Toward Better Intraseasonal and Seasonal Prediction: Verification and Evaluation of the NOGAPS Model Forecasts
Abstract
Intraseasonal and seasonal prediction provides important information for decision-making and resource management, and has received increased attention in recent years. Despite substantial progresses in numerical modeling in the past few decades, skillful seasonal prediction remains a challenge for many models. Verification and evaluation of model forecasts can offer users necessary information on the model prediction skills and uncertainties, and provide model development teams with useful information on model improvements.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2013
- Accession Number
- ADA597661
Entities
People
- Melinda S. Peng
- Zhuo Wang
Organizations
- University of Illinois Urbana–Champaign