Hamideh Ebrahimi

Investigation of rain effects on Aquarius Sea Surface Salinity measurements

The Aquarius/SAC-D mission has been providing Sea Surface Salinity (SSS), globally over the ocean, for almost 3 years. As a member of the AQ/SAC-D Cal/Val team, the Central Florida Remote Sensing Laboratory has analyzed these salinity retrievals in the presence of rain and has noted the strong correlation between the spatial patterns of reduced SSS and the spatial distribution of rainfall. It was determined that this is the result of a cause and effect relationship, as opposed to SSS measurement errors. Hence, it is important to understand these SSS changes due to seawater dilution by rain and the associated near-surface salinity stratification. This paper addresses the effects of rainfall on the Aquarius (AQ) SSS retrieval using a macro-scale Rain Impact Model (RIM) in the region of high convective rain over the Inter-tropical Convergence Zone. This model, based on the superposition of a one-dimension eddy diffusion (turbulent diffusion) model, relates sea surface salinity to depth, rain accumulation and time since rainfall. For aiding in the identification of instantaneous and prior rainfall accumulations, an AQ Rain Accumulation product was developed. This product, based on the NOAA CMORPH rain data set, provides the rainfall history for 24 h prior to the observation time, which is integrated over each AQ SSS measurement cell. In this paper results of the RIM validation are presented by comparing AQ measured and RIM simulated SSS for several months of 2012. Results show the high cross correlation for these comparisons and also with the corresponding SSS anomalies relative to HYCOM.

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...

Intercalibrating the GPM constellation using the GPM Microwave Imager (GMI)

A constellation of disparate radiometers is inherent to the Global Precipitation Measurement (GPM) mission concept. The task of the Intersatellite Calibration Working group is to generate adjustments to make the measurements of all these radiometers physically consistent. A key role of the GPM Microwave Imager (GMI) on the GPM Core satellite is to serve as a transfer standard among the constellation radiometers. The TRMM Microwave Imager (TMI) has served this role during the development phase and for interim corrections early in the GPM mission. The stability of GMI appears to be very good and a physically based calibration has been generated that appears to be accurate at the 1K level or better.

Use of Monte Carlo simulation in remote sensing data analysis

In the summer of 2011, the Aquarius earth science satellite was launched to measure Sea Surface Salinity (SSS) using a L-band microwave radiometer/scatterometer. This is an important oceanic parameter for monitoring the earths water cycle over oceans and for modeling global climate change. The microwave remote sensing of SSS is a challenging objective. The SSS signal is weak and there are many interfering error sources that must be corrected to achieve an accurate SSS measurement. This paper deals with the use of random processes theory for assessing the effects of rainfall on the retrieved SSS. In this paper we use the Monte Carlo method that is one of the best methods for analysis of random processes, to investigate the multilayer effect caused by rainfall on the L-band brightness temperature and the resulting SSS retrieval.

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.

Negative impacts of rainfall on Aquarius Sea Surface Salinity measurements

The remote sensing of Sea Surface Salinity (SSS) by the Aquarius L-band radiometer is a very challenging task. This paper describes one particular challenge, namely to remove the effects of rain contamination on the measurement of ocean surface brightness temperature. Instantaneously, rain drops striking the ocean increases the surface roughness that raises the ocean surface brightness temperature and that results in a corresponding reduction of the retrieved SSS. Moreover, over time periods of hours, rain accumulation can produce a fresh water lens that modifies the ocean brightness, which also affects the retrieved ocean salinity. This paper investigates these negative effects of instantaneous and accumulated rainfall on Aquarius SSS measurement.

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.

Investigation of radiative tranfer model effect on radiometric inter-calibration of GPM sounder channels

This paper concerns the development of an improved algorithm for the inter-satellite radiometric calibration (XCAL) for microwave sounders in support of NASAs Global Precipitation Mission (GPM). This research extends previous XCAL work by incorporating different radiative transfer models for atmospheric water vapor absorption (namely; Rosenkranz and MonoRTM) to assess the robustness of the CFRSL “double difference” technique for sounder X-CAL. This paper presents new results of the GPM Microwave Imager (GMI) comparisons with the SAPHIR sounder on the Megha-Tropique satellite. Using a one-year GMI observations, we present a statistical analysis of SAPHIR radiometric biases performed over time and viewing geometry (SAPHIR scan angles).