Ewa J. Kwiatkowska

New aerosol models for the retrieval of aerosol optical thickness and normalized water-leaving radiances from the SeaWiFS and MODIS sensors over coastal regions and open oceans.

We describe the development of a new suite of aerosol models for the retrieval of atmospheric and oceanic optical properties from the SeaWiFS and MODIS sensors, including aerosol optical thickness (τ), angstrom coefficient (α), and water-leaving radiance (L(w)). The new aerosol models are derived from Aerosol Robotic Network (AERONET) observations and have bimodal lognormal distributions that are narrower than previous models used by the Ocean Biology Processing Group. We analyzed AERONET data over open ocean and coastal regions and found that the seasonal variability in the modal radii, particularly in the coastal region, was related to the relative humidity. These findings were incorporated into the models by making the modal radii, as well as the refractive indices, explicitly dependent on relative humidity. From these findings, we constructed a new suite of aerosol models. We considered eight relative humidity values (30%, 50%, 70%, 75%, 80%, 85%, 90%, and 95%) and, for each relative humidity value, we constructed ten distributions by varying the fine-mode fraction from zero to 1. In all, 80 distributions (8 Rh×10 fine-mode fractions) were created to process the satellite data. We also assumed that the coarse-mode particles were nonabsorbing (sea salt) and that all observed absorptions were entirely due to fine-mode particles. The composition of the fine mode was varied to ensure that the new models exhibited the same spectral dependence of single scattering albedo as observed in the AERONET data. The reprocessing of the SeaWiFS data show that, over deep ocean, the average τ(865) values retrieved from the new aerosol models was 0.100±0.004, which was closer to the average AERONET value of 0.086±0.066 for τ(870) for the eight open-ocean sites used in this study. The average τ(865) value from the old models was 0.131±0.005. The comparison of monthly mean aerosol optical thickness retrieved from the SeaWiFS sensor with AERONET data over Bermuda and Wallops Island show very good agreement with one another. In fact, 81% of the data points over Bermuda and 78% of the data points over Wallops Island fall within an uncertainty of ±0.02 in optical thickness. As a part of the reprocessing effort of the SeaWiFS data, we also revised the vicarious calibration gain factors, which resulted in significant improvement in angstrom coefficient (α) retrievals. The average value of α from the new models over Bermuda is 0.841±0.171, which is in good agreement with the AERONET value of 0.891±0.211. The average value of α retrieved using old models is 0.394±0.087, which is significantly lower than the AERONET value.

Cross calibration of ocean-color bands from Moderate Resolution Imaging Spectroradiometer on Terra platform

Ocean-color applications require maximum uncertainties in blue-wavelength water-leaving radiances in oligotrophic ocean of approximately 5%. Water-leaving radiances from Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite, however, exhibit temporal drift of the order of 15% as well as sensor changes in response versus scan and polarization sensitivity, which cannot be tracked by onboard calibrators. This paper introduces an instrument characterization approach that uses Earth-view data as a calibration source. The approach models the top of the atmosphere signal over ocean that the instrument is expected to measure, including its polarization, with water-leaving radiances coming from another well-calibrated global sensor. The cross calibration allows for significant improvement in derived MODIS-Terra ocean-color products, with largest changes in the blue wavelengths.

Corrections to the Calibration of MODIS Aqua Ocean Color Bands Derived From SeaWiFS Data

The National Aeronautics and Space Administration ocean color products of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua have been reprocessed in 2009. This paper describes the changes to the calibration approach for MODIS Aqua. Due to a significant downward trend in the operational MODIS Aqua water-leaving radiances at 412 nm, the previous calibration approach was no longer sufficient. The new approach uses SeaWiFS water-leaving radiances to adjust the temporal trends of the radiometric calibration of MODIS Aqua bands at 412 and 443 nm. The adjustments to the temporal trends at the beginning of the scan are minor but are significant around nadir and at the end of scan (up to 5% at 412 nm and up to 1% for 443 nm). The remaining five bands (488 to 678 nm) are adjusted with regard to their scan-angle dependence only; no temporal correction is necessary. There is no indication that the sensor polarization sensitivity needs to be modified for MODIS Aqua.

