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The representation of dry-season low-level clouds over Western Equatorial Africa in reanalyses and historical CMIP6 simulations

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Abstract

Within the equatorial zone, Western Equatorial Africa (WEA) has a record low sunshine duration during the June–September dry season due to the persistence of low clouds. This study examines the ability of two reanalysis products (ERA5 and MERRA-2) and eight CMIP6 models (both coupled and atmosphere-only historical simulations) to reproduce the climatology of these low clouds, by comparing it with ground observations and a satellite product. All datasets show a reasonable representation of the regional distribution of low clouds over the Tropical Atlantic and the neighbouring African continent. However, CMIP6 models tend to underestimate the low cloud fraction, especially over WEA in the coupled simulations. This underestimation is partly due to an insufficient seasonal sea-surface temperature (SST) cooling over the Eastern Equatorial Atlantic from April to July in most models, which reduces the lower-tropospheric stability (LTS). However, the inability to reproduce the JJAS low cloud fraction does not necessarily scale with the SST biases of the CMIP6 models. Observed interannual variations of WEA low-cloud fraction are strongly controlled by LTS, itself mostly related to Atlantic SST. The strong dependence of low clouds on interannual SST variations is captured by most, but not all the CMIP6 models. Additional drivers of interannual variations identified in this study, such as mid-tropospheric temperatures over WEA and Bight of Bonny surface winds, emerge inconsistently in CMIP6. Further analyses are needed to disentangle the roles played by SST and independent atmospheric forcings on WEA low cloud formation.

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Availability of data and material

All the data used in this work are publicly available. ISD cloud data are accessible from www.ncdc.noaa.gov/isd/data-access, and EECRA cloud data from NCAR at www.climateguide.ucar.edu/climate-data. The CALIOP satellite data come from the GCM-Oriented CALIPSO Cloud Product (GOCCP) at www.climserv.ipsl.polytechnique.fr/cfmip-obs/Calipso_goccp.html. ERA5 reanalyses are available from https://cds.climate.copernicus.eu and MERRA-2 from www.gmao.gsfc.nasa.gov/reanalysis/MERRA-2/data_access. CMIP6 data can be downloaded from www.esgf-node.llnl.gov/search/cmip6.

References

  • Adebiyi AA, Zuidema P (2018) Low cloud cover sensitivity to biomass-burning aerosols and meteorology over the southeast Atlantic. J Climate 31(11):4329–4346. https://doi.org/10.1175/JCLI-D-17-0406.1

    Article  Google Scholar 

  • Andersen H, Cermak J, Fuchs J, Knippertz P, Gaetani M, Quinting J et al (2020) Synoptic-scale controls of fog and low-cloud variability in the Namib Desert. Atmos Chem Phys 20(6):3415–3438

    Article  Google Scholar 

  • Bellomo K, Clement AC, Mauritsen T, Rädel G, Stevens B (2015) The influence of cloud feedbacks on equatorial Atlantic variability. J Climate 28(7):2725–2744

    Article  Google Scholar 

  • Berruex M (1958) Contribution à la connaissance de l’atmosphère équatoriale: une année de radiosondages à Léopoldville. Acad Roy Sc Col Mém 5(5):79

    Google Scholar 

  • Bosilovich MG, Lucchesi R, Suarez M (2016) MERRA-2: File Specification. GMAO Office Note No.9 (Version 1.1), 73p. Retrieved from http://gmao.gsfc.nasa.gov/pubs/office_notes.

  • Bouka-Biona C, Benech B, Druillet A, Minga A, Nganga D (1993) Evolution thermodynamique diurne de l’atmosphère dans et au-dessus de la forêt du Mayombe en saison sèche, in Echange foret atmosphère en milieu tropical humide, Cros et al., Eds. Unesco, Paris, 11–38

  • Bush ER, Jeffery K, Bunnefeld N, Tutin C, Musgrave R, Moussavou G, Makaga L (2019) Ground data confirm warming and drying are at a critical level for forest survival in western equatorial Africa (No. e27848v1). PeerJ. https://doi.org/10.7287/peerj.preprints.27848v1

    Article  Google Scholar 

  • Camberlin P (2018) Climate of Eastern Africa. Oxford Research Encyclopedia of Climate Science. Retrieved from https://doi.org/10.1093/acrefore/9780190228620.001.0001/acrefore-9780190228620-e-512

