Numerical simulation of physical parameters in the atmosphere applying the WRF model to analyze the weather within Tiquipaya municipality (Bolivia).

Authors

  • Franz Pablo Antezana Lopez Universidad de Beihang
  • Giovana Silvia Cachaca Tapia Universidad Privada del Valle
  • Valeria Coral Rodríguez García Universidad Privada del Valle
  • Sergio Rodríguez Belmonte Universidad Privada del Valle

DOI:

https://doi.org/10.52428/20758944.v17i51.132

Keywords:

WRF, Numerical simulation, Atmosphere, Times series, Climate variables, Spatial analysis

Abstract

Behavior of natural phenomena will be studied through a numerical model, which will allow a weather forecast in its atmospheric variables for the near future. The meteorological variables analyzed were fourfold: wind behavior (speed and direction), radiation, humidity, and temperature. The development of the numerical model will help describe the behavior of a physical system based on mathematical equations that will describe the atmosphere's behavior.

 

The information to verify and adjust the numerical model was obtained from the in-situ station at Universidad Privada del Valle. A visual adjustment is made to the curves of the simulated climatological variables regarding the curves recorded for temperature, humidity, radiation, wind speed and direction, to evaluate the model effectiveness and reliability. The research concludes that the adjusted model is a tool that will allow a regressive analysis and short-term forecast of extreme climatological events that occur in the municipality of Tiquipaya. This procedure will serve as an early warning system for climatic factors.

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References

Anusha Sathyanadh, Thara V. Prabha, B. Balaji, E.A. Resmi, Anandakumar Karipot, Evaluation of WRF PBL parameterization schemes against direct observations during a dry event over the Ganges valley, Atmospheric Research, Volume 193, 2017, Pages 125-141, ISSN 0169-8095, https://doi.org/10.1016/j.atmosres.2017.02.016.

Casallas, A., Celis, N., Ferro, C., Barrera, E. L., Peña, C., Corredor, J., & Segura, M. B. (2020). Validation of PM10 and PM2.5 early alert in Bogotá, Colombia, through the modeling software WRF-CHEM. Environmental Science and Pollution Research, (27), 35930-35940. https://doi.org/10.1007/s11356-019-06997-9

Colin Cameron, A.; Windmeijer, Frank A.G.; Gramajo, H; Cane, DE; Khosla, C (1997). An R-squared measure of goodness of fit for some common nonlinear regression models. Journal of Econometrics 77 (2): páginas329-342.ISSN:0304-4076. https://doi.org/10.1016/S0304-4076(96)01818-0

Dudhia, J. and Wang, J. (2014) WRF Advanced Usage and Best Practices. 16th WRF Annual Workshop, Boulder, June 2014.

http://www2.mmm.ucar.edu/wrf/users/workshops/WS2014/ppts/best_prac_wrf.pdf

Duque Franco, Isabel, & Montoya Garay, Jhon Williams. (2021). Cambio climático y urbanización. Cuadernos de Geografía: Revista Colombiana de Geografía, 30(2), 274-279. Epub August 27, 2021. Retrieved December 03, 2021, from http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0121-215X2021000200274&lng=en&tlng=es.

Fernandez, L. & Labra, R. (2020). Estaciones meteorológicas: su importancia en la decisión de cuánto regar [Webinar]. Academia de riego KILIMO. https://academiaderiego.kilimoagtech.com/decargar-webinar-estaciones-meteorol%C3%B3gicas

García F., Willman, Delfín S., Mirko, Ledezma P., Mauricio, & Arévalo S., Boris. (2021). Integrando métodos de evaluación de riesgos de deslizamientos e inundaciones en cuencas del Tunari y zona de Alto Cochabamba. Acta Nova, 10(1), 61-95. Recuperado en 03 de diciembre de 2021, de http://www.scielo.org.bo/scielo.php?script=sci_arttext&pid=S1683-07892021000100005&lng=es&tlng=es.

