Ground Validation for the Tropical Rainfall Measuring Mission (TRMM)

Abstract 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 validation techniques show good agreement between gauge-measured and radar-estimated rainfall. A comparison of the NASA GV products and those developed independently by the University of Washington for a subset of data from the Kwajalein Atoll site also shows good agreement. A comparison of NASA GV rain intensities to satellite retrievals from the TRMM Microwave Imager (TMI), precipitation radar (PR), and Combined (COM) algorithms is presented, and it is shown that the GV and satellite estimates agree quite well over the open ocean.

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Comparisons of Instantaneous TRMM Ground Validation and Satellite Rain-Rate Estimates at Different Spatial Scales

Journal of Applied Meteorology and Climatology ◽

10.1175/2008jamc1875.1 ◽

2008 ◽

Vol 47 (8) ◽

pp. 2215-2237 ◽

Cited By ~ 62

Author(s):

David B. Wolff ◽

Brad L. Fisher

Keyword(s):

Rain Rate ◽

Spatial Scales ◽

Tropical Rainfall Measuring Mission ◽

Heavy Rain ◽

Global Ocean ◽

Ground Validation ◽

Microwave Imager ◽

Rain Events ◽

Trmm Microwave Imager ◽

Rain Rates

Abstract This study provides a comprehensive intercomparison of instantaneous rain rates observed by the two rain sensors aboard the Tropical Rainfall Measuring Mission (TRMM) satellite with ground data from two regional sites established for long-term ground validation: Kwajalein Atoll and Melbourne, Florida. The satellite rain algorithms utilize remote observations of precipitation collected by the TRMM Microwave Imager (TMI) and the Precipitation Radar (PR) aboard the TRMM satellite. Three standard level II rain products are generated from operational applications of the TMI, PR, and combined (COM) rain algorithms using rain information collected from the TMI and the PR along the orbital track of the TRMM satellite. In the first part of the study, 0.5° × 0.5° instantaneous rain rates obtained from the TRMM 3G68 product were analyzed and compared to instantaneous Ground Validation (GV) program rain rates gridded at a scale of 0.5° × 0.5°. In the second part of the study, TMI, PR, COM, and GV rain rates were spatiotemporally matched and averaged at the scale of the TMI footprint (∼150 km2). This study covered a 6-yr period (1999–2004) and consisted of over 50 000 footprints for each GV site. In the first analysis, the results showed that all of the respective rain-rate estimates agree well, with some exceptions. The more salient differences were associated with heavy rain events in which one or more of the algorithms failed to properly retrieve these extreme events. Also, it appears that there is a preferred mode of precipitation for TMI rain rates at or near 2 mm h−1 over the ocean. This mode was noted over ocean areas of Kwajalein and Melbourne and has been observed in TRMM tropical–global ocean areas as well.

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Radar Rainfall Estimation for Ground Validation Studies of the Tropical Rainfall Measuring Mission

Journal of Applied Meteorology ◽

10.1175/1520-0450-36.6.735 ◽

1997 ◽

Vol 36 (6) ◽

pp. 735-747 ◽

Cited By ~ 38

Author(s):

Grzegorz J. Ciach ◽

Witold F. Krajewski ◽

Emmanouil N. Anagnostou ◽

Mary L. Baeck ◽

James A. Smith ◽

...

Keyword(s):

Tropical Rainfall Measuring Mission ◽

Estimation Algorithm ◽

Rain Gauge ◽

Performance Criterion ◽

Local Network ◽

Rainfall Estimation ◽

Radar Rainfall ◽

Tropical Rainfall ◽

Rain Gauges ◽

Ground Validation

Abstract This study presents a multicomponent rainfall estimation algorithm, based on weather radar and rain gauge network, that can be used as a ground-based reference in the satellite Tropical Rainfall Measuring Mission (TRMM). The essential steps are constructing a radar observable, its nonlinear transformation to rainfall, interpolation to rectangular grid, constructing several timescale accumulations, bias adjustment, and merging of the radar rainfall estimates and rain gauge data. Observations from a C-band radar in Darwin, Australia, and a local network of 54 rain gauges were used to calibrate and test the algorithm. A period of 25 days was selected, and the rain gauges were split into two subsamples to apply cross-validation techniques. A Z–R relationship with continuous range dependence and a temporal interpolation scheme that accounts for the advection effects is applied. An innovative methodology was used to estimate the algorithm controlling parameters. The model was globally optimized by using an objective function on the level of the final products. This is equivalent to comparing hundreds of Z–R relationships using a uniform and representative performance criterion. The algorithm performance is fairly insensitive to the parameter variations around the optimum. This suggests that the accuracy limit of the radar rainfall estimation based on power-law Z–R relationships has been reached. No improvement was achieved by using rain regime classification prior to estimation.

