Spectral kernel approach to study radiative response to interannual variability of climate variables

The radiative kernel approach provides a simple way to separate the radiative response to different climate parameters and to decompose the feedback into radiative and climate response components. Therefore, it enables a better understanding of the underlying physical processes responsible for the feedback. Based on the nearly six years of satellite (CERES/MODIS) data, we calculated and analyzed the solar spectral reflectance kernels for various climate parameters in different latitude regions over global. The kernel nonlinearity error in the calculation is also tested. This error varies a lot depending on climate parameter, wavelength, surface, and solar elevation; it could be large in some absorption bands for some parameters but is negligible in most conditions. The spectral kernels are used to calculate the different radiative responses from different climate parameter changes in different latitudes. The results show that the radiative response is sensitive to snow coverage change in high latitude land and to sea ice concentration in polar ocean. In low latitude regions, the radiative response is mainly contributed by cloud property changes, especially cloud fraction and optical depth. The large cloud height effect is limited in the absorption bands and particle size effect is mainly in the near infrared spectrum. The kernel approach is also tested by direct comparison with SCIAMACHY measurement. The monthly mean interannual variability of spectral reflectance based on the kernel technique is consistent with satellite observation.