Comparison of CMORPH and TRMM-3B42 over Mountainous Regions of Africa and South America

Dinku, Tufa; Connor, Stephen J.; Ceccato, Pietro

doi:10.1007/978-90-481-2915-7_11

Cited by 131 publications

(148 citation statements)

References 7 publications

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“…Among several TMPA data products, the 3B42 (research) (TMPA-3B42R) was used in this study as recommended by previous researchers (Winsemius, 2009;Dinku et al, 2010;Almazroui, 2011;Vernimmen et al, 2012). The available three-hourly data throughout a time span of 8 years (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) were aggregated to daily, monthly and yearly resolutions.…”

Section: Methodology and Resultsmentioning

confidence: 99%

“…In studies in locations with higher altitudes and particularly in the foothills of mountainous regions (e.g., the Andes), there were notorious differences between the two sources of data (Tian and Peters-Lidard, 2010). In this regard, the TRMM data might show lower values than the gauge rainfall (Dinku et al, 2010;Javanmard et al, 2010). The spatial resolution of the satellite-borne data possibly plays a minor role when attempting to mimic ground precipitation patterns in mountain range foothill areas.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Experiences in using the TMPA-3B42R satellite data to complement rain gauge measurements in the Ecuadorian coastal foothills

Arias-Hidalgo

Bhattacharya

Mynett

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. At present, new technologies are becoming available to extend the coverage of conventional meteorological datasets. An example is the TMPA-3B42R dataset (research -v6). The usefulness of this satellite rainfall product has been investigated in the hydrological modeling of the Vinces River catchment (Ecuadorian lowlands). The initial TMPA-3B42R information exhibited some features of the precipitation spatial pattern (e.g., decreasing southwards and westwards). It showed a remarkable bias compared to the groundbased rainfall values. Several time scales (annual, seasonal, monthly, etc.) were considered for bias correction. High correlations between the TMPA-3B42R and the rain gauge data were still found for the monthly resolution, and accordingly a bias correction at that level was performed. Bias correction factors were calculated, and, adopting a simple procedure, they were spatially distributed to enhance the satellite data. By means of rain gauge hyetographs, the bias-corrected monthly TMPA-3B42R data were disaggregated to daily resolution. These synthetic time series were inserted in a hydrological model to complement the available rain gauge data to assess the model performance. The results were quite comparable with those using only the rain gauge data. Although the model outcomes did not improve remarkably, the contribution of this experimental methodology was that, despite a high bias, the satellite rainfall data could still be corrected for use in rainfall-runoff modeling at catchment and daily level. In absence of rain gauge data, the approach may have the potential to provide useful data at scales larger than the present modeling resolution (e.g., monthly/basin).

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Section: Methodology and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experiences in using the TMPA-3B42R satellite data to complement rain gauge measurements in the Ecuadorian coastal foothills

Arias-Hidalgo

Bhattacharya

Mynett

et al. 2013

Hydrol. Earth Syst. Sci.

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“…In terms of QZ, the possible reason for this poor correlation is that most of this region stands at high elevations (over 4000 m). Many previous studies had revealed that TMPA products perform poorly in mountainous area [25,53,54]. These factors also lead to greater overestimation of annual precipitation across QZ and XJ than that in other regions.…”

Section: Methodsmentioning

confidence: 96%

Evaluation of IMERG and TRMM 3B43 Monthly Precipitation Products over Mainland China

2016

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Abstract:As the successor of the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM) mission significantly improves the spatial resolution of precipitation estimates from 0.25˝to 0.1˝. The present study analyzed the error structures of Integrated Multisatellite Retrievals for GPM (IMERG) monthly precipitation products over Mainland China from March 2014 to February 2015 using gauge measurements at multiple spatiotemporal scales. Moreover, IMERG products were also compared with TRMM 3B43 products. The results show that: (1) overall, IMERG can capture the spatial patterns of precipitation over China well. It performs a little better than TRMM 3B43 at seasonal and monthly scales; (2) the performance of IMERG varies greatly spatially and temporally. IMERG performs better at low latitudes than at middle latitudes, and shows worse performance in winter than at other times; (3) compared with TRMM 3B43, IMERG significantly improves the estimation accuracy of precipitation over the Xinjiang region and the Qinghai-Tibetan Plateau, especially over the former where IMERG increases Pearson correlation coefficient by 0.18 and decreases root-mean-square error by 54.47 mm for annual precipitation estimates. However, most IMERG products over these areas are unreliable; and (4) IMERG shows poor performance in winter as TRMM 3B43 even if GPM improved its ability to sense frozen precipitation. Most of them over North China are unreliable during this period.

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“…They found that SREs are more reliable over areas with strong convective precipitation and flat surfaces, such as the tropical oceans and South America. Dinku et al (2010) evaluated CMORPH and two TMPA products (3B42 and 3B42RT) for mountainous regions of Africa and South America. Both products underestimated the occurrence and amount of rainfall which they attributed to the complex terrain and orographic rain process.…”

Section: Introductionmentioning

confidence: 99%

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

Zambrano‐Bigiarini

Nauditt²,

Birkel

et al. 2017

Hydrol. Earth Syst. Sci.

233

153

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Abstract. Accurate representation of the real spatiotemporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SREs) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods.This study attempts to exhaustively evaluate -for the first time -the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-Adj, MSWEPv1.1, and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25 • grid if necessary). The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities.Results revealed that most SRE products performed better for the humid South (36.4-43.7 • S) and Central Chile (32.18-36.4 • S), in particular at low-and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (autumn and winter; MAM-JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no-rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all timescales, which can be clearly attributed to its bias-correction procedure using 217 stations from Chile. Good results were also obtained by the research products CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR, and the real-time PERSIANN-CCS-Adj were less skillful in representing observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resource assessments. We finally conclude that despite improvements of most SRE products, a site-specific assessment is still needed before any use in catchment-scale hydrological studies.

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Comparison of CMORPH and TRMM-3B42 over Mountainous Regions of Africa and South America

Cited by 131 publications

References 7 publications

Experiences in using the TMPA-3B42R satellite data to complement rain gauge measurements in the Ecuadorian coastal foothills

Experiences in using the TMPA-3B42R satellite data to complement rain gauge measurements in the Ecuadorian coastal foothills

Evaluation of IMERG and TRMM 3B43 Monthly Precipitation Products over Mainland China

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

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