No abstract

A compilation of aircraft observations of the atmospheric surface layer is compared with several meteorological analyses and QuikSCAT wind products. The observations are taken during the Greenland Flow Distortion Experiment, in February and March 2007, during cold-air outbreak conditions and moderate to high wind speeds. About 150 data points spread over six days are used, with each data point derived from a 2-min run (equivalent to a 12 km spatial average). The observations were taken 30-50 m above the sea surface and are adjusted to standard heights. Surface-layer temperature, humidity and wind, as well as sea-surface temperature (SST) and surface turbulent fluxes are compared against co-located data from the ECMWF operational analyses, NCEP Global Reanalyses, NCEP North American Regional Reanalyses (NARR), Met Office North Atlantic European (NAE) operational analyses, two MM5 hindcasts, and two QuikSCAT products.In general, the limited-area models are better at capturing the mesoscale high wind speed features and their associated structure; often the models underestimate the highest wind speeds and gradients. The most significant discrepancies are: a poor simulation of relative humidity by the NCEP global and MM5 models, a cold bias in 2 m air temperature near the sea-ice edge in the NAE model, and an overestimation of wind speed above 20 m s −1 in the QuikSCAT wind products. In addition, the NCEP global, NARR and MM5 models all have significant discrepancies associated with the parametrisation of surface turbulent heat fluxes. A high-resolution prescription of the SST field is crucial in this region, although these were not generally used at this time.

Salt stress is an important constraint to lucerne (Medicago sativa L.) production in many parts of the world. Seeds of 3 lucerne varieties, cvv. Victoria, Golden Empress, and Victor, were used to investigate the effects of seed priming with 5 µm/L brassinolide on germination and seedling growth under a high level of salt stress (13.6 dS/m NaCl solution). The results showed that germination percentage, germination index, and vigour index of lucerne seeds primed with brassinolide were significantly higher than those of the non-primed seeds under salinity stress in each variety. Seed priming with brassinolide significantly increased the shoot fresh weight, shoot dry weight, and root dry weight in 2 varieties, and significantly increased the root length and root vigour in each variety. It also significantly increased the activities of antioxidant enzymes, peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT), in Victoria and Victor seedlings. During seedling growth, the primed seeds significantly reduced the malondialdehyde (MDA) accumulation. This suggests that priming lucerne seed with brassinolide at a suitable concentration can improve germination and seedling growth under high-saline soils.

A strategy was proposed for constructing core collections by least distance stepwise sampling (LDSS) based on genotypic values. In each procedure of cluster, the sampling is performed in the subgroup with the least distance in the dendrogram during constructing a core collection. Mean difference percentage (MD), variance difference percentage (VD), coincidence rate of range (CR) and variable rate of coefficient of variation (VR) were used to evaluate the representativeness of core collections constructed by this strategy. A cotton germplasm collection of 1,547 accessions with 18 quantitative traits was used to construct core collections. Genotypic values of all quantitative traits of the cotton collection were unbiasedly predicted based on mixed linear model approach. By three sampling percentages (10, 20 and 30%), four genetic distances (city block distance, Euclidean distance, standardized Euclidean distance and Mahalanobis distance) combining four hierarchical cluster methods (nearest distance method, furthest distance method, unweighted pair-group average method and Ward's method) were adopted to evaluate the property of this strategy. Simulations were conducted in order to draw consistent, stable and reproducible results. The principal components analysis was performed to validate this strategy. The results showed that core collections constructed by LDSS strategy had a good representativeness of the initial collection. As compared to the control strategy (stepwise clusters with random sampling strategy), LDSS strategy could construct more representative core collections. For LDSS strategy, cluster methods did not need to be considered because all hierarchical cluster methods could give same results completely. The results also suggested that standardized Euclidean distance was an appropriate genetic distance for constructing core collections in this strategy.

This paper quantifies and discusses the impact of high-resolution, high-frequency atmospheric forcing on the ocean circulation in the vicinity of the Denmark Strait. The approach is to force a 2 km resolution regional ocean circulation model with atmospheric states from reanalysis products that have different spatial and temporal resolutions. We use the National Center for Environmental Prediction global reanalysis data (2.5 • resolution, 6-hourly output) and a specially configured regional atmospheric model (12 km resolution, hourly output). The focus is on the month-long period in winter 2007 during the Greenland Flow Distortion Experiment. Diagnostics of upper-ocean currents and mixing are sensitive to the small-scale variability in the high-resolution regional atmospheric model. The hydrographic state of the ocean model is insensitive over the month-long experiments, however. Both sea ice and the fluxes of volume, heat, and freshwater across the east Greenland shelf break and through the Denmark Strait show a moderate response to the high-resolution atmospheric forcing. The synoptic-scale atmospheric state has a large role in controlling sea ice too, while internal ocean dynamics is the dominant factor controlling the flux diagnostics. It is the high spatial resolution, not the temporal resolution, that causes these effects, with O(10 km)-scale features being most important. The sea-level wind field is responsible, with the other atmospheric fields playing relatively minor roles.