1. Penn State K. Davis, K. Craig, A. Desai, S. Kang, B. Reen, S. Richardson, N. Seaman and D. Stauffer Department of Meteorology The Pennsylvania State University University Park, PA Mesoscale variability in convective boundary layer structure observed during IHOP: Causes and implications for convective initiation

2. Penn State Acknowledgements and Collaborators DIAL groups –NASA Langley, LASE, Browell, Ismail et al –CNRS France, LEANDRE, Flamant et al –DLR Germany, DLR DIAL, Ehret et al University of Wyoming King Air team –Field crew –LeMone et al, NCAR Land surface modeling/fluxes –ALEXI project, U. Wisconsin, J. Mecikalski –NOAH LSM, Chen and Manning, NCAR Add ground-based profiling groups, NAST NCAR-ATD –ISFF group –Parsons, Weckwerth, Tignor, Baeuerele, many others UCAR/JOSS NSF Atmospheric Sciences Division (IHOP) NASA Land Surface Hydrology program (SGP97)

3. Penn State overview Goals/background Products we propose to create Preliminary results –Large scale ABL heterogeneity –Small scale ABL heterogeneity –Attempt to model ABL heterogeneity

4. Penn State Background – land surface processes and ABL development Modeling studies have suggested that land surface conditions are critical to properly predict moist convection in the Great Plains (Avissar et al). RAMS, cloud fields Surface observations have shown little climatological connection between surface energy balance heterogeneity and mesoscale flow (Shaw, Doran et al). OK surface met data ABL observations are often absent or scarce in previous studies. The ABL is critical to this question. Where available, ABL observations have shown only modest mesoscale flow in the presence of strong but fairly small scale (10- 20 km) flux heterogeneity (Sun et al, Ehret et al). BOREAS - DLR Larger-scale (~250 km) ABL heterogeneity has been observed and tentatively linked to the surface energy budget (Desai et al, Reen et al). SGP97 – LASE

5. Penn State Goals Building blocks –Document mesoscale heterogeneity in the atmospheric boundary layer (ABL). DIAL, DOW, HRDL, UWKA –Map the surface energy budget over the same mesoscale region. ALEXI, NOAH, ISFF, UWKA Role of the land surface –Examine the degree to which land surface heterogeneity is responsible for ABL heterogeneity. MM5, observations –Examine the potential for land-atmosphere interactions to focus the initiation of moist convection. MM5, observations Data assimilation –Examine the degree to which improved ABL and land surface data improve model predictions of ABL development and moist convection. MM5, observations Model development –Evaluate the ability of ABL and land surface models to simulate the structures observed during IHOP. MM5, observations, ABL and LS model choices New area of focii? –Mesoscale rolls – appeared on many BLH day, possibly important for CI –Microscale structure of the entrainment zone

6. Penn State Methods (to date) Airborne lidar. 200-300 km scale. –Backscatter for ABL depth. ~10m x 10m resolution. –Differential absorption lidar (DIAL) for ABL H 2 O mixing ratio –Doppler lidar for turbulent vertical winds U. Wyoming King Air. 60 km scale. –Turbulent variables, fluxes Surface flux towers –Spaced along King Air flight tracks Remote sensing, land surface models. IHOP domain –Map surface energy budget Mesoscale model. IHOP domain. –Determine the degree to which the surface energy budget governs mesoscale heterogeneity in the ABL. Collect observations for at least 10 days over the same region. Go beyond case studies. All BLH days.

7. Penn State Completed Missions 12 BLH missions with joint airborne H 2 O lidar and flux aircraft operations. No cases that led directly to deep convection. Dates spanning 19 May through 22 June, 2002.

8. Penn State BL Heterogeneity Mission Example29 May, 2002

9. Penn State Expected Products High-resolution ABL depth and water vapor maps for all BLH missions (joint with lidar groups). Add ground-based profilers, NAST? Surface energy balance maps for all BLH missions (joint with NCAR, UWisconsin). MM5 reanalysis fields for all BLH missions, including airborne lidar data assimilation. Suitable to submit to JOSS as merged “data” products? Would IHOP scientists use these products?

