The AMMA-CATCH Gourma observatory site in Mali:
7The experimental strategy includes deployment of a variety of instruments, from local to 8 meso-scale, dedicated to monitoring and documentation of the major variables characterizing 9 the climate forcing, and the spatio-temporal variability of surface processes and state 10 variables such as vegetation mass, leaf area index (LAI), soil moisture and surface fluxes.
11This paper describes the Gourma site, its associated instrumental network and the research 12 activities that have been carried out since 1984. In the AMMA project, emphasis is put on the 13 relations between climate, vegetation and surface fluxes. However, the Gourma site is also 14 important for development and validation of satellite products, mainly due to the existence of 15 large and relatively homogeneous surfaces. The social dimension of the water resource uses 16 and governance is also briefly analyzed, relying on field enquiry and interviews.
18The climate of the Gourma region is semi-arid, daytime air temperatures are always high and
29Land surface in the Gourma is characterized by rapid response to climate variability, strong
Global ocean tide loading charts of the radial displacement, the potential divided by g (gravity acceleration), and the gravity effect have been computed using the 11 constituents M2, S2, N2, K2, K1, O1, P1, Q1, Mf, Mm, Ssa of Schwiderski's tidal model. These new charts have a resolution of 1° × 1° on the continents as well as on the oceanic area. A description of Farrell's convolution method to compute the loading effects is given, and an estimate of the numerical errors leads to the conclusion that these global charts have a precision better than 2.5% independent of the accuracy of Schwiderski's maps. The current approximation of the loading effects by a proportionality relation with the local oceanic tides is also compared with Farrell's convolution method. Departures of several centimeters systematically appear, in particular over the continental shelves. We then show that the maps of the oceanic tides deduced from satellite altimetry could be corrected for the loading effect by an iterative computational procedure based on our algorithm of Farrell's convolution.
Satellite-altimeter data over ice sheets provide the best tool for mapping their topography and its possible climatic variations. However, these data are affected by measurement errors, orbit errors, and slope errors. We develop here a three-step inversion technique which accommodates the a priori information on the expected topography and correctly handles and propagates the data errors: it estimates first a large-scale reference surface, then maps the residuals related to undulations, and finally iteratively corrects the slope error. The method is tested on overlapping small fragments of the Antarctic ice sheet, using a sub-set of Seasat data. Finally, a topographic map of Terre Adélie is produced. Over areas of small slopes, the a posteriori error should be of the order of 0.4 m. Using ERS-I data, it is therefore expected that climatic variations in the ice-sheet topography since the introduction of Seasat will be observable.
The eight leading ocean tides (M2, S2, N2, K2, K1, O1, P1, and Q1) have been mapped in Asian semienclosed seas by inverting combined sets of tide gauge harmonic constants and a reduced set of TOPEX/POSEIDON satellite altimeter data. The tidal maps are given on a 0.5°×0.5° grid with their formal error estimates. Numerical experiments conducted in the South China Sea have shown the inverse solutions to be quite insensitive to changes in the parameters of the a priori covariance functions for both the tidal signals and data residual errors. Once the various parameters of the inversion scheme are fixed, the algorithm is applied to the Sea of Okhotsk, the Sea of Japan, the “East China” Sea (including the Bo Hai and Yellow Seas) and the Indonesian Seas. A set of tide gauge constants, not used in our solutions, is then used for comparison. Though these accuracy estimates may be biased because of the uneven stations coverage, we conclude that the inversion of only 21 cycles of TOPEX/POSEIDON data leads to solutions with an accuracy comparable to the Schwiderski (1980b, c) semiempirical model and the Cartwright and Ray (1990) model derived from Geosat altimetry.
[1] The spatio-temporal evolution of Sahelian vegetation is analyzed using the Normalized Difference Vegetation Index (NDVI) obtained from the NOAA/AVHRR sensor (1982 -2003). Dominant patterns are identified using rotated EOFs. While the first four modes are associated with specific biogeo-climatic conditions in space, significant time scales are detected using a multi-tapers method. Three interannual time scales ($6.2-, 4.5-and 3.6-year) are present in the first and third NDVI modes over the western Sahel. A quasi-biennial time scale ($2.6-year) is present in second and fourth NDVI modes over the northeast Sahel. During summer, significant lagged correlations are found between the NDVI second (9-month lag) and third (10-month lag) modes, the meridional Atlantic Sea Surface Temperature (SST)
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