T. Dinter

Universität Bremen, Bremen, Bremen, Germany

Are you T. Dinter?

Claim your profile

Publications (40)66.81 Total impact

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Chlorophyll fluorescence is directly linked to the physiology of phytoplankton or plants. Here, we present a new satellite remote sensing approach to retrieve chlorophyll fluorescence at its red peak (~ 685 nm) by using measurements from the hyperspectral instruments SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) and Global Ozone Monitoring Experiment-2 (GOME-2). This method, which is based on the Differential Optical Absorption Spectroscopy (DOAS) technique, was used to exploit narrow spectral structures resulting from the filling-in of the Fraunhofer Fe I line, which originates from fluorescence. The reference spectra for chlorophyll fluorescence were calculated by the coupled ocean–atmosphere radiative transfer model SCIATRAN. We compared our results on marine chlorophyll fluorescence observations with the MODIS Terra normalized Fluorescence Line Height (nFLH) product for the average of years 2003–2011 and year 2009. Our method also enables the retrieval of chlorophyll fluorescence above land vegetation scenes. The results for the fluorescence observed above terrestrial vegetation for July and December 2009 were compared to MODIS Enhanced Vegetation Index (EVI). The comparisons show good spatial agreement between different retrievals providing evidence for the good performance of our algorithm. The method presented is generic and can be applied to other hyperspectral instruments in the future. Having established the retrieval technique, extensive studies of chlorophyll fluorescence will improve global knowledge on physiology and photosynthetic efficiency, in both the marine and terrestrial realms, and its dependence on environmental factors.
    Remote Sensing of Environment 07/2015; 166. DOI:10.1016/j.rse.2015.05.018 · 6.39 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The availability of light in the ocean is an important parameter for the determination of phytoplankton photosynthesis processes and primary production from satellite data. It is also a useful parameter for other applications, e.g. the determination of heat fluxes. In this study, a method was developed utilising the vibrational Raman scattering (VRS) effect of water molecules to determine the number of photons available in the ocean water, which is expressed by the depth integrated scalar irradiance E0. Radiative transfer simulations with the SCIATRAN fully coupled ocean–atmosphere radiative transfer model (RTM) show clearly the relationship of E0 with the strength of the VRS signal measured at the top of the atmosphere (TOA). Taking advantage of VRS structures in hyper-spectral satellite measurements, a retrieval technique to derive E0 in the wavelength region from 390 to 444.5 nm was developed. This approach uses the weighting function differential optical absorption spectroscopy (WF-DOAS) technique, applied to TOA radiances, measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). Based on the approach of Vountas et al. (2007), where the DOAS method was used to fit modelled spectra of VRS, the method was improved by using the weighting function of VRS (VRS-WF) in the DOAS fit. This was combined with a look-up table (LUT) technique, where the E0 value was obtained for each VRS satellite fit directly. The VRS-WF and the LUT were derived from calculations with the SCIATRAN RTM (Rozanov et al., 2014). RTM simulations for different chlorophyll a concentrations and illumination conditions clearly show that low fit factors of VRS retrieval results correspond to low amounts of light in the water column and vice versa. Exemplarily, 1 month of SCIAMACHY data were processed and a global map of the depth integrated scalar irradiance E0 was retrieved. Spectral structures of VRS were clearly identified in the radiance measurements of SCIAMACHY. The fitting approach led to consistent results and the WF-DOAS algorithm results of VRS correlated clearly with the chlorophyll concentration in case-I water. Comparisons of the diffuse attenuation coefficient, extracted by VRS fit results, with the established GlobColour Kd(490) product show consistent results.
    Ocean Science Discussions 05/2015; 12(1):31-81. DOI:10.5194/osd-12-31-2015 · 0.94 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer – MERIS – Polymer product developed by Steinmetz et al., 2011) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.
    Ocean Science 02/2015; 11:139-158. DOI:10.5194/os-11-139-2015 · 1.96 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Diatoms are the major marine primary producers on the global scale and, recently, several methods have been developed to retrieve their abundance or dominance from satellite remote sensing data. In this work, we highlight the importance of the Southern Ocean (SO) in developing a global algorithm for diatom using an Abundance Based Approach (ABA). A large global in situ data set of phytoplankton pigments was compiled, particularly with more samples collected in the SO. We revised the ABA to take account of the information on the penetration depth (Z(pd)) and to improve the relationship between diatoms and total chlorophyll-a (TChla). The results showed that there is a distinct relationship between diatoms and TChla in the SO, and a new global model (ABA(Zpd)) improved the estimation of diatoms abundance by 28% in the SO compared with the original ABA model. In addition, we developed a regional model for the SO which further improved the retrieval of diatoms by 17% compared with the global ABA(Zpd) model. As a result, we found that diatom may be more abundant in the SO than previously thought. Linear trend analysis of diatom abundance using the regional model for the SO showed that there are statistically significant trends, both increasing and decreasing, in diatom abundance over the past eleven years in the region.
    Remote Sensing 10/2014; 6(10):10089-10106. DOI:10.3390/rs61010089 · 3.18 Impact Factor
  • Source
    M.A. Soppa · T. Dinter · B. B. Taylor · A. Bracher
    [Show abstract] [Hide abstract]
    ABSTRACT: The paper 'Satellite derived euphotic depth in the Southern Ocean: Implications for primary production modelling’ contains an error in the validation of satellite phytoplankton absorption. The main conclusions are not affected by this error and the corrected results are presented here.
    Remote Sensing of Environment 01/2014; 140:717-718. DOI:10.1016/j.rse.2013.10.013 · 6.39 Impact Factor
  • M.A. Soppa · T. Dinter · B. B. Taylor · A. Bracher
    [Show abstract] [Hide abstract]
    ABSTRACT: The euphotic depth (Z(eu)) is a key parameter in modelling primary production (PP) using satellite ocean colour. However, evaluations of satellite Z(eu) products are scarce. The objective of this paper is to investigate existing approaches and sensors to estimate Z(eu) from satellite and to evaluate how different Z(eu) products might affect the estimation of PP in the Southern Ocean (SO). Euphotic depth was derived from MODIS and SeaWiFS products of (i) surface chlorophyll-a (Z(eu)-Chla) and (ii) inherent optical properties (Z(eu)-IOP). They were compared with in situ measurements of Z(eu) from different regions of the SO. Both approaches and sensors are robust to retrieve Z(eu), although the best results were obtained using the IOP approach and SeaWiFS data, with an average percentage of error (E) of 25.43% and mean absolute error (MAE) of 0.10 m (log scale). Nevertheless, differences in the spatial distribution of Z(eu)-Chla and Z(eu)-IOP for both sensors were found as large as 30% over specific regions. These differences were also observed in PP. On average, PP based on Z(eu)-Chla was 8% higher than PP based on Z(eu)-IOP, but it was up to 30% higher south of 60 degrees S. Satellite phytoplankton absorption coefficients (a(ph)) derived by the Quasi-Analytical Algorithm at different wavelengths were also validated and the results showed that MODIS a(ph) are generally more robust than SeaWiFS. Thus, MODIS a(ph) should be preferred in PP models based on a(ph) in the SO. Further, we reinforce the importance of investigating the spatial differences between satellite products, which might not be detected by the validation with in situ measurements due to the insufficient amount and uneven distribution of the data. (c) 2013 Elsevier Inc. All rights reserved.
    Remote Sensing of Environment 10/2013; 137:198-211. DOI:10.1016/j.rse.2013.06.017 · 6.39 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Phycobiliproteins are a family of water-soluble pigment proteins that play an important role as accessory or antenna pigments and absorb in the green part of the light spectrum poorly used by chlorophyll a. The phycoerythrins (PEs) are one of four types of phycobiliproteins that are generally distinguished based on their absorption properties. As PEs are water-soluble, they are generally not captured with conventional pigment analysis. Here we present a statistical model based on in situ measurements of three transatlantic cruises which allows us to derive relative PE concentration from standardized hyperspectral underwater radiance measurements (Lu). The model relies on Empirical Orthogonal Function (EOF) analysis of Lu spectra and subsequent Generalized Linear Model with measured PE concentrations as the response variable and EOF loadings as predictor variables. The method is used to predict relative PE concentrations throughout the water column and to calculate integrated PE estimates based on those profiles.
