K. Ahmad

Precipitation measurements using the QuikSCAT Radiometer

Microwave brightness temperatures are obtained from the SeaWinds scatterometer on the QuikSCAT satellite. These QuikSCAT Radiometer (QRad) measurements are used to infer instantaneous oceanic rain rates using a statistical retrieval algorithm that is based upon collocated TMI measurements. QRad instantaneous rain rate measurements have been binned in 0.5 hour local time windows onto a 0.5/spl deg//spl times/0.5/spl deg/ ocean grid. Also, an average rain rate product is produced, where QRad instantaneous rain rates have been averaged for five-day intervals (pentads) in the 0.5 hour local time windows. The scientific utility of QRad rain measurements is that they provide increased temporal and spatial sampling, which complements that provided by the TRMM Microwave Imager (TMI) and the Special Sensor Microwave Imagers (SSMIs) on the three DMSP satellites. Examples for the year 2000 are presented with corresponding rain rate measurements derived from TMI and SSMI. The results demonstrate that QRad rain measurements agree well with these independent rain observations.

QuikSCAT Radiometer (QRad) Rain Rates Level 2B Data Product

The scatterometer SeaWinds onboard the QuikSCAT satellite measures the ocean normalized radar cross section to infer the surface wind vector. In addition, SeaWinds simultaneously measures the polarized microwave brightness temperature of the ocean/atmosphere, and this passive microwave measurement capability is known as the QuikSCAT Radiometer (QRad). Microwave brightness temperatures measured by QRad are used to infer instantaneous rain rates over oceans using a statistical retrieval algorithm that has been developed using collocated QRad brightness temperatures with Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rate measurements. In this paper, QRad retrieved rain rate examples are presented and comparisons are made with the standard TRMM 2A12 data product. Validation results demonstrate that QRad rain measurements agree well with these independent microwave rain observations. QRad rain estimates starting from 1999 will be available in JPL reprocessing of QuikSCAT winds as part of the level 2B science data product. These rain estimates can be potentially used to improve flagging of rain-contaminated oceanic wind vector retrievals. Moreover, the broad swath coverage of QRad affords additional independent sampling of the oceanic rain, thus, QRad rain retrievals have the potential for contributing to NASAs Precipitation Measurement Mission objectives of improving the global sampling of oceanic rain within 3 hour windows.

Oceanic rain identification using multifractal analysis of QuikSCAT Sigma-0

The presence of rain over oceans interferes with the measurement of sea surface wind speed and direction from the Sea Winds scatterometer, and as a result, in rain regions wind measurements contain biases. In past research at the Central Florida Remote Sensing Lab, it has been observed that rain has multifractal behavior. In this paper we present an algorithm to detect the presence of rain so that rain regions are flagged. The forward and aft views of the high resolution horizontal polarization backscatter are used for the extraction of textural information with the help of multifractals. A negated multifractal exponent is computed to discriminate between wind and rain. Pixels with exponent value above a threshold are classified as rain pixels and those that do not meet the threshold are further examined with the help of correlation of the multifractal exponent within a predefined neighborhood of individual pixels. It was observed that the rain has less correlation within a neighborhood compared to wind. This property is utilized for reactivation of the pixels that fall below a certain threshold of correlation. An adaptive multifractal exponent and threshold is used, as we deal with a wide range of latitudes. Validation results are presented through comparison with the Tropical Rainfall Measurement Mission Microwave Imager (TMI) 2A12 rain retrieval product for one day. The results show that the algorithm is effective in identifying rain pixels. Some algorithm deficiencies in high wind speed regions are also discussed. Comparisons with other proposed approaches are also presented.

Oceanic Rainfall Retrievals using passive and active measurements from SeaWinds Remote Sensor

The SeaWinds sensor was launched onboard two satellite missions. The first was the QuikSCAT mission launched in mid 1999 by NASA, and the second was the ADEOS II mission launched by JAXA in late 2002. SeaWinds operates at a ku-band frequency of 13.4 GHz, and was originally designed to measure the speed and direction of the ocean surface wind vector by relating the normalized radar backscatter measurements to the near surface wind vector through a geophysical model function. In addition to the backscatter measurement capability, SeaWinds simultaneously measures the polarized radiometric emission from the surface and atmosphere, utilizing a ground signal processing algorithm known as the QuikSCAT / SeaWinds Radiometer (QRad / SRad). This paper presents an oceanic rainfall retrieval algorithm that combines the simultaneous active radar backscatter and the passive microwave brightness temperatures observed by the SeaWinds sensor. The retrieval algorithm is statistically based, and has been developed using collocated measurements from SeaWinds, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rates, and the National Center for Environmental Prediction (NCEP) wind fields. The rain is retrieved on a wind vector cell (WVC) measurement grid that has a spatial resolution of 25 km. Examples of the rain estimates from SeaWinds are presented, and comparisons are made with the standard TRMM 2A12 rain data product. Validation results demonstrate that SeaWinds rain measurements are in good agreement with the independent microwave rain observations obtained from TMI. Further, by applying a threshold on the retrieved rain rates, SeaWinds rain estimates can be utilized as a rain flag. In order to evaluate the performance of the SeaWinds flag, comparisons are made with the Impact based Multidimensional Histogram (IMUDH) rain flag developed by JPL. Results emphasize the powerful rain detection capabilities of the SeaWinds retrieval algorithm. Due to its broad swath coverage, SeaWinds affords additional independent sampling of the oceanic rainfall, which may contribute to the future NASAs Precipitation Measurement Mission (PMM) objectives of improving the global sampling of oceanic rain within 3 hour windows. Also, since SeaWinds is the only sensor onboard QuikSCAT, the SeaWinds rain estimates can be used to improve the flagging of rain-contaminated oceanic wind vector retrievals. The passive-only rainfall retrieval algorithm (QRad /SRad) has been implemented by JPL as part of the level 2B science data product, and can be obtained from the Physical Oceanography Distributed Data Archive (PO.DAAC).

