Thursday, May 16, 2019

ERA5 Data for Alaska - Including Download Link

Back in November I took an initial look at the new ERA5 reanalysis data set from the world-leading ECMWF weather modeling and forecasting center in Europe.  At the time, the ERA5 data was only available for 2000-2017, but the reanalysis now extends back to 1979, and a further extension to 1950 will soon come online.  The high quality of the data assimilation and modeling framework that's used to produce the reanalysis makes this a real treasure trove of historical climate data.

It's an interesting exercise to compare the ERA5 data for Alaska to NOAA's climate division data, produced by NCEI.  For many years the climate division data was only available for the lower 48, but in 2015 the data set was expanded to include 13 climate zones in Alaska; here's a map.

To facilitate a direct comparison, I calculated area-averages for several ERA5 variables within each of Alaska's climate divisions.  For example, there are 605 ERA5 grid cells that at least partially intersect the Southeast Interior division; so I calculated the area of the intersection for each grid cell and added up the fractional contributions to the total area of the Southeast Interior zone.

Here's a chart showing the mean temperatures for January and for July in the Southeast Interior (which includes Fairbanks).  Aside from a modest cold bias in the ERA5 values in January, the performance is outstanding.

The situation is not quite as good in the North Slope division, which is not surprising as the observing network is more sparse, and moreover weather analysis and forecasting models (like the ECMWF model that underpins ERA5) often have a more difficult time with atmospheric physics in the Arctic.

Interestingly the 1979-2018 linear temperature trends are similar for January, but the ERA5 trend is much smaller than NCEI's trend for July in the North Slope division.

Looking at precipitation, ERA5 does fairly well for the Southeast Interior in both January and July, but again the agreement is not as good for the North Slope.  Precipitation is always a major challenge for reanalysis, and so these results are pretty good.

Finally, I did a quick comparison of ERA5 solar radiation to the CERES gridded data for the Southeast Interior, and again I used an area average for both data sets.  The results show a very close correspondence for the month of March, but there is only modest agreement in July.

We could of course keep going with all sorts of comparisons between ERA5 and other data sets, and between ERA5 and historical climate observations around the state, but there's no doubt that ERA5 is a very high quality reanalysis.  Beyond the pure fidelity of the data, however, the real value of the reanalysis is that it's spatially and temporally complete; and ERA5 even includes uncertainty estimates, although I haven't looked at that aspect yet.

For readers who might like to take a look at the Alaska data themselves, the following link provides the area-averaged data for the 13 climate divisions, including mean temperature, precipitation, solar radiation, and 10m wind speed.

Thursday, May 9, 2019

Follow-Up on Break-Up

As a quick follow-up on the topic of predicting breakup dates, I looked at whether breakup is more closely related to hourly temperatures above freezing rather than daily mean temperatures above freezing.  This is something that reader Eric suggested a while back, and reader BJ re-emphasized that daily average temperatures could be misleading.

I pulled out hourly temperature data from 1998-2018 in Fairbanks and calculated the accumulation of thaw degree hours up until the date of breakup in Nenana, i.e. the sum of the hourly temperature excess (if any) above 32°F.  Historical hourly data from Nenana is not quite complete enough for this task, so data from Fairbanks will have to do.

Here's a scatter plot of thaw degree hours (TDHs) versus thaw degree days (TDDs) accumulated through breakup; click to enlarge.

Not surprisingly, it's a very good relationship, but the best-fit line is flatter than would be expected for a one-to-one relationship.  Superficially, this suggests that hourly data is indeed a better predictor of breakup date than daily data, because there is less variance in TDHs at breakup than in TDDs at breakup.  (Imagine if TDHs were a perfect predictor: the best-fit line would be horizontal.)  The standard deviations of the two variables demonstrate the difference: the standard deviation of TDHs at breakup is 25% of their mean value, whereas TDDs have a standard deviation of 31% of the mean value.

A bit more work confirms that the typical range of thaw degree hours at breakup is associated with a slightly smaller date window than for thaw degree days.  See the chart below, which attempts to illustrate this.  If we're using daily data, we find that a typical (80%) range of TDDs at breakup corresponds to a 7-day climatological window, but if we use hourly data the window is narrowed to about 6 days.  It's obviously a small difference - hourly data is no holy grail for breakup prediction - but it seems that readers were correct to suggest that we can do better than daily average temperatures.  A more thorough investigation would require a more careful modeling effort with daily data... perhaps I'll return to that next spring.

Friday, May 3, 2019

Snow After Green-Up

According to the National Weather Service office in Fairbanks, green-up occurred on West Chena Ridge on Wednesday evening after the temperature reached a summer-like 70°F earlier in the day.  This means that the hillside turned distinctly green for the first time as birch and aspen leaves emerged en masse.

1101 PM AKDT WED MAY 1 2019

1101 PM AKDT WED MAY 1 2019




The 70°F on May 1st was one of the earliest occurrences on record for such warmth, but a wild swing back to colder weather has occurred in the short time since.  This morning rain turned to mixed rain and snow at valley level, and then finally to plain snow before tapering off.  Some accumulations were observed in the hills, but apparently not in Fairbanks itself.

Looking back at the history of Fairbanks hourly weather data since 1950, I can't find any other instance of plain snow in the hourly observations after the date of the first 70°F.  There have been a number of instances of light mixed rain and snow, but most were very light with visibility of 10 miles or more, and plain snow (as occurred for a couple of hours this morning) appears to be unprecedented after the first 70°F day.  However, it should be noted that May 27, 1978 brought enough wet rain/snow to accumulate 0.1" , and that was 2 weeks after the first 70°F of the year.

More substantial snow occurred today at locations farther up the Tanana River valley, such as Tok and Northway.  And the history shows this isn't unprecedented; in mid-May 1995, 5 inches of snow fell in Northway less than a week after the temperature reached a remarkable 82°F.  The temperature only reached that level on 3 more days that year in Northway (elevation 1715').

Saturday, April 27, 2019

Breakup Modeling

Following on from the last post, I'd like to discuss briefly some results that came out of an attempt to simulate the distribution of breakup dates for the Tanana River at Nenana.  The annual Nenana guessing game is of course a venerable Alaskan tradition, and the resulting historical record of breakup is an invaluable piece of climate data extending back to a time when modern weather measurements were sparse and sometimes rudimentary.  Here's a chart of the long-term Nenana history, courtesy of Rick Thoman; click to enlarge.

It goes without saying that the trend towards earlier breakup dates is consistent with the long-term warming trend, but it's interesting to consider whether we can say anything about how consistent the breakup trend is with the measured temperature trend.  Has breakup advanced more or less than we would expect based on observed temperatures?

In previous posts I've expressed the view that breakup dates can be modeled quite well using the accumulation of thaw degree days (TDDs), i.e. the excess of daily mean temperatures above 32°F; the ice typically goes out within a fairly well-defined range of  TDD values.  Of course there are other factors at play, including ice thickness, the amount of sunshine, and occasionally heavy precipitation that brings forward the breakup date, but there's no doubt that air temperature is the key variable that drives breakup timing in most years.

Assuming then that we need to model breakup in terms of TDDs, we have to deal with the complication that TDDs are not linearly related to mean temperature (unless the daily mean temperature always stays on one side of freezing).  As a consequence, there's no simple way to translate a long-term temperature change of X°F into Y TDDs and thereby derive the change in breakup date using the observed TDD-breakup relationship.  Finding the change in TDDs requires a more careful approach that deals adequately with the temperature-TDD relationship.

A related challenge is that the variance of temperature is an essential component of the TDD accumulation, and so temperature variance and even skewness must be accounted for in the model.  If the daily mean temperature just followed the long-term normal each day, with no other variance, then TDDs would accumulate much more slowly than they actually do, because it's the above-normal days that provide most of the TDDs in the early and middle part of the meltout process each year.  Only later in the thaw can merely normal temperatures do any real damage to the ice.

