翟召坤
, 卢善龙, 王萍
ZHAI Zhaokun, LU Shanlong, WANG Ping
通讯作者:
收稿日期: 2016-05-1
修回日期: 2016-10-11
网络出版日期: 2017-02-28
版权声明: 2017 《地球信息科学学报》编辑部 《地球信息科学学报》编辑部 所有
基金资助:
作者简介:
作者简介：翟召坤（1991-）,男,山东淄博人,硕士生,主要从事水资源遥感与软件系统开发方面研究。 E-mail: zhaokunzhai@163.com
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摘要
北极海冰对全球气候起着非常重要的调制作用,海冰范围是海冰监测的基本参数。近40年,北极地区持续变暖,北极海冰显著减少,进而引发北极自然环境恶化、北半球极端天气频发、全球海平面上升等一系列环境和气候问题。准确获取北极海冰范围及其演变趋势,确定海冰变化对全球气候系统的响应,是研究和预测全球气候变化趋势的关键之一。HasISST和OISST海冰数据集在海冰监测中应用最为广泛,可为北极地区长时间序列海冰变化研究提供基础数据,但这2套数据集空间分辨率相对较低,应用于北极关键区对中国气候响应研究方面存在很大的局限,为解决这一问题和弥补国内海冰监测微波遥感数据的空白,2011年6月27日,国家卫星气象中心（National Satellite Meteorological Center, NSMC）发布了FY（Fengyun, FY）北极海冰数据集,该数据集利用搭载在FY卫星上的微波成像仪（Microwave Radiation Imager, MWRI）数据,使用Enhance NASA Team算法制作,该算法利用前向辐射传输模型模拟北极地区4种海表类型（海水、新生冰、一年冰和多年冰）在不同大气条件下MWRI辐射亮温,进而得到每种大气条件下0~100%的海冰覆盖度查找表（海冰覆盖度每次增加1%）,通过观测值与模拟值的比对得到海冰覆盖度,由该数据集计算得到的北极海冰范围在大部分区域与实际情况相符。该产品虽已进行通道间匹配误差修正和定位精度偏差订正,但由于其搭载的微波成像仪（Microwave Radiation Imager, MWRI）天线长度有限,造成传感器探测到的地物回波信号相对较弱,难以区分海冰和近岸附近的陆地,影响了该数据集的精度和应用。为解决这一问题,本文基于美国冰雪中心（National Snow and Ice Data Center, NSIDC）发布的海冰产品对FY海冰数据集进行优化,NSIDC产品利用判断矩阵对海岸线附近的像元进行识别,并对误差像元进行不同程度的修正,由NSIDC产品计算得到的北极海冰范围与实际情况更为符合。数据集优化大大提高了FY海冰数据集的精度,研究结果表明,优化后FY海冰数据集与NSIDC产品相关系数高达0.9997,且二者日、月、年平均最大海冰范围偏差仅为3.5%、1.9%、0.9%,且FY海冰数据集优化过程对其较好的空间分异特征无明显影响。该数据集可正确地反映北极海冰范围及其变化情况,且海岸线附近海冰的分布情况更准确,可为北极海冰变化研究提供可靠的基础数据。
关键词：
Abstract
Arctic sea ice plays a very important role in the modulation of global climate and sea ice extent is a basic parameter for sea ice monitoring. In recent 40 years, a series of environmental and climatic issues such as degradation of Arctic natural environment, frequent extreme weather in the Northern Hemisphere and global sea-level rise are caused by continuous warming and apparent sea ice decrease in Arctic. So it′s important to know the extent, variation, trend of Arctic sea ice and its response to global climate change. The most commonly used datasets such as HadISST and OISST sea ice dataset provided long time series of changes in sea ice of the Arctic regions. However, the spatial resolution of these datasets is relatively low. There are some limits in the study of response of sea ice change in Arctic key regions to weather and climate in China. To overcome these problems and to make up the lack of passive microwave sea ice dataset provided by China, FY (Feng Yun) sea ice dataset is developed by NSMC (National Satellite Meteorological Center) on June 27th, 2011. In this dataset, the Enhanced NASA Team (NT2) algorithm is used based on the data of MWRI (Microwave Radiation Imager) sensor carried on FY satellite. In this algorithm, direct radiative transfer model is used to model MWRI brightness temperature for four surface types (ice-free ocean, new-formed ice, one-year ice and multi-years ice) and for different atmospheric conditions. Then, sea ice coverage lookup table (0% to 100% in 1% increments) is obtained based on modeled brightness temperature considering different atmospheric conditions. Sea ice coverage is confirmed by comparing observed value with modeled value. Sea ice extent is consistent with the actual situation in most Arctic regions. Although matching errors between channels and positioning errors have been corrected in FY dataset, the received echo signal is relatively weak due to the shorter antenna on MWRI. The weak echo signal makes it difficult to correctly differentiate the boundary between sea ice and near sea shore land, which greatly impact the total accuracy of the dataset and its application. In order to solve this problem, this study introduces a method of optimizing FY Arctic sea ice dataset based on NSIDC (National Snow and Ice Data Center) sea ice product. In NSIDC product, judgment matrix was created covering the entire grid and identifying each pixel as land, shore, near-shore, offshore or ocean as determined by the land/sea mask. Then, these different pixels are corrected in different degrees, respectively. Sea ice extent calculated from NSIDC product is strongly consistent to the actual situation. The accuracy of FY dataset is greatly improved. The analysis results indicated an extremely significantly positive correlation with the NSIDC product (R2 = 0.9997) during June 27th, 2011-December 31st, 2015. The maximum deviation percent of daily, monthly and annually sea ice extent is 3.5%, 1.9% and 0.9%, respectively. Also, the optimization process of FY dataset has no obvious influence on the spatial stratified heterogeneity of the dataset. The optimized FY dataset can correctly reflect Arctic sea ice extent and its variation, especially in coastline regions. It can provide reliable basic data for the study of Arctic sea ice change.
