Report 59: Statistical Significance
of Trends and Trend Differences in Layer-Average Atmospheric Temperature
Time Series.
B.D. Santer, J.J. Hnilo, T.M.L. Wigley, J.S. Boyle, D.J. Gaffen, D.
Nychka, D.E. Parker, and K.E. Taylor
August 2000, 19 pp.
This paper examines trend uncertainties in layer-average
free atmosphere temperatures arising from the use of different trend estimation
methods. It also considers statistical issues that arise in assessing the
significance of individual trends and of trend differences between data
sets. Possible causes of these trends are not addressed. We use data from
satellite and radiosonde measurements and from two reanalysis projects.
To facilitate intercomparison, we compute from reanalyses and radiosonde
data temperatures equilvalent to those from the satellite-based Microwave
Sounding Unit (MSU). We compare liner trends based on minimization of absolte
deviations (LA) and minimization of squared deviations (LS). Differences
are generally less the 0.05ºC/decade over 1959-1996. Over 1979-1993,
they exceed 0.10ºC/decade for lower tropospheric time series and 0.15ºC/decade
for the lower stratosphere. Trend fitting by the LA method can degrade
the lower-tropospheric trend agreenebt of 0.03ºC/decade (over 1979-1996)
previously reported for the MSU and radiosonde data. In assessing trend
significance we employ two methods to account for temporal autocorrelation
effects. With our perferred method, virtually none of the individual 1979-1993
trends in deep-lower tenperatures are significantly different from zero.
To examine trend differences between data sets we compute 95% confidence
intervals for individual trends and show that these overlap fir almost
all data sets considered. Confidence intervals for lower-tropospheric trends
encompass both zero and the model-projected trends due to athropogenic
effects. We also test the significance of a trend in d (t), the
times series of differences between a pair of data sets. Use of d (t)
removes
variability common to both time series and facilitates identification of
small trend differences. This more discerning test reveals that roughly
30% of the data set comparisons have significant differences in lower-tropospheric
trends, primarily related to differences in measurement system. Our study
gives empirical estimates os statistical uncertainties in recent atmospheric
temperature trends. These estimates and the simple significance testing
framework used here facilitate the interpretation of previous temperature
trend comparisons involving satellite, radiosonde, and reanalysis data
sets.