In the results below, the percentage-point change (%, from 1979–2017) and the number of occurrences (days) per year for each weather type are discussed. Separate analyses were also computed for traditional meteorological seasons. While calculated at individual points, for simplicity, results were also summarized for separate regions (Fig. 1) and discussed below.

Fig. 1 The regions discussed in this research. Note that regions 16 and 17 are not included as they are located south of the study domain Full size image

Throughout most of the US and Canada, all cool WTs [Dry Cool (DC), Cool (C), Humid Cool (HC)] show substantial decreases, while all warm WTs [Dry Warm (DW), Warm (W), Humid Warm (HW)] show marked increased frequency from 1979–2017 (Fig. 2). In terms of magnitude, there is only a slight change in the frequency of transitional WTs [Cold Front Passage (CFP) and Warm Front Passage (WFP)], with both increasing in frequency in much of the US (significantly in parts of the West) and decreasing over all but the extreme western portions of Canada. On average across the study domain, of the 11 GWTC weather types, HW and DW showed the most widespread significant trends towards more frequent occurrences (+6.1 and +2.9%, respectively), at the expense of C and DC (−5.7 and −4.5% respectively), though with substantial geographic variability. On average across the domain of study, this equates to a net gain of +22 HW days/year (between the start and end of the record) and +10 DW days/year, at the expense of −21 Cool days/year and −17 DC days/year (Fig. 2). Warm WT days also increased by 3.4% (+13 days/year) on average. Combined, across the domain as a whole, the three warm WTs have increased by 12.4% (+45 days/year) largely at the expense of the three cool WTs, decreasing by −11.8% (−43 days/year) over the 39-year period. Seasonally, the largest changes are in autumn, when WT frequencies change an average of over 37 days/season (Fig. 3). When year-over-year occurrences of WTs are examined, it should be noted that many of these trends are non-linear, especially the increase in HW and the decrease in DC (Fig. 4).

Fig. 2 Annual change in the number of occurrences (per year) of each WT in each region, 1979 to 2017. Note that regions 16 and 17 are not included (as they are outside of the study domain). Darker reds (blues) indicate progressively more positive (negative) changes Full size image

Fig. 3 Domain-wide average change in the number of occurrences per season for each WT, 1979 to 2017. The rightmost (Total) column is the summed absolute value of the changes for each season. Darker reds (blues) indicate progressively more positive (negative) changes Full size image

Fig. 4 Year-over-year plots of the number of occurrences of each WT averaged across the entire domain. The black line in each plot is a third-order polynomial fit to the underlying data in the bar graphs. Numbers in the title of each subplot indicate the total number of days/year change in each WT as calculated using Theil-Sen (and thus, match the numbers in Fig. 2). NOTE: the y-axis in each subplot can differ Full size image

Spatially, the most widespread changes are noted in northeastern Canada (Fig. 5), around Hudson Bay and the Canadian archipelago (Regions 7 and 9), especially with the HW, C and DC weather types. Here, frequency changes are on the order of +/− 23 to 30 days/year, with an average change of nearly +42 days/year for the Warm WT and −48 days/year (−13.1%) for the Cool WT across Region 9—the largest change of any WT in any region. Further, many of these changes are highly non-linear (Fig. S6). In these same regions, on a seasonal basis, the greatest magnitude of frequency changes comes in autumn (September-November) and winter (December-February). In autumn these areas have seen decreases of 6–14 days/season of each of the three cool WTs (HC, C and DC) and gaining 6 to 12 days/season of each of the warm WTs (HW, W, and DW) within that three month period (Table S3). In winter, the changes are heavily concentrated in extreme north-central Canada and the Canadian Archipelago (Region 9), where each of the cool and warm WTs change by at least +/− 8 days/season, with the Warm WT increasing by 17 days/season (about 40% of the annual change, Table S4). While frequency changes of these WTs in summer (June-August; Table S2) and spring (March-May; Table S1)—especially with decreased Cool WTs—also largely show these respective trends, their magnitude and geographic coverage are less than the changes in autumn and winter.

