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

== Atlas.9 North America ==

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The assessment in this section focuses on changes in average temperature and precipitation (rainfall and snow) for North America, including the most recent years of observations, updates to observed datasets, the consideration of recent studies using CMIP5 and those using CMIP6 and CORDEX simulations. Assessment of changes in extremes is in [[IPCC:Wg1:Chapter:Chapter-11|Chapter 11]] (Tables 11.19–21) and climatic impact-drivers in [[IPCC:Wg1:Chapter:Chapter-12|Chapter 12]] (Table 12.8).

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=== Atlas.9.1 Key Features of the Regional Climate and Findings From Previous IPCC Assessments ===

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==== Atlas.9.1.1 Key Features of the Regional Climate ====

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The recent-past climate of North America is characterized by high spatial heterogeneity and by variability at diverse temporal scales. Considering the traditional Köppen-Geiger classification, North America covers all main climate types (see reference region descriptions below). Important geographical features influence local climates over various distances, like the Rocky Mountains through cyclogenesis ( [[#Grise--2013|Grise et al., 2013]] ) and the Great Lakes through lake-effect snowfall ( [[#Wright--2013|Wright et al., 2013]] ). The cryosphere is an important component of the climate system in North America, with fundamental roles for sea ice cover, snow cover and permafrost. The ocean surrounding the continent also influences its climate, with water temperatures strongly influencing hurricane activity which impacts the coasts of eastern Mexico and south-eastern USA ( [[#Walsh--2010|Walsh et al., 2010]] ). Temporal variability is influenced by several large-scale atmospheric modes (Table Atlas.1 and Annex IV) with the North Atlantic Oscillation (NAO) affecting north-eastern USA and eastern Canada precipitation ( [[#Whan--2017|Whan and Zwiers, 2017]] ), and El Niño–Southern Oscillation (ENSO) affecting temperature and precipitation in California, although in a complex and not yet fully understood manner ( [[#Yoon--2015|Yoon et al., 2015]] ; [[#Yeh--2018|Yeh et al., 2018]] ).

The reference regions defined for summarising North America climate change (Figure Atlas.26) include: North-Western North America (NWN), characterized by a sub-Arctic climate with cool summers and rainfall all year round; North-Eastern North America (NEN), which also has a sub-Arctic climate with sections of tundra climate in the far north (these two northern regions are also discussed in Section [[#Atlas.11.2|Atlas.11.2]] , Polar Arctic); Western North America (WNA), which has a complex but mainly cold semi-arid climate; Central North America (CNA) with a mainly continental climate in the northern part of the region and a humid subtropical climate in the southern portion; Eastern North America (ENA) with a humid continental climate in the northern half and a humid subtropical climate to the south; Northern Central America (northern Mexico; NCA), has a temperate climate to the north of the Tropic of Cancer, with marked differences between winter and summer, modulated by the North American Monsoon ( [[#Peel--2007|Peel et al., 2007]] ).

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==== Atlas.9.1.1 Findings From Previous IPCC Assessments ====

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The IPCC AR5 ( [[#Bindoff--2013|Bindoff et al., 2013]] ; [[#Hartmann--2013|Hartmann et al., 2013]] ) found that the climate of North America has changed due to anthropogenic causes ( ''high confidence'' ), in particular with primarily increasing annual precipitation and annual temperature ( ''very high confidence'' ). Assessment of CMIP5 ensemble projections concluded that mean annual temperature over North America and annual precipitation north of 45°N will ''very likely'' continue to increase in the future. Also, CMIP5 projects increases in winter precipitation over Canada and Alaska and decreases in winter precipitation over the south-western USA and much of Mexico.

The CMIP5 multi-model ensemble generally reproduces the observed spatial patterns but somewhat underestimates the extent and intensity of the North American Monsoon, and also underestimates wetting over Central North America over the period of 1950–2012 during the winter season according to AR5 ( [[#Flato--2013|Flato et al., 2013]] ). In the long term (2081–2100), the largest changes of precipitation over North America are projected to occur in the mid- and high latitudes and during winter ( [[#Kirtman--2013|Kirtman et al., 2013]] ).

