Fog and Low Stratus Obstruction of Wind Lidar Observations in Germany—A Remote Sensing-Based Data Set for Wind Energy Planning
Fog and Low Stratus Obstruction of Wind Lidar Observations in Germany—A Remote Sensing-Based Data Set for Wind Energy Planning
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DOI：
10.3390/en13153859
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发表时间：
2020-07
期刊：
影响因子：
3.2
通讯作者：
B. Rösner;Sebastian Egli;B. Thies;Tina Beyer;Doron Callies;L. Pauscher;J. Bendix
中科院分区：
文献类型：
--
作者：
B. Rösner;Sebastian Egli;B. Thies;Tina Beyer;Doron Callies;L. Pauscher;J. Bendix
相干测风多普勒激光雷达（CWDL）是一种经济有效的方法，可以在不需要建造气象塔的情况下估计轮毂高度的风力潜力。然而，雾和低层云（FLS）可能会对激光雷达测量的可用性产生负面影响。提前获得关于预期激光雷达部署地点的风数据可用性的这种减少的信息在测量策略的规划过程中是有益的。在本文中，我们表明，FLS的可用性减少可以通过比较时间序列的激光雷达测量，进行WindCubes V1和V2，与时间序列的云底高度（CBA）来自卫星数据。这使我们能够计算估计可用性的平均地图（2006-2017年），包括FLS引起的德国数据丢失，可用于规划目的。这些地图显示，德国的低山脉和阿尔卑斯山地区经常达到80%或更低的关键数据可用性阈值。特别是在冬季，在德国的南部和中部地区使用激光雷达时，必须特别小心。如果仅计划较短的激光雷达活动（3-6个月），则还应考虑天气类型的代表性，因为在个别年份和持续天气类型下，低地地区也可能受到较高数据丢失率的暂时影响。这是由不同的例子所示，例如，在反气旋天气类型下的辐射雾期间。
Coherent wind doppler lidar (CWDL) is a cost-effective way to estimate wind power potential at hub height without the need to build a meteorological tower. However, fog and low stratus (FLS) can have a negative impact on the availability of lidar measurements. Information about such reductions in wind data availability for a prospective lidar deployment site in advance is beneficial in the planning process for a measurement strategy. In this paper, we show that availability reductions by FLS can be estimated by comparing time series of lidar measurements, conducted with WindCubes v1 and v2, with time series of cloud base altitude (CBA) derived from satellite data. This enables us to compute average maps (2006–2017) of estimated availability, including FLS-induced data losses for Germany which can be used for planning purposes. These maps show that the lower mountain ranges and the Alpine regions in Germany often reach the critical data availability threshold of 80% or below. Especially during the winter time special care must be taken when using lidar in southern and central regions of Germany. If only shorter lidar campaigns are planned (3–6 months) the representativeness of weather types should be considered as well, because in individual years and under persistent weather types, lowland areas might also be temporally affected by higher rates of data losses. This is shown by different examples, e.g., during radiation fog under anticyclonic weather types.