Abstract
A major challenge to climate-related research is the lack of a well-documented historical climate dataset. Unfortunately, most of the climate databases in developing countries have a critical data quality problem (missing data in time series and inhomogeneity). This study aimed to prepare a complete and homogenized climate dataset for the Tekeze river basin in Ethiopia and to assess the impact of detected inhomogeneity in major climate characteristics. Satellite and reanalysis climate products were used to fill in the missing data in the time series after a thorough evaluation and bias correction to the latter dataset. Together with other quality control approaches, the Multiple Analysis of Series for Homogenization (MASH) software was used for climate data homogenization. Results show that both minimum temperature (Tmin) and maximum temperature (Tmax) have a large number of breakpoints compared to rainfall. After homogenization, the original raw climate data was compared with the homogenized data. As the results show, the detected inhomogeneity causes a significant error to the region’s climate characteristics. For instance, following homogenization process, some stations have shown a change in trend magnitude from – 122 mm/decade to 0.2 mm/decade, from 1.2 °C/decade to 0.3 °C/decade, and from 1.5 °C/decade to 0.6 °C/decade for rainfall, Tmin, and Tmax respectively. The temperature trend resulted from the homogenized dataset is by far in agreement with trend results provided at the country level (nearly 0.3 °C to 0.4 °C/decade). Therefore, there is an urgent need of documenting a complete and homogenized historical climate dataset as a prerequisite for reliable climate-related studies.
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References
Aguilar E, Brunet M (2003) Guidelines on climate metadata and homogenization. In: Report WMO-TD 1186, World meteorological Organization. Switzerland, Geneva 50 p
Andang’o H, Ouma J, Muthama N, Opere A (2016) Investigating the homogeneity of monthly rainfall records in Kenya. J Meteorol Relat Sci 9:48–54. https://doi.org/10.20987/jmrs.4.05.2016
AU, & FAO (2012) National strategy and action plan for the implementation of the Great Green Wall Initiative in Ethiopia
Ayehu GT, Tadesse T, Gessesse B, Dinku T (2018) Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia. Atmos Meas Tech 11(4):1921–1936. https://doi.org/10.5194/amt-11-1921-2018
Boissonnade AC, Heitkemper LJ, Whitehead D (2002) Weather data_ cleaning and enhancement. In: Risk Management Solutions. Corporation, Earth Satellite
Conrad V, Pollak LW (1950) Methods in climatology. Harvard University Press
Costa AC, Soares A (2008) Homogenization of climate data: review and new perspectives using geostatistics. Math Geosci 41(3):291–305. https://doi.org/10.1007/s11004-008-9203-3
Della-Marta P, Collins D, Braganza K (2004) Updating Australia’s high-quality annual temperature dataset. Aust Meteorol Mag 53(2):75–93
Dile YT, Srinivasan R (2014) Evaluation of CFSR climate data for hydrologic prediction in data-scarce watersheds: an application in the Blue Nile River Basin. JAWRA J Am Water Resour Assoc 50(5):1226–1241. https://doi.org/10.1111/jawr.12182
Fazzini M, Bisci C, Billi P (2015) The climate of Ethiopia. In Landscapes and Landforms of Ethiopia (pp. 65–87)
Feng S, Hu Q, Qian W (2004) Quality control of daily meteorological data in China, 1951–2000: a new dataset. Int J Climatol 24(7):853–870. https://doi.org/10.1002/joc.1047
Fuka DR, Walter MT, MacAlister C, Degaetano AT, Steenhuis TS, Easton ZM (2014) Using the Climate Forecast System Reanalysis as weather input data for watershed models. Hydrol Process 28(22):5613–5623. https://doi.org/10.1002/hyp.10073
Gebere S, Alamirew T, Merkel B, Melesse A (2015) Performance of high resolution satellite rainfall products over data scarce parts of Eastern Ethiopia. Remote Sens 7(9):11639–11663. https://doi.org/10.3390/rs70911639
Gebrechorkos SH, Hülsmann S, Bernhofer C (2017) Evaluation of multiple climate data sources for managing environmental resources in East Africa. Hydrol Earth Syst Sci Discuss 1–43. https://doi.org/10.5194/hess-2017-558
Gebremicael TG, Mohamed YA, Van der Zaag P, Berhe AG, Haile GG, Hagos EY, Hagos MK (2017) Comparison and validation of eight satellite rainfall products over the rugged topography of Tekeze-Atbara Basin at different spatial and temporal scales. Hydrol Earth Syst Sci Discuss 1–31. https://doi.org/10.5194/hess-2017-504
