theIASHub | 17 Jun, 2024 | 4
Context: Indian National Centre for Ocean Information Services (INCOIS) has developed a Bayesian Convolutional Neural Network to predict the emergence of El Niño and La Niña conditions they are different phases of El Niño Southern Oscillation (ENSO) up to 15 months in advance.
Bayesian Convolutional Neural Network
ENSO
oIn India, while El Niño conditions usually lead to a weak monsoon and intense heatwaves, La Niña conditions result in a strong monsoon.
Comparison of BCNN with Existing Weather Models
oThere are two main types of weather models: statistical models and dynamic models.
oStatistical models rely on diverse datasets from various sources for generating forecasts.
oDynamic models utilize 3D mathematical simulations of the atmosphere using High Performance Computers (HPC).
üDynamic models generally provide more accurate forecasts compared to statistical models due to their detailed simulations.
oIn contrast, other existing models typically provide predictions up to six to nine months in advance.
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