Retrieval of aerosol parameters from the oxygen A band in the presence of chlorophyll fluorescence

Abstract

Abstract.We have investigated the precision of retrieved aerosol parameters for a generic aerosol retrieval algorithm over vegetated land using the O 2 A band. Chlorophyll fluorescence is taken into account in the forward model. Fluorescence emissions are modeled as isotropic contributions to the upwelling radiance field at the surface and they are retrieved along with aerosol parameters. Precision is calculated by propagating measurement errors and a priori errors, including model parameter errors, using the forward model's derivatives. Measurement errors consist of noise and calibration errors. The model parameter errors considered are related to the single scattering albedo, surface pressure and temperature profile. We assume that measurement noise is dominated by shot noise; thus, results apply to grating spectrometers in particular. We describe precision for various atmospheric states, observation geometries and spectral resolutions of the instrument in a number of retrieval simulations. These precision levels can be compared with user requirements. A comparison of precision estimates with the literature and an analysis of the dependence on the a priori error in the fluorescence emission indicate that aerosol parameters can be retrieved in the presence of chlorophyll fluorescence: if fluorescence is present, fluorescence emissions should be included in the state vector to avoid biases in retrieved aerosol parameters.

Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

“…Since approximately 1%-2% of the absorbed solar energy by vegetation is released as fluorescence (against typically about 19% released as heat and about 80% used for photosynthesis [29]), capturing the SiF requires sensors with good signal-to-noise ratios (and fine spectral resolutions, see below). At the same time, SiF may potentially interfere with retrieval of other atmospheric properties [30,31].…”

Comparison of dust-layer heights from active and passive satellite sensors

“…In the absence of clouds, these bands contain information on the aerosol height (Wang et al, 2012). The algorithm developed at KNMI within the TROPOMI/Sentinel-5 Precursor programme (Veefkind et al, 2012) is based on the optimal estimation method and aims to derive the aerosol-layer height (Sanders and de Haan, 2013). This method has also been applied to Greenhouse gases Observing SATellite (GOSAT) and GOME-2 data within the ongoing ESA AeroPro study, in support of the Sentinel-4 development.…”

“…The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CloudAerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite , and https: //www-calipso.larc.nasa.gov/) provides detailed vertical information with a vertical resolution of 30 m below 8.2 km and a horizontal footprint of 335 m. Passive solar and thermal infrared satellite instruments may provide global data on a daily basis with horizontal resolution of the order of tens of kilometres. For example, Vandenbussche et al (2013) retrieved desert dust aerosol vertical profiles from Infrared Atmospheric Sounding Interferometer (IASI) measurements; Cuesta et al (2015) described the three-dimensional distribution of a dust outbreak over eastern Asia, including dust height and also using IASI measurements; Sanders and de Haan (2013) used the O 2 A-band to retrieve aerosol-layer height from the Global Ozone Monitoring Experiment-2A (GOME-2A). Dust top height may also be estimated using stereo view techniques by either utilizing instruments with multi-angle capabilities (for example the Advanced Along Track Scanning Radiometer, AATSR, Virtanen et al, 2014) or by combining measurement from different sensors (see for example Merucci et al, 2016).…”

Comparison of dust layer heights from active and passive satellite sensors

“…The algorithm developed at KNMI within the TROPOMI/Sentinel 5 Precursor programme (Veefkind et al, 2012) is based on the optimal estimation method and aims at deriving the aerosol layer height (Sanders and de Haan, 2013). This method has also been applied to Greenhouse gases Observing SATellite (GOSAT) and GOME-2 data within the on-going ESA AEROPRO study, in support of the Sentinel-4 development.…”

“…The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite (Winker et al, 2009, and https://www-calipso.larc.nasa.gov/) provides detailed vertical information with a vertical resolution of 30 m below 8.2 km and a horizontal footprint of 335 m. Passive solar and thermal infrared satellite instruments may provide global data on a daily basis with horizontal resolution on the order of tens of km. For example Vandenbussche et al (2013) 15 retrieved desert dust aerosol vertical profiles from Infrared Atmospheric Sounding Interferometer (IASI) measurements; Cuesta et al (2015) described the three-dimensional distribution, including dust height, of a dust outbreak over East Asia also using IASI measurements; Sanders and de Haan (2013) used the O 2 A-band to retrieve aerosol layer height from the Global Ozone Monitoring Experiment-2A (GOME). Dust top height may also be estimated using stereo view techniques by either utilizing instruments with multi-angle capabilities (for example the Advanced Along Track Scanning Radiometer, AATSR, Virtanen…”