Advisors: Anna Brooke and Haim Kutiel

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1 STSM report - Gulf Of Lyon Sea Surface Temperature anomalies and heavy precipitation events in the Cévennes- Vivarais region By Lotem Robins, University of Haifa Advisors: Anna Brooke and Haim Kutiel Hosting institution: Mercator Ocean Advisors at hosting institution: Marie Drévillon, Jonathan Beuvier, Charly Régnier Introduction: Heavy rain events (HPE) occur frequently at the southern regions of France. Those HPE might lead to a loss of human- life and economic damage. A region in southern France that suffers from severe HPE is the Cevennes- Vivarais region (CV). On a global scale, the HPE events in the CV are related to a North Atlantic atmospheric circulation pattern, the strong cyclonic westerly flow (CSW), which is characterized by a deep low above the English Channel, at the 500hpa, and south westerly winds above western Europe (Ricard et al., 2012). At meso- scale, low level southerly winds from the Mediterranean advect warm and moist air towards the Massif Central, which result in maximum potential energy, due to topographic change (Berthou et al., 2014). Different studies tried to show the influence of Sea Surface Temperature (SST) on the floods occurrence, intensity and spatial distribution. A significant correlation with SST anomalies in the western Mediterranean during the autumn season is shown by Berthou et al. (2014 ), and it is related to preceding strong winds coming from a northerly direction (Mistral and Tramontane). Lebeaupin Brossier, Ducrocq and Girdani (2008), explain that HPE events in the northwestern Mediterranean basin are most often characterized by a moderate to intense low level, on- shore jet stream, that transpose air masses warmed and moistened by the Mediterranean Sea. The sea and the atmosphere exchange energy at their interface, and the SST, as a proxy for oceanic mixed layer temperature, and together with low

2 level atmospheric variables, are key variables to understand these energy exchanges. The spatial distribution of the rain is discussed in Berthou et al., (2015) which claims, that the change of the precipitation location is related to a shift of the winds, due to both topographic and oceanic effects. First there is the enhanced blocking effect of the Alps, and second, a surface pressure anomaly with stronger stratification on the western side of the coastal front is largely related to SST variations. A closer look at the Gulf of Lyon (GOL) will show the main oceanographic features at play. A cyclonic circulation, generating a doming structured patch of colder water is present at the surface at a 100 km scale (Marshall and Schott, 1999). This cyclonic circulation can be characterized by three main features: The Northern Current Flows southwestward throughout the year along the continental slope, the current surface is most of the time wide (~40 km) and shallow, except from late January until the middle of March, when it becomes narrower and deeper and tends to flow closer to the slope (Alberola, Millot and Font, 1995). Further more, the transport of the Northern current varies between the winter and the summer. Higher transport occurs in the winter, 1.5-2Sv, while a 1Sv transport is recorded in the summer (Pascual and Gomis, 2002). Alberola, Millot and Font (1995) estimate that the Northern current flux reaches its peek in December with a value of ~1.6Sv and gradually decrease until July to ~1Sv. The Balearic front The Balearic basin is a transition region between the Northern current, flowing to the north of the basin, and intense mesoscale eddies, derived from the Algerian current. Near the Balearic Islands, a flow through the sills of recent Atlantic waters, together with deflected flow from the northern current, creates the Balearic current. The later, creates the Balearic front with colder water from the north. The front is made out of recent Atlantic Water from the Balearic current (AW) and old AW, from the Northern current, and so it can be recognized by salinity or temperature. Lopez Garcia et al. (1994) determine that the Balearic density front is at the surface a salinity front, accompanied by thermal differences during the seasons, so that the salinity front should be considered as the front signature. Font et al. (1988, in: Lopez Garcia et al.,1994) estimate an average flux value of 0.5Sv.

3 Pascual and Gomis (2002) suggest a difference between the winter flux of 0.3Sv and the summer flux of 0.6Sv. Fig 1 A schematic of the Balearic basin features. Pascual and Gomis, The Winter Convective Cell Deep water unique formation that transport water from the deepest layer of the ocean, up to the surface. The main cyclonic circulation described before, is essential for the occurrence of this deep cell, and defines a specific area for it. The altimetry of the area called the Rhone fan, together with the cyclonic circulation at surface, causing an upwards movement, as an onset of the deep vertical mixing. Another reason for the deep water cell is the strong northern wind, Tramontane and Mistral, which cool the SST and creates denser water at the upper levels (Leaman and Schott, 1990). Madec et al. (1991) estimate that the deep convective cell begins at December, yet until February the contribution (deflection) to the Northern current and the contribution (deflection) to the Balearic current have the same values.

4 Mercator Ocean has produced a Mediterranean Sea ocean synthesis, called MEDRYS, which gives access to a gridded estimation of the Mediterranean sea temperature, salinity and currents in 3D at relative high resolution (1/12 ) for the period. The object of this report is to take advantage of this dataset, homogeneous and close as possible to ocean observations, to define a statistical relation, during the period , for the months of August until December, between three parameters: The rain intensity at the CV, an indexed value of the main features in the GOL (Northern Current, Balearic Front and the Convective Cell), during a CSW - a defined atmospheric synoptic situation. To summarize, the question is to try to characterize the relationship between the GOL oceanic features and lower atmosphere temperature, on the HPE intensity in the CV. Atmospheric data used, and building of atmospheric indices: In order to determine CSW events the NCEP- NCAR atmospheric reanalysis was used, at the surface level, and at the 500hpa level. Ricard et al. (2012) concluded that the center of a low pressure system is located above the English Channel, at a level of 500hpa. The later location was used for a calculation of a gradient from this center to a westerly point. The same process was made for the Surface level, bringing in consideration that the surface low, should develop to the east of the 500hpa low, because it is a characteristic of a Mid- latitude cyclone. Only values above the 75 th percentile for both levels were considered as CSW patterns, and the results were checked against Ricard et al (2012). In the CV region, a network of rain gauges from was used to determine precipitation intensity, this data was downloaded from the HyMEX data- base. The daily rain data from 463 rain gauges in the area of study (Fig 2), were used to determine an HPE events, that were defined as more than 100 mm per day, at least in two rain gauges in the area of study. The hourly rain data was used to determine the initial phase of the HPE event, which was defined as the hour when the first 10 mm of precipitation was accumulated.

After determining HPE using the rain gauges data, the HPE were filtered according to the CSW pattern, to make sure that the analysis is performed on a well defined atmospheric pressure situation.

5 After determining HPE using the rain gauges data, the HPE were filtered according to the CSW pattern, to make sure that the analysis is performed on a well defined atmospheric pressure situation. The initial time was used to define the date for calculating the index value of the GOL features, and the GOL air temperature minus the SST (air- SST) values. Fig 2 Rain gauges in the area of study. For the air temperature above the GOL, the ALDERA model (atmospheric forcing dataset for the MEDRYS12 ocean reanalysis described below) was used. The ALDERA data set here has the same spatial grid as MEDRYS12, and has a temporal resolution of three hours. Oceanic data used, and building of oceanic indices: For the GOL SST the MEDRYS12 (Hamon, et al. 2015) was used, which is a regional reanalysis of the Mediterranean Sea for the period of The reanalysis is based on the NEMOMED12 model (Beuvier et al.,2012) forced with ALDERA

6 atmospheric forcings, and the SAM2 data assimilation system (Lellouche et al 2013), assimilating jointly in a multivariate way the satellite SST (analyses) and sea level anomalies (along track), and insitu temperature and salinity profiles. The NEMOMED12 configuration covers the whole of the Mediterranean, excluding the black sea, and including a buffer zone from the Atlantic- ocean, in a horizontal resolution of 1/12, which could be converted to 6 to 7.5 km. The time resolution, used from the reanalysis, for this research was daily. An SST index was calculated for each main oceanic feature of the GOL : For the Northern Current a selected point was used considering the continental shelf effect on the current, and the fluctuations of the current. The co- ordinates used are: 5.67E, 42.9N. For the Convective Cell, the reference point was the Lyon buoy, which is used in several studies of the convective cell. Even though the convective cell usually starts to develop at the beginning of December, due its equal effect both on the Northern current and the Balearic current until February, it was not calculated in the final index. The Balearic front was defined by salinity values from MEDRYS12. The front was defined as the maximum value of gradient between two neighbor values, in the Balearic area. SST values were calculated at the front coordinates, and an average was done to get a single value. This process was done for each month separately, owing to the monthly changes of the location of the front. Results: Analysis of the statistical relationship The frequency of the HPE (Fig 3) during the period of study, , at different months, shows that the majority of HPE occur during the months of October and November. Nevertheless, a small amount of HPE occur starting from August.

