1. The correction of initial values of temperature at low model levels Blinov D. Revokatova A. Rivin G. Rozinkina I. Sapuncova E.

2. Motivation Temperature, model errors (COSMO-Ru7): in most cases underestimation of T at the surface Winter, January, 17-31, 2014 Summer, August, 13-22, 2013 Less convective mixing Severe underestimation of temperature at low model levels (winter) Low qulity of forecast It leads to more stable stratification High overestimation of pollutants concentration, ecological aspects (COSMO-ART) H, m

3. The idea: To correct initial values of temperature at low model levels by using observations (temperature at 2 meters) Algorithm: 1.Interpolation of t2m to the model grid. Based on Rivin G., Heise E. «Operational DWD numerical forecasts as input to flood forecasting models», Computational Science and High Performance Computing, Spinger Berlin / Heidelberg, p. 83-97, 2006. Cressman scheme: For each grid point 4 point neighborhood with different effective radiuses have been chosen (10, 40, 70 and 110 km ) For each station k, in the point neighborhood horizontal distance from the grid (ρh) and ρv difference in height therebetween were calculated. Then factor (coeffitient) by which the temperature at the station k taken into account during the interpolation was determined. If sum of Σw > threshold values, than

4. Algorithm: 2. Correction of temperature al low models level: Assume that at GME analysis of temperature (T) field at 925 hPa (~550 m) is pretty exactly (due-to using of atmospheric sounding data) Thus we need to correct T at low model levels. And increment decreases with H. Monin-Obukhov theory (logarithmic temperature profile). GME temperature field at low model levels represent stratification. We are trying to keep it, thus increment should decrease with H. During the experiments the optimal amount of corrected levels was determed. 4 levels from surface Dependence of coefficient for T correction from H №40=10 m №39=35 m №38=69 m №37=96 m

5. Algorithm: 3. Correction of temperature in soils: Distribution of t2m (Obs) to the soils according to Fourier's laws As a result we got corrected (by t2m obs.) initial temperature field in soil and at 5 low model levels corrected soils

6. T_2M for Krasnaya Polyana at 12:00 15 February 2014 Errors in temperature field: The daytime temperature is underestimated, especially in clear sky conditions Sometimes temperature at 2m better in GME than DAS, In result temperature at surface and at low models levels than initial data from GME. On a 12-h forecast temperature error in GME is minimal, because surface analyze for initial GME data exist.

7. Results GME Corrected ProfilerObsRadiosonde Temperature profile, 13.02.2012 from 00 UTC to 12 h

8. GME Corrected ProfilerObsRadiosonde Temperature profile, 26.02.2012 from 00 UTC to 12 h GME Corrected ProfilerObsRadiosonde Temperature profile, 26.02.2012 from 00 UTC to 12 h GME Corrected ProfilerObsRadiosonde Temperature profile, 26.02.2012 from 00 UTC to 24 h

9. Results GMECorrectedObs Temperature at 2 meters, 13.02.2012 from 12 UTC to 72 h

10. Dependence of T profile changes on forecast time

11. 25.06.2014, Forecast UTC 00 + 72 h. Belgorod. Convective precipitation (RAIN_CON) UTC 00 + 5 h There is no convective precipitation in modif. exp. at 5 and 11 Vertical profile of temperature With corrected T. Without corrected T. ! ! 8 4

12. Lipeck 25.06.2014, Forecast UTC 00 + 72 h. Lipeck Convective precipitation (RAIN_CON) UTC 00 + 7 h !! There is no convective precipitation in modif.exp. at 7 and 8 h Vertical profile of temperature Without corrected T. With corrected T. 10 5

13. Brief conclusions: Temperature at low model levels and in soil can (and shall!) be corrected using synoptic observation (t2m). Special module for such correction was developed in Russian Hydrometcentre. This module technically is ready for operational use This module was tested (for COSMO-Ru7) and show good results: initial field of temperature can be improved, and quality of t2m forecast increases. In some cases convective precipitation can decreased due to changes in temperature profiles. Large-scale precipitation configuration almost does not change.

14. Future Plans Do more experiments for statistics of errors Assessment of precipitation change (after implementation of the correction module). Especially convective precipitation. Coupling with DAS Implementation of the temperature correction module to the COSSMO-Ru forecast (maybe with dependence of season: only cold?.. Only strong stable stratification, or inversion (no convective case))