Implementation of Quality Control Algorithms for Improved Rain Rate Estimates from Commercial Microwave Links at City Scale

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F24%3A00376918" target="_blank" >RIV/68407700:21110/24:00376918 - isvavai.cz</a>

Výsledek na webu

<a href="http://program-icud2024.iwcconferences.com/" target="_blank" >http://program-icud2024.iwcconferences.com/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Implementation of Quality Control Algorithms for Improved Rain Rate Estimates from Commercial Microwave Links at City Scale

Popis výsledku v původním jazyce

In order to utilize the rainfall data from OS sensors, it is necessary to perform quality control (QC) because the devices are neither originally designed for rainfall monitoring nor properly maintained or installed. Therefore, they can be affected by various factors other than rainfall, such as environmental conditions and technical issues. By implementing QC, potential errors and uncertainties in the data can be identified and corrected, and the accuracy and precision of the rainfall estimates can be improved. Previous studies have indicated that performing QC on CML signal level data, which serves as the input for the retrieval algorithms, can improve rainfall retrieval results and rain field reconstruction. In this paper, we investigate the application effects of QC methods applicable to single links (SL) and QC methods relying on neighbouring links (NL) at city scale with high density of CMLs and short correlation lengths. We also investigate the synergy of simultaneously utilizing both QC methods for short time steps of 5 minutes. The findings of this study provide guidance for improving the accuracy of retrieval and rain field reconstruction results.

Název v anglickém jazyce

Implementation of Quality Control Algorithms for Improved Rain Rate Estimates from Commercial Microwave Links at City Scale

Popis výsledku anglicky

In order to utilize the rainfall data from OS sensors, it is necessary to perform quality control (QC) because the devices are neither originally designed for rainfall monitoring nor properly maintained or installed. Therefore, they can be affected by various factors other than rainfall, such as environmental conditions and technical issues. By implementing QC, potential errors and uncertainties in the data can be identified and corrected, and the accuracy and precision of the rainfall estimates can be improved. Previous studies have indicated that performing QC on CML signal level data, which serves as the input for the retrieval algorithms, can improve rainfall retrieval results and rain field reconstruction. In this paper, we investigate the application effects of QC methods applicable to single links (SL) and QC methods relying on neighbouring links (NL) at city scale with high density of CMLs and short correlation lengths. We also investigate the synergy of simultaneously utilizing both QC methods for short time steps of 5 minutes. The findings of this study provide guidance for improving the accuracy of retrieval and rain field reconstruction results.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10501 - Hydrology

Projekt

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Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů