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    Progress and Developments of Downburst Prediction Applications of GOES 

    Source: Weather and Forecasting:;2015:;volume( 030 ):;issue: 005:;page 1182
    Author(s): Pryor, Kenneth L.
    Publisher: American Meteorological Society
    Abstract: he National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR) has developed and evaluated a suite of products that assess convective storm?generated ...
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    Virtual Fixture Generation for Task Planning With Complex Geometries 

    Source: Journal of Computing and Information Science in Engineering:;2021:;volume( 021 ):;issue: 006:;page 061001-1
    Author(s): Sharp, Andrew; Pryor, Mitch
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Many robotic processes require the system to maintain a tool’s orientation and distance from a surface. To do so, researchers often use virtual fixtures (VFs) to either guide the robot along a path or forbid it from leaving ...
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    Multiparameter Real-World System Identification Using Iterative Residual Tuning 

    Source: Journal of Mechanisms and Robotics:;2021:;volume( 013 ):;issue: 003:;page 031021-1
    Author(s): Allevato, Adam; Pryor, Mitch; Thomaz, Andrea L.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this work, we consider the problem of nonlinear system identification using data to learn multiple and often coupled parameters that allow a simulator to more accurately model a physical system or mechanism and close ...
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    Do Machine Learning Approaches Offer Skill Improvement for Short-Term Forecasting of Wind Gust Occurrence and Magnitude? 

    Source: Weather and Forecasting:;2022:;volume( 037 ):;issue: 005:;page 525
    Author(s): Jacob Coburn; Sara C. Pryor
    Publisher: American Meteorological Society
    Abstract: Wind gusts, and in particular intense gusts, are societally relevant but extremely challenging to forecast. This study systematically assesses the skill enhancement that can be achieved using artificial neural networks ...
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    Projecting Future Energy Production from Operating Wind Farms in North America. Part II: Statistical Downscaling 

    Source: Journal of Applied Meteorology and Climatology:;2023:;volume( 062 ):;issue: 001
    Author(s): Coburn, Jacob; Pryor, Sara C.
    Publisher: American Meteorological Society
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    Projecting Future Energy Production from Operating Wind Farms in North America. Part III: Variability 

    Source: Journal of Applied Meteorology and Climatology:;2023:;volume( 062 ):;issue: 011:;page 1523
    Author(s): Coburn, Jacob; Pryor, Sara C.
    Publisher: American Meteorological Society
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    Projecting Future Energy Production from Operating Wind Farms in North America. Part II: Statistical Downscaling 

    Source: Journal of Applied Meteorology and Climatology:;2023:;volume( 062 ):;issue: 001:;page 81
    Author(s): Coburn, Jacob; Pryor, Sara C.
    Publisher: American Meteorological Society
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    Differential Credibility of Climate Modes in CMIP6 

    Source: Journal of Climate:;2021:;volume( 034 ):;issue: 020:;page 8145
    Author(s): Coburn, Jacob;Pryor, S. C.
    Publisher: American Meteorological Society
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    Evolution of the Internal Climate Modes under Future Warming 

    Source: Journal of Climate:;2022:;volume( 036 ):;issue: 002:;page 511
    Author(s): Jacob Coburn; Sara C. Pryor
    Publisher: American Meteorological Society
    Abstract: Climate modes play an important role in weather and climate variability over multiple spatial and temporal scales. This research assesses Earth system model (ESM) projections of the spatiotemporal characteristics of key ...
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    On the Proper Order of Markov Chain Model for Daily Precipitation Occurrence in the Contiguous United States 

    Source: Journal of Applied Meteorology and Climatology:;2008:;volume( 047 ):;issue: 009:;page 2477
    Author(s): Schoof, J. T.; Pryor, S. C.
    Publisher: American Meteorological Society
    Abstract: Markov chains are widely used tools for modeling daily precipitation occurrence. Given the assumption that the Markov chain model is the right model for daily precipitation occurrence, the choice of Markov model order was ...
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