scholarly journals Hybrid Models for Weather Parameter Forecasting

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Rashmi Bhardwaj ◽  
Varsha Duhoon
Keyword(s):  
Weather Forecasting ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Hybrid Models ◽  
Complex Task ◽  
Tropical Country ◽  
Metropolitan Cities ◽  
Weather Parameters ◽  
Conventional Models ◽  
Simple Models

The objective of the paper is to compare hybrid conjunction models with conventional models for the reduction of errors in weather forecasting. Besides the simple models like RBF model, SMO model, and LibSVM model, different hybrid conjunction models have been used for forecasting under different schemes. The forecasts from these models are further compared on the basis of errors calculated and time taken by the hybrid models and simple models in order to forecast weather parameters. In this paper, conjunction models over the convectional models are designed for forecasting the weather parameters for the reduction of error. India is a tropical country with variations in weather conditions. The objective is to build a conjunction model with less error to forecast weather parameters. A hybrid conjunction model is developed and analysed for different weather parameters for different metropolitan cities of India. Performance measurement is analysed for weather parameters. It is observed that, on the basis of error comparison and time taken by the models, the hybrid wavelet-neuro-RBF model gives better results as compared to the other models due to lower values of determined errors, better performance, and lesser time taken. The study becomes significant as weather forecasting with accuracy is a complex task along with the reduction of prediction error by the application of different models and schemes. It is concluded that the proposed hybrid model is helpful for forecasting and making policies in advance for the betterment of the human being, farmers, tourists, and so on as in all these activities, weather forecast plays an important role.

scholarly journals Weather conditions and weather forecast on the planets of the solar system based on the behavior of Rossby waves

2010 ◽  
Vol 90 (1) ◽  
pp. 135-144
Author(s):  
Milivoj Gavrilov ◽  
Lazar Lazic ◽  
Jasmina Djordjevic
Keyword(s):  
Solar System ◽  
Rossby Waves ◽  
Weather Forecasting ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Relative Movement ◽  
Rotating Fluids ◽  
Atmospheric Processes ◽  
Rotation System ◽  
Dominant Influence

Out of all atmospheric processes on the planets of the Solar System, special attention will be devoted here to leading circulation of planetary or global scales, known as Rossby waves. These waves occur in all rotating fluids that have relative movement to the rotation system. Rossby waves exert dominant influence on so-called global weather. Based on the knowledge of some properties of Rossby waves are made approximate analysis of weather conditions on the planets of the Solar System. Also, these considerations can serve as an introduction to weather forecasting on the planet. .

scholarly journals A novel weather parameters prediction scheme and their effects on crops

2022 ◽  
Vol 12 (1) ◽  
pp. 639
Author(s):  
Naveen Lingaraju ◽  
Hosaagrahara Savalegowda Mohan
Keyword(s):  
Weather Forecasting ◽  
Fitness Function ◽  
Research Work ◽  
Geographical Location ◽  
Weather Forecast ◽  
Forecast Model ◽  
Weather Data ◽  
Prediction Scheme ◽  
Weather Parameters ◽  
Technological World

Weather forecast is significantly imperative in today’s smart technological world. A precise forecast model entails a plentiful data in order to attain the most accurate predictions. However, a forecast of future rainfall from historical data samples has always been challenging and key area of research. Hence, in modern weather forecasting a combo of computer models, observation, and knowledge of trends and patterns are introduced. This research work has presented a fitness function based adaptive artificial neural network scheme in order to forecast rainfall and temperature for upcoming decade (2021-2030) using historical weather data of 20 different districts of Karnataka state. Furthermore, effects of these forecasted weather parameters are realized over five major crops of Karnataka namely rice, wheat, jowar, maize, and ragi with the intention of evaluation for efficient crop management in terms of the passing relevant messages to the farmers and alternate measures such as suggesting other geographical locations to grow the same crop or growing other suitable crops at same geographical location. A graphical user interface (GUI) application has been developed for the proposed work in order to ease out the flow of work.

