• Arrighi, J., and et al. , 2017: Dialogue for decision-making: Unpacking the ‘City Learning Lab’ approach. Working Paper Series 7, Red Cross/Red Crescent Climate Centre, 15 pp., www.climatecentre.org/downloads/files/RCCC_JA_wps%207%20City%20Learning%20Lab%20v2.pdf.

    • Search Google Scholar
    • Export Citation
  • Becker, T., B. Stevens, and C. Hohenegger, 2017: Imprint of the convective parameterization and sea-surface temperature on large-scale convective self-aggregation. J. Adv. Model. Earth Syst., 9, 14881505, https://doi.org/10.1002/2016MS000865.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berthou, S., E. Kendon, D. Rowell, M. Roberts, S. Tucker, and R. A. Stratton, 2019a: Larger future intensification of rainfall in the West African Sahel in a convection-permitting model. Geophys. Res. Lett., 46, 13 29913 307, https://doi.org/10.1029/2019GL083544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berthou, S., D. P. Rowell, J. Crook, E. J. Kendon, M. Roberts, R. Stratton, and C. Wilcox, 2019b: Improved climatological precipitation characteristics over West Africa at convection-permitting scales. Climate Dyn., 53, 19912011, https://doi.org/10.1007/s00382-019-04759-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berthou, S., E. J. Kendon, S. C. Chan, N. Ban, D. Leutwyler, C. Schär, and G. Fosser, 2020: Pan-European climate at convection-permitting scale: A model intercomparison study. Climate Dyn., 55, 3550, https://doi.org/10.1007/s00382-018-4114-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beucher, F., J. Lafore, F. Karbou, and R. Roca, 2014: High-resolution prediction of a major convective period over West Africa. Quart. J. Roy. Meteor. Soc., 140, 14091425, https://doi.org/10.1002/qj.2225.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beucher, F., J. Lafore, and N. Chapelon, 2020: Simulation and analysis of the moist vortex associated with the extreme rain event of Ouagadougou in 2009. Quart. J. Roy. Meteor. Soc., 146, 86104, https://doi.org/10.1002/qj.3645.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Birch, C. E., D. J. Parker, A. O’Leary, J. H. Marsham, C. M. Taylor, P. P. Harris, and G. M. S. Lister, 2012: Impact of soil moisture and convectively generated waves on the initiation of a West African mesoscale convective system. Quart. J. Roy. Meteor. Soc., 139, 17121730, https://doi.org/10.1002/qj.2062.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Birch, C. E., D. J. Parker, J. Marsham, D. Copsey, and L. Garcia-Carreras, 2014a: A seamless assessment of the role of convection in the water cycle of the West African monsoon. J. Geophys. Res. Atmos., 119, 28902912, https://doi.org/10.1002/2013JD020887.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Birch, C. E., J. H. Marsham, D. J. Parker, and C. M. Taylor, 2014b: The scale dependence and structure of convergence fields preceding the initiation of deep convection. Geophys. Res. Lett., 41, 47694776, https://doi.org/10.1002/2014GL060493.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bouvier, C., N. Chahinian, M. Adamovic, C. Cassé, A. Crespy, A. Crès, and M. Alcoba, 2018: Large-scale GIS-based urban flood modelling: A case study on the City of Ouagadougou. Advances in Hydroinformatics, P. Gourbesville, J. Cunge, and G. Caignaert, Eds., Springer, 703717

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burgin, L., and et al. , 2019a: FCFA HyCRISTAL climate rural narrative infographic and brief. Zenodo, accessed 12 December 2020, https://doi.org/10.5281/zenodo.3257287.

    • Crossref
    • Export Citation
  • Burgin, L., and et al. , 2019b: FCFA HyCRISTAL climate rural narrative infographic and brief. Zenodo, accessed 12 December 2020, https://doi.org/10.5281/zenodo.3257302.

