Winter Season Severity Index (AWSSI) Trend: Lower 48

I've written about the Accumulated Winter Season Severity Index (AWSSI) before (Mayes Boustead et al., 2015). It's perhaps the only tool to fully encapsulate the intensity/severity of a winter season. It is not perfect, but it's more than sufficient to conduct assessments and comparisons between locations and between seasons.

Quick recap, during the winter, you accumulate winter severity points (AWSSI points) for low temperature, high temperature, new snowfall, and snow depth each day. The more wintry the value, the more points it gets. Table 1 shows the values that can accumulate daily based on the magnitude of the climate variables. Over the course of the season across the entire U.S., the low temperature column is where 46% of the season's points accumulate. Snow depth accounts for 34%, high temperature accounts for 12%, and snowfall accounts for 8%. In more southerly latitudes, most points come from the low temperature.

Table 1. AWSSI point values.

Maps:

The following figures were generated for the 1948-49 to 2020-21 winter seasons using all available station data in the GHCN-D climate database. As long as a station had no fewer than 7 missing days for the October-April time period, it was included. There was no minimum number of years for inclusion. For each year, all qualifying stations were used. Some years had more available stations than others. On average, 2000-4000 stations were used in each year's analysis. 1948-49 was selected as the start year because there was a significant increase in U.S. station density beginning in 1948. 

For seasonal average, maximum, and minimum, I used an inverse distance weighted (IDW) algorithm with 15 kilometer grid cells. For trend analysis, I used 150 km grid cells because there is sufficient noise between neighboring stations to require a broader generalization.

Note: this is a Lower 48 analysis only (for now) because large data gaps, and because the lack of Canadian snowfall / snow depth data leave odd artifacts behind.

Figure 1: 1948-49 to 2020-21 average.

Figure 2: 1948-49 to 2020-21 maximum seasonal value.

Figure 3: 1948-49 to 2020-21 minimum seasonal value.

Figure 4: 1948-49 to 2020-21 change in AWSSI points (raw point values). Trend is the difference between the beginning and end points of a linear regression line (150 km grid cells).

Figure 5: 1948-49 to 2020-21 change in AWSSI points (as a percentage). Trend is the difference between the beginning and end points of a linear regression line divided by the starting value times one hundred (150 km grid cells).

Figure 6: 1948-49 to 2020-21 average length of winter in days. The beginning of winter is defined as the date of the first measurable snow, first daily max temp ≤ 32°F, or December 1st – whichever is first. The end date is the last day with measurable snow, the last day with snow on the ground, the last day with a max temp ≤ 32, or February 28/29 – whichever is latest.

Figure 7: 1948-49 to 2020-21 change in the length of winter. Trend is the difference between the beginning and end points of a linear regression line divided by the starting value times one hundred (150 km grid cells). The beginning of winter is defined as the date of the first measurable snow, first daily max temp ≤ 32°F, or December 1st – whichever is first. The end date is the last day with measurable snow, the last day with snow on the ground, the last day with a max temp ≤ 32, or February 28/29 – whichever is latest.

Figure 8. All qualifying stations used in the analysis depicted in all figures.

Video 1. Each year's AWSSI value from 1948-49 to 2020-21. 

References:

Mayes Boustead, B.E., Hilberg, S.D., Shulski, M.D. and Hubbard, K.G. (2015) The accumulated winter season severity index (AWSSI). Journal of Applied Meteorology and Climatology, 54, 1693–1712. https://doi-org.uaf.idm.oclc.org/10.1175/JAMC-D-14-0217.1.

Ford, T. W., Budikova, D., & Wright, J. D. (2021). Characterizing winter season severity in the Midwest United States, Part I: Climatology and recent trends. International Journal of Climatology, 1– 16. https://doi-org.uaf.idm.oclc.org/10.1002/joc.7431