Publications & Presentations
The links below provide access to a collection of publications, presentations, posters and more published by the project
CMUG Integration Meetings
- Integration Meeting November 2023
- Integration Meeting October 2022
- Integration Meeting October 2021
- Integration Meeting November 2019
- Integration Meeting October 2018
- Integration Meeting February 2017
- Integration Meeting March 2016
- Integration Meeting May 2015
- Integration Meeting June 2014
- Integration Meeting June 2013
- Integration Meeting May 2012
- Integration Meeting March 2011
CMUG Newsletters
- CMUG Newsletter for Integration Meeting October 2024
- CMUG Newsletter for CSWG Meeting March 2024
- CMUG Newsletter for Integration Meeting November 2023
- CMUG Newsletter for Integration Meeting October 2022
- CMUG Newsletter for CSWG Meeting April 2022
- CMUG Newsletter for Integration Meeting October 2021
- CMUG Newsletter for CSWG Meeting May 2021
- CMUG Newsletter for CSWG Meeting January 2021
- CMUG Newsletter for CSWG Meeting October 2020
- CMUG Newsletter 6, January 2016
- CMUG Overview Newsletter, August 2015
- CMUG Newsletter 5, June 2015
- CMUG Newsletter 4, September 2014
- CMUG Newsletter 3, January 2013
- CMUG Newsletter 2, October 2011
- CMUG Newsletter 1, December 2010
Scientific Publications
- Acosta-Navarro, J. C., García-Serrano, J., Lapin, V., Ortega, P. (2022). Added value of assimilating springtime Arctic sea ice concentration in summer-fall climate predictions. Environmental Research Letters, 17. 064008. https://doi.org/10.1088/1748-9326/ac6c9b
- Adloff, F., Jordá, G., Somot, S., Sevault, F., Arsouze, T., Meyssignac, B., Li, L., and Planton, S. (2018). Improving sea level simulation in Mediterranean regional climate models. Climate Dynamics, 51, 1167-1178. https://doi.org/10.1007/s00382-017-3842-3
- Albergel, C., Zheng, Y., Bonan, B., Dutra, E., Rodríguez-Fernández, N., Munier, S., Draper, C., de Rosnay, P., Muñoz-Sabater, J., Balsamo, G., Fairbairn, D., Meurey, C. and Calvet, J.-C. (2020). Data assimilation for continuous global assessment of severe conditions over terrestrial surfaces. Hydrology and Earth System Sciences, 24(9), 4291-4316. https://doi.org/10.5194/hess-24-4291-2020
- Bellprat, O., Massonnet, F., Siegert, S., Prodhomme, C., Macias-Gómez, D., Guemas, V. and Doblas-Reyes, F. (2017). Uncertainty propagation in observational references to climate model scales. Remote Sensing of Environment, 203(15), 101-108. http://dx.doi.org/10.1016/j.rse.2017.06.034
- Bilbao, R., Wild, S., Ortega, P., Acosta-Navarro, J., Arsouze, T., Bretonnière, P.-A., Caron, L.-P., Castrillo, M., Cruz-García, R., Cvijanovic, I., Doblas-Reyes, F., Donat, M., Dutra, E., Echevarría, P., Ho, A.-C., Loosveldt-Tomas, S., Moreno-Chamarro, E., Pérez-Zanon, N., Ramos, A., Ruprich-Robert, Y., Sicardi, V., Tourigny, E. and Vegas-Regidor, J. (2021). Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth. Earth System Dynamics, 12, 173-196. https://doi.org/10.5194/esd-12-173-2021
- Bock, L., Lauer, A., Schlund, M., Barreiro, M., Bellouin, N., Jones, C., Meehl, G. A., Predoi, V., Roberts, M. J. and Eyring, V. (2020). Quantifying progress across different CMIP phases with the ESMValTool. Journal of Geophysical Research: Atmospheres, 125(21). https://doi.org/10.1029/2019JD032321
- Bock, L., and A. Lauer (2024). Cloud properties and their projected changes in CMIP models with low to high climate sensitivity, Atmos. Chem. Phys., 24, 1587-1605, https://doi.org/10.5194/acp-24-1587-2024