    • Crossref
    • Export Citation
  • Burgin, L., D. Rowell, and J. Marsham, 2020: Possible futures for East Africa under a changing climate: Technical appendix for HyCRISTAL’s Climate Risk Narratives. Zenodo, accessed 12 December 2020, https://doi.org/105281/zenodo.3620757.

    • Search Google Scholar
    • Export Citation
  • Bush, M., and et al. , 2020: The first Met Office unified model/JULES regional atmosphere and land configuration, RAL1. Geosci. Model Dev., 13, 19992029, https://doi.org/10.5194/gmd-13-1999-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chaboureau, J.-P., and et al. , 2016: Fennec dust forecast intercomparison over the Sahara in June 2011. Atmos. Chem. Phys., 16, 69776995, https://doi.org/10.5194/acp-16-6977-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chapman, S., C. Birch, E. Pope, S. Sallu, C. Bradshaw, J. Davie, and J. Marsham, 2020: Impact of climate change on crop suitability in sub-Saharan Africa in parameterized and convection permitting regional climate models. Environ. Res. Lett., 15, 094086, https://doi.org/10.1088/1748-9326/ab9daf.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, W. J., and et al. , 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
  • Coppin, D., and S. Bony, 2018: On the interplay between convective aggregation, surface temperature gradients, and climate sensitivity. J. Adv. Model. Earth Syst., 10, 31233138, https://doi.org/10.1029/2018MS001406.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coppola, E., and et al. , 2020: A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean. Climate Dyn., 55, 334, https://doi.org/10.1007/s00382-018-4521-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crook, J., C. Klein, S. Folwell, C. M. Taylor, D. J. Parker, and T. Stein, 2019: Assessment of the representation of West African storm lifecycles in convection-permitting simulations. Earth Space Sci., 6, 818835, https://doi.org/10.1029/2018EA000491.

    • Search Google Scholar
    • Export Citation
  • Dolman, A. J., and D. Gregory, 1992: The parametrization of rainfall interception in GCMs. Quart. J. Roy. Meteor. Soc., 118, 455467, https://doi.org/10.1002/qj.49711850504.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunning, C., E. Black, and R. Allan, 2016: The onset and cessation of seasonal rainfall over Africa. J. Geophys. Res. Atmos., 121, 11 40511 424, https://doi.org/10.1002/2016JD025428.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Engel, T., A. H. Fink, P. Knippertz, G. Pante, and J. Bliefernicht, 2017: Extreme precipitation in the West African cities of Dakar and Ouagadougou: Atmospheric dynamics and implications for flood risk assessments. J. Hydrometeor., 18, 29372957, https://doi.org/10.1175/JHM-D-16-0218.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Evans, B. E., D. P. Rowell, and F. H. M. Semazzi, 2020: The Future-climate current-policy framework: Towards an approach that links climate science to sector policy development. Environ. Res. Lett., 15, 114037, https://doi.org/10.1088/1748-9326/abbeb9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Field, P. R., and et al. , 2017: Exploring the convective grey zone with regional simulations of a cold air outbreak. Quart. J. Roy. Meteor. Soc., 143, 25372555, https://doi.org/10.1002/qj.3105.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Finney, D. L., J. H. Marsham, E. J. Kendon, D. P. Rowell, P. M. Boorman, R. J. Keane, R. A. Stratton, and C. A. Senior, 2019: Implications of improved representation of convection for the East Africa water budget using a convection-permitting model. J. Climate, 32, 21092129, https://doi.org/10.1175/JCLI-D-18-0387.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Finney, D. L., J. Marsham, D. Rowell, E. Kendon, S. Tucker, R. Stratton, and L. Jackson, 2020a: Effects of explicit convection on future projections of mesoscale circulations, rainfall, and rainfall extremes over Eastern Africa. J. Climate, 33, 27012718, https://doi.org/10.1175/JCLI-D-19-0328.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Finney, D. L., and et al. , 2020b: African lightning and its relation to rainfall and climate change in a convection-permitting model. Geophys. Res. Lett., 47, e2020GL088163, https://doi.org/10.1029/2020GL088163.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fitzpatrick, R. G. J., and et al. , 2020a: How a typical West African day in the future-climate compares with current-climate conditions in a convection-permitting and parameterized convection climate model. Climatic Change, 163, 267296, https://doi.org/10.1007/s10584-020-02881-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fitzpatrick, R. G. J., and et al. , 2020b: What drives the intensification of mesoscale convective systems over the West African Sahel under climate change? J. Climate, 33, 31513172, https://doi.org/10.1175/JCLI-D-19-0380.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Flato, G., and et al. , 2013: Climate Change 2013: The Physical Science Basis, T. F. Stocker et al. , Eds., Cambridge University Press, 741866., https://doi.org/10.1017/CBO9781107415324.020.

