GIDAS Richard Engelen The GIDAS crew Antje Miha

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G-IDAS Richard Engelen

G-IDAS Richard Engelen

The G-IDAS crew Antje Miha Richard Martin Angela Luke

The G-IDAS crew Antje Miha Richard Martin Angela Luke

Deliverables Deliverable Description Delivery date D_G-IDAS_1. 1 Integrated system based on GEMS Month 1

Deliverables Deliverable Description Delivery date D_G-IDAS_1. 1 Integrated system based on GEMS Month 1 D_G-IDAS_1. 2 Updated system for reanalysis Month 12 D_G-IDAS_2. 1 NRT global analyses and forecasts 12 -hourly from month 1 D_G-IDAS_2. 2 Delayed-mode global analyses and forecasts Monthly from month 7 D_G-IDAS_2. 3 Extension of GEMS reanalysis Month 12 D_G-IDAS_3. 1 Web-based information system Periodic from month 4 D_G-IDAS_3. 2 Web based monitoring and validation Periodic from month 4 D_G-IDAS_3. 3 Web-based graphical display and supply of data Periodic from month 4 Status

Deliverables Deliverable Description Delivery date D_G-IDAS_1. 3 Updated and validated system for G-IDAS_2 Month

Deliverables Deliverable Description Delivery date D_G-IDAS_1. 3 Updated and validated system for G-IDAS_2 Month 18 D_G-IDAS_1. 4 Updated system for GAS Month 29 D_G-IDAS_2. 1 NRT global analyses and forecasts 12 -hourly from month 1 D_G-IDAS_2. 2 Delayed-mode global analyses and forecasts Monthly from month 7 D_G-IDAS_2. 4 MACC reanalysis Month 29 D_G-IDAS_3. 1 Web-based information system Periodic from month 4 D_G-IDAS_3. 2 Web based monitoring and validation Periodic from month 4 D_G-IDAS_3. 3 Web-based graphical display and supply of data Periodic from month 4 D_G-IDAS_3. 4 Report on validation of preoperational global service Month 29 Status

Milestones Deliverable Description Delivery date Status M_G-IDAS_1 NRT production Month 1 On time M_G-IDAS_2

Milestones Deliverable Description Delivery date Status M_G-IDAS_1 NRT production Month 1 On time M_G-IDAS_2 Initial global service provision Month 4 On time M_G-IDAS_3 Start of delayed-mode production Month 7 Slightly delayed M_G-IDAS_4 Start of MACC reanalysis Month 13 Started early M_G-IDAS_5 Upgraded global system Month 19 On time M_G-IDAS_6 System ready for GAS Month 29 No GAS yet

NEAR-REAL-TIME

NEAR-REAL-TIME

60 Meteorological observations 50 40 30 20 10 0 1996 1997 1998 1999 2000

60 Meteorological observations 50 40 30 20 10 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 40 Number of observations used per day (millions) CONV+AMV TOTAL 30 20 10 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Megha Tropiques Sentinel 3 GOSAT ADM Aeolus Earth. CARE SMOS TERRA/AQUA AMV GMS/MTSAT Rad GOES Rad METEOSAT Rad FY-2 C/D AMV GMS/MTSAT AMV GOES AMV HY-2 A METEOSAT AMV Oceansat JASON-1/2/3 Quik. SCAT FY-3 A/B AURA AQUA TRMM GCOM-W/C CHAMP/GRACE TERRASAR-X/SAC-C COSMIC ENVISAT ERS-1/2 METOP DMSP NOAA

Atmospheric Composition

Atmospheric Composition

Planned → passive → active The global system produces daily plots of observation-model difference

Planned → passive → active The global system produces daily plots of observation-model difference statistics passive active Time series and geographical plots are generated to monitor the input data, but also to provide feedback to data providers. From planned to active for MOPITT CO observations

Atmospheric Composition

Atmospheric Composition

NRT production MACC has continuously delivered daily near-real-time analyses and forecasts. Significant MACC developments

NRT production MACC has continuously delivered daily near-real-time analyses and forecasts. Significant MACC developments are in place for first MACC-II upgrade.

Use of global NRT production Boundary condition server RAQ WMO SDS-WAS

Use of global NRT production Boundary condition server RAQ WMO SDS-WAS

Developments • Dual-mode aerosol • Capability to assimilate CALIPSO aerosol lidar data • Changes

Developments • Dual-mode aerosol • Capability to assimilate CALIPSO aerosol lidar data • Changes in ozone bias correction (MLS added as anchor) Dual-mode aerosol • Combined assimilation of IASI and MOPITT CO • Assimilation of OMI SO 2 to detect volcanic ash plumes Aerosol lidar data

DELAYED-MODE

DELAYED-MODE

Delayed Mode The aim and challenge of the delayed-mode run is to provide optimal

Delayed Mode The aim and challenge of the delayed-mode run is to provide optimal analyzed fields to be used in flux inversions or as boundary conditions for regional studies. A secondary aim is to support development of new retrievals of CH 4 and CO 2.

