Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics
By Ming Zhao, J. Golaz, I. Held, V. Ramaswamy, Shian‐Jiann Lin, Yi Ming, Paul Ginoux, B. Wyman, Leo Donner, D. Paynter and 1 more. 2016
141 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/be6ff4b1a5fbb73215e84f60ab16cbe55e2ae0a6
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
- Tapio Schneider
- L. Harris
- Robert Hallberg
- S. Griffies
- Shian‐Jiann Lin
- I. Held
- Andrew T. Wittenberg
- V. Ramaswamy
In Global and Planetary Change
- Tapio Schneider
- Shian‐Jiann Lin
- L. Harris
- S. Griffies
- Robert Hallberg
- Alistair Adcroft
- P. Phillipps
- Yi Ming
Citations in the corpus
- Cloud feedback mechanisms and their representation in global climate models (2017, unknown): “As discussed in this review, microphysical processes constitute a major source of uncertainty in future cloud responses, particularly with regard to mixed-phase cloud-radiative properties(19) and precipitation efficiency in convective clouds.(107) The treatment of cloud–aerosol interactions also rem”
- Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations (2017, background): “…sizes in a cloud, the fraction of cloud condensate that precipitates out, and the phase partitioning of cloud condensate into liquid and ice [e.g., Stainforth et al., 2005; Jiang et al., 2012; Suzuki et al., 2013; Golaz et al., 2013; Bodas-Salcedo et al., 2014; Zhao et al., 2016; Kay et al., 2016].”
- The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs (2018, background): “Most of the difference is due to different cloud feedbacks, which can be traced to the models’ representation of convective clouds (Zhao, 2014; Zhao et al., 2016).”
- The GFDL Earth System Model Version 4.1 (GFDL‐ESM 4.1): Overall Coupled Model Description and Simulation Characteristics (2020, background): “, 2011) and the focus of considerable subsequent work to understand and improve (Golaz et al., 2013; Zhao et al., 2016).”
- The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 2. Model Description, Sensitivity Studies, and Tuning Strategies (2018, background): “, 2016], especially the representation of convective precipitation microphysics and cumulus mixing, which together determine the bulk convective precipitation efficiency [Zhao, 2014; Zhao et al., 2016].”