Assessment of Superflux relative to marine science and oceanography

A general assessment of the Superflux project is made in relation to marine science and oceanography. It is commented that the program clearly demonstrated the effectiveness of state-of-the-art technology required to study highly dynamic estuarine plumes, and the necessity of a broadly interdisciplinary, interactive remote sensing and shipboard program required to significantly advance the understanding of transport processes and impacts of estuarine outflows

Applications of ISES for the oceans

The need in oceanography for direct broadcast, why, and what type are discussed. Four reasons for support exist: need for real-time observations in support of field studies; need to back up point failures; need for experimentation with onboard processing and selection of data for direct broadcasting; and the need to develop future operational NOAA systems. Each of these areas is examined

Superflux I, II, and III experiment design: Remote sensing aspects

The Chesapeake Bay plume study called Superflux is described. The study was initiated to incorporate the disciplines of both resources management and remote sensing in accomplishing the following objectives: (1) process oriented research to understand the impact of estuarine outflows on continental shelf ecosystems; (2) monitoring and assessment to delineate the role of remote sensing in future monitoring and assessment programs; and (3) remote sensing research: to advance the state of the art in remote sensing systems as applied to sensing of the marine environment, thereby hastening the day when remote sensing can be used operationally for monitoring and assessment and for process oriented research

Satellite detection of phytoplankton export from the mid-Atlantic Bight during the 1979 spring bloom

Analysis of Coastal Zone Color Scanner (CZCS) imagery confirms shipboard and in situ moored fluorometer observations of resuspension of near-bottom chlorophyll within surface waters (1 to 10 m) by northwesterly wind events in the mid-Atlantic Bight. As much as 8 to 16 micrograms chl/l are found during these wind events from March to May, with a seasonal increase of algal biomass until onset of stratification of the water column. Rapid sinking or downwelling apparently occurs after subsequent wind events, however, such that the predominant surface chlorophyll pattern is approx. 0.5 to 1.5 micrograms/l over the continental shelf during most of the spring bloom. Perhaps half of the chlorophyll increase observed by satellite during a wind resuspension event represents in-situ production during the 4 to 5 day interval, with the remainder attributed to accumulation of algal biomass previously produced and temporarily stored within near-bottom water. Present calculations suggest that about 10% of the primary production of the spring bloom may be exported as ungrazed phytoplankton carbon from mid-Atlantic shelf waters to those of the continental slope

Spatial patterns in temperature and chlorophyll on Nantucket Shoals from airborne remote sensing data, May 7-9, 1981

Spatial patterns in 4 aerial mappings of temperature and chlorophyll over Nantucket Shoals were analyzed using a variety of statistical techniques. The goal was to determine whether statistical methods could provide insight concerning phytoplankton dynamics on the Shoals. Statistical techniques included a covariance analysis of large scale trends and a spectral analysis of detrended data. Airborne remote sensors had provided the necessary synopticity in which to observe temporal variability on scales of 0.5–2 days. Maximum correlations between chlorophyll, temperature and depth occurred at nonzero lags, suggesting westward movement of water over the Shoals and a time lag in phytoplankton growth. Covariance patterns in data taken at the same time of day and phase of tide are notably similar. Power spectra of chlorophyll in 2 distinct regions of phytoplankton patches were different in shape. Horizontal variation in nutrients affecting growth rates on scales of 10–25 km could account for the differences

Analysis of ALOPE data from Superflux

Remote sensing data collected with the airborne lidar oceanographic probing experiment (ALOPE) laser fluorosensor during the Superflux 1 and Superflux 2 experiments were analyzed using two techniques. A qualitative technique which requires no supplementary data provided a near-real-time estimate of relative abundance of the golden-brown and green phytoplankton color groups. Contour plots developed for the later mission are used to demonstrate the utility of this technique. A quantitative technique which requires supplementary data to define the attenuation coefficient provides chlorophyll a concentration by color group. The sum of the golden-brown and green chlorophyll a data yields total chlorophyll a values which may be compared with in situ data. As expected, the golden-brown population was dominant in the Chesapeake Bay and the Bay plume whereas the green population was dominant in shelf waters

An Empirical Approach to Ocean Color Data: Reducing Bias and the Need for Post-Launch Radiometric Re-Calibration

