Daily atmospheric circulation catalogue for western Europe using multivariate techniques

Abstract

This study uses principal component analysis (PCA) and clustering (CL) techniques to characterize the daily surface synoptic circulation patterns over the region 30°N-60°N by 30°W-15°E, for the period 1960-2001 using the NCEP/NCAR Reanalysis Project data. The methodology used, previously proposed by Esteban et al. (2005) to identify heavy snowfall days over Andorra (Pyrenees), involves a pre-processing approach consisting of a spatial standardization of the data used for the rotated PCA on S-mode analysis and correlation matrix, and Varimax rotation of the retained components. For the clustering process, an alternative approximation based on the PCA results (positive and negative phases) to decide the centroids and the number of groups for the K-means clustering is shown, followed by the rejection of the iterations for this non-hierarchical algorithm. Twenty sea level pressure (SLP) circulation patterns were obtained, with all days classified. The composite maps for SLP and 500 hPa geopotential height (GPH), the monthly distribution, and the long-term variability for each of the circulation patterns is obtained. The results are consistent with the subjective knowledge of the daily atmospheric circulation over the area treated, and seem to be an easy and accessible way for the synoptic studies of short-lived (from weekly to daily) phenomena. In addition, this methodology appears to be applicable to all climatic areas of the world, as it characterizes well enough the complex circulation variability at mid-latitudes, including the surface low-pressure gradient patterns normally located over the Mediterranean in summer.

Meteorological Patterns Linked to Landslide Triggering in Asturias (NW Spain): A Preliminary Analysis

“…Obtained results point out the cyclonic patterns SAA and AD as the main cause of rainfall-triggered landslides in Asturias during the wet period, which is consistent with the results obtained for Western Europe [44]. SAA and AD patterns were identified in 75% of the events analysed between October and May, causing a total of 681 landslides.…”

Daily near-surface large-scale atmospheric circulation patterns over the wider Caribbean

“…Cluster analysis, unlike EOF's linear decomposition, is a nonlinear approach that identifies the dense aggregation of flow patterns around a few primary types, which entails, the "identification of the peaks of the probability density function" of the circulation or flow fields (Burlando 2009). Cluster analysis has been used to classify atmospheric circulation flows over the Svalbard region (Käsmacher and Schneider 2011), the Mediterranean Sea (Burlando 2009), northeastern Iberian Peninsula (Jiménez et al 2009), the Grand Canyon (Kaufmann and Whiteman 1999), Switzerland (Weber and Furger 2001), and over western Europe (Esteban et al 2006), as well as at single-point locations (Clifton and Lundquist 2012). The popular cluster analysis technique k-means (McQueen 1967) tends to produce circulation types for which the within cluster sum-of-squares variance is locally minimized rather than globally minimized.…”

Determination of the Jenkinson and Collison’s weather types for the western Mediterranean basin over the 1948-2009 period. Temporal analysis

“…It enables us to determine the main synoptic and surface circulation patterns, as well as at different tropospheric levels, based on extensive sea surface pressure and geopotential at 500 hPa and other levels databases, very often reanalysis, which cannot be processed manually (Huth et al, 2008;Esteban et al, 2006). However, multivariate analysis is not a totally objective process, but rather semi-objective, given that thresholds need to be established and that there is a need to choose from different options at different stages of application, such as establishment of the level of variance explained by the components, the number of synoptic types, the use of T or S modes, rotating or not the components obtained (with the choice in this case of the rotation method), using a hierarchical classification or not, etc.…”