Simulating heterogeneous vegetation in climate models. Identifying when secondary vegetation becomes important
Abstract To parameterize the land surface in global climate models (GCMs) data must be provided at a variety of resolutions. In GCMs, high‐resolution data must be aggregated to the coarser resolution of the GCM. The method used for parameter aggregation can lead to the simulation of very different l...
| Published in: | Hydrological Processes |
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| Main Author: | |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
1995
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| Online Access: | http://dx.doi.org/10.1002/hyp.3360090516 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fhyp.3360090516 https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.3360090516 |
| Summary: | Abstract To parameterize the land surface in global climate models (GCMs) data must be provided at a variety of resolutions. In GCMs, high‐resolution data must be aggregated to the coarser resolution of the GCM. The method used for parameter aggregation can lead to the simulation of very different land surface climatologies. It is shown that the most important transition from a simulation of homogeneous tundra to one of homogeneous coniferous forest is the initial increase in forest. The differences between the simulation of tundra and the simulation of tundra with two‐ninths coniferous forest are considerable. This suggests that the land surface is sensitive to the aggregated parameters in non‐linear ways. It suggests that more care is needed in data aggregation, and that improved algorithms for data aggregation must be developed, because these data sets represent the foundations on which advanced land surface parameterizations are built. Finally, it shows that the influence of relatively small amounts of secondary vegetation should be represented in GCMs. |
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