A Process-Based Assessment of CMIP5 Rainfall in the Congo Basin: The September–November Rainy Season

A. Creese School of Geography and the Environment, University of Oxford, Oxford, United Kingdom

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R. Washington School of Geography and the Environment, University of Oxford, Oxford, United Kingdom

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Abstract

Congo basin September–November rainfall varies by up to a factor of 3 across CMIP5 coupled models. The severe lack of observational data in this region makes model evaluation difficult using standard techniques. This study uses a process-based assessment to evaluate the plausibility of mechanisms related to coupled model rainfall in September–November. Models tend to simulate a rainfall maximum in either the west or east of the basin. In most months, western Congo rainfall is positively correlated with eastern Congo rainfall across models, as relatively wet models are often wetter everywhere; however, in August–November this correlation becomes insignificant, suggesting that processes relating to rainfall differences in each subdomain are distinct. Composite analysis of wet and dry models in each subdomain suggests that the tropical eastern Atlantic SST bias helps differentiate between models in the west: wetter models tend to have a larger (~1°–2°C) and more equatorward SST bias, higher evaporation over the ocean, and higher local convection. In the east, rainfall differences between models are related to more remote SST differences, including cold South Atlantic and warm eastern Indian Ocean SSTs. Wetter models exhibit stronger westerly flow across the tropical eastern Atlantic, as part of an enhanced equatorial zonal overturning cell. Dry models in the east feature a stronger and more equatorward northerly component of the midlevel African easterly jet, which may contribute to suppressed convection over the domain. This assessment casts doubt on the credibility of models that are very wet in the west of the Congo basin and have a large Atlantic SST bias.

ORCID: 0000-0002-2681-2555.

© 2018 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: Amy Creese, amy.creese@ouce.ox.ac.uk

Abstract

Congo basin September–November rainfall varies by up to a factor of 3 across CMIP5 coupled models. The severe lack of observational data in this region makes model evaluation difficult using standard techniques. This study uses a process-based assessment to evaluate the plausibility of mechanisms related to coupled model rainfall in September–November. Models tend to simulate a rainfall maximum in either the west or east of the basin. In most months, western Congo rainfall is positively correlated with eastern Congo rainfall across models, as relatively wet models are often wetter everywhere; however, in August–November this correlation becomes insignificant, suggesting that processes relating to rainfall differences in each subdomain are distinct. Composite analysis of wet and dry models in each subdomain suggests that the tropical eastern Atlantic SST bias helps differentiate between models in the west: wetter models tend to have a larger (~1°–2°C) and more equatorward SST bias, higher evaporation over the ocean, and higher local convection. In the east, rainfall differences between models are related to more remote SST differences, including cold South Atlantic and warm eastern Indian Ocean SSTs. Wetter models exhibit stronger westerly flow across the tropical eastern Atlantic, as part of an enhanced equatorial zonal overturning cell. Dry models in the east feature a stronger and more equatorward northerly component of the midlevel African easterly jet, which may contribute to suppressed convection over the domain. This assessment casts doubt on the credibility of models that are very wet in the west of the Congo basin and have a large Atlantic SST bias.

ORCID: 0000-0002-2681-2555.

© 2018 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: Amy Creese, amy.creese@ouce.ox.ac.uk
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  • Balas, N., S. E. Nicholson, and D. Klotter, 2007: The relationship of rainfall variability in west central Africa to sea-surface temperature fluctuation. Int. J. Climatol., 27, 13351349, https://doi.org/10.1002/joc.1456.

    • 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
  • Biasutti, M., A. H. Sobel, and S. J. Camargo, 2009: The role of the Sahara low in summertime Sahel rainfall variability and change in the CMIP3 models. J. Climate, 22, 57555771, https://doi.org/10.1175/2009JCLI2969.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Black, E., J. Slingo, and K. R. Sperber, 2003: An observational study of the relationship between excessively strong short rains in coastal East Africa and Indian Ocean SST. Mon. Wea. Rev., 131, 7494, https://doi.org/10.1175/1520-0493(2003)131<0074:AOSOTR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blamey, R. C., and C. J. C. Reason, 2012: Mesoscale convective complexes over southern Africa. J. Climate, 25, 753766, https://doi.org/10.1175/JCLI-D-10-05013.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bollasina, M. A., and Y. Ming, 2013: The general circulation model precipitation bias over the southwestern equatorial Indian Ocean and its implications for simulating the South Asian monsoon. Climate Dyn., 40, 823838, https://doi.org/10.1007/s00382-012-1347-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camberlin, P., and R. E. Okoola, 2003: The onset and cessation of the “long rains” in eastern Africa and their interannual variability. Theor. Appl. Climatol., 54, 4354, https://doi.org/10.1007/s00704-002-0721-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collier, M., and P. Uhe, 2012: CMIP5 datasets from the ACCESS1.0 and ACCESS1.3 coupled climate models. Centre for Australian Weather and Climate Research Tech. Rep. 059, 25 pp.

