Separation of Atmospheric Circulation Patterns Governing Regional Variability of Arctic Sea Ice in Summer

In recent decades,Arctic summer sea ice extent(SIE)has shown a rapid decline overlaid with large interannual variations,both of which are influenced by geopotential height anomalies over Greenland(GL-high)and the central Arctic(CA-high).In this study,SIE along coastal Siberia(Sib-SIE)and Alaska(Ala-SIE)is found to account for about 65%and 21%of the Arctic SIE interannual variability,respectively.Variability in Ala-SIE is related to the GL-high,whereas variability in Sib-SIE is related to the CA-high.A decreased Ala-SIE is associated with decreased cloud cover and increased easterly winds along the Alaskan coast,promoting ice-albedo feedback.A decreased Sib-SIE is associated with a significant increase in water vapor and downward longwave radiation(DLR)along the Siberian coast.The years 2012 and 2020 with minimum recorded ASIE are used as examples.Compared to climatology,summer 2012 is characterized by a significantly enhanced GL-high with major sea ice loss along the Alaskan coast,while summer 2020 is characterized by an enhanced CA-high with sea ice loss focused along the Siberian coast.In 2012,the lack of cloud cover along the Alaskan coast contributed to an increase in incoming solar radiation,amplifying ice-albedo feedback there;while in 2020,the opposite occurs with an increase in cloud cover along the Alaskan coast,resulting in a slight increase in sea ice there.Along the Siberian coast,increased DLR in 2020 plays a dominant role in sea ice loss,and increased cloud cover and water vapor both contribute to the increased DLR.

Stratospheric Ozone-induced Cloud Radiative Effects on Antarctic Sea Ice

Recent studies demonstrate that the Antarctic Ozone Hole has important influences on Antarctic sea ice.While most of these works have focused on effects associated with atmospheric and oceanic dynamic processes caused by stratospheric ozone changes,here we show that stratospheric ozone-induced cloud radiative effects also play important roles in causing changes in Antarctic sea ice.Our simulations demonstrate that the recovery of the Antarctic Ozone Hole causes decreases in clouds over Southern Hemisphere(SH)high latitudes and increases in clouds over the SH extratropics.The decrease in clouds leads to a reduction in downward infrared radiation,especially in austral autumn.This results in cooling of the Southern Ocean surface and increasing Antarctic sea ice.Surface cooling also involves ice-albedo feedback.Increasing sea ice reflects solar radiation and causes further cooling and more increases in Antarctic sea ice.

Albedo of Coastal Landfast Sea Ice in Prydz Bay,Antarctica:Observations and Parameterization

The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica（off Zhongshan Station）during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters（e.g., snow thickness, ice thickness, surface temperature, and air temperature） were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.

A Sensitivity Study of Arctic Ice-Ocean Heat Exchange to the Three-Equation Boundary Condition Parametrization in CICE6

In this study,we perform a stand-alone sensitivity study using the Los Alamos Sea ice model version 6(CICE6)to investigate the model sensitivity to two Ice-Ocean(IO)boundary condition approaches.One is the two-equation approach that treats the freezing temperature as a function of the ocean mixed layer(ML)salinity,using two equations to parametrize the IO heat exchanges.Another approach uses the salinity of the IO interface to define the actual freezing temperature,so an equation describing the salt flux at the IO interface is added to the two-equation approach,forming the so-called three-equation approach.We focus on the impact of the three-equation boundary condition on the IO heat exchange and associated basal melt/growth of the sea ice in the Arctic Ocean.Compared with the two-equation simulation,our three-equation simulation shows a reduced oceanic turbulent heat flux,weakened basal melt,increased ice thickness,and reduced sea surface temperature(SST)in the Arctic.These impacts occur mainly at the ice edge regions and manifest themselves in summer.Furthermore,in August,we observed a downward turbulent heat flux from the ice to the ocean ML in two of our three-equation sensitivity runs with a constant heat transfer coefficient(0.006),which caused heat divergence and congelation at the ice bottom.Additionally,the influence of different combinations of heat/salt transfer coefficients and thermal conductivity in the three-equation approach on the model simulated results is assessed.The results presented in this study can provide insight into sea ice model sensitivity to the three-equation IO boundary condition for coupling the CICE6 to climate models.

An Unprecedented Record Low Antarctic Sea-ice Extent during Austral Summer 2022

Seasonal minimum Antarctic sea ice extent(SIE)in 2022 hit a new record low since recordkeeping began in 1978 of 1.9 million km^(2) on 25 February,0.17 million km^(2) lower than the previous record low set in 2017.Significant negative anomalies in the Bellingshausen/Amundsen Seas,the Weddell Sea,and the western Indian Ocean sector led to the new record minimum.The sea ice budget analysis presented here shows that thermodynamic processes dominate sea ice loss in summer through enhanced poleward heat transport and albedo-temperature feedback.In spring,both dynamic and thermodynamic processes contribute to negative sea ice anomalies.Specifically,dynamic ice loss dominates in the Amundsen Sea as evidenced by sea ice thickness(SIT)change,while positive surface heat fluxes contribute most to sea ice melt in the Weddell Sea.