    • Crossref
    • Export Citation
  • Galle, S., and et al. , 2018: AMMA-CATCH, a critical zone observatory in West Africa monitoring a region in transition. Vadose Zone J., 17, 180062, https://doi.org/10.2136/vzj2018.03.0062.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garcia-Carreras, L., and et al. , 2013: The impact of convective cold pool outflows on model biases in the Sahara. Geophys. Res. Lett., 40, 16471652, https://doi.org/10.1002/grl.50239.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gibba, P., M. Sylla, E. Okogbue, A. Gaye, M. Nikiema, and I. Kebe, 2019: State-of-the-art climate modeling of extreme precipitation over Africa: Analysis of CORDEX added-value over CMIP5. Theor. Appl. Climatol., 137, 10411057, https://doi.org/10.1007/s00704-018-2650-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gregory, D., and P. R. Rowntree, 1990: A mass-flux convection scheme with representation of cloud ensemble characteristics and stability dependent closure. Mon. Wea. Rev., 118, 14831506, https://doi.org/10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hart, N., R. Washington, and R. Stratton, 2018: Stronger local overturning in convective-permitting regional climate model improves simulation of the subtropical annual cycle. Geophys. Res. Lett., 45, 11 33411 342, https://doi.org/10.1029/2018GL079563.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heinold, B., P. Knippertz, J. H. Marsham, S. Fiedler, N. S. Dixon, K. Schepanski, B. Laurent, and I. Tegen, 2013: The role of deep convection and nocturnal low-level jets for dust emission in summertime West Africa: Estimates from convection-permitting simulations. J. Geophys. Res. Atmos., 118, 43854400, https://doi.org/10.1002/jgrd.50402.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hirons, L. C., N. P. Klingaman, and S. J. Woolnough, 2018: The impact of air-sea interactions on the representation of tropical precipitation extremes. J. Adv. Model Earth Syst., 10, 550559, https://doi.org/10.1002/2017MS001252.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holloway, C. E., and et al. , 2014: Understanding and representing atmospheric convection across scales: Recommendations from the meeting held at Dartington Hall, Devon, UK, 28–30 January 2013. Atmos. Sci. Lett., 15, 348353, https://doi.org/10.1002/asl2.508.

