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NASA NTRS2017

Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.

SMAPVEX15↗

NASA NTRS2016

Wearable Biosensor Monitor to Support Autonomous Crew Health and Performance

During future human exploration missions, spaceflight crews will encounter adverse health outcomes and decrements in performance during the missions and for long term health. The Psychophysiological Research Lab is currently conducting a technology demonstration of a prototype wearable biosensor system (Astroskin) on astronaut surrogates during 30 day missions within NASAs Human Exploration Research Analog (HERA). HERA, located at Johnson Spaceflight Center, represents a flight analog for simulation of isolation, confinement and remote conditions of mission exploration scenarios. Astroskin, an autonomous medical monitoring system, consists of an intelligent garment for the upper body and a headband fitted with sensors, and associated software and hardware that can measure, transmit and store vital signs (ECG, respiration, blood pressure, etc.), sleep quality and activity level of the wearer. One of the main goals of the technology demonstration is to evaluate the performance of the Astroskin system (i.e., data quality), crew usability and comfort. To validate the Astroskin as a viable option for use during future spaceflight missions, crew data from HERA are sent to Ames researchers for processing and analyses. Crew surveys on usability and comfort will also be evaluated. This work supports the Exploration Medical Capabilities element within NASAs Human Research Program.

space analog↗

NASA NTRS1998

OCTS and SeaWiFS Bio-Optical Algorithm and Product Validation and Intercomparison in US Coastal Waters

The successful launch of the National Space Development Agency of Japan (NASDA) Ocean Color and Temperature Sensor (OCTS) in August 1996, and the launch of Orbital Science Corporation's (OSC) Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) in August 1997 signaled the beginning of a new era for ocean color research and application. These data may be used to remotely evaluate 1) water quality, 2) transport of sediments and adhered pollutants, 3) primary production, upon which commercial shellfish and finfish populations depend for food, and 4) harmful algal blooms which pose a threat to public health and economies of affected areas. Several US government agencies have recently expressed interest in monitoring U.S. coastal waters using optical remote sensing. This renewed interest is broadly driven by 1) resource management concerns over the impact of coastward shifts in population and land use on the ecosystems of estuaries, wetlands, nearshore benthic environments and fisheries, 2) recognition of the need to understand short time scale global change due to urbanization of sensitive land-margin ecosystems, and 3) national security issues. Satellite ocean color sensors have the potential to furnish data at the appropriate time and space scales to evaluate and resolve these concerns and problems. In this draft technical memorandum, we outline our progress during the first year of our SIMBIOS project to evaluate ocean color bio-optical algorithms and products generated using OCTS and SeaWiFS data in coastal US waters.

Brown, Christopher W.↗

NASA NTRS1998

Development of a System to Assess Biofilm Formation in the International Space Station

The design requirements for the water treatment systems aboard the International Space Station (ISS) include and require recycling as much water as possible and to treat the water for intentional contamination (hygiene, urine distillate, condensate, etc.) and unintentional contamination in the form of biofilm and microorganisms. As part of an effort to address the latter issue, a biofilm system was developed by Marshall Space Flight Center (MSFC) to simulate the conditions aboard ISS with respect to materials, flow rates, water conditions, water content, and handling. The tubing, connectors, sensors, and fabricated parts included in the system were chosen for specific attributes as applicable to emulate an orbital water treatment system. This paper addresses the design and development process of the system, as well as the configuration, operation, and system procedures for maintenance to assure that the simulation is valid for the representative data as it applies to water degradation and biofilm/microbial growth. Preliminary biofilm/microbial results are also presented.

Charles E Martin↗

NASA NTRS2004

Optimization of Ocean Color Algorithms: Application to Satellite Data Merging

The objective of the program is to develop and validate a procedure for ocean color data merging, which is one of the major goals of the SIMBIOS project. As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized water-leaving radiances L((sub wN)(lambda)) from single or multiple sensors and uses them in the inversion of a semi-analytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) It works with single or multiple data sources regardless of their specific bands; 2) It exploits band redundancies and band differences; 3) It accounts for uncertainties in the L((sub wN)(lambda)) data; 4) It provides uncertainty estimates for the retrieved variables.

Ritorena, Stephane↗

NASA NTRS1996

On-orbit application of H-infinity to the middeck active controls experiment: Overview of results

The Middeck Active Control Experiment (MACE) was successfully completed during the flight of STS-67 in March 1995. MACE provided an on-orbit validation of modem robust control theory and system identification techniques through the testing of a flexible, multi-instrument, science platform in the micro-gravity environment of the Space Shuttle's Middeck. As part of this experiment, H-infinity control design was validated in zero gravity (0-G) environment. The control objective was to isolate a payload sensor from a 5O Hz bandwidth disturbance occurring on the test article. Controllers were designed with the use of finite element models developed using 1 -G measurements and a measurement model obtained by applying system identification techniques to open loop data obtained on orbit. Over 50 single-input, single-output and multi-input, multi-output, single and multi-axis H-infinity control designs were evaluated on-orbit. Up to 19 dB reduction in vibration levels and 25 Hz bandwidth of control were achieved.

Woods-Vedeler, Jessica A.↗

NASA NTRS2001

In Situ Aerosol Optical Thickness Collected by the SIMBIOS Program (1997-2000): Protocols, and and Data QC and Analysis

The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project Office activities on in situ aerosol optical thickness (i.e., protocols, and data QC and analysis). This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.

Fargion, Giulietta S.↗

NASA NTRS2019

Passive/active Microwave Soil Moisture Change Disaggregation Using Smapvex12 Data

The SMAPVEX12 (Soil Moisture Active Passive (SMAP) Validation Experiment 2012) experiment was conducted during June-July 2012 in Manitoba, Canada with the goal of collecting remote sensing data and ground measurements for the development and testing of soil moisture retrieval algorithms under varying vegetation and soil conditions for the SMAP satellite. The aircraft based soil moisture data provided by the passive/active microwave sensor PALS (Passive and Active L-band System) has a nominal spatial resolution of 1600 m. However, this resolution is not compatible with agricultural, meteorological and hydrological studies that require high spatial resolutions and this issue can be solved by soil moisture disaggregation. The soil moisture disaggregation algorithm integrates radiometer soil moisture retrievals and high-resolution radar observations and it can provide soil moisture estimates at a finer scale than the radiometer data alone. In this study, a change detection algorithm was used for disaggregation of coarse resolution passive microwave soil moisture retrievals with radar backscatter coefficients obtained from the higher spatial resolution UAVSAR (Unmanned Air Vehicle Synthetic Aperture Radar) at crop field scale. The accuracy of the disaggregated change in soil moisture was evaluated using ground based soil moisture measurements collected during SMAPVEX12 campaign. The results showed that soil moisture spatial variabilities were better characterized by the disaggregated change in soil moisture estimates at 5 m / 800 m resolution as well as good agreement with in situ measurements. It also showed that VWC (Vegetation Water Content) did not have a big impact on disaggregation algorithm performance, with R2 of the disaggregated results ranging 0.628-0.794. The 5 m and 800m resolution disaggregated soil moisture did no show significant difference in statistical performance variables.

Radar Backscatter↗

NASA NTRS2013

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in-land water bodies. Results presented are from the 10 April 2013 overflight of the Monterey Bay region and focus primarily on the first objective - sensitivity to atmospheric correction. On-going and future work will continue to evaluate if PHYDOTax can be applied to historical (SeaWiFS and MERIS), existing (MODIS, VIIRS, and HICO), and future (PACE, GEO-CAPE, and HyspIRI) satellite sensors. Demonstration of cross-platform continuity may aid in calibration and validation efforts of these sensors.

Biological Oceanography↗

NASA NTRS2003

Viewing Atmospheric Aerosols from the MODIS Satellite Sensor

The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, complementing field and modeling efforts to produce a comprehensive picture of aerosol characteristics. The three years of Terra-MODIS data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the MODIS aerosol optical thickness retrievals are accurate to within the pre-launch expectations, on a global basis. The global statistics, however, can hide local biases in the product. Some of these biases will be discussed. Nevertheless, the products can be used and are currently being used to answer some pressing questions concerning aerosol radiative forcing, aerosol-cloud interaction, estimating aerosol sources and height of transport, and Air Quality forecasting. A survey of current applications of MODIS aerosol products will be presented.

Remer, L.↗

NASA NTRS2007

Sampling Biases in MODIS and SeaWiFS Ocean Chlorophyll Data

Although modem ocean color sensors, such as MODIS and SeaWiFS are often considered global missions, in reality it takes many days, even months, to sample the ocean surface enough to provide complete global coverage. The irregular temporal sampling of ocean color sensors can produce biases in monthly and annual mean chlorophyll estimates. We quantified the biases due to sampling using data assimilation to create a "truth field", which we then sub-sampled using the observational patterns of MODIS and SeaWiFS. Monthly and annual mean chlorophyll estimates from these sub-sampled, incomplete daily fields were constructed and compared to monthly and annual means from the complete daily fields of the assimilation model, at a spatial resolution of 1.25deg longitude by 0.67deg latitude. The results showed that global annual mean biases were positive, reaching nearly 8% (MODIS) and >5% (SeaWiFS). For perspective the maximum interannual variability in the SeaWiFS chlorophyll record was about 3%. Annual mean sampling biases were low (<3%) in the midlatitudes (between -40deg and 40deg). Low interannual variability in the global annual mean sampling biases suggested that global scale trend analyses were valid. High latitude biases were much higher than the global annual means, up to 20% as a basin annual mean, and over 80% in some months. This was the result of the high solar zenith angle exclusion in the processing algorithms. Only data where the solar angle is <75deg are permitted, in contrast to the assimilation which samples regularly over the entire area and month. High solar zenith angles do not facilitate phytoplankton photosynthesis and consequently low chlorophyll concentrations occurring here are missed by the data sets. Ocean color sensors selectively sample in locations and times of favorable phytoplankton growth, producing overestimates of chlorophyll. The biases derived from lack of sampling in the high latitudes varied monthly, leading to artifacts in the apparent seasonal cycle from ocean color sensors. A false secondary peak in chlorophyll occurred in May-August, which resulted from lack of sampling in the Antarctic.

Gregg, Watson W.↗

NASA NTRS2003

Estimating Uncertainty in GPCP and TRMM Multi-Satellite Precipitation Estimates

One of the high-priority problems in satellite precipitation estimation is developing algorithms for estimating the errors in precipitation retrievals by individual sensors and subsequent multi-satellite combinations. Classically, we distinguish between "random" and "bias" errors, which do and do not, respectively average to zero over a "big enough" time/space sample. The current operational GPCP and TRMM multi-satellite algorithms are nearly unique in estimating random error for the monthly precipitation estimates from individual sensor systems (including gauge), following Huffman, and then making multi-sensor combinations. No routinely operational global precipitation produces estimates of bias error. Subsequently, a similar scheme has been followed to provide random error estimates for the Multi-satellite Precipitation Analysis (MPA) being computed in real time and after real time for TRMM. The Huffman algorithm for random error is briefly reviewed, including a discussion of the limitations imposed on the algorithm by standard monthly precipitation data sets. Starting from a very simple theoretical treatment of the histogram of precipitation samples in a month, an equation is developed that depends on the estimated average precipitation rate for the month, the number of samples in the month, and two constants. The constants are set separately for each source of precipitation estimate (such as "raingauge") by calibration at selected ground sites. We discuss recent work validating the random error estimates to highlight the successes and limitations of this first-generation approach. We then consider what information is needed from the individual sensor algorithms to facilitate additional accuracy in the estimation of random errors across the time/space span of climate regimes which a global estimation system must handle. In addition, the thorny issue of estimating bias is raised. Finally, the role of error estimates (and the qualitative errors!) in creating combinations of precipitation estimates from different individual sensors is discussed. This issue is particularly important when fine scales in space and time are being considered, say the 0.25 x 0.25-deg 3-hourly estimates in the MPA.

