Bo Qu

The simulated response of dimethylsulfide production in the Arctic Ocean to global warming

Sulfate aerosols (of both biogenic and anthropogenic origin) play a key role in the Earth’s radiation balance both directly through scattering and absorption of solar and terrestrial radiation, and indirectly by modifying cloud microphysical properties. However, the uncertainties associated with radiative forcing of climate due to aerosols substantially exceed those associated with the greenhouse gases. The major source of sulfate aerosols in the remote marine atmosphere is the biogenic compound dimethylsulfide (DMS), which is ubiquitous in the world’s oceans and is synthesized by plankton. Climate models point to significant future changes in sea-ice cover in the Arctic Ocean due to warming. This will have consequences for primary production and the sea-to-air flux of a number of biogenic compounds, including DMS. In this paper we discuss the impact of warming on the future production of DMS in the Arctic Ocean. A DMS production model has been calibrated to current climate conditions with satellite ocean colour data (SeaWiFS) using a genetic algorithm, an efficient non-derivative based optimization technique. We use the CSIRO Mk 2 climate model to force the DMS model under enhanced greenhouse climate conditions. We discuss the simulated change in DMS flux and its consequences for future aerosol production and the radiative budget of the Arctic. Significant decreases in sea-ice cover (by 18.5% annually and 61% in summer–autumn), increases in mean annual sea surface temperature of 1◦C, and a decrease of mixed layer depth by 13% annually are predicted to result in annual DMS flux increases of over 80% by the time of equivalent CO2 tripling (2080). Estimates of the impact of this increase in DMS emissions suggest significant changes to summer aerosol concentrations and the radiative balance in the Arctic region.

Global simulations of the impact on contemporary climate of a perturbation to the sea-to-air flux of dimethylsulfide

The sea-to-air flux of the biogenic sulfur (S) compound dimethylsulfide (DMS) is thought to constitute an important radiative impact on climate, especially in remote marine areas. Previous biogeochemical modelling analyses simulate medium to large changes in the sea-to-air flux of DMS in polar regions under warming scenarios. Here we assess the global radiative impact of such a prescribed change in DMS flux on contemporary climate using a low-resolution atmospheric gen eral circulation model. This impact operates through the atmospheric oxidation of DMS to radiatively-active sulfate aerosols, which are known to both reflect incom ing short-wave radiation and to affect the microphysical properties of clouds, for example, through an increase in cloud albedo. We use an atmospheric GCM with incorporated sulfur cycle, coupled to a mixed-layer (‘q-flux’) ocean, to estimate the climatic response to a prescribed meridionally-variable change in zonal DMS flux, as simulated in a previous modelling analysis. We compare baseline sulfur emissions (contemporary anthropogenic S and contemporary DMS sea-to-air flux), with contemporary anthropogenic S and a perturbed DMS flux. Our results indicate that the global mean DMS vertically integrated concentration increases by about 41 per cent. The relative increase in DMS annual emission is around 17 per cent in 70–80°N, although the most significant increase is in 50–70°S, up to 70 per cent. However, concentrations of atmospheric SO 2 and SO 4 2– increase by only about eight per cent. The oxidation of DMS by OH increases by about 20 per cent.

Spike in phytoplankton biomass in Greenland Sea during 2009 and the correlations among chlorophyll-a, aerosol optical depth and ice cover

The distributions and correlations of chlorophyll-a (Chl-a), aerosol optical depth (AOD) and ice cover in the southeast Arctic Ocean-Greenland Sea (10°W–10°E, 70°–80°N) between 2003 and 2009 were studied using satellite data and statistical analyses. Regression analysis showed correlations between Chl-a and AOD, Chl-a and ice cover, and AOD and ice cover with different time lags. The time lag of Chl-a and AOD indicated their long-term equilibrium relationship. Peaks in AOD and Chl-a and generally occurred in May and July, respectively. Despite the time lag, the correlation between Chl-a and AOD in the study region was as high as 0.7. The peak gap between Chl-a and AOD shifted for about 6 weeks during 2003–2009. In the summer and autumn of 2009, Chl-a and AOD levels were much higher than during the other years, especially in the northern band of the study region (75°–80°N). The driving forces for this localized increase in phytoplankton biomass could be mainly attributed to the very high rate of ice melting in spring and early summer and the high wind speed in autumn, together with the increased deposition of aerosol throughout the year. The unusually high AOD in the spring of 2003 was mainly due to a massive fire in Russia, which occurred in the first half of the year. Over the 7 years of the study, the sea surface temperature generally decreased. This may have been due to the release of dimethylsulfide into the air, excreted in large amounts from abundant phytoplankton biomass, and its subsequent reaction, form large amounts of aerosol, and resulting in regional cooling.

Dimethylsulfide model calibration in the Barents Sea using a genetic algorithm and neural network

Environmental context Future changes in marine biogenic aerosol emissions in Arctic seas are likely to affect the radiative budget of the region. Here we employ a calibrated biogeochemical model to simulate change in sulfate aerosol emissions in the Barents Sea, and find strong increases occur by the late 21st century. If replicated across the Arctic Ocean, such increases in sulfate aerosol loading to the Arctic atmosphere may decrease the rate of warming at polar latitudes. Abstract Global warming of climate is connected to ecosystem change, especially in the polar oceans. Biogenic emissions of dimethylsulfide (DMS) are the main biogenic source of sulfate aerosols to the marine atmosphere and may change in the Arctic, where warming is currently very rapid. Here, we simulate DMS distribution and sea-to-air flux in the Barents Sea (30–40°E and 70–80°N) for the period 2003–05. A genetic algorithm is used to calibrate the key parameters in the DMS model. We use MODIS satellite chlorophyll-a data and regional DMS field data to calibrate the model. Owing to limited DMS observations in the Arctic Ocean, multiple data sources were used and compared. A back-propagation neural network is used for predicting regional DMS based on previous history time series. Parameter sensitivity analysis is done based on DMS flux output. Global climate model forcings for 1×CO2 to 3×CO2 conditions are used to force the biogeochemical model under future climate warming (c. 2080). The simulation results show that under tripled CO2, DMS flux would increase 168 to 279% from autumn through winter and would increase 112% during ice melting season. DMS flux would increase much more in ice-melt-affected water. The increased DMS flux under 3×CO2 indicates that regional warming could slow owing to the emission of DMS in the Arctic, if the increase in emissions of anthropogenic greenhouse gases is controlled.

The relationships among aerosol optical depth, ice, phytoplankton and dimethylsulfide and the implication for future climate in the Greenland Sea

The sea-to-air flux of dimethylsulphide (DMS) is one of the major sources of marine biogenic aerosol, and can have an important radiative impact on climate, especially in the Arctic Ocean. Satellite-derived aerosol optical depth (AOD) is used as a proxy for aerosol burden which is dominated by biogenic aerosol during summer and autumn. The spring sea ice melt period is a strong source of aerosol precursors in the Arctic. However, high aerosol levels in early spring are likely related to advection of continental pollution from the south (Arctic haze). Higher AOD was generally registered in the southern part of the study region. Sea ice concentration (SIC) and AOD were positively correlated, while cloud cover (CLD) and AOD were negative correlation. The seasonal peaks of SIC and CLD were both one month ahead of the peak in AOD. There is a strong positive correlation between AOD and SIC. Melting ice is positively correlated with chlorophyll a (CHL) almost through March to September, but negatively correlated with AOD in spring and early summer. Elevated spring and early summer AOD most likely were influenced by combination of melting ice and higher spring wind in the region. The peak of DMS flux occurred in spring due to the elevated spring wind and more melting ice. DMS concentration and AOD were positively correlated with melting ice from March to May. Elevated AOD in early autumn was likely related to the emission of biogenic aerosols associated with phytoplankton synthesis of DMS. The DMS flux would increase more than triple by 2100 in the Greenland Sea. The significant increase of biogenic aerosols could offset the warming in the Greenland Sea.

The correlation and regression analysis on aerosol optical depth, ice cover and cloud cover in Greenland Sea

Researches on Arctic aerosol, ice cover and cloud cover have received great attention and it related to the regional even global climate changing. We here study the distributions and the coupling relationships of AOD, cloud cover (CLD) and ice cover (ICE) in the Greenland Sea (20°W-10°E, 70°N-80°N) during 2003-2012. Enhanced statistics methods, such as lag regression method and co-integration analysis method are used for correlation and regression analysis. According to the 10 years satellite data, AOD was high in spring, and low in summer. Generally, AOD was higher down south and lower up north. CLD and AOD mainly had negative correlations and ICE and AOD had positive correlations. According to the lag regression analysis by statistical software EViews, both the peaks of CLD and peaks of ICE were all 1 month earlier than the peak of AOD. The co-integration test suggested that both ICE(-1) and CLD(-1) and AOD were all zero-order integration, and there was no unit root in the residual, so there all had long-run equilibrium relationships. ICE and AOD were stationary series, and the residual had no unit root, they were good coupling. The melting of sea ice and decreasing of cloud cover would all result in the increasing of the AOD content. However, the relationship between AOD and CLD was weaker than the relationship between AOD and ICE, indicating that the aerosol in Arctic mostly came from the sea rather than from the air.

DMS model calibration using Genetic Algorithm

Recent researchers suggested Dimethyl sulphide (DMS) flux emission in Arctic Ocean plays an important role for the global warming. A Genetic Algorithm (GA) method was developed and used in calibrating the DMS model parameters in Barents Sea in Arctic Ocean (70-80N, 30-35E). Two-step GA calibrations were performed. First step was to calibrate the most sensitive parameters based on Chlorophyll_a (CHL) satellite SeaWIFS 8-day data. DMS model was then calibrated for another 5 most sensitive parameters. The best fitness was as good as -0.76 for CHL calibration in 1998-2002. The GA proved an efficient tool in the multiple-parameter calibration task. Model simulations indicate significant inter-annual variation in the CHL amount leading to significant inter-annual variability in the observed and modeled production of DMS and DMS flux in the study region in Arctic Ocean.