First some background for our readers that may not be familiar with the term “random walk”
New Paper “Random Walk Lengths Of About 30 Years In Global Climate” By Bye Et Al 2011
There is a new paper [h/t to Ryan Maue and Anthony Watts] titled
Bye, J., K. Fraedrich, E. Kirk, S. Schubert, and X. Zhu (2011), Random walk lengths of about 30 years in global climate, Geophys. Res. Lett., doi:10.1029/2010GL046333, in press. (accepted 7 February 2011)
The abstract reads [highlight added]
“We have applied the relation for the mean of the expected values of the maximum excursion in a bounded random walk to estimate the random walk length from time series of eight independent global mean quantities (temperature maximum, summer lag, temperature minimum and winter lag over the land and in the ocean) derived from the NCEP twentieth century reanalysis (V2) (1871-2008) and the ECHAM5 IPCC AR4 twentieth century run for 1860-2100, and also the Millenium 3100 yr control run mil01, which was segmented into records of specified period. The results for NCEP, ECHAM5 and mil01 (mean of thirty 100 yr segments) are very similar and indicate a random walk length on land of 24 yr and over the ocean of 20 yr. Using three 1000 yr segments from mil01, the random walk lengths increased to 37 yr on land and 33 yr over the ocean. This result indicates that the shorter records may not totally capture the random variability of climate relevant on the time scale of civilizations, for which the random walk length is likely to be about 30 years. For this random walk length, the observed standard deviations of maximum temperature and minimum temperature yield respective expected maximum excursions on land of 1.4 and 0.5 C and over the ocean of 2.3 and 0.7 C, which are substantial fractions of the global warming signal.”
The text starts with
“The annual cycle is the largest climate signal, however its variability has often been overlooked as a climate diagnostic, even though global climate has received intensive study in recent times, e.g. IPCC (2007), with a primary aim of accurate prediction under global warming.”
We agree with the authors of the paper on this statement. This is one of the reasons we completed the paper
Herman, B.M. M.A. Brunke, R.A. Pielke Sr., J.R. Christy, and R.T. McNider, 2010: Global and hemispheric lower tropospheric temperature trends. Remote Sensing, 2, 2561-2570; doi:10.3390/rs2112561
where our abstract reads
“Previous analyses of the Earth’s annual cycle and its trends have utilized surface temperature data sets. Here we introduce a new analysis of the global and hemispheric annual cycle using a satellite remote sensing derived data set during the period 1979–2009, as determined from the lower tropospheric (LT) channel of the MSU satellite. While the surface annual cycle is tied directly to the heating and cooling of the land areas, the tropospheric annual cycle involves additionally the gain or loss of heat between the surface and atmosphere. The peak in the global tropospheric temperature in the 30 year period occurs on 10 July and the minimum on 9 February in response to the larger land mass in the Northern Hemisphere. The actual dates of the hemispheric maxima and minima are a complex function of many variables which can change from year to year thereby altering these dates.
Here we examine the time of occurrence of the global and hemispheric maxima and minima lower tropospheric temperatures, the values of the annual maxima and minima, and the slopes and significance of the changes in these metrics. The statistically significant trends are all relatively small. The values of the global annual maximum and minimum showed a small, but significant trend. Northern and Southern Hemisphere maxima and minima show a slight trend toward occurring later in the year. Most recent analyses of trends in the global annual cycle using observed surface data have indicated a trend toward earlier maxima and minima.”
The 2011 Bye et al GRL paper conclusion reads
“In 1935, the International Meteorological Organisation confirmed that ‘climate is the average weather’ and adopted the years 1901-1930 as the ‘climate normal period’. Subsequently a period of thirty years has been retained as the classical period of averaging (IPCC 2007). Our analysis suggests that this administrative decision was an inspired guess. Random walks of length about 30 years within natural variability are an ‘inconvenient truth’ which must be taken into account in the global warming debate. This is particularly true when the causes of trends in the temperature record are under consideration.”
This paper is yet another significant contribution that raises further issues on the use of multi-decadal linear surface temperature trends to diagnose climate change.