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

2014 ◽  
Vol 31 (9) ◽  
pp. 1902-1921 ◽  
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.

scholarly journals An Experimental Study of the Small-Scale Variability of Rainfall

2012 ◽  
Vol 13 (1) ◽  
pp. 351-365 ◽  
Author(s):  
Ali Tokay ◽  
Kurtuluş
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Small Scale ◽  
Sharp Drop ◽  
Temporal Sampling ◽  
Precipitation Measurement ◽  
Variable Nature ◽  
Different Seasons ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Small-scale variability of rainfall has been studied employing six dual rain gauge sites at Wallops Island, Virginia. The rain gauge sites were separated between 0.4 and 5 km, matching the beamwidth of Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) precipitation radars. During a 2-yr observational period, over 7100 rainy samples were received at 5-min integration. A single gauge did not report as high as 67% of the time when at least one of the other gauges had rainfall in one of the seasons. Since rainfall from one of the six rain gauges is sufficient for the rainy footprint from a satellite, this demonstrates the common occurrence of the partial beamfilling. For the periods where all gauges were reporting rainfall, a single gauge had at most 13% difference from the areal average rainfall in one of the seasons. This suggests that at the spatial scale of 5 km, the variability caused by the rain gradient is relatively less important than the variability arising from a partially filled footprint. During the passage of frontal systems and tropical cyclones, the beam was filled by rain most of the time and this resulted in relatively higher correlation distances. The correlation distance had a sharp drop off from 45 km in moderately variable rainfall to 3 km in highly variable rainfall and ranged from 5 to 35 km between the different seasons. This demonstrates its highly variable nature. Considering temporal sampling, the monthly rainfall error was 35% and 73% for 3-hourly and twice-daily observations, respectively.

scholarly journals Comparison of Oceanic Multisatellite Precipitation Data from Tropical Rainfall Measurement Mission and Global Precipitation Measurement Mission Datasets with Rain Gauge Data from Ocean Buoys

2019 ◽  
Vol 36 (5) ◽  
pp. 903-920 ◽  
Author(s):  
Qiaoyan Wu ◽  
Yilei Wang
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Tropical Pacific ◽  
Tropical Rainfall ◽  
High Rainfall ◽  
Precipitation Measurement ◽  
The Tropics ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
The Tropical Pacific

AbstractThree satellite-derived precipitation datasets [the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA) dataset, the NOAA Climate Prediction Center morphing technique (CMORPH) dataset, and the newly available Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) dataset] are compared with data obtained from 55 rain gauges mounted on floating buoys in the tropics for the period 1 April 2014–30 April 2017. All three satellite datasets underestimate low rainfall and overestimate high rainfall in the tropical Pacific Ocean, but the TMPA dataset does this the most. In the high-rainfall (higher than 4 mm day−1) Atlantic region, all three satellite datasets overestimate low rainfall and underestimate high rainfall, but the IMERG dataset does this the most. For the Indian Ocean, all three rainfall satellite datasets overestimate rainfall at some gauges and underestimate it at others. Of these three satellite products, IMERG is the most accurate in estimating mean precipitation over the tropical Pacific and Indian Oceans, but it is less accurate over the tropical Atlantic Ocean for regions of high rainfall. The differences between the three satellite datasets vary by region and there is a need to consider uncertainties in the data before using them for research.

scholarly journals Comparative Strengths of SCaMPR Satellite QPEs with and without TRMM Ingest versus Gridded Gauge-Only Analyses

2013 ◽  
Vol 14 (1) ◽  
pp. 153-170 ◽  
Author(s):  
Yu Zhang ◽  
Dong-Jun Seo ◽  
David Kitzmiller ◽  
Haksu Lee ◽  
Robert J. Kuligowski ◽  
...  
Keyword(s):  
False Alarm ◽  
Tropical Rainfall Measuring Mission ◽  
Detection Rates ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Trmm Precipitation ◽  
Microwave Imager ◽  
Quantitative Precipitation Estimates ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract This paper assesses the accuracy of satellite quantitative precipitation estimates (QPEs) from two versions of the Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) algorithm relative to that of gridded gauge-only QPEs. The second version of SCaMPR uses the QPEs from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and Microwave Imager as predictands whereas the first version does not. The assessments were conducted for 22 catchments in Texas and Louisiana against National Weather Service operational multisensor QPE. Particular attention was given to the density below which SCaMPR QPEs outperform gauge-only QPEs and effects of TRMM ingest. Analyses indicate that SCaMPR QPEs can be competitive in terms of correlation and CSI against sparse gauge networks (with less than one gauge per 3200–12 000 km2) and over 1–3-h scale, but their relative strengths diminish with temporal aggregation. In addition, the major advantage of SCaMPR QPEs is its relatively low false alarm rates, whereas gauge-only QPEs exhibit better skill in detecting rainfall—though the detection skill of SCaMPR QPEs tends to improve at higher rainfall thresholds. Moreover, it was found that ingesting TRMM QPEs help mitigate the positive overall bias in SCaMPR QPEs, and improve the detection of moderate–heavy and particularly wintertime precipitation. Yet, it also tends to elevate the false alarm rate, and its impacts on detection rates can be slightly negative for summertime storms. The implications for adoption of TRMM and Global Precipitation Measurement (GPM) QPEs for NWS operations are discussed.

