Marty J. Bell, Director of Research and Modeling, WeatherFlow, Inc. email@example.com, (970) 818-7635, Corresponding author Forrest J. Masters, Associate Professor of Civil and Coastal Engineering, University of Florida, firstname.lastname@example.org, (352) 294-7792 Jeff H. Copeland, Chief Scientist, WeatherFlow, Inc. email@example.com, (970) 818-7637 Bill P. Thorson, Modeling Specialist, WeatherFlow, Inc. firstname.lastname@example.org, (970) 818-7636 Tony H. McGee, Research Scientist, WeatherFlow, Inc. email@example.com, (757) 868-0888
Submission to the
Sixth Conference on Transition of Research to Operations 2016 AMS Meeting
Despite more than a half century of advancements in boundary layer research and anemometric technology, surface wind speed data collected by ASOS, AWOS and other mesonet systems are widely used without any correction for variations in site conditions and hardware configurations. The consequence of overlooking the effects of observation height, upwind fetch (terrain and topography), instrument response characteristics, and data acquisition methods can be significant. For example, the literature has shown that ‘raw' gust measurements measured at airports can underpredict equivalent values for true open exposure conditions by as much as 40% (Powell et al., 1996; Masters et al., 2010). The implications reach far beyond operational forecasting of severe weather for public safety. Siting of wind energy resources, calculation of wind loading in building codes and engineering standards, and rate-setting for property and casualty insurance are just a few examples of day-to-day activities that apply wind speed conversion techniques to convert in situ observations to a standard metadata format (e.g., ASCE 7 basic wind speed, Saffir Simpson Hurricane Wind Scale).
This paper describes the efforts of a novel public-private partnership to improve weather informatics, specifically as it relates to monitoring and predicting surface weather conditions in terrestrial and near-shore environment during landfall of Atlantic tropical cyclones. The Florida Coastal Monitoring Program (FCMP) and WeatherFlow Inc. are teaming to relay standardize surface wind speed measurements in real-time to support numerical weather prediction and hind-casting of surface wind fields. Thematically, these efforts are grounded in the observing and modeling & prediction thrusts of the conference's human-centered “domains of action.”
The FCMP is a joint university consortium that deploys adaptive mesonets in the path of land-falling Atlantic Tropical Cyclones to conduct wind engineering and boundary layer research (Balderrama et al., 2011). The current focus of the program is to collect high-fidelity wind speed measurements in suburban and urban terrain to better characterize turbulence conditions in the built environment. WeatherFlow owns and operates the second largest private mesonet in the CONUS, including a network of 400+ coastal stations, ~100 of which are designed to withstand extreme wind loading. Data are ingested into its StormPrint model, an application of the WRF-ARW numerical weather prediction model and the Gridpoint Statistical Interpolation (GSI) data assimilation tools to produce fine-mesoscale surface wind fields. Raw data are processed in real-time using the objective estimation technique described in Masters et al. (2010). Directional roughness lengths are estimated from several years of historical records from permanent weather stations (i.e. gusts and mean wind speed reports) and high-resolution time series data from the adaptive mesonets. Data are then converted to a prescribed metadata format (i.e., height, terrain, and short duration average) accounting for the mechanical response characteristics of cup and propeller anemometers and the sampling and block averaging method of the data acquisition hardware. This approach is fully automated and can be applied to a wide range of surface weather station types located in a large region. Developing standardized, composite datasets is straightforward, requires minimal computational expense, and can easily adapt to the metadata requirements of different user groups.
This paper will explore the value of its tool in operational forecasting, emergency management, and meteorological and wind engineering research. The common data collection procedures applied in adaptive and fixed weather station networks will be reviewed, followed by a detailed discussion about the operational logistics for deployment and analysis. Case studies from recent hurricanes will be presented to demonstrate the efficacy of this approach to produce accurate representations of the surface wind field. Finally, we will explore the state of observing technology in a practical context and describe a path forward to unify research and operations across multiple fields.
Balderrama, J.A., F.J. Masters, K.R. Gurley, D.O. Prevatt, L.D. Aponte-Bermudez, T.A. Reinhold, J.-P. Pinelli, C.S. Subramanian, S.D. Schiff, and A.G. Chowdhury, 2011: The Florida Coastal Monitoring Program (FCMP): A review. Journal of Wind Engineering and Industrial Aerodynamics, 99(9), 979-995.
Masters, F.J., P.J. Vickery, P. Bacon, and E.N. Rappaport, 2010: Toward objective, standardized intensity estimates from surface wind speed observations. Bulletin of the American Meteorological Society, 91, 1665-1682.
Powell, M. D., S. Houston, and T. A. Reinhold, 1996: Hurricane Andrew's landfall in South Florida. Part I: Standardizing measurements for documen- tation of surface wind fields. Wea. Forecasting, 11, 304–328.