Winter Cold - Part 4

Back in January through March I penned three posts about the surprising cold in Alaska last winter, trying to identify a key cause for the dramatic change from the warmth of recent years (see here, here, and here).  In my view the discussion wasn't very satisfying in the end, as it failed to pinpoint an obvious driver for the winter pattern.  However, I finished up the last post with a promise to explore in more detail the close similarity with the winter of 1989-1990, so that's what I'll try to do here.

First let's remind ourselves of the broad pattern similarity between the two winters.  Here are the 500mb height and temperature anomaly maps for the two winters (December-February); notice the strong west-east ridge across the central North Pacific as well as the cold trough over Alaska and the strong similarity in the northeastern Pacific region (e.g. warm in British Columbia).  Click to enlarge the maps.


I also mentioned last time that the similarity extended to the temporal evolution of the high-latitude circulation pattern, with the Arctic Oscillation becoming increasingly positive in both winters.  This is illustrated in the chart below, which I find quite remarkable: the AO index evolved in strikingly similar ways at times through the two winters.  For instance, both winters saw increasingly positive peaks of the AO, and even with similar timing: around December 1 and early January, and then a pair of enormous peaks during February.

A daily AO index above +6 is a rare extreme, and outside these two winters only one other date since 1950 has achieved this feat: January 14, 1989, which was right at the onset of the infamous Alaska cold snap.  Coincidence?  Not a chance.

 

An obvious question therefore is, was there a common mechanism that was driving the AO towards a more amplified positive state as these winters progressed?  In considering this possibility, the first place to look is the tropics, where we might hypothesize that a persistent pattern of rainfall anomalies provided a favorable configuration to strengthen the circumpolar flow in the high latitudes.  This could occur either by a pathway that directly strengthens the westerly momentum at higher latitudes, or by an unusual reduction in disturbances to the normal wintertime polar vortex.  In atmospheric dynamics, the tropics tend to drive the extratropics more than the other way around - for example, the dominant El Niño/La Niña oscillation has very predictable effects on higher latitude circulation patterns.

In Part 2 of the discussion I looked at the tropical rainfall patterns from last winter and failed to find a similarity to historical patterns associated with cold in Alaska.  However, that analysis was a broad overview, and 1989-1990 was mentioned as a relatively close match, so let's take a closer look at the tropical features of the two winters.

First, the sea surface temperature maps (see below) show a strong similarity with respect to a region of anomalous warmth centered near 0°N 180°E.  (Note that I've plotted both maps in terms of the departure from the immediately preceding 30-year mean to put them on equal footing in regard to climate trends.)  Equatorial warmth near the Date Line corresponds approximately to the Niño4 region, which is the westernmost of the boxes that are used to measure ENSO SST anomalies (see here for explanation).  We can therefore describe the warmth as a kind of El Niño warming, but it's a "Central Pacific" or "Modoki" El Niño anomaly.  A traditional El Niño has its equatorial warmth focused much farther east, closer to South America.

Looking at rainfall estimates from the state-of-the-art ERA5 reanalysis gives an indication of how the tropical circulation was displaced relative to normal.

Both winters saw enhanced rainfall near the equator at about 170°E (on the west side of the warm SST region), and both years also had dry conditions to the east of the Date Line around 0-5°N, and wet conditions north of this and extending northward roughly to Hawaii.  Another key similarity is the zone of dryness north of the equator from about 80°E-140°E, reflecting a large region of unusual subsidence (sinking air and dry weather) from Sri Lanka to the Philippines.  (These maps are showing absolute rainfall anomalies rather than the more usual "percent of normal", because it's the absolute magnitude of the tropical heating anomalies - caused by excess condensation in deep rain clouds - that we're interested in.)

Finally, the lower atmospheric wind patterns tie together the SST and rainfall anomalies, and really illustrate again how similar the two winters were in the Pacific basin.  The maps below show the average 850mb winds (speed and direction) at left, and the maps on the right show the departure from normal of the westerly wind speed.

The pattern of west-east wind anomalies is remarkably similar from the tropical region spanning the eastern Indian Ocean to the western Pacific Ocean, and all the way up to the central and northern North Pacific.  Focusing on the equator, notice the change from easterly wind anomalies over Indonesia to westerly anomalies over the western Pacific; this implies a very similar focus of subsidence and lack of rainfall near 130-140°E.  Farther east, the westerly wind anomaly extending to near the Date Line is consistent with high SSTs, because the usual easterly trade winds (a cooling influence) were weakened or even reversed in this area.

Putting it all together at last, my interpretation is that the pronounced realignment of tropical rainfall patterns was closely linked to the intensification of the mid-latitude ridge across the North Pacific and, therefore, the positive AO phase.  A first and simple explanation is that enhanced rainfall near the Date Line strengthened the Hadley circulation over the central Pacific, with significantly more mass being displaced poleward at high elevation and then descending to reinforce the subtropical ridge to the north (roughly north of Hawaii).  A stronger subtropical ridge is a key aspect of the positive AO phase, as it implies a stronger pressure gradient northward to the Arctic, and therefore a stronger mid-latitude jet stream.

A second and slightly less straightforward aspect involves the fact that rain clouds over Indonesia and the far western Pacific are usually a strong source of wave disturbances that travel north (and south) into the extratropics and affect the high-latitude circulation.  When these disturbances are frequent and strong, they tend to weaken the polar vortex and produce a less positive AO phase; but last winter these wave disturbances were weaker than usual, and this contributed to the polar vortex becoming very strong and the AO becoming increasingly positive.  And so the reduction in rainfall near the Maritime Continent seems to be a key piece of the puzzle, just as much as the enhanced tropical rainfall farther east.

If you've made it this far, congratulations - this turned into a slightly technical discussion.  Understanding the remote influences and connections in global climate is an enormous challenge, but the remarkable convergence of events across the North Pacific and Arctic in the two winters of 1989-1990 and 2019-2020 provides a clear illustration, I think, that these connections are real and significant.

North Pacific Temperature Update

I added a new post on the Alaska "Blob Tracker" blog this morning:

https://alaskapacificblob.wordpress.com/2016/11/14/dramatic-changes-in-recent-weeks/

The contrast between a strongly positive PDO phase and now strongly negative NPM phase is quite remarkable.  Looking at past years in which this combination was observed during winter, it is typical to see a stronger than usual Aleutian Low and a strong ridge over the western half of Canada.

Unfortunately for snow-lovers, this pattern is a distinctly dry one for interior Alaska and a distinctly warm one for southern and southeastern Alaska.  Of course, there's no guarantee that the North Pacific temperatures will remain in this pattern for the next 3 months, but I wouldn't want to bet against it.

Pacific Temperature Patterns

On this blog there has often been discussion of the influence of Pacific Ocean temperature patterns on Alaska climate, and rightly so, as the evolving oceanic thermal patterns are known to create first-order impacts on seasonal (and decadal to multi-decadal) climate in this part of the world.  In this connection we usually talk about the El Niño - Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) as the two big players.

A few weeks ago reader Eric suggested that we could do an objective multi-variate analysis of the impacts of ENSO and the PDO to decipher which is more important at different times of the year.  The challenge here is that the two phenomena, as they are usually defined, are not at all independent, so it is impossible to obtain a clean separation of the impacts.  However, if we could re-define the different Pacific temperature patterns to be independent of each other, then we could proceed.  This is the approach followed by Dennis Hartmann of the University of Washington in a paper published this year:

http://www.atmos.washington.edu/~dennis/Hartmann-2015-Geophysical_Research_Letters.pdf

Hartmann looks at temperature patterns over a large domain from 30°S to 65°N across the Pacific and calculates the top 3 EOFs, which are the independent spatial patterns that dominate the variability over time.  The top pattern/EOF largely represents ENSO but also includes significant variability that we normally think of as the PDO (see Hartmann's figure 1, reproduced below).  The second pattern/EOF also resembles the PDO pattern, so we can think of the PDO as contributing to both EOF1 and EOF2.  Hartmann's third mode is what he calls the North Pacific Mode, and he focuses on this pattern as being implicated in the extreme circulation anomaly over North America in winter 2013-2014.

The independence of the three temperature patterns allows us to proceed with Eric's idea of a multi-variate linear regression, and so I've done this for Fairbanks monthly and seasonal temperatures since 1950.  The first chart below shows the estimated coefficients of regression between the 3 Pacific modes and Fairbanks monthly temperature.  This can be interpreted as the temperature anomaly that typically occurs in Fairbanks when each of the modes has an anomaly of 1 standard deviation; for example, when EOF1 is one standard deviation above normal in January, Fairbanks is typically 3 °F above normal.  Note that the coefficients are very small in summer for two reasons: first, because there is a less robust impact of the Pacific modes, and second because the summer temperature variability is much smaller.

It's interesting - to say the least - that Hartmann's North Pacific Mode (EOF3) has a small impact compared to ENSO and the PDO, and it is negatively correlated with temperature in most months.  I did not expect to see this, because the North Pacific Mode is closely related to "the Blob" of warm northeast Pacific SSTs that has recently gained notoriety, and I have speculated that this anomaly was partly responsible for the warmth of the past two winters in Alaska.  This analysis would suggest that we can't pin the recent warmth on "the Blob".

Here's the corresponding chart for seasonal (3-month) mean temperatures in Fairbanks.

If we look at the statistical significance of the 3 predictors in the multiple regression model, we find that the impacts of the Pacific modes are generally more robust for seasonal temperatures than for monthly temperatures, as we would expect.  The charts below show the t-values of the individual regression coefficients; the t-values directly indicate the probability that the coefficients could have been obtained by random chance.  On a seasonal basis, the ENSO/PDO impacts are highly statistically significant from autumn through late spring.  The NPM also shows up as significant at certain times of the year, but with a negative coefficient as noted above.

The overall correlation coefficients for the 3-predictor models (monthly and seasonal) are shown below - again generally higher for seasonal than monthly anomalies, and especially in the autumn.

From the perspective of seasonal forecasting it is interesting also to look at the statistical impacts on a lagged basis, because of course we don't know ahead of time how the Pacific temperature patterns will evolve in the months ahead.  The chart below provides a quick look at this; here I've repeated the procedure using seasonal Fairbanks temperatures and the Pacific modes one month ahead of the first month of the season - for example, the columns for DJF show the significance of the regression between November Pacific patterns and December-February Fairbanks temperatures.  The results indicate that the predictability associated with EOF1, the ENSO/PDO mode, is largely retained at a one-month lag, but EOF2 and EOF3 lose most of their predictive power.  This is not too surprising, as the coupled ENSO/PDO anomalies evolve slowly, but the 2nd and 3rd modes can change significantly over the course of a few months.