Mechanisms of convective cloud organization by cold pools over tropical warm ocean during the AMIE/DYNAMO field campaign

This paper investigates the mechanisms of convective cloud organization by precipitation-driven cold pools over the warm tropical Indian Ocean during the 2011 Atmospheric Radiation Measurement (ARM) Madden-Julian Oscillation (MJO) Investigation Experiment / Dynamics of the MJO (AMIE/DYNAMO) field campaign. A high-resolution regional model simulation is performed using the Weather Research and Forecasting model during the transition from suppressed to active phases of the November 2011 MJO. The simulated cold pool lifetimes, spatial extent and thermodynamic properties agree well with the radar and ship-borne observations from the field campaign. The thermodynamic and dynamic structures of the outflow boundaries of isolated and intersecting cold pools in the simulation and the associated secondary cloud populations are examined. Intersecting cold pools last more than twice as long, are twice as large, 41% more intense (measured by buoyancy), and 62% deeper than isolated cold pools. Consequently, intersecting cold pools trigger 73% more convective clouds than isolated ones. This is possibly due to stronger outflows that enhance secondary updraft velocities by up to 45%. However, cold pool-triggered convective clouds grow into deep convection not because of the stronger secondary updrafts at cloud base, but rather due to closer spacing (aggregation) between clouds and larger cloud clusters more » that formed along the cold pool boundaries when they intersect. The close spacing of large clouds moistens the local environment and reduces entrainment drying, allowing the clouds to further develop into deep convection. Implications to the design of future convective parameterization with cold pool-modulated entrainment rates are discussed. « less

[1]  Hailong Wang,et al.  Modeling Mesoscale Cellular Structures and Drizzle in Marine Stratocumulus. Part I: Impact of Drizzle on the Formation and Evolution of Open Cells , 2009 .

[2]  E. F. Bradley,et al.  Bulk Parameterization of Air–Sea Fluxes: Updates and Verification for the COARE Algorithm , 2003 .

[3]  Christopher S. Bretherton,et al.  A Mass-Flux Scheme View of a High-Resolution Simulation of a Transition from Shallow to Deep Cumulus Convection , 2006 .

[4]  James W. Wilson,et al.  Initiation of Convective Storms at Radar-Observed Boundary-Layer Convergence Lines , 1986 .

[5]  K. Droegemeier,et al.  Three-Dimensional Numerical Modeling of Convection Produced by Interacting Thunderstorm Outflows. Part I: Control Simulation and Low-Level Moisture Variations , 1985 .

[6]  P. Zuidema,et al.  Simulated Convective Invigoration Processes at Trade Wind Cumulus Cold Pool Boundaries , 2014 .

[7]  James W. Wilson,et al.  Convective Storm Initiation in a Moist Tropical Environment , 2008 .

[8]  A. P. Siebesma,et al.  Influence of the subcloud layer on the development of a deep convective ensemble , 2012 .

[9]  R. Houze,et al.  Cloud organization and growth during the transition from suppressed to active MJO conditions , 2015 .

[10]  F. Chéruy,et al.  A Density Current Parameterization Coupled with Emanuel’s Convection Scheme. Part II: 1D Simulations , 2010 .

[11]  David A. Randall,et al.  High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land , 2006 .

[12]  Edward J. Zipser,et al.  Mesoscale and convective-scale downdrafts as distinct components of squall-line structure , 1977 .

[13]  G. Thompson,et al.  Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization , 2008 .

[14]  Zaviša I. Janić Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso model , 2001 .

[15]  Catherine RioJean-Yves Control of deep convection by sub-cloud lifting processes: the ALP closure in the LMDZ5B general circulation model , 2012 .

[16]  Shepard A. Clough,et al.  Impact of an improved longwave radiation model, RRTM, on the energy budget and thermodynamic properties of the NCAR community climate model, CCM3 , 2000 .

[17]  Y. Hong,et al.  Precipitation Estimation from Remotely Sensed Imagery Using an Artificial Neural Network Cloud Classification System , 2004 .

[18]  Martin Köhler,et al.  Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time‐scales , 2008 .

[19]  Environment and the Lifetime of Tropical Deep Convection in a Cloud-Permitting Regional Model Simulation , 2013 .

[20]  Parameterization of Wind Gustiness for the Computation of Ocean Surface Fluxes at Different Spatial Scales , 2002 .

[21]  Frédéric Hourdin,et al.  Shifting the diurnal cycle of parameterized deep convection over land , 2009 .

[22]  G. Thompson,et al.  Evaluation of convection‐permitting model simulations of cloud populations associated with the Madden‐Julian Oscillation using data collected during the AMIE/DYNAMO field campaign , 2014 .

[23]  R. Houze,et al.  The cloud population and onset of the Madden‐Julian Oscillation over the Indian Ocean during DYNAMO‐AMIE , 2013 .