Fig. 5 The percentage-point change in the annual percent-frequency of occurrence of each WT over the period 1979–2017. Note that the 9 ‘core WTs’ share the large color bar, while the two ‘transitional WTs’ share the smaller colorbar. White areas indicate areas of near-zero change. Dots show locations of statistical significance (p < 0.05) Full size image

The significant frequency trends are largely in line with previous research discussing Arctic amplification.2,3 This region is experiencing 2–3 °C higher average temperatures over past few decades along with a nearly concordant rise in dew point temperatures (Fig. 6). Furthermore, the greatest increase in temperatures in these regions are largely seen in autumn3 as the air cools to temperatures lower than those at the sea surface, leading to a net transfer of excess heat to the lower troposphere. This net heat flux feeds back on itself, slowing sea ice growth in winter and changing surface albedo,17 leading to increased evaporation and greater atmospheric moisture—likely contributing to the substantial increases (decreases) in W and HW (C and DC) WTs in Northeastern Canada in these two seasons.

Fig. 6 Change in mean annual temperature (top) and dew point temperature (bottom), computed from Theil-Sen slope estimates of annually averaged monthly average temperatures (in °C) over the period 1979–2017. Darkest colors on both ends of each colorbar represent the 5th and 95th percentiles of distributions Full size image

Separate from the Arctic, another major area of changed WT frequency is noted with the DW type in the Southern US and most of Northern Mexico, where this WT is occurring +26–40 more days per year on average. While experiencing lesser magnitude temperature changes (1–2 °C warmer) than the Arctic, when combined with a slight decrease in dew point over the same period, DW frequency has increased +7.0 to +10.9% in these areas annually, including 10–16 more DW days in spring and 5–9 more DW days in summer. For a location that is already hot, dry, facing water shortages, and experiencing increasing population,18 this trend is particularly problematic in terms of human health, especially with an aging population (e.g., refs. 19,20). Furthermore, in southwestern Texas and northern Mexico (Region 3) in particular, much of the gain in both the W and HW WTs comes in summer, likely adding to this public health burden.

Contrasting with the rest of the study domain, Northwestern Canada shows a strong trend towards more frequent humid types [HC, Humid (H) and HW] at the expense of dry types [DC, Dry (D), and DW]. Nowhere is this more apparent than in Region 13, stretching from Saskatchewan to the Yukon-Alaska border, where the humid types occur anywhere from 16–21 more times per year currently, and all dry types occur 14–16 fewer times per year. Region 12 along the extreme west coast of Canada shows similar trends with all but DC. These trends are mostly a reflection of the changes in summer and, to a lesser extent, in spring. This apparent divergence from the trends noted in the rest of the country, however, are largely unsurprising considering the region’s negligible warming over the period, but its substantial rise in dew point since 1979 (Fig. 6). In the opposite corner of the continent, Florida also shows this same pattern (increased humid types, decreased dry types), with the exception of DW, as it too has a slight increase in dew point and only a weak increase in temperature over the 39-year period.

Any seasonal geographic variability that does not show up in the annual analysis occurs mostly in the spring and is fairly minor (Fig. S2). Foremost are the uptick in HW days in the eastern US (+9 days/spring in Region 4, 43% of the annual total change in the region), the lack of decrease in Cool WTs throughout most of Canada, and the slight increase of DC in much of the northwest. Outside of spring, a significant increase in DC in the Desert Southwest in winter is also of note (Fig. S4). This last one is mostly offset by decreases in DC in other seasons yielding mostly insignificant annual changes. However, this can still be problematic, especially since the impact of weather types on human health often varies by season. For example, Lee (2015)11 found that DC weather types in winter are related to increased mortality, while DW and HW weather types are related to decreased mortality. However, in summer, these impacts are opposite.21

