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===== 8.4.2.8.1 Extratropical cyclones and storm tracks ===== <div id="h4-25-siblings" class="h4-siblings"></div> The AR5 found that extratropical storms were expected to decrease in the Northern Hemisphere (NH), but only by a few percent. Meanwhile, precipitation associated with extratropical storms was projected to increase due to thermodynamic increases in moisture but potentially also due to intensification from increased latent heat release. Latent heating is a strong influence on extratropical storms, so it is plausible that changes in precipitation and associated latent heating could affect extratropical storm intensity and thus precipitation (Z. Zhang et al., 2019) . There is increased evidence that precipitation associated with individual extratropical storms is projected to increase, following thermodynamic drivers with negligible dynamic change ( [[#Yettella--2017|Yettella and Kay, 2017]] ). Comparisons with reanalyses also support the projected increase in thermodynamic precipitation with little dynamic response for precipitation associated with extratropical storms ( [[#Li--2014|Li et al., 2014]] ). There is ''high confidence'' that projected increases inprecipitation associated with extratropical storms in the NH (Marciano et al. , 2015; Pepler et al. , 2016; Michaelis et al. , 2017; [[#Yettella--2017|Yettella and Kay, 2017]] ; [[#Zhang--2017|Zhang and Colle, 2017]] ; Hawcroft et al. , 2018; Kodama et al. , 2019) . A projected decrease in the number of extratropical cyclones over the NH during the boreal summer in CMIP5 models was reported by [[#Chang--2016|Chang et al. (2016)]] who related this decrease with a decrease in cloudiness and thus accentuating increased maximum temperatures. However, model spread was quite large, especially over North America, thus there is only ''low confidence'' in this seasonal signal. In AR5, the Southern Hemisphere (SH) storm track was deemed ''likely'' to shift poleward, the North Pacific storm track ''more likely than not'' to shift poleward, while the North Atlantic storm track was ''unlikely'' to display any discernible changes. There was ''low confidence'' in regional storm track changes and the associated surface climate impacts, although a weakening of the Mediterranean storm track was a robust response of the models. Since AR5, the SH mid-latitude storm track is projected to shift poleward and the westerlies are projected to strengthen over Australia (CSIRO and BoM, 2015). Although thermodynamic effects were considered to be the most important factor in overall projections of increased mid-latitude precipitation, the general poleward shift in cyclogenesis and an enhanced latitudinal displacement of individual cyclones may play a role ( [[#Tamarin-Brodsky--2017|Tamarin-Brodsky and Kaspi, 2017]] ). In AR5, several factors were identified as relevant to the uncertainties in projections of cyclone intensity, frequency, location of storm tracks and precipitation associated with ETCs. These include horizontal resolution, resolution of the stratosphere, and how changes in the Atlantic meridional overturning circulation (AMOC) were simulated. Since AR5, projections of extratropical cyclones and storm tracks have been examined further, largely confirming previous assessments. In particular, extratropical cyclone precipitation scales with the product of cyclone intensity (as measured by near-surface wind speed) and atmospheric moisture content ( [[#Pfahl--2016|Pfahl and Sprenger, 2016]] ) . Booth et al. (2018) showed that the fraction of rainfall generated by the convection scheme in simulated extratropical cyclones is highly model- and resolution-dependent, which may be a source of uncertainty regarding their precipitation response to anthropogenic forcings. Also, increased moisture availability may increase the maximum intensity of individual storms while reducing the overall frequency as poleward energy transport becomes more efficient. The role of temperature trends in influencing storm tracks has been further investigated, both in terms of upper tropospheric tropical warming ( [[#Zappa--2017|Zappa and Shepherd, 2017]] ) and lower tropospheric Arctic amplification (J. [[#Wang--2017|]] [[#Wang--2017|]] [[#Wang--2017|Wang et al., 2017]] ), including the direct role of Arctic sea ice loss ( [[#Zappa--2018|Zappa et al., 2018]] ), and the competition between their influences (Shaw et al. , 2016) . Physical linkages between Arctic amplification and changes in the mid-latitudes are uncertain, as discussed in [[IPCC:Wg1:Chapter:Chapter-10|Chapter 10]] (Cross-Chapter Box 10.1). The remote and local SST influence has been further examined by [[#Ciasto--2016|Ciasto et al. (2016)]] , who confirmed sensitivity of the storm tracks to the SST trends generated by the models and suggested that the primary greenhouse gas influence on storm track changes was indirect, acting through the greenhouse gas influence on SSTs. The importance of the stratospheric polar vortex in storm track changes has received more attention ( [[#Zappa--2017|Zappa and Shepherd, 2017]] ; Mindlin et al. , 2020) and the anticipated recovery of the ozone layer further complicates the role of the stratosphere ( [[#Shaw--2016|Shaw et al., 2016]] ; [[#Bracegirdle--2020b|Bracegirdle et al., 2020b]] ). Biases remain in cyclone locations, intensities, cloud features, and precipitation ( [[#Catto--2016|Catto, 2016]] , [[#Chang--2016|Chang et al., 2016]] ). Uncertainties in projected precipitation changes in many mid-latitude regions can be explained to a large degree by uncertainties in projected storm track or ETC changes. Multiple studies ( [[#Chang--2013|Chang et al., 2013]] ; [[#Zappa--2015|Zappa et al., 2015]] ; [[#Chang--2018|Chang, 2018]] ) have shown strong relationships between model-projected precipitation change in many regions and model-projected change in storm track activity near that regions. While front frequency is well represented, frontal precipitation frequency is too high and the intensity is too low ( [[#Catto--2015|Catto et al., 2015]] ). Some of the bias in storm tracks appears to be related to limitations in model realization of blocking ( [[#Zappa--2014|Zappa et al., 2014]] ). The CMIP6 generation of models has improved representation of storm tracks in both hemispheres ( [[#Bracegirdle--2020a|Bracegirdle et al., 2020a]] ; [[#Harvey--2020|Harvey et al., 2020]] ). Simulation of storm tracks and their associated precipitation generally improve with increasing resolution beyond that used in most current climate models ( Jung et al. , 2006; Michaelis et al. , 2017; Barcikowska et al. , 2018 ). In terms of projections, the decreases in cyclone occurrence over the Mediterranean were replicated in a higher resolution model ( [[#Raible--2018|Raible et al., 2018]] ). The projected changes in storm tracks and the associated mechanisms have several important implications for water cycle projections. PβE changes in the Mediterranean, California and Chile are directly linked to storm track changes (Zappa et al. , 2020) . Where the storm tracks are robustly projected to shift (SH, North Pacific) or weaken (Mediterranean), understanding the physical causes of the related changes in precipitation helps increase confidence in the projections. Understanding the competing influences provides context for why other regions do not exhibit a consistent signal and cautions against regional projections based on individual models. However, model bias and the need for relatively high resolution to reproduce the relevant dynamics is an important overall limit on confidence in current CMIP6 projections. In summary, there is the ''high confidence'' that precipitation associated with extratropical storms will increase with global warming in most regions. The SH storm track will ''likely'' shift poleward, the North Pacific storm track ''more likely than not'' will shift poleward, and the North Atlantic storm track is ''unlikely'' to have a simple poleward shift/ display any discernible changes. There is ''low confidence'' in regional storm track changes, although a weakening of the Mediterranean storm track is a robust response of the models. <div id="8.4.2.8.2" class="h4-container"></div> <span id="atmospheric-rivers-1"></span>
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