The effects of interactions between surface forcings in the development of a model-simulated polar low in Hudson Bay

Abstract

A 30-km version of the Canadian Regional Climate Model is used to simulate a polar low development in early December 1988 over the Hudson Bay. This polar low is quantitatively analyzed in detail, in the initial and mature stages of its development, in order to understand physically how sea surface conditions influence this mesocyclone. This analysis is realized via the description of the effects of different atmospheric forcings (i.e. thermal and vorticity advection, and turbulent and convective fluxes) on the polar low development (called the direct effects) using the diagnostic equations of omega and vorticity tendency. Also, the effects of forcing interactions on subsequent cyclone development (called the indirect effects) is analyzed via the diagnostic equations of vorticity and thermal advection tendencies. In the early stage of development, a low-level cyclogenesis appears over the northwestern Hudson Bay essentially due to diabatic forcings in the context of low-level cold air advection. Progressively, the synergetic effect of time rate of changes in advection terms, resulting from surface diabatic and stress forcings, favours low-level cyclogenesis and baroclinicity over open water near the sea-ice margin, whose shape is determinant for the deepening and tracking of the polar low. In the mature stage, the growth in advection terms becomes the main factor of cyclone intensification with the increase in low-level convection. Forcings are maximum near the surface and differ substantially from the vertical structure found in classical extratropical cyclones. In the upper troposphere they appear to play a secondary role in this polar low development. Finally, the polar low studied here is primarily the result of combined forcing interactions near the sea-ice edge, which are responsible for vorticity and thermal advection changes at low levels. It is also found that the indented sea-ice shape is a favourable factor for the local surface cyclogenesis due to the formation of local Laplacians of diabatic and thermal forcings.

Air‐sea interactions during an Arctic storm

“…These reanalysis fields are widely used in Canadian atmospheric and oceanographic community studies. CRCM was applied in previous Arctic studies [ Gachon et al , 2003; Qian et al , 2008; Wyser et al , 2008; Joly et al , 2011]. In particular, Wyser et al [2008] implemented CRCM in the western Arctic to compare eight regional climate models, showing that CRCM has a reasonable simulation of Arctic climatology.…”

Temperature change signals in northern Canada: convergence of statistical downscaling results using two driving GCMs

“…From a climatological point of view, this strong warming in a summer month does not seem to be physical plausible. The winter, spring and fall months should experience much stronger warming in the north, especially in Arctic regions where the retreat of sea-ice and the decrease of the snow cover season primarily induce the higher effect in intra-annual scale temperature changes, with strong amplification related to a reduction of the surface albedo and an increase in surface diabatic fluxes (see for example the effects of these fluxes over Hudson Bay on low-level air temperature in winter in Gachon et al, 2003). During the summer season, a warming of 11°C, as for example in July at Cape Dorset, produces a monthly mean temperature of around 18°C (Figure 4) and a nearly equivalent warming in the cold water surrounding this location (i.e.…”

“…Indeed, the error in GCM simulations of contemporary climate and the range of response to increasing greenhouse gas concentrations is largest in areas affected by sea ice (Flato, 2004). Sea ice and snow cover are also highly sensitive to fine-scale climate forcings (both atmospheric and oceanic; see for example the Hudson Bay system in Gachon et al, 2003, andin Saucier et al, 2004), not explicitly incorporated in coarse GCMs. For instance, small inland seas or channels in the Canadian Arctic Archipelago are not present in most GCMs, which cover almost all this area with land, and only roughly depict the relevant watersheds ( Figure 1).…”

A multivariate multi-site statistical downscaling model for daily maximum and minimum temperatures

“…Northerly winds generally determine low temperatures, while southerly winds determine high temperatures, especially in a continental area such as Canada where low-level cold or warm air advections, originating from the Arctic basin and the Gulf of Mexico/ southern USA respectively, and strongly varying over the year, play a key role in the determining 2 m air temperature and its variability (see for example the effect of northerly and southerly winds on the lowlevel air temperature fluctuations during winter storm events in the Hudson Bay area in Gachon et al 2003).…”

“…The inflation procedure increases the downscaled temperature anomaly each day by adjusting a factor; however, the main drawback of this procedure is that all local variance originates from large-scale variability (Huth 2002). It is well known that the regional or local scale variability of low level air temperatures is also influenced by surface conditions, especially in large northern land masses, such as Canada, where snow cover and frost properties of the soil (among other factors) play a key role in modulating the surface radiative or low level diabatic fluxes over the year (see the study of the Hudson Bay area in winter in Gachon et al 2003). With the randomization procedure, adding noise to the downscaled predictand series supplements the underestimated variability (von Storch, 1999, Huth 2002, Hessami et al 2008.…”