1!Lecture Ch. 12!• Review of simplified climate model!• Revisiting: Kiehl and Trenberth!• Overview of “atmospheric heat engine”!• Current research on clouds-climate!Curry and Webster, Ch. 12!For Wednesday: Read Ch. 13!Simplified Climate Model!• Atmosphere described as one layer!– Albedo αp~0.31: reflectance by surface, clouds, aerosols, gases !– Shortwave flux absorbed at surface!• Earth behaves as a black body!– Temperature Te: equivalent black-body temperature of earth!– Longwave flux emitted from surface!Curry and Webster, Ch. 12 pp. 331-337; also Liou, 1992!FS=0.25*S0(1- αp) FL=σTe4 FL Emitted from sphere surface 4πr2 FS Incident on projected disc πr2 FS = FL Simplified Climate Model!• Incoming shortwave = Outgoing longwave!• Energy absorbed = Energy emitted!FS = 0.25*S0(1- αp) FL = σTe4 Solar Constant!• Luminosity of the sun !• Irradiance at earth S0 = L0/(4πd2) = 1.4x103 W/m2!€ d = 1.5 ×1011m (p.437)€ Area = 4πd 2L0 ~ 3.9x1026 W (p. 331)!Simplified Climate Model!• At thermal equilibrium (why?)!• Observed surface temperature T = 288K!• What’s missing?!FS = FL 0.25*S0(1- αp) = σTe4 Te = [0.25*S0(1- αp)/σ]0.25$Te ~ 255K Sensitivity to Albedo!• What if albedo changes?!• 1% decrease in albedo warms temperature 1K!• 1% increase in albedo cools temperature 1K!Te = [0.25*S0(1- αp)/σ]0.25$αp=0.31, Te ~ 255K αp=0.30, Te ~ ?2!Add an Atmosphere!!• Atmosphere is transparent to non-reflected portion of the solar beam!• Atmosphere in radiative equilibrium with surface!• Atmosphere absorbs all the IR emission!Fsurf FS TOA: FS = Fatm 0.25*S0(1- αp) = σTatm4 Tatm = 255K Fatm Fatm Atmos: Fsurf = 2Fatm σTsurf4 = 2σTatm4 Tsurf = 303K What’s wrong?!• With no atmosphere, Tsurf = 255K • With “atmosphere”, Tsurf = 303K • From observations, Tsurf = 288K • Real atmosphere: !– Not perfectly transparent to incoming solar!– Not perfectly opaque to infrared!– Not in pure radiative equilibrium with surface!• Three assumptions were wrong!!Atmospheric Heat Engine!• Latitudinal and meridional heat transfer!• Walker circulation and Aus-Asia monsoons!• Efficiency, irreversibility, entropy!• Hydrological cycle!Curry and Webster, Ch. 12!The Atmospheric “Heat Engine”!3!Atmospheric Heat Engine!Atmospheric Entropy!• Difference between energy and entropy flux!• Irreversible processes!Atmospheric Entropy!• Internal production of entropy by Earth!Hydrological Cycle!• Definition!• Residence times!4!Latitudinal Heating Distribution!• Net heating at equator!• Net cooling at poles!Heating and Circulation!• Fluid motion from vertical density gradient!5!Meridional Heat Transfer!• Equator-to-pole heat transport!Zonal Heat Transfer!• Walker circulation!• Asian-Australian monsoon!WCRP 1998: “Reducing the uncertainty in cloud-climate feedbacks is one of the toughest challenges facing the climate community” IPCC 2007: “Water vapor changes represent the largest feedback affecting climate sensitivity and are now better understood” “Cloud feedbacks remain the largest source of uncertainty” Cloud-Climate feedbacks But which clouds and where and why? IPCC 2007: “Cloud feedbacks remain the largest source of uncertainty” Doubling CO2 less low clouds in GFDL 4 K global warming Doubling CO2 more low clouds in NCAR 2 K global warming B.Soden/G.Stephens GFDL and NCAR have opposite low cloud cover sensitivity to CO2 doubling Large sensitivity in the sub-tropics6!How well are stratocumulus represented? Observations versus ECMWF Re-Analysis (ERA) Cloud cover Liquid water path Surface shortwave July 1987, San Nicolas island, California Severe underestimation of Sc clouds Duynkerke and Teixeira, JCLI, 2001 33!Tropical and subtropical cloud regime transitions: GCSS Pacific Cross-section Intercomparison (GPCI) Models and observations are analyzed along a transect from stratocumulus, across shallow cumulus, to deep convection ISCCP Low Cloud Cover (%) Courtesy C. Hannay GPCI is a working group of the GEWEX Cloud Systems Study (GCSS) Participation of 22 international climate/weather prediction models 34!How representative is the cross-section? Total cloud cover histograms NCAR, 20 N, 215 E GFDL, 20 N, 215 E 20 N, 210 E 20 N, 210 E 20 N, 220 E 20 N, 220 E Results from adjacent points are similar. Models are different. 35!GPCI: JJA98 mean vertical velocity All models exhibit Hadley-circulation-like features… NCAR (Pa/s) BMRC GFDL ascending in ITCZ descending in subtropics major differences in convection and subsidence 36!GPCI mean relative humidity – JJA 2003 General RH pattern from models and AIRS observations is similar … … But there are substantial and problematic differences between models and AIRS 37!Parameterization problem in climate models Atmospheric/oceanic model equation for a generic variable can be written as: Using Reynolds decomposition and averaging to get an equation for the mean: " ""It is assumed that S is linear and the horizontal divergence terms of the sub-grid fluxes can be neglected7!38!Parameterization problem in Climate models Essence of parameterization problem How to estimate the joint PDFs of generic model variables estimating , and also co-variances Temperature (K) probability PDF of temperature in the grid-box longitude latitude Resolution of climate prediction models: Δx=Δy~100 km Δx Δy 39!Low cloud cover - ISCCP observations Low cloud cover – old model Low cloud cover – new model PDF-based stratocumulus cloud parameterization in a coupled model Models and observations for Aug. 2004 New model much closer to observations Teixeira et al. 40!SST sensitivity to cloud parameterization SST: old_model - analysis SST: new_model - analysis SST: new_model – old_model Models and observations for Aug. 2004 Large SST warm biases reduced by new model Teixeira et al. 41!Summary Cloud-climate feedbacks are a major issue in climate prediction Climate prediction models still have serious difficulties in representing small-scale physical processes such as turbulence, clouds and convection Recent satellite data can characterize in a fairly comprehensive manner cloud regime transitions (e.g. subtropics to tropics
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