Probabilistic subseasonal weather forecasts for the energy & agricultural sectors

Award Information
Agency: Department of Commerce
Branch: National Oceanic and Atmospheric Administration
Contract: WC-133R-15-CN-0066
Agency Tracking Number: 15-1-003
Amount: $94,849.06
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 8.3.1C
Solicitation Number: N/A
Timeline
Solicitation Year: 2015
Award Year: 2015
Award Start Date (Proposal Award Date): 2015-08-27
Award End Date (Contract End Date): 2016-02-27
Small Business Information
845 Spring Street NW, Unit # 129, Atlanta, GA, 30308-1043
DUNS: 625305268
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Mark Jelinek
 General Manager
 (404) 919-2673
 mjelinek@cfanclimate.com
Business Contact
 Judith Curry
Title: President
Phone: (404) 803-2012
Email: curry.judith@gmail.com
Research Institution
N/A
Abstract
The proposed research addresses Climate Adaptation and Mitigation: Probability Forecasts of Business Impact Variables from CFS2 Ensembles. Climate Forecast Applications Network (CFAN) develops innovative weather and climate forecast tools that support decision-oriented solutions for our clients. The focus of this proposal is on business-relevant subseasonal forecasts for the energy and agricultural sectors, including applications to renewable energy. Analysis of the reforecast library against observation and analyses enables predictability assessment of business-relevant variables by region, initial and target month, and enables predictability assessment and recent forecast errors to correct for model bias error to improve the shape of the ensemble distribution. A multi-model prediction system using the CFSv2 and ECMWF forecasts will be developed to exploit the advantages of each model using ensemble clustering techniques. A strategy for assessing confidence of each forecast is based on a comprehensive forecast evaluation, predictability assessment, and ensemble characteristics. A web-based dashboard system is designed to display and deliver the forecast information in a flexible manner to aid decision support integration. Commercial applications of the forecast products will be targeted at the energy and agricultural sectors in the U.S. and Asia.

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

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