  • 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
  • Creese, A., and R. Washington, 2016: Using qflux to constrain modeled Congo basin rainfall in the CMIP5 ensemble. J. Geophys. Res. Atmos., 121, 13 41513 442, https://doi.org/10.1002/2016JD025596.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dargie, G. C., S. L. Lewis, I. T. Lawson, E. T. A. 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/10.1038/nature21048.

    • 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., 2017: Climate of western and central equatorial Africa. Oxford Research Encyclopedia of Climate Science, 46 pp., https://doi.org/10.1093/acrefore/9780190228620.013.511.

    • Crossref
    • Export Citation
  • Dezfuli, A., 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., 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
  • Dieppois, B., M. Rouault, and M. New, 2015: The impact of ENSO on southern African rainfall in CMIP5 ocean atmosphere coupled climate models. Climate Dyn., 45, 24252442, https://doi.org/10.1007/s00382-015-2480-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Donner, L. J., and Coauthors, 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J. Climate, 24, 34843519, https://doi.org/10.1175/2011JCLI3955.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dufresne, J.-L., and Coauthors, 2013: Climate change projections using the IPSL-CM5 Earth System Model: From CMIP3 to CMIP5. Climate Dyn., 40, 21232165, https://doi.org/10.1007/s00382-012-1636-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dyer, E. L. E., D. B. A. 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
  • Eichhorn, A., and J. Bader, 2017: Impact of tropical Atlantic sea-surface temperature biases on the simulated atmospheric circulation and precipitation over the Atlantic region: An ECHAM6 model study. Climate Dyn., 49, 20612075, https://doi.org/10.1007/s00382-016-3415-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Folland, C. K., T. N. Palmer, and D. E. Parker, 1986: Sahel rainfall and worldwide sea temperatures, 1901–85. Nature, 320, 602607, https://doi.org/10.1038/320602a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fontaine, B., S. Janicot, and V. Moron, 1995: Rainfall anomaly patterns and wind field signals over West Africa in August (1958–1989). J. Climate, 8, 15031510, https://doi.org/10.1175/1520-0442(1995)008<1503:RAPAWF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gent, P. R., and Coauthors, 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991, https://doi.org/10.1175/2011JCLI4083.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grist, J. P., and S. E. Nicholson, 2001: A study of the dynamic factors influencing the rainfall variability in the West African Sahel. J. Climate, 14, 13371359, https://doi.org/10.1175/1520-0442(2001)014<1337:ASOTDF>2.0.CO;2.

    • 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
  • Harris, I., P. D. Jones, T. J. Osborn, and D. H. Lister, 2014: Updated high-resolution grids of monthly climatic observations—The CRU TS3.10 dataset. Int. J. Climatol., 34, 623642, https://doi.org/10.1002/joc.3711.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hart, N. C. G., C. J. C. Reason, and N. Fauchereau, 2013: Cloud bands over southern Africa: Seasonality, contribution to rainfall variability and modulation by the MJO. Climate Dyn., 41, 11991212, https://doi.org/10.1007/s00382-012-1589-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hastenrath, S., 2000: Zonal circulations over the equatorial Indian Ocean. J. Climate, 13, 27462756, https://doi.org/10.1175/1520-0442(2000)013<2746:ZCOTEI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hazeleger, W., and Coauthors, 2010: EC-Earth: A seamless Earth-system prediction approach in action. Bull. Amer. Meteor. Soc., 91, 13571364, https://doi.org/10.1175/2010BAMS2877.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hirons, L., and A. Turner, 2018: The impact of Indian Ocean mean-state biases on the representation of the East African short rains. J. Climate, https://doi.org/10.1175/JCLI-D-17-0804.1, in press.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoerling, M., J. Hurrell, J. Eischeid, and A. Phillips, 2006: Detection and attribution of twentieth-century northern and southern African rainfall change. J. Climate, 19, 39894008, https://doi.org/10.1175/JCLI3842.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., and Coauthors, 2007: The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J. Hydrometeor., 8, 3855, https://doi.org/10.1175/JHM560.1.

