event

Spectrum: An Underutilized Dimension in Climate Observations and Model Diagnostics

Primary tabs

EAS Spring 2018 Seminar Series Presents: Dr. Xianglei Huang, University of Michigan

While broadband flux has been widely used in climate studies, its integrand, the spectral flux, has not been fully utilized in climate studies. An important trait of spectral flux is that they can reveal compensating biases, which cannot be revealed by broadband diagnostics alone. 

After giving a couple of examples corroborating this trait of spectral flux, I will introduce an algorithm that can derive such spectral flux over the entire longwave spectrum from currently available satellite observations. 

Using three GCMs as case studies, I will then show the application of the such spectral flux and spectral cloud radiative effects in GCM evaluations. Next, a spectral radiative kernel technique is described, which allows us to obtain spectral details of longwave radiative feedbacks without performing time-consuming partial radiative perturbation calculation. The spectral radiative kernel makes it possible to derive spectral details of longwave feedbacks for CMIP3 and CMIP5 models. 

I will describe what insight can be gleaned from such spectral radiative feedback analysis, further highlighting the unique merit of spectral dimension in the climate studies. 

At last, I will provide my perspectives on the synergy between current satellite observations and future missions such as FORUM by ESA and PREFIRE by NASA for this direction of research.

Status

  • Workflow Status:Published
  • Created By:nlawson3
  • Created:12/21/2017
  • Modified By:nlawson3
  • Modified:03/21/2018

Keywords