A Dark Target Algorithm for the GOSAT TANSO-CAI Sensor in Aerosol Optical Depth Retrieval over Land

Cloud and Aerosol Imager (CAI) onboard the Greenhouse Gases Observing Satellite (GOSAT) is a multi-band sensor designed to observe and acquire information on clouds and aerosols. In order to retrieve aerosol optical depth (AOD) over land from the CAI sensor, a Dark Target (DT) algorithm for GOSAT CAI was developed based on the strategy of the Moderate Resolution Imaging Spectroradiometer (MODIS) DT algorithm. When retrieving AOD from satellite platforms, determining surface contributions is a major challenge. In the MODIS DT algorithm, surface signals in the visible wavelengths are estimated based on the relationships between visible channels and shortwave infrared (SWIR) near the 2.1 µm channel. However, the CAI only has a 1.6 µm band to cover the SWIR wavelengths. To resolve the difficulties in determining surface reflectance caused by the lack of 2.1 μm band data, we attempted to analyze the relationship between reflectance at 1.6 µm and at 2.1 µm. We did this using the MODIS surface reflectance product and then connecting the reflectances at 1.6 µm and the visible bands based on the empirical relationship between reflectances at 2.1 µm and the visible bands. We found that the reflectance relationship between 1.6 µm and 2.1 µm is typically dependent on the vegetation conditions, and that reflectances at 2.1 µm can be parameterized as a function of 1.6 µm reflectance and the Vegetation Index (VI). Based on our experimental results, an Aerosol Free Vegetation Index (AFRI2.1)-based regression function connecting the 1.6 µm and 2.1 µm bands was summarized. Under light aerosol loading (AOD at 0.55 µm < 0.1), the 2.1 µm reflectance derived by our method has an extremely high correlation with the true 2.1 µm reflectance (r-value = 0.928). Similar to the MODIS DT algorithms (Collection 5 and Collection 6), a CAI-applicable approach that uses AFRI2.1 and the scattering angle to account for the visible surface signals was proposed. It was then applied to the CAI sensor for AOD retrieval; the retrievals were validated by comparisons with ground-level measurements from Aerosol Robotic Network (AERONET) sites. Validations show that retrievals from the CAI have high agreement with the AERONET measurements, with an r-value of 0.922, and 69.2% of the AOD retrieved data falling within the expected error envelope of ± (0.1 + 15% AODAERONET)

PHOTONS/AERONET sunphotometer network overview. Description – Activities - Results

Fourteenth International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics celebrado del 24 al 30 de junio de 2007 en Buryatia, Russia

Remote sensing of aerosols by using polarized, directional and spectral measurements within the A-Train: the PARASOL mission

Instruments dedicated to aerosol monitoring are recently available and the POLDER (POLarization and Directionality of the Earth's Reflectances) instrument on board the PARASOL (Polarization &amp; Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) mission is one of them. By measuring the spectral, angular and polarization properties of the radiance at the top of the atmosphere, in coordination with the other A-Train instruments, PARASOL provides the aerosol optical depths (AOD) as well as several optical and microphysical aerosol properties. The instrument, the inversion schemes and the list of aerosol parameters are described. Examples of retrieved aerosol parameters are provided as well as innovative approaches and further inversion techniques

Challenges and New Advances in Ocean Color Remote Sensing of Coastal Waters

Knowing that coastal areas concentrate about 60% of the world's population (within 100 km from the coast), that 75-90% of the global sink of suspended river load takes place in coastal waters in which about 15% of the primary production occurs, the ecological, societal and economical value of these areas are obvious (fish resources, aquaculture, water quality information, recreation areas management, global carbon budget, etc). In that context, precise assessment of suspended particulate matter (SPM) concentrations and of the phenomena controlling its temporal variability is a key objective for many research fields in coastal areas. SPM which encompasses organic (living and non-living) and inorganic matter controls the penetration of light into the water and brings new nutrients into the system, both key parameters influencing phytoplankton primary production. Concentrations and availability of SPM are also known to control rates of food intake, growth and reproduction for various filter feeder organisms. Phytoplankton is highly sensitive to environmental perturbations (such as nutrient inputs, light, and turbulence). The abundance, biomass and dynamics of phytoplankton in coastal areas therefore reflect the prevailing environmental conditions and represent key parameters for assessing information on the ecological conditions, as well as on the coastal water quality. Because phytoplankton is highly sensitive to environmental perturbations [1], its distribution patterns and temporal variability represent good indicators of the ecological conditions of a defined region [2, 3]. Coastal waters also host complex ecosystems and represent important fishery areas that support industry and provide livelihood to coastal settlements. The food chain in the coastal ocean is generally short (especially in upwelling systems, having as low as three trophic levels) whereas the open ocean food web presents up to six trophic levels [4]. As a result, when compared to the open ocean, a relative lower fraction of the primary production gets respired in the coastal ocean while a higher fraction reaches the uppermost trophic level (fish) [5] or is exported to adjacent areas (coastal or open sea)..