    Journal of Geophysical Research Atmospheres 06/2013; 118(6):2948–2960. DOI:10.1002/jgrc.20201 · 3.44 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The goal of this study was to improve PhytoDOAS, which is a new retrieval method for quantitative identification of major phytoplankton functional types (PFTs) using hyper-spectral satellite data. PhytoDOAS is an extension of the Differential Optical Absorption Spectroscopy (DOAS, a method for detection of atmospheric trace gases), developed for remote identification of oceanic phytoplankton groups. Thus far, PhytoDOAS has been successfully exploited to identify cyanobacteria and diatoms over the global ocean from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) hyper-spectral data. This study aimed to improve PhytoDOAS for remote identification of coccolithophores, another functional group of phytoplankton. The main challenge for retrieving more PFTs by PhytoDOAS is to overcome the correlation effects between different PFT absorption spectra. Different PFTs are composed of different types and amounts of pigments, but also have pigments in common, e.g. chl a, causing correlation effects in the usual performance of the PhytoDOAS retrieval. Two ideas have been implemented to improve PhytoDOAS for the PFT retrieval of more phytoplankton groups. Firstly, using the fourth-derivative spectroscopy, the peak positions of the main pigment components in each absorption spectrum have been derived. After comparing the corresponding results of major PFTs, the optimized fit-window for the PhytoDOAS retrieval of each PFT was determined. Secondly, based on the results from derivative spectroscopy, a simultaneous fit of PhytoDOAS has been proposed and tested for a selected set of PFTs (coccolithophores, diatoms and dinoflagellates) within an optimized fit-window, proven by spectral orthogonality tests. The method was then applied to the processing of SCIAMACHY data over the year 2005. Comparisons of the PhytoDOAS coccolithophore retrievals in 2005 with other coccolithophore-related data showed similar patterns in their seasonal distributions, especially in the North Atlantic and the Arctic Sea. The seasonal patterns of the PhytoDOAS coccolithophores indicated very good agreement with the coccolithophore modeled data from the NASA Ocean Biochemical Model (NOBM), as well as with the global distributions of particulate inorganic carbon (PIC), provided by MODIS (MODerate resolution Imaging Spectroradiometer)-Aqua level-3 products. Moreover, regarding the fact that coccolithophores belong to the group of haptophytes, the PhytoDOAS seasonal coccolithophores showed good agreement with the global distribution of haptophytes, derived from synoptic pigment relationships applied to SeaWiFS chl a. As a case study, the simultaneous mode of PhytoDOAS has been applied to SCIAMACHY data for detecting a coccolithophore bloom which was consistent with the MODIS RGB image and the MODIS PIC map of the bloom, indicating the functionality of the method also in short-term retrievals.
    Ocean Science 11/2012; 8(6):1055-1070. DOI:10.5194/os-8-1055-2012 · 1.96 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: We are proposing the development of an algorithm, using the combination of data from OCLI (Sentinel-3) and Sentinel-5P sensors, which derives globally pyhtoplankton groups (phytoplankton functional types) biomass. The information of the total biomass will be achieved by standard processing of the Chlorophyll-a (chl-a) concentration using satellite data from multispectral imaging instruments (firstly SeaWiFS, MODIS and MERIS merged within the GlobColour data set, later OLCI data). The percentage of the main phytoplankton types on the total biomass will be retrieved by the analysis of characteristic absorption features in hyperspectral satellite measurements (firstly SCIAMACHY, later Sentinel-5-P) using the PhytoDOAS method by Bracher et al. (2009) and improved by Sadeghi et al. (2011). Thus, a synergistic product from information of multi- and hyperspectral satellite instruments which complements one another will be developed. The two instruments of the Sentinel mission will enable a data product of weekly to monthly temporal and 7 km by 7 km spatial resolution. On the the SCIAMACHY/Globcolour product (starting in 2002 until today) will be limited to a monthly and 0.5° degree resolution. The application of the algorithm is for assessing the spatial and temporal variability of specific phytoplankton types' biomass on longer time scale (10 to 20 and more years) with global coverage. This will engross the understanding of the role of different phytoplankton types in the world ocean's ecosystem and improve estimates on the contribution of different phytoplankton types to the global carbon cycle. The concept of the algorithm development, including its uncertainity determined via validaton with in-situ phytoplankton data and sensitivity studies using the coupled atmospheric-oceanic radiative transfer model SCIATRAN (Rozanov et al. 2002, Blum et al. in press) and examples for its application are given in the presentation.