ASPECTS OF ARCTIC SEA ICE OBSERVABLE BY SEQUENTIAL PASSIVE MICROWAVE OBSERVATIONS FROM THE NIMBUS-5 SATELLITE.

USGS Publications Warehouse

Campbell, William J.; Gloersen, Per; Zwally, H. Jay; ,

1984-01-01

Observations made from 1972 to 1976 with the Electrically Scanning Microwave Radiometer on board the Nimbus-5 satellite provide sequential synoptic information of the Arctic sea ice cover. This four-year data set was used to construct a fairly continuous series of three-day average 19-GHz passive microwave images which has become a valuable source of polar information, yielding many anticipated and unanticipated discoveries of the sea ice canopy observed in its entirety through the clouds and during the polar night. Short-term, seasonal, and annual variations of key sea ice parameters, such as ice edge position, ice types, mixtures of ice types, ice concentrations, and snow melt on the ice, are presented for various parts of the Arctic.

Towards a climatology of tropical cyclone morphometric structures using a newly standardized passive microwave satellite dataset

NASA Astrophysics Data System (ADS)

Cossuth, J.; Hart, R. E.

2013-12-01

storm's rainband and eyewall organization. Ultimately, this project develops a consistent climatology of TC structures using a new database of research-quality historical TC satellite microwave observations. Not only can such data sets more accurately study TC structural evolution, but they may facilitate automated TC intensity estimates and provide methods to enhance current operational and research products, such as at the NRL TC webpage (http://www.nrlmry.navy.mil/TC.html). The process of developing the dataset and possible objective definitions of TC structures using passive microwave imagery will be described, with preliminary results suggesting new methods to identify TC structures that may interrogate and expand upon physical and dynamical theories. Structural metrics such as threshold analysis of the outlines of the TC shape as well as methods to diagnose the inner-core size, completion, and magnitude will be introduced.

Potential of bias correction for downscaling passive microwave and soil moisture data

USDA-ARS?s Scientific Manuscript database

Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...

Satellite passive microwave rain measurement techniques for land and ocean

NASA Technical Reports Server (NTRS)

Spencer, R. W.

1985-01-01

Multiseasonal rainfall was found to be measurable over land with satellite passive microwave data, based upon comparisons between Nimbus 7 Scanning Multichannel Microwave Radiometer (SMME) brightness temperatures (T sub B) and operational WSR-57 radar rain rates. All of the SMMR channels (bipolarized 37, 21, 18, 10.7, and 6.6. GHz T sub B) were compared to radar reflectivities for 25 SMMR passes and 234 radar scans over the U.S. during the spring, summer, and fall of 1979. It was found that the radar rain rates were closely related to the difference between 37 and 21 GHz T sub B. This result is due to the volume scattering effects of precipitation which cause emissivity decreases with frequency, as opposed to emissive surfaces (e.g., water) whose emissivities increase with frequency. Two frequencies also act to reduce the effects of thermometric temperature variations on T sub B to a miminum. During summer and fall, multiple correlation coefficients of 0.80 and 0.75 were obtained. These approach the limit of correlation that can be expected to exist between two very different data sources, especially in light of the errors attributable to manual digitization of PPI photographs of variable quality from various operational weather radar not calibrated for research purposes. During the spring, a significantly lower (0.63) correlation was found. This poorer performance was traced to cases of wet, unvegetated soil being sensed at the lower frequencies through light rain, partly negating the rain scattering signal.

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.;

Passive microwave soil moisture downscaling using vegetation index and skin surface temperature

USDA-ARS?s Scientific Manuscript database

Soil moisture satellite estimates are available from a variety of passive microwave satellite sensors, but their spatial resolution is frequently too coarse for use by land managers and other decision makers. In this paper, a soil moisture downscaling algorithm based on a regression relationship bet...

PolarCube: A High Resolution Passive Microwave Satellite for Sounding and Imaging at 118 GHz

NASA Astrophysics Data System (ADS)

Weaver, R. L.; Gallaher, D. W.; Gasiewski, A. J.; Sanders, B.; Periasamy, L.; Hwang, K.; Alvarenga, G.; Hickey, A. M.

2013-12-01

PolarCube is a 3U CubeSat hosting an eight-channel passive microwave spectrometer operating at the 118.7503 GHz oxygen resonance that is currently in development. The project has an anticipated launch date in early 2015. It is currently being designed to operate for approximately12 months on orbit to provide the first global 118-GHz spectral imagery of the Earth over full seasonal cycle and to sound Arctic vertical temperature structure. The principles used by PolarCube for temperature sounding are well established in number of peer-reviewed papers going back more than two decades, although the potential for sounding from a CubeSat has never before been demonstrated in space. The PolarCube channels are selected to probe atmospheric emission over a range of vertical levels from the surface to lower stratosphere. This capability has been available operationally for over three decades, but at lower frequencies and higher altitudes that do not provide the spatial resolution that will be achieved by PolarCube. While the NASA JPSS ATMS satellite sensor provides global coverage at ~32 km resolution, the PolarCube will improve on this resolution by a factor of two, thus facilitating the primary science goal of determining sea ice concentration and extent while at the same time collecting profile data on atmospheric temperature. Additionally, we seek to correlate freeze-thaw line data from SMAP with our near simultaneously collected atmospheric temperature data. In addition to polar science, PolarCube will provide a first demonstration of a very low cost passive microwave sounder that if operated in a fleet configuration would have the potential to fulfill the goals of the Precipitation Atmospheric Temperature and Humidity (PATH) mission, as defined in the NRC Decadal Survey. PolarCube 118-GHz passive microwave spectrometer in deployed configuration

Assessing concentration uncertainty estimates from passive microwave sea ice products

NASA Astrophysics Data System (ADS)

Meier, W.; Brucker, L.; Miller, J. A.

2017-12-01

Sea ice concentration is an essential climate variable and passive microwave derived estimates of concentration are one of the longest satellite-derived climate records. However, until recently uncertainty estimates were not provided. Numerous validation studies provided insight into general error characteristics, but the studies have found that concentration error varied greatly depending on sea ice conditions. Thus, an uncertainty estimate from each observation is desired, particularly for initialization, assimilation, and validation of models. Here we investigate three sea ice products that include an uncertainty for each concentration estimate: the NASA Team 2 algorithm product, the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF) product, and the NOAA/NSIDC Climate Data Record (CDR) product. Each product estimates uncertainty with a completely different approach. The NASA Team 2 product derives uncertainty internally from the algorithm method itself. The OSI-SAF uses atmospheric reanalysis fields and a radiative transfer model. The CDR uses spatial variability from two algorithms. Each approach has merits and limitations. Here we evaluate the uncertainty estimates by comparing the passive microwave concentration products with fields derived from the NOAA VIIRS sensor. The results show that the relationship between the product uncertainty estimates and the concentration error (relative to VIIRS) is complex. This may be due to the sea ice conditions, the uncertainty methods, as well as the spatial and temporal variability of the passive microwave and VIIRS products.

Antartic sea ice, 1973 - 1976: Satellite passive-microwave observations

NASA Technical Reports Server (NTRS)

Zwally, H. J.; Comiso, J. C.; Parkinson, C. L.; Campbell, W. J.; Carsey, F. D.; Gloersen, P.

1983-01-01

Data from the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus 5 satellite are used to determine the extent and distribution of Antarctic sea ice. The characteristics of the southern ocean, the mathematical formulas used to obtain quantitative sea ice concentrations, the general characteristics of the seasonal sea ice growth/decay cycle and regional differences, and the observed seasonal growth/decay cycle for individual years and interannual variations of the ice cover are discussed. The sea ice data from the ESMR are presented in the form of color-coded maps of the Antarctic and the southern oceans. The maps show brightness temperatures and concentrations of pack ice averaged for each month, 4-year monthly averages, and month-to-month changes. Graphs summarizing the results, such as areas of sea ice as a function of time in the various sectors of the southern ocean are included. The images demonstrate that satellite microwave data provide unique information on large-scale sea ice conditions for determining climatic conditions in polar regions and possible global climatic changes.

Bias correction for rainrate retrievals from satellite passive microwave sensors

NASA Technical Reports Server (NTRS)

Short, David A.

1990-01-01

Rainrates retrieved from past and present satellite-borne microwave sensors are affected by a fundamental remote sensing problem. Sensor fields-of-view are typically large enough to encompass substantial rainrate variability, whereas the retrieval algorithms, based on radiative transfer calculations, show a non-linear relationship between rainrate and microwave brightness temperature. Retrieved rainrates are systematically too low. A statistical model of the bias problem shows that bias correction factors depend on the probability distribution of instantaneous rainrate and on the average thickness of the rain layer.

Interannual and Decadal Variability of Ocean Surface Latent Heat Flux as Seen from Passive Microwave Satellite Algorithms

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Jackson, Darren L.; Wick, Gary A.; Roberts, Brent; Miller, Tim L.

2007-01-01

Ocean surface turbulent fluxes are critical links in the climate system since they mediate energy exchange between the two fluid systems (ocean and atmosphere) whose combined heat transport determines the basic character of Earth's climate. Deriving physically-based latent and sensible heat fluxes from satellite is dependent on inferences of near surface moisture and temperature from coarser layer retrievals or satellite radiances. Uncertainties in these "retrievals" propagate through bulk aerodynamic algorithms, interacting as well with error properties of surface wind speed, also provided by satellite. By systematically evaluating an array of passive microwave satellite algorithms, the SEAFLUX project is providing improved understanding of these errors and finding pathways for reducing or eliminating them. In this study we focus on evaluating the interannual variability of several passive microwave-based estimates of latent heat flux starting from monthly mean gridded data. The algorithms considered range from those based essentially on SSM/I (e.g. HOAPS) to newer approaches that consider additional moisture information from SSM/T-2 or AMSU-B and lower tropospheric temperature data from AMSU-A. On interannual scales, variability arising from ENSO events and time-lagged responses of ocean turbulent and radiative fluxes in other ocean basins (as well as the extratropical Pacific) is widely recognized, but still not well quantified. Locally, these flux anomalies are of order 10-20 W/sq m and present a relevant "target" with which to verify algorithm performance in a climate context. On decadal time scales there is some evidence from reanalyses and remotely-sensed fluxes alike that tropical ocean-averaged latent heat fluxes have increased 5-10 W/sq m since the early 1990s. However, significant uncertainty surrounds this estimate. Our work addresses the origin of these uncertainties and provides statistics on time series of tropical ocean averages, regional space

Arctic Sea ice, 1973-1976: Satellite passive-microwave observations

NASA Technical Reports Server (NTRS)

Parkinson, Claire L.; Comiso, Josefino C.; Zwally, H. Jay; Cavalieri, Donald J.; Gloersen, Per; Campbell, William J.

1987-01-01

The Arctic region plays a key role in the climate of the earth. The sea ice cover affects the radiative balance of the earth and radically changes the fluxes of heat between the atmosphere and the ocean. The observations of the Arctic made by the Electrically Scanning Microwave Radiometer (ESMR) on board the Nimbus 5 research satellite are summarized for the period 1973 through 1976.

Passive Microwave Rainfall Estimates from the GPM Mission

NASA Astrophysics Data System (ADS)

Kummerow, Christian; Petkovic, Veljko

2017-04-01

The Global Precipitation Measurement (GPM) mission was launched in February 2014 as a joint mission between JAXA from Japan and NASA from the United States. GPM carries a state of the art dual-frequency precipitation radar and a multi-channel passive microwave radiometer that acts not only to enhance the radar's retrieval capability, but also as a reference for a constellation of existing satellites carrying passive microwave sensors. In March of 2016, GPM released Version 4 of its precipitation products that consists of radar, radiometer, and combined radar/radiometer products. The precipitation products from these sensors or sensor combination are consistent by design and show relatively minor differences in the mean global sense. Closer examination of the biases, however, reveals regional biases between active and passive sensors that can be directly related top the nature of the convection. By looking at cloud systems instead of individual satellite pixels, the relationship between biases and the large scale environmental state become obvious. Organized convection, which occurs more readily in regimes with large Convective Available Potential Energy (CAPE) and shear tend to drive biases in different directions than isolated convection. This is true over both land and ocean. This talk will present the latest findings and explore these discrepancies from a physical perspective in order to gain some understanding between cloud structures, information content, and retrieval differences. This analysis will be used to then drive a bigger picture of how GPM's latest results inform the Global Water and Energy budgets.

Passive microwave remote sensing for sea ice research

NASA Technical Reports Server (NTRS)

1984-01-01

Techniques for gathering data by remote sensors on satellites utilized for sea ice research are summarized. Measurement of brightness temperatures by a passive microwave imager converted to maps of total sea ice concentration and to the areal fractions covered by first year and multiyear ice are described. Several ancillary observations, especially by means of automatic data buoys and submarines equipped with upward looking sonars, are needed to improve the validation and interpretation of satellite data. The design and performance characteristics of the Navy's Special Sensor Microwave Imager, expected to be in orbit in late 1985, are described. It is recommended that data from that instrument be processed to a form suitable for research applications and archived in a readily accessible form. The sea ice data products required for research purposes are described and recommendations for their archival and distribution to the scientific community are presented.

Classification methods for monitoring Arctic sea ice using OKEAN passive/active two-channel microwave data

USGS Publications Warehouse

Belchansky, Gennady I.; Douglas, David C.

2000-01-01

This paper presents methods for classifying Arctic sea ice using both passive and active (2-channel) microwave imagery acquired by the Russian OKEAN 01 polar-orbiting satellite series. Methods and results are compared to sea ice classifications derived from nearly coincident Special Sensor Microwave Imager (SSM/I) and Advanced Very High Resolution Radiometer (AVHRR) image data of the Barents, Kara, and Laptev Seas. The Russian OKEAN 01 satellite data were collected over weekly intervals during October 1995 through December 1997. Methods are presented for calibrating, georeferencing and classifying the raw active radar and passive microwave OKEAN 01 data, and for correcting the OKEAN 01 microwave radiometer calibration wedge based on concurrent 37 GHz horizontal polarization SSM/I brightness temperature data. Sea ice type and ice concentration algorithms utilized OKEAN's two-channel radar and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter, together with a priori knowledge about the scattering parameters and natural emissivities of basic sea ice types. OKEAN 01 data and algorithms tended to classify lower concentrations of young or first-year sea ice when concentrations were less than 60%, and to produce higher concentrations of multi-year sea ice when concentrations were greater than 40%, when compared to estimates produced from SSM/I data. Overall, total sea ice concentration maps derived independently from OKEAN 01, SSM/I, and AVHRR satellite imagery were all highly correlated, with uniform biases, and mean differences in total ice concentration of less than four percent (sd<15%).

Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

USDA-ARS?s Scientific Manuscript database

Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

Enhanced hemispheric-scale snow mapping through the blending of optical and microwave satellite data

NASA Astrophysics Data System (ADS)

Armstrong, R. L.; Brodzik, M. J.; Savoie, M.; Knowles, K.

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. Global snow cover fluctuation can now be monitored over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere weekly snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Decadal trends and their significance are compared for the two data types. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as throughout the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the

Arctic multiyear ice classification and summer ice cover using passive microwave satellite data

NASA Technical Reports Server (NTRS)

Comiso, J. C.

1990-01-01

Passive microwave data collected by Nimbus 7 were used to classify and monitor the Arctic multilayer sea ice cover. Sea ice concentration maps during several summer minima are analyzed to obtain estimates of ice floes that survived summer, and the results are compared with multiyear-ice concentrations derived from these data by using an algorithm that assumes a certain emissivity for multiyear ice. The multiyear ice cover inferred from the winter data was found to be about 25 to 40 percent less than the summer ice-cover minimum, indicating that the multiyear ice cover in winter is inadequately represented by the passive microwave winter data and that a significant fraction of the Arctic multiyear ice floes exhibits a first-year ice signature.

Snowmelt on the Greenland Ice Sheet as Derived From Passive Microwave Satellite Data

NASA Technical Reports Server (NTRS)

Abdalati, Waleed; Steffen, Konrad

1997-01-01

The melt extent of the snow on the Greenland ice sheet is of considerable importance to the ice sheet's mass and energy balance, as well as Arctic and global climates. By comparing passive microwave satellite data to field observations, variations in melt extent have been detected by establishing melt thresholds in the cross-polarized gradient ratio (XPGR). The XPGR, defined as the normalized difference between the 19-GHz horizontal channel and the 37-GHz vertical channel of the Special Sensor Microwave/Imager (SSM/I), exploits the different effects of snow wetness on different frequencies and polarizations and establishes a distinct melt signal. Using this XPGR melt signal, seasonal and interannual variations in snowmelt extent of the ice sheet are studied. The melt is found to be most extensive on the western side of the ice sheet and peaks in late July. Moreover, there is a notable increasing trend in melt area between the years 1979 and 1991 of 4.4% per year, which came to an abrupt halt in 1992 after the eruption of Mt. Pinatubo. A similar trend is observed in the temperatures at six coastal stations. The relationship between the warming trend and increasing melt trend between 1979 and 1991 suggests that a 1 C temperature rise corresponds to an increase in melt area of 73000 sq km, which in general exceeds one standard deviation of the natural melt area variability.

Twenty-four year record of Northern Hemisphere snow cover derived from passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Armstrong, Richard L.; Brodzik, Mary Jo

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. It is now possible to monitor the global fluctuation of snow cover over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a smiliar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible statellite data and the visible data typically show higher monthly variability. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as on into the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the negative spectral gradient driving the passive microwave algorithm

Passive microwave algorithm development and evaluation

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1995-01-01

The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached.

Arctic and Antarctic Sea Ice Concentrations from Multichannel Passive-Microwave Satellite Data Sets: October 1978-September 1995 User's Guide

NASA Technical Reports Server (NTRS)

Cavalieri, Donald J.; Parkinson, Claire L.; Gloersen, Per; Zwally, H. Jay

1997-01-01

Satellite multichannel passive-microwave sensors have provided global radiance measurements with which to map, monitor, and study the Arctic and Antarctic polar sea ice covers. The data span over 18 years (as of April 1997), starting with the launch of the Scanning Multichannel Microwave Radiometer (SMMR) on NASA's SeaSat A and Nimbus 7 in 1978 and continuing with the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMI) series beginning in 1987. It is anticipated that the DMSP SSMI series will continue into the 21st century. The SSMI series will be augmented by new, improved sensors to be flown on Japanese and U.S. space platforms. This User's Guide provides a description of a new sea ice concentration data set generated from observations made by three of these multichannel sensors. The data set includes gridded daily ice concentrations (every-other-day for the SMMR data) for both the north and south polar regions from October 26, 1978 through September 30, 1995, with the one exception of a 6-week data gap from December 3, 1987 through January 12, 1988. The data have been placed on two CD-ROMs that include a ReadMeCD file giving the technical details on the file format, file headers, north and south polar grids, ancillary data sets, and directory structure of the CD-ROM. The CD-ROMS will be distributed by the National Snow and Ice Data Center in Boulder, CO.

Passive Microwave Studies of Atmospheric Precipitation and State

NASA Technical Reports Server (NTRS)

Staelin, David H.; Rosenkranz, Philip W.; Shiue, James C. (Technical Monitor)

2002-01-01

The principal contributions of this research on novel passive microwave spectral techniques are in the areas of: (1) global precipitation mapping using the opaque spectral bands on research and operational weather satellites, (2) development and analysis of extensive aircraft observational imaging data sets obtained using the MIT instrument NAST-M near 54 and 118 GHz over hurricanes and weather ranging from tropical to polar; simultaneous data from the 8500-channel infrared spectrometer NAST-I was obtained and analyzed separately, (3) estimation of hydrometeor diameters in cell tops using data from aircraft and spacecraft, (4) continued improvement of expressions for atmospheric transmittance at millimeter and sub-millimeter wavelengths, (5) development and airborne use of spectrometers operating near 183- and 425-GHz bands, appropriate to practical systems in geosynchronous orbit, and (6) preliminary studies of the design and performance of future geosynchronous microwave sounders for temperature and humidity profiles and for continuous monitoring of regional precipitation through most clouds. This work was a natural extension of work under NASA Grant NAG5-2545 and its predecessors. This earlier work had developed improved airborne imaging microwave spectrometers and had shown their sensitivity to precipitation altitude and character. They also had prepared the foundations for precipitation estimation using the opaque microwave bands. The field demonstration and improvement of these capabilities was then a central part of the present research reported here, during which period the first AMSU data became available and several hurricanes were overflown by NAST-M, yielding unique data about their microwave signatures. This present work has in turn helped lay the foundation for future progress in incorporating the opaque microwave channels in systems for climatologically precise global precipitation mapping from current and future operational satellites. Extension of

Arctic and Antarctic Sea Ice, 1978-1987: Satellite Passive-Microwave Observations and Analysis

NASA Technical Reports Server (NTRS)

Gloersen, Per; Campbell, William J.; Cavalieri, Donald J.; Comiso, Josefino C.; Parkinson, Claire L.; Zwally, H. Jay

1992-01-01

This book contains a description and analysis of the spatial and temporal variations in the Arctic and Antarctic sea ice covers from October 26, 1978 through August 20, 1987. It is based on data collected by the Scanning Multichannel Microwave Radiometer (SMMR) onboard the NASA Nimbus 7 satellite. The 8.8-year period, together with the 4 years of the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR) observations presented in two earlier volumes, comprises a sea ice record spanning almost 15 years.

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Improved Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.;

A novel algorithm for monitoring reservoirs under all-weather conditions at a high temporal resolution through passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Zhang, Shuai; Gao, Huilin

2016-08-01

Flood mitigation in developing countries has been hindered by a lack of near real-time reservoir storage information at high temporal resolution. By leveraging satellite passive microwave observations over a reservoir and its vicinity, we present a globally applicable new algorithm to estimate reservoir storage under all-weather conditions at a 4 day time step. A weighted horizontal ratio (WHR) based on the brightness temperatures at 36.5 GHz is introduced, with its coefficients calibrated against an area training data set over each reservoir. Using a predetermined area-elevation (A-H) relationship, these coefficients are then applied to the microwave data to calculate the storage. Validation results over four reservoirs in South Asia indicate that the microwave-based storage estimations (after noise reduction) perform well (with coefficients of determination ranging from 0.41 to 0.74). This is the first time that passive microwave observations are fused with other satellite data for quantifying the storage of individual reservoirs.

Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons

NASA Astrophysics Data System (ADS)

Karthikeyan, L.; Pan, Ming; Wanders, Niko; Kumar, D. Nagesh; Wood, Eric F.

2017-11-01

Soil moisture is widely recognized as an important land surface variable that provides a deeper knowledge of land-atmosphere interactions and climate change. Space-borne passive and active microwave sensors have become valuable and essential sources of soil moisture observations at global scales. Over the past four decades, several active and passive microwave sensors have been deployed, along with the recent launch of two fully dedicated missions (SMOS and SMAP). Signifying the four decades of microwave remote sensing of soil moisture, this Part 2 of the two-part review series aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy for retrieving soil moisture. The first part discusses the developments made in active and passive microwave soil moisture retrieval algorithms. We assess the evolution of the products of various sensors over the last four decades, in terms of daily coverage, temporal performance, and spatial performance, by comparing the products of eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product) with the International Soil Moisture Network (ISMN) in-situ stations and the Variable Infiltration Capacity (VIC) land surface model simulations over the Contiguous United States (CONUS). In the process, the regional impacts of vegetation conditions on the spatial and temporal performance of soil moisture products are investigated. We also carried out inter-satellite comparisons to study the roles of sensor design and algorithms on the retrieval accuracy. We find that substantial improvements have been made over recent years in this field in terms of daily coverage, retrieval accuracy, and temporal dynamics. We conclude that the microwave soil moisture products have significantly evolved in the last four decades and will

Botswana water and surface energy balance research program. Part 2: Large scale moisture and passive microwaves

NASA Technical Reports Server (NTRS)

Vandegriend, A. A.; Owe, M.; Chang, A. T. C.

1992-01-01

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. The research program 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 are explained in general and activities performed within the passive microwave research component are summarized. The microwave theory is discussed taking into account: soil dielectric constant, emissivity, soil roughness effects, vegetation effects, optical depth, single scattering albedo, and wavelength effects. The study site is described. The soil moisture data and its processing are considered. The relation between observed large scale soil moisture and normalized brightness temperatures is discussed. Vegetation characteristics and inverse modeling of soil emissivity is considered.

Tactical Approaches for Making a Successful Satellite Passive Microwave ESDR

NASA Astrophysics Data System (ADS)

Hardman, M.; Brodzik, M. J.; Gotberg, J.; Long, D. G.; Paget, A. C.

2014-12-01

Our NASA MEaSUREs project is producing a new, enhanced resolution gridded Earth System Data Record for the entire satellite passive microwave (SMMR, SSM/I-SSMIS and AMSR-E) time series. Our project goals are twofold: to produce a well-documented, consistently processed, high-quality historical record at higher spatial resolutions than have previously been available, and to transition the production software to the NSIDC DAAC for ongoing processing after our project completion. In support of these goals, our distributed team at BYU and NSIDC faces project coordination challenges to produce a high-quality data set that our user community will accept as a replacement for the currently available historical versions of these data. We work closely with our DAAC liaison on format specifications, data and metadata plans, and project progress. In order for the user community to understand and support our project, we have solicited a team of Early Adopters who are reviewing and evaluating a prototype version of the data. Early Adopter feedback will be critical input to our final data content and format decisions. For algorithm transparency and accountability, we have released an Algorithm Theoretical Basis Document (ATBD) and detailed supporting technical documentation, with rationale for all algorithm implementation decisions. For distributed team management, we are using collaborative tools for software revision control and issue tracking. For reliably transitioning a research-quality image reconstruction software system to production-quality software suitable for use at the DAAC, we have adopted continuous integration methods for running automated regression testing. Our presentation will summarize bothadvantages and challenges of each of these tactics in ensuring production of a successful ESDR and an enduring production software system.

Some comments on passive microwave measurement of rain

NASA Technical Reports Server (NTRS)

Wilheit, Thomas T.

1986-01-01

It is argued that because microwave radiation interacts much more strongly with hydrometeors than with cloud particles, microwave measurements from space offer a significant chance of making global precipitation estimates. Over oceans, passive microwave measurements are essentially attenuation measurements that can be very closely related to the rain rate independently of the details of the drop-size distribution. Over land, scattering of microwave radiation by the hydrometeors, especially in the ice phase, can be used to estimate rainfall. In scattering, the details of the drop-size distribution are very important and it is therefore more difficult to achieve a high degree of accuracy. The SSM/I (Special Sensor Microwave Imager), a passive microwave imaging sensor that will be launched soon, will have dual-polarized channels at 85.5 GHz that will be very sensitive to scattering by frozen hydrometeors. Other sensors being considered for the future space missions would extend the ability to estimate rain rates from space. The ideal spaceborne precipitation-measurement system would use the complementary strengths of passive microwave, radar, and visible/infrared measurements.

Four Decades of Microwave Satellite Soil Moisture Observations: Product validation and inter-satellite comparisons

NASA Astrophysics Data System (ADS)

Lanka, K.; Pan, M.; Wanders, N.; Kumar, D. N.; Wood, E. F.

2017-12-01

The satellite based passive and active microwave sensors enhanced our ability to retrieve soil moisture at global scales. It has been almost four decades since the first passive microwave satellite sensor was launched in 1978. Since then soil moisture has gained considerable attention in hydro-meteorological, climate, and agricultural research resulting in the deployment of two dedicated missions in the last decade, SMOS and SMAP. Signifying the four decades of microwave remote sensing of soil moisture, this work aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy of retrieving soil moisture. We considered daily coverage, temporal performance, and spatial performance to assess the accuracy of products corresponding to eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product), using 1058 ISMN in-situ stations and the VIC LSM soil moisture simulations (VICSM) over the CONUS. Our analysis indicated that the daily coverage has increased from 30 % during 1980s to 85 % (during non-winter months) with the launch of dedicated soil moisture missions SMOS and SMAP. The temporal validation of passive and active soil moisture products with the ISMN data place the range of median RMSE as 0.06-0.10 m3/m3 and median correlation as 0.20-0.68. When TMI, AMSR-E and WindSAT are evaluated, the AMSR-E sensor is found to have produced the brightness temperatures with better quality, given that these sensors are paired with same retrieval algorithm (LPRM). The ASCAT product shows a significant improvement during the temporal validation of retrievals compared to its predecessor ERS, thanks to enhanced sensor configuration. The SMAP mission, through its improved sensor design and RFI handling, shows a high retrieval accuracy under all-topography conditions

Combining Passive Microwave Sounders with CYGNSS information for improved retrievals: Observations during Hurricane Harvey

NASA Astrophysics Data System (ADS)

Schreier, M. M.

2017-12-01

The launch of CYGNSS (Cyclone Global Navigation Satellite System) has added an interesting component to satellite observations: it can provide wind speeds in the tropical area with a high repetition rate. Passive microwave sounders that are overpassing the same region can benefit from this information, when it comes to the retrieval of temperature or water profiles: the uncertainty about wind speeds has a strong impact on emissivity and reflectivity calculations with respect to surface temperature. This has strong influences on the uncertainty of retrieval of temperature and water content, especially under extreme weather conditions. Adding CYGNSS information to the retrieval can help to reduce errors and provide a significantly better sounder retrieval. Based on observations during Hurricane Harvey, we want to show the impact of CYGNSS data on the retrieval of passive microwave sensors. We will show examples on the impact on the retrieval from polar orbiting instruments, like the Advanced Technology Microwave Sounder (ATMS) and AMSU-A/B on NOAA-18 and 19. In addition we will also show the impact on retrievals from HAMSR (High Altitude MMIC Sounding Radiometer), which was flying on the Global Hawk during the EPOCH campaign. We will compare the results with other observations and estimate the impact of additional CYGNSS information on the microwave retrieval, especially on the impact in error and uncertainty reduction. We think, that a synergetic use of these different data sources could significantly help to produce better assimilation products for forecast assimilation.

Passive Microwave Remote Sensing of Soil Moisture

NASA Technical Reports Server (NTRS)

Njoku, Eni G.; Entekhabi, Dara

1996-01-01

Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive Microwave soil moisture sensors currently considered for space operation are in the range 10-20 km. The most useful frequency range for soil moisture sensing is 1-5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.

Wind Retrievals under Rain for Passive Satellite Microwave Radiometers and its Applications to Hurricane Tracking

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank J.

2008-01-01

We have developed an algorithm that retrieves wind speed under rain using C-hand and X-band channels of passive microwave satellite radiometers. The spectral difference of the brightness temperature signals due to wind or rain allows to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. We &ve trained a statistical algorithm that applies under hurricane conditions and is able to measure wind speeds in hurricanes to an estimated accuracy of about 2 m/s. We have also developed a global algorithm, that is less accurate but can be applied under all conditions. Its estimated accuracy is between 2 and 5 mls, depending on wind speed and rain rate. We also extend the wind speed region in our model for the wind induced sea surface emissivity from currently 20 m/s to 40 mls. The data indicate that the signal starts to saturate above 30 mls. Finally, we make an assessment of the performance of wind direction retrievals from polarimetric radiometers as function of wind speed and rain rate

Seasonal Snow Extent and Snow Mass in South America Using SMMR and SSM/I Passive Microwave Data (1979-2003)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Chiu, L.; Kelly, R. E.; Powell, H.; Chiu, L.

2007-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-satellite and the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2003, both snow cover extent and snow depth (snow mass) were investigated during coldest months (May-September), primarily in the Patagonia area of Argentina and in Chile. Most of the seasonal snow in South America is in the Patagonia region of Argentina. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and also usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average snow extent during the 25-year period of record, is 320,700 km(exp 2). In July of 1984, the average monthly snow cover was 701,250 km(exp 2) - the most extensive coverage observed between 1979 and 2003. However, in July of 1989, snow cover extent was only 120 km(exp 2). The 25-year period of record shows a sinusoidal like pattern, though there appears to be no obvious trend in either increasing or decreasing snow extent or snow mass between 1979 and 2003.

Seasonal Snow Extent and Snow Mass in South America using SMMR and SSM/I Passive Microwave Data (1979-2006)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Kelly, R. E. J.; Chiu, L.

2008-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and the Special Sensor Microwave Imagers (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow water equivalent (snow mass) were investigated during the coldest months (May-September), primarily in the Patagonia area of Argentina and in the Andes of Chile, Argentina and Bolivia, where most of the seasonal snow is found. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 km(exp 2). In July of 1984, the average monthly snow cover extent was 701,250 km(exp 2) the most extensive coverage observed between 1979 and 2006. However, in July of 1989, snow cover extent was only 120,000 km(exp 2). The 28-year period of record shows a sinusoidal like pattern for both snow cover and snow mass, though neither trend is significant at the 95% level.

A Review on Passive and Integrated Near-Field Microwave Biosensors

PubMed Central

Guha, Subhajit; Jamal, Farabi Ibne

2017-01-01

In this paper we review the advancement of passive and integrated microwave biosensors. The interaction of microwave with biological material is discussed in this paper. Passive microwave biosensors are microwave structures, which are fabricated on a substrate and are used for sensing biological materials. On the other hand, integrated biosensors are microwave structures fabricated in standard semiconductor technology platform (CMOS or BiCMOS). The CMOS or BiCMOS sensor technology offers a more compact sensing approach which has the potential in the future for point of care testing systems. Various applications of the passive and the integrated sensors have been discussed in this review paper. PMID:28946617

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

NASA Technical Reports Server (NTRS)

Blonski, Slawomir

2007-01-01

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.

Aircraft and satellite passive microwave observations of the Bering Sea ice cover during MIZEX West

NASA Technical Reports Server (NTRS)

Cavalieri, D. J.; Gloersen, P.; Wilheit, T. T., Jr.

1986-01-01

Passive microwave measurements of the Bering Sea were made with the NASA CV-990 airborne laboratory during February. Microwave data were obtained with imaging and dual-polarized, fixed-beam radiometers in a range of frequencies from 10 to 183 GHz. The high resolution imagery at 92 GHz provides a particularly good description of the marginal ice zone delineating regions of open water, ice compactness, and ice-edge structure. Analysis of the fixed-beam data shows that spectral differences increase with a decrease in ice thickness. Polarization at 18 and 37 GHz distinguishes among new, young, and first-year ice types.

Passive microwave structure of severe tornadic storms on 16 November 1987

NASA Technical Reports Server (NTRS)

Heymsfield, Gerald M.; Fulton, Richard

1994-01-01

Passive microwave observations using the Special Sensor Microwave/Imager (SSM/I) are presented for severe tornadic storms in the lower midwestern United States on 16 November 1987. These measurements are compared with Geostationary Operational Environmental Satellite infrared (IR) measurements for the same case. The IR observations had a classic 'V' cold feature commonly associated with severe Midwest thunderstorms. The minimum microwave brightness temperatures at 86 GHz, which primarily respond to ice scattering by larger ice particles, were located in the convective region and the warm interior of the anvil top, between the arms of the IR V feature. The interior warm region was the only portion of the entire anvil region that had high 86-GHz polarization difference temperatures. Microphysical implications of these multispectral observations are discussed. The observations suggest that there are large variations of ice microphysical characteristics spatially and vertically in the anvil region. These observations are discussed in the context of previous dynamical and microphysical hypotheses on the IR V feature.

Convective climatology over the southwest U.S. and Mexico from passive microwave and infrared data

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Howard, Kenneth W.; Keehn, Peter R.; Maddox, Robert A.; Adler, Robert F.

1992-01-01

Passive microwave data from the Special Sensor Microwave Imager (SSM/I) were used to estimate the amount of rainfall in the June-August season for the regions of the southwest U.S. and Mexico, and the results are compared to rain-gauge observations and to IR climatologies of Maddox et al. (1992), using both the hourly IR data and IR data sampled at the time of the overpass of the SSM/I. A comparison of the microwave climatology with monthly rainfall measured by the climatological gage network over several states of western Mexico resulted in a 0.63 correlation and a large (482 mm) bias, due to sampling and the incongruity of rain gages and satellite estimates. A comparison between the IR and microwave data showed that the IR tended toward higher percentages along the coast compared to the microwave.

Calibrated, Enhanced-Resolution Brightness Temperature Earth System Data Record: A New Era for Gridded Passive Microwave Data

NASA Astrophysics Data System (ADS)

Hardman, M.; Brodzik, M. J.; Long, D. G.

2017-12-01

Since 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Up until recently, the available global gridded passive microwave data sets have not been produced consistently. Various projections (equal-area, polar stereographic), a number of different gridding techniques were used, along with various temporal sampling as well as a mix of Level 2 source data versions. In addition, not all data from all sensors have been processed completely and they have not been processed in any one consistent way. Furthermore, the original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. As part of NASA MEaSUREs, we have re-processed all data from SMMR, all SSM/I-SSMIS and AMSR-E instruments, using the most mature Level 2 data. The Calibrated, Enhanced-Resolution Brightness Temperature (CETB) Earth System Data Record (ESDR) gridded data are now available from the NSIDC DAAC. The data are distributed as netCDF files that comply with CF-1.6 and ACDD-1.3 conventions. The data have been produced on EASE 2.0 projections at smoothed, 25 kilometer resolution and spatially-enhanced resolutions, up to 3.125 km depending on channel frequency, using the radiometer version of the Scatterometer Image Reconstruction (rSIR) method. We expect this newly produced data set to enable scientists to better analyze trends in coastal regions, marginal ice zones and in mountainous terrain that were not possible with the previous gridded passive microwave data. The use of the EASE-Grid 2.0 definition and netCDF-CF formatting allows users to extract compliant geotiff images and

Ramifications of a potential gap in passive microwave data for the long-term sea ice climate record

NASA Astrophysics Data System (ADS)

Meier, W.; Stewart, J. S.

2017-12-01

The time series of sea ice concentration and extent from passive microwave sensors is one of the longest satellite-derived climate records and the significant decline in Arctic sea ice extent is one of the most iconic indicators of climate change. However, this continuous and consistent record is under threat due to the looming gap in passive microwave sensor coverage. The record started in late 1978 with the launch of the Scanning Multichannel Microwave Radiometer (SMMR) and has continued with a series of Special Sensor Microwave Imager (SSMI) and Special Sensor Microwave Imager and Sounder (SSMIS) instruments on U.S. Defense Meteorological Satellite Program (DMSP) satellites. The data from the different sensors are intercalibrated at the algorithm level by adjusting algorithm coefficients so that the output sea ice data is as consistent as possible between the older and the newer sensor. A key aspect in constructing the time series is to have at least two sensors operating simultaneously so that data from the older and newer sensor can be obtained from the same locations. However, with recent losses of the DMSP F19 and F20, the remaining SSMIS sensors are all well beyond their planned mission lifetime. This means that risk of failure is not small and is increasing with each day of operation. The newest passive microwave sensor, the JAXA Advanced Microwave Scanning Radiometer-2 (AMSR2), is a potential contributor to the time series (though it too is now beyond it's planned 5-year mission lifetime). However, AMSR2's larger antenna and higher spatial resolution presents a challenge in integrating its data with the rest of the sea ice record because the ice edge is quite sensitive to the sensor resolution, which substantially affects the total sea ice extent and area estimates. This will need to be adjusted for if AMSR2 is used to continue the time series. Here we will discuss efforts at NSIDC to integrate AMSR2 estimates into the sea ice climate record if needed. We

Seasonal Snow Extent and Snow Volume in South America Using SSM/I Passive Microwave Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Chang, A. T. C.; Hall, D. K.; Kelly, R.; Houser, Paul (Technical Monitor)

2001-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1992-1998, both snow cover extent and snow depth (snow mass) were investigated during the winter months (May-August) in the Patagonia region of Argentina. Since above normal temperatures in this region are typically above freezing, the coldest winter month was found to be not only the month having the most extensive snow cover but also the month having the deepest snows. For the seven-year period of this study, the average snow cover extent (May-August) was about 0.46 million sq km and the average monthly snow mass was about 1.18 x 10(exp 13) kg. July 1992 was the month having the greatest snow extent (nearly 0.8 million sq km) and snow mass (approximately 2.6 x 10(exp 13) kg).

Arctic multiyear ice classification and summer ice cover using passive microwave satellite data

NASA Astrophysics Data System (ADS)

Comiso, J. C.

1990-08-01

The ability to classify and monitor Arctic multiyear sea ice cover using multispectral passive microwave data is studied. Sea ice concentration maps during several summer minima have been analyzed to obtain estimates of ice surviving the summer. The results are compared with multiyear ice concentrations derived from data the following winter, using an algorithm that assumes a certain emissivity for multiyear ice. The multiyear ice cover inferred from the winter data is approximately 25 to 40% less than the summer ice cover minimum, suggesting that even during winter when the emissivity of sea ice is most stable, passive microwave data may account for only a fraction of the total multiyear ice cover. The difference of about 2×106 km2 is considerably more than estimates of advection through Fram Strait during the intervening period. It appears that as in the Antarctic, some multiyear ice floes in the Arctic, especially those near the summer marginal ice zone, have first-year ice or intermediate signatures in the subsequent winter. A likely mechanism for this is the intrusion of seawater into the snow-ice interface, which often occurs near the marginal ice zone or in areas where snow load is heavy. Spatial variations in melt and melt ponding effects also contribute to the complexity of the microwave emissivity of multiyear ice. Hence the multiyear ice data should be studied in conjunction with the previous summer ice data to obtain a more complete characterization of the state of the Arctic ice cover. The total extent and actual areas of the summertime Arctic pack ice were estimated to be 8.4×106 km2 and 6.2×106 km2, respectively, and exhibit small interannual variability during the years 1979 through 1985, suggesting a relatively stable ice cover.

Snow depth and snow cover retrieval from FengYun3B microwave radiation imagery based on a snow passive microwave unmixing method in Northeast China

NASA Astrophysics Data System (ADS)

Gu, Lingjia; Ren, Ruizhi; Zhao, Kai; Li, Xiaofeng

2014-01-01

The precision of snow parameter retrieval is unsatisfactory for current practical demands. The primary reason is because of the problem of mixed pixels that are caused by low spatial resolution of satellite passive microwave data. A snow passive microwave unmixing method is proposed in this paper, based on land cover type data and the antenna gain function of passive microwaves. The land cover type of Northeast China is partitioned into grass, farmland, bare soil, forest, and water body types. The component brightness temperatures (CBT), namely unmixed data, with 1 km data resolution are obtained using the proposed unmixing method. The snow depth determined by the CBT and three snow depth retrieval algorithms are validated through field measurements taken in forest and farmland areas of Northeast China in January 2012 and 2013. The results show that the overall of the retrieval precision of the snow depth is improved by 17% in farmland areas and 10% in forest areas when using the CBT in comparison with the mixed pixels. The snow cover results based on the CBT are compared with existing MODIS snow cover products. The results demonstrate that more snow cover information can be obtained with up to 86% accuracy.

Measuring the global distribution of intense convection over land with passive microwave radiometry

NASA Technical Reports Server (NTRS)

Spencer, R. W.; Santek, D. A.

1985-01-01

The global distribution of intense convective activity over land is shown to be measurable with satellite passive-microwave methods through a comparison of an empirical rain rate algorithm with a climatology of thunderstorm days for the months of June-August. With the 18 and 37 GHz channels of the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), the strong volume scattering effects of precipitation can be measured. Even though a single frequency (37 GHz) is responsive to the scattering signature, two frequencies are needed to remove most of the effect that variations in thermometric temperatures and soil moisture have on the brightness temperatures. Because snow cover is also a volume scatterer of microwave energy at these microwavelengths, a discrimination procedure involving four of the SMMR channels is employed to separate the rain and snow classes, based upon their differences in average thermometric temperature.

Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

PubMed

Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M

2014-08-01

The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.

A passive and active microwave-vector radiative transfer (PAM-VRT) model

NASA Astrophysics Data System (ADS)

Yang, Jun; Min, Qilong

2015-11-01

A passive and active microwave vector radiative transfer (PAM-VRT) package has been developed. This fast and accurate forward microwave model, with flexible and versatile input and output components, self-consistently and realistically simulates measurements/radiation of passive and active microwave sensors. The core PAM-VRT, microwave radiative transfer model, consists of five modules: gas absorption (two line-by-line databases and four fast models); hydrometeor property of water droplets and ice (spherical and nonspherical) particles; surface emissivity (from Community Radiative Transfer Model (CRTM)); vector radiative transfer of successive order of scattering (VSOS); and passive and active microwave simulation. The PAM-VRT package has been validated against other existing models, demonstrating good accuracy. The PAM-VRT not only can be used to simulate or assimilate measurements of existing microwave sensors, but also can be used to simulate observation results at some new microwave sensors.

Estimation of snow emissivity via assimilation of multi-frequency passive microwave data into an ensemble-based data assimilation system

NASA Astrophysics Data System (ADS)

Farhadi, L.; Bateni, S. M.; Auligne, T.; Navari, M.

2017-12-01

Snow emissivity is a key parameter for the estimation of snow surface temperature, which is needed as an initial value in climate models and determination of the outgoing long-wave radiation. Moreover, snow emissivity is required for retrieval of atmospheric parameters (e.g., temperature and humidity profiles) from satellite measurements and satellite data assimilations in numerical weather prediction systems. Microwave emission models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Existing microwave emission models introduce significant uncertainties in their snow emissivity estimates. This is mainly due to shortcomings of the dense media theory for snow medium at high frequencies, and erroneous forcing variables. The well-known limitations of passive microwave data such as coarse spatial resolution, saturation in deep snowpack, and signal loss in wet snow are the major drawbacks of passive microwave retrieval algorithms for estimation of snow emissivity. A full exploitation of the information contained in the remote sensing data can be achieved by merging them with snow emission models within a data assimilation framework. Such an optimal merging can overcome the specific limitations of models and remote sensing data. An Ensemble Batch Smoother (EnBS) data assimilation framework was developed in this study to combine the synthetically generated passive microwave brightness temperatures at 1.4-, 18.7-, 36.5-, and 89-GHz frequencies with the MEMLS microwave emission model to reduce the uncertainty of the snow emissivity estimates. We have used the EnBS algorithm in the context of observing system simulation experiment (or synthetic experiment) at the local scale observation site (LSOS) of the NASA CLPX field campaign. Our findings showed that the developed methodology significantly improves the estimates of the snow emissivity. The simultaneous assimilation of passive microwave brightness

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1994-01-01

During the first half of our second project year we have accomplished the following: (1) acquired a new AVHRR data set for the Beaufort Sea area spanning an entire year; (2) acquired additional ATSR data for the Arctic and Antarctic now totaling over seven months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; (6) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and SSM/I; and (7) continued work on compositing GAC data for coverage of the entire Arctic and Antarctic. During the second half of the year we will continue along these same lines, and will undertake a detailed validation study of the AVHRR and ATSR retrievals using LEADEX and the Beaufort Sea year-long data. Cloud masking methods used for the AVHRR will be modified for use with the ATSR. Methods of blending in situ and satellite-derived surface temperature data sets will be investigated.

CDRD and PNPR passive microwave precipitation retrieval algorithms: verification study over Africa and Southern Atlantic

NASA Astrophysics Data System (ADS)

Panegrossi, Giulia; Casella, Daniele; Cinzia Marra, Anna; Petracca, Marco; Sanò, Paolo; Dietrich, Stefano

2015-04-01

The ongoing NASA/JAXA Global Precipitation Measurement mission (GPM) requires the full exploitation of the complete constellation of passive microwave (PMW) radiometers orbiting around the globe for global precipitation monitoring. In this context the coherence of the estimates of precipitation using different passive microwave radiometers is a crucial need. We have developed two different passive microwave precipitation retrieval algorithms: one is the Cloud Dynamics Radiation Database algorithm (CDRD), a physically ¬based Bayesian algorithm for conically scanning radiometers (i.e., DMSP SSMIS); the other one is the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross¬-track scanning radiometers (i.e., NOAA and MetOp¬A/B AMSU-¬A/MHS, and NPP Suomi ATMS). The algorithms, originally created for application over Europe and the Mediterranean basin, and used operationally within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF, http://hsaf.meteoam.it), have been recently modified and extended to Africa and Southern Atlantic for application to the MSG full disk area. The two algorithms are based on the same physical foundation, i.e., the same cloud-radiation model simulations as a priori information in the Bayesian solver and as training dataset in the neural network approach, and they also use similar procedures for identification of frozen background surface, detection of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. In addition, similar procedures for the screening of not ¬precipitating pixels are used. A novel algorithm for the detection of precipitation in tropical/sub-tropical areas has been developed. The precipitation detection algorithm shows a small rate of false alarms (also over arid/desert regions), a superior detection capability in comparison with other widely used screening algorithms, and it is applicable

High Resolution UAV-based Passive Microwave L-band Imaging of Soil Moisture

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Stachura, M.; Elston, J.; McIntyre, E. M.

2013-12-01

Due to long electrical wavelengths and aperture size limitations the scaling of passive microwave remote sensing of soil moisture from spaceborne low-resolution applications to high resolution applications suitable for precision agriculture requires use of low flying aerial vehicles. This presentation summarizes a project to develop a commercial Unmanned Aerial Vehicle (UAV) hosting a precision microwave radiometer for mapping of soil moisture in high-value shallow root-zone crops. The project is based on the use of the Tempest electric-powered UAV and a compact digital L-band (1400-1427 MHz) passive microwave radiometer developed specifically for extremely small and lightweight aerial platforms or man-portable, tractor, or tower-based applications. Notable in this combination are a highly integrated UAV/radiometer antenna design and use of both the upwelling emitted signal from the surface and downwelling cold space signal for precise calibration using a lobe-correlating radiometer architecture. The system achieves a spatial resolution comparable to the altitude of the UAV above the ground while referencing upwelling measurements to the constant and well-known background temperature of cold space. The radiometer incorporates digital sampling and radio frequency interference mitigation along with infrared, near-infrared, and visible (red) sensors for surface temperature and vegetation biomass correction. This NASA-sponsored project is being developed both for commercial application in cropland water management, L-band satellite validation, and estuarian plume studies.

Severe Storm Identification with Satellite Microwave Radiometry: An Initial Investigation with Nimbus-7 SMMR Data.

NASA Astrophysics Data System (ADS)

Spencer, Roy W.; Howland, Michael R.; Santek, David A.

1987-06-01

In an attempt to determine the feasibility of detecting and monitoring severe weather with future satellite passive microwave observations, the severe weather characteristics of convective storms as observed by the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) are investigated. Low 37 GHz brightness temperatures (due to scattering of upwelling radiation by precipitation size ice) were related to the occurrence of severe weather (large hail, strong winds or wind damage, tornados and funnel clouds) within one hour of the satellite observation time. During 1979 and 1980 over the study area within the United States, there were 263 storms that had cold 37 GHz signatures. Of these storms, 15 percent were reported as severe. The relative number of storms falling in hail, wind, or tornadic categories did not differ from those expected climatologically. Critical Success Indices (CSIs) of 0.32, 0.48 and 0.38 were achieved for the low brightness temperature thresholding of severe versus nonsevere storms during 1979, 1980 and the two years combined, respectively. The preliminary indication is that a future geostationary passive microwave imaging capability at 37 GHz (or possibly higher frequencies), with sufficient spatial and temporal resolution, would facilitate the detection and monitoring of severe convective storms. This capability would provide a useful complement to radar, especially over most of the globe which is not covered by radar.

Estimation of Rainfall Rates from Passive Microwave Remote Sensing.

NASA Astrophysics Data System (ADS)

Sharma, Awdhesh Kumar

Rainfall rates have been estimated using the passive microwave and visible/infrared remote sensing techniques. Data of September 14, 1978 from the Scanning Multichannel Microwave Radiometer (SMMR) on board SEA SAT-A and the Visible and Infrared Spin Scan Radiometer (VISSR) on board GOES-W (Geostationary Operational Environmental Satellite - West) was obtained and analyzed for rainfall rate retrieval. Microwave brightness temperatures (MBT) are simulated, using the microwave radiative transfer model (MRTM) and atmospheric scattering models. These MBT were computed as a function of rates of rainfall from precipitating clouds which are in a combined phase of ice and water. Microwave extinction due to ice and liquid water are calculated using Mie-theory and Gamma drop size distributions. Microwave absorption due to oxygen and water vapor are based on the schemes given by Rosenkranz, and Barret and Chung. The scattering phase matrix involved in the MRTM is found using Eddington's two stream approximation. The surface effects due to winds and foam are included through the ocean surface emissivity model. Rainfall rates are then inverted from MBT using the optimization technique "Leaps and Bounds" and multiple linear regression leading to a relationship between the rainfall rates and MBT. This relationship has been used to infer the oceanic rainfall rates from SMMR data. The VISSR data has been inverted for the rainfall rates using Griffith's scheme. This scheme provides an independent means of estimating rainfall rates for cross checking SMMR estimates. The inferred rainfall rates from both techniques have been plotted on a world map for comparison. A reasonably good correlation has been obtained between the two estimates.

A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval

NASA Astrophysics Data System (ADS)

Takbiri, Zeinab; Ebtehaj, Ardeshir M.; Foufoula-Georgiou, Efi

2017-06-01

We present a multi-sensor Bayesian passive microwave retrieval algorithm for flood inundation mapping at high spatial and temporal resolutions. The algorithm takes advantage of observations from multiple sensors in optical, short-infrared, and microwave bands, thereby allowing for detection and mapping of the sub-pixel fraction of inundated areas under almost all-sky conditions. The method relies on a nearest-neighbor search and a modern sparsity-promoting inversion method that make use of an a priori dataset in the form of two joint dictionaries. These dictionaries contain almost overlapping observations by the Special Sensor Microwave Imager and Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) F17 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua and Terra satellites. Evaluation of the retrieval algorithm over the Mekong Delta shows that it is capable of capturing to a good degree the inundation diurnal variability due to localized convective precipitation. At longer timescales, the results demonstrate consistency with the ground-based water level observations, denoting that the method is properly capturing inundation seasonal patterns in response to regional monsoonal rain. The calculated Euclidean distance, rank-correlation, and also copula quantile analysis demonstrate a good agreement between the outputs of the algorithm and the observed water levels at monthly and daily timescales. The current inundation products are at a resolution of 12.5 km and taken twice per day, but a higher resolution (order of 5 km and every 3 h) can be achieved using the same algorithm with the dictionary populated by the Global Precipitation Mission (GPM) Microwave Imager (GMI) products.

A concept for global crop forecasting. [using microwave radiometer satellites

NASA Technical Reports Server (NTRS)

Lovelace, U. M.; Wright, R. L.

