Journal ArticleDOI
A new PCA‐ANN algorithm for retrieval of rainfall structure in a precipitating atmosphere
TLDR
In this paper, the authors developed an algorithm, using PCA-based neural network, to retrieve the vertical rainfall structure in a precipitating atmosphere, powered by a rigorous solution to the plane parallel radiative transfer equation for the atmosphere with thermodynamically consistent vertical profiles of humidity, temperature and cloud structures.Abstract:
Purpose – The purpose of this paper is to develop an algorithm, using PCA‐based neural network, to retrieve the vertical rainfall structure in a precipitating atmosphere. The algorithm is powered by a rigorous solution to the plane parallel radiative transfer equation for the atmosphere with thermodynamically consistent vertical profiles of humidity, temperature and cloud structures, together with “measured” vertical profiles of the rain structure derived from a radar.Design/methodology/approach – The raining atmosphere is considered to be a plane parallel, radiatively participating medium. The atmospheric thermodynamic profiles such as pressure, temperature and relative humidity along with wind speed at sea surface and cloud parameters corresponding to Nargis, a category 4 tropical cyclone that made its landfall on May 2, 2008 at the Republic of Myanmar, are obtained by solving the flux form of Euler's equations in three‐dimensional form. The state‐of‐the‐art community software Weather Research and Forec...read more
Citations
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Journal ArticleDOI
Short-Term Rainfall Forecasting Using Multi-Layer Perceptron
TL;DR: This paper proposes a novel solution called Dynamic Regional Combined short-term rainfall Forecasting approach (DRCF) using Multi-layer Perceptron (MLP) and shows that DRCF outperforms existing approaches in both threat score (TS) and root mean square error (RMSE).
Journal ArticleDOI
Assimilation of multi-channel radiances in mesoscale models with an ensemble technique to improve track forecasts of Tropical cyclones
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The Effect of Anthropogenic Heat and Moisture on Local Weather at Industrial Heat Islands: A Numerical Experiment
TL;DR: In this paper , the role of heat and moisture emitted from anthropogenic sources on the local weather with the aid of numerical weather prediction is addressed, where the authors conducted a numerical simulation to understand the effect of heat on local weather.
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Intercomparison between IMD ground radar and TRMM PR observations using alignment methodology and artificial neural network
TL;DR: In this paper, an inter-comparison of ground radar reflectivity with space-borne TRMM's Precipitation Radar using alignment methodology has been presented, where a supervised learning algorithm based on the back-propagation neural network is used for this purpose.
Journal ArticleDOI
Rainfall Estimation From TEMPEST-D CubeSat Observations: A Machine-Learning Approach
TL;DR: In this paper , a machine-learning model was used to produce surface rainfall estimates from TEMPEST-D microwave radiance observations from a CubeSat, which is based on an artificial neural network (ANN).
References
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A Description of the Advanced Research WRF Version 2
William C. Skamarock,Joseph B. Klemp,Jimy Dudhia,David O. Gill,Dale Barker,Wei Wang,Jordan G. Powers +6 more
TL;DR: The Weather Research and Forecasting (WRF) model as mentioned in this paper was developed as a collaborative effort among the NCAR Mesoscale and Microscale Meteorology (MMM) Division, the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Prediction (NCEP) and Forecast System Laboratory (FSL), the Department of Defense's Air Force Weather Agency (AFWA) and Naval Research Laboratory (NRL), the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma, and the Federal Aviation Administration (F
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The Tropical Rainfall Measuring Mission (TRMM) Sensor Package
TL;DR: In this article, the authors present a reference guide to users wishing to make use of the Tropical Rainfall Measuring Mission data, which covers each of the three primary rainfall instruments: the passive microwave radiometer, the precipitation radar, and the Visible and Infrared Radiometer System on board the spacecraft.
A tutorial on Principal Components Analysis
TL;DR: PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension.
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A time-split nonhydrostatic atmospheric model for weather research and forecasting applications
TL;DR: The Advanced Research WRF (ARW) model is described, representative of this generation and of a class of models using explicit time-splitting integration techniques to efficiently integrate the Euler equations, and is the first fully compressible conservative-form nonhydrostatic atmospheric model suitable for both research and weather prediction applications.
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New Equations for Computing Vapor Pressure and Enhancement Factor
TL;DR: In this paper, the saturation vapor pressure and temperature for moist air were derived for the meteorologically interesting region of −80 to +50°C. The equations are designed to be easily implemented on a calculator or computer and can be used to convert in either direction.