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Global Precipitation Measurement (GPM) Ground Validation (GV) Prototype in the Korean Peninsula

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-13-00193.1 ◽

2014 ◽

Vol 31 (9) ◽

pp. 1902-1921 ◽

Cited By ~ 18

Author(s):

Ji-Hye Kim ◽

Mi-Lim Ou ◽

Jun-Dong Park ◽

Kenneth R. Morris ◽

Mathew R. Schwaller ◽

...

Keyword(s):

Korean Peninsula ◽

Rain Rate ◽

Tropical Rainfall Measuring Mission ◽

Rain Gauge ◽

International Partnerships ◽

Precipitation Measurement ◽

Ground Validation ◽

Microwave Imager ◽

Global Precipitation Measurement ◽

Global Precipitation

Abstract Since 2009, the Korea Meteorological Administration (KMA) has participated in ground validation (GV) projects through international partnerships within the framework of the Global Precipitation Measurement (GPM) Mission. The goal of this work is to assess the reliability of ground-based measurements in the Korean Peninsula as a means for validating precipitation products retrieved from satellite microwave sensors, with an emphasis on East Asian precipitation. KMA has a well-developed operational weather service infrastructure composed of meteorological radars, a dense rain gauge network, and automated weather stations. Measurements from these systems, including data from four ground-based radars (GRs), were combined with satellite data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and used as a proxy for GPM GV over the Korean Peninsula. A time series of mean reflectivity differences (GR − PR) for stratiform-only and above-brightband-only data showed that the time-averaged difference fell between −2.0 and +1.0 dBZ for the four GRs used in this study. Site-specific adjustments for these relative mean biases were applied to GR reflectivities, and detailed statistical comparisons of reflectivity and rain rate between PR and bias-adjusted GR were carried out. In rain-rate comparisons, surface rain from the TRMM Microwave Imager (TMI) and the rain gauges were added and the results varied according to rain type. Bias correction has had a positive effect on GR rain rate comparing with PR and gauge rain rates. This study confirmed advance preparation for GPM GV system was optimized on the Korean Peninsula using the official framework.

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Evaluation of TRMM Rain Estimates Using Ground Measurements over Central Florida

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-11-080.1 ◽

2012 ◽

Vol 51 (5) ◽

pp. 926-940 ◽

Cited By ~ 14

Author(s):

Jianxin Wang ◽

David B. Wolff

Keyword(s):

Time Scales ◽

Tropical Rainfall Measuring Mission ◽

Multiple Time Scales ◽

Multiple Time ◽

Monthly Basis ◽

Central Florida ◽

Temporal Sampling ◽

Ground Validation ◽

Microwave Imager ◽

Rain Rates

AbstractThis study evaluates space-based rain estimates from the Tropical Rainfall Measuring Mission (TRMM) satellite using ground-based measurements from the radar (GR) and tipping-bucket rain gauges (TG) over the TRMM Ground Validation (GV) site at Melbourne, Florida. The satellite rain products are derived from the TRMM Microwave Imager (TMI), precipitation radar (PR), and combined (COM) rain algorithms using observations from both instruments. The TRMM satellite and GV rain products are spatiotemporally matched and are intercompared at multiple time scales over the 12-yr period from 1998 to 2009. On monthly and yearly scales, the TG agree excellently with the GR because the GR rain rates are generated using the TG data as a constraint on a monthly basis. However, large disagreements exist between the GR and TG at shorter time scales because of their significantly different spatial and temporal sampling modes. The yearly biases relative to the GR for the PR and TMI are generally negative, with a few exceptions. The COM bias fluctuates from year to year over the 12-yr period. The PR, TMI, and COM are in good overall agreement with the GR in the lower range of rain rates, but the agreement is notably worse at higher rain rates. The diurnal cycle of rainfall is captured well by all products, but the peak satellite-derived rainfall (PR, TMI, and COM) lags the peak from the ground measurements (GR and TG) by ~1 h.

