MODIS遥感监测滇池蓝藻水华分布

以中分辨率的MODIS数据作为遥感影像源,运用蓝藻水华在蓝波段、红波段和近红外波段的光谱特征,使用假彩色合成法（RGB：6-2-1）和归一化植被指数法对滇池的蓝藻水华进行遥感监测。通过星地同步试验,证明了该两种方法的正确性。其中假彩色合成法通过色彩差异表现蓝藻水华,具有视觉效果较好的优点,归一化植被指数法则以数值大小的方式区别水华浓度,该方法建立反演模型后可用于定量研究。     

保障日照自记纸感光迹线清晰的方法

通过对日照纸涂药药品的试验分析,找出影响日照感光质量的因素为药品纯度不够、配药多用自来水和药品保存过程中药效退化等问题,总结出用混合涂药法配制日照药液的最佳比例为赤血盐、枸橼酸铁铵分别与水的比例（质量比）为1：8和2：8;并结合实际工作经验,总结出提高日照感光质量的方法。     

柳州市糯玉米高产稳产的气象条件分析

通过分期播种试验得出糯玉米的单产、发育期天数、双苞率、穗行数、行粒数、秃顶度等产量因子。以确定高产量的形成与这些产量因子之间的关系:穗行数、行粒数的数值越大,产量就越高。秃顶度则相反,产量高秃顶度小,产量低秃顶度大;高积温易形成高产量,降水条件要求充足且分布均匀也有利于高产量的形成,在南方地区略少的日照有利于干物质的积累。同时分析了气象要素对穗长、穗行数、行粒数的影响:降水有利于高穗位的形成,日照则相反,秃顶度与雨日呈负相关,与日照呈正相关,穗行数与积温呈负相关。行粒数与积温呈正相关,与日照呈负相关。     

结语

1.我省大小麦产量的空间分布和年际波动与大小麦生育期内的日照时数的空间分布和降水量的年际变化密切相关,与生育期的长短有关。就是说,决定我省大小麦产量的地区差异的气候条件主要是日照条件,而产量的年际波动则主要是由降水的多少决定的;有效分蘖期和抽穗成熟期是两个气候关键期,又是决定穗粒重的重要时期,降水偏少日照编多有利于形成合理的穗粒性状。 2.本省大小麦的农业气候条件总的讲是有利有弊,利为主,弊不少。气温高→低→高,降水少→多,日照多→少→多的时间变化与大小麦生育阶段对气象条件的要求基本同步;有一     

苍梧县橄榄生产气象条件分析

通过对橄榄产量与气象条件的相关分析,得出影响橄榄产量形成的关键气象因子,主要有秋梢抽生期,花芽形成期的日照,气温,花果期的降水量等条件,根据这些因子的影响机制及苍梧特定的地理,气候环境条件,提出选好适宜发展种植区,促秋梢,控冬梢以及适时防旱排涝等栽培管理措施。     

中国日照类型区划初探

本文根据日照百分率年变程曲线类型,应用聚类分析方法,把全国划分为12个日照区。主要类型有:冬半年少日照但盛夏干旱多日照形成“A”型的南方区;冬半年多日照但盛夏多雨少日照形成“V”型的东北—华北—西南区;全年日照丰富的南疆区,北疆区和东疆区;以及属于热带干湿季比较分明的南海区。另外,在南方区和东北—华北—西南区之间有5个过渡区;在南海区和南方区之间也有1个过渡区。这12个日照区的地域分布及日照百分率年变程曲线类型与我国天气气候特点很吻合。     

昆明市主城区一次局地短时强降水特征研究

利用NCEP 1°×1°再分析资料、多普勒天气雷达及5 min地面自动站加密观测资料,对2018年6月8日夜间昆明主城区突发的局地短时强降水天气过程,从环流背景、地形作用、中尺度特征等方面进行分析,结果表明:孟加拉湾低压、切变线与地面冷锋是此次过程的天气尺度影响系统;充沛的水汽条件、对流不稳定条件是强降水天气形成的有利条件;主城特殊的地形及南侧滇池水体对降水有增幅作用。多普勒雷达特征显示",列车效应"明显,强回波集中在中低层,具有明显的辐合;6 min的雷达组合反射率CR和雨强分布RZ与5 min的雨量变化有较好的对应关系。     

苍梧县橄榄生产气象条件分析

通过对橄榄产量②与气象条件的相关分析,得出影响橄榄产量形成的关键气象因子,主要有秋梢抽生期、花芽形成期的日照、气温,花果期的降水量等条件.根据这些因子的影响机制及苍梧特定的地理、气候环境条件,提出选好适宜发展种植区、促秋梢、控冬梢以及适时防旱排涝等栽培管理措施.     

