Working memory (WM) maintains a limited amount of information over a short period of time at the service of other ongoing mental activities. Xie, Weizhen Cappiello, Marcus Park, Hyung-Bum Deldin, Patricia Chan, Raymond C K Zhang, Weiwei Schizotypy is associated with reduced mnemonic precision in visual working memory. The framework developed in this article can be adapted to estimate the “best possible†precision of other vegetation indices derived using data from other remote sensing satellites. Transforming the computed NDVI into a single byte for disk storage results in little or no loss of precision. Using typical solar zenith angles for AVHRR image acquisitions over Australia, ± 0.01 NDVI units is typically with “best possible†precision attainable in the NDVI, although this degrades significantly over dark targets, and at large solar zenith angles. While the radiance resolution of a spectral observation is essentially fixed by the instrument characteristics, the reflectance resolution is the radiance resolution divided by the cosine of the solar zenith angle.
The framework is based on the “best possible†precision concept, which assumes that signal quantization is the only source of observational error. This article reports on a formal statistical framework for assessing the precision of the NDVI derived from NOAA-AVHRR observations. This unitless index is computed using near-infrared and red reflectances, and thus has both an accuracy and precision. Vegetation studies using NOAA-AVHRR data have tended to focus on the use of the normalized difference vegetation index (NDVI). International Nuclear Information System (INIS) The precision of the NDVI derived from AVHRR observations
#Netcontrol radoslaw mazur software
A software emulator was used to mimic the use of reduced precision floating point arithmetic in simulations. Model simulations are performed with a superparameterized single-column model version of the OpenIFS model that is forced by observational data sets. It is shown that the precision analysis can be used to improve model efficiency for both simulations in double precision and in reduced precision. The precision analysis is also used to identify model parts that are of less importance thus enabling a reduction of model complexity. It is shown not only that numerical precision can be reduced significantly but also that the results of the reduced precision analysis provide valuable information for the quantification of model uncertainty for individual model components. This is nontrivial for a complex model that shows chaotic behavior such as the cloud resolving model in this paper. An approach to identify the optimal level of precision for many different model components is presented, and a detailed analysis of precision is performed. The use of reduced numerical precision to reduce computing costs for the cloud resolving model of superparameterized simulations of the atmosphere is investigated. Subramanian, Aneesh Dawson, Andrew Palmer, T. for Ethernet, RS232, RS485 or USB.A study of reduced numerical precision to make superparameterization more competitive using a hardware emulator in the OpenIFS modelĭüben, Peter D.
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