MT-MADRAS brightness temperature analysis for terrain characterization and land surface microwave emissivity estimation

This article reports the potential of the ‘MADRAS’ payload on-board the Megha-Tropiques satellite for land surface studies. The analysis has been divided into two parts as application of MADRAS data for studying the land surface properties and estimation of microwave emissivity directly from MADRAS brightness temperature (TB) data by applying an in-house developed Microwave Radiative Transfer Computation Code. The derived emissivity is further used to characterize the microwave emissivity of different land surface classes. The polarization difference (PD) parameters, the difference between horizontal (H-) and vertical (V-) polarization of TBs at 18 and 36 GHz clearly discern surface features of different surface classes such as deserts, arid/semi-arid an d vegetated regions. Land surface microwave emissivity for MADRAS channels is derived on a global basis. These are inter-compared with the emissivity derived from the operational TRMM Microwave Imager and are in reasonably good agreement. The analysis based on emissivity shows spectral variation for different surface classes

Global Land Surface Emissivity Estimation From AMSR2 Observations

A reliable estimate of emissivity is critical for a wide range of applications for the atmosphere, the biosphere, the lithosphere, the cryosphere, and the hydrosphere. This study uses three years (August 2012 – July 2015) of data from the Advanced Microwave Scanning Radiometer-2 (AMSR2) sensor that is onboard the Global Change Observation Mission 1st Water (GCOM-W1) satellite to explore estimates of instantaneous global land emissivity. A method is adopted to remove the known inconsistency in penetration depths between microwave brightness temperatures and infrared-based ancillary data that could cause differences between day and night emissivity estimates. After removing the diurnal atmospheric effects, the resulting retrieved cloud-free land emissivities realistically represent well-known large-scale features. As expected, the polarization differences of estimated emissivities show noticeable seasonal variations over the deciduous woodland and grassland regions due to changes in vegetation density. The potential of estimated emissivities for high-latitude snow detection and freeze/thaw states identification is also demonstrated

The sensitivity of land emissivity estimates from AMSR-E at C and X bands to surface properties

Microwave observations at low frequencies exhibit more sensitivity to surface and subsurface properties with little interference from the atmosphere. The objective of this study is to develop a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) and to investigate its sensitivity to land surface properties. The developed product complements existing land emissivity products from SSM/I and AMSU by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C- and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, are obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties are obtained from the TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. A sensitivity test confirms the small effect of the atmosphere but shows that skin temperature accuracy can significantly affect emissivity estimates. Retrieved emissivities at C- and X-bands and their polarization differences exhibit similar patterns of variation with changes in land cover type, soil moisture, and vegetation density as seen at SSM/I-like frequencies (Ka and Ku bands). The emissivity maps from AMSR-E at these higher frequencies agree reasonably well with the existing SSM/I-based product. The inherent discrepancy introduced by the difference between SSM/I and AMSR-E frequencies, incidence angles, and calibration has been assessed. Significantly greater standard deviation of estimated emissivities compared to SSM/I land emissivity product was found over desert regions. Large differences between emissivity estimates from ascending and descending overpasses were found at lower frequencies due to the inconsistency between thermal IR skin temperatures and passive microwave brightness temperatures which can originate from below the surface. The mismatch between day and night AMSR-E emissivities is greater than ascending and descending differences of SSM/I emissivity. This is because of unique orbit time of AMSR-E (01:30 a.m./p.m. LT) while other microwave sensors have orbit time of 06:00 to 09:00 (a.m./p.m.). This highlights the importance of considering the penetration depth of the microwave signal and diurnal variability of the temperature in emissivity retrieval. The effect of these factors is greater for AMSR-E observations than SSM/I observations, as AMSR-E observations exhibit a greater difference between day and night measures. This issue must be addressed in future studies to improve the accuracy of the emissivity estimates especially at AMSR-E lower frequencies

The Sensitivity of Land Emissivity Estimates From AMSR-E as C and X Bands to Surface Properties