  • Caniaux G, Giordani H, Redelsperger JL, Guichard F, Key E, Wade M (2011) Coupling between the Atlantic cold tongue and the West African monsoon in boreal spring and summer. J Geophys Res 116:C04003. https://doi.org/10.1029/2010JC006570

    Article  Google Scholar 

  • Cesana G, Waliser DE (2016) Characterizing and understanding systematic biases in the vertical structure of clouds in CMIP5/CFMIP2 models. Geophys Res Lett. https://doi.org/10.1002/2016GL070515

    Article  Google Scholar 

  • Cesana G, Kay JE, Chepfer H, English JM, De Boer G (2012) Ubiquitous low-level liquid-containing Arctic clouds: New observations and climate model constraints from CALIPSO-GOCCP. Geophys Res Lett. https://doi.org/10.1029/2012GL053385

    Article  Google Scholar 

  • Champagne O, Aellig R, Fink AH, Philippon N, Camberlin P, Moron V, Knippertz P, Seze G, van der Linden R (2022) Climatology of low-level clouds over Western equatorial Africa based on ground observations and satellites. J Climate (to be published)

  • Chepfer H, Bony S, Winker D, Chiriaco M, Dufresne JL, Sèze G (2008) Use of CALIPSO lidar observations to evaluate the cloudiness simulated by a climate model. Geophys Res Lett 35(15):L15704. https://doi.org/10.1029/2008GL034207

    Article  Google Scholar 

  • Chepfer H, Bony S, Winker D, Cesana G, Dufresne JL, Minnis P, Zeng S (2010) The GCM-oriented CALIPSO cloud product (CALIPSO-GOCCP). J Geophys Res Atmos. https://doi.org/10.1029/2009JD012251

    Article  Google Scholar 

  • Chepfer H, Cesana G, Winker D, Getzewich B, Vaughan M, Liu Z (2013) Comparison of two different cloud climatologies derived from CALIOP-attenuated backscattered measurements (Level 1): the CALIPSO -ST and the CALIPSO -GOCCP. J Atmos Oceanic Technol 30(4):725–744. https://doi.org/10.1175/JTECH-D-12-00057.1

    Article  Google Scholar 

  • Clairac B, Cros B, Senechal J (1989) Le climat du Mayombe. In: Revue des connaissances sur le Mayombe. PNUD, MAB, UNESCO, Paris, pp 47–68.

  • Copernicus Climate Change Service (C3S) (2017) ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Retrieved March 5, 2020, from Copernicus Climate Change Service Climate Data Store (CDS). https://cds.climate.copernicus.eu/cdsapp#!/home

  • Couralet C, Sterck FJ, Sass-Klaassen U, Van Acker J, Beeckman H (2010) Species-specific growth responses to climate variations in understory trees of a Central African rain forest. Biotropica 42(4):503–511

    Article  Google Scholar 

  • Danso DK, Anquetin S, Diedhiou A, Kouadio K, Kobea AT (2020) Daytime low-level clouds in West Africa–occurrence, associated drivers, and shortwave radiation attenuation. Earth Syst Dyn 11(4):1133–1152. https://doi.org/10.5194/esd-11-1133-2020

    Article  Google Scholar 

  • Dione C, Lohou F, Lothon M, Adler B, Babić K, Kalthoff N et al (2019) Low-level stratiform clouds and dynamical features observed within the southern West African monsoon. Atmos Chem Phys 19(13):8979–8997. https://doi.org/10.5194/acp-19-8979-2019

    Article  Google Scholar 

  • Dommo A, Philippon N, Vondou DA, Sèze G, Eastman R (2018) The June–September low cloud cover in Western Central Africa: mean spatial distribution and diurnal evolution, and associated atmospheric dynamics. J Climate 31(23):9585–9603. https://doi.org/10.1175/JCLI-D-17-0082.1

    Article  Google Scholar 

  • Eastman R, Warren SG (2014) Diurnal cycles of cumulus, cumulonimbus, stratus, stratocumulus, and fog from surface observations over land and ocean. J Clim 27(6):2386–2404. https://doi.org/10.1175/JCLI-D-13-00352.1

    Article  Google Scholar 

  • Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE (2016) Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geosci Model Dev 9(5):1937–1958. https://doi.org/10.5194/gmd-9-1937-2016

    Article  Google Scholar 

  • Merle J, Fieux M, Hisard P (1980) Annual signal and interannual anomalies of sea surface temperature in the eastern equatorial Atlantic Ocean. In Oceanography and Surface Layer Meteorology in the B/C Scale (pp 77–101). Pergamon

