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首页> 外文期刊>Atmospheric Measurement Techniques Discussions >Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing
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Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

机译:利用机载光谱太阳遥感联合检索北极液态水云和地表雪性质

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pstrongAbstract./strong The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness i??/i and cloud droplet effective radius ir/isubeff,a??C/sub may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size ir/isubeff,a??S/sub. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of i??/i and ir/isubeff,a??C/sub for liquid water clouds. In general, the impact of uncertainties of ir/isubeff,a??S/sub is largest for small snow grain sizes. While the uncertainties of retrieved i??/i are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved ir/isubeff,a??C/sub increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83span class="thinspace"/span% for i??/i and 62span class="thinspace"/span% for ir/isubeff,a??C/sub. brbr In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (i??/i, ir/isubeff,a??C/sub, ir/isubeff,a??S/sub) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths i??/isub1/suba??=a??1040span class="thinspace"/spannm (sensitive to ir/isubeff,a??S/sub), i??/isub2/suba??=a??1650span class="thinspace"/spannm (sensitive to i??/i), and i??/isub3/suba??=a??2100span class="thinspace"/spannm (sensitive to ir/isubeff,a??C/sub) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of i??/i, ir/isubeff,a??C/sub, and ir/isubeff,a??S/sub show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of i??/i, and low ir/isubeff,a??S/sub but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated./p.
机译:> >摘要。被动反射遥感在高反射地面上的云层特性具有挑战性,这主要是由于云层反射率与下层表面(海冰和雪)的反射率之间的对比度较低。假设光谱的不确定性可能会导致检索到的云光学厚度Δε和云滴有效半径 r eff,aΔC的不确定性地表反照率,主要由通常未知的有效雪粒径 r eff,a ?? S 决定。因此,第一步,对于常规的双谱检索技术 ?? 和 r eff,a ??,对假定雪粒大小的影响进行了系统地量化。 C 用于液态水云。通常,对于小雪粒, r eff,a ?? S 的不确定性影响最大。虽然检索到的 ?? 的不确定性与云的光学厚度和太阳天顶角无关,但检索到的 r eff,a ?? C 对于光学上稀薄的云层和太阳较高时,增加。对于 ?? 和62 class =“ thinspace”> % >%表示 r eff,a ?? C 。 在论文的第二部分中,提出了一种检索方法,该方法可以同时导出所有三个参数( ?? , r eff,a? ?C , r eff,a ?? S ),因此可以解释雪粒大小的变化。在三种波长 ?? 1 a ?? = a ?? 1040 class =“ thinspace”> nm处光谱云反射率的比率(敏感到 r eff,a ?? S ), ?? 2 a ?? = a ?? 1650 < span class =“ thinspace”> nm(对 ?? 敏感)和 ?? 3 a ?? = a?在三光谱检索算法中组合了2100 class =“ thinspace”> nm(对 r eff,a ?? C 敏感)。在一项可行性研究中,使用光谱模块化机载辐射测量系统(SMART)在北极混合相云中冰的垂直分布研究活动(VERDI,2012年4月/ 5月)中收集的光谱云反射率测量值来测试检索程序。分析了加拿大波弗特海上空的两个观测案例,一个是积雪覆盖的海冰,另一个是积雪覆盖的海冰边缘。 ?? , r eff,a ?? C 和 r eff的检索值, a ?? S 显示了在被冰雪覆盖的海冰和开阔水域中云特性的连续过渡,并且与基于卫星数据的估计一致。结果表明,对于 ?? 的高值和 r eff,a ?? S 的低值,三光谱检索的不确定性增加,但是可以估算覆盖云区域的有效雪粒大小。

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