Coupled Lake-Atmosphere-Land Physics Uncertainties in a Great Lakes
Regional Climate Model
Abstract
This study develops a surrogate-based method to assess the uncertainty
within a convective permitting integrated modeling system of the Great
Lakes region, arising from interacting physics parameterizations across
the lake, atmosphere, and land surface. Perturbed physics ensembles of
the model during the 2018 summer are used to train a neural network
surrogate model to predict lake surface temperature (LST) and
near-surface air temperature (T2m). Average physics uncertainties are
determined to be 1.5°C for LST and T2m over land, and 1.9°C for T2m over
lake, but these have significant spatiotemporal variations. We find that
atmospheric physics parameterizations are the dominant sources of
uncertainty for both LST and T2m, and there is a substantial
atmosphere-lake physics interaction component. LST and T2m over the lake
are more uncertain in the deeper northern lakes, particularly during the
rapid warming phase that occurs in late spring/early summer. The LST
uncertainty increases with sensitivity to the lake model’s surface wind
stress scheme. T2m over land is more uncertain over forested areas in
the north, where it is most sensitive to the land surface model, than
the more agricultural land in the south, where it is most sensitive to
the atmospheric planetary boundary and surface layer scheme. Uncertainty
also increases in the southwest during multiday temperature declines
with higher sensitivity to the land surface model. Last, we show that
the deduced physics uncertainty of T2m is statistically smaller than a
regional warming perturbation exceeding 0.5°C.