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基于GLASS数据估算中国陆表净辐射及其空间分布分析

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陈征¹^,²^,, 胡德勇³^,, 蒋卫国¹^,², 曹冉¹^,²

1. 北京师范大学减灾与应急管理研究院,北京 100875

2. 北京师范大学环境演变与自然灾害教育部重点实验室,北京 100875

3. 首都师范大学资源环境与旅游学院,北京 100048

Land surface radiation budget parameterization and spatial analysis over China using GLASS data

CHENZheng¹^,²^,, HUDeyong³^,, JIANGWeiguo¹^,², CAORan¹^,²

1. Beijing Normal University, Beijing 100875, China

2. Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing 100875, China

3. Capital Normal University, Beijing 100048, China

通讯作者:胡德勇（1974- ）,男,湖南慈利人,博士,副教授,主要从事遥感和地理信息系统在自然灾害、资源环境等领域应用。E-mail: deyonghu@163.com
收稿日期:2015-06-9
修回日期:2015-11-23
网络出版日期:2016-01-23
版权声明:2016《地理研究》编辑部《地理研究》编辑部
基金资助:

国家自然科学基金项目（41171318,41571077）

北京市教委科研计划面上项目（KM201510028018）

卫星测绘技术与应用国家测绘地理信息局重点实验室开放基金（KLSMTA-201305）

中央高校基本科研业务费专项基金

作者简介:
-->作者简介：陈征（1988- ）,女,河南商丘人,博士研究生,研究方向为资源环境遥感。E-mail: lubyn@126.com

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摘要
地表辐射收支是能量循环的重要参数,影响着地球水热平衡,是全球气候变化研究的重要方面。多数研究利用MODIS数据估算地表辐射收支,模型输入参数复杂。综合利用GLASS数据、MODIS数据和地面实测数据,采用Bisht等提出的净辐射估算方法,制订一种简单的地表辐射收支估算方案,分别计算2010年1-12月中旬卫星过境时刻中国陆表净辐射的最大值。通过改进的正弦模型将估算结果转换为日最大地表净辐射,并利用地面实测日最大净辐射值对估算结果进行了验证。研究表明：综合利用GLASS数据、MODIS数据和地面实测数据建立的地表辐射收支模型能够很好地模拟中国陆表净辐射的分布,与地面实测日最大净辐射值具有较好的一致性,平均误差为27.21 W?m^-2,克服了利用其他遥感数据估算地表辐射收支输入参数复杂,数据量大的缺点,适用于大尺度地表陆表辐射收支研究。

关键词：陆表辐射收支;参数化;GLASS;正弦模型
Abstract
Land surface radiation is an important parameter with regard to energy cycling and global water-heat balance. Estimating land surface radiation is a significant part of global climate change research. Series of remote sensing data have been used in the calculation of each parameter of the land surface radiation budget. The MODIS data are widely used, but the schemes are complicated. How to estimate land surface radiation easily and accurately is always an appropriate subject of debate. The GLASS data were published by Peking University in 2012 and can be directly used in global change research. Firstly, GLASS data (including albedo data, land surface emissivity data and downward shortwave radiation data), MODIS land surface temperature data and ground observed data were employed to develop a modified parameterization scheme of net radiation based on the research published by Bisht et al. in 2005. The maximum net radiation over eight continuous days in the middle of each month in 2010 was calculated using the scheme presented in this paper. Because the values that were obtained at the time of the satellite passing by were instantaneous, the instantaneous values were translated into the daily maximum data using the modified sinusoidal model and validated using ground observed data. There was a good agreement between ground observed data and the parameterization results and the average bias was 27.21 W

?

m^-2. The results showed that the scheme presented in this paper was an effective model to calculate land surface radiation over China. Our scheme required less input data. It can be applied to calculate land surface radiation at the scale of a large region. The spatial pattern change over China in 2010 was also analyzed. The results show that the land surface radiation changes significantly with the seasons and there are differences between different places at the same time. Generally, the value of net radiation increases in the first eight months and decreases in the last four months. The maximum net radiation gradually decreases from south to north. The probable reason is the different characters of the underlying surface, including land cover and geographic location.

Keywords：land surface radiation budget;parameterization;GLASS;sinusoidal model

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陈征, 胡德勇, 蒋卫国, 曹冉. 基于GLASS数据估算中国陆表净辐射及其空间分布分析[J]. , 2016, 35(1): 25-36 https://doi.org/10.11821/dlyj201601003
CHEN Zheng, HU Deyong, JIANG Weiguo, CAO Ran. Land surface radiation budget parameterization and spatial analysis over China using GLASS data[J]. 地理研究, 2016, 35(1): 25-36 https://doi.org/10.11821/dlyj201601003

1 引言

地表辐射收支是影响地表—大气能量交换和再分配过程的重要参数,影响着地表水热平衡和能量循环,被广泛应用于气候监测、天气预报和农业气象研究,是当前全球气候变化研究领域的热点之一。如何简化地表辐射收支估算模型并提高估算精度仍是地表辐射平衡研究的重要内容,探讨该问题对于提高气候变化监测效率具有重要意义。
地面实测数据和遥感数据是用于地表辐射收支参数化的两种重要数据。利用地面实测数据计算陆表辐射收支一般是将地面实测数据按照某种规则进行空间插值以获得一定空间范围的结果,或通过经验统计方法建立基于地面辐射实测数据和气象资料估算地表辐射收支的经验—统计模型,通过反演得到一定范围内地表净辐射^[1-5]。此方法考虑了大气对太阳辐射的散射和吸收,在点尺度上估算精度较高,但由于地面台站数量有限且分布不均,地表覆被类型复杂,实时气象参数（如气溶胶,云的含量等）难以获取,因此不能满足大范围净辐射估算的需求^[6]。遥感技术的发展解决了大范围同步观测的问题,利用遥感数据可建立地表净辐射参数的定量估算方案^[7-13]。近年来,MODIS数据、Landsat系列数据等被广泛应用于地表辐射收支的研究中。Bisht等基于MODIS产品估算了小区域地表净辐射^[8-12],朱君等利用MODIS产品实现了中国地表短波净辐射的估算^[7]。利用遥感数据估算陆表辐射收支克服了实测数据估算的局限性,大大提高了大范围内净辐射的估算精度,是大范围、多尺度地表净辐射估算的有效途径,但其输入数据组成较复杂,数据量较大,且在点尺度上的估算精度不及地面实测法。另外,结合遥感数据和地面实测数据估算地表净辐射的方法^[14,15],在大范围地区可能无法获取足够的同步地面观测资料验证估算结果,因此具有一定的局限性。目前,针对中国陆表净辐射的研究大多利用MODIS产品等遥感数据,输入参数复杂,精度有限,因此制订一种简单的中国陆表净辐射参数化方案对于宏观把握中国地表辐射平衡现状具有重要意义。2012年北京师范大学首次发布了全球陆表参量产品GLASS（Global LAnd Surface Satellite Products System）数据,包括叶面积指数、地表反照率、地表发射率、下行短波辐射和光合有效辐射5种陆表特征参量产品（http://glass-product.bnu.edu.cn）,可直接服务于全球陆表变化研究,极大地促进了气候系统模型的研发和改进。
利用GLASS数据、MODIS数据和地面观测站点实测数据,构建一种简单的地表辐射收支遥感参数化模型,估算2010年1-12月中旬中国陆表地表净辐射的瞬时最大值,并通过改进的正弦模型得到日最大地表净辐射值,利用地面实测日最大净辐射值对估算结果进行精度检验。在验证通过的基础上,对中国2010年月中旬最大地表净辐射空间分布进行分析。

2 数据来源与研究方法

2.1 数据来源

2.1.1 遥感数据产品所用遥感数据包括GLASS数据、MODIS数据产品。GLASS数据主要包括地表反照率数据、下行短波辐射数据、地表发射率数据,来源于北京师范大学（http://glass-product.bnu.edu.cn）。MODIS数据采用地表温度产品MOD11A2,空间分辨率为1 km,来源于美国航天航空局数据中心（http://labsweb.nascom.nasa.gov）。MODIS和GLASS数据均需要投影转换,裁剪等处理,GLASS数据和MODIS数据的基本参数和用途如表1所示。
Tab. 1
表1
表1GLASS、MODIS数据及用途
Tab. 1The parameters and application of GLASS and MODIS data

数据名称	数据参数	数据用途
GLASS地表反照率产品	空间分辨率1 km,Sinusoidal投影,8天合成产品	短波净辐射估算
GLASS下行短波辐射产品	空间分辨率5 km,Sinusoidal投影,时间分辨率3 h	短波净辐射估算
MODIS地表温度产品	空间分辨率1 km,Sinusoidal投影,8天合成产品	长波净辐射估算
GLASS地表发射率产品	空间分辨率1 km,Sinusoidal投影,8天合成产品	长波净辐射估算

