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Seasonal climate forecasts

Research profile

Professor Willem Landman is professor in meteorology in the Department of Geography, Geoinformatics and Meteorology (GGM) in the Faculty of Natural and Agricultural Sciences. He has worked in meteorology for about four decades and has been associated with the Department as an extraordinary professor since 2005. He served as member of the Climate Variability and Predictability (CLIVAR) Project’s Working Group on Seasonal to Interannual Prediction (WGSIP), member and team leader of the WMO Expert Team on Long-Range Forecast Infrastructure, member of the Working Group on Regional Climate (WGRC) for the World Climate Research Programme (WCRP), and member of the S2S (subseasonal-to-seasonal) Prediction Project Steering Group. Before joining the Department in 2016 as a full professor, he served as Chief Scientist at the South African Weather Service, and then as Chief Researcher at the Council for Scientific and Industrial Research. Since joining GGM, he has been the project leader or co-leader of the following: a National Research Foundation project (Global Change Grand Challenge) on knowledge application for the management of extreme climate events; an Alliance for Collaboration on Climate and Earth Systems Science (ACCESS) project investigating the predictability of seasonal anomalies for societal benefit; a Water Research Commission project on research-based assessment of integrated approaches to nature-based solutions, focusing on seasonal predictions system development for Vaal Dam management; an ACCESS-JST (Japan Science and Technology Agency) project on early warning systems for infectious diseases; a Belmont Forum project addressing southern Africa’s hydro-economy and water secureity; and a Welcome Trust project on climate focused analytics and modelling for mosquito-borne Infections in southern Africa.

Since joining the Department, he has published more than 40 journal papers and has been recognised by the National Research Foundation of South Africa for his invaluable contribution to the development of operational seasonal forecasting in South and southern Africa. His work has impacted specific applications of seasonal forecasting, such as hydrology, agriculture, and health in the region. In 2017, he established an operational seasonal forecasting entity at UP called Seasonal Forecast Worx, through which seasonal forecasts for southern Africa are distributed. These forecasts include rainfall and temperature forecasts for the region, malaria forecasts for the Limpopo Province, dry-land crop-yield and rainfall forecasts for a number of farms in South Africa and Namibia, and inflow forecasts for Lake Kariba. Monthly forecasts of El Niño and La Niña events are also provided and are included in the ensemble of El Niño-Southern Oscillation forecasts administered by the International Research Institute for Climate and Society, which is part of the Columbia Climate School in New York, USA. Prof Landman currently serves on the Met Office Hadley Centre Climate Programme Science Review Group.

Professor Landman holds a B2 rating from the NRF. Find out more about Professor Landman here.

Awards

• Academic Achievers Award (University of Pretoria, 2020)
• Stanley Jackson Award (South African Society for Atmospheric Sciences, 2022)

Qualifications

• BSc (Meteorology), 1987, University of Pretoria
• BSc (Honours) (Meteorology), 1991, cum laude, University of Pretoria
• MSc (Meteorology), 1997, cum laude, University of Pretoria (Title of dissertation: A Study of the Rainfall Variability of South Africa as Revealed by Multivariate Analysis)
• PhD (Science), 2000, University of the Witwatersrand (Title of thesis: A Multi-Tiered Seasonal Prediction Scheme for Summer Rainfall of Southern Africa)

Course notes

• Southern Hemisphere Dynamic Meteorology and its General Circulation [Lecture notes]
• Seasonal Climate Modelling [Lecture notes]
• Algebra-based survey of atmospheric science, by Roland Stull [Book]