scholarly journals Evaluation of Radar Rainfall Products: Lessons Learned from the NASA TRMM Validation Program in Florida

2006 ◽  
Vol 23 (11) ◽  
pp. 1492-1505 ◽  
Author(s):  
Eyal Amitai ◽  
David A. Marks ◽  
David B. Wolff ◽  
David S. Silberstein ◽  
Brad L. Fisher ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Product Evaluation ◽  
Radar Data ◽  
Lessons Learned ◽  
Limiting Factors ◽  
Radar Rainfall ◽  
Precipitation Measurement ◽  
Ground Validation ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract Evaluation of the Tropical Rainfall Measuring Mission (TRMM) satellite observations is conducted through a comprehensive ground validation (GV) program. Since the launch of TRMM in late 1997, standardized instantaneous and monthly rainfall products are routinely generated using quality-controlled ground-based radar data adjusted to the gauge accumulations from four primary sites. As part of the NASA TRMM GV program, effort is being made to evaluate these GV products. This paper describes the product evaluation effort for the Melbourne, Florida, site. This effort allows us to evaluate the radar rainfall estimates, to improve the algorithms in order to develop better GV products for comparison with the satellite products, and to recognize the major limiting factors in evaluating the estimates that reflect current limitations in radar rainfall estimation. Lessons learned and suggested improvements from this 8-yr mission are summarized in the context of improving planning for future precipitation missions, for example, the Global Precipitation Measurement (GPM).

scholarly journals Comparison of GPM IMERG and TRMM 3B43 Products over Cyprus

2020 ◽  
Vol 12 (19) ◽  
pp. 3212
Author(s):  
Adrianos Retalis ◽  
Dimitris Katsanos ◽  
Filippos Tymvios ◽  
Silas Michaelides
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Monthly Basis ◽  
Rain Gauges ◽  
Annual Basis ◽  
Precipitation Measurement ◽  
Satellite Retrievals ◽  
Gauge Station ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) high-resolution product and Tropical Rainfall Measuring Mission (TRMM) 3B43 product are validated against rain gauges over the island of Cyprus for the period from April 2014 to June 2018. The comparison performed is twofold: firstly, the Satellite Precipitation (SP) estimates are compared with the gauge stations’ records on a monthly basis and, secondly, on an annual basis. The validation is based on ground data from a dense and well-maintained network of rain gauges, available in high temporal (hourly) resolution. The results show high correlation coefficient values, on average reaching 0.92 and 0.91 for monthly 3B43 and IMERG estimates, respectively, although both IMERG and TRMM tend to underestimate precipitation (Bias values of −1.6 and −3.0, respectively), especially during the rainy season. On an annual basis, both SP estimates are underestimating precipitation, although IMERG estimates records (R = 0.82) are slightly closer to that of the corresponding gauge station records than those of 3B43 (R = 0.81). Finally, the influence of elevation of both SP estimates was considered by grouping rain gauge stations in three categories, with respect to their elevation. Results indicated that both SP estimates underestimate precipitation with increasing elevation and overestimate it at lower elevations.

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

2018 ◽  
Vol 35 (7) ◽  
pp. 1457-1470 ◽  
Author(s):  
Rachael Kroodsma ◽  
Stephen Bilanow ◽  
Darren McKague
Keyword(s):  
Processing System ◽  
Tropical Rainfall Measuring Mission ◽  
Temperature Bias ◽  
Data Product ◽  
Precipitation Measurement ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Bias Corrections

AbstractThe 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.

scholarly journals Evaluation and Application of Satellite Precipitation Products in Studying the Summer Precipitation Variations over Taiwan

2020 ◽  
Vol 12 (3) ◽  
pp. 347 ◽  
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Ya-Hui Chang ◽  
Chian-Yi Liu
Keyword(s):  
Summer Precipitation ◽  
Tropical Rainfall Measuring Mission ◽  
Temporal Variations ◽  
Rain Gauge ◽  
Satellite Precipitation ◽  
Reference Base ◽  
Precipitation Measurement ◽  
June July ◽  
Global Precipitation Measurement ◽  
Global Precipitation