  • Farneti R, Stiz A, Ssebandeke JB (2022) Improvements and persistent biases in the southeast tropical Atlantic in CMIP models. NPJ Clim Atmos Sci 5(1):1–11. https://doi.org/10.1038/s41612-022-00264-4

    Article  Google Scholar 

  • Feng F, Wang K (2019) Does the modern-era retrospective analysis for research and applications-2 aerosol reanalysis introduce an improvement in the simulation of surface solar radiation over China? Int J Climatol 39(3):1305–1318. https://doi.org/10.1002/joc.5881

    Article  Google Scholar 

  • Fink AH, Schuster R, Trentmann J, Schrage JM, Yorke C (2011) Ultra-low clouds over the southern West African monsoon region. Geophys Res Lett 38:L21808. https://doi.org/10.1029/2011GL049278

    Article  Google Scholar 

  • Hahn CJ, Warren SG (1999) Extended edited synoptic cloud reports from ships and land stations over the globe, 1952–1996. Carbon Dioxide Information Analysis Center, Oak Ridge. https://doi.org/10.2172/12532

    Book  Google Scholar 

  • Hannak L, Knippertz P, Fink AH, Kniffka A, Pante G (2017) Why do global climate models struggle to represent low-level clouds in the West African Summer Monsoon? J Climate 30(5):1665–1687. https://doi.org/10.1175/JCLI-D-16-0451.1

    Article  Google Scholar 

  • Hersbach H, Coauthors (2020) The ERA5 global reanalysis. Quart J Roy Meteor Soc 146(714):1999–2049. https://doi.org/10.1002/qj.3803

    Article  Google Scholar 

  • Hill PG, Allan RP, Chiu JC, Stein TH (2016) A multisatellite climatology of clouds, radiation, and precipitation in southern West Africa and comparison to climate models. J Geophys Res 121(18):10–857

    Article  Google Scholar 

  • Hu ZZ, Huang B, Pegion K (2008) Low cloud errors over the Southeastern Atlantic in the NCEP CFS and their association with lower-tropospheric stability and air-sea interaction. J Geophys Res. https://doi.org/10.1029/2007JD009514

    Article  Google Scholar 

  • Hua W, Zhou L, Nicholson SE, Chen H, Qin M (2019) Assessing reanalysis data for understanding rainfall climatology and variability over Central Equatorial Africa. Clim Dyn 53(1):651–669. https://doi.org/10.1007/s00382-018-04604-0

    Article  Google Scholar 

  • Jiang JH, Su H, Wu L, Zhai C, Schiro KA (2021) Improvements in cloud and water vapor simulations over the tropical oceans in CMIP6 compared to CMIP5. Earth Space Sci 8(5):e2020EA001520

    Article  Google Scholar 

  • Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Climate 6:1587–1606

    Article  Google Scholar 

  • Knippertz P, Fink AH, Schuster R, Trentmann J, Schrage JM, Yorke C (2011) Ultra-low clouds over the southern West African monsoon region. Geophys Res Lett. https://doi.org/10.1029/2011GL049278

    Article  Google Scholar 

  • Konsta D, Dufresne JL, Chepfer H, Vial J, Koshiro T, Kawai H, Ogura T (2022) Low-level marine tropical clouds in six CMIP6 models are too few, too bright but also too compact and too homogeneous. Geophys Res Lett 49(11):e2021GL097593

    Article  Google Scholar 

  • Koseki S, Imbol Koungue RA (2021) Regional atmospheric response to the Benguela Niñas. Int J Climatol 41:E1483–E1497. https://doi.org/10.1002/joc.6782

    Article  Google Scholar 

  • Lacaux JP, Delmas R, Kouadio G, Cros B, Andreae MO (1992) Precipitation chemistry in the Mayombe forest of equatorial Africa. J Geophys Res 97(D6):6195–6206

    Article  Google Scholar 

  • Lauer A, Hamilton K (2013) Simulating clouds with global climate models: a comparison of CMIP5 results with CMIP3 and satellite data. J Clim 26(11):3823–3845

    Article  Google Scholar 

  • Leduc‐Leballeur M, De Coëtlogon G, Eymard L (2013) Air–sea interaction in the Gulf of Guinea at intraseasonal time‐scales: wind bursts and coastal precipitation in boreal spring. Q J Roy Meteorol Soc 139(671):387–400

    Article  Google Scholar 

  • Longandjo GNT, Rouault M (2020) On the structure of the regional-scale circulation over Central Africa: seasonal evolution, variability, and mechanisms. J Clim 33(1):145–162