Gofa F, Mamara A, Anadranistakis M, Flocas H (2019) Developing gridded climate data sets of precipitation for Greece based on homogenized time series. Climate 7(5). https://doi.org/10.3390/cli7050068
Golub AA, Fuss S, Lubowski R, Hiller J, Khabarov N, Koch N, Krasovskii A, Kraxner F, Laing T, Obersteiner M, Palmer C, Piris-Cabezas P, Reuter WH, Szolgayová J, Taschini L, Wehkamp J (2018) Escaping the climate policy uncertainty trap: options contracts for REDD+. Clim Pol 18(10):1227–1234. https://doi.org/10.1080/14693062.2017.1422478
Gonzalez-Rouco JF, Jimenez JL, Quesada V, Valero F (2000) Quality control and homogeneity of precipitation data in the Southwest of Europe. J Clim 14
Guttman NB (1998) Homogeneity, Data adjustments and climatic normals. Natl Clim Data Cent
Hamed KH (2009) Enhancing the effectiveness of prewhitening in trend analysis of hydrologic data. J Hydrol 368(1-4):143–155. https://doi.org/10.1016/j.jhydrol.2009.01.040
Hamed KH, Rao AR (1998) A modified Mann Kendal test for autocorrelated data. J Hydrol 204:182–196
Hasanpour Kashani M, Dinpashoh Y (2011) Evaluation of efficiency of different estimation methods for missing climatological data. Stoch Env Res Risk A 26(1):59–71. https://doi.org/10.1007/s00477-011-0536-y
Hessels TM (2015) Comparison and validation of several open access remotely sensed rainfall products for the nile basin
IPCC (2014) Climate Change; Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland. 151
Jury MR, Funk C (2013) Climatic trends over Ethiopia: regional signals and drivers. Int J Climatol 33(8):1924–1935. https://doi.org/10.1002/joc.3560
Kusangaya S, Warburton ML, Archer van Garderen E, Jewitt GPW (2014) Impacts of climate change on water resources in southern Africa: a review. Phys Chem Earth, Parts A/B/C 67-69:47–54. https://doi.org/10.1016/j.pce.2013.09.014
Lakatos M, Szentimrey T, Bihari Z, Szalai S (2006) Proceedings of the fifth seminar for homogenization and quality control in climatological databases. World Meteorol Organ
Lakatos M, Szentimrey T, Bihari Z, Szalai S (2013) Creation of a homogenized climate database for the Carpathian region by applying the MASH procedure. J Hung Meteorol Serv 117(1):143–158
Li Z, Cao L, Zhu Y, Yan Z (2016) Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960–2013. J Meteorol Res 30(1):53–66. https://doi.org/10.1007/s13351-016-5054-x
Li Z, Yan Z (2010) Application of multiple analysis of series for homogenization to Beijing daily temperature series (1960–2006). Adv Atmos Sci 27(4):777–787. https://doi.org/10.1007/s00376-009-9052-0
Luo M, Liu T, Meng F, Duan Y, Frankl A, Bao A, De Maeyer P (2018) Comparing bias correction methods used in downscaling precipitation and temperature from regional climate models: a case study from the Kaidu River Basin in Western China. Water 10(8):1046. https://doi.org/10.3390/w10081046
Mahmood R, Jia S (2016) Quality control and homogenization of daily meteorological data in the trans-boundary region of the Jhelum River basin. J Geogr Sci 26(12):1661–1674. https://doi.org/10.1007/s11442-016-1351-7
Mamara A, Argiriou AA, Anadranistakis M (2012) Homogenization of mean monthly temperature time series of Greece. Int J Climatol 33:2649–2666. https://doi.org/10.1002/joc.3614
Menne MJ, Williams CN (2009) Homogenization of temperature series via pairwise comparisons. J Clim 22(7):1700–1717. https://doi.org/10.1175/2008jcli2263.1
Peterson TC, Easterling DR, Karl TR, Groisman P, Nicholls N, Plummer N, Torok S, Auer I, Boehm R, Gullett D, Vincent L, Heino R, Tuomenvirta H, Mestre O, Szentimrey T, Salinger J, Førland EJ, Hanssen-Bauer I, Alexandersson H, Jones P, Parker D (1998) Homogeneity adjustments of in situ atmospheric climate data: a review. Int J Climatol 18:1493–1517
Reeves J, Chen J, Wang XL, Lund R, Lu QQ (2007) A review and comparison of changepoint detection techniques for climate data. J Appl Meteorol Climatol 46(6):900–915. https://doi.org/10.1175/jam2493.1
Roth V, Lemann T (2015) Comparing CFSR and conventional weather data for discharge and sediment loss modelling with SWAT in small catchments in the Ethiopian Highlands. Hydrol Earth Syst Sci Discuss 12(2):2113–2153. https://doi.org/10.5194/hessd-12-2113-2015
Serdeczny O, Adams S, Baarsch F, Coumou D, Robinson A, Hare W, Schaeffer M, Perrette M, Reinhardt J (2016) Climate change impacts in Sub-Saharan Africa: from physical changes to their social repercussions. Reg Environ Chang 17(6):1585–1600. https://doi.org/10.1007/s10113-015-0910-2