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GLASS反照率数据是基于MODIS数据和AVHRR数据利用AB（Angular Bin）算法开发的参数产品,由多波段地表方向反射率或大气层顶方向反射率通过简单的线性回归估算得到日地表反照率,通过时空滤波算法（statistics-based temporal filtering,STF）检测和去除异常值并填充缺失值^[16],得到时间和空间上连续的1981-2010年全球8天合成地表反照率产品,空间分辨率为1 km^[17]。Liu等利用地面实测数据和MODIS的地表反照率数据MOD43对GLASS地表反照率产品进行了对比验证,结果显示晴空条件下,均方根误差小于0.05,表明GLASS地表反照率产品与MCD43具有很好的一致性^[18]。GLASS地表反照率数据取值范围0~1,被用于计算短波净辐射。
GLASS地表发射率数据的基本算法是首先根据NDVI值将全球陆表划分为水体、冰雪、裸土、植被覆盖和过渡区域,根据辐射传输模型的计算结果将水体、冰雪均赋值为0.985,通过建立地表发射率和MODIS 7个窄波段黑空反照率间的线性关系得到裸地、植被覆盖和过渡区域的地表发射率。研究表明,GLASS地表发射率产品与MODIS地表发射率产品、地面实测值有较好的一致性,且总体精度优于MODIS产品^[19-22]。GLASS地表发射率数据取值范围0~1,空间分辨率为1 km,被用于计算长波净辐射。
GLASS下行短波辐射数据是基于多个静止卫星和极轨卫星,包括MODIS、GOES、FY2-C等数据,采用改进的查找表法,即MOTRAN模型,建立表达不同卫星大气顶层（top of atmosphere,TOA）的辐亮度和地表下行短波辐射关系的查找表,进而通过卫星观测数据估算下行短波辐射^[23]。Huang的研究表明,GLASS下行短波辐射与地面实测值相比,R²达0.8以上,均方根误差为90~130 W?m^{-2 [24]}。GLASS下行短波辐射数据空间分辨率为5 km,被用于计算短波净辐射。
2.1.2 地面观测数据地面实测数据为中国地面气候资料日值数据集中的空气温度和相对湿度以及中国辐射资料日值数据集中的日最大净辐射,来源于中国气象科学数据共享服务网（http://cdc.nmic.cn/home.do）。地面气象站包括全国824个国家级基准、基本气象站,以及其他级别测站15个共839个,日平均气温数据的比例因子为0.1,单位为℃,日平均相对湿度的比例因子为1%,空气温度和相对湿度数据均通过克里格插值得到空间分辨率为1 km的全国空间分布数据。共收集到122个辐射地面站实测数据,去除部分数据缺测站点,最终可用站点数据约50组,日最大净辐射单位为W?m^-2。实测数据主要参数及用途如表2所示。
Tab. 2
表2
表2实测数据及用途
Tab. 2The application of ground-based data

数据名称	数据参数	数据用途
空气温度日值数据集	可用测站数839个,比例因子0.1,单位℃	空气发射率估算
相对湿度日值数据集	可用测站数839个,比例因子1%,无单位	空气发射率估算
辐射资料日值数据集	可用测站数为50个,单位W?m^-2	精度检验

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2.1.3 其他数据包括1

\begin{matrix} ∶ \end{matrix}

400万中国行政区划数据及GMTED2010地表高程数据,主要用于空气温度插值结果的修正。

2.2 研究方法

地表净辐射是太阳短波辐射在“地—气”系统中经过吸收、散射和反射、发射等作用后,地表接收的辐射收支净余部分。通常,地表净辐射还可表示为地表短波净辐射和地表长波净辐射之和,根据辐射平衡公式有：

\begin{matrix} R_{n} = R_{s}^{↓} - R_{s}^{↑} + R_{l}^{↓} - R_{l}^{↑} = R_{n}^{s} + R_{n}^{l} \end{matrix}

（1）
式中：

\begin{matrix} R_{n} \end{matrix}

为地表净辐射;

\begin{matrix} R_{s}^{↓} \end{matrix}

和

\begin{matrix} R_{s}^{↑} \end{matrix}

分别为下行短波辐射和上行短波辐射;

\begin{matrix} R_{l}^{↓} \end{matrix}

和

\begin{matrix} R_{l}^{↑} \end{matrix}

分别为下行长波辐射和上行长波辐射;

\begin{matrix} R_{n}^{s} \end{matrix}

为地表短波净辐射;

\begin{matrix} R_{n}^{l} \end{matrix}

为地表长波净辐射。
太阳辐射是地球的主要能量来源,入射到地面的太阳短波辐射包括直射辐射和散射辐射两部分,经地面反射后,地面实际吸收的太阳短波辐射即为短波净辐射,公式为^[8]：

\begin{matrix} R_{n}^{s} = (1 - α) R_{s}^{↓} \end{matrix}

（2）
式中：

\begin{matrix} α \end{matrix}

为地表反照率;利用GLASS地表反照率和下行短波辐射数据作为输入参数即可计算出

\begin{matrix} R_{n}^{s} \end{matrix}

。
在接收太阳辐射的同时,地表也以热辐射的形式向外辐射能量并接收主要来自大气向下的长波辐射。地表向外辐射的长波辐射能量包括地表自身发射的热辐射和对大气长波辐射的反射能量,计算公式^[25]为：

\begin{matrix} R_{n}^{l} = R_{l}^{↓} - R_{l}^{↑} = R_{l}^{↓} - (1 - ε_{s}) R_{l}^{↓} - R_{ls}^{↑} \end{matrix}

（3）
式中：

\begin{matrix} R_{ls}^{↑} \end{matrix}

为地表自身发射的热辐射,

\begin{matrix} R_{ls}^{↑} = σ ε_{s} T_{s}^{4} \end{matrix}

;

\begin{matrix} R_{l}^{↓} = σ ε_{a} T_{a}^{4} \end{matrix}

\begin{matrix} R_{l}^{↓} \end{matrix}

取决于近地表大气温度和空气发射率;

\begin{matrix} ε_{s} \end{matrix}

为地表发射率,输入数据为GLASS地表发射率数据。上行长波辐射

\begin{matrix} R_{l}^{↑} \end{matrix}

取决于地表发射率和地表温度,根据Stenffan-Boltzmann方程有：

\begin{matrix} R_{n}^{l} = σ ε_{s} ε_{a} T_{a}^{4} - σ ε_{s} T_{s}^{4} \end{matrix}

（4）
式中：

\begin{matrix} ε_{a} \end{matrix}

为空气发射率;T_a为空气温度（近地面空气温度,单位：K）,利用地面实测数据进行计算;T_s为地表温度（单位：K）,输入数据为MODIS地表温度数据;

\begin{matrix} σ \end{matrix}

为Steffan-Boltzmann常数,取值为5.6697×10^-8W?m^-2K^-4。
Iziomon等利用饱和水气压和空气温度估算了空气发射率,研究表明在晴空条件下该方法较为适用^[26]。根据马格纳斯公式及水汽压与相对湿度的关系^[27]得到空气发射率的计算公式为：

\begin{matrix} ε_{a} = 1 - 0.35 \exp (- 10 \times \frac{e_{s} \times RH}{T_{a}}) \end{matrix}

（5）
式中：e_s为空气温度为T_a时的饱和水汽压,

\begin{matrix} e_{s} = 6.1078 \exp [17.13 (T_{a} - 273.16) / (T_{a} - 38)] \end{matrix}

;T_a为空气温度;RH为相对湿度,利用地面实测值进行计算。
为了定量检验参数化结果,利用Bisht^[8]等提出的方法,假设在晴空条件下,昼间任意时刻的地表净辐射可以近似表示为当日净辐射通量最大值的函数：

\begin{matrix} R_{n} (t) = R_{n_max} \sin [(\frac{t - t {}_{rise}}{t_{set} - t_{rise}}) π] \end{matrix}

（6）
式中：R_n(t)为任一像元t时刻地表净辐射通量;R_{n_max}为每日地表净辐射通量的瞬时最大值,为一个与时间无关的常量;t_rise为该像元所在纬度的日出时刻;t_set为该像元所在纬度的日落时刻。
对于任一像元,R_n(t)随时间变化近似符合图1中所示红色曲线。图中蓝色区域面积等于R_n(t)在昼长时间内的积分值,即测站测得的每日昼间单位面积地表净辐射累积量。图中给出了MODIS过境时刻,即地表净辐射反演结果对应的时刻。从图中可以看出,卫星过境时刻t_overpass并非日地表净辐射通量最大的时刻,因此,需要根据卫星过境时刻采集的地表净辐射通量估算出当日地表净辐射通量的最大值。

显示原图|下载原图ZIP|生成PPT
图1日最大净辐射估算原理示意图
-->Fig. 1The diagram of maximum net radiation estimation
-->

假设用于反演的地表参数获取当天天气晴好,则当日的昼间地表净辐射变化可以用图1中类似的正弦曲线来描述,且地面站测得最大日净辐射通量值的时刻对应图1中正弦曲线的顶点位置。不同地理位置的最大日净辐射通量获取时间对应当日地表净辐射的曲线相当于将图1中曲线沿着x轴水平移动。
研究表明,大部分的测站均在午后3个小时之内获取到当天净辐射通量的最大值,极少部分由于太阳高度或者天气的原因（如云、雨天气）造成时间点的进一步向后推移。基于Bisht等的假设,忽略由天气等原因造成的个别日间净辐射最大值获取时间的大幅度后延,认为卫星过境时刻至最大值获取时刻这一段时间间隔内,净辐射值变化仍然符合图1所示的正弦曲线关系。根据这一假设的条件,将式（6）改写为：

\begin{matrix} R_{n_max} = {R ’}_{n} / \sin [\frac{0.5 T - (t_{\max} - t_{overpass})}{T} π], T = t_{set} - t_{rise} \end{matrix}

