The European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) has been downscaled using a regional model covering Alaska at 20-km spatial and hourly temporal resolution for 1979–2013. Stakeholders can utilize these enhanced-resolution data to investigate climate- and weather-related phenomena in Alaska. Temperature and precipitation are analyzed and compared among ERA-Interim, WRF Model downscaling, and in situ observations. Relative to ERA-Interim, the downscaling is shown to improve the spatial representation of temperature and precipitation around Alaska’s complex terrain. Improvements include increased winter and decreased summer higher-elevation downscaled seasonal average temperatures. Precipitation is also enhanced over higher elevations in all seasons relative to the reanalysis. These spatial distributions of temperature and precipitation are consistent with the few available gridded observational datasets that account for topography. The downscaled precipitation generally exceeds observationally derived estimates in all seasons over mainland Alaska, and it is less than observations in the southeast. Temperature biases tended to be more mixed, and the downscaling reduces absolute bias at higher elevations, especially in winter. Careful selection of data for local site analysis from the downscaling can help to reduce these biases, especially those due to inconsistencies in elevation. Improved meteorological station coverage at higher elevations will be necessary to better evaluate gridded downscaled products in Alaska because biases vary and may even change sign with elevation.

[1] Seasonal breakup of landfast sea ice consists of movement and irreversible ice detachment in response to winds or oceanic forces in the late stages of ice decay. The breakup process of landfast sea ice in the Chukchi Sea at Barrow, Alaska, was analyzed for the years 2000 through 2010 on the basis of local observations of snow and ice conditions, weather records, image sequences obtained from cameras, coastal X band marine radar, and satellite imagery. We investigated the relation of breakup to winds, tides, and nearshore current measurements from a moored acoustic Doppler current profiler. Two breakup modes are distinguished at Barrow on the basis of the degree of ice decay. Mechanical breakup due to wind and oceanic forces follows ablation and weakening of the ice. Thermal breakup is the result of ice disintegration under melt ponds, requiring little force to induce dispersion. Grounded pressure ridges are pivotal in determining the breakup mode. The timing of thermal breakup of the nearshore ice cover was found to correlate with the measured downwelling solar radiation in June and July. This linkage allows for the development of an operational forecast of landfast ice breakup. Results from forecasts during 2 years demonstrate that thermal breakup can be predicted to within a couple of days 2 weeks in advance. The cumulative shortwave energy absorbed by the ice cover provides for a measure of the state of ice decay and potential for disintegration. Discriminating between the two modes of breakup bears the potential to greatly increase forecasting skill.Citation: Petrich, C., H. Eicken, J. Zhang, J. Krieger, Y. Fukamachi, and K. I. Ohshima (2012), Coastal landfast sea ice decay and breakup in northern Alaska: Key processes and seasonal prediction,

The Weather Research and Forecasting Model (WRF) and its variational data assimilation system (WRFDA) are applied to the Chukchi-Beaufort Seas and adjacent Arctic Slope region for high-resolution regional atmospheric reanalysis study. To optimize WRFDA performance over the study area, a set of sensitivity experiments are carried out to analyze the model sensitivity to model background errors (BEs) and the assimilation of various observational datasets. Observational data are assimilated every 6 h and the results are verified against unassimilated observations. In the BE sensitivity analyses, the results of assimilating in situ surface observations with a customized, domain-dependent BE are compared to those using the WRFprovided global BE. It is found that the customized BE is necessary in order to achieve positive impacts from WRFDA assimilation for the study area. When seasonal variability is incorporated into the customized BE, the impacts are minor. Sensitivity analyses examining the assimilation of different datasets via WRFDA demonstrate that 1) positive impacts are always seen through the assimilation of in situ surface and radiosonde measurements, 2) assimilating Quick Scatterometer (QuikSCAT) winds improves the simulation of the 10-m wind field over ocean and coastal areas, and 3) selectively assimilating Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved profiles under clear-sky and snow-free conditions is essential to avoid degradation of assimilation performance, while assimilation of Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) retrievals has little impact, most likely due to limited data availability. Based on the sensitivity results, a 1-yr (2009) experimental reanalysis is conducted and consistent improvements are achieved, particularly in capturing mesoscale processes such as mountain barrier and seabreeze effects.

