Navigation and meteorological data during campaign TARA_20091011Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20111124Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20120314Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20090913Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20100108Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20100214Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20100302Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20100309Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) was a global survey of ocean ecosystems aboard the Sailing Vessel Tara. It carried out extensive measurements of environmental conditions and collected plankton (viruses, bacteria, protists and metazoans) for later analysis using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data publication provides permanent links to original and updated versions of validated data files containing navigation and meteorological data collected during the entire Tara Oceans Expedition (2009-2013).

Climate forecast data (Nino3.4 SST, Arctic sea ice extent) and observational references, link to files in Rdata format

This data set contains seasonal forecasts of sea surface temperature and Arctic sea ice extent from state-of-the-art climate models, along with observational references used to evaluate those forecasts. Common skill scores like the correlation between modelled and observed time series are also reported.

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.

Biogeochemical data from terrestrial and aquatic ecosystems in a periglacial catchment, West Greenland

Global warming is expected to be most pronounced in the Arctic where permafrost thaw and release of old carbon may provide an important feedback mechanism to the climate system. To better understand and predict climate effects and feedbacks on the cycling of elements within and between ecosystems in northern latitude landscapes, a thorough understanding of the processes related to transport and cycling of elements is required. A fundamental requirement to reach a better process understanding is to have access to high-quality empirical data on chemical concentrations and biotic properties for a wide range of ecosystem domains and functional units (abiotic and biotic pools). The aim of this study is therefore to make one of the most extensive field data sets from a periglacial catchment readily available that can be used both to describe present-day periglacial processes and to improve predictions of the future. Here we present the sampling and analytical methods, field and laboratory equipment and the resulting biogeochemical data from a state-of-the-art whole-ecosystem investigation of the terrestrial and aquatic parts of a lake catchment in the Kangerlussuaq region, West Greenland. This data set allows for the calculation of whole-ecosystem mass balance budgets for a long list of elements, including carbon, nutrients and major and trace metals.

Inventory of SINOPS project data sets

During the SINOPS project, an optimal state of the art simulation of the marine silicon cycle is attempted employing a biogeochemical ocean general circulation model (BOGCM) through three particular time steps relevant for global (paleo-) climate. In order to tune the model optimally, results of the simulations are compared to a comprehensive data set of 'real' observations. SINOPS' scientific data management ensures that data structure becomes homogeneous throughout the project. Practical work routine comprises systematic progress from data acquisition, through preparation, processing, quality check and archiving, up to the presentation of data to the scientific community. Meta-information and analytical data are mapped by an n-dimensional catalogue in order to itemize the analytical value and to serve as an unambiguous identifier. In practice, data management is carried out by means of the online-accessible information system PANGAEA, which offers a tool set comprising a data warehouse, Graphical Information System (GIS), 2-D plot, cross-section plot, etc. and whose multidimensional data model promotes scientific data mining. Besides scientific and technical aspects, this alliance between scientific project team and data management crew serves to integrate the participants and allows them to gain mutual respect and appreciation.