Objective

"As typhoons move, our approach to oceanic observation errors must also adapt."                  Accurate Sea Surface Temperature (SST) prediction is crucial for forecasting extreme weather and typhoon trajectories. Most Conventional Data Assimilation (DA) techniques have uniformly applied a Fixed Observation Error (Fixed R) to observation data. However, under extreme weather conditions like typhoons, sea surface variability differs drastically depending on the location relative to the storm.
 

Based on the theory by He (2024), which suggests that error characteristics vary by quadrant relative to the typhoon's heading, this simulation demonstrates the effectiveness of Adaptive Data Assimilation (DA) by dynamically adjusting the Observation Error Covariance (R).