首页|基于观测与预报数据融合的森林火险预报

基于观测与预报数据融合的森林火险预报

扫码查看
针对气象因子日变化波动大容易引起森林火险气象等级预报变动大这一问题,参考布龙-戴维斯方案森林火险气象预报模型的构建思路,利用2016-2020年广西1 785个森林火灾样本和气象观测数据,建立森林火险气象指数模型(简称"模型").将气象观测数据输入模型,计算出每日森林火险气象监测指数,同时,将智能网格预报数据输入模型,计算出每日森林火险气象预报指数,然后利用加权算法将每日森林火险气象监测指数和每日森林火险气象预报指数进行融合计算,得到森林火险气象融合预报指数.利用2021年6月-2023年6月789个火灾样本,对林火险气象融合预报指数进行验证,结果表明:融合后未来1~7 d森林火险等级预报准确率从82%~56%,较融合前预报准确率提升1%~3%,基本满足目前广西森林火险气象等级预报业务应用.
Forest Fire Risk Forecast Based on the Fusion of Observation and Forecast Data
Aiming at the problem that the large daily fluctuation of meteorological factors was easy to cause the large change of forest fire weather grade forecast,the forest fire weather index model(referred to as the model)was established by referring to the idea of constructing the forest fire weather forecast model of Brown-Davis scheme,using 1 785 forest fire samples and meteorological observation data in Guangxi from 2016 to 2020.The meteorological observation data was input into the model to calculate the daily forest fire risk meteorological monitoring index.Meanwhile,the intelligent grid forecast data was input into the model to calculate the daily forest fire risk meteorological forecast index.Then the weighted algorithm was used to integrate the daily forest fire risk meteorological monitoring index and the daily forest fire risk meteorological forecast index to obtain the forest fire risk meteorological fusion forecast index.Using 789 fire samples from June 2021 to June 2023,the forest fire weather fusion forecast index was verified.The results show that the prediction accuracy of forest fire danger grade in the next 1 to 7 days after the fusion is from 82%to 56%,which is 1%~3%higher than that before the fusion,and basically met the current application of forest fire weather classification forecast in Guangxi.

forest fire insuranceobservation and predictiondata fusionexponentmodel

罗永明、曾行吉、谢映、何立、陈燕丽

展开 >

广西壮族自治区气象科学研究所/国家卫星气象中心遥感应用基础,南宁 530022

广西壮族自治区气象信息中心,南宁 530022

森林火险 观测与预报 数据融合 指数 模型

广西自然科学基金广西重点研发计划

2020GXNSFAA238046桂科AB20159022

2024

科学技术与工程
中国技术经济学会

科学技术与工程

CSTPCD北大核心
影响因子:0.338
ISSN:1671-1815
年,卷(期):2024.24(23)