Abstract
Abstract. Quantitative precipitation estimates are obtained with more uncertainty under the influence of changing climate variability and complex topography from numerical weather prediction (NWP) models. On the other hand, hydrologic model simulations depend heavily on the availability of reliable precipitation estimates. Difficulties in estimating precipitation impose an important limitation on the possibility and reliability of hydrologic forecasting and early warning systems. This study examines the performance of the Weather Research and Forecasting (WRF) model and the Multi Precipitation Estimates (MPE) algorithm in producing the temporal and spatial characteristics of the number of extreme precipitation events observed in the western Black Sea region of Turkey. Precipitation derived from WRF model with and without the three-dimensional variational (3DVAR) data assimilation scheme and MPE algorithm at high spatial resolution (5 km) are compared with gauge precipitation. WRF-derived precipitation showed capabilities in capturing the timing of precipitation extremes and to some extent the spatial distribution and magnitude of the heavy rainfall events, whereas MPE showed relatively weak skills in these aspects. WRF skills in estimating such precipitation characteristics are enhanced with the application of the 3DVAR scheme. Direct impact of data assimilation on WRF precipitation reached up to 12% and at some points there is a quantitative match for heavy rainfall events, which are critical for hydrological forecasts.
Highlights
Influences of global warming and climate change are becoming more dominant with increasing numbers of catastrophic events observed around the world
Weather Research and Forecasting (WRF) model is implemented with a 3DVAR assimilation scheme that introduces conventional meteorological observations including the surface and upper-air measurements of pressure, temperature, humidity and wind speed into the initial stage of the model and adjust boundary conditions to improve the performance of shortterm simulations of heavy rainfall events
WRF model better follows observed temporal fluctuations than non-assimilated WRF and Multi Precipitation Estimates (MPE), except during the second peak of rainfall event 13, where MPE is in agreement with the ground observation
Summary
Influences of global warming and climate change are becoming more dominant with increasing numbers of catastrophic events observed around the world. The study of precipitation amounts during the last 50 years on land shows that the percentage of extreme precipitation compared to total precipitation has increased (Trenberth et al, 2007). As it occurs and is evident in several geographical regions on the earth, these types of extreme events are being observed throughout regions more prone to flooding in semiarid environments. Flood forecasting systems are becoming more widespread for emergency cases where life and property are concerned Such systems help to predict hazardous events and allow sufficient time for action.
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