The list shown on this page is not updated frequently. A most up-to-date list of my publications can be found on my
Google Scholar and
ResearchGate pages.
In Review
Lackner, C. P. T. W. Juliano, et al.: Vertical structure of clouds and precipitation during Arctic cold-air outbreaks and warm-air intrusions: observations from COMBLE. In review at Journal of Geophysical Research: Atmospheres. DOI: https://doi.org/10.22541/essoar.167169287.71859473/v1
Haupt, S. E., T. W. Juliano, et al.: Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy. In review at Wind Energy Science. DOI: https://doi.org/10.5194/wes-2022-113.
Juliano, T. W., et al.: Toward a better understanding of wildfire behavior in the wildland-urban interface: A case study of the 2021 Marshall Fire. In review at Geophysical Research Letters. DOI: https://doi.org/10.1002/essoar.10512566.1
Eghdami, M., T. W. Juliano, et al.: Characterizing the environmental controls on the 2021 Santa Coloma de Queralt pyroconvective event using WRF-Fire. In review at Journal of Advances in Modeling Earth Systems.
Published
2023
[15] Shamsaei, K., T. W. Juliano, M. Roberts, H. Ebrahimian, B. Kosović, N. P. Lareau, and E. Taciroglu, 2023: Coupled fire-atmosphere simulation of the 2018 Camp Fire using WRF-Fire. International Journal of Wildland Fire. DOI: https://doi.org/10.1071/WF22013
2022
[14] Rybchuk, A., T. W. Juliano, J. K. Lundquist, D. Rosencrans, N. Bodini, and M. Optis, 2022: The sensitivity of the fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme, Wind Energ. Sci., 7, 2085–2098. DOI: https://doi.org/10.5194/wes-7-2085-2022
[13] Liu, Y., Y. Qian, S. Feng, L. K. Berg, T. W. Juliano, P. A. Jiménez, E. Grimit, and Y. Liu, 2022: Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-Solar, Sol. Energy, 241, 1–12. DOI: https://doi.org/10.1016/j.solener.2022.05.064
[12] DeCastro, A. L., T. W. Juliano, B. Kosović, H. Ebrahimian, and J. K. Balch, 2022: A computationally efficient method for updating fuel inputs for wildfire behavior models using Sentinel imagery and random forest classification. Remote Sens., 14, 1447. DOI: https://doi.org/10.3390/rs14061447
[11] Geerts, B., T. W. Juliano, et al., 2022: The COMBLE campaign: a study of marine boundary-layer clouds in Arctic cold-air outbreaks, Bull. Amer. Meteor. Soc, 103, E1371–E1389. DOI: https://doi.org/10.1175/BAMS-D-21-0044.1
[10] Arthur, R. S., T. W. Juliano, B. Adler, R. Krishnamurthy, J. K. Lundquist, B. Kosović, and P. A. Jiménez, 2022: Improved representation of horizontal variability and turbulence in mesoscale simulations of an extended cold-air pool event, J. Appl. Meteor. Climatol., 61, 685–707. DOI: https://doi.org/10.1175/JAMC-D-21-0138.1
[9] Eghdami, M., A. P. Barros, P. A. Jiménez, T. W. Juliano, and B. Kosović, 2022: Diagnosis of second-order turbulent properties of the surface layer for three-dimensional flow based on the Mellor and Yamada model, Mon. Wea. Rev., 150, 1003–1021. DOI: https://doi.org/10.1175/MWR-D-21-0101.1
[8] Juliano, T. W., B. Kosović, P. A. Jiménez, M. Eghdami, S. E. Haupt, and A. Martilli, 2022: “Gray zone” simulations using a three-dimensional planetary boundary layer parameterization in the Weather Research and Forecasting model, Mon. Wea. Rev., 150, 1585–1619. DOI: https://doi.org/10.1175/MWR-D-21-0164.1
[7] Juliano, T. W., P. A. Jiménez, B. Kosović, T. Eidhammer, G. Thompson, L. K. Berg, J. Fast, A. Motley, and A. Polidori, 2022: Smoke from 2020 United States wildfires responsible for substantial solar energy forecast errors, Environ. Res. Lett., 17, 034010. DOI: https://doi.org/10.1088/1748-9326/ac5143
[6] Liu, Y., Y. Qian, S. Feng, L. K. Berg, T. W. Juliano, P. A. Jiménez, and Y. Liu, 2022: Sensitivity of solar irradiance to model parameters in cloud and aerosol treatments of WRF-Solar, Sol. Energy, 233, 446–460. DOI: https://doi.org/10.1016/j.solener.2022.01.061
Pre-2022
[5] Juliano, T. W. and Z. J. Lebo, 2020: Linking large-scale circulation patterns to low-cloud properties, Atmos. Chem. Phys., 20, 7125–7138. DOI: https://doi.org/10.5194/acp-20-7125-2020
[4] Kosović, B., P. J. Munoz, T. W. Juliano, A. Martilli, M. Eghdami, A. P. Barros, and S. E. Haupt, 2020: Three-dimensional planetary boundary layer parameterization for high-resolution mesoscale simulations, J. of Phys.: Conf. Ser., 1452, 012080. DOI: https://doi.org/10.1088/1742-6596/1452/1/012080
[3] Juliano, T. W., M. M. Coggon, G. Thompson, D. A. Rahn, J. H. Seinfeld, A. Sorooshian, and Z. J. Lebo, 2019: Marine boundary layer clouds associated with coastally trapped disturbances: Observations and model simulations. J. Atmos. Sci., 76, 2963–2993. DOI: https://doi.org/10.1175/JAS-D-18-0317.1
[2] Juliano, T. W., Z. J. Lebo, G. Thompson, and D. A. Rahn, 2019: A new perspective on coastally trapped disturbances using data from the satellite era. Bull. Amer. Meteor. Soc., 100, 631–651. DOI: https://doi.org/10.1175/BAMS-D-18-0002.1
[1] Juliano, T. W., T. R. Parish, D. A. Rahn, and D. C. Leon, 2017: An atmospheric hydraulic jump in the Santa Barbara Channel. J. Appl. Meteor. Climatol., 56, 2981–2998. DOI: https://doi.org/10.1175/JAMC-D-16-0396.1
