62 research outputs found
Verification results for the Spectral Ocean Wave Model (SOWM) by means of significant wave height measurements made by the GEOS-3 spacecraft
Significant wave heights estimated from the shape of the return pulse wave form of the altimeter on GEOS-3 for forty-four orbit segments obtained during 1975 and 1976 are compared with the significant wave heights specified by the spectral ocean wave model (SOWM), which is the presently operational numerical wave forecasting model at the Fleet Numerical Weather Central. Except for a number of orbit segments with poor agreement and larger errors, the SOWM specifications tended to be biased from 0.5 to 1.0 meters too low and to have RMS errors of 1.0 to 1.4 meters. The much fewer larger errors can be attributed to poor wind data for some parts of the Northern Hemisphere oceans. The bias can be attributed to the somewhat too light winds used to generate the waves in the model. Other sources of error are identified in the equatorial and trade wind areas
Vector wind, horizontal divergence, wind stress and wind stress curl from SEASAT-SASS at one degree resolution
Conventional data obtained in 1983 are contrasted with SEASAT-A scatterometer and scanning multichannel microwave radiometer (SMMR) data to show how observations at a single station can be extended to an area of about 150,000 square km by means of remotely sensed data obtained in nine minutes. Superobservations at a one degree resolution for the vector winds were estimated along with their standard deviations. From these superobservations, the horizontal divergence, vector wind stress, and the curl of the wind stress can be found. Weather forecasting theory is discussed and meteorological charts of the North Pacific Ocean are presented. Synoptic meteorology as a technique is examined
Synoptic scale wind field properties from the SEASAT SASS
Dealiased SEASAT SEASAT A Scatterometer System SASS vector winds obtained during the Gulf Of Alaska SEASAT Experiment GOASEX program are processed to obtain superobservations centered on a one degree by one degree grid. The grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. These superobservations winds are then processed further to obtain estimates of synoptic scale vector winds stress fields, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations of the estimates for each grid point value. They also explain the concentration of water vapor, liquid water and precipitation found by means of the SMMR Scanning Multichannel Microwave Radiometer at fronts and occlusions in terms of strong warm, moist air advection in the warm air sector accompanied by convergence in the friction layer. Their quality is far superior to that of analyses based on conventional data, which are shown to yield many inconsistencies
The measurement of the winds near the ocean surface with a radiometer-scatterometer on Skylab
The author has identified the following significant results. There were a total of twenty-six passes in the ZLV mode that yielded useful data. Six were in the in-track noncontiguous mode; all others were in the cross-track noncontiguous mode. The wind speed and direction, as effectively determined in a neutral atmosphere at 19.5 m above the sea surface, were found for each cell scanned by S193. It is shown how the passive microwave measurements were used both to compute the attenuation of the radar beam and to determine those cells where the backscatter measurement was suspect. Given the direction of the wind from some independent source, with the typical accuracy of measurement by available meteorological methods, a backscatter measurement at a nadir angle of 50, 43, or 32 deg can be used to compute the speed of the wind averaged over the illuminated area
Social cognition in people with schizophrenia: A cluster-analytic approach
Background The study aimed to subtype patients with schizophrenia on the basis of social cognition (SC), and to identify cut-offs that best discriminate among subtypes in 809 out-patients recruited in the context of the Italian Network for Research on Psychoses. Method A two-step cluster analysis of The Awareness of Social Inference Test (TASIT), the Facial Emotion Identification Test and Mayer-Salovey-Caruso Emotional Intelligence Test scores was performed. Classification and regression tree analysis was used to identify the cut-offs of variables that best discriminated among clusters. Results We identified three clusters, characterized by unimpaired (42%), impaired (50.4%) and very impaired (7.5%) SC. Three theory-of-mind domains were more important for the cluster definition as compared with emotion perception and emotional intelligence. Patients more able to understand simple sarcasm (14 for TASIT-SS) were very likely to belong to the unimpaired SC cluster. Compared with patients in the impaired SC cluster, those in the very impaired SC cluster performed significantly worse in lie scenes (TASIT-LI <10), but not in simple sarcasm. Moreover, functioning, neurocognition, disorganization and SC had a linear relationship across the three clusters, while positive symptoms were significantly lower in patients with unimpaired SC as compared with patients with impaired and very impaired SC. On the other hand, negative symptoms were highest in patients with impaired levels of SC. Conclusions If replicated, the identification of such subtypes in clinical practice may help in tailoring rehabilitation efforts to the person's strengths to gain more benefit to the person
Social cognition in people with schizophrenia: A cluster-analytic approach
Background The study aimed to subtype patients with schizophrenia on the basis of social cognition (SC), and to identify cut-offs that best discriminate among subtypes in 809 out-patients recruited in the context of the Italian Network for Research on Psychoses. Method A two-step cluster analysis of The Awareness of Social Inference Test (TASIT), the Facial Emotion Identification Test and Mayer-Salovey-Caruso Emotional Intelligence Test scores was performed. Classification and regression tree analysis was used to identify the cut-offs of variables that best discriminated among clusters. Results We identified three clusters, characterized by unimpaired (42%), impaired (50.4%) and very impaired (7.5%) SC. Three theory-of-mind domains were more important for the cluster definition as compared with emotion perception and emotional intelligence. Patients more able to understand simple sarcasm (14 for TASIT-SS) were very likely to belong to the unimpaired SC cluster. Compared with patients in the impaired SC cluster, those in the very impaired SC cluster performed significantly worse in lie scenes (TASIT-LI <10), but not in simple sarcasm. Moreover, functioning, neurocognition, disorganization and SC had a linear relationship across the three clusters, while positive symptoms were significantly lower in patients with unimpaired SC as compared with patients with impaired and very impaired SC. On the other hand, negative symptoms were highest in patients with impaired levels of SC. Conclusions If replicated, the identification of such subtypes in clinical practice may help in tailoring rehabilitation efforts to the person's strengths to gain more benefit to the person
Quantum simulation of the Hubbard model with dopant atoms in silicon
In quantum simulation, many-body phenomena are probed in controllable quantum
systems. Recently, simulation of Bose-Hubbard Hamiltonians using cold atoms
revealed previously hidden local correlations. However, fermionic many-body
Hubbard phenomena such as unconventional superconductivity and spin liquids are
more difficult to simulate using cold atoms. To date the required single-site
measurements and cooling remain problematic, while only ensemble measurements
have been achieved. Here we simulate a two-site Hubbard Hamiltonian at low
effective temperatures with single-site resolution using subsurface dopants in
silicon. We measure quasiparticle tunneling maps of spin-resolved states with
atomic resolution, finding interference processes from which the entanglement
entropy and Hubbard interactions are quantified. Entanglement, determined by
spin and orbital degrees of freedom, increases with increasing covalent bond
length. We find separation-tunable Hubbard interaction strengths that are
suitable for simulating strongly correlated phenomena in larger arrays of
dopants, establishing dopants as a platform for quantum simulation of the
Hubbard model.Comment: 6 pages, 5 figures. Supplementary: 13 pages, 7 figures. New version
with some additional discussion, accepted in Nature Communication
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