Record-breaking snow in Moscow and Montreal in 2012 - a tale of two cities (29 November and 27 December 2012)

by Sheldon J. Kusselson (NOAA NESDIS)

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The two record-breaking snow events in Moscow (November) and Montreal (December) perfectly illustrate the pattern of warm, moist air originating in the lower latitudes being transported poleward (in this case north) ahead of a deep upper level trough of low pressure (see Powerpoint Presentation, PPT, 4469 KB).

If the storm gets strong enough, the concentration of highest moisture or “the atmospheric river of moisture” can be thrown back into the cold air north and northwest of the upper level low, producing heavy snowfall. This is what happened in these two cases, resulting in record-breaking snowfall in Moscow at the end of November and a record daily amount of snow in Montreal, Canada at the end of December.

Conceptual models of the ‘atmospheric river’ of moisture and moist conveyor belt are shown in slides 10-12 at the far left top and bottom, respectively. Notice that in the Montreal case (bottom), the amount of moisture within the “atmospheric river” was higher and further into the cold season than the November case in Moscow. This may, at least partly, explain why the Montreal case produced more snow than the Moscow event.

Also, notice that in the Moscow example, some of the moisture conveyor belted cyclonically around the upper level low, producing significant snows in central Europe — referred a TROWAL or TROugh of Warm air ALoft (google: TROWAL) by American forecasters.

It is possible that the Moscow snow event (slides 10-12, top, second image from left) did not have the full benefit of the deep moisture (still lower amounts of precipitation than the Montreal case) that originated over northern Africa, because of the diversion of some of that moisture in producing heavy snow in central Europe. Still there was a significant amount of moisture (at least for Europe) and transport to produce a record November snow for Moscow.

In both cases (slides 10-12, far right, top and bottom images) the pattern recognition of the GOES-13 water vapour and Meteosat-9 and AQUA MODIS Airmass RGB deep upper low with PV anomalies, or lifting mechanisms out ahead, helped supplement the low level wind flow on the moisture plume of the Blended TPW. The lifting mechanisms would increasingly ‘squeeze out’ the moisture as snow as the warm moist air lifted and cooled on its way north.

Also of note, research, and many case studies in the past, have shown that low to middle level winds parallel the highest moisture insures a continual supply of deep moisture into a precipitation producing system, making for a highly efficiently way to both replace the precipitation (in this case snow) that has already fallen and continue the heavy precipitation process, as long as a forcing mechanism is nearby.

Figure 1
Met-9, 29 November 2012, 12:00 UTC
Channel 09 (IR10.8) with SYNOP observations and SatRep analysis
Full Resolution (PNG, 563 KB, source: EUMeTrain)

Figure 2
Met-9, 29 November 2012, 12:00 UTC, Airmass RGB
Full Resolution (JPG, 180 KB)
Animation (28 Nov 00:00 UTC - 29 Nov 12:00 UTC, MPG, 10061 KB)
Natural Colour RGB (10:00 UTC, JPG, 189 KB)

Figure 3
29 November 2012, 12:00 UTC
Left: Met-9 Airmass RGB product (source: EUMeTrain)
Right: blended TPW product (source: NOAA NESDIS)
Full Resolution (PNG, 428 KB, source: Sheldon Kusselson, NOAA)
Powerpoint Presentation (PPTX, 4469 KB)
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