Editing IPCC:AR6/WGI/Chapter-4 (section)

===== 4.5.1.1.3 Changes in temperature variability =====

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It has long been recognized that along with mean temperatures also variance and skewness of the temperature distribution may be changing ( [[#Gregory--1995|Gregory and Mitchell, 1995]] ; [[#Mearns--1997|Mearns et al., 1997]] ). By amplifying or dampening changes in the tail of temperature distribution such changes are potentially highly relevant to extremes (Section 11.3.1) and pose a serious challenge to adaptation measures. Changes in temperature variability can occur from diurnal to multi-decadal time scales and from the local to the global scale with potentially even opposing signals in different seasons and at the different spatial scales

Changes in GSAT variability are poorly understood. Based on model experiments it has been suggested that unforced variability of GSAT tends to decrease in a warmer world as a result of reduced albedo variability in high latitudes resulting from melting snow and sea ice ( [[#Huntingford--2013|Huntingford et al., 2013]] ; [[#Brown--2017|Brown et al., 2017]] ), but ''confidence'' remains ''low'' and an observed change has not been detected. An assessment of changes in global temperature variability is inherently challenging due to the interplay of unforced internal variability and forced changes.

Changes in tropical temperature variability may arise from changes in the amplitude of ENSO ( [[#4.5.3.2|Section 4.5.3.2]] ). Over the extratropics, several studies have identified robust large-scale patterns of changes in variability of annual and particularly seasonal mean temperature, including (i) a reduction in mid- to high-latitude winter temperature variability and (ii) an increase in summer temperature variability over land in the tropics and subtropics ( [[#Huntingford--2013|Huntingford et al., 2013]] ; [[#Holmes--2016|Holmes et al., 2016]] ; see Figure 4.21). The multi-ensemble average across seven single-model initial-condition large ensembles projects a consistent reduction in year-to-year December–January–February (DJF) variability around about 50°N–70°N and June–July–August (JJA) variability around 55°S–70°S along the edge of the sea ice- and snow-covered region (Figure 4.21). There is growing evidence that year-to-year and day-to-day temperature variability decreases in winter over northern mid- to high-latitudes ( [[#Fischer--2011|Fischer et al., 2011]] ; [[#De%20Vries--2012|De Vries et al., 2012]] ; [[#Screen--2014|Screen, 2014]] ; [[#Schneider--2015|Schneider et al., 2015]] ; [[#Holmes--2016|Holmes et al., 2016]] ; [[#Borodina--2017|Borodina et al., 2017]] ; [[#Tamarin-Brodsky--2020|Tamarin-Brodsky et al., 2020]] ) which implies that the lowest temperatures rise more than the respective climatological mean temperatures ( ''medium confidence'' ). Over the NH, reduced high-latitude temperature variability is associated with disproportionally large warming in source region of cold-air advection due to Arctic amplification and land–sea contrast ( [[#De%20Vries--2012|De Vries et al., 2012]] ; [[#Screen--2014|Screen, 2014]] ; [[#Holmes--2016|Holmes et al., 2016]] ). It has further been argued that a reduction in snow and sea ice coverage from partly to completely snow- and ice-free ocean and land surface would substantially reduce cold-season temperature variability ( [[#Gregory--1995|Gregory and Mitchell, 1995]] ; [[#Fischer--2011|Fischer et al., 2011]] ; [[#Borodina--2017|Borodina et al., 2017]] ) and lead to a shortening of the cold season and earlier onset of the warm season ( [[#Cassou--2016|Cassou and Cattiaux, 2016]] ). Mid-latitudinal winter temperature variability is further affected by a complex interplay of a multitude of processes including potential changes in atmospheric circulation, but there is ''low confiden'' ce in the dominant contribution of Arctic warming compared to other drivers ( [[IPCC:Wg1:Chapter:Chapter-10#cross-chapter-box-10.1|Cross-Chapter Box 10.1]] ).

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[[File:fcdb5520d6e52e8460074f9c7ca3f057 IPCC_AR6_WGI_Figure_4_21.png]]

'''Figure''' '''4.21 |''' '''Percentage change in interannual variability of (left) December–January–February (DJF) and (right) June–July–August (JJA) mean temperature averaged across seven large initial condition ensembles.''' Average changes across seven single-model, initial-condition large ensembles are shown for RCP8.5 in 2081–2100 (and where not available for 2080–2099) relative to 1995–2014. Standard deviations are calculated across all members of the large ensembles for every given year to avoid inflation due to the underlying trend and then averaged across the period. Changes are averaged across the ensembles MPI-GE (100 members, [[#Maher--2019|Maher et al., 2019]] ), CanESM2 (50 members, [[#Kirchmeier-Young--2017|Kirchmeier-Young et al., 2017]] ), NCAR-CESM (30 members, [[#Kay--2015|Kay et al., 2015]] ), GFDL-CM3 (20 members, [[#Sun--2018|Sun et al., 2018]] ), GFDL-ESM2M (30 members, [[#Rodgers--2015|Rodgers et al., 2015]] ), CSIRO-Mk3-6-0 (30 members, [[#Jeffrey--2013|Jeffrey et al., 2013]] ) and EC-EARTH (16 members, [[#Hazeleger--2010|Hazeleger et al., 2010]] ). Also see [[#Deser--2020|Deser et al. (2020)]] for further information on those ensembles. Diagonal lines indicate areas with low model agreement where fewer than 80% of the models agree on the sign of the change, and no overlay areas with high model agreement where at least 80% of the models agree on the sign of the change. Further details on data sources and processing are available in the chapter data table (Table 4.SM.1).

In JJA, the multi-model average projects an increase in year-to-year JJA variability over Central Europe and North America (Figure 4.21). In particular an increase in daily to interannual summer temperature variability has been projected over central Europe as a result of larger year-to-year variability in soil moisture conditions varying between a wet and dry regime and leading to enhanced land–atmosphere interaction ( [[#Seneviratne--2006|Seneviratne et al., 2006]] ; [[#Fischer--2012|Fischer et al., 2012]] ; [[#Holmes--2016|Holmes et al., 2016]] ). Furthermore, the amplified warming in the source regions of warm-air advection due to land–ocean warming contrast and amplified Mediterranean warming ( [[#Seager--2014a|Seager et al., 2014a]] ; [[#Brogli--2019|Brogli et al., 2019]] ), may lead to disproportionally strong warming of the hottest days and summers and thereby increased variability. Enhanced temperature variability is further projected over some land regions in the subtropics and tropics ( [[#Bathiany--2018|Bathiany et al., 2018]] ).

In summary, there is ''medium confidence'' that continued warming will regionally lead to increased and decreased year-to-year temperature variability in the extratropics and there is ''medium confidence'' that year-to-year temperature variability will decrease over parts of the mid- to high- latitudes of the winter hemisphere.

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