- Cheruy, F., Ducharne, A., Hourdin, F., Musat, I., Vignon, É., Gastineau, G., Bastrikov, V., Vuichard, N., Dugresne, J.-L., Ghattas, J., Grandpeix, J.-Y., Idelkadi, A., Mellul, L., Maignan, F., Ménégoz, M., Ottlé, C., Peylin, P., Servonnat, J., Wang, F. and Zhao, Y. (2020). Improved near-surface continental climate in IPSL-CM6A-LR by combined evolutions of atmospheric and land surface physics. Journal of Advances in Modeling Earth Systems, 12(10). https://doi.org/10.1029/2019MS002005
- Dragani, R. (2016). A comparative analysis of UV nadir-backscatter and infrared limb-emission ozone data assimilation. Atmospheric Chemistry and Physics, 16(13), 8539-8557. https://doi.org/10.5194/acp-16-8539-2016
- Eyring, V., Righi, M., Lauer, A., Evaldsson, M., Wenzel, S., Jones, C., Anav, A., Andrews, O., Cionni, I., Davin, E. L., Deser, C., Ehbrecht, C., Friedlingstein, P., Gleckler, P., Gottschaldt, K.-D., Hagemann, S., Juckes, M., Kindermann, S., Krasting, J., Kunert, D., Levine, R., Loew, A., Mäkelä, J., Martin, G., Mason, E., Phillips, A. S., Read, S., Rio, C., Roehrig, R., Senftleben, D., Sterl, A., van Ulft, L. H., Walton, J., Wang, S. and Williams, K. D. (2016). ESMValTool (v1.0) – a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP. Geoscientific Model Development, 9(5), 1747-1802. https://doi.org/10.5194/gmd-9-1747-2016
- Eyring, V., Cox, P., Flato, G., Gleckler, P., Abramowitz, G., Caldwell, P., Collins, W., Gier, B., Hall, A., Hoffman, F., Hurtt, G., Jahn, A., Jones, C., Klein, S., Krasting, J., Kwiatkowski, L., Lorenz, R., Maloney, E., Meehl, G., Pendergrass, A., Pincus, R., Ruane, A., Russell, J., Sanderson, B., Santer, B., Sherwood, S., Simpson, I., Stouffer, R. and Williamson, M. (2019). Taking climate model evaluation to the next level. Nature Climate Change, 9, 102-110. https://doi.org/10.1038/s41558-018-0355-y
- Eyring, V., Bock, L., Lauer, A., Righi, M., Schlund, M., Andela, B., Arnone, E., Bellprat, O., Brötz, B., Caron, L.-P., Carvalhais, N., Cionni, I., Cortesi, N., Crezee, B., Davin, E., Davini, P., Debeire, K., de Mora, L., Deser, C., Docquier, D., Earnshaw, P., Ehbrecht, C., Gier, B., Gonzales-Reviriego, N., Goodman, P., Hagemann, S., Hardiman, S., Hassler, B., Hunter, A., Kadow, C., Kindermann, S., Koirala, S., Koldunov, N., Lejeune, Q., Lembo, V., Lovato, T., Lucarini, V., Massonnet, F., Müller, B., Pandde, A., Pérez-Zanón, N., Phillips, A., Predoi, V., Russell, J., Sellar, A., Serva, F., Stacke, T., Swaminathan, R., Torralba, V., Vegas-Regidor, J., von Hardenberg, J., Weigel, K. and Zimmermann, K. (2020). Earth System Model Evaluation Tool (ESMValTool) v2.0 0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP. Geoscientific Model Development, 13(7), 3383-3438. https://doi.org/10.5194/gmd-13-3383-2020
- Ford, D. A. (2020). Assessing the role and consistency of satellite observation products in global physical-biogeochemical ocean reanalysis. Ocean Science, 16, 875-893. https://doi.org/10.5194/os-16-875-2020
- Ford, D. A., Edwards, K., Lea, D., Barciela, R., Martin, M. and Demaria, J. (2012). Assimilating GlobColour ocean colour data into a pre-operational physical-biogeochemical model. Ocean Science, 8, 751-771. https://doi.org/10.5194/os-8-751-2012
- Ford, D. A. and Barciela, R. (2017). Global marine biogeochemical reanalyses assimilating two different sets of merged ocean colour products. Remote Sensing of Environment, 203, 40-54. https://doi.org/10.1016/j.rse.2017.03.040
- Gier, B., Buchwitz, M., Reuter, M., Cox, P., Friedlingstein, P. and Eyring, V. (2020). Spatially resolved evaluation of Earth system models with satellite column-averaged CO2. Biogeosciences, 17, 6115-6144. https://doi.org/10.5194/bg-17-6115-2020
- Guemas, V., Chevallier, M., Déqué, M., Bellprat, O. and Doblas-Reyes, F. (2016). Impact of sea ice initialization on sea ice and atmosphere prediction skill on seasonal timescales. Geophysical Research Letters, 43(8), 3889-3896. https://doi.org/10.1002/2015GL066626
- Hollmann, R., Merchant, C., Saunders, R., Downy, C., Buchwitz, M., Cazenave, A., Chuvieco, E., Defourny, P., de Leeuw, G., Forsberg, R., Holzer-Popp, T., Paul, F., Sandven, S., Sathyendranath, S., van Roozendael, M. and Wagner, W. (2013). The ESA Climate Change Initiative: Satellite Data Records for Essential Climate Variables. Bulletin of the American Meteorological Society, 1541-1552. https://doi.org/10.1175/BAMS-D-11-00254.1
- Kaps, A., A. Lauer, G. Camps-Valls, P. Gentine, L. Gómez-Chova and V. Eyring, "Machine-Learned Cloud Classes From Satellite Data for Process-Oriented Climate Model Evaluation," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-15, 2023, Art no. 4100515, doi: 10.1109/TGRS.2023.3237008
- Kaps, A., Lauer, A., Kazeroni, R., Stengel, M., and Eyring, V.: Characterizing clouds with the CCClim dataset, a machine learning cloud class climatology, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-424, accepted, 2024.
- Klose, M., Jorba, O., Gonçalves Ageitos, M., Escribano, J., Dawson, M., Obiso, V., Di Tomaso, E., Basart, S., Montané Pinto, G., Macchia, F., Ginoux, P., Guerschman, J., Prigent, C., Huang, Y., Kok, J., Miller, R. and Pérez García-Pando, C. (2021). Mineral dust cycle in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) Version 2.0. Geoscientific Model Development, 14, 6403-6444. https://doi.org/10.5194/gmd-14-6403-2021
- Lauer, A., L. Bock, B. Hassler, M. Schröder, and M. Stengel. (2023) Cloud climatologies from global climate models – a comparison of CMIP5 and CMIP6 models with satellite data. Journal of Climate, 36 (2), 281-311. DOI10.1175/JCLI-D-22-0181.1 https://doi.org/10.1175/JCLI-D-22-0181.1
- Lauer, A., Eyring, V., Righi, M., Buchwitz, M., Defourny, P., Evaldsson M., Friedlingstein, P., de Jeu, R., de Leeuw, G., Loew, A., Merchant, C., Müller, B., Popp, T., Reuter, M., Sandven, S., Senftleben, D., Stengel, M., Van Roozendael, M., Wenzel, S. and Willén U. (2017). Benchmarking CMIP5 models with a subset of ESA CCI Phase 2 data using the ESMValTool. Remote Sensing of Environment, 205, 9-39. https://doi.org/10.1016/j.rse.2017.01.007
- Lauer, A., Eyring, V., Bellprat, O., Bock, L., Gier, B., Hunter, A., Lorenz, R., Pérez-Zanón, N., Righi, M., Schlund, M., Senftleben, D., Weigel, K. and Zechlau, S. (2020). Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for emergent constraints and future projections from Earth system models in CMIP. Geoscientific Model Development, 13, 4205-4228. https://doi.org/10.5194/gmd-13-4205-2020
- Lean, K. and Saunders, R. (2013). Validation of the ATSR Reprocessing for Climate (ARC) Dataset Using Data from Drifting Buoys and a Three-Way Error Analysis. American Meteorological Society, 26(13), 4758-4772. https://doi.org/10.1175/JCLI-D-12-00206.1
- Loew, A. (2013). Terrestrial satellite records for climate studies: how long is long enough? A test case for the Sahel. Theoretical and Applied Climatology, 115, 427-440. https://doi.org/10.1007/s00704-013-0880-6
- Loew, A., Stacke, T., Dorigo, W., de Jeu, R. and Hagemann, S. (2013). Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies. Hydrology and Earth System Sciences, 17, 3523-3542. https://doi.org/10.5194/hess-17-3523-2013
