Vicarious Calibration of Global Precipitation Measurement Microwave Radiometers

The vicarious cold calibration method of Ruf has been used to assess the calibration of the TMI, WindSat, SSM/I F13 and SSM/I F14 microwave radiometers using data from the GPM Inter-Calibration Working Group. Significant scan position dependent biases are seen for TMI (as large as 1 K) and for WindSat (as large as 5 K) – scan position dependent biases in SSM/I data were removed prior to processing. These biases are thought to be due to obstructions in the edge of scan field of view from the given instrument and its spacecraft. WindSat vertically polarized data also show a linear decrease in vicarious cold calibration brightness temperatures with scan position. SSM/I F13 and F14 vicarious cold brightness temperatures differ by an amount consistent with a ~.2 ° offset in their relative Earth incidence angles

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

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

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

Toward vicarious calibration of microwave remote-sensing satellites in arid environments

The Soil Moisture and Ocean Salinity (SMOS) satellite marks the commencement of dedicated global surface soil moisture missions, and the first mission to make passive microwave observations at L-band. On-orbit calibration is an essential part of the instrument calibration strategy, but on-board beam-filling targets are not practical for such large apertures. Therefore, areas to serve as vicarious calibration targets need to be identified. Such sites can only be identified through field experiments including both in situ and airborne measurements. For this purpose, two field experiments were performed in central Australia. Three areas are studied as follows: 1) Lake Eyre, a typically dry salt lake; 2) Wirrangula Hill, with sparse vegetation and a dense cover of surface rock; and 3) Simpson Desert, characterized by dry sand dunes. Of those sites, only Wirrangula Hill and the Simpson Desert are found to be potentially suitable targets, as they have a spatial variation in brightness temperatures of <4 K under normal conditions. However, some limitations are observed for the Simpson Desert, where a bias of 15 K in vertical and 20 K in horizontal polarization exists between model predictions and observations, suggesting a lack of understanding of the underlying physics in this environment. Subsequent comparison with model predictions indicates a SMOS bias of 5 K in vertical and 11 K in horizontal polarization, and an unbiased root mean square difference of 10 K in both polarizations for Wirrangula Hill. Most importantly, the SMOS observations show that the brightness temperature evolution is dominated by regular seasonal patterns and that precipitation events have only little impact

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

Microwave Radiometer Inter-Calibration: Algorithm Development and Application.

Microwave radiometer inter-calibration is an essential component of any effort to combine measurements from two or more radiometers into one dataset for scientific studies. One spaceborne instrument in low Earth orbit is not sufficient to perform long-term climate studies or to provide measurements more than twice per day at any given location on Earth. Measurements from several radiometers are necessary for analyses over extended temporal and spatial ranges. In order to combine the measurements, the radiometers need to be inter-calibrated due to the instruments having unique instrument designs and calibrations. Inter-calibration ensures that consistent scientific parameters are retrieved from the radiometers. The development of a cold end inter-calibration algorithm is presented. The algorithm makes use of vicarious cold calibration, along with the double difference method, to calculate calibration differences between radiometers. The performance of the algorithm is characterized using data from current conical scanning microwave radiometers. The vicarious cold calibration double difference is able to sufficiently account for design differences between two radiometers including frequency, earth incidence angle, and orbital characteristics. An estimate of the uncertainty in the inter-calibration algorithm is given as a result of potential errors in the geophysical inputs and improper accounting of seasonal and diurnal variability. The vicarious cold calibration double difference method is shown to be a valid and accurate inter-calibration algorithm. Results are compared with calibration differences calculated using alternate algorithms and sufficient agreement is attained. Inter-calibration is shown to be necessary for achieving consistency in retrieved scientific parameters by using the vicarious cold calibration double difference method to inter-calibrate two radiometers that are then used to derive rain accumulations. Inter-calibration results in a significant improvement in the rain accumulation agreement between the radiometers. This validates inter-calibration algorithm development and shows that it has a positive impact on achieving consistency in scientific parameter retrievals.PhDAtmospheric, Oceanic and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107078/1/rakro_1.pd

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

Global Precipitation Measurement (GPM): Unified Precipitation Estimation From Space

Global Precipitation Measurement (GPM) is an international satellite mission that uses measurements from an advanced radar/radiometer system on a Core Observatory as reference standards to unify and advance precipitation estimates through a constellation of research and operational microwave sensors. GPM is a science mission focusing on a key component of the Earth's water and energy cycle, delivering near real-time observations of precipitation for monitoring severe weather events, freshwater resources, and other societal applications. This work presents the GPM mission design, together with descriptions of sensor characteristics, inter-satellite calibration, retrieval methodologies, ground validation activities, and societal applications

Tracking Radiometer Calibration Stability Using Three-Point Onboard Calibration

Absolute calibration of radiometers is implemented onboard using one hot and one cold external calibration targets. However, two-point calibration methods are unable to differentiate calibration drifts and associated errors from fluctuations in receiver gain and offset. This paper investigates the use of onboard three-point calibration algorithm for microwave radiometers to track calibration drifts and characterize associated errors in Earth and Space measurements of the radiometer