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K. Davis, K. Craig, A. Desai, S. Kang, B. Reen, S. Richardson, N. Seaman and D. Stauffer

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

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K. Davis, K. Craig, A. Desai, S. Kang, B. Reen, S. Richardson, N. Seaman and D. Stauffer

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  1. Mesoscale variability in convective boundary layer structure observed during IHOP: Causes and implications for convective initiation 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

  2. 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. overview • Goals/background • Products we propose to create • Preliminary results • Large scale ABL heterogeneity • Small scale ABL heterogeneity • Attempt to model ABL heterogeneity

  4. 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. 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. Methods (to date) • Airborne lidar. 200-300 km scale. • Backscatter for ABL depth. ~10m x 10m resolution. • Differential absorption lidar (DIAL) for ABL H2O 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. Completed Missions • 12 BLH missions with joint airborne H2O lidar and flux aircraft operations. • No cases that led directly to deep convection. • Dates spanning 19 May through 22 June, 2002.

  8. BL Heterogeneity Mission Example 29 May, 2002

  9. 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. 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. East – West moisture gradient and its impact on the ABL

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

  13. station1 station2 station3 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. East-west soil moisture gradient also evident in indirect flux estimates derived via computer models, and based on satellite surface temps.

  15. SOUNDINGS (Dodge City) 19 May 12 UTC 29 May 12 UTC Strong capping inversion Strong surface energy balance gradient Weak capping inversion Strong surface energy balance gradient

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

  17. 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. East West 35 km

  18. LEANDRE: 19 May 2002 East West 35 km

  19. 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. East West 37 km

  20. LEANDRE: 29 May 2002 East West 37 km

  21. LEANDRE H2O VAPOR 29 May 2002

  22. BL Heterogeneity Mission Example 29 May, 2002

  23. LASE: 30 May, 2002.An additional view of CBL heterogeneity with a weak capping inversion.CBL depth via lidar backscatter, and CBL H2O content via DIAL.

  24. Visible Satellite: 30 May 2002, 2007 UTC

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

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

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

  28. U Wyoming King Air flux latent heat flux observations (line) reflect the south to north soil moisture gradient along the “Homestead track” station1 station2 station3

  29. BL Heterogeneity Mission Example 29 May, 2002

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

  31. Case study: Southern Great Plains 97 Experiment, 12-13 July, 1997 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. Desai et al, in prep; Reen et al, in prep

  32. Attempts to model coupled land surface - ABL development using MM5:SGP97 example North, moist, recent rainfall Approx wet/dry soil line Reen et al, in prep South, dry • 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.

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

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