1983-01-01

The mission, instrumentation, and design concepts for microwave radiometer satellites for continuous crop condition forecasting and monitoring on a global basis are described. Soil moisture affects both crop growth and the dielectric properties of the soil, and can be quantified by analysis of reflected radiance passively received by orbiting spacecraft. A dedicated satellite reading a swath 200 km across, with 1 km and 1 K temperature resolution, could track the time-varying changes of solid moisture, sea ice, and water surface temperature. Launched by the Shuttle into an interim orbit, a boost would place the satellite in a 400 or 700 km orbit. Resolution requirements indicate a 45-725 m diam antenna, with 70 dB gain, operating at frequencies of 1.08, 2.03, and 4.95 GHz to ensure atmospheric transparency. Alternative structural concepts include either double-layer tetrahedral or single-layer geodesic trusses as the basic structural members. An analysis of the electrostatic positioning of the parabolic antenna membrane is outlined.

Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations

NASA Technical Reports Server (NTRS)

Yueh, Simon H.; Chaubell, Mario J.

2012-01-01

Several L-band microwave radiometer and radar missions have been, or will be, operating in space for land and ocean observations. These include the NASA Aquarius mission and the Soil Moisture Active Passive (SMAP) mission, both of which use combined passive/ active L-band instruments. Aquarius s passive/active L-band microwave sensor has been designed to map the salinity field at the surface of the ocean from space. SMAP s primary objectives are for soil moisture and freeze/thaw detection, but it will operate continuously over the ocean, and hence will have significant potential for ocean surface research. In this innovation, an algorithm has been developed to retrieve simultaneously ocean surface salinity and wind from combined passive/active L-band microwave observations of sea surfaces. The algorithm takes advantage of the differing response of brightness temperatures and radar backscatter to salinity, wind speed, and direction, thus minimizing the least squares error (LSE) measure, which signifies the difference between measurements and model functions of brightness temperatures and radar backscatter. The algorithm uses the conjugate gradient method to search for the local minima of the LSE. Three LSE measures with different measurement combinations have been tested. The first LSE measure uses passive microwave data only with retrieval errors reaching 1 to 2 psu (practical salinity units) for salinity, and 1 to 2 m/s for wind speed. The second LSE measure uses both passive and active microwave data for vertical and horizontal polarizations. The addition of active microwave data significantly improves the retrieval accuracy by about a factor of five. To mitigate the impact of Faraday rotation on satellite observations, the third LSE measure uses measurement combinations invariant under the Faraday rotation. For Aquarius, the expected RMS SSS (sea surface salinity) error will be less than about 0.2 psu for low winds, and increases to 0.3 psu at 25 m/s wind speed

Satellite remote sensing of the ocean

NASA Technical Reports Server (NTRS)

Fu, Lee-Lueng; Liu, W. T.; Abbott, Mark R.

1990-01-01

A concise description of the principles and applications of several selected instruments that have been utilized most frequently in remote sensing of the ocean from satellites is presented. Emphasis is placed on the current progress in oceanographic applications and the outlook of the instruments in future oceanographic satellite missions is discussed. The instruments under discussion are placed into three groups: active microwave sensors, passive ocean color and infrared sensors, and passive microwave sensors.

Consistency Between Convection Allowing Model Output and Passive Microwave Satellite Observations

NASA Astrophysics Data System (ADS)

Bytheway, J. L.; Kummerow, C. D.

2018-01-01

Observations from the Global Precipitation Measurement (GPM) core satellite were used along with precipitation forecasts from the High Resolution Rapid Refresh (HRRR) model to assess and interpret differences between observed and modeled storms. Using a feature-based approach, precipitating objects were identified in both the National Centers for Environmental Prediction Stage IV multisensor precipitation product and HRRR forecast at lead times of 1, 2, and 3 h at valid times corresponding to GPM overpasses. Precipitating objects were selected for further study if (a) the observed feature occurred entirely within the swath of the GPM Microwave Imager (GMI) and (b) the HRRR model predicted it at all three forecast lead times. Output from the HRRR model was used to simulate microwave brightness temperatures (Tbs), which were compared to those observed by the GMI. Simulated Tbs were found to have biases at both the warm and cold ends of the distribution, corresponding to the stratiform/anvil and convective areas of the storms, respectively. Several experiments altered both the simulation microphysics and hydrometeor classification in order to evaluate potential shortcomings in the model's representation of precipitating clouds. In general, inconsistencies between observed and simulated brightness temperatures were most improved when transferring snow water content to supercooled liquid hydrometeor classes.

Passive Microwave Measurements of Salinity: The Gulf Stream Experiment

NASA Technical Reports Server (NTRS)

LeVine, D. M.; Koblinsky, C.; Haken, M.; Howden, S.; Bingham, F.; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

Passive microwave sensors at L-band (1.4 GHz) operating from aircraft have demonstrated that salinity can be measured with sufficient accuracy (I psu) to be scientifically meaningful in coastal waters. However, measuring salinity in the open ocean presents unresolved issues largely because of the much greater accuracy (approximately 0.2 psu) required of global maps to be scientifically viable. The development of a satellite microwave instrument to make global measurements of SSS (Sea Surface Salinity) is the focus of a joint JPL/GSFC/NASA ocean research program called Aquarius. In the summer of 1999 a series of measurements called, The Gulf Stream Experiment, were conducted as part of research at the Goddard Space Flight Center to test the potential for passive microwave remote sensing of salinity in the open ocean. The measurements consisted of airborne microwave instruments together with ships and drifters for surface truth. The study area was a 200 km by 100 km rectangle about 250 km east of Delaware Bay between the continental shelf waters and north wall of the Gulf Stream. The primary passive instruments were the ESTAR radiometer (L-band, H-pol) and the SLFMR radiometer (L-band, V-pol). In addition, the instruments on the aircraft included a C-band radiometer (ACMR), an ocean wave scatterometer (ROWS) and an infrared radiometer (for surface temperature). These instruments were mounted on the NASA P-3 Orion aircraft. Sea surface measurements consisted of thermosalinograph data provided by the R/V Cape Henlopen and the MN Oleander, and data from salinity and temperature sensors on three surface drifters deployed from the R/V Cape Henlopen. The primary experiment period was August 26-September 2, 1999. During this period the salinity field within the study area consisted of a gradient on the order of 2-3 psu in the vicinity of the shelf break and a warm core ring with a gradient of 1-2 psu. Detailed maps were made with the airborne sensors on August 28 and 29 and

The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

NASA Astrophysics Data System (ADS)

Kelly, R. E. J.; Saberi, N.; Li, Q.

2017-12-01

With moderate to high spatial resolution (<1 km) regional to global snow water equivalent (SWE) observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides

A 1DVAR-based snowfall rate retrieval algorithm for passive microwave radiometers

NASA Astrophysics Data System (ADS)

Meng, Huan; Dong, Jun; Ferraro, Ralph; Yan, Banghua; Zhao, Limin; Kongoli, Cezar; Wang, Nai-Yu; Zavodsky, Bradley

2017-06-01

Snowfall rate retrieval from spaceborne passive microwave (PMW) radiometers has gained momentum in recent years. PMW can be so utilized because of its ability to sense in-cloud precipitation. A physically based, overland snowfall rate (SFR) algorithm has been developed using measurements from the Advanced Microwave Sounding Unit-A/Microwave Humidity Sounder sensor pair and the Advanced Technology Microwave Sounder. Currently, these instruments are aboard five polar-orbiting satellites, namely, NOAA-18, NOAA-19, Metop-A, Metop-B, and Suomi-NPP. The SFR algorithm relies on a separate snowfall detection algorithm that is composed of a satellite-based statistical model and a set of numerical weather prediction model-based filters. There are four components in the SFR algorithm itself: cloud properties retrieval, computation of ice particle terminal velocity, ice water content adjustment, and the determination of snowfall rate. The retrieval of cloud properties is the foundation of the algorithm and is accomplished using a one-dimensional variational (1DVAR) model. An existing model is adopted to derive ice particle terminal velocity. Since no measurement of cloud ice distribution is available when SFR is retrieved in near real time, such distribution is implicitly assumed by deriving an empirical function that adjusts retrieved SFR toward radar snowfall estimates. Finally, SFR is determined numerically from a complex integral. The algorithm has been validated against both radar and ground observations of snowfall events from the contiguous United States with satisfactory results. Currently, the SFR product is operationally generated at the National Oceanic and Atmospheric Administration and can be obtained from that organization.

Bridging the Global Precipitation and Soil Moisture Active Passive Missions: Variability of Microwave Surface Emissivity from In situ and Remote Sensing Perspectives

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P.; Hong, Y.; Turk, J.

2016-12-01

The overland precipitation retrievals from satellite passive microwave (PMW) sensors such as the Global Precipitation Mission (GPM) microwave imager (GMI) are impacted by the land surface emissivity. The estimation of PMW emissivity faces challenges because it is highly variable under the influence of surface properties such as soil moisture, surface roughness and vegetation. This study proposes an improved quantitative understanding of the relationship between the emissivity and surface parameters. Surface parameter information is obtained through (i) in-situ measurements from the International Soil Moisture Network and (ii) satellite measurements from the Soil Moisture Active and Passive mission (SMAP) which provides global scale soil moisture estimates. The variation of emissivity is quantified with soil moisture, surface temperature and vegetation at various frequencies/polarization and over different types of land surfaces to sheds light into the processes governing the emission of the land. This analysis is used to estimate the emissivity under rainy conditions. The framework built with in-situ measurements serves as a benchmark for satellite-based analyses, which paves a way toward global scale emissivity estimates using SMAP.

Variations in global land surface phenology: a comparison of satellite optical and passive microwave data

NASA Astrophysics Data System (ADS)

Tong, X.; Tian, F.; Brandt, M.; Zhang, W.; Liu, Y.; Fensholt, R.

2017-12-01

Changes in vegetation phenological events are among the most sensitive biological responses to climate change. In last decades, facilitating by satellite remote sensing techniques, land surface phenology (LSP) have been monitored at global scale using proxy approaches as tracking the temporal change of a satellite-derived vegetation index. However, the existing global assessments of changes in LSP are all established on the basis of leaf phenology using NDVI derived from optical sensors, being responsive to vegetation canopy cover and greenness. Instead, the vegetation optical depth (VOD) parameter from passive microwave sensors, which is sensitive to the aboveground vegetation water content by including as well the woody components in the observations, provides an alternative, independent and comprehensive means for global vegetation phenology monitoring. We used the unique long-term global VOD record available for the period 1992-2012 to monitoring the dynamics of LSP metrics (length of season, start of season and end of season) in comparison with the dynamics of LSP metrics derived from the latest GIMMS NDVI3G V1. We evaluated the differences in the linear trends of LSP metrics between two datasets. Currently, our results suggest that the level of seasonality variation of vegetation water content is less than the vegetation greenness. We found significant phenological changes in vegetation water content in African woodlands, where has been reported with little leaf phenological change regardless of the delays in rainfall onset. Therefore, VOD might allow us to detect temporal shifts in the timing difference of vegetation water storage vs. leaf emergence and to see if some ecophysiological thresholds seem to be reached, that could cause species turnover as climate change-driven alterations to the African monsoon proceed.

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Anagnostou, Emmanouil N.; Olson, William S.; Starr, David OC. (Technical Monitor)

2002-01-01

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.

An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path

NASA Astrophysics Data System (ADS)

Greenwald, Thomas J.; Bennartz, Ralf; Lebsock, Matthew; Teixeira, João.

2018-04-01

The first extended comprehensive data set of the retrieval uncertainties in passive microwave observations of cloud liquid water path (CLWP) for warm oceanic clouds has been created for practical use in climate applications. Four major sources of systematic errors were considered over the 9-year record of the Advanced Microwave Scanning Radiometer-EOS (AMSR-E): clear-sky bias, cloud-rain partition (CRP) bias, cloud-fraction-dependent bias, and cloud temperature bias. Errors were estimated using a unique merged AMSR-E/Moderate resolution Imaging Spectroradiometer Level 2 data set as well as observations from the Cloud-Aerosol Lidar with Orthogonal Polarization and the CloudSat Cloud Profiling Radar. To quantify the CRP bias more accurately, a new parameterization was developed to improve the inference of CLWP in warm rain. The cloud-fraction-dependent bias was found to be a combination of the CRP bias, an in-cloud bias, and an adjacent precipitation bias. Globally, the mean net bias was 0.012 kg/m2, dominated by the CRP and in-cloud biases, but with considerable regional and seasonal variation. Good qualitative agreement between a bias-corrected AMSR-E CLWP climatology and ship observations in the Northeast Pacific suggests that the bias estimates are reasonable. However, a possible underestimation of the net bias in certain conditions may be due in part to the crude method used in classifying precipitation, underscoring the need for an independent method of detecting rain in warm clouds. This study demonstrates the importance of combining visible-infrared imager data and passive microwave CLWP observations for estimating uncertainties and improving the accuracy of these observations.

An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path

PubMed Central

Bennartz, Ralf; Lebsock, Matthew; Teixeira, João

2018-01-01

Abstract The first extended comprehensive data set of the retrieval uncertainties in passive microwave observations of cloud liquid water path (CLWP) for warm oceanic clouds has been created for practical use in climate applications. Four major sources of systematic errors were considered over the 9‐year record of the Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E): clear‐sky bias, cloud‐rain partition (CRP) bias, cloud‐fraction‐dependent bias, and cloud temperature bias. Errors were estimated using a unique merged AMSR‐E/Moderate resolution Imaging Spectroradiometer Level 2 data set as well as observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization and the CloudSat Cloud Profiling Radar. To quantify the CRP bias more accurately, a new parameterization was developed to improve the inference of CLWP in warm rain. The cloud‐fraction‐dependent bias was found to be a combination of the CRP bias, an in‐cloud bias, and an adjacent precipitation bias. Globally, the mean net bias was 0.012 kg/m2, dominated by the CRP and in‐cloud biases, but with considerable regional and seasonal variation. Good qualitative agreement between a bias‐corrected AMSR‐E CLWP climatology and ship observations in the Northeast Pacific suggests that the bias estimates are reasonable. However, a possible underestimation of the net bias in certain conditions may be due in part to the crude method used in classifying precipitation, underscoring the need for an independent method of detecting rain in warm clouds. This study demonstrates the importance of combining visible‐infrared imager data and passive microwave CLWP observations for estimating uncertainties and improving the accuracy of these observations. PMID:29938146

CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

NASA Astrophysics Data System (ADS)

Mugnai, A.; Smith, E. A.; Tripoli, G. J.; Bizzarri, B.; Casella, D.; Dietrich, S.; Di Paola, F.; Panegrossi, G.; Sanò, P.

2013-04-01

Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters) over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW) radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome), and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD) algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR) algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale), and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are provided

Evaluation of three different data fusion approaches that uses satellite soil moisture from different passive microwave sensors to construct one consistent climate record

NASA Astrophysics Data System (ADS)

van der Schalie, Robin; de Jeu, Richard; Kerr, Yann; Wigneron, Jean-Pierre; Rodríguez-Fernández, Nemesio; Al-Yaari, Amen; Drusch, Matthias; Mecklenburg, Susanne; Dolman, Han

2016-04-01

Datasets that are derived from satellite observations are becoming increasingly important for measuring key parameters of the Earth's climate and are therefore crucial in research on climate change, giving the opportunity to researchers to detect anomalies and long-term trends globally. One of these key parameters is soil moisture (SM), which has a large impact on water, energy and biogeochemical cycles worldwide. A long-term SM data record from active and passive microwave satellite observations was developed as part of ESA's Climate Change Initiative (ESA-CCI-SM, http://www.esa-soilmoisture-cci.org/). Currently the dataset covers a period from 1978 to 2014 and is updated regularly, observations from a several microwave satellites including: ERS-1, ERS-2, METOP-A, Nimbus 7 SMMR, DMSP SSM/I, TRMM TMI, Aqua AMSRE, Coriolis WindSat, and GCOM-W1 AMSR2. In 2009, ESA launched the Soil Moisture and Ocean Salinity (SMOS, Kerr et al., 2010) mission, carrying onboard a unique L-band radiometer, but its SM retrievals are not yet part of this dataset. Due to the different radiometric characteristics of SMOS, integrating SMOS into the ESA-CCI-SM dataset is not straight forward. Therefore several approaches have been tested to fuse soil moisture retrievals from SMOS and AMSRE, which currently forms the basis of the passive microwave part within ESA-CCI-SM project. These approaches are: 1. A Neural Network Fusion approach (Rodríguez-Fernández et al., 2015), 2. A regression approach (Wigneron et al., 2004; Al-Yaari et al., 2015) and 3. A radiative transfer based approach, using the Land Parameter Retrieval Model (Van der Schalie et al., 2016). This study evaluates the three different approaches and tests their skills against multiple datasets, including MERRA-Land, ERA-Interim/Land, the current ESA-CCI-SM v2.2 and in situ measurements from the International Soil Moisture Network and present a recommendation for the potential integration of SMOS soil moisture into the ESA

Global relation between microwave satellite vegetation products and vegetation productivity

NASA Astrophysics Data System (ADS)

Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Miralles, Diego G.; Dorigo, Wouter A.

2017-04-01

The occurrence of unfavourable environmental conditions like droughts commonly reduces the photosynthetic activity of ecosystems and, hence, their potential to take up carbon from the atmosphere. Ecosystem photosynthetic activity is commonly determined using remote sensing observations in the optical domain, which however have limitations particularly in regions of frequent cloud cover, e.g. the tropics. In this study, we explore the potential of vegetation optical depth (VOD) from microwave satellite observations as an alternative source for assessing vegetation productivity. VOD serves as an estimate for vegetation density and water content, which has an impact on plant physiological processes and hence should potentially provide a link to gross primary production (GPP). However, to date, it is unclear how microwave-retrieved VOD data and GPP data are related. We compare seasonal dynamics and anomalies of VOD retrievals from different satellite sensors and microwave frequencies with site level and global GPP estimates. We use VOD observations from active (ASCAT) and passive microwave sensors (AMSR-E, SMOS). We include eddy covariance measurements from the FLUXNET2015 dataset to assess the VOD products at site level. For a global scale analysis, we use the solar-induced chlorophyll fluorescence (SIF) observations from GOME-2 as a proxy for GPP and the FLUXCOM GPP product, which presents an upscaling of site measurements based on remote sensing data. Our results demonstrate that in general a good agreement between VOD and GPP or SIF exists. However, the strength of these relations depends on the microwave frequency, land cover type, and the time within the growing season. Correlations between anomalies of VOD and GPP or SIF support the assumption that microwave-derived VOD can be used to monitor vegetation productivity dynamics. The study is performed as part of the EOWAVE project funded by the Vienna University of Technology (http://eowave.geo.tuwien.ac.at/) and

Infrared and Passive Microwave Radiometric Sea Surface Temperatures and Their Relationships to Atmospheric Forcing

NASA Technical Reports Server (NTRS)

Castro, Sandra L.

2004-01-01

The current generation of infrared (IR) and passive microwave (MW) satellite sensors provides highly complementary information for monitoring sea surface temperature (SST). On the one hand, infrared sensors provide high resolution and high accuracy but are obscured by clouds. Microwave sensors on the other hand, provide coverage through non-precipitating clouds but have coarser resolution and generally poorer accuracy. Assuming that the satellite SST measurements do not have spatially variable biases, they can be blended combining the merits of both SST products. These factors have motivated recent work in blending the MW and IR data in an attempt to produce high-accuracy SST products with improved coverage in regions with persistent clouds. The primary sources of retrieval uncertainty are, however, different for the two sensors. The main uncertainty in the MW retrievals lies in the effects of wind-induced surface roughness and foam on emissivity, whereas the IR retrievals are more sensitive to the atmospheric water vapor and aerosol content. Average nighttime differences between the products for the month periods of January 1999 and June 2000 are shown. These maps show complex spatial and temporal differences as indicated by the strong spatially coherent features in the product differences and the changes between seasons. Clearly such differences need to be understood and accounted for if the products are to be combined. The overall goals of this project are threefold: (1) To understand the sources of uncertainty in the IR and MW SST retrievals and to characterize the errors affecting the two types of retrieval as a fiction of atmospheric forcing; (2) To demonstrate how representative the temperature difference between the two satellite products is of Delta T; (3) To apply bias adjustments and to device a comprehensive treatment of the behavior of the temperature difference across the oceanic skin layer to determine the best method for blending thermal infrared

The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

2017-12-01

The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will

High spatial resolution passive microwave sounding systems

NASA Technical Reports Server (NTRS)

Staelin, D. H.; Rosenkranz, P. W.; Bonanni, P. G.; Gasiewski, A. W.

1986-01-01

Two extensive series of flights aboard the ER-2 aircraft were conducted with the MIT 118 GHz imaging spectrometer together with a 53.6 GHz nadir channel and a TV camera record of the mission. Other microwave sensors, including a 183 GHz imaging spectrometer were flown simultaneously by other research groups. Work also continued on evaluating the impact of high-resolution passive microwave soundings upon numerical weather prediction models.

Active/passive microwave sensor comparison of MIZ-ice concentration estimates. [Marginal Ice Zone (MIZ)

NASA Technical Reports Server (NTRS)

Burns, B. A.; Cavalieri, D. J.; Keller, M. R.

1986-01-01

Active and passive microwave data collected during the 1984 summer Marginal Ice Zone Experiment in the Fram Strait (MIZEX 84) are used to compare ice concentration estimates derived from synthetic aperture radar (SAR) data to those obtained from passive microwave imagery at several frequencies. The comparison is carried out to evaluate SAR performance against the more established passive microwave technique, and to investigate discrepancies in terms of how ice surface conditions, imaging geometry, and choice of algorithm parameters affect each sensor. Active and passive estimates of ice concentration agree on average to within 12%. Estimates from the multichannel passive microwave data show best agreement with the SAR estimates because the multichannel algorithm effectively accounts for the range in ice floe brightness temperatures observed in the MIZ.

Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics

PubMed Central

Chuang, Ting-Wu; Henebry, Geoffrey M.; Kimball, John S.; VanRoekel-Patton, Denise L.; Hildreth, Michael B.; Wimberly, Michael C.

2012-01-01

Environmental variability has important influences on mosquito life cycles and understanding the spatial and temporal patterns of mosquito populations is critical for mosquito control and vector-borne disease prevention. Meteorological data used for model-based predictions of mosquito abundance and life cycle dynamics are typically acquired from ground-based weather stations; however, data availability and completeness are often limited by sparse networks and resource availability. In contrast, environmental measurements from satellite remote sensing are more spatially continuous and can be retrieved automatically. This study compared environmental measurements from the NASA Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and in situ weather station data to examine their ability to predict the abundance of two important mosquito species (Aedes vexans and Culex tarsalis) in Sioux Falls, South Dakota, USA from 2005 to 2010. The AMSR-E land parameters included daily surface water inundation fraction, surface air temperature, soil moisture, and microwave vegetation opacity. The AMSR-E derived models had better fits and higher forecasting accuracy than models based on weather station data despite the relatively coarse (25-km) spatial resolution of the satellite data. In the AMSR-E models, air temperature and surface water fraction were the best predictors of Aedes vexans, whereas air temperature and vegetation opacity were the best predictors of Cx. tarsalis abundance. The models were used to extrapolate spatial, seasonal, and interannual patterns of climatic suitability for mosquitoes across eastern South Dakota. Our findings demonstrate that environmental metrics derived from satellite passive microwave radiometry are suitable for predicting mosquito population dynamics and can potentially improve the effectiveness of mosquito-borne disease early warning systems. PMID:23049143

Topical cyclone rainfall characteristics as determined from a satellite passive microwave radiometer

NASA Technical Reports Server (NTRS)

Rodgers, E. B.; Adler, R. F.

1979-01-01

Data from the Nimbus-5 Electrically Scanning Microwave Radiometer (ESMR-5) were used to calculate latent heat release and other rainfall parameters for over 70 satellite observations of 21 tropical cyclones in the tropical North Pacific Ocean. The results indicate that the ESMR-5 measurements can be useful in determining the rainfall characteristics of these storms and appear to be potentially useful in monitoring as well as predicting their intensity. The ESMR-5 derived total tropical cyclone rainfall estimates agree favorably with previous estimates for both the disturbance and typhoon stages. The mean typhoon rainfall rate (1.9 mm h(-1)) is approximately twice that of disturbances (1.1 mm h(-1)).

Satellite and aircraft passive microwave observations during the Marginal Ice Zone Experiment in 1984

NASA Technical Reports Server (NTRS)

Gloersen, Per; Campbell, William J.

1988-01-01

This paper compares satellite data on the marginal ice zone obtained during the Marginal Ice Zone Experiment in 1984 by Nimbus 7 with simultaneous mesoscale aircraft (in particular, the NASA CV-990 airborne laboratory) and surface observations. Total and multiyear sea ice concentrations calculated from the airborne multichannel microwave radiometer were found to agree well with similar calculations using the Nimbus SMMR data. The temperature dependence of the determination of multiyear sea-ice concentration near the melting point was found to be the same for both airborne and satellite data. It was found that low total ice concentrations and open-water storm effects near the ice edge could be reliably distinguished by means of spectral gradient ratio, using data from the 0.33-cm and the 1.55-cm radiometers.

Satellite passive microwaves for monitoring deforestation and drought-induced carbon losses in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Brandt, M.; Wigneron, J. P.; Chave, J.; Tagesson, T.; Penuelas, J.; Ciais, P.; Rasmussen, K.; Tian, F.; Mbow, C.; Al-Yaari, A.; Rodriguez-Fernandez, N.; Zhang, W.; Kerr, Y. H.; Tucker, C. J.; Mialon, A.; Verger, A.; Fensholt, R.

2017-12-01

The African continent is facing one of the driest periods in the past three decades and continuing deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for an operational tool for monitoring carbon stock dynamics. Knowledge of the amount, distribution, and turnover of carbon in African vegetation is crucial for understanding the effects of human pressure and climate change, but the shortcomings of optical and radar satellite products and the lack of systematic field inventories have led to considerable uncertainty in documenting patterns and dynamics of carbon stocks, in particular for drylands. Static carbon maps have been developed, but the temporal dynamics of carbon stocks cannot be derived from the benchmark maps, impeding timely, repeated, and reliable carbon assessments. The Soil Moisture and Ocean Salinity (SMOS) mission launched in 2009 was the first passive microwave-based satellite system operating at L-band (1.4 GHz) frequency. The low frequencies allow the satellite to sense deep within the canopy layer with less influence by the green non-woody plant components. The vegetation optical depth (VOD) derived from SMOS, henceforth L-VOD, is thus less sensitive to saturation effects, marking an important step forward in the monitoring of carbon as a natural resource. In this study, we apply for the first time L-VOD to quantify the inter-annual dynamics of aboveground carbon stocks for the period 2010-2016. We use this new technique to document patterns of carbon gains and losses in sub-Saharan Africa with a focus of dryland response to recent dry years. Results show that drylands lost carbon at a rate of -0.06 Pg C y-1 associated with drying trends, while humid areas lost only -0.02 Pg C y-1. These trends reflect a high inter-annual variability with a very wet (2011) and a very dry year (2016) associated with carbon gains and losses respectively. This study demonstrates, first, the operational applicability of L

A Long-Term and Reproducible Passive Microwave Sea Ice Concentration Data Record for Climate Studies and Monitoring

NASA Technical Reports Server (NTRS)

Peng, G.; Meier, W. N.; Scott, D. J.; Savoie, M. H.

2013-01-01

A long-term, consistent, and reproducible satellite-based passive microwave sea ice concentration climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea ice concentration data are on the National Snow and Ice Data Center (NSIDC) polar stereographic grid with nominal 25 km × 25 km grid cells in both the Southern and Northern Hemisphere polar regions from 9 July 1987 to 31 December 2007. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea ice concentration CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The data set, along with detailed data processing steps and error source information, can be found at http://dx.doi.org/10.7265/N5B56GN3.

WWLLN lightning and satellite microwave radiometrics at 37 to 183 GHz: Thunderstorms in the broad tropics

NASA Astrophysics Data System (ADS)

Solorzano, N. N.; Thomas, J. N.; Hutchins, M. L.; Holzworth, R. H.

2016-10-01

We investigate lightning strokes and deep convection through the examination of cloud-to-ground (CG) lightning from the World Wide Lightning Location Network (WWLLN) and passive microwave radiometer data. Microwave channels at 37 to 183.3 GHz are provided by the Tropical Rainfall Measuring Mission satellite (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave Imager/Sounder (SSMIS) on the Defense Meteorological Satellite Program (DMSP) satellite F16. The present study compares WWLLN stroke rates and minimum radiometer brightness temperatures (Tbs) for two Northern Hemisphere and Southern Hemisphere summers (2009-2011) in the broad tropics (35°S to 35°N). To identify deep convection, we use lightning data and Tbs derived from all channels and differences in the Tbs (ΔTbs) of the three water vapor channels near 183.3 GHz. We find that stroke probabilities increase with increasing Tb depressions for all frequencies examined. Moreover, we apply methods that use the 183.3 GHz channels to pinpoint deep convection associated with lightning. High lightning stroke probabilities are found over land regions for both intense and relatively weak convective systems, although the TMI 85 GHz results should be used with caution as they are affected by a 7 km gap between the conical scans. Over the ocean, lightning is associated mostly with larger Tb depressions. Generally, our results support the noninductive thundercloud charging mechanism but do not rule out the inductive mechanism during the mature stages of storms. Lastly, we present a case study in which lightning stroke rates are used to reconstruct microwave radiometer Tbs.

Report from the Passive Microwave Data Set Management Workshop

NASA Technical Reports Server (NTRS)

Armstrong, Ed; Conover, Helen; Goodman, Michael; Krupp, Brian; Liu, Zhong; Moses, John; Ramapriyan, H. K.; Scott, Donna; Smith, Deborah; Weaver, Ronald

2011-01-01

Passive microwave data sets are some of the most important data sets in the Earth Observing System Data and Information System (EOSDIS), providing data as far back as the early 1970s. The widespread use of passive microwave (PM) radiometer data has led to their collection and distribution over the years at several different Earth science data centers. The user community is often confused by this proliferation and the uneven spread of information about the data sets. In response to this situation, a Passive Microwave Data Set Management Workshop was held 17 ]19 May 2011 at the Global Hydrology Resource Center, sponsored by the NASA Earth Science Data and Information System (ESDIS) Project. The workshop attendees reviewed all primary (Level 1 ]3) PM data sets from NASA and non ]NASA sensors held by NASA Distributed Active Archive Centers (DAACs), as well as high ]value data sets from other NASA ]funded organizations. This report provides the key findings and recommendations from the workshop as well as detailed tabluations of the datasets considered.

Improving Global Analysis and Short-Range Forecast Using Rainfall and Moisture Observations Derived from TRMM and SSM/I Passive Microwave Instruments

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.; Kummerow, Christian D.; Simpson, Joanne

2000-01-01

The Global Precipitation Mission, a satellite project under consideration as a follow-on to the Tropical Rainfall Measuring Mission (TRMM) by the National Aeronautics and Space Agency (NASA) in the United States, the National Space Development Agency (NASDA) in Japan, and other international partners, comprises an improved TRMM-like satellite and a constellation of 8 satellites carrying passive microwave radiometers to provide global rainfall measurements at 3-hour intervals. The success of this concept relies on the merits of rainfall estimates derived from passive microwave radiometers. This article offers a proof-of-concept demonstration of the benefits of using, rainfall and total precipitable water (TPW) information derived from such instruments in global data assimilation with observations from the TRMM Microwave Imager (TMI) and 2 Special Sensor Microwave/Imager (SSM/I) instruments. Global analyses that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data analyses contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. We show that assimilating the 6-h averaged TMI and SSM/I surface rainrate and TPW retrievals improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the upper tropospheric moisture in the analysis produced by the Goddard Earth Observing System (GEOS) Data Assimilation System, as verified against radiation measurements by the Clouds and the Earth's Radiant Energy System (CERES) instrument and brightness temperature observations by the TIROS Operational Vertical Sounder (TOVS) instruments. Typically, rainfall assimilation improves clouds and radiation in areas of active convection, as well as the latent heating and large-scale motions in the tropics, while TPW assimilation leads to reduced

Estimating the Thickness of Sea Ice Snow Cover in the Weddell Sea from Passive Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Arrigo, K. R.; vanDijken, G. L.; Comiso, J. C.

1996-01-01

Passive microwave satellite observations have frequently been used to observe changes in sea ice cover and concentration. Comiso et al. showed that there may also be a direct relationship between the thickness of snow cover (h(sub s)) on ice and microwave emissivity at 90 GHz. Because the in situ experiment of experiment of Comiso et al. was limited to a single station, the relationship is re-examined in this paper in a more general context and using more extensive in situ microwave observations and measurements of h from the Weddell Sea 1986 and 1989 winter cruises. Good relationships were found to exist between h(sub s) sand the emissivity at 90 GHz - 10 GHz and the emissivity at 90 GHz - 18.7 GHz when the standard deviation of h(sub s) was less than 50% of the mean and when h(sub s) was less than 0.25 m. The reliance of these relationships on h(sub s) is most likely caused by the limited penetration through the snow of radiation at 90 GHz. When the algorithm was applied to the Special Sensor Microwave/Imager (SSM/I) satellite data from the Weddell Sea, the resulting mean h(sub s) agreed within 5% of the mean calculated from greater than 1400 in situ observations.

High Resolution Freeze and Thaw States Detection Using Combination of Sentinel 1A SAR and Passive Microwave Measurements

NASA Astrophysics Data System (ADS)

Azarderakhsh, M.; McDonald, K. C.; Norouzi, H.; Rebolledo, M. A.; Prakash, S.

2017-12-01

The freeze and thaw (FT) cycles in high-latitude regions have great impact on many biogeochemical transitions, hydrology and ecosystem especially in wetland areas. Passive and active microwave remote sensing data from satellite observations have been deployed in the past to define the status of the surface in terms of freeze and thaw. While many progresses have been made in this field, the limitations attached to such observations have hindered our ability to fully predict the change of surface state in the scale that is appropriate for the aforementioned applications. The transition between freeze and thaw states may occur frequently (even within a day) especially during shifts from cold to warm seasons and vice versa. Passive microwave sensors have different acquisition times, and data fusion of these sensors may provide a complete diurnal variation estimate of FT states. However, the coarse spatial resolution of these measurements may undermine their applicability. However, active microwave backscatter measurements from sensors such as Sentinel 1A and the Advanced Land Observing Satellite Phased Array L-Band SAR (ALOS PALSAR) can deliver high resolution information about wetlands and FT status. In this project, Synthetic Aperture Radar (SAR) c-band backscatter data from Sentinel 1 from April 2014 to June 2017 are deployed to detect high resolution freeze/thaw states and wetland areas. The contrasts between frozen and thawed seasons are used to define FT states after performing required radiometric corrections and calibrations. A method based on phase changes in polarized images is developed for different land cover types to maximize the accuracy of the detections. The aggregated (up-scaled) estimates from active measurements are compared to passive microwave-based FT product. The results of this method reveal that the estimates are relatively in good agreement with SNOw TELemetry (SNOTEL) ground measurements. Finally, a downscaling method is tried to link

A method for combining passive microwave and infrared rainfall observations

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Giglio, Louis

1995-01-01

Because passive microwave instruments are confined to polar-orbiting satellites, rainfall estimates must interpolate across long time periods, during which no measurements are available. In this paper the authors discuss a technique that allows one to partially overcome the sampling limitations by using frequent infrared observations from geosynchronous platforms. To accomplish this, the technique compares all coincident microwave and infrared observations. From each coincident pair, the infrared temperature threshold is selected that corresponds to an area equal to the raining area observed in the microwave image. The mean conditional rainfall rate as determined from the microwave image is then assigned to pixels in the infrared image that are colder than the selected threshold. The calibration is also applied to a fixed threshold of 235 K for comparison with established infrared techniques. Once a calibration is determined, it is applied to all infrared images. Monthly accumulations for both methods are then obtained by summing rainfall from all available infrared images. Two examples are used to evaluate the performance of the technique. The first consists of a one-month period (February 1988) over Darwin, Australia, where good validation data are available from radar and rain gauges. For this case it was found that the technique approximately doubled the rain inferred by the microwave method alone and produced exceptional agreement with the validation data. The second example involved comparisons with atoll rain gauges in the western Pacific for June 1989. Results here are overshadowed by the fact that the hourly infrared estimates from established techniques, by themselves, produced very good correlations with the rain gauges. The calibration technique was not able to improve upon these results.

Silicon carbide passive heating elements in microwave-assisted organic synthesis.

PubMed

Kremsner, Jennifer M; Kappe, C Oliver

2006-06-09

Microwave-assisted organic synthesis in nonpolar solvents is investigated utilizing cylinders of sintered silicon carbide (SiC)--a chemically inert and strongly microwave absorbing material--as passive heating elements (PHEs). These heating inserts absorb microwave energy and subsequently transfer the generated thermal energy via conduction phenomena to the reaction mixture. The use of passive heating elements allows otherwise microwave transparent or poorly absorbing solvents such as hexane, carbon tetrachloride, tetrahydrofuran, dioxane, or toluene to be effectively heated to temperatures far above their boiling points (200-250 degrees C) under sealed vessel microwave conditions. This opens up the possibility to perform microwave synthesis in unpolar solvent environments as demonstrated successfully for several organic transformations, such as Claisen rearrangements, Diels-Alder reactions, Michael additions, N-alkylations, and Dimroth rearrangements. This noninvasive technique is a particularly valuable tool in cases where other options to increase the microwave absorbance of the reaction medium, such as the addition of ionic liquids as heating aids, are not feasible due to an incompatibility of the ionic liquid with a particular substrate. The SiC heating elements are thermally and chemically resistant to 1500 degrees C and compatible with any solvent or reagent.

Verification of a New NOAA/NSIDC Passive Microwave Sea-Ice Concentration Climate Record

NASA Technical Reports Server (NTRS)

Meier, Walter N.; Peng, Ge; Scott, Donna J.; Savoie, Matt H.

2014-01-01

A new satellite-based passive microwave sea-ice concentration product developed for the National Oceanic and Atmospheric Administration (NOAA)Climate Data Record (CDR) programme is evaluated via comparison with other passive microwave-derived estimates. The new product leverages two well-established concentration algorithms, known as the NASA Team and Bootstrap, both developed at and produced by the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC). The sea ice estimates compare well with similar GSFC products while also fulfilling all NOAA CDR initial operation capability (IOC) requirements, including (1) self describing file format, (2) ISO 19115-2 compliant collection-level metadata,(3) Climate and Forecast (CF) compliant file-level metadata, (4) grid-cell level metadata (data quality fields), (5) fully automated and reproducible processing and (6) open online access to full documentation with version control, including source code and an algorithm theoretical basic document. The primary limitations of the GSFC products are lack of metadata and use of untracked manual corrections to the output fields. Smaller differences occur from minor variations in processing methods by the National Snow and Ice Data Center (for the CDR fields) and NASA (for the GSFC fields). The CDR concentrations do have some differences from the constituent GSFC concentrations, but trends and variability are not substantially different.

Toward all weather, long record, and real-time land surface temperature retrievals from microwave satellite observations

NASA Astrophysics Data System (ADS)

Jimenez, Carlos; Prigent, Catherine; Aires, Filipe; Ermida, Sofia

2017-04-01

The land surface temperature can be estimated from satellite passive microwave observations, with limited contamination from the clouds as compared to the infrared satellite retrievals. With ˜60% cloud cover in average over the globe, there is a need for "all weather," long record, and real-time estimates of land surface temperature (Ts) from microwaves. A simple yet accurate methodology is developed to derive the land surface temperature from microwave conical scanner observations, with the help of pre-calculated land surface microwave emissivities. The method is applied to the Special Sensor Microwave/Imagers (SSM/I) and the Earth observation satellite (EOS) Advanced Microwave Scanning Radiometer (AMSR-E) observations?, regardless of the cloud cover. The SSM/I results are compared to infrared estimates from International Satellite Cloud Climatology Project (ISCCP) and from Advanced Along Track Scanning Radiometer (AATSR), under clear-sky conditions. Limited biases are observed (˜0.5 K for both comparisons) with a root-mean-square difference (RMSD) of ˜5 K, to be compared to the RMSE of ˜3.5 K between ISCCP et AATSR. AMSR-E results are compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky estimates. As both instruments are on board the same satellite, this reduces the uncertainty associated to the observations match-up, resulting in a lower RMSD of ˜ 4K. The microwave Ts is compared to in situ Ts time series from a collection of ground stations over a large range of environments. For 22 stations available in the 2003-2004 period, SSM/I Ts agrees very well for stations in vegetated environments (down to RMSD of ˜2.5 K for several stations), but the retrieval methodology encounters difficulties under cold conditions due to the large variability of snow and ice surface emissivities. For 10 stations in the year 2010, AMSR-E presents an all-station mean RMSD of ˜4.0 K with respect tom the ground Ts. Over the same stations, MODIS

Disaggregation Of Passive Microwave Soil Moisture For Use In Watershed Hydrology Applications

NASA Astrophysics Data System (ADS)

Fang, Bin

In recent years the passive microwave remote sensing has been providing soil moisture products using instruments on board satellite/airborne platforms. Spatial resolution has been restricted by the diameter of antenna which is inversely proportional to resolution. As a result, typical products have a spatial resolution of tens of kilometers, which is not compatible for some hydrological research applications. For this reason, the dissertation explores three disaggregation algorithms that estimate L-band passive microwave soil moisture at the subpixel level by using high spatial resolution remote sensing products from other optical and radar instruments were proposed and implemented in this investigation. The first technique utilized a thermal inertia theory to establish a relationship between daily temperature change and average soil moisture modulated by the vegetation condition was developed by using NLDAS, AVHRR, SPOT and MODIS data were applied to disaggregate the 25 km AMSR-E soil moisture to 1 km in Oklahoma. The second algorithm was built on semi empirical physical models (NP89 and LP92) derived from numerical experiments between soil evaporation efficiency and soil moisture over the surface skin sensing depth (a few millimeters) by using simulated soil temperature derived from MODIS and NLDAS as well as AMSR-E soil moisture at 25 km to disaggregate the coarse resolution soil moisture to 1 km in Oklahoma. The third algorithm modeled the relationship between the change in co-polarized radar backscatter and the remotely sensed microwave change in soil moisture retrievals and assumed that change in soil moisture was a function of only the canopy opacity. The change detection algorithm was implemented using aircraft based the remote sensing data from PALS and UAVSAR that were collected in SMPAVEX12 in southern Manitoba, Canada. The PALS L-band h-polarization radiometer soil moisture retrievals were disaggregated by combining them with the PALS and UAVSAR L

Error Characterisation and Merging of Active and Passive Microwave Soil Moisture Data Sets

NASA Astrophysics Data System (ADS)

Wagner, Wolfgang; Gruber, Alexander; de Jeu, Richard; Parinussa, Robert; Chung, Daniel; Dorigo, Wouter; Reimer, Christoph; Kidd, Richard

2015-04-01

As part of the Climate Change Initiative (CCI) programme of the European Space Agency (ESA) a data fusion system has been developed which is capable of ingesting surface soil moisture data derived from active and passive microwave sensors (ASCAT, AMSR-E, etc.) flown on different satellite platforms and merging them to create long and consistent time series of soil moisture suitable for use in climate change studies. The so-created soil moisture data records (latest version: ESA CCI SM v02.1 released on 5/12/2014) are freely available and can be obtained from http://www.esa-soilmoisture-cci.org/. As described by Wagner et al. (2012) the principle steps of the data fusion process are: 1) error characterisation, 2) matching to account for data set specific biases, and 3) merging. In this presentation we present the current data fusion process and discuss how new error characterisation methods, such as the increasingly popular triple collocation method as discussed for example by Zwieback et al. (2012) may be used to improve it. The main benefit of an improved error characterisation would be a more reliable identification of the best performing microwave soil moisture retrieval(s) for each grid point and each point in time. In case that two or more satellite data sets provides useful information, the estimated errors can be used to define the weights with which each satellite data set are merged, i.e. the lower its error the higher its weight. This is expected to bring a significant improvement over the current data fusion scheme which is not yet based on quantitative estimates of the retrieval errors but on a proxy measure, namely the vegetation optical depth (Dorigo et al., 2015): over areas with low vegetation passive soil moisture retrievals are used, while over areas with moderate vegetation density active retrievals are used. In transition areas, where both products correlate well, both products are being used in a synergistic way: on time steps where only one of

Improved Passive Microwave Algorithms for North America and Eurasia

NASA Technical Reports Server (NTRS)

Foster, James; Chang, Alfred; Hall, Dorothy

1997-01-01

Microwave algorithms simplify complex physical processes in order to estimate geophysical parameters such as snow cover and snow depth. The microwave radiances received at the satellite sensor and expressed as brightness temperatures are a composite of contributions from the Earth's surface, the Earth's atmosphere and from space. Owing to the coarse resolution inherent to passive microwave sensors, each pixel value represents a mixture of contributions from different surface types including deep snow, shallow snow, forests and open areas. Algorithms are generated in order to resolve these mixtures. The accuracy of the retrieved information is affected by uncertainties in the assumptions used in the radiative transfer equation (Steffen et al., 1992). One such uncertainty in the Chang et al., (1987) snow algorithm is that the snow grain radius is 0.3 mm for all layers of the snowpack and for all physiographic regions. However, this is not usually the case. The influence of larger grain sizes appears to be of more importance for deeper snowpacks in the interior of Eurasia. Based on this consideration and the effects of forests, a revised SMMR snow algorithm produces more realistic snow mass values. The purpose of this study is to present results of the revised algorithm (referred to for the remainder of this paper as the GSFC 94 snow algorithm) which incorporates differences in both fractional forest cover and snow grain size. Results from the GSFC 94 algorithm will be compared to the original Chang et al. (1987) algorithm and to climatological snow depth data as well.

Sensitivity of Active and Passive Microwave Observations to Soil Moisture during Growing Corn

NASA Astrophysics Data System (ADS)

Judge, J.; Monsivais-Huertero, A.; Liu, P.; De Roo, R. D.; England, A. W.; Nagarajan, K.

2011-12-01

Soil moisture (SM) in the root zone is a key factor governing water and energy fluxes at the land surface and its accurate knowledge is critical to predictions of weather and near-term climate, nutrient cycles, crop-yield, and ecosystem productivity. Microwave observations, such as those at L-band, are highly sensitive to soil moisture in the upper few centimeters (near-surface). The two satellite-based missions dedicated to soil moisture estimation include, the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission and the planned NASA Soil Moisture Active/Passive (SMAP) [4] mission. The SMAP mission will include active and passive sensors at L-band to provide global observations of SM, with a repeat coverage of every 2-3 days. These observations can significantly improve root zone soil moisture estimates through data assimilation into land surface models (LSMs). Both the active (radar) and passive (radiometer) microwave sensors measure radiation quantities that are functions of soil dielectric constant and exhibit similar sensitivities to SM. In addition to the SM sensitivity, radar backscatter is highly sensitive to roughness of soil surface and scattering within the vegetation. These effects may produce a much larger dynamic range in backscatter than that produced due to SM changes alone. In this study, we discuss the field observations of active and passive signatures of growing corn at L-band from several seasons during the tenth Microwave, Water and Energy Balance Experiment (MicroWEX-10) conducted in North Central Florida, and to understand the sensitivity of these signatures to soil moisture under dynamic vegetation conditions. The MicroWEXs are a series of season-long field experiments conducted during the growing seasons of sweet corn, cotton, and energy cane over the past six years (for example, [22]). The corn was planted on July 5 and harvested on September 23, 2011 during MicroWEX-10. The size of the field was 0.04 km2 and the soils

Estimating Soil Moisture from Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Owe, M.; VandeGriend, A. A.; deJeu, R.; deVries, J.; Seyhan, E.

1998-01-01

Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data

Arctic sea-ice variations from time-lapse passive microwave imagery

USGS Publications Warehouse

Campbell, W.J.; Ramseier, R.O.; Zwally, H.J.; Gloersen, P.

1980-01-01

This paper presents: (1) a short historical review of the passive microwave research on sea ice which established the observational and theoretical base permitting the interpretation of the first passive microwave images of Earth obtained by the Nimbus-5 ESMR; (2) the construction of a time-lapse motion picture film of a 16-month set of serial ESMR images to aid in the formidable data analysis task; and (3) a few of the most significant findings resulting from an early analysis of these data, using selected ESMR images to illustrate these findings. ?? 1980 D. Reidel Publishing Co.

An Orbital "Virtual Radar" from TRMM Passive Microwave and Lightning Observations

NASA Technical Reports Server (NTRS)

Boccippio, Dennis J.

2004-01-01

The retrieval of vertical structure from joint passive microwave and lightning observations is demonstrated. Three years of data from the TRMM (Tropical Rainfall Measuring Mission) are used as a training dataset for regression and classification neural networks; the TMI (TRMM Microwave Imager) and LIS (Lightning Imaging Sensor) provide the inputs, the PR (Precipitation Radar) provides the training targets. Both vertical reflectivity profile categorization (into 9 convective, 7 stratiform, 2 mixed and 6 anvil types) and geophysical parameters (surface rainfall, vertically integrated liquid (VIL), ice water content (IWC) and echo tops) are retrieved. Retrievals are successful over both land and ocean surfaces. The benefit of using lightning observations as inputs to these retrievals is quantitatively demonstrated; lightning essentially provides an additional convective/stratiform discriminator, and is most important for isolation of midlevel (tops in the mixed phase region) convective profile types (this is because high frequency passive microwave observations already provide good convective/stratiform discrimination for deep convective profiles). This is highly relevant as midlevel convective profiles account for an extremely large fraction of tropical rainfall, and yet are most difficult to discriminate from comparable-depth stratiform profile types using passive microwave observations alone.

History of Satellite Observations of East Pacific Atmospheric Rivers

NASA Astrophysics Data System (ADS)

Vonder Haar, T. H.; Forsythe, J. M.; Seaman, C.

2017-12-01

The terms "Atmospheric River" or "Tropospheric River" were not used in refereed literature until the 1990's, although earlier works hinted at the existence of narrow corridors of moisture transport. With the advent of satellite observations in the 1960's, meteorologists began to discover the fingerprints of these phenomena via cloud observations. Early geostationary satellites depicted "cloud rivers" or "pipeline cirrus" impacting the U.S. west coast, with only indirect evidence of large water vapor transport. Routine use of passive microwave imagery to retrieve total column water vapor began in the late 1980's with the launch of the Special Sensor Microwave / Imager instrument, whose descendants continue to provide realtime monitoring of atmospheric rivers today. Passive microwave data opened the door to quantitative studies of atmospheric rivers, by providing the water vapor measurements needed to compute integrated moisture flux. Atmospheric rivers are detected in near-realtime from passive microwave water vapor products. In recent years, dedicated coastal observatories, multidecadal global water vapor data sets, cloud radars, and satellite sounding systems have begun to probe the 4-dimensional moisture structure of atmospheric rivers. The timeline of our understanding of atmospheric rivers will be presented from the standpoint of evolving satellite observing systems.

Target detection using microwave irradiances from natural sources: A passive, local and global surveillance system

NASA Technical Reports Server (NTRS)

Stacey, J. M.

1984-01-01

Detection of metal objects on or near the Earth's surface was investigated using existing, passive, microwave sensors operating from Earth orbit. The range equations are derived from basic microwave principles and theories and the expressions are given explicitly to estimate the signal to noise ratio for detecting metal targets operating as bistatic scatterers. Actual measurements are made on a range of metal objects observed from orbit using existing passive microwave receiving systems. The details of the measurements and the results are tabulated and discussed. The advantages of a passive microwave sensor as it is applied to surveillance of metal objects as viewed from aerial platforms or from orbit, are examined.

A Look at Seasonal Snow Cover and Snow Mass in the Southern Hemisphere from 1979-2006 Using SMMR and SSM/I Passive Microwave Data

NASA Technical Reports Server (NTRS)

Foster, James

2009-01-01

Seasonal snow cover in extra-tropical areas of South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and from the Special Sensor Microwave Imagers (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow mass were estimated for the months of May-September. Most of the seasonal snow in South America occurs in the Patagonia region of Argentina. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 sq km. The seasonal (May-September) 2 average snow cover extent was greatest in 1984 (464,250 sq km) and least in 1990 (69,875 sq km). In terms of snow mass, 1984 was also the biggest year (1.19 x 10(exp 13) kg) and 1990 was the smallest year (0.12 X 10(exp 13) kg). A strong relationship exists between the snow cover area and snow mass, correlated at 0.95, though no significant trend was found over the 28 year record for either snow cover extent or snow mass. For this long term climatology, snow mass and snow cover extent are shown to vary considerably from month to month and season to season. This analysis presents a consistent approach to mapping and measuring snow in South America utilizing an appropriate and readily available long term snow satellite dataset. This is the optimal dataset available, thus far, for deriving seasonal snow cover and snow mass in this region. Nonetheless, shallow snow, wet snow, snow beneath forests, as well as snow along coastal areas all may confound interpretation using passive microwave approaches. More work needs to be done to reduce the uncertainties in the data and hence, increase the confidence of the interpretation

Analysis of ground-measured and passive-microwave-derived snow depth variations in midwinter across the Northern Great Plains

USGS Publications Warehouse

Chang, A.T.C.; Kelly, R.E.J.; Josberger, E.G.; Armstrong, R.L.; Foster, J.L.; Mognard, N.M.

2005-01-01

Accurate estimation of snow mass is important for the characterization of the hydrological cycle at different space and time scales. For effective water resources management, accurate estimation of snow storage is needed. Conventionally, snow depth is measured at a point, and in order to monitor snow depth in a temporally and spatially comprehensive manner, optimum interpolation of the points is undertaken. Yet the spatial representation of point measurements at a basin or on a larger distance scale is uncertain. Spaceborne scanning sensors, which cover a wide swath and can provide rapid repeat global coverage, are ideally suited to augment the global snow information. Satellite-borne passive microwave sensors have been used to derive snow depth (SD) with some success. The uncertainties in point SD and areal SD of natural snowpacks need to be understood if comparisons are to be made between a point SD measurement and satellite SD. In this paper three issues are addressed relating satellite derivation of SD and ground measurements of SD in the northern Great Plains of the United States from 1988 to 1997. First, it is shown that in comparing samples of ground-measured point SD data with satellite-derived 25 ?? 25 km2 pixels of SD from the Defense Meteorological Satellite Program Special Sensor Microwave Imager, there are significant differences in yearly SD values even though the accumulated datasets showed similarities. Second, from variogram analysis, the spatial variability of SD from each dataset was comparable. Third, for a sampling grid cell domain of 1?? ?? 1?? in the study terrain, 10 distributed snow depth measurements per cell are required to produce a sampling error of 5 cm or better. This study has important implications for validating SD derivations from satellite microwave observations. ?? 2005 American Meteorological Society.