（7）
式中：

\begin{matrix} {R ’}_{n} \end{matrix}

为卫星过境时刻地表净辐射通量,即本文地表净辐射通量的反演结果;T为当日的昼长。式（7）将日最大地表净辐射通量表示为关于卫星过境时刻净辐射与过境时刻的函数。
需要注意的是,为了计算日最大地表净辐射通量,还需要知道昼长T的值。假设忽略月内太阳直射点纬度的变化,即忽略月内每日昼长时间的微小变化,认为在同一纬度,同一月内每日各处的日出日落地方时是一个定值（以月中旬为参考）,即昼长时间T为常量。对于给定月份某一纬度范围的像元,可以根据卫星过境时刻净辐射通量估算其像元单位面积地表上的日最大净辐射通量。将这一结论进行推广,如果计算得到每月中旬太阳直射点纬度位置,并根据此计算当月研究区内不同纬度范围内的日出、日落时间以及昼长,便可以计算得到不同纬度范围的像元在不同月份的单位面积地表最大日净辐射通量,是一个与月份及纬度有关的分段函数,可简单表示为：

\begin{matrix} E_{n} = E (mon, Φ), mon \in [1,12], Φ \in [3 . 86^{°} N, 53 . 55^{°} N] \end{matrix}

（8）
式中：E为包含12个表达式的分段函数;mon表示月份参数;Φ表示像元所在地理纬度,中国地区的纬度范围为3.86°N~53.55°N。

3 结果分析

3.1 精度检验

根据得到的地表净辐射参数化方案,将实验数据代入式（1）~式（5）,对2010年中国陆表净辐射进行估算,得到2010年1-12月中旬地表净辐射参数化结果。
用于反演地表净辐射通量的地表参数实际上是经过月中旬8天最大值合成而得到的昼间卫星过境时刻的各参量值。因此计算得到的地表短波、长波净辐射以及地表净辐射均相当于卫星过境时刻的瞬时值,而用于精度验证的数据为地面测站测量得到日净辐射最大值统计结果,两者并不是同一状态的量,不能直接进行对比分析。因此,为了定量评价参数化结果精度,需要将估算得到的卫星过境时刻地表净辐射通量换算为当日净辐射最大值,以便进行比较。
研究选用相关系数r、均方根误差RMSE、模拟效率EF三种指标来评价估算结果的精度。为了便于计算,选取春分点所在的3月作为研究时间节点。忽略月内太阳直射点移动,认为3月太阳直射点位于0°纬线,即研究区范围内日出时间为6点,日落时间18点,昼夜长度相等且等于12小时,MODIS过境时间为地方时10:30和13:30,则可以采用式（7）计算3月所有站点对应像元最大日地表净辐射,以便利用地面站点实测值进行精度验证。表3列举了选取的12个省份的3月份估算结果精度（表3）。
Tab. 3
表3
表33月地表净辐射参数化结果检验
Tab. 3The accuracy assessment result of estimated land surface net radiation for March

省份	实测值	参数化结果	省份	实测值	参数化结果
天津	592	559.707	新疆	468	473.902
山西	565	592.055	内蒙古	502	509.267
山东	523	552.982	青海	561	565.139
江苏	572	574.559	四川	599	615.411
安徽	585	577.384	江西	614	595.536
福建	677	675.584	广东	603	601.846

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表3所示的检验结果表明,参数化结果与地面实测值具有很好的一致性,最大误差约为32 W?m^-2。按照式（7）和式（8）的计算方法,对12个月的参数化结果进行检验,日最大地表净辐射估算值与实测值的散点图如图2所示,灰色实线为散点的拟合直线,对角线为1

\begin{matrix} ∶ \end{matrix}

1等值线。最小二乘回归拟合结果显示,其显著性在P<0.05范围内显著,表明散点分布有一定的稳定性,二者有显著的相关性。从图2中可以看出,大部分的点散布在1

\begin{matrix} ∶ \end{matrix}

1等值线下方,表明该处的估测值与实测值相比偏小;较少的部分散布在其上方,表明该处估测值大于实测值。有一部分散点偏离程度较大,如等值线下方大致呈圆弧分布的点,其估测值远小于实测值,必将影响相关系数及RMSE等评价指标的值。

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图2日最大地表净辐射通量的估测值与实测值散点图
-->Fig. 2Comparison of observed and estimated daily maximum net radiation
-->

对全国50个测站的地表净辐射日内变化进行模拟,得到12个月的各测站所在空间位置的日最大净辐射,并将实际测量结果与反演结果进行统计分析,得到最终的各项精度检验指标（表4）。
Tab. 4
表4
表42010年内日最大地表净辐射精度检验结果
Tab. 4The precision inspection results of daily maximum net radiation in 2010

月份	1月	2月	3月	4月	5月	6月	7月	8月	9月	10月	11月	12月
r	0.82	0.86	0.94	0.92	0.84	0.90	0.87	0.84	0.91	0.85	0.82	0.85
RMSE	40.17	29.20	21.46	24.55	24.26	20.39	26.62	27.48	21.00	27.11	29.47	34.79
EF(%)	72.40	84.10	90.40	89.30	90.80	88.40	90.20	90.00	93.10	84.50	82.30	77.70

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从表4可以看出,年内日最大地表净辐射的实测值与估计值的相关系数在0.80以上,且均通过了显著性检验（P<0.05）。RMSE最大值出现在1月,为40.17W?m^-2,表明1月份各站点所在空间位置的数据离散程度较高,同时发现12月份的RMSE也达到了34 W?m^-2以上,通过对数据的进一步分析发现主要是由于位于东北部分站点实测值极低,如黑龙江最北部的漠河站点,1月份某日测到的日最大净辐射通量甚至为负,而由8天最大值合成后反演得到的结果却为正值,这样就造成了很大的偏差。模拟效率EF是用于评价实测值变化能够由模型所解释的比例,在这里被引入用于评价模型对反演结果的影响。除了1月份和12月份,其余月份的模拟效率均在80%以上,整体趋势与RMSE的变化相符合,但并不完全一致。整体看来,夏季的估测结果要优于冬季,可能是由于采用春分点秋分点作为参考地理位置对估测结果造成了一定的影响。

3.2 地表净辐射参数化结果

参数化结果空间分布如图3所示。将参数化结果分为10个等级,将小于0 W?m^-2的赋值为1,大于800 W?m^-2的赋值为10,其他的以100 W?m^-2为步长进行赋值,对每个等级的面积进行统计（图4）。

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图32010年3月、7月、10月及12月中国陆表净辐射空间分布
-->Fig. 3The distribution of land surface net radiation in March, July, October, and December, 2010
-->

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图4参数化结果分级统计
-->Fig. 4The statistical map of parameterized results
-->

按照气象划分法,通常以阳历3-5月为春季,6-8月为夏季,9-11月为秋季,12月-次年2月为冬季。图4中所示的统计结果表明,中国陆表净辐射具有明显的季节变化特征和空间特征,符合中国地表净辐射的变化规律,表现为地表净辐射值从春季到夏季逐渐增加,夏季到冬季逐渐减少,春季和冬季地表净辐射值处于多个区间范围,空间上差异较大,秋季次之,夏季空间差异最小。在春季,全国60%以上的地区地表净辐射值在6~8级范围内,且地表净辐射值为8级的面积不断增加,值为6级和7级的地区比重最大。在夏季,全国70%以上的地区地表净辐射在7~9级范围内,值为8级的地区比重逐渐增加,8月份全国空间差异达到最小值。秋季到冬季处于6级以下的地表净辐射面积逐渐增加,冬季地表净辐射值主要在3~5级范围内,空间上的差异性逐渐增大。
按照地势,中国由西到东分为三个阶梯：西藏、青海等位于第一阶梯,海拔较高,地形以高原、山地为主;内蒙古、云南等处于第二阶梯,以高原、盆地为主要地形;东三省,河南等位于第三阶梯,地势较为平坦,以平原和丘陵地形为主。从图5（a）的统计结果可以看出,西藏地区地表净辐射变化较为平缓,8月达最大值,内蒙古地区年内变化较大在6月达到最大值,河南地表净辐射年内波动性明显,在5月和8月分别有一个峰值,而在7月出现下凹。从植被覆盖的角度看,处于第一阶梯的西藏和处于第二阶梯的内蒙古均以草地为主,秋冬季节草地枯萎,地表净辐射较低,春夏季节草地生长茂盛,地表净辐射较高;农作物是处于第三阶梯的河南省的主要植被类型,由于农作物物候期的特点,夏季的6-7月份农作物采收,地表净辐射减小因此在7月份出现下凹现象,而植被生长茂盛的5月和8月分别达到峰值。从气候特点看,西藏和内蒙古均处于寒冷区域,因此年内最大净辐射低于河南;由于内蒙古高原处于青藏高原的北部,因此其年内地表净辐射小于西藏地区。

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图5典型区域地表净辐射年内变化
-->Fig. 5The annual change of net radiation in typical areas
-->

黑龙江、河南和湖南均处于第一阶梯,分别位于中国北部,中部和南部。如图5（b）所示,三者的地表净辐射年内总体呈先增加后减小的趋势,不同季节具有不同的分布特征：① 除夏季外,地表净辐射由南到北依次减小。其中,1-2月河南和湖南的净辐射变化剧烈,黑龙江则变化平缓;3-4月黑龙江变化较为剧烈,而河南和湖南变化较为平缓。② 5月、6月南方地区处于梅雨季节,湖南受云雨的影响地表净辐射呈下降趋势,而河南和黑龙江气候相对干燥呈上升趋势。③ 6-8月由于受到植被物候期的影响,河南地区地表净辐射减小,湖南地区地表净辐射达到最大值。

