Ruiyao Chen

Intercalibration of the GPM Microwave Radiometer Constellation

AbstractThe Global Precipitation Measurement (GPM) mission is a constellation-based satellite mission designed to unify and advance precipitation measurements using both research and operational microwave sensors. This requires consistency in the input brightness temperatures (Tb), which is accomplished by intercalibrating the constellation radiometers using the GPM Microwave Imager (GMI) as the calibration reference. The first step in intercalibrating the sensors involves prescreening the sensor Tb to identify and correct for calibration biases across the scan or along the orbit path. Next, multiple techniques developed by teams within the GPM Intersatellite Calibration Working Group (XCAL) are used to adjust the calibrations of the constellation radiometers to be consistent with GMI. Comparing results from multiple approaches helps identify flaws or limitations of a given technique, increase confidence in the results, and provide a measure of the residual uncertainty. The original calibration difference...

Three-way inter-satellite radiometric calibration between GMI, TMI and WindSat

Satellite precipitation measurements began a new era with the commissioning of the new Global Precipitation Measurements Microwave Imager (GMI) in March 2014. For the previous 17 years, the Tropical Rainfall Measurements Mission (TRMM) Microwave Imager (TMI), operating in a non-sun-synchronous orbit, served as the radiometric transfer standard for the constellation radiometers. Previously, the Central Florida Remote Sensing Lab has conducted independent inter-comparisons over oceans between TRMM Microwave Imager (TMI) and the Naval Research Labs WindSat polarimetric radiometer, and found that the radiometric calibration of TMI relative to WindSat exhibited exceptional long-term radiometric stability over > 5 years. This paper presents results of the three-way inter-calibration of GMI, TMI and WindSat brightness temperatures during the GPM/TRMM/WindSat overlap period March 2014 - March 2015.

Hot load temperature correction for the Tropical Rainfall Measuring Mission Microwave Imager (TMI)

The TRMM Microwave Imager has provided a nearly two-decade satellite remote sensing data set for studying climate change, and the legacy data processing is in progress and will be released in late 2017. During this reprocessing, it was discovered that the hot-load suffers an occasional transient solar intrusion, which resulted in a small systematic brightness temperature error. This paper describes an approach to remove this error.

Creating a Multidecadal Ocean Microwave Brightness Dataset: Three-Way Intersatellite Radiometric Calibration Among GMI, TMI, and WindSat

The Tropical Rainfall Measuring Mission (TRMM), launched in late November 1997 into a low earth orbit, produced the longest satellite-derived precipitation time series of 17 years. During the second half of this mission, a collection of cooperative weather satellites, with microwave radiometers, was combined to produce a 6-h tropical precipitation product, and the TRMM Microwave Imager (TMI) was used as the radiometric transfer standard to intercalibrate the constellation members. To continue this valuable precipitation climate data record, the Global Precipitation Mission (GPM) observatory was launched in February 2014, and the GPM Microwave Imager (GMI) became the new transfer standard that normalized the microwave radiance measurements of the GPM constellation radiometers. Previously, the Central Florida Remote Sensing Lab conducted intercomparisons over oceans, between TMI and the Naval Research Laboratorys WindSat polarimetric radiometer and found that the radiometric calibration of TMI relative to WindSat exhibited exceptional long-term radiometric stability over a period >8 years. Moreover, for purposes of assessing global climate change, it is crucial that a seamless transfer between the TRMM and the GPM microwave brightness temperature time series be achieved. Therefore, this paper presents arguments that the 3-way (WindSat, TMI, and GMI) intersatellite radiometric comparisons, performed during the 13-month period overlap, can be used to bridge the TRMM and GPM eras and assure a stable radiometric calibration between the diverse constellations member radiometers.

Inter-calibration of MHS AND AMSU-B microwave radiometers from TRMM to GPM ERA

In this paper the inter-calibration of Microwave Humidity Sounders and Advanced Microwave Sounding Unit-B on board of NOAA and METOP satellites which are cross track polar orbiters is been investigated, and regional and seasonal dependence of the calibration bias will be discussed.

