Seasonal variability of solar UV radiation in ocean waters is estimated on a global scale by combining satellite measurements of scene reflectivity (TOMS), column ozone (TOMS) and chlorophyll concentration (SeaWiFS) with radiative transfer calculations for an ocean-atmosphere system. The new features are an extension of underwater radiative transfer (scattering and absorption) into the UV, inclusion of polarization in the above water diffuse radiances, the proper treatment of Fresnel reflection, and first order atmospheric backscatter of water-leaving radiance to the oceans. Maps of downwelling diffuse irradiances (Ed) at ocean surface and at different depths in the ocean, diffuse attenuation coefficient (Kd), and ten percent penetration depth (Z10) of solar irradiation are computed for open ocean waters. Results on spectral irradiances at 310 nm in UV-B and at 380 nm in UV-A part of the spectrum are presented with particular emphasis on the role of aerosols, clouds, and ozone in the atmosphere and chlorophyll concentrations in the ocean.
Increased levels of biologically harmful Uv radiatonhave beenshown to affec aquatic ecosystems, marine photocynmetiry, and their imapct on carbon cycling. A quantiative assessment of UV effectw requires an estimate of the in-water raiationfield. An esitmate of underwater UV radiatonis porosed based on satellit meausrments fromthe TOMS and SeaWiFS and modesl fo radiatve transfer (RT). The Hydrolight code, modified toe xtnd it to the 290 - 400 nm wavleength range, is used for REt calucaitons in theocean. Solar direc tandidffuse radiances at the ocean surfce are calculated using a fulll RT code for clear-sky coditions, whicha re then modified for clouds and aerosols.Teh TOMS total column ozone and reflectivity productsa reinputs for RT calcuaitons in the atmosphere. An essential component of the in-water RT model is a model of seawater inherent optical properties (IOP). The IOP model is an extension of the Case-1 water model to the UV spectral region. Pure water absorption is interpolated between experimental datasets available in the literature. A new element of the IOP model is parameterization of particulate matter absorption in the UV based on recent in situ data. The SeaWiFS chlorophyll product is input for the IOP model. The in-water computational scheme is verified by comparing the calculated diffuse attenuation coefficient Kd, with one measured for a variety of seawater IOP. The calculated Kd is in a good agreement with the measured Kd. The relative RMS error for all of the cruise stations is about 20%. The error may be partially attributed to variability of solar illumination conditions not accounted for in calculations. The conclusion is that we are now able to model ocean UV irradiances and IOP properties with accuracies approaching those visible region, and in agreement with experimental in situ data.
Side by side comparisons of Langley type Dobson AD double wavelength pair direct sun observations between SBUV/2, SSBUV flight models and the NOAA world primary standard Dobson spectrophotometer 83 and 61 show that the SBUV/2 type instruments yield column ozone amounts that are 2% higher than the NOAA Dobson spectrometers. Similar results have been obtained with a radiometrically stable multi-filter spectroradiometer (MFS) under less than ideal conditions. A new approach based on a modeled table look-up method for using zenith sky radiances to derive total column ozone from zenith clear sky conditions has been tested using SBUV/2, SSBUV flight models and the MFS equipped with narrow band interference filters at the Dobson AD wavelength pairs. These clear zenith sky observations yield total column ozone that is in good agreement with ozone from the NOAA Dobson spectrophotometer direct sun observations. New model calculations on the relationship between satellite nadir radiances and surface based zenith clear sky radiances suggest that the combination of a very radiometrically stable MFS combined with a compact high performance double monochromator could be used to derive a common radiometric scale among satellite borne ozone monitoring instruments using the solar backscatter ultraviolet technique, and to be able to determine the drift in the radiometric calibration of ozone remote sensing instruments in space.
