Mechanisms of Rainfall Biases in Two CORDEX-CORE Regional Climate Models at Rainfall Peaks over Central Equatorial Africa

Alain T. Tamoffo aPhysics Department, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
bLaboratory for Environmental Modelling and Atmospheric Physics (LEMAP), Physics Department, University of Yaoundé I, Yaoundé, Cameroon

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Leonard K. Amekudzi aPhysics Department, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

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Torsten Weber cClimate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Hamburg, Germany

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Derbetini A. Vondou bLaboratory for Environmental Modelling and Atmospheric Physics (LEMAP), Physics Department, University of Yaoundé I, Yaoundé, Cameroon

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Edmund I. Yamba aPhysics Department, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

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Daniela Jacob cClimate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Hamburg, Germany

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Abstract

Two regional climate models (RCMs) participating in the CORDEX–Coordinated Output for Regional Evaluations (CORDEX-CORE) project feature a dipole-type rainfall bias during March–May (MAM) and September–November (SON) over central equatorial Africa (CEA), consisting of positive bias in west central equatorial Africa (WCEA) and negative bias in east central equatorial Africa (ECEA). One is the Regional Model version 2015 (REMO2015) and the other is the fourth version of the Regional Climate Model (RegCM4-v7). RCMs are nested in three Earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5), and in the reanalysis ERA-Interim, at ∼25-km spacing grid resolution. This study highlights misrepresented underlying physical processes associated with these rainfall biases through a process-based evaluation. Both RCMs produce a weaker Congo basin cell, associated with a weaker land–ocean zonal surface pressure gradient. Consequently, less water vapor enters the region, and little is transported from WCEA to ECEA, resulting in higher moisture availability in the west than in the east. This leads to an unevenly distributed moisture across the region, favoring a stronger atmospheric instability in WCEA where the moist static energy (MSE) anomalously increases through an enhanced latent static energy (LSE). Moisture arrives at a slower pace in ECEA, associated with the weak cell’s strength. The intensity of ascent motions in response to the orographic constraint is weak to destabilize atmospheric stability in the lower layers, necessary for initiating deep convection. Therefore, the convection is shallow in ECEA related to underestimating the MSE due to the reduced LSE.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Alain T. Tamoffo, alaintamoffotchio@gmail.com

Abstract

Two regional climate models (RCMs) participating in the CORDEX–Coordinated Output for Regional Evaluations (CORDEX-CORE) project feature a dipole-type rainfall bias during March–May (MAM) and September–November (SON) over central equatorial Africa (CEA), consisting of positive bias in west central equatorial Africa (WCEA) and negative bias in east central equatorial Africa (ECEA). One is the Regional Model version 2015 (REMO2015) and the other is the fourth version of the Regional Climate Model (RegCM4-v7). RCMs are nested in three Earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5), and in the reanalysis ERA-Interim, at ∼25-km spacing grid resolution. This study highlights misrepresented underlying physical processes associated with these rainfall biases through a process-based evaluation. Both RCMs produce a weaker Congo basin cell, associated with a weaker land–ocean zonal surface pressure gradient. Consequently, less water vapor enters the region, and little is transported from WCEA to ECEA, resulting in higher moisture availability in the west than in the east. This leads to an unevenly distributed moisture across the region, favoring a stronger atmospheric instability in WCEA where the moist static energy (MSE) anomalously increases through an enhanced latent static energy (LSE). Moisture arrives at a slower pace in ECEA, associated with the weak cell’s strength. The intensity of ascent motions in response to the orographic constraint is weak to destabilize atmospheric stability in the lower layers, necessary for initiating deep convection. Therefore, the convection is shallow in ECEA related to underestimating the MSE due to the reduced LSE.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Alain T. Tamoffo, alaintamoffotchio@gmail.com