The SR1.5 ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ) reported a stronger warming compared to the global mean over Central and Eastern North America, and a weakening of storm activity over North America under 1.5°C of global warming. The SROCC ( [[#Hock--2019b|Hock et al., 2019b]] ) reported that snow depth or mass is projected to decline by 25% mainly at lower elevations over the high mountains in Western North America. The SRCCL ( [[#Mirzabaev--2019|Mirzabaev et al., 2019]] ) observed vegetation greening in Central North America with ''high confidence'' .

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=== Atlas.9.2 Assessment and Synthesis of Observations, Trends, and Attribution ===

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The observed trends in annual mean surface temperature (Figure Atlas.11 and the Interactive Atlas) across near-Arctic latitudes are exceptionally pronounced (&gt;0.5°C per decade), significant and consistent across datasets except for far north-east Canada where trends are not significant in the CRU dataset. Significant positive trends are seen across the rest of North America during 1961–2015 (Figure Atlas.11) though over the shorter 1980–2015 period the regional dataset Daymet ( [[#Thornton--2016|Thornton et al., 2016]] ) records non-significant changes over southern Alaska, western and south-central Canada, and north-central USA (Interactive Atlas). An analysis of annual mean surface temperature in the Berkeley Earth dataset aggregated over the reference regions (Figure Atlas.11) demonstrates that a temperature change signal has emerged over all regions of North America. There is a detectable anthropogenic influence ( ''medium confidence'' ) on the observed upward annual temperature trends in Western and northern North America ( [[#Vose--2017|Vose et al., 2017]] ; Z. [[#Wang--2017|]] [[#Wang--2017|Wang et al., 2017]] ; [[#Smith--2019|Smith et al., 2019]] ).

Compared to temperature, trends in annual precipitation over 1961–2015 are generally non-significant though there are consistent positive trends over parts of ENA and CNA (Figure Atlas.11 and Daymet, Interactive Atlas) ( ''high confidence'' ). The global and regional datasets in Figure Atlas.11 and the Interactive Atlas also indicate significant decreases in precipitation in parts of south-western USA and north-western Mexico (Figure 2.15) though these are not all spatially coherent so there is only ''medium confidence'' in a drying trend over this region.

Several factors account for the differences in temperature and precipitation trend significance. Observed trends in precipitation are relatively modest compared to the very large natural interannual variability of precipitation. Furthermore, the precipitation observing network is spatially inadequate ( [[IPCC:Wg1:Chapter:Chapter-10#10.2.2.3|Section 10.2.2.3]] ) and temporally inconsistent ( [[IPCC:Wg1:Chapter:Chapter-10#10.2.2.2|Section 10.2.2.2]] ) over some regions of North America, particularly over the Arctic and mountainous areas. So detection of multi-decadal trends is difficult, especially for regions with summer convective precipitation maxima that may be spatially patchy ( [[#Easterling--2017|Easterling et al., 2017]] ). See [[IPCC:Wg1:Chapter:Chapter-2#2.3|Section 2.3]] for further discussion of precipitation trends.

There is evidence of a recent decline in the overall North American annual maximum snow mass, with a trend for non-alpine regions above 40°N during 1980–2018 estimated from the bias-corrected GlobSnow 3.0 data ( ''medium confidence'' ) ( [[#Pulliainen--2020|Pulliainen et al., 2020]] ). This is despite technical challenges with in situ measurements and remote-sensing retrievals of snow variables ( [[#Larue--2017|Larue et al., 2017]] ; [[#Smith--2017|Smith et al., 2017]] ; X.L. [[#Wang--2017|]] [[#Wang--2017|Wang et al., 2017]] ; [[#Zeng--2018|Zeng et al., 2018]] ), spatial heterogeneity and interpolation assumptions that affect gridded reference products, notably over alpine and forested areas ( [[#Mudryk--2015|Mudryk et al., 2015]] ; [[#Dozier--2016|Dozier et al., 2016]] ; [[#Cantet--2019|Cantet et al., 2019]] ), and breaks in instruments and procedures ( [[#Kunkel--2007|Kunkel et al., 2007]] ; [[#Mortimer--2020|Mortimer et al., 2020]] ). Changes in snow cover have evolved in a complex way, with both positive and negative trends, and differing from one metric to another ( [[#Knowles--2015|Knowles, 2015]] ; [[#Brown--2019|Brown et al., 2019]] ). Evidence of snow cover decline includes decreases in annual maximum snow depth and in snow water equivalent ( [[#Vincent--2015|Vincent et al., 2015]] ; [[#Kunkel--2016|Kunkel et al., 2016]] ; [[#Mote--2018|Mote et al., 2018]] ), as well as a shortening of the snow-season duration ( [[#Knowles--2015|Knowles, 2015]] ; [[#Vincent--2015|Vincent et al., 2015]] ). However, reported snow-decline trends are statistically significant only for a fraction of the concerned areas or locations ( ''low confidence'' ) (Figure Atlas.25). See also Sections 2.3.2.2 and 9.5.3.1.

