Versions Compared

Old Version 115

changes.mady.by.user Michela Giusti

Saved on

compared with

New Version 116

changes.mady.by.user Michela Giusti

Saved on

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

Expand
titleTable 4: assimilated satellite observations (real-time)


Instrument

Satellite

Space Agency

Data Provider

Species

MODIS

EOS-Aqua, EOS-Terra

NASA

NASA

AOD

MLS

EOS-Aura

NASA

NASA

O3 profile

OMI

EOS-Aura

NASA

KNMI

O3

OMPS

NOAA-20*, Suomi NPP

NOAA

EUMESAT

O3 layers

IASI

METOP-B, METOP-C

EUMETSAT/CNES

AC-SAF

CO

MOPITT

EOS-Terra

NASA

NCAR

CO

GOME-2

METOP-B, METOP-C

EUMETSAT/ESA

AC-SAF

O3, NO2, volcanic SO2

PMAp

METOP-B, METOP-C

EUMETSAT

EUMETSAT

AOD

TROPOMI

Sentinel-5p

ESA/NSO

ESA/KNMI/DLR

O3, volcanic SO2, NO2, CO

VIIRS

 S-NPP and NOAA20 

NOAA

NOAA/Eumetsat

AOD

IASI

METOP-B, -C

EUMETSAT/CNES

ULB/LATMOS

volcanic SO2

SLSTR

Sentinel-3

ESA/EUMETSAT

EUMETSAT

AOD


...

Expand
titleTable 5: monitored satellite observations (real-time)


Instrument

Satellite

Space Agency

Data Provider

Species

GOME-2

METOP-B, METOP-C

EUMETSAT/ESA

AC-SAF

HCHO

SLSTR

Sentinel-3A, Sentinel-3B

EUMETSAT/ESA

EUMETSAT

AOD

TROPOMI

Sentinel-5p

ESA/NSO

ESA/KNMI/DLR

HCHO

VIIRS

 NOAA21

NOAA

NOAA/Eumetsat

AOD

OMPS

NOAA-21

NOAA

EUMESAT

O3 limb-profile, O3 nadir-profile

GEMS

GK-2B

NIER

NIER

O3, NO2

TEMPO

TEMPO

NASA

NASA

O3, NO2


...

Implementation dateCycleSummary of changesResolution/Resolution changeNew species
12 May 202650r1

Atmospheric composition, Meteorology

Horizontal: 40km, Vertical: 137 levels

With the implementation of the IFS Cycle 50r1 a subset of model levels forecast fields is available every hourly step

12 November 202449r1

Atmospheric composition, Meteorology

Horizontal: 40km, Vertical: 137 levels

none

27 June 202348r1

Atmospheric composition, Meteorology, GRIB encoding

Horizontal: 40km, Vertical: 137 levels

See parameters in green in tables below

1 Feb 202347r3Assimilation of AOD from VIIRS 
none
15 Dec 202247r3Update of the T159 background error covariance wavelet file to use the correct NWP background errors. The update leads to considerably improved NWP forecast scores.  As a consequence, smaller changes to AOD and upper tropospheric and lower stratospheric ozone are also expected.Horizontal: 40km, Vertical: 137 levelsnone
22 Feb 202247r3A fix of low-level T/q in fog conditions was introduced with the 12 UTC cycle on 22 Feb 2022Horizontal: 40km, Vertical: 137 levelsnone
12 October 202147r3Atmospheric composition, MeteorologyHorizontal: 40km, Vertical: 137 levelsnone
18 May 2021 (12UTC cycle)47r2Atmospheric composition, MeteorologyHorizontal: 40km, Vertical: 137 levelsnone
6 October 202047r1Atmospheric composition, MeteorologyHorizontal: 40km, Vertical: 137 levelsnone
9 July 201946r1Atmospheric composition, MeteorologyHorizontal: 40km, Vertical: from 60 to 137 levelsAerosols: nitrate and ammonium
26 June 201845r1Atmospheric composition, MeteorologyHorizontal: 40km, Vertical: 60 levelsSee Table 1 and 2
26 September 201743r3Atmospheric composition, MeteorologyHorizontal: 40km, Vertical: 60 levelsnone
24 January 201743r1Atmospheric composition, MeteorologyHorizontal: 40km, Vertical: 60 levelsnone
21 June 201641r1Atmospheric composition, MeteorologyHorizontal: from 80km to 40km, Vertical: 60 levelsnone

...

