Technical Note: Calibration and validation of geophysical observation models

We present a method to calibrate and validate observational models that interrelate remotely sensed energy fluxes to geophysical variables of land and water surfaces. Coincident sets of remote sensing observation of visible and microwave radiations and geophysical data are assembled and subdivided into calibration (Cal) and validation (Val) data sets. Each Cal/Val pair is used to derive the coefficients (from the Cal set) and the accuracy (from the Val set) of the observation model. Combining the results from all Cal/Val pairs provides probability distributions of the model coefficients and model errors. The method is generic and demonstrated using comprehensive matchup sets from two very different disciplines: soil moisture and water quality. The results demonstrate that the method provides robust model coefficients and quantitative measure of the model uncertainty. This approach can be adopted for the calibration/validation of satellite products of land and water surfaces, and the resulting uncertainty can be used as input to data assimilation schemes

CoastColour Round Robin datasets: A data base 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.JRC.H.1-Water Resource

Proxy indicators of sand temperature help project impacts of global warming on sea turtles in northern Australia

Global warming poses serious threats to sea turtle populations since sex determination and hatching success are dependent on nest temperature. Nest sex ratios may be skewed towards a predominantly female output, and eggs may be consistently exposed to temperatures that exceed thermal mortality thresholds. Consequently, understanding the rates at which sand temperatures are likely to change represents an immediate priority. Here, we use regression analyses to correlate air temperature (AT) and high-resolution sea surface temperature (SST) to sand temperature at 5 rookeries\ud in northern Australia. We show that previous studies using only AT could potentially be improved by including SST as a covariate. At our study sites, combined SST and AT models\ud explained between 79 and 94% of the variance in sand temperature in recent years. Our results suggest that hatchling production will skew towards all females at 3 of our sites by 2070 (Moulter Cay, Milman Island and Bramble Cay) and by as early as 2030 at Ashmore Island and Bare Sand Island. The projections presented here can inform the timely and targeted implementation of local-scale management strategies to reduce the impacts of global warming on sea turtle populations. Identifying and testing new strategies deserves immediate attention, as does further research into the adaptive capacity of sea turtles

Measurements of CDOM absorption spectra using different Instruments and techniques: A round robin exercise and extensive field data set.

The optical measurement of Chromophoric Dissolved Organic Matter (CDOM) throughout the open-ocean and coastal regions has played a crucial role in the development of Ocean Color algorithms. However many spectrophotometric instruments equipped with 10cm cells are not sensitive enough to measure light attenuation from CDOM in open ocean or case 1 waters. One solution is to significantly increase the optical path length, which gives the photons of light a greater probability of being absorbed before reaching the detector. Liquid waveguide capillary cells (LWCC), integrating cavity absorption meters (ICAM), and Wetlabs absorption attenuation meters have all become prominent instruments in the community for making long path length measurements. However limitations arise due to the loss of light from scattering, spectral offsets caused by temp and salinity offsets, and cell contamination with subsequent micro-bubble formation. An extensive round robin comparison was carried out with versions of all these instruments at NASA Goddard Space Flight Center in the fall of 2013. It was part of an ongoing CDOM workshop with an international committee. Many new insights pertaining to the methodology and results of the measurements will be presented along with an extensive field data set of LWCC measurements.JRC.H.1-Water Resource

Regional to global assessments of phytoplankton dynamics from the SeaWiFS mission

Photosynthetic production of organic matter by microscopic oceanic phytoplankton fuels ocean ecosystems and contributes roughly half of the Earth's net primary production. For 13 years, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission provided the first consistent, synoptic observations of global ocean ecosystems. Changes in the surface chlorophyll concentration, the primary biological property retrieved from SeaWiFS, have traditionally been used as a metric for phytoplankton abundance and its distributionlargely reflects patterns in vertical nutrient transport. On regional to global scales, chlorophyll concentrations covary with sea surface temperature (SST) because SST changes reflect light and nutrient conditions. However, the oceanmay be too complex to be well characterized using a single index such as the chlorophyll concentration. A semi-analytical bio-optical algorithm is used to help interpret regional to global SeaWiFS chlorophyll observations from using three independent, well-validated ocean color data products; the chlorophyll a concentration, absorption by CDM and particulate backscattering.First, we show that observed long-term, global-scale trends in standard chlorophyll retrievals are likely compromised by coincident changes in CDM. Second, we partition the chlorophyll signal into a component due to phytoplankton biomass changes and a component caused by physiological adjustments in intracellular chlorophyll concentrations to changes in mixed layer light levels. We show that biomass changes dominate chlorophyll signals for the high latitude seas and where persistent vertical upwelling is known to occur, while physiological processes dominate chlorophyll variability over much of the tropical and subtropical oceans. The SeaWiFS data set demonstrates complexity in the interpretation of changes in regional to global phytoplankton distributions and illustrates limitations for the assessment of phytoplankton dynamics using chlorophyll retrievals alone