A hierarchical Bayesian regression framework to analyze climate data from Central Asia region | ||||
| The Egyptian Journal of Environmental Change | ||||
| Article 3, Volume 16, Issue 2, October 2024, Page 31-50 PDF (2.62 MB) | ||||
| Document Type: Peer-reviewed articles | ||||
| DOI: 10.21608/ejec.2024.381182 | ||||
 View on SCiNiTO | ||||
| Abstract | ||||
| This study introduces a straightforward framework for analyzing climate data related to the minimum and maximum temperatures of countries in Central Asia (Kazakhstan, Kyrgyzstan, Tadjikistan, Turkmenistan, and Uzbekistan), considering annual temperature averages over a long period of time ranging from the early 1900's to the beginning of the year 2000. The data analysis used standard existing multiple linear regression models under a hierarchical Bayesian approach, assuming as covariates latitude and longitude of the climate stations, temporal factors (linear, quadratic, and cubic effects of years), and altitude of the climate station. The findings yielded highly accurate results in identifying significant factors influencing climate change, such as time (year), altitude, and spatial factors, as well as in predicting average temperatures in future years. Furthermore, the obtained results align with numerous other studies in the literature, indicating that all regions of the world are already experiencing climate change. In particular, we observed that annual average minimum temperatures in Central Asia are increasing in the five countries assumed in the study at the end of the follow-up period (close to the year 2003). We also observed similar results for the annual average maximum temperatures. | ||||
| Keywords | ||||
| climate data; multiple linear regression models; Bayesian inference; MCMC métodos; minimum and maximum yearly average temperatures | ||||
| References | ||||
|
References
Achcar, J. A. and de Oliveira, R. P. (2022) Climate change: use of non-homogeneous poisson processes for climate data in presence of a change-point. Environmental Modeling & Assessment, 27(2):385–398.
Aguilar E, Peterson T, Obando PR, et. al. (2005) Changes in precipitation and temperature extremes in central america and northern south america, 1961–2003. Journal of Geophysical Research: Atmospheres 110(D23).
Alexander, L. V., Zhang, X., Peterson, T. C., Caesar, J., Gleason, B., Klein Tank, A., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., et al. (2006) Global observed changes in daily climate extremes of temperature and precipitation. Journal of Geophysical Research: Atmospheres, 111(D5).
Almazroui, M., Saeed, F., Saeed, S., Ismail, M., Ehsan, M. A., Islam, M. N., Abid, M. A., O’Brien, E., Kamil, S., Rashid, I. U., et al. (2021) Projected changes in climate extremes using CMIP6 simulations over SREX regions. Earth Systems and Environment, 5(3):481–497.
Arnell, N. W. and Lloyd-Hughes, B. (1999) The global-scale impacts of climate change on water resources and -oodingunder new climate and socio-economic scenarios. Climatic change, 122(1):127–140.
Bell A, Fairbrother M, Jones K. (2019) Fixed and random effects models: making an informed choice. Quality and quantity 53:1051–1074.
Besag, J. (1974) Spatial interaction and the statistical analysis of lattice systems. Journal of the Royal Statistical Society: Series B (Methodological), 36(2):192–225.
Bonan, G. B. (2008) Forests and climate change: forcings, feedbacks, and the climate benefts of forests. Science, 320(5882):1444-1449.
Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F., and Jones, P. D. (2006) Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850. Journal of Geophysical Research: Atmospheres, 111(D12).
Brown, S. J., Caesar, J., and Ferro, C. A. 2008 Global changes in extreme daily temperature since 1950, Journal of Geophysical Research: Atmospheres, 113(D5).
Campbell J, Bedford R, Bedford R. (2014) Migration and climate change in oceania. People on the move in a changing climate: The regional impact of environmental change on migration pp 177–204.
Casella, G. and George, E. I. (1992) Explaining the Gibbs sampler. The American Statistician, 46(3):167–174.