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part II: Evaluation of Estimates Using Independent Data

NASA Technical Reports Server (NTRS)

Yang, Song; Olson, William S.; Wang, Jian-Jian; Bell, Thomas L.; Smith, Eric A.; Kummerow, Christian D.

2006-01-01

Rainfall rate estimates from spaceborne microwave radiometers are generally accepted as reliable by a majority of the atmospheric science community. One of the Tropical Rainfall Measuring Mission (TRMM) facility rain-rate algorithms is based upon passive microwave observations from the TRMM Microwave Imager (TMI). In Part I of this series, improvements of the TMI algorithm that are required to introduce latent heating as an additional algorithm product are described. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, 0.5 deg. -resolution estimates of surface rain rate over ocean from the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over earlier algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly 2.5 -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data is limited, TMI-estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain-rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with (a) additional contextual information brought to the estimation problem and/or (b) physically consistent and representative databases supporting the algorithm. A model of the random error in instantaneous 0.5 deg. -resolution rain-rate estimates appears to be consistent with the levels of error determined from TMI comparisons with collocated

Protection of passive radio frequencies used for earth exploration by satellite

NASA Astrophysics Data System (ADS)

Rochard, Guy

2004-10-01

Space-borne passive sensing of the Earth"s surface and atmosphere has an essential and increasing importance in Earth Observation. The impressive progress recently made or shortly expected in weather analysis, warning and forecasts (in particular for dangerous weather phenomena as rain and floods, storms, cyclones, droughts) as well as in the study and prediction of climate change, is mainly attributable to the spaceborne observations. On this basis, economic studies show that meteorological services have a high positive impact on a wide range of economic activities, notwithstanding safety of life and property aspects. Space-borne passive sensing feeds crucial observational data to numerical weather predction models run on the most advanced super-computers that are operated by a few global forecasting centers. All meteorological and environmental satellite organizations operate these crucial remote-sensing missions as part of the GOS of the World Weather Watch and others... Spaceborne passive sensing for meterological applications is performed in frequency bands allocated to the Earth Exploration-Satellite Service. This is named "EESS passive" in the ITU-R Radio Regulations. The appropriate bands are uniquely determined by the physical properties (e.g. molecular resonance) of constituents of the atmosphere, and are therefore one of the unique natural resources (similarly to Radio Astronomy bands). Passive measurements at several frequencies in the microwave spectrum must be made simultaneously in order to extract the individual contribution of the geophysical parameter of interest. Bands below 100 GHz are of particular importance to provide an "all-weather" capability since many clouds are almost transparent at these frequencies. Along this line, the two first figures below about zenithal opacity describes respectively the atmosphere optical thickness due to water vapor and dry components in the frequency range 1 to 275 GHz and 275 GHz to 1000 GHz on which have

Microwave remote sensing: Active and passive. Volume 1 - Microwave remote sensing fundamentals and radiometry

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Moore, R. K.; Fung, A. K.

1981-01-01

The three components of microwave remote sensing (sensor-scene interaction, sensor design, and measurement techniques), and the applications to geoscience are examined. The history of active and passive microwave sensing is reviewed, along with fundamental principles of electromagnetic wave propagation, antennas, and microwave interaction with atmospheric constituents. Radiometric concepts are reviewed, particularly for measurement problems for atmospheric and terrestrial sources of natural radiation. Particular attention is given to the emission by atmospheric gases, clouds, and rain as described by the radiative transfer function. Finally, the operation and performance characteristics of radiometer receivers are discussed, particularly for measurement precision, calibration techniques, and imaging considerations.

AMISS - Active and passive MIcrowaves for Security and Subsurface imaging

NASA Astrophysics Data System (ADS)

Soldovieri, Francesco; Slob, Evert; Turk, Ahmet Serdar; Crocco, Lorenzo; Catapano, Ilaria; Di Matteo, Francesca

2013-04-01

The FP7-IRSES project AMISS - Active and passive MIcrowaves for Security and Subsurface imaging is based on a well-combined network among research institutions of EU, Associate and Third Countries (National Research Council of Italy - Italy, Technische Universiteit Delft - The Netherlands, Yildiz Technical University - Turkey, Bauman Moscow State Technical University - Russia, Usikov Institute for Radio-physics and Electronics and State Research Centre of Superconductive Radioelectronics "Iceberg" - Ukraine and University of Sao Paulo - Brazil) with the aims of achieving scientific advances in the framework of microwave and millimeter imaging systems and techniques for security and safety social issues. In particular, the involved partners are leaders in the scientific areas of passive and active imaging and are sharing their complementary knowledge to address two main research lines. The first one regards the design, characterization and performance evaluation of new passive and active microwave devices, sensors and measurement set-ups able to mitigate clutter and increase information content. The second line faces the requirements to make State-of-the-Art processing tools compliant with the instrumentations developed in the first line, suitable to work in electromagnetically complex scenarios and able to exploit the unexplored possibilities offered by new instrumentations. The main goals of the project are: 1) Development/improvement and characterization of new sensors and systems for active and passive microwave imaging; 2) Set up, analysis and validation of state of art/novel data processing approach for GPR in critical infrastructure and subsurface imaging; 3) Integration of state of art and novel imaging hardware and characterization approaches to tackle realistic situations in security, safety and subsurface prospecting applications; 4) Development and feasibility study of bio-radar technology (system and data processing) for vital signs detection and

Passive Microwave Precipitation Retrieval Uncertainty Characterized based on Field Campaign Data over Complex Terrain

NASA Astrophysics Data System (ADS)

Derin, Y.; Anagnostou, E. N.; Anagnostou, M.; Kalogiros, J. A.; Casella, D.; Marra, A. C.; Panegrossi, G.; Sanò, P.

2017-12-01

Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements. Such measurements can be obtained from field campaigns facilitated by research quality sensors such as locally deployed weather radar and in situ weather stations. This study uses such high quality and resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations from three field experiments in Mid-Atlantic US East Coast (NASA IPHEX experiment), the Olympic Peninsula of Washington State (NASA OLYMPEX experiment), and the Mediterranean to characterize the error characteristics of multiple passive microwave (PMW) sensor retrievals. The study first conducts an independent error analysis of the XPOL radar reference rainfall fields against in situ rain gauges and disdrometer observations available by the field experiments. Then the study evaluates different PMW precipitation products using the XPOL datasets (GR) over the three aforementioned complex terrain study areas. We extracted matchups of PMW/GR rainfall based on a matching methodology that identifies GR volume scans coincident with PMW field-of-view sampling volumes, and scaled GR parameters to the satellite products' nominal spatial resolution. The following PMW precipitation retrieval algorithms are evaluated: the NASA Goddard PROFiling algorithm (GPROF), standard and climatology-based products (V 3, 4 and 5) from four PMW sensors (SSMIS, MHS, GMI, and AMSR2), and the precipitation products based on the algorithms Cloud Dynamics and Radiation Database (CDRD) for SSMIS and Passive microwave Neural network

Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

NASA Technical Reports Server (NTRS)

Olson, William S.; Grecu, Mircea; Yang, Song; Tao, Wei-Kuo

2004-01-01

In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression

Correlation studies of passive and active microwave data in the marginal ice zone

NASA Technical Reports Server (NTRS)

Comiso, J. C.

1991-01-01

The microwave radiative and backscatter characteristics of sea ice in an Arctic marginal ice zone have been studied using near-simultaneous passive and active synthetic aperture radar microwave data. Intermediate-resolution multichannel passive microwave data were registered and analyzed. Passive and active microwave data generally complement each other as the two sensors are especially sensitive to different physical properties of the sea ice. In the inner pack, undeformed first-year ice is observed to have low backscatter values but high brightness temperatures while multiyear ice has generally high backscatter values and low brightness temperatures. However, in the marginal ice zone, the signature and backscatter for multiyear ice are considerably different and closer to those of first-year ice. Some floes identified by photography as snow-covered thick ice have backscatter similar to that of new ice or open water while brash ice has backscatter similar to or higher than that of ridged ice.

Satellite microwave observations of soil moisture variations. [by the microwave radiometer on the Nimbus 5 satellite

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Rango, A.; Neff, R.

1975-01-01

The electrically scanning microwave radiometer (ESMR) on the Nimbus 5 satellite was used to observe microwave emissions from vegetated and soil surfaces over an Illinois-Indiana study area, the Mississippi Valley, and the Great Salt Lake Desert in Utah. Analysis of microwave brightness temperatures (T sub B) and antecedent rainfall over these areas provided a way to monitor variations of near-surface soil moisture. Because vegetation absorbs microwave emission from the soil at the 1.55 cm wavelength of ESMR, relative soil moisture measurements can only be obtained over bare or sparsely vegetated soil. In general T sub B increased during rainfree periods as evaporation of water and drying of the surface soil occurs, and drops in T sub B are experienced after significant rainfall events wet the soil. Microwave observations from space are limited to coarse resolutions (10-25 km), but it may be possible in regions with sparse vegetation cover to estimate soil moisture conditions on a watershed or agricultural district basis, particularly since daily observations can be obtained.

Combining Satellite Microwave Radiometer and Radar Observations to Estimate Atmospheric Latent Heating Profiles

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Olson, William S.; Shie, Chung-Lin; L'Ecuyer, Tristan S.; Tao, Wei-Kuo

2009-01-01

In this study, satellite passive microwave sensor observations from the TRMM Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q1-QR) in regions of precipitation. The TMI heating algorithm (TRAIN) is calibrated, or "trained" using relatively accurate estimates of heating based upon spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based upon a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically-integrated condensation and surface precipitation. Estimates of Q1-QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q1 produced by combining TMI Q1-QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q1 from two field campaigns, although the satellite estimates exhibit heating profile structure with sharper and more intense heating peaks than the rawinsonde estimates. 2

Validating Microwave-Based Satellite Rain Rate Retrievals Over TRMM Ground Validation Sites

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Wolff, D. B.

2008-12-01

Multi-channel, passive microwave instruments are commonly used today to probe the structure of rain systems and to estimate surface rainfall from space. Until the advent of meteorological satellites and the development of remote sensing techniques for measuring precipitation from space, there was no observational system capable of providing accurate estimates of surface precipitation on global scales. Since the early 1970s, microwave measurements from satellites have provided quantitative estimates of surface rainfall by observing the emission and scattering processes due to the existence of clouds and precipitation in the atmosphere. This study assesses the relative performance of microwave precipitation estimates from seven polar-orbiting satellites and the TRMM TMI using four years (2003-2006) of instantaneous radar rain estimates obtained from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The seven polar orbiters include three different sensor types: SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), and AMSR-E. The TMI aboard the TRMM satellite flies in a sun asynchronous orbit between 35 S and 35 N latitudes. The rain information from these satellites are combined and used to generate several multi-satellite rain products, namely the Goddard TRMM Multi-satellite Precipitation Analysis (TMPA), NOAA's CPC Morphing Technique (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Instantaneous rain rates derived from each sensor were matched to the GV estimates in time and space at a resolution of 0.25 degrees. The study evaluates the measurement and error characteristics of the various satellite estimates through inter-comparisons with GV radar estimates. The GV rain observations provided an empirical ground-based reference for assessing the relative performance of each sensor and sensor

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1995-01-01

During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

Analysis of passive microwave signatures over snow-covered mountainous area

NASA Astrophysics Data System (ADS)

Kim, R. S.; Durand, M. T.

2015-12-01

Accurate knowledge of snow distribution over mountainous area is critical for climate studies and the passive microwave(PM) measurements have been widely used and invested in order to obtain information about snowpack properties. Understanding and analyzing the signatures for the explicit inversion of the remote sensing data from land surfaces is required for successful using of passive microwave sensors but this task is often ambiguous due to the large variability of physical conditions and object types. In this paper, we discuss the pattern of measured brightness temperatures and emissivities at vertical and horizontal polarization over the frequency range of 10.7 to 89 GHz of land surfaces under various snow and vegetation conditions. The Multiband polarimetric Scanning Radiometer(PSR) imagery is used over NASA Cold Land Processes Field Experiment(CLPX) study area with ground-based measurements of snow depth and snow properties. Classification of snow under various conditions in mountainous area is implemented based on different patterns of microwave signatures.

Bias adjustment of infrared-based rainfall estimation using Passive Microwave satellite rainfall data

NASA Astrophysics Data System (ADS)

Karbalaee, Negar; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2017-04-01

This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the Integrated Multisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained.

Timing and regional patterns of snowmelt on Antarctic sea ice from passive microwave satellite observations

NASA Astrophysics Data System (ADS)

Arndt, Stefanie; Willmes, Sascha; Dierking, Wolfgang; Nicolaus, Marcel

2016-04-01

The better understanding of temporal variability and regional distribution of surface melt on Antarctic sea ice is crucial for the understanding of atmosphere-ocean interactions and the determination of mass and energy budgets of sea ice. Since large regions of Antarctic sea ice are covered with snow during most of the year, observed inter-annual and regional variations of surface melt mainly represents melt processes in the snow. It is therefore important to understand the mechanisms that drive snowmelt, both at different times of the year and in different regions around Antarctica. In this study we combine two approaches for observing both surface and volume snowmelt by means of passive microwave satellite data. The former is achieved by measuring diurnal differences of the brightness temperature TB at 37 GHz, the latter by analyzing the ratio TB(19GHz)/TB(37GHz). Moreover, we use both melt onset proxies to divide the Antarctic sea ice cover into characteristic surface melt patterns from 1988/89 to 2014/15. Our results indicate four characteristic melt types. On average, 43% of the ice-covered ocean shows diurnal freeze-thaw cycles in the surface snow layer, resulting in temporary melt (Type A), less than 1% shows continuous snowmelt throughout the snowpack, resulting in strong melt over a period of several days (Type B), 19% shows Type A and B taking place consecutively (Type C), and for 37% no melt is observed at all (Type D). Continuous melt is primarily observed in the outflow of the Weddell Gyre and in the northern Ross Sea, usually 20 days after the onset of temporary melt. Considering the entire data set, snowmelt processes and onset do not show significant temporal trends. Instead, areas of increasing (decreasing) sea-ice extent have longer (shorter) periods of continuous snowmelt.

Radiation measurements from polar and geosynchronous satellites

NASA Technical Reports Server (NTRS)

Vonderhaar, T. H.; Kidder, S. Q.; Hillger, D. W.; Ellis, J. S.

1978-01-01

The following topics are discussed: (1) cloud effects in climate determination; (2) annual variation in the global heat balance of the earth; (3) the accuracy of precipitation estimates made from passive microwave measurements from satellites; (4) seasonal oceanic precipitation frequencies; (5) determination of mesoscale temperature and moisture fields over land from satellite radiance measurements; and (6) Nimbus 6 scanning microwave spectrometer data evaluation for surface wind and pressure components in tropical storms.

Global mapping of sea-ice production from the satellite microwaves

NASA Astrophysics Data System (ADS)

Ohshima, K. I.; Nihashi, S.; Iwamoto, K.; Tamaru, N.; Nakata, K.; Tamura, T.

2016-12-01

Global overturning circulation is driven by density differences. Saline water rejected by sea-ice production in coastal polynyas is the main source of dense water, and thus sea-ice production is a key factor in the overturning circulation. However, until recently sea-ice production and its interannual variability have not been well understood due to difficulties of in situ observation. The most effective means of detection of thin-ice area and estimation of sea-ice production on large scales is satellite remote sensing using passive microwave sensors, specifically the Special Sensor Microwave/Imager and Advanced Microwave Scanning Radiometer. This is based upon their ability to gain complete polar coverage on a daily basis irrespective of clouds and darkness. We have estimated sea-ice production globally based on heat flux calculations using the satellite-derived thin ice thickness data. The mapping demonstrates that ice production rate is high in Antarctic coastal polynyas, in contrast to Arctic coastal polynyas. This is consistent with the formation of Antarctic Bottom Water (AABW). The Ross Ice Shelf polynya has by far the highest ice production in the Southern Hemisphere. The mapping has revealed that the Cape Darnley polynya is the second highest production area, leading to the discovery of the missing (fourth) source of AABW in this region. In the region off the Mertz Glacier Tongue, sea-ice production decreased by as much as 40 %, due to the glacier calving in early 2010, resulting in a significant decrease in AABW production. The Okhotsk Northwestern polynya exhibits the highest ice production in the Northern Hemisphere, and the resultant dense water formation leads to overturning in the North Pacific. Estimates of its ice production show a significant decrease over the past 30-50 years, likely causing the weakening of the North Pacific overturning. The mapping also provides surface boundary conditions and validation data of heat- and salt-flux associated

Advances in satellite oceanography

NASA Technical Reports Server (NTRS)

Brown, O. B.; Cheney, R. E.

1983-01-01

Technical advances and recent applications of active and passive satellite remote sensing techniques to the study of oceanic processes are summarized. The general themes include infrared and visible radiometry, active and passive microwave sensors, and buoy location systems. The surface parameters of sea surface temperature, windstream, sea state, altimetry, color, and ice are treated as applicable under each of the general methods.

A microwave satellite water vapour column retrieval for polar winter conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perro, Christopher; Lesins, Glen; Duck, Thomas J.

A new microwave satellite water vapour retrieval for the polar winter atmosphere is presented. The retrieval builds on the work of Miao et al. (2001) and Melsheimer and Heygster (2008), employing auxiliary information for atmospheric conditions and numerical optimization. It was tested using simulated and actual measurements from the Microwave Humidity Sounder (MHS) satellite instruments. Ground truth was provided by the G-band vapour radiometer (GVR) at Barrow, Alaska. For water vapour columns less than 6 kg m -2, comparisons between the retrieval and GVR result in a root mean square (RMS) deviation of 0.39 kg m -2 and a systematic bias of 0.08 kg m -2. These results aremore » compared with RMS deviations and biases at Barrow for the retrieval of Melsheimer and Heygster (2008), the AIRS and MIRS satellite data products, and the ERA-Interim, NCEP, JRA-55, and ASR reanalyses. When applied to MHS measurements, the new retrieval produces a smaller RMS deviation and bias than for the earlier retrieval and satellite data products. The RMS deviations for the new retrieval were comparable to those for the ERA-Interim, JRA-55, and ASR reanalyses; however, the MHS retrievals have much finer horizontal resolution (15 km at nadir) and reveal more structure. The new retrieval can be used to obtain pan-Arctic maps of water vapour columns of unprecedented quality. It may also be applied to measurements from the Special Sensor Microwave/Temperature 2 (SSM/T2), Advanced Microwave Sounding Unit B (AMSU-B), Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Technology Microwave Sounder (ATMS), and Chinese MicroWave Humidity Sounder (MWHS) instruments.« less

Studies of the Antarctic Sea Ice Edges and Ice Extents from Satellite and Ship Observations

NASA Technical Reports Server (NTRS)

Worby, Anthony P.; Comiso, Josefino C.

2003-01-01

Passive-microwave derived ice edge locations in Antarctica are assessed against other satellite data as well as in situ observations of ice edge location made between 1989 and 2000. The passive microwave data generally agree with satellite and ship data but the ice concentration at the observed ice edge varies greatly with averages of 14% for the TEAM algorithm and 19% for the Bootstrap algorithm. The comparisons of passive microwave with the field data show that in the ice growth season (March - October) the agreement is extremely good, with r(sup 2) values of 0.9967 and 0.9797 for the Bootstrap and TEAM algorithms respectively. In the melt season however (November - February) the passive microwave ice edge is typically 1-2 degrees south of the observations due to the low concentration and saturated nature of the ice. Sensitivity studies show that these results can have significant impact on trend and mass balance studies of the sea ice cover in the Southern Ocean.

The effects of snowpack grain size on satellite passive microwave observations from the Upper Colorado River Basin

USGS Publications Warehouse

Josberger, E.G.; Gloersen, P.; Chang, A.; Rango, A.

1996-01-01

Understanding the passive microwave emissions of a snowpack, as observed by satellite sensors, requires knowledge of the snowpack properties: water equivalent, grain size, density, and stratigraphy. For the snowpack in the Upper Colorado River Basin, measurements of snow depth and water equivalent are routinely available from the U.S. Department of Agriculture, but extremely limited information is available for the other properties. To provide this information, a field program from 1984 to 1995 obtained profiles of snowpack grain size, density, and temperature near the time of maximum snow accumulation, at sites distributed across the basin. A synoptic basin-wide sampling program in 1985 showed that the snowpack exhibits consistent properties across large regions. Typically, the snowpack in the Wyoming region contains large amounts of depth hoar, with grain sizes up to 5 mm, while the snowpack in Colorado and Utah is dominated by rounded snow grains less than 2 mm in diameter. In the Wyoming region, large depth hoar crystals in shallow snowpacks yield the lowest emissivities or coldest brightness temperatures observed across the entire basin. Yearly differences in the average grain sizes result primarily from variations in the relative amount of depth hoar within the snowpack. The average grain size for the Colorado and Utah regions shows much less variation than do the grain sizes from the Wyoming region. Furthermore, the greatest amounts of depth hoar occur in the Wyoming region during 1987 and 1992, years with strong El Nin??o Southern Oscillation, but the Colorado and Utah regions do not show this behavior.

Signals of Opportunity Earth Reflectometry (SoOp-ER): Enabling new microwave observations from small satellites

NASA Astrophysics Data System (ADS)

Garrison, J. L.; Piepmeier, J. R.; Shah, R.; Lin, Y. C.; Du Toit, C. F.; Vega, M. A.; Knuble, J. J.

2016-12-01

Several recent experiments have demonstrated remote sensing by reutilizing communication satellite transmissions as sources in a bistatic radar configuration. This technique, referred to as "Signals of Opportunity Earth Reflectometry" (SoOp-ER), combines aspects of passive radiometry, active scatterometry and radar altimetry, but is essentially a new and alternative approach to microwave remote sensing. Reflectometry was first demonstrated with Global Navigation Satellite System (GNSS) signals, enabled by their use of pseudorandom noise (PRN) codes for ranging. Two decades of research in GNSS reflectometry has culminated in the upcoming launches of several satellite missions within the next few years (TechDemoSat-1, CYGNSS, and GEROS-ISS). GNSS signals, however, have low power and are confined to a few L-band frequencies allocated to radionavigation. Communication satellites, in contrast, transmit in nearly all bands penetrating the Earth's atmosphere at very high radiated powers to assure a low bit-error-rate. High transmission power and a forward scatter geometry result in a very high signal to noise ratio at the receiver. Surface resolution is determined by the signal bandwidth, not the antenna beam. In many applications, this will allow small, low gain antennas to be used to make scientifically useful measurements. These features indicate that SoOp-ER instruments would be an ideal technology for microwave remote sensing from small platforms. SoOp-ER observations are referenced at the specular point and a constellation of small satellites, evenly spaced in the same orbit, would provide global coverage through parallel specular point ground tracks. This presentation will summarize the current instrument development work by the authors on three different application of SoOp-ER: P-band (230-270 MHz) sensing of root-zone soil moisture (RZSM), S-band sensing of ocean winds and Ku/Ka-band altimetry. Potential mission scenarios using small satellite constellations

Advanced Passive Microwave Radiometer Technology for GPM Mission

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Im, Eastwood; Kummerow, Christian; Principe, Caleb; Ruf, Christoper; Wilheit, Thomas; Starr, David (Technical Monitor)

2002-01-01

An interferometer-type passive microwave radiometer based on MMIC receiver technology and a thinned array antenna design is being developed under the Instrument Incubator Program (TIP) on a project entitled the Lightweight Rainfall Radiometer (LRR). The prototype single channel aircraft instrument will be ready for first testing in 2nd quarter 2003, for deployment on the NASA DC-8 aircraft and in a ground configuration manner; this version measures at 10.7 GHz in a crosstrack imaging mode. The design for a two (2) frequency preliminary space flight model at 19 and 35 GHz (also in crosstrack imaging mode) has also been completed, in which the design features would enable it to fly in a bore-sighted configuration with a new dual-frequency space radar (DPR) under development at the Communications Research Laboratory (CRL) in Tokyo, Japan. The DPR will be flown as one of two primary instruments on the Global Precipitation Measurement (GPM) mission's core satellite in the 2007 time frame. The dual frequency space flight design of the ERR matches the APR frequencies and will be proposed as an ancillary instrument on the GPM core satellite to advance space-based precipitation measurement by enabling better microphysical characterization and coincident volume data gathering for exercising combined algorithm techniques which make use of both radar backscatter and radiometer attenuation information to constrain rainrate solutions within a physical algorithm context. This talk will discuss the design features, performance capabilities, applications plans, and conical/polarametric imaging possibilities for the LRR, as well as a brief summary of the project status and schedule.

The COWVR Mission: Demonstrating Small Satellite Capability to Fill the Looming Gap in Microwave Radiometer Coverage

NASA Astrophysics Data System (ADS)

Brown, S. T.; Focardi, P.; Kitiyakara, A.; Maiwald, F.; Milligan, L.; Montes, O.; Padmanabhan, S.; Redick, R.; Russell, D.

2017-12-01

Passive microwave radiometer systems have been providing important Earth observations for over 30 years, including by not limited to surface wind vector, atmospheric and surface temperature, water vapor, clouds, precipitation, snow and sea ice. These data are critical for weather forecasting and the longevity of the record, along with careful calibration, has also enabled the extraction of climate records. But the future of these systems, conically scanning systems in particular, is uncertain. These sensors are have typically been developed at high cost and deployed on large spacecraft. A solution may lie in smaller, lower-cost but equally capable sensors manifested on free-flying small-satellites which can open the door to new possibilities and an avenue for sustainable passive microwave observation. Among the possibilities are deployment in constellations to shorten revisit time to improve weather forecasting or routine deployment of single sensors over time to ensure an unbroken long duration climate record. The Compact Ocean Wind Vector Radiometer (COWVR) mission, formally the US Air Force ORS-6 mission, will demonstrate a new generation conically scanning passive microwave radiometer on a small satellite. COWVR is an 18-34 GHz fully polarimetric radiometer with a 75cm aperture designed to provide measurements of ocean vector winds with an accuracy that meets or exceeds that provided by WindSat in all non-precipitating conditions, but using a simpler design which has both performance and cost advantages. This paper will give an overview of the COWVR instrument and mission and its performance estimated from pre-launch calibration data. While the COWVR mission is a focused technology demonstration mission, the sensor design is scalable to a much broader frequency range while retaining its low-cost advantage. We will describe extensions of the COWVR design that have been developed and the capabilities of such systems when deployed in a constellation scenario or

Passive microwave studies of frozen lakes

NASA Technical Reports Server (NTRS)

Hall, D. K.; Foster, J. L.; Rango, A.; Chang, A. T. C.

1978-01-01

Lakes of various sizes, depths and ice thicknesses in Alaska, Utah and Colorado were overflown with passive microwave sensors providing observations at several wavelengths. A layer model is used to calculate the microwave brightness temperature, T sub B (a function of the emissivity and physical temperatures of the object), of snowcovered ice underlain with water. Calculated T sub B's are comparable to measured T sub B's. At short wavelengths, e.g., 0.8 cm, T sub B data provide information on the near surface properties of ice covered lakes where the long wavelength, 21.0 cm, observations sense the entire thickness of ice including underlying water. Additionally, T sub B is found to increase with ice thickness. 1.55 cm observations on Chandalar Lake in Alaska show a T sub B increase of 38 K with an approximate 124 cm increase in ice thickness.

Satellite Observation Systems for Polar Climate Change Studies

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.

2012-01-01

The key observational tools for detecting large scale changes of various parameters in the polar regions have been satellite sensors. The sensors include passive and active satellite systems in the visible, infrared and microwave frequencies. The monitoring started with Tiros and Nimbus research satellites series in the 1970s but during the period, not much data was stored digitally because of limitations and cost of the needed storage systems. Continuous global data came about starting with the launch of ocean color, passive microwave, and thermal infrared sensors on board Nimbus-7 and Synthetic Aperture Radar, Radar Altimeter and Scatterometer on board SeaSat satellite both launched in 1978. The Nimbus-7 lasted longer than expected and provided about 9 years of useful data while SeaSat quit working after 3 months but provided very useful data that became the baseline for follow-up systems with similar capabilities. Over the years, many new sensors were launched, some from Japan Aeronautics and Space Agency (JAXA), some from the European Space Agency (ESA) and more recently, from RuSSia, China, Korea, Canada and India. For polar studies, among the most useful sensors has been the passive microwave sensor which provides day/night and almost all weather observation of the surface. The sensor provide sea surface temperature, precipitation, wind, water vapor and sea ice concentration data that have been very useful in monitoring the climate of the region. More than 30 years of such data are now available, starting with the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7, the Special Scanning Microwave/Imager (SSM/I) on board a Defense Meteorological Satellite Program (DMSP) and the Advanced Microwave Scanning Radiometer on board the EOS/ Aqua satellite. The techniques that have been developed to derive geophysical parameters from data provided by these and other sensors and associated instrumental and algorithm errors and validation techniques

Investigating the value of passive microwave observations for monitoring volcanic eruption source parameters

NASA Astrophysics Data System (ADS)

Montopoli, Mario; Cimini, Domenico; Marzano, Frank

2016-04-01

the dispersal fine-ash cloud, but tend to saturate near the source due to the strong optical extinction of ash cloud top layers. Conversely, observations at microwave (MW) channels from LEO satellites have demonstrated to carry additional information near the volcano source due to the relative lower opacity. This feature makes satellite MW complementary to IR radiometry for estimating source parameters close to the volcano emission, at the cost of coarser spatial resolution. The presentation shows the value of passive MW observations for the detection and quantitative retrieval of volcanic emission source parameters through the investigation of notable case studies, such as the eruptions of Grímsvötn (Iceland, May 2011) and Calbuco (Cile, April 2015), observed by the Special Sensor Microwave Imager/Sounder and the Advanced Technology Microwave Sounder.

Passive microwave observations of the Wedell Sea during austral winter and early spring

NASA Technical Reports Server (NTRS)

Grenfell, T. C.; Comiso, J. C.; Lange, M. A.; Eicken, H.; Wensnahan, M. R.

1994-01-01

The results of multispectral passive microwave observations (6.7 to 90-GHz) are presented from the cruises of the FS Polarstern in the Weddell Sea from July to December 1986. This paper includes primarily the analysis of radiometric observations taken at ice station sites. Averaged emissivity spectra for first-year (FY) ice were relatively constant throughout the experiment and were not statistically different from FY ice signatures in the Arctic. Detailed ice characterization was carried out at each site to compare the microwave signatures of the ice with the physical properties. Absorption optical depths of FY ice were found to be sufficiently high that only the structure in the upper portions of the ice contributed significantly to interstation emissivity variations. The emissivities at 90-GHz, e(90), had the greatest variance. Both e(90) at vertical polarization and GR(sub e)(90, 18.7)(defined as (e(sub V)(90)-e(sub V)(18.7))/e(sub V)(90 + e(sub V)(18.7)) depended on the scattering optical depth which is a function of the snow grain diameter and layer thickness. The variance showed a latitude dependence and is probably due to an increase in the strength of snow metamorphism nearer the northern edge of the ice pack. The contribution of variations of near-surface brine volume to the emissivity was not significant over the range of values encountered at the station sites. Emissivity spectra are presented for a range of thin ice types. Unsupervised principal component analysis produced three significant eigenvectors and showed a separation among four different surface types: open water, thin ice, FY ice, and FY ice with a thick snow cover. A comparison with SMMR satellite data showed that average ice concentrations derived from the ship's ice watch log were consistent with the satellite concentrations. The surface based emissivities for FY ice were also compared with emissivities calculated from scanning multichannel microwave radiometer (SMMR) satellite radiances

Comparing upper tropospheric humidity data from microwave satellite instruments and tropical radiosondes

NASA Astrophysics Data System (ADS)

Moradi, Isaac; Buehler, Stefan A.; John, Viju O.; Eliasson, Salomon

2010-12-01

Atmospheric humidity plays an important role in the Earth's climate. Microwave satellite data provide valuable humidity observations in the upper troposphere with global coverage. In this study, we compare upper tropospheric humidity (UTH) retrieved from the Advanced Microwave Sounding Unit and the Microwave Humidity Sounder against radiosonde data measured at four of the central facilities of the Atmospheric Radiation Measurement program. The Atmospheric Radiative Transfer Simulator (ARTS) was used to simulate satellite brightness temperatures from the radiosonde profiles. Strong ice clouds were filtered out, as their influence on microwave measurements leads to incorrect UTH values. Day and night radiosonde profiles were analyzed separately to take into account the radiosonde radiation bias. The comparison between radiosonde and satellite is most meaningful for data in cloud-free, nighttime conditions and with a time difference of less than 2 hr. We found good agreement between the two data sets. The satellite data were slightly moister than the radiosonde data, with a mean difference of 1%-2.3% relative humidity (RH), depending on the radiosonde site. Monthly gridded data were also compared and showed a slightly larger mean difference of up to 3.3% RH, which can be explained by sampling issues.

Microwave Brightness Temperatures of Tilted Convective Systems

NASA Technical Reports Server (NTRS)

Hong, Ye; Haferman, Jeffrey L.; Olson, William S.; Kummerow, Christian D.

1998-01-01

Aircraft and ground-based radar data from the Tropical Ocean and Global Atmosphere Coupled-Ocean Atmosphere Response Experiment (TOGA COARE) show that convective systems are not always vertical. Instead, many are tilted from vertical. Satellite passive microwave radiometers observe the atmosphere at a viewing angle. For example, the Special Sensor Microwave/Imager (SSM/I) on Defense Meteorological Satellite Program (DMSP) satellites and the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) on the TRMM satellite have an incident angle of about 50deg. Thus, the brightness temperature measured from one direction of tilt may be different than that viewed from the opposite direction due to the different optical depth. This paper presents the investigation of passive microwave brightness temperatures of tilted convective systems. To account for the effect of tilt, a 3-D backward Monte Carlo radiative transfer model has been applied to a simple tilted cloud model and a dynamically evolving cloud model to derive the brightness temperature. The radiative transfer results indicate that brightness temperature varies when the viewing angle changes because of the different optical depth. The tilt increases the displacements between high 19 GHz brightness temperature (Tb(sub 19)) due to liquid emission from lower level of cloud and the low 85 GHz brightness temperature (Tb(sub 85)) due to ice scattering from upper level of cloud. As the resolution degrades, the difference of brightness temperature due to the change of viewing angle decreases dramatically. The dislocation between Tb(sub 19) and Tb(sub 85), however, remains prominent.

Snowpack monitoring in North America and Eurasia using passive microwave satellite data

NASA Technical Reports Server (NTRS)

Foster, J. L.; Rango, A.; Hall, D. K.; Chang, A. T. C.; Allison, L. J.; Diesen, B. C., III

1980-01-01

Areas of the Canadian high plains, the Montana and North Dakota high plains, and the steppes of central Russia have been studied in an effort to determine the utility of spaceborne microwave radiometers for monitoring snow depths in different geographic areas. Significant regression relationships between snow depth and microwave brightness temperatures were developed for each of these homogeneous areas. In each of the study areas investigated in this paper, Nimbus-6 (0.81 cm) ESMR data produced higher correlations than Nimbus-5 (1.55 cm) ESMR data in relating microwave brightness temperature to snow depth. It is difficult to extrapolate relationships between microwave brightness temperature and snow depth from one area to another because different geographic areas are likely to have different snowpack conditions.

Applications of Nano-Satellites and Cube-Satellites in Microwave and RF Domain

NASA Technical Reports Server (NTRS)

Simons, Rainee N.; Goverdhanam, Kavita

2015-01-01

This paper presents an overview of microwave technologies for Small Satellites including NanoSats and CubeSats. In addition, examples of space communication technology demonstration projects using CubeSats are presented. Furthermore, examples of miniature instruments for Earth science measurements are discussed.

Applications of Nano-satellites and Cube-satellites in Microwave and RF Domain

NASA Technical Reports Server (NTRS)

Simons, Rainee N.; Goverdhanam, Kavita

2015-01-01

This paper presents an overview of microwave technologies for Small Satellites including NanoSats and CubeSats. In addition, examples of space communication technology demonstration projects using CubeSats are presented. Furthermore, examples of miniature instruments for Earth science measurements are discussed.

Estimating stratospheric temperature trends using satellite microwave radiances

NASA Technical Reports Server (NTRS)

Hudson, Robert D.; Newman, Paul A.; Schoeberl, Mark R.

1990-01-01

The objective was to evaluate and intercompare stratospheric temperatures using Microwave Sounding Unit (MSU) data as a basis data set. The MSU, aboard the NOAA polar orbiter satellite series, provides twice daily global coverage over a layer (50-150 mb) at approximately a (170km)(exp 2) resolution. Conventional data sets will be compared to the satellite data in the lower stratosphere in order to assess their quality for trend computations.

Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Vrije; VandeGriend, Adriaan A.

2000-01-01

Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm

The Satellite Passive-Microwave Record of Sea Ice in the Ross Sea Since Late 1978

NASA Technical Reports Server (NTRS)

Parkinson, Claire L.

2009-01-01

Satellites have provided us with a remarkable ability to monitor many aspects of the globe day-in and day-out and sea ice is one of numerous variables that by now have quite substantial satellite records. Passive-microwave data have been particularly valuable in sea ice monitoring, with a record that extends back to August 1987 on daily basis (for most of the period), to November 1970 on a less complete basis (again for most of the period), and to December 1972 on a less complete basis. For the period since November 1970, Ross Sea sea ice imagery is available at spatial resolution of approximately 25 km. This allows good depictions of the seasonal advance and retreat of the ice cover each year, along with its marked interannual variability. The Ross Sea ice extent typically reaches a minimum of approximately 0.7 x 10(exp 6) square kilometers in February, rising to a maximum of approximately 4.0 x 10(exp 6) square kilometers in September, with much variability among years for both those numbers. The Ross Sea images show clearly the day-by-day activity greatly from year to year. Animations of the data help to highlight the dynamic nature of the Ross Sea ice cover. The satellite data also allow calculation of trends in the ice cover over the period of the satellite record. Using linear least-squares fits, the Ross Sea ice extent increased at an average rate of 12,600 plus or minus 1,800 square kilometers per year between November 1978 and December 2007, with every month exhibiting increased ice extent and the rates of increase ranging from a low of 7,500 plus or minus 5,000 square kilometers per year for the February ice extents to a high of 20,300 plus or minus 6,100 kilometers per year for the October ice extents. On a yearly average basis, for 1979-2007 the Ross Sea ice extent increased at a rate of 4.8 plus or minus 1.6 % per decade. Placing the Ross Sea in the context of the Southern Ocean as a whole, over the November 1978-December 2007 period the Ross Sea had

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 2; Evaluation of Estimates Using Independent Data

NASA Technical Reports Server (NTRS)

Yang, Song; Olson, William S.; Wang, Jian-Jian; Bell, Thomas L.; Smith, Eric A.; Kummerow, Christian D.

2004-01-01

Rainfall rate estimates from space-borne k&ents are generally accepted as reliable by a majority of the atmospheric science commu&y. One-of the Tropical Rainfall Measuring Mission (TRh4M) facility rain rate algorithms is based upon passive microwave observations fiom the TRMM Microwave Imager (TMI). Part I of this study describes improvements in the TMI algorithm that are required to introduce cloud latent heating and drying as additional algorithm products. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, OP5resolution estimates of surface rain rate over ocean fiom the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over forerunning algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm, and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly, 2.5 deg. -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data are limited, TMI estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with: (a) additional contextual information brought to the estimation problem, and/or; (b) physically-consistent and representative databases supporting the algorithm. A model of the random error in instantaneous, 0.5 deg-resolution rain rate estimates appears to be consistent with the levels of error determined from TMI comparisons to collocated radar

Glacial Boundary Features Delineated Using Enhanced-resolution Passive-microwave Data to Determine Melt Season Variation of the Vatnajokull Ice Cap, Iceland

NASA Astrophysics Data System (ADS)

Marzillier, D. M.; Ramage, J. M.

2017-12-01

Temperate glaciers such as those seen in Iceland experience high annual mass flux, thereby responding to small scale changes in Earth's climate. Decadal changes in the glacial margins of Iceland's ice caps are observable in the Landsat record, however twice daily AMSR-E Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) allow for observation on a daily temporal scale and a 3.125 km spatial scale, which can in turn be connected to patterns seen over longer periods of time. Passive microwave data allow for careful observation of melt onset and duration in Iceland's glacial regions by recording changes in emissivity of the ice surface, known as brightness temperature (TB), which is sensitive to fluctuations in the liquid water content of snow and ice seen during melting in glaciated regions. Enhanced resolution of this data set allows for a determination of a threshold that defines the melting season. The XPGR snowmelt algorithm originally presented by Abdalati and Steffen (1995) is used as a comparison with the diurnal amplitude variation (DAV) values on Iceland's Vatnajokull ice cap located at 64.4N, -16.8W. Ground-based air temperature data in this region, digital elevation models (DEMs), and river discharge dominated by glacial runoff are used to confirm the glacial response to changes in global climate. Results show that Iceland glaciers have a bimodal distribution of brightness temperature delineating when the snow/ice is melting and refreezing. Ground based temperatures have increased on a decadal trend. Clear glacial boundaries are visible on the passive microwave delineating strong features, and we are working to understand their variability and contribution to glacier evolution. The passive microwave data set allows connections to be made between observations seen on a daily scale and the long term glacier changes observed by the Landsat satellite record that integrates the

Spatially enhanced passive microwave derived soil moisture: capabilities and opportunities

USDA-ARS?s Scientific Manuscript database

Low frequency passive microwave remote sensing is a proven technique for soil moisture retrieval, but its coarse resolution restricts the range of applications. Downscaling, otherwise known as disaggregation, has been proposed as the solution to spatially enhance these coarse resolution soil moistur...

Using the JPL Tropical Cyclone Information System to study the climatology of hurricane precipitation structure from 10 years of passive microwave satellite observations in the Atlantic

NASA Astrophysics Data System (ADS)

Hristova-Veleva, Svetla; Haddad, Ziad; Knosp, Brian; Lambrigtsen, Bjorn; Li, P. Peggy; Poulsen, William; Seo, Eun-Kyoung; Shen, Tsae-Pyng; Turk, Francis J.; Vu, Quoc

2013-04-01

In spite of recent improvements in hurricane track forecast accuracy, currently there are still many unanswered questions about the physical processes that determine hurricane genesis, and evolution. Furthermore, a significant amount of work remains to be done in validating and improving hurricane forecast models. None of this can be accomplished without a comprehensive set of multi-parameter observations that are relevant to both the large-scale and the storm-scale processes in the atmosphere and in the ocean. Despite the significant amount of satellite observations today, they are still underutilized in hurricane research and operations, due to complexity and volume. To facilitate hurricane research, we developed the JPL Tropical Cyclone Information System (TCIS) of multi-instrument satellite observations pertaining to: i) the thermodynamic and microphysical structure of the storms; ii) the air-sea interaction processes; iii) the larger-scale environment as depicted by the SST and the Total Precipitable Water of the environment (Hristova-Veleva et al., 2008, 2011). Our goal was to create a one-stop place to provide the researchers with an extensive set of observed hurricane data, and their graphical representation, organized in an easy way to determine when coincident observations from multiple instruments are available. In this study we use the 10+ years of passive microwave observations of Atlantic hurricanes to create composite structures that are segregated by hurricane category and by intensification rate. The use of composite structures provides a statistically robust framework (e.g. Rogers et al., 2012). We analyze the storm asymmetry as depicted by several factors - brightness temperatures and their derivatives such as a newly-develop Rain Indicator and a new convective/stratiform separation that is based on the value and the spatial variability of this Rain Indicator. The goal is to determine whether the storm morphology (in particular, the storm

First validation of satellite microwave liquid water path with ship-based observations in marine low clouds

NASA Astrophysics Data System (ADS)

Painemal, D.; Cadeddu, M. P.; Greenwald, T. J.; Minnis, P.

2015-12-01

We present the first validation study of satellite microwave liquid water path, from four operational sensors, against in-situ observations from a ship-borne three-channel microwave radiometer collected over the northeast Pacific during May-August of 2013, along a ship transect length of 40˚ (33.7˚N, 118.2˚W - 21.3˚N, 157.8˚W). The satellite sensors analyzed here are: The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Special Sensor Microwave Imager/Sounder (SSMIS) on the Defense Meteorological Satellite Program F16 and F17 satellites, and The Advanced Microwave Scanning Radiometer (AMSR-2) on board the Global Change Observation Mission - Water (GCOM-W1). Satellite retrievals show an overall correlation with hourly-averaged in-situ observations of 0.86 and a positive bias of 10.0 gm2, which decreases to 1.0 gm2 and a correlation that increases to 0.91 when selecting overcast scenes. The satellite bias for broken scenes remains below 22.2 gm2, although the removal of clear-sky in-situ samples yields an unbiased relationship. Satellites produce a diurnal cycle with amplitudes (35-47 gm2) consistent with ship-based observations. Longitudinal biases remain below 17.4 gm2, and they are negligible in overcast scenes and when clear-sky samples are removed from the in-situ hourly average. Our study indicates that satellite microwave retrievals are a reliable dataset for climate studies in marine warm low clouds. The implications for satellite visible/infrared retrievals will be also discussed.

Active-Passive Microwave Remote Sensing of Martian Permafrost and Subsurface Water

NASA Technical Reports Server (NTRS)

Raizer, V.; Linkin, V. M.; Ozorovich, Y. R.; Smythe, W. D.; Zoubkov, B.; Babkin, F.

2000-01-01

The investigation of permafrost formation global distribution and their appearance in h less than or equal 1 m thick subsurface layer would be investigated successfully by employment of active-passive microwave remote sensing techniques.

Passive Microwave Algorithms for Sea Ice Concentration: A Comparison of Two Techniques

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Cavalieri, Donald J.; Parkinson, Claire L.; Gloersen, Per

1997-01-01

The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux(e.g. heat, salt, and water) calculations to small change in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in but larger disagreements in the seasonal regions and in summer. In some ares in the Antarctic, the Bootstrap technique show ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.

Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice

NASA Technical Reports Server (NTRS)

Bliss, Angela C.; Miller, Jeffrey A.; Meier, Walter N.

2017-01-01

Two long records of melt onset (MO) on Arctic sea ice from passive microwave brightness temperatures (Tbs) obtained by a series of satellite-borne instruments are compared. The Passive Microwave (PMW) method and Advanced Horizontal Range Algorithm (AHRA) detect the increase in emissivity that occurs when liquid water develops around snow grains at the onset of early melting on sea ice. The timing of MO on Arctic sea ice influences the amount of solar radiation absorbed by the ice-ocean system throughout the melt season by reducing surface albedos in the early spring. This work presents a thorough comparison of these two methods for the time series of MO dates from 1979through 2012. The methods are first compared using the published data as a baseline comparison of the publically available data products. A second comparison is performed on adjusted MO dates we produced to remove known differences in inter-sensor calibration of Tbs and masking techniques used to develop the original MO date products. These adjustments result in a more consistent set of input Tbs for the algorithms. Tests of significance indicate that the trends in the time series of annual mean MO dates for the PMW and AHRA are statistically different for the majority of the Arctic Ocean including the Laptev, E. Siberian, Chukchi, Beaufort, and central Arctic regions with mean differences as large as 38.3 days in the Barents Sea. Trend agreement improves for our more consistent MO dates for nearly all regions. Mean differences remain large, primarily due to differing sensitivity of in-algorithm thresholds and larger uncertainties in thin-ice regions.

Multi-Frequency Radar/Passive Microwave retrievals of Cold Season Precipitation from OLYMPEX data

NASA Astrophysics Data System (ADS)

Tridon, Frederic; Battaglia, Alessandro; Turk, Joe; Tanelli, Simone; Kneifel, Stefan; Leinonen, Jussi; Kollias, Pavlos

2017-04-01

Due to the large natural variability of its microphysical properties, the characterization of solid precipitation over the variety of Earth surface conditions remain a longstanding open issue for space-based radar and passive microwave (MW) observing systems, such those on board the current NASA-JAXA Global Precipitation measurement (GPM) core and constellation satellites. Observations from the NASA DC-8 including radar profiles from the triple frequency Advanced Precipitation Radar (APR-3) and brightness temperatures from PMW radiometers with frequencies ranging from 89 to 183 GHz were collected during November-December 2015 as part of the OLYMPEX-RADEX campaign in western Washington state. Observations cover orographically-driven precipitation events with flight transects over ocean, coastal areas, vegetated and snow-covered surfaces. This study presents results obtained by a retrieval optimal estimation technique capable of combining the various radar and radiometer measurements in order to retrieve the snow properties such as equivalent water mass and characteristic size. The retrieval is constrained by microphysical a-priori defined by in situ measurements whilst the most recent ice scattering models are used in the forward modelling. The vast dataset collected during OLYMPEX is particular valuable because it can provide very strong tests for the fidelity of ice scattering models deep in the non-Rayleigh regime. In addition, the various scattering tables of snow aggregates with different degrees of riming can be exploited to assess the potential of multi-wavelength active and passive microwave systems in identifying the primary ice growth process (i.e. aggregation vs riming vs deposition). First comparisons with in-situ observations from the coordinated flights of the Citation aircraft will also be presented.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to

In-depth Analysis of Land Surface Emissivity using Microwave Polarization Difference Index to Improve Satellite QPE

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P. E.; Hong, Y.; Wen, Y.; Turk, J.; Gourley, J. J.

2015-12-01

One of primary uncertainties in satellite overland quantitative precipitation estimates (QPE) from passive sensors such as radiometers is the impact on the brightness temperatures by the surface land emissivity. The complexity of surface land emissivity is linked to its temporal variations (diurnal and seasonal) and spatial variations (subsurface vertical profiles of soil moisture, vegetation structure and surface temperature) translating into sub-pixel heterogeneity within the satellite field of view (FOV). To better extract the useful signal from hydrometeors, surface land emissivity needs to be determined and filtered from the satellite-measured brightness temperatures. Based on the dielectric properties of surface land cover constitutes, Microwave Polarization Differential index (MPDI) is expected to carry the composite effect of surface land properties on land surface emissivity, with a higher MPDI indicating a lower emissivity. This study analyses the dependence of MPDI to soil moisture, vegetation and surface skin temperature over 9 different land surface types. Such analysis is performed using the normalized difference vegetation index (NDVI) from MODIS, the near surface air temperature from the RAP model and ante-precedent precipitation accumulation from the Multi-Radar Multi-Sensor as surrogates for the vegetation, surface skin temperature and shallow layer soil moisture, respectively. This paper provides 1) evaluations of brightness temperature-based MPDI from the TRMM and GPM Microwave Imagers in both raining and non-raining conditions to test the dependence of MPDI to precipitation; 2) comparisons of MPDI categorized into instantly before, during and immediately after selected precipitation events to examine the impact of modest-to-heavy precipitation on the spatial pattern of MPDI; 3) inspections of relationship between MPDI versus rain fraction and rain rate within the satellite sensors FOV to investigate the behaviors of MPDI in varying

Summer Arctic sea ice character from satellite microwave data

NASA Technical Reports Server (NTRS)

Carsey, F. D.

1985-01-01

It is pointed out that Arctic sea ice and its environment undergo a number of changes during the summer period. Some of these changes affect the ice cover properties and, in turn, their response to thermal and mechanical forcing throughout the year. The main objective of this investigation is related to the development of a method for estimating the areal coverage of exposed ice, melt ponds, and leads, which are the basic surface variables determining the local surface albedo. The study is based on data obtained in a field investigation conducted from Mould Bay (NWT), Nimbus 5 satellite data, and Seasat data. The investigation demonstrates that microwave data from satellites, especially microwave brightness temperature, provide good data for estimating important characteristics of summer sea ice cover.

Large area mapping of soil moisture using the ESTAR passive microwave radiometer

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Levine, D. M.; Swift, C. T.; Schmugge, T. J.

1994-01-01

Investigations designed to study land surface hydrologic-atmospheric interactions, showing the potential of L band passive microwave radiometry for measuring surface soil moisture over large areas, are discussed. Satisfying the data needs of these investigations requires the ability to map large areas rapidly. With aircraft systems this means a need for more beam positions over a wider swath on each flightline. For satellite systems the essential problem is resolution. Both of these needs are currently being addressed through the development and verification of Electronically Scanned Thinned Array Radiometer (ESTAR) technology. The ESTAR L band radiometer was evaluated for soil moisture mapping applications in two studies. The first was conducted over the semiarid rangeland Walnut Gulch watershed located in south eastern Arizona (U.S.). The second was performed in the subhumid Little Washita watershed in south west Oklahoma (U.S.). Both tests showed that the ESTAR is capable of providing soil moisture with the same level of accuracy as existing systems.

Abnormal Winter Melting of the Arctic Sea Ice Cap Observed by the Spaceborne Passive Microwave Sensors

NASA Astrophysics Data System (ADS)

Lee, Seongsuk; Yi, Yu

2016-12-01

The spatial size and variation of Arctic sea ice play an important role in Earth’s climate system. These are affected by conditions in the polar atmosphere and Arctic sea temperatures. The Arctic sea ice concentration is calculated from brightness temperature data derived from the Defense Meteorological Satellite program (DMSP) F13 Special Sensor Microwave/Imagers (SSMI) and the DMSP F17 Special Sensor Microwave Imager/Sounder (SSMIS) sensors. Many previous studies point to significant reductions in sea ice and their causes. We investigated the variability of Arctic sea ice using the daily sea ice concentration data from passive microwave observations to identify the sea ice melting regions near the Arctic polar ice cap. We discovered the abnormal melting of the Arctic sea ice near the North Pole during the summer and the winter. This phenomenon is hard to explain only surface air temperature or solar heating as suggested by recent studies. We propose a hypothesis explaining this phenomenon. The heat from the deep sea in Arctic Ocean ridges and/ or the hydrothermal vents might be contributing to the melting of Arctic sea ice. This hypothesis could be verified by the observation of warm water column structure below the melting or thinning arctic sea ice through the project such as Coriolis dataset for reanalysis (CORA).

