CMIP6 Recommendations from The Cloud Feedback Model Inter-comparison Project CFMIP. Building bridges between cloud communities



Similar documents
Investigating mechanisms of cloud feedback differences.

The impact of parametrized convection on cloud feedback.

SPOOKIE: The Selected Process On/Off Klima Intercomparison Experiment

CFMIP-2 : Cloud Feedback Model Intercomparison Project Phase 2

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

A glance at compensating errors between low-level cloud fraction and cloud optical properties using satellite retrievals

Interpretation of the positive low-cloud feedback predicted by a climate model under global warming

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

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

Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations

WCRP Grand Challenge on. Clouds, Circulation and Climate Sensitivity

Suvarchal Kumar Cheedela

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

A process oriented descrip-on of oceanic clouds derived from A- train observa-ons, for climate model evalua-on

Boundary-Layer Cloud Feedbacks on Climate An MMF Perspective

Clouds, Circulation, and Climate Sensitivity

Comment on "Observational and model evidence for positive low-level cloud feedback"

Atmospheric Processes

STRATEGY & Parametrized Convection

Evaluating GCM clouds using instrument simulators

Structural similarities and differences in. two perturbed physics ensembles

How To Model An Ac Cloud

Performance Metrics for Climate Models: WDAC advancements towards routine modeling benchmarks

Evaluating the Impact of Cloud-Aerosol- Precipitation Interaction (CAPI) Schemes on Rainfall Forecast in the NGGPS

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

Comparison of Cloud and Radiation Variability Reported by Surface Observers, ISCCP, and ERBS

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

Interactive comment on Total cloud cover from satellite observations and climate models by P. Probst et al.

A new positive cloud feedback?

MARK D. ZELINKA STEPHEN A. KLEIN

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

An update on the WGNE/WGCM Climate Model Metrics Panel

Observed Cloud Cover Trends and Global Climate Change. Joel Norris Scripps Institution of Oceanography

Earth s Cloud Feedback

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

CAUSES. (Clouds Above the United States and Errors at the Surface)

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

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

Improving Representation of Turbulence and Clouds In Coarse-Grid CRMs

Why aren t climate models getting better? Bjorn Stevens, UCLA

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

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

How To Understand Cloud Radiative Effects

Selecting members of the QUMP perturbed-physics ensemble for use with PRECIS

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

Evaluating climate model simulations of tropical cloud

Ecosystem-land-surface-BL-cloud coupling as climate changes

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

Description of zero-buoyancy entraining plume model

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

Evaluation of Precipitation and High-Level Cloud Areas Associated with Large-Scale Circulation over the Tropical Pacific in the CMIP3 Models

Increasing Atmospheric Poleward Energy Transport with Global Warming

JournalofGeophysicalResearch: Atmospheres

A SURVEY OF CLOUD COVER OVER MĂGURELE, ROMANIA, USING CEILOMETER AND SATELLITE DATA

Since launch in April of 2006, CloudSat has provided

A hybrid cloud regime methodology used to evaluate Southern. Ocean cloud and shortwave radiation errors in ACCESS

TOPIC: CLOUD CLASSIFICATION

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

The ARM-GCSS Intercomparison Study of Single-Column Models and Cloud System Models

EXASCALE CLIMATE DATA ANALYSIS

Guy Carpenter Asia-Pacific Climate Impact Centre, School of energy and Environment, City University of Hong Kong

Science Goals for the ARM Recovery Act Radars

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

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

Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels

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

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

Number of activated CCN as a key property in cloud-aerosol interactions. Or, More on simplicity in complex systems

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

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

Attributing the behavior of low-level clouds in large-scale models to sub-grid scale parameterizations

Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations. Final Report

Improving Hydrological Predictions

Cloud-resolving simulation of TOGA-COARE using parameterized largescale

Cloud Parameterizations in SUNYA Regional Climate Model for the East Asia Summer Monsoon Simulations

Clouds and Convection

The ozone hole indirect effect: Cloud-radiative anomalies accompanying the poleward shift of the eddy-driven jet in the Southern Hemisphere

Formation & Classification

Cloud-Resolving Simulations of Convection during DYNAMO

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

REVIEW ARTICLE. How Well Do We Understand and Evaluate Climate Change Feedback Processes?

