Comparison of CloudSat Cloud Liquid Water Paths in Arctic Summer Using Ground-Based Microwave Radiometer

Arctic clouds strongly influence the regional radiation balance, temperature, melting of sea ice, and freezing of sea water. Despite their importance, there is a lack of systematic and reliabie observations of Arctic clouds. The CloudSat satellite launched in 2006 with a 94GHz Cloud Profiling Radar （CPR） may contribute to close this gap. Here we compare one of the key parameters, the cloud liquid water path （LWP） retrieved from CloudSat observations and from microwave radiometer （MWR） data taken during the ASCOS （Arctic Summer Cloud Ocean Study） cruise of the research vessel Oden from August to September 2008. Over the 45 days of the ASCOS cruise, collocations closer than 3 h and 100 km were found in only 9 d, and collocations closer than 1 h and 30 km in only 2 d. The poor correlations in the scatter plots of the two LWP retrievals can be explained by the patchiness of the cloud cover in these two days （August 5th and September 7th）, as confirmed by coincident MODIS （Moderate-resolution Imaging Spectroradiome- ter） images. The averages of Oden-observed LWP values are systematically higher （40-70 g m-2） than the corresponding CloudSat observations （0-50 g m2）. These are cases of generally low LWP with presumably small droplets, and may be explained by the little sensitivity of the CPR to small droplets or by the surface clutter.

Retrieval of Microwave Surface Emissivities at TMI Frequencies in Shouxian

Using a microwave radiative transfer model, atmospheric sounding profiles, satellite brightness temperatures, and some surface observed measurements under cloud-free conditions, surface emissivities at the frequencies of TRMM/TMI (Tropical Rainfall Measuring Mission Microwave Imager) at Shouxian in HUBEX (Huaihe River Basin Energy and Water Cycle Experiment) are retrieved. Compared to the microwave surface emissivities with changing conditions of the surface, it is found that the microwave emissivities have some sensitive variability with the conditions of the surface, and the variability is reasonable. In the calculation, the surface air temperatures are assumed to equal the surface skin temperatures, and only the emissivity at Shouxian is calculated; the calculation of the emissivities over the region of HUBEX needs more measurements.

中国首个地基高分辨率傅里叶变换光谱观测站的大气成分长期观测研究

长期观测主要大气成分的体积混合比(VMR)廓线和柱总量对掌握中国气候变化和碳收支具有重要意义。本文对我国首个TCCON高分辨率傅里叶变换光谱(FTS)地基观测站——合肥观测站开展了系统性研究,该观测站可观测30多种大气成分的柱总量和VMR廓线。本文公布了2014年以来合肥观测站观测到的部分关键大气成分的时间序列,总结了迄今为止该站点取得的主要研究成果,包括光谱反演表征和归一化、关键大气成分的总体演变特征、排放估计、卫星和化学传输模式(CTM)校验以及对大气污染来源和传输的相关研究。同时,本文还对合肥观测站的观测、科学研究和未来研究计划进行了展望。中国明确提出2030年二氧化碳排放达到峰值,2060年实现碳中和。合肥观测站将为中国政府制定绿色经济政策、实现碳中和及《巴黎协定》目标提供科学支撑。

利用GOME卫星资料分析北京大气NO_2污染变化

利用GOME(Global Ozone Monitoring Experiment,全球臭氧监测实验)1996年1月—2002年12月NO2对流层柱浓度月平均卫星遥感资料以及根据北京市2001年1月1日—2002年12月31日NO2污染指数数据计算出的地面NO2日均质量浓度值,分析了北京市城市大气NO2污染变化的季节变化特征以及年际变化,并将2001年1月—2002年12月北京上空GOME NO2对流层柱浓度月平均值变化与北京市地面NO2日均质量浓度月平均值变化进行了比较,结果表明两者随时间的变化趋势具有较好的一致性,据此可以利用GOME NO2对流层柱浓度月平均卫星遥感资料来分析特定区域大气NO2的季节变化和年际变化。

