Calibration of scatterometer wind speed under hurricane conditions

AbstractFour scatterometers, namely: METOP-A, METOP-B, ERS-2 and OCEANSAT-2 were re-calibrated against combined National Data Buoy Center (NDBC) data and aircraft Stepped Frequency Microwave Radiometer (SFMR) data from hurricanes. As a result, continuous calibration relations over the wind speed range 0 to 45 ms-1 were developed. The calibration process uses match-up criteria of 50 km and 30 min for the buoy data. However, due to the strong spatio-temporal wind speed gradients in hurricanes, a method which considers both scatterometer and SFMR data in a storm-centred translating frame of reference is adopted. The results show that although the scatterometer radar cross-section is degraded at high wind speeds, it is still possible to recover wind speed data using the re-calibration process. Data validation between the scatterometers shows that the calibration relations produce consistent results across all scatterometers and reduce the bias and root mean square error compared to previous calibrations. In addition, the results extend the useful range of scatterometer measurements to as high as 45 ms-1.

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Calibration and Cross Validation of Global Ocean Wind Speed Based on Scatterometer Observations

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-19-0119.1 ◽

2020 ◽

Vol 37 (2) ◽

pp. 279-297 ◽

Cited By ~ 7

Author(s):

Agustinus Ribal ◽

Ian R. Young

Keyword(s):

Wind Speed ◽

Cross Validation ◽

Regression Line ◽

Total Duration ◽

Global Ocean ◽

High Wind ◽

Wind Speeds ◽

Buoy Data ◽

Ocean Wind

AbstractGlobal ocean wind speed observed from seven different scatterometers, namely, ERS-1, ERS-2, QuikSCAT, MetOp-A, OceanSat-2, MetOp-B, and Rapid Scatterometer (RapidScat) were calibrated against National Data Buoy Center (NDBC) data to form a consistent long-term database of wind speed and direction. Each scatterometer was calibrated independently against NDBC buoy data and then cross validation between scatterometers was performed. The total duration of all scatterometer data is approximately 27 years, from 1992 until 2018. For calibration purposes, only buoys that are greater than 50 km offshore were used. Moreover, only scatterometer data within 50 km of the buoy and for which the overpass occurred within 30 min of the buoy recording data were considered as a “matchup.” To carry out the calibration, reduced major axis (RMA) regression has been applied where the regression minimizes the size of the triangle formed by the vertical and horizontal offsets of the data point from the regression line and the line itself. Differences between scatterometer and buoy data as a function of time were investigated for long-term stability. In addition, cross validation between scatterometers and independent altimeters was also performed for consistency. The performance of the scatterometers at high wind speeds was examined against buoy and platform measurements using quantile–quantile (Q–Q) plots. Where necessary, corrections were applied to ensure scatterometer data agreed with the in situ wind speed for high wind speeds. The resulting combined dataset is believed to be unique, representing the first long-duration multimission scatterometer dataset consistently calibrated, validated and quality controlled.

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Study on the Influence of Baseline Control System on the Fragility of Large-Scale Wind Turbine considering Seismic-Aerodynamic Combination

Advances in Civil Engineering ◽

10.1155/2020/8471761 ◽

2020 ◽

Vol 2020 ◽

pp. 1-15

Author(s):

Chenyang Yuan ◽

Jing Li ◽

Jianyun Chen ◽

Qiang Xu ◽

Yunfei Xie

Keyword(s):

