IPCC Report.pdf - Adam Curry

Changes in Climate Extremes and their Impacts on the Natural Physical EnvironmentChapter 3Box 3-1 | Definition and Analysis of Climate Extremes in the Scientific LiteratureThis box provides some details on the definition of climate extremes in the scientific literature and on common approaches employed fortheir investigation.A large amount of the available scientific literature on climate extremes is based on the use of so-called ‘extreme indices,’ which caneither be based on the probability of occurrence of given quantities or on threshold exceedances (Section 3.1.2). Typical indices that areseen in the scientific literature include the number, percentage, or fraction of days with maximum temperature (Tmax) or minimumtemperature (Tmin), below the 1st, 5th, or 10th percentile, or above the 90th, 95th, or 99th percentile, generally defined for given timeframes (days, month, season, annual) with respect to the 1961-1990 reference time period. Commonly, indices for 10th and 90thpercentiles of Tmax/Tmin computed on daily time frames are referred to as ‘cold/warm days/nights’ (e.g., Figures 3-3 and 3-4; Tables 3-1to 3-3, and Section 3.3.1; see also Glossary). Other definitions relate to, for example, the number of days above specific absolutetemperature or precipitation thresholds, or more complex definitions related to the length or persistence of climate extremes. Someadvantages of using predefined extreme indices are that they allow some comparability across modelling and observational studies andacross regions (although with limitations noted below). Moreover, in the case of observations, derived indices may be easier to obtainthan is the case with daily temperature and precipitation data, which are not always distributed by meteorological services. Peterson andManton (2008) discuss collaborative international efforts to monitor extremes by employing extreme indices. Typically, although notexclusively, extreme indices used in the scientific literature reflect ‘moderate extremes,’ for example, events occurring as often as 5 or 10%of the time. More extreme ‘extremes’ are often investigated using Extreme Value Theory (EVT) due to sampling issues (see below).Extreme indices are often defined for daily temperature and precipitation characteristics, and are also sometimes applied to seasonalcharacteristics of these variables, to other weather and climate variables, such as wind speed, humidity, or to physical impacts andphenomena. Beside analyses for temperature and precipitation indices (see Sections 3.3.1 and 3.3.2; Tables 3-2 and 3-3), other studiesare, for instance, available in the literature for wind-based (Della-Marta et al., 2009) and pressure-based (Beniston, 2009a) indices, forhealth-relevant indices (e.g., ‘heat index’) combining temperature and relative humidity characteristics (e.g., Diffenbaugh et al., 2007;Fischer and Schär, 2010; Sherwood and Huber, 2010), and for a range of dryness indices (see Box 3-3).Extreme Value Theory is an approach used for the estimation of extreme values (e.g., Coles, 2001), which aims at deriving a probabilitydistribution of events from the tail of a probability distribution, that is, at the far end of the upper or lower ranges of the probabilitydistributions (typically occurring less frequently than once per year or per period of interest, i.e., generally less than 1 to 5% of theconsidered overall sample). EVT is used to derive a complete probability distribution for such low-probability events, which can also helpanalyzing the probability of occurrence of events that are outside of the observed data range (with limitations). Two different approachescan be used to estimate the parameters for such probability distributions. In the block maximum approach, the probability distributionparameters are estimated for maximum values of consecutive blocks of a time series (e.g., years). In the second approach, instead of theblock maxima the estimation is based on events that exceed a high threshold (peaks over threshold approach). Both approaches areused in climate research.Continued next pageHence, the present chapter does not directly consider the dimensions ofvulnerability or exposure, which are critical in determining the humanand ecosystem impacts of climate extremes (Chapters 1, 2, and 4).This report defines an ‘extreme climate or weather event’ or ‘climateextreme’ as “the occurrence of a value of a weather or climate variableabove (or below) a threshold value near the upper (or lower) ends of therange of observed values of the variable” (see Glossary). Severalaspects of this definition can be clarified thus:• Definitions of thresholds vary, but values with less than 10, 5, 1%, oreven lower chance of occurrence for a given time of the year (day,month, season, whole year) during a specified reference period(generally 1961-1990) are often used. In some circumstances,information from sources other than observations, such as modelprojections, can be used as a reference.• Absolute thresholds (rather than these relative thresholds basedon the range of observed values of a variable) can also be used toidentify extreme events (e.g., specific critical temperatures forhealth impacts).• What is called an extreme weather or climate event will vary fromplace to place in an absolute sense (e.g., a hot day in the tropicswill be a different temperature than a hot day in the mid-latitudes),and possibly in time given some adaptation from society (seeBox 3-1).• Some climate extremes (e.g., droughts, floods) may be the resultof an accumulation of moderate weather or climate events (thisaccumulation being itself extreme). Compound events (see Section3.1.3), that is, two or more events occurring simultaneously, canlead to high impacts, even if the two single events are not extremeper se (only their combination).116