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[[File:3fc61d5e24945064372a96beca40da5f IPCC_AR6_WGI_Atlas_Figure_25.png]]

'''Figure Atlas.25''' '''|''' '''Grid-box trends (mm yr''' –1 ''') in annual maximum snow depth for cold-season periods of 1960/1961 to 2014/2015 in North America.''' '''(Left)''' Numbers indicate number of stations available in that grid box. '''(Right)''' Boxes with ‘x’ indicate non-significant trends (at the p &lt; 0.05 level of significance; [[#Kunkel--2016|Kunkel et al., 2016]] ).

[[#Rupp--2013|Rupp et al. (2013)]] applied a standard fingerprinting approach to CMIP5 models and determined that the decline in Northern Hemisphere spring snow cover extent could only be explained by simulations that included natural and anthropogenic forcing. In an attribution study focusing on direct physical causes, it was found that increased spring snowmelt in northern Canada was driven by warming-induced high-latitude changes such as atmospheric moisture, cloud cover, and energy advection ( [[#Mioduszewski--2014|Mioduszewski et al., 2014]] ).

In an analysis of drivers of the record low snow water equivalent (SWE) values of spring 2015 in the western USA, it was found that the relative importance of greenhouse gases varies spatially ( [[#Mote--2016|Mote et al., 2016]] ). See also [[IPCC:Wg1:Chapter:Chapter-3#3.4.2|Section 3.4.2]] for further discussion of anthropogenic influences on snow extent.

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=== Atlas.9.3 Assessment of Model Performance ===

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CMIP6 models have been evaluated in the literature, although these studies have not included the full set of CMIP6 simulations. [[#Fan--2020|Fan et al. (2020)]] established on a continental basis for North America that temperature pattern correlations were quite accurate. [[#Thorarinsdottir--2020|Thorarinsdottir et al. (2020)]] compared maximum and minimum temperatures over Europe and North America with several observational datasets and found that the CMIP6 ensemble agreed better with ERA5 data than did CMIP5. [[#Srivastava--2020|Srivastava et al. (2020)]] evaluated historical CMIP6 simulations for precipitation, comparing them with several observational datasets over the continental US. Most models show a wet bias over the eastern half of the continental USA and the north-east region, while dry biases persist in the central part of the country ( [[#Akinsanola--2020a|Akinsanola et al., 2020a]] ; [[#Almazroui--2021|Almazroui et al., 2021]] ). The spatial structure of biases is similar in CMIP5 and CMIP6, but with lower magnitudes in CMIP6. [[#Agel--2020|Agel and Barlow (2020)]] examined 16 CMIP6 models over the north-eastern USA for precipitation and did not find a distinct improvement over CMIP5, although they did find the higher-resolution models tended to perform better. On the basis of the evidence so far, there is ''medium confidence'' that CMIP6 models are improved compared to CMIP5 in terms of biases in mean temperature and precipitation over North America.

