当前位置:网站首页>Simulation of Future Air Pollution Changes Based on Global Model Comparison Program CMIP6 and Regional Climate-Chemistry Coupling Model WRF-Chem
Simulation of Future Air Pollution Changes Based on Global Model Comparison Program CMIP6 and Regional Climate-Chemistry Coupling Model WRF-Chem
2022-07-30 07:08:00 【WangYan2022】
The national carbon peak carbon neutrality (double carbon) goal puts forward new requirements for future air pollution control, and also puts forward uncertainties for the simulation and prediction of the evolution trend and spatial pattern of the atmospheric environment under the background of future climate changesex and challenges.Based on different shared socioeconomic pathways (SSPs) and the latest anthropogenic emission trends, the Sixth International Coupling Model Intercomparison Project (CMIP6) projected future climate change trends under different social sharing pathways and GHG emission scenarios. These results are as follows:It is possible to simulate and predict the evolution trend of air pollution under the background of future climate change.
Dynamic downscaling of the projected global climate data from the Model Comparison Program, combined with projected future climate change, using regional climate models and coupled climate-chemical models to predict and simulate the temporal and spatial evolution of air pollution in the future.The model comparison plan involves format conversion and downscaling of data, and regional models involve complex dynamic and chemical processes, which are difficult in data utilization and model operation.
Lecture/On MachineCMIP6 Data and Operation Platform Construction
1. CMIP Model Comparison Program Introduction: Background, Meaning, Scenario Explanation

2. CMIP data download method

3. Data format explanation and practice (NETCDF)

4. Explanation and practice of data conversion tools (CDO/NCO)

5. Installation of virtual machines and related software libraries

Lecture/Lab CMIP6 data-driven WRF and WRF-Chem modes
1.WRF data format explanation

2.CMIP6 scenario data is used to provide meteorological driving field code interpretation in WRF-Chem model

3. Explanation of future scenario emission inventory (SSP, DPEC)

4. Data processing practice
Lecture/On-board Future Scenario Simulation of WRF-Chem
1. Based on CMIP6 and future scenario emission inventory,Driving WRF-Chem Model
2. Initial Boundary Conditions
3. Explanation of Simulation Experiment Ideas:
1) Impact Trend of Climate Change and Emission Change on Future Air Pollution
2) Pollution-Meteorological Interaction
Lecture/On-board Q&A
1. Data acquisition and processing
2. Mode setting
3. Other problems
Recommended models for atmospheric science and air pollution:
●[Tutorial] Calpuff Model of Air Pollution Diffusion
●[Tutorial] A full set of regional high-precision geoscience simulation WRF meteorological modeling, multi-case application and exquisite mapping
●[Tutorial] SMOKE model emission inventory processing technology and practical application method in multi-mode and VOCs emission accounting
●【Tutorial】Application and Improvement of Air Quality Prediction Model System (CMAQ) and Practical Techniques for Establishment of Pollutant Emission Inventory
●【Tutorial】Pretreatment, Operation and Practical Application of WRF-Hydro Coupling Model of Meteorology and Hydrology
●【Tutorial】RegionApplication of Meteorology-Atmospheric Chemistry Online Coupling Model (WRF/Chem) in Atmospheric Environment
●【Tutorial】Practical Technical Application of CLM Land Surface Process Model
●【Tutorial】Practical Technical Application of NCL Data Analysis and Processing
●【Tutorial】Practical technical application of PMF source analysis of atmospheric particulate matter
●【Tutorial】EKMA curve and atmospheric O3 source analysis
●【Tutorial】Practical technical application of CMIP6 data processing
●【Tutorial】WRF DA dataAssimilation System Theory, Operation and Variation, Hybrid Assimilation New Method Technical Application
●【Tutorial】Practical Technical Application of Python Artificial Intelligence in Meteorology
●【Tutorial】R Language in Meteorology, Hydrology Data Processing and ApplicationResult analysis, drawing practice technology application
●【Tutorial】Air quality simulation and pollution source analysis technology and case study based on CAMx
●【Tutorial】MCM box model modeling method and practical application of atmospheric O3 source analysis
br> ●【Tutorial】The application of Python in the automatic operation and pre-processing of WRF model
边栏推荐
- 常用损失函数(一):Focal Loss
- 第一个WebAssembly程序
- SQL Server安装教程
- MySQL achievement method 】 【 5 words, single table SQL queries
- Flink CDC implements Postgres to MySQL streaming processing transmission case
- Using PyQt5 to add an interface to YoloV5 (1)
- 生产力工具分享——简洁而不简单
- Using custom annotations, statistical method execution time
- 线程的5种状态
- C语言学习经验
猜你喜欢

Invalid bound statement (not found)出现的原因和解决方法

Detailed explanation of regular expression syntax and practical examples

protobuf编码及网络通信应用(一)

Mycat2.0 build tutorial

MySQL - 函数及约束命令

sql中 exists的用法

CLUE模型构建方法、模型验证及土地利用变化情景预测

sqli-labs shooting range SQL injection learning Less-1

Flink CDC implements Postgres to MySQL streaming processing transmission case

建造者模式(Swift 实现)
随机推荐
TDengine集群搭建
CLUE模型构建方法、模型验证及土地利用变化情景预测
十六、Kotlin进阶学习:协程详细学习。
MySQL - Function and Constraint Commands
Using custom annotations, statistical method execution time
基于PyTorch深度学习无人机遥感影像目标检测、地物分类及语义分割
根据ip地址获取地理位置及坐标(离线方式)
[Getting C language from zero basis - navigation summary]
基于全球模式比较计划CMIP6与区域气候-化学耦合模式 WRF-Chem 的未来大气污染变化模拟
Flink CDC implements Postgres to MySQL streaming processing transmission case
“R语言+遥感”的水环境综合评价方法
十五、Kotlin进阶学习:一、子类与子类型;二、协变;三、逆变;
Xcode 建立 UIKit 项目(Hello World)
原型模式(Prototype):Swift 实现
TDengineGUI无法连接TDengine
Detailed explanation of regular expression syntax and practical examples
Arthas command parsing (watch/tt/sc)
MySQL index optimization and failure scenarios
Go简单实现协程池
[MATLAB] Image Processing - Recognition of Traffic Signs