Improving RAMS and WRF mesoscale forecasts over two distinct vegetation covers using an appropriate thermal roughness length parameterization
Abstract
Land Surface Models (LSM) have shown some difficulties to properly simulate day-time 2-m air and surface skin temperatures. This kind of models are coupled to atmospheric models in mesoscale modelling, such as the Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting (WRF) Model. This model coupling is used within Numerical Weather Prediction Systems (NWP) in order to forecast key physical processes for...
Paper Details
Title
Improving RAMS and WRF mesoscale forecasts over two distinct vegetation covers using an appropriate thermal roughness length parameterization
Published Date
Jan 1, 2020
Volume
280
Pages
107791 - 107791
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History