Bucchignani, E. A Wind Field Reconstruction from Numerical Weather Prediction Data Based on a Meteo Particle Model. Meteorology2024, 3, 70-82.
Bucchignani, E. A Wind Field Reconstruction from Numerical Weather Prediction Data Based on a Meteo Particle Model. Meteorology 2024, 3, 70-82.
Bucchignani, E. A Wind Field Reconstruction from Numerical Weather Prediction Data Based on a Meteo Particle Model. Meteorology2024, 3, 70-82.
Bucchignani, E. A Wind Field Reconstruction from Numerical Weather Prediction Data Based on a Meteo Particle Model. Meteorology 2024, 3, 70-82.
Abstract
In the present work, a methodology for wind field reconstruction based on the Meteo Particle Model (MPM) from Numerical Weather Prediction (NWP) data is presented. The development of specific wind forecast services is a challenging research topic, in particular for what concerns the availability of accurate local weather forecasts in highly populated areas. Currently, even if NWP Limited Area Models (LAMs) are run at spatial resolution of about 1 km, this level of information is not sufficient for many applications, for example to support drone operation in urban contexts. The coupling of MPM with the NWP Limited Area Model COSMO has been implemented in such a way that the MPM reads the NWP output over a selected area and provides wind values in the generical point considered for the investigation. The numerical results obtained reveal a good behavior of the method in reproducing the general trend of wind speed, as confirmed also by the power spectra analysis. The MPM is able to step over the intrinsic limitations of the NWP model in terms of spatial and temporal resolution even if the MPM inherits the bias that inevitably affects the COSMO output.
Keywords
Limited Area Models; wind field reconstruction; MPM
Subject
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
