Related Experiment Video
Updated: Jun 27, 2026
06:10
Using Generative Art to Convey Past and Future Climate Transitions
Published on: March 31, 2023
The computational future for climate and Earth system models: on the path to petaflop and beyond
Warren M Washington1, Lawrence Buja, Anthony Craig
1National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO 80305, USA. wmw@ucar.edu
Summary
Climate and Earth system models evolved from individual components to comprehensive systems. Advances in knowledge and computing power enable more complex Earth system modeling.
Area of Science:
- Earth System Science
- Climate Modeling
- Computational Science
Background:
- Climate and Earth system models developed from individual components (atmospheric, ocean, etc.).
- Early research aimed to integrate biogeochemical cycles into climate models.
- Initial progress was constrained by computational power and process understanding.
Purpose of the Study:
- To trace the historical development of climate and Earth system models.
- To highlight the evolution towards comprehensive Earth system modeling.
- To discuss the impact of computational advancements on model development.
Main Methods:
- Historical review of climate and Earth system model development.
- Discussion of computational limitations and advancements.
- Analysis of successes and challenges in model integration.
Main Results:
- Significant progress in knowledge, observations, and supercomputing capabilities.
- Earth system models now incorporate interactive biogeochemical processes.
- Current supercomputers are better equipped for complex model simulations.
Conclusions:
- The evolution of climate and Earth system models is marked by increasing complexity and integration.
- Supercomputing advancements have been crucial for overcoming previous limitations.
- Future development hinges on continued progress in scientific understanding and computational resources.
Related Concept Videos
01:50Global Climate Change
Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
01:16What is Climate?
Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
01:17Ampere-Maxwell's Law: Problem-Solving
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the problem,...
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the problem,...
01:27Microbes and Climate Change
Microorganisms are pivotal agents in Earth's biogeochemical cycles, significantly influencing climate dynamics through their metabolic activities. These microbes modulate the levels of key greenhouse gases by both contributing to and helping mitigate climate change.Microbial Contributions to Greenhouse Gas EmissionsRising global temperatures accelerate microbial metabolism, which, in turn, speeds up the decomposition of organic matter. This process releases carbon dioxide (CO₂) through...
01:20Parallel Processing
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
01:20Maxwell-Boltzmann Distribution: Problem Solving
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by