On dynamic and thermodynamic components of cloud changes

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

Roy W. Spencer 1. Search and Discovery Article # (2009) Posted September 8, Abstract

Perturbed physics ensemble using the MIROC5 coupled atmosphere ocean GCM without flux corrections: experimental design and results

Improving Low-Cloud Simulation with an Upgraded Multiscale Modeling Framework

Addendum to the CMIP5 Experiment Design Document: A compendium of relevant s sent to the modeling groups

Sensitivity studies of developing convection in a cloud-resolving model

Selected Ac)vi)es Overseen by the WDAC

THE CURIOUS CASE OF THE PLIOCENE CLIMATE. Chris Brierley, Alexey Fedorov and Zhonghui Lui

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

Parameterization of Cumulus Convective Cloud Systems in Mesoscale Forecast Models

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

Modelling the Earth System. Understanding and predicting climate changes and fluctuations

Clouds and the Energy Cycle

REGIONAL CLIMATE AND DOWNSCALING

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

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

Tropical Cloud Population

Transcription:

CMIP6 Recommendations from The Cloud Feedback Model Inter-comparison Project CFMIP Building bridges between cloud communities CFMIP Committee members Mark Webb, Chris Bretherton, Sandrine Bony, Steve Klein, Masahiro Watanabe, Bjorn Stevens + input from Steve Sherwood and members of the COSP Project Management Committee

The objective of CFMIP-2 is to provide a better assessment of climate change cloud feedbacks by improving the evaluation of clouds simulated by climate models and the understanding of cloud-climate feedback processes.

CFMIP Observation Simulator Package (COSP) Bodas-Salcedo et al., 2011 http://www.cfmip.net Quantitative evaluation of the 3D distribution of clouds and cloud properties in models COSP is being used by all the major modelling groups in CMIP5 (& NWP)

Clouds and model systematic errors... CMIP5 Multimodel Mean SST error model-obs Over-estimate of absorbed SW radiation primarily due to mid-level topped ISCCP cloud regime (e.g. Bodas-Salcedo et al., submitted) COSP also useful for : + evaluation of polar clouds, etc + emerging constraints + analysis cloud feedbacks cloud regimes

CMIP5 cloud feedbacks analyzed in terms of cloud types & processes COSP simulator outputs are not useful only for evaluating clouds but also for the understanding of cloud feedbacks - Positive cloud feedback - Primarily arises from low-level and high-level cloud feedbacks - Spread primarily arises from low-level cloud feedbacks (using COSP simulator outputs) Zelinka et al., J. Climate, 2013

CFMIP2/CMIP5 Experiment Hierarchy

CMIP5 models also predict fast adjustments of the atmospheric circulation to increased CO2 4xCO2 fixedsst (AMIP, sstclim) Abrupt 4xCO2 (OAGCM) AQUA 4xCO2 fixed SST (AMIP, sstclim) Abrupt 4xCO2 (OAGCM) RCP8.5 end 21C RCP8.5 end 21C Robust direct effect of CO2 on the strength of the overturning atmospheric circulation in the tropics Bony et al., NGS, 2013

High frequency cfsites outputs at site locations - Timestep level (e.g. 30 minute) frequency outputs at 120 locations - Clouds, radiation, precipitation and environmental variables - Temperature/humidity tendencies for advection, convection, PBL, -> diurnal cycle, analysis of cloud feedback processes, etc

CMIP5 / CFMIP2 : What went well? A fair number of groups submitted CFMIP experiments, including simulator and process outputs. A large number of studies with COSP CFMIP provides computationally inexpensive experiments which have led to new insights into cloud feedback and adjustment mechanisms, and precipitation responses to climate change... and have formed the basis for additional CFMIP experiments (e.g. COOKIE or SPOOKIE). Analysis of CFMIP-2 outputs are ongoing and we are still receiving data from some modelling groups, so the full value of the CFMIP experiments is yet to be realised.

