青藏高原表面温度对温室气体增加的响应及其不确定性:基于CMIP6的研究

Response of Tibetan Plateau surface temperature to greenhouse gas increase and its uncertainty:a study based on CMIP6

近几十年来,青藏高原呈现显著增暖趋势,准确预估青藏高原未来气候变化对农业、生态系统、社会经济和人类生存与发展有着重要的科学意义。本研究基于CMIP6模式中18个模式在CO_(2)浓度突然4倍(abrupt-4×CO_(2))强迫下的实验结果,运用气候反馈响应分析方法(CFRAM),研究温室气体强迫下青藏高原增暖响应、进行归因分析并讨论其模式间差异的来源。结果表明,高原地表增暖在很大程度上是温室气体强迫和正的水汽反馈造成的,并通过反照率反馈、云反馈以及地表热存储过程进一步放大,表面感热和潜热过程抑制了升温的幅度。其中,反照率反馈是造成青藏高原变暖比全球陆面平均增暖更强烈的原因。高原增暖响应的不确定性主要由云反馈贡献,其次是反照率反馈以及水汽反馈,但被感热和潜热过程削减。

The Tibetan Plateau,often referred to as the“Roof of the World”and the“Third Pole”,is of considerable importance due to its high altitude,vast scale,and complex terrain,rendering it a pivotal element in global climate dynamics.In the last five decades,the plateau has witnessed a pronounced warming trend,with temperatures increasing at a rate twice that of the global average.Precise forecasting of future climate change in this region is paramount for various sectors,including agriculture,ecosystems,and socio-economic development.This study employs data from an experiment involving 18 models in the CMIP6 model,wherein the CO_(2) concentration suddenly quadruples(abrupt-4×CO_(2)),to investigate the response of the Tibetan Plateau to greenhouse gas forcing.Specifically,the study focuses on feedback processes using the climate feedback response analysis method(CFRAM).The findings reveal that surface warming on the plateau is primarily driven by greenhouse gas forcing and positive water vapor feedback,further amplified by albedo and cloud feedback.Processes such as surface heat storage,sensible heat,and latent heat play roles in moderating temperature increases.Cloud feedback emerges as a significant source of uncertainty in plateau warming response,followed by albedo and water vapor feedbacks,while sensible and latent heat processes aid in mitigating this uncertainty.Variations in projected warming,particularly in central-eastern and southern regions of the plateau,stem from inter-model differences in surface heat storage and atmospheric dynamics.Enhanced parameterization to surface albedo and cloud cover is identified as an effective strategy to alleviate spatial uncertainty in model predictions of regional warming across the Tibetan Plateau.The spatial distribution of uncertainty in feedback processes varies,with maximum standard deviations observed in different regions for each process,corresponding to areas projected to experience significant warming.In summary,although greenhouse gas forcing models generally exhibit consistent trends across the Tibetan Plateau,variations in feedback processes and regional dynamics highlight the necessity for enhanced parameterization and resolution in climate models to improve predictions in this pivotal region.