DARK AR Detection Catalog (ERA5, 1979–2023)

This dataset provides yearly binary atmospheric-river (AR) masks derived from the ERA5 reanalysis, produced using the DARK (formerly Buffet v1.0) detection algorithm.Although originally developed with a polar (Antarctic) focus, the implementation operates globally on the full ERA5 grid.All outputs follow ARTMIP Tier-1 conventions, including variable naming, attributes, dimensions, CF metadata, and filename structure. Method Input field ERA5 vertically integrated water vapor flux components:viwve (eastward) and viwvn (northward) Data source: ERA5 reanalysis (ECMWF), typically 6-hourly fields. Overview of the steps Rolling seasonal threshold (98th percentile baseline)For each leap day-of-year (1–366), compute a 15-day rolling climatology of Integrated Vapor Transport (IVT) and extract the 98th percentile.Non-leap years are mapped to leap-year DOYs by shifting days ≥ 29 Feb (+1).The 98th-percentile field is precomputed from 1979–2023. Exceedance maskA grid cell is marked 1 if the local IVT exceeds its day-of-year threshold; otherwise 0. Area filtering (< 200 000 km²)Connected regions are identified using 8-connectivity and periodic longitude boundaries (dateline continuity).Components with total area < 200 000 km² are removed.Grid-cell areas are computed on WGS-84 using geocentric radius and local Δlat/Δlon. Length filtering (< 2 000 km)Each connected component is skeletonized and represented as a graph.The endpoint-to-endpoint path best aligned with the principal component axis is selected, extended to the edges, and smoothed using a B-spline.Sub-grid geodesic segment lengths (WGS-84) are summed; components shorter than 2 000 km are discarded. Output assemblyEach yearly NetCDF file contains the binary field ar_binary_tag(time, lat, lon) with values 1 = AR and 0 = no AR. Files & Format One NetCDF file per year: ERA5.ar_tag.DARK.<freq>.<YYYYMMDD-YYYYMMDD>.nc where <freq> is inferred from input ERA5 temporal resolution (e.g. 6hourly). Variables Variable Type Description ar_binary_tag(time, lat, lon) byte 1 = AR, 0 = no AR Attributes: description = "binary indicator of atmospheric river" scheme = "DARK" version = "1.0" credits = "Developed by Victoire Buffet, Vincent Favier, and Benjamin Pohl" Coordinates: time — CF-compliant (minutes since <year>-01-01 00:00:00, calendar = "standard", axis = "T") lat — degrees_north (axis = "Y") lon — degrees_east (axis = "X") Compression: NetCDF-4 deflate (zlib=True, complevel=1, shuffle=True); time unlimited. Spatial / Temporal Coverage Spatial: Global ERA5 native 0.25° × 0.25° grid.