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An Army Brigade Explores Building a High-Temperature Training Risk Early-Warning System

陆军某旅探索构建高温训练风险预警体系
PLA Daily (解放军报) 14 August 2026
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An unidentified Army brigade has built a four-level heat-stroke early-warning system that combines field temperature-humidity sensors, individual heat-tolerance curves, and PLA-wide tiered prevention standards to replace commander judgment with automated alerts that can suspend or halt outdoor training in real time. The article documents a recognized institutional problem — that the PLA's existing summer training safety model depended on cadre experience (经验主导) and was prone to lagging assessments and inconsistent standards — and records one brigade's data-driven (数据驱动) fix as a model worth publicizing. The framing in PLA Daily points to broader institutional pressure to systematize heat-casualty prevention across the force, though the article does not establish whether this brigade's approach has been directed or adopted above the brigade level.

PLA Daily report by Ma Dinggui and reporter Sun Xingwei: "The load-bearing cross-country event is being adjusted to indoor physical training!" On a midsummer afternoon, Company Commander He of an Army brigade immediately adjusted his training plan upon receiving a heat stroke risk early-warning notice issued by the brigade's duty room.

"Weather indices are an important indicator for high-temperature training risk early warnings, but they are not the only criterion. Relying solely on subjective experience to conduct heat stroke prevention and control is highly prone to misjudgment." The brigade's leadership explained that every year after the onset of the hottest summer period (入伏), the garrison location frequently experiences high-temperature and high-humidity weather, placing considerable pressure on heat stroke prevention and control. In the past, risk prevention and control for high-temperature training relied primarily on the risk-assessment capabilities of leading cadres, who would generally evaluate training intensity by observing weather conditions and the physical condition of officers and soldiers. This model had shortcomings such as lagging assessments, vague standards, and rough-and-ready prevention and control measures, making it difficult to effectively guard against the occurrence of heat stroke and liable to leave safety hazards.

To address this, the brigade explored building a high-temperature training risk early-warning system: equipping field temperature and humidity measurement devices to dynamically monitor weather data, promptly issue early-warning information, and scientifically adjust training plans; drawing heat tolerance curves based on officers' and soldiers' training conditions to establish risk-data early-warning contingency plans; and, by collecting multidimensional visualized data and cross-referencing the PLA-wide heat stroke tiered prevention and control standards, generating early-warning reference charts for training risk levels and safe training durations. The brigade's leadership told reporters that they have accordingly established a four-level response mechanism: green warning — conduct high-intensity training as normal; yellow warning — reduce load-bearing and shorten rest intervals; orange warning — suspend field load-bearing events; red warning — immediately halt all outdoor training. This ensures scientific training (科学练兵) and safe training.

In order to further drive the shift in heat stroke prevention and control from "experience-led (经验主导)" to "data-driven (数据驱动)," the brigade has refined officers' and soldiers' thermal health databases by leveraging opportunities such as induction physical examinations, quarterly heat tolerance screenings, and high-temperature training assessments, providing scientific data support for summer training. Before summer training begins, they comprehensively assess the training environment and other conditions to scientifically set training events, training intensity, and rest frequency, moving the prevention threshold forward. "In the past, summer training mainly relied on feel to regulate the training tempo; now we let the data speak — prevention and control is more scientific, and training is safer." A battalion commander in the brigade told reporters that before this summer began, they specifically organized a data-based heat prevention specialist training session, organizing training cadres and medics to study and master heat index assessment, data collection and analysis, and tiered emergency response procedures, resolutely breaking down the traditional prevention and control mindset of "experience over standards, physical sensation substituting for data (经验大于标准、体感代替数据)."

It is reported that since the onset of the hottest summer period this year, units throughout the brigade have steadily completed planned training tasks, with assessment scores on multiple training events surpassing the same period in previous years.

Original Chinese
解放军报讯 马锭贵、记者孙兴维报道:“负重越野课目调整为室内体能训练!”盛夏午后,陆军某旅何连长依据旅值班室发布的热射病风险预警通知,立即调整训练计划。 “天气指数是高温训练风险预警的重要指标,但不是唯一标准,仅凭主观经验开展热射病防治极易出现误判。”该旅领导介绍,每年入伏以后,驻地高温高湿天气频发,热射病防控压力较大。以往,高温训练风险防控主要依赖带队骨干的风险预判能力,一般通过观察天气情况和官兵身体状态,综合评估训练强度。这种模式存在预判滞后、标准模糊、防控粗放等短板,难以有效防范热射病发生,容易埋下安全隐患。 为此,该旅探索构建高温训练风险预警体系:配备野外测温测湿设备,动态监测天气数据,及时发布预警信息,科学调整训练计划;依据官兵训练情况绘制热耐力曲线图,建立风险数据预警预案;通过采集多元可视化数据,对照全军热射病分级防控标准,生成训练风险等级、安全训练时长等预警参照图。该旅领导告诉记者,他们据此建立四级响应机制:绿色预警,常态开展高强度训练;黄色预警,减少负重、缩短休息间隔;橙色预警,暂停野外负重课目;红色预警,即刻停止室外训练,确保科学练兵、安全训练。 为了进一步推动热射病防治从“经验主导”转向“数据驱动”,该旅结合入营体检、季度热耐力筛查和高温训练测评等时机,完善官兵热健康数据库,为夏季练兵提供科学数据支撑。夏季训练前,他们综合训练环境等情况,科学设置训练课目、训练强度和休息频次,将预防关口前移。“以前夏季训练主要凭感觉调控训练节奏,如今用数据说话,防控更科学,训练更安全。”该旅某营营长告诉记者,今年入夏之前,他们专门组织数据化防暑专项培训,组织训练骨干和卫生员学习掌握热指数研判、数据采集分析和分级应急处置流程,坚决破除“经验大于标准、体感代替数据”的传统防控思维。 据介绍,今年入伏以来,该旅各单位稳步完成计划内训练任务,多个训练课目考核成绩超过往年同期水平。