PanXML - a tool to create XML files for DOI registration of publications in the catalog DataCite of the German National Library of Science and Technology

The software PanXML is a tool to create XML files needed for DOI registration at the German National Library of Science and Technology (TIB). PanXML is distributed as freeware for the operating systems Microsoft Windows, Apple OS X and Linux. An XML file created by PanXML is based on the XSD file article-doi_v3.2.xsd. Further schemas may be added on request.

(Table 1) Stable oxygen isotopic ratios and yearly snow accumulation of firn and ice cores from Svalbard

We analyse ice cores from Vestfonna ice cap (Nordaustlandet, Svalbard). Oxygen isotopic measurements were made on three firn cores (6.0, 11.0 and 15.5 m deep) from the two highest summits of the glacier located on the SW-NE and NW-SE central ridges. Sub-annual d18O cycles were preserved and could be counted visually in the uppermost parts of the cores, but deeper layers were affected by post-depositional smoothing. A pronounced d18O minimum was found near the bottom of the three cores. We consider candidates for this d18O signal to be a valuable reference horizon since it is also seen elsewhere in Nordaustlandet. We attribute it to isotopically depleted snow precipitation, which NCEP/NCAR reanalysis shows was unusual for Vestfonna, and came from northerly air during the cold winter of 1994/95. Finding the 1994/95 time marker allows establishment of a precise depth/age scale for the three cores. The derived annual accumulation rates indirectly fill a geographical gap in mass balance measurements and thus provide information on spatial and temporal variability of precipitation over the glacier for the period spanned by the cores (1992-2009). Comparing records at the two locations also reveals that the snow net accumulation at the easternmost part of Vestfonna was only half of that in the western part over the last 17 years.

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.