An extreme weather event means that an observed value of a weather variable falls above or below an upper or lower threshold within a range of observed values for a region. The Intergovernmental Panel on Climate Change (IPCC) suggests using a threshold respresenting the bottom 10% or top 10% of severity for a given event type in a given location for climate research (IPCC, 2012). That means an extreme weather event at one location may be a normal event at another location. Based on analysis of surface temperature, gust wind speed, and precipitation, the weather during the Tragedy Hours is found to qualify as an extreme cold event and an extreme high gust wind speed event.
High-impact weather events have never been precisely defined. They are normally perceived as events having major effects on society and economy, such as severe thunderstorms, tropical cyclones, and heatwaves. However, it is hard to measure the effects on society and economy because both depend on human activity. It is likely that a non-severe weather event causes a major effect on society. As an example, a light rain event during National Day marching activities with the participation of around 10 000 people is a high-impact weather event. With 21 deaths, there is no doubt that the weather on the Tragedy Day is considered a high-impact weather event. But if there were no race, it would not have been high-impact weather. So, an extreme weather event does not have to be a high-impact weather event, and a normal weather event might be an extreme weather event.
Defining the weather event on 22 May as high-impact weather or extreme weather is not the key point of this study. The ECMWF deterministic forecast with lead time of 30 hours correctly predicted the time and location of the cold front and its associated low temperature, high gust wind speed, and light precipitation. However, tragedy still occurred. Therefore, the key question is: What lessons have we learned from this tragedy?
1) In addition to standard weather forecasts, hazard and impact forecasts of high-impact weather should be developed in order to reduce loss of life risks.
One may ask why the model forecast information was not utilized to warn the race organizers and runners. To answer that question, it is helpful to recognize that a high-quality weather service should be tailored to different users based on their specific needs. In this case, warnings were issued only regarding weather, which apparently did not translate into a warning of potential risks to organizers and runners. Hazard and impact forecasts, in addition to the weather forecast, would have been useful in preventing the tragedy. What the organizers and runners really needed was a hypothermia risk forecast at the race site for a particularly short time period. Currently in China, hypothermia risk is not the service responsibility of the local weather forecasting agencies. With more and more people being involved in the Ultramarathon in China, the market might stimulate private enterprises to make hazard and impact forecasts in the future. It is also suggested that the government should enact rules requiring marathon organizers to obtain and secure specialized forecast services and products from the local weather forecasting agencies.
2) Probability forecasts can provide valuable information and hence should be issued by government weather agencies and communicated well to the public.
About ten years ago, probability weather forecasts first appeared in China, but it was difficult for the government and public to accept it because probabilistic forecasts were perceived as imprecise. Even with recent advances in numerical weather prediction, the accuracy of deterministic forecasts can still vary a lot from day to day due to atmospheric predictability limits. Therefore, a deterministic forecast alone can not provide adequate information for planning and decision making. In this tragedy case, the deterministic forecast and at least half of the ensemble members produced high wind speed forecasts 10 days prior to the event. Simply put, there was greater than a 50% risk of high wind speed, and the organizers should have had enough time to prepare for the risk if the forecast and its probability had been delivered to the end-user. Even if the message of the 50% risk of low temperature and high wind speed were delivered to the runners just one day before the event, most of them would have worn jackets.
3) Knowledge of how to evaluate the impact of weather should be delivered to public.
Although high-impact weather normally refers to severe weather, non-severe weather can become high-impact weather when certain human outdoor activities are involved. Runners in shorts and vests are vulnerable to low temperatures, which in this case were exasperated by high wind speeds and precipitation. In this case, the organizers and most of the runners were not aware of the high wind speed warning and the precipitation forecast. It should be pointed out that there were 4–5 runners who had passed the CP2–CP3 segment successfully that day because they had brought outdoor jackets to keep them warm. Different people may evaluate the impact or risk of weather at different levels. If the organizers (or runners) had been able to make the right impact evaluation and prepared the runners (or themselves) for the extreme weather, the tragedy would have been prevented.
How to increase the value of weather forecasts to provide better service to users and to prevent weather-related disasters is a great challenge. To meet this challenge, the World Meteorological Organization (WMO) World Weather Research Program (WWRP) launched a 10-year international high-impact weather (HIWeather) project in 2016.
The HIWeather project is guided by the idea of an end-to-end approach for the provision and improvement of forecasts and warnings for high-impact weather events, from understanding, observing, and predicting the phenomenon and its impact, to an appropriate communication of forecasts and risks, and to successful warnings. A conceptual model of warning chain was produced in the HIWeather project in pursuit of successful weather-hazards warnings. The value chain comprises the following components and their connections: observations, weather forecast, hazard forecast, impact forecast, the generation of warnings, and decision making (Fig. 6). Those components need not only meteorological and related physical sciences, but also social, behavioral, and economic sciences. Thus, the bridges connecting them depend on applications of social science, especially communication science. From observation to decision making, there are several “mountains and valleys” to overcome. Collaborations among scientists in different areas, governments, social media, and citizens are needed for successful hazard prevention.
Conceptual model of warning value chain. Bridges represent interdisciplinary or interagency communication (reproduced from Zhang et al., 2019).
Acknowledgements. This study was supported by the National Key Research and Development Project (Grant No. 2017YFC1502004) and National Natural Science Foundation of China under Grant No. 42030607.