North America has been extensively used as a test bed for regional climate model (RCM) experiments, such as the North American Regional Climate Change Assessment Program (NARCCAP; [[#Mearns--2009|Mearns et al., 2009]] ), the MultiRCM Ensemble Downscaling (MRED; [[#Yoon--2012|Yoon et al., 2012]] ), and NA-CORDEX ( [[#Bukovsky--2020|Bukovsky and Mearns, 2020]] ). Therefore, much performance evaluation has been conducted with a focus on specific climate features in North America. For the North American Monsoon region, multi-model performance evaluation ( [[#Bukovsky--2013|Bukovsky et al., 2013]] ; [[#Tripathi--2013|Tripathi and Dominguez, 2013]] ; [[#Cerezo-Mota--2016|Cerezo-Mota et al., 2016]] ) or a single-member performance ( [[#Lucas-Picher--2013|Lucas-Picher et al., 2013]] ; [[#Martynov--2013|Martynov et al., 2013]] ; [[#Šeparović--2013|Šeparović et al., 2013]] ) demonstrated the added value of RCMs, particularly more recent CORDEX simulations, through improved simulation of summer precipitation and the climatological winter storm tracks across the western USA. NA-CORDEX simulations were more successful at reproducing weather types compared to a single model-based large perturbed-physics ensemble ( [[#Prein--2019|Prein et al., 2019]] ). The application of a complex evaluation tool to the full suite of NA-CORDEX simulations found that the higher-resolution simulations (25 km compared with 50 km) of precipitation were improved, particularly for daily intensity ( [[#Gibson--2019|Gibson et al., 2019]] ).

However, deficiencies have also been reported. For example, excessive storm occurrence over the east coast of North America was found ( [[#Poan--2018|Poan et al., 2018]] ), and amplitude in the simulated annual cycle was generally excessive in NA-CORDEX simulations. RCMs tend to produce more (less) precipitation over mountains (the coastal plains; [[#Cerezo-Mota--2016|Cerezo-Mota et al., 2016]] ) and winter precipitation in the western USA had large positive biases in all RegCM simulations, regardless of the driving GCM ( [[#Mahoney--2021|Mahoney et al., 2021]] ).

Recently, convective-permitting RCMs have been used to simulate North American climate features and generated better simulations of precipitation. For example, summer precipitation over the south-western USA was improved due to better representation of organized mesoscale convective systems at the sub-daily scale ( [[#Castro--2012|Castro et al., 2012]] ; [[#Liu--2017|Liu et al., 2017]] ; [[#Prein--2017a|Prein et al., 2017a]] ; [[#Pal--2019|Pal et al., 2019]] ), the diurnal cycle of convection ( [[#Nesbitt--2008|Nesbitt et al., 2008]] ), and in terms of means (and extremes) for the north-eastern USA ( [[#Komurcu--2018|Komurcu et al., 2018]] ).

Recent studies have examined RCMs’ simulation of SWE, a quantity of primary importance notably for hydrological modelling, though its ground measurements are restricted by relatively high time and monetary costs ( [[#Smith--2017|Smith et al., 2017]] ; [[#Odry--2020|Odry et al., 2020]] ) which limit model assessment. Also, studies often emphasize that a false impression of model skill for SWE can be obtained by compensating temperature and precipitation biases. Assessment frameworks have dealt with these issues by considering observational uncertainty ( [[#Mccrary--2017|Mccrary et al., 2017]] ) and by decomposing SWE biases into their contributing processes ( [[#Rhoades--2018|Rhoades et al., 2018]] ; [[#Xu--2019|Xu et al., 2019]] ). SWE biases exceed observational uncertainty in several 50-km reanalysis-driven NARCCAP simulations over several regions, for all cold months ( [[#Mccrary--2017|Mccrary et al., 2017]] ). Analyses of NA-CORDEX simulations show that refining spatial resolution from 50 to 12 km improves certain (but not all) aspects of SWE, stemming from improved mean precipitation and topography-related temperature ( [[#Xu--2019|Xu et al., 2019]] ). Similarly an assessment of RCM simulations of freezing rain over eastern Canada found a mix of improved and deteriorated aspects from higher resolution ( [[#St-Pierre--2019|St-Pierre et al., 2019]] ).

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=== Atlas.9.4 Assessment and Synthesis of Projections ===

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CMIP5 and CMIP6 surface temperature and precipitation projections over the region are similar, with all regions warming more than the global average, most prominently those in the north (Figure Atlas.26). CMIP6 projects, for all scenarios and time periods, higher temperature changes (Chapter 4), with this contrast more accentuated in the long-term future and at higher global warming levels. The higher warming in the north (Interactive Atlas) is clear when comparing NEN, with increases from 2°C to over 8.5°C on an annual basis for SSP5-8.5 (near term to long term compared to a 1995–2014 baseline), to NCA, where changes range from 1.5°C to 6°C across the same periods. Maps showing changes in temperature and precipitation, and their robustness, are available in the Interactive Atlas. The number of model results (i.e., ensemble size used to generate these figures) differs, and this sample size difference may affect the results, but the patterns and magnitudes of change are generally consistent and thus it is ''very likely'' that temperatures will increase throughout the 21st century in all land areas, with stronger warming in the far north.

