| 21 Jan 2025
Rain gauges and X-band radar hourly comparison under complex orographic conditions in Reunion Island during the passage of the cyclone Batsirai
Abstract. Weather radar observations and quantitative precipitation estimation (QPE) are in the early stages of development in the South-West Indian Ocean (SWIO) region, which is prone to heavy rainfall, particularly during the passage of tropical cyclones. Given the topography of SWIO islands, orography plays an important role in the spatial distribution of precipitation. The ESPOIRS project was designed to investigate such dynamics in Reunion Island, Seychelles, and Madagascar using a mobile X-band radar. Reunion Island served as a testbed to evaluate X-band radar retrieved QPE using specific comparisons between several radar approaches and available rain gauges. This is the first study to use an X-band dual-polarization radar in the SWIO region. Our research focuses on the intense tropical cyclone event Batsirai in Reunion Island and shows the effectiveness of dual-polarization radar when compared to single-polarization radar in mitigating reflectivity attenuation. Both the Hitschfeld and Bordan and the philinear algorithms were employed and evaluated for this purpose. As our study encountered challenges related to noisy and low-resolution differential phase (𝜙𝑑𝑝) data, we detailed the pre-processing steps used to extract reliable 𝜙𝑑𝑝 data from the observed measurements. Furthermore, we tested two precipitation estimators, R(Z) and R(kdp). We observed that the accuracy of R(Z) depends on the attenuation correction method. Additionally, using the extracted 𝜙𝑑𝑝, we calculated an empirical model for R(kdp) for Reunion Island. This model provided better results compared to the R(Z) estimates, which can be explained by the fact that kdp is directly linked to precipitation concentration and does not require attenuation correction. Our findings highlight that the accuracy of the radar QPE is strongly influenced by local topography, which in turn governs local rainfall patterns, while the accuracy of QPE also depends on the type of precipitation.
This manuscript deals with the quantitative estimation of rainfall in the south-west Indian Ocean, more particularly on Réunion Island where the orographic enhancement of rainfall can be very significant. A polarisation diversity X-band research radar was installed and tested. The authors state that this is the first search radar of this type to be deployed in this region of the world. The authors chose as a case study the passage of cyclone Batsirai in February 2022. They propose to compare the rainfall estimates obtained by radar using data from 6 rain gauges available on the island as a reference. Two radar rain intensity estimators were tested: the first based on the radar reflectivity factor Z, the second on the specific differential phase Kdp. For the first estimator, which is very sensitive to attenuation by precipitation, two attenuation correction methods were applied and evaluated: the method of Hitschfeld and Bordan (1954) and the so-called phi-linear method of Bringi et al. (1990). The authors confirmed the results of the literature on the subject: the fact that the second correction method is more reliable than the first and that the estimate with Kdp is more efficient for intense precipitation than the Z estimator. A third method, directly deriving the rainfall intensity from Kdp is also used and compared.
This article does not provide any new knowledge per se, but reports on the first quantitative rainfall estimates using polarisation diversity search radar in the south-west Indian Ocean. Section 2 is interesting because it provides a detailed description of the differential phase shift pre-processing.
In my opinion, some points in the article need to be corrected or clarified, in particular certain equations. It is a pity that the operational radar data available from the National Meteorological Centre is not used (or that its use is not discussed) in this study. In addition, the study only covers one case study, which does not provide a robust assessment. The case chosen corresponds to a very specific cyclone situation. This is both a strength (the type of event is poorly documented, particularly the interaction with the terrain) and a weakness (there are doubts about the quality of the reference intensities provided by the rain gauges under these conditions, which makes it more difficult to compare radar and rain gauge estimates).
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