The SSC has also been used in a number of papers to examine weather-type frequency changes in parts of North America. Among them, Vanos and Cakmak (2013)13 found similar changes in Canada to those found herein. Of note, a Dry Polar WT is significantly decreasing in frequency in most sub-regions of the country over the 60+ year period of record, especially in summer, where some regions are experiencing about 8 fewer Dry Polar days/summer. Oppositely, a Moist Tropical weather type was found to significantly increase in frequency over the same time period (by up to 5 days in some regions), especially in summer. Unfortunately, the SSC and GWTC are not directly comparable (the SSC is based on surface observations, while the GWTC is based on reanalysis and classifies spatiotemporally-relative differences from average on a fine-scale grid; please see Lee, 201416 for a detailed discussion on the differences in these two classifications). Thus, especially in the Arctic regions, the Dry Polar weather type becomes nearly ubiquitous in the SSC, while the DC WT of the GWTC maintains a similar frequency throughout all seasons. Nonetheless, some similar results are noted herein, especially in southeastern Canada, where DC is declining and HW is increasing around +/− 5 to 10 days per summer.

Over the 1948–2005 time period, Knight et al., (2008)22 found widespread significant decreases in the SSC’s Dry Polar WT in the eastern and western thirds of the US, increased frequency of a humid WT (Moist Moderate) in the Midwest and western US, and decreases in transitional weather throughout the country. While a few results herein [e.g., decreased DC (and C) in the northeastern US, and perhaps increased HW in the northeast] are similar to those found in Knight et al. (2008),22 their results are largely in contrast to the current research, especially in regards to transitional (WFP, CFP) weather, as this research finds slight increases in both transitional WTs across much of the US. Using a previous version of the SSC (the SSC1),23 Kalkstein et al., (1998)24 also found significant decreases in transitional weather across the US, along with increased winter Dry Polar and increased summer Moist Tropical, especially in the southeastern US. Both studies (refs 22,24) however, found locations in the desert southwest US had large summertime increases in a Dry Tropical weather type—analogous to the DW type herein. Both of these studies use time periods that end 10–20 years prior to the time series used in the current research, prior to the warmest years on record globally.25 In more recent research evaluating summertime SSC WT frequencies, in the Midwestern US, Vanos et al., (2015)26 found increasing Moist Tropical and decreasing Dry Polar WTs; and in eastern North America, Senkbeil et al., (2017)27 found dramatic increases in summer Moist Tropical and large decreases in Dry Polar and transitional weather. However, these studies only determine trends over a regional domain and a single season.

While a 39-year period of record is used to evaluate the significance of WT trends, this still is considered a fairly short temporal domain to be confident in this being a true climate change signal. The use of Theil-Sen slope estimates (described below) in lieu of simple linear regression largely mitigates the influence of potential high-leverage outliers on these results.28 However, in order to gauge the influence of starting and ending points a bit further, we ran the same analyses multiple times, each time omitting 1–3 years at the beginning and/or 1–3 years at the end. The overall spatial pattern of the slopes was virtually identical when averaging the results from this alternative time domain analysis, and nearly 89% of the continent remains unchanged with regard to statistical significance/insignificance of the slopes (Fig. S5). As with all secular examinations of any component of the climate system, other decadal and interdecadal forcing agents (e.g., teleconnections and oscillations) are undoubtedly contributing to short-term fluctuations in WT frequency. A detailed analysis of such factors is outside the scope of this research, but they were examined in Lee (2016)29 with regards to their impact on wintertime weather type frequencies.

As would be expected, many of the above results are largely in agreement with the general changes in temperatures or dew points over this time period (e.g., where dew points and temperatures are both rising, we generally see increases in HW and decreases in DC); many pattern correlations between WT frequency and these two variables are r > |0.5| (Table S5). However, there are also more subtle changes noted here that a simple univariate analysis of either individual meteorological variable is unable to elucidate. For example, increased DW in the Desert Southwest is offset by significant decreases of multiple WTs (and not only HC, as would be expected); and decreases in DC in Canada are offset by increases in both HW and DW in the east, and increases in the Humid WT and even HC in the West. Moreover, CFP and WFP changes are not well correlated with either temperature or dew point trends (Table S5), yet are important meteorological phenomena leading to dramatic short-term weather variability affecting the mid-latitude population. All of these additional analyses reveal that depending on location and the WT of interest, there is considerable variability in the association between background warming and the trends in these WTs, highlighting the value of such an analysis.