A Decomposition of the Atmospheric and Surface Contributions to the Outgoing Longwave Radiation

Abstract

The outgoing longwave radiation (OLR), which consists of the thermal radiation from both the atmosphere and surface, is of critical importance to the Earth radiation energy budget. To understand the global OLR distribution, it is important to quantify the varying atmospheric and surface contributions. In this work, we present such a quantification using radiative transfer computations based on global reanalysis atmospheric data. By dissecting the OLR simulated following the radiative transfer equation, we quantitatively measure the layer‐wise atmospheric contributions to OLR and compare it to the surface contribution in different spectral bands. One focus of this study is on the OLR in the far‐infrared (FIR), for which new satellites are expected to provide unprecedented measurements. We find that around 45% of the global mean OLR is radiated in the FIR and in polar regions the FIR contribution can increase to 60%. Our vertical decomposition of OLR discloses that although the atmospheric contribution generally surpasses the surface contribution, the enhanced FIR contribution in the polar regions mainly results from a relatively stronger surface (as opposed to atmospheric) contribution. This is allowed by the opening of the atmospheric window in the FIR in these extremely dry regions. Our analysis also reveals that the tropopause layer makes a minimum contribution to the OLR, which may be a unique spectroscopic feature of the Earth atmosphere. Clouds are found to reduce the atmospheric contribution in the FIR while enhancing it in the mid‐infrared.

Diagnosing the Radiation Biases in Global Climate Models Using Radiative Kernels

“…Interestingly, these positive non‐cloud biases tend to be compensated by cloud biases of an opposite sign, which in some models results in a seemingly good all‐sky radiation budget (see Table 1 and Table S1 in Supporting Information ) as noted above. In addition, it is also interesting to notice that the surface temperature caused radiation biases are mostly noticeable in the Polar region, in agreement with the recognition that the atmosphere is the most transparent to surface emission in these regions (e.g., Feng et al., 2023; H. Huang & Huang, 2022). It ought to be noted that the biases in these geophysical variables can be detected by simply comparing GCM simulations to the observations, although their impacts on the radiation balance of the model would not be conveniently quantified without the aid of the kernels.…”

“…Interestingly, these positive non-cloud biases tend to be compensated by cloud biases of an opposite sign, which in some models results in a seemingly good all-sky radiation budget (see Table 1 and Table S1 in Supporting Information S1) as noted above. In addition, it is also interesting to notice that the surface temperature caused radiation biases are mostly noticeable in the Polar region, in agreement with the recognition that the atmosphere is the most transparent to surface emission in these regions (e.g., Feng et al, 2023;H. Huang & Huang, 2022).…”

Band-by-band spectral radiative kernels based on the ERA5 reanalysis

“…35 , evidencing that the ERA5 spectral kernels generated here capture the major spectral features of the radiative sensitivity. Moreover, the TOA kernels resemble the vertically decomposed atmospheric contribution to OLR as shown in Huang and Huang 29 , corroborating the fact that the OLR in different bands mostly originates from different vertical layers.…”

“…A number of studies have demonstrated how climate changes can be better detected by radiation spectral changes 15 – 22 and can be attributed based on the distinctive spectral signatures of radiative forcing and feedback 19 , 23 , 24 . A growing interest especially worth noting is that in the far-infrared (FIR) spectrum, which is crucial for the Earth energy budget 25 – 29 and has motivated ongoing development of several satellites 26 – 28 . Spectrally decomposed kernels would facilitate the dissection of Earth radiation budget, including that in the FIR, and help identify the major geophysical variables accounting for the radiation variability.…”

How a Stable Greenhouse Effect on Earth Is Maintained Under Global Warming

“…Observations and advanced Earth system models have shown that the Earth's climate system is relatively stable, despite longwave spectra being nearly opaque (only 17% of the global‐mean surface thermal emission is transmitted through the clear‐sky atmosphere to space (Costa & Shine, 2012; Huang & Huang, 2022, Figure S1). This stability is quantified by the clear‐sky longwave feedback parameter, defined as the change in OLR per degree of surface warming.…”