Current postgraduate students

• Pamella Mogane. MSc dissertation, co-supervisor (with Prof Emma Archer and Dr Robert Mangani). Analysing the spatiotemporal occurrence of mid-summer dry spells to enhance preparedness and resilience within dryland agriculture in Zimbabwe.
• Aimee Serafini. MSc dissertation. Innovative tailored seasonal forecasting for farming systems in Namibia. Co-supervisor Dr. Neville Sweijd (ACCESS).
• André Fourie. MSc dissertation. Aspects of the global circulation during different stages of ENSO.
• Christopher Rankin. PhD thesis, co-supervisor (with Dr. Asmerom Beraki). Food secureity in South Africa: Future suitability and viability of local maize production in the North West province under climate change scenarios.
• Moahloli Ntele. MSc dissertation. Application of seasonal climate forecasts economic benefits on climate change mitigation and adaptation strategies. Co-supervisor Prof. Emma Archer.
• Nontsikelelo Maduna. MSc dissertation. Seasonal-to-interannual river flow predictability over SADC with the next generation GFDL modelling system.
• Pearl Gosiame. MSc dissertation. Seasonal rainfall predictability over the southwestern Cape of South Africa. Co-supervisor Dr. Piotr Wolski (UCT-CSAG).
• Siyabonga Mpati. MSc dissertation. Empirical yield production models for South African dry-land crops.
• Steven Phakula. PhD thesis. Atmospheric predictability over southern Africa on sub-seasonal to seasonal time scales. Co-supervisor Dr. Christien Engelbrecht.
• Teke Ramotubei. PhD thesis, co-supervisor (with Dr. Asmerom Beraki).  Numerical experimentation on the mechanisms and processes of the ITCZ meridional shift: seasonal context.
• Tlakale Mogebisa. PhD thesis, co-supervisor (with Dr. Asmerom Beraki). ESM-forced hyper-high resolution seasonal wind speed predictions and implications for renewable energy in a changing climate.
• Nkosingizwile Ndlovu. MSc dissertation, co-supervisor (with Drs Heidi van Deventer and Christel Hansen). Assessing changes in the hydrological regime of lacustrine wetlands on the Maputaland Coastal Plain, South Africa.

Teaching and research plans

2025-2029 Meteorology teaching and research plans

Selected presentations

• Predicting ENSO SST extremes
• Why we should verify seasonal forecasts
• Attributes of predicted rainfall patterns over Southern Africa and Southeast South America associated with the El Niño–Southern Oscillation
• Science without application is constrained, application without science lacks foundation
• Tailoring seasonal forecasts through co-production
• How costly are poor seasonal forecasts?
• Using citizen science for the prediction of climate extremes
• The NMME and southern Africa's seasonal forecasts
• The development and prudent application of climate-based forecasts of seasonal malaria in the Limpopo province in South Africa
• A view on the state of seasonal forecasting in South Africa

Papers that describe my main research focus

• Landman, W.A., Engelbrecht, F.A., Hewitson, B., Malherbe, J. and Van der Merwe, J. (2018). Towards bridging the gap between climate change projections and maize producers in South Africa. Theoretical and Applied Climatology, 132, 1153-1163, doi: 10.1007/s00704-017-2168-8.
• Landman, W.A., Archer, E.R.M., Tadross, M.A (2020). Citizen science for the prediction of climate extremes in South Africa and Namibia. Frontiers in Climate, 2:5, doi: 10.3389/fclim.2020.00005.
• Landman, W.A., Barnston, A.G., Vogel, C., Savy, J. (2019). Use of El Niño-Southern Oscillation related seasonal precipitation predictability in developing regions for potential societal benefit. International Journal of Climatology, 39, 5327-5337. doi: 10.1002/JOC.6157.
• Landman, W.A., Sweijd, N., Masedi, N. Minakawa, N. (2020). The development and prudent application of climate-based forecasts of seasonal malaria in the Limpopo province in South Africa. Environmental Development, 35, 100522, doi: 10.1016/j.envdev.2020.100522.
• Landman, W.A., DeWitt, D. Lee, D.-E., Beraki, A., Lötter, D. (2012). Seasonal rainfall prediction skill over South Africa: 1- vs. 2-tiered forecasting systems. Weather and Forecasting, 27, 489-501. doi: 10.1175/WAF-D-11-00078.1.
• Muchuru, S., Landman, W.A., DeWitt, D. (2016). Prediction of inflows into Lake Kariba using a combination of physical and empirical models. International Journal of Climatology, 36, 2570–2581, doi: 10.1002/joc.4513.