古尔班通古特沙漠春季土壤含水量空间格局

春季积雪融水是古尔班通古特沙漠土壤水分的重要补给源之一,为早春植物的萌发和生长创造了有利的条件。为掌握该地区春季沙丘的土壤水分分布状况,采用探地雷达测量技术,于2010年4月进行了多次野外测量,并通过对地面直达波信号的提取和分析,初步获得了一致的测量结果。结果表明:(1)探地雷达地面直达波测量的土壤平均含水量与20 cm深同步TDR的测量结果非常接近,两者总体相差在0.02 cm3/cm3以内,充分反映了GPR地面直达波测量结果的有效性和精确性;(2)春季积雪完全融化后,沙丘/沙垄顶部土壤水分明显低于垄间低地,这与前人的研究一致,反映了积雪和冻土层在消融过程中,沙丘表面融水在坡面重力作用下,沿难以透水的冻土层上界自坡上向坡下迁移,形成了垄间最高、坡部次之和垄顶最少的分布格局;(3)垄间低地的土壤水分明显受到低矮灌草丛的影响进行再分布,这是由于积雪最初沿植丛基部开始消融,并以植丛为中心形成漏斗状融洞,从而形成以植丛为中心汇集较多融雪水的格局,而垄间低地中较为高大的梭梭乔木对融雪水的再分布影响明显不如低矮的灌草丛,这与其地表茎基过少有关。此外,探地雷达测量实验提供了详实可靠的表层土壤含水量分布信息,可为荒漠生态系统的空间尺度研究提供真实可靠的数据基础。

中德合作三江源区和甜水海地区多年冻土退化过程科学考察和研究进展

为准确了解青藏高原多年冻土退化过程及其环境效应,中国科学院寒区旱区环境与工程研究所和德国海德堡大学环境物理研究所共同组成科研小组,先后对我国三江源区、西昆仑甜水海地区进行了多年冻土退化过程的前期勘察研究工作.首次在人烟稀少的玉树-不冻泉沿线等地建立了3个长期综合观测研究站.在技术手段上,除应用常规的坑探、水土取样、水分现场观测、地面调查外,主要应用了最新的双天线、多回路探地雷达勘测技术,对不同地貌条件下的活动层结构特征、上限附近冻土结构、冷生组构等诸多方面进行了快速勘察,同时还进行了水分场分布规律、盐份迁移过程的初步研究.研究结果表明:地表景观特征对热质迁移规律、地温场具有重要影响;青藏高原新疆甜水海地区的低温(<-4℃)冻土与高原东部和腹地的高温(>-1℃)冻土在地质背景和地下冰发育情况等方面有所区别;甜水海地区生态环境在过去30多年的时间里已发生重大改变:地表植被发生大面积退化,地表普遍发生不同程度盐渍化;在该地区发现大量小型冻胀丘、石环等冰缘现象的存在.探地雷达勘察结果显示,地表地貌单元、植被分布、地表水分条件的变化均对多年冻土上限变化和地下冰的赋存产生重要影响.

Geomorphological Evolution Revealed by Aeolian Sedimentary Structure in Badain Jaran Desert on Alxa Plateau, Northwest China

The Badain Jaran Desert,located in the Alxa Plateau,Northwest China,features mega-dunes and a unique dune-lake alternation landscape.This paper presented the aeolian sediment structures of three representative dunes in the Badain Jaran Desert using ground-penetrating radar (GPR).We processed and analyzed the GPR data and investigated the feasibility of using integrated GPR and sedimentological data to reconstruct dunes structure,sedimentary environment and geomorphological evolution.The results show that the internal structures of star dune and transverse dune represent various stages of mega-dune evolution: the main deposition processes of mega-dune are similar to those of transverse dunes but have a more complicated mechanism of sand transport and deposition because of the superimposition of dunes;the upper section of the mega-dune has a structure similar to that of star dune,with vertical aggradations on top.Diffraction hyperbolae in the GPR profile indicates that the presence of ancient dunes characterized by calcareous cementation layers is involved in the maintenance of mega-dunes,and water levels,shown by continuous,sub-horizontal GPR reflections,are supposed to be closely related to mega-dunes and the interdune lakes.Outcrop of wet sand and horizontal stratifications on the GPR image indicate moisture potentials with different levels inside mega-dunes.The multiplex geomorphology in the Badain Jaran Desert is the result of global climatic undulation,the unique geographical location,the geological structural features,etc.

