Centre for Research on the Epidemiology of Disasters. The Human Cost of Weather related Disasters
633 1995-2015. The United Nations Office for Disaster Risk Reduction. United Nations 2015.
634 2. World Meteorological Organization. State of the Climate in Africa 2019. WMO 2020, WMO- No. 1253.
635 3. United States Agency International Development. Climate Change Adaptation in Zambia. USAID 2020.
636 4. Venäläinen, A.; Pilli-Sihvola, K.; Tuomenvirta, H.; Ruuhela, R.; Kululanga, E.; Mtilatila, L.; Kanyanga, J.K.;
637 Nkomoki, J. Analysis of the meteorological capacity for early warnings in Malawi and Zambia. Climate
638 and Development 2015, 8, 1–7. doi:10.1080/17565529.2015.1034229.
639 5. Skamarock, W.C.; Klemp, J.B.; Dudhia, J.; Gill, D.O.; Liu, Z.; Berner, J.; Wang, W.; Powers, J.G.; Duda, M.G.;
640 Barker, D.M.; Huang, X.Y. A Description of the Advanced Research WRF Version 4. Technical report,
641 NCAR, 2019. NCAR Tech. Note NCAR/TN-556+STR, 145 pp, doi:10.5065/1dfh-6p97.
642 6. Courtier, P.; Geleyn, J.F. A global numerical weather predictionmodel with variable resolution: Application
643 to the shallow model equations. Q. J. Roy. Meteorol. Soc. 1988, 114, 1321–1346.
644 7. Walters, D.; Baran, A.J.; Boutle, I.; Brooks, M.; Earnshaw, P.; Edwards, J.; Furtado, K.; Hill, P.; Lock, A.;
645 Manners, J.; Morcrette, C.; Mulcahy, J.; Sanchez, C.; Smith, C.; Stratton, R.; Tennant, W.; Tomassini, L.;
646 Van Weverberg, K.; Vosper, S.; Willett, M.; Browse, J.; Bushell, A.; Carslaw, K.; Dalvi, M.; Essery, R.;
647 Gedney, N.; Hardiman, S.; Johnson, B.; Johnson, C.; Jones, A.; Jones, C.; Mann, G.; Milton, S.; Rumbold,
648 H.; Sellar, A.; Ujiie, M.; Whitall, M.; Williams, K.; Zerroukat, M. The Met Office Unified Model Global
649 Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations. Geosci. Model Devel. 2019, 12, 1909–1963.
650 doi:10.5194/gmd-12-1909-2019.
651 8. Sela, J. Implementation of the sigma pressure hybrid coordinate into GFS. NCEP Office Note 2009, 461, 1 –
652 25.
Version December 30, 2020 submitted to Climate 31 of 34
653 9. ECMWF. IFS Documentation CY47R1. Technical report, ECMWF, 2020.
654 10. Maidment, R.I.; Grimes, D.I.F.; Black, E.; Tarnavsky, E.; Young, M.; Greatrex, H.; Allan, R.P.; Stein, T.H.M.;
655 Nkonde, E.; Senkunda, S.; Alcántara, E.M.U. A new, long-term daily satellite-based rainfall dataset for
656 operational monitoring in Africa. Nature Scientific Data 2017, 4, 170063. doi:10.1038/sdata.2017.63.
657 11. World Meteorological Organization. Commission for basic systems severe weather forecasting
658 demonstration project (SWFDP): The overall project plan. Technical report, WMO, 2010.
659 12. World Meteorological Organization. WorldWeather Information Service: Official Forecasts. WMO 2020.
660 13. Bauer, P.; Thorpe, A.; Brunet, G. The quiet revolution of numerical weather prediction. Nature 2015,
661 525, 47–55. doi:10.1038/nature14956.
662 14. Carr, H. Atos supercomputer to enhance weather prediction capabilities for leading European numerical
663 weather centre ECMWF. ECMWF 2020.
664 15. Met Office Press Office. Up to £1.2billion for weather and climate supercomputer. Met Office 2020.
665 16. Motshegwa, T.; Wright, C.; Sithole, H.; Ngolwe, C.; Morgan, A. Developing a Cyber-infrastructure for
666 Enhancing Regional Collaboration on Education, Research, Science, Technology and Innovation. 2018
667 IST-AfricaWeek Conference (IST-Africa), 2018, pp. 1–9.
668 17. Bopape, M.M.; Sithole, H.; Motshegwa, T.; Rakate, E.; Engelbrecht, F.; Morgan, A.; Ndimeni, L.; Botai, O.J.
