Joint MAP D-PHASE Scientific Meeting - COST 731 mid-term seminar, May 2008, Bologna. ErgebnissErgebniss : Long-Term Evaluation of COSMO-DE and COSMO-EU Forecasts Within General Observation Period (GOP) 2007: First Results Thorsten Reinhardt, Susanne Crewell, Christoph Selbach Universität zu Köln, Institut für Geophysik und Meteorologie, Zülpicher Str. 49a, Köln, Germany Integrated Water Vapor (IWV) Outlook Cloud Base Height (Ceiling) Cloud base height data: - from DWD ceilometer stations (yellow) Fig 5: Ceilometer network.  Regime-related model deficits Are certain model deficits connected with specific regions or weather situations?  Error structure in the hydrological cycle Are there multivariate error patterns? Cross-correlate model errors of different quantities - integrated water vapor - cloud base height - surface precipitation - cloud properties (with J. Fischer & S. Stapelberg, FU Berlin) cloud optical thickness, cloud top pressure, synthetic vs observed brightness temperatures Area-dependency in model deficits? Acknowledgements The authors are grateful to Deutscher Wetterdienst for providing model and ceilometer data and to GFZ Potsdam for providing GPS IWV data. References: Baldauf, M.; Förstner, J.; Klink, S.; Reinhardt, T.; Schraff, C.; Seifert, A.; Stephan, K. (2006): Kurze Beschreibung des Lokal-Modells Kürzestfrist LMK und seiner Datenbanken auf dem Datenserver des DWD. Deutscher Wetterdienst, Offenbach, 70 p. Guerova, G., E. Brockmann, J. Quiby, F. Schubiger, and C. Matzler (2003): Validation of NWP mesoscale models with Swiss GPS network AGNES. J. Appl. Meteorol., 42, 1, Schulz, J.-P.; Schättler, U. (2005): Kurze Beschreibung des Lokal- Modells LME und seiner Datenbanken auf dem Datenserver des DWD. Deutscher Wetterdienst, Offenbach, 65 p. Vömel, H. et al. (2007): Radiation dry bias of the Vaisala RS92 humidity sensor., J. Atmos. Oceanic Technol., 22, Fig 7: Diurnal cycle of cloud base height bias (upper panel) and RMSE (lower panel) of COSMO-DE vs ceilometer. Dec Colors indicate start times of model (see Fig. 2). Data with observations > 5000m not taken into account. Fig 6: Two-dimensional frequency distribution of COSMO- DE model vs ceilometer-observed cloud base height. Full year  Cloud base height in model not unambiguously determinable. Which threshold of fractional cloud cover to apply?  E.g. few cases (as in Dec.2007, Fig 7) with low stratus in observation (but not in simulation) can dominate monthly statistics. Cloud base height evaluation not as straightforward as IWV:  Model IWV bias mainly depends on the start time of the model  Model runs started at 12, 15, 18 (,21) UTC are significantly drier than those started at 00…. 09 UTC  COSMO-EU dryer than COSMO-DE  Diurnal cycle in COSMO-DE better than in COSMO-EU The model runs started at 12, 15, 18 (and, to some extent, 21 UTC) are significantly drier than those started at 00, 03, 06, 09 UTC. The likely reason for this behavior is that in the first group of model runs (started UC) the water vapor information from 12-UTC ascends enters while in the second group of model runs the water vapor information from 00-UTC ascends is ingested (see Fig. 4). A similar difference has been reported by Guerova etal. (2003) for a previous version of the COSMO model for Switzerland. Especially in COSMO-DE the dryer model runs (started 12, 15, 18 UTC) gain moisture with time in their first forecast hours. RMSE increases with forecast lead time, as to be expected. Model vs GPS GPS IWV data: -from GFZ Potsdam (red) -from Swiss AGNES network (blue) Radiosonde vs GPS Fig. 4: Mean difference between night-time and day-time IWV Bias (RS-GPS) for different radiosonde stations and months (of 2007). A comparison of radiosonde vs GPS IWV observations revealed that 12-UTC IWV observations by radiosonde ascents were significantly dryer than those from 00- UTC ascents (Fig. 4). The bias between radiosonde and GPS differs from station to station, but is for all stations greater at 12 UTC than at 00 UTC. The reason for this difference between 00 UTC and 12 UTC is probably a daytime dry bias of about 7% in radiosonde humidity measurements due to radiative effects (Vömel et al., 2007), whereas GPS IWV observations do not show such a dependency on time of the day. Fig 1: GPS network. Fig 2: Diurnal cycle of IWV bias (upper panel) and RMSE (lower panel) of COSMO-DE vs GPS, Feb.-Sep Colors indicate start time of model runs. Fig 3: As Fig. 2, but for COSMO-EU. COSMO-DE (2.8 km mesh size, permitting explicit convection on grid scale, see Baldauf et al, 2006) Day 1 00UTC Day 2 00UTC + 21 h forecast 7 forecasts for given target time! Day 1 3 UTC Day 1 6 UTC Day 1 9 UTC Forecasts started every 3 h: Lagged forecast ensemble Day 1 21 UTC DWD Routine Models COSMO-EU (7 km mesh size, parameterized (Tiedtke) convection, see Schulz & Schättler, 2005)