finding 2.5 : key-message-2-5

Annual average temperature over the contiguous United States has increased by 1.2ºF (0.7°C) over the last few decades and by 1.8°F (1°C) relative to the beginning of the last century (very high confidence). Additional increases in annual average temperature of about 2.5°F (1.4°C) are expected over the next few decades regardless of future emissions, and increases ranging from 3°F to 12°F (1.6°–6.6°C) are expected by the end of century, depending on whether the world follows a higher or lower future scenario, with proportionally greater changes in high temperature extremes (high confidence).



This finding is from chapter 2 of Impacts, Risks, and Adaptation in the United States: The Fourth National Climate Assessment, Volume II.

Process for developing key messages:

This chapter is based on the collective effort of 32 authors, 3 review editors, and 18 contributing authors comprising the writing team for the Climate Science Special Report (CSSR),75cf1c0b-cc62-4ca4-96a7-082afdfe2ab1 a featured U.S. Global Change Research Project (USGCRP) deliverable and Volume I of the Fourth National Climate Assessment (NCA4). An open call for technical contributors took place in March 2016, and a federal science steering committee appointed the CSSR team. CSSR underwent three rounds of technical federal review, external peer review by the National Academies of Sciences, Engineering, and Medicine, and a review that was open to public comment. Three in-person Lead Authors Meetings were conducted at various stages of the development cycle to evaluate comments received, assign drafting responsibilities, and ensure cross-chapter coordination and consistency in capturing the state of climate science in the United States. In October 2016, an 11-member core writing team was tasked with capturing the most important CSSR key findings and generating an Executive Summary. The final draft of this summary and the underlying chapters was compiled in June 2017.

The NCA4 Chapter 2 author team was pulled exclusively from CSSR experts tasked with leading chapters and/or serving on the Executive Summary core writing team, thus representing a comprehensive cross-section of climate science disciplines and supplying the breadth necessary to synthesize CSSR content. NCA4 Chapter 2 authors are leading experts in climate science trends and projections, detection and attribution, temperature and precipitation change, severe weather and extreme events, sea level rise and ocean processes, mitigation, and risk analysis. The chapter was developed through technical discussions first promulgated by the literature assessments, prior efforts of USGCRP,75cf1c0b-cc62-4ca4-96a7-082afdfe2ab1 e-mail exchanges, and phone consultations conducted to craft this chapter and subsequent deliberations via phone and e-mail exchanges to hone content for the current application. The team placed particular emphasis on the state of science, what was covered in USGCRP,75cf1c0b-cc62-4ca4-96a7-082afdfe2ab1 and what is new since the release of the Third NCA in 2014.dd5b893d-4462-4bb3-9205-67b532919566

Description of evidence base:

The Key Message and supporting text summarize extensive evidence documented in the climate science literature. Similar statements about changes exist in other reports (e.g., NCA3,dd5b893d-4462-4bb3-9205-67b532919566 Climate Change Impacts in the United States,e251f590-177e-4ba6-8ed1-6f68b5e54c8a SAP 1.1: Temperature trends in the lower atmosphere).f135add4-6d4c-4d88-a8f1-b880dbf5334f

Evidence for changes in U.S. climate arises from multiple analyses of data from in situ, satellite, and other records undertaken by many groups over several decades. The primary dataset for surface temperatures in the United States is nClimGrid,29960c69-6168-4fb0-9af0-d50bdd91acd3,596a7f1e-6ce5-4bdf-b144-d0715a7567bd though trends are similar in the U.S. Historical Climatology Network, the Global Historical Climatology Network, and other datasets. Several atmospheric reanalyses (e.g., 20th Century Reanalysis, Climate Forecast System Reanalysis, ERA-Interim, and Modern Era Reanalysis for Research and Applications) confirm rapid warming at the surface since 1979, and observed trends closely track the ensemble mean of the reanalyses.8243ec9e-5b70-4c53-a6bd-a8f41adb2d9c Several recently improved satellite datasets document changes in middle tropospheric temperatures.0215f34d-335f-4105-a3eb-b660e0ff8a78,42bc6c69-ca8d-4e06-8ad0-2fbad9cfd924 Longer-term changes are depicted using multiple paleo analyses (e.g., Trouet et al. 2013, Wahl and Smerdon 2012).5a3d5be0-e40f-4ea7-8f99-422db7954577,dc59a0d7-9c9d-45d8-966d-cf4bdedddc5a

