Abstract Over the past decade, the Arctic has seen unprecedented declines in the summer sea ice area, leading to larger and longer exposed open water areas. The Atmospheric Infrared Sounder is a useful yet underutilized tool to study corresponding atmospheric changes and their feedbacks between 2003 and 2013. Most pronounced warming occurs between November and April, with skin and air temperatures increasing on average 2.5 K and 1.5 K over the Arctic Ocean. In response to sea ice loss, evaporation rates (i.e., moisture flux) increased between August and October by 1.5 × 10 −3 g m −2 s −1 (3.8 W m −2 latent heat flux energy), increasing the water vapor feedback and cloud cover. Although most trends are positive over the Arctic Ocean, there is considerable interannual variability. Increasing specific humidity in May and corresponding downward moisture fluxes cause earlier melt onset; warming skin temperatures and radiative responses to increased water vapor and cloud cover in autumn delay freeze‐up.
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 Numerous studies have addressed links between summer atmospheric circulation patterns and interannual variability and the downward trend in total September Arctic sea ice extent. In general, low extent is favored when the preceding summer is characterized by positive sea level pressure (SLP) anomalies over the central Arctic Ocean north of Alaska. High extent is favored when low pressure dominates. If such atmospheric patterns could be predicted several months out, these links provide an avenue for improved seasonal predictability of total September extent. We analyze detrended September extent time series (1979–2015), atmospheric reanalysis fields, ice age and motion, and Atmospheric Infrared Sounder data, to show that while there is merit to this summer circulation framework, it has limitations. Large departures in total September extent relative to the trend line are preceded by a wide range of summer circulation patterns. While patterns for the four years with the largest positive departures in September extent have below average SLP over the central Arctic Ocean, they differ markedly in the magnitude and location of pressure and air temperature anomalies. Differences in circulation for the four years with the largest negative departures are equally prominent. Circulation anomalies preceding Septembers with ice extent close to the trend also have a wide range of patterns. In turn, years (such as 2013 and 2014) with almost identical total September extent were preceded by very different summer circulation patterns. September ice conditions can also be strongly shaped by events as far back as the previous winter or spring.
Moisture flux from the southern ocean using AIRS data, daily for 2003-2016. this is using AIRS version 6 data (AIRS/AMSU combination). Boisvert, L., Vihma, T., & Shie, C. L. (2020). Evaporation from the Southern Ocean estimated on the basis of AIRS satellite data. Journal of Geophysical Research: Atmospheres, 125(1), e2019JD030845. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019JD030845
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.
In recent decades, the Arctic has experienced rapid atmospheric warming and sea ice loss, with an ice-free Arctic projected by the end of this century. Cyclones are synoptic weather events that transport heat and moisture into the Arctic, and have complex impacts on sea ice, and the local and global climate. However, the effect of a changing climate on Arctic cyclone behavior remains poorly understood. This study uses high resolution (4 km), regional modeling techniques and downscaled global climate reconstructions and projections to examine how recent and future climatic changes alter cyclone behavior. Results suggest that recent climate change has not yet had an appreciable effect on Arctic cyclone characteristics. However, future sea ice loss and increasing surface temperatures drive large increases in the near-surface temperature gradient, sensible and latent heat fluxes, and convection during cyclones. The future climate can alter cyclone trajectories and increase and prolong intensity with greatly augmented wind speeds, temperatures, and precipitation. Such changes in cyclone characteristics could exacerbate sea ice loss and Arctic warming through positive feedbacks. The increasing extreme nature of these weather events has implications for local ecosystems, communities, and socio-economic activities.
Abstract Arctic sea ice has undergone significant change in areal coverage, thickness, ice type since the 1980s and more recently since the early 2000s, where a “New Arctic” regime now exists. Since the sea ice modulates exchanges of energy from the ocean to the atmosphere, this changing sea ice environment has profound effects on the local climate. However, due to the Arctic's remote location, wide‐spread and long‐term data records of the atmosphere are few and far between. The Atmospheric Infrared Sounder (AIRS) onboard NASA's Aqua satellite was launched in May 2002 has been collecting twice daily, global data of the Earth's temperature and humidity for over 20 years. We use AIRS temperature and humidity data to investigate relationships between the sea ice, and surface and atmospheric conditions between 2003 and 2022. The Arctic atmosphere is becoming warmer and wetter with sea ice loss and the change is most pronounced near the surface. Strongest correlations occur in the fall when the surface and lower atmosphere are tightly coupled. When comparing the first (2003–2012) and last (2013–2022) decade of the New Arctic, results show that the warming and moistening is slowing down as the sea ice regime and sea ice loss has stabilized in 2013–2022. Cooling and drying is occurring in winter in the Barents and other peripheral seas in the last decade possibly due to a negative feedback loop, where winter sea ice regrowth is occurring at a faster pace. This work highlights the importance of sea ice atmosphere interactions and long‐term climate data records, specifically in remote and drastically changing places like the Arctic.
Abstract The timing of melt onset affects the surface energy uptake throughout the melt season. Yet the processes triggering melt and causing its large interannual variability are not well understood. Here we show that melt onset over Arctic sea ice is initiated by positive anomalies of water vapor, clouds, and air temperatures that increase the downwelling longwave radiation (LWD) to the surface. The earlier melt onset occurs; the stronger are these anomalies. Downwelling shortwave radiation (SWD) is smaller than usual at melt onset, indicating that melt is not triggered by SWD. When melt occurs early, an anomalously opaque atmosphere with positive LWD anomalies preconditions the surface for weeks preceding melt. In contrast, when melt begins late, clearer than usual conditions are evident prior to melt. Hence, atmospheric processes are imperative for melt onset. It is also found that spring LWD increased during recent decades, consistent with trends toward an earlier melt onset.
Abstract Precipitation is a major component of the hydrologic cycle and plays a significant role in the sea ice mass balance in the polar regions. Over the Southern Ocean, precipitation is particularly uncertain due to the lack of direct observations in this remote and harsh environment. Here we demonstrate that precipitation estimates from eight global reanalyses produce similar spatial patterns between 2000 and 2010, although their annual means vary by about 250 mm yr −1 (or 26% of the median values) and there is little similarity in their representation of interannual variability. ERA-Interim produces the smallest and CFSR produces the largest amount of precipitation overall. Rainfall and snowfall are partitioned in five reanalyses; snowfall suffers from the same issues as the total precipitation comparison, with ERA-Interim producing about 128 mm less snowfall and JRA-55 about 103 mm more rainfall compared to the other reanalyses. When compared to CloudSat -derived snowfall, these five reanalyses indicate similar spatial patterns, but differ in their magnitude. All reanalyses indicate precipitation on nearly every day of the year, with spurious values occurring on an average of about 60 days yr −1 , resulting in an accumulation of about 4.5 mm yr −1 . While similarities in spatial patterns among the reanalyses suggest a convergence, the large spread in magnitudes points to issues with the background models in adequately reproducing precipitation rates, and the differences in the model physics employed. Further improvements to model physics are required to achieve confidence in precipitation rate, as well as the phase and frequency of precipitation in these products.
