
Separation of the Effects of Land and Climate Model Errors on Simulated Contemporary Land Carbon Cycle Trends in the MPI Earth System Model version 1*
Author(s) -
Daniela Dalmonech,
Sönke Zaehle,
Gregor Schürmann,
Victor Brovkin,
Christian H. Reick,
Reiner Schnur
Publication year - 2014
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli-d-13-00593.1
Subject(s) - earth system science , environmental science , climate model , climatology , carbon cycle , greenhouse gas , climate change , climate sensitivity , atmosphere (unit) , productivity , water cycle , atmospheric sciences , transient climate simulation , precipitation , downscaling , meteorology , ecosystem , geography , ecology , geology , macroeconomics , economics , biology
The capacity of Earth System Models (ESMs) to make reliable projections of future atmospheric CO2 and climate is strongly dependent on the ability of the land surface model to adequately simulate the land carbon (C) cycle. Defining "adequate" performance of the land model requires an understanding of the contributions of climate model and land model errors to the land C cycle. Here, we apply a benchmarking framework based on significant, observed characteristics of the land C cycle for the contemporary period, for which sufficient evaluation data are available, to test the ability of the JSBACH land surface component of the MPI Earth System Model (MPI-ESM), to simulate land C trends. We give particular attention to the role of potential effects caused by climate biases and therefore investigate the results of model configurations in which JSBACH is interactively "coupled" to atmosphere and ocean components, and an "uncoupled" configuration, where JSBACH is driven by reconstructed meteorology. The ability of JSBACH to simulate the observed phase of phenology and seasonal C fluxes is not strongly affected by climate biases. Contrarily, noticeable differences in the simulated gross primary productivity and land C stocks emerge between coupled and uncoupled configurations, leading to significant differences in the decadal terrestrial C balance, and its sensitivity to climate. These differences are strongly controlled by climate biases of the MPI-ESM, in particular those affecting soil moisture. To effectively characterize model performance, the potential effects of climate biases on the land C dynamics need to be considered during the development and calibration of land surface models