Subseasonal Climate Forecasts: Unparalleled InsightThe World Climate Service produces subseasonal climate forecasts from 2 to 6 weeks in advance and provides the tools needed to understand and create these challenging predictions.
Commodity trading desk meteorologists using World Climate Service gain multiple benefits. They include:
1) Stay informed with efficient, intuitive access to market-moving multi-model forecasts for weeks 2-6 World Climate Service customers have access to a powerful and intuitive map interface for viewing subseasonal forecast maps from multiple dynamical models, including zoom and forecast progression functionality. CFSv2 forecasts to week 6 are updated daily, and a proprietary multi-model blend is available.
2) Understand forecast confidence and risk with calibrated probability forecasts World Climate Service probability forecasts are rigorously calibrated using a long history of model reforecasts and observations, and comprehensive information about model skill is provided. Probability and skill information allows users to understand and track model performance, manage risk appropriately, and develop valuable decision systems.
3) Monitor and understand impacts of critical subseasonal climate drivers
The World Climate Service provides tools to monitor, understand, and anticipate the key phenomena that affect subseasonal climate fluctuations.
Overview - World Climate ServiceThe World Climate Service is a web-based information service providing:
- Subseasonal Climate Forecasts - Forecasts of climate and weather conditions from 2 weeks to 6 weeks in advance
- Seasonal Climate Forecasts - Forecasts of climate conditions from 1 month to 6 months in advance
- Taking advantage of both dynamical and statistical prediction capabilities
- Emphasizing probabilistic information and quantitative forecast confidence for decision-making
- Creating optimal blends of the information used for prediction
- Providing transparency through on-demand forecast verification and skill statistics
- Predicting and explaining the phenomena and known influences driving the forecast