Uncertainties of ENSO-related Regional Hadley Circulation Anomalies within Eight Reanalysis Datasets

El Nino-Southern Oscillation(ENSO),the leading mode of global interannual variability,usually intensifies the Hadley Circulation(HC),and meanwhile constrains its meridional extension,leading to an equatorward movement of the jet system.Previous studies have investigated the response of HC to ENSO events using different reanalysis datasets and evaluated their capability in capturing the main features of ENSO-associated HC anomalies.However,these studies mainly focused on the global HC,represented by a zonal-mean mass stream function(MSF).Comparatively fewer studies have evaluated HC responses from a regional perspective,partly due to the prerequisite of the Stokes MSF,which prevents us from integrating a regional HC.In this study,we adopt a recently developed technique to construct the three-dimensional structure of HC and evaluate the capability of eight state-of-the-art reanalyses in reproducing the regional HC response to ENSO events.Results show that all eight reanalyses reproduce the spatial structure of HC responses well,with an intensified HC around the central-eastern Pacific but weakened circulations around the Indo-Pacific warm pool and tropical Atlantic.The spatial correlation coefficient of the three-dimensional HC anomalies among the different datasets is always larger than 0.93.However,these datasets may not capture the amplitudes of the HC responses well.This uncertainty is especially large for ENSO-associated equatorially asymmetric HC anomalies,with the maximum amplitude in Climate Forecast System Reanalysis(CFSR)being about 2.7 times the minimum value in the Twentieth Century Reanalysis(20CR).One should be careful when using reanalysis data to evaluate the intensity of ENSO-associated HC anomalies.

China’s Recent Progresses in Polar Climate Change and Its Interactions with the Global Climate System

During the recent four decades since 1980,a series of modern climate satellites were launched,allowing for the measurement and record-keeping of multiple climate parameters,especially over the polar regions where traditional observations are difficult to obtain.China has been actively engaging in polar expeditions.Many observations were conducted during this period,accompanied by improved Earth climate models,leading to a series of insightful understandings concerning Arctic and Antarctic climate changes.Here,we review the recent progress China has made concerning Arctic and Antarctic climate change research over the past decade.The Arctic temperature increase is much higher than the global-mean warming rate,associated with a rapid decline in sea ice,a phenomenon called the Arctic Amplification.The Antarctic climate changes showed a zonally asymmetric pattern over the past four decades,with most of the fastest changes occurring over West Antarctica and the Antarctic Peninsula.The Arctic and Antarctic climate changes were driven by anthropogenic greenhouse gas emissions and ozone loss,while tropical-polar teleconnections play important roles in driving the regional climate changes and extreme events over the polar regions.Polar climate changes may also feedback to the entire Earth climate system.The adjustment of the circulation in both the troposphere and the stratosphere contributed to the interactions between the polar climate changes and lower latitudes.Climate change has also driven rapid Arctic and Southern ocean acidification.Chinese researchers have made a series of advances in understanding these processes,as reviewed in this paper.

Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness

In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis data.Meanwhile,deep learning predictions of sea ice thickness(SIT)have yet to receive ample attention.In this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/observations.These models enable monthly predictions of Arctic SIT without considering the complex physical processes involved.Through comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT anomalies.Regarding the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most cases.The models also demonstrate robust performances in predicting SIT and SIE during extreme events.The effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications.

Specific Relationship between the Surface Air Temperature and the Area of the Terra Nova Bay Polynya,Antarctica

Antarctic polynyas play an important role in regional atmosphere?ice?ocean interactions and are considered to help generate the global deep ocean conveyer belt.Polynyas therefore have a potential impact on the Earth’s climate in terms of the production of sea ice and high-salinity shelf water.In this study,we investigated the relationship between the area of the Terra Nova Bay polynya and the air temperature as well as the eastward and northward wind based on the ERA5 and ERAInterim reanalysis datasets and observations from automatic weather stations during the polar night.We examined the correlation between each factor and the polynya area under different temperature conditions.Previous studies have focused more on the effect of winds on the polynya,but the relationship between air temperature and the polynya area has not been fully investigated.Our study shows,eliminating the influence of winds,lower air temperature has a stronger positive correlation with the polynya area.The results show that the relationship between the polynya area and air temperature is more likely to be interactively influenced.As temperature drops,the relationship of the polynya area with air temperature becomes closer with increasing correlation coefficients.In the low temperature conditions,the correlation coefficients of the polynya area with air temperature are above 0.5,larger than that with the wind speed.