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Availability of High-Quality TRMM Ground Validation Data from Kwajalein, RMI: A Practical Application of the Relative Calibration Adjustment Technique

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2008jtecha1174.1 ◽

2009 ◽

Vol 26 (3) ◽

pp. 413-429 ◽

Cited By ~ 20

Author(s):

David A. Marks ◽

David B. Wolff ◽

David S. Silberstein ◽

Ali Tokay ◽

Jason L. Pippitt ◽

...

Keyword(s):

Tropical Rainfall Measuring Mission ◽

Radar Data ◽

Marshall Islands ◽

Practical Application ◽

High Quality ◽

Validation Data ◽

Tropical Ocean ◽

Nasa Goddard Space ◽

Ground Validation ◽

Improved Stability

Abstract Since the Tropical Rainfall Measuring Mission (TRMM) satellite launch in November 1997, the TRMM Satellite Validation Office (TSVO) at NASA Goddard Space Flight Center (GSFC) has been performing quality control and estimating rainfall from the KPOL S-band radar at Kwajalein, Republic of the Marshall Islands. Over this period, KPOL has incurred many episodes of calibration and antenna pointing angle uncertainty. To address these issues, the TSVO has applied the relative calibration adjustment (RCA) technique to eight years of KPOL radar data to produce Ground Validation (GV) version 7 products. This application has significantly improved stability in KPOL reflectivity distributions needed for probability matching method (PMM) rain-rate estimation and for comparisons to the TRMM precipitation radar (PR). In years with significant calibration and angle corrections, the statistical improvement in PMM distributions is dramatic. The intent of this paper is to show improved stability in corrected KPOL reflectivity distributions by using the PR as a stable reference. Intermonth fluctuations in mean reflectivity differences between the PR and corrected KPOL are on the order of ±1–2 dB, and interyear mean reflectivity differences fluctuate by approximately ±1 dB. This represents a marked improvement in stability with confidence comparable to the established calibration and uncertainty boundaries of the PR. The practical application of the RCA method has salvaged eight years of radar data that would have otherwise been unusable and has made possible a high-quality database of tropical ocean–based reflectivity measurements and precipitation estimates for the research community.

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The Varying Response of Microwave Signatures to Different Types of Overland Rainfall Found over the Korean Peninsula

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2009jtecha1364.1 ◽

2010 ◽

Vol 27 (4) ◽

pp. 785-792 ◽

Cited By ~ 4

Author(s):

Eun-Kyoung Seo ◽

Guosheng Liu ◽

Myoung-Seok Suh ◽

Byung-Ju Sohn

Keyword(s):

Korean Peninsula ◽

Tropical Rainfall Measuring Mission ◽

Rain Gauge ◽

Additional Information ◽

Ice Particles ◽

Systematic Biases ◽

Microwave Imager ◽

Rain Events ◽

Microwave Signatures ◽

Rain Rates

Abstract The Tropical Rainfall Measuring Mission (TRMM) precipitation radar and ground rain measurements were used to investigate the performance of the TRMM Microwave Imager (TMI) land algorithm. In particular, data from a dense network of rain gauges being operated over the Korean Peninsula were utilized. To retrieve information related to the rainfall rate over land, the TRMM land algorithm relies mainly on brightness temperature TB depression at vertically polarized 85(V) GHz because of scattering by ice particles. It refers to the relationships between 85(V)-GHz TBs and rain rates in its predefined database. By comparing the TMI rain rates with the surface rain gauge and TRMM radar measurements, it was found that there are a variety of relationships between 85(V)-GHz TBs and rainfall rates resulting from the various types of precipitating clouds. The TMI land algorithm, therefore, could not resolve some raining clouds such as warm clouds as well as cold clouds having small amounts of ice particles above the rain layer. The rainfall amounts for those missed rain events are significant. As a result, rain rates produced by the land algorithm show systematic biases, which are a function of raining cloud types. Meanwhile, it is found that the 37-GHz TMI channels contain additional information on surface rain; the uncertainties in retrieving rain rates from TBs at TMI frequencies can be reduced up to 11% if all polarized 37- and 85-GHz TBs are used as predictors.

