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      Systematic Underestimation of Canopy Conductance Sensitivity to Drought by Earth System Models

      1 , 2 , 3 , 4 , 5 , 2 , 6
      AGU Advances
      American Geophysical Union (AGU)

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          Abstract

          The response of vegetation canopy conductance ( g c ) to changes in moisture availability () is a major source of uncertainty in climate projections. While vegetation typically reduces stomatal conductance during drought, accurately modeling how and to what degree stomata respond to changes in moisture availability at global scales is particularly challenging, because no global scale g c observations exist. Here, we leverage a collection of satellite, reanalysis and station‐based near‐surface air and surface temperature estimates, which are physically and statistically linked to due to the local cooling effect of g c through transpiration, to develop a novel emergent constraint of in an ensemble of Earth System Models (ESMs). We find that ESMs systematically underestimate by ∼33%, particularly in grasslands, croplands, and savannas in semi‐arid and bordering regions of the Central United States, Central Europe, Southeastern South America, Southern Africa, Eastern Australia, and parts of East Asia. We show that this underestimation occurs because ESMs inadequately reduce g c when soil moisture decreases. As g c controls carbon, water and energy fluxes, the misrepresentation of modeled contributes to biases in ESM projections of gross primary production, transpiration, and temperature during droughts. Our results suggest that the severity and duration of droughts may be misrepresented in ESMs due to the impact of sustained g c on both soil moisture dynamics and the biosphere‐atmosphere feedbacks that affect local temperatures and regional weather patterns.

          Plain Language Summary

          During photosynthesis, plants open their stomata to take in carbon dioxide and inevitably, lose water through transpiration. As a result, when soil moisture is low, plants reduce their stomatal apertures to conserve water, simultaneously reducing their carbon dioxide uptake. It is critical for Earth System Models (ESMs) to incorporate accurate vegetation responses to moisture availability to make accurate future climate projections. Here, we show that these ESMs are systematically underestimating the sensitivity of vegetation to moisture availability, and that this underestimation is leading to incorrect climate projections of carbon, water, and energy fluxes during droughts.

          Key Points

          • Earth System Models (ESMs) underestimate the sensitivity of canopy conductance to changes in moisture availability

          • The underestimation is greatest in semi‐arid and bordering regions with temperatures between 5 and 25°C and leaf area index over 1

          • This misrepresentation leads to errors in ESM projections of carbon, water, and energy fluxes during drought

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          Most cited references66

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          WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas

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            Natural Evaporation from Open Water, Bare Soil and Grass

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              Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset

              CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5° latitude by 0.5° longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901–2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically.
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                Author and article information

                Contributors
                Journal
                AGU Advances
                AGU Advances
                American Geophysical Union (AGU)
                2576-604X
                2576-604X
                February 2024
                January 04 2024
                February 2024
                : 5
                : 1
                Affiliations
                [1 ] Department of Environmental Science University of Arizona Tucson AZ USA
                [2 ] Department of Environmental Science, Policy, and Management University of California, Berkeley Berkeley CA USA
                [3 ] Sino‐French Institute for Earth System Science College of Urban and Environmental Sciences Peking University Beijing China
                [4 ] Department of Geography National University of Singapore Singapore Singapore
                [5 ] Center for Nature‐based Climate Solutions National University of Singapore Singapore Singapore
                [6 ] Climate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA USA
                Article
                10.1029/2023AV001026
                7745b68c-d02c-4b7f-8e8f-1624f553e18e
                © 2024

                http://creativecommons.org/licenses/by-nc/4.0/

                http://creativecommons.org/licenses/by-nc/4.0/

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