CHELSA_2.1: Documentation for _CHELSA 2.1_
In EvolEcolGroup/pastclim: Manipulate Time Series of Palaeoclimate Reconstructions
CHELSA_2.1 R Documentation
Documentation for CHELSA 2.1
Description
CHELSA version 2.1 is a database of high spatial resolution global weather and
climate data, covering both the present and future projections.
Details
IMPORTANT: If you use this dataset, make sure to cite the original publication
for the CHELSA dataset:
Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H.,
Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017)
Climatologies at high resolution for the Earth land surface areas.
Scientific Data. 4 170122. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/sdata.2017.122")}
Present-day reconstructions are based on the mean for the period 1981-2000
and are available at at the high resolution of 0.5 arc-minutes (CHELSA_2.1_0.5m).
In pastclim, the datasets are given
a date of 1990 CE (the mid-point of the period of interest). There are 19 “bioclimatic” variables, as well as monthly
estimates for mean temperature, and precipitation. The dataset is very large, as it
includes estimates for the oceans as well as the land masses. An alternative to
downloading the very large files is to use virtual rasters, which allow the
data to remain on the server, with only the pixels required for a given operation
being downloaded. Virtual rasters can be used by choosing (CHELSA_2.1_0.5m_vsi)
Future projections are based on the models in CMIP6, downscaled and de-biased
using the CHELSA algorithm 2.1. Monthly values of mean temperature,
and total precipitation, as well as 19 bioclimatic
variables were processed for
5 global climate models (GCMs), and for three
Shared Socio-economic Pathways (SSPs): 126, 370 and 585. Model and
SSP can be chosen by changing the ending of the dataset name
CHELSA_2.1_GCM_SSP_RESm.
Available values for GCM are: "GFDL-ESM4", "IPSL-CM6A-LR", "MPI-ESM1-2-HR",
"MRI-ESM2-0", and "UKESM1-0-LL". For SSP, use: "ssp126",
"ssp370", and "ssp585". RES is currently limited to "0.5m". Example dataset names are
CHELSA_2.1_GFDL-ESM4_ssp126_0.5m and CHELSA_2.1_UKESM1-0-LL_ssp370_0.5m
As for present reconstructions, an alternative to
downloading the very large files is to use virtual rasters. Simply append
"_vis" to the name of the dataset of interest (CHELSA_2.1_GFDL-ESM4_ssp126_0.5m_vsi).
The dataset are averages over 30 year
periods (2011-2040, 2041-2070, 2071-2100).
In pastclim, the midpoints of the periods (2025, 2055, 2075) are used as the time stamps. All 3 periods
are automatically downloaded for each combination of GCM model and SSP, and are selected
as usual by defining the time in functions such as region_slice().
EvolEcolGroup/pastclim documentation built on June 30, 2024, 1:26 a.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| CHELSA_2.1 | R Documentation |
Documentation for CHELSA 2.1
Description
CHELSA version 2.1 is a database of high spatial resolution global weather and climate data, covering both the present and future projections.
Details
IMPORTANT: If you use this dataset, make sure to cite the original publication for the CHELSA dataset:
Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017) Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/sdata.2017.122")}
Present-day reconstructions are based on the mean for the period 1981-2000
and are available at at the high resolution of 0.5 arc-minutes (CHELSA_2.1_0.5m).
In pastclim, the datasets are given
a date of 1990 CE (the mid-point of the period of interest). There are 19 “bioclimatic” variables, as well as monthly
estimates for mean temperature, and precipitation. The dataset is very large, as it
includes estimates for the oceans as well as the land masses. An alternative to
downloading the very large files is to use virtual rasters, which allow the
data to remain on the server, with only the pixels required for a given operation
being downloaded. Virtual rasters can be used by choosing (CHELSA_2.1_0.5m_vsi)
Future projections are based on the models in CMIP6, downscaled and de-biased using the CHELSA algorithm 2.1. Monthly values of mean temperature, and total precipitation, as well as 19 bioclimatic variables were processed for 5 global climate models (GCMs), and for three Shared Socio-economic Pathways (SSPs): 126, 370 and 585. Model and SSP can be chosen by changing the ending of the dataset name CHELSA_2.1_GCM_SSP_RESm.
Available values for GCM are: "GFDL-ESM4", "IPSL-CM6A-LR", "MPI-ESM1-2-HR", "MRI-ESM2-0", and "UKESM1-0-LL". For SSP, use: "ssp126", "ssp370", and "ssp585". RES is currently limited to "0.5m". Example dataset names are CHELSA_2.1_GFDL-ESM4_ssp126_0.5m and CHELSA_2.1_UKESM1-0-LL_ssp370_0.5m
As for present reconstructions, an alternative to downloading the very large files is to use virtual rasters. Simply append "_vis" to the name of the dataset of interest (CHELSA_2.1_GFDL-ESM4_ssp126_0.5m_vsi).
The dataset are averages over 30 year
periods (2011-2040, 2041-2070, 2071-2100).
In pastclim, the midpoints of the periods (2025, 2055, 2075) are used as the time stamps. All 3 periods
are automatically downloaded for each combination of GCM model and SSP, and are selected
as usual by defining the time in functions such as region_slice().
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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