利用MFRSR反演西北混合相和沙尘云光学及物理特性的研究
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摘要
云作为地球辐射收支系统的重要调节器,在大气能量循环、水汽循环甚至在地球气候系统中扮演着非常关键的角色。云对地表和大气层顶的辐射通量以及大气中辐射能量再分布的影响,主要取决于云量、云的相态和光学厚度等信息。我国西北地区作为干旱半干旱区典型气候特征的代表区,混合相云和沙尘云成为该地区一种非常普遍的云的存在类型,增加了该地区云的光学和物理特性研究的复杂性,因此建立相关的反演算法将显得尤为重要。本论文基于地基遥感仪器多滤波旋转影带辐射仪(MFRSR)独特的观测几何和准确的大气透射观测,分别发展了薄混合相云、沙尘云光学特性的反演算法,也提出了精确估计天空云量的光谱透射率比值方法。通过理论上的敏感性试验以及兰州大学半干旱气候与环境观测站(SACOL)和中美沙尘暴联合观测实验移动观测站(张掖和景泰站)实时观测资料的评估和验证,取得了令人满意的结果。
我们利用MFRSR的直接辐射和总辐射两个瞬时光谱观测,在辐射闭合的假定下,根据水云和冰云散射相函数的不同所引起的直接辐射及总辐射的差异,推断冰云和水云光学厚度混合率并识别云的热动力相态信息,继而精确估计薄混合相云的光学厚度。对该方法而言,1%的辐射观测误差所引起的总云光学厚度和混合率反演最大不确定性分别为8.4%和0.107;根据前向散射模拟以及SACOL、张掖和景泰站实时观测资料的评估和验证发现,基于云相识别的薄混合相云反演算法使直接辐射和总辐射反演的云光学厚度高度一致:两者之间的斜率为1.084,相关系数为0.96,均方根误差为0.679;因云粒子有效半径的差异所引起的太阳直接辐射和总辐射反演的云光学厚度的最大偏差(相对误差)分别为0.21(7.9%)和0.30(9.4%)。因此,该反演算法不仅能够精确反演薄混合相云的光学厚度,而且也提供了多云条件下薄混合云中独一无二的水云和冰云光学厚度混合率。
另外,本文也利用MFRSR光谱辐射观测成功提出了进行云量估计的透射率比值方法(Ratio Method)。该方法主要基于云和晴天气溶胶的光谱特征来区分天空云分数(即云量)。敏感性试验和实际观测表明,所选择波段的透射比对太阳天顶角和主要的大气气体吸收是不敏感的。由于该算法中具有当地云天和晴天背景的判断,因此比值方法的反演则不依赖于仪器的绝对校正,与云和气溶胶光学特性的变化仅表现出微弱的关系,本质上减小了反演的不确定性,且其不确定性小于10%。由于窄带光谱辐射计观测目前非常广泛,这个简单的比值方法将本质上增强云量观测的能力。
基于非球形沙尘气溶胶的散射特性,本文还发展了一种能够反演沙尘云中沙尘气溶胶光学厚度的方法。该方法通过结合地基遥感仪器多滤波旋转影带辐射计(MFRSR)的透射观测和雷达反演的云参数,根据沙尘气溶胶和云滴吸收特性的差异,区分和估计了沙尘及云的光学特性。敏感性试验表明,该方法对云特性的反演误差是不敏感的,并且薄沙尘云中沙尘和总光学厚度的最大绝对偏差仅仅只有0.056和0.1,厚沙尘云的反演误差则主要依赖于总沙尘云特性的激光雪达反演误差。该方法的发展为精确估计沙尘云辐射强迫和评估沙尘云的直接和间接辐射效应奠定了基础。
Clouds are an important modulator of the energy budget of the planet and play a critical role in the atmospheric energy cycle, water vapor cycle as well as earth climate system. The impact of clouds on the radiative fluxes, both at the surface and top of the atmosphere as well as the redistribution of the radiant energy in the atmosphere, depends on cloud cover, thermodynamic phase and optical depth. The northwestern China is a typical arid and semi-arid climatic characteristic representative area and there are some special cloud type, such as mixed-phase clouds and dusty clouds. The existence of these clouds increases the complexity and uncertainty of cloud optical properties retrieval. Thus it becomes more and more important to build up the retrieval method for mixed-phase cloud and dusty cloud. Based on the particular observation geometry of Multifilter Rotating Shadowband Radiometer (MFRSR) and accurate transmittance measurements, in this study, we have developed a method for retrieving optical properties of optically thin mixed-phase cloud and dusty cloud, respectively. Additionally, a ratio method for accurately estimating fractional sky cover from spectral transmittance measurements has also been developed. The theoretical sensitivity studies and validation and evaluation from measurements at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site, Zhangye and Jingtai mobile facility during China-US joint dusty storms observation achieve satisfactory results.
