1. The revised Diagnostics of 2m Values - Motivation, Method and Impact - M. Raschendorfer, FE14 Matthias Raschendorfer DWD COSMO Cracow 2008

4. Matthias Raschendorfer DWD COSMO Cracow 2008 There was some significant overestimation of 2m temperature round noon at grid points with a rough surface (city points) accompanied by nearly saturated soil and too high 2m dew points Obviously SMA couldn’t correct this errors What was the reason? Could we expect related errors in other variables?

5. deviation of T2m compared to SYNOP- measure parameters controlling evapotranspiration: -soil moisture modified relation between sensible and latent heat flux daily cycle of boundary layer profiles for temperature and humidity Diagnosis onto 2m level daily cycle of T2m, TP2m turbulence model SMA -min. stomata resistance, PLCOV, LAI, root depth, sealing, soil type, … The feed back with soil moisture analysis SMA:

6. Matthias Raschendorfer DWD COSMO Cracow 2008 We assumed a systematic shortcoming in the calculation of 2m temperatures at grid points with a rough surface (city points) causing to high values at daytime SMA reacted by moistening the soil until it was saturated Artificial soil moistening may have caused artificial evaporation accompanied by a too moist and too cold boundary layer At that point SMA couldn’t correct the discrepancy any longer As a reason of that shortcoming we found a discrepancy between 2m values referring to the whole grid box and those taken at a standard SYNOP lawn

7. laminar layer logarithmic Prandtl- layer profile unstable stable linear interpolated Prandtl layer roughness layer expon. roughness- layer profile lowest model main level upper boundary of the lowest model layer lower boundary of the lowest model layer SYNOP station lawn profile Mean GRID box profile Turbulent velocity scale profile turbulence- scheme Exponential roughness layer profile is valid for the whole grid box, but it is not present at a SYNOP station no storage capacity Diagnosis of 2m-values with respect to a SYNOP lawn:

8. Accumulated soil moisture increments of SMA for routine and Exp 6343: The accumulated effect of SMA on soil moisture averaged along a domain that more or less covers Germany is plotted for the fist 6 weeks of Exp. 6343. For about the first 14 days SMA of Exp. 6343 (green and blue lines) takes water out of the soil, whereas SMA of our routine always brings additional water into the soil. During this period soil moisture has adapted to the new formulation of T2m diagnostics. Integrated along the whole 6 week period SMA of the routine has significantly moistened the soil, indicating a systematic error. In contrast SMA of Exp. 6343 shows almost no systematic trend. Period of soil moisture adoption

9. ( & ‘plant cover’ 70% & ‘surface height’800m) ‘city’ :=

10. Soil depth in [cm] Soil moisture profiles:

12. T2m of Exp. 6343 – T2m of r the routine Roughness length Joined frequency distribution of roughness length and difference of T2m:

16. For “summer”

17. For winter

18. Mean surface flux densities:

21. LME ROUT

22. Matthias Raschendorfer DWD COSMO Cracow 2008 Conclusion: Discrepancy between the transfer layer of a mean model grid box and a SYNOP lawn caused The introduction of a SYNOP lawn for deduction of 2m values cured the problem There are still problems with the daily cycle of near surface values (too warm at midnight) - daytime overestimation of T_2m compared to SYNOP measurement for rough grid points - a too wet soil and a too moist and too cold boundary layer due to the action of SMA - That may be cured by a reformulation of profile functions through the transfer layer - This step had to be delayed due to other priorities - We should introduce these steps now with first priority!

23. Thank You for attention!

24. Time-Height Cross-section for “errors” in the boundary layer: Temperature “error” Dew point “error” Too coldToo moist 800 m a.g. 0 m a.g.

25. For “summer”

26. For winter

27. LME ROUT

28. Advection of a warm bias Too cold from noon to night Still to cold during morning Downward mixing of positive bias above