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Overdispersion phenomenon in stochastic modeling of precipitation

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Low-pressure area

In meteorology, a low-pressure area, low area or low is a region where the atmospheric pressure is lower than that of surrounding locations. Low-pressure areas are commonly associated with inclement weather (such as cloudy, windy, with possible rain or storms), while high-pressure areas are associated with lighter winds and clear skies. Winds circle anti-clockwise around lows in the northern hemisphere, and clockwise in the southern hemisphere, due to opposing Coriolis forces.

Stochastic

Stochastic (stəˈkæstɪk; ) refers to the property of being well described by a random probability distribution. Although stochasticity and randomness are distinct in that the former refers to a modeling approach and the latter refers to phenomena themselves, these two terms are often used synonymously. Furthermore, in probability theory, the formal concept of a stochastic process is also referred to as a random process.

Rain gauge

A rain gauge (also known as udometer, pluviometer, pluviameter, ombrometer, and hyetometer) is an instrument used by meteorologists and hydrologists to gather and measure the amount of liquid precipitation over a predefined area, over a period of time. It is used to determine the depth of precipitation (usually in mm) that occurs over a unit area and measure rainfall amount. The first known rainfall records were kept by the Ancient Greeks, at around 500 BCE.

Mixture distribution

In probability and statistics, a mixture distribution is the probability distribution of a random variable that is derived from a collection of other random variables as follows: first, a random variable is selected by chance from the collection according to given probabilities of selection, and then the value of the selected random variable is realized. The underlying random variables may be random real numbers, or they may be random vectors (each having the same dimension), in which case the mixture distribution is a multivariate distribution.

Numerical weather prediction

Numerical weather prediction (NWP) uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. Though first attempted in the 1920s, it was not until the advent of computer simulation in the 1950s that numerical weather predictions produced realistic results. A number of global and regional forecast models are run in different countries worldwide, using current weather observations relayed from radiosondes, weather satellites and other observing systems as inputs.

General circulation model

A general circulation model (GCM) is a type of climate model. It employs a mathematical model of the general circulation of a planetary atmosphere or ocean. It uses the Navier–Stokes equations on a rotating sphere with thermodynamic terms for various energy sources (radiation, latent heat). These equations are the basis for computer programs used to simulate the Earth's atmosphere or oceans. Atmospheric and oceanic GCMs (AGCM and OGCM) are key components along with sea ice and land-surface components.

Time series

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Stochastic cellular automaton

Stochastic cellular automata or probabilistic cellular automata (PCA) or random cellular automata or locally interacting Markov chains are an important extension of cellular automaton. Cellular automata are a discrete-time dynamical system of interacting entities, whose state is discrete. The state of the collection of entities is updated at each discrete time according to some simple homogeneous rule. All entities' states are updated in parallel or synchronously.

Normal distribution

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Supersymmetric theory of stochastic dynamics

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