Calibration of Reflectivity Observations from the Weather Radar Network of Cyprus Against GPM Dual-Frequency Precipitation Radar
Journal
IEEE EXPLORE
Date Issued
September 5, 2024
Author(s)
Loulli, Eleni
Bühl, Johannes
Michaelides, Silas
Loukas, Athanasios
HADJIMITSIS, DIOFANTOS
DOI
10.1109/IGARSS53475.2024.10641921
Abstract
This paper analyses polarimetric weather radar data to
explore their potential for comprehensive and reliable
precipitation and thus, drought monitoring in Cyprus.
Reflectivity measurements from the two ground-based X
band dual-polarization radars of the Department of
Meteorology of the Republic of Cyprus are compared with
measurements obtained from the Dual-Frequency
Precipitation Radar (DPR) onboard NASA’s Global
Precipitation Measurement (GPM) mission in order to
calibrate the ground-based reflectivity. The comparison is
done using a volume matching method that allows us to
associate the datasets both in space and time. To correct the
attenuation, we examine a Z-A relationship approach and the
forward gate-by-gate attenuation correction based on an
iterative approach with scalable constraints. Preliminary
results show a significant underestimation of the ground
based reflectivity, as well as a notable impact of attenuation
that leads to a major source of error for rainfall estimation
explore their potential for comprehensive and reliable
precipitation and thus, drought monitoring in Cyprus.
Reflectivity measurements from the two ground-based X
band dual-polarization radars of the Department of
Meteorology of the Republic of Cyprus are compared with
measurements obtained from the Dual-Frequency
Precipitation Radar (DPR) onboard NASA’s Global
Precipitation Measurement (GPM) mission in order to
calibrate the ground-based reflectivity. The comparison is
done using a volume matching method that allows us to
associate the datasets both in space and time. To correct the
attenuation, we examine a Z-A relationship approach and the
forward gate-by-gate attenuation correction based on an
iterative approach with scalable constraints. Preliminary
results show a significant underestimation of the ground
based reflectivity, as well as a notable impact of attenuation
that leads to a major source of error for rainfall estimation
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