Expand the use of eddy - resolving models, particularly in regional / process studies designed to: i) test the robustness of AMOC variability mechanisms identified in coarser GCMs or idealized models; ii) address the origins of
persistent model bias in the North Atlantic region (e.g., Gulf Stream separation and the North Atlantic Current path); and iii) assess the role of ocean turbulence in AMOC variability.
Not exact matches
Using 19 climate
models, a team of researchers led by Professor Minghua Zhang of the School of Marine and Atmospheric Sciences at Stony Brook University, discovered
persistent dry and warm
biases of simulated climate over the region of the Southern Great Plain in the central U.S. that was caused by poor
modeling of atmospheric convective systems — the vertical transport of heat and moisture in the atmosphere.
General circulation
models and downscaled regional
models exhibit
persistent biases in deep convective initiation location and timing, cloud top height, stratiform area and precipitation fraction, and anvil coverage.
Preliminary investigations suggest that these
biases are related to the fact that the
model has
persistent high thin clouds that reduces incoming solar radiation at the surface forcing an artificially low land skin temperature.
Limited understanding of clouds is the major source of uncertainty in climate sensitivity, but it also contributes substantially to
persistent biases in
modelled circulation systems.
In fact, current satellite instruments such as SCIAMACHY have been shown to have
persistent biases in space and time (e.g. Bergamaschi et al., 2013; Houweling et al., 2014) that need to be accounted for if satellite data are to be assimilated into atmospheric inverse
models.»