500m gridded historical and future climate surfaces for Risaralda, Colombia
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The gridded yearly climate data (5-year moving averages) were developed from weather station observations (from IDEAM and Cenicafe) for the period 1980 to 2010, at 500 m spatial resolution, for monthly precipitation, monthly minimum temperature and maximum temperature, following the method of Hijmans et al. (2005). In areas with low station density and low interpolaton quality, weather observations were complemented with pseudo-stations from AgMERRA for temperature (Ruane et al., 2015) and CHIRPS (Funk et al., 2015) for precipitation. The results were aggregated into decadal and 30-yr climatology data. Future climate data was developed by downscaling CMIP5 projections from 14 General Circulation Models (GCMs) for all four RCPs (RCP 2.6, 4.5, 6.0 and 8.5; IPCC, 2013) following the method of Ramirez-Villegas and Jarvis (2010). Data were fo' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Agroclimatic indices","Climate change","Decision and Policy Analysis - DAPA","Downscaling","Latin America and the Caribbean","Maximum temperature","Minimum temperature","Precipitation","Weather stations"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The gridded yearly climate data (5-year moving averages) were developed from weather station observations (from IDEAM and Cenicafe) for the period 1980 to 2010, at 500 m spatial resolution, for monthly precipitation, monthly minimum temperature and maximum temperature, following the method of Hijmans et al. (2005). In areas with low station density and low interpolaton quality, weather observations were complemented with pseudo-stations from AgMERRA for temperature (Ruane et al., 2015) and CHIRPS (Funk et al., 2015) for precipitation. The results were aggregated into decadal and 30-yr climatology data. Future climate data was developed by downscaling CMIP5 projections from 14 General Circulation Models (GCMs) for all four RCPs (RCP 2.6, 4.5, 6.0 and 8.5; IPCC, 2013) following the method of Ramirez-Villegas and Jarvis (2010). Data were fo' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The gridded yearly climate data (5-year moving averages) were developed from weather station observations (from IDEAM and Cenicafe) for the period 1980 to 2010, at 500 m spatial resolution, for monthly precipitation, monthly minimum temperature and maximum temperature, following the method of Hijmans et al. (2005). In areas with low station density and low interpolaton quality, weather observations were complemented with pseudo-stations from AgMERRA for temperature (Ruane et al., 2015) and CHIRPS (Funk et al., 2015) for precipitation. The results were aggregated into decadal and 30-yr climatology data. Future climate data was developed by downscaling CMIP5 projections from 14 General Circulation Models (GCMs) for all four RCPs (RCP 2.6, 4.5, 6.0 and 8.5; IPCC, 2013) following the method of Ramirez-Villegas and Jarvis (2010). Data were fo
Agroclimatic indices; Climate change; Decision and Policy Analysis - DAPA; Downscaling; Latin America and the Caribbean; Maximum temperature; Minimum temperature; Precipitation; Weather stations