GPM Plans for Radiometer Intercalibration

The international Global Precipitation Measurement (GPM) mission led by NASA and JAXA is planned as a multi-radiometer constellation mission. A key mission component is the ability to intercalibrate the Tb from the partner constellation radiometers and create inter-calibrated, mission consistent Tc. One of the enabling strategies for this approach is the launching of a joint NASA/JAXA core satellite which contains a JAXA/NICT provided dual precipitation radar and a NASA provided Microwave Imaging passive radiometer. The observations from these instruments on the core satellite provide the opportunity to develop a transfer reference standard that can then be applied across the partner provided constellation radiometers that enables the creation of mission consistent brightness temperatures. The other aspect of the strategy is the development of a community consensus intercalibration algorithm that will be applied to the Tb observations from partner radiometers and create the best calibrated Tc. Also described is the development of the framework in which the inter-calibration is included in the final algorithm. A part of the latter effort has been the development of a generic, logical structure which can be applied across radiometer types and which guarantees the user community that key information for using Tc properly is recorded. Ke

Creating a Consistent Oceanic Multi-decadal Intercalibrated TMI-GMI Constellation Data Record

The Tropical Rainfall Measuring Mission (TRMM), launched in late November 1997 into a low earth orbit, produced the longest microwave radiometric data time series of 17-plus years from the TRMM Microwave Imager (TMI). The Global Precipitation Measuring (GPM) mission is the follow-on to TRMM, designed to provide data continuity and advance precipitation measurement capabilities. The GPM Microwave Imager (GMI) performs as a brightness temperature (Tb) calibration standard for the intersatellite radiometric calibration (XCAL) for the other constellation members; and before GPM was launched, TMI was the XCAL standard. This dissertation aims at creating a consistent oceanic multi-decadal Tb data record that ensures an undeviating long-term precipitation record covering TRMM-GPM eras. As TMI and GMI share only a 13-month common operational period, the U.S. Naval Research Laboratory\u27s WindSat radiometer, launched in 2003 and continuing today provides the calibration bridge between the two. TMI/WindSat XCAL for their \u3e 9 years\u27 period, and WindSat/GMI XCAL for one year are performed using a robust technique developed by the Central Florida Remote Sensing Lab, named CFRSL XCAL Algorithm, to estimate the Tb bias of one relative to the other. The 3-way XCAL of GMI/TMI/WindSat for their joint overlap period is performed using an extended CFRSL XCAL algorithm. Thus, a multi-decadal oceanic Tb dataset is created. Moreover, an important feature of this dataset is a quantitative estimate of the Tb uncertainty derived from a generic Uncertainty Quantification Model (UQM). In the UQM, various sources contributing to the Tb bias are identified systematically. Next, methods for quantifying uncertainties from these sources are developed and applied individually. Finally, the resulting independent uncertainties are combined into a single overall uncertainty to be associated with the Tb bias on a channel basis. This dissertation work is remarkably important because it provides the science community with a consistent oceanic multi-decadal Tb data record, and also allows the science community to better understand the uncertainty in precipitation products based upon the Tb uncertainties provided

GPM Mission Overview

The Global Precipitation Measurement (GPM) Mission is an international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products. Relative to current global rainfall products, GPM data products will be characterized by: (1) more accurate instantaneous precipitation measurements (especially for light rain and cold-season solid/snow precipitation), (2) more frequent sampling by an expanded constellation of microwave radiometers that include operational humidity sounders over land, (3) inter-calibrated microwave brightness temperatures from constellation radiometers within a unified framework, and (4) physical-based precipitation retrievals from constellation radiometers using a common a priori cloud hydrometeor database derived from GPM Core sensor measurements. The cornerstone of the GPM mission is the deployment of a Core Observatory in a unique 65 degree non-Sun-synchronous orbit to serve as a physics observatory and a calibration reference to improve precipitation measurements by a constellation of dedicated and operational passive microwave sensors. The Core Observatory will carry a KulKa-band Dual-frequency Precipitation Radar (DPR) and a multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The combined use ofDPR and GMI measurements will place greater constraints on possible solutions to radiometer retrievals to improve the accuracy and consistency of precipitation retrievals from all constellation radiometers. As a science mission with integrated application goals, GPM is designed to (1) advance precipitation measurement capability from space through combined use of active and passive microwave sensors, (2) advance the knowledge of the global water/energy cycle and freshwater availability through better description of the space-time variability of global precipitation, and (3) improve weather, climate, and hydrological prediction capabilities through more accurate and frequent measurements of instantaneous precipitation rates and time-integrated rainfall accumulation. An overview of the GPM mission concept and science activities in the United States, together with an update on international collaborations in radiometer intercalibration and ground validation, will be presented

Spaceborne Microwave Radiometry: Calibration, Intercalibration, and Science Applications.

