4.7 Article

Sensitivity of Modeled CO2Air-Sea Flux in a Coastal Environment to Surface Temperature Gradients, Surfactants, and Satellite Data Assimilation

期刊

REMOTE SENSING
卷 12, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/rs12122038

关键词

data assimilation; 1D ecosystem model; CO2; air-sea gas exchange

资金

  1. European Space Agency (ESA) through the OceanFlux Greenhouse Gases project [4000104762/11/I-AM]
  2. NERC National Capability Modeling
  3. UK National Centre for Earth Observation
  4. European Union - INTERREG IVA 2 Mers Seas Zeeen Cross-border Cooperation Programme 2007-2013 [07-027-FR-ISECA]
  5. NERC [NE/R006849/1, nceo020005, nceo020007, NE/M005038/1, pml010006, NE/K002058/1, pml010010, nceo020004] Funding Source: UKRI
  6. Natural Environment Research Council [NE/R015953/1, NE/K002058/1] Funding Source: researchfish

向作者/读者索取更多资源

This work evaluates the sensitivity of CO(2)air-sea gas exchange in a coastal site to four different model system configurations of the 1D coupled hydrodynamic-ecosystem model GOTM-ERSEM, towards identifying critical dynamics of relevance when specifically addressing quantification of air-sea CO(2)exchange. The European Sea Regional Ecosystem Model (ERSEM) is a biomass and functional group-based biogeochemical model that includes a comprehensive carbonate system and explicitly simulates the production of dissolved organic carbon, dissolved inorganic carbon and organic matter. The model was implemented at the coastal station L4 (4 nm south of Plymouth, 50 degrees 15.00'N, 4 degrees 13.02'W, depth of 51 m). The model performance was evaluated using more than 1500 hydrological and biochemical observations routinely collected at L4 through the Western Coastal Observatory activities of 2008-2009. In addition to a reference simulation (A), we ran three distinct experiments to investigate the sensitivity of the carbonate system and modeled air-sea fluxes to (B) the sea-surface temperature (SST) diurnal cycle and thus also the near-surface vertical gradients, (C) biological suppression of gas exchange and (D) data assimilation using satellite Earth observation data. The reference simulation captures well the physical environment (simulated SST has a correlation with observations equal to 0.94 with ap> 0.95). Overall, the model captures the seasonal signal in most biogeochemical variables including the air-sea flux of CO(2)and primary production and can capture some of the intra-seasonal variability and short-lived blooms. The model correctly reproduces the seasonality of nutrients (correlation > 0.80 for silicate, nitrate and phosphate), surface chlorophyll-a (correlation > 0.43) and total biomass (correlation > 0.7) in a two year run for 2008-2009. The model simulates well the concentration of DIC, pH and in-water partial pressure of CO2(pCO(2)) with correlations between 0.4-0.5. The model result suggest that L4 is a weak net source of CO2(0.3-1.8 molCm(-2)year(-1)). The results of the three sensitivity experiments indicate that both resolving the temperature profile near the surface and assimilation of surface chlorophyll-a significantly impact the skill of simulating the biogeochemistry at L4 and all of the carbonate chemistry related variables. These results indicate that our forecasting ability of CO(2)air-sea flux in shelf seas environments and their impact in climate modeling should consider both model refinements as means of reducing uncertainties and errors in any future climate projections.

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