    • Search Google Scholar
    • Export Citation
  • Jack, C. D., R. G. Jones, L. Burgin, and J. Daron, 2020: Climate risk narratives: An iterative reflective process for co-producing and integrating climate knowledge. Climate Risk Manage., 29, 100239, https://10.1016/J.CRM2020.100239.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jackson, L., R. J. Keane, D. L. Finney, J. H. Marsham, D. J. Parker, C. A. Senior, and R. A. Stratton, 2019: Regional differences in the response of rainfall to convectively coupled Kelvin waves over tropical Africa. J. Climate, 32, 81438165, https://doi.org/10.1175/JCLI-D-19-0014.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jackson, L., D. Finney, E. Kendon, J. Marsham, D. Parker, R. Stratton, L. Tomassini, and S. Tucker, 2020: The effect of explicit convection on couplings between rainfall, humidity and ascent over Africa under climate change. J. Climate, 33, 83158337, https://doi.org/10.1175/JCLI-D-19-0322.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • James, R., and et al. , 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
  • Jones, L., and et al. , 2015: Ensuring climate information guides long-term development. Nat. Climate Change, 5, 812814, https://doi.org/10.1038/nclimate2701.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Judt, F., 2018: Insights into atmospheric predictability through global convection-permitting model simulations. J. Atmos. Sci., 75, 14771497, https://doi.org/10.1175/JAS-D-17-0343.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kendon, E. J., R. A. Stratton, S. O. Tucker, J. H. Marsham, S. Berthou, D. P. Rowell, and C. A. Senior, 2019: Enhanced future changes in wet and dry extremes over Africa at convection-permitting scale. Nat. Commun., 10, 1794, https://doi.org/10.1038/S41467-019-09776-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kendon, E. J., A. F. Prein, C. A. Senior, and A. Stirling, 2020: Challenges and outlook for convection-permitting climate modelling. Philos. Trans. Roy. Soc., 379A, 20190547, https://doi.org/10.1098/rsta.2019.0547.

    • Search Google Scholar
    • Export Citation
  • Lafore, J.-P., and et al. , 2017: A multi-scale analysis of the extreme rain event of Ouagadougou in 2009. Quart. J. Roy. Meteor. Soc., 143, 30943109, https://doi.org/10.1002/qj.3165.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lemos, M., C. Kirchhof, and V. Ramprasad, 2012: Narrowing the climate information usability gap. Nat. Climate Change, 2, 789794, https://doi.org/10.1038/nclimate1614.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marsham, J. H., P. Knippertz, N. S. Dixon, D. J. Parker, and G. M. S. Lister, 2011: The importance of the representation of deep convection for modeled dust-generating winds over West Africa during summer. Geophys. Res. Lett., 38, L16803, https://doi.org/10.1029/2011GL048368.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marsham, J. H., N. S. Dixon, L. Garcia-Carreras, G. M. S. Lister, D. J. Parker, P. Knippertz, and C. E. Birch, 2013: The role of moist convection in the West African monsoon system: Insights from continental-scale convection-permitting simulations. Geophys. Res. Lett., 40, 18431849, https://doi.org/10.1002/grl.50347.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mase, A., and L. Prokopy, 2014: Unrealized potential: A review of perceptions and use of weather and climate information in agricultural decision making. Wea. Climate Soc., 6, 4761, https://doi.org/10.1175/WCAS-D-12-00062.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maurer, V., I. Bischoff-Gauß, N. Kalthoff, L. Gantner, R. Roca, and H. Panitz, 2017: Initiation of deep convection in the Sahel in a convection-permitting climate simulation for northern Africa. Quart. J. Roy. Meteor. Soc., 143, 806816, https://doi.org/10.1002/qj.2966..

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miralles, D. G., J. H. Gash, T. R. H. Holmes, R. A. M. de Jeu, and A. J. Dolman, 2010: Global canopy interception from satellite observations. J. Geophys. Res., 115, D16122, https://doi.org/10.1029/2009JD013530.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mittal, N., and et al. , 2021: Tailored climate projections enhance understanding of site-specific vulnerability of tea. Climate Risk Manage., submitted.

    • Search Google Scholar
    • Export Citation
  • Moss, R. H., and et al. , 2010: The next generation of scenarios for climate change research and assessment. Nature, 463, 747756, https://doi.org/10.1038/nature08823.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, J. M., and et al. , 2018: UKCP18 land projections: Science report. Met Office Rep., 191 pp., www.metoffice.gov.uk/pub/data/weather/uk/ukcp18/science-reports/UKCP18-Land-report.pdf.

    • Search Google Scholar
    • Export Citation
  • Mwalukanga, B., G. Siame, and A. McClure, 2016: Report on the Inception Workshop and Learning Lab Held on 6th and 7th September, 2016 at Chaminuka Lodge. Tech. Rep., 19 pp., www.fractal.org.za/wp-content/uploads/2017/03/FRACTAL_Lusaka-LL1_Report.pdf.

