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Page 1© Crown copyright 2004 AER sub-project: report to GEMS plenary Olivier Boucher GEMS - Kick-off meeting - 4-6 July 2005
Page 2© Crown copyright 2004 GEMS-aerosol mailing list firstname.lastname@example.org Archive on http://wwsympa.univ-lille1.fr/wws Please ask me if you would like to be added on the list. Minutes and list of actions to be circulated on this mailing list.
Page 3© Crown copyright 2004 WP1 - Direct modelling Very good start! Initial focus on dust and sea-salt (next 2 months) Modelling of other aerosol components (BC, OC, sulfate, BB) Testing of parametrisations ------------------------------------------------------------------------- Action: meeting to be arranged between MetOffice/SA-UPMC/ECMWF to address the issue of stratospheric aerosols Action: check with RAQ how best we can best provide boundaries Model validation of transport needed: trop-strat exchange
Page 4© Crown copyright 2004 WP2 - Emissions Inventory of inventories available! Dust and sea-salt emissions are parametrized. Biomass burning: GWEM, modified for fire counts + BUOYANT analytical model for height Consistency with other sub-projects Vertical dependence (stack heights) Diurnal, weekly, and seasonal variations
Page 5© Crown copyright 2004 WP3 - Data assimilation The logical split of work is - background error covariance matrix: ECMWF - observation error covariance matrix: CEA-IPSL-LSCE with inputs from ECMWF, CNRS-LOA, and Met Office. Meeting to be arranged. Set up a methodology and apply it to MODIS/MERIS/ATSR/SEVIRI ------------------------------------------------------------------------- Action: meeting to be arranged between SA-UPMC/ECMWF/IASB to address the issue of data assimilation for stratospheric aerosols
Page 6© Crown copyright 2004 WP4 - Model evaluation - Correlation coefficients (observed vs simulated aerosol properties) - current models perform well on monthly means - challenge will be to get good correlation on daily means - Linear fits: slope, offset - Root-mean square errors - largely used in RAQ - Taylor diagrams - summarizes model performance in terms of correlation coefficient, standard deviation, and RMS. - Figures of merit - useful to test the transport for particular events - has been used for ETEX
Page 7© Crown copyright 2004 WP4 - Model evaluation Report on skill scores: earlier delivery (T0+6months) Initial focus on dust and sea-salt (next 2 months) measurement groups to come with selection of events periods cover years 2000 and 2003/2004 subset of AERONET stations, GAW sites, lidar site table (lat, long, aerosol prop, sampling) ==> JJM More complete model evaluation table of skill scores for aerosol properties and dataset AEROCOM validation + more detailed validation using additional in-situ surface and aircraft data 2000 and 2003/2004 for consistency with other sub-projects
Page 1© Crown copyright 2004 Skill scores for GEMS-aerosol Olivier Boucher GEMS - Kick-off meeting July 2005.
GEMS-Aerosol WP_AER_4: Evaluation of the model and analysis Lead Partners: NUIG & CNRS-LOA Partners: DWD, RMIB, MPI-M, CEA- IPSL-LSCE,ECMWF, DLR (at no.
GEMS Kick-Off Meeting, Hamburg Aerosols: WP1 Jean-Jacques Morcrette, Olivier Boucher With contributions at ECMWF from: Soumia Serrar: handling of surface.
Emissions in GEMS Data on emissions are needed for the 4 sub-systems GHG, GRG, AER and RAQ GEMS Project has dedicated tasks for emissions and surface fluxes.
Operational assimilation of dust optical depth Bruce Ingleby, Yaswant Pradhan and Malcolm Brooks © Crown copyright 08/2013 Met Office and the Met Office.
GEMS coordinating meeting - Reading - 15 December 2003 Current status of GEMS-Aerosol Olivier Boucher (LOA / CNRS / USTL) + aerosol partners.
GEMS AEROSOL WP2 refinement of aerosol emission sources M.Sofiev Air Quality Research Finnish Meteorological Institute.
Martin G. Schultz, MPI Meteorology, Hamburg GEMS proposal preparation meeting, Reading, Dec 2003 GEMS RG Global reactive gases monitoring and forecast.
Slide 1 Dust Modelling Workshop, 26 Feb08 Dust Modelling Workshop, Reading U., 26 February 2008 Modelling dust aerosols for the ECMWF IFS J.-J. Morcrette,
year analysis Upgrade + integration Direct model implementation BB sources Soil dust 1D-VAR /4D-VARadjointization analysis Evaluation.
Rong-Ming Hu and Randall Martin Inspiring Minds. Retrieval of Aerosol Single Scattering Albedo (SSA) Determined with radiative transfer calculation.
1 Examining Seasonal Variation of Space-based Tropospheric NO 2 Columns Lok Lamsal.
Evaluation of GEOS-CHEM Aerosol Optical Thicknesses : comparisons to satellite data for 2003 S. Generoso & I. Bey LMCA, EPFL, Lausanne, Switzerland Acknowledgements.
Page 1 © Crown copyright 2004 Aircraft observations of Biomass burning aerosol Ben Johnson, Simon Osborne & Jim Haywood AMMA SOP0 Meeting, Exeter, 15 th.
