Charles-Antoine Guérin

Stéphan T Grilli

Patrick Moran

Annette Grilli

Tania Insua

Tsunami detection by High Frequency Radar using a Time-Correlation Algorithm: performance analysis based on data from a HF radar in British Columbia

A High-Frequency (HF) radar was installed by Ocean Networks Canada in Tofino, BC, to detect tsunamis from far-and near-field sources on the Pacific Ocean side of Vancouver Island; in particular, from seismic sources in the Cascadia Subduction Zone. Based on a classical analysis of the Doppler spectrum, this HF radar can measure ocean surface currents up to a 85-110 km range depending on sea state. However, an inherent limitation of detection of small and short-lived tsunami currents is the conflicting requirement for short integration time and sufficient accuracy (resolution) of the Doppler spectra. This limits a direct tsunami detection typically to shallow water areas over the continental shelf where tsunami currents have become sufficiently strong due to wave shoaling.

 tsunami wave trains and seafloor bathymetry, using data simulated with a radar simulator.

Here, the TCA is for the first time applied to actual radar data measured with the ONC WERA HF radar and numerically modified by a synthetic tsunami current. Using a state-of-the-art long wave model we perform tsunami simulations with realistic source and bathymetry, and combine the resulting currents with the background currents and radar backscattered signal measured by the HF radar system. This combination makes it possible to evaluate the performance of the proposed TCA detection algorithm, based on an experimental rather than numerically simulated, data set of radar signal. Our findings confirm that an actual detection can be achieved beyond the continental shelf, where tsunami currents are small (as low as 5 cm/s), in deeper water than when using an algorithm based on a direct inversion of currents from the measured radar Doppler spectra.

INTRODUCTION

The use of shore-based High Frequency (HF) radars to detect incoming tsunami waves was proposed almost 40 years ago by Barrick (1979) and, more recently, was supported by numerical simulations (see, e.g., [START_REF] Lipa | HF radar detection of tsunamis[END_REF], [START_REF] Heron | Tsunami observations by coastal ocean radar[END_REF], [START_REF] Dzvonkovskaya | Simulation of tsunami signatures in ocean surface current maps measured by HF radar[END_REF], [START_REF] Gurgel | Simulation and detection of tsunami signatures in ocean surface currents measured by HF radar[END_REF] and (Grilli et al., 2016a)), and by HF radar measurements of the Tohoku 2011 tsunami made in Japan [START_REF] Hinata | Propagating tsunami wave and subsequent resonant response signals detected by HF radar in the Kii Channel, Japan[END_REF][START_REF] Lipa | Japan tsunami current flows observed by HF radars on two continents[END_REF][START_REF] Lipa | Tsunami arrival detection with high frequency (HF) radar[END_REF], in Chile ( [START_REF] Dzvonkovskaya | Ocean surface current measurements using HF radar during the 2011 Japan tsunami hitting Chilean coast[END_REF]), and in Hawaii ( [START_REF] Benjamin | The 2011 Tohoku tsunami south of Oahu: high-frequency Doppler radio observations and model simulations of currents[END_REF]). HF radars are routinely used to estimate surface currents based on the analysis of the Doppler spectrum over a grid of radar cells, covering a sweep area of tens to hundreds of kms, and new radars have been installed or existing radar used as a means of detecting tsunami currents as well. To do so, tsunami detection algorithms were proposed (see some of the above studies), based on identifying the oscillatory nature of tsunami currents, in space and/or time in the radar measurements. There are, however, some intrinsic limitations to this detection method. In order to be detectable, the magnitude of the tsunami current should be larger than the threshold of accuracy of the Dopplerbased estimation. This accuracy depends mainly on the radar frequency and integration time used to compute the Doppler spectrum. Estimating small currents requires large integration times, but this is in contradiction with the oscillatory nature of tsunami currents, as a large integration time will cause averaging and significant decrease of these currents, which will become less measurable. Hence, the integration time must remain short enough (up to a few minutes) to avoid averaging out the tsunami induced current, which will reduce the resolution and detection threshold of the Doppler-based methods. In practice, this limits a direct detection of tsunami currents by way of Doppler shifts to the continental shelf where currents have become sufficiently large due to shoaling; hence, this also means small warning times, unless there is a very wide shelf.

Recently, (Grilli et al., 2016a(Grilli et al., ,b, 2017) ) proposed a new detection method, which we refer to as the "Time Correlation Algorithm" (TCA), which does not require inverting Doppler spectra for the currents, but is based on the space-time correlation properties of the radar signal along pre-computed tsunami wave rays. By performing numerical radar and tsunami simulations for both idealized (Grilli et al., 2016a) and realistic [START_REF] Grilli | Algorithms for tsunami detection by high frequency radar: Development and case studies for tsunami impact in british columbia, canada[END_REF][START_REF] Grilli | Tsunami detection by High Frequency Radar beyond the continental shelf: II. Extension of algorithms and validation on realistic case studies[END_REF] seafloor bathymetry, we found that the TCA detection algorithm could be applied beyond the continental shelf, in deeper water, where tsunami currents are small (a few cm/s).

Here, for the first time, we report on the implementation of the TCA using actual measured radar data measured off of the Pacific Ocean side of Vancouver Island (radar deployed at Tofino, BC), together with simulated tsunami currents using a state-of-the-art tsunami propagation model. As it has been customary in other related works, we superimpose the effect of tsunami currents on the measured radar signal by the introduction, in each radar cell, of a phase shift depending on a current memory term (see details below). We show results for a Mw 9.1 far-field seismic source in the Semidi Subduction Zone (SSZ; Fig. 1). The numerical generation of a tsunami for this source was presented elsewhere and we refer to [START_REF] Grilli | Algorithms for tsunami detection by high frequency radar: Development and case studies for tsunami impact in british columbia, canada[END_REF][START_REF] Grilli | Tsunami detection by High Frequency Radar beyond the continental shelf: II. Extension of algorithms and validation on realistic case studies[END_REF] for details.

WERA HF RADAR SYSTEM USED IN THIS WORK

To mitigate the elevated tsunami hazard along the shores of Vancouver Island in British Columbia, Canada, Ocean Networks Canada (ONC) has been developing a Tsunami Early Warning System combining instrument deployment on the seafloor as part of their Neptune Observatory, and a shore-based High-Frequency (HF) radar installed near Tofino (BC) (Fig. 2), which has been operational since April 2016. This WERA HF radar, with carrier frequency f EM = 13.5 MHz, can detect and estimate ocean radial currents up to a 85-110 km range depending on sea state, as the propagation losses increases with sea surface roughness. An example of a typical current map is shown in Fig. 2.

The radar sweep area is outlined in Fig. 4 and is covered by radar cells, within which the received radar signal is averaged. The cells all have a radial length ∆R = 1.5 km and an angular opening ∆φ r = 1 degree in the azimuthal direction; the detection sector of the sweep area is 120 degree, implying that cells are 1.48 km wide at a 85 km range and narrower closer to the radar (cell area: ∆S = R ∆R ∆φ r increases with range). The orientation of the radar array of 12 antennas (275 deg. from N, clockwise; centered at 49 • 4' 24.82" N, 125 • 46' 11.55" W; Fig. 2) is such that one side of the sweep area boundary is nearly parallel to the coastline southeast of Tofino, and the array length (110 m) allows for approximately a 12 degree azimuthal resolution. In the direction finding algorithm, as the radar signal is processed for overlapping angular windows, surface currents are estimated in a larger number of radar cells with a 1 degree azimuthal resolution.