In March 2019, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG)-Final v6 (hereafter IMERG6) was released, with data concerning precipitation dating back to June 2000. The National Aeronautics and Space Administration (NASA) has suggested that researchers use IMERG6 to replace the frequently used Tropical Rainfall Measuring Mission (TRMM)-3B42 v7 (hereafter TRMM7), which is expected to cease operation in December 2019. This study aims to evaluate the performance of IMERG6 and TRMM7 in depicting the variations of summer (June, July, and August) precipitation over Taiwan during the period 2000–2017. Data used for the comparison also includes IMERG-Final v5 (hereafter IMERG5) and Global Satellite Mapping of Precipitation for Global Precipitation Measurement (GSMaP)-Gauge v7 (hereafter GSMaP7) during the summers of 2014–2017. Capabilities to apply the four satellite precipitation products (SPPs) in studying summer connective afternoon rainfall (CAR) events, which are the most frequently observed weather patterns in Taiwan, are also examined. Our analyses show that when using more than 400 local rain-gauge observations as a reference base for comparison, IMERG6 outperforms TRMM7 quantitatively and qualitatively, more accurately depicting the variations of the summer precipitation over Taiwan at multiple timescales (including mean status, daily, interannual, and diurnal). IMERG6 also performs better than TRMM7 in capturing the characteristics of CAR activities in Taiwan. These findings highlight that using IMERG6 to replace TRMM7 adds value in studying the spatial-temporal variations of summer precipitation over Taiwan. Furthermore, the analyses also indicated that IMERG6 outperforms IMERG5 and GSMaP7 in the examination of most of the features of summer precipitation over Taiwan during 2014–2017.

scholarly journals Optimization of Cloud-Radiation Databases for Passive Microwave Precipitation Retrievals over Ocean

2016 ◽  
Vol 33 (8) ◽  
pp. 1649-1671 ◽  
Author(s):  
Eun-Kyoung Seo ◽  
Sung-Dae Yang ◽  
Mircea Grecu ◽  
Geun-Hyeok Ryu ◽  
Guosheng Liu ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Optimization Method ◽  
Passive Microwave ◽  
Brightness Temperatures ◽  
Precipitation Measurement ◽  
Microwave Imager ◽  
Microwave Radiometers ◽  
Trmm Microwave Imager ◽  
Global Precipitation Measurement ◽  
Global Precipitation

AbstractUsing Tropical Rainfall Measuring Mission (TRMM) observations from storms collected over the oceans surrounding East Asia, during summer, a method of creating physically consistent cloud-radiation databases to support satellite radiometer retrievals is introduced. In this method, vertical profiles of numerical model-simulated cloud and precipitation fields are optimized against TRMM radar and radiometer observations using a hybrid empirical orthogonal function (EOF)–one-dimensional variational (1DVAR) approach.The optimization is based on comparing simulated to observed radar reflectivity profiles and the corresponding passive microwave observations at the frequencies of the TRMM Microwave Imager (TMI) instrument. To minimize the discrepancies between the actual and the synthetic observations, the simulated cloud and precipitation profiles are optimized by adjusting the contents of the hydrometeors. To reduce the dimension of the hydrometeor content profiles in the optimization, multivariate relations among hydrometeor species are used.After applying the optimization method to modify the simulated clouds, the optimized cloud-radiation database has a joint distribution of reflectivity and associated brightness temperatures that is considerably closer to that observed by TRMM PR and TMI, especially at 85 GHz. This implies that the EOF–1DVAR approach can generate profiles with realistic distributions of frozen hydrometeors, such as snow and graupel. This approach may be similarly adapted to operate with the variety and capabilities of the passive microwave radiometers that compose the Global Precipitation Measurement (GPM) constellation. Furthermore, it can be extended to other oceanic regions and seasons.

scholarly journals Calibrating Ground-Based Radars against TRMM and GPM

2018 ◽  
Vol 35 (2) ◽  
pp. 323-346 ◽  
Author(s):  
Robert A. Warren ◽  
Alain Protat ◽  
Steven T. Siems ◽  
Hamish A. Ramsay ◽  
Valentin Louf ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Calibration Error ◽  
Low Latitude ◽  
Piecewise Constant ◽  
Precipitation Measurement ◽  
Ground Validation ◽  
Reflectivity Data ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Spaceborne Radar

AbstractCalibration error represents a significant source of uncertainty in quantitative applications of ground-based radar (GR) reflectivity data. Correcting it requires knowledge of the true reflectivity at well-defined locations and times during a volume scan. Previous work has demonstrated that observations from certain spaceborne radar (SR) platforms may be suitable for this purpose. Specifically, the Ku-band precipitation radars on board the Tropical Rainfall Measuring Mission (TRMM) satellite and its successor, the Global Precipitation Measurement (GPM) mission Core Observatory satellite together provide nearly two decades of well-calibrated reflectivity measurements over low-latitude regions (±35°). However, when comparing SR and GR reflectivities, great care must be taken to account for differences in instrument sensitivity and frequency, and to ensure that the observations are spatially and temporally coincident. Here, a volume-matching method, developed as part of the ground validation network for GPM, is adapted and used to quantify historical calibration errors for three S-band radars in the vicinity of Sydney, Australia. Volume-matched GR–SR sample pairs are identified over a 7-yr period and carefully filtered to isolate reflectivity differences associated with GR calibration error. These are then used in combination with radar engineering work records to derive a piecewise-constant time series of calibration error for each site. The efficacy of this approach is verified through comparisons between GR reflectivities in regions of overlapping coverage, with improved agreement when the estimated errors are removed.

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

2010 ◽  
Vol 49 (2) ◽  
pp. 310-324 ◽  
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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