| Autor: |
Bibraj Raj, Swaroop Sahoo, N. Puviarasan, V. Chandrasekar |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Atmosphere, Vol 15, Iss 2, p 154 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2073-4433 |
| DOI: |
10.3390/atmos15020154 |
| Popis: |
North East Monsoon (NEM) is the major source of rainfall for the south-eastern parts of peninsular India. Short time rainfall prediction data (i.e., nowcasting) are based on the observations from Doppler weather radars which has a high spatial and temporal resolution. This study focuses on the short-term ensemble prediction system using weather radar data to predict precipitation during the NEM and is the first of its kind in the Indian region to make an assessment of the operational performance of the prediction system. Six rainfall events have been studied for the assessment of short-term prediction system where the precipitation systems are different and include a tropical storm observed over different days during the 2022 NEM season. To assess the performance of the system, Fractional Skill Scores (FSS) at a 1 km window have been computed for a lead time of 0–2 h for all the rainfall events with more than 750 samples using different optical flow methods and ensemble sizes. The best average skill score and maximum skill score obtained at a 2 h lead time is 0.65 and 0.78 for tropical storms, 0.5 and 0.78 for stratiform and 0.15 and 0.38 for convective precipitation. It has found that the performance of the model is best for precipitation systems that are widespread and have a longer life period. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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