In light of these considerations, I set up a simulation of daily mean temperatures in Nenana using an ARIMA model based on the statistical characteristics of observed April temperatures from 1999 to 2018.  I decided to use Nenana data rather than Fairbanks because the 1999-2018 relationship between TDDs and breakup is better for Nenana than for Fairbanks (not really a surprise!).  In creating the synthetic temperature data, I accounted for both the changing variance of temperatures through the melt season (i.e. decreasing variance as spring advances) and also the fairly substantial skewness of the temperature distribution (i.e. a heavier tail on the cold side of normal).

Here are some examples of synthetic temperatures for the first half of the year, with the black line being the 1981-2010 normal.  There is a slight tendency towards above-normal temperatures, because that is what has been observed in April (and most other months) in the last 20 years.  I won't claim that the synthetic series are perfectly realistic, but the final results suggest they are adequate for the purpose of the breakup model.

For each simulation it is straightforward to add up the TDDs and estimate the probability of breakup on each date by referring to the observed joint distribution of TDDs and breakup dates.  For example, the median (1999-2018) TDD value in Nenana on breakup day is 116, so for each simulation we can say that the cumulative probability of breakup reaches 50% when TDDs reach 116.  If we do this not just for the median but for each empirical quantile, then we obtain a cumulative distribution for each simulation; and if we repeat the process many times, we get a smooth result - see below.

The empirical cumulative probability curve is shown with the blue markers; note that several of the breakup dates have occurred more than once, with 1 May occurring 4 times since 1999.

The agreement between the observed and simulated curves is quite good; for example, the median of the simulated curve falls between April 30 and May 1, which is spot on according to the 1999-2018 history.  It's important to note that this good agreement is not guaranteed to occur, because the simulated temperatures may or may not produce realistic rates and timing of TDD accumulations.  To cite an extreme example of a poor simulation, if we assume perfectly normal temperatures every day, the cumulative probability of breakup is much too late and also too narrow - see below.  As I noted above, purely normal temperatures would produce far too few TDDs in the typical date window for breakup.

As an aside, it's interesting to observe how extreme the 2013 outlier was.  According to the simulated distribution - based on the 1999-2018 temperature distribution - there is less than a 0.01% chance of breakup being as late as May 20; this implies it was a one in ten-thousand year event for the modern climate, although I'd be very skeptical of my model's ability to estimate probabilities this far out in the tail.

The final step (for now) in the investigation is to shift the mean temperature up or down to examine how the breakup distribution changes.  Using 5000 simulations at each 1°F increment from 10°F of cooling to 10°F of warming, we arrive at the following result.

It's interesting to see that the sensitivity of breakup date is slightly greater for temperatures below the recent climate, and slightly less for higher temperatures.  This is a consequence of the changing variance through the season, and the fact that I've assumed no change in variance relative to the recent climate.  Under this (probably false) assumption, as the climate warms and breakup moves into a higher-variance portion of the year, it takes more warming to produce the same increase in TDDs (because of the increasing variance).  Alternatively, in a colder climate, with breakup in a lower variance part of the spring, there is a larger response of TDDs to mean temperatures, and breakup dates respond a bit more quickly.

Finally, to address the question I posed at the beginning - what about the observed change in breakup dates?  Well, the helpful trend lines on Rick's chart show that breakup has advanced about 6-7 days since before 1970, and based on the cool side of the chart above, this would correspond to about 3-3.5°F of temperature change.  And this is about right; the mean temperature change in Fairbanks between 1930-1970 and 1999-2018 was +3.2°F in April.  Using this approach, we can say that the long-term breakup history at Nenana strongly supports the long-term historical temperature data from the area, and I find this very encouraging from a climate science perspective.

