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Pedro Sequera, Jorge E. González, Kyle McDonald, Steve LaDochy, and Daniel Comarazamy

understanding the combined effects of large-scale (GHG and PDO) and regional-scale (UHI) factors on summer coastal cooling following the methodology developed by Comarazamy et al. (2010 , 2013 ). This approach integrates ground and remote sensing information ( Comarazamy et al. 2010 ) as well as mesoscale atmospheric modeling and statistical techniques ( Comarazamy et al. 2013 ), allowing quantification of the individual and combined contributions of LCLU changes and large-scale forcings to the magnitude

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Andres Schmidt, Beverly E. Law, Mathias Göckede, Chad Hanson, Zhenlin Yang, and Stephen Conley

-down perspectives. Both modeling techniques are affected by uncertainties that make direct comparisons challenging. Atmospheric inverse modeling uses measurements of atmospheric mixing ratios of a trace gas to constrain surface fluxes of the same gas to match those mixing ratio observations. This is achieved by linking the mixing ratios to the fluxes through a transport model ( Gerbig et al. 2003 ). While accounting for uncertainties associated with mixing ratio observations, the transport model, and the

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