Drivers of extreme wind events in Mexico for windpower applications

Abstract

In this study, we use a k-mean clustering approach to investigate the weather patterns responsible for extreme wind speed events throughout Mexico using 40 years of the ERA-5 atmospheric reanalysis. Generally, we find a large geographical split between the weather patterns that generate the strongest winds across the country. The highest wind power production periods therefore occur at different times in different regions across the country. In the South, these are associated with cold surge events, where an anticyclone is present in the Gulf of Mexico resulting in a strong Northerly flow across the Isthmus of Tehuantepec. In the NorthEast , Easterly trade winds are responsible for the strongest wind events, whereas in the NorthWest , it is the proximity of the North Pacific High. However, the weakest winds and lowest power production periods occur at the same times for all stations with the exception of Baja California Sur, meaning that low wind power production may be unavoidable at these times. The El Niño Southern Oscillation is found to influence wind speeds at some locations across Mexico at sub-seasonal timescales. We report that statistically stronger wind speeds are observed during the Summer during El Niño months than during La Niña months for both sites in Chiapas and Oaxaca.

Wind-Ramp Predictability

“…These events generate wind ramps in the region of the FCOV station, when the wind is from the southeast. These events are similar to the weather patterns reported by Thomas et al (2020) [41], they are common from January to May and they contribute significantly to extreme winds. The winter wind ramps in CDCU station and FCOV mast are related, the passage of a frontal system over CDCU station tends to generate ramps in FCOV mast and vice versa.…”

Weather patterns in Southeast Asia: Relationship with tropical variability and heavy precipitation

“…Cluster analysis was then performed on the reduced phase space defined by the leading principal components. This methodology is conceptually similar to that followed by other previous studies (e.g., Cassou, 2008;Sáenz and Durán-Quesada, 2015;Neal et al, 2016;Thomas et al, 2020). This methodology has been applied ten times to construct three sets of patterns:…”

What do large‐scale patterns teach us about extreme precipitation over the Mediterranean at medium‐ and extended‐range forecasts?

“…Many recent studies have analysed these interactions between surface conditions and such atmospheric variables (e.g. cold spells and geopotential height at 500 hPa: Ferranti et al, 2018; wind power and geopotential height at 500 hPa: Grams et al, 2017; wind extremes and geopotential height at 500 hPa: Thomas et al, 2021; precipitation and weather patterns generated from multiple variables: Hoy et al, 2014).…”

“…Such a variable of reliable forecasting skill at the sub‐seasonal scale is the atmospheric flow variability in the lower and middle troposphere, usually depicted by large‐scale patterns over extended domains (Vitart, 2014; Lavaysse et al ., 2018). Many recent studies have analysed these interactions between surface conditions and such atmospheric variables (e.g., cold spells and geopotential height at 500 hPa: Ferranti et al ., 2018; wind power and geopotential height at 500 hPa: Grams et al ., 2017; wind extremes and geopotential height at 500 hPa: Thomas et al ., 2021; precipitation and weather patterns generated from multiple variables: Hoy et al ., 2014; precipitation and sea‐surface temperature: Rieger et al ., 2021).…”