Validation of QuikSCAT Radiometer rain rates using the TRMM microwave radiometer

The primary mission of the SeaWinds scatterometer on the QuikSCAT satellite is to infer surface wind vector from ocean backscatter measurements. Occasionally the backscatter measurements are contaminated by the presence of rain; therefore a reliable method of identifying rain is needed. Fortunately, the SeaWinds scatterometer simultaneously obtains active (scattering) and passive (emission) measurements of the ocean; thus, the QuikSCAT Radiometer (QRad) measured brightness temperatures can be used to infer rain rate within the scatterometer antenna field-of-view. This paper describes a new QuikSCAT Level-2B science product of rain rate over oceans. The principal use of this product for quality control purposes to provide a quantitative rain flag associated with QuikSCAT wind vector cells. The QRad rain rate algorithm is described and the characteristics of the rain rates product are presented. This product has been validated by near-simultaneous comparisons with rain rate measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). An example of QuikSCAT retrieved winds in the presence of rain is presented with collocated QRad rain measurements. Results demonstrate that the QRad rain rate product provides a reliable, quantitative wind vector quality flag.

An Improved Oceanic Rainfall Retrieval Algorithm and Results from Seawinds

This paper describes the development of an oceanic rainfall retrieval algorithm that combines both the simultaneous active (radar backscatter) and passive (microwave brightness temperatures) observations from the SeaWinds scatterometer on the QuikSCAT satellite. The retrieval algorithm is statistically based, and has been developed using collocated measurements from SeaWinds, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rates, and the National Center for Environmental Prediction (NCEP) wind fields. The rain is retrieved on a wind vector cell (WVC) measurement grid that has a spatial resolution of 25 km. Due to its broad swath coverage, SeaWinds affords additional independent sampling of the oceanic rainfall, which may contribute to NASAs future Global Precipitation Mission. Results emphasize the powerful rain detection capabilities of the SeaWinds retrieval algorithm.

Hurricane wind vector estimates from WindSat polarimetric radiometer

Abstract : WindSat is the worlds first microwave polarimetric radiometer, designed to measure ocean vector winds. In late 2004, the first preliminary oceanic wind vector results were released, and this paper presents the first evaluation of this product for several Atlantic hurricanes during the 2003 season. Both wind speed and wind direction comparisons will be made with surface wind analysis (H*Wind) developed by the NOAA Hurricane Research Division (HRD) and provided by the NOAA National Hurricane Center (NHC). Examples are presented where HRD aircraft flights were conducted within several hours of the WindSat overpass. These H*Wind surface wind analyses provide the most complete independent surface winds comparison data set available. Both WindSat retrieved wind speeds and wind directions are evaluated (against H*Wind) as a function of storm quadrant. To complement the analysis, rain rates were derived using WindSat brightness temperatures with a modified version of the TMI 2A12 heritage rain algorithm. Effects of rain on the derived wind speeds and directions are discussed.

Application of QuikSCAT radiometer rain rates to near-real-time global precipitation estimates: a global precipitation mission pathfinder

The SeaWinds scatterometer onboard the QuikSCAT satellite simultaneously measures the polarized microwave brightness temperature of the ocean/atmosphere. QuikSCAT Radiometer (QRad) brightness temperatures are used to infer instantaneous oceanic rain rates using a statistical retrieval algorithm that has been developed using collocated QRad brightness temperatures with TRMM Microwave Imager (TMI) rain rate measurements. The algorithm produces earth-located instantaneous rain rate binned in 0.5 hour universal time windows and produced on a 50-km earth grid. The orbit of QuikSCAT allows independent rain temporal sampling that can be used to improve the estimation of global rainfall in 3 hour windows, which is a goal of the future Global Precipitation Mission (GPM). In this work, QRad retrieved rain rate examples are presented and comparisons are made with the TRMM 3B42RT near real time product. Results demonstrate that QRad rain measurements agree well with these independent microwave rain observations and superior to the visible/infrared rain estimates, which demonstrates the utility of adding QRad to the 3B42RT product.