Study of atmospheric and bidirectional effects on surface reflectance and vegetation index time series: Application to NOAA AVHRR and preparation for future space missions

The objectives of the investigation, namely 'to characterize the atmospheric and directional effects on surface reflectance and vegetation index using the First International Satellite Cloud Climatology Project (ISLCSP) Field Experiment (FIFE) data set, develop new algorithms to obtain better Advanced Very High Resolution Radiometer (AVHRR) indices, and define possible improvements for future satellite missions', were addressed in three separate, yet complementary studies. First, it was shown, from theoretical calculations, that visible and near infrared reflectances combined linearly at optimum (one or two) viewing angles relate linearly to the fraction of photosynthetically available radiation absorbed by plants, f(sub par), can be used independently of the type of foliage and substrate, eliminate the effects of sub-pixel spatial heterogeneity, and improve the accuracy of the f(sub par) estimates when compared to the Normalized Difference Vegetation Index, NDVI. Second, it was demonstrated that NDVI, even though it is not a linear combination of radiances or reflectances, can be spatially integrated without significant loss of information from scales of 300 to 1000 m. Third, AVHRR visible and near-infrared reflectances over the FIFE site, separating temporal and bidirectional components and determining the model parameters through an original iterative scheme was successfully modeled. It appears that NDVI generated from the top-of-atmosphere reflectances normalized by the bidirectional effects (as determined in the scheme) is a better vegetation index than maximum NDVI. Details about the three studies are presented

Estimating Photosynthetically Available Radiation (PAR) at the Earth's surface from satellite observations

Current satellite algorithms to estimate photosynthetically available radiation (PAR) at the earth' s surface are reviewed. PAR is deduced either from an insolation estimate or obtained directly from top-of-atmosphere solar radiances. The characteristics of both approaches are contrasted and typical results are presented. The inaccuracies reported, about 10 percent and 6 percent on daily and monthly time scales, respectively, are useful to model oceanic and terrestrial primary productivity. At those time scales variability due to clouds in the ratio of PAR and insolation is reduced, making it possible to deduce PAR directly from insolation climatologies (satellite or other) that are currently available or being produced. Improvements, however, are needed in conditions of broken cloudiness and over ice/snow. If not addressed properly, calibration/validation issues may prevent quantitative use of the PAR estimates in studies of climatic change. The prospects are good for an accurate, long-term climatology of PAR over the globe

Bayesian Methodology for Ocean Color Remote Sensing

66 pagesThe inverse ocean color problem, i.e., the retrieval of marine reflectance from top-of-atmosphere (TOA) reflectance, is examined in a Bayesian context. The solution is expressed as a probability distribution that measures the likelihood of encountering specific values of the marine reflectance given the observed TOA reflectance. This conditional distribution, the posterior distribution, allows the construction of reliable multi-dimensional confidence domains of the retrieved marine reflectance. The expectation and covariance of the posterior distribution are computed, which gives for each pixel an estimate of the marine reflectance and a measure of its uncertainty. Situations for which forward model and observation are incompatible are also identified. Prior distributions of the forward model parameters that are suitable for use at the global scale, as well as a noise model, are determined. Partition-based models are defined and implemented for SeaWiFS, to approximate numerically the expectation and covariance. The ill-posed nature of the inverse problem is illustrated, indicating that a large set of ocean and atmospheric states, or pre-images, may correspond to very close values of the satellite signal. Theoretical performance is good globally, i.e., on average over all the geometric and geophysical situations considered, with negligible biases and standard deviation decreasing from 0.004 at 412 nm to 0.001 at 670 nm. Errors are smaller for geometries that avoid Sun glint and minimize air mass and aerosol influence, and for small aerosol optical thickness and maritime aerosols. The estimated uncertainty is consistent with the inversion error. The theoretical concepts and inverse models are applied to actual SeaWiFS imagery, and comparisons are made with estimates from the SeaDAS standard atmospheric correction algorithm and in situ measurements. The Bayesian and SeaDAS marine reflectance fields exhibit resemblance in patterns of variability, but the Bayesian imagery is less noisy and characterized by different spatial de-correlation scales, with more realistic values in the presence of absorbing aerosols. Experimental errors obtained from match-up data are similar to the theoretical errors determined from simulated data. Regionalization of the inverse models is a natural development to improve retrieval accuracy, for example by including explicit knowledge of the space and time variability of atmospheric variables

Monthly surface thermal forcing in the tropical Pacific from 1980 to 1983

Monthly distributions of surface latent heat flux and solar irradiance in the tropical Pacific were computed from observations of the scanning multichannel microwave radiometer on Nimbus-7 and the visible infrared spin scan radiometer on GOES-W. They are the dominant variable components of the surface heat flux, the sum of which gives the approximate thermal forcing on the ocean. Monthly maps of this sum, from January 1980 to September 1983, and within 20 deg N and 20 deg S, 180 deg and 80 deg W, are presented

Inversion Schemes to Retrieve Atmospheric and Oceanic Parameters from SeaWiFS Data

