Methods. WorldClim Paper abstract bibtex [Excerpt] For a complete description, see: [\n] Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978. [\n] The data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as "1 km2" resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables. [\n] The WorldClim interpolated climate layers were made using: [::] Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others. [::] The SRTM elevation database (aggregeated to 30 arc-seconds, "1 km") [::] The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.
@article{worldclimMethods2015,
title = {Methods},
author = {{WorldClim}},
date = {2015},
url = {http://mfkp.org/INRMM/article/13768029},
abstract = {[Excerpt] For a complete description, see:
[\textbackslash n] Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.
[\textbackslash n] The data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as "1 km2" resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.
[\textbackslash n] The WorldClim interpolated climate layers were made using:
[::] Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others. [::] The SRTM elevation database (aggregeated to 30 arc-seconds, "1 km") [::] The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13768029,global-scale,modelling,open-data,worldclim}
}
Downloads: 0
{"_id":"Ygd57MqyqHWanJaWe","bibbaseid":"worldclim-methods","authorIDs":[],"author_short":["WorldClim"],"bibdata":{"bibtype":"article","type":"article","title":"Methods","author":[{"firstnames":[],"propositions":[],"lastnames":["WorldClim"],"suffixes":[]}],"date":"2015","url":"http://mfkp.org/INRMM/article/13768029","abstract":"[Excerpt] For a complete description, see: [\\n] Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978. [\\n] The data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as \"1 km2\" resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables. [\\n] The WorldClim interpolated climate layers were made using: [::] Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others. [::] The SRTM elevation database (aggregeated to 30 arc-seconds, \"1 km\") [::] The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","keywords":"*imported-from-citeulike-INRMM,~INRMM-MiD:c-13768029,global-scale,modelling,open-data,worldclim","bibtex":"@article{worldclimMethods2015,\n title = {Methods},\n author = {{WorldClim}},\n date = {2015},\n url = {http://mfkp.org/INRMM/article/13768029},\n abstract = {[Excerpt] For a complete description, see:\n\n[\\textbackslash n] Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\n\n[\\textbackslash n] The data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as \"1 km2\" resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\n\n[\\textbackslash n] The WorldClim interpolated climate layers were made using:\n\n[::] Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others. [::] The SRTM elevation database (aggregeated to 30 arc-seconds, \"1 km\") [::] The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.},\n keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13768029,global-scale,modelling,open-data,worldclim}\n}\n\n","author_short":["WorldClim"],"key":"worldclimMethods2015","id":"worldclimMethods2015","bibbaseid":"worldclim-methods","role":"author","urls":{"Paper":"http://mfkp.org/INRMM/article/13768029"},"keyword":["*imported-from-citeulike-INRMM","~INRMM-MiD:c-13768029","global-scale","modelling","open-data","worldclim"],"downloads":0},"bibtype":"article","biburl":"https://tmpfiles.org/dl/58794/INRMM.bib","creationDate":"2020-07-02T22:41:33.816Z","downloads":0,"keywords":["*imported-from-citeulike-inrmm","~inrmm-mid:c-13768029","global-scale","modelling","open-data","worldclim"],"search_terms":["methods","worldclim"],"title":"Methods","year":null,"dataSources":["DXuKbcZTirdigFKPF"]}