Major components of the global climate system and their main interactions

What is a reanalysis?

A reanalysis provides a data-rich description of the recent climate by combining models with observations. To produce a reanalysis, weather observations collected in past decades are fed into a modern numerical weather prediction system, which provides a physically consistent description of the Earth system. Using a model simulation of the Earth system ensures that the reanalysis is physically consistent and spatially and temporally complete, and that it encompasses many variables for which observations are not always available. Constantly correcting the simulation towards past observations ensures that the reanalysis is consistent with those observations.

Reanalysis production

The project focus was on the production and assessment of multi-decadal reanalyses of the global climate system including atmosphere, land, ocean, and cryosphere, combined with consistent information on the carbon cycle. Two unique reanalyses have been produced:
  • CERA-C0C, the first European coupled ensemble of reanalyses spanning the whole 20th century (1901-2010), which includes gridded data for the ocean, sea-ice, land, atmosphere and carbon (CERA-20C-carbon);
  • CERA-SAT, the first European coupled ensemble of reanalyses spanning 9 years (2008-2016) of the satellite era, generated using all available observations.

Observational data sets

Substantial work was directed at data recovery, reprocessing, and quality control of input observations for reanalysis (Brönnimann et al, 2018, BAMS, in press), with emphasis on improving and extending the usable satellite climate data records, and expanding access to early 20th century in-situ observations. Observations rescued, post-processed and quality-controlled within the ERA-CLIM2 project were fed into existing international data repositories, so that they can be retrieved and used for any reanalysis' production (e.g., they have been already used by the Copernicus Climate Change Service to generate the ERA-5 reanalysis). The digitised surface data were submitted to ISPD (pressure) and ISTI (temperature), respectively. The ERA-CLIM2 upper air data were integrated into the latest version 2.1 of the CHUAN data. The data were also reformatted and inserted into the ECMWF Observation Data Base (ODB2) format, and stored in the MARS archive.

ERA-CLIM2 work reports

ERA-CLIM2 scientific and technological advances have been reported and discussed extensively in the projects deliverables. The most important results have also been published in peer-reviewed journals. To date (29 Jan 2018), 67 ERA-CLIM2 related publications (i.e. publications that either use ERA-CLIM2 data, or were written as part of ERA-CLIM2 work) have been published, are under revision or submitted. Here is the list in alphabetic order:
  1. Ballesteros Cánovas, J. A., M. Stoffel, M. Rohrer, G. Benito, M. Beniston, S. Brönnimann, 2018: Ocean-to-stratosphere linkages caused extreme winter floods in 1936 over the North Atlantic Basin. Scientific Reports (submitted).
  2. Brönnimann, S., 2015: Verschiebung der Tropen führte bereits früher zu Dürren. Hydrologie und Wasserbewirtschaftung 59, 427-428.
  3. Brönnimann, S., A. M. Fischer, E. Rozanov, P. Poli, G. P. Compo, P. D. Sardeshmukh, 2015: Southward shift of the Northern tropical belt from 1945 to 1980. Nature Geoscience 8, 969-974 doi:10.1038/NGEO2568.
  4. Brönnimann, S., A. Malik, A. Stickler, M. Wegmann, C. C. Raible, S. Muthers, J. Anet, E. Rozanov and W. Schmutz, 2016: Multidecadal Variations of the Effects of the Quasi-Biennial Oscillation on the Climate System. Atmospheric Chemistry and Physics 16, 15529-15543.
  5. Brönnimann, S., M. Jacques Coper, A. Fischer, 2017: Regnerischere Südseeinseln wegen Ozonloch. Physik in unserer Zeit 48, 215-216.
  6. Brönnimann, S., M. Jacques-Coper, E. Rozanov, A. M. Fischer, O. Morgenstern, G. Zeng, H. Akiyoshi, and Y. Yamashita, 2017: Tropical circulation and precipitation response to Ozone Depletion and Recovery. Environ. Res. Lett. 12, 064011, doi:10.1088/1748-9326/aa7416.
  7. Brönnimann, S., R. Allan, C. Atkinson, R. Buizza, O. Bulygina, P. Dahlgren, D. Dee, R. Dunn, P. Gomes, V. John, S. Jourdain, L. Haimberger, H. Hersbach, J. Kennedy, P. Poli, J. Pulliainen, N. Rayner, R. Saunders, J. Schulz, A. Sterin, A. Stickler, H. Titchner, M. A. Valente, C. Ventura, C. Wilkinson, 2018: Observations for Reanalyses. Bull. Amer. Meteorol. Soc., in press.