Retrieval of Aerosol Microphysical Properties from AERONET Photopolarimetric Measurements

Atmospheric aerosols play an important role in earth climate by scattering and absorbing solar and terrestrial radiation, and indirectly through altering the cloud formation, life- time, and radiative properties. However, accurate quantification of these effects is in no small part hindered by our limited knowledge about the particle size distribution (PSD) and refractive index, the aerosol microphysical properties essentially pertain to aerosol optical and cloud-forming properties. The research goal of this thesis is to obtain the aerosol microphysical properties of both fine and coarse modes from the polarimetric solar radiation measured by the SunPhotometer of the Aerosol Robotic Network (AERONET). We achieve so by (1) developing an inversion algorithm that integrates rigorous radiative transfer model with a statistical optimization approach, (2) conducting a sensitivity study and error budgeting exercise to examine the potential value of adding polarization to the current radiance-only inversion, and (3) performing retrievals using available AERONET polarimetric measurements. The results from theoretical information and error analysis indicate a remarkable increase in information by adding additional polarization into the inversion: an overall increase of 2–5 of degree of freedom for signal comparing with radiance-only measurements. Correspond- ingly, retrieval uncertainty can be reduced by 79% (57%), 76% (49%), 69% (52%), 66% (46%), and 49% (20%) for the fine-mode (coarse-mode) aerosol volume concentration, the effective radius, the effective variance, the real part of refractive index, and single scattering albedo (SSA), respectively, resulting in their retrieval errors of 2.3% (2.9%), 1.3% (3.5%), 7.2% (12%), 0.005 (0.035), and 0.019 (0.068). In real cases, we demonstrate that our retrievals are overall consistent with current AERONET operational inversions, but can offer mode-resolved refractive index and SSA with sufficient accuracy for the aerosol composed by spherical particles. Along with the polarimetric retrieval, we also performed radiance-only retrieval to reveal the improvements by adding polarization in the inversion. The comparison analysis indicates that with polar- ization, retrieval error can be reduced by over 50% in PSD parameters, by 10–30% in the refractive index, and by 10–40% in SSA, which is consistent with the theoretical results. Adviser: Jun Wan

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia

Profiling of fine and coarse particle mass : Case studies of Saharan dust and Eyjafjallajökull/Grimsvötn volcanic plumes

© Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 LicenseThe polarization lidar photometer networking (POLIPHON) method introduced to separate coarse-mode and fine-mode particle properties of Eyjafjallajokull volcanic aerosols in 2010 is extended to cover Saharan dust events as well. Furthermore, new volcanic dust observations performed after the Grimsvotn volcanic eruptions in 2011 are presented. The retrieval of particle mass concentrations requires mass-specific extinction coefficients. Therefore, a review of recently published mass-specific extinction coefficients for Saharan dust and volcanic dust is given. Case studies of four different scenarios corroborate the applicability of the profiling technique: (a) Saharan dust outbreak to central Europe, (b) Saharan dust plume mixed with biomass-burning smoke over Cape Verde, and volcanic aerosol layers originating from (c) the Eyjafjallajokull eruptions in 2010 and (d) the Grimsvotn eruptions in 2011. Strong differences in the vertical aerosol layering, aerosol mixing, and optical properties are observed for the different volcanic eventsPeer reviewe

Global observations of aerosol-cloud-precipitation-climate interactions: Global observations of aerosol-cloud-precipitation-climateinteractions

Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects ofmeteorology fromthose of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing.Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol-cloud-precipitation-climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing