CPAS
Year: 2025
Type: article
Abstract: 1. How is the Lianke Platform for Atmospheric Simulation (CPAS)? The Lianke Platform for Atmospheric Simulation (CPAS) is a cloud-based service platform that implements Custom Unstructured Grid Generation (CUMG) and Hierarchical Time Stepping (HTS) on MPAS-A (Model for Multiscale Prediction - Atmosphere), better meeting the computational needs of users of atmospheric numerical models. CPAS is a service platform developed based on MPAS-A and WRF. Many numerical weather prediction (NWP) models, such as WRF, use rectangular grids to balance accuracy and computational cost. These grids achieve local optimization by nesting high-resolution regions within coarser ones. MPAS-A, on the other hand, uses global spherical centroid Voronoi tessellation (SCVT) to achieve local optimization with variable-resolution grids. While practical and promising, MPAS-A uses a constant global time step determined by the smallest grid cell, which limits resolution variability. Modeling even a small, high-resolution region of the entire Earth requires significant computational resources. ApplicationsLogistics, Shipping, and AviationWeather Forecasting (Sea, Land, and Air) and Optimization for RoutesPort Management OptimizationExtreme Weather Event ForecastingFuel Consumption ForecastingAir Quality Forecasting and AnalysisEnergyIndustrial Wind Farm Power Generation ForecastingHydropower Operation OptimizationSolar Power Generation ForecastingPower Demand ForecastingRevenue from Damage to Power Facilities Caused by Ice and Landslides 2. Product FeaturesThe first atmospheric observation platform based on the MPAS meteorological model and integrated with cloud computingCustomizable grid structureAutomatic improvement of terrain and coastline resolutionOptimized load balancing and excellent scalabilityScale-adaptive physicsSupport for geographic data of varying resolutionsAdvantages3. Improved Accuracy by Eliminating Lateral Boundary ConditionsCompared to WRF, CPAS does not require lateral boundary conditions. In WRF's dynamical downscaling, lateral boundary conditions are constrained by the global model, often limiting the synoptic-scale airflow in its regional model. Furthermore, regional models often suffer from differences in physical parameters between the global and regional models. Therefore, CPAS improves accuracy while providing significant flexibility in the evolution of the initial state. 4. Reduce Computational Costs and Improve EfficiencyCPAS automatically assigns the optimal time step based on resolution changes. This allows CPAS users to freely create grid configurations with widely varying resolutions, which is not possible in the official MPAS-A distribution. Hierarchical time steps allow this variable-resolution global model to be used as a regional model with multiple nested domains. Calculations can be focused on the user's area of interest. 5. Reduce Human Resources and Setup CostsNo software installation is required. Computational experiments are conducted in the cloud. CPAS will provide an easy-to-use visualization system and cloud-based result review capabilities. 6. What is the Chinese Academy of Sciences Atmospheric Quality Simulation Platform (OPER)? Based on the "Three Lines and One List" regional technical guidelines, the Chinese Academy of Sciences Atmospheric Environment Simulation Platform (OPER) utilizes core technologies such as an integrated regional meteorological transmission model, a source attribute diagnosis model, and an integrated user suggestion algorithm to comprehensively address regional scheduling issues, compliance gaps, and control measures, identifying key areas for atmospheric environmental protection and key control measures. OPER draws on advanced traditional high-level control models to provide a multi-layered and multi-level atmospheric environmental quality control solution. The OPER platform generates specialized, indicative data for environmental planning and decision-making departments, including environmental capacity, environmental quality assessments, and local planning measures (e.g., the "Three Lines and One List," historical and future re-measurements). This supports scientific pollution emergency response, facilitates PM2.5 and pollution source tracing and coordination in disaster-stricken areas, and meets environmental governance goals for both short-term emergency response and long-term compliance planning. 7. What is the Lianke Atmospheric Environmental Quality Simulation Platform (OPER)? The Lianke Atmospheric Environmental Quality Simulation Platform (OPER) is an online monitoring platform focused on improving regional air quality. Based on the "Three Lines and One List" technical guidelines, the platform integrates core technologies such as regional meteorological models, atmospheric chemical transport models, source apportionment diagnostic models, and comprehensive emission reduction recommendation algorithms. It helps users comprehensively determine regional allowable emissions of atmospheric pollutants, compliance gaps, and control measures, thereby identifying key areas and key control measures for atmospheric environmental protection. OPER revolutionizes the traditional total volume control model, enabling more precise quality and total volume control. The OPER platform generates professional, indicative data, such as atmospheric environmental capacity and environmental compliance assessment quality, providing a scientific basis for environmental planning and decision-making departments to formulate emission reduction measures (such as the "Three Lines and One Project" plan and historical and future severe pollution emergency response calculations). This effectively strengthens the source tracing and coordinated emission reduction of PM2.5 and ozone pollution, meeting the environmental governance goals of both short-term emergency response and long-term compliance planning. 8. Product FeaturesGIS Display of Atmospheric Pollution Sources and Emission Inventory ManagementEmission InventoryAutomatic Gridding and Display AnalysisAirQuality Baseline Simulation AnalysisRegional Source Tracing Simulation AnalysisAir QualityScenario Simulation AnalysisComprehensive Air Pollution Emission Reduction RecommendationsRefined Air Quality Analysis and ForecastOperational Forecast and Warning System*Refined to 1 km AdvantagesOnline operation, no installation requiredSaving users' time and costs for system installation, equipment procurement, and hardware and software operation and maintenance, effectively combining high-performance computing with cloud applications. The platform provides an interface for uploading pollution source emission inventories online for real-time viewing and calculation. Accurate and efficient algorithms It integrates advanced international numerical models such as SMOKE, MPAS, CPAS, WRF, CMAQ, and CAMx with independently developed technologies, integrating data assimilation, objective emission reduction recommendations and effectiveness assessment, and computational task workflow management. Customized Analysis Based on user needs, it conducts pollution source diagnosis and sensitivity analysis across time, space, industry, and precursors, assisting decision-making and customizing short-, medium-, and long-term compliance and control plans. The user-friendly online interactive environment facilitates analysis (automatically generating daily and heavy pollution reports) and emission reduction scenario simulation. Multi-Scenario Assessment It provides scenario assessments and comparisons of different emission reduction options for different pollution levels. Ex-ante assessments facilitate the development of scientifically sound control plans, while ex-post assessments quantitatively analyze the effectiveness of human and environmental interventions. The platform provides a customizable multi-scenario platform to support heavy pollution emergency response, compliance management, and coordinated emission reduction.
Author: Michael Cheung
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W7080227065
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