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      Mass-conserving coupling of total column CO<sub>2</sub> (XCO<sub>2</sub>) from global to mesoscale models: Case study with CMS-Flux inversion system and WRF-Chem (v3.6.1)

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          Abstract

          <p><strong>Abstract.</strong> Quantifying the uncertainty of inversion-derived fluxes and attributing the uncertainty to errors in either flux or transport continue to be challenges in the characterization of surface sources and sinks of carbon dioxide (CO<sub>2</sub>). It is also not clear if fluxes inferred in a coarse-resolution global system will remain optimal in a higher-resolution modeling environment. Here we present an off-line coupling of the mesoscale Weather Research and Forecasting (WRF) model to optimized biogenic CO<sub>2</sub> fluxes and mole fractions from the global Carbon Monitoring System inversion system (CMS-Flux). The coupling framework consists of methods to constrain the mass of CO<sub>2</sub> introduced into WRF, effectively nesting our North American domain within the global model. We test the coupling by simulating Greenhouse gases Observing SATellite (GOSAT) column-averaged dry-air mole fractions (XCO<sub>2</sub>) over North American for 2010. We find mean model-model differences in summer of ~<span class="thinspace"></span>0.12<span class="thinspace"></span>ppm. While 85<span class="thinspace"></span>% of the XCO<sub>2</sub> values are due to long-range transport from outside our North American domain, most of the model-model differences appear to be due to transport differences in the fraction of the troposphere below 850<span class="thinspace"></span>hPa. The framework methods can be used to couple other global model inversion results to WRF for further study using different boundary layer and transport parameterizations.</p>

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          Author and article information

          Journal
          Geoscientific Model Development Discussions
          Geosci. Model Dev. Discuss.
          Copernicus GmbH
          1991-962X
          February 01 2019
          : 1-35
          Article
          10.5194/gmd-2018-342
          da990e90-2f65-437c-a1ef-5021710bba64
          © 2019

          https://creativecommons.org/licenses/by/4.0/

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