Effects of sea surface temperature accuracy on offshore wind resource assessment using a mesoscale model

Shimada, Shinichi; Ohsawa, Teruo; Kogaki, Tetsuya; Steinfeld, Gerald; Heinemann, Detlev

doi:10.1002/we.1796

Cited by 23 publications

(20 citation statements)

References 24 publications

(49 reference statements)

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“…In addition, wind speeds tend to be higher during the day than at night due to temperature gradients and this effect is intensified in summer. Current wind resources and capacity factors in Japan have also been estimated using meteorological models [16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Global Warming on Wind Energy Resources and Ramp Events in Japan

Ohba¹

2019

Atmosphere

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This study investigated the impact of global warming on Japanese wind energy resources and their short-term variations using the large ensemble d4PDF dataset, which consists of dynamically downscaled historical and +4K future climate projections. The capacity factor under the future and present climate was estimated from an idealized power curve based on hourly near-surface wind speeds. The +4K warming future climate projections showed significant changes in wind energy resources that varied both regionally and seasonally. The wind energy potential was projected to slightly increase (decrease) from winter to spring over northern (southern) Japan and decrease from summer to autumn over most of Japan. The projected annual production decreased by about ~5% over Japan in response to climate change. The frequency of wind ramp events also decreased in the latter seasons. The relationship to synoptic weather was investigated using self-organizing maps, whereby weather patterns (WPs) over the region in the present and future +4K climate were classified for a two-dimensional lattice. Future probabilistic projections of WPs under the global warming scenario showed both increases and decreases in the frequency of different WPs, with corresponding advantages and disadvantages for wind power generation with regard to future changes in capacity factors in Japan. The importance of these frequency changes on the total change was further assessed by separating the dynamical and thermodynamic contributions.

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Section: Introductionmentioning

confidence: 99%

The Impact of Global Warming on Wind Energy Resources and Ramp Events in Japan

Ohba¹

2019

Atmosphere

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“…Hiroyuki et al () run the RAMS model through 8 and 2 km resolution simulations to investigate wind energy potential over the area of Tokyo (Japan), and found good agreement with observations, with a 4.8% prediction error on annual mean wind speed. Rather good scores were also obtained by Shimada et al () in reproducing wind data for offshore wind resource assessment over Japan after applying MM5 and WRF models with 4.5 and 1.5 km resolutions. Guilherme et al () ran the WRF model to derive wind data for Portugal using 6 and 3 km resolution, obtaining model simulation winds slightly weaker (about 5%) than the measured data.…”

Section: Introductionmentioning

confidence: 99%

Aircraft wind measurements to assess a coupled WRF‐CALMET mesoscale system

Gioli

Gualtieri

Busillo³

et al. 2013

Meteorological Applications

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Long term aircraft observations of wind magnitude along an ∼250 km flight track in central Italy, performed over 1.5 years, are compared with the output of an existing mesoscale prognostic-diagnostic (WRF-CALMET) model chain aimed at assessing wind potential maps at regional scale. Aircraft measurements are used to evaluate model performance along spatial and temporal transects at moderate altitude from the ground (∼75 m), where observational frameworks are rarely available. Spatial wind analysis was capable of assessing overall model performance, while highlighting some limitations: the implemented models have better performance in inland areas with respect to coastal areas, while they are capable of representing diurnal variability in all regions correctly. Overall agreement is within 3% in the cold season and 16% in the warm season, while the greatest differences, above 30%, are obtained in coastal areas in the summer. The hypothesis supporting these results is that summer sea breeze regimes that develop consistently from the coast through the interior land are not entirely resolved from mesoscale modelling. Finally, the model performance and limitations related to complex orography are highlighted. This study demonstrates the added value that may derive from aircraft wind measurements as an additional observational framework for applied meteorology studies.

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“…This study used satellite-observed sea surface temperature for estimating changes in wind speed because temperature is one of the principal climate factors and satellite-observed sea surface temperature is able to estimate variations in winds, swells, and waves [23,24]. The sea surface temperatures are the optimum interpolation sea surface temperatures (OISST), as re-analysis data based on ships, buoys, and advanced, very high-resolution radiometer in satellites [25].…”

Section: Sea Surface Temperature Datamentioning

confidence: 99%

Offshore Wind Speed Forecasting: The Correlation between Satellite-Observed Monthly Sea Surface Temperature and Wind Speed over the Seas around the Korean Peninsula

Kim

Kang

2017

Energies

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Abstract:Wind power forecasting is a key role for large-scale wind power penetration on conventional electric power systems by understanding stochastic nature of winds. This paper proposes an empirical statistical model for forecasting monthly offshore wind speeds as a function of remotely sensed sea surface temperatures over the seas around the Korean Peninsula. The model uses the optimal lagged multiple linear regression method, and predictors are characterized by mixed periodicities derived from the autocorrelation between spatially variable satellite-observed sea surface temperatures and wind speeds at all grid points over a period of about ten years (2001 to 2008). Offshore wind speeds were found to be correlated with sea surface temperatures within a seasonal range of two-to four-month lags. In particular, offshore wind speeds were closely associated with the sea surface temperature at lag 4 M, followed by lag 3 M and lag 2 M. Correlation is less at lag 1 M as compared lag 2 M, lag 3 M and lag 4 M. The results demonstrate that this approach successfully produces accurate depictions of monthly wind speeds at the gridded network. The hindcast offshore wind speeds and wind power density showed slightly improved skills compared to the seasonally varying climatology with the value of root-mean square errors, +18% and +23%, respectively. The spatial distributions of the monthly gridded wind speed and wind power density remained fairly stable from one month to another, whereas individual regions displayed slight differences in variability. The results of this study are expected to be useful in establishing guidelines for operating and managing nascent offshore farms around the Korean Peninsula.

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Effects of sea surface temperature accuracy on offshore wind resource assessment using a mesoscale model

Cited by 23 publications

References 24 publications

The Impact of Global Warming on Wind Energy Resources and Ramp Events in Japan

The Impact of Global Warming on Wind Energy Resources and Ramp Events in Japan

Aircraft wind measurements to assess a coupled WRF‐CALMET mesoscale system

Offshore Wind Speed Forecasting: The Correlation between Satellite-Observed Monthly Sea Surface Temperature and Wind Speed over the Seas around the Korean Peninsula

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