Anchorage Termination Dust

Background

Here in Anchorage, there is a local term for the first snowfall of the season that falls on the nearby Chugach Mountains – Termination Dust. According to the Dictionary of Alaska English (see Fig. 1), it represents the end-of-summer snow that falls on the surrounding mountains. The term appears to have originated, or was at least popularized, in Anchorage. That said, the first known published use of the term was in 1953 in the Fairbanks Daily Newsminer (Fig. 2).

As the air begins to cool for the season, the freezing level gradually drops. Occasionally, it drops low enough to cause snow to form at the elevation below the surrounding peaks. Fig 3 shows the percent of the time that the weather balloon launched twice daily in Anchorage is less than or equal to +1°C (34°F) at the 850 mb geopotential height (approximately 4,700' in August). This is a temperature where it's cold enough for precipitation to fall as snow. On July and August days when this happens, the average elevation of the 850 mb height level is 4,600'. When precipitation is falling, that cold air is dragged lower down in the atmosphere hundreds of feet. 

If you ask the average Anchorage resident, the most common description of Termination Dust is the snow that marks the beginning of the end of fall. It's a marker for people to do the things necessary to get ready for the upcoming winter.

Criteria

OK, so that's a little of the background. Now, as an Anchorage-based climatologist, EVERY SINGLE YEAR, when snow first hits the peaks, I get asked "is this Termination Dust?" My first response is that there is no one definition. Everyone has their own idea of what it is. Does a coating along the top of the mountains in July count? What about the snow that frequently dots the top of Pioneer Peak above 6,000' as seen during the Alaska State Fair in August? Is that Termination Dust?

Without a consistent definition, there's no way to track how it changes over time. As our climate warms, we'd like to have some data to show how this aspect of the climate responds to increasing temperatures. The Nenana Ice Classic and Fairbanks green-up are some other Alaska-specific seasonal markers that we note the annual trends of because someone took the time to mark down when they occurred.

As a climate scientist and a long-time Anchorage resident, I have given this a fair amount of thought over the years. Here are my criteria for Termination Dust:

1) Must occur on or After August 1st. Period. Since it represents the beginning of the end of summer, it makes no sense to allow a snow that occurs before peak summer temperatures typically occur (mid to late July). Inspection of Fig. 3 shows that early August is when the atmosphere at 4,000' to 5,000' begins to cool off.

2) There must be a solid snow cover above 4,000' as viewed from Midtown Anchorage across most of the front range. There should be no ambiguity. If one person thinks it's Termination Dust and another does not, it probably isn't. I chose 4,000' for the solid snow because most of the tops of the mountains in the Chugach Mountain front range that you see from town go above 4,000'. At this elevation, more that 50% of the mountaintop horizon is covered. Photo 1 has an annotated drone photo showing Front Range peaks with their elevation values and where the 4,000' line is as viewed from south Anchorage. [The perspective from other parts of town will be different.]

Photo 2 is also a drone photo with an approximately 3,800' snowfall from 2020. Photos 3 and 4 show a near Termination Dust right at 4,000'. Photos 5 & 6 show lower elevation snows. These lower elevation snows are too low to be a requirement to count as Termination Dust, but if it's the first event, they obviously count. Remember, this is an Anchorage-specific definition. Many places across Alaska now incorporate the Termination Dust terminology to describe their local first mountain snow. 

Alternatively, any accumulating snow down to 3,500' should count. At this elevation, Flattop Mountain gets snow.

3) The snow must hang around for at least 12 hours and still cover most of the areas half a day later. If it snows and then quickly melts due to sun, warm temperatures, or rain, then it doesn't count. You need several inches of snow to survive half a day hours from mid-August to mid-September at 4,000'. Since there are no trees above this elevation, the snow is sitting on bare ground.

4) There is only one Termination Dust event per season. By definition it is a "first" event. If there's a Termination Dust, then it melts away, and another event comes along two weeks later that looks exactly the same, only the first one counts. 

