1. Boundary Layer Verification ECMWF training course May 2010 Maike Ahlgrimm

2. What does the BL parameterization do? Attempts to integrate effects of small scale turbulent motion on prognostic variables at grid resolution. Turbulence transports temperature, moisture and momentum (+tracers). Ultimate goal: correct model output

3. Which aspect of the BL can we evaluate? 1.2m temperature/humidity 2.Depth of BL 3.Diurnal variability of BL height 4.Structure of BL (temperature, moisture, velocity profiles) 5.Turbulent transport within BL 6.Boundaries: entrainment, surface fluxes, clouds etc. large scale small scale Chandra et al., sub. to J. Climate

4. Part 1 Depth of the boundary layer

5. BL depth from radiosondes Problem: Define the top of the BL! Concept: At he top of the BL, the air motion transitions from turbulent to laminar flow. For an equitable comparison, apply the same criteria for identification of this transition to model profiles and radiosonde profiles. Alternative for convectively driven boundary layers: turbulent mixing leads to T and q gradients at the BL top. Identify these gradients in the profile. DSE/cp Figure: Martin Köhler normalized BL height

6. Richardson number-based approach Richardson number defined as: flow is turbulent if Ri is negative flow is laminar if Ri above critical value calculate Ri for model/radiosonde profile and define BL height as level where Ri exceeds critical number buoyancy production/consumption shear production (usually negative) Ri=

7. Difficulties with this approach discrete model layers -> bulk Ri number where is the top and bottom of the bulk layer? how much do surface fluxes increase buoyancy? not most reliable model field for sonde profiles, surface fluxes usually unavailable noise in sonde profiles can introduce uncertainties diagnostic BLH in IFS is currently tuned to best agree with paramete- rization based BL height

8. How-to Need T, u,v,q,z and some constants Define conserved variable, e.g. virtual dry static energy: Apply smoothing in the vertical if necessary Starting at lowest model level, calculate Ri number, adding an excess to the dse to make up for missing surface fluxes Iterate, until Ri exceeds critical level (e.g. 0.25) Assign height of nearest layer as BL top height

9. Example: dry convective boundary layer NW Africa 2K excess 1K excess Theta [K] profiles shifted Figures: Martin Köhler

10. Example: Inversion-topped BL Inversion capped BLs dominate in the subtropical oceanic regions Identify height of jump across inversion EPIC, October 2001 southeast Pacific

11. Limitations of sonde measurements Sonde measurements are limited to populated areas Depend on someone to launch them (cost) Model grid box averages are compared to point measurements (representativity error)

12. Took many years to compile this map Neiburger et al. 1961

13. Calipso tracks Arabic peninsula - daytime CALIPSO tracks

14. BL from lidar how-to Easiest: use level 2 product (GLAS) Algorithm searches from the ground up for significant drop in backscatter signal Align model observations in time and space with satellite track and compare directly, or compare statistics surface return backscatter from BL aerosol molecular backscatter Figure: GLAS ATBD

15. Example: Lidar-derived BL depth from GLAS Only 50 days of data yield a much more comprehensive picture than Neiburgers map. Ahlgrimm & Randall, 2006

16. Limitations to this method Definition of BL top is tied to aerosol concentration - will pick residual layer Does not work well for cloudy conditions (excluding BL clouds), or when elevated aerosol layers are present Overpasses only twice daily, same local time Difficult to monitor given location

17. The case of marine stratocumulus Well mixed convective layer underneath strong inversion Are clouds part of the BL? As Sc transition to trade cumulus, where is the BL top?

18. Stratocumulus cloud top height Model underestimates Sc top height Köhler & Ahlgrimm, sub. Hannay et al. 2009 EPIC SEP

19. Part 2 Diurnal cycle of boundary layer height

20. Diurnal cycle of convective BL from radiosonde Example: stratocumulus-topped marine BL in the south-east Pacific: East Pacific Investigation of Climate (EPIC), 2001 Clear diurnal cycle of ~200m with minimum in early afternoon, maximum during early morning. Bretherton et al. 2004, BAMS

21. Diurnal cycle from CALIPSO

22. Part 3 Turbulent transport

23. Flux towers Example: Cabauw, 213m mast obtain measurements of roughness length, drag coefficients etc. KNMI webpage

24. Bomex: trade cumulus regime Stevens et al. 2001

25. Bomex - DualM Dual Mass Flux parameterization - example of statistical scheme mixing K-diffusion and mass flux approach Updraft and environmental properties are described by PDFs, based on LES Need to evaluate PDFs! Neggers et al. 2009

26. Turbulent characteristics: humidity Raman lidar provides high resolution (in time and space) water vapor observations Plot: Franz Berger (DWD)

27. Turbulent characteristics: vertical motion Observations from mm-wavelength cloud radar at ARM SGP, using insects as scatterers. Chandra et al., sub. to J. Climate local time reflectivity doppler velocity red dots: ceilometer cloud base

28. Turbulent characteristics: vertical motion Variance and skewness statistics in the convective BL (cloud free) from four summer seasons at ARM SGP Chandra et al., sub. to J. Climate

29. Part 4 Boundaries

30. Forcing BL turbulence driven through surface fluxes, or radiative cooling at cloud top. Check: albedo, soil moisture, roughness length, clouds BL top entrainment rate: important but elusive quantity

31. Entrainment rate - DYCOMS II Example: DYCOMS II - estimate entrainment velocity mixed layer concept: Stevens et al. 2003

32. Summary & Considerations What parameter do you want to verify? What observations are most suitable? Define parameter in model and observations in as equitable and objective a manner as possible. Compare! Are your results representative? How do model errors relate to parameterization?

33. References (in no particular order) Neiburger et al.,1961: The Inversion Over the Eastern North Pacific Ocean Bretherton et al., 2004: The EPIC Stratocumulus Study, BAMS Stevens et al., 2001: Simulations of trade wind cumuli under a strong inversion, J. Atmos. Sci. Stevens et al., 2003: Dynamics and Chemistry of Marine Stratocumulus - DYCOMS II, BAMS Chandra, A., P. Kollias, S. Giangrande, and S. Klein: Long-term Observations of the Convective Boundary Layer Using Insect Radar Returns at the SGP ARM Climate Research Facility, submitted to J. Climate Hannay et al., 2009: Evaluation of forecasted southeast Pacific stratocumulus in the NCAR, GFDL, and ECMWF models. J. Climate Köhler et al.: Stratocumulus in the ECMWF model. submitted to QJRMS Ahlgrimm & Randall, 2006: Diagnosing monthly mean boundary layer properties from reanalysis data using a bulk boundary layer model. JAS Neggers, 2009: A dual mass flux framework for boundary layer convection. Part II: Clouds. JAS