远红外高光谱遥感技术及其冰云遥感应用（特邀）特邀综述
The observation of atmospheric far-infrared radiation is of significance for a deeper understanding of radiation exchange and balance in the earth-atmosphere system, especially in polar regions. More importantly, compared with other bands, far-infrared bands have inimitable advantages in remote sensing of ice clouds, upper layer water vapor in the troposphere, and atmosphere ingredients.
On the one hand, far-infrared radiation plays a crucial role in regulating climate and energy balance. Far-infrared radiation accounts for about 40% to 65% of the Earth's energy emitted to space and thus makes great contributions to the Earth's OLR (outgoing longwave radiation) and atmospheric cooling. However, there is still significant uncertainty in addressing the key issues related to heat flux regulation factors in cold and dry polar conditions due to the limited observations of far-infrared radiation, which has a negative influence on the accuracy of climate models. On the other hand, in atmospheric remote sensing, far-infrared spectra are highly sensitive to low-concentration water vapor in low temperature conditions, making it important for remote sensing of water vapor in polar regions, and in the upper troposphere and lower stratosphere. Additionally, the complex refractive indices of water and ice exhibit different spectral characteristics in mid-infrared and far-infrared bands, further enhancing the ability for cloud detection and phase recognition. Meanwhile, far-infrared hyperspectral radiation is considered to have the potential to improve the retrieval accuracy of microphysical and optical properties of thin ice clouds.
However, currently direct measurements of far-infrared radiation at hyperspectral resolution are still relatively limited due to technical issues related to precise spectroscopic and highly sensitive measurements. The most recent measurement of spaceborne far-infrared hyperspectral spectra can be traced back to the 1970s when the National Aeronautics and Space Administration of the United States (NASA) launched the Nimbus-III and Nimbus-IV using the IRIS (infrared interferometer sound) infrared interferometer, which measured far-infrared to mid-infrared radiation with a relatively rough spectral resolution (2.8 cm-1) and a spatial resolution ranging from 400 cm-1 to 1600 cm-1. However, this is still the only satellite borne far-infrared radiation spectral observation data that can be obtained on a global scale. The main technical difficulties for spaceborne far-infrared radiation measurements lie in high-sensitivity detectors and hyperspectral optical systems (such as beam splitters). Due to the low photon energy in the infrared band, traditional infrared hyperspectral interferometers often require cooling by liquid helium (or liquid nitrogen) to improve measurement accuracy and signal-to-noise ratio, and this cannot be extended to satellite applications. Additionally, the moving mirror system of the Fourier spectrometer must also consider tilt and other errors when carried in space. These factors have become the main constraints on the development of high-precision and hyperspectral measurements of atmospheric far-infrared radiation for spaceborne payloads.
In recent years, with the development of high-sensitive uncooled detectors and beam splitters, a few comprehensive observation experiments of atmospheric far-infrared radiation at hyperspectral resolution have been conducted based on ground-based and airborne prototypes. Institutions such as the European Space Agency (ESA) and the NASA have also proposed a series of missions to observe far-infrared radiation by satellite instruments. Retrievals of ice cloud characteristics using hyperspectral far-infrared radiation have become an important frontier field and research hotspot. Thus, it is important and necessary to summarize the existing research to guide the future development of this field more rationally.
The main theoretical basis of far-infrared hyperspectral remote sensing is reviewed and summarized. We also introduce the advantages of far-infrared hyperspectral remote sensing of ice clouds from atmospheric absorption and ice crystal particle scattering sensitivities. Afterward, the development of far-infrared hyperspectral instruments for atmospheric remote sensing is sorted and summarized, with a focus on the technical parameters and key technical issues of the relevant instruments. From the perspective of technological breakthroughs in far-infrared radiation measurements, the key technologies associated with detectors, spectrometers, and beam splitters currently adopted have been classified and introduced (Tables 1-3). From the perspective of the platforms, the corresponding instruments and observation experiments of ground-based and airborne, and the main experimental results are introduced. Then, the main spaceborne missions to measure atmospheric far-infrared at hyperspectral resolution are summarized, including FORUM (ESA) and PREFIRE (NASA). Subsequently, the advantages and research progress of far-infrared hyperspectral technology for remote sensing of ice clouds are discussed. Since far-infrared spectra can provide complementary information on remote sensing of ice clouds, we compare studies about synergistic retrievals of ice cloud parameters and phase recognition by far-infrared and mid-infrared spectrum. In the end, the problems and the ongoing research trends in this field are discussed, including possible technological breakthroughs in the future and possible innovations in the future. The potential applications of far-infrared hyperspectral technology in ice cloud remote sensing in the future are also pointed out.
Far-infrared radiation measurements with hyperspectral resolution and highly sensitive measurements are gradually becoming a popular tool for atmospheric remote sensing. In summary, conducting global ice cloud remote sensing by hyperspectral far-infrared in the future still calls for in-depth and detailed explorations to promote the development of instrument technology, and also calls for a large number of observational experiments to develop accurate forward and retrieval algorithms.
