High Impact Weather Events in Eurasia: Selected, Simulated and Storified

Lead Research Organisation: University of Exeter
Department Name: Mathematics

Abstract

HIWAVES3 facilitates a dialogue between climate modelers, impact modelers and partners in different geographical regions with knowledge of local societal relevant meteorological events to construct stories of selected high-impact extreme events, simulated for present-day and future climate conditions. The story includes the origin of the extreme event from a meteorological perspective, its inter-regional linkages, its predictability, its societal impact and how climate change affects its magnitude and probability. Such stories, made available for schools, the general public and governments, are effective communication means, more so than bare numbers about the expected mean temperature increase, precipitation changes in percentages and such. Based on surveys, extreme summer events with large societal impacts, like droughts and floods, will be selected from the recent past for China, India and Europe. Similar events will be identified in large ensembles of global climate simulations. The size of the ensembles allows an analysis of the inter-regional linkages between the Arctic, the Midlatitudes and the Indian Monsoon region through large-scale Rossby waves and other meteorological factors leading to the extreme, like soil-moisture and sea-surface temperature conditions. In addition, a one in a thousand year event in China, India and Europe, although not witnessed in the recent past, will be analysed. The predictability of the event, weeks to months in advance will be assessed through additional simulations. Using empirical methods and process-based models, the impact on crop yields and economy will be estimated as well as the number of premature deaths. Using large ensembles under projected 2050 conditions the effect of climate change on these extremes and their impacts will be analysed. This research material is translated into powerful stories about concrete events that illustrate how climate affects man, man affects climate, how different geographical regions are connected and how extreme the weather might get. The meteorological data of these events will be made available for further impact studies.

Planned Impact

An essential part of HIWAVES3 is to create powerful stories about selected high-impact extreme events in the regions of interest covered by the partners in the consortium, namely in China, Europe and India. The stories include the origin of the extreme event from a meteorological perspective, its inter-regional linkages, its predictability, its societal impact and how climate change affects its magnitude and probability. We believe that such stories, made available for schools, the general public and governments, are effective communication means, more so than bare numbers about the expected mean temperature increase, precipitation changes in % and such. The scientific knowledge about the high impact extremes will also be communicated to the scientific community through peer-reviewed papers and presentations at conferences. KNMI advices the Dutch government on matters regarding climate change and extreme weather conditions. Results from HIWAVES3 will directly feed into these activities. Digital Explorer will take part in HIWAVES3 to help create the stories and provide tools and templates for the communication of the results to the general public and schools. The communication will be tailored to the culture and national circumstances of the partners. To engage climate data users in HIWAVES3 we plan a survey about high-impact extremes. This survey will contain first examples of real-world and simulated high-impact events and we will ask for feedback on the communication of these results and try to find out what we should do in the second part of the project to better serve the needs of the users that we will identify. Climate data users from the survey will be invited to the mid-term and end-of-term meetings for exchange of knowledge and ideas. KNMI hosts a wealth of model data and real-world data. The datasets from HIWAVES3 will be made available through the KNMI servers using standard protocols.

Publications

10 25 50
 
Description 1) Observations show that reduced regional sea-ice cover is coincident with cold mid-latitude winters on interannual timescales. However, it remains unclear whether these observed links are causal, and model experiments suggest that they might not be. Here we apply two independent approaches to infer causality from observations and climate models and to reconcile these sources of data. Models capture the observed correlations between reduced sea ice and cold mid-latitude winters, but only when reduced sea ice coincides with anomalous heat transfer from the atmosphere to the ocean, implying that the atmosphere is driving the loss. Causal inference from the physics-based approach is corroborated by a lead-lag analysis, showing that circulation-driven temperature anomalies precede, but do not follow, reduced sea ice. Furthermore, no mid-latitude cooling is found in modelling experiments with imposed future sea-ice loss. Our results show robust support for anomalous atmospheric circulation simultaneously driving cold mid-latitude winters and mild Arctic conditions, and reduced sea ice having a minimal influence on severe mid-latitude winters.

