The leaves on the trees are rapidly covering the ground across the Hudson Valley. The air is beginning to feel a bit more crisp in the morning, and the children just celebrated Halloween. As our minds begin to turn toward more wintry thoughts, it must mean that it’s time for the HVW Winter Outlook once again. Each fall season, we compile observational weather data from across the globe, and begin to compare it against historical weather conditions. We use a series of metrics and data elements to project our best bet for the coming winter. Based on that data, and the long range computer guidance… lets take a look at what this coming winter may hold for the Hudson Valley.
Winter Temperatures : Near to Slightly Below Average (-1.5° to +0.5° vs. Average)
Winter temperatures in the Hudson Valley are likely to be near to slightly below average. For the second straight season, a weak to moderate La Nina is projected. This combined with similarly warm waters in the northern Pacific, should lead to persistant ridging over the northeast Pacific Ocean. This should result in a persistent trough in the eastern US, and that should allow frequent shots of cold air to infiltrate the Northeast US. The core of the cold is likely to be in the upper midwest, but even our area could be slightly below average for the season as a whole. The other point worth mention, is that we could see a faster start to winter than in previous years. A colder than average December is appearing increasingly likely.
Winter Snowfall : Near to Above Average (100% – 125% of Average) 43″ to 54″
A winter projecting a peristent trough in the eastern US is also favorable for a snowier than average winter season. The regular access to cold air, combined with a trend that favors storms to track along and up the east coast, sets the stage for multiple east coast snowstorms. Major snow events are a bit random due to the combination of ingredients that are needed, and thus are difficult to reliably project in a winter outlook. However, based on seasons that had very similar conditions, this coming winter appears likely to have several opportunities for significant snow events, that could result in slightly above average snowfall. The seasonal average in Poughkeepsie over the last 30 years is 43.0″. We project between 43″ and 54″ of snow this season. For perspective, Poughkeepsie saw 50.4″ of snow last winter.
Month by Month
For a little more detail, here is each month’s temperature and snowfall projection, for a more detailed idea of how the winter may play out, month by month.
Methodology / Discussion
By now, many of you may have a fairly good idea of the factors and indicators we usually look at when compiling the data for the Winter Outlook. Everything starts with the Sea Surface Temperatures or SSTs.
When we look at the SST pattern, we are looking for years that have a similar SST profile to the current and projected pattern for the winter. You can see the current sea surface temperatures and how they compare to average. We like to focus in on 3 specific areas when creating the winter outlook. The area labeled ‘A’ is the tropical Pacific Ocean or the ENSO (El Nino Southern Oscillation). This is where the terms “El Nino” and “La Nina” come from. The slightly cooler than average temperatures hint at a possible weak ‘La Nina’ for the coming winter. The area labeled ‘B’ is the northern Pacific Ocean, and that is key because of the amount of warm water in that part of the ocean over the past several years. The warm water favors an atmospheric ridge over the western US, which also then favors a reflexive eastern trough. Then lastly area ‘C’ is the northwest Atlantic, which is important for the same reason ‘B’ is. The warm waters tend to favor ridging over the Atlantic, which could have influence on the winter storm track, as well as the potential for warm air to sneak up the east coast.
So we can see the current pattern in place, next we want to see if we expect any dramatic changes in the pattern for the coming winter.
The seasonal computer guidance suggests the ENSO region ‘A’, may cool a bit more, signaling a weak to moderate La Nina for the coming winter. The northern Pacific ‘B’ warm pool is projected to hold, with some cooler than average waters developing along the North American coastline. The Atlantic Ocean ‘C’ continues to be warmer than average. As a whole, the computer data does not change too dramatically from the current conditions… the biggest factor being the additional cooling of the ENSO region.
So now that we have good agreement between the current SSTs and the computer model SSTs, the next step is the most labor intensive. We go through over 50 years of data, and look for winters that most similarly reflect the conditions shown above. We select the years that are the best fit, and those become our analog years, from which we will develop the winter outlook. After researching the data, we have pulled 7 winters. When we blend those 7 winter SSTs, it looks very similar to the computer model projection for the winter.
Those winters are: 1995-1996, 2000-2001, 2005-2006, 2008-2009, 2013-2014, 2017-2018 and 2020-2021. When blending those 7 winters, the analog SST pattern looks impressively closer to the projected winter pattern by the model. The logic being, if the conditions this winter are the same as these years in the past, then we should experience similar results. So this season, in addition to the SST pattern, we brought in a few new tools. Three additional factors we analyzed for similarities were: Atlantic Tropical Seasons prior to the winter; QBO (Quasi-Biennial Oscillation) index; and warmer than average Octobers prior to the winter.
In the interest of time, we won’t detail all of them here, but we will go into more detail in later discussions. For purposes of this conversation, what is important to understand is that for each of these criteria, we went through roughly the last 30 winter seasons, and reviewed each criteria for years that were similar to the conditions we are experiencing, or expecting this winter. We selected those years, and compared them to the winters we identified through the SST method above. Several winters appeared multiple times in the additional criteria, especially the 1995-1996, 2005-2006, and 2017-2018 winters. The reason this is important, is because we were able to develop multiple layers of assurance that our analog years are accurate.
Seasonal forecasting is a very imperfect science. It relies on a set of assumptions, that are built on a forecast. More simply, a forecast based on a forecast. We know what our current conditions are, because we can observe them. But we cannot be sure that those conditions will be the same several months from now. So we rely on a computer model forecast data to extrapolate if those conditions will be the same 2 or 3 months from now. Then… based off that data, we then use our experience and understanding of the science to develop the winter outlook based on a variety of additional factors. With that said… last season, we actually did OK…
The actual temperatures were about a half a degree out of the range we projected. That could be attributed in part to climate change, because global temperatures 20 or 30 years ago were a degree or so cooler, which we try (but may not fully) take into consideration when developing the outlook. But our snowfall projection of 100% to 133% of average (42″ to 56″) likely seems like a large range… but when you recognize that in 19-20 Poughkeepsie saw only 16″ of snow… it doesn’t seem like that large of a range. We saw 50.4″ (120% of the annual average) of snow… when the annual average in Poughkeepsie was 42″ at the start of last season.
So there is certainly ability to project correctly in these winter outlooks, it just relies on there being no surprises in the projected data. Will we see surprises this winter? Almost certainly. The big question will be, what kind of surprises? Luckily for you… we’ll be here to enjoy the ride with you, and discover what the coming winter holds. We hope you enjoyed the 2021-2022 Winter Outlook. Thank you all for your continued support.
-Alex and Bill