1 引言
远红外辐射一般是指波长为15~100 μm（波数为100~667 cm-1）的电磁波，介于中红外与微波之间［1-2］。大气远红外辐射的观测对于深入理解地气系统（尤其是极地地区）的辐射交换与辐射平衡具有重要意义，而且在大气遥感领域，该波段对于冰云、对流层中上层水汽的遥感等具有其他波段不可比拟的优势［3-4］。
首先，远红外是地气系统发射辐射的重要波段，大气层顶40%~65%的长波辐射冷却发生于远红外波段，而对流层中上层的晴空长波辐射冷却也主要发生在远红外波段，进而在影响大气动力过程方面发挥着关键作用［3］。模拟研究表明，在热带地区，约1/4的温室效应发生在远红外波段，而在北极冬季地区，该比例增加到1/3［5］。此外，地表发射率、冰云、水云、水汽等在远红外波段的独特光谱特征，为人们深入了解其在气候系统中的辐射反馈效应提供了可能［6］。而在极地气候变化研究方面，地表发射率、水汽吸收和冰云光学特性等在极地能量平衡方面发挥着关键作用，但其在远红外波段的光谱特性目前仍然存在很大的不确定性，这在一定程度上阻碍了人们对极地寒冷干燥条件下热通量调节因素的理解，进而对气候模式的准确性产生重要影响［7］。如Turner等［8］通过CESM（Community Earth System Model）模式的模拟表明，远红外波段水汽连续吸收的差异可导致大气中热通量垂直分布的不确定性，从而带来温度、水汽和高云云量等大气状态的差异。
在大气参数的遥感方面，远红外辐射对低温条件下低浓度的水汽具有较高的敏感性，使其在极地地区以及对流层上部和平流层下部的水汽遥感方面具有重要应用［9-10］。此外，水和冰的复折射率在中红外和远红外波段具有不同的光谱特征，这进一步增强了云相态识别能力［11-12］。并且，冰云中小粒子的尺度与远红外波长相当，对冰云粒子具有较高的敏感性，这有利于全球云微物理特征的反演［1-2，13］。长期以来，高纬度地区薄冰云的观测仍没有得到有效解决，其发生发展特性仍然具有较大的不确定性，导致其在大气环流模式中的代表性较差，而远红外高光谱辐射（光谱分辨率小于波数的1/100）被认为具有改进薄冰云微物理和光学特性反演精度的潜力［14-16］。
然而，到目前为止，地气系统远红外辐射的直接测量仍相对有限。最近一次星载远红外辐射光谱测量还要追溯到20世纪70年代NASA发射的Nimbus-III和 Nimbus-IV上搭载的IRIS（Infrared Interferometer Sounder）红外干涉仪，其以相对粗糙的光谱分辨率（2.8 cm-1）和空间分辨率测量了波数为400~1600 cm-1的远红外-中红外辐射，但这依然是目前唯一可获取的覆盖全球范围的星载远红外辐射光谱观测数据［17］。Xie等［18］基于Nimbus-IV上的IRIS-D干涉仪观测数据，探索了远红外-中红外联合反演大气温湿廓线、地表温度和地表发射率的可行性与优势，指出增加远红外光谱辐射可明显增加湿度廓线和地表发射率的信息含量，这对未来星载高光谱遥感具有重要意义。
卫星载荷以高光谱分辨率和高灵敏度测量远红外辐射的主要技术难点在于探测器及高光谱光学系统（如分束器等）。由于红外波段的光子能量较低，传统的红外高光谱干涉仪［如AERI（Atmospheric Emitted Radiance Interferometer）］为提高测量精度与信噪比，往往需要使用液氦（或液氮）制冷［12］。而远红外波段的光子能量比中红外波段更低，且制冷系统很难长时间稳定地应用于卫星载荷的冷却。此外，傅里叶变换光谱仪的动镜系统在空间搭载时也必须考虑倾斜等误差［19］。这些因素制约星载载荷以高精度、高光谱测量大气远红外辐射的发展。近年来，随着灵敏非制冷探测技术与分束器工艺的发展，欧洲航天局（ESA）、美国国家航空航天局（NASA）等机构提出了系列远红外卫星载荷计划，并基于机载或地基原型机开展测试实验，利用该波段进行冰云特性的探测成为重要的前沿领域和研究热点。
本文综述了近些年远红外高光谱辐射在冰云特征参数遥感方面的研究现状及进展，首先介绍了远红外辐射进行大气遥感的理论基础，然后从关键技术与探测平台的角度对远红外高光谱仪器的发展过程进行了分类总结和梳理，并重点对远红外高光谱冰云参数遥感的原理和方法进行了讨论，最后对远红外高光谱冰云特性遥感技术进行了总结和展望，提出了未来的研究思路与方案。
2 远红外大气遥感的理论基础
远红外高光谱大气遥感主要以星载或机载天底观测的方式，或在极寒干燥的条件下（极地、高山等条件下）以天顶观测的方式，测量大气或云等目标发射或散射的远红外辐射，根据辐射光谱特征的变化反演云特性、温湿廓线、大气气体成分等，因此，远红外波段大气、云的辐射特性分析是实现相应参数遥感的首要条件。
远红外波段存在多种气体分子的典型吸收线，如H2O、CO2、O3、N2O、HNO3、HO等。其中，H2O、CO2是最主要的吸收气体，其吸收主要由纯转动能级跃迁和振动能级跃迁导致［20-21］。
图 1. 红外波段由主要气体分子吸收线导致的光学厚度分布［3］。（a）H2O、CO2；（b）其余吸收气体
Fig. 1. Optical depth attributed to lines of main gas molecules throughout infrared band[3]. (a) H2O and CO2; (b) remaining key absorbers
冰云辐射效应的不确定性是导致全球辐射强迫模拟存在较大误差的重要因素［25］，而这主要来源于对描述冰云的关键参数（如冰晶粒子形状、有效粒子尺度、冰水路径/冰水含量、光学厚度等）的观测误差及其辐射参数化误差，因此，提高冰云微物理特性的测量准确性一直是大气遥感领域的前沿课题。
图 2. 红外波段冰的复折射率的实部（实线）和虚部（虚线）随波数的变化［1］
Fig. 2. Real part (solid line) and imaginary part (dashed line) of refractive index of ice as functions of wavenumber in infrared band[1]
复折射率的差异导致冰晶粒子散射特性的差异。
图 3. 远红外-中红外波段冰晶粒子和液态水滴粒子的散射特性［28-29］。（a）消光效率因子；（b）吸收效率因子；（c）散射效率因子；（d）单散射反照率
Fig. 3. Scattering properties of ice crystal particles and liquid water droplets in far-infrared and mid-infrared bands[28-29]. (a) Extinction efficiency; (b) absorption efficiency; (c) scattering efficiency; (d) single scattering albedo
