| Summary: | This is a data set of monthly averaged variables simulated by the hydrostatic regional atmospheric climate model RACMO2.3p2 over the Antarctic Peninsula. At the lateral and ocean boundaries the model is forced by ERA-Interim reanalysis data every 6 hours from January 1979 to August 2019. After August 2019, the model is forced by ERA5 reanalyses every 3 hours, with an overlap from 2016, to December 2022. The model is run at a horizontal resolution of 5.5 km and 40 vertical levels for the Antarctic Peninsula domain, which, after 2018, constitutes an update of the simulation forced from 1979-2018 by ERA-Interim reported in van Wessem et al., 2018. Upper air relaxation of wind, humidity and temperature is not active for this domain. This version of the model is specifically applied to the polar regions by interactive coupling to a multilayer snow model that calculates melt, refreezing, percolation and runoff of meltwater (Ettema et al., 2010). In addition, snow albedo is calculated through a prognostic scheme for snow grain size (Kuipers Munneke et al., 2011) while a drifting snow scheme simulates the interaction of the near-surface air with drifting snow (Lenaerts et al., 2010). This dataset is provided on a rotated polar coordinate grid. In such a rotated pole projection the grid is defined over the equator and then rotated to the area of interest. One of the advantages is that the grid distance can be defined in fraction of degrees, which results in near equidistant grid cells as long as the domain is small enough, and provides the most accurate model calculations. However, re-projecting these data on other grids is often troublesome, as after rotation the grid is non-equidistant and most software packages cannot directly handle this. Stef Lhermitte provided a nice solution for reprojecting the RACMO data on his gitlab-page: https://gitlab.tudelft.nl/slhermitte/manuals/blob/master/RACMO_reproject.md. The dataset includes the following surface- and atmospheric variables. Additional variables and higher temporal ...
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