Evaluation and Comparison of TRMM Multi-Satellite Precipitation Products With Reference to Rain Gauge Observations in Hunza River Basin, Karakoram Range, Northern Pakistan

Abstract

Abstract:The performance evaluation of satellite-based precipitation products at local and regional scales is crucial for modification in satellite-based precipitation retrieval algorithms, as well as for the provision of guidance during the selection of substitute precipitation data. This study evaluated the performances of three Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products (3B42V6, 3B42RT and 3B42V7) with a reference to rain gauge observations in the Hunza River basin, northern Pakistan. Multi-spatial (pixel and basin) and temporal (daily, monthly, seasonal and annual) resolutions were considered for performance evaluation of TMPA products. Results revealed that the spatial pattern of observed precipitation over the basin was adequately captured by 3B42V7 but misplaced by 3B42V6 and 3B42RT. All TMPA products were unable to capture the intense precipitation events. On the daily time scale, the performance of TMPA products was very poor over both spatial scales. 3B42V6 underestimated the precipitation (31.25% and 44.27% on pixel and basin scales, respectively). By contrast, 3B42RT significantly overestimated the precipitation (47.91% and 38.62% on pixel and basin scales, respectively), while 3B42V7 showed overestimation (17.30%) on pixel scale and slight underestimation (6.24%) on the basin scale. On the seasonal scale, TMPA products showed significant biases with observed precipitation data. We found that the TMPA products performed relatively better on monthly and annual time scales and overall performance of 3B42V7 product was better than that of 3B42V6 and 3B42RT. The bias in 3B42V7 was improved by 85.90% compared with 3B42V6 and by 116.16% compared with 3B42RT. Thus, it is concluded that the TMPA products were unreliable to capture the intense precipitation events and retain high errors on daily and seasonal scales. Therefore, caution should be considered while using these precipitation estimates as a substitute data in hydrology, meteorology and climatology studies in Hunza River basin. However, due to the reasonable performance of monthly and annual 3B42V7 estimates, these can be used as an acceptable substitute for applications in the region.

Evaluation of Three-Hourly TMPA Rainfall Products Using Telemetric Rain Gauge Observations at Lai Nullah Basin in Islamabad, Pakistan

“…Overall, both of the TMPA products underestimated rainfall across the entire study period. However, 3B72V7 performed better than 3B42RT, which agrees with the finding of various recently conducted studies [53,54,57,77,78] in Pakistan. Further, our study strengthens the fact that the performance of TMPA products depends upon seasons and various timescales [16,79].…”

The Spatiotemporal Variability of Temperature and Precipitation Over the Upper Indus Basin: An Evaluation of 15 Year WRF Simulations

“…Krakauer et al [4] compared different precipitation datasets with the available stations' data over the Indus Basin and found the TRMM dataset to perform best among the remote sensing datasets. Similarly, Ali et al [43] evaluated the TRMM Multi-satellite Precipitation Analysis (TMPA) precipitation products (3B42V6, 3B42V7, and 3B42RT) with gauge stations over the Hunza Basin in Karakoram Mountainous range. They also found 3B42V7 reasonably better than the other two products.…”

Revealing Vertical Distribution of Precipitation in the Glacierized Upper Indus Basin Based on Multiple Datasets

“…Several studies have reported a very low amount of annual precipitation in UIB quantified from different products [e.g., 300 mm based on TRMM in Bookhagen and Burbank (2010) and Immerzeel et al (2009Immerzeel et al ( , 2010]. Many previous studies have discussed the applicability, usefulness, calibration, and limitations of TRMM dataset in Himalaya-Karakorum-Hindu Kush region (Ali et al 2017;Anjum et al 2016Anjum et al , 2018Burbank 2006, 2010;Cheema and Bastiaanssen 2012;Dahri et al 2016;Khan et al 2018;Khan et al 2014;Maggioni et al 2016). The differences in our and their results owing to different coverage of study area, periods, and meteorological stations applied in the analysis.…”