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Atmospheric precipitable water vapor over Iran using MODIS products: climatology and intercomparison

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Abstract

This study presents a statistical evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric precipitable water vapor (PWV) products over Iran. Long-term level 3 monthly (2003–2020) and level 2 daily (January 2004 and July 2008) MODIS PWV data were compared with ERA5 as the latest ECMWF re-analysis and radiosonde data sets, respectively. Among the factors that are causing errors in the MODIS retrieval PWV value, the effect of weather conditions including cloudiness and aerosols is investigated. On a monthly scale, our analysis shows that the Cloud Fraction (CF) and Aerosol Optical Depth (AOD) have a strong relationship with the distribution of MODIS percentage errors (compared to ERA5), especially during the summer season. However, the average annual PWV values from MODIS and ERA5 are close to each other (13 and 13.3 mm, respectively). In addition, the MODIS PWV data have a significant negative correlation coefficient with the topography data. This suggests that MODIS level-3 monthly PWV data are valuable to calculate the monthly long-term climatology of PWV over Iran. On a daily scale, the comparison was carried out in two different weather conditions. Results show that in a clear sky with high visibility (despite the time lag between two data sets), MODIS and radiosonde PWV have a close relationship (R2 = 0.73 in July 2008), while R2 is reduced significantly during cloudy conditions with low visibility (lower than 10 KM) in all stations (R2 = 0.05 in July 2008). These results confirm that the accuracy of the MODIS PWV data is strongly dependent on weather conditions, both in summer and winter time.

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The datasets generated for this study can be obtained from the corresponding author upon reasonable request.

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Correspondence to Mohammad Rezaei.

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Responsible Editor: Silvia Trini Castelli.

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Rezaei, M., Khazaei, M. Atmospheric precipitable water vapor over Iran using MODIS products: climatology and intercomparison. Meteorol Atmos Phys 134, 15 (2022). https://doi.org/10.1007/s00703-021-00854-6

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  • DOI: https://doi.org/10.1007/s00703-021-00854-6

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