3.3 讨论

从精度检验结果看,参数化结果较实测值偏小,造成这种现象的可能有三个：首先是数据方面,本文采用于短波净辐射估算的GLASS下行短波数据的时间分辨率为3 h,其中覆盖中国区域的时间是格林尼治时间的0:00-12:00,西部地区的覆盖时间是北京时间的14:00-20:00。在日最大值估算中假设地表净辐射瞬时值为卫星过境时间,与数据获取时间有一定的偏差,因此会影响估算结果。另外选取的地面实测数据的时间与遥感数据相对应,但没有排除天气的影响,这也会造成误差的积累。第二种可能是由于地表温度的变化不可忽略,或者近地表有明显的热量交换,同样会造成卫星热通道采样值的减小从而影响到估算结果。第三种可能是在进行给定某日的昼间净辐射变化模拟时,由于实测的日最大净辐射获取时间与卫星过境时间提前或者相差不多时或者不同纬度范围昼长相差不可忽略时,造成式（7）中分母偏大,从而使估测得到的日最大净辐射值偏小。同样,1

\begin{matrix} ∶ \end{matrix}

1等值线上方的点由于产品生成的误差,近地表热环境的突然变化,以及昼长估算偏大或者辐射的后延比较严重,如下午或者接近太阳落山才达到最值,那么势必会影响到估算得到的日最大净辐射的结果,造成估算结果偏大。特别第三种原因,在实际估算过程中,相当一部分的RMSE是由于正弦曲线的不完美假设造成的。
采用Bisht等提出的计算方法,利用GLASS、MODIS和地面实测数据估算的地表辐射收支的平均误差为27.21 W?m^-2,与已有研究的误差74 W?m^{-2 [8]}和37 W?m^{-2 [10]}相比,有了很大的提高。参数化过程主要包括地表反照率、下行短波辐射、地表发射率、地表温度、空气温度、相对湿度7个输入参数,其中GLASS地表反照率数据和地表发射率数据在空间和时间上是连续的,且去除了云的影响,下行短波辐射数据的分辨率为5 km,为高分辨率的辐射分布数据^[26,27]。利用MODIS数据计算地表辐射收支需要MODIS地表反照率数据MOD43、地表温度和发射率数据MOD11、大气廓线数据数据MOD07、地理位置数据MOD03、气溶胶数据MOD05^[8],5种MODIS产品均没有去除云的影响,需要利用MODIS的云掩膜数据MOD06进行处理^[10],计算模型复杂,数据量较大。因此,从计算结果和过程看,利用文中的方法估算地表辐射收支不仅计算简单,数据量较小且计算结果与地面实测值具有很好的一致性。

4 结论

利用MODIS数据、GLASS数据和地面实测数据制订了一种简单的中国陆表辐射收支参数化方案,克服了利用其他遥感产品进行地表净辐射参数化输入参数复杂、数据量大的缺点。此外,对Bisht等采用的正弦公式进行了改进,建立了日最大净辐射与瞬时地表净辐射的关系,并应用于参数化结果的精度检验中。得出以下结论：
（1）利用GLASS数据、MODIS数据产品和地面实测数据相结合的方式能够较好地估算出晴空条件下昼间最大地表净辐射,通过8天最大值合成能够有效减少云的影响,反映了2010年中国陆表净辐射的年内变化特征,适用于大尺度地表净辐射变化研究。
（2）改进的正弦模型能够满足日最大地表净辐射的估算要求,很好地模拟给定地点某日昼长内地表净辐射随时间的变化关系,尤其是在太阳高度角相对较大的地区或季节。经验证,计算得到的日最大值与实测净辐射有较好的一致性,相关系数均在0.8以上,模拟效率达70%以上,RMSE的最大值为40.17 W?m^-2。
本文所得的地表净辐射结果为瞬时最大值的8天合成,仅能定性反映2010年中国陆表净辐射的瞬时年内变化特征,不能量化某一时间段的实际地表辐射收支情况;另外,本文未考虑地形对地表辐射收支的影响,这些局限性是今后研究工作中亟待进一步解决的问题。
The authors have declared that no competing interests exist.

