Simultaneous assimilation of SMOS soil moisture and atmospheric CO2 in-situ observations to constrain the global terrestrial carbon cycle

2016 ◽  
Vol 180 ◽  
pp. 334-345 ◽  
Author(s):  
M. Scholze ◽  
T. Kaminski ◽  
W. Knorr ◽  
S. Blessing ◽  
M. Vossbeck ◽  
...  
2010 ◽  
Vol 2 (1) ◽  
pp. 103-109 ◽  
Author(s):  
Martin Lukac ◽  
Alexandru Milcu ◽  
Dennis Wildman ◽  
Rob Anderson ◽  
Tom Sloan ◽  
...  

2020 ◽  
Author(s):  
Gabriele Messori ◽  
Guiomar Ruiz-Pérez ◽  
Stefano Manzoni ◽  
Giulia Vico

<p>The terrestrial biosphere is a key component of the global carbon cycle and is heavily influenced by climate. This interaction spans a wide range of temporal (from sub-daily to paleoclimatic) and spatial (from local to continental and global) scales and a multitude of bio-physical processes. In part due to this complexity, a comprehensive picture of the physical links and correlations between climate drivers and carbon cycle metrics at different scales remains elusive, framing the scope of this contribution. Here, we specifically explore how precipitation, soil moisture and aggregated climate variability indices relate to the variability of the European terrestrial carbon cycle at sub-daily to interannual scales (i.e. excluding long-term trends). We first discuss broad areas of agreement and disagreement in the literature. For example, while most carbon cycle proxies tend to correlate positively with precipitation, responses to soil moisture and climate indices are more variable. In fact, soil moisture often correlates positively with productivity in water-limited environments, and negatively in light limited ones, or can exhibit nonlinear relations with the carbon cycle proxies. We then conclude by outlining some existing knowledge gaps and by proposing avenues for improving our holistic understanding of the role of climate drivers in modulating the terrestrial carbon cycle.</p>


2020 ◽  
Author(s):  
Mousong Wu ◽  
Marko Scholze ◽  
Fei Jiang ◽  
Hengmao Wang ◽  
Wenxin Zhang ◽  
...  

<p>The terrestrial carbon cycle is an important part of the global carbon budget due to its large gross exchange fluxes with the atmosphere and their sensitivity to climate change. Terrestrial biosphere models show large uncertainties in estimating carbon fluxes, which impacts global carbon budget assessments. The land surface carbon cycle is tightly controlled by soil moisture through plant physiological processes. In this context, accurate soil moisture data will improve the modeling of carbon fluxes in a model-data fusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate 36 years (1980-2015) of surface soil moisture data as provided by the ESA CCI in combination with atmospheric CO<sub>2</sub> concentration observations at global scale. We will present the methods used for assimilating long-term remotely sensed soil moisture into the terrestrial biosphere model, and demonstrate the importance of soil moisture in modeling ecosystem carbon cycle processes. We will also investigate the impacts of soil moisture on the terrestrial carbon cycle during climate extremes at various scales.</p>


2021 ◽  
Author(s):  
David Fairbairn ◽  
Patricia de Rosnay ◽  
Peter Weston

<p>Environmental (e.g. floods, droughts) and weather prediction systems rely on an accurate representation of soil moisture (SM). The EUMETSAT H SAF aims to provide high quality satellite-based hydrological products, including SM.<br>ECMWF is producing ASCAT root zone SM for H SAF. The production relies on an Extended Kalman filter to retrieve root zone SM from surface SM satellite data. A 10 km sampling reanalysis product (1992-2020) forced by ERA5 atmospheric fields (H141/H142) is produced for H SAF, which assimilates ERS/SCAT (1992-2006) and ASCAT-A/B/C (2007-2020) derived surface SM. The root-zone SM performance is validated using sparse in situ observations globally and generally demonstrates a positive and consistent correlation over the period. A negative trend in root-zone SM is found during summer and autumn months over much of Europe during the period (1992-2020). This is consistent with expected climate change impacts and is particularly alarming over the water-scarce Mediterranean region. The recent hot and dry summer of 2019 and dry spring of 2020 are well captured by negative root-zone SM anomalies. Plans for the future H SAF data record products will be presented, including the assimilation of high-resolution EPS-SCA-derived soil moisture data.</p>


2018 ◽  
Vol 13 (6) ◽  
pp. 064023 ◽  
Author(s):  
Benjamin Quesada ◽  
Almut Arneth ◽  
Eddy Robertson ◽  
Nathalie de Noblet-Ducoudré

2009 ◽  
Vol 23 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
Shilong Piao ◽  
Philippe Ciais ◽  
Pierre Friedlingstein ◽  
Nathalie de Noblet-Ducoudré ◽  
Patricia Cadule ◽  
...  

2008 ◽  
Vol 12 (6) ◽  
pp. 1323-1337 ◽  
Author(s):  
C. Albergel ◽  
C. Rüdiger ◽  
T. Pellarin ◽  
J.-C. Calvet ◽  
N. Fritz ◽  
...  

Abstract. A long term data acquisition effort of profile soil moisture is under way in southwestern France at 13 automated weather stations. This ground network was developed in order to validate remote sensing and model soil moisture estimates. In this paper, both those in situ observations and a synthetic data set covering continental France are used to test a simple method to retrieve root zone soil moisture from a time series of surface soil moisture information. A recursive exponential filter equation using a time constant, T, is used to compute a soil water index. The Nash and Sutcliff coefficient is used as a criterion to optimise the T parameter for each ground station and for each model pixel of the synthetic data set. In general, the soil water indices derived from the surface soil moisture observations and simulations agree well with the reference root-zone soil moisture. Overall, the results show the potential of the exponential filter equation and of its recursive formulation to derive a soil water index from surface soil moisture estimates. This paper further investigates the correlation of the time scale parameter T with soil properties and climate conditions. While no significant relationship could be determined between T and the main soil properties (clay and sand fractions, bulk density and organic matter content), the modelled spatial variability and the observed inter-annual variability of T suggest that a weak climate effect may exist.


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