An 88 ka temperature record from a subtropical lake on the southeastern margin of the Tibetan Plateau (third pole): new insights and future perspectives

Reconciling East Asia's mid-Holocene temperature discrepancy through vegetation-climate feedback

The term "Holocene temperature conundrum" refers to the inconsistencies between proxy-based reconstructions and transient model simulations, and it challenges our understanding of global temperature evolution during the Holocene. Climate reconstructions indicate a cooling trend following the Holocene Thermal Maximum, while model simulations indicate a consistent warming trend due to ice-sheet retreat and rising greenhouse gas concentrations. Various factors, such as seasonal biases and overlooked feedback processes, have been proposed as potential causes for this discrepancy. In this study, we examined the impact of vegetation-climate feedback on the temperature anomaly patterns in East Asia during the mid-Holocene (∼6 ka). By utilizing the fully coupled Earth system model EC-Earth and performing simulations with and without coupled dynamic vegetation, our objective was to isolate the influence of vegetation changes on regional temperature patterns. Our findings reveal that vegetation-climate feedback contributed to warming across most of East Asia, resulting in spatially diverse temperature changes during the mid-Holocene and significantly improved model-data agreement. These results highlight the crucial role of vegetation-climate feedback in addressing the Holocene temperature conundrum and emphasize its importance for simulating accurate climate scenarios.

The Holocene temperature conundrum answered by mollusk records from East Asia

Seasonal biases (the warm-season contribution) of Holocene mean annual temperature (MAT) reconstructions from geological records were proposed as a possible cause of the mismatch with climate simulated temperature. Here we analyze terrestrial mollusk assemblages that best reflect seasonal signals and provide quantitative MAT and four-season temperature records for northern China during the past 20,000 years. The MAT estimated from the seasonal temperatures of a four-season-mean based on mollusks shows a peak during ~9000-4000 years ago, followed by a cooling trend. In general, the contribution of summer and winter temperature to MAT is significantly greater than that of spring and autumn temperatures. The relative contribution of each season varies over time and corresponds roughly with the seasonal insolation in each season. This independent evidence from mollusk records from the mid-latitudes of East Asia does not support the Holocene long-term warming trend observed in climate simulations and the seasonal bias explanation.

Spatiotemporal hysteresis distribution and decomposition of solar activities and climatic oscillation during 1900-2020

Solar radiation is the external driving force of the Earth's climate system. In different spatial and temporal scales, meteorological elements have different responses and lag periods to solar activity (SA), climatic oscillation (CO), geographic factors (GF) and other influencing factors. However, such studies are not abundant and in-depth in the world. To further understand the "solar-climate-water resource" system, this study considers China as the study area and investigates the monthly data of temperature (T) and precipitation (P) during 1900-2020 that were obtained from 3836 grid stations. The strong interaction and lag distribution between T or P with SA and CO were studied and influence weights of SA, CO, and geographical factors (GF) of each grid station were calculated. A multivariate hysteretic decomposition model was established to simulate and quantitatively decompose the periodic lag considering the factors of the earth's revolution. It is found that the strong interaction/lag periods obtained in a long-time scale can be decomposed into several periods shorter than the SA period. The distribution of strong interaction/lag periods is nested with topography and echoes with cities. The underlying surface conditions and urbanization are also important factors affecting the T and P lag. There are two distinct dividing lines in the lag period and influencing factor pattern of T and P. The T dividing line moves through valleys where water or mountain ranges meet, where the gap facilitates monsoon movement across regions, while the P dividing line is a zone of dramatic terrain, where tall mountains block water vapor transport. In the lag trend of T, the northern region of China has the longest lag period, and the lag period of surrounding regions tends to converge to the northern region. The lag period caused by SN in southwest China is larger than that in northwest China, while the lag effect of CO is opposite in the above two regions. The lag trend of P also has the above characteristics, but the difference is that the lag period in central China is the longest.