Fig 3 The distribution of HPE events at the CV area during the period 2000-2011, at the months of interest.

7 Fig 3 The distribution of HPE events at the CV area during the period , at the months of interest. Analyzing the mean SST value of each point of interest in the GOL (Fig 4), by using a monthly average shows that the Balearic front is much warmer then the other two features during the month of August to October, while that during the months of November to December, the values of the all three features are almost equal. If the assumption of a relationship between the three features is correct, than we can separate into two different seasons when the features behave differently, and are possibly linked in a different way. For this reason, the statistical analysis was first conducted solely on the period between August to October.

Fig 4 The differences of SST during the months of research, at the different features in the cyclonic circulation in the GOL. Few steps were done in order to create the SST index.

8 Fig 4 The differences of SST during the months of research, at the different features in the cyclonic circulation in the GOL. Few steps were done in order to create the SST index. The first step, after defining each feature as described before, using the initial time of the HPE calculation, it was possible to determine a SST value for each feature. The second step was to create one value out of the oceanic features that was done by weighting the different transport of water, at Sverdrup, of each oceanic feature. SST!"#$% = 1.3 SST!" SST!" From Fig 5, it is clear that the indexed value of the SST made by the oceanographic features at the GOL, at the two different periods (Aug- Oct, Nov- Dec) differs largely, while Nov- Dec period tends to lower values of the index, the Aug- Oct tends for higher values. The size of the circle is relative to the amount of accumulated rain at the HPE. From the following results it is hard to identify any clear tendency of relation between the other variables.

9 Fig 5 A visualization of the effect of the two periods on the oceanographic features. A linear regression was calculated between the three variables: SST index, air- SST and accumulated rain, using the HPE dates, for accumulated rain and HPE initial time, for calculating the SST index and air- SST, at well defined time (for SST daily resolution and for air- SST 3 hourly resolution). As shown in Fig 6 the R² = , which is a low value, showing a lack of relation between the three variables, when calculated this way. Understanding the effect of each of the independent variables, SST index and air- SST, on the dependent variable, the accumulated rain, is essential for better understanding the reasons for the low value of the R².

10 Fig 6 a 3D linear regression presenting the relation between two independent variables: SST index and air- SST and a dependent variable of accumulated rain. From the two variable regressions it is clear that both of the variables are not correlated to the dependent variable. The SST index coefficient values are the lowest, reaching only 0.09 at the 3 rd polynomial regression, implementing the small effect of the SST indexed oceanographic features on the HPE at the CV. It is possible to explain the low values for few reasons: miss correct weighting based on the Sv of the different features, loss of data by using pointed data and a low number of events. The low values of the air- SST are possible to explain by the mean calculation done on the different values, and a small number of events.

Fig 7 (Top) Two variable regression at different polynomial degrees representing the relation between SST index (independent) and accumulated rain (dependent).

11 Fig 7 (Top) Two variable regression at different polynomial degrees representing the relation between SST index (independent) and accumulated rain (dependent). (Bottom) Two variable regression at different polynomial degrees representing the relation between air- SST (independent) and accumulated rain (dependent). Conclusion: The distribution of the HPE and their occurrence during CSW atmospheric pattern were in agreement with other articles and research at the subject of HPE at the CV. Further more, different articles suggested as well that the majority of HPE southern France occur during October. The difference relations between the three oceanographic features during the different months is well noticed, and implement a general different behavior of the GOL water, during initial time of HPE between August until October and between November- December.

