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Such distortion hinders accurate estimation of weather parameters such as the reflectivity and velocity.
The difficulty is mainly attributed to the extremely significant signal interferences, which hinder accurate estimation of weather parameters.
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The interference inevitably distorts the received signals of the radars, thereby leading to inaccurate estimations of weather parameters.
Estimation of the weather influence on transmission lines is required to capture the stochastic behavior of the weather [17].
All transmission lines with the same voltage level are taken as the basic samples for the estimation of one weather area.
Considering the vast road network varied conditions of which need to be constantly monitored locally and regionally during winter weather events, RWIS stations must be placed strategically so that they can collectively provide informative inputs required for accurate estimation of the road weather and surface conditions of the whole highway network.
Estimation for weather-related failure probability of overhead transmission lines is essential in the reliability assessment of a power system.
This implies that a choice of degrees of freedom lower or higher than this optimal value will lead to over- or under-estimation of the effect of weather variables.
These results can be applied to retrospective estimation of the impact of space weather on GNSS positioning and for development of new ionospheric irregularity models.
Kurylyk and Macquarrie (2014) performed analytical solution for estimation of the ground temperature at different weather conditions.
Official statistics cannot be used for estimation of seasonal consumption since, due to weather conditions, supplies are transported when possible, i.e. mainly during the summer.
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