Biosphere-Atmosphere Gas Exchange & Atmospheric Chemistry Group
Keywords: Photochemical air pollution, atmospheric chemistry modeling, eddy covariance, ozone, BVOCs,
vegetation, seawater, evapotranspiration, micrometeorology
Developing tools for improved evapotranspiration prediction
A reliable forecast of potential evapotranspiration (ET0) is key to precise irrigation scheduling toward reducing water and agrochemical use while optimizing crop yield. In this study, we examine the benefits of using the Weather Research and Forecasting (WRF) Model for ET0 and precipitation forecasts with simulations at a 3-km grid spatial resolution and an hourly temporal resolution output over Israel. The simulated parameters needed to calculate ET0 using the Penman–Monteith approach, as well as calculated ET0 and precipitation, were compared to observations from a network of meteorological stations (see Bughici et al., 2019).
WRF forecasts of all Penman–Monteith meteorological parameters, except wind speed Ws, were significantly sensitive to seasonality and synoptic conditions, whereas forecasts of Ws consistently showed high bias associated with strong local effects, leading to high bias in the evaluated Penman–Monteith–ET0. Local Ws bias correction using observations on days preceding the forecast and interpolation of the resulting Penman–Monteith–ET0 to other locations led to significant improvement in ET0 forecasts over the investigated area. By using this hybrid forecast approach (WRFBC) that combines WRF numerical simulations with statistical bias corrections (for the year 2007), daily ET0 forecast bias was reduced from an annual mean of 13% with WRF to 3% with WRFBC, while maintaining a high model–observation correlation.
