Overview of WG5 activities and Conditional Verification Project Adriano Raspanti - WG5 Bucharest, September 2006

Arguments Brief report of WG 5 activities Agenda of WG5 parallel session in Bucharest Brief report CV project Some highlights of verification results

Report of WG 5 activities

CV Priority Project

CV Priority Project: some examples of results C= conditonalT=tot cloud cover O= filter on observationS= clear sky M= mask on forecast

CV Priority Project: some examples of results C= conditonalT=tot cloud cover O= filter on observationS= clear sky M= mask on forecast

CV Priority Project: some examples of results C= conditonalT=tot cloud cover O= filter on observationS= clear sky M= mask on forecast

CV Priority Project Probably another task about “Special case studies” should be added, such as a “very cold winter” or “rainy summer”. Some tasks of the Project will be revised

Highlights of verification results From DWD The main aspect of verification against surface weather observation was the monitoring of the new LME. A simple conditional verification was introduced. This cv explains that the negative temperature bias during winter time is dominated by cases with observations above 0°C. This type of verification shows also that problems with positive pressure bias is mostly connected with high pressure values. A comparison between operational LME (lowest model layer 10 m) results and test runs with the old LM (lowest model layer around 35 m) show the advantages of the new model especially concerning temperature forecasts during winter season.

Highlights of verification results From MCH The standard deviation of the pressure error (both PMSL and PS) is lower than in any previous autumn, winter and spring (less) The strong dry bias from previous winters in the dewpoint temperature (TD_2M) has disappeared, but this spring, a wet bias instead of the usual dry bias is visible (due to the introduction of the prognostic TKE scheme on 1 December 2005) The general cold bias in T_2M has disappeared The absolute precipitation bias (TOT_PREC) and the frequency bias for the 0.1mm/12h threshold are both larger than in all previous spring seasons except spring 2001

Highlights of verification results From MCH: about precipitation WINTER : Precipitation amounts are overestimated especially for gridpoints > 800m. The low amounts [0.1mm/6h] show an overestimation at all height ranges. The high amounts [10 mm/6h] are underestimated for gridpoints 1500m. The overall overestimation of precipitation for gridpoints < 1500 m comes from the strong overestimation for precipitation < 2mm/6h. SPRING 2006: Precipitation amounts have almost no bias for gridpoints 800m. The low amounts [0.1 mm/6h] show an overestimation at all height ranges. The high amounts [10 mm/6h] are underestimated for gridpoints 800m.

Highlights of verification results From MCH: OtherOther

Highlights of verification results From IMGW The 2 m temperature: A monthly and seasonal variation for the scores of temperature is observed.The mean error is negative in the winter and positive in spring and the summer. In the spring and summer we observed the large diurnal amplitude of mean error and amplitude of RMSE with maximum value during a day. The dew point temperature: The monthly variation of mean error is observed.The bias with the diurnal amplitude is observed in the spring. The RMSE increases with the forecast time.

Highlights of verification results From IMGW The sea level pressure: The RMSE and ME increases with the forecast time.The RMSE error is smaller in the spring and summer and higher in the winter. The ME is about zero in the first day (especially in winter) and negative in the following days. The 10 m wind speed: The ME is mostly positive and increases during the forecast. The RMSE is quite smooth. The model predicted more the precipitation than it occured

Highlights of verification results From CNMCA: precipitation Winter and Spring 2006 : generally there’s an over forecast of rainfall events, FBIAS>1, but with values better than the previous year especially for 06 hours cumulated rainfall; around FBI=1 for most of the ranges for mm thresholds with a decrease for higher thresholds. Rainfall amounts are overestimated especially over mountain area, even if relatively high POD can be found, but at same time low ETS and high FAR. Inner low land stations show better performances with lower FBIAS and high ETS and POD values versus thresholds.Winter Spring 2006

Highlights of verification results From CNMCA: precipitation Summer 2006: generally there’s an overforecast of rainfall events, FBIAS>1 (almost 2!), for lower thresholds and FBIAS<1 for higher thresholds; around FBI=1 for most of the ranges for mm thresholds. For all the stations plot the 06 cumulated precipitation has FBI=1 for almost all the thresholds (except for +12 and +36). Rainfall amounts are overestimated especially over mountain area. For all the stratifications ETS is extremely low.Summer 2006

Highlights of verification results From CNMCA: T2m Summer 2006: a diurnal cycle is present in the Mean Error, with max from 03 to 12 UTC (!) and a min at 18 UTC (15 UTC in 2005), except for Coastal stations that present their max values during early morning. Higher values for MAE when the max values in ME are reached. Worst performance for mountain stations, maybe due also to different altitudes between model and stations (no correction).Summer 2006