4.6 Article

Hurricane Isaac: A Longitudinal Analysis of Storm Characteristics and Power Outage Risk

Journal

RISK ANALYSIS
Volume 36, Issue 10, Pages 1936-1947

Publisher

WILEY-BLACKWELL
DOI: 10.1111/risa.12552

Keywords

Hurricanes; power outages; random forest

Funding

  1. Environment, Energy, Sustainability and Health Institute (E2SHI)
  2. NSF IGERT Water, Climate, and Health program at Johns Hopkins University
  3. NSF from CMMI [1149460]
  4. Direct For Social, Behav & Economic Scie [1631409] Funding Source: National Science Foundation
  5. Divn Of Social and Economic Sciences [1631409] Funding Source: National Science Foundation

Ask authors/readers for more resources

In August 2012, Hurricane Isaac, a Category 1 hurricane at landfall, caused extensive power outages in Louisiana. The storm brought high winds, storm surge, and flooding to Louisiana, and power outages were widespread and prolonged. Hourly power outage data for the state of Louisiana were collected during the storm and analyzed. This analysis included correlation of hourly power outage figures by zip code with storm conditions including wind, rainfall, and storm surge using a nonparametric ensemble data mining approach. Results were analyzed to understand how correlation of power outages with storm conditions differed geographically within the state. This analysis provided insight on how rainfall and storm surge, along with wind, contribute to power outages in hurricanes. By conducting a longitudinal study of outages at the zip code level, we were able to gain insight into the causal drivers of power outages during hurricanes. Our analysis showed that the statistical importance of storm characteristic covariates to power outages varies geographically. For Hurricane Isaac, wind speed, precipitation, and previous outages generally had high importance, whereas storm surge had lower importance, even in zip codes that experienced significant surge. The results of this analysis can inform the development of power outage forecasting models, which often focus strictly on wind-related covariates. Our study of Hurricane Isaac indicates that inclusion of other covariates, particularly precipitation, may improve model accuracy and robustness across a range of storm conditions and geography.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available