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  • Alber, K., A. Raghavendra, L. Zhou, Y. Jiang, H. S. Sussman, and S. L. Solimine, 2021: Analyzing intensifying thunderstorms over the Congo Basin using the Gálvez-Davison index from 1983–2018. Climate Dyn., 56, 949967, https://doi.org/10.1007/s00382-020-05513-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baccini, A., and Coauthors, 2012: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nat. Climate Change, 2, 182185, https://doi.org/10.1038/nclimate1354.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Balas, N., S. E. Nicholson, and D. Klotter, 2007: The relationship of rainfall variability in West Central Africa to sea-surface temperature fluctuations. Int. J. Climatol., 27, 13351349, https://doi.org/10.1002/joc.1456.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bell, J. P., A. M. Tompkins, C. Bouka-Biona, and I. S. Sanda, 2015: A process-based investigation into the impact of the Congo basin deforestation on surface climate. J. Geophys. Res., 120, 57215739, https://doi.org/10.1002/2014JD022586.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bentsen, M., and Coauthors, 2013: The Norwegian Earth System Model, NorESM1-M—Part 1: Description and basic evaluation of the physical climate. Geosci. Model Dev., 6, 687720, https://doi.org/10.5194/gmd-6-687-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T., 2004: Maintenance of the midtropospheric North African summer circulation: Saharan high and African easterly jet. J. Climate, 18, 29432962, https://doi.org/10.1175/JCLI3446.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, W. J., and Coauthors, 2011: Development and evaluation of an Earth system model—HadGEM2. Geosci. Model Dev., 4, 10511075, https://doi.org/10.5194/gmd-4-1051-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, K. H., and E. K. Vizy, 2006: Coupled model simulations of the West African monsoon system: Twentieth- and twenty-first-century simulations. J. Climate, 19, 36813703, https://doi.org/10.1175/JCLI3814.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, K. H., and E. K. Vizy, 2016: The Congo Basin Walker circulation: Dynamics and connections to precipitation. Climate Dyn., 47, 697717, https://doi.org/10.1007/s00382-015-2864-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, K. H., Y. Liu, and E. K. Vizy, 2020: Congo Basin drying associated with poleward shifts of the African thermal lows. Climate Dyn., 54, 863883, https://doi.org/10.1007/s00382-019-05033-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Creese, A., and R. Washington, 2016: Using qflux to constrain modeled Congo Basin rainfall in the CMIP5 ensemble. J. Geophys. Res. Atmos., 121, https://doi.org/10.1002/2016JD025596.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Creese, A., and R. Washington, 2018: A process-based assessment of CMIP5 rainfall in the Congo Basin: The September–November rainy season. J. Climate, 31, 74177439, https://doi.org/10.1175/JCLI-D-17-0818.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dargie, G. C., S. L. Lewis, I. T. Lawson, E. T. Mitchard, S. E. Page, Y. E. Bocko, and S. A. Ifo, 2017: Age, extent and carbon storage of the central Congo Basin peatland complex. Nature, 542, 8690, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dezfuli, A. K., and S. E. Nicholson, 2013: The relationship of rainfall variability in western equatorial Africa to the tropical oceans and atmospheric circulation. Part II: The boreal autumn. J. Climate, 26, 6684, https://doi.org/10.1175/JCLI-D-11-00686.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dezfuli, A. K., B. F. Zaitchik, and A. Gnanadesikan, 2015: Regional atmospheric circulation and rainfall variability in south equatorial Africa. J. Climate, 28, 809818, https://doi.org/10.1175/JCLI-D-14-00333.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dickinson, R., R. Errico, F. Giorgi, and G. Bates, 1989: A regional climate model for the western United States. Climatic Change, 15, 383422, https://doi.org/10.1007/BF00240465.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dosio, A., and H. Panitz, 2016: Climate change projections for CORDEX-Africa with COSMO-CLM regional climate model and differences with the driving global climate models. Climate Dyn., 46, 15991625, https://doi.org/10.1007/s00382-015-2664-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dosio, A., and Coauthors, 2021a: Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models. Climate Dyn., 57, 31353158, https://doi.org/10.1007/s00382-021-05859-w.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dosio, A., I. Pinto, C. Lennard, M. B. Sylla, C. Jack, and G. Nikulin, 2021b: What can we know about recent past precipitation over Africa? Daily characteristics of African precipitation from a large ensemble of observational products for model evaluation. Earth Space Sci., 8, e2020EA001466, https://doi.org/10.1029/2020EA001466.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dyer, E. L., D. B. Jones, J. Nusbaumer, H. Li, O. Collins, G. Vettoretti, and D. Noone, 2017: Congo Basin precipitation: Assessing seasonality, regional interactions, and sources of moisture. J. Geophys. Res. Atmos., 122, 68826898, https://doi.org/10.1002/2016JD026240.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fierro, A. O., J. Simpson, M. A. Lemone, J. M. Straka, and B. F. Smull, 2009: On how hot towers fuel the Hadley cell: An observational and modeling study of line-organized convection in the equatorial trough from TOGA COARE. J. Atmos. Sci., 66, 27302746, https://doi.org/10.1175/2009JAS3017.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fotso-Nguemo, T. C., D. A. Vondou, W. M. Pokam, Z. Y. Djomou, I. Diallo, A. Haensler, and C. Tchawoua, 2017: On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa. Climate Dyn., 49, 38133838, https://doi.org/10.1007/s00382-017-3547-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fotso-Nguemo, T. C., and Coauthors, 2021: Potential impact of 1.5, 2 and 3°C global warming levels on heat and discomfort indices changes over Central Africa. Sci. Total Environ., 804, 150099, https://doi.org/10.1016/j.scitotenv.2021.150099.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Funk, C., and Coauthors, 2015: The Climate Hazards Infrared Precipitation with Stations—A new environmental record for monitoring extremes. Sci. Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garcin, Y., and Coauthors, 2018: Early anthropogenic impact on Western Central African rainforests 2,600 y ago. Proc. Natl. Acad. Sci. USA, 115, 32613266, https://doi.org/10.1073/pnas.1715336115.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giorgi, F., 1989: Two-dimensional simulations of possible mesoscale effects of nuclear war fires: 1. Model description. J. Geophys. Res., 94, 1127, https://doi.org/10.1029/JD094iD01p01127.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giorgi, F., and W. J. Gutowski, 2015: Regional dynamical downscaling and the CORDEX initiative. Annu. Rev. Environ. Resour., 40, 467490, https://doi.org/10.1146/annurev-environ-102014-021217.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giorgi, F., C. Jones, and G. R. Asrar, 2009: Addressing climate information needs at the regional level: The CORDEX framework. WMO Bull., 58, 175183, https://public.wmo.int/en/bulletin/addressing-climate-information-needs-regional-level-cordex-framework.

