|Paul Robert Harasti
The diagnosis, exploitation, and prediction of electro-magnetic (EM) radiation scatter and refraction in the troposphere impact the success of US Navy and Marine Corps missions that utilize tactical radars and weather radars, which both operate at wavelengths ranging from centimeters to millimeters. For tactical radar systems, the probability of detection as a function of range (including over-the-horizon) of point targets depends on the geometric scattering properties of the target, forward Bragg Scatter from turbulence-induced refractivity fluctuations, attenuation and forward Rayleigh and Mie from clouds, and mean refractivity variations of the troposphere along the EM radiation’s propagation path. Often, strong gradients in humidity and temperature inversions in the marine atmospheric boundary layer trap the EM radiation in ducts, carrying it further in range along the surface than in normal propagation conditions. Likewise, the interpretation, geolocation, and exploitation of radar echoes detected from distributed weather targets (precipitation, cloud, clear-air turbulence) depend on the same propagation conditions as well as the underlying assumptions of the scattering processes involved. NRL is engaged in both theoretical and applied research to better understand and optimally assimilate radar-derived weather and refractivity properties into its diagnostic and predictive systems utilized by the US Armed forces. Methods are sought to improve the tropospheric turbulence, boundary layer, and reflectivity-to-water parameterizations utilized by NRL's mesoscale numerical weather prediction model, which will in turn lead to improved tropospheric weather and refractivity awareness and tactical decision aids for the warfighter. Additional process studies are needed to improve our understanding of the internal cloud dynamics and microphysics through exploitation, integration, and analyses of observations obtained from a unique target tracking weather radar that is able to detect individual precipitation particles (a U.S. Navy high-powered [3MW], high resolution [0.5m], ground-based, polarimetric, Doppler radar located at Cape Canaveral, Florida), and also from a complimentary set of portable, remotely-accessed, advanced surface instrumentation for obtaining vertical profilers of clouds and environmental conditions, and in situ cloud measurements obtained by advanced research jet aircraft.
Harasti, PR et al: "Real-time implementation of single-Doppler radar analysis methods for tropical cyclones: Algorithm improvements and use with WSR-88D display data". Weather and Forecasting 19 (4): 219-239, 2004.
Harasti, PR, List, R: "Principal component analysis of Doppler radar data. Part I: Geometric connections between eigenvectors and the core region of atmospheric vortices". Journal of the Atmospheric Sciences 62 (11): 4027–4042, 2005.
Harasti, PR: "An expanded VVP technique to resolve primary and environmental circulations in hurricanes". Journal of Atmospheric and Oceanic Technology 31 (2): 249-271, 2014.
Karimian A, et al: "Toward the Assimilation of the Atmospheric Surface Layer Using Numerical Weather Prediction and Radar Clutter Observations". Journal of Applied Meteorology and Climatology 52 (10): 2345-2355, 2013.
Schmidt JM, et al: "Radar observations of individual rain drops in the free atmosphere". Proceedings of the National Academies of Sciences of the USA 109: 9293-9298, 2012.
Schmidt, JM et al: "Evidence for a nimbostratus uncinus in a convectively generated mixed-phase stratiform cloud shield". Journal of the Atmospheric Sciences 74 (12): 4093-4116, 2017.
Schmidt, JM et al: "Radar detection of individual raindrops". Bulletin of the American Meteorological Society 100 (12): 2433-2450, 2019.
Thompson WT, Haack T: "An investigation of sea surface temperature influence on microwave refractivity: The wallops 2000 experiment". Journal of Applied Meteorology and Climatology 50(11): 2319-2337, 2011.
Zhao, Q et al: "Using radar wind observations to improve mesoscale numerical weather prediction". Weather and Forecasting 21 (8): 502-522, 2006.
Zhao, Q et al: "Improving short-term storm prediction by assimilating both radar radial-wind and reflectivity observations". Weather and Forecasting 23 (6): 373-391, 2008.
Atmospheric refractivity; EM Scattering from clear air and hydrometeors; Radio frequency propagation; Numerical weather prediction; EM propagation modeling; Microwave and mm- wave radar applications; Reflectivity-hydrometeor parameterizations; NWP physics parameterizations; Refractivity retrievals from observations;