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  • 1
    Keywords: Geography ; Oceanography ; Physical geography ; Atmospheric sciences ; Remote sensing ; Geography ; Oceanography ; Physical geography ; Atmospheric sciences ; Remote sensing ; Fallstudiensammlung ; European Space Agency ; Satellitenfernerkundung ; European Space Agency ; Fernerkundung ; Geowissenschaften ; Umweltveränderung ; Forschungsprojekt ; European Space Agency ; Satellitenfernerkundung
    Description / Table of Contents: 1 CHIMTEA: Chemical Impact of Thunderstorms on Earth's Atmosphere -- 2 TIBAGS: Tropospheric Iodine monoxide and its coupling to Biospheric and Atmospheric variables – a Global Satellite study -- 3 Green SAR - Greenland and Antarctic grounding lines from SAR data.- 4 Sea surface roughness manifestations around ocean fronts -- 5 The impact of near-surface salinity structure on SMOS retrievals -- 6 SMASPARES--SMOS Data Assimilation for Parameter Estimation in Radiative Transfer Models -- 7 PROgRESSIon – Investigating the Prototyping of Operational Estimation of Energy Fluxes and Soil Moisture Content Using a Variant of the “Triangle” Inversion Methodology -- 8 Crustal Modelling and Moho Estimation with GOCE Gravity Data.-.
    Type of Medium: Online Resource
    Pages: Online-Ressource (XIII, 144 p. 60 illus., 7 illus. in color, online resource)
    Edition: 1st ed. 2016
    ISBN: 9783319169521
    Series Statement: Springer Earth System Sciences
    RVK:
    Language: English
    Note: Includes bibliographical references and index , 1 CHIMTEA: Chemical Impact of Thunderstorms on Earth's Atmosphere2 TIBAGS: Tropospheric Iodine monoxide and its coupling to Biospheric and Atmospheric variables - a   Global Satellite study -- 3 Green SAR - Greenland and Antarctic grounding lines from SAR data.-  4 Sea surface roughness manifestations around ocean fronts -- 5 The impact of near-surface salinity structure on SMOS retrievals -- 6 SMASPARES--SMOS Data Assimilation for Parameter Estimation in Radiative  Transfer Models -- 7 PROgRESSIon - Investigating the Prototyping of Operational Estimation of Energy   Fluxes and Soil Moisture Content Using a Variant of the “Triangle” Inversion Methodology -- 8 Crustal Modelling and Moho Estimation with GOCE Gravity Data.-.
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  • 2
    Keywords: Oceanography. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (152 pages)
    Edition: 1st ed.
    ISBN: 9783319169521
    Series Statement: Springer Earth System Sciences Series
    DDC: 550.28
    Language: English
    Note: Intro -- Preface -- The Changing Earth Science Network Projects 2011--2013 -- ESA EO Science Strategy and the Support to Science Element (STSE) -- The Changing Earth Science Network -- Acknowledgments -- Contents -- 1 CHIMTEA---Chemical Impact of Thunderstorms on Earth's Atmosphere -- Abstract -- 1 Introduction -- 1.1 Lightning in the Upper Atmosphere -- 1.2 Chemistry of Thunderstorms and Transient Luminous Events -- 2 Instruments and Data -- 3 TLE-Producing Thunderstorms -- 4 Measuring TLE- and Lightning-NOx from Space -- 4.1 Thunderstorm Signatures in MIPAS2D NO2 -- 5 Climate-Chemistry Sensitivity to TLE-NOx -- 6 Conclusions and Future Lines -- Acknowledgements -- References -- 2 TIBAGS: Tropospheric Iodine Monoxide and Its Coupling to Biospheric and Atmospheric Variables---a Global Satellite Study -- Abstract -- 1 Background Information -- 2 The Satellite Sensor -- 3 Data Analysis -- 4 Considerations on the Air Mass Factor -- 5 Detection Limit and Averaging -- 6 Observations Above Antarctica -- 6.1 Spatial and Temporal Variations of IO Vertical Columns -- 6.2 Comparison of IO and BrO Distributions -- 6.3 Relation of the Halogen Oxides to Sea Ice Cover -- 7 Relations Between IO and Biospheric Parameters -- 7.1 Comparison Between IO and Chlorophyll-a Above Antarctica -- 7.2 Comparison Between IO and Chlorophyll-a Above Ocean Areas -- 7.3 Comparison Between IO, Chlorophyll-a and Diatoms for Southeast Asia -- 8 Summary -- Acknowledgments -- References -- 3 GreenSAR---Greenland and Antarctic Grounding Lines from SAR Data -- Abstract -- 1 Introduction -- 2 Retreat of the Grounding Line of the Pine Island Glacier, West Antarctic Ice Sheet -- 2.1 Introduction -- 2.2 Methods -- 2.3 Results -- 2.4 Discussion -- 3 Grounding Line Retreat of Petermann Gletscher, Greenland Ice Sheet -- 4 Conclusions -- Acknowledgments -- References. , 4 Sea Surface Roughness Manifestations Around Ocean Fronts -- Abstract -- 1 Introduction -- 2 Wave--Current Interactions and Surface Roughness -- 2.1 Surface Waves in Currents -- 2.2 Relaxation Time -- 2.3 