ALBERT

Description: The Surface Ocean CO2 Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO2 (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO2 values) and extended data coverage (from 1968–2007 to 1968–2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longerterm variation, as well as initialisation or validation of ocean carbon models and coupled climate-carbon models.

Description: The factors controlling estuarine phytoplankton diversity and production are relatively well known in temperate systems. Less however is known about the factors affecting phytoplankton community distribution in tropical estuaries. This is surprising given the economic and ecological importance of these large, deltaic ecosystems, such as are found in South East Asia. Here we present the results from an investigation into the factors controlling phytoplankton distribution and phytoplankton-bacterial coupling in the Bach Dang Estuary, a sub-estuary of the Red River system, in Northern Vietnam. Phytoplankton diversity and primary and bacterial production, nutrients and metallic contaminants (mercury and organotin) were measured during two seasons: wet (July 2008) and dry (March 2009). Phytoplankton community composition differed between the two seasons with only a 2% similarity between July and March. The large spatial extent and complexity of defining the freshwater sources meant that simple mixing diagrams could not be used in this system. We therefore employed multivariate analyses to determine the factors influencing phytoplankton community structure. Salinity and suspended particulate matter were important factors in determining phytoplankton distribution, particularly during the wet season. We also show that phytoplankton community structure is probably influenced by the concentrations of mercury species (inorganic mercury and methyl mercury in both the particulate and dissolved phases) and of tri-, di, and mono-butyl tin species found in this system. Freshwater phytoplankton community composition was associated with dissolved methyl mercury and particulate inorganic mercury concentrations during the wet season, whereas, during the dry season, dissolved methyl mercury and particulate butyl tin species were important factors for the discrimination of the phytoplankton community structure. Phytoplankton-bacterioplankton coupling was also investigated during both seasons. In the inshore, riverine stations the ratio between bacterial production and dissolved primary production was high supporting the hypothesis that bacterial carbon demand is supported by allochthonous riverine carbon sources. The inverse was true in the offshore stations, where BP:DPP values were less than 1, potentially reflecting differences in primary production due to shifting phytoplankton community diversity.

Description: This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

Description: Winter CO2 fluxes represent an important component of the annual carbon budget in northern ecosystems. Understanding winter respiration processes and their responses to climate change is also central to our ability to assess terrestrial carbon cycle and climate feedbacks in the future. The factors influencing the spatial and temporal pattern of winter respiration (RECO) of northern ecosystems are poorly understood. For this reason, we analyzed eddy covariance flux data sets from 57 ecosystem sites ranging from ~35° N to ~70° N. Deciduous forests carry the highest winter RECO ratios (9.7–10.5 g C m−2 d−1), when winter is defined as the period during which air temperature remained below 0 °C. By contrast, wetland ecosystems had the lowest winter RECO (2.1–2.3 g C m−2 d−1). Evergreen needle-leaved forests, grasslands and croplands were characterized by intermediate winter RECO values of 7.4–7.9 g C m−2 d−1, 5.8–6.0 g C m−2 d−1, and 5.2–5.3 g C m−2 d−1, respectively. Cross site analysis showed that winter air or soil temperature, and the seasonal amplitude of the leaf area index inferred from satellite observation, which is a proxy for the amount of litter available for RECO in the subsequent winter, are the two main factors determining spatial pattern of daily mean winter RECO. Together, these two factors can explain 71% (Tair, ΔLAI) or 69% (Tsoil, ΔLAI) of the spatial variance of winter RECO across the 57 sites. The spatial temperature sensitivity of daily winter RECO was determined empirically by fitting an Arrhenius relationship to the data. The activation energy parameter of this relationship was found to decrease at increasing soil temperature at a rate of 83.1 KJ ° C-1 (r = −0.32, p 〈 0.05), which implies a possible dampening of the increase in winter RECO due to global warming. The interannual variability of winter RECO is better explained by soil temperature than by air temperature, likely due to the insulating effects of snow cover. The increase in winter RECO with a 1 °C warming based calculated from the spatial analysis was almost that double that calculated from the temporal analysis. Thus, models that calculate the effects of warming on RECO based only on spatial analyses could be over-estimating the impact.

