Isoline Retrieval

	Isoline Retrieval Isoline retrieval is a remote sensing inverse method that retrieves one or more isolines of a trace atmospheric constituent or variable. When used to validate another contour, it is the most accurate method possible for the task. When used to retrieve a whole field, it is a general, nonlinear inverse method and a robust estimator. For validating advected contours Rationale Suppose we have, as in contour advection, inferred knowledge of a single contour or isoline of an atmospheric constituent, ''q'' and we wish to validate this against satellite remote-sensing data. Since satellite instruments cannot measure the constituent directly, we need to perform some sort of inversion. In order to validate the contour, it is not necessary to know, at any given point, the exact value of the constituent. We only need to know whether it falls inside or outside, that is, is it greater than or less than the value of the contour, ''q0''. This is a classification problem. Let: : j = \begin 1 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon]
picture info	Remote Sensing Remote sensing is the acquisition of information about an physical object, object or phenomenon without making physical contact with the object, in contrast to in situ or on-site observation. The term is applied especially to acquiring information about Earth and other planets. Remote sensing is used in numerous fields, including geophysics, geography, land surveying and most Earth science disciplines (e.g. exploration geophysics, hydrology, ecology, meteorology, oceanography, glaciology, geology). It also has military, intelligence, commercial, economic, planning, and humanitarian applications, among others. In current usage, the term ''remote sensing'' generally refers to the use of satellite- or airborne-based sensor technologies to detect and classify objects on Earth. It includes the surface and the atmosphere and oceans, based on wave propagation, propagated signals (e.g. electromagnetic radiation). It may be split into "active" remote sensing (when a signal is emitted b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon]
	RTTOV (radiative Transfer Code) RTTOV - the fast radiative transfer model for calculations of radiances for satellite infrared or microwave nadir scanning radiometers (see push broom scanner). Given an atmospheric profile of temperature, variable gas concentrations, cloud and surface properties RTTOV calculates radiances and brightness temperatures. The only mandatory input is water vapour. Optionally ozone, carbon dioxide, nitrous oxide, methane and carbon monoxide can be variable with all other constituents assumed to be constant. The range of temperatures and water vapour concentrations over which the optical depth computations are valid depends on the training datasets which were used. The spectral range of the RTTOV9.1 model is 3-20 micrometres (500 – 3000 cm-1) in the infrared. RTTOV contains forward, tangent linear, adjoint and K (full Jacobian matrices) versions of the model; the latter three modules for variational assimilation or retrieval applications. One of several applications of RTTOV ar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon]
	Robust Estimator Robust statistics are statistics that maintain their properties even if the underlying distributional assumptions are incorrect. Robust statistical methods have been developed for many common problems, such as estimating location, scale, and regression parameters. One motivation is to produce statistical methods that are not unduly affected by outliers. Another motivation is to provide methods with good performance when there are small departures from a parametric distribution. For example, robust methods work well for mixtures of two normal distributions with different standard deviations; under this model, non-robust methods like a t-test work poorly. Introduction Robust statistics seek to provide methods that emulate popular statistical methods, but are not unduly affected by outliers or other small departures from model assumptions. In statistics, classical estimation methods rely heavily on assumptions that are often not met in practice. In particular, it is often assumed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon]
picture info	Error Function In mathematics, the error function (also called the Gauss error function), often denoted by , is a function \mathrm: \mathbb \to \mathbb defined as: \operatorname z = \frac\int_0^z e^\,\mathrm dt. The integral here is a complex Contour integration, contour integral which is path-independent because \exp(-t^2) is Holomorphic function, holomorphic on the whole complex plane \mathbb. In many applications, the function argument is a real number, in which case the function value is also real. In some old texts, the error function is defined without the factor of \frac. This nonelementary integral is a sigmoid function, sigmoid function that occurs often in probability, statistics, and partial differential equations. In statistics, for non-negative real values of , the error function has the following interpretation: for a real random variable that is normal distribution, normally distributed with mean 0 and standard deviation \frac, is the probability that falls in the range . ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon]
	Proxy (statistics) In statistics, a proxy or proxy variable is a variable that is not in itself directly relevant, but that serves in place of an unobservable or immeasurable variable. In order for a variable to be a good proxy, it must have a close correlation, not necessarily linear, with the variable of interest. This correlation might be either positive or negative. Proxy variable must relate to an unobserved variable, must correlate with disturbance, and must not correlate with regressors once the disturbance is controlled for. Examples In social sciences, proxy measurements are often required to stand in for variables that cannot be directly measured. This process of standing in is also known as operationalization. Per-capita gross domestic product (GDP) is often used as a proxy for measures of standard of living or quality of life. Montgomery ''et al.'' examine several proxies used, and point out limitations with each, stating "In poor countries, no single empirical measure can be expected ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon]