Abstract
This work presents a contribution to regional climate modeling studies with emphasis on seasonal variability of precipitation in the Amazon Basin (AMZ) and Northeast region of Brazil (NEB). In this sense, the present study aimed to analyze the sensitivity of the simulations carried out for the period 2001 to 2005 (5 years), using two different Planetary Boundary Layer parameterization schemes (Holtslag and UW-PBL) available in the regional climate model version 4 (RegCM4). As initial and large-scale boundary conditions, ERA15 reanalyses were used. Data from the Climate Prediction Center morphing technique (CMORPH) were used for the precipitation assessment. Statistical metrics were used to evaluate the simulations. The dominant feature in RegCM4 simulations is a dry bias with the largest average value (~ 6.0 mm d−1) in part of AMZ Basin, while the lowest mean bias precipitation (~ 1.0 mm d−1), mainly located in NEB region. It was found that both experiments are able to adequately represent the pattern of annual cycle of precipitation when compared to the CMORPH. The UW-PBL scheme experiment had the best performance in the northern sector of AMZ Basin in the austral summer season, with the highest correlation value (~ 0.6). Both experiments showed persistent dry bias in the southern sector of the AMZ Basin during the austral summer season. The Holtslag scheme experiment showed greater ability to reproduce climate variability in the NEB region, especially during austral winter season, with the highest correlation value (~ 0.8). This study can help RegCM users in choosing the suitable configuration of their experiments. In general, the results show that precipitation is better simulated by the Reg_UW-PBL experiment in part of AMZ Basin, while the Reg_Holtslag experiment has better performance in representing the precipitation in the NEB region.
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References
Biudes, M. S., Campelo Júnior, J. H., Nogueira, J. D. S., & Sanches, L. (2009). Estimativa do balanço de energia em cambarazal e pastagem no norte do Pantanal pelo método da razão de Bowen. Revista Brasileira De Meteorologia, 24, 56–64. https://doi.org/10.1590/S0102-77862009000200003
Bretherton, C. S., Mccaa, J. R., & Grenier, H. (2004). A New parameterization for shallow cumulus convection and its application to marine subtropical cloud-topped boundary layers description and 1d results. Month Weat Rev., 132(4), 864–882.
Cavalcanti, I. F. A., Ferreira, N. J., Justi Da Silva, M. G. A., & Silva Dias, M. A. F. (2009). (Eds) Tempo e clima no Brasil. Oficina de Textos, São Paulo, Brasil.
Ceccherini, G., Ameztoy, I., Hernández, C. P. R., & Moreno, C. C. (2015). High-resolution precipitation datasets in south america and west africa based on satellite-derived rainfall, enhanced vegetation index and digital elevation model. Remote Sensing, 7, 6454–6488. https://doi.org/10.3390/rs70506454
Coppola, E., Stocchi, P., Pichelli, E., Torres Alavez, J. A., Glazer, R., Giuliani, G., Di Sante, F., Nogherotto, R., & Giorgi, F. (2021). Non-Hydrostatic RegCM4 (RegCM4-NH): Model description and case studies over multiple domains. Geosci Model Develop Discuss. https://doi.org/10.5194/gmd-2020-435
Dee, D. P., Uppala, S. M., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M., Balsamo, G., & Bauer, D. P. (2011). The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quarter Journal Royal Meteorology Society, 137, 553–597. https://doi.org/10.1002/qj.828
Dickinson, R. E., Henderson-Sellers, A., & Kennedy, P. J. (1993). Biosphere-atmosphere transfer scheme (BATS) version 1E as coupled to the NCAR community climate model boulder Colorado. NCAR Tech Rep, 72, 387.
Elguindi, N., Giorgi, F., Nagarajan, B., Pal, J., Solmon, F., Rauscher, S., Zakey, A., Brien, T., Nogherotto, R., & Giuliani, G. (2014). Regional climate model RegCM user manual version 46. The Abdus Salam International Centre for Theoretical Physics Trieste Italy, 21, 54.