Source analysis of spaceborne microwave radiometer interference over land

NASA Astrophysics Data System (ADS)

Guan, Li; Zhang, Sibo

2016-03-01

Satellite microwave thermal emissions mixed with signals from active sensors are referred to as radiofrequency interference (RFI). Based on Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) observations from June 1 to 16, 2011, RFI over Europe was identified and analyzed using the modified principal component analysis algorithm in this paper. The X band AMSR-E measurements in England and Italy are mostly affected by the stable, persistent, active microwave transmitters on the surface, while the RFI source of other European countries is the interference of the reflected geostationary TV satellite downlink signals to the measurements of spaceborne microwave radiometers. The locations and intensities of the RFI induced by the geostationary TV and communication satellites changed with time within the observed period. The observations of spaceborne microwave radiometers in ascending portions of orbits are usually interfered with over European land, while no RFI was detected in descending passes. The RFI locations and intensities from the reflection of downlink radiation are highly dependent upon the relative geometry between the geostationary satellite and the measuring passive sensor. Only these fields of view of a spaceborne instrument whose scan azimuths are close to the azimuth relative to the geostationary satellite are likely to be affected by RFI.

Pre-Launch Characterization of the Advanced Technology Microwave Sounder (ATMS) on the Joint Polar Satellite System-1 Satellite (JPSS-1)

NASA Astrophysics Data System (ADS)

Kim, Edward; Leslie, Vince; Lyu, Joseph; Smith, Craig; McCormick, Lisa; Anderson, Kent

2016-04-01

The Advanced Technology Microwave Sounder (ATMS) is the newest generation of microwave sounder in the international fleet of polar-orbiting weather satellites, replacing the Advanced Microwave Sounding Unit (AMSU) which first entered service in 1998. The first ATMS was launched aboard the Suomi NPP (S-NPP) satellite in late 2011. The second ATMS is manifested on the Joint Polar Satellite System-1 Satellite (JPSS-1). ATMS provides 22 channels of temperature and humidity sounding observations over a frequency range from 23 to 183 GHz. These microwave soundings provide the highest impact data ingested by operational Numerical Weather Prediction (NWP) models, and are the most critical of the polar-orbiting satellite observations, particularly because microwave sensing can penetrate clouds. This paper will present performance characterizations from pre-launch calibration measurements of the JPSS-1 ATMS just completed in December, 2015. The measurements were conducted in a thermal vacuum chamber with blackbody targets simulating cold space, ambient, and a variable Earth scene. They represent the best opportunity for calibration characterization of the instrument since the environment can be carefully controlled. We will present characterizations of the sensitivity (NEDT), accuracy, nonlinearity, noise spectral characteristics, gain stability, repeatability, and inter-channel correlation. An estimate of expected "striping" will be presented, and a discussion of reflector emissivity effects will also be provided. Comparisons will be made with the S-NPP flight unit. Finally, we will describe planned on-orbit characterizations - such as pitch and roll maneuvers - that will further improve both the measurement quality and the understanding of various error contributions.

Snowmelt and Surface Freeze/Thaw Timings over Alaska derived from Passive Microwave Observations using a Wavelet Classifier

NASA Astrophysics Data System (ADS)

Steiner, N.; McDonald, K. C.; Dinardo, S. J.; Miller, C. E.

2015-12-01

Arctic permafrost soils contain a vast amount of organic carbon that will be released into the atmosphere as carbon dioxide or methane when thawed. Surface to air greenhouse gas fluxes are largely dependent on such surface controls as the frozen/thawed state of the snow and soil. Satellite remote sensing is an important means to create continuous mapping of surface properties. Advances in the ability to determine soil and snow freeze/thaw timings from microwave frequency observations improves upon our ability to predict the response of carbon gas emission to warming through synthesis with in-situ observation, such as the 2012-2015 Carbon in Arctic Reservoir Vulnerability Experiment (CARVE). Surface freeze/thaw or snowmelt timings are often derived using a constant or spatially/temporally variable threshold applied to time-series observations. Alternately, time-series singularity classifiers aim to detect discontinuous changes, or "edges", in time-series data similar to those that occur from the large contrast in dielectric constant during the freezing or thaw of soil or snow. We use multi-scale analysis of continuous wavelet transform spectral gradient brightness temperatures from various channel combinations of passive microwave radiometers, Advanced Microwave Scanning Radiometer (AMSR-E, AMSR2) and Special Sensor Microwave Imager (SSM/I F17) gridded at a 10 km posting with resolution proportional to the observational footprint. Channel combinations presented here aim to illustrate and differentiate timings of "edges" from transitions in surface water related to various landscape components (e.g. snow-melt, soil-thaw). To support an understanding of the physical basis of observed "edges" we compare satellite measurements with simple radiative transfer microwave-emission modeling of the snow, soil and vegetation using in-situ observations from the SNOw TELemetry (SNOTEL) automated weather stations. Results of freeze/thaw and snow-melt timings and trends are

Snowpack monitoring in North America and Eurasia using passive microwave satellite data

NASA Technical Reports Server (NTRS)

Foster, J. L.; Rango, A.; Hall, D. K.

1980-01-01

Areas of the Canadian high plains, the Montana and North Dakota high plains, and the steppes of central Russia were studied in an effort to determine the utility of spaceborne electrical scanning microwave radiometers (ESMR) for monitoring snow depths in different geographic areas. Significant regression relationships between snow depth and microwave brightness temperatures were developed for each of these homogeneous areas. In the areas investigated, Nimbus 6 (.081 cm) ESMR data produced higher correlations than Nimbus 5 (1.55 cm) ESMR data in relating microwave brightness temperature and snow depth from one area to another because different geographic areas are likely to have different snowpack conditions.

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

NASA Technical Reports Server (NTRS)

Tsang, Leung; Hwang, Jenq-Neng

1996-01-01

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

An equivalent method of mixed dielectric constant in passive microwave/millimeter radiometric measurement

NASA Astrophysics Data System (ADS)

Su, Jinlong; Tian, Yan; Hu, Fei; Gui, Liangqi; Cheng, Yayun; Peng, Xiaohui

2017-10-01

Dielectric constant is an important role to describe the properties of matter. This paper proposes This paper proposes the concept of mixed dielectric constant(MDC) in passive microwave radiometric measurement. In addition, a MDC inversion method is come up, Ratio of Angle-Polarization Difference(RAPD) is utilized in this method. The MDC of several materials are investigated using RAPD. Brightness temperatures(TBs) which calculated by MDC and original dielectric constant are compared. Random errors are added to the simulation to test the robustness of the algorithm. Keywords: Passive detection, microwave/millimeter, radiometric measurement, ratio of angle-polarization difference (RAPD), mixed dielectric constant (MDC), brightness temperatures, remote sensing, target recognition.

A flexible telecom satellite repeater based on microwave photonic technologies

NASA Astrophysics Data System (ADS)

Sotom, Michel; Benazet, Benoît; Maignan, Michel

2017-11-01

Future telecom satellite based on geo-stationary Earth orbit (GEO) will require advanced payloads in Kaband so as to receive, route and re-transmit hundreds of microwave channels over multiple antenna beams. We report on the proof-of-concept demonstration of a analogue repeater making use of microwave photonic technologies for supporting broadband, transparent, and flexible cross-connectivity. It has microwave input and output sections, and features a photonic core for LO distribution, frequency down-conversion, and cross-connection of RF channels. With benefits such as transparency to RF frequency, infinite RF isolation, mass and volume savings, such a microwave photonic cross-connect would compare favourably with microwave implementations, and based on optical MEMS switches could grow up to large port counts.

Analytical and Numerical Studies of Active and Passive Microwave Ocean Remote Sensing

DTIC Science & Technology

2001-09-30

of both analytical and efficient numerical methods for electromagnetics and hydrodynamics. New insights regarding these phenomena can then be applied to improve microwave active and passive remote sensing of the ocean surface.

Cloud Liquid Water Path Comparisons from Passive Microwave and Solar Reflectance Satellite Measurements: Assessment of Sub-Field-of-View Cloud Effects in Microwave Retrievals

NASA Technical Reports Server (NTRS)

Greenwald, Thomas J.; Christopher, Sundar A.; Chou, Joyce

1997-01-01

Satellite observations of the cloud liquid water path (LWP) are compared from special sensor microwave imager (SSM/I) measurements and GOES 8 imager solar reflectance (SR) measurements to ascertain the impact of sub-field-of-view (FOV) cloud effects on SSM/I 37 GHz retrievals. The SR retrievals also incorporate estimates of the cloud droplet effective radius derived from the GOES 8 3.9-micron channel. The comparisons consist of simultaneous collocated and full-resolution measurements and are limited to nonprecipitating marine stratocumulus in the eastern Pacific for two days in October 1995. The retrievals from these independent methods are consistent for overcast SSM/I FOVS, with RMS differences as low as 0.030 kg/sq m, although biases exist for clouds with more open spatial structure, where the RMS differences increase to 0.039 kg/sq m. For broken cloudiness within the SSM/I FOV the average beam-filling error (BFE) in the microwave retrievals is found to be about 22% (average cloud amount of 73%). This systematic error is comparable with the average random errors in the microwave retrievals. However, even larger BFEs can be expected for individual FOVs and for regions with less cloudiness. By scaling the microwave retrievals by the cloud amount within the FOV, the systematic BFE can be significantly reduced but with increased RMS differences of O.046-0.058 kg/sq m when compared to the SR retrievals. The beam-filling effects reported here are significant and are expected to impact directly upon studies that use instantaneous SSM/I measurements of cloud LWP, such as cloud classification studies and validation studies involving surface-based or in situ data.

Calibration of the Microwave Limb Sounder on the Upper Atmosphere Research Satellite

NASA Technical Reports Server (NTRS)

Jarnot, R. F.; Cofield, R. E.; Waters, J. W.; Flower, D. A.; Peckham, G. E.

1996-01-01

The Microwave Limb Sounder (MLS) is a three-radiometer, passive, limb emission instrument onboard the Upper Atmosphere Research Satellite (UARS). Radiometric, spectral and field-of-view calibrations of the MLS instrument are described in this paper. In-orbit noise performance, gain stability, spectral baseline and dynamic range are described, as well as use of in-flight data for validation and refinement of prelaunch calibrations. Estimated systematic scaling uncertainties (3 sigma) on calibrated limb radiances from prelaunch calibrations are 2.6% in bands 1 through 3, 3.4% in band 4, and 6% in band 5. The observed systematic errors in band 6 are about 15%, consistent with prelaunch calibration uncertainties. Random uncertainties on individual limb radiance measurements are very close to the levels predicted from measured radiometer noise temperature, with negligible contribution from noise and drifts on the regular in-flight gain calibration measurements.

Investigation of antenna pattern constraints for passive geosynchronous microwave imaging radiometers

NASA Technical Reports Server (NTRS)

Gasiewski, A. J.; Skofronick, G. M.

1992-01-01

Progress by investigators at Georgia Tech in defining the requirements for large space antennas for passive microwave Earth imaging systems is reviewed. In order to determine antenna constraints (e.g., the aperture size, illumination taper, and gain uncertainty limits) necessary for the retrieval of geophysical parameters (e.g., rain rate) with adequate spatial resolution and accuracy, a numerical simulation of the passive microwave observation and retrieval process is being developed. Due to the small spatial scale of precipitation and the nonlinear relationships between precipitation parameters (e.g., rain rate, water density profile) and observed brightness temperatures, the retrieval of precipitation parameters are of primary interest in the simulation studies. Major components of the simulation are described as well as progress and plans for completion. The overall goal of providing quantitative assessments of the accuracy of candidate geosynchronous and low-Earth orbiting imaging systems will continue under a separate grant.

Snow Crystal Orientation Effects on the Scattering of Passive Microwave Radiation

NASA Technical Reports Server (NTRS)

Foster, J. L.; Barton, J. S.; Chang, A. T. C.; Hall, D. K.

1999-01-01

For this study, consideration is given to the role crystal orientation plays in scattering and absorbing microwave radiation. A discrete dipole scattering model is used to measure the passive microwave radiation, at two polarizations (horizontal and vertical), scattered by snow crystals oriented in random and non random positions, having various sizes (ranging between 1 micrometers to 10,000 micrometers in radius), and shapes (including spheroids, cylinders, hexagons). The model results demonstrate that for the crystal sizes typically found in a snowpack, crystal orientation is insignificant compared to crystal size in terms of scattering microwave energy in the 8,100 gm (37 GHz) region of the spectrum. Therefore, the assumption used in radiative transfer approaches, where snow crystals are modeled as randomly oriented spheres, is adequate to account for the transfer of microwave energy emanating from the ground and passing through a snowpack.

The Passive Microwave Neural Network Precipitation Retrieval (PNPR) for AMSU/MHS and ATMS cross-track scanning radiometers

NASA Astrophysics Data System (ADS)

Sano', Paolo; Casella, Daniele; Panegrossi, Giulia; Cinzia Marra, Anna; Dietrich, Stefano

2016-04-01

Spaceborne microwave cross-track scanning radiometers, originally developed for temperature and humidity sounding, have shown great capabilities to provide a significant contribution in precipitation monitoring both in terms of measurement quality and spatial/temporal coverage. The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross-track scanning radiometers, originally developed for the Advanced Microwave Sounding Unit/Microwave Humidity Sounder (AMSU-A/MHS) radiometers (on board the European MetOp and U.S. NOAA satellites), was recently newly designed to exploit the Advanced Technology Microwave Sounder (ATMS) on board the Suomi-NPP satellite and the future JPSS satellites. The PNPR algorithm is based on the Artificial Neural Network (ANN) approach. The main PNPR-ATMS algorithm changes with respect to PNPR-AMSU/MHS are the design and implementation of a new ANN able to manage the information derived from the additional ATMS channels (respect to the AMSU-A/MHS radiometer) and a new screening procedure for not-precipitating pixels. In order to achieve maximum consistency of the retrieved surface precipitation, both PNPR algorithms are based on the same physical foundation. The PNPR is optimized for the European and the African area. The neural network was trained using a cloud-radiation database built upon 94 cloud-resolving simulations over Europe and the Mediterranean and over the African area and radiative transfer model simulations of TB vectors consistent with the AMSU-A/MHS and ATMS channel frequencies, viewing angles, and view-angle dependent IFOV sizes along the scan projections. As opposed to other ANN precipitation retrieval algorithms, PNPR uses a unique ANN that retrieves the surface precipitation rate for all types of surface backgrounds represented in the training database, i.e., land (vegetated or arid), ocean, snow/ice or coast. This approach prevents different precipitation estimates from being inconsistent with one

Active/Passive Remote Sensing of the Ocean Surface at Microwave Frequencies

DTIC Science & Technology

1999-09-30

This report summarizes research activities and results obtained under grant N000l4-99-1-0627 "Active/Passive Remote Sensing of the Ocean Surface at...Measurements were completed during April 1999 by the Microwave Remote Sensing Laboratory at the University of Massachusetts.

Evaluation of multichannel Wiener filters applied to fine resolution passive microwave images of first-year sea ice

NASA Technical Reports Server (NTRS)

Full, William E.; Eppler, Duane T.

1993-01-01

The effectivity of multichannel Wiener filters to improve images obtained with passive microwave systems was investigated by applying Wiener filters to passive microwave images of first-year sea ice. Four major parameters which define the filter were varied: the lag or pixel offset between the original and the desired scenes, filter length, the number of lines in the filter, and the weight applied to the empirical correlation functions. The effect of each variable on the image quality was assessed by visually comparing the results. It was found that the application of multichannel Wiener theory to passive microwave images of first-year sea ice resulted in visually sharper images with enhanced textural features and less high-frequency noise. However, Wiener filters induced a slight blocky grain to the image and could produce a type of ringing along scan lines traversing sharp intensity contrasts.

Satellite Snow-Cover Mapping: A Brief Review

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.

1995-01-01

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow

Investigating Satellite Microwave observations of Precipitation in Different Climate Regimes

NASA Astrophysics Data System (ADS)

Wang, N.; Ferraro, R. R.

2013-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperature characteristics similar to precipitation Ongoing work by GPM microwave radiometer team is constructing databases through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The original data sets will focus on stratification by emissivity class, surface temperature and total perceptible water. We'll perform sensitivity studies to determine the potential role of ancillary data (e.g., land surface temperature, snow cover/water equivalent, etc.) to improve precipitation estimation over land in different climate regimes, including rain and snow. In other words, what information outside of the radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

Satellite passive remote sensing of off-shore pollutants, volume 2

NASA Technical Reports Server (NTRS)

1979-01-01

Satellite detection and monitoring of off-shore dumped pollutants, other than oil, are discussed. Summaries of satellite sensor performance in three spectral bands (visible, infrared, and microwave) are presented. The bulk of the report gives all the calculations, trade-offs and limitations of the three sensor systems. It is asserted that the problem of pollution monitoring is not a sensor problem but a problem of mathematical modeling and data processing.

Effectiveness evaluation of double-layered satellite network with laser and microwave hybrid links based on fuzzy analytic hierarchy process

NASA Astrophysics Data System (ADS)

Zhang, Wei; Rao, Qiaomeng

2018-01-01

In order to solve the problem of high speed, large capacity and limited spectrum resources of satellite communication network, a double-layered satellite network with global seamless coverage based on laser and microwave hybrid links is proposed in this paper. By analyzing the characteristics of the double-layered satellite network with laser and microwave hybrid links, an effectiveness evaluation index system for the network is established. And then, the fuzzy analytic hierarchy process, which combines the analytic hierarchy process and the fuzzy comprehensive evaluation theory, is used to evaluate the effectiveness of the double-layered satellite network with laser and microwave hybrid links. Furthermore, the evaluation result of the proposed hybrid link network is obtained by simulation. The effectiveness evaluation process of the proposed double-layered satellite network with laser and microwave hybrid links can help to optimize the design of hybrid link double-layered satellite network and improve the operating efficiency of the satellite system.

Synergistic use of multispectral satellite data for monitoring land surface change

NASA Technical Reports Server (NTRS)

Choudhury, Bhaskar J.

1991-01-01

Observations by the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA satellites were used to compute visible and near infrared reflectances and surface temperature, while passive microwave observations at 37 GHz frequency by the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) on board, respectively, the Nimbus-7 and DMSP-F8 satellites were used to compute polarization difference. These observations were analyzed along transects from rainforest to desert over northern Africa for the period 1979-1987, which included an unprecedented drought during 1984 over the Sahel zone. Model simulations were made to understand the interrelationship among multispectral data.

Potential Application of Airborne Passive Microwave Observations for Monitoring Inland Flooding Caused by Tropical Cyclones

NASA Technical Reports Server (NTRS)

Hood, Robbie E.; Radley, C.D.; LaFontaine, F.J.

2008-01-01

Inland flooding from tropical cyclones can be a significant factor in storm-related deaths in the United States and other countries. Information collected during NASA tropical cyclone field studies suggest surface water and flooding induced by tropical cyclone precipitation can be detected and therefore monitored using passive microwave airborne radiometers. In particular, the 10.7 GHz frequency of the NASA Advanced Microwave Precipitation Radiometer (AMPR) flown on the NASA ER-2 has demonstrated high resolution detection of anomalous surface water and flooding in numerous situations. This presentation will highlight the analysis of three cases utilizing primarily satellite and airborne radiometer data. Radiometer data from the 1998 Third Convection and Moisture Experiment (CAMEX-3) are utilized to detect surface water during landfalling Hurricane Georges in both the Dominican Republic and Louisiana. A third case is landfalling Tropical Storm Gert in Eastern Mexico during the Tropical Cloud Systems and Processes (TCSP) experiment in 2005. AMPR data are compared to topographic data and vegetation indices to evaluate the significance of the surface water signature visible in the 10.7 GHz information. The results of this study suggest the benefit of an aircraft 10 GHz radiometer to provide real-time observations of surface water conditions as part of a multi-sensor flood monitoring network.

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

NASA Technical Reports Server (NTRS)

Maslanik, J. A.; Key, J.

1992-01-01

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

Severe storm identification with satellite microwave radiometry: An initial investigation with Nimbus-7 SMMR data

NASA Technical Reports Server (NTRS)

Spencer, R. W.; Howland, M. R.

1984-01-01

The severe weather characteristics of convective storms as observed by the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) are investigated. Low 37 GHz brightness temperatures (due to scattering of upwelling radiation by precipitation size ice) are related to the occurrence of severe weather (large hail, strong winds or wind damage, tornadoes and funnel clouds) within one hour of the satellite observation time. During 1979 and 1980 over the United States there were 263 storms which had very cold 37 GHz signatures. Of these storms 15% were severe. The SMMR detected hail, wind, and tornadic storms equally well. Critical Success Indices (CSI's) of 0.32, 0.48, and 0.38 are achieved for the thresholding of severe vs. nonsevere low brightness temperature events during 1979, 1980, and the two years combined, respectively. Such scores are comparable to skill scores for early radar detection methods. These results suggest that a future geostationary passive microwave imaging capability at 37 GHz, with sufficient spatial and temporal resolution, would allow the detection of severe convective storms. This capability would provide a useful complement to radar, especially in areas not covered by radar.

An Inter-calibrated Passive Microwave Brightness Temperature Data Record and Ocean Products

NASA Astrophysics Data System (ADS)

Hilburn, K. A.; Wentz, F. J.

2014-12-01

Inter-calibration of passive microwave sensors has been the subject of on-going activity at Remote Sensing Systems (RSS) since 1974. RSS has produced a brightness temperature TB data record that spans the last 28 years (1987-2014) from inter-calibrated passive microwave sensors on 14 satellites: AMSR-E, AMSR2, GMI, SSMI F08-F15, SSMIS F16-F18, TMI, WindSat. Accompanying the TB record are a suite of ocean products derived from the TBs that provide a 28-year record of wind speed, water vapor, cloud liquid, and rain rate; and 18 years (1997-2014) of sea surface temperatures, corresponding to the period for which 6 and/or 10 GHz measurements are available. Crucial to the inter-calibration and ocean product retrieval are a highly accurate radiative transfer model RTM. The RSS RTM has been continually refined for over 30 years and is arguably the most accurate model in the 1-100 GHz spectrum. The current generation of TB and ocean products, produced using the latest version of the RTM, is called Version-7. The accuracy of the Version-7 inter-calibration is estimated to be 0.1 K, based on inter-satellite comparisons and validation of the ocean products against in situ measurements. The data record produced by RSS has had a significant scientific impact. Over just the last 14 years (2000-2013) RSS data have been used in 743 peer-reviewed journal articles. This is an average of 4.5 peer-reviewed papers published every month made possible with RSS data. Some of the most important scientific contributions made by RSS data have been to the study of the climate. The AR5 Report "Climate Change 2013: The Physical Science Basis" by the Intergovernmental Panel on Climate Change (IPCC), the internationally accepted authority on climate change, references 20 peer-reviewed journal papers from RSS scientists. The report makes direct use of RSS water vapor data, RSS atmospheric temperatures from MSU/AMSU, and 9 other datasets that are derived from RSS data. The RSS TB data record is

An Evaluation of Soil Moisture Retrievals Using Aircraft and Satellite Passive Microwave Observations during SMEX02

NASA Technical Reports Server (NTRS)

Bolten, John D.; Lakshmi, Venkat

2009-01-01

The Soil Moisture Experiments conducted in Iowa in the summer of 2002 (SMEX02) had many remote sensing instruments that were used to study the spatial and temporal variability of soil moisture. The sensors used in this paper (a subset of the suite of sensors) are the AQUA satellite-based AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System) and the aircraft-based PSR (Polarimetric Scanning Radiometer). The SMEX02 design focused on the collection of near simultaneous brightness temperature observations from each of these instruments and in situ soil moisture measurements at field- and domain- scale. This methodology provided a basis for a quantitative analysis of the soil moisture remote sensing potential of each instrument using in situ comparisons and retrieved soil moisture estimates through the application of a radiative transfer model. To this end, the two sensors are compared with respect to their estimation of soil moisture.

Microwave Observations of Precipitation and the Atmosphere

NASA Technical Reports Server (NTRS)

Staelin, David H.; Rosenkranz, Philip W.

2004-01-01

This research effort had three elements devoted to improving satellite-derived passive microwave retrievals of precipitation rate: morphological rain-rate retrievals, warm rain retrievals, and extension of a study of geostationary satellite options. The morphological precipitation-rate retrieval method uses for the first time the morphological character of the observed storm microwave spectra. The basic concept involves: 1) retrieval of point rainfall rates using current algorithms, 2) using spatial feature vectors of the observations over segmented multi-pixel storms to estimate the integrated rainfall rate for that storm (cu m/s), and 3) normalization of the point rain-rate retrievals to ensure consistency with the storm-wide retrieval. This work is ongoing, but two key steps have been completed: development of a segmentation algorithm for defining spatial regions corresponding to single storms for purposes of estimation, and reduction of some of the data from NAST-M that will be used to support this research going forward. The warm rain retrieval method involved extension of Aquai/AIRS/AMSU/HSB algorithmic work on cloud water retrievals. The central concept involves the fact that passive microwave cloud water retrievals over approx. 0.4 mm are very likely associated with precipitation. Since glaciated precipitation is generally detected quite successfully using scattering signatures evident in the surface-blind 54- and 183-GHz bands, this new method complements the first by permitting precipitation retrievals of non-glaciated events. The method is most successful over ocean, but has detected non-glaciated convective cells over land, perhaps in their early formative stages. This work will require additional exploration and validation prior to publication. Passive microwave instrument configurations for use in geostationary orbit were studied. They employ parabolic reflectors between 2 and 4 meters in diameter, and frequencies up to approx.430 GHz; this

An extended global Earth system data record on daily landscape freeze-thaw status determined from satellite passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Kim, Youngwook; Kimball, John S.; Glassy, Joseph; Du, Jinyang

2017-02-01

The landscape freeze-thaw (FT) signal determined from satellite microwave brightness temperature (Tb) observations has been widely used to define frozen temperature controls on land surface water mobility and ecological processes. Calibrated 37 GHz Tb retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and SSM/I Sounder (SSMIS) were used to produce a consistent and continuous global daily data record of landscape FT status at 25 km grid cell resolution. The resulting FT Earth system data record (FT-ESDR) is derived from a refined classification algorithm and extends over a larger domain and longer period (1979-2014) than prior FT-ESDR releases. The global domain encompasses all land areas affected by seasonal frozen temperatures, including urban, snow- and ice-dominant and barren land, which were not represented by prior FT-ESDR versions. The FT retrieval is obtained using a modified seasonal threshold algorithm (MSTA) that classifies daily Tb variations in relation to grid-cell-wise FT thresholds calibrated using surface air temperature data from model reanalysis. The resulting FT record shows respective mean annual spatial classification accuracies of 90.3 and 84.3 % for evening (PM) and morning (AM) overpass retrievals relative to global weather station measurements. Detailed data quality metrics are derived characterizing the effects of sub-grid-scale open water and terrain heterogeneity, as well as algorithm uncertainties on FT classification accuracy. The FT-ESDR results are also verified against other independent cryospheric data, including in situ lake and river ice phenology, and satellite observations of Greenland surface melt. The expanded FT-ESDR enables new investigations encompassing snow- and ice-dominant land areas, while the longer record and favorable accuracy allow for refined global change assessments that can better distinguish transient weather extremes, landscape phenological shifts

Synergistic use of active and passive microwave in soil moisture estimation

NASA Technical Reports Server (NTRS)

O'Neill, P.; Chauhan, N.; Jackson, T.; Saatchi, S.

1992-01-01

Data gathered during the MACHYDRO experiment in central Pennsylvania in July 1990 have been utilized to study the synergistic use of active and passive microwave systems for estimating soil moisture. These data sets were obtained during an eleven-day period with NASA's Airborne Synthetic Aperture Radar (AIRSAR) and Push-Broom Microwave Radiometer (PBMR) over an instrumented watershed which included agricultural fields with a number of different crop covers. Simultaneous ground truth measurements were also made in order to characterize the state of vegetation and soil moisture under a variety of meteorological conditions. A combination algorithm is presented as applied to a representative corn field in the MACHYDRO watershed.

A Comparison between Lightning Activity and Passive Microwave Measurements

NASA Technical Reports Server (NTRS)

Kevin, Driscoll T.; Hugh, Christian J.; Goodman, Steven J.

1999-01-01

A recent examination of data from the Lightning Imaging Sensor (LIS) and the TRMM Microwave Imager (TMI) suggests that storm with the highest frequency of lightning also possess the most pronounced microwave scattering signatures at 37 and 85 GHz. This study demonstrates a clear dependence between lightning and the passive microwave measurements, and accentuates how direct the relationship really is between cloud ice and lightning activity. In addition, the relationship between the quantity of ice content and the frequency of lightning (not just the presence of lightning) , is consistent throughout the seasons in a variety of regimes. Scatter plots will be presented which show the storm-averaged brightness temperatures as a function of the lightning density of the storms (L/Area) . In the 85 GHz and 37 GHz scatter plots, the brightness temperature is presented in the form Tb = k1 x log10(L/Area) + k2, where the slope of the regression, k1, is 58 for the 85 GHz relationship and 30.7 for the 37 GHz relationship. The regression for both these fits showed a correlation of 0.76 (r2 = 0.58), which is quite promising considering the simple procedure used to make the comparisons, which have not yet even been corrected for the view angle differences between the instruments, or the polarization corrections in the microwave imager.

Snowfall Rate Retrieval using NPP ATMS Passive Microwave Measurements

NASA Technical Reports Server (NTRS)

Meng, Huan; Ferraro, Ralph; Kongoli, Cezar; Wang, Nai-Yu; Dong, Jun; Zavodsky, Bradley; Yan, Banghua; Zhao, Limin

2014-01-01

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow-on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2014). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two-stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The ATMS SFR product is validated against radar and gauge snowfall data and shows that the ATMS algorithm outperforms the AMSU/MHS SFR.

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

NASA Technical Reports Server (NTRS)

Yueh, Simon H.

2004-01-01

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Challenges in Interpreting and Validating Satellite Soil Moisture Information

USDA-ARS?s Scientific Manuscript database

Global soil moisture products are now being generated routinely using microwave-based satellite observing systems. These include the NASA Soil Moisture Active Passive (SMAP) mission. In order to fully exploit these observations they must be integrated with both in situ measurements and model-based e...

Sea Ice and Ice Temperature Variability as Observed by Microwave and Infrared Satellite Data

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Recent reports of a retreating and thinning sea ice cover in the Arctic have pointed to a strong suggestion of significant warming in the polar regions. It is especially important to understand what these reports mean in light of the observed global warning and because the polar regions are expected to be most sensitive to changes in climate. To gain insight into this phenomenon, co-registered ice concentrations and surface temperatures derived from two decades of satellite microwave and infrared data have been processed and analyzed. While observations from meteorological stations indicate consistent surface warming in both regions during the last fifty years, the last 20 years of the same data set show warming in the Arctic but a slight cooling in the Antarctic. These results are consistent with the retreat in the Arctic ice cover and the advance in the Antarctic ice cover as revealed by historical satellite passive microwave data. Surface temperatures derived from satellite infrared data are shown to be consistent within 3 K with surface temperature data from the limited number of stations. While not as accurate, the former provides spatially detailed changes over the twenty year period. In the Arctic, for example, much of the warming occurred in the Beaufort Sea and the North American region in 1998 while slight cooling actually happened in parts of the Laptev Sea and Northern Siberia during the same time period. Big warming anomalies are also observed during the last five years but a periodic cycle of about ten years is apparent suggesting a possible influence of the North Atlantic Oscillation. In the Antarctic, large interannual and seasonal changes are also observed in the circumpolar ice cover with regional changes showing good coherence with surface temperature anomalies. However, a mode 3 is observed to be more dominant than the mode 2 wave reported in the literature. Some of these spatial and temporal changes appear to be influenced by the Antarctic

High power microwave components for space communications satellite

NASA Technical Reports Server (NTRS)

Jankowski, H.; Geia, A.

1972-01-01

Analyzed, developed, and tested were high power microwave components for communications satellites systems. Included were waveguide and flange configurations with venting, a harmonic filter, forward and reverse power monitors, electrical fault sensors, and a diplexer for two channel simultaneous transmission. The assembly of 8.36 GHz components was bench tested, and then operated for 60 hours at 3.5 kW CW in a high vacuum. The diplexer was omitted from this test pending a modification of its end irises. An RF leakage test showed only that care is required at flange junctions; all other components were RF tight. Designs were extrapolated for 12 GHz and 2.64 GHz high power satellite systems.

Ice water path estimation and characterization using passive microwave radiometry

NASA Technical Reports Server (NTRS)

Vivekanandan, J.; Turk, J.; Bringi, V. N.

1991-01-01

Model computations of top-of-atmospheric microwave brightness temperatures T(B) from layers of precipitation-sized ice of variable bulk density and ice water content (IWC) are presented. It is shown that the 85-GHz T(B) depends essentially on the ice optical thickness. The results demonstrate the potential usefulness of scattering-based channels for characterizing the ice phase and suggest a top-down methodology for retrieval of cloud vertical structure and precipitation estimation from multifrequency passive microwave measurements. Attention is also given to radiative transfer model results based on the multiparameter radar data initialization from the Cooperative Huntsville Meteorological Experiment (COHMEX) in northern Alabama. It is shown that brightness temperature warming effects due to the inclusion of a cloud liquid water profile are especially significant at 85 GHz during later stages of cloud evolution.

A Texture-Polarization Method for Estimating Convective/Stratiform Precipitation Area Coverage from Passive Microwave Radiometer Data

NASA Technical Reports Server (NTRS)

Olson, William S.; Hong, Ye; Kummerow, Christian D.; Turk, Joseph; Einaudi, Franco (Technical Monitor)

2000-01-01

Observational and modeling studies have described the relationships between convective/stratiform rain proportion and the vertical distributions of vertical motion, latent heating, and moistening in mesoscale convective systems. Therefore, remote sensing techniques which can quantify the relative areal proportion of convective and stratiform, rainfall can provide useful information regarding the dynamic and thermodynamic processes in these systems. In the present study, two methods for deducing the convective/stratiform areal extent of precipitation from satellite passive microwave radiometer measurements are combined to yield an improved method. If sufficient microwave scattering by ice-phase precipitating hydrometeors is detected, the method relies mainly on the degree of polarization in oblique-view, 85.5 GHz radiances to estimate the area fraction of convective rain within the radiometer footprint. In situations where ice scattering is minimal, the method draws mostly on texture information in radiometer imagery at lower microwave frequencies to estimate the convective area fraction. Based upon observations of ten convective systems over ocean and nine systems over land, instantaneous 0.5 degree resolution estimates of convective area fraction from the Tropical Rainfall Measuring Mission Microwave Imager (TRMM TMI) are compared to nearly coincident estimates from the TRMM Precipitation Radar (TRMM PR). The TMI convective area fraction estimates are slightly low-biased with respect to the PR, with TMI-PR correlations of 0.78 and 0.84 over ocean and land backgrounds, respectively. TMI monthly-average convective area percentages in the tropics and subtropics from February 1998 exhibit the greatest values along the ITCZ and in continental regions of the summer (southern) hemisphere. Although convective area percentages. from the TMI are systematically lower than those from the PR, monthly rain patterns derived from the TMI and PR rain algorithms are very similar

Compact tunable and reconfigurable microwave photonic filter for satellite payloads

NASA Astrophysics Data System (ADS)

Santos, M. C.; Yoosefi, O.

2017-11-01

The trend towards the photonic processing of electrical signals at microwave frequencies for satellite payloads is increasing at a breathtaking pace, mainly spurred by prospects of wide electrical bandwidth operation, low mass and volume, reduced electrical noise levels, immunity to electromagnetic interferences and resistance to both temperature and radiation.

Real Time Monitoring of Flooding from Microwave Satellite Observations

NASA Technical Reports Server (NTRS)

Galantowicz, John F.; Frey, Herb (Technical Monitor)

2002-01-01

We have developed a new method for making high-resolution flood extent maps (e.g., at the 30-100 m scale of digital elevation models) in real-time from low-resolution (20-70 km) passive microwave observations. The method builds a "flood-potential" database from elevations and historic flood imagery and uses it to create a flood-extent map consistent with the observed open water fraction. Microwave radiometric measurements are useful for flood monitoring because they sense surface water in clear-or-cloudy conditions and can provide more timely data (e.g., compared to radars) from relatively wide swath widths and an increasing number of available platforms (DMSP, ADEOS-II, Terra, NPOESS, GPM). The chief disadvantages for flood mapping are the radiometers' low resolution and the need for local calibration of the relationship between radiances and open-water fraction. We present our method for transforming microwave sensor-scale open water fraction estimates into high-resolution flood extent maps and describe 30-day flood map sequences generated during a retrospective study of the 1993 Great Midwest Flood. We discuss the method's potential improvement through as yet unimplemented algorithm enhancements and expected advancements in microwave radiometry (e.g., improved resolution and atmospheric correction).

The Effects of Rainfall Inhomogeneity on Climate Variability of Rainfall Estimated from Passive Microwave Sensors

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Poyner, Philip; Berg, Wesley; Thomas-Stahle, Jody

2007-01-01

Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (T(sub b)) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km X 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global

Determination of precipitation profiles from airborne passive microwave radiometric measurements

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Hakkarinen, Ida M.; Pierce, Harold F.; Weinman, James A.

1991-01-01

This study presents the first quantitative retrievals of vertical profiles of precipitation derived from multispectral passive microwave radiometry. Measurements of microwave brightness temperature (Tb) obtained by a NASA high-altitude research aircraft are related to profiles of rainfall rate through a multichannel piecewise-linear statistical regression procedure. Statistics for Tb are obtained from a set of cloud radiative models representing a wide variety of convective, stratiform, and anvil structures. The retrieval scheme itself determines which cloud model best fits the observed meteorological conditions. Retrieved rainfall rate profiles are converted to equivalent radar reflectivity for comparison with observed reflectivities from a ground-based research radar. Results for two case studies, a stratiform rain situation and an intense convective thunderstorm, show that the radiometrically derived profiles capture the major features of the observed vertical structure of hydrometer density.

The Upper Atmosphere Research Satellite microwave limb sounder instrument

NASA Astrophysics Data System (ADS)

Barath, F. T.; Chavez, M. C.; Cofield, R. E.; Flower, D. A.; Frerking, M. A.; Gram, M. B.; Harris, W. M.; Holden, J. R.; Jarnot, R. F.; Kloezeman, W. G.

1993-06-01

The microwave limb sounder (MLS) on the Upper Atmosphere Research Satellite (UARS) is the first satellite experiment using limb sounding techniques at microwave frequencies. Primary measurement objectives are stratospheric ClO, O3, H2O, temperature, and pressure. Measurements are of thermal emission: all are performed simultaneously and continuously and are not degraded by ice clouds or volcanic aerosols. The instrument has a 1.6-m mechanically scanning antenna system and contains heterodyne radiometers in spectral bands centred near 63, 183, and 205 GHz. The radiometers operate at ambient temperature and use Schottky-diode mixers with local oscillators derived from phase-locked Gunn oscillators. Frequency tripling by varactor multipliers generates the 183- and 205-GHz local oscillators, and quasi-optical techniques inject these into the mixers. Six 15-channel filter banks spectrally resolve stratospheric thermal emission lines and produce an output spectrum every 2 s. Thermal stability is sufficient for 'total power' measurements which do not require fast chopping. Radiometric calibration, consisting of measurements of cold space and an internal target, is performed every 65-s limb scan. Instrument in-orbit performance has been excellent, and all objectives are being met.

The Upper Atmosphere Research Satellite microwave limb sounder instrument

NASA Technical Reports Server (NTRS)

Barath, F. T.; Chavez, M. C.; Cofield, R. E.; Flower, D. A.; Frerking, M. A.; Gram, M. B.; Harris, W. M.; Holden, J. R.; Jarnot, R. F.; Kloezeman, W. G.

1993-01-01

The microwave limb sounder (MLS) on the Upper Atmosphere Research Satellite (UARS) is the first satellite experiment using limb sounding techniques at microwave frequencies. Primary measurement objectives are stratospheric ClO, O3, H2O, temperature, and pressure. Measurements are of thermal emission: all are performed simultaneously and continuously and are not degraded by ice clouds or volcanic aerosols. The instrument has a 1.6-m mechanically scanning antenna system and contains heterodyne radiometers in spectral bands centred near 63, 183, and 205 GHz. The radiometers operate at ambient temperature and use Schottky-diode mixers with local oscillators derived from phase-locked Gunn oscillators. Frequency tripling by varactor multipliers generates the 183- and 205-GHz local oscillators, and quasi-optical techniques inject these into the mixers. Six 15-channel filter banks spectrally resolve stratospheric thermal emission lines and produce an output spectrum every 2 s. Thermal stability is sufficient for 'total power' measurements which do not require fast chopping. Radiometric calibration, consisting of measurements of cold space and an internal target, is performed every 65-s limb scan. Instrument in-orbit performance has been excellent, and all objectives are being met.

Global Precipitation Estimates from Cross-Track Passive Microwave Observations Using a Physically-Based Retrieval Scheme

NASA Technical Reports Server (NTRS)

Kidd, Chris; Matsui, Toshi; Chern, Jiundar; Mohr, Karen; Kummerow, Christian; Randel, Dave

2015-01-01

The estimation of precipitation across the globe from satellite sensors provides a key resource in the observation and understanding of our climate system. Estimates from all pertinent satellite observations are critical in providing the necessary temporal sampling. However, consistency in these estimates from instruments with different frequencies and resolutions is critical. This paper details the physically based retrieval scheme to estimate precipitation from cross-track (XT) passive microwave (PM) sensors on board the constellation satellites of the Global Precipitation Measurement (GPM) mission. Here the Goddard profiling algorithm (GPROF), a physically based Bayesian scheme developed for conically scanning (CS) sensors, is adapted for use with XT PM sensors. The present XT GPROF scheme utilizes a model-generated database to overcome issues encountered with an observational database as used by the CS scheme. The model database ensures greater consistency across meteorological regimes and surface types by providing a more comprehensive set of precipitation profiles. The database is corrected for bias against the CS database to ensure consistency in the final product. Statistical comparisons over western Europe and the United States show that the XT GPROF estimates are comparable with those from the CS scheme. Indeed, the XT estimates have higher correlations against surface radar data, while maintaining similar root-mean-square errors. Latitudinal profiles of precipitation show the XT estimates are generally comparable with the CS estimates, although in the southern midlatitudes the peak precipitation is shifted equatorward while over the Arctic large differences are seen between the XT and the CS retrievals.

Variations in West Antarctic Ice Front and Passive Microwave Brightness Temperature for 8 Years Duration in 2000s

NASA Astrophysics Data System (ADS)

Kim, J.; Yu, J.; Wang, L.; Liu, H.

2017-12-01

Changes in Antarctic ice sheet are caused by various reasons such as changes in Holocene climate, precipitation, and ocean temperature. Such issues of changes in ice sheet has been mainly focused on the Antarctic peninsula, and it is known that ice retreat of the area is caused by changes in atmospheric and ocean temperatures. For the case of West Antarctica, ice front change research is relatively rarely conducted except the Pine island glacier area. This study has monitored ice front changes of West Antarctica and compared the patterns with the changes in brightness temperature based on remote sensing techniques. We used 2000 Radarsat-1 and 2008 Rasarsat-2 SAR data to delineate coastlines of whole West Antarctica based on the locally thresholding adaptive algorithm. The delineated coast lines are analyzed to figure out ice front change patterns between the duration. The variations in brightness temperature for the same duration are calculated based on Defense Meteorological Satellite Program (DMSP)'s Special Sensor Microwave/Images-Special Sensor Microwave Imager/Sounder (SSM/I-SSMIS) passive microwave data. The results show ice front of West Antarctica shows advancing trend except the pine island glacier area. The brightness temperature had decreasing trend during the study period. It infers that changes in ice front and brightness temperature of West Antarctica have considerable relationships. It is expected that a long term monitoring of the relationship would contribute understanding ice dynamics of West Antarctica significantly.

Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

DOE PAGES

Cadeddu, Maria P.; Marchand, Roger; Orlandi, Emiliano; ...

2017-08-11

Satellite and ground-based microwave radiometers are routinely used for the retrieval of liquid water path (LWP) under all atmospheric conditions. The retrieval of water vapor and LWP from ground-based radiometers during rain has proved to be a difficult challenge for two principal reasons: the inadequacy of the nonscattering approximation in precipitating clouds and the deposition of rain drops on the instrument's radome. In this paper, we combine model computations and real ground-based, zenith-viewing passive microwave radiometer brightness temperature measurements to investigate how total, cloud, and rain LWP retrievals are affected by assumptions on the cloud drop size distribution (DSD) andmore » under which conditions a nonscattering approximation can be considered reasonably accurate. Results show that until the drop effective diameter is larger than similar to 200 mu m, a nonscattering approximation yields results that are still accurate at frequencies less than 90 GHz. For larger drop sizes, it is shown that higher microwave frequencies contain useful information that can be used to separate cloud and rain LWP provided that the vertical distribution of hydrometeors, as well as the DSD, is reasonably known. The choice of the DSD parameters becomes important to ensure retrievals that are consistent with the measurements. A physical retrieval is tested on a synthetic data set and is then used to retrieve total, cloud, and rain LWP from radiometric measurements during two drizzling cases at the atmospheric radiation measurement Eastern North Atlantic site.« less

Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cadeddu, Maria P.; Marchand, Roger; Orlandi, Emiliano

Satellite and ground-based microwave radiometers are routinely used for the retrieval of liquid water path (LWP) under all atmospheric conditions. The retrieval of water vapor and LWP from ground-based radiometers during rain has proved to be a difficult challenge for two principal reasons: the inadequacy of the nonscattering approximation in precipitating clouds and the deposition of rain drops on the instrument's radome. In this paper, we combine model computations and real ground-based, zenith-viewing passive microwave radiometer brightness temperature measurements to investigate how total, cloud, and rain LWP retrievals are affected by assumptions on the cloud drop size distribution (DSD) andmore » under which conditions a nonscattering approximation can be considered reasonably accurate. Results show that until the drop effective diameter is larger than similar to 200 mu m, a nonscattering approximation yields results that are still accurate at frequencies less than 90 GHz. For larger drop sizes, it is shown that higher microwave frequencies contain useful information that can be used to separate cloud and rain LWP provided that the vertical distribution of hydrometeors, as well as the DSD, is reasonably known. The choice of the DSD parameters becomes important to ensure retrievals that are consistent with the measurements. A physical retrieval is tested on a synthetic data set and is then used to retrieve total, cloud, and rain LWP from radiometric measurements during two drizzling cases at the atmospheric radiation measurement Eastern North Atlantic site.« less

Satellite-based Tropical Cyclone Monitoring Capabilities

NASA Astrophysics Data System (ADS)

Hawkins, J.; Richardson, K.; Surratt, M.; Yang, S.; Lee, T. F.; Sampson, C. R.; Solbrig, J.; Kuciauskas, A. P.; Miller, S. D.; Kent, J.

2012-12-01

Satellite remote sensing capabilities to monitor tropical cyclone (TC) location, structure, and intensity have evolved by utilizing a combination of operational and research and development (R&D) sensors. The microwave imagers from the operational Defense Meteorological Satellite Program [Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS)] form the "base" for structure observations due to their ability to view through upper-level clouds, modest size swaths and ability to capture most storm structure features. The NASA TRMM microwave imager and precipitation radar continue their 15+ yearlong missions in serving the TC warning and research communities. The cessation of NASA's QuikSCAT satellite after more than a decade of service is sorely missed, but India's OceanSat-2 scatterometer is now providing crucial ocean surface wind vectors in addition to the Navy's WindSat ocean surface wind vector retrievals. Another Advanced Scatterometer (ASCAT) onboard EUMETSAT's MetOp-2 satellite is slated for launch soon. Passive microwave imagery has received a much needed boost with the launch of the French/Indian Megha Tropiques imager in September 2011, basically greatly supplementing the very successful NASA TRMM pathfinder with a larger swath and more frequent temporal sampling. While initial data issues have delayed data utilization, current news indicates this data will be available in 2013. Future NASA Global Precipitation Mission (GPM) sensors starting in 2014 will provide enhanced capabilities. Also, the inclusion of the new microwave sounder data from the NPP ATMS (Oct 2011) will assist in mapping TC convective structures. The National Polar orbiting Partnership (NPP) program's VIIRS sensor includes a day night band (DNB) with the capability to view TC cloud structure at night when sufficient lunar illumination exits. Examples highlighting this new capability will be discussed in concert with additional data fusion efforts.

Comparative analysis of multisensor satellite monitoring of Arctic sea-ice

USGS Publications Warehouse

Belchansky, G.I.; Mordvintsev, Ilia N.; Douglas, David C.

1999-01-01

This report represents comparative analysis of nearly coincident Russian OKEAN-01 polar orbiting satellite data, Special Sensor Microwave Imager (SSM/I) and Advanced Very High Resolution Radiometer (AVHRR) imagery. OKEAN-01 ice concentration algorithms utilize active and passive microwave measurements and a linear mixture model for measured values of the brightness temperature and the radar backscatter. SSM/I and AVHRR ice concentrations were computed with NASA Team algorithm and visible and thermal-infrared wavelength AVHRR data, accordingly

The 4-8 GHz Microwave Active and Passive Spectrometer (MAPS). Volume 1: Radar section

NASA Technical Reports Server (NTRS)

Ulaby, F. T.

1973-01-01

The performance characteristics of the radar section of the prototype 4-8 GHz Microwave Active and Passive Spectrometer system are reported. Active and passive spectral responses were measured of natural, cultivated, and human-made surfaces over the 4-18 GHz region of frequencies for look angles between zero and 70 degrees and for all possible linear polarization combinations. Soil and plant samples were collected to measure their dielectric properties and moisture content. The FORTRAN program for area calculation is provided.

Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

NASA Astrophysics Data System (ADS)

Nobis, T. E.

2017-12-01

Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick; Johnson, Benjamin T.

2010-01-01

Physically-based passive microwave precipitation retrieval algorithms require a set of relationships between satellite observed brightness temperatures (TB) and the physical state of the underlying atmosphere and surface. These relationships are typically non-linear, such that inversions are ill-posed especially over variable land surfaces. In order to better understand these relationships, this work presents a theoretical analysis using brightness temperature weighting functions to quantify the percentage of the TB resulting from absorption/emission/reflection from the surface, absorption/emission/scattering by liquid and frozen hydrometeors in the cloud, the emission from atmospheric water vapor, and other contributors. The results are presented for frequencies from 10 to 874 GHz and for several individual precipitation profiles as well as for three cloud resolving model simulations of falling snow. As expected, low frequency channels (<89 GHz) respond to liquid hydrometeors and the surface, while the higher frequency channels become increasingly sensitive to ice hydrometeors and the water vapor sounding channels react to water vapor in the atmosphere. Low emissivity surfaces (water and snow-covered land) permit energy downwelling from clouds to be reflected at the surface thereby increasing the percentage of the TB resulting from the hydrometeors. The slant path at a 53deg viewing angle increases the hydrometeor contributions relative to nadir viewing channels and show sensitivity to surface polarization effects. The TB percentage information presented in this paper answers questions about the relative contributions to the brightness temperatures and provides a key piece of information required to develop and improve precipitation retrievals over land surfaces.

Assessing Applications of GPM and IMERG Passive Microwave Rain Rates in Modeling and Operational Forecasting

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Le Roy, A.; Smith, M. R.; Case, J.

2016-12-01

In support of NASA's recently launched GPM `core' satellite, the NASA-SPoRT project is leveraging experience in research-to-operations transitions and training to provide feedback on the operational utility of GPM products. Thus far, SPoRT has focused on evaluating the Level 2 GPROF passive microwave and IMERG rain rate estimates. Formal evaluations with end-users have occurred, as well as internal evaluations of the datasets. One set of end users for these products is National Weather Service Forecast Offices (WFOs) and National Weather Service River Forecast Centers (RFCs), comprising forecasters and hydrologists. SPoRT has hosted a series of formal assessments to determine uses and utility of these datasets for NWS operations at specific offices. Forecasters primarily have used Level 2 swath rain rates to observe rainfall in otherwise data-void regions and to confirm model QPF for their nowcasting or short-term forecasting. Hydrologists have been evaluating both the Level 2 rain rates and the IMERG rain rates, including rain rate accumulations derived from IMERG; hydrologists have used these data to supplement gauge data for post-event analysis as well as for longer-term forecasting. Results from specific evaluations will be presented. Another evaluation of the GPM passive microwave rain rates has been in using the data within other products that are currently transitioned to end-users, rather than as stand-alone observations. For example, IMERG Early data is being used as a forcing mechanism in the NASA Land Information System (LIS) for real-time soil moisture product over eastern Africa. IMERG is providing valuable precipitation information to LIS in an otherwise data-void region. Results and caveats will briefly be discussed. A third application of GPM data is using the IMERG Late and Final products for model verification in remote regions where high-quality gridded precipitation fields are not readily available. These datasets can now be used to verify NWP

A multifrequency evaluation of active and passive microwave sensors for oil spill detection and assessment

NASA Technical Reports Server (NTRS)

Fenner, R. G.; Reid, S. C.; Solie, C. H.

1980-01-01

An evaluation is given of how active and passive microwave sensors can best be used in oil spill detection and assessment. Radar backscatter curves taken over oil spills are presented and their effect on synthetic aperture radar (SAR) imagery are discussed. Plots of microwave radiometric brightness variations over oil spills are presented and discussed. Recommendations as to how to select the best combination of frequency, viewing angle, and sensor type for evaluation of various aspects of oil spills are also discussed.

Soil Moisture Active/Passive (SMAP) L-band microwave radiometer post-launch calibration

USDA-ARS?s Scientific Manuscript database

The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM / 6 PM sun-synchronous orbit at 685-km altitude. Since April 2015, the radiometer has been under calibration and validation to assess the quality of the radiometer L1B data product. Calibrat...

