共查询到19条相似文献，搜索用时 390 毫秒
1.
基于华北典型污染地区的地基多轴差分吸收光谱仪（MAX-DOAS）近4年的观测数据，利用最优估计算法和LIDORT辐射传输模式反演了该区域气溶胶的消光系数垂直廓线和光学厚度（AOD）.MAX-DOAS观测反演的AOD与全球气溶胶观测网络同波段在华北地区的AOD间具有很好的一致性，相关系数都在0.9以上，证明MAX-DOAS具备对华北污染区域气溶胶光学厚度和消光系数垂直廓线的反演能力.AOD的反演误差表现为冬季最大，春夏最小，早晚大于正午，这是因为冬季以及早晚太阳天顶角较大导致信噪比偏小，所以AOD反演误差偏大.反演廓线表明该区域气溶胶主要集中在1 km以下的边界层，浓度随高度呈指数递减，部分情况下峰值出现在300 m处；气溶胶光学厚度夏季最大，冬季最小，正午较大，早晚较小.在东风条件下浓度最高，表明东边（即重工业城市唐山方向）的输送对香河和周边区域的气溶胶积聚有重要贡献. 相似文献
2.
利用AERONET资料对珠三角地区气溶胶物理性质特征进行分析,建立珠三角地区的气溶胶模型,在此基础上,根据RT3 辐射传输模型构建矢量查找表,采用多角度偏振方法从PARASOL L1B数据反演得到细模态气溶胶光学厚度(AOD),最后采用2007-2009年MODIS总的AOD产品和本文的细模态AOD三年的反演结果分析了珠三角地区气溶胶的时间变化和空间分布特征,为深入研究珠三角地区污染物的局地排放和输送提供了条件.结果表明:(1)珠三角地区对流层气溶胶呈双峰型对数正态分布,其中细粒子平均半径主要集中在0.05~0.1,标准方差以0.5、0.6为主,粗粒子平均半径以0.9、1.0为主,标准方差为0.6、0.7,复折射指数实部以1.4、1.5 居多,虚部以0、0.01为主,细粒子所占比例大于70%,珠三角气溶胶呈现出粗颗粒物和细颗粒物并存的特征;(2)PARASOL业务算法中的气溶胶模型在珠三角地区有较大的局限性,引入当地气溶胶模型使细模态AOD的反演精度较卫星产品有了很大提高,细模态AOD主要反映了珠三角地区二次污染的强度;(3)珠三角地区总AOD值春季较大,秋夏季次之,冬季较小,并呈现逐年较小的趋势;(4)珠三角地区细模态AOD也在逐年降低,2009年细模态AOD年均值比2007年低了0.02,在空间分布上,高值地区主要集中在广州、佛山、中山等城市. 相似文献
3.
《中国科学:地球科学》2017,(9)
大气中SO_2是一种对城市大气环境变化和全球辐射能量平衡有着重要影响的痕量气体.BRD(Band Residual Difference Algorithm)和DOAS(Differential Optical Absorption Spectroscopy)算法是两种主要的SO_2总量遥感反演算法,分别被用于美国和欧洲不同卫星载荷数据的SO_2反演.然而,目前缺少两种算法在相同观测条件下SO_2反演的精度比较及不确定性分析、在物理数学反演机制上的差异追因.因此,本文基于相同的仿真模拟数据和卫星紫外辐射观测数据,反演获得不同大气状况下的BRD和DOAS SO_2总量并进行精度比较验证.从算法反演通道、O_3吸收、气溶胶、地表反射率和观测角度影响等方面,讨论分析BRD和DOAS反演结果差异及反演误差的原因.结果表明,在低浓度SO_2情况下,BRD反演SO_2总量更接近于正演输入SO_2总量,DOAS反演结果存在高估,但相对于BRD算法,DOAS算法长时间序列卫星反演结果更能表现出SO_2的季节变化特征;在高浓度SO_2情况下,BRD(310.8~314.4nm)和DOAS(315~327nm)反演结果的绝对值差异明显且存在低估,BRD(310.8~314.4nm)SO_2反演值及反演精度都低于DOAS(315~327nm)反演结果.基于高光谱分辨率大气辐射传输模型SCIATRAN的反演不确定性分析结果显示,反演通道选择、紫外O_3吸收、气溶胶、地表反射率和观测角度对SO_2总量反演精度的影响较大.本研究对于SO_2卫星遥感反演算法的改进及SO_2反演产品的应用具有重要的科学意义,也可促进中国未来大气成分SO_2卫星遥感产品的研发. 相似文献
4.