Emanuel, K. A. (1991). A scheme for representing cumulus convection in large-scale models. Journal of Atmospheric Science, 48(21), 2313–2335. https://doi.org/10.1175/1520-0469(1991)048%3c2313:ASFRCC%3e2.0.CO;2
Gasparetto, P. (2011). Relações entre a altura média da camada limite planetária e as condições de instabilidade atmosférica na região metropolitana de Fortaleza - Ceará. 68p. Monografia (Graduação) Curso de Física, Universidade Estadual do Ceará, Fortaleza.
Giorgi, F., & Anyah, R. O. (2012). The Road Towards RegCM4. Climate Research, 52, 3–6. https://doi.org/10.3354/cr01089
Giorgi, F., Coppola, E., Solmon, F., Mariotti, L., Sylla, M. B., Bi, X., Elguindi, N., Diro, T. G., Nair, V., Giuliani, G., Turuncoglu, U., Cozzini, S., Güttler, I., O’Brien, T. A., Tawfik, A. B., Shalaby, A., Zakey, A. S., Steiner, A. L., Stordal, F., … Brankovic, C. (2012). RegCM4: Model description and preliminary tests over multiple CORDEX domains. Climate Research, 52, 7–29. https://doi.org/10.3354/cr01018
Giorgi, F., & Mearns, L. O. (1999). Introduction to special section: regional climate modeling revisited. Journal of Geophysical Research, 104(D6), 6335–6352. https://doi.org/10.1029/98JD02072
Gomes, H. B., Ambrizzi, T., & Silva, D. A. (2019). Climatology of easterly wave disturbances over the tropical South Atlantic. Climate Dynamics, 53, 1393–1411. https://doi.org/10.1007/s00382-019-04667-7
Grenier, H., & Bretherton, C. S. (2011). A moist PBL parameterization for large-scale models and its application to subtropical cloudtopped marine boundary layers. Monthly Weather Review, 129(3), 357–377. https://doi.org/10.1175/1520-0493(2001)129%3c0357:AMPPFL%3e2.0.CO;2
Gutierrez, C. B. B., de Souza, E. B., & Gutierrez, D. M. G. (2022). Global/regional impacts on present and near-future climate regimes in the metropolitan region of Belém. Eastern Amazon. Atmosphere, 13(7), 1077. https://doi.org/10.3390/atmos13071077
Güttler, I., Branković, Č, O’Brien, T. A., Coppola, E., Grisogono, B., & Giorgi, F. (2014). Sensitivity of the regional climate model RegCM4.2 to planetary boundary layer parameterisation. Climate Dynamics, 43, 1753–1772. https://doi.org/10.1007/s00382-013-2003-6
Hastenrath, S. (2012). Exploring the climate problems of Brazil’s Nordeste: A review. Climatic Change, 112, 243–251. https://doi.org/10.1007/s10584-011-0227-1
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., & Simmons, A. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146, 1999–2049. https://doi.org/10.1002/qj.3803
Holtslag, A., De Bruijn, E. I. F., & Pan, H. L. (1990). A high resolution air mass transformation model for short-range weather forecasting. Monthly Weather Review, 118, 1561–1575. https://doi.org/10.1175/1520-0493(1990)118%3c1561:AHRAMT%3e2.0.CO;2
Joyce, R. J., Janowiak, J. E., Arkin, P. A., & Xie, P. (2004). CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. Journal of Hydrometeorology, 5, 487–503. https://doi.org/10.1175/1525-7541(2004)005%3c0487:CAMTPG%3e2.0.CO;2
Kalmár, T., Pieczka, I., & Pongrácz, R. (2021). A sensitivity analysis of the different setups of the RegCM4. 5 model for the Carpathian region. International Journal of Climatology, 41, E1180–E1201. https://doi.org/10.1002/joc.6761
Khayatianyazdi, F., Kamali, G., Mirrokni, S. M., & Memarian, M. H. (2021). Sensitivity evaluation of the different physical parameterizations schemes in regional climate model RegCM45 for simulation of air temperature and precipitation over North and West of Iran. Dynamics of Atmospheres and Oceans. https://doi.org/10.1016/j.dynatmoce.2020.101199
