Toward form func.on rela.onships for mul.cellular/ organized convec.on. Toward a moist dynamics that takes account of cloud systems

Similar documents
The effects of organization on convective and large-scale interactions using cloud resolving simulations with parameterized large-scale dynamics

CRM simula+ons with parameterized large- scale dynamics using +me- dependent forcings from observa+ons

Evalua&ng Downdra/ Parameteriza&ons with High Resolu&on CRM Data

Boundary-Layer Cloud Feedbacks on Climate An MMF Perspective

Convec'on, Humidity, and Predictability in a Near- Global Aquaplanet CRM

GCMs with Implicit and Explicit cloudrain processes for simulation of extreme precipitation frequency

Cloud-Resolving Simulations of Convection during DYNAMO

Cloud feedback. Chris Bretherton University of Washington. Rob Wood, Peter Blossey, Matt Wyant, Dennis Hartmann, Mark Zelinka

A Review on the Uses of Cloud-(System-)Resolving Models

Description of zero-buoyancy entraining plume model

Developing Continuous SCM/CRM Forcing Using NWP Products Constrained by ARM Observations

Diurnal Cycle of Convection at the ARM SGP Site: Role of Large-Scale Forcing, Surface Fluxes, and Convective Inhibition

Large Eddy Simulation (LES) & Cloud Resolving Model (CRM) Françoise Guichard and Fleur Couvreux

Cloud-resolving simulation of TOGA-COARE using parameterized largescale

Frank and Charles Cohen Department of Meteorology The Pennsylvania State University University Park, PA, U.S.A.

Trimodal cloudiness and tropical stable layers in simulations of radiative convective equilibrium

An economical scale-aware parameterization for representing subgrid-scale clouds and turbulence in cloud-resolving models and global models

Turbulence-microphysics interactions in boundary layer clouds

What the Heck are Low-Cloud Feedbacks? Takanobu Yamaguchi Rachel R. McCrary Anna B. Harper

Usama Anber 1, Shuguang Wang 2, and Adam Sobel 1,2,3

Month-Long 2D Cloud-Resolving Model Simulation and Resultant Statistics of Cloud Systems Over the ARM SGP

The formation of wider and deeper clouds through cold-pool dynamics

Using Cloud-Resolving Model Simulations of Deep Convection to Inform Cloud Parameterizations in Large-Scale Models

Limitations of Equilibrium Or: What if τ LS τ adj?

Insights into low- la.tude cloud feedbacks from high- resolu.on models

Parameterization of Cumulus Convective Cloud Systems in Mesoscale Forecast Models

Cloud-resolving simulation of TOGA-COARE using parameterized largescale

Convective Vertical Velocities in GFDL AM3, Cloud Resolving Models, and Radar Retrievals

Super-parametrization in climate and what do we learn from high-resolution

Iden%fying CESM cloud and surface biases at Summit, Greenland

STRATEGY & Parametrized Convection

Comparison of the Vertical Velocity used to Calculate the Cloud Droplet Number Concentration in a Cloud-Resolving and a Global Climate Model

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP ICE

Research Objective 4: Develop improved parameterizations of boundary-layer clouds and turbulence for use in MMFs and GCRMs

ATMS 310 Jet Streams

MOGREPS status and activities

1D shallow convective case studies and comparisons with LES

How To Model An Ac Cloud

MICROPHYSICS COMPLEXITY EFFECTS ON STORM EVOLUTION AND ELECTRIFICATION

Improving Low-Cloud Simulation with an Upgraded Multiscale Modeling Framework

Continental and Marine Low-level Cloud Processes and Properties (ARM SGP and AZORES) Xiquan Dong University of North Dakota

The horizontal diffusion issue in CRM simulations of moist convection

Mass flux fluctuation in a cloud resolving simulation with diurnal forcing

Atmospheric Stability & Cloud Development

Various Implementations of a Statistical Cloud Scheme in COSMO model

Tropical Cloud Population

Convective Systems over the South China Sea: Cloud-Resolving Model Simulations

Improving Representation of Turbulence and Clouds In Coarse-Grid CRMs

Sensitivity studies of developing convection in a cloud-resolving model

Potential Climate Impact of Large-Scale Deployment of Renewable Energy Technologies. Chien Wang (MIT)

The impact of parametrized convection on cloud feedback.

Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data

Goal: Understand the conditions and causes of tropical cyclogenesis and cyclolysis

Impact of microphysics on cloud-system resolving model simulations of deep convection and SpCAM

Project Title: Quantifying Uncertainties of High-Resolution WRF Modeling on Downslope Wind Forecasts in the Las Vegas Valley

CHARACTERISTICS OF CLOUDS AND THE NEAR CLOUD ENVIRONMENT IN A SIMULATION OF TROPICAL CONVECTION

Simulation of low clouds from the CAM and the regional WRF with multiple nested resolutions

How To Find Out How Much Cloud Fraction Is Underestimated

Lecture 3. Turbulent fluxes and TKE budgets (Garratt, Ch 2)

