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Global Climate Response to Anthropogenic Aerosol Indirect Effects

Global Climate Response to Anthropogenic Aerosol Indirect Effects. John H. Seinfeld California Institute of Technology AMS Annual Meeting January 13, 2009. Anthropogenic Emissions. Climate Sensitive Emissions. Emissions. Aerosols. Aerosols. Climate (radiation, temp., winds, clouds).

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Global Climate Response to Anthropogenic Aerosol Indirect Effects

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  1. Global Climate Response to Anthropogenic Aerosol Indirect Effects John H. Seinfeld California Institute of Technology AMS Annual Meeting January 13, 2009

  2. Anthropogenic Emissions Climate Sensitive Emissions Emissions Aerosols Aerosols Climate (radiation, temp., winds, clouds) Climate (radiation, temp., winds, clouds) Offline vs. Online Approach in Global Models • Online aerosols • Compute aerosols during the climate simulation • Offline aerosols • Obtain aerosol mass and properties a priori

  3. Time Time Transient vs. Equilibrium Climate • Transient Climate • Start from initial state (e.g. pre-industrial) • Specified annually varying forcing changes • Temporal evolution of the response is of interest Forcing (Anth. CO2 levels) Response (Ts)

  4. DTs Time Time Transient vs. Equilibrium Climate • Transient Climate • Start from initial state (e.g., pre-industrial) • Specified annually varying forcing • Temporal evolution of the response is of interest Forcing (Anth. CO2 levels) Response (Ts)

  5. Time Time Transient vs. Equilibrium Climate • Equilibrium Climate • Forcing is constant during the course of simulation • Integrate until equilibrium is reached • Relative changes in final response vs. changes in forcing Forcing (Anth. CO2 levels) Response (Ts)

  6. DF(2-1) DTs,(2-1) Time Time Transient vs. Equilibrium Climate • Equilibrium Climate • Forcing is constant during the course of simulation • Integrate until equilibrium is reached • Relative changes in final response vs. changes in forcing Forcing (Anth. CO2 levels) Response (Ts)

  7. The CACTUS Unified Model Chemistry, Aerosol, and Climate: Tropospheric Unified Simulation (CACTUS) [ Liaoet al., 2004]

  8. The CACTUS Unified Model Chemistry, Aerosol, and Climate: Tropospheric Unified Simulation (CACTUS) [ Liao et al., 2004]

  9. The CACTUS Unified Model Chemistry, Aerosol, and Climate: Tropospheric Unified Simulation (CACTUS) [ Liaoet al., 2004]

  10. The CACTUS Unified Model Chemistry, Aerosol, and Climate: Tropospheric Unified Simulation (CACTUS) (no AIE) [ Liaoet al., 2004]

  11. Aerosol Indirect Climatic Effects Cloud Albedo Effect (–0.2 to –1.9 W m-2) Cloud Lifetime Effect (Clean) (Polluted) Total AIE forcing: –0.3 to –2.4 W m-2

  12. Aerosol Indirect Climatic Effects Size-resolving microphysics? Parameterization? (Clean) (Polluted)

  13. Aerosol Indirect Climatic Effects using GISS III Chen, W.-T., H. Liao, A. Nenes, P. Adams, and J. H. Seinfeld (JGR submitted)

  14. Derive Aerosol-Nc Correlations • TOMAS microphysics model within GISS II’ • Conserve both aerosol mass and number concentrations • Present-day sulfate and sea salt (internal mixing) • Derive CCN spectra for each grid

  15. Derive Aerosol-Nc Correlations • TOMAS microphysics model within GISS II’ • Conserve both aerosol mass and number concentrations • Present-day sulfate and sea salt (internal mixing) • Derive CCN spectra for each grid • With the predicted CCN spectra, apply the CCN activation parameterization inFountoukis and Nenes [2005] • In each grid, vary aerosol mass between 0.05 and 5 times the average concentration, and compute the corresponding Nc

  16. Derive Aerosol-Nc Correlations • TOMAS microphysics model within GISS II’ • Conserve both aerosol mass and number concentrations • Present-day sulfate and sea salt (internal mixing) • Derive CCN spectra for each grid • With the predicted CCN spectra, apply the CCN activation parameterization inFountoukis and Nenes [2005] • In each grid, vary aerosol mass between 0.05 and 5 times the average concentration, and compute the corresponding Nc • Fit Nc with the molar concentrations of total soluble ions (mi), (formulation proposed by Boucher and Lohmann [1995]) • Coefficients A and B are computed for each grid cell and for each month to account for geographic and seasonal variations of aerosol-cloud interactions

  17. Derive Offline Nc for Climate Simulations • Use aerosol mass predicted by the Unified Model; apply the above correlations to derive consistent offline Nc • Use sea salt for 20C in all conditions • When converting aerosol mass to soluble ions: • sulfate, ammonium, and nitrate are fully soluble, • POA and SOA are 80% soluble, • BC is insoluble • Set a lower limit of 20 cm–3 for Nc; interpolate from 9 to 23 layers

  18. Modify Warm Stratiform Clouds in GISS III • In standard GISS III,cloud droplet size (rv) and autoconversion rates of stratiform clouds only depend on liquid water density (m) and liquid water mixing ratio (ql), not explicitly related to Nc

  19. Modify Warm Stratiform Clouds in GISS III • In standard GISS III,cloud droplet size (rv) and autoconversion rates of stratiform clouds only depend on liquid water density (m) and liquid water mixing ratio (ql), not explicitly related to Nc

  20. Adjustment to the New Autoconversion Rate • For the same liquid water density, K&K >> Sundqvistparameterization (20 to100 x) • Increase in liquid water path and “drift” toward a cooler climate compare to standard GISS III

  21. Adjustment to the New Autoconversion Rate • For the same liquid water density, K&K >> Sundqvist parameterization (20 to100 x) • Increase in liquid water path and “drift” toward a cooler climate compare to standard GISS III • Proper adjustment to the new autoconversion rates is needed • Scale the K&K autoconversion with a tuning parameter (): • Testing values between 10 and 100. • For each value of, carry out one year of simulation with modified stratiform cloud scheme; diagnose the TOA radiation fluxes • Compare to standard GISS III for present day equilibrium climate • Optimum value 40

  22. Equilibrium Simulations with GISS III • Two 100- year equilibrium simulations using standard GISS III • Use the final year from each simulation as I.C.