THE TIME-CORRELATION ALGORITHM (TCA)

According to first-order Bragg theory, the complex backscattered signal received at time t for a given radar cell p is of the form:

V q (t) = α + e -2iπ f B t + α -e +2iπ f B t
(1) where α ± are constant complex coefficients function of sea state, range, and radar calibration, and f B = g/(πλ EM ) is the Bragg frequency (λ EM is the electromagnetic wavelength). In the presence of a constant current U, the complex radar signal experiences a Doppler frequency shift f U = -2U/λ EM and is thus multiplied by a complex exponential e 2iπ f U t . For a variable current in time, U(t), the Doppler frequency shift is obtained through the integration of the instantaneous Doppler frequency f U (t) = -2U(t)/λ EM , and the radar time series is multiplied by the complex exponential e iM (t) , where In the presence of a tsunami wave train, we therefore have the modified radar signal:

M(t) = - 4π λ EM t -∞ U(t )dt (2)
V q (t) = α + e -2iπ f B t + α -e +2iπ f B t e iM(t) (3)
The additional phase shift is sometimes referred to as the "memory term", as it integrates the past values of the current. Now, the presence of a tsunami wave train within a given sea state manifests itself as a slowly varying induced orbital current, proportional to the local wave elevation, which propagates with the tsunami phase speed. The main idea underlying the TCA is to take advantage of the unique large scale coherency of this tsunami-induced current, to identify its occurence in the radar signal through its effect on the memory term. As the tsunami wave train propagates over large distances with little deformation, along wave rays and at a known (depth-dependent) phase speed (approximated by c = √ gh, with h the local depth), the induced currents at successive locations along such rays should be strongly correlated. More specifically, we expect the strongest correlation to occur between the current U p (t) at cell p and the time-shifted current U q (t + t pq ) at cell q, where t pq is the tsunami travel time from cell p to cell q. This property carries over the memory term and therefore also to the radar signal itself. The TCA thus calculates correlations of the complex backscattered radar signal time series (V p (t),V q (t + t pq )) received from 2 given cells (p, q), located along the same tsunami ray:

C pq (τ;t) = corr{V p (t + τ -t p ), V q (t -t q )} , ( 4
)
where t p and t q are the travel times from some reference cell p 0 to the cells p and q, respectively, and τ an additional time lag. With this definition, the maximum correlation is expected at τ = 0, that is when the time lag between the two signals is t pq = t qt p . Hence, when a change in pattern of correlations C pq occurs near τ = 0, this indicates that a tsunami is propagating through the radar sweep area. In practice, the ensemble average is obtained through a temporal average with a running time window:

C pq (τ;t) =| 1 T c t+ Tc 2 t-Tc 2 V p (t + τ -t p ) V * q (t -t q ) dt | (5)
with T c the length of the time window, which should be sufficiently large to capture the oscillations of the tsunami current, that is at least one-third to one-half the tsunami dominant period T t .

TSUNAMI SIMULATIONS

Time series of tsunami currents are obtained in each radar cell from results of simulations performed with the state-of-the-art long wave model FUNWAVE-TVD (Shi et al. 2012;Kirby et al. 2013a), by one-way coupling, using nested grids G0, G1, G2, G3 (Fig. 1). Time series of simulated tsunami horizontal currents u t are projected in the radar radial direction R as U tr = u t • R and spatially-averaged over individual radar cells covering the radar sweep area. Here, we only detail results obtained for a M w 9.1 far-field seismic source located in the Semidi Subduction zone (SSZ; Fig. 1), but simulations were also performed for large seismic sources in the Cascade Subduction Zone [START_REF] Insua | Preliminary tsunami hazard assessment in British Columbia, Canada[END_REF]. Figure 5 shows 4 snapshots of the radial tsunami current magnitude computed over the radar sweep area for the SSZ incident tsunami.

Wave rays were computed from a number of assumed incident directions by solving the wave geometric optic equation, and radar cells aligned along selected individual wave rays were identified (Fig. 4).

RADAR TIME SERIES

In earlier work [START_REF] Grilli | Algorithms for tsunami detection by high frequency radar: Development and case studies for tsunami impact in british columbia, canada[END_REF][START_REF] Grilli | Tsunami detection by High Frequency Radar beyond the continental shelf: II. Extension of algorithms and validation on realistic case studies[END_REF], a numerical validation of the TCA detection algorithm was performed for the simulated SSZ tsunami (Figs. 1,4,5), on the basis of numerically simulated radar signals using a radar simulator parameterized using the main characteristics of the actual WERA HF radar system in Tofino. The conclusion was that the TCA algorithm had the potential to detect the incoming tsunami further offshore, in deeper water, than using an algorithm based on currents directly inverted from the Doppler spectra. Despite these encouraging results, no definitive conclusions could be drawn before the TCA algorithm was tested with actual field radar data, which is the object of this paper. Indeed, besides the idealization of the radar signal in the simulator, particularly its decay and SNR with range, the background oceanic currents have also been idealized in this earlier work and ionospheric contamination as well as RFI ignored.

While it is impossible to generate a real tsunami on demand and see its impact on radar data, one can, however, numerically simulate the effect of a synthetic current, including from a tsunami, on a measured radar signal. This technique was already used for instance in [START_REF] Gurgel | Simulation and detection of tsunami signatures in ocean surface currents measured by HF radar[END_REF] to simulate a past tsunami event and simulate the effect it would have produced on actual radar data. If not a definitive assessment of an operational TCA detection algorithm, this approach, which will be pursued here, represents a further step towards a more realistic simulator and a better evaluation of the detection algorithm performance.

To this aim, large amounts of raw signal recorded by the Tofino HF radar system, at a sampling rate ∆t = 0.26 s, were obtained and processed in range and azimuth, using the software developed by Helzel Messtechnik GmbH, to produce time series of the complex backscattered signal V p (t) for each radar cell q (Fig. 4). Within this data, a few complete days of records were processed that represented different oceanic conditions.To simulate the impact of the computed tsunami on the radar data, we multiplied the latter by the complex memory term from Eq. ( 2), i.e.:

V tsu p (t) = V p (t) e iM(t) (6)
To avoid spurious values sometimes observed in the radar signal time series and to equalize their magnitude at different ranges, only the recentered and normalized complex values of the radar signal time series were retained, i.e., we considered signals of the form:

S p (t) = V p (t) -V p V p (t) , S tsu p (t) = V tsu p (t) -V tsu p V tsu p (t) (7)
where V p and V tsu p are the temporal means of the signals (without and with tsunami) in the window of observation. The blue and black solid lines represent the same function computed at 30 min intervals, the red solid line is the difference between these, which departs weakly from zero (marked by dashed black line). A very stable pattern is observed for 4 different reference times (yellowed labels).

Radar signal correlations were calculated based on S tsu p (t) between pairs of cells (p, q) and referred to as C pq (τ;t) and C tsu pq (τ;t), whether computed using the actual radar signal S p , without a tsunami, or the modified signal S tsu p , simulating the presence of a tsunami. In each case, we correlated the signal at radar cell p with that at its Mth neighbor, p + M, for N successive values (that is p = p 0 , p 0 + 1, .., p 0 + N -1). The N resulting correlations were normalized by their maximum and averaged over the N available pairs: A further smoothing in time was finally applied to remove higherfrequency oscillations in average correlation. The function C tsu p 0 ,N,M (τ;t), in the presence of the tsunami, is defined in a similar way as in Eq. ( 8). The mean correlations C 30,6,2 and C tsu 30,6,2 were computed along the 2 tsunami wave rays marked in Fig. 4, using the radar cells numbered 30 to 35 (corresponding to distances/radar ranges from 45 to 52.5 km) and correlating them with neighboring cells 2 up (i.e., cells 37 to 42), using an integration window T c = 900 s and a smoothing window of 120 sec. Several days of radar data corresponding to different meteo-oceanic conditions were tested.

C p 0 ,N,M (τ;t) = 1 N p 0 +N-1 ∑ p=p 0 C p,p+M (τ;t) max τ (C p,p+M (τ;t)) (8)
First, we evaluated the average correlation function C 30,6,2 (τ;t) for the original radar data, using two times series separated by 30 min. Fig. 6 shows an example for a sequence of 25 min of original radar data extracted from day 238. Note that the observed correlation remains very stable in time, when considering the 4 reference times marked on the subplots. Next, we computed the average correlation function C tsu 30,6,2 (τ;t) in the presence of the simulated tsunami, where the first time series of complex radar signal was thus multiplied by the additional phase shift due to the tsunami current memory term (Eq. ( 7)), while the second time series (30 min before tsunami arrival) was kept unchanged. Fig. 7 shows a clear increase of the mean correlation C tsu p 0 ,N,M at the time where the tsunami wave train reaches the radar cells. Again, this is due to the very coherent structure of the memory term across time and space, resulting in a high degree of correlation once the signal has been shifted by the appropriate propagation time between radar cells located along the same wave ray.

By contrast with the idealized case developed in Grilli et al. (2016a,b), where the radar data showed a flat correlation in the absence of the tsunami, here the correlation of the time-shifted radar data, C pq (τ;t) exhibits a strong peak in correlation near the zero time lag, even in the absence of tsunami. This is an artifact of the preexisting cross-correlation of the radar signals simultaneously recorded at neighbor cells, likely due to the broadening of the range cell by the filtering window used for range discrimination in the range finding algorithm processing the raw radar data. This can be seen in Fig. 8, which plots the normalized crosscorrelation of the radar signals calculated different radar cells (here from cells 30 to 36), for different values of M (here 0,2,4,6): A marked peak in correlation is visible, even when the radar cells are far apart. Since the propagation time t pq between neighboring cells is smaller than the integration time used in Eq. ( 4), there is an overlap in the time intervals [t p -T c /2,t p + T c /2] and [t q -T c /2,t q + T c /2], which yields a peak of the correlation at the time lag τ = -t pq . However, even though the time-shifted correlation in Eq. ( 4) is not flat in the absence of the tsunami, the occurrence of the latter manifests itself through a clear increase of the mean correlation C p 0 ,N,M , due to highly correlated structure of the memory term caused by the tsunami current for time-shifted radar cell time series. Hence, tsunami detection is easily achieved, by observing a clear change of pattern of the mean correlation with respect to some reference function. In an operational way, the reference correlation for a given sea state in the absence of tsunami could be simply obtained from the radar signal recorded in the recent past, say, the previous 30 or 60 min of data, in such a way that the sea state and the radar characteristics can be assumed to be quasi-steady while the tsunami wave train has not yet reached the radar cells.

corr{S p (t + τ), S p+M (t)} corr{S p (t), S p (t)} (9)
To further confirm these observations, Fig. 9 shows correlations similar to those computed for day 238 in Fig. 7, computed for another day of data, day 227. In both cases for days 227 and 238, tsunami detection could be achieved at time 1h40 by observing similar changes in pattern of the mean correlation, in the corresponding subplots of Fig. 7 and9 (in fact at 1h40 + 450 s = 1h47 as one should account for the half the integration time window T c = 900 sec). Such tsunami detection would thus take place about 30 min before tsunami arrival at the shore. Note that in using cells 30 to 35, detection was made possible based on the effect on correlation of fairly weak tsunami currents, simulated at the border of In view of on these results, in an operational tsunami detection algorithm based on TCA, a detection criterion could thus be developed based on observing a marked positive difference between, ∆C, between the current time mean correlation C tsu p 0 ,N,M and a reference mean correlation obtained from the recent past (e.g., 30 min earlier), which can be permanently computed and archived. A warning could thus be issued when ∆C increases above a to be defined threshold. For this a thorough statistical analysis based on extensive numerical simulations over a large number of days will be necessary in order to establish a related probability of detection.

It is expected that the detection performance of the algorithm can be improved by considering multiple wave rays and cells, and combining the corresponding correlations in some way. This is an entire new analysis, which remains to be done, but to verify this expectation, Fig. 12 shows the same correlation functions plotted at the same 4 times on day 238 using the wave ray labeled 285 in Fig. 4, rather than ray 225 as before. The continental shelf extends farther along this ray than along the previously considered ray 225 (see Fig. 10) , hence the induced tsunami currents reach a stronger magnitude for larger ranges than in the previous case. We see that detection would again occur at 1h40 min along this ray, based on the correlation threshold criterion.

We now compare the results of the TCA-based detection algorithm with what would be achievable with the same data using the classical de- tection method based on the Doppler spectrum. The range-Doppler maps obtained for the same radar time series along the same ray 225, with tsunami superimposed to the data, are plotted in Fig. 13 for the same 4 reference times, using an integration time of 2 min (note, this small integration time is acceptable considering the new method developed for processing Doppler spectra used here). While small deformations of the Bragg lines are indeed visible at times 1h48 and 1h56, it is difficult to discriminate those from the natural oscillations due to the spatial variations of the background current and not knowing that they are there, one would not be able to identify these and invert for the tsunami currents.

BEYOND THE SHELF DETECTION

We finally tested the sensitivity of the TCA detection algorithm to range, and hence current magnitude, by the farthest radar cells, which are well beyond the continental shelf, with corresponding water depths of 1,000 m or more (Fig. 10). We thus recomputed the same mean correlations as plotted in Figs. 7 and9 for days 238 and 227, using the radar data, with superimposed (weaker) tsunami currents, of cells 40 to 45 combined with cells 42 to 47. Results in Figs. 14 and 15 show the evolution of the mean correlation C tsu 40,6,2 during the propagation time of the tsunami. A small but clear overall increase of this function can still be seen, as the tsunami reaches the selected cells (around 1h40). The lesser values of the contrast ∆C, as compared to the middle range cell case (C tsu 30,6,2 ), could lead to false alarms. However, this correlation jump could be reinforced by considering multiple wave rays, and in any case this could serve to issue an initial warning, to be confirmed once the tsunami reaches the middle cell range, where currents become larger and the correlation contrast becomes higher.

CONCLUSIONS

We tested the TCA algorithm for early tsunami detection proposed and validated in our earlier work purely based on numerical simulations [START_REF] Grilli | Algorithms for tsunami detection by high frequency radar: Development and case studies for tsunami impact in british columbia, canada[END_REF][START_REF] Grilli | Tsunami detection by High Frequency Radar beyond the continental shelf: II. Extension of algorithms and validation on realistic case studies[END_REF], using for the first time actual radar data measured by the ONC WERA HF radar deployed at Tofino, BC, on the Pacific Ocean side of Vancouver Island. The effect of an incoming tsunami (from a M w 9.1 far field seismic tsunami originating in the Semidi Subduction Zone), simulated using a state-of-the-art long wave model, is superimposed onto the experimental HF radar data by way of a current memory term; this method that has been used and validated in HF radar papers published by other groups (e.g. [START_REF] Gurgel | Simulation and detection of tsunami signatures in ocean surface currents measured by HF radar[END_REF]).

A detection method was developed that compares mean correlations of radar signal from various radar cells, time shifted by the tsunami propagation time along precomputed wave rays; a marked increase in the pre-existing correlation (say 30 min in the past) indicates that a tsunami is propagating into the radar sweep area. Results obtained so far are very promising and confirm the predictions made in our earlier work that the TCA algorithm has the potential for detecting a tsunami in deeper water, beyond the continental shelf, where tsunami-induced currents are small (as low as 5 cm/s), than when using an algorithm based on a direct inversion of currents from the measured radar Doppler spectra.

Further tests and improvements are in progress, whose results will be presented at the conference.

Fig. 1 :

 1 Fig. 1: Zoom-in on area of the Pacific Ocean covered by the 2 arc-min grid G0, with initial surface elevation (color scale in meter) of the M w 9.1 SAFRR seismic source in the Semidi Subduction Zone (SSZ); boundaries of nested model grids off of Vancouver Island, BC, are shown as black boxes: G1 (0.6 arc-min), G2 (270 m), and G3 (90 m)

Fig. 2 :

 2 Fig. 2: The ONC WERA HF radar site in Tofino, BC.

Fig. 3 :

 3 Fig. 3: Typical map of radial surface currents measured by the WERA HF radar installed in Tofino, BC, by inversion of the Doppler spectra.

Fig. 4 :

 4 Fig. 4: Footprint of ONC WERA HF radar sweep area off of Tofino, BC, with the marked trace (red solid lines) of 2 wave rays corresponding to tsunami sources originating from the North-West (285) and South-West (225) direction.

  Tsunami propagation times between such cells are computed based on the long wave phase velocity, as a function of the local bathymetry. For the calculation presented here, 2 single rays were selected (labeled by number 225 and 285 in Fig 4). The reference of time (t = 0) corresponds to the initiation of the tsunami wave train at the source. Time is then measured onwards from this initial event. It takes approximatively 2 hours and 20 min for this tsunami to reach the shore of Vancouver Island near Tofino, BC (see Fig 5).

Fig. 5 :

 5 Fig. 5: Snapshot of tsunami radial current signed magnitude U tr , simulated for the SSZ far-field seismic tsunami (Fig. 1) in the radar sweep area (color scale is in m/s). Yellowed numbers indicate propagation times from the tsunami source.

Fig. 6 :

 6 Fig.6: Mean correlation C 30,6,2 calculated along wave ray 225 (Fig.4) for original radar data from day 238 (i.e., in the absence of a tsunami). The blue and black solid lines represent the same function computed at 30 min intervals, the red solid line is the difference between these, which departs weakly from zero (marked by dashed black line). A very stable pattern is observed for 4 different reference times (yellowed labels).

Fig. 7 :

 7 Fig.7: Mean correlation calculated along wave ray 225 (Fig.4) for day 238, C 30,6,2 (blue solid line) original data 30 min before tsunami arrival, and C tsu 30,6,2 (black solid line), with tsunami superimposed on the radar data; 6 pairs of radar cells in the middle range (30-35 combined with 32-37) were used. The difference correlation (red solid line) clearly increases above some positive threshold as the tsunami wave train reaches the radar cells.

