Scenario changes in the climatology of winter midlatitude cyclone activity over eastern North America and the Northwest Atlantic

Abstract

[1] The present study explores how midlatitude winter cyclone activity can be modified under warming-induced conditions due to enhanced greenhouse gas concentrations. We performed simulations with the Canadian Regional Climate Model (CRCM version 3.5) implemented on a domain that covers the Northwest Atlantic and eastern North America. These simulations are driven by control conditions (1975)(1976)(1977)(1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994) and high-CO 2 scenario conditions (2040)(2041)(2042)(2043)(2044)(2045)(2046)(2047)(2048)(2049)(2050)(2051)(2052)(2053)(2054)(2055)(2056)(2057)(2058)(2059) suggested by the Canadian Climate Centre model, CGCM2 (Second Generation Coupled Global Climate Model), following the IPCC IS92a scenario. Comparisons between model simulations for the control period (1975)(1976)(1977)(1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994) and North America Regional analysis (NARR) suggest that both CGCM2 and CRCM reliably reproduce the overall NARR patterns of sea level pressure, tropospheric baroclinicity and Atlantic storm tracks. However, compared to CGCM2 results, CRCM offers an improvement in simulations of the most intense cyclones. Although both models underestimate the track density of intense cyclones, the CGCM2 underestimates are larger than those of CRCM. Under the high-CO 2 climate change scenario, the CRCM and CGCM2 model simulations show similar changes in sea level pressure, surface temperature, and total track density of midlatitude winter cyclones. Although we can see the northwest shift of the dominant Atlantic storm track, it is not statistically significant. Moreover, simulations from both models show a decrease in the total cyclone track density along the Canadian east coast; the decrease is more robust in CRCM simulations than in CGCM2 results. For intense cyclones, CRCM simulations show a slight decrease in the track density, while no such change is found in CGCM2 simulations.

Challenges of tracking extratropical cyclones in regional climate models

“…From studies based on the use of several reanalysis datasets with a single ETC-tracking algorithm, it is known that tracking results are also sensitive to the uncertainty in data (Hodges et al 2011). Data processing, like the interpolation of GCM outputs on a finer grid as in Long et al (2009), also influences tracking statistics. As such, these sources of uncertainty should be kept in mind or even used as error bars when assessing studies like this one.…”

“…Application of ETC tracking algorithms to RCM-produced datasets, however, introduces additional challenges. In order to investigate these challenges, we compare ETC tracking results of a simulation produced by the Canadian Regional Climate Model (CRCM) over North America at a 45-km resolution driven by ECMWF ERAInterim, with the results obtained directly from the driving Several studies have concentrated on comparing ETC statistics obtained from a tracking algorithm applied on both regional climate models outputs and global data (GCM or reanalysis) over the Atlantic (Jiang and Perrie 2007;Semmler et al 2008a, b;Woollings et al 2009;Long et al 2009), Europe (Lionello et al 2008) and over the Arctic (Shkolnik and Efimov 2013). Some of these studies are in fact sensitivity experiments where RCMs are driven by reanalyses in various contexts.…”

Relationship between Snow Extent and Midlatitude Disturbance Centers

“…The metric s BI is a measure of the growth rate of a baroclinic wave and is sometimes referred to as the eddy growth rate (Long et al 2009). Equation (1) can be rearranged and discretized as…”

Investigating added value of regional climate modeling in North American winter storm track simulations

“…He et al 2013;Marciano et al 2015). Long et al (2009) have shown that an earlier version of the Canadian Regional Climate Model could improve the representation of intense cyclones with respect to its driving GCM. Among other interesting points, RCMs provide an improved description of the surface topography which, in the case of North America, is a decisive element in storm development (Brayshaw et al 2009).…”