Editing IPCC:AR6/WGI/Chapter-10 (section)

===== 10.3.3.4.1 Convection including tropical cyclones =====

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Convection is the process of vertical mixing due to atmospheric instability. Deep moist convection is associated with thunderstorms and severe weather such as heavy precipitation and strong wind gusts. Convection may occur in single locations, in spatially extended severe events such as supercells, and organized into larger mesoscale convective systems such as squall lines or tropical cyclones, and embedded in fronts (see below). Shallow and deep convection are not explicitly simulated but parametrized in standard global and regional models. In consequence, these models suffer from several biases. AR5 has stated that many CMIP3 and CMIP5 models simulate the peak in the diurnal cycle of precipitation too early, but increasing resolution and better parametrizations help to mitigate this problem ( [[#Flato--2014|Flato et al., 2014]] ). Similar issues arise for RCMs with parametrized deep convection ( [[#Prein--2015|Prein et al., 2015]] ), which also tend to overestimate high cloud cover ( [[#Langhans--2013|Langhans et al., 2013]] ; [[#Keller--2016|Keller et al., 2016]] ).

Non-hydrostatic RCMs at convection-permitting resolution (4 km and finer) improve features such as the initiation and diurnal cycle of convection ( [[#Zhu--2012|Zhu et al., 2012]] ; [[#Prein--2013a|Prein et al., 2013a]] , b; [[#Fosser--2015|Fosser et al., 2015]] ; [[#Stratton--2018|Stratton et al., 2018]] ; [[#Sugimoto--2018|Sugimoto et al., 2018]] ; [[#Finney--2019|Finney et al., 2019]] ; [[#Berthou--2020|Berthou et al., 2020]] ; [[#Ban--2021|Ban et al., 2021]] ; [[#Pichelli--2021|Pichelli et al., 2021]] ), the triggering of convection by orographic lifting ( [[#Langhans--2013|Langhans et al., 2013]] ; [[#Fosser--2015|Fosser et al., 2015]] ), and maximum vertical wind speeds in convective cells ( [[#Meredith--2015a|Meredith et al., 2015a]] ). Also spatial patterns of precipitation ( [[#Prein--2013a|Prein et al., 2013a]] , b; [[#Stratton--2018|Stratton et al., 2018]] ), precipitation intensities ( [[#Prein--2015|Prein et al., 2015]] ; [[#Fumière--2020|Fumière et al., 2020]] ; [[#Ban--2021|Ban et al., 2021]] ; [[#Pichelli--2021|Pichelli et al., 2021]] ), the scaling of precipitation with temperature ( [[#Ban--2014|Ban et al., 2014]] ), cloud cover ( [[#Böhme--2011|Böhme et al., 2011]] ; [[#Langhans--2013|Langhans et al., 2013]] ) and its resultant radiative effects ( [[#Stratton--2018|Stratton et al., 2018]] ), as well as the annual cycle of tropical convection ( [[#Hart--2018|Hart et al., 2018]] ) are improved. Phenomena such as supercells, mesoscale convective systems, or the local weather associated with squall lines are not captured by global models and standard RCMs. Convection-permitting RCM simulations, however, have been shown to realistically simulate supercells ( [[#Trapp--2011|Trapp et al., 2011]] ), mesoscale convective systems, their life cycle and motion ( [[#Prein--2017|Prein et al., 2017]] ; [[#Crook--2019|Crook et al., 2019]] ), and heavy precipitation associated with a squall line ( [[#Kendon--2014|Kendon et al., 2014]] ). There is ''high confidence'' that simulations at convection-permitting resolution add value to the representation of deep convection and related phenomena.

Convection is the key ingredient of tropical cyclones. An intercomparison of high-resolution AGCM simulations ( [[#Shaevitz--2014|Shaevitz et al., 2014]] ) showed that tropical cyclone intensities appeared to be better represented with increasing model resolution. [[#Takayabu--2015|Takayabu et al. (2015)]] have compared simulations of typhoon Haiyan at different resolutions ranging from 20 km to 1 km (Figure 10.8). While the eyewall structure in the precipitation pattern was strongly smoothed in the coarse resolution simulations, it was well-resolved at the highest resolution. [[#Gentry--2010|Gentry and Lackmann (2010)]] found similar improvements in simulating hurricane Ivan for horizontal resolutions between 8 km and 1 km. High-resolution coupled ocean–atmosphere simulations improve the representation of the radial structure of core convection and thereby the rapid intensification of the cyclone ( [[#Kanada--2017b|Kanada et al., 2017b]] ). There is ''high confidence'' that convection-permitting resolution is required to realistically simulate the three-dimensional structure of tropical cyclones.

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[[File:1b451650234bba076f5e7d74e3147fc1 IPCC_AR6_WGI_Figure_10_8.png]]

'''Figure 10.8''' '''|''' '''Hourly accumulated precipitation profiles (mm hour''' –1 ''') around the eye of Typhoon Haiyan.''' Represented by '''(a)''' Global Satellite Mapping of Precipitation (GSMaP) data (multi-satellite observation), '''(b)''' Guiuan radar (PAGASA), '''(c)''' Weekly Ensemble Prediction System (WEPS) data (JMA; 60 km), '''(d)''' NHRCM (20 km), '''(e)''' NHRCM (5 km), and '''(f)''' WRF (1 km) models. Panels (b), (d–f) are adapted from [[#Takayabu--2015|Takayabu et al. (2015)]] , CCBY3.0 https://creativecommons.org/licenses/by/3.0 . Further details on data sources and processing are available in the chapter data table (Table 10.SM.11).

Initial studies with convection-permitting global models suggests that improvements in representing convection, as described for RCMs above, have a positive impact on the tropical and extratropical atmospheric circulation and, thus, regional climate ( [[#Satoh--2019|Satoh et al., 2019]] ; [[#Stevens--2019|Stevens et al., 2019]] ; see also [[IPCC:Wg1:Chapter:Chapter-8#8.5.1.2|Section 8.5.1.2]] and Chapter 7). Computational constraints currently limit these simulations to a length of few months only, such that they cannot yet be used for routine climate change studies.

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