792
Views
0
CrossRef citations to date
0
Altmetric
ORIGINAL ARTICLE

Exploring the accuracy of correlation coefficients representing the long-term meteorological data for projecting weather in Bahrain for sustainability

ORCID Icon, , &
Pages 231-247 | Received 02 Oct 2022, Accepted 26 Jan 2023, Published online: 09 Apr 2023

References

  • Al-Humaiqani, M. M., & Al-Ghamdi, S. G. (2022). The built environment resilience qualities to climate change impact: Concepts, frameworks, and directions for future research. Sustainable Cities and Society, 80, 103797. doi:10.1016/j.scs.2022.103797
  • Alnaser, W. E. (1993). New model to estimate the solar global irradiation using astronomical and meteorological parameters. Renewable Energy. 3(2-3), 175–177. doi:10.1016/0960-1481(93)90016-A
  • Alnaser, W. E., & Aldudiafa, H. S. (1990). Calculation of the global, diffused and direct solar radiation in Bahrain. Solar & Wind Technology, 7(2-3), 309–311. doi:10.1016/0741-983X(90)90101-7
  • Alnaser, W. E., & Awadalla, N. S. (1990). Empirical model to estimate the global radiation in Bahrain by the knowledge of some astronomical parameters. Solar & Wind Technology, 7(5), 537–539. doi:10.1016/0741-983X(90)90059-B
  • Alnaser, W. E., Awadalla, N. S., & Almoataz, L. A. (1992). Use of solar radiation measurement to detect the pollution of Bahrain’s sky caused by the Gulf War. Proceedings of the 1st Bahrain International Conference on Environment, Manama, Bahrain, February 24–26 (Vol. 1, pp. 309–323).
  • Andrić, I., Koc, M., & Al-Ghamdi, S. G. (2019). A review of climate change implications for built environment: Impacts, mitigation measures and associated challenges in developed and developing countries. Journal of Cleaner Production, 211, 83–102. doi:10.1016/j.jclepro.2018.11.128
  • Build. (2021). What climate factors are important considerations for building projects? Posted on 2nd June 2021. Retrieved from https://www.build-review.com/what-climate-factors-are-important-considerations-for-building-projects/
  • Carpenter, S., Walker, B., Anderies, J. M., & Abel, N. (2001). From metaphor to measurement: Resilience of what to what? Ecosystems, 4(8), 765–781. doi:10.1007/s10021-001-0045-9
  • Ceccato, P., Ramirez, B., Manyangadze, T., Gwakisa, P., & Thomson, M. C. (2018). Data and tools to integrate climate and environmental information into public health. Infectious diseases of Poverty, 7(1), 126. doi:10.1186/s40249-018-0501-9
  • Centre for Disease Control and Prevention (CDC). (2022). Impact of the built environment on health. Retrieved from https://www.cdc.gov/nceh/publications/factsheets/impactofthebuiltenvironmentonhealth.pdf
  • Chen, L., Cao, L., Zhou, Z., Zhang, D., & Liao, J. (2021). A new globally reconstructed sea surface temperature analysis dataset since 1900. Journal of Meteorological Research, 35(6), 911–925. doi:10.1007/s13351-021-1098-7
  • Chen, Y., Moufouma-Okia, W., Masson-Delmotte, V., Zhai, P., & Pirani, A. (2018). Recent progress and emerging topics on weather and climate extremes since the fifth assessment report of the intergovernmental panel on climate change. Annual Review of Environment and Resources, 43(1), 35–59. doi:10.1146/annurev-environ-102017-030052
  • Danny, H. W., Li, L. Y., & Lam, J. C. (2012). Impact of climate change on energy use in the built environment in different climate zones – A review. Energy, 42(1), 103–112. doi:10.1016/j.energy.2012.03.044
  • Dervis, K. (2007). Devastating for the world’s poor. UN Chronicle Online Edition, 1–4. Retrieved from https://www.uncclearn.org/wp-content/uploads/library/undp30.pdf
  • Duhoon, V., & Bhardwaj, R. (2021). Artificial intelligence technique for weather parameter forecasting. International Conference on Computational Performance Evaluation (ComPE), Shillong, India (pp. 098–102). doi:10.1109/ComPE53109.2021.9751934
  • El Bakkush, A. F., Bondinuba, F. K., Bondinuba, F., & Harris, D. J. (2015). The effect of outdoor air temperature on the thermal performance of a residential building. Journal of Multidisciplinary Engineering Science and Technology (JMEST), 2(9), 2563–2570.
  • Environmental Protection Agency (EPA). (2022). Basic information about the built environment. Retrieved from https://www.epa.gov/smm/basic-information-about-built-environment#builtenviron
  • European Environment Agency (EEA). (2021). Climate change is one of the biggest challenges of our times. Retrieved from https://www.eea.europa.eu/themes/climate/climate-change-is-one-of
