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| Titel |
Analysis of Numerical Weather Predictions of Reference Evapotranspiration and Precipitation |
| VerfasserIn |
Theodor Bughici, Naftali Lazarovitch, Erick Fredj, Eran Tas |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250141250
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| Publikation (Nr.) |
 EGU/EGU2017-4737.pdf |
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| Zusammenfassung |
| This study attempts to improve the forecast skill of the evapotranspiration (ET0) and
Precipitation for the purpose of crop irrigation management over Israel using the Weather
Research and Forecasting (WRF) Model. Optimized crop irrigation, in term of timing and
quantities, decreases water and agrochemicals demand. Crop water demands depend on
evapotranspiration and precipitation. The common method for computing reference
evapotranspiration, for agricultural needs, ET0, is according to the FAO Penman-Monteith
equation. The weather variables required for ET0 calculation (air temperature, relative
humidity, wind speed and solar irradiance) are estimated by the WRF model. The WRF
Model with two-way interacting domains at horizontal resolutions of 27, 9 and 3 km is used
in the study. The model prediction was performed in an hourly time resolution and
a 3 km spatial resolution, with forecast lead-time of up to four days. The WRF
prediction of these variables have been compared against measurements from 29
meteorological stations across Israel for the year 2013. The studied area is small but with
strong climatic gradient, diverse topography and variety of synoptic conditions. The
forecast skill that was used for forecast validation takes into account the prediction
bias, mean absolute error and root mean squared error. The forecast skill of the
variables was almost robust to lead time, except for precipitation. The forecast skill was
tested across stations with respect to topography and geographic location and for all
stations with respect to seasonality and synoptic weather system determined by
employing a semi-objective synoptic systems classification to the forecasted days. It was
noticeable that forecast skill of some of the variables was deteriorated by seasonality and
topography. However, larger impacts in the ET0 skill scores on the forecasted day are
achieved by a synoptic based forecast. These results set the basis for increasing the
robustness of ET0 to synoptic effects and for more precise crop irrigation over Israel. |
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