Jarlan Lionel, Driouech F., Tourre Y., Duchemin Benoît, Bouyssie M., Abaoui J., Ouldbba A., Mokssit A., Chehbouni Abdelghani. (2014). Spatio- temporal variability of vegetation cover over Morocco (1982-2008) : linkages with large scale climate and predictability. International Journal of Climatology, 34 (4), p. 1245-1261. ISSN 0899-8418.
Titre du document
Spatio- temporal variability of vegetation cover over Morocco (1982-2008) : linkages with large scale climate and predictability
Jarlan Lionel, Driouech F., Tourre Y., Duchemin Benoît, Bouyssie M., Abaoui J., Ouldbba A., Mokssit A., Chehbouni Abdelghani
Source
International Journal of Climatology, 2014,
34 (4), p. 1245-1261 ISSN 0899-8418
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 (approximate to 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 Nino' 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.
Plan de classement
Sciences du milieu [021]
;
Etudes, transformation, conservation du milieu naturel [082]
;
Télédétection [126]