参考文献原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子

[1]	高扬子, 何洪林, 张黎, 等. 近50年中国地表净辐射的时空变化特征分析 . 地球信息科学学报, 2013, 15(1): 1-10.https://doi.org/10.3724/SP.J.1047.2013.00001 Magsci [本文引用: 1]摘要基于GIS空间分析技术与Mann-Kendall趋势分析方法,对中国陆地区域699个气象站点1961-2010年逐年、季平均地表净辐射进行时空变化特征分析,结果表明:(1)参数拟合后的FAO Penman修正式对模拟站点逐日地表净辐射的总体精度较高,均方根误差为27.9W ·m<sup>-2</sup>,相关系数为0.85,平均相对误差为0.13;(2)全国近50年站点平均地表净辐射在年、季均呈现出较明显的下降过程,年均降幅为0.74W ·m<sup>-2</sup> ·10a<sup>-1</sup>,不同季节的下降幅度存在差异,夏季降幅最大;(3)逐站点分析显示全国大部分站点(59.8%)年均地表净辐射呈显著下降趋势(0.05),东部趋势变化比西部明显,夏季在地表净辐射年际变化中的贡献最大,华北、华中、华南地区的站点在春夏秋季均呈显著下降趋势。 [Gao Yangzi, He Honglin, Zhang Li, et al.Spatio-temporal variation characteristics of surface net radiation in China over the past 50 years. Journal of Geo-information Science, 2013, 15(1): 1-10.]https://doi.org/10.3724/SP.J.1047.2013.00001 Magsci [本文引用: 1]摘要基于GIS空间分析技术与Mann-Kendall趋势分析方法,对中国陆地区域699个气象站点1961-2010年逐年、季平均地表净辐射进行时空变化特征分析,结果表明:(1)参数拟合后的FAO Penman修正式对模拟站点逐日地表净辐射的总体精度较高,均方根误差为27.9W ·m<sup>-2</sup>,相关系数为0.85,平均相对误差为0.13;(2)全国近50年站点平均地表净辐射在年、季均呈现出较明显的下降过程,年均降幅为0.74W ·m<sup>-2</sup> ·10a<sup>-1</sup>,不同季节的下降幅度存在差异,夏季降幅最大;(3)逐站点分析显示全国大部分站点(59.8%)年均地表净辐射呈显著下降趋势(0.05),东部趋势变化比西部明显,夏季在地表净辐射年际变化中的贡献最大,华北、华中、华南地区的站点在春夏秋季均呈显著下降趋势。
[2]	崔耀平, 刘纪远, 胡云峰, 等. 城市不同下垫面辐射平衡的模拟分析 . 科学通报, 2012, 57(6): 465-473.Magsci摘要 <p>利用北京市2010 年的实测数据, 首先对局地尺度的城市净辐射参数化方案(NARP)进行了验证, 分析NARP 在城市区域的适用性. 在此基础上, 人为设置4 种不同下垫面类型(纯的林地、草地、道路、房屋), 在其他条件一致的情况下模拟不同下垫面的辐射差异, 以更清晰解读不同下垫面的辐射平衡各分量, 特别是净辐射的不同特征. 结果显示: (1) NARP 模拟的净辐射值与实测净辐射值具有较好的一致性, 相关系数为0.98, 模拟效率可达0.93; (2) 不同下垫面对各辐射分量的影响不同, 上行长波辐射的值很大, 占到全年进入地表总辐射能量的84.3%, 净辐射的年均值在38.2~53.4 W/m<sup>2</sup> 之间, 其中草地最小, 道路最大; (3) 城市扩展过程中常见的林地-道路、草地-道路、草地-房屋等转类, 净辐射都呈现出持续增加态势. 其中, 最大增加值出现在5 月份, 增幅可达24.6 W/m<sup>2</sup>(草地-道路), 说明城市扩展过程通常也伴随能量收入连续增加的过程.</p> [Cui Yaoping, Liu Jiyuan, Hu Yunfeng, et al.Modeling the radiation balance of different urban underlying surfaces. Chinese Science Bulletin, 2012, 57(6): 465-473.]Magsci摘要 <p>利用北京市2010 年的实测数据, 首先对局地尺度的城市净辐射参数化方案(NARP)进行了验证, 分析NARP 在城市区域的适用性. 在此基础上, 人为设置4 种不同下垫面类型(纯的林地、草地、道路、房屋), 在其他条件一致的情况下模拟不同下垫面的辐射差异, 以更清晰解读不同下垫面的辐射平衡各分量, 特别是净辐射的不同特征. 结果显示: (1) NARP 模拟的净辐射值与实测净辐射值具有较好的一致性, 相关系数为0.98, 模拟效率可达0.93; (2) 不同下垫面对各辐射分量的影响不同, 上行长波辐射的值很大, 占到全年进入地表总辐射能量的84.3%, 净辐射的年均值在38.2~53.4 W/m<sup>2</sup> 之间, 其中草地最小, 道路最大; (3) 城市扩展过程中常见的林地-道路、草地-道路、草地-房屋等转类, 净辐射都呈现出持续增加态势. 其中, 最大增加值出现在5 月份, 增幅可达24.6 W/m<sup>2</sup>(草地-道路), 说明城市扩展过程通常也伴随能量收入连续增加的过程.</p>
[3]	Jacobs J M, Myers D A, Anderson M C, et al.GOES surface insolation to estimation wetlands evapotranspiration. Journal of Hydrology, 2000, 266(1-2): 53-65.https://doi.org/10.1016/S0022-1694(02)00117-8 URL摘要 Incoming solar radiation derived from GOES-8 satellite observations, in combination with local meteorological measurements, were used to model evapotranspiration from a wetland. The wetland experiment was conducted in the Paynes Prairie Preserve, North Central Florida during a growing season characterized by significant convective activity. The satellite solar radiation measurements generally agreed with pyranometer data gathered at the site. The satellite net radiation estimates were in good agreement with the 30-min averages of measured net radiometer data. Satellite derived net radiation estimates were used in the Penman-Monteith and Priestley-Taylor models to calculate evapotranspiration. The calculated instantaneous evaporative fluxes were in good agreement with 30-min average ground-based eddy correlation system measurements. The daily averages of modeled evapotranspiration were in very good agreement ( r=0.90) with reference eddy flux measurements.
[4]	Nishida K, Nemani R R, Running S W, et al.An operational remote sensing algorithm of land surface evaporation. Journal of Geophyscial Research, 2003, 108: 469-474.https://doi.org/10.1029/2002JD002062 URL摘要 [1] Partitioning of solar energy at the Earth surface has significant implications in climate dynamics, hydrology, and ecology. Consequently, spatial mapping of energy partitioning from satellite remote sensing data has been an active research area for over two decades. We developed an algorithm for estimating evaporation fraction (EF), expressed as a ratio of actual evapotranspiration (ET) to the available energy (sum of ET and sensible heat flux), from satellite data. The algorithm is a simple two-source model of ET. We characterize a landscape as a mixture of bare soil and vegetation and thus we estimate EF as a mixture of EF of bare soil and EF of vegetation. In the estimation of EF of vegetation, we use the complementary relationship of the actual and the potential ET for the formulation of EF. In that, we use the canopy conductance model for describing vegetation physiology. On the other hand, we use “VI- T s ” (vegetation index-surface temperature) diagram for estimation of EF of bare soil. As operational production of EF globally is our goal, the algorithm is primarily driven by remote sensing data but flexible enough to ingest ancillary data when available. We validated EF from this prototype algorithm using NOAA/AVHRR data with actual observations of EF at AmeriFlux stations (standard error ≌ 0.17 and R 2 ≌ 0.71). Global distribution of EF every 8 days will be operationally produced by this algorithm using the data of MODIS on EOS-PM (Aqua) satellite.
[5]	Ozgoren M, Bilgili M, Sahin B.Estimation of global solar radiation using ANN over Turkey. Expert Systems with Applications, 2012, 39(5): 5043-5051.https://doi.org/10.1016/j.eswa.2011.11.036 URL [本文引用: 1]摘要 The main objective of the present study is to develop an artificial neural network (ANN) model based on multi-nonlinear regression (MNLR) method for estimating the monthly mean daily sum global solar radiation at any place of Turkey. For this purpose, the meteorological data of 31 stations spread over Turkey along the years 2000-2006 were used as training (27 stations) and testing (4 stations) data. Firstly, all independent variables (latitude, longitude, altitude, month, monthly minimum atmospheric temperature, maximum atmospheric temperature, mean atmospheric temperature, soil temperature, relative humidity, wind speed, rainfall, atmospheric pressure, vapor pressure, cloudiness and sunshine duration) were added to the Enter regression model. Then, the Stepwise MNLR method was applied to determine the most suitable independent (input) variables. With the use of these input variables, the results obtained by the ANN model were compared with the actual data, and error values were found within acceptable limits. The mean absolute percentage error (MAPE) was found to be 5.34% and correlation coefficient ( R ) value was obtained to be about 0.9936 for the testing data set.
[6]	Li Z, Zhao L F, Fu Zhuo.Estimating net radiation flux in Tibetan Plateau by assimilating MODIS LST products with an ensemble Kalman filter and particle filter. International Journal of Applied Earth Observation and Geoinformation, 2012, 19(10): 1-11.https://doi.org/10.1016/j.jag.2012.04.003 URL [本文引用: 1]摘要 Net radiation flux is a key physical variable of energy and water exchange processes in land-atmosphere interactions. Among the methods to estimate net radiation flux, measurements and estimates from modeling have their limitations. Data assimilation methods have potential to estimate net radiation flux more accurately by merging model dynamics and observations. In this paper, two data assimilation schemes are developed based on the Common Land Model (CoLM) using the ensemble Kalman filter (EnKF) and particle filter (PF) algorithms, respectively, to improve predictions of surface net radiation flux in the Tibetan Plateau. First, Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) products were used to update the LAI in CoLM. It was found that sparse vegetation in the Tibetan Plateau has an obvious influence on the surface temperature. Then, the experiments of assimilating MODIS land surface temperature (LST) products were carried out with the EnKF and PF algorithms, respectively. The two schemes were tested and validated with observations from two automatic weather stations (AWSs) in Muztaga in the Tibetan Plateau during the period of October 1, 2009-September 30, 2010. The results show that the two assimilation schemes are both feasible and an improvement over the predictions of cases with no assimilation for the estimations of surface temperature and net radiation flux. Furthermore, the different surface types and the accuracy of MODIS LST products have an important influence on the assimilation results. In addition, the performances of EnKF and PF are almost same in the study.
[7]	朱君, 唐伯惠. 利用MODIS数据计算中国地表短波净辐射通量的研究 . 遥感信息, 2008, (3): 60-65.URL Magsci [本文引用: 2]摘要地表短波净辐射是辐射能量的重要收入部分,对研究地表辐射平衡、地气能量交换以及各种天气气候的形成都具有决定性的意义.目前国际上利用卫星数据计算地表短波净辐射大多采用空间分辨率较低的宽通道反照率数据(如ERBE卫星数据,空间分辨率为35km),这难以满足局部尺度的能量平衡和蒸散等研究的需要.本文利用空间分辨率达1km的窄通道多光谱MODIS卫星数据,通过相关处理计算,无需气象数据和地面测量数据的参与,就获得了中国的地表短波净辐射通量分布图.经与禹城地区地面实测数据对比可知,晴空时均方根误差小于20 W/m2,有云时均方根误差小于35 W/m2,表明本文使用的地表短波净辐射反演方法适合中国范围地表短波净辐射的计算. [Zhu Jun, Tang Bohui.Net surface shortwave radiation mapping over China using MODIS data. Remote Sensing Information, 2008, (3): 60-65.]URL Magsci [本文引用: 2]摘要地表短波净辐射是辐射能量的重要收入部分,对研究地表辐射平衡、地气能量交换以及各种天气气候的形成都具有决定性的意义.目前国际上利用卫星数据计算地表短波净辐射大多采用空间分辨率较低的宽通道反照率数据(如ERBE卫星数据,空间分辨率为35km),这难以满足局部尺度的能量平衡和蒸散等研究的需要.本文利用空间分辨率达1km的窄通道多光谱MODIS卫星数据,通过相关处理计算,无需气象数据和地面测量数据的参与,就获得了中国的地表短波净辐射通量分布图.经与禹城地区地面实测数据对比可知,晴空时均方根误差小于20 W/m2,有云时均方根误差小于35 W/m2,表明本文使用的地表短波净辐射反演方法适合中国范围地表短波净辐射的计算.