scholarly journals Weather Prediction using Machine Learning and IOT

2020 ◽  
Vol 9 (4) ◽  
pp. 2094-2098
Keyword(s):  
Machine Learning ◽  
Weather Forecasting ◽  
Learning Algorithm ◽  
Weather Prediction ◽  
Weather Conditions ◽  
Data Sets ◽  
Machine Learning Algorithm ◽  
Time Data ◽  
Weather Parameters ◽  
Set Up

This project proposes a method for forecasting weather conditions and predicting rainfall by means of machine learning. Here, there are two set ups: one, to measure the weather parameters like temperature, humidity using sensors along with Arduino and another set up, to display the current values(status) and predicted rainfall based on the trained machine learning data sets. The weather forecasting and prediction is done based on the older datasets collected and compared with the current values. The user need not have a backup of huge data to predict the rainfall. Instead a machine learning algorithm can suffice the same. The temperature, humidity sensor modules are used to measure weather parameters and interfaced to an Arduino controller. The proposed setup will compare the forecast value with real-time data, and the predict rainfall based on the dataset fed to the machine learning algorithm.

scholarly journals Weather Forecast through Data Mining

2021 ◽  
pp. 90-95
Author(s):  
Swati Pandey ◽  
Shruti Sharma ◽  
Shubham Kumar ◽  
Kanchan Bhatt ◽  
Dr. Rakesh Kumar Arora
Keyword(s):  
Nearest Neighbor ◽  
Weather Forecasting ◽  
Regression Tree ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Classification And Regression Tree ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Random Forest Classification ◽  
Forest Classification

Weather Forecasting is the attempt to predict the weather conditions based on parameters such as temperature, wind, humidity and rainfall. These parameters will be considered for experimental analysis to give the desired results. Data used in this project has been collected from various government institution sites. The algorithm used to predict weather includes Neural Networks(NN), Random Forest, Classification and Regression tree (C &RT), Support Vector Machine, K-nearest neighbor. The correlation analysis of the parameters will help in predicting the future values. This web based application we will have its own chat bot where user can directly communicate about their query related to Weather Forecast and can have experience of two-way communication.

scholarly journals Pembuatan Aplikasi Prakiraan Cuaca Menggunakan Bahasa Pemrograman Visual Basic

Jurnal MIPA ◽  
2013 ◽  
Vol 2 (2) ◽  
pp. 140
Author(s):  
Ricky Daniel Aror ◽  
Hesky S. Kolibu ◽  
Guntur Pasau
Keyword(s):  
Weather Forecasting ◽  
Weather Forecast ◽  
Visual Basic ◽  
Computer Application ◽  
Basic Form ◽  
Application Program ◽  
Weather Forecasters ◽  
Software Program ◽  
Weather Parameters ◽  
Visual Basic 6.0

Metode prakiraan cuaca yang selama ini hanya dilakukan secara manual dengan melihat parameter-parameter cuaca yang ada, sehingga dibuat suatu program aplikasi komputer untuk memudahkan para prakirawan dalam menganalisa dan membuat prakiraan cuaca. Software pembuat program, Visual Basic 6.0 dimanfaatkan dalam pembuatan program aplikasi prakiraan cuaca ini. Tersedianya form pada Visual Basic yang mudah untuk dimodifikasi, memudahkan pengguna untuk mengatur tampilan aplikasi kemudian dijalankan dengan menggunakan kode (script) sebagai perintah. Hasilnya berupa sebuah program aplikasi prakiraan cuaca berekstensi *.exe yang dapat dijalankan pada perangkat komputer. Dengan menggunakan aplikasi prakiraan cuaca ini para prakirawan akan lebih mudah menganalisis dan mengoreksi langsung pada aplikasi ini jika ada kesalahan dan waktu yang dibutuhkan relatif lebih cepat (efisien).Methods of weather forecasting have only done manually by using provided weather parameters, so there is a need to build ​​a computer application program in facilitating the forecasters to analyze and make forecasts. Maker software program called Visual Basic 6.0 application program was utilized in building this forecasts application. Availability of the Visual Basic form that is easy to modify allows users to adjust the display and then run the application using the code (script) as a command. The result is a weather forecast application program with extension *.exe that can be run on the computer. By using this application the weather forecasters will be easier to analyze and correct it directly on the application if there is an error and the time it takes relatively more quickly (efficiently).

