Observing and Studying Extreme Low Pressure Events with Altimetry

The ability of altimetry to detect extreme low pressure events and the relationship between sea level pressure and sea level anomalies during extra-tropical depressions have been investigated. Specific altimeter treatments have been developed for tropical cyclones and applied to obtain a relevant along-track sea surface height (SSH) signal: the case of tropical cyclone Isabel is presented here. The S- and C-band measurements are used because they are less impacted by rain than the Ku-band, and new sea state bias (SSB) and wet troposphere corrections are proposed. More accurate strong altimeter wind speeds are computed thanks to the Young algorithm. Ocean signals not related to atmospheric pressure can be removed with accuracy, even within a Near Real Time context, by removing the maps of sea level anomaly (SLA) provided by SSALTO/Duacs. In the case of Extra-Tropical Depressions, the classical altimeter processing can be used. Ocean signal not related to atmospheric pressure is along-track filtered. The sea level pressure (SLP)-SLA relationship is investigated for the North Atlantic, North Pacific and Indian oceans; three regression models are proposed allowing restoring an altimeter SLP with a mean error of 5 hPa if compared to ECMWF or buoys SLP. The analysis of barotropic simulation outputs points out the regional variability of the SLP/Model Sea Level relationship and the wind effects

A new phase in the production of quality-controlled sea level data

Sea level is an essential climate variable (ECV) that has a direct effect on many people through inundations of coastal areas, and it is also a clear indicator of climate changes due to external forcing factors and internal climate variability. Regional patterns of sea level change inform us on ocean circulation variations in response to natural climate modes such as El Niño and the Pacific Decadal Oscillation, and anthropogenic forcing. Comparing numerical climate models to a consistent set of observations enables us to assess the performance of these models and help us to understand and predict these phenomena, and thereby alleviate some of the environmental conditions associated with them. All such studies rely on the existence of long-term consistent high-accuracy datasets of sea level. The Climate Change Initiative (CCI) of the European Space Agency was established in 2010 to provide improved time series of some ECVs, including sea level, with the purpose of providing such data openly to all to enable the widest possible utilisation of such data. Now in its second phase, the Sea Level CCI project (SL_cci) merges data from nine different altimeter missions in a clear, consistent and well-documented manner, selecting the most appropriate satellite orbits and geophysical corrections in order to further reduce the error budget. This paper summarises the corrections required, the provenance of corrections and the evaluation of options that have been adopted for the recently released v2.0 dataset (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). This information enables scientists and other users to clearly understand which corrections have been applied and their effects on the sea level dataset. The overall result of these changes is that the rate of rise of global mean sea level (GMSL) still equates to ∼ 3.2 mm yr−1 during 1992–2015, but there is now greater confidence in this result as the errors associated with several of the corrections have been reduced. Compared with v1.1 of the SL_cci dataset, the new rate of change is 0.2 mm yr−1 less during 1993 to 2001 and 0.2 mm yr−1 higher during 2002 to 2014. Application of new correction models brought a reduction of altimeter crossover variances for most corrections

On the statistical stability of the M2 barotropic and baroclinic tidal characteristics from along-track TOPEX/Poseidon satellite altimetry analysis

International audienceAn along-track analysis of 7 years of TOPEX/Poseidon (T/P) data has been performed on the global ocean over the period 1993-1999. Such long time series allow us to determine the semidiurnal tidal component very accurately, while resolving the aliasing problems, at least for the main tidal wave M2. As already inferred by other authors, this along-track analysis detects the surface signatures of the internal tides signal that maintains coherence with the M2 astronomical forcing. By analyzing the T/P data in different periods of 3 years or more, the stability of the M2 tidal characteristics is demonstrated for the barotropic component as well as for the baroclinic signal observed in the altimetric data. This stability varies with location. For the barotropic component the dispersion of the results as a function of the length and period of analysis is only significant over the areas of ocean mesoscale activity (noise impact) and of large barotropic tidal signal (separating the different components of the tidal signal proves difficult). The baroclinic tidal signal appears to be surprisingly stable over many areas located around strong topographic gradients like submarine ridges. A methodology has been developed to draw a map of these areas. This can be of help for ocean modelers to specify areas of higher vertical mixing associated with internal tidal wave activity and for those who assimilate altimetric data in their models by giving guidance on where to increase the uncertainty of the altimeter data over these areas

Atlas de marée de l'océan global FES2014: conception et performance

International audienc

Article Observing and Studying Extreme Low Pressure Events with

sensor

A new phase in the production of quality-controlled sea level data

Sea level is an essential climate variable (ECV) that has a direct effect on many people through inundations of coastal areas, and it is also a clear indicator of climate changes due to external forcing factors and internal climate variability. Regional patterns of sea level change inform us on ocean circulation variations in response to natural climate modes such as El Niño and the Pacific Decadal Oscillation, and anthropogenic forcing. Comparing numerical climate models to a consistent set of observations enables us to assess the performance of these models and help us to understand and predict these phenomena, and thereby alleviate some of the environmental conditions associated with them. All such studies rely on the existence of long-term consistent high-accuracy datasets of sea level. The Climate Change Initiative (CCI) of the European Space Agency was established in 2010 to provide improved time series of some ECVs, including sea level, with the purpose of providing such data openly to all to enable the widest possible utilisation of such data. Now in its second phase, the Sea Level CCI project (SL_cci) merges data from nine different altimeter missions in a clear, consistent and well-documented manner, selecting the most appropriate satellite orbits and geophysical corrections in order to further reduce the error budget. This paper summarises the corrections required, the provenance of corrections and the evaluation of options that have been adopted for the recently released v2.0 dataset (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). This information enables scientists and other users to clearly understand which corrections have been applied and their effects on the sea level dataset. The overall result of these changes is that the rate of rise of global mean sea level (GMSL) still equates to ∼ 3.2 mm yr−1 during 1992–2015, but there is now greater confidence in this result as the errors associated with several of the corrections have been reduced. Compared with v1.1 of the SL_cci dataset, the new rate of change is 0.2 mm yr−1 less during 1993 to 2001 and 0.2 mm yr−1 higher during 2002 to 2014. Application of new correction models brought a reduction of altimeter crossover variances for most corrections