Spatial interpolation of two‐metre temperature over Norway based on the combination of numerical weather prediction ensembles and in situ observations

Accurate hourly two‐metre temperature gridded fields available in near real‐time are valuable products for numerous applications, such as civil protection and energy production planning. An analysis ensemble of temperature is obtained from the combination of a numerical weather prediction ensemble (background) and in situ observations. At the core of the flow‐dependent spatial interpolation method lies the analysis step of the local ensemble transform Kalman filter (LETKF). A scaling factor and a localization procedure have been added to correct for deficiencies of the background. Each observation is characterized by its own representativeness, which is allowed to vary in time. We call the method described here an Ensemble‐based Statistical Interpolation (EnSI) scheme for spatial analysis and it has been integrated into the operational post‐processing systems in use at the Norwegian Meteorological Institute (MET Norway). The benefits of the analysis are assessed over a 1‐year time period (July 2017–July 2018) and a case‐study is presented for a challenging situation over complex terrain. EnSI gives more accurate results than an interpolation method based exclusively on observations. The analysis ensemble provides a more informative representation of the uncertainty than a spatial analysis based on a single‐field background. EnSI reduces the number of large prediction errors in the analysis compared to the background by almost 50%, reduces the ensemble spread and increases its accuracy

A Simplified Method to Distinguish Farmed (Salmo salar) from Wild Salmon: Fatty Acid Ratios Versus Astaxanthin Chiral Isomers

Mislabeling of farmed and wild salmon sold in markets has been reported. Since the fatty acid content of fish may influence human health and thus consumer behavior, a simplified method to identify wild and farmed salmon is necessary. Several studies have demonstrated differences in lipid profiles between farmed and wild salmon but no data exists validating these differences with government-approved methods to accurately identify the origin of these fish. Current methods are both expensive and complicated, using highly specialized equipment not commonly available. Therefore, we developed a testing protocol using gas chromatography (GC), to determine the origin of salmon using fatty acid profiles. We also compared the GC method with the currently approved FDA (United States Food and Drug Administration) technique that uses analysis of carotenoid optical isomers and found 100% agreement. Statistical validation (n = 30) was obtained showing elevated 18:2n-6 (z = 4.56; P = 0.0001) and decreased 20:1n-9 (z = 1.79; P = 0.07) in farmed samples. The method is suitable for wide adaptation because fatty acid methyl ester analysis is a well-established procedure in labs that conduct analysis of lipid composition and food constituents. GC analysis for determining the origin of North American salmon compared favorably with the astaxanthin isomer technique used by the FDA and showed that the fatty acid 18:2n-6 was the key indicator associated with the origin of these salmon