CMIP5 / CFMIP2 : Science questions How well do climate models simulate clouds? (in the vertical, from the tropics to the poles) What is the role of fast adjustments to CO2? (diagnostic forcing/feedbacks, uncertainties in climate sensitivity) What are the physical processes underlying cloud feedbacks? (and the inter-model spread) How well do we understand precipitation changes? (including regional patterns)

CMIP5 / CFMIP2 : Publications Already a large number of CFMIP-2/CMIP5 studies and related publications; see http://www.cfmip.net -> CFMIP Meetings for presentations http://www.cfmip.net -> CFMIP publications for a full list, including : Many COSP papers on CMIP5 models: Klein et al 2013; Tsushima et al 2013; Bodas et al 2013; Konsta et al 2013; Lacagnina et al (submitted); Zelinka et al 2013; Cesana and Chepfer 2013; Stevens et al 2013; Xie et al 2013; Franklin et al 2013; John et al 2013; von Salzen et al 2013;Wang and Su 2013; Nam et al 2013 Quantifying forcings and feedbacks in idealised CFMIP5/CFMIP-2 experiments: Zelinka et al 2013; Andrews et al 2012; Vial et al 2013; Geoffroy et al, 2012 Parts 1&2; Shiogama et al 2013; Yoshimori et al 2013; Webb et al (in preparation); Tsushima et al (in preparation) Demonstration that aquaplanets reproduce a large inter-model spread : Stevens and Bony 2013; Medeiros et al (in preparation) Understanding adjustment/feedback mechanisms in GCMs/SCMs: Brient and Bony 2012; Kamae and Watanabe, 2012a,b; Brient and Bony 2013; Webb and Lock 2013; Ogura at al (in press); Zhang et al (submitted); Demoto et al (2013); Sherwood et al (submitted). Understanding cloud feedback/adjustment mechanisms in LES/MLMs: Rieck et al 2012; Zhang et al 2012; Blossey at al 2013; Bretherton et al 2013; De Roode et al (submitted); Dal Gesso et al (submitted); Bretherton et al (submitted)

Towards CFMIP3/CMIP6 : Proposals for Filling Science Gaps (1) To strengthen, develop and generalize the findings of CFMIP2/CMIP5 (role of cloud processes in model biases and response to forcings) : - Favor the continuity with CFMIP2/CMIP5 to encourage the implementation of CMIP experiments and COSP/process outputs in more models than in CMIP5. To better assess and understand cloud feedbacks and adjustments in coupled models : - Propose experiments aiming at diagnosing the time-varying radiative forcing in historical experiments - Propose +/- 3% abrupt solar forcing AOGCM experiments to examine coupled feedbacks without CO2 adjustments - Request process outputs (3D tendencies, cfsites) in sections of picontrol & abrupt4xco2

Towards CFMIP3/CMIP6 : Proposals for Filling Science Gaps (2) To understand the impact of clouds and cloud changes on regional temperatures, circulation and precipitation : - Propose sensitivity experiments with clouds made transparent to radiation (Clouds On/Off Klimate Experiments, COOKIE) - Promote idealized experiments in simplified frameworks (e.g. aquaplanets, global RCE) To test physical hypotheses (and observational constraints) about the link between processes, model formulation (e.g. parameterizations) and cloud responses : - Propose a hierarchy of short-term T-AMIP experiments (4xCO2, +4K) to examine timescales and identify causal links between cloud-controlling factors and cloud responses. - Encourage sensitivity tests to parameterizations based on CFMIP experiments (e.g. Selected Processes On/Off Klimate Intercomparison Experiment, SPOOKIE) - Propose inexpensive idealized experiments (e.g. aquaplanets, global RCE) to fill the gap between CMIP models and Cloud-Resolving models (global CRM, SP-GCMs)

Preliminary COOKIE results: Impact of PBL cloud-radiative effects on tropical circulation and precipitation Precipitation (offpblamip-amip) CNRM-CM5 Surface wind (offpblamip-amip) CNRM-CM5 EC-EARTH ECHAM6 ECHAM6 IPSL-CM5B IPSL-CM5B IPSL-CM5A IPSL-CM5A mm/day m/s Solange Fermepin and the EUCLIPSE/COOKIE participants

Preliminary SPOOKIE results: Impact of switching off convective parametrization on net cloud feedback in amip/amip4k HadGEM2-A Standard 0.25 Wm-2K-1 MRI-CGCM3 Standard 0.10 Wm-2K-1 MIROC5 Standard -0.22 Wm-2K-1 Range = 0.47 Wm-2K-1 HadGEM2-A ConvOff -0.05 Wm-2K-1 HadGEM2-A ConvOff 0.25 Wm K -2-1 MRI-CGCM3 ConvOff -0.08 Wm-2K-1 Range = 0.26 Wm-2K-1 MRI-CGCM3 Standard 0.25 Wm-2K-1 MIROC5 ConvOff 0.18 Wm-2K-1 MIROC5 Standard 0.25 Wm-2K-1 Mark Webb, Adrian Lock, Masahiro Watanabe, Hideaki Kawai, Tsuyoshi Koshiro, Thorsten Mauritsen

