Integrated Multi-satellite Retrievals For GPM Products Research Articles

Statistical and hydrological evaluation of the latest Integrated Multi-satellitE Retrievals for GPM (IMERG) over a midlatitude humid basin in South China

Recently, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) products with high spatial (0.1° × 0.1°) and temporal (half-hourly) resolution have become operationally available. It is of crucial importance to comprehensively evaluate these new products before they are applied extensively. This study focuses on statistical and hydrological evaluations of the latest IMERG (Version 05) products: the near-real-time “Early” run and “Late” run IMERG products (IMERG-E and IMERG-L, respectively), and the post-real-time “Final” run IMERG product (IMERG-F) over the mid-latitude humid Mishui basin in South China during 2014–2015, in comparison with their predecessors, the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) products (3B42RT and 3B42V7). The post-real-time IMERG-F presents the best performance among the five satellite precipitation products (SPPs), with the highest daily correlation coefficient (CC) of 0.85 and the lowest daily root-mean square error of 5.58 mm at the basin scale. The near-real-time IMERG-E and IMERG-L demonstrate comparable performance with 3B42V7. In addition, the Taylor diagrams visually demonstrate that the IMERG products are better than the 3B42 products. For hydrological simulations under scenario I (model calibration based on rain gauge observations), the post-real-time IMERG-F performs obviously better than the 3B42V7 does, with a relatively high CC of 0.81, a good Nash–Sutcliffe coefficient of 0.63, and an acceptable relative bias of −3.98%. Both the IMERG-E and IMERG-L demonstrate a better performance than the 3B42RT does. For scenario II (model recalibration based on each satellite dataset), the hydrological performances of both the IMERG and 3B42 products are improved. The IMERG-E, especially, demonstrates streamflow simulation performance comparable to that of the 3B42V7, both for the whole simulation period and flood season, indicating the great potential of the latest near-real-time IMERG-E product for flood simulation and prediction. Overall, this systematic evaluation highlights that the latest IMERG products have desirable hydrological utility in the study region. This study will provide useful guidelines for hydrological applications of the new generation SPPs, as well as IMERG algorithm development.

Global intercomparison and regional evaluation of GPM IMERG Version-03, Version-04 and its latest Version-05 precipitation products: Similarity, difference and improvements

The overarching goal of this study is to intercompare the newly released Integrated Multi-satellitE Retrievals for GPM (IMERG) Version 05 (V05) products with its former Version 04 (V04) and Version 03 (V03) products and also assess any differences and improvements, with cross-evaluation against the Global Precipitation Climatology Project (GPCP) Version 2.3, Multi-Source Weighted-Ensemble Precipitation (MSWEP) Version 2.1 and the dense gauge networks in China. Firstly, the gauge-adjusted products (Final run) of V03, V04 and V05 are compared over the globe. Then, the near-real-time products without gauge adjustments (Early and Late run) and Final run products of all versions are evaluated against ground-based observations comprised of more than 30,000 gauges over Mainland China at 0.1° × 0.1° grid and hourly and daily temporal scales. The primary conclusions are: (1) globally, both V04 and V05 Final run show significant differences and improvements from V03. Particularly, the overall mean oceanic precipitation of V04 and V05 increases by +31.36% and +28.81% respectively from that of V03 and much closer to GPCP and MSWEP; (2) over Mainland China, the Early and Late run products of the same version (V03 or V04) generally have similar performance, while V04 Early and Late run have better performance in most regions than the corresponding run of V03 except in the arid Xinjiang Province and the mountainous Tibetan Plateau; and (3) V04 and V03 Final run show comparable performance, while V05 Final run generally improves upon both V04 and V03 and has the best performance among the seven standard IMERG products. The improvement of V05 Final run is particularly evident in southeastern and western China. At a timely matter, the study provides first-hand global and regional assessment feedback to IMERG algorithm developers and also sheds insights for GPM precipitation product users across the world.

