Analysis of the regional spectral properties in northwestern South China Sea based on an empirical orthogonal function

This study presents an analysis of the spectral characteristics of remote sensing reflectance(Rrs)in northwestern South China Sea based on the in situ optical and water quality data for August 2018.Rrswas initially divided into four classes,classes A to D,using the max-classification algorithm,and the spectral properties of whole Rrs were characterized using the empirical orthogonal function(EOF)analysis.Subsequently,the dominant factors in each EOF mode were determined.The results indicated that more than 95%of the variances of Rrs are partly driven by the back-scattering characteristics of the suspended matter.The initial two EOF modes were well correlated with the total suspended matter and back-scattering coefficient.Furthermore,the first EOF modes of the four classes of Rrs(A-D Rrs-EOF1)significantly contributed to the total variances of each Rrs class.In addition,the correlation coefficients between the amplitude factors of class A-D Rrs-EOF1 and the variances of the relevant water quality and optical parameters were better than those of the unclassified ones.The spectral shape of class ARrs-EOF1 was governed by the absorption characteristic of chlorophyll a and colored dissolved organic matter(CDOM).The spectral shape of class B Rrs-EOF1 was governed by the absorption characteristic of CDOM since it exhibited a high correlation with the absorption coefficient of CDOM(ag(λ)),whereas the spectral shape of class C Rrs-EOF1 was governed by the back-scattering characteristics but not affected by the suspended matter.The spectral shape of class D Rrs-EOF1 exhibited a relatively good correlation with all the water quality parameters,which played a significant role in deciding its spectral shape.

ROTATED COMPLEX EMPIRICAL ORTHOGONAL FUNCTION(RCEOF)ANALYSIS:THEORY AND EXAMPLES—PART I

In this paper,a new diagnostic method,the rotated complex empirical orthogonal function (RCEOF)analysis is developed.The general principle and the mathematical foundation of RCEOF are discussed.

ROTATED COMPLEX EMPIRICAL ORTHOGONAL FUNCTION(RCEOF)ANALYSIS—PART Ⅱ:THEORY AND EXAMPLES

The numerical solving and the program designing of the rotated complex empirical orthogonal function(RCEOF)are discussed.Some examples of RCEOF are also presented.

基于REOF的不同量级降雨侵蚀力时空变化——以重庆市为例

研究重庆市不同地理分区内各量级降雨侵蚀力的时空变化特征,为该地区进行更加精准的区域性水土流失防治工作提供理论依据。选取1981-2020年重庆市31个站点逐日降雨数据,利用旋转经验正交函数(Rotated Empirical Orthogonal Function,REOF)对降雨侵蚀力进行地理分区,并结合R/S、5年滑动平均、Mann-Kendall检验等方法,分析各分区不同量级降雨侵蚀力时空变化。结果表明:①重庆市降雨侵蚀力可分为6个地理区域(Ⅰ-Ⅵ区);②重庆市多年平均降雨侵蚀力为5784.04 MJ·mm/(hm^(2)·h·a),不同降雨侵蚀力从大到小依次为:大雨、暴雨、中雨、大暴雨;③大雨侵蚀力在Ⅰ-Ⅲ区和Ⅴ-Ⅵ区占主导优势,暴雨侵蚀力在Ⅳ区占主导优势。各分区中,中雨、大雨及暴雨侵蚀力主要集中在5-9月,大暴雨侵蚀力集中在6-8月;④各区不同量级降雨侵蚀力年际变化从小到大依次为:中雨、大雨、暴雨、大暴雨;同一量级降雨侵蚀力的整体变化趋势均不显著;Hurst指数表明,中雨侵蚀力在Ⅰ和Ⅴ区、大雨侵蚀力在Ⅱ和Ⅴ区、大暴雨侵蚀力在Ⅰ和Ⅲ区呈强持续上升趋势;⑤中雨、大雨及大暴雨侵蚀力在渝东南、渝东北占主导优势,暴雨侵蚀力在渝西以及重庆中部占主导优势,且Ⅰ区酉阳和秀山、Ⅱ区开州、Ⅲ区北碚和铜梁、Ⅳ区璧山和永川、Ⅴ区巫溪和云阳及Ⅵ区忠县是不同量级降雨侵蚀力的高峰中心。通过对重庆各分区不同量级降雨侵蚀力的分析,明确了可能引起土壤侵蚀的主要雨型、高发时期和潜在风险较高的地区,可为区域水土流失动态监测和水土保持措施的合理制定提供参考。

Feature analysis of stratospheric wind and temperature fields over the Antigua site by rocket data

