One of the most common questions we get asked every year is “I heard we are going to be in an El Niño this winter, does that mean it’s going to be warmer/cooler and wetter/drier than normal?” The typical answer to this question is, well, it depends. A lot of people may not realize it, but our atmosphere is extremely complex. So complex in fact that even with today’s technology, our computer models can miss details on a big storm within 12 hours due to the complexity some of these storms hold. The atmosphere acts a lot like a liquid in the sense that while we can get a grasp of general directions and tendencies and patterns, at the end of the day that liquid is going to go whichever direction it wants and act however it wants. The atmosphere essentially does the same thing as we sometimes have instances when all of our pattern drivers point to a warmer and drier Central US, but end up with a cooler and wetter pattern instead. How could something like this happen? The answer is because there are many variables at play.
ENSO (El Niño Southern Oscillation) is one of, if not the most well-known seasonal pattern drivers. We can be in a certain state (El Niño or La Niña) for as short as a couple months and as long as multiple years. The one misconception many people have with ENSO is that winter forecasts are almost strictly tied to whichever state we are in. “If we are in a La Niña, then we are GOING to see warmer and wetter conditions in the Ohio Valley”. While this can be a tendency, this does not mean every La Niña year is going to fit this mold. Why is that? Well, it stems back to the idea that ENSO is not the only pattern driver on Earth and also that the magnitude of ENSO is important.
We decided to take a look at the winters of the past 20 years (December, January, February) and their ENSO states. For clarity, DJF 2000 means we are looking at the December of 1999, and January/ February of 2000. Below is a look at the Oceanic Niño Index (ONI) for the past 20 winters. The ONI, simply put, is an index to measure the “strength” of ENSO. Negative values (blue) represent La Niña like conditions in the equatorial Pacific and positive values (red) represent El Niño like conditions. The more negative the value is, the stronger the La Niña is:
Here we can see that in the past 20 years, we have had 7 El Niño years, 8 La Niña years, and 5 neutral years. “Neutral” is defined as an ONI value with a magnitude smaller than +/- 0.5. One thing to note is that these values were part of varying stretches of an ENSO state. For example, our ONI values in the winters of 2015 & 2016 were part of a stretch of 19 months of El Niño ONI values, while our ONI value in 2007 was part of an El Niño that lasted 5 months. Using each year’s ENSO state, we came up with temperature and precipitation anomalies for what each ENSO state tendsto look like:
There is certainly a lot to dissect from these 6 images, but we want to highlight some of the key points. Our El Niño years (‘03, ‘05, ‘07, ‘10, ‘15, ‘16, ‘19) tend to be cooler and wetter in the OH Valley region with warmer than average conditions out west. La Nina years (’00, ’01, ’06, ’08, ’09, ’11, ’12, ’18) are slightly warmer than average and run the risk of above normal precipitation in the OH Valley with cooler conditions tending to stretch from the Pacific NW to the Northern Plains. We also see the Southern US drier than normal. Interestingly, our neutral years (’02, ’04, ’13, ’14, ’17) has above normal temperatures minus the Pacific Northwest. We also see the OH Valley slightly above normal precipitation-wise, but there are not any real tendencies here. “So, now that we have tendencies as to what each ENSO state usually looks like, we know what a winter will look like based on its ONI value, right?” Well, not exactly. Below is a look at 4 different La Niña years that all had an ONI value of -0.8 or -0.9. 2018 (bottom right image) is really the only year that even somewhat resembles the La Niña anomaly plot from the previous image. This shows that years with similar ENSO strengths do not always end up behaving the same, especially temperature wise. “How could they look so different?” As we previously mentioned, there are other “gears” in play that are driving the atmosphere:
