Frank Fell

Numerical simulation of the light field in the atmosphere–ocean system using the matrix-operator method

Abstract A computer code to calculate the light field in the stratified atmosphere–ocean system is described and validated. The code is based on the matrix-operator method and includes multiple scattering as well as the effects at the flat or rough sea surface and the ocean ground. Special emphasis is put on the methods employed to ensure numerical accuracy and energy conservation. The code is validated by comparing model predictions with the analytical solution of the radiative transfer equation for a semi-infinite Rayleigh scattering atmosphere and by a model intercomparison for selected problems of the radiative transfer in the atmosphere–ocean system. The observed deviations from the analytical solution are smaller than 0.1% for solar and observation zenith angles

Evaluating the performance of artificial neural network techniques for pigment retrieval from ocean color in Case I waters

[1] In the present paper, we report on a method to retrieve the pigment concentration in Case I waters from ocean color. The method is derived from radiative transfer (RT) simulations and subsequent application of artificial neural network (ANN) techniques. Information on absorption and total scattering of pure seawater, colored dissolved organic matter, and marine particles are mostly taken from published measurements or parameterizations. Additionally, a new model relating the backscattering of marine particles to pigment concentration and wavelength is introduced. The such defined inherent optical properties are input to a RTcode in order to generate a synthetic data set of remote sensing reflectance spectra. This synthetic data set is then used for the training of a set of ANNs with the aim to approximate the functional relationship between ocean color and pigment concentration. The different ANNs are obtained by systematic variations of input parameters, architecture, and noise level added to the training data. The performance of each individual ANN-based pigment retrieval scheme is assessed by applying it to the remote sensing reflectance spectra contained in the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Algorithm MiniWorkshop (SeaBAM) data set and comparing the retrieved pigment concentrations to those actually measured. The most successful ANN compares favorably with commonly used empirical pigment retrieval schemes. Compared, e.g., to the SeaWiFS algorithms OC2B and OC4, the square of the correlation coefficient r 2 is increased from 0.924 (OC2B), respectively, 0.928 (OC4) to 0.934 (ANN). The root mean square error of the retrieved log-transformed pigment concentration drops from 0.156 for OC2B, respectively, 0.151 for OC4 to 0.148 for the ANN-based pigment retrieval scheme. Furthermore, the latter shows a higher resistance against noisy input data. INDEX TERMS: 4275 Oceanography: General: Remote sensing and electromagnetic processes (0689); 4552 Oceanography: Physical: Ocean optics; 4594 Oceanography: Physical: Instruments and techniques; 4855 Oceanography: Biological and Chemical: Plankton; KEYWORDS: Case I waters, pigment retrieval, artificial neural network

Application of the active learning method to the retrieval of pigment from spectral remote sensing reflectance data

Due to the noise that is present in remote sensing data, a robust method to retrieve information is needed. In this study, the active learning method (ALM) is applied to spectral remote sensing reflectance data to retrieve in‐water pigment. The heart of the ALM is a fuzzy interpolation method that is called the ink drop spread (IDS). Three datasets (SeaBAM, synthetic and NOMAD) are used for the evaluation of the selected ALM approach. Comparison of the ALM with the ocean colour 4 (OC4) algorithm and the artificial neural network (ANN) algorithm demonstrated the robustness of the ALM approach in retrieval of in‐water constituents from remote sensing reflectance data. In addition, the ALM identified and ranked the most relevant wavelengths for chlorophyll and pigment retrieval.

Artificial-neural-network-based atmospheric correction algorithm: application to MERIS data

After the successful launch of the Medium Resolution Imaging Spectrometer (MERIS) on board of the European Space Agency (ESA) Environmental Satellite (ENVISAT) on March 1st 2002, first MERIS data are available for validation purposes. The primary goal of the MERIS mission is to measure the color of the sea with respect to oceanic biology and marine water quality. We present an atmospheric correction algorithm for case-I waters based on the inverse modeling of radiative transfer calculations by artificial neural networks. The proposed correction scheme accounts for multiple scattering and high concentrations of absorbing aerosols (e.g. desert dust). Above case-I waters, the measured near infrared path radiance at Top-Of-Atmosphere (TOA) is assumed to originate from atmospheric processes only and is used to determine the aerosol properties with the help of an additional classification test in the visible spectral region. A synthetic data set is generated from radiative transfer simulations and is subsequently used to train different Multi-Layer-Perceptrons (MLP). The atmospheric correction scheme consists of two steps. First a set of MLPs is used to derive the aerosol optical thickness (AOT) and the aerosol type for each pixel. Second these quantities are fed into a further MLP trained with simulated data for various chlorophyll concentrations to perform the radiative transfer inversion and to obtain the water-leaving radiance. In this work we apply the inversion algorithm to a MERIS Level 1b data track covering the Indian Ocean along the west coast of Madagascar.

