Probabilistic subseasonal weather forecasts for the energy & agriculture sectors

Award Information
Agency: Department of Commerce
Branch: N/A
Contract: WC-133R-16-CN-0100
Agency Tracking Number: WC-133R-16-CN-0100
Amount: $399,635.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: 8.3.1
Solicitation Number: NOAA-2015-2
Timeline
Solicitation Year: 2016
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-07-18
Award End Date (Contract End Date): 2018-07-24
Small Business Information
20 Woodchuck Ct,, Reno, NV, 89519
DUNS: 625305268
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Violeta Toma
 (678) 772-3118
 vtoma@cfanclimate.com
Business Contact
 Judith Curry
Phone: (404) 803-2012
Email: curry.judith@gmail.com
Research Institution
N/A
Abstract
This proposal from Climate Forecast Applications Network addresses the challenge of providing business-relevant subseasonal forecasts for the energy and agricultural sectors, including applications to renewable energy. An innovative multi-model prediction system using the CFSv2 and ECMWF forecasts will be developed to exploit the advantages of each model. An interactive web-based dashboard system is designed to display and deliver the forecast information in a flexible and dynamic manner to aid decision support integration. A comprehensive assessment of predictability of businessrelevant variables by region, initial and target month, and atmospheric flow regimes provides the basis for assessing the confidence of individual forecasts and for identifying forecast ‘windows of opportunity’. An ensemble calibration scheme uses predictability assessment, reforecasts and recent forecast errors to correct for model bias error and to improve the shape of the ensemble distribution. Advanced ensemble interpretation techniques support scenario predictions of extreme events. A strategy for assessing confidence of each forecast is based on a comprehensive forecast evaluation, predictability assessment, and ensemble characteristics.

* Information listed above is at the time of submission. *

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