Keywords：
北极海冰约占全球海冰面积的30%[1],在全球气候系统中扮演重要角色[2-4]。海冰的反照率高达80%[5],可通过改变海气之间的热量、水汽交换通 量[6]来影响区域乃至全球气候系统。近年来,北极地区持续变暖,且速度远高于全球平均水平,北极年均海冰范围在1978-2012年持续减少,每10年减少3.5%~4.1%,夏季减小最快[7],2007年和2012年夏季北极海冰覆盖面积大幅度减少,在过去1450年以来都是独一无二的[8]。北极海冰的上述变化对区域和全球气候变化影响成为了热点研究内容,尤其是2007年和2012年夏季北极海冰极小值的出现与中纬度地区天气、气候的响应关系引起了国内外很多学者的关注[9-12],从而使人们对反映海冰变化数据集的准确性、时间过程连续性和空间分辨率一致性提出了更高要求。
卫星遥感技术在海冰监测中发挥不可替代的作用[13],多光谱遥感数据空间分辨率相对较高,但受天气影响较大,数据量有限,很难形成质量较高海冰产品;微波遥感具有全天时、全天候的特点[14],利用微波辐射亮度温度数据反演得到海冰覆盖度,进而得到海冰范围和面积是目前全球海冰监测的主要方法[15]。很多学者根据一年冰、多年冰、有强烈地表散射的海冰等不同类型海冰特点以及卫星传感器的特性,设计了多种海冰提取算法并制作了一系列海冰产品。Cavalieri等[16]和Comiso等[17]利用搭载在Nimbus-7上的多通道扫描微波辐射计（SMMR）、DMSP上的专用微波成像仪（SSM/I）和专用微波成像/探测仪（SSMIS）的低空间分辨率频段数据,分别采用NASA Team算法[18]和Bootstrap算法[19],反演得到空间分辨率为25 km的NSIDC全球海冰产品;Spreen等[20]利用分别搭载在Aqua和GCOM-W1上的AMSR-E和AMSR2的高空间分辨率频段数据,采用ARTIST Sea Ice（ASI）算法[20]反演得到空间分辨率为6.25 km的ASI全球海冰产品,但该产品时间过程存在中断情况;Rayner等[21]和Reynolds等[22]综合现有的数字化海冰图表和微波海冰产品,并在误差校正的基础上分别制作了全球海冰数据集HadISST和OISST,但产品的空间分辨率仅为1°。
风云三号B星（FY3B）是中国新一代极轨气象卫星,为中期数值天气预报、全球变化研究和预测、大范围自然灾害和地表生态环境监测提供基础数据。搭载在该星上的微波成像仪（Microwave Radiation Imager, MWRI）为海冰研究增添了新的数据源,杨虎等[23]将MWRI传感器与国际上同类仪器进行对比,该传感器偏差特性与同类微波遥感仪器相当,能够为地球物理参数的反演提供足够高的精 度,且该传感器空间分辨率优于国外同类型传感器（SMMR、SMM/I、SSMIS）。杨虎等利用MWRI数据,采用Enhanced NASA Team算法[24],反演得到了空间分辨率为12.5 km的FY全球海冰产品。该产品虽已进行通道扫描方向偏差修正和定位精度偏差订正,但由于MWRI传感器天线长度有限,造成传感器探测到的地物回波信号相对较弱,且传感器获取的数据地理定位不准,导致已发布的FY海冰数据集海岸线附近海水、海冰、陆地像元存在错分现象,由该产品得到的北极海冰范围整体偏大,与实际海冰分布情况不符,影响了该产品在北极海冰监测业务系统中的应用。
目前时间一致性较好的2套产品分别为哈德莱气候预报中心（Hadley）制作的HadISST海冰数据和美国国家环境预报中心（NCEP）制作的OISST海冰数据,二者对重叠时间段的海冰数据进行偏差调整,取得了非常好的一致性,但2套产品空间分辨率仅为1°,用于分析北极海冰变化对中国气候影响,特别是研究格陵兰海、巴伦支海、喀拉海等关键海区的影响方面,存在较大的局限;MODIS海冰产品利用光学遥感数据得到,空间分辨率最高可达1 km[25],但受云雾影响,难以形成时间过程连续、空间范围全覆盖的海冰产品;而其他高空间分辨率光学传感器数据由于卫星重访周期较长,目前仅应用于局地海域海冰监测,还未大规模应用于北极海冰监测;NSIDC和NCEP海冰产品空间分辨率相对较高[26-27],时间序列也较长,且NSIDC产品在制作过程中,对海岸线附近海水、海冰、陆地像元错分现象进行了修正,使海冰的分布更符合实际情况。为了制作一套时空过程连续且能满足应用精度需求的FY海冰数据集,本文以NSIDC产品为参考数据源,对FY北极海冰数据集进行了优化,得到了空间分布较为准确、空间分辨率较高的北极海冰数据集,为北极海冰变化研究提供了基础数据。
研究区为整个北极地区,即北纬66°34'以内的区域,总面积为2100万km2,包括北冰洋以及格陵兰岛、埃尔斯米尔岛、帕里群岛等诸多岛屿和亚、欧、北美大陆北部的部分区域[28],主要海域有格陵兰海、喀拉海、巴伦支海等海域（图1）。
本文采用的数据源包括NSIDC和FY北极海冰数据集,由于FY海冰数据集是使用Enhanced NASA Team算法反演得到的空间分辨率为12.5 km的产品,研究选用经插值得到的使用NASA Team算法反演得到的空间分辨率为12.5 km的NSIDC海冰产品。其中,NSIDC和FY海冰数据集分别是美国国家冰雪数据中心网站（http://nsidc.org/data/polaris/）和国家卫星气象中心风云卫星遥感数据服务网（http://fy3.satellite.cma.gov.cn/portalsite/default.aspx）公开共享的海冰产品,二者时间跨度均为2011年6月27日至 2015年12月31日。
数据预处理包括格式转换、投影处理和海冰覆盖度范围调整。其中,数据集格式统一转换为Geotiff;投影参数为极方位立体投影（Polar Stereographic Grids）[29-30];海冰覆盖度范围统一调整为0~100,110为极点区域无意义值,120为陆地。
图2 陆地、海水辐射亮温的模型模拟值和实际测量值[
Fig. 2 Simulated and measured brightnesstemperature between land and sea[
在微波遥感影像上,陆地区域的实际辐射亮度温度高于海水,且差异较为明显（图2）,但由于传感器自身的原因,实际获取的亮温差异变小,导致海冰产品海岸线附近海水、海冰、陆地像元错分现象,这种情况在夏季尤为严重。NSIDC产品利用判断矩阵对海岸线附近的像元进行识别并对异常情况分别进行不同程度的修正,使海冰分布情况更符合实际情况;FY的MWRI传感器精度略低于SMMR、SMM/I、SSMIS,虽然FY产品虽也进行过类似的处理,但在现有发布的产品中此误差仍然非常明显,通过对比分析同时相的NSIDC和FY产品,发现在北极地区大部分区域,二者海冰分布情况较为一致,但在海陆交界处二者差异较大,主要表现为FY产品部分海水和陆地被错分为海冰,且FY产品北极点中心无意义区域过大,导致FY产品海冰范围偏大,通过处理这两部分误差即可实现FY海冰数据集精度的大幅提高。由于二者均是对北极海冰实际分布情况的反映,且空间分辨率一致,因此,本研究使用NSIDC产品对FY产品进行修正。
图3 NSIDC与FY修正后海冰范围散点图
Fig. 3 Linear regression analysis between NSIDC and enhanced FY sea ice extent
对比分析NSIDC和FY产品空间分布（图3）,本研究对FY产品海水错分为海冰、陆地错分为海冰、海冰错分为陆地、海冰错分为无意义区域、海水错分为无意义区域5种情况。对其分别参照NSIDC产品进行修正,具体方法如下：