A passive microwave technique for estimating rainfall and vertical structure information from space. Part 1: Algorithm description

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Giglio, Louis

1994-01-01

This paper describes a multichannel physical approach for retrieving rainfall and vertical structure information from satellite-based passive microwave observations. The algorithm makes use of statistical inversion techniques based upon theoretically calculated relations between rainfall rates and brightness temperatures. Potential errors introduced into the theoretical calculations by the unknown vertical distribution of hydrometeors are overcome by explicity accounting for diverse hydrometeor profiles. This is accomplished by allowing for a number of different vertical distributions in the theoretical brightness temperature calculations and requiring consistency between the observed and calculated brightness temperatures. This paper will focus primarily on the theoretical aspects of the retrieval algorithm, which includes a procedure used to account for inhomogeneities of the rainfall within the satellite field of view as well as a detailed description of the algorithm as it is applied over both ocean and land surfaces. The residual error between observed and calculated brightness temperatures is found to be an important quantity in assessing the uniqueness of the solution. It is further found that the residual error is a meaningful quantity that can be used to derive expected accuracies from this retrieval technique. Examples comparing the retrieved results as well as the detailed analysis of the algorithm performance under various circumstances are the subject of a companion paper.

Assimilation of Feng-Yun-3B satellite microwave humidity sounder data over land

NASA Astrophysics Data System (ADS)

Chen, Keyi; Bormann, Niels; English, Stephen; Zhu, Jiang

2018-03-01

The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.

Determination of tropical cyclone surface pressure and winds from satellite microwave data

NASA Technical Reports Server (NTRS)

Kidder, S. Q.

1979-01-01

An approach to the problem of deducing wind speed and pressure around tropical cyclones is presented. The technique, called the Surface Wind Inference from Microwave data (SWIM technique, uses satellites microwave sounder data to measure upper tropospheric temperature anomalies which may then be related to surface pressure anomalies through the hydrostatic and radiative transfer equations. Surface pressure gradients outside of the radius of maximum wind are estimated for the first time. Future instruments may be able to estimate central pressure with + or - 0/1 kPa accuracy.

Estimating effective roughness parameters of the L-MEB model for soil moisture retrieval using passive microwave observations from SMAPVEX12

USDA-ARS?s Scientific Manuscript database

Although there have been efforts to improve existing soil moisture retrieval algorithms, the ability to estimate soil moisture from passive microwave observations is still hampered by problems in accurately modeling the observed microwave signal. This paper focuses on the estimation of effective sur...

Orbiting passive microwave sensor simulation applied to soil moisture estimation

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Clark, B. V.; Pitchford, W. M.; Paris, J. F.

1979-01-01

A sensor/scene simulation program was developed and used to determine the effects of scene heterogeneity, resolution, frequency, look angle, and surface and temperature relations on the performance of a spaceborne passive microwave system designed to estimate soil water information. The ground scene is based on classified LANDSAT images which provide realistic ground classes, as well as geometries. It was determined that the average sensitivity of antenna temperature to soil moisture improves as the antenna footprint size increased. Also, the precision (or variability) of the sensitivity changes as a function of resolution.

Estimating the time of melt onset and freeze onset over Arctic sea-ice area using active and passive microwave data

USGS Publications Warehouse

Belchansky, Gennady I.; Douglas, David C.; Mordvintsev, Ilia N.; Platonov, Nikita G.

2004-01-01

Accurate calculation of the time of melt onset, freeze onset, and melt duration over Arctic sea-ice area is crucial for climate and global change studies because it affects accuracy of surface energy balance estimates. This comparative study evaluates several methods used to estimate sea-ice melt and freeze onset dates: (1) the melt onset database derived from SSM/I passive microwave brightness temperatures (Tbs) using Drobot and Anderson's [J. Geophys. Res. 106 (2001) 24033] Advanced Horizontal Range Algorithm (AHRA) and distributed by the National Snow and Ice Data Center (NSIDC); (2) the International Arctic Buoy Program/Polar Exchange at the Sea (IABP/POLES) surface air temperatures (SATs); (3) an elaborated version of the AHRA that uses IABP/POLES to avoid anomalous results (Passive Microwave and Surface Temperature Analysis [PMSTA]); (4) another elaborated version of the AHRA that uses Tb variance to avoid anomalous results (Mean Differences and Standard Deviation Analysis [MDSDA]); (5) Smith's [J. Geophys. Res. 103 (1998) 27753] vertically polarized Tb algorithm for estimating melt onset in multiyear (MY) ice (SSM/I 19V–37V); and (6) analyses of concurrent backscattering cross section (σ°) and brightness temperature (Tb) from OKEAN-01 satellite series. Melt onset and freeze onset maps were created and compared to understand how the estimates vary between different satellite instruments and methods over different Arctic sea-ice regions. Comparisons were made to evaluate relative sensitivities among the methods to slight adjustments of the Tbcalibration coefficients and algorithm threshold values. Compared to the PMSTA method, the AHRA method tended to estimate significantly earlier melt dates, likely caused by the AHRA's susceptibility to prematurely identify melt onset conditions. In contrast, the IABP/POLES surface air temperature data tended to estimate later melt and earlier freeze in all but perennial ice. The MDSDA method was least sensitive to

Microwave emission measurements of sea surface roughness, soil moisture, and sea ice structure

NASA Technical Reports Server (NTRS)

Gloersen, P.; Wilheit, T. T.; Schmugge, T. J.

1972-01-01

In order to demonstrate the feasibility of the microwave radiometers to be carried aboard the Nimbus 5 and 6 satellites and proposed for one of the earth observatory satellites, remote measurements of microwave radiation at wavelengths ranging from 0.8 to 21 cm have been made of a variety of the earth's surfaces from the NASA CV-990 A/C. Brightness temperatures of sea water surfaces of varying roughness, of terrain with varying soil moisture, and of sea ice of varying structure were observed. In each case, around truth information was available for correlation with the microwave brightness temperature. The utility of passive microwave radiometry in determining ocean surface wind speeds, at least for values higher than 7 meters/second has been demonstrated. In addition, it was shown that radiometric signatures can be used to determine soil moisture in unvegetated terrain to within five percentage points by weight. Finally, it was demonstrated that first year thick, multi-year, and first year thin sea ice can be distinguished by observing their differing microwave emissivities at various wavelengths.

Satellite passive microwave remote sensing for estimating diurnal variation of leaf water content, as a proxy of evapotranspiration, in the Dry Chaco Forest, Argentina

NASA Astrophysics Data System (ADS)

Barraza Bernadas, V.; Grings, F.; Ferrazzoli, P.; Carbajo, A.; Fernandez, R.; Karszenbaum, H.

2012-12-01

Evapotranspiration (ET) is a key component of water cycle, which is strongly linked with environmental condition and vegetation functioning. Since it is very difficult to robustly estimate it from remote sensing data at regional scale it is usually inferred from other proxies using water balance. This work describes a procedure to estimate ET in a dry forest by monitoring diurnal variation of leaf water content (LWC), using multitemporal passive microwave remote sensing observations. Hourly observations provide the opportunity to monitor repetitive diurnal variations of passive microwave observations, which can only be accounted by changes in LWC (which is itself related to water vapor that enters to the atmosphere from land surface). To this end, we calculated the vegetation frequency index (FI) as FI= 2*(TBKa-TBX)/ ((TBKa +TBX)), where TBKa and TBX indicate brightness temperatures at 37 and 10.6 GHz respectively. There is both theoretical and experimental evidence that link this index to microwave to LWC. The index was computed for vertical polarization, because it presents higher correlation with vegetation state. At diurnal temporal scale, changes in LWC are commonly very small. Nevertheless, it was previously shown that passive remote sensing data (FI computed using Ku and Ka bands) acquired at different hours can be used to estimate the seasonal changes in ET. In this work, we present a procedure based on the hourly changes of FI, which are interpreted as changes in LWC. In order to present a quantitative estimation, the discrete forest model described in (Ferrazzoli and Guerriero, 1996) has been used to simulate the variations of FI with LWC. To illustrate the procedure, AMSR-E and WINDSAT data from 2007-2009 at X and Ka bands were used, and up to four observations per day at four different local times (2.30 am, 7.00 am, 2.30 pm and 7.00 pm) were analyzed. The region addressed is the area of the Dry Chaco forest located in Bermejo River Basin in Argentina

Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

NASA Astrophysics Data System (ADS)

Langlois, A.; Royer, A.; Derksen, C.; Montpetit, B.; Dupont, F.; GoïTa, K.

2012-12-01

Satellite-passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two-step iteration method compared to standalone simulations with the snow model.

Passive Microwave Remote Sensing of Colorado Watersheds Using Calibrated, Enhanced-Resolution Brightness Temperatures (CETB) from AMSR-E and SSM/I for Estimation of Snowmelt Timing

NASA Astrophysics Data System (ADS)

Johnson, M.; Ramage, J. M.; Troy, T. J.; Brodzik, M. J.

2017-12-01

Understanding the timing of snowmelt is critical for water resources management in snow-dominated watersheds. Passive microwave remote sensing has been used to estimate melt-refreeze events through brightness temperature satellite observations taken with sensors like the Special Sensor Microwave Imager (SSM/I) and the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). Previous studies were limited to lower resolution ( 25 km) datasets, making it difficult to quantify the snowpack in heterogeneous, high-relief areas. This study investigates the use of newly available passive microwave calibrated, enhanced-resolution brightness temperatures (CETB) produced at the National Snow and Ice Data Center to estimate melt timing at much higher spatial resolution ( 3-6 km). CETB datasets generated from SSM/I and AMSR-E records will be used to examine three mountainous basins in Colorado. The CETB datasets retain twice-daily (day/night) observations of brightness temperatures. Therefore, we employ the diurnal amplitude variation (DAV) method to detect melt onset and melt occurrences to determine if algorithms developed for legacy data are valid with the improved CETB dataset. We compare melt variability with nearby stream discharge records to determine an optimum melt onset algorithm using the newly reprocessed data. This study investigates the effectiveness of the CETB product for several locations in Colorado (North Park, Rabbit Ears, Fraser) that were the sites of previous ground/airborne surveys during the NASA Cold Land Processes Field Experiment (CLPX 2002-2003). In summary, this work lays the foundation for the utilization of higher resolution reprocessed CETB data for snow evolution more broadly in a range of environments. Consequently, the new processing methods and improved spatial resolution will enable hydrologists to better analyze trends in snow-dominated mountainous watersheds for more effective water resources management.

Signatures of Hydrometeor Species from Airborne Passive Microwave Data for Frequencies 10-183 GHz

NASA Technical Reports Server (NTRS)

Cecil, Daniel J.; Leppert, Kenneth, II

2014-01-01

There are 2 basic precipitation retrieval methods using passive microwave measurements: (1) Emission-based: Based on the tendency of liquid precipitation to cause an increase in brightness temperature (BT) primarily at frequencies below 22 GHz over a radiometrically cold background, often an ocean background (e.g., Spencer et al. 1989; Adler et al. 1991; McGaughey et al. 1996); and (2) Scattering-based: Based on the tendency of precipitation-sized ice to scatter upwelling radiation, thereby reducing the measured BT over a relatively warmer (usually land) background at frequencies generally 37 GHz (e.g., Spencer et al. 1989; Smith et al. 1992; Ferraro and Marks 1995). Passive microwave measurements have also been used to detect intense convection (e.g., Spencer and Santek 1985) and for the detection of hail (e.g., Cecil 2009; Cecil and Blankenship 2012; Ferraro et al. 2014). The Global Precipitation Measurement (GPM) mission expands upon the successful Tropical Rainfall Measurement Mission program to provide global rainfall and snowfall observations every 3 hours (Hou et al. 2014). One of the instruments on board the GPM Core Observatory is the GPM Microwave Imager (GMI) which is a conically-scanning microwave radiometer with 13 channels ranging from 10-183 GHz. Goal of this study: Determine the signatures of various hydrometeor species in terms of BTs measured at frequencies used by GMI by using data collected on 3 case days (all having intense/severe convection) during the Mid-latitude Continental Convective Clouds Experiment conducted over Oklahoma in 2011.

Computer-Aided Design of Low-Noise Microwave Circuits

NASA Astrophysics Data System (ADS)

Wedge, Scott William

1991-02-01

Devoid of most natural and manmade noise, microwave frequencies have detection sensitivities limited by internally generated receiver noise. Low-noise amplifiers are therefore critical components in radio astronomical antennas, communications links, radar systems, and even home satellite dishes. A general technique to accurately predict the noise performance of microwave circuits has been lacking. Current noise analysis methods have been limited to specific circuit topologies or neglect correlation, a strong effect in microwave devices. Presented here are generalized methods, developed for computer-aided design implementation, for the analysis of linear noisy microwave circuits comprised of arbitrarily interconnected components. Included are descriptions of efficient algorithms for the simultaneous analysis of noisy and deterministic circuit parameters based on a wave variable approach. The methods are therefore particularly suited to microwave and millimeter-wave circuits. Noise contributions from lossy passive components and active components with electronic noise are considered. Also presented is a new technique for the measurement of device noise characteristics that offers several advantages over current measurement methods.

Choice of antenna geometry for microwave power transmission from solar power satellites

NASA Technical Reports Server (NTRS)

Potter, Seth D.

1992-01-01

A comparison is made between square and circular transmitting antennas for solar power satellite microwave power transmission. It is seen that the exclusion zone around the rectenna needed to protect populations from microwaves is smaller for a circular antenna operating at 2.45 GHz than it is for a square antenna at that frequency. If the frequency is increased, the exclusion zone size remains the same for a square antenna, but becomes even smaller for a circular antenna. Peak beam intensity is the same for both antennas if the frequency and antenna area are equal. The circular antenna puts a somewhat greater amount of power in the main lobe and somewhat less in the side lobes. Since rain attenuation and atmospheric heating remain problems above 10 GHz, it is recommended that future solar power satellite work concentrate on circular transmitting antennas at frequencies of roughly 10 GHz.

Satellite Power System (SPS). State and local regulations as applied to satellite power system microwave receiving antenna facilities

NASA Technical Reports Server (NTRS)

Kotin, A. D.

1978-01-01

State and local regulation of power plant construction and operation of solar power satellite (SPS) receiving stations is presented. Each receiving antenna station occupies a land area 100-200 km square, receives microwave transmissions from the solar power satellite, and converts them into electricity for transmission to the power grid. The long lead time associated with the SPS and the changing status of state and local regulation dictated emphasis on: generic classification of the types of regulation, and identification of regulatory vectors which affect rectenna facilities.

Thin Sea-Ice Thickness as Inferred from Passive Microwave and In Situ Observations

NASA Technical Reports Server (NTRS)

Naoki, Kazuhiro; Ukita, Jinro; Nishio, Fumihiko; Nakayama, Masashige; Comiso, Josefino C.; Gasiewski, Al

2007-01-01

Since microwave radiometric signals from sea-ice strongly reflect physical conditions of a layer near the ice surface, a relationship of brightness temperature with thickness is possible especially during the early stages of ice growth. Sea ice is most saline during formation stage and as the salinity decreases with time while at the same time the thickness of the sea ice increases, a corresponding change in the dielectric properties and hence the brightness temperature may occur. This study examines the extent to which the relationships of thickness with brightness temperature (and with emissivity) hold for thin sea-ice, approximately less than 0.2 -0.3 m, using near concurrent measurements of sea-ice thickness in the Sea of Okhotsk from a ship and passive microwave brightness temperature data from an over-flying aircraft. The results show that the brightness temperature and emissivity increase with ice thickness for the frequency range of 10-37 GHz. The relationship is more pronounced at lower frequencies and at the horizontal polarization. We also established an empirical relationship between ice thickness and salinity in the layer near the ice surface from a field experiment, which qualitatively support the idea that changes in the near-surface brine characteristics contribute to the observed thickness-brightness temperature/emissivity relationship. Our results suggest that for thin ice, passive microwave radiometric signals contain, ice thickness information which can be utilized in polar process studies.

Characterization of errors in a coupled snow hydrology-microwave emission model

USGS Publications Warehouse

Andreadis, K.M.; Liang, D.; Tsang, L.; Lettenmaier, D.P.; Josberger, E.G.

2008-01-01

Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (GBMR), air-craft [Polarimetric Scanning Radiometer (PSR)], and satellite [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)] TB measurements. Limitations of the model at the point scale were not as evident when comparing areal estimates. The coupled model was able to reproduce the TB spatial patterns observed by PSR in two of three sites. However, this was mostly due to the presence of relatively dense forest cover. An interesting result occurs when examining the spatial scaling behavior of the higher-resolution errors; the satellite-scale error is well approximated by the mode of the (spatial) histogram of errors at the smaller scale. In addition, TB prediction errors were almost invariant when aggregated to the satellite scale, while forest-cover fractions greater than 30% had a significant effect on TB predictions. ?? 2008 American Meteorological Society.

Sea Ice Concentration Estimation Using Active and Passive Remote Sensing Data Fusion

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, F.; Zhang, S.; Zhu, T.

2017-12-01

In this abstract, a decision-level fusion method by utilizing SAR and passive microwave remote sensing data for sea ice concentration estimation is investigated. Sea ice concentration product from passive microwave concentration retrieval methods has large uncertainty within thin ice zone. Passive microwave data including SSM/I, AMSR-E, and AMSR-2 provide daily and long time series observations covering whole polar sea ice scene, and SAR images provide rich sea ice details with high spatial resolution including deformation and polarimetric features. In the proposed method, the merits from passive microwave data and SAR data are considered. Sea ice concentration products from ASI and sea ice category label derived from CRF framework in SAR imagery are calibrated under least distance protocol. For SAR imagery, incident angle and azimuth angle were used to correct backscattering values from slant range to ground range in order to improve geocoding accuracy. The posterior probability distribution between category label from SAR imagery and passive microwave sea ice concentration product is modeled and integrated under Bayesian network, where Gaussian statistical distribution from ASI sea ice concentration products serves as the prior term, which represented as an uncertainty of sea ice concentration. Empirical model based likelihood term is constructed under Bernoulli theory, which meets the non-negative and monotonically increasing conditions. In the posterior probability estimation procedure, final sea ice concentration is obtained using MAP criterion, which equals to minimize the cost function and it can be calculated with nonlinear iteration method. The proposed algorithm is tested on multiple satellite SAR data sets including GF-3, Sentinel-1A, RADARSAT-2 and Envisat ASAR. Results show that the proposed algorithm can improve the accuracy of ASI sea ice concentration products and reduce the uncertainty along the ice edge.

Satellite microwave and in situ observations of the Weddell Sea ice cover and its marginal ice zone

NASA Technical Reports Server (NTRS)

Comiso, J. C.; Sullivan, C. W.

1986-01-01

The radiative and physical characteristics of the Weddell Sea ice cover and its marginal ice zone are analyzed using multichannel satellite passive microwave data and ship and helicopter observations obtained during the 1983 Antarctic Marine Ecosystem Research. Winter and spring brightness temperatures are examined; spatial variability in the brightness temperatures of consolidated ice in winter and spring cyclic increases and decrease in brightness temperatures of consolidated ice with an amplitude of 50 K at 37 GHz and 20 K at 18 GHz are observed. The roles of variations in air temperature and surface characteristics in the variability of spring brightness temperatures are investigated. Ice concentrations are derived using the frequency and polarization techniques, and the data are compared with the helicopter and ship observations. Temporal changes in the ice margin structure and the mass balance of fresh water and of biological features of the marginal ice zone are studied.

HAMP - the microwave package on the High Altitude and LOng range research aircraft (HALO)

NASA Astrophysics Data System (ADS)

Mech, M.; Orlandi, E.; Crewell, S.; Ament, F.; Hirsch, L.; Hagen, M.; Peters, G.; Stevens, B.

2014-12-01

An advanced package of microwave remote sensing instrumentation has been developed for the operation on the new German High Altitude LOng range research aircraft (HALO). The HALO Microwave Package, HAMP, consists of two nadir-looking instruments: a cloud radar at 36 GHz and a suite of passive microwave radiometers with 26 frequencies in different bands between 22.24 and 183.31 ± 12.5 GHz. We present a description of HAMP's instrumentation together with an illustration of its potential. To demonstrate this potential, synthetic measurements for the implemented passive microwave frequencies and the cloud radar based on cloud-resolving and radiative transfer model calculations were performed. These illustrate the advantage of HAMP's chosen frequency coverage, which allows for improved detection of hydrometeors both via the emission and scattering of radiation. Regression algorithms compare HAMP retrieval with standard satellite instruments from polar orbiters and show its advantages particularly for the lower atmosphere with a root-mean-square error reduced by 5 and 15% for temperature and humidity, respectively. HAMP's main advantage is the high spatial resolution of about 1 km, which is illustrated by first measurements from test flights. Together these qualities make it an exciting tool for gaining a better understanding of cloud processes, testing retrieval algorithms, defining future satellite instrument specifications, and validating platforms after they have been placed in orbit.

HAMP - the microwave package on the High Altitude and LOng range research aircraft HALO

NASA Astrophysics Data System (ADS)

Mech, M.; Orlandi, E.; Crewell, S.; Ament, F.; Hirsch, L.; Hagen, M.; Peters, G.; Stevens, B.

2014-05-01

An advanced package of microwave remote sensing instrumentation has been developed for the operation on the new German High Altitude LOng range research aircraft (HALO). The HALO Microwave Package, HAMP, consists of two nadir looking instruments: a cloud radar at 36 GHz and a suite of passive microwave radiometers with 26 frequencies in different bands between 22.24 and 183.31 ± 12.5 GHz. We present a description of HAMP's instrumentation together with an illustration of its potential. To demonstrate this potential synthetic measurements for the implemented passive microwave frequencies and the cloud radar based on cloud resolving and radiative transfer model calculations were performed. These illustrate the advantage of HAMP's chosen frequency coverage, which allows for improved detection of hydrometeors both via the emission and scattering of radiation. Regression algorithms compare HAMP retrieval with standard satellite instruments from polar orbiters and show its advantages particularly for the lower atmosphere with a reduced root mean square error by 5 and 15% for temperature and humidity, respectively. HAMP's main advantage is the high spatial resolution of about 1 km which is illustrated by first measurements from test flights. Together these qualities make it an exciting tool for gaining better understanding of cloud processes, testing retrieval algorithms, defining future satellite instrument specifications, and validating platforms after they have been placed in orbit.

Estimating snow depth of alpine snowpack via airborne multifrequency passive microwave radiance observations: Colorado, USA

NASA Astrophysics Data System (ADS)

Kim, R. S.; Durand, M. T.; Li, D.; Baldo, E.; Margulis, S. A.; Dumont, M.; Morin, S.

2017-12-01

This paper presents a newly-proposed snow depth retrieval approach for mountainous deep snow using airborne multifrequency passive microwave (PM) radiance observation. In contrast to previous snow depth estimations using satellite PM radiance assimilation, the newly-proposed method utilized single flight observation and deployed the snow hydrologic models. This method is promising since the satellite-based retrieval methods have difficulties to estimate snow depth due to their coarse resolution and computational effort. Indeed, this approach consists of particle filter using combinations of multiple PM frequencies and multi-layer snow physical model (i.e., Crocus) to resolve melt-refreeze crusts. The method was performed over NASA Cold Land Processes Experiment (CLPX) area in Colorado during 2002 and 2003. Results showed that there was a significant improvement over the prior snow depth estimates and the capability to reduce the prior snow depth biases. When applying our snow depth retrieval algorithm using a combination of four PM frequencies (10.7,18.7, 37.0 and 89.0 GHz), the RMSE values were reduced by 48 % at the snow depth transects sites where forest density was less than 5% despite deep snow conditions. This method displayed a sensitivity to different combinations of frequencies, model stratigraphy (i.e. different number of layering scheme for snow physical model) and estimation methods (particle filter and Kalman filter). The prior RMSE values at the forest-covered areas were reduced by 37 - 42 % even in the presence of forest cover.

Aircraft active microwave measurements for estimating soil moisture

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Chang, A.; Schmugge, T. J.

1981-01-01

Both active and passive microwave sensors are sensitive to variations in near-surface soil moisture. The principal advantage of active microwave systems for soil moisture applications is that high spatial resolution can be retained even at satellite attitudes. The considered investigation is concerned with the use of active microwave scatterometers for estimating near-surface soil moisture. Microwave scatterometer data were obtained during a series of three aircraft flights over a group of Oklahoma research watersheds during May 1978. Data were obtained for the C, L, and P bands at angles of incidence between 5 and 50 degrees. The best results were obtained using C band data at incidence angles of 10 and 15 degrees and soil moisture depth of 0 to 15 cm. These results were in excellent agreement with the conclusions of the truck-mounted scatterometer measurement program reported by Ulaby et al. (1978, 1979).

A passive microwave snow depth algorithm with a proxy for snow metamorphism

USGS Publications Warehouse

Josberger, E.G.; Mognard, N.M.

2002-01-01

Passive microwave brightness temperatures of snowpacks depend not only on the snow depth, but also on the internal snowpack properties, particularly the grain size, which changes through the winter. Algorithms that assume a constant grain size can yield erroneous estimates of snow depth or water equivalent. For snowpacks that are subject to temperatures well below freezing, the bulk temperature gradient through the snowpack controls the metamorphosis of the snow grains. This study used National Weather Service (NWS) station measurements of snow depth and air temperature from the Northern US Great Plains to determine temporal and spatial variability of the snow depth and bulk snowpack temperature gradient. This region is well suited for this study because it consists primarily of open farmland or prairie, has little relief, is subject to very cold temperatures, and has more than 280 reporting stations. A geostatistical technique called Kriging was used to grid the randomly spaced snow depth measurements. The resulting snow depth maps were then compared with the passive microwave observations from the Special Sensor Microwave Imager (SSM/I). Two snow seasons were examined: 1988-89, a typical snow year, and 1996-97, a record year for snow that was responsible for extensive flooding in the Red River Basin. Inspection of the time series of snow depth and microwave spectral gradient (the difference between the 19 and 37 GHz bands) showed that while the snowpack was constant, the spectral gradient continued to increase. However, there was a strong correlation (0.6 < R2 < 0.9) between the spectral gradient and the cumulative bulk temperature gradient through the snowpack (TGI). Hence, TGI is an index of grain size metamorphism that has occurred within the snowpack. TGI time series from 21 representative sites across the region and the corresponding SSM/I observations were used to develop an algorithm for snow depth that requires daily air temperatures. Copyright ?? 2002

Combining Passive Microwave Rain Rate Retrieval with Visible and Infrared Cloud Classification.

NASA Astrophysics Data System (ADS)

Miller, Shawn William

The relation between cloud type and rain rate has been investigated here from different approaches. Previous studies and intercomparisons have indicated that no single passive microwave rain rate algorithm is an optimal choice for all types of precipitating systems. Motivated by the upcoming Tropical Rainfall Measuring Mission (TRMM), an algorithm which combines visible and infrared cloud classification with passive microwave rain rate estimation was developed and analyzed in a preliminary manner using data from the Tropical Ocean Global Atmosphere-Coupled Ocean Atmosphere Response Experiment (TOGA-COARE). Overall correlation with radar rain rate measurements across five case studies showed substantial improvement in the combined algorithm approach when compared to the use of any single microwave algorithm. An automated neural network cloud classifier for use over both land and ocean was independently developed and tested on Advanced Very High Resolution Radiometer (AVHRR) data. The global classifier achieved strict accuracy for 82% of the test samples, while a more localized version achieved strict accuracy for 89% of its own test set. These numbers provide hope for the eventual development of a global automated cloud classifier for use throughout the tropics and the temperate zones. The localized classifier was used in conjunction with gridded 15-minute averaged radar rain rates at 8km resolution produced from the current operational network of National Weather Service (NWS) radars, to investigate the relation between cloud type and rain rate over three regions of the continental United States and adjacent waters. The results indicate a substantially lower amount of available moisture in the Front Range of the Rocky Mountains than in the Midwest or in the eastern Gulf of Mexico.

Multifrequency passive microwave observations of soil moisture in an arid rangeland environment

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Schmugge, T. J.; Parry, R.; Kustas, W. P.; Ritchie, J. C.; Shutko, A. M.; Khaldin, A.; Reutov, E.; Novichikhin, E.; Liberman, B.

1992-01-01

A cooperative experiment was conducted by teams from the U.S. and U.S.S.R. to evaluate passive microwave instruments and algorithms used to estimate surface soil moisture. Experiments were conducted as part of an interdisciplinary experiment in an arid rangeland watershed located in the southwest United States. Soviet microwave radiometers operating at wavelengths of 2.25, 21 and 27 cm were flown on a U.S. aircraft. Radio frequency interference limited usable data to the 2.25 and 21 cm systems. Data have been calibrated and compared to ground observations of soil moisture. These analyses showed that the 21 cm system could produce reliable and useful soil moisture information and that the 2.25 cm system was of no value for soil moisture estimation in this experiment.

Results From the First 118 GHz Passive Microwave Observations Over Antarctica

NASA Astrophysics Data System (ADS)

McAllister, R.; Gallaher, D. W.; Gasiewski, A. J.; Periasamy, L.; Belter, R.; Hurowitz, M.; Hosack, W.; Sanders, B. T.

2017-12-01

Cooperation between the University of Colorado (Center for Environmental Technology, National Snow and Ice Data Center, and Colorado Space Grant Consortium) and the private corporation Orbital Micro Systems (OMS) has resulted in a highly miniturized passive microwave sensor. This sensor was successfully flown over Antarctica in onboard NASA's DC-8 in Operation Ice Bridge (OIB) in October / November of 2016. Data was collected from the "MiniRad" 8 channel miniaturized microwave sensor, which operated as both a sounder and an imager. The non-calibrated observation included both high and low altitude observations over clouds, sea, ice, ice sheets, and mountains as well as terrain around Tierra del Fuego. Sample results and their significance will be discussed. The instrument is in a form factor suitable for deployment in cubesats and will be launched into orbit next year. Commercial deployments by OMS in a constellation configuration will shortly follow.

Mapping Daily and Maximum Flood Extents at 90-m Resolution During Hurricanes Harvey and Irma Using Passive Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Galantowicz, J. F.; Picton, J.; Root, B.

2017-12-01

Passive microwave remote sensing can provided a distinct perspective on flood events by virtue of wide sensor fields of view, frequent observations from multiple satellites, and sensitivity through clouds and vegetation. During Hurricanes Harvey and Irma, we used AMSR2 (Advanced Microwave Scanning Radiometer 2, JAXA) data to map flood extents starting from the first post-storm rain-free sensor passes. Our standard flood mapping algorithm (FloodScan) derives flooded fraction from 22-km microwave data (AMSR2 or NASA's GMI) in near real time and downscales it to 90-m resolution using a database built from topography, hydrology, and Global Surface Water Explorer data and normalized to microwave data footprint shapes. During Harvey and Irma we tested experimental versions of the algorithm designed to map the maximum post-storm flood extent rapidly and made a variety of map products available immediately for use in storm monitoring and response. The maps have several unique features including spanning the entire storm-affected area and providing multiple post-storm updates as flood water shifted and receded. From the daily maps we derived secondary products such as flood duration, maximum flood extent (Figure 1), and flood depth. In this presentation, we describe flood extent evolution, maximum extent, and local details as detected by the FloodScan algorithm in the wake of Harvey and Irma. We compare FloodScan results to other available flood mapping resources, note observed shortcomings, and describe improvements made in response. We also discuss how best-estimate maps could be updated in near real time by merging FloodScan products and data from other remote sensing systems and hydrological models.

Satellite microwave observations of a storm complex: A comparative analysis

NASA Technical Reports Server (NTRS)

Martin, D. W.

1985-01-01

The hypothesis that cold events correspond to a particular stage in a class of thunderstorms was tested. That class is a storms class which updrafts are: (1) strong, broad and moist, and (2) extend well above the freezing level. Condition (1) implies strong mesoscale forcing. Condition (2) implies a tall updraft or a relatively low freezing level. Such storms should have big, intense radar echoes and cold, fast-growing anvils. The thunderstorm events were analyzed by radar, rain gauge and GOES infrared observations. Radar was the starting point for detection and definition of the hypothesized thunderstorms. The radar signature is compared to the signature of the storm in rain gauge observations, satellite infrared images and satellite microwave images.

Satellite Gravimetry Applied to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matthew

2010-01-01

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

Development of a modified two-scale electromagnetic model simulating both active and passive microwave measurements: Comparison to data remotely sensed over the ocean

NASA Astrophysics Data System (ADS)

Boukabara, S. A.; Eymard, L.; Guillou, C.; Lemaire, D.; Sobieski, P.; Guissard, A.

2002-08-01

Spaceborne microwave remote sensing allows the determination of oceanic and atmospheric parameters. Operational payloads such as ERS-1 and ERS-2 and TOPEX/Poseidon as well as missions such as Jason (from NASA-Centre National d'Etudes) or Envisat (from the European Space Agency), have contained or contain paired microwave instruments looking at the nadir direction. This combination consists of microwave radiometers and a radar-altimeter. For the frequencies chosen in oceanographic satellite payloads, the active mode signal is mostly dependent on the surface state through its reflectivity and thus used for the near-surface wind speed retrieval. The active mode can also be attenuated by the atmosphere. On the other hand, the passive mode is related to the surface emissivity and the atmospheric radiation through the radiative transfer equation. Until now, the oceanic and atmospheric parameters have been retrieved separately, the latter being used to correct radar measurements. However, the reflectivity and the emissivity of a target are not independent quantities; hence the synergistic use of these two kinds of microwave measurements should allow one to improve the retrieval quality of the sea and atmosphere parameters. For this purpose, a unified model has been developed for the simulation of both the microwave backscattering coefficient σ° (active measurement) and the microwave emissivity, an important factor for the brightness temperature TB simulation, for every configuration (incidence angles, frequency, polarizations), taking into account the fact that the reflectivity and the emissivity are complementary to unity. The atmospheric absorption is computed following a widely used model from the literature. This paper gives a description and a first attempt of validation of this approach through a comparison with real data. The performance of the model is assessed by comparing the simulations to both brightness temperatures and backscattering coefficients from ERS

Assimilation of active and passive microwave observations for improved estimates of soil moisture and crop growth

USDA-ARS?s Scientific Manuscript database

An Ensemble Kalman Filter-based data assimilation framework that links a crop growth model with active and passive (AP) microwave models was developed to improve estimates of soil moisture (SM) and vegetation biomass over a growing season of soybean. Complementarities in AP observations were incorpo...

Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

NASA Technical Reports Server (NTRS)

Winesett, Thomas; Magi, Brian; Cecil, Daniel

2015-01-01

Lightning observations are collected using ground-based and satellite-based sensors. The National Lightning Detection Network (NLDN) in the United States uses multiple ground sensors to triangulate the electromagnetic signals created when lightning strikes the Earth's surface. Satellite-based lightning observations have been made from 1998 to present using the Lightning Imaging Sensor (LIS) on the NASA Tropical Rainfall Measuring Mission (TRMM) satellite, and from 1995 to 2000 using the Optical Transient Detector (OTD) on the Microlab-1 satellite. Both LIS and OTD are staring imagers that detect lightning as momentary changes in an optical scene. Passive microwave remote sensing (85 and 37 GHz brightness temperatures) from the TRMM Microwave Imager (TMI) has also been used to quantify characteristics of thunderstorms related to lightning. Each lightning detection system has fundamental limitations. TRMM satellite coverage is limited to the tropics and subtropics between 38 deg N and 38 deg S, so lightning at the higher latitudes of the northern and southern hemispheres is not observed. The detection efficiency of NLDN sensors exceeds 95%, but the sensors are only located in the USA. Even if data from other ground-based lightning sensors (World Wide Lightning Location Network, the European Cooperation for Lightning Detection, and Canadian Lightning Detection Network) were combined with TRMM and NLDN, there would be enormous spatial gaps in present-day coverage of lightning. In addition, a globally-complete time history of observed lightning activity is currently not available either, with network coverage and detection efficiencies varying through the years. Previous research using the TRMM LIS and Microwave Imager (TMI) showed that there is a statistically significant correlation between lightning flash rates and passive microwave brightness temperatures. The physical basis for this correlation emerges because lightning in a thunderstorm occurs where ice is first

Low frequency microwave radiometer for N-ROSS

NASA Astrophysics Data System (ADS)

Hollinger, J. P.; Lo, R. C.

1984-01-01

The all weather, global determination of sea surface temperature (SST) has been identified as a requirement needed to support naval operations.The target SST accuracy is + or 1.0 K with a surface resolution of 10 km. Investigations of the phenomenology and technology of remote passive microwave sensing of the ocean environment over the past decade have demonstrated that this objective is presently attainable. Preliminary specification and trade off studies were conducted to define the frequency, polarization, scan geometry, antenna size, and other essential parameters of the low frequency microwave radiometer (LFMR). It will be a meter deployable mesh surface antenna. It is to be flown on the Navy-Remote Ocean Sensing System (N-ROSS) satellite scheduled to be launched in late 1988.

Relationship between passive microwave-derived snowmelt and surface-measured discharge, Wheaton River, Yukon Territory, Canada

NASA Astrophysics Data System (ADS)

Ramage, J. M.; McKenney, R. A.; Thorson, B.; Maltais, P.; Kopczynski, S. E.

2006-03-01

Snow volume and melt timing are major factors influencing the water cycle at northern high altitudes and latitudes, yet both are hard to quantify or monitor in remote mountainous regions. Twice-daily special sensor microwave imager (SSM/I) passive microwave observations of seasonal snow melt onset in the Wheaton River basin, Yukon Territory, Canada (60 ° 0805N, 134 ° 5345W), are used to test the idea that melt onset date and duration of snowpack melt-refreeze fluctuations control the timing of the early hydrograph peaks with predictable lags. This work uses the SSM/I satellite data from 1988 to 2002 to evaluate the chronology of melt and runoff patterns in the upper Yukon River basin. The Wheaton River is a small (875 km2) tributary to the Yukon, and is a subarctic, partly glacierized heterogeneous basin with near-continuous hydrographic records dating back to 1966. SSM/I pixels are sensitive to melt onset due to the strong increase in snow emissivity, and have a robust signal, in spite of coarse (>25 × 25 km2) pixel resolution and varied terrain. Results show that Wheaton River peak flows closely follow the end of large daily variations in brightness temperature of pixels covering the Wheaton River, but the magnitude of flow is highly variable, as might be expected from interannual snow mass variability. Spring rise in the hydrograph follows the end of high diurnal brightness temperature (Tb) amplitude variations (DAV) by 0 to 5 days approximately 90% of the time for this basin. Subsequent work will compare these findings for a larger (7250 km2), unglacierized tributary, the Ross River, which is farther northeast (61 ° 5940N, 132 ° 2240W) in the Yukon Territory. These techniques will also be used to try to determine the improvement in melt detection and runoff prediction from the higher resolution (15 × 15 km2) advanced microwave scanning radiometer for EOS (AMSR-E) sensor.

Towards better understanding of high-mountain cryosphere changes using GPM data: A Joint Snowfall and Snow-cover Passive Microwave Retrieval Algorithm

NASA Astrophysics Data System (ADS)

Ebtehaj, A.; Foufoula-Georgiou, E.

2016-12-01

Scientific evidence suggests that the duration and frequency of snowfall and the extent of snow cover are rapidly declining under global warming. Both precipitation and snow cover scatter the upwelling surface microwave emission and decrease the observed high-frequency brightness temperatures. The mixture of these two scattering signals is amongst the largest sources of ambiguities and errors in passive microwave retrievals of both precipitation and snow-cover. The dual frequency radar and the high-frequency radiometer on board the GPM satellite provide a unique opportunity to improve passive retrievals of precipitation and snow-cover physical properties and fill the gaps in our understating of their variability in view of climate change. Recently, a new Bayesian rainfall retrieval algorithm (called ShARP) was developed using modern approximation methods and shown to yield improvements against other algorithms in retrieval of rainfall over radiometrically complex land surfaces. However, ShARP uses a large database of input rainfall and output brightness temperatures, which might be undersampled. Furthermore, it is not capable to discriminate between solid and liquid phase of precipitation and specifically discriminate the background snow-cover emission and its contamination effects on the retrievals. We address these problems by extending it to a new Bayesian land-atmosphere retrieval framework (ShARP-L) that allows joint retrievals of atmospheric constituents and land surface physical properties. Using modern sparse approximation techniques, the database is reduced to atomic microwave signatures in a family of compact class consistent dictionaries. These dictionaries can efficiently represent the entire database and allow us to discriminate between different land-atmosphere states. First the algorithm makes use of the dictionaries to detect the phase of the precipitation and type of the land-cover and then it estimates the physical properties of precipitation and

Passive microwave remote sensing of an anisotropic random-medium layer

NASA Technical Reports Server (NTRS)

Lee, J. K.; Kong, J. A.

1985-01-01

The principle of reciprocity is invoked to calculate the brightness temperatures for passive microwave remote sensing of a two-layer anisotropic random medium. The bistatic scattering coefficients are first computed with the Born approximation and then integrated over the upper hemisphere to be subtracted from unity, in order to obtain the emissivity for the random-medium layer. The theoretical results are illustrated by plotting the emissivities as functions of viewing angles and polarizations. They are used to interpret remote sgnsing data obtained from vegetation canopy where the anisotropic random-medium model applies. Field measurements with corn stalks arranged in various configurations with preferred azimuthal directions are successfully interpreted with this model.

Usability and Interoperability Improvements for an EASE-Grid 2.0 Passive Microwave Data Product Using CF Conventions

NASA Astrophysics Data System (ADS)

Hardman, M.; Brodzik, M. J.; Long, D. G.

2017-12-01

Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Historical versions of the gridded passive microwave data sets were produced as flat binary files described in human-readable documentation. This format is error-prone and makes it difficult to reliably include all processing and provenance. Funded by NASA MEaSUREs, we have completely reprocessed the gridded data record that includes SMMR, SSM/I-SSMIS and AMSR-E. The new Calibrated Enhanced-Resolution Brightness Temperature (CETB) Earth System Data Record (ESDR) files are self-describing. Our approach to the new data set was to create netCDF4 files that use standard metadata conventions and best practices to incorporate file-level, machine- and human-readable contents, geolocation, processing and provenance metadata. We followed the flexible and adaptable Climate and Forecast (CF-1.6) Conventions with respect to their coordinate conventions and map projection parameters. Additionally, we made use of Attribute Conventions for Dataset Discovery (ACDD-1.3) that provided file-level conventions with spatio-temporal bounds that enable indexing software to search for coverage. Our CETB files also include temporal coverage and spatial resolution in the file-level metadata for human-readability. We made use of the JPL CF/ACDD Compliance Checker to guide this work. We tested our file format with real software, for example, netCDF Command-line Operators (NCO) power tools for unlimited control on spatio-temporal subsetting and concatenation of files. The GDAL tools understand the CF metadata and produce fully-compliant geotiff files from our data. ArcMap can then reproject the geotiff files on-the-fly and work

Status of the use of microwave power transmission technology in the solar power satellite

NASA Technical Reports Server (NTRS)

Brown, W. C.

1985-01-01

Attention is given to recent advances in the technologies needed to build and transport a Solar Power satellite. Among the areas of NASA sponsored SPS research are: the application of ground-based, electronically steerable arrays to the SPS space-based microwave transmitting antenna; and the application of microwave transmission technology to a low-cost LEO-to-GEO transportation system to build the SPS. A photograph of a thin-film etched circuit rectenna for powering the LEO-to-GEO transportation system is provided.

Ocean surveillance satellites

NASA Astrophysics Data System (ADS)

Laurent, D.

Soviet and U.S. programs involving satellites for surveillance of ships and submarines are discussed, considering differences in approaches. The Soviet program began with the Cosmos 198 in 1967 and the latest, the Cosmos 1400 series, 15 m long and weighing 5 tons, carry radar for monitoring ships and a nuclear reactor for a power supply. Other Soviet spacecraft carrying passive microwave sensors and ion drives powered by solar panels have recently been detonated in orbit for unknown reasons. It has also been observed that the Soviet satellites are controlled in pairs, with sequential orbital changes for one following the other, and both satellites then overflying the same points. In contrast, U.S. surveillance satellites have been placed in higher orbits, thus placing greater demands on the capabilities of the on-board radar and camera systems. Project White Cloud and the Clipper Bow program are described, noting the continued operation of the White Cloud spacecraft, which are equipped to intercept radio signals from surface ships. Currently, the integrated tactical surveillance system program has completed its study and a decision is expected soon.

The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for AMSU/MHS observations: description and application to European case studies

NASA Astrophysics Data System (ADS)

Sanò, P.; Panegrossi, G.; Casella, D.; Di Paola, F.; Milani, L.; Mugnai, A.; Petracca, M.; Dietrich, S.

2015-02-01

radiometers as they become available (such as the cross-track scanning Suomi National Polar-orbiting Partnership (NPP) Advanced Technology Microwave Sounder (ATMS)), and it is suitable for operational use as it is computationally very efficient. PNPR has been recently extended for applications to the regions of Africa and the South Atlantic, and an extended validation over these regions (using 2 yr of data acquired by the Tropical Rainfall Measuring Mission precipitation radar for comparison) is the subject of a paper in preparation. The PNPR is currently used operationally within the EUMETSAT Hydrology Satellite Application Facility (H-SAF) to provide instantaneous precipitation from passive microwave cross-track scanning radiometers. It undergoes routinely thorough extensive validation over Europe carried out by the H-SAF Precipitation Products Validation Team.

Nonlinear bias analysis and correction of microwave temperature sounder observations for FY-3C meteorological satellite

NASA Astrophysics Data System (ADS)

Hu, Taiyang; Lv, Rongchuan; Jin, Xu; Li, Hao; Chen, Wenxin

2018-01-01

The nonlinear bias analysis and correction of receiving channels in Chinese FY-3C meteorological satellite Microwave Temperature Sounder (MWTS) is a key technology of data assimilation for satellite radiance data. The thermal-vacuum chamber calibration data acquired from the MWTS can be analyzed to evaluate the instrument performance, including radiometric temperature sensitivity, channel nonlinearity and calibration accuracy. Especially, the nonlinearity parameters due to imperfect square-law detectors will be calculated from calibration data and further used to correct the nonlinear bias contributions of microwave receiving channels. Based upon the operational principles and thermalvacuum chamber calibration procedures of MWTS, this paper mainly focuses on the nonlinear bias analysis and correction methods for improving the calibration accuracy of the important instrument onboard FY-3C meteorological satellite, from the perspective of theoretical and experimental studies. Furthermore, a series of original results are presented to demonstrate the feasibility and significance of the methods.

Antarctic Sea Ice Thickness and Snow-to-Ice Conversion from Atmospheric Reanalysis and Passive Microwave Snow Depth

NASA Technical Reports Server (NTRS)

Markus, Thorsten; Maksym, Ted

2007-01-01

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.

Advances in Satellite Microwave Precipitation Retrieval Algorithms Over Land

NASA Astrophysics Data System (ADS)

Wang, N. Y.; You, Y.; Ferraro, R. R.

2015-12-01

Precipitation plays a key role in the earth's climate system, particularly in the aspect of its water and energy balance. Satellite microwave (MW) observations of precipitation provide a viable mean to achieve global measurement of precipitation with sufficient sampling density and accuracy. However, accurate precipitation information over land from satellite MW is a challenging problem. The Goddard Profiling Algorithm (GPROF) algorithm for the Global Precipitation Measurement (GPM) is built around the Bayesian formulation (Evans et al., 1995; Kummerow et al., 1996). GPROF uses the likelihood function and the prior probability distribution function to calculate the expected value of precipitation rate, given the observed brightness temperatures. It is particularly convenient to draw samples from a prior PDF from a predefined database of observations or models. GPROF algorithm does not search all database entries but only the subset thought to correspond to the actual observation. The GPM GPROF V1 database focuses on stratification by surface emissivity class, land surface temperature and total precipitable water. However, there is much uncertainty as to what is the optimal information needed to subset the database for different conditions. To this end, we conduct a database stratification study of using National Mosaic and Multi-Sensor Quantitative Precipitation Estimation, Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Technology Microwave Sounder (ATMS) and reanalysis data from Modern-Era Retrospective Analysis for Research and Applications (MERRA). Our database study (You et al., 2015) shows that environmental factors such as surface elevation, relative humidity, and storm vertical structure and height, and ice thickness can help in stratifying a single large database to smaller and more homogeneous subsets, in which the surface condition and precipitation vertical profiles are similar. It is found that the probability of detection (POD) increases

A microwave systems approach to measuring root zone soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W.; Paris, J. F.; Clark, B. V.

1983-01-01

Computer microwave satellite simulation models were developed and the program was used to test the ability of a coarse resolution passive microwave sensor to measure soil moisture over large areas, and to evaluate the effect of heterogeneous ground covers with the resolution cell on the accuracy of the soil moisture estimate. The use of realistic scenes containing only 10% to 15% bare soil and significant vegetation made it possible to observe a 60% K decrease in brightness temperature from a 5% soil moisture to a 35% soil moisture at a 21 cm microwave wavelength, providing a 1.5 K to 2 K per percent soil moisture sensitivity to soil moisture. It was shown that resolution does not affect the basic ability to measure soil moisture with a microwave radiometer system. Experimental microwave and ground field data were acquired for developing and testing a root zone soil moisture prediction algorithm. The experimental measurements demonstrated that the depth of penetration at a 21 cm microwave wavelength is not greater than 5 cm.

Feasibility of detecting aircraft wake vortices using passive microwave radiometers

NASA Technical Reports Server (NTRS)

Harrington, Richard F.

1993-01-01

The feasibility of detecting the cold core of the wake vortex from the wingtips of an aircraft using a passive microwave radiometer was investigated. It was determined that there is a possibility that a cold core whose physical temperature drop is 10 C or greater and which has a diameter of 5 m or greater can be detected by a microwave radiometer. The radiometer would be a noise injection balanced Dicke radiometer operating at a center frequency of 60 GHz. It would require a noise figure of 5 dB, a predetection bandwidth of 6 GHz, and an integration time of 2 seconds resulting in a radiometric sensitivity of 0.018 K. However, three additional studies are required. The first would determine what are the fluctuations in the radiometric antenna temperature due to short-term fluctuations in atmospheric pressure, temperature, and relative humidity. Second, what is the effect of the pressure and temperature drop within the cold core of the wake vortex on its opacity. The third area concerns the possibility of developing a 60 GHz radiometer with a radio metric sensitivity an order of magnitude improvement over the existing state of the art.

Passive microwave characteristics of the Bering Sea ice cover during Marginal Ice Zone Experiment (MIZEX) West

NASA Technical Reports Server (NTRS)

Cavalieri, D. J.; Gloersen, P.; Wilheit, T. T.; Calhoon, C.

1984-01-01

Passive microwave measurements of the Bering Sea were made with the NASA CV-990 airborne laboratory during February. Microwave data were obtained with imaging and dual-polarized, fixed-beam radiometers in a range of frequencies from 10 to 183 GHz. The high resolution imagery at 92 GHz provides a particularly good description of the marginal ice zone delineating regions of open water, ice compactness, and ice-edge structure. Analysis of the fixed-beam data shows that spectral differences increase with a decrease in ice thickness. Polarization at 18 and 37 GHz distinguishes among new, young, and first-year sea ice types.

Microwave system performance for a solar power satellite during startup/shutdown operations

NASA Technical Reports Server (NTRS)

Arndt, G. D.; Berlin, L. A.

1979-01-01

The paper investigates the system performance and antenna characteristics under startup/shutdown conditions for the high power beam from a solar power satellite. Attention is given to the present microwave system reference configuration together with the dc power distribution system in the solar array and in the antenna. The pattern characteristics for the main beam, sidelobes, and grating lobes are examined for eight types of energizing configurations which include: random sequences, two types of concentric circles, and three types of line strips. In conclusion, it is noted that a proper choice of sequences should not cause environmental problems due to increased microwave radiation levels during the short time periods of energizing and de-energizing the antenna.

Soil moisture extremes drive tree canopy death in 2011 Texas drought: multispectral (Landsat, NAIP) and L-band passive microwave remote sensing (SMOS-IC)

NASA Astrophysics Data System (ADS)

Swenson, J. J.; Schwantes, A. M.; Johnson, D. M.; Domec, J. C.; Wigneron, J. P.

2017-12-01

Climate change is bringing more frequent and intense droughts that are causing broad scale tree mortality events. Detecting regional drought stress is now more frequently monitored with passive microwave satellite sensing of soil moisture (SM) and vegetation water status (through the vegetation optical depth (VOD) index), that can be validated with in-situ measurements of soil moisture or corroborated with satellite multispectral indices of greenness. The detection of canopy death however marks the passing of a definitive physiological threshold. We compare soil moisture from the L-band SMOS-IC passive microwave product (2010-20176) to an accurate and detailed (30-m spatial resolution) map of canopy loss across the US state of Texas during the record breaking 2011 drought. The SMOS-IC product (25 km) is a new and simpler product of soil moisture and VOD that has been shown to be more accurate than past SMOS products and it is independent of ancillary data. Canopy loss was mapped from Landsat imagery trained with 186, 41 km2 subplots of classified National Agriculture Inventory Program color infrared aerial imagery recorded before and after the drought. Bringing these two datasets of disparate spatial resolution together and averaging them across the state, we find that areas with at least 25% tree cover that experienced the most canopy loss (highest quartile) had lower soil moisture compared to areas with less canopy loss in 2011. These areas with the most loss, experienced up to 9 weeks of the growing season at < 0.05 SM (m3/m3), while the rest of Texas forests, experienced just 1 week at that SM. The following years, 2012 - 2016, dropped below 0.05 SM very rarely (two weeks each in 2012 and 2015, and never for 2013, 2014, 2016). Forests during the drought of 2011 experienced the absolute lowest SM (0.031) and had the earliest onset of low SM across the 6 years analyzed. Analyzing areas of drought induced canopy loss with SM preceding and during drought across a

Performance analysis of rain attenuation on earth-to-satellite microwave links design in Libya

NASA Astrophysics Data System (ADS)

Rafiqul Islam, Md; Hussein Budalal, Asma Ali; Habaebi, Mohamed H.; Badron, Khairayu; Fadzil Ismail, Ahmad

2017-11-01

Performances of earth-to-satellite microwave links operating in Ku, Ka, and V-bands are degraded by the environment and strongly attenuated by rain. Rain attenuation is the most significant consideration and challenge to design a reliable earth-to-satellite microwave links for these frequency bands. Hence, it is essential for satellite link designer to take into account rain fade margin accurately before system implementation. Rain rate is the main measured parameter to predict of rain attenuation. Rainfall statistical data measured and recorded in Libya for the period of 30 years are collected from 5 locations. The prediction methods require one minute integration time rain intensity. Therefore, collected data were analyzed and processed to convert into one-minute rain rate cumulative distribution in Libya. The model proposed by ITU-R is used to predict and investigate rain fade based on converted 1-minute rain rate data. Rain fade predicted at two locations are used for performance analysis in terms of link spectral efficiency and throughput. V-band downlink shows that 99.99% availability is possible in all the Southern part stations in Libya at 0.29 bps/Hz spectral efficiency and 20.74 Mbps throughput when 72 MHz transponder band width is used which is not feasible in Northern part. Results of this paper will be a very useful resource to design highly reliable earth-to-satellite communication links in Libya.