More complex interactions:Continuing progress in understanding the dynamics of regional climate change under a warming climate

Our planet experienced a number of extreme climate events in 2022,including extreme summer heat in the northern hemisphere,droughts in China and Brazil,and floods in Pakistan,South Africa,and Australia.Persistent global warming is believed to be the key factor in these extreme climate events,which were rare in past decades.Understanding the physical dynamics of regional climate change is essential if we are to reliably project such events in a warmer climate.

MOFs在催化有机分子转化中的应用

金属有机框架化合物(MOF),又称多孔性配位聚合物,是有机配体与金属离子自组装而成的一类新型有机-无机杂化多孔材料,是纳米材料的重要组成部分。与其他多孔材料相比,MOFs具有较大的比表面积、高的孔隙率以及结构和性质可调等特性,使其在非均相催化领域具有良好的应用前景。本文首先对MOFs催化的背景进行简述,然后对近年来报道的MOFs用于有机分子催化转化反应的进展进行了综述及展望,以期为MOFs催化有机反应的设计和开发提供参考。

南大洋增暖及其气候影响

过去几十年南大洋在南极平流层臭氧消耗和大气二氧化碳浓度增加的共同作用下大幅增暖,显著影响着南极冰架和冰盖的融化、海平面上升、南北半球的降水分配以及热带海洋和大气环流等,引发了深远的气候效应.全球变暖背景下南大洋西风表现为极向加强,同时进入南大洋的热辐射和淡水通量持续增加,由此上翻的海水可吸收更多的热量和碳,经由更强的平均流向北输送,更多地在45°S附近海域下沉并存储.当前对南大洋增暖背后诸多复杂的物理过程仍缺乏足够的理解,比如来自冰架、冰盖及海洋涡旋的作用、热带-极地相互作用、南大洋本身对全球变暖的响应等,尤其是有限的观测数据和较低分辨率的模式无法准确呈现快速变化的物理现象和机理.因此,南大洋的未来增暖存在很大的不确定性且可能长期持续,但近期的进展为深入认知南大洋增暖及其气候影响奠定了坚实的基础.

南极爆发性增温创造新纪录

Antarctica is considered as an important component of the global climate system, not only because of its ability to drive global sea-level rise through ice melting [1], but also because of its stabilizing effect on global atmospheric energy balance/circulation [2].In recent years, Antarctica has experienced rapid climatic changes and frequent climate extremes, such as a rapid decrease in summer sea ice extent since 2016 [3] and the highest air temperature recorded at Esperanza station in the Antarctic Peninsula on 9February 2020 [4]. In this context, climate extremes in Antarctica have received increasing attention recently [4–7].

Legal Effect of Smart Contracts Based on Blockchain

Smart contracts are increasingly used in financial innovation area.In view of smart contracts’legal effects,a study is implemented in this paper.First,Smart contracts appear as a set of computer codes,and carry the mutual consensus of the transaction parties and under the principle of freedom of contract form.Thus,smart contracts can be understood as a type of contractual written form in the hightech context.Then the agreement automatic enforcement was made by the five-element structure,and the traditional situation of enforcement uncertainty was avoided.The results show that it is necessary to examine whether the meaning of the machine matches the meaning of the party,and whether the machine meaning is in conformity with the legal provisions.Finally,the conclusion was drawn that the legal effect of smart contract can be clarified in response to the booming financial technology.