Examples: Are the following First Snows Termination Dust?

A) A 4,000' solid snow cover across the horizon on July 15th. Not Termination Dust

B) Snow dots the tops of the 5,000' peaks (e.g., O'Malley Peak, South Suicide Peak) on August 15th. Not Termination Dust

C) Snow covers the peaks in the Eagle River valley on September 1st above 4,000' but not the peaks visible from Midtown above 4,000'. Not Termination Dust (for Anchorage)

D) Heavy snow covers the Front Range at Flattop Mountain elevation and persists until the next day. Termination Dust

E) A light accumulation of snow covers the Front Range at Flattop Mountain elevation but melts out a few hours later. Termination Dust.

F) Heavy snow covers areas above 4,000' for several days and then melts out but no one sees it because it's in the clouds the entire time. Not Termination Dust

G) No snow in the mountains all Fall, but then snow falls everywhere down to sea level on October 1st. Termination Dust

Remarks

Even with a somewhat formal definition outlined above, there will still be some subjectivity. Perhaps a consensus by observers at the National Weather Service in Anchorage can make the "call" just as they do in Fairbanks for green-up.

Photos

Photo 1. Chugach Mountain peaks as viewed from south Anchorage (Abbott Rd.) with names annotated. Bottom panel shows approximate area covered by snow at 4,000' from this perspective. Photo credit: Brian Brettschneider.

Photo 2. Similar perspective as Photo 1, but with actual snow near the 3,800' level. Photo credit: Brian Brettschneider.

Photo 3. Snow level at 3,800'. Snow is covering Kanchee, Konoya, Tikishla, and Wolverine Peaks. Far peak on right (no snow) is Rusty Point. Photo credit: Brian Brettschneider.

Photo 4. Snow level at 3,900'-4,000'. Snow is covering O'Malley Peak, The Wedge, Ptarmigan Peak, Peak 3, and South Suicide Peak. Photo credit: Brian Brettschneider.

Photo 5.  Snow level at 3,500'. Snow is covering Kanchee, Konoya, Tikishla, and Wolverine Peaks. More area between peaks is snow covered than in Photo 1. Photo credit: Brian Brettschneider.

Photo 6.  Snow level at 3,000'. Snow is covering Wolverine Peak, O'Malley Peak, The Wedge, and Flattop Mountain. The snow is nearly unbroken from horizon-to-horizon. Photo credit: Brian Brettschneider.

Figures

Fig 1. Article from Aug 25, 1969, Anchorage Daily Times. It attributes the term to a man named Ken Sheppard from 20 years prior (~1949). 

Fig 2. Definition of Termination Dust from the Dictionary of Alaska English (Tabbert 1991). Thanks to Annie Zak for the image ( https://twitter.com/annie_zak/status/779465428217176064 ). 

Fig 3. Early reference to Termination Dust from the September 22, 1953, Fairbanks Daily Newsminer. Thanks to Rick Thoman for the image ( https://twitter.com/AlaskaWx/status/779486539923337216 ). 

Fig 4. Percentage of the time that the 850 mb temperature in Anchorage is ≤ 1°C (<34°F).

Acknowledgements: A very special thank you to Rick Thoman for the research resulting in Fig. 2, the suggestion for Fig 3., and as a sounding board for ideas.

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Termination Frost?

Is there such thing as Termination Frost? The first time of the year there is a little frost on a car windshield, people note it as the first frost of the year. From a growing-season point of view, I would argue that there needs to be significant coverage of frost on grassy (or low-lying) vegetation at a location for it to be considered Termination Frost.

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Dates:

1956: September 19th

1957: September 27th

2008: September 26th

2009: September 22nd

2010: September 26th

2011: September 20th

2012: September 5th

2013: September 19

2014: September 29th

2015: August 29th

2016: September 22nd

2017: October 5th

2018: September 24th

2019: September 23rd

2020: October 12

2021: September 15th

2022: September 9th

2023: September 6th

2024: September 27th (?)

