Abstract. Accurate long-term daily cloud-gap-filled fractional snow cover products are essential for climate change and snow hydrological studies in the Asian Water Tower (AWT) region, but existing Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products are not sufficient. In this study, the multiple-endmember spectral mixture analysis algorithm based on automatic endmember extraction (MESMA-AGE) and the multistep spatiotemporal interpolation algorithm (MSTI) are used to produce the MODIS daily cloud-gap-filled fractional snow cover product over the AWT region (AWT MODIS FSC). The AWT MODIS FSC products have a spatial resolution of 0.005° and span from 2000 to 2022. The 2745 scenes of Landsat-8 images are used for the areal-scale accuracy assessment. The fractional snow cover accuracy metrics, including the coefficient of determination (R2), root mean squared error (RMSE) and mean absolute error (MAE), are 0.80, 0.16 and 0.10, respectively. The binarized identification accuracy metrics, including overall accuracy (OA), producer's accuracy (PA) and user's accuracy (UA), are 95.17 %, 97.34 % and 97.59 %, respectively. Snow depth data observed at 175 meteorological stations are used to evaluate accuracy at the point scale, yielding the following accuracy metrics: an OA of 93.26 %, a PA of 84.41 %, a UA of 82.14 % and a Cohen kappa (CK) value of 0.79. Snow depth observations from meteorological stations are also used to assess the fractional snow cover resulting from different weather conditions, with an OA of 95.36 % (88.96 %), a PA of 87.75 % (82.26 %), a UA of 86.86 % (78.86 %) and a CK of 0.84 (0.72) under the MODIS clear-sky observations (spatiotemporal reconstruction based on the MSTI algorithm). The AWT MODIS FSC product can provide quantitative spatial distribution information on snowpacks for mountain hydrological models, land surface models and numerical weather prediction in the Asian Water Tower region. This dataset is freely available from the National Tibetan Plateau Data Center at https://doi.org/10.11888/Cryos.tpdc.272503 (Jiang et al., 2022) or from the Zenodo platform at https://doi.org/10.5281/zenodo.10005826 (Jiang et al., 2023a).

中文翻译：

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亚洲水塔地区MODIS每日云隙填充分数积雪数据集（2000-2022年）


摘要。准确的长期每日云隙填充分数积雪产品对于亚洲水塔（AWT）地区的气候变化和积雪水文研究至关重要，但现有的中分辨率成像光谱仪（MODIS）积雪产品还不够。本研究采用基于自动端元提取的多端元光谱混合分析算法（MESMA-AGE）和多步时空插值算法（MSTI）来生成AWT上的MODIS日云隙填充分数积雪产品区域（AWT MODIS FSC）。 AWT MODIS FSC产品的空间分辨率为0.005°，跨度为2000年至2022年。使用Landsat-8影像的2745个场景进行面尺度精度评估。分数积雪精度指标，包括确定系数 (R2)、均方根误差 (RMSE) 和平均绝对误差 (MAE)，分别为 0.80、0.16 和 0.10。二值化识别准确度指标，包括总体准确度（OA）、生产者准确度（PA）和用户准确度（UA）分别为95.17%、97.34%和97.59%。利用175个气象站观测的雪深数据来评估点尺度的精度，得出以下精度指标：OA为93.26%，PA为84.41%，UA为82.14%，科恩卡帕（CK）值为0.79。气象站的积雪深度观测也用于评估不同天气条件下的积雪覆盖率，OA为95.36 ％（88.96 ％），PA为87.75 ％（82.26 ％），UA为86.86 ％（78.86 ％） ），MODIS晴空观测（基于MSTI算法的时空重建）下的CK为0.84（0.72）。 AWT MODIS FSC产品可以为亚洲水塔地区的山地水文模型、地表模型和数值天气预报提供积雪的定量空间分布信息。该数据集可从国家青藏高原数据中心 https://doi.org/10.11888/Cryos.tpdc.272503（Jiang et al., 2022）或 Zenodo 平台 https://doi.org/ 免费获取10.5281/zenodo.10005826（Jiang 等人，2023a）。