  8. Brönnimann, Stefan; Rob Allan, Roberto Buizza, Olga Bulygina, Per Dahlgren, Dick Dee, Pedro Gomes , Sylvie Jourdain, Leopold Haimberger, Hans Hersbach, Paul Poli, Jouni Pulliainen, Nick Rayner, Jörg Schulze, Alexander Sterin, Alexander Stickler, Maria Antonia Valente, Maria Clara Ventura, Clive Wilkinson, 2017: Preparing Observation Data for European Reanalyses in ERA CLIM and ERA CLIM2 Projects, CODATA 2017. St. Petersburg. Book of Abstracts.
  9. Brugnara, Y., Brönnimann S., Zamuriano, M., Schild, J., Rohr, C., Segesser, D., 2016: December 1916: Deadly Wartime Weather. Geographica Bernensia G91. 8 pp. ISBN 978-3-905835-47-2, doi:10.4480/GB2016.G91.01
  10. Brugnara, Y., S. Brönnimann, M. Zamuriano, J. Schild, C. Rohr and D. Segesser, 2017: Los reanálisis arrojan luz sobre el desastre de los aludes de 1916. Tiempo y Clima, 58, 16-20.
  11. Brugnara, Y., S. Brönnimann, M. Zamuriano, J. Schild, C. Rohr and D. Segesser, 2017: Reanalysis sheds light on 1916 avalanche disaster. ECMWF Newsletter 151, 28-34.
  12. Buizza, R., Brönnimann, S., Fuentes, M., Haimberger, L., Laloyaux, P., Martin, M., Alonso-Balmaseda, M., Becker, A., Blaschek, M., Dahlgren, P., de Boisseson, E., Dee, D., Xiangbo, F., Haines, K., Jourdain, S., Kosaka, Y., Lea, D., Mayer, M., Messina, P., Perruche, C., Peylin, P., Pullainen, J., Rayner, N., Rustemeier, E., Schepers, D., Schulz, J., Sterin, A., Stichelberger, S., Storto, A., Testut, C.-E., Valente, M.-A., Vidard, A., Vuichard, N., Weaver, A., While, J., and Ziese, M., 2018: The ERA-CLIM2 project. Bull. Amer. Met. Soc., in press.
  13. Cram, T.A., Compo, G.P., Xungang Yin, Allan, R.J., C. McColl, R. S. Vose, J.S. Whitaker, N. Matsui, L. Ashcroft, R. Auchmann, P. Bessemoulin, T. Brandsma, P. Brohan, M. Brunet, J. Comeaux, R. Crouthamel, B. E. Gleason, Jr., P. Y. Groisman, H. Hersbach, P. D. Jones, T. Jonsson, S. Jourdain, G. Kelly, K. R. Knapp, A. Kruger, H. Kubota, G. Lentini, A. Lorrey, N. Lott, S. J. Lubker, J. Luterbacher, G. J. Marshall, M. Maugeri, C. J. Mock, H. Y. Mok, O. Nordli, M. J. Rodwell, T. F. Ross, D. Schuster, L. Srnec, M. A. Valente, Z. Vizi, X. L. Wang, N. Westcott, J. S. Woollen, S. J. Worley,   2015:  The International  Surface Pressure Databank version 2.  Geoscience Data Journal, 2, 31–46. doi: 10.1002/gdj3.25.
  14. de Boisséson, E., Balmaseda, M.A. & Mayer, M. Clim Dyn (2017). Ocean heat content variability in an ensemble of twentieth century ocean reanalyses.
  15. Delaygue, G., S. Brönnimann, P. Jones, J. Blanche, and M. Schwander, 2017: Reconstruction of Lamb weather type series back to the 18th century. Clim. Dyn. (submitted).
  16. Dunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L., 2016: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491,, 2016.
  17. Feng, X., and K. Haines, 2017: Atmospheric response and feedback to sea surface temperatures in coupled and uncoupled ECMWF reanalyses, In preparation.
  18. Feng, X., Haines, K., Liu, C., and de Boisseson, E., 2018: Improved SST-precipitation relationships in the first ECMWF coupled climate reanalysis. Submitted to GRL.
  19. Feng, X., Haines, K. and Boisseson, E. (2017) Coupling of surface air and sea surface temperatures in the CERA-20C reanalysis. Quarterly Journal of the Royal Meteorological Society. ISSN 0035-9009 doi: 10.1002/qj.3194 (In Press).