12 On a global scale, it is a physical fact, that the SST is a key variable for the interaction layers between the ocean and the air. On a more regional scale, it was shown in different articles that a complex relation between the ocean mixed layer and the atmospheric boundary layer, occur in the GOL, preceding the HPE events at southern France, and as well at the CV area. The statistical calculation in the following research did not yield the expected results. Low values of the coefficient between the independent variables, SST index and air- SST (separately and together) and the dependent variable, accumulated rain at the CV, determine that several problems occur during the process. The first problem was the indexing of the SST and the averaging of the air- SST, which cost in a big lost of data. If each feature would have been analyze alone, before creating the combined feature. It would have been possible to give a weight for the index according to the coefficient of each feature on the accumulated rain. A second problem was the time resolution, while the ALDERA data was on 3 hourly- resolution, the MEDRYS12 data was on daily resolution, made by a daily average. The last problem is that no model validation was made during the research, which might compensate different biases, at the statistical analysis results. Prospects: A future approach is to use the data of MEDRYS12 to find spatial patterns of SST at the GOL area, before HPE events at the CV. By using this approach it is necessary to validate the model, and that will be done using Soil Moisture and Ocean Salinity Satellite (SMOS) raw data of the GOL area, to validate the model values at the area. The benefit of the following approach is the small amount of lost of data, and retrieving the conclusion based on the data, using more complex statistical analysis tools. Only after finding the results it will be possible to explain them physically.

13 Personal note: The STSM was a great opportunity for me, and I am thankful for taking a part of it. I have gained a lot of knowledge, in the different dimensions, starting from developing human communication skills and friendly working environment to new working tools and deeper understandings of physical processes. I would use this opportunity to thank anyone that was involved. References: Ricard, D., Véronique, D. And Auger, L A Climatology of the Mesoscale Environment Associated with Heavily Precipitating Events over a Northwestern Mediterranean Area. Journal of applied meteorology and climatology, 51: Berthou, S., Mailler, S., Drobinski, P., Arsouze, T., Bastin, S., Béranger, K. And Lebeaupin- Brossier, C Prior history of Mistral and Tramontane winds modulates heavy precipitation events in southern France. Tellus A, 66, 24064, Lebeaupin- Brossier, C., Ducrocq, V. And Giordani, H Sensitivity of three Mediterranean heavy rain events to two different sea surface fluxes parameterizations in high- resolution numerical modeling. Journal of geophysical research, 113, D Berthou, S., Mailler, S., Drobinski, P., Arsouze, T., Bastin, S., Béranger, K. And Lebeaupin- Brossier, C Sensitivity of an intense rain event between atmosphere- only and atmosphere- ocean regional coupled modles: 19 September Q. J. R. Meteorol. Soc., 141: Marshall, J. And Schott F Open- ocean convection: observations, theory and models. Reviews of Geophysics, 37(1): 1-64.

14 Alberola, C., Millot, C. And Font, J On the seasonal and mesoscale variabilities of the Northern Current during the PRIMO- 0 experiment in the western Mediterranean Sea. Oceanologica ACTA, 18(2): Pascual, A. And Gomis, D Use of surface data to estimate geostrophic transport. Journal of atmospheric and oceanic technology, 20: Lopez Garcia, M.j., Millot, C., Font, J. And Garcia- Ladona, E Surface circulation variability in the Balearic Basin. Journal of geophysical research, 99(C2): Leaman, K.D. And Schott, A Hydrographic structure of the convection regime in the gulf of lions: Winter Journal of physical oceanography(21): Madec G., Chartier, M., Delecluse, P. And Crepon, M A Three- Dimensional numerical study of deep water formation in the northwestern Mediterranean sea. Journal of physical oceanography(21): Hamon, M., Beuvier, J., Somot, S., Lellouche, J.M., Greiner E., Jordà, G., Bouin, M.N., Arsouze, T., Béranger, K., Sevault, F., Dubois, C., Drevillon, M. and Drillet, Y Design and validation of MEDRYS, a Mediterranean sea reanalysis over Ocean Science discussions, 12: Beuvier, J., Lebeaupin- Brossier, C., Béranger, K., Arsouze, T., Bourdallé- Badie, R.,Deltel, C.,Drillet, Y., Drobinski, P., Ferry, N., Lyard, F., Sevault, F., and Somot, S MED12, oceanic component for the modeling of the regional Mediterranean Earth System, Mercator Ocean 30 Quaterly Newsletter, 46: NCEP Reanalysis data: NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at HyMEX data: Météo- France the HyMeX database teams (ESPRI/IPSL and SEDOO/Observatoire Midi- Pyrénées

Mediterranean Sea circulation according to the NEMO-MED model : focus on the North-Western Mediterranean Sea

Mediterranean Sea circulation according to the NEMO-MED model : focus on the North-Western Mediterranean Sea Thomas Arsouze, Jonathan Beuvier, Karine Béranger, Samuel Somot, Cindy Lebeaupin-Brossier, Romain