Simulating satellite observations of sea surface temperature and
chlorophyll in CESM2 to assess model and sampling bias
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.