BICI-ULL: Bioclimatic indicators dataset for the orographically complex Canary Islands archipelago

Description

BICI−ULL (Bioclimatic Indicators in the Canary Islands by the ULL−GOTA) includes 53 biovariables derived from monthly temperature, precipitation, radiation, humidity, and wind speed averages over different periods calculated through dynamic regionalisation models. This project aims to improve our understanding of climate and its impacts on small, isolated regions with diverse ecosystems, providing valuable insights for the scientific community. The dataset can be found in the ‘Bioclimatic indicators’ folder. It consists of 795 files in NetCDF4 format with a grid cell resolution of 3×3 km, covering the region of the Canary Islands. The files represent 53 bioclimatic indicators calculated in 30-year intervals for the periods: 1980−2009, 2030−2059, and 2070−2099, under the Representative Concentration Pathway (RCP) scenarios RCPs 4.5 and 8.5, for future. The non-hydrostatic WRF model, with boundary conditions from three global models (GFDL−ESM2M, IPSL−CM5A−MR, and MIROC−ESM), was used to perform the simulations. The grid dimensions are (186×77), with a total of 14322 cell points. It covers a longitude range of 18.3◦W to 13.3◦W and a latitude range of 27.5◦N to 29.6◦N, although the biovariables are only computed for land cells. The files comply with the CF conventions for climate and forecast metadata designed to promote the processing and exchange of files created with the netCDF4 Application Programmer Interface. The names associated with each file follow the format: BIOx_model_rcp_yini_yend.nc The raw data from which the biovariables are generated are also available in this repository, in the ‘Raw Data’ folder. These include the standard variables: Mean, maximum, and minimum temperature (TG, TX, TN), precipitation (PR), shortwave downwelling flux (SR), relative humidity (RH), and wind speed (WS). Each file contains 12 timesteps, one for each month (January, February, …). The content of the variables is the mean over the 30-year periods. A specific bias adjustment technique known as the Scaled Distribution Mapping (SDM) algorithm, designed to preserve trends, was used (Switanek et al., 2017). File names follow the format: model_yini_yend_rcp_variable.nc x represents the number of the climatic indicator model makes reference to the driving Global Circulation Model used for the regionalsation simulations. It can be GFDL, IPSL, or MIROC. rcp indicates the forcing scenario, RCP 4.5 or RCP 8.5, or it will be defined as ‘HIST’ in the case of the historical period. yind and yend represent the years of the period, with ini identifying the first year of the period and end identifying the last year. variable refers to the standard variable, which can be TG, TX, TN, PR, SR, RH, WS The main folders contain, in turn, subfolders corresponding to each driving global model, and to the respective period and scenario. The definition of the 53 BICI-ULL bioindicators have been also summarised in the BICI-ULL_bioindicators_definitions.pdf file.

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