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Climate Modeling. Inez Fung Dept of Earth and Planetary Science Dept of Environmental Science, Policy and Management UC Berkeley. Atmosphere. momentum. mass. energy. water vapor. convective mixing. Ocean. momentum. mass. energy. salinity. Earth’s Energy Balance, with GHG. Sun.
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Climate Modeling Inez Fung Dept of Earth and Planetary Science Dept of Environmental Science, Policy and Management UC Berkeley
Atmosphere momentum mass energy water vapor convective mixing
Ocean momentum mass energy salinity
Earth’s Energy Balance, with GHG Sun Earth 100 70 30 20absorbed by atm 23 7 114 95 CO2, H2O, GHG 50 absorbed by sfc
Climate Processes • Radiative transfer: solar & terrestrial • phase transition of water • Convective mixing • cloud microphysics • Evapotranspirat’n • Movement of heat and water in soils
Climate Feedbacks Decrease snow cover; Decrease reflectivity of surface Increase absorption of solar energy Evaporation from ocean, Increase water vapor in atm Enhance greenhouse effect Increase cloud cover; Decrease absorption of solar energy Warming
Observed Warming greatest at high latitudes Amplification of warming due to decrease of albedo (melting of snow and ice)
Will cloud cover increase or decrease with warming? [models: decrease; warm air can hold more moisture; +ve feedback] Saturation Vapor Pressure (mb) Temperature (K) C A B + water vapor + longwave abs Warming liquid B A C + water vapor + cloud cover + longwave abs - shortwave abs A vapor 275 280 285 290 295 300
“Externally Forced” climate variability: Milankovitch Cycles (Orbital Variations) 120,000 yr Temperature Departure (K) Last Glacial Max Co-Variations of CO2and Climate
“Internal” Variability of the Climate System 1885 • e.g. • El-Nino / Southern Oscillation • Instability of the air-sea system in the equatorial pacific • Irregular • 2-7 year 1995
Climate Forcing: expressed as a change in radiative heating (W/m2) at surface for a given change in trace gas composition or other change external to the climate system Cumulative climate forcing since 1800 Hansen PNAS 2001
Ship Tracks:- more cloud condensation nuclei- smaller drops- more drops- more reflective- D energy balance
Numerical Weather Prediction ( ~ days) Initial Conditions t = 0 hr Prediction t = 6 hr 12 18 24 • 1st Numerical Weather Prediction Experiment • Charney, Fjortoft and von Neumann (1950, Tellus) • Barotropic Vorticity Eqn • ENIAC computer (10 word memory) • 1 layer over N America • Now: Operational forecasts (model validation in ~days); • require model + initial conditions (obs atm)
Seasonal Climate Prediction ( ~ months) ( El – Nino Southern Oscillation ) {Prediction} t = 1 mo 2 3 { Initial Conditions} Atm + Ocn t = 0 • Coupled atmosphere-ocean instability • Require observations of initial states of both atm & ocean, • esp. Equatorial Pacific • Cane & Zebiak ( 1986, 1987) • {Ensemble} of forecasts • Forecast statistics (mean & variance) – probability • Now – experimental forecasts (model testing in ~months)
Climate Models Capture Magnitude and Timing of Recent Warming Meehl et al. 2006; Hansen et al. 2005
Fig. 3. Height anomalies at 500 hPa (gpm) for the 1995 Chicago heat wave (anomalies for 13 to 14 July 1995 from July 1948 to 2003 as base period), from NCEP/NCAR reanalysis data (A) and the 2003 Paris heat wave (anomalies for 1 to 13 August 2003 from August 1948 to 2003 as base period), from NCEP/NCAR reanalysis data (B) G. A. Meehl et al., Science 305, 994 -997 (2004) Published by AAAS
Fig. 4. Height anomalies at 500 hPa (gpm) for events that satisfy the heat wave criteria in the model in future climate (2080 to 2099) for grid points near Chicago (A) and Paris (B), using the same base period as in Fig G. A. Meehl et al., Science 305, 994 -997 (2004) Published by AAAS
21stC warming depends on CO2 increase 21thC “Business as usual”: CO2 increasing 380 to 680 ppmv 20thC stabilizn: CO2 constant at 380 ppmv for the 21stC Meehl et al. (Science 2005)