Climate trends on the extreme winds in Brazil

Pes, Marcelo P.; Pereira, Enio Bueno; Marengo, José A.; Martins, Fernando Ramos; Heinemann, Detlev; Schmidt, Michael

doi:10.1016/j.renene.2016.12.101

Cited by 42 publications

(24 citation statements)

References 7 publications

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“…Positive and negative geographic trends exist across portions of northeastern and southeastern Brazil of the lowest 5 and 25% quantiles (Figures 5(a) and (b)). This finding is supported by Pes et al (2017), who documented that weather stations located along the coast of Brazil showed changes in minimum wind speeds between 1947 and 2014. A gradual spatial expansion of wind trend magnitudes is detected with the largest changes occurring among the upper quantile wind speeds (i.e.…”

Section: Linear Trend Analysissupporting

confidence: 64%

“…The high frequency of low wind speeds observed by INMET sites could also be influencing the overall seasonal and annual distribution. Pes et al (2017) identified data quality issues when examining minimum and maximum surface wind trends across Brazil between 1947 and 2014.…”

Section: Wind Climatologymentioning

confidence: 99%

“…Much of Brazilian research conducted since Silva et al (2010) has focused on assessing changes in surface winds with respect to present and future wind energy production (Lucena et al, 2010;Pereira et al, 2013;Santos and Silva, 2013;Pes et al, 2017). Lucena et al (2010) showed that future wind energy production should increase for coastal * Correspondence to: J. M. Gilliland, Department of Geography and Anthropology, Louisiana State University, 227 Howe-Russell-Kniffen Geoscience Complex, 70803 Baton Rouge, Louisiana, USA.…”

Section: Introductionmentioning

confidence: 99%

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Surface wind speed: trend and climatology of Brazil from 1980–2014

Gilliland

Keim

2017

Intl Journal of Climatology

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This study examines the spatial and temporal surface (10 m) wind speed trend characteristics of Brazil during 1980-2014 using two in situ and three climate reanalysis datasets. Nonparametric regression is used to understand how mean seasonal and annual wind speeds change over space and time across Brazil. Overall temporal linear trends show that station and reanalysis products exhibit varying seasonal and annual wind speed trends. A geographic examination displays statistically significant (P < 0.05) positive (negative) mean wind speed trends for equatorial (southeastern and central) Brazil. Quantile regression is performed to interpret how wind speed changed across different percentiles. Results show that the largest positive and negative spatial wind speed trends occur for the upper percentiles (75 and 95%). The spatial and temporal trends and correlations described could be interconnected to possible changes developing with the location of Intertropical Convergence Zone and South Atlantic Anticyclone over the study region. Results have implications for optimizing renewable wind energy production and development across Brazil.

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Section: Linear Trend Analysissupporting

confidence: 64%

Section: Wind Climatologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Surface wind speed: trend and climatology of Brazil from 1980–2014

Gilliland

Keim

2017

Intl Journal of Climatology

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“…The statistical significance of annual sustained and gust HWEs and mean direction were tested using Mann–Kendall test (Mann, ; Kendall, ) and Sen's slope (Sen, ). These nonparametric regression tests were selected based on the distribution of the data and previous applications used to study extreme near‐surface winds (e.g., Hundecha et al ., ; Pes et al ., ; Gilliland and Keim, ).…”

Section: Methodsmentioning

confidence: 99%

A climatology of high‐wind events for the eastern United States

Gilliland

Black

Durkee

et al. 2019

Intl Journal of Climatology

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This study examines the spatial and temporal characteristics of high‐wind events (HWEs) based on the National Weather Service high‐wind criteria for 391 first‐order weather stations in the eastern United States from 1973 to 2015. A geographical analysis on the frequency of sustained and gust HWEs shows that the highest occurrences were reported in the Great Plains and Great Lakes, while the lowest number of observations occurred in the Mid‐South and Southeast. Linear trends show that the yearly frequency of sustained and gust HWEs are significantly decreasing (−0.579 days/year) and increasing (0.943 days/year) respectively during the 43‐year study period. These trends do not persist when the HWE data are normalized (long‐term mean is removed from the yearly count), but shows a cyclical anomaly pattern for both sustained and gust winds. Overall, 90 and 82% of all sustained and gust HWEs occur from the northwest or southwest quadrant, but when interpreted from a spatial perspective the mean wind direction of HWEs can be classified into specific regional wind groupings. However, this persistent southwesterly wind direction has gradually shifted to a more southerly (northerly) orientation for sustained (gust) HWEs over the study period.

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“…Often theoretical distributions are used to describe the long-term gust climate. In several studies the two-parameter Gumbel distribution (Gu) was applied to capture extreme x characteristics [15][16][17][18]. The three-parameter Generalized Extreme Value distribution (GEV) and Gu were used for extreme x value estimation in China [8].…”

Section: Introductionmentioning

confidence: 99%

Global Gust Climate Evaluation and Its Influence on Wind Turbines

et al. 2017

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Strong gusts negatively affect wind turbines in many ways. They (1) harm their structural safety; (2) reduce their wind energy output; and (3) lead to a shorter wind turbine rotor blade fatigue life. Therefore, the goal of this study was to provide a global assessment of the gust climate, considering its influence on wind turbines. The gust characteristics analyzed were: (1) the gust speed return values for 30, 50 and 100 years; (2) the share of gust speed exceedances of cut-out speed; and (3) the gust factor. In order to consider the seasonal variation of gust speed, gust characteristics were evaluated on a monthly basis. The global monthly wind power density was simulated and geographical restrictions were applied to highlight gust characteristics in areas that are generally suitable for wind turbine installation. Gust characteristics were computed based on ERA-interim data on a 1 • × 1 • spatial resolution grid. After comprehensive goodness-of-fit evaluation of 12 theoretical distributions, Wakeby distribution was used to compute gust speed return values. Finally, the gust characteristics were integrated into the newly developed wind turbine gust index. It was found that the Northeastern United States and Southeast Canada, Newfoundland, the southern tip of South America, and Northwestern Europe are most negatively affected by the impacts of gusts. In regions where trade winds dominate, such as eastern Brazil, the Sahara, southern parts of Somalia, and southeastern parts of the Arabian Peninsula, the gust climate is well suitable for wind turbine installation.

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Climate trends on the extreme winds in Brazil

Cited by 42 publications

References 7 publications

Surface wind speed: trend and climatology of Brazil from 1980–2014

Surface wind speed: trend and climatology of Brazil from 1980–2014

A climatology of high‐wind events for the eastern United States

Global Gust Climate Evaluation and Its Influence on Wind Turbines

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