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Lightning-caused fire modeling data for Uden et al. (2026)

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Zenodo2026-03-23 更新2026-05-26 收录
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https://zenodo.org/doi/10.5281/zenodo.19193050
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This repository contains: Data used to drive lightning prediction, ignition efficiency, and lightning-caused fire probability models from Uden et al., 2026 A paleoclimate-compatible framework for modeling lightning-caused ignition probability in Alaska Code used to generate this data can be found on Github under the version tag v1.0 (https://github.com/charliuden/Lightning-Fire-Models-Uden-2026/releases/tag/v1.0). Contents: model_drivers/ lightning_prediction_drivers_xxxx_xxxx.csv : used to train the lightning prediction models Ignition_efficiency_drivers_xxxx_xxxx.csv : used to train the ignition efficiency models Fire_probability_daily_drivers_2002_2011.parquet : parquet file containing daily climate, fuel moisture, and land cover predictors for  ignition efficiency and fire probability on a continuous 0.25x0.25 grid for Alaska Fire_probability_seasonal_drivers_2002_2011.parquet : parquet file containing summer climate summaries for predicting lightning strike rate and fire probability on continuous 0.25x0.25 grid for Alaska Observed_binary_fire_data_2002_2018.shp : shapefile containing daily binary lightning-caused fire observations on a continuous 0.25x0.25 degree grid for Alaska. 1=at least one lighting-caused fire occurred, 0 no fire occurred.  Drivers_predictions_and_observations_2002-2011_10x.csv : daily values of model predictor variables (climate, fuel moisture, land cover), predictions of lightning strike rate, ignition efficiency, and fire probability, and observations of lighting strike rate and lightning-caused fire.  model_performance/ Random forest, coefficient estimates, and performance metrics for lighting prediction models and ignition efficiency models. Model_predictions/ predictions from fire model Other_data/ Unprocessed fire location data downloaded from AKFED [1] Partially processed datasets generated during data preprocessing, including: Lighting strike rates Era5 climate data Wildfire data Land cover data Some of these .csv files are used to generate figures for the manuscript Rds/ Rds files containing fitted lightning prediction and ignition efficiency bayesian models    Data cover the Alaska for the years 2002 - 2018. Unprocessed ERA5 climate data [2] can be downloaded from Copernicus Climate Change Service  and include CAPE (J/kg), 2 meter temperature (℃), instantaneous 10 meter wind gust (m/s), mean surface downward short-wave radiation flux (W/m2), surface pressure (Pa), mean total precipitation rate (kg/m2/s), and relative humidity (%, calculated from temperature and 2 meter dew point temperature). Unprocessed daily lighting strike count data can be downloaded from the Alaska Lightning Detection Network (ALDN), maintained by the Alaska Fire Service (AFS) [3], [4]. Wildfire ignition data were obtained from the Alaska-Yukon-Northwest Territories Fire Emissions Database (AKFED), version 2, archived at the Oak Ridge National Laboratory Distributed Active Archive Center [1]. Unprocessed land-cover data come from the North American Land Change Monitoring System (NALCMS) to derive vegetation cover predictors [5] References: [1] R. C. Scholten, S. Veraverbeke, R. Jandt, E. A. Miller, and B. M. Rogers, “ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018,” ORNL Distrib. Act. Arch. Cent. DAAC Dataset 103334ORNLDAAC1812 2021, p. 1812, Jan. 2021, doi: 10.3334/ORNLDAAC/1812.  [2] H. Hersbach et al., “The ERA5 global reanalysis,” Q. J. R. Meteorol. Soc., vol. 146, no. 730, pp. 1999–2049, 2020, doi: 10.1002/qj.3803.  [3] U.S. Department of the Interior, Bureau of Land Management (BLM), “BLM AFS Impact System Lightning 1986-2012 Points, NAD83.” Mar. 07, 2024. [Online]. Available: https://fire.ak.blm.gov/predsvcs/maps.php  [4] U.S. Department of the Interior, Bureau of Land Management (BLM), “BLM AFS TOA Lightning 2012-2025 Points, WGS84.” Oct. 06, 2025. [Vector digital data]. Available: https://fire.ak.blm.gov/predsvcs/maps.php  [5] Commission for Environmental Cooperation (CEC), “NALCMS. The North American Land Change Monitoring System — A trinational collaboration of more than 21 million square kilometers.” Sep. 25, 2024. [2005, 2010, 2015, and 2025 raster digital data]. Available: https://www.cec.org/north-american-environmental-atlas/?_atlas_keyword=land-cover

本数据集仓库包含以下内容: 用于训练Uden等(2026)提出的雷击预测、点火效率以及雷击引发火灾概率模型的数据集,该研究构建了兼容古气候的阿拉斯加雷击点火概率建模框架。 用于生成该数据集的代码可在GitHub的v1.0版本标签下获取:https://github.com/charliuden/Lightning-Fire-Models-Uden-2026/releases/tag/v1.0。 数据集内容: model_drivers/ 目录: lightning_prediction_drivers_xxxx_xxxx.csv:用于训练雷击预测模型的驱动数据集 Ignition_efficiency_drivers_xxxx_xxxx.csv:用于训练点火效率模型的驱动数据集 Fire_probability_daily_drivers_2002_2011.parquet:Parquet格式文件(Parquet),包含阿拉斯加地区连续0.25×0.25度网格上用于点火效率与火灾概率建模的每日气候、燃料湿度以及土地覆盖预测因子数据 Fire_probability_seasonal_drivers_2002_2011.parquet:Parquet格式文件(Parquet),包含用于预测阿拉斯加连续0.25×0.25度网格上雷击频次与火灾概率的夏季气候汇总数据 Observed_binary_fire_data_2002_2018.shp:Shapefile格式文件(Shapefile),包含阿拉斯加连续0.25×0.25度网格上的每日二进制雷击引发火灾观测数据:1代表该网格内至少发生1起雷击引发的火灾,0代表未发生火灾 Drivers_predictions_and_observations_2002-2011_10x.csv:包含2002至2011年每日的模型预测因子(气候、燃料湿度、土地覆盖)、雷击频次、点火效率与火灾概率的模型预测结果,以及雷击频次与雷击引发火灾的观测数据 model_performance/ 目录: 包含雷击预测模型与点火效率模型的随机森林、系数估计值以及性能指标 Model_predictions/ 目录: 包含火灾模型的预测结果 Other_data/ 目录: 从AKFED[1]下载的未处理火灾位置数据 数据预处理过程中生成的部分处理数据集,包括: 雷击频次数据 ERA5气候数据(ERA5) 野火数据 土地覆盖数据 部分此类CSV文件用于生成论文的插图 Rds/ 目录: 包含已拟合的雷击预测与点火效率贝叶斯模型的Rds格式文件 本数据集覆盖2002至2018年的阿拉斯加地区。未处理的ERA5气候数据[2]可从哥白尼气候变化服务中心获取,包含对流有效位能(CAPE,单位:J/kg)、2米气温(单位:℃)、瞬时10米阵风风速(单位:m/s)、平均地表向下短波辐射通量(单位:W/m²)、地表气压(单位:Pa)、平均总降水率(单位:kg/m²/s)以及相对湿度(单位:%,由气温与2米露点温度计算得到)。未处理的每日雷击计数数据可从阿拉斯加消防局(AFS)维护的阿拉斯加雷击探测网络(ALDN)获取[3][4]。野火点火数据源自阿拉斯加-育空-西北地区野火排放数据库(AKFED)第二版,存档于橡树岭国家实验室分布式主动存档中心[1]。未处理的土地覆盖数据来自北美土地变化监测系统(NALCMS),用于提取植被覆盖预测因子[5] 参考文献: [1] R. C. Scholten、S. Veraverbeke、R. Jandt、E. A. Miller与B. M. Rogers,"ABoVE:2001-2018年阿拉斯加、育空地区与西北地区的火灾点火、燃烧面积与排放",橡树岭国家实验室分布式主动存档中心(ORNL DAAC)数据集103334ORNLDAAC1812,2021年,第1812页,2021年1月,DOI: 10.3334/ORNLDAAC/1812. [2] H. Hersbach等,"ERA5全球再分析数据",《皇家气象学会季刊》,第146卷,第730期,第1999-2049页,2020年,DOI: 10.1002/qj.3803. [3] 美国内政部土地管理局(BLM),"BLM AFS影响系统雷击点数据(1986-2012),NAD83坐标系",2024年3月7日,[在线资源],可访问:https://fire.ak.blm.gov/predsvcs/maps.php [4] 美国内政部土地管理局(BLM),"BLM AFS TOA雷击点数据(2012-2025),WGS84坐标系",2025年10月6日,[矢量数字数据],可访问:https://fire.ak.blm.gov/predsvcs/maps.php [5] 环境合作委员会(CEC),"NALCMS:北美土地变化监测系统——覆盖超2100万平方公里的三国协作项目",2024年9月25日,[2005、2010、2015与2025年栅格数字数据],可访问:https://www.cec.org/north-american-environmental-atlas/?_atlas_keyword=land-cover
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创建时间:
2026-03-23
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