Last update: Jul 2020
Karin van der Wiel
www.karinvanderwiel.nl | firstname.lastname@example.org | +31 (0)30 2206 783
Hi, I'm Karin.
I work as a scientist at the Royal Netherlands Meteorological Institute (KNMI), in the R&D weather and climate modelling department.
My research focuses on extreme weather and climate events, and how these influence society or ecosystems. For example, extreme precipitation events and consequent flooding, or the sensitivity of renewable power systems to meteorological variability. Furthermore, I am involved in making the next generation of KNMI climate scenarios for the Netherlands (to be published in 2021 and 2023).
With my work I hope to contribute to increasing our understanding of Earth’s weather and climate in a way that is useful for society.
Please be in contact with any questions, requests for PDFs of publications or anything else. Thank you for visiting!
Van der Wiel et al., 2018: 100-year Lower Mississippi floods in a global climate model: characteristics and future changes
Van Oldenborgh et al., 2017: Attribution of extreme rainfall from Hurricane Harvey, August 2017
Van der Wiel et al., 2017: Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change.
→ See also the FAQs prepared for broad interest
Van der Wiel et al., 2016: The resolution dependence of contiguous U.S. precipitation extremes in response to CO2 forcing.
Extreme precipitation, very heavy rainfall, can occur on a whole range of time scales and may be the result of various meteorological conditions. Depending on local land conditions and land-atmosphere interactions, these heavy rain conditions may lead to flooding and therewith increase societal risks. From physical principles, related to the amount of water vapour air can hold, we expect extreme precipitation events to become more intense with global climate change.
At NOAA GFDL we investigated how precipitation extremes are represented in various GFDL global climate models of different horizontal resolution. Increased resolution improves the quality of simulated extremes: precipitation intensity, spatial patterns and seasonality. We further showed that the climate change projections depend on model resolution, adding uncertainty to existing estimates from -generally- relatively low resolution models. It is difficult to identify trends in the observed record due to large internal variability.
The GFDL climate model includes as the first global GCM a river routing model. In a follow-up study we used this feature to identify the atmospheric and land processes that lead to extreme high river discharge. In the model extreme Lower Mississippi floods are caused by a combination of high snow melt and precipitation. Maybe due to opposite trends in these two variables, the model does not show increases or decreases in flood likelihood.
For the heavy rainfall event in southern Louisiana of August 2016, that resulted in devastating flooding, I was part of a team of WWA-scientists who investigated the climatological statistics of this event. The results of our rapid attribution were reported by various media. A selection: EN: NOAA, New York Times, Washington Post, CNN, Associated Press, USA Today, The Guardian (1), The Guardian (2), TIME, Rolling Stone, climate.gov, WIRED, NationSwell, The Times Picayune, Inside Climate News, Climate Central, Science Museum of Virginia, NL: KNMI.
A similar attribution analysis was performed for the extreme rainfall from Hurricane Harvey, August 2017 in Houston, TX, USA. These results were reported in, among others: EN: Washington Post, New York Times, The Guardian, Daily Mail, Associated Press, AGU, National Geographic, CarbonBrief, Popular Science, Delta, Futurity, NL: KNMI. At the 2017 AGU fall meeting I participated in a press conference discussing this paper: video.
