Manuela Grippa

The AMMA Land Surface Model Intercomparison Project (ALMIP)

The rainfall over West Africa has been characterized by extreme variability in the last half-century, with prolonged droughts resulting in humanitarian crises. There is, therefore, an urgent need to better understand and predict the West African monsoon (WAM), because social stability in this region depends to a large degree on water resources. The economies are primarily agrarian, and there are issues related to food security and health. In particular, there is a need to better understand land–atmosphere and hydrological processes over West Africa because of their potential feedbacks with the WAM. This is being addressed through a multiscale modeling approach using an ensemble of land surface models that rely on dedicated satellite-based forcing and land surface parameter products, and data from the African Multidisciplinary Monsoon Analysis (AMMA) observational field campaigns. The AMMA land surface model (LSM) Intercomparison Project (ALMIP) offline, multimodel simulations comprise the equivalent of a multimodel reanalysis product. They currently represent the best estimate of the land surface processes over West Africa from 2004 to 2007. An overview of model intercomparison and evaluation is presented. The far-reaching goal of this effort is to obtain better understanding and prediction of the WAM and the feedbacks with the surface. This can be used to improve water management and agricultural practices over this region.

Rain-Use-Efficiency: What it Tells us about the Conflicting Sahel Greening and Sahelian Paradox

Abstract: Rain Use Efficiency (RUE), defined as Aboveground Net Primary Production (ANPP) divided by rainfall, is increasingly used to diagnose land degradation. Yet, the outcome of RUE monitoring has been much debated since opposite results were found about land degradation in the Sahel region. The debate is fueled by methodological issues, especially when using satellite remote sensing data to estimate ANPP, and by differences in the ecological interpretation. An alternative method which solves part of these issues relies on the residuals of ANPP regressed against rainfall (―ANPP residuals‖). In this paper, we use long-term field observations of herbaceous vegetation mass collected in the Gourma region in Mali together with remote sensing data (GIMMS-3g Normalized Difference Vegetation Index) to estimate ANPP, RUE, and the ANPP residuals, over the period 1984–2010. The residuals as well as RUE do not reveal any trend over time over the Gourma region, implying that vegetation is resilient over that period, when data are aggregated at the Gourma scale. We find no conflict between field-derived and satellite-derived results in terms of trends. The nature (linearity) of the ANPP/rainfall relationship is investigated and is found to have no impact on the RUE and residuals interpretation. However, at odds with a stable RUE, an increased run-off coefficient has

Role of atmospheric circulation with respect to the interannual variability in the date of snow cover disappearance over northern latitudes between 1988 and 2003

[1] This paper analyzes the main spatial patterns in the dates of snow cover disappearance variability over northern latitudes between 1988 and 2003. The dates of snow cover disappearance were calculated using satellite passive microwave data from the Special Sensor Microwave/Imager. Spatial and temporal patterns were obtained using principal components analysis in the S mode. We identified eight components, each representing a large region characterized by homogeneous interannual variability in the dates of snow cover disappearance. We found that atmospheric circulation, summarized by means of teleconnection indices, had an important impact on the date of snow cover disappearance for most of these regions. A role is played by the Arctic Oscillation in western Siberia, the spring east Atlantic/west Russian pattern in central Siberia, and the Pacific North

El Niño–Southern Oscillation influences on the interannual variability of leaf appearance dates in central Siberia

(1) This paper analyses the role of the El Nino-Southern Oscillation (ENSO) on the interannual variability of the leaf appearance dates of boreal forests in the Northern Hemisphere (1982-2004). We find significant negative correlations between the ENSO, quantified by means of the Southern Oscillation Index (SOI), and the leaf appearance dates in central Siberia with up to 9 months lag. The correlations between leaf appearance dates and summer Sea Surface Temperatures (SST) show a pattern that resembles the ENSO phenomena with positive and significant correlations in the East Pacific and negative in the West. These findings are explained by the role of SOI on Sea Level Pressures, 500 hPa Geopotential and the wind flow direction and intensity during the months of leaf appearance (April and May) and on average temperatures, which determine noticeably the date of leaf appearance. Citation: Vicente-Serrano, S. M., N. Delbart, T. Le Toan, and M. Grippa (2006), El Nino - Southern Oscillation influences on the interannual variability of leaf appearance dates in central Siberia, Geophys. Res. Lett., 33, L03707,

Modeling Surface Runoff and Water Fluxes over Contrasted Soils in the Pastoral Sahel: Evaluation of the ALMIP2 Land Surface Models over the Gourma Region in Mali

AbstractLand surface processes play an important role in the West African monsoon variability. In addition, the evolution of hydrological systems in this region, and particularly the increase of surface water and runoff coefficients observed since the 1950s, has had a strong impact on water resources and on the occurrence of floods events. This study addresses results from phase 2 of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project (ALMIP2), carried out to evaluate the capability of different state-of-the-art land surface models to reproduce surface processes at the mesoscale. Evaluation of runoff and water fluxes over the Mali site is carried out through comparison with runoff estimations over endorheic watersheds as well as evapotranspiration (ET) measurements. Three remote-sensing-based ET products [ALEXI, MODIS, and Global Land Evaporation Amsterdam Model (GLEAM)] are also analyzed. It is found that, over deep sandy soils, surface runoff is generally ove...

Analysis of Suspended Particulate Matter and Its Drivers in Sahelian Ponds and Lakes by Remote Sensing (Landsat and MODIS): Gourma Region, Mali

The Sahelian region is characterized by significant variations in precipitation, impacting water quantity and quality. Suspended particulate matter (SPM) dynamics has a significant impact on inland water ecology and water resource management. In-situ data in this region are scarce and, consequently, the environmental factors triggering SPM variability are yet to be understood. This study addresses these issues using remote sensing optical data. Turbidity and SPM of the Agoufou Lake in Sahelian Mali were measured from October 2014 to present, providing a large range of `values (SPM ranging from 106 to 4178 mg/L). These data are compared to satellite reflectance from Landsat (ETM+, OLI) and MODIS (MOD09GQ, MYD09GQ). For each of these sensors, a spectral band in the near infrared region is found to be well suited to retrieve turbidity and SPM, up to very high values (R2 = 0.70) seldom addressed by remote sensing studies. The satellite estimates are then employed to assess the SPM dynamics in the main lakes and ponds of the Gourma region and its links to environmental and anthropogenic factors. The main SPM seasonal peak is observed in the rainy season (June to September) in relation to precipitation and sediment transport. A second important peak occurs during the dry season, highlighting the importance of resuspension mechanisms in maintaining high values of SPM. Three different periods are observed: first, a relatively low winds period in the early dry season, when SPM decreases rapidly due to deposition; then, a period of wind-driven resuspension in January‒March; and lastly, an SPM deposition period in April–May, when the monsoon replaces the winter trade wind. Overall, a significant increase of 27% in SPM values is observed between 2000 and 2016 in the Agoufou Lake. The significant spatio-temporal variability in SPM revealed by this study highlights the importance of high resolution optical sensors for continuous monitoring of water quality in these poorly instrumented regions.

Atmospheric circulation and variability of the vegetation in the Central Siberia (1982-2001)

This paper analyses the spatial distribution of the inter-annual variability of vegetation activity in central Siberia and its relationship with atmospheric circulation variability. We used NOAA-AVHRR NDVI series from Pathfinder Land Data Set at 1 degree of spatial resolution, and we calculated the 81 Cuadernos de Investigacion Geografica 2006 No 32 pp. 81-102 ISSN 0211-6820