Control System ◽

Wind Speed ◽

Wind Turbine ◽

Large Scale ◽

Fragility Curves ◽

Operating Conditions ◽

Ground Acceleration ◽

Wind Speeds ◽

Speed Range ◽

Wind Actions

The purpose of this paper is to explore the effect of the baseline control system (BCS) on the fragility of large-scale wind turbine when seismic and wind actions are considered simultaneously. The BCS is used to control the power output by regulating rotor speed and blade-pitch angle in real time. In this study, the fragility analysis was performed and compared between two models using different peak ground acceleration, wind speeds, and specified critical levels. The fragility curves with different wind conditions are obtained using the multiple stripe analysis (MSA) method. The calculation results show that the probability of exceedance specified critical level increases as the wind speed increases in model 1 without considering BCS, while does not have an obvious change in the below-rated wind speed range and has a significant decrease in the above-rated wind speed range in model 2 with considering BCS. The comparison depicts that if the BCS is neglected, the fragility of large-scale wind turbine will be underestimated in around the cut-in wind speed range and overestimated in the over-rated wind speed range. It is concluded that the BCS has a great effect on the fragility especially within the operating conditions when the rated wind speed is exceeded, and it should be considered when estimating the fragility of wind turbine subjected to the interaction of seismic and aerodynamic loads.

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Overall Adaptive Controller Design of PMSG Under Whole Wind Speed Range: A Perturbation Compensation Based Approach

Processes ◽

10.3390/pr7100732 ◽

2019 ◽

Vol 7 (10) ◽

pp. 732 ◽

Cited By ~ 2

Author(s):

Jian Chen ◽

Wenyong Duan ◽

Xiaodong Yang ◽

Lanhong Zhang ◽

Yi Shan ◽

...

Keyword(s):

Adaptive Control ◽

Wind Speed ◽

Control Strategy ◽

Controller Design ◽

Current Control ◽

Parameter Uncertainties ◽

Pitch Control ◽

Grid Current ◽

Wind Speeds ◽

Speed Range

This paper proposes an adaptive overall control strategy of the permanent magnet synchronous generator-based wind energy conversion system (WECS) in the whole wind speed range. For the machine side, the maximum power point tracking (MPPT) operation is realized by stator current and mechanical rotation speed control under below-rated wind speeds. Under above-rated wind speeds, the extracted wind power is limited via pitch control. For the grid side, the reactive and active power injected into grid is regulated by DC-Link voltage and grid current control loop. In addition, under grid voltage dips, the pitch control is employed for limiting grid current and maintaining the DC-Link voltage around its rated value. The fault ride-through capability (FRTC) can be enhanced. The overall control strategy is based on perturbation estimation technique. A designed observer is used for estimating the perturbation term including all system nonlinearities, uncertainties and disturbances, so as to compensate the real perturbation. Then, an adaptive control for the original nonlinear system can be realized. The effectiveness of the proposed overall control strategy is verified by applying the strategy to a 2-MW WECS in MATLAB/Simulink. The results show that, compared with the feedback linearizing control (FLC) strategy and conventional vector control (VC) strategy, the proposed perturbation observer based adaptive control (PO-AC) strategy realizes the control objectives without knowing full state information and accurate system model, and improves the robustness of the WECS parameter uncertainties and FRTC.

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Development for wind friction velocity retrieval algorithm based on the SFMR and NOAA dropwindsondes measurements in hurricane conditions

10.5194/egusphere-egu21-9086 ◽

2021 ◽

Author(s):

Evgeny Poplavsky ◽

Nikita Rusakov ◽

Olga Ermakova ◽

Daniil Sergeev ◽

Yuliya Troitskaya ◽

...

Keyword(s):

