Spatial interpolation of surface air temperature by Kriging models

Jing-si Li, Run-qiu Pan, Fu-lin FAN

Research output: Contribution to journalArticle

Abstract

This paper aims to describe spatial interpolation methods to estimate surface air temperatures (SATs). The SAT at a particular location where SAT observations are not available is estimated through a Kriging interpolation between SAT measurements from 192 meteorological sites at which daily SAT observations have been obtained. A temporal de-trending method based on a Fourier series is used to model and remove the annual trend in original data in order to ensure the stationarity of de-trended data from which kriging parameters are determined. Furthermore, a spatial or surface de-trending in terms of geographic coordinates including altitude, latitude and longitude of each location is adopted in a Kriging model. Besides a Kriging model, an inverse distance weighting (IDW) interpolation method is tested as a comparison. The accuracies of both spatial interpolation approaches are assessed by calculating and comparing their mean absolute error (MAE) and root mean square error (RMSE) when taking each meteorological site as the target location in a cross-validation procedure. The results show that the Kriging model performs better than the IDW method at 174 sites. In addition, the temporal and spatial de-trending methods make the main contribution to the accurate capture of spatial correlations of SATs in the study area in a Kriging process.
Translated title of the contributionSpatial interpolation of surface air temperature by Kriging models
LanguageChinese
Article number5
Pages21-27
Number of pages7
JournalJournal of Southwest China Normal University (Natural Science Edition)
Volume41
Issue number5
Publication statusPublished - 31 May 2016

Fingerprint

Interpolation
Air
Temperature
Fourier series
Temperature measurement
Mean square error

Keywords

  • surface air temperature
  • kriging model
  • inverse distance weighting method
  • fourier series
  • temporal de-trending
  • spatial de-trending
  • spatial interpolation
  • meteorological sites

Cite this

@article{39ced8cd849c4c8aab1cc0bb1bbe5cb4,
title = "基于Kriging模型的地面气温空间插值研究",
abstract = "This paper aims to describe spatial interpolation methods to estimate surface air temperatures (SATs). The SAT at a particular location where SAT observations are not available is estimated through a Kriging interpolation between SAT measurements from 192 meteorological sites at which daily SAT observations have been obtained. A temporal de-trending method based on a Fourier series is used to model and remove the annual trend in original data in order to ensure the stationarity of de-trended data from which kriging parameters are determined. Furthermore, a spatial or surface de-trending in terms of geographic coordinates including altitude, latitude and longitude of each location is adopted in a Kriging model. Besides a Kriging model, an inverse distance weighting (IDW) interpolation method is tested as a comparison. The accuracies of both spatial interpolation approaches are assessed by calculating and comparing their mean absolute error (MAE) and root mean square error (RMSE) when taking each meteorological site as the target location in a cross-validation procedure. The results show that the Kriging model performs better than the IDW method at 174 sites. In addition, the temporal and spatial de-trending methods make the main contribution to the accurate capture of spatial correlations of SATs in the study area in a Kriging process.",
keywords = "surface air temperature, kriging model, inverse distance weighting method, fourier series, temporal de-trending, spatial de-trending, spatial interpolation, meteorological sites",
author = "Jing-si Li and Run-qiu Pan and Fu-lin FAN",
year = "2016",
month = "5",
day = "31",
language = "Chinese",
volume = "41",
pages = "21--27",
journal = "Journal of Southwest China Normal University (Natural Science Edition)",
issn = "1000-5471",
number = "5",

}

基于Kriging模型的地面气温空间插值研究. / Li, Jing-si; Pan, Run-qiu; FAN, Fu-lin.

In: Journal of Southwest China Normal University (Natural Science Edition), Vol. 41, No. 5, 5, 31.05.2016, p. 21-27.

Research output: Contribution to journalArticle

TY - JOUR

T1 - 基于Kriging模型的地面气温空间插值研究

AU - Li, Jing-si

AU - Pan, Run-qiu

AU - FAN, Fu-lin

PY - 2016/5/31

Y1 - 2016/5/31

N2 - This paper aims to describe spatial interpolation methods to estimate surface air temperatures (SATs). The SAT at a particular location where SAT observations are not available is estimated through a Kriging interpolation between SAT measurements from 192 meteorological sites at which daily SAT observations have been obtained. A temporal de-trending method based on a Fourier series is used to model and remove the annual trend in original data in order to ensure the stationarity of de-trended data from which kriging parameters are determined. Furthermore, a spatial or surface de-trending in terms of geographic coordinates including altitude, latitude and longitude of each location is adopted in a Kriging model. Besides a Kriging model, an inverse distance weighting (IDW) interpolation method is tested as a comparison. The accuracies of both spatial interpolation approaches are assessed by calculating and comparing their mean absolute error (MAE) and root mean square error (RMSE) when taking each meteorological site as the target location in a cross-validation procedure. The results show that the Kriging model performs better than the IDW method at 174 sites. In addition, the temporal and spatial de-trending methods make the main contribution to the accurate capture of spatial correlations of SATs in the study area in a Kriging process.

AB - This paper aims to describe spatial interpolation methods to estimate surface air temperatures (SATs). The SAT at a particular location where SAT observations are not available is estimated through a Kriging interpolation between SAT measurements from 192 meteorological sites at which daily SAT observations have been obtained. A temporal de-trending method based on a Fourier series is used to model and remove the annual trend in original data in order to ensure the stationarity of de-trended data from which kriging parameters are determined. Furthermore, a spatial or surface de-trending in terms of geographic coordinates including altitude, latitude and longitude of each location is adopted in a Kriging model. Besides a Kriging model, an inverse distance weighting (IDW) interpolation method is tested as a comparison. The accuracies of both spatial interpolation approaches are assessed by calculating and comparing their mean absolute error (MAE) and root mean square error (RMSE) when taking each meteorological site as the target location in a cross-validation procedure. The results show that the Kriging model performs better than the IDW method at 174 sites. In addition, the temporal and spatial de-trending methods make the main contribution to the accurate capture of spatial correlations of SATs in the study area in a Kriging process.

KW - surface air temperature

KW - kriging model

KW - inverse distance weighting method

KW - fourier series

KW - temporal de-trending

KW - spatial de-trending

KW - spatial interpolation

KW - meteorological sites

UR - http://en.cnki.com.cn/Article_en/CJFDTotal-XNZK201605005.htm

UR - http://en.cnki.com.cn/Journal_en/A-A000-XNZK-2016-05.htm

M3 - Article

VL - 41

SP - 21

EP - 27

JO - Journal of Southwest China Normal University (Natural Science Edition)

T2 - Journal of Southwest China Normal University (Natural Science Edition)

JF - Journal of Southwest China Normal University (Natural Science Edition)

SN - 1000-5471

IS - 5

M1 - 5

ER -