式中：D1和D2分别为NSIDC和FY海冰产品;A、B、C、D分别代表海水、海冰覆盖度、无意义值和陆地取值范围。
本文选取判定系数、最大偏差百分比、空间分异性来评价修正后FY产品的精度。相关系数R（式（6））是衡量2个变量之间线性相关程度的指标,相关系数的平方称为判定系数,判定系数的大小决定了2个变量之间相关的密切程度;偏差百分比（Percentage of Deviation, PD）为修正值与参考值之间偏差百分比（式（7））,其中,CE（Corrected Extent）为修正后FY产品海冰范围,RE（Reference Extent）为NSIDC产品海冰范围;空间分异性,全称空间分层异质性（spatial stratified heterogeneity）,是指某一属性值在不同区域之间存在差异,如气候分带、生态分区、地理区划、以及各种分类现象,可利用地理探测器q-statistic（式（8））来检验不同产品的可分 性[31-32]。式（8）中,总体（population）被划分为h=1,…,L个层（strata）,即L个子区域或L个子总体,N和
对NSIDC产品和FY修正后产品重叠时间段内日平均海冰范围偏差值进行统计,发现二者的偏差较小,且对二者偏差最大的前20组数据进行线性回归分析表明,二者之间的判定系数R2为0.9997（图3）,说明修正后的FY产品与NSIDC产品一致性较好。
利用式（7）对2套产品进行不同时间尺度偏差分析,结果表明,二者日平均、月平均、年平均最大偏差分别出现在2014年6月30日、2015年7月、2015年,最大偏差百分比分别为3.5%、1.9%、0.9%,修正后FY产品与NSIDC产品具有非常好的一 致性。
利用式（8）对NSIDC产品和修正前后FY产品进行空间分异性检验,发现q值均为1,说明NSIDC产品和FY产品修正前后均具有较好的空间分异,且FY数据集优化过程对其较好的空间分异特征无明显影响。
本文选取NSIDC产品与修正前后FY产品在重叠时间段内（2011年6月27日至2015年12月31日）春、夏、秋、冬4个季节同一时相海水、海冰、陆地空间分布进行对比（图4）。研究表明：① 春季,FY产品亚欧大陆海岸线附近存在部分陆地错分为海冰的情况,冰岛海岸线附近此情况较为严重,北大西洋和五大湖地区均存在部分海水错分为海冰的情况（图4（b））,经过修正,错分现象得到明显改善（图4（c））;② 夏季,FY产品在格陵兰岛海岸线附近存在部分陆地错分为海冰的情况,北美大陆海岸线附近、巴伦支海附近及五大湖地区错分情况较为严重（图4（e））,修正后,分布情况趋于正常（图4（f））;③ 秋季,FY产品在亚欧大陆及北美大陆海岸线附近陆地错分为海冰的情况特别严重,北美大陆部分地区存在少量海水错为分海冰的情况（图4（h））,修正后,分布情况趋于正常（图4（i））;④ 冬季,FY产品陆地错分为海冰的现象主要集中在冰岛和北美大陆,巴伦支海附近也存在少量陆地错分为海冰的情况（图4（k））,经过修正,错分现象得到明显改善（图4（l））;且FY产品北极点中心无意义区域过大的现象均得到了修正。
图4 NSIDC产品（a, d, g, j）与FY产品修正前（b, e, h, k）、修正后（c, f, i, l）空间分布对比图
Fig. 4 Spatial distribution maps of NSIDC (a, d, g, j), the original FY product (b, e, h, k) and the enhanced FY product (c, f, i, l)
研究区NSIDC产品与修正前后FY产品在重叠时间段内的日平均海冰范围对比结果表明,修正前FY产品海冰范围整体比NSIDC产品大,且二者差异在2012年夏季达到最大,修正后此现象得到消除;将轨道数据插值到网格数据时发生异常,修正前FY产品海冰范围在2011年9月30日、2012年5月7日、20日及7月5日、6日、7日和2015年5月4日存在异常跳跃现象（图5中圆圈所示）,修正后此现象得到消除;修正前FY产品海冰范围春秋两季与NSIDC产品差异较小,冬夏两季差异较大,且FY产品海冰范围在冬季波动范围较大,修正后海冰范围与NSIDC产品差异较小,变化趋势趋于稳定,海冰范围在2012年夏季减小速度最快（图（5））。
图5 NSIDC产品、FY产品修正前后2011年6月27日至2015年12月31日日平均海冰范围变化对比图
Fig. 5 Comparisons of daily sea ice extent variation between NSIDC and FY product from June 27th, 2011 to December31st, 2015
与日平均海冰范围类似,FY产品月平均海冰范围修正前整体比NSIDC产品大,且在2012年夏季差异最大,修正后FY与NDSIDC产品月平均海冰范围差异较日平均海冰范围更小,同样,月平均海冰范围在2012年夏季减小的速度最快（图6）。修正前FY产品年平均海冰范围整体也呈现增大的情况,修正后二者表现出更好的一致性（图7）。
图6 NSIDC产品、FY产品修正前后2011年6月至2015年12月月平均海冰范围变化对比图
Fig. 6 Comparisons of monthly sea ice extent variation between NSIDC and FY product from June, 2011 to December, 2015
图7 NSIDC产品、FY产品修正前后2011-2015年年平均海冰范围变化对比图
Fig. 7 Comparisons of annual sea ice extent variation between NSIDC and FY product during 2011-2015
图8、9给出了2011-2015年不同季节NSIDC产品和FY修正后产品海冰范围时间序列,其中春季取3-5月的平均,夏季取6-8月的平均、秋季取9-11的平均,冬季取当年12月至次年2月的平均。从图中可看出,修后的FY产品与NSIDC产品虽然在不同季节年际变率存在一定的差异,春冬季节二者差异较大,夏秋季节差异较小,但各个季节2条曲线都有非常一致的年际变率,二者的相关系数的显著性均在99%置信度水平之上,这说明修正后的FY海冰数据集可有效地反映北极地区海冰分布情况。
图8 2011-2015年春、夏两季NSIDC产品和FY修正后产品海冰范围时间序列
Fig. 8 Comparisons of sea ice extent variation between NSIDC and FY product in spring andsummer during the period of 2011-2015
图9 2011-2015年秋、冬两季NSIDC产品和FY修正后产品海冰范围时间序列
Fig. 9 Comparisons of sea ice extent variation between NSIDC and FY product in autumn andwinter during the period of 2011-2015
自2011年FY海冰数据集公开发布以来,还没有针对FY海冰数据集误差像元修正的相关研究,本文通过分析现有的海冰产品,参照NSIDC海冰产品修正了FY海冰产品中因传感器精度问题导致的误差,研究结果表明,修正后FY产品与NSIDC产品的R2为0.9997,二者日平均、月平均、年平均最大偏差分别为3.5%、1.9%、0.9%,且FY数据集优化过程对其较好的空间分异特征无明显影响。
