Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM, an evaluation at a pan-India scale?

Abstract

Abstract. Last couple of decades have seen the outburst of a number of satellite based precipitation products with Tropical Rainfall Measuring Mission (TRMM) as the most widely used for hydrologic applications. Transition of TRMM into Global Precipitation Mission (GPM) promises enhanced spatio-temporal resolution along with upgrades in sensors and rainfall estimation techniques. Dependence of systematic error components in rainfall estimates of Integrated Multi-satellitE Retrievals for GPM (IMERG), and their variation with climatology and topography, was evaluated over 86 basins in India for year 2014 and compared with the corresponding (2014) and retrospective (1998–2013) TRMM estimates. IMERG outperformed TRMM for all rainfall intensities across a majority of Indian basins, with significant improvement in low rainfall estimates showing smaller negative biases in 75 out of 86 basins. IMERG increased the inter-basin variability in bias for medium and high rainfall estimates. Low rainfall estimates in TRMM showed a systematic dependence on basin climatology, with significant overprediction in semi-arid basins which gradually improved in the higher rainfall basins. Medium and high rainfall estimates of TRMM exhibited a strong dependence on basin topography, with declining skill in the higher elevation basins. Systematic dependence of error components on basin climatology and topography was reduced in IMERG, especially in terms of topography. Rainfall-runoff modeling using Variable Infiltration Capacity (VIC) model over a flood prone basin (Mahanadi) revealed that improvement in rainfall estimates in IMERG didn’t translate into improvement in runoff simulations. More studies are required over basins in different hydro-climatic zones to evaluate the hydrologic significance of IMERG.

Blending multi-satellite, atmospheric reanalysis and gauge precipitation products to facilitate hydrological modelling

“…With rapid advances in remote sensing technologies and climate system modelling in recent decades, spaceborne sensors and state-of-the-art numerical weather models have produced vast precipitation datasets with a near-global coverage and an unprecedented spatiotemporal resolution (Sunilkumar et al, 2016;Prakash et al, 2018). For example, the Integrated Multi-satellitE Retrievals for GPM (IMERG) product is now available at 0.1° spatial and 30-minute temporal resolutions, and is anticipated to play a growing role in hydrological and meteorological monitoring (Beria et al, 2017;Massari et al, 2020). One of the latest global atmospheric reanalysis products, ERA5 provides hourly estimates for a large number of atmospheric, land and oceanic climate variables, and exhibits substantial improvements comparing to its predecessor in many regions of the globe (Graham et al, 2019;Tang et al, 2020;Tarek et al, 2020).…”

The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

“…Prakash et al [2016] compared the IMERG rainfall product with the TMPA rainfall product and ground-based rainfall data during heavy rainfall events over the southwest India. Beria et al [2016] evaluated the IMERG rainfall with the TRMM-3B42 at basin scale, which is relevant in terms of water resources assessment for policy makers. All these studies concluded that the IMERG showed good capability to capture rainfall events.…”