Microwave observations at low frequencies exhibit more sensitivity to surface and subsurface properties with little interference from the atmosphere. The objective of this study is to develop a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) and to investigate its sensitivity to land surface properties. The developed product complements existing land emissivity products from SSM/I and AMSU by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C- and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, are obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties are obtained from the TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. A sensitivity test confirms the small effect of the atmosphere but shows that skin temperature accuracy can significantly affect emissivity estimates. Retrieved emissivities at C- and X-bands and their polarization differences exhibit similar patterns of variation with changes in land cover type, soil moisture, and vegetation density as seen at SSM/I-like frequencies (Ka and Ku bands). The emissivity maps from AMSR-E at these higher frequencies agree reasonably well with the existing SSM/I-based product. The inherent discrepancy introduced by the difference between SSM/I and AMSR-E frequencies, incidence angles, and calibration has been assessed. Significantly greater standard deviation of estimated emissivities compared to SSM/I land emissivity product was found over desert regions. Large differences between emissivity estimates from ascending and descending overpasses were found at lower frequencies due to the inconsistency between thermal IR skin temperatures and passive microwave brightness temperatures which can originate from below the surface. The mismatch between day and night AMSR-E emissivities is greater than ascending and descending differences of SSM/I emissivity. This is because of unique orbit time of AMSR-E (01:30 a.m./p.m. LT) while other microwave sensors have orbit time of 06:00 to 09:00 (a.m./p.m.). This highlights the importance of considering the penetration depth of the microwave signal and diurnal variability of the temperature in emissivity retrieval. The effect of these factors is greater for AMSR-E observations than SSM/I observations, as AMSR-E observations exhibit a greater difference between day and night measures. This issue must be addressed in future studies to improve the accuracy of the emissivity estimates especially at AMSR-E lower frequencies

Microwave land emissivity calculations using AMSU measurements

http://ieeexplore.ieee.org/iel5/36/30753/01424271.pd

Passive millimeter-wave retrieval of global precipitation utilizing satellites and a numerical weather prediction model

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 229-234).This thesis develops and validates the MM5/TBSCAT/F([lambda]) model, composed of a mesoscale numerical weather prediction (NWP) model (MM5), a two-stream radiative transfer model (TBSCAT), and electromagnetic models for icy hydrometeors (F([lambda])), to be used as a global precipitation ground-truth for evaluating alternative millimeter-wave satellite designs and for developing methods for millimeter-wave precipitation retrieval and assimilation. The model's predicted millimeter-wave atmospheric radiances were found to statistically agree with those observed by satellite instruments [Advanced Microwave Sounding Unit-A/B (AMSU-A/B)] on the United States National Ocean and Atmospheric Administration NOAA-15, -16, and -17 satellites over 122 global representative storms. Whereas such radiance agreement was found to be sensitive to assumptions in MM5 and the radiative transfer model, precipitation retrieval accuracies predicted using the MM5/TBSCAT/F([lambda]) model were found to be robust to the assumptions.(cont.) Appropriate specifications for geostationary microwave sounders and their precipitation retrieval accuracies were studied. It was found that a 1.2-m micro-scanned filled-aperture antenna operating at 118/166/183/380/425 GHz, which is relatively inexpensive, simple to build, technologically mature, and readily installed on a geostationary satellite, could provide useful observation of important global precipitation with ~20-km resolution every 15 minutes. AMSU global precipitation retrieval algorithms for retrieving surface precipitation rate, peak vertical wind, and water-paths for rainwater, snow, graupel, cloud water, cloud ice, and the sum of rainwater, snow, and graupel, over non-icy surfaces were developed separately using a statistical ensemble of global precipitation predicted by the MM5/TBSCAT/F([lambda]) model. Different algorithms were used for land and sea, where principal component analysis was used to attenuate unwanted noises, such as surface effects and angle dependence. The algorithms were found to perform reasonably well for all types of precipitation as evaluated against MM5 ground-truth. The algorithms also work over land with snow and sea ice, but with a strong risk of false detections. AMSU surface precipitation rates retrieved using the algorithm developed in this thesis reasonably agree with those retrieved for the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) aboard the Aqua satellite over both land and sea.(cont.) Surface precipitation rates retrieved using the Advanced Microwave Sounding Unit (AMSU) aboard NOAA-15 and -16 satellites were further compared with four similar products derived from other systems that also observed the United States Great Plains (USGP) during the summer of 2004. These systems include AMSR-E aboard the Aqua satellite, the Special Sensor Microwave/Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) F-13, -14, and -15 satellites, the passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) aboard the TRMM satellite, and a surface precipitation rate product (NOWRAD), produced and marketed by Weather Services International Corporation (WSI) using observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) systems of the Next-Generation Weather Radar (NEXRAD) program. The results show the reasonable agreement among these surface precipitation rate products where the difference is mostly in the retrieval resolution, which depends on instruments' characteristics. A technique for assimilating precipitation information from observed millimeter-wave radiances to MM5 model was proposed. Preliminary study shows that wind and other correction techniques could help align observations at different times so that information from observed radiances is used at appropriate locations.by Chinnawat Surussavadee.Ph.D