Abstract
This study provides an overview of the impact of a statistical bias correction based on histogram equalization functions on a set of high resolution climate simulations over the Senegal River Basin. Regarding the future changes of extreme precipitation (greater than 50 mm), the models diverge in predicting heavy rainfall events in the majority of the basin. However, an increase of extreme precipitation is found around the Guinean Highlands. The results show also an increase of dry day’s length and a decrease of wet days spells by all the RCMs, except one model that shows an opposite change of these climate indices. The bias correction affects mainly the magnitude of the climate change signals of extreme precipitation. Changes under the Representative Concentration Pathways (RCP8.5) are the most pronounced with uncorrected data. Bias corrected RCMs data are potentially useful for climate change impact studies over the Senegal River Basin. This study highlights a convergence of all RCMs (except for RCA RCM) in projecting a decrease of wet days and an increase of dry days over the Senegal River Basin.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Vizy, E.K., Cook, K.H.: Mid-twenty-first-century changes in extreme events over Northern and Tropical Africa. J. Clim. 25, 5748–5767 (2012)
Hagemann, S., et al.: Climate change impact on available water resources obtained using multiple global climate and hydrology models. Earth Syst. Dynam. 4, 129–144 (2013). https://doi.org/10.5194/esd-4-129
Giorgi, F., Jones, C., Asrar, G.: Addressing climate information needs at the regional level: the CORDEX framework. World. Meteorol. Org. Bull. 58, 175–183 (2009)
Klutse, N.A.B., Sylla, M.B., Diallo, I., et al.: Daily characteristics of West African summer monsoon precipitation in CORDEX simulations. Theor. Appl. Climatol. 123, 369 (2016). https://doi.org/10.1007/s00704-014-1352-3
Haensler, A., Hagemann, S., Jacob, D.: The role of simulation setup in a long-term high resolution climate change projection for southern African region. Theor. Appl. Climatol. 106, 153–169 (2011). https://doi.org/10.1007/s00704-011-0420-1
van Roosmalen, L., Sonnenborg, T.O., Jensen, K.H., Christensen, J.H.: Comparison of hydrological simulations of climate change using perturbation of observations and distribution-based scaling. Vadose Zone J. 10(1), 136–150 (2011). https://doi.org/10.2136/vzj2010.0112
Ly, M., Traore, S.B., Alhassane, A., Sarr, B.: Evolution of some observed climate extremes in the West African Sahel. Weather Clim. Extremes 1, 19–25 (2013). https://doi.org/10.1016/j.wace.2013.07.005
Faramarzi, M., et al.: Modeling impacts of climate change on freshwater availability in Africa. J. Hydrol. 480, 85–101 (2013)
Sarr, M.A., Zorome, M., Seidou, O., Bryant, C.R., Gachon, P.: Recent trends in selected extreme precipitation indices in Senegal – a change-point approach. J. Hydrol. 505, 326–333 (2013)
Sarr, M., Seidou, O., Tramblay, Y., El Adlouni, S.: Comparison of downscaling methods for mean and extreme precipitation in Senegal. J. Hydrol. Reg. Stud. 4, 369–385 (2015)
McSweeney, C., New, M., Lizcano, G.: UNDP Climate Change Country Profiles: Senegal (2010a). http://country-profiles.geog.ox.ac.uk/. Accessed 24 Feb 2018
McSweeney, C., New, M., Lizcano, G., Lu, X.: The UNDP climate change country profiles improving the accessibility of observed and projected climate information for studies of climate change in developing countries. Bull. Am. Meteor. Soc. 91, 157–166 (2010)
Giraldo Osorio, J.D., García Galiano, S.G.: Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin. Hydrol. Earth Syst. Sci. 15, 3605–3615 (2011). https://doi.org/10.5194/hess-15-3605-2011
