The self-organizing map in synoptic climatological research

Sheridan, Scott C.; Lee, Cameron C.

doi:10.1177/0309133310397582

Cited by 182 publications

(182 citation statements)

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“…SOM is a clustering algorithm with growing use in synoptic and statistical climatology and statistical downscaling (Sheridan and Lee 2011). Perhaps the greatest advantage of SOM is the ability to take advantage of the built-in topological constraints (similar nodes are "close" to each other in data space) to visualize a continuum of atmospheric states in a visual two dimensional "SOM map".…”

Section: Discussionmentioning

confidence: 99%

“…SOM, an artificial neural net-based method of topologically-sensitive clustering (Kohonen 2001), is often used in synoptic climatology for identifying large-scale synoptic circulation patterns (Hewitson and Crane 2002;Sheridan and Lee 2011). SOM is visualized as an array of data archetypes or nodes, which represents a nonlinear two dimensional mapping of circulation types.…”

Section: Som Of Circulation Patternsmentioning

confidence: 99%

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Interannual rainfall variability and SOM-based circulation classification

et al. 2017

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synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained variance, is consistent with the general understanding of the dominant processes and atmospheric variables that affect rainfall variability at a particular location. Keywords SOM · Synoptic circulation · Rainfall variability · Southern AfricaThe relationship between synoptic circulation and local expressions of climate is the foundation of synoptic climatology and traditionally underpins the process of interpretative weather forecasting. The basic premise of synoptic climatology is that the large-scale atmospheric circulation exerts some control over weather and related environmental phenomena at the Earth's surface, thereby providing a level of deterministic forcing which influences the local weather. This directly leads to the use of atmospheric circulation patterns as a means to express drivers of weather (and climate) variability. Self-Organizing Maps (SOM, Kohonen 2001) is a pattern clustering method that is used as one of the methods to derive synoptic circulation types in this and other contexts, including statistical downscaling (e.g. Hewitson and Crane 2006;Yin et al. 2011;Ohba et al. 2016) and process-based validation of GCMs (e.g. Brown et al. 2010;Finnis et al. 2009;Higgins and Cassano 2010).In the application of SOM to study climate variability, the evolution of synoptic drivers of weather is typically represented by progression through classes of daily synoptic states identified as SOM nodes. That progression Abstract Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disa...

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Section: Discussionmentioning

confidence: 99%

Section: Som Of Circulation Patternsmentioning

confidence: 99%

Interannual rainfall variability and SOM-based circulation classification

et al. 2017

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“…The 1454 wind components (2 components each at 727 locations) were first standardized and then subjected to an s-mode principal components analysis (PCA), with the resulting principal component scores (PCs) retained as the input data into the classification. Developed by Kohonen et al (1995), self-organizing maps (SOMs) are a clustering methodology increasingly employed by synoptic climatologists over the past two decades (e.g., Cavazos, 1999;Hewtison and Crane, 2002;Sheridan and Lee, 2011). Unlike traditional clustering methods, SOMs are able to order the resultant clusters (e.g., synoptic-scale wind patterns) onto a multi-dimensional plane, with similar clusters adjacently located in this 'SOM-space', and dissimilar patterns spaced further apart (Hewtison and Crane, 2002).…”

Section: Atmospheric Data Processing and Synoptic Classification Usinmentioning

confidence: 99%

“…Unlike traditional clustering methods, SOMs are able to order the resultant clusters (e.g., synoptic-scale wind patterns) onto a multi-dimensional plane, with similar clusters adjacently located in this 'SOM-space', and dissimilar patterns spaced further apart (Hewtison and Crane, 2002). This structure to the classification allows for a more intuitive visualization of circulation-based synoptic patterns and their impacts on any climate-related outcome (e.g., water clarity; Sheridan and Lee, 2011). For a detailed discussion on the use of the SOM methodology in synoptic climatology, please see Hewitson and Crane (2002) and Sheridan and Lee (2011).…”

Section: Atmospheric Data Processing and Synoptic Classification Usinmentioning

confidence: 99%

Water clarity patterns in South Florida coastal waters and their linkages to synoptic-scale wind forcing

Pirhalla¹,

Sheridan²,

Lee³

et al. 2017

Satell Oceanogr Meteorol

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Temporal variability in water clarity for South Florida’s marine ecosystems was examined through satellite-derived light attenuation (Kd) coefficients, in the context of wind- and weather patterns. Reduced water clarity along Florida’s coasts is often the result of abrupt wind-resuspension events and other exogenous factors linked to frontal passage, storms, and precipitation. Kd data between 1998 and 2013 were synthesized to form a normalized Kd index (KDI) and subsequently compared with Self Organizing Map (SOM)-based wind field categorizations to reveal spatiotemporal patterns and their inter-relationships. Kd climatological maximums occur from October through December along southern sections of the West Florida Shelf (WFS) and from January through March along the Florida Straits. Spatial clusters of elevated Kd occur along 3 spatial domains: central WFS, southern WFS, and Florida Straits near the Florida Reef Tract, where intra-seasonal variability is the highest, and clarity patterns are associated with transitional wind patterns sequenced with cyclonic circulation. Temporal wind transitions from southerly to northerly, typically accompanying frontal passages, most often result in elevated Kd response. Results demonstrate the potential of using synoptic climatological analysis and satellite indices for tracking variability in water clarity and other indicators related to biological health.

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“…As proven in this research topic, the use of circulation weather types' classifications is also becoming frequent to explore climate variability in regions outside Europe. Regarding methodologies, the use of nonlinear methods such as the self-organizing maps (Sheridan and Lee, 2011) is becoming popular, and the introduction of new methodologies, such as the merging weather types and Lagrangian transport presented in the research topic (e.g., Ramos et al, 2014a) is also expected.…”

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confidence: 99%

Circulation Weather types as a tool in atmospheric, climate and environmental research

2015

Frontiers Research Topics

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Classifications of circulation weather systems have a long history in meteorology and climatology. Starting with manual classifications (Hess and Brezowsky, 1952;Lamb, 1972) over specific regions of the globe, these tools (generally called "catalogs of synoptic types") were restricted mainly to weather forecasting and historical climate studies.In the last decades, the advance of computing resources and the availability of datasets have fostered the development of fast and objective methods that process large amounts of data. Many climatological studies and applications require these data to be as simplified as possible; this is often achieved by analyzing gridded datasets (usually sea level pressure or geopotential height at different levels), and grouping the data into a relatively small number of distinct categories. Since these types are based on meteorological fields observed at a specific instant, they are also called Eulerian classifications.Several classification methods of circulation weather types have been developed, and are currently used in a wide range of applications (Huth et al., 2008(Huth et al., , 2010Philipp et al., 2010). In addition, in 2002, Sheridan stated that the "Synoptic weather-typing, or the classification of weather conditions or patterns into categories, continues to be popular, and numerous methods have been developed over the past century" (Sheridan, 2002). The increasing interdisciplinary use of circulation weather types in Europe became clear when the European project "Harmonization and Applications of Weather Types Classifications for European Regions-COST733, " where a wide range of classification schemes for different spatial domains were developed and compared within the scope of distinct applications. (Huth et al

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The self-organizing map in synoptic climatological research

Cited by 182 publications

References 69 publications

Interannual rainfall variability and SOM-based circulation classification

Interannual rainfall variability and SOM-based circulation classification

Water clarity patterns in South Florida coastal waters and their linkages to synoptic-scale wind forcing

Circulation Weather types as a tool in atmospheric, climate and environmental research

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