are presented. Simulation studies were conducted to determine the sensitivity of the method. It is observed that a maximum of about 289 pieces of data can be extracted from a set of Nimbus 7 WFOV satellite measurements. The albedos derived using the deconvolution method are compared with albedos derived using the WFOV archival method; the developed albedo field achieved a 20 percent reduction in the global rms regional reflected flux density errors. The deconvolution method is applied to estimate the mean, daily average TOA albedo field for January 1983. A strong and extensive albedo maximum (0.42), which corresponds to the El Nino/Southern Oscillation event of 1982-1983, is detected over the south central Pacific Ocean.

Hucek, Richard R.↗
DOE OSTI2018

Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon–Cerrado border

Abstract. Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest–savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon–Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961–1990 and interannual climate variability for 1948–2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. Furthermore, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon–Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessment of Storm-Associated Precipitation and Its Extremes Using Observational Data Sets and Climate Model Short-Range Hindcasts

Heavy precipitation, often associated with weather phenomena such as tropical cyclones, extratropical cyclones (ETCs), atmospheric rivers (ARs), and mesoscale convective systems (MCSs), can cause significant socio-economic loss. Here, in this study, we apply atmospheric feature trackers to quantify the contributions of these storm types in observational data sets and climate model short-range hindcasts. We generate a global hourly storm data set at 0.25° spatial resolution covering 2006–2020, based on the tracking results from TempestExtremes and Python FLEXible object TRacKeR. Our analyses show that these four storm types account for 67% of global annual mean precipitation and 82% of top 1% precipitation extremes, with MCSs mainly over the tropics, and ARs and ETCs over the midlatitudes. The percentage of precipitation contributions from these storms also show strong seasonality over many geographical locations. We further apply the tracking results to the Energy Exascale Earth System Model (E3SM) short-range hindcasts and evaluate how well these storms are simulated. The evaluation show that E3SM, with ∼1° resolution, significantly underestimates storm-associated precipitation totals and extremes, especially for MCSs in the tropics. Our analysis also suggests that model fails to capture the correct mean diurnal phases and amplitude of MCS precipitation. This phenomenon-based approach provides a better understanding of precipitation characteristics and can lead to enhanced model evaluation by revealing underlying problems in model physics related to precipitation processes associated with the heavy-precipitating storms.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Seasonal Correlations of SST, Water Vapor, and Convective Activity in Tropical Oceans: A New Hyperspectral Data Set for Climate Model Testing

The analysis of the response of the Earth Climate System to the seasonal changes of solar forcing in the tropical oceans using four years of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) data between 2002 and 2006 gives new insight into amplitude and phase relationships between surface and tropospheric temperatures, humidity, and convective activity. The intensity of the convective activity is measured by counting deep convective clouds. The peaks of convective activity, temperature in the mid-troposphere, and water vapor in the 0 - 30 N and 0 - 30 S tropical ocean zonal means occur about two months after solstice, all leading the peak of the sea surface temperature by several weeks. Phase is key to the evaluation of feedback. The evaluation of climate models in terms of zonal and annual means and annual mean deviations from zonal means can now be supplemented by evaluating the phase of key atmospheric and surface parameters relative to solstice. The ability of climate models to reproduce the statistical flavor of the observed amplitudes and relative phases for broad zonal means should lead to increased confidence in the realism of their water vapor and cloud feedback algorithms. AIRS and AMSU were launched into a 705 km altitude polar sun-synchronous orbit on the EOS Aqua spacecraft on May 4, 2002, and have been in routine data gathering mode since September 2002.

Atmospheric Infrared Sounder↗
NASA NTRS2015

Results from CrIS/ATMS Obtained Using an "AIRS Version-6 Like" Retrieval Algorithm

A main objective of AIRS/AMSU on EOS is to provide accurate sounding products that are used to generate climate data sets. Suomi NPP carries CrIS/ATMS that were designed as follow-ons to AIRS/AMSU. Our objective is to generate a long term climate data set of products derived from CrIS/ATMS to serve as a continuation of the AIRS/AMSU products. We have modified an improved version of the operational AIRS Version-6 retrieval algorithm for use with CrIS/ATMS. CrIS/ATMS products are of very good quality, and are comparable to, and consistent with, those of AIRS.