Fig. 8 :Fig. 9 :

 89 Fig. 8: Self-correlation in time of the radar signal calculated along wave ray 225 (Fig.4), in the absence of a tsunami current, at cell 30 and its cross-correlation with neighboring cells 32, 34 and 36. A marked peak is observed at the zero time lag, even for the farthest apart cells.

Fig. 10 :

 10 Fig. 10: Bathymetry along wave rays 225 (black) and 285 (magenta), used for validating the tsunami detection algorithm. The dashed vertical lines indicate the intervals of radar cells under consideration for middlerange (cells 30-37, red) and far-range (blue) detection.

Fig. 11 :

 11 Fig. 11: Time series of cell-averaged tsunami radial currents (time is measured from the start of the SSZ event), at 6 cells 30 to 35, along wave ray 225 (Fig. 4). In the various curves, a decreasing current magnitude corresponds to an increasing range and hence cell number. The red dashed lines mark the 4 times of observations used in the subplots of Figs. 6, 7 and 9.

Fig. 12 :

 12 Fig.12: Same as Fig.7for ray 285. The change in correlation pattern with and without a tsunami are more drastic due to the stronger tsunami currents along this ray.

Fig. 13 :

 13 Fig. 13: Range-Doppler maps for the same radar data (with superimposed tsunami) as in Fig 8 (day 238), with cell numbers on the vertical axis. A small deformation of the Bragg lines is visible at times 1h48 and 1h56 but is difficult to discriminate from the natural oscillations due to the spatial variations of the background current.

Fig. 14 :

 14 Fig. 14: Mean correlation calculated along wave ray 225 (Fig. 4) for day 238, C 40,6,2 (blue solid line) original data 30 min before tsunami arrival, and C tsu 30,6,2 (blue solid line), with tsunami superimposed on the radar data; 6 pairs of radar cells in the middle range (40-45 combined with 42-47) were used. Even though the difference correlation (red solid line) is small in absolute value, there is a clear increase above some positive threshold as the tsunami wave train reaches the radar cells.

Fig. 15 :

 15 Fig. 15: Same as Fig. 14 for day 227.

Acknowledgements The authors thank the company Helzel Messtechnik GmbH (in particular Dr. A. Dzvonkovskaya) for technical support to process the radar data and Ocean Network Canada for the WERA data and support to the University of Rhode Island to conduct this research. C.-A. Guérin also acknowledges the CNRS, the University of Toulon and the French-American Fulbright commission for supporting his sabbatical leave at URI.


Ms Peggy Drouillet
email: drouillet@vjf.inserm.fr

Ms Monique Kaminski

Ms Blandine De Lauzon-Guillain

Ms Anne Forhan

Pierre Ducimetière

Prof Michel Schweitzer

Prof Guillaume Magnin

Dr Valérie Goua

Dr Olivier Thiébaugeorges

Dr Marie-Aline Charles

Association between maternal seafood consumption before pregnancy and fetal growth: evidence for an association in overweight women. The "EDEN mother-child" cohort (study of pre and early postnatal determinants of the child's development and health)

Keywords: Epidemiology, pregnancy, seafood, birthweight, fetal growth, overweight

Studies, in countries with high seafood consumption, suggested its benefit on fetal growth and child development. The objective of our study was to determine the association between seafood consumption in French pregnant women and fetal growth. Pregnant women included in the EDEN mother-child cohort study completed two food frequency questionnaires on their usual diet in the year before and during the last three months of pregnancy (n=1805). Fetal circumferences were measured by ultrasound, and anthropometry at birth. Variables were compared across tertiles of the mother's seafood consumption by multiple linear regressions adjusted for confounding variables. Analyses were stratified according to maternal overweight because of interaction (p<0.01). As results, there was no association between seafood intake and fetal growth in the whole sample of women. For overweight women (n=464), a higher consumption before pregnancy was associated with higher fetal biparietal and abdominal circumferences and anthropometric measures. From the lowest to the highest tertiles, mean birthweight was 167g higher (p=0.002). No significant association was found with consumption at the end of pregnancy. In conclusion, high seafood consumption before pregnancy is positively associated with fetal growth in overweight women. Follow-up of the infants may help determine potential beneficial consequences for the child's health and development.

INTRODUCTION

A high intake of marine fat rich in long-chain n-3 Fatty Acids (FAs) is associated with an increase in birthweight in humans. [START_REF] Olsen | Intake of marine fat, rich in (n-3)polyunsaturated fatty acids, may increase birthweight by prolonging gestation[END_REF] In both epidemiologic [START_REF] Olsen | Gestational age in relation to marine n-3 fatty acids in maternal erythrocytes: a study of women in the Faroe Islands and Denmark[END_REF][START_REF] Harper | Increased birth weight in northerly islands: is fish consumption a red herring?[END_REF][START_REF] Olsen | Pregnancy duration and the ratio of long-chain n-3 fatty acids to arachidonic acid in erythrocytes from Faroese women[END_REF][START_REF] Olsen | Does fish consumption during pregnancy increase fetal growth? A study of the size of the newborn, placental weight and gestational age in relation to fish consumption during pregnancy[END_REF][START_REF] Olsen | Frequency of seafood intake in pregnancy as a determinant of birth weight: evidence for a dose dependent relationship[END_REF][START_REF] Olsen | Duration of pregnancy in relation to seafood intake during early and mid pregnancy: prospective cohort[END_REF] and intervention studies, [START_REF] Olsen | Randomised controlled trial of effect of fishoil supplementation on pregnancy duration[END_REF][START_REF] Olsen | A possible preventive effect of low-dose fish oil on early delivery and pre-eclampsia: indications from a 50-year-old controlled trial[END_REF][START_REF] Olsen | Fish oil supplementation and duration of pregnancy. A randomized controlled trial[END_REF] mainly performed in women from Denmark and the Faroe Islands, intake of fish or marine n-3 FAs by pregnant women increased birthweight by both prolonging duration of pregnancy and increasing fetal growth rate. Marine fat has been shown to reduce the risk of pre-term delivery [START_REF] Olsen | Randomised clinical trials of fish oil supplementation in high risk pregnancies. Fish Oil Trials In Pregnancy (FOTIP) Team[END_REF][START_REF] Olsen | Low consumption of seafood in early pregnancy as a risk factor for preterm delivery: prospective cohort study[END_REF] and intrauterine growth retardation. [START_REF] Rogers | Maternal fish intake in late pregnancy and the frequency of low birth weight and intrauterine growth retardation in a cohort of British infants[END_REF] Several mechanisms have been suggested for this association. The first one is a delayed spontaneous delivery, resulting from altered balance between the prostaglandins involved in the initiation of labour. [START_REF] Olsen | Intake of marine fat, rich in (n-3)polyunsaturated fatty acids, may increase birthweight by prolonging gestation[END_REF] Indeed n-3

FAs may decrease the endogenous production of arachidonic acid-derived eicosanoids such as prostaglandins PGF 2α and PGE 2 . [START_REF] Hansen | Dietary (n-3)-fatty acids, prostaglandins, and prolonged gestation in humans[END_REF] The second one is an increased fetal growth rate, resulting from improved placental blood flow due to lowered thromboxane/prostacyclin ratio [START_REF] Andersen | Diet, pre-eclampsia, and intrauterine growth retardation[END_REF] and blood viscosity. [START_REF] Olsen | Does fish consumption during pregnancy increase fetal growth? A study of the size of the newborn, placental weight and gestational age in relation to fish consumption during pregnancy[END_REF] Beside birthweight, neonatal head circumference has been positively related to fish intake. In a fishing community, Thorsdottir et al. [START_REF] Thorsdottir | Association of fish and fish liver oil intake in pregnancy with infant size at birth among women of normal weight before pregnancy in a fishing community[END_REF] found that newborns of women consuming less fish and fish oil had a smaller head circumference than those of women consuming higher levels.

Studies from other parts of the world (USA, …) did not find such association between fish consumption and birth size, [START_REF] Buck | Maternal fish consumption and infant birth size and gestation: New York State Angler Cohort Study[END_REF] or even found an inverse relationship between seafood intake during pregnancy and fetal growth. [START_REF] Oken | Associations of seafood and elongated n-3 fatty acid intake with fetal growth and length of gestation: results from a US pregnancy cohort[END_REF] A randomised controlled trial, [START_REF] Knudsen | Fish oil in various doses or flax oil in pregnancy and timing of spontaneous delivery: a randomised controlled trial[END_REF] including women with a low dietary fish intake, did not find any differences in spontaneous delivery between fish oil supplemented and control groups. Thus, the role of maternal seafood consumption on fetal growth remains controversial.