Kadaverugu, R., Gurav, C., Rai, A. et al. Quantification of heat mitigation by urban green spaces using InVEST model—a scenario analysis of Nagpur City, India. Arab J Geosci 14, 82 (2021). https://doi.org/10.1007/s12517-020-06380-w.

Kadaverugu, R., Matli, C. & Biniwale, R. Suitability of WRF model for simulating meteorological variables in rural, semi-urban and urban environments of Central India. Meteorol Atmos Phys 133, 1379–1393 (2021). https://doi.org/10.1007/s00703-021-00816-y

Michalakes John, Loft Richard, Bourgeois A. (2002). Performance-Portability and The Weather Research and Forecast Model, website: https://www.researchgate.net/publication/2859247_Performance-Portability_And_The_Weather_Research_And_Forecast_Model

Moscoso-Vanegas, Diana Lucía, Vázquez-Freire, Verónica Eulalia, & Astudillo-Alemán, Ana Lucía. (2015). Modelamiento de la calidad del aire en la ciudad de Cuenca-Ecuador. Iteckne, 12(2), 188-197. Retrieved December 03, 2021, from http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S1692-17982015000200010&lng=en&tlng=es.

Peckham, S. E., Grell, G., McKeen, S. A., Ahmadov, R., Wong, K. Y., Barth, M., ... & Freitas, S. R. (2017), WRF-Chem version 3.8. 1 user's guide, NOAA Technical memorandum OAR GSD(48), http://doi.org/10.7289/V5/TM-OAR-GSD-48

Rahul Boadh, A.N.V. Satyanarayana, T.V.B.P.S. Rama Krishna, Srikanth Madala, Sensitivity of PBL schemes of the WRF-ARW model in simulating the boundary layer flow parameters for their application to air pollution dispersion modeling over a tropical station, Atmósfera, Volume 29, Issue 1, 2016, Pages 61-81, ISSN 0187-6236, https://doi.org/10.20937/ATM.2016.29.01.05.

Rutledge, G.K., J. Alpert, R. J. Stouffer and B. Lawrence, (2003), The NOAA National Operational Model Archive and Distribution System (NOMADS), Realizing TeraComputing: Proceedings of the Tenth ECMWF Workshop on the Use of High Performance Computing in Meteorology (November 2002), W. Zwieflhofer and N. Kreitz, Eds., World Scientific, pp. 106–129.

Verde, A. V., Rodríguez, R. C. C., & Rodríguez, A. R. (2015). Evaluación del pronóstico de viento del modelo Weather Research Forecast (WRF) en torres de prospección eólica. Revista Cubana de Meteorología, Volumen 21 Número 2, 16-28. ISSN: 266-4-0880. http://rcm.insmet.cu/index.php/rcm/article/view/410

Wang, W., Bruy`ere, C., Duda, M., Dudhia, J., Gill, D., Lin, H.-C., Michalakes, J., Rizvi, S., Zhang, X., Beezley, J. D., Coen,J. L., and Mandel, J.: ARW Version 3 Modeling System User’sGuide (2012). National Center of Atmospheric Research. Website: https://www.yumpu.com/en/document/read/6710200/wrf-arw-users-guide-mmm-ucar

WRF. (2017), de Centro de Ciencias de la Atmósfera, UNAM, website: http://grupo-ioa.atmosfera.unam.mx/pronosticos/index.php/meteorologia/inf-wrf

Published

10-12-2021

How to Cite

Antezana Lopez, F. P., Cachaca Tapia, G. S., Rodríguez García, V. C., & Rodríguez Belmonte, S. (2021). Numerical simulation of physical parameters in the atmosphere applying the WRF model to analyze the weather within Tiquipaya municipality (Bolivia) . Journal Boliviano De Ciencias, 17(51), 38–59. https://doi.org/10.52428/20758944.v17i51.132

Issue

Section

Scientific Paper

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