Evaluation of hydrological utility of IMERG Final run V05 and TMPA 3B42V7 satellite precipitation products in the Yellow River source region, China

Global satellite precipitation products, such as Tropical Rainfall Measuring Mission (TRMM) and its successor, Global Precipitation Measurement (GPM), have provided hydrologists with a critical precipitation data source for hydrological applications in data-sparse or ungauged basins. This study conducts a comparative analysis on the quality of the TRMM Multi-satellite Precipitation Analysis 3B42V7 and the Integrated Multi-satellite Retrievals for GPM (IMERG) Final Run version 05 precipitation products and their hydrological utilities in the Yellow River source region (YRSR), a mountainous Alpine region in northwestern China, from April 2014 to December 2016. Results indicate that when evaluated against the ground precipitation observations, IMERG generally improves the daily precipitation estimates relative to its predecessor 3B42V7. In addition, and the correlation coefficients (CCs) of IMERG (0.328 and 0.527) are significantly higher at grid and basin scales than those of 3B42V7 (0.287 and 0.458). However, the 3-hourly precipitation estimates from both products poorly correlate with the ground observations at grid and basin scales. By using the grid-based Xinanjiang (GXAJ) hydrological model calibrated with the gauge-based precipitation for daily streamflow simulations, the 3B42V7-driven model run shows acceptable hydrological simulation skill with regard to the Nash-Sutcliffe model efficiency coefficient (NSE = 0.729), whereas IMERG demonstrates improved performance (NSE = 0.810), which is comparable with the gauge-based simulation (NSE = 0.807). Input-specific model recalibration effectively enhances the hydrological performance of both satellite products (NSE = 0.856 for IMERG and NSE = 0.840 for 3B42V7). Additionally, the gauge-benchmarked GXAJ model with 3B42V7 has limited hydrological skill in simulating three historical flood events at 3-hourly time intervals (NSE = −0.070 to 0.702), while IMERG has a slightly better performance (NSE = 0.266–0.792). Model recalibration also significantly improves the simulations of two out of three flood events, and the NSE skill cores of IMERG (0.581–0.901) and 3B42V7 (−0.795 to 0.852) are relatively lower than that of the gauge-based simulation (0.753–0.969) but comparable. Overall, the IMERG and 3B43V7 satellite precipitation products can be adopted as reliable precipitation sources for hydrological simulations at daily and sub-daily time scales in the study area, with IMERG better suited than 3B42V7. Considering that the low CC values exist in both IMERG and 3B42V7 products, in particular, at a sub-daily temporal scale, the GPM research community should further improve the calibration algorithms and enhance the quality of IMERG products in YRSR. Performing bias-correction of satellite precipitation products is also necessary for hydrological modelers to effectively improve their hydrological utilities.

NWP-Based Adjustment of IMERG Precipitation for Flood-Inducing Complex Terrain Storms: Evaluation over CONUS

This paper evaluates the use of precipitation forecasts from a numerical weather prediction (NWP) model for near-real-time satellite precipitation adjustment based on 81 flood-inducing heavy precipitation events in seven mountainous regions over the conterminous United States. The study is facilitated by the National Center for Atmospheric Research (NCAR) real-time ensemble forecasts (called model), the Integrated Multi-satellitE Retrievals for GPM (IMERG) near-real-time precipitation product (called raw IMERG) and the Stage IV multi-radar/multi-sensor precipitation product (called Stage IV) used as a reference. We evaluated four precipitation datasets (the model forecasts, raw IMERG, gauge-adjusted IMERG and model-adjusted IMERG) through comparisons against Stage IV at six-hourly and event length scales. The raw IMERG product consistently underestimated heavy precipitation in all study regions, while the domain average rainfall magnitudes exhibited by the model were fairly accurate. The model exhibited error in the locations of intense precipitation over inland regions, however, while the IMERG product generally showed correct spatial precipitation patterns. Overall, the model-adjusted IMERG product performed best over inland regions by taking advantage of the more accurate rainfall magnitude from NWP and the spatial distribution from IMERG. In coastal regions, although model-based adjustment effectively improved the performance of the raw IMERG product, the model forecast performed even better. The IMERG product could benefit from gauge-based adjustment, as well, but the improvement from model-based adjustment was consistently more significant.