Another way to view the past 2 decades is to look at mean temps for DJF since 2000. Below is a graph of 4 cities in the OH Valley/ Midwest that all have roughly the same latitude: Columbus, OH, Indianapolis, IN, Springfield, IL, and Kansas City, MO (Note: black line in the graph is the mean temperature for the past 20 DJF periods for all cities combined). We noted 4 examples of years when temperatures did the opposite of what one might expect if they went strictly off what shouldhappen based on our ENSO state. The point of this graph and these examples is not to just cherry pick years where we saw opposite trends of what tends to happen, but rather to show that there is not a 1 to 1 correlation of El Niño/ La Niña winters = cooler/warmer than average temps. While a certain pattern tendsto happen, this does not mean it is always goingto happen:
Another example of this is to look at snow accumulation for the past 20 winters (DJF accumulation only). We are looking at the same 4 cities as we did for temperatures, Columbus, OH, Indianapolis, IN, Springfield, IL, and Kansas City, MO. (Note: black line in each graph is the average snowfall amount for the past 20 DJF periods for that city). While we could dissect every year plotted, we want to focus on 3 years in particular. The first being 2011 (green arrows) where we have above normal snowfall for all 4 cities. The very next year (2012, orange arrows) we see below normal snowfall by a foot plus for all 4 cities. It is interesting to see that these two years were both La Niña years, yet produced such different snowfall totals. The third year to analyze is 2014 (red arrows) where we had one of, if not the snowiest DJF across the Midwest in the past 20 years. Looking back at our analogs, it is tempting to chalk that winter up as an El Niño due to its tendenciescof being above normal precipitation, however our ONI shows that this was actually neutral year:
Two other quick tidbits we came across while looking at ENSO values that we wanted to share with you- We looked at all monthly ONI values dating back to 1950 and noticed an interesting trend. The 6 largest ONI values (red dots) each came in different decades (black lines denote decade change), and those top ONI values have become increasingly more positive every decade. This is trend could be linked to climate change and one that we will have to watch over the coming years to see if this is something we continue as we soon enter a new decade:
The other figure we wanted to share is one coming from NOAA that shows global surface temperature anomalies since 1980, with the ENSO state shaded over the months that a certain state was observed (La Niña = blue, El Niño = red, neutral = gray). These temperature anomalies are produced by comparing each month’s global surface temperature to our 1900-1999 global surface temperature average. While La Niña events are certainly cooler than El Niño events globally, this does not necessarily mean the entire globe will observe that tendency. As shown in the examples above, we tend to see the opposite in the central US. We also found it interesting that in recent, cooler periods (La Niña), we are actually seeing global temperature anomalies much higher than in warmer periods (El Niño) that happened in the 1980s and 1990s. As our globe continues to warm, this should be another trend that continues and one we will have to keep an eye on:
We did not dive too deep into other pattern drivers and what their indices looked like for the 2000’s because we wanted to focus more on ENSO and how there is not a 1 to 1 connection between a certain ENSO state and observed temp/precip values. Some of the global pattern drivers other than ENSO that should be looked at when discussing a seasonal forecast, especially winter, are the Quasi-Biennial Oscillation (QBO), Pacific Decadal Oscillation (PDO), Atlantic Multi-Decadal Oscillation (AMO), and the Atmospheric Angular Momentum (AAM) among others. While ENSO is certainly an important player in the oceanic/atmospheric teleconnection pattern, there are definitely other factors just mentioned that have an influence as to how a winter plays out.
So, next time you hear from the local news or your current weather provider that the OH Valley/ Midwest is going to have a warmer than normal winter just because we are seeing La Niña like conditions across the globe, don’t put too much stock into that forecast because chances are they have not looked at these other pattern drivers due to this misconception that ENSO drives our weather. Here at BAMWX, we make sure to look under every stone to see which drivers are currently impacting our weather the most so you have the most accurate information for the months ahead. Contact us at [emailprotected] to see how our service can help your business save time, money, and resources by delivering an accurate weather forecast that will allow you to make the best decisions! Even if you don’t own a business, follow us on Facebook, Twitter, and Instagram at bamwxcom for the latest!