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this study temporal variations of coccolithophore blooms are investigated using satellite data. Eight years, from 2003 to 2010, of data of SCIAMACHY, a hyper-spectral satellite sensor on-board ENVISAT, were processed by the PhytoDOAS method to monitor the biomass of coccolithophores in three selected regions. These regions are characterized by frequent occurrence of large coccolithophore blooms. The retrieval results, shown as monthly mean time-series, were compared to related satellite products, including the total surface phytoplankton, i.e., total chlorophyll-a (from GlobColour merged data) and the particulate inorganic carbon (from MODIS-Aqua). The inter-annual variations of the phytoplankton bloom cycles and their maximum monthly mean values have been compared in the three selected regions to the variations of the geophysical parameters: sea-surface temperature (SST), mixed-layer depth (MLD) and surface wind speed, which are known to affect phytoplankton dynamics. For each region the anomalies and linear trends of the monitored parameters over the period of this study have been computed. The patterns of total phytoplankton biomass and specific dynamics of coccolithophores chlorophyll-a in the selected regions are discussed in relation to other studies. The PhytoDOAS results are consistent with the two other ocean color products and support the reported dependencies of coccolithophore biomass' dynamics to the compared geophysical variables. This suggests, that PhytoDOAS is a valid method for retrieving coccolithophore biomass and for monitoring its bloom developments in the global oceans. Future applications of time-series studies using the PhytoDOAS data set are proposed, also using the new upcoming generations of hyper-spectral satellite sensors with improved spatial resolution.
    Biogeosciences Discussions 12/2011; 8(6):11725-11765. DOI:10.5194/bgd-8-11725-2011
  • [Show abstract] [Hide abstract]
    ABSTRACT: The goal of this study was to improve PhytoDOAS, which is a new retrieval method for quantitative identification of major Phytoplankton Functional Types (PFTs) using hyper-spectral satellite data. PhytoDOAS is an extension of the Differential Optical Absorption Spectroscopy (DOAS, a method for detection of atmospheric trace gases), developed for remote identification of oceanic phytoplankton groups. Thus far, PhytoDOAS has been successfully exploited to identify cyanobacteria and diatoms over the global ocean from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) hyper-spectral data. The main challenge for retrieving more PFTs by PhytoDOAS is to overcome the correlation effects between different PFTs' absorption spectra. Different PFTs are composed of different types and amounts of pigments, but also have pigments in common, e.g., chl-a, causing correlation effects in the usual performance of the PhytoDOAS retrieval. Two ideas have been implemented to improve PhytoDOAS for the PFT retrieval of more phytoplankton groups. Firstly, using the fourth-derivative spectroscopy, the peak positions of the main pigment components in each absorption spectrum have been derived. After comparing the corresponding results of major PFTs, the optimized fit-window for the PhytoDOAS retrieval of each PFT was determined. Secondly, based on the results from derivative spectroscopy, simultaneous fit of PhytoDOAS has been proposed and tested for a selected set of PFTs (coccolithophores, diatoms and dinoflagllates) within an optimized fit-window. The method was then applied to the processing of SCIAMACHY data over the year 2005. Comparisons of the PhytoDOAS PFT retrievals in 2005 with the modeled PFT data from the NASA Ocean Biochemical Model (NOBM) showed similar patterns in their seasonal distributions for diatoms and coccolithophores, especially in the northern parts of the global ocean. The seasonal patterns of the PhytoDOAS coccolithophores indicated very good agreement with the global distributions of Particulate Inorganic Carbon (PIC) provided by MODIS (MODerate resolution Imaging Spectroradiometer)-Aqua level-3 products. Since PIC is known as a proxy for the abundance of coccolithophores (in open ocean), the latter agreement indicates the basic functionality of the method in retrieving coccolithophores. Moreover, as a case study, the simultaneous mode of PhytoDOAS has been applied to SCIAMACHY data for detecting a coccolithophore bloom around New Zealand (reported by NASA from MODIS imagery in December 2009); the result was quite consistent with the MODIS RGB image and the MODIS PIC map of the bloom, indicating the functionality of the method in short-term retrievals.
    Ocean Science Discussions 11/2011; 8(6):2271-2311. DOI:10.5194/osd-8-2271-2011 · 0.94 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Since clouds play an essential role in the Earth&apos;s climate system, it is important to understand the cloud characteristics as well as their distribution on a global scale using satellite observations. The main scientific objective of SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) onboard the ENVISAT satellite is the retrieval of vertical columns of trace gases. On the one hand, SCIAMACHY has to be sensitive to low variations in trace gas concentrations which means the ground pixel size has to be large enough. On the other hand, such a large pixel size leads to the problem that SCIAMACHY spectra are often contaminated by clouds. SCIAMACHY spectral measurements are not well suitable to derive a reliable sub-pixel cloud fraction that can be used as input parameter for subsequent retrievals of cloud properties or vertical trace gas columns. Therefore, we use MERIS/ENVISAT spectral measurements with its high spatial resolution as sub-pixel information for the determination of MerIs Cloud fRation fOr Sciamachy (MICROS). Since MERIS covers an even broader swath width than SCIAMACHY, no problems in spatial and temporal collocation of measurements occur. This enables the derivation of a SCIAMACHY cloud fraction with an accuracy much higher as compared with other current cloud fractions that are based on SCIAMACHY&apos;s PMD (Polarization Measurement Device) data. We present our new developed MICROS algorithm, based on the threshold approach, as well as a qualitative validation of our results with MERIS satellite images for different locations, especially with respect to bright surfaces such as snow/ice and sands. In addition, the SCIAMACHY cloud fractions derived from MICROS are intercompared with other current SCIAMACHY cloud fractions based on different approaches demonstrating a considerable improvement regarding geometric cloud fraction determination using the MICROS algorithm.
    Atmospheric Measurement Techniques 02/2011; 3(4). DOI:10.5194/amtd-3-3601-2010 · 3.21 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: For the determination of aerosol optical thickness (AOT) Bremen AErosol Retrieval (BAER) has been developed. Method and main features on the aerosol retrieval are described together with validation and results. The retrieval separates the spectral aerosol reflectance from surface and Rayleigh path reflectance for the shortwave range of the measured spectrum of top-of-atmosphere reflectance for wavelength less than 0.670 μm. The advantage of MERIS (Medium Resolution Imaging Spectrometer on the Environmental Satellite – ENVISAT – of the European Space Agency – ESA) and SeaWiFS (Sea viewing Wide Field Sensor on OrbView-2 spacecraft) observations is the availability of several spectral channels in the blue and visible range enabling the spectral determination of AOT in 7 (or 6) channels (0.412–0.670 μm) and additionally channels in the NIR, which can be used to characterize the surface properties. A dynamical spectral surface reflectance model for different surface types is used to obtain the spectral surface reflectance for this separation. The normalized differential vegetation index (NDVI), taken from the satellite observations, is the model input. Further surface bi-directional reflectance distribution function (BRDF) is considered by the Raman-Pinty-Verstraete (RPV) model. Spectral AOT is obtained from aerosol reflectance using look-up-tables, obtained from radiative transfer calculations with given aerosol phase functions and single scattering albedos either from aerosol models, given by model package "optical properties of aerosol components" (OPAC) or from experimental campaigns. Validations of the obtained AOT retrieval results with data of Aerosol Robotic Network (AERONET) over Europe gave a preference for experimental phase functions derived from almucantar measurements. Finally long-term observations of SeaWiFS have been investigated for 11 year trends in AOT. Western European regions have negative trends with decreasing AOT with time. For the investigated Asian region increasing AOT have been found.
    01/2011; 3(3). DOI:10.5194/amt-4-151-2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Results of a new methodology for retrievals of surface particulate matter concentration (PM10) from satellite reflectance measurements over Germany are presented in this paper. The retrieval derives effective radii from Ångström-alpha exponents and benefits from the fitting of a smooth spectral slope from seven MERIS spectrometer channels. Comparisons with ground measurements from the air quality surveillance show standard deviations of 33.9% with -18.9% bias over Hamburg. Over rural sites a standard deviation of 17.9% (bias 12.9%) is reached. We discuss critically limitations and potential applications of the retrieval. Additionally, we talk about the aspects at comparing of retrieved particulate matter with ground station measurements.