Assessment of the GPM and TRMM Precipitation Products Using the Rain Gauge Network over the Tibetan Plateau

Using high-quality hourly observations from national-level ground-based stations, the satellite-based rainfall products from both the Global Precipitation Measurement (GPM) Integrated MultisatellitE Retrievals for GPM (IMERG) and its predecessor, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), are statistically evaluated over the Tibetan Plateau (TP), with an emphasis on the diurnal variation. The results indicate that: (1) the half-hourly IMERG rainfall product can explicitly describe the diurnal variation over the TP, but with discrepancies in the timing of the greatest precipitation intensity and an overestimation of the maximum rainfall intensity over the whole TP. In addition, the performance of IMERG on the hourly timescale, in terms of the correlation coefficient and relative bias, is different for regions with sea level height below or above 3500 m; (2) the IMERG products, having higher correlation and lower root-mean-square error, perform better than the TMPA products on the daily and monthly timescales; and (3) the detection ability of IMERG is superior to that of TMPA, as corroborated by a higher Hanssen and Kuipers score, a higher probability of detection, a lower false alarm ratio, and a lower bias. Compared to TMPA, the IMERG products ameliorate the overestimation across the TP. In conclusion, GPM IMERG is superior to TRMM TMPA over the TP on multiple timescales.

Multi time-scale evaluation of high-resolution satellite-based precipitation products over northeast of Austria

Over the years, combinations of different methods that use multi-satellites and multi-sensors have been developed for estimating global precipitation. Recently, studies that have evaluated Integrated Multi-satellite Retrievals for GPM (IMERG) Final-Run (FR) version V-03D and other precipitation products have indicated better performance for IMERG-FR compared to other similar products in different climate regimes. This study comprehensively evaluates the two GPM-IMERG products, specifically IMERG-FR and IMERG-Real-Time (RT) late-run, against a dense station network (62 stations) in northeast Austria from mid-March 2015 to the end of January 2016 using different time-scales. Both products are examined against station data in capturing the occurrence and statistical characteristics of precipitation intensity. With regard to probability density functions (PDFs), the satellite precipitation estimate (SPE) products have detected more heavy and extreme precipitation events than the ground measurements. Both precipitation products at all time-scales, except for IMERG-RT 12-hourly and daily precipitation, capture less occurrence of precipitation than the station dataset for light precipitation. This partially explains the under-detection of precipitation events. For all time-scales, both IMERG products' CDFs (Cumulative Distribution Function) are well above that of the stations' precipitation. For lower precipitation levels, IMERG-RT is slightly below the IMERG-FR whereas IMERG-RT is above IMERG-FR at higher precipitation levels. Furthermore, for entire spectrum precipitation rates (P ≥ 0.1 mm), 1, 3, 6-hourly, IMERG-FR did not show a clear improvement of the Bias over IMERG-RT, while for 12-hourly and daily precipitation estimates, the bias in IMERG-FR has improved compared to IMERG-RT. In addition, IMERG-FR shows a considerable improvement in RMSE as compared to IMERG-RT. IMERG-FR, however, systematically underestimates moderate to extreme precipitation and overestimates light precipitation for all time scales against rain-gauges in northeast Austria. When comparing the bias, RMSE, and correlation coefficients, IMERG-FR has outperformed IMERG-RT particularly for 6-hourly, 12-hourly, and daily precipitation. Despite the general low probability of detection (POD) and threat score (TS) and the high false alarm ratio (FAR) within specified precipitation thresholds, the contingency table shows relatively acceptable values of the POD, TS and FAR for precipitation without classification.

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

Recently, the Global Precipitation Measurement (GPM) mission has released the Integrated Multi-satellite Retrievals for GPM (IMERG) at a fine spatial (0.1° × 0.1°) and temporal (half hourly) resolutions. A comprehensive evaluation of this newly launched precipitation product is very important for satellite-based precipitation data users as well as for algorithm developers. The objective of this study was to provide a preliminary and timely performance evaluation of the IMERG product over the northern high lands of Pakistan. For comparison reference, the real-time and post real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products were also evaluated parallel to the IMERG. All of the selected precipitation products were evaluated at annual, monthly, seasonal and daily time scales using reference gauges data from April 2014 to December 2016. The results showed that: (1) the precipitation estimates from IMERG, 3B42V7 and 3B42RT products correlated well with the reference gauges observations at monthly time scale (CC = 0.93, 0.91, 0.88, respectively), whereas moderately at the daily time scale (CC = 0.67, 0.61, and 0.58, respectively); (2) Compared to the 3B42V7 and 3B42RT, the precipitation estimates from IMERG were more reliable in all seasons particularly in the winter season with lowest relative bias (2.61%) and highest CC (0.87); (3) IMERG showed a clear superiority over 3B42V7 and 3B42RT products in order to capture spatial distribution of precipitation over the northern Pakistan; (4) Relative to the 3B42V7 and 3B42RT, daily precipitation estimates from IMEREG showed lowest relative bias (9.20% vs. 21.40% and 26.10%, respectively) and RMSE (2.05 mm/day vs. 2.49 mm/day and 2.88 mm/day, respectively); and (5) Light precipitation events (0–1 mm/day) were usually overestimated by all said satellite-based precipitation products. In contrast moderate (1–20 mm/day) to heavy (>20 mm/day) precipitation events were underestimated by both TMPA products while IMERG was found capable to detect moderate to heavy precipitation events more precisely. Overall, the performance of IMERG was better than that of TMPA products. This preliminary evaluation of new generation of satellite-based precipitation estimates might be a useful feedback for sensor and algorithm developers as well as data users.

Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria

Abstract. The Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) products provide quasi-global (60° N–60° S) precipitation estimates, beginning March 2014, from the combined use of passive microwave (PMW) and infrared (IR) satellites comprising the GPM constellation. The IMERG products are available in the form of near-real-time data, i.e., IMERG Early and Late, and in the form of post-real-time research data, i.e., IMERG Final, after monthly rain gauge analysis is received and taken into account. In this study, IMERG version 3 Early, Late, and Final (IMERG-E,IMERG-L, and IMERG-F) half-hourly rainfall estimates are compared with gauge-based gridded rainfall data from the WegenerNet Feldbach region (WEGN) high-density climate station network in southeastern Austria. The comparison is conducted over two IMERG 0.1° × 0.1° grid cells, entirely covered by 40 and 39 WEGN stations each, using data from the extended summer season (April–October) for the first two years of the GPM mission. The entire data are divided into two rainfall intensity ranges (low and high) and two seasons (warm and hot), and we evaluate the performance of IMERG, using both statistical and graphical methods. Results show that IMERG-F rainfall estimates are in the best overall agreement with the WEGN data, followed by IMERG-L and IMERG-E estimates, particularly for the hot season. We also illustrate, through rainfall event cases, how insufficient PMW sources and errors in motion vectors can lead to wide discrepancies in the IMERG estimates. Finally, by applying the method of Villarini and Krajewski (2007), we find that IMERG-F half-hourly rainfall estimates can be regarded as a 25 min gauge accumulation, with an offset of +40 min relative to its nominal time.

On the Spatial and Temporal Sampling Errors of Remotely Sensed Precipitation Products

Observation with coarse spatial and temporal sampling can cause large errors in quantification of the amount, intensity, and duration of precipitation events. In this study, the errors resulting from temporal and spatial sampling of precipitation events were quantified and examined using the latest version (V4) of the Global Precipitation Measurement (GPM) mission integrated multi-satellite retrievals for GPM (IMERG), which is available since spring of 2014. Relative mean square error was calculated at 0.1° × 0.1° every 0.5 h between the degraded (temporally and spatially) and original IMERG products. The temporal and spatial degradation was performed by producing three-hour (T3), six-hour (T6), 0.5° × 0.5° (S5), and 1.0° × 1.0° (S10) maps. The results show generally larger errors over land than ocean, especially over mountainous regions. The relative error of T6 is almost 20% larger than T3 over tropical land, but is smaller in higher latitudes. Over land relative error of T6 is larger than S5 across all latitudes, while T6 has larger relative error than S10 poleward of 20°S–20°N. Similarly, the relative error of T3 exceeds S5 poleward of 20°S–20°N, but does not exceed S10, except in very high latitudes. Similar results are also seen over ocean, but the error ratios are generally less sensitive to seasonal changes. The results also show that the spatial and temporal relative errors are not highly correlated. Overall, lower correlations between the spatial and temporal relative errors are observed over ocean than over land. Quantification of such spatiotemporal effects provides additional insights into evaluation studies, especially when different products are cross-compared at a range of spatiotemporal scales.

