Iranian Journal of Geophysics

Iranian Journal of Geophysics

Investigating the effect of height difference correction between reanalysis grid points and observation stations on the accuracy of ERA5 2m temperature and pressure data

Document Type : Research Article

Authors
1 Assistant Professor, Babol Noshirvani University of Technology, Civil Engineering Department, Mazandaran, Iran
2 Ph.D., Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran
Abstract
Temperature and surface pressure are among the critical variables in various meteorological and climatic applications. Reanalysis products have become valuable sources of temperature and pressure data in recent years and have garnered much attention. Due to the elevation difference between reanalysis grid points and ground stations, surface pressure and 2m temperature derived from reanalysis products exhibit noticeable biases. In this study, using 10 years of measured data from 202 synoptic stations in Iran, the impact of elevation correction on the accuracy of ERA5 Land (ERA5L) pressure and 2m temperature data was investigated. Three different models were used for elevation correction. A comparison of error statistics before and after elevation correction revealed that in most stations the accuracy of ERA5L temperature and pressure data are improved after elevation correction. The results indicate that after data calibration, the average bias and Root Mean Square Error (RMSE) of surface pressure in the region improved by 96% and 66%, respectively. Compared to surface pressure, the positive impact of elevation correction on ERA5L temperature was less pronounced, with average bias and RMSE improving by 68% and 13%, respectively. Furthermore, for the elevation calibration of ERA5L pressure, the three used models were compared. A comparison of error statistics across all stations demonstrated that the performance of the three models did not show significant differences in the Iran region.
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Baker, J. C., Castilho de Souza, D., Kubota, P. Y., et al., 2021, An assessment of land–atmosphere interactions over South America using satellites, reanalysis, and two global climate models: Journal of Hydrometeorology, 22(4), 905-922.
Berg, H., 1948, Allgemeine meteorologie. Du¨mmler, Verlag, p 337
Bevis, M., Businger, S., Chiswell, S., Herring, T. A., Anthes, R. A., Rocken, C., and Ware, R. H., 1994, GPS meteorology: Mapping zenith wet delays onto precipitable water: Journal of Applied Meteorology and Climatology, 33(3), 379-386.‏
Bevis, M., Businger, S., Herring, T. A., Rocken, C., Anthes, R. A., and Ware, R. H., 1992, GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system: Journal of Geophysical Research: Atmospheres, 97(D14), 15787-15801.‏
Böhm, J., Lagler, K., Schindelegger, M., Krásná, H., Weber, R., and Möller, G., 2013, GPT2: An improved model for tropospheric slant delays in VLBI and GNSS analysis: The European Navigation Conference Proceedings (p. 4), The European Navigation Conference.‏
Davis, J. L., Herring, T. A., Shapiro, I. I., Rogers, A. E. E., and Elgered, G., 1985, Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length: Radio Science, 20(6), 1593-1607.‏
Hersbach, H., and Dee, D., 2016, ERA5 reanalysis is in production: ECMWF Newsletter, 147, Reading, UK: ECMWF.‏
Hofmann-Wellenhof, B., Lichtenegger, H., and Wasle, E., 2007, GNSS–global navigation satellite systems: GPS, GLONASS, Galileo, and more: Springer Science and Business Media.‏
Huai, B., Wang, J., Sun, W., Wang, Y., and Zhang, W., 2021, Evaluation of the near-surface climate of the recent global atmospheric reanalysis for Qilian Mountains, Qinghai-Tibet Plateau: Atmospheric Research, 250, 105401.‏
Huang, L., Fang, X., Zhang, T., Wang, H., Cui, L., and Liu, L., 2023, Evaluation of surface temperature and pressure derived from MERRA-2 and ERA5 reanalysis datasets and their applications in hourly GNSS precipitable water vapor retrieval over China: Geodesy and Geodynamics, 14(2), 111-120.‏
Lagler, K., Schindelegger, M., Böhm, J., Krásná, H., and Nilsson, T., 2013, GPT2: Empirical slant delay model for radio space geodetic techniques: Geophysical Research Letters, 40(6), 1069-1073.‏
Li, J., Zhang, B., Yao, Y., Liu, L., Sun, Z., and Yan, X., 2020, A refined regional model for estimating pressure, temperature, and water vapor pressure for geodetic applications in China: Remote Sensing, 12(11), 1713.
Paredes, P., Martins, D. S., Pereira, L. S., Cadima, J., and Pires, C., 2018, Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes: Agricultural Water Management, 210, 340-353.‏
Parracho, A. C., Bock, O., and Bastin, S., 2018, Global IWV trends and variability in atmospheric reanalyses and GPS observations: Atmospheric Chemistry and Physics, 18(22), 16213-16237.‏
Pelosi, A., Terribile, F., D’Urso, G., and Chirico, G. B., 2020, Comparison of ERA5L and UERRA MESCAN-SURFEX reanalysis data with spatially interpolated weather observations for the regional assessment of reference evapotranspiration: Water, 12(6), 1669.
Ruffault, J., Moron, V., Trigo, R. M., and Curt, T., 2017, Daily synoptic conditions associated with large fire occurrence in Mediterranean France: evidence for a wind-driven fire regime: International Journal of Climatology, 37(1), 524-533.‏
Saastamoinen, J., 1972, Atmospheric correction for the troposphere and stratosphere in radio ranging of satellites, in Henriksen, S. W., Manchini, A., Chovitz, B. H., eds., The Use of Artificial Satellites for Geodesy, 15: AGU, Washington, D.C., 247–251.
Rothacher, M., 2002, Estimation of station heights with GPS. In Vertical Reference Systems: IAG Symposium Cartagena, Colombia, February 20–23, (pp. 81-90).
Sam-Khaniani, A., and Mohammadi, A., 2022, Comparison of ERA5-Land reanalysis data with surface observations over Iran: Iranian Journal of Geophysics (in Persian), 16(1), 195-212, doi: 10.30499/ijg.2022.313494.1376.
Sheffield, J., Goteti, G., and Wood, E. F., 2006, Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling: Journal of Climate, 19(13), 3088-3111.‏
Singh, V. P., and Woolhiser, D. A., 2002, Mathematical modeling of watershed hydrology: Journal of Hydrologic Engineering, 7(4), 270-292.‏
Soci, C., Bazile, E., Besson, F., and Landelius, T., 2016, High-resolution precipitation re-analysis system for climatological purposes: Tellus A: Dynamic Meteorology and Oceanography, 68(1), 29879.‏
Su, H., Yang, T., Sun, B., and Yang, X., 2021, Modified atmospheric pressure extrapolation model using ERA5 for geodetic applications: GPS Solutions, 25(3), 118.‏
Tarek, M., Brissette, F. P., and Arsenault, R., 2020, Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America: Hydrology and Earth System Sciences, 24(5), 2527-2544.
Vedel, H., 2000, Conversion of WGS84 Geometric Heights to NWP Model HIRLAM Geopotential Heights: Danish Meteorological Institute Scientific Rep. 00-04, Copenhagen.
Wang, X., Zhang, K., Wu, S., Fan, S., and Cheng, Y., 2016, Water vapor weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend: Journal of Geophysical Research: Atmospheres, 121(2), 833-852.‏
Xu, G., 2007, GPS: Theory, Algorithms and Applications: Springer: Berlin/Heidelberg, Germany; ISBN 9783540727149.
Zhang, W., Zhang, H., Liang, H., et al., 2019, On the suitability of ERA5 in hourly GPS precipitable water vapor retrieval over China: Journal of Geodesy, 93, 1897-1909.‏