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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 55 records · Page 3
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NASA NTRS2011

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

Kim, Edward↗
NASA NTRS1987

The correspondence of surface climate parameters with satellite and terrain data

One of the goals of the research was to develop a ground sampling stragegy for calibrating remotely sensed measurements of surface climate parameters. The initial sampling strategy involved the stratification of the terrain based on important ancillary surface variables such as slope, exposure, insolation, geology, drainage, fire history, etc. For a spatially heterogeneous population, sampling error is reduced and efficiency increased by stratification of the landscape into more homogeneous sub-areas and by employing periodic random spacing of samples. These concepts were applied in the initial stratification of the study site for the purpose of locating and allocating instrumentation.

Dozier, Jeff↗
NASA NTRSDate not supplied

A Spectral Fingerprinting Method for Deriving Consistent Climate Data Records from Multiple Satellite IR Sounders

Deriving Climate Data Records (CDRs) from multiple IR sounders such AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C requires from current operational products are challenging due to different radiative transfer models and retireavl algorithms used for processing level 2 data. We developed a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm, which uses a single set of radiative kernels a robust spectral fingerprinting method to performs retrievals using spatiotemporally averaged L1 hyperspectral radiances directly. The ClimFiSP algorithm provides accurate data fusion CDR products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. We plan to add IASI to the CDR data set in the future. The ClimFiSP is being transitioned to NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRS1981

A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect

A climatological model/variable termed the sponge (a measure of moisture availability based on daily temperature maxima and minima, and precipitation) was tested for potential biogeograhic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic form, suggest that, as generalized climatic index, sponge is particularly appropriate for large-area and global vegetation monitoring. The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge and AVHRR data was initiated. Along an east-west Texas gradient, vegetation, sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values along the Texas gradient suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.

Greegor, D.↗
NASA NTRS1981

A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect

A new experimental climatological model/variable termed the sponge, a measure of moisture availability based on daily temperature maxima and minima and precipitation, is tested for potential biogeographic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic from, suggest that, as a generalized climatic index, sponge's simplicity and sensitivity make particularly appropriate for trans-regional biogeographic studies (e.g., large-area and global vegetation monitoring). The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.

Greegor, D. H.↗
NASA NTRS1978

The earth radiation budget satellite system for climate research

The mission implications of providing earth radiation budget data for climate studies have been thoroughly studied. The results of these studies indicate the need for a multisensor, multisatellite system consisting of high and midinclination orbits. To meet this need, NASA and NOAA are planning a joint Earth Radiation Budget Satellite System (ERBSS) composed of instruments on two of NOAA's near-polar Sun-synchronous TIROS-N/NOAA A through G series of operational satellites and on an NASA midinclination satellite of the Applications Explorer Mission (AEM) type referred to as ERBS-A/AEM. This paper describes the scientific objectives of ERBSS, the associated data analysis methods, mission analysis (sampling), and instrument definition.

Woerner, C. V.↗
NASA NTRS2011

Estimating Contrail Climate Effects from Satellite Data

An automated contrail detection algorithm (CDA) is developed to exploit six of the infrared channels on the 1-km MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites. The CDA is refined and balanced using visual error analysis. It is applied to MODIS data taken by Terra and Aqua over the United States during 2006 and 2008. The results are consistent with flight track data, but differ markedly from earlier analyses. Contrail coverage is a factor of 4 less than other retrievals and the retrieved contrail optical depths and radiative forcing are smaller by approx.30%. The discrepancies appear to be due to the inability to detect wider, older contrails that comprise a significant amount of the contrail coverage. An example of applying the algorithm to MODIS data over the entire Northern Hemisphere is also presented. Overestimates of contrail coverage are apparent in some tropical regions. Methods for improving the algorithm are discussed and are to be implemented before analyzing large amounts of Northern Hemisphere data. The results should be valuable for guiding and validating climate models seeking to account for aviation effects on climate.

Minnis, Patrick↗
NASA NTRS1988

Assessment of polar climate change using satellite technology

Using results of selected studies, this paper highlights some of the problems that exist in the remote sensing of snow and ice, and demonstrates the importance of remote sensing for the study of snow and ice in determining the effect of temperature increase, due to the atmospheric CO2 increase, on the cryospheric features. Evidence obtained from NOAA, Nimbus, and other satellites, that may already indicate a global or at least a regional warming, includes an increase in permafrost temperature in northern Alaska and the retreat of many of the world's small glaciers in the last 100 years. It is emphasized that remote sensing is of major importance as the method of obtaining data for monitoring future changes in cryospheric features.

Hall, Dorothy K.↗
NASA NTRS2004

Lagrangian Assimilation of Satellite Data for Climate Studies in the Arctic

Under this grant we have developed and tested a new Lagrangian model of sea ice. A Lagrangian model keeps track of material parcels as they drift in the model domain. Besides providing a natural framework for the assimilation of Lagrangian data, it has other advantages: 1) a model that follows material elements is well suited for a medium such as sea ice in which an element retains its identity for a long period of time; 2) model cells can be added or dropped as needed, allowing the spatial resolution to be increased in areas of high variability or dense observations; 3) ice from particular regions, such as the marginal seas, can be marked and traced for a long time; and 4) slip lines in the ice motion are accommodated more naturally because there is no internal grid. Our work makes use of these strengths of the Lagrangian formulation.

Lindsay, Ronald W.↗
NASA NTRS2011

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly Terra MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid within +/-3 hours of 17:00Z or 2:00 PM Local Solar Time. Preliminary validation of the ISTs at Summit Camp, Greenland, during the 2008-09 winter, shows that there is a cold bias using the MODIS IST which underestimates the measured surface temperature by approximately 3 C when temperatures range from approximately -50 C to approximately -35 C. The ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present. Differences in the APP and MODIS cloud masks have so far precluded the current IST records from spanning both the APP and MODIS IST time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The Greenland IST climate-quality data record is suitable for continuation using future Visible Infrared Imager Radiometer Suite (VIIRS) data and will be elevated in status to a CDR when at least 9 more years of climate-quality data become available either from MODIS Terra or Aqua, or from the VIIRS. The complete MODIS IST data record will be available online in the summer of 2011.

Hall, Dorothy K.↗
NASA NTRS2011

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

Zhang, Ping↗
NASA NTRS2012

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

Hall, Dorothy K.↗