An Algorithm to Detect Tropical Deep Convective Clouds Through AMSU-B Water Vapor Channels

An algorithm to detect tropical deep convective clouds and deep convective overshootings based on the measurements from the three water vapor channels （1833GHz± 1GHz, 183.3GHz±3GHz and 183.3GHz±7GHz） of the Advanced Microwave Sounding Unit-B （AMSU-B） is presented. This algorithm is an improved version of the method of Hong et al. （2005）. The proposed procedure is based on the statistical analysis of seven years＇ （2001-2007） measurements from AMSU-B on NOAA-16. From the 1-d histograms of the brightness temperature of the three water vapor channels and the 2-d histograms of the brightness temperature dif- ference between these channels, new thresholds for brightness temperature differences and the brigb.tness temperature of chamM 18 （183.3 GHz 4-1 GHz） are suggested. The new algorithm is employed to investigate the mean distribution of tropical deep convective clouds and convective overshootings from 30＇S to 30＇N for the years 2001 to 2007. The major concentration of deep convective clouds and convective overshootings is found over the Intertropical Convergence Zone （ITCZ）, the South Pacific Convergence Zone （SPCZ）, tropical Africa, South America, the Indian Ocean and Indonesia ruth an average fraction of 0.4%. In terms of these clouds we identity, the secondary Intertropical Convergence Zone located in the eastern South Pacific and parallel to the main ITCZ in the North Pacific. The convective overshooting is more frequently observed over land than over the ocean.

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.

A Review of Arctic-Subarctic Ocean Linkages: Past Changes, Mechanisms, and Future Projections

Arctic Ocean gateway fluxes play a crucial role in linking the Arctic with the global ocean and affecting climate and marine ecosystems.We reviewed past studies on Arctic-Subarctic ocean linkages and examined their changes and driving mechanisms.Our review highlights that radical changes occurred in the inflows and outflows of the Arctic Ocean during the 2010s.Specifically,the Pacific inflow temperature in the Bering Strait and Atlantic inflow temperature in the Fram Strait hit record highs,while the Pacific inflow salinity in the Bering Strait and Arctic outflow salinity in the Davis and Fram straits hit record lows.Both the ocean heat convergence from lower latitudes to the Arctic and the hydrological cycle connecting the Arctic with Subarctic seas were stronger in 2000-2020 than in 1980-2000.CMIP6 models project a continuing increase in poleward ocean heat convergence in the 21st century,mainly due to warming of inflow waters.They also predict an increase in freshwater input to the Arctic Ocean,with the largest increase in freshwater export expected to occur in the Fram Strait due to both increased ocean volume export and decreased salinity.Fram Strait sea ice volume export hit a record low in the 2010s and is projected to continue to decrease along with Arctic sea ice decline.We quantitatively attribute the variability of the volume,heat,and freshwater transports in the Arctic gateways to forcing within and outside the Arctic based on dedicated numerical simulations and emphasize the importance of both origins in driving the variability.

Erratum to “A Review of Arctic–Subarctic Ocean Linkages: Past Changes, Mechanisms, and Future Projections”

In the Review Article"A Review of Arctic–Subarctic Ocean Linkages:Past Changes,Mechanisms,and Future Projections"[1],the x-axis in Figure 4B and y-axis in Figure 8F were skewed during picture beautification by an artist.These errors did not affect the conclusions of the paper.Figures 4B and 8F have now been corrected in the PDF and HTML(full text).

雅安市春季一次典型臭氧污染过程分析

雅安市春季(4—5月)臭氧(O_(3))污染问题日渐凸显.基于雅安市区国控监测站点大气O_(3)监测数据,运用HYSPLIT后向轨迹模式、潜在源贡献因子法(WPSCF)与浓度权重轨迹分析(WCWT)等方法,探讨了2015—2023年雅安市春季O_(3)污染特征及一次典型O_(3)污染过程(2023年4月9—10日)成因.结果表明,春季雅安MDA8 O_(3)浓度和O_(3)超标天数波动上升,2023年分别达到111μg·m^(-3)和9d,活跃的本地光化学生成过程和区域传输过程是重要驱动因素.在春季O_(3)污染的形成过程中,低水平风速、盆地内下沉气流作用等不利的扩散条件使得雅安市区各类污染物累积、浓度水平显著升高,特别是夜间O_(3)浓度升高导致较高的本底浓度水平.日间700 hPa以下高度上24 h增温显著、较强的太阳辐射和低湿条件,有利于NO_(x)和VOCs等前体物快速发生光化学氧化反应形成O_(3).潜在源区(眉山和成都等)O_(3)及其前体物的传输,加剧了雅安市午后O_(3)污染程度,O_(3)浓度增长可达20μg·m^(-3)以上.因此,对雅安市春季O_(3)污染的防控需要加强本地前体物减排,同时考虑对周边地区施行协同减排措施.

