Ground calibration of multifrequency scanning microwave radiometer (MSMR)

Misra, Tapan; Jha, Ayush; Putrevu, Deepak; Rao, Jiayu; Dave, Dilip B.; Rana, S. S.

doi:10.1109/36.992823

Cited by 21 publications

(7 citation statements)

References 6 publications

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“…When the brightness temperature exceeded 320 K, the data processing procedure set it to 320 K, which marked the data point as being a saturated observation. Data analysis reported by Misra et al (2002) during the post launch period confirmed that the calibration coefficients were correct. However, our review of numerous MSMR datasets showed that saturation of the MSMR observations did occasionally occur (figure 1).…”

Section: Oceansat-1/msmr and Data Descriptionsupporting

confidence: 73%

“…Differences in the atmospheric transmissivity at 18.0 GHz and 19.4 GHz cannot be ignored under the same water vapour condition. Misra et al (2002) had reported that the MSMR calibration coefficients were correct after launch. However, large biases between the MSMR and TMI measured brightness temperatures were found.…”

Section: Comparison Of Msmr and Tmi Brightness Temperaturesmentioning

confidence: 97%

“…The MSMR was designed to measure brightness temperature within the range of 78-320 K. Ground calibrations, which were conducted before launch, showed that the accuracies of MSMR brightness temperatures at all four frequencies were higher than 0.5 K at an ambient temperature of 283 K (Misra et al 2002). For almost all conditions of interest, the land surface brightness temperature should fall within this range.…”

Section: Oceansat-1/msmr and Data Descriptionmentioning

confidence: 99%

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Evaluation of the Oceansat‐1 Multi‐frequency Scanning Microwave Radiometer and its potential for soil moisture retrieval

Wen

Jackson

Bindlish

et al. 2006

International Journal of Remote Sensing

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The Multi-frequency Scanning Microwave Radiometer (MSMR) aboard the Indian Space Research Organization-Oceansat-1 platform measured land surface brightness temperature at a C-band frequency and provided an opportunity for exploring large-scale soil moisture retrieval during its two-year period of operation. These data may provide a valuable extension to the Scanning Multichannel Microwave Radiometer (SMMR) and the Advanced Microwave Scanning Radiometer (AMSR) since they covered a portion of the time period between the two missions. This investigation was one of the first to utilize the MSMR data for a land application and, as a result, several data quality issues had to be addressed. These included geolocation accuracy, calibration (particularly over land), erroneous data, and the significance of anthropogenic radio-frequency interference (RFI). Calibration of the low frequency channels was evaluated using inter-comparisons between the Tropical Rainfall Measuring Mission/Microwave Imager (TRMM/ TMI) and the MSMR brightness temperatures. Biases (TMI T B .MSMR T B ) of 3.4 and 3.6 K were observed over land for the MSMR 10.65 GHz horizontal and vertical polarization channels, respectively. These results suggested that additional calibration of the MSMR data was required. Comparisons between the MSMR measured brightness temperature and ground measured volumetric soil moisture collected during the South Great Plain experiment (SGP99) indicated that the lower frequency and horizontal polarization observations had higher sensitivity to soil moisture. Using a previously developed soil emission model, multi-temporal regional soil moisture distributions were retrieved for the continental United States. Comparisons between the MSMR based soil moisture and ground measured volumetric soil moisture indicated a standard error of estimate of 0.052 m 3 /m 3 .

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Section: Oceansat-1/msmr and Data Descriptionsupporting

confidence: 73%

Section: Comparison Of Msmr and Tmi Brightness Temperaturesmentioning

confidence: 97%

Section: Oceansat-1/msmr and Data Descriptionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of the Oceansat‐1 Multi‐frequency Scanning Microwave Radiometer and its potential for soil moisture retrieval

Wen

Jackson

Bindlish

et al. 2006

International Journal of Remote Sensing

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show abstract

“…The 6.6 GHz Tbs and thereby derived GPDs are available only at 150 km grid, whereas 10 GHz Tbs and thereby derived GPDs are available at 75 & 150 Km grids. The operationally derived geophysical parameters from MSMR are wind speed, cloud liquid water, water vapour and surface temperatures over the global oceans [ Gohil et al , 2000; Mishra et al , 2002] are well validated using both in situ [ Sharma et al , 2003] and other satellite data [ Varma et al , 2002a]. Varma et al [2002b, 2003] demonstrated use of Multichannel Passive Microwave Radiometer (MSMR) onboard Indian Remote Sensing Satellite (IRS‐P4) for rain rate measurement.…”

