Version 3 of the Global Aridity Index and Potential Evapotranspiration Database

Abstract

The “Global Aridity Index and Potential Evapotranspiration Database - Version 3” (Global-AI_PET_v3) provides high-resolution (30 arc-seconds) global hydro-climatic data averaged (1970–2000) monthly and yearly, based upon the FAO Penman-Monteith Reference Evapotranspiration (ET0) equation. An overview of the methods used to implement the Penman-Monteith equation geospatially and a technical evaluation of the results is provided. Results were compared for technical validation with weather station data from the FAO “CLIMWAT 2.0 for CROPWAT” (ET0: r2 = 0.85; AI: r2 = 0.90) and the U.K. “Climate Research Unit: Time Series v 4.04” (ET0: r2 = 0.89; AI: r2 = 0.83), while showing significant differences to an earlier version of the database. The current version of the Global-AI_PET_v3 supersedes previous versions, showing a higher correlation to real world weather station data. Developed using the generally agreed upon standard methodology for estimation of reference ET0, this database and notably, the accompanying source code, provide a robust tool for a variety of scientific applications in an era of rapidly changing climatic conditions.

The Ecosystem Integrity Index: a novel measure of terrestrial ecosystem integrity

“…Model selection was undertaken using backwards stepwise selection based on AIC values (Zuur, 2009). Variables were selected for testing based on a literature review of likely predictors of NPP and included: latitude, bioclimatic variables (Fick and Hijmans, 2017), mean, min and max solar radiation (Fick and Hijmans, 2017); aridity (Global Aridity Index, Zomer and Trabucco, 2022); total nitrogen, cation exchange capacity, predicted sand concentration, pH of water in soil (Poggio et al ., 2021); continuous heatinsolation load index (CHILI, Theobald et al ., 2015); roughness of terrain, slope, topographic position index, terrain ruggedness index (Amatulli et al ., 2018); landforms (Sayre et al ., 2020). The final model structure included latitude as an interaction with total annual precipitation, mean annual temperature, and the mean temperature of the coldest quarter.…”

Global climate-related predictors at kilometer resolution for the past and future

“…In addition to station measurements, we compared CHELSA-BIOCLIM+ variables to gridded data from station-based interpolation and from a weather research and forecasting (WRF) model simulation. Gridded data from station-based interpolations originated or were built from WorldClim v2.0 (Fick and Hijmans, 2017) and from the Global Aridity Index and Potential Evapotranspiration Database version 3 (Zomer et al, 2022) and had a global coverage and spatial resolution of 30 arcsec. We calculated annual climatologies from WorldClim's monthly wind speed and solar-radiation climatologies and from the monthly climatology of Global-AI_PET's potential evapotranspiration.…”

Distribution of graminoids in open habitats in Tajikistan and Kyrgyzstan

“…Based on the coordinates, we derived the mean annual temperature and the sum of annual precipitation from the CHELSA dataset, with a resolution of 0.00833 decimal degrees (30 arc sec; Karger et al 2017aKarger et al , 2017b. Global Aridity Index (hereinafter referred to as Aridity Index) was obtained from the Global-PET geospatial dataset available on the CGIAR-CSI GeoPortal (Zomer et al 2022). Aridity Index values are unitless and decrease with more arid conditions (Zomer et al 2022).…”

“…Global Aridity Index (hereinafter referred to as Aridity Index) was obtained from the Global-PET geospatial dataset available on the CGIAR-CSI GeoPortal (Zomer et al 2022). Aridity Index values are unitless and decrease with more arid conditions (Zomer et al 2022). Livestock density data were obtained from the Gridded Livestock of the World database at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator) (GLW v3.1; Gilbert et al 2018).…”