In the early 1990s a series of surface-based direct sun and zenith sky measurements of total column ozone were made with SBUV/2 flight models and the SSBUV Space Shuttle instrument in Boulder, Colorado which were compared with NOAA Dobson Instrument direct sun observations and TOMS instrument overpass observations of column ozone. These early measurements led to the investigation of the accuracy of derived total column ozone amounts and aerosol optical depths from zenith sky observations. Following the development and availability of radiometrically stable IAD narrow band interference filter and nitrided silicon photodiodes a simple compact multifilter spectroradiometer was developed which can be used as a calibration transfer standard spectroradiometer (CTSS) or as a surface based instrument remote sensing instruments for measurements of total column ozone and aerosol optical depths. The total column ozone derived from zenith sky observations agrees with Dobson direct sun AD double wavelength pair measurements and with TOMS overpass ozone amounts within uncertainties of about 1%. When used as a calibration transfer standard spectroradiometer the multifilter spectroradiometer appears to be capable of establishing instrument radiometric calibration uncertainties of the order of 1% or less relative to national standards laboratory radiometric standards.
Multi-channel remote sensing of ocean color from space has a rich history -- from the past CZCS, to the present SeaWiFS, and to the near-future MODIS. The atmospheric correction algorithms for processing remotely sensed data from these sensors were mainly developed by Howard Gordon at University of Miami. The algorithms were primarily designed for retrieving water leaving radiances in the visible spectral region over clear deep ocean areas. The information about atmospheric aerosols is derived from channels between 0.66 and 0.87 micrometer, where the water leaving radiances are close to zero. The derived aerosol information is extrapolated back to the visible when retrieving water leaving radiances from remotely sensed data. For the turbid coastal environment, the water leaving radiances for channels between 0.66 and 0.87 micrometer may not be close to zero because of back scattering by suspended materials in the water. Under these conditions, the channels are no longer useful for deriving information on atmospheric aerosols. As a result, the algorithms developed for applications to clear ocean waters cannot be easily modified to retrieve water leaving radiances from remote sensing data acquired over the costal environments. We have recently developed a fast and fully functional atmospheric correction algorithm for hyperspectral remote sensing of ocean color with the Coastal Ocean Imaging Spectrometer (COIS). Our algorithm uses lookup tables generated with a vector radiative transfer code developed by Ahmad and Fraser (1982) and a spectral matching technique for the retrieval of water leaving radiances. The information on atmospheric aerosols is estimated using dark channels beyond 0.86 micron. Quite reasonable results were obtained when applying the algorithm to process spectral imaging data acquired over Chesapeake Bay with the NASA JPL Airborne Visible Infrared Imaging Spectrometer (AVIRIS).
We believe that an essential feature in machine learning is the real time satisfaction of multiple objectives such as identification, tracking, etc. The machine learning problem may be viewed as a nonlinear adaptive control problem where the environment plays the role of the `plant,' while the learner is the controller. Multiobjective optimization (MOO) in the control problem typically deals with simultaneous optimization of more than one objective, where each objective is described via a cost functional. In such a situation there often exists a region of tradeoff wherein one cost may be improved at the expense of others. Such a region is called the Pareto optimal (PO) set. A parameterization of this set simplifies the attainment of the existing tradeoff. Working within the Pareto set guaranties optimum tradeoff. As an example this algorithm is applied to the control of a dc motor.
The work presented here is an extension of previous work, where estimation of the parameters of a plant was incorporated through exploratory schedules (ES), which are reference input trajectories designed to enhance the learning of system parameters. ESes were earlier generated off-line and used in an open-loop fashion. Moreover, these ESes were used between actual control tasks, therefore limiting the process of estimation during idle time. Here the authors attempt to generate ESes in a closed-loop manner. Such trajectories in general may not be the desired trajectories, resulting in larger tracking errors. However, ESes offer faster convergence to the system parameters and therefore yield smaller long-term tracking errors. The automation for the design of ESes requires on-line modification of the desired trajectory to enhance learning at the expense of poorer initial tracking.
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