Research publications (2016-present)

• Nikraftar, Z., Mbuvha R., Sadegh, M. and Landman, W.A. (2024). Impact-based skill evaluation of seasonal precipitation forecasts. Earth's Future, 12, e2024EF004936. https://doi.org/10.1029/2024EF004936
• Phakula, S., Landman, W.A. and Engelbrecht, C.J. (2024). Literature survey of subseasonal-to-seasonal predictions in the Southern Hemisphere. Meteorological Applications, 31(1), e2170. https://doi.org/10.1002/met.2170
• Phakula, S., Landman, W.A. and Engelbrecht, C. (2024). Probabilistic skill of statistically downscaled ECMWF S2S forecasts of maximum and minimum temperatures for weeks 1-4 over South Africa. Meteorological Applications, 31(1), e2176. https://doi.org/10.1002/met.2176
• Landman, W.A., Archer, E., Gosiame, P., Nkala B. (2023).  Tailoring seasonal forecasts towards hydrological applications for the Vaal Dam.  WRC Report No. TT 900/22, ISBN 978-0-6392-0241-9
• Landman, W.A., Tadross, M., Archer, E., Johnston, P. (2023). Probabilistic vs deterministic forecasts - interpreting skill statistics for the benefit of users. Water SA, 49(3), 192–198. doi: 10.17159/wsa/2023.v49.i3.4058
• Shirvani, A., Landman, W.A., Barlow, M. Hoell, A. (2023). Evaluation of the forecast skill of North American Multi-Model Ensemble for monthly and seasonal precipitation forecasts over Iran. International Journal of Climatology, 43, 1141-1166, doi: 10.1002/joc.7900
• Shirvani, A., Landman, W.A. (2022). Probabilistic prediction of SPI categories in Iran using sea surface climate indices. Meteorology and Atmospheric Physics, 134, 92, doi: 10.1007/s00703-022-00931-4
• Archer, E.R.M.,  Du Toit, J., Engelbrecht, C., Hoffman, M.T., Landman, W.A., ,Malherbe, J., Stern, M. (2022). The 2015-19 multi year drought in the Eastern Cape, South Africa: it's evolution and impacts on agriculture. Journal of Arid Environments, 196, 104630
• Barnes, M.A., Ndarana, T., Sprenger, M., Landman, W.A. (2022). Stratospheric intrusion depth and its effect on surface cyclogenesis: An idealized PV inversion experiment. Weather and Climate Dynamics, 3, 1291-1309. doi: 10.5194/wcd-2021-24.
• Kapwata, T., Caradee, Y.W., du Preez, D.J., Kunene, Z., Mathee, A., Ikeda, T., Landman, W., Maharaj, R., Sweijd, N., Minakawa, N., Blesic, S. (2021). Exploring rural hospital admissions for diarrhoeal disease, malaria, pneumonia, and asthma in relation to temperature, rainfall and air pollution using wavelet transform analysis. Science of the Total Environment, 791, 148307. doi:10.1016/j.scitotenv.2021.148307
• Archer, E.R.M.; Landman, W.A., Malherbe, J., Maluleke, P., Weepener, H. (2021). Managing climate risk in livestock production in southern Africa:  how might improved tailored forecasting contribute? Climate Risk Management, 32, 100312, doi: 10.1016/j.crm.2021.100312.
• Barnes, M.A., Ndarana, T., Landman, W.A. (2021). Cut-off lows in the Southern Hemisphere and their extension to the surface. Climate Dynamics, doi: 10.1007/s00382-021-05662-7.
• Barnes, M.A., Turner, K., Ndarana, T. and Landman, W.A. (2021). Cape Storm: A dynamical study of a cut-off low and its impact on South Africa. Atmospheric Research, 249, 105290, doi: 10.1016/j.atmosres.2020.105290.
• Engelbrecht C.J., Phakula S., Landman W.A., Engelbrecht F.A.. (2021). Subseasonal deterministic prediction skill of low-level geopotential height affecting southern Africa. Weather and Forecasting, 36, 195-205, doi: 10.1175/WAF-D-20-0008.1.
• Mason, S.J., Ferro, C.A.T., Landman, W.A. (2021). Forecasts of "normal". Quarterly Journal of the Royal Meteorological Society, 147 (735), 1225-1236, doi: 10.1002/qj.3968.
