Directional Component Analysis

picture info	Directional Component Analysis Directional component analysis (DCA) is a statistical method used in climate science for identifying representative patterns of variability in space-time data-sets such as historical climate observations, weather prediction ensembles or climate ensembles. The first DCA pattern is a pattern of weather or climate variability that is both likely to occur (measured using likelihood) and has a large impact (for a specified linear impact function, and given certain mathematical conditions: see below). The first DCA pattern contrasts with the first PCA pattern, which is likely to occur, but may not have a large impact, and with a pattern derived from the gradient of the impact function, which has a large impact, but may not be likely to occur. DCA differs from other pattern identification methods used in climate research, such as EOFs, rotated EOFs and extended EOFs in that it takes into account an external vector, the gradient of the impact. DCA provides a way to reduce large ens ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Ensemble Forecasting Ensemble forecasting is a method used in or within numerical weather prediction. Instead of making a single forecast of the most likely weather, a set (or ensemble) of forecasts is produced. This set of forecasts aims to give an indication of the range of possible future states of the atmosphere. Ensemble forecasting is a form of Monte Carlo analysis. The multiple simulations are conducted to account for the two usual sources of uncertainty in forecast models: (1) the errors introduced by the use of imperfect initial conditions, amplified by the chaotic nature of the equations of the atmosphere, which is often referred to as sensitive dependence on initial conditions; and (2) errors introduced because of imperfections in the model formulation, such as the approximate mathematical methods to solve the equations. Ideally, the verified future atmospheric state should fall within the predicted ensemble spread, and the amount of spread should be related to the uncertainty (error) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Multivariate T-distribution In statistics, the multivariate ''t''-distribution (or multivariate Student distribution) is a multivariate probability distribution. It is a generalization to random vectors of the Student's ''t''-distribution, which is a distribution applicable to univariate random variables. While the case of a random matrix could be treated within this structure, the matrix ''t''-distribution is distinct and makes particular use of the matrix structure. Definition One common method of construction of a multivariate ''t''-distribution, for the case of p dimensions, is based on the observation that if \mathbf y and u are independent and distributed as N(,) and \chi^2_\nu (i.e. multivariate normal and chi-squared distributions) respectively, the matrix \mathbf\, is a ''p'' × ''p'' matrix, and is a constant vector then the random variable =/\sqrt + has the density : \frac\left +\frac(-)^T^(-)\right and is said to be distributed as a multivariate ''t''-distribution with para ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Data Analysis Data analysis is the process of inspecting, Data cleansing, cleansing, Data transformation, transforming, and Data modeling, modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and Statistical h ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Numerical Climate And Weather Models Numerical may refer to: * Number * Numerical digit * Numerical analysis Numerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic computation, symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics). It is the study of ... {{disambig ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Climate And Weather Statistics Climate is the long-term weather pattern in a region, typically averaged over 30 years. More rigorously, it is the mean and variability of meteorological variables over a time spanning from months to millions of years. Some of the meteorological variables that are commonly measured are temperature, humidity, atmospheric pressure, wind, and precipitation. In a broader sense, climate is the state of the components of the climate system, including the atmosphere, hydrosphere, cryosphere, lithosphere and biosphere and the interactions between them. The climate of a location is affected by its latitude, longitude, terrain, altitude, land use and nearby water bodies and their currents. Climates can be classified according to the average and typical variables, most commonly temperature and precipitation. The most widely used classification scheme is the Köppen climate classification. The Thornthwaite system, in use since 1948, incorporates evapotranspiration along with temperature ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Lagrange Multiplier In mathematical optimization, the method of Lagrange multipliers is a strategy for finding the local maxima and minima of a function (mathematics), function subject to constraint (mathematics), equation constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variable (mathematics), variables). It is named after the mathematician Joseph-Louis Lagrange. Summary and rationale The basic idea is to convert a constrained problem into a form such that the derivative test of an unconstrained problem can still be applied. The relationship between the gradient of the function and gradients of the constraints rather naturally leads to a reformulation of the original problem, known as the Lagrangian function or Lagrangian. In the general case, the Lagrangian is defined as \mathcal(x, \lambda) \equiv f(x) + \langle \lambda, g(x)\rangle for functions f, g; the notation \langle \cdot, \cdot \rangle denotes an inner prod ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	European Centre For Medium-Range Weather Forecasts The European Centre for Medium-Range Weather Forecasts (ECMWF) is an independent intergovernmental organisation supported by most of the nations of Europe. It is based at three sites: Shinfield Park, Reading, United Kingdom; Bologna, Italy; and Bonn, Germany. It operates one of the largest supercomputer complexes in Europe and the world's largest archive of numerical weather prediction data. History ECMWF was established in 1975, in recognition of the need to pool the scientific and technical resources of Europe's meteorological services and institutions for the production of weather forecasts for medium-range timescales (up to approximately two weeks) and of the economic and social benefits expected from it. The Centre employs about 350 staff, mostly appointed from across the member states and co-operating states. In 2017, the centre's member states accepted an offer from the Italian Government to move ECMWF's data centre to Bologna, Italy. The new site, a former tobacco ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Climatic Research Unit The Climatic Research Unit (CRU) is a component of the University of East Anglia and is one of the leading institutions concerned with the study of natural and anthropogenic climate change. With a staff of some thirty research scientists and students, the CRU has contributed to the development of a number of the data sets widely used in climate research, including one of the global temperature records used to monitor the state of the climate system, as well as statistical software packages and climate models. History The CRU was founded in 1972 as part of the university's School of Environmental sciences. The establishment of the Unit owed much to the support of Sir Graham Sutton, a former Director-General of the Meteorological Office, Lord Solly Zuckerman, an adviser to the University, and Professors Keith Clayton and Brian Funnel, Deans of the School of Environmental Sciences in 1971 and 1972. Initial sponsors included British Petroleum, the Nuffield Foundation and Roya ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]