Huffman, G. J.↗

NASA NTRS2017

Wearable Biosensor Monitor to Support Autonomous Crew Health and Readiness to Perform

For future human exploration missions, NASA needs a health monitoring system composed of hardware that is compact, fully interoperable with an integrated data management system, and requires minimal consumables. Such a system will be achieved through the integration of small, easy to use biomedical sensors that will have the ability to measure, store and transmit physiological parameters during operational and ambulatory activity. Since 2012, the Canadian Space Agency (CSA) has been active in funding the development of wearable biomonitoring sensors. The Astroskin is the first prototype and consists of a shirt-based garment and headband with embedded sensors, and associated software and technology that measure vital signs, sleep quality and activity level of the wearer. NASA and CSA have been collaborating since 2014 to test and validate this system in a lab environment at Ames Research Center and more recently in the Human Exploration Research Analog (HERA) located at Johnson Spaceflight Center. Specific objectives of the HERA study were: 1) to assess the performance of the Astroskin biosensor system for long-term health monitoring (24-hours) capabilities and during exercise as a measure of crew fitness; 2) to obtain crew feedback on comfort and usability of the Astroskin system; 3) to demonstrate performance of Bluetooth communication during real-time transmission and for verification of data in this environment; and 4) to obtain baseline data for further development of algorithms and tools that facilitate decision support for diagnosing and monitoring of a sick or injured crewmember. HERA Campaign 3 included four missions (each 30-days in duration) with four crewmembers assigned to each mission. A total of 9 men and 7 women participated in the Astroskin evaluation that included continuous physiological monitoring (24-hours) on mission days MD-11, MD1 (high workload), MD15 (low workload), MD19, MD29, and MD+7. Mission days 19 and 29 also included 30 minutes of sub-maximal exercise on a cycle ergometer. Following each 24-hour monitoring session crew physiological data were downloaded to laptops and each crewmember completed a 28 question survey on their experiences with the Astroskin hardware and software. This presentation will focus on lessons learned from the HERA missions. Specifically it will address Astroskin system performance in terms of data loss and data quality (no comparison to lab standard devices), wireless communication with the onboard mobile device, crew usability and comfort, and future development of a next generation biomonitoring system.

crew fitness↗

NASA NTRS1987

Some data processing requirements for precision Nap-Of-the-Earth (NOE) guidance and control of rotorcraft

Nap-Of-the-Earth (NOE) flight in a conventional helicopter is extremely taxing for two pilots under visual conditions. Developing a single pilot all-weather NOE capability will require a fully automatic NOE navigation and flight control capability for which innovative guidance and control concepts were examined. Constrained time-optimality provides a validated criterion for automatically controlled NOE maneuvers if the pilot is to have confidence in the automated maneuvering technique. A second focus was to organize the storage and real-time updating of NOE terrain profiles and obstacles in course-oriented coordinates indexed to the mission flight plan. A method is presented for using pre-flight geodetic parameter identification to establish guidance commands for planned flight profiles and alternates. A method is then suggested for interpolating this guidance command information with the aid of forward and side looking sensors within the resolution of the stored data base, enriching the data content with real-time display, guidance, and control purposes. A third focus defined a class of automatic anticipative guidance algorithms and necessary data preview requirements to follow the vertical, lateral, and longitudinal guidance commands dictated by the updated flight profiles and to address the effects of processing delays in digital guidance and control system candidates. The results of this three-fold research effort offer promising alternatives designed to gain pilot acceptance for automatic guidance and control of rotorcraft in NOE operations.