    • Search Google Scholar
    • Export Citation
  • Neumann, B., A. T. Vafeidis, J. Zimmermann, and R. J. Nicholls, 2015: Future coastal population growth and exposure to sea-level rise and coastal flooding - A global assessment. PLOS ONE, 10, e0118571, https://doi.org/10.1371/journal.pone.0118571.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nka, B. N., L. Oudin, H. Karambiri, J. E. Paturel, and P. Ribstein, 2015: Trends in floods in West Africa: Analysis based on 11 catchments in the region. Hydrol. Earth Syst. Sci., 19, 47074719, https://doi.org/10.5194/hess-19-4707-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pante, G., and P. Knippertz, 2019: Resolving Sahelian thunderstorms improves mid-latitude weather forecasts. Nat. Commun., 10, 3487, https://doi.org/10.1038/s41467-019-11081-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Panthou, G., T. Vischel, and T. Lebel, 2014: Recent trends in the regime of extreme rainfall in the Central Sahel. Int. J. Climatol., 34, 39984006, https://doi.org/10.1002/joc.3984.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Panthou, G., and et al. , 2018: Rainfall intensification in tropical semi-arid regions: The Sahelian case. Environ. Res. Lett., 13, 064013, https://doi.org/10.1088/1748-9326/aac334.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pearson, K. J., R. J. Hogan, R. P. Allan, G. M. S. Lister, and C. E. Holloway, 2010: Evaluation of the model representation of the evolution of convective systems using satellite observations of outgoing longwave radiation. J. Geophys. Res., 115, D20206, https://doi.org/10.1029/2010JD014265.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pinto, I., C. Lennard, M. Tadross, B. Hewitson, A. Dosio, G. Nikulin, H. Panitz, and M. E. Shongwe, 2016: Evaluation and projections of extreme precipitation over southern Africa from two CORDEX models. Climatic Change, 135, 655668, https://doi.org/10.1007/s10584-015-1573-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prein, A. F., and et al. , 2015: A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Rev. Geophys., 53, 323361, https://doi.org/10.1002/2014RG000475.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax, 2007: Daily high-resolution blended analyses for sea surface temperature. J. Climate, 20, 54735496, https://doi.org/10.1175/2007JCLI1824.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, A., M. Woodage, J. Marsham, E. Highwood, C. Ryder, W. McGinty, S. Wilson, and J. Crook, 2018: Can explicit convection improve modelled dust in summertime West Africa? Atmos. Chem. Phys., 18, 90259048, https://doi.org/10.5194/acp-18-9025-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Satoh, M., and et al. , 2018: Toward reduction of the uncertainties in climate sensitivity due to cloud processes using a global non-hydrostatic atmospheric model. Prog. Earth Planet. Sci., 5, 67, https://doi.org/10.1186/s40645-018-0226-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Satoh, M., B. Stevens, F. Judt, M. Khairoutdinov, S.-J. Lin, W. M. Putman, and P. Düben, 2019: Global cloud-resolving models. Curr. Climate Change Rep., 5, 172184, https://doi.org/10.1007/s40641-019-00131-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Senior, C., and et al. , 2020: Technical guidelines for using CP4-Africa simulation data. Zenodo, accessed 12 December 2020, https://doi.org/10.5281/zenodo.4316466.