Several studies found relations between maternal body mass index (BMI) and fetal growth (20- 22) and maternal BMI may be associated with difference in food intake. Nevertheless, studies interested in the association between seafood and/or marine n-3 FA and fetal growth did not take into account potential influence of overweight in this relation.

In the context of the well established association between smaller size at birth and adult metabolic and cardiovascular risk, the investigation of nutritional factors potentially affecting fetal growth in humans is warranted. [START_REF] Gunnarsdottir | Size at birth and coronary artery disease in a population with high birth weight[END_REF][START_REF] Gunnarsdottir | Relationship between size at birth and hypertension in a genetically homogeneous population of high birth weight[END_REF][START_REF] Birgisdottir | Size at birth and glucose intolerance in a relatively genetically homogeneous, high-birth weight population[END_REF][START_REF] De Boo | The developmental origins of adult disease (Barker) hypothesis[END_REF] The aim of the present study was therefore to explore the relationship between seafood consumption before and during pregnancy and fetal growth in a French population, with a particular care to the potential effect of maternal overweight on this relation.

METHODS

Population and study design

Pregnant women seen for a prenatal visit at the departments of Obstetrics and Gynaecology of the University Hospitals of Nancy and Poitiers before 24 weeks of amenorrhea (WA) were invited to participate. Enrolment started in 2003 in February in Poitiers and September in Nancy, lasted 27 months in each center and ended up in the inclusion of 2002 women (969 in Poitiers, 1033 in Nancy). Exclusion criteria were twin pregnancies, known diabetes before pregnancy, not being able to speak and read French, planned moving away from the region.

Among women who fulfilled these inclusion criteria, 55% agreed to participate.

The study was approved by the Ethic Committee of the Bicêtre Hospital. Written consents were obtained from the mother for herself at inclusion and for her newborn child after delivery.

Standard ultrasound fetal measurements were recorded from routine examinations performed between 20-24 and 30-34 WA. Measurements included head, biparietal and abdominal circumferences and femur length. All ultrasound examinations were performed by a limited number of specialists who standardised procedures before the study.

At a visit performed between 24-28 WA by midwives research assistants, maternal height was measured with a wall Seca 206 stadiometer (Hamburg, Germany) to the nearest 0.2cm and maternal weight was measured using electronic Terraillon SL 351 scales (Hanson Ltd, UK) to the nearest 0.1kg. Skinfolds were measured using a commercial Harpenden caliper (Chasmor Ltd, London, UK) three times in the following order: tricipital (posterior aspect of the arm, at midpoint between the acromion and the olecranon), bicipital (anterior aspect of the arm, at midpoint between the acromion and the olecranon), subscapular (1cm below the lower angle at the scapula) and supra-iliac (1cm over the iliac crest, at the midaxillary line). After a five minute rest, three measures of systolic and diastolic blood pressures were performed at twominute intervals with an Omron M4I device (Omron Healthcare Europe, Hoofddorp, The Netherlands). Women came to the examination in a fasting state and received a 50g glucose load. Glucose concentrations were measured on fasting and one hour after challenge. Weight before pregnancy, educational level and smoking habits during pregnancy were obtained by interview. Prepregnancy body mass index (pBMI) was computed as reported weight (kg) / measured height squared (m²). According to references of the International Obesity Task Force, overweight was defined as a BMI of 25kg/m² and above and obesity as a BMI of 30kg/m² and above.

A second visit was performed by the same research assistants 1.8 days (range 0-16) after delivery. Mother's weight and skinfolds were obtained with the same protocol as above.

Several anthropometric measurements were performed on the newborn. Circumferences were measured to the nearest 0.1cm in duplicate using a tape: left arm circumference measured at midpoint between the acromion and the olecranon; left wrist circumference measured at the level of the styloid processes of the radius and ulna; head circumference measured at the largest occipitofrontal circumference. Skinfolds were measured in triplicate using a commercial Holtain caliper (Chasmor Ltd, London, UK)) in the following order: tricipital skinfold measured at the same level as the midarm circumference; subscapular skinfold measured at the lower angle of the scapula -It has been shown that in neonates, the sum of skinfolds is well correlated with fat mass as measured by Dual-Energy X-Ray. [START_REF] Koo | Body composition in neonates: relationship between measured and derived anthropometry with dual-energy X-ray absorptiometry measurements[END_REF] Gestational age at delivery (determined from the date of the last menstrual period and early ultrasound assessment), birthweight, recumbent length and weight on the day of the postpartum examination, placental weight (in Poitiers only) were extracted from clinical record. In the two obstetric departments, electronic Seca scales (Hamburg, Germany: Seca 737 in Nancy and Seca 335 in Poitiers) were used to measure infant weight and wooden somatometer (Testut, Béthune, France) to measure length.

Large-and Small-for-gestational age neonates were defined as babies with a birthweight respectively over the 90 th percentile and below the 10 th percentile of French gestational age and gender specific reference curves. [START_REF] Mamelle | Fetal growth from the AUDIPOG study. I. Establishment of reference curves[END_REF] Dietary assessment Mothers completed two food frequency questionnaires (FFQs) similar to the questionnaire developed for the French population in the Fleurbaix-Laventie Ville Santé Study. [START_REF] De Lauzon | The Three-Factor Eating Questionnaire-R18 is able to distinguish among different eating patterns in a general population[END_REF] This FFQ has been validated against a series of 24 hour recalls. [START_REF] Deschamps | Reproducibility and relative validity of a Food Frequency Questionnaire among French adults and adolescents[END_REF] The questionnaire used in the EDEN Study is very close to that of the FLVS Study with the addition of some questions for a more specific assessment of the intake of fish and trophallergic foods, foods rich in folates, n-3 FAs and vitamin A. It inquires about the intake of 137 different foods or food groups with a 7-item scale ranking from never to more than once a day.

The first-trimester FFQ (completed at recruitment) concerned the usual diet during the year before pregnancy; the second FFQ (completed in the first few days following delivery) investigated food intake during the last three months of pregnancy. Six questions inquired about seafood consumption. They were "At which frequency did you eat": 1) fresh or frozen fish (bought unprocessed); 2) oily fish; 3) smoked or salted fish; 4) breaded fish; 5) dishes containing fish; 6) shellfish. We combined responses to the six questions and generated an average frequency of seafood servings per month for each woman, by weighing each frequency with the midpoint of the category (i.e. 2 for the category 1-3 servings/month).

To calculate energy and nutrient intakes, we multiplied, for each food, the intake frequency by the nutrient composition for a portion size. Portion sizes were determined using pictures for 12 food types (meat, French fries, pasta, vegetables, cakes, cheese) on a three level scale or were standard portions for the French adult population for other food types. [START_REF] Su | Portions alimentaires -Manuel photos pour l'estimation des quantités[END_REF] We then summed contributions across all foods to obtain total intake of energy and various macro-and micronutrients. Food composition was obtained from the SU.VI.MAX. nutrient composition database [START_REF] Su | Table de composition des aliments[END_REF] which is based on a French nutrient composition database [START_REF] Favier | Répertoire général des aliments, table de composition[END_REF] and on US department of Agriculture publications; it is continually incremented by other published sources and personal communications from laboratories and manufacturers. [START_REF] Ireland | Répertoire général des aliments, table de composition[END_REF](35)[START_REF] Of | Fatty acids. Supplement to McCance & Woddowson's The Composition of Foods[END_REF] Energy and nutrient intakes were not estimated when more than 3 items of the FFQ were missing.

Moreover, these estimations were not taken into account when total energy intake was under 1000 kcal/day or over 5000 kcal/day.

To study the hypothesis that other food frequently eaten by seafood eaters, could confound the studied relationship, dietary patterns were identified in a principal component analysis performed on the 33 food groups created from the 137 items of the FFQ.

Variable description and statistical analyses

The mean frequency of monthly seafood servings was compared between centers by Student's t test. Relationships between socio-demographic characteristics of women and seafood consumption were studied by linear regressions adjusted for center and mother's age. To study relationships between seafood consumption and fetal growth, we divided women into approximate tertiles according to their average seafood consumption (tertile 1 < once a week / tertile 3 > twice a week) (the number of women reporting no consumption of seafood was too small to be analysed separately. However, analyses were run with and without including these women). Fetal growth was characterized by anthropometric measures at birth and ultrasound measures. Relationships between seafood consumption and these variables were studied by multiple linear regressions adjusted for center, mother's age, smoking habits, height, parity, gestational age, newborn's sex; variables were compared across tertiles of the mother's seafood consumption. Moreover risks of large-and small-for-gestational age newborns were studied according to seafood intake by logistic regression. Separate analyses were performed for seafood intake before pregnancy and during the last three months of pregnancy.