本文算法可实现FY产品优化的自动处理,解决了海岸线附近海水、海冰、陆地错分现象和极点无海冰覆盖区域偏大的情况,优化后的FY产品与NSIDC产品具有较好的一致性;缺点是并未考虑错分像元具体的海冰覆盖度,随着后续卫星传感器姿态的自我修正能力的提高,获取的数据地理定位精度的提升,错分现象可能会得到改善;光学遥感海冰产品虽然覆盖范围有限,但空间分辨率相对较高,如何有效利用光学遥感产品对FY产品优化进行有效补充是后续研究工作的重点。
FY北极海冰数据集的精度的提高,为探索北极海冰变化趋势与全球气候变化的内在联系提供了精度更高的基础数据,尤其在揭示北极海冰对中国气候的影响机制,提取海冰影响的关键区方面具有重要的应用价值。该产品的广泛使用不仅有助于推动国产被动微波传感器的改进与发展,而且对推动国产传感器数据在全球海冰监测中的应用也具有重要意义。
本文的优化算法只针对2011-2015年的FY产品,如何制作一套以FY产品为基础,综合1978-2011年的遥感海冰产品,为北极地区长时间序列海冰变化分析研究提供基础数据,是气象部门关注的重点,也是下一步的研究工作。
The authors have declared that no competing interests exist.
| [1] |
On the interannual variability of arctic sea-level pressure and sea ice [J].https://doi.org/10.1080/07055900.1992.9649455 URL [本文引用: 1] 摘要
Monthly mean sea-level pressure (SLP) data from the Northern Hemisphere for the period January 1952-December 1987 are analysed. Fluctuations in this field over the Arctic on interannual time-scales and their statistical association with fluctuations farther south are determined. The standard deviation of the interannual variability is largest compared with that of the annual cycle along the seaboards of the major land masses. The SLP anomalies are generally in phase over the entire Arctic Basin and extend south over the northern Russia and Canada, but tend to be out of phase with fluctuations at mid-latitudes, The anomalies are most closely associated with fluctuations over the North Atlantic and Europe except near the Chukchi Sea to the north of Bering Strait. The associations with the North Pacific fluctuations become increasingly more prominent at most Arctic sites (e.g. the Canadian Arctic Archipelago) as the time-scale increases. Associations between the SLP fluctuations and atmospheric indices that represent processes affecting sea-ice drift (wind stress and wind stress curl) are determined. In every case local associations dominate, but some remote ones are also evident. For example, changes in the magnitude of the wind stress curl over the Beaufort Sea are increased if the atmospheric circulation over the North Pacific is intensified; wind stress over the region where sea ice is exchanged between the Beaufort Gyre and the Transpolar Drift Stream is modulated by both the Southern and North Atlantic Oscillations. Severe sea-ice conditions in the Greenland Sea (as measured by the Koch Ice Index) coincide with a weakened atmospheric circulation over the North Atlantic.
|
| [2] |
The effect of solar radiation variations on the climate of the Earth [J].https://doi.org/10.1111/j.2153-3490.1969.tb00466.x URL [本文引用: 1] 摘要
ABSTRACT It follows from the analysis of observation data that the secular variation of the mean temperature of the Earth can be explained by the variation of short-wave radiation, arriving at the surface of the Earth. In connection with this, the influence of long-term changes of radiation, caused by variations of atmospheric transparency on the thermal regime is being studied. Taking into account the influence of changes of planetary albedo of the Earth under the development of glaciations on the thermal regime, it is found that comparatively small variations of atmospheric transparency could be sufficient for the development of quaternary glaciations.