    Atmospheric Measurement Techniques 01/2011; 4(3). DOI:10.5194/amt-4-523-2011 · 3.21 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Natural, short-lived halocarbons play a role in the stratospheric ozone budget, besides the anthropogenic emitted long-lived chlorine- and bromine fluorocarbons. The tropical oceans are a known source of reactive iodine and bromine to the atmosphere in the form of iodinated and brominated methanes (VSLS), as methyl iodide (CH3I), dibromomethane (CH2Br2) and bromoform (CHBr3), which contributes to reactive bromine within the lower stratosphere. Elevated atmospheric concentrations above the oceans are related to oceanic super-saturations of the compounds, caused by photochemical and biological production. The tropical Western Pacific is of special interest since it is a largely uncharacterized region for the oceanic compounds and in certain regions a projected hot spot for their emissions and transport pathways into the stratosphere. Under the leadership of IFM-GEOMAR (Kiel, Germany) a cruise with RV Sonne was conducted from 9 to 25 October 2009 in the tropical western Pacific to investigate trace gas emissions on a 4030 nm (7,500 km) and 60 degrees latitude covering transit between Tomakomai (Japan, 42°35,4‘N/ 141°37,5‘E) and Townsville (Australia, 19°06,6’S/ 146°50,5‘E). The ships cruise crossed various biogeochemical regimes of the northern and southern western Pacific Ocean, which differ in seawater properties, currents, productivity and atmospheric dynamics (e.g. Kuroshio Front, Northern Pacific Gyre, Pacific warm pool and Coral Seas). We will present highlights of the oceanic and atmospheric halocarbon measurements during the ships campaign, halocarbon emissions from the western Pacific Ocean, sources and transport calculations, including contributions to stratospheric bromine.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Since clouds play an essential role in the Earth's climate system, it is important to understand the cloud characteristics as well as their distribution on a global scale using satellite observations. One of the main scientific objectives of SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) on ENVISAT is the retrieval of cloud parameters which are also relevant for the study of tropospheric constituents. On the one hand, SCIAMACHY has to be sensitive to low variations in trace gas concentrations which means the ground pixel size has to be large enough. On the other hand, such a large pixel size leads to the problem that SCIAMACHY spectra are not well suitable to derive a reliable cloud fraction that can be used as input parameter for subsequent retrievals of cloud properties or vertical trace gas columns. Therefore, we use MERIS/ENVISAT spectral measurements with its high spatial resolution as sub-pixel information for the determination of MerIs Cloud fRation fOr Sciamachy (MICROS). Since MERIS covers an even broader swath width than SCIAMACHY, no problems with spatial and temporal matches of measurements occur. This enables the derivation of a SCIAMACHY cloud fraction with an accuracy much higher as compared with other current cloud fractions that are based on SCIAMACHY's PMD (Polarization Measurement Device) data. We present our new developed MICROS algorithm based on the threshold approach as well as a qualitative validation of our results with MERIS satellite imageries for different locations, especially with respect to bright surfaces such as snow/ice and sands. In addition, the SCIAMACHY cloud fractions derived from MICROS are intercompared with other current SCIAMACHY cloud fractions based on different approaches demonstrating a considerable improvement regarding 'true' cloud fraction determination using the MICROS algorithm.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Natural, short-lived halocarbons play a role in the stratospheric ozone budget, besides the anthropogenic emitted, long-lived chlorine- and brominefluorocarbons. The tropical oceans are a known source of reactive iodine and bromine to the atmosphere in the form of iodinated and brominated methanes (VSLS), as e.g.methyl iodide (CH3I), dibromomethane (CH2Br2) and bromoform (CHBr3), which contributes to reactive bromine within the lower stratosphere. Elevated atmospheric concentrations above the oceans are related to oceanic supersaturations of the compounds, caused by photochemical and biological production. The tropical Western Pacific is of special interest since it is a largely uncharacterized region for the oceanic compounds and in certain regions a projected hot spot for their emissions and transport pathways into the stratosphere. From 9 to 25 October 2009 the IFM-GEOMAR (Kiel, Germany) conducted a cruise with RV Sonne in the tropical western Pacific to investigate trace gas emissions on a 4030 nm (7,500 km) and 60 degrees latitude covering transit between Tomakomai (Japan, 42°35,4‘N/ 141°37,5‘E) and Townsville (Australia, 19°06,6'S/ 146°50,5‘E). The ships cruise crossed various biogeochemical regimes of the northern and southern western Pacific Ocean, which differ in seawater properties, currents, productivity and atmospheric dynamics (e.g. Kuroshio Front, Northern Pacific Gyre, Pacific warm pool and Coral Seas). We will present highlights of the oceanic and atmospheric halocarbon measurements during the ships campaign, halocarbon emissions from the western Pacific Ocean, sources and the relationship between VSLS emissions and various phytoplankton functional groups, as being derived from in situ and satellite measurements.
