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O rganized Convection Parameterization for GCMs. `. Mitchell W. Moncrieff Climate & Global Dynamics Laboratory National Center f or Atmospheric Research Boulder, Colorado, USA. Multiscale coherent structures in a turbulent environment.
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Organized Convection Parameterization for GCMs ` Mitchell W. Moncrieff Climate & Global Dynamics Laboratory National Center for Atmospheric Research Boulder, Colorado, USA Multiscale coherent structures in a turbulent environment Convection Parameterization: Progress and Challenges (CPPC) Met Office, Exeter, UK, July 15-19, 2019
Questions • Is organized convection parameterizable? • What’s the physical basis? • Effects in CAMGCM? • Verification?
Moist convective organization • Excellent progress over the past half-a-century in understanding mesoscale processes, e.g., mesoscale convective system (MCS) and multiscale organization • Field-campaign & satellite measurements, cloud-system simulations, dynamical models show the ubiquity of convective organization, a key element of Earth’s water & energy cycles, weather-climate system, etc. • But organized convection is missing from contemporaryGCMs: not parameterized, not resolved • Dual-definition acronym, MCSP: Mesoscale Convective System Parameterization --- MCS Multiscale Coherent Structure Parameterization --- Generalization • MCSP prototype implemented in the NCAR Community Atmosphere Model (Moncrieff, Liu, Bogenschutz2017)
Key contribution of MCS to tropical precipitation Tropical Rainfall Measurement Mission (TRMM) satellite data show MCSs: • Provide > 50% of tropical precipitation, > 70% some places • Are embedded in phenomena that challenge GCMs, e.g. monsoons, ITCZ, MJO, tropical waves • Important to water & energy cycle, atmospheric waves, climate variability, etc.
Multiscale self-similarity Seek minimalist representation, proof-of-concept
Organized Convection Approximate Convective Processes as Functions of Mean-state Variables Parameterization Field-campaign & Satellite Observations Future GCM Cumulus Parameterization + MCSP Cloud-system Resolving Models Nonlinear Dynamical Models Multiscale Coherent Structure Parameterization (MCSP) Multiscale Coherent Structures Slantwise Layer Overturning Contemporary GCM Cumulus Parameterization
Slantwise Layer Overturning • Dynamical role of vertical shear • Mesoscale convective systems (MCS): Cumulonimbus ensembles • Tropical superclusters: MCS ensembles
MCS: Two primary scales Propagation direction L~100 km Deep convection L ~ 10 km Stratiformregion L ~ 100 km
MCS as an ensemble of cumulonimbus Lafore & Moncrieff (1989)
Mesoscale circulation generated by ensemble Lafore & Moncrieff (1989)
Anatomy of MCSP Multiscale Coherent Structures MCSP Slantwise Layer Overturning Lagrangian Dynamics
Multiscale coherent structures Classical Paradigm MCSP Paradigm Reynolds-averaged Field of Transient Cumulus Multiscale Coherent Structures Embedded in a Cumulus Field Entraining Plume Slantwise Layer Overturning
Slantwise layer overturning • Mesoscale circulations generated by ensembles of propagating cumulonimbus exchange tropospheric layers, distinct from small-scale lateral mixing • Vertical shear and the convection-generated mesoscale pressure gradient provide dynamical sources of energy: • Available kinetic energy AKE = ( - • Pressure-gradient work PGW = • Organized convection features: i)‘top-heavy’ heating, ii) counter-gradient momentum transport (‘negative viscosity’) • Mean-state parameters: R = SLOCAPE / AKE and E = PGW / AKE where SLOCAPE is distinct from and much smaller than CAPE
