Reference Evapotranspiration Comparison of Any Two Cities Using Python and NASA Power’s API

This study delves into the science and practical application of estimating reference evapotranspiration (ET_o) with a specific focus on city environments. Urbanization’s growing footprint has significant implications for water resource management and environmental engineering, making accurate ET_o assessments crucial for informed decision-making. The present research presents a code developed to facilitate the comparison of ET_o dynamics between two cities, spanning from 1990 to the present day. Leveraging NASA’s powerful climate datasets through their APIs, this code addresses key data management challenges, ensuring the reliability and quality of the analysis. Importantly, the code employs the Penman-Monteith equation, renowned for its accuracy, to enhance precision in ET_o estimation. The code provides an intuitive interface, empowering researchers and practitioners to explore and contrast ET_o patterns between cities of their choice within specified date ranges. The implementation relies on a selection of Python libraries, including Geocoder, NumPy, and Matplotlib, to facilitate seamless data processing, visualization, and interpretation. Validation exercises were conducted against field data collected in Haryana, India, establishing the code’s robustness and its potential as a powerful tool for climate data analysis. This research significantly advances city climate studies, enabling a deep understanding of ET_o variations between diverse city settings. This study promotes data-driven decision-making and sustainable practices for a resilient future.