  • [Show abstract] [Hide abstract]
    ABSTRACT: The goal of this study is to improve Phyto-DOAS, the retrieval method of identification of major Phytoplankton Functional Types (PFTs) using ocean-color data provided by a high spectrally-resolved satellite sensor, SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) on board ENVISAT. Phyto-DOAS is an extension of DOAS (Differential Optical Absorption Spectroscopy), originally developed to retrieve atmospheric trace gases, for remote identification of oceanic phytoplankton. So far Phyto-DOAS has been successfully exploited to identify Cyanobacteria and Diatom over global ocean (Bracher et al. 2009). The main challenge for retrieving more PFTs by Phyto-DOAS is to overcome the overlapping effects of different PFTs absorption spectra. Different PFTs are composed of different types and concentrations of pigments, but also have pigments in common, e.g. Chl-a, which cause correlation effects in the standard Phyto-DOAS retrieval. In this study two ideas have been implemented to overcome this limitation of Phyto-DOAS: Firstly, using the method of fourth-derivative spectroscopy (Aguirre-Gomez et al. 1995) the peak positions of the main pigment components in each absorption spectrum have been derived. After comparing the corresponding results of major PFTs, the optimized fit-window for DOAS-retrieval of each PFT is determined. Secondly, the simultaneous fitting of different PFTs has been implemented (over the year 2008) to include the real oceanic situation in the retrieval. Within this step the provided optimized fit-windows have been tested to produce higher fit quality. Validation of the global PFTs biomass distribution has been performed using in-situ data sets obtained during several transatlantic cruises in the year 2008.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A retrieval of particulate matter concentration (PM10) from satellite data is presented as well as improvements of the aerosol optical depth retrieval by the Bremen aerosol algorithm. The add-on retrieval of particulate matter uses the derivation of the effective radii from the Ångstroem exponents and an assumed log-normal size distribution function. The Ångstroem exponent is derived through the multi-channel approach using MERIS/Envisat data, and benefits from the fitting of a smooth spectral slope of aerosol optical depth and the surface reflectance. The advantage of the retrieval is that this retrieval of the aerosol mass, i.e., in particular the effective radius, is exclusively based on spectral information from satellite measurements, global aerosol models, and meteorological parameters. ECMWF Boundary layer height, humidity, temperature, and pressure data are used in the retrieval; a retrieval of PM inferred without meteorological information and a proper BRDF is shown to be not very promising. Over the city of Hamburg, the aerosol optical depths agree within a standard deviation of 0.03 and 0.068 for all thirteen wavelengths between 412 and 885 nm, compared with AERONET and ground based air quality measurements; the particulate matter concentrations show agreement with a correlation factor of 0.64. In addition to the urban site of Hamburg, comparisons of PM10 measurements over rural sites in Germany exhibit a correlation coefficient of 0.75.
    01/2010; DOI:10.5194/amtd-3-5429-2010
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: To date, the software package SCIATRAN [V. V. Rozanov et al., 2002; A. 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]. Figure 1: Scheme of atmospheric and oceanic coupled radiative transfer So far, the coupling for the scalar radiative transfer is included. To analyse the quality of this new scalar coupled ocean-atmosphere radiative transfer version of SCIATRAN, model results of this and of the uncoupled SCIATRAN version are compared to observations, using satellite and in-situ measurements. In particular, we compared MERIS-TOA (top of the atmosphere) reflectances with SCIATRAN calculations. The data were chosen due to varying chlorophyll concentrations at different sites during different seasons. The main input parameters required to model the measured data properly, such as concentrations of water vapour, ozone, chlorophyll, aerosol optical thickness as well as observation and illumination geometry, are taken from the MERIS satellite and AERONET data base measurements and used in the same way for both versions. Each version takes the optical properties of organic and inorganic small (phytoplankton, bacteria, dust etc. < 1µm) and large (phytoplankton, zooplankton, sand etc. >/= 1µm) particles measured by in-situ observations into account. Furthermore, in the coupled version the single scattering albedo and the extinction coefficient can be set. Nevertheless, these two properties of water particles have a non-neglecting impact on the modelled result, but they are not often measured and not available from the MERIS satellite data at all. Therefore, common values based on theory and own tests are used. Figure 2 shows first results of these comparisons for two sites in the Pacific Ocean.