从
综上所述，尽管远红外波段存在严重的大气吸收，但在部分“窗口”内，散射辐射对冰云特性仍有较高的敏感性。并且，远红外与中红外波段的散射效应在云参数反演方面将可能提供互补信息，从而进一步提高反演精度［30］。
3 远红外高光谱大气遥感仪器
目前，对于大气远红外辐射的高灵敏度探测技术主要分为测热探测技术和光电探测技术。其中，测热探测器主要包括基于热释电效应的热电探测器和针对大气辐射等分布式波源的微型测辐射热计。热电探测器在太赫兹至红外的宽波段范围内均具有较高的响应速度，为了提高探测灵敏度，采用DLaTGS（氘化L-丙氨酸硫酸三苷肽）、LiTaO3（钽酸锂）、PZT（锆酸盐）等聚合材料可进一步减小介电常数。微型测辐射热计比传统半导体测辐射热计的尺寸小，避免了热容量的限制，从而实现室温条件下大气远红外辐射的高灵敏度探测。同时，将微型测辐射热计扩展为微型测辐射热计阵列，可实现地球-大气分布式远红外谱的高效探测。这些优势使得测热探测技术成为当前星载大气远红外辐射高效探测的首选。而光电导探测器则主要基于半导体的本征激发或掺杂半导体的非本征激发效应。为了避免半导体的热致电离，该型探测器通常需要冷却至液氦的温度，这在一定程度上限制了其在星载探测仪器中的应用。
而目前对大气远红外辐射的高光谱测量技术主要包括棱镜、光栅以及干涉仪等技术。对于大气远红外辐射连续光谱，通过棱镜或衍射光栅产生色散，旋转色散元件实现频谱的选择，并将不同频谱能量连续地投射到探测狭缝上。但这种分频方法得到的总能量依赖于狭缝的面积和光学器件能接收的立体角。而干涉仪技术则是通过调整光程差测量干涉图样，再通过傅里叶变换获得频谱，其优势在于：相对于狭缝，干涉仪的大面积通光孔径具有明显的通量优势，增强了检测微弱信号的能力。然而，干涉仪动镜系统在空间卫星平台搭载时也必须考虑倾斜等误差。
上述内容对当前大气远红外高光谱测量仪器的关键技术进行了综述，下面主要从观测平台的角度对大气远红外高光谱仪器的发展进行简要介绍。值得注意的是，尽管通过对传统红外高光谱仪器（AERI）等探测系统进行改装也可实现中红外向远红外辐射测量的扩展，如I-BEST（interferometer for basic observations of emitted spectral radiance of the troposphere）在AERI的基础上增加高灵敏度非制冷热电探测器，可实现100~1600 cm-1范围内的红外辐射测量［31-32］，AERI‐ER（AERI extended range）［12］和E-AERI（extended-range AERI）［33］增加半导体碲化镉和半金属化合物碲化汞混合的光电导探测器，实现400 cm-1以上的红外辐射的测量，但本文重点在于对采用新技术体制实现远红外辐射的高光谱、高精度测量仪器的介绍，因此本文对I-BEST、AERI‐ER和E-AERI等仪器不做介绍。
3.1 地基大气远红外高光谱辐射探测仪
20世纪90年代，欧盟和欧洲航天局提出大气远红外辐射测量计划REFIR（radiation explorer in the far-infrared），目的是利用傅里叶变换光谱仪实现大气远红外辐射的高光谱测量，并为未来星载应用进行仪器布局设计和关键技术验证［34］。为此，REFIR-BB（REFIR-breadboard）、REFIR-PAD（REFIR-prototype for applications and development）和FIRMOS（far-infrared radiation mobile observation system）等原型机先后开展了观测实验。
REFIR-BB和REFIR-PAD分别为该计划设计的地基和球载（机载）原型机，主要指标如
表 1. REFIR-BB、REFIR-PAD和FIRMOS的主要指标参数
Table 1. Key parameters of REFIR-BB, REFIR-PAD, and FIRMOS
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图 4. REFIR-BB的光路示意图（M1~M5为定镜，P1~P3为偏振分束器，RTMA和RTMB分别为两条光路的角反射动镜）［37］
Fig. 4. Optical schematic of REFIR-BB (M1-M5 represent plane mirror, P1-P3 are polarizing beam splitters, and RTMA and RTMB are rooftop mirrors for arms A and B, respectively)[37]
REFIR-PAD在REFIR-BB的基础上，移除了45°偏振分束器（即
3.2 空基大气远红外高光谱辐射探测仪
由于低层大气水汽和二氧化碳的强吸收作用，对星载远红外大气辐射探测仪器进行综合观测实验验证一般需要在极其干燥的地基站点（高山站点、极地、沙漠等）或机载、球载平台上进行。
TAFTS（tropospheric airborne Fourier transform spectrometer）是目前唯一仍在运行的机载远红外高光谱辐射观测仪，其主要指标参数如
表 2. TAFTS和FIRST的主要指标参数
Table 2. Key parameters of TAFTS and FIRST
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可见，上述机载远红外高光谱仪器为了减小背景噪声，均需要主动制冷。尽管不符合卫星平台应用的需求，但飞行试验结果验证了宽带分束器和灵敏探测器技术的可行性。
3.3 星载大气远红外高光谱辐射探测计划
鉴于远红外辐射在地气系统辐射平衡与大气遥感中的重要作用，基于卫星平台实现大气上行远红外辐射的高光谱分辨率、高精度的观测一直是国际学术研究的前沿。为此，相关机构提出星载大气远红外高光谱辐射探测计划，如FORUM（ESA）、PREFIRE（NASA）等。
