Description: This observational study compares seasonal variations of surface fluxes (turbulent, radiative, and soil heat) and other ancillary atmospheric/surface/permafrost data based on in-situ measurements made at terrestrial research observatories located near the coast of the Arctic Ocean. Hourly-averaged multiyear data sets collected at Eureka (Nunavut, Canada) and Tiksi (East Siberia, Russia) are analyzed in more detail to elucidate similarities and differences in the seasonal cycles at these two Arctic stations, which are situated at significantly different latitudes (80.0°N and 71.6°N, respectively). While significant gross similarities exist in the annual cycles of various meteorological parameters and fluxes, the differences in latitude, local topography, cloud cover, snowfall, and soil characteristics produce noticeable differences in fluxes and in the structures of the atmospheric boundary layer and upper soil temperature profiles. An important factor is that even though higher latitude sites (in this case Eureka) generally receive less annual incoming solar radiation but more total daily incoming solar radiation throughout the summer months than lower latitude sites (in this case Tiksi). This leads to a counter-intuitive state where the average active layer (or thaw line) is deeper and the topsoil temperature in midsummer are higher in Eureka which is located almost 10° north of Tiksi. The study further highlights the differences in the seasonal and latitudinal variations of the incoming shortwave and net radiation as well as the moderating cloudiness effects that lead to temporal and spatial differences in the structure of the atmospheric boundary layer and the uppermost ground layer. Specifically the warm season (Arctic summer) is shorter and mid-summer amplitude of the surface fluxes near solar noon is generally less in Eureka than in Tiksi. During the dark Polar night and cold seasons (Arctic winter) when the ground is covered with snow and air temperatures are sufficiently below freezing, the near-surface environment is generally stably stratified and the hourly averaged turbulent fluxes are quite small and irregular with on average small downward sensible heat fluxes and upward latent heat and carbon dioxide fluxes. The magnitude of the turbulent fluxes increases rapidly when surface snow disappears and the air temperatures rise above freezing during spring melt and eventually reaches a summer maximum. Throughout the summer months strong upward sensible and latent heat fluxes and downward carbon dioxide (uptake by the surface) are typically observed indicating persistent unstable (convective) stratification. Due to the combined effects of day length and solar zenith angle, the convective boundary layer forms in the High Arctic (e.g., in Eureka) and can reach long-lived quasi-stationary states in summer. During late summer and early autumn all turbulent fluxes rapidly decrease in magnitude when the air temperature decreases and falls below freezing. Unlike Eureka, a pronounced zero-curtain effect consisting of a sustained surface temperature hiatus at the freezing point is observed in Tiksi during fall due to wetter and/or water saturated soils.

Description: he Year of Polar Prediction (YOPP) is focused on a number of Special Observing Periods (SOPs) of two to three months’ duration in both the Northern and Southern Hemispheres. One feature of the SOPs is a program of enhanced radiosonde and buoy measurements contributing to assessments of how the extra observations support improved forecast skills. Another activity resulting from the SOPs is the YOPP Supersite Model Intercomparison Project (YOPPsiteMIP). The YOPPsiteMIP concept is unique compared to Climate Model Intercomparison Projects (CMIPs) because of (1) a focus on Numerical Weather Prediction (NWP) scales, processes and improvements, (2) the selection of polar, intensive, surface observing locations (YOPP Supersites) for which the NWP centers will create high-resolution model outputs and (3) special merged, observation outputs for the YOPP Supersites matched to the model outputs. These unique datasets of matched model time-step output and multi-variate high-frequency observations will enable detailed analysis of fast, small-scale processes. Example processes of interest are coupling mechanisms between the atmosphere, ocean, land and ice; cloud/precipitation micro- and macro-physics; the energy budgets over land, ocean and ice; and structure of the planetary boundary layer and the ocean mixed layer. The YOPPsiteMIP planning has focused so far on Arctic terrestrial YOPP Supersites, however, discussions are initiated on expanding the concept to selected Antarctic sites, as well as to ships and ice-stations in the Arctic Ocean. Preliminary results of the observation-model process-based evaluations at the YOPP Supersites relevant to environmental predictions ranging from weather to S2S scales will be presented.

Description: 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 2 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 or rBC and sulfate concentrations quite well, compared to previous 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 overestimates 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 3 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 modeling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anticorrelation 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.

Description: IASOA activities and partnerships were initiated as a part of the 2007-2009 International Polar Year (IPY) and are expected to continue for many decades as a legacy program. The IASOA focus is on coordinating intensive measurements of the Arctic atmosphere collected in the U.S., Canada, Russia, Norway, Finland, and Greenland, to create synthesis science that leads to an understanding of why, and not just how the Arctic atmosphere is evolving. The IASOA premise is that there are limitations with Arctic modeling and satellite observations that can only be addressed with boots-on-the-ground, in-situ observations and that the potential of combining individual station and network measurements into an integrated observing system is tremendous. The IASOA vision is that by further integrating with other network observing programs focusing on hydrology, glaciology, oceanography, terrestrial, and biological systems it will be possible to understand the mechanisms of the entire Arctic system, perhaps well enough for humans to mitigate undesirable change, and adapt to inevitable change.

Description: With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.