High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land
By M. Khairoutdinov, David A. Randall. 2006
349 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/33219e70f7275463bc51c2cc33f3498b724e66c7
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
- C. Hohenegger
- Anton Beljaars
- David A. Randall
- Z. Kuang
- A. D. Del Genio
- Bjorn Stevens
- L. Schlemmer
- A. P. Siebesma
In Global and Planetary Change
- C. Hohenegger
- David A. Randall
- Z. Kuang
- Anton Beljaars
- Bjorn Stevens
- L. Schlemmer
- A. D. Del Genio
- Daehyun Kim
Citations in the corpus
- Could Machine Learning Break the Convection Parameterization Deadlock? (2018, background): “For instance, the transition between shallow and deep convection can be correctly captured at convective permitting scale [ Khairoutdinov and Randall , 2006; Khairoutdinov et al. , 2009].”
- On the Growth of Layers of Nonprecipitating Cumulus Convection (2007, background): “The modulating effect of cloud-layer depth on precipitation may be important to the diurnal cycle of convection over land (Khairoutdinov and Randall 2006) as well as aerosol effects on clouds (Albrecht 1989).”
- Entrainment and detrainment in cumulus convection: an overview (2013, positive): “…in ε have been noticed by DelGenio and Wu (2010) for TWP-ICE (Tropical Warm Pool International Cloud Experiment), Kuang and Bretherton (2006) for an idealised oceanic transition case, and Khairoutdinov and Randall (2006) for the LBA (Large-scale Biosphere–Atmosphere) experiment over Amazonia.”
- Representing Equilibrium and Nonequilibrium Convection in Large-Scale Models (2014, methodology): “Despite employing a similar basic convective framework, the models can produce substantially different large-scale tropical wave spectra and intraseasonal variability such as the Madden–Julian oscillation (Lin et al. 2006; Kim et al. 2011; Blackburn et al. 2013; Benedict et al. 2013).”
- Convection‐permitting models: a step‐change in rainfall forecasting (2016, background): “CPMs are able to reproduce the positive feedback between precipitation formation and the development of deep convection via the formation of cold pools from evaporation of precipitation (Khairoutdinov and Randall, 2006), although the timescales on which this occurs may not be perfectly simulated bec”
- The Formation of Wider and Deeper Clouds as a Result of Cold-Pool Dynamics (2014, methodology): “One frequently discussed mechanism is an increase of the cloud diameter (Kuang and Bretherton 2006; Khairoutdinov and Randall 2006).”
- Parameterizing Convective Organization to Escape the Entrainment Dilemma (2011, background): “This time scale choice is based loosely on visual impressions, time lapse movies, and model realizations such as Khairoutdinov and Randall (2006) of the diurnal organization and development process over land.”
- CORRIGENDUM of the MJO Transition from Shallow to Deep Convection in Cloudsat-Calipso Data and GISS GCM Simulations (2012, background): “…indicate instead that mesoscale convergence at the gust front formed by the spreading of downdraft-generated boundary layer cold pools is associated with the weaker entrainment characteristic of deep convection (Kuang and Bretherton 2006; Khairoutdinov and Randall 2006; Del Genio and Wu 2010).”
- Mechanisms of convective cloud organization by cold pools over tropical warm ocean during the AMIE/DYNAMO field campaign (2015, methodology): “The center of a cold pool is characterized by colder and drier air that has significantly lower moist static energy than the edge (Figure 4d), consistent with previous studies [B€ oing et al., 2012; Khairoutdinov and Randall, 2006; Tompkins, 2001].”
- Tropospheric water vapor, convection, and climate (2010, background): “One problem may be that shallow, narrow convection entrains much more than deep convection, resulting in an inability of the shallow systems to evolve into deep convective systems, and that assumed entrainment rates do not reflect this [Grabowski et al., 2006; Khairoutdinov and Randall, 2006].”
- Influence of the subcloud layer on the development of a deep convective ensemble (2012, methodology): “Forced uplift at the outflow boundary (the edge of a cold pool), where a gust front occurs, can act as a catalyst for deep convection (Krueger 1988; Khairoutdinov and Randall 2006).”
- Shifting the diurnal cycle of parameterized deep convection over land (2009, background): “…introduced here allow to account for the role played on deep convection development by cloud base layer [Chaboureau et al., 2004] or tropospheric [Derbyshire et al., 2004] humidity, by the size of thermals at cloud base [Kuang and Bretherton, 2006], and by wakes [Khairoutdinov and Randall, 2006].”
- The Role of Entrainment in the Diurnal Cycle of Continental Convection (2010, background): “More recently, Khairoutdinov and Randall (2006) found that, in a highresolution 3D simulation, undilute plumes were completely absent.”
- Mechanisms for convection triggering by cold pools (2015, background): “In recent years, different authors have suggested that the subcloud layer is a crucial component in the rapid transition from shallow to deep convection [Tompkins, 2001; Chaboureau et al., 2004; Khairoutdinov and Randall, 2006; Kuang and Bretherton, 2006; Zhang and Klein, 2010; Böing et al., 2012].”
- Large‐Eddy Simulation of Maritime Deep Tropical Convection (2009, methodology): “This study supports previous findings that cold pools play a very important role in organizing deep convection on the mesoscale and in triggering new deep convective cells (Tompkins 2001; Kuang and Bretherton 2006; Khairoutdinov and Randall 2006).”