Lessons Learned from the Tragedy during the 100 km Ultramarathon Race in Baiyin, Gansu Province on 22 May 2021

Zhang, Qinghong; Ng, Chan-Pang; Dai, Kun; Xu, Jun; Tang, Jian; Sun, Juanzhen; Mu, Mu

doi:10.1007/s00376-021-1246-0

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…More detailed findings and lessons learnt using the concept of the warning value chain were analysed by project members for a cold-front induced ultramarathon tragedy in Jingtai County of Baiyin City, China in May 2020 (Zhang et al, 2021). Project members at the Bureau of Meteorology held an internal workshop with pre-workshop surveys interviewing forecasters, embedded meteorologists, communication specialists and managers to assess the performance of each part of the warning value chain for a heavy rain and flood event in eastern Australia in March 2021.…”

Section: High Impact Weather Events Studiedmentioning

confidence: 99%

Using value chain approaches to evaluate the end-to-end warning chain

et al. 2023

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Abstract. The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system covering weather and hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities. Warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision. In November 2020, a 4-year international project under the World Meteorological Organization (WMO) World Weather Research Programme was instigated to explore value chain approaches to describe and evaluate warning systems for high impact weather by integrating physical and social science. It aims to create a framework with guidance and tools for using value chain approaches, and to develop a database of high impact weather warning case studies for scientists and practitioners to review, analyse and learn from previous experience using value chain approaches. Here we describe a template for high-impact weather event case study collection that provides a tool for scientists and practitioners involved in researching, designing and evaluating weather-related warning systems to review previous experience of high impact weather events and assess their efficacy.

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Section: High Impact Weather Events Studiedmentioning

confidence: 99%

Using value chain approaches to evaluate the end-to-end warning chain

et al. 2023

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“…K). This relates to the need for vulnerability and exposure to be included in IFWs and the identification of appropriate audiences' relevant trigger points (or thresholds) (Zhang et al 2021). It is not enough to collect only past event impact data and expect the impacts to be the same for future events or different populations.…”

Section: ) Urban and Rural Impactsmentioning

confidence: 99%

Identifying the Impact-Related Data Uses and Gaps for Hydrometeorological Impact Forecasts and Warnings

Harrison

Potter

Prasanna

et al. 2022

Weather, Climate, and Society

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Impact Forecasts and Warnings (IFW) are key to resilience for hydrometeorological hazards. Communicating the potential social, economic, and environmental hazard impacts allows individuals and communities to adjust their plans and better prepare for the consequences of the hazard. IFW systems require additional knowledge about impacts, and underlying vulnerability and exposure. Lack of data or knowledge about impacts, vulnerability, and exposure has been identified as a challenge for IFW implementation. In this study, we begin to address this challenge by developing an understanding of the data needs and uses for IFWs. Using Grounded Theory Methodology, we conducted a series of interviews with users and creators of hazard, impact, vulnerability, and exposure data (e.g., warning services, forecasters, meteorologists, hydrologists, emergency managers, data specialists, risk modellers) to understand where these data are needed and used in the Warning Value Chain, a concept used to represent and understand the flow of information amongst actors in the warning chain (Golding et al., 2019). In support of existing research, we found a growing need for creating, gathering, and using impact, vulnerability, and exposure data for IFWs. Furthermore, we identified different approaches for impact forecasting and defining impact thresholds using objective models and subjective impact-oriented discussions depending on the data available. We also provided new insight into a growing need to identify, model, and warn for social and health impacts, which have typically taken a back seat to modelling and forecasting physical and infrastructure impacts. Our findings on the data needs and uses within IFW systems will help guide their development and provide a pathway for identifying specific relevant data sources.

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“…A brief review of the event was given in the official report and by Zhang et al. (2021). Here it is summarized as: (a) the 2 m temperature decreased by 5–7°C between 08:00 and 13:00 BJT; (b) precipitation began at 10:30 BJT, increased between 11:00 and 12:00 BJT, and decreased after 14:00 BJT; (c) graupel fell at high altitudes on the mountain; and (d) the average wind speed between CP2 and CP3 was approximately 10.8–17.1 m s −1 , with gusts of 17.2–24.4 m s −1 , indicating a fresh gale (17.2–20.5 m s −1 ) or strong gale (20.5–24.4 m s −1 ) event.…”

Section: Introductionmentioning

confidence: 99%

“…The large‐scale process associated with the 2021 ultramarathon tragedy has been identified as a cold front passing event, which can be predicted by the operational numerical weather prediction (NWP) models (Zhang et al., 2021). However, the meso‐ and micro‐scale processes remain unclear.…”

Section: Introductionmentioning

confidence: 99%

Simulation of the Effect of Small‐Scale Mountains on Weather Conditions During the May 2021 Ultramarathon in Gansu Province, China

Xue

Zhang

et al. 2022

JGR Atmospheres

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Hypothermia killed 21 participants of the 100 km cross‐country Ultramarathon Mountain race in Baiyin, Gansu Province in northwestern China on 22 May 2021, when a large‐scale cold front passed by the race site. The hypothermia was caused by low temperatures, high winds, and hail‐like precipitation, as reported by survivors. However, there is no meteorological station near the race site, leading to a lack of data on the exact weather conditions during the race. Considering the complex topography of the race site, the weather conditions must be re‐built using high‐resolution model simulations, so that the tragedy can be investigated. In this study, the weather conditions in this mountainous area were simulated using the Weather Research and Forecasting model with a 333 m horizontal grid size. The results show that interaction between the mountain wind and orographic precipitation led to a 6.7°C decrease in temperature and a 12 m s−1 increase in wind speed. Precipitation increased owing to orographic accent and convergence, and fell as graupel. High‐speed downslope winds were the result of large‐amplitude trapped lee waves. The combination of low temperatures, high winds, and spillover graupel on the lee resulted in the blizzard‐like weather during the race, thus the hypothermia amongst the runners. The apparent temperature was estimated to be as low as −10°C. Our study shows that mesoscale numerical models with a grid size of hundreds of meters should be used to improve weather forecasts in mountainous regions and prevent future tragedies for special events.

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Lessons Learned from the Tragedy during the 100 km Ultramarathon Race in Baiyin, Gansu Province on 22 May 2021

Cited by 7 publications

References 7 publications

Using value chain approaches to evaluate the end-to-end warning chain

Using value chain approaches to evaluate the end-to-end warning chain

Identifying the Impact-Related Data Uses and Gaps for Hydrometeorological Impact Forecasts and Warnings

Simulation of the Effect of Small‐Scale Mountains on Weather Conditions During the May 2021 Ultramarathon in Gansu Province, China

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