Nowcasting cloud fields for U.S. Air Force special operations
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Authors
Zoufaly, Sean L.
Subjects
operational nowcasting
low cloud forecasting
cloud reflectance
ISR
Bayesian estimation
statistical post-processing
machine learning
low cloud forecasting
cloud reflectance
ISR
Bayesian estimation
statistical post-processing
machine learning
Advisors
Nuss, Wendell A.
Date of Issue
2017-03
Date
Mar-17
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
Nowcasting is a trending subset of numerical weather prediction that aims to produce a highly accurate analysis of current conditions along with a short-term forecast. One of the greatest challenges to a nowcast system operating in data-sparse regions is that of accurately forecasting clouds. Clouds significantly impact a variety of operations, particularly intelligence, surveillance and reconnaissance. A prototype nowcast system is developed and tested on a case of summertime stratus clouds over the Monterey Bay in California. This system ingests high-resolution geostationary satellite data and mesoscale model fields to produce gridded 06-h forecasts of cloud reflectance and probability of cloud. A statistical post-processing technique is applied using Bayesian estimation to train the system from a set of past predictor variables and observed imagery. This approach demonstrates skill over a climatology-based approach and shows an ability to accurately forecast non-typical cloud patterns. It proves to be very computationally feasible for nowcasting. This study lays down the initial framework for a highly accurate nowcast system that can operate anywhere in the world to enable mission success while reducing costs.
Type
Thesis
Description
Series/Report No
Department
Meteorology
Organization
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NPS Report Number
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Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.