Atmospheric Downscaling using Genetic Programming
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| Title: | Main Title: Atmospheric Downscaling using Genetic Programming |
| Description: | Abstract: The coupling of atmospheric, land-surface and subsurface hydrological models requires appropriate up- and downscaling procedures. Hydrological models are usually based on high spatiotemporal resolution. Applying atmospheric models as the same high resolution is in the majority of cases computationally not feasible. In the rst phase of the TR 32 a downscaling scheme has been developed to gain high-resolution forcing data for land-surface and hydrological models from the coarser atmospheric model output. This scheme consist of three steps. Step 1 is a bi-quadratic spline interpolation. In step 2 deterministic downscaling rules are applied, which are based on dependencies between the atmospheric variables in the lower boundary layer and high-resolution data on surface properties. Finally in step 3 the missing small-scale variability is added as noise. The performance of the scheme is very di erent for each of the variables and strongly dependent on the prevailing weather conditions. This is due to the fact that so far deterministic rules could be found only for some variables and under certain conditions. Up to now the interdependencies between the surface parameters and the atmospheric variables have been only exploited by calculating linear Pearson correlations between the surface properties and the atmospheric variables at one and the same grid point. In order to broaden the search space we now want to consider also non-linear dependencies, temporally delayed dependencies and relations between di erent grid points. There are in nite possible interdependencies and rules, which makes it impossible to search by hand. Therefore we will set up an automatic program based on the method of genetic programming to enable the computer to automatically learn possible downscaling rules from data. |
Responsible Party
| Creator: | Tanja Zerenner (Author) |
| Publisher: | CRC/TR32 Database (TR32DB) |
| Publication Year: | 2013 |
Topic
| TR32 Topic: | Atmosphere |
| Related Subproject: | C4 |
| Subject: | Keyword: PhD Report |
File Details
| Filename: | Report1_Zerenner_2012.pdf |
| Data Type: | Text - Text |
| File Size: | 1.8 MB |
| Date: | Available: 16.07.2012 |
| 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 |
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Specific Information - Report
| Report Date: | 16th of July, 2012 |
| Report Type: | PhD Report |
| Report City: | Bonn, Germany |
| Report Institution: | Meteorological Institute, University Bonn |
| Number of Pages: | 10 (1 - 10) |
| Further Information: | TR32 Student Report Phase II |
Metadata Details
| Metadata Creator: | Tanja Zerenner |
| Metadata Created: | 04.12.2013 |
| Metadata Last Updated: | 04.12.2013 |
| Subproject: | C4 |
| Funding Phase: | 2 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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| Page Visits: | 702 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 1 |
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