----------------------------------------------------------------------------------------------------------------------- AFRICLIM 3.0: high-resolution ensemble climate projections for Africa ----------------------------------------------------------------------------------------------------------------------- Available at << https://webfiles.york.ac.uk/KITE/AfriClim/ >> and via << http://www.york.ac.uk/environment/research/kite/resources/ >> Contact: environment-kite@york.ac.uk Last updated: July 2015 FOLDER STRUCTURE ~~~~~~~~~~~~~~~~ Highest level: GeoTIFF_[res] Second level: [centre]_[base] for rcm projections africlim_ensemble_v3_[base] for ensemble projections Third level: [rcp] Fourth level: [year] Fifth level: [statistic] [res] Grid resolution in arc-seconds: 30s, 60s, 150s, 300s, 600s [centre] Regional centre (e.g. smhi) or 'baseline' for present-day [base] High-resolution baseline: cru, worldclim, tamsat, chirps [rcp] Representative Concentration Pathway of the IPCC-AR5 (RCP4.5 or RCP8.5) [year] 2055 (mid-century, mean over 2041-2070) or 2085 (late-century, mean over 2071-2100) [statistic] Ensemble statistic: mean, min, max FILE NONMENCLATURE ~~~~~~~~~~~~~~~~~~ Each zip archive contains a set of GeoTIFFs (Int16, UInt16 or Byte), grouped either as sets of months 1-12 (pr, tas, tasmin and tasmax), or as sets of summary variables related to temperature (tbio) or moisture (mbio). Extract the maps using a utility such as PeaZip or 7-Zip. The maps use a geographic coordinate system (WGS1984) which is embedded in the files. File nomenclature is then as follows Present:[var]_[month]_[base][res].tif Future: [var]_[rcp]_[year]_[month]_[gcm]_[rcm]_[base][res].tif [var] Monthly or summary variable (as detailed below) [rcp] Representative Concentration Pathway of the IPCC-AR5 (RCP4.5 or RCP8.5) [year] 2055 (mid-century, mean over 2041-2070) or 2085 (late-century, mean over 2071-2100) [month] 1-12 (monthly sets only) [gcm] Driving GCM (e.g. ICHEC-EC-EARTH) or [statistic] for ensembles [rcm] Regional Climate Model used for dynamically downscaling GCMs to 0.44 decimal degrees (e.g. SMHI-RCA4) [base] High-resolution baseline for change-factor downscaling: cr=CRU, wc=WorldClim, ts=TAMSAT, ch=CHIRPS [res] Grid resolution in arc-seconds: 30s, 60s, 150s, 300s, 600s Monthly variables ***************** [pr] Monthly precipitation (mm, UInt16) [tas] Monthly 2-metre air temperature (C x10, Int16) [tasmax] Monthly average of daily maximum temperature (C x10, Int16) [tasmin] Monthly average of daily minimum temperature (C x10, Int16) Summary variables ***************** Temperature (tbio) [BIO1] Mean annual temperature [1] (C x10, Int16) [BIO2] Mean diurnal range in temp [2] (C x10, Int16) [BIO3] Isothermality [3] (C x10, Int16) [BIO4] Temperature Seasonality [4] (C x10, Int16) [BIO5] Max temp warmest month (C x10, Int16) [BIO6] Min temp coolest month (C x10, Int16) [BIO7] Annual temperature range [5] (C x10, Int16) [BIO10] Mean temp warmest quarter [6] (C x10, Int16) [BIO11] Mean temp coolest quarter [6] (C x10, Int16) [PET] Potential evapotranspiration [7](mm, UInt16) Moisture (mbio) [BIO12] Mean annual rainfall [8] (mm, UInt16) [BIO13] Rainfall wettest month (mm, UInt16) [BIO14] Rainfall driest month (mm, UInt16) [BIO15] Rainfall seasonality [4] (mm, UInt16) [BIO16] Rainfall wettest quarter [6] (mm, UInt16) [BIO17] Rainfall driest quarter [6] (mm, UInt16) [MI] Annual moisture index [9] (x100, UInt16) [MIMQ] Moisture index moist quarter [6](x100, UInt16) [MIAQ] Moisture index arid quarter [6] (x100, UInt16) [DM] Number of dry months [10] (months, Byte) [LLDS] Length of longest dry season [11] (months, Byte) 'BIO' variables correspond to ANUCLIM/WorldClim nomenclature, although derivation for [4] is not identical [1] Mean of monthly means. [2] Mean of monthly (max temp - min temp). [3] 100 × BIO2 / BIO7. [4] Standard deviation over monthly values. [5] BIO5 - BIO6. [6] Any consecutive three-month period. [7] Hargreaves 1985 method. [8] Sum of monthly rainfall. [9] BIO12 / PET. [10] Dry if monthly moisture index < 0.5. [11] Maximum run of consecutive dry months [10,11] Multimodel estimates are given to nearest month. Bimodality in moisture index is given by (DM-LLDS)>1 LINKS ~~~~~ Underlying datasets/repositories - CORDEX: http://cordex.dmi.dk/joomla/ - CRU CL 2.0: http://www.cru.uea.ac.uk/cru/data/hrg/ - WorldClim Version 1.4: http://worldclim.org/ - TAMSAT TARCAT 2.0: http://www.met.reading.ac.uk/~tamsat/ - CHIRPS 1.8: http://chg.geog.ucsb.edu/data/chirps/index.html CITATIONS ~~~~~~~~~ Platts PJ, Omeny PA, Marchant R (2015). AFRICLIM: high-resolution climate projections for ecological applications in Africa. African Journal of Ecology 53, 103-108 Platts PJ, Omeny PA, Marchant R (2015). AFRICLIM 3.0: high-resolution ensemble climate projections for Africa. figshare, doi:10.6084/m9.figshare.1284624