Improvement on Quantitative Measurement of Fly Ash Contents Using Laser-Induced Breakdown Spectroscopy

Contents of fly ash are important factors for the operation of coal-fired plants. Real-time monitoring of coal and fly ash such as unburned carbon in fly ash can be an indicator of the combustion conditions. Because of the strong signal intensity and the relative simplicity of the LIBS (Laser- Induced Breakdown Spectroscopy) technique, LIBS can be applicable for real-time composition measurement of coal and fly ash. This research presented here focused on the clarification of the effects of plasma temperature and coexisting materials on quantitative measurement of fly ash contents. Quantitative capability of LIBS was improved using the proposed plasma temperature correction method. The CO2 effect was also discussed to accurately evaluate unburned carbon in fly ash in exhausts. Using the results shown in this study, quantitative measurement of fly ash contents has been improved for wider applications of LIBS to practical fields.

Arctic sea ice concentration and thickness data assimilation in the FIO-ESM climate forecast system

To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model(FIO-ESM)climate forecast system,satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic IceOcean Modeling and Assimilation System(PIOMAS)are assimilated into this system,using the method of localized error subspace transform ensemble Kalman filter(LESTKF).Five-year(2014–2018)Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation.Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent.All the biases of ice concentration,ice cover,ice volume,and ice thickness can be reduced dramatically through ice concentration and thickness assimilation.The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system.The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation.Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-toseasonal(S2 S)Prediction Project,FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast.Since sea ice thickness in the PIOMAS is updated in time,it is a good choice for data assimilation to improve sea ice prediction skills in the near-realtime Arctic sea ice seasonal prediction.

Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data

Snow depth over sea ice is an essential variable for understanding the Arctic energy budget.In this study,we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)against recent satellite retrievals.The CMIP6 models capture some aspects of the observed snow depth climatology and variability.The observed variability lies in the middle of the models’simulations.All the models show negative trends of snow depth during 1993-2014.However,substantial spatiotemporal discrepancies are identified.Compared to the observation,most models have late seasonal maximum snow depth(by two months),remarkably thinner snow for the seasonal minimum,an incorrect transition from the growth to decay period,and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice.Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic.Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099.Under the SSP5-8.5 scenario,the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January.Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution,the inclusion of a hightop atmospheric model,and biogeochemistry processes are important factors for snow depth simulation.

Erratum to:Stratospheric Ozone-induced Cloud Radiative Effects on Antarctic Sea Ice

The article“Stratospheric Ozone-induced Cloud Radiative Effects on Antarctic Sea Ice”,written by Yan XIA,Yongyun HU,Jiping LIU,Yi HUANG,Fei XIE,and Jintai LIN was originally published electronically on the publisher’s internet portal on 7 of March 2020 without open access.With the author(s)’decision to opt for Open Choice,the copyright of the article changed on 11 of April 2020 to©The Author(s),2020 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License,which permits use,sharing,adaptation,distribution and reproduction in any medium or format,as long as you give appropriate credit to the original author(s)and the source,provide a link to the Creative Commons licence,and indicate if changes were made.The images or other third party material in this article are included in the article’s Creative Commons licence,unless indicated otherwise in a credit line to the material.If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use,you will need to obtain permission directly from the copyright holder.To view a copy of this licence,visit http://creativecommons.org/licenses/by/4.0.

Preface to the Special Issue on Antarctic Meteorology and Climate:Past,Present and Future

The Antarctic,including the continent of Antarctica and the Southern Ocean,is a critically important part of the Earth system.Research in Antarctic meteorology and climate has always been a challenging endeavor.Studying and predicting weather patterns in the Antarctic are important for understanding their role in local-to-global processes and facilitating field studies and logistical operations in the Antarctic(e.g.,Walsh et al.,2018).Studies of climate change in the Antarctic are comparatively neglected compared to those of the Arctic.However,significant climate changes have occurred in the Antarctic in the past several decades,i.e.,a strong warming over the Antarctic Peninsula even with a recent minor cooling,a deepening of the Amundsen Sea low,a rapid warming of the upper ocean north of the circumpolar current,an increase of Antarctic sea ice since the late 1970s followed by a recent rapid decrease,and an accelerated ice loss from the Antarctic ice shelf/sheet since the late 1970s(e.g.,Turner et al.,2005;Raphael et al.,2016;Sallée,2018;Parkinson,2019;Rignot et al.,2019).Investigating recent climate change in the Antarctic and the underlying mechanisms are important for predicting future climate change and providing information to policymakers.

Uniqueness of Lekima compared to tropical cyclones landed in the east coast of China during 1979–2019

Tropical cyclone (TC) causes huge damage to lives and properties due to strong winds,storm surge,heavy rainfall and flooding(Peduzzi et al.,2012;Zhang et al.,2009).Climate model simulations suggested that the frequency of TCs might increase during the 21st century,especially over the western North Pacific (Emanuel,2013).Climate changes tend to double the economic damages caused by natural disaster,i.e.,strong TCs.East Asia hit by TCs may suffer great damages in the future (Mendelsohn et al.,2012).

Subseasonal to seasonal Arctic sea-ice prediction:A grand challenge of climate science

On 15 September 2020,the Arctic sea-ice extent(SIE)reached its annual minimum,which,based on data from the National Snow and Ice Data Center(NSIDC,2020a),was about 3.74 million km^(2)(1.44 million square miles).This value was about 40%less than the climate average(~6.27 million km^(2))during 1980–2010.It was second only to the record low(3.34 million km^(2))set on 16 September 2012,but significantly smaller than the previous second-lowest(4.145 million km^(2),set on 7 September 2016)and third-lowest(4.147 million km^(2),set on 14 September 2007)values,making 2020 the second-lowest SIE year of the satellite era(42 years of data).

The SOOS Asian Workshop: Exploring possibilities for collaboration

The first Southern Ocean Observing System （SOOS） Asian Workshop was successfully held in Shanghai, China in May 2013, attracting over 40 participants from six Asian nations and widening exposure to the objectives and plans of SOOS. The workshop was organized to clarify Asian research activities currently taking place in the Southern Ocean and to discuss, amongst other items, the potential for collaborative efforts with and between Asian countries in $OOS-related activities. The workshop was an important mechanism to initiate discussion, understanding and collaborative avenues in the Asian domain of SOOS beyond current established eflbrts. Here we present some of the major outcomes of the workshop covering the principle themes of SOOS and attempt to provide a way forward to achieve a more integrated research community, enhance data collection and quality, and guide scientific strategy in the Southern Ocean.

Numerical simulation of deep-hole resistivity anomaly caused by drilling construction in Xinfengjiang geoelectric station

The Xinfengjiang reservoir in Guangdong Province is one of the large reservoirs that have triggered earthquakes of magnitude greater than 6.Numerous earthquakes have occurred since the impoundment of the reservoir,making it one of the most active seismic zones in south China.In 2015,a set of deep-hole resistivity anomalies was observed in the Heping geoelectric station in Dongyuan county,located near the Xinfengjiang reservoir.After a field investigation,we found that a planned well drilling construction of new measuring channels was being carried out during that corresponding period of time.After careful comparison and analysis on the basis of the collected raw data,we had a reason to believe that drilling construction,rather than the inducement of the Xinfengjiang reservoir,was the main culprit for those unusual georesistivity values.So as to verify the above conjecture,we constructed a series of 3D finite element models based on the geological and hydrological infor-mation around Heping station and analyzed the drilling disturbances,respectively.Some significant conclusions were finally drawn according to the precise numerical simulation.This study gives a good example by combining numerical simulation with engineering practice as a way to understand the root cause of georesistivity anomalies in reality.

The Gravity Gauge Theory and Gravity Field Equation in Flat Space

In this paper, we have proposed the theory of gravity gauge, and the gravity theory has been introduced into quantum field theory. We have further given the tensor equation of gravity field in the flat space, and found the gravity field equation is the Lorentz covariant and gauge invariant. The gravity theory can be quantized and can be unified with the electroweak and strong interaction at a new gauge group .

Photon and Elementary Particles Theory

At present, the research of single-photon is a hot topic, it has been widely applied in quantum measurement, quantum entanglement and quantum information. In this paper, we have proposed a new single photon theory, which is the vector potential A rotation at the vertical motion direction of photon, it can produce the microscopic electric field and magnetic field, and they satisfy the Maxwell equations. We have calculated photon spin, momentum, energy, and found there are left-handed and right-handed photon. In addition, we study the multi-photon theory and the dynamics theory between photons interaction. On this basis, we have further given the compound structures of electron, proton, neutron, neutrino, π meson, dark matter with the photon structural theory, and calculated their mass, charge and spin.

Research on the Teaching Reform of Polymer Materials Foundation Course-Based on the Case Analysis Method

In today's education and teaching reform,the traditional teaching method in the teaching of polymer materials has been gradually replaced with various new teaching methods.Among them,the case analysis method is a very efective teaching method,which has been applied to the teaching of polymer materials.Through example-based teaching,students 125 participation can be effectively improved,and their theoretical knowledge can be fully utilized.This would have a positive role in promoting the improvement of students'knowledge system and their learning ability.In regard to this,this article analyzes the application of case analysis in the teaching of polymer materials so as to improve its efficiency and quality.

Landscape of human organoids:Ideal model in clinics and research

In the last decade,organoid research has entered a golden era,signifying a pivotal shift in the biomedical landscape.The year 2023 marked a milestone with the publication of thousands of papers in this arena,reflecting exponential growth.However,amid this burgeoning expansion,a comprehensive and accurate overview of the field has been conspicuously absent.Our review is intended to bridge this gap,providing a panoramic view of the rapidly evolving organoid landscape.We meticulously analyze the organoid field from eight distinctive vantage points,harnessing our rich experience in academic research,industrial application,and clinical practice.We present a deep exploration of the advances in organoid technology,underpinned by our long-standing involvement in this arena.Our narrative traverses the historical genesis of organoids and their transformative impact across various biomedical sectors,including oncology,toxicology,and drug development.We delve into the synergy between organoids and avant-garde technologies such as synthetic biology and single-cell omics and discuss their pivotal role in tailoring personalized medicine,enhancing high-throughput drug screening,and constructing physiologically pertinent disease models.Our comprehensive analysis and reflective discourse provide a deep dive into the existing landscape and emerging trends in organoid technology.We spotlight technological innovations,methodological evolution,and the broadening spectrum of applications,emphasizing the revolutionary influence of organoids in personalized medicine,oncology,drug discovery,and other fields.Looking ahead,we cautiously anticipate future developments in the field of organoid research,especially its potential implications for personalized patient care,new avenues of drug discovery,and clinical research.We trust that our comprehensive review will be an asset for researchers,clinicians,and patients with keen interest in personalized medical strategies.We offer a broad view of the present and prospective capabilities of organoid technology,encompassing a wide range of current and future applications.In summary,in this review we attempt a comprehensive exploration of the organoid field.We offer reflections,summaries,and projections that might be useful for current researchers and clinicians,and we hope to contribute to shaping the evolving trajectory of this dynamic and rapidly advancing field.

Co-chaperoning of chlorophyll and carotenoid biosynthesis by ORANGE family proteins in plants

Chlorophylls and carotenoids are essential photosynthetic pigments.Plants spatiotemporally coordinate the needs of chlorophylls and carotenoids for optimal photosynthesis and fitness in response to diverse environmental and developmental cues.However,how the biosynthesis pathways of these two pigments are coordinated,particularly at posttranslational level to allow rapid control,remains largely unknown.Here,we report that the highly conserved ORANGE(OR)family proteins coordinate both pathways via posttranslationally mediating the first committed enzyme in each pathway.We demonstrate that OR family proteins physically interact with magnesium chelatase subunit I(CHLI)in chlorophyll biosynthesis pathway in addition to phytoene synthase(PSY)in carotenoid biosynthesis pathway and concurrently stabilize CHLI and PSY enzymes.We show that loss of OR genes hinders both chlorophyll and carotenoid biosynthesis,limits light-harvesting complex assembly,and impairs thylakoid grana stacking in chloroplasts.Overexpression of OR safeguards photosynthetic pigment biosynthesis and enhances thermotolerance in both Arabidopsis and tomato plants.Our findings establish a novel mechanism by which plants coordinate chlorophyll and carotenoid biosynthesis and provide a potential genetic target to generate climate-resilient crops.

The role of aluminum sensing and signaling in plant aluminum resistance

As researchers have gained a better understanding in recent years into the physiological, molecular, and genetic basis of how plants deal with aluminum （AI） toxicity in acid soils prevalent in the tropics and sub-tropics, it has become clear that an important component of these responses is the triggering and regulation of cellular pathways and processes by AI. In this review of plant AI signaling, we begin by summarizing the understanding of physiological mechanisms of AI resistance, which first led researchers to realize that AI stress induces gene expression and modifies protein function during the activation of AI resistance responses. Subsequently, an overview of AI resistance genes and their function provides verification that AI induction of gene expression plays a major role in AI resistance in many plant species. More recent research into the mechanistic basis for Al-induced transcrip- tional activation of resistance genes has led to the identifica- tion of several transcription factors as well as cis-elements in the promoters of AI resistance genes that play a role in greater Al-induced gene expression as well as higher constitutive expression of resistance genes in some plant species. Finally, the post-transcriptional and translational regulation of AI resistance proteins is addressed, where recent research has shown that AI can both directly bind to and alter activity of certain organic acid transporters, and also influence AI resistance proteins indirectly, via protein phosphorylation.