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[[File:0f5495015e52f10ea2a8b085346935cc IPCC_AR6_WGI_Atlas_Figure_26.png]]

'''Figure Atlas.26''' '''|''' '''Regional changes over land in annual mean surface air temperature andprecipitation relative to the 1995–2014 baseline for the reference regions in North America (warming since the 1850–1900 pre-industrial baseline is also provided as an offset).''' Bar plots in the left panel of each region triplet show the median (dots) and 10th–90th percentile range (bars) across each model ensemble for annual mean temperature changes for four datasets (CMIP5 in intermediate colours; a subset of CMIP5 used to drive CORDEX in light colours; CORDEX overlying the CMIP5 subset with dashed bars; and CMIP6 in solid colours); the first six groups of bars represent the regional warming over two time periods (near-term 2021–2040 and long-term 2081–2100) for three scenarios (SSP1-2.6/RCP2.6, SSP2-4.5/RCP4.5 and SSP5-8.5/RCP8.5), and the remaining bars correspond to four global warming levels (GWLs: 1.5°C, 2°C, 3°C and 4°C). The scatter diagrams of temperature against precipitation changes display the median (dots) and 10th–90th percentile ranges for the above four warming levels for December–January–February (DJF; middle panel) and June–July–August (JJA; right panel), respectively; for the CMIP5 subset only the percentile range of temperature is shown, and only for 3°C and 4°C GWLs. Changes are absolute for temperature (in °C) and relative (as %) for precipitation. See [[#Atlas.1.3|Atlas.1.3]] for more details on reference regions ( [[#Iturbide--2020|Iturbide et al., 2020]] ) and [[#Atlas.1.4|Atlas.1.4]] for details on model data selection and processing. The script used to generate this figure is available online ( [[#Iturbide--2021|Iturbide et al., 2021]] ) and similar results can be generated in the Interactive Atlas for flexibly defined seasonal periods. Further details on data sources and processing are available in the chapter data table (Table Atlas.SM.15).

CMIP5 results have been analysed extensively (e.g., [[#Maloney--2014|Maloney et al., 2014]] ) and used in major climate change assessments. The most recent US National Climate Assessment analysis of CMIP5 focusing on RCP4.5 and RCP8.5 for two future time periods stated that the USA would continue to warm regardless of the scenario, but is ''likely'' to be higher with higher-emissions scenarios (e.g., RCP8.5). Projected changes in precipitation are somewhat complex, but increased precipitation dominates in winter and spring, whereas in summer changes are more variable and uncertain. Canada’s Changing Climate Report (Bush and Lemmen, 2019) presents changes in temperature and precipitation, as well as other variables, such as snow, for future periods in Canada using results from CMIP5. It indicates that annual and winter precipitation is projected to increase everywhere in Canada over the 21st century with larger percentage increases in the north. Temperature is also projected to increase, regardless of the scenario, and with larger changes occurring in the north.

To provide the basis for generating additional information compared to that derived from CMIP5 the NA-CORDEX experiments were designed to involve a GCM-RCM matrix which included multiple GCMs that sampled the full range of climate sensitivity, multiple RCMs, at two different spatial resolutions (25 and 50 km) and a range of emissions scenarios (in most cases RCP4.5 and RCP8.5; [[#Mearns--2017|Mearns et al., 2017]] ). [[#Karmalkar--2018|Karmalkar (2018)]] noted that the NA-CORDEX models cover sub-regional ranges of temperature change from the CMIP5 GCMs better than NARCCAP did for the CMIP3 models. This structural design shift provides greater confidence in the NA-CORDEX results in terms of sampling the uncertainty across the CMIP5 models (Figure Atlas.27; [[#Bukovsky--2020|Bukovsky and Mearns, 2020]] ). The pattern of warming is as seen in CMIP5 and CMIP6, which also builds confidence that the RCMs generate high-resolution results consistent with CMIP5 on large scales whilst providing added value over regions such as the complex topography of the Rocky Mountains in the western USA, which are not well resolved in the GCMs. There is ''high confidence'' that downscaling a subset of CMIP models that spans the range of climate sensitivities in the full ensemble is critical for producing a representative range of dynamically downscaled projections.

