Using the LARS-WG Model to Predict the Maximum Temperature in Zakho City, Iraq
DOI:
https://doi.org/10.31185/ejuow.Vol12.Iss4.563Keywords:
LARS-WG, GCMs, Downscaling, Maximum temperature, Zakho.Abstract
Climate change has significantly impacted residential environments in many parts of the world. Scientists are nowadays more motivated to study and predict future changes in essential climatic elements, including temperature, to provide helpful reference results for future planning and managing. This study aims to estimate the impact of global warming on Zakho City, northern Iraq. The daily maximum temperatures are downscaled using the Long Ashton Research Station Weather Generator (LARS-WG) model based on the SSP585 scenario. Five General Circulation Models (GCMs) outputs are used for the selected period (2021-2040). The results exhibit that the statistical analysis validated the LARS-WG model’s ability and dependability to downscale maximum temperature time series, and the average of five GCMs showed a rise in the monthly data of the studied period compared to the reference period (1985-2015). The predicted increase for the maximum temperature ranges between 1.4 to 2.7 ºC. The obtained results of the current research have the chance to improve comprehension of how the urban environment is affected by climate change and motivate stakeholders and planners to identify the most effective means of reducing these effects
References
Rhodes, C.J.J.S.p., Only 12 years left to readjust for the 1.5-degree climate change option–Says International Panel on Climate Change report: Current commentary. 2019. 102(1): p. 73-87.
Naqi, N.M., et al., Statistical analysis of extreme weather events in the Diyala River basin, Iraq. Journal of Water and Climate Change,, 2021. 12(8): p. 3770-3785.
Yu, T., et al., East Asia dust storms in spring 2021: Transport mechanisms and impacts on China. Atmospheric Research, 2023. 290: p. 106773.
Rami, A., et al., Atmospheric analysis of dust storms in Sistan region. Journal of Atmospheric and Solar-Terrestrial Physics, 2022. 227: p. 105800.
Ledari, D.G., M. Hamidi, and Y.J.J.o.A.E. Shao, Numerical simulation of the 18 February 2017 frontal dust storm over southwest of Iran using WRF-Chem, satellite imagery, and PM10 concentrations. Journal of Arid Environments, 2022. 196: p. 104637.
Hamidi, M.J.C., The key role of water resources management in the Middle East dust events. Catena, 2020. 187: p. 104337.
Khazaei, B., et al., Climatic or regionally induced by humans? Tracing hydro-climatic and land-use changes to better understand the Lake Urmia tragedy. Journal of hydrology, 2019. 569: p. 203-217.
Khazaei, B., et al., Climatic or regionally induced by humans? Tracing hydro-climatic and land-use changes to better understand the Lake Urmia tragedy. ournal of hydrology, 2019. 569: p. 203-217.
Zubaidi, S.L., et al., A Novel approach for predicting monthly water demand by combining singular spectrum analysis with neural networks. Journal of hydrology, 2018. 561: p. 136-145.
Zubaidi, S.L., et al. Short-term water demand prediction in residential complexes: Case study in Columbia city, USA. in 2018 11th International Conference on Developments in eSystems Engineering (DeSE). 2018. IEEE.
Zubaidi, S.L., et al., Short-term urban water demand prediction considering weather factors. Water resources management,, 2018. 32: p. 4527-4542.
Fowler, H.J., S. Blenkinsop, and C.J.I.J.o.C.A.J.o.t.R.M.S. Tebaldi, Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. nternational Journal of Climatology, 2007. 27(12): p. 1547-1578.
Trzaska, S. and E.J.U.S.A.f.I.D.b.T.T.A. Schnarr, A review of downscaling methods for climate change projections. International Development, 2014. 45(05): p. 45-2621.
Semenov, M.A., E.M. Barrow, and A.J.U.M.H.U. Lars-Wg, A stochastic weather generator for use in climate impact studies. resources.rothamsted.ac.uk, 2002: p. 1-27.
Khoi, D.N., et al., Impact of climate change on hydro-meteorological drought over the Be River Basin, Vietnam. Journal of Water and Climate Change, 2021. 12(7): p. 3159-3169.
Javan, K., A. Movaghari, and J.-S. Park, Projected changes in extreme precipitation indices over the Lake Urmia basin in Iran. Journal of Water and Climate Change, 2023. 14(8): p. 2564-2582.
Hosseini Baghanam, A., et al., Policy-Making toward Integrated Water Resources Management of Zarrine River Basin via System Dynamics Approach under Climate Change Impact. Sustainability, 2022. 14(6).
Moghadam, S.H., P.-S. Ashofteh, and H.A. Loáiciga, Investigating the performance of data mining, lumped, and distributed models in runoff projected under climate change. Journal of Hydrology, 2023. 617.
Osman, Y., et al., Climate change model as a decision support tool for water resources management in northern Iraq: a case study of Greater Zab River. Journal of Water and Climate Change, 2019. 10(1): p. 197-209.
Mohammed, R., M.J.T. Scholz, and a. climatology, Climate change and water resources in arid regions: uncertainty of the baseline time period. Theoretical and applied climatology, 2019. 137(1): p. 1365-1376.
Yaseen T. Mustafa, D.R.I., Land Use Land Cover Change in Zakho District, Kurdistan Region, Iraq: Past, Current and Future. International Conference, 2019.
Abdellatif, M., et al., Quantitative assessment of sewer overflow performance with climate change in northwest England. Hydrological Sciences Journal, 2015. 60(4): p. 636-650.
Räisänen, J.J.C.d., Twenty-first century changes in snowfall climate in Northern Europe in ENSEMBLES regional climate models. Climate dynamics, 2016. 46: p. 339-353.
Zamani, M.G., et al., Developing sustainable strategies by LID optimization in response to annual climate change impacts. Journal of Cleaner Production, 2023. 416.
Tikuye, B.G., et al., Modelling the impacts of changing land use and climate on sediment and nutrient retention in Lake Tana Basin, Upper Blue Nile River Basin, Ethiopia. Ecological Modelling, 2023. 482.
Soltani, S., et al., Climate change and energy use efficiency in arid and semiarid agricultural areas: A case study of Hamadan-Bahar plain in Iran. Energy, 2023. 268.
Morid, R., Y. Shimatani, and T. Sato, An integrated framework for prediction of climate change impact on habitat suitability of a river in terms of water temperature, hydrological and hydraulic parameters. Journal of Hydrology, 2020. 587.
Daniels, A.E., et al., Climate projections FAQ. 2012: United States Department of Agriculture, Forest Service, Rocky Mountain ….
Khan, S.F. and U.A. Naeem, Future climate projections using the LARS-WG6 downscaling model over Upper Indus Basin, Pakistan. Environ Monit Assess, 2023. 195(7): p. 810.
Khalaf, R.M., et al., Projections of precipitation and temperature in Southern Iraq using a LARS-WG Stochastic weather generator. Physics and Chemistry of the Earth, Parts A/B/C, 2022. 128.
Hassan, Z., et al., Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature. Theoretical and applied climatology, 2014. 116: p. 243-257.
Willis, J.C., et al., Use of an individual‐based model to forecast the effect of climate change on the dynamics, abundance and geographical range of the pest slug Deroceras reticulatum in the UK. Global Change, 2006. 12(9): p. 1643-1657.
Osman, Y., et al., Climate change and future precipitation in an arid environment of the MIDDLE EAST: CASE study of Iraq. 2017. 25(3).
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Copyright (c) 2024 Sura M. Abdulsahib, Salah L. Zubaidi, Nadheer S. Ayoob
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