Name
Abstract | ||
|---|---|---|
Earth system models (ESMs) are based on physical principles that are intended to emulate climate behavior. They're the primary mechanisms for obtaining projections of future conditions under different climate change scenarios. Because ESMs rely on the distinct modeling of certain physical processes and initial conditions, different ESMs can produce different responses for the same external forcing... |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/MCSE.2015.105 | Computing in Science & Engineering |
Keywords | Field | DocType |
Meteorology,South America,Ocean temperature,Uncertainty,Land surface temperature,Mathematical model,Earth | Land surface temperature,Climate model,Climate change,Computer science,Theoretical computer science,Earth system model,Artificial intelligence,Weather forecasting,Meteorology,Multi-task learning,Earth system science,Structure learning,Machine learning | Journal |
Volume | Issue | ISSN |
17 | 6 | 1521-9615 |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| André Ricardo Gonçalves | 1 | 16 | 6.43 |
| Fernando J. Von Zuben | 2 | 831 | 81.83 |
| Arindam Banerjee | 3 | 4716 | 233.98 |