Editing IPCC:AR6/WGI/Chapter-8 (section)

===== 8.5.1.2.1 High-resolution global climate models =====

<div id="h4-32-siblings" class="h4-siblings"></div>

Since AR5, horizontal resolution has increased in most global climate models, which has led to several improvements in the simulation of the water cycle (see also [[IPCC:Wg1:Chapter:Chapter-10#10.3.1.1|Section 10.3.1.1]] ), not only in areas with steep or complex orography, but also over the tropical oceans and within the North Pacific and North Atlantic storm tracks (Piazza et al. , 2016; Roberts et al. , 2018; Bui et al. , 2019; [[#Chen--2019|Chen and Dai, 2019]] ; Vannière et al. , 2019) . Yet, the added value of higher resolution global climate models is not systematic (Johnson et al. , 2016; Ogata et al. , 2017; D. Huang et al. , 2018; Mahajan et al. , 2018; Vannière et al. , 2019) and needs careful assessment ( [[#Haarsma--2016|Haarsma et al., 2016]] ; [[#Caldwell--2019|Caldwell et al., 2019]] ). Several AGCM studies suggest that increased spatial resolution leads to better simulation of the atmospheric moisture transport from ocean to land, the geographical distribution of annual mean precipitation ( [[#Demory--2014|Demory et al., 2014]] ), and the frequency distribution of daily precipitation intensities (L. [[#Zhang--2016|]] [[#Zhang--2016|]] [[#Zhang--2016|]] [[#Zhang--2016|Zhang et al., 2016]] ; [[#Chen--2019|Chen and Dai, 2019]] ) including extremes in many( [[#Jacob--2014|Jacob et al., 2014]] ; [[#Westra--2014|Westra et al., 2014]] ), but not all cases ( [[#Bador--2020|Bador et al., 2020]] ).

Part of the improvement in simulated precipitation accuracy is related to improved simulation of the frequency and/or mean intensity of tropical ( [[#Roberts--2015|Roberts et al., 2015]] ; [[#Walsh--2015|Walsh et al., 2015]] ) and extratropical ( [[#Hawcroft--2016|Hawcroft et al., 2016]] ) cyclones. Idealized regional experiments also show that the North Atlantic storm track response to global warming can be amplified in higher resolution models ( [[#Willison--2015|Willison et al., 2015]] ). Increased atmospheric horizontal resolution can be also important for simulating Northern Hemisphere (NH) blockings ( [[#Davini--2017|Davini et al., 2017]] ; [[#Schiemann--2017|Schiemann et al., 2017]] ) and synoptic features of the East Asian summer monsoon ( [[#Yao--2017|Yao et al., 2017]] ; [[#Kusunoki--2018|Kusunoki, 2018]] ). Variable resolution based on grid stretching may be a valuable alternative for simulating regional phenomena like monsoons (Sabin et al. , 2013; Krishnan et al. , 2016) or tropical cyclones ( [[#Harris--2016|Harris et al., 2016]] ; [[#Chauvin--2017|Chauvin et al., 2017]] ), while avoiding inconsistencies in the forcings or physics that can be found in RCMs driven by GCMs ( [[#Boé--2020|Boé et al., 2020]] ; [[#Tapiador--2020|Tapiador et al., 2020]] ).

Increasing horizontal model resolution in CMIP5 and CMIP6 models leads to a systematic increase in global mean precipitation, enhanced moisture advection to land in close connection with increased orographic precipitation, and a partial reduction of the long-standing double ITCZ bias ( [[#Demory--2014|Demory et al., 2014]] ; [[#Caldwell--2019|Caldwell et al., 2019]] ; [[#Vannière--2019|Vannière et al., 2019]] ). Recent studies based on HighResMIP simulations ( [[#Haarsma--2016|Haarsma et al., 2016]] ) confirm the added value of increased horizontal resolution (at least 50 km in the atmosphere and 25 km in the ocean) for the simulation of tropical ( [[#Roberts--2020|Roberts et al., 2020]] ) and extratropical cyclones ( [[#Priestley--2020b|Priestley et al., 2020b]] ). CMIP6 model biases in annual mean precipitation are only slightly reduced at higher resolution (Figure 3.10).

High resolution representation of the land surface is also important for simulating many features of the terrestrial water cycle, such as orographic precipitation, snow, runoff and streamflow in complex topography areas ( [[#Zhao--2015|Zhao and Li, 2015]] ). However, the added value may be easier to assess in offline rather than online land surface simulations ( [[#Döll--2016|Döll et al., 2016]] ) given the possible use of bias-corrected atmospheric forcings. Offline high-resolution GHMs are routinely used to monitor water resources or to assess the hydrological impacts of bias-adjusted global climate projections ( [[#Davie--2013|Davie et al., 2013]] ; S. [[#Huang--2017|Huang et al., 2017]] , 2018). Yet, the development and calibration of ‘hyper-resolution’ hydrological models, with gridcells of typically 100 m to 1 km, raises a number of issues given the lack of comprehensive surface or subsurface information ( [[#Bierkens--2015|Bierkens et al., 2015]] ) and the lack of coupling with the atmosphere (Berg and Sheffield, 2018a).

In summary, there is ''high confidence'' that increasing horizontal resolution in GCMs can reduce a number of systematic model errors of relevance for the water cycle, including synoptic circulation and the statistics of daily precipitation. High-resolution GCMs and GHMs provide improved representation of land surfaces, including topography, vegetation and land use change, which are required to accurately simulate changes in the terrestrial water cycle. However, there is ''low confidence'' that the higher horizontal resolution simulations currently available provide more accurate projections of the large-scale features of the water cycle.

<div id="8.5.1.2.2" class="h4-container"></div>

<span id="regional-climate-models-and-convective-permitting-models"></span>