North American Extreme Temperature Events and Related Large Scale Meteorological Patterns: A Review of Statistical Methods, Dynamics, Modeling, and Trends

Two BER funded DOE laboratory scientists, Ruby Leung (PNNL) and Michael Wehner (LBNL), are among the principal authors of a comprehensive new review of the large scale meteorological patterns (LSMP) responsible for short term North American heat waves and cold snaps. The objective of this paper is to review statistical methods, dynamics, modeling efforts and trends related to such events. In particular, the role of LSMPs on observed past and simulated future extreme temperature changes is explored. Leung reviewed the state of the art in climate modeling of LSMP and extreme temperatures and future changes. Wehner reviewed the current statistical modeling of observed and simulated temperature extremes and trends and assessed climate model performance in simulating observations. The paper concludes by assessing gaps in our knowledge about LSMPs and temperature extremes.


This review paper was part of the activities conducted under the auspices of the US CLIVAR “Extremes and Large Scale Meteorological Patterns” Working Group. Previously, the working group sponsored a workshop on the topic at the Lawrence Berkeley National Laboratory.


Citation: Richard Grotjahn, Robert Black, Ruby Leung, Michael F. Wehner, Mathew Barlow. Mike Bosilovich, Alexander Gershunov, William J. Gutowski, John R. Gyakum, Richard W. Katz, Yun-Young Lee, Young-Kwon Lim, Prabhat (2015) North American Extreme Temperature Events and Related Large Scale Meteorological Patterns: A Review of Statistical Methods, Dynamics, Modeling, and Trends. Climate Dynamics, 0930-7575. 10.1007/s00382-015-2638-6


Performance portrait of the CMIP5 models’ ability to represent the temperature based ETCCDI indices over North American land. The colors represent normalized root mean square errors (RMSE) of seasonal indices compared to the ERA Interim reanalysis. Blue colors represent errors lower than the median error, while red colors represent errors larger than the median error. Seasons are denoted by triangles within each square. Models marked with “*” are not included in the RCP8.5 projections. Root mean square errors normalized by the model median RMSE for 3 other reanalyses are shown in the rightmost columns for comparison.



Projected seasonal changes in North American extreme temperatures from the CMIP5 multi-model at the end of this century under the RCP8.5 forcing scenario. The reference period is 1985-2005 while the future period is 2080-2100. Winter changes are shown on the left while summer changes are shown on the right. The top figures represent changes in cold nights (Tnn) while the lower figures represent changes in hot days (Txx). Units: Kelvins.


tas_figure1 tas_figure1_right

Change over 1950-2007 in estimated 20-year annual return values (oC) for a) hot tail of daily maximum temperature (TXx), b) cold tail of daily maximum temperature, (TXn) c) hot tail of daily minimum temperature, (TNx) and d) cold tail of daily minimum temperature (TNn). Results are based on fitting extreme value statistical models with a linear trend in the location parameter to exceedances of a location-specific threshold (greater than the 99th percentile for upper tail and less than the 1th percentile for lower tail). As this analysis was based on anomalies with respect to average values for that time of year, hot minimum temperature values, for example, are just as likely to occur in winter as in summer. The circles indicate the z-score for the estimated change (estimate divided by its standard error), with absolute z-scores exceeding 1, 2, and 3 indicated by open circles of increasing size. Higher z-score indicates greater statistical significance.