ENSO Precipitation Variations as Seen by GPM and TRMM Radar and Passive Microwave Observations

NASA Astrophysics Data System (ADS)

Adler, R. F.; Wang, J. J.

2017-12-01

Tropical precipitation variations related to ENSO are the largest-scale such variations both spatially and in magnitude and are also the main driver of surface temperature-surface rainfall relationships on the inter-annual scale. GPM (and TRMM before it) provide a unique capability to examine these relations with both the passive and active microwave approaches. Documenting the phase and magnitudes of these relationships are important to understand these large-scale processes and to validate climate models. However, as past research by the authors have shown, the results of these relations have been different for passive vs. radar retrievals. In this study we re-examine these relations with the new GPM Version 5 products, focusing on the 2015-2016 El Nino event. The recent El Nino peaked in Dec. 2015 through Feb. 2016 with the usual patterns of precipitation anomalies across the Tropics as evident in both the GPM GMI and the Near Surface (NS) DPR (single frequency) retrievals. Integrating both the rainfall anomalies and the SST anomalies over the entire tropical ocean area (25N-25S) and comparing how they vary as a function of time on a monthly scale during the GPM era (2014-2017), the radar-based results show contrasting results to those from the GMI-based (and GPCP) results. The passive microwave data (GMI and GPCP) indicates a slope of 17%/C for the precipitation variations, while the radar NS indicates about half that ( 8%/C). This NS slope is somewhat less than calculated before with GPM's V4 data, but is larger than obtained with TRMM PR data ( 0%/C) for an earlier period during the TRMM era. Very similar results as to the DPR NS calculations are also obtained for rainfall at 2km and 4km altitude and for the Combined (DPR + GMI) product. However, at 6km altitude, although the reflectivity and rainfall magnitudes are much less than at lower altitudes, the slope of the rainfall/SST relation is 17%/C, the same as calculated with the passive microwave data. The

Empirical retrieval of sea spray aerosol production using satellite microwave radiometry

NASA Astrophysics Data System (ADS)

Savelyev, I. B.; Yelland, M. J.; Norris, S. J.; Salisbury, D.; Pascal, R. W.; Bettenhausen, M. H.; Prytherch, J.; Anguelova, M. D.; Brooks, I. M.

2017-12-01

This study presents a novel approach to obtaining global sea spray aerosol (SSA) production source term by relying on direct satellite observations of the ocean surface, instead of more traditional approaches driven by surface meteorology. The primary challenge in developing this empirical algorithm is to compile a calibrated, consistent dataset of SSA surface flux collected offshore over a variety of conditions (i.e., regions and seasons), thus representative of the global SSA production variability. Such dataset includes observations from SEASAW, HiWASE, and WAGES field campaigns, during which the SSA flux was measured from the bow of a research vessel using consistent and state-of-the-art eddy covariance methodology. These in situ data are matched to observations of the state of the ocean surface from Windsat polarimetric microwave satellite radiometer. Previous studies demonstrated the ability of WindSat to detect variations in surface waves slopes, roughness and foam, which led to the development of retrieval algorithms for surface wind vector and more recently whitecap fraction. Similarly, in this study, microwave emissions from the ocean surface are matched to and calibrated against in situ observations of the SSA production flux. The resulting calibrated empirical algorithm is applicable for retrieval of SSA source term throughout the duration of Windsat mission, from 2003 to present.

Fusion of radar and satellite target measurements

NASA Astrophysics Data System (ADS)

Moy, Gabriel; Blaty, Donald; Farber, Morton; Nealy, Carlton

2011-06-01

A potentially high payoff for the ballistic missile defense system (BMDS) is the ability to fuse the information gathered by various sensor systems. In particular, it may be valuable in the future to fuse measurements made using ground based radars with passive measurements obtained from satellite-based EO/IR sensors. This task can be challenging in a multitarget environment in view of the widely differing resolution between active ground-based radar and an observation made by a sensor at long range from a satellite platform. Additionally, each sensor system could have a residual pointing bias which has not been calibrated out. The problem is further compounded by the possibility that an EO/IR sensor may not see exactly the same set of targets as a microwave radar. In order to better understand the problems involved in performing the fusion of metric information from EO/IR satellite measurements with active microwave radar measurements, we have undertaken a study of this data fusion issue and of the associated data processing techniques. To carry out this analysis, we have made use of high fidelity simulations to model the radar observations from a missile target and the observations of the same simulated target, as gathered by a constellation of satellites. In the paper, we discuss the improvements seen in our tests when fusing the state vectors, along with the improvements in sensor bias estimation. The limitations in performance due to the differing phenomenology between IR and microwave radar are discussed as well.

Passive microwave derived snowmelt timing: significance, spatial and temporal variability, and potential applications

NASA Astrophysics Data System (ADS)

Semmens, Kathryn Alese

Snow accumulation and melt are dynamic features of the cryosphere indicative of a changing climate. Spring melt and refreeze timing are of particular importance due to the influence on subsequent hydrological and ecological processes, including peak runoff and green-up. To investigate the spatial and temporal variability of melt timing across a sub-arctic region (the Yukon River Basin (YRB), Alaska/Canada) dominated by snow and lacking substantial ground instrumentation, passive microwave remote sensing was utilized to provide daily brightness temperatures (Tb) regardless of clouds and darkness. Algorithms to derive the timing of melt onset and the end of melt-refreeze, a critical transition period where the snowpack melts during the day and refreezes at night, were based on thresholds for Tb and diurnal amplitude variations (day and night difference). Tb data from the Special Sensor Microwave Imager (1988 to 2011) was used for analyzing YRB terrestrial snowmelt timing and for characterizing melt regime patterns for icefields in Alaska and Patagonia. Tb data from the Advanced Microwave Scanning Radiometer for EOS (2003 to 2010) was used for determining the occurrence of early melt events (before melt onset) associated with fog or rain on snow, for investigating the correlation between melt timing and forest fires, and for driving a flux-based snowmelt runoff model. From the SSM/I analysis: the melt-refreeze period lengthened for the majority of the YRB with later end of melt-refreeze and earlier melt onset; and positive Tb anomalies were found in recent years from glacier melt dynamics. From the AMSR-E analysis: early melt events throughout the YRB were most often associated with warm air intrusions and reflect a consistent spatial distribution; years and areas of earlier melt onset and refreeze had more forest fire occurrences suggesting melt timing's effects extend to later seasons; and satellite derived melt timing served as an effective input for model

Impact of Uncertainty in the Drop Size Distribution on Oceanic Rainfall Retrievals From Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Wilheit, Thomas T.; Chandrasekar, V.; Li, Wanyu

2007-01-01

The variability of the drop size distribution (DSD) is one of the factors that must be considered in understanding the uncertainties in the retrieval of oceanic precipitation from passive microwave observations. Here, we have used observations from the Precipitation Radar on the Tropical Rainfall Measuring Mission spacecraft to infer the relationship between the DSD and the rain rate and the variability in this relationship. The impact on passive microwave rain rate retrievals varies with the frequency and rain rate. The total uncertainty for a given pixel can be slightly larger than 10% at the low end (ca. 10 GHz) of frequencies commonly used for this purpose and smaller at higher frequencies (up to 37 GHz). Since the error is not totally random, averaging many pixels, as in a monthly rainfall total, should roughly halve this uncertainty. The uncertainty may be lower at rain rates less than about 30 mm/h, but the lack of sensitivity of the surface reference technique to low rain rates makes it impossible to tell from the present data set.

The Satellite Test Unit (STU), part of the Passive Aerodynamically Stabilized Magnetically Damped

NASA Technical Reports Server (NTRS)

1996-01-01

STS-77 ESC VIEW --- The Satellite Test Unit (STU), part of the Passive Aerodynamically Stabilized Magnetically Damped Satellite (PAMS) is seen moments after its ejection from the cargo bay of the Space Shuttle Endeavour. The scene was photographed with an Electronic Still Camera (ESC) onboard Endeavour's crew cabin during the deployment. The six-member crew will continue operations (tracking, rendezvousing and station-keeping) with PAMS-STU periodically throughout the remainder of the mission. GMT: 03:29:31.

The Satellite Test Unit (STU), part of the Passive Aerodynamically Stabilized Magnetically Damped

NASA Technical Reports Server (NTRS)

1996-01-01

STS-77 ESC VIEW --- The Satellite Test Unit (STU), part of the Passive Aerodynamically Stabilized Magnetically Damped Satellite (PAMS) is seen moments after its ejection from the cargo bay of the Space Shuttle Endeavour. The scene was photographed with an Electronic Still Camera (ESC) onboard Endeavour's crew cabin during the deployment. The six-member crew will continue operations (tracking, rendezvousing and station-keeping) with PAMS-STU periodically throughout the remainder of the mission. GMT: 03:29:43.

The Satellite Test Unit (STU), part of the Passive Aerodynamically Stabilized Magnetically Damped

NASA Technical Reports Server (NTRS)

1996-01-01

STS-77 ESC VIEW --- The Satellite Test Unit (STU), part of the Passive Aerodynamically Stabilized Magnetically Damped Satellite (PAMS) is seen moments after its ejection from the cargo bay of the Space Shuttle Endeavour. The scene was photographed with an Electronic Still Camera (ESC) onboard Endeavour's crew cabin during the deployment. The six-member crew will continue operations (tracking, rendezvousing and station-keeping) with PAMS-STU periodically throughout the remainder of the mission. GMT: 03:29:29.

International Network of Passive Correlation Ranging for Orbit Determination of a Geostationary Satellite

NASA Astrophysics Data System (ADS)

Kaliuzhnyi, Mykola; Bushuev, Felix; Shulga, Oleksandr; Sybiryakova, Yevgeniya; Shakun, Leonid; Bezrukovs, Vladislavs; Moskalenko, Sergiy; Kulishenko, Vladislav; Malynovskyi, Yevgen

2016-12-01

An international network of passive correlation ranging of a geostationary telecommunication satellite is considered in the article. The network is developed by the RI "MAO". The network consists of five spatially separated stations of synchronized reception of DVB-S signals of digital satellite TV. The stations are located in Ukraine and Latvia. The time difference of arrival (TDOA) on the network stations of the DVB-S signals, radiated by the satellite, is a measured parameter. The results of TDOA estimation obtained by the network in May-August 2016 are presented in the article. Orbital parameters of the tracked satellite are determined using measured values of the TDOA and two models of satellite motion: the analytical model SGP4/SDP4 and the model of numerical integration of the equations of satellite motion. Both models are realized using the free low-level space dynamics library OREKIT (ORbit Extrapolation KIT).

Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent in Afghanistan's Hindu Kush

NASA Astrophysics Data System (ADS)

Dozier, J.; Bair, N.; Calfa, A. A.; Skalka, C.; Tolle, K.; Bongard, J.

2015-12-01

The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements such as the Hindu Kush range in Afghanistan. During the snow season, we can use two measurements: (1) passive microwave estimates of SWE, which generally underestimate in the mountains; (2) fractional snow-covered area from MODIS. Once the snow has melted, we can reconstruct the accumulated SWE back to the last significant snowfall by calculating the energy used in melt. The reconstructed SWE values provide a training set for predictions from the passive microwave SWE and snow-covered area. We examine several machine learning methods—regression-boosted decision trees, bagged trees, neural networks, and genetic programming—to estimate SWE. All methods work reasonably well, with R2 values greater than 0.8. Predictors built with multiple years of data reduce the bias that usually appears if we predict one year from just one other year's training set. Genetic programming tends to produce results that additionally provide physical insight. Adding precipitation estimates from the Global Precipitation Measurements mission is in progress.

Environmental assessment for the satellite power system-concept development and evaluation program-microwave health and ecological effects

NASA Technical Reports Server (NTRS)

1980-01-01

Potential health and ecological effects of the microwave beam from the microwave power transmission system (MPTS) of the satellite power system (SPS) are discussed. A detailed critical review of selected scientific articles from the published literature on the biological effects of nonionizing electromagnetic radiation is provided followed by an assessment of the possible effects of the SPS, based on exposure values for the reference system.

Microwave signatures of ice hydrometeors from ground-based observations above Summit, Greenland

DOE PAGES

Pettersen, Claire; Bennartz, Ralf; Kulie, Mark S.; ...

2016-04-15

Multi-instrument, ground-based measurements provide unique and comprehensive data sets of the atmosphere for a specific location over long periods of time and resulting data compliment past and existing global satellite observations. Our paper explores the effect of ice hydrometeors on ground-based, high-frequency passive microwave measurements and attempts to isolate an ice signature for summer seasons at Summit, Greenland, from 2010 to 2013. Furthermore, data from a combination of passive microwave, cloud radar, radiosonde, and ceilometer were examined to isolate the ice signature at microwave wavelengths. By limiting the study to a cloud liquid water path of 40 g m -2more » or less, the cloud radar can identify cases where the precipitation was dominated by ice. These cases were examined using liquid water and gas microwave absorption models, and brightness temperatures were calculated for the high-frequency microwave channels: 90, 150, and 225GHz. By comparing the measured brightness temperatures from the microwave radiometers and the calculated brightness temperature using only gas and liquid contributions, any residual brightness temperature difference is due to emission and scattering of microwave radiation from the ice hydrometeors in the column. The ice signature in the 90, 150, and 225 GHz channels for the Summit Station summer months was isolated. Then, this measured ice signature was compared to an equivalent brightness temperature difference calculated with a radiative transfer model including microwave single-scattering properties for several ice habits. Furthermore, initial model results compare well against the 4 years of summer season isolated ice signature in the high-frequency microwave channels.« less

Error sources in passive and active microwave satellite soil moisture over Australia

USDA-ARS?s Scientific Manuscript database

Development of a long-term climate record of soil moisture (SM) involves combining historic and present satellite-retrieved SM data sets. This in turn requires a consistent characterization and deep understanding of the systematic differences and errors in the individual data sets, which vary due to...

Volcanic eruption source parameters from active and passive microwave sensors

NASA Astrophysics Data System (ADS)

Montopoli, Mario; Marzano, Frank S.; Cimini, Domenico; Mereu, Luigi

2016-04-01

appealing for estimates close to the volcano emission source. Near the source the cloud optical thickness is expected to be large enough to induce saturation effects at the infrared sensor receiver thus vanishing the brightness temperature difference methods for the ash cloud identification. In the light of the introduction above, some case studies at Eyjafjallajökull 2010 (Iceland), Etna (Italy) and Calbuco (Cile), on 5-10 May 2010, 23rd Nov., 2013 and 23 Apr., 2015, respectively, are analysed in terms of source parameter estimates (manly the cloud top and mass flax rate) from ground based microwave weather radar (9.6 GHz) and satellite Low Earth Orbit microwave radiometers (50 - 183 GH). A special highlight will be given to the advantages and limitations of microwave-related products with respect to more conventional tools.

Spatial and Temporal Variations of Surface Characteristics on the Greenland Ice Sheet as Derived from Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Anderson, Mark; Rowe, Clinton; Kuivinen, Karl; Mote, Thomas

1996-01-01

The primary goals of this research were to identify and begin to comprehend the spatial and temporal variations in surface characteristics of the Greenland ice sheet using passive microwave observations, physically-based models of the snowpack and field observations of snowpack and firn properties.

Passive correlation ranging of a geostationary satellite using DVB-S payload signals.

NASA Astrophysics Data System (ADS)

Shakun, Leonid; Shulga, Alexandr; Sybiryakova, Yevgeniya; Bushuev, Felix; Kaliuzhnyi, Mykola; Bezrukovs, Vladislavs; Moskalenko, Sergiy; Kulishenko, Vladislav; Balagura, Oleg

2016-07-01

Passive correlation ranging (PaCoRa) for geostationary satellites is now considered as an alternate to tone-ranging (https://artes.esa.int/search/node/PaCoRa). The PaCoRa method has been employed in the Research Institute "Nikolaev astronomical observatory" since the first experiment in August 2011 with two stations spatially separated on 150 km. The PaCoRa has been considered as an independent method for tracking the future Ukrainian geostationary satellite "Lybid'. Now a radio engineering complex (RC) for passive ranging consists of five spatially separated stations of receiving digital satellite television and a data processing center located in Mykolaiv. The stations are located in Kyiv, Kharkiv, Mukacheve, Mykolaiv (Ukraine) and in Ventspils (Latvia). Each station has identical equipment. The equipment allows making synchronous recording of fragments of the DVB-S signal from the quadrature detector output of a satellite television receiver. The fragments are recorded every second. Synchronization of the stations is performed using GPS receivers. Samples of the complex signal obtained in this way are archived and are sent to the data processing center over the Internet. Here the time differences of arrival (TDOA) for pairs of the stations are determined as a result of correlation processing of received signals. The values of the TDOA that measured every second are used for orbit determination (OD) of the satellite. The results of orbit determination of the geostationary telecommunication satellite "Eutelsat-13B" (13º East) obtained during about four months of observations in 2015 are presented in the report. The TDOA and OD accuracies are also given. Single-measurement error (1 sigma) of the TDOA is equal about 8.7 ns for all pairs of the stations. Standard deviations and average values of the residuals between the observed TDOA and the TDOA computed using the orbit elements obtained from optical measurements are estimated for the pairs Kharkiv-Mykolaiv and

Utilization of downscaled microwave satellite data and GRACE Total Water Storage anomalies for improving streamflow prediction in the Lower Mekong Basin

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Gupta, M.; Bolten, J. D.

2016-12-01

The Mekong river is the world's eighth largest in discharge with draining an area of 795,000 km² from the Eastern watershed of the Tibetan Plateau to the Mekong Delta including, Myanmar, Laos PDR, Thailand, Cambodia, Vietnam and three provinces of China. The populations in these countries are highly dependent on the Mekong River and they are vulnerable to the availability and quality of the water resources within the Mekong River Basin. Soil moisture is one of the most important hydrological cycle variables and is available from passive microwave satellite sensors (such as AMSR-E, SMOS and SMAP), but their spatial resolution is frequently too coarse for effective use by land managers and decision makers. The merging of satellite observations with numerical models has led to improved land surface predictions. Although performance of the models have been continuously improving, the laboratory methods for determining key hydraulic parameters are time consuming and expensive. The present study assesses a method to determine the effective soil hydraulic parameters using a downscaled microwave remote sensing soil moisture product based on the NASA Advanced Microwave Scanning Radiometer (AMSR-E). The soil moisture downscaling algorithm is based on a regression relationship between 1-km MODIS land surface temperature and 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) to produce an enhanced spatial resolution ASMR-E-based soil moisture product. Since the optimized parameters are based on the near surface soil moisture information, further constraints are applied during the numerical simulation through the assimilation of GRACE Total Water Storage (TWS) within the land surface model. This work improves the hydrological fluxes and the state variables are optimized and the optimal parameter values are then transferred for retrieving hydrological fluxes. To evaluate the performance of the system in helping improve

Calibration of passive remote observing optical and microwave instrumentation; Proceedings of the Meeting, Orlando, FL, Apr. 3-5, 1991

NASA Technical Reports Server (NTRS)

Guenther, Bruce W. (Editor)

1991-01-01

Various papers on the calibration of passive remote observing optical and microwave instrumentation are presented. Individual topics addressed include: on-board calibration device for a wide field-of-view instrument, calibration for the medium-resolution imaging spectrometer, cryogenic radiometers and intensity-stabilized lasers for EOS radiometric calibrations, radiometric stability of the Shuttle-borne solar backscatter ultraviolet spectrometer, ratioing radiometer for use with a solar diffuser, requirements of a solar diffuser and measurements of some candidate materials, reflectance stability analysis of Spectralon diffuse calibration panels, stray light effects on calibrations using a solar diffuser, radiometric calibration of SPOT 23 HRVs, surface and aerosol models for use in radiative transfer codes. Also addressed are: calibrated intercepts for solar radiometers used in remote sensor calibration, radiometric calibration of an airborne multispectral scanner, in-flight calibration of a helicopter-mounted Daedalus multispectral scanner, technique for improving the calibration of large-area sphere sources, remote colorimetry and its applications, spatial sampling errors for a satellite-borne scanning radiometer, calibration of EOS multispectral imaging sensors and solar irradiance variability.

Real-time new satellite product demonstration from microwave sensors and GOES-16 at NRL TC web

NASA Astrophysics Data System (ADS)

Cossuth, J.; Richardson, K.; Surratt, M. L.; Bankert, R.

2017-12-01

The Naval Research Laboratory (NRL) Tropical Cyclone (TC) satellite webpage (https://www.nrlmry.navy.mil/TC.html) provides demonstration analyses of storm imagery to benefit operational TC forecast centers around the world. With the availability of new spectral information provided by GOES-16 satellite data and recent research into improved visualization methods of microwave data, experimental imagery was operationally tested to visualize the structural changes of TCs during the 2017 hurricane season. This presentation provides an introduction into these innovative satellite analysis methods, NRL's next generation satellite analysis system (the Geolocated Information Processing System, GeoIPSTM), and demonstration the added value of additional spectral frequencies when monitoring storms in near-realtime.

Synergistic method for boreal soil moisture and soil freeze retrievals using active and passive microwave instruments

NASA Astrophysics Data System (ADS)

Smolander, Tuomo; Lemmetyinen, Juha; Rautiainen, Kimmo; Schwank, Mike; Pulliainen, Jouni

2017-04-01

Soil moisture and soil freezing are important for diverse hydrological, biogeochemical, and climatological applications. They affect surface energy balance, surface and subsurface water flow, and exchange rates of carbon with the atmosphere. Soil freezing controls important biogeochemical processes, like photosynthetic activity of plants and microbial activity within soils. Permafrost covers approximately 24% of the land surface in the Northern Hemisphere and seasonal freezing occurs on approximately 51% of the area. The retrieval method presented is based on an inversion technique and applies a semiempirical backscattering model that describes the dependence of radar backscattering of forest as a function of stem volume, soil permittivity, the extinction coefficient of forest canopy, surface roughness, incidence angle, and radar frequency. It gives an estimate of soil permittivity using active microwave measurements. Applying a Bayesian assimilation scheme, it is also possible to use other soil permittivity retrievals to regulate this estimate to combine for example low resolution passive observations with high resolution active observations for a synergistic retrieval. This way the higher variance in the active retrieval can be constricted with the passive retrieval when at the same time the spatial resolution of the product is improved compared to the passive-only retrieval. The retrieved soil permittivity estimate can be used to detect soil freeze/thaw state by considering the soil to be frozen when the estimate is below a threshold value. The permittivity retrieval can also be used to estimate the relative moisture of the soil. The method was tested using SAR (Synthetic Aperture Radar) measurements from ENVISAT ASAR instrument for the years 2010-2012 and from Sentinel-1 satellite for the years 2015-2016 in Sodankylä area in Northern Finland. The synergistic method was tested combining the SAR measurements with a SMOS (Soil Moisture Ocean Salinity) radiometer

Low-frequency microwave radiometer for N-ROSS

NASA Astrophysics Data System (ADS)

Hollinger, J. P.; Lo, R. C.

1985-04-01

The all weather, global determination of sea surface temperature (SST) has been identified as a requirement needed to support naval operations. The target SST accuracy is + or - 1.0 K with a surface resolution of 10 km. Investigations of the phenomenology and technology of remote passive microwave sensing of the ocean environment over the past decade have demonstrated that this objective is presently attainable. Preliminary specification and trade off studies were conducted to define the frequency, polarization, scan geometry, antenna size, and other esstential parameters of the low frequency microwave radiometer (LFMR). It will be a dual polarized, dual frequency system at 5.2 and 10.4 GHz using a 4.9 meter deployable mesh surface antenna. It is to be flown on the Navy-Remote Ocean Sensing System (N-ROSS) satellite scheduled to be launched in late 1988.

Low-frequency microwave radiometer for N-ROSS

NASA Technical Reports Server (NTRS)

Hollinger, J. P.; Lo, R. C.

1985-01-01

The all weather, global determination of sea surface temperature (SST) has been identified as a requirement needed to support naval operations. The target SST accuracy is + or - 1.0 K with a surface resolution of 10 km. Investigations of the phenomenology and technology of remote passive microwave sensing of the ocean environment over the past decade have demonstrated that this objective is presently attainable. Preliminary specification and trade off studies were conducted to define the frequency, polarization, scan geometry, antenna size, and other esstential parameters of the low frequency microwave radiometer (LFMR). It will be a dual polarized, dual frequency system at 5.2 and 10.4 GHz using a 4.9 meter deployable mesh surface antenna. It is to be flown on the Navy-Remote Ocean Sensing System (N-ROSS) satellite scheduled to be launched in late 1988.

A Prognostic Methodology for Precipitation Phase Detection using GPM Microwave Observations —With Focus on Snow Cover

NASA Astrophysics Data System (ADS)

Takbiri, Z.; Ebtehaj, A.; Foufoula-Georgiou, E.; Kirstetter, P.

2017-12-01

Improving satellite retrieval of precipitation requires increased understanding of its passive microwave signature over different land surfaces. Passive microwave signals over snow-covered surfaces are notoriously difficult to interpret because they record both emission from the land below and absorption/scattering from the liquid/ice crystals. Using data from the Global Precipitation Measurement (GPM) core satellite, we demonstrate that the microwave brightness temperatures of rain and snowfall shifts from a scattering to an emission regime from summer to winter, due to expansion of the less emissive snow cover underneath. We present evidence that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The study also examines a prognostic nearest neighbor matching method for the detection of precipitation and its phase from passive microwave observations using GPM data. The nearest neighbor uses the weighted Euclidean distance metric to search through an a priori database that is populated with coincident GPM radiometer and radar data as well as ancillary snow cover fraction. The results demonstrate prognostic capabilities of the proposed method in detection of terrestrial snowfall. At the global scale, the average probability of hit and false alarm reaches to 0.80 and remains below 0.10, respectively. Surprisingly, the results show that the snow cover may help to better detect precipitation as the detection rate of terrestrial precipitation is increased from 0.75 (no snow cover) to 0.84 (snow-covered surfaces). For solid precipitation, this increased rate of detection is larger than its liquid counterpart by almost 8%. The main reasons are found to be related to the multi-frequency capabilities of the nearest neighbor matching that can properly isolate the atmospheric signal from the background emission and the fact that the precipitation can exhibit an emission-like (warmer

NASA sea ice and snow validation plan for the Defense Meteorological Satellite Program special sensor microwave/imager

NASA Technical Reports Server (NTRS)

Cavalieri, Donald J. (Editor); Swift, Calvin T. (Editor)

1987-01-01

This document addresses the task of developing and executing a plan for validating the algorithm used for initial processing of sea ice data from the Special Sensor Microwave/Imager (SSMI). The document outlines a plan for monitoring the performance of the SSMI, for validating the derived sea ice parameters, and for providing quality data products before distribution to the research community. Because of recent advances in the application of passive microwave remote sensing to snow cover on land, the validation of snow algorithms is also addressed.

Classification of Active Microwave and Passive Optical Data Based on Bayesian Theory and Mrf

NASA Astrophysics Data System (ADS)

Yu, F.; Li, H. T.; Han, Y. S.; Gu, H. Y.

2012-08-01

A classifier based on Bayesian theory and Markov random field (MRF) is presented to classify the active microwave and passive optical remote sensing data, which have demonstrated their respective advantages in inversion of surface soil moisture content. In the method, the VV, VH polarization of ASAR and all the 7 TM bands are taken as the input of the classifier to get the class labels of each pixel of the images. And the model is validated for the necessities of integration of TM and ASAR, it shows that, the total precision of classification in this paper is 89.4%. Comparing with the classification with single TM, the accuracy increase 11.5%, illustrating that synthesis of active and passive optical remote sensing data is efficient and potential in classification.

Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

NASA Astrophysics Data System (ADS)

Crow, W. T.; Bolten, J. D.

2014-12-01

Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

Effects of weather on the retrieval of sea ice concentration and ice type from passive microwave data

NASA Technical Reports Server (NTRS)

Maslanik, J. A.

1992-01-01

Effects of wind, water vapor, and cloud liquid water on ice concentration and ice type calculated from passive microwave data are assessed through radiative transfer calculations and observations. These weather effects can cause overestimates in ice concentration and more substantial underestimates in multi-year ice percentage by decreasing polarization and by decreasing the gradient between frequencies. The effect of surface temperature and air temperature on the magnitudes of weather-related errors is small for ice concentration and substantial for multiyear ice percentage. The existing weather filter in the NASA Team Algorithm addresses only weather effects over open ocean; the additional use of local open-ocean tie points and an alternative weather correction for the marginal ice zone can further reduce errors due to weather. Ice concentrations calculated using 37 versus 18 GHz data show little difference in total ice covered area, but greater differences in intermediate concentration classes. Given the magnitude of weather-related errors in ice classification from passive microwave data, corrections for weather effects may be necessary to detect small trends in ice covered area and ice type for climate studies.

An intercomparison of available soil moisture estimates from thermal-infrared and passive microwave remote sensing and land-surface modeling

USDA-ARS?s Scientific Manuscript database

Remotely-sensed soil moisture studies have mainly focused on retrievals using active and passive microwave (MW) sensors whose measurements provided a direct relationship to soil moisture (SM). MW sensors present obvious advantages such as the ability to retrieve through non-precipitating cloud cover...

A comparative study of the SMAP passive soil moisture product with existing satellite-based soil moisture products

USDA-ARS?s Scientific Manuscript database

NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015 to provide global mapping of high-resolution soil moisture and freeze thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The radiometer-only soil moisture product (L2...

Non-military microwave applications

NASA Astrophysics Data System (ADS)

Bierman, Howard

1990-04-01

The nonmilitary applications of microwave technology in medicine, communications, and agriculture are discussed. Particular attention is given to a microwave multichannel multipoint video distribution system (a broadcasting system with up to 20 programs drawn from satellites, video tape libraries, and locally generated material); microwaves used in DBS distribution; satellite receivers for data communications; microwave thermography used for early cancer detection, brain temperature measurements, and appendicitis diagnosis; an experimental Doppler radar assembly for guiding robots walking on a factory floor; and an agricultural application where microwaves are used to break down slugs in soil and thus improve potato and grain crops. Schematic diagrams are included.

The microwave limb sounder for the Upper Atmosphere Research Satellite

NASA Technical Reports Server (NTRS)

Waters, J. W.; Peckham, G. E.; Suttie, R. A.; Curtis, P. D.; Maddison, B. J.; Harwood, R. S.

1988-01-01

The Microwave Limb Sounder was designed to map the concentrations of trace gases from the stratosphere to the lower thermosphere, to improve understanding of the photochemical reactions which take place in this part of the atmosphere. The instrument will measure the intensity of thermal radiation from molecules in the atmosphere at frequencies corresponding to rotational absorption bands of chlorine monoxide, ozone, and water vapor. Molecular concentration profiles will be determined over a height range of 15 to 80 km (20 to 45 km for C10). The 57 deg inclination orbit proposed for the Upper Atmosphere Research Satellite will allow global coverage.

Soil moisture retrieval by active/passive microwave remote sensing data

NASA Astrophysics Data System (ADS)

Wu, Shengli; Yang, Lijuan

2012-09-01

This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship

Satellite passive microwave rain rate measurement over croplands during spring, summer and fall

NASA Technical Reports Server (NTRS)

Spencer, R. W.

1984-01-01

Rain-rate algorithms for spring, summer and fall that have been developed from comparisons between the brightness temperatures measured by the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and rain rates derived from operational WSR-57 radars over land are described. Data were utilized from a total of 25 SMMR passes and 234 radars, resulting in about 12,000 observations of about 1600 sq/km areas. Multiple correlation coefficients of 0.63, 0.80 and 0.75 are achieved for the spring, summer and fall algorithms, respectively. Most of this information is in the form of multifrequency contrast in brightness temperature, which is interpreted as a measurement of the degree to which the land-emitted radiation is attenuated by the rain systems. The SMMR 37-GHz channel has more information on rain rate than any other channel. By combining the lower frequency channels with the 37-GHz observations, variations in land and precipitation thermometric temperatures can be removed, leaving rain attenuation as the major effect on brightness temperature. Polarization screening at 37 GHz is found to be sufficient to screen out cases of wet ground, which is only important when the ground is relatively vegetation free. Heavy rain cases are found to be significant part of the algorithms' success, because of the strong microwve signatures (low-brightness temperatures) that result from the presence of precipitation-sized ice in the upper portions of heavily precipitating storms. If IR data are combined with the summer microwave data, an improved (0.85) correlation with radar rain rates is achieved.

Crop moisture estimation over the southern Great Plains with dual polarization 1.66 centimeter passive microwave data from Nimbus 7

NASA Technical Reports Server (NTRS)

Mcfarland, M. J.; Harder, P. H., II; Wilke, G. D.; Huebner, G. L., Jr.

1984-01-01

Moisture content of snow-free, unfrozen soil is inferred using passive microwave brightness temperatures from the scanning multichannel microwave radiometer (SMMR) on Nimbus-7. Investigation is restricted to the two polarizations of the 1.66 cm wavelength sensor. Passive microwave estimates of soil moisture are of two basic categories; those based upon soil emissivity and those based upon the polarization of soil emission. The two methods are compared and contrasted through the investigation of 54 potential functions of polarized brightness temperatures and, in some cases, ground-based temperature measurements. Of these indices, three are selected for the estimated emissivity, the difference between polarized brightness temperatures, and the normalized polarization difference. Each of these indices is about equally effective for monitoring soil moisture. Using an antecedent precipitation index (API) as ground control data, temporal and spatial analyses show that emissivity data consistently give slightly better soil moisture estimates than depolarization data. The difference, however, is not statistically significant. It is concluded that polarization data alone can provide estimates of soil moisture in areas where the emissivity cannot be inferred due to nonavailability of surface temperature data.

Operational satellites and the global monitoring of snow and ice

NASA Technical Reports Server (NTRS)

Walsh, John E.

1991-01-01

The altitudinal dependence of the global warming projected by global climate models is at least partially attributable to the albedo-temperature feedback involving snow and ice, which must be regarded as key variables in the monitoring for global change. Statistical analyses of data from IR and microwave sensors monitoring the areal coverage and extent of sea ice have led to mixed conclusions about recent trends of hemisphere sea ice coverage. Seasonal snow cover has been mapped for over 20 years by NOAA/NESDIS on the basis of imagery from a variety of satellite sensors. Multichannel passive microwave data show some promise for the routine monitoring of snow depth over unforested land areas.

The NASA Soil Moisture Active Passive (SMAP) Mission: Overview

NASA Technical Reports Server (NTRS)

O'Neill, Peggy; Entekhabi, Dara; Njoku, Eni; Kellogg, Kent

2011-01-01

The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council?s Decadal Survey [1]. Its mission design consists of L-band radiometer and radar instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every 2-3 days. The combined active/passive microwave soil moisture product will have a spatial resolution of 10 km and a mean latency of 24 hours. In addition, the SMAP surface observations will be combined with advanced modeling and data assimilation to provide deeper root zone soil moisture and net ecosystem exchange of carbon. SMAP is expected to launch in the late 2014 - early 2015 time frame.

Satellite microwave detection of contrasting changes in surface inundation across pan-Arctic permafrost zones

NASA Astrophysics Data System (ADS)

Watts, J.; Kimball, J. S.; Jones, L. A.; Schroeder, R.; McDonald, K. C.

2012-12-01

Surface water inundation in the Arctic is concomitant with soil permafrost and strongly influences land-atmosphere water, energy and carbon (CO2, CH4) exchange, and plant community structure. We examine recent (2003-2010) surface water inundation patterns across the pan-Arctic (≥ 50 deg.N) and within major permafrost zones using satellite passive microwave remote sensing retrievals of fractional open water extent (Fw) derived from Advanced Microwave Scanning Radiometer for EOS (AMSR-E) 18.7 and 23.8 GHz brightness temperatures. The AMSR-E Fw retrievals are insensitive to atmosphere contamination and solar illumination effects, enabling daily Fw monitoring across the Arctic. The Fw retrievals are sensitive to sub-grid scale open water inundation area, including lakes and wetlands, within the relatively coarse (~25-km resolution) satellite footprint. A forward model error sensitivity analysis indicates that total Fw retrieval uncertainty is within ±4.1% (RMSE), and AMSR-E Fw compares favorably (0.71 < R2 < 0.84) with alternative static open water maps derived from finer scale (30-m to 250-m resolution) Landsat, MODIS and SRTM radar-based products. The Fw retrievals also show dynamic seasonal and annual variability in surface inundation that corresponds (0.71 < R < 0.87) with regional wet/dry cycles inferred from basin discharge records, including Yukon, Mackenzie, Ob, Yenisei, and Lena basins. A regional change analysis of the 8-yr AMSR-E record shows no significant trend in pan-Arctic wide Fw, and instead reveals contrasting inundation changes within permafrost zones. Widespread Fw wetting is observed within continuous (92% of grid cells with significant trend show wetting; p < 0.1) and discontinuous (82%) permafrost zones, while areas with sporadic/isolated permafrost show widespread (71%) Fw drying. These results are consistent with previous studies showing evidence of changes in regional surface hydrology influenced by permafrost degradation under recent

Predicting Near Real-Time Inundation Occurrence from Complimentary Satellite Microwave Brightness Temperature Observations

NASA Astrophysics Data System (ADS)

Fisher, C. K.; Pan, M.; Wood, E. F.

2017-12-01

Throughout the world, there is an increasing need for new methods and data that can aid decision makers, emergency responders and scientists in the monitoring of flood events as they happen. In many regions, it is possible to examine the extent of historical and real-time inundation occurrence from visible and infrared imagery provided by sensors such as MODIS or the Landsat TM; however, this is not possible in regions that are densely vegetated or are under persistent cloud cover. In addition, there is often a temporal mismatch between the sampling of a particular sensor and a given flood event, leading to limited observations in near real-time. As a result, there is a need for alternative methods that take full advantage of complimentary remotely sensed data sources, such as available microwave brightness temperature observations (e.g., SMAP, SMOS, AMSR2, AMSR-E, and GMI), to aid in the estimation of global flooding. The objective of this work was to develop a high-resolution mapping of inundated areas derived from multiple satellite microwave sensor observations with a daily temporal resolution. This system consists of first retrieving water fractions from complimentary microwave sensors (AMSR-2 and SMAP) which may spatially and temporally overlap in the region of interest. Using additional information in a Random Forest classifier, including high resolution topography and multiple datasets of inundated area (both historical and empirical), the resulting retrievals are spatially downscaled to derive estimates of the extent of inundation at a scale relevant to management and flood response activities ( 90m or better) instead of the relatively coarse resolution water fractions, which are limited by the microwave sensor footprints ( 5-50km). Here we present the training and validation of this method for the 2015 floods that occurred in Houston, Texas. Comparing the predicted inundation against historical occurrence maps derived from the Landsat TM record and MODIS

Tropical cyclone intensities from satellite microwave data

NASA Technical Reports Server (NTRS)

Vonderhaar, T. H.; Kidder, S. Q.

1980-01-01

Radial profiles of mean 1000 mb to 250 mb temperature from the Nimbus 6 scanning microwave spectrometer (SCAMS) were constructed around eight intensifying tropical storms in the western Pacific. Seven storms showed distinct inward temperature gradients required for intensification; the eighth displayed no inward gradient and was decaying 24 hours later. The possibility that satellite data might be used to forecast tropical cyclone turning motion was investigated using estimates obtained from Nimbus 6 SCAMS data tapes of the mean 1000 mb to 250 mb temperature field around eleven tropical storms in 1975. Analysis of these data show that for turning storms, in all but one case, the turn was signaled 24 hours in advance by a significant temperature gradient perpendicular to the storm's path, at a distance of 9 deg to 13 deg in front of the storm. A thresholding technique was applied to the North Central U.S. during the summer to estimate precipitation frequency. except

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures for Falling Snow Events

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Johnson, Benjamin T.

2011-01-01

Physically based passive microwave precipitation retrieval algorithms require a set of relationships between satellite -observed brightness temperatures (TBs) and the physical state of the underlying atmosphere and surface. These relationships are nonlinear, such that inversions are ill ]posed especially over variable land surfaces. In order to elucidate these relationships, this work presents a theoretical analysis using TB weighting functions to quantify the percentage influence of the TB resulting from absorption, emission, and/or reflection from the surface, as well as from frozen hydrometeors in clouds, from atmospheric water vapor, and from other contributors. The percentage analysis was also compared to Jacobians. The results are presented for frequencies from 10 to 874 GHz, for individual snow profiles, and for averages over three cloud-resolving model simulations of falling snow. The bulk structure (e.g., ice water path and cloud depth) of the underlying cloud scene was found to affect the resultant TB and percentages, producing different values for blizzard, lake effect, and synoptic snow events. The slant path at a 53 viewing angle increases the hydrometeor contributions relative to nadir viewing channels. Jacobians provide the magnitude and direction of change in the TB values due to a change in the underlying scene; however, the percentage analysis provides detailed information on how that change affected contributions to the TB from the surface, hydrometeors, and water vapor. The TB percentage information presented in this paper provides information about the relative contributions to the TB and supplies key pieces of information required to develop and improve precipitation retrievals over land surfaces.

Statistical Analysis of the Correlation between Microwave Emission Anomalies and Seismic Activity Based on AMSR-E Satellite Data

NASA Astrophysics Data System (ADS)

qin, kai; Wu, Lixin; De Santis, Angelo; Zhang, Bin

2016-04-01

Pre-seismic thermal IR anomalies and ionosphere disturbances have been widely reported by using the Earth observation system (EOS). To investigate the possible physical mechanisms, a series of detecting experiments on rock loaded to fracturing were conducted. Some experiments studies have demonstrated that microwave radiation energy will increase under the loaded rock in specific frequency and the feature of radiation property can reflect the deformation process of rock fracture. This experimental result indicates the possibility that microwaves are emitted before earthquakes. Such microwaves signals are recently found to be detectable before some earthquake cases from the brightness temperature data obtained by the microwave-radiometer Advanced Microwave-Scanning Radiometer for the EOS (AMSR-E) aboard the satellite Aqua. This suggested that AMSR-E with vertical- and horizontal-polarization capability for six frequency bands (6.925, 10.65, 18.7, 23.8, 36.5, and 89.0 GHz) would be feasible to detect an earthquake which is associated with rock crash or plate slip. However, the statistical analysis of the correlation between satellite-observed microwave emission anomalies and seismic activity are firstly required. Here, we focus on the Kamchatka peninsula to carry out a statistical study, considering its high seismicity activity and the dense orbits covering of AMSR-E in high latitudes. 8-years (2003-2010) AMSR-E microwave brightness temperature data were used to reveal the spatio-temporal association between microwave emission anomalies and 17 earthquake events (M>5). Firstly, obvious spatial difference of microwave brightness temperatures between the seismic zone at the eastern side and the non-seismic zone the western side within the Kamchatka peninsula are found. Secondly, using both vertical- and horizontal-polarization to extract the temporal association, it is found that abnormal changes of microwave brightness temperatures appear generally 2 months before the

Perception via satellite

USGS Publications Warehouse

Robinove, Charles J.

1970-01-01

The earth resources observation satellite (EROS) program in the Department of the Interior is intended to gather and use data from satellites and aircraft on natural and man-made features of the earth's surface. Earth resources technology satellite will provide the EROS program with data for use in dealing with natural resource problems and understanding the interaction between man and the environment. Applications will include studies of tectonic features, hydrologic problems, location of fish schools, determination of the conditions of range land, mapping land use for urban planning, studies of erosion and change along coastlines and major streams, and inventories of land use and land forms. In addition, the ERTS data may be used for detecting forest and crop diseases and inventorying crops. The ERTS satellite will be in a polar, sun-synchronous orbit so that each point on the earth's surface will be sensed every 17 to 20 days, at the same time of day. Multispectral photography is being investigated for its usefulness in hydrology. Side-looking airborne radar has not yet been widely used in hydrologic studies, although it is an excellent tool for all-weather, day or night, coverage of large areas. Other techniques being investigated include passive microwave radiometry, ultraviolet and visible stimulated luminescence, and absorption spectroscopy.

A field evaluation of a satellite microwave rainfall sensor network

NASA Astrophysics Data System (ADS)

Caridi, Andrea; Caviglia, Daniele D.; Colli, Matteo; Delucchi, Alessandro; Federici, Bianca; Lanza, Luca G.; Pastorino, Matteo; Randazzo, Andrea; Sguerso, Domenico

2017-04-01

An innovative environmental monitoring system - Smart Rainfall System (SRS) - that estimates rainfall in real-time by means of the analysis of the attenuation of satellite signals (DVB-S in the microwave Ku band) is presented. Such a system consists in a set of peripheral microwave sensors placed on the field of interest, and connected to a central processing and analysis node. It has been developed jointly by the University of Genoa, with its departments DITEN and DICCA and the Genoese SME "Darts Engineering Srl". This work discusses the rainfall intensity measurements accuracy and sensitivity performance of SRS, based on preliminary results from a field comparison experiment at the urban scale. The test-bed is composed by a set of preliminary measurement sites established from Autumn 2016 in the Genoa (Italy) municipality and the data collected from the sensors during a selection of rainfall events is studied. The availability of point-scale rainfall intensity measurements made by traditional tipping-bucket rain gauges and radar areal observations allows a comparative analysis of the SRS performance. The calibration of the reference rain gauges has been carried out at the laboratories of DICCA using a rainfall simulator and the measurements have been processed taking advantage of advanced algorithms to reduce counting errors. The experimental set-up allows a fine tuning of the retrieval algorithm and a full characterization of the accuracy of the rainfall intensity estimates from the microwave signal attenuation as a function of different precipitation regimes.

Effects of Atmospheric Water and Surface Wind on Passive Microwave Retrievals of Sea Ice Concentration: a Simulation Study

NASA Astrophysics Data System (ADS)

Shin, D.; Chiu, L. S.; Clemente-Colon, P.

2006-05-01

The atmospheric effects on the retrieval of sea ice concentration from passive microwave sensors are examined using simulated data typical for the Arctic summer. The simulation includes atmospheric contributions of cloud liquid water, water vapor and surface wind on the microwave signatures. A plane parallel radiative transfer model is used to compute brightness temperatures at SSM/I frequencies over surfaces that contain open water, first-year (FY) ice and multi-year (MY) ice and their combinations. Synthetic retrievals in this study use the NASA Team (NT) algorithm for the estimation of sea ice concentrations. This study shows that if the satellite sensor's field of view is filled with only FY ice the retrieval is not much affected by the atmospheric conditions due to the high contrast between emission signals from FY ice surface and the signals from the atmosphere. Pure MY ice concentration is generally underestimated due to the low MY ice surface emissivity that results in the enhancement of emission signals from the atmospheric parameters. Simulation results in marginal ice areas also show that the atmospheric effects from cloud liquid water, water vapor and surface wind tend to degrade the accuracy at low sea ice concentration. FY ice concentration is overestimated and MY ice concentration is underestimated in the presence of atmospheric water and surface wind at low ice concentration. This compensating effect reduces the retrieval uncertainties of total (FY and MY) ice concentration. Over marginal ice zones, our results suggest that strong surface wind is more important than atmospheric water in contributing to the retrieval errors of total ice concentrations in the normal ranges of these variables.

Satellite microwave observations of the interannual variability of snowmelt on sea ice in the Southern Ocean

NASA Astrophysics Data System (ADS)

Willmes, S.; Haas, C.; Nicolaus, M.; Bareiss, J.

2009-04-01

Snowmelt processes on Antarctic sea ice are examined. We present a simple snowmelt indicator based on diurnal brightness temperature variations from microwave satellite data. The method is validated through extensive field data from the western Weddell Sea and lends itself to the investigation of interannual and spatial variations of the typical snowmelt on Antarctic sea ice. We use in situ measurements of physical snow properties to show that despite the absence of strong melting, the summer period is distinct from all other seasons with enhanced diurnal variations of snow wetness. A microwave emission model reveals that repeated thawing and refreezing causes the typical microwave emissivity signatures that are found on perennial Antarctic sea ice during summer. The proposed melt indicator accounts for the characteristic phenomenological stages of snowmelt in the Southern Ocean and detects the onset of diurnal snow wetting. An algorithm is presented to map large-scale snowmelt onset, based on satellite data from the period between 1988 and 2006. The results indicate strong meridional gradients of snowmelt onset with the Weddell, Amundsen and Ross Seas showing earliest (beginning of October) and most frequent snowmelt. Moreover, a distinct interannual variability of melt onset dates and large areas of first-year ice where no diurnal freeze-thawing occurs at the surface are determined.

Satellite microwave observations of the interannual variability of snowmelt on sea ice in the Southern Ocean

NASA Astrophysics Data System (ADS)

Willmes, Sascha; Haas, Christian; Nicolaus, Marcel; Bareiss, JöRg

2009-03-01

Snowmelt processes on Antarctic sea ice are examined. We present a simple snowmelt indicator based on diurnal brightness temperature variations from microwave satellite data. The method is validated through extensive field data from the western Weddell Sea and lends itself to the investigation of interannual and spatial variations of the typical snowmelt on Antarctic sea ice. We use in-situ measurements of physical snow properties to show that despite the absence of strong melting, the summer period is distinct from all other seasons with enhanced diurnal variations of snow wetness. A microwave emission model reveals that repeated thawing and refreezing cause the typical microwave emissivity signatures that are found on perennial Antarctic sea ice during summer. The proposed melt indicator accounts for the characteristic phenomenological stages of snowmelt in the Southern Ocean and detects the onset of diurnal snow wetting. An algorithm is presented to map large-scale snowmelt onset based on satellite data from the period between 1988 and 2006. The results indicate strong meridional gradients of snowmelt onset with the Weddell, Amundsen, and Ross Seas showing earliest (beginning of October) and most frequent snowmelt. Moreover, a distinct interannual variability of melt onset dates and large areas of first-year ice where no diurnal freeze thawing occurs at the surface are determined.

New Technique for Retrieving Liquid Water Path over Land using Satellite Microwave Observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deeter, M.N.; Vivekanandan, J.

2005-03-18

We present a new methodology for retrieving liquid water path over land using satellite microwave observations. As input, the technique exploits the Advanced Microwave Scanning Radiometer for earth observing plan (EOS) (AMSR-E) polarization-difference signals at 37 and 89 GHz. Regression analysis performed on model simulations indicates that over variable atmospheric and surface conditions the polarization-difference signals can be simply parameterized in terms of the surface emissivity polarization difference ({Delta}{var_epsilon}), surface temperature, liquid water path (LWP), and precipitable water vapor (PWV). The resulting polarization-difference parameterization (PDP) enables fast and direct (noniterative) retrievals of LWP with minimal requirements for ancillary data. Single-more » and dual-channel retrieval methods are described and demonstrated. Data gridding is used to reduce the effects of instrumental noise. The methodology is demonstrated using AMSR-E observations over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site during a six day period in November and December, 2003. Single- and dual-channel retrieval results mostly agree with ground-based microwave retrievals of LWP to within approximately 0.04 mm.« less

An assessment of the differences between spatial resolution and grid size for the SMAP enhanced soil moisture product over homogeneous sites

USDA-ARS?s Scientific Manuscript database

Satellite-based passive microwave remote sensing typically involves a scanning antenna that makes measurements at irregularly spaced locations. These locations can change on a day to day basis. Soil moisture products derived from satellite-based passive microwave remote sensing are usually resampled...

Snowmelt Pattern and Lake Ice Phenology around Tibetan Plateau Estimated from Enhanced Resolution Passive Microwave Data

NASA Astrophysics Data System (ADS)

Xiong, C.; Shi, J.; Wang, T.

2017-12-01

Snow and ice is very sensitive to the climate change. Rising air temperature will cause the snowmelt time change. In contrast, the change in snow state will have feedback on climate through snow albedo. The snow melt timing is also correlated with the associated runoff. Ice phenology describes the seasonal cycle of lake ice cover and includes freeze-up and breakup periods and ice cover duration, which is an important weather and climate indicator. It is also important for lake-atmosphere interactions and hydrological and ecological processes. The enhanced resolution (up to 3.125 km) passive microwave data is used to estimate the snowmelt pattern and lake ice phenology on and around Tibetan Plateau. The enhanced resolution makes the estimation of snowmelt and lake ice phenology in more spatial detail compared to previous 25 km gridded passive microwave data. New algorithm based on smooth filters and change point detection was developed to estimate the snowmelt and lake ice freeze-up and break-up timing. Spatial and temporal pattern of snowmelt and lake ice phonology are estimated. This study provides an objective evidence of climate change impact on the cryospheric system on Tibetan Plateau. The results show significant earlier snowmelt and lake ice break-up in some regions.

Precise monitoring of global temperature trends from satellites

NASA Technical Reports Server (NTRS)

Spencer, Roy W.; Christy, John R.

1990-01-01

Passive microwave radiometry from satellites provides more precise atmospheric temperature information than that obtained from the relatively sparse distribution of thermometers over the earth's surface. Accurate global atmospheric temperature estimates are needed for detection of possible greenhouse warming, evaluation of computer models of climate change, and for understanding important factors in the climate system. Analysis of the first 10 years (1979 to 1988) of satellite measurements of lower atmospheric temperature changes reveals a monthly precision of 0.01 C, large temperature variability on time scales from weeks to several years, but no obvious trend for the 10-year period. The warmest years, in descending order, were 1987, 1988, 1983, and 1980. The years 1984, 1985, and 1986 were the coolest.

