scholarly journals Exploring the coastal effects relevant for offshore wind farming using the space borne synthetic aperture radar data in the German Bight

2021 ◽  
Author(s):  
Bughsin Djath ◽  
Johannes Schulz-Stellenfleth
Keyword(s):  
Thermal Stability ◽  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
German Bight ◽  
Atmospheric Stability ◽  
Sea Surface ◽  
Offshore Wind ◽  
Synthetic Aperture ◽  
Horizontal Wind ◽  
Wind Speeds

<p>In the coastal zone complex atmospheric processes such as momentum and heat fluxes are  caused by large differences between the land and the sea. The smoother sea surface leads to wind speeds, which are usually higher over the ocean than over land. In addition, there are complicated effects caused by temperature gradients in the ocean due to water depth variations.  This study focuses on the investigation of the change in the horizontal wind field and the atmospheric stability between the coast and up to 200 km offshore.</p><p>The wind resources at 10 m height are assessed from synthetic aperture radar (SAR) data acquired by the satellites Sentinel1A/B over the German Bight within the period of 2017-2020 with a focus on offshore wind directions. The satellite data provide information on sea surface roughness, which can be linked to near surface wind speed.  Information on the air-sea thermal components is  provided by model data from the German weather service (DWD).</p><p>The SAR data  show a significant increase of wind speed offshore in most cases. Increasing wind speeds between land and sea over fetch distances of 70 km and more are often detected. The increase δu in horizontal wind speed between offshore and the coast exceeds 2.5 m/s in average. Furthermore, the estimated atmospheric stability shows an impact on the wind speed gradients. The thermal stability appears to dictate the distance over which the wind increases. Strong thermal stability tends to influence the horizontal wind gradient by increasing the fetch distance over more than 100 km. In the context of offshore wind farming, the potential effects of these horizontal wind gradients on the wind power will be discussed.</p>

scholarly journals Comparison of C-Band Quad-Polarization Synthetic Aperture Radar Wind Retrieval Models

2018 ◽  
Vol 10 (9) ◽  
pp. 1448 ◽  
Author(s):  
He Fang ◽  
Tao Xie ◽  
William Perrie ◽  
Guosheng Zhang ◽  
Jingsong Yang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Surface Wind ◽  
Synthetic Aperture ◽  
Northwest Pacific ◽  
Sar Images ◽  
Retrieval Models ◽  
Wind Retrieval ◽  
Wind Speeds ◽  
Aperture Radar

This work discusses the accuracy of C-2PO (C-band cross-polarized ocean backscatter) and CMOD4 (C-band model) geophysical model functions (GMF) for sea surface wind speed retrieval from satellite-born Synthetic Aperture Radar (SAR) images over in the Northwest Pacific off the coast of China. In situ observations are used for comparison of the retrieved wind speed using two established wind retrieval models: C-2PO model and CMOD4 GMF. Using 439 samples from 92 RADARSAT-2 fine quad-polarization SAR images and corresponding reference winds, we created two subset wind speed databases: the training and testing subsets. From the training data subset, we retrieve ocean surface wind speeds (OSWSs) from different models at each polarization and compare with reference wind speeds. The RMSEs of SAR-retrieved wind speeds are: 2.5 m/s: 2.11 m/s (VH-polarized), 2.13 m/s (HV-polarized), 1.86 m/s (VV-polarized) and 2.26 m/s (HH-polarized) and the correlation coefficients are 0.86 (VH-polarized), 0.85(HV-polarized), 0.87(VV-polarized) and 0.83 (HH-polarized), which are statistically significant at the 99.9% significance level. Moreover, we found that OSWSs retrieved using C-2PO model at VH-polarized are most suitable for moderate-to-high winds while CMOD4 GMF at VV-polarized tend to be best for low-to-moderate winds. A hybrid wind retrieval model is put forward composed of the two models, C-2PO and CMOD4 and sets of SAR test data are used in order to establish an appropriate wind speed threshold, to differentiate the wind speed range appropriate for one model from that of the other. The results show that the OSWSs retrieved using our hybrid method has RMSE of 1.66 m/s and the correlation coefficient are 0.9, thereby significantly outperforming both the C-2PO and CMOD4 models.

scholarly journals Atmospheric Fronts along the East Coast of Taiwan Studied by ERS Synthetic Aperture Radar Images

2007 ◽  
Vol 64 (3) ◽  
pp. 922-937 ◽  
Author(s):  
Werner Alpers ◽  
Jen-Ping Chen ◽  
I-I. Lin ◽  
Chun-Chi Lien
Keyword(s):  
Synthetic Aperture Radar ◽  
East Coast ◽  
Sea Surface ◽  
Offshore Wind ◽  
Synthetic Aperture ◽  
Katabatic Wind ◽  
Land Breeze ◽  
Mountain Range ◽  
Synoptic Scale ◽  
Atmospheric Fronts

