Real-time bias adjustment for satellite-based precipitation estimates over Mainland China

نویسندگان

چکیده

• A new approach to reduce the systematic biases of TMPA-RT in real time is proposed. Systematic bias and RMSE were significantly reduced after adjustment. Method focus on correcting hit bias, rarely corrected false precipitation. The limitation CSMW less improvement correlation coefficients. An improved cumulative distribution function (CDF)-based multi-satellite precipitation estimates proposed verified over Mainland China. Efforts are primarily focused establishing bias-adjusting model by adopting CDF based a Self-adaptive Moving Window (CSMW), which systematically integrates China Gauge-based Daily Precipitation Analysis (CGDPA) into real-time TRMM Multisatellite (TMPA-RT). In our modelling experiments, first 9-yr (2008–2016) data pairs used calibrate establish satellite-gauge relationship, was then applied last 3 years 2017–2019 as validation. Assessment results during independent validation period show that can positive original relative (RB) decreases from 16.01% before adjustments ?0.29%, root-mean-square error (RMSE) also has dramatic drop 13%. component analysis indicates substantial mainly manifested events (observed rain correctly detected satellite) but it failed miss not satellite). This arises because majority missed drizzle falls below rain/no-rain discriminant threshold, normally excluded algorithm. Additionally, seems have at medium-high rates (>8 mm/day), enhancing coefficient between satellite retrievals ground observations. major advantage this its applicability when gauge available, could further facilitate expansion satellite-based for natural hazards forecasting.

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ژورنال

عنوان ژورنال: Journal of Hydrology

سال: 2021

ISSN: ['2589-9155']

DOI: https://doi.org/10.1016/j.jhydrol.2021.126133