Band‐by‐Band Contributions to the Longwave Cloud Radiative Feedbacks

Huang, X., X. Chen, and Q. Yue (2019), Band‐by‐Band Contributions to the Longwave Cloud Radiative Feedbacks, Geophys. Res. Lett., 46, 6998-7006, doi:10.1029/2019GL083466.
Abstract: 

Cloud radiative feedback is central to our projection of future climate change. It can be estimated using the cloud radiative kernel (CRK) method or adjustment method. This study, for the first time, examines the contributions of each spectral band to the longwave (LW) cloud radiative feedbacks (CRFs). Simulations of three warming scenarios are analyzed, including +2 K sea surface temperature, 2 × CO2, and 4 × CO2 experiments. While the LW broadband CRFs derived from the CRK and adjustment methods agree with each other, they disagree on the relative contributions from the far‐infrared and window bands. The CRK method provides a consistent band‐by‐band decomposition of LW CRF for different warming scenarios. The simulated and observed short‐term broadband CRFs for the 2003–2013 period are similar to the long‐term counterparts, but their band‐by‐band decompositions are different, which can be further related to the cloud fraction changes in respective simulations and observation. Plain Language Summary We studied how the cloud change in response to surface temperature change leads to the changes of radiation at the top of the atmosphere (referred to as cloud radiative feedback) over different frequency ranges in the longwave (referred to as spectral bands). While different methods can provide a similar estimate of broadband cloud radiative feedbacks, the decomposition to different longwave spectral bands can be different from one method to another. The cloud radiative kernel method can provide a more consistent band‐by‐band decomposition of the longwave cloud radiative feedback for different warming scenarios. The decomposition for cloud radiative feedback derived from the warming experiments is considerably different from that derived from decadal‐scale observations and simulations. Such differences in spectral band decomposition can be related to the specific cloud fraction changes for different types of clouds defined with respect to cloud top pressure and cloud opacity.

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