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Fog and Low Stratus Obstruction of Wind Lidar Observations in Germany—A Remote Sensing-Based Data Set for Wind Energy Planning

1
Laboratory for Climatology and Remote Sensing (LCRS), University of Marburg, 35032 Marburg, Germany
2
Ramboll, 81541 Munich, Germany
3
Fraunhofer IEE Kassel, 34119 Kassel, Germany
*
Author to whom correspondence should be addressed.
Energies 2020, 13(15), 3859; https://doi.org/10.3390/en13153859
Received: 26 May 2020 / Revised: 20 July 2020 / Accepted: 22 July 2020 / Published: 28 July 2020
(This article belongs to the Section B2: Wind, Wave and Tidal Energy)
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. View Full-Text
Keywords: wind; lidar; availability; fog; clouds wind; lidar; availability; fog; clouds
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MDPI and ACS Style

Rösner, B.; Egli, S.; Thies, B.; Beyer, T.; Callies, D.; Pauscher, L.; Bendix, J. Fog and Low Stratus Obstruction of Wind Lidar Observations in Germany—A Remote Sensing-Based Data Set for Wind Energy Planning. Energies 2020, 13, 3859. https://doi.org/10.3390/en13153859

AMA Style

Rösner B, Egli S, Thies B, Beyer T, Callies D, Pauscher L, Bendix J. Fog and Low Stratus Obstruction of Wind Lidar Observations in Germany—A Remote Sensing-Based Data Set for Wind Energy Planning. Energies. 2020; 13(15):3859. https://doi.org/10.3390/en13153859

Chicago/Turabian Style

Rösner, Benjamin, Sebastian Egli, Boris Thies, Tina Beyer, Doron Callies, Lukas Pauscher, and Jörg Bendix. 2020. "Fog and Low Stratus Obstruction of Wind Lidar Observations in Germany—A Remote Sensing-Based Data Set for Wind Energy Planning" Energies 13, no. 15: 3859. https://doi.org/10.3390/en13153859

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