Sensitivity analysis of atmospheric phenomena models for precipitation assessment on the Paraíba do Sul River Watershed
DOI:
https://doi.org/10.5902/2179460X66757Keywords:
Atmospheric modeling system, Rainfall simulation, Convective Boundary Condition, Cloud microphysicsAbstract
This paper is aimed at performing a group of experiments to evaluate the sensitivity to cumulus and microphysics schemes, as represented in numerical simulations of the Weather Research and Forecasting (WRF) model. The convective schemes of Kain-Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell-Devenyi (GD), Grell-Freita (GF), Grell 3D (G3D), Tiedtke and New Tiedtke (NT) were tested in association with the microphysics schemes of Kessler, Purdue Lin, WSM3, WSM5, WSM6, ETA (Ferrier) and Goddard (totaling forty-nine experiments) in order to identify the combination which best represents the cumulative rainfall distribution in the Paraíba do Sul watershed. In order to evaluate the best performance experiments, they were submitted to statistical tests of bias (BIAS), root mean square error (RMSE), absolute mean error (MAE) and Coefficient of Determination (R2). Results show that combinations WSM5 and GD; Goddard and G3D; Perdue Lin and G3D; WSM5 and G3D form a group of four physical configurations statistically similar and able to predict well the mean rainfall in the Paraiba do Sul watershed. It was noticed also that the cumulus scheme has a greater weight than microphysics in rainfall simulations being GD3 the best performing.
Downloads
References
AVOLIO, E.; STEFANO, F. WRF simulations for a heavy rainfall event in southern Italy: Verification and sensitivity tests. Atmospheric Research, [s.l.], v. 209, p. 14-35, 2018.
BENDER, F. D. Checking Sao Paulo weather forecast with WRF operating model. 2012. 164p. Atmospheric Sciences Mastership Thesis – Instituto de Astronomia, Geofísica e Ciências Atmosféricas da Universidade de São Paulo: USP. (in Portuguese).
CALADO, R. N.; DERECZYNSKI, C. P.; CHOU, S. C.; SUEIRO, G.; MOURA, J. D. O.; RANDER, V.; BRASILIENSE, C. S. Eta-5km Model Simulation Performance Assessment for the Heavy Rainfall Case in the Paraíba do Sul River Basin in January 2000. Revista brasileira de meteorologia, [s.l.], v. 33, p. 83-96, 2018.
CEIVAP, 2019. Geoenvironmental Data. Available in: www.ceivap.org.br/dados-gerais.php. Access in: June 26th, 2019.
CHEN, S. H.; SUN, W. Y. A one-dimensional time dependent cloud model. J. Meteor. Soc. Japan, [s.l.], v. 80, p. 99–118, 2002.
COMIN, A.; JUSTINO, F.; PEZZI, L.; GURJÃO, C. D. S.; SHUMACHER, V.; FERNAÁNDEZ, A.; SUTIL. U. A. Extreme rainfall event in the Northeast coast of Brazil: a numerical sensitivity study, Meteorology and Atmospheric Physics, v. 133, p. 141–162, 2020.
CONRAD, O. 2015. Module Simple Kriging. SAGA-GIS Module Library Documentation (v2.2.1). http://www.saga-gis.org/saga_tool_doc/2.2.1/statistics_kriging_1.html. Access in June 06th, 2020.
DI, Z.; DUAN, Q.; GONG, W.; WANG, C.; GAN, Y.; QUAN, J.; LI, J.; MIAO, C.; YE, A.; TONG, C. Assessing WRF model parameter sensitivity: A case study with 5-day summer precipitation forecasting in the Greater Beijing Area. Geophysical Research Letters, [s.l.], v. 42, n. 2, p. 579-587, 2015.
DUDHIA, J. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., [s.l.], v. 46, p. 3077–3107, 1989.
FERREIRA, P.; CASTANHEIRA, J. M.; ROCHA, A.; FERREIRA, J. 2008. Sensitivity study of surface forecasts in Portugal, by WRF, in view of the variation of physical parameters. XXX Jornadas Científicas de la Associación Meteorológica Española, Zaragoza. (in Portuguese).
GRELL, G. A. Prognostic Evaluation of Assumptions Used by Cumulus Parameterizations. Mon. Wea. Rev., [s.l.], v. 121, p. 764–787, 1993.
GRELL, G. A.; FREITAS, S. R. A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling, Atmos. Chem. Phys., [s.l.], v. 14, p. 5233-5250, 2014.
GRELL, G. A.; DEVENYI, D. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., [s.l.], v. 29, 1693, 2002.
GUNWANI, P.; MOHAN, M. Sensitivity of WRF model estimates to various PBL parameterizations in different climatic zones over India. Atmospheric research, [s.l.], v. 194, p. 43-65, 2017.
HONG S. Y.; DUDHIA, J.; CHEN S. H. A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Wea Rev, [s.l.], v. 132, p. 103–120, 2004.
HONG, S-Y; LIM, J-O. J. The WRF single-moment 6-class microphysics scheme (WSM6). Asia-Pacific Journal of Atmospheric Sciences, [s.l.], v. 42, n. 2, p. 129-151, 2006.