Description: The Surface Ocean CO2 Atlas (SOCAT) is an effort by the international marine carbon research community. It aims to improve access to carbon dioxide measurements in the surface oceans by regular releases of quality controlled and fully documented synthesis and gridded fCO2 (fugacity of carbon dioxide) products. SOCAT version 2 presented here extends the data set for the global oceans and coastal seas by four years and has 10.1 million surface water fCO2 values from 2660 cruises between 1968 and 2011. The procedures for creating version 2 have been comparable to those for version 1. The SOCAT website (http://www.socat.info/) provides access to the individual cruise data files, as well as to the synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Scientific users can also retrieve the data as downloadable files or via Ocean Data View. Version 2 enables carbon specialists to expand their studies until 2011. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longer-term variation, as well as initialisation or validation of ocean carbon models and coupled-climate carbon models.

Description: The Surface Ocean CO2 Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO2 (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO2 values) and extended data coverage (from 1968–2007 to 1968–2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longerterm variation, as well as initialisation or validation of ocean carbon models and coupled climate-carbon models. Data coverage Repository-References: Individual data set files and synthesis product: doi:10.1594/PANGAEA.811776 Gridded products: doi:10.3334/CDIAC/OTG.SOCAT_V2_GRID Available at: http://www.socat.info/ Coverage: 79° S to 90° N; 180° W to 180° E Location Name: Global Oceans and Coastal Seas Date/Time Start: 16 November 1968 Date/Time End: 26 December 2011

Description: This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry/transport and general circulation models have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over an order of magnitude exists in the modeled vertical distribution of OA that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing and is important for model evaluation against OA and OC observations, it is resolved only by few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median secondary OA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.4–3.8 Tg) with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA / sulfate burden ratio of is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations the model-observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model/measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and of POA aging, although, the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The correlations overall are low when comparing with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that the knowledge about the processes, on top of the sources, are important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to separate between anthropogenic and natural OA and accurately calculate the impact of OA on climate.

Description: Immersion freezing is the most relevant heterogeneous ice nucleation mechanism through which ice crystals are formed in mixed-phase clouds. In recent years, an increasing number of laboratory experiments utilizing a variety of instruments have examined immersion freezing activity of atmospherically relevant ice nucleating particles (INPs). However, an inter-comparison of these laboratory results is a difficult task because investigators have used different ice nucleation (IN) measurement methods to produce these results. A remaining challenge is to explore the sensitivity and accuracy of these techniques and to understand how the IN results are potentially influenced or biased by experimental parameters associated with these techniques. Within the framework of INUIT (Ice Nucleation research UnIT), we distributed an illite rich sample (illite NX) as a representative surrogate for atmospheric mineral dust particles to investigators to perform immersion freezing experiments using different IN measurement methods and to obtain IN data as a function of particle concentration, temperature (T), cooling rate and nucleation time. Seventeen measurement methods were involved in the data inter-comparison. Experiments with seven instruments started with the test sample pre-suspended in water before cooling, while ten other instruments employed water vapor condensation onto dry-dispersed particles followed by immersion freezing. The resulting comprehensive immersion freezing dataset was evaluated using the ice nucleation active surface-site density (ns) to develop a representative ns(T) spectrum that spans a wide temperature range (−37 °C 〈 T 〈 −11 °C) and covers nine orders of magnitude in ns. Our inter-comparison results revealed a discrepancy between suspension and dry-dispersed particle measurements for this mineral dust. While the agreement was good below ~ −26 °C, the ice nucleation activity, expressed in ns, was smaller for the wet suspended samples and higher for the dry-dispersed aerosol samples between about −26 and −18 °C. Only instruments making measurement techniques with wet suspended samples were able to measure ice nucleation above −18 °C. A possible explanation for the deviation between −26 and −18 °C is discussed. In general, the seventeen immersion freezing measurement techniques deviate, within the range of about 7 °C in terms of temperature, by three orders of magnitude with respect to ns. In addition, we show evidence that the immersion freezing efficiency (i.e., ns) of illite NX particles is relatively independent on droplet size, particle mass in suspension, particle size and cooling rate during freezing. A strong temperature-dependence and weak time- and size-dependence of immersion freezing efficiency of illite-rich clay mineral particles enabled the ns parameterization solely as a function of temperature. We also characterized the ns (T) spectra, and identified a section with a steep slope between −20 and −27 °C, where a large fraction of active sites of our test dust may trigger immersion freezing. This slope was followed by a region with a gentler slope at temperatures below −27 °C. A multiple exponential distribution fit is expressed as ns(T) = exp(23.82 × exp(−exp(0.16 × (T + 17.49))) + 1.39) based on the specific surface area and ns(T) = exp(25.75 × exp(−exp(0.13 × (T + 17.17))) + 3.34) based on the geometric area (ns and T in m−2 and °C, respectively). These new fits, constrained by using an identical reference samples, will help to compare IN measurement methods that are not included in the present study and, thereby, IN data from future IN instruments.

