In the current work we present six hindcast WRF (Weather Research and Forecasting model) simulations for the EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with different configurations in microphysics, convection and radiation for the time period 1990–2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic temperature and precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly linked to the Grell–Devenyi convection and CAM (Community Atmosphere Model) radiation schemes, intensifies the negative bias in summer temperatures over northern Europe (max −2.5 °C). Conversely, a strong positive bias in downward shortwave radiation in summer over central (40–60%) and southern Europe mitigates the systematic cold bias over these regions, signifying a typical case of error compensation. Maximum winter cold biases are over northeastern Europe (−2.8 °C); this location suggests that land–atmosphere rather than cloud–radiation interactions are to blame. Precipitation is overestimated in summer by all model configurations, especially the higher quantiles which are associated with summertime deep cumulus convection. The largest precipitation biases are produced by the Kain–Fritsch convection scheme over the Mediterranean. Precipitation biases in winter are lower than those for summer in all model configurations (15–30%). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature and precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest pathways for model improvement.

The existence of African easterly waves (AEWs) north of the African easterly jet (AEJ) core with maximum amplitude at low levels has been confirmed and clarified using radiosonde data and the U.K. Meteorological Office global model analysis from the hurricane season of 1995. At Bamako (12.5°N, 8.0°W) the AEWs were characterized mainly by maximum amplitudes at the level of the AEJ (around 700 mb), whereas at Dakar (14.7°N, 17.5°W) the waves were characterized by maxima between 850 and 950 mb. The low-level waves to the north of the AEJ arise in association with baroclinic interactions between the negative meridional potential vorticity (PV) gradients in the jet core and the positive low-level gradient of potential temperature, θ, enhanced by the presence of low-static-stability air north of the AEJ. These waves follow the positive meridional θ gradients over northern Africa in contrast to the jet-level AEWs that follow the meridional PV gradients at the level of the AEJ. Cross-correlation analysis... Abstract The existence of African easterly waves (AEWs) north of the African easterly jet (AEJ) core with maximum amplitude at low levels has been confirmed and clarified using radiosonde data and the U.K. Meteorological Office global model analysis from the hurricane season of 1995. At Bamako (12.5°N, 8.0°W) the AEWs were characterized mainly by maximum amplitudes at the level of the AEJ (around 700 mb), whereas at Dakar (14.7°N, 17.5°W) the waves were characterized by maxima between 850 and 950 mb. The low-level waves to the north of the AEJ arise in association with baroclinic interactions between the negative meridional potential vorticity (PV) gradients in the jet core and the positive low-level gradient of potential temperature, θ, enhanced by the presence of low-static-stability air north of the AEJ. These waves follow the positive meridional θ gradients over northern Africa in contrast to the jet-level AEWs that follow the meridional PV gradients at the level of the AEJ. Cross-correlation analysis...

This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.