    Article  Google Scholar 

  • Li J, Carlson BE, Rossow WB, Lacis AA, Zhang Y (2015) An intercomparison of the spatiotemporal variability of satellite-and ground-based cloud datasets using spectral analysis techniques. J Clim 28(14):5716–5736

    Article  Google Scholar 

  • Lu Z, Liu X, Zhang Z, Zhao C, Meyer K, Rajapakshe C et al (2018) Biomass smoke from southern Africa can significantly enhance the brightness of stratocumulus over the southeastern Atlantic Ocean. Proc Nat Acad Sci 115(12):2924–2929

    Article  Google Scholar 

  • Lübbecke JF, Rodríguez-Fonseca B, Richter I, Martín-Rey M, Losada T, Polo I, Keenlyside NS (2018) Equatorial Atlantic variability—modes, mechanisms, and global teleconnections. Wiley Interdisciplinary Rev 9(4):e527

    Google Scholar 

  • Lutz K, Rathmann J, Jacobeit J (2013) Classification of warm and cold water events in the eastern tropical Atlantic Ocean. Atmos Sci Lett 14(2):102–106

    Article  Google Scholar 

  • Mallet M, Solmon F, Nabat P, Elguindi N, Waquet F, Bouniol D et al (2020) Direct and semi-direct radiative forcing of biomass-burning aerosols over the southeast Atlantic (SEA) and its sensitivity to absorbing properties: a regional climate modeling study. Atmos Chem Phys 20(21):13191–13216. https://doi.org/10.5194/acp-20-13191-2020

    Article  Google Scholar 

  • Mallet M, Nabat P, Johnson B, Michou M, Haywood JM, Chen C, Dubovik O (2021) Climate models generally underrepresent the warming by Central Africa biomass-burning aerosols over the Southeast Atlantic. Sci Adv 7:41. https://doi.org/10.1126/sciadv.abg9998

    Article  Google Scholar 

  • Meynadier R, de Coëtlogon G, Leduc-Leballeur M, Eymard L, Janicot S (2016) Seasonal influence of the sea surface temperature on the low atmospheric circulation and precipitation in the eastern equatorial Atlantic. Clim Dyn 47(3):1127–1142. https://doi.org/10.1007/s00382-015-2892-7

    Article  Google Scholar 

  • Miao H, Wang X, Liu Y, Wu G (2019) An evaluation of cloud vertical structure in three reanalyses against CloudSat/cloud-aerosol lidar and infrared pathfinder satellite observations. Atmos Sci Lett 20(7):e906

    Article  Google Scholar 

  • Moron V, Camberlin P, Aellig R, Champagne O, Fink AH, Knippertz P, Philippon P (2023) Diurnal to interannual variability of stratiform cloud cover over western equatorial Africa in May-October (1971–2019). submitted to Int J Climatology

  • Myers TA, Scott RC, Zelinka MD et al (2021) Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity. Nat Clim Chang 11:501–507. https://doi.org/10.1038/s41558-021-01039-0

    Article  Google Scholar 

  • Nam C, Bony S, Dufresne JL, Chepfer H (2012) The ‘too few, too bright’ tropical low-cloud problem in CMIP5 models. Geophys Res Lett. https://doi.org/10.1029/2012GL053421

    Article  Google Scholar 

  • Neupane N (2016) The Congo basin zonal overturning circulation. Adv Atmos Sci 33(6):767–782. https://doi.org/10.1007/s00376-015-5190-8

    Article  Google Scholar 

  • Okumura Y, Xie SP (2004) Interaction of the Atlantic equatorial cold tongue and the African monsoon. J Clim 17(18):3589–3602

    Article  Google Scholar 

  • Philippon N, Cornu G, Monteil L, Gond V, Moron V, Pergaud J et al (2019) The light-deficient climates of western Central African evergreen forests. Envir Res Lett 14(3):1–11. https://doi.org/10.1088/1748-9326/aaf5d8

    Article  Google Scholar 

  • Philippon N, Ouhechou A, Camberlin P, Trentmann J, Fink AH, Maloba-Makanga JD, Morel B, Samba G (2021) Characterization of sunshine duration in Western Equatorial Africa: in-situ measurements vs SARAH-2 satellite estimates. Submitted to Journal of Applied Meteorology and Climatology

  • Réjou-Méchain M, Mortier F, Bastin JF et al (2021) Unveiling African rainforest composition and vulnerability to global change. Nature 593:90–94. https://doi.org/10.1038/s41586-021-03483-6