Towards CGILS RCE : Global Radiative-Convective Equilibrium simulations Popke, Stevens and Voigt, JAMES, 2013

Towards CFMIP3/CMIP6 : Main CFMIP Recommendations Favor the continuity with CFMIP2/CMIP5 : CMIP6 should be an opportunity for modeling groups to provide the experiments and outputs they did not provide at the time of CMIP5. Communicate better rationale for experiments and outputs to tackle science gaps, in connection with WCRP Grand Challenges (e.g. COSP = evaluation + feedback diagnostics) Raise priority of inexpensive idealized experiments (e.g. amip4xco2, amip4k and aquaplanets) which isolate the influence of basic physical processes on climate change uncertainties. Make a limited set of key simulator and process diagnostics core/high priority (e.g. temperature and humidity tendency terms, ISCCP and CALIPSO simulator outputs.

Towards CFMIP3/CMIP6 : Proposed Experiment Hierarchy

A concern about CFMIP diagnostics in CMIP Scientific benefits from CFMIP are as much due to COSP and process diagnostics as additional experiments (e.g. amip4k, amip4xco2, aquaplanets) These diagnostics need to be in core CMIP (or DEC) experiments (e.g. amip, picontrol, abrupt4xco2) If CMIP core experiments are frozen in advance of other MIPs, it is crucial that the CFMIP process diagnostics are included in the CMIP core experiments This will also be an issue for other MIPs which depend on diagnostics in the core CMIP experiments -> CFMIP will do its best to : define the CFMIP design and output requirements early communicate the rationale of CFMIP experiments and diagnostics to modeling groups

Close Connection between CFMIP and the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity CFMIP closely associated with each initiative of this Grand Challenge : - Climate and Hydrological Sensitivtiy - Coupling Clouds to Circulation - Understanding Changing Patterns - Leveraging Observational Records - Developing Mode Reliable Models As part of this Grand Challenge, CFMIP will : - widen its focus and interests (e.g. coupling clouds, convection circulation) - develop stronger connections to PMIP (paleo), GASS (processes), SPARC (dynamics), WGNE (model biases) and observations.

Additional slides

Amip4K Net Cloud Feedback along GPCI from models with cfsites data (Mark Webb) Trade Cumulus Crown copyright Met Office Transition Region Coastal Stratocumulus

cfsites: Moist Static Energy Budget Approach following Brient and Bony 2013, Webb and Lock 2013 Δ Cloud Fraction ΔMSE Convection Δ LH = +7 W/m2 ΔMSE Radiation ΔMSE Advection ΔMSE Turbulent Mixing Δ SH = -5 W/m2 MRI-CGCM3 Trade Cu s9 AMIP 4K AMIP Response JJA: Shallow convection and turbulent mixing feedbacks drives cloud loss (Mark Webb)

Clouds have improved in CMIP5 models compared to those in CFMIP-1 particularly optically thick clouds: Klein et al 2013: Are climate model simulations of clouds improving? evaluation using the ISCCP simulator. (JGR) An

Improvements are seen in mainly in the radiative properties of optically thicker low and high topped cloud regimes rather than frequency of occurrence. Shall ow Midlevel Thin Low level Conv ective Deep Strato cu Cumu lus Topp ed Cirru s Trans ition Anvil Conv CFMIP1 -> CMIP5 Change of in-regime Net CRE RMSE swcf_trop.04.ps Change between CFMIP-1 and CMIP5 of in-regime Net Cloud Radiative Effect (Net CRE) RMSE within daily ISCCP simulator cloud regimes in the tropics Tsushima et al 2013: Quantitative evaluation of the seasonal variations in climate model cloud regimes. (Climate Dynamics)

Vial, Dufresne and Bony 2013: On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. (Climate Dynamics)

Stevens and Bony, 2013 (Science)

Use of ISCCP simulator to break down feedbacks into contributions from different cloud types: Zelinka et al 2013: Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5. (J. Climate)

Observational constraints on responses of stratocumulus and frontal cloud regimes in amipfuture experiments. Net CRE in Sc regime (W/m2) Frequency of Frontal regime [0,1] Present day (AMIP) amipfuture amip response amipfuture amip response Value consistent with ISCCP observations Present day (AMIP) Yoko Tsushima, Met Office Hadley Centre