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

Using High Frequency Passive Microwave, A-train, and TRMM Data to Evaluate Hydrometer Structure in the NASA GEOS-5 Data Assimilation System

NASA Technical Reports Server (NTRS)

Robertson, Franklin; Bacmeister, Julio; Bosilovich, Michael; Pittman, Jasna

2007-01-01

Validating water vapor and prognostic condensate in global models remains a challenging research task. Model parameterizations are still subject to a large number of tunable parameters; furthermore, accurate and representative in situ observations are very sparse, and satellite observations historically have significant quantitative uncertainties. Progress on improving cloud / hydrometeor fields in models stands to benefit greatly from the growing inventory ofA-Train data sets. ill the present study we are using a variety of complementary satellite retrievals of hydrometeors to examine condensate produced by the emerging NASA Modem Era Retrospective Analysis for Research and Applications, MERRA, and its associated atmospheric general circulation model GEOS5. Cloud and precipitation are generated by both grid-scale prognostic equations and by the Relaxed Arakawa-Schubert (RAS) diagnostic convective parameterization. The high frequency channels (89 to 183.3 GHz) from AMSU-B and MRS on NOAA polar orbiting satellites are being used to evaluate the climatology and variability of precipitating ice from tropical convective anvils. Vertical hydrometeor structure from the Tropical Rainfall Measuring Mission (TRMM) and CloudSat radars are used to develop statistics on vertical hydrometeor structure in order to better interpret the extensive high frequency passive microwave climatology. Cloud liquid and ice water path data retrieved from the Moderate Resolution Imaging Spectroradiometer, MODIS, are used to investigate relationships between upper level cloudiness and tropical deep convective anvils. Together these data are used to evaluate cloud / ice water path, gross aspects of vertical hydrometeor structure, and the relationship between cloud extent and surface precipitation that the MERRA reanalysis must capture.

Foreword to the Special Issue on the 11th Specialist Meeting on Microwave Radiometry and Remote Sensing Applications (MicroRad 2010)

NASA Technical Reports Server (NTRS)

Le Vine, David M; Jackson, Thomas J.; Kim, Edward J.; Lang, Roger H.

2011-01-01

The Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad 2010) was held in Washington, DC from March 1 to 4, 2010. The objective of MicroRad 2010 was to provide an open forum to report and discuss recent advances in the field of microwave radiometry, particularly with application to remote sensing of the environment. The meeting was highly successful, with more than 200 registrations representing 48 countries. There were 80 oral presentations and more than 100 posters. MicroRad has become a venue for the microwave radiometry community to present new research results, instrument designs, and applications to an audience that is conversant in these issues. The meeting was divided into 16 sessions (listed in order of presentation): 1) SMOS Mission; 2) Future Passive Microwave Remote Sensing Missions; 3) Theory and Physical Principles of Electromagnetic Models; 4) Field Experiment Results; 5) Soil Moisture and Vegetation; 6) Snow and Cryosphere; 7) Passive/Active Microwave Remote Sensing Synergy; 8) Oceans; 9) Atmospheric Sounding and Assimilation; 10) Clouds and Precipitation; 11) Instruments and Advanced Techniques I; 12) Instruments and Advanced Techniques II; 13) Cross Calibration of Satellite Radiometers; 14) Calibration Theory and Methodology; 15) New Technologies for Microwave Radiometry; 16) Radio Frequency Interference.

Effects of atmospheric turbulence on microwave and millimeter wave satellite communications systems. [attenuation statistics and antenna design

NASA Technical Reports Server (NTRS)

Devasirvatham, D. M. J.; Hodge, D. B.

1981-01-01

A model of the microwave and millimeter wave link in the presence of atmospheric turbulence is presented with emphasis on satellite communications systems. The analysis is based on standard methods of statistical theory. The results are directly usable by the design engineer.

First results of the COBE satellite measurement of the anisotropy of the cosmic microwave background radiation

NASA Technical Reports Server (NTRS)

Smoot, G. F.; Aymon, J.; De Amici, G.; Bennett, C. L.; Kogut, A.; Gulkis, S.; Backus, C.; Galuk, K.; Jackson, P. D.; Keegstra, P.

1991-01-01

The concept and operation of the Differential Microwave Radiometers (DMR) instrument aboard NASA's Cosmic Background Explorer satellite are reviewed, with emphasis on the software identification and subtraction of potential systematic effects. Preliminary results obtained from the first six months of DMR data are presented, and implications for cosmology are discussed.

First microwave map of the Moon with Chang'E-1 data: The role of local time in global imaging

NASA Astrophysics Data System (ADS)

Zheng, Y. C.; Tsang, K. T.; Chan, K. L.; Zou, Y. L.; Zhang, F.; Ouyang, Z. Y.

2012-05-01

Among recent lunar orbiters, only the Chinese Chang'E-1 (CE-1) was equipped with a passive microwave radiometer (MRM) to measure the natural microwave emission from the lunar surface. The microwave emission, characterized by a frequency-dependent brightness temperature (TB), is related to the physical temperature and dielectric properties of the lunar surface. By measuring the brightness temperature at different frequencies, detailed thermal behavior and properties of the lunar surface can be retrieved. Using CE-1's microwave data, we present here a set of microwave maps of the Moon constructed through a rescaling of TB to noontime or midnight. The adopted processing technique helps to reduce the effect of mixing up the temporal and spatial variations introduced by the satellite's localized measurements which cover different locations of the globe at different lunar local times. The resulting maps show fine structures unseen in previous microwave maps that disregarded the local time effect. We discussed the new features revealed and their possible connections with the lunar geology.

Snow Microwave Radiative Transfer (SMRT): A new model framework to simulate snow-microwave interactions for active and passive remote sensing applications

NASA Astrophysics Data System (ADS)

Loewe, H.; Picard, G.; Sandells, M. J.; Mätzler, C.; Kontu, A.; Dumont, M.; Maslanka, W.; Morin, S.; Essery, R.; Lemmetyinen, J.; Wiesmann, A.; Floury, N.; Kern, M.

2016-12-01

Forward modeling of snow-microwave interactions is widely used to interpret microwave remote sensing data from active and passive sensors. Though different models are yet available for that purpose, a joint effort has been undertaken in the past two years within the ESA Project "Microstructural origin of electromagnetic signatures in microwave remote sensing of snow". The new Snow Microwave Radiative Transfer (SMRT) model primarily facilitates a flexible treatment of snow microstructure as seen by X-ray tomography and seeks to unite respective advantages of existing models. In its main setting, SMRT considers radiation transfer in a plane-parallel snowpack consisting of homogeneous layers with a layer microstructure represented by an autocorrelation function. The electromagnetic model, which underlies permittivity, absorption and scattering calculations within a layer, is based on the improved Born approximation. The resulting vector-radiative transfer equation in the snowpack is solved using spectral decomposition of the discrete ordinates discretization. SMRT is implemented in Python and employs an object-oriented, modular design which intends to i) provide an intuitive and fail-safe API for basic users ii) enable efficient community developments for extensions (e.g. for improvements of sub-models for microstructure, permittivity, soil or interface reflectivity) from advanced users and iii) encapsulate the numerical core which is maintained by the developers. For cross-validation and inter-model comparison, SMRT implements various ingredients of existing models as selectable options (e.g. Rayleigh or DMRT-QCA phase functions) and shallow wrappers to invoke legacy model code directly (MEMLS, DMRT-QMS, HUT). In this paper we give an overview of the model components and show examples and results from different validation schemes.

Soil Moisture Active Passive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration

NASA Technical Reports Server (NTRS)

Peng, Jinzheng; Piepmeier, Jeffrey R.; Misra, Sidharth; Dinnat, Emmanuel P.; Hudson, Derek; Le Vine, David M.; De Amici, Giovanni; Mohammed, Priscilla N.; Yueh, Simon H.; Meissner, Thomas

2016-01-01

The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude. Since April, 2015, the radiometer is under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods including the SMAP L1B TA2TB (from Antenna Temperature (TA) to the Earth's surface Brightness Temperature (TB)) algorithm and TA forward models are outlined, and validation approaches to calibration stability/quality are described in this paper including future work. Results show that the current radiometer L1B data satisfies its requirements.

Soil Moisture ActivePassive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration

NASA Technical Reports Server (NTRS)

Peng, Jinzheng; Piepmeier, Jeffrey R.; Misra, Sidharth; Dinnat, Emmanuel P.; Hudson, Derek; Le Vine, David M.; De Amici, Giovanni; Mohammed, Priscilla N.; Yueh, Simon H.; Meissner, Thomas

2016-01-01

The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude. Since April, 2015, the radiometer is under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods including the SMAP L1B TA2TB (from Antenna Temperature (TA) to the Earth’s surface Brightness Temperature (TB)) algorithm and TA forward models are outlined, and validation approaches to calibration stability/quality are described in this paper including future work. Results show that the current radiometer L1B data satisfies its requirements.

Portable microwave frequency dissemination in free space and implications on ground-to-satellite synchronization.

PubMed

Miao, J; Wang, B; Bai, Y; Yuan, Y B; Gao, C; Wang, L J

2015-05-01

Frequency dissemination and synchronization in free space play an important role in global navigation satellite system, radio astronomy, and synthetic aperture radar. In this paper, we demonstrated a portable radio frequency dissemination scheme via free space using microwave antennas. The setup has a good environment adaptability and high dissemination stability. The frequency signal was disseminated at different distances ranging from 10 to 640 m with a fixed 10 Hz locking bandwidth, and the scaling law of dissemination stability on distance and averaging time was discussed. The preliminary extrapolation shows that the dissemination stability may reach 1 × 10(-12)/s in ground-to-satellite synchronization, which far exceeds all present methods, and is worthy for further study.

Modeling UV-B Effects on Primary Production Throughout the Southern Ocean Using Multi-Sensor Satellite Data

NASA Technical Reports Server (NTRS)

Lubin, Dan

2001-01-01

This study has used a combination of ocean color, backscattered ultraviolet, and passive microwave satellite data to investigate the impact of the springtime Antarctic ozone depletion on the base of the Antarctic marine food web - primary production by phytoplankton. Spectral ultraviolet (UV) radiation fields derived from the satellite data are propagated into the water column where they force physiologically-based numerical models of phytoplankton growth. This large-scale study has been divided into two components: (1) the use of Total Ozone Mapping Spectrometer (TOMS) and Special Sensor Microwave Imager (SSM/I) data in conjunction with radiative transfer theory to derive the surface spectral UV irradiance throughout the Southern Ocean; and (2) the merging of these UV irradiances with the climatology of chlorophyll derived from SeaWiFS data to specify the input data for the physiological models.

Assessing the relationship between microwave vegetation optical depth and gross primary production

NASA Astrophysics Data System (ADS)

Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Liu, Yi Y.; Miralles, Diego G.; Parinussa, Robert; van der Schalie, Robin; Vreugdenhil, Mariette; Schwalm, Christopher R.; Tramontana, Gianluca; Camps-Valls, Gustau; Dorigo, Wouter A.

2018-03-01

At the global scale, the uptake of atmospheric carbon dioxide by terrestrial ecosystems through photosynthesis is commonly estimated through vegetation indices or biophysical properties derived from optical remote sensing data. Microwave observations of vegetated areas are sensitive to different components of the vegetation layer than observations in the optical domain and may therefore provide complementary information on the vegetation state, which may be used in the estimation of Gross Primary Production (GPP). However, the relation between GPP and Vegetation Optical Depth (VOD), a biophysical quantity derived from microwave observations, is not yet known. This study aims to explore the relationship between VOD and GPP. VOD data were taken from different frequencies (L-, C-, and X-band) and from both active and passive microwave sensors, including the Advanced Scatterometer (ASCAT), the Soil Moisture Ocean Salinity (SMOS) mission, the Advanced Microwave Scanning Radiometer for Earth Observation System (AMSR-E) and a merged VOD data set from various passive microwave sensors. VOD data were compared against FLUXCOM GPP and Solar-Induced chlorophyll Fluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). FLUXCOM GPP estimates are based on the upscaling of flux tower GPP observations using optical satellite data, while SIF observations present a measure of photosynthetic activity and are often used as a proxy for GPP. For relating VOD to GPP, three variables were analyzed: original VOD time series, temporal changes in VOD (ΔVOD), and positive changes in VOD (ΔVOD≥0). Results show widespread positive correlations between VOD and GPP with some negative correlations mainly occurring in dry and wet regions for active and passive VOD, respectively. Correlations between VOD and GPP were similar or higher than between VOD and SIF. When comparing the three variables for relating VOD to GPP, correlations with GPP were higher for the original VOD time

Aircraft and satellite measurement of ocean wave directional spectra using scanning-beam microwave radars

NASA Technical Reports Server (NTRS)

Jackson, F. C.; Walton, W. T.; Baker, P. L.

1982-01-01

A microwave radar technique for remotely measuring the vector wave number spectrum of the ocean surface is described. The technique, which employs short-pulse, noncoherent radars in a conical scan mode near vertical incidence, is shown to be suitable for both aircraft and satellite application, the technique was validated at 10 km aircraft altitude, where we have found excellent agreement between buoy and radar-inferred absolute wave height spectra.

Design of a 12 channel fm microwave receiver. [for satellite ground stations

NASA Technical Reports Server (NTRS)

Risch, C. O.; Rosenbaum, F. J.; Gregory, R. O.

1974-01-01

The design, fabrication, and performance of elements of a low cost FM microwave satellite ground station receiver is described. It is capable of accepting 12 contiguous color television equivalent bandwidth channels in the 11.72 to 12.2 GHz band. Each channel is 40 MHz wide and incorporates a 4 MHz guard band. The modulation format is wideband FM and the channels are frequency division multiplexed. Twelve independent CATV compatible baseband outputs are provided. The overall system specifications are first discussed, then consideration is given to the receiver subsystems and the signal branching network.

Meteorological Satellites (METSAT) and Earth Observing System (EOS) Advanced Microwave Sounding Unit-A (AMSU-A) Stress Analysis Report

NASA Technical Reports Server (NTRS)

Heffner, Robert

1996-01-01

Stress analysis of the primary structure of the Meteorological Satellites Project (METSAT) Advanced Microwave Sounding Units-A, A1 Module using static loads is presented. The structural margins of safety and natural frequency predictions for the METSAT design are reported.

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

Validation of the Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval in an Arctic tundra environment

NASA Astrophysics Data System (ADS)

Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip

2017-05-01

This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.

Localized electrical fine tuning of passive microwave and radio frequency devices

DOEpatents

Findikoglu, Alp T.

2001-04-10

A method and apparatus for the localized electrical fine tuning of passive multiple element microwave or RF devices in which a nonlinear dielectric material is deposited onto predetermined areas of a substrate containing the device. An appropriate electrically conductive material is deposited over predetermined areas of the nonlinear dielectric and the signal line of the device for providing electrical contact with the nonlinear dielectric. Individual, adjustable bias voltages are applied to the electrically conductive material allowing localized electrical fine tuning of the devices. The method of the present invention can be applied to manufactured devices, or can be incorporated into the design of the devices so that it is applied at the time the devices are manufactured. The invention can be configured to provide localized fine tuning for devices including but not limited to coplanar waveguides, slotline devices, stripline devices, and microstrip devices.

Spatial Variability of Barrow-Area Shore-Fast Sea Ice and Its Relationships to Passive Microwave Emissivity

NASA Technical Reports Server (NTRS)

Maslanik, J. A.; Rivas, M. Belmonte; Holmgren, J.; Gasiewski, A. J.; Heinrichs, J. F.; Stroeve, J. C.; Klein, M.; Markus, T.; Perovich, D. K.; Sonntag, J. G.;

Radio Frequency Survey of the 21-cm Wavelength(l.4 GHz) Allocation for Passive Microwave Observing

NASA Technical Reports Server (NTRS)

Piepmeier, J. R.; Midon, M.; Caroglanian, A.; Ugweje, O. C.

2003-01-01

Because of the need to develop 1.4-GHz radiometers, a set of RF surveys was conducted in and around our laboratories. In this paper, a measurement campaign and analysis of radio frequency interference (RFI) in the 21 cm wavelength allocation for passive microwave observing, was undertaken. The experimental setup and measurement procedure are outlined and measured data are interpreted. Significant signals were discovered within and surrounding the allocated spectrum at 1.4 GHz. Some implications for remote sensing are discussed.

Space Solar Power Satellite Systems, Modern Small Satellites, and Space Rectenna

NASA Astrophysics Data System (ADS)

Bergsrud, Corey Alexis Marvin

Space solar power satellite (SSPS) systems is the concept of placing large satellite into geostationary Earth orbit (GEO) to harvest and convert massive amounts of solar energy into microwave energy, and to transmit the microwaves to a rectifying antenna (rectenna) array on Earth. The rectenna array captures and converts the microwave power into usable power that is injected into the terrestrial electric grid for use. This work approached the microwave power beam as an additional source of power (with solar) for lower orbiting satellites. Assuming the concept of retrodirectivity, a GEO-SSPS antenna array system tracks and delivers microwave power to lower orbiting satellites. The lower orbiting satellites are equipped with a stacked photovoltaic (PV)/rectenna array hybrid power generation unit (HPGU) in order to harvest solar and/or microwave energy for on-board use during orbit. The area, and mass of the PV array part of the HPGU was reduced at about 32% beginning-of-life power in order to achieve the spacecraft power requirements. The HPGU proved to offer a mass decrease in the PGU, and an increase in mission life due to longer living component life of the rectenna array. Moreover, greater mission flexibility is achieved through a track and power delivery concept. To validate the potential advantages offered by a HPGU, a mission concept was presented that utilizes modern small satellites as technology demonstrators. During launch, a smaller power receiving "daughter" satellite sits inside a larger power transmitting "mother" satellite. Once separated from the launch vehicle the daughter satellite is ejected away from the mother satellite, and each satellite deploys its respective power transmitting or power receiving hardware's for experimentation. The concept of close proximity mission operations between the satellites is considered. To validate the technology of the space rectenna array part of the HPGU, six milestones were completed in the design. The first

Estimation of polar low characteristics for the Nordic Seas for 1995-2008 using satellite data

NASA Astrophysics Data System (ADS)

Smirnova, Julia; Chapron, Bertrand; Zabolotskikh, Elizaveta; Leonid Bobylev, Mr

In recent years the scientific research confirmed the fact of the global warming. The Arctic climate is warming even more rapidly. Powerful storm polar lows having wind speeds of about 25 m/c are known to be the cause of hazardous weather. Polar lows present themselves as the atmospheric phenomena the horizontal dimensions of which do not exceed 1,000 km, appear and which exist from 12 to 24 hours. The wave fall and low temperatures can lead to increased probability of vessel icing the intensity of which increases with the high wind speed and large wave height. Study of the mesoscale processes, such as polar lows in the Arctic has become especially relevant due to the sharp sea ice decreasing in the Arctic Ocean and Arctic seas in recent years. Only the use of satellite data allows obtaining regular and spacious information about the polar lows. Early detection and evaluation of the characteristics of the polar lows is an extremely important task to ensure the safety of navigation, fishing and oil industry in the Arctic region. With new open areas dangerous polar lows can arise over them. So early detection of the polar lows, studying their characteristics, tracking their movement and prediction presents one the most important problems of the modern science. The present-day meteorological observational network has severe limitations in detecting all, especially small mesoscale cyclones, so there is a strong need for new and/or improved methods to detect and monitor polar lows. Satellite remote sensing seems to be the most feasible tool for early detection and monitoring of the polar lows. Several remote sensing sensors are capable to detect a polar low but each of them suffers from various deficiencies. In the work, satellite passive microwave data have been intensively exploited aiming at obtaining the fields of geophysical parameters inside the polar lows. DMSP Special Sensor Microwave/Imager - SSM/I data were used in the research. The polar lows have been

Passive Microwave Soil Moisture Retrieval through Combined Radar/Radiometer Ground Based Simulator with Special Reference to Dielectric Schemes

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K., ,, Dr.; O'Neill, Peggy, ,, Dr.

2014-05-01

indicated a higher performance in terms of soil moisture retrieval accuracy for the Mironov dielectric model (RMSE of 0.035 m3/m3), followed by Dobson, Wang & Schmugge, and Hallikainen. This analysis indicates that Mironov dielectric model is promising for passive-only microwave soil moisture retrieval and could be a useful choice for SMAP satellite soil moisture retrieval. Keywords: Dielectric models; Single Channel Algorithm, Combined Radar/Radiometer, Soil moisture; L band References: Behari, J. (2005). Dielectric Behavior of Soil (pp. 22-40). Springer Netherlands O'Neill, P. E., Lang, R. H., Kurum, M., Utku, C., & Carver, K. R. (2006), Multi-Sensor Microwave Soil Moisture Remote Sensing: NASA's Combined Radar/Radiometer (ComRAD) System. In IEEE MicroRad, 2006 (pp. 50-54). IEEE. Srivastava, P. K., Han, D., Rico Ramirez, M. A., & Islam, T. (2013), Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology, 498, 292-304. USDA OPE3 web site at http://www.ars.usda.gov/Research/.

Cassini radar and radiometry observations of Saturn's airless icy satellites

NASA Astrophysics Data System (ADS)

Le Gall, A. A.; West, R.; Janssen, M. A.; Leyrat, C.; Bonnefoy, L.; Lellouch, E.

2017-12-01

The Cassini Radar is a multimode microwave sensor operating in the Ku-band, at a wavelength of 2.2 cm. While it was initially designed to examine the surface of Titan through the veil of its optically-opaque atmosphere, it is occasionally used to observe airless Saturn's moons from long ranges (>50 000 km) and, less frequently, during targeted flybys. In its active mode, the instrument measures the surface reflectivity in the backscattering direction. In its passive mode - or radiometry mode - it records the microwave thermal emission from the near-surface (typically few meters). Doing so, it provides insights into the degree of purity and maturity of the water-ice regolith of the investigated objects. In particular, it can reveal hemispheric dichotomies or regional anomalies and satellite-to-satellite variabilities which give clues into what is common and what is specific to the history of each satellite and to the processes that have shaped their surface/subsurface. In this paper, we will give an overview of the Cassini radar/radiometry observations of Saturnian icy moons, most of which have not been published yet. Now that the mission has come to an end, we will describe how the radio investigation of these objects can be pursued from Earth-based radiotelescopes.

Polar research from satellites

NASA Technical Reports Server (NTRS)

Thomas, Robert H.

1991-01-01

In the polar regions and climate change section, the topics of ocean/atmosphere heat transfer, trace gases, surface albedo, and response to climate warming are discussed. The satellite instruments section is divided into three parts. Part one is about basic principles and covers, choice of frequencies, algorithms, orbits, and remote sensing techniques. Part two is about passive sensors and covers microwave radiometers, medium-resolution visible and infrared sensors, advanced very high resolution radiometers, optical line scanners, earth radiation budget experiment, coastal zone color scanner, high-resolution imagers, and atmospheric sounding. Part three is about active sensors and covers synthetic aperture radar, radar altimeters, scatterometers, and lidar. There is also a next decade section that is followed by a summary and recommendations section.

Ionosphere/microwave beam interaction study. [satellite solar energy conversion

NASA Technical Reports Server (NTRS)

Duncan, L. M.; Gordon, W. E.

1977-01-01

A solar power satellite microwave power density of 20mw sq cm was confirmed as the level where nonlinear interactions may occur in the ionosphere, particularly at 100 km altitude. Radio wave heating at this altitude, produced at the Arecibo Observatory, yielded negative results for radio wave heating of an underdense ionosphere. Overdense heating produced striations in the ionosphere which may cause severe radio frequency interference problems under certain conditions. The effects of thermal self-focusing are shown to be limited severely geographically. The aspect sensitivity of field-aligned striations makes interference-free regions above magnetic latitude about 60 deg. A test program is proposed to simulate the interaction of the SPS beam with the ionosphere, to measure the effects of the interaction on the ionosphere and on communication and navigation systems, and to interpret the results.

Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail M.; Johnson, Benjamin T.; Munchak, S. Joseph

2013-01-01

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

False-color display of special sensor microwave/imager (SSM/I) data

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.; Kummerow, Christian D.

1989-01-01

Displays of multifrequency passive microwave data from the Special Sensor Microwave/Imager (SSM/I) flying on the Defense Meteorological Satellite Program (DMSP) spacecraft are presented. Observed brightness temperatures at 85.5 GHz (vertical and horizontal polarizations) and 37 GHz (vertical polarization) are respectively used to 'drive' the red, green, and blue 'guns' of a color monitor. The resultant false-color images can be used to distinguish land from water, highlight precipitation processes and structure over both land and water, and detail variations in other surfaces such as deserts, snow cover, and sea ice. The observations at 85.5 GHz also add a previously unavailable frequency to the problem of rainfall estimation from space. Examples of mesoscale squall lines, tropical and extra-tropical storms, and larger-scale land and atmospheric features as 'viewed' by the SSM/I are shown.

False-color display of special sensor microwave/imager (SSM/I) data

NASA Astrophysics Data System (ADS)

Negri, Andrew J.; Adler, Robert F.; Kummerow, Christian D.

1989-02-01

Displays of multifrequency passive microwave data from the Special Sensor Microwave/Imager (SSM/I) flying on the Defense Meteorological Satellite Program (DMSP) spacecraft are presented. Observed brightness temperatures at 85.5 GHz (vertical and horizontal polarizations) and 37 GHz (vertical polarization) are respectively used to 'drive' the red, green, and blue 'guns' of a color monitor. The resultant false-color images can be used to distinguish land from water, highlight precipitation processes and structure over both land and water, and detail variations in other surfaces such as deserts, snow cover, and sea ice. The observations at 85.5 GHz also add a previously unavailable frequency to the problem of rainfall estimation from space. Examples of mesoscale squall lines, tropical and extra-tropical storms, and larger-scale land and atmospheric features as 'viewed' by the SSM/I are shown.

Design/cost tradeoff studies. Appendix A. Supporting analyses and tradeoffs, book 1. Earth Observatory Satellite system definition study (EOS)

NASA Technical Reports Server (NTRS)

1974-01-01

A listing of the Earth Observatory Satellite (EOS) candidate missions is presented for use as a baseline in describing the EOS payloads. The missions are identified in terms of first, second, and third generation payloads. The specific applications of the EOS satellites are defined. The subjects considered are: (1) orbit analysis, (2) space shuttle interfaces, (3) thematic mapping subsystem, (4) high resolution pointable imager subsystem, (5) the data collection system, (6) the synthetic aperture radar, (7) the passive multichannel microwave radiometer, and (8) the wideband communications and handling equipment. Illustrations of the satellite and launch vehicle configurations are provided. Block diagrams of the electronic circuits are included.

Microwave and physical properties of sea ice in the winter marginal ice zone

NASA Technical Reports Server (NTRS)

Tucker, W. B., III; Perovich, D. K.; Gow, A. J.; Grenfell, T. C.; Onstott, R. G.

1991-01-01

Surface-based active and passive microwave measurements were made in conjunction with ice property measurements for several distinct ice types in the Fram Strait during March and April 1987. Synthesis aperture radar imagery downlinked from an aircraft was used to select study sites. The surface-based radar scattering cross section and emissivity spectra generally support previously inferred qualitative relationships between ice types, exhibiting expected separation between young, first-year and multiyear ice. Gradient ratios, calculated for both active and passive data, appear to allow clear separation of ice types when used jointly. Surface flooding of multiyear floes, resulting from excessive loading and perhaps wave action, causes both active and passive signatures to resemble those of first-year ice. This effect could possibly cause estimates of ice type percentages in the marginal ice zone to be in error when derived from aircraft- or satellite-born sensors.

On the characterization of subpixel effects for passive microwave remote sensing of snow in montane environments

NASA Astrophysics Data System (ADS)

Vander Jagt, Benjamin John

Snow and its water equivalent plays a vital role in global water and energy balances, with particular relevance in mountainous areas with arid and semi-arid climate regimes. Spaceborne passive microwave (PM) remote sensing measurements are attractive for snowpack characterization due to their continuous global coverage and historical record; over 30 years of research has been invested in the development of methods to characterize large-scale snow water resources from PM-based measurements. Historically, use of PM data for snowpack characterization in montane enviroments has been obstructed by the complex subpixel variability of snow properties within the PM measurement footprint. The main subpixel effects can be grouped as: the effect of snow microstructure (e.g. snow grain size) and stratigraphy on snow microwave emission, vegetation attenuation of PM measurements, and the sensitivity PM brightness temperature (Tb) observation to the variability of different subpixel properties at spaceborne measurement scales. This dissertation is focused on a systematic examination of these issues, which thus far have prevented the widespread integration of snow water equivalent (SWE) retrieval methods. It is meant to further our comprehension of the underlying processes at work in these rugged, remote, a hydrologically important areas. The role that snow microstructure plays in the PM retrievals of SWE is examined first. Traditional estimates of grain size are subjective and prone to error. Objective techniques to characterize grain size are described and implemented, including near infrared (NIR), stereology, and autocorrelation based approaches. Results from an intensive Colorado field study in which independent estimates of grain size and their modeled brightness temperature (Tb) emission are evaluated against PM Tb observations are included. The coarse resolution of the passive microwave measurements provides additional challenges when trying to resolve snow states via

SAR and passive microwave observations of the Odden during Mizex '87

NASA Technical Reports Server (NTRS)

Sutherland, Laura L.; Shuchman, Robert A.; Gloersen, Per; Johannessen, Johnny A.; Johannessen, Ola M.

1989-01-01

The Odden, a protuberance of sea ice in the Greenland Sea Basin, was studied using the NIMBUS-7 scanning multichannel microwave radiometer (SMMR) satellite and an X-band (3 cm) synthetic aperture radar (SAR) aircraft. The sea ice, meteorological, and oceanographic conditions within the northern portion of the Odden were also studied in March and April 1987. The SMMR data, which were first validated with in situ ship measurements and the SAR data, showed rapid 2-4 day oscillations of the Odden ice edge. The oscillations at 74-75 deg N were several hundred kilometers in extent. The rapid oscillation of the Odden does not appear to be a result of wind-induced ice drift, but rather results from the rapid formation of thin ice off the main ice edge.

Mapping the spatial distribution and time evolution of snow water equivalent with passive microwave measurements

USGS Publications Warehouse

Guo, J.; Tsang, L.; Josberger, E.G.; Wood, A.W.; Hwang, J.-N.; Lettenmaier, D.P.

2003-01-01

This paper presents an algorithm that estimates the spatial distribution and temporal evolution of snow water equivalent and snow depth based on passive remote sensing measurements. It combines the inversion of passive microwave remote sensing measurements via dense media radiative transfer modeling results with snow accumulation and melt model predictions to yield improved estimates of snow depth and snow water equivalent, at a pixel resolution of 5 arc-min. In the inversion, snow grain size evolution is constrained based on pattern matching by using the local snow temperature history. This algorithm is applied to produce spatial snow maps of Upper Rio Grande River basin in Colorado. The simulation results are compared with that of the snow accumulation and melt model and a linear regression method. The quantitative comparison with the ground truth measurements from four Snowpack Telemetry (SNOTEL) sites in the basin shows that this algorithm is able to improve the estimation of snow parameters.

Atmospheric correction for retrieving ground brightness temperature at commonly-used passive microwave frequencies.

PubMed

Han, Xiao-Jing; Duan, Si-Bo; Li, Zhao-Liang

2017-02-20

An analysis of the atmospheric impact on ground brightness temperature (Tg) is performed for numerous land surface types at commonly-used frequencies (i.e., 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz and 89.0 GHz). The results indicate that the atmosphere has a negligible impact on Tg at 1.4 GHz for land surfaces with emissivities greater than 0.7, at 6.93 GHz for land surfaces with emissivities greater than 0.8, and at 10.65 GHz for land surfaces with emissivities greater than 0.9 if a root mean square error (RMSE) less than 1 K is desired. To remove the atmospheric effect on Tg, a generalized atmospheric correction method is proposed by parameterizing the atmospheric transmittance τ and upwelling atmospheric brightness temperature Tba↑. Better accuracies with Tg RMSEs less than 1 K are achieved at 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz and 36.5 GHz, and worse accuracies with RMSEs of 1.34 K and 4.35 K are obtained at 23.8 GHz and 89.0 GHz, respectively. Additionally, a simplified atmospheric correction method is developed when lacking sufficient input data to perform the generalized atmospheric correction method, and an emissivity-based atmospheric correction method is presented when the emissivity is known. Consequently, an appropriate atmospheric correction method can be selected based on the available data, frequency and required accuracy. Furthermore, this study provides a method to estimate τ and Tba↑ of different frequencies using the atmospheric parameters (total water vapor content in observation direction Lwv, total cloud liquid water content Lclw and mean temperature of cloud Tclw), which is important for simultaneously determining the land surface parameters using multi-frequency passive microwave satellite data.

An inter-sensor comparison of the microwave signatures of Arctic sea ice

NASA Technical Reports Server (NTRS)

Onstott, R. G.

1986-01-01

Active and passive microwave and physical properties of Arctic sea ice in the marginal ice zone were measured during the summer. Results of an intercomparison of data acquired by an aircraft synthetic aperture radar, a passive microwave imager and a helicopter-mounted scatterometer indicate that early-to-mid summer sea ice microwave signatures are dominated by snowpack characteristics. Measurements show that the greatest contrast between thin first-year and multiyear sea ice occurs when operating actively between 5 and 10 GHz. Significant information about the state of melt of snow and ice is contained in the active and passive microwave signatures.

Study of LEO-SAT microwave link for broad-band mobile satellite communication system

NASA Technical Reports Server (NTRS)

Fujise, Masayuki; Chujo, Wataru; Chiba, Isamu; Furuhama, Yoji; Kawabata, Kazuaki; Konishi, Yoshihiko

1993-01-01

In the field of mobile satellite communications, a system based on low-earth-orbit satellites (LEO-SAT's) such as the Iridium system has been proposed. The LEO-SAT system is able to offer mobile telecommunication services in high-latitude areas. Rain degradation, fading and shadowing are also expected to be decreased when the system is operated at a high elevation angle. Furthermore, the propagation delay generated in the LEO-SAT system is less pronounced than that in the geostationary orbit satellite (GEO-SAT) system and, in voice services, the effect of the delay is almost negligible. We proposed a concept of a broad-band mobile satellite communication system with LEO-SAT's and Optical ISL. In that system, a fixed L-band (1.6/1.5 GHz) multibeam is used to offer narrow band service to the mobile terminals in the entire area covered by a LEO-SAT and steerable Ka-band (30/20 GHz) spot beams are used for the wide band service. In this paper, we present results of a study of LEO-SAT microwave link between a satellite and a mobile terminal for a broad-band mobile satellite communication system. First, the results of link budget calculations are presented and the antennas mounted on satellites are shown. For a future mobile antenna technology, we also show digital beamforming (DBF) techniques. DBF, together with modulation and/or demodulation, is becoming a key technique for mobile antennas with advanced functions such as antenna pattern calibration, correction, and radio interference suppression. In this paper, efficient DBF techniques for transmitting and receiving are presented. Furthermore, an adaptive array antenna system suitable for this LEO-SAT is presented.

Assessing the Relative Performance of Microwave-based Satellite Rain Rate Retrievals using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2008-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecast of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (AQUA) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparison with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellites is examined via comparisons with GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSRE over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm hr-1. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching

Analytical Retrieval of Global Land Surface Emissivity Maps at AMSR-E passive microwave frequencies

NASA Astrophysics Data System (ADS)

Norouzi, H.; Temimi, M.; Khanbilvardi, R.

2009-12-01

Land emissivity is a crucial boundary condition in Numerical Weather Prediction (NWP) modeling. Land emissivity is also a key indicator of land surface and subsurface properties. The objective of this study, supported by NOAA-NESDIS, is to develop global land emissivity maps using AMSR-E passive microwave measurements along with several ancillary data. The International Satellite Cloud Climatology Project (ISCCP) database has been used to obtain several inputs for the proposed approach such as land surface temperature, cloud mask and atmosphere profile. The Community Radiative Transfer Model (CRTM) has been used to estimate upwelling and downwelling atmospheric contributions. Although it is well known that correction of the atmospheric effect on brightness temperature is required at higher frequencies (over 19 GHz), our preliminary results have shown that a correction at 10.7 GHz is also necessary over specific areas. The proposed approach is based on three main steps. First, all necessary data have been collected and processed. Second, a global cloud free composite of AMSR-E data and corresponding ancillary images is created. Finally, monthly composting of emissivity maps has been performed. AMSR-E frequencies at 6.9, 10.7, 18.7, 36.5 and 89.0 GHz have been used to retrieve the emissivity. Water vapor information obtained from ISCCP (TOVS data) was used to calculate upwelling, downwelling temperatures and atmospheric transmission in order to assess the consistency of those derived from the CRTM model. The frequent land surface temperature (LST) determination (8 times a day) in the ISCCP database has allowed us to assess the diurnal cycle effect on emissivity retrieval. Differences in magnitude and phase between thermal temperature and low frequencies microwave brightness temperature have been noticed. These differences seem to vary in space and time. They also depend on soil texture and thermal inertia. The proposed methodology accounts for these factors and

Modelling the passive microwave signature from land surfaces: a review of recent results and application to the SMOS & SMAP soil moisture retrieval algorithms

USDA-ARS?s Scientific Manuscript database

Two passive microwave missions are currently operating at L-band to monitor surface soil moisture (SM) over continental surfaces. The SMOS sensor, based on an innovative interferometric technology enabling multi-angular signatures of surfaces to be measured, was launched in November 2009....

Using a Support Vector Machine and a Land Surface Model to Estimate Large-Scale Passive Microwave Temperatures over Snow-Covered Land in North America

NASA Technical Reports Server (NTRS)

Forman, Barton A.; Reichle, Rolf Helmut

2014-01-01

A support vector machine (SVM), a machine learning technique developed from statistical learning theory, is employed for the purpose of estimating passive microwave (PMW) brightness temperatures over snow-covered land in North America as observed by the Advanced Microwave Scanning Radiometer (AMSR-E) satellite sensor. The capability of the trained SVM is compared relative to the artificial neural network (ANN) estimates originally presented in [14]. The results suggest the SVM outperforms the ANN at 10.65 GHz, 18.7 GHz, and 36.5 GHz for both vertically and horizontally-polarized PMW radiation. When compared against daily AMSR-E measurements not used during the training procedure and subsequently averaged across the North American domain over the 9-year study period, the root mean squared error in the SVM output is 8 K or less while the anomaly correlation coefficient is 0.7 or greater. When compared relative to the results from the ANN at any of the six frequency and polarization combinations tested, the root mean squared error was reduced by more than 18 percent while the anomaly correlation coefficient was increased by more than 52 percent. Further, the temporal and spatial variability in the modeled brightness temperatures via the SVM more closely agrees with that found in the original AMSR-E measurements. These findings suggest the SVM is a superior alternative to the ANN for eventual use as a measurement operator within a data assimilation framework.

Impacts of Different Assimilation Methodologies on Crop Yield Estimates Using Active and Passive Microwave Dataset at L-Band

NASA Astrophysics Data System (ADS)

Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.

2013-12-01

Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield

The Global Precipitation Measurement (GPM) Microwave Imager (GMI): Instrument Overview and Early On-Orbit Performance

NASA Technical Reports Server (NTRS)

Draper, David W.; Newell, David A.; Wentz, Frank J.; Krimchansky, Sergey; Jackson, Gail

2015-01-01

The Global Precipitation Measurement (GPM) mission is an international satellite mission that uses measurements from an advanced radar/radiometer system on a core observatory as reference standards to unify and advance precipitation estimates made by a constellation of research and operational microwave sensors. The GPM core observatory was launched on February 27, 2014 at 18:37 UT in a 65? inclination nonsun-synchronous orbit. GPM focuses on precipitation as a key component of the Earth's water and energy cycle, and has the capability to provide near-real-time observations for tracking severe weather events, monitoring freshwater resources, and other societal applications. The GPM microwave imager (GMI) on the core observatory provides the direct link to the constellation radiometer sensors, which fly mainly in polar orbits. The GMI sensitivity, accuracy, and stability play a crucial role in unifying the measurements from the GPM constellation of satellites. The instrument has exhibited highly stable operations through the duration of the calibration/validation period. This paper provides an overview of the GMI instrument and a report of early on-orbit commissioning activities. It discusses the on-orbit radiometric sensitivity, absolute calibration accuracy, and stability for each radiometric channel. Index Terms-Calibration accuracy, passive microwave remote sensing, radiometric sensitivity.

Evaluation of monthly rainfall estimates derived from the special sensor microwave/imager (SSM/I) over the tropical Pacific

NASA Technical Reports Server (NTRS)

Berg, Wesley; Avery, Susan K.

1995-01-01

Estimates of monthly rainfall have been computed over the tropical Pacific using passive microwave satellite observations from the special sensor microwave/imager (SSM/I) for the period from July 1987 through December 1990. These monthly estimates are calibrated using data from a network of Pacific atoll rain gauges in order to account for systematic biases and are then compared with several visible and infrared satellite-based rainfall estimation techniques for the purpose of evaluating the performance of the microwave-based estimates. Although several key differences among the various techniques are observed, the general features of the monthly rainfall time series agree very well. Finally, the significant error sources contributing to uncertainties in the monthly estimates are examined and an estimate of the total error is produced. The sampling error characteristics are investigated using data from two SSM/I sensors and a detailed analysis of the characteristics of the diurnal cycle of rainfall over the oceans and its contribution to sampling errors in the monthly SSM/I estimates is made using geosynchronous satellite data. Based on the analysis of the sampling and other error sources the total error was estimated to be of the order of 30 to 50% of the monthly rainfall for estimates averaged over 2.5 deg x 2.5 deg latitude/longitude boxes, with a contribution due to diurnal variability of the order of 10%.

On-Chip Microwave Quantum Hall Circulator

NASA Astrophysics Data System (ADS)

Mahoney, A. C.; Colless, J. I.; Pauka, S. J.; Hornibrook, J. M.; Watson, J. D.; Gardner, G. C.; Manfra, M. J.; Doherty, A. C.; Reilly, D. J.

2017-01-01

Circulators are nonreciprocal circuit elements that are integral to technologies including radar systems, microwave communication transceivers, and the readout of quantum information devices. Their nonreciprocity arises from the interference of microwaves over the centimeter scale of the signal wavelength, in the presence of bulky magnetic media that breaks time-reversal symmetry. Here, we realize a completely passive on-chip microwave circulator with size 1 /1000 th the wavelength by exploiting the chiral, "slow-light" response of a two-dimensional electron gas in the quantum Hall regime. For an integrated GaAs device with 330 μ m diameter and about 1-GHz center frequency, a nonreciprocity of 25 dB is observed over a 50-MHz bandwidth. Furthermore, the nonreciprocity can be dynamically tuned by varying the voltage at the port, an aspect that may enable reconfigurable passive routing of microwave signals on chip.

Estimating ecosystem iso/anisohydry using microwave satellite data and its applications in ecohydrology

NASA Astrophysics Data System (ADS)

Li, Y.; Guan, K.; Gentine, P.; Konings, A. G.; Bhattacharya, A.; Meinzer, F. C.; Kimball, J. S.; Xu, X.; Anderegg, W.; McDowell, N. G.; Martínez-Vilalta, J.; Long, D. G.; Good, S. P.

2017-12-01

The concept of iso/anisohydry describes the degree to which plants regulate their water status, operating from isohydric with strict stomatal closure to anisohydric with greater stomatal conductance under drying conditions. Though some species-level measures of iso/anisohydry exist at limited locations, ecosystem scale information is still largely unavailable. In this study, we use diurnal observations from active (Ku-Band backscatter from QuikSCAT) and passive (X-band Vegetation Optical Depth [VOD] from AMSR-E) microwave satellite data to estimate global ecosystem iso/anisohydry. The two independent estimates from radar backscatter and VOD show good agreement at low and mid-latitudes but diverge at high latitudes. Grasslands, croplands, wetlands, and open shrublands are more anisohydric, whereas evergreen broadleaf and deciduous broadleaf forests are more isohydric. The direct validation with upscaled in-situ species iso/anisohydry estimates indicates that the VOD estimates have much better agreement than the backscatter in terms of their iso/anisohydry metrics. The indirect validation suggests that both estimates are consistent with prior knowledge that vegetation water status of anisohydric ecosystems more closely tracks environmental fluctuations of water availability and demand than their isohydric counterparts. The ecosystem level iso/anisohydry can be applied to reveal new insights into spatio-temporal ecosystem response to droughts. We conducted a case study to demonstrate the potential application of iso/anisohydry. We find that during the 2011 drought in US, over the drought affected region in the southern US, isohydric ecosystems experienced larger decline in productivity (NDVI and GPP) than anisohydric ones. However, during the 2012 drought in central US, both isohydric and anisohydric ecosystems exhibited similar decline in productivity.

A data-driven and physics-based single-pass retrieval of active-passive microwave covariation and vegetation parameters for the SMAP mission

NASA Astrophysics Data System (ADS)

Entekhabi, D.; Jagdhuber, T.; Das, N. N.; Baur, M.; Link, M.; Piles, M.; Akbar, R.; Konings, A. G.; Mccoll, K. A.; Alemohammad, S. H.; Montzka, C.; Kunstmann, H.

2016-12-01

The active-passive soil moisture retrieval algorithm of NASA's SMAP mission depends on robust statistical estimation of active-passive covariation (β) and vegetation structure (Γ) parameters in order to provide reliable global measurements of soil moisture on an intermediate level (9km) compared to the native resolution of the radiometer (36km) and radar (3km) instruments. These parameters apply to the SMAP radiometer-radar combination over the period of record that was cut short with the end of the SMAP radar transmission. They also apply to the current SMAP radiometer and Sentinel 1A/B radar combination for high-resolution surface soil moisture mapping. However, the performance of the statistically-based approach is directly dependent on the selection of a representative time frame in which these parameters can be estimated assuming dynamic soil moisture and stationary soil roughness and vegetation cover. Here, we propose a novel, data-driven and physics-based single-pass retrieval of active-passive microwave covariation and vegetation parameters for the SMAP mission. The algorithm does not depend on time series analyses and can be applied using minimum one pair of an active-passive acquisition. The algorithm stems from the physical link between microwave emission and scattering via conservation of energy. The formulation of the emission radiative transfer is combined with the Distorted Born Approximation of radar scattering for vegetated land surfaces. The two formulations are simultaneously solved for the covariation and vegetation structure parameters. Preliminary results from SMAP active-passive observations (April 13th to July 7th 2015) compare well with the time-series statistical approach and confirms the capability of this method to estimate these parameters. Moreover, the method is not restricted to a given frequency (applies to both L-band and C-band combinations for the radar) or incidence angle (all angles and not just the fixed 40° incidence

Transmission media appropriate laser-microwave solar power satellite system

NASA Astrophysics Data System (ADS)

Schäfer, C. A.; Gray, D.

2012-10-01

As a solution to the most critical problems with Solar power Satellite (SPS) development, a system is proposed which uses laser power transmission in space to a receiver high in the atmosphere that relays the power to Earth by either cable or microwave power transmission. It has been shown in the past that such hybrid systems have the advantages of a reduction in the mass of equipment required in geostationary orbit and avoidance of radio frequency interference with other satellites and terrestrial communications systems. The advantage over a purely laser power beam SPS is that atmospheric absorption is avoided and outages due to clouds and precipitation will not occur, allowing for deployment in the equatorial zone and guaranteeing year round operation. This proposal is supported by brief literature surveys and theoretical calculations to estimate crucial parameters in this paper. In relation to this concept, we build on a recently proposed method to collect solar energy by a tethered balloon at high altitude because it enables a low-cost start for bringing the first Watt of power to Earth giving some quick return on investment, which is desperately missing in the traditional SPS concept. To tackle the significant problem of GW-class SPSs of high launch cost per kg mass brought to space, this paper introduces a concept which aims to achieve a superior power over mass ratio compared to traditional satellite designs by the use of thin-film solar cells combined with optical fibres for power delivery. To minimise the aperture sizes and cost of the transmitting and receiving components of the satellite and high altitude receiver, closed-loop laser beam pointing and target tracking is crucial for pointing a laser beam onto a target area that is of similar size to the beam's diameter. A recently developed technique based on optical phase conjugation is introduced and its applicability for maintaining power transmission between the satellite and high altitude receiver is

A new modem for microwave time synchronisation via geosynchronous telecommunication satellites

NASA Astrophysics Data System (ADS)

Dienert, Michael

1992-06-01

A study illustrating the two way time transfer technique and describing the use of this technique with the MITREX (Microwave Time and Range Experiment) SATRE (Satellite Time and Range Experiment) modems is presented. The two way time transfer technique via geosynchronous telecom satellites is one of the most accurate methods for synchronization and comparison of remote clocks. Most of the unknown propagation delays can be eliminated by the two way principle. The use of a coherent spread spectrum technique with a truncated pseudonoise code offers a resolution better than 30 ps of the measured time interval. The receiver is built around a Delay Locked Loop (DLL), which correlates the received signal with the known PN sequence to derive the control signal of the loop. In the locked state both PN sequences are synchronous and tracking errors of less than 30 ps are possible. Results showing the accuracy of the modem depending on signal to noise ratio and variation of total input power levels are presented and show that the expected improvement of the jitter of the internal delay by an increase of the chip rate is possible.

Microwave Lightcraft concept

NASA Technical Reports Server (NTRS)

2004-01-01

Looking like an alien space ship or a flying saucer the Microwave Lightcraft is an unconventional launch vehicle approach for delivering payload to orbit using power transmitted via microwaves. Microwaves re beamed from either a ground station or an orbiting solar power satellite to the lightcraft. The energy received breaks air molecules into a plasma and a magnetohydrodynamic fanjet provides the lifting force. Only a small amount of propellant is required for circulation, attitude control and deorbit.

Rain-on-snow and ice layer formation detection using passive microwave radiometry: An arctic perspective

NASA Astrophysics Data System (ADS)

Langlois, A.; Royer, A.; Montpetit, B.; Johnson, C. A.; Brucker, L.; Dolant, C.; Richards, A.; Roy, A.

2015-12-01

With the current changes observed in the Arctic, an increase in occurrence of rain-on-snow (ROS) events has been reported in the Arctic (land) over the past few decades. Several studies have established that strong linkages between surface temperatures and passive microwaves do exist, but the contribution of snow properties under winter extreme events such as rain-on-snow events (ROS) and associated ice layer formation need to be better understood that both have a significant impact on ecosystem processes. In particular, ice layer formation is known to affect the survival of ungulates by blocking their access to food. Given the current pronounced warming in northern regions, more frequent ROS can be expected. However, one of the main challenges in the study of ROS in northern regions is the lack of meteorological information and in-situ measurements. The retrieval of ROS occurrence in the Arctic using satellite remote sensing tools thus represents the most viable approach. Here, we present here results from 1) ROS occurrence formation in the Peary caribou habitat using an empirically developed ROS algorithm by our group based on the gradient ratio, 2) ice layer formation across the same area using a semi-empirical detection approach based on the polarization ratio spanning between 1978 and 2013. A detection threshold was adjusted given the platform used (SMMR, SSM/I and AMSR-E), and initial results suggest high-occurrence years as: 1981-1982, 1992-1993; 1994-1995; 1999-2000; 2001-2002; 2002-2003; 2003-2004; 2006-2007; 2007-2008. A trend in occurrence for Banks Island and NW Victoria Island and linkages to caribou population is presented.

Passive microwave device applications of high T(c) superconducting thin films

NASA Astrophysics Data System (ADS)

Lyons, W. G.; Withers, R. S.

1990-11-01

Superconductors with a transition temperature T(c) from 40 K to 125 K are analyzed, with focus placed on their behavior around the boiling point of liquid nitrogen (77 K). It is shown that high-T(c) superconductors are similar to conventional type-II superconductors with paired holes instead of paired electrons. The nature of the electromagnetic response of a superconductor is illustrated with a two-fluid model, and surface resistance and conductor loss are assessed. Several microwave applications of high-T(c) superconductors are outlined including a six-pole dielectric loaded cavity filter used in multiplexers on current communication satellites and a four-pole superconducting filter. An implementation of a chirp filter using superconducting striplines with a cascaded array of backward-wave couplers to achieve a downchirp is presented as well as a 60-GHz phased antenna utilizing microstrip lines in the feed network.

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2010-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSRE over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2011-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU

Microwave radiative transfer studies of precipitation

NASA Technical Reports Server (NTRS)

Bringi, V. N.; Vivekanandan, J.; Turk, F. Joseph

1993-01-01

Since the deployment of the DMSP SSM/I microwave imagers in 1987, increased utilization of passive microwave radiometry throughout the 10 - 100 GHz spectrum has occurred for measurement of atmospheric constituents and terrestrial surfaces. Our efforts have focused on observations and analysis of the microwave radiative transfer behavior of precipitating clouds. We have focused particular attention on combining both aircraft and SSM/I radiometer imagery with ground-based multiparameter radar observations. As part of this and the past NASA contract, we have developed a multi-stream, polarized radiative transfer model which incorporates scattering. The model has the capability to be initialized with cloud model output or multiparameter radar products. This model provides the necessary 'link' between the passive microwave radiometer and active microwave radar observations. This unique arrangement has allowed the brightness temperatures (TB) to be compared against quantities such as rainfall, liquid/ice water paths, and the vertical structure of the cloud. Quantification of the amounts of ice and water in precipitating clouds is required for understanding of the global energy balance.

High Resolution Monthly Oceanic Rainfall Based on Microwave Brightness Temperature Histograms

NASA Astrophysics Data System (ADS)

Shin, D.; Chiu, L. S.

2005-12-01

A statistical emission-based passive microwave retrieval algorithm has been developed by Wilheit, Chang and Chiu (1991) to estimate space/time oceanic rainfall. The algorithm has been applied to Special Sensor Microwave Imager (SSM/I) data taken on board the Defense Meteorological Satellite Program (DMSP) satellites to provide monthly oceanic rainfall over 2.5ox2.5o and 5ox5o latitude-longitude boxes by the Global Precipitation Climatology Project-Polar Satellite Precipitation Data Center (GPCP-PSPDC, URL: http://gpcp-pspdc.gmu.edu/) as part of NASA's contribution to the GPCP. The algorithm has been modified and applied to the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data to produce a TRMM Level 3 standard product (3A11) over 5ox5o latitude/longitude boxes. In this study, the algorithm code is modified to retrieve rain rates at 2.5ox2.5o and 1ox1o resolutions for TMI. Two months of TMI data have been tested and the results compared with the monthly mean rain rates derived from TRMM Level 2 TMI rain profile algorithm (2A12) and the original 5ox5o data from 3A11. The rainfall pattern is very similar to the monthly average of 2A12, although the intensity is slightly higher. Details in the rain pattern, such as rain shadow due to island blocking, which were not discernible from the low resolution products, are now easily discernible. The spatial average of the higher resolution rain rates are in general slightly higher than lower resolution rain rates, although a Student-t test shows no significant difference. This high resolution product will be useful for the calibration of IR rain estimates for the production of the GPCP merge rain product.

