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Optimization of Regional Scale Numerical Weather Prediction & Air University of Texas at El Paso ScholarWorks@UTEP Open Access Theses & Dissertations 2020-01-01 Optimization Of Regional Scale Numerical Weather Prediction & Air Quality Model For The Paso Del Norte Region Suhail Mahmud University of Texas at El Paso Follow this and additional works at: https://scholarworks.utep.edu/open_etd Part of the Atmospheric Sciences Commons, and the Meteorology Commons Recommended Citation Mahmud, Suhail, "Optimization Of Regional Scale Numerical Weather Prediction & Air Quality Model For The Paso Del Norte Region" (2020). Open Access Theses & Dissertations. 3176. https://scholarworks.utep.edu/open_etd/3176 This is brought to you for free and open access by ScholarWorks@UTEP. It has been accepted for inclusion in Open Access Theses & Dissertations by an authorized administrator of ScholarWorks@UTEP. For more information, please contact [email protected]. OPTIMIZATION OF REGIONAL SCALE NUMERICAL WEATHER PREDICTION & AIR QUALITY MODEL FOR THE PASO DEL NORTE REGION SUHAIL MAHMUD Doctoral Program in Computational Science APPROVED: Rosa Fitzgerald, Ph.D., Chair Javier Polanco, Ph.D., Co-Chair Duanjun Lu, Ph.D. Rodrigo Romero, Ph.D. Stephen L. Crites, Jr., Ph.D. Dean of the Graduate School Copyright © by Suhail Mahmud 2020 Dedication My Parents, Family and Friends for all the unconditional love and support OPTIMIZATION OF REGIONAL SCALE NUMERICAL WEATHER PREDICTION & AIR QUALITY MODELS FOR PASO DEL NORTE REGION by SUHAIL MAHMUD DISSERTATION Presented to the Faculty of the Graduate School of The University of Texas at El Paso in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY Computational Science Program THE UNIVERSITY OF TEXAS AT EL PASO December 2020 Acknowledgements I want to offer my gratitude to the Almighty Allah, the most merciful for his kindness in giving me ability to complete my doctoral degree successfully. I also would like to express my deepest gratefulness to my doctoral advisor, Dr. Rosa Fitzgerald, Professor of the Computational Science Program & Physics Department at The University of Texas at El Paso. Her precision of vision, her proficiency in the subject, and her appreciative and helpfulness are truly inspiring to me. Aside from introducing me to fascinating ideas and teaching me techniques to make them precise, she has also assisted me to become an independent researcher. Her offer to collaborate on the research of Atmospheric Science has boosted my confidence, and her continuous support during that project has enabled me to thrive. I also wish to thank the other members of my dissertation committee, namely, Dr. Duanjun Lu (Jackson State University), Dr. Rodrigo Romero, and Dr. Javier Polanco, faculties of The University of Texas at El Paso. Their generous suggestions, comments, and guidance were invaluable to the completion of this work. I also want to thank Dr. Ming Ying Leung, the Director of Computational Science program for her assistance that helped me to successfully complete my Ph.D. dissertation. I am immensely grateful to my family members for their unfailing love and support. I would also like to express my gratitude to my teachers and friends from my high-school days in Bangladesh to my doctoral years in the City of El Paso, Texas, for their love and trust in me. Finally, to my wife, for her graceful support and motivation. v Abstract Improvement of the Accuracy and Forecast capability of the Numerical Weather Prediction (NWP) models and Air Quality Models (AQM) are critical issues in today’s scientific study of Meteorology and Air Pollution. The models for these predictions are dependent on topography, climate, initial and boundary conditions, domain size, and computational efficiency. Different techniques such as Data Assimilation, Ensemble Methods, Increased Computing Capacity to achieve higher model resolution, and Improved Physics Schemes can be used to address this problem. In this study, the NWP models, the Weather and Research Forecast (WRF), and the HYSPLIT models, were enhanced for the Paso Del Norte (PdN) region by applying these techniques. In addition, the CAMx model was refined and successfully implemented for this region. The PdN region comprises El Paso, TX, Ciudad Juarez, Mexico, and some neighboring cities in New Mexico, an ideal region to perform air quality studies. Several sources of experimental data, such as Radiosonde, Ozonesonde, Satellite-based sounder profile, Continuous Ambient Monitoring Stations (CAMS), and Ceilometer, were used in this study. Selecting the best Physics and Chemistry schemes for the models was also a challenging part of this study. Different data assimilation techniques like Incorporating Satellite observations from METOPS and NOAA- 18/19, METAR data, NWS data was another objective of this work. To validate the NWP models’ results for the PdN region, they were inter-compared with meteorological satellite data, ground stations, and radiosonde datasets. In this study, the ozone results from CAMx were extensively inter-compared with ozonesonde datasets. Meteorological variables such as temperature, pressure, relative humidity, wind speed, and ozone concentrations were also analyzed at several locations in vi the PdN region. Additionally, several other studies using statistical analysis and machine learning were performed to predict ground-level pollutant concentration. An in-depth sensitivity analysis of the planetary boundary layer using different meteorological schemes was also conducted. This improved the accuracy of the PBL retrieval for this region. Retrieval methods using observational data (Ceilometers, radiosonde), NWP models (WRF, HYSPLIT), and Satellite data (CALIPSO) were inter-compared for validation and calibration. vii Table of Contents Dedication ...................................................................................................................................... iii Acknowledgements ..........................................................................................................................v Abstract .......................................................................................................................................... vi Table of Contents ......................................................................................................................... viii List of Tables ................................................................................................................................ xii List of Figures .............................................................................................................................. xiv List of Illustrations ...................................................................................................................... xvii 1. Introduction .............................................................................................................................1 1.1 Motivation ......................................................................................................................4 1.2. Research Problem ............................................................................................................4 1.3. Objective and Scope: .......................................................................................................6 1.4. Organization of the dissertation .......................................................................................7 2. Literature Review.........................................................................................................................8 3. Data Background .......................................................................................................................19 3.1. Paso del Norte: ...............................................................................................................19 3.2. Ground Stations: ............................................................................................................21 3.3 Numerical Weather Prediction Models: ..........................................................................24 viii 3.3.1. Weather Research and Forecasting Model (WRF): ...........................................24 3.3.2. HYSPLIT Model ................................................................................................26 3.4 Air Quality Model: ..........................................................................................................29 3.4.1. CMAQ: ..............................................................................................................29 3.4.2. CAMx: ...............................................................................................................32 3.5 Radiosonde and Ozonesonde: .........................................................................................33 3.6 National Weather Service: ..............................................................................................35 3.7. Weather Satellite ............................................................................................................36 3.8. Instrumentation: .............................................................................................................39 3.8.1. Ceilometer ..........................................................................................................39 4. Methodology .........................................................................................................................42 4.1. Optimized performance of WRF on HPC cluster: .......................................................42
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