On the basis of the simultaneous measurements of direct and total radiation from MFRSR, we allow partitions of direct-beam and total radiation determined by different thermodynamic phase. Under the assumption of radiation closure, we further infer mixed ratio of cloud water and ice for optical thin clouds and identify cloud thermodynamic phase, and thus accurately estimate optical depths of optically thin mixed-phase cloud. For the new retrieval method, 1% measurement error will result in maximum uncertainties of 8.4% and 0.107 in retrieved total optical depths and mixed ratio, respectively. According to validation and evaluation using forward simulations and in situ measurements at SACOL, Zhangye and Jingtai sites, the new retrieval method achieves the high consistency of retrieved cloud optical depth from direct-beam and total radiation: the slope of 1.084 between the two with correlation coefficient of 0.96 and RMS of 0.679. The maximum biases (relative errors) of cloud optical depths within the range of effective radius of clouds are 0.21 (7.9%) and 0.30 (9.4%). Therefore, the retrieval method provides not only accuracy retrievals of cloud optical depths but also unique mixed ratio of cloud water and ice for optically thin clouds under overcast conditions.
A ratio method for estimating fractional sky cover from spectral measurements has been developed. The spectral characteristics of clouds and clear-sky aerosols are utilized to partition sky fraction (sky cover). As illustrated in our sensitivity study and demonstrated in real measurements, the transmittance ratio at selected wavelengths is insensitive to solar zenith angle and major atmospheric gaseous absorption. With a localized baseline procedure, retrievals of this ratio method are independent of absolute calibration and weakly sensitive to changes in cloud and aerosol optical properties. Therefore this method substantially reduces the retrieval uncertainty. The uncertainty of this method, estimated through the sensitivity study and intercomparison, is less than 10%. With globally deployed narrowband radiometers, this simple ratio method can substantially enhance the current capability for monitoring fractional sky cover.
Based on the scattering properties of nonspherical dust aerosol, a new approach is also developed for retrieving dust aerosol optical depths of dusty clouds. The new method is based on transmittance measurements from surface-based instruments multi-filter rotating shadowband radiometer (MFRSR) and cloud parameters from lidar measurements. It uses the difference of absorption between dust aerosols and water droplets for distinguishing and estimating the optical properties of dusts and clouds, respectively. As illustrated in sensitivity study, this new retrieval method is not sensitive to the retrieval error of cloud properties and the maximum absolute deviations of dust aerosol and total optical depths for thin dusty cloud retrieval algorithm are only 0.056 and 0.1, respectively, for given possible uncertainties. The retrieval error for thick dusty cloud mainly depends on lidar-based total dusty cloud properties. The retrieval method lays the foundation on accurately estimating dusty cloud radiative forcing and evaluating direct and indirect effect of dust aerosols on cloud.
我们利用MFRSR的直接辐射和总辐射两个瞬时光谱观测,在辐射闭合的假定下,根据水云和冰云散射相函数的不同所引起的直接辐射及总辐射的差异,推断冰云和水云光学厚度混合率并识别云的热动力相态信息,继而精确估计薄混合相云的光学厚度。对该方法而言,1%的辐射观测误差所引起的总云光学厚度和混合率反演最大不确定性分别为8.4%和0.107;根据前向散射模拟以及SACOL、张掖和景泰站实时观测资料的评估和验证发现,基于云相识别的薄混合相云反演算法使直接辐射和总辐射反演的云光学厚度高度一致:两者之间的斜率为1.084,相关系数为0.96,均方根误差为0.679;因云粒子有效半径的差异所引起的太阳直接辐射和总辐射反演的云光学厚度的最大偏差(相对误差)分别为0.21(7.9%)和0.30(9.4%)。因此,该反演算法不仅能够精确反演薄混合相云的光学厚度,而且也提供了多云条件下薄混合云中独一无二的水云和冰云光学厚度混合率。
另外,本文也利用MFRSR光谱辐射观测成功提出了进行云量估计的透射率比值方法(Ratio Method)。该方法主要基于云和晴天气溶胶的光谱特征来区分天空云分数(即云量)。敏感性试验和实际观测表明,所选择波段的透射比对太阳天顶角和主要的大气气体吸收是不敏感的。由于该算法中具有当地云天和晴天背景的判断,因此比值方法的反演则不依赖于仪器的绝对校正,与云和气溶胶光学特性的变化仅表现出微弱的关系,本质上减小了反演的不确定性,且其不确定性小于10%。由于窄带光谱辐射计观测目前非常广泛,这个简单的比值方法将本质上增强云量观测的能力。
基于非球形沙尘气溶胶的散射特性,本文还发展了一种能够反演沙尘云中沙尘气溶胶光学厚度的方法。该方法通过结合地基遥感仪器多滤波旋转影带辐射计(MFRSR)的透射观测和雷达反演的云参数,根据沙尘气溶胶和云滴吸收特性的差异,区分和估计了沙尘及云的光学特性。敏感性试验表明,该方法对云特性的反演误差是不敏感的,并且薄沙尘云中沙尘和总光学厚度的最大绝对偏差仅仅只有0.056和0.1,厚沙尘云的反演误差则主要依赖于总沙尘云特性的激光雪达反演误差。该方法的发展为精确估计沙尘云辐射强迫和评估沙尘云的直接和间接辐射效应奠定了基础。