Kiehl, J. T., Hack, J. J., Bonan, G. B., Boville, B. A., Williamson, D. L., & Rasch, P. J. (1998). The national center for atmospheric research community climate model: CCM3. Journal of Climate, 11, 1131–1149. https://doi.org/10.1175/1520-442(1998)011%3c1131:TNCFAR%3e2.0.CO;2
Llopart, M. P., Reboita, M. S., & Da Rocha, R. P. (2019). Assessment of multimodel climate projections of water resources over South America CORDEX domain. Climate Dynamics, 54, 99–116. https://doi.org/10.1007/s00382-019-04990-z
Marengo, J. A., Nobre, C., Tomasella, J., Oyama, M., Oliveira, G. S., Oliveira, R., Camargo, H., Alves, L. M., & Brown, I. F. (2008). The drought of Amazonia in 2005. Journal of Climate, 21, 495–516. https://doi.org/10.1175/2007JCLI1600.1
Marengo, J., Tomasella, J., Alves, L., Soares, W., & Rodriguez, D. (2011). The drought of 2010 in the context of historical droughts in the Amazon region. Geophysical Research Letters, 38, 1–5. https://doi.org/10.1029/2011GL047436
Marengo, J. A., Torres, R. R., & Alves, L. M. (2017). Drought in Northeast Brazil - past, present, and future. Theoretical and Applied Climatology, 129(3), 1189–1200. https://doi.org/10.1007/s00704-016-1840-8
Maurya, R. K. S., Sinha, P., Mohanty, M. R., & Mohanty, U. C. (2018). RegCM4 model sensitivity to horizontal resolution and domain size in simulating the Indian summer monsoon. Atmospheric Research, 210, 15–33. https://doi.org/10.1016/j.atmosres.2018.04.010
Moreira, G. A. (2013). Métodos para obtenção da altura da camada limite planetária a partir de dados de lidar. Dissertação (Mestrado)-Curso de Tecnologia Nuclear - Materiais, Universidade de São Paulo, São Paulo
Muller, C., & Moura, A. B. D. (2005). Modelagem da dispersão atmosférica a partir da teoria k: comparação entre difusividades. Revista Liberato., 6, 443.
O’Brien, T. A., Chuang, P. Y., Sloan, L. C., Faloona, I. C., & Rossiter, D. L. (2012). Coupling a new turbulence parametrization to RegCM adds realistic stratocumulus clouds. Geoscientific Model Development, 5, 989–1008. https://doi.org/10.5194/gmd-5-989-2012
Oliveira, P. T., Silva, C. M. S., & Lima, K. C. (2017). Climatology and trend analysis of extreme precipitation in subregions of Northeast Brazil. Theoretical and Applied of Climatology, 130, 77–79. https://doi.org/10.1007/849s00704-016-1865-z
Orlanski, I. (1975). A Rational Subdivision of Scales for Atmospheric Processes. Bulletin of the American Meteorological Society., 56(5), 527–530.
Pal, J. S., Small, E. E., & Eltahir, E. A. (2000). Simulation of regional-scale water and energy budgets: Representation of subgrid cloud and precipitation processes within RegCM. Journal of Geophysical Research, 105(D24), 29579–29594. https://doi.org/10.1029/2000JD900415
Pareja-Quispe, D., Franchito, S. H., & Fernandez, J. P. R. (2021). Assessment of the RegCM4 performance in simulating the surface radiation budget and hydrologic balance variables in South America. Earth Systems and Environment, 5, 499–518. https://doi.org/10.1007/s41748-021-00249-y
Reboita, M. S., Ambrizzi, T., Crespo, N. M., Dutra, L. M. M., Ferreira, G. W. S., Rehbein, A., Drumond, A., Da Rocha, R. P., & Souza, C. A. (2021). Impacts of teleconnection patterns on South America climate. New York: Annals of the Academy of Sciences.
