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Evaluation of CloudSat snowfall rate profiles by a comparison with in situ micro-rain radar observations in East Antarctica

机译:通过与南极东部的微雨雷达实地观测比较,评估CloudSat降雪率分布

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The Antarctic continent is a vast desert and is the coldest and the most unknown area on Earth. It contains the Antarctic ice sheet, the largest continental water reservoir on Earth that could be affected by the current global warming, leading to sea level rise. The only significant supply of ice is through precipitation, which can be observed from the surface and from space. Remote-sensing observations of the coastal regions and the inner continent using CloudSat radar give an estimated rate of snowfall but with uncertainties twice as large as each single measured value, whereas climate models give a range from half to twice the space–time-averaged observations. The aim of this study is the evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based micro-rain radars (MRRs), located at the coastal French Dumont d'Urville station and at the Belgian Princess Elisabeth station located in the Dronning Maud Land escarpment zone. This in turn leads to a better understanding and reassessment of CloudSat uncertainties. We compared a total of four precipitation events, two per station, when CloudSat overpassed within 10?km of the station and we compared these two different datasets at each vertical level. The correlation between both datasets is near-perfect, even though climatic and geographic conditions are different for the two stations. Using different CloudSat and MRR vertical levels, we obtain 10?km space-scale and short-timescale (a few seconds) CloudSat uncertainties from ?13 % up to +22 %. This confirms the robustness of the CloudSat retrievals of snowfall over Antarctica above the blind zone and justifies further analyses of this dataset.
机译:南极大陆是一片广阔的沙漠,是地球上最冷,最未知的地区。它包含南极冰盖,这是地球上最大的大陆性水库,可能受到当前全球变暖的影响,从而导致海平面上升。冰的唯一重要供应是通过降水,可以从表面和太空观察到。使用CloudSat雷达对沿海地区和内陆进行的遥感观测可得出降雪率的估计值,但不确定性是每个单个测量值的两倍,而气候模型的观测范围是时空平均观测值的一半至两倍。这项研究的目的是通过与位于法国沿海Dumont d'Urville站和位于比利时的Elisabeth公主站的两个地面微雨雷达(MRR)进行比较,对CloudSat雷达的垂直降水率剖面进行评估。在Dronning Maud Land悬崖地区。反过来,这可以更好地理解和重新评估CloudSat的不确定性。当CloudSat在距站点10?km的范围内超过时,我们总共比较了四个降水事件,每个站点有两个,并且我们在每个垂直级别比较了这两个不同的数据集。即使两个站的气候和地理条件不同,两个数据集之间的相关性也接近完美。使用不同的CloudSat和MRR垂直水平,我们获得10?km的空间尺度和短时间尺度(几秒钟)的CloudSat不确定度,从?13%到+22%。这证实了CloudSat检索盲区上方南极上空降雪的鲁棒性,并证明了对该数据集进行进一步分析的合理性。

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