The wind and temperature fields at 20 to 55 km above the Antigua launch site(17°N,61°W)were analyzed by using sounding rocket data published by the research organization on Stratosphere-Troposphere Processes and their Role in Climate(SPARC).The results showed distinct variations in the wind and temperature fields at different heights from the 1960s to the 1990s.The overall zonal wind speed showed a significant increasing trend with the year,and the overall change in meridional wind speed showed a falling trend from 1976 to 1990,whereas the temperature field showed a significant cooling trend from 1964 to 1990.The times the trends mutated varied at different levels.By taking the altitudes at 20,35,and 50 km as representatives,we found that the zonal wind speed trend had mutated in 1988,1986,and 1986,respectively;that the meridional wind speed trend had mutated in 1990,1986,and 1990,respectively;and that the temperature trend had mutated separately in 1977,1973,and 1967,respectively.Characteristics of the periodic wind and temperature field variations at different heights were also analyzed,and obvious differences were found in time scale variations across the different layers.The zonal and meridional wind fields were basically characterized as having a significant periodic variation of 5 years across the three layers,and each level was characterized as having a periodic variation of less than 5 years.Temperature field variation at the three levels was basically characterized as occurring in 10-year and 5-year cycles.

基于complex-EOF的高频地波雷达海流数据的空时特性

利用布设在高频地波雷达福建示范区的东山、龙海2个雷达站的约3天的海流数据进行矢量正交经验函数分析。分析结果表明前3个模态的方差贡献率分别为91%、4%和1.4%,累计方差贡献率达到了96%,是主要模态。模态1的空时分布特性表明模态1主要反映了半日潮流的信息,并且在一定程度上反映了水深分布的信息;模态2的空时分布特性表明模态2主要反映了风生流以及流场旋转特性的信息;模态3的空时分布特性表明模态3主要反映了上升流的信息。

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR-SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.

Statistical analysis of surface hydrography and circulation variations in northern South China Sea

To study the variations in surface hydrography and circulation in northern South China Sea (NSCS), rotated empirical orthogonal function (REOF) and extended associate pattern analysis (EAPA) are used with daily sea surface salinity (SSS), sea surface temperature (SST) and sea surface height (SSH) datasets cover- ing 1 126 days from American Navy Experimental Real-Time East Asian Seas Ocean Nowcast System in this paper. Results show that in summer, the SCS Diluted Water Expansion (SDWE) is the most dominant factor con- trolling SSS variations in the NSCS. The remarkable SDWE usually begins in early July, reaches its maximum in middle August and weakens in late September. In summer flourishing period, its low saline core is just limited between 21°N and 22°N because of strong surface anomalous anticyclonic circulation in the NSCS. In early or late stage, the anomalous anticyclonic circulation becomes weak or turns into cyclonic one, thus the weak SCS diluted water can disperse. And its influence on the SSS variations has obviously decreased. The Kuroshio intrusion is the second controlling factor, and it has the almost opposite seasonal or intraseasonal oscillations and spatial charac- teristics to the SDWE. Winter Kuroshio Intrusion (WKI) begins in early November and lasts about three months. Intraseasonal Kuroshio Intrusion (IKI) takes place at any seasons. The westward Ekman transport produced by the north anomaly of East Asia Monsoon (EAM) pushes warmer and more saline seawater into the NSCS through the Bashi Strait and seems to decide the intensity of seasonal and intraseasonal Kuroshio intrusions.

斯里兰卡极端降水时空演变特征及趋势预测

斯里兰卡是中国“一带一路”倡议的重要节点国家,极端降水对当地社会经济威胁较大,极易引发灾害。选取当地10个气象站2008—2020年的逐日降水资料,基于RClimDex模型计算斯里兰卡6个极端降水指标,利用经验正交函数分析、Morlet小波分析和重标极差法(R/S分析)等,分析极端降水事件的时空演变特征。结果表明:极端降水指数在时间分布上,除持续干旱指数(CDD)呈减少趋势外,其他各指数均为上升趋势;极端降水指数空间差异表现为北部沿海平原地带的极端降水强度高于南部沿海平原,拉特纳普勒市以西地区为斯里兰卡降水事件的多发区;极端降水指数周期性明显,绝大多数极端降水指数以6~7 a为第一主周期。R/S分析表明当地极端降水事件未来持续可能性较大。研究成果可为斯里兰卡极端气候预测、生态环境保护、防灾减灾工作等提供决策支持。

