The impact of long-term memory on the climate response to greenhouse gas emissions

Abstract

Global warming exerts a strong impact on the Earth system. Despite recent progress, Earth System Models still project a large range of possible warming levels. Here we employ a generalized stochastic climate model to derive a response operator which computes the global mean surface temperature given specific forcing scenarios to quantify the impact of past emissions on current warming. This approach enables us to systematically separate between the “forcing-induced direct” and the “memory-induced indirect” trends. Based on historical records, we find that the direct-forcing-response is weak, while we attribute the major portion of the observed global warming trend to the indirect-memory responses that are accumulated from past emissions. Compared to CMIP6 simulations, our data-driven approach projects lower global warming levels over the next few decades. Our results suggest that CMIP6 models may have a higher transient climate sensitivity than warranted from the observational record, due to them having larger long-term memory than observed.

Separating Anthropogenically‐ and Naturally‐Caused Temperature Trends: A Systematic Approach Based On Climate Memory Analysis

“…This is reasonable for temperatures as discussed in Yuan et al. (2022), where a proportional relationship between the trend of effective anthropogenic radiative forcings and the trend of ɛ ( t ) extracted from GMST was revealed. Accordingly, the abovementioned steps depict a roadmap for removing the long‐lasting impacts of anthropogenic forcings on temperatures, as well as quantifying anthropogenic and natural trends in a given temperature timeseries.…”

“…By feeding the detrended ɛ ( t ) back to FISM, one can separate the long‐lasting impacts of anthropogenic forcings on temperatures. Note that in this way we assumed that natural forcings or internal variabilities will not induce remarkable long‐term trends in ɛ ( t ), and this is justified by the recently revealed proportional relationship between the trend of effective anthropogenic radiative forcings and the trend of ɛ ( t ) (Yuan et al., 2022). Moreover, compared to the anthropogenic forcing, the trend of historical solar forcing is very weak (Figure S17 in Supporting Information ), which may not lead to big impacts on the findings if it is ignored.…”

Grand Challenges in Earth Science: The Weather–Climate–Society Nexus over Northeast Asia

“…Large uncertainties in climate and Earth system models were discussed from the perspective of interactions with internal variability and external forcing (Chen et al 2020;Gong et al 2022). A recent study using a fractional integral statistical model was introduced to capture a realistic warming signal to bypass "hot model" problems that may be attributed to overestimated memory of the Earth climate system (Yuan et al 2022).…”