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Jean O. Dickey, Steven L. Marcus, and Olivier de Viron

Climatic Research Unit temperature series since 1850 (HadCRUT3; Brohan et al. 2006 ). Because anthropogenic effects have significantly altered Earth’s climate since the start of the industrial revolution ( Solomon et al. 2007 ), we correct for these by removing estimated anthropogenic temperature change as specified by appropriately forced runs of coupled atmosphere–ocean general circulation models from the observed temperature series. The GISTEMP data were corrected using the anthropogenic

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Duo Chan and Qigang Wu

1. Introduction Attribution studies have indicated that it is extremely likely that there has been a substantial anthropogenic contribution to global and continental surface air temperature (SAT) increases since the middle of the twentieth century ( Hegerl et al. 2007 ; Bindoff et al. 2014 ). On subcontinental and smaller scales, the relative contribution of internal variability compared to the forced response to observed changes tends to be larger, since spatial differences in internal

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Shao-Yi Lee and Chien Wang

subcontinent. High amounts of precipitation occur in this season, particularly over southwestern India as well as northeastern India where the monsoon flow meets orography. In the past decade, there has been an increase in studies on the effects of anthropogenic aerosols on the South Asian summer monsoon because of concerns over the climate effects of the escalating abundance of anthropogenic aerosols over South Asia and surrounding regions. The persistent aerosol layer in the region, or the “atmospheric

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Andrew Hoell, Martin Hoerling, Jon Eischeid, Xiao-Wei Quan, and Brant Liebmann

western Indian Ocean, which has effectively expanded the warm-pool region westward.” The argument for anthropogenically driven precipitation declines of March–May East African precipitation was revisited in Funk and Hoell (2015) . Therein, a global SST trend absent effects of El Niño–Southern Oscillation was estimated from the fully forced suite of historical simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5, Taylor et al. 2012 ). This “residual trend pattern,” which

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Jenny Lindén, Jan Esper, and Björn Holmer

1. Introduction It is well known that anthropogenic changes in land cover and land use (LCLU) can impact climate, with the most pronounced effects found in urban areas. A changed energy balance caused by many factors—increased thermal admittance of urban materials, limited radiative and advective cooling due to the urban geometry, lowered evapotranspiration cooling due to sealed surfaces and limited vegetation coverage, and anthropogenic heat release—tend to increase air temperatures in urban

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Qin Su and Buwen Dong

et al. 2016 ). In addition, Northeastern China experienced a hot summer in 2014, which was associated with decrease in precipitation ( Wilcox et al. 2015a ). Previous studies demonstrated a crucial role of anthropogenic activity in increasing the occurrence of the extreme temperatures and long-lasting heat waves over China ( Wen et al. 2013 ; Sun et al. 2014 ; Lu et al. 2016 ; Freychet et al. 2017 , 2018a , b ; Chen and Dong 2019 ), as well as intensifying the magnitude of the extreme

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Dominikus Heinzeller, Wolfgang Junkermann, and Harald Kunstmann

anthropogenic changes in levels of greenhouse gases and ozone in the atmosphere, whereas anthropogenic aerosols do not contribute significantly. This stands in contrast to numerous studies of the impact of aerosols on the build-up of clouds and precipitation through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics [see Tao et al. (2012) for a review]. Lee and Feingold (2013) investigated aerosol effects on cloud field properties

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Ryan J. Kramer and Brian J. Soden

applicability of the observational data to better understand anthropogenic climate change. Without intending to completely reconcile observations with model results, we investigate whether there is a fundamental difference between the constraints on Δ P under anthropogenic climate change and internal climate variability. This is not simply an academic question, but one that has important practical implications, since it is the shorter-time-scale internal variability that frequently dominates the

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Britton B. Stephens, Peter S. Bakwin, Pieter P. Tans, Ron M. Teclaw, and Daniel D. Baumann

layer to the interior of continents, and to apply these continental measurements to study global CO 2 budgeting, terrestrial biospheric processes, atmospheric transport, and industrial emissions. Presently, observed trends in atmospheric O 2 provide our best constraint on the long-term global partitioning of terrestrial and oceanic sinks for anthropogenic CO 2 ( Houghton et al. 2001 ). A key value in calculating this partitioning is the assumed O 2 :CO 2 ratio for the terrestrial uptake of

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Andrew R. Jongeward, Zhanqing Li, Hao He, and Xiaoxiong Xiong

attribution more reliably than any single source can suggest where the strengths of one data type can augment the deficiencies of others. This work expands on previous studies by considering the anthropogenic effects downwind of any significant anthropogenic sources. This paper is presented as follows. Section 2 describes the data products employed for this work. Section 3 contains results of AOD trend analysis from satellite and surface observational datasets. Section 4 discusses the attribution of

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