669 A Regional Project in Support of the SADC Cyber-Infrastructure Framework Implementation: Weather
670 and Climate. Data Sci. J. 2019, 18, 34. doi:10.5334/dsj-2019-034.
671 18. Kanno, H.; Sakurai, T.; Shinjo, H.; Miyazaki, H.; Ishimoto, Y.; Saeki, T.; UMETSU, C. Analysis
672 of Meteorological Measurements made over Three Rainy Seasons and Rainfall Simulations in
673 Sinazongwe District, Southern Province, Zambia. Japan Agricultural Research Quarterly 2015, 49, 59–71.
674 doi:10.6090/jarq.49.59.
675 19. Stensrud, D. Parametrization schemes. Keys to understanding numerical weather prediction models.
676 Reprint of the 2007 hardback ed. Parameterization Schemes: Keys to Understanding Numerical Weather
677 Prediction Models 2007, p. 480. doi:10.1017/CBO9780511812590.
678 20. Stull, R.B. An introduction to boundary layer meteorology. Dordrecht: Kluwer Academic Publishers 1988, p.
679 666.
680 21. Houze, R.A.J. Cloud Dynamics. Academic Press 1994, p. 573.
681 22. Deardorff, J.W. Parameterization of the planetary boundary layer for use in general circulation models.
682 Monthly Weather Review 1974, 100, 93–106. doi:10.1175/1520-0493(1972)100<0093:POTPBL>2.3.CO;2.
683 23. Qian, Y.; Yan, H.; Berg, L.K.; Hagos, S.; Feng, Z.; Yang, B.; Huang, M. Assessing Impacts of PBL and
684 Surface Layer Schemes in Simulating the Surface-Atmosphere Interactions and Precipitation over the
685 Tropical Ocean Using Observations from AMIE/DYNAMO. Journal of Climate 15 Nov. 2016, 29, 8191 –
686 8210. doi:10.1175/JCLI-D-16-0040.1.
687 24. Jahn, D.; Gallus, W. Impacts of Modifications to a Local Planetary Boundary Layer Scheme
688 on Forecasts of the Great Plains Low-Level Jet Environment. Weather and Forecasting 2018, 33.
689 doi:10.1175/WAF-D-18-0036.1.
690 25. Hong, S.Y.; Noh, Y.; Dudhia, J. A New Vertical Diffusion Package with an Explicit Treatment of Entrainment
691 Processes. Monthly Weather Review 2006, 134, 2318–2341. doi:10.1175/MWR3199.1.
692 26. Nakanishi, M.; Niino, H. Development of an Improved Turbulence Closure Model for the Atmospheric
693 Boundary Layer. Journal of the Meteorological Society of Japan 2009, 87, 895–912. doi:10.2151/jmsj.87.895.
694 27. Bélair, S.; Mailhot, J.; Strapp, J.W.; MacPherson, J.I. An Examination of Local versus Nonlocal Aspects of a
695 TKE-Based Boundary Layer Scheme in Clear Convective Conditions. Journal of Applied Meteorology 1999,
696 38, 1499 – 1518. doi:10.1175/1520-0450(1999)038<1499:AEOLVN>2.0.CO;2.
697 28. Cohen, A.E.; Cavallo, S.M.; Coniglio, M.C.; Brooks, H.E.; Jirak, I.L. Evaluation of Multiple Planetary
698 Boundary Layer Parameterization Schemes in Southeast U.S. Cold Season Severe Thunderstorm
699 Environments. Weather and Forecasting 2017, 32, 1857 – 1884. doi:10.1175/WAF-D-16-0193.1.
700 29. Comin, A.; Justino, F.; Pezzi, L.; Gurjão, C.; Schumacher, V.; Fernández, A.; Sutil, U. Extreme rainfall event
701 in the Northeast coast of Brazil: a numerical sensitivity study. Meteorology and Atmospheric Physics 2020.
702 doi:10.1007/s00703-020-00747-0.
703 30. Hu, X.M.; Nielsen-Gammon, J.W.; Zhang, F. Evaluation of Three Planetary Boundary Layer
704 Schemes in the WRF Model. Journal of Applied Meteorology and Climatology 2010, 49, 1831 – 1844.
705 doi:10.1175/2010JAMC2432.1.
Version December 30, 2020 submitted to Climate 32 of 34
706 31. de Lange, A.; Naidoo, M.; Garland, R.; Dyson, L. Sensitivity of meteorological variables on planetary
707 boundary layer parameterization schemes in the WRF-ARW model. Atmospheric Research 2020, p. 105214.