Delayed-mode CO 2 CH 4 A significant amount of the synoptic variability of the

Delayed-mode CO 2 CH 4 A significant amount of the synoptic variability of the greenhouse gases is driven by the meteorology. However, the surface fluxes drive the signature of low and high concentrations.

CH 4 assimilation in delayed-mode run GOSAT IASI SCIAMACHY

CH 4 assimilation in delayed-mode run GOSAT IASI SCIAMACHY

REANALYSIS

REANALYSIS

Reanalysis

Reanalysis

Reanalysis • 2003 – 2010 • T 255 L 60 = 80 km on

Reanalysis • 2003 – 2010 • T 255 L 60 = 80 km on 60 levels • Coupled to MOZART chemical transport model • Aerosols, reactive gases, and greenhouse gases on top of meteorology • New emissions (anthropogenic, fires, lightning) • Use of Variational Bias Correction (Var. BC)

Global data server users Reanalysis data has been downloaded by users around the world.

Global data server users Reanalysis data has been downloaded by users around the world.

State of the Climate Total AOD anomaly 2011 AOD anomaly for biomass burning SON

State of the Climate Total AOD anomaly 2011 AOD anomaly for biomass burning SON 2011 The aerosol reanalysis has earned its place in the State of the Climate of the American Meteorological Society

Volcanic SO 2 Significant progress has been made in the simulation and data assimilation

Volcanic SO 2 Significant progress has been made in the simulation and data assimilation of volcanic ash plumes. The AOD anomaly is complemented by a SO 2 plume through the assimilation of OMI data.

Volcanic SO 2 The assimilation of OMI SO 2 data produces a plume that

Volcanic SO 2 The assimilation of OMI SO 2 data produces a plume that is confirmed by the IASI SO 2 detection.

GLOBAL SERVICES

GLOBAL SERVICES

Web site Web server distributed over MACC partners. Thousands of plots are generated each

Web site Web server distributed over MACC partners. Thousands of plots are generated each day.

Web site use 2011

Web site use 2011

Monitoring/verification Input data is monitored and output data is continuously checked against independent observations.

Monitoring/verification Input data is monitored and output data is continuously checked against independent observations.

GDA

GDA

Changes compared to G-IDAS • More interaction between GDA and other subprojects. ECMWF personnel

Changes compared to G-IDAS • More interaction between GDA and other subprojects. ECMWF personnel will work on GDA and the sub-project of their specialization • Stronger focus on data acquisition, data dissemination, meta data development, web, … • Put procedures in place for running a reliable operational global service

Plans • • GDA. 1: Coordination • • • Coordination of GDA work Coordination

Plans • • GDA. 1: Coordination • • • Coordination of GDA work Coordination of interaction with other sub-projects Coordination of interaction with ECMWF developments GDA. 2: Integration of new developments • • • Model and data assimilation developments Integrated global analysis and forecasting system Adaptation to new input data streams Adaptation to new output data streams Interaction with external GMES-related research developments

Plans • • GDA. 3: Global production • • Near-real-time production Delayed-mode production Reanalyses

Plans • • GDA. 3: Global production • • Near-real-time production Delayed-mode production Reanalyses for atmospheric composition Support for science community and space agencies GDA. 4: Global services • • • Monitoring and verification Product display, supply, and general web services User support

Exciting improvements C-Tessel Additional satellite observations Groundbased data GLOMAP C-IFS Better integration with NWP

Exciting improvements C-Tessel Additional satellite observations Groundbased data GLOMAP C-IFS Better integration with NWP

MACC-II NRT assimilation and forecasting chain ENS FC 22 07 Global DA/FC Clock time

MACC-II NRT assimilation and forecasting chain ENS FC 22 07 Global DA/FC Clock time Global data acquisition 18 21 00 06 03 Global assimilation window 09 12 15 18 21 00 UTC ENS FC @ 00 UTC for 96 h (4 days) Analysis Model time Global FC @ 00 UTC for 120 h (5 days)

Delayed-mode system Satellite data In-situ data Data Assimilation Improved prior fluxes Flux inversion Optimized

Delayed-mode system Satellite data In-situ data Data Assimilation Improved prior fluxes Flux inversion Optimized fluxes Forward run Boundary conditions

Optimized CO 2 flux run

Optimized CO 2 flux run

Reanalysis • Continuation of MACC reanalysis for 2011 and 2012 • Focused short reanalyses

Reanalysis • Continuation of MACC reanalysis for 2011 and 2012 • Focused short reanalyses using new ESA-CCI data sets • Interact with ECMWF Reanalysis group on future developments

Web and data services • Redesign of web site • User-friendly interface for data

Web and data services • Redesign of web site • User-friendly interface for data • Operational data streams on ftp More routine monitoring and verification plots available for users and validation groups.