Automatic identification of weather systems from numerical weather prediction data using genetic algorithm

Wong, Ka Yan; Yip, Chi Lap; Li, Ping Wah

doi:10.1016/j.eswa.2007.07.032

Cited by 20 publications

(9 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, two methods of identifying fronts using static patterns were developed. The application of pattern recognition to identify frontal systems has been used with some success by identifying features such as ''stripes'' (e.g., Jann 2002) or segments of arcs (Wong et al 2008). However, given the strong climatological features of the region, a method to detect patterns specific to the SWWA has been developed here.…”

Section: Temperature Gradientmentioning

confidence: 99%

A Comparison of Automated Methods of Front Recognition for Climate Studies: A Case Study in Southwest Western Australia

Hope

Keay

Pook

et al. 2014

Monthly Weather Review

View full text Add to dashboard Cite

The identification of extratropical fronts in reanalyses and climate models is an important climate diagnostic that aids dynamical understanding and model verification. This study compares six frontal identification methods that are applied to June and July reanalysis data over the Central Wheatbelt of southwest Western Australia for . Much of the winter rainfall over this region originates from frontal systems. Five of the methods use automated algorithms. These make use of different approaches, based on shifts in 850-hPa winds (WND), gradients of temperature (TGR) and wet-bulb potential temperature (WPT), pattern matching (PMM), and a self-organizing map (SOM). The sixth method was a manual synoptic technique (MAN). On average, about 50% of rain days were associated with fronts in most schemes (although methods PMM and SOM exhibited a lower percentage). On a daily basis, most methods identify the same systems more than 50% of the time, and over the 28-yr period the seasonal time series correlate strongly. The association with rainfall is less clear. The WND time series of seasonal frontal counts correlate significantly with Central Wheatbelt rainfall. All automated methods identify fronts on some days that are classified as cutoff lows in the manual analysis, which will impact rainfall correlations. The front numbers identified on all days by the automated methods decline from 1979 to 2006 (but only the TGR and WPT trends were significant at the 10% level). The results here highlight that automated techniques have value in understanding frontal behavior and can be used to identify the changes in the frequency of frontal systems through time.

show abstract

Section: Temperature Gradientmentioning

confidence: 99%

A Comparison of Automated Methods of Front Recognition for Climate Studies: A Case Study in Southwest Western Australia

Hope

Keay

Pook

et al. 2014

Monthly Weather Review

View full text Add to dashboard Cite

show abstract

“…That said, once these meteorological events are categorized, the possibility of automatic ramp-event detection becomes feasible (e.g., Wong et al 2008). This suggests that future work should repeat this effort in other regions where high penetrations of distributed PV arrays are present, as these are the events most likely to cause widespread supply-demand balancing problems on the electrical grid.…”

Section: Discussionmentioning

confidence: 99%

“…For time scales greater than 1 min, the sites affected by a collective ramp event can be as far apart as 1000 km (Murata et al 2009). This manuscript uses applied meteorological methods to support the second option by categorizing the weather events associated with ramp events; this will allow for the future development of event climatologies and paves the way for developing forecasts of weather types that cause ramp events, possibly through automated weather pattern detection (Wong et al 2008) or statistical forecasting methods that operate with awareness of the prevailing weather pattern (Boland 2015). If a collective PV ramp event is experienced-that is, most PV arrays in a city simultaneously ramp up or ramp down-then the impact of distributed PV systems on grid stability is at a maximum during that period.…”

Section: A Literature Reviewmentioning

confidence: 99%

Categorizing the Meteorological Origins of Critical Ramp Events in Collective Photovoltaic Array Output

Wellby

Engerer²

2016

Journal of Applied Meteorology and Climatology

View full text Add to dashboard Cite

Photovoltaic (PV) solar power use is increasing globally. The Australian Capital Territory (ACT) has legislated a renewable energy target of 90% by 2020; to reach this target, use of distributed PV solar arrays is expected to increase. Cloud cover can cause the power output of PV installations to rapidly increase or decrease, resulting in ACT-wide collective ramp events. Accurate forecasts of when the ramp events will occur are needed for electricity providers to plan for these abrupt output changes and to ensure that electricity supplies remain stable. This paper categorizes the weather events that cause changes in the output of rooftop PV arrays in the ACT, providing a foundation for future PV output forecasting to be based on weather event identification. This paper identifies citywide collective ramp events, which occur when a 60% change in collective PV power output (with respect to the clear-sky potential) is experienced within 60 min. Such events are termed critical collective ramp events. Throughout the period between January 2012 and July 2014, 34 critical ramp events occurred. Eighteen of these events were positive collective ramp events, caused most frequently by Australian northwest cloud bands and radiation fog dissipation. Sixteen negative collective ramp events were recorded, and they were caused most frequently by the passage of cold fronts and thunderstorms. The categories developed herein will make it possible to improve short-term solar forecasting methods and to enable meteorologists to contribute to forecasting critical events.

show abstract

“…Among these, while the method proposed by Hu [9] can locate the approximate position of a trough and ridge meteorological system, it cannot extract the specific trough lines. Additionally, Wong's method [10] can only analyze the trough lines in the local region of interest. Therefore, the comparison is mainly made with ant colony theory-based [11], Douglas-Peucker algorithm-based [12] and principal curvature-based [14] methods.…”

Section: Comparison and Analysismentioning

confidence: 99%

“…Hu et al [9] utilized the vector rotation tracing method to conduct a contour analysis and determined the central location of synoptic systems, such as troughs and ridges, through the relationship between the characteristic points and their adjacent isobaric lines. Wong et al [10] identified low-pressure regions by defining a fitness function based on a genetic algorithm, and the adjacent curvature segment of the isobaric line was regarded as the characteristic trough line. Moreover, Mou et al [11] first identified the isobaric line in pressure field data through the edge detection algorithm and then analyzed the trough points and trough lines based on the ant colony algorithm.…”

Section: Introductionmentioning

confidence: 99%

Automatic Analysis of Trough Lines Based on Curvature Tracing

Huang

Yin

et al. 2018

Atmosphere

View full text Add to dashboard Cite

To solve the problems that arise in traditional automatic methods for trough line analysis with regard to low processing efficiency and analytical accuracy, an automatic method for trough line analysis was proposed in this study, comprising the following steps. Firstly, the curvature of contour lines was calculated using geopotential height field data to extract tracing start points, and candidate and non-candidate trough points were classified and recognized based on their curvature and relative positions. Afterwards, among the candidates, the eligible trough points were connected from tracing start point. Finally, the automatically analyzed trough lines were obtained after some post-processing steps. The experimental results indicate that the method is able to effectively identify meteorological trough lines, and that its performance is superior to some previous analysis methods of trough line in terms of analytical accuracy and processing speed.

show abstract

Automatic identification of weather systems from numerical weather prediction data using genetic algorithm

Cited by 20 publications

References 22 publications

A Comparison of Automated Methods of Front Recognition for Climate Studies: A Case Study in Southwest Western Australia

A Comparison of Automated Methods of Front Recognition for Climate Studies: A Case Study in Southwest Western Australia

Categorizing the Meteorological Origins of Critical Ramp Events in Collective Photovoltaic Array Output

Automatic Analysis of Trough Lines Based on Curvature Tracing

Contact Info

Product

Resources

About