M. Vountas

Ring effect: impact of rotational Raman scattering on radiative transfer in Earth's atmosphere.

Abstract One significant limitation to the accuracy of the remote sensing of trace gas constituents in the atmosphere, using UV-visible spectroscopy and scattered sunlight, has often been a reliable knowledge of the so-called Ring effect. In this study it is demonstrated that the filling-in of Fraunhofer and gas absorption features, resulting from Rotational Raman scattering (RRS), explains to high accuracy the Ring effect. A radiative transfer model has been adapted to include RRS and carefully validated by comparison with Ring effect data by other models and from ground-based and satellite data. The analysis of the principle components of the simulated Ring spectra enabled the Fraunhofer and gas absorption filling-in to be separated. This yields a simple, and therefore computational fast, parameterization of the Ring effect suitable for trace gas retrievals. This approach was tested for the retrieval of NO 2 which is considered to be a worst case with respect to absorption feature filling-in for a trace gas retrieved from scattered light. Analysis of the errors in the vertical column of NO 2 derived using differential optical absorption spectroscopy (DOAS) technique indicate that they are dependent on the amount of NO 2 present in the atmosphere when regarding the experimental Ring spectra. This implies that calculated Ring spectra may be superior for DOAS retrievals, compared to the experimentally determined Ring spectra.

Development, Production and Evaluation of Aerosol Climate Data Records from European Satellite Observations (Aerosol_cci)

Producing a global and comprehensive description of atmospheric aerosols requires integration of ground-based, airborne, satellite and model datasets. Due to its complexity, aerosol monitoring requires the use of several data records with complementary information content. This paper describes the lessons learned while developing and qualifying algorithms to generate aerosol Climate Data Records (CDR) within the European Space Agency (ESA) Aerosol_cci project. An iterative algorithm development and evaluation cycle involving core users is applied. It begins with the application-specific refinement of user requirements, leading to algorithm development, dataset processing and independent validation followed by user evaluation. This cycle is demonstrated for a CDR of total Aerosol Optical Depth (AOD) from two subsequent dual-view radiometers. Specific aspects of its applicability to other aerosol algorithms are illustrated with four complementary aerosol datasets. An important element in the development of aerosol CDRs is the inclusion of several algorithms evaluating the same data to benefit from various solutions to the ill-determined retrieval problem. The iterative approach has produced a 17-year AOD CDR, a 10-year stratospheric extinction profile CDR and a 35-year Absorbing Aerosol Index record. Further evolution cycles have been initiated for complementary datasets to provide insight into aerosol properties (i.e., dust aerosol, aerosol absorption).

Global Distribution of Cloud Top Height as Retrieved from SCIAMACHY Onboard ENVISAT Spaceborne Observations

The spatial and temporal analysis of the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard ENVISAT global cloud top height data for 2003–2006 is presented. The cloud top height is derived using a semi-analytical cloud top height retrieval algorithm based on an asymptotic solution of the radiative transfer equation in the oxygen A-band. The analysis is valid for thick clouds only. As expected, clouds are higher in the equatorial region. The cloud altitudes decrease towards the Poles due to the general decrease of the troposphere height. The global average cloud top height as derived from SCIAMACHY measurements is 7.3 km. We also studied the planetary reflectivity R at 443 nm and found that the annual average is R = 0.49 ± 0.08 for the years analyzed.

Global cloud top height and thermodynamic phase distributions as obtained by SCIAMACHY on ENVISAT

Global cloud top height spatial distribution as obtained using highly spectrally resolved (≈0.42 nm) SCIAMACHY on ENVISAT measurements in the oxygen A‐band is presented. Also the global cloud phase index map is given. The results were derived using semi‐analytical cloud retrieval algorithms developed by the authors specifically for SCIAMACHY cloud retrievals. The algorithm is applicable for clouds having an optical thickness larger than 5. Therefore, only thick cloud fields were selected for this study. We found that the global average cloud top height is close to 6 km and the most frequent value of the phase index is close to 0.8.

