Smith A, Barth M, Boos W, Bou-Zeid E, Kawatani Y, Lee S, Mechem D, Remer L, Rozoff C, van den Heever S, et al. 2020. Data availability principles and practice. Journal of the Atmospheric Sciences. 77:3983–3984. doi:10.1175/JAS-D-20-0303.1. Referenced from doi.org: Data availability principles and practice.

Gerges F, Boufadel M, Bou-Zeid E, Nassif H, Wang J. 2023. Deep Learning-Enabled Prediction of Daily Solar Irradiance from Simulated Climate Data. pp. 102–109. Referenced from doi.org: Deep Learning-Enabled Prediction of Daily Solar Irradiance from Simulated Climate Data.

Yang J, Bou-Zeid E. 2019. Designing sensor networks to resolve spatiooral urban temperature variations: Fixed, mobile or hybrid?. Environmental Research Letters. 14. doi:10.1088/1748-9326/ab25f8. Referenced from doi.org: Designing sensor networks to resolve spatiooral urban temperature variations: Fixed, mobile or hybrid?.

Allouche M, Bou-Zeid E, Ansorge C, Katul G, Chamecki M, Acevedo O, Thanekar S, Fuentes J. 2022. The Detection, Genesis, and Modeling of Turbulence Intermittency in the Stable Atmospheric Surface Layer. Journal of the Atmospheric Sciences. 79:1171–1190. doi:10.1175/JAS-D-21-0053.1. Referenced from doi.org: The Detection, Genesis, and Modeling of Turbulence Intermittency in the Stable Atmospheric Surface Layer.

Choi B, Pozzi M, Bergés M, Bou-Zeid E. 2021. Developing time-variant filter for meso-scale surface temperature prediction. pp. 59–65.

Li D, Bou-Zeid E, Barlage M, Chen F, Smith J. 2013. Development and evaluation of a mosaic approach in the WRF-Noah framework. Journal of Geophysical Research Atmospheres. 118:11,918–. doi:10.1002/2013JD020657. Referenced from doi.org: Development and evaluation of a mosaic approach in the WRF-Noah framework.

Talebpour M, Welty C, Bou-Zeid E. 2021. Development and testing of a fully-coupled subsurface-land surface-atmosphere hydrometeorological model: High-resolution application in urban terrains. Urban Climate. 40. doi:10.1016/j.uclim.2021.100985. Referenced from doi.org: Development and testing of a fully-coupled subsurface-land surface-atmosphere hydrometeorological model: High-resolution application in urban terrains.

Shah S, Bou-Zeid E. 2014. Direct numerical simulations of turbulent Ekman layers with increasing static stability: Modifications to the bulk structure and second-order statistics. Journal of Fluid Mechanics. 760:494–539. doi:10.1017/jfm.2014.597. Referenced from doi.org: Direct numerical simulations of turbulent Ekman layers with increasing static stability: Modifications to the bulk structure and second-order statistics.

Zahn E, Bou-Zeid E, Good S, Katul G, Thomas C, Ghannam K, Smith J, Chamecki M, Dias N, Fuentes J, et al. 2022. Direct partitioning of eddy-covariance water and carbon dioxide fluxes into ground and plant components. Agricultural and Forest Meteorology. 315. doi:10.1016/j.agrformet.2021.108790. Referenced from doi.org: Direct partitioning of eddy-covariance water and carbon dioxide fluxes into ground and plant components.

El-Samra R, Haddad A, Alameddine I, Bou-Zeid E, El-Fadel M. 2024. Downscaling Climatic Variables at a River Basin Scale: Statistical Validation and Ensemble Projection under Climate Change Scenarios. Climate. 12. doi:10.3390/cli12020027. Referenced from doi.org: Downscaling Climatic Variables at a River Basin Scale: Statistical Validation and Ensemble Projection under Climate Change Scenarios.

Gerges F, Boufadel M, Bou-Zeid E, Nassif H, Wang J. 2023. Downscaling daily wind speed with Bayesian deep learning for climate monitoring. International Journal of Data Science and Analytics. doi:10.1007/s41060-023-00397-6. Referenced from doi.org: Downscaling daily wind speed with Bayesian deep learning for climate monitoring.

Gerges F, Boufadel MC, Bou-Zeid E, Nassif H, Wang JTL. 2024. Downscaling daily wind speed with Bayesian deep learning for climate monitoring. International Journal of Data Science and Analytics. 17:411 – 424. doi:10.1007/s41060-023-00397-6. Referenced from www.scopus.com: Downscaling daily wind speed with Bayesian deep learning for climate monitoring.