    • Search Google Scholar
    • Export Citation
  • Giorgi, F., and Coauthors, 2012: RegCM4: Model description and preliminary tests over multiple CORDEX domains. Climate Res., 52, 729, https://doi.org/10.3354/cr01018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gleckler, P. J., K. E. Taylor, and C. Doutriaux, 2008: Performance metrics for climate models. J. Geophys. Res., 113, D06104, https://doi.org/10.1029/2007jd008972.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gutowski, W. J., Jr., and Coauthors, 2016: WCRP COordinated Regional Downscaling EXperiment (CORDEX): A diagnostic MIP for CMIP6. Geosci. Model Dev., 9, 40874095, https://doi.org/10.5194/gmd-9-4087-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haensler, A., F. Saeed, and D. Jacob, 2013: Assessing the robustness of projected precipitation changes over central Africa on the basis of a multitude of global and regional climate projections. Climatic Change, 121, 349363, https://doi.org/10.1007/s10584-013-0863-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hamada, A., Y. N. Takayabu, C. Liu, and E. J. Zipser, 2015: Weak linkage between the heaviest rainfall and tallest storms. Nat. Commun., 6, 6213, https://doi.10.1038/ncomms7213.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harris, I., T. J. Osborn, P. Jones, and D. Lister, 2020: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data, 7, 109, https://doi.org/10.1038/s41597-020-0453-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 19992049, https://doi.org/10.1002/qj.3803.

