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

=== 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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