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Eurasian October snow water equivalent: using self‐organizing maps to characterize variability and identify relationships to the MJO
Author(s) -
Henderson Gina R.,
Barrett Bradford S.,
South Kaitlyn
Publication year - 2017
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.4725
Subject(s) - madden–julian oscillation , climatology , snow , geopotential height , environmental science , teleconnection , atmospheric sciences , convection , geology , precipitation , el niño southern oscillation , geography , meteorology
Variability in October daily snow water equivalent (SWE) change using self‐organizing maps ( SOMs ) was explored in this study. In addition, connections between October Eurasian daily snow water equivalent change ( ΔSWE ) and the leading mode of atmospheric intra‐seasonal variability, the Madden–Julian Oscillation ( MJO ), were considered. Through this analysis, dipole and tripole patterns of daily ΔSWE over Eurasia were identified and were moderately negatively correlated to mid‐tropospheric geopotential height anomalies. Additionally, SOM nodes capturing over 91% of October days were found moderately correlated with at least one MJO phase. The majority of correlation coefficients with magnitude above 0.30 were found for MJO phases 4–7, indicating that tropical convective anomalies over the Indian Ocean and Maritime Continent have the most impact on October circulation and snow variability. Furthermore, MJO phases with above‐normal frequency were most often found in SOM nodes with positive correlations between their respective 500‐ hPa height anomalies, while MJO phases with below‐normal frequency were most often found in SOM nodes with negative correlations between their respective 500‐ hPa height anomalies. These correlation patterns provide additional evidence linking the MJO to Eurasian snow variability. These results highlight a new application of SOMs in identifying snow variability throughout Eurasia during the month of October, in addition to providing evidence for tropical modulation of the extratropics on the intra‐seasonal timescale.