arXiv subjects

Harini S

Publications and source records attributed to Harini S.

3 recordsLinked to original sources

arXiv2026

Prediction and Predictability of the Wet-Season Rainfall over Southeast India

The challenge in predicting sub-regional climate within the Indian monsoon region is exacerbated by its increasing variability in a warming world. While exploring the seasonal predictability of rainfall over the state of Tamil Nadu in southeast India, we identify an overall increase in the monthly rainfall and its variability in recent years due to an increase in surface temperature, water vapour and moisture convergence. We attribute the increasing excess rainfall to a long-term reduction in convective inhibition. We further find an increasing trend in the length of the rainy season due to an earlier onset and a delayed withdrawal of the large-scale monsoon over the southeastern and southwestern regions of southern peninsular India, respectively. Further, the simultaneous (0- month lead) predictability of the primary wet-season (October-December, OND) rainfall over Tamil Nadu is dominated by sea surface temperature (SST) anomalies in the North Indian Ocean. However, a global tropical SST climate network reveals a high potential predictability and potential to realize significant forecast skill at a lead time of up to 10 months. The long-lead predictability arises from SST and rainfall interactions across the tropical Indo-Pacific and equatorial Atlantic regions. Our findings provide a robust data-driven methodology for skillful seasonal rainfall prediction over Tamil Nadu, despite the increasing rainfall variability.

physics.ao-ph↗

arXiv2024

Enhancing Image Retrieval : A Comprehensive Study on Photo Search using the CLIP Mode

Photo search, the task of retrieving images based on textual queries, has witnessed significant advancements with the introduction of CLIP (Contrastive Language-Image Pretraining) model. CLIP leverages a vision-language pre training approach, wherein it learns a shared representation space for images and text, enabling cross-modal understanding. This model demonstrates the capability to understand the semantic relationships between diverse image and text pairs, allowing for efficient and accurate retrieval of images based on natural language queries. By training on a large-scale dataset containing images and their associated textual descriptions, CLIP achieves remarkable generalization, providing a powerful tool for tasks such as zero-shot learning and few-shot classification. This abstract summarizes the foundational principles of CLIP and highlights its potential impact on advancing the field of photo search, fostering a seamless integration of natural language understanding and computer vision for improved information retrieval in multimedia applications

cs.CV↗

arXiv2023

TiO2 multi-leg nanotubes for Surface-enhanced Raman scattering

In the recent past, significant research efforts have been put forth to fabricate low-cost noble metal-free substrates for surface-enhanced Raman spectroscopy (SERS) applications. Here we propose semiconducting TiO2 multi-leg nanotubes (TiO2 MLNTs, with and without the gold nanoparticle coating) as SERS substrates. TiO2 MLNTs show unique multi-leg morphology compared to the conventional non-multi-leg tubes and possess better light-harvesting properties. TiO2 MLNTs are fabricated with a simple and versatile single-step electrochemical anodization method. Remarkable high SERS sensitivity is observed towards the detection of Methylene blue (MB), up to nM concentration (E.F. ~104). The same is attributed to the resonantly matched photonic absorption edge of TiO2 MLNTs with the wavelength of incident laser probe light. On the other hand, gold nanoparticle-coated TiO2 MLNTs demonstrated further enhancement in SERS sensitivity (E.F. ~105, for nM of MB) facilitated by the synergy that exists between the plasmonic modes (LSPRs) of Au and the photonic absorption mode of TiO2 MLNTs.

physics.chem-ph↗