If we assume then that the modeling results are reliable, how much warming would be needed before an April 14 breakup (as this year) would be typical?  April 14 falls right at the upper edge of my results; about 10°F of climate warming would be required.  Of course, this ignores the many other factors that could influence breakup with such a dramatic degree of climate change, such as the response of ice thickness to massive winter warming.

Wednesday, April 24, 2019

Breakup Dates

Yesterday evening the "official" breakup was recorded at 7:16pm (April 23rd) on the Yukon River at Dawson in the Yukon Territory.  Although the ice again had a very difficult time filling in the channel next to Dawson City this winter, in the end it held on just long enough to avoid setting a new record for early breakup; the record from 2016 stands at 11:15am on the same date.  (However, 2016 was a leap year, so arguably April 23rd was a day later that year.)

Here's a photo of the river this morning, taken from high above on the west side, courtesy of  (Click to enlarge.)

Most readers probably already know that breakup was easily the earliest of record on the Kuskokwim River at Bethel (April 12) and the Tanana River at Nenana (April 14).  The previous record was April 20 in both places.  In view of the extreme warmth that occurred in March, it's really no surprise that new records were set.

Readers may also recall that back in March I ventured to make some forward-looking statements about the likely early breakup at Nenana, so it's worth going back to see how that played out.  The figure below is an update of the one I showed earlier, and it depicts several different elements:

  • Horizontal black line: the median value (141) of accumulated thaw degree days in Fairbanks as of the date of breakup at Nenana.  Historically speaking, breakup is equally likely to occur before or after this number of "heat units" has accumulated.
  • Red and blue lines: 10th and 90th percentiles of thaw degree days (TDDs) at breakup; breakup is 80% likely to occur on a day when accumulated TDDs are in this range.
  • Dashed black line: the median of the 15-day forecast for future TDDs, as of March 26 (the date of the blog post).
  • Gray shading: the middle 80% range of the 15-day forecast distribution
  • Green line: the observed accumulated TDDs this year

It turns out that the forecast from March 26 was considerably too warm, and thawing almost ceased for about 10 days after my post.  This possibility fell inside the range of uncertainty for the forecast, but it wasn't the most likely outcome, and so it pushed back the date of breakup compared to what I thought was most likely.

However, another aspect of the forecast worked out remarkably well: breakup eventually occurred on the day when Fairbanks TDDs reached 141, which coincidentally is exactly equal to the long-term median (i.e. the green line reached the black line on the very date of breakup).  This was lucky; we obviously don't expect to hit the median of a sampling distribution very often.  Nevertheless, it does provide some evidence that the general approach to predicting breakup is valid.

In the next post I'll describe some additional work I've done to extend the TDD/breakup modeling, leading to some interesting results about the sensitivity of breakup dates to long-term changes in average temperature (climate change).

Thursday, April 18, 2019

Winter Lives

A couple of weeks ago I mentioned that the earliest recorded date for spring's permanent meltout of snow cover in Fairbanks was in 2016, when semi-continuous snow cover was seen for the last time on April 8th.  With this year's meltout on April 4th, the record was in jeopardy - but a slightly unusual early spring snowfall has changed the scene once again.

Of course there is usually still snow remaining on the ground at this date in Fairbanks, and last year the depth was measured at 17" on April 18th.  And it's not unusual to get a little bit of snow this late in the season; but the 2.2" that fell yesterday is somewhat unusual; this is only the 18th time with this much snow in Fairbanks after the middle of April (1930-present).  In 2002, 13" of snow fell in the second half of April, and 14" fell in 1992 between May 8 and May 17.

Here's the view from the UAF webcam yesterday morning at about 8:30am.

The balloon sounding from Fairbanks airport reported a temperature of -8.3°C at 850mb yesterday afternoon, and while this is not particularly unusual, it is striking to note that fully two-thirds of the winter (November-March) was warmer than this.  So in this respect we might say that the air mass bringing snow to Fairbanks this week is more wintry than most of the winter that just ended.  The November-March average 850mb temperature this winter was a mere -6.6°C, the warmest on record (2nd and 3rd place go to 2014-15 and 2015-16).

