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CliMA

@ClimateMachine

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An alliance of scientists and engineers @caltech @mit and @nasajpl building the first Earth system model that automatically learns from diverse data sources.

Pasadena, CA
Joined November 2018
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@ClimateMachine
CliMA
2 years
Today! 🎊.
@ClimateMachine
CliMA
2 years
JAMES @theAGU will have a CliMA Earth System Model special collection. Will open for submissions this June 30.
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@ClimateMachine
CliMA
2 years
Wishing so much happiness to all at #Caltech2023 commencement. Congratulations to our CliMA family Haakon, Ronak, and Dr. Ignacio 💙.
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@ClimateMachine
CliMA
2 years
RT @CaltechESE: A beautiful evening celebrating our #Caltech2023 graduates @CaltechESE 🎉🎉🎉 We are so proud of you and we are so excited for….
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@ClimateMachine
CliMA
2 years
JAMES @theAGU will have a CliMA Earth System Model special collection. Will open for submissions this June 30.
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@ClimateMachine
CliMA
2 years
RT @JuliaHub_Inc: The 2023 Julia User & Developer Survey is now open!.Click here to participate: Julia users and #d….
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@ClimateMachine
CliMA
2 years
One of our goals at CliMA is to use observations to inform our climate model. In this blog post, we give an introduction to ensemble Kalman inversion, a tool we use extensively to achieve this.
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clima.caltech.edu
By Eviatar Bach and Oliver Dunbar To understand this blog post, you will need some basic familiarity with probability (Bayes’ theorem, covariance) and multivariate calculus. In climate modeling, sm…
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@ClimateMachine
CliMA
2 years
Thank you @RenatoBraghiere.
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@ClimateMachine
CliMA
2 years
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:
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@ClimateMachine
CliMA
2 years
We have launched the CliMA Newsletter. Please click through and join our mailing list.
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@ClimateMachine
CliMA
2 years
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
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@ClimateMachine
CliMA
3 years
Understanding the probability of #extremeweather events requires specialized statistical tools. CliMA researchers are exploring these for future use with simulations from the CliMA Earth System Model. #uncertainty #simulation #sampling #bootstrapping
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clima.caltech.edu
Weather disasters are extremely damaging to humans (e.g., severe storms, heat waves, and flooding), our livelihoods (e.g., drought and wildfire), and to the environment (e.g., coral bleaching via m…
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@ClimateMachine
CliMA
3 years
GRIDDINGMACHINE is a new database and software to share global datasets. We aim to maximally reduce the time used to find and access datasets. #JuliaLang #MATLAB #GNUoctave #pythonprogramming #Rprogramminglanguage
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@ClimateMachine
CliMA
3 years
RT @Caltech: How do we know if extreme weather events can be attributed to climate change?. Tapio Schneider, of @ClimateMachine, answers:.h….
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scienceexchange.caltech.edu
Extreme event attribution quantifies how likely extreme weather events are with anthropogenic (human-caused) climate change and without it.
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@ClimateMachine
CliMA
3 years
RT @CaltechESE: Check out the stellar research one of our @Caltech SURF students completed this summer! Stay tuned for more!.
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@ClimateMachine
CliMA
3 years
At CliMA, we've developed an automated algorithm that finds when, and where, we should collect data to best inform climate models
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@ClimateMachine
CliMA
3 years
RT @APS_GPC: Climate-physics-curious? Sign up for the new GPC virtual seminar series! Prof. Tapio Schneider and Prof. @MorganEONeill will….
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@ClimateMachine
CliMA
3 years
Methods from Weather Forecasting Can Be Adapted to Assess Risk of COVID-19 Exposure.
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@ClimateMachine
CliMA
3 years
RT @ValeriaVally21: And. It's a wrap!.The students at the Grad Student Math Modeling Camp @UDelaware did an amazing job, going way above&b….
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