Boundary Layer ◽

Wind Speed ◽

Atmospheric Boundary Layer ◽

Friction Velocity ◽

Microwave Radiometer ◽

Field Measurements ◽

Retrieval Algorithm ◽

Self Similarity ◽

Defect Profile ◽

Stepped Frequency

The work is concerned with the development of a method for the retrieval of tropical cyclones boundary atmospheric layer parameters, namely the wind friction velocity and wind speed at meteorological height. For the analysis, we used the results of field measurements of wind speed profiles from dropwindsondes launched from National Oceanic and Atmospheric Administration (NOAA) aircraft and collocated data from the Stepped-Frequency Microwave Radiometer (SFMR) located onboard of the same aircraft.The results of radiometric measurements were used to obtain the emissivity values, which were compared with the field data obtained from the falling dropwindsondes. Using the algorithm taking into account the self-similarity of the velocity defect profile (Ermakova et al., 2019), the parameters of the atmospheric boundary layer were determined from the data measured by dropwindsondes. This algorithm gives an opportunity to obtain the wind speed value at meteorological height and wind friction velocity from the averaged data in the wake part of the profiles of the marine atmospheric boundary layer.A comparison of the wind speed U10 dependencies, retrieved from the SFMR data and measurements from dropwindsondes, with the similar dependencies obtained in (Uhlhorn et al., 2007), was made, and their satisfactory agreement was demonstrated. This work was supported by the RFBR projects No. 19-05-00249, 19-05-00366.

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A Comparative Assessment of Surface Wind Speed and Sea Surface Temperature over the Indian Ocean by TMI, MSMR, and ERA-40

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech2021.1 ◽

2007 ◽

Vol 24 (6) ◽

pp. 1131-1142 ◽

Cited By ~ 23

Author(s):

Anant Parekh ◽

Rashmi Sharma ◽

Abhijit Sarkar

Keyword(s):

Wind Speed ◽

Indian Ocean ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Microwave Radiometer ◽

Surface Wind ◽

Surface Wind Speed ◽

Sea Surface ◽

Wind Speeds ◽

Low Wind Speeds

A 2-yr (June 1999–June 2001) observation of ocean surface wind speed (SWS) and sea surface temperature (SST) derived from microwave radiometer measurements made by a multifrequency scanning microwave radiometer (MSMR) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is compared with direct measurements by Indian Ocean buoys. Also, for the first time SWS and SST values of the same period obtained from 40-yr ECMWF Re-Analysis (ERA-40) have been evaluated with these buoy observations. The SWS and SST are shown to have standard deviations of 1.77 m s−1 and 0.60 K for TMI, 2.30 m s−1 and 2.0 K for MSMR, and 2.59 m s−1 and 0.68 K for ERA-40, respectively. Despite the fact that MSMR has a lower-frequency channel, larger values of bias and standard deviation (STD) are found compared to those of TMI. The performance of SST retrieval during the daytime is found to be better than that at nighttime. The analysis carried out for different seasons has raised an important question as to why one spaceborne instrument (TMI) yields retrievals with similar biases during both pre- and postmonsoon periods and the other (MSMR) yields drastically different results. The large bias at low wind speeds is believed to be due to the poorer sensitivity of microwave emissivity variations at low wind speeds. The extreme SWS case study (cyclonic condition) showed that satellite-retrieved SWS captured the trend and absolute magnitudes as reflected by in situ observations, while the model (ERA-40) failed to do so. This result has direct implications on the real-time application of satellite winds in monitoring extreme weather events.

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Extreme Wind Speeds Retrieval Using Sentinel-1 IW Mode SAR Data

Remote Sensing ◽

10.3390/rs13101867 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1867

Author(s):

Yuan Gao ◽

Jian Sun ◽

Jie Zhang ◽

Changlong Guan

Keyword(s):

