Downscaling near-surface atmospheric fields with multi-objective Genetic Programming
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| Title: | Main Title: Downscaling near-surface atmospheric fields with multi-objective Genetic Programming |
| Description: | Abstract: The coupling of models for the different components of the Soil-Vegetation-Atmosphere-System is required to investigate component interactions and feedback processes. However, the component models for atmosphere, land-surface and subsurface are usually operated at different resolutions in space and time owing to the dominant processes. The computationally often more expensive atmospheric models, for instance, are typically employed at a coarser resolution than land-surface and subsurface models. Thus up- and downscaling procedures are required at the interface between the atmospheric model and the land-surface/subsurface models. We apply multi-objective Genetic Programming (GP) to a training data set of high-resolution atmospheric model runs to learn equations or short programs that reconstruct the fine-scale fields (e.g., 400 m resolution) of the near-surface atmospheric state variables from the coarse atmospheric model output (e.g., 2.8 km resolution). Like artificial neural networks, GP can flexibly incorporate multivariate and nonlinear relations, but offers the advantage that the solutions are human readable and thus can be checked for physical consistency. Using the Strength Pareto Approach for multi-objective fitness assignment allows us to consider multiple characteristics of the fine-scale fields during the learning procedure. |
Responsible Party
| Creator: | Tanja Zerenner (Author) |
| Publisher: | CRC/TR32 Database (TR32DB) |
| Publication Year: | 2014 |
Topic
| TR32 Topic: | Atmosphere |
| Related Subproject: | C4 |
| Subjects: | Keywords: PhD Report, Downscaling and Disaggregation, Spatial Heterogeneity |
File Details
| Filename: | report5_paperdraft.pdf |
| Data Type: | Text - Text |
| File Size: | 4.4 MB |
| Date: | Available: 08.09.2014 |
| Mime Type: | application/pdf |
| Data Format: | |
| Language: | English |
| Status: | Completed |
Constraints
| Download Permission: | Only Project Members |
| General Access and Use Conditions: | For internal use only. |
| Access Limitations: | For internal use only. |
| Licence: | [TR32DB] Data policy agreement |
Geographic
Specific Information - Report
| Report Date: | 7th of July, 2014 |
| Report Type: | PhD Report |
| Report City: | Bonn, Germany |
| Report Institution: | Meteorological Institute, University Bonn |
| Number of Pages: | 18 (1 - 18) |
| Further Information: | TR32 Student Report Phase II |
Metadata Details
| Metadata Creator: | Tanja Zerenner |
| Metadata Created: | 08.09.2014 |
| Metadata Last Updated: | 08.09.2014 |
| Subproject: | C4 |
| Funding Phase: | 2 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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Dataset Statistics
| Page Visits: | 616 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 2 |
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