Description: We investigate factors influencing European winter (DJFM) air temperatures for the period 1979?2015 with the focus on changes during the recent period of rapid Arctic warming (1998?2015). We employ meteorological reanalyses analysed with a combination of correlation analysis, two pattern clustering techniques, and back-trajectory airmass identification. In all five selected European regions, severe cold winter events lasting at least 4 days are significantly correlated with warm Arctic episodes. Relationships during opposite conditions of warm Europe/cold Arctic are also significant. Correlations have become consistently stronger since 1998. Large-scale pattern analysis reveals that cold spells are associated with the negative phase of the North Atlantic Oscillation (NAO?) and the positive phase of the Scandinavian (SCA+) pattern, which in turn are correlated with the divergence of dry-static energy transport. Warm European extremes are associated with opposite phases of these patterns and the convergence of latent heat transport. Airmass trajectory analysis is consistent with these findings, as airmasses associated with extreme cold events typically originate over continents, while warm events tend to occur with prevailing maritime airmasses. Despite Arctic?wide warming, significant cooling has occurred in northeastern Europe owing to a decrease in adiabatic subsidence heating in airmasses arriving from the southeast, along with increased occurrence of circulation patterns favouring low temperature advection. These dynamic effects dominated over the increased mean temperature of most circulation patterns. Lagged correlation analysis reveals that SCA? and NAO+ are typically preceded by cold Arctic anomalies during the previous 2-3 months, which may aid seasonal forecasting.

Description: There is as yet no standard methodology for measuring wind gusts from a moving platform. To address this, we have developed a method to derive gusts from research aircraft data. First we evaluated four different approaches, including Taylor’s hypothesis of frozen turbulence, to derive the gust length scales that correspond to the gust time scales, namely, the gust duration (seconds) and the sample period (typically 10 min). The novelty of our method is in using peak factors (deviation of the gust from the mean wind speed normalized by the local turbulence) to convert between the scales. After devising a way to derive the gust length scales, we calculated the gust factors from aircraft observations and tested them against those from four parameterizations originally developed for weather stations. Three of them performed well (R2=0.66 or higher), while the fourth overestimated the gust factors in unstable conditions(R2=0.52). The mean errors for all methods were low, from -0.02 to 0.05, indicating that wind gust factors can indeed be measured from research aircraft. Moreover, we showed that aircraft can provide gust measurements within the whole boundary layer, if horizontal legs are flown at multiple levels over the same track. This is a significant advance, as gust measurements are usually limited to heights reached by weather masts. In unstable conditions over the open ocean the gust factor was nearly constant with height throughout the boundary layer, the near-surface values only slightly exceeding those at upper levels. Furthermore, we found gust factors to be strongly dependent on surface roughness conditions, which differed between the open ocean and sea ice in the Arctic marine environment. The roughness effect on the gust factor was stronger than the effect of boundary-layer stability.

Description: The vertical structure of the atmospheric boundary layer (ABL), simulated with the mesoscale modelWeather Research and Forecasting (WRF) as well as with its polar optimized version Polar WRF, was compared to tethered balloon soundings and mast observations taken in March and April 2009 from two Arctic fjords in Svalbard. From twelve short (48 h) simulations, the Quasi-Normal Scale Elimination scheme for the ABL and the NOAH land surface scheme for the surface were found to perform best and were selected for one long (16 day) simulation. The differences in performance of the standard WRF and Polar WRF were marginal. A warm bias, especially near the surface, was found in the modelled temperature profiles related to underestimated temperature inversion strength and depth. The modelled humidity inversions were generally deeper but weaker than the observed, and often occurred independently of temperature inversions. The largest errors in temperature and humidity occurred under high pressure conditions. Multiple temperature and humidity inversions were usually not captured byWRF. Compared to the compact sea ice east of Svalbard, the modelled temperature and humidity inversions were weaker and less frequent over the fjords. The biases in modelled wind speed profiles were closely related to low-level jets (LLJs); the modelled LLJs were stronger and deeper, and typically located at higher altitudes than the observed LLJs. Errors in the near-surface variables were notably reduced by applying post-processing equations based on othermodelled variables.