Climatologies at high resolution for the earth's land surface areas

TL;DR

This paper introduces CHELSA, a high-resolution climate dataset for land surface areas, improving precipitation predictions and aiding ecological and environmental research.

Contribution

The study presents a novel high-resolution climate dataset derived from downscaled reanalysis data, with improved precipitation modeling and validation against existing datasets.

Findings

CHELSA provides accurate temperature and precipitation climatologies at 30 arc seconds resolution.

Precipitation predictions from CHELSA outperform other standard datasets.

Using CHELSA enhances species distribution modeling accuracy.

Abstract

High resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA Climatologies at high resolution for the earths land surface areas data of downscaled model output temperature and precipitation estimates of the ERA Interim climatic reanalysis to a high resolution of 30 arc seconds. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979 to 2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature but that its predictions of precipitation patterns are better.