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Simulating satellite observations of sea surface temperature and chlorophyll in CESM2 to assess model and sampling bias
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  • Genevieve Clow,
  • Nicole Suzanne Lovenduski,
  • Michael N Levy,
  • Keith Lindsay,
  • Jennifer E Kay,
  • Isaac Davis,
  • Brian Medieros
Genevieve Clow
University of Colorado Boulder

Corresponding Author:genevieve.clow@colorado.edu

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Nicole Suzanne Lovenduski
University of Colorado Boulder
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Michael N Levy
National Center for Atmospheric Research (UCAR)
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Keith Lindsay
National Center for Atmospheric Research (UCAR)
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Jennifer E Kay
University of Colorado Boulder
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Isaac Davis
National Center for Atmospheric Research
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Brian Medieros
National Center for Atmospheric Research (UCAR)
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Abstract

Satellite observations of SST and chlorophyll are commonly used to validate Earth system models. However, these observations are impacted by sampling bias due to sea ice, cloud cover, and solar zenith angle, which prevent satellite detection. To bridge the gap between models and observations, we have developed a satellite simulator for SST and chlorophyll within the Community Earth System Model (CESM2), which generates synthetic MODIS observations at model run-time. The modeled observations allow us to remove the impact of sampling bias in order to update estimates of model bias. We present results from a hindcast simulation and analyze years 2003 to 2016, comparing the model to real-world MODIS observations over the same time period. Although satellite sampling bias in SST and chlorophyll is generally small compared to model bias, modeled MODIS observations of chlorophyll and SST reduce apparent ocean model bias on a global scale. However, the relative importance of these two biases varies regionally and on different spatial and temporal scales.