SeaWinds on QuikScat radiometric measurements and calibration

Jones, Walter L.; Mehershahi, Rushad J.; Zec, Josko; Long, D.G.

doi:10.1109/igarss.2000.858010

Cited by 14 publications

(7 citation statements)

References 1 publication

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“…The three main RTM components that contribute to the Tb captured by a space-borne sensor are the apparent brightness temperature from radiometer measurements, the ocean surface brightness temperature, and the ocean surface which reflects the sky brightness with some loss. This is an incoherent summation from the atmosphere and surface [4,9].…”

Section: Materials and Calibration Methodsmentioning

confidence: 99%

“…It combines active and passive Ku-band microwave measurements in dual-receiver channels. The backscatter is measured in a narrowband channel, and the brightness temperature (Tb) in a wider band channel, both from the ocean surface and through the intervening atmosphere [4]. The primary use of scatterometer measurements is wind vector retrieval over the sea surface.…”

Section: Introductionmentioning

confidence: 99%

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Radiometric Calibration of RapidScat Using the GPM Microwave Imager

Al-Sabbagh

Alsabah

Zec

2018

The 2nd International Electronic Conference on Remote Sensing

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Flying in a non-Sun-synchronous orbit, RapidScat is the first scatterometer capable of measuring ocean vector winds over the full diurnal cycle, instead of observing a given location at a fixed time of day. The non-Sun-synchronous orbit also enables the overlap with other satellite instruments that have been flying in Sun-synchronous orbits. RapidScat covered the latitude range between ±51.6° and was operated on board the International Space Station between September 2014 and August 2016. This paper describes the process that combines RapidScat's active and passive modes, simultaneously measuring both the radar surface backscatter (active mode) and the microwave emission determining the system noise temperature (passive mode). This work also presents the radiometric (passive mode) cross-calibration using the GPM (Global Precipitation Measurement) Microwave Imager (GMI) as a reference to eliminate the measurement biases of brightness temperature between a pair of radiometer channels that are operating at slightly different frequencies and incidence angles. Since the RapidScat operates at 13.4 GHz, and the closest GMI channel is 10.65 GHz, GMI brightness temperatures were normalized before the calibration. Normalization was based on the radiative transfer model (RTM) to yield an equivalent brightness temperature prior to the direct comparison with RapidScat. The seasonal and systematic biases were calculated for both polarizations as a function of geometry, atmospheric, and ocean brightness temperature models. The calculated biases may be used for measurement correction and for reprocessing of geophysical retrievals.

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Section: Materials and Calibration Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Radiometric Calibration of RapidScat Using the GPM Microwave Imager

Al-Sabbagh

Alsabah

Zec

2018

The 2nd International Electronic Conference on Remote Sensing

View full text Add to dashboard Cite

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“…Thus with the two pencil beams, it is possible to isolate the microwave emissions from the earth into elliptical footprints defined by the one‐way antenna pattern half‐power contours (approximately 35 km × 50 km). Details of the QRad instrument and its radiometric calibration are provided by Jones et al [2000] and Mehershahi [2000].…”

Section: Quikscat Radiometermentioning

confidence: 99%

“…Analysis has shown that this spectral ratio yields equivalent QRad T b 's accurate to within a few Kelvin [ Mehershahi , 2000; Jones et al , 2000]. However, for the given frequencies, this spectral ratio exhibits a nearly exponential dependence on atmospheric columnar water vapor as shown in Figure 5.…”

Section: Quikscat Radiometermentioning

confidence: 99%

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Oceanic rain rate estimates from the QuikSCAT Radiometer: A Global Precipitation Mission pathfinder

et al. 2005

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[1] The SeaWinds scatterometer, launched onboard the QuikSCAT satellite in 1999, measures global ocean vector winds. In addition to measuring radar backscatter, SeaWinds simultaneously measures the microwave brightness temperature of the atmosphere/surface, and this passive microwave measurement capability is known as the QuikSCAT Radiometer (QRad). This paper presents a QRad retrieval algorithm used to infer instantaneous oceanic rain rates. This statistical algorithm is trained using near-simultaneous observations of major rain events by QRad and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). Rain rate retrieval algorithm validation is presented through comparisons with independent rain measurements from the TMI 2A12 surface rain rates and the TRMM 3B42RT composite microwave and visible and infrared near-real time data product. Results demonstrate that QRad rain rate measurements are in good agreement with these independent microwave rain observations and superior to the visible/infrared rain estimates. Thus the QRad rain measurement time series is a valuable addition to the oceanic precipitation climatology that can be used to improve the diurnal estimation of the global rainfall, which is a goal for the future Global Precipitation Mission program. Moreover, the availability of QRad data will provide GPM users early access to learn to use less-precise rain measurements that will occur in the GPM era with the use of less-capable constellation satellites. Finally, these QRad rain estimates will be available in the planned data reprocessing (FY 2006) of QuikSCAT winds to improve the rain flagging of rain-contaminated oceanic wind vector retrievals.

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Physically based modeling of QuikSCAT SeaWinds passive microwave measurements for rain detection

et al. 2002

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[1] We present a method for detecting rain-contaminated wind vector cells in QuikSCAT SeaWinds scatterometer observations. This rain detection method uses passive measurements of microwave brightness temperature obtained as a signal processing byproduct from the standard SeaWinds active scatterometer measurements. The rain flag is developed theoretically first by calibrating the SeaWinds brightness temperatures using Special Sensor Microwave Imager (SSM/I) observations and then by using physically based simulations including the effects of both rain and ice precipitation. Rain retrievals are validated by comparison to SSM/I-observed rain rates and to other independently produced SeaWinds rain flags and produce rain maps that agree well with the SSM/I estimates. The rain detection method may be used to complement existing rain flags in the current operational QuikSCAT data product. In addition, an atmospheric correction algorithm was developed to dynamically adjust the backscatter coefficient measurements for variations in water vapor and cloud liquid water; results are not significantly different from the climatological correction currently implemented.

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SeaWinds on QuikScat radiometric measurements and calibration

Cited by 14 publications

References 1 publication

Radiometric Calibration of RapidScat Using the GPM Microwave Imager

Radiometric Calibration of RapidScat Using the GPM Microwave Imager

Oceanic rain rate estimates from the QuikSCAT Radiometer: A Global Precipitation Mission pathfinder

Physically based modeling of QuikSCAT SeaWinds passive microwave measurements for rain detection

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