Imperial College London
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ProfessorDavidHam

Faculty of Natural Sciences, Department of Mathematics

Professor of Computational Mathematics
 
 
 
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Contact

 

+44 (0)20 7594 5003david.ham Website CV

 
 
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Location

 

753Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Hill:2014:10.5194/os-10-323-2014,
author = {Hill, J and Popova, EE and Ham, DA and Piggott, MD and Srokosz, M},
doi = {10.5194/os-10-323-2014},
journal = {Ocean Science},
pages = {323--343},
title = {Adapting to life: ocean biogeochemical modelling and adaptive remeshing},
url = {http://dx.doi.org/10.5194/os-10-323-2014},
volume = {10},
year = {2014}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - An outstanding problem in biogeochemical modelling of the ocean is that many of the key processes occur intermittently at small scales, such as the sub-mesoscale, that are not well represented in global ocean models. This is partly due to their failure to resolve sub-mesoscale phenomena, which play a significant role in vertical nutrient supply. Simply increasing the resolution of the models may be an inefficient computational solution to this problem. An approach based on recent advances in adaptive mesh computational techniques may offer an alternative. Here the first steps in such an approach are described, using the example of a simple vertical column (quasi-1-D) ocean biogeochemical model. We present a novel method of simulating ocean biogeochemical behaviour on a vertically adaptive computational mesh, where the mesh changes in response to the biogeochemical and physical state of the system throughout the simulation. We show that the model reproduces the general physical and biological behaviour at three ocean stations (India, Papa and Bermuda) as compared to a high-resolution fixed mesh simulation and to observations. The use of an adaptive mesh does not increase the computational error, but reduces the number of mesh elements by a factor of 2–3. Unlike previous work the adaptivity metric used is flexible and we show that capturing the physical behaviour of the model is paramount to achieving a reasonable solution. Adding biological quantities to the adaptivity metric further refines the solution. We then show the potential of this method in two case studies where we change the adaptivity metric used to determine the varying mesh sizes in order to capture the dynamics of chlorophyll at Bermuda and sinking detritus at Papa. We therefore demonstrate that adaptive meshes may provide a suitable numerical technique for simulating seasonal or transient biogeochemical behaviour at high vertical resolution whilst minimising the number of elements in the mesh. M
AU  - Hill,J
AU  - Popova,EE
AU  - Ham,DA
AU  - Piggott,MD
AU  - Srokosz,M
DO  - 10.5194/os-10-323-2014
EP  - 343
PY  - 2014///
SP  - 323
TI  - Adapting to life: ocean biogeochemical modelling and adaptive remeshing
T2  - Ocean Science
UR  - http://dx.doi.org/10.5194/os-10-323-2014
UR  - http://www.ocean-sci.net/10/323/2014/os-10-323-2014.html
VL  - 10
ER  -
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