Constraining the Potential Evapotranspiration of Egypt Using the Regional Climate Model (RegCM4) and Climate Research Unit Dataset (CRU)

Samy A Anwar*

Samy A Anwar*

Volume4-Issue5
Dates: Received: 2023-05-11 | Accepted: 2023-05-30 | Published: 2023-05-31
Pages: 942-952

Abstract

Accurate forecast of the Potential Evapotranspiration (PET) at a location (where station observation is not available) is necessary in arid/hyper-arid regions (e.g., Egypt) to monitor daily agricultural activities. The Penman-Monteith equation is the standard physical method to compute the PET, but it requires many variables (mostly are calculated empirically). Instead, the Hargreaves-Samani (HS) method was used because it is recommended by the Food and Agriculture Organization and it requires only two variables: global incident solar radiation and daily mean air temperature. Additionally, regional climate models (e.g., RegCM4) can be an alternative tool to estimate the PET constrained by a long-term gridded PET data (Climate Research Unit; CRU) at any location. To accomplish this task, a 39-year simulation was conducted. The RegCM4 was driven by the ERA-Interim reanalysis with 60 km grid spacing. Preliminary results indicated that the RegCM4 was able to capture the monthly variability of the simulated PET with respect to the CRU; however the model overestimates the PET particularly in the summer months (June, July and August). Over all considered locations, performance of the RegCM4 was notably improved when a linear regression model (LRM; between RegCM4 and CRU) was used (indicated by a low bias between the corrected RegCM4 and CRU). In conclusion, the RegCM4 model can accurately calculate the PET at the location of interest by means of the HS equation and a LRM either in the present climate or under different future scenarios.

FullText HTML FullText PDF DOI: 10.37871/jbres1755

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How to cite this article

Anwar SA. Constraining the Potential Evapotranspiration of Egypt Using the Regional Climate Model (RegCM4) and Climate Research Unit Dataset (CRU). J Biomed Res Environ Sci. 2023 May 31; 4(5): 942-952. doi: 10.37871/jbres1755, Article ID: JBRES1755, Available at: https://www.jelsciences.com/articles/jbres1755.pdf

Subject area(s)

