Precipitation Biases in the ECMWF Integrated Forecasting System

Abstract Precipitation is a key component of the global water cycle and plays crucial role in flooding, droughts, supply. One way to manage its socioeconomic effects based on precipitation forecasts from numerical weather prediction (NWP) models, an important step improve by diagnosing NWP biases. In this study, we investigate biases European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS). Using IFS control forecast 12 June 2019 11 2020 at 5219 stations globally, show that each boreal winter summer half years, 1) has average wet bias 2) displays similar patterns starting 0000 1200 UTC across days 1–5. These are dependent observed (climatological) precipitation; with low have bias, while high dry bias. Southeast Asia 1.61 mm day −1 (in summer) over study period overestimated 31.0% 3. This hydrological signature several hypothesized processes including issues specifying snowpack Tibetan Plateau, which may affect mei-yu front. implications land–atmosphere feedbacks, river discharge, ocean circulation region. Reducing these could lead more accurate cycle.