Low‐frequency variability of the tropical Atlantic surface topography: Altimetry and model comparison

Abstract

Altimetric data, climatological hydrological data, and numerical model results are compared over the tropical Atlantic Ocean between November 1986 and November 1988. All reproduce the seasonal cycle of the dynamic topography rather well, and the agreement is particularly good between altimetry and the primitive equation model. The study of the 1986–1988 period reveals interannual events evidenced by both the altimetry and the models, especially during spring 1988 in the Gulf of Guinea.

Upper equatorial Atlantic variability during 2002 and 2005 associated with equatorial Kelvin waves

“…In order to investigate the equatorial Kelvin waves in a basin‐wide context, the available satellite observations of SSHs are now considered in detail. Figure 5 illustrates apparent eastward propagating SSH anomalies along the equator which are superimposed on a strong seasonal cycle [see e.g., Arnault et al , 1992; Schouten et al , 2005]. The SSH anomalies also mirror the general features of the boreal summer extreme events as shown in Figure 1a, with prevailing positive (negative) values in the cold tongue region during warm (cold) events [see e.g., França et al , 2003].…”

“…Substantial progress in the description of equatorial waves has been made with the availability of altimeter measurements: First attempts to fit meridional equatorial wave modes to altimetric sea surface height (SSH) data took place in the Pacific to investigate the ENSO phenomenon [e.g., Delcroix et al , 1991]. In the Atlantic, equatorial waves and their seasonal timescales have been described at an early stage from altimeter measurements [e.g., Arnault et al , 1992] while their interannual timescales have only more recently been established by França et al [2003]. In addition, the existence of altimetric data allowed Katz [1997] to further investigate the Kelvin wave signal as observed during the warm event in 1984 [ Katz , 1987].…”

Comparison of TOPEX/POSEIDON altimetry and in situ sea level data at Sao Tome Island, Gulf of Guinea

“…Studying the seasonal variability in the tropical Atlantic from the merged GEOS 3 and Seasat data, M•nard [1988] concluded that the very low amplitude of the seasonal altimetric signal in the Gulf of Guinea (_+4 cm instead of _+9 cm) was due to the excessive smoothing which was used to remove the large orbital errors inherent in both altimeters and to accommodate the widely unbalanced space-time distribution of the data. From the analysis of Geosat data, Arnault et al [1992] also observed very low altimetric signals in the Gulf of Guinea, compared to hydrographic and numerical model signals. They discussed the possible causes of this weakness and concluded that the orbit error correction using a low-order polynomial adjustment removes a significant part of the oceanic signal, especially for short ground tracks.…”

Tropical Atlantic sea level variability from Geosat (1985–1989)

“…the long-term observations, though limited to surface topography. Seasat and Geosat altimeter data have been used extensively in the tropical regions; Kelvin and Rossby waves have been tracked along the equatorial Pacific during the 19861987 El Niño [Miller et al, 1988;Delcroix et al, 19911 as well as Legeckis waves [Malarde et al, 1987;Périgaud, 19901. In the Atlantic, altimetric data have been successfully compared with in situ data [Ménard, 1988;Carton and Katz, 1990;Arnaztlt et al, 1992al or with model results [Arnault et al, 1992b;Didden and Schott, 19921. Recently, two new sets of Geosat data have been released by the National Oceanic and Atmospheric Administration (NOAA): crossover difference records (XDRs) from the geodetic mission [Ckeney et al, 1991al and geophysical data records (GDRs) from the exact repeat mission [Cheney et al, 1991bl. Both XDRs and GDRs contain a significantly improved water vapor correction derived from two satellite sensors operating during the Geosat mission: the TIROS operational vertical sounder (TOVS) and the special sensor microwave imager (SSMI).…”