Use of WorldView-2 time series to establish a wetland monitoring program for potential offsite impacts of mine site rehabilitation

The Ramsar-listed wetlands of the Magela Creek floodplain, situated in the World Heritage Kakadu National Park, in northern Australia are recognised for their biodiversity and cultural values. The floodplain is also a downstream receiving environment for Ranger uranium mine, which is entering closure and rehabilitation phases. Vegetation on the floodplain is spatially and temporally variable which is related to the hydrology of the region, primarily the extent and level of inundation and available soil moisture. Time-series mapping of the floodplain vegetation will provide a contemporary baseline of annual vegetation dynamics to assist with determining whether change is natural or a result of the potential impacts of mine closure activities such as increased suspended sediment moving downstream. The research described here used geographic object-based image analysis (GEOBIA) to classify the upper Magela Creek floodplain vegetation from WorldView-2 imagery captured over four years (2010–2013) and ancillary data including a canopy height model. A step-wise rule set was used to implement a decision tree classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010, May 2011, June 2012 and June 2013 with overall accuracies of over 80% for each map. Most of the error appears to be associated with confusion between vegetation classes that are spectrally similar such as the classes dominated by grasses. Object-based change detection was then applied to the maps to analyse change between dates. Results indicate that change between dates was detected for large areas of the floodplain. Most of the change is associated with the amount of surface water present, indicating that although imagery was captured at the same time of year, the imagery represents different stages of the seasonal cycle of the floodplain.     

京津冀及周边地区冬季能见度与PM2.5浓度和环境湿度的多元回归分析

2013年至今,中国冬季与雾霾相伴的低能见度事件频发,京津冀及周边地区尤为严重。PM_2.5浓度与环境湿度是导致低能见度的最关键影响因素。为了深入研究PM_2.5浓度与环境湿度对大气能见度的影响,利用2017年1月京津冀及周边地区MICAPS气象数据与PM_2.5观测数据,运用天气学诊断分析方法讨论了不同相对湿度下PM_2.5浓度、环境湿度对冬季能见度变化的相对贡献,按照地理环境与污染程度差异将京津冀及周边地区划分为北京-天津地区与河北-山东地区,建立了PM_2.5浓度与环境湿度（由露点温度、温度代表）对能见度的多元回归方程,并对2015、2016、2018、2019年冬季能见度进行了回算检验。结果显示:相对湿度低于70%、PM_2.5浓度低于75 μg/m3时,北京-天津地区与河北-山东地区能见度多高于10 km,PM_2.5浓度升高是此时能见度迅速降低的主导因素;相对湿度从70%上升至85%和PM_2.5浓度从75 μg/m3升高200 μg/m3的共同作用导致了能见度降低到10 km至5 km;能见度进一步从5 km下降至2 km则更多依赖于相对湿度进一步从85%升高至95%,PM_2.5浓度与此时能见度相关减弱;能见度降低至2 km甚至更低主要是由于水汽近饱和状态下（相对湿度95%以上）的雾滴消光引起,与PM_2.5浓度的变化关系不大。与不分组直接拟合相比,以相对湿度85%为界线,分别拟合能见度能够很大程度优化多元回归模型,相对湿度高于85%时能见度拟合值的均方根误差从9.2和5.2 km下降至0.5和0.7 km,5 km以下拟合能见度的误差大幅度减小。按相对湿度85%将数据分组所得的拟合方程对2015、2016、2018、2019年1月能见度估算结果较好,观测值与拟合值相关系数均高于0.91,为雾-霾数值预报系统提供了新的能见度参数化算法。      

济南PM2.5质量浓度与气象条件相关性初步研究

通过对济南2013年12月—2018年2月PM2.5质量浓度数据分析得出,PM2.5质量浓度平均和最大值均为冬季最高,春秋季次之,夏季最低;PM2.5质量浓度值1月和12月最高,8月最低;其质量浓度呈明显的逐年递减趋势。在不同风向上PM2.5质量浓度存在显著差异性,在N风向和ESE(盛行)风向上均出现了质量浓度较大值,一方面与污染物的异地输送有关,另一方面与济南的特殊地形有关。研究表明,无论污染源在山脉的背风侧还是迎风侧,都很容易导致高浓度污染;尤其在冬季,山脉地形还会加重逆温影响,使污染程度加重。通过相关性研究发现,冬季、春季和秋季,PM2.5质量浓度与相对湿度和平均总云量均呈正相关,与日照时数及其距平呈负相关;冬季,PM2.5质量浓度与平均气温及其距平以及最高、最低气温均呈正相关,与平均、最高、最低气压均呈负相关;春季和秋季,PM2.5质量浓度与气温距平值呈正相关;夏季和秋季,PM2.5质量浓度与日降水量呈负相关,而且随着雨强的增大,对PM2.5的洗消作用越显著。上述变量间相关性均通过了P≤0.01显著性检验。     