铜川日照时数变化特征及影响因素分析

利用铜川3站1964--2003年40a逐日日照观测记录进行分析,结合影响日照的总云量、低云量、烟雾日数、沙尘日数和降水日数等资料,采用数理统计方法,分析了铜川日照的变化和影响日照变化的因素。结果表明：铜川日照时数的年际变化在1964—1984年变化相对平稳,后期出现3～4a周期性变化,90年代中期以后为缓慢增长阶段;季度分布很不均衡,冬季和秋季最小,夏季最大,春季的3月日照时数呈增长趋势;日照时数自北向南逐渐减少,90年代中期以后增幅呈现北部的宜君增多显著,南部的耀州区增长缓慢;云对日照的影响不是简单的量化对比,与云种类有很大关系;雨（雪）、雾、沙尘、烟箍等天气现象均对日照有影响,降水和雾日对日照影响主要是秋季的连阴雨天气,沙尘、烟霾日数远远少于雾日,对日照时数的影响只在冬春季,且影响不大。     

四川省太阳能资源分布特征及其开发利用建议

本文利用四川省1971~2000年日照、水汽及太阳辐射观测资料,分别模拟计算了四川省高原和盆地太阳辐射值,分析了全省日照、太阳辐射及太阳能的分布特征。结果表明:四川省日照分布的基本特征是高原多、盆地少,高原冬春日照多于夏秋,盆地春夏日照多于秋冬;太阳辐射年总量呈经向分布,其东西差异达一倍以上;盆地南部及西南部是四川省乃至全国太阳能资源贫乏区;川西高原是四川省太阳能资源最为丰富的地区,也是全国太阳能资源三级分布区之一,有很大的开发利用价值,对四川省能源的可持续发展有重要意义。     

卫星遥感太湖蓝藻水华分布及其气象影响要素分析

分析2003--2007年太湖蓝藻水华遥感监测信息指出,近年来,太湖蓝藻水华的时空分布具有如下特征:(1)太湖蓝藻水华爆发的频次和覆盖面积有扩大的趋势;(2)蓝藻水华爆发时间范围有从夏、秋季向温度更低的冬、春季发展的趋势;(3)蓝藻水华爆发频次最高的区域以及爆发最严重的区域主要集中在太湖西部和北部.蓝藻水华爆发的影响要素中除了污染物质的分布,还包括各种气象要素.经过地面气象观测资料与卫星观测资料的对比分析,发现温度、风、光照、降水等气象要素都会对蓝藻水华爆发起到一定程度的影响作用.其中温度、光照因素对蓝藻水华爆发起到促进作用,风、降水因素对蓝藻水华爆发起到抑制作用.同时注意到,由于湖泊污染情况正处在不断变化之中,因而各种气象要素对蓝藻水华爆发的影响程度也在发生着变化.     

2007年太湖蓝藻水华提前暴发气象成因探讨

2007年5月太湖蓝藻提前暴发,引发无锡自来水污染,出现供水危机.本文从影响蓝藻水华形成的气象要素入手,分析了无锡2007年冬春季节的气候特点.由于北方冷空气强度偏弱,位置偏北,导致2007年冬春季气候异常,气温记录连创新高,降水偏少,风向转换提前,造成越冬蓝藻种源丰富,复苏繁殖提早,从而导致蓝藻水华提前暴发.     

人工调控措施对玄武湖水质的影响

对玄武湖实施清淤引水、藻华治理、种群恢复等措施前后的水体数据进行分析,结果表明：清淤引水工程可短时间内降低沉积物中污染物浓度,缓解水体富营养化程度,但从长期效果分析,水体中的营养盐含量并未显著改善.藻华治理能在短期内有效抑制水体中的蓝藻水华,治理后水体各项指标均有提升,水生植物种群得以恢复,是短期改善水体水质的有效方式.在种群恢复阶段与往年相比,水体各项指标均有所改善,持续时间更长,是一种理想的湖泊治理方法.     

基于MODIS植被指数的太湖蓝藻信息提取方法研究

有效地提取蓝藻水华信息对分析蓝藻动态分布有重要意义,而卫星遥感技术是进行太湖水质监测与保护的措施之一.本文以2007年7月25日Terra/MODIS数据为主要数据源,用比值植被指数(Irv)、归一化植被指数(Indv)和增强型植被指数(Iev),研究提取太湖蓝藻信息.结果表明:植被指数可以有效提取遥感影像中的蓝藻水华信息,其中Indv是应用效果较好的植被指数之一;在掩膜处理后,用Indv提取了太湖蓝藻的面积分布信息,效果较好;此外,选取Indv为测试变量,利用决策树分类法,有效地把蓝藻水华高浓度覆盖区、中浓度覆盖区和轻浓度覆盖区分开来,为准确掌握太湖蓝藻发生、发展趋势和发生程度提供可靠信息.     

Impact of Taihu Lake on City Ozone in the Yangtze River Delta

The lake-breeze at Taihu Lake generates a different specific heat capacity between the water body and the surrounding land. Taihu Lake has a significant impact on the atmospheric conditions and the air quality in the Yangtze River Delta. This phenomenon is referred to as the Taihu Lake effect. In this study, two simulations were conducted to determine the impact of the Taihu Lake effect in the reference experiment(R-E) and sensitivity experiments(NO TH). The control simulations demonstrated that the meteorological field and the spatial distribution of ozone(O3) concentrations over Taihu lake obviously changed once the land-use type of water body was substituted by cropland. The surface temperature of Taihu Lake was reduced under the impact of Taihu Lake, and a huge temperature difference caused a strong lake-breeze effect. The results also showed that the difference in the average concentrations of O3 between the R-E and NO TH experiments reached 12 ppbv in most areas of Taihu Lake, all day, on 20 May 2014. During daytime(0800–1600 LST, LST=UTC+8), the influence of the Taihu Lake effect on O3 in the Suzhou region was not significant. However, the influence of the Taihu Lake effect on O3 in the Suzhou region was obvious during nighttime(1800–2400 LST). The larger changes in the physical and chemical processes were horizontal and vertical advections under the influence of the Taihu Lake effect in Taihu Lake.     

Sea ice and wind: Effects on primary productivity in the Barents Sea

Abstract

The Barents Sea is divided into a northern and a southern part by the Polar Front (at about 75–76° N) where Atlantic waters descend under Arctic waters. Near to and north of the Polar Front, the spring bloom of phytoplankton is triggered by the stability induced in the upper 20 m by the melting of ice. The pycnocline is too strong to be eroded by wind. Primary productivity after the bloom is therefore small and largely regenerative. Underneath the pycnocline there is a 3–5 m thick layer characterized by dense, slow‐growing algal populations. New productivity north of the Polar Front is no more than 40 g C m^?2 a^?1.

In permanently open waters south of the Polar Front, the spring bloom starts in early May. Rhythmic wind‐induced mixing related to the atmospheric low‐pressure belt reaches an average 40–60 m depth in the growth season, and secondary phytoplankton maxima may arise. As a result, new annual productivity is more than doubled, i.e. 90 g C m^?2 a^?1, relative to the same system without wind. Although productivity is highest south of the Polar Front, it is more concentrated north of it, in the sense that high new production is mainly related to a 20–50 km wide belt that sweeps the area following the ice edge northwards while the ice melts through the summer.     

Spatial distribution and long-term trends of water transparency in Lake Ladoga

Based on the analysis of the surface water transparency (the depth of the Secchi disk disappearance), a seasonal trend of transparency for the entire lake water area was derived for the largest European lake, Lake Ladoga, on an equidistant grid and for limnetic regions. A spatial distribution of monthly mean water transparency of Lake Ladoga is considered from May to October. Climatic trends of transparency are assessed for the period from 1905 to 2003. The climatic trends are analyzed with a linear model used for each month from May to September. The areas with significant negative trends are singled out. A mean trend value is 0.02 m/year. The character of a spatial trend distribution changes depending on the month. In summer, the area with significant trends increases and covers about half of the lake water area. In the spring and in the fall, this area is much smaller and coincides with the southern regions of the lake.     

淀山湖蓝藻发生程度气象预测模型

为了为淀山湖蓝藻控制提供技术依据,根据1998—2009年淀山湖蓝藻发生程度和同期气象资料,用相关分析方法分析淀山湖蓝藻暴发的气象条件,用逐步判别方法建立淀山湖蓝藻发生程度的气象预测模型。结果表明:主要影响淀山湖蓝藻暴发的气象因子是温度。气象指标为:7—8月平均气温大于等于29℃,6—9月日最高气温大于等于35℃日数大于等于16天,7—8月日照时数大于等于420h,6—8月降水量小于等于420mm;气象预测模型Ⅰ(起报时间6月初)和模型Ⅱ(起报时间8月初)拟合的准确率分别为91.7%和100%;2010年试报,模型Ⅰ预测正确,模型Ⅱ预测值比实际值低1级。建立的淀山湖蓝藻发生程度气象预测模型可应用于业务。     

The international polar year (IPY) circumpolar flaw lead (CFL) system study: The importance of brine processes for α‐ and γ‐hexachlorocyclohexane (HCH) accumulation or rejection in sea ice

Abstract

We present evidence that both geophysical and thermodynamic conditions in sea ice are important in understanding pathways of accumulation or rejection of hexachlorocyclohexanes (HCHs). α‐ and γ‐HCH concentrations and α‐HCH enantiomer fractions have been measured in various ice classes and ages from the Canadian High Arctic. Mean α‐HCH concentrations reached 0.642 ± 0.046 ng L–1 in new and young ice (<30 cm), 0.261 ±0.015 ng L–1 in the first‐year ice (30–200 cm) and 0.208 ±0.045 in the old ice (>200 cm). Mean γ‐HCH concentrations were 0.066 ± 0.006 ng L–1 in new and young ice, 0.040 ±0.002 ng L–1 in the first‐year ice and 0.040 ±0.007 ng L–1 in the old ice. In general, α‐HCH concentrations and vertical distributions were highly dependent on the initial entrapment of brine and the subsequent desalination process. γ‐HCH levels and distribution in sea ice were not as clearly related to ice formation processes. During the year, first‐year ice progressed from freezing (accumulation) to melting (ablation). Relations between the geophysical state of the sea ice and the vertical distribution of HCHs are described as ice passes through these thermodynamic states. In melting ice, which corresponded to the algal bloom period, the influence of biological processes within the bottom part of the ice on HCH concentrations and α‐HCH enantiomer fraction is discussed using both univariate and multivariate approaches.