Sets of reference grids#

Several reference grids (with 0.5° 1°, and 2° spatial resolution) are used in the Atlas to interpolate CORDEX, CMIP5 and CMIP6 ensembles to common regular grids (also 0.25° for regional observations and EURO-CORDEX). Some datasets produced using these masks are:

  • land sea masks: land_sea_mask_*.nc4

  • mountain ranges masks: mountain_ranges_mask_*.nc4

A Jupyter notebook illustrating a simple example of their use in R is provided in notebooks. The figure below represents these masks for the 0.5°, 1°, and 2° resolutions.

Land-sea masks#

The land-sea masks for the 0.5°, 1°, and 2° grids are produced using the land-sea mask of the [ESSD - WFDE5: Bias-Adjusted ERA5 Reanalysis Data for Impact Studies] dataset (ERA5 bias adjusted, file [Near Surface Meteorological Variables from 1979 to 2019 Derived from Bias-Corrected Reanalysis]). The coarser 1° and 2° grids are produced upscaling the 0.5° grid and using a ≥0.5 threshold for land/sea ratio in the resulting gridboxes. The 0.25° grid is obtained from the [ERA5 Hourly Data on Single Levels from 1959 to Present] grid (land-sea mask), considering the same threshold (0.5) for land/sea ratio.

Mountain-ranges masks#

The mountain ranges masks (0.5°, 1°, and 2°) have been defined using the K1 global mountains GIS datalayer ([Rmgsc.Cr.Usgs.Gov - /Outgoing/Ecosystems/Global/]; file: GlobalMountainsK1Binary.zip; Kapos et al. 2000). The raster is based on 1 km DEM and has been upscaled to 0.5° using a 0.75 threshold for mountain area extent within the gridbox. The 2° and 1° masks are upscaled versions of the 0.5° grid considering a 0.5 threshold for mountain area extent within the gridbox to better match the mountain areas in the different resolution grids.

Special masks#

Includes auxiliary masks used to filter out gridboxes with no observational data (infilled with distintant station values) for different observational datasets used in the Interactive Atlas [IPCC WGI Interactive Atlas].

References#

Dev

Developing a map of the world's mountain forests. https://www.cabdirect.org/cabdirect/abstract/20000613977.

Sur

Near surface meteorological variables from 1979 to 2019 derived from bias-corrected reanalysis. https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.20d54e34?tab=overview.

Rmg

Rmgsc.cr.usgs.gov - /outgoing/ecosystems/Global/. https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/.

ERA

ERA5 hourly data on single levels from 1959 to present. https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview.

ESS

ESSD - WFDE5: bias-adjusted ERA5 reanalysis data for impact studies. https://essd.copernicus.org/articles/12/2097/2020/.

IPC

IPCC WGI Interactive Atlas. https://interactive-atlas.ipcc.ch/regional-information#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.

[Developing a Map of the World's Mountain Forests., n.d.]