Changes of Mean Square Slope -- 3 Current Refraction -- 3.1 Canonical Current Gradients -- 3.2 Centered Current Gradients -- 4 First Approximation: Without Propagation -- 4.1 Wind Wave Spectral Symmetry -- 4.2 Divergence, Strain, and Polarization Index -- 5 One-Dimensional Cases -- 5.1 Case 1: Acrossfront Current `divergence' -- 5.2 Case 2: Alongfront Current `shear' -- 5.2.1 Without Propagation -- 5.2.2 With Propagation -- 6 Generation of Short Waves by Wave Breaking -- 7 Observations -- 8 Discussion -- 8.1 Waves with Dominant Action Contrast -- 8.1.1 Response to Oscillatory Currents -- 8.1.2 Response to Isolated Current Front -- 8.2 Waves with Dominant mss Contrast -- 8.3 Relaxation and Current Gradient Length Scale -- 8.4 Numerical Illustration -- 9 Conclusion -- Acknowledgments -- References -- 5 The Impact of Near-Surface Salinity Structure on SMOS Retrievals -- Abstract -- 1 Introduction -- 2 A Review of Upper Ocean Mixing Processes -- 2.1 Surface Waves -- 2.2 Internal Waves -- 2.3 Convective Mixing -- 3 Methodology -- 3.1 ASIP -- 3.2 SPURS Cruises -- 3.3 SMOS Data -- 4 Results and Discussion -- 4.1 ASIP Dataset from the Strasse Cruise -- 4.2 Comparison Between ASIP and SMOS Data -- 5 Summary and Future Work -- Acknowledgements -- References -- 6 SMASPARES--SMOS Data Assimilation for Parameter Estimation in Radiative Transfer Models -- Abstract -- 1 Introduction -- 2 The Rur and Erft Catchments -- 3 SMOS L2 Accuracy in the Rur and Erft Catchments -- 4 Radiative Transfer Parameter Estimation in a 1D System -- 4.1 Experimental Design -- 4.2 Results of the 1D Experiment -- 5 Radiative Transfer Parameter Estimation in a 2D System. , 5.1 Model Set up and Numerical Experiment -- 5.2 Results of the 2D Experiment -- 6 Conclusion and Outlook -- Acknowledgments -- References -- 7 PROgRESSIon---Investigating the Prototyping of Operational Estimation of Energy Fluxes and Soil Moisture Content Using a Variant of the ``Triangle'' Inversion Methodology -- Abstract -- 1 Introduction -- 2 Datasets and Study Sites -- 2.1 AATSR Satellite Data -- 2.2 Land Surface Process Model -- 2.3 Ancillary In-Situ Data -- 3 ``Triangle'' Implementation Using AATSR Products -- 4 Validation Approach -- 5 Results and Discussion -- 6 Conclusions -- Acknowledgments -- References -- 8 Crustal Modelling and Moho Estimation with GOCE Gravity Data -- Abstract -- 1 Introduction -- 2 Inverse Gravimetric Problem -- 3 Local Solution -- 3.1 Local Inversion Algorithm -- 3.2 Numerical Results -- 4 Global Solution -- 4.1 Global Inversion Algorithm -- 4.2 Numerical Results -- 5 Conclusions -- References.
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  • 3
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    In:  Supplement to: Land, Peter Edward; Findlay, Helen S; Shutler, Jamie D; Ashton, Ian G C; Holding, Thomas; Grouazel, Antoine; Girard-Ardhuin, Fanny; Reul, Nicolas; Piolle, Jean-Francois; Chapron, Bertrand; Quilfen, Yves; Bellerby, Richard G J; Bhadury, Punyasloke; Salisbury, Joseph; Vandemark, Doug; Sabia, Roberto (2019): Optimum satellite remote sensing of the marine carbonate system using empirical algorithms in the global ocean, the Greater Caribbean, the Amazon Plume and the Bay of Bengal. Remote Sensing of Environment, 235, 111469, https://doi.org/10.1016/j.rse.2019.111469
    Publication Date: 2023-09-16
    Description: Published empirical algorithms for oceanic total alkalinity (TA) and dissolved inorganic carbon (DIC) are used with monthly sea surface salinity (SSS) and temperature (SST) derived from satellite (SMOS, Aquarius, SST CCI) and interpolated in situ (CORA) measurements and climatological (WOA) ancillary data to produce monthly maps of TA and DIC at one degree spatial resolution. Earth system model TA and DIC (HADGEM2-ES) are also included. Results are compared with in situ (GLODAPv2) TA and DIC and results analysed in five regions (global, Greater Caribbean, Amazon plume, Amazon plume with in situ SSS 〈 35 and Bay of Bengal). Results are presented in three versions, denoted by 'X' in the lists below: using all available data (X = ''); excluding data with bathymetry 〈 500m (X = 'Depth500'); excluding data with both bathymetry 〈 500m and distance from nearest coast 〈 300 km (X = 'Depth500Dist300'). Datasets S1 to S5 are .csv lists of matchups in each region - date and location, in situ TA and DIC measurements and estimated uncertainties, all input datasets, estimates of TA and DIC from all outputs, and the best available output estimates of TA and DIC for each matchup. S1_GlobalAlgorithmMatchupsX.csv S2_GreaterCaribbeanAlgorithmMatchupsX.csv S3_AmazonPlumeAlgorithmMatchupsX