|lvi.||M Kolbe, et al.: Impact of Atmospheric Rivers on Future Poleward Moisture Transport and Arctic Climate in EC-Earth2. Journal of Geophysical Research - Atmospheres.|
|lv.||L Muntjewerf, R Bintanja, T Reerink, K van der Wiel (2023): The KNMI Large Ensemble Time Slice (KNMI–LENTIS). Geoscientific Model Development, 16, pp. 4581-4597. |
|liv.||WCH Chan, NW Arnell, G Darch, K Facer-Childs, TG Shepherd, M Tanguy, K van der Wiel (2023): Current and future risk of unprecedented hydrological droughts in Great Britain. Journal of Hydrology, 625, pp. 130074. |
|liii.||H Goulart, K van der Wiel, C Folberth, E Boere, B van den Hurk (2023): Increase of simultaneous soybean failures due to climate change. Earth's Future, 11, pp. e2022EF003106. |
|lii.||E Tschumi, S Lienert, A Bastos, P Ciais, K Gregor, F Joos, J Knauer, P Papastefanou, A Rahmig, K van der Wiel, K Williams, Y Xu, S Zähle, J Zscheischler (2023): Large variability in simulated response of vegetation composition and carbon dynamics to variations in drought-heat occurrence. Journal of Geophysical Research: Biogeosciences, 128, pp. e2022JG007332. |
|li.||G Lenderink, H de Vries, E van Meijgaard, K van der Wiel, F Selten (2023): A perfect model study on the reliability of the added small-scale information in regional climate change projections. Climate Dynamics, 60, pp. 2563-2579. |
|l.||SM Hauswirth, K van der Wiel, MFP Bierkens, V Beijk, N Wanders (2023): Simulating hydrological extremes for different warming levels–combining large scale climate ensembles with local observation based machine learning models. Frontiers in Water, 5, pp. 11008108. |
|xlix.||K van der Wiel, TJ Batelaan, N Wanders (2023): Large increases of multi-year droughts in north-western Europe in a warmer climate. Climate Dynamics, 60, pp. 1781–1800. |
|xlviii.||SJ Bakke, N Wanders, K van der Wiel, LM Tallaksen (2023): A data-driven model for Fennoscandian wildfire danger. Natural Hazards and Earth System Sciences, 23, pp. 65-89. |
|xlvii.||H de Vries, G Lenderink, K van der Wiel, E van Meijgaard (2022): Quantifying the role of the large‑scale circulation on European summer precipitation change. Climate Dynamics, 59, pp. 2871-2886. |
|xlvi.||L van der Most, K van der Wiel, RMJ Benders, PW Gerbens-Leenes, P Kerkmans, R Bintanja (2022): Extreme Events in the European Renewable Power System: Validation of a Modeling Framework to Estimate Renewable Electricity Production and Demand from Meteorological Data. Renewable and Sustainable Energy Reviews, 170, pp. 112987. |
|xlv.||T Zhang, K van der Wiel, T Wei, J Screen, X Yue, B Zheng, F Selten, R Bintanja, W Anderson, R Blackport, S Glomsrod, Y Liu, X Cui, X Yang, (2022): Increased wheat price spikes and larger economic inequality with 2°C global warming. One Earth, 5, pp. 907-916. |
|xliv.||MT Craig, J Wohland, LP Stoop, A Kies, B Pickering, HC Bloomfield, J Browell, M de Felice, CJ Dent, A Deroubaix, F Frischmuth, PLM Gonzalez, A Grochowicz, K Gruber, P Hartel, M Kittel, L Kotzur, I Labuhn, JK Lundquist, N Pflugradt, K van der Wiel, M Zeyringer, DJ Brayshaw (2022): Overcoming the disconnect between energy system and climate modelling. Joule, 6, pp. 1405-1417. |
|xliii.||E Tschumi, S Lienert, K van der Wiel, F Koos, J Zschleischler (2022): A climate database with varying drought-heat signatures for climate impact modelling. Geoscience Data Journal, 9, pp. 154-166. |
|xlii.||N Bloemendaal, H de Moel, AB Martinez, S Muis, ID Haigh, K van der Wiel, RJ Haarsma, PJ Ward, MJ Roberts, JCM Dullaart, JCJH Aerts (2022): A globally consistent local-scale assessment of future tropical cyclone risk. Science advances, 8, pp. eabm8438. |