[8]	Bisht G, Venturini V, Islam S, et al.Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear sky days. Remote Sensing of Environment, 2005, 97(1): 52-67.https://doi.org/10.1016/j.rse.2005.03.014 URL [本文引用: 5]摘要 A simple scheme is proposed to estimate instantaneous net radiation over large heterogeneous areas for clear sky days using only remote sensing observations. Our method attempts to develop an algorithm which primarily uses remote sensing information and eliminates the need for ground information as model input, by using various land and atmospheric data products available from Terra–MODIS. It explicitly recognizes the need for spatially varied parameters and provides a distributed net radiation map over large heterogeneous domain with fine spatial resolution. Since instantaneous net radiation estimates have limited scope compared to daily average values or diurnal cycle, a sinusoidal model is proposed to estimate diurnal cycle of net radiation. The sinusoidal model is capable of retrieving the diurnal variations of net radiation with a single instantaneous net radiation estimate from the satellite. Preliminary results, using data over Southern Great Plains, show good agreement with ground-based observations. It appears that the methodology presented here can estimate instantaneous and daily net radiation with comparable accuracy to those of current methods that use ground-based observations and mainly provide point estimates.
[9]	Tang B H, Li Z L.Estimation of instantaneous net surface long radiation from MODIS cloud-free data. Remote Sensing of Environment, 2008, 112(9): 3482-3492.https://doi.org/10.1016/j.rse.2008.04.004 URL摘要 This paper develops a statistical regression method to estimate the instantaneous Downwelling Surface Longwave Radiation (DSLR) for cloud-free skies using only the satellite-based radiances measured at the Top Of the Atmosphere (TOA), and subsequently combines the DSLR with the MODIS land surface temperature/emissivity products (MOD11_L2) to estimate the instantaneous Net Surface Longwave Radiation (NSLR). The proposed method relates the DSLR directly to the TOA radiances in the MODIS Thermal InfraRed (TIR) channels provided that the terrain altitude and the satellite Viewing Zenith Angle (VZA) are known. The simulation analysis shows that the instantaneous DSLR could be estimated by the proposed method with the Root Mean Square Error (RMSE) of 12.4 W/mfor VZA = 0 and terrain altitude = 0 km. Similar results are obtained for the other VZAs and altitudes. Considering the MODIS instrumental errors of 0.25 K for the TOA brightness temperatures in channels 28, 33 and 34, and of 0.05 K for channels 29 and 31, and of 0.35 K for channel 36, the overall retrieval accuracy in terms of the RMSE is decreased to 13.1 W/mfor the instantaneous DSLR. Moreover, a comparison of MODIS derived DSLR and NSLR are done with the field measurements made at six sites of the Surface Radiation Budget Network (SURFRAD) in the United States for days with cloud-free conditions at the moment of MODIS overpass in 2006. The results show that the bias, RMSE and the square of the correlation coefficient () between the MODIS derived DSLR with the proposed method and the field measured DSLR are 20.3 W/m, 30.1 W/mand 0.91 respectively, and bias = 11.7 W/m, RMSE = 26.1 W/mand = 0.94 for NSLR. In addition, the scheme proposed by Bisht et al. [Bisht, G., Venturini, V., Islam, S., & Jiang, L. (2005). Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear-sky days. 52-67], which requires the MODIS atmospheric profile product (MOD07) and also the MODIS land surface temperature/emissivity products (MOD11_L2) as inputs, is used to estimate the instantaneous DSLR and NSLR for comparison with the field measurements as well as the MODIS derived DSLR and NSLR using our proposed method. The results of the comparisons show that, at least for our cases, our proposed method for estimating DSLR from the MODIS radiances at the TOA and the resultant NSLR gives results comparable to those estimated with Bisht et al.'s scheme [Bisht, G., Venturini, V., Islam, S., & Jiang, L. (2005). Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear-sky days. 52-67].
[10]	Bisht G, Bras R L.Estimation of net radiation from the MODIS data under all sky conditions Southern Great Plains case study. Remote Sensing of Environment, 2010, 114(7): 1522-1534.https://doi.org/10.1016/j.rse.2010.02.007 URL [本文引用: 2]摘要 Net radiation is a key component in the surface radiation budget. Numerous studies have developed frameworks to estimate net radiation or its components (upwelling or downwelling longwave and/or shortwave radiation) from remote sensing data for clear sky conditions. Application of existing methodologies to estimate net radiation for cloudy sky conditions from remote sensing sensors remains a significant challenge. In this paper, we present a framework to estimate instantaneous and daily average net radiation under all sky conditions from using the data from the MODerate Resolution Imaging Spectroradiometer (MODIS), onboard from the Terra satellites. Bisht et al. (2005) methodology is used for the clear sky portion of the MODIS overpass; while for cloudy portion of the MODIS overpass an extension of Bisht et al. (2005) methodology is applied. The extension of Bisht et al. (2005) methodology utilizes the MODIS cloud data product (MOD06_L2) for cloud top temperature, cloud fraction, cloud emissivity, cloud optical thickness and land surface temperature for cloudy days. The methodology is applied over the Southern Great Plains (SGP) for a time period covering all seasons of 2006. During the MODIS-Terra overpasses in 2006 over the SGP, only 24% of day-overpasses and 9% of night-overpasses had 75% or more of the study region as cloud free. Thus, this proposed study is applicable to a large portion of the MODIS-Terra overpasses. The root mean square errors (RMSE) of instantaneous and daily average net radiation estimated under cloudy conditions using the MOD06_L2 product, comparing to ground-based measurements are 3702W02m 61022 and 3802W02m 61022 , respectively. The strength of the proposed methodology is that it can rely exclusively on remote sensing data in the absence of ancillary ground observations, thus it has a potential to estimate surface energy budget globally.
[11]	Kim H, Liang S L.Development of a hybrid method for estimating land surface shortwave net radiation from MODIS data. Remote Sensing of Environment, 2010, 114(11): 2393-2402.https://doi.org/10.1016/j.rse.2010.05.012 URL摘要 Accurate estimation of shortwave net radiation (S-n) at a high spatial resolution is critical for regional and global land surface models. Current surface radiation budget products have fine temporal resolutions, but only coarse spatial resolutions that are not suitable for land applications. A hybrid algorithm was developed in this study to estimate S-n from MODIS data under both clear and cloudy sky conditions without requiring coarser resolution ancillary data. This algorithm was validated using ground measurements at seven sites of the SURFace RADiation budget observing network (SURFRAD) in the United States. Instantaneous S-n estimated by this method was also compared with GEWEX/SRB and ISCCP data, and other methods. The results indicate that our algorithm can produce S-n at 1-km resolution with improved accuracy and is easily implemented to generate operational global products. Daily integrated S-n is estimated at 1-km resolution using instantaneous S-n. These finer spatial resolution datasets capture the specific sequence of the redistribution of the available energy at the Earth's surface. Therefore, they support recent high resolution land surface models. (C) 2010 Elsevier Inc. All rights reserved.
[12]	Hou J T, Jia J S, Zhao T B, et al.Satellite-based estimation of daily average net radiation under clear-sky conditions. Advances in Atmospheric Sciences, 2014, 31(3): 705-720.https://doi.org/10.1007/s00376-013-3047-6 Magsci [本文引用: 1]摘要 <p>Daily average net radiation (DANR) is an important variable for estimating evapotranspiration from satellite data at regional scales, and is used for atmospheric and hydrologic modeling, as well as ecosystem management. A scheme is proposed to estimate the DANR over large heterogeneous areas under clear-sky conditions using only remotely sensed data. The method was designed to overcome the dependence of DANR estimates on ground data, and to map spatially consistent and reasonably distributed DANR, by using various land and atmospheric data products retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) data. An improved sinusoidal model was used to retrieve the diurnal variations of downward shortwave radiation using a single instantaneous value from satellites. The downward shortwave component of DANR was directly obtained from this instantaneous value, and the upward shortwave component was estimated using satellite-derived albedo products. Four observations of air temperature from MOD07_L2 and MYD07_L2 data products were used to derive the downward longwave component of DANR, while the upward longwave component was estimated using the land surface temperature (LST) and the surface emissivity from MOD11_L2. Compared to <em>in situ</em> observations at the cropland and grassland sites located in Tongyu, northern China, the root mean square error (RMSE) of DANR estimated for both sites under clear-sky conditions was 37 W m<em><sup>-2</sup></em> and 40 W m<em><sup>-2</sup></em>, respectively. The errors in estimation of DANR were comparable to those from previous satellite-based methods. Our estimates can be used for studying the surface radiation balance and evapotranspiration.</p>