INPE. Information on monthly and seasonal climate monitoring products for rains in Brazil on the CPTEC / INPE page. 2014. (in Portuguese). Available in: <http://clima.cptec.inpe.br/~rclima1/pdf/Documento_produto_indice.pdf>. Access in: May 25th, 2020.
JANJIC, Z. I. The Step–Mountain Eta Coordinate Model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., [s.l.], v. 122, p. 927–945, 1994.
KAIN, J. S. The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., [s.l.], v. 43, p. 170–181, 2004.
KESSLER E. 1969. On the Distribution and Continuity of Water Substance in Atmospheric Circulations. In: On the Distribution and Continuity of Water Substance in Atmospheric Circulations. Meteorological Monographs, v. 10. American Meteorological Society, Boston, MA.
LIU, D.; YANG, B.; ZHANG, Y.; QIAN, Y.; HUANG, A.; ZHOU, Y.; ZHANG, L. Combined impacts of convection and microphysics parameterizations on the simulations of precipitation and cloud properties over Asia. Atmospheric research, [s.l.], v. 212, p. 172-185, 2018.
MAYOR, Y. G.; MESQUITA M. D. S. Numerical Simulations of the 1 May 2012 Deep Convection Event over Cuba: Sensitivity to Cumulus and Microphysical Schemes in a High-Resolution Model, Advances in Meteorology, v. 2015. Article ID 973151, p. 16, 2015.
MESQUITA, M. D. S. 2019. A Bayesian approach for evaluating regional climate models. 2012. Available in: https://statmos.washington.edu/cbms/mesquita_Poster.pdf. Access in: August 5th, 2019.
MEYER, D.; RIECHERT, M. Open source QGIS toolkit for the Advanced Research WRF modelling system. Environmental Modelling & Software, [s.l.], v. 112, p. 166–178, 2019.
MOHAN, P. R.; SRINIVAS, C. V.; YESUBABU, V.; BASKARAN, R.; VENKATRAMAN, B. Simulation of a heavy rainfall event over Chennai in Southeast India using WRF: Sensitivity to microphysics parameterization. Atmospheric Research, [s.l.], v. 210, p. 83-99, 2018. https://doi.org/10.1016/j.atmosres.2018.04.005.
PADILHA, S. F. 2011. Heavy rain event simulations in the state of Rio de Janeiro using the WRF model. 127p. Meteorology Mastership Thesis – Instituto de Geociências do Centro de Ciências Matemáticas e da Natureza: UERJ. (in Portuguese).
PATEL, P., GHOSH, S., KAGINALKAR, A., ISLAM, S., & KARMAKAR, S. Performance evaluation of WRF for extreme flood forecasts in a coastal urban environment. Atmospheric Research, [s.l.], v. 223, p. 39-48, 2019.
QGIS. Web: http://www.qgis.org/en/site/forusers/download.html. Access in May 30th, 2019.
RODRÍGUEZ, L. G.; ANABOR, V.; PUHALES, F. S.; PIVA, E. D. Estimation of the probability of precipitation from nonparametric statistical techniques applied to numerical WRF simulations: a case study. Ciência e Natura, Santa Maria, v. 38, p. 491-497, 2016.
ROGERS, E.; BLACK, T.; FERRIER, B.; LIN, Y.; PARRISH, D.; DI MEGO, G. 2001. Changes to the NCEP Meso Eta Analysis and Forecast System: Increase in resolution, new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis. NWS Technical Procedures Bulletin at http://www.emc.ncep.noaa.gov/mmb/mmbpll/e ta12tpb/
R-PROJECT. Web: https://cran.r-project.org/src/base/R-3/. Access in September 10th, 2019.
SILVA, F. P.; ROTUNNO FILHO, O. C. SAMPAIO, R. J.; DRAGAUD, I. C. D. V; ARAÚJO, A. A. M.; SILVA, M. G. A. J; PIRES, J. D. 2017. Evaluation of atmospheric thermodynamics and dynamics during heavy-rainfall and no-rainfall events in the metropolitan area of Rio de Janeiro, Brazil. Meteorology and Atmospheric Physics, p. 1-13.
SILVA, F. P.; SILVA, M. G. A. J, MENEZES, W. F.; ALMEIDA, V. A. Evaluation of Atmospheric Indicators Using the WRF Numerical Model in Rain Events in Rio de Janeiro City. Anuário do Instituto de Geociências, v. 38, n. 2, p. 81-90, 2016.
SIMPSON, J.; KUMMEROW, C.; TAO W-K.; ADLER, R. F. On the tropical rainfall measuring mission (TRMM). Meteorol Atmos Phys, [s.l.], v. 60, p. 19–36, 1996.
SKAMAROCK, W.; KLEMP, J.; DUDHIA, J.; Gill, D.; BARKER, D.; DUDA, M.; HUANG, X.; WANG, W.; POWERS, J. 2019. A Description of the Advanced Research WRF Model Version 4. NCAR Technical Note NCAR/TN-556+STR, 145 pp. doi:10.5065/1dfh-6p97.