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

1997-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an eleven year period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444 km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are converted to monthly rainfall amounts and then compared to those for non-tropical cyclone systems. The main results of this study indicate that: 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maxima in tropical cyclone rainfall are poleward (5 deg to 10 deg latitude depending on longitude) of the maxima in non-tropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% of the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the ITCZ; and 5) in general, tropical cyclone rainfall is enhanced during the El Nino years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites.

NASA Astrophysics Data System (ADS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

2000-10-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an 11-yr period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and interannual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important.To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444-km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain-rate observations are converted to monthly rainfall amounts and then compared with those for nontropical cyclone systems.The main results of this study indicate that 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maximum tropical cyclone rainfall is poleward (5°-10° latitude depending on longitude) of the maximum nontropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% off the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the Intertropical Convergence Zone; and 5) in general, tropical cyclone rainfall is enhanced during the El Niño years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

Quantifying the clear-sky bias of satellite-derived infrared LST

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Trigo, I. F.; DaCamara, C.

2017-12-01

Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.; Raymond, William H.

1990-01-01

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

Microwave anisotropies in the light of the data from the COBE satellite

NASA Technical Reports Server (NTRS)

Dodelson, Scott; Jubas, Jay M.

1993-01-01

The recent measurement of anisotropies in the cosmic microwave background by the Cosmic Background Explorer (COBE) satellite and the recent South Pole experiment offer an excellent opportunity to probe cosmological theories. We test a class of theories in which the universe today is flat and matter dominated, and primordial perturbations are adiabatic parameterized by an index n. In this class of theories the predicted signal in the South Pole experiment depends on n, the Hubble constant, and the baryon density. For n = 1 a large region of this parameter space is ruled out, but there is still a window open which satisfies constraints from COBE, the South Pole experiment, and big bang nucleosynthesis.

Electrically scanning microwave radiometer for Nimbus E

NASA Technical Reports Server (NTRS)

1973-01-01

An electronically scanning microwave radiometer system has been designed, developed, and tested for measurement of meteorological, geomorphological and oceanographic parameters from NASA/GSFC's Nimbus E satellite. The system is a completely integrated radiometer designed to measure the microwave brightness temperature of the earth and its atmosphere at a microwave frequency of 19.35 GHz. Calibration and environmental testing of the system have successfully demonstrated its ability to perform accurate measurements in a satellite environment. The successful launch and data acquisition of the Nimbus 5 (formerly Nimbus E) gives further demonstration to its achievement.

Comparison of stratospheric temperature profiles from a ground-based microwave radiometer with lidar, radiosonde and satellite data

NASA Astrophysics Data System (ADS)

Navas-Guzmán, Francisco; Kämpfer, Niklaus; Haefele, Alexander; Keckhut, Philippe; Hauchecorne, Alain

2015-04-01

temperature profiles retrieved from TEMPERA radiometer with the ones obtained from different techniques such as in-situ (radiosondes), active remote sensing (lidar) and passive remote sensing on board of Aura satellite (MLS) measurements. Moreover, a statistical analysis of the stratospheric temperature from TEMPERA measurements for three years of data have been performed.The results evidence the capability of TEMPERA radiometer to monitor the temperature in the stratosphere for a long-term. The detection of some singular sudden stratospheric warming (SSW) during the analyzed period shows the necessity of these continuous monitoring in order to measure and understand some important processes which could happen on a short time scale. References [1] D. W. Thompson, D. J. Seidel, W. J. Randel, C.-Z. Zou, A. H. Butler, C. Mears, A. Osso, C. Long, and R. Lin, "The mystery of recent stratospheric temperature trends," Nature, vol. 491, no. 7426, pp. 692-697, 2012. [2] O. Stähli, A. Murk, N. Kämpfer, C. Mätzler, and P. Eriksson, "Microwave radiometer to retrieve temperature profiles from the surface to the stratopause," Atmospheric Measurement Techniques Discussions, vol. 6, no. 2, pp. 2857-2905, 2013.

HTS thin films: Passive microwave components and systems integration issues

NASA Technical Reports Server (NTRS)

Miranda, F. A.; Chorey, C. M.; Bhasin, K. B.

1995-01-01

The excellent microwave properties of the High-Temperature-Superconductors (HTS) have been amply demonstrated in the laboratory by techniques such as resonant cavity, power transmission and microstrip resonator measurements. The low loss and high Q passive structures made possible with HTS, present attractive options for applications in commercial, military and spacebased systems. However, to readily insert HTS into these systems improvement is needed in such areas as repeatability in the deposition and processing of the HTS films, metal-contact formation, wire bonding, and overall film endurance to fabrication and assembly procedures. In this paper we present data compiled in our lab which illustrate many of the problems associated with these issues. Much of this data were obtained in the production of a space qualified hybrid receiver-downconverter module for the Naval Research Laboratory's High Temperature Superconductivity Space Experiment 2 (HTSSE-2). Examples of variations observed in starting films and finished circuits will be presented. It is shown that under identical processing the properties of the HTS films can degrade to varying extents. Finally, we present data on ohmic contacts and factors affecting their adhesion to HTS films, strength of wire bonds made to such contacts, and aging effects.

Active and Passive Microwave Determination of the Circulation and Characteristics of Weddell and Ross Sea Ice

NASA Technical Reports Server (NTRS)

Drinkwater, Mark R.; Liu, Xiang

2000-01-01

A combination of satellite microwave data sets are used in conjunction with ECMWF (Medium Range Weather Forecasts) and NCEP (National Center for Environment Prediction) meteorological analysis fields to investigate seasonal variability in the circulation and sea-ice dynamics of the Weddell and Ross Seas. Results of sea-ice tracking using SSM/I (Special Sensor Microwave Imager), Scatterometer and SAR images are combined with in-situ data derived from Argos buoys and GPS drifters to validate observed drift patterns. Seasonal 3-month climatologies of ice motion and drift speed variance illustrate the response of the sea-ice system to seasonal forcing. A melt-detection algorithm is used to track the onset of seasonal melt, and to determine the extent and duration of atmospherically-led surface melting during austral summer. Results show that wind-driven drift regulates the seasonal distribution and characteristics of sea-ice and the intensity of the cyclonic Gyre circulation in these two regions.

Assessment of the Barren Ground Caribou Die-off During Winter 2015-2016 Using Passive Microwave Observations

NASA Astrophysics Data System (ADS)

Dolant, C.; Montpetit, B.; Langlois, A.; Brucker, L.; Zolina, O.; Johnson, C. A.; Royer, A.; Smith, P.

2018-05-01

In summer 2016, more than 50 Arctic Barren Ground caribous were found dead on Prince Charles Island (Nunavut, Canada), a species recently classified as threatened. Neither predator nor sign of diseases was observed and reported. The main hypothesis is that caribous were not able to access food due to a very dense snow surface, created by a strong storm system in spring. Using satellite microwave data, a significant increase in brightness temperature polarization ratio at 19 and 37 GHz was observed in spring 2016 (60% higher than previous two winter seasons). Based on microwave radiative transfer simulations, such anomaly can be explained with a very dense snow surface. This is consistent with the succession of storms and strong winds highlighted in ERA-Interim over Prince Charles Island in spring 2016. Using several sources of data, this study shows that changes in snow conditions explain the caribou die-off due to restricted foraging.

Passive L-Band H Polarized Microwave Emission During the Corn Growth Cycle

NASA Astrophysics Data System (ADS)

Joseph, A. T.; van der Velde, R.; O'Neill, P. E.; Kim, E. J.; Lang, R. H.; Gish, T. J.

2012-12-01

Hourly L-band (1.4 GHz) horizontally (H) polarized brightness temperatures (TB's) measured during five episodes (more than two days of continuous measurements) of the 2002 corn growth cycle are analyzed. These TB measurements were acquired as a part of a combined active/passive microwave field campaign, and were obtained at five incidence and three azimuth angles relative to the row direction. In support of this microwave data collection, intensive ground sampling took place once a week. Moreover, the interpretation of the hourly TB's could also rely on the data obtained using the various automated instruments installed in the same field. In this paper, the soil moisture and temperature measured at fixed time intervals have been employed as input for the tau-omega model to reproduce the hourly TB. Through the calibration of the vegetation and surface roughness parameterizations, the impact of the vegetation morphological changes on the microwave emission and the dependence of the soil surface roughness parameter, hr, on soil moisture are investigated. This analysis demonstrates that the b parameter, appearing in the representation of the canopy opacity, has an angular dependence that varies throughout the growing period and also that the parameter hr increases as the soil dries in a portion of the dry-down cycle. The angular dependence of the b parameter imposes the largest uncertainty on TB simulations near senescence as the response of b to the incidence is also affected by the crop row orientation. On the other hand, the incorporation of a soil moisture dependent hr parameterization was responsible for the largest error reduction of TB simulations in the early growth cycle. A.T. Joseph, R. Van der Velde, P.E. O'Neill, R.H. Lang, and T. Gish, "Soil moisture retrieval during a corn growth cycle using L-band (1.6 GHz) radar observations", IEEE Transactions on Geoscience and Remote Sensing, vol. 46, DOI:10.1109/TGRS.2008.917214, Aug. 2008. M.C. Dobson, F.T. Ulaby, M

Program on application of communications satellites to educational development: Design of a 12 channel FM microwave receiver. [color television from communication satellites

NASA Technical Reports Server (NTRS)

Risch, C. O.; Rosenbaum, F. J.; Gregory, R. O.

1974-01-01

The design, fabrication, and performance of elements of a low cost FM microwave satellite ground station receiver is described. It is capable of accepting 12 contiguous color television equivalent bandwidth channels in the 11.72 to 12.2 GHz band. Each channel is 40 MHz wide and incorporates a 4 MHz guard band. The modulation format is wideband FM and the channels are frequency division multiplexed. Twelve independent CATV compatible baseband outputs are provided. The overall system specifications are first discussed, then consideration is given to the receiver subsystems and the signal branching network.

Machine Learning on Images: Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent

NASA Astrophysics Data System (ADS)

Dozier, J.; Tolle, K.; Bair, N.

2014-12-01

We have a problem that may be a specific example of a generic one. The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements. Several independent methods exist, but all are problematic. The remotely sensed date of disappearance of snow from each pixel can be combined with a calculation of melt to reconstruct the accumulated SWE for each day back to the last significant snowfall. Comparison with streamflow measurements in mountain ranges where such data are available shows this method to be accurate, but the big disadvantage is that SWE can only be calculated retroactively after snow disappears, and even then only for areas with little accumulation during the melt season. Passive microwave sensors offer real-time global SWE estimates but suffer from several issues, notably signal loss in wet snow or in forests, saturation in deep snow, subpixel variability in the mountains owing to the large (~25 km) pixel size, and SWE overestimation in the presence of large grains such as depth and surface hoar. Throughout the winter and spring, snow-covered area can be measured at sub-km spatial resolution with optical sensors, with accuracy and timeliness improved by interpolating and smoothing across multiple days. So the question is, how can we establish the relationship between Reconstruction—available only after the snow goes away—and passive microwave and optical data to accurately estimate SWE during the snow season, when the information can help forecast spring runoff? Linear regression provides one answer, but can modern machine learning techniques (used to persuade people to click on web advertisements) adapt to improve forecasts of floods and droughts in areas where more than one billion people depend on snowmelt for their water resources?

High-spatial-resolution passive microwave sounding systems

NASA Technical Reports Server (NTRS)

Staelin, D. H.; Rosenkranz, P. W.

1994-01-01

The principal contributions of this combined theoretical and experimental effort were to advance and demonstrate new and more accurate techniques for sounding atmospheric temperature, humidity, and precipitation profiles at millimeter wavelengths, and to improve the scientific basis for such soundings. Some of these techniques are being incorporated in both research and operational systems. Specific results include: (1) development of the MIT Microwave Temperature Sounder (MTS), a 118-GHz eight-channel imaging spectrometer plus a switched-frequency spectrometer near 53 GHz, for use on the NASA ER-2 high-altitude aircraft, (2) conduct of ER-2 MTS missions in multiple seasons and locations in combination with other instruments, mapping with unprecedented approximately 2-km lateral resolution atmospheric temperature and precipitation profiles, atmospheric transmittances (at both zenith and nadir), frontal systems, and hurricanes, (3) ground based 118-GHz 3-D spectral images of wavelike structure within clouds passing overhead, (4) development and analysis of approaches to ground- and space-based 5-mm wavelength sounding of the upper stratosphere and mesosphere, which supported the planning of improvements to operational weather satellites, (5) development of improved multidimensional and adaptive retrieval methods for atmospheric temperature and humidity profiles, (6) development of combined nonlinear and statistical retrieval techniques for 183-GHz humidity profile retrievals, (7) development of nonlinear statistical retrieval techniques for precipitation cell-top altitudes, and (8) numerical analyses of the impact of remote sensing data on the accuracy of numerical weather predictions; a 68-km gridded model was used to study the spectral properties of error growth.

Statistical characteristics of polar lows over the Nordic Seas based on satellite passive microwave data

NASA Astrophysics Data System (ADS)

Smirnova, J. E.; Zabolotskikh, E. V.; Bobylev, L. P.; Chapron, B.

2016-12-01

In this study polar lows over the Nordic Seas for the period of 1995-2008 have been detected and studied using the Special Sensor Microwave Imager (SSM/I) data. A new methodology for polar low detection and monitoring based on the analysis of the total atmospheric water vapor content (WVC) fields retrieved from SSM/I was used. Lifetimes, diameters, translation speeds, distances traveled, and intensities were estimated for the detected polar lows using SSM/I WVC, sea surface wind speed fields and infrared imagery. Over the Norwegian and Barents Seas, the polar low activity was found to be almost equal. A positive tendency in the total number of polar lows for the time period of 1995-2008 was detected.

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Microwave remote sensing of sea ice in the AIDJEX Main Experiment. [Arctic Ice Dynamics Joint Experiment

NASA Technical Reports Server (NTRS)

Campbell, W. J.; Wayenberg, J.; Ramseyer, J. B.; Ramseier, R. O.; Vant, M. R.; Weaver, R.; Redmond, A.; Arsenault, L.; Gloersen, P.; Zwally, H. J.

1978-01-01

A microwave remote sensing program of sea ice in the Beaufort Sea was conducted during the Arctic Ice Dynamics Joint Experiment (AIDJEX). Several types of both passive and active sensors were used to perform surface and aircraft measurements during all seasons of the year. In situ observations were made of physical properties (salinity, temperature, density, surface roughness), dielectric properties, and passive microwave measurements were made of first-year, multiyear, and first-year/multiyear mixtures. Airborne passive microwave measurements were performed with the electronically scanning microwave radiometer while airborne active microwave measurements were performed by synthetic aperture radar, X- and L-band radar, and a scatterometer.

Satellite observed global variations in ecosystem-scale plant water storage

NASA Astrophysics Data System (ADS)

Tian, F.; Wigneron, J. P.; Brandt, M.; Fensholt, R.

2017-12-01

Plant water storage is a key component in ecohydrological processes and tightly coupled with global carbon and energy budgets. Field measurements of individual trees have revealed diurnal and seasonal variations in plant water storage across different tree species and sizes. However, global estimation of plant water storage is challenged by up-scaling from individual trees to an ecosystem scale. The L-band passive microwaves are sensitive to water stored in the stems, branches and leaves, with dependence on the vegetation structure. Thus, the L-band vegetation optical depth (L-VOD) parameter retrieved from satellite passive microwave observations can be used as a proxy for ecosystem-scale plant water storage. Here, we employ the recently developed SMOS (Soil Moisture and Ocean Salinity) L-VOD dataset to investigate spatial patterns in global plant water storage and its diurnal and seasonal variations. In addition, we compare the spatiotemporal patterns between plant water storage and canopy greenness (i.e., enhanced vegetation indices, EVI) to gain ecohydrological insights among different territorial biomes, including boreal forest and tropical woodland. Generally, seasonal dynamics of plant water storage is much smaller than canopy greenness, yet the temporal coupling of these two traits is totally different between boreal and tropical regions, which could be related to their strategies in plant water regulation.

A Combined Infrared and Microwave Technique for Studying the Diurnal Variation of Rainfall over Amazonia

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Anagnostou, Emmanouil; Adler, Robert F.

1999-01-01

Over 10 years of continuous data from the Special Sensor microwave Imager (SSM/I) aboard a series of Defense Department satellites has made it possible to construct regional rainfall climatologies at high spatial resolution. Using the Goddard Profiling Algorithm (GPROF), monthly estimates of precipitation were made over the region of northern Brazil, including the Amazon Basin, for 1987 to 1998. GPROF is a physical approach to passive microwave precipitation retrieval, which uses the Goddard Cumulus Ensemble (cloud) model to establish prior probability densities of precipitation structures. Precipitation fields from GPROF were stratified into morning and evening satellite overpasses, and accumulated at monthly intervals at 0.5 degree spatial resolution. Important diurnal effects were noted in the analysis, the most pronounced being a land/sea breeze circulation along the northern coast of Brazil and a mountain/valley circulation along the Andes. There were also indications of morning rainfall maxima along the major rivers, and evening maxima between the rivers. The addition of simultaneous geosynchronous infrared (IR) data leads to the current technique, which takes advantage of the 30 minute sampling and 4 km spatial resolution of the infrared channel and the better physics of the microwave retrieval. The resultant IR method is subsequently used to derive the diurnal variability of rainfall over the Amazon basin, and further, to investigate the relative contribution from its convective and stratiform components.

Frequency band justifications for passive sensors, 1 to 10 GHz. [for monitoring earth resources and the environment

NASA Technical Reports Server (NTRS)

1976-01-01

Remote sensor systems operating in the microwave region of the frequency spectrum provide information unobtainable with basic imaging techniques such as photography, television, or multispectral imaging. The frequency allocation requirements for passive microwave sensors used in the earth exploration satellite and space research services are presented for: (1) agriculture, forestry, and range resources; (2) land use survey and mapping: (3) water resources; (4) weather and climate; (5) environmental quality; and (6) marine resources, estuarine and oceans. Because measurements are required simultaneously in multiple frequency bands to adequately determine values of some phenomena, the relationships between frequency bands are discussed. The various measurement accuracies, dynamic range, resolutions and frequency needs are examined. A band-by-band summary of requirements, unique aspects, and sharing analyses of the required frequency bands is included.

Satellite Data Simulator Unit: A Multisensor, Multispectral Satellite Simulator Package

NASA Technical Reports Server (NTRS)

Masunaga, Hirohiko; Matsui, Toshihisa; Tao, Wei-Kuo; Hou, Arthur Y.; Kummerow, Christian D.; Nakajima, Teruyuki; Bauer, Peter; Olson, William S.; Sekiguchi, Miho; Nakajima, Teruyuki

2010-01-01

Several multisensor simulator packages are being developed by different research groups across the world. Such simulator packages [e.g., COSP , CRTM, ECSIM, RTTO, ISSARS (under development), and SDSU (this article), among others] share overall aims, although some are targeted more on particular satellite programs or specific applications (for research purposes or for operational use) than others. The SDSU or Satellite Data Simulator Unit is a general-purpose simulator composed of Fortran 90 codes and applicable to spaceborne microwave radiometer, radar, and visible/infrared imagers including, but not limited to, the sensors listed in a table. That shows satellite programs particularly suitable for multisensor data analysis: some are single satellite missions carrying two or more instruments, while others are constellations of satellites flying in formation. The TRMM and A-Train are ongoing satellite missions carrying diverse sensors that observe clouds and precipitation, and will be continued or augmented within the decade to come by future multisensor missions such as the GPM and Earth-CARE. The ultimate goals of these present and proposed satellite programs are not restricted to clouds and precipitation but are to better understand their interactions with atmospheric dynamics/chemistry and feedback to climate. The SDSU's applicability is not technically limited to hydrometeor measurements either, but may be extended to air temperature and humidity observations by tuning the SDSU to sounding channels. As such, the SDSU and other multisensor simulators would potentially contribute to a broad area of climate and atmospheric sciences. The SDSU is not optimized to any particular orbital geometry of satellites. The SDSU is applicable not only to low-Earth orbiting platforms as listed in Table 1, but also to geostationary meteorological satellites. Although no geosynchronous satellite carries microwave instruments at present or in the near future, the SDSU would be

Sensitivity of Support Vector Machine Predictions of Passive Microwave Brightness Temperature Over Snow-covered Terrain in High Mountain Asia

NASA Astrophysics Data System (ADS)

Ahmad, J. A.; Forman, B. A.

2017-12-01

High Mountain Asia (HMA) serves as a water supply source for over 1.3 billion people, primarily in south-east Asia. Most of this water originates as snow (or ice) that melts during the summer months and contributes to the run-off downstream. In spite of its critical role, there is still considerable uncertainty regarding the total amount of snow in HMA and its spatial and temporal variation. In this study, the NASA Land Information Systems (LIS) is used to model the hydrologic cycle over the Indus basin. In addition, the ability of support vector machines (SVM), a machine learning technique, to predict passive microwave brightness temperatures at a specific frequency and polarization as a function of LIS-derived land surface model output is explored in a sensitivity analysis. Multi-frequency, multi-polarization passive microwave brightness temperatures as measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over the Indus basin are used as training targets during the SVM training process. Normalized sensitivity coefficients (NSC) are then computed to assess the sensitivity of a well-trained SVM to each LIS-derived state variable. Preliminary results conform with the known first-order physics. For example, input states directly linked to physical temperature like snow temperature, air temperature, and vegetation temperature have positive NSC's whereas input states that increase volume scattering such as snow water equivalent or snow density yield negative NSC's. Air temperature exhibits the largest sensitivity coefficients due to its inherent, high-frequency variability. Adherence of this machine learning algorithm to the first-order physics bodes well for its potential use in LIS as the observation operator within a radiance data assimilation system aimed at improving regional- and continental-scale snow estimates.

The Advanced Technology Microwave Sounder (ATMS): First Year On-Orbit

NASA Technical Reports Server (NTRS)

Kim, Edward J.

2012-01-01

The Advanced Technology Microwave Sounder (ATMS) is a new satellite microwave sounding sensor designed to provide operational weather agencies with atmospheric temperature and moisture profile information for global weather forecasting and climate applications. A TMS will continue the microwave sounding capabilities first provided by its predecessors, the Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit (AMSU). The first flight unit was launched a year ago in October, 2011 aboard the Suomi-National Polar-Orbiting Partnership (S-NPP) satellite, part of the new Joint Polar-Orbiting Satellite System (JPSS). Microwave soundings by themselves are the highest-impact input data used by Numerical Weather Prediction models; and A TMS, when combined with the Cross-track Infrared Sounder (CrIS), forms the Cross-track Infrared and Microwave Sounding Suite (CrIMSS). The microwave soundings help meet sounding requirements under cloudy sky conditions and provide key profile information near the surface. ATMS was designed & built by Aerojet Corporation in Azusa, California, (now Northrop Grumman Electronic Systems). It has 22 channels spanning 23-183 GHz, closely following the channel set of the MSU, AMSU-AI/2, AMSU-B, Microwave Humidity Sounder (MHS), and Humidity Sounder for Brazil (HSB). It continues their cross-track scanning geometry, but for the first time, provides Nyquist sample spacing. All this is accomplished with approximately V. the volume, Y, the mass, and Y, the power of the three AMSUs. A description will be given of its performance from its first year of operation as determined by post-launch calibration activities. These activities include radiometric calibration using the on-board warm targets and cold space views, and geolocation determination. Example imagery and zooms of specific weather events will be shown. The second ATMS flight model is currently under construction and planned for launch on the "Jl" satellite of the JPSS program in

Current Operational Use of and Future Needs for Microwave Imagery at NOAA

NASA Astrophysics Data System (ADS)

Goldberg, M.; McWilliams, G.; Chang, P.

2017-12-01

There are many applications of microwave imagery served by NOAA's operational products and services. They include the use of microwave imagery and derived products for monitoring precipitation, tropical cyclones, sea surface temperature under all weather conditions, wind speed, snow and ice cover, and even soil moisture. All of NOAA's line offices including the National Weather Service, National Ocean Service, National Marine Fisheries Service, and Office of Oceanic and Atmospheric Research rely on microwave imagery. Currently microwave imagery products used by NOAA come from a constellation of satellites that includes Air Force's Special Sensor Microwave Imager Sounder (SSMIS), the Japanese Advanced Microwave Scanning Radiometer (AMSR), the Navy's WindSat, and NASA's Global Precipitation Monitoring (GPM) Microwave Imager (GMI). Follow-on missions for SSMIS are very uncertain, JAXA approval for a follow-on to AMSR2 is still pending, and GMI is a research satellite (lacking high-latitude coverage) with no commitment for operational continuity. Operational continuity refers to a series of satellites, so when one satellite reaches its design life a new satellite is launched. EUMETSAT has made a commitment to fly a microwave imager in the mid-morning orbit. China and Russia have demonstrated on-orbit microwave imagers. Of utmost importance to NOAA, however, is the quality, access, and latency of the data This presentation will focus on NOAA's current requirements for microwave imagery data which, for the most part, are being fulfilled by AMSR2, SSMIS, and WindSat. It will include examples of products and applications of microwave imagery at NOAA. We will also discuss future needs, especially for improved temporal resolution which hopefully can be met by an international constellation of microwave imagers. Finally, we will discuss what we are doing to address the potential gap in imagery.

Day 1 for the Integrated Multi-Satellite Retrievals for GPM (IMERG) Data Sets

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K. L.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

2014-12-01

The Integrated Multi-satellitE Retrievals for GPM (IMERG) is designed to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG was developed to use GPM Core Observatory data as a reference for the international constellation of satellites of opportunity that constitute the GPM virtual constellation. Computationally, IMERG is a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design, development, testing, and current status. IMERG provides 0.1°x0.1° half-hourly data, and will be run at multiple times, providing successively more accurate estimates: 4 hours, 8 hours, and 2 months after observation time. In Day 1 the spatial extent is 60°N-S, for the period March 2014 to the present. In subsequent reprocessing the data will extend to fully global, covering the period 1998 to the present. Both the set of input data set retrievals and the IMERG system are substantially different than those used in previous U.S. products. The input passive microwave data are all being produced with GPROF2014, which is substantially upgraded compared to previous versions. For the first time, this includes microwave sounders. Accordingly, there is a strong need to carefully check the initial test data sets for performance. IMERG output will be illustrated using pre-operational test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. Finally, we will summarize the expected release of various output products, and the subsequent reprocessing sequence.

Microwave responses of the western North Atlantic

NASA Technical Reports Server (NTRS)

Stacey, J. M.; Girard, M. A.

1985-01-01

Features and objects in the Western North Atlantic Ocean - the Eastern Seaboard of the United States - are observed from Earth orbit by passive microwaves. The intensities of their radiated flux signatures are measured and displayed in color as a microwave flux image. The features of flux emitting objects such as the course of the Gulf Stream and the occurrence of cold eddies near the Gulf Stream are identified by contoured patterns of relative flux intensities. The flux signatures of ships and their wakes are displayed and discussed. Metal data buoys and aircraft are detected. Signal to clutter ratios and probabilities of detection are computed from their measured irradiances. Theoretical models and the range equations that explain passive microwave detection using the irradiances of natural sources are summarized.

Soil Moisture Active Passive (SMAP) Microwave Radiometer Radio-Frequency Interference (RFI) Mitigation: Initial On-Orbit Results

NASA Technical Reports Server (NTRS)

Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Johnson, Joel T.; Aksoy, Mustafa; Bringer, Alexandra

2015-01-01

The Soil Moisture Active Passive (SMAP) mission, launched in January 2015, provides global measurements of soil moisture using a microwave radiometer. SMAPs radiometer passband lies within the passive frequency allocation. However, both unauthorized in-band transmitters as well as out-of-band emissions from transmitters operating at frequencies adjacent to this allocated spectrum have been documented as sources of radio frequency interference (RFI) to the L-band radiometers on SMOS and Aquarius. The spectral environment consists of high RFI levels as well as significant occurrences of low level RFI equivalent to 0.1 to 10 K. The SMAP ground processor reports the antenna temperature both before and after RFI mitigation is applied. The difference between these quantities represents the detected RFI level. The presentation will review the SMAP RFI detection and mitigation procedure and discuss early on-orbit RFI measurements from the SMAP radiometer. Assessments of global RFI properties and source types will be provided, as well as the implications of these results for SMAP soil moisture measurements.

Machine Learning Algorithms for Automated Satellite Snow and Sea Ice Detection

NASA Astrophysics Data System (ADS)

Bonev, George

The continuous mapping of snow and ice cover, particularly in the arctic and poles, are critical to understanding the earth and atmospheric science. Much of the world's sea ice and snow covers the most inhospitable places, making measurements from satellite-based remote sensors essential. Despite the wealth of data from these instruments many challenges remain. For instance, remote sensing instruments reside on-board different satellites and observe the earth at different portions of the electromagnetic spectrum with different spatial footprints. Integrating and fusing this information to make estimates of the surface is a subject of active research. In response to these challenges, this dissertation will present two algorithms that utilize methods from statistics and machine learning, with the goal of improving on the quality and accuracy of current snow and sea ice detection products. The first algorithm aims at implementing snow detection using optical/infrared instrument data. The novelty in this approach is that the classifier is trained using ground station measurements of snow depth that are collocated with the reflectance observed at the satellite. Several classification methods are compared using this training data to identify the one yielding the highest accuracy and optimal space/time complexity. The algorithm is then evaluated against the current operational NASA snow product and it is found that it produces comparable and in some cases superior accuracy results. The second algorithm presents a fully automated approach to sea ice detection that integrates data obtained from passive microwave and optical/infrared satellite instruments. For a particular region of interest the algorithm generates sea ice maps of each individual satellite overpass and then aggregates them to a daily composite level, maximizing the amount of high resolution information available. The algorithm is evaluated at both, the individual satellite overpass level, and at the daily

Monitoring Freeze-Thaw States in the Pan-Arctic: Application of Microwave Remote Sensing to Monitoring Hydrologic and Ecological Processes

NASA Astrophysics Data System (ADS)

McDonald, K. C.; Kimball, J. S.

2004-12-01

The transition of the landscape between predominantly frozen and non-frozen conditions in seasonally frozen environments impacts climate, hydrological, ecological and biogeochemical processes profoundly. Satellite microwave remote sensing is uniquely capable of detecting and monitoring a range of related biophysical processes associated with the measurement of landscape freeze/thaw status. We present the development, physical basis, current techniques and selected hydrological applications of satellite-borne microwave remote sensing of landscape freeze/thaw states for the terrestrial cryosphere. Major landscape hydrological processes embracing the remotely-sensed freeze/thaw signal include timing and spatial dynamics of seasonal snowmelt and associated soil thaw, runoff generation and flooding, ice breakup in large rivers and lakes, and timing and length of vegetation growing seasons and associated productivity and trace gas exchange. Employing both active and passive microwave sensors, we apply a selection of temporal change classification algorithms to examine a variety of hydrologic processes. We investigate contemporaneous and retrospective applications of the QuikSCAT scatterometer, and the SSM/I and SMMR radiometers to this end. Results illustrate the strong correspondence between regional thawing, seasonal ice break up for rivers, and the springtime pulse in river flow. We present the physical principles of microwave sensitivity to landscape freeze/thaw state, recent progress in applying these principles toward satellite remote sensing of freeze/thaw processes over broad regions, and potential for future global monitoring of this significant phenomenon of the global cryosphere. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, and at the University of Montana, Missoula, under contract to the National Aeronautics and Space Administration.

Antarctic Iceberg Tracking Based on Time Series of Aqua AMSRE Microwave Brightness Temperature Measurements

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Peterson, Craig

2006-01-01

Observations of icebergs are identified as one of the requirements for the GEOSS (Global Earth Observation System of Systems) in the area of reducing loss of life and property from natural and human-induced disasters. However, iceberg observations are not included among targets in the GEOSS 10-Year Implementation Plan, and thus there is an unfulfilled need for iceberg detection and tracking in the near future. Large Antarctic icebergs have been tracked by the National Ice Center and by the academic community using a variety of satellite sensors including both passive and active microwave imagers, such as SSM/I (Special Sensor Microwave/Imager) deployed on the DMSP (Defense Meteorological Satellite Program) spacecraft. Improvements provided in recent years by NASA and non-NASA satellite radars, scatterometers, and radiometers resulted in an increased number of observed icebergs and even prompted a question: Is The Number of Antarctic Icebergs Really Increasing? [D.G. Long, J. Ballantyne, and C. Bertoia, Eos, Transactions of the American Geophysical Union 83 (42): 469 & 474, 15 October 2002]. AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System) represents an improvement over SSM/I, its predecessor. AMSR-E has more measurement channels and higher spatial resolution than SSM/I. For example, the instantaneous field of view of the AMSR-E s 89-GHz channels is 6 km by 4 km versus 16 km by 14 km for SSM/I s comparable 85-GHz channels. AMSR-E, deployed on the Aqua satellite, scans across a 1450-km swath and provides brightness temperature measurements with nearglobal coverage every one or two days. In polar regions, overlapping swaths generate coverage up to multiple times per day and allow for creation of image time series with high temporal resolution. Despite these advantages, only incidental usage of AMSR-E data for iceberg tracking has been reported so far, none in an operational environment. Therefore, an experiment was undertaken in the RPC

High-performance flexible microwave passives on plastic

NASA Astrophysics Data System (ADS)

Ma, Zhenqiang; Seo, Jung-Hun; Cho, Sang June; Zhou, Weidong

2014-06-01

We report the demonstration of bendable inductors, capacitors and switches fabricated on a polyethylene terephthalate (PET) substrate that can operate at high microwave frequencies. By employing bendable dielectric and single crystalline semiconductor materials, spiral inductors and metal-insulator-metal (MIM) capacitors with high quality factors and high resonance frequencies and single-pole, single-throw (SPST) switches were archived. The effects of mechanical bending on the performance of inductors, capacitors and switches were also measured and analyzed. We further investigated the highest possible resonance frequencies and quality factors of inductors and capacitors and, high frequency responses and insertion loss. These demonstrations will lead to flexible radio-frequency and microwave systems in the future.

An Algorithm to Generate Deep-Layer Temperatures from Microwave Satellite Observations for the Purpose of Monitoring Climate Change. Revised

NASA Technical Reports Server (NTRS)

Goldberg, Mitchell D.; Fleming, Henry E.

1994-01-01

An algorithm for generating deep-layer mean temperatures from satellite-observed microwave observations is presented. Unlike traditional temperature retrieval methods, this algorithm does not require a first guess temperature of the ambient atmosphere. By eliminating the first guess a potentially systematic source of error has been removed. The algorithm is expected to yield long-term records that are suitable for detecting small changes in climate. The atmospheric contribution to the deep-layer mean temperature is given by the averaging kernel. The algorithm computes the coefficients that will best approximate a desired averaging kernel from a linear combination of the satellite radiometer's weighting functions. The coefficients are then applied to the measurements to yield the deep-layer mean temperature. Three constraints were used in deriving the algorithm: (1) the sum of the coefficients must be one, (2) the noise of the product is minimized, and (3) the shape of the approximated averaging kernel is well-behaved. Note that a trade-off between constraints 2 and 3 is unavoidable. The algorithm can also be used to combine measurements from a future sensor (i.e., the 20-channel Advanced Microwave Sounding Unit (AMSU)) to yield the same averaging kernel as that based on an earlier sensor (i.e., the 4-channel Microwave Sounding Unit (MSU)). This will allow a time series of deep-layer mean temperatures based on MSU measurements to be continued with AMSU measurements. The AMSU is expected to replace the MSU in 1996.

Active and passive microwave measurements in Hurricane Allen

NASA Technical Reports Server (NTRS)

Delnore, V. E.; Bahn, G. S.; Grantham, W. L.; Harrington, R. F.; Jones, W. L.

1985-01-01

The NASA Langley Research Center analysis of the airborne microwave remote sensing measurements of Hurricane Allen obtained on August 5 and 8, 1980 is summarized. The instruments were the C-band stepped frequency microwave radiometer and the Ku-band airborne microwave scatterometer. They were carried aboard a NOAA aircraft making storm penetrations at an altitude of 3000 m and are sensitive to rain rate, surface wind speed, and surface wind vector. The wind speed is calculated from the increase in antenna brightness temperature above the estimated calm sea value. The rain rate is obtained from the difference between antenna temperature increases measured at two frequencies, and wind vector is determined from the sea surface normalized radar cross section measured at several azimuths. Comparison wind data were provided from the inertial navigation systems aboard both the C-130 aircraft at 3000 m and a second NOAA aircraft (a P-3) operating between 500 and 1500 m. Comparison rain rate data were obtained with a rain radar aboard the P-3. Evaluation of the surface winds obtained with the two microwave instruments was limited to comparisons with each other and with the flight level winds. Two important conclusions are drawn from these comparisons: (1) the radiometer is accurate when predicting flight level wind speeds and rain; and (2) the scatterometer produces well behaved and consistent wind vectors for the rain free periods.

Pre-Launch Radiometric Performance Characterization of the Advanced Technology Microwave Sounder on the Joint Polar Satellite System-1 Satellite

NASA Technical Reports Server (NTRS)

Smith, Craig K.; Kim, Edward; Leslie, R. Vincent; Lyu, Joseph; McCormick, Lisa M.; Anderson, Kent

2017-01-01

The Advanced Technology Microwave Sounder (ATMS) is a space-based, cross-track radiometer for operational atmospheric temperature and humidity sounding, utilizing 22 channels over a frequency range from 23 to 183 gigahertz. The ATMS for the Joint Polar Satellite System-1 has undergone two rounds of re-work in 2014-2015 and 2016, following performance issues discovered during and following thermal vacuum chamber (TVAC) testing at the instrument and observatory level. Final shelf-level testing, including measurement of pass band characteristics and spectral response functions, was completed in December 2016. Final instrument-level TVAC testing and calibration occurred during February 2017. Here we will describe the instrument-level TVAC calibration process, and illustrate with results from the final TVAC calibration effort.

Microwave Radiometer Technology Acceleration Mission (MiRaTA): Advancing Weather Remote Sensing with Nanosatellites

NASA Astrophysics Data System (ADS)

Cahoy, K.; Blackwell, W. J.; Bishop, R. L.; Erickson, N.; Fish, C. S.; Neilsen, T. L.; Stromberg, E. M.; Bardeen, J.; Dave, P.; Marinan, A.; Marlow, W.; Kingsbury, R.; Kennedy, A.; Byrne, J. M.; Peters, E.; Allen, G.; Burianek, D.; Busse, F.; Elliott, D.; Galbraith, C.; Leslie, V. V.; Osaretin, I.; Shields, M.; Thompson, E.; Toher, D.; DiLiberto, M.

2014-12-01

The Microwave Radiometer Technology Acceleration (MiRaTA) is a 3U CubeSat mission sponsored by the NASA Earth Science Technology Office (ESTO). Microwave radiometer measurements and GPS radio occultation (GPSRO) measurements of all-weather temperature and humidity provide key contributions toward improved weather forecasting. The MiRaTA mission will validate new technologies in both passive microwave radiometry and GPS radio occultation: (1) new ultra-compact and low-power technology for multi-channel and multi-band passive microwave radiometers, and (2) new GPS receiver and patch antenna array technology for GPS radio occultation retrieval of both temperature-pressure profiles in the atmosphere and electron density profiles in the ionosphere. In addition, MiRaTA will test (3) a new approach to spaceborne microwave radiometer calibration using adjacent GPSRO measurements. The radiometer measurement quality can be substantially improved relative to present systems through the use of proximal GPSRO measurements as a calibration standard for radiometric observations, reducing and perhaps eliminating the need for costly and complex internal calibration targets. MiRaTA will execute occasional pitch-up maneuvers so that the radiometer and GPSRO observations sound overlapping volumes of atmosphere through the Earth's limb. To validate system performance, observations from both microwave radiometer (MWR) and GPSRO instruments will be compared to radiosondes, global high-resolution analysis fields, other satellite observations, and to each other using radiative transfer models. Both the radiometer and GPSRO payloads, currently at TRL5 but to be advanced to TRL7 at mission conclusion, can be accommodated in a single 3U CubeSat. The current plan is to launch from an International Space Station (ISS) orbit at ~400 km altitude and 52° inclination for low-cost validation over a ~90-day mission to fly in 2016. MiRaTA will demonstrate high fidelity, well-calibrated radiometric

Past, Current and Future of the Advanced Microwave Scanning Radiometer (AMSR) Series

NASA Astrophysics Data System (ADS)

Kachi, M.; Maeda, T.; Ono, N.; Tomii, N.; Kasahara, M.; Mokuno, M.; Sobue, S.

2017-12-01

Due to its penetrating capability, passive microwave remote sensing provides all-weather observation of the Earth's surface through clouds, and has bulk sensitivity to atmospheric column and some land surface layers such as snow. The first AMSR series instrument on orbit was the AMSR for EOS (AMSR-E) provided to NASA's Aqua satellite launched in May 2002. AMSR-E had 1.6-m diameter antenna and 14 channels with V and H polarizations including surface-sensitive C-band (6.9-GHz) channels those were not available in previous passive microwave imagers. Instant Field Of View (IFOV) of AMSR-E is largely improved due to antenna size. This IFOV improvement mainly contribute to C-band channel since its IFOV is larger (75x43-km) even though bigger antenna size. The latest AMSR series instrument on orbit, AMSR-2, was launched in May 2012 on board the Global Change Observation Mission - Water (GCOM-W) satellite. The GCOM-W satellite was injected to the A-train orbit to keep observation continuities to AMSR-E and seek synergies with the other A-train constellation satellites. Antenna size of AMSR-2 is 2.0-m diameter with 16 channels. Channel set is almost identical to that of AMSR-E, but new 7.3-GHz channels are added along with previous 6.9-GHz channels to mitigate influence of Radio Frequency Interferences (RFIs) in brightness temperature. IFOV of AMSR-2 is also improved from AMSR-E due to larger antenna size. AMSR-2 has completed its 5-year designed mission life in May 2017, and continues scientific observations without any serious problem. Besides the 10-month gaps between AMSR-E and AMSR2, the AMSR series provide long-term high-resolution and highly-frequent global observation of water-related parameters over 15-year. Upon the success of AMSR series, we have started discussion of possible follow-on mission with various user communities as well as expansion of application of AMSR-2 and follow-on data in new fields. Highest priority from users is gap-less, in terms of both

Microwave remote sensing of sea ice in the AIDJEX Main Experiment

USGS Publications Warehouse

Campbell, W.J.; Wayenberg, J.; Ramseyer, J.B.; Ramseier, R.O.; Vant, M.R.; Weaver, R.; Redmond, A.; Arsenaul, L.; Gloersen, P.; Zwally, H.J.; Wilheit, T.T.; Chang, T.C.; Hall, D.; Gray, L.; Meeks, D.C.; Bryan, M.L.; Barath, F.T.; Elachi, C.; Leberl, F.; Farr, Tom

1978-01-01

During the AIDJEX Main Experiment, April 1975 through May 1976, a comprehensive microwave sensing program was performed on the sea ice of the Beaufort Sea. Surface and aircraft measurements were obtained during all seasons using a wide variety of active and passive microwave sensors. The surface program obtained passive microwave measurements of various ice types using four antennas mounted on a tracked vehicle. In three test regions, each with an area of approximately 1.5 ?? 104 m2, detailed ice crystallographic, dielectric properties, and brightness temperatures of first-year, multiyear, and first-year/multiyear mixtures were measured. A NASA aircraft obtained passive microwave measurements of the entire area of the AIDJEX manned station array (triangle) during each of 18 flights. This verified the earlier reported ability to distinguish first-year and multiyear ice types and concentration and gave new information on ways to observe ice mixtures and thin ice types. The active microwave measurements from aircraft included those from an X- and L-band radar and from a scatterometer. The former is used to study a wide variety of ice features and to estimate deformations, while both are equally usable to observe ice types. With the present data, only the scatterometer can be used to distinguish positively multiyear from first-year and various types of thin ice. This is best done using coupled active and passive microwave sensing. ?? 1978 D. Reidel Publishing Company.

Mapping Greenland's Firn Aquifer using L-band Microwave Radiometry

NASA Astrophysics Data System (ADS)

Miller, J.; Bringer, A.; Jezek, K. C.; Johnson, J. T.; Scambos, T. A.; Long, D. G.

2016-12-01

Greenland's recently discovered firn aquifer is one of the most interesting, yet still mysterious, components of the ice sheet system. Many open questions remain regarding timescales of refreezing and/or englacial drainage of liquid meltwater, and the connections of firn aquifers to the subglacial hydrological system. If liquid meltwater production at the surface of the Greenland ice sheet continues to increase, subsequent increases in the volume of mobile liquid meltwater retained within Greenland's firn aquifer may increase the possibility of crevasse-deepening via hydrofracture. Hydrofracture is an important component of supraglacial lake drainage leading to at least temporary accelerated flow velocities and ice sheet mass balance changes. Firn aquifers may also support hydrofracture-induced drainage and thus are potentially capable of significantly influencing ice sheet mass balance and sea level rise. Spaceborne L-band microwave radiometers provide an innovative tool for ice-sheet wide mapping of the spatiotemporal variability of Greenland's firn aquifer. Both refreezing and englacial drainage may be observable given the sensitivity of the microwave response to the upper surface of liquid meltwater retained within snow and firn pore space as well as the ability of L band instruments to probe the ice sheet from the surface to the firn-ice transition at pore close-off depth. Here we combine L-band (1.4 GHz) brightness temperature observations from multiple sources to demonstrate the potential of mapping firn aquifers on ice sheets using L-band microwave radiometry. Data sources include the interferometric MIRAS instrument aboard ESA's Soil Moisture and Ocean Salinity (SMOS) satellite mission and the radiometer aboard NASA's Soil Moisture Active Passive (SMAP) satellite mission. We will also present mulit-frequency L-band brightness temperature data (0.5-2 GHz) that will be collected over several firn aquifer areas on the Greenland ice sheet by the Ohio State

Satellite remote sensing over ice

NASA Technical Reports Server (NTRS)

Thomas, R. H.

1984-01-01

Satellite remote sensing provides unique opportunities for observing ice-covered terrain. Passive-microwave data give information on snow extent on land, sea-ice extent and type, and zones of summer melting on the polar ice sheets, with the potential for estimating snow-accumulation rates on these ice sheets. All weather, high-resolution imagery of sea ice is obtained using synthetic aperture radars, and ice-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on ice-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack ice and they give an indication of sea-ice characteristics.

Satellite remote sensing over ice

NASA Technical Reports Server (NTRS)

Thomas, R. H.

1986-01-01

Satellite remote sensing provides unique opportunities for observing ice-covered terrain. Passive-microwave data give information on snow extent on land, sea-ice extent and type, and zones of summer melting on the polar ice sheets, with the potential for estimating snow-accumulation rates on these ice sheets. All weather, high-resolution imagery of sea ice is obtained using synthetic aperture radars, and ice-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on ice-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack ice and they give an indication of sea-ice characteristics.

HTS thin films: Passive microwave components and systems integration issues

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miranda, F.A.; Chorey, C.M.; Bhasin, K.B.

1994-12-31

The excellent microwave properties of the High-Temperature-Superconductors (HTS) have been amply demonstrated in the laboratory by techniques such as resonant cavity, power transmission and microstrip resonator measurements. The low loss and high Q passive structures made possible with HTS, present attractive options for applications in commercial, military and space-based systems. However, to readily insert HTS into these systems improvement is needed in such areas as repeatability in the deposition and processing of the HTS films, metal-contact formation, wire bonding, and overall film endurance to fabrication and assembly procedures. In this paper we present data compiled in our lab which illustratemore » many of the problems associated with these issues. Much of this data were obtained in the production of a space qualified hybrid receiver-downconverter module for the Naval Research Laboratory`s High Temperature Superconductivity Space Experiment II (HTSSE-II). Examples of variations observed in starting films and finished circuits will be presented. It is shown that under identical processing the properties of the HTS films can degrade to varying extents. Finally, we present data on ohmic contacts and factors affecting their adhesion to HTS films, strength of wire bonds made to such contacts, and aging effects.« less

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and

Assessment of the Relative Accuracy of Hemispheric-Scale Snow-Cover Maps

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Kelly, Richard E.; Riggs, George A.; Chang, Alfred T. C.; Foster, James L.; Houser, Paul (Technical Monitor)

2001-01-01

There are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period October 23 - December 25, 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), which both rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, however discrepancies exist as to the location and extent of the snow cover among those maps. The large (approx. 30 km) footprint of the SSM/I data and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.32 million sq km in the amount of snow mapped using MODIS versus SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping ability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.

Classification of sea ice types with single-band (33.6 GHz) airborne passive microwave imagery

NASA Astrophysics Data System (ADS)

Eppler, Duane T.; Farmer, L. Dennis; Lohanick, Alan W.; Hoover, Mervyn

1986-09-01

During March 1983 extensive high-quality airborne passive Ka band (33.6 GHz) microwave imagery and coincident high-resolution aerial photography were obtained of ice along a 378-km flight line in the Beaufort Sea. Analysis of these data suggests that four classes of winter surfaces can be distinguished solely on the basis of 33.6-GHz brightness temperature: open water, frazil, old ice, and young/first-year ice. New ice (excluding frazil) and nilas display brightness temperatures that overlap the range of temperatures characteristic of old ice and, to a lesser extent, young/first-year ice. Scenes in which a new ice or nilas are present in appreciable amounts are subject to substantial errors in classification if static measures of Ka band radiometric brightness temperature alone are considered. Textural characteristics of nilas and new ice, however, differ significantly from textural features characteristic of other ice types and probably can be used with brightness temperature data to classify ice type in high-resolution single-band microwave images. In any case, open water is radiometrically the coldest surface observed in any scene. Lack of overlap between brightness temperatures characteristic of other surfaces indicates that estimates of the areal extent of open water based on only 33.6-GHz brightness temperatures are accurate.

The Goddard Profiling Algorithm (GPROF): Description and Current Applications

NASA Technical Reports Server (NTRS)

Olson, William S.; Yang, Song; Stout, John E.; Grecu, Mircea

2004-01-01

Atmospheric scientists use different methods for interpreting satellite data. In the early days of satellite meteorology, the analysis of cloud pictures from satellites was primarily subjective. As computer technology improved, satellite pictures could be processed digitally, and mathematical algorithms were developed and applied to the digital images in different wavelength bands to extract information about the atmosphere in an objective way. The kind of mathematical algorithm one applies to satellite data may depend on the complexity of the physical processes that lead to the observed image, and how much information is contained in the satellite images both spatially and at different wavelengths. Imagery from satellite-borne passive microwave radiometers has limited horizontal resolution, and the observed microwave radiances are the result of complex physical processes that are not easily modeled. For this reason, a type of algorithm called a Bayesian estimation method is utilized to interpret passive microwave imagery in an objective, yet computationally efficient manner.

MAPIR: An Airborne Polarmetric Imaging Radiometer in Support of Hydrologic Satellite Observations

NASA Technical Reports Server (NTRS)

Laymon, C.; Al-Hamdan, M.; Crosson, W.; Limaye, A.; McCracken, J.; Meyer, P.; Richeson, J.; Sims, W.; Srinivasan, K.; Varnevas, K.

2010-01-01

In this age of dwindling water resources and increasing demands, accurate estimation of water balance components at every scale is more critical to end users than ever before. Several near-term Earth science satellite missions are aimed at global hydrologic observations. The Marshall Airborne Polarimetric Imaging Radiometer (MAPIR) is a dual beam, dual angle polarimetric, scanning L band passive microwave radiometer system developed by the Observing Microwave Emissions for Geophysical Applications (OMEGA) team at MSFC to support algorithm development and validation efforts in support of these missions. MAPIR observes naturally-emitted radiation from the ground primarily for remote sensing of land surface brightness temperature from which we can retrieve soil moisture and possibly surface or water temperature and ocean salinity. MAPIR has achieved Technical Readiness Level 6 with flight heritage on two very different aircraft, the NASA P-3B, and a Piper Navajo.

The Variation of Tropical Cyclone Rainfall within the North Atlantic and Pacific as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward; Pierce, Harold; Adler, Robert

1999-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations in the North Atlantic and in three equal geographical regions of the North Pacific (i.e., Western, Central, and Eastern North Pacific). These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the 1987-1989, 1991-1998 North Atlantic and Pacific rainfall during June-November when tropical cyclones are most abundant. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from the Defence Meteorological Satellite Program (DMSP) Special Sensor Microwave/ Radiometer (SSM/I) observations within 444 km radius of the center of those North Atlantic and Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are then multiplied by the number of hours in a given month. Mean monthly rainfall amounts are also constructed for all the other North Atlantic and Pacific raining systems during this eleven year period for the purpose of estimating the geographical distribution and intensity of rainfall contributed by non-tropical cyclone systems. Further, the combination of the non-tropical cyclone and tropical cyclone (i.e., total) rainfall is constructed to delineate the fractional amount that tropical cyclones contributed to the total North Pacific rainfall.

Monitoring of "all-weather" evapotranspiration using optical and passive microwave remote sensing imagery over the River Source Region in Southwest China

NASA Astrophysics Data System (ADS)

Ma, Y.; Liu, S.

2017-12-01

Accurate estimation of surface evapotranspiration (ET) with high quality is one of the biggest obstacles for routine applications of remote sensing in eco-hydrological studies and water resource management at basin scale. However, many aspects urgently need to deeply research, such as the applicability of the ET models, the parameterization schemes optimization at the regional scale, the temporal upscaling, the selecting and developing of the spatiotemporal data fusion method and ground-based validation over heterogeneous land surfaces. This project is based on the theoretically robust surface energy balance system (SEBS) model, which the model mechanism need further investigation, including the applicability and the influencing factors, such as local environment, and heterogeneity of the landscape, for improving estimation accuracy. Due to technical and budget limitations, so far, optical remote sensing data is missing due to frequent cloud contamination and other poor atmospheric conditions in Southwest China. Here, a multi-source remote sensing data fusion method (ESTARFM: Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) method will be proposed through blending multi-source remote sensing data acquired by optical, and passive microwave remote sensors on board polar satellite platforms. The accurate "all-weather" ET estimation will be carried out for daily ET of the River Source Region in Southwest China, and then the remotely sensed ET results are overlapped with the footprint-weighted images of EC (eddy correlation) for ground-based validation.

A Prototype Hail Detection Algorithm and Hail Climatology Developed with the Advanced Microwave Sounding Unit (AMSU)

NASA Technical Reports Server (NTRS)