contributor author | Xu, Cheng-Dong | |
contributor author | Wang, Jin-Feng | |
contributor author | Hu, Mao-Gui | |
contributor author | Li, Qing-Xiang | |
date accessioned | 2017-06-09T16:49:50Z | |
date available | 2017-06-09T16:49:50Z | |
date copyright | 2014/06/01 | |
date issued | 2014 | |
identifier issn | 1558-8424 | |
identifier other | ams-74898.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4217173 | |
description abstract | probabilistic spatiotemporal approach based on a spatial regression test (SRT-PS) is proposed for the quality control of climate data. It provides a quantitative probability that represents the uncertainty in each temperature observation. The assumption of SRT-PS is that there might be large uncertainty in the station record if there is a large residual difference between the record estimated in the spatial regression test and the true station record. The result of SRT-PS is expressed as a confidence probability ranging from 0 to 1, where a value closer to 1 indicates less uncertainty. The potential of SRT-PS to estimate quantitatively the uncertainty in temperature observations was demonstrated using an annual temperature dataset for China for the period 1971?2000 with seeded errors. SRT-PS was also applied to assess a real dataset, and was compared with two traditional quality control approaches: biweight mean and biweight standard deviation and SRT. The study provides a new approach to assess quantitatively the uncertainty in temperature observations at meteorological stations. | |
publisher | American Meteorological Society | |
title | Estimation of Uncertainty in Temperature Observations Made at Meteorological Stations Using a Probabilistic Spatiotemporal Approach | |
type | Journal Paper | |
journal volume | 53 | |
journal issue | 6 | |
journal title | Journal of Applied Meteorology and Climatology | |
identifier doi | 10.1175/JAMC-D-13-0179.1 | |
journal fristpage | 1538 | |
journal lastpage | 1546 | |
tree | Journal of Applied Meteorology and Climatology:;2014:;volume( 053 ):;issue: 006 | |
contenttype | Fulltext | |