Kevin R. Turpie

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models.

Abstract We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll‐a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed‐layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite‐derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low‐productivity seasons as well as in sea ice‐covered/deep‐water regions. Depth‐resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption‐based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll‐a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic‐relevant parameters.

Future Retrievals of Water Column Bio-Optical Properties using the Hyperspectral Infrared Imager (HyspIRI)

Interpretation of remote sensing reflectance from coastal waters at different wavelengths of light yields valuable information about water column constituents, which in turn, gives information on a variety of processes occurring in coastal waters, such as primary production, biogeochemical cycles, sediment transport, coastal erosion, and harmful algal blooms. The Hyperspectral Infrared Imager (HyspIRI) is well suited to produce global, seasonal maps and specialized observations of coastal ecosystems and to improve our understanding of how phytoplankton communities are spatially distributed and structured, and how they function in coastal and inland waters. This paper draws from previously published studies on high-resolution, hyperspectral remote sensing of coastal

On-orbit calibration of the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite for ocean color applications

The NASA Ocean Biology Processing Group (OBPG) developed two independent calibrations of the Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) moderate resolution reflective solar bands using solar diffuser measurements and lunar observations, and implemented a combined solar- and lunar-based calibration to track temporal changes in radiometric response of the instrument. Differences between the solar and lunar data sets have been used to identify issues and verify improvements in each. Linearization of the counts-to-radiance conversion yields a more consistent calibration at low radiance levels. Correction of a recently identified error in the VIIRS solar unit vector coordinate frame has been incorporated into the solar data and diffuser screen transmission functions. Temporal trends in the solar diffuser stability monitor data have been evaluated and addressed. Fits to the solar calibration time series show mean residuals per band of 0.067%-0.17%. Periodic residuals in the VIIRS lunar data are confirmed to arise from a wavelength-dependent libration effect for the sub-spacecraft point in the output of the U.S. Geological Survey Robotic Lunar Observatory photometric model of the Moon. Temporal variations in the relative spectral responses for each band have been assessed, and significant impact on band M1 (412 nm) lunar data has been identified and rectified. Fits to the lunar calibration time series, incorporating sub-spacecraft point libration corrections, show mean residuals per band of 0.069%-0.20%. Lunar calibrations have been used to adjust the solar-derived radiometric corrections for bands M1, M3, and M4. After all corrections, the relative differences in the solar and lunar calibrations for bands M1-M7 are 0.093%-0.22%. The OBPG has achieved a radiometric stability for the VIIRS on-orbit calibration that is commensurate with those achieved for SeaWiFS and Aqua MODIS, supporting the incorporation of VIIRS data into the long-term NASA ocean color data record.

The Effects of Tidal Inundation on the Reflectance Characteristics of Coastal Marsh Vegetation

Abstract Hyperspectral and sophisticated multispectral imagery are increasingly used to obtain detailed information on species composition, condition, biomass, and other characteristics of coastal marshes. However, how differing levels of tidal inundation affect the reflectance characteristics of emergent marsh vegetation remains not well documented. In 1994–1996, general reflectance spectra were collected for three common brackish marsh species with different canopy architectures (Schoenoplectus americanus, Spartina patens, and Spartina cynosuroides) in field experiments in which changing levels of tidal inundation were simulated in specially nonreflected enclosures. Reprocessing the data with software not then available has allowed greater delineation of variations in the data, especially in the red–near-infrared boundary, that previously could not be differentiated. Spectra for all three species showed significant reductions in near-infrared reflectance (900–1100 nm) with progressive substrate inundation, the sharpest decline occurring for S. americanus, for which the narrow, tapering culms allowed substantial submergence of total aboveground biomass (and greatly decreased leaf area index [LAI]) after water depths on substrates reached 15 cm. Increasing inundation produced a particularly significant change in the 700–825-nm band of the spectral curve. Maximum peak percent reflectance shifted as much as 40 nm in these wavelengths, with two maxima over 100 nm apart in wavelength appearing in both the S. americanus and S. patens curves at water depths >30 cm. Simulations of Landsat Thematic Mapper bands show that the Normalized Difference Vegetation Index (NDVI) is highly correlated with LAI and suggest that NDVI-based estimates for marsh biomass can be strongly influenced by the effects of marsh canopy submergence on LAI.