Retrieval methodology↗
NASA NTRS2015

CrIS/ATMS Retrievals Using the Latest AIRS/AMSU Retrieval Methodology

This research is being done under the NPP Science Team Proposal: Analysis of CrISATMS Using an AIRS Version 6-like Retrieval Algorithm Objective: Generate a long term CrISATMS level-3 data set that is consistent with that of AIRSAMSU Approach: Adapt the currently operational AIRS Science Team Version-6 Retrieval Algorithm, or an improved version of it, for use with CrISATMS data. Metric: Generate monthly mean level-3 CrISATMS climate data sets and evaluate the results by comparison of monthly mean AIRSAMSU and CrISATMS products, and more significantly, their inter-annual differences and, eventually, anomaly time series. The goal is consistency between the AIRSAMSU and CrISATMS climate data sets.

Retrieval Methodology↗
NASA NTRS2000

A Sea-Surface Radiation Data Set for Climate Applications in the Tropical Western Pacific and South China Sea

The sea-surface shortwave and longwave radiative fluxes have been retrieved from the radiances measured by Japan's Geostationary Meteorological Satellite 5. The surface radiation data set covers the domain 40S-40N and 90E-170W. The temporal resolution is 1 day, and the spatial resolution is 0.5 deg x 0.5 deg latitude-longitude. The retrieved surface radiation have been validated with the radiometric measurements at the Atmospheric Radiation Measuring (ARM) site on Manus island in the equatorial western Pacific for a period of 15 months. It has also been validated with the measurements at the radiation site on Dungsha island in the South China Sea during the South China Sea Monsoon Experiment (SCSMEX) Intensive Observing Period (May and June 1998). The data set is used to study the effect of El Nino and East Asian Summer monsoon on the heating of the ocean in the tropical western Pacific and the South China Sea. Interannual variations of clouds associated with El Nino and the East Asian Summer monsoon have a large impact on the radiative heating of the ocean. It has been found that the magnitude of the interannual variation of the seasonal mean surface radiative heating exceeds 40 W/sq m over large areas. Together with the Clouds and the Earth's Radiant Energy System (CERES) shortwave fluxes at top of the atmosphere and the radiative transfer calculations of clear-sky fluxes, this surface radiation data set is also used to study the impact of clouds on the solar heating of the atmosphere. It is found that clouds enhance the atmospheric solar heating by approx. 20 W/sq m in the tropical western Pacific and the South China Sea. This result is important for evaluating the accuracy of solar flux calculations in clear and cloudy atmospheres.

Chou, Ming-Dah↗
NASA NTRS2007

Seasonal Correlations of SST, Water Vapor, and Convective Activity in Tropical Oceans: A New Hyperspectral Data Set for Climate Model Testing

The analysis of the response of the Earth Climate System to the seasonal changes of solar forcing in the tropical oceans using four years of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) data between 2002 and 2006 gives new insight into amplitude and phase relationships between surface and tropospheric temperatures, humidity, and convective activity. The intensity of the convective activity is measured by counting deep convective clouds. The peaks of convective activity, temperature in the mid-troposphere, and water vapor in the 0-30 N and 0-30 S tropical ocean zonal means occur about two months after solstice, all leading the peak of the sea surface temperature by several weeks. Phase is key to the evaluation of feedback. The evaluation of climate models in terms of zonal and annual means and annual mean deviations from zonal means can now be supplemented by evaluating the phase of key atmospheric and surface parameters relative to solstice. The ability of climate models to reproduce the statistical flavor of the observed amplitudes and relative phases for broad zonal means should lead to increased confidence in the realism of their water vapor and cloud feedback algorithms. AIRS and AMSU were launched into a 705 km altitude polar sun-synchronous orbit on the EOS Aqua spacecraft on May 4, 2002, and have been in routine data gathering mode since September 2002.

