Agrolib are a set of libraries for agrometeorological modeling and climate analysis. They include a numerical solution for three-dimensional water and heat flow in the soil, water balance, meteorological data interpolation, daily weather generator, radiation budget, snow accumulation and melt, plant development and plant water uptake.

Elastic thickness of the lithosphere, yield strength envelope, and heat flow calculations.

Gradient boosting regression algorithm for prediction of geothermal heat flow (in Antarctica)

These are real and live Machine learning and statistical models built in R language and python by kamil-Bello Furqan

Regional aggregate heat flow distributions and heat flow anomaly quantification