Last week,
in the Proceedings of the National Academy of Sciences we published
a method for analysing recordbreaking extreme events in climate
time series, with applications to the global annualmean temperature
and to July temperatures in Moscow. Here we provide some supplementary
information on this paper.
Download
the paper
Regarding the application to Moscow,
our key finding was "an approximate 80% probability that the
2010 July heat record would not have occurred without climate warming".
As described in the paper, climate warming specifically refers to
the slow time evolution of the local July temperature as described
by a smooth nonlinear trend line, which reveals a significant climatic
warming over the last three decades. This trend curve is produced
from the monthly July values for 18812009 as described in the Methods
section of the paper and is made available for download here:
moscow_smooth.dat
(this file contains two columns: year and temperature in ºC)
We also provide the matlab code with which our Monte
Carlo simulations can easily be reproduced:
moscow_extremes.m
(note that running this code requires the above data file as well
as matlab)
By running this code it is found that the expected
number of heat records in the last decade (20002009) is 0.41. Since
in a stationary climate the expected number would be only 0.079,
the probability that a record in that decade is due to the climatic
change is found to be (0.410.079)/0.41, i.e. 81%.
A further discussion of the Moscow data used in the
paper was published at Realclimate: The
Moscow warming hole.
Also at Realclimate we discuss a tutorial example
that helps to understand the statistics: On
recordbreaking extremes.