Reboita, M. S., Fernandez, J. P. R., Llopart, M. P., Da Rocha, R. P., Pampuch, A. L., & Cruz, F. T. (2014). Assessment of RegCM4.3 over the CORDEX South America domain: Sensitivity analysis for physical parameterization schemes. Climate Research, 60, 215–234. https://doi.org/10.3354/cr01239
Reboita, M. S., Gan, M. A., Da Rocha, R. P., & Ambrizzi, T. (2010). Regimes de precipitação na América do Sul: Uma revisão bibliográfica. Revista Brasileira De Meteorologia, 25(2), 185–204. https://doi.org/10.1590/s0102-77862010000200004
Riehl, H. (1954). Tropical Meteorology. 392p. McGraw-Hill, New York.
Rosa, A. G., Sousa, A. M. L. D., Costa, J. A. D., & Souza, E. B. D. (2016). Erosividade da chuva em Rondon do Pará, PA, Brasil de 1999 a 2015 e projetada para 2035. Revista Ambiente & Água, 11, 1006–1021. https://doi.org/10.4136/ambi-agua.1956
Sánchez, J. G. (2017). Estudo espectral da turbulência da Camada Limite Superficial na região da Estação Antártica Brasileira. 60p. Dissertação (Mestrado) - Departamento de Ciências Atmosféricas do Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo
Santos, E. B., Lucio, P. S., & Silva, C. M. S. (2015). Precipitation regionalization of the Brazilian Amazon. Atmospheric Science Letters, 16, 185–192. https://doi.org/10.1002/asl2.535
Siemann, A. L., Chaney, N., & Wood, E. F. (2018). Development and validation of a long-term, global, terrestrial sensible heat flux dataset. Journal of Climate, 31(15), 6073–6095. https://doi.org/10.1175/JCLI-D-17-0732.1
Sodré, G. R. C., & Rodrigues, L. L. M. (2013). Comparação entre estimativa da precipitação observada pela técnica CMORPH e estações meteorológicas do INMET em diferentes regiões do Brasil. Revista Brasileira De Geografia Física, 6(2), 301–307.
Taylor, K. E. (2001). Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research: Atmospheres, 106(7), 7183–7192. https://doi.org/10.1029/2000jd900719
Tiedtke, M. (1989). A comprehensive mass-flux scheme for cumulus parameterization in large-scale models. Monthly Weather Review, 117, 1779–1800. https://doi.org/10.1175/1520-0493(1989)117%3c1779:ACMFSF%3e2.0.CO;2
Wilks, D. S. (2011). Statistical Methods in the Atmospheric Sciences. Burlington, USA: Academic Press.
WMO. (2007). The Role of Climatological Normals in a Changing Climate (WMO-TD no. 1377/WCDMP-No. 61). Geneva, Switzerland.
Zeng, X., Zhao, M., & Dickinson, R. E. (1998). Intercomparison of bulk aerodynamic algorithms for the computation of sea surface fluxes using TOGA COARE and TAO Data. Journal of Climate, 11, 2628–2644. https://doi.org/10.1175/1520-0442(1998)011%3c2628:IOBAAF%3e2.0.CO;2
Acknowledgements
The authors would like to thank CAPES for the financial assistance, the ICTP for the regional climate model used in the study, and the CMORPH precipitation data provided by NOAA/OAR/ESRL PSL, Boulder, Colorado, USA. The authors are particularly grateful for the instructive and helpful comments of the anonymous reviewers.
Funding
This research was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), through a doctoral fellowship to the first author in the scope of the Graduate Program in Climate Sciences (PPGCC) of the Federal University of Rio grande do Norte.
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da Silva, M.L., Cho-Luck, L.E.N., da Silva, J.C.G. et al. Assessing of Two Planetary Boundary Layer Schemes in RegCM4 Model Over the Tropical Region of Brazil. Pure Appl. Geophys. 180, 2901–2914 (2023). https://doi.org/10.1007/s00024-023-03282-2
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DOI: https://doi.org/10.1007/s00024-023-03282-2