1961—2017年辽宁省旱涝急转现象时空演变特征

利用1961-2017年辽宁省61个气象站逐月降水数据,以5-8月为研究时段建立旱涝急转指数（drought-flood abrupt alternation index,DFAI）序列,采用线性倾向法、趋势分析、阶段性分析、T检验、ArcGIS空间插值等方法对辽宁省降水集中期的旱涝急转现象进行时空特征分析。结果表明：1961-2017年辽宁省降水集中期DFAI总体以-0.7/（10 a）的速率下降,有13 a出现旱转涝,有19 a出现涝转旱;DFAI强度以0.1/（10 a）的速率略呈上升趋势。近57 a,辽宁省旱转涝多发生在20世纪60年代,涝转旱多发生在20世纪70年代和20世纪初之后,1989年出现了涝转旱的突变,发生频率呈增多趋势,1994年又出现旱转涝的突变,发生频率呈减少趋势。典型旱转涝年（2013年）,DFAI的高值区分布在中、西部地区;典型涝转旱年（2014年）,DFAI绝对值的高值区分布在东北部和中西部地区。DFAI变化率在空间分布上具有明显的中、北部增多,东、西部减少的趋势差异。     

1960—2018年辽河流域日降水集中程度分析

基于1960-2018年的日降水资料,计算辽河流域降水集中指数（CI）,分析日降水集中程度的时空特征。结果表明：降水集中指数CI可以有效描述辽河流域降水集中程度,辽河流域年CI指数平均为0.67,降水集中程度总体呈现出东部和西部低、南部和北部高的鞍型空间分布特征;夏季降水集中程度最高,各站点季平均CI指数为0.65,空间分布与年分布较一致,冬季平均CI指数最低,为0.60,由东南向西北递减;研究时段内年CI指数表现为不显著的减小趋势,其中东部区域减小的趋势最大;各子区域年CI指数平均变化周期为3 a左右,其中1985年以前,变化周期较短,在2 a左右,1985年以后,变化周期超过3 a。     

CMIP5模式对辽宁省气温模拟能力及未来2℃升温阈值出现时间评估

利用全球气候模式、多模式集合和辽宁省气象观测数据,评估了不同典型浓度路径下19个全球气候模式和多模式集合对辽宁省气温变化模拟能力和可信度。结果表明:最优模式模拟结果优于多模式集合,具有较高的可信度。随着全球二氧化碳排放浓度增加,气温变化率和可信度呈增加趋势,首次达到2℃年份呈提前趋势,大部分站点出现在2011年之前,且出现年份越晚,升幅往往越高,反之亦然。大部分站点首次稳定到达2℃阈值开始年份在2022年之前,结束年份出现在2019—2026年,持续时间在13 a以下,开始年份均呈西早—东晚分布形势,结束时间和持续时间分布较均匀,且随着全球二氧化碳排放浓度增加,升温幅度呈上升趋势。不同典型浓度路径下各区域最高温、最低温和平均气温出现年份和变化特征均比较一致。     

Acidification of Lower St. Lawrence Estuary Bottom Waters

Accumulation of metabolic CO₂ can acidify marine waters above and beyond the ongoing acidification of the ocean by anthropogenic CO₂. The impact of respiration on carbonate chemistry and pH is most acute in hypoxic and anoxic basins, where metabolic CO₂ accumulates to high concentrations. The bottom waters of the Lower St. Lawrence Estuary (LSLE), where persistently severe hypoxia has developed over the last 80 years, is one such case. We have reconstructed the evolution of pH in the bottom waters from historical and recent data, and from first principles relating the stoichiometry of CO₂ produced to oxygen consumed during microbial degradation of organic matter. Based on the value of the atmospheric partial pressure of CO₂ that best reproduces the preformed dissolved inorganic carbon concentration in the bottom waters, we estimate the average ventilation age of the bottom waters to be 16?±?3 years. The pH of the bottom waters has decreased by 0.2 to 0.3 over the last 75 years, which is four to six times greater than can be attributed to the uptake of anthropogenic CO₂. The pH decrease is accompanied by a decline in the saturation state with respect to both calcite and aragonite. As of 2007, bottom waters in the LSLE are slightly supersaturated with respect to calcite (Ω_c?≈?1.06?±?0.04) but are strongly undersaturated with respect to aragonite (Ω_a?≈?0.67?±?0.03).