  20. Franke, J., S. Brönnimann, J. Bhend, Y. Brugnara, 2017: A monthly global paleo-reanalysis of the atmosphere from 1600 to 2005 for studying past climatic variations. Scientific Data 4, 170076. doi: 10.1038/sdata.2017.76.
  21. Hegerl, G., S. Brönnimann, T. Cowan, and A. Schurer, 2018: The early 20th century warming: anomalies, causes and consequences. WIREs Climate Change (submitted).
  22. Hersbach, H., Brönnimann, S., Haimberger, L., Mayer, M., Villiger, L., Comeaux, J., Simmons, A., Dee, D., Jourdain, S., Peubey, C., Poli, P., Rayner, N., Sterin, A. M., Stickler, A., Valente, M. A. and Worley, S. J., 2017: The potential value of early (1939–1967) upper-air data in atmospheric climate reanalysis. Q. J. R. Meteorol. Soc., 143, 1197–1210.
  23. Jourdain, S. E.Roucaute, P.Dandin, J.-P.Javelle, I. Donet, S.Menassère, N.Cénac, 2015: Le sauvetage des données anciennes à Météo-France  De la conservation à la mise à disposition des données, La Météorologie n°89-mai 2015, p47-55.
  24. Kopylov V.N., Sterin A.M., 2016: SYSTEM ANALYSIS IN RIHMI-WDC FOR THE MULTI-PURPOSE DATA COLLECTION, STATISTICAL PROCESSING AND ANALYSIS OF HYDROMETEOROLOGICAL HAZARDOUS PHENOMENA. Geoinformatics Research. Transactions of GC RAS.  Book of Abstracts of the International Conference, Т. 4. № 2. С. 7.
  25. KOSYKH, Valeriy, Evgenii VJAZILOV, Alexander STERIN, Olga BULYGINA, 2017: WDCs in OBNINSK, RUSSIA: ON A WAY TO WDS RESOURCE INTEGRATION. CODATA 2017. St. Petersburg. 2017. Book of Abstracts.
  26. Laloyaux, P., M. Balmaseda, S. Broennimann, R. Buizza, P. Dalhgren, E. de Boisseson, D. Dee, Y. Kosaka, L. Haimberger, H. Hersbach, M. Martin, P. Poli, D. Scheppers, 2018: CERA-20C: A coupled reanalysis of the Twentieth Century. Q. J. Roy. Meteorol. Soc., submitted.
  27. Landgraf, M., 2016: Variabilität des atmosphärischen Energiehaushalts der Tropen, berechnet für die Periode 1939-66 aus Reanalysedaten. Master Thesis, Univ. Vienna
  28. Lavrov A.S., Sterin A.M., 2017: COMPARISON OF FREE ATMOSPHERE TEMPERATURE SERIES FROM RADIOSONDE AND SATELLITE DATA, Russian Meteorology and Hydrology. 2017. Т. 42. № 2. С. 95-104.
  30. Lea, D. J., I. Mirouze, M. J. Martin, R. R. King, A. Hines, D. Walters, and M. Thurlow, 2015: Assessing a New Coupled Data Assimilation System Based on the Met Office Coupled Atmosphere-Land-Ocean-Sea Ice Model. Monthly Weather Review, 143, 4678-4694, doi: 10.1175/MWR-D-15-0174.1.
  31. Malik, A., and S. Brönnimann, 2017: Factors Affecting the Inter-annual to Centennial Timescale Variability of Indian Summer Monsoon Rainfall Climate Dynamics (accepted).
  32. Malik, A., S. Brönnimann, A. Stickler, C. C. Raible, S. Muthers, J. Anet, E. Rozanov, W. Schmutz, 2017: Decadal to Multi-decadal Scale Variability of Indian Summer Monsoon Rainfall in the Coupled Ocean-Atmosphere-Chemistry Climate Model SOCOL-MPIOM. Clim. Dynam., 49, 3551-3572, doi:10.1007/s00382-017-3529-9.
