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Xiao-Ming Hu, Ming Xue, Petra M. Klein, Bradley G. Illston, and Sheng Chen

2000 ; Hu et al. 2013b ). Oke et al. (1991) used a simple energy balance model to assess the relative importance of the commonly stated intrinsic causes of UHI under calm and cloudless conditions, including anthropogenic heat, thermal properties/moisture availability of the materials of the city, street canyon geometry, and urban greenhouse gases. The first three of these were identified as the main intrinsic causative factors contributing to the UHII in a modeling study conducted by Ryu and

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Jie Chen, Xiangquan Li, Jean-Luc Martel, François P. Brissette, Xunchang J. Zhang, and Allan Frei

natural or anthropogenic external forcing (external climate variability). ICV is the natural fluctuation intrinsic to a given climate state due to internal interactions within the complex nonlinear climate system. External forcing includes anthropogenic forcing such as greenhouse gas (GHG) emission and tropospheric aerosol loading acting on the atmosphere’s composition, and natural external forcing ranging from radiation variations due to pulse-like events such as explosive volcanic eruptions and

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Gabriele C. Hegerl, Thomas J. Crowley, Myles Allen, William T. Hyde, Henry N. Pollack, Jason Smerdon, and Eduardo Zorita

1. Introduction Climate records over the last millennium provide observational information on natural climate variability on time scales of multiple decades and centuries. It is from this backdrop of natural climate variability that anthropogenic changes need to be distinguished (e.g., Mitchell et al. 2001 ; International Ad Hoc Detection and Attribution Group 2005 ). Reconstructions of preinstrumental surface temperature have employed “proxy” information derived from historical records, tree

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John Austin, Larry W. Horowitz, M. Daniel Schwarzkopf, R. John Wilson, and Hiram Levy II

overall recommendation of the 2010 Stratosphere–Troposphere Processes and Their Role in Climate (SPARC) Chemistry–Climate Model Validation (CCMVal) report ( SPARC CCMVal 2010 ). In this paper, the stratospheric temperature results and ozone distributions from the model are investigated to determine the likely effects of natural and anthropogenic processes on the historical stratosphere (1860–2005), including the effects of volcanoes and human produced halocarbons. 2. Description of model and

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Lauren M. Hand and J. Marshall Shepherd

. O. J. Brown , 2003 : Mountain and radar measurements of anthropogenic aerosol effects on snow growth and snowfall rate. Geophys. Res. Lett. , 30 , 1538 . doi:10.1029/2002GL016855 . Bradley , A. A. , and J. A. Smith , 1994 : The hydrometeorological environment of extreme rainstorms in the southern plains of the United States. J. Appl. Meteor. , 33 , 1428 – 1431 . Braham , R. R. , R. G. Semonin , A. H. Auer , S. A. Changnon Jr. , and J. M. Hales , 1981 : Summary

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H. Annamalai, Jan Hafner, K. P. Sooraj, and P. Pillai

aerosols ( Ramanathan et al. 2005 ), we show here that anthropogenic forcing through sea surface temperature (SST) warming over the tropical western Pacific likely causes the drying trend over South Asia. The All-India Rainfall (AIR) index is widely used as a measure of the strength of the Indian summer monsoon ( Parthasarathy et al. 1994 ). A simple running mean applied to AIR seasonal anomalies (see Fig. 1a , red line) shows dry and wet periods: dry periods occurred from 1900 to 1930 and from 1965

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Cheng Qian and Xuebin Zhang

weakening in the temperature seasonality in the Northern Hemisphere from 1950 to 2005 has been detected, particularly in the high latitudes (50°–70°N) and East Asia, and the overall spatiotemporal pattern of phase 5 of the Coupled Model Intercomparison Project (CMIP5) model-simulated response to external and anthropogenic forcings is consistent with the observed changes as revealed through the optimal fingerprinting technique ( Qian and Zhang 2015 ). To date, however, no optimal fingerprinting detection

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J. S. Gregg, L. M. Losey, R. J. Andres, T. J. Blasing, and G. Marland

1. Introduction With the increasing concentration of carbon dioxide (CO 2 ) in the atmosphere and its implications for global climate ( Solomon et al. 2007 ), there is a growing need for developing a more detailed description of the various components within the global carbon cycle. Scientific inquiries and analyses now call for data on anthropogenic CO 2 emissions at spatial and temporal scales finer than the countries and years at which emissions inventories have traditionally been conducted

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R. Bassett, P. J. Young, G. S. Blair, F. Samreen, and W. Simm

.5% ( United Nations 2015 ). Some end-of-century projections put Lagos’s population close to 100 million ( Hoornweg and Pope 2017 ). Yet, insufficient observations in Nigeria means understanding environmental risks is challenging ( Alens 2014 ). Inadvertent effects of large, rapid urbanization are well documented globally and include loss of vegetation and ecosystems ( Grimm et al. 2008 ; Seto et al. 2012 ; Ajibola et al. 2012 ; Obiefuna et al. 2013 ), degradation of water ( Ouyang et al. 2006

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Guoyong Leng and Qiuhong Tang

our ability to adapt to anthropogenic climate change (e.g., Döll 2002 ; Fischer et al. 2007 ; Elgaali et al. 2007 ; Yano et al. 2007 ; Rodríguez Díaz et al. 2007 ; Pfister et al. 2011 ; Konzmann et al. 2013 ). Overall, an increase in long-term mean IWD was estimated in a warming climate in most of these studies because of enhanced evaporative demand. For example, Döll (2002) predicted an increase of global IWD by ~5% by the 2020s and by ~10% by the 2070s based on the year 1995 irrigated

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