Yann Blanchard

and 5 more

This paper focuses on the accuracy of longwave radiation flux retrievals at the top and bottom of the atmosphere at Eureka station, Canada, in the high Arctic. We report comparisons between seven products derived from (1) calculations based on a combination of ground-based and space-based lidar and radar observations, (2) standard radiometric observations from the CERES satellite, (3) direct observations at the surface from a broadband radiation station and (4) the ERA-Interim and ERA5 reanalyses. Statistical, independent analyses are first performed to look at recurring bias and trends in fluxes at Top and Bottom of the Atmosphere. The analysis is further refined comparing fluxes derived from coincident observations decomposed by scene types. Results show that radiative transfer calculations using ground-based lidar-radar profiles derived at Eureka agree well with TOA LW fluxes observed by CERES and with BOA LW fluxes reference. CloudSat-CALIPSO also show good agreement with calculations from ground-based sensor observations, with a relatively small bias. This bias is shown to be largely due to low and thick cloud occurrences that the satellites are insensitive to owing to attenuation from clouds above and surface clutter. These conditions of opaque low clouds, cause an even more pronounced bias for CERES BOA flux calculation in winter, due to the deficit of low clouds identified by MODIS. ERA-I and ERA5 fluxes behave differently, the large positive bias observed with ERA-I is much reduced in ERA5. ERA5 is closer to reference observations due to a better behaviour of low and mid-level clouds.

Stefanie Arndt

and 4 more

An improved understanding of the seasonality of the Arctic snowpack properties related to the timing and intensity of snowmelt processes is the key driver to better quantify atmosphere-ice-ocean interactions, and in particular the seasonal energy and mass budgets of the ice-covered polar oceans. Various satellite data products over the last decades have shown a trend towards an earlier snowmelt onset in the Arctic, thus contributing to Arctic amplification and sea-ice decline, underlining the need to better understand these processes. We present here the physical snow properties from spring 2020 examined during the “Multidisciplinary drifting Observatory for the Study of Arctic Climate” (MOSAiC). We focus on southerly air mass advection events in mid-April that were associated with near-surface air temperatures near freezing at the MOSAiC floe. In doing so, we emphasize a single sampling site that was revisited daily-to-weekly throughout the spring. At the sampling site, snow depth ranged from 10 to 14 cm with the bulk density varying between 200 to 350 kg m-3, mainly driven by freshly fallen snow. The vertical snow structure prior to the warm event was characterized by large pores with distinct snow crystal structures and widespread depth hoar crystals, both related to the strong temperature gradient in the snowpack. During the warm air intrusion, increasing temperatures temporarily reversed the thermal gradient in the snow. The warm snow surface, now above a relatively cold snow/ice interface, resulted temporary negative vertical heat flux values observed to be up to -12 Wm-2. Because the snow/ice interface is close to freezing, the negative flux is an indicator that melt may have occurred. Once temperatures dropped again, the vertical temperature and heat flux gradients returned back to the previous patterns. However, the decreased snow grain sizes throughout the snowpack due to the warming and the associated compacted lower layers now dominated the snowpack. Such a temporary warm spell event has decisive impacts on the sea-ice energy and mass budget of the MOSAiC floe. Understanding this effect on a local scale will help to transfer that knowledge to larger spatial scales, and thus to quantify the influence of warm air intrusions during winter and/or spring in the ice-covered Arctic basin.