  33. Malik, A., S. Brönnimann, P. Perona, 2017: Statistical link between external climate forcings and modes of ocean variability. Climate Dynamics doi: 10.1007/s00382-017-3832-5
  34. Mayer, M., Fasullo, J. T., Trenberth, K. E., and Haimberger, L. 2016: ENSO-Driven Energy Budget Perturbations in Observations and CMIP Models. Climate Dynamics, 47, 4009–4029
  35. Mayer, M., L. Haimberger, J. M. Edwards, P Hyder, 2017: Towards consistent diagnostics of the coupled atmosphere and ocean energy budgets. J. Climate, DOI: 10.1175/JCLI-D-17-0137.1
  36. Mayer, M., L. Haimberger, M. Pietschnig, and A. Storto, 2016: Facets of Arctic energy accumulation based on observations and reanalyses 2000-2015, Geophys. Res. Lett., 43.
  37. Mulholland, D. P., Haines, K. and Balmaseda, M. A., 2016: Improving seasonal forecasting through tropical ocean bias corrections. Q.J.R. Meteorol. Soc., 142: 2797-2807. doi: 10.1002/qj.2869
  38. Mulholland, D. P., P. Laloyaux, K. Haines and M.-A. Balmaseda, 2015: Origin and impact of initialisation shocks in coupled atmosphere-ocean forecasts. Mon. Wea. Review,
  39. Nabavi, S.O., Haimberger, L., Samimi, C., 2016: Climatology of dust distribution over West Asia from homogenized remote sensing data. Aeolian Research, 21, pp. 93-107.
  40. Nabavi, S.O., Haimberger, L., Samimi, C., 2017: Sensitivity of WRF-chem predictions to dust source function specification in West Asia. Aeolian Research, 24, pp. 115-131.
  41. Pellerej, R., A. Vidard, F. Lemarié, 2016: Toward variational data assimilation for coupled models: first experiments on a diffusion problem. CARI 2016, Oct 2016, Tunis, Tunisia. 2016
  42. Peylin, P., Bacour, C., MacBean, N., Leonard, S., Rayner, P. J., Kuppel, S., Koffi, E. N., Kane, A., Maignan, F., Chevallier, F., Ciais, P., and Prunet, P., 2016: A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle, Geosci. Model Dev., 9, 3321-3346, doi: 10.5194/gmd-9-3321-2016
  43. Peylin, P., et al. Relative contribution of uncertainties on climate, land use scenario and model parameters to the dynamic of land carbon fluxes during the past century, in preparation
  44. Pietschnig, M., M. Mayer, T. Tsubouchi, A. Storto, L. Haimberger, 2017: Comparing reanalysis-based volume and temperature transports through Arctic Gateways with mooring-derived estimates. Ocean Science, submitted.
  45. Poli et al, 2017:  Recent Advances in Satellite Data Rescue. BAMS
  46. Rohrer, M., S. Brönnimann, O. Martius, C. C. Raible, M. Wild, G. P. Compo, 2017: Representation of cyclones, blocking anticyclones, and circulation types in multiple reanalyses and model simulations. J. Climate (revised).
  47. Rustemeier, E., Ziese, M.,Meyer-Christoffer, A., Schneider, U., Finger, P., Becker, A., 2017: Uncertainty assessment of the ERA-20C reanalysis based on the monthly in-situ precipitation analyses of the Global Precipitation Climatology Centre. In prep for submission to J. Hydrometeor.
  48. Schmocker, J., H. P. Liniger, J N. Ngeru, Y. Brugnara, R. Auchmann, and S. Brönnimann, 2016: Trends in mean and extreme precipitation in the Mount Kenya region from observations and reanalyses. Int. J. Climatol. 36, 1500-1514, doi:10.1002/joc.4438.
  49. Sterin A.M., Nikolaev D.A., 2016: TECHNOLOGIES OF RIHMI-WDC IN OLD DATA RESCUE, MANAGEMENT AND QUALITY ASSUREMENT. Geoinformatics Research. Transactions of GC RAS.  Book of Abstracts of the International Conference. Т. 4. № 2. С. 113.
  51. Sterin A.M., Timofeev A.A., 2016: Geoinformatics Research. QUANTILE REGRESSION AS AN INSTRUMENT TO DETAILED CLIMATE TREND ASSESSMENT. Transactions of GC RAS.  Book of Abstracts of the International Conference. Т. 4. № 2. С. 112.
  52. Sterin, A. M., and A.S. Lavrov. , 2017: ON THE ESTIMATES OF TROPSPHERIC TEMPERATURE ANOMALIES IN 2015-2016. Fundamental and Applied Climatology, 2017, No.2. p.111-129
  53. Stichelberger, S.., 2017: Ocean reanalyses vs. in-situ observations: A comparison of volume, temperature and freshwater transport through Arctic gateways. Master Thesis, Univ. Vienna, 107pp.
