SBIR-STTR Award

Prescient Weather proposes four Phase I tasks to increase the value of the new NOAA Climate Forecast System to commercial customers. The capabilities demonstrated and explored in Phase I will be developed and integrated in Phase II as components of a new Seasonal Information and Decision Support System (SIDSS) for our World Climate Service customers. The Phase I tasks are: Improve season forecast calibration with a new climate-conserving calibration algorithm that produces relatively flat rank probability diagrams; Convert calibrated forecasts of meteorological variables into forecasts of impact and decision variables such as degree days or wind power availability’ Explore calibration of two-to-four week forecasts with conditioning on expected flow patterns; Explore the potential of model output statistics (MOS) to calibrate and improve weekly and monthly forecasts of seasonal variability. Several of the tasks will explore the use of principal component methods to project forecasts on the historical verification data and to define flow regimes for conditional calibration. The SIDSS development in Phase II will focus on the client decision context, present historical and predicted information including numerical and analog forecast, and facilitate client development of individualized forecasts. It is a key part of our commercialization strategy. SUMMARY OF

Anticipated Results:
Client-centered calibration of the new NOAA Climate Forecast System will improve the skill and reliability of the forecasts on the scale of weeks and months thus enhancing their value to a wide range of activities impacted by weather or climate. A focus on the client decision context with a Seasonal Information and Decision Support System (SIDSS) to present the calibrated forecasts will further increase their commercial value

Prescient Weather process five integrated Phase II tasks to increase the value of the NOAA Climate Forecast System and to assist the private sector in managing weather and climate risk and opportunity: The Phase II tasks are: (1) Develop an optimal WCS seasonal multi - model ensemble by calibrating and combining the NWS CFSv2, the ECMWF SFSv4, and the new National Multi - Model Ensemble (NMME) to create more skillful operational seasonal forecasts; (2) Develop an optimal WCS weekly forecast ensemble from the same models and then create an operational multi - model probability forecast; (3) Develop probability forecasts for impact variables critical in agriculture, energy, and renewable energy on the weekly, monthly, and seasonal scale; (4) Develop effective methods for combining probability forecasts, business models, and forecast performance statistics to enable users to act on the forecast with confidence in the consequences; (5) Complete and implement the Internet - based Seasonal and Subseasonal Prediction, Information, and Decision Support System (SSPIDSS) as the interactive workspace to support decision - making. The SSPIDSS implementation will focus on the client decision context, presenting a tier of probabilistic forecasts of meteorological and industry variables on the scale of seasons for long - range strategy, months and weeks for tactical adjustments, and days for immediate action. SUMMARY OF

Anticipated Results:
The Phase II accomplishments will bring notable innovation to the management of climate risk and opportunity with the aid of probability forecasts for periods of two to four weeks, months, and seasons. Operational products will (1) combine independent models into multi - models providing more skillful and reliable forecasts than are now available; (2) include probability forecasts of variables needed for business decisions in agriculture, energy, and renewable energy; (3) offer decision support based on a model of business response to climate variability that includes options for hedging and mitigating risk and incorporates the historical performance of the forecast system