Earth system modelling (ESM) is essential for understanding past, present and future Earth
processes. Deep learning (DL), with the data-driven strength of neural networks, has …

Numerous current efforts seek to improve the representation of ecosystem ecology and
vegetation demographic processes within Earth System Models (ESM s). These …

Land surface models (LSMs) are a vital tool for understanding, projecting, and predicting the
dynamics of the land surface and its role within the Earth system, under global change …

An earth system model (MIROC-ESM 2010) is fully described in terms of each model
component and their interactions. Results for the CMIP5 (Coupled Model Intercomparison …

The projected loss of soil carbon to the atmosphere resulting from climate change is a
potentially large but highly uncertain feedback to warming. The magnitude of this feedback …

Stocks of soil organic carbon represent a large component of the carbon cycle that may
participate in climate change feedbacks, particularly on decadal and centennial timescales …

Climate-driven vegetation mortality is occurring globally and is predicted to increase in the
near future. The expected climate feedbacks of regional-scale mortality events have …

The magnitude and evolution of parameters that characterize feedbacks in the coupled
carbon–climate system are compared across nine Earth system models (ESMs). The …

Knowledge of future terrestrial carbon (C) pools and fluxes is based on simulations by
Dynamic Global Vegetation Models (DGVMs; Cox et al., 2000; Sitch et al., 2008). For …

Plant traits–the morphological, anatomical, physiological, biochemical and phenological
characteristics of plants and their organs–determine how primary producers respond to …