Abstract The existence of quasi-stationary alongshore atmospheric fronts typically located 30–70 km off the east coast of Taiwan is demonstrated by analyzing synthetic aperture radar (SAR) images of the sea surface acquired by the European Remote Sensing Satellites ERS-1 and ERS-2. For the data interpretation, cloud images from the Japanese Geostationary Meteorological Satellite GMS-4 and the American Terra satellite, rain-rate maps from ground-based weather radars, sea surface wind data from the scatterometer on board the Quick Scatterometer (QuikSCAT) satellite, and meteorological data from weather maps and radiosonde ascents have also been used. It is shown that these atmospheric fronts are generated by the collisions of the two airflows from opposing directions: one is associated with a weak easterly synoptic-scale wind blowing against the high coastal mountain range at the east coast of Taiwan and the other with a local offshore wind. At the convergence zone where both airflows collide, air is forced to move upward, which often gives rise to the formation of coast-parallel cloud bands. There are two hypotheses about the origin of the offshore wind. The first one is that it is a thermally driven land breeze/katabatic wind, and the second one is that it is wind resulting from recirculated airflow from the synoptic-scale onshore wind. Air blocked by the mountain range at low Froude numbers is recirculated and flows at low levels back offshore. Arguments in favor of and against the two hypotheses are presented. It is argued that both the recirculation of airflow and land breeze/katabatic wind contribute to the formation of the offshore atmospheric front but that land breeze/katabatic wind is probably the main cause.

German Bight Storminess over the Last Century

2020 ◽  
Author(s):  
Daniel Krieger ◽  
Oliver Krueger ◽  
Frauke Feser ◽  
Ralf Weisse ◽  
Birger Tinz ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
German Bight ◽  
Geostrophic Wind ◽  
Air Pressure ◽  
Offshore Wind ◽  
Pressure Data ◽  
Storm Activity ◽  
Wind Speeds ◽  
North East

<p>Assessing past storm activity provides valuable knowledge for economic and ecological sectors, such as the renewable energy sector, insurances, or health and safety. However, long time series of wind speed measurements are often not available as they are usually hampered by inhomogeneities due to changes in the surroundings of a measurement site, station relocations, and changes in the instrumentation. On the contrary, air pressure measurements provide mostly homogeneous time series as the air pressure is usually unaffected by such factors.</p><p>Therefore, we perform statistical analyses on historical pressure data measured at several locations within the German Bight (southeastern North Sea) between 1897 and 2018. We calculate geostrophic wind speeds from triplets of mean sea level pressure observations that form triangles over the German Bight. We then investigate the evolution of German Bight storminess from 1897 to 2018 through analyzing upper quantiles of geostrophic wind speeds, which act as a proxy for past storm activity. The derivation of storm activity is achieved by enhancing the established triangle proxy method via combining and merging storminess time series from numerous partially overlapping triangles in an ensemble-like manner. The utilized approach allows for the construction of robust, long-term and subdaily German Bight storminess time series. Further, the method provides insights into the underlying uncertainty of the time series.</p><p>The results show that storm activity over the German Bight is subject to multidecadal variability. The latest decades are characterized by an increase in activity from the 1960s to the 1990s, followed by a decline lasting into the 2000s and below-average activity up until present. The results are backed through a comparison with reanalysis products from four datasets, which provide high-resolution wind and pressure data starting in 1979 and offshore wind speed measurements taken from the FINO-WIND project. This study also finds that German Bight storminess positively correlates with storminess in the North-East Atlantic in general. In certain years, however, notably different levels of storm activity in the two regions can be found, which likely result from shifted large-scale circulation patterns.</p>

scholarly journals US East Coast synthetic aperture radar wind atlas for offshore wind energy

2020 ◽  
Vol 5 (3) ◽  
pp. 1191-1210 ◽  
Author(s):  
Tobias Ahsbahs ◽  
Galen Maclaurin ◽  
Caroline Draxl ◽  
Christopher R. Jackson ◽  
Frank Monaldo ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
East Coast ◽  
Offshore Wind ◽  
Synthetic Aperture ◽  
The Us ◽  
Wind Retrievals ◽  
Wind Resources ◽  
Us East Coast ◽  
Aperture Radar

