Publications

Academic papers

• Veldkamp, S, Whan, K., Dirksen, S., and Schmeits, M. 2020. Statistical post-processing of wind speed forecasts using convolutional neural networks. Monthly Weather Review (submitted). Link to arxiv
• Vannitsem, S. et al. 2020. Statistical Postprocessing for Weather Forecasts — Review, Challenges and Avenues in a Big Data World. BAMS (submitted).
• van Straaten, C., Whan, K., Coumou, D., van den Hurk, B., and Schmeits, M. 2020. The influence of aggregation and statistical post-processing on the sub-seasonal predictability of European temperatures. QJRMS (accepted).
• Whan, K., Sillmann, J., Schaller, N. and Haarsma, R. 2020. Future changes in atmospheric rivers and extreme precipitation in Norway. Climate Dynamics. https://doi.org/10.1007/s00382-019-05099-z
• Bakker, K., Whan, K., Knap, W., and Schmeits, M. 2019. Comparison of statistical post-processing methods for probabilistic NWP forecasts of solar radiation. Solar Energy, 191, 138-150. DOI: 10.1016/j.solener.2019.08.044.
• Nur Ratri, D., Whan, K., and Schmeits, M. 2019. A comparative verification of raw and bias-corrected ECMWF seasonal ensemble precipitation reforecasts in Java (Indonesia). Journal of Applied Meteorology and Climatology.
• van Straaten, C., Whan, K., and Schmeits, M. 2018. Statistical post-processing and multivariate structuring of high-resolution ensemble precipitation forecasts. Journal of Hydrometerology., DOI: 10.1175/JHM-D-18-0105.1
• Rahimi, M., Mohammadian, N., Vanashi, AR. and Whan, K. 2018. Trends in Indices of Extreme Temperature and Precipitation in Iran over the Period 1960-2014. Open Journal of Ecology, 8 (07), 396. DOI: 10.4236/oje.2018.87024.
• Whan, K., and Schmeits, M. 2018. Comparing area-probability forecasts of (extreme) local precipitation using parametric and machine learning statistical post-processing methods. Monthly Weather Review. DOI: 10.1175/MWR-D-17-0290.1. 
• Drake, J., Patti, A.F., Whan, K., Jackson, W.R. and Cavagnaro, T.R. 2018. Can we maintain productivity on broad acre dairy farms during early stage transition from mineral to compost fertilisation? Agriculture, Ecosystems & Environment. DOI: 10.1016/j.agee.2017.12.022.
• Philip, S., Kew, S., Hauser, M., Guillod, B., Teuling, A., Whan, K., Uhe, P. and Van Oldenborgh, GJ. 2017. Western US high June 2015 temperatures and their relation to global warming and soil moisture. Climate Dynamics, 1-15. DOI: 10.1007/s00382-017-3759-x
• van der Wiel, K., Kapnick, S. B., van Oldenborgh, G. J., Whan, K., Philip, S., Vecchi., G. A., Singh, R. K., Arrighi, J. and Cullen, H. 2017. Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change. Hydrology and Earth System Sciences Discussions. DOI: 10.5194/hess-2016-448
• Teufel, B., Diro, G.T., Whan, K., Milrad, S., Jeong, D. I., Ganji, A., Huziy, O., Winger., K., Gyakum, J. R.,  de Elia, R., Zwiers, F. and Sushama, L. 2016. Investigation of the 2013 Alberta flood from weather and climate perspectives. Climate Dynamics. DOI: 10.1007/s00382-016-3229-8
• Whan, K. and Zwiers, F. 2016. The impact of ENSO and the NAO on extreme winter precipitation in North America in observations and regional climate models, Climate Dynamics. DOI: 10.1007/s00382-016-3148-x
• Whan, K., Zwiers, F.  and Sillmann, J. 2016. The influence of atmospheric blocking on extreme winter minimum temperatures in North America, Journal of Climate. DOI: 10.1175/JCLI-D-15-0493.1.
• Curry, C., Tencer, B., Whan, K., Weaver, A., Giguere, M. and Wiebe, E. 2016. Searching for added value in simulating climate extremes with a high-resolution regional climate model over Western Canada. Atmosphere-Ocean, DOI:10.1080/07055900.2016.1158146
• Curry, C., Tencer, B., Whan, K., Weaver, A., Giguere, M. and Wiebe, E. 2016. Searching for added value in simulating climate extremes with a high-resolution regional climate model over Western Canada. II. Basin-scale results. Atmosphere-Ocean, DOI:10.1080/07055900.2016.1215287
• Whan, K. and Zwiers, F. 2015. Evaluation of extreme rainfall and temperature over North America in CanRCM4 and CRCM5. Climate Dynamics, DOI: 10.1007/s00382-015-2807-8.
• Whan, K., Zscheischler, J.,  Orth, R.,  Shongwe, M., Rahimi., M., Asare, E. and  Seneviratne, S.I. 2015. Impact of soil moisture on extreme maximum temperatures in Europe, Weather and Climate Extremes
• Whan, K., L. Alexander, A. Imielska, S. McGree, D. Jones, E. Ene, S. Finaulahi, K. Inape, L. Jacklick, R. Kumar, V. Laurent, H. Malala, P. Malsale, R. Mitiepo, M. Ngemaes, A. Peltier, A. Porteous, S. Seuseu, E. Skilling, L. Tahani, U. Toorua and M. Vaiimene 2013. Trends and variability of temperature extremes in the tropical Western Pacific, International Journal of Climatology, 34, 8, 2585–2603
• McGree, S., K. Whan, D. Jones, A. Imielska, L. Alexander, H. Diamond, E. Ene, S. Finaulahi, K. Inape, L. Jacklick, R. Kumar, V. Laurent, H. Malala, P. Malsale, R. Mitiepo, T. Moniz, M. Ngemaes, A. Peltier, A. Porteous, S. Seuseu, E. Skilling, L. Tahani, F. Teimitsi, U. Toorua and M. Vaiimene 2013. An updated Assessment of Trends and Variability in total and extreme rainfall in the tropical Western Pacific, International Journal of Climatology, 34, 8, 2775–2791
  