SOUZA, C. V. F.; RANGEL, R. H. O.; CATALDI, M. Numerical Assessment of the Influence of Urbanization on the Convection Regime and Precipitation Patterns of the São Paulo Metropolitan Region. Revista Brasileira de Meteorologia, [s.l.], v. 32, n. 4, p. 495-508, 2017.
TAO, W. K.; SIMPSON, J.; MCCUMBER, M. An ice-Water Saturation Adjustment. Monthly Weather Reviews, [s.l.], v. 117, p. 231–235, 1989.
TIEDTKE, M. A comprehensive mass flux scheme for cumulus parameterization in large–scale models. Mon. Wea. Rev., [s.l.], v. 117, p. 1779–1800, 1989.
VERDIN, A.; FUNK, C.; RAJAGOPALAN, B.; KLEIBER, W. Kriging and Local Polynomial Methods for Blending Satellite-Derived and Gauge Precipitation Estimates to Support Hydrologic Early Warning Systems. IEEE Transactions on Geoscience and Remote Sensing, v. 54, n. 5, p. 2552-2562, 2016. DOI: 10.1109/TGRS.2015.2502956.
WANG, W.; BRUYERE, C.; DUDA, M.; DUDHIA, J.; GILL, D.; LIN, H. C.; MICHALAKES, J.; RIZVI, S.; ZHANG, X.; BEEZLEY, J. D.; COEN, J. L.; KAVULICH, M.; WERNER, K.; CHEN, M.; BERNER, J.; MUNOZ-ESPARZA, D.; REEN, B.; FOSSEL, K.; MANDEL, J. 2019. ARW Version 4 Modeling System User’s Guide, Mesoscale & Microscale Meteorology Division, National Center for Atmospheric Research.
WARNER, Thomas Tomkins. Numerical weather and climate prediction. Cambridge University Press, 2010.
WRF Modeling System Download. Web: http://www2.mmm.ucar.edu/wrf/users/download/get_source.html. Access in September 14th, 2019.
YANG, Q.; DAI, Q.; HAN, D.; CHEN, Y.; ZHANGA, S. Sensitivity analysis of raindrop size distribution parameterizations in WRF rainfall simulation. Atmospheric Research, [s.l.], v. 228, p. 1-13, 2019. https://doi.org/10.1016/j.atmosres.2019.05.019.
ZHANG, C.; WANG, Y. and HAMILTON, K. Improved representation of boundary layer clouds over the southeast pacific in ARW–WRF using a modified Tiedtke cumulus parameterization scheme. Mon. Wea. Rev., [s.l.], v. 139, p. 3489–3513, 2011.
ZHANG, C.; WANG, Y. Futuras Mudanças Projetadas da Atividade de Ciclones Tropicais sobre o Norte do Norte e Pacífico Sul em um Modelo Climático Regional de 20 km de Malha. J. Climate, [s.l.], v. 30, p. 5923-5941, 2017.
Published
Versions
- 2022-12-06 (2)
- 2022-12-01 (1)
How to Cite
Issue
Section
License
Copyright (c) 2021 Ciência e Natura
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
To access the DECLARATION AND TRANSFER OF COPYRIGHT AUTHOR’S DECLARATION AND COPYRIGHT LICENSE click here.
Ethical Guidelines for Journal Publication
The Ciência e Natura journal is committed to ensuring ethics in publication and quality of articles.
Conformance to standards of ethical behavior is therefore expected of all parties involved: Authors, Editors, Reviewers, and the Publisher.
In particular,
Authors: Authors should present an objective discussion of the significance of research work as well as sufficient detail and references to permit others to replicate the experiments. Fraudulent or knowingly inaccurate statements constitute unethical behavior and are unacceptable. Review Articles should also be objective, comprehensive, and accurate accounts of the state of the art. The Authors should ensure that their work is entirely original works, and if the work and/or words of others have been used, this has been appropriately acknowledged. Plagiarism in all its forms constitutes unethical publishing behavior and is unacceptable. Submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behavior and is unacceptable. Authors should not submit articles describing essentially the same research to more than one journal. The corresponding Author should ensure that there is a full consensus of all Co-authors in approving the final version of the paper and its submission for publication.
Editors: Editors should evaluate manuscripts exclusively on the basis of their academic merit. An Editor must not use unpublished information in the editor's own research without the express written consent of the Author. Editors should take reasonable responsive measures when ethical complaints have been presented concerning a submitted manuscript or published paper.
Reviewers: Any manuscripts received for review must be treated as confidential documents. Privileged information or ideas obtained through peer review must be kept confidential and not used for personal advantage. Reviewers should be conducted objectively, and observations should be formulated clearly with supporting arguments, so that Authors can use them for improving the paper. Any selected Reviewer who feels unqualified to review the research reported in a manuscript or knows that its prompt review will be impossible should notify the Editor and excuse himself from the review process. Reviewers should not consider manuscripts in which they have conflicts of interest resulting from competitive, collaborative, or other relationships or connections with any of the authors, companies, or institutions connected to the papers.