708 doi:10.1016/j.atmosres.2020.105214.
709 32. Libanda, B.; Ogwang, B.; Ongoma, V.; Ngonga, C.; Nyasa, L. Diagnosis of the 2010 DJF flood over Zambia.
710 Natural Hazards 2015. doi:10.1007/s11069-015-2069-z.
711 33. Hachigonta, S.; Reason, C. Interannual variability in dry and wet spell characteristics over Zambia. Climate
712 Research 2006, 32, 49–62. doi:10.3354/cr032049.
713 34. Thurlow, J.; Zhu, T.; Diao, X. The Impact of Climate Variability and Change on Economic Growth and
714 Poverty in Zambia. International Food Policy Research Institute (IFPRI), IFPRI discussion papers 2009.
715 35. Nyambe, S.; Gomes, C.; Lubasi, F.; Gomes, A. Analysis of lightning occurence in Zambia. 2014, pp.
716 1919–1925. doi:10.1109/ICLP.2014.6973442.
717 36. Libanda, B.; Nkolola, N.; Bathsheba, M. Rainfall Variability over Northern Zambia. Journal of Scientific
718 Research and Reports 2015, 6, 416–425. doi:10.9734/JSRR/2015/16189.
719 37. del Ninno, C.; Marini, A. Household’s vulnerability to shocks in Zambia. Social Protection Discussion paper,
720 the World Bank 2005, 526, 43.
721 38. Luque-Fernandez, M.; Bauernfeind, A.; Díaz, J.; Linares, C.; Omeiri, N.; Guibert, D. Influence of
722 temperature and rainfall on the evolution of cholera epidemics in Lusaka, Zambia, 2003–2006: analysis
723 of a time series. Transactions of the Royal Society of Tropical Medicine and Hygiene 2008, 103, 137–43.
724 doi:10.1016/j.trstmh.2008.07.017.
725 39. Chinowsky, P.; Schweikert, A.; Strzepek, N.; Strzepek, K. Infrastructure and climate change: a
726 study of impacts and adaptations in Malawi, Mozambique, and Zambia. Climatic Change 2014, 130.
727 doi:10.1007/s10584-014-1219-8.
728 40. Thurlow, J.; Diao, X. Current Climate Variability and Future Climate Change: Estimated
729 Growth and Poverty Impacts for Zambia. Review of Development Economics 2012, 16.
730 doi:10.1111/j.1467-9361.2012.00670.x.
731 41. Clark, P.; Roberts, N.; Lean, H.; Ballard, S.; Charlton-Perez, C. Convection-permitting models: A
732 step-change in rainfall forecasting. Meteorol Appl 2016, 23. doi:10.1002/met.1538.
733 42. Wang, W. WRF: More Runtime Options. WRF Tutorial, UNSW, Sydney, Australia 2017, p. 46.
734 43. Sun, B.Y.; Bi, X. Validation for a tropical belt version of WRF: sensitivity tests on radiation and
735 cumulus convection parameterizations. Atmospheric and Oceanic Science Letters 2019, pp. 1–9.
736 doi:10.1080/16742834.2019.1590118.
737 44. Iacono, M.; Delamere, J.; Mlawer, E.; Shepard, M.; Clough, S.; Collins, W. Radiative Forcing by
738 Long-Lived Greenhouse Gases: Calculations with the AER Radiative Transfer Models. J. Geophys Res, 113.
739 doi:10.1029/2008JD009944.
740 45. Hong, S.Y.; Kim, J.H.; Lim, J.O.; Dudhia, J. The WRF single moment microphysics scheme (WSM). Journal
741 of the Korean Meteorological Society 2006, 42, 129–151.
742 46. Tiedtke, M.A. A Comprehensive Mass Flux Scheme For Cumulus Parameterization In Large-Scale Models.
743 Mon Weather Rev 1989, 117. doi:10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.
744 47. Zhang, C.; Wang, Y.; Hamilton, K. Improved Representation of Boundary Layer Clouds over the Southeast
745 Pacific in ARW-WRF Using a Modified Tiedtke Cumulus Parameterization Scheme. Mon Weather Rev 2011,
746 139, 3489–3513. doi:10.1175/MWR-D-10-05091.1.
