Analysis of PBL Turbulent and Non-turbulent Fluxes M. Hicks 1, S. Kang 2, B. Demoz 1, E. Joseph 1, 1 Howard University, Washington, DC, USA 2 UCAR, Boulder,

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Presentation transcript:

Analysis of PBL Turbulent and Non-turbulent Fluxes M. Hicks 1, S. Kang 2, B. Demoz 1, E. Joseph 1, 1 Howard University, Washington, DC, USA 2 UCAR, Boulder, CO, USA

Outline Overview HUBC Characteristics Methodology Preliminary Results Future Work

Motivation Previous (observational and model) studies have suggested that strong heterogeneous CBLs can produce non-turbulent fluxes at scales with magnitudes comparable to turbulent fluxes (Kang and Davis 2008, Kang et al. 2007, LeMone et al. 2002, Mahrt et al. 1994a,b) Implying turbulent theory may fail under these conditions From (Kang, 2008)

Objective & Purpose Objective –Examine the importance of non-turbulent to turbulent heat and moisture transport in a heterogeneous CBL. Look at the importance of presenting a proper timescale Purpose –Analyze the non-turbulent and turbulent characteristics of fluxes at HUBC through tower observation No one has used tower observations to examine non- turbulent flux exchanges

Howard University Beltsville, MD Research Campus Site Characteristics –Located 12 miles NE of Washington, DC –Heterogeneous landscape –Experiences a wide range of water vapor and aerosol concentrations HU Beltsville Campus

Methodology 1.Apply FFT and MR Spectra analysis to find timescale,, needed to separate turbulent and non-turbulent fluxes –The traditional 30 minute may not be sufficient in eliminating non-turbulent fluxes for heterogeneous cases. (Vickers and Mahrt 2003) 2.Examine the contribution of non-turbulent fluxes to total flux X Tot =X-, X NT =[X]-, X T =X-[X]

Case Study

Preliminary Results Vertical velocity energy pass 100 sec is small as expected WVMR has strong energy exchanges around 1000 sec A timescale less much less than 30mins is needed to separate T and NT fluxes The NT fluxes are not very strong

Separating Fluxes Green~ Instantaneous timeseries red ~mesoscale averaged timeseries, [X] blue ~domain averaged timeseries, X’=X- X NT =[X]-, X T =X-[X]

Preliminary Results The intensity of W T transport of non- turbulent heat is clearly seen The lack of intensity from pure non- turbulent mesoscale flux is seen

Summary We showed that a 30 minute timescale average may not always represent pure turbulence. –It is believed that including non-turbulence can give a bias to CBL parameterizations Interscale flux maybe able to explain intense moments of non-turbulence

Future Work Make Further progress with analysis surface layer CBL turbulent and non-turbulent fluxes Expand diagnosis to examine flux characteristics of the well mixed and inversion layers of the heterogeneous CBL. –Summer 2010 HUBC Field Campaign Tethersonde Balloon HURL ~1min MDE wind profiler ~1min Microwave Radiometer (r,T) ~2min Leosphere lidar ~10s Radiosondes

Acknowledgements I thank all supporters of this work, –Dr. Songlak Kang for suggestions –Dr. Belay Demoz –Dr. Everette Joseph –Dr. Demetrius Venable and HURL team –NCAS for support

Backup Slides

Overview Why Study PBL Fluxes??? –Fluxes play a critical role in the development of the height of the PBL Operational obs of PBL heights are not taken to validate forecast model parameterizations –Models at time can significantly over or under estimate PBL heights

From Kang et al., 2007

Monin-Obukov Similarity theory Businger et al. 1971

Kang and Davis 2008 Weak heterogeneous case Strong heterogeneous case Turbulent flux Interscale flux Non-Turbulent flux

Preliminary Results Green line is instantaneous timeseries, X red line is mesoscale averaged timeseries, [X] blue line is domain averaged timeseries, F(sec -1 ) X NT =[X]-, X T =X-[X] F(sec -1 )