The science has become clear and convincing that the Earth's climate is rapidly changing [e.g., Intergovernmental Panel on Climate Change (IPCC), 2014]. Along with the overall changes in climate, there is strong evidence of an increasing trend over recent decades in the frequency, intensity, and duration of some types of extreme weather events, with resulting effects on U.S. society.

We present an overview of practices and challenges related to the detection and attribution of observed changes in climate extremes. Detection is the identification of a statistically significant change in the extreme values of a climate variable over some period of time. Issues in detection discussed include data quality, coverage, and completeness. Attribution takes that detection of a change and uses climate model simulations to evaluate whether a cause can be assigned to that change. Additionally, we discuss a newer field of attribution, event attribution, where individual extreme events are analyzed for the express purpose of assigning some measure of whether that event was directly influenced by anthropogenic forcing of the climate system.

Given the increases in spatial resolution and other improvements in climate modeling capabilities over the last decade since the CMIP3 simulations were completed, CMIP5 provides a unique opportunity to assess scientific understanding of climate variability and change over a range of historical and future conditions. With participation from over 20 modeling groups and more than 40 global models, CMIP5 represents the latest and most ambitious coordinated international climate model intercomparison exercise to date. Observations dating back to 1900 show that the temperatures in the twenty-first century have the largest spatial extent of record breaking and much above normal mean monthly maximum and minimum temperatures. The 20-yr return value of the annual maximum or minimum daily temperature is one measure of changes in rare temperature extremes.

Review of the climate science for severe convective storms, extreme precipitation, hurricanes and typhoons, and severe snowstorms and ice storms in the US shows that the ability to detect and attribute trends varies, depending on the phenomenon. A specific subset of extreme weather and climate types affecting the country is discussed to examine these extreme weather conditions. The categories of storms described were selected as they caused property damage and loss of life. The identification of an extreme occurrence was based on meteorological properties in place of the destructiveness. The primary purpose was to examine the scientific evidence for the prevailing capability to detect trends and understand their causes for certain weather types, including severe convective storms and hurricanes and typhoons.

Some of the long-term changes in weather and climate extremes across the US have occurred as expected in the warming climate, but the trends vary throughout the country and easily detected due to multiyear and decadal variations. The US National Climate Assessment has to address extremes, as these are changing and anthropogenic climate change has a role in altering the probabilities of some of the extreme events. Extreme events also drive changes in natural and human systems more than average climatic conditions. Four workshops have been held to provide technical input to the US National Climate Assessment writing team where leading scientists in the field worked jointly to determine how best to assess the state of the science in understanding the decadal- to century-scale variability and changes in various types of extreme events.

Weather and climate extremes profoundly affect society and the environment, resulting in the loss of life, property, and habitat. The extremes discussed herein are causally related: extratropical storms account for the majority of extreme winds during the cold season, and extreme waves are largely driven by extreme winds. For assessment purposes, extremes are defined based on meteorological principles rather than physical destructiveness. Nevertheless, each of these extremes can result in substantial societal impacts. Estimates of extratropical storm activity primarily derive from two sources: atmospheric reanalyses and pressure-based indices. Reanalysis products have the advantage of uniform space and time fields on which to locate pressure minima or vorticity maxima, facilitating the identification of storm tracks. In contrast, pressure-based indices have the advantage of being directly computed from in situ observations, which often extend further back in time than most reanalyses.