Gridded precipitation products on the Hindu Kush-Himalaya: Performance and accuracy of seven precipitation products

Abstract

Climate change is expected to change precipitation and temperature patterns, which will impact the hydrological regime in Asia. Most river systems in the region originate from the Hindu Kush-Himalayas, and the altered precipitation patterns pose a threat to their sustainability, making it a major concern for planners and stakeholders. Obtaining accurate data on precipitation distribution is crucial for water accounting, which poses challenge. To address this, gridded precipitation products developed from satellite imagery and modeling techniques have become a viable alternative or addition to observed rainfall. However, the accuracy of these products in the region is uncertain. In this study, we aim to evaluate and compare the seven most commonly used precipitation products for the regions to address this gap. The study evaluated seven rainfall products, namely APHRODITE, TRMM, CHIRPS, PERSIANN-CDR, CMORPH, WFDEI, and GPCC by comparing daily, dekadal, and monthly rainfall data to 168 stations data in six countries and 11 river basins in the HKH region. The analysis used four continuous statistical indicators (Pearson correlation coefficient, Bias, Root Mean Square Error, and Nash–Sutcliffe Efficiency coefficient) and two categorical indicators (Probability of Detection and False Alarm Ratio). APHRODITE consistently performed well in several basins with high r values and low RMSE values, but had positive or negative bias values in different basins. CMORPH had the lowest positive bias value in the Ganga_Brahmaputra basin, while GPCC showed the largest r value and lowest RMSE value in the Sindha basin. CHIRPS performed well in Afghanistan, but had positive bias values. GPCC performed well in Myanmar and Pakistan, but had negative or positive bias values. APHRODITE performed consistently well in Nepal, but had negative bias values. Overall, the performance of different gridded precipitation products varies depending on the country and type of evaluation.

Evaluating the accuracy of APHRODITE and CHIRPS satellite-based precipitation products for meteorological drought

“…Furthermore, APHRODITE performed well in Z1 and Z2, particularly for dry classes, aligning with previous findings (Mishra et al, 2023;Lai et al, 2020;Han & Zhou, 2012;Khandu et al, 2016;Bhardwaj et al, 2017). In contrast, CHIRPS displayed better performance for wet classes, exhibited a general overestimation tendency (Mishra et al, 2023;Aadhar & Mishra, 2017), and showed weaker performance in high-elevation regions (Khandu et al, 2016), as seen in Figure 10.…”

“…It is important to note that spatial averaging within each zone and data-filling processes may have impacted the comparison results (Awchi & Suliman, 2021;Trenberth et al, 2014) variations contributed to differences between SbPPs and GS (Zhong et al, 2019;Awchi & Suliman, 2021). Furthermore, APHRODITE performed well in Z1 and Z2, particularly for dry classes, aligning with previous findings (Mishra et al, 2023;Lai et al, 2020;Han & Zhou, 2012;Khandu et al, 2016;Bhardwaj et al, 2017). In contrast, CHIRPS displayed better performance for wet classes, exhibited a general overestimation tendency (Mishra et al, 2023;Aadhar & Mishra, 2017), and showed weaker performance in high-elevation regions (Khandu et al, 2016), as seen in Figure 10.…”

“…The consistency and accuracy of APHRODITE's spatiotemporal data have been satisfactorily evaluated for various regions (Xu et al, 2016;Tan et al, 2020;Bhardwaj et al, 2017;Mishra et al, 2023;Raziei et al, 2013;Katiraie-Boroujerdy et al, 2016;Ghalhari et al, 2016;Yang et al, 2014). Furthermore, Xu et al (2016) found APHRODITE to be suitable for hydrological modeling and flood simulations in China.…”

“…Due to limited precipitation data availability in Iraq and concerns regarding the quantity and quality of ground station data, two SbPPs were considered: the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) (Yatagai et al, 2012) and the Climate Hazards Group (CHG) InfraRed Precipitation with Station data (CHIRPS) (Funk et al, 2015). SbPPs offer readily available, well-implemented data for climate studies at various spatiotemporal scales (Mishra et al, 2023;Das et al, 2022). However, their reliability varies regionally, necessitating comparison with terrestrial datasets before implementation in research (Tan et al, 2017;Bhardwaj et al, 2017).…”

Using Hydrological Models and Remote Sensing to Characterize Snow Pack Behaviour in High Mountain Environments

“…The most promising alternative involves incorporating worldwide data, such as high-resolution daily precipitation datasets like ERA5-Land (European Center for Medium-Range Weather Forecasts fifth generation), satellite precipitation data from CMORPH (Climate Prediction Center Morphing Technique), CPC UPP (Climate Prediction Center Unified Precipitation Project), APHRODITE (Asian Precipitation Highly Resolved Observational Data), and TRMM (Tropical Rainfall Measuring Mission). Satellite and reanalysis precipitation products require evaluation against in-situ data and calibration to hydrological models before use, with varying regional impacts on product performance [22,23].…”