Evaluating the WRF model’s ability to predict extreme temperatures : a record-breaking high temperatures case in the Basque Country
- 1Basque Meteorology Agency (EUSKALMET), Basque Country, Spain
- 2BRTA, Tecnalia, Weather & Climate Area, Basque Country, Spain
The summer of 2022 in the Basque Country was characterized by extremely dry and hot conditions. In a major part of the region, precipitation levels were 50% below average, and the mean temperature was 2.4 ºC higher than the 1981-2010 climatology. This made it the warmest summer on record, second only to 2003. In the midst of this arid and sweltering season, a historic persistent and high temperatures event occurred between July 13th and 18th. During the episode, maximum temperatures exceeded 40 ºC in some areas for several consecutive days, with the highest recorded temperature reaching 43.6 ºC. Minimum temperatures were also persistently high, with some stations not dropping below 20 or even 25 ºC during the warmest days.
Given the extreme and challenging context in terms of surface heating and evapotranspiration, we assessed the ability of the WRF model with a operational forecasting configuration to reproduce the observed atmospheric conditions during the estudied case. Although wind patterns and hourly temperature evolution where generally well-reproduced, maximum temperatures were slightly underestimated and minimum temperatures were greatly overestimated in some areas. Specifically, the WRF configuration did not accurately capture the local weakening of wind at night and the subsequent formation of surface-based thermal inversions on days when offshore southerly winds prevailed.
In this work we present different aspects related with the fine-tune temperature prediction during this significant heatwave episode. We present results from different sensitivity experiments on the operational configuration. We tested various dynamics options, finer land-use databases, and physical parameterizations. We also include some comparison results with other forecast systems available in Euskalmet as other mesoescale models or statistical prediction systems.
How to cite: Arrillaga, J. A., R. Gelpi, I., Diaz de Arcaya, A., Castaño, A., and Gaztelumendi, S.: Evaluating the WRF model’s ability to predict extreme temperatures : a record-breaking high temperatures case in the Basque Country, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-255, https://doi.org/10.5194/ems2023-255, 2023.