On any given day, some region of the globe is likely to be affected by significant negative temperature anomalies. Depending on the severity, extreme cold periods may be deemed cold air outbreaks (CAOs). These CAOs can be detrimental to the agricultural industry and human health, especially in less prepared regions. A systematic CAO classification was developed using a set of criteria concerning magnitude, duration, and spatial extent from two gridded reanalysis datasets from 1979 – 2018. Trends in CAOs were calculated for different regions across the globe and the results from each reanalysis dataset compared with one another to identify discrepancies. CAOs were found to have decreased in spatial extent, frequency, duration, and magnitude across much of the globe, particularly across Alaska, Canada, and the North Atlantic, while an increase in CAOs was observed in Eastern Europe, Central Eurasia, and the Southern Ocean.

Accurate sub-seasonal to seasonal (S2S) weather forecast between 2 weeks and several months is crucial to making informed decisions regarding changes in the risk of extreme weather events, resource management, agriculture, forestry, public health, energy, etc. However, significant gaps exist between the needs of society and what forecasters can produce, especially over longer lead times. Using three goodness-of-fit metrics, this study examined the ability of the SOMs-generated CFSv2 to forecast the correct (observed) circulation pattern, as opposed to the actual observed gridded field over a 90-day forecast period. Mean sea-level pressure (MSLP), near-surface wind (wnd10m), 850-mb temperature (t850), and 700-mb geopotential heights (z700) from the North American Regional Reanalysis were used to categorize the synoptic-scale circulation for three regions (East, West, and Gulf) across North America from January 1979 – December 2016. Expectedly, forecast skill generally decreased from the first day down to the skill of climatology (after 10 -15 days) and also varied regionally, seasonally, and between variables. The forecasts for the winter and summer seasons outperformed others, while t850 and z700 forecasts outperformed wnd10m, except in the west region. More importantly, this study found that the SOMs-generated CFSv2 forecasts improve upon the skill of the raw CFSv2 forecast near the one 1 – 2 weeks lead time. This study thus demonstrates the potential utility of a SOMs-based forecasting method in medium-range weather forecasts.

While many studies comparing atmospheric reanalysis and surface observations have focused on the similarity of mean fields, trends, or frequencies of extreme events, very few have assessed how similar surface observations and reanalysis data sets are in terms of their specific identification of extreme temperature event days. Here, we assess the similarity between surface observations and three reanalysis products: ERA5, ERA5-LAND, and NARR, in terms of the days on which they identify extreme temperature events. We assess similarity from 1979-2016 for 231 locations in the United States and Canada, assessing Extreme Heat and Cold Event days, as well as their counterpart events that are relative for the time of year. Cold Events have a greater match than Heat Events. ERA5 has the greatest match percentage with station data across the study region. Match percentage is greatest in mid-latitude, continental locations, with poorer performance in coastal areas, and the Arctic.

Upon the backdrop of steadily rising global average temperatures, it is the extreme weather events that are arguably more important and impactful than changing averages – especially on human health. This research examines trends in North America of three different parameters of extreme temperature events important to human thermal comfort and public health: their frequency, duration, and spatial extent. Most of the changes are expected; that is, with warmer temperatures there are more frequent extreme heat events that are lasting longer and covering more area. However, we highlight some intriguing divergences from this pattern. For example, despite quickly rising autumn temperatures in northern Canada, a concurrent decrease in temperature variability is resulting in extreme heat events remaining stable and is instead manifest more as significant decreases in extreme cold events. In parts of the western US, even though there is no significant trend in autumn mean temperatures, there is a significant rise in extreme cold events. And, in the southern High Plains in summer, despite little trend in averages, a more negative skew to the distribution is nonetheless leading to significant increases in heat events. Seasonal and geographic variability in the trends of extreme dew point events is also explored. For example, increases in extreme humidity events are ubiquitous throughout most of Canada, particularly in summer; but the US has a northeast (increasing humid events) to southwest (increasing dry events) dichotomy that is strongest in winter. While such nuances might complicate our efforts to broadly generalize the message of climate change, these distinctions suggest a renewed emphasis on local- to regional-scale analyses (rather than larger scales) when providing actionable climate information for planners and policymakers.

Historical and future simulated temperature data from five climate models in the Coupled Model Intercomparing Project Phase 6 (CMIP6) are used to understand how climate change might alter cold air outbreaks (CAOs) in the future. Three different Shared Socioeconomic Pathways (SSPs), SSP 1 – 2.6, SSP 2 – 4.5, and SSP 5 – 8.5 are examined to identify potential fluctuations in CAOs across the globe between 2015 and 2054. Though CAOs may remain persistent or even increase in some regions through 2040, all five climate models show CAOs disappearing by 2054. Climate models were able to accurately simulate the spatial distribution and trends of historical CAOs, but there were large errors in the simulated interannual frequency of CAOs in the North Atlantic and North Pacific. Fluctuations in complex processes, such as Atlantic Meridional Overturning Circulation, may be contributing to each model’s inability to simulate historical CAOs in these regions.

In recent decades, there is a broad consensus in the literature that heat-related mortality overall has declined relative to the magnitude of the heat event. This said, as society is aging and the climate is warming, it is uncertain that this trajectory can be sustained moving forward, particularly as historically rare events become more common. To explore more recent trends, using a recently extended data set, we explored trends in anomalous mortality associated with extreme heat event days for the period 1975-2018 across the largest 107 metropolitan areas of the United States. We defined heat using an excess heat factor, and once events were identified, used a distributed-lag nonlinear model (DLNM) to assess mortality response over a cumulative 10-day period. In addition to total mortality, we also assessed subsets of those 65+ and 45-64, each of which were subdivided by sex. Results indicate that, overall, heat-related mortality associated with any given heat event day is decreasing. The most substantive decreases in mortality are those 65 and older, which may be associated with greater awareness as well as that population being the target of most intervention systems. Indeed, in many locations heat-related mortality among women 65 and older is no longer statistically significant. In contrast, while overall rates are lower, such trends are not seen in those aged 45-64. In particular, there is an increase in mortality among men 45–64 of 11.3 deaths per year across the US, most concentrated in southern and southwestern US cities. Overall, however, the general decreases in heat related mortality are being offset somewhat by the increase in heat event days, particularly since 2010. Given the impacts of the heat events since 2018 over the US West in particular, it is clear that heat-related mortality is not something confined to the past.