scholarly journals Temperature error‐correction method for surface air temperature data

2020 ◽  
Vol 27 (6) ◽  
Author(s):  
Jie Yang ◽  
Xuan Deng ◽  
Qingquan Liu ◽  
Renhui Ding
Keyword(s):  
Error Correction ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Correction Method ◽  
Temperature Data ◽  
Temperature Error ◽  
Error Correction Method

Design of a temperature error correction method used for meteorology and climate research

2021 ◽  
Vol 263 ◽  
pp. 105817
Author(s):  
Jie Yang ◽  
Qingquan Liu ◽  
Gaoying Chen ◽  
Xuan Deng ◽  
Li Zhang
Keyword(s):  
Error Correction ◽  
Correction Method ◽  
Temperature Error ◽  
Climate Research ◽  
Error Correction Method

Calibrating and Evaluating Reanalysis Surface Temperature Error by Topographic Correction

2008 ◽  
Vol 21 (6) ◽  
pp. 1440-1446 ◽  
Author(s):  
Tianbao Zhao ◽  
Weidong Guo ◽  
Congbin Fu
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Original Data ◽  
Reanalysis Data ◽  
Temperature Data ◽  
Temperature Error ◽  
Topographic Correction ◽  
Temperature Errors

Abstract Based on the observed daily surface air temperature data from 597 stations over continental China and two sets of reanalysis data [NCEP–NCAR and 40-yr ECMWF Re-Analysis (ERA-40)] during 1979–2001, the altitude effects in calibrating and evaluating reanalyzed surface temperature errors are studied. The results indicate that the accuracy of interpolated surface temperature from the reanalyzed gridpoint value or the station observations depends much on the altitudes of original data. Bias of interpolated temperature is usually in proportion to the increase of local elevation and topographical complexity. Notable improvements of interpolated surface temperature have been achieved through “topographic correction,” especially for ERA-40, which highlights the necessity of removal of “elevation-induced bias” when using and evaluating reanalyzed surface temperature.

scholarly journals <i>Brief communication</i> "A statistical validation for the cycles found in air temperature data using a Morlet wavelet-based method"

2010 ◽  
Vol 17 (3) ◽  
pp. 269-272 ◽  
Author(s):  
S. Nicolay ◽  
G. Mabille ◽  
X. Fettweis ◽  
M. Erpicum
Keyword(s):  
Air Temperature ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Weather Forecast ◽  
Temperature Data ◽  
Temperature Time Series ◽  
Climatic Data ◽  
Statistical Validation ◽  
Confidence Levels ◽  
Temperature Time

Abstract. Recently, new cycles, associated with periods of 30 and 43 months, respectively, have been observed by the authors in surface air temperature time series, using a wavelet-based methodology. Although many evidences attest the validity of this method applied to climatic data, no systematic study of its efficiency has been carried out. Here, we estimate confidence levels for this approach and show that the observed cycles are significant. Taking these cycles into consideration should prove helpful in increasing the accuracy of the climate model projections of climate change and weather forecast.

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