Abstract:
Numerical Weather Models (NWMs) utilize data collected via diverse sources such as automated
weather stations, radars, air balloons, and satellite images. Before using such multimodal data
in a NWM, it is necessary to transcode data into a format ingested by the NWM. Moreover, the
data integration system’s response time needs to be relatively low to forecast and monitor timesensitive
weather events like hurricanes, storms, and flash floods that require rapid and frequent
execution of NWMs. The resulting weather data also need to be accessed by many researchers
and third-party applications such as logistic and agricultural insurance firms. Existing weather
data integration systems are based on monolithic or client-server architectures; hence, unable to
benefit from novel computational models such as cloud computing and containerized applications.
Moreover, most of these softwares are proprietary or closed-source, making it difficult to customize
them for an island like Sri Lanka with different weather seasons. Therefore, in this research, we
propose Weather Data Integration and Assimilation System (WDIAS) that utilizes microservices
to achieve scalability, high availability, and low-cost operation based on cloud computing. The
use of stateless microservices also enables WDIAS to add new features on the fly with rollover
capabilities. Moreover, WDIAS provides a modular framework to integrate data from different
sources, export into different formats, and add new functionality by adding extension modules.
We demonstrate the utility of WDIAS using a cloud-based experimental setup and weather-related
synthetic workloads.
Citation:
karunarathne, H,M,G,C. (2021). Weather data integration and assimilation system [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/22274