Spatial representation of high latitude soil properties in CMIP5 earth system models
Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in models is a prerequisite for reducing existing uncertainty in predicting carbon-climate feedbacks.
A team of researchers led by Umakant Mishra (EVS) compared the spatial representation and environmental controls of SOC stocks and active-layer thicknesses projected by the Coupled Model Intercomparison Project phase 5 (CMIP5) models with those predicted from geospatial predictions, based on observation data for the state of Alaska. The study found different spatial heterogeneity and environmental controls of active-layer thickness and SOC stocks in model projections in comparison to observations. Prediction errors, when calculated for independent validation sites, were several times larger in model predictions compared to geospatial predictions. Primary factors leading to observed differences were (1) lack of spatial heterogeneity in model predictions, (2) differences in assumptions concerning environmental controls of SOC and active-layer thickness, and (3) the absence of pedogenic processes in model structures.
As model spatial resolution increases and important ecosystem processes are added to include critical soil dynamics in the arctic, our study will provide a spatial benchmark to evaluate model outputs of permafrost-affected systems. Our results should help to reduce uncertainties and improve the capability of models to predict carbon-climate feedbacks of permafrost systems.
This study has been accepted for publication in Geoderma – "Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models," by U. Mishra, B. Drewniak, J.D. Jastrow, R.M. Matamala, and U.W.A. Vitharana (doi: 10.1016/j.geoderma.2016.04.017).