Satellite remote sensing of changes in NO_x emissions over China during 1996-2010

Satellite derived NO2 column data have been used to study Chinese national fossil fuel consumption and pollutant emissions.Based on NO 2 retrievals from two satellites (GOME and SCIAMACHY) for 1996-2010,we analyzed the characteristics and evolution of regional pollution related to NO x emissions in China.Satellite observations indicated that the highly polluted regions were expanding.Anthropogenic emission dominated areas have expanded from the east to central and western China,and new highly polluted regions have formed throughout the nation.Bottom-up emission estimates suggested a 133% increase in anthropogenic NOx emissions in East Central China during 1996 to 2010,which was lower than the 184% increase of the NO2 columns measured by the satellites.We found that growth rates of NOx emissions have slowed in Chinese megacities over recent years,in contrast to which,the NOx emissions were soaring in medium-sized cities,indicating that strict controls of NOx emissions from coal-fired facilities are required in China.

An improved Landsat Image Mosaic of Antarctica

A revised Landsat Image Mosaic of Antarctica （LIMA） is presented, using the 1073 multi-band scenes of the original Land- sat-7 ETM＋ LIMA image collection available at the United States Geological Survey （USGS： http：//lima.usgs.gov/）. Three improvements have been applied during the data processing： （1） DN saturation is adjusted by adopting a linear regression, which has a lower root mean square error than the ratio regression used by LIMA; （2） solar elevation angle is calculated using pixel-level latitude/longitude and the acquisition time and date of the central pixel of the scene, improving slightly upon the bi- linear interpolation of the solar elevation angles of scene comers applied in LIMA; and （3） two additional image bands, Band 5 and Band 7, are sharpened using the panchromatic band （Band 8） and a Gram-Schmidt Spectral Sharpening algorithm to more easily distinguish snow, cloud and exposed rocks. The final planetary reflectance product is stored in 16-bit bands to preserve the full radiometric content of the scenes. A comparative statistical analysis among 12 sample regions indicates that the new mosaic has enhanced visual qualities, information entropy, and information content for land cover classification relative to LIMA.

Global land mapping of satellite-observed CO_(2)total columns using spatio-temporal geostatistics

This study presents an approach for generating a global land mapping dataset of the satellite measurements of CO_(2)total column(XCO_(2))using spatio-temporal geostatistics,which makes full use of the joint spatial and temporal dependencies between observations.The mapping approach considers the latitude-zonal seasonal cycles and spatio-temporal correlation structure of XCO_(2),and obtains global land maps of XCO_(2),with a spatial grid resolution of 1°latitude by 1°longitude and temporal resolution of 3 days.We evaluate the accuracy and uncertainty of the mapping dataset in the following three ways:(1)in cross-validation,the mapping approach results in a high correlation coefficient of 0.94 between the predictions and observations,(2)in comparison with ground truth provided by the Total Carbon Column Observing Network(TCCON),the predicted XCO_(2)time series and those from TCCON sites are in good agreement,with an overall bias of 0.01 ppm and a standard deviation of the difference of 1.22 ppm and(3)in comparison with model simulations,the spatio-temporal variability of XCO_(2)between the mapping dataset and simulations from the CT2013 and GEOS-Chem are generally consistent.The generated mapping XCO_(2)data in this study provides a new global geospatial dataset in global understanding of greenhouse gases dynamics and global warming.

Investigating missing sources of glyoxal over China using a regional air quality model (RAMS-CMAQ)

Currently, modeling studies tend to significantly underestimate observed space-based glyoxal （CHOCHO） vertical column densities （VCDs）, implying the existence of missing sources of giyoxal. Several recent studies suggest that the emissions of aromatic compounds and molar yields of glyoxal in the chemical mechanisms may both be underestimated, which can affect the simulated glyoxal concentrations. In this study, the influences of these two factors on glyoxal amounts over China were investigated using the RAMS-CMAQ modeling system for January and July 2014. Four sensitivity simulations were performed, and the results were compared to satellite observations. These results demonstrated significant impacts on glyoxal concentrations from these two factors. In case 1, where the emissions of aromatic compounds were increased three-fold, improvements to glyoxal VCDs were seen in high anthropogenic emissions regions. In case 2, where molar yields of glyoxal from isoprene were increased five-fold, the resulted concentrations in July were B-B-fold higher, achieving closer agreement between the modeled and measured glyoxal VCDs. The combined changes from both cases 1 and 2 were applied in case B, and the model succeeded in further reducing the underestimations of glyoxal VCDs. However, the results over most of the regions with pronounced anthropogenic emissions were still underestimated. So the molar yields of giyoxal from anthropogenic precursors were considered in case 4. With these additional mole yield changes （a two-fold increase）, the improved concentrations agreed better with the measurements in regions of the lower reaches of the Yangtze River and Yellow River in January but not in July.

