Important data of cloud properties for assessing the response of GCM clouds in climate change simulations

Yoko TsushimaJAMSTEC/Frontier Research

Center for Global Change

Contents

• Cloud feedback uncertainty in GCM global warming simulations– Uncertainty in the tropics– Uncertainty in the mid-high latitudes

• “Toward fusion of satellite observation and ultra-high resolution modeling” : Global cloud resolving model NICAM– Data– Workshop announcement: 3rd-5th, Oct, Kusatsu, Japan

Cloud feedback in the tropics

15 AR4 coupled ocean-atmosphere GCMs+1%/yr CO2:

(low-sensitivitymodels)

(high-sensitivitymodels)

The cooling effectof clouds is reduced

(enhancesclimate sensitivity)

The cooling effectof clouds is enhanced

(decreasesclimate sensitivity)

Sensitivity of the tropical NET CRF tolong-term SST changes (W/m2/K)

Bony and Dufresne, GRL (2005)

ISCCP cloud amounts and ERA40 500mb(tropical oceans, 1984-2000)

Upper-level cloud tops

Low-level cloud tops

Subsidenceregimes

HS GCMsLS GCMs

HS GCMsLS GCMs

HS GCMsLS GCMs

Convectiveregimes

Sensitivity of the tropical CRFto long-term SST changes in global warming experiments

(W/m2/K)

2 OAGCM groups:High-Sensitivity models 0)Low-Sensitivity models 0)

CRF

SST

+1%/yr CO2 :

Interannual Climate Variations(an example, not an analogue!)

1984-2000 monthly data :• ISCCP-FD radiative fluxes• Reynolds SST• ERA40 or NCEP2 reanalyses

AR4 OAGCMs:•20th century simulations • HS (N=8) vs LS (N=7) models High-Sensitivity models

Low-Sensitivity models

convective regimes subsidence

Sensitivity of the SW CRF to SST changes composited by dynamical regimes

OBS

It is in regimes of large-scale subsidence (associated with low-level clouds)that the relationship between cloud radiative forcing and SST :

(1) Differs the most among models in climate change (explains most of inter-model differences in cloud feedbacks)

(2) Disagrees the most with observations in current interannualclimate variability (models underestimate the sensitivity of cloudsalbedo to a change in SST)

The simulation of marine boundary-layer clouds is at the heartof tropical cloud feedback uncertainties in AR4 models.

Any impact on the simulation of ENSO variability ?? Needs some investigation..

Change in Cloud water: feedback in the mid and high

latitudes

Cloud Feedback Model Intercomparison Project (CFMIP)

McAvaney and Le Treut (2003)

• Outputs from IPCC models with more cloud variables than IPCC outputs.

• Slab ocen experiments with 1xCO2, 2xCO2.

• Webb et al.,2006– The intermodel range in net cloud feedback is larger t

han the associated clear-sky response range: the differences in cloud response make the largest contribution to the range in climate sensitivity.

Clim

ate

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6.3℃

4.0℃

3.6℃

2.9℃

2.3℃

Tsushima et al., 2006Cloud water (1xCO2)

0 1.5e-4

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[hPa]Cloud ice (1xCO2)

－ 90 － 60 － 30 0 30 60 90

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[hPa]Cloud liquid(2xCO2－ 1xCO2)

-2e-5 0 2e-5

－ 90 － 60 － 30 0 30 60 90

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[hPa]

Zonal mean profile of relative humidity, cloud water, cloud ice under 1xCO2 climate in [60S:30S]

Relative humidity

Cloud water

Cloud ice

Implications from multi-GCM analysis

Assessment of the mean state and sensitivity of

• Low clouds in the large scale subsidence region

• Mixed-phase level clouds (which is dominant clouds in the extra-tropics)

using observational data are important for assessing GCM clouds.

“Toward fusion of satellite observation and ultra-high

resolution modeling” : Global cloud resolving model NICAM

Global Cloud Resolving Model NICAM (Nonhydrostatic ICosahedral Atmospheric Model)

• Icosahedral grid & Nonhydrostatic model & Explicit cloud physics• Development since 2000: number of test cases• Problems of Current GCMs:Δx~ 20km at best & hydrostatic, cloud parameterization• Horizontal resolution: up to dx=3.5km

Global cloud resolving simulations with NICAM 3.5km-mesh Aqua Planet Experiment GCM expemeriments with realistic land/sea disribution

• 30days run through Apr. 2004• preliminary results with 14km-mesh

OutlinesOutlines

Icosahedral gridsIcosahedral grids

Original Icosahedron

Glevel-1 Glevel-3 Glevel-5

Glevel-0Glevel-9: Δx=14kmGlevel-10: Δx=7kmGlevel-11: Δx=3.5km

Condensed water distribution in Aqua planet experimentCondensed water distribution in Aqua planet experiment

Tsushima, 2006 What are the definition of “cloud liquid”, “rain”, “cloud

ice”and “snow”? Usage of observational definition is useful.

“Total condensed water” data are also informative.

condensed water cloud liquid rain

cloud ice snow

Preliminary results of Preliminary results of a global cloud-resolving simulation a global cloud-resolving simulation

with realistic topographywith realistic topography

•dx=14km (glevel9) L40 without parameterizationdx=14km (glevel9) L40 without parameterization•dx=7, 3.5km, on goingdx=7, 3.5km, on going•Apr. 2004, short-term (H.Miura)Apr. 2004, short-term (H.Miura)•Perpetual July experiment, statistics (S.Iga)Perpetual July experiment, statistics (S.Iga)

Apr. 2004 short term exp.Apr. 2004 short term exp.

NICAM 14km GMS/GOES

Initial condition: 2004/04/01 0UTC, 30 days simulation with 14km-mesh

2004/04/05 00UTC

2004/04/02 00UTC 2004/04/03 00UTC 2004/04/04 00UTC

GOES-9 Kochi-Univ.(http://weather.is.kochi-u.ac.jp/)

NICAM gl-09

2004/04/05 00UTC 2004/04/06 00UTC 2004/04/07 00UTC

2004/04/08 00UTC 2004/04/09 00UTC 2004/04/10 00UTC

Satoh et al.,2006

Precipitation statics comparison between global cloud resolving simulation wiPrecipitation statics comparison between global cloud resolving simulation with NICAM and TRMM PR datath NICAM and TRMM PR data

Data SummaryData SummaryA global cloud resolving model (GCRM)

Nonhydrostatic system & Icosahedral grid: NICAMavoid ambiguity of cumulus parameterizationsUse of the Earth Simulator

An aqua-planet-experiment dx=3.5km and 54 layersHierarchical structure of cloud convectionMoist Kelvin wave structure with realistic phase speedInternal motions including wave structure Nasuno et al.(2006,submitted to JAS)

GCRM runs on the realistic land-ocean distributiondx=14km, 30days done: dx=7, 3.5km, on-going Apr. 2004, short-term (H.Miura) Perpetual July experiment, statistics (S.Iga)

Announcement of a Workshop Announcement of a Workshop High resolution & cloud modeling workshop “toward fusion of satellite observation and ultra-high resoluti

on modeling”3rd-5th, Oct, Kusatsu, Japan

If you are interested in the data and/or the workshop, please contact me!

Thank you.

Yoko TsushimaE-mail: tsussi@jamstec.go.jp Frontier Research Center for Global Change/JAMSTEC Japan