2019年，ESA提出FORUM（far-infrared outgoing radiation understanding and monitoring mission）［4］计划，旨在通过卫星平台以高光谱分辨率、高精度、高灵敏度测量大气上行远红外辐射，澄清驱动气候变化的关键因子及物理过程之间的联系［52］。该计划包括傅里叶变换光谱仪FSI（FORUM sounding instrument）以及热红外成像仪FEI（FORUM embedded imager），其中FSI拟基于Mach-Zehnder非偏振干涉测量方案，采用非制冷DLaTGS热电探测器，相关技术已在前文所述的地基REFIR-PAD和FIRMOS等仪器中得到验证，主要技术参数如
表 3. FORUM和PREFIRE计划的主要指标参数
Table 3. Key parameters of FORUM and PREFIRE
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图 5. FORUM和IASI-NG卫星地面轨迹和足印：FORUM FSI足印（红色）、FEI足印（黄色）和IASI-NG足印（蓝色）［4］
Fig. 5. Satellite ground tracks and footprints of FORUM and IASI-NG: FORUM FSI footprints (red), FEI footprints (yellow), and IASI-NG footprints (blue)[4]
PREFIRE（polar radiant energy in the far infrared experiment）计划的目的是通过大气上行远红外辐射定量反演地表发射率、温湿廓线、冰云宏微观参数，为极地气候变化及气候预测研究提供基础支撑［7，54］。通过在异步高倾角轨道上布置两个立方体卫星以几小时的时间间隔对极地地区进行扫描，实现与极轨卫星相似的观测范围［55］。每个卫星都携带相同的轻型低功率远红外高光谱仪（TIRS），采用64✕8像素的非制冷焦平面热电探测器，可测量4~54 μm的中红外和远红外辐射，主要技术参数如
4 远红外高光谱冰云遥感的反演方法
远红外辐射光谱含有丰富的地表、大气廓线和云的信息，尤其是在极地地区，低温和地表冰/雪导致基于星载中红外发射辐射特征的识别方法无法应用。而远红外波段冰晶粒子的散射作用为冰云的识别和反演提供了有效信息。因此，远红外高光谱辐射在极地地区云的宏微观参数、温湿廓线、地表发射率等特性的反演方面具有重要的应用价值。下面重点从云检测与相态识别、云微物理参数反演两个方面对远红外高光谱的应用进行介绍。
4.1 云检测与相态识别方法
目前，中红外到近红外波段已存在多种云检测与相态识别的算法，如累积判别分析、最小残差法、云掩模方法等，这些算法主要可以分为两类：基于特征参数（特定的光谱通道亮温或不同通道亮温差/比值等）的分类方法以及代价函数最优化的分类方法等，且这些算法均需要进行精确的光谱定标［3，56-57］。而远红外辐射包含了冰晶粒子的散射信息，因此其与中红外辐射的联合将可能进一步提升云检测及相态识别的准确性。
传统中红外-近红外云检测与相态识别算法一般采用8 μm、11 μm和12 μm或3.7 μm、11 μm和12 μm等通道的观测辐射［12，58］，但对于薄卷云、光学厚云及粒子尺度较大的云，该组合的识别效果较差。Rathke等［23］将远红外与中红外辐射光谱联合，利用北极地区的联合观测数据进行云相态识别，结果如
表 4. 不同仪器云相态识别的一致性比较［29］
Table 4. Comparison of cloud phase identification consistency between FTIR and other instruments[29]
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冰云在远红外波段同时具有吸收和散射效应，而吸收和散射效应均与温度有关，考虑到冬季极地对流层下层普遍存在近等温层和逆温层，因此星载大气远红外辐射在极地云相态识别和反演中将提供更多的信息。如Peterson等［29］提出的星载远红外-中红外高光谱云检测及相态识别算法，充分利用了449 cm-1和521 cm-1双通道亮温差的阈值进行相态识别。
图 6. 采用不同波段的通道正确识别冰云的概率［29］
Fig. 6. Probability of correctly identifying ice clouds using channels of different bands[29]
近年来，基于主成分分析、人工神经网络或支持向量机等方法的机器学习技术也已广泛应用于高分辨率卫星成像仪的云识别，通过建立云参数、大气廓线、地表等信息与光谱辐射的映射关系，实现高效的云相态识别。比较著名的方法是Maestri等［14］针对FORUM计划开发的基于主成分分析的云检测与相态识别算法（CIC）。该算法通过相似性指数或一致性指数描述光谱的相似程度，评估其与不同类别云的相似性，从而实现分类。模拟结果表明，该方法对云的识别性能参数从0.6增加到0.79，尤其是238~545 cm-1波段的光谱辐射能够提高几乎所有大气条件下的卷云探测性能。光学厚度小于0.06的薄卷云识别率也从25%增加至60%。此外，该方法成功应用于机载TAFTS和ARIES实际测量的远红外-红外光谱［59］以及地基REFIR-PAD实际测量的大气辐射光谱［60］，结果证明了远红外和中红外辐射光谱的联合提高了薄卷云的识别率，并且薄卷云的识别率随云层高度的增加而提高，对于云顶高度高于7 km的卷云，最小可探测光学厚度从0.2降低到0.09。
4.2 冰云微物理参数反演方法
冰云微物理参数主要包括冰晶粒子尺度、冰水含量（路径）、光学厚度、尺度谱等参量。红外高光谱全波段反演冰云微物理参数的经典方法包括最优估计理论、查找表、神经网络等。
目前，使用远红外高光谱遥感冰云微物理参数最为广泛的反演方法是Di Natale等［16］基于最优估计理论开发的云-大气参数协同反演（SACR）算法。该反演算法是为FORUM计划建立的，可反演参数包括冰云有效粒子直径、光学厚度、液态水云的有效粒子直径、大气温湿廓线等。随后，将该算法应用在地基REFIR-PAD、FIRMOS的实际观测［61-62］，基本流程为：首先利用CIC算法进行云检测与相态识别，然后根据激光雷达后向散射截面反演得到云顶、云底高度作为约束条件［63］，最后通过逐步迭代减小代价函数，使模拟光谱趋近于实测光谱。对于反演结果的验证，则主要通过与微雨雷达、激光雷达等主动遥感的反演结果相比较，以及开展远红外高光谱的闭合实验等手段进行。类似地，Palchetti等［30］、Maestri等［11］也基于最优估计的迭代方法实现远红外-中红外波段云微物理参数的反演。Libois等［13］则利用最优估计理论评估了远红外波段对传统中红外波段冰云微物理参数反演精度的增益，认为对于极地和对流层上层冰云，增加远红外通道可以将光学厚度、有效粒子直径和云顶高度反演值的不确定度降低50%以上。
