Oman Provisional Climate Normal Based on the Observation from 2010 to 2021

Climate normal calculation over Oman is a key challenge due to scattered and inconsistent ground observations. Based on the available observations record to calculate the normal, the study derives the Provisional Climate Normal. The data from selected stations in this project have been tested and investigated by using the quality check and missing data evaluation. It is found that ERA-5 is the best reanalysis data in temperature as the correlation coefficient is higher compared to ERA-5 land and MERRA-2 which explains the reason for choosing ERA-5 data to calculate the regression model to fulfil the missing data. By using MODIS data, the Urban Heat Island Index (UHI) shows that Sohar and Muscat stations have the greatest UHI effect and Rustaq has the negative UHI trend. Regarding the interpolation, the project used different interpolation methods to calculate the provisional climate normal for Oman, showing that different variogram fitting models must be used for different months for Kriging interpolation. The final results show that all the interpolation methods struggle to predict the air temperature during summertime due to a complex spatial contrast and distribution, except GWR which shows a well-predicted dataset by which it can be said that the GWR is the best performing method for the temperature over Oman.

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Publication Details

Journal
Atmospheric and Climate Sciences
Published
2025-01-01
DOI
https://doi.org/10.4236/acs.2025.154041
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
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article

Oman Provisional Climate Normal Based on the Observation from 2010 to 2021

Kahlan Al Toubi, Munira Al Quraini, Afada Al Hubaishi
Atmospheric and Climate Sciences
Climate variability and models
article

Oman Provisional Climate Normal Based on the Observation from 2010 to 2021

Kahlan Al Toubi, Munira Al Quraini, Afada Al Hubaishi
article en

Abstract

Climate normal calculation over Oman is a key challenge due to scattered and inconsistent ground observations. Based on the available observations record to calculate the normal, the study derives the Provisional Climate Normal. The data from selected stations in this project have been tested and investigated by using the quality check and missing data evaluation. It is found that ERA-5 is the best reanalysis data in temperature as the correlation coefficient is higher compared to ERA-5 land and MERRA-2 which explains the reason for choosing ERA-5 data to calculate the regression model to fulfil the missing data. By using MODIS data, the Urban Heat Island Index (UHI) shows that Sohar and Muscat stations have the greatest UHI effect and Rustaq has the negative UHI trend. Regarding the interpolation, the project used different interpolation methods to calculate the provisional climate normal for Oman, showing that different variogram fitting models must be used for different months for Kriging interpolation. The final results show that all the interpolation methods struggle to predict the air temperature during summertime due to a complex spatial contrast and distribution, except GWR which shows a well-predicted dataset by which it can be said that the GWR is the best performing method for the temperature over Oman.

Atmospheric and Climate SciencesVol. 15(04)
Agence Nationale de l'Aviation Civile et de la Météorologie (SN)
Openalex Percentile: Top 75%
Climate variability and models
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