《中国科学:地球科学》2015,(6)
基于最优估计理论,采用LBLRTM和VLIDORT辐射传输模式以及包含Line Mixing效应的aer_v_3.2数据库,构建了一套短波红外高光谱卫星反演XCO2的算法.利用该算法试验了Line Mixing效应对卫星反演结果的影响,对GOSAT卫星观测光谱数据进行了系统性试验反演,并利用选取的TCCON站点一年中的匹配观测资料进行了地面验证,同时与GOSAT卫星官方L2B产品进行了比对.试验表明,忽略Line Mixing将系统性低估约0.25%的CO2柱浓度.在气溶胶光学厚度小于0.3的大气条件下,本文反演算法反演结果与GOSAT官方数据产品精度接近,与地基观测值相差小于1%,而高浓度气溶胶背景下卫星反演CO2浓度的有效方法仍有待于突破. 相似文献
5.
研究表明在珠三角目前的污染状况下,至少一半以上的紫外辐射被大气气溶胶衰减,如此大幅度的紫外辐射衰减对城市生态系统和物种化学循环,尤其是臭氧光化学反应过程有重大的影响.利用地面观测的臭氧、紫外辐射、气溶胶辐射特性参数以及辐射和化学模式定量评估了大气气溶胶对地面臭氧影响的显著性.实例分析表明,珠三角大气气溶胶和紫外辐射与臭氧之间的相关性显著,气溶胶光学厚度（AOD）与地面PM10的浓度相关性高达0.98,AOD与相应时次的紫外辐射和臭氧的反相关性明显,相关系数可达-0.9.分析表明气溶胶污染通过衰减紫外辐射可显著降低臭氧的产率,AOD为0.6时臭氧的午间峰值区消失,AOD至1.2时午间峰值区呈下降趋势,造成午间臭氧的生成产率明显降低.目前干季（10,11,12和1月）广州的气溶胶光学厚度AOD550 nm≥0.6（AOD340 nm≥1.0）的出现概率为47%（55%）,珠三角在干季出现臭氧极大值的机会少与严重的气溶胶污染抑制臭氧峰值的出现应有密切的关系.分析表明应用辐射化学模式计算气溶胶的辐射效应时对单散射因子（SSA）十分敏感,表明应用辐射化学模式计算臭氧的产率时应慎重选取合理的单散射因子值. 相似文献
6.
香港气溶胶光学厚度与PM_(10)质量浓度的季节变异及相关性 总被引：1，自引：0，他引：1
《中国科学:地球科学》2015,(4)
利用经验模分解方法,分析了香港地区2005~2011年期间经垂直标高订正后的气溶胶光学厚度(AOD/Hi)与湿度订正后的可吸入颗粒物(PM10×f(RH))在半年、年和长期趋势等不同时间尺度上的变化特征及相关性.结果表明:香港地区AOD/Hi与PM10×f(RH)均存在显著的半年和年周期振荡,其中半年的峰值分别出现在3月和10月.受沙尘天气以及内陆污染物输送的影响,二者的半年振荡的第一个峰值的振幅均值都显著高出10月,是一年中污染最为明显的时期;年周期尺度上,二者的变化过程与年降雨量和太阳总辐射呈负相关关系,表现为冬季高夏季低,其中峰值都出现在2月前后,相比沙尘天气促成的半年振荡的第一个峰值提前发生一个月左右,其振幅均值仅为半年振荡的第一个峰值的一半.长期趋势上,2005~2011年间二者整体呈现显著的下降趋势,其中PM10×f(RH)下降速率达到平均每年14μg m-3,归因于大气颗粒物浓度的下降以及对二氧化硫等气溶胶颗粒物排放的控制.AOD/Hi与PM10×f(RH)的回归分析显示二者在半年和年时间尺度上的相关性(0.67和0.79)均超过95%置信度检验.下降趋势上存在明显的非线性关系,当AOD/Hi不超过0.44的范围时,PM10×f(RH)的下降速率慢于AOD/Hi的下降速率,但在超过0.44时,PM10×f(RH)的下降速率明显高于AOD/Hi.上述结果表明AOD/Hi能够反映出香港地面站点污染物监测数据PM10×f(RH)在半年、年周期以及长期趋势上的变化特征,可用于分析评价香港地区的空气质量状况. 相似文献
7.
利用卫星数据遥感陆地气溶胶一直是国际上研究的难点与热点.利用新一代传感器MODIS(中分辨率成像光谱仪)数据,DDV(Dark Dense Vegetation)算法反演陆地气溶胶的分布以及性质已经取得了较好的效果.然而,该算法只适用于诸如水体、浓密植被等较低地表反射率区域,大大限制了该算法的实际应用范围,尤其是无法应用于城市等亮地表区域气溶胶的遥感反演.文中提出了基于利用TERRA和AQUA双星MODIS数据的协同反演模型算法(SYNTAM-Synergy of Terra and Aqua MODIS),用以反演陆地气溶胶的光学厚度等信息.该算法实现了地表反射率与气溶胶光学厚度的同时反演,可应用于各种地表反射率类型,包括城市等亮地表区域.通过与国际AERONET的地面观测数据对比做初步的反演验证,结果表明,该算法具有较高的精度,进一步的验证工作还在继续. 相似文献
8.
MODIS陆地气溶胶遥感反演 总被引：6，自引：0，他引：6
利用卫星数据遥感陆地气溶胶一直是国际上研究的难点与热点. 利用新一代传感器MODIS(中分辨率成像光谱仪)数据, DDV(Dark Dense Vegetation)算法反演陆地气溶胶的分布以及性质已经取得了较好的效果. 然而, 该算法只适用于诸如水体、浓密植被等较低地表反射率区域, 大大限制了该算法的实际应用范围, 尤其是无法应用于城市等亮地表区域气溶胶的遥感反演. 文中提出了基于利用TERRA和AQUA双星MODIS数据的协同反演模型算法(SYNTAM-Synergy of Terra and Aqua MODIS), 用以反演陆地气溶胶的光学厚度等信息. 该算法实现了地表反射率与气溶胶光学厚度的同时反演, 可应用于各种地表反射率类型, 包括城市等亮地表区域. 通过与国际AERONET的地面观测数据对比做初步的反演验证, 结果表明, 该算法具有较高的精度, 进一步的验证工作还在继续. 相似文献
9.
城市环境大气重污染过程周边源影响域 总被引：39，自引：9，他引：39
北京城市周边污染源影响问题是北京环境污染治理决策亟待解决的关键环节之一. 综合分析2001年1~3月份BECAPEX(Beijing City Atmospheric Pollution Experiment), MODIS (Moderate Resolution Imaging Spectroradiometer)与TOMS(Total Ozone Mapping Spectrometer)卫星遥感资料, 提出追踪污染源“上游”风场合成矢量法. 通过统计分析北京及周边地区TOMS与MODIS卫星遥感气溶胶区域性特征, 发现北京城市重污染过程与南部周边城市群落排放源影响相关显著, 北京周边向南开口的类似“马蹄型”地形可能导致周边源远距离输送的污染物“滞留”效应, 形成北京与南部周边排放源近似南-北向带状影响域. 综合分析北京地区重污染过程轨迹特征, 并选取2001年1~3月份重污染过程与空气质量良好时段作为分析样本, 采用HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory)轨迹模式进行模拟试验, 揭示了北京城区重污染过程河北、山东和天津等地城市群落污染排放源扩散轨迹. 选取北京城区异常重污染过程个例, 并用RAMS(Regional Atmosphere Model System)模式模拟试验, 亦揭示了北京城区异常污染过程周边外源贡献率, 进一步证实了北京城市重污染过程加剧的重要因素之一是南部周边城市污染物外源的输入. 相似文献
10.
