DARK (formerly Buffet v1.0) AR Detection Catalog (MERRA-2, 1980–2017, ARTMIP format)

This dataset provides yearly binary atmospheric-river (AR) masks derived from MERRA-2 reanalysis, produced by the DARK detection algorithm. Although the method was developed with a polar (Antarctic) emphasis, the implementation operates globally and scans the full MERRA-2 grid. Output files follow the ARTMIP Tier-1 conventions (variable name, attributes, dimensions, CF metadata, and filename pattern). Method Input field. The algorithm uses MERRA-2 total IVT directly from ARTMIP yearly files (DOI: 10.5065/D62R3QFS). Overview of the steps : Rolling seasonal threshold (98th percentile).For each leap day-of-year (1…366) we compute a 15-day rolling window climatology of IVT at each grid cell and take the 98th percentile across all selected days and years. Non-leap years are mapped to the leap DOY by shifting days ≥ 29 Feb (+1). Exceedance mask.A grid cell is marked 1 if the local IVT of a given day exceeds its local and day-of-year threshold (98th percentile as defined in 1), else 0. Area filtering (< 20, 000 km²). We treat longitude as periodic so features crossing that seam aren’t split and drop components with area < 20,000 km². Grid-cell areas are computed on WGS-84 using geocentric radius and the local Δlat/Δlon. Length filtering ( < 2000 km) with seam-free centerlines.For each remaining component (AR candidate) and time: We compute a skeleton of each AR candidate, build a pixel-adjacency graph, enumerate endpoint-to-endpoint paths, and select the one most aligned with the component’s PCA axis. The path is extended to the object edges and smoothed with a B-spline. Geodesic segment lengths are summed using WGS-84 (geopy) to get a sub-grid AR length. Components shorter than 2000 km are discarded. Output assembly.We write a yearly byte (i1) mask ar_binary_tag(time,lat,lon), with 1 where an AR is detected and 0 elsewhere. Files & Format One NetCDF per year:MERRA2.ar_tag.Buffet.<freq>.<YYYYMMDD-YYYYMMDD>.ncwhere <freq> is inferred (e.g., 3hourly, 6hourly). Variables ar_binary_tag(time, lat, lon) — byte; 1 = AR, 0 = no AR.Attributes: description = "binary indicator of atmospheric river" scheme = "Buffet" version = "1.0" credits = "Developed by Victoire Buffet, Vincent Favier, and Benjamin Pohl" time(time) — CF time with standard_name, long_name, units = "minutes since <year>-01-01 00:00:00", calendar = "standard", axis = "T". lat(lat) — degrees_north; CF/ARTMIP attributes (standard_name, long_name, axis). lon(lon) — degrees_east; CF/ARTMIP attributes (standard_name, long_name, axis). Compression: data variable uses NetCDF-4 deflate (zlib=True, complevel=1, shuffle=True). time is unlimited. Spatial/Temporal Coverage Spatial: Global MERRA-2 native 2D grid (the algorithm targets polar/Antarctic ARs but evaluates the globe). 