Columnar aerosol properties in a northeastern atlantic site (plymouth united kingdom) by means of ground based skyradiometer data during years 2000-2008.

Between 2000 and 2008, columnar optical and radiative properties were measured at the Plymouth Marine Laboratory (PML), UK (50° 21.95′N, 4° 8.85′W) using an automatic Prede POM01L sun–sky photometer. The database was analyzed for aerosol optical properties using the SKYRAD radiative inversion algorithm and calibrated using the in situ SKYIL calibration method. Retrievals include aerosol optical depth, Ångström wavelength exponent, aerosol volume distribution, refractive index and single scattering albedo. The results show that the Plymouth site is characterized by low values of aerosol optical depth with low variability (0.18 ± 0.08 at 500 nm) and a mean annual Ångström exponent of 1.03 ± 0.21. The annual mean of the single scattering albedo is 0.97, indicative of non-absorbing aerosols. The aerosol properties were classified in terms of air mass back trajectories: the area is mainly affected by Atlantic air masses and the dominant aerosol type is a mixture of maritime particles, present in low burdens with variable size. The maritime air masses were defined by annual mean values for the AOD (at 500 nm) of 0.13–0.14 and a wavelength exponent of 0.96–1.03. Episodic anthropogenic and mineral dust intrusions occasionally occur, but they are sporadic and dilute (AOD at 500 nm about 0.20). Tropical continental air masses were characterized by the highest AOD at 500 nm (0.34) and the lowest wavelength exponent (0.83), although they were the least represented in the analysis.

The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.