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Experimental and modeled UV erythemal irradiance under overcast conditions: The role of cloud optical depth

机译:阴天条件下的实验和建模UV红斑辐照度:云光学深度的作用

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This paper evaluates the relationship between the cloud modification factor (CMF) in the ultraviolet erythemal range and the cloud optical depth (COD) retrieved from the Aerosol Robotic Network (AERONET) cloud mode algorithm under overcast cloudy conditions (confirmed with sky images) at Granada, Spain, mainly for non-precipitating, overcast and relatively homogenous water clouds. Empirical CMF showed a clear exponential dependence on experimental COD values, decreasing approximately from 0.7 for COD Combining double low line 10 to 0.25 for COD Combining double low line 50. In addition, these COD measurements were used as input in the LibRadtran radiative transfer code allowing the simulation of CMF values for the selected overcast cases. The modeled CMF exhibited a dependence on COD similar to the empirical CMF, but modeled values present a strong underestimation with respect to the empirical factors (mean bias of 22%). To explain this high bias, an exhaustive comparison between modeled and experimental UV erythemal irradiance (UVER) data was performed. The comparison revealed that the radiative transfer simulations were 8% higher than the observations for clear-sky conditions. The rest of the bias (~14%) may be attributed to the substantial underestimation of modeled UVER with respect to experimental UVER under overcast conditions, although the correlation between both dataset was high (R~2 ~ 0.93). A sensitive test showed that the main reason responsible for that underestimation is the experimental AERONET COD used as input in the simulations, which has been retrieved from zenith radiances in the visible range. In this sense, effective COD in the erythemal interval were derived from an iteration procedure based on searching the best match between modeled and experimental UVER values for each selected overcast case. These effective COD values were smaller than AERONET COD data in about 80% of the overcast cases with a mean relative difference of 22%.
机译:本文评估了格拉纳达在多云阴天条件下(经天空图像确认)紫外线红斑范围内的云修正因子(CMF)与从气溶胶机器人网络(AERONET)云模式算法检索到的云光学深度(COD)之间的关系。 ,西班牙,主要用于非降水,阴天和相对均质的水云。经验CMF对实验COD值显示出明显的指数依赖性,从双低线10组合的COD的0.7降低到双低线50组合的COD的0.25左右。此外,这些COD测量值用作LibRadtran辐射转移代码的输入,针对选定的阴暗案例的CMF值的模拟。建模的CMF与经验CMF相似,显示出对COD的依赖性,但是建模值相对于经验因素表现出强烈的低估(平均偏差为22%)。为了解释这种高偏差,在模型和实验的紫外线红斑辐照度(UVER)数据之间进行了详尽的比较。比较表明,辐射传输模拟比晴朗天空条件下的观测值高8%。其余的偏差(〜14%)可能是由于建模的UVER相对于阴天条件下的实验UVER的低估所致,尽管两个数据集之间的相关性很高(R〜2〜0.93)。一项敏感的测试表明,造成这一低估的主要原因是在模拟中用作实验输入的实验性AERONET COD,该值已从可见范围内的天顶辐射中获取。从这个意义上说,红斑间隔中的有效COD是从迭代过程中得出的,该迭代过程基于针对每个选定的阴暗情况搜索建模UVER值与实验UVER值之间的最佳匹配。在大约80%的阴暗情况下,这些有效的COD值小于AERONET COD数据,平均相对差为22%。

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