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There is a growing demand for regional-scale climate predictions and assessments. Quantifying the impacts of uncertainty in initial conditions and lateral boundary forcing data on regional model simulations can potentially add value to the usefulness of regional climate modeling. Results from a regional model depend on the realism of the driving data from either global model outputs or global analyses; therefore, any biases in the driving data will be carried through to the regional model. This study used four popular global analyses and achieved 16 driving datasets by using different interpolation procedures. The spread of the 16 datasets represents a possible range of driving data based on analyses to the regional model. This spread is smaller than typically associated with global climate model realizations of the Arctic climate. Three groups of 16 realizations were conducted using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) in an Arctic domain, varying both initial and lateral boundary conditions, varying lateral boundary forcing only, and varying initial conditions only. The response of monthly mean atmospheric states to the variations in initial and lateral driving data was investigated. Uncertainty in the regional model is induced by the interaction between biases from different sources. Because of the nonlinearity of the problem, contributions from initial and lateral boundary conditions are not additive. For monthly mean atmospheric states, biases in lateral boundary conditions generally contribute more to the overall uncertainty than biases in the initial conditions. The impact of initial condition variations decreases with the simulation length while the impact of variations in lateral boundary forcing shows no clear trend. This suggests that the representativeness of the lateral boundary forcing plays a critical role in long-term regional climate modeling. The extent of impact of the driving data uncertainties on regional climate modeling is variable dependent. For some sensitive variables (e.g., precipitation, boundary layer height), even the interior of the model may be significantly affected. [ABSTRACT FROM AUTHOR]

The Beaufort–Chukchi cyclones of October 1963 and August 2000 produced the highest winds ever recorded in Barrow, Alaska. In both cases, winds of 25 m s[sup -1] were observed with gusts unofficially reported at 33 m s[sup -1] . The October 1963 storm caused significant flooding, contaminated drinking water, and interrupted power supplies. The August 2000 storm caused the wreck of a $6 million dredge, and removed roofs from 40 buildings. Both storms were unusual in that they tracked eastward from the East Siberian Sea into the Chukchi and Beaufort Seas, rather than following a more typical northward track into the Arctic Ocean. This paper addresses, through modeling and analysis, the development processes of these two storms. The October 1963 system was a long-lived, warm core, zonally elongated cyclone that traversed around the Arctic basin through the Canadian Archipelago. The August 2000 system was an open-wave cyclone that dissipated rapidly into a weak, cold core eddy in the Alaskan sector of the Beaufort Sea. Approximating the contributions to development using terms in a quasigeostrophic omega equation, it was found that both storms were characterized by the increasing importance of the convergence of the Q vector (representing differential vorticity advection and thermal advection) in the midtroposphere, at the expense of forcing by the turbulent fluxes of heat, moisture, and momentum in the boundary layer. However, the influence of surface turbulent fluxes in the early stages of development was important, particularly for the August 2000 cyclone, which passed over an extensive coastal lead in the East Siberian Sea. This study concludes that the observed retreat in western Arctic ice cover is unlikely to be an important contributor to increasing cyclonic activity in the region, but that ice retreat north of Eurasia could have an impact. [ABSTRACT FROM AUTHOR]