Here's what the 500mb analysis looked like yesterday afternoon, courtesy of Environment Canada; the healthy low pressure system over western Alaska is responsible for the chilly conditions.  (Click to enlarge.)

And here's a sequence of surface observation maps showing the cold air working its way down from the northwest between Monday afternoon and Wednesday afternoon.  The cold is really nothing to write home about at all, but it does feel refreshing to see something more like normal on the map.

Finally, as everyone knows, breakup has already occurred at Nenana and Bethel, and it was the earliest on record for both locations (more on that later).  This morning, however, the Kuskokwim at Bethel was glazed over again with a dusting of fresh snow; this seems like a pretty unusual event (freeze-over after spring breakup), but others might know if it's been seen before.

Friday, April 12, 2019

Snow Depth Conundrum

After last week's early meltout of snow in Fairbanks, I started thinking a bit more about the absence of a long-term trend in the meltout date.  It's a puzzle because late winter temperatures have increased over time; for example, March and April in Fairbanks have been about 3°F warmer since 1980 than they were before, and consequently the accumulated thawing degree days by April 23 (the long-term normal meltout date) have approximately doubled.  The trend towards earlier breakup at Nenana provides independent confirmation of the warming; see this post for the history at Nenana:

As mentioned before, a cursory analysis suggests that higher snow depth at the end of winter could explain the unexpected "resilience" of Fairbanks snow cover compared to earlier decades.  And so we might hypothesize that snowfall has increased over time, but this is not borne out by the data; the chart below shows the March 15 snow depth (purple markers) and the accumulated snowfall (green markers) between the date of establishment of the winter snowpack and March 15.  The long-term trend in snowfall is essentially zero, but there is a rising trend in snow depth (admittedly quite small - about 2.5" over the 90-year history).

What about liquid equivalent precipitation?  If snow density has increased, then precipitation and snowpack water content may have increased despite no change in accumulated snowfall.  Surprisingly, liquid equivalent precipitation also fails to show an increase over time, and in fact there is a slight decreasing trend, although that's mostly because of the incredibly wet winter of 1936-37.

So if precipitation and snowfall haven't increased, then is the snow depth trend just an artifact of changing measurement practices and/or location?  Perhaps, but I'm inclined to believe that snow depth (and presumably snowpack water content) really have increased, because it helps explain the meltout dates.

If we take the ratio of the snow depth to total precipitation, we find a result that suggests there really has been a change in the characteristics of Fairbanks winter precipitation over time; recent decades have produced a notably higher end-of-winter snow depth per inch of precipitation in the previous winter.

Assuming that measurement practices are not to blame, there are only a couple of explanations I can think of here.  One is that cloudiness may have increased, perhaps along with humidity, so that snow evaporation has declined and there is more snow left at the end of winter.  There would be little actual melting of snow prior to March 15, but snowpack can be affected by sunshine, humidity, and wind.  I wouldn't be surprised if cloudiness has increased, but rising temperatures typically dictate rising evaporation rates even if relative humidity increases a bit, so I am not sure how plausible this explanation is.

Another possibility is that Fairbanks used to see more of its winter precipitation as rain, not snow.  Admittedly this seems like an absurd proposition, because freezing (or plain) rain has been a notable winter problem in recent years and seems unlikely to have occurred more often in the colder winters of the past.  However, we do know that a few winters of long ago (e.g. 1936-37) produced some extreme rainfall events, so perhaps we shouldn't dismiss the idea out of hand.  It may be conceivable that the recent climate has produced more of the winter's precipitation as snow, thereby contributing more to the snow pack - but more dense snow, so as not to increase the total snowfall (or else snow depth measuring practices have changed over time).

Can anyone suggest other aspects of the problem that I may have overlooked?  It would be nice to be able to nail down a good explanation for why meltout dates have defied the long-term warming trend.