Simulation of MERIS measurements above selected ocean waters

We report on a number of radiative transfer calculations that have been performed in order to predict Medium Resolution Imaging Spectrometer (MERIS) measurements for the anticipated spectral bands and observation geometries for selected open ocean and coastal waters. The simulations show that, above coastal waters, significant levels of the water-leaving radiance must be expected in several of the MERIS channels dedicated to the atmospheric correction. These channels should be included in the algorithms to retrieve concentrations of water constituents. In addition, sunglint may affect large parts of MERIS satellite images, especially in the lower latitudes between ca 20 N and 20 S. Radiative transfer calculations similar to those presented here are used to derive algorithms for the assessment of constituent concentrations in Case II waters from ocean colour measurements.

Application of the Active Learning Method for the estimation of geophysical variables in the Caspian Sea from satellite ocean colour observations

Remotely sensed data inherently contain noise. The development of inverse modelling methods with a low sensitivity to noise is in demand for the estimation of geophysical variables from remotely sensed data. The Active Learning Method (ALM) is well known to have a low sensitivity to noise. For the first time, ALM was utilized for the inversion of radiative transfer calculations with the aim of estimating chlorophyll a (Chl a), coloured dissolved organic matter (CDOM), and suspended particulate matter (SPM) in the Caspian Sea using MERIS (MEdium Resolution Imaging Spectrometer) data. ALM training is straightforward and fast. The ALM inversion models revealed the most relevant variables and showed a short processing time in operational applications for the estimation of geophysical variables. The mean absolute percentage errors of Chl a, SPM, and CDOM estimation using ALM inversion models were 44, 70, and 73%, respectively. According to the ALM results, it can be introduced as a new method for inverse modelling of ocean colour observations.

Spectral absorption coefficient measured in situ in the North Sea with a marine radiometric spectrometer system

A submersible marine radiometric spectrometer system, capable of simultaneous measurements of the in situ spectral and angular properties of the underwater oceanic light field, is used to determine spectral inherent optical properties of marine waters. The inversion methods used to convert the sampled light field measurements into estimates of spectral absorption are presented and sample results for three water types obtained during a cruise in the North Sea are given.

The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses

The Global Energy and Water cycle Exchanges (GEWEX) Data and Assessments Panel (GDAP) initiated the GEWEX Water Vapor Assessment (G-VAP), which has the main objectives to quantify the current state of art in water vapour products being constructed for climate applications and to support the selection process of suitable water vapour products by GDAP for its production of globally consistent water and energy cycle products. During the construction of the G-VAP data archive, freely available and mature satellite and reanalysis data records with a minimum temporal coverage of 10 years were considered. The archive contains total column water vapour (TCWV) as well as specific humidity and temperature at four pressure levels (1000, 700, 500, 300 hPa) from 22 different data records. All data records were remapped to a regular longitude/latitude grid of 2°x2°. The archive consists of four different folders: 22 TCWV data records covering the period 2003-2008, 11 TCWV data records covering the period 1988-2008, as well as seven specific humidity and seven temperature data records covering the period 1988-2009. The G-VAP data archive is referenced under the following digital object identifier (doi): http://dx.doi.org/10.5676/EUM SAF CM/GVAP/V001. Within G-VAP, the characterisation of water vapour products is, among other ways, achieved through intercomparisons of the considered data records, as a whole and grouped into three classes of predominant retrieval condition: clear-sky, cloudy-sky and all-sky. Associated results are shown using the 22 TCWV data records. The standard deviations among the 22 TCWV data records have been analysed and exhibit distinct maxima over central Africa and the tropical warm pool (in absolute terms) as well as over the poles and mountain regions (in relative terms). The variability in TCWV within each class can be large and prohibits conclusions on systematic differences in TCWV between the classes.

Effects of the wind direction on the light-field reflected from a wind roughened sea surface

A method is presented which allows for an approximate treatment of the radiative transfer above an asymmetrically reflecting wind roughened sea surface. The radiative transfer model used for this purpose is based on the matrix operator method. The efficiency of this method is mainly due to the separation of zenith and azimuth dependence, expanding the latter into a Fourier series. In the case of light fields symmetric with respect to the principal plane, the Fourier expansion of all relevant parameters consists of cosine terms only and the radiative transfer is calculated independently for each Fourier coefficient. However, when taking the effects of the wind direction into account, the light field produced at the rough sea surface is asymmetric. As a result, cosine and sine coefficients of all spectral frequencies are coupled in the layer representing the sea surface. The problem is considerably simplified, when the asymmetric reflection at the sea surface is only applied to the direct solar radiation, and symmetric reflection is assumed for the diffuse radiation incident on the sea surface. Using this simplified treatment, the Fourier coefficients again decouple, and the asymmetrically reflecting rough sea surface can easily be incorporated into the matrix operator method. The effect of the wind direction on the light field at the sea surface and at the top of the atmosphere is shown for a few examples. The calculations show that the radiances at the top of the atmosphere is shown for few examples. The calculations show that the radiances at the top of the atmosphere are altered up to 10 percent to 30 percent in the sunglint affected angular domains, depending on wind speed and direction. In contrast to that, the fluxes remain fairly independent on the wind direction.

Automated atmospheric correction of AVHRR channel 1 and 2 data using dark surface targets

A method is presented to allow for operational atmospheric correction of AVHRR channels 1 and 2 data. The method is based on radiative transfer calculations and subsequent application of artificial neural network techniques. The method is applied to derive atmospherically corrected NDVI maps of the river Elbe catchment area in Central Europe.