Interaction terms between seafood consumption, before and in the last three months of pregnancy and gestational age (p=0.08 and 0.26 respectively), maternal BMI before pregnancy (p=0.003 and 0.38 respectively), average number of cigarettes smoked per day during pregnancy (p=0.47 and 0.31 respectively) and maternal educational level (p=0.11 and 0.67 respectively) were estimated for birthweight. Several adjustments for educational level, maternal food consumptions (energy and lipid intakes, alcohol intake, dietary pattern, vitamins and/or minerals supplementation), and maternal health (systolic/diastolic arterial pressure, fasting plasma glucose and triglycerides) were also performed.

All analyses were performed with SAS version 9.1 (Cary, N.C., USA).

RESULTS

Subjects characteristics

Data at birth were available for 1896 women out of 2002 included in the study because mainly of women who decided to stop the study, women lost for follow-up and miscarriages or fetal deaths. Analyses included 1805 women who completed the two FFQs and for whom seafood consumption was assessed (67 not included because of at least one missing FFQ, 13 for missing data on seafood consumption). Women for whom time between delivery and clinical exam were spaced from more than 7 days were not included also (n=11). The main characteristics of included women (and their newborns), compared with the 91 excluded ones, are shown in Table 1. Mean maternal age was 29 years (range 17-45), whereas excluded women were slightly younger. This latter group had less often reached a university level and were more often single. Among included women, mean pBMI was 23kg/m², 10.1% had a pBMI < 18.5kg/m², 17.5% were overweight and 8.3% were obese.

Mean birthweight of the offspring of included women was 3284g. The average frequency of seafood intake before pregnancy was 8.5 times/month. The most frequently consumed fish was white fish (60%). A reduction in the seafood consumption was observed over time falling to 8.2 times/month during the last three months of pregnancy (p=0.09). This was mainly due to a decrease in the intake of shellfish. Sociodemographic characteristics of women and seafood consumption before pregnancy Seafood consumption was higher with age by 13% per decade (p=0.0003). Overweight women ate less seafood than the others (7.9 vs. 8.7 times/month; p=0.05). Women with a university level ate seafood more often than the others (9.0 vs. 7.9 times/month; p=0.001).

Income level was also associated with seafood intake, with a higher consumption for women whose household's income was higher than 3,000 Euros/month compared to women with lower income (9.4 vs. 8.1 times/month; p=0.003). Women living alone ate seafood more often than the others (9.6 vs. 8.4 times/month; p=0.07). Seafood consumption was not significantly lower in women who had smoked at some point of the pregnancy than in women who had never smoked during their pregnancy (p=0.40), but decreased when the number of cigarettes smoked increased (p=0.13). Seafood intake did not differ according to the season when the dietary assessment was made (p=0.58). Seafood and alcohol consumptions were positively associated (p=0.003). Women who were supplemented with vitamins and/or minerals ate seafood more often (9.0 vs. 8.3 times/month; p=0.07).

All these relationships were also observed for seafood consumption during the last three months of pregnancy, except for those with vitamins and mineral supplementation and for alcohol consumption.

Seafood consumption and fetal growth

There was no relationship between seafood intake and newborn anthropometric, as well as ultrasound measures in the whole sample of women (Table 2). However, maternal overweight before pregnancy modified the relationship between seafood consumption and several outcomes (for birthweight and others newborn anthropometric variables: p for interaction < 0.01).

Mean birthweight was significantly greater with higher seafood consumption in overweight women whereas this relation was not observed in non-overweight women (Figure 1). Because maternal overweight was identified as a factor of interaction, results are given separately for women with a pBMI < and > 25kg/m².

In non-overweight women, fetal growth was not associated with seafood consumption prior to pregnancy (Table 3A, Table 4,Table 5); whereas in overweight women, fetal growth was significantly associated with seafood consumption prior to pregnancy. In a first regression model adjusted for confounding variables, seafood consumption was considered with tertiles.

In overweight women, a difference in pre-pregnancy seafood consumption from less than five times to more than nine times/month was associated with on average an increase in birthweight of 5.1%, height of 1.4%, head circumference of 1.3%, arm circumference of 4.4% and wrist circumference of 3.2% (Table 3B). Moreover, the sum of skinfolds was also greater, a mean difference of 8.0% was observed between the two extreme tertiles. After adjustment for maternal educational level or household's income, results remained unchanged: mean birthweight between low and high tertiles of seafood intake was 171 (5.3%) after adjustment for educational level.

A subsequent adjustment for total energy, lipid or alcohol intakes did not change the measures of association (Data not shown). One dietary pattern identified by principal component analysis was characterized by a high intake of fruit, vegetables, whole grain, and seafood and a low intake of food rich in fats and sugar. Spearman correlation between seafood consumption and the score for this pattern derived from the principal component analysis was 0.31 (p<0.0001). This pattern was associated with newborn anthropometry with the same trend as for seafood consumption (data not shown). When the model was adjusted for the pattern score, seafood consumption remained associated with newborn anthropometry whereas the pattern score was no longer significant. Mean birthweight difference between low and high tertiles of seafood intake was 163g (4.8%).

After further adjustments for maternal vitamins and/or minerals supplementation and for systolic or diastolic arterial pressure, fasting plasma glucose and triglycerides (at 6 th month of pregnancy) or number of days between birth and measurements for those not performed at birth these associations remained unchanged: when all these variables were included in the model, the average birthweight difference between the lowest and highest tertiles of seafood consumption was 206g (6.3%), compared to 167g in the model without these additional adjustments (data not shown).

For ultrasound measures (Table 3B), between the first and the third tertiles of seafood consumption, abdominal circumference was 2.2% larger and head circumference 1.2% larger at 20-24 WA. At 30-34 WA, these observations followed the same trend but were not significant. However, similar observation was made for the biparietal diameter with a difference of 1.3% between the two extreme tertiles. No other significant association was found.

Furthermore, risks for large-or small-for-gestational age neonates did not vary according to seafood intake in all women or in non-overweight women (Table 5). In overweight women, the risk for small-for-gestational age neonates increased with decreasing seafood intake (OR=3.23 between tertile 1 and tertile 3, p=0.04), while the risk of large-for-gestational age neonates decreased (OR=0.29, p=0.009).

Results remained unchanged when shellfish were not taken into account, but relationships were less strong. Mean birthweight difference between low and high tertiles was 157g (4.8%; p=0.001). Moreover, when women who reported never consuming seafood were excluded from the analyses, results were unchanged: the increase in BW between the two extreme tertiles of seafood consumption was 170g (5.2%; p=0.002).

No association was found between seafood intake and placental weight or length of gestation (data not shown). No statistically significant associations were found in non-overweight women.

DISCUSSION

In the French "EDEN mother-child" cohort, higher consumption of seafood before pregnancy was associated with greater fetal growth, in overweight women only. This relation included birthweight, height, head, arm and wrist circumferences and sum of skinfolds, with a similar trend for some ultrasound measures. Several other epidemiologic studies have shown that intake of fish or marine n-3 FAs by pregnant women is associated with an increase in birthweight occurring through both an increase in duration of pregnancy and fetal growth rate. [START_REF] Olsen | Duration of pregnancy in relation to seafood intake during early and mid pregnancy: prospective cohort[END_REF][START_REF] Olsen | Consumption of marine n-3 fatty acids during pregnancy as a possible determinant of birth weight. A review of the current epidemiologic evidence[END_REF][START_REF] Olsen | The potential benefits of using fish oil in relation to preterm labor: the case for a randomized controlled trial?[END_REF] An increase in head circumference was also noted by Odent et al. [START_REF] Odent | Prenatal care and sea fish[END_REF] and Thorsdottir et al.. [START_REF] Thorsdottir | Association of fish and fish liver oil intake in pregnancy with infant size at birth among women of normal weight before pregnancy in a fishing community[END_REF] Several previously published studies demonstrated a heavier placenta [START_REF] Olsen | Does fish consumption during pregnancy increase fetal growth? A study of the size of the newborn, placental weight and gestational age in relation to fish consumption during pregnancy[END_REF] and a longer gestation [START_REF] Olsen | Randomised clinical trials of fish oil supplementation in high risk pregnancies. Fish Oil Trials In Pregnancy (FOTIP) Team[END_REF][START_REF] Olsen | Low consumption of seafood in early pregnancy as a risk factor for preterm delivery: prospective cohort study[END_REF] among women who consumed more fish but we did not observe these associations.

