Abstract This paper describes the methodology for deriving yearly pixel-wise snow melt-off day maps from optical data-based FSC (Fractional Snow Cover) without conducting any interpolation for cloud-obscured pixels or otherwise missing data. The Copernicus CryoLand Pan-European FSC time series for 2001–2016 re-gridded to 0.1° serves as input for the production of 16 years of melt-off day maps for Europe. These maps are compared with passive microwave radiometer (MWR) melt retrievals, to compare the performance of these two independent datasets, particularly concerning the effect of physiographic and snow conditions on the accuracy of the melt-off day estimates. Both these datasets are evaluated against melt-off day derived from in situ snow depth (SD) time series observed at European weather stations. We also present the relationship of these snow melt-off day products to a passive microwave radiometer-derived landscape freeze/thaw product. Our results show that the melt-off day derived from optical springtime FSC time series provides the strongest correlation with the snow melt-off day with respect to the in situ data. Overall the deviation of CryoLand FSC data derived melt-off day to that indicated by in situ observations is quite small, with positive bias of 0.9 days, and RMSE of 13.1 days. For 85% of the analyzed cases the differences are between ±10 days. Across Europe the MWR-based detection of melt-off day is less accurate; the investigated method performs the best for areas with sustained seasonal snow cover. Based on the time series for MWR-based melt-off day (1980–2016) and FT-ESDR (1980–2014), separately for boreal forests and tundra, we also found a clear trend towards earlier snow clearance: a decrease of melt-off day by as much as ~5 days per decade in boreal forest region was observed.

中文翻译：

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从光学和微波辐射计数据得出的融雪日的准确性——一项针对欧洲的研究

摘要 本文描述了从基于光学数据的 FSC（部分积雪）导出逐年像素级融雪日图的方法，无需对云遮挡像素或其他缺失数据进行任何插值。2001-2016 年哥白尼 CryoLand 泛欧 FSC 时间序列重新网格化为 0.1°，作为制作欧洲 16 年融化日图的输入。这些地图与被动微波辐射计 (MWR) 融化反演进行了比较，以比较这两个独立数据集的性能，特别是关于地貌和雪况对融化日估计准确性的影响。这两个数据集都是根据欧洲气象站观测到的原位雪深 (SD) 时间序列得出的融化日进行评估的。我们还介绍了这些融雪日产品与被动微波辐射计衍生的景观冻结/解冻产品的关系。我们的结果表明，根据原位数据，从光学春季 FSC 时间序列得出的融化日与雪融化日的相关性最强。总体而言，CryoLand FSC 数据得出的融化天数与原位观测值的偏差非常小，正偏差为 0.9 天，RMSE 为 13.1 天。对于 85% 的分析案例，差异在 ±10 天之间。在整个欧洲，基于 MWR 的融化日检测不太准确；所调查的方法在持续季节性积雪的地区表现最佳。基于基于 MWR 的融化日（1980-2016）和 FT-ESDR（1980-2014）的时间序列，