Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan

Anjum, Muhammad Naveed; Ding, Yongjian; Shangguan, Donghui; Ahmad, Ijaz; Ijaz, Muhammad Wajid; Farid, Hafiz Umar; Yagoub, Yousif Elnour; Zaman, Muhammad; Adnan, Muhammad

doi:10.1016/j.atmosres.2018.02.010

Cited by 146 publications

(122 citation statements)

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“…Generally, rain gauges and groundbased weather radars are major sources of precipitation data, and they are considered as the most reliable sources (Tapiador et al, 2012). However, uneven distribution, insufficient density, limited spatial coverage hamper the wide application of these ground-based precipitation observations (GPOs), especially in the basins with complex topography (Anjum et al, 2018;Li et al, 2017). In recent years, the rapid development of satellite observations and retrieval techniques has prompted the continuous improvement of satellitebased precipitation estimations (SPEs), providing new opportunities for regional, national, and global scale applications [Kim et al, 2018;J Su et al, 2017;Wu et al, 2012] to overcome the limitation of GPOs.…”

Section: Introductionmentioning

confidence: 99%

The Assessment and Comparison of TMPA and IMERG Products Over the Major Basins of Mainland China

Lü

Ryu

et al. 2019

Earth and Space Science

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The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission (IMERG) aims to deliver the "best" precipitation estimation from space and has attracted much attention. The Version 05 of IMERG products including the near-real-time "Early" and "Late" run products (IMERG-E and IMERG-L, respectively), and the post-real-time "Final" run IMERG product (IMERG-F) are assessed at both national and basin scales against gauge observations over Mainland China for a 4-year period (from April 2014 to March 2018). As control products for comparison, their predecessor Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products (i.e., TMPA-RT and TMPA-V7) are also employed. Components analysis confirms the best performance of IMERG-F among the five SPEs in three different categories. All five SPEs feature increasing bias and root mean square difference (RMSD) with increasing daily gauge total precipitation, and such issue is less pronounced for IMERG-F-as evidenced by the lowest bias and RMSD across all precipitation rates. Besides, compared to TMPA, IMERG products exhibit better accuracy in detecting real precipitation evens, especially for light-to-medium rain (<60 mm/day), but they do not demonstrate significant improvement in the assessment of severe over/underestimation. In the basin-scale comparison, all five SPEs catch the key variation feature of basin-averaged precipitation time series (except TMPA-RT over Continental River Basin). Overall, IMERG-F demonstrates the best performance over all nine basins despite the slight overestimation, followed by TMPA-V7. IMERG-E and IMERG-L show performance close to or even better than TMPA-V7 in terms of the correlation coefficient and RMSD.

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Section: Introductionmentioning

confidence: 99%

The Assessment and Comparison of TMPA and IMERG Products Over the Major Basins of Mainland China

Lü

Ryu

et al. 2019

Earth and Space Science

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“…version (IMERG-v04), while the latest released version (IMERG-v05) has remained unreported so far. The IMERG-v04 was assessed in Malaysia [28], Italy [29], and Pakistan [30,31] while using gauges and/or radar precipitation estimates as references. These studies brought relevant information about IMERG-v04 relative performance in comparison to the others considered SPEs versions.…”

Section: Introductionmentioning

confidence: 99%

Benefits of the Successive GPM Based Satellite Precipitation Estimates IMERG–V03, –V04, –V05 and GSMaP–V06, –V07 Over Diverse Geomorphic and Meteorological Regions of Pakistan

et al. 2018

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Launched in 2014, the Global Precipitation Measurement (GPM) mission aimed at ensuring the continuity with the Tropical Rainfall Measuring Mission (TRMM) launched in 1997 that has provided unprecedented accuracy in Satellite Precipitation Estimates (SPEs) on the near-global scale. Since then, various SPE versions have been successively made available from the GPM mission. The present study assesses the potential benefits of the successive GPM based SPEs product versions that include the Integrated Multi-Satellite Retrievals for GPM (IMERG) version 3 to 5 (-v03, -v04, -v05) and the Global Satellite Mapping of Precipitation (GSMaP) version 6 to 7 (-v06, -v07). Additionally, the most effective TRMM based SPEs products are also considered to provide a first insight into the GPM effectiveness in ensuring TRMM continuity. The analysis is conducted over different geomorphic and meteorological regions of Pakistan while using 88 precipitations gauges as the reference. Results show a clear enhancement in precipitation estimates that were derived from the very last IMERG-v05 in comparison to its two previous versions IMERG-v03 and -v04. Interestingly, based on the considered statistical metrics, IMERG-v03 provides more consistent precipitation estimate than IMERG-v04, which should be considered as a transition IMERG version. As expected, GSMaP-v07 precipitation estimates are more accurate than the previous GSMaP-v06. However, the enhancement from the old to the new version is very low. More generally, the transition from TRMM to GPM is successful with an overall better performance of GPM based SPEs than TRMM ones. Finally, all of the considered SPEs have presented a strong spatial variability in terms of accuracy with none of them outperforming the others, for all of the gauges locations over the considered regions. to ensure the continuity of the TRMM mission. From the GPM mission, two new SPEs were made available: the Integrated Multi-Satellite Retrievals for GPM (IMERG) [14] and a new version of GSMaP product. Available at a 0.1 • and half-hourly and hourly temporal scales, respectively, they offer the opportunity of capturing finer local precipitation variations in space and time [15]. Due to their recent release, few studies report on GPM based SPEs.A first attempt was made by, [16] while comparing IMERG to its predecessor TMPA at the monthly timescale. The study highlighted the differences in both precipitation datasets, which vary according to surfaces and precipitations rates. Since then, numerous studies were dedicated to provide more insights into this discrepancy and highlighted the potential IMERG benefits over its predecessor TMPA at a more local scale. For example, in India, IMERG was found more accurate in the estimation of mean monsoon precipitation than TMPA [17]. In China, IMERG precipitation estimates were compared with the gauges observation at the national level considering daily [18] and monthly temporal scales [19], and a local level study reported on IMERG precipitation estimates over the Chinese Bei...