[24]  F. Guichard,et al.  A Parameterization of Mesoscale Enhancement of Surface Fluxes for Large-Scale Models , 2000 .

[25]  Jean-François Geleyn,et al.  An Approach for Convective Parameterization with Memory: Separating Microphysics and Transport in Grid-Scale Equations , 2007 .

[26]  Yonghua Chen,et al.  CORRIGENDUM of the MJO Transition from Shallow to Deep Convection in Cloudsat-Calipso Data and GISS GCM Simulations , 2012 .

[27]  S. McFarlane,et al.  Constructing a Merged Cloud–Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll , 2014 .

[28]  S. Bony,et al.  LMDZ5B: the atmospheric component of the IPSL climate model with revisited parameterizations for clouds and convection , 2013, Climate Dynamics.

[29]  Charles N. Long,et al.  Tracking Pulses of the Madden–Julian Oscillation , 2013 .

[30]  D. Randall,et al.  Large‐Eddy Simulation of Maritime Deep Tropical Convection , 2009 .

[31]  Charles Cohen,et al.  A Quantitative Investigation of Entrainment and Detrainment in Numerically Simulated Cumulonimbus Clouds , 2000 .

[32]  Steven K. Krueger,et al.  Numerical simulation of tropical cumulus clouds and their interaction with the subcloud layer , 1988 .

[33]  H. Niino,et al.  A Statistical Analysis of Surface Turbulent Heat Flux Enhancements Due to Precipitating Clouds Observed in the Tropical Western Pacific , 2008 .

[34]  Edward R. Dougherty,et al.  An introduction to morphological image processing , 1992 .

[35]  R. Rotunno,et al.  A Theory for Strong, Long-Lived Squall Lines , 1988 .

[36]  Masahiro Sugiyama,et al.  A Cumulus Parameterization with State-Dependent Entrainment Rate. Part I: Description and Sensitivity to Temperature and Humidity Profiles , 2010 .

[37]  William I. Gustafson,et al.  Impact of resolution on simulation of closed mesoscale cellular convection identified by dynamically guided watershed segmentation , 2014 .

[38]  J. Dudhia Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Model , 1989 .

[39]  Sungsu Park,et al.  A Unified Convection Scheme (UNICON). Part I: Formulation , 2014 .

[40]  A. Arakawa,et al.  The Macroscopic Entrainment Processes of Simulated Cumulus Ensemble. Part I: Entrainment Sources , 1997 .

[41]  R. Wood,et al.  Aircraft observations of cold pools under marine stratocumulus , 2013 .

[42]  James F. W. Purdom,et al.  Some Uses of High-Resolution GOES Imagery in the Mesoscale Forecasting of Convection and Its Behavior , 1976 .

[43]  C. Hohenegger,et al.  The Formation of Wider and Deeper Clouds as a Result of Cold-Pool Dynamics , 2014 .

[44]  R. Houze,et al.  Evolution of the Population of Precipitating Convective Systems over the Equatorial Indian Ocean in Active Phases of the Madden–Julian Oscillation , 2013 .

[45]  Ann M. Fridlind,et al.  Control of deep convection by sub-cloud lifting processes: the ALP closure in the LMDZ5B general circulation model , 2013, Climate Dynamics.

[46]  S. McFarlane,et al.  Life Cycle of Midlatitude Deep Convective Systems in a Lagrangian Framework , 2012 .

[47]  G. Young,et al.  A Convective Wake Parameterization Scheme for Use in General Circulation Models , 1998 .

[48]  Jean-Philippe Lafore,et al.  A Density Current Parameterization Coupled with Emanuel’s Convection Scheme. Part I: The Models , 2010 .

[49]  B. Albrecht,et al.  On Trade Wind Cumulus Cold Pools , 2012 .

[50]  Adrian M. Tompkins,et al.  Organization of Tropical Convection in Low Vertical Wind Shears: The Role of Cold Pools , 2001 .

[51]  R. Rauber,et al.  A Revised Conceptual Model of the Tropical Marine Boundary Layer. Part II: Detecting Relative Humidity Layers Using Bragg Scattering from S-Band Radar , 2013 .

[52]  Angela K. Rowe,et al.  Microphysical characteristics of MJO convection over the Indian Ocean during DYNAMO , 2014 .

[53]  K. Landu,et al.  Advection, moistening, and shallow‐to‐deep convection transitions during the initiation and propagation of Madden‐Julian Oscillation , 2014 .

[54]  G. Bryan,et al.  Observations of a Squall Line and Its Near Environment Using High-Frequency Rawinsonde Launches during VORTEX2 , 2010 .

[55]  Richard H. Johnson,et al.  Structure and Properties of Madden–Julian Oscillations Deduced from DYNAMO Sounding Arrays , 2013 .

[56]  Shepard A. Clough,et al.  Thin Liquid Water Clouds: Their Importance and Our Challenge , 2007 .