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The ICTP RegCM System and Aerosol Modeling F. Giorgi , F. Solmon , A. Zakey ICTP, Trieste, Italy Contributions from A. Shalaby , A. Konare ,. Goldschmidt 2009 Conference, Davos, Switzerland, 22-26 June 2009. The ICTP Regional Climate Model RegCM4. Used for a wide range
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The ICTP RegCM System and Aerosol Modeling F. Giorgi, F. Solmon, A. Zakey ICTP, Trieste, Italy Contributions from A. Shalaby, A. Konare, Goldschmidt 2009 Conference, Davos, Switzerland, 22-26 June 2009
The ICTP Regional Climate Model RegCM4 Used for a wide range of applications Flexible, user-friendly modeling system Adaptable to any region of the World Coupled atmosphere – ocean version Used by a wide scientific community Capability of interactive vegetation (CLM, IBIS) Capability of interactive aerosol/chemistry
Sample of RegCM domains used ΔX=10-120 KM
“Simple” Aerosols in RegCM4 General approach Tracer model / RegCM3 Primary Emissions Removal terms Physico – chemical transformations Transport Strongly dependent on the nature of the tracer Particles and chemical species considered (12 tracers). Sea-Salt (2 bins) 0.05-1 µm 1.0-10 µm Qian and Giorgi 1999; Qian et al. 2001; Solmon et al. 2006; Zakey et al. 2006; 2008
Climate-aerosol model coupling Regional Climate Model Winds, PBL Processes Clouds, Precipitation Semi-direct effects Clouds, Temperature, Water Vapor Aerosol Model Source, Transport, Removal Radiative Fluxes Heating Rate Aerosol Radiative Forcing Aerosol Concentration Aerosol Concentration Simple indirect effect scheme Rc = f(χ) Radiative Transfer Package SW and LW Cloud Reflectivity
Example I East Asia • During the last decades East Asia has been one of the most rapidly developing regions of the world • As a result, anthropogenic aerosol emissions over the region have considerably increased, thereby (possibly) affecting the climate of the region • A series of studies investigated the possible regional climatic effects of anthropogenic aerosols over East Asia • Qian and Giorgi (1999,2000), Qian et al. (2001, 2003), Chameides et al. (1999,2002),Streets and Waldhoff (2000),Kaiser and Qian (2002),Giorgi et al. (2002,2003)
Aerosol extinction coefficient averaged for 1981-1998Kaiser and Qian (2002) Change of observed mean temperature (oC) in ChinaQian and Giorgi (2000)
SO2 Burden, DJF, CONT SO4 Burden, DJF, CONT SO2 Burden, JJA, CONT SO4 Burden, JJA, CONT
Temperature, MAM, IND1-CONT Temperature, DJF, IND1-CONT Temperature, JJA, IND1-CONT Temperature, SON, IND1-CONT
Example II: Effect of dust on the African monsoon Solmon et al. 2006 Zakey et al. 2006 Konare et al 2008 Solmon et al. 2008
Case study: Dust storm of 20-28 February 2000 TOMS (aerosol index) SeaWIFS (NGSFC) RegCM (0.1-10 µm dust burden) Zakey et al, 2006
Validation in “climate” mode RegCM Lidar M’Bour Konaré et al., 2008; Solmon et al., 2008 MISR AOD JJA (2000-2006) RegCM AOD
Precipitation, CRU (1961-1990) – (1901-1980) The dust forcing can strengthen the occurrence of drought in the Sahel Precipitation Dust - nodust
Mean Landuse and Elevation 60-km Land surface sub-grid scale model in RegCM4 (Giorgi et al. 2003) • Define a regular fine scale sub-grid for each coarse scale model grid-box. • Landuse, topography, and soil are characterized on the fine grid. • Disaggregate climatic fields from the coarse grid to the fine grid (e.g. temperature, precipitation). • Disaggregation technique based on the elevation differences between the coarse grid and the fine grid. • Perform BATS surface physics computations on the fine grid. • Reaggregate the surface fields from the fine grid to the coarse grid.
60-km Numerical Experiments • Simulation period: 1 Oct 1994 to 1 Sept 1995 • Land Surface computations performed on subgrid. • CTL • 60-km; no subgrid cells • EXP15 • 15-km; 16 subgrid cells • EXP10 • 10-km; 36 subgrid cells 15-km 10-km
OBS (CRU) CTL EXP15 EXP10 OBS (CRU) CTL EXP15 EXP10 Results: Temperature WINTER (DJF) SUMMER (JJA)
Station OBS CTL EXP15 EXP10 WINTER (DJF) Station OBS CTL EXP15 EXP10 SPRING (MAM) Results: Snow
Domain envisioned for PAPRIKA PAPRIKA Nested Domain Dx = 15-20 km Sub-Grid Scheme, Dx=2-3 km CORDEX Domain Dx = 50 km
Key questions from the regional modeling side • What model development is needed? • Coupling with a “snow/glacier” module • Use simple parameterizations of snow albedo as a function of BC and Dust • Disaggregation of precipitation and temperature • What data can be used for model validation? • Atmospheric data • Other data? • What simulations will be performed? • RCM domain/resolution? • GCM(s)? • Scenarios? • Time slices?
Dynamical and precipitation response to dust forcing ( DUST -NODUST, JJA 1996-2006) ( NODUST, JJA 1996-2006) m.s-1 m.s-1 Mean circulation at 865 hpa Differential circulation at 865 hpa mm/day mm/day 15 Konaré et al., 2008; Solmon et al., 2008
Cloud water, meridional circulation and precipitation difference Dust – Nodust, 15W-15E Average Solmon et al., 2008 2 : ‘Elevated heat pump’ effect ( Lau et al., 2009) 1: Weakening of the ‘monsoon pump’ Dust heating rate
Dynamics: MM5 Hydrostatic (Giorgi et al. 1993a,b) Radiation: CCM3 (Kiehl 1996) Large-Scale Clouds & Precipitaion: SUBEX (Pal et al 2000) Cumulus convection: Grell (1993) Anthes-Kuo (1977) MIT (Emanuel 1991) Boundary Layer: Non-local,Holtslag (1990) Aerosols: SO4, OC, BC (Solmon et al 2005) Dust (Zakey et al 2006) Sea salt (Zakey et al. 2009) Gas phase chemistry: Shalaby et al. 2010 Land Surface: BATS (Dickinson et al 1993) SUB-BATS (Giorgi et al 2003) CLM (Steiner et al 2009) Tropical Band Coupled Lake (Host. Et al. 1994) Coupled Ocean MIT (Artale et al. 2010) ROMS (Ratnam et al. 2009) ICTP Regional Climate ModelRegCM4
The RegCM regional climate model systemParticipation to intercomparison projects • PIRCS (US, ISU) • NARCCAP (US, UCSC) • PRUDENCE (Europe, ICTP) • ENSEMBLES (Europe, ICTP) • CECILIA (Central Europe, Central-Eastern European partners) • AMMA (West Africa, ICTP, African partners) • CLARIS (South America, U. Sao Paulo) • RMIP (East Asia, CMA) • CORDEX (Multiple domains, RegCNET)
Number of papers using RegCM (from the ISI) 50 40 30 20 10 10 90 94 96 98 00 02 04 06 08 92