Application of Self-organizing Maps to classify the meteorological origin of wind gusts in Australia

Spassiani, Alessio; Mason, Matthew S.

doi:10.1016/j.jweia.2021.104529

Cited by 19 publications

(12 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The SOM is a clustering method that projects highdimensional data to a visually comprehensible, twodimensional map. It provides a spatially organized set of patterns of data variability and has been widely used in atmospheric sciences (e.g., Ohba et al, 2018;Song et al, 2019;Spassiani and Mason, 2021). In this study, we apply SOM to recognize patterns of wind speed forecast anomalies and corresponding IC uncertainties.…”

Section: Som Analysismentioning

confidence: 99%

Local-thermal-gradient and large-scale-circulation impacts on turbine-height wind speed forecasting over the Columbia River Basin

2022

View full text Add to dashboard Cite

Abstract. We investigate the sensitivity of turbine-height wind speed forecast to initial condition (IC) uncertainties over the Columbia River Gorge (CRG) and Columbia River Basin (CRB) for two typical weather phenomena, i.e., local-thermal-gradient-induced marine air intrusion and a cold frontal passage. Four types of turbine-height wind forecast anomalies and their associated IC uncertainties related to local thermal gradients and large-scale circulations are identified using the self-organizing map (SOM) technique. The four SOM types are categorized into two patterns, each accounting for half of the ensemble members. The first pattern corresponds to IC uncertainties that alter the wind forecast through a modulating weather system, which produces the strongest wind anomalies in the CRG and CRB. In the second pattern, the moderate uncertainties in local thermal gradient and large-scale circulation jointly contribute to wind forecast anomaly. We analyze the cross section of wind and temperature anomalies through the gorge to explore the evolution of vertical features of each SOM type. The turbine-height wind anomalies induced by large-scale IC uncertainties are more concentrated near the front. In contrast, turbine-height wind anomalies induced by the local IC thermal uncertainties are found above the surface thermal anomalies. Moreover, the wind forecast accuracy in the CRG and CRB is limited by IC uncertainties in a few specific regions, e.g., the 2 m temperature within the basin and large-scale circulation over the northeast Pacific around 140∘ W.

show abstract

Section: Som Analysismentioning

confidence: 99%

Local-thermal-gradient and large-scale-circulation impacts on turbine-height wind speed forecasting over the Columbia River Basin

2022

View full text Add to dashboard Cite

show abstract

“…3 Threshold selection algorithm Some storm separation methods are based on the classification of events belonging to very large wind datasets, without giving detailed meteorological descriptions of the events due to the prohibitive cost of that process when using long data series. For example, Spassiani and Mason [29] proposed selforganizing maps that utilise wind gust speed, temperature and pressure data to automate the classification of convective and non-convective events. Holmes [39] classified wind gusts as synoptic or non-synoptic based on the ratio of the wind gust speed (during the event) to the mean wind speed during the twohour time frame either before or after the event time.…”

Section: Generalised Pareto Distribution and Average Recurrence Intervalmentioning

confidence: 99%

“…Quality-controlled daily peak wind gust data recorded by 29 different Automatic Weather Stations (AWS) located across NSW, for available data up to the end of 2021, were obtained from the Bureau of Meteorology (BOM) and used to model and map the frequency, average recurrence interval (ARI) and direction of extreme gusts. Since extreme gusts generated by different mechanisms can follow different probability distributions, extreme gust events are separated here into different associated storm types, as done in [18,29]. While the in-situ data are the most accurate and reliable gust measurements, a limitation of using them is that many gusts will be missed even within areas of relatively good sampling.…”

Section: Introductionmentioning

confidence: 99%

Analysis and characterisation of extreme wind gust hazards in New South Wales, Australia

Rafei

Sherwood

Evans

et al. 2022

Preprint

View full text Add to dashboard Cite

Extreme wind gusts cause major socioeconomic damage, and the rarity and localised nature of those events make their analysis challenging by either modelling or empirical approaches. Data from 29 automatic weather stations located in New South Wales (eastern Australia), with a maximum data range of 1998-2021, are used to study the distribution, frequency and average recurrence intervals (ARIs) of extreme gusts via a peaks-over-threshold approach. We distinguish between gust events generated by synoptic phenomena (e.g., cyclones and frontal systems), hereafter called ”synoptic events” and convective phenomena (i.e., thunderstorms), hereafter called ”convective events”, using the wind time series. For synoptic events the results show a gradient in the frequencies of gusts > 25 m/s that decreases when going inland from the coast, in contrast to the case for convective events which are more uniformly distributed geographically and have higher occurrence frequencies for extremes across nearly all inland locations. The ARI analysis shows that at inland locations extreme wind gusts are dominated by convective events, whereas coastal stations have similar frequencies of both types at low ARIs but again a dominance of convective events at the highest ARIs. Wind direction was also investigated and extreme gusts were found to be predominantly westerly at inland locations, with more variable direction for convective than synoptic events, and southerlies at coastal stations. This study confirms the dominant role of thunderstorms in producing the most extreme gusts in the region, and shows that wind risk varies strongly with distance from the coast.

show abstract

“…The SOM is a clustering method that projects high-dimensional data to a visually comprehensible, two-dimensional map. It provides a spatially organized set of patterns of data variability and has been widely used in atmospheric sciences (e.g., Ohba et al, 2018;Song et al, 2019;Spassiani and Mason, 2021). In this study, we apply SOM to recognize patterns of wind speed forecast anomalies and corresponding IC uncertainties.…”

Section: Som Analysismentioning

confidence: 99%

Local thermal gradient and large-scale circulation impacts on turbine-height wind speed forecasting over the Columbia Basin

Liu

Qian

Berg

2021

Preprint

View full text Add to dashboard Cite

Abstract. We investigate the sensitivity of turbine-height wind speed forecast to initial condition (IC) uncertainties over the Columbia River Gorge (CRG) and Columbia River Basin (CRB) for two typical weather phenomena, i.e., local thermal gradient induced marine air intrusion and a cold frontal passage. Four types of turbine-height wind forecast anomalies and their associated IC uncertainties related to local thermal gradients and large-scale circulations are identified using the self-organizing map (SOM) technique. The four SOM types are categorized into two patterns, each accounting for half of the ensemble members. The first pattern corresponds to IC uncertainties that alter the wind forecast through modulating weather system, which produces the strongest wind anomalies in the CRG and CRB. In the second pattern, the moderate local thermal gradient and large-scale circulation uncertainties jointly contribute to wind forecast anomaly. We analyze the cross-section of wind and temperature anomalies through the gorge to explore the evolution of vertical features of each SOM type. The turbine-height wind anomalies induced by large-scale IC uncertainties are more concentrated near the front. In contrast, turbine-height wind anomalies induced by the local IC thermal uncertainties are found above the surface thermal anomalies. Moreover, the wind forecast accuracy in the CRG and CRB are limited by IC uncertainties in a few specific regions, e.g., the 2-m temperature within the basin and large-scale circulation over the northeast Pacific around 140° W.

show abstract

Application of Self-organizing Maps to classify the meteorological origin of wind gusts in Australia

Cited by 19 publications

References 38 publications

Local-thermal-gradient and large-scale-circulation impacts on turbine-height wind speed forecasting over the Columbia River Basin

Local-thermal-gradient and large-scale-circulation impacts on turbine-height wind speed forecasting over the Columbia River Basin

Analysis and characterisation of extreme wind gust hazards in New South Wales, Australia

Local thermal gradient and large-scale circulation impacts on turbine-height wind speed forecasting over the Columbia Basin

Contact Info

Product

Resources

About