|xli.||Y Boulaguiem, J Zschleischler, E Vignotto, K van der Wiel, S Engelke (2022): Modeling and simulating spatial extremes by combining extreme value theory with generative adversarial networks. Environmental Data Science, 1, pp. 1-18. |
|xl.||E Tschumi, S Lienert, K van der Wiel, F Koos, J Zschleischler (2022): The effects of varying drought-heat signatures on terrestrial carbon dynamics and vegetation composition. Biogeosciences, 19, pp. 1979-1993. |
|xxxix.||T Kelder, N Wanders, K van der Wiel, TI Marjoribanks, LJ Slater, RI Wilby, C Prudhomme (2022): Interpreting extreme climate impacts from large ensemble simulations—are they unseen or unrealistic?. Environmental Research Letters, 17, pp. 044052. |
|xxxviii.|| H Goulart, K van der Wiel, C Folberth, J Balkovic, B van den Hurk (2021): Weather-induced crop failure events under climate change: a storyline approach. Earth System Dynamics, 12, pp. 1503-1527. |
|xxxvii.||E Bevacqua, C De Michele, C Manning, A Couasnon, AFS Ribeiro, AM Ramos, E Vignotto, A Bastos, S Blesić, F Durante, J Hillier, SC Oliveira, JG Pinto, E Ragno, P Rivoire, K Saunders, K van der Wiel, W Wu, T Zhang, J Zscheischler (2021): Guidelines for studying diverse types of compound weather and climate events. Earth's Future, 9, pp. e2021EF002340. |
|xxxvi.||K van der Wiel, G Lenderink, H de Vries (2021): Physical storylines of future European drought events like 2018 based on ensemble climate modelling. Weather and Climate Extremes, 33, pp. 100350. |
|xxxv.||R Sperna Weiland, K van der Wiel, FM Selten, D Coumou (2021): Intransitive atmosphere dynamics leading to persistent hot-dry or cold-wet European summers. Journal of Climate, 34, pp. 6303-6317. |
|xxxiv.||GJ van Oldenborgh, K van der Wiel, S Kew, S Philip, F Otto, R Vautard, A King, F Lott, J Arrighi, R Singh, M van Aalst (2021): Pathways and pitfalls in extreme event attribution. Climatic Change, 166, pp. 13. |
|xxxiii.||G van Kempen, K van der Wiel, LA Melsen (2021): The impact of hydrological model structure on the simulation of extreme runoff events. Natural Hazards and Earth System Sciences, 21, pp. 961-976. |
|xxxii.||J Vogel, P Rivoire, C Deidda, L Rahimi, CA Sauter, E Tschumi, K van der Wiel, T Zhang, J Zschleischler (2021): Identifying meteorological drivers of extreme impacts: an application to simulated crop yields. Earth System Dynamics, 12, pp. 151-172. |
|xxxi.||PNJ Bonekamp, N Wanders, K van der Wiel, AF Lutz, WW Immerzeel (2021): Using large ensemble modelling to derive future changes in mountain specific climate indicators in a 2 °C and 3 °C warmer world in High Mountain Asia. International Journal of Climatology, 41, pp. E964-E979. |
|xxx.||SF Kew, SY Philip, M Hauser, M Hobbins, N Wanders, GJ van Oldenborgh, K van der Wiel, TIE Veldkamp, J Kimutai, C Funk, FEL Otto (2021): Impact of precipitation and increasing temperatures on drought in eastern Africa. Earth System Dynamics, 12, pp. 17-35. |
|xxix.||K van der Wiel, R Bintanja (2021): Contribution of climatic changes in mean and variability to monthly temperature and precipitation extremes. Communications Earth and Environment, 2, pp. 1-11. |
|xxviii.||S Vijverberg, M Schmeits, K van der Wiel, D Coumou (2020): Sub-seasonal statistical forecasts of eastern United States hot temperature events. Monthly Weather Review, 148, pp. 4799-4822. |
