Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set

Abstract

Abstract. The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of two years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry-transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry-climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC/rBC and sulfate concentrations quite well, compared to past comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January-March underestimated by 59 and 37% for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44% for July–September), but with over- as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is three times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modelling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anti-correlation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution.

Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models

“…Simulated BC concentrations from AMAP and other models were recently compared to observations by Eckhardt et al . [] and AMAP [] based on comprehensive data sets from surface sites and aircraft campaigns. Identical AMAP model configurations and emission data sets were used by Eckhardt et al and for the current study so that findings by Eckhardt et al .…”

“…Furthermore, Eckhardt et al . [] concluded that substantial variability in aircraft measurements and model results arises from the fact that some campaigns targeted biomass burning plumes while others avoided such plumes, which affects the robustness of climatologically meaningful comparisons with models. Generally, comparisons of vertical profiles are currently limited by a lack of horizontal, vertical, and long‐term coverage of aircraft campaigns, which is problematic given the substantial variability in Arctic BC concentrations.…”

Changing black carbon transport to the Arctic from present day to the end of 21st century

“…Yet elemental carbon and organic carbon aerosol fields simulated by CAM4 show relatively large biases compared to near‐surface measurements at the IMPROVE (United States Interagency Monitoring of Protected Visual Environments) sites [ Lamarque et al , ]. Some of the biases in CAM4, such as the underestimation of BC both near surface and in middle‐high troposphere in Arctic, are also consistent with other models [e.g., Koch et al , ; Lee et al , ; Eckhardt et al , ].…”

International Arctic Systems for Observing the Atmosphere: An International Polar Year Legacy Consortium

“…The IASOA consortium has mobilized in response to the lesson learned from this history. Although recent data availability is beginning to result in multiobservatory analyses (e.g., Eckhardt et al 2015;Berchet et al 2015;Stone et al 2014) that were not coordinated by IASOA, it cannot be assumed that full utilization of the networked observatory data will happen spontaneously. It is for this reason that one decade after its inception, IASOA is supporting a pan-Arctic, international collaboration that is furthering a network-based science approach to understanding the Arctic atmosphere system.…”

“…Black carbon affects Arctic climate through the direct absorption of incoming solar radiation, aerosol indirect effects on cloud radiative forcing, and modification of surface albedo when deposited on snow (Quinn et al 2008). Work is being done on many fronts related to the Arctic black carbon topic, including the development of emissions inventories, analyses of transport trajectories and sources, modeling of black carbon in the atmosphere (Eckhardt et al 2015), and measurements in the snow ), in order to better understand the black carbon climatology and resulting climatic implications (Sharma et al 2006;Hegg et al 2009;Doherty et al 2010).…”