Wind Speed ◽

Mean Squared Error ◽

Incident Angle ◽

Microwave Radiometer ◽

Surface Wind ◽

European Space Agency ◽

Noise Removal ◽

Wind Retrieval ◽

Wind Speeds ◽

Microwave Radar

With the improvement in microwave radar technology, spaceborne synthetic aperture radar (SAR) is widely used to observe the tropical cyclone (TC) wind field. Based on European Space Agency Sentinel-1 Interferometric Wide swath (IW) mode imagery, this paper evaluates the correlation between vertical transmitting–horizontal receiving (VH) polarization signals and extreme ocean surface wind speeds (>40 m/s) under strong TC conditions. A geophysical model function (GMF) Sentinel-1 IW mode wind retrieval model after noise removal (S1IW.NR) was proposed, according to the SAR images of nine TCs and collocated stepped frequency microwave radiometer (SFMR) and soil moisture active passive (SMAP) radiometer wind speed measurements. Through curve fitting and regression correction, the new GMF exploits the relationships between VH-polarization normalized radar cross section, incident angle, and wind speed in each sub-swath and covers wind speeds up to 74 m/s. Based on collocated SAR and SFMR measurements of four TCs, the new GMF was validated in the wind speed range from 2 to 53 m/s. Results show that the correlation coefficient, bias, and root mean squared error were 0.89, −0.89 m/s, and 4.13 m/s, respectively, indicating that extreme winds can be retrieved accurately by the new model. In addition, we investigated the relationship between the S1IW.NR wind retrieval bias and the SFMR-measured rain rate. The S1IW.NR model tended to overestimate wind speeds under high rain rates.

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Evaluation of wind speed estimates in reanalyses for wind energy applications

Advances in Science and Research ◽

10.5194/asr-18-115-2021 ◽

2021 ◽

Vol 18 ◽

pp. 115-126

Author(s):

Sebastian Brune ◽

Jan D. Keller ◽

Sabrina Wahl

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Surface Characteristics ◽

Horizontal Resolution ◽

Hilly Terrain ◽

Average Wind Speed ◽

Wind Speeds ◽

Energy Applications ◽

Spatio Temporal ◽

Regional Reanalysis

Abstract. A correct spatio-temporal representation of retrospective wind speed estimates is of large interest for the wind energy sector. In this respect, reanalyses provide an invaluable source of information. However, the quality of the various reanalysis estimates for wind speed are difficult to assess. Therefore, this study compares wind measurements at hub heights from 14 locations in Central Europe with two global (ERA5, MERRA-2) and one regional reanalysis (COSMO-REA6). Employing metrics such as bias, RMSE and correlation, we evaluate the performance of the reanalyses with respect to (a) the local surface characteristics (offshore, flat onshore, hilly onshore), (b) various height levels (60 to 200 m) and (c) the diurnal cycle. As expected, we find that the reanalyses show the smallest errors to observations at offshore sites. Over land, MERRA-2 generally overestimates wind speeds, while COSMO-REA6 and ERA5 represent the average wind speed more realistically. At sites with flat terrain, ERA5 correlates better with observations than COSMO-REA6. In contrast, COSMO-REA6 performs slightly better over hilly terrain, which can be explained by the higher horizontal resolution. In terms of diurnal variation, ERA5 outperforms both other reanalyses. While the overestimation of MERRA-2 is consistent throughout the day, COSMO-REA6 significantly underestimates wind speed at night over flat and hilly terrain due to a misrepresentation of nightly low level jets and mountain and valley breezes. Regarding the representation of downtime of wind turbines due to low/high wind speeds, we find that MERRA-2 is consistently underperforming with respect to the other reanalyses. Here COSMO-REA6 performs better over the ocean, while ERA5 shows the best results over land.

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Harvesting Variable-Speed Wind Energy with a Dynamic Multi-Stable Configuration

Materials ◽

10.3390/ma13061389 ◽

2020 ◽

Vol 13 (6) ◽

pp. 1389

Author(s):

Yuansheng Wang ◽

Zhiyong Zhou ◽

Qi Liu ◽

Weiyang Qin ◽

Pei Zhu

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Stable Configuration ◽

Variable Speed ◽

Coherence Resonance ◽

Wind Speeds ◽

Piezoelectric Beam ◽

Speed Range ◽

Low Wind Speeds ◽

Large Output

To harvest the energy of variable-speed wind, we proposed a dynamic multi-stable configuration composed of a piezoelectric beam and a rectangular plate. At low wind speeds, the system exhibits bi-stability, whereas, at high wind speeds, the system exhibits a dynamic tri-stability, which is beneficial for harvesting variable-speed wind energy. The theoretical analysis was carried out. For validation, the prototype was fabricated, and a piezoelectric material was bonded to the beam. The corresponding experiment was conducted, with the wind speed increasing from 1.5 to 7.5 m/s. The experiment results prove that the proposed harvester could generate a large output over the speed range. The dynamic stability is helpful to maintain snap-through motion for variable-speed wind. In particular, the snap-through motion could reach coherence resonance in a range of wind speed. Thus, the system could keep large output in the environment of variable-speed wind.

