The research begins by stating that the current stance in climate studies, which is manifested in the first decade of the 21st century exhibiting slower or muted warming compared to the last two decades of the 20th century. The majority of studies focus on the radiative exchange between the Earth’s temperature and outer space, but the authors emphasize that such an approach can easily dismiss individual feedback responses (Hu et al., 2017). The main reason is that internal non-radiative processes, such as oceanic heat storage, evaporation heat fluxes, and convective atmospheric energy transport, are not fully included in the conventional forms of the climate analysis (Hu et al., 2017). The researchers integrate the process-based decomposition method, which is essentially focused on the climate feedback response analysis method (CFRAM).
The given approach allows authors to avoid the major pitfall of running the climate model twice, where the original climate system is reflected in the virtual climate system, which creates improper compensating effects from collective feedbacks (Hu et al., 2017). The main finding is that CO2 is the largest contributor between the two mentioned periods, and oceanic heat storage leads to high warming rates in tropical oceans. In addition, Arctic polar warming amplification (PWA) is primarily caused by atmospheric dynamic feedbacks and ice-albedo.
However, it is important to note that the research process of decomposition analysis possesses a number of limitations. The methodology does not factor-in aerosol forcings properly, which leads to errors. Time means fields are based on long-term mean clouds, whereas fluxes are derived from instantaneous clouds. Therefore, the research fails to correctly analyze the longitudinal differences between the mean values. In addition, cloud feedback is overestimated by offline calculations. The authors partially remove such errors, but they still influence the decomposition process (Hu et al., 2017). Lastly, ERA-Interim data can be another course of error due to the lack of certainty in atmospheric components.
Hu, X., Li, Y., Yang, S., Deng, Y., & Cai, M. (2017). Process-based decomposition of the decadal climate difference between 2002-13 and 1984-95. Journal of Climate, 30(12), 4373-4393.