Climate is the statistics (usually, mean or variability) of weather, usually over a 30-year interval. It is measured by assessing the patterns of variation in temperature, humidity, atmospheric pressure, wind, precipitation, atmospheric particle count and other meteorological variables in a given region over long periods of time. Climate differs from weather, in that weather only describes the short-term conditions of these variables in a given region.
A region's climate is generated by the climate system, which has five components: atmosphere, hydrosphere, cryosphere, lithosphere, and biosphere.
The climate of a location is affected by its latitude, terrain, and altitude, as well as nearby water bodies and their currents. Climates can be classified according to the average and the typical ranges of different variables, most commonly temperature and precipitation. The most commonly used classification scheme was Köppen climate classification originally developed by Wladimir Köppen. The Thornthwaite system, in use since 1948, incorporates evapotranspiration along with temperature and precipitation information and is used in studying biological diversity and the potential effects on it of climate changes. The Bergeron and Spatial Synoptic Classification systems focus on the origin of air masses that define the climate of a region.
The field of Complex Networks has emerged as an important area of science to generate novel insights into nature of complex systems. The application of the theory to Climate Science is a young and emerging field. , , , To identify and analyze patterns in global climate, scientists model the climate data as Complex Networks.
Unlike most of the real-world networks in which nodes and edges are well defined, nodes in climate networks are identified with the spatial grid points of underlying global climate data set, which is defined arbitrarily and can be represented at various resolutions. Two nodes are connected by an edge depending on the degree of statistical dependence between corresponding pairs of time-series taken from climate data, on the basis of similarity shared in climatic variability.,, The climate network approach enables novel insights into the dynamics of the climate system over many spatial scales., ,
Depending upon the choice of nodes and/or edges, climate networks may take many different forms, shapes, sizes and complexities. Tsonis et al introduced the field of complex networks to climate. In their model, the nodes for the network were constituted by a single variable (500 hPa) from NCEP/NCAR Reanalysis datasets. In order to estimate the edges between nodes, correlation coefficient at zero time lag between all possible pairs of nodes was estimated. A pair of nodes was considered to be connected, if their correlation coefficient is above a threshold of 0.5.
In viticulture, the climates of wine regions are categorised based on the overall characteristics of the area's climate during the growing season. While variations in macroclimate are acknowledged, the climates of most wine regions are categorised (somewhat loosely based on the Köppen climate classification) as being part of a Mediterranean (for example Tuscany), maritime (ex: Bordeaux) or continental climate (ex: Columbia Valley). The majority of the world's premium wine production takes place in one of these three climate categories in locations between the 30th parallel and 50th parallel in both the northern and southern hemisphere. While viticulture does exist in some tropical climates, most notably Brazil, the amount of quality wine production in those areas is so small that the climate effect has not been as extensively studied as other categories.
Beyond establishing whether or not viticulture can even be sustained in an area, the climatic influences of a particular area goes a long way in influencing the type of grape varieties grown in a region and the type of viticultural practices that will be used. The presence of adequate sun, heat and water are all vital to the healthy growth and development of grapevines during the growing season. Additionally, continuing research has shed more light on the influence of dormancy that occurs after harvest when the grapevine essentially shuts down and reserves its energy for the beginning of the next year's growing cycle.
Innovation is a new idea, or more-effective device or process. Innovation can be viewed as the application of better solutions that meet new requirements, unarticulated needs, or existing market needs. This is accomplished through more-effective products, processes, services, technologies, or business models that are readily available to markets, governments and society. The term "innovation" can be defined as something original and more effective and, as a consequence, new, that "breaks into" the market or society.
While a novel device is often described as an innovation, in economics, management science, and other fields of practice and analysis, innovation is generally considered to be the result of a process that brings together various novel ideas in a way that they have an impact on society.
In business and economics, innovation can be a catalyst to growth. With rapid advancements in transportation and communications over the past few decades, the old world concepts of factor endowments and comparative advantage which focused on an area’s unique inputs are outmoded for today’s global economy. Economist Joseph Schumpeter, who contributed greatly to the study of innovation economics, argued that industries must incessantly revolutionize the economic structure from within, that is innovate with better or more effective processes and products, as well as market distribution, such as the connection from the craft shop to factory. He famously asserted that “creative destruction is the essential fact about capitalism”. In addition, entrepreneurs continuously look for better ways to satisfy their consumer base with improved quality, durability, service, and price which come to fruition in innovation with advanced technologies and organizational strategies.
In time series analysis (or forecasting) — as conducted in statistics, signal processing, and many other fields — the innovation is the difference between the observed value of a variable at time t and the optimal forecast of that value based on information available prior to time t. If the forecasting method is working correctly successive innovations are uncorrelated with each other, i.e., constitute a white noise time series. Thus it can be said that the innovation time series is obtained from the measurement time series by a process of 'whitening', or removing the predictable component. The use of the term innovation in the sense described here is due to Hendrik Bode and Claude Shannon (1950) in their discussion of the Wiener filter problem, although the notion was already implicit in the work of Kolmogorov.
Innovation is a subscription-based magazine, compiling recent developments in the area of research in Singapore and globally. The format and style is designed to be accessible to an "educated layperson", and also includes relevant fields such as patenting. The magazine is jointly published by the National University of Singapore and World Scientific.
To date, local Singaporean companies such as the Defence, Science and Technology Agency (DSTA) and academia have been featured in the magazine.
Aside from the cover story, each magazine generally has the following columns:
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