Remotely sensed optical data are fundamental to be integrated into biogeochemical models, since the key role of the optical properties on lower trophic dynamics. In this paper, it is shown how ocean optics satellite products are used to constrain the optical algorithm adopted in the operational biogeochemical model system MedBFM that produces analyses, forecasts and reanalyses for the Mediterranean Sea biogeochemistry within the European Copernicus Marine Environment Monitoring Service (CMEMS).

Two different data sets of diffuse attenuation coefficients ($K_d$) for downward planar irradiance were used in MedBFM to carry out three 15-year simulations. The first simulation is based on climatological values retrieved with a global algorithm; the second uses an updated, interannually variable product from 4 different sensors, obtained with a regional algorithm specifically developed for the Mediterranean Sea; the third is forced by a climatological data set extracted from the updated algorithm. Differences between the two $K_d$ data sets are evaluated in terms of the adopted/differing remote sensing algorithms, and the impact of the two different optical forcings on the MedBFM model output is quantified, with a specific focus on chlorophyll, also distinguishing the effect of using the interannually variable $K_d$ by the one related to the algorithm upgrade.

The differences between the interannually variable $K_d$ data set and the climatological one amount to 10%, resulting in local variations of chlorophyll vertical profile concentration, larger than 20% in some periods of the year. Noticeable effects are also observed on the along-basin zonal range of deep chlorophyll maximum depths during the simulated period, which increases with the use of the updated $K_d$ data set. In the western Mediterranean, interannual variability of chlorophyll in summer grows up to 40% at 100 m.

Matching-up the updated model outputs with quality-controlled Biogeochemical-Argo floats data of fluorescence-derived chlorophyll results in a small increase of the model skill.

遥感光学数据是整合到生物地球化学模型中的基础，因为光学特性对降低营养动力学起着关键作用。在本文中，展示了如何使用海洋光学卫星产品来约束在操作生物地球化学模型系统MedBFM中采用的光学算法，该模型可对欧洲哥白尼海洋环境监测服务（CMEMS）中的地中海生物地球化学进行分析，预测和再分析。

漫射衰减系数的两个不同数据集（${ķ}_d$向下的平面辐照度在MedBFM中用于进行三个15年的模拟。第一次模拟基于使用全局算法检索的气候值；第二种使用来自4个不同传感器的更新的，年际可变的产品，该产品是通过专门为地中海开发的区域算法获得的；第三个是由从更新算法中提取的气候数据集强迫的。两者之间的差异${ķ}_d$ 根据采用的/不同的遥感算法评估数据集，并量化两种不同的光学强迫对MedBFM模型输出的影响，特别侧重于叶绿素，还区分了使用年际变量的影响 ${ķ}_d$ 由一个与算法升级有关的。

年际变量之间的差异 ${ķ}_d$数据集和气候学数据的总和为10％，导致叶绿素垂直剖面浓度的局部变化，在一年中的某些时期大于20％。在模拟期间，对深叶绿素最大深度的沿盆地区域范围也观察到了明显的影响，随着更新的使用，这种影响增加${ķ}_d$数据集。在地中海西部，夏季叶绿素的年际变化在100 m处增长至40％。

将更新后的模型输出与质量控制的生物地球化学-Argo浮标数据（来自荧光的叶绿素）进行匹配，会导致模型技能的小幅提高。