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The Asymmetric and Symmetric SAM indices are computed as the projection of geopotential height anomalies onto the zonally asymmetric and zonally symmetric parts of the SAM field. The detailed methodology can be found in Campitelli et al. (2022). The source of the data is https://www.cima.fcen.uba.ar/~elio.campitelli/asymsam/

Usage

download_asymsam_monthly(use_cache = FALSE, file = NULL)

download_asymsam_daily(levels = 700, use_cache = FALSE, file = NULL)

Arguments

use_cache

logical option to save and load from cache. If `TRUE`, results will be cached in memory if `file` is `NULL` or on disk if `file` is not `NULL`.

file

optional character with the full path of a file to save the data. If `cache` is `FALSE` but `file` is not `NULL`, the results will be downloaded from the internet and saved on disk.

levels

atmospheric levels in hPa to download. If "all" download all available levels. Available levels are: 1, 2, 3, 5, 7, 10, 20, 30, 50, 70, 100, 125, 150, 175, 200, 225, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 775, 800, 825, 850, 875, 900, 925, 950, 975 and 1000.

Value

  • Lev: Atmospheric level in hPa

  • Date: Date object that uses the first of the month as a placeholder. Date formatted as date on the first of the month because R only supports one partial of date time

  • Index: Type of index. Either "sam", "ssam" or "asam".

  • Value: Value of the index

  • Value_normalized: Value of the index normalized by the standard deviation of the index

  • R.squared: The variance explained by the index (only in the daily version)

References

Campitelli, E., Díaz, L. B., & Vera, C. (2022). Assessment of zonally symmetric and asymmetric components of the Southern Annular Mode using a novel approach. Climate Dynamics, 58(1), 161–178. https://doi.org/10.1007/s00382-021-05896-5

Examples

if (FALSE) {
asymsam <- download_asymsam_monthly()
}