    • 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
  • James, R., R. Washington, and R. Jones, 2015: Process-based assessment of an ensemble of climate projections for West Africa. J. Geophys. Res. Atmos., 120, 12211238, https://doi.org/10.1002/2014JD022513.

    • 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
  • Jeffrey, S., L. Rotstayn, M. Collier, S. Dravitzki, C. Hamalainen, C. Moeseneder, K. Wong, and J. Syktus, 2013: Australia’s CMIP5 submission using the CSIRO-Mk3.6 model. Aust. Meteor. Oceanogr. J., 63, 113, https://doi.org/10.22499/2.6301.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C. D., and Coauthors, 2011: The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci. Model Dev., 4, 543570, https://doi.org/10.5194/gmd-4-543-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Joseph, S., A. K. Sahai, B. N. Goswami, P. Terray, S. Masson, and J.-J. Luo, 2012: Possible role of warm SST bias in the simulation of boreal summer monsoon in SINTEX-F2 coupled model. Climate Dyn., 38, 15611576, https://doi.org/10.1007/s00382-011-1264-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jury, M. R., E. Matari, and M. Matitu, 2009: Equatorial African climate teleconnections. Theor. Appl. Climatol., 95, 407416, https://doi.org/10.1007/s00704-008-0018-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., and T. N. Krishnamurti, 1978: Northern summer tropical circulations during drought and normal rainfall months. Mon. Wea. Rev., 106, 331347, https://doi.org/10.1175/1520-0493(1978)106<0331:NSTCDD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Large, W. G., and G. Danabasoglu, 2006: Attribution and impacts of upper-ocean biases in CCSM3. J. Climate, 19, 23252346, https://doi.org/10.1175/JCLI3740.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lazenby, M. J., M. C. Todd, and Y. Wang, 2016: Climate model simulation of the south Indian Ocean convergence zone: Mean state and variability. Climate Res., 68, 5971, https://doi.org/10.3354/cr01382.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, L., and Coauthors, 2013: The Flexible Global Ocean-Atmosphere-Land System Model, grid-point version 2: FGOALS-g2. Adv. Atmos. Sci., 30, 543560, https://doi.org/10.1007/s00376-012-2140-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liebmann, B., and Coauthors, 2014: Understanding recent eastern Horn of Africa rainfall variability and change. J. Climate, 27, 86308645, https://doi.org/10.1175/JCLI-D-13-00714.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lyon, B., and D. G. DeWitt, 2012: A recent and abrupt decline in the East African long rains. Geophys. Res. Lett., 39, L02702, https://doi.org/10.1029/2011GL050337.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marsland, S. J., H. Haak, J. H. Jungclaus, M. Latif, and F. Röske, 2003: The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Modell., 5, 91127, https://doi.org/10.1016/S1463-5003(02)00015-X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Munday, C., and R. Washington, 2017: Circulation controls on southern African precipitation in coupled models: The role of the Angola low. J. Geophys. Res. Atmos., 122, 861877, https://doi.org/10.1002/2016JD025736.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neale, R. B., and Coauthors, 2012: Description of the NCAR Community Atmosphere Model (CAM 5.0). NCAR Tech. Note NCAR/TN-486+STR, 268 pp., http://www.cesm.ucar.edu/models/cesm1.2/cam/docs/description/cam5_desc.pdf.

  • Newell, R. E., and J. W. Kidson, 1984: African mean wind changes between Sahelian wet and dry periods. J. Climatol., 4, 2733, https://doi.org/10.1002/joc.3370040103.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Niang, I., and Coauthors, 2014: Africa. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Cambridge University Press, 1199–1265, http://www.ipcc.ch/pdf/assessment-report/ar5/wg2/WGIIAR5-Chap22_FINAL.pdf.