Firstly, we have analyzed atmospheric transmittance and sky radiance data connected at the Scripps Institution of Oceanography pier, La Jolla during the winters of 1993 and 1994. Aerosol optical thickness at 870 nm was generally low in La Jolla, with most values below 0.1 after correction for stratospheric aerosols. For such low optical thickness, variability in aerosol scattering properties cannot be determined, and a mean background model, specified regionally under stable stratospheric component, may be sufficient for ocean color remote sensing, from space. For optical thicknesses above 0. 1, two modes of variability characterized by Angstrom exponents of 1.2 and 0.5 and corresponding, to Tropospheric and Maritime models, respectively, were identified in the measurements. The aerosol models selected for ocean color remote sensing, allowed one to fit, within measurement inaccuracies, the derived values of Angstrom exponent and 'pseudo' phase function (the product of single scattering albedo and phase function), key atmospheric correction parameters. Importantly, the 'pseudo' phase function can be derived from measurements of the Angstrom exponent. Shipborne sun photometer measurements at the time of satellite overpass are usually sufficient to verify atmospheric correction for ocean color

Comments on the "Spatial variability of coastal surface water temperature during upwelling"

International audienceComments on the article "Spatial variability of coastal surface water temperature during upwelling

Satellite determination of the mesoscale variability of the sea surface temperature

International audienceSatellite infrared data have been used to investigate the mesoscale variability of the SST (sea surface temperature) field. A statistical analysis of the SST field has been performed by means of the structure function. Results give the equivalent power-law exponent n of the spatial variance density spectrum E(k) ∼ k−h. The exponent n was found to vary from 1.5 to 2,3 with a mean value of 1.8 in the ]range of scales 3–100 km which is in agreement with previous one-dimensional analysis from shipborne and airborne measurements. These observed values of n are discussed and compared with the values predicted by turbulence theories

Atmospheric correction of satellite optical imagery over the río de la plata highly turbid waters using a SWIR-based principal component decomposition technique

Estimating water reflectance accurately from satellite optical data requires implementing an accurate atmospheric correction (AC) scheme, a particularly challenging task over optically complex water bodies, where the signal that comes from the water prevents using the near-infrared (NIR) bands to separate the perturbing atmospheric signal. In the present work, we propose a new AC scheme specially designed for the Río de la Plata—a funnel-shaped estuary in the Argentine– Uruguayan border—highly scattering turbid waters. This new AC scheme uses far shortwave infrared (SWIR) bands but unlike previous algorithms relates the atmospheric signal in the SWIR to the signal in the near-infrared (NIR) and visible (VIS) bands based on the decomposition into principal components of the atmospheric signal. We describe the theoretical basis of the algorithm, analyze the spectral features of the simulated principal components, theoretically address the impact of noise on the results, and perform match-ups exercises using in situ measurements and Moderate Resolution Imaging Spectrometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) imagery over the region. Plausible water reflectance retrievals were obtained in the NIR and VIS bands from both simulations and match-ups using field data—with better performance (i.e., lowest errors and offsets, and slopes closest to 1) compared to existing AC schemes implemented in the NASA Data Analysis Software (SeaDAS). Moreover, retrievals over images in the VIS and NIR bands showed low noise, and the correlation was low between aerosol and water reflectance spatial fields.Fil: Gossn, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Frouin, Robert. University of California at San Diego. Scripps Institution of Oceanography; Estados UnidosFil: Dogliotti, Ana Inés. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentin

Satellite-derived photosynthetically available and total solar irradiance at the surface during FIFE's intensive field campaigns

Satellite-derived photosynthetically available and total solar irradiance at the surface during First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment's (FIFE) intensive field compaigns are addressed. Graphs showing photosynthetically available radiation (PAR) vs. Julian Day and insolation vs. Julian Day are included

Automatic detection of optical signatures within and around floating Tonga - Fiji pumice rafts using MODIS, VIIRS, and OLCI Satellite Sensors

An underwater volcanic eruption off the Vava’u island group in Tonga on 7 August 2019 resulted in the creation of floating pumice on the ocean’s surface extending over an area of 150 km2. The pumice’s far-reaching effects from its origin in the Tonga region to Fiji and the methods of automatic detection using satellite imagery are described, making it possible to track the westward drift of the pumice raft over 43 days. Level 2 Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-3 Ocean and Land Color Instrument (OLCI), and Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) imagery of sea surface temperature, chlorophyll-a concentration, quasi-surface (i.e., Rayleigh-corrected) reflectance, and remote sensing reflectance were used to distinguish consolidated and fragmented rafts as well as discolored and mesotrophic waters. The rafts were detected by a 1 to 3.5 °C enhancement in the MODIS-derived “sea surface temperature” due to the emissivity difference of the raft material. Large plumes of discolored waters, characterized by higher satellite reflectance/backscattering of particles in the blue than surrounding waters (and corresponding to either submersed pumice or associated white minerals), were associated with the rafts. The discolored waters had relatively lower chlorophyll-a concentration, but this was artificial, resulting from the higher blue/red reflectance ratio caused by the reflective pumice particles. Mesotrophic waters were scarce in the region of the pumice rafts, presumably due to the absence of phytoplanktonic response to a silicium-rich pumice environment in these tropical oligotrophic environments. As beach accumulations around Pacific islands surrounded by coral shoals are a recurrent phenomenon that finds its origin far east in the ocean along the Tongan trench, monitoring the events from space, as demonstrated for the 7 August 2019 eruption, might help mitigate their potential economic impacts