Spaceborne microwave radiometry is the backbone for assimilation into numerical weather forecasts and provides important information for Earth and environment science. The extensive radiometric data must go through the process of calibration and intercalibration prior to science application. This work deals with the entire process by providing systematic methods and addressing critical challenges. These methods have been applied to NASA and JAXA’s Global Precipitation Measurement (GPM) mission and many other radiometers to make important contributions and to solve long-standing issues with coastal science applications. Specifically, it addresses four important challenges: 1) improving cold calibration with scan dependent characterization; 2) reducing the uncertainty of warm calibration; 3) deriving calibration dependence across the full range of brightness temperatures with both cold and warm calibration; and 4) investigating calibration variability and dependence on geophysical parameters. One critical challenge in science applications of radiometer data is that coastal science products from radiometers have previously been largely unavailable due to land contamination. We therefore develop methods to correct for land contamination and derive coastal science products. This thesis addresses these challenges by developing their solutions and then applying them to the GPM mission and its radiometer constellation.PhDAtmospheric, Oceanic and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120728/1/johnxun_1.pd

Ocean water vapor and cloud liquid water trends from 1992 to 2005 TOPEX Microwave Radiometer data

The continuous 1992–2005 data set of the TOPEX Microwave Radiometer (TMR) has been reprocessed to provide global, zonal, and regional scale histories of overocean integrated water vapor (IWV) and cloud liquid water (CLW). Results indicate well-defined trends in IWV on global and hemisphere scales, with values of 1.8 ± 0.4%/decade (60°S–60°N), 2.4 ± 0.4%/decade (0–60°N), and 1.0 ± 0.5%/decade (0–60°S). The uncertainties represent 1 standard deviation of the regressed slope parameter adjusted for lag 1 autocorrelation. These results are comparable to earlier results based on analyses of the multiinstrument SSM/I ocean measurements beginning in 1988. For the 1992–2005 interval, comparisons between SSM/I- and TMR-derived IWV trends show remarkable agreement, with global trends differing by less than 0.3%/decade, comparable to the statistical uncertainty level and about one-sixth of the global TMR-derived trend. Latitudinal and regional analyses of IWV trends show large variability about the global mean, with synoptic scale variations of IWV trends ranging from ∼−8 to +8%/decade. Averaged over 5° latitude bands the IWV trends reveal a near zero minimum in the Southern Tropical Pacific and maximum values of ∼4%/decade over the 30–40N latitude band. Comparisons with band latitude averaged SST data over the same 1992–2005 interval roughly match a delta_IWV/delta_SST trend scaling of ∼11%/K, consistent with previously observed tropical and midlatitude seasonal variability. TMR-derived CLW trends are fractionally comparable to the IWV trends. The CLW values are 1.5 ± 0.6%/decade (60°S–60°N), 2.0 ± 0.8%/decade (0–60°N), and 1.1 ± 0.8%/decade (0–60°S). When scaled to global mean CLW derived from SSM/I and compared seasonally, the TMR CLW variations exhibit excellent tracking with the SSM/I results. Unlike IWV, however, the CLW statistical uncertainties do not likely reflect the dominant error component in the retrieved trends. The 1992–2005 CLW trend estimates were particularly sensitive to short-term trends in the first and last 2 years of the TMR archive. Additional errors difficult to quantify include strong aliasing effects from precipitation cells and uncertainties in the radiative transfer models utilized in the generation of the TMR CLW algorithm

Impact of Microwave Sounder Calibration on Precipitation for the Global Precipitation Measurement Mission

Cross-track microwave sounders make up a significant percentage of the radiometers included in the Global Precipitation Measurement (GPM) constellation. Therefore, it is important to properly assess the calibration of each sounder instrument and to understand the impact of the calibration on the derived precipitation rates. This ensures an accurate precipitation product is produced for the entire constellation. This paper will use data from past and current microwave sounders to show how offsets in the calibration can impact the precipitation using the GPM Level 2 GPROF algorithm. Potential improvements to the instrument calibration will be assessed by analyzing how they would positively impact the precipitation trends and agreement among the constellation sensors

Radiometric Correction of Observations from Microwave Humidity Sounders

The Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) are total power microwave radiometers operating at frequencies near the water vapor absorption line at 183 GHz. The measurements of these instruments are crucial for deriving a variety of climate and hydrological products such as water vapor, precipitation, and ice cloud parameters. However, these measurements are subject to several errors that can be classified into radiometric and geometric errors. The aim of this study is to quantify and correct the radiometric errors in these observations through intercalibration. Since the bias in the calibration of microwave instruments changes with scene temperature, a two-point intercalibration correction scheme was developed based on averages of measurements over the tropical oceans and nighttime polar regions. The intercalibration coefficients were calculated on a monthly basis using measurements averaged over each specified region and each orbit, then interpolated to estimate the daily coefficients. Since AMSU-B and MHS channels operate at different frequencies and polarizations, the measurements from the two instruments were not intercalibrated. Because of the negligible diurnal cycle of both temperature and humidity fields over the tropical oceans, the satellites with the most stable time series of brightness temperatures over the tropical oceans (NOAA-17 for AMSU-B and NOAA-18 for MHS) were selected as the reference satellites and other similar instruments were intercalibrated with respect to the reference instrument. The results show that channels 1, 3, 4, and 5 of AMSU-B on board NOAA-16 and channels 1 and 4 of AMSU-B on board NOAA-15 show a large drift over the period of operation. The MHS measurements from instruments on board NOAA-18, NOAA-19, and MetOp-A are generally consistent with each other. Because of the lack of reference measurements, radiometric correction of microwave instruments remain a challenge, as the intercalibration of these instruments largely depends on the stability of the reference instrument

TRMM Microwave Imager (TMI) Alignment and Along-Scan Bias Corrections

The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) dataset released by the Precipitation Processing System (PPS) has been updated to a final version following the decommissioning of the TRMM satellite in April 2015. The updates are based on increased knowledge of radiometer calibration and sensor performance issues. In particular, the Global Precipitation Measurement (GPM) Microwave Imager (GMI) is used as a model for many of the TMI updates. This paper discusses two aspects of the TMI data product that have been reanalyzed and updated: alignment and along-scan bias corrections. The TMI's pointing accuracy is significantly improved over prior PPS versions, which used at-launch alignment values.A TMI instrument mounting offset is discovered as well as new alignment offsets for the two TMI feedhorns. The original TMI along-scan antenna temperature bias correction is found to be generally accurate over ocean, but a scene temperature-dependent correction is needed to account for edge-of-scan obstruction. These updates are incorporated into the final TMI data version, improving the quality of the data product and ensuring accurate geophysical parameters can be derived from TMI

TRMM Microwave Imager (TMI) Updates for Final Data Version Release

The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) dataset released by the Precipitation Processing System (PPS) will be updated to a final version within the next year. These updates are based on increased knowledge in recent years of radiometer calibration and sensor performance issues. In particular, the Global Precipitation Measurement (GPM) Microwave Imager (GMI) is used as a model for many of the TMI version updates. This paper discusses four aspects of the TMI data product that will be improved: spacecraft attitude, calibration and quality control, along-scan bias corrections, and sensor pointing accuracy. These updates will be incorporated into the final TMI data version, improving the quality of the data product and ensuring accurate geophysical parameters can be derived from TMI

An Emissive Antenna Correction for The Tropical Rainfall Measuring Mission Microwave Imager (TMI)

This dissertation deals with the radiometric calibration of a satellite microwave radiometer known as the TRMM Microwave Imager (TMI), which operated on NASA’s Tropical Rainfall Measuring Mission (TRMM). This multi-frequency, conical-scanning, passive microwave, remote sensor measures the earth’s blackbody emissions (brightness temperature, Tb) from a low earth orbit and covers the tropics (±35° latitude). The original scientific objective for TRMM’s 3-year mission was to measure the statistics of rainfall in the tropics. However, the mission was quite successful, and TRMM was extended for greater than 17 years to provide a long-term satellite rain measurements, which has contributed significantly to the study of global climate change. A significant part of the extended TRMM mission was the establishment of a constellation of satellite radiometer that provide frequent global rainfall measurements that enable severe storm warnings for operational hazard forecast by the international weather community. TRMM played a key role by serving as the radiometric calibration standard for the TRMM constellation microwave radiometers. The objective of this dissertation is to improve the radiometric calibration of TMI and to provide to NASA a new robust, physics-based algorithm for the legacy data processing of the TRMM brightness temperature data product, which will be called TMI 1B11 V8. Moreover, the results of this new procedure have been validated using the double difference techniques with the Global Precipitation Mission Microwave Imager (GMI), which is the replacement satellite mission to TRMM