Summary of Enhanced Precision in Rainfall Forecasting For Mumbai: Utilizing Physics Informed Convlstm2d Models For Finer Spatial and Temporal Resolution, by Ajay Devda et al.
Enhanced Precision in Rainfall Forecasting for Mumbai: Utilizing Physics Informed ConvLSTM2D Models for Finer Spatial and Temporal Resolution
by Ajay Devda, Akshay Sunil, Murthy R, B Deepthi
First submitted to arxiv on: 1 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A deep learning spatial model is introduced to enhance rainfall prediction accuracy on a finer scale, specifically targeting cities. Previous investigations into rainfall prediction leveraged numerical weather prediction methods, statistical approaches, and deep learning techniques. This study hypothesizes that integrating physical understanding improves the precipitation prediction skill of deep learning models for finer spatial scales. A physics-informed ConvLSTM2D model is used to predict precipitation 6hr and 12hr ahead for Mumbai, India. The model is trained on ERA5 reanalysis data, selecting predictor variables across various geopotential levels. The study utilizes four different grids representing different spatial grid locations of Mumbai, reflecting current advancements in meteorological research emphasizing efficiency and localized precision. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps predict rainfall in tropical areas like India. Rainfall prediction is tricky because the weather patterns are complex and changeable. Scientists have tried using computers to forecast the rain before, but this study uses a special kind of computer model that combines physical understanding with deep learning techniques. The goal is to make more accurate predictions for specific cities, like Mumbai. The team tested their method by training it on historical data from different parts of Mumbai and found it worked well. |
Keywords
* Artificial intelligence * Deep learning * Precision
