Thursday, 3 June 2021: 1:40 PM
James D. Doyle, Naval Research Laboratory, Monterey, CA; and M. G. Fearon, P. M. Finocchio, and C. Amerault
Arctic cyclones that rapidly intensify are notoriously difficult to predict, particularly with regard to their attendant mesoscale boundary layer features such as near-surface jets that can have important impacts on changes to the sea ice extent and ocean state. In this study, we compare and contrast initial condition sensitivity and multi-scale predictability aspects of several noteworthy intense high-latitude cyclones. We explore the sensitivity and predictability of the Arctic Cyclone of 2012 (AC12) that was centered on the Arctic Ocean in early August 2012 and was the strongest summer storm in the Arctic since satellite observations began in 1979 with a peak intensity of 962 hPa. A second cyclone of focus is the Arctic Cyclone of 2016 (AC16) that featured several intense cyclogenesis events leading to long-lived cyclonic activity that occurred in August and September of 2016. Both AC12 and AC16 were associated with rapid sea ice extent reductions. Eight other cyclones are investigated making up a representative sample of Arctic cyclones, some of which occurred during the special observing period of the Year of Polar Prediction in summer of 2018.
We apply the COAMPS nonhydrostatic moist adjoint system using nested grids to identify the key drivers of sensitivity and predictability barriers of these Arctic cyclones. The adjoint diagnostics indicate that the intensity of severe winds and strong surface fluxes in these high-latitude storms in open ocean regions and along the sea ice edge are especially sensitive to narrow filaments in the moisture and temperature fields and to a lesser degree the wind fields. The mesoscale structure (e.g., low-level jets) associated with these cyclones are also sensitive to the surface flux distribution, which is linked to the sea ice edge location. The results of this study underscore the need for accurate moisture observations on the mesoscale and data assimilation systems that can adequately assimilate these observations in order to reduce the forecast uncertainties for these intense cyclones. However, given the nature of the sensitivities and the potential for rapid perturbation and error growth, the intrinsic predictability of the mesoscale structure associated with these intense Arctic cyclones appears to be limited. We will also discuss a new observing campaign planned for summer 2021 focused on Arctic cyclones and sponsored by the Office of Naval Research.
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