A Study of the Internal Boundary Layer Generated at the Alcantara Space Center

Pires, Luciana Bassi Marinho; Fisch, Gilberto; Gielow, Ralf; Souza, Leandro Franco de; Avelar, Ana Cristina; Paula, Igor Braga de; Girardi, R.

doi:10.5923/s.ajee.201501.08

Cited by 7 publications

(7 citation statements)

References 35 publications

(49 reference statements)

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“…The predominant wind direction on the Irish west coast is eastward, flowing from the sea toward the land. Simulations of these type of flows have shown that for a moderate coastal slope, onshore wind speeds recorded in proximity of the shore can equate the wind speeds at sea just before reaching the coast (Bassi Marinho Pires et al, 2015). Following this principle, the wind speeds derived from satellite measurement were not scaled to the weather station terrain elevation but instead were considered as being in the same streamline and kept at the OCN product elevation of 10 m a.s.l.…”

Section: Coastal Weather Stationsmentioning

confidence: 99%

“…Several studies have already attempted to assess the offshore wind energy potential using spaceborne scatterometers, such as ERS-1, ERS-2, NSCAT, QuickSCAT and AS-CAT (Sánchez et al, 2007;Pimenta et al, 2008;Karagali et al, 2014;Bentamy and Croize-Fillon, 2014;Remmers et al, 2019). However, the grid spacing of these instruments is at best 12.5 km 2 , which prevents the assessment in coastal areas (0-20 km from the shore) and the study of fine submesoscale processes that can affect turbine yields and climate processes.…”

Section: Introductionmentioning

confidence: 99%

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Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland

Montera¹,

Remmers²,

Desmond³

et al. 2020

Wind Energ. Sci.

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Abstract. In this paper, surface wind speed and average wind power derived from Sentinel-1 Synthetic Aperture Radar Level 2 Ocean (OCN) product were validated against four weather buoys and three coastal weather stations around Ireland. A total of 1544 match-up points was obtained over a 2-year period running from May 2017 to May 2019. The match-up comparison showed that the satellite data underestimated the wind speed compared to in situ devices, with an average bias of 0.4 m s−1, which decreased linearly as a function of average wind speed. Long-term statistics using all the available data, while assuming a Weibull law for the wind speed, were also produced and resulted in a significant reduction of the bias. Additionally, the average wind power was found to be consistent with in situ data, resulting in an error of 10 % and 5 % for weather buoys and coastal stations, respectively. These results show that the Sentinel-1 Level 2 OCN product can be used to estimate the wind resource distribution, even in coastal areas. Maps of the average and seasonal wind speed and wind power illustrated that the error was spatially dependent, which should be taken into consideration when working with Sentinel-1 Synthetic Aperture Radar data.

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Section: Coastal Weather Stationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland

Montera¹,

Remmers²,

Desmond³

et al. 2020

Wind Energ. Sci.

View full text Add to dashboard Cite

show abstract

“…The most probable situation by far for the west coast of Ireland is that the wind is flowing from the sea towards the land. Simulations of these type of flows have shown that for a moderate coastal slope, onshore wind speeds recorded at proximity to the shore can equate the wind speeds at sea just before reaching the coast (Bassi Marinho Pires et al, 2015). Therefore, the wind speed derived from satellite measurements were not scaled to the altitude of the weather stations, but instead they were considered as being on the same streamline.…”

Section: Coastal Weather Stationsmentioning

confidence: 99%

Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland

Montera¹,

Remmers²,

Desmond³

et al. 2019

Preprint

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Abstract. In this paper, surface wind speed and average wind power derived from Sentinel-1 Synthetic Aperture Radar Level 2 OCN product were validated against four weather buoys and three coastal weather stations around Ireland. A total of 1544 match-up points was obtained over a two-year period running from May 2017 to May 2019. The match-up comparison showed that the satellite underestimated the wind speed compared to in situ devices, with an average bias of 0.4 m/s, which decreased linearly as a function of wind speed. Long-term statistics using all the available data, while assuming a Weibull law for the wind speed, were also produced and resulted in a significant reduction of the bias. Additionally, the average wind power was found to be consistent with in situ data, resulting in an error of 10 % and 5 % for weather buoys and coastal stations, respectively. These results showed that the Sentinel-1 Level 2 OCN product can be used to estimate the wind speed distribution, even in coastal areas. Maps of the average and seasonal wind speed and wind power illustrated that the error was spatially dependent, which should be taken into considerations when working with Sentinel-1 SAR data.

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“…In other approaches, the wind profile is directly used to estimate z 0 and d from wind measurements at different heights over a homogeneous surface from within the inertial sublayer. In their work, [52] estimated z 0 and d for cotton, orchards and desert covers from wind measures using the wind profile; [36] obtained z 0 and d from measures of different instruments; [5] calculated z 0 and d from wind measures and wind profile with radar in desert; [73] and [68] used anemometer measures at different heights for cliff coverage; [11] estimated z 0 and d from field measures in peatlands; [83] obtained z 0 and d from friction velocity (u ) measures using the wind profile; [13] used different measure equipment and compared results with other authors in desert; [67] presented a regression of data obtained with radio-wind probes in forest; [45] obtained d from simultaneous scintillation measurements at two heights. Both parameters can be estimated by solving the non-linear wind profile equations: see, e.g., [26] for seas and land, and [18] for forest canopy.…”

Section: Land Cover Databasesmentioning

confidence: 99%

Characterization of Geographical and Meteorological Parameters

Montero

Rodríguez

Oliver

2018

Wind Field and Solar Radiation Characterization and Forecasting

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This chapter is devoted to the introduction of some geographical and meteorological information involved in the numerical modeling of wind fields and solar radiation. Firstly, a brief description of the topographical data given by a Digital Elevation Model and Land Cover databases are provided. In particular, the Information System of Land Cover of Spain (SIOSE) is considered. The study is focused in the roughness length and the displacement height parameters that appear in the logarithmic wind profile, as well as in the albedo related to solar radiation computation. An extended literature review and characterization of both parameters are reported. Next, the concept of atmospheric stability is introduced from the Monin-Obukhov similarity theory to the recent revision of Zilitinkevich of the Neutral and Stable Boundary Layers (SBL). The latter considers the effect of the free-flow static stability and baroclinicity on the turbulent transport of momentum and of the Convective Boundary Layers (CBL), more precisely, the scalars in the boundary layer, as well as the model of turbulent entrainment. 2.1 Geographical data The main geographical information for wind and solar radiation modeling may be classified into two general databases, the topographical data related to the orography of the region to be studied and the land cover databases containing the information of the land uses. In this section, both are introduced.

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A Study of the Internal Boundary Layer Generated at the Alcantara Space Center

Cited by 7 publications

References 35 publications

Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland

Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland

Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland

Characterization of Geographical and Meteorological Parameters

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