Abstract. We present the first synthetic aperture radar (SAR) offshore wind atlas of the US East Coast from Georgia to the Canadian border. Images from RADARSAT-1, Envisat, and Sentinel-1A/B are processed to wind maps using the geophysical model function (GMF) CMOD5.N. Extensive comparisons with 6008 collocated buoy observations of the wind speed reveal that biases of the individual systems range from −0.8 to 0.6 m s−1. Unbiased wind retrievals are crucial for producing an accurate wind atlas, and intercalibration of the SAR observations is therefore applied. Wind retrievals from the intercalibrated SAR observations show biases in the range of to −0.2 to 0.0 m s−1, while at the same time improving the root-mean-squared error from 1.67 to 1.46 m s−1. The intercalibrated SAR observations are, for the first time, aggregated to create a wind atlas at the height 10 m a.s.l. (above sea level). The SAR wind atlas is used as a reference to study wind resources derived from the Wind Integration National Dataset Toolkit (WTK), which is based on 7 years of modelling output from the Weather Research and Forecasting (WRF) model. Comparisons focus on the spatial variation in wind resources and show that model outputs lead to lower coastal wind speed gradients than those derived from SAR. Areas designated for offshore wind development by the Bureau of Ocean Energy Management are investigated in more detail; the wind resources in terms of the mean wind speed show spatial variations within each designated area between 0.3 and 0.5 m s−1 for SAR and less than 0.2 m s−1 for the WTK. Our findings indicate that wind speed gradients and variations might be underestimated in mesoscale model outputs along the US East Coast.

scholarly journals US East Coast synthetic aperture radar wind atlas for offshore wind energy

2019 ◽  
Author(s):  
Tobias Ahsbahs ◽  
Galen Maclaurin ◽  
Caroline Draxl ◽  
Christopher Jackson ◽  
Frank Monaldo ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
East Coast ◽  
Mesoscale Model ◽  
Wrf Model ◽  
Offshore Wind ◽  
Synthetic Aperture ◽  
Wind Resources ◽  
Us East Coast ◽  
Aperture Radar

Abstract. We present the first synthetic aperture radar (SAR)-based offshore wind atlas of the US East Coast from Georgia to the Canadian border. Images from Radarsat-1, Envisat, Sentinel-1A, and Sentinel-1B are processed to wind maps using the Geophysical Model Function (GMF) CMOD5.N. Extensive comparisons with 6,008 collocated buoy observations revealed that biases of the individual system range from −0.8 to 0.6 m/s. Unbiased wind retrievals are crucial for producing an accurate wind atlas and intercalibration for correcting these biases by adjusting the normalized radar cross section is applied. The intercalibrated SAR observations show biases in the range of to −0.2 to 0.0 m/s, while at the same time improving the root mean squared error from 1.67 to 1.46 m/s. These intercalibrated SAR observations are, for the first time, aggregated to create a wind atlas. Monthly averages are used to correct artefacts from seasonal biases. The SAR wind atlas is used as a reference to study wind resources derived from the Weather Research and Forecasting (WRF) model. Comparisons focus on the spatial variation of wind resources and show that model results estimate lower coastal wind speed gradients than those from SAR. At sites designated for offshore wind development by the Bureau of Ocean Energy Management, mean wind speeds typically vary between 0.3 and 0.5 m/s for SAR and less than 0.2 m/s for the WRF model within each site. Findings indicate that wind speed gradients and variation might be underestimated in mesoscale model outputs along US East Coast.

scholarly journals Comparison of Synthetic Aperture Radar–Derived Wind Speeds with Buoy Wind Speeds along the Mountainous Alaskan Coast

2008 ◽  
Vol 47 (5) ◽  
pp. 1365-1376 ◽  
Author(s):  
C. M. Fisher ◽  
G. S. Young ◽  
N. S. Winstead ◽  
J. D. Haqq-Misra
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Global Model ◽  
Synthetic Aperture ◽  
Retrieval Models ◽  
Wind Speed Profile ◽  
Wind Speeds ◽  
The Impact ◽  
Aperture Radar

Abstract Satellite-borne synthetic aperture radar (SAR) offers the potential for remotely sensing surface wind speed both over the open sea and in close proximity to the coast. The resolution improvement of SAR over scatterometers is of particular advantage near coasts. Thus, there is a need to verify the performance of SAR wind speed retrieval in coastal environments adjacent to very complex terrain and subject to strong synoptic forcing. Mountainous coasts present a challenge because the wind direction values required for SAR wind speed retrieval algorithms cannot be obtained from global model analyses with as much accuracy there as over the open ocean or adjacent to gentle coasts where most previous SAR accuracy studies have been conducted. The performance of SAR wind speed retrieval in this challenging environment is tested using a 7-yr dataset from the mountainous coast of the Gulf of Alaska. SAR-derived wind speeds are compared with direct measurements from three U.S. Navy Oceanographic Meteorological Automatic Device (NOMAD) buoys. Both of the commonly used SAR wind speed retrieval models, CMOD4 and CMOD5, were tested, as was the impact of correcting the buoy-derived wind speed profile for surface-layer stability. Both SAR wind speed retrieval models performed well although there was some wind speed–dependent bias. This may be either a SAR wind speed retrieval issue or a buoy issue because buoys can underestimate winds as wind speed and thus sea state increase. The full set of tests is performed twice, once using wind directions from the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model analyses and once using wind direction observations from the buoys themselves. It is concluded that useful wind speeds can be derived from SAR backscatter and global model wind directions even in proximity to mountainous coastlines.

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