Shen L, Lu L, Hu T, Lin R, Wang J, Xu C (2018) Homogeneity test and correction of daily temperature and precipitation data (1978–2015) in North China. Adv Meteorol 2018:1–17. https://doi.org/10.1155/2018/4712538
Skrynyk O, Aguilar E, Skrynyk O, Sidenko V, Boichuk D, Osadchyi V (2018) Quality control and homogenization of monthly extreme air temperature of Ukraine. Int J Climatol 39(4):2071–2079. https://doi.org/10.1002/joc.5934
Sotiriadou S, Mallio Z (2018) Climate data processing, assessment and corrective methods. 13th International Conference on Protection and restoration of the Environment
Soto Golcher C, Arts B, Visseren-Hamakers I (2018) Seeing the forest, missing the field: Forests and agriculture in global climate change policy. Land Use Policy 77:627–640. https://doi.org/10.1016/j.landusepol.2018.06.014
Squintu AA, van der Schrier G, Brugnara Y, Klein Tank A (2019) Homogenization of daily temperature series in the European Climate Assessment & Dataset. Int J Climatol 39(3):1243–1261. https://doi.org/10.1002/joc.5874
Štěpánek P, Zahradníček P, Farda A (2013) Experiences with data quality control and homogenization of daily records of various meteorological elements in the Czech Republic in the period 1961-2010. J Hung Meteorol Serv 117(1):123–141
Stepanek P, Zahradnicek P, Skalak P (2009) Data quality control and homogenization of air temperature and precipitation series in the area of the Czech Republic in the period 1961–2007. Adv Sci Res 3:23–26
Szentimrey T (1999) Multiple analysis of series for homogenization (MASH). Paper presented at the Proceedings of the second seminar for homogenization of surface climatological data
Szentimrey T (2000) Multiple analysis of series for homogenization (MASH), seasonal application of MASH (SAM), automatic using of meta data. Paper presented at the Proceedings of the Third Seminar for Homogenization of Surface Climatological Data, Budapest, Hungary
Szentimrey T (2017) Manual for Multiple Analysis of Series for Homogenization (MASH 3.03). Hungarian Meteorological Service: Budapest, Hungary
Tayanç M, Dalfes HNZ, Karaca M, Yenigün O (1998) A comparative assessment of different methods for detecting inhomogeneities in Turkish temperature data set. Int J Climatol 18:561–578
Toté C, Patricio D, Boogaard H, van der Wijngaart R, Tarnavsky E, Funk C (2015) Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique. Remote Sens 7(2):1758–1776. https://doi.org/10.3390/rs70201758
Trewin B (2017) WMO guidline on climate normals calculation. World Meteorological Organization, WMO-No. 1203
Vincent LA (1998) A technique for the identification of inhomogeneities in Canadian temperature series. J Clim 11:1094–1104
Woldesenbet TA, Elagib NA, Ribbe L, Heinrich J (2017) Gap filling and homogenization of climatological datasets in the headwater region of the Upper Blue Nile Basin, Ethiopia. Int J Climatol 37(4):2122–2140. https://doi.org/10.1002/joc.4839
Yang S, Wang XL, Wild M (2018) Homogenization and trend analysis of the 1958–2016 in situ surface solar radiation records in China. J Clim 31(11):4529–4541. https://doi.org/10.1175/jcli-d-17-0891.1
Zahradníček P, Rasol D, Cindrić K, Štěpánek P (2014) Homogenization of monthly precipitation time series in Croatia. Int J Climatol 34(14):3671–3682. https://doi.org/10.1002/joc.3934
Zhen L, Zhong-Wei Y, Hong W (2015) Updated homogenized chinese temperature series with physical consistency. 8(1). https://doi.org/10.3878/AOSL20140062
Acknowledgments
The authors would like to thank the National Meteorological Agency of Ethiopia for providing observed rainfall data for the study. The authors would also like to extend their gratitude to the Pan African University Institute of Water and Energy Science (PAUWES), Abou Bakr Belkaid University of Tlemcen, Center for Development Research (ZEF) at University of Bonn and Wollo University for all their support.
Funding
This work has been funded by the German Federal Ministry of Education and Research (BMBF) under Water and Energy Security for Africa (WESA) project with a grant number 01DG16010C.
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Yimer, S.M., Kumar, N., Bouanani, A. et al. Homogenization of daily time series climatological data in the Eastern Nile basin, Ethiopia. Theor Appl Climatol 143, 737–760 (2021). https://doi.org/10.1007/s00704-020-03407-w
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DOI: https://doi.org/10.1007/s00704-020-03407-w