Global Climatology of Fine Particulate Matter Concentrations Estimated from Remote-Sensed Aerosol Optical Depth Aaron van Donkelaar 1, Randall Martin 1,2,
Estimation of the contribution of mineral dust to the total aerosol depth: Particular focus on Atlantic Ocean G. Myhre, A. Grini, T.K. Berntsen, T.F. Berglen,
GEMS Kick-Off Meeting, Hamburg Aerosols: WP3 Jean-Jacques Morcrette, Olivier Boucher With contributions at ECMWF from: Angela Benedetti: background error.
AERONET in the context of aerosol remote sensing from space and aerosol global modeling Stefan Kinne MPI-Meteorology, Hamburg Germany.
Dust aerosols in NU-WRF – background and current status Mian Chin, Dongchul Kim, Zhining Tao.
Sylvia Generoso, Isabelle Bey Evaluation of aerosol and CO distributions from boreal fires in GEOS-Chem using satellite products Preliminary results using.
Modelling the radiative impact of aerosols from biomass burning during SAFARI-2000 Gunnar Myhre 1,2 Terje K. Berntsen 3,1 James M. Haywood 4 Jostein K.
Preliminary Evaluation of LMDz-INCA Against SOP2 Observations I. Bouarar, M. Pham, K. Law (S.A.) D. Hauglustaine (L.S.C.E.), F. Hourdin (I.P.S.L). AMMA.
MPI-Meteorology Hamburg, Germany Evaluation of year 2004 monthly GlobAER aerosol products Stefan Kinne.
AIRS Radiance and Geophysical Products: Methodology and Validation Mitch Goldberg, Larry McMillin NOAA/NESDIS Walter Wolf, Lihang Zhou, Yanni Qu and M.
Global Aerosol Forecasting System Applications to Houston/Costa Rica Aura Validation Experiments Arlindo da Silva Global Modeling and Assimilation Office,
Main Topic: Vertical Characterization of Aerosols Sub-topic: Tropospheric and Stratospheric Aerosol Erin Robinson, July5, 2010.
Wildfire Emission Modelling in GEMSJ. Kaiser IGBP-QUEST Fire Workshop, Exeter, October 2005Slide 1 Wildfire Emission Modelling in GEMS Johannes Kaiser.
Evaluation aerosol CCI satellite retrievals MACC assimilations Reading 2012.
On contribution of wild-land fires to atmospheric composition M.Prank 1, J. Hakkarainen 1, T. Ermakova 2, J.Soares 1, R.Vankevich 2, M.Sofiev 1 1 Finnish.
The Zambezi River Valley and surrounding areas, July, 2011.
Incorporating Satellite Time-Series data into Modeling Watson Gregg NASA/GSFC/Global Modeling and Assimilation Office Topics: Models, Satellite, and In.
Using MODIS fire count data as an interim solution for estimating biomass burning emission of aerosols and trace gases Mian Chin, Tom Kucsera, Louis Giglio,
Chemical Data Assimilation: Aerosols - Data Sources, availability and needs Raymond Hoff Physics Department/JCET UMBC.
Page 1© Crown copyright 2006 Modelled & Observed Atmospheric Radiation Balance during the West African Dry Season. Sean Milton, Glenn Greed, Malcolm Brooks,
A. Morrow, R. V. Martin, S. Sharma, L. Huang, A. Herber, R. Leaitch, J. Burkehart, S. M. Li, and P. Liu NETCARE Workshop November 4 th 2014 Understanding.
PREV AIR : An operational system for air quality monitoring and forecasting presented by Laurence Rouïl.
Solène Turquety – AGU fall meeting, San Francisco, December 2006 High Temporal Resolution Inverse Modeling Analysis of CO Emissions from North American.
Transpacific transport of anthropogenic aerosols: Integrating ground and satellite observations with models AAAR, Austin, Texas October 18, 2005 Colette.
1 1. FY09 GOES-R3 Project Proposal Title Page Title: Trace Gas and Aerosol Emissions from GOES-R ABI Project Type: GOES-R algorithm development project.
Retrieving sources of fine aerosols from MODIS/AERONET observations by inverting GOCART model INVERSION: Oleg Dubovik 1 Tatyana Lapyonok 1 Tatyana Lapyonok.
© Crown copyright Met Office An Introduction to PRECIS PRECIS Workshop, University of Reading, 13 th -17 th May, 2013.
QA filtering of individual pixels to enable a more accurate validation of aerosol products Maksym Petrenko Presented at MODIS Collection 7 and beyond Retreat.
Estimating PM 2.5 from MODIS and MISR AOD Aaron van Donkelaar and Randall Martin March 2009.
Land Surface Evaporation 1. Key research issues 2. What we learnt from OASIS 3. Land surface evaporation using remote sensing 4. Data requirements Helen.
TNO experience M. Schaap, R. Timmermans, H. Denier van der Gon, H. Eskes, D. Swart, P. Builtjes On the estimation of emissions from earth observation data.
Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting October 2005, Ljubljana, Slovenia.
Page 1© Crown copyright Aircraft observations of mineral dust.
C. sampling strategy D. source configuration F. source-receptor matrix I. estimation of fluxes J. strategy evaluation uncertainty G. concentration pseudo-data.
Transpacific transport of pollution as seen from space Funding: NASA, EPA, EPRI Daniel J. Jacob, Rokjin J. Park, Becky Alexander, T. Duncan Fairlie, Arlene.
Developing Daily Biomass Burning Inventories from Satellite Observations and MOPITT Observations of CO during TRACE P Colette Heald Advisor: Daniel Jacob.
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