Details
These dataset consists of soil temperature layers calculated by adding monthly soil temperature offsets to monthly air-temperature maps from the CHELSA dataset. These soil temperature layers were then used to calculate annual means, temperature ranges, standard deviation, warmest and coldest months and quarters. Wettest and driest quarters were identified for each pixel based on CHELSA monthly values.
Subdatasets
meanTemperature0to5cm | Mean annual temperature (0-5cm)
meanDurnalRange0to5cm | Mean diurnal range (0-5cm)
isothermality0to5cm | Isothermality, calculated as the mean
diurnal range divided by the annual
amplitude, multiplied by 100 (0-5cm)
amplitude0to5cm | Annual temperature amplitude (0-5cm)
meanColdestQuarter0to5cm | Mean temperature of the coldest 3 months of the year (0-5cm)
meanWarmestQuarter0to5cm | Mean temperature of the warmest 3 months of the year (0-5cm)
meanWettestMonth0to5cm | Mean temperature of the wettest 3 months of the year (0-5cm)
meanDriestMonth0to5cm | Mean temperature of the driest 3 months of the year (0-5cm)
minColdestMonth0to5cm | Minimum temperature of the coldest month of the year (0-5cm)
maxWarmestMonth0to5cm | Maximum temperature of the coldest month of the year (0-5cm)
seasonality0to5cm | Temperature standard deviation (0-5cm)
masDMT query
# data call without specifying subdataset and resolution
list_data("soilClim")
# data call for specific subdataset
list_data("soilClim/meanTemperature0to5cm")
# data call to subdataset with a specific resolution
list_data("soilClim/meanTemperature0to5cm/1km")
References
(bibtex)
[1] Lembrechts, van den
Hoogen, and Aalto (2021)