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Dust modelling Earth Science BSC activites ●BSC - DREAM8b 72h daily forecast - ●BSC - DREAM8b evaluation.

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Presentation on theme: "Dust modelling Earth Science BSC activites ●BSC - DREAM8b 72h daily forecast - ●BSC - DREAM8b evaluation."— Presentation transcript:

1 Dust modelling Earth Science BSC activites ●BSC - DREAM8b 72h daily forecast - ●BSC - DREAM8b evaluation activities - DREAM improvement (Pérez et al., 2006a; Pérez et al., 2006b) - BoDEx model intercomparison (Todd et al., 2008) - DREAM8b vs. SAMUM-I (Haustein et al., 2009; GRL) - DREAM8b vs. AERONET 2004 (Basart et al., 2011) ●NMMB NWP model development and evaluation - NMMB/BSC-DUST (Perez et al., 2011; Haustein et al., 2011) - NMMB/BSC-CHEM (Poster Jorba et al., 2011) - NMMB/BSC-DUST with aerosols (AERO) Earth Sciences Department, Barcelona Supercomputing Center (BSC-CNS), Barcelona, Spain Environmental Modeling Laboratory, Technical University of Catalonia (UPC), Barcelona, Spain

2 NCEP-NMMB ●Non-hydrostatic Multiscale Model at the Arakawa B grid ●Still under development at NCEP (Janjic, 2005; Janjic and Black, 2007) ●Follows the general modeling philosophy of the WRF-NMM (Janjic, 2001; 2003) ●Hence the evolution of ETA model with updated meteorological core ●Built on NWP experience by relaxing hydrostatic approximation ●Unified model for a broad range of spatial and temporal scales ●Developed within the Earth System Modeling Framework (ESMF) ●Arakawa B grid and regular (global) or rotated (regional) lat/lon coordinate ●Lorenz vertical staggering and Pressure-sigma hybrid coordinate ●Adams-Bashforth/Crank-Nicholson for horizontal/vertical advection ●The non-hydrostatic option as an add-on module ●NMMB regional will become the next-generation NCEP mesoscale model for operational weather forecasting in 2011 replacing NAM (WRF-NMME) model

3 RUN DYNAMICSRUN PHYSICS Coupler DYN-PHYS Dynamics export T, U, V, Q, CW, Q2, OMGALF Coupler DYN-PHYS Physics Export T, U, V, Q, CW, Q2 ATM Structure of NMMb using Earth System Modeling Framework (ESMF)

4 RUN DYN (DUST, CHEM hadv,vadv and hdiff) RUN PHYS (Dust Emission, vdiff, deposition, chem emission, vdiff, photolysis, chemical mechanism, deposition) Coupler DYN-PHYS Dynamics export T, U, V, Q, CW, Q2, OMGALF, DUST, CHEM Coupler DYN-PHYS Physics Export T, U, V, Q, CW, Q2, DUST, CHEM ATM NMMb/BSC-DUST-CHEM using Earth System Modeling Framework (ESMF) DUST and gas-phase CHEM modules fully embeded within the atmospheric driver

5 NMMB/BSC-DUST ●NMMB/BSC - DUST is embedded into the NMMB model and solves the mass balance equation for dust taking into account the following processes similar to the design of BSC-DREAM8b  dust generation/emission by surface wind  horizontal and vertical advection  vertical transport/diffusion by turbulence and convection  dry deposition and gravitational settling - sedimentation, gravitational settling (Stokes-Cunningham approx.) and surface layer parameterization  wet removal including in-cloud and below-cloud scavenging - dust scavenging is computed separately for convective and grid-scale precipitation - Ferrier grid-scale microphysics and BMJ convective adjustment scheme - Below cloud scavenging in each layer (Slinn, 1984; Loosmoore and Cederwall, 2004)  RRTM SW/LW dust radiative feedback

6 MODEL RESULTS Regional test case  Regional North African domain at 0.25x0.25º spatial resolution  40 vertical layers and fundamental time step of 40 seconds  1x1º NCEP analysis meteorology data reinitialized every 24 hours  updated of boundary conditions every 6 hours  Non-hydrostatic physics and dust cold start period of 3 days  SAMUM-I period May 2006  BoDEx period March 2005  Dust storm in March 2004 BSC - Mare Nostrum

7 RESULTS: SAMUM-I SAMUM-I on 18 May 2006 abc e f d

8 RESULTS: SAMUM-I a c e g b d f h Day of May 2006 Stations a e h f c b d g red - AERONET blue - Bodélé green - EARLINET  Naples  Athens  Thessaloniki SAMUM-I

9 RESULTS: SAMUM-I a b c d e f g h j k SAMUM-I

10 RESULTS: SAMUM-I a b c d e j k SAMUM-I djek

11 bc f g ed a RESULTS: SAMUM-I

12 NMMB/BSC-DUST (NCEP-FNL) Day of March 2005 NCEP (FNL) 1 x 1 analysis PIBAL sonde wind speed at Chicha RESULTS: BoDEx Bodélé Stations

13 RESULTS: BoDEx Sunphotometer Chicha

14 RESULTS: Dust Event Perfect dust storm on 3 March 2004 LDA MSG/SEVIRI product ab c e f d For more information on LDA MSG/SEVIRI product → Govaerts et al., 2010

15 RESULTS: Dust Event Perfect dust storm on 3 March 2004 LDA MSG/SEVIRI product ab c e f d For more information on LDA MSG/SEVIRI product → Govaerts et al., 2010

16 Conclusion ●NMMB/BSC-DUST versus SAMUM-I - Good qualitative reproduction of the dust cycle but moderate differences - Very good temporal agreement between model and AERONET AOD - Acceptable agreement in the profiles between model and EARLINET lidars - Model wind is fairly well simulated from NMMB (no radiative feedback here) ●NMMB/BSC-DUST versus BoDEx - The Bodélé low level jet (LLJ) can be nicely identified in the model - Peak wind speeds are underestimated nonetheless over the Bodélé - Diurnal 2m temperature depends heavily on initial soil moisture data - Soil moisture feeds also back model wind, hence simulated dust uptake

17 GLOBAL ANNUAL Rosenstiel School Miami Network sites NMMB/BSC-DUST Total surface concentration observations

18 GLOBAL ANNUAL AERONET sites NMMB/BSC-DUST Total AOD observations

19 Simulation: Global simulation for year º x 0.5º x 40 vertical levels Cold start without data assimilation Initial conditions from NCEP analysis 1x1º. Meteorological fields updated with NCEP every 24 hours. Aeronet validation:  Aeronet data here is Coarse AOD (mainly dust over dust affected stations)  We validate daily averages NMMb/BSC-Dust 2006 global simulation

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25 AERONET BCN site MPLidar Technical University of Catalonia (UPC), Barcelona-Spain

26 THANK YOU FOR YOUR ATTENTION Acknowledgements This work is funded by the projects CGL , CGL , CGL of the Spanish Ministry of Science and Innovation. Simulations have beenperformed in the Marenostrum supercomputer. We thank the AERONET and EARLINET community for their valuable data as well as the SAMUM-I and BoDEx people for providing their comprehensive data. C. Pérez O. Jorba S. Basart K. Haustein K. Serradell F.Martínez J.M. Baldasano


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