Calibration of Ensemble Forecasts Using Reforecast Datasets

Award Information
Agency:
Department of Defense
Branch
Defense Threat Reduction Agency
Amount:
$749,905.00
Award Year:
2007
Program:
SBIR
Phase:
Phase II
Contract:
HDTRA1-07-C-0122
Award Id:
79006
Agency Tracking Number:
RDI060003360
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
P O Box 3029, Norman, OK, 73070
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
133622717
Principal Investigator:
Fanyou Kong
Sr. Research Scientist
(405) 325-0056
fanyou.kong@atscwx.com
Business Contact:
Vicki Rose
Managing Business Directo
(405) 325-0056
vicki.rose@atscwx.com
Research Institute:
n/a
Abstract
Fine-scale, well-calibrated probabilistic weather forecasts are increasingly in demand for such weather-critical applications as battlespace management, and accurate prediction of high-value airborne operations. Built upon the Phase I effort we have just completed, the principal objective of this proposed study (Phase II) is to develop a reliable, efficient, and easily deployable reforecast-calibration system prototype based on fine-scale ensemble reforecast datasets and use it to produce well-calibrated, fine-scale probabilistic weather forecast products. This study consists of three major components. The first component is to produce a basic 20-year fine-scale ensemble reforecast dataset over the CONUS domain using the WRF-ARW modeling system. The second component is to further develop and examine various MOS-based statistical models that apply to more variables and multiple classes and to refine the Phase I KNN calibration techniques, using the large reforecast sample base, and to compare the two techniques. The third component is to conduct sensitivity experiments to study data-sparse impact and the trade-offs between ensemble size and reforecast length, in order to assess the feasibility and effectiveness of the deployable reforecast-calibration system.

* information listed above is at the time of submission.

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