Evidence for changes in U.S. climate arises from multiple analyses of in situ data using widely published climate extremes indices. For the analyses presented here, the source of in situ data is the Global Historical Climatology Network–Daily dataset.9b433446-b58f-4358-9737-5a6ccc2f6fcf Changes in extremes were assessed using long-term stations with minimal missing data to avoid network-induced variability on the long-term time series. Cold wave frequency was quantified using the Cold Spell Duration Index,e6ecbe14-fe1b-46f8-bad5-bde9e4cc658a heat wave frequency was quantified using the Warm Spell Duration Index,e6ecbe14-fe1b-46f8-bad5-bde9e4cc658a and heat wave intensity was quantified using the Heat Wave Magnitude Index Daily.546ef0fe-bfae-43ee-969e-5870c581e426 Station-based index values were averaged into 4° grid boxes, which were then area-averaged into a time series for the contiguous United States. Note that a variety of other threshold and percentile-based indices were also evaluated, with consistent results (e.g., the Dust Bowl was consistently the peak period for extreme heat). Changes in record-setting temperatures were quantified, as in Meehl et al. (2016).72301197-e20a-4328-accb-4276341a25db

Projections are based on global model results and associated downscaled products from CMIP5 for a lower scenario (RCP4.5) and a higher scenario (RCP8.5). Model weighting is employed to refine projections for each RCP. Weighting parameters are based on model independence and skill over North America for seasonal temperature and annual extremes. The multimodel mean is based on 32 model projections that were statistically downscaled using the LOcalized Constructed Analogs technique.62c66ef3-cddb-4797-ba0e-5672fbcc27b3 The range is defined as the difference between the average increase in the three coolest models and the average increase in the three warmest models. All increases are significant (i.e., more than 50% of the models show a statistically significant change, and more than 67% agree on the sign of the change).b63c9720-f770-4718-89cc-53b3616e2bec

New information and remaining uncertainties:

The primary uncertainties for surface data relate to historical changes in station location, temperature instrumentation, observing practice, and spatial sampling (particularly in areas and periods with low station density, such as the intermountain West in the early 20th century). Much research has been done to account for these issues, resulting in techniques that make adjustments at the station level to improve the homogeneity of the time series (e.g., Easterling and Peterson 1995, Menne and Williams 2009a7bd80fe-7df0-456b-9978-8f7e222bfafa,32bec5d2-97fe-41c5-8eed-6920bbf096f4). Further, Easterling et al. (1996)2b8701b9-46d8-4a52-a7a8-c074fe313126 examined differences in area-averaged time series at various scales for homogeneity-adjusted temperature data versus non-adjusted data and found that when the area reached the scale of the NCA regions, little differences were found. Satellite records are similarly impacted by non-climatic changes such as orbital decay, diurnal sampling, and instrument calibration to target temperatures. Several uncertainties are inherent in temperature-sensitive proxies, such as dating techniques and spatial sampling.

Global climate models are subject to structural and parametric uncertainty, resulting in a range of estimates of future changes in average temperature. This is partially mitigated through the use of model weighting and pattern scaling. Furthermore, virtually every ensemble member of every model projection contains an increase in temperature by mid- and late-century. Empirical downscaling introduces additional uncertainty (e.g., with respect to stationarity).

Assessment of confidence based on evidence:

There is very high confidence in trends since 1895, based on the instrumental record, since this is a long-term record with measurements made with relatively high precision. There is high confidence for trends that are based on surface/satellite agreement since 1979, since this is a shorter record. There is medium confidence for trends based on paleoclimate data, as this is a long record but with relatively low precision.

There is very high confidence in observed changes in average annual and seasonal temperature and observed changes in temperature extremes over the United States, as these are based upon the convergence of evidence from multiple data sources, analyses, and assessments including the instrumental record.

There is high confidence that the range of projected changes in average temperature and temperature extremes over the United States encompasses the range of likely change, based upon the convergence of evidence from basic physics, multiple model simulations, analyses, and assessments.

References :

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