|
| [3] |
The Role of Sea Ice in Climate [J].URL 摘要
A great many atmospheric and oceanic events are involved in the growth of sea ice, an important but not completely understood influence on the climate system. (Author/BB)
|
| [4] |
The role of sea ice in climatic variability: Theories and evidence [J].https://doi.org/10.1080/07055900.1983.9649166 URL [本文引用: 1] 摘要
ABSTRACT The climatic role of sea ice is assessed in a survey of the recent literature. Theoretical or model‐based results are compared with existing evidence of ice‐atmosphere interactions over scales ranging from the local and regional to the hemispheric and global.The evidence shows that sea‐ice fluctuations are meteorologically important locally, primarily through associations with air temperature. On the regional and hemispheric scales, atmospheric and sea‐ice fluctuations are correlated according to both observational evidence and model experiments. While the causal links have not been evaluated quantitatively, there is evidence that the stronger signal occurs in the response of the ice to the atmosphere. On the longer time‐scales, model experiments and qualitative arguments suggest that sea ice may play a major role in the climatic change. However, the results of large‐scale coupled model simulations contain deficiencies and must be viewed with caution pending more realistic treatments of sea‐ice dynamics, leads, ice thickness variations, and the areally‐integraled effects of the small‐scale features of sea ice.
|
| [5] |
Reflective properties of white sea ice and snow [J].https://doi.org/10.5194/tc-10-2541-2016 URL [本文引用: 1] 摘要
Abstract White ice (ice with a highly scattering granular layer on top of its surface) and snow-covered ice occupy a large part of the sea ice area in the Arctic, the former in summer, the latter in the cold period. The inherent optical properties (IOPs) and the reflectance of these types of ice are considered from the point of view of the light scattering and radiative transfer theories. The IOPs – the extinction and absorption coefficients and the scattering phase function – are derived with the assumption that both the snow cover and the scattering layer of white ice are random mixtures of air and ice with the characteristic grain size significantly larger than the wavelength of incident light. Simple analytical formulas are put forward to calculate the bidirectional reflectance factor (BRF), albedo at direct incidence (the directional–hemispherical reflectance), and albedo at diffuse incidence (the bihemispherical reflectance). The optical model developed is verified with the data of the in situ measurements made during the R/V Polarstern expedition ARK-XXVII/3 in 2012.
|
| [6] |
An analysis of Arctic sea ice fluctuations, 1953-77 [J]. |
| [7] |
Climate change 2014 synthesis report [J].https://doi.org/10.1111/j.1728-4457.2001.00203.x URL [本文引用: 1] 摘要
This Synthesis Report is based on the reports of the three Working Groups of the Intergovernmental Panel on Climate Change (IPCC), including relevant Special Reports. It provides an integrated view of climate change as the final part of the IPCC’s Fifth Assessment Report (AR5). This summary follows the structure of the longer report, which addresses the following topics: Observed changes and their causes; Future climate change, risks and impacts; Future pathways for adaptation, mitigation and sustainable development; Adaptation and mitigation.
|
| [8] |
Reconstructed changes in Arctic sea ice over the past 1,450 years [J].https://doi.org/10.1038/nature10581 URL [本文引用: 1] 摘要
Arctic sea ice extent is now more than two million square kilometres less than it was in the late twentieth century, with important consequences for the climate, the ocean and traditional lifestyles in the Arctic. Although observations show a more or less continuous decline for the past four or five decades, there are few long-term records with which to assess natural sea ice variability. Until now, the question of whether or not current trends are potentially anomalous has therefore remained unanswerable. Here we use a network of high-resolution terrestrial proxies from the circum-Arctic region to reconstruct past extents of summer sea ice, and show that--although extensive uncertainties remain, especially before the sixteenth century--both the duration and magnitude of the current decline in sea ice seem to be unprecedented for the past 1,450 years. Enhanced advection of warm Atlantic water to the Arctic seems to be the main factor driving the decline of sea ice extent on multidecadal timescales, and may result from nonlinear feedbacks between sea ice and the Atlantic meridional overturning circulation. These results reinforce the assertion that sea ice is an active component of Arctic climate variability and that the recent decrease in summer Arctic sea ice is consistent with anthropogenically forced warming.
|
| [9] |
McGrath R, Wang S. The impact of Arctic sea ice on the Arctic energy budget and on the climate of the Northern mid-latitudes [J].
The atmospheric general circulation model EC-EARTH-IFS has been applied to investigate the influence of both a reduced and a removed Arctic sea ice cover on the Arctic energy budget and on the climate of the Northern mid-latitudes. Three 40-year simulations driven by original and modified ERA-40 sea surface temperatures and sea ice concentrations have been performed at T255L62 resolution, corresponding to 79 km horizontal resolution. Simulated changes between sensitivity and reference experiments are most pronounced over the Arctic itself where the reduced or removed sea ice leads to strongly increased upward heat and longwave radiation fluxes and precipitation in winter. In summer, the most pronounced change is the stronger absorption of shortwave radiation which is enhanced by optically thinner clouds. Averaged over the year and over the area north of 70掳 N, the negative energy imbalance at the top of the atmosphere decreases by about 10 W/min both sensitivity experiments. The energy transport across 70掳 N is reduced. Changes are not restricted to the Arctic. Less extreme cold events and less precipitation are simulated in sub-Arctic and Northern mid-latitude regions in winter.
|
| [10] |
Arctic sea ice reduction and European cold winters in CMIP5 climate change experiments [J].URL 摘要
ABSTRACT European winter climate and its possible relationship with the Arctic sea ice reduction in the recent past and future as simulated by the models of the Climate Model Intercomparison Project phase 5 (CMIP5) is investigated, with focus on the cold winters. While Europe will warm overall in the future, we find that episodes of cold months will continue to occur and there remains substantial probability for the occurrence of cold winters in Europe linked with sea ice reduction in the Barents and Kara Sea sector. A pattern of cold-European warm-Arctic anomaly is typical for the cold events in the future, which is associated with the negative phase of the Arctic Oscillation. These patterns, however, differ from the corresponding patterns in the historical period, and underline the connection between European cold winter events and Arctic sea ice reduction.
|
| [11] |
The role of global climate change in the extreme low summer Arctic sea ice extent in 2012 [J].URL 摘要
The article discusses a comparison between the observed September 2012 Arctic sea ice extent (ASIE) anomaly and the trend of Arctic sea ice loss from 2011-2012 with model-simulated internal viability and response to climate forcings. Coupled Model Intercomparison Project Phase 5 simulations are used to examine whether the ASIE phenomena are responses to anthropogenic and natural forcing. Predictions that the Arctic Ocean will be free of ice in summer within several decades are cited.