Climate Change Biology

References

Terink W, Immerzeel WW, Droogers P. Climate change projections of precipitation and reference evapotranspiration for the Middle East and Northern Africa until 2050. Int J Climatol. 2013;33:3055-3072. doi: 10.1002/joc.3650.
IPCC. Climate Change 2007: Synthesis Report. Technical report, IPCC. 2007.
Ajjur SB, Al-Ghamdi SG. Global hotspots for future absolute temperature extremes from CMIP6 models. Earth Space Sci. 2021;8:2021. doi: 10.1029/2021EA001817.
Hamed MM, Iqbal Z, Nashwan MS, Ahmed FK, Shamsuddin S. Diminishing evapotranspiration paradox and its cause in the Middle East and North Africa. Atmos Res. 2023;289:106760. doi: 10.1016/j.atmosres.2023.106760.
Allen GR, Pereira SL, Raes D, Smith M. Crop evapotranspiration: Guidelines for computing crop water requirements. Food and Agricultural Organization of the United Nations (FAO) Report 56. Rome. 1998;300.
Howell TA, Steiner JL, Schneider AD, Evett SR, Tolk JA. Seasonal and maximum daily evapotranspiration of irrigated winter wheat, sorghum, and corn-southern high plains. Transactions of the American Society of Agricultural Engineers, ASAE. 1997;40(3):623-634. doi: 10.13031/2013.21321.
Itenfisu D, Elliot RL, Allen RG, Walter IA. Comparison off reference evapotranspiration calculation as part of the ASCE standardization effort. J Irrig and Drain Eng. 2003;129(6):440-448. doi: 10.1061/(ASCE)0733-9437(2003)129:6(440).
Alkaeed O, Flores C, Jinno K, Tsutsumi A. Comparison of several reference evapotranspiration methods for Itoshima Peninsula area, Fukuoka, Japan. Memoirs of the Faculty of Engineering, Kyushu University. 2006;66(1):1-14.
Brutsaert W, Parlange MB. Hydrologic cycle explains the evaporation paradox. Nature. 1998;396(6706):30.
Anwar SA, Salah Z, Khald W, Zakey AS. Projecting the potential evapotranspiration of Egypt using a high-resolution Regional Climate Model (RegCM4). Environ Sci Proc. 2022;19(1):43. doi: 10.3390/ecas2022-12841.
Anwar SA, Lazić I. Estimating the potential evapotranspiration of Egypt using a regional climate model and a high-resolution reanalysis dataset. Environ Sci Proc. 2023;25(1):29. doi: 10.3390/ECWS-7-14253.
Anwar SA, Malcheva K, Srivastava A. Estimating the potential evapotranspiration of Bulgaria using a high‑resolution regional climate model. Theor Appl Climatol. 2023;152:1175-1188. doi: 10.1007/s00704-023-04438-9.
Niaghi AR. Evaluate several potential evapotranspiration methods for regional use in Tabriz, Iran. J Appl Environ Biol Sci. 2013;3(6):31-41.
Hargreaves GL, Allen RG. History and evaluation of hargreaves evapotranspiration equation. J Irrigat Drain Eng. 2013;129:53-63. doi: 10.1061/(ASCE)0733-9437(2003)129:1(53).
Irmak S, Irmak A, Allen RG, Jones JW. Solar and net radiation-based equations to estimate reference evapotranspiration in humid climates. J Irrig Drain Eng. 2003;129:5. doi: 10.1061/(ASCE)0733-9437(2003)129:5(336).
Potop V, Boroneant C. Assessment of potential evapotranspiration at Chisinau station. In: Rožnovsky J, Litschmann T, editors. Mendel and Bioclimatology, Conference proceedings from the Mendel and Bioclimatology International Conference, Czech Republic Brno. September 2014;3(5):343–354.
Murat C, Hatice C, Tefaruk H, Kisi O. Modifying Hargreaves-Samani equation with meteorological variables for estimation of reference evapotranspiration in Turkey. Hydrology Research. 2007;48(2):480-497. doi: 10.2166/nh.2016.217.
Sperna Weiland FC, Tisseuil C, Durr HH, Vrac M, van Beek LPH. Selecting the optimal method to calculate daily global reference potential evaporation from CFSR reanalysis data for application in a hydrological model study. Hydrol Earth Syst Sci. 2012;16:983-1000. doi: 10.5194/hess-16-983-2012.
Giorgi F, Coppola E, Solmon F, Mariotti L, Mouhamadou BS, Xunqiang Bi, N Elguindi, GT Diro, Vijayakumar S Nair, G Giuliani, UU Turuncoglu, S Cozzini, Ivan Güttler, TA O’Brien, AB Tawfik, A Shalaby, Sahar Zakey, Allison L S, Frode Stordal, LC Sloan, Čedo Branković. RegCM4: Model description and preliminary tests over multiple CORDEX domains. Clim Res. 2012;52:7-29. doi: 10.3354/cr01018.
Harris I, Osborn TJ, Jones P, Lister D Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci Data. 2020;7:109. doi: 10.1038/s41597-020-0453-3.
