Tuesday, July 14, 2015

Warm and Dry Extremes

In pondering this year's record-setting fire season in Alaska (up to 4.4 million acres burned as of yesterday), I found myself wondering "just how dry and warm has it been?"  The extreme fire behavior suggests that the accumulated climate anomalies over the past several months must have been equally extreme, so it's of interest to see if the data reflect this.

First I'll show results for Fairbanks.  The chart below shows the temperature and precipitation ranks for periods of varying length ending with June.  The ranks are calculated with respect to the history since 1930.  So for example, June temperature by itself was very close to the 1930-2014 median temperature, but June precipitation was ranked 31 out of 85 previous years (i.e. percentile rank of 36%).  If we do the calculation for May and June combined, the temperature was ranked 93% and the precipitation was ranked 25%, so the May-June period was much warmer than normal and considerably drier than normal.



As we include more months in the average, going farther back into spring and winter, the temperature ranks generally keep growing and the precipitation ranks keep dropping, until we find that the most recent October-June period (9 months ending in June) was ranked 96% for temperature and only 14% for precipitation.  Going even farther back, however, we see the effects of last year's very wet summer in Fairbanks, which raises the precipitation ranks as we include those months.

Now take a look at the chart below for McGrath.  All running averages from 1-12 months are above the 94th percentile for temperature (with several being records), and periods from 4-12 months are below the 10th percentile for precipitation.  In other words, it has been both extremely warm AND extremely dry in McGrath over seasonal timescales leading up to this summer.  In view of these numbers, the extreme fire season is anything but a surprise.


The figures below show another way of looking at this year's temperature and precipitation within the historical distribution, for a specific combination of averaging periods (6 months for precipitation, 3 months for temperature).  I picked this combination because McGrath had the driest January-June period on record and the warmest April-June period.  I've also colored the years that had strong El Niño or La Niña conditions in April through June, just to see how strong the El Niño connection is.  It seems that recent warmth is consistent with the El Niño influence in both Fairbanks and McGrath, and there's a slight tilt towards drier conditions in Fairbanks during strong El Niño conditions (as we noted here).  However, La Niña does not necessarily bring the opposite anomalies, as some of the strongest La Niña years were also very dry in Fairbanks in late spring.



Here's a graphical depiction of this year's record year-to-date precipitation deficit in McGrath.  The moisture situation has improved slightly in the past couple of weeks, but we're still at the driest year-to-date on record.


7 comments:

  1. A reminder of previous work done on the PDO and El Nino:
    http://ak-wx.blogspot.com/2014/04/el-nino-and-spring.html
    http://ak-wx.blogspot.com/2014/03/el-nino-and-summer.html
    http://ak-wx.blogspot.com/2014/09/el-nino-and-positive-pdo-in-winter.html

    The above works suggested to me that while El Nino can be a powerful weather motivator, the PDO has a much larger influence. So with both indices being extremely positive, it's no wonder that we've been hot and dry.

    ReplyDelete
    Replies
    1. Eric, I agree. It would be interesting to try to quantify the relative magnitude of the impacts at different times of the year.

      Delete
    2. Here's an idea.

      First, find the correlation between the PDO and ENSO by month over the record period. Basically we need to see how independent the two indices are.

      Second, assuming sufficient independence, do a regression off of PDO and ENSO for the temperatures for each climatological month. Then we can plot these coefficients and see the relative relevance of PDO and ENSO for the different times of the year.

      Third, we can use these coefficients to estimate what our temperatures should be. Then the difference between what we modeled and what we observe can be explained by other unknown parameters.

      Fouth, we can then, within reason, estimate the temperatures of the long term forecast based on estimated PDO and ENSO values.

      While I expect this exercise to be only partly predictive, I think it would be a good exercise in statistics and informative in its own way.

      Delete
    3. Eric, good suggestions. The immediate problem is that they are not at all independent: they correlate at roughly R=0.5 throughout the year (with some variation). The approach you suggest may be more suited to independent EOFs like those of Hartmann 2015; the classical PDO is not confined to a single EOF, but at least we have independence.

      http://onlinelibrary.wiley.com/doi/10.1002/2015GL063083/abstract

      I'll give this some more thought. Thanks!

      Delete
  2. Don't forget to review the Blob:

    https://en.wikipedia.org/wiki/The_Blob_(Pacific_Ocean)
    http://onlinelibrary.wiley.com/doi/10.1002/2015GL063306/full

    Gary

    ReplyDelete
  3. This comment has been removed by the author.

    ReplyDelete
  4. Predictions for continued warmth for Alaska...30 day and long range as of yesterday. We could use an El Nino winter to allow more outdoor activity:

    http://www.cpc.ncep.noaa.gov/products/predictions/long_range/fxus07.html
    http://www.cpc.ncep.noaa.gov/products/predictions/long_range/fxus05.html

    Visual short and long range outlooks:

    http://www.cpcpara.ncep.noaa.gov

    Gary

    ReplyDelete