Strengthening Grid Resilience: Improved Freezing Rain Nowcasting for Utility Outage Prevention

Industrial Relevance & Need:

Freezing rain (FZRA) represents a critical threat to power infrastructure, causing over $16 billion in insured property losses from 1949-2000. Single ice storm events have produced over 100mm of ice accretion, resulting in extended power outages and damages exceeding $4.4 billion. Power utilities urgently need advanced tools for accurate FZRA nowcasting, vulnerability assessment, and improved monitoring to maintain grid stability and develop effective risk mitigation strategies.

Project Goals:

Enhance utility network reliability and resilience by improving freezing rain detection and short-term prediction using advanced dual polarization radar and NYS Mesonet observations. Improve outage prediction model performance through better characterization and nowcasting of freezing rain, enabling utilities to better anticipate and mitigate storm-related outages through precise warning timing and location accuracy. 

Objectives:

Phase I: Develop dual polarization radar algorithm to distinguish freezing rain from other winter precipitation and calculate ice accumulation. Validate against surface observations and historical storm cases across the Northeast. Include the UAlbany radar-based FZRA product as additional UConn Outage Prediction Model (OPM) predictor and test the framework. 

Phase II: Integrate radar products into NYS MESONET dashboard with real-time utility alerts for icing conditions. Collaborate with utility partners to define operational thresholds (ice accretion rates, outage risk levels) and tailor alert outputs for decision support. Quantify benefits through case studies measuring reduced outage duration and improved storm response efficiency.