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Potential and limitations of space-based methods for the retrieval of surface UV-B daily doses: A numerical study

机译:基于空间的方法获取表面UV-B日剂量的潜力和局限性:一项数值研究

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摘要

For a typical space-borne algorithm for the estimation of surface UV-B daily doses, the implications of a limited temporal sampling of cloud properties and of the neglect of three-dimensional radiative effects are addressed. By means of six synthetic diurnal cloud cycles, different temporal samplings of cloud properties have been investigated, while surface and atmospheric properties have been kept constant. The results have been compared with benchmark calculations of the daily doses using a 15 min time step. The neglect of the horizontal photon transport imposes limitations to the estimation of daily doses since it leads to statistical uncertainties up to 25% and biases ranging from 3% to 9%. Additionally, when a reduced temporal sampling is used, maximum uncertainties increase up to 85% when probing the cloud field only every 4 hours. Even in this case, however, 25 40% of the daily doses in the model domain have an accuracy between 20% and +20%. The time around noon turns out to be of crucial importance for a precise estimation of UV daily doses. Therefore usually a limited number of cloud probes around noon is particularly efficient, although in case of high temporal and spatial cloud variability throughout the day three cloud probes can still be too few to prevent the occurrence of large (>80%) deviations. Finally, by spatial averaging, a large improvement of the agreement between reference values and daily doses computed with a given time sampling can be achieved.
机译:对于用于估计表面UV-B日剂量的典型星载算法,解决了云特性有限的时间采样和三维辐射效应的忽略的影响。通过六个合成的昼间云周期,研究了云特性的不同时间采样,同时保持了表面和大气特性不变。将结果与使用15分钟时间步长的每日剂量基准计算进行了比较。忽略水平光子传输会限制每日剂量的估计,因为这会导致统计不确定性高达25%,偏差范围为3%至9%。此外,当使用减少的时间采样时,仅每4小时探测一次云场时,最大不确定度增加到85%。但是,即使在这种情况下,模型域中25-40%的日剂量也具有20%至+ 20%的准确度。事实证明,中午左右的时间对于精确估计紫外线日剂量至关重要。因此,通常在中午左右有限数量的云探测特别有效,尽管在全天时间和空间云变化很大的情况下,三个云探测仍然可能太少而无法防止出现较大的偏差(> 80%)。最后,通过空间平均,可以大大提高参考值与通过给定时间采样计算的每日剂量之间的一致性。

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