不管是最优估计理论还是查找表、神经网络等反演方法，其中都涉及到自然界复杂形状的冰晶粒子散射特性的计算，这也是当前影响冰云参数反演精度的一个重要因素。随着光散射理论和计算电磁学技术的发展，研究人员已建立针对可见光到红外波段的不同尺度参数（最大直径与波长的比值）非球形冰晶散射特性的计算方法，如有限差分时域、几何光学积分方程、改进的几何光学等，在红外波段已开展多种粒子散射特性的验证与有云条件下的辐射传输闭合实验。而随着地基、机载高光谱干涉仪的发展，远红外波段不同形状粒子散射特性计算的验证也得以开展。
Di Natale等［64］分析了采用不同粒子形状的组合时星载远红外-中红外高光谱的敏感性。模拟时采用八棱柱状、子弹花瓣状、中空柱状、平板状4种形状各按25%的比例均匀混合，每种形状粒子的单散射特性采用Yang等［2］的计算结果。分别对热带、中纬度、极地地区的卷云特征进行计算，混合后的模拟光谱与采用单一粒子的光谱差值如
图 7. 混合粒子形状的模拟光谱与采用单一粒子的光谱差值，及其与FORUM和IASI-NG噪声的比较［64］。（a）~（c）中纬度地区的模拟结果；（d）~（f）热带地区的模拟结果；（g）~（i）极地的模拟结果
Fig. 7. Differences between upwelling radiances generated by using habit mixture (Mix) as for simulations and by using single habits, and comparison with FORUM noise and IASI-NG noise[64]. (a)-(c) Simulation results for mid-latitudes; (d)-(f) simulations for tropics; (g)-(i) simulations for polar scenarios
Bantges等［48］利用TAFTS、ARIES等机载高光谱干涉仪实际测量的远红外-中红外光谱评估了Baum等［28］计算的冰晶粒子光学散射特性数据库表征真实冰云光学特性的能力，结果表明该散射特性数据库在中红外波段的计算光谱与实测光谱较为一致，但在远红外波段与实测光谱存在一定的差距。辐射通量计算结果表明：当中红外波段的模拟光谱与实际光谱一致时，远红外波段的辐射通量差值达到1~2 W/m2；当远红外波段的模拟光谱与实际光谱较为一致时，中红外波段的辐射通量差值为3 W/m2。并且指出，冰晶粒子的尺度谱分布、冰的折射率随温度的变化、冰晶粒子的粗糙度等因素可能是影响冰晶粒子光学特性模拟的重要因素。
5 总结和展望
大气远红外高光谱辐射的高精度观测对于深入理解地气系统的辐射交换与辐射平衡具有重要意义。在大气遥感领域，该波段可与中红外波段协同提供冰云、对流层中上层水汽遥感的互补信息。尤其是对于极地地区冰云的宏微观物理参数，远红外高光谱辐射信息将进一步提升观测的准确性，对于冰云辐射强度的评估、提高冰云在气候模式中的代表性具有重要意义。
在大气远红外辐射的测量方面，非制冷高灵敏度探测器和高效宽带分束器技术仍是未来重点研究的方向，这是进一步降低仪器噪声水平、实现大气微量气体成分等微弱信号目标遥感的重要措施。目前，大气远红外辐射探测器一般采用热电探测器、微型测辐射热计，已实现室温条件下大气远红外辐射的高灵敏度探测，在多次的综合观测实验中进行了测试与验证，这也是未来星载载荷的发展方向。而光电导探测技术一般需要冷却至接近液氦的温度，这在一定程度上限制了其在星载仪器中的应用。对于大气远红外辐射的高光谱测量，干涉仪技术在检测微弱信号方面具有明显优势，但在卫星平台上需要考虑动镜倾斜等偏差。此外，集干涉仪和光栅技术于一体的空间外差光谱技术可在窄带光谱范围内实现超光谱分辨，其无动镜、超分辨、大通量、大视场和较小尺寸、质量等优势，也将是未来大气远红外辐射高光谱、高精度测量的重要发展方向。而我国在该方面的研究起步较晚，当前研究人员已在实验室设计实现了基于制冷测辐射热计、热释电探测器等技术的远红外辐射高灵敏度测量，对GaAs等材料在远红外波段的光学特性进行了分析，开展了远红外高光谱大气遥感应用的初步探索。为推进我国远红外大气遥感技术的发展，应进一步深化各部门单位及国际交流合作，发挥多学科交叉融合的优势，着重加强大气远红外高光谱遥感技术应用的基础及关键技术研究。
在远红外大气辐射传输与遥感方法研究方面，当前研究人员尽管已针对地基高光谱仪器开展了部分辐射传输闭合实验，但对于冰云条件下远红外-中红外全波段的光谱模拟尚需进一步的研究。尤其是对于自然界中复杂冰云粒子形状的有效表征问题，需要进一步结合不同尺度冰晶微物理观测资料开发远红外-中红外全波段的冰晶散射模型，以便更好地支撑远红外高光谱冰云遥感的发展。在反演方法方面，应用最优估计理论对全波段光谱进行拟合迭代，对于辐射传输模式的速度和精度都提出了较高的要求，在正向模拟的验证方法上仍需大量的研究工作。另外，多波段仪器的联合观测与应用，不仅可以实现探测场景的扩展，多波段遥感仪器的数据融合比对还可以在很大程度上提高云参数的探测精度，如结合亚毫米波、微波遥感将可能进一步提高光学厚云、液态水云、降水等参数的探测精度，并有可能实现云和大气温湿廓线参数的同时反演等。
综上所述，结合我国风云气象卫星的发展规划，开展大气远红外高光谱辐射的测量关键技术的攻关与验证，布局多波段大气遥感技术的综合观测，对于深入理解地气系统的辐射平衡、改进冰云辐射强迫效应的评估将发挥越来越重要的作用。
[1] Naud C, Russell J E, Harries J E. Remote sensing of cirrus cloud properties in the far infrared[J]. Proceedings of SPIE, 2001, 4168: 30-38.
[2] Yang P, Mlynczak M G, Wei H L, et al. Spectral signature of ice clouds in the far-infrared region: single-scattering calculations and radiative sensitivity study[J]. Journal of Geophysical Research: Atmospheres, 2003, 108(D18): 4569-4583.