Assessment of GPM and TRMM Precipitation Products over Singapore

The evaluation of satellite precipitation products (SPPs) at regional and local scales is essential in improving satellite-based algorithms and sensors, as well as in providing valuable guidance when choosing alternative precipitation data for the local community. The Tropical Rainfall Measuring Mission (TRMM) has made significant contributions to the development of various SPPs since its launch in 1997. The Global Precipitation Measurement (GPM) mission launched in 2014 and is expected to continue the success of TRMM. During the transition from the TRMM era to the GPM era, it is necessary to assess GPM products and make comparisons with TRMM products in different regions to achieve a global view of the performance of GPM products. To this end, this study aims to assess the capability of the latest Integrated Multi-satellite Retrievals for GPM (IMERG) and two TRMM Multisatellite Precipitation Analysis (TMPA) products (TMPA 3B42 and TMPA 3B42RT) in estimating precipitation over Singapore that represents a typical tropical region. The evaluation was conducted at daily, monthly, seasonal and annual scales from 1 April 2014 to 31 January 2016. The capability of SPPs in detecting rainy/non-rainy days and different precipitation classes was also evaluated. The findings showed that: (1) all SPPs correlated well with measurements from gauges at the monthly scale, but moderately at the daily scale; (2) SPPs performed better in the northeast monsoon season (1 December–15 March) than in the inter-monsoon 1 (16 March–31 May), southwest monsoon (1 June–30 September) and inter-monsoon 2 (1 October–30 November) seasons; (3) IMERG had better performance in the characterization of spatial precipitation variability and precipitation detection capability compared to the TMPA products; (4) for the daily precipitation estimates, IMERG had the lowest systematic bias, followed by 3B42 and 3B42RT; and (5) most of the SPPs overestimated moderate precipitation events (1–20 mm/day), while underestimating light (0.1–1 mm/day) and heavy (>20 mm/day) precipitation events. Overall, IMERG is superior but with only slight improvement compared to the TMPA products over Singapore. This study is one of the earliest assessments of IMERG and a comparison of it with TMPA products in Singapore. Our findings were compared with existing studies conducted in other regions, and some limitations of the IMERG and TMPA products in this tropical region were identified and discussed. This study provides an added value to the understanding of the global performance of the IMERG product.

Evaluation of the GPM IMERG satellite-based precipitation products and the hydrological utility

Pre-occupation evaluation of latest generation satellite-based precipitation products (SPPs) is an essential step before the massive scale use. Taking the Beijiang River Basin as the case study, we used nine statistical evaluation indices and the Variable Infiltration Capacity (VIC) distributed hydrological model to quantitatively evaluate the performance and the hydrological utility of three Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) products: the near-real-time “Early” run and “Late” run IMERG products (IMERG-E and IMERG-L), and the post-real-time “Final” run IMERG product (IMERG-F) over south China during 2014–2015, with the last-generation Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42-V7 product as comparison. The IMERG-F presents satisfactory accuracy with high correlation coefficient (CC=0.63) and low relative bias (0.92%), while the IMERG-E and IMERG-L performs relatively poorly featuring low correlation (with CC of 0.49 and 0.52 respectively) with the ground observations. All of the three IMERG products present apparently higher probability of detection (POD, 0.64–0.67) but have higher false alarm ratio (FAR, ≧0.14) than the 3B42-V7. The hydrological simulation under scenario I (model calibrated by the gauge observations) shows that, the IMERG-F, with a high Nash–Sutcliffe coefficient of efficiency (NSCE) of 0.742, presents better hydrological performance than the 3B42-V7; the IMERG-E and IMERG-L perform poorly for the whole simulation period with NSCE lower than 0.35 and relative bias higher than 28% while perform satisfactorily during the flood season with apparently higher NSCE of 0.750 and 0.733 respectively. The hydrological simulation under scenario II (model calibrated by the 3B42-V7) shows that the performance of all the IMERG products was significantly improved. Generally, the IMERG-F has high accuracy and good hydrological utility, while the IMERG-E and IMERG-L products have satisfactory hydrological utility during the flood season and thus have great potential for the real-time application such as flood forecasting. The late-run IMERG-L presents little improvement in performance comparing with the early-run IMERG-E, therefore, the timelier IMERG-E is recommended to be firstly considered.

