loti: Global temperature anomalies

In gamclass: Functions and Data for a Course on Modern Regression and Classification

Global temperature anomalies

Description

GISS (Goddard Institute for Space Studies) Land-Ocean Temperature Index (LOTI) data for the years 1880 to 2019, giving anomalies in 0.01 degrees Celsius, from the 1951 - 1980 average.

Usage

loti

Format

A data frame with 140 observations on the following 19 variables.

Year

a numeric vector

Jan

a numeric vector

Feb

a numeric vector

Mar

a numeric vector

Apr

a numeric vector

May

a numeric vector

Jun

a numeric vector

Jul

a numeric vector

Aug

a numeric vector

Sep

a numeric vector

Oct

a numeric vector

Nov

a numeric vector

Dec

a numeric vector

JtoD

Jan-Dec averages

D.N

Dec-Nov averages

DJF

Dec-Jan-Feb averages

MAM

Mar-Apr-May

JJA

Jun-Jul-Aug

SON

Sept-Oct-Nov

JtoD2011

January to December average, from data accessed in 2011

Source

Data are the Combined Land-Surface Air and Sea-Surface Water Temperature Anomalies (Land-Ocean Temperature Index, LOTI), in 0.01 degrees Celsius, from https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.txt Data in the column JtoD2011 was accessed 2011-09-06.

Also available is a CSV file, with anomalies in degrees Celsius.

References

GISTEMP Team, 2020: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 2020-11-13 at https://data.giss.nasa.gov/gistemp/.

Examples

data(loti)
plot(JtoD ~ Year, data=loti)
## Add 11 point moving average
ma11 <- filter(loti$JtoD, rep(1,11)/11, sides=2)
lines(loti$Year, ma11)

gamclass documentation built on Aug. 21, 2023, 5:07 p.m.