1. ASAR imaging of the coastal upwelling in the Baltic Sea Igor Kozlov* (RSHU), Vladimir Kudryavtsev (RSHU/NIERSC), Johnny Johannessen (NERSC), Bertrand Chapron (IFREMER/RSHU), Inga Dailidienė (KU), Alexander Myasoedov (RSHU)

2. Motivation: Manifestation of SST fronts in SAR imagery is well known phenomena which has been investigated by many authors, see e.g. Askari et al., 1993; Beal et al., 1997; Johannessen et al., 1991; Marmorino et al., 1994; Weissmann et al., 1980. Though the qualitative relation of SAR anomalies to SST anomalies (fronts) is now well known, their quantitative relation and dependence on environmental parameters are poorly established.

3. OBJECTIVE: Assess ASAR capability to image coastal upwelling fronts and to find empirical relation between radar backscatter and SST anomalies SPECIFIC OBJECTIVES: to interpret SAR signatures of coastal upwelling events in the Baltic Sea to identify the governing mechanisms leading to SAR manifestation to evaluate SAR imaging capabilities for SST front detection to find empirical relation between SAR and SST anomalies

4. 2.1 Study site and in situ data Ta and Tw from coastal stations Region of interest: the SE Baltic Sea Data - coastal upwelling in the SE Baltic on 15 July-25 July 2006 - Envisat ASAR images (7 WSM images) supplemented with MODIS SST data - NCEP GFS 0.5 degree wind fields

5. 2.1 Coastal upwelling in the SE Baltic Sea – 16 July 2006

6. 2.2 Coastal upwelling in the SE Baltic Sea - 19 July 2006

7. Upwelling signatures in concurrent MODIS and SAR data The similar correlation between SAR and SST anomalies was observed in all 7 cases. Establishment of a governing mechanism leading toSAR and SST similarity is a subject for following analysis.

8. 2.3 MODEL APPROACH - Geostrophic flow is slowly varying on SST scales. - Passing over SST front stratification of ABL varies leading to spatial change in surface wind stress. - This can be described by classical resistance law for planetary ABL :, where is stratification parameter, and are universal functions. - Then varying surface stress affect surface roughness and thus radar backscatter. It can be expressed in terms of any GMF, e.g. CMOD4 as:, where U 10 is equivalent wind speed for the neutral stratification linked to wind surface stress over SST front as:

9. 2.4.1 Modeling the MABL response on upwelling front INPUT: Geostrophic wind INPUT: MODIS SST OUTPUT: Model surface wind NRCS σ° INPUT Geostr. wind INPUT SST Wind stress, effective U 10 Resistance law

10. 2.4.2 Modeling upwelling manifestation in SAR with CMOD4 Observed NRCS Model NRCS

11. 2.4.2 Modeling upwelling manifestation in SAR with CMOD4

12. Good relation between the modeled and observed NRCS indicates that ABL stratification mechanism is valid. Thus we may anticipate that impact of SST on radar backscatter signal can be parameterized via dimensionless stratification parameter: which accounts for environmental parameters: SST, air temperature and 10-m wind speed.

13. Parameterization: The empirical relationship fit the data quite well. Maximum suppression of the NRCS over cold SST is about -10 dB. Since the underlying physics has no regional restriction, we anticipate that suggested relationship can be applied for other areas and conditions (6) 2.6 Empirical relationship between radar contrast and background wind speed and SST drop across the front.

14. If creterion for reliable SAR detection of SST front is 3 dB, then from this figure we find that SAR imaging of the SST front with Is possible at wind speed thus, SAR imaging of SST front is restricted by low to moderate wind speed conditions. 2.7 When the SAR detection of the SST front is feasible?

15. We found that ABL strat mechanism indeed the main source for the SAR imaging of the SST front. However, numerous small-scale dark features observed inside the larger–scale pattern. This may be caused by impact of surfactants affecting the NRCS through damping of Bragg waves We suggest that accumulation of such surfactants take place In the current convergence zones. 3. Discussion

16. In order to interpret the impact of surfactants on SAR imaging we follow aproach suggested by Kudryavtsev et al (JGR, 2012) for interpretation of SAR signature of mesoscale current. Main idea: Appearance of convergence zone results from interaction of Ekman and SQG current. SQG determined from SST snapshot and Ekman current from SAR derived wind. Determined in such a way convergence zones should indicate location of surfactants accumulation and thus location of dark SAR features. Basic equations: 4. Relation of surfactants to current features After Klein and Hua, 1990 Isern-, 200

17. To calculate the surface current divergence field we used the data of 16 July 2006 - MODIS SST field and the SAR derived wind speed field as input parameters. 4. Effects of surfactants on SAR imaging of upwelling front Apparent qualitative relation between simulated convergence zones and fine structure of ASAR image indicates that they are indeed caused by surface slicks linked to convergence zones.

18. Conclusions ASAR provides valuable information on SST front location We found that MABL stratification mechanism is governing mechanism responsible for SAR imaging of SST front SAR image anomalies depend on dimensionless stratification parameter μ f accounting for SST drop over front and wind speed. Suggested empirical relationship between SAR and SST anomalies can further be used for other studies. In addition a SAR signature of coastal uwelling possesses linear dark features due to presence of surface films. We found that these films are accumulated in the zones of surface current convergence. Thus, the combined effect of the MABL stratification and the effect of the Bragg wave damping by the surfactants accumulating in the surface current convergence produces rather complex SAR signatures of the upper ocean upwelling dynamics in the coastal zone. Support by the Russian Government under Mega-grant No. 11.G34.31.0078 for RSHU is kindly acknowledged.

19. thank you!