Atmospheric Infrared Sounder (AIRS)↗
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↗
DOE OSTI2024

Statistical Downscaling of Climate Models for Solar Resource Assessment

This study presents the development of statistical models to efficiently downscale future projections of solar irradiance for solar energy applications. A climate data set simulated from a Regional Climate Model (RCM) obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) is selected as input to the statistical models to create high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). Our approach builds statistical downscaling models that (1) regrid RCM data (0.22 degree and daily spatiotemporal resolution), (2) correct bias of GHI projections, (3) downscale the future GHI project from daily-scale to hourly-scale, and (4) spatially downscale to generate GHI at 8-km resolution. To calibrate and validate the statistical models, we adapt and use the National Solar Radiation Database (NSRDB). Preliminary results show that the statistical downscaling approach downscales future projections of GHI under two climate scenarios (RCP4.5 and RCP8.5) with a nBIAS of 3%, nMAE of 34% and nRMSE of 46% estimated against NSRDB for the contiguous United State. This presentation will summarize the implemented methodology and validation results as well as future extension of this research.

climate data↗
NASA NTRS2011

NASA's Global Change Master Directory: Discover and Access Earth Science Data Sets, Related Data Services, and Climate Diagnostics

NASA's Global Change Master Directory provides the scientific community with the ability to discover, access, and use Earth science data, data-related services, and climate diagnostics worldwide. The GCMD offers descriptions of Earth science data sets using the Directory Interchange Format (DIF) metadata standard; Earth science related data services are described using the Service Entry Resource Format (SERF); and climate visualizations are described using the Climate Diagnostic (CD) standard. The DIF, SERF and CD standards each capture data attributes used to determine whether a data set, service, or climate visualization is relevant to a user's needs. Metadata fields include: title, summary, science keywords, service keywords, data center, data set citation, personnel, instrument, platform, quality, related URL, temporal and spatial coverage, data resolution and distribution information. In addition, nine valuable sets of controlled vocabularies have been developed to assist users in normalizing the search for data descriptions. An update to the GCMD's search functionality is planned to further capitalize on the controlled vocabularies during database queries. By implementing a dynamic keyword "tree", users will have the ability to search for data sets by combining keywords in new ways. This will allow users to conduct more relevant and efficient database searches to support the free exchange and re-use of Earth science data. http://gcmd.nasa.gov/

Aleman, Alicia↗
NASA NTRS2013

Results from CrIS-ATMS Obtained Using the AIRS Science Team Retrieval Methodology

AIRS was launched on EOS Aqua in May 2002, together with AMSU-A and HSB (which subsequently failed early in the mission), to form a next generation polar orbiting infrared and microwave atmospheric sounding system. AIRS/AMSU had two primary objectives. The first objective was to provide real-time data products available for use by the operational Numerical Weather Prediction Centers in a data assimilation mode to improve the skill of their subsequent forecasts. The second objective was to provide accurate unbiased sounding products with good spatial coverage that are used to generate stable multi-year climate data sets to study the earth's interannual variability, climate processes, and possibly long-term trends. AIRS/AMSU data for all time periods are now being processed using the state of the art AIRS Science Team Version-6 retrieval methodology. The Suomi-NPP mission was launched in October 2011 as part of a sequence of Low Earth Orbiting satellite missions under the "Joint Polar Satellite System" (JPSS). NPP carries CrIS and ATMS, which are advanced infra-red and microwave atmospheric sounders that were designed as follow-ons to the AIRS and AMSU instruments. The main objective of this work is to assess whether CrIS/ATMS will be an adequate replacement for AIRS/AMSU from the perspective of the generation of accurate and consistent long term climate data records, or if improved instruments should be developed for future flight. It is critical for CrIS/ATMS to be processed using an algorithm similar to, or at least comparable to, AIRS Version-6 before such an assessment can be made. We have been conducting research to optimize products derived from CrIS/ATMS observations using a scientific approach analogous to the AIRS Version-6 retrieval algorithm. Our latest research uses Version-5.70 of the CrIS/ATMS retrieval algorithm, which is otherwise analogous to AIRS Version-6, but does not yet contain the benefit of use of a Neural-Net first guess start-up system which significantly improved results of AIRS Version-6. Version-5.70 CrIS/ATMS temperature profile and surface skin temperature retrievals are of very good quality, and are better than AIRS Version-5 retrievals, but are still significantly poorer than those of AIRS Version-6. CrIS/ATMS retrievals should improve when a Neural-Net start-up system is ready for use. We also examined CrIS/ATMS retrievals generated by NOAA using their NUCAPS retrieval algorithm, which is based on earlier versions of the AIRS Science Team retrieval algorithms. We show that the NUCAPS algorithm as currently configured is not well suited for climate monitoring purposes.

CrIS↗