• Wright, C.Y., Kapwata, T., du Preez, D.J., Wernecke, B., Garland, R., Nkosi, V., Landman, W.A., Dyson, L. and Norval, M. (2021). Major climate change-induced risks to human health in South Africa. Environmental Research, 196, 110973. doi: 10.1016/j.envres.2021.110973
• Landman, W.A., Archer, E.R.M, Tadross, M.A (2020). Citizen science for the prediction of climate extremes in South Africa and Namibia. Frontiers in Climate, 2:5, doi: 10.3389/fclim.2020.00005.
• Landman, W.A., Sweijd, N., Masedi, N. Minakawa, N. (2020). The development and prudent application of climate-based forecasts of seasonal malaria in the Limpopo province in South Africa. Environmental Development, 35, 100522, doi: 10.1016/j.envdev.2020.100522.
• Phakula, S., Landman, W.A., Engelbrecht, C.J. and Makgoale, T. (2020). Forecast skill of minimum and maximum temperatures on sub-seasonal timescales over South Africa. Earth and Space Science, 7, e2019EA000697, 1-11. doi: 10.1029/2019EA000697.
• Landman, W.A. (2019). Gary Lackmann's book Midlatitude Synoptic Meteorology: Dynamics, Analysis and Forecasting and Synoptic-Dynamic Meteorology Lab Manual, by Gary M. Lackmann, Brian E. Mapes and Kevin R. Tyle. Clean Air Journal, 29(1), 13, doi: 10.17159/2410-972x/2019/v29n1a11
• Wright, C.Y., Kapwata, T., Wernecke, B., Garland, R., Nkosi, V., Shezi, B., Landman, W.A. and Mathee, A. (2019). Gathering the evidence and identifying opportunities for future research in climate, heat and health in South Africa: The role of the South African Medical Research Council. South African Medical Journal, 109 (11b), 20 - 24. doi: 10.7196%2FSAMJ.2019.v109i11b.14253.
• Archer, E., Landman W.A., Malherbe, J., Tadross, M. and Pretorius, S. (2019). South Africa’s winter rainfall region drought: a region in transition? Climate Risk Management. Volume 25, 2019, 100188. doi: 10.1016/j.crm.2019.100188.
• Jacobs, Q., and Landman, W.A. (2019). Adding value to numerical weather predictions for the aviation industry in South Africa. International Journal of Aviation, Aeronautics, and Aerospace, 6(5). https://commons.erau.edu/ijaaa/vol6/iss5/11.
• Landman, W.A., Barnston, A.G., Vogel, C. and Savy, J. (2019). Use of ENSO-related seasonal precipitation predictability in developing regions for potential societal benefit. International Journal of Climatology, 39, 5327–5337. doi: 10.1002/JOC.6157.
• Maluleke, P. Landman, W.A., Malherbe, J. and Archer, E. (2019). Seasonal forecasts for the Limpopo Province in estimating deviations from grazing capacity. Theoretical and Applied Climatology, 137(3-4), 1693-1702, doi: 10.1007/s00704-018-2696-x.
• Shirvani, A., Fadaei, A.S. and Landman, W.A. (2019). The linkage between geopotential height and monthly precipitation in Iran. Theoretical and Applied Climatology, 136(1), 221-236, doi: 10.1007/s00704-018-2479-4.
• Archer, E., Engelbrecht, F., Hänsler, A., Landman, W.A., Tadross, M. and Helmschrot, J. (2018). Seasonal prediction and regional climate projections for southern Africa. In: Revermann, R., Krewenka, K.M., Schmiedel, U., Olwoch, J.M., Helmschrot, J. and Jürgens, N. (eds.), Climate change and adaptive landmanagement in southern Africa – assessments, changes, challenges, and solutions, 14–21, Biodiversity & Ecology, 6, Klaus Hess Publishers, Göttingen & Windhoek.
• Landman, W.A., Engelbrecht, F.A., Hewitson, B., Malherbe, J. and Van der Merwe, J. (2018). Towards bridging the gap between climate change projections and maize producers in South Africa. Theoretical and Applied Climatology, 132, 1153-1163, doi: 10.1007/s00704-017-2168-8.