- Loew, A., Andersson, A., Trentmann, J. and Schröder, M. (2016). Assessing Surface Solar Radiation Fluxes in the CMIP Ensembles. American Meteorological Society, 29(20), 7231-7246. https://doi.org/10.1175/JCLI-D-14-00503.1
- Massonnet, F., Bellprat, O., Guemas, V. and Doblas-Reyes, F. (2016). Using climate models to estimate the quality of global observational data sets. Science, 354(6311), 452-455. https://doi.org/10.1594/PANGAEA.864680
- Merchant, C., Embury, O., Rayner, N., Berry, D., Corlett, G., Lean, K., Veal, K., Kent, E., Llewellyn-Jones, D., Remedios, J. and Saunders, R. (2012). A 20 year independent record of sea surface temperature for climate from Along-Track Scanning Radiometers. Journal of Geophysical Research, 117(C12). https://doi.org/10.1029/2012JC008400
- Peano, D., Hemming, D., Materia, S., Delire, C., Fan, Y., Joetzjer, E., Lee, H., Nabel, J., Park, T., Peylin, P., Wårlind, D., Wiltshire, A. and Zaehle, S. (2021). Plant phenology evaluation of CRESCENDO land surface models – Part 1: Start and end of the growing season. Biogeosciences, 18, 2405-2428. https://doi.org/10.5194/bg-18-2405-2021
- Popp, T., Hegglin, M., Hollmann, R., Ardhuin, F., Bartsch, A., Bastos, A., Bennett, V., Boutin, J., Brockmann, C., Buchwitz, M., Chuvieco, E., Ciais, P., Dorigo, W., Ghent, D., Jones, R., Lavergne, T., Merchant, C., Meyssignac, B., Paul, F., Quegan, S., Sathyendranath, S., Scanlon, T., Schröder, M., Simis, S. and Willén, U. (2020). Consistency of Satellite Climate Data Records for Earth System Monitoring. American Meteorological Society, 101(11), E1948-E1971. https://doi.org/10.1175/BAMS-D-19-0127.1
- Sevault, F., Somot, S., Alias, A., Dubois, C., Lebeaupin-Brossier, C., Nabat, P., Adloff, F. Déqué, M. and Decharme, B. (2014). A fully coupled Mediterranean regional climate system model: design and evaluation of the ocean component for the 1980-2012 period. Tellus A: Dynamic Meteorology and Oceanography, 68(s2). https://doi.org/10.3402/tellusa.v66.23967
- Waliser, D., Gleckler, P., Ferraro, R., Taylor, K., Ames, S., Biard, J., Bosilovich, M., Brown, O., Chepfer, H., Cinquini, L., Durack, P., Eyring, V., Mathieu, P.-P., Lee, T., Pinnock, S., Potter, G., Rixen, M., Saunders, R., Schulz, J., Thépaut, J.-N. and Tuma, M. (2020). Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6. Geoscientific Model Development, 13, 2945-2958. https://doi.org/10.5194/gmd-13-2945-2020
- Wernecke, A., Notz, D., Kern, S., and Lavergne, T.: Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals, The Cryosphere, 18, 2473–2486, https://doi.org/10.5194/tc-18-2473-2024, 2024.
- Yue, C., Ciais, P., Cadule, P., Thonicke, K. and van Leeuwen, T. (2015). Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 2: Carbon emissions and the role of fires in the global carbon balance. Geoscientific Model Development, 8, 1321-1338. https://doi.org/10.5194/gmd-8-1321-2015
- Yue, C., Ciais, P., Cadule, P., Thonicke, K., Archibald, S., Poulter, B., Hao, W., Hantson, S., Mouillot, F., Friedlingstein, P., Maignan, F. and Viovy, N. (2014). Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 1: simulating historical global burned area and fire regimes. Geoscientific Model Development, 7(6), 2747-2767. https://doi.org/10.5194/gmd-7-2747-2014
- Zheng, Y., Albergel, C., Munier, S., Bonan, B. and Calvet, J.-C. (2020). An offline framework for high-dimensional ensemble Kalman filters to reduce the time to solution. Geoscientific Model Development, 13(8), 3607-3625. https://doi.org/10.5194/gmd-13-3607-2020