  54. Stickler, A., Brönnimann, S., Valente, M.A., Bethke, J., Sterin, A., Jourdain, S., Roucaute, E., Vasquez, M.V., Reyes, D.A., Guzman, J.G., Allan, R.J.  and  Dee, D.,  2014:   ERA-CLIM: Historical Surface and Upper-Air Data for Future Reanalyses.  Bull. Amer. Met. Soc.,  95, 9,  1419-1430:
  55. Stickler, A., S. Storz, C. Jörg, R. Wartenburger, H. Hersbach, G. Compo, P. Poli, D. Dee, and S. Brönnimann, 2015: Upper‐air observations from the German Atlantic Expedition (1925-27) and comparison with the Twentieth Century and ERA‐20C reanalyses. Meteorol. Z., 24, 525-544, doi:10.1127/metz/2015/0683.
  56. Storto, A., C. Yang, and S. Masina, 2016: Sensitivity of global ocean heat content from reanalyses to the atmospheric reanalysis forcing: A comparative study, Geophys. Res. Lett., 43, 5261–5270, doi:10.1002/2016GL068605.
  57. Storto, A., M. J. Martin, B. Deremble, and S. Masina, 2017: Strongly coupled data assimilation experiments with linearized ocean-atmosphere balance relationships, submitted to MWR.
  58. Storto, A., Yang, C., & Masina, S., 2017: Constraining the global ocean heat content through assimilation of CERES-derived TOA energy imbalance estimates. Geophysical Research Letters, 44.
  59. Thorne P. W., R. J. Allan, L. Ashcroft, P. Brohan, R.J.H Dunn, M. J. Menne, P. Pearce, J. Picas, K. M. Willett, M. Benoy, S. Bronnimann, P. O. Canziani, J. Coll, R. Crouthamel, G. P. Compo, D. Cuppett, M. Curley, C. Duffy, I. Gillespie, J. Guijarro, S. Jourdain, E. C. Kent, H. Kubota, T. P. Legg, Q. Li, J. Matsumoto, C. Murphy, N. A. Rayner, J. J. Rennie, E. Rustemeier, L. Slivinski, V. Slonosky, A. Squintu, B. Tinz, M. A. Valente, S. Walsh, X. L. Wang, N. Westcott, K. Wood, S. D. Woodruff, and S. J. Worley, 2017: Towards an integrated set of surface meteorological observations for climate science and applications. B. Amer. Meteorol. Soc. (accepted)
  60. Vuichard et al., Accounting for Carbon and Nitrogen interactions in a Global Terrestrial Ecosystem Model: Multi-site evaluation of the ORCHIDEE model, in preparation
  61. Weaver A. T., Gurol S, Tshimanga J, Chrust M, Piacentini A., 2017: "Time"-parallel diffusion-based correlation operators. Technical Memorandum 808, ECMWF, Reading, UK.
  62. Weaver AT, Tshimanga J, Piacentini A, 2016: Correlation operators based on an implicitly formulated diffusion equation solved with the Chebyshev iteration. Q. J. Roy. Meteorol. Soc., 142: 455-471.
  63. Wegmann M., Brönnimann S., Orsolini Y., Dutra E., Bulygina O., Sterin A., 2017: EURASIAN SNOW DEPTH IN LONG-TERM CLIMATE REANALYSES. Cryosphere. 2017. Т. 11. № 2. С. 923-935.
  64. Wegmann M., Brönnimann S., Orsolini Y., Vázquez M., Gimeno L., Nieto R., Bulygina O., Sterin A., Jaiser R., Handorf D., Rinke A., Dethloff K., 2015: ARCTIC MOISTURE SOURCE FOR EURASIAN SNOW COVER VARIATIONS IN AUTUMNEnvironmental Research Letters. 2015. Т. 10. № 5. С. 054015.
  65. Wegmann M., S. Brönnimann and G. P. Compo, 2016: Tropospheric circulation during the early twentieth century Arctic warming. Climate Dynamics 48, 2405–2418, doi:10.1007/s00382-016-3212-6.
  66. Wegmann, M., Y. Orsolini, E. Dutra, O. Bulygina, A. Sterin and S. Brönnimann, 2016: Eurasian snow depth in long-term climate reanalyses. The Cryosphere 11, 923-935.
  67. While, J., M.J. Martin, 2017: Variational bias correction of satellite sea surface temperature data incorporating direct observations of the bias. In preparation.