|xxvii.||SY Philip, SF Kew, GJ van Oldenborgh, F Otto, R Vautard, K van der Wiel, A King, F Lott, J Arrighi, R Singh, M van Aalst (2020): A protocol for probabilistic extreme event attribution analyses. Advances in Statistical Climatology, Meteorology and Oceanography, 6, pp. 177-203. |
|xxvi.|| JR Brown, M Lengaigne, BR Lintner, MJ Widlansky, K van der Wiel, C Dutheil, BK Linsley, AJ Matthews, J Renwick (2020): South Pacific Convergence Zone dynamics, variability, and impacts in a changing climate. Nature Reviews Earth & Environment, 1, pp. 530-543. |
|xxv.||SY Philip, SF Kew, K van der Wiel, N Wanders, GJ van Oldenborgh (2020): Regional differentiation in climate change induced drought trends in the Netherlands. Environmental Research Letters, 15, pp. 094081. |
|xxiv.||Nanditha JS, K van der Wiel, U Bhatia, D Stone, FM Selten, V Mishra (2020): A seven-fold rise in the probability of exceeding the observed hottest summer in India in a 2°C warmer world. Environmental Research Letters, 15, pp. 044028. |
|xxiii.||K van der Wiel, FM Selten, R Bintanja, R Blackport, JA Screen (2020): Ensemble climate-impact modelling: extreme impacts from moderate meteorological conditions. Environmental Research Letters, 15, pp. 034050. |
|xxii.||R Bintanja, K van der Wiel, EC van der Linden, J Reusen, L Bogerd, F Krikken, FM Selten (2020): Strong future increases in Arctic precipitation variability linked to poleward moisture transport. Science Advances, 6, pp. eaax6869. |
|xxi.||A Sebastian, A Gori, RB Blessing, K van der Wiel and B Bass (2019): Disentangling the impacts of human and environmental change on catchment response during Hurricane Harvey. Environmental Research Letters, 14, pp. 124023. |
|xx.||GA Vecchi, T Delworth, H Murakami, SD Underwood, AT Wittenberg, F Zeng, W Zhang, J Baldwin, K Bhatia, W Cooke, J He, SB Kapnick, T Knutson, G Villarini, K van der Wiel, W Anderson, V Balaji, J-H Chen, K Dixon, R Gudgel, L Harris, L Jia, NC Johnson, S-J Lin, M Liu, J Ng, A Rosati, J Smith, X Yang (2019): Tropical cyclone sensitivities to CO2 doubling: Roles of atmospheric resolution, synoptic variability and background climate changes. Climate Dynamics, 53, pp. 5999–6033. |
|xix.||K van der Wiel, HC Bloomfield, RW Lee, LP Stoop, R Blackport, JA Screen, FM Selten (2019): The influence of weather regimes on European renewable energy production and demand. Environmental Research Letters, 14, pp. 094010. |
|xviii.||R Blackport, JA Screen, K van der Wiel, R Bintanja (2019): Minimal influence of reduced Arctic sea ice on coincident cold winters in mid-latitudes. Nature Climate Change, 9, pp. 697-704. |
|xvii.||K van der Wiel, LP Stoop, BRH van Zuijlen, R Blackport, MA van den Broek, FM Selten (2019): Meteorological conditions leading to extreme low variable renewable energy production and extreme high energy shortfall. Renewable and Sustainable Energy Reviews, 111, pp. 261-275. |
|xvi.||K van der Wiel, N Wanders, FM Selten, MFP Bierkens (2019): Added value of large ensemble simulations for assessing extreme river discharge in a 2 °C warmer world. Geophysical Research Letters, 46, pp. 2093-2102. |
|xv.||S Philip, S Sparrow, SF Kew, K van der Wiel, N Wanders, R Singh, A Hassan, K Mohammed, H Javid, K Haustein, FEL Otto, F Hirpa, RH Rimi, AKM Saiful Islam, DCH Wallom, and GJ van Oldenborgh (2019): Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives. Hydrology and Earth System Sciences, 23, pp. 1409-1429. Highlighted article. |
|xiv.||K van der Wiel, SB Kapnick, GA Vecchi, JA Smith, PCD Milly, L Jia (2018): 100-year Lower Mississippi floods in a global climate model: characteristics and future changes. Journal of Hydrometeorology, 19, pp. 1547-1563. |
