Effects of weather parameters on endurance running performance

The aim of the analysis was to evaluate how single or combinations of weather parameters (temperature, humidity, wind speed, solar load) affect peak performance during endurance running events and identify which events are most vulnerable to varying weather conditions. Results for the marathon, 50 km race-walk, 20 km race-walk, 10,000 m, 5,000 m and 3,000 m-steeplechase were obtained from the official websites of the largest competitions in the world. Finish times for all races were collected from the first year of each competition for which data were available online until the end of 2019. The collection of these data was completed between February 2016 and September 2020 We obtained the date, time, and location for each race from its official website while the relevant longitude and latitude were obtained from www.locationiq.com. Weather data (air temperature, dew point, wind speed, and cloud coverage) corresponding to the time at half-way in each race were obtained from the closest meteorological station using the official dataset of the National Oceanic and Atmospheric Administration (www.ncei.noaa.gov/data/global-hourly). In cases where these data were not available, we retrieved the information from widely-used meteorology websites (www.wunderground.com and www.weatherspark.com). Wind speed was adjusted for height above the ground and air friction coefficient (i.e., large city with tall buildings). Dew point data were converted to relative humidity. For cases where cloud coverage was not available in the National Oceanic and Atmospheric Administration datasets, the cloud coverage (in okta) was computed using relative humidity data based on previous methodology and applying coefficients of 0.25 for low and high as well as 0.5 for middle clouds, as previously suggested. Solar radiation was calculated using the date, time, and coordinates of each race, while accounting for cloud coverage. Thereafter, the Heat Index, Simplified WBGT and WBGT, were calculated using previous methodology.本研究旨在评估气象参数（气温、湿度、风速、太阳负荷）单独或组合作用对耐力跑赛事巅峰表现的影响，并识别最易受天气条件变化影响的赛事项目。本研究的马拉松、50公里竞走、20公里竞走、10000米、5000米及3000米障碍赛（3,000 m-steeplechase）数据，均取自全球顶级赛事的官方网站。所有赛事的完赛时间采集区间为各赛事可在线获取数据的首个年份至2019年末，数据收集工作于2016年2月至2020年9月间完成。我们从各赛事的官方网站获取了赛事举办日期、时间及场地信息，经纬度坐标则通过www.locationiq.com获取。对应各赛事半程时刻的气象数据（气温、露点温度、风速及云量），取自距离赛事场地最近的气象站，数据来源为美国国家海洋和大气管理局（National Oceanic and Atmospheric Administration）的官方数据集（www.ncei.noaa.gov/data/global-hourly）；若该渠道无法获取所需数据，则从常用气象网站www.wunderground.com及www.weatherspark.com调取信息。研究人员对风速进行了地面高度与空气摩擦系数的校正（例如存在高层建筑的大城市场景），并将露点温度数据转换为相对湿度。若美国国家海洋和大气管理局的数据集中缺失云量数据，则基于既往研究方法，利用相对湿度数据计算云量（以奥克塔（okta）为单位）：低云与高云的系数取值为0.25，中云系数取值为0.5，与此前研究建议一致。结合各赛事的举办日期、时间及场地坐标，并考虑云量影响，研究人员计算得到太阳辐射量。随后，基于既往研究方法，分别计算了热应激指数（Heat Index）、简化湿球黑球温度（Simplified WBGT）及湿球黑球温度（WBGT）。