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      Soil moisture dominates dryness stress on ecosystem production globally

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          Abstract

          Dryness stress can limit vegetation growth and is often characterized by low soil moisture (SM) and high atmospheric water demand (vapor pressure deficit, VPD). However, the relative role of SM and VPD in limiting ecosystem production remains debated and is difficult to disentangle, as SM and VPD are coupled through land-atmosphere interactions, hindering the ability to predict ecosystem responses to dryness. Here, we combine satellite observations of solar-induced fluorescence with estimates of SM and VPD and show that SM is the dominant driver of dryness stress on ecosystem production across more than 70% of vegetated land areas with valid data. Moreover, after accounting for SM-VPD coupling, VPD effects on ecosystem production are much smaller across large areas. We also find that SM stress is strongest in semi-arid ecosystems. Our results clarify a longstanding question and open new avenues for improving models to allow a better management of drought risk.

          Abstract

          Dryness stresses vegetation and can lead to declines in productivity, increased emission of carbon, and plant mortality, but the drivers of this stress remain unclear. Here the authors show that soil moisture plays a dominant role relative to atmospheric water demand over most global land vegetated areas.

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          The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)

          The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) is the latest atmospheric reanalysis of the modern satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO). MERRA-2 assimilates observation types not available to its predecessor, MERRA, and includes updates to the Goddard Earth Observing System (GEOS) model and analysis scheme so as to provide a viable ongoing climate analysis beyond MERRA’s terminus. While addressing known limitations of MERRA, MERRA-2 is also intended to be a development milestone for a future integrated Earth system analysis (IESA) currently under development at GMAO. This paper provides an overview of the MERRA-2 system and various performance metrics. Among the advances in MERRA-2 relevant to IESA are the assimilation of aerosol observations, several improvements to the representation of the stratosphere including ozone, and improved representations of cryospheric processes. Other improvements in the quality of MERRA-2 compared with MERRA include the reduction of some spurious trends and jumps related to changes in the observing system, and reduced biases and imbalances in aspects of the water cycle. Remaining deficiencies are also identified. Production of MERRA-2 began in June 2014 in four processing streams, and converged to a single near-real time stream in mid 2015. MERRA-2 products are accessible online through the NASA Goddard Earth Sciences Data Information Services Center (GES DISC).
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            Updated high-resolution grids of monthly climatic observations - the CRU TS3.10 Dataset

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              A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions

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                Author and article information

                Contributors
                laibao.liu@env.ethz.ch
                sonia.seneviratne@ethz.ch
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                29 September 2020
                29 September 2020
                2020
                : 11
                : 4892
                Affiliations
                [1 ]GRID grid.5801.c, ISNI 0000 0001 2156 2780, Institute for Atmospheric and Climate Science, , ETH Zurich, ; Zurich, Switzerland
                [2 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, College of Urban and Environmental Sciences, , Peking University, ; Beijing, China
                Author information
                http://orcid.org/0000-0001-9140-0509
                http://orcid.org/0000-0003-3539-8621
                http://orcid.org/0000-0002-0057-4878
                http://orcid.org/0000-0001-9528-2917
                Article
                18631
                10.1038/s41467-020-18631-1
                7524720
                32994398
                b939ec9a-16d5-4751-aa94-a07a56d8770e
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 December 2019
                : 19 August 2020
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                © The Author(s) 2020

                Uncategorized
                atmospheric dynamics,ecosystem ecology
                Uncategorized
                atmospheric dynamics, ecosystem ecology

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