[3] Harries J, Carli B, Rizzi R, et al. The far-infrared earth[J]. Reviews of Geophysics, 2008, 46(4): RG4004.
[4] Palchetti L, Brindley H, Bantges R, et al. FORUM: unique far-infrared satellite observations to better understand how earth radiates energy to space[J]. Bulletin of the American Meteorological Society, 2020, 101(12): E2030-E2046.
[5] Brindley H E, Harries J E. The impact of far I.R. absorption on clear sky greenhouse forcing: sensitivity studies at high spectral resolution[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 1998, 60(2): 151-180.
[6] Pan F, Huang X L. The spectral dimension of modeled relative humidity feedbacks in the CMIP5 experiments[J]. Journal of Climate, 2018, 31(24): 10021-10038.
[7] L'Ecuyer T S, Drouin B J, Anheuser J, et al. The polar radiant energy in the far infrared experiment: a new perspective on polar longwave energy exchanges[J]. Bulletin of the American Meteorological Society, 2021, 102(7): E1431-E1449.
[8] Turner D D, Merrelli A, Vimont D, et al. Impact of modifying the longwave water vapor continuum absorption model on community Earth system model simulations[J]. Journal of Geophysical Research: Atmospheres, 2012, 117(D4): D016440.
[9] Turner D D, Mlawer E J. The radiative heating in underexplored bands campaigns[J]. Bulletin of the American Meteorological Society, 2010, 91(7): 911-923.
[10] Merrelli A, Turner D D. Comparing information content of upwelling far-infrared and midinfrared radiance spectra for clear atmosphere profiling[J]. Journal of Atmospheric and Oceanic Technology, 2012, 29(4): 510-526.
[11] Maestri T, Arosio C, Rizzi R, et al. Antarctic ice cloud identification and properties using downwelling spectral radiance from 100 to 1, 400 cm-1[J]. Journal of Geophysical Research: Atmospheres, 2019, 124(8): 4761-4781.
[12] Turner D D, Ackerman S A, Baum B A, et al. Cloud phase determination using ground-based AERI observations at SHEBA[J]. Journal of Applied Meteorology, 2003, 42(6): 701-715.
[13] Libois Q, Blanchet J P. Added value of far-infrared radiometry for remote sensing of ice clouds[J]. Journal of Geophysical Research: Atmospheres, 2017, 122(12): 6541-6564.
[14] Maestri T, Cossich W, Sbrolli I. Cloud identification and classification from high spectral resolution data in the far infrared and mid-infrared[J]. Atmospheric Measurement Techniques, 2019, 12(7): 3521-3540.
[15] Saito M, Yang P, Huang X L, et al. Spaceborne middle- and far-infrared observations improving nighttime ice cloud property retrievals[J]. Geophysical Research Letters, 2020, 47(18): e87491.
[16] Di Natale G, Palchetti L, Bianchini G, et al. The two-stream δ-Eddington approximation to simulate the far infrared Earth spectrum for the simultaneous atmospheric and cloud retrieval[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2020, 246: 106927.