Explaining the Spectral Red-Edge Features of Inundated Marsh Vegetation

ABSTRACT Turpie, K.R., 2013. Explaining the spectral red-edge features of inundated marsh vegetation. In a previously published experiment, canopy reflectance spectrum was measured for three monospecific canopies as water level was artificially increased. As the water rose, spectral features appeared that could not be explained by the experimenters. To better understand their published results, a combination of a shallow-water reflectance model and a canopy reflectance model was used to simulate the spectral effects observed with increasing levels of inundation. Information from the Lee shallow water, in particular, helped explain the key spectral features observed during high water levels. However, the simulation results also suggested interesting implications regarding the nonlinear mixing of water and vegetation reflection spectra as found in marsh or other flooded canopies. As water level increases, the influence of leaf reflectance below the waters surface changes the characteristics of the background aquatic spectrum. In particular, the simulation yielded a 20-nm shift in the red-edge position as water rose from the bottom to the top of the canopy, which is very similar to the experimental results. This suggests that the interaction of water and chlorophyll absorption features and leaf reflectance near the red-edge of the vegetation spectrum can significantly the influence red-edge position of an inundated canopy. This, in turn, could affect the use of the red-edge position for indicating plant condition in remote-sensing applications of inundated vegetation.

A Synthesis of VIIRS Solar and Lunar Calibrations

The NASA VIIRS Ocean Science Team (VOST) has developed two independent calibrations of the SNPP VIIRS moderate resolution reflective solar bands using solar diffuser and lunar observations through June 2013. Fits to the solar calibration time series show mean residuals per band of 0.078–0.10%. There are apparent residual lunar libration correlations in the lunar calibration time series that are not accounted for by the ROLO photometric model of the Moon. Fits to the lunar time series that account for residual librations show mean residuals per band of 0.071–0.17%. Comparison of the solar and lunar time series shows that the relative differences in the two calibrations are 0.12–0.31%. Relative uncertainties in the VIIRS solar and lunar calibration time series are comparable to those achieved for SeaWiFS, Aqua MODIS, and Terra MODIS. Intercomparison of the VIIRS lunar time series with those from SeaWiFS, Aqua MODIS, and Terra MODIS shows that the scatter in the VIIRS lunar observations is consistent with that observed for the heritage instruments. Based on these analyses, the VOST has derived a calibration lookup table for VIIRS ocean color data based on fits to the solar calibration time series.

Updates to the on-orbit calibration of SNPP VIIRS for ocean color applications

The NASA Ocean Biology Processing Group (OBPG) has continued monitoring the SNPP VIIRS on-orbit calibration since the derivation of the calibration for Reprocessing 2014.0 of the VIIRS ocean color data set. That calibration was based on solar and lunar observations through July 2014. Updates to the R2014.0 calibration include: 1) the addition of solar and lunar observations through May 2015; 2) the extension of the lunar libration corrections to incorporate sub-solar point corrections in addition to sub-spacecraft point corrections; 3) the implementation of a shortwave infrared (SWIR) band lunar and solar calibration; and 4) the absolute calibration of the solar observations using solar diffuser measurements. The SWIR band lunar calibration shows residual libration effects. Comparison of the lunar and solar time series yields lunar-derived adjustments to the solar calibration. The solar calibration time series show RMS residuals per band of 0.066–0.17%. The lunar calibration time series show RMS residuals per band of 0.072–0.23%. The solar and lunar time series show RMS differences per band of 0.10–0.23%. The VIIRS on-orbit calibration stability is comparable to that achieved for heritage instruments (SeaWiFS, Aqua MODIS). The quality of the resulting ocean color products is sufficient for incorporation of the VIIRS data into the long-term NASA ocean color data record.

Comparison of two methodologies for calibrating satellite instruments in the visible and near-infrared

Traditionally, satellite instruments that measure Earth-reflected solar radiation in the visible and near infrared wavelength regions have been calibrated for radiance responsivity in a two-step method. In the first step, the relative spectral response (RSR) of the instrument is determined using a nearly monochromatic light source such as a lamp-illuminated monochromator. These sources do not typically fill the field of view of the instrument nor act as calibrated sources of light. Consequently, they only provide a relative (not absolute) spectral response for the instrument. In the second step, the instrument views a calibrated source of broadband light, such as a lamp-illuminated integrating sphere. The RSR and the spheres absolute spectral radiance are combined to determine the absolute spectral radiance responsivity (ASR) of the instrument. More recently, a full-aperture absolute calibration approach using widely tunable monochromatic lasers has been developed. Using these sources, the ASR of an instrument can be determined in a single step on a wavelength-by-wavelength basis. From these monochromatic ASRs, the responses of the instrument bands to broadband radiance sources can be calculated directly, eliminating the need for calibrated broadband light sources such as lamp-illuminated integrating spheres. In this work, the traditional broadband source-based calibration of the Suomi National Preparatory Project Visible Infrared Imaging Radiometer Suite sensor is compared with the laser-based calibration of the sensor. Finally, the impact of the new full-aperture laser-based calibration approach on the on-orbit performance of the sensor is considered.

Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

Abstract The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite‐based sensors can repeatedly record the visible and near‐infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100‐m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short‐wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14‐bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3‐d repeat low‐Earth orbit could sample 30‐km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.