Response of the large‐scale structure of the atmosphere to global warming

By Geoffrey K. Vallis, P. Zurita‐Gotor, C. Cairns, J. Kidston. 2015

282 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/83eae6063cfc58562aea1eaeadf60e58f0aec11c

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

1. P. O’Gorman
2. J. Dwyer
3. M. Byrne

In Global and Planetary Change

1. P. O’Gorman
2. J. Dwyer
3. M. Byrne

Citations in the corpus

• Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events (2018, background): “The RF fails to generalize because climate warming leads to higher temperatures and an upward shift of the circulation and thermal structure [Singh and O’Gorman, 2012] including the tropopause [Vallis et al., 2015], but there are not examples in the training data from the control climate with such h”