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《水信息学和数值天气预报在实时洪水预报中的应用进展英文版》可供水利工程、气象科学、防灾减灾工程、环境科学、地球科学等专业科研人员、工程技术人员、管理人员、研究生参考。
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《水信息学和数值天气预报在实时洪水预报中的应用进展英文版》针对洪水预报的预见期短、预报精度低等问题，介绍了解决方案即构建基于数据同化技术的陆气耦合实时洪水预报系统所涉及的关键技术问题，包括中尺度数值大气模式的降雨预报、数据同化技术与同化方案、流域水文模型及实时校正方法及构建陆气耦合洪水预报系统等，《水信息学和数值天气预报在实时洪水预报中的应用进展英文版》探索了利用气象与水文的跨学科交叉优势，在中尺度WRF模式与流域水文模型的耦合过程中，实现基于变分同化技术的数据同化方案，开发了一套完整的基于数据同化的陆气耦合实时预报技术体系，以提高WRF模式的降雨预报精度，延长洪水预报的预见期。研究成果对提高我国实时洪水预报水平，并可为我国洪水风险管理和防洪减灾提供重要的理论和技术支撑。
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| 目錄：
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PART I Introduction and the study site
Chapter 1 Introduction
1.1 Background and motivation
1.2 Scope and aim of the book
1.3 Layout and structure
Chapter 2 Study site and data sources
2.1 The Brue catchment
2.2 The HYREX experiment
2.3 Weather radar and rain gauge network
2.4 Input to the mesoscale NWP model
2.5 Data utilisation and treatment of invalid data in the book
PART II Data mining issues for rainfall-runoff modelling
Chapter 3 Calibration data selection of the rainfall-runoff model
3.1 Introduction
3.2 Probability Distributed Model
3.3 Spectral analysis methods and the ICF index
3.4 Calibration methods and scenario design
3.5 Model performances of different calibration scenarios
3.6 Similarity between the calibration and validation data
3.7 Conclusions
Chapter 4 Optimal data time interval for real-time flood forecasting
4. 1 Introduction
4.2 Observed rainfall-runoff data with different time intervals
4.3 Real-time updating scheme: the ARMA model
4.4 Impact of time interval on real-time flood forecasting by case studies
4.5 Hypothetical pattern for the selection of the optimal time interval
4. 6 Conclusions
PART III Rainfall prediction using the mesoscale NWP model
Chapter 5 Numerical weather prediction and the WRF model
5. 1 Introduction
5.2 The development of numerical weather prediction
5.3 Principles and functions of the NWP model
5.4 The mesoscale NWP model
5.5 Weather Research and Forecasting model
5.6 Conclusions
Chapter 6 Sensitivity of the WRF model to domain configurations and storm types
6.1 Introduction
6.2 WRF configuration and verification
6.3 Data and experiment design
6.4 Sensitivity of the WRF model in rainfall simulation
6.5 Uncertainties in the sensitivity analyses
6.6 Conclusions
Chapter 7 Variational data assimilation system for the WRF model
7. I Introduction
7.2 Principles of the variational data assimilation system for WRF
7.3 Observation pre-proeessing OBSPROC
7.4 Running WRF-3DVar in cold-start and cycling mode
7.5 Updating WRF boundary, conditions WRFBC
7.6 Generating background error GENBE
7.7 Assimilating weather radar data
7.8 Conclusions
Chapter 8 Rainfall forecasting with data assimilation by WRF-3DVar
8.1 Purpose
8.2 ECMWF forecast products, stoma events and WRF configurations
8.3 Observational data assimilated by WRF-3DVar
8.4 Rainfall forecasting results for 24h storm events of four types
8.5 Quantification of errors of using 24h rainfall accumulations
8.6 Limitations of the radar correction ratio
8.7 Conclusions
PART IV The Integrated real-time flood forecasting system and conclusions
Chapter 9 Real-time flood forecasting using the WRF forecasted rainfall
9.1 Introduction
9.2 Real-time forecasting system by integrating WRF, PDM and ARMA
9.3 Forecast design and system identification
9.4 Performance testing of the real-time forecasting system
9.5 Evaluation of the WRF forecasted rainfall for flood forecasting
9.6 Conclusions
Chapter 10 Conclusions and recommendations
10.1 Conclusions
10.2 Limitations and recommendations for future work
References
Appendix
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