2008-2024 Average: September 20th

2008-2024 Median: September 22nd

Wettest Months of the Year: 1991-2020

Using the 1991-2020 gridded climate normals, here are the ranking from wettest to driest of each of the 12 months of the year. 

IMPORTANT NOTE: I standardized the length of each month for an apples-to-apples comparison. For example, if February averages 3.00" of precipitation and March averages 3.05" of precipitation, February will have a higher rank since their precipitation fell on fewer days. It is functionally a ranking of average daily precipitation. Also, Hawai'i was not included in this data set, so their data is not shown on the maps.

Heavy Precipitation Trends

By it's very definition, a warming world will be, well warmer. Surprise! What about precipitation? What about heavy precipitation events? There is a strong theoretical framework to suggest that a warmer world will be wetter overall and that more frequent heavy precipitation events will occur. Of course the world is warmer now than it was 10 or 20 or 50 years ago. We do not need to speculate about the wetter world hypothesis, we can test it. 

NCA4

The 4th National Climate Assessment (NCA4) looked at past and future trends in heavy precipitation by looking at the change in 99th percentile events. Fig. 1 shows a 59-year trend in these 99th percentile events.

Fig 1. Regional change in 99th percentile precipitation events from the 4th National Climate Assessment during the 1958-2016 period. This is Figure 2.6 in the report. 

The methodology of the NCA4 map is shown above is as follows:

1. Stations were chosen with less than 10% missing precipitation data for 1901-2016
2. For each station, the 99th percentile threshold of daily precipitation was determined from the 1901-2016 data using only days with at least 0.5 mm of precipitation.
3. For each station, for each year, the total amount of precipitation falling on days when the daily precipitation exceeds the 99th percentile threshold was calculated.
4. For each one-degree by one-degree grid box, for each year with available data, the average amount of precipitation exceeding the 99th percentile was calculated for all stations in a grid box.
5. For each region, for each year, we calculated the average amount of precipitation exceeding the 99th percentile threshold was calculated by averaging all of the grid box values in each region.
6. For each region, the trend over 1901-2016 using ordinary least squares regression.
7. The change was calculated as the percentage difference between the end points of the trend line. The end points are 1901 and 2016.

Fig. 1 shows a notable increase of heavy precipitation events in all regions, with the largest increases the farther east you go. The NCA4 map is functionally showing different recurrence intervals at different locations though. Since they are looking at a top 1% precipitation event, if precipitation fell on 100 days per year, it's a value you expect to occur once per year. If precipitation falls 50 days per year, it's a value you expect to occur every other year. Now you are comparing a 1-year event at one location with a 2-year event at another location. This problem is exacerbated the farther west you go. 

If the NCA4 analysis looked at lower percentile events (e.g., 90th or 75th percentile), the temporal problem would go away since practically every location receives measurable precipitation 4+ or 10+ times per year.

Alternate Methodology

A slightly different way of thinking about it is in terms of the days per year that certain precipitation values are expected to occur. If you find the value that occurs on average 5 days per year over a baseline time period, you can count the annual frequency of that event and build a time series to assess whether it is increasing or decreasing. If you do the same thing at a different location 1,000 km away, the trends (not the values) are directly comparable since the time components are the same. 

For this study, I did just that by extracting daily precipitation values for 310 midnight-to-midnight stations in the U.S. and 20 stations in Canada. The period of record in this study is 1951-2020. A 70-year period is more than long enough to make statements about long-term trends. For inclusion in this study, a station must have 65+ complete years during the 70-year period. A complete year means no more than seven missing days.

The establishment of a baseline period is necessary to not only identify an overall trend, but to specifically identify whether the current period is experiencing more of these days than in prior periods. The 1951-1990 period was used to compute a simple average value for the precipitation amount that occurred 3 days per year, 5 days per year, 10 days per year, and 25 days per year.