Including thermal effects in CFD simulations

Convective Clouds. Convective clouds 1

Weak pressure gradient approximation and its analytical solutions

Evaluation of clouds in GCMs using ARM-data: A time-step approach

Simulations of Clouds and Sensitivity Study by Wearther Research and Forecast Model for Atmospheric Radiation Measurement Case 4

Long-term Observations of the Convective Boundary Layer (CBL) and Shallow cumulus Clouds using Cloud Radar at the SGP ARM Climate Research Facility

This chapter discusses: 1. Definitions and causes of stable and unstable atmospheric air. 2. Processes that cause instability and cloud development

High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land

Climate Models: Uncertainties due to Clouds. Joel Norris Assistant Professor of Climate and Atmospheric Sciences Scripps Institution of Oceanography

Physical properties of mesoscale high-level cloud systems in relation to their atmospheric environment deduced from Sounders

How To Write A New Vertical Diffusion Package

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

Fog and Cloud Development. Bows and Flows of Angel Hair

Formation & Classification

Coupling between subtropical cloud feedback and the local hydrological cycle in a climate model

Theory of moist convection in statistical equilibrium

Atmospheric Processes

J4.1 CENTRAL NORTH CAROLINA TORNADOES FROM THE 16 APRIL 2011 OUTBREAK. Matthew Parker* North Carolina State University, Raleigh, North Carolina

A new positive cloud feedback?

Can latent heat release have a negative effect on polar low intensity?

The Ideal Gas Law. Gas Constant. Applications of the Gas law. P = ρ R T. Lecture 2: Atmospheric Thermodynamics

Ecosystem change and landsurface-cloud

National Center for Atmospheric Research,* Boulder, Colorado. (Manuscript received 2 December 1999, in final form 3 October 2000)

Aspects of the parametrization of organized convection: Contrasting cloud-resolving model and single-column model realizations

RADIATION IN THE TROPICAL ATMOSPHERE and the SAHEL SURFACE HEAT BALANCE. Peter J. Lamb. Cooperative Institute for Mesoscale Meteorological Studies

Cumulus Convection, Climate Sensitivity, and Heightened Imperatives for Physically Robust Cumulus Parameterizations in Climate Models

Climatic Properties of Tropical Precipitating Convection under Varying Environmental Conditions

Quality Assurance in Atmospheric Modeling

Surface Rainfall Cold Cloud Fractional Coverage Relationship in TOGA COARE: A Function of Vertical Wind Shear

7B.2 MODELING THE EFFECT OF VERTICAL WIND SHEAR ON TROPICAL CYCLONE SIZE AND STRUCTURE

EAJF and Cancer - A Review

Indian Ocean and Monsoon

How To Find Out How Much Cloud Fraction Is Underestimated

Stochastic variability of mass flux in a cloud resolving simulation

Unified Cloud and Mixing Parameterizations of the Marine Boundary Layer: EDMF and PDF-based cloud approaches

Overview and Cloud Cover Parameterization

Chapter 7 Stability and Cloud Development. Atmospheric Stability

Towards an NWP-testbed

Evaluating GCM clouds using instrument simulators

How do Scientists Forecast Thunderstorms?

Dutch Atmospheric Large-Eddy Simulation Model (DALES v3.2) CGILS-S11 results

Transcription:

Toward form func.on rela.onships for mul.cellular/ organized convec.on or maybe Toward a moist dynamics that takes account of cloud systems (review/ essay in prep. for JMSJ) Brian Mapes University of Miami

Mo.va.on Disconnect between detailed observa.ons and large scale desires that jus.fy them Observa.ons are 4+ dimensional (xyzt +scales) full of rich mesoscale texture (cloud systems) How can observa.ons of all this truly inform understanding and modeling?

Example: mixing in convec.on The authors iden/fy the entrainment rate coefficient of the convec/on scheme as the most important single parameter... [out of 31]...[for]... HadSM3 climate sensi/vity Rougier et al. 2009, J.Clim. doi:10.1175/2008jcli2533.1. Brooks Salzwedel Plume #1 2009 12" x 8 Mixed Media

Find me the entrainment coefficient 300 km 30 hour radar reflec.vity loop S POL, DYNAMO, Indian Ocean (Maldives) Oct 2011

Column water vapor (MIMIC) shows summer.me low level flow 850

Representa.ve summer 2006 9 cloudsat radar echo objects <200km in horizontal width

now with >200km ones in red

Models have mesoscales too. So what? GEOS 5 5km mesh (!) global model Runs: Putman & Suarez (2011), NASA GSFC / Figs: Mapes, Song & Putman, in prep.

An organ ized set of cells from Gk. organon "implement", lit. "that with which one works," from PIE... We know a lot about form......but not enough about func.on The Anatomy Lesson of Dr. Nicolaes Tulp Rembrandt 1632 medicine in the 1600s

Connecting form to function Definitions & measures of function 1. Offline diagnostic: sensitivity matrix 2. Test-harness performance: column with parameterized large-scale dynamics 3. Inline: super-param (vs. under-resolved) Ways to control for form Domain size and shape; vertical wind shear Conditional sampling (a route for using obs?)

