Bathymetric map of Heron Reef, Australia, derived from airborne hyperspectral data at 1 m resolution

A simple method for efficient inversion of arbitrary radiative transfer models for image analysis is presented. The method operates by representing the shape of the function that maps model parameters to spectral reflectance by an adaptive look-up tree (ALUT) that evenly distributes the discretization error of tabulated reflectances in spectral space. A post-processing step organizes the data into a binary space partitioning tree that facilitates an efficient inversion search algorithm. In an example shallow water remote sensing application, the method performs faster than an implementation of previously published methodology and has the same accuracy in bathymetric retrievals. The method has no user configuration parameters requiring expert knowledge and minimizes the number of forward model runs required, making it highly suitable for routine operational implementation of image analysis methods. For the research community, straightforward and robust inversion allows research to focus on improving the radiative transfer models themselves without the added complication of devising an inversion strategy.

Simulated Bromoform emission and concentration using the ocean biogeochemistry model MPIOM/HAMOCC forced by 6-hourly NCEP data

Bromoform (CHBr3) is one important precursor of atmospheric reactive bromine species that are involved in ozone depletion in the troposphere and stratosphere. In the open ocean bromoform production is linked to phytoplankton that contains the enzyme bromoperoxidase. Coastal sources of bromoform are higher than open ocean sources. However, open ocean emissions are important because the transfer of tracers into higher altitude in the air, i.e. into the ozone layer, strongly depends on the location of emissions. For example, emissions in the tropics are more rapidly transported into the upper atmosphere than emissions from higher latitudes. Global spatio-temporal features of bromoform emissions are poorly constrained. Here, a global three-dimensional ocean biogeochemistry model (MPIOM-HAMOCC) is used to simulate bromoform cycling in the ocean and emissions into the atmosphere using recently published data of global atmospheric concentrations (Ziska et al., 2013) as upper boundary conditions. Our simulated surface concentrations of CHBr3 match the observations well. Simulated global annual emissions based on monthly mean model output are lower than previous estimates, including the estimate by Ziska et al. (2013), because the gas exchange reverses when less bromoform is produced in non-blooming seasons. This is the case for higher latitudes, i.e. the polar regions and northern North Atlantic. Further model experiments show that future model studies may need to distinguish different bromoform-producing phytoplankton species and reveal that the transport of CHBr3 from the coast considerably alters open ocean bromoform concentrations, in particular in the northern sub-polar and polar regions.