2) Whether Arctic amplification has contributed to a wavier circulation and more frequent extreme weather in midlatitudes remains an open question. For two to three decades starting from the mid-1980s, accelerated Arctic warming and a reduced meridional near-surface temperature gradient coincided with a wavier circulation. However, waviness remains largely unchanged in model simulations featuring strong Arctic amplification. Here, we show that the previously reported trend toward a wavier circulation during autumn and winter has reversed in recent years, despite continued Arctic amplification, resulting in negligible multidecadal trends. Models capture the observed correspondence between a reduced temperature gradient and increased waviness on interannual to decadal time scales. However, model experiments in which a reduced temperature gradient is imposed do not feature increased wave amplitude. Our results strongly suggest that the observed and simulated covariability between waviness and temperature gradients on interannual to decadal time scales does not represent a forced response to Arctic amplification.

3) The investigation of risk due to weather and climate events is an example of policy relevant science. Risk is the result of complex interactions between the physical environment (geophysical events or conditions, including but not limited to weather and climate events) and societal factors (vulnerability and exposure). The societal impact of two similar meteorological events at different times or different locations may therefore vary widely. Despite the complex relation between meteorological conditions and impacts most meteorological research is focused on the occurrence or severity of extreme meteorological events, and climate impact research often undersamples climatological natural variability. Here we argue that an approach of ensemble climate-impact modelling is required to adequately investigate the relationship between meteorology and extreme impact events. We demonstrate that extreme weather conditions do not always lead to extreme impacts; in contrast, extreme impacts may result from (coinciding) moderate weather conditions. Explicit modelling of climate impacts, using the complete distribution of weather realisations, is thus necessary to ensure that the most extreme impact events are identified. The approach allows for the investigation of high-impact meteorological conditions and provides higher accuracy for consequent estimates of risk.

4) The growing share of variable renewable energy increases the meteorological sensitivity of power systems. This study investigates if large-scale weather regimes capture the influence of meteorological variability on the European energy sector. For each weather regime, the associated changes to wintertime-mean and extreme-wind and solar power production, temperature-driven energy demand and energy shortfall (residual load) are explored. Days with a blocked circulation pattern, i.e. the 'Scandinavian Blocking' and 'North Atlantic Oscillation negative' regimes, on average have lower than normal renewable power production, higher than normal energy demand and therefore, higher than normal energy shortfall. These average effects hide large variability of energy parameters within each weather regime. Though the risk of extreme high energy shortfall events increases in the two blocked regimes (by a factor of 1.5 and 2.0, respectively), it is shown that such events occur in all regimes. Extreme high energy shortfall events are the result of rare circulation types and smaller-scale features, rather than extreme magnitudes of common large-scale circulation types. In fact, these events resemble each other more strongly than their respective weather regime mean pattern. For (sub-)seasonal forecasting applications weather regimes may be of use for the energy sector. At shorter lead times or for more detailed system analyses, their ineffectiveness at characterising extreme events limits their potential.
Exploitation Route Inform adaptation and mitigation of societal hazards related to extreme weather
Sectors Aerospace, Defence and Marine,Agriculture, Food and Drink,Energy,Environment,Healthcare,Government, Democracy and Justice,Transport

 
Description HIWAVES3 official partners 
Organisation Center for International Climate and Environmental Research - Oslo (CICERO)
Country Norway 
Sector Academic/University 
PI Contribution Providing climate model simulations and expertise in climate extremes
Collaborator Contribution Providing impact modelling and expertise in climate impacts
Impact None to date
Start Year 2016
 
Description HIWAVES3 official partners 
Organisation Chinese Academy of Sciences
Country China 
Sector Public 
PI Contribution Providing climate model simulations and expertise in climate extremes
Collaborator Contribution Providing impact modelling and expertise in climate impacts
Impact None to date
Start Year 2016
 
Description HIWAVES3 official partners 
Organisation Indian Institutes of Technology
Country India 
Sector Academic/University 
PI Contribution Providing climate model simulations and expertise in climate extremes
Collaborator Contribution Providing impact modelling and expertise in climate impacts
Impact None to date
Start Year 2016
 
Description HIWAVES3 official partners 
Organisation Royal Netherlands Meteorological Institute
Country Netherlands 
Sector Academic/University 
PI Contribution Providing climate model simulations and expertise in climate extremes
Collaborator Contribution Providing impact modelling and expertise in climate impacts
Impact None to date
Start Year 2016