Terrestrial Earth couple climate–carbon spatial variability and uncertainty

Abstract

Underlying patterns of varied and rapidly changing weather phenomena characterized the atmospheric environment of Earth regions and Earth as a whole. Simplified models for the Thornthwaite moisture index estimation based on precipitation and evapotranspiration were developed. Geostatistics was used to characterize spatial patterns of the terrestrial Earth climates using the structure of covariance between the moisture index and net primary production (NPP) or gross primary production (GPP) derived from the MODerate Resolution Imaging Spectroradiometer sensor (MODIS) data products. Global terrestrial snow cover information was used to differentiate climates of the Earth Northern and Southern hemispheres. Two moisture index models were implemented globally using Thornthwaite evapotranspiration derived from high resolution temperature and the evapotranspiration derived from the MODIS data products. The inclusion of NPP or GPP in the climate models, improved the prediction of the moisture index in the terrestrial Earth, with better application of the models with NPP. Regions with higher error values in the Earth indicated random climate conditions and major difficult for climate spatial prediction. The moisture index model using Thornthwaite evapotranspiration determined less dry climates when compared to the moisture index model using Penman–Monteith evapotranspiration.