Observations of the last century are considered to investigate the decadal scale Pacific/North Atlantic teleconnections. By using wavelet analysis we find a significant low‐frequency coherency between major indices of climate variability. In particular, at periods between 10 and 20 yr, the North Atlantic Oscillation (NAO) tends to be out of phase with the El Niño/Southern Oscillation (ENSO) (strong Icelandic low during La Niña) and the Pacific Decadal Oscillation (PDO), but in phase with the North Pacific Index (NPI). Hence, the Icelandic low is strong during La Niña, but the Aleutian low is weak. The band‐pass SST pattern shows a close relationship between the “decadal‐ENSO” mode in the Pacific and the sea surface temperature anomaly tripole in the Atlantic, consistent with the low‐frequency global teleconnections. The spatial sea level patterns corresponding to the band‐pass filtered indices suggest that the Aleutian‐Icelandic Low seesaw is a main interbasin link on decadal time scale, consistent with the larger coherency of the NPI with the NAO than with ENSO.

Three multivariate statistical methods to estimate the influence of SST or boundary forcing on the atmosphere are discussed. Lagged maximum covariance analysis (MCA) maximizes the covariance between the atmosphere and prior SST, thus favoring large responses and dominant SST patterns. However, it does not take into account the possible SST evolution during the time lag. To correctly represent the relation between forcing and response, a new SST correction is introduced. The singular value decomposition (SVD) of generalized equilibrium feedback assessment (GEFA-SVD) identifies in a truncated SST space the optimal SST patterns for forcing the atmosphere, independently of the SST amplitude; hence it may not detect a large response. A new method based on GEFA, named maximum response estimation (MRE), is devised to estimate the largest boundary-forced atmospheric signal. The methods are compared using synthetic data with known properties and observed North Atlantic monthly anomaly data. The synthetic data shows that the MCA is generally robust and essentially unbiased. GEFA-SVD is less robust and sensitive to the truncation. MRE is less sensitive to truncation and nearly as robust as MCA, providing the closest approximation to the largest true response to the sample SST. To analyze the observations, a 2-month delay in the atmospheric response is assumed based on recent studies. The delay strongly affects GEFA-SVD and MRE, and it is key to obtaining consistent results between MCA and MRE. The MCA and MRE confirm that the dominant atmospheric signal is the NAO-like response to North Atlantic horseshoe SST anomalies. When the atmosphere is considered in early winter, the response is strongest and MCA most powerful. With all months of the year, MRE provides the most significant results. GEFA-SVD yields SST patterns and NAO-like atmospheric responses that depend on lag and truncation, thus lacking robustness. When SST leads by 1 month, a significant mode is found by the three methods, but it primarily reflects, or is strongly affected by, atmosphere persistence.

[1] The advanced microwave sounding unit (AMSU) -A and -B sensors provide observations of humidity and temperature that are relevant for meteorological and climate studies. The use of these observations in numerical weather prediction models has increased in the past 10 years because of some improvements in data assimilation. However, an appropriate use of AMSU measurements apart from assimilation context is rather difficult and depends for the most part on how successfully the instrumental characteristics are accounted for. In particular, atmosphere humidity and temperature variations can be completely hidden by features because of the effect of the observation zenith angle. In this paper, 8 years of AMSU-A and -B observations have been corrected from the observations zenith angle effect and have been used to study temperature and humidity variations over West Africa. Comparisons have been made between AMSU observations and selected atmospheric fields from European Centre for Medium-Range Weather Forecasts analyses as well as outgoing longwave radiation estimates. It has been found that observations from AMSU-A channel 5 can be used to monitor the heat low evolution and that AMSU-B observations from channels 3 and 5 are well adapted to study the humidity variations in direct link with the African monsoon from intraseasonal to interannual scales.

The magnitude and time variability of the total volume transport of the Antarctic Circumpolar Current through Drake Passage is a key climatic index, yet still uncertain. We processed ten years of TOPEX/Poseïdon data along two adjacent descending tracks in Drake Passage assuming (following Gille, 1994) that the surface current velocity has a profile structure of double Gaussian jets corresponding respectively to the Subantarctic Front (SAF) and the Polar Front (PF). We seek the location, width and intensity of each jet as a function of time. Results from the two tracks are coherent and show that the time evolution of the flows is well constrained, although the absolute magnitude of the flow is not. Robust conclusions can be drawn using correlations between parameters and spectral analysis of their time evolution. The two front locations are positively correlated (0.68). When the SAF is farther south, it is also wider and has a larger surface transport. When the PF is farther south, it narrows with a smaller surface transport. The two widths are significantly negatively correlated (-0.58) and the maximum velocities are independent (0.08). The surface transports associated with the SAF and PF are strongly anti-correlated (-0.98) so that the variance of total surface transport is much smaller than the variance of the surface transport of each individual front. Spectral peaks for SAF and PF surface transports are, in order of decreasing amplitude, less than 4 months, semi-annual, 2.6 years and annual. The total surface transport variations are distributed into two broad bands (less than 4 months-the most energetic-and from 0.5 to 3 years)