scholarly journals Rain Attenuation Prediction Model for Satellite Communications Based on The Météo-France Ensemble Prediction System PEARP

2018 ◽  
Author(s):  
Isabelle Dahman ◽  
Philippe Arbogast ◽  
Nicolas Jeannin ◽  
Bouchra Benammar
Keyword(s):  
Communication Systems ◽  
Weather Forecasting ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Satellite Communications ◽  
General Idea ◽  
Ensemble Prediction ◽  
Second Phase ◽  
Electromagnetic Spectrum ◽  
Mitigation Techniques

Abstract. This paper presents an example of usage of Ensemble Weather Forecast for the control of Satellite-based Communication Systems. Satellite communication systems become increasingly sensitive to weather conditions as their operating frequency is increasing to avoid electromagnetic spectrum congestion and enhance their capacity. In the microwave domain, electromagnetic waves that are conveying information are attenuated between the satellite and Earth terminals in presence of hydrometeors (mostly rain drops and more marginally cloud droplets). To maintain a reasonable level of service availability, even with adverse weather conditions considering the scarcity of amplification power in spacecraft, fade mitigation techniques have been developed. The general idea behind those fade mitigation techniques is to re-route, change the characteristics, or re-schedule the transmission in case of too significant propagation impairments. For some systems, a scheduling on how to use those mechanisms some hours in advance is required, making assumptions on the future weather conditions affecting the link. To this aim the use of weather forecast data to control the attenuation compensation mechanisms seems of particular interest to maximize the performances of the communication links and hence of the associated economic value. A model to forecast the attenuation on the link based on forecasted rainfall amounts from deterministic or ensemble weather forecasting is presented and validated. In a second phase, the model's application to a simplified telecommunication system allows demonstrating the valuable contribution of weather forecasting in the system's availability optimization or in the system's throughput optimization. The benefit of using ensemble weather forecasting rather than deterministic ones is demonstrated as well.

scholarly journals Weather forecast in north-western Greece: RISKMED warnings and verification of MM5 model

2010 ◽  
Vol 10 (2) ◽  
pp. 383-394 ◽  
Author(s):  
A. Bartzokas ◽  
V. Kotroni ◽  
K. Lagouvardos ◽  
C. J. Lolis ◽  
A. Gkikas ◽  
...  
Keyword(s):  
Air Temperature ◽  
Weather Forecasting ◽  
Precipitation Amount ◽  
Warning System ◽  
Weather Forecast ◽  
Early Morning ◽  
Meteorological Model ◽  
Adverse Weather ◽  
North Western ◽  
Western Greece

Abstract. The meteorological model MM5 is applied operationally for the area of north-western Greece for one-year period (1 June 2007–31 May 2008). The model output is used for daily weather forecasting over the area. An early warning system is developed, by dividing the study area in 16 sub-regions and defining specific thresholds for issuing alerts for adverse weather phenomena. The verification of the model is carried out by comparing the model results with observations from three automatic meteorological stations. For air temperature and wind speed, correlation coefficients and biases are calculated, revealing that there is a significant overestimation of the early morning air temperature. For precipitation amount, yes/no contingency tables are constructed for 4 specific thresholds and some categorical statistics are applied, showing that the prediction of precipitation in the area under study is generally satisfactory. Finally, the thunderstorm warnings issued by the system are verified against the observed lightning activity.