    Article  Google Scholar 

  • Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis for climate. J Clim 15:1609–1625

    Article  Google Scholar 

  • Richter I (2015) Climate model biases in the eastern tropical oceans: causes, impacts and ways forward. Wiley Interdisciplinary Rev 6(3):345–358

    Google Scholar 

  • Richter I, Tokinaga H (2020) An overview of the performance of CMIP6 models in the tropical Atlantic: mean state, variability, and remote impacts. Clim Dyn 55:2579–2601. https://doi.org/10.1007/s00382-020-05409-w

    Article  Google Scholar 

  • Richter I, Xie SP, Wittenberg AT, Masumoto Y (2012) Tropical Atlantic biases and their relation to surface wind stress and terrestrial precipitation. Clim Dyn 38:985–1001. https://doi.org/10.1007/s00382-011-1038-9

    Article  Google Scholar 

  • Richter I, Xie SP, Behera SK, Masumoto Y (2014) Equatorial Atlantic variability and its relation to mean state biases in CMIP5. Clim Dyn 42(1):171–188

    Article  Google Scholar 

  • Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E et al (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24(14):3624–3648. https://doi.org/10.1175/JCLI-D-11-00015.1

    Article  Google Scholar 

  • Schrage JM, Fink AH (2012) Nocturnal continental low-level stratus over tropical west africa: observations and possible mechanisms controlling its onset. Mon Wea Rev 140(6):1794–1809. https://doi.org/10.1175/MWR-D-11-00172.1

    Article  Google Scholar 

  • Schuster R, Fink AH, Knippertz P (2013) Formation and maintenance of nocturnal low-level stratus over the southern west African monsoon region during AMMA 2006. J Atmos Sci 70(8):2337–2355. https://doi.org/10.1175/JAS-D-12-0241.1

    Article  Google Scholar 

  • Servain J, Merle J (1993) Interannual climate variations over the tropical Atlantic Ocean. In: Shukla J (ed) Prediction of interannual climate variations. NATO ASI series, vol 6. Springer, Berlin

    Google Scholar 

  • Shannon LV, Boyd AJ, Bundrit GB, Taunton-Clark J (1986) On the existence of an El Niño–type phenomenon in the Benguela system. J Mar Sci 44:495–520

    Google Scholar 

  • Slingo JM (1987) The development and verification of a cloud prediction scheme for the ECMWF model. Quart J Roy Meteor Soc 113:899–927

    Article  Google Scholar 

  • Smith A, Lott N, Vose R (2011) The integrated surface database: recent developments and partnerships. Bull Am Met Soc 92(6):704–708. https://doi.org/10.1175/2011BAMS3015.1

    Article  Google Scholar 

  • Sun F, Hall A, Qu X (2011) On the relationship between low cloud variability and lower tropospheric stability in the Southeast Pacific. Atmos Chem Phys 11(17):9053–9065

    Article  Google Scholar 

  • Tiedtke M (1993) Representation of clouds in large-scale models. Mon Weather Rev 121(11):3040–3061

    Article  Google Scholar 

  • Tompkins AM, Feudale L (2010) Seasonal ensemble predictions of West African monsoon precipitation in the ECMWF System 3 with a focus on the AMMA special observing period in 2006. Weather Forecast 25(2):768–788

    Article  Google Scholar 

  • Trewartha GT (1981) The Earth’s problem climates. University of Wisconsin Press, Berlin, p 371

    Google Scholar 

  • Trzaska S, Robertson AW, Farrara JD, Mechoso CR (2007) South Atlantic variability arising from air–sea coupling: local mechanisms and tropical–subtropical interactions. J Clim 20:3345–3365. https://doi.org/10.1175/JCLI4114.1

    Article  Google Scholar 

  • Tschirhart G (1959) Les perturbations atmosphériques intéressant I'AEF méridionale. Monogr Mét Nat, Paris, 13, 32 p

  • Vallès-Casanova I, Lee SK, Foltz GR, Pelegrí JL (2020) On the spatiotemporal diversity of Atlantic Niño and associated rainfall variability over West Africa and South America. Geophys Res Lett 47(8):e2020GL087108

    Article  Google Scholar 

  • Vaughan MA, Powell KA, Winker DM, Hostetler CA, Kuehn RE, Hunt WH et al (2009) Fully automated detection of cloud and aerosol layers in the CALIPSO lidar measurements. J Atmos Oceanic Technol 26(10):2034–2050. https://doi.org/10.1175/2009JTECHA1228.1