[17] Persky M J. A review of spaceborne infrared Fourier transform spectrometers for remote sensing[J]. Review of Scientific Instruments, 1995, 66(10): 4763-4797.
[18] Xie Y, Huang X L, Chen X H, et al. Joint use of far-infrared and mid-infrared observation for sounding retrievals: learning from the past for upcoming far-infrared missions[J]. Earth and Space Science, 2023, 10(3): EA002684.
[19] Sgheri L, Belotti C, Ben-Yami M, et al. The FORUM end-to-end simulator project: architecture and results[J]. Atmospheric Measurement Techniques, 2022, 15(3): 573-604.
[20] GoodyR M. Atmospheric radiation[M]. Oxford: Clarendon Press, 1964.
[21] 齐琳琳, 王晓丹, 吉微. 中远红外光谱区间的海区上空大气透过率特性分析[J]. 激光与光电子学进展, 2022, 59(1): 0101002.
[22] GoodyR M, YungY L. Atmospheric radiation: theoretical basis[M]. 2nd ed. New York: Oxford University Press, 1996: 67-124.
[23] Rathke C, Fischer J, Neshyba S, et al. Improving IR cloud phase determination with 20 microns spectral observations[J]. Geophysical Research Letters, 2002, 29(8): 1209-1213.
[24] Green P D, Newman S M, Beeby R J, et al. Recent advances in measurement of the water vapour continuum in the far-infrared spectral region[J]. Philosophical Transactions Series A, Mathematical, Physical, and Engineering Sciences, 2012, 370(1968): 2637-2655.
[25] IPCC. Special report on the ocean and cryosphere in a changing climate[M]. Cambridge: Cambridge University Press, 2019: 755.
[26] Warren S G. Optical constants of ice from the ultraviolet to the microwave[J]. Applied Optics, 1984, 23(8): 1206-1225.
[27] Warren S G, Brandt R E. Optical constants of ice from the ultraviolet to the microwave: a revised compilation[J]. Journal of Geophysical Research: Atmospheres, 2008, 113(D14): D14220.
[28] Baum B A, Yang P, Heymsfield A J, et al. Ice cloud single-scattering property models with the full phase matrix at wavelengths from 0.2 to 100 µm[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2014, 146: 123-139.
[29] Peterson C A, Huang X L, Chen X H, et al. Synergistic use of far- and mid-infrared spectral radiances for satellite-based detection of polar ice clouds over ocean[J]. Journal of Geophysical Research: Atmospheres, 2022, 127(9): JD035733.
[30] Palchetti L, Di Natale G, Bianchini G. Remote sensing of cirrus cloud microphysical properties using spectral measurements over the full range of their thermal emission[J]. Journal of Geophysical Research: Atmospheres, 2016, 121(18): 10804-10819.
[31] Serio C, Esposito F, Masiello G, et al. Interferometer for ground-based observations of emitted spectral radiance from the troposphere: evaluation and retrieval performance[J]. Applied Optics, 2008, 47(21): 3909-3919.
[32] Bhawar R, Bianchini G, Bozzo A, et al. Spectrally resolved observations of atmospheric emitted radiance in the H2O rotation band[J]. Geophysical Research Letters, 2008, 35(4): GL032207.
[33] Sussmann R, Reichert A, Rettinger M. The Zugspitze radiative closure experiment for quantifying water vapor absorption over the terrestrial and solar infrared: part 1: setup, uncertainty analysis, and assessment of far-infrared water vapor continuum[J]. Atmospheric Chemistry and Physics, 2016, 16(18): 11649-11669.
[34] Palchetti L, Bianchini G, Pellegrini M, et al. Radiometric performances of the Fourier transform spectrometer for the Radiation Explorer in the Far-Infrared (REFIR) space mission[J]. Proceedings of SPIE, 2004, 5570: 433-444.
[35] Palchetti L, Bianchini G, Castagnoli F, et al. Breadboard of a Fourier-transform spectrometer for the Radiation Explorer in the Far Infrared atmospheric mission[J]. Applied Optics, 2005, 44(14): 2870-2878.
[36] Esposito F, Grieco G, Leone L, et al. REFIR/BB initial observations in the water vapour rotational band: results from a field campaign[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2007, 103(3): 524-535.
[37] Carli B, Barbis A, Harries J E, et al. Design of an efficient broadband far-infrared Fourier-transform spectrometer[J]. Applied Optics, 1999, 38(18): 3945-3950.
[38] Bianchini G, Palchetti L, Carli B. A wide-band nadir-sounding spectroradiometer for the characterization of the Earths outgoing long-wave radiation[J]. Proceedings of SPIE, 2006, 6361: 63610A.
[39] Palchetti L, Belotti C, Bianchini G, et al. Technical note: first spectral measurement of the Earths upwelling emission using an uncooled wideband Fourier transform spectrometer[J]. Atmospheric Chemistry and Physics, 2006, 6(12): 5025-5030.
[40] Bianchini G, Palchetti L. Technical note: REFIR-PAD level 1 data analysis and performance characterization[J]. Atmospheric Chemistry and Physics, 2008, 8(14): 3817-3826.
[41] Bianchini G, Palchetti L, Muscari G, et al. Water vapor sounding with the far infrared REFIR-PAD spectroradiometer from a high-altitude ground-based station during the ECOWAR campaign[J]. Journal of Geophysical Research: Atmospheres, 2011, 116(D2): D02310.
[42] Maestri T, Rizzi R, Tosi E, et al. Analysis of cirrus cloud spectral signatures in the far infrared[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2014, 141: 49-64.
