The impact of Arctic conventional and satellite observations on regional short-range weather forecasts is assessed using observing-system experiments, in which observations are removed (denied) when creating the initial conditions of the forecasts. The experiments are conducted with the AROME-Arctic regional mesoscale numerical weather prediction system, using as lateral boundary conditions (LBCs) observing-system experiments performed at the European Centre for Medium-Range Forecasts (ECMWF) with the global forecasting system. This allows the assessment of the relative impacts of observations on forecast skill through regional data assimilation (DA), through LBCs, and the total impact due to the denial of observations in both the regional and global forecasting systems. The study is conducted during the first and second Special Observing Periods of the Year Of Polar Prediction. The total impact on the upper-air forecasts is dominated by the impact of observations through their assimilation in the LBCs, while for the winter period the impact on surface fields is dominated by the regional DA. The latter is significant up to 36 hr, while the former impact can last throughout the verified forecast range (48 hr). The use of observations in the LBCs has both significantly positive and significantly negative impacts. In terms of total impact on forecast skill, conventional observations, followed by infrared radiances, have the largest impact on all upper-air parameters, except for humidity. For upper-air humidity forecasts, the microwave radiances have the largest impact. In terms of observation impact through regional DA, conventional observations play the largest role for upper-air temperature and geopotential, microwave for upper-air humidity, and atmospheric motion vectors and Infrared Atmospheric Sounding Interferometer (IASI) for wind forecast. Regional DA of conventional observations also contributes the most to improvements of surface fields, except for 10-m winds, for which the microwave temperature-sensitive radiances are the most important.

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The assimilation of microwave and infrared (IR) radiance satellite observations within numerical weather prediction (NWP) models have been an important component in the effort of improving the accuracy of analysis and forecast. Such capabilities were implemented during the development of the high-resolution Copernicus European Regional Reanalysis (CERRA), funded by the Copernicus Climate Change Services (C3S). The CERRA system couples the deterministic system with the ensemble data assimilation to provide periodic updates of the background error covariance matrix. Several key factors for the assimilation of radiances were investigated, including appropriate use of variational bias correction (VARBC), surface-sensitive AMSU-A observations and observation error correlation. Twenty-one-day impact studies during the summer and winter seasons were conducted. Generally, the assimilation of radiances has a small impact on the analysis, while greater impacts are observed on short-range (12 and 24-h) forecasts with an error reduction of 1–2% for the mid and high troposphere. Although, the current configuration provided less accurate forecasts from 09 and 18 UTC analysis times. With the increased thinning distances and the rejection of IASI observation over land, the errors in the analyses and 3 h forecasts on geopotential height were reduced up to 2%.

The bearingless induction motor is a nonlinear, multi-variable and strongly coupling system. In this paper, a new nonlinear internal model control (IMC) strategy based on inverse system theory is proposed to realize the decoupling control for the bearingless induction motor. The mathematical model of the motor is built and then the inverse system method is applied to decouple the original nonlinear system. Finally the internal model control method is introduced to ensure the robustness of the closed-loop system. The effectiveness of the proposed strategy are demonstrated by simulation.

A large area of Pacific Coast forests is characterized by shallow soil, with negligible rainfall in the growing season. This study explores water-seeking strategy on such a site. We studied availability of bedrock water and its effects on growth and ecophysiology of 11-yr-old planted Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) and sprouting Pacific madrone (Arbutus menziesii Pursh). The study was carried out at three regulated densities of madrone sprouts on shallow (<50 cm) residual soils in southwest Oregon. Total bedrock water depleted from March to September, as observed in drill holes by neutron probe, did not differ significantly (P > 0.05) among three densities of madrone. However, cover in plots with the highest density of madrone (1322 sprout clumps/ha) depleted 50 mm of water from the 1.5 m layer by June, whereas vegetation on lower density treatments withdrew 15-28 mm by June, with later withdrawal distributed more uniformly through the growing season. Madrone density significantly affected basal diameter (P ≤ 0.0001) and height growth (P ≤ 0.002) of Douglas-fir. Madrone was consistently taller than Douglas-fir in all plots. The height of 11-yr-old madrone sprout clumps (424-465 cm) did not differ significantly among densities. Madrone leaf area index and biomass were higher at the high density of madrone than at medium density (P ≤ 0.045, LAI; P ≤ 0.001, biomass). Physiological advantages and rooting habits of madrone give it a competitive advantage over Douglas-fir in this area that it might not have if bedrock did not provide the principal water reservoir for summer growth. For. Sci. 41(4):744-757.