  • Hua, W., L. Zhou, H. Chen, S. E. Nicholson, A. Raghavendra, and Y. Jiang, 2016: Possible causes of the Central Equatorial African long-term drought. Environ. Res. Lett., 11, 124002, https://doi.org/10.1088/1748-9326/11/12/124002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hua, W., L. Zhou, S. E. Nicholson, H. Chen, and M. Qin, 2019: Assessing reanalysis data for understanding rainfall climatology and variability over Central Equatorial Africa. Climate Dyn., 53, 651669, https://doi.org/10.1007/s00382-018-04604-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, B., and Coauthors, 2017: Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Climate, 30, 81798205, https://doi.org/10.1175/JCLI-D-16-0836.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., R. F. Adler, D. T. Bolvin, and G. Gu, 2009: Improving the global precipitation record: GPCP version 2.1. Geophys. Res. Lett., 36, L17808, https://doi.org/10.1029/2009GL040000.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hung, M., J. Lin, W. Wang, D. Kim, T. Shinoda, and S. J. Weaver, 2013: MJO and convectively coupled equatorial waves simulated by CMIP5 climate models. J. Climate, 26, 61856214, https://doi.org/10.1175/JCLI-D-12-00541.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ilori, O. W., and I. A. Balogun, 2021: Evaluating the performance of new CORDEX-Africa regional climate models in simulating West African rainfall. Model. Earth Syst. Environ., https://doi.org/10.1007/s40808-021-01084-w, in press.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jackson, B., S. E. Nicholson, and D. Klotter, 2009: Mesoscale convective systems over western equatorial Africa and their relationship to large-scale circulation. Mon. Wea. Rev. 137, 12721294, https://doi.org/10.1175/2008MWR2525.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jacob, D., 2001: A note to the simulation of the annual and inter-annual variability of the water budget over the Baltic Sea drainage basin. Meteor. Atmos. Phys., 77, 6173, https://doi.org/10.1007/s007030170017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jacob, D., and R. Podzun, 1997: Sensitivity studies with the regional climate model REMO. Meteor. Atmos. Phys., 63, 119129, https://doi.org/10.1007/bf01025368.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • James, R., and Coauthors, 2018: Evaluating climate models with an African lens. Bull. Amer. Meteor. Soc., 99, 313336, https://doi.org/10.1175/BAMS-D-16-0090.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janowiak, J., and P. Xie, 2011: ISLSCP II GTS gauge-based analyses of daily precipitation over global land areas. ORNL Distributed Active Archive Center Datasets, accessed March 2020, https://doi.org/10.3334/ornldaac/1001.

    • Search Google Scholar
    • Export Citation
  • Jiang, Y., L. Zhou, C. J. Tucker, A. Raghavendra, W. Hua, Y. Y. Liu, and J. Joiner, 2019: Widespread increase of boreal summer dry season length over the Congo rainforest. Nat. Climate Change, 9, 617622, https://doi.org/10.1038/s41558-019-0512-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C., F. Giorgi, and G. Asrar, 2011: The Coordinated Regional Downscaling Experiment: CORDEX: An international downscaling link to CMIP5. CLIVAR Exchanges. No. 56, International CLIVAR Project Office, Southampton, United Kingdom, 3440.

    • Search Google Scholar
    • Export Citation
  • Kamae, Y., H. Ueda, and A. Kitoh, 2011: Hadley and Walker circulations in the mid-Pliocene warm period simulated by an atmospheric general circulation model. J. Meteor. Soc. Japan, 89, 475493, https://doi.org/10.2151/jmsj.2011-505.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., K. Yoshimura, Y. Yhang, and S. Hong, 2010: Errors of interannual variability and trend in dynamical downscaling of reanalysis. J. Geophys. Res., 115, D17115, https://doi.org/10.1029/2009jd013511.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • King, A. D., and L. J. Harrington, 2018: The inequality of climate change from 1.5 to 2°C of global warming. Geophys. Res. Lett., 45, 50305033, https://doi.org/10.1029/2018gl078430.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuete, G., W. P. Mba, and R. Washington, 2019: African easterly jet south: Control, maintenance mechanisms and link with southern subtropical waves. Climate Dyn., 54, 15391552, https://doi.org/10.1007/s00382-019-05072-w.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Legates, D. R., and C. J. Willmott, 1990: Mean seasonal and spatial variability in gauge-corrected, global precipitation. Int. J. Climatol., 10, 111127, https://doi.org/10.1002/joc.3370100202.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Longandjo, G. N. T., and M. Rouault, 2020: On the structure of the regional-scale circulation over central Africa: Seasonal evolution, variability, and mechanisms. J. Climate, 33, 145162, https://doi.org/10.1175/JCLI-D-19-0176.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Malhi, Y., 2018: Ancient deforestation in the green heart of Africa. Proc. Natl. Acad. Sci. USA, 115, 32023204, https://doi.org/10.1073/pnas.1802172115.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morioka, Y., S. Masson, P. Terray, C. Prodhomme, S. K. Behera, and Y. Masumoto, 2014: Role of tropical SST variability on the formation of subtropical dipoles. J. Climate, 27, 44864507, https://doi.org/10.1175/JCLI-D-13-00506.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moufouma-Okia, W., and R. Jones, 2015: Resolution dependence in simulating the African hydroclimate with the HadGEM3-RA regional climate model. Climate Dyn., 44, 609632, https://doi.org/10.1007/s00382-014-2322-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Munday, C., R. Washington, and N. Hart, 2021: African low-level jets and their importance for water vapor transport and rainfall. Geophys. Res. Lett., 48, e2020GL090999, https://doi.org/10.1029/2020GL090999.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NASA, 2016: Modern-Era Retrospective Analysis for Research and Applications, version 2. Goddard Earth Sciences Data and Information Services Center, accessed 12 September 2017, https://disc.gsfc.nasa.gov/daac-bin/FTPSubset.pl.