Cassano, E. N., Glisan, J. M., Cassano, J. J., Gutowski Jr, W. J., and Seefeldt, M. W. (2015) Self-organizing map analysis of widespread temperature extremes in Alaska and Canadá. Climate Research, 62(3):199–218.
Chen, H., Xu, C.-Y., and Guo, S. (2012) Comparison and evaluation of multiple GCMs, statistical downscaling and hydrological models in the study of climate change impacts on runoff. Journal of hydrology, 434:36–45.
Chib, S. and Greenberg, E. (1995) Understanding the Metropolis-Hastings algorithm. The american statistician, 49(4):327–335.
Costello, A., Abbas, M., Allen, A., Ball, S., Bell, S., Bellamy, R., Friel, S., Groce, N., Johnson, A., Kett, M., et al. (2009) Managing the health effects of climate change: Lancet and University College London Institute for Global Health Commission.
Cressie, N. and Chan, N. H. (1989) Spatial modeling of regional variables. Journal of the American Statistical Association, 84(406):393–401.
Donat, M., Alexander, L. V., Yang, H., Durre, I., Vose, R., Dunn, R. J., Willett, K. M., Aguilar, E., Brunet, M., Caesar, J., et al. (2013) Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset, Journal of Geophysical Research: Atmospheres, 118(5):2098–2118.
Draper, N. R. and Smith, H. (1998) Applied regression analysis, volume 326. JohnWiley and Sons.
Fang, S., Qi, Y., Han, G., and Zhou, G. (2015) Changing trends and abrupt features of extreme temperature in mainland China during 1960 to 2010. Earth System Dynamics Discussions, 6(1):979–1000.
Feng, R., Yu, R., Zheng, H., and Gan, M. (2018) Spatial and temporal variations in extreme temperature in Central Asia. International Journal of Climatology, 38:e388–e400.
Gelfand, A. E. and Smith, A. F. (1990) Sampling-based approaches to calculating marginal densities. Journal of the American statistical association, 85(410):398–409.
Gilks, W. R., Best, N. G., and Tan, K. K. (1995) Adaptive rejection Metropolis sampling within Gibbs sampling. Journal of the Royal Statistical Society: Series C (Applied Statistics), 44(4):455–472.
Guillemain M, P$ddot{o}$ys$ddot{a}$ H, Fox AD, et al. (2013) Effects of climate change on european ducks: what do we know and what do we need to know? Wildlife Biology 19(4):404–419.
Hawkins, E., Ortega, P., Suckling, E., Schurer, A., Hegerl, G., Jones, P., Joshi, M., Osborn, T. J., Masson-Delmotte, V., Mignot, J., et al. (2017) Estimating changes in global temperature since the preindustrial period. Bulletin of the American Meteorological Society, 98(9):1841-1856.
Horton, D. E., Johnson, N. C., Singh, D., Swain, D. L., Rajaratnam, B., and Diffenbaugh, N. S. (2015) Contribution of changes in atmospheric circulation patterns to extreme temperature trends. Nature, 522(7557):465–469.
Hu, Z., Zhang, C., Hu,Q., and Tian, H. (2014) Temperature changes in Central Asia from 1979 to 2011 based on multiple datasets. Journal of Climate, 27(3):1143–1167.
Iglesias A, Garrote L, Quiroga S, et al. (2012) A regional comparison of the effects of climate change on agricultural crops in europe. Climatic change 112:29–46.
Jones P G, Thornton P K. (2003) The potential impacts of climate change on maize production in africa and latin america in 2055. Global environmental change 13(1):51–59.
Kabir, R., Khan, H. T., Ball, E., and Caldwell, K. (2016) Climate change impact: the experience of the coastal areas of Bangladesh affected by cyclones Sidr and Aila. Journal of environmental and public health.
Kaczan, D. J. and Orgill-Meyer, J. (2020) The impact of climate change on migration: a synthesis of recent empirical insights. Climatic Change, 158(3):281-300.
Klein Tank, A. M., Peterson, T., Quadir, D., Dorji, S., Zou, X., Tang, H., Santhosh, K., Joshi, U., Jaswal, A., Kolli, R., et al. (2006) Changes in daily temperature and precipitation extremes in central and south Asia. Journal of Geophysical Research: Atmospheres, 111(D16).
Laird, N. M. and Ware, J. H. (1982) Random-effects models for longitudinal data. Biometrics, pages 963–974.
Levermann, A., Clark, P. U., Marzeion, B., Milne, G. A., Pollard, D., Radic, V., and Robinson, A. (2013) The multimillennial sea-level commitment of global warming. Proceedings of the National Academy of Sciences , 110(34):13745-13750.
Li, Z. and Fang, H. (2016) Impacts of climate change on water erosion: A review. Earth-Science Reviews, 163:94-117.
Luo, M., Liu, T., Meng, F., Duan, Y., Bao, A., Frankl, A., and De Maeyer, P. (2019) Spatiotemporal characteristics of future changes in precipitation and temperature in Central Asia. International Journal of Climatology, 39(3):1571–1588.
Matthews, T. (2018) Humid heat and climate change. Progress in Physical Geography: Earth and Environment, 42(3):391-405.
McCulloch, C. E. and Searle, S. R. (2004) Generalized, linear, and mixed models. JohnWiley & Sons.
Ozturk, T., Turp, M. T., Türke³, M., and Kurnaz, M. L. (2017) Projected changes in temperature and precipitation climatology of Central Asia CORDEX Region 8 by using RegCM4 v3.5, Atmospheric Research, 183:296–307.
Perelet, R. et al. (2007) Central Asia: Background paper on climate change. Fighting climate change: Human solidarity in a divided world, UNDP Human Development Report.
Poloczanska, E. S., Brown, C. J., Sydeman, W. J., Kiessling, W., Schoeman, D. S., Moore, P. J., Brander, K., Bruno, J. F.,Buckley, L. B., Burrows, M. T., et al. (2013) Global imprint of climate change on marine life. Nature Climate Change, 3(10):919-925.
Propastin, P., Kappas, M., and Muratova, N. (2008) Inter-annual changes in vegetation activities and their relationship to temperature and precipitation in Central Asia from 1982 to 2003. Journal of Environmental Informatics, 12(2).
Rahmstorf, S., Cazenave, A., Church, J. A., Hansen, J. E., Keeling, R. F., Parker, D. E., and Somerville, R. C. (2007) Recent climate observations compared to projections. Science, 316(5825):709-709.
Reyer, C. P., Otto, I. M., Adams, S., Albrecht, T., Baarsch, F., Cartsburg, M., Coumou, D., Eden, A., Ludi, E., Marcus, R., et al. (2017) Climate change impacts in Central Asia and their implications for development. Regional Environmental Change, 17(6):1639–1650.
Seber, G. A. (2015) Nonlinear regression models. In The linear model and hypothesis, pages 117–128. Springer.
Serdeczny, O., Adams, S., Baarsch, F., Coumou, D., Robinson, A., Hare, W., Schaeffer, M., Perrette, M., and Reinhardt, J. (2017) Climate change impacts in Sub-Saharan Africa: From physical changes to their social repercussions. Regional Environmental Change, 17(6):1585-1600.
Singh, N. K., Bhattacharya, R., and Borrok, D. M. (2020) A Bayesian framework to unravel food, groundwater, and climate linkages: A case study from Louisiana. PloS one, 15(7):e0236757.
Smith, T. M. and Reynolds, R. W. (2005) A global merged land-air-sea surface temperature reconstruction based on historical observations (1880–1997). Journal of climate, 18(12):2021–2036.