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Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations

Ocean Science ◽

10.5194/os-4-265-2008 ◽

2008 ◽

Vol 4 (4) ◽

pp. 265-274 ◽

Cited By ~ 67

Author(s):

A. Bentamy ◽

D. Croize-Fillon ◽

C. Perigaud

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Surface Wind Speed ◽

Global Scale ◽

Global Ocean ◽

Wind Vector ◽

Wind Speeds ◽

Wind Retrievals ◽

Buoy Data

Abstract. The new scatterometer Advanced SCATterometer (ASCAT) onboard MetOp-A satellite provides surface wind speed and direction over global ocean with a spatial resolution of 25 km square over two swaths of 550 km widths. The accuracy of ASCAT wind retrievals is determined through various comparisons with moored buoys. The comparisons indicate that the remotely sensed wind speeds and directions agree well with buoy data. The root-mean-squared differences of the wind speed and direction are less than 1.72 m/s and 18°, respectively. At global scale, ASCAT winds are compared with surface winds derived from QuikSCAT scatterometer. The results confirm the buoy analyses, especially for wind speed ranging between 3 m/s and 20 m/s. For higher wind conditions, ASCAT is biased low. The ASCAT underestimation with respect to QuikSCAT winds is wind speed dependent. The comparisons based on the collocated scatterometer data collected after 17 of October 2007 indicate that there are significant improvements compared to previous periods.

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Improved Stepped Frequency Microwave Radiometer Tropical Cyclone Surface Winds in Heavy Precipitation

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-14-00028.1 ◽

2014 ◽

Vol 31 (11) ◽

pp. 2392-2408 ◽

Cited By ~ 56

Author(s):

Bradley W. Klotz ◽

Eric W. Uhlhorn

Keyword(s):

Brightness Temperature ◽

Doppler Radar ◽

Microwave Radiometer ◽

Surface Wind ◽

Heavy Precipitation ◽

Wind Speeds ◽

Stepped Frequency ◽

Rain Rates ◽

The Impact ◽

Retrieval Bias

AbstractSurface wind speeds retrieved from airborne stepped frequency microwave radiometer (SFMR) brightness temperature measurements are important for estimating hurricane intensity. The SFMR performance is highly reliable at hurricane-force wind speeds, but accuracy is found to degrade at weaker wind speeds, particularly in heavy precipitation. Specifically, a significant overestimation of surface wind speeds is found in these conditions, suggesting inaccurate accounting for the impact of rain on the measured microwave brightness temperature. In this study, the wind speed bias is quantified over a broad range of operationally computed wind speeds and rain rates, based on a large sample of collocated SFMR wind retrievals and global positioning system dropwindsonde surface-adjusted wind speeds. The retrieval bias is addressed by developing a new SFMR C-band relationship between microwave absorption and rain rate (κ−R) from National Oceanic and Atmospheric Administration WP-3D aircraft tail Doppler radar reflectivity and in situ Droplet Measurement Technologies Precipitation Imaging Probe measurements to more accurately model precipitation impacts. Absorption is found to be a factor of 2 weaker than is estimated by the currently operational algorithm. With this new κ–R relationship, surface wind retrieval bias is significantly reduced in the presence of rain at wind speeds weaker than hurricane force. At wind speeds greater than hurricane force where little bias exists, no significant change is found. Furthermore, maximum rain rates computed using the revised algorithm are around 50% greater than operational measurements, which is more consistent with maximum reflectivity-estimated rain rates in hurricanes.

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