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TRMM Calibration of SSM/I Algorithm for Overland Rainfall Estimation

Journal of Applied Meteorology and Climatology ◽

10.1175/jam2379.1 ◽

2006 ◽

Vol 45 (6) ◽

pp. 875-886 ◽

Cited By ~ 13

Author(s):

Tufa Dinku ◽

Emmanouil N. Anagnostou

Keyword(s):

South Asia ◽

Amazon Basin ◽

Tropical Rainfall Measuring Mission ◽

Retrieval Algorithm ◽

Calibration Data ◽

Error Statistics ◽

Microwave Imager ◽

Rain Rates ◽

Rain Retrieval

Abstract This paper extends the work of Dinku and Anagnostou overland rain retrieval algorithm for use with Special Sensor Microwave Imager (SSM/I) observations. In Dinku and Anagnostou, Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) rainfall estimates were used to calibrate TRMM Microwave Imager (TMI) retrieval. Regional differences in PR-based TMI calibration were investigated by testing the algorithm over four geographic regions, consisting of Africa, northern South America (containing the Amazon basin), the continental United States, and south Asia. In this paper the performance of Dinku and Anagnostou's technique applied on SSM/I data over three of these regions (Africa, Amazon, and South Asia) is demonstrated. Two approaches are investigated for using PR rainfall products to calibrate the algorithm parameters. In the first approach, TMI channels are remapped to the spatial resolutions of the corresponding SSM/I channels; then, PR is used to calibrate the rain retrieval on the remapped TMI data. In the second approach, the PR-based TMI algorithm calibration is performed at a coarser (0.25°) resolution. To assess the quality of algorithm estimates with respect to PR, rainfall fields derived from Dinku and Anagnostou, applied to SSM/I observations (using parameters determined from both approaches), are compared with matched (within ±15 min of the satellites' overpass time difference) PR surface rain rates. Calibration data come from the wet seasons (January–March) of 2000 and 2001. To assess the quality of the estimates with respect to PR, data from a 5-month period (December–April) of 2002, 2003, and 2004 are used. In comparison with the latest version of the Goddard profiling (GPROF) algorithm rain estimates, the current algorithm shows significant improvements in terms of both bias and random error reduction. The paper also shows that rain estimation based on TMI observations is associated with lower error statistics in comparison with the corresponding SSM/I retrievals.

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

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2264.1 ◽

2010 ◽

Vol 49 (2) ◽

pp. 310-324 ◽

Cited By ~ 35

Author(s):

Jianxin Wang ◽

David B. Wolff

Keyword(s):

Time Scales ◽

Estimation Error ◽

Tropical Rainfall Measuring Mission ◽

Error Variance ◽

Rain Gauge ◽

Error Characteristics ◽

Precipitation Measurement ◽

Ground Validation ◽

Rain Rates ◽

Global Precipitation

Abstract Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) space-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 time scales and are helpful to understand better 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 space-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement satellite and other satellites.

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Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2007jtecha895.1 ◽

2008 ◽

Vol 25 (1) ◽

pp. 43-56 ◽

Cited By ~ 59

Author(s):

Jianxin Wang ◽

Brad L. Fisher ◽

David B. Wolff

Keyword(s):

Rain Rate ◽

Tropical Rainfall Measuring Mission ◽

Rain Gauge ◽

Radar Reflectivity ◽

Time Shift ◽

Estimation Errors ◽

Rate Estimation ◽

Reflectivity Data ◽

Rain Rates ◽

Event Definition

Abstract This paper describes the cubic spline–based operational system for the generation of the Tropical Rainfall Measuring Mission (TRMM) 1-min rain-rate product 2A-56 from tipping-bucket (TB) gauge measurements. A simulated TB gauge from a Joss–Waldvogel disdrometer is employed to evaluate the errors of the TB 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 1-min rain rates are averaged over 4–7-min intervals or longer, the errors dramatically reduce. 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-min rain rates higher and lower than 3 mm h−1, respectively. These errors decrease to 5% and 14% when rain rates are used at the 7-min scale. The radar reflectivity–rain-rate distributions drawn from the large amount of 7-min rain rates and radar reflectivity data are mostly insensitive to the event definition. The time shift due to inaccurate clocks can also cause rain-rate estimation errors, which increase with the shifted time length. Finally, some recommendations are proposed for possible improvements of rainfall measurements and rain-rate estimations.

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