Abstract
The worldwide variations such as climate crisis and global warming are influencing considerably living species and earth due to their implication in the severity and rate of extreme weather. Thus, the seasonal precipitation prediction is of great importance due to the geographical, geomorphological, and seasonal characteristics of Atlantic and Mediterranean positions showing significant events impacting rainfall. In this research, we present a precipitation forecasting model based on multivariate time series where several factors affect the accuracy performance to mitigate extreme events induced by climate change. The purpose is to study the relationship between several climate variables, including surface pressure, wind speed, relative humidity, corrected precipitation, and temperature range, influencing precipitation and the design of an effective multivariate forecasting model showing the temporal evolution of different climate factors. Additionally, the prediction model was designed using a vector autoregression model and tested on monthly data collected from the NASA portal between 1981 and 2021. The introduced model extracts the variations of the time series characteristics and the interactive relationship of several related variables. We performed the Augmented Dickey-Fuller (ADFuller) test for stationarity and the cointegration causality test. The accuracy of the rainfall forecast model was evaluated using regression metrics, including mean absolute error, mean squared error, and root mean squared error, which showed effectiveness in predicting the monthly rainfall of Morocco. Our results showed a decrease in rainfall and a variation in the aridity index in Morocco between 1981 and 2021, reaching a peak in 1996 with a drought index value of 24.25 (semi-humid climate) and a minimum value in 2017 with an aridity index of 5.57 (arid climate). We conclude that during the twentieth and the beginning of the twenty-first centuries (1981–2021), Morocco experienced a change in climate levels from semi-humid to semi-arid and currently knows arid climate. Our model can capture real-world behavior, providing better forecasting performance, while the choice of the best lag value and the split interval of the time series is a challenging task.
Kaoutar Bargach and Soufiana Mekouar: These authors contributed equally.
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
Battisti, D. S., & Naylor, R. L. (2009). Historical warnings of future food insecurity with unprecedented seasonal heat. Science, 323(5911), 240–244.
Bosilovich, M. G., Lucchesi, R., & Suarez, M. (2015). MERRA-2: File specification. No. GSFC-E-DAA-TN27096.
Craven, B. D., & Islam, S. M. (2011). Ordinary least-squares regression. The SAGE dictionary of quantitative management research, 224–228.
Diks, C., & Panchenko, V. (2006). A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics and Control, 30(9–10), 1647–1669.
Houssa, A. A., Drissi, S., Asehraou, A., Asfers, A., Oubaki, L., & Chraibi, H. (2017). Changements climatiques au Maroc: quels systèmes de culture et quelles biotechnologies pour s'y adapter?. Revue Marocaine des Sciences Agronomiques et Vétérinaires, 5(3).
Hulme, M., Barrow, E. M., Arnell, N. W., Harrison, P. A., Johns, T. C., & Downing, T. E. (1999). Relative impacts of human-induced climate change and natural climate variability. Nature, 397(6721), 688–691.
Ionac, N., Grigore, E., & Constantin, D. (2015). Évaluation des phénomènes de dessèchement et de sécheresse dans la zone continentale du plateau de la Dobroudja du Sud. In XXVIIIe Colloque de l’Association Internationale de Climatologie (pp. 269–274).
Lütkepohl, H. (2013). Vector autoregressive models. Handbook of Research Methods and Applications in Empirical Macroeconomics. 139–164.
Mushtaq, R. (2011). Augmented dickey fuller test. SSRN Electron. J. 1911068. https://doi.org/10.2139/ssrn.1911068
Rifai, N., Khattabi, A., & Rhazi, L. (2014). Impact du changement climatique sur les températures journalières minimales et maximales et les précipitations de la région de Tanger (nord-ouest du Maroc) quantifié à partir d’une méthode de descente d’échelle statistique. VertigO, 14(3): 15474. https://doi.org/10.4000/vertigo.15474
Sakamoto, Y., Ishiguro, M., & Kitagawa, G. (1986). Akaike information criterion statistics. Dordrecht, The Netherlands: D. Reidel, 81(10.5555), 26853.
Woillez, M. N. (2019). Revue de littérature sur le changement climatique au Maroc: observations, projections et impacts. Papiers de recherche, 1–33.
Zivot, E., & Wang J. (2006). Vector autoregressive models for multivariate time series. Modeling financial time series with S-PLUS® (2006): 385–429.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Bargach, K., Mekouar, S. (2024). Statistical Analysis of Climate Variability and Prediction of Rainfall in Morocco. In: Chenchouni, H., et al. Recent Advancements from Aquifers to Skies in Hydrogeology, Geoecology, and Atmospheric Sciences. MedGU 2022. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-47079-0_61
Download citation
DOI: https://doi.org/10.1007/978-3-031-47079-0_61
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-47078-3
Online ISBN: 978-3-031-47079-0
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)