1 / 9

A Multi-Model Analysis of Aerosol Effects on Clouds Simulated by Global Climate Models

A Multi-Model Analysis of Aerosol Effects on Clouds Simulated by Global Climate Models. Steven Ghan, Minghuai Wang, H. Wang, and K. Zhang Pacific Northwest National Laboratory D. Neubauer, U. Lohmann, and S. Ferrachat ETH T. Takamura Kyushu University. AeroCom.

krohn
Télécharger la présentation

A Multi-Model Analysis of Aerosol Effects on Clouds Simulated by Global Climate Models

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A Multi-Model Analysis of Aerosol Effects on Clouds Simulated by Global Climate Models Steven Ghan, Minghuai Wang, H. Wang, and K. Zhang Pacific Northwest National Laboratory D. Neubauer, U. Lohmann, and S. Ferrachat ETH T. Takamura Kyushu University

  2. AeroCom • An open international initiative of scientists interested in the advancement of understanding of the global aerosol and its impact on climate • Protocols for standardized diagnostics from global aerosol models • Use of surface, aircraft and satellite observations of the aerosol to evaluate simulations • Use of common emissions • Special experiments designed to focus on specific aerosol effects on climate • We are leading an AeroCom study focusing on aerosol effects on clouds

  3. Aerosol shortwave indirect forcing (SWAIE)* vs change in shortwave cloud forcing (dSWCF) *Ghan, Atmos. Chem. Phys. (2013)

  4. Factorization ΔR: aerosol indirect forcing R: cleansky shortwave cloud forcing τ: cloud optical depth Nd: cloud droplet number L: liquid water path re: droplet effective radius CCN: CCN at 1 km (0.1% supersaturation)

  5. Factorization: ΔR dR: AIE R: cleansky shortwave cloud forcing tau: cloud optical depth Nd: cloud droplet number CCN: CCN concentration

  6. Factorization: dlntau/dlnNd tau: cloud optical depth Nd: cloud droplet number CCN: CCN concentration LWP: liquid water path

  7. Spop vs. dlnLWP/dlnCCN Over ocean (Wang et al., 2012, GRL) Spop=-dlnPOP/dlnAI

  8. Conclusions • Constraints on sensitivity of LWP to aerosol are helpful • Sensitivity of droplet number to CCN also contributes to uncertainty in indirect effects • Examination of results from other models will fill out the exploration of parameter space

  9. THANKS!

More Related