    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., and J. P. Grist, 2003: The seasonal evolution of the atmospheric circulation over West Africa and equatorial Africa. J. Climate, 16, 10131030, https://doi.org/10.1175/15200442(2003)016%3c1013:TSEOTA%3e2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., and A. K. Dezfuli, 2013: The relationship of rainfall variability in western equatorial Africa to the tropical oceans and atmospheric circulation. Part I: The boreal spring. J. Climate, 26, 4565, https://doi.org/10.1175/JCLI-D-11-00653.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., D. Klotter, L. Zhou, and W. Hua, 2019: Validation of satellite precipitation estimates over the Congo Basin. J. Hydrometeor., 20, 631656, https://doi.org/10.1175/JHM-D-18-0118.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Novella, N. S., and W. M. Thiaw, 2013: African Rainfall Climatology version 2 for famine early warning systems. J. Appl. Meteor. Climatol., 52, 588606, https://doi.org/10.1175/JAMC-D-11-0238.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oort, A. H., and J. J. Yienger, 1996: Observed interannual variability in the Hadley circulation and its connection to ENSO. J. Climate, 9, 27512767, https://doi.org/10.1175/1520-0442(1996)0092.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pokam, W. M., L. A. Djiotang, and F. K. Mkankam, 2012: Atmospheric water vapor transport and recycling in equatorial central Africa through NCEP/NCAR reanalysis data. Climate Dyn., 38, 17151729, https://doi.org/10.1007/s00382-011-1242-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pokam, W. M., C. L. Bain, R. S. Chadwick, R. Graham, D. J. Sonwa, and F. M. Kamga, 2014: Identification of processes driving low-level westerlies in west equatorial Africa. J. Climate, 27, 42454262, https://doi.org/10.1175/JCLI-D-13-00490.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Popke, D., B. Stevens, and A. Voigt, 2013: Climate and climate change in a radiative-convective equilibrium version of ECHAM6. J. Adv. Model. Earth Syst., 5 (1), 114, https://doi.org/10.1029/2012MS000191.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Raghavendra, A., 2020: Factors influencing rainfall over the Congo. Ph.D. thesis. State University of New York at Albany, 161 pp., https://www.proquest.com/openview/b0398896db318fc3b5411e85ef38b6f4/1? cbl=18750&diss=y&pq-origsite=gscholar.

    • Search Google Scholar
    • Export Citation
  • Raghavendra, A., L. Zhou, Y. Jiang, and W. Hua, 2018: Increasing extent and intensity of thunderstorms observed over the Congo Basin from 1982 to 2016. Atmos. Res., 213, 1726, https://doi.org/10.1016/j.atmosres.2018.05.028.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Raghavendra, A., P. E. Roundy, and L. Zhou, 2019: Trends in tropical wave activity from the 1980s to 2016. J. Climate, 32, 16611676, https://doi.org/10.1175/jcli-d-18-0225.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Remedio, A. R., and Coauthors, 2019: Evaluation of new CORDEX simulations using an updated Köppen–Trewartha climate classification. Atmosphere, 10, 726, https://doi.org/10.3390/atmos10110726.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roeckner, E., and Coauthors, 1996: The atmospheric general circulation model ECHAM4: Model description and simulation of present-day climate. Max Planck Institute for Meteorology Rep. 218, 171 pp.

