6533b7d8fe1ef96bd126afb2

RESEARCH PRODUCT

Analysis of the linkages between rainfall and land surface conditions in the West African monsoon through CMAP, ERS-WSC, and NOAA-AVHRR data

Pierre-louis FrisonNathalie PhilipponEric MouginLionel Jarlan

subject

DYNAMICSAtmospheric Science010504 meteorology & atmospheric sciencesAdvanced very-high-resolution radiometerDIFFERENCE VEGETATION INDEX0211 other engineering and technologiesSoil ScienceTIME-SERIES02 engineering and technologyWIND SCATTEROMETER DATAAquatic ScienceOceanographyMonsoonSOIL-MOISTURE01 natural sciencesNormalized Difference Vegetation Index[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsGeochemistry and PetrologyCIRCULATIONSEarth and Planetary Sciences (miscellaneous)[ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces environmentPrecipitation[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentWater contentTEMPERATURE021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesWater Science and TechnologyEcologyMoisturePaleontologyForestry15. Life on landScatterometerVARIABILITYGeophysics13. Climate actionSpace and Planetary ScienceClimatologyPRECIPITATIONSoil waterEnvironmental scienceSAHEL RAINFALL

description

International audience; The European Remote Sensing Wind Scatterometer (ERS-WSC) backscattering coefficient, NOAA Advanced Very High Resolution Radiometer (NOAA-AVHRR) Normalized Difference Vegetation Index (NDVI), and Climate Prediction Center Merged Analysis Precipitation ( CMAP) precipitation data sets are studied over the period August 1991 to December 2000 to document ( 1) the interannual and intra-annual evolutions of vegetation photosynthetic activity and soil-vegetation water content over West Africa and ( 2) their two-way links with precipitation. Over the Sahel, at interannual timescales the strongest relationships between vegetation, soil moisture, and precipitation are observed from July to October and when 1-month lag is considered between the parameters. This delay reflects the vegetation response time to the moisture pulses that follow precipitation events. The high correlation between NDVI and sigma_0 at interannual timescales confirms the importance of vegetation in the backscattering coefficient. However, sigma_0 shows stronger statistical links with precipitation, suggesting that this product contains additional useful information related in particular to upper soil moisture. Over Guinea, large differences are observed between the two remote sensing products, and their relationship with precipitation at interannual timescales is weaker. Sigma_ 0 is significantly linked to precipitation from July to November, whereas NDVI does not show any significant relationship with precipitation. NDVI and sigma_0 serial correlations over the Sahel and Guinea suggest that a 2-month memory usually characterizes vegetation photosynthetic activity and soil-vegetation water content anomalies. However, anomalies disappearance in winter then reappearance in the following spring also suggests an interseason memory held by deep soil moisture reservoirs and deep-rooted plants. A composite analysis reveals that the wettest Sahelian rainy seasons were preceded by positive anomalies of soil-vegetation water content over Guinea from winter to spring. Cross correlations and Granger causality analyses partly relate these winter to spring land surface anomalies to those recorded in precipitation during the previous autumn. Spring soil-vegetation water content anomalies strengthen the meridional gradient of soil-vegetation water content over the subcontinent. This gradient is thought to contribute to the gradient of entropy that drives the West African monsoon.

10.1029/2005jd006394https://hal.archives-ouvertes.fr/hal-00293369/file/2005JD006394.pdf