OscillationIndices.md

In camposfa/ClimGrid: Read and analyze gridded climate data and global oscillation indices

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Utility functions for climate data

ClimGrid includes functions for pulling the most recent data for several large-scale climate oscillation indices from various online data repositories. Supported climate indices include:

• Niño 1+2 Monthly ERSSTv4 ("nino1.2")
• Niño 3 Monthly ERSSTv4 (""nino3")
• Niño 4 Monthly ERSSTv4 ("nino4")
• Niño 3.4 Monthly ERSSTv4 ("nino3.4")
• Southern Oscillation Index ("soi")
• Oceanic Niño Index ("oni"), same as 3-month running average in Niño 3.4
• Multivariate ENSO Index ("mei")
• Dipole Mode index ("dmi")
• Pacific Decadal Oscillation ("pdo")
• Atlantic Multidecadal Oscillation ("amo")
• North Atlantic Oscillation ("nao")
• Southern Annular Mode ("sam")

The function load_climate_index returns a named list of monthly climate index data. Each element of the list is an object of class dplyr::tbl_df.

  indices <- load_climate_index(c("nao", "mei"))

## Reading MEI data from http://www.esrl.noaa.gov/psd/enso/mei/table.html
## Reading NAO data from http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/norm.nao.monthly.b5001.current.ascii.table

  indices

## $mei
## Source: local data frame [789 x 3]
## 
##       date_of  value index
##        (time)  (dbl) (chr)
## 1  1950-01-01 -1.027   mei
## 2  1950-02-01 -1.149   mei
## 3  1950-03-01 -1.298   mei
## 4  1950-04-01 -1.081   mei
## 5  1950-05-01 -1.427   mei
## 6  1950-06-01 -1.391   mei
## 7  1950-07-01 -1.309   mei
## 8  1950-08-01 -1.057   mei
## 9  1950-09-01 -0.627   mei
## 10 1950-10-01 -0.402   mei
## ..        ...    ...   ...
## 
## $nao
## Source: local data frame [789 x 3]
## 
##       date_of value index
##        (time) (dbl) (chr)
## 1  1950-01-16  0.92   nao
## 2  1950-02-16  0.40   nao
## 3  1950-03-16 -0.36   nao
## 4  1950-04-16  0.73   nao
## 5  1950-05-16 -0.59   nao
## 6  1950-06-16 -0.06   nao
## 7  1950-07-16 -1.26   nao
## 8  1950-08-16 -0.05   nao
## 9  1950-09-16  0.25   nao
## 10 1950-10-16  0.85   nao
## ..        ...   ...   ...

Squash all the list elements together to a single tbl_df with dplyr::bind_rows:

  indices_df <- dplyr::bind_rows(indices)
  summary(indices_df)

##     date_of                        value             index          
##  Min.   :1950-01-01 00:00:00   Min.   :-3.18000   Length:1578       
##  1st Qu.:1966-06-04 18:00:00   1st Qu.:-0.67000   Class :character  
##  Median :1982-11-08 12:00:00   Median : 0.01450   Mode  :character  
##  Mean   :1982-11-08 01:06:36   Mean   : 0.01378                     
##  3rd Qu.:1999-04-12 06:00:00   3rd Qu.: 0.68925                     
##  Max.   :2015-09-16 00:00:00   Max.   : 3.04900

camposfa/ClimGrid documentation built on May 13, 2019, 11:02 a.m.