However in these studies mainly performed in population with high all fish and shellfish intake, the observation was not limited to overweight women. This may be due to higher seafood consumption than that observed in our study. In the intervention study by Olsen et al. the level of n-3 FA intake was 6.1g/day in the intervention group vs. 2.7g/day in the control group, whereas in our study estimated mean intake was 1.2g/day. Another difference lies in the fact that our study focused on seafood whereas many of the studies were often interested in fish or fish oil intake only. [START_REF] Olsen | Duration of pregnancy in relation to seafood intake during early and mid pregnancy: prospective cohort[END_REF][START_REF] Olsen | Consumption of marine n-3 fatty acids during pregnancy as a possible determinant of birth weight. A review of the current epidemiologic evidence[END_REF][START_REF] Olsen | The potential benefits of using fish oil in relation to preterm labor: the case for a randomized controlled trial?[END_REF] In our study, results were unchanged when shellfish were not taken into account, but relationships were less strong.

Results found in subgroups analyses must be taken with caution because they are more prone to false positive errors. No study reported before an interaction between seafood intake and mother's overweight status for fetal growth. One study found an association between seafood intake and birthweight only in non-smokers. [START_REF] Olsen | Does fish consumption during pregnancy increase fetal growth? A study of the size of the newborn, placental weight and gestational age in relation to fish consumption during pregnancy[END_REF] The interaction with smoking was tested and found non significant in our study. . There may be however some biological explanation for an association stronger with higher mother's fat mass. A regular intake of fish before pregnancy may be associated with variations in the FAs composition stored in the adipose tissue. Overweight women have an enhanced ability to release FAs from adipose tissue to sustain fetal growth. The assumption of a role of stored FAs in the relationship seafood consumption and fetal growth is reinforced by the fact that seafood consumption before pregnancy is more strongly associated with fetal growth than consumption during the last three months of pregnancy. The storage of long chain polyunsaturated FAs and the balance of the n-3 and n-6 families in maternal adipose tissue is of great importance since it is a reserve of these FAs for the developing foetus; [START_REF] Haggarty | Effect of placental function on fatty acid requirements during pregnancy[END_REF][START_REF] Ak | Transport mechanisms for long-chain polyunsaturated fatty acids in the human placenta[END_REF][START_REF] Haggarty | Placental regulation of fatty acid delivery and its effect on fetal growth--a review[END_REF][START_REF] Innis | Essential fatty acid transfer and fetal development[END_REF] they are among the materials required for fetal brain, nervous system and retinal growth. [START_REF] Mccann | Is docosahexaenoic acid, an n-3 long-chain polyunsaturated fatty acid, required for development of normal brain function? An overview of evidence from cognitive and behavioral tests in humans and animals[END_REF] All of the n-6 and n-3 FAs accumulated by the foetus are derived by transfer across the placenta, which is provided with a specific system to ensure this function. Placental FAs transfer involves diffusion as well as membrane and cytosolic FA binding proteins; membrane binding proteins that favour n-6 and n-3 FAs over non-essential FAs and arachidonic and docosahexaenoic acid over linoleic and α-linolenic acid may be important in facilitating placental transfer of the latter longer chain n-6 and n-3 FAs to the fetus. The substrate of the placenta is provided by the maternal diet and the high rate of mobilization from maternal adipose stores.

Our study is not based on a representative sample which may limit the applicability of the results to whole population. Compared to a national perinatal survey performed in 2003 on a representative sample of French women after delivery, [START_REF] Blondel | Trends in perinatal health in metropolitan France between 1995 and 2003: results from the National Perinatal Surveys[END_REF] the 55% of eligible women who agreed to participate in the EDEN study had similar age, proportion of unmarried couples, birthweight of the offspring, prematurity rate but had a higher frequency of university level (53 vs 43 %).

In conclusion, our study shows a relationship between maternal seafood intake and fetal growth in the French population, which seems to be specific to overweight women. We suggest that the enrichment in long chain n-3 FAs in the maternal adipose tissue stored before conception is a possible mediator of this relationship. [START_REF] Olsen | Intake of marine fat, rich in (n-3)polyunsaturated fatty acids, may increase birthweight by prolonging gestation[END_REF] (times/month) 8.5 (7.3) Seafood [START_REF] Olsen | Gestational age in relation to marine n-3 fatty acids in maternal erythrocytes: a study of women in the Faroe Islands and Denmark[END_REF] (times/month) 8.2 (7.4) Total energy intake [START_REF] Olsen | Intake of marine fat, rich in (n-3)polyunsaturated fatty acids, may increase birthweight by prolonging gestation[END_REF] (kcal/d) * 2303.6 (769.5) Total energy intake [START_REF] Olsen | Gestational age in relation to marine n-3 fatty acids in maternal erythrocytes: a study of women in the Faroe Islands and Denmark[END_REF] (kcal/d) * 2376.5 (778.1) Total lipid intake [START_REF] Olsen | Intake of marine fat, rich in (n-3)polyunsaturated fatty acids, may increase birthweight by prolonging gestation[END_REF] (g/d) * 97.7 (39.8) Total lipid intake [START_REF] Olsen | Gestational age in relation to marine n-3 fatty acids in maternal erythrocytes: a study of women in the Faroe Islands and Denmark[END_REF] (g/d) * 104.1 (41.0) Alcohol intake [START_REF] Olsen | Intake of marine fat, rich in (n-3)polyunsaturated fatty acids, may increase birthweight by prolonging gestation[END_REF] (g/d) * 7.6 (15.2) Alcohol intake [START_REF] Olsen | Gestational age in relation to marine n-3 fatty acids in maternal erythrocytes: a study of women in the Faroe Islands and Denmark[END_REF] [START_REF] Olsen | Intake of marine fat, rich in (n-3)polyunsaturated fatty acids, may increase birthweight by prolonging gestation[END_REF] Intakes before pregnancy, [START_REF] Olsen | Gestational age in relation to marine n-3 fatty acids in maternal erythrocytes: a study of women in the Faroe Islands and Denmark[END_REF] Intakes in the last three months of pregnancy * Only for women whom nutrient intakes has been estimated (n=1601) † only in Poitiers (n=832/39)

Figure 1 Birthweight

 1 Figure 1 Mean birthweight and average seafood consumption per week, according to maternal BMI. The EDEN study.

Table 1

 1 Maternal and neonatal characteristics of the cohort (n=1896)

		Mean (SE) or %
		Included	Not included	p (t test)
		(n=1805)	(n=91)
	Mothers
	Age (years)	29.1 (4.9)	27.0 (5.0)	<0.0001
	Height (m)	1.64 (0.06)	1.63 (0.06)	0.15
	Prepregnant BMI (kg/m²)	23.2 (4.5)	23.6 (5.5)	0.42
	Overweight (%)	26.2%	27.6%	0.78
	Centre (% Poitiers)	49.4%	45.1%	0.42
	University Level	53%	42%	0.03
	Income >3000€/month (%)	27.4%	19.8%	0.11
	Multipara	55%	55%	0.97
	Single	7%	14%	0.02
	Smoking during pregnancy	26%	32%	0.21
	Intakes
	Seafood

ACKNOWLEDGMENTS

We are indebted to the participating families, to the midwife research assistants (L Douhaud, S Bedel, B Lortholary, S Gabriel, M Rogeon, M Malinbaum) for data collection and to P Lavoine for checking, coding and data entry.

We acknowledge all the funding sources for the EDEN study: Fondation pour la Recherche Médicale (FRM), French Ministry of Research: IFR program, INSERM Nutrition Research Program, French Ministry of Health Perinatality Program, French Agency for Environment Security (AFFSET), French National Institute for Population Health Surveillance (INVS), Paris-Sud University, French National Institute for Health Education (INPES), Nestlé, Mutuelle Générale de l'Education Nationale (MGEN), French speaking association for the study of diabetes and metabolism (Alfediam), National Agency for Research (ANR non thematic program)

Abbreviations

(p)BMI: (pre-pregnancy) Body Mass Index WA: Weeks of Amenorrhea FFQ(s): Food Frequency Questionnaire(s) FA(s): Fatty Acid(s) 24


Zaynab Guerraou

Sébastien Angelliaume

Charles-Antoine Guérin

MULTIFREQUENCY ANALYSIS OF RADAR SEA CLUTTER DIRECTIONNAL ASYMMETRIES

Keywords: Sea surface, NRCS, directional asymmetry, electromagnetic frequency, polarization

This paper reports the first results inferred from the investigation of sea clutter azimuthal variations and their dependence on the radar electromagnetic frequency. We summarize the results derived from the study of SAR data acquired simultaneously at X-and L-band by ONERA (The French aerospace laboratory) and compare them to results stemming from other experiments in the literature. The conclusions drawn suggest that the azimuthal asymmetry is more pronounced at X than L band, potentially indicating that the directional asymmetry of the NRCS is gradually diminished as the frequency decreases. This seems to entail that the asymmetry is likely associated to the small scales of roughness whose electromagnetic returns are measured at X band and not at L band.

