Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System

Abstract In this paper, we propose a new capability for an oceanic hazards outlook containing delineations of where winds and waves are expected to have the potential of posing a hazard to either life or property at sea. This new product is based on NOAA’s Global Ensemble Forecast System, focused on developing a probabilistic forecast of 10-m wind speed (U10) and significant wave height (Hs) for week 2. The methodology involves defining temporal and spatial windows to postprocess the ensemble members and analyzing the tail of the probability density function generated by the pooled dataset. Specific thresholds for U10 and Hs as well as probability levels are defined in the algorithm to generate probability maps. The performance is assessed through statistical validation using NDBC buoy data and reanalysis, followed by case studies. Results indicate that the probabilistic forecast is skillful in predicting waves up to 9 m and winds up to 48 kt (1 kt ≈ 0.51 m s −1 ), particularly for extratropical systems. In addition, with weaker signals and lower probabilities forecasted, extreme extratropical events associated with hurricane-force winds could be in many cases successfully detected in the week 2 forecast. Therefore, the probability maps provide valuable guidance for practical applications, helping in decision-making for maritime operations.

Authors

Institutions

Publication Details

Journal
Weather and Forecasting
Published
2025-05-30
DOI
https://doi.org/10.1175/waf-d-24-0154.1
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System

Ricardo M. Campos, Darin Figurskey, Avichal Mehra, Joseph Sienkiewicz
Weather and Forecasting
Ocean Waves and Remote Sensing
article

Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System

Ricardo M. Campos, Darin Figurskey, Avichal Mehra, Joseph Sienkiewicz
article en

Abstract

Abstract In this paper, we propose a new capability for an oceanic hazards outlook containing delineations of where winds and waves are expected to have the potential of posing a hazard to either life or property at sea. This new product is based on NOAA’s Global Ensemble Forecast System, focused on developing a probabilistic forecast of 10-m wind speed (U10) and significant wave height (Hs) for week 2. The methodology involves defining temporal and spatial windows to postprocess the ensemble members and analyzing the tail of the probability density function generated by the pooled dataset. Specific thresholds for U10 and Hs as well as probability levels are defined in the algorithm to generate probability maps. The performance is assessed through statistical validation using NDBC buoy data and reanalysis, followed by case studies. Results indicate that the probabilistic forecast is skillful in predicting waves up to 9 m and winds up to 48 kt (1 kt ≈ 0.51 m s −1 ), particularly for extratropical systems. In addition, with weaker signals and lower probabilities forecasted, extreme extratropical events associated with hurricane-force winds could be in many cases successfully detected in the week 2 forecast. Therefore, the probability maps provide valuable guidance for practical applications, helping in decision-making for maritime operations.

Weather and ForecastingVol. 40(8)
NOAA National Centers for Environmental Prediction (US)
University of Miami, Mississippi State University, National Oceanic and Atmospheric Administration, Cooperative Institute for Marine and Atmospheric Studies, University of Miami, NOAA Weather Program Office
Openalex Percentile: Top 86%
Ocean Waves and Remote Sensing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.