  • Nicholson, S. E., 1980: The nature of rainfall fluctuations in subtropical West Africa. Mon. Wea. Rev., 108, 473487, https://doi.org/10.1175/1520-0493(1980)108<0473:TNORFI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., 2017: Climate and climatic variability of rainfall over eastern Africa. Rev. Geophys., 55, 590635, https://doi.org/10.1002/2016RG000544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., and D. Entekhabi, 1987: Rainfall variability in equatorial and southern Africa: Relationships with sea surface temperatures along the southwestern coast of Africa. J. Climate Appl. Meteor., 26, 561578, https://doi.org/10.1175/1520-0450(1987)026<0561:RVIEAS>2.0.CO;2.

    • Crossref
    • 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/10.1175/1520-0442(2003)016<1013:TSEOTA>2.0.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
  • Pokam, W. M., L. A. Tchotchou 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
  • Pomposi, C., Y. Kushnir, and A. Giannini, 2015: Moisture budget analysis of SST-driven decadal Sahel precipitation variability in the twentieth century. Climate Dyn., 44, 33033321, https://doi.org/10.1007/s00382-014-2382-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prodhomme, C., P. Terray, S. Masson, T. Izumo, T. Tozuka, and T. Yamagata, 2014: Impacts of Indian Ocean SST biases on the Indian monsoon: As simulated in a global coupled model. Climate Dyn., 42, 271290, https://doi.org/10.1007/s00382-013-1671-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reason, C. J. C., and H. Mulenga, 1999: Relationships between South African rainfall and SST anomalies in the southwest Indian Ocean. Int. J. Climatol., 19, 16511673, https://doi.org/10.1002/(SICI)1097-0088(199912)19:15<1651::AID-JOC439>3.0.CO;2-U.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Richter, I., 2015: Climate model biases in the eastern tropical oceans: Causes, impacts and ways forward. Wiley Interdiscip. Rev.: Climate Change, 6, 345358, https://doi.org/10.1002/wcc.338.

    • Search Google Scholar
    • Export Citation
  • Richter, I., S.-P. Xie, A. T. Wittenberg, and Y. Masumoto, 2012: Tropical Atlantic biases and their relation to surface wind stress and terrestrial precipitation. Climate Dyn., 38, 9851001, https://doi.org/10.1007/s00382-011-1038-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Richter, I., and Coauthors, 2016: An overview of coupled GCM biases in the tropics. Indo-Pacific Climate Variability and Predictability, S. K. Behera and T. Yamagata, Eds., World Scientific, 213–263.

    • Crossref
    • Export Citation
  • Rowell, D. P., B. B. B. Booth, S. E. Nicholson, and P. Good, 2015: Reconciling past and future rainfall trends over East Africa. J. Climate, 28, 97689788, https://doi.org/10.1175/JCLI-D-15-0140.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sandjon, A. T., A. Nzeukou, and C. Tchawoua, 2012: Intraseasonal atmospheric variability and its interannual modulation in central Africa. Meteor. Atmos. Phys., 117, 167179, https://doi.org/10.1007/s00703-012-0196-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmidt, G. A., and Coauthors, 2014: Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive. J. Adv. Model. Earth Syst., 6, 141184, https://doi.org/10.1002/2013MS000265.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneider, U., A. Becker, P. Finger, A. Meyer-Christoffer, B. Rudolf, and M. Ziese, 2015: GPCC full data reanalysis at 0.5°: Monthly land-surface precipitation from rain-gauges built on GTS-based and historic data, version 7.0. GPCC, accessed 19 May 2016, https://doi.org/10.5676/DWD_GPCC/FD_M_V7_050.

    • Crossref
    • Export Citation
  • Scoccimarro, E., and Coauthors, 2011: Effects of tropical cyclones on ocean heat transport in a high-resolution coupled general circulation model. J. Climate, 24, 43684384, https://doi.org/10.1175/2011JCLI4104.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sorí, R., R. Nieto, S. M. Vicente-Serrano, A. Drumond, and L. Gimeno, 2017: A Lagrangian perspective of the hydrological cycle in the Congo River basin. Earth Syst. Dyn., 8, 653675, https://doi.org/10.5194/esd-8-653-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, Q., C. Miao, Q. Duan, H. Ashouri, S. Sorooshian, and K.-L. Hsu, 2018: A review of global precipitation datasets: Data sources, estimation, and intercomparisons. Rev. Geophys., 56, 79107, https://doi.org/10.1002/2017RG000574.

