A RESTful API to access weather data from the India Meteorological Department.
Energy measurement framework for Mobile Apps
Analysis of the projected changes of the Indian summer monsoon using 32 CMIP6 models
A supervised Learning approach to find the trends on which the monsoon rainfall depends and its prediction.
A continuous, absolute-dated, 150,000-year record of monsoon hydroclimate dynamics from a permanent lagoon in the core monsoon region of northern Australia, compared to global circulation model hindcasts
Weather Showing Project is a simple and responsive web application that displays real-time weather information for any city. It shows temperature, humidity, wind speed, and conditions using a clean interface and live API data, helping users quickly check current weather in an easy and reliable way.
Restaurant Food Ordering Chatbot: An AI-driven assistant for your e-commerce site to streamline food ordering. Built with Node.js, Express.js, and Mongoose, it handles menu navigation, order placement, status tracking, and general inquiries, enhancing user engagement and automating customer support.
This repo contains R code to grab ITF data from NOAA CPC ftp server : https://ftp.cpc.ncep.noaa.gov/fews/itf/
Python program used to get power readings via the Monsoon HV Power Monitor
Code to extract annual drought features from daily drought indices
Monsoons & Air Quality in Seoul, South Korea
India's Climate Digital Twin — AI-powered geospatial reanalysis and prognostic forecasting platform fusing IMD and MOSDAC INSAT-3D satellite data. Built for ISRO BAH 2026.
Interactive visualization of possible historical dhow voyages and port connections across the Indian Ocean
The Climate Dynamics Lab at IIT Delhi studies the Indian monsoon and its response to climate change. Using high-resolution modeling, observational data, and machine learning, we investigate monsoon variability, extreme events, and long-term trends to improve prediction and support regional climate resilience.
🌊 ENSO Macro Risk Desk - A Bloomberg-style terminal mapping El Niño/La Niña to commodity & sector risk, with Granger+CCM causal testing. Live on HF Spaces.
Hypothesis test of shifting fire intensity from 'natural' to 'anthropogenic' fire regime in the Late Pleistocene of Sahul
ML pipeline to forecast Mumbai's monthly rainfall using 121 years of IMD data. Compares XGBoost, Random Forest, SARIMA, LSTM, and Prophet — XGBoost achieves a ~69% RMSE reduction over SARIMA. Includes 12-month forward forecast and trained model.
Monthly weather data and best travel seasons for Maldives - temperature, rainfall, wind conditions by atoll
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