INTRODUCTION

The study and modeling of directional asymmetries can give more insight into ways of improving theories on wind and surface wave coupling in the context of the recovery of geophysical parameters (e.g. for wind vector retrieval applications). More Analyses of these asymmetries are being documented based on measurements acquired using the ever increasing capabilities of airborne and space-borne instruments. The numerous data sets described in the literature show evidence of azimuthal variation of the NRCS at medium grazing angles with different empirical relationships derived to relate the angular variations to the wind and/or wave directions. However, the mechanisms at the origin of these upwind/downwind (UDA) and upwind/crosswind (UCA) observations are far from being fully understood and taken into account by scattering models. One major difficulty in this prospect is deciphering the contributions from short and long scale surface waves to these directional asymmetries. Performing a frequency analysis can provide an indication of the surface roughness scales and features that are likely to drive the azimuthal modulation, depending on wind/wave conditions and geometrical properties. The aim of the work presented herein is to investigate this frequency dependence as derived from ONERA data. The present paper is organized as follows: section 2 provides a brief overview of data having served as a basis for this study. Section 3 then exhibits results of azimuthal variations obtained from the previously described data. Section 4 establishes a comparative study by referring to results drawn from other data in the literature. Section 5 gives conclusions of the work presented herein and opens up perspectives to paired and complementary studies.

ONERA DATA

SETHI is an airborne remote sensing imaging system maintained and operated within ONERA. It integrates a new generation of radar and optronic payloads and can operate over a wide range of frequency bands from UHF-VHF to Xband, including L-band, with long range, very high resolution, polarimetric and interferometric capabilities and spans a wide range of acquisition geometries. SETHI is a pod-based system operating onboard a Falcon 20 Dassault aircraft, which is owned by AvDEF.

Data under analysis for this study have been collected within the framework of the POLLUPROOF campaign during which quad-pol SAR data were acquired at X-and Lband, with a range (across-track) resolution of 0.5 m (bandwidth from 9.6 to 9.9 GHz) and 1.0 m (bandwidth from 1.25 to 1.4 GHz), respectively. Images are processed with an azimuth (along-track) resolution equal to the range resolution at both X-and L-band, which implies an integration time equal to 1.1 s at X-band and 4.1 s at Lband. The instrument noise floor has been estimated using the method proposed in [START_REF] Hajnsek | Inversion of surface parameters from polarimetric SAR[END_REF] and the results are shown in fig. 1. The estimated Noise Equivalent Sigma0 (NESZ) is very low, ranging from around -37 to -50 dB at X-band and from around -51 to -53 dB at L-band, providing a good signal to noise ratio (SNR) over the imaged areas for efficient analysis. Figure 1

RESULTS

To have a complete azimuth scan in the purpose of studying the directional dependency, a circular flight has been performed at a nearly constant incidence angle of 45° at X and L band. This scan corresponds to wind and wave conditions indicated in the first row of table 1. Figure 2 illustrates the variations of the resulting co-polarized and cross-polarized NRCS for this scan with respect to the azimuth angle relative to the wind direction. We recover the commonly observed pattern of a sinusoidal variation with respect to the wind direction: a maximum in the upwind direction, a secondary maximum in the downwind direction and two minima in the crosswind directions. This pattern can be accurately modeled by a truncated Fourier series expansion.

Table 2 summarizes the values of upwind/downwind and upwind/crosswind asymmetries. At X band, the UDA is found to be more pronounced for HH than VV polarization and the trend is slightly reversed for the UCA. The crosspolarized data present a less important azimuthal modulation compared to the co-polarized data. These conclusions are in accordance with the ones drawn from the study of the X band polarimetric dataset in [START_REF] Guerraou | Investigation of Azimuthal Variations From X-Band Medium Grazing-Angle Sea Clutter[END_REF]. These qualitative trends remain the same at L band and we tend to generalize them irrespective of the underlying frequency band. Nevertheless, the discrepancy in the orders of magnitudes of the asymmetries between the two frequency bands is noticeable. Figure 2 and table 2 clearly show that the asymmetries are significantly less important at L band, the difference reaching 2.15 dB (respectively 1.1 dB) in UDA at HH (respectively at VV) and about 5.5 dB in UCA at both HH and VV polarizations. In the upwind and downwind directions, the NRCS at X band is higher than the one at L band, which matches with the experimentally observed and physically modeled trend in the plateau region. However, due to the low azimuthal modulation at L band in contrast to the X band, the crosswind NRCS at X band becomes lower than the one at L band.

DISCUSSION

The previously inferred L band results are consistent with the study carried out by Isoguchi et al. [START_REF] Isoguchi | An L-Band Ocean Geophysical Model Function Derived From PALSAR[END_REF], in which they examine the L band NRCS dependence on ocean surface wind and show that L band measurements present relatively slight azimuthal modulation (1 to 2 dB) at comparable wind speeds of 8 to 10 m/s. Consistent results are deduced from the study undertaken in [START_REF] Unal | The polarizationdependent relation between radar backscatter from the ocean surface and surface wind vector at frequencies between 1 and 18 GHz[END_REF], where it is shown that, at a fixed incidence angle and for mild to moderate wind speeds, the UDA increases with radar frequency. In the same perspective, the results reported by Masuko et al. [START_REF] Masuko | Measurement of microwave backscattering signatures of the ocean surface using X band and Ka band airborne scatterometers[END_REF] exhibit a more pronounced UDA at Ka band compared to X band (1 dB discrepancy) in the vicinity of 50° incidence angle at 9.5m/s wind speed. This seems to corroborate the assumption that short waves that are instantaneously interacting with local winds are apparently the most associated to directional asymmetries. It is also noteworthy that this assumption aligns with Cox and Munk's sun glitter measurements [START_REF] Cox | Measurement of the Roughness of the Sea Surface from Photographs of the Sun's Glitter[END_REF] short-scale surface waves have been damped, the surface azimuthal asymmetry was significantly diminished, thus pointing out the role of small-scale ripples in generating directional asymmetries.

CONCLUSION AND PERSPECTIVES

The first results derived from ONERA data indicate that the directional asymmetries are enhanced as the radar frequency increases. However, a more thorough analysis is needed to confirm this frequency dependence and investigate its behavior with respect to incidence angle and wind speed.

For this purpose the study of other data acquired by ONERA at X and L band at different incidence angles and sea states is underway. Moreover, in parallel to the work on experimental data, attempts to improve the modeling of the asymmetries and better characterize and model their behavior with respect to the frequency are carried out based on NRCS simulations using the GO-SSA scattering model [START_REF] Soriano | A cutoff invariant twoscale model in electromagnetic scattering from sea surfaces[END_REF]. This latter study is beyond the scope of this paper.

Figure 1 :Figure 2 :

 12 Figure 1: Estimations of the NESZ at L (left panel) and X (right panel) bands

  illustrates the noise levels and table 1 provides the ground truth data for this campaign.

	*ONERA (The French Aerospace Lab),	**MIO (UM 110, UTLN/AMU/CNRS/IRD) F-
	Electromagnetism and Radar Department, France	83957 La Garde, France

Table 1 : ground truth data for the experiment.

 1 confirming that, for a slick surface where

	Date	Time (UTC)	Wind speed (m/s)	Wind direction (from-deg)	Wave height (m)	Wave direction (from-deg)
	18 may, 2015	17:00	8	255	0.5	240
	22 may, 2015	13:00	7	315	2	270
	22 may, 2015	16:00	7	315	1.75	270
							HH	VV	HV
							UDA	UCA	UDA	UCA	UDA	UCA
							(DB)	(DB)	(DB)	(DB)	(DB)	(DB)
						X BAND	3.1	7	1.3	7.5	0.8	3.7
						L BAND	0.95	1.9	0.2	2	0.1	1

Table 2 : UCA and UDA asymmetries at X and L band as derived from ONERA data at 45° incidence angle.

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