Workflow-Based Platform Design and Implementation for Numerical Weather Prediction Models and Meteorological Data Service

Xiaoxia, Chen; Wei, Min; Sun, Jing

doi:10.4236/acs.2017.73025

Cited by 4 publications

(6 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Relate work Key point Meteorological big data service 18-25 18,19 Meteorological big data 20 Application of meteorological big data 21 A smart meteorological service model 22,23 Development of meteorological data for applications and modeling 24,25 Investigation on the meteorological big data services Meteorological scientific workflow 26-31 26,27 The development and application of workflow 28 The workflow scheduling issue 29 The meteorological workflow 30 Design and implementation of meteorological data workflows 31 The advantage of meteorological workflows Meteorological product service 32-36 32,33 The meteorological services 34 The development and creation of meteorological services 35 An evaluation of satellite/model proxies for hydrometeorology monitoring 36 The importance of meteorological services…”

Section: Itemmentioning

confidence: 99%

“…Chen et al proposed several models for weather forecasting and an example for the design and implementation of meteorological data workflows. 36 Hence, the meteorological workflows could coordinate a range of data-intensive tasks involving a variety of large-scale data to enable efficient implementation of the complex meteorological services.…”

Section: Meteorological Scientific Workflowmentioning

confidence: 99%

“…The interrelations between the tasks of the meteorological applications are represented in a breeze by workflow model which defines various parameters to realize the automation of the entire process. Chen et al proposed several models for weather forecasting and an example for the design and implementation of meteorological data workflows 36 . Hence, the meteorological workflows could coordinate a range of data‐intensive tasks involving a variety of large‐scale data to enable efficient implementation of the complex meteorological services.…”

Section: Architecture Classification and Definition Of Meteorological...mentioning

confidence: 99%

See 2 more Smart Citations

Resource management for meteorological service in cloud‐edge computing: A survey

Tang¹,

Zhang

et al. 2020

Trans Emerging Tel Tech

View full text Add to dashboard Cite

The ever‐increasing volume of data and the higher demand for real‐time services in the meteorological industry have made the relevant departments face some problems such as how to process data efficiently and deliver services instantly. Hence, by intervening in cloud computing and building meteorological cloud platform, the data are effectively managed and processed which means reliable services could be satisfied. However, a large amount of complex heterogeneous data generated by meteorological stations remote from the cloud center is sent to the cloud for processing to impose bandwidth pressure on the cloud. It will bring substantial access delays in case of frequent access. Meanwhile, the data in the public cloud will encounter security problems for the sensitivity. Therefore, appropriate assistive techniques such as edge computing are urgent to be chosen to solve the aforementioned problems. The collaborative work of edge computing and cloud makes meteorological data sent to the edge nodes for processing, which effectively cuts down the bandwidth pressure, reduces the transmission delay, and advances data security of the cloud. In this paper, we first describe the architecture, classification, and definition of meteorological services in the cloud. Then, the resource management of meteorological services in edge computing and cloud computing is summarized respectively. Furthermore, meteorological applications in cloud computing is introduced. Besides, we explore the future work of meteorological service provisioning in collaborative edge computing and cloud.

show abstract

Section: Itemmentioning

confidence: 99%

Section: Meteorological Scientific Workflowmentioning

confidence: 99%

Section: Architecture Classification and Definition Of Meteorological...mentioning

confidence: 99%

See 1 more Smart Citation

Resource management for meteorological service in cloud‐edge computing: A survey

Tang¹,

Zhang

et al. 2020

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…This technique uses equations drawn from the principles of physics and thermodynamics to create predictions. While NWP is an effective solution for many forecasting problems, it still has limitations, such as using an excessive amount of computing power [2]. Additionally, forecasting using NWP may be susceptible to noise that may be included in the observations of meteorological variables because of the assumptions about meteorological variables utilized in this technique [3].…”

Section: Introductionmentioning

confidence: 99%

A novel wind power prediction model using graph attention networks and bi-directional deep learning long and short term memory

Mansoury,

Bourakadi,

Yahyaouy

et al. 2023

IJECE

View full text Add to dashboard Cite

<span lang="EN-US">Today, integrating wind energy forecasting is an important area of research due to the erratic nature of wind. To achieve this goal, we propose a new model of wind speed prediction based on graph attention networks (GAT), we added a new attention mechanism and a learnable adjacency matrix to the GAT structure to obtain attention scores for each weather variable. The results of the GAT-based model are merged with the bi-directional deep learning long and short-term memory (BiLSTM) layer to take advantage of the geographic and temporal properties of historical weather data. The experiments and analyzes are carried out using precise meteorological data collected from wind farms in the Moroccan city of Tetouan. We show that the proposed model can learn complex input-output correlations of meteorological data more efficiently than previous wind speed prediction algorithms. Due to the resulting attention weights, the model also provides more information about the main weather factors for the evaluated forecast work.</span>

show abstract

“…Lin et al (2018) find that it is of great significance to actively adapt to the characteristics of information dissemination in the all-media era, and propose the construction of meteorological information dissemination mechanism. Chen et al (2017) present a set of best practices for workflow design and implementation for numerical weather prediction models and meteorological data service, which have been in operation in China Meteorological Administration for years and have proven to be effective in the managing of the complexities of large-scale meteorological related work flows. Lin et al (2017) propose a set of software classification method based on software operating characteristics with principal component analysis used to reduce the dimension of software running feature data and to interpret software characteristic information, and a modified K-means algorithm used to classify the meteorological data processing.…”

Section: Introductionmentioning

confidence: 99%

Design and Application of Integrated Monitoring Model for Provincial Meteorological Observation Data Transmission

Zhang¹,

Chen²,

Shen³

et al. 2019

GEP

View full text Add to dashboard Cite

With the development of meteorological services, there are more and more types of real-time observation data, and the timeliness requirements are getting higher and higher. The monitoring methods of existing meteorological observation data transmission can no longer meet the needs. This paper proposes a new monitoring model, namely the "integrated monitoring model" for provincial meteorological observation data transmission. The model can complete the whole network monitoring of meteorological observation data transmission process. Based on this model, the integrated monitoring system for meteorological observation data transmission in Guangdong Province is developed. The system uses Java as the programming language, and integrates J2EE, Hibernate, Quartz, Snmp4j and Slf4j frameworks, and uses Oracle database as the data storage carrier, following the MVC specification and agile development concept. The system development uses four key technologies, including simple network management protocol, network connectivity detection technology, remote host management technology and thread pool technology. The integrated monitoring system has been put into business application. As a highlight of Guangdong's meteorological modernization, it has played an active role in many major meteorological services.

show abstract

Workflow-Based Platform Design and Implementation for Numerical Weather Prediction Models and Meteorological Data Service

Cited by 4 publications

References 1 publication

Resource management for meteorological service in cloud‐edge computing: A survey

Resource management for meteorological service in cloud‐edge computing: A survey

A novel wind power prediction model using graph attention networks and bi-directional deep learning long and short term memory

Design and Application of Integrated Monitoring Model for Provincial Meteorological Observation Data Transmission

Contact Info

Product

Resources

About