11/16/20121Lecture 32Evaporation and TranspirationObservations, Part 2Dennis BaldocchiDepartment of Environmental Science, Policy and ManagementUniversity of California, BerkeleyESPM 129 Biometeorology11/16/2012Day0 50 100 150 200 250 300 350ET (mm d-1)0123456Day0 50 100 150 200 250 300 350ET (mm d-1)0123456Day0 50 100 150 200 250 300 350ET (mm d-1)0123456Tropical Forest, BrazilTemperate Deciduous Forest, TennesseeSavanna Woodland, CaliforniaDay0 100 200 300ET (mm d-1)0123456Temperate Conifer Rain Forest, British Columbia and JapanABCDESPM 129 BiometeorologyAnnual Variation in Daily Evaporation11/16/20122Day of Year0 50 100 150 200 250 300 350ET (mm d-1)01234California-DeciduousItaly-DeciduousDay of Year0 50 100 150 200 250 300 350ET (mm d-1)0.00.51.01.52.02.53.0France-evergreenPortugal-evergreenItaly-evergreen(A)(B)Evergreen and Deciduous Mediterranean OaksESPM 129 BiometeorologySeasonal and Annual Time ScalesAnnual Grassland, 2004Day0 50 100 150 200 250 300 350E (MJ m-2 d-1)02468101214Actual LEPotential LEPotential and Actual Evaporation are Decoupled in Semi-Arid SystemESPM 129 Biometeorology11/16/20123Forest EvaporationET (mm/y)500 1000 1500 2000pdf0.000.020.040.060.080.100.120.140.160.18TakeHome Points: ET > 200 mm/yMedian = 402 mm/ySkewed Distribution, Max ~ 2300 mm/yESPM 129 BiometeorologyA linear additive model has the following statistics: ET = -141 + 116*Rn + 0.378 * ppt, r2= 0.819. The color bar refers to annual ETStatistical Model between Annual Forest ET, Net Radiation and PrecipitationESPM 129 Biometeorology11/16/20124Fisher et al., 2008Global ET pdf, 1989, ISLSCPESPM 129 BiometeorologyFluxNET WUECarbon Assimilation Scales with Water UseFLUXNET 2007LE (mm y-1)0 200 400 600 800 1000 1200 1400GPP (gC m-2 y-1)0100020003000400050006000ESPM 129 Biometeorology11/16/20125Year1970 1975 1980 1985 1990 1995 2000Evaporation (mm year-1)02004006008001000Catchment Eddy Covariance Sap Flow Equilibrium EvaporationWalker Branch Watershed, TN; Wilson et al. 2001Interannual Variation, Temperate Deciduous ForestESPM 129 BiometeorologyTharandt Forest, GermanyGrunwald et alYear1996 1998 2000 2002 2004 2006Water flux20040060080010001200precipitation, mm/yevaporation, mm/yESPM 129 BiometeorologyDecadal Variation in Evaporation11/16/20126Plynlimon, WalesYear1970 1975 1980 1985 1990 1995 2000 2005 2010Evaporation (mm y-1)200300400500600700800900grassland conifer forest Marc and Robinson, 2007 HESSStand Age also affects differences between ET of forest vs grasslandESPM 129 BiometeorologyESPM 129 BiometeorologyDecline in Long Term Pan Evaporation..Shouldn’t the Hydrological Cycle Be Accelerating with Global Warming?11/16/20127ESPM 129 BiometeorologyDecline in Pan Evaporation is attributed toGlobal Dimming, reduction of sunlightGlobal Stilling, reduction in wind speedPan Evaporation measures Atmospheric DemandActual Evaporation depends on Supply and DemandIn Semi-Arid Environments, Trends in Pan ET are not a good indicator in Trends in ET, where Pan Evaporation and ET are complementaryBudyko Curve, Fluxnet dataRn/(ppt)01234Ea/ppt0.00.20.40.60.81.01.21.4Choudhury ModelClassic View, The Budyko Curve with Evaporation Flux MeasurementsEvap Demand >>PrecipitationPrecipitation >>Evaporation, whichIs energy limitedDefines Bounds, But Many Sources of Variance RemainX and Y are AutoCorrelated, through pptESPM 129 Biometeorology11/16/20128FLUXNET Sitess/(s+)Rnet (MJ m-2 y-1)0 500 1000 1500 2000 2500LE (MJ m-2 y-1)05001000150020002500r2 = 0.89Annual Sums of Latent Energy Scales with Equilibrium Energy, in a Saturating FashionESPM 129 BiometeorologyForestsppt (mm y-1)0 1000 2000 3000 4000 5000ET (mm y-1)05001000150020002500Coefficients:b[0] 108.8b[1] 0.464r ² 0.756Annual Precipitation explains 75% of the Variation in Water Lost Via Forest Evaporation, GloballyAbout 46% of Annual Precipitation to Forests, Globally, is Evaporated to the AtmosphereESPM 129 Biometeorology11/16/20129ppt (mm/y)200 400 600 800 1000ET (mm/y)2004006008001000grassland: ET +/- 87 mm/y; ppt +/- 170 mm/yoak savanna: ET +/- 61 mm/ySmall Inter-Annual Variability in ET compared to PPTIn Semi-Arid Regions, Most ET is lost as Precipitation ESPM 129 BiometeorologyMediterranean oaksppt (mm y-1)0 200 400 600 800 1000 1200 1400ET (mm y-1)0100200300400500600Evergreen, FranceEvergreen, PortugalEvergreen, ItalyDeciduous, CaliforniaDeciduous, ItalyMaximum ET is Capped (< 500 mm/y) Near Lower Limit of Mediterranean PPTBaldocchi et al Ecol Applications, 2010ESPM 129 Biometeorology11/16/201210ESPM 129 BiometeorologyDoes Biodiversity affect Evaporation?ESPM 129 BiometeorologyBiodiversity and Evaporation on Annual Time ScalesNumber of Species012345678LE/Rn0.00.20.40.60.81.01.2Coefficients: b[0] 0.592 b[1] -0.0316 r ² 0.12611/16/201211AtmosphericradiativetransferCanopy photosynthesis,Evaporation, Radiative transferSoil evaporationBeam PARNIRDiffuse PARNIRAlbdeo‐>Nitrogen ‐> Vcmax, JmaxLAI, Clumping‐> canopy radiative transferdePury & Farquhar two leaf Photosynthesis modelRnetSurface conductancePenman‐Monteithevaporation modelRadiation at understorySoil evaporationshadesunlitBESS, Breathing-Earth Science SimulatorESPM 129 BiometeorologyLessons Learned from the CanOak Model25+ years of Developing and Testing a Hierarchy of Scaling Models with Flux Measurements at Contrasting Oak Woodland Sites in Tennessee and CaliforniaWe Must:• Couple Carbon and Water Fluxes• Assess Non-Linear Biophysical Functions with Leaf-Level Microclimate Conditions• Consider Sun and Shade fractions separately• Consider effects of Clumped Vegetation on Light Transfer• Consider Seasonal Variations in Physiological Capacity of Leaves and Structure of the Canopy11/16/201212Necessary Attributes of Global Biophysical ET Model:Applying Lessons from the Berkeley Biomet Class and CANOAK• Treat Canopy as Dual Source (Sun/Shade), Two-Layer (Vegetation/Soil) system– Treat Non-Linear Processes with Statistical Rigor (Norman, 1980s)• Requires Information on Direct and Diffuse Portions of Sunlight– Monte Carlo Atmospheric Radiative Transfer model (Kobayashi + Iwabuchi,, 2008)• Light transfer through canopies MUST consider Leaf Clumping– Apply New Global Clumping Maps of Chen et al./Pisek et al.• Couple Carbon-Water Fluxes for Constrained Stomatal Conductance Simulations– Photosynthesis and Transpiration on Sun/Shade Leaf Fractions (dePury and Farquhar, 1996)– Compute Leaf Energy Balance to compute Leaf Saturation Vapor Pressure and