|
| [12] |
Effects of Arctic sea ice decline on weather and climate: A review [J].https://doi.org/10.1007/s10712-014-9284-0 URL [本文引用: 1] 摘要
ABSTRACT The areal extent, concentration and thickness of sea ice in the Arctic Ocean and adjacent seas have strongly decreased during the recent decades, but cold, snow-rich winters have been common over mid-latitude land areas since 2005. A review is presented on studies addressing the local and remote effects of the sea ice decline on weather and climate. It is evident that the reduction in sea ice cover has increased the heat flux from the ocean to atmosphere in autumn and early winter. This has locally increased air temperature, moisture, and cloud cover and reduced the static stability in the lower troposphere. Several studies based on observations, atmospheric reanalyses, and model experiments suggest that the sea ice decline, together with increased snow cover in Eurasia, favours circulation patterns resembling the negative phase of the North Atlantic Oscillation and Arctic Oscillation. The suggested large-scale pressure patterns include a high over Eurasia, which favours cold winters in Europe and northeastern Eurasia. A high over the western and a low over the eastern North America have also been suggested, favouring advection of Arctic air masses to North America. Mid-latitude winter weather is, however, affected by several other factors, which generate a large inter-annual variability and often mask the effects of sea ice decline. In addition, the small sample of years with a large sea ice loss makes it difficult to distinguish the effects directly attributable to sea ice conditions. Several studies suggest that, with advancing global warming, cold winters in mid-latitude continents will no longer be common during the second half of the twenty-first century. Recent studies have also suggested causal links between the sea ice decline and summer precipitation in Europe, the Mediterranean, and East Asia.
|
| [13] |
2002-2011年北极海冰时空变化分析 [J].https://doi.org/10.11834/jrs.20132044 URL [本文引用: 1] 摘要
基于2002年—2011年AMSR-E海冰密集度数据,分析了北极海冰的时空变化特征及其原因.结果表明海冰外缘线面积每年减小8.28×104 km2,下降趋势最快的季节为夏季,下降速度是1979年—2006年的两倍多,而且海冰密集度也在降低.2003年、2004年的冰情相对较重,2007年海冰面积最小.长期冰在2002年—2010年间减少了近30％,减少的区域主要在波弗特海、楚科奇海、东西伯利亚海、拉普贴夫海、喀拉海以及由这些边缘海向北极方向延伸的北冰洋的广大区域,长期冰减少的地方大部分为季节性海冰增加的地方.海冰面积与年平均气温之间有显著的负相关关系,随着全球气候变暖的加剧,这种减小趋势将会持续.
Spatio-temporal variability of Arctic sea ice from 2002 to 2011 [J].https://doi.org/10.11834/jrs.20132044 URL [本文引用: 1] 摘要
基于2002年—2011年AMSR-E海冰密集度数据,分析了北极海冰的时空变化特征及其原因.结果表明海冰外缘线面积每年减小8.28×104 km2,下降趋势最快的季节为夏季,下降速度是1979年—2006年的两倍多,而且海冰密集度也在降低.2003年、2004年的冰情相对较重,2007年海冰面积最小.长期冰在2002年—2010年间减少了近30％,减少的区域主要在波弗特海、楚科奇海、东西伯利亚海、拉普贴夫海、喀拉海以及由这些边缘海向北极方向延伸的北冰洋的广大区域,长期冰减少的地方大部分为季节性海冰增加的地方.海冰面积与年平均气温之间有显著的负相关关系,随着全球气候变暖的加剧,这种减小趋势将会持续.
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| [14] |
我国微波遥感现状及前景 [J].
分析比较了遥感技术中使用的可见光、红外和微波遥感器的特点，介绍了微波遥感理论研究内容和我国的研究现状，叙述了我国机载合成孔径侧视雷达、机载微波辐射计、机载微波散射计、机载海洋雷达高度计的研制和应用状况，指出目前我国机载微波遥感器已基本达到实用水平，并且在生产建设、科学研究和防灾减灾中发挥出作用。列出了国际主要对地观测卫星装载遥感器的情况，从中看出微波遥感器在对地观测中日益增强的作用，建议国家对微波遥感的研究和应用加强统一领导，加强机载实用运行、陆基实验、微波遥感理论研究，以确保早日实现我国自己的星载微波遥感。
Current Situation and Prospect of Microwave Remote Sensing in China [J].
分析比较了遥感技术中使用的可见光、红外和微波遥感器的特点，介绍了微波遥感理论研究内容和我国的研究现状，叙述了我国机载合成孔径侧视雷达、机载微波辐射计、机载微波散射计、机载海洋雷达高度计的研制和应用状况，指出目前我国机载微波遥感器已基本达到实用水平，并且在生产建设、科学研究和防灾减灾中发挥出作用。列出了国际主要对地观测卫星装载遥感器的情况，从中看出微波遥感器在对地观测中日益增强的作用，建议国家对微波遥感的研究和应用加强统一领导，加强机载实用运行、陆基实验、微波遥感理论研究，以确保早日实现我国自己的星载微波遥感。
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| [15] |
Passive microwave algorithms for sea ice concentration: A comparison of two techniques [J].https://doi.org/10.1016/S0034-4257(96)00220-9 URL [本文引用: 1] 摘要
Abstract The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux (e.g., heat, salt, and water) calculations to small changes in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in winter but larger disagreements in the seasonal regions and in summer. In some areas in the Antarctic, the Bootstrap technique shows ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.
|
| [16] |
|
| [17] |
|
| [18] |
Passive microwave remote sensing for sea ice research [J].https://doi.org/10.1029/EO066i049p01210 URL [本文引用: 1] 摘要
Abstract During the last decade, considerable progress has been made in the application of passive microwave remote sensing to the study of sea ice. With the December 1972 launch of the Nimbus 5 electrically scanning microwave radiometer (ESMR-5), complete coverage of the polar regions provided the synoptic observations needed for undertaking a detailed study of global sea ice variability for the first time. The ESMR-5 data have been used successfully to document sea ice changes in both hemispheres and to associate these changes with atmospheric and oceanic influences [Zwally et al., 1983; Parkinson et al., 1985].