747 48. Zhang, S.; Matsui, T.; Cheung, S.; Zupanski, M.; Peters-Lidard, C. Impact of Assimilated
748 Precipitation-Sensitive Radiances on the NU-WRF Simulation of the West African Monsoon. Mon Weather
749 Rev 2017, 145. doi:10.1175/MWR-D-16-0389.1.
750 49. Holtslag, A.A.M.; Boville, B.A. Local Versus Nonlocal Boundary-Layer Diffusion in a Global Climate
751 Model. Journal of Climate 1993, 6, 1825–1842. doi:10.1175/1520-0442(1993)006<1825:LVNBLD>2.0.CO;2.
752 50. Bretherton, C.S.; Park, S. A NewMoist Turbulence Parameterization in the Community AtmosphereModel.
753 Journal of Climate 2009, 22, 3422–3448. doi:10.1175/2008JCLI2556.1.
754 51. Hong, S.Y.; Pan, H.L. Nonlocal Boundary Layer Vertical Diffusion in a Medium-Range Forecast Model.
755 Monthly Weather Review 1996, 124, 2322–2339. doi:10.1175/1520-0493(1996)124<2322:NBLVDI>2.0.CO;2.
756 52. Lean, H.W.; Clark, P.A.; Dixon, M.; Roberts, N.M.; Fitch, A.; Forbes, R.; Halliwell, C. Characteristics of
757 High-Resolution Versions of the Met Office Unified Model for Forecasting Convection over the United
758 Kingdom. Mon. Weather Rev. 2008, 136, 3408–3424.
Version December 30, 2020 submitted to Climate 33 of 34
759 53. Kain, J.S.; Weiss, S.J.; Levit, J.J.; Baldwin, M.E.; Bright, D.R. Examination of convection-allowing
760 configurations of theWRF model for the prediction of severe convective weather: The SPC/NSSL Spring
761 Program 2004. Wea. Forecasting 2006, 21, 167–181.
762 54. Crook, J.; Klein, C.; Folwell, S.; Taylor, C.M.; Parker, D.J.; Stratton, R.; Stein, T. Assessment of the
763 Representation ofWest African Storm Lifecycles in Convection-Permitting Simulations. Earth Space Sci.
764 2019, 6, 818–835. doi:10.1029/2018EA000491.
765 55. Tarnavsky, E.; Grimes, D.; Maidment, R.; Black, E.; Allan, R.; Stringer, M.; Chadwick, R.; Kayitakire, F.
766 Extension of the TAMSAT Satellite-Based Rainfall Monitoring over Africa and from 1983 to Present. J Appl
767 Meteorol and Clim 2014, 53, 2805–2822. doi:10.1175/JAMC-D-14-0016.1.
768 56. Huffman, G.; Bolvin, D.; Braithwaite, D.; Hsu, K.; Joyce, R.; P., X. Integrated Multi-satellitE Retrievals for
769 GPM (IMERG), version 4.4. NASA’s Precipitation Processing Center. NASA 2014.
770 57. Hersbach, H.; Dee, D. ERA5 reanalysis is in production. ECMWF 2016.
771 58. Davis, C.; Brown, B.; Bullock, R. Object-Based Verification of Precipitation Forecasts. Part I:
772 Methodology and Application to Mesoscale Rain Areas. Monthly Weather Review 2006, 134, 1772 – 1784.
773 doi:10.1175/MWR3145.1.
774 59. Davis, C.; Brown, B.; Bullock, R. Object-Based Verification of Precipitation Forecasts. Part II: Application to
775 Convective Rain Systems. Monthly Weather Review 2006, 134, 1785 – 1795. doi:10.1175/MWR3146.1.
776 60. Brown, B.; Bullock, R.; Gotway, J.; Ahijevch, D.; Davis, C.; Gilleland, E.; Holland, L. Application of the
777 MODE object-based verification tool for the evaluation of model precipitation fields. Preprints, 22nd Conf.
778 on Weather Analysis and Forecasting/18th Conf. on Numerical Weather Prediction, Park City, UT, Amer. Meteor.
779 Soc., 10A.2. [Available online at http://ams.confex.com/ams/pdfpapers/124856.pdf] 2007.
780 61. Beusch, L.; Foresti, L.; Gabella, M.; Hamann, U. Satellite-Based Rainfall Retrieval: From Generalized Linear
781 Models to Artificial Neural Networks. Remote Sensing 2018, 10, 939. doi:10.3390/rs10060939.
782 62. Kerns, B.; Chen, S. ECMWF and GFS model forecast verification during DYNAMO: Multiscale variability
783 in MJO initiation over the equatorial Indian Ocean. Journal of Geophysical Research: Atmospheres 2014, 119.
784 doi:10.1002/2013JD020833.
