Size-partitioned phytoplankton carbon concentrations retrieved from ocean color data, links to data in netCDF format

Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield - 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

Age and alkenone-derived Holocene sea-surface temperature records of sediment core M40-4-SL78

This Special Issue of The Holocene contains 16 research papers based on a symposium at the 11th International Meeting of the European Union of Geosciences held in Strasbourg in April 2001. The aim of the symposium was a state-of-the-art assessment of empirical studies of postglacial marine and terrestrial climatic archives and their integration with numerical climate models. This editorial places the individual papers in the broader context of natural climate variability and anthropogenic impacts on the global climate system, regional differences in climate between maritime and continental areas, and the need for an improved theoretical basis for understanding the underlying causes of environmental change. The focus of the Special Issue is the dynamic and relatively well-understood climate of the North Atlantic and the European realm, where, in relation to the steepest offshore temperature gradient on Earth, observational data are abundant and many recent advances have been made in climate reconstruction from proxy archives. The editorial also contains a summary and overview of the papers included in the four main sections of the Special Issue, which emphasize: (1) numerical modelling experiments; (2) models of glacier buildup and equilibrium-line altitude; (3) marine and terrestrial proxy records of climatic change; and (4) multiproxy palaeoenvironmental reconstruction of a Portuguese lagoonal system.