Section: Introductionmentioning

confidence: 99%

Distribution and intraseasonal variability of rain over Indian Oceanic region from Indian Remote Sensing Satellite IRS‐P4 Multifrequency Scanning Microwave Radiometer

et al. 2003

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[1] Multifrequency Scanning Microwave Radiometer (MSMR) onboard Indian Remote Sensing Satellite (IRS-P4) has been utilized for measurement of precipitation over Indian Oceanic region. MSMR-derived monthly rain rates for the month of August for three consecutive years are compared with that from TMI and PR. A reasonably good agreement is found. Rain distributions are presented for three seasons, namely, premonsoon (February-May), monsoon (June-September), and postmonsoon (OctoberJanuary) for the entire period of MSMR from June 1999 to September 2001. The yearto-year difference in the three seasons is found in agreement with the weather reports. Latitudinal distribution of the MSMR-derived rain rate for the Arabian Sea and the Bay of Bengal and for the entire study area are analyzed and are found to be in good agreement with climatology. Furthermore, starting from 60°E longitude up to 95°E, at every 5°i nterval, latitudinal distribution of rain rate is plotted for the three monsoon seasons. It is found that the vigor of monsoon rain begins building up between 65°and 70°E and goes beyond 95°E. A time series and wavelet analysis of daily rain rate is presented for monsoon seasons of three consecutive years. Wavelet analysis clearly shows the presence of long waves of 30-60 and 10-20 day oscillations and also of synoptic scale of 3-6 day oscillations in the monsoon rain. Furthermore, Hovmoller diagrams of daily rain over the northern Bay of Bengal are analyzed for monsoon seasons of three years, and some northward propagation of rain is reported.

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“…MSMR is basically a four frequency (6.6, 10.6, 18 and 21 GHz), dual polarisation (V & H) passive microwave radiometer observing the earth and its atmosphere from an altitude of 720 km. An overview of ground calibration methodology and expected performance of the onboard sensors is given in Misra et al (2002). The orbital characteristics of the IRS-P4 satellite result in near global coverage, with a repeat cycle of two days.…”

Section: Irs P4 Msmrmentioning

confidence: 99%

Surface winds in The Arabian Sea from MSMR — an Empirical approach

Parekh

Sarkar

Ravichandran

2005

J Indian Soc Remote Sens

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Multi-channel Scanning Microwave Radiometer (MSMR) onboard IRS P4 (Oceansat I) measured Brightness Temperature data of the different bands are found sensitive to the surface and the overlying atmosphere to different degrees. A judicious combination of multi-channel data can provide such oceanic/atmospheric parameters as surface wind speed, sea surface temperature, water vapour in the marine atmosphere, etc. This paper highlights results obtained in relation to surface wind speed. Co-location and concurrence of several ocean data buoys in the Arabian Sea with MSMR observations allowed empirical construction of D-matrix coefficients for surface wind speed. With both MSMR and the Arabian Sea buoys functioning for. the period of one and a half year (June, 1999 to December, 2000 without interruptions provided a large database. All channels are found to exhibit moderate sensitivity to surface wind speed. MSMR data in the immediate vicinity (within 150 kin) of the buoy locations and within a time window of one hour were used. A multi-channel linear equation for surface wind speed was subsequently derived. The equation was subjected to tests with independent data set for the period January -June 2001 over the Arabian Sea and found to be moderately accurate. The empirical equation is expected to be useful for regional applications over the Arabian Sea and over regions closer to west coasts, which might have been flagged out in the operational geophysical data stream. An interesting subset of data revealed the wind signatures of the May 2001 cyclone in the Arabian Sea.

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Ground calibration of multifrequency scanning microwave radiometer (MSMR)

Cited by 21 publications

References 6 publications

Evaluation of the Oceansat‐1 Multi‐frequency Scanning Microwave Radiometer and its potential for soil moisture retrieval

Evaluation of the Oceansat‐1 Multi‐frequency Scanning Microwave Radiometer and its potential for soil moisture retrieval

Distribution and intraseasonal variability of rain over Indian Oceanic region from Indian Remote Sensing Satellite IRS‐P4 Multifrequency Scanning Microwave Radiometer

Surface winds in The Arabian Sea from MSMR — an Empirical approach

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