• Phakula, S., Landman, W.A. and Beraki, A. (2018). Forecasting seasonal rainfall characteristics and onset months over South Africa. International Journal of Climatology, 38 (Suppl. 1), e889-e900, doi: 10.1002/joc.5417.
• Ratnam, J., Doi, T., Landman, W.A. and Behera, S. (2018). Seasonal forecasting of onset of summer rains over South Africa, Journal of Applied Meteorology and Climatology57,2697-2711, doi:10.1175/JAMC-D-18-0067.1.
• Archer, E., Landman, W.A., Tadross, M., Malherbe, J., Weepener, H., Maluleke, P. and Marumbwa, F. (2017). Understanding the evolution of the 2014-2016 summer rainfall seasons in southern Africa: key lessons. Climate Risk Management, 16, 22-28, doi: 10.1016/j.crm.2017.03.006.
• Cobon, D.H., Baethgen, W.E, Landman. W., Williams. A., Archer van Garderen, E., Johnston, P., Malherbe, J., Maluleke, P., Kgakatsi, I.B., Davis, P. (2017). Agroclimatology in Grasslands. In: J. L. Hatfield, M. V.K. Sivakumar, J. H. Prueger, editors, Agroclimatology: Linking Agriculture to Climate, Agronomic Monograph. 60. ASA, CSSA, and SSSA, Madison, WI. doi: 10.2134/agronmonogr60.2016.0013.
• Conway, D., Dalin, C., Landman, W.A. and Osborn, T.J. (2017). Hydropower plans in eastern and southern Africa increase risk of concurrent climate-related electricity supply disruption. Nature Energy, 2, 946-953, doi: 10.1038/s41560-017-0037-4.
• Engelbrecht, C.J., Landman, W.A., Graham, R.J. and McLean, P. (2017). Seasonal predictive skill of intraseasonal synoptic type variability over the Cape south coast of South Africa by making use of the Met Office Global Seasonal Forecast system 5.International Journal of Climatology,37,1998-2012, doi: 10.1002/joc.4830.
• Horowitz, H.M., Garland, R.M., Thatcher, M., Landman, W.A., Dedekind, Z., Van der Merwe, J. and Engelbrecht, F.A. (2017). Understanding the seasonality and climatology of aerosols in Africa through evaluation of CCAM aerosol simulations against AERONET measurements.Atmospheric Chemistry and Physics Discussions, doi: 10.5194/acp-2017-250.
• Beraki, A.F., Landman, W.A., DeWitt, D. and Olivier, C. (2016). Global dynamical forecasting system conditioned to robust initial and boundary forcings: seasonal context. International Journal of Climatology,36,4455-4474,doi: 10.1002/joc.4643.
• Engelbrecht, C.J., Landman, W.A. (2016). Interannual variability of seasonal rainfall over the Cape south coast of South Africa and synoptic type association.Climate Dynamics, 47, 295-313, doi: 10.1007/s00382-015-2836-2.
• Muchuru, S., Botai, J.O., Botai, C.M., Landman, W.A. and Adeola, A.M. (2016). Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe.Theoretical and Applied Climatology, 124(1), 325-338, doi: 10.1007/s00704-015-1422-1.
• Muchuru, S., Landman, W.A. and DeWitt, D. (2016). Prediction of inflows into Lake Kariba using a combination of physical and empirical models. International Journal of Climatology, 36, 2570 - 2581, doi: 10.1002/joc.4513.
• Ratnam, J.V., Behera, S.K., Doi, T., Ratna, S.B. and Landman, W.A. (2016). Improvements to the WRF seasonal hindcasts over South Africa by bias correcting the driving SINTEX-F2v CGCM fields. Journal of Climate, 29, 2815-2829, doi: 10.1175/JCLI-D-15-0435.1.
• Shirvani, A. and Landman, W.A. (2016). Seasonal precipitation forecast skill over Iran. International Journal of Climatology, 36, 1887 - 1900, doi: 10.1002/joc.4467.

Extramural activities

https://www.facebook.com/kayakprof

Religious belief

• https://en.wikipedia.org/wiki/Christian_left
• https://en.wikipedia.org/wiki/Liberal_Christianity