The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining precipitation estimates from multiple satellites, as well as gauge analyses where feasible, at fine scales (0.25° × 0.25° and 3 hourly). TMPA is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The dataset covers the latitude band 50°N–S for the period from 1998 to the delayed present. Early validation results are as follows: the TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate–dependent low bias due to lack of sensitivity to low precipitation rates over ocean in one of the input products [based on Advanced Microwave Sounding Unit-B (AMSU-B)]. At finer scales the TMPA is successful at approximately reproducing the s...

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The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales

The MODIS cloud mask uses several cloud detection tests to indicate a level of confidence that the MEDIS is observing clear skies. It will be produced globally at single-pixel resolution; the algorithm uses as many as 14 of the MEDIS 36 spectral bands to maximize reliable cloud detection and to mitigate past difficulties experienced by sensors with coarser spatial resolution or fewer spectral bands. The MEDIS cloud mask is ancillary input to MEDIS land, ocean, and atmosphere science algorithms to suggest processing options. The MEDIS cloud mask algorithm will operate in near real time in a limited computer processing and storage facility with simple easy-to-follow algorithm paths. The MEDIS cloud mask algorithm identifies several conceptual domains according to surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. Once a pixel has been assigned to a particular domain (defining an algorithm path), a series of threshold tests attempts to detect the presence of clouds in the instrument field of view. Each cloud detection test returns a confidence level that the pixel is clear ranging in value from 1 (high) to zero (low). There are several types of tests, where detection of different cloud conditions relies on different tests. Tests capable of detecting similar cloud conditions are grouped together. While these groups are arranged so that independence between them is maximized, few, if any, spectral tests are completely independent. The minimum confidence from all tests within a group is taken to be representative of that group. These confidences indicate absence of particular cloud types. The product of all the group confidences is used to determine the confidence of finding clear-sky conditions. This paper outlines the MEDIS cloud masking algorithm. While no present sensor has all of the spectral bands necessary for testing the complete MEDIS cloud mask, initial validation of some of the individual cloud tests is presented using existing remote sensing data sets.

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Discriminating clear sky from clouds with MODIS

A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data

global product and is consistent in its retrieval approach for the entire period of data record. The moisture retrievals are made with a radiative transfer-based land parameter retrieval model. The various sensors have different technical specifications, including primary wavelength, spatial resolution, and temporal frequency of coverage. These sensor specifications and their effect on the data retrievals are discussed. The model is described in detail, and the quality of the data with respect to the different sensors is discussed as well. Examples of the different sensor retrievals illustrating global patterns are presented. Additional validation studies were performed with large-scale observational soil moisture data sets and are also presented. The data will be made available for use by the general science community.

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Multisensor historical climatology of satellite-derived global land surface moisture

Vegetation effects on the microwave emission of soils

An overview of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) Program is presented. This ground validation (GV) program is based at NASA Goddard Space Flight Center in Greenbelt, Maryland, and is responsible for processing several TRMM science products for validating space-based rain estimates from the TRMM satellite. These products include gauge rain rates, and radar-estimated rain intensities, type, and accumulations, from four primary validation sites (Kwajalein Atoll, Republic of the Marshall Islands; Melbourne, Florida; Houston, Texas; and Darwin, Australia). Site descriptions of rain gauge networks and operational weather radar configurations are presented together with the unique processing methodologies employed within the Ground Validation System (GVS) software packages. Rainfall intensity estimates are derived using the Window Probability Matching Method (WPMM) and then integrated over specified time scales. Error statistics from both dependent and independent val...

Ground Validation for the Tropical Rainfall Measuring Mission (TRMM)

The NASA Langley Research Center's L-band pushbroom microwave radiometer (PBMR) aboard the NASA C-130 aircraft was used to map surface soil moisture at and around the Konza Prairie Natural Research Area in Kansas during the four intensive field campaigns of FIFE in May-October 1987. A total of 11 measurements were made when soils were known to be saturated. This measurement was used for the calibration of the vegetation effect on the microwave absorption. Based on this calibration, the data from other measurements on other days were inverted to generate soil moisture maps. Good agreement was found when the estimated soil moisture values were compared with those independently measured on the ground at a number of widely separated locations. There was a slight bias between the estimated and measured values, the estimated soil moisture on the average being lower by about 1.8%. >

The L-band PBMR measurements of surface soil moisture in FIFE

This paper describes the cubic spline based operational system for the generation of the TRMM one-minute rain rate product 2A-56 from Tipping Bucket (TB) gauge measurements. Methodological issues associated with applying the cubic spline to the TB gauge rain rate estimation are closely examined. A simulated TB gauge from a Joss-Waldvogel (JW) disdrometer is employed to evaluate effects of time scales and rain event definitions on errors of the rain rate estimation. The comparison between rain rates measured from the JW disdrometer and those estimated from the simulated TB gauge shows good overall agreement; however, the TB gauge suffers sampling problems, resulting in errors in the rain rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When one minute rain rates are averaged to 4-7 minute or longer time scales, the errors dramatically reduce. The rain event duration is very sensitive to the event definition but the event rain total is rather insensitive, provided that the events with less than 1 millimeter rain totals are excluded. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-minute TB rain rates higher and lower than 3 mm per hour, respectively. These errors decrease to 5% and 14% when TB rain rates are used at 7-minute scale. The radar reflectivity-rainrate (Ze-R) distributions drawn from large amount of 7-minute TB rain rates and radar reflectivity data are mostly insensitive to the event definition.

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Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

A six-channel airborne total-power Millimeter-wave Imaging Radiometer (MIR) was recently built to provide measurements of atmospheric water vapor, clouds, and precipitation. The instrument is a cross-track scanner that has a 3-dB beamwidth of 3.5° and an angular swath of 100°. It measures radiation at the frequencies of 89, 150, 183.3 ± 1, 183.3 ± 3, 183.3 ± 7, and 220 GHz. The inclusion of the 220-GHz receiver makes this instrument unique; no other instrument has made atmospheric radiation measurements using this combination of frequencies. The temperature sensitivities ΔT, based on the actual flight data with a 6.8-ms integration time, are found to be 0.44, 0.44, 1.31, 1.30. 1.02, and 1.07 K. The instrument has two external calibration loads maintained at the temperatures of 330 and 250 K (the ambient temperature at an aircraft altitude of 20 km). These calibration load temperatures are monitored precisely so that the radiometric measurements of the instrument could be made to better than 1 K o...

An Airborne Millimeter-Wave Imaging Radiometer for Cloud, Precipitation, and Atmospheric Water Vapor Studies

Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) spaced-based rain estimates, and hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar-gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar-gauge differences into the gauge area-point error variance and radar rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar rain estimates at various times scales, and are helpful to better understand the differences between measured radar and gauge rain rates. It is envisaged that this study will contribute to better utilization of GV radar rain products to validate versatile spaced-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement, and other satellites.

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Jianxin Wang

Papers

Ground Validation for the Tropical Rainfall Measuring Mission (TRMM)

The L-band PBMR measurements of surface soil moisture in FIFE

Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

An Airborne Millimeter-Wave Imaging Radiometer for Cloud, Precipitation, and Atmospheric Water Vapor Studies

Evaluation of TRMM Ground-Validation Radar-Rain Errors Using Rain Gauge Measurements