A database of daily Lagrangian Arctic sea ice parcel drift tracks with coincident ice and atmospheric conditions to study the fate of sea ice in the ‘New Arctic’. Files are multi-part zip files containing trajectory and ancillary data on an annual basis over a sea ice year.
Abstract Atmospheric data from the Atmospheric Infrared Sounder (AIRS) were used to study an extreme warm and humid air mass transported over the Barents–Kara Seas region by an Arctic cyclone at the end of December 2015. Temperature and humidity in the region was ~10°C (>3 σ above the 2003–14 mean) warmer and ~1.4 g kg −1 (>4 σ above the 2003–14 mean) wetter than normal during the peak of this event. This anomalous air mass resulted in a large and positive flux of energy into the surface via the residual of the surface energy balance (SEB), compared to the weakly negative SEB from the surface to the atmosphere expected for that time of year. The magnitude of the downwelling longwave radiation during the event was unprecedented compared to all other events detected by AIRS in December/January since 2003. An approximate budget scaling suggests that this anomalous SEB could have resulted in up to 10 cm of ice melt. Thinning of the ice pack in the region was supported by remotely sensed and modeled estimates of ice thickness change. Understanding the impact of this anomalous air mass on a thinner, weakened sea ice state is imperative for understanding future sea ice–atmosphere interactions in a warming Arctic.
Abstract. Since the early 2000s, sea ice has experienced an increased rate of decline in thickness and extent and transitioned to a seasonal ice cover. This shift to thinner, seasonal ice in the 'New Arctic' is accompanied by a reshuffling of energy flows at the surface. Understanding the magnitude and nature of this reshuffling and the feedbacks therein remains limited. A novel database is presented that combines satellite observations, model output, and reanalysis data with daily sea ice parcel drift tracks produced in a Lagrangian framework. This dataset consists of daily time series of sea ice parcel locations, sea ice and snow conditions, and atmospheric states. Building on previous work, this dataset includes remotely sensed radiative and turbulent fluxes from which the surface energy budget can be calculated. Additionally, flags indicate when sea ice parcels travel within cyclones, recording distance and direction from the cyclone center. The database drift track was evaluated by comparison with sea ice mass balance buoys. Results show ice parcels generally remain within 100km of the corresponding buoy, with a mean distance of 82.6 km and median distance of 54 km. The sea ice mass balance buoys also provide recordings of sea ice thickness, snow depth, and air temperature and pressure which were compared to this database. Ice thickness and snow depth typically are less accurate than air temperature and pressure due to the high spatial variability of the former two quantities when compared to a point measurement. The correlations between the ice parcel and buoy data are high, which highlights the accuracy of this Lagrangian database in capturing the seasonal changes and evolution of sea ice. This database has multiple applications for the scientific community; it can be used to study the processes that influence individual sea ice parcel time series, or to explore generalized summary statistics and trends across the Arctic. Applications such as these may shed light on the atmosphere-snow-sea ice interactions in the changing Arctic environment.
Abstract Precipitation is expected to increase in a warming climate, which can have profound impacts on local and global hydrologic budgets. However, the precipitation in high latitudes remains highly uncertain. We compare wintertime precipitation in the North Atlantic using GPM‐IMERG, GPCP, MERRA‐2 and ERA5 between 2000–2019 and show that while interannual variations between products are similar, large differences in magnitudes exist, specifically in areas of higher precipitation where Integrated Multi‐satellitE Retrievals for GPM (IMERG) produces an excess of 2 mm day −1 . EOF analysis demonstrates observations and reanalyses show similar spatial variability in the most dominant precipitation patterns and are highly correlated ( r = −0.6) with the North Atlantic Oscillation. Analysis of IMERG extreme precipitation further shows that it is most densely populated in this same area where large discrepancies in magnitudes between products exist. IMERG extreme precipitation was found to drive the monthly anomalies. Future work needs to be focused on extreme precipitation characteristics, patterns and the driving atmospheric factors.
