scholarly journals The large influence of climate model bias on terrestrial carbon cycle simulations

2017 ◽  
Vol 12 (1) ◽  
pp. 014004 ◽  
Author(s):  
Anders Ahlström ◽  
Guy Schurgers ◽  
Benjamin Smith
Keyword(s):  
Carbon Cycle ◽  
Climate Model ◽  
Model Bias ◽  
Terrestrial Carbon ◽  
Large Influence ◽  
Climate Model Bias ◽  
Terrestrial Carbon Cycle

scholarly journals The African contribution to the global climate-carbon cycle feedback of the 21st century

2010 ◽  
Vol 7 (2) ◽  
pp. 513-519 ◽  
Author(s):  
P. Friedlingstein ◽  
P. Cadule ◽  
S. L. Piao ◽  
P. Ciais ◽  
S. Sitch
Keyword(s):  
Carbon Cycle ◽  
21St Century ◽  
Climate Model ◽  
Global Climate ◽  
Future Climate Change ◽  
Amazon Forest ◽  
Terrestrial Carbon ◽  
Carbon Cycle Model ◽  
Terrestrial Carbon Cycle ◽  
Carbon Balances

Abstract. Future climate change will have impact on global and regional terrestrial carbon balances. The fate of African tropical forests over the 21st century has been investigated through global coupled climate carbon cycle model simulations. Under the SRES-A2 socio-economic CO2 emission scenario of the IPCC, and using the Institut Pierre Simon Laplace coupled ocean-terrestrial carbon cycle and climate model, IPSL-CM4-LOOP, we found that the warming over African ecosystems induces a reduction of net ecosystem productivity, making a 38% contribution to the global climate-carbon cycle positive feedback. Most of this contribution comes from African grasslands, followed by African savannahs, African tropical forest contributing little to the global climate-carbon feedback. However, the vulnerability of the African rainforest ecosystem is quite large. In contrast, the Amazon forest, despite its lower vulnerability, has a much larger overall contribution due to its 6 times larger extent.

scholarly journals Impact of sulphur dioxide on the terrestrial carbon cycle

2019 ◽  
Vol 55 (1) ◽  
pp. 41-53
Author(s):  
A. V. Eliseev ◽  
M. Zhang ◽  
R. D. Gizatullin ◽  
A. V. Altukhova ◽  
Yu. P. Perevedentsev ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Atmospheric Chemistry ◽  
Sulphur Dioxide ◽  
Climate Model ◽  
Transport Model ◽  
Terrestrial Carbon ◽  
Near Surface ◽  
Terrestrial Carbon Cycle ◽  
Academy Of Sciences ◽  
The Impact

In this paper, the earlier results, which were obtained with the climate model developed at the A.M. Obu khov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM) and related to the impact of the atmospheric sulphur dioxide on terrestrial carbon cycle, are elucidated. Because of the unavailability of the global data for near surface SO2 concentration, it was reconstructed by using statistical model which was fitted employing the output of the atmospheric chemistry-transport model RAMS-CMAQ. The obtained results are in general agreement with those reported earlier. In particular, the most significant SO2 impact on terrestrial carbon cycle is simulated for south-east North America and for Europe. However, such impact for south-east Asia is markedly weaker in comparison to that reported earlier, which is related to excessive moisture content in the atmosphere of this region.

scholarly journals Potential strong contribution of future anthropogenic land-use and land-cover change to the terrestrial carbon cycle

2018 ◽  
Vol 13 (6) ◽  
pp. 064023 ◽  
Author(s):  
Benjamin Quesada ◽  
Almut Arneth ◽  
Eddy Robertson ◽  
Nathalie de Noblet-Ducoudré
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Carbon Cycle ◽  
Land Cover Change ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Cycle ◽  
Anthropogenic Land Use

scholarly journals Spatiotemporal patterns of terrestrial carbon cycle during the 20th century

2009 ◽  
Vol 23 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
Shilong Piao ◽  
Philippe Ciais ◽  
Pierre Friedlingstein ◽  
Nathalie de Noblet-Ducoudré ◽  
Patricia Cadule ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
20Th Century ◽  
Spatiotemporal Patterns ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Cycle

scholarly journals Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

2017 ◽  
Author(s):  
Marko Scholze ◽  
Michael Buchwitz ◽  
Wouter Dorigo ◽  
Luis Guanter ◽  
Shaun Quegan
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Full Description ◽  
Model Data ◽  
Terrestrial Carbon ◽  
Carbon Cycle Model ◽  
Terrestrial Carbon Cycle ◽  
Uncertainty Estimates ◽  
Global Carbon

Abstract. The global carbon cycle is an important component of the Earth system and it interacts with the hydrological, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification 5 of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by model-data fusion or data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation, and systematic and 10 well error-characterized observations relevant to the carbon cycle. Relevant observations for assimilation include various in-situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model 15 benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current 20 observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al. (2005) emphasising the rapid advance in relevant space-based observations.

scholarly journals Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño

2020 ◽  
Author(s):  
Lina Teckentrup ◽  
Martin G. De Kauwe ◽  
Andrew J. Pitman ◽  
Benjamin Smith
Keyword(s):  
Carbon Cycle ◽  
El Niño ◽  
El Nino ◽  
Terrestrial Carbon ◽  
Near Surface ◽  
Terrestrial Carbon Cycle ◽  
El Niño Events ◽  
Ep El Niño ◽  
The Impact ◽  
El Nino Events

Abstract. The El Niño‐Southern Oscillation (ENSO) influences the global climate and the variability in the terrestrial carbon cycle on interannual timescales. Two different expressions of El Niño have recently been identified: (i) Central–Pacific (CP) and (ii) Eastern–Pacific (EP). Both types of El Nino are characterised by above average sea surface temperature anomalies in the respective locations. Studies exploring the impact of these expressions of El Niño on the carbon cycle have identified changes in the amplitude of the concentration of interannual atmospheric carbon dioxide (CO2) variability, as well as different lags in terrestrial CO2 release to the atmosphere following increased tropical near surface air temperature. We employ the dynamic global vegetation model LPJ–GUESS within a synthetic experimental framework to examine the sensitivity and potential long term impacts of these two expressions of El Niño on the terrestrial carbon cycle. We manipulated the occurrence of CP and EP events in two climate reanalysis datasets during the later half of the 20th and early 21st century by replacing all EP with CP and separately all CP with EP El Niño events. We found that the different expressions of El Niño affect interannual variability in the terrestrial carbon cycle. However, the effect on longer timescales was negligible for both climate reanalysis datasets. We conclude that capturing any future trends in the relative frequency of CP and EP El Niño events may not be critical for robust simulations of the terrestrial carbon cycle.

Sign in / Sign up

Export Citation Format

Share Document