Long, cold winters: How this past winter demonstrated climate variability

This week’s topic is somewhat of a continuation to the post Victoria published on Monday: Cold spell occurrences.

Figure 1: The annual mean temperature for the states of Maryland (red) and Virginia (blue) from 1895-2014. Note that there is a significant linear increase, however, the trend is weak due to a cyclic pattern.

Figure 1: The annual mean temperature for the states of Maryland (red) and Virginia (blue) from 1895-2014. Note that there is a significant linear increase, however, the trend is weak due to a cyclic pattern.

When we hear about climate change and global warming, we often think only about the warming aspect. While it is true that our local climate appears to be warming (Figure 1), climate change can also manifest as “variability.”
So what does variability mean to us in everyday life?
In terms of climate change in the Chesapeake region, variability can come in the form of having a cold winter even though previous winters may have been comparatively warmer. A higher variability in winter temperatures can mean we have a higher chance of having an anomalous warm and/or anomalous cold year, even if the overall gradual mean trend is a warming.

A linear regression of the annual mean temperature in the states of Maryland and Virginia suggest a gradual, but weak, increasing trend. Using the slopes, Figure 1 suggests that the mean annual temperature is increasing at a rate of 0.17°F/decade in Maryland and 0.09°F/decade in Virginia. However, this mean increase does not explain why this past winter was so tremendously terrible.

Figure 2: The occurrence of cold spells in the near-shore Chesapeake Bay region from 1901-2010.

Figure 2: The occurrence of cold spells in the near-shore Chesapeake Bay region from 1901-2010.

Figure 2 is the number of cold spell occurrences in the near-shore Chesapeake Bay region from 1901-2010. The cold spell duration index is defined as the number of cold periods which last at least 6 consecutive days, where “cold” is when the minimum daily temperature is below the 10th percentile from 1961-1990.

The mean number of cold spells was 1.2 (or roughly 1 cold spell per year), however, it is clear that the data is variable and that this mean is not the best way to describe the trend.

For example, a year with ~2 cold spells (such as 1989) followed by a year with no cold spells (such as 1990) would have an average of 1 cold spell. That average would suggest that both these “years” were similar, but in truth 1990 no cold spells while previous year had almost 2 weeks’ worth of consecutive chilly days.

Going back to Figure 2, this time series shows that cold spells occurred consistently in the beginning of the 20th century. But sometime after the 1940’s, we started to experience more years with no cold spells. However, after the 1940’s, there were 3 years with incredibly long cold spells.

Those three notable excursions are each linked to “buzz-worthy” winters. For example, in 1960, many parts of Maryland and Northern Virginia experienced a very cold and snowy December. And 1979 was a curious period when a huge snowstorm rolled though on President’s Day, and then remained cold (in the single digits and teens!) so very little snow could melt afterwards. More recently, in 1999, a low pressure air mass moved over central Maryland and Northern Virginia, creating dangerous icy conditions.

Figure 3: The density distribution of the cold spell duration index for 1910-1960 (blue) and 1961-2010 (black) with the mean for each time range in the vertical dashed line.

Figure 3: The density distribution of the cold spell duration index for 1910-1960 (blue) and 1961-2010 (black) with the mean for each time range in the vertical dashed line.

Overall, the number of cold spells in the near-shore Chesapeake Bay region appear to have decreased. Figure 3 shows that the mean number of cold spells was >1 from 1910-1960 (1.32 spells) and decreased to <1 from 1961-2010 (0.83 spells). This density function also tells us that the probability of a year with less than 1 cold spell increased; in other words, we are more likely to have few cold spells in the 1961-2010 time range compared to earlier in the century.

So what does this mean to us? Well, in essence, having a long cold period each year is becoming less frequent. But, this certainly does not mean that we will never have cold spells. Anyone living in the Northeast region can attest to this fact after our winter!

So how can we be getting warmer and still have a crazy cold winter? This is where the climate variability comes into play.

Figure 4: The coefficient of variation, or spread of the data, for the cold spell duration index in the Chesapeake region. This increase in variance infers that the swing between a winter with a long, cold period and having no long cold spells is increasing.

Figure 4: The coefficient of variation, or spread of the data, for the cold spell duration index in the Chesapeake region. This increase in variance infers that the swing between a winter with a long, cold period and having no long cold spells is increasing.

The variance, or how spread out the data is, can sometimes help us assess “extreme” climate occurrences better than the mean. (Think of the word variety; we have more of a variety of cold spell occurrences than in the beginning of the 20th century).

While cold spells are occurring less frequently, they do still occur and have been manifesting as many long cold spells. So, don’t throw away those winter coats just yet!

These warm-cold-to-warm winters truly test our resiliency, or ability to recover from an event, such as all that snow we got!

Kari Pohl

About Kari Pohl

I am a post-doctoral researcher at NOAA and the University of Maryland (Center for Environmental Science at Horn Point Laboratory). My work investigates how climate variability and extremes affect the diverse ecosystems in Chesapeake Bay. I received a Ph.D. in oceanography from the University of Rhode Island (2014) and received a B.S. in Environmental Science and a B.A. in Chemistry from Roger Williams University (2009). When I am not busy being a scientist, my hobbies include running, watching (and often yelling at) the Boston Bruins, and taking photos of my cat.
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