First Evaluation of the Day-1 IMERG over the Upper Blue Nile Basin

Abstract This work presents a first evaluation of the performance of the Integrated Multisatellite Retrievals for GPM (IMERG) precipitation product over the upper Blue Nile basin of Ethiopia. One of the unique features of this study is the availability of hourly rainfall measurements from an experimental rain gauge network in the area. Both the uncalibrated and calibrated versions of IMERG are evaluated, and their performance is contrasted against another high-resolution satellite product, which is the Kalman filter (KF)-based Climate Prediction Center (CPC) morphing technique (CMORPH). The analysis is performed for hourly and daily time scales and at spatial scales that correspond to the nominal resolution of satellite products, which is 0.1° spatial resolution. The period analyzed is focused on a single wet season (May–October 2014). Evaluation is performed using several statistical and categorical error metrics, as well as spatial correlation analysis to assess the ability of satellite products to represent spatial variability of precipitation in the area. Results show that both IMERG products have a better bias ratio and correlation coefficient on both time scales as compared to CMORPH. Comparison statistics show a slight improvement in the skill of detecting rainfall events in IMERG products compared to CMORPH. Results also show a decreasing trend in the detection ability of satellite products for increasing threshold values, highlighting the need to further improve detection during heavy precipitation.

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

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.

Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results

The new generation of weather observatory satellites, namely Global Precipitation Measurement (GPM) constellation satellites, is the lead observatory of the 10 highly advanced earth orbiting weather research satellites. Indeed, GPM is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. This work compares the final run of the Integrated Multi-satellitE Retrievals for GPM (IMERG) product, the post real time of TRMM and Multi-satellite Precipitation Analysis (TMPA-3B42) and the Era-Interim product from the European Centre for Medium Range Weather Forecasts (ECMWF) against the Iran Meteorological Organization (IMO) daily precipitation measured by the synoptic rain-gauges over four regions with different topography and climate conditions in Iran. Assessment is implemented for a one-year period from March 2014 to February 2015. Overall, in daily scale the results reveal that all three products lead to underestimation but IMERG performs better than other products and underestimates precipitation slightly in all four regions. Based on monthly and seasonal scale, in Guilan all products, in Bushehr and Kermanshah ERA-Interim and in Tehran IMERG and ERA-Interim tend to underestimate. The correlation coefficient between IMERG and the rain-gauge data in daily scale is far superior to that of Era-Interim and TMPA-3B42. On the basis of daily timescale of bias in comparison with the ground data, the IMERG product far outperforms ERA-Interim and 3B42 products. According to the categorical verification technique in this study, IMERG yields better results for detection of precipitation events on the basis of Probability of Detection (POD), Critical Success Index (CSI) and False Alarm Ratio (FAR) in those areas with stratiform and orographic precipitation, such as Tehran and Kermanshah, compared with other satellite/model data sets. In particular, for heavy precipitation (>15 mm/day), IMERG is superior to the other products in all study areas and could be used in future for meteorological and hydrological models, etc.

Statistical and Hydrological Comparisons between TRMM and GPM Level-3 Products over a Midlatitude Basin: Is Day-1 IMERG a Good Successor for TMPA 3B42V7?

Abstract The goal of this study is to quantitatively intercompare the standard products of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and its successor, the Global Precipitation Measurement (GPM) mission Integrated Multisatellite Retrievals for GPM (IMERG), with a dense gauge network over the midlatitude Ganjiang River basin in southeast China. In general, direct comparisons of the TMPA 3B42V7, 3B42RT, and GPM Day-1 IMERG estimates with gauge observations over an extended period of the rainy season (from May through September 2014) at 0.25° and daily resolutions show that all three products demonstrate similarly acceptable (~0.63) and high (0.87) correlation at grid and basin scales, respectively, although 3B42RT shows much higher overestimation. Both of the post-real-time corrections effectively reduce the bias of Day-1 IMERG and 3B42V7 to single digits of underestimation from 20+% overestimation of 3B42RT. The Taylor diagram shows that Day-1 IMERG and 3B42V7 are comparable at grid and basin scales. Hydrologic assessment with the Coupled Routing and Excess Storage (CREST) hydrologic model indicates that the Day-1 IMERG product performs comparably to gauge reference data. In many cases, the IMERG product outperforms TMPA standard products, suggesting a promising prospect of hydrologic utility and a desirable hydrologic continuity from TRMM-era product heritages to GPM-era IMERG products. Overall, this early study highlights that the Day-1 IMERG product can adequately substitute TMPA products both statistically and hydrologically, even with its limited data availability to date, in this well-gauged midlatitude basin. As more IMERG data are released, more studies to explore the potential of GPM-era IMERG in water, weather, and climate research are urgently needed.