Exploring single polarization X-band weather radar potentials for local meteorological and hydrological applications

Conti, Francesco Lo; Francipane, Antonio; Pumo, Dario; Noto, Leonardo

doi:10.1016/j.jhydrol.2015.10.071

Cited by 25 publications

(19 citation statements)

References 45 publications

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“…Therefore, despite their good performance, they would be of very limited applicability in mountain regions as the Andes. For instance, this study differs from [11] in the evaluation at longer distances from radar, 60 km instead of 20 km and more significantly in the Z-R relationship performance. Contrary to [11] that used a unique event-based derived Z-R for the rainfall derivation of the Palermo radar, [1] has already demonstrated the high variability of Z-R relationships at the southern Andes of Ecuador and its impact on rainfall derivation.…”

Section: Comparison Of the Models -Temporal And Spatial Evaluationmentioning

confidence: 68%

“…Individual corrections related to physical and atmospheric conditions that may influence the reflectivity values recorded by the radar are applied. The complete correction chain differs depending on the radar location and the study goals (e.g., [11,21,36]). To facilitate the reproducibility of this study, we used the methods implemented in the wradlib library [37,38] which is developed in python programming language.…”

Section: Step-wise Correction Modelmentioning

confidence: 99%

“…Nonetheless, several studies [2,7,8], given their financial capabilities, have used the key advantage of the derived features of dual-polarized radars to perform attenuation correction efficiently. On the other hand, the single polarized version of X-band, despite its restrictions and uncertainties [9] compared to dual-polarization, has also been successfully deployed (e.g., [10][11][12]), even in remote areas such as high mountains. Recently, Bendix et al [13] reported the first X-band radar network at high altitudes in the southern Andes of Ecuador (Radarnet-Sur).…”

Section: Introductionmentioning

confidence: 99%

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Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model

et al. 2019

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Despite many efforts of the radar community, quantitative precipitation estimation (QPE) from weather radar data remains a challenging topic. The high resolution of X-band radar imagery in space and time comes with an intricate correction process of reflectivity. The steep and high mountain topography of the Andes enhances its complexity. This study aims to optimize the rainfall derivation of the highest X-band radar in the world (4450 m a.s.l.) by using a random forest (RF) model and single Plan Position Indicator (PPI) scans. The performance of the RF model was evaluated in comparison with the traditional step-wise approach by using both, the Marshall-Palmer and a site-specific Z–R relationship. Since rain gauge networks are frequently unevenly distributed and hardly available at real time in mountain regions, bias adjustment was neglected. Results showed an improvement in the step-wise approach by using the site-specific (instead of the Marshall-Palmer) Z–R relationship. However, both models highly underestimate the rainfall rate (correlation coefficient < 0.69; slope up to 12). Contrary, the RF model greatly outperformed the step-wise approach in all testing locations and on different rainfall events (correlation coefficient up to 0.83; slope = 1.04). The results are promising and unveil a different approach to overcome the high attenuation issues inherent to X-band radars.

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Section: Comparison Of the Models -Temporal And Spatial Evaluationmentioning

confidence: 68%

Section: Step-wise Correction Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model

et al. 2019

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“…The use of X-band weather radars is rapidly increasing with the advance of technology and data correction and processing algorithms, as well as their reduced costs for installation and maintenance with respect to the operational long-range C-and S-band systems. The high resolution and the increased sensitivity of X-band radars make them quite suitable for nowcasting purposes [102][103][104]. The range limitation of X-band radars due to the larger attenuation in rain in this microwave band can be surpassed using radar networks, whose setup improves also the accuracy of radar products [105][106][107].…”

Section: Discussionmentioning

confidence: 99%

“…In future, radar data assimilation in CHAOS modeling system and radar tracking algorithms, which are available for operational radars but are equally applied to X-band radars [103], can be implemented for nowcasting purposes, supporting better estimations of both atmospheric and hydrological characteristics during flash flooding situations.…”

Section: Discussionmentioning

confidence: 99%

A Multi-Platform Hydrometeorological Analysis of the Flash Flood Event of 15 November 2017 in Attica, Greece

et al. 2018

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Urban areas often experience high precipitation rates and heights associated with flash flood events. Atmospheric and hydrological models in combination with remote-sensing and surface observations are used to analyze these phenomena. This study aims to conduct a hydrometeorological analysis of a flash flood event that took place in the sub-urban area of Mandra, western Attica, Greece, using remote-sensing observations and the Chemical Hydrological Atmospheric Ocean Wave System (CHAOS) modeling system that includes the Advanced Weather Research Forecasting (WRF-ARW) model and the hydrological model (WRF-Hydro). The flash flood was caused by a severe storm during the morning of 15 November 2017 around Mandra area resulting in extensive damages and 24 fatalities. The X-band dual-polarization (XPOL) weather radar of the National Observatory of Athens (NOA) observed precipitation rates reaching 140 mm/h in the core of the storm. CHAOS simulation unveils the persistent orographic convergence of humid southeasterly airflow over Pateras mountain as the dominant parameter for the evolution of the storm. WRF-Hydro simulated the flood using three different precipitation estimations as forcing data, obtained from the CHAOS simulation (CHAOS-hydro), the XPOL weather radar (XPOL-hydro) and the Global Precipitation Measurement (GMP)/Integrated Multi-satellitE Retrievals for GPM (IMERG) satellite dataset (GPM/IMERG-hydro). The findings indicate that GPM/IMERG-hydro underestimated the flood magnitude. On the other hand, XPOL-hydro simulation resulted to discharge about 115 m3/s and water level exceeding 3 m in Soures and Agia Aikaterini streams, which finally inundated. CHAOS-hydro estimated approximately the half water level and even lower discharge compared to XPOL-hydro simulation. Comparing site-detailed post-surveys of flood extent, XPOL-hydro is characterized by overestimation while CHAOS-hydro and GPM/IMERG-hydro present underestimation. However, CHAOS-hydro shows enough skill to simulate the flooded areas despite the forecast inaccuracies of numerical weather prediction. Overall, the simulation results demonstrate the potential benefit of using high-resolution observations from a X-band dual-polarization radar as an additional forcing component in model precipitation simulations.

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Monthly Hydrological Indicators to Assess Possible Alterations on Rivers’ Flow Regime

Pumo

Francipane

Cannarozzo

et al. 2018

Water Resour Manage

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Exploring single polarization X-band weather radar potentials for local meteorological and hydrological applications

Cited by 25 publications

References 45 publications

Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model

Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model

A Multi-Platform Hydrometeorological Analysis of the Flash Flood Event of 15 November 2017 in Attica, Greece

Monthly Hydrological Indicators to Assess Possible Alterations on Rivers’ Flow Regime

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