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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 NTRS2016

Complex Signal Kurtosis and Independent Component Analysis for Wideband Radio Frequency Interference Detection

Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

microwave↗
NASA NTRS2022

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗
NASA NTRS1992

Numerical sensitivity analysis of passive EHF and SMMW channels to tropospheric water vapor, clouds, and precipitation

Potential uses of specific extremely High Frequency (EHF) and Sub-Millimeter-Wave (SMMW) channels at 90, 166, 183, 220, 325, 340, and 410 GHz for passive spaceborne remote sensing of the troposphere and lower stratosphere are investigated using an iterative numerical radiative transfer model. Collectively, these channels offer potential for high spatial resolution imaging using diffraction-limited apertures of practical size, along with the ability to profile water vapor, map precipitation beneath optically opaque cloud cover, and to measure nonprecipitating cloud (e.g., cirrus) parameters. A widely-spaced set of EHF and SMMW channels can yield observable degrees of freedom related to clouds and precipitation not available by exclusively using the more thoroughly studied microwave channels below 183 GHz. A new passive airborne imaging instrument for tropospheric meteorological sensing is described.

Gasiewski, A. J.↗
NASA NTRS1982

Microwave remote sensing of soil moisture, volume 1

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

Mcfarland, M. J.↗
NASA NTRS1973

Microwave signatures of first-year and multiyear sea ice.

A combination of remote sensing from an aircraft and simultaneous surface measurements have confirmed the feasibility of identifying old and new sea ice according to its emission of thermal radiation at wavelengths between 0.3 and 3 cm. Emissivity of first-year thick ice with a surface temperature of about 260 K is 0.95 or greater for wavelengths between 0.81 and 11 cm; the emissivity of multiyear ice is 0.8 at 0.81 cm and 0.95 at 11 cm, increasing monotonically in this wavelength interval. The ease with which multiyear ice can be distinguished from first-year ice using a passive microwave radiometer is demonstrated by comparing mosaics prepared both from photographs and images of 1.55-cm radiation.

Gloersen, P.↗
NASA NTRS2007

NASA's Potential Contributions to Avalanche Forecasting Using Active and Passive Microwave Measurements

This Candidate Solution is based on using active and passive microwave measurements acquired from NASA satellites to improve USDA (U.S. Department of Agriculture) Forest Service forecasting of avalanche danger. Regional Avalanche Centers prepare avalanche forecasts using ground measurements of snowpack and mountain weather conditions. In this Solution, range of the in situ observations is extended by adding remote sensing measurements of snow depth, snow water equivalent, and snowfall rate acquired by satellite missions that include Aqua, CloudSat, future GPM (Global Precipitation Measurement), and the proposed SCLP (Snow and Cold Land Processes). Measurements of snowpack conditions and time evolution are improved by combining the in situ and satellite observations with a snow model. Recurring snow observations from NASA satellites increase accuracy of avalanche forecasting, which helps the public and the managers of public facilities make better avalanche safety decisions.

Blonski, Slawomir↗
NASA NTRS2016

Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring

Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.

SMOS↗
NASA NTRS1972

Microwave signatures of first-year and multiyear sea ice

A combination of remote sensing from an aircraft and simultaneous surface measurements have confirmed the feasibility of identifying old and new sea ice according to its emission of thermal radiation at wavelengths between 0.3 and 3 cm. Emissivity of first-year thick ice with a surface temperature of about 260 K is 0.95 or greater for wavelengths between 0.81 and 11 cm; the emissivity of multiyear ice is 0.8 at 0.81 cm and 0.95 at 11 cm, increasing monotonically in this wave length interval. The ease with which multiyear ice can be distinguished from first-year ice using a passive microwave radiometer is demonstrated by comparing mosaics prepared both from photographs and images of 1.55 cm radiation.

Gloersen, P.↗
NASA NTRS2001

The Role of Combination Techniques in Maximizing the Utility of Precipitation Estimates from Several Multi-Purpose Remote-Sensing Systems

Multi-purpose remote-sensing products from various satellites have proved crucial in developing global estimates of precipitation. Examples of these products include low-earth-orbit and geosynchronous-orbit infrared (leo- and geo-IR), Outgoing Longwave Radiation (OLR), Television Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) data, and passive microwave data such as that from the Special Sensor Microwave/ Imager (SSM/I). Each of these datasets has served as the basis for at least one useful quasi-global precipitation estimation algorithm; however, the quality of estimates varies tremendously among the algorithms for the different climatic regions around the globe.