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“…Precipitation is a crucial component of the Earth's water and energy cycles. Reliable and accurate precipitation information plays an important role in hydrology, climatology, and water resource management [1][2][3][4][5][6][7][8][9][10][11]. Rain gauge networks may provide relatively accurate precipitation measurements but with an uneven distribution of stations and limited spatial representativeness [12].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Evaluation of GPM-IMERG, CMORPH, and TMPA Precipitation Products with Gauged Rainfall over Mainland China

Guang-hua

Lü

Crow

et al. 2018

Advances in Meteorology

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over China. Moreover, IMERG V05B was compared with IMERG V04A, the Tropical Rainfall Measuring Mission (TRMM) 3B42, and the Climate Prediction Center Morphing technique (CMORPH)-CRT in this study. Categorical verification techniques and statistical methods are used to quantify their performance. Results illustrate the following.(1) Except for IMERG V04A's severe underestimation over the Tibetan Plateau (TP) and Xinjiang (XJ) with high negative relative biases (RBs) and CMORPH-CRT's overestimation over XJ with high positive RB, the four satellite-based precipitation products generally capture the same spatial patterns of precipitation over China.(2) At the annual scale over China, the IMERG products do not show an advantage over its predecessor (TRMM 3B42) in terms of RMSEs, RRMSEs, and Rs; meanwhile, the performance of IMERG products is worse than TRMM 3B42 in spring and summer according to the RMSE, RRMSE, and R metrics. Between the two IMERG products, IMERG V05B shows the anticipated improvement (over IMERG V04A) with a decrease in RMSE from 0.4496 to 0.4097 mm/day, a decrease of RRMSE from 16.95% to 15.44%, and an increase of R from 0.9689 to 0.9759 during the whole study period. Similar results are obtained at the seasonal scale. Among the four satellite products, CMORPH-CRTshows the worst seasonal performance with the highest RMSE (0.6247 mm/day), RRMSE (23.55%), and lowest R (0.9343) over China. (3) Over XJ and TP, IMERG V05B clearly improves the strong underestimation of precipitation in IMERG V04A with the RBs of 5.2% vs. −21.8% over XJ, and 2.78% vs. −46% over TP. Results at the annual scale are similar to those obtained at the seasonal scale, except for summer results over XJ. While, over the remaining subregions, the two IMERG products have a close performance; meanwhile, IMERG V04A slightly improves IMERG V05B's overestimation according to RBs (except for HN) at the annual scale. However, all four products are unreliable over XJ at both an annual and seasonal scale. (4) Across all products, TRMM 3B42 best reproduces the probability density function (PDF) of daily precipitation intensity. (5) According to the categorical verification technique in this study, both IMERG products yield better results for the detection of precipitation events on the basis of probability of detection (POD) and critical success index (CSI) categorical evaluations compared to TRMM 3B42 and CMORPH-CRT over China and across most of the subregions. However, all four products have room for further improvement, especially in high-latitude and dry climate regions. ese findings provide valuable feedback for both IMERG algorithm developers and data set users.

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Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan

Cited by 146 publications

References 65 publications

The Assessment and Comparison of TMPA and IMERG Products Over the Major Basins of Mainland China

The Assessment and Comparison of TMPA and IMERG Products Over the Major Basins of Mainland China

Benefits of the Successive GPM Based Satellite Precipitation Estimates IMERG–V03, –V04, –V05 and GSMaP–V06, –V07 Over Diverse Geomorphic and Meteorological Regions of Pakistan

Comprehensive Evaluation of GPM-IMERG, CMORPH, and TMPA Precipitation Products with Gauged Rainfall over Mainland China

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