Application of machine-learning techniques toward the creation of a consistent and calibrated global chlorophyll concentration baseline dataset using remotely sensed ocean color data

This paper introduces a machine-learning approach to satellite ocean color sensor cross calibration. The cross-calibration objective is to eliminate incompatibilities among sensor data from different missions and produce merged daily global ocean color coverage. The approach is designed and investigated using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard of the Terra satellite and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Data from these two sensors show apparent discrepancies originating from differences in sensor design, calibration, processing algorithms, and from the rate of change in the atmosphere and ocean within 1(1/2) h between sensor imaging of the same regions on the ground. The discrepancies have complex, noisy, and often contradictory time and space variabilities. Support vector machines are used to bring MODIS data to the SeaWiFS representation where SeaWiFS data are considered to exemplify a consistent ocean color baseline. Support vector machines are effective in learning and resolving convoluted data relationships between the two sensors given a variety of bio-optical, atmospheric, viewing geometry, and ancillary information. The method works accurately in low chlorophyll waters and shows a potential to eliminate sensor problems, such as scan angle dependencies and seasonal and spatial trends in data. The results illustrate that MODIS and SeaWiFS differences are noisy and highly variable, which makes it difficult to extrapolate the cross-calibration knowledge onto new time and space domains and to define representative global ocean color datasets for support vector machine training.

Atmospheric correction for NO 2 absorption in retrieving water-leaving reflectances from the SeaWiFS and MODIS measurements

The absorption by atmospheric nitrogen dioxide (NO2) gas in the visible has been traditionally neglected in the retrieval of oceanic parameters from satellite measurements. Recent measurements of NO2 from spaceborne sensors show that over the Eastern United States the NO2 column amount often exceeds 1 Dobson Unit (approximately 2.69x10(16) molecules/cm2). Our radiative transfer sensitivity calculations show that under high NO2 conditions (approximately 1x10(16) molecules/cm2) the error in top-of-atmosphere (TOA) reflectance in the blue channels of the sea-viewing wide field-of-view sensor (SeaWiFS) and moderate-resolution imaging spectroradiometer (MODIS) sensors is approximately 1%. This translates into approximately 10% error in water-leaving radiance for clear waters and to higher values (>20%) in the coastal areas. We have developed an atmospheric-correction algorithm that allows an accurate retrieval of normalized water-leaving radiances (nLws) in the presence of NO2 in the atmosphere. The application of the algorithm to 52 MODIS scenes over the Chesapeake Bay area show a decrease in the frequency of negative nLw estimates in the 412 nm band and an increase in the value of nLws in the same band. For the particular scene reported in this paper, the mean value of nLws in the 412 nm band increased by 17%, which is significant, because for the MODIS sensor the error in nLws attributable to the digitization error in the observed TOA reflectance over case 2 waters is approximately 2.5%.

Merger of ocean color data from multiple satellite missions within the SIMBIOS project

The purpose of data merger activities undertaken by the National Aeronautic and Space Administrations (NASA) Sensor Intercomparison and Merger for Biological and Interdisciplinary Studies (SIMBIOS) Project is to create scientific quality ocean color data encompassing measurements from multiple satellite missions. The fusion of data from multiple satellites will improve the quality of ocean color products over single-mission data sets by expanding spatial and temporal coverage of the worlds oceans and increasing statistical confidence in generated parameters. The merger will also support a variety of new applications by taking advantage of sensor-varying calibration, spectral, spatial, temporal, and ground coverage characteristics. Leading to the data merger goals, the SIMBIOS Project has established a thorough ocean color validation program and has been cross-comparing and cross-calibrating sensor data with in situ measurements and data among the missions. The SIMBIOS Science Team has been studying data merger algorithms based on spectral data assimilation and spatial interpolation. The SIMBIOS Project Office has implemented statistical objective analysis and regression techniques based on artificial neural networks and support vector machines. The accuracy of the merger methods will be evaluated using in situ data, statistical analyses, and simple chlorophyll means -- the method already implemented within the SIMBIOS Project. This paper defines challenges and suggests solutions for data merger based on the example of daily chlorophyll concentration products from Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS).

