Geography

Geography

Spatial and Temporal Assessment of the Accuracy of Precipitation Estimates from the ERA5-Land Reanalysis Database in Isfahan Province over the Past Two Decades

Document Type : Research Article

Authors
Ali Shahi 1
Bromand Salahi 2
1 Ph.D. Student of Climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
2 Professor of Climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.
10.22034/jiga.2025.2066496.1426
Abstract
Extended Abstract 
Introduction
According to various studies, precipitation has high volatility and greater uncertainty in forecasting than other atmospheric variables, especially temperature. Considering the special importance of precipitation in the life of living organisms, accurate data without statistical gaps must be available to further understand it. Since there are numerous limitations in the construction and maintenance of fixed ground stations, the need for appropriate databases from robust sources is greatly felt. One of these sources is reanalysis data, which can be used in calculations if their performance accuracy is evaluated.
 
Methodology
In the present study, after receiving the reanalysis data, due to its NC format, the precipitation data were converted to text format based on the coordinates of the research stations using R software. Due to the fact that the unit of measurement was meters for comparison under the same conditions, the precipitation data was converted to millimeters by multiplying the data by 1000. To evaluate the accuracy of the ERA5-Land reanalysis data, which have a much stronger horizontal resolution than the ERA5 type (horizontal resolution of approximately 31 km), the Taylor mathematical diagram was used. For this purpose, the reference for precipitation data was synoptic ground stations. Using the Taylor diagram, station precipitation data and reanalysis of all six stations were compared. The studies showed that the raw output of the reanalysis data does not have sufficient quality and accuracy in the study area due to its high bias. To reduce errors and optimize the data, bias correction was applied using the Quantile Mapping method. For each station, separated by monthly time scale, a Taylor diagram was drawn as the average precipitation over the 20-year study period. Then, for each month, separately for each station, the precipitation calculated by the two databases was compared using R software. The difference in average precipitation calculated by two ground stations and reanalysis was visually zoned with a geographic information system, and the amount of difference, overestimation, and underestimation of the ERA5-Land station was evaluated at each station.
 
Results and Discussion
According to the comparison between the precipitation data of the two ground stations and the reanalysis, the evaluation results with the Taylor diagram indicated a high error in the precipitation estimation by ERA5-Land in Isfahan province, so that the correlation coefficient value was zero in all months. Based on the Quantile Mapping method, bias correction optimized the precipitation data with very good performance, and the correlation coefficient reached 0.97 in some months. According to the graph drawn in the R software environment, the performance of the reanalysis database compared to the ground station in different months based on 6 stations in Isfahan province was consistent and had a low error. Zoning the difference in the average precipitation estimated by the reanalysis database with the synoptic station in the geographic information system software environment showed that the difference in precipitation between the two databases was appropriate and acceptable.
 
Conclusion
The results showed that the ERA5-Land precipitation data are not able to estimate the precipitation of the study area directly (raw), but after bias correction using the quantile mapping method, it made a very good estimate of the precipitation of Isfahan province with a maximum difference of 10 mm compared to the ground station data. The best performance of the ERA5-Land database is in the winter and autumn seasons. In terms of spatiality, the maximum and minimal differences of precipitation data between the two databases have been visible in the west and north of the study area, respectively. No specific spatial distribution was observed in terms of overestimation and underestimation.

 
Keywords
ERA5-Land
Precipitation
Quantile Mapping
Reanalysis data
Isfahan Province

Subjects

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Geography
Volume 23, Issue 86
Autumn2024, pp.1-200.
Autumn 2025
Pages 43-69