Validation and Projections for Solar Radiation up to 2100: HadGEM2-AO Global Circulation Model

The objective of this work is to evaluate the results of solar radiation projections between 2006 and 2013 for the state of Rio Grande do Sul, Brazil. The projections are provided by the General Circulation Models (MCGs) belonging to the Coupled Model Intercomparison Phase 5 (CMIP5). In all, the results of the simulation of six models are evaluated, compared to monthly data, measured by a network of thirteen meteorological stations of the National Meteorological Institute (INMET). The performance of the models is evaluated by the Nash coefficient and the Bias. The results are presented in the form of tables, graphs and spatialization maps. The ACCESS1-0 RCP 4.5 model presented the best results for the solar radiation simulations, for the most optimistic scenario, in much of the state. The efficiency coefficients (CEF) were between 0.95 and 0.98. In the most pessimistic scenario, HADGen2-AO RCP 8.5 had the best accuracy among the analyzed models, presenting coefficients of efficiency between 0.94 and 0.98. From this validation, solar radiation projection maps were elaborated, indicating a seasonal increase of this climatic variable in some regions of the Brazilian territory, mainly in the spring.

• Elison Eduardo Jardim Bierhals
• Claudineia Brazil
• Deivid Pires
• Rafael Haag
• Elton Gimenez Rossini

• climate change
• projections
• solar radiation
• validation.

[1] Martins, Fernando Ramos; PEREIRA, Enio Bueno; ECHER, MP de S. Levantamento dos recursos de energia solar no Brasil com o emprego de satélite geoestacionário–o Projeto Swera. Revista Brasileira de Ensino de Física, v. 26, n. 2, p. 145-159, 2004.
[2] IPCC. Climate Change 2007 - The Physical Science Basis Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Solomon, S, Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp, 2007.
[3] Knutti, R.; Furrer, R.; Tebaldi, C.; Cermak, J.; Meehl, G. A. Challengesin combining projections from multiple climate models. Journal of Climate, v. 23, p.2739-2758, 2010.
[4] Maraun, D.; Shepherd, T. G.; Widmann, M.; Zappa, G.; Walton, D.; Gutiérrez, J. M.; Hagemann, S.; Richter, I.; Soares, P. M. M.; Hall, A.; Mearns, L. O. "Towards processinformed bias correction of climate change simulations". Nature Climate Change, v. 7, n. 11, p. 764–773, 2017.
[5] Machado, Aline Ribeiro; Mello Junior, Arisvaldo Vieira; Wendland, Edson Cezar. Avaliação do modelo J2000/JAMS para modelagem hidrológica em bacias hidrográficas brasileiras. Eng. Sanit. Ambient., Rio de Janeiro, v. 22, n. 2, p. 327-340, Apr. 2017 .
[6] Menezes, Priscila Melo Leal. Análise de fácies e proveniência sedimentar em sambaquis do litoral centro-sul de Santa Catarina. 2009. Tese de Doutorado. Universidade de São Paulo.
[7] Burnett, Dougal; BARBOUR, Edward; HARRISON, Gareth P. The UK solar energy resource and the impact of climate change. Renewable Energy, v. 71, p. 333-343, 2014.
[8] Nobre, Carlos A.; SAMPAIO, Gilvan; SALAZAR, Luis. Cenários de mudança climática para a América do Sul para o final do século 21. Parcerias Estratégicas, v. 13, n. 27, p. 19-42, 2010.
[9] Bennett, Neil D. et al. Characterising performance of environmental models. Environmental Modelling & Software, v. 40, p. 1-20, 2013.
[10] Bronzatti, F. L.; Iarozinski Neto, A. Matrizes energéticas no Brasil: cenário 2010-2030. In: Encontro Nacional de Engenharia de Produção, p.28., 2008, Rio de Janeiro, 2008.
[11] Silveira, Cleiton Silva et al. Avaliação de Desempenho dos Modelos do CMIP5 quanto à Representação dos Padrões de Variação da Precipitação no Século XX sobre a Região Nordeste do Brasil, Amazônia e Bacia da Prata e Análise das Projeções para o Cenário RCP8.5. Revista brasileira de meteorologia, v. 28, n. 3, 2013.
[12] Alves, Lincoln Muniz. Simulaçoes da Variabilidade do Clima Presente sobre a América do Sul utilizando um Modelo climático Regional. Master Science Dissertation, 2007.
[13] INPE, Atlas Brasileiro de Energia Solar. Instituto Nacional de Pesquisas Espaciais, 2017. URL https://goo. gl/dZgWWv.