Analysis of image striping due to polarization correction artifacts in remotely sensed ocean scenes

The characterization of the polarization sensitivity of a remote sensing sensor can have a large impact on the data quality of the top-of-atmosphere radiances measured by optical sensors on earth-orbiting satellites. This paper describes an algorithm to improve the polarization characterization of certain elements of an imaging sensor (e.g. detectors, or mirror sides) relative to each other, as well as the application to an ocean color sensor. The key step in the analysis is the separation of the measured radiances into two groups: those that are increased by the polarization correction, and those that are decreased.

Merger of ocean color information from multiple satellite missions under the NASA SIMBIOS Project Office

The purpose of data merger activities undertaken by the Sensor Intercomparison and Merger for Biological and Interdisciplinary Studies (SIMBIOS) Project is to create scientific quality ocean color data sets encompassing measurements from multiple satellite missions. To meet this goal, a number of image processing and data fusion methodologies have been developed within the Project Office. A backpropagation neural network has been employed to map ocean color products from one sensor along with extracted ancillary parameters into products from another sensor. This enabled seamless fusion of data from both sensors to improve ocean color daily global coverage. Concurrently, statistical objective analysis has been implemented to validate the neural network approach. Wavelet-based image multiresolution analysis has been used to merge measurements from sensors of different spatial resolutions and also to examine the prospect of enhancing oceanic features in lower resolution imagery through the use of higher resolution data. Finally, a merger of satellite and in situ measurements has been developed.

Corrections to the calibration of MODIS Aqua ocean color bands derived from SeaWiFS data

The National Aeronautics and Space Administration ocean color products of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua have been reprocessed in 2009. This paper describes the changes to the calibration approach for MODIS Aqua. Due to a significant downward trend in the operational MODIS Aqua water-leaving radiances at 412 nm, the previous calibration approach was no longer sufficient. The new approach uses SeaWiFS water-leaving radiances to adjust the temporal trends of the radiometric calibration of MODIS Aqua bands at 412 and 443 nm. The adjustments to the temporal trends at the beginning of the scan are minor but are significant around nadir and at the end of scan (up to 5% at 412 nm and up to 1% for 443 nm). The remaining five bands (488 to 678 nm) are adjusted with regard to their scan-angle dependence only; no temporal correction is necessary. There is no indication that the sensor polarization sensitivity needs to be modified for MODIS Aqua.

Characterization of MODIS VIS/NIR spectral band detector-to-detector differences

MODIS has 36 spectral bands with wavelengths in the visible (VIS), near-infrared (NIR), short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR). It makes observations at three nadir spatial resolutions: 0.25km for bands 1-2 (40 detectors per band), 0.5km for bands 3-7 (20 detectors per band), and 1km for bands 8-36 (10 detectors per band). The VIS, NIR, and SWIR are the reflective solar bands (RSB), which are calibrated on-orbit by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). The bi-directional reflectance factor (BRF) of the SD provides a RSB calibration reference and its on-orbit changes are tracked by the SDSM. In addition, MODIS lunar observations are regularly scheduled and used to track the RSB calibration stability. On-orbit observations show that the changes in detector response are wavelength and scan angle dependent. In this study, we focus on detector-to-detector calibration differences in the MODIS VIS/NIR spectral bands, which are determined using SD and lunar observations, while the calibration performance is evaluated using the Earth view (EV) level 1B (L1B) data products. For Aqua MODIS, the detector calibration differences and their impact are also characterized using standard ocean color data products. The current calibration approach for MODIS RSB carries a band-averaged response versus scan angle (RVS) correction. The results from this study suggest that a detector-based RVS correction should, due to changes in the scan mirrors optical properties, be implemented in order to maintain and improve the current RSB L1B data product quality, particularly, for several VIS bands in Terra MODIS.