Access to CAMS global air quality forecast and analysis data through the ECMWF public Web API service ended on 30 June 2021.

The data are also available through ECMWF Dissemination for a feeservice charge. In this way, users can select the data needed and they will be automatically delivered. Data can be configure and order from the ECMWF Product Requirements Catalogue.

Users with direct access to MARS can browse the data on the MARS catalogue under class=mc and expver= 0001.

...

Variations in delivery times may occur due to the non-operational nature of this ADS service, as issues may arise which cause delays. For any time-critical work, users should rely on ECMWF SFTP service or they can automatically receive the data through ECMWF Dissemination for a fee (data can be configure and order from the ECMWF Product Requirements Catalogue).

Spatial grid

CAMS Global atmospheric composition forecasts data currently has a resolution of approximately 40 km (approximately 0.35 degrees). The data are archived either as spectral coefficients with a triangular truncation of T511 or on a reduced Gaussian grid with a resolution of N256. These grids are so called "linear grids", sometimes referred to as TL511. 

...

  • Agustí-Panareda, A., Diamantakis, M., Massart, S., Chevallier, F., Muñoz-Sabater, J., Barré, J., Curcoll, R., Engelen, R., Langerock, B., Law, R. M., Loh, Z., Morguí, J. A., Parrington, M., Peuch, V.-H., Ramonet, M., Roehl, C., Vermeulen, A. T., Warneke, T., and Wunch, D., 2019: Modelling CO2 weather – why horizontal resolution matters, Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019
  • Agusti-Panareda, A., M. Diamantakis, V. Bayona, F. Klappenbach, and A. Butz, 2017: Improving the inter-hemispheric gradient of total column atmospheric CO2 and CH4 in simulations with the ECMWF semi-Lagrangian atmospheric global model, Geosci. Model Dev., 10, 1-18, https://doi.org/10.5194/gmd-10-1-2017
  • Agustí-Panareda, A., Massart, S., Chevallier, F., Balsamo, G., Boussetta, S., Dutra, E., and Beljaars, A., 2016: A biogenic CO2 flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO2 analyses and forecasts, Atmos. Chem. Phys., 16, 10399–10418, https://doi.org/10.5194/acp-16-10399-2016
  • Agustí-Panareda, A., Massart, S., Chevallier, F., Boussetta, S., Balsamo, G., Beljaars, A., Ciais, P., Deutscher, N. M., Engelen, R., Jones, L., Kivi, R., Paris, J.-D., Peuch, V.-H., Sherlock, V., Vermeulen, A. T., Wennberg, P. O., and Wunch, D., 2014: Forecasting global atmospheric CO2, Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014
  • Barré, J., Aben, I., Agustí-Panareda, A., Balsamo, G., Bousserez, N., Dueben, P., Engelen, R., Inness, A., Lorente, A., McNorton, J., Peuch, V.-H., Radnoti, G., and Ribas, R.: Systematic detection of local CH4emissions anomalies combining satellite measurements and high-resolution forecasts, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-550, in review, 2020.
  • Bozzo, A. and Benedetti, A. and Flemming, J. and Kipling, Z. and Rémy, S., 2020: An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF, Geosci. Model Dev., 3, 1007–1034, https://doi.org/10.5194/gmd-13-1007-2020
  • Diamantakis, M. and Agustí-Panareda, A., 2017: A positive definite tracer mass fixer for high resolution weather and atmospheric composition forecasts, ECMWF Technical Memoranda, No. 819, 2017.
  • Flemming, J., Huijnen, V., Arteta, J., Bechtold, P., Beljaars, A., Blechschmidt, A.-M., Diamantakis, M., Engelen, R. J., Gaudel, A., Inness, A., Jones, L., Josse, B., Katragkou, E., Marecal, V., Peuch, V.-H., Richter, A., Schultz, M. G., Stein, O., and Tsikerdekis, A., 2015: Tropospheric chemistry in the Integrated Forecasting System of ECMWF, Geosci. Model Dev., 8, 975–1003, https://doi.org/10.5194/gmd-8-975-2015
