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Important data of cloud properties for assessing the response of GCM clouds in climate change simulations. Yoko Tsushima JAMSTEC/Frontier Research Center for Global Change. Contents. Cloud feedback uncertainty in GCM global warming simulations Uncertainty in the tropics - PowerPoint PPT Presentation


  • Important data of cloud properties for assessing the response of GCM clouds in climate change simulationsYoko TsushimaJAMSTEC/Frontier Research Center for Global Change

  • ContentsCloud feedback uncertainty in GCM global warming simulationsUncertainty in the tropicsUncertainty in the mid-high latitudesToward fusion of satellite observation and ultra-high resolution modeling : Global cloud resolving model NICAMDataWorkshop announcement: 3rd-5th, Oct, Kusatsu, Japan

  • Cloud feedback in the tropics

  • 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)

  • +1%/yr CO2 :

  • 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.,2006The intermodel range in net cloud feedback is larger than the associated clear-sky response range: the differences in cloud response make the largest contribution to the range in climate sensitivity.

  • Tsushima et al., 2006

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

  • Implications from multi-GCM analysisAssessment 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

  • OutlinesGlobal Cloud Resolving Model NICAM (Nonhydrostatic ICosahedral Atmospheric Model)Icosahedral grid & Nonhydrostatic model & Explicit cloud physicsDevelopment since 2000: number of test casesProblems of Current GCMs:x~ 20km at best & hydrostatic, cloud parameterizationHorizontal resolution: up to dx=3.5km

    Global cloud resolving simulations with NICAM3.5km-mesh Aqua Planet ExperimentGCM expemeriments with realistic land/sea disribution30days run through Apr. 2004preliminary results with 14km-mesh

  • Icosahedral gridsOriginal IcosahedronGlevel-0Glevel-9: x=14kmGlevel-10: x=7kmGlevel-11: x=3.5km

  • Condensed water distribution in Aqua planet experimentTsushima, 2006What are the definition of cloud liquid, rain, cloud iceand snow? Usage of observational definition is useful.Total condensed water data are also informative.

    condensed watercloud liquidraincloud icesnow

  • Preliminary results of a global cloud-resolving simulation with realistic topography

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

  • Apr. 2004 short term exp.NICAM 14kmGMS/GOESInitial condition: 2004/04/01 0UTC, 30 days simulation with 14km-mesh 2004/04/05 00UTC

  • 2004/04/02 00UTC2004/04/03 00UTC2004/04/04 00UTCGOES-9 Kochi-Univ.(http://weather.is.kochi-u.ac.jp/) NICAM gl-09

  • 2004/04/05 00UTC2004/04/06 00UTC2004/04/07 00UTC

  • 2004/04/08 00UTC2004/04/09 00UTC2004/04/10 00UTC

  • Precipitation statics comparison between global cloud resolving simulation with NICAM and TRMM PR dataSatoh et al.,2006

  • Data SummaryA global cloud resolving model (GCRM)Nonhydrostatic system & Icosahedral grid: NICAMavoid ambiguity of cumulus parameterizationsUse of the Earth SimulatorAn 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-goingApr. 2004, short-term (H.Miura)Perpetual July experiment, statistics (S.Iga)

  • Announcement of a Workshop High resolution & cloud modeling workshop toward fusion of satellite observation and ultra-high resolution modeling3rd-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

    It is not in regimes of deep convective area, but in regimes of large-scale subsidence that theWhen we see cloud water profile, its concentration is the largest in the deep convective region in the tropics, but their change in global warming is not so large.The amount and radiative properties of cloud ice is so sensitive to their formulation of microphysics (tuning parameter) in the model. quantitative estimate of total cloud water including both liquid and ice with the observation is informative.Total condensed water: to Chris.