Walsh, T., Layton, T., Wanik D. W., Mellor J., 2018: Agent Based Model to Estimate Time to Restoration of Storm-Induced Power Outages, Infrastructures Volume 3(3), Page 33. DOI: 10.3390/infrastructures3030033
Wanik, D. W., Anagnostou, E. N., Astitha, M., Yang, J., Hartman, B. M., Frediani, M.E., Lackmann, G. M., 2018: “A Case Study on Power Outage Impacts from Future Hurricane Sandy Scenarios”, Accepted – Early Release Online. DOI:10.1175/JAMC-D-16-0408.1.
Wanik, D. W., He, J., Layton, T., Anagnostou, E. N., Hartman, B. M., 2017: Estimated Time of Restoration (ETR) Guidance for Electric Distribution Networks, Journal of Homeland Security and Emergency Management, Accepted November 2017. Link.
Cole, T.A., Wanik, D.W., Molthan, A.L., Román, M.O., Griffin, R.E, 2017: Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas, Remote Sens. Volume 9, Page 286. DOI: 10.3390/rs9030286
Wanik, D. W., Parent, J. R., Anagnostou, E. N., 2017: Using Vegetation Management and LiDAR-Derived Tree Height Data to Improve Outage Predictions for Electric Utilities, Electric Power Systems Research, Volume 146, May 2017, Pages 236–245. DOI: 10.1016/j.epsr.2017.01.039.
He, J., Wanik, D. W., Hartman, B. M., Anagnostou, E. N., 2016: Nonparametric Tree- Based Predictive Modeling of Storm Damage to Power Distribution Network, Risk Analysis. DOI:10.1111/risa.12652.
Wanik, D. W., Anagnostou, E. N., Hartman, B. M., Frediani, M. E., Astitha, M., 2015: Storm Outage Modeling for an Electric Distribution Network in Northeastern USA, Natural Hazards, Vol 79, p. 1359. DOI: 10.1007/s11069-015-1908-2
Presentation by Graduate Student T. Walsh, Feb 2019: Presentation
Poster with project overview, 2018: Poster_2018EEC
Michael Stephen Walters, Jaemo Yang, Marika Koukoula, Gregory Thompson and Marina Astitha, 2018: “Evaluation of Winter Weather Prediction During Extreme Snowfall Events for the NE US.” AGU Fall Meeting 2018, A048-Extreme Weather Events: Forecast skill, Uncertainty Quantification and Impact Modeling, Washington, DC, 10-14 December 2018. Poster presentation.
Jaemo Yang, Marina Astitha, Diego Cerrai, Peter Watson, 2018: “Uncertainty Assessment of Extreme Storm Forecasts Using Numerical Weather Prediction and Gridded Bayesian Linear Regression”. AGU Fall Meeting 2018, A048-Extreme Weather Events: Forecast skill, Uncertainty Quantification and Impact Modeling, Washington, DC, 10-14 December 2018. Poster presentation.
J. Yang, M. Astitha and C. S. Schwartz, 2018: Gridded Bayesian Linear Regression to Improve Storm Forecasts Using NCAR’s Real-Time Prediction System for Northeast United States. 98th Annual Meeting of the American Meteorological Society, 25th Conference on Probability and Statistics, Jan 8-11, 2018, Austin, TX, USA. Oral presentation.
J. Yang, M. Astitha and C. S Schwartz, 2017: Improvement of Storm Forecasts Using Gridded Bayesian Linear Regression for Northeast United States. AGU Fall Meeting 2017, NG001: Advances in Data Assimilation, Predictability and Uncertainty Quantification, New Orleans, 11-15 December 2017. Oral presentation.
J. Yang, M. Astitha, L. Delle Monache, and S. Alessandrini, 2017: Improvement of wind speed prediction using statistical and analog techniques for NE U.S. 97th Annual Meeting of the American Meteorological Society, 22–26 January, 2017 Washington State Convention Center, Seattle, Washington. Poster presentation.
J. Yang, M. Astitha, L. Delle Monache, and S. Alessandrini, 2016: Analog ensemble and Bayesian regression techniques to improve the wind speed prediction during extreme storms in the NE U.S. American Geophysical Union Fall 2016 Meeting, Dec 12-16, 2016, San Francisco, CA. Poster presentation.
J. Yang, M. Astitha and L. Delle Monache, 2016: Improvement of the numerical prediction of extreme weather events using Analog ensemble and Bayesian regression techniques in NE U.S. 3rd Annual New England Graduate Student Water Symposium (NEGSWS), September 9-11, 2016, University of Massachusetts Amherst, MA. Poster presentation.
Yang, J., M. Astitha, E.N. Anagnostou, B. Hartman, G. Kallos, 2015: Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach. American Geophysical Union Fall 2015 Meeting, Dec 14-18, 2015, San Francisco, CA.