Near-surface meteorology during the Arctic Summer Cloud Ocean Study (ASCOS): evaluation of reanalyses and global climate models

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)-Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget

Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System

By synthesising remote-sensing measurements made in the central Arctic into a model-gridded Cloudnet cloud product, we evaluate how well the Met Office Unified Model (UM) and the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS) capture Arctic clouds and their associated interactions with the surface energy balance and the thermodynamic structure of the lower troposphere. This evaluation was conducted using a 4-week observation period from the Arctic Ocean 2018 expedition, where the transition from sea ice melting to freezing conditions was measured. Three different cloud schemes were tested within a nested limited-area model (LAM) configuration of the UM – two regionally operational single-moment schemes (UM_RA2M and UM_RA2T) and one novel double-moment scheme (UM_CASIM-100) – while one global simulation was conducted with the IFS, utilising its default cloud scheme (ECMWF_IFS). Consistent weaknesses were identified across both models, with both the UM and IFS overestimating cloud occurrence below 3 km. This overestimation was also consistent across the three cloud configurations used within the UM framework, with >90 % mean cloud occurrence simulated between 0.15 and 1 km in all the model simulations. However, the cloud microphysical structure, on average, was modelled reasonably well in each simulation, with the cloud liquid water content (LWC) and ice water content (IWC) comparing well with observations over much of the vertical profile. The key microphysical discrepancy between the models and observations was in the LWC between 1 and 3 km, where most simulations (all except UM_RA2T) overestimated the observed LWC. Despite this reasonable performance in cloud physical structure, both models failed to adequately capture cloud-free episodes: this consistency in cloud cover likely contributes to the ever-present near-surface temperature bias in every simulation. Both models also consistently exhibited temperature and moisture biases below 3 km, with particularly strong cold biases coinciding with the overabundant modelled cloud layers. These biases are likely due to too much cloud-top radiative cooling from these persistent modelled cloud layers and were consistent across the three UM configurations tested, despite differences in their parameterisations of cloud on a sub-grid scale. Alarmingly, our findings suggest that these biases in the regional model were inherited from the global model, driving a cause–effect relationship between the excessive low-altitude cloudiness and the coincident cold bias. Using representative cloud condensation nuclei concentrations in our double-moment UM configuration while improving cloud microphysical structure does little to alleviate these biases; therefore, no matter how comprehensive we make the cloud physics in the nested LAM configuration used here, its cloud and thermodynamic structure will continue to be overwhelmingly biased by the meteorological conditions of its driving model

The Arctic Summer Cloud Ocean Study (ASCOS): overview and experimental design

The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol-cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007-2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21′ N, 01°29′ W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets

Impact of summertime anthropogenic emissions on atmospheric black carbon at Ny-Ålesund in the Arctic

Measurements of equivalent black carbon (EBC), calculated from aethalometer measurements of light attenuation, were carried out in July 2011 at Ny-Ålesund in the Arctic. Highly elevated EBC concentrations were observed within the settlement of Ny-Ålesund, with a median value of 17 ng m−3, which was about two times the background level. Results from the ensemble empirical mode decomposition method suggested that about 60–80% of atmospheric EBC concentrations at Ny-Ålesund were from local emissions, while only 20–40% arrived via atmospheric transport. The estimated average local emission rate was 8.1 g h−1, with an uncertainty of approximately a factor of two. The pollution plume was confined to 10 km downwind of the settlement, with the total EBC deposition estimated to be 6.4–44 ng m−2 h−1. This may affect snow black carbon (BC) concentrations in nearby glaciated areas. The efficiencies of the long-range transport were estimated based on cluster analysis and potential precipitation contribution function, and the results implied that transport from western Europe is more efficient than from central Russia, on account of relatively rapid transport from western Europe and infrequent precipitation along this route. However, there was no correlation between air mass back-trajectories and EBC concentrations, suggesting that the contribution of long-range transport to EBC measured in Ny-Ålesund might be not significant in this season