Abstract
This study aims to examine the temporal impacts of atmospheric-oceanic patterns, on snow cover variations of the widest snow-prone zone in Iran (Central Alborz mountains \(\sim\)400,000 km2). For this purpose, the snow cover area was derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor images during 2000–2016 years. Thirty indices related to atmospheric-oceanic patterns were provided from the National Oceanic and Atmospheric Administration (NOAA) website. The strongest significant teleconnection effects occur with time lags. Atlantic Meridional Mode (AMM), North Pacific pattern (NP), Hurricane Activity (HA), Western Hemisphere Warm Pool (WHWP), Extreme Eastern ENSO (Niño [1 + 2]), and Eastern ENSO (Niño [3]), were the most effective signals on the snow cover variations in Central Alborz region. The AMM, HA, and WHWP indices, were the directly related ones with 2-, 4- and 4-month time lags, respectively. Indices NP, Niño (1 + 2), and Niño (3) were the inversely related signals and their most severe effects appeared after a 1-, 4-, and 4-month lags, respectively. A wavelet coherence analysis was also used for teleconnection investigation. It has illustrated that the mentioned time lags of these signals, have a significant 9–15-months period’ relation with snow cover variations, during the whole study years. In the following, the time lags of the indices were applied as inputs to forecast the snow cover area. The models including the least square support vector machine (LSSVM) and group method of data handling (GMDH) were utilized for this purpose. According to the values of normalized root mean square error (between 0.1 and 0.2) and Nash-Sutcliff (> 0.75), the GMDH had acceptable predictions, especially for long-term forecasting horizons (12- and 24-month-ahead). The applied input approach can have research value for forecasting snow cover area in other mountainous regions of the world, and also to reconstruct the snow data, in the years when satellite imagery was not available.
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Bahrami-Pichaghchi, H., Aghelpour, P. An estimation and multi-step ahead prediction study of monthly snow cover area, based on efficient atmospheric-oceanic dynamics. Clim Dyn 60, 743–765 (2023). https://doi.org/10.1007/s00382-022-06341-x
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DOI: https://doi.org/10.1007/s00382-022-06341-x