The detailed mesoscale climatology of surface winds in the Chukchi-Beaufort Seas and adjacent Arctic Slope region is analyzed using the recently developed Chukchi-Beaufort High-Resolution Atmospheric Reanalysis (CBHAR). Within the study area, surface winds are mainly driven by the prevailing synoptic weather patterns of the Beaufort high and Aleutian low and are further modulated by local geographic features through thermodynamic and dynamic processes. Sea breezes, up-or downslope winds, and the mountain barrier jets are all clearly captured by CBHAR. Sea breezes emerge in June-September and last most of the day, with a maximum spatial extent 100 km inland and 50 km offshore and maximum speed around 1-3 m s 21 in the late afternoon [;1500 Alaska standard time (AKST)]. Thermodynamic impacts of mountains on the surface winds vary from time to time. Drainage flows begin to build at the mountaintop in September and reach the strongest during November-February, occupying the entire slope. Upslope winds demonstrate a clear diurnal cycle during summer, starting to build around 0900 local time, reaching the maximum strength around 1500 local time and continuing until 2100 local time. The mountain barrier jets (MBJs) are found to be most active around the Chukotka Mountains during cold seasons. Both sea breezes and MBJs are also subject to variations and changes in response to adjusted large-scale atmosphere circulation. Storm activities can inhibit the development of sea breezes. Different responses from the Beaufort high and Aleutian low to anomalies in large-scale circulations play a vital role in the variations of MBJ activities over the Chukotka Mountains.

ABSTRACT. Meteorological observations from more than 250 stations in the Beaufort and Chukchi Sea coastal, interior, and offshore regions were gathered and quality-controlled for the period 1979 through 2009. These stations represent many different observing networks that operate in the region for the purposes of aviation, fire weather, coastal weather, climate, surface radiation, and hydrology and report data hourly or sub-hourly. A unified data quality control (QC) has been applied to these multi-resource data, incorporating three main QC procedures: the threshold test (identifying instances of an observation falling outside of a normal range); the step change test (identifying consecutive values that are excessively different); and the persistence test (flagging instances of excessively high or low variability in the observations). Methods previously developed for daily data QC do not work well for hourly data because they flag too many data entries. Improvements were developed to obtain the proper limits for hourly data QC. These QC procedures are able to identify the suspect data while producing far fewer Type I errors (the erroneous flagging of valid data). The fraction of flagged data for the entire database illustrates that the persistence test was failed the most often (1.34%), followed by the threshold (0.99%) and step change tests (0.02%).Comparisons based on neighboring stations were not performed for the database; however, correlations between nearby stations show promise, indicating that this type of check may be a viable option in such cases. This integrated high temporal resolution dataset will be invaluable for weather and climate analysis, as well as regional modeling applications, in an area that is undergoing significant climatic change.Key words: western Arctic, meteorological observations, data quality, automated quality control, Beaufort Sea, Chukchi Sea, Alaska RÉSUMÉ. Des observations météorologiques provenant de plus de 250 stations des régions côtières, intérieures et extracôtières de la mer de Beaufort et de la mer des Tchouktches ont été recueillies pendant la période allant de 1979 à 2009, puis elles ont fait l'objet d'un contrôle de la qualité. Ces stations relèvent de plusieurs réseaux d'observation différents qui existent dans la région à des fins d'aviation, de météorologie forestière, de météorologie côtière, de climat, de rayonnement de surface et d'hydrologie, et elles fournissent des données horaires ou subhoraires. Un contrôle de la qualité (CQ) unifié des données a été appliqué à ces données provenant de sources multiples en faisant appel à trois méthodes principales de CQ, soit le test d'acceptabilité (qui a permis de déterminer dans quels cas une observation ne faisait pas partie de la gamme normale); le test de la variation discrète (qui a permis de détecter les valeurs consécutives qui sont excessivement différentes); et le test de la persistance (qui a permis de repérer les cas de variabilité excessivement élevée ou basse). Les anciennes méthodes de CQ des données quo...