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 (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

Assessment of reference evapotranspiration methods in semi-arid regions : can weather forecast data be used as alternate of ground meteorological parameters ?

In this study, the performance of three empirical methods for estimating reference evapotranspiration (ET0): Makkink (Mak) and Priestley-Taylor (PT) (radiation-based) and Hargreaves-Samani (HARG) (temperature-based) were assessed in semi-and regions. The values of ET0 derived using these three methods were compared to those estimated using the reference FAO Penman-Monteith (FAO-PM) method under semi-arid conditions of the Tensift basin (central of Morocco) and the Yaqui Valley (Northwest Mexico). The results showed that the HARG method is the best one to estimate ET0 over both semi-and test sites. Conversely, the performance of the other two empirical methods was poor except under humid conditions. However when the parameters alpha and C-m figurate in the PT and Mak equations are locally calibrated, the performance of these two methods greatly improved. Additionally, this study showed that, when measurements of meteorological parameters needed for estimating ET0 (which are not always available especially in developing countries) are lacking, the climatic data generated with numerical weather prediction models provide an alternative and effective solution to estimate ET0. In this regard, data generated using a weather forecast model (ALADIN) over the Tensift basin showed that the HARG model is the most accurate one for estimating the spatio-temporal variability of ET0