Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data
In weather radar applications, the Z-R relationship is considered one of the most crucial factors for providing quality quantitative precipitation estimates. However, the relationship’s parameters vary in time and space, making the derivation of an optimal relationship for a specific weather radar s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Hydrology |
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| Online Access: | https://www.mdpi.com/2306-5338/9/8/137 |
| _version_ | 1827617885256679424 |
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| author | Apollon Bournas Evangelos Baltas |
| author_facet | Apollon Bournas Evangelos Baltas |
| author_sort | Apollon Bournas |
| collection | DOAJ |
| description | In weather radar applications, the Z-R relationship is considered one of the most crucial factors for providing quality quantitative precipitation estimates. However, the relationship’s parameters vary in time and space, making the derivation of an optimal relationship for a specific weather radar system challenging. This research focused on the analysis of the spatiotemporal variability of the parameters for a newly installed X-Band weather radar in Athens, Greece, by performing correlation and optimization analyses between high temporal resolution weather radar and rain gauge datasets. The correlation analysis was performed to assess the available datasets and provide the base of quality control. Multiple Z-R relationships were then derived for the following three optimization procedures; event-based relationships, station-based relationships, and a single area-based relationship. The results highlighted the region’s spatial variability regarding the Z-R relationship and the correlation between the station location and its parameter values. Moreover, it was found that stations near the coast and the front end of precipitation systems featured parameter values typical of convective type events. Finally, a single Z-R relationship was determined under a calibration and validation scheme, <i>Z</i> = 321<i>R</i><sup>1.53,</sup>, which was validated with good agreement. |
| first_indexed | 2024-03-09T09:56:43Z |
| format | Article |
| id | doaj.art-d719a0f8d2884373a78fd86fe0283434 |
| institution | Directory Open Access Journal |
| issn | 2306-5338 |
| language | English |
| last_indexed | 2024-03-09T09:56:43Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Hydrology |
| spelling | doaj.art-d719a0f8d2884373a78fd86fe02834342023-12-01T23:46:16ZengMDPI AGHydrology2306-53382022-07-019813710.3390/hydrology9080137Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge DataApollon Bournas0Evangelos Baltas1Department of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, 5 Iroon Polytechniou, 157 80 Athens, GreeceDepartment of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, 5 Iroon Polytechniou, 157 80 Athens, GreeceIn weather radar applications, the Z-R relationship is considered one of the most crucial factors for providing quality quantitative precipitation estimates. However, the relationship’s parameters vary in time and space, making the derivation of an optimal relationship for a specific weather radar system challenging. This research focused on the analysis of the spatiotemporal variability of the parameters for a newly installed X-Band weather radar in Athens, Greece, by performing correlation and optimization analyses between high temporal resolution weather radar and rain gauge datasets. The correlation analysis was performed to assess the available datasets and provide the base of quality control. Multiple Z-R relationships were then derived for the following three optimization procedures; event-based relationships, station-based relationships, and a single area-based relationship. The results highlighted the region’s spatial variability regarding the Z-R relationship and the correlation between the station location and its parameter values. Moreover, it was found that stations near the coast and the front end of precipitation systems featured parameter values typical of convective type events. Finally, a single Z-R relationship was determined under a calibration and validation scheme, <i>Z</i> = 321<i>R</i><sup>1.53,</sup>, which was validated with good agreement.https://www.mdpi.com/2306-5338/9/8/137Z-R relationshipAthensspatial Z-R variabilityweather radarrain gauge correlationX-band |
| spellingShingle | Apollon Bournas Evangelos Baltas Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data Hydrology Z-R relationship Athens spatial Z-R variability weather radar rain gauge correlation X-band |
| title | Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data |
| title_full | Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data |
| title_fullStr | Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data |
| title_full_unstemmed | Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data |
| title_short | Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data |
| title_sort | determination of the z r relationship through spatial analysis of x band weather radar and rain gauge data |
| topic | Z-R relationship Athens spatial Z-R variability weather radar rain gauge correlation X-band |
| url | https://www.mdpi.com/2306-5338/9/8/137 |
| work_keys_str_mv | AT apollonbournas determinationofthezrrelationshipthroughspatialanalysisofxbandweatherradarandraingaugedata AT evangelosbaltas determinationofthezrrelationshipthroughspatialanalysisofxbandweatherradarandraingaugedata |