Comparing high resolution WRF-VPRM simulations and two global CO<sub>2</sub> transport models with coastal tower measurements of CO<sub>2</sub>
In order to better understand the effects that mesoscale transport has on atmospheric CO<sub>2</sub> distributions, we have used the atmospheric WRF model coupled to the diagnostic biospheric model VPRM, which provides high resolution biospheric CO<sub>2</sub> fluxes based on...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2009-05-01
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| Series: | Biogeosciences |
| Online Access: | http://www.biogeosciences.net/6/807/2009/bg-6-807-2009.pdf |
| Summary: | In order to better understand the effects that mesoscale transport has on atmospheric CO<sub>2</sub> distributions, we have used the atmospheric WRF model coupled to the diagnostic biospheric model VPRM, which provides high resolution biospheric CO<sub>2</sub> fluxes based on MODIS satellite indices. We have run WRF-VPRM for the period from 16 May to 15 June in 2005 covering the intensive period of the CERES experiment, using the CO<sub>2</sub> fields from the global model LMDZ for initialization and lateral boundary conditions. The comparison of modeled CO<sub>2</sub> concentration time series against observations at the Biscarosse tower and against output from two global models – LMDZ and TM3 – clearly reveals that WRF-VPRM can capture the measured CO<sub>2</sub> signal much better than the global models with lower resolution. Also the diurnal variability of the atmospheric CO<sub>2</sub> field caused by recirculation of nighttime respired CO<sub>2</sub> is simulated by WRF-VRPM reasonably well. Analysis of the nighttime data indicates that with high resolution modeling tools such as WRF-VPRM a large fraction of the time periods that are impossible to utilize in global models, can be used quantitatively and may help to constrain respiratory fluxes. The paper concludes that we need to utilize a high-resolution model such as WRF-VPRM to use continental observations of CO<sub>2</sub> concentration data with more spatial and temporal coverage and to link them to the global inversion models. |
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| ISSN: | 1726-4170 1726-4189 |