The MSG Technique: Improving Commercial Microwave Link Rainfall Intensity by Using Rain Area Detection from Meteosat Second Generation

Autor: H. Oliver Gao, Joost C. B. Hoedjes, Ben H. P. Maathuis, Kingsley K. Kumah, Noam David, Bob Su
Přispěvatelé: Department of Water Resources, UT-I-ITC-WCC, Faculty of Geo-Information Science and Earth Observation
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Remote Sensing, Vol 13, Iss 3274, p 3274 (2021)
Remote sensing, 13(16):3274, 1-17. Multidisciplinary Digital Publishing Institute (MDPI)
Remote Sensing; Volume 13; Issue 16; Pages: 3274
ISSN: 2072-4292
Popis: Commercial microwave link (MWL) used by mobile telecom operators for data transmission can provide hydro-meteorologically valid rainfall estimates according to studies in the past decade. For the first time, this study investigated a new method, the MSG technique, that uses Meteosat Second Generation (MSG) satellite data to improve MWL rainfall estimates. The investigation, conducted during daytime, used MSG optical (VIS0.6) and near IR (NIR1.6) data to estimate rain areas along a 15 GHz, 9.88 km MWL for classifying the MWL signal into wet–dry periods and estimate the baseline level. Additionally, the MSG technique estimated a new parameter, wet path length, representing the length of the MWL that was wet during wet periods. Finally, MWL rainfall intensity estimates from this new MSG and conventional techniques were compared to rain gauge estimates. The results show that the MSG technique is robust and can estimate gauge comparable rainfall estimates. The evaluation scores every three hours of RMSD, relative bias, and r2 based on the entire evaluation period results of the MSG technique were 2.61 mm h−1, 0.47, and 0.81, compared to 2.09 mm h−1, 0.04, and 0.84 of the conventional technique, respectively. For convective rain events with high intensity spatially varying rainfall, the results show that the MSG technique may approximate the actual mean rainfall estimates better than the conventional technique.
Databáze: OpenAIRE