作为一种新兴的被动遥感技术,全极化微波辐射计不仅可以提供海面风速产品,还可以提供海面风向产品.以往利用全极化微波辐射计观测亮温进行海面风场反演仅在晴空条件下进行,本文通过对观测亮温结合台风区域海面风场的分布特征进行分析,验证了全极化微波辐射计具有在台风等恶劣天气条件下进行海面风场观测的能力.基于敏感性分析实验,确定使用6.8 GHz和10.7 GHz等低频通道组合可进行台风区域内海面风场反演.其中,海面风速反演使用基于统计的多元线性回归算法,同时对海面温度、大气水汽含量、云中液态水含量及降水强度等物理量进行反演计算,为海面风向反演做准备.海面风向反演使用物理统计法进行,借鉴散射计风向反演使用的最大似然估计法.通过在全极化辐射传输前向模型中加入降水对大气透过率的影响、设计第三和第四Stokes通道亮温环境影响修正函数,在实现台风区域内海面风向反演的同时减小了反演误差.通过对“云娜”台风境内海面风场进行数值计算,验证了本文反演算法的可行性,并对反演误差的空间分布特征进行了分析.将2004年各台风过程的海面风场反演结果与散射计风场产品进行对比,海面风速和海面风向反演的均方根误差分别为1.64 m·s-1和18.02°. 相似文献
11.
针对2011年12月初北京及华北持续近一周的严重大雾天气这一热点事件,从城市群大雾过程气溶胶区域影响的视角,基于"973"项目"北京及周边地区大气-水-土环境污染机理与调控原理"的研究工作,就北京及周边地区大雾天气与大气气溶胶区域影响的关系等方面进行了讨论.研究表明,北京城市大雾前低空SO2和NO2浓度存在"积聚"与"突增"现象.北京及周边地区冬季雾日数和气溶胶光学厚度则呈正相关,并具有"同位相"的年际变化趋势.研究同时发现北京及其南部周边的冬季气溶胶高值区呈南北向带状分布,其与北京周边居民户数高值区有所吻合,反映了冬季北京城市气溶胶颗粒物的远距离影响源区及大尺度输送效应.统计分析指出,冬季北京气溶胶颗粒物PM10、PM2.5主要影响成分是SO2和NOX,且有关研究也表明,电厂、采暖和工业面源是SO2的三大本地排放源,而机动车、电厂、工业为NOX的三大本地排放源,上述大气PM10、PM2.5主成分污染源亦与雾水样本化学分析结果相吻合,即冬季由于燃煤在生活能源中的比例较大,北京雾水中硫元素和碳元素的含量都较高.因此,北京冬季大雾不仅与北京城区气溶胶及其污染排放影响存在相关关系,而且与北京周边天津、河北、山东等地气溶胶及大气污染物的远距离输送和气溶胶区域影响效应有着重要的联系.因此,北京雾霾天气及相关大气污染的治理工作首先要着眼于局地污染物的减排,但同时如何做好区域大气污染的协同治理也是不容忽视的问题. 相似文献
12.
《中国科学:地球科学(英文版)》2015,(6)
Reflectance measurements of both the visible and infrared bands of passive remote sensing sensors are widely used to retrieve aerosol optical depth(AOD) information. This is performed commonly for data obtained over both ocean and land, and these measurements allow for the off line development of a lookup table using radiative transfer models. Owing to molecular and aerosol effects, the reflected light received by the sensor is usually highly polarized. The linear polarization effect may be up to 100%, and the polarization factor of a sensor optical system will change the total intensity as well as the polarization status of the signal reaching the detector. The detector response will be different when the incident light polarization status changes, even if the total intensity remains constant. However, if the polarization calibration is neglected, it will cause obvious errors in the aerosol data retrieval. This is especially true for aerosol optical depth retrieval over an ocean. This measurement relies directly on the reflectance output of the sensor. Cases involving land surfaces are not discussed herein because the inhomogeneous properties conceal the error due to polarization. Taking the 550 and 860 nm bands as examples, the difference between the real top-of-atmosphere(TOA) reflectance and the reflectance reaching the detector is calculated using three different sensor polarization standards according to the Sea-viewing Wide Field-of-view Sensor(Sea Wi FS) and Moderate Resolution Imaging Spectroradiometer(MODIS) standards. The differences in AOD retrieval are also demonstrated using the lookup table developed previously from a vector radiative transfer code. The results reveal that under a normal situation in which the AOD is 0.15, the maximum AOD retrieval error could reach 0.04 in 550 nm but only 0.02 in 860 nm for the dust aerosol model. For the soot aerosol model, the maximum AOD retrieval error is 0.1 in 550 nm and 0.12 in 860 nm, indicating that the lack of polarization calibration will lead to large errors in aerosol retrieval over an ocean. 相似文献
13.