    • Search Google Scholar
    • Export Citation
  • Rowell, D. P., 2013: Simulating SST teleconnections to Africa: What is the state of the art? J. Climate, 26, 53975418, https://doi.org/10.1175/JCLI-D-12-00761.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneider, U., A. Becker, P. Finger, A. Meyer-Christoffer, M. Ziese, and B. Rudolf, 2013: GPCC’s new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor. Appl. Climatol., 115, 1540, https://doi.org/10.1007/s00704-013-0860-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sinclaire, Z., A. Lenouo, C. Tchawoua, and S. Janicot, 2015: Synoptic Kelvin type perturbation waves over Congo basin over the period 1979–2010. J. Atmos. Sol. Terr. Phys., 130–131, 4356, https://doi.org/10.1016/j.jastp.2015.04.015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sørland, S. L., and Coauthors, 2021: COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: A review. Geosci. Model Dev., 14, 51255154, https://doi.org/10.5194/gmd-14-5125-2021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stachnik, J. P., and C. Schumacher, 2011: A comparison of the Hadley circulation in modern reanalyses. J. Geophys. Res., 116, D22102, https://doi.org/10.1029/2011jd016677.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevens, B., and Coauthors, 2013: Atmospheric component of the MPI-M Earth System Model: ECHAM6. J. Adv. Model. Earth Syst., 5, 146172, https://doi.org/10.1002/jame.20015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taguela, T. N., and Coauthors, 2020: CORDEX multi-RCM hindcast over central Africa: Evaluation within observational uncertainty. J. Geophys. Res., 125, e2019JD031607, https://doi.org/10.1029/2019JD031607.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tamoffo, A. T., and Coauthors, 2019: Process-oriented assessment of RCA4 regional climate model projections over the Congo Basin under 1.5°C and 2°C global warming levels: Influence of regional moisture fluxes. Climate Dyn., 53, 19111935, https://doi.org/10.1007/s00382-019-04751-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tamoffo, A. T., A. Dosio, D. A. Vondou, and D. Sonkoué, 2020: Process-based analysis of the added value of dynamical downscaling over central Africa. Geophys. Res. Lett., 47, e2020GL089702, https://doi.org/10.1029/2020GL089702.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tamoffo, A. T., G. Nikulin, D. A. Vondou, A. Dosio, R. Nouayou, M. Wu, and P. M. Igri, 2021: Process-based assessment of the impact of reduced turbulent mixing on Congo Basin precipitation in the RCA4 Regional Climate Model. Climate Dyn., 56, 19511965, https://doi.org/10.1007/s00382-020-05571-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, https://doi.org/10.1175/BAMS-D-11-00094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Teichmann, C., and Coauthors, 2020: Assessing mean climate change signals in the global CORDEX-CORE ensemble. Climate Dyn., 57, 12691292, https://doi.org/10.1007/s00382-020-05494-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Titchner, H. A., and N. A. Rayner, 2014: The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations. J. Geophys. Res., 119, 28642889, https://doi.org/10.1002/2013jd020316.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Todd, M. C., and R. Washington, 2004: Climate variability in central equatorial Africa: Influence from the Atlantic sector. Geophys. Res. Lett., 31, L23202, https://doi.org/10.1029/2004GL020975.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Toniazzo, T., and S. Woolnough, 2013: Development of warm SST errors in the southern tropical Atlantic in CMIP5 decadal hindcasts. Climate Dyn., 43, 28892913, https://doi.org/10.1007/s00382-013-1691-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vondou, D. A., and A. Haensler, 2017: Evaluation of simulations with the regional climate model REMO over Central Africa and the effect of increased spatial resolution. Int. J. Climatol., 37, 741760, https://doi.org/10.1002/joc.5035.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wahl, S., M. Latif, W. Park, and N. Keenlyside, 2009: On the tropical Atlantic SST warm bias in the Kiel Climate Model. Climate Dyn., 36, 891906, https://doi.org/10.1007/s00382-009-0690-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Washington, R., R. James, H. Pearce, W. M. Pokam, and W. Moufouma-Okia, 2013: Congo Basin rainfall climatology: Can we believe the climate models? Philos. Trans. Roy. Soc. London, B368, 20120296, https://doi.org/10.1098/rstb.2012.0296.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weber, T., A. Haensler, and D. Jacob, 2017: Sensitivity of the atmospheric water cycle to corrections of the sea surface temperature bias over southern Africa in a regional climate model. Climate Dyn., 51, 28412855, https://doi.org/10.1007/s00382-017-4052-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weber, T., A. Haensler, D. Rechid, S. Pfeifer, B. Eggert, and D. Jacob, 2018: Analyzing regional climate change in Africa in a 1.5, 2, and 3°C global warming world. Earth’s Future, 6, 643655, https://doi.org/10.1002/2017EF000714.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, S., and K. H. Cook, 2021: Influence of Walker circulations on East African rainfall. Climate Dyn., https://doi.org/10.1007/s00382-020-05579-7.

    • Search Google Scholar
    • Export Citation
  • Zhou, L., and Coauthors, 2014: Widespread decline of Congo rainforest greenness in the past decade. Nature, 509, 8690, https://doi.org/10.1038/nature13265.

    • Crossref
    • Search Google Scholar
    • Export Citation
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