Haerter, J.O., Hagemann, S., Moseley, C., Piani, C.: Climate model bias correction and the role of timescales. Hydrol. Earth Syst. Sci. 15, 1065–1079 (2011). www.hydrol-earth-syst-sci.net/15/1065/2011/, http://doi.org/10.5194/hess-15-1065
Hagemann, S., Chen, C., Haerter, J.O., Heinke, J., Gerten, D., Piani, C.: Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models. J. Hydrometeor 12, 556–578 (2011). https://doi.org/10.1175/2011JHM1336.1
Schoetter, R., Hoffmann, P., Rechid, D., Schlünzen, K.H.: Evaluation and bias correction of regional climate model results using model evaluation measures. J. Appl. Meteor. Climatol. 51, 1670–1684 (2012). https://doi.org/10.1175/JAMC-D-11-0161.1
Chen, C., Haerter, J.O., Hagemann, S., Piani, C.: On the contribution of statistical bias correction to the uncertainty in the projected hydrological cycle. Geophys. Res. Letters 38, L20403 (2011)
Dosio, A., Paruolo, P.: Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: evaluation on the present climate. J. Geophys. Res. 116, D16106 (2011). https://doi.org/10.1029/2011JD015934
Piani, C., et al.: Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. J. Hydrol. 395, 199–215 (2010). https://doi.org/10.1016/j.jhydrol.2010.10.024
OMVS: Sdage du fleuve Sénégal, rapport de phase 1: etat des lieux et diagnostic. version finale Decembre, 457 pp. (2009)
Weedon, G.P., Balsamo, G., Bellouin, N., Gomes, S., Best, M.J., Viterbo, P.: The WFDEI meteorological forcing data set: WATCH forcing data methodology applied to ERA-Interim reanalysis data. Water Resour. Res. 50, 7505–7514 (2014). https://doi.org/10.1002/2014WR015638
Mbaye, M.L., Haensler, A., Hagemann, S., Gaye, A.T., Moseley, C., Afouda, A.: Impact of statistical bias correction on the projected climate change signals of the regional climate model REMO over the Senegal River Basin. Int. J. Climatol. 36, 2035–2049 (2016). https://doi.org/10.1002/joc.4478
Baldauf, M.: Stability analysis for linear discretisations of the advection equation with Runge-Kutta time integration. J. Comput. Phys. 227 (2008). https://doi.org/10.1016/j.jcp.2008.03.025
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Weather Rev. 117, 1779–1800 (1989)
Kain, J.S., Fritsch, J.M.: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci. 47, 2784–2802 (1990)
Kain, J.S., Fritsch, J.M.: Convective parameterization for Mesoscale models: the Kain-Fritsch scheme. In: Emanuel, K.A., Raymond, D.J. (eds.) The Representation of Cumulus Convection in Numerical Models. MM, pp. 165–170. American Meteorological Society, Boston, MA (1993). https://doi.org/10.1007/978-1-935704-13-3_16
Acknowledgments
We thank the Laboratoire Physique de l’Atmosphère et de l’Océan (LPAO/ESP/UCAD/SENEGAL) and the Laboratoire d’Océanographie, des Sciences de l’Environnement et du Climat (LOSEC/UFR ST/Physics Department/UASZ/SENEGAL) where this work has been done. Many thanks to Stefan Hagemann, Andreas Haensler, Tobias Stacke and Christopher Moseley for their supports during our stay in Hamburg (Germany).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Mbaye, M.L., Diatta, S., Gaye, A.T. (2018). Climate Change Signals Over Senegal River Basin Using Regional Climate Models of the CORDEX Africa Simulations. In: Kebe, C., Gueye, A., Ndiaye, A., Garba, A. (eds) Innovations and Interdisciplinary Solutions for Underserved Areas. InterSol 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 249. Springer, Cham. https://doi.org/10.1007/978-3-319-98878-8_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-98878-8_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98877-1
Online ISBN: 978-3-319-98878-8
eBook Packages: Computer ScienceComputer Science (R0)