Shiri J, Nazemi AH, Sadraddini AA, Landeras G, Kisi O, Fard AF, Mart P. Comparison of heuristic and empirical approaches for estimating reference evapotranspiration from limited inputs in Iran. Comput Electron Agric. 2014;108:230-241. doi: 10.1016/j.compag.2014.08.007.
Mostafa SM, Anwar SA, Zakey AS, Wahab MMA. Bias-correcting the maximum and minimum air temperatures of Egypt using a high-resolution Regional Climate Model (RegCM4). Eng Proc. 2023;31:73. doi: 10.3390/ASEC2022-13852.
Kiehl JT, Hack JJ, Bonan GB, Boville BA, Briegleb BP, Williamson DL, Rasch PJ. Description of the NCAR Community Climate Model (CCM3) (No. NCAR/TN-420+STR). University Corporation for Atmospheric Research. 1996. doi: 10.5065/D6FF3Q99.
Holtslag AAM, Boville BA. Local versus nonlocal boundary layer diffusion in a global model. J Climate. 1993;6:1825-1842. doi: 10.1175/1520-0442(1993)006<1825:LVNBLD>2.0.CO;2.
Emanuel KA. A scheme for representing cumulus convection in large-scale models. J Atmos Sci. 1991;48(21):2313-2335. doi: 10.1175/1520-0469(1991)048<2313:ASFRCC>2.0.CO;2.
Anwar SA, Hejabi S. The influence of different initial conditions on the soil temperature profile of Egypt using a regional climate model. Eng Proc. 2023;31:62. doi: 10.3390/ASEC2022-13850.
Dee DP, Uppala SM, Simmons AJ, Berrisford P, P Poli, S Kobayashi, U Andrae, MA Balmaseda, G Balsamo, P Bauer, P Bechtold, ACM Beljaars, L van de Berg, J Bidlot, N Bormann, C Delsol, R Dragani, M Fuentes, AJ Geer, L Haimberger, SB Healy, H Hersbach, EV Hólm, L Isaksen, P Kållberg, M Köhler, M Matricardi, AP McNally, BM Monge-Sanz, JJ Morcrette, BK Park, C Peubey, P de Rosnay, C Tavolato, JN Thépaut, F Vitart. The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. QJR Meteorol Soc. 2011;137:553-597. doi: 10.1002/qj.828.
Taylor KE. Summarizing multiple aspects of model performance in a single diagram. J Geophysical Research. 2001;106(D7):7183-7192. doi: 10.1029/2000JD900719.
Er-Raki S, Chehbouni A, Khabba S, Simonneaux V, Jarlan L, Ouldbba A, Rodriguez JC, Allen R. Assessment of reference evapotranspiration methods in semi-arid regions: Can weather forecast data be used as alternate of ground meteorological parameters? J Arid Environ. 2010;74(12):1587-1596. doi: 10.1016/j.jaridenv.2010.07.002.
Srivastava A, Sahoo B, Raghuwanshi NS, Singh R. Evaluation of variable-infiltration capacity model and MODIS-terra satellite-derived grid-scale evapotranspiration estimates in a River Basin with Tropical Monsoon-Type climatology. J Irrig Drain. Eng. 2017;143(8). doi: 10.1061/(ASCE)IR.1943-4774.0001199.
Srivastava A, Kumari N, Maza M. Hydrological response to agricultural land use heterogeneity using variable infiltration capacity model. Water Resour Manag. 2020;34(12):3779-3794. doi: 10.1007/s11269-020-02630-4.
Jonathan S, Paulo B, Edoardo B, John C, Tereza Ca, Alessandro C, Jens H C, Ole B C, Erika C, Jason P E, Giovanni F, Beate G, Filippo G, Daniela J, Jack K, Torben K, René L, Christopher JL, Levent KM, Delei L, Marta L, Niall MC, Gustavo N, Grigory N, Tugba O, Hans-Jürgen P, Rosmeri PR, Silvina A S, Jozef S, Fredolin T, Claas T, Robert V, Jürgen VV, Katja W, George Zi, Alessandro D. Global exposure of population and land-use to meteorological droughts under different warming levels and SSPs: A CORDEX-based study. Int J Climatol. 2021;41(15):6825-6853. doi: 10.1002/joc.7302.
Anwar SA, Mamadou O, Diallo I, Sylla MB. On the influence of vegetation cover changes and vegetation-runoff systems on the simulated summer potential evapotranspiration of tropical Africa using RegCM4. Earth Syst Environ. 2021;5:883-897. doi: 10.1007/s41748-021-00252-3.
Taylor KE, Stouffer RJ, Meehl GA. An Overview of CMIP5 and the experiment design. Bull Amer Meteor Soc. 2012;93:485-498. doi: 10.1175/BAMS-D-11-00094.1.
Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE. Overview of the coupled model intercomparison project Phase 6 (CMIP6) experimental design and organization. Geosci Model Dev. 2016;9:1937-1958. doi: 10.5194/gmd-9-1937-2016.
Anwar SA. Influence of direct-downscaling and one-way nesting on daily mean air temperature of Egypt using the RegCM4. J Biomed Res Environ Sci. 2023;4(3):338-347. doi: 10.37871/jbres1681.
Anwar SA, Mostafa SM. On the sensitivity of the daily mean air temperature of Egypt to boundary layer schemes using a high-resolution regional climate model (RegCM4). J Biomed Res Environ Sci. 2023;4(3):474-484. doi: 10.37871/jbres1700.