Rajni

Accurate forecasting of the Indian Ocean Dipole (IOD) and El-Niño-Southern Oscillation (NINO3.4) is crucial for understanding regional weather patterns in the Indian subcontinent. Addressing the challenges associated with IOD and NINO3.4 prediction, a robust multi-task autoregressive deep learning model is introduced for precise forecasting of these indices and key grid projections sea surface temperature (SST), surface-level pressure gradient (SLG), and horizontal wind velocity (U-Comp) over a short to mid-term window (20 months). Utilizing spatiotemporal (SST, SLG, U-Comp) and temporal (IOD and NINO3.4) modalities, the proposed model predicts future IOD and NINO3.4, as well as SST, SLG, and U-Comp, in an autoregressive scheme. The multi-task learning component regularizes the model, effectively capturing the evolving dynamics of global patterns conditioned on IOD and NINO3.4. The comprehensive evaluation explores various task settings, including a duo-setting that predicts IOD or NINO3.4 with spatiotemporal information, showcasing notable proficiency. In a multi-task environment, where both temporal IOD, NINO3.4, and spatiotemporal SST, SLG, U-Comp are predicted, the model successfully forecasts IOD and NINO3.4 indices alongside grid projections with modest accuracy in root mean square error (RMSE). To enhance the model’s interpretability regarding spatiotemporal dynamics, a tailored version of Grad-CAM is employed, providing critical insights for climate prediction. This research advances climate prediction models, offering a comprehensive framework with significant implications for informed decision-making in the Indian subcontinent’s climatic context.

The demand for energy has increased worldwide and the planet is facing acute shortage of resources such as fossil fuels for production of energy. These unrenewa

The Visakhapatnam port, India is a major natural port, situated in between the Kolkata and Chennai on the East Coast and in terms of latitude and longitude its location is 17.6856∘ N, 83.2160∘ E has experienced an extreme wave oscillations 2.0 to 6.0 m in the midst of its severe weather events. In this paper numerical studies are performed to analyze the frequency distribution over the oceanic surface of standing waves in Visakhapatnam port at four respective synthetic record stations in presence of partially reflecting harbor. The convergence study is conducted to obtain the numerical accuracy of the scheme and simulation results are validated with the available studies experimentally from Ippen and Goda (1963) and Lee (1971) also with the analytical approximations. Further, the spectral density is determined corresponding to the wave period for the incident waves striking with several directions towards the Visakhapatnam port at four different record stations. The computation of the resonant frequencies is conducted in the Visakhapatnam port to examine the safe locations for the moored ship. Abstract goes here.