Tao Wang


2019

DOI bib
Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization
Yongwen Liu, Shilong Piao, Thomas Gasser, Philippe Ciais, Hui Yang, Han Wang, Trevor F. Keenan, Mengtian Huang, Shiqiang Wan, Jian Song, Kai Wang, Ivan A. Janssens, Josep Peñuelas, Chris Huntingford, Xuhui Wang, M. Altaf Arain, Yuanyuan Fang, Joshua B. Fisher, Maoyi Huang, D. N. Huntzinger, Akihiko Ito, Atul K. Jain, Jiafu Mao, A. M. Michalak, Changhui Peng, Benjamin Poulter, Christopher R. Schwalm, Xiaoying Shi, Hanqin Tian, Yaxing Wei, Ning Zeng, Qiuan Zhu, Tao Wang
Nature Geoscience, Volume 12, Issue 10

Clarifying how increased atmospheric CO2 concentration (eCO2) contributes to accelerated land carbon sequestration remains important since this process is the largest negative feedback in the coupled carbon–climate system. Here, we constrain the sensitivity of the terrestrial carbon sink to eCO2 over the temperate Northern Hemisphere for the past five decades, using 12 terrestrial ecosystem models and data from seven CO2 enrichment experiments. This constraint uses the heuristic finding that the northern temperate carbon sink sensitivity to eCO2 is linearly related to the site-scale sensitivity across the models. The emerging data-constrained eCO2 sensitivity is 0.64 ± 0.28 PgC yr−1 per hundred ppm of eCO2. Extrapolating worldwide, this northern temperate sensitivity projects the global terrestrial carbon sink to increase by 3.5 ± 1.9 PgC yr−1 for an increase in CO2 of 100 ppm. This value suggests that CO2 fertilization alone explains most of the observed increase in global land carbon sink since the 1960s. More CO2 enrichment experiments, particularly in boreal, arctic and tropical ecosystems, are required to explain further the responsible processes. The northern temperate carbon sink is estimated to increase by 0.64 PgC each year for each increase in atmospheric CO2 concentrations by 100 ppm, suggests an analysis of data from field experiments at 7 sites constraints.

2018

DOI bib
ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks
Gerhard Krinner, Chris Derksen, Richard Essery, M. Flanner, Stefan Hagemann, Martyn P. Clark, Alex Hall, Helmut Rott, Claire Brutel‐Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad W. Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, F. Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy M. Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, R. M. Law, David M. Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, О. Н. Насонова, Tomoko Nitta, Michio Niwano, John W. Pomeroy, M. S. Raleigh, Gerd Schaedler, В. А. Семенов, Tanya Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, Dan Zhu
Geoscientific Model Development, Volume 11, Issue 12

Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).