DOI: 10.5281/zenodo.7340417
title: Detection of Atmospheric Rivers in the Northern Hemisphere based on ERA5 reanalysis data and the IPART algorithm, 1979-2020

description: # 1. Overview This is a catalogue of atmospheric river (AR) detections over the Northern Hemisphere, based on 6-hourly ERA5 reanalysis dataset and the Image-Processing based Atmospheric River Tracking (IPART) algorithm. Time domain of the data: From 1979-Jan-01 to 2020-Dec-31 Temporal resolution is 6-hourly Spatial domain of the data: Northern Hemisphere, land and ocean Spatial resolution is 0.25 * 0.25 degrees latitude/longitude Input data from ERA5 include: Vertical integral of northward water vapour flux, in kg/(m s). Vertical integral of eastward water vapour flux, in kg/(m s). Data in the Northern Hemisphere domain (0 - 90 N), at 0.25 * 0.25 degrees latitude/longitude resolution are obtained from https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5. Version v3.0.8 of the IPART Python module used for detection and tracking of atmospheric rivers is preserved at <strong>10.5281/zenodo.4164826</strong>, available via Creative Commons Attribution 4.0 International license and developed openly at the Github repository https://github.com/ihesp/IPART. # 2. File naming convention The data files are named using the following convention: ar_YYYYMM.nc where: YYYY: 4-digit year number MM: 2-digit month number E.g. `ar_199902.nc` means detections in Feb of 1999. Months are calendar months, including Feb-29th in leap-years. # 3. Data format Data are saved in netCDF format. Each data file contains one 3-dimensional array, of a shape `(t, 360, 1440)`, where: `t`: length of the time dimension. Since data are 6-hourly, t equals 4 * num_of_days_in_month. `360`: latitude dimension, from 0 - 90N, with a 0.25-degree step. `1440`: longitude dimension, from 80 - 440 E (shifted eastward by 80 degrees to put both the Pacific and Atlantic oceans within the domain), with a 0.25-degree step. Each time slice of the data contains maps of the Northern Hemisphere, with integer values in grid cells. Possible values are: 0: meaning no AR is detected in the grid cell. 1, 2, ... ,n: integer labels, each corresponding to the region of an AR entity. # 4. Important parameters in the IPART algorithm Here are the most important parameters used when detecting ARs from ERA5 data using the IPART python module: THR filtering kernel: `[16, 13, 13]`. `16` means 16 time slices, or equivalently 4 days given 6-hourly input data. `13` means 13 grid cells, or equivalently ~325 km, given 0.25 degrees latitude/longitude input data. Note that both of these temporal and spacial lengths are half of the sizes of the filtering kernel. minimum area: `50 * 1e4`, in km^2, minimum size of AR region candidates. maximum area: `1800 * 1e4`, in km^2, maximum size of AR region candidates. minimum L/W: `2.0`, minimum length/width ratio of AR region candiates. minimum length: `2000`, in km, minimum length of AR region candidates. minimum latitude: `20`, minimum latitude of the geometrical centroid of an AR region candidate. maximum latitude: `80`, maximum latitude of the geometrical centroid of an AR region candidate. For more details regarding these parameters, as well as the IPART algorithm, please refer to our published works: Xu, G., Ma, X., Chang, P., and Wang, L.: Image-processing-based atmospheric river tracking method version 1 (IPART-1), Geosci. Model Dev., 13, 4639–4662, https://doi.org/10.5194/gmd-13-4639-2020, 2020. Or the Github repository that houses the IPART module: https://github.com/ihesp/IPART