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Zhao Yang, Francina Dominguez, Hoshin Gupta, Xubin Zeng, and Laura Norman

coupled to a land surface and urban modeling system that aimed to address emerging issues in urban areas ( Skamarock et al. 2008 ). Our experiment uses the Noah land surface model (LSM) to model the land surface ( Chen and Dudhia 2001 ), thereby providing surface energy fluxes and surface skin temperatures that serve as the boundary conditions for the atmospheric model. While the original version of Noah LSM has a bulk parameterization for urban land use, our experiment uses a single-layer UCM to

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

assessments of the terrestrial carbon fluxes are especially challenging since they need to be nested into global scale grids that provide boundary conditions, which accurately represent processes outside the modeling domain. Assessments need to be made at scales appropriate for decision-making, which requires representation of finescale processes that are usually missing from coarse-scale applications. Our study region is ideal for the development of a modeling framework that could be applied in other

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A L. Hirsch, A. J. Pitman, J. Kala, R. Lorenz, and M. G. Donat

terrain-following pressure-based vertical coordinates ( Skamarock et al. 2008 ). WRF simulations are typically forced with reanalysis or GCM output (for scenario simulations) at 6-hourly intervals to define the lateral boundary conditions. We use WRF coupled to the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM) ( Wang et al. 2011 ). CABLE includes a coupled model of stomatal conductance, photosynthesis, and partitioning of absorbed net radiation into latent and sensible

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Dev Niyogi, Ming Lei, Chandra Kishtawal, Paul Schmid, and Marshall Shepherd

; Hand and Shepherd 2009 ; Niyogi et al. 2011 ; Kishtawal et al. 2010 ; Smith et al. 2012 ; Yeung et al. 2015 ; Haberlie et al. 2015 ). Studies such as Pielke et al. (2011) document recent efforts in understanding the climatic impacts of LULCC. In general, the LULCC impact on rainfall is attributed to dynamic mesoscale boundaries such as changes in atmospheric convergence zones ( Rozoff et al. 2003 ; van den Heever and Cotton 2007 ; Lei et al. 2008 ) and aerosol impacts ( Rosenfeld 2000

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

entire extent of the SoCAB. The vertical grid included 50 levels from 1000 to 100 hPa, covering up to an altitude of approximately 16.12 km. Boundary conditions were provided every 6 h by the National Centers for Environmental Prediction (NCEP) 2.5° reanalysis data ( Kalnay et al. 1996 ) for all simulations, in addition to the 1° resolution NOAA’s Optimum Interpolation Sea Surface Temperature analysis ( Reynolds 1988 ) for initial conditions of SSTs. NCEP reanalysis was chosen over other higher

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Keith J. Harding, Tracy E. Twine, and Yaqiong Lu

; Means 1954 ). Abundant low-level convergence, cyclonic shear, and moisture convergence to the north of the GPLLJ maximum dynamically force convective development above the planetary boundary layer at night. For these reasons, the diurnal maximum in warm-season rainfall occurs at night instead of during peak heating when instability is the greatest ( Bonner 1968 ; Helfand and Schubert 1995 ; Weaver and Nigam 2011 ). Variations in the GPLLJ are influenced by fluctuations in the gradient between the

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Zhijuan Liu, Xiaoguang Yang, Xiaomao Lin, Kenneth G. Hubbard, Shuo Lv, and Jing Wang

factors. The yield gap between potential yield and attainable yield is mainly due to noncontrollable factors that include various environmental conditions and technologies available at research stations for the farmers’ field. This component of the yield gaps therefore cannot be narrowed or exploitable further in the current technologies ( Van Tran 2001 ). On the other hand, the yield gap between attainable yield and potential farmers’ yield is mainly due to differences in agronomic factors. This gap

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G. Strandberg and E. Kjellström

rainfall patterns in an RCM ( Wu et al. 2016 ). The simulations made in this study with vegetation changes in only one-half of the model domain show very small or no effect in the unchanged part. The conclusion is that there is no robust evidence for teleconnections given changes in a small area like one-half of Europe; this should be considered with the caveat that the simulations in this study use reanalysis boundary conditions and are not totally free to simulate their own atmospheric circulation

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Madhavi Jain, A. P. Dimri, and D. Niyogi

, Bhagpat, Sonepat, Jhajjar, Faridabad, and Gurgaon districts at its administrative boundary ( Figure 1a ). The NCR region also includes the Panipat, Rohtak, Rewari, Alwar, Bulandshahar, and Meerut districts. In the larger domain, the city lies between the Himalayas in the north and the Aravalis in the south, with the Yamuna River cutting through the city on the eastern side. Delhi is located in the plains with its elevation ranging from 213 to 290 m. Hot and dry summers and fairly cold winters

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Soumaya Belmecheri, Flurin Babst, Amy R. Hudson, Julio Betancourt, and Valerie Trouet

the “pracma” package in R) were applied to the seasonal series of 180 values for the 10° longitudinal windows to determine the spatially coherent NHJ positions for each season ( Figure S2 ). This longitudinal window was chosen because it is a robust representation of the NHJ cores within the longitudinal window range. The peak detection method identifies the eastern and western boundaries of the seasonal NHJ cores. Based on the longitudinal coherence (spatial correlation between neighboring

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