Clement, Warren F.↗

NASA NTRS2009

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Balaban, Edward↗

NASA NTRS2011

Next-Generation Aura/OMI NO2 and SO2 Products

The measurement of both SO2 and NO2 gases are recognized as an essential component of atmospheric composition missions. We describe current capabilities and limitations of the operational Aura/OMI NO2 and SO2 data that have been used by a large number of researchers. Analyses of the data and validation studies have brought to light a number of areas in which these products can be expanded and improved. Major improvements for new NASA standard (SP) NO2 product include more accurate tropospheric and stratospheric column amounts, along with much improved error estimates and diagnostics. Our approach uses a monthly NO2 climatology based on the NASA Global Modeling Initiative (GMI) chemistry-transport model and takes advantage of OMI data from cloudy scenes to find clean areas where the contribution from the trap NO2 column is relatively small. We then use a new filtering, interpolation and smoothing techniques for separating the stratospheric and tropospheric components of NO2, minimizing the influence of a priori information. The new algorithm greatly improves the structure of stratospheric features relative to the original SP. For the next-generation OMI SO2 product we plan to implement operationally the offline iterative spectral fitting (ISF) algorithm and re-process the OMI Level-2 SO2 dataset using a priori SO2 and aerosol profiles, clouds, and surface reflectivity appropriate for observation conditions. This will improve the ability to detect and quantify weak tropospheric SO2 loadings. The new algorithm is validated using aircraft in-situ data during field campaigns in China (2005 and 2008) and in Maryland (Frostburg, 2010 and DISCOVER-AQ in July 2011). The height of the SO2 plumes will also be estimated for high SO2 loading cases (e.g., volcanic eruptions). The same SO2 algorithm will be applied to the data from OMPS sensor to be launched on NPP satellite later this year. The next-generation NO2 and SO2 products will provide critical information (e.g., averaging kernels) for evaluation of chemistry-transport models, for data assimilation, and to impose top-down constraints on the SO2 and NO2 emission sources.

Krotkov, Nickolay↗

NASA NTRS2016

On-Orbit Calibration and Performance of S-NPP VIIRS DNB

The S-NPP VIIRS instrument has successfully operated since its launch in October 2011. The VIIRS Day-Night Band (DNB) is a panchromatic channel covering wavelengths from 0.5 to 0.9 m that is capable of observing Earth scenes during both day and nighttime orbits at a spatial resolution of 750 m. To cover the large dynamic range, the DNB operates at low, mid, or high gain stages, and it uses an onboard solar diffuser (SD) for its low gain stage calibration. The SD observations also provide a means to compute gain ratios of low-to-mid and mid-to-high gain stages. This paper describes the DNB on-orbit calibration methodologies used by the VIIRS Characterization Support Team (VCST) in supporting the NASA earth science community with consistent VIIRS sensor data records (SDRs) made available by the Land Science Investigator-led Processing Systems (SIPS). It provides an assessment and update of DNB on-orbit performance, including the SD degradation in the DNB spectral range, detector gain and gain ratio trending, stray light contamination and its correction. Also presented in this paper are performance validations based on earth scenes and lunar observations.

Chen, H.↗

NASA NTRS1994

Coastal zone color scanner 'system calibration': A retrospective examination

During its lifetime the Coastal Zone Color Scanner (CZCS) produced approximately 66,000 images. These have been placed in an archive of 'raw' radiance (sensor counts) in a subsampled format that is easily accessible. They have also been processed to form global fields, at reduced resolution, of normalized water-leaving radiance, phytoplankton pigments, and diffuse attenuation coefficient. Using this archive, we have tried to characterize some aspects of the 'system calibration' for the 8-year lifetime of CZCS. Specifically, we have assumed that the sensitivity of the red band decayed in a simple manner similar to the well-known long-term degradation of the shorter-wavelength bands, and we examined the sensitivity of the green and yellow bands by computing the globally averaged water-leaving radiance, over 10-day periods, for all of the imagery. The results provided evidence that in addition to the long-term degradation, short-term (2 weeks to 1 month) variations in the radiometric sensitivity of these bands started in early fall 1981 and continued for the rest of the mission. In contrast, the data suggested the absence of such variations prior to August 1981. It is reasonable to believe that the sensitivity of the blue (and probably the red) band underwent such variations as well; however our methodology cannot be used to study the other bands. Thus, after these fluctuations began, the actual values of CZCS - estimated pigment concentrations at a given location should be viewed with skepticism; however, the global patterns of derived pigment concentrations should be valid. Had an extensive set of surface measurements of water-leaving radiance, e.r., from moored buoyes or drifters, had been available during the CZCS mission, these fluctuations could have been removed from the data set, and this would have greatly increased its value. The lessons learned from CZCS that is, the requirement of good radiometric calibration and stability and the necessity of 'sea truth' stations to monitor the performance of the system (sensor plus algorithms), are being applied to the sea-viewing wide-field-of-view senso (Sea WiFS) scheduled for launch in August 1993.

Evans, Robert H.↗