Mapping the Antarctic Polar Front: Weekly realizations from 2002 to 2014, links to NetCDF file and MPEG4 movie

We map the weekly position of the Antarctic Polar Front (PF) in the Southern Ocean over a 12-year period (2002-2014) using satellite sea surface temperature (SST) estimated from cloud-penetrating microwave radiometers. Our study advances previous efforts to map the PF using hydrographic and satellite data and provides a unique realization of the PF at weekly resolution across all longitudes. The mean path of the PF is asymmetric; its latitudinal position spans from 44 to 64° S along its circumpolar path. SST at the PF ranges from 0.6 to 6.9 °C, reflecting the large spread in latitudinal position. The average intensity of the front is 1.7 °C per 100 km, with intensity ranging from 1.4 to 2.3 °C per 100 km. Front intensity is significantly correlated with the depth of bottom topography, suggesting that the front intensifies over shallow bathymetry. Realizations of the PF are consistent with the corresponding surface expressions of the PF estimated using expendable bathythermograph data in the Drake Passage and Australian and African sectors. The climatological mean position of the PF is similar, though not identical, to previously published estimates. As the PF is a key indicator of physical circulation, surface nutrient concentration, and biogeography in the Southern Ocean, future studies of physical and biogeochemical oceanography in this region will benefit from the provided data set.

High-resolution dynamical downscaling products for the North Slope of Alaska and surrounding areas, links to model result files

Climatic changes are most pronounced in northern high latitude regions. Yet, there is a paucity of observational data, both spatially and temporally, such that regional-scale dynamics are not fully captured, limiting our ability to make reliable projections. In this study, a group of dynamical downscaling products were created for the period 1950 to 2100 to better understand climate change and its impacts on hydrology, permafrost, and ecosystems at a resolution suitable for northern Alaska. An ERA-interim reanalysis dataset and the Community Earth System Model (CESM) served as the forcing mechanisms in this dynamical downscaling framework, and the Weather Research & Forecast (WRF) model, embedded with an optimization for the Arctic (Polar WRF), served as the Regional Climate Model (RCM). This downscaled output consists of multiple climatic variables (precipitation, temperature, wind speed, dew point temperature, and surface air pressure) for a 10 km grid spacing at three-hour intervals. The modeling products were evaluated and calibrated using a bias-correction approach. The ERA-interim forced WRF (ERA-WRF) produced reasonable climatic variables as a result, yielding a more closely correlated temperature field than precipitation field when long-term monthly climatology was compared with its forcing and observational data. A linear scaling method then further corrected the bias, based on ERA-interim monthly climatology, and bias-corrected ERA-WRF fields were applied as a reference for calibration of both the historical and the projected CESM forced WRF (CESM-WRF) products. Biases, such as, a cold temperature bias during summer and a warm temperature bias during winter as well as a wet bias for annual precipitation that CESM holds over northern Alaska persisted in CESM-WRF runs. The linear scaling of CESM-WRF eventually produced high-resolution downscaling products for the Alaskan North Slope for hydrological and ecological research, together with the calibrated ERA-WRF run, and its capability extends far beyond that. Other climatic research has been proposed, including exploration of historical and projected climatic extreme events and their possible connections to low-frequency sea-atmospheric oscillations, as well as near-surface permafrost degradation and ice regime shifts of lakes. These dynamically downscaled, bias corrected climatic datasets provide improved spatial and temporal resolution data necessary for ongoing modeling efforts in northern Alaska focused on reconstructing and projecting hydrologic changes, ecosystem processes and responses, and permafrost thermal regimes. The dynamical downscaling methods presented in this study can also be used to create more suitable model input datasets for other sub-regions of the Arctic.