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Spatio-temporal variability of vegetation cover over Morocco (1982–2008): linkages with large scale climate and predictability



The dominant patterns of vegetation cover interannual variability over Morocco are isolated using rotated extended empirical orthogonal functions applied to AVHRR NDVI data (1982–2008). The three leading modes capture the NDVI signal at the vegetation peak for three distinct locations: mode 1 (18.7% of total variance) is located along the Atlantic coastline, mode 2 (13.1%) is southwest of the Riff Mountain whilst mode 3 (11.2%) is along the Mediterranean coastline. Correlations between the NDVI time coefficients for the modes ‘Atlantic’ and ‘Mediterranean’ dominated by annuals and precipitation amount during the early stage of the vegetation cycle (NDJ) are found. Significant fluctuations of NDVI time coefficients are isolated: a quasi-biennial signal is present in the three modes and an additional quasi-quadriennial (∼4.4 years) signal is identified for the ‘Atlantic’ mode only. Connection between vegetation activity and atmospheric and oceanic climate signals are sought using time-lag correlation analyses. The NAO during fall-beginning of winter (NDJ) is found to impact vegetation peak for the ‘Atlantic’ mode while the Scandinavian Pattern is related to NDVI peak over the ‘Atlantic’ and ‘Riff’ latter in the season (DJF). A significant connection is also found between vegetation over the ‘Atlantic’ mode and the ‘Riff’ and the ‘Atlantic Niño’ mode leading the SST variability in the equatorial Atlantic with a 6-months lag. Finally, linkages between NDVI and climate information are used to build a seasonal prediction model for NDVI using multiple linear regression. The NDVI anomalies during March–April may be predicted with a reasonable accuracy from January with 79% of explained variance, 60% and 72% for the ‘Atlantic’, the ‘Riff’ and the ‘Mediterranean’ regions, respectively. Results have (1) direct impacts for a better understanding of the role of large-scale climate signals on vegetation cover over Morocco and (2) contribute to the implementation of an agricultural early warning system.