青海省多年地表感热通量的时空变化特征

选取青海省35个气象站观测数据,基于CHEN-WENG感热系数方案,计算了1980—2017年青海省地表感热通量。利用小波分析、Mann-Kendall突变检验和经验正交函数法(Empirical Orthogonal Function,EOF),对感热通量的时空变化特征及其影响因子进行分析。结果表明:(1)1980年以来,青海省全年和各季节感热通量总体上均呈上升趋势,并具有28 a的主周期和约18 a的副周期,冬季的周期变化较为复杂;(2)全年和各季节感热通量与地气温差存在显著相关性,2004—2017年受地气温差增大的影响上升;(3)全年、春季和秋季感热通量与风速存在显著相关性,1980—2004年受风速减小的影响感热通量下降;(4)夏季降水与感热通量呈显著负相关;(5)从空间上看,全年以及春季感热通量呈现出显著的东西分异,秋、冬季表现出一定程度的南北分异。

基于REOF分析的山东省年降水区域特征及趋势分析

[目的]探究山东省不同气候分区年降水量的时空特征,为该地区气候分析、防灾减灾提供更加区域性的参考依据。[方法]根据山东省95个国家地面气象观测站1991—2020年降水年值数据,首先对山东省年降水场进行气候分区,然后通过相关统计方法分析各分区降水的时空变化特征。[结果](1)山东省各降水模态降水偏少的年份更多,降水偏多的年份降水强度更大,年代际变化均较为明显,但各模态降水偏多偏少的年份分布及强度变化有所不同。(2)山东省年降水量大致由东南向西北递减,年降水场划分为东南沿海区(Ⅰ区)、西北平原区(Ⅱ区)和中部山地区(Ⅲ区)3个区域,各降水分区年降水均呈不显著增加趋势,趋势率各不相同,突变均不明显。(3)山东省各降水分区年降水量均具有较为明显的周期性特征,东南沿海区年降水场存在2个较为明显的能量中心,中心尺度均为2~3 a,未来变化具有强持续性;西北平原区年降水场存在3个较为明显的能量中心,中心尺度分别为5~7 a, 3 a和2~3 a,未来变化具有持续性;中部山地区年降水场存在2个较为明显的能量中心,中心尺度分别为2~3 a, 6 a,未来变化具有强持续性。[结论]山东省降水偏少的年份更多,降水偏多的年份降水强度更大,年降水场大致可分为3个分区,各分区年降水量均呈不显著增加趋势,均具有较为明显的周期性特征,且未来变化均具有持续性。

基于相对湿润指数的浙江省茶叶气象干旱特征分析

【目的】研究浙江省茶叶气象干旱的演变规律,为茶叶安全生产优化布局提供科学依据。【方法】利用浙江省68个地面气象观测站50 a(1971—2020年)的逐日气温、降水量、日照时数等数据,基于相对湿润指数、正交经验函数和小波分析法等分析浙江省茶叶气象干旱的时空分布规律。【结果】浙江省茶叶生产夏季干旱的强度和发生频率高于秋季,且均呈现西高东低的分布,中西部尤其金衢盆地的干旱强度和频率为全省最强,浙北地区次之,沿海地区最小。茶叶夏季干旱站次比呈逐年下降的趋势,秋季则呈现先升后降的趋势,2000年以后夏秋两季出现极端大范围茶叶气象干旱的年份增多。茶叶夏季和秋季干旱强度的正交经验函数第一模态表现为全省变化一致性,第二模态中沿海局部地区和内陆呈反相位变化,夏秋两季干旱强度的主模态时间序列分别存在2-6、2-4、6-10 a的振荡周期。【结论】浙江省在夏季和秋季出现茶叶气象干旱的频率在下降,但出现极端干旱的概率在增加,应重点加强茶叶主产区干旱监测预警能力建设,提升防旱抗旱能力。

1961—2020年黄河源区降水时空变化特征研究

基于1961—2020年黄河源区16个雨量站点的逐日降水资料,应用线性趋势法、Mann-Kendall(MK)检验、滑动t检验、Pettitt检验、小波分析、经验正交分解(EOF)方法对黄河源区年降水、季节降水、汛期降水的变化趋势及时空分布特征进行分析。结果表明:(1)黄河源区年降水以10.0 mm/10 a的趋势显著增加;除冬季呈不明显的减少趋势外,春季、夏季、秋季和汛期降水同样呈增加趋势。(2)黄河源区降水除春季无明显突变外,全年、夏季、秋季、冬季和汛期的对应突变年份分别为2015年、1998年、2018年、2016年和2019年。(3)黄河源区年降水存在3~7 a、6~12 a、9~13 a和16~24 a的变化周期,第一、第二主周期为19 a和11 a,两种主周期都经历了3次“丰-枯”变化;年降水存在2种模态,4种降水表现类型,2种模态的年份数为35 a和13 a。研究成果可为黄河源区防汛抗旱及上游水库群水资源调度提供参考。

