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@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix gcis: <http://data.globalchange.gov/gcis.owl#> .
@prefix cito: <http://purl.org/spar/cito/> .
@prefix biro: <http://purl.org/spar/biro/> .

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   dcterms:identifier "key-finding-5-2";
   gcis:findingNumber "5.2"^^xsd:string;
   gcis:findingStatement "Recurring patterns of variability in large-scale atmospheric circulation (such as the North Atlantic Oscillation and Northern Annular Mode) and the atmosphere–ocean system (such as El Niño–Southern Oscillation) cause year-to-year variations in U.S. temperatures and precipitation (<em>high confidence</em>). Changes in the occurrence of these patterns or their properties have contributed to recent U.S. temperature and precipitation trends (<em>medium confidence</em>), although confidence is <em>low</em> regarding the size of the role of human activities in these changes."^^xsd:string;
   gcis:isFindingOf <https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability>;
   gcis:isFindingOf <https://data.globalchange.gov/report/climate-science-special-report>;

## Properties of the finding:
   gcis:findingProcess "Recurring modes of variability strongly affect temperature and precipitation over the United States on interannual timescales (<em>high confidence</em>) as supported by a very large number of observational and modeling studies. Changes in some recurring patterns of variability have contributed to recent trends in U.S. temperature and precipitation (<em>medium confidence</em>). The causes of these changes are uncertain due to the limited observational record and because models exhibit some difficulties simulating these recurring patterns of variability and their underlying physical mechanisms."^^xsd:string;
   
   gcis:descriptionOfEvidenceBase "The Key Finding is supported by a large number of studies that diagnose recurring patterns of variability and their changes, as well as their impact on climate over the United States. Regarding year-to-year variations, a large number of studies based on models and observations show statistically significant associations between North Atlantic Oscillation/Northern Annular Mode and United States temperature and precipitation, as well as El Niño–Southern Oscillation and related U.S. climate teleconnections. Regarding recent decadal trends, several studies provide evidence for concurrent changes in the North Atlantic Oscillation/Northern Annular Mode and climate anomalies over the United States. Modeling studies provide evidence for a linkage between cooling trends of the tropical Pacific Ocean that resemble La Niña and precipitation changes in the southern United States. Several studies describe a decadal modification of ENSO. Modeling evidence is provided that such decadal modifications can be due to internal variability. Climate models are widely analyzed for their ability to simulate recurring patterns of variability and teleconnections over the United States. Climate model projections are also widely analyzed to diagnose the impact of human activities on NAM/NAO, ENSO teleconnections, and other recurring modes of variability associated with climate anomalies."^^xsd:string;
   
   gcis:assessmentOfConfidenceBasedOnEvidence "There is <em>high confidence</em> that preferred patterns of variability affect U.S. temperature on a year-to-year timescale, based on a large number of studies that diagnose observational data records and long simulations. There is <em>medium confidence</em> that changes in the occurrence of these patterns or their properties have contributed to recent U.S. temperature and precipitation trends. Several studies agree on a linkage between decadal changes in the NAO/NAM and climate trends over the United States, and there is some modeling evidence for a linkage between a La Niña-like cooling trend over the tropical Pacific and precipitation changes in the southwestern United States. There is no robust evidence for observed decadal changes in the properties of ENSO and related United States climate impacts. Confidence is <em>low</em> regarding the size of the role of human influences in these changes because models do not agree on the impact of human activity on preferred patterns of variability or because projected changes are small compared to internal variability. "^^xsd:string;
   
   gcis:newInformationAndRemainingUncertainties "A key uncertainty is related to limited observational records and our capability to properly simulate climate variability on decadal to multidecadal timescales, as well as to properly simulate recurring patterns of climate variability, underlying physical mechanisms, and associated variations in temperature and precipitation over the United States."^^xsd:string;

   a gcis:Finding .

## This finding cites the following entities:


<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/JCLI-D-14-00254.1>;
   biro:references <https://data.globalchange.gov/reference/0cc23089-0001-453b-b3f7-99b53325f44b>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/jcli-d-15-0226.1>;
   biro:references <https://data.globalchange.gov/reference/0eca3f20-4ffe-4d20-baaa-2d605941578d>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1029/2010GL044007>;
   biro:references <https://data.globalchange.gov/reference/20e157eb-e2b4-4201-8422-1a0dc8cd499f>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/1520-0442(1992)005%3C0577:STPAWT%3E2.0.CO;2>;
   biro:references <https://data.globalchange.gov/reference/20e48aa7-625b-4527-8639-e0bcd469b79d>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/1520-0442(2001)014%3C1277:ROTNCR%3E2.0.CO;2>;
   biro:references <https://data.globalchange.gov/reference/26e7ebff-78f5-4697-8203-cfc9586c6a0c>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/2010JCLI3584.1>;
   biro:references <https://data.globalchange.gov/reference/2f2d945e-b0fe-43d7-a521-2a9219236862>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1088/1748-9326/12/1/014001>;
   biro:references <https://data.globalchange.gov/reference/33619644-54fd-43b3-9fa8-e7ac5ddec196>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/2009jcli3420.1>;
   biro:references <https://data.globalchange.gov/reference/39a41162-bda6-4606-9561-37e3e1839913>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/jcli-d-12-00542.1>;
   biro:references <https://data.globalchange.gov/reference/3c2004f1-4f51-4b84-8ec0-64a5e2c3a790>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1088/1748-9326/8/1/014019>;
   biro:references <https://data.globalchange.gov/reference/4e933785-f080-4cc8-86a0-5259159292e0>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/report/ipcc-ar5-wg1/chapter/wg1-ar5-chapter14-final>;
   biro:references <https://data.globalchange.gov/reference/541fc57b-d7ad-4617-97de-2df91f99afc0>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1126/science.269.5224.676>;
   biro:references <https://data.globalchange.gov/reference/56bdd0b7-8658-48c1-9814-24ea5a5c2fc9>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/JCLI-D-14-00822.1>;
   biro:references <https://data.globalchange.gov/reference/655f721c-7b5f-4f69-a788-fa1ee8a2488e>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/jcli-d-15-0441.1>;
   biro:references <https://data.globalchange.gov/reference/6782b38a-17f4-40d2-9cff-da07da38f76a>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/BAMS-D-13-00117.1>;
   biro:references <https://data.globalchange.gov/reference/7f094c4f-301c-422c-8fba-371b5502767c>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1002/grl.50249>;
   biro:references <https://data.globalchange.gov/reference/94d52b54-b40c-4447-a525-b79062fcedf1>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1175/jcli3530.1>;
   biro:references <https://data.globalchange.gov/reference/99d2a237-b811-4c42-9bc3-cfd6cbb76504>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1038/nature08316>;
   biro:references <https://data.globalchange.gov/reference/a3771226-1458-474e-ba3b-f046d4351558>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/report/ipcc-ar5-wg1/chapter/wg1-ar5-chapter09-final>;
   biro:references <https://data.globalchange.gov/reference/a46eaad1-5c17-46f7-bba6-d3fee718a092>.

<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   cito:cites <https://data.globalchange.gov/article/10.1007/s00704-007-0345-x>;
   biro:references <https://data.globalchange.gov/reference/b35b1dec-2d93-42a8-8a85-ba1a2cfa76b9>.



<https://data.globalchange.gov/report/climate-science-special-report/chapter/circulation-variability/finding/key-finding-5-2>
   prov:wasDerivedFrom <https://data.globalchange.gov/report/climate-science-special-report/chapter/front-matter/figure/confidence---likelihood>.