|
| [19] |
|
| [20] |
Sea ice remote sensing using AMSR-E 89-GHz channels [J].https://doi.org/10.1029/2005JC003384 URL [本文引用: 2] 摘要
Recent progress in sea ice concentration remote sensing by satellite microwave radiometers has been stimulated by two developments: First, the new sensor Advanced Microwave Scanning Radiometer-EOS (AMSR-E) offers spatial resolutions of approximately 6 4 km at 89 GHz, nearly 3 times the resolution of the standard sensor SSM/I at 85 GHz (15 13 km). Second, a new algorithm enables estimation of sea ice concentration from the channels near 90 GHz, despite the enhanced atmospheric influence in these channels. This allows full exploitation of their horizontal resolution, which is up to 4 times finer than that of the channels near 19 and 37 GHz, the frequencies used by the most widespread algorithms for sea ice retrieval, the NASA-Team and Bootstrap algorithms. The ASI algorithm used combines a model for retrieving the sea ice concentration from SSM/I 85-GHz data proposed by Svendsen et al. (1987) with an ocean mask derived from the 18-, 23-, and 37-GHz AMSR-E data using weather filters. During two ship campaigns, the correlation of ASI, NASA-Team 2, and Bootstrap algorithms ice concentrations with bridge observations were 0.80, 0.79, and 0.81, respectively. Systematic differences over the complete AMSR-E period (2002-2006) between ASI and NASA-Team 2 are below -2 8.8%, and between ASI and Bootstrap are 1.7 10.8%. Among the geophysical implications of the ASI algorithm are: (1) Its higher spatial resolution allows better estimation of crucial variables in numerical atmospheric and ocean models, for example, the heat flux between ocean and atmosphere, especially near coastlines and in polynyas. (2) It provides an additional time series of ice area and extent for climate studies.
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| [21] |
Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century [J].https://doi.org/10.1029/2002JD002670 URL [本文引用: 1] 摘要
We present the Met Office Hadley Centre's sea ice and sea surface temperature (SST) data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1掳 latitude-longitude grid from 1871. The companion HadMAT1 runs monthly from 1856 on a 5掳 latitude-longitude grid and incorporates new corrections for the effect on NMAT of increasing deck (and hence measurement) heights. HadISST1 and HadMAT1 temperatures are reconstructed using a two-stage reduced-space optimal interpolation procedure, followed by superposition of quality-improved gridded observations onto the reconstructions to restore local detail. The sea ice fields are made more homogeneous by compensating satellite microwave-based sea ice concentrations for the impact of surface melt effects on retrievals in the Arctic and for algorithm deficiencies in the Antarctic and by making the historical in situ concentrations consistent with the satellite data. SSTs near sea ice are estimated using statistical relationships between SST and sea ice concentration. HadISST1 compares well with other published analyses, capturing trends in global, hemispheric, and regional SST well, containing SST fields with more uniform variance through time and better month-to-month persistence than those in GISST. HadMAT1 is more consistent with SST and with collocated land surface air temperatures than previous NMAT data sets.
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| [22] |
Daily high-resolution-blended analyses for sea surface temperature [J]. |
| [23] |
https://doi.org/10.3969/j.issn.2095-1973.2013.04.014 URL [本文引用: 1] 摘要
风云三号卫星(FY-3)为极 轨系列卫星,目前为止分别于2008年5月和2010年10月发射了上午轨道(A)和下午轨道(B)两颗卫星。微波成像仪(MicroWave Radiometer Imager,MWRI)是装载于FY-3上的重要遥感仪器。该仪器为10通道双极化微波成像仪器,中心观测频率设置为 10.65,18.7,23.8,36.5和89.0GHz,每个频点有垂直(V)和水平(H)两个探测通道。获取的对地观测亮温数据可用于定量获取大气 降水、水汽、海面风速、海温、海冰分布、土壤湿度和陆表温度等地球物理参数信息。目前微波成像仪运行状态稳定,每天获取两次全球覆盖数据。主要介绍微波成 像仪定标状况和主要业务产品算法。
https://doi.org/10.3969/j.issn.2095-1973.2013.04.014 URL [本文引用: 1] 摘要
风云三号卫星(FY-3)为极 轨系列卫星,目前为止分别于2008年5月和2010年10月发射了上午轨道(A)和下午轨道(B)两颗卫星。微波成像仪(MicroWave Radiometer Imager,MWRI)是装载于FY-3上的重要遥感仪器。该仪器为10通道双极化微波成像仪器,中心观测频率设置为 10.65,18.7,23.8,36.5和89.0GHz,每个频点有垂直(V)和水平(H)两个探测通道。获取的对地观测亮温数据可用于定量获取大气 降水、水汽、海面风速、海温、海冰分布、土壤湿度和陆表温度等地球物理参数信息。目前微波成像仪运行状态稳定,每天获取两次全球覆盖数据。主要介绍微波成 像仪定标状况和主要业务产品算法。
|
| [24] |
An enhancement of the NASA Team sea ice algorithm [J]. |
| [25] |
Sea Iice extent and classification mapping with the moderate resolution imaging spectroradiometer airborne simulator [J].https://doi.org/10.1111/j.0954-6820.1971.tb07425.x URL [本文引用: 1] 摘要
ABSTRACT An algorithm for mapping sea ice extent and generalized classification of sea ice by reflective and temperature characteristics with Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) data is presented. The algorithm was tested using a MAS scene over the Bering Sea near St. Lawrence Island, Alaska, USA, acquired 8 April 1995. Clouds were masked with the University of Wisconsin cloud masking algorithm. Ice surface temperature was estimated with a split-window technique. Sea ice extent and generalized type of sea ice were identified based on reflective characteristics and estimated ice surface temperature using a grouped criteria technique. Resulting maps were consistent with visual interpretation and with sea ice extent and type information reported in prior studies of the region.
|
| [26] |
Deriving long-term time series of sea ice cover from satellite passive-microwave multisensor data sets [J].https://doi.org/10.1029/1999JC900081 URL [本文引用: 1] 摘要
Abstract We have generated consistent sea ice extent and area data records spanning 18.2 years from passive-microwave radiances obtained with the Nimbus 7 scanning multichannel microwave radiometer and with the Defense Meteorological Satellite Program F8, F11, and F13 special sensor microwave/imagers. The goal in the creation of these data was to produce a long-term, consistent set of sea ice extents and areas that provides the means for reliably determining sea ice variability over the 18.2-year period and also serves as a baseline for future measurements. We describe the method used to match the sea ice extents and areas from these four multichannel sensors and summarize the problems encountered when working with radiances from sensors having different frequencies, different footprint sizes, different visit times, and different calibrations. A major obstacle to adjusting for these differences is the lack of a complete year of overlapping data from sequential sensors. Nonetheless, our procedure reduced ice extent differences during periods of sensor overlap to less than 0.05% and ice area differences to 0.6% or less.
