How should sparse marine in situ measurements be compared to a continuous model: an example

This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-to-point method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.

Real-time sea surface air temperature retrieval over Southern Ocean using AMSR-E data

The AMSR-E satellite data and in-situ data were applied to retrieve sea surface air temperature (Ta) over the Southern Ocean. The in-situ data were obtained from the 24~(th) -26~(th) Chinese Antarctic Expeditions during 2008-2010. First, Ta was used to analyze the relativity with the bright temperature (Tb) from the twelve channels of AMSR-E, and no high relativity was found between Ta and Tb from any of the channels. The highest relativity was 0.38 (with 23.8 GHz). The dataset for the modeling was obtained by using in-situ data to match up with Tb, and two methods were applied to build the retrieval model. In multi-parameters regression method, the Tbs from 12 channels were used to the model and the region was divided into two parts according to the latitude of 50°S. The retrieval results were compared with the in-situ data. The Root Mean Square Error (RMS) and relativity of high latitude zone were 0.96℃and 0.93, respectively. And those of low latitude zone were 1.29 ℃ and 0.96, respectively. Artificial neural network (ANN) method was applied to retrieve Ta.The RMS and relativity were 1.26 ℃ and 0.98, respectively.

The meso-scale response of subarctic North Pacific seabird community structure to lower trophic level abundance and diversity

Understanding the mechanisms that structure communities and influence biodiversity are fundamental goals of ecology. To test the hypothesis that the abundance and diversity of upper-trophic level predators (seabirds) is related to the underlying abundance and diversity of their prey (zooplankton) and ecosystem-wide energy availability (primary production), we initiated a monitoring program in 2002 that jointly and repeatedly surveys seabird and zooplankton populations across a 7,500 km British Columbia-Bering Sea-Japan transect. Seabird distributions were recorded by a single observer (MH) using a strip-width technique, mesozooplankton samples were collected with a Continuous Plankton Recorder, and primary production levels were derived using the appropriate satellite parameters and the Vertically Generalized Production Model (Behrenfeld and Falkowski 1997). Each trophic level showed clear spatio-temporal patterns over the course of the study. The strongest relationship between seabird abundance and diversity and the lower trophic levels was observed in March/April ('spring') and significant relationships were also found through June/July ('summer'). No discernable relationships were observed during the September/October ('fall') months. Overall, mesozooplankton abundance and biomass explained the dominant portion of seabird abundance and diversity indices (richness, Simpson's Index, and evenness), while primary production was only related to seabird richness. These findings underscore the notion that perturbations of ocean productivity and lower trophic level ecosystem constituents influenced by climate change, such as shifts in timing (phenology) and synchronicity (match-mismatch), could impart far-reaching consequences throughout the marine food web.

Variations in GDGT distributions through the water column in the South East Atlantic Ocean

The TetraEther indeX of 86 carbon atoms (TEX86) temperature proxy is widely used in reconstructions of past sea surface temperature. Most current calibrations are based on surface sediment distributions of the glycerol dialkyl glycerol tetraether lipids (GDGTs) that comprise TEX86 and assume that these GDGTs are exported from the upper mixed layer. However, GDGT export from deeper waters could impact sedimentary GDGT distributions and therefore TEX86 paleothermometry. Here we examine GDGT distributions in suspended particulate matter (SPM) and underlying sediments collected from the Southeast Atlantic Ocean. Our results reveal different GDGT distributions - specifically the ratio between GDGTs bearing 2 vs. 3 cyclopentyl moieties, [2/3] ratios - between surface, subsurface (>50-200 m) and deep water (>200 m) SPM, which suggests the occurrence of in situ (deep) production that is not apparent when considering TEX86. The GDGT distributions in sediments match those of subsurface waters rather than surface waters, suggesting that they have not been preferentially derived from the upper mixed layer; this is consistent with GDGT abundances being highest in shallow subsurface SPM (˜100 to 200 m). It remains unclear what governs the different [2/3] ratios throughout the water column, but it is likely related to a combination of temperature and thaumarchaeotal community structure.

CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters.

The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive intercomparison due to the availability of quality checked in situ databases. The CoastColour Round Robin (CCRR) project, funded by the European Space Agency (ESA), was designed to bring together three reference data sets using these to test algorithms and to assess their accuracy for retrieving water quality parameters. This paper provides a detailed description of these reference data sets, which include the Medium Resolution Imaging Spectrometer (MERIS) level 2 match-ups, in situ reflectance measurements, and synthetic data generated by a radiative transfer model (HydroLight). These data sets, representing mainly coastal waters, are available from doi:10.1594/PANGAEA.841950. The data sets mainly consist of 6484 marine reflectance (either multispectral or hyperspectral) associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: total suspended matter (TSM) and chlorophyll a (CHL) concentrations, and the absorption of coloured dissolved organic matter (CDOM). Inherent optical properties are also provided in the simulated data sets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three data sets are compared. Match-up and in situ sites where deviations occur are identified. The distributions of the three reflectance data sets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Photoacclimation of natural phytoplankton communities

Phytoplankton regulate internal pigment concentrations in response to light and nutrient availability. Chlorophyll to carbon ratios (Chl:Cphyto) are commonly reported as a function of growth irradiance (Eg) for evaluating the photoacclimation response of phytoplankton. In contrast to most culture experiments, natural phytoplankton communities experience fluctuating environmental conditions making it difficult to compare field and lab observations. Observing and understanding photoacclimation in nature is important for deciphering changes in Chl:Cphyto resulting from environmental forcings and for accurately estimating net primary production (NPP) in models which rely on a parameterized description of photoacclimation. Here we employ direct analytical measurements of Cphyto and parallel high-resolution biomass estimates from particulate backscattering (bbp) and flow cytometry to investigate Chl:Cphyto in natural phytoplankton communities. Chl:Cphyto observed over a wide range of Eg in the field was consistent with photoacclimation responses inferred from satellite observations. Field-based photoacclimation observations for a mixed natural community contrast with laboratory results for single species grown in continuous light and nutrient replete conditions. Applying a carbon-based net primary production (NPP) model to our field data for a north-south transect in the Atlantic Ocean results in estimates that closely match 14C depth-integrated NPP for the same cruise and with historical records for the distinct biogeographic regions of the Atlantic Ocean. Our results are consistent with previous satellite and model observations of cells growing in natural or fluctuating light and showcase how direct measurements of Cphyto can be applied to explore phytoplankton photophysiology, growth rates, and production at high spatial resolution in-situ.