Sensitivity of Local Numerical Weather Prediction Models
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".
Deadline for manuscript submissions: closed (6 February 2024) | Viewed by 453
Special Issue Editor
Special Issue Information
Dear Colleagues,
The operation of Local Numerical Weather Prediction (NWP) Models has become a widespread activity regarding the support of weather forecasting. This endeavor is carried out using a broad spectrum of sources ranging from International Organizations and Regional Meteorological Services to Academic Institutes and Companies, even to the enthusiastic aspirant in the area of meteorology with modest computing resources available. However, in addition to the complexities of installing NWP Models to the many different computer architectures as well as data assimilation issues, such an undertaking is quite challenging regarding the proper choice of the many internal parameter values for the NWP Models to have the optimum performance. A significant step towards this direction is to estimate the sensitivity of the various NWP Models in reference to a variety of parameters related to its many physical constituents (e.g., turbulence, convection, land‒sea properties, grid-scale microphysics, or cloud cover) on a comparative basis. The Special Issue invites contributions that gauge the sensitivity of Local NWP Models for the community of atmospheric sciences to obtain important and operationally useful insights on which parameters display the greatest effect over a variety of domains and weather situations. It is expected that these works will provide a significant resource over a wide framework of relevant methodologies. Additionally, it will motivate and guide researchers, developers, and end users in general to improve the model performance either heuristically or systematically by adopting the available optimization techniques.
Dr. Euripides N. Avgoustoglou
Guest Editor
Manuscript Submission Information
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Keywords
- computer simulation
- model parameters
- sensitivity
- optimization
- numerical schemes
- resolution
- convection
- extreme weather events