     

利用WRF-Chem模拟研究京津冀地区夏季大气污染物的分布和演变

应用WRF—Chem（Weather Research and Forecasting Model with Chemistry）模式模拟研究了2007年8月京津冀地区近地面O3、NO2、PM2.5浓度的时空变化特征,将模拟结果与观测数据进行详细对比,结果表明,模式可以较好地模拟O3、PM2.5,浓度的空间分布和时间变化特征,成功再现了8月33和PM2.5的几次积累增加过程,其中O,的模拟值与观测值的相关系数为0．69～0．86,PM2.5的相关系数为0．44～0．49,但模式对NO2的模拟相对较差,相关系数为0．27～0．43。北京、天津地区为O3月均低值区,月均体积浓度约30×10^-9,渤海及京津冀以西地区O3月平均体积浓度可达60×10^-9;PM2,呈现南高北低的分布特征,变化范围为120～240μg／m3。14时月平均03体积浓度在北京、天津地区低于周边地区,约为60×10^-9;而PM2.5质量浓度在环渤海地区和河北南部较高,为100～120μg/m^3。8月17日北京出现一次典型的高浓度O,污染事件,14时北京地区温度达到33℃,O3体积浓度为80×10^-9～110×10^-9。在局地排放、化学反应和外来输送的共同作用下,渤海西岸和北岸PM2.5的质量浓度超过120μg／m3,其中二次气溶胶质量浓度为50～100μg／m3,一次排放人为气溶胶质量浓度为10～20μg／m3,海盐质量浓度为1～7μg／m3,二次气溶胶是该地区PM2.5的主要贡献者。     

Oceanic climatology in the coupled model FGOALS-g2: Improvements and biases

The present study examines simulated oceanic climatology in the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 (FGOALS-g2) forced by historical external forcing data. The oceanic temperatures and circulations in FGOALS-g2 were found to be comparable to those observed, and substantially improved compared to those simulated by the previous version, FGOALS-g1.0. Compared with simulations by FGOALS-g1.0, the shallow mixed layer depths were better captured in the eastern Atlantic and Pacific Ocean in FGOALS-g2. In the high latitudes of the Northern Hemisphere, the cold biases of SST were about 1°C–5°C smaller in FGOALS-g2. The associated sea ice distributions and their seasonal cycles were more realistic in FGOALS-g2. The pattern of Atlantic Meridional Overturning Circulation (AMOC) was better simulated in FGOALS-g2, although its magnitude was larger than that found in observed data. The simulated Antarctic Circumpolar Current (ACC) transport was about 140 Sv through the Drake Passage, which is close to that observed. Moreover, Antarctic Intermediate Water (AAIW) was better captured in FGOALS-g2. However, large SST cold biases (>3°C) were still found to exist around major western boundary currents and in the Barents Sea, which can be explained by excessively strong oceanic cold advection and unresolved processes owing to the coarse resolution. In the Indo-Pacific warm pool, the cold biases were partly related to the excessive loss of heat from the ocean. Along the eastern coast in the Atlantic and Pacific Oceans, the warm biases were due to overestimation of shortwave radiation. In the Indian Ocean and Southern Ocean, the surface fresh biases were mainly due to the biases of precipitation. In the tropical Pacific Ocean, the surface fresh biases (>2 psu) were mainly caused by excessive precipitation and oceanic advection. In the Indo-Pacific Ocean, fresh biases were also found to dominate in the upper 1000 m, except in the northeastern Indian Ocean. There were warm and salty biases (3°C–4°C and 1–2 psu) from the surface to the bottom in the Labrador Sea, which might be due to large amounts of heat transport and excessive evaporation, respectively. For vertical structures, the maximal biases of temperature and salinity were found to be located at depths of >600 m in the Arctic Ocean, and their values exceeded 4°C and 2 psu, respectively.     

北京一次持续性雾霾过程的阶段性特征及影响因子分析

利用北京地区高时间分辨率观测资料对2009年11月3—8日一次持续性雾霾天气过程中的气象因素和气溶胶演变特征进行了分析。结果表明,该次雾霾过程具有明显的阶段性特征,前期以霾为主,中期发展为雾霾交替,后期随着相对湿度减小再次转换为霾并最终消散。边界层逆温是低能见度过程形成的必要条件,但并不最终决定雾霾低能见度强度。相对湿度和PM_2.5浓度是决定能见度大小的两个关键影响因子,对能见度的影响体现出阶段性特征。大部分时段PM_2.5浓度是影响能见度的主要因子,当能见度小于1 km时,能见度变化更多受相对湿度影响。不同的情景计算表明,控制PM_2.5浓度对于改善本次过程的能见度有重要作用。