The high spatial resolution and temporal observation frequency of HJ-1/CCD make it suitable for aerosol monitoring. However, because of the lack of a shortwave infrared band, it is difficult to use HJ-1/CCD imagery to retrieve aerosol optical depth (AOD). We developed a new algorithm for HJ-1/CCD AOD retrieval by introducing MODIS surface reflectance outputs (MOD09) as support. In this algorithm HJ-1/CCD blue band surface reflectance was retrieved through MOD09 blue band surface reflectance by band matching of the two sensors. AOD at 550 nm was then generated through a pre-calculated look-up table for HJ-1/CCD. Eighteen HJ-1/CCD images covering the Jing-Jin-Tang (Beijing-Tianjin-Tangshan) region were used to retrieve AOD using the new algorithm, and the AODs were then validated using AERONET ground measurements in Beijing and Xianghe. The validation shows that compared with AERONET ground measurements, 27/29 AODs have error less than 0.1 in absolute value. 相似文献
14.
The high spatial resolution and temporal observation frequency of HJ-1/CCD make it suitable for aerosol monitoring. However, because of the lack of a shortwave infrared band, it is difficult to use HJ-1/CCD imagery to retrieve aerosol optical depth (AOD). We developed a new algorithm for HJ-1/CCD AOD retrieval by introducing MODIS surface reflectance outputs (MOD09) as support. In this algorithm HJ-1/CCD blue band surface reflectance was retrieved through MOD09 blue band surface reflectance by band matching of the two sensors. AOD at 550 nm was then generated through a pre-calculated look-up table for HJ-1/CCD. Eighteen HJ-1/CCD images covering the Jing-Jin-Tang (Beijing-Tianjin-Tangshan) region were used to retrieve AOD using the new algorithm, and the AODs were then validated using AERONET ground measurements in Beijing and Xianghe. The validation shows that compared with AERONET ground measurements, 27/29 AODs have error less than 0.1 in absolute value.
相似文献15.
Improvement of snow depth retrieval for FY3B-MWRI in China 总被引：3，自引：0，他引：3
The primary objective of this work is to develop an operational snow depth retrieval algorithm for the FengYun3B Microwave Radiation Imager(FY3B-MWRI)in China.Based on 7-year(2002–2009)observations of brightness temperature by the Advanced Microwave Scanning Radiometer-EOS(AMSR-E)and snow depth from Chinese meteorological stations,we develop a semi-empirical snow depth retrieval algorithm.When its land cover fraction is larger than 85%,we regard a pixel as pure at the satellite passive microwave remote-sensing scale.A 1-km resolution land use/land cover(LULC)map from the Data Center for Resources and Environmental Sciences,Chinese Academy of Sciences,is used to determine fractions of four main land cover types(grass,farmland,bare soil,and forest).Land cover sensitivity snow depth retrieval algorithms are initially developed using AMSR-E brightness temperature data.Each grid-cell snow depth was estimated as the sum of snow depths from each land cover algorithm weighted by percentages of land cover types within each grid cell.Through evaluation of this algorithm using station measurements from 2006,the root mean square error(RMSE)of snow depth retrieval is about 5.6 cm.In forest regions,snow depth is underestimated relative to ground observation,because stem volume and canopy closure are ignored in current algorithms.In addition,comparison between snow cover derived from AMSR-E and FY3B-MWRI with Moderate-resolution Imaging Spectroradiometer(MODIS)snow cover products(MYD10C1)in January 2010 showed that algorithm accuracy in snow cover monitoring can reach 84%.Finally,we compared snow water equivalence(SWE)derived using FY3B-MWRI with AMSR-E SWE products in the Northern Hemisphere.The results show that AMSR-E overestimated SWE in China,which agrees with other validations. 相似文献
16.
Kenechukwu Okoli Korbinian Breinl Luigia Brandimarte Anna Botto Elena Volpi Giuliano Di Baldassarre 《水文科学杂志》2013,58(13-14):1913-1926
ABSTRACTThis study compares model averaging and model selection methods to estimate design floods, while accounting for the observation error that is typically associated with annual maximum flow data. Model selection refers to methods where a single distribution function is chosen based on prior knowledge or by means of selection criteria. Model averaging refers to methods where the results of multiple distribution functions are combined. Numerical experiments were carried out by generating synthetic data using the Wakeby distribution function as the parent distribution. For this study, comparisons were made in terms of relative error and root mean square error (RMSE) referring to the 1-in-100 year flood. The experiments show that model averaging and model selection methods lead to similar results, especially when short samples are drawn from a highly asymmetric parent. Also, taking an arithmetic average of all design flood estimates gives estimated variances similar to those obtained with more complex weighted model averaging. 相似文献
17.
