Snowfall and snow accumulation processes during the MOSAiC winter and spring season
Snowfall and snow accumulation processes during the MOSAiC winter and spring season
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MOSAiC冬春季节降雪和积雪过程
DOI：
10.5194/tc-2021-126
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
M. Lehning
中科院分区：
文献类型：
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作者：
D. Wagner;M. Shupe;O. Persson;T. Uttal;M. Frey;A. Kirchgaessner;M. Schneebeli;Matthias Jaggi;Amy R. Macfarlane;P. Itkin;Stefanie Arndt;S. Hendricks;D. Krampe;R. Ricker;J. Regnery;Nikolai Kolabutin;Egor Shimanshuck;M. Oggier;Ian A. Raphael;M. Lehning
摘要。来自北极气候研究多学科漂流观测站（MOSAiC）的数据使我们能够详细研究几乎整个积累季节（2019年11月至2020年5月）的降雪、积雪和侵蚀的时间动态。我们基于雪深（HS）和从SnowMicroPen （SMP）获取的密度，以及沿固定样条路径大约每周测量的雪深，计算了海冰上的累积雪水当量（SWE）。因此，计算的SWE考虑了平均路径长度为1469 m的表面非均匀性。我们使用积雪的SWE与MOSAiC期间安装的降水传感器进行比较。将这些数据与ERA5再分析漂移轨迹的降雪率进行了比较。我们的研究表明，简单拟合的HS-SWE函数可以很好地用于基于SMP SWE检索和雪深测量的样条路径计算SWE。我们发现到2020年4月26日，积雪累积量为34毫米。此外，我们还发现，安装在“极地之星”号科考船顶甲板栏杆上的维萨拉现代天气探测器22 （PWD22）受吹雪的影响最小，与沿样带的SWE反演结果吻合良好，但它也系统性地低估了降雪。OTT Pluvio2和OTT Parsivel2主要受风和吹雪的影响，导致实测降水率较高，但在消除飘雪期时，特别是OTT Pluvio2与地面测量值的一致性较好。与ERA5降雪数据的比较表明，降雪事件的时间很好，与地面测量结果很吻合，但也有高估的倾向。船载ka波段ARM天顶雷达（KAZR）反演的降雪量与SWE的积雪值吻合较好，与ERA5的差异可比较。假设KAZR衍生降雪量为上限，PWD22为累积降雪量范围的下限，我们估计在2019年10月31日至2020年4月26日期间测量的72至107毫米。在同一时期，我们估计由于侵蚀和升华造成的沿样带降水质量损失在53%至68%之间。到2020年5月7日，我们建议累计降雪量为98-114毫米。
Abstract. Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation, and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth (HS) and density retrievals from a SnowMicroPen (SMP) and approximately weekly-measured snow depths along fixed transect paths. Hence, the computed SWE considers surface heterogeneities over an average path length of 1469 m. We used the SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were compared with ERA5 reanalysis snowfall rates for the drift track. Our study shows that the simple fitted HS-SWE function can well be used to compute SWE along a transect path based on SMP SWE retrievals and snow-depth measurements. We found an accumulated snow mass of 34 mm SWE until 26 April 2020. Further, we found that the Vaisala Present Weather Detector 22 (PWD22), installed on a railing on the top deck of research vessel Polarstern was least affected by blowing snow and showed good agreements with SWE retrievals along the transect, however, it also systematically underestimated snowfall. The OTT Pluvio2 and the OTT Parsivel2 were largely affected by wind and blowing snow, leading to higher measured precipitation rates, but when eliminating drifting snow periods, especially the OTT Pluvio2 shows good agreements with ground measurements. A comparison with ERA5 snowfall data reveals a good timing of the snowfall events and good agreement with ground measurements but also a tendency towards overestimation. Retrieved snowfall from the ship-based Ka-band ARM Zenith Radar (KAZR) shows good agreements with SWE of the snow cover and comparable differences as ERA5. Assuming the KAZR derived snowfall as an upper limit and PWD22 as a lower limit of a cumulative snowfall range, we estimate 72 to 107 mm measured between 31 October 2019 and 26 April 2020. For the same period, we estimate the precipitation mass loss along the transect due to erosion and sublimation as between 53 and 68 %. Until 7 May 2020, we suggest a cumulative snowfall of 98–114 mm.
DOI：
10.1029/2019jc015913
发表时间：
2020-10
期刊：
Journal of geophysical research. Oceans
影响因子：
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作者：
Liston GE;Itkin P;Stroeve J;Tschudi M;Stewart JS;Pedersen SH;Reinking AK;Elder K
通讯作者：
Elder K
DOI：
10.1029/2020jc016308
发表时间：
2021-01
期刊：
Journal of geophysical research. Oceans
影响因子：
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作者：
Webster MA;DuVivier AK;Holland MM;Bailey DA
通讯作者：
Bailey DA