Future predictions of precipitation and temperature in Iraq using the statistical downscaling model
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Iraq is facing a critical water crisis that has ever experienced. This necessitates a wise management for present and future water resources. Future water availability is mainly influenced by the impacts of climate changes and to dams in Turkey, Syria, Iran, and northern Iraq. The meteorological parameters obtained from global circulation models (GCM) cannot be used to assess the impacts of future climate changes on the water resources availability at catchment scale. The dynamical or statistical downscaling is employed to transfer the coarse resolution of GCM into a finer. In this study, the future maximum/minimum temperature and precipitation for 12 stations of Iraq were projected for three future periods 2020s (2011–2040), 2050s (2041–2070), and 2080s (2071–2100) from the Canadian GCM model (CanESM2) under different scenarios (RCP2.5, RCP4.5, and RCP8.5) using statistical downscaling model (SDSM). The model was set up utilizing partial correlation and significance level of 0.05 between National Center for Environmental Prediction/Atmospheric Research (NCEP/NCAR) parameters as predictors and the local station data as predictand. Subsequently, the model was calibrated and validated against daily data by using 70% of the data for calibration and the remaining 30% for the validation. Thereafter, the calibrated model was applied to downscale future scenarios of CanESM2 predictors. The study proved a satisfactory performance of SDSM for simulation of maximum-minimum temperatures and precipitation for future periods. All considered stations and the scenarios were consistent in predicting increasing trend of maximum-minimum temperature and decreasing trend of precipitations. RCP8.5 scenario shows the worst trend of precipitation and temperature.
KeywordsStatistical downscaling Projections Precipitation Temperature Iraq
The Ministry of Higher Education and Scientific Research in Iraq is acknowledged for their support during the study. The authors are grateful for the IPCC for making the global climate change models freely available.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Al-Ansari NA, Ezz-Aldeen M, Knutsson S, Zakaria S (2012) Water harvesting and reservoir optimization in selected areas of south Sinjar Mountain, Iraq. J Hydrol Eng 18:1607–1616. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000712 CrossRefGoogle Scholar
- Al-Dousari A (2005) Causes and indicators of land degradation in the North-Western part of Kuwait. Arab Gulf J Sci Res 23(2):69–79Google Scholar
- Al-Ghadban AN, Uddin S, Beg MU, Al-Dousari AM, Gevao B, Al-Yamani F (2008) Ecological consequences of river manipulations and drainage of Mesopotamian marshes on the Arabian Gulf ecosystem: investigations on changes in sedimentology and environmental quality, with special reference to Kuwait Bay. Kuwait Institute for Scientific Research (KISR) 9362:1–141Google Scholar
- Al-Mukhtar M (2018) Integrated approach to forecast future suspended sediment load by means of SWAT and artificial intelligence models, a case study. FOG Journal 51(Jun):52–77Google Scholar
- Elhakeem A, Elshorbagy WE, AlNaser H, Dominguez F (2015) Downscaling global circulation model projections of climate change for the United Arab Emirates. J Water Resour Plan Manag 141(9):04015007Google Scholar
- Gachon P, St-Hilaire A, Ouarda TBM.J, Nguyen VTV, Lin C, Milton J, Chaumont D, Goldstein J, Hessami M, Nguyen TD, Selva F, Nadeau M, Roy P, Parishkura D, Major N, Choux M, Bourque A, (2005) A First Evaluation of the Strength and Weaknesses of Statistical Downscaling Methods for Simulating Extremes over Various Regions of Eastern Canada. Sub-component, Climate Change Action Fund (CCAF), Environment Canada, Montreal, Quebec, Canada, 209 ppGoogle Scholar
- Huth R (2002) Statistical downscaling of daily temperature in Central Europe. J Clim 15(13):1731–1742. https://doi.org/10.1175/1520-0442(2002)015<1731:sdodti>2.0.co;2 CrossRefGoogle Scholar
- IPCC (2013) In: Stocker TF, Qin D, Plattner GK, Tignor MM, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, p 1535Google Scholar
- Jones RG, Murphy JM, Noguer M (1995) Simulation of climate change over Europe using a nested regional climate model. I. Assessment of control climate, including sensitivity to location of lateral boundaries. Q J R Meteorol Soc 121(526):1413–1450. https://doi.org/10.1002/qj.49712152610 CrossRefGoogle Scholar
- Krause P, Boyle DP, Bäse F (2005) Comparison of different efficiency criteria for hydrological model assessment. Adv Geosci 5:89–97Google Scholar
- Nimah MN (2008) Water resources (2008) report of the Arab forum for environment and development. In: Tolba MK, Saab NW (eds) Arab environment and future challenges, Chapter 5. Arab Forum for Environment and Development, Cairo, pp 63–74Google Scholar
- Romanowicz RJ, Bogdanowicz E, Debele SE, Doroszkiewicz J, Hisdal H, Lawrence D, Meresa HK, Napiórkowski JJ, Osuch M, Strupczewski WG, Wilson D (2016) Climate change impact on hydrological extremes: preliminary results from the polish-Norwegian project. Acta Geophys 64(2):477–509. https://doi.org/10.1515/acgeo-2016-0009
- Wilby RL, Dawson CW (2007) Statistical downscaling model (SDSM), version 4.2. Department of Geography, Lancaster University, LancashireGoogle Scholar
- Zakaria S et al (2013) Estimation of annual harvested runoff at Sulaymaniyah governorate, Kurdistan region of Iraq. Nat Sci 05(12):1272–1283Google Scholar