Huffman, George J.↗
NASA NTRS2003

Satellite Detection of Precipitation over the North Pacific

Intense extratropical winter cyclones often impact the West Coast of North America with strong winds and heavy precipitation. Several times during a winter season, short-term forecasts (24 - 48 hours) of these storms are seriously deficient with central pressure errors in the 10's of hPa and surface low position errors in the 100's of km. For example, 48-hr sea level pressure errors (forecast - observation) at buoy 46005 off the Oregon coast for the 2001 - 2002 winter season is plotted. In addition, two times the standard deviation (determined from pressure errors from the last four winter seasons) are also shown. It is evident from this figure that large forecast errors (i.e. greater than 10 hPa) occurred about 10 times this past winter at buoy 46005 with three events where the errors were 20 hPa. Beside large forecast errors of sea level pressure, numerical forecasts of precipitation for land falling cyclones can also be flawed. This is due in large part to the lack of accurate precipitation information over the ocean. Therefore, remote sensing techniques are the only viable option for obtaining accurate information on the distribution and intensity of precipitation over the North Pacific. Due to the radiative characteristics of precipitation sized hydrometeors at microwave frequencies, microwave sensors are able to detect precipitation over oceanic regions. Past studies have demonstrated the utility of passive microwave rainrate data for locating intense rainfall in rapidly deepening cyclones, in detecting developing polar mesocyclones and in determining frontal bands. There are currently many sources of microwave rainrate data: the Special Sensor Microwave Imager (SSM/I) (currently flying on three platforms), the Advanced Microwave Sounding Unit (AMSU-B) (currently flying on NOAA-15, NOAA-16, and NOAA-17), and the Tropical Rainfall Measuring Mission Microwave Imager (TMI). Data will soon be available from the Advanced Microwave Radiometer-EOS (AMSR-E) on the Aqua platform. In this paper, we present a new technique for mapping rainrate distributions over the North Pacific utilizing rainrate estimates from several microwave sensors and upper-tropospheric winds derived from geosynchronous satellite IR data. The goal of this work is to develop a way to obtain high temporal and spatial rainfall information over the North Pacific. This information will be used to support the verification of model derived precipitation distributions and to support the analysis of in situ measurements of rainfall during the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE) field campaigns.

Smith, Jeremy↗
NASA NTRS2016

RFI Detection and Mitigation using Independent Component Analysis as a Pre-Processor

Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Soil Moisture and Ocean Salinity (SMOS), Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

independent component analysis↗
NASA NTRS1989

Instrument description of the airborne microwave temperature profiler

The microwave temperature profiler (MTP) is a passive microwave radiometer installed in the NASA ER-2 aircraft and used to measure profiles of air temperature versus altitude. It operates at 57.3 and 58.8 GHz, where oxygen molecules emit thermal radiation. Brightness temperature is measured at a selection of viewing elevation angles every 14 s. MTP was the only remote sensing experiment aboard the ER-2 during the Airborne Antarctic Ozone Experiment. This paper describes hardware, calibration, and performance aspects of the MTP.

Denning, Richard F.↗
NASA NTRS1982

Multifrequency remote sensing of soil moisture

Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.

Theis, S. W.↗
NASA NTRS1986

The first International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment - FIFE

The International Satellite Land Surface Climatology Project (ISLSCP) will verify the use of satellite data for the estimation of land-surface properties through field experiments using point measurements on the ground and areal measurements from aircraft overflights. It will study approaches for obtaining areal averages of the radiation, moisture, and heat fluxes made using remotely sensed data, by combining the surface point measurements of the fluxes with the aircraft areal observations using a surface energy balance model. Surface parameters to be estimated from aircraft observations include: surface radiation temperature, albedo, land cover or vegetation index, and surface soil moisture. The latter will be obtained using passive and active microwave approaches. The area-averages of the surface properties will be compared with satellite data. The First ISLSCP Field Experiment is planned for a site having relatively uniform vegetation cover in the central great plains of the U.S.A.

Schmugge, T. J.↗
NASA NTRS1977

Interpretation of multispectral and infrared thermal surveys of the Suez Canal Zone, Egypt

Remote sensing airborne surveys were conducted, as part of the plan of rehabilitation, of the Suez Canal Zone using I2S multispectral camera and Bendix LN-3 infrared passive scanner. The multispectral camera gives four separate photographs for the same scene in the blue, green, red, and near infrared bands. The scanner was operated in the microwave bands of 8 to 14 microns and the thermal surveying was carried out both at night and in the day time. The surveys, coupled with intensive ground investigations, were utilized in the construction of new geological, structural lineation and drainage maps for the Suez Canal Zone on a scale of approximately 1:20,000, which are superior to the maps made by normal aerial photography. A considerable number of anomalies belonging to various types were revealed through the interpretation of the executed multispectral and infrared thermal surveys.

Elshazly, E. M.↗
NASA NTRS1980

Enhancement of remote sensing through microwave technology

This overview begins with a brief look at remote sensing to date, focusing on the state of the art and the benefits that have been derived from it. Current and future microwave sensing developments are discussed pointing out special advantages and capabilities and noting the anticipated benefits. The frequency requirements of microwave sensing are outlined and the particular need to both allocate, and when necessary, protect active and passive operational sensing frequencies is emphasized.

Cehelsky, M.↗
NASA NTRS1992

Botswana water and surface energy balance research program. Part 1: Integrated approach and field campaign results

The Botswana water and surface energy balance research program was developed to study and evaluate the integrated use of multispectral satellite remote sensing for monitoring the hydrological status of the Earth's surface. Results of the first part of the program (Botswana 1) which ran from 1 Jan. 1988 - 31 Dec. 1990 are summarized. Botswana 1 consisted of two major, mutually related components: a surface energy balance modeling component, built around an extensive field campaign; and a passive microwave research component which consisted of a retrospective study of large scale moisture conditions and Nimbus scanning multichannel microwave radiometer microwave signatures. The integrated approach of both components in general are described and activities performed during the surface energy modeling component including the extensive field campaign are summarized. The results of the passive microwave component are summarized. The key of the field campaign was a multilevel approach, whereby measurements by various similar sensors were made at several altitudes and resolution. Data collection was performed at two adjacent sites of contrasting surface character. The following measurements were made: micrometeorological measurements, surface temperatures, soil temperatures, soil moisture, vegetation (leaf area index and biomass), satellite data, aircraft data, atmospheric soundings, stomatal resistance, and surface emissivity.

Vandegriend, A. A.↗
NASA NTRS2010

Satellite Gravimetry Applied to Drought Monitoring

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Rodell, Matthew↗