[43] Rizzi R, Arosio C, Maestri T, et al. One year of downwelling spectral radiance measurements from 100 to 1400 cm-1 at Dome Concordia: results in clear conditions[J]. Journal of Geophysical Research: Atmospheres, 2016, 121(18): 10937-10953.
[44] Palchetti L, Barucci M, Belotti C, et al. Observations of the downwelling far-infrared atmospheric emission at the Zugspitze observatory[J]. Earth System Science Data, 2021, 13(9): 4303-4312.
[45] Belotti C, Barbara F, Barucci M, et al. The Far-Infrared Radiation Mobile Observation System (FIRMOS) for spectral characterization of the atmospheric emission[J]. Atmospheric Measurement Techniques, 2023, 16(10): 2511-2529.
[46] Canas T A, Murray J E, Harries J E. Tropospheric airborne Fourier transform spectrometer (TAFTS)[J]. Proceedings of SPIE, 1997, 3220: 91-102.
[47] Warwick L, Brindley H, Di Roma A, et al. Retrieval of tropospheric water vapor from airborne far-infrared measurements: a case study[J]. Journal of Geophysical Research: Atmospheres, 2022, 127(7): JD034229.
[48] Bantges R J, Brindley H E, Murray J E, et al. A test of the ability of current bulk optical models to represent the radiative properties of cirrus cloud across the mid- and far-infrared[J]. Atmospheric Chemistry & Physics, 2020, 20(21): 12889-12903.
[49] Bellisario C, Brindley H E, Murray J E, et al. Retrievals of the far infrared surface emissivity over the Greenland Plateau using the tropospheric airborne Fourier transform spectrometer (TAFTS)[J]. Journal of Geophysical Research: Atmospheres, 2017, 122(22): 12152-12166.
[50] Mlynczak M G, Johnson D G, Latvakoski H, et al. First light from the Far-Infrared Spectroscopy of the Troposphere (FIRST) instrument[J]. Geophysical Research Letters, 2006, 33(7): GL025114.
[51] Mlynczak M G, Cageao R P, Mast J C, et al. Observations of downwelling far-infrared emission at Table Mountain California made by the FIRST instrument[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2016, 170: 90-105.
[52] Ridolfi M, Del Bianco S, Di Roma A, et al. FORUM earth explorer 9: characteristics of level 2 products and synergies with IASI-NG[J]. Remote Sensing, 2020, 12(9): 1496-1515.
[53] Ben-Yami M, Oetjen H, Brindley H, et al. Emissivity retrievals with FORUMs end-to-end simulator: challenges and recommendations[J]. Atmospheric Measurement Techniques, 2022, 15(6): 1755-1777.
[54] Xie Y, Huang X L, Chen X H, et al. Retrieval of surface spectral emissivity in polar regions based on the optimal estimation method[J]. Journal of Geophysical Research: Atmospheres, 2022, 127(5): JD035677.
[55] Kahn B H, Drouin B J, L'Ecuyer T S. Assessment of sampling sufficiency for low-cost satellite missions: application to PREFIRE[J]. Journal of Atmospheric and Oceanic Technology, 2020, 37(12): 2283-2298.
[56] 逄淑林, 孙林, 杜永明, 等. 全谱段光谱成像仪遥感影像云检测算法[J]. 激光与光电子学进展, 2023, 60(22): 2228003.
[57] 尚华哲, 胡斯勒图, 李明, 等. 基于被动遥感卫星可见至红外通道观测的云特性遥感[J]. 光学学报, 2022, 42(6): 0600003.
[58] Key J R, Intrieri J M. Cloud particle phase determination with the AVHRR[J]. Journal of Applied Meteorology, 2000, 39(10): 1797-1804.
[59] Magurno D, Cossich W, Maestri T, et al. Cirrus cloud identification from airborne far-infrared and mid-infrared spectra[J]. Remote Sensing, 2020, 12(13): 2097.
[60] Cossich W, Maestri T, Magurno D, et al. Ice and mixed-phase cloud statistics on the Antarctic Plateau[J]. Atmospheric Chemistry and Physics, 2021, 21(18): 13811-13833.
[61] Di Natale G, Turner D D, Bianchini G, et al. Consistency test of precipitating ice cloud retrieval properties obtained from the observations of different instruments operating at Dome C (Antarctica)[J]. Atmospheric Measurement Techniques, 2022, 15(24): 7235-7258.
[62] Di Natale G, Barucci M, Belotti C, et al. Comparison of mid-latitude single- and mixed-phase cloud optical depth from co-located infrared spectrometer and backscatter lidar measurements[J]. Atmospheric Measurement Techniques, 2021, 14(10): 6749-6758.
[63] Di Natale G, Bianchini G, Del Guasta M, et al. Characterization of the far infrared properties and radiative forcing of Antarctic ice and water clouds exploiting the spectrometer-LiDAR synergy[J]. Remote Sensing, 2020, 12(21): 3574-3595.
[64] Di Natale G, Palchetti L. Sensitivity studies toward the retrieval of ice crystal habit distributions inside cirrus clouds from upwelling far infrared spectral radiance observations[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2022, 282: 108120.
Article Outline
刘磊, 李书磊, 胡帅, 曾庆伟. 远红外高光谱遥感技术及其冰云遥感应用（特邀）[J]. 光学学报, 2024, 44(6): 0600002. Lei Liu, Shulei Li, Shuai Hu, Qingwei Zeng. Hyperspectral Remote Sensing Technology of Far-Infrared Radiation and Its Application in Ice Cloud Retrievals (Invited)[J]. Acta Optica Sinica, 2024, 44(6): 0600002.
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