Lagrangian dynamics Nonlinear Lagrangian models are steady in a propagating frame-of-reference and 3D = • Nonlinear equations are transformed into integrable form, = 0 • Integration along trajectories ( defines a set of conserved quantities, = • Calculate transport properties of organized convection using dynamical modeld • Verify models by cloud-resolving simulation & observational data
MCSP Zhang & McFarlane Cumulus ensemble • Large-scale effects of organized convection (i.e., heat and momentum transport) measured as the difference between GCM with & without MCSP • Minimal computational overhead • Prototype canonical formulation • - 1st and/or 2ndbaroclinic (top-heavy convective heating • - 1stbaroclinic acceleration by mesoscale momentum transport
WRF (1 km) TRMM MJOs during the Year of Tropical Convection (YOTC) April 2009 MJO Time–longitude diagram of 15°S–15°N averaged OLR anomalies during May 2008–April 2009 YOTC event; MJO-filtered OLR anomalies superimposed. April 2009 time-longitude distribution of 10oS-10oN averaged rain rate (mm h-1) Moncrieff et al. (2012) Moncrieff & Liu (2019)
Prototype heat & momentum tendencies for slantwise layer overturning Propagation Direction 1stbaroclinic 2nd baroclinic
MCSP effects on annual precipitation (8 years) 1stBaroclinic momentum transport 2ndBaroclinicheating Momentum transport & heating
MCSP effects on tropical waves MCSP: Momentum Transport ( 0, 1)
Conclusions • Prototype MCSP: - Demo of the global effects of convective organization - Precipitation pattern consistent with TRMM measurements - Spatial patterns of heat & momentum parameterization differ - Computationally efficient, use in full GCM suite, including ensembles - Extends, does not replace, cumulus parameterization • Next steps: - Scale-selection mechanisms for multiscale organization - Effects in coupled GCMs (e.g., CESM, E3SM) - Scale-invariance: cumulonimbus, MCS, tropical supercluster - Subseasonal-to-seasonal prediction implications
Acknowledgements • NASA: Collaborative Research with City College of New York (CCNY) Diagnostic Analysis & Cloud-System Modeling of Organized Tropical Convection in the YOTC-ECMWF Global Database. • ECMWF: WCRP-WWRP THORPEX Year of Tropical Convection (YOTC) virtual global field campaign • DOE: Improving Momentum Transport Processes in the Energy Exoscale Earth System Model (E3SM)
References Moncrieff, M.W., 1992: Organized convective systems: Archetypal models, mass and momentum flux theory, and parameterization. Quart. J. Roy. Meteorol. Soc., 118, 819-850. Moncrieff, M.W., 2004: Analytic representation of the large-scale organization of tropical convection. J. Atmos. Sci., 61,1521-1538. Moncrieff, M. W., 2010: The multiscale organization of moist convection and the intersection of weather and climate. In Climate Dynamics: Why Does Climate Vary? Geophys. Monogr. Ser., 189, Eds. D-Z. Sun and F. Bryan, pp. 3–26, doi:10.1029/2008GM000838. Moncrieff, M.W., and D.E. Waliser, 2015: Organized Convection and the YOTC Project, Seamless Prediction of the Earth-System: From Minutes to Months, (G. Brunet, S. Jones, and P.M. Ruti, Eds.), WMO-No. 1156, ISBN 978-92-63-11156-2, 283-309, doi: http://library.wmo.int/pmb_ged/wmo_1156_en.pdf. Moncrieff, M.W., D. E. Waliser, M.J. Miller, M.E. Shapiro, G. Asrar, and J. Caughey, 2012: Multiscale convective organization and the YOTC Virtual Global Field Campaign. Bull. Amer. Meteorol. Soc., 93, 1171-1187, doi:10.1175/BAMS-D-11-00233.1. Moncrieff, M.W., C. Liu and P. Bogenschutz, 2017: Simulation, modeling and dynamically based parameterization of organized tropical convection for global climate models. J. Atmos. Sci., 74, 1363-1380, doi:10.1175/JAS-D-16-0166.1. Tao, W-K., and M. W. Moncrieff, 2009: Multiscale cloud system modeling, Rev. Geophys., 47, RG4002, doi:10.1029/2008RG000276.