Clouds are an important modulator of the energy budget of the planet and play a critical role in the atmospheric energy cycle, water vapor cycle as well as earth climate system. The impact of clouds on the radiative fluxes, both at the surface and top of the atmosphere as well as the redistribution of the radiant energy in the atmosphere, depends on cloud cover, thermodynamic phase and optical depth. The northwestern China is a typical arid and semi-arid climatic characteristic representative area and there are some special cloud type, such as mixed-phase clouds and dusty clouds. The existence of these clouds increases the complexity and uncertainty of cloud optical properties retrieval. Thus it becomes more and more important to build up the retrieval method for mixed-phase cloud and dusty cloud. Based on the particular observation geometry of Multifilter Rotating Shadowband Radiometer (MFRSR) and accurate transmittance measurements, in this study, we have developed a method for retrieving optical properties of optically thin mixed-phase cloud and dusty cloud, respectively. Additionally, a ratio method for accurately estimating fractional sky cover from spectral transmittance measurements has also been developed. The theoretical sensitivity studies and validation and evaluation from measurements at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site, Zhangye and Jingtai mobile facility during China-US joint dusty storms observation achieve satisfactory results.
On the basis of the simultaneous measurements of direct and total radiation from MFRSR, we allow partitions of direct-beam and total radiation determined by different thermodynamic phase. Under the assumption of radiation closure, we further infer mixed ratio of cloud water and ice for optical thin clouds and identify cloud thermodynamic phase, and thus accurately estimate optical depths of optically thin mixed-phase cloud. For the new retrieval method, 1% measurement error will result in maximum uncertainties of 8.4% and 0.107 in retrieved total optical depths and mixed ratio, respectively. According to validation and evaluation using forward simulations and in situ measurements at SACOL, Zhangye and Jingtai sites, the new retrieval method achieves the high consistency of retrieved cloud optical depth from direct-beam and total radiation: the slope of 1.084 between the two with correlation coefficient of 0.96 and RMS of 0.679. The maximum biases (relative errors) of cloud optical depths within the range of effective radius of clouds are 0.21 (7.9%) and 0.30 (9.4%). Therefore, the retrieval method provides not only accuracy retrievals of cloud optical depths but also unique mixed ratio of cloud water and ice for optically thin clouds under overcast conditions.
A ratio method for estimating fractional sky cover from spectral measurements has been developed. The spectral characteristics of clouds and clear-sky aerosols are utilized to partition sky fraction (sky cover). As illustrated in our sensitivity study and demonstrated in real measurements, the transmittance ratio at selected wavelengths is insensitive to solar zenith angle and major atmospheric gaseous absorption. With a localized baseline procedure, retrievals of this ratio method are independent of absolute calibration and weakly sensitive to changes in cloud and aerosol optical properties. Therefore this method substantially reduces the retrieval uncertainty. The uncertainty of this method, estimated through the sensitivity study and intercomparison, is less than 10%. With globally deployed narrowband radiometers, this simple ratio method can substantially enhance the current capability for monitoring fractional sky cover.
Based on the scattering properties of nonspherical dust aerosol, a new approach is also developed for retrieving dust aerosol optical depths of dusty clouds. The new method is based on transmittance measurements from surface-based instruments multi-filter rotating shadowband radiometer (MFRSR) and cloud parameters from lidar measurements. It uses the difference of absorption between dust aerosols and water droplets for distinguishing and estimating the optical properties of dusts and clouds, respectively. As illustrated in sensitivity study, this new retrieval method is not sensitive to the retrieval error of cloud properties and the maximum absolute deviations of dust aerosol and total optical depths for thin dusty cloud retrieval algorithm are only 0.056 and 0.1, respectively, for given possible uncertainties. The retrieval error for thick dusty cloud mainly depends on lidar-based total dusty cloud properties. The retrieval method lays the foundation on accurately estimating dusty cloud radiative forcing and evaluating direct and indirect effect of dust aerosols on cloud.
引文
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