Extremes

How is extreme weather changing?

• World Weather Attribution is taking on an important question of the degree to which individual weather extremes can be attributed to climate change. Peter Sherman articulated some concerns regarding the methodology 2025.
• An examination of the implicatons of weather shocks in agricultural regions found that the implications for net migration are miniimal, but that this reflects offsetting influences between how people migrate according to their education and income status 2025.
• Vast numbers of people depend on the the Indian monsoon and are exposed to its excesses or deficiencies, making it important to scrutinize historical records for systematic shifts. Whereas many studies have found increases in extreme monsoon precipitation in central India, Marena Lin examined the coverage of weather-station data and how their measurements are gridded and made available by the India Meteorological Department (IMD). She found that shifts in the coverage of rainfall gages likely led to a systematic rise in the number of extreme events counted after 1975 (2018). This study highlights the importance of accounting for observing changes when estimating trends, and that it would be useful for the IMD to publicly release the underlying data used in their gridded products.
• The magnitude and frequency of extremes can be viewed from the perspective of deviations from a normal distribution. Cristi Proistosescu led up a study with Andy Rhines showing how filtering of time series suppresses non-normality and illustrating the implications for identification of the timescales from which non-normal variations arise (2016). Furthermore, atmospheric radiosonde data are shown to have a frequency structure of non-normal variability that is consistent with the generating mechanism existing at or above the diurnal frequencies resolved in the analysis. The study also indicates that developing new tools, or importing them from other fields, would be useful for better identifying the sources of non-normality in geophysical time series.
• Karen McKinnon, Andy Rhines, and Martin Tingley demonstrated skillful prediction for extreme summer temperatures as much as 50 days in advance (2016). The technique was determined empirically and extensively tested on withheld data. It involves an evolving pattern of sea surface temperatures in the mid-latitude Pacific that appears to interact with the atmospheric circulation so as to align high pressure systems over the Eastern U.S., though the exact mechanistic relationship remains speculative.
• In order to use quantile regression to estimates trends in instrumental temperature records one must first correct for the effects of rounding. But much temperature data is rounded in Fahrenheit, transformed into Celsius, and again rounded, causing subtle biases in reported values and making it difficult to fully account for the effects, especially since meta-data on rounding practices is often not available. Andy Rhines developed a Hidden Markov Model and applied it to identify double-rounding and correct for its effects amongst more than half of the daily temperature data archived in the Global Historical Climate Network (2015).
• Martin Tingley demonstrated that Arctic tree rings over-represent the cooling response to volcanic eruptions (2014), a result agreeing with Zan Stine's findings that Arctic tree ring growth is limited both by temperature and light availability (2014). Volcanic eruptions generally decrease both temperature and total light availability, and a greater diffusive light fraction need not offset overall dimming in already low light conditions. Martin also found that warmer intervals are generally characterized by greater spatial variability in both instrumental and late-Holocene proxy records (2015).
• Thomas Laepple showed that regional variability of sea surface temperatures in instrumental observations is about twice that in the CMIP5 simulation ensemble at decadal time scales (2014a), indicating a higher chance of obtaining extremes on account of internal variability than is generally simulated. Use of corrected paleoclimate records (2013) to extend the comparison to longer time scales shows the model-data mismatch in regional variance grows, reaching two orders of magnitude at millennial time scales (2014b).
• Examination of the relationship between seasonal average and extreme daily temperatures demonstrates that much of the interannual variability in the temperature distribution is the expected consequence of finitely sampling a non-normal distribution. The major exception is that Midwestern summer temperatures show strong indications of nonstationarity, whereby the probability of high temperature extremes increases more rapidly with warming than would be anticipated from the historical sample distributions (2014).
• Nathan Mueller showed that the hottest summer temperatures in the U.S. Midwest have been cooling over the last century because of increasing agricultural intensification and associated increases in transpiration (2015). Temperatures return to historically high values during drought, however, because of limitations upon evapotranspiration. The transition to dry soils appears to explain the change in probability distribution discussed above.
• In examining gridded temperatures at seasonal timescales, Andy Rhines and Martin Tingley found that interdecadal changes in the distribution of temperature variability is adequately explained through a simple shift in the mean over instrumental (2013) and proxy timescales (2013b). This discrepancy largely disappears after averaging spatially, suggesting the utility of further exploring space-time temperature scaling.

References

• Sherman, Huybers, and Tziperman, On the Attribution of Weather Events to Climate Change Using Empirically Fit Extreme Value Distributions, Journal of Climate, 38(12), 2025. link
• Benveniste, Huybers, and Proctor, Global climate migration is a story of who and not just how many, Nature Communications, 16(1), 2025. link
• Lin and Huybers, If rain falls in India and no one reports it, are historical trends in monsoon extremes biased?, Geophysical Research Letters, 2018. link, pdf
• Proistosescu, Rhines, and Huybers, Identification and interpretation of non-normality in atmospheric time series, Geophysical Research Letters, 2016. link
• McKinnon, Rhines, Tingley, and Huybers Long-lead predictions of eastern United States hot days from Pacific sea surface temperatures, Nature Geoscience, 2016. link
• Rhines, Tingley, McKinnon, Huybers Decoding the precision of historical temperature observations, Quarterly Journal of the Royal Meteorological Society, 2015. pdf
• Tingley and Huybers Heterogeneous warming of Northern Hemisphere surface temperatures over the last 1200 years, Journal of Geophysical Research - Atmospheres, 2015. pdf
• Mueller, Butler, McKinnon, Rhines, Tingley, Holbrook, and Huybers Cooling of US Midwest summer temperature extremes from cropland intensification, Nature Climate Change, 2015. pdf
• Huybers, McKinnon, Rhines, and Tingley U.S. daily temperatures: the meaning of extremes in the context of non-normality, Journal of Climate, 2014. pdf
• Stine and Huybers Arctic tree rings as recorders of variations in light availability, Nature Communications, 2014. pdf
• Laepple and Huybers Ocean surface temperature variability: Large model-data differences at decadal and longer periods, PNAS, 2014. pdf
• Laepple and Huybers Global and regional variability in marine surface temperatures, Geophysical Research Letters, 2014. pdf
• Tingley, Stine, and Huybers Temperature reconstructions from tree-ring densities overestimate volcanic cooling, Geophysical Research Letters, 2014. pdf
• Rhines and Huybers Comment: Frequent summer temperature extremes reflect changes in the mean, not the variance, Proceedings of the National Academy of Sciences, 2013. pdf
• Tingley and Huybers Recent temperature extremes at high northern latitudes unprecedented in the past 600 years, Nature, 2013. pdf data and code
• Laepple and Huybers Reconciling discrepancies between Uk37 and Mg/Ca reconstructions of Holocene marine temperature variability, Earth and Planetary Science Letters, 2013. pdf