A new empirical approach is developed for ocean color remote sensing. Called the Empirical Satellite Radiance-In situ Data (ESRID) algorithm, the approach uses relationships between satellite water-leaving radiances and in situ data after full processing, i.e., at Level-3, to improve estimates of surface variables while relaxing requirements on post-launch radiometric re-calibration. The approach is evaluated using SeaWiFS chlorophyll, which is the longest time series of the most widely used ocean color geophysical product. The results suggest that ESRID 1) drastically reduces the bias of ocean chlorophyll, most impressively in coastal regions, 2) modestly improves the uncertainty, and 3) reduces the sensitivity of global annual median chlorophyll to changes in radiometric re-calibration. Simulated calibration errors of 1% or less produce small changes in global median chlorophyll (less than 2.7%). In contrast, the standard NASA algorithm set is highly sensitive to radiometric calibration: similar 1% calibration errors produce changes in global median chlorophyll up to nearly 25%. We show that 0.1% radiometric calibration error (about 1% in water-leaving radiance) is needed to prevent radiometric calibration errors from changing global annual median chlorophyll more than the maximum interannual variability observed in the SeaWiFS 9-year record (+/- 3%), using the standard method. This is much more stringent than the goal for SeaWiFS of 5% uncertainty for water leaving radiance. The results suggest ocean color programs might consider less emphasis of expensive efforts to improve post-launch radiometric re-calibration in favor of increased efforts to characterize in situ observations of ocean surface geophysical products. Although the results here are focused on chlorophyll, in principle the approach described by ESRID can be applied to any surface variable potentially observable by visible remote sensing

SeaWiFS technical report series. Volume 31: Stray light in the SeaWiFS radiometer

Some of the measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) will not be useful as ocean measurements. For the ocean data set, there are procedures in place to mask the SeaWiFS measurements of clouds and ice. Land measurements will also be masked using a geographic technique based on each measurment's latitude and longitude. Each of these masks involves a source of light much brighter than the ocean. Because of stray light in the SeaWiFS radiometer, light from these bright sources can contaminate ocean measurements located a variable number of pixels away from a bright source. In this document, the sources of stray light in the sensor are examined, and a method is developed for masking measurements near bright targets for stray light effects. In addition, a procedure is proposed for reducing the effects of stray light in the flight data from SeaWiFS. This correction can also reduce the number of pixels masked for stray light. Without these corrections, local area scenes must be masked 10 pixels before and after bright targets in the along-scan direction. The addition of these corrections reduces the along-scan masks to four pixels before and after bright sources. In the along-track direction, the flight data are not corrected, and are masked two pixels before and after. Laboratory measurements have shown that stray light within the instrument changes in a direct ratio to the intensity of the bright source. The measurements have also shown that none of the bands show peculiarities in their stray light response. In other words, the instrument's response is uniform from band to band. The along-scan correction is based on each band's response to a 1 pixel wide bright sources. Since these results are based solely on preflight laboratory measurements, their successful implementation requires compliance with two additional criteria. First, since SeaWiFS has a large data volume, the correction and masking procedures must be such that they can be converted into computationally fast algorithms. Second, they must be shown to operate properly on flight data. The laboratory results, and the corrections and masking procedures that derive from them, should be considered as zeroeth order estimates of the effects that will be found on orbit

SeaWiFS technical report series. Volume 23: SeaWiFS prelaunch radiometric calibration and spectral characterization

Based on the operating characteristics of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), calibration equations have been developed that allow conversion of the counts from the radiometer into Earth-existing radiances. These radiances are the geophysical properties the instrument has been designed to measure. SeaWiFS uses bilinear gains to allow high sensitivity measurements of ocean-leaving radiances and low sensitivity measurements of radiances from clouds, which are much brighter than the ocean. The calculation of these bilinear gains is central to the calibration equations. Several other factors within these equations are also included. Among these are the spectral responses of the eight SeaWiFS bands. A band's spectral response includes the ability of the band to isolate a portion of the electromagnetic spectrum and the amount of light that lies outside of that region. The latter is termed out-of-band response. In the calibration procedure, some of the counts from the instrument are produced by radiance in the out-of-band region. The number of those counts for each band is a function of the spectral shape of the source. For the SeaWiFS calibration equations, the out-of-band responses are converted from those for the laboratory source into those for a source with the spectral shape of solar flux. The solar flux, unlike the laboratory calibration, approximates the spectral shape of the Earth-existing radiance from the oceans. This conversion modifies the results from the laboratory radiometric calibration by 1-4 percent, depending on the band. These and other factors in the SeaWiFS calibration equations are presented here, both for users of the SeaWiFS data set and for researchers making ground-based radiance measurements in support of Sea WiFS

SeaWiFS technical report series. Volume 28: SeaWiFS algorithms, part 1

This document provides five brief reports that address several algorithm investigations sponsored by the Calibration and Validation Team (CVT) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. This volume, therefore, has been designated as the first in a series of algorithm volumes. Chapter 1 describes the initial suite of masks, used to prevent further processing of contaminated radiometric data, and flags, which are employed to mark data whose quality (due to a variety of factors) may be suspect. In addition to providing the mask and flag algorithms, this chapter also describes the initial strategy for their implementation. Chapter 2 evaluates various strategies for the detection of clouds and ice in high latitude (polar and sub-polar regions) using Coastal Zone Color Scanner (CZCS) data. Chapter 3 presents an algorithm designed for detecting and masking coccolithosphore blooms in the open ocean. Chapter 4 outlines a proposed scheme for correcting the out-of-band response when SeaWiFS is in orbit. Chapter 5 gives a detailed description of the algorithm designed to apply sensor calibration data during the processing of level-1b data