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Radiative consequences of low-temperature infrared refractive indices for supercooled water clouds

机译:低温红外折射率对过冷水云的辐射后果

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摘要

Simulations of cloud radiative properties for climate modeling and remote sensing rely on accurate knowledge of the complex refractive index (CRI) of water. Although conventional algorithms employ a temperature-independent assumption (TIA), recent infrared measurements of supercooled water have demonstrated that the CRI becomes increasingly ice-like at lower temperatures. Here, we assess biases that result from ignoring this temperature dependence. We show that TIA-based cloud retrievals introduce spurious ice into pure, supercooled clouds, or underestimate cloud optical thickness and droplet size. TIA-based downwelling radiative fluxes are lower than those for the temperature-dependent CRI by as much as 1.7 W m (in cold regions), while top-of-atmosphere fluxes are higher by as much as 3.4 W m (in warm regions). Proper accounting of the temperature dependence of the CRI, therefore, leads to significantly greater local greenhouse warming due to supercooled clouds than previously predicted. The current experimental uncertainty in the CRI at low temperatures must be reduced to account for supercooled clouds properly in both climate models and cloud-property retrievals.
机译:用于气候建模和遥感的云辐射特性模拟依赖于对水的复折射率(CRI)的准确了解。尽管常规算法采用与温度无关的假设(TIA),但最近对过冷水进行的红外测量表明,CRI在较低温度下变得越来越像冰。在这里,我们评估了由于忽略这种温度依赖性而导致的偏差。我们表明,基于TIA的云取回将伪冰引入纯净的过冷云中,或者低估了云的光学厚度和液滴大小。基于TIA的下流辐射通量比温度相关的CRI低1.7 W m(在寒冷地区),而大气顶通量则高达3.4 W m(在温暖地区) 。因此,正确计算CRI的温度依赖性会导致由于过冷云而导致的局部温室变暖比以前预计的要大得多。必须降低当前CRI在低温下的实验不确定性,以在气候模型和云属性检索中适当地考虑过冷云。

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