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| [27] |
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| [28] |
影响北极地区迅速变化的一些关键过程研究 [J].
最近研究证明 ,近半个世纪来 ,北极地区正在发生迅速变化。部分地区温度上升了 2— 3°C ,北冰洋海冰退缩 5 %,中心地区海冰厚度变薄 ,海面压力降低 ,中上层水淡化和变暖 ,吸收CO2 能力增加 ,臭氧耗损和紫外线辐射增强。中国于 1 999年开展了“中国首次北极科学考察” ,在楚科奇海、加拿大海盆、白令海以及临近海域开展了海冰气相互作用的多学科综合考察 ,对北极的区域特征及其在全球变化中的作用研究获得一些新的认识。观测到加拿大海盆中层水持续增暖的现象 ,揭示了西北冰洋与白令海水体交换的途径和次表层暖水结构 ,发现了加拿大海盆是北冰洋河水的主要储存区。利用联合冰站观测数据 ,模拟了北冰洋夏季大气边界层结构和下垫面能量平衡的变化特征 ,定量给出了北冰洋夏季海 /气和冰 /气之间湍流通量和边界层参数的差异。海 /气CO2 的通量观测表明 ,考察区的大部分海域均为大气CO2 汇区 ;西北冰洋海冰区具有较高的生物泵运转效率 ,楚科奇海陆架是一个高效的有机碳“汇”区 ,寒冷水体中微生物活动并未受到明显抑制。沉积物的地球化学过程研究表明 ,海底表层沉积物中碘含量存在着由低纬度到高纬度增加趋势 ,北极地区可能是碘的汇区 ,碘可作为极区古海洋中的地球化学元素变化的重要指标。楚科奇海、白令海
Study on key process affecting rapid chances in the Arctic [J].
最近研究证明 ,近半个世纪来 ,北极地区正在发生迅速变化。部分地区温度上升了 2— 3°C ,北冰洋海冰退缩 5 %,中心地区海冰厚度变薄 ,海面压力降低 ,中上层水淡化和变暖 ,吸收CO2 能力增加 ,臭氧耗损和紫外线辐射增强。中国于 1 999年开展了“中国首次北极科学考察” ,在楚科奇海、加拿大海盆、白令海以及临近海域开展了海冰气相互作用的多学科综合考察 ,对北极的区域特征及其在全球变化中的作用研究获得一些新的认识。观测到加拿大海盆中层水持续增暖的现象 ,揭示了西北冰洋与白令海水体交换的途径和次表层暖水结构 ,发现了加拿大海盆是北冰洋河水的主要储存区。利用联合冰站观测数据 ,模拟了北冰洋夏季大气边界层结构和下垫面能量平衡的变化特征 ,定量给出了北冰洋夏季海 /气和冰 /气之间湍流通量和边界层参数的差异。海 /气CO2 的通量观测表明 ,考察区的大部分海域均为大气CO2 汇区 ;西北冰洋海冰区具有较高的生物泵运转效率 ,楚科奇海陆架是一个高效的有机碳“汇”区 ,寒冷水体中微生物活动并未受到明显抑制。沉积物的地球化学过程研究表明 ,海底表层沉积物中碘含量存在着由低纬度到高纬度增加趋势 ,北极地区可能是碘的汇区 ,碘可作为极区古海洋中的地球化学元素变化的重要指标。楚科奇海、白令海
|
| [29] |
Map projections: Theory and applications [M]. |
| [30] |
Map projections-A working manual [M]. |
| [31] |
Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun region, China [J].https://doi.org/10.1080/13658810802443457 URL [本文引用: 1] 摘要
Physical environment, man-made pollution, nutrition and their mutual interactions can be major causes of human diseases. These disease determinants have distinct spatial distributions across geographical units, so that their adequate study involves the investigation of the associated geographical strata. We propose four geographical detectors based on spatial variation analysis of the geographical strata to assess the environmental risks of health: the risk detector indicates where the risk areas are; the factor detector identifies factors that are responsible for the risk; the ecological detector discloses relative importance between the factors; and the interaction detector reveals whether the risk factors interact or lead to disease independently. In a real-world study, the primary physical environment (watershed, lithozone and soil) was found to strongly control the neural tube defects (NTD) occurrences in the Heshun region (China). Basic nutrition (food) was found to be more important than man-made pollution (chemical fertilizer) in the control of the spatial NTD pattern. Ancient materials released from geological faults and subsequently spread along slopes dramatically increase the NTD risk. These findings constitute valuable input to disease intervention strategies in the region of interest.
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| [32] |
A measure of spatial stratified heterogeneity [J].https://doi.org/10.1016/j.ecolind.2016.02.052 URL [本文引用: 1] 摘要
Spatial stratified heterogeneity, referring to the within-strata variance less than the between strata-variance, is ubiquitous in ecological phenomena, such as ecological zones and many ecological variables. Spatial stratified heterogeneity reflects the essence of nature, implies potential distinct mechanisms by strata, suggests possible determinants of the observed process, allows the representativeness of observations of the earth, and enforces the applicability of statistical inferences. In this paper, we propose a q -statistic method to measure the degree of spatial stratified heterogeneity and to test its significance. The q value is within [0,1] (0 if a spatial stratification of heterogeneity is not significant, and 1 if there is a perfect spatial stratification of heterogeneity). The exact probability density function is derived. The q -statistic is illustrated by two examples, wherein we assess the spatial stratified heterogeneities of a hand map and the distribution of the annual NDVI in China.
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