Next generation Land model developed in CliMA is ready to simulate fluxes and hyperspectral canopy optical properties at the same time. Example of the model simulated solar-induced chlorophyll fluorescence (SIF). Read the blog: clima.caltech.edu/2023/05/01…

We have launched the CliMA Newsletter. Please click through and join our mailing list. conta.cc/42R9rq7

Harnessing full power of data and #machinelearning in #EarthSystemModeling requires flexible learning methods to deal with indirect and #noisydata. We demonstrated that #ensembleKalmanprocesses can aid in this challenging task. #JuliaLang tinyurl.com/3xa3t865

GRIDDINGMACHINE is a new database and software to share global datasets. We aim to maximally reduce the time used to find and access datasets. clima.caltech.edu/2022/08/19… #JuliaLang #MATLAB #GNUoctave #pythonprogramming #Rprogramminglanguage

At CliMA, we've developed an automated algorithm that finds when, and where, we should collect data to best inform climate models clima.caltech.edu/2022/07/21…

Methods from Weather Forecasting Can Be Adapted to Assess Risk of COVID-19 Exposure clima.caltech.edu/press-medi…

CliMA awarded Google Cloud Customer Award Winner: Sustainability clima.caltech.edu/press-medi…

With the goal of developing an accessible, performant high-resolution model of atmospheric phenomena, the CliMA team has developed a new large-eddy simulation (LES) framework called the ClimateMachine: clima.caltech.edu/2022/01/13…

Our team is currently working on exploring and predicting how the climate will change by creating computer models of the real world. 🌍 @Caltech youtube.com/watch?v=Puifkybe…

At CliMA, we are in the process of running hundreds of simulations to create an atlas of data under various conditions. These will be used to train out global models and be made freely available for research. #climatechange #machinelearning #ai #science #computing