Aerosol retrieval algorithms for the MODerate Resolution Imaging Spectroradiometer (MODIS) have been developed to estimate aerosol and microphysical properties of the atmosphere, which help to address aerosol climatic issues at global scale. However, higher spatial resolution aerosol products for urban areas have not been well researched mainly due to the difficulty of differentiating aerosols from bright surfaces in urban areas. Here, a new aerosol retrieval algorithm using the MODIS 500 m resolution image... 相似文献
18.
Aerosol can induce visibility reduction, affect radiation balance and modify cloud property on the environmental effect, and show the harmful effects on human health. Insight of aerosol becomes an integral task in the process of control measures for environmental pollution. The present study provided an analysis of temporal–spatial variations of aerosol optical depth (AOD) using the MOD04 level-2 in collection 6 (C6) with the deep blue retrieval algorithm from January 2005 to December 2015 over Yangtze River Delta (YRD) in China. The AOD validations between MODIS and Aerosol Robotic Network (AERONET) were estimated by the methods of regression, correlation. Then, the periodic features and trends of AOD and angstrom exponent (AE) were explored with the wavelet transformation (WT) procedure. Further, the variations of AOD and AE spatial distribution on multi-time scales (annual, monthly and season) were demonstrated. Meantime, the sources of AOD are discussed. It was found that the daily AOD from MODIS has a strong correlation relationship (slope?=?0.9838, r?=?0.84) with AERONET over YRD. The variations of both AOD and AE on time series have been distinct temporal periodic (12, 6 and 4 months) characteristics, and show the decreasing trends on annual and semi-annual periods. On annual, the AOD on spatial distribution is slowly declining from the northwest towards the southeast, and the AE on spatial distribution is gradually decreasing from the northwest to the southeast and from the land to the coast. The variations both inter-annual AOD and AE on spatial distribution show the inverse trends, respectively. On monthly, the means of AOD range from minimum 0.46 in January to maximum 0.90 in July, and the variations of spatial distribution mainly occur in the north parts of Yangtze River and some scattered areas with high terrain and south coast. The means of AE range from minimum 1.13 in October to maximum 1.58 in April, and the variations of spatial distribution are mainly found in the south of Henan, the north of Jiangsu, the coast belt and the riverside of Yangtze River and the high terrain regions. On seasonality, the means of AOD reaches its maximum 0.68 in summer and minimum 0.50 in winter, and the variations of spatial distribution mainly occur in the coast belt, the north parts of Hongze Lake and the south parts with high terrain. The means of AE reaches its maximum 1.48 in spring and minimum 1.25 in autumn, and the variations of spatial distribution were shown the similarity with that of monthly. 相似文献
19.
Space‐borne passive microwave snow water equivalent (SWE) retrieval algorithms are attractive for continuous SWE monitoring over large mountainous areas. The performance of three SWE retrieval algorithms, which were considered relevant for operational purposes, was examined for each month over the Colorado River Basin. In addition, statistical post‐processing was tested as a means of improving the SWE estimates from each algorithm. The evaluation started with the so‐called Chang equation, which was a pioneer algorithm and is still used in practice. Successive attempts were then made to improve the algorithm's performance through the calibration of the equation's coefficient and through the inclusion of brightness temperature data from various frequency channels. The Chang equation consistently underestimated SWE with average bias between 30 mm in November and more than 300 mm in April and root mean square error (RMSE) exceeding 500 mm at many locations in April. The statistical post‐processing effectively removed the bias and reduced the RMSE by half for all the months. When the Chang equation's coefficients were calibrated at each site, biases were reduced by approximately 85%, and RMSE was reduced by 40%–50%. Finally, the multiple channel equations produced unbiased SWE estimates with RMSEs 50%–60% of those from the Chang equation. However, the statistical post‐processing did not reduce RMSE for both calibrated algorithms. The last algorithm produced the most reliable estimates for at‐site analysis, but its skill deteriorated when analyses were performed over larger areal extents; therefore, it is only recommended for SWE monitoring over smaller areas. For larger areas, the calibrated Chang equation is desirable because it only requires interpolations of a calibrated coefficient, which was spatially coherent. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献