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Solecki W, Rosenzweig C, Blake R, de Sherbinin A, Matte T, Moshary F, Rosenzweig B, Arend M, Gaffin S, Bou-Zeid E, et al. 2015. New york city panel on climate change 2015 report chapter 6: Indicators and monitoring. Annals of the New York Academy of Sciences. 1336:89–106. doi:10.1111/nyas.12587. Referenced from doi.org: New york city panel on climate change 2015 report chapter 6: Indicators and monitoring.

Mahrt L, Bou-Zeid E. 2020. Non-stationary Boundary Layers. Boundary-Layer Meteorology. 177:189–204. doi:10.1007/s10546-020-00533-w. Referenced from doi.org: Non-stationary Boundary Layers.

Wang Z-H, Bou-Zeid E. 2012. A novel approach for the estimation of soil ground heat flux. Agricultural and Forest Meteorology. 154-155:214. doi:10.1016/j.agrformet.2011.12.001. Referenced from doi.org: A novel approach for the estimation of soil ground heat flux.

Yang J, Wang Z-H, Li Q, Vercauteren N, Bou-Zeid E, Parlange M. 2017. A novel approach for unraveling the energy balance of water surfaces with a single depth temperature measurement. Limnology and Oceanography. 62:89–103. doi:10.1002/lno.10378. Referenced from doi.org: A novel approach for unraveling the energy balance of water surfaces with a single depth temperature measurement.

Gerges F, Boufadel M, Bou-Zeid E, Nassif H, Wang J. 2022. A Novel Bayesian Deep Learning Approach to the Downscaling of Wind Speed with Uncertainty Quantification. Vol. 13282 LNAI. pp. 55–66. Referenced from doi.org: A Novel Bayesian Deep Learning Approach to the Downscaling of Wind Speed with Uncertainty Quantification.

Gerges F, Boufadel M, Bou-Zeid E, Nassif H, Wang J. 2022. A Novel Deep Learning Approach to the Statistical Downscaling of Temperatures for Monitoring Climate Change. pp. 1–7. Referenced from doi.org: A Novel Deep Learning Approach to the Statistical Downscaling of Temperatures for Monitoring Climate Change.

Zahn E, Ghannam K, Chamecki M, Moene A, Kustas W, Good S, Bou-Zeid E. 2024. Numerical Investigation of Observational Flux Partitioning Methods for Water Vapor and Carbon Dioxide. Authorea Preprints. doi:10.22541/essoar.170716371.17109325/v1. Referenced from doi.org: Numerical Investigation of Observational Flux Partitioning Methods for Water Vapor and Carbon Dioxide.

Anderson W, Li Q, Bou-Zeid E. 2015. Numerical simulation of flow over urban-like topographies and evaluation of turbulence temporal attributes. Journal of Turbulence. 16:809–831. doi:10.1080/14685248.2015.1031241. Referenced from doi.org: Numerical simulation of flow over urban-like topographies and evaluation of turbulence temporal attributes.