• Whan, K., B. Timbal and J. Lindesay, 2013. Linear and nonlinear statistical analysis of the impact of sub-tropical ridge intensity and position on south-east Australian rainfall, International Journal of Climatology, 34, 2, 326–342. DOI: 10.1002/job.3689

Student projects

• Jieyu Chen (2020, UU): Quality control of wind observations from citizen science stations. Co-supervised with Dr Jason Frank (UU) and Dr Kate Saunders (TU Delft).
• Simon Veldkamp (2019, UU): Statistical Post-processing of wind speed forecasts using convolutional neural networks. Co-supervised with Dr Sjoerd Dirksen (UU) and Dr Maurice Schmeits (KNMI). 
• Edward Groot (2019, UU): Probabilistic thunderstorm forecasts using statistical post-processing: Comparison of logistic regression and quantile regression forests and an investigation of physical predictors. Co-supervised with Dr Willem Jan van de Berg (UU) and Dr Maurice Schmeits (KNMI). 
• Daan van Dijk (2019, TU Delft): Road temperatures with random forests. Co-supervised with Marcel Molendijk (KNMI). 
• Kilian Bakker (2018, UU): Improving solar radiation forecasts using advanced statistical post-processing methods. Published paper. Co-supervised with Dr Jason Frank (UU), Dr Maurice Schmeits (KNMI), and Dr Wouter Knap (KNMI).
• Eleftherios Ioannidis (2018): Probabilistic wind speed forecasting using parametric and non-parametric statistical post-processing methods.  Co-supervised with Dr Maurice Schmeits (KNMI). 
• Romà Domènech Masana (2017, Radboud) : Improving the GLAMEPS wind speed forecasts using a machine learning technique. Co-supervised with Dr Eric Cator (Radboud) and Dr Maurice Schmeits (KNMI). 
• Chiem van Straaten (2017, UU): Statistical Post-processing and Multivariate Structuring of High-Resolution Ensemble Precipitation Forecasts. Co-supervised with Dr Maurice Schmeits (KNMI). 

Technical reports

• Timbal, B., K. Whan and M. Raupach 2009. Climate change influence of changes in evapotranspiration, runoff and drainage across SEA, through both physical and ecological processes. Final Report for Project 1.3.1P. South Eastern Australian Climate initiative.
• Timbal, B., J. Arblaster, K. Braganza, E. Fernandez, H. Hendon, B. Murphy, M. Raupach, C. Rakich, I. Smith, K. Whan and M. Wheeler 2010. Understanding the anthropogenic nature of the observed rainfall decline across South Eastern Australia. The CAWCR – Bureau of Meteorology Contribution to SEACI -1 Theme 1 From January 2006 to June 2009. Melbourne: SEACI.

Internal presentations

• Statistical Post-Processing workshop – TU Delft 2019 – Using random forests and the Schaake Shuffle to make probabilistic forecasts of extreme precipitation from deterministic Harmonie output.

• Canadian Network for Regional Climate and Weather Processes – Evaluation of regional climate models: extreme indices, statistical extremes and relationships with circulation
• Canadian Network for Regional Climate and Weather Processes – Analysis of Extremes in Regional Models
• Introduction to climate extremes and indices – Noumea workshop for PACCSAP
• Climate extremes lecture – PadClim workshop for PACCSAP
• South-east Australian Climate Initiative
• The Fenner School of Environment and Society

Conference attendance

• 8th European Windstorm Workshop (Birmingham) – 2019: Probabilistic wind speed forecasting using parametric and non-parametric statistical post-processing methods
• European Geosciences Union (EGU) – 2017:  Probabilistic forecasts of extreme local precipitation using HARMONIE predictors and comparing 3 different post-processing methods
• European Geosciences Union (EGU) – 2017: Atmospheric rivers and extreme precipitation in Norway
• European Geosciences Union (EGU) – 2016: The influence of atmospheric blocking on extreme winter minimum temperatures in North America
• The Canadian Meteorological Society Annual Meeting (CMOS) – 2014
• The American Meteorological Society Annual Meeting (AMS) – 2013
• The Australian Meteorological and Oceanographic Society Annual Meeting (AMOS) – 2008, 2012, 2013
• International Conference on Southern Hemisphere Meteorology and Oceanography (ICSHMO) – 2009, 2012
• Climate Change Beijing – 2011
• The Australian-New Zealand Climate Forum (ANZCF) – 2010
• The American Geophysical Union Fall Meeting (AGU) – 2010

PhD Thesis

• Interactions between large-scale modes of climate and their relationship with Australian climate and hydrology (ANU)