The revised Diagnostics of 2m Values - Motivation, Method and Impact -

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

4. 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? DWD COSMO Cracow 2008 Matthias Raschendorfer

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

6. 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 At that point SMA couldn’t correct the discrepancy any longer Artificial soil moistening may have caused artificial evaporation accompanied by a too moist and too cold boundary layer 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 DWD COSMO Cracow 2008 Matthias Raschendorfer

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

8. Period of soil moisture adoption 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.

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

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

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

16. For “summer”

17. For winter

18. Mean surface flux densities:

21. LME ROUT LME ROUT

22. Conclusion: Discrepancy between the transfer layer of a mean model grid box and a SYNOP lawn caused - 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 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) - 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! DWD COSMO Cracow 2008 Matthias Raschendorfer

23. Thank You for attention!

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

25. For “summer”

26. For winter

27. LME ROUT LME ROUT

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