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

scholarly journals Cold weather is a predisposing factor for testicular torsion in a tropical country. A retrospective study

2014 ◽  
Vol 133 (3) ◽  
pp. 187-190 ◽  
Author(s):  
Daniel de Oliveira Gomes ◽  
Rafael Rocha Vidal ◽  
Bruno Figueiredo Foeppel ◽  
Danilo Fiorindo Faria ◽  
Minori Saito
Keyword(s):  
Retrospective Study ◽  
Symptom Onset ◽  
Testicular Torsion ◽  
Weather Conditions ◽  
Cold Weather ◽  
Predisposing Factor ◽  
Tropical Country ◽  
Etiologic Role ◽  
Urological Emergency

CONTEXT AND OBJECTIVE:Testicular torsion is a medical and urological emergency because it can lead to loss of the organ. The theory of seasonal testicular torsion occurrence is based on studies from institutions located in cold and temperate regions. The objective here was to determine whether cold weather is associated with higher incidence of testicular torsion in a tropical country, such as Brazil.DESIGN AND SETTING:Retrospective study, conducted in a tertiary and teaching hospital.METHODS:Patients with acute testicular torsion confirmed by surgery between April 2006 and March 2011 were studied. Information on weather conditions at the time of symptom onset was collected.RESULTS:A total of 64 testicular torsion cases were identified. The months with the highest incidences of testicular torsion were June (16%), July (19%) and August (11%), which had the lowest mean temperatures, of 17.6 °C, 16.4 °C and 18.2 °C, respectively. Eleven percent of cases occurred during spring (October to December), 16% occurred in summer (January to March), 34% occurred in fall (April to June) and 39% occurred in winter (July to September). There was a significant association between the incidence of testicular torsion and the season (fall and winter), P < 0.001.CONCLUSIONS:Testicular torsion follows a seasonal association even in a tropical country, and is more frequent in the colder months of the year, namely fall and winter, when almost three-quarters of the cases occurred. These observations add further evidence that cold weather has an etiologic role in testicular torsion occurrence.

Urban Finescale Forecasting Reveals Weather Conditions with Unprecedented Detail

2017 ◽  
Vol 98 (12) ◽  
pp. 2675-2688 ◽  
Author(s):  
R. J. Ronda ◽  
G. J. Steeneveld ◽  
B. G. Heusinkveld ◽  
J. J. Attema ◽  
A. A. M. Holtslag
Keyword(s):  
Local Governments ◽  
Weather Forecasting ◽  
Weather Prediction ◽  
Morphological Characteristics ◽  
Weather Conditions ◽  
Human Thermal Comfort ◽  
Forecasting System ◽  
The Impact ◽  
Urban Weather ◽  
Neighborhood Level

Abstract Urban landscapes impact the lives of urban dwellers by influencing local weather conditions. However, weather forecasting down to the street and neighborhood scale has been beyond the capabilities of numerical weather prediction (NWP) despite the fact that observational systems are now able to monitor urban climate at these scales. In this study, weather forecasts at intra-urban scales were achieved by exploiting recent advances in topographic element mapping and aerial photography as well as looking at detailed mappings of soil characteristics and urban morphological properties, which were subsequently incorporated into a specifically adapted Weather Research and Forecasting (WRF) Model. The urban weather forecasting system (UFS) was applied to the Amsterdam, Netherlands, metropolitan area during the summer of 2015, where it produced forecasts for the city down to the neighborhood level (a few hundred meters). Comparing these forecasts to the dense network of urban weather station observations within the Amsterdam metropolitan region showed that the forecasting system successfully determined the impact of urban morphological characteristics and urban spatial structure on local temperatures, including the cooling effect of large water bodies on local urban temperatures. The forecasting system has important practical applications for end users such as public health agencies, local governments, and energy companies. It appears that the forecasting system enables forecasts of events on a neighborhood level where human thermal comfort indices exceeded risk thresholds during warm weather episodes. These results prove that worldwide urban weather forecasting is within reach of NWP, provided that appropriate data and computing resources become available to ensure timely and efficient forecasts.

Sign in / Sign up

Export Citation Format

Share Document