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[[File:148f532049c9b5cbf83f229a952736e2 IPCC_AR6_WGI_Atlas_Figure_27.png]]

'''Figure Atlas.27''' '''|''' '''Changes (2070–2099 relative to 1970–1999) in the annual mean surface air temperature by three GCMs (GFDL-ESM2M, MPI-ESM-LR, HadGEM2-ES) and two RCMs (WRF and RegCM4) nested in the GCMs, for the RCP8.5 scenario over North America (after [[#Bukovsky--2020|Bukovsky and Mearns, 2020]] ).'''

There are striking contrasts in the seasonal results for precipitation for the sub-regions (Figure Atlas.26). The northern regions and ENA all show steady increases with the global warming levels ( ''very high confidence'' ). For example, the projected increases in the NEN region range from 7% in the near term to 40% at the end of the 21st century for the SSP5-8.5 scenario. In contrast, projected changes for NCA are for significant decreases both on an annual basis (Interactive Atlas) and in winter, and which become greater as warming increases ( [[#Akinsanola--2020b|Akinsanola et al., 2020b]] ; [[#Almazroui--2021|Almazroui et al., 2021]] ). The other two regions (WNA and CNA) exhibit mainly increases in winter. In summer, distributions are in general less uniform except for NWN and NEN, which display steady increases with global warming levels (but smaller than in winter). WNA and CNA mainly show decreases (based on the median values) but with some models projecting increases. Projections from the NA-CORDEX ensemble are consistent with those from the GCMs whilst providing greater detail of precipitation changes over the mountains and along the coasts (Interactive Atlas; [[#Bukovsky--2020|Bukovsky and Mearns, 2020]] ). Similar results are found in other analyses of RCM projections ( [[#Wang--2015|Wang and Kotamarthi, 2015]] ; [[#Ashfaq--2016|Ashfaq et al., 2016]] ; [[#Teichmann--2021|Teichmann et al., 2021]] ). Also, further analysis of the NA-CORDEX projections showed substantial changes in weather types related to increased monsoonal flow frequency and drying of the northern Great Plains in summer ( [[#Prein--2019|Prein et al., 2019]] ).

In summary, NEN, NWN and most of ENA will ''very likely'' experience increased annual mean precipitation, with greater increases at higher levels of warming ( ''very high confidence'' ). In NCA decreases predominate on an annual basis and particularly in winter ( ''high confidence'' ). Projected changes in summer are highly uncertain throughout other regions apart from the far northern parts of NEN and NWN which will ''likely'' experience increases ( ''high confidence'' ).

As discussed in [[IPCC:Wg1:Chapter:Chapter-10#10.3.3.4|Section 10.3.3.4]] , an important advance in regional modelling over the past decade or so is the use of convection-permitting regional models (CPMs; [[#Prein--2015|Prein et al., 2015]] , [[#Prein--2017a|Prein et al., 2017a]] ). There have been a number of experiments using CPMs over North America (e.g., [[#Rasmussen--2014|Rasmussen et al., 2014]] ; [[#Prein--2015|Prein et al., 2015]] , [[#Prein--2019|Prein et al., 2019]] ; [[#Liu--2017|Liu et al., 2017]] ; [[#Komurcu--2018|Komurcu et al., 2018]] ). A CPM study over North America that investigated changes in Mesoscale Convective Systems projected that by the end of the century, assuming an RCP8.5 scenario, their frequency more than tripled and associated precipitation increased by 80% ( [[#Prein--2017b|Prein et al., 2017b]] ). A multiple nesting of WRF over the north-eastern USA, downscaling to 3 km a CESM GCM climate projection assuming an RCP8.5 scenario, found a different pattern of precipitation change of mixed increases and decreases compared to the GCM projection of increases every month ( [[#Komurcu--2018|Komurcu et al., 2018]] ). These investigations demonstrate the potential of very-high-resolution simulations to add important dimensions to our understanding of regional climate change, though not necessarily to reduce uncertainty ( ''high confidence'' ).

It is ''virtually certain'' that snow cover will experience a general decline across North America during the 21st century, in terms of extent, annual duration and SWE, based on CMIP5 ( [[#Maloney--2014|Maloney et al., 2014]] ), CMIP6 ( [[#Mudryk--2020|Mudryk et al., 2020]] ), NA-CORDEX ( [[#Mahoney--2021|Mahoney et al., 2021]] ) and NARCCAP (e.g., [[#McCrary--2019|McCrary and Mearns, 2019]] ) simulations. For some regions the decline could be discernible over the next few decades, for example in the western USA ( [[#Fyfe--2017|Fyfe et al., 2017]] ). It is, however, ''likely'' that some high-latitude regions will rather experience an increase in certain winter snow cover properties ( [[#Mudryk--2018|Mudryk et al., 2018]] ; [[#McCrary--2019|McCrary and Mearns, 2019]] ), due to snowfall increase ( [[#Krasting--2013|Krasting et al., 2013]] ) prevailing over the warming effect. Discussion of changes in snow in the future is also covered in [[IPCC:Wg1:Chapter:Chapter-9#9.5.3|Section 9.5.3]] , but for larger regions.

The fraction of precipitation falling as snow is projected to decrease practically everywhere over North America, including over the western USA and south-western Canada ( [[#Mahoney--2021|Mahoney et al., 2021]] ), and in the Great Lakes basin where lake-effect precipitation is important ( [[#Suriano--2016|Suriano and Leathers, 2016]] ). In this basin, the frequency of heavy lake-effect snowstorms is expected to decrease during the 21st century, except for a possible temporary increase around Lake Superior by mid-century, if local air temperatures remain low enough ( [[#Notaro--2015|Notaro et al., 2015]] ). CMIP5 simulations of the periods 1981–2000 and 2081–2100 over the central and eastern USA suggest a northward shift in the transition zone between rain-dominated and snow-dominated areas, by about 2° latitude under the RCP4.5 scenario and 4° latitude under the RCP8.5 scenario ( [[#Ning--2015|Ning and Bradley, 2015]] ). Rain-on-snow event properties over North America should also evolve during the 21st century, with non-trivial dependencies on the positioning relative to the freezing line ( [[#Jeong--2018|Jeong and Sushama, 2018]] ) and on elevation ( [[#Musselman--2018|Musselman et al., 2018]] ).

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=== Atlas.9.5 Summary ===

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Across North America it is ''very likely'' that positive surface temperature trends are persistent '''.''' Across near-Arctic latitudes of North America, increases are exceptionally pronounced, greater than 0.5°C per decade ( ''high confidence'' ). In parts of Eastern and Central North America it is ''likely'' that annual precipitation has increased over the period 1961–2015 but with no clear trends in other regions except for parts of the south-western USA and north-western Mexico where there is ''medium confidence'' in drying.

Model representation of the climatology of mean temperature and precipitation has ''likely'' improved compared to AR5 over North America. This is aided by continuous model development, and the existence of new coordinated modelling initiatives such as NA-CORDEX. There is ''high confidence'' that downscaling a subset of CMIP models that spans the range of climate sensitivities in the full ensemble is critical for producing a representative range of dynamically downscaled projections.

It is ''virtually certain'' that annual and seasonal surface temperatures over all of North America will continue to increase at a rate greater than the global average, with greater increases in the far north. It is ''very likely'' , based on global and regional model future projections, that on an annual time scale precipitation will increase over most of North America north of about 45°N and in Eastern North America, and it is ''likely'' that it will decrease in the south-western USA and northern Mexico, particularly in winter. Elsewhere the direction of change of precipitation is uncertain. It is ''virtually certain'' that snow cover will experience a decline over most regions of North America during the 21st century, in terms of water equivalent, extent and annual duration '''.''' It is, however, ''likely'' that some high-latitude regions will rather experience an increase in winter SWE, due to the snowfall increase prevailing over the warming effect.

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