0.5° in latitude, 0.625° in longitude. Temporal: 1980–2017, using the time resolution provided by the input MERRA-2 IVT files (3-hourly). Parameters (defaults) Rolling window: 15 days Percentile: 98th Minimum area: 20,000 km² Minimum length: 2,000 km Reproducibility Inputs Yearly MERRA-2 files with a 2D IVT variable:ARTMIP_MERRA_2D_{year}_3h.nc (or equivalent pattern) Two stages Build rolling‐DOY percentiles (once):percentile_98_IVT_rolling_15D_merra2.nc Tag each year to produce ar_binary_tag yearly files. Software Python ≥ 3.9; key libraries: xarray, numpy, scipy, scikit-image, geopy, networkx, matplotlib. Geodesics computed with geopy (WGS-84). Files written CF-compliant with netCDF4. Credits Developed by Victoire Buffet, Vincent Favier, and Benjamin Pohl at Institut des Géosciences de l'Environnement (Grenoble) and Biogéosciences (Dijon). Keywords Atmospheric Rivers; MERRA-2; ARTMIP; IVT; Antarctic; Polar Meteorology Related Material ARTMIP format and Tier-1 conventions. MERRA-2 reanalysis documentation.本数据集提供基于MERRA-2再分析资料生成的逐年大气河流（Atmospheric River, AR）二值掩膜，该掩膜由DARK检测算法生成。尽管该方法的开发以极地（南极）大气河流为重点，但实现方案可全球运行，并覆盖完整的MERRA-2网格。输出文件遵循ARTMIP Tier-1规范（包含变量名、属性、维度、气候与预报（Climate and Forecast, CF）元数据以及文件名格式）。 方法 输入场。该算法直接使用ARTMIP逐年文件中的MERRA-2整层积分水汽通量（Integrated Vapor Transport, IVT），相关文件的DOI为：10.5065/D62R3QFS。 步骤概述 1. 滚动季节阈值（第98百分位数）：针对每个闰年日序（1…366），我们在每个网格点上计算15天滑动窗口的整层积分水汽通量气候态，并选取所有选定日期与年份中的第98百分位数。非闰年的日期通过将2月29日及以后的日期向后偏移1天，映射至闰年日序。 2. 超标掩膜：若某一天某网格点的局地IVT超过其对应局地日序阈值（即上述第98百分位数），则该网格点标记为1，否则为0。 3. 区域过滤（面积<20000 km²）：我们将经度视为周期性边界，因此跨越该边界的大气河流特征不会被分割，并移除面积小于20000 km²的连通分量。网格点面积基于WGS-84坐标系，通过地心半径与局地经纬度增量Δlat/Δlon计算得到。 4. 长度过滤（长度<2000 km），采用无接缝中心线：针对每个剩余的连通分量（AR候选对象）与时刻：我们为每个AR候选对象提取骨架，构建像素邻接图，枚举所有端点到端点的路径，并选取与该分量主成分分析（Principal Component Analysis, PCA）轴最对齐的路径。将该路径延伸至对象边界，并使用B样条进行平滑。基于WGS-84坐标系（通过geopy库实现）对测地线分段长度求和，得到亚网格尺度的AR长度。移除长度小于2000 km的连通分量。 输出组装：我们生成逐年的字节型（i1）掩膜ar_binary_tag(time,lat,lon)，其中1代表检测到AR，0代表未检测到。 文件与格式 每年对应一个NetCDF文件，命名格式为：MERRA2.ar_tag.Buffet.<freq>.<YYYYMMDD-YYYYMMDD>.nc，其中<freq>为时间分辨率（例如3小时、6小时），可通过文件信息推断得到。 变量 1. ar_binary_tag(time, lat, lon)：字节型变量，1代表存在AR，0代表无AR。其属性包括： - description = "binary indicator of atmospheric river"：大气河流二值指示符 - scheme = "Buffet"：方案为Buffet - version = "1.0"：版本1.0 - credits = "Developed by Victoire Buffet, Vincent Favier, and Benjamin Pohl"：由Victoire Buffet、Vincent Favier与Benjamin Pohl开发 2. time(time)：符合CF规范的时间变量，包含standard_name、long_name，单位为"minutes since <year>-01-01 00:00:00"，日历类型为"standard"，轴类型为"T"。 3. lat(lat)：以北纬为单位的纬度变量，包含CF/ARTMIP标准属性：standard_name、long_name与axis。 4. lon(lon)：以东经为单位的经度变量，包含CF/ARTMIP标准属性：standard_name、long_name与axis。 压缩设置：数据变量采用NetCDF-4格式的deflate压缩（zlib=True, complevel=1, shuffle=True）。time维度为无限制维度。 时空覆盖范围 空间范围：全球MERRA-2原生二维网格（本算法虽以极地/南极AR为开发目标，但对全球网格进行了检测）。纬度分辨率为0.5°，经度分辨率为0.625°。 时间范围：1980年至2017年，时间分辨率与输入的MERRA-2 IVT文件一致，为3小时一次。 参数（默认值） - 滑动窗口：15天 - 百分位数：第98百分位 - 最小面积：20000 km² - 最小长度：2000 km 可复现性 输入数据：包含二维IVT变量的逐年MERRA-2文件，命名格式为ARTMIP_MERRA_2D_{year}_3h.nc（或等效命名格式）。 两个处理阶段： 1. 构建滑动日序百分位数（仅需执行一次）：生成文件percentile_98_IVT_rolling_15D_merra2.nc 2. 对每年数据进行标记，生成逐年的ar_binary_tag文件。 软件环境：Python版本≥3.9；核心依赖库包括：xarray、numpy、scipy、scikit-image、geopy、networkx、matplotlib。测地线计算通过geopy库实现，采用WGS-84坐标系。输出文件符合CF规范，采用netCDF4库写入。 致谢：本数据集由格勒诺布尔环境地球科学研究所（Institut des Géosciences de l'Environnement）及第戎生物地球科学研究所（Biogéosciences）的Victoire Buffet、Vincent Favier与Benjamin Pohl开发。 关键词：大气河流；MERRA-2；ARTMIP；IVT；南极；极地气象学 相关资料： 1. ARTMIP格式与Tier-1规范 2. MERRA-2再分析资料文档