Ensemble Prediction of Atmospheric Refractivity Conditions for EM PropagationSource: Journal of Applied Meteorology and Climatology:;2016:;volume( 055 ):;issue: 010::page 2113DOI: 10.1175/JAMC-D-16-0033.1Publisher: American Meteorological Society
Abstract: n ensemble forecast system has been developed at the Naval Research Laboratory to improve the analyses and forecasts of atmospheric refractivity for electromagnetic (EM) propagation with the intention of accounting for uncertainties in model forecast errors. Algorithms for a matrix of ensemble statistics have been developed to analyze the probability, location, intensity, and structure of ducting of various types. Major parameters of ducting layers and their ensemble statistics are calculated from the ensemble forecasts. Their relationships to the large-scale and mesoscale environment are also investigated. The Wallops Island field experiment from late April to early May 2000 is selected to evaluate the system. During the spring season, this coastal region maintains a strong sea surface temperature gradient between cold shelf waters and the warm Gulf Stream, where the boundaries between land, the coastal water, and the Gulf Stream have a strong influence on marine boundary layer structures and the formation of ducting layers. Sounding profiles during the field experiment are used in the study to further understand the structures of the ducting layers and also to validate the ensemble forecast system. While some advantages of the ensemble system over the deterministic forecast for atmospheric refractivity prediction in the boundary layer are studied and demonstrated in this study, the weaknesses of the current ensemble system are revealed for future improvement of the system.
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contributor author | Zhao, Qingyun | |
contributor author | Haack, Tracy | |
contributor author | McLay, Justin | |
contributor author | Reynolds, Carolyn | |
date accessioned | 2017-06-09T16:51:15Z | |
date available | 2017-06-09T16:51:15Z | |
date copyright | 2016/10/01 | |
date issued | 2016 | |
identifier issn | 1558-8424 | |
identifier other | ams-75329.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4217653 | |
description abstract | n ensemble forecast system has been developed at the Naval Research Laboratory to improve the analyses and forecasts of atmospheric refractivity for electromagnetic (EM) propagation with the intention of accounting for uncertainties in model forecast errors. Algorithms for a matrix of ensemble statistics have been developed to analyze the probability, location, intensity, and structure of ducting of various types. Major parameters of ducting layers and their ensemble statistics are calculated from the ensemble forecasts. Their relationships to the large-scale and mesoscale environment are also investigated. The Wallops Island field experiment from late April to early May 2000 is selected to evaluate the system. During the spring season, this coastal region maintains a strong sea surface temperature gradient between cold shelf waters and the warm Gulf Stream, where the boundaries between land, the coastal water, and the Gulf Stream have a strong influence on marine boundary layer structures and the formation of ducting layers. Sounding profiles during the field experiment are used in the study to further understand the structures of the ducting layers and also to validate the ensemble forecast system. While some advantages of the ensemble system over the deterministic forecast for atmospheric refractivity prediction in the boundary layer are studied and demonstrated in this study, the weaknesses of the current ensemble system are revealed for future improvement of the system. | |
publisher | American Meteorological Society | |
title | Ensemble Prediction of Atmospheric Refractivity Conditions for EM Propagation | |
type | Journal Paper | |
journal volume | 55 | |
journal issue | 10 | |
journal title | Journal of Applied Meteorology and Climatology | |
identifier doi | 10.1175/JAMC-D-16-0033.1 | |
journal fristpage | 2113 | |
journal lastpage | 2130 | |
tree | Journal of Applied Meteorology and Climatology:;2016:;volume( 055 ):;issue: 010 | |
contenttype | Fulltext |