Sensitivity of Tropospheric and Stratospheric Temperature Trends to Radiosonde Data Quality

Abstract

Radiosonde data have been used, and will likely continue to be used, for the detection of temporal trends in tropospheric and lower-stratospheric temperature. However, the data are primarily operational observations, and it is not clear that they are of sufficient quality for precise monitoring of climate change. This paper explores the sensitivity of upper-air temperature trend estimates to several data quality issues. Many radiosonde stations do not have even moderately complete records of monthly mean data for the period 1959-95. In a network of 180 stations (the combined Global Climate Observing System Baseline Upper-Air Network and the network developed by J. K. Angell), only 74 stations meet the data availability requirement of at least 85% of nonmissing months of data for tropospheric levels (850-100 hPa). Extending into the lower stratosphere (up to 30 hPa), only 22 stations have data records meeting this requirement for the same period, and the 30-hPa monthly data are generally based on fewer daily observations than at 50 hPa and below. These networks show evidence of statistically significant tropospheric warming, particularly in the Tropics, and stratospheric cooling for the period 1959-95. However, the selection of different station networks can cause network-mean trend values to differ by up to 0.1 K decade Ϫ1. The choice of radiosonde dataset used to estimate trends influences the results. Trends at individual stations and pressure levels differ in two independently produced monthly mean temperature datasets. The differences are generally less than 0.1 K decade Ϫ1 , but in a few cases they are larger and statistically significant at the 99% confidence level. These cases are due to periods of record when one dataset has a distinct bias with respect to the other. The statistical method used to estimate linear trends has a small influence on the result. The nonparametric median of pairwise slopes method and the parametric least squares linear regression method tend to yield very similar, but not identical, results with differences generally less than Ϯ0.03 K decade Ϫ1 for the period 1959-95. However, in a few instances the differences in stratospheric trends for the period 1970-95 exceed 0.1 K decade Ϫ1. Instrument changes can lead to abrupt changes in the mean, or change-points, in radiosonde temperature data records, which influence trend estimates. Two approaches to removing change-points by adjusting radiosonde temperature data were attempted. One involves purely statistical examination of time series to objectively identify and remove multiple change-points. Methods of this type tend to yield similar results about the existence and timing of the largest change-points, but the magnitude of detected change-points is very sensitive to the particular scheme employed and its implementation. The overwhelming effect of adjusting time series using the purely statistical schemes is to remove the trends, probably because some of the detected change-points are not spurious signals but represent real atmosphe...

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