Abstract
Understanding errors in surface air temperature (SAT) data and related uncertainties is crucial for climate studies because of their impact on the accuracy of statistical inferences in scientific conclusions. In recent decades, considerable research has focused on the trends and evolution of SAT on the Tibetan Plateau (TP). However, assessment of the uncertainties in SAT change on the TP has not been done adequately, which is of considerable importance for climate research. Using station-observed SAT data from the TP, this study estimates long-term variations and trends of sampling error variances in gridded monthly SAT data over recent decades. Results revealed large sampling error variances in northern and western parts of the TP but small variances in eastern, southern, and central areas. The sampling error variances also exhibited strong monthly variations with maximum errors in winter and minimum values in summer. Furthermore, spatial distributions of the trends of seasonal and annual mean sampling error variances were found distributed unevenly with decreasing trends found mainly in central and southern parts of the TP and increasing trends in northeastern, southeastern, and northwestern areas. Additionally, differences were also found in the trends of seasonal and annual mean sampling error variances on various timescales.
Highlights
Large numbers of applications and studies require information concerning the errors in surface air temperature (SAT) datasets for estimation of the relevant uncertainties and for reaching meaningful and accurate conclusions regarding climate change [1,2,3,4]
Uncertainties in observation data can be classified into three groups: (1) observational error, the uncertainties due to station data quality; (2) sampling error, the uncertainties in a grid box mean caused by estimating the mean from a small number of point values; and (3) temporal interpolation error, the uncertainties associated with filling gaps in the station data record [3,8]
As a first step in addressing this problem, we recently investigated the sampling error variances in SAT on the Tibetan Plateau (TP) [11]
Summary
Large numbers of applications and studies require information concerning the errors in surface air temperature (SAT) datasets for estimation of the relevant uncertainties and for reaching meaningful and accurate conclusions regarding climate change [1,2,3,4] Such information is critical in assessment of the optimal global or regional average SAT time series, linear trend, and ranking of extreme climate records [5,6,7]. Our previous work focused mainly on the impact of the sampling error on the regional average SAT time series of the TP rather than the variational characteristics of the sampling error itself These issues are important in relation to research and understanding of climate change over the TP, they are yet to be assessed and quantified fully.
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