A novel post-processing algorithm for Halo Doppler lidars

Vakkari, Ville; Manninen, Antti; O’Connor, Ewan; Schween, Jan H.; Zyl, P. G. van

doi:10.5194/amt-2018-323

Cited by 2 publications

(2 citation statements)

References 20 publications

(41 reference statements)

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“…It remains, however, to be investigated if there are any additionally dependence on pulse repetition frequency, pulse averaging, pulse power, pulse width and other parameters as it is the case for the estimate of the uncertainty in the velocity measurements. Manninen et al [25] and Vakkari et al [26] presented a novel post-processing algorithm that performs a correction for the instruments background noise. The algorithm which still is in a trial stage has been developed for a Halo Doppler wind lidar and successfully applied to measurements carried out in Finland.…”

Section: Discussionmentioning

confidence: 99%

“…A method to compensate for the instrument noise which reduces the signal-to-noise ratio threshold value that is used as a measure of the data quality is presented in [25]. Along this line [26] suggests a post-processing algorithm that provides a better estimate of the signal-to-noise-ratio of the observations, which results in a more accurate estimate of the uncertainty of the line-of-sight measurements. Presently the algorithm is implemented for a Halo Doppler Wind Lidar in Finland and is shown to improve the sensitivity of the observations with at least a factor of five.…”

Section: Introductionmentioning

confidence: 99%

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Carrier-to-Noise-Threshold Filtering on Off-Shore Wind Lidar Measurements

Gryning

Floors

2019

Sensors

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Wind lidar observations are characterized by a Carrier-to-Noise-Ratio that is often used to filter the observations. The choice of the Carrier-to-Noise-Ratio threshold value for the wind lidar observations is found to have an effect on the climatological wind speed distribution in such a way that when the Carrier-to-Noise-Ratio (CNR) threshold value is increased the wind speed distribution is shifted to higher values. Based on one year of observations carried out with a wind lidar from 126 m to 626 m height at the FINO3 (Forschungsplattform in Nord- und Ostsee Nr. 3) research platform in the North Sea, the effect that the choice of the Carrier-to-Noise threshold value has on the climatology of the wind speed and direction as well as the wind power density in relation to wind energy is illustrated and discussed. In the one-year data set considered here it is found that for thresholds larger than −29 dB, the mean wind speed and wind rose measured by the wind lidar become a function of the threshold value, and for values smaller than ~ −29 dB further decrease of the Carrier-to-Noise-Ratio threshold has a minor effect on the estimated mean wind speed and wind rose. The analysis of the data set from the North Sea shows that the limit for the Carrier-to-Noise-Ratio of the observations should be −29 dB or less to obtain a threshold independent estimate of the mean wind speed and wind rose. Alternatively, all valid observations should be used for the analysis. Although this study is specific for the conditions in the North Sea, we suggest that for a representative estimation of the wind resource with wind lidars, the effect of the CNR threshold filtering on the wind distribution should be studied when the recovery rate is less than 100%.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Carrier-to-Noise-Threshold Filtering on Off-Shore Wind Lidar Measurements

Gryning

Floors

2019

Sensors

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Looking for an Offshore Low-Level Jet Champion among Recent Reanalyses: A Tight Race over the Baltic Sea

et al. 2020

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With an increasing interest in offshore wind energy, focus has been directed towards large semi-enclosed basins such as the Baltic Sea as potential sites to set up wind turbines. The meteorology of this inland sea in particular is strongly affected by the surrounding land, creating mesoscale conditions that are important to take into consideration when planning for new wind farms. This paper presents a comparison between data from four state-of-the-art reanalyses (MERRA2, ERA5, UERRA, NEWA) and observations from LiDAR. The comparison is made for four sites in the Baltic Sea with wind profiles up to 300 m. The findings provide insight into the accuracy of reanalyses for wind resource assessment. In general, the reanalyses underestimate the average wind speed. The average shear is too low in NEWA, while ERA5 and UERRA predominantly overestimate the shear. MERRA2 suffers from insufficient vertical resolution, which limits its usefulness in evaluating the wind profile. It is also shown that low-level jets, a very frequent mesoscale phenomenon in the Baltic Sea during late spring, can appear in a wide range of wind speeds. The observed frequency of low-level jets is best captured by UERRA. In terms of general wind characteristics, ERA5, UERRA, and NEWA are similar, and the best choice depends on the application.

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A novel post-processing algorithm for Halo Doppler lidars

Cited by 2 publications

References 20 publications

Carrier-to-Noise-Threshold Filtering on Off-Shore Wind Lidar Measurements

Carrier-to-Noise-Threshold Filtering on Off-Shore Wind Lidar Measurements

Looking for an Offshore Low-Level Jet Champion among Recent Reanalyses: A Tight Race over the Baltic Sea

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