  • Flemming, J. and Benedetti, A. and Inness, A. and Engelen, R. J. and Jones, L. and Huijnen, V. and Remy, S. and Parrington, M. and Suttie, M. and Bozzo, A. and Peuch, V.-H. and Akritidis, D. and Katragkou, E., 2017: The CAMS interim Reanalysis of Carbon Monoxide, Ozone and Aerosol for 2003–2015,  Atmos. Chem. Phys.,17, 1945-1983, https://doi.org/10.5194/acp-17-1945-2017
  • Huijnen, V. and Flemming, J. and Chabrillat, S. and Errera, Q. and Christophe, Y. and Blechschmidt, A.-M. and Richter, A. and Eskes, H., 2016: C-IFS-CB05-BASCOE: stratospheric chemistry in the Integrated Forecasting System of ECMWF, Geosci. Model Dev., 9, 3071–3091, https://doi.org/10.5194/gmd-9-3071-2016
  • Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M., 2019: The CAMS reanalysis of atmospheric composition, Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019
  • Inness, A. and Flemming, J. and Heue, K.-P. and Lerot, C. and Loyola, D. and Ribas, R. and Valks, P. and van Roozendael, M. and Xu, J. and Zimmer, W., 2019: Monitoring and assimilation tests with TROPOMI data in the CAMS system:
    near-real-time total column ozone, Atmos. Chem. Phys., 19, 3939–3962, https://acp.copernicus.org/articles/19/3939/2019/
  • Inness, A. and Coauthors, 2015: Data assimilation of satellite-retrieved ozone, carbon monoxide and nitrogen dioxide with ECMWF's Composition-IFS, Atmos. Chem. Phys., 15, 5275-5303, https://doi.org/10.5194/acp-15-5275-2015
  • Massart, S., Agusti-Panareda, A., Aben, I., Butz, A., Chevallier, F., Crevoisier, C., Engelen, R., Frankenberg, C., and Hasekamp, O., 2014: Assimilation of atmospheric methane products into the MACC-II system: from SCIAMACHY to TANSO and IASI, Atmos. Chem. Phys., 14, 6139–6158, https://doi.org/10.5194/acp-14-6139-2014
  • Massart, S., Agustí-Panareda, A., Heymann, J., Buchwitz, M., Chevallier, F., Reuter, M., Hilker, M., Burrows, J. P., Deutscher, N. M., Feist, D. G., Hase, F., Sussmann, R., Desmet, F., Dubey, M. K., Griffith, D. W. T., Kivi, R., Petri, C., Schneider, M., and Velazco, V. A., 2016: Ability of the 4-D-Var analysis of the GOSAT BESD XCO2 retrievals to characterize atmospheric CO2 at large and synoptic scales, Atmos. Chem. Phys., 16, 1653–1671, https://doi.org/10.5194/acp-16-1653-2016
  • Rémy, S. and Kipling, Z. and Flemming, J. and Boucher, O. and Nabat, P. and Michou, M. and Bozzo, A. and Ades, M. and Huijnen, V. and Benedetti, A. and Engelen, R. and Peuch, V.-H. and Morcrette, J.-J., 2019: Description and evaluation of the tropospheric aerosol scheme in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS-AER, cycle 45R1), Geosci. Model Dev., 12, 4627-4659, https://doi.org/10.5194/gmd-12-4627-2019
  • Chabrillat, S., Rémy, S., Errera, Q., Huijnen, V., Bingen, C., Debosscher, J., Hendrick, F., Metzger, S., Mora, A., Minganti, D., Op de beek, M., Reisenfeld, L., Williams, J. E., Eskes, H., and Flemming, J., 2025: Modelling stratospheric composition for the Copernicus Atmosphere Monitoring Service: multi-species evaluation of IFS-COMPO Cy49, Geosci. Model Dev., 18, 8973–9014, https://doi.org/10.5194/gmd-18-8973-2025


Info
iconfalse

This document has been produced in the context of theCopernicus Atmosphere Monitoring Service (CAMS).

The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of CAMS on behalf of the European Union (Delegation Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view.

...