Soares, M. d. O., Campos, C. C., Carneiro, P., Barroso, H., Marins, R. V., Teixeira, C. E. P., Menezes, M. O. B., Pinheiro, L. d. S., Viana, M. B., Feitosa, C. V., et al. (2021) Challenges and perspectives for the Brazilian semi-arid coast under global environmental changes. Perspectives in Ecology and Conservation, 19(3):267–278.
Somanathan E, Somanathan R, Sudarshan A, et al. (2021) The impact of temperature on productivity and labor supply: Evidence from indian manufacturing. Journal of Political Economy 129(6):1797–1827, 2021
Springmann, M., Mason-D’Croz, D., Robinson, S., Garnett, T., Godfray, H. C. J., Gollin, D., Rayner, M., Ballon, P., and Scarborough, P. (2016) Global and regional health effects of future food production under climate change: A modelling study. The Lancet, 387(10031):1937-1946.
Stocker, T. (2014) Climate change 2013: the physical science basis: Working Group I contribution to the Fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge university press.
Stocker, T. (2014) Climate change 2013: the physical science basis: Working Group I contribution to the Fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge university press.
Tao, H., Fraedrich, K., Menz, C., and Zhai, J. (2014) Trends in extreme temperature indices in the Poyang Lake Basin, china. Stochastic Environmental Research and Risk Assessment, 28(6):1543–1553.
Tawn, J., Shooter, R., Towe, R., and Lamb, R.(2018) Modelling spatial extreme events with environmental applications. Spatial Statistics, 28:39–58.
Tonkaz, T. and Çetin, M. (2007) Effects of urbanization and land-use type on monthly extreme temperatures in a developing semi-arid region, Turkey. Journal of arid environments, 68(1):143–158.
Turner, M. G., Calder, W. J., Cumming, G. S., Hughes, T. P., Jentsch, A., LaDeau, S. L., Lenton, T. M., Shuman, B. N., Turetsky, M. R., Ratajczak, Z., et al. (2020) Climate change, ecosystems and abrupt change: Science priorities. Philosophical Transactions of the Royal Society B, 375(1794):20190105.
Valipour, M., Bateni, S. M., and Jun, C. (2021) Global surface temperature: A new insight. Climate, 9(5), 2021.
Verbeke, G. (1997) Linear mixed models for longitudinal data. In Linear mixed models in practice, pages 63–153. Springer.
Wall, M. M.(2004) A close look at the spatial structure implied by the CAR and SAR models. Journal of statistical planning and inference, 121(2):311–324, 2004.
Wang, H., Chen, Y., Chen, Z., and Li,W. (2013) Changes in annual and seasonal temperature extremes in the arid region of China, 1960–2010. Natural hazards, 65(3):1913–1930.
Williams, M. and Konovalov, V. (2008) Central Asia temperature and precipitation data, 1879–2003. Boulder, Colorado: USA National Snow and Ice Data Center, 2008.
Yin, G., Hu, Z., Chen, X., and Tiyip, T. (2016) Vegetation dynamics and its response to climate change in Central Asia. Journal of Arid Land, 8(3):375–388.
Zarei, A. R., Mahmoudi, M. R., and Shabani, A. (2021) Investigating of the climatic parameters effectiveness rate on barley water requirement using the random forest algorithm, Bayesian multiple linear regression and cross-correlation function. Paddy andWater Environment, 19(1):137–148.
Zhao, C., Liu, B., Piao, S., Wang, X., Lobell, D. B., Huang, Y., Huang, M., Yao, Y., Bassu, S., Ciais, P., et al. (2017) Temperature increase reduces global yields of major crops in four independent estimates. Proceedings of the National Academy of Sciences, 114(35):9326-9331.
Zhong, K., Zheng, F.,Wu, H., Qin, C., and Xu, X. (2017) Dynamic changes in temperature extremes and their association with atmospheric circulation patterns in the Songhua River Basin, China. Atmospheric Research, 190:77–88. | ||||
|
Statistics Article View: 149 PDF Download: 156 |
||||