    • 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
  • Tierney, J. E., C. C. Ummenhofer, and P. B. deMenocal, 2015: Past and future rainfall in the Horn of Africa. Sci. Adv., 1, e1500682, https://doi.org/10.1126/sciadv.1500682.

    • 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. Atmos., 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
  • Uccellini, L. W., and D. R. Johnson, 1979: The coupling of upper and lower tropospheric jet streaks and implications for the development of severe convective storms. Mon. Wea. Rev., 107, 682703, https://doi.org/10.1175/1520-0493(1979)107<0682:TCOUAL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ummenhofer, C. C., A. Sen Gupta, M. H. England, and C. J. C. Reason, 2009: Contributions of Indian Ocean sea surface temperatures to enhanced East African rainfall. J. Climate, 22, 9931013, https://doi.org/10.1175/2008JCLI2493.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van Der Ent, R. J., H. H. G. Savenije, B. Schaefli, and S. C. Steele-Dunne, 2010: Origin and fate of atmospheric moisture over continents. Water Resour. Res., 46, W09525, https://doi.org/10.1029/2010WR009127.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Viste, E., D. Korecha, and A. Sorteberg, 2013: Recent drought and precipitation tendencies in Ethiopia. Theor. Appl. Climatol., 112, 535551, https://doi.org/10.1007/s00704-012-0746-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voldoire, A., and Coauthors, 2013: The CNRM-CM5.1 global climate model: Description and basic evaluation. Climate Dyn., 40, 20912121, https://doi.org/10.1007/s00382-011-1259-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., L. Zhang, S.-K. Lee, L. Wu, and C. R. Mechoso, 2014: A global perspective on CMIP5 climate model biases. Nat. Climate Change, 4, 201205, https://doi.org/10.1038/nclimate2118.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Washington, R., and Coauthors, 2006: African climate change: Taking the shorter route. Bull. Amer. Meteor. Soc., 87, 13551366, https://doi.org/10.1175/BAMS-87-10-1355.

    • 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, 368B, 20120296, https://doi.org/10.1098/rstb.2012.0296.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and Coauthors, 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 63126335, https://doi.org/10.1175/2010JCLI3679.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, A. P., and Coauthors, 2012: Recent summer precipitation trends in the greater Horn of Africa and the emerging role of Indian Ocean sea surface temperature. Climate Dyn., 39, 23072328, https://doi.org/10.1007/s00382-011-1222-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, C. A., N. P. Hanan, J. C. Neff, R. J. Scholes, J. A. Berry, A. S. Denning, and D. F. Baker, 2007: Africa and the global carbon cycle. Carbon Balance Manag., 2, https://doi.org/10.1186/1750-0680-2-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, T., and Coauthors, 2013: Global carbon budgets simulated by the Beijing Climate Center Climate System Model for the last century. J. Geophys. Res. Atmos., 118, 43264347, https://doi.org/10.1002/jgrd.50320.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 25392558, https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, Z., P. Chang, I. Richter, W. Kim, and G. Tang, 2014: Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble. Climate Dyn., 43, 31233145, https://doi.org/10.1007/s00382-014-2247-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, W., R. Seager, M. A. Cane, and B. Lyon, 2015: The rainfall annual cycle bias over East Africa in CMIP5 coupled climate models. J. Climate, 28, 97899802, https://doi.org/10.1175/JCLI-D-15-0323.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yukimoto, S., and Coauthors, 2012: A new global climate model of the Meteorological Research Institute: MRI-CGCM3—Model description and basic performance. J. Meteor. Soc. Japan, 90A, 2364, https://doi.org/10.2151/jmsj.2012-A02.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zuidema, P., and Coauthors, 2016: Challenges and prospects for reducing coupled climate model SST biases in the eastern tropical Atlantic and Pacific Oceans: The U.S. CLIVAR eastern tropical oceans synthesis working group. Bull. Amer. Meteor. Soc., 97, 23052328, https://doi.org/10.1175/BAMS-D-15-00274.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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