10. Penn State Preliminary findings Surface energy budget heterogeneity was extreme Kang –Persistent, climatological east-west gradient –Local variations due to recent precipitation ABL heterogeneity was evident –East-west gradient was realized in different ways depending on atmospheric environment Craig –Some local heterogeneity was also persistent over time, suggesting land-surface origins Kang, Craig Comparisons of ABL-LSM schemes within MM5 show a great deal of variability among model formulations. Reen

11. Penn State East – West moisture gradient and its impact on the ABL

12. Penn State Station7(E) Station1(W) Station4(C) Persistent west to east soil moisture gradient Station 1 = west. Station 4 = central. Station 7 = east. Intense rainfall associated with frontal passage.

13. Penn State station1station2station3 East – west soil moisture gradient is reflected in U. Wyoming King Air flux measurements WEST: L=125 W m -2 Line represents 10km UWKA latent heat flux measurements. EAST: L=300 W m -2 Apparent error in eastern flux towers on this date.

14. Penn State East-west soil moisture gradient also evidentin indirect flux estimates derived via computermodels, and based on satellite surface temps.

15. Penn State 19 May 12 UTC29 May 12 UTC SOUNDINGS (Dodge City) Strong capping inversion Strong surface energy balance gradient Weak capping inversion Strong surface energy balance gradient

16. Penn State 19 May 2002 1845-1926 UTC 29 May 2002 1839-1913 UTC LEANDRE FLIGHT TRACKS Strong capping inversion Strong surface energy balance gradient Weak capping inversion Strong surface energy balance gradient

17. Penn State West East 35 km LEANDRE: 19 May 2002 Pre-front of 23-24 May. Strong capping inversion.300 km scale CBL heterogeneity.CBL depth as seen via lidar backscatter.

18. Penn State LEANDRE: 19 May 2002 35 km West East

19. Penn State West East 37 km LEANDRE: 29 May 2002 Post-front of 23-24 May. Weak capping inversion.300 km scale CBL heterogeneity.CBL depth as seen via lidar backscatter.

20. Penn State 37 km West East LEANDRE: 29 May 2002

21. Penn State LEANDRE H 2 O VAPOR 29 May 2002

22. Penn State BL Heterogeneity Mission Example29 May, 2002

23. Penn State LASE: 30 May, 2002. An additional view of CBL heterogeneity with a weak capping inversion. CBL depth via lidar backscatter, and CBL H 2 O content via DIAL.

24. Penn State Visible Satellite: 30 May 2002, 2007 UTC

25. Penn State Smaller scale heterogeneity: Along the UW King Air flight track

26. Penn State station7 station9 station8 Eastern soil moisture conditions remain fairly homogeneous throughout the study.

27. Penn State station2 station1 station3 Western soil moisture conditions become quite Heterogeneous, especially around 27 May.

28. Penn State station1station2 station3 U Wyoming King Air flux latent heat flux observations (line) reflect the south to north soil moisture gradient along the “Homestead track”

29. Penn State BL Heterogeneity Mission Example29 May, 2002

30. Penn State DLR lidar shows the context of the UW King Air observations along this N-S gradient. Is the ABL heterogeneity closely tied to soil conditions? Pattern was repeated on multiple DLR Falcon passes over 3 hours. South North

31. Penn State Case study: Southern Great Plains 97 Experiment, 12-13 July, 1997 Desai et al, in prep; Reen et al, in prep NASA LASE backscatter from the NASA P-3.Wavelet ABL top derivation, Davis et al, 2000.250 km, N-S flight track in central Oklahoma. Moist soils, North; Dry soils, South.

32. Penn State Attempts to model coupled land surface - ABL development using MM5: SGP97 example Spatial variability is difficult to reproduce. Role of the surface energy balance is not entirely clear. Different ABL-LSM schemes give very different mean ABL heights and mixing ratios. Reen et al, in prep North, moist, recent rainfall South, dry Approx wet/dry soil line

33. Penn State Good ideas? Centrally choreographed instrument intercomparison work Centrally choreographed data assimilation efforts Central guidance on the creation(?) of a project reanalysis product