(Algorithm tuned for polar ARs but operates globally.) Temporal: 1979 – 2023, using ERA5 6-hourly timesteps. Parameters (defaults) Rolling window: 15 days Percentile: 98th Minimum area: 200 000 km² Minimum length: 2 000 km Reproducibility Inputs ERA5 u/v flux files:vertical_integral_of_eastward_water_vapour_flux_{year}.ncvertical_integral_of_northward_water_vapour_flux_{year}.nc Percentile baseline:percentile_98_IVT_rolling_15D_era5.nc (1979–2023) Outputs Yearly AR masks:ERA5.ar_tag.DARK.6hourly.YYYYMMDD-YYYYMMDD.nc Software Python ≥ 3.11 Key libraries: xarray, numpy, scipy, scikit-image, geopy, networkx, matplotlib Geodesic distances computed with geopy (WGS-84) NetCDF written CF-1.6-compliant using netCDF4 Credits Developed by Victoire Buffet, Vincent Favier, and Benjamin Pohlat Institut des Géosciences de l’Environnement (Grenoble) and Biogéosciences (Dijon). Keywords Atmospheric Rivers; ERA5; ARTMIP; IVT; Antarctic; Polar Meteorology; Reanalysis; Climate Diagnostics Related Material ARTMIP format and Tier-1 conventions ERA5 reanalysis documentation本数据集提供基于ERA5再分析资料（ERA5 reanalysis）生成的逐年二元大气河流（Atmospheric River, AR）掩膜产品，采用DARK（前身为Buffet v1.0）检测算法制作。该算法最初针对极地（南极）场景开发，但目前可在完整ERA5网格上开展全球范围运算。所有输出均遵循ARTMIP Tier-1规范，涵盖变量命名、属性、维度、CF元数据以及文件名结构。 ## 方法 ### 输入场 ERA5垂直积分水汽通量分量：东向viwve与北向viwvn。 数据来源：欧洲中期天气预报中心（European Centre for Medium-Range Weather Forecasts, ECMWF）的ERA5再分析资料，通常为6小时分辨率场。 ### 流程概述 1. 滚动季节阈值（98th百分位基准） 针对每个闰年日序（1–366），计算15天滑动的积分水汽输送（Integrated Vapor Transport, IVT）气候态，并提取其98th百分位值。非闰年通过将2月29日及之后的日期加1天，映射至闰年日序。98th百分位场已于1979–2023年期间预计算完成。 2. 超标掩膜 若网格单元的局地IVT超过对应日序的阈值，则标记为1；否则为0。 3. 区域滤波（<20000 km²） 采用8连通性与周期经度边界（国际日期变更线连续性）识别连通区域。移除总面积小于20000 km²的连通分量。网格单元面积基于WGS-84椭球，采用地心半径与局部经纬度增量计算得到。 4. 长度滤波（<2000 km） 对每个连通分量进行骨架化处理并表示为图结构。选取与主成分轴对齐最优的端点到端点路径，将其延伸至区域边缘并通过B样条进行平滑。累加子网格测地线线段长度（WGS-84基准），丢弃长度小于2000 km的连通分量。 5. 输出组装 逐年的NetCDF文件包含二元场`ar_binary_tag(time, lat, lon)`，其中取值1代表存在大气河流，0代表无大气河流。 ## 文件与格式 每年对应一个NetCDF文件，文件名格式为： `ERA5.ar_tag.DARK.<freq>.<YYYYMMDD-YYYYMMDD>.nc` 其中`<freq>`由输入ERA5的时间分辨率推断（例如`6hourly`）。 ### 变量 | 变量名 | 类型 | 描述 | |----------------------------|------|--------------------------| | `ar_binary_tag(time, lat, lon)` | byte | 1=存在大气河流，0=无大气河流 | ### 属性 - `description = "二元大气河流指示标志"` - `scheme = "DARK"`：检测方案为DARK - `version = "1.0"`：版本1.0 - `credits = "由Victoire Buffet、Vincent Favier与Benjamin Pohl开发"` ### 坐标 - `time`：符合CF规范（距`<年份>-01-01 00:00:00`的分钟数，日历类型为`standard`，轴类型为`T`） - `lat`：北纬度数（轴类型为`Y`） - `lon`：东经度数（轴类型为`X`） 压缩设置：采用NetCDF-4 deflate压缩（zlib=True，complevel=1，shuffle=True）；时间维度为无限制维度。 ## 时空覆盖范围 - 空间：全球ERA5原生0.25°×0.25°网格（算法最初针对极地大气河流优化，但支持全球运算） - 时间：1979–2023年，采用ERA5的6小时间隔时间步长。 ## 默认参数设置 - 滑动窗口：15天 - 百分位：98th - 最小面积：20000 km² - 最小长度：2000 km ## 可复现性 ### 输入数据 ERA5的u/v通量文件：`vertical_integral_of_eastward_water_vapour_flux_{year}.nc`、`vertical_integral_of_northward_water_vapour_flux_{year}.nc` 百分位基准场：`percentile_98_IVT_rolling_15D_era5.nc`（1979–2023年） ### 输出产品 逐年AR掩膜：`ERA5.ar_tag.DARK.6hourly.YYYYMMDD-YYYYMMDD.nc` ### 软件环境 Python ≥3.11 核心依赖库：xarray、numpy、scipy、scikit-image、geopy、networkx、matplotlib 测地线距离通过geopy计算（WGS-84基准） NetCDF文件按照CF-1.6规范通过netCDF4库写入。 ## 致谢 本数据集由Victoire Buffet、Vincent Favier与Benjamin Pohl在格勒诺布尔地球科学研究所（Institut des Géosciences de l’Environnement）及第戎生物地球科学研究所（Biogéosciences）开发完成。 ## 关键词 大气河流；ERA5；ARTMIP；IVT；南极；极地气象；再分析资料；气候诊断 ## 相关资料 - ARTMIP格式与Tier-1规范 - ERA5再分析资料文档