EGU25-1941, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-1941
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Wednesday, 30 Apr, 10:45–12:30 (CEST), Display time Wednesday, 30 Apr, 08:30–12:30
 
Hall X4, X4.94
Progress in Cloud MICAPS Engine
Feng Xue
Feng Xue
  • National Meteorological Centre,CMA, Forecasting System Laboratory, Beijing, China (xuef@cma.gov.cn)

Cloud MICAPS Engine is a next-generation cloud and component-based application development framework for Meteorological Information Comprehensive Analysis and Processing System(MICAPS)  in China, which has the following features:

I.Microservice Architecture
It utilizes a hybrid microservices management framework composed of K8s (Kubernetes) and Spring Cloud. The primary computational services are based on the underlying K8s + container cloud to implement microservices, while the upper-layer business applications integrate business-oriented microservices functions through Spring Cloud.

II.Real-time Visualization and Analysis
Developed using B/S technology, all weather-related business data is encapsulated as meteorological data layers through methods such as OGC, resumable transmission, and streaming services for loading by front-end business applications. It includes professional analysis components for common meteorological business operations such as points, lines, and surfaces, as well as interactive analysis of time curves, vertical soundings, and arbitrary sections.

III.Real-time Visualization Rendering
Based on real-time drawing technologies such as WebGL and WebGPU, it supports real-time product map services for products with high access volumes through pre-processing and pre-service methods, forming a highly consistent map service data environment with an integrated approach.

IV.Collaborative Editing and Forecast Service
Based on a 2D/3D map engine, the high-resolution real-time data visualization rendering technology is supported by CogTiff data storage and service technology. Real-time synchronization of interactive editing operations is achieved through WebSocket to realize real-time collaboration among multi-terminals. The back-end data editing algorithm realizes the consistency of updated data in FIFO.


V.LLM-driven Interaction and Processing
Large language models technology is used, with aggregating algorithms in the whole process of intelligent digital forecast service business, including observation perception, analysis diagnosis, interactive judgment, processing and generation, inspection and evaluation. "AI Agent" is the core to drive human-computer intelligent interaction and information recommendation.

Cloud MICAPS Engine  will be released later in 2025.

How to cite: Xue, F.: Progress in Cloud MICAPS Engine, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1941, https://doi.org/10.5194/egusphere-egu25-1941, 2025.