weather prediction papers


Empirical orthogonal functions and statistical weather prediction
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ABSTRACT A statistical forecasting formula may be established by determining, from a given sample of data, vthe linear combination of a set of predictors which forms the best approximation to_a given predic tand. The dynamical basis for prediction by such formulas

The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation
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Summary¶ In this paper, we first describe the current status of the Advanced Regional Prediction System of the Center for Analysis and Prediction of Storms at the University of Oklahoma. A brief outline of future plans is also given. Two rather successful cases of

Implementation of the lake parameterisation scheme FLake into the numerical weather prediction model COSMO
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The application of the lake model FLake to represent the effect of lakes in numerical weather prediction (NWP) and climate models is discussed. As a lake parameterisation scheme FLake is implemented into the limited-area NWP model COSMO. Results from a numerical

Parameterization of lakes in numerical weather prediction : Description of a lake model
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A lake model intended for use as a lake parameterization module in numerical weather prediction (also in climate modelling and other environmental applications) is developed. The model is capable of predicting the vertical temperature structure and mixing conditions

A fuzzy case-based system for weather prediction
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Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. We describe an investigation into the application of case-based reasoning in airport weather forecasting. Knowledge about temporal features that human forecasters use

Application of data mining techniques in weather prediction and climate change studies
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Weather forecasting is a vital application in meteorology and has been one of the most scientifically and technologically challenging problems around the world in the last century. In this paper, we investigate the use of data mining techniques in forecasting maximum

Experiments aiming at monthly and seasonal numerical weather prediction
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The authors thermal model for monthly and seasonal numerical prediction of temperatures is generalized, so that besides radiation other forms of heating (or the anomalies ofheating) are generated within the model. This is done by expressing such heating as a linear function

Implementation of the initial ACCESS numerical weather prediction system
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The Australian Community Climate and Earth-System Simulator (ACCESS) is a coupled climate and earth system simulator being developed as a joint initiative of the Bureau of Meteorology and CSIRO in cooperation with the university community in Australia. The main

ANN approach for weather prediction using back propagation
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Temperature forecasting is important because they are used to protect life and property. Temperature forecasting is the application of science and technology to predict the state of the temperature for a future time at a given location. Temperature forecasts are made by

17.3 Testing of a new nonlocal boundary layer vertical diffusion scheme in numerical weather prediction applications
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The nonlocal boundary layer vertical diffusion scheme implemented by Hong and Pan (1996, HP hereafter) for the operational MRF model revealed a consistent improvement of the skill for precipitation forecasts over the continental US in the NCEP MRF model (Caplan

ARPEGE/ALADIN: A numerical weather prediction model for Central-Europe with the participation of the Hungarian Meteorological Service
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This paper intends to give a general description of the limited area numerical weather prediction model ARPEGE/ALADIN developed by a collaboration between Meteo-France and some Central- and Eastern-European meteorological services (and also Morocco) including the Hungarian

A decision tree for weather prediction
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A decision tree represents a decision support tool very often used because it is simple to understand and interpret. Classification and Regression Trees-CART-is a technique formed by a collection of rules based on values of certain variables in the modelling data set. This

Aerosol-cloud-precipitation effects over Germany as simulated by a convective-scale numerical weather prediction model
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Possible aerosol-cloud-precipitation effects over Germany are investigated using the COSMO model in a convection-permitting configuration close to the operational COSMO- DE. Aerosol effects on clouds and precipitation are modeled by using an advanced two

Demonstration of NRT GPS water vapor monitoring for numerical weather prediction in Germany
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Within the framework of the German Project GPS Atmosphere Sounding(GASP) an operational monitoring of integrated water vapor using 170 GPS sites in Germany and neighboring countries is performed with an accuracy of±1-2 mm. The results can be

Post-processing rainfall forecasts from numerical weather prediction models for short-term streamflow forecasting
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Sub-daily ensemble rainfall forecasts that are bias free and reliably quantify forecast uncertainty are critical for flood and short-term ensemble streamflow forecasting. Postprocessing of rainfall predictions from numerical weather prediction models is typically

External data for lake parameterization in Numerical Weather Prediction and climate modeling
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Lake parameterizations in atmospheric modeling include a set of external data to indicate and to map physical properties of lakes. The main challenge is the need to consider all the lakes in the atmospheric model domain and to specify the corresponding parameters. For

Receding horizon optimal control of greenhouse climate based on the lazy man weather prediction
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In greenhouse climate control a long term control strategy can be computed based on a model describing plant behaviour in relation to indoor climate and outdoor weather and a criterion reflecting maximum profit. In these computations the greenhouse climate dynamics

Evaluation of numerical weather prediction solar irradiance forecasts in the US
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We evaluate the performance of seven global irradiance (GHI) forecast models. The models are based directly or indirectly on numerical weather prediction (NWP). They are validated against one year of high quality measurements from the 7-station SURFRAD network

The application of total lightning detection and cell tracking for severe weather prediction
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Intracloud (IC) lightning is better correlated to storm severity than cloud-to-ground (CG) lightning. The detection of both IC and CG flashes, or total lightning, enables improvements in the lead time of severe weather prediction and alerting. The WeatherBug Total Lightning

Chaos and weather prediction January 2000
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The weather is a chaotic system. Small errors in the initial conditions of a forecast grow rapidly, and affect predictability. Furthermore, predictability is limited by model errors due to the approximate simulation of atmospheric processes of the stateof-the-art numerical

weather prediction machine learning

Component-based machine learning modelling approach for design stage building energy prediction : weather conditions and size
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Building energy predictions are playing an important role in steering the design towards the required sustainability regulations. Time-consuming nature of detailed Building Energy Modelling (BEM) has introduced simplified BEM and metamodels within the design process

Prediction of Extreme Weather Events using Machine Learning Technique
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In climate applications, an event is an instance in time when a significantand persistent change occurs. Spatiotemporal Data Mining is used in the department of meteorology for the prediction of all kinds of weather data and global changes. The main problem is prediction of

ANovel FOREST FIRE PREDICTION TOOL UTILIZING FIRE WEATHER AND MACHINE LEARNING METHODS
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Wildfires are an essential and natural part of ecosystems that help restore them. Many species of plants rely on such fires to cleanse the environment for better regeneration and growth. Additionally, they have the potential to support the growth of thriving native species

An application of machine learning to geomagnetic index prediction : aiding human space weather forecasting
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humans need to do other tasks (and sleep, eat, ) have algorithmic tools to help human forecasters and alert them we show scoping study for new tool to help human forecasters



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