We have developed a satellite-based numerical simulation for determining the extent to which enhanced solar ultraviolet radiation (UVR) under the springtime Antarctic ozone decrese affects primary production throughout the Southern Ocean. This satellite approach using NASA Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data for chlorophyll and phytoplankton biomass, passive microwave data for sea ice concentration, and Total Ozone Mapping Spectrometer (TOMS) data for total column ozone and cloud reflectivity, circumvents many of the limitations involved with extrapolating point field measurements to larger geographical areas. The satellite data are used to force a physiology-based model of phytoplankton growth in response to UV-B, UV-A, and photosynthetically active radiation(PAR). Comparison with field measurements in the Western Antarctic Peninsula region shows excellent agreement. UVR-induced losses of surface phytoplankton production were substantial under all ozone conditions, due mostly to UV-A. However, when integrated to the 0.1% light depth, the loss of primary production resulting from enhanced fluxes of UV-B due to ozone depletion was less than 0.25%. The loss of primary production is minimized by the strong attenuation of UVR in the water column and by the spatial and temporal mismatch between the maximum extent of the Antarctic ozone hole and the maximum abundance of phytoplankton in the open water.
Spectrally resolved radiometric measurements of middle infrared atmospheric emission can be used in conjunction with detailed radiative transfer calculations to retrieve cloud emissivity, and to estimate cloud liquid water path (LWP), optical depth, and equivalent radius of the droplet size distribution. Using a discrete-ordinates radiative transfer formulation, an algorithm has been developed to retrieve these cloud properties from FTIR data. The algorithm has been successfully applied to a four month Antarctic data set provided by the CalSpace FTIR Spectroradiometer. Radiative transfer calculations were performed to estimate spectral cloud emissivity for a range of cloud optical depth, liquid water content, and equivalent radius, sufficient to bracket values expected in the field. These calculations made use of bi-modal droplet size distributions actually observed in Antarctic clouds. Using a least- squares algorithm, a theoretical cloud emission spectrum is chosen which best reproduces a given measured brightness temperature spectrum. The results show marked differences in cloud emissivity between high and low overcast layers, and between clouds with and without precipitation. The results also suggest that the emissivity of a maritime Antarctic cloud deck should be smaller for a given LWP than the parameterization frequently used in general circulation models.
Two methods have been investigated to map UV surface irradiance over Antarctica and the adjacent oceans using satellite remote sensing and ground truth radiometer measurements. Both methods are based on radiance observations from the Advanced Very High Resolution Radiometer (AVHRR) and from the Total Ozone Mapping Spectrometer (TOMS). Surface albedo and cloud optical depth are estimated from visible and infrared AVHRR data, and ozone concentration is derived from TOMS data. Radiative transfer models are applied to retrieve geophysical parameters from satellite data but also to compute the surface UV irradiance. The two methods differ in: (1) the derivation of cloud optical depth, and (2) the type of radiative transfer model used. Preliminary results from both methods are presented and compared with ground measurements made at Palmer Station, Antarctica.
The polar regions are expected to be particularly sensitive to anthropogenic global change. Due to the difficulties in modeling high latitude climate and the logistical challenges with polar field work, satellite remote sensing will have an increasingly important role to play in polar climate research. For studies of atmospheric radiation and meteorology, accurate cloud detection and classification is crucial. Modern methods for polar cloud classification utilize both multispectral threshold and automated pattern recognition techniques. For monitoring sea ice concentration, passive microwave sensors offer an all-weather advantage over visible or infrared scanners, although over clear-sky scenes the latter can provide a much finer spatial resolution. The various algorithms for satellite retrieval and remote sensing in the polar regions are constantly being refined and improved.
Spectrally resolved radiometric measurements of middle infrared atmospheric emission can be used in conjunction with detailed radiative transfer calculations to retrieve cloud emissivity, and to estimate cloud liquid water path (LWP), optical depth, and equivalent radius of the droplet size distribution. Using a discrete-ordinates radiative transfer formulation, an algorithm has been developed to retrieve these cloud properties from FTIR data. The algorithm has been successfully applied to a four month Antarctic data set provided by the CalSpace FTIR Spectroradiometer. Radiative transfer calculations were performed to estimate spectral cloud emissivity for a range of cloud optical depth, liquid water content, and equivalent radius, sufficient to bracket values expected in the field. These calculations made use of bi-modal droplet size distributions actually observed in Antarctic clouds. Using a least- squares algorithm, a theoretical cloud emission spectrum is chosen which best reproduces a given measured brightness temperature spectrum. The results show marked differences in cloud emissivity between high and low overcast layers, and between clouds with and without precipitation. The results also suggest that the emissivity of a maritime Antarctic cloud deck should be smaller for a given LWP than the parameterization frequently used in general circulation models.
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