Description: We have improved an ozone DIfferential Absorption Lidar (DIAL) system, originally developed in March 2010. The improved DIAL system consists of a Nd:YAG laser and a 2 m Raman cell filled with 8.1 × 105 Pa of CO2 gas which generate four Stokes lines (276, 287, 299, and 312 nm) of stimulated Raman scattering, and two receiving telescopes with diameters of 49 and 10 cm. Using this system, 44 ozone profiles were observed in the 1–6 km altitude range over Saga (33.24° N, 130.29° E) in 2012. High-ozone layers were observed at around 2 km altitude during April and May. Ozone column amounts within the 1–6 km altitude range were almost constant (19.1 DU on average) from January to March, and increased to 26.7 DU from late April to July. From mid-July through August, ozone column amounts decreased greatly to 14.3 DU because of exchanges of continental and maritime air masses. Then in mid-September they increased again to 22.1 DU within 1−6 km, and subsequently decreased slowly to 17.3 DU, becoming almost constant by December. The Meteorological Research Institute's chemistry–climate model version 2 (MRI-CCM2) successfully predicted most of these ozone variations with the following exceptions. MRI-CCM2 could not predict the high-ozone volume mixing ratios measured at around 2 km altitude on 5 May and 11 May, possibly in part because emissions were assumed in the model to be constant (climatological data were used). Ozone volume mixing ratios predicted by MRI-CCM2 were low in the 2–6 km range on 7 July and high in the 1–4 km range on 19 July compared with those measured by DIAL.

Description: We have improved an ozone DIfferential Absorption Lidar (DIAL) system, originally developed in March 2010. The improved DIAL system consists of a Nd:YAG laser and a 2 m Raman cell filled with 8.1 × 105 Pa of CO2 gas which generate four Stokes lines (276, 287, 299, and 312 nm) of stimulated Raman scattering, and two receiving telescopes with diameters of 49 and 10 cm. Using this system, 44 ozone profiles were observed in the 1–6 km altitude range over Saga (33.24° N, 130.29° E) in 2012. High ozone concentration layers were observed at around 2 km altitude during April and May. Ozone column amounts within the 1–6 km altitude range were almost constant from January to March, and increased from late April to July. From mid-July through August, ozone column amounts decreased greatly because of exchanges of continental and maritime air masses. Then in mid-September they increased again within 1–6 km, and subsequently decreased slowly, becoming almost constant by December. The Meteorological Research Institute's Chemistry-Climate Model version 2 (MRI-CCM2) successfully predicted most of these ozone variations with the following exceptions. MRI-CCM2 could not predict the high ozone-mixing ratios measured at around 2 km altitude on 5 May and 11 May, possibly in part because emissions were assumed in the model to be constant (climatological data were used). Ozone-mixing ratios predicted by MRI-CCM2 were low in the 2–6 km range on 7 July and high in the 1–4 km range on 19 July compared with those measured by DIAL.