北部湾叶绿素a浓度时空变化及影响因素

【目的】研究北部湾表层叶绿素a质量浓度的时空分布及其影响因子,为北部湾初级生产力评估及深远海养殖提供依据。【方法】基于2003-2020年逐月卫星遥感叶绿素a质量浓度、海表面温度(SST)、降雨数据以及再分析风场数据,利用经验正交分解(EOF)、小波相干等方法分析SST、降雨、风等环境因子对北部湾叶绿素a质量浓度的影响。【结果与结论】北部湾叶绿素a质量浓度呈近岸高、中央低的空间分布规律。年际变化特征明显,2016年为浓度峰值年,平均质量浓度为1.6 mg·m^(-3),2010年质量浓度最低,仅为1.1 mg·m^(-3)。在季节变化方面,北部湾区域平均叶绿素a质量浓度冬季最高,春季浓度最低,涠洲岛南侧海域平均叶绿素a质量浓度冬季最高,夏季节最低。红河河口区域夏、秋叶绿素a质量浓度高于春、冬叶绿素a质量浓度。长山山脉东侧区域平均叶绿素a质量浓度在秋季最高,在春季最低。月变化方面,北部湾叶绿素a质量浓度在5月最低,12月最高。海表面温度、降雨和风是影响北部湾叶绿素a质量浓度时空分布的主要因素。在北部湾的中、东海域,海表面温度与叶绿素a质量浓度显著负相关(P <0.05,r <-0.8)。降雨的影响主要集中在湾西部,降雨增加的径流量提供更多营养物质,使红河河口区域夏、秋季叶绿素a质量浓度较高,长山山脉东岸区域叶绿素a质量浓度在秋季达到峰值。风速与北部湾叶绿素a质量浓度显著正相关(P <0.01,r=0.4)。

基于索周法的辽宁省干旱周期演变特征研究

为探究辽宁省不同气候特征区域年、季干旱周期性规律,基于辽宁省22个国家地面气象观测站1961~2020年逐日降水数据,首先采用旋转经验正交函数对研究区进行降水分区,再计算不同时间尺度的标准化降水指数,利用索周法分析各分区不同尺度标准化降水指数周期特征,并与Morlet小波周期分析的结果进行对比。研究表明,索周法可以很好地应用于干旱周期分析。年尺度上,Ⅰ、Ⅱ区存在7年左右的显著周期规律,Ⅲ区周期规律以5年为主。季尺度上,Ⅰ、Ⅱ区各季节的周期规律以4~7年为主,而Ⅲ区周期尺度稍长,各季节主要表现为6~9年,各分区不同时间尺度周期演变特征存在一定的差异。

Spatio-temporal variability of surface chlorophyll a in the Yellow Sea and the East China Sea based on reconstructions of satellite data of 2001-2020

Chlorophyll-a(Chl-a)concentration is a primary indicator for marine environmental monitoring.The spatio-temporal variations of sea surface Chl-a concentration in the Yellow Sea(YS)and the East China Sea(ECS)in 2001-2020 were investigated by reconstructing the MODIS Level 3 products with the data interpolation empirical orthogonal function(DINEOF)method.The reconstructed results by interpolating the combined MODIS daily+8-day datasets were found better than those merely by interpolating daily or 8-day data.Chl-a concentration in the YS and the ECS reached its maximum in spring,with blooms occurring,decreased in summer and autumn,and increased in late autumn and early winter.By performing empirical orthogonal function(EOF)decomposition of the reconstructed data fields and correlation analysis with several potential environmental factors,we found that the sea surface temperature(SST)plays a significant role in the seasonal variation of Chl a,especially during spring and summer.The increase of SST in spring and the upper-layer nutrients mixed up during the last winter might favor the occurrence of spring blooms.The high sea surface temperature(SST)throughout the summer would strengthen the vertical stratification and prevent nutrients supply from deep water,resulting in low surface Chl-a concentrations.The sea surface Chl-a concentration in the YS was found decreased significantly from 2012 to 2020,which was possibly related to the Pacific Decadal Oscillation(PDO).

