Blog

Bridging the gap between disciplines at CliMA

Legendary basketball coach for the Chicago Bulls, Phil Jackson, once said, “The strength of the team is each individual member. The strength of each member is the team.” At CliMA, our team is made up of individuals from diverse academic backgrounds who have come together to work on one of the defining global problems of our time. The complexity of predicting climate change and ascertaining the associated uncertainties demands expertise from diverse, traditionally disparate, academic and professional backgrounds. At CliMA, we have assembled an A-list team that is taking on the challenge to provide the accurate and actionable climate predictions…
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CliMA 0.1: A first milestone in the next generation of climate models

At CliMA, we are building an Earth System Model (ESM) that harnesses more data than ever before to produce accurate and precise climate predictions. Today, the release of CliMA 0.1 brings us one step closer toward achieving our goals. CliMA v0.1.0 consists of code for large eddy simulations (LES) of turbulent flows in atmosphere and oceans and for dynamical cores of general circulation models (GCM) for the ocean and atmosphere. All CliMA code is written in Julia, a dynamic, high-level programming language for high-performance scientific computing. Caltech Postdoctoral Scholars Akshay Sridhar and Zhaoyi Shen, together with others, are in the…
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50th Anniversary of Earth Day

Fifty years ago today, millions gathered in demonstrations, teach-ins, and community-cleanups, with words and deeds demanding a more sustainable future. The first Earth Day marked the beginning of the environmental movement, and it achieved results. The Clean Air Act and the Environmental Protection Agency were established, leading to cleaner air and water for all of us. To reflect on five decades of environmental change, a group of friends and colleagues led by Philippe Tortell (with whom I went to graduate school) wrote a series of essays, released as a book today.

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Earth System Modeling 2.0

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized in models, such as clouds, turbulence, and ecosystems. But breakthroughs in the accuracy of climate projections are finally within reach. New tools from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both. Scientific, computational, and mathematical challenges need to be confronted to realize such an ESM, for example, developing parameterizations suitable for automated learning, and learning algorithms suitable for ESMs. While these challenges are substantial, building an ESM that learns…
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Climate goals and computing the future of clouds

How low clouds respond to warming remains the greatest source of uncertainty in climate projections. Climate models projecting that much less sunlight will be reflected by low clouds when the climate warms indicate that CO2 concentrations can only reach 470 ppm before the 2℃ warming threshold of the Paris agreement is crossed—a CO2 concentration that will probably be reached in the 2030s. By contrast, models projecting a weak decrease or increase in low-cloud reflection indicate that CO2 concentrations may reach almost 600 ppm before the Paris threshold is crossed. In a new paper, we outline how new computational and observational tools enable us to reduce these vast…
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