    • Search Google Scholar
    • Export Citation
  • Shongwe, M., C. Lennard, B. Liebmann, E. Kalognoumou, L. Ntsangwane, and I. Pinto, 2014: An evaluation of CORDEX regional climate models in simulating precipitation over Southern Africa. Atmos. Res. Lett., 16, 199207, https://doi.org/10.1002/asl2.538.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Soares, P., and R. Cardoso, 2018: A simple method to assess the added value using high-resolution climate distributions: Application to the Euro-Cordex daily precipitation. Int. J. Climatol., 38, 14841498, https://doi.org/10.1002/joc.5261.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stein, T., and et al. , 2019: An evaluation of clouds and precipitation in convection-permitting forecasts for South Africa. Wea. Forecasting, 34, 233254, https://doi.org/10.1175/WAF-D-18-0080.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevens, B. M., and et al. , 2019: DYAMOND: The DYnamics of the atmospheric general circulation modeled on non-hydrostatic domains. Prog. Earth Planet. Sci., 6, 61, https://doi.org/10.1186/s40645-019-0304-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stratton, R. A., and et al. , 2018: A pan-Africa convection-permitting regional climate simulation with the Met Office unified model: CP4-Africa. J. Climate, 31, 34853508, https://doi.org/10.1175/JCLI-D-17-0503.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, C. M., C. E. Birch, D. J. Parker, N. Dixon, F. Guichard, G. Nikulin, and G. M. S. Lister, 2013: Modeling soil moisture-precipitation feedback in the Sahel: Importance of spatial scale versus convective parameterization. Geophys. Res. Lett., 40, 62136218, https://doi.org/10.1002/2013GL058511.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, C. M., and et al. , 2017: Frequency of extreme Sahelian storms tripled since 1982 in satellite observations. Nature, 544, 475478, https://doi.org/10.1038/nature22069.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tomassini, L., P. R. Field, R. Honnert, S. Malardel, R. McTaggart-Cowan, K. Saitou, A. T. Noda, and A. Seifert, 2017: The “Grey Zone” cold air outbreak global model intercomparison: A cross evaluation using large-eddy simulations. J. Atmos. Sci., 9, 3964, https://doi.org/10.1002/2016MS000822.

    • Search Google Scholar
    • Export Citation
  • TRMM, 2011: TRMM (TMPA) Rainfall Estimate L3 3 hour 0.25 degree × 0.25 degree V7. Tech. Rep., Goddard Earth Sciences Data and Information Services Center, accessed 12 December 2020, https://doi.org/10.5067/TRMM/TMPA/3H/7.

    • Search Google Scholar
    • Export Citation
  • Van de Walle, J., W. Thiery, O. Brousse, N. Souverijns, M. Demuzere, and N. van Lipzig, 2020: A convection-permitting model for the Lake Victoria basin: Evaluation and insight into the mesoscale versus synoptic atmospheric dynamics. Climate Dyn., 54, 17791799, https://doi.org/10.1007/s00382-019-05088-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vischel, T., and T. Lebel, 2007: Assessing the water balance in the Sahel: Impact of small scale rainfall variability on runoff. Part II: Idealized modeling of runoff sensitivity. J. Hydrol., 333, 340355, https://doi.org/10.1016/j.jhydrol.2006.09.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vischel, T., T. Lebel, S. Massuel, and B. Cappelaere, 2009: Conditional simulation schemes of rain fields and their application to rainfall–runoff modeling studies in the Sahel. J. Hydrol., 375, 273286, https://doi.org/10.1016/j.jhydrol.2009.02.028.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vizy, E. K., and K. H. Cook, 2019: Understanding the summertime diurnal cycle of precipitation over sub-Saharan West Africa: Regions with daytime rainfall peaks in the absence of significant topographic features. Climate Dyn., 52, 29032922, https://doi.org/10.1007/s00382-018-4315-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vrac, M., P. Drobinski, A. Merlo, M. Herrmann, C. Lavaysse, L. Li, and S. Somot, 2012: Dynamical and statistical downscaling of the French Mediterranean climate: Uncertainty assessment. Nat. Hazards Earth Syst. Sci., 12, 27692784, https://doi.org/10.5194/nhess-12-2769-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wainwright, C. M., J. H. Marsham, D. P. Rowell, D. L. Finney, and E. Black, 2021: Future changes in seasonality in Eastern Africa from regional simulations with explicit and parametrised convection. J. Climate, 34, 13671385, https://doi.org/10.1175/JCLI-D-20-0450.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Walters, D., and et al. , 2017: The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geosci. Model Dev., 10, 14871520, https://doi.org/10.5194/gmd-10-1487-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilcox, C., and et al. , 2018: Trends in hydrological extremes in the Senegal and Niger Rivers. J. Hydrol., 566, 531545, https://doi.org/10.1016/j.jhydrol.2018.07.063.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilcox, C., C. Aly, T. Vischel, G. Panthou, J. Blanchet, G. Quantin, and T. Lebel, 2021: Stochastorm: A stochastic rainfall simulator for convective storms. J. Hydrometeor., 22, 387404, https://doi.org/10.1175/JHM-D-20-0017.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woodhams, B., C. Birch, J. Marsham, C. Bain, N. Roberts, and D. Boyd, 2018: What is the added-value of a convection-permitting model for forecasting extreme rainfall over tropical East Africa? Mon. Wea. Rev., 146, 27572780, https://doi.org/10.1175/MWR-D-17-0396.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., R. Joyce, S. Wu, S.-H. Yoo, Y. Yarosh, F. Sun, and R. Lin, 2017: Reprocessed, bias-corrected CMORPH global high-resolution precipitation estimates from 1998. J. Hydrometeorology, 18, 16171641, https://doi.org/10.1175/JHM-D-584-16-0168.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Convection-Permitting Regional Climate Change Simulations for Understanding Future Climate and Informing Decision-Making in Africa