  • Griggs, D., Stafford-Smith, M., Warrilow, D., Street, R., Vera, C., Scobie, M., & Sokona, Y. (2021). Use of weather and climate information essential for SDG implementation. Nature reviews. Earth & Environment, 2(1), 2–4. doi:10.1038/s43017-020-00126-8
  • Hui, S. C. M., & Tsang, M. F. (2005). Climatic data for sustainable building design in Hong Kong. In Proceedings of the Joint Symposium 2005: New Challenges in Building Services, 15 November 2005, Hong Kong SAR, Climatic data for sustainable building design in Hong Kong. Retrieved from https://www.researchgate.net/publication/255575775_Climatic_data_for_sustainable_building_design_in_Hong_Kong
  • Hung, N. Q., Babel, M. S., Weesakul, S., & Tripathi, N. K. (2009). An artificial neural network model for rainfall forecasting in Bangkok, Thailand. Hydrology and Earth System Sciences, 13(8), 1413–1425. doi:10.1155/2013/525383
  • Kazemzadeh, M., Noori, Z., Jamali, S., & Abdi, A. M. (2022). Forty years of air temperature change over Iran reveals linear and nonlinear warming. Journal of Meteorological Research, 36(3), 462–477. doi:10.1007/s13351-022-1184-5
  • Lacasse, M. A. (2019). An overview of durability and climate change of building components. Canadian Journal of Civil Engineering, 46(11), v–viii. doi:10.1139/cjce-2019-0625
  • Litta, A. J., Idicula, S. M., & Mohanty, U. C. (2013). Artificial neural network model in prediction of meteorological parameters during premonsoon thunderstorms. International Journal of Atmospheric Sciences, 2013, 1–14. doi:10.1155/2013/525383
  • Mabon, L., Kondo, K., Kanekiyo, H., Hayabuchi, Y., & Yamaguchi, A. (2019). Fukuoka: Adapting to climate change through urban green space and the built environment? Cities (London, England), 93, 273–285. doi:10.1016/j.cities.2019.05.007
  • Nabipour, N., Mosavi, A., Hajnal, E., Nadai, L., Shamshirband, S., & Chau, K.-W. (2020). Modeling climate change impact on wind power resources using adaptive neuro-fuzzy inference system. Engineering Applications of Computational Fluid Mechanics, 14(1), 491–506. doi:10.1080/19942060.2020.1722241
  • Otto-Zimmermann, K. (2010). Resilient cities: Cities and adaptation to climate change. Proceedings of the Global Forum 2010, Bonn, Germany ,Springer. doi:10.1007/978-94-007-4223-9
  • PLANETCALC Online. (2022). Calculators function approximation with regression analysis. Retrieved from https://planetcalc.com/5992/
  • Sebestyén, V., Czvetkó, T., & Abonyi, J. (2021). The applicability of big data in climate change research: The importance of system of systems thinking. Frontiers in Environmental Science, 9, 619092. doi:10.3389/fenvs.2021.61909
  • Sharafati, A., & Pezeshki, E. (2020). A strategy to assess the uncertainty of a climate change impact on extreme hydrological events in the semi-arid Dehbar catchment in Iran. Theoretical and Applied Climatology, 139(1-2), 389–402. doi:10.1007/s00704-019-02979-6
  • Sfetsos, A., & Coonick, A. H. (2000). Univariate and multivariate forecasting of hourly solar radiation with artificial intelligence techniques. Solar Energy, 68(2), 169–178. doi:10.1016/S0038-092X(99)00064-X
  • Sharifi, A., & Yamagata, Y. (2018). Resilience-oriented urban planning. In Y. Yamagata & A. Sharifi (Eds.), Resilience-oriented urban planning. Lecture notes in energy (Vol. 65). Cham: Springer. doi:10.1007/978-3-319-75798-8_1
  • Solomon, S., Plattner, G. K., Knutti, R., & Friedlingstein, P. (2009). Irreversible climate change due to carbon dioxide emissions. Proceedings of the National Academy of Sciences of the United States of America, 106(6), 1704–1709. doi:10.1073/pnas.0812721106
  • Świąder, M., Szewrański, S., Kazak, J. K., Van Hoof, J., Lin, D., Wackernagel, M., & Alves, A. (2018). Application of ecological footprint accounting as a part of an integrated assessment of environmental carrying capacity: A case study of the footprint of food of a large city. Resources, 7(3), 52. doi:10.3390/resources7030052
  • UNFCCC. (2017). Survey of adaptation actions and needs. United Nations Framework Convention on Climate Change. https://unfccc.int/news/survey-of-adaptation-actions-and-needs
  • Zhao, G. H., Xinyue, Cui, X., Sun, J., Li, T., Wang, Q., … Ye, X., B. (2021). Analysis of the distribution pattern of Chinese Ziziphus jujuba under climate change based on optimized biomod2 and MaxEnt models. Ecological Indicators, 132, 108256. doi:10.1016/j.ecolind.2021.108256
  • Zięba, Z., Dąbrowska1, J., Marschalko, M., Pinto, J., Mrówczyńska, M., Leśniak, A., … Kazak, J. K. (2020). Built environment challenges due to climate change. IOP Conference Series: Earth and Environmental Science, 609, 1–10. 10.1088/1755-1315/609/1/012061/pdf.