Calibration of Millimeter Wave Sounder Radiometers on Polar Orbiting Satellites

This paper discusses the radiometric calibration of millimeter sounder radiometers, on polar orbiter satellites in the NASA Global Precipitation Mission (GPM) constellation; and presents radiometric bias results. Because the Tropical Rainfall Measurement Mission (TRMM) operated for over 17 years, it is important to combine the TRMM and the GPM precipitation datasets to produce a climate data record for global climate change studies. In the last decade of TRMMs operation, sounder radiometers were introduced into the TRMM constellation, which included: Advanced Microwave Sounding Unit-B sensors flown on NOAA weather satellites and the microwave humidity sounders sensors flown on NOAA and meteorological operational satellite program satellites. These sensors have provided an invaluable dataset of radiance measurements with full earth coverage, which has been used in precipitation measurements, weather prediction, and climate studies.

Inter-calibration of microwave radiometeres on polar orbiters in the GPM constellation

In this paper the calibration of sensors in polar orbiter satellites in the GPM constellation has been addressed. Since the lunch of TRMM at 1998, AMSU-B sensors flown on NOAA-15, NOAA-16, NOAA-17, and the MHS sensors flown on NOAA-18, NOAA-19, MetOp-A and MetOp-B have provided an invaluable datasets of full coverage of earth which have been extensively used in weather prediction. Here, the calibration between these radiometers and regional and scan position dependence of the calibration biases has been investigated.

Sensitivity of XCAL double difference approach to ocean surface emissivity and its impact on inter-calibration in GPM constellation

A robust XCAL double difference (DD) approach for radiometric calibration has been successfully applied between the TRMM Microwave Imager, TMI, (previous calibration transfer standard for NASAs Precipitation Measuring Mission) and a number of precipitation measuring radiometers in polar sun-synchronous orbits. Now that the TRMM Mission has ended (April 2015), the radiometric transfer standard was changed from TMI to the current GPM Microwave Imager (GMI). The use of an ocean radiative transfer model (RTM) is an integral part of our XCAL DD approach. Because the RTM physics is imperfect and because the environmental parameters are likewise only estimates of their true values, it is important to assess the sensitivity of the derived brightness temperature biases to these limitations. Therefore, in this paper, we conduct the inter-calibration between GMI and other constellation satellite microwave radiometers using the XCAL DD approach with two different ocean surface emissivity models. Results are presented that demonstrate the robustness of the XCAL DD approach for multiple instruments over a wide range of channel frequencies.

A Non-MLE Approach for Satellite Scatterometer Wind Vector Retrievals in Tropical Cyclones

Satellite microwave scatterometers are the principal source of global synoptic-scale ocean vector wind (OVW) measurements for a number of scientific and operational oceanic wind applications. However, for extreme wind events such as tropical cyclones, their performance is significantly degraded. This paper presents a novel OVW retrieval algorithm for tropical cyclones which improves the accuracy of scatterometer based ocean surface winds when compared to low-flying aircraft with in-situ and remotely sensed observations. Unlike the traditional maximum likelihood estimation (MLE) wind vector retrieval technique, this new approach sequentially estimates scalar wind directions and wind speeds. A detailed description of the algorithm is provided along with results for ten QuikSCAT hurricane overpasses (from 2003-2008) to evaluate the performance of the new algorithm. Results are compared with independent surface wind analyses from the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Divisions H*Wind surface analyses and with the corresponding SeaWinds Projects L2B-12.5 km OVW products. They demonstrate that the proposed algorithm extends the SeaWinds capability to retrieve wind speeds beyond the current range of approximately 35 m/s (minimal hurricane category-1) with improved wind direction accuracy, making this new approach a potential candidate for current and future conically scanning scatterometer wind retrieval algorithms.