  23. Equilibrium Simulations with GISS III • Two 100- year equilibrium simulations using standard GISS III • Use the final year from each simulation as I.C. • Four 20-year equilibrium simulations using modifiedGISS III • Perturbations only in Nc (PI to 20C and 20C to 21C) • Perturbations in GHG, ADE, and Nc (20C to 21C)

  24. Equilibrium Simulations with GISS III • Two 100- year equilibrium simulations using standard GISS III • Use the final year from each simulation as I.C. • Four 20-year equilibrium simulations using modifiedGISS III • Perturbations only in Nc (PI to 20C and 20C to 21C) • Perturbations in GHG, ADE, and Nc (20C to 21C)

  25. Perturbation of Nc -- from PI to 20C Stream function • Large Nc increase and negative TOA SW cloud forcing over 30–60oN (especially in JJA) • TOA net cloud forcing = –1.32 W m–2 • Ts = –0.95 K; stronger cooling in NH • ITCZ: southward shift • Precip = –3% Nc at surface Nc TOA CF Ts Precip.

  26. Perturbation of Nc -- from 20C to 21C Stream function • Nc increase is smaller than perturbation from PI to 20C • Nc increase peaks around 30oN (DJF > JJA) • Ncdecreases in northern high latitudes owing to predicted sulfate reduction • TOA net cloud forcing = –0.42 W m–2 • Ts = –0.25 K • Precip. = –1% Nc at surface Nc TOA CF Ts Precip.

  27. Perturbation of GHG, ADE and AIE from 2000 to 2100 • Patterns dominated by GHG warming • Ts = +4.61 K; amplified warming in the Arctic • Broadened Hadley Cell with strengthened ascending branches in convection zone near the Equator • Precip. = +8% • Stratiform precipitation decreases over 45oS–45oN Ts (Precip.-Evap.) Strat. Precip.

  28. Effects of Including AIE in GISS III Modified GISS III (GHG+ADE+AIE) Standard GISS III (GHG+ADE) • Similar change in Ts (+4.61 K vs. +4.88 K) and circulation • Smaller increase in total precip. (+8% vs. +11%) • Decrease vs. increase of stratiform precip. (–3% vs. +5%), especially in lower latitudes Ts (Precip.-Evap.) Strat. Precip.

  29. Summary • Perturbation of Nc from PI to 20C • Large Nc increase over 30–60oN • AIE forcing = –1.81 W m-2, Ts = –0.95 K, Precip. = –3.0 % • Southward shift of ITCZ • Perturbation of Nc from 20C to 21C • Smaller Nc increase (peaks at 30oN) • AIE forcing = –0.84 W m-2, Ts = –0.25 K, Precip. = –1.0 % • No significant change in circulation • Compare modified version (GHG+ADE+AIE) with standard version (GHG+ADE) • Decrease in stratiform precip.; smaller precipitation increase • Similar change in Ts and circulation

  30. Stepwise vs. Fully Coupled Simulations • The previous studies on ADE and AIE adopted a “stepwise” method • No feedback of climate on the offline aerosols and Nc • Liao et al. [2008] (submitted) • Study the effects of full coupling on predicted future climate and future O3 and aerosols

  31. Stepwise vs. Fully Coupled Simulations • The previous studies on ADE and AIE adopted a “stepwise” method • No feedback of climate on the offline aerosols and Nc • Liao et al. [2008] (submitted) • Study the effect of full coupling on predicted future climate and future O3 and aerosols • The CACTUS Unified Model • SRES A2 scenario: include GHG, tropospheric O3, and aerosols • ADE only, no AIE • Equilibrium simulations: compare results between “stepwise” and “fully coupled” methods

  32. Stepwise vs. Fully Coupled Simulation • Effects of full coupling on predicted aerosols in 21C • Reductions of all aerosol burdens in mid to high latitudes in NH • Increases in JJA aerosol burdens over populated and biomass burning areas • Increases in aerosol burdens over the topics

  33. Stepwise vs. Fully Coupled Simulation • Effects of full coupling on predicted aerosols in 21C • Reductions of all aerosol burdens in mid to high latitudes in NH • Increases in JJA aerosol burdens over populated and biomass burning areas • Increases in aerosol burdens over the topics • Effects of full coupling on predicted climate in 21C • A stronger global warming (an additional 0.4 K increase) • Weaker convection and precipitation

  34. Stepwise vs. Fully Coupled Simulation • Effects of full coupling on predicted aerosols in 21C • Reductions of all aerosol burdens in mid to high latitudes in NH • Increases in JJA aerosol burdens over populated and biomass burning areas • Increases in aerosol burdens over the topics • Effects of full coupling on predicted climate in 21C • A stronger global warming (an additional 0.4 K increase) • Weaker convection and precipitation • Positive feedback between ADE forcing and aerosol burdens • aerosol concentrations  • boundary-layer height and wet deposition of aerosols  • aerosol concentrations in lower tropospheric 

  35. Climate & Hydrological Sensitivities (20C to 21C)

  36. Climate & Hydrological Sensitivities (20C to 21C)

  37. Acknowledgement • NASA IDS • US EPA

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