太行山地区1973—2022年暴雨时空演变特征分析

基于太行山地区13个气象站点50 a的逐日降水数据,使用Mann-Kendall突变检验、信噪比检验、Sen’s斜率估计、小波分析法、正交函数分解等方法,对太行山地区的暴雨时空演变规律进行了研究。结果表明:(1)太行山地区年暴雨量波动幅度较大,根据拟合斜率和Sen’s斜率估计法的结果可知,太行山地区的暴雨量将会呈增多趋势;(2)Mann-Kendall突变检验和信噪比检验结果表明,2006年太行山暴雨量发生了由少变多的突变;(3)Morlet小波分析结果表明,在2017—2020间研究区暴雨量存在2~3 a的周期尺度变换;(4)该地区暴雨量经验正交函数(EOF)展开的前两个模态显示,暴雨量呈现全区一致变化以及西南—东北向的空间变化特征,这两个模态情境下的暴雨状况受到环流因子和地形的共同影响。

贵州夏季降水异常及其与海温异常的关系

利用贵州1961—2018年夏季0.5°×0.5°格点月降水资料和全球逐月海面温度(以下简称“海温”)资料,分析贵州夏季降水量的时空分布特征及其与前期海温的联系,并合成分析海温异常影响大气环流异常从而对降水量产生的影响。结果表明:(1)贵州夏季和夏季各月降水量均无显著趋势变化,降水量从东北部的中部向西南逐渐增加,并且贵州夏季降水异常主要有全区一致型、南北反向型和东西反向型3个模态。(2)贵州夏季降水异常与北赤道暖流区、加利福尼亚冷流区、北太平洋中纬度海域的海温异常联系密切。(3)北赤道暖流区和加利福尼亚冷流区的显著时段是前一年6—11月,其中7月影响最为显著,影响范围主要是贵州东部及南部;北太平洋中纬度海域是前一年6—7月,其中7月影响最为显著,影响范围主要是贵州东北部及东南部。(4)关键海区海温与贵州降水偏少年的联系不如偏多年密切。

近30年中国雷暴天气气候特征分析

利用1981-2010年雷暴观测资料,采用EOF分解和主值函数分析等方法,对中国年平均雷暴日的时空分布特征、年际变化及异常变化特征进行了分析。结果表明,年平均雷暴日的地理分布可大致分为4个区域,分别为东南高发区、西南高发区、东北次高区和西北低发区。年平均雷暴日的时间分布表现为夏季多、冬季少;一天之中雷暴出现的时间集中在下午到晚上。雷暴日数的年际变化呈现出1980年代和2000年代2个相对多发期和1990年代相对少发期,其中2000年代雷暴事件的相对多发表现为下午和夜间雷暴事件的增加。近30年中国北方地区的雷暴整体呈现出减少趋势,而南方则是先减后增,其距平场的年代际变化较为明显。EOF分解后距平场第一向量的方差贡献达到32.4%,在空间上表现为南北相异型,其余各向量也不同程度地表现出区域性异常,前12个向量累积方差贡献达到80.9%。此外,ENSO事件对中国雷暴尤其是南方地区影响较为明显,两广和云贵地区呈现出相反的距平变化。

新疆艾比湖流域土壤有机质的空间分布特征及其影响因素

根据新疆艾比湖流域土壤有机质(SOM)数据,分析了土壤质地、植被群落类型和土壤剖面深度3个因素对SOM含量的影响,进一步研究了流域内有机质在不同土壤深度的空间分布特征及其沿土壤剖面深度垂直分布的空间异质性。结果表明:植被群落类型显著影响SOM含量,而土壤质地和深度对有机质总体分布水平影响不显著;随土壤深度变化有机质分布呈现不同的空间变异特征,流域内0—80 cm土壤有机质高含量区域与低含量区域斑块化分布呈现孔穴特征,但在80—120 cm土壤有机质含量变化较为连续,呈现流域东、西两端高而中间低的分布特征;有机质沿土壤深度垂直分布模式在流域内表现出分异特征,流域中部SOM随土壤深度增加而降低,SOM含量从0—20 cm浅层土壤的2.85 g/kg降至100—120 cm深层土壤的1.51 g/kg;但在流域东部和西部SOM随土壤深度增加呈升高趋势,流域西部SOM含量从0—20 cm土壤的1.80 g/kg大幅增加至100—120cm土壤的6.61 g/kg,流域东部SOM含量则从0—20 cm土壤的1.04 g/kg逐步增至100—120 cm土壤的2.86g/kg。艾比湖流域有机质在浅层和深层土壤不同的空间分布特征与干旱区绿洲生态景观斑块化分异特征和植被根际沉积特点密切相关,流域内土壤剖面成土演化的空间异质性对有机质沿土壤深度垂直分布的空间变异性有显著制约。