    Article  Google Scholar 

  • Vignesh PP, Jiang JH, Kishore P, Su H, Smay T, Brighton N, Velicogna I (2020) Assessment of CMIP6 cloud fraction and comparison with satellite observations. Earth Space Sci 7(2):e2019EA000975

    Article  Google Scholar 

  • Voldoire A, Claudon M, Caniaux G, Giordani H, Roehrig R (2014) Are atmospheric biases responsible for the tropical Atlantic SST biases in the CNRM-CM5 coupled model? Clim Dyn 43(11):2963–2984. https://doi.org/10.1007/s00382-013-2036-x

    Article  Google Scholar 

  • Voldoire A, Saint-Martin D, Sénési S, Decharme B, Alias A, Chevallier M et al (2019a) Evaluation of CMIP6DECK experiments with CNRM-CM6-1. J Adv Model Earth Syst 11:2177–2213. https://doi.org/10.1029/2019MS001683

    Article  Google Scholar 

  • Voldoire A, Exarchou E, Sanchez-Gomez E et al (2019b) Role of wind stress in driving SST biases in the Tropical Atlantic. Clim Dyn 53:3481–3504. https://doi.org/10.1007/s00382-019-04717-0

    Article  Google Scholar 

  • Wahl S, Latif M, Park W, Keenlyside N (2011) On the tropical Atlantic SST warm bias in the Kiel climate model. Clim Dyn 36(5):891–906

    Article  Google Scholar 

  • Webb MJ, Andrews T, Bodas-Salcedo A, Bony S, Bretherton CS, Chadwick R et al (2017) The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6. Geosci. Model Dev 10:359–384. https://doi.org/10.5194/gmd-10-359-2017

    Article  Google Scholar 

  • Wood R (2012) Stratocumulus clouds. Mon Wea Rev 140:2373–2423. https://doi.org/10.1175/MWR-D-11-00121.1

    Article  Google Scholar 

  • Xu Z, Chang P, Richter I, Tang G (2014) Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble. Clim Dyn 43(11):3123–3145

    Article  Google Scholar 

  • Zebiak EZ (1993) Air-sea interaction in the equatorial Atlantic region. J Climate 6:1567–1586

    Article  Google Scholar 

  • Zelinka MD, Randall DA, Webb MJ, Klein SA (2017) Clearing clouds of uncertainty. Nat Clim Chang 7:674–678. https://doi.org/10.1038/nclimate3402

    Article  Google Scholar 

  • Zhang C (1993) Large-scale variability of atmospheric deep convection in relation to sea surface temperature in the tropics. J Climate 6(10):1898–1913

    Article  Google Scholar 

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Acknowledgements

This study is part of the project DYVALOCCA (https://dyvalocca.osug.fr/) funded by ANR and DFG under contracts ANR-19-CE01-0021 and DFG FI 786/5-1. Computations were performed using HPC resources from DNUM CCUB (Centre de Calcul de l’Université de Bourgogne), Dijon, France. The authors thank an anonymous reviewer whose very constructive remarks contributed to improve the manuscript.

Funding

This work has been carried out as part of the DYVALOCCA project funded in France by ANR (Grant ANR-19-CE01-0021) and in Germany by DFG (Grant FI-786/5-1).

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Authors and Affiliations

  1. Centre de Recherches de Climatologie/Biogéosciences, Université de Bourgogne, Dijon, France

    P. Camberlin, J. Pergaud & A. Berger

  2. SOFREN, Nantes, France

    C. F. Togbedji

  3. Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany

    R. Aellig, A. H. Fink & P. Knippertz

  4. Aix Marseille Univ, CNRS, IRD, INRAE, Collège de France, CEREGE, Aix-en-Provence, France

    V. Moron

  5. IRI, Columbia University, New York, USA

    V. Moron

  6. Institut des Géosciences de l’Environnement (IGE), University of Grenoble Alpes, CNRS, IRD, Grenoble INP [Institute of Engineering and Management University of Grenoble Alpes], Grenoble, France

    N. Philippon

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  1. P. Camberlin
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Camberlin, P., Togbedji, C.F., Pergaud, J. et al. The representation of dry-season low-level clouds over Western Equatorial Africa in reanalyses and historical CMIP6 simulations. Clim Dyn 61, 2815–2837 (2023). https://doi.org/10.1007/s00382-023-06714-w

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  • DOI: https://doi.org/10.1007/s00382-023-06714-w

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