785 63. Dias, J.; Gehne, M.; Kiladis, G.; Sakaeda, N.; Bechtold, P.; Haiden, T. Equatorial Waves and the Skill
786 of NCEP and ECMWF Numerical Weather Prediction Systems. Monthly Weather Review 2018, 146.
787 doi:10.1175/MWR-D-17-0362.1.
788 64. Molongwane, C.; Bopape, M.J.; Fridlind, A.; Motshegwa, T.; Matsui, T.; Phaduli, E.; Sehurutshi, B.; Maisha,
789 R. Sensitivity of Botswana Ex-Tropical Cyclone Dineo rainfall simulations to cloud microphysics scheme.
790 AAS Open Research 2020, 3, 30. doi:10.12688/aasopenres.13062.1.
791 65. Ndarana, T.; Rammopo Tsholanang, S.; Chikoore, H.; Barnes, M.A.; Bopape, M.J. A quasi-geostrophic
792 diagnosis of the zonal flow associated with cut-off lows over South Africa and surrounding oceans. Clim.
793 Dyn. 2020.
794 66. Somses, S.; Bopape, M.J.M.; Ndarana, T.; Fridlind, A.; Matsui, T.; Phaduli, E.; Limbo, A.; Maikhudumu, S.;
795 Maisha, R.; Rakate, E. Convection parametrization and multi-nesting dependence of a heavy rainfall event
796 over Namibia with Weather Research and Forecasting (WRF) model. Climate 2020.
797 67. Thorne, V.; Coakeley, P.; Grimes, D.; Dugdale, G. Comparison of TAMSAT and CPC Rainfall
798 Estimates with rainfall, for southern Africa. International Journal of Remote Sensing 2001, 22, 1951–1974.
799 doi:10.1080/01431160118816.
800 68. Syama, S.; Masocha, M.; Dube, T. Evaluation of TAMSAT satellite rainfall estimates for southern
801 Africa: An inter-product comparison study. Physics and Chemistry of the Earth, Parts A/B/C 2019.
802 doi:10.1016/j.pce.2019.02.008.
803 69. Beck, H.; Pan, M.; Roy, T.; Weedon, G.; Pappenberger, F.; van Dijk, A.; Huffman, G.; Adler, R.; Wood, E.
804 Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS. Hydrol.
805 Earth Syst. Sci. 2019, 23, 207–224. doi:10.5194/hess-23-207-2019.
806 70. Bopape, M.J.; Engelbrecht, F.; Randall, D.; Landman, W. Simulations of an isolated two-dimensional
807 thunderstorm: Sensitivity to cloud droplet size and the presence of graupel. Asia-Pac J Atmos Sci 2014, 50.
808 doi:10.1007/s13143-014-0003-z.
809 71. Champion, A.; Hodges, K. Importance of resolution and model configuration when downscaling extreme
810 precipitation. Tellus A 2014, 66. doi:10.3402/tellusa.v66.23993.
Version December 30, 2020 submitted to Climate 34 of 34
72. Medeiros, 811 B.; Hall, A.; Stevens, B. What controls the mean depth of the PBL? Earth Space Sci. 2005,
812 18, 3157–3172.
813 73. Efstathiou, G.A.; Plant, R.S.; Bopape, M.J.M. Simulation of an Evolving Convective Boundary Layer Using
814 a Scale-Dependent Dynamic Smagorinsky Model at Near-Gray-Zone Resolutions. J. Appl. Meteorol. Clim.
815 2018, 57, 2197–2214.
816 74. Bopape, M.J.; Plant, R.; Coceal, O.; Efstathiou, G.; Valdivieso, M. Effects of stability functions in a dynamic
817 model convective boundary layer simulation. Atmospheric Science Letters 2020. doi:10.1002/asl.1008.
818 75. Steeneveld, G.J.; Peerlings, E. Mesoscale Model Simulation of a Severe Summer Thunderstorm in The
819 Netherlands: Performance and Uncertainty Assessment for Parameterised and Resolved Convection.
820 Atmosphere 2020, 11. doi:10.3390/atmos11080811.
821 76. Cintineo, R.; Otkin, J.A.; Xue, M.; Kong, F. Evaluating the Performance of Planetary Boundary Layer
822 and Cloud Microphysical Parameterization Schemes in Convection-Permitting Ensemble Forecasts
823 Using Synthetic GOES-13 Satellite Observations. Monthly Weather Review 2014, 142, 163 – 182.
824 doi:10.1175/MWR-D-13-00143.1.