Retrieval of Terrestrial Plant Fluorescence Based on the In-Filling of Far-Red Fraunhofer Lines Using SCIAMACHY Observations

Chlorophyll fluorescence is directly linked to the photosynthetic efficiency of plants. As satellite-based remote sensing has been shown to have the potential to derive global information about fluorescence it has become subject of various recently published studies stimulating an upsurge in this research field. This manuscript presents a simple and fast retrieval method for solar induced terrestrial plant fluorescence (SIF) which relies on only a few prerequisites. The spaced based remote sensing spectrometers used in this work typically exhibit an additive spectral feature, which is not fluorescence. This is often accompanying the actual SIF retrieval and can significantly deteriorate the results. To account for this effect a correction method has been developed and is combined with the retrieval. The method has been applied to ten years of SCIAMACHY data with promising results. The retrieved SIF values are lying between 0 and 4 mW [m-²,sr-¹,nm-¹]. However, most of the retrieved values are not exceeding 1.5 [m-²,sr-¹,nm-¹], agreeing with previous studies on the subject. Results have been retrieved for SCIAMACHY spatial resolution of 240 x 30 km² and gridded to 80 arc minutes. A clear seasonal variation could be shown utilizing 10 years of SCIAMACHY data (2002-2012). In absence of large area ground based validation data a final judgment of the results presented is not feasible. However, a direct comparison to data of others was showing similar results for most areas.

XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation

A cloud identification algorithm used for cloud masking, which is based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths, has been developed for the retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance, as observed from space, is very different from that of aerosols. Clouds show a high spatial variability in the scale of a hundred metres to a few kilometres, whereas aerosols in general are homogeneous. The concept of spatial variability of reflectances at the top of the atmosphere is mainly applicable over the ocean, where the surface background is sufficiently homogeneous for the separation between aerosols and clouds. Aerosol retrievals require a sufficiently accurate cloud identification to be able to mask these ground scenes. However, a conservative mask will exclude strong aerosol episodes and a less conservative mask could introduce cloud contamination that biases the retrieved aerosol optical properties (e.g. aerosol optical depth and effective radii). A detailed study on the effect of cloud contamination on aerosol retrievals has been performed and parameters are established determining the threshold value for the MODIS aerosol cloud mask (3× 3-STD) over the ocean. The 3×3-STD algorithm discussed in this paper is the operational cloud mask used for MODIS aerosol retrievals over the ocean. A prolonged pollution haze event occurred in the northeast part of China during the period 16–21 December 2016. To assess the impact of such events, the amounts and distribution of aerosol particles, formed in such events, need to be quantified. The newly launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3 is the successor of the MEdium Resolution Imaging Spectrometer (MERIS). It provides measurements of the radiance and reflectance at the top of the atmosphere, which can be used to retrieve the aerosol optical thickness (AOT) from synoptic to global scales. In this study, the recently developed AOT retrieval algorithm eXtensible Bremen AErosol Retrieval (XBAER) has been applied to data from the OLCI instrument for the first time to illustrate the feasibility of applying XBAER to the data from this new instrument. The first global retrieval results show similar patterns of aerosol optical thickness, AOT, to those from MODIS and MISR aerosol products. The AOT retrieved from OLCI is validated by comparison with AERONET observations and a correlation coefficient of 0.819 and bias (root mean square) of 0.115 is obtained. The haze episode is well captured by the OLCI-derived AOT product. XBAER is shown to retrieve AOT well from the observations of MERIS and OLCI.

Chapter 5 – Aerosol and Cloud Bottom Altitude Covariations From Multisensor Spaceborne Measurements

Abstract In this chapter we explore covariation of fine mode aerosol optical depth (AOD fm ) with the bottom altitude of clouds. The aerosol and cloud records are derived from coincident measurements of the Advanced Along-Track Scanning Radiometer (AATSR) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), being both sensors payload of the European Environmental Satellite (Envisat), for the period 2003–2009. Upon long-term validation of the spaceborne cloud bottom height (CBH) with lidar measurements at three ground-based Atmospheric Radiation Measurement (ARM) facilities, we select six regions above water masses that are characterized by a seasonal variation between winter and summer months of both quantities. Sea surface temperature is seen to consistently determine variations of absolute CBH values, whereas CBH anomalies are mostly seen to be negatively correlated with AOD fm . In particular, this relationship holds for those regions closer to source emissions.

Improving the PhytoDOAS method to retrieve coccolithophores using hyper-spectral satellite data.