|xiii.||L Krishnamurthy, GA Vecchi, X Yang, K van der Wiel, V Balaji, SB Kapnick, L Jia, F Zeng, K Paffendorf, S Underwood (2018): Causes and probability of occurrence of extreme precipitation events like Chennai 2015. Journal of Climate, 31, pp. 3831–3848. |
|xii.||FEL Otto, K van der Wiel, GJ van Oldenborgh, S Philip, S Kew, P Uhe, H Cullen (2018): Climate change increases the probability of heavy rains in Northern England/Southern Scotland like those of storm Desmond - a real-time event attribution revisited. Environmental Research Letters, 13, pp. 024006. |
|xi.|| GJ van Oldenborgh, K van der Wiel, A Sebastian, R Singh, J Arrighi, FEL Otto, K Haustein, S Li, GA Vecchi, H Cullen (2017): Attribution of extreme rainfall from Hurricane Harvey, August 2017. Environmental Research Letters, 12, pp. 124009. Featured article. |
|x.||K van der Wiel, ST Gille, SG Llewellyn Smith, PF Linden, C Cenedese (2017): Characteristics of colliding sea breeze gravity current fronts: a laboratory study. Quarterly Journal of the Royal Meteorological Society, 143, pp. 1434-1441. |
|ix.||K van der Wiel, SB Kapnick, GJ van Oldenborgh, K Whan, S Philip, GA Vecchi, RK Singh, J Arrighi, H Cullen (2017): Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change. Hydrology and Earth System Sciences, 21, pp. 897-921. Highlighted article. |
|viii.||K van der Wiel, SB Kapnick, GA Vecchi (2017): Shifting patterns of mild weather in response to projected radiative forcing. Climatic Change, 140, pp. 649-658. |
|vii.||K van der Wiel, SB Kapnick, GA Vecchi, WF Cooke, TL Delworth, L Jia, H Murakami, S Underwood, F Zeng (2016): The resolution dependence of contiguous U.S. precipitation extremes in response to CO2 forcing. Journal of Climate, 29, pp. 7991-8012. |
|vi.||MA Stiller-Reeve, C Heuzé, WT Ball, RH White, G Messori, K van der Wiel, I Medhaug, AH Eckes, A O'Callaghan, MJ Newland, SR Williams, M Kasoar, HE Wittmeier and V Kumer (2016): Improving together: better science writing through peer learning. Hydrology and Earth System Science, 20, pp. 2965-2973. |
|v.||K van der Wiel, AJ Matthews, MM Joshi, DP Stevens (2016): The influence of diabatic heating in the South Pacific Convergence Zone on Rossby wave propagation and the mean flow. Quarterly Journal of the Royal Meteorological Society, 142, pp. 901-910. |
|iv.||K van der Wiel, AJ Matthews, MM Joshi, DP Stevens (2016): Why the South Pacific Convergence Zone is diagonal. Climate Dynamics, 46, pp. 1683-1698. |
|iii.||K van der Wiel, AJ Matthews, DP Stevens, MM Joshi (2015): A dynamical framework for the origin of the diagonal South Pacific and South Atlantic Convergence Zones. Quarterly Journal of the Royal Meteorological Society, 141, pp. 1997-2010. Featured article. |
|ii.||MM Joshi, M Stringer, K van der Wiel, A O'Callaghan, S Fueglistaler (2015): IGCM4: A fast, parallel and flexible intermediate climate model. Geoscientific Model Development, 8, pp. 1157-1167. |
|i.||W Hazeleger, X Wang, C Severijns, S Ştefănescu, R Bintanja, A Sterl, K Wyser, T Semmler, S Yang, B van den Hurk, T van Noije, E van der Linden, K van der Wiel (2012): EC-Earth V2.2: description and validation of a new seamless earth system prediction model. Climate Dynamics, 39, pp. 2611-2629. |
A pdf-version of my C.V. is available here.
Dr Karin van der Wiel
Royal Netherlands Meteorological InstitutePostbus 2013730 AE De BiltNetherlands
+31 (0)30 2206 783 ← Temporarily working from home, hence no office phone.E-mail: email@example.com