[13]	全维俊, 陈洪滨, 郭文利, 等. 两种反演地表净太阳辐射的参数化模式在北京地区的比较 . 气象学报, 2009, 67(4): 623-630.https://doi.org/10.11676/qxxb2009.062 Magsci [本文引用: 1]摘要地表净太阳辐射（NSSR）在地表辐射平衡、地气能量交换、天气预报、气候变化和太阳能利用等研究方面具有重要的作用。利用卫星遥感技术能在广大的空间区域内快速地获取地表净太阳辐射的分布情况，特别是在无人观测的极地和海洋区域。本文基于CERES/SSF卫星数据，分别采用两种地表净太阳辐射(NSSR)的卫星反演参数化模式—Li模式与Masuda模式计算了北京市上甸子地区2005年1、4、7和10月的NSSR，并将反演结果与上甸子大气本底站的实测结果进行了对比分析，并对两种模式进行了修正以更好地反演北京地区的地表净太阳辐射。结果显示： Li模式和Masuda模式反演结果与实测结果间的平均绝对误差MBE在晴空条件下分别为和，在云天下分别为和；Li模式相对于Masuda模式具有偏大的趋势，在晴天和云天条件下两者的平均绝对偏差MAD分别为和；对Li模式和Masuda模式进行线性拟合回归后能有效减小反演过程中的系统性偏差，修改后的Li模式和Masuda模式在所有天空状况下反演的月平均NSSR值与观测值间的MBE分别为和，均方根误差RMSE分别为和。 [Quan Weijun, Chen Hongbin, Guo Wenli, et al.Net surface solar radiation over Beijing area derived by two parameterization models: A comparison. Acta Meteorologica Sinica, 2009, 67(4): 623-630.]https://doi.org/10.11676/qxxb2009.062 Magsci [本文引用: 1]摘要地表净太阳辐射（NSSR）在地表辐射平衡、地气能量交换、天气预报、气候变化和太阳能利用等研究方面具有重要的作用。利用卫星遥感技术能在广大的空间区域内快速地获取地表净太阳辐射的分布情况，特别是在无人观测的极地和海洋区域。本文基于CERES/SSF卫星数据，分别采用两种地表净太阳辐射(NSSR)的卫星反演参数化模式—Li模式与Masuda模式计算了北京市上甸子地区2005年1、4、7和10月的NSSR，并将反演结果与上甸子大气本底站的实测结果进行了对比分析，并对两种模式进行了修正以更好地反演北京地区的地表净太阳辐射。结果显示： Li模式和Masuda模式反演结果与实测结果间的平均绝对误差MBE在晴空条件下分别为和，在云天下分别为和；Li模式相对于Masuda模式具有偏大的趋势，在晴天和云天条件下两者的平均绝对偏差MAD分别为和；对Li模式和Masuda模式进行线性拟合回归后能有效减小反演过程中的系统性偏差，修改后的Li模式和Masuda模式在所有天空状况下反演的月平均NSSR值与观测值间的MBE分别为和，均方根误差RMSE分别为和。
[14]	Hurtado E, Sobrino J A.Daily net radiation estimated from air temperature and NOAA-AVHRR data: A case study for the Iberian Peninsula. Journal of Remote Sensing, 2001, 22(8): 1521-1533.https://doi.org/10.1080/01431160121189 URL [本文引用: 1]摘要 In this work we present a methodology to obtain the daily net radiation flux from NOAA-AVHRR data. To achieve this we need first to obtain shortwave net radiation flux from the solar global radiation flux and the albedo map. Secondly, we need to obtain the upward longwave radiation flux from surface temperature and emissivity and the downward longwave radiation flux from air temperature and vapour pressure. A daily net radiation flux image corresponding to flat areas of the Iberian Peninsula is presented as an example in which we show that daily net radiation flux can be obtained with an uncertainty of approximately 1.5 mm day -1 .
[15]	郭建茂, 于强, 王连喜, 等. 宁南地区地表特征参数及辐射平衡区域分布 . 地理研究, 2007, 26(6): 1127-1135.Magsci [本文引用: 1]摘要 <p>本文利用2001年6月30日LANDSAT-7 ETM+卫星遥感资料和宁夏南部及周边区域22个气象站气象观测资料,求得地表特征参数中NDVI、地表反射率、地表温度和地表辐射平衡各量中地表短波吸收辐射、地表长波辐射区域、大气逆辐射、净辐射的区域分布和分布直方图,将地表分成5类,分类别讨论了其各量分布特征。主要研究结果表明:地表特征参数及地表辐射平衡各量的分布均呈现明显的地带性,各区域分布图上山体、水体的轮廓很显著,主要原因是山上及河流附近生长着茂密的植被,说明植被的分布在相当程度上影响了辐射平衡各量和地表特征参数的分布。</p> [Guo Jianmao, Yu Qiang, Wang Lianxi, et al.Study on regional distribution of land surface parameters and components of surface radiation balance over South Ningxia. Geographical Research, 2007, 26(6): 1127-1135.]Magsci [本文引用: 1]摘要 <p>本文利用2001年6月30日LANDSAT-7 ETM+卫星遥感资料和宁夏南部及周边区域22个气象站气象观测资料,求得地表特征参数中NDVI、地表反射率、地表温度和地表辐射平衡各量中地表短波吸收辐射、地表长波辐射区域、大气逆辐射、净辐射的区域分布和分布直方图,将地表分成5类,分类别讨论了其各量分布特征。主要研究结果表明:地表特征参数及地表辐射平衡各量的分布均呈现明显的地带性,各区域分布图上山体、水体的轮廓很显著,主要原因是山上及河流附近生长着茂密的植被,说明植被的分布在相当程度上影响了辐射平衡各量和地表特征参数的分布。</p>
[16]	Liu N F, Liu Q, Wang L Z, et al.Mapping spatially and temporally continuous shortwave albedo for global land surface from MODIS data. Hydrology and Earth System Sciences Discussion, 2012, 9(7): 9043-9064.https://doi.org/10.5194/hessd-9-9043-2012 URL [本文引用: 1]摘要 Land-surface albedo plays a critical role in the Earth's radiant energy budget studies. Satellite remote sensing is an effective approach to acquire regional and global albedo observations. However, owing to cloud coverage, seasonal snow and sensor malfunctions, spatially-temporally continuous albedo datasets are often inaccessible. GLASS preliminary albedo datasets (GLASS02A2x, x = 1, 2, 3 and 4) are newly developed global daily land-surface albedo products. Like other products, GLASS02A2x albedo surfers from large areas of missing data. Beside this, sharp fluctuations exist in GLASS02A2x time series due to data noise and algorithm uncertainties. In this study, a statistics-based temporal filterer (STF) is proposed to fill the data gaps and smooth the fluctuations in GLASS02A2x albedo time series. The result of STF algorithm is the GLASS final albedo product (GLASS02A06). Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODIS product, the final GLASS albedo product is much more competent in capturing the surface albedo variations. Although the STF algorithm is designed for GLASS albedo product, it is able to incorporate other albedo products. The STF method may also be applied to other parameters, such as the LAI and soil moisture.
[17]	Zhao X, Liang S L, Liu S H, et al.The Global Land Surface Satellite (GLASS) remote sensing data processing system and products. Remote Sensing, 2013, 5(5): 2436-2450.https://doi.org/10.3390/rs5052436 Magsci [本文引用: 1]摘要 Using remotely sensed satellite products is the most efficient way to monitor global land, water, and forest resource changes, which are believed to be the main factors for understanding global climate change and its impacts. A reliable remotely sensed product should be retrieved quantitatively through models or statistical methods. However, producing global products requires a complex computing system and massive volumes of multi-sensor and multi-temporal remotely sensed data. This manuscript describes the ground Global LAnd Surface Satellite (GLASS) product generation system that can be used to generate long-sequence time series of global land surface data products based on various remotely sensed data. To ensure stabilization and efficiency in running the system, we used the methods of task management, parallelization, and multi I/O channels. An array of GLASS remote sensing products related to global land surface parameters are currently being produced and distributed by the Center for Global Change Data Processing and Analysis at Beijing Normal University in Beijing, China. These products include Leaf Area Index (LAI), land surface albedo, and broadband emissivity (BBE) from the years 1981 to 2010, downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) from the years 2008 to 2010.
[18]	Liu Q, Wang L Z, Qu Y, et al.Preliminary evaluation of the long-term GLASS product. International Journal of Digital Earth, 2013, 6(S1): 69-95. [本文引用: 1]
[19]	Cheng J, Liang S L.Estimating global land surface broadband thermal-infrared emissivity using advanced very high resolution radiometer optical data. International Journal of Digital Earth, 2013, 6(S1): 34-39.https://doi.org/10.1080/17538947.2013.783129 URL [本文引用: 1]摘要 An algorithm for retrieving global eight-day 5 km broadband emissivity (BBE) from advanced very high resolution radiometer (AVHRR) visible and near-infrared data from 1981 through 1999 was presented. Land surface was divided into three types according to its normalized difference vegetation index (NDVI) values: bare soil, vegetated area, and transition zone. For each type, BBE at 8–13.5 08m was formulated as a nonlinear function of AVHRR reflectance for Channels 1 and 2. Given difficulties in validating coarse emissivity products with ground measurements, the algorithm was cross-validated by comparing retrieved BBE with BBE derived through different methods. Retrieved BBE was initially compared with BBE derived from moderate-resolution imaging spectroradiometer (MODIS) albedos. Respective absolute bias and root-mean-square error were less than 0.003 and 0.014 for bare soil, less than 0.002 and 0.011 for transition zones, and 610.002 and 0.005 for vegetated areas. Retrieved BBE was also compared with BBE obtained through the NDVI threshold method. The proposed algorithm was better than the NDVI threshold method, particularly for bare soil. Finally, retrieved BBE and BBE derived from MODIS data were consistent, as were the two BBE values.
[20]	Dong L X, Hu J Y, Tang S H, et al.Field validation of the GLASS land surface broadband emissivity database using pseudo-invariant sand dune sites in northern China. International Journal of Digital Earth, 2013, 6(S1): 96-112.https://doi.org/10.1080/17538947.2013.822573 URL摘要 The land surface broadband emissivity (LSBE) is a key parameter for estimating surface radiation, and there have been many studies of the LSBE at global or local scales. However, few studies have validated the surface emissivity database with multi-point field measurement data using infrared radiometry, especially in China. In this study, we focus on the validation of the emissivity product of the global land surface satellite (GLASS) LSBE database for northern China for the period from 2006 to 2011. Specifically, we have employed an eight-day averaged, gridded emissivity product in the 8-13.5 μm spectral range produced at a spatial resolution of 1000 m from the Moderate Resolution Imaging Spectrometer albedo product using a new algorithm. The GLASS LSBE database was validated over bare surfaces with field measurement data from sand samples collected at many pseudo-invariant sand dune sites located in western and northwestern China. By comparing measured emissivity for different land surface types at different sites and different times, it was shown that the results were consistent and that the accuracy of the field measurements was reliable. The results of the validation of GLASS LSBE with these field emissivity data showed very good agreement.