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  • 1 Met Office, Exeter, United Kingdom
  • | 2 University of Leeds, Leeds, United Kingdom
  • | 3 Met Office, Exeter, United Kingdom
  • | 4 U.K. Centre for Ecology and Hydrology, Wallingford, United Kingdom
  • | 5 Met Office, Exeter, United Kingdom
  • | 6 U.K. Centre for Ecology and Hydrology, Wallingford, United Kingdom, and Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
  • | 7 Met Office, Exeter, United Kingdom
  • | 8 University of Leeds, Leeds, United Kingdom
  • | 9 Met Office, Exeter, United Kingdom
  • | 10 Univ. Grenoble Alpes, IRD, CNRS, Grenoble INP, IGE, Grenoble, France
  • | 11 Met Office, Exeter, United Kingdom
  • | 12 University of Leeds, Leeds, United Kingdom
  • | 13 Met Office, Exeter, United Kingdom
  • | 14 University of Oxford, Oxford, United Kingdom
  • | 15 Climate Systems Analysis Group, University of Cape Town, Cape Town, South Africa
  • | 16 University of Leeds, Leeds, United Kingdom
  • | 17 University of Oxford, Oxford, United Kingdom
  • | 18 Red Cross Red Crescent Climate Centre, The Hague, Netherlands
  • | 19 IGAD Climate Prediction and Application Centre, Nairobi, Kenya
  • | 20 University of Zambia and Lusaka City Council, Lusaka, Zambia
  • | 21 University of Leeds, Leeds, United Kingdom
  • | 22 Met Office, Exeter, United Kingdom
  • | 23 U.K. Centre for Ecology and Hydrology, and National Centre for Earth Observation, Wallingford, United Kingdom
  • | 24 Met Office, Exeter, United Kingdom
  • | 25 University of Reading, and National Centre for Atmospheric Science, Reading, United Kingdom
  • | 26 University of Oxford, Oxford, United Kingdom
  • | 27 Met Office, Exeter, United Kingdom
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Abstract

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact-relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly, effects of explicit convection affect not only projected changes in rainfall extremes, dry spells, and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change means that we can provide regional decision-makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the U.K. Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international coordination of such computationally and human-resource expensive simulations as effectively as possible.

© 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: C. A. Senior, cath.senior@metoffice.gov.uk

Abstract

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact-relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly, effects of explicit convection affect not only projected changes in rainfall extremes, dry spells, and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change means that we can provide regional decision-makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the U.K. Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international coordination of such computationally and human-resource expensive simulations as effectively as possible.

© 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: C. A. Senior, cath.senior@metoffice.gov.uk

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