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Statistical Parameterization of Heterogeneous Oceanic Convection
Journal of Physical Oceanography, 2007Abstract A statistical convective adjustment scheme is proposed that attempts to account for the effects of mesoscale and submesoscale variability of temperature and salinity typically observed in the oceanic convective regions. Temperature and salinity in each model grid box are defined in terms of their mean, variance, and mutual ...
PASQUERO, CLAUDIA, Tziperman, E.
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The Physics and Parameterization of Moist Atmospheric Convection
1997Preface R.K. Smith. A: Moist Convection. 1. Overview of Atmospheric Convection K.A. Emanuel. 2. Thermodynamics of Moist and Cloudy Air R.K. Smith. 3. The Mesoscale Organization of Deep Convection J.-L. Redelsperger. 4. Trade Cumulus: Observations and Modelling A.K. Betts. 5. Convection in Stratocumulus-Topped Atmospheric Boundary Layers C.S. Bretherton.
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Using Deep Learning for Convection Parameterization
Data-driven approaches using machine learning to parameterizing model physical processes in Earth System Models have been actively explored in recent years. Deep-learning-based convection parameterization is one such example. While significant progress has been made in emulating convection using neural networks (NN), serious roadblocks remain ...Guang Zhang, Yilun Han, Yong Wang
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The Kain–Fritsch Convective Parameterization: An Update
Journal of Applied Meteorology, 2004Numerous modifications to the Kain‐Fritsch convective parameterization have been implemented over the last decade. These modifications are described, and the motivating factors for the changes are discussed. Most changes were inspired by feedback from users of the scheme (primarily numerical modelers) and interpreters of the model output (mainly ...
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Parameterization of Atmospheric Convection
2014Robert S Plant, Jun-Ichi Yano
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Improved Convective Ice Microphysics Parameterization in the NCAR CAM Model
Journal of Geophysical Research D: Atmospheres, 2021Lin Lin, Qiang Fu, Xiaohong Liu
exaly