[21]	Liang S L, Zhao X, Liu S H, et al.A long-term Global Land Surface Satellite (GLASS) data-set for environmental studies. International Journal of Digital Earth, 2013, 6(S1): 1-24.https://doi.org/10.1080/17538947.2013.805262 URL摘要 ABSTRACT Recently, five Global LAnd Surface Satellite (GLASS) products have been released: leaf area index (LAI), shortwave broadband albedo, longwave broadband emissivity, incident short radiation, and photosynthetically active radiation (PAR). The first three products cover the years 1982–2012 (LAI) and 1981–2010 (albedo and emissivity) at 1–5 km and 8-day resolutions, and the last two radiation products span the period 2008–2010 at 5 km and 3-h resolutions. These products have been evaluated and validated, and the preliminary results indicate that they are of higher quality and accuracy than the existing products. In particular, the first three products have much longer time series, and are therefore highly suitable for various environmental studies. This paper outlines the algorithms, product characteristics, preliminary validation results, potential applications and some examples of initial analysis of these products.
[22]	Cheng J, Liang S L.Estimating the broadband longwave emissivity of global bare soil from the MODIS shortwave albedo product. Journal of Geophysical Research: Atmospheres, 2014, 119: 614-634.https://doi.org/10.1002/2013JD020689 URL Magsci [本文引用: 1]摘要 <p>A constant land surface longwave emissivity value, or very simple parameterization, has been adopted by current land surface models because of a current lack of reliable observations. Of all the various Earth surface types, bare soil has the highest variations in broadband emissivity (BBE). We propose here a new algorithm to estimate BBE in the 8–13.5 µm spectral range based on the Moderate Resolution Imaging Spectrometer (MODIS) albedo product for bare soil. This algorithm takes advantage of both Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) longwave emissivity and MODIS shortwave albedo products, as well as the established linear relationship between ASTER BBE and seven MODIS spectral albedos for bare soil. In order to mitigate step discontinuities in the global land surface BBE product, a transition zone was established and the BBE estimation method was also provided. Three linear formulae were derived for bare soil and transition zones, respectively. Given the accuracy of 0.01 for MODIS spectral albedo, the absolute accuracy of BBE retrieval is better than 0.017. The validation results obtained from the three field trials conducted in China and one field trial in western/southwestern U.S. indicated that the average difference between the estimated BBE and the measured BBE was 0.016. We have introduced a new strategy to generate global land surface BBE using MODIS data. This strategy was used to generate global 8 day 1 km land surface BBE products from 2000 through 2010.</p>
[23]	Jin H A, Li A N, Bian J H, et al.Validation of Global Land Surface Satellite (GLASS) downward shortwave radiation product in the rugged surface. Journal of Mountain Science, 2013, 10(5): 812-823.https://doi.org/10.1007/s11629-013-2543-6 URL [本文引用: 1]摘要 The downward shortwave radiation(DSR) is an essential parameter of land surface radiation budget and many land surface models that characterize hydrological,ecological and biogeochemical processes.The new Global LAnd Surface Satellite(GLASS) DSR datasets have been generated recently using multiple satellite data in China.This study investigates the performances of direct comparison approach,which is mostly used for validation of surface insolation retrieved from satellite data over the plain area,and indirect comparison approach,which needs a fine resolution map of DSR as reference,for validation of GLASS DSR product in time-steps of 1 and 3 hours over three Chinese Ecosystem Research Network sites located in the rugged surface.Results suggest that it probably has a large uncertainty to assess GLASS DSR product using the direct comparison method between GLASS surface insolation and field measurements over complex terrain,especially at Mt.Gongga 3,000 m station with root mean square error of 279.04 and 229.06 W/m2in time-steps of 1 and 3 hours,respectively.Further improvement for validation of GLASS DSR product in the rugged surface is suggested by generation of a fine resolution map of surface insolation and comparison of the aggregated fine resolution map with GLASS product in the rugged surface.The validation experience demonstrates that the GLASS DSR algorithm is satisfactory with determination coefficient of 0.83 and root mean square error of 81.91W/m2over three Chinese Ecosystem Research Network sites,although GLASS product overestimates DSR compared to the aggregated fine resolution map of surface insolation.
[24]	Huang G H, Wang W Z, Zhang X T, et al.Preliminary validation of GLASS-DSSR products using surface measurements collected in arid and semi-arid regions of China. International Journal of Digital Earth, 2013, 6(S1): 50-68.https://doi.org/10.1080/17538947.2013.825655 URL [本文引用: 1]摘要 Global Land Surface Satellite-downward surface shortwave radiation (GLASS-DSSR) products have been routinely produced from 2008-2010 based on an improved look-up table algorithm, which explicitly accounts for the variations of cloud optical depth, water vapor content, and elevation. In this study, we validated and assessed the accuracy of these products in arid and semiarid regions of China. Toward this goal, observation data-sets provided by the Arid and Semiarid Region Collaborative Observation Project as well as four other metrological sites were collected, chosen, and preprocessed for the final validation. Due to the possible effect of spatial collocation and the strong adjacency pixel effect in instantaneous products, we used a more sophisticated validating scheme in order to reduce the impacts from these effects as much as possible. Evidences indicate that the GLASS-DSSR products are considerably accurate over most parts of arid and semiarid regions in China, but in complex terrain areas the products might need further refinements. The R 2 at all sites (except Naqu) was larger than 0.8 with a root mean square error (RMSE) range of about in 90鈥130 W/m 2 . Linear regression analyses suggest that GLASS-DSSR products tend to overestimate DSSR in the interval of low surface-measured values and symmetrically underestimate DSSR in the interval of high values. This systematic error may result from inappropriate assumptions about clouds and aerosol loadings over the regions in the operational algorithm.
[25]	Ryu Y, Kang S, Moon S K, et al.Evaluation of land surface radiation balance derived from moderate resolution imaging spectroadiometer (MODIS) over complex terrain and heterogeneous landscape on clear sky days. Agriculture and Forest Meteorology, 2008, 148(10): 1538-1552. [本文引用: 1]
[26]	黄妙芬, 邢旭峰, 朱启疆, 等. 定量遥感地表净辐射通量所需大气下行长波辐射估算模型改进 . 地理研究, 2005, 24(5): 757-765.Magsci [本文引用: 2]摘要 <p>利用半湿润季风气候类型夏季近地层气象观测资料,对得到广泛应用的十种晴天大气下行辐射估算模型和两种昙天大气下行辐射估算模型进行检验。指出其中Iziomon(2003)晴天大气下行辐射估算模型是半湿润季风气候类型夏季较适用的估算模型。然而,在有云天空,Iziomon(2003)昙天估算模型误差比较大。本文依据实测资料,对Iziomon(2003)昙天大气下行辐射估算模型进行修正,修正后的模型估算值与实测值非常接近。由于应用常规气象站的大气温湿度来估算大气下行辐射仅代表近地层大气对其的贡献,不能反映整层大气的贡献,尤其在近地层与高空大气的水汽状况不一致时,上述模型将有较大的误差。为此本文结合Iziomon(2003)晴天模型中大气比辐射率的表达式,提出了运用红外辐射计以37°高度角对天空的观测值,来推算大气下行辐射的新方法。小汤山的试验数据表明,新模型的反演精度优于上述传统模型。</p> [Huang Miaofen, Xing Xufeng, Zhu Qijiang, et al.Improvement of models for the estimation of downward atmospheric long-wave radiation for retrieving net radiation fluxes based on remote sensing. Geographical Research, 2005, 24(5): 757-765.]Magsci [本文引用: 2]摘要 <p>利用半湿润季风气候类型夏季近地层气象观测资料,对得到广泛应用的十种晴天大气下行辐射估算模型和两种昙天大气下行辐射估算模型进行检验。指出其中Iziomon(2003)晴天大气下行辐射估算模型是半湿润季风气候类型夏季较适用的估算模型。然而,在有云天空,Iziomon(2003)昙天估算模型误差比较大。本文依据实测资料,对Iziomon(2003)昙天大气下行辐射估算模型进行修正,修正后的模型估算值与实测值非常接近。由于应用常规气象站的大气温湿度来估算大气下行辐射仅代表近地层大气对其的贡献,不能反映整层大气的贡献,尤其在近地层与高空大气的水汽状况不一致时,上述模型将有较大的误差。为此本文结合Iziomon(2003)晴天模型中大气比辐射率的表达式,提出了运用红外辐射计以37°高度角对天空的观测值,来推算大气下行辐射的新方法。小汤山的试验数据表明,新模型的反演精度优于上述传统模型。</p>
[27]	彭光雄, 李京, 陈云浩, 等. 利用MODIS大气廓线产品计算空气相对湿度的方法研究 . 热带气象学报, 2007, 23(6): 611-615.https://doi.org/10.3969/j.issn.1004-4965.2007.06.013 URL [本文引用: 2]摘要森林火灾遍及全球，损失巨大。火险天气指数（FWI）是森林火灾预警和管理的有效工具。相对湿度（RH）是计算天气火险指数一个非常重要的参数。然而，由插值方法得到的RH在远离气象站点的地方往往存在很大的误差。因此，尝试利用MODIS遥感数据计算基于像元的高分辨率RH。MODIS的MOD07大气廓线产品，可以提供大气可降水量和地表气温数据。基于地面水汽压和大气可降水量的经验关系，利用MODIS数据计算了地表空气的相对湿度，平均绝对误差小于5％。结果表明，利用MODIS数据能简单而有效地计算地表空气的相对湿度，拓展了遥感技术在森林火险管理中的应用。 [Peng Guangxiong, Li Jing, Chen Yunhao, et al.A Method of estimating relative humidity from MODIS atmospheric profile products. Journal of Tropical Meteorology, 2007, 23(6): 611-615.]https://doi.org/10.3969/j.issn.1004-4965.2007.06.013 URL [本文引用: 2]摘要森林火灾遍及全球，损失巨大。火险天气指数（FWI）是森林火灾预警和管理的有效工具。相对湿度（RH）是计算天气火险指数一个非常重要的参数。然而，由插值方法得到的RH在远离气象站点的地方往往存在很大的误差。因此，尝试利用MODIS遥感数据计算基于像元的高分辨率RH。MODIS的MOD07大气廓线产品，可以提供大气可降水量和地表气温数据。基于地面水汽压和大气可降水量的经验关系，利用MODIS数据计算了地表空气的相对湿度，平均绝对误差小于5％。结果表明，利用MODIS数据能简单而有效地计算地表空气的相对湿度，拓展了遥感技术在森林火险管理中的应用。

基于GLASS数据估算中国陆表净辐射及其空间分布分析

本站小编 Free考研考试/2021-12-29

Land surface radiation budget parameterization and spatial analysis over China using GLASS data

1 引言