Hypothesis: more organized convec.on couples more strongly to large scales e.g. more 2D vs. isotropic 3D in 'parameterized LSD' test harnesses for periodic CRMs WTG harness for CRM Linear gravity wave coupling (Kuang 2010) 2.5D (narrow periodic domain) 2D CRM 3D CRM 3D Wang and Sobel 2011 Riley, Mapes, Kuang in prep.

3D small- No Shear 3D With Shear Robe and Emanuel 2001 doubly periodic x (km) Strict 2D Mapes (2004)

Linear response function (or sensitivity matrix) M Kuang (2010 JAS) devised one way to build it using a set of long eq'm runs of a periodic CRM, with mild forcing perturbations that span the space (2NP runs) build M's inverse this way, and do matrix inversion edit small eigenvalues of M ( negative; it's a stable system)

Effect of T on subsequent 4h hea.ng p coordinates view each built from >100,000 days of CRM.me inhibits hea.ng above T 650 >0 (Kuang 2012)

Sensi.vity of column integrated hea.ng to T at various pressure levels Sensi.vity of 4h rain <dt/dt> to T (p) inhibits hea.ng above T 700 >0

Sensi.vity profiles: from 3D small CRM S T ( p) = d Q 1 next 4h dt( p) S q ( p) = d Q 1 dq(p) S aer (p) = d Q 1 d[aerosol( p)] eff. inhib. layer Moisture in free troposphere is favorable WARM PBL + MOIST PBL Computa.ons: Kuang (2010) / Figs: Mapes and Kuang in prep.

Test of <M> COARE sonde array 120d of 6h data

Or, try to es.mate <M> by mul.ple linear regression Regress COARE budget derived rainrate onto (first few EOFs of) T'(p) and q'(p) profiles

Regression sensi.vity profiles from EOFs of T&q Black: 10 modes 2(purple) to 9(red) modes from Siwon Song

Regression sensi.vity profiles from EOFs of T&q Black: 10 modes 2(purple) to 9(red) modes from Siwon Song

3D small domain CRM and 1 CEOF mode regression S T ( p) = d Q 1 4h dt(p) S q ( p) = d Q 1 4h dq(p) shape too controlled by EOF rather than by regression? Siwon Song, work in progress

Sensi.vity profiles: 3D small domain CRM S T ( p) = d Q 1 next 4 h dt( p) Different entrainment formula.ons (Sahany et al. 2011) S q ( p) = d Q 1 dq(p) eff. inhib. layer Moisture in free troposphere slightly favorable WARM PBL +GOOD+ MOIST PBL

Sensi.vity profiles: 3D small domain CRM Different entrainment formula.ons S T ( p) = d Q 1 next 4 h dt( p) S q ( p) = d Q 1 dq(p) eff. inhib. layer Moisture in free troposphere slightly favorable WARM PBL +GOOD+ MOIST PBL

convec.on: different sensi.vity Midlevel inflows, layer overturning Coherent structures fewer of them, so ZK had to use >200,000 days of CRM.me for...

Organized convec.on sensi.vi.es to large scale (domain mean) T anomalies: inhibits hea.ng above

Sensi.vity of big domain rain to LS T and q ORG: NOT INHIBITED BY T800! Computa.ons: Kuang 2012 in review / Figs: Mapes and Kuang in prep.

Jump to GCM experimenta/on... org Ω access to less diluted plume By this def., trad. GCMs have ubiquitous org., not lack of it!

Org(x,y,t): a prognos.c scalar in CAM5 UWens scheme with 2 plumes (more vs. less mixing) precipita.on evapora.on of rain subgrid geography and breezes stochas.c component forced, t=3h decay, advected org(t) shear (rolls, deforma.on lines, etc.) plume overlap more likely (precondi.oned local environs) 2 nd plume wider (mixes less) more mass flux in 2 nd plume updrau base warmer than grid mean deeper convec.on

Org(x,y,t): a 2D prognos.c scalar variable evapora.on of rain subgrid geography and breezes stochas.c component org(t) + plume overlap more likely forced, (precondi.oned 3h decay, local environs) advected 2 nd plume wider (mixes less) precipita.on shear (rolls, deforma.on lines, etc.) more mass flux in 2 nd plume updrau base warmer than grid mean deeper convec.on

Similar mystery from S. Bush, A. Turner Met Office model clandes.ne pers. comm. 2012 1.5x entrain rains MORE!!?

Key points/ conclusions Mesoscale/mul.scale structure confounds obsmodel connec.ons Need an account of how form relates to func.on Defining func/on is half the bavle Controlling form is the other half Is org. a con.nuum from isotropic 3D to 2D?

Results Offline diagnos.c of func.on: matrix M 4 hour <Q1> sensi.vity profile, from 128km 3D CRM: +sensi.vity to PBL ( parcel ), free trop q; inhibi.on to 600mb Sensi.vity of 2048 x 128 w/ mesoscale org differs: More sensi.ve to q, T at 700mb a posi/ve influence inhibi.on layer extends up to 400 300 mb Param: org access to less dilute updraus By this def, org too ubiquitous in trad. GCMs, not missing Mystery: some places more org reduces rainfall or more entrainment increases rainfall (Reading/UKMO) Working/thinking how to bring in obs bever