In this work we focus on the Alboran Sea (western Mediterranean) to relate wind field and ocean velocity variability with chlorophyll

En este trabajo nos centramos en el mar de Alborán (Mediterráneo Occidental) para relacionar los campos de velocidad del viento y del océano con la variabilidad de la clorofila

Ocean primary production is usually controlled by upwelling, entrainment and/or mixing of high nutrient subsurface water into the euphotic zone (

The dynamics of the Alboran Sea area (

We use the ROMS model (

The paper is structured as follows. The next section introduces the methodological approach, specifically detailing the model implementation and the output model data analysis. We then show the results and discuss them in the context of previous studies.

A climatological simulation of the Alboran Sea area was run using the Regional Ocean Model System (ROMS:

The model is forced by a seasonal cycle atmospheric forcing. The air temperature, short-wave radiation, long-wave radiation, precipitation, cloud cover and freshwater flux used to force the model come from ERA-40 reanalysis (

The simulation domain ranges from 5.9°W to 1.48°E zonally and from 33.82°N to 38.88°N meridionally (see

We ran the model using climatological atmospheric forcing and climatological boundary conditions. The initial conditions for starting the simulations were obtained using the same interpolated fields as the ones used for the boundary conditions for all variables. After an 8-year spin-up period, we used the ninth year as the study period.

The regional ROMS implementation has been already tested using satellite and cruise data in previous works (

The model output and associated data analysis have daily time resolution. In order to relate the modelled phytoplankton (Chl

The 20-m layer is expected to capture the essential dynamics of surface ocean properties and also the surface Cha

Second, we split these four fields into an adjusted harmonic signal (annual, semi-annual and quarterly) that we shall call ‘seasonal’ part (

$$\begin{array}{c}y(t)={A}_{a}\mathrm{cos}\left(\frac{2\pi}{365.25}t-{\phi}_{a}\right)+{A}_{sa}\mathrm{cos}\left(\frac{2\pi}{182.63}t-{\phi}_{sa}\right)+\\ +{A}_{q}\mathrm{cos}\left(\frac{2\pi}{91.31}t-{\phi}_{q}\right)\end{array}$$ |

where _{a}, _{as}, _{q}, and _{a}, _{as}, _{q}, are the amplitude and phase of the annual, semi-annual and quarterly cycles. Phases are expressed in days and a zero time lag indicates January 1. After removing the trend, annual and semi-annual cycle for each grid point, the empirical orthogonal functions (EOFs) of each variable are computed. EOFs are calculated using a singular value decomposition of the covariance matrix of data, and retaining as EOFs the eigenvectors associated with non-zero eigenvalues, as is explained in

$$\theta (x,y,t)={\displaystyle \sum _{j-1}^{n}{m}_{j}(x,y){A}_{j}(t)}$$ |

where _{j} corresponds to the j_{th }EOF function and _{j} is its EOF coefficient (EOFt)

The results on the relationships between the seasonal and residual parts of the surface velocity versus the Chl

Chl |
U | V | W | UWi | |||||
---|---|---|---|---|---|---|---|---|---|

EOFt | 1 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | |

Seasonal | Exp. Var. (%) | 82 | 38 | 30 | 43 | 31 | 41 | 29 | 95 |

Corr. with Chl |
–0.2 | 0.79 |
–0.08 | 0.76 |
0.95 |
–0.2 | 0.92 |
||

Residual | Exp. Var. (%) | 30 | 10 | 9 | 11 | 10 | 3 | 3 | 71 |

Corr. with Chl |
0.69 |
0.29 | –0.3 | 0.67 |
0.25 | 0.39 | 0.22 |

Correlations were calculated between Chl

As expected, the eigenvalue spectra of the residual fields (not shown) showed an almost uniform distribution of the explained variance among all the modes (around the 10%). The correlation between the EOFt series of Chl

The coastal upwelling signal was better captured by the seasonal part, while the variance of the residual part was larger off-shore (

The first EOFt of the Chl

The temporal evolution of the first EOFts of both seasonal parts seems to evolve with a time lag in Chl

In

The most correlated EOFt components of the Chl

In this work we have studied the physical mechanisms that can drive Chl

To further analyse these mechanisms, we split the contribution of upwelling-enhanced Chl

Using an EOF analysis we found that while seasonal Chl

The residual part of the three-dimensional velocity field therefore acts as a response to the instabilities or perturbations in the mean structures of the Alboran Sea: the Atlantic Jet, WAG, EAG and AOF. The seasonal component of the variability accounts for these stable structures and the residual component accounts for their short-term variability. In terms of the velocity field, the off-shore transport of the Chl

Our results also quantify the relative contribution of these two time scales, showing that the modelled residual contribution of Chl

The spatial extension of Chl

The main results of this work have shown the importance of the contribution of the horizontal velocity residuals in accounting for the Chl

JS was funded by the Spanish Ministry of Science and Innovation (through the MedEX project CTM2008-04036-E/MAR) and the EU project Marine-Vectors project FP7-KBBE 266445. JS acknowledges a CSIC JAE-Doc contract co-funded by the FSE. We also wish to acknowledge the useful comments of Manuel Vargas and one anonymous referee, which helped to improve the manuscript.