API Client for NASA POWER Global Meteorology, Surface Solar Energy and Climatology in R

Download meteorological data from NASA POWER using a simple Python API client (https://power.larc.nasa.gov/).

Simple Python script to download historical meteorological data records from 1981 to today for any place on Earth from Nasa Power: https://power.larc.nasa.gov/data-access-viewer/

Official code for arXiv:2604.11807 - Physics-Informed State Space Models for Off-Grid Solar Forecasting

Bot for downloading Solar irradiance data at target locations and region surrounded it.

Instantly estimate soil water loss worldwide!

☀️ Analyze NASA POWER solar irradiance data with a professional Python toolkit for accurate assessments in climate research and renewable energy.

Solar Radiation Prediction from NASA POWER data Ver.2

Professional Python toolkit for analyzing NASA POWER satellite-derived solar irradiance data with multi-language support, document export capabilities, and comprehensive statistical analysis features

Machine learning-based flood and flash flood prediction across 8 Malaysian cities using Decision Tree, Random Forest, and XGBoost. 16-year NASA POWER MERRA-2 dataset (2010–2026).

Wind vs. Solar LCOE feasibility analysis at a real Ankara site (METU K1) using live PVGIS & NASA POWER APIs, DCF modelling, and 2026 Turkish market data

Automate the downloading and merging process from NASA POWER dataset

Official code: Physics-Informed Cross-Attention Networks for Solar Irradiance Forecasting with Dual Self+Cross Attention

This program aims to develop a solar potential map of India.

Official code for arXiv:2604.13455 - Physics-Guided CNN-BiLSTM for Solar Irradiance Forecasting

Project analyzing the relationship between El Niño weather patterns and cocoa futures market volatility using NASA satellite data and financial market analysis.

AI-based Smart Farming Decision Support System using multi-temporal NASA climate data | Decision Tree, Random Forest & Gradient Boosting | ACLI Index | 92.61% Accuracy | IEEE WAMS 2026 Accepted Paper

Official code for arXiv:2604.11909 - Thermodynamic Liquid Manifold Networks for Autonomous Microgrids

Web-based drought monitoring and SPI drought analysis platform by AgriMetSoft.

Feasibility study and machine learning forecasting pipeline (XGBoost) for a 1.08 MWp rooftop solar PV microgrid at École Centrale Casablanca. Integrates live NASA POWER meteorology and physical flat-roof spacing constraints.