Example

Fig 2. Sample data for Dallas-Ft. Worth, TX, International Airport.

Fig. 2 shows a sample of how the data for Dallas-Ft. Worth, TX, was computed and evaluated for the precipitation event that occurs 5 days per year. During the 1951-1990 baseline period, every day's precipitation total (including 0.00" and Trace) were collected and sorted. Assuming no missing days, the 200th largest precipitation total during that 40-year period is the value that occurs 5 days per year on average. (Note: adjustments were made for missing days.) In the case of Dallas-Ft. Worth, this precipitation value was 1.41".

Next, we count the number of days in all years that had at least 1.41" of precipitation on a calendar day during the 1951-2020 period. The green line in Fig. 2 shows the annual time series. Finally, we fit a linear regression line to the 70-year time series and measure the difference (as a percentage) between the starting point of the regression line in 1951 and the ending point of the regression line in 2020. In the case of Dallas-Ft. Worth, the dashed black (regression) line goes from 4.15 to 6.72. This ending value is 63% greater than the beginning value.

What I like about this methodology (of course I like my methodology the best!) is that it lets you do a meaningful comparison across both space and time. The NCA4 methodology of using pure percentiles has a time problem. Other studies that look at changes in days per year with 1" or 2" of precipitation have a space problem since those values are rare in some areas and common in others. 

Maps and Interpretation

Now that we have the methodology out of the way, let's look at the maps. Specifically, there are maps for the trend change in the recurrence of the event that historically occurred 3 days per year, 5 days per year, 10 days per year, and 25 days per year. The first four maps (Figs 3-6) show the changes as a percentage at the station level. The next four maps (Figs 7-10) show the changes as a percentage at the state level by interpolating a weighted surface based on station values. The final four maps (Figs 11-14) show the precipitation values that were being evaluated for each time period for each station.

The obvious conclusion to draw is that the medium- and low-frequency precipitation events are becoming more frequent. This is not surprising. Unlike the NCA4 map, which looked at the very low frequency events, this study looks at the rate that slightly more common precipitation events occur and confirms that they are increasing as well.

Precipitation Change Maps (Stations)

Fig 3. Change in the frequency of precipitation events that historically (1951-1990) occurred 3 days per year by station. U.S. average is +30% increase. 

Fig 4. Change in the frequency of precipitation events that historically (1951-1990) occurred 5 days per year by station. U.S. average is +26% increase. 

Fig 5. Change in the frequency of precipitation events that historically (1951-1990) occurred 10 days per year by station. U.S. average is +20% increase

Fig 6. Change in the frequency of precipitation events that historically (1951-1990) occurred 25 days per year by station. U.S. average is +14% increase

Precipitation Change Maps (States)

Fig. 7. Change in the frequency of precipitation events that historically (1951-1990) occurred 3 days per year by state. U.S. average is +30% increase.

Fig. 8. Change in the frequency of precipitation events that historically (1951-1990) occurred 5 days per year by state. U.S. average is +26% increase.

Fig. 9. Change in the frequency of precipitation events that historically (1951-1990) occurred 10 days per year by state. U.S. average is +20% increase.

Fig. 10. Change in the frequency of precipitation events that historically (1951-1990) occurred 25 days per year by state. U.S. average is +14% increase.

Precipitation Amount Maps

Fig 11. Amount of precipitation that historically (1951-1990) occurred 3 days per year.

Fig 12. Amount of precipitation that historically (1951-1990) occurred 5 days per year.

Fig 13. Amount of precipitation that historically (1951-1990) occurred 10 days per year.

Fig 14. Amount of precipitation that historically (1951-1990) occurred 25 days per year.

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For the Alaska folks, here are charts for several major stations around the state. Stations will be in alphabetical order. No figure captions are given. They are similar to Fig. 2, except that each of the four precipitation categories are shown.

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Here are 4-panel plots of stations outside of Alaska. The 45 plots are in alphabetical order by city name.