A Unified Representation of Deep Moist Convection in Numerical Modeling of the Atmosphere. Part II
By Chien‐Ming Wu, A. Arakawa. 2013
141 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/da3589c8581e21f62da9ef066614e5a703165229
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
- Lukas Hubert Leufen
- Clara Betancourt
- Amirpasha Mozaffari
- Michael Langguth
- Bing Gong
- Martin G. Schultz
- Scarlet Stadtler
- Felix Kleinert
In Global and Planetary Change
- Lukas Hubert Leufen
- Clara Betancourt
- Amirpasha Mozaffari
- Michael Langguth
- Bing Gong
- Martin G. Schultz
- Scarlet Stadtler
- Felix Kleinert
Citations in the corpus
- Can deep learning beat numerical weather prediction? (2021, background): “…fully mass or energy conserving, and parameterization schemes, which are needed to incorporate the effects of unresolved sub-grid scale processes on the grid-scale variables, may lead to spurious competition between grid-scale and sub-grid-scale processes, for example in cloud schemes [132,133].”