卫星遥感观测中国1996～2010年氮氧化物排放变化

利用卫星遥感观测的NO2浓度作为化石能源消耗和污染物排放的示踪,基于GOME和SCIAMACHY的NO2对流层柱浓度数据对1996～2010年间中国氮氧化物排放的时空格局变化进行了分析.结果表明,我国氮氧化物排放的区域性特征日益显著,呈明显的空间扩张态势,原有排放高值区的范围不断扩大,新的高值区不断出现,受人为源排放影响的范围在从东部向中西部扩张.1996～2010年间,华东、华北地区的人为源氮氧化物排放量增加了133%,而同期卫星观测到NO2浓度增长了184%.最近几年特大城市的氮氧化物排放增速在减缓,而中型城市的排放增速在加快,显示我国亟需对燃煤氮氧化物排放进行控制.

改进的南极洲陆地卫星影像镶嵌图

研究改进LIMA数据处理方法,使用1073景Landsat7-ETM+数据制作了改进的南极洲陆地卫星影像镶嵌图.改进的镶嵌图较LIMA的优势体现在影像处理流程的3个方面:(1)DN值饱和溢出调整采用更高精度的线性回归方法;(2)利用每个像元的经纬度和影像中心点的拍摄时间逐像元计算太阳高度角,提高了太阳高度角的计算精度;(3)选择了更有效的GS融合方法,将更多的波段(波段5和7)加入融合产品的制作,在南极地类识别上优势更加明显.另外,以16bit进行存储的行星反射率产品很好的保持了冰雪表面的高辐射分辨率.从目视效果、信息熵以及分类等方面与LIMA数据进行比较,结果表明本文数据具有明显的优势.

Towards reliable Arctic sea ice prediction using multivariate data assimilation

Rapid declines in Arctic sea ice have captured attention and pose significant challenges to a variety of stakeholders. There is a rising demand for Arctic sea ice prediction at daily to seasonal time scales, which is partly a sea ice initial condition problem. Thus, a multivariate data assimilation that integrates sea ice observations to generate realistic and skillful model initialization is needed to improve predictive skill of Arctic sea ice. Sea ice data assimilation is a relatively new research area. In this review paper, we focus on two challenges for implementing multivariate data assimilation systems for sea ice forecast. First, to address the challenge of limited spatiotemporal coverage and large uncertainties of observations, we discuss sea ice parameters derived from satellite remote sensing that(1) have been utilized for improved model initialization, including concentration, thickness and drift, and(2) are currently under development with the potential for enhancing the predictability of Arctic sea ice, including melt ponds and sea ice leads. Second, to strive to generate the ‘‘best" estimate of sea ice initial conditions by combining model simulations/forecasts and observations, we review capabilities and limitations of different data assimilation techniques that have been developed and used to assimilate observed sea ice parameters in dynamical models.

AntarcticaLC2000：The new Antarctic land cover database for the year 2000

Antarctica plays a key role in global energy balance and sea level change.It has been conventionally viewed as a whole ice body with high albedo in General Circulation Models or Regional Climate Models and the differences of land cover has usually been overlooked.Land cover in Antarctica is one of the most important drivers of changes in the Earth system.Detailed land cover information over the Antarctic region is necessary as spatial resolution improves in land process models.However,there is a lack of complete Antarctic land cover dataset derived from a consistent data source.To fill this data gap,we have produced a database named Antarctic Land Cover Database for the Year 2000(AntarcticaLC2000) using Landsat Enhanced Thematic Mapper Plus(ETM+) data acquired around 2000 and Moderate Resolution Imaging Spectrometer(MODIS) images acquired in the austral summer of 2003/2004 according to the criteria for the 1:100000-scale.Three land cover types were included in this map,separately,ice-free rocks,blue ice,and snow/firn.This classification legend was determined based on a review of the land cover systems in Antarctica(LCCSA) and an analysis of different land surface types and the potential of satellite data.Image classification was conducted through a combined usage of computer-aided and manual interpretation methods.A total of 4067 validation sample units were collected through visual interpretation in a stratified random sampling manner.An overall accuracy of 92.3%and the Kappa coefficient of 0.836 were achieved.Results show that the areas and percentages of ice-free rocks,blue ice,and snow/firn are 73268.81 km2(0.537%),225937.26 km2(1.656%),and 13345460.41 km2(97.807%),respectively.The comparisons with other different data proved a higher accuracy of our product and a more advantageous data quality.These indicate that AntarcticaLC2000,the new land cover dataset for Antarctica entirely derived from satellite data,is a reliable product for a broad spectrum of applications.