Post-graduate education in Germany has changed a lot over the past decades. Formerly, PhD students generally did not have the option to attend formal classes and lectures and were expected to conduct their independent research, including occasionally teaching courses for students. Since the introduction of bachelor and masters studies with the Bologna Process in the late 90th, the higher education in Europe has been harmonized, leading to more structured and focused studies at the expense of a broad and universal disciplinary education. At this same time, special fields such as Earth System Science became more interdisciplinary. In consequence, universities and research institutes have established so-called research schools and/or graduate schools, offering specific courses and training alongside the doctorate. Especially, Earth System Science has developed from an interesting concept in Earth Sciences education to a fully integrative Science focussed on understanding the complex system Earth. This evolution is partially due to the radical and far reaching anthropogenic changes and the general feeling of helplessness with regards to the possible consequences and future impacts on the Earth System. The Helmholtz “Earth System Science Research School” (ESSReS) is a small unit of PhD students co-organized by three educational and research institutions in the city state Bremen: University of Bremen (Institute for Environmental Physics, IUP), Jacobs University (School of Engineering and Science (JU)), and Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research in Bremerhaven (AWI). ESSReS aims at the integration of research at the interface of Geology, Biology, Physics, Geophysics, Mathematics and Informatics. It is therefore multi- and interdisciplinary in every aspect. The training, curriculum, and PhD research subjects are closely located at the interfaces between the participating disciplines. This is guaranteed by interdisciplinary supervision of the PhD project. The long-term goal of ESSReS is not only to enhance exchange and interaction between these disciplines, but to enforce a newly integrated concept, where separation between disciplines becomes more and more obsolete. Now, at the end of two three-years terms of PhD student education it can be stated that ESSReS provide a solid base for a new generation of excellent scientists in Earth and Environmental Sciences.Information about past environmental conditions is preserved in the elemental signature of biogenic marine carbonates. Thus, trace element to calcium ratios (Me/Ca) of biogenic calcium carbonates, such as bivalve shells, are often used to reconstruct past environmental conditions at the time of carbonate formation (Foster et al., 2008). In this study, we examine the suitability of the long-lived (> 400 years) bivalve Arctica islandica as a high-resolution bioarchive by measuring Me/Ca ratios in the shell carbonate. Pb/Ca concentrations in A. islandica shells reflect anthropogenic gasoline lead consumption and further provide a centennial record of lead pollution for the collection site off the coast of Virginia, USA. With A. islandica shells from the North Sea we test the hypothesis that Ba/Ca and Mn/Ca ratios are indicators of the diatom abundance. Our results indicate that statistically both ratios correlate well with the diatom abundance, and yet, on a year-to-year base, there is no consistent reflection of diatom abundance patterns in the Ba/Ca and Mn/Ca annual profiles. These findings indicate that primary production affects Ba/Ca and Mn/Ca shell ratios, though we suggest that both elements are coupled to primary production through different processes and are affected by further, yet unknown processes.To date, the software package SCIATRAN (Rozanov et al. 2002; Rozanov et al., 2005, 2008) has been used for modelling radiative processes in the atmosphere for the retrieval of trace gases from satellite data from the satellite sensor SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY onboard the satellite ENVISAT). This SCIATRAN version only accounted for radiative transfer within the atmosphere and reflection of light at the earth surface. However, radiation also passes the air-water interface, proceeds within the water and is modified by the water itself and the water constituents. Therefore, SCIATRAN has been extended by oceanic radiative transfer and coupling it to the atmospheric radiative transfer model under the terms of established models for radiative transfer underwater (Kopelevich 1983; Morel et al. 1974, 2001; Shifrin 1988; Buitevald et al. 1994; Cox and Munk 1954a, 1954b; Breon and Henriot 2006; Mobley 1994) and extending the data bases to include the specific properties of the water constituents (Pope and Fry 1997; Haltrin 2006; Prieur and Sathyendranath 1981).

DETERMINATION OF PHYTOPLANKTON CONCENTRATIONS FROM SPACE-BORNE SPECTROSCOPIC MEASUREMENTS

Since its launch into orbit on board of the ENVISAT spacecraft on March 1st, 2002, the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) continuously measures transmitted, reflected and scattered solar radiation from 220 - 2380 nm at moderate spectral resolution (0,2 nm - 1,5 nm). Global maps of atmospheric trace gas distributions are derived from these measurements using the Differential Optical Absorption Spectroscopy (DOAS) technique. Although SCIAMACHY is primarily an atmospheric mission, part of the detected solar radiation penetrates the ocean surface and picks up an absorption signal from molecular species in sea water. In the visible part of the measured spectra, spectral features of chlorophyll can clearly be identified. We show that the spectral signature of chlorophyll in SCIAMACHY spectra can be used to infer column densities of phytoplankton abundance. We present first results obtained in a case study of a phytoplankton bloom event off the West African coast in March 2003 and compare the results with ocean colour measurements of the SeaWifs instrument. While the spatial resolution of the SCIAMACHY instrument (60 x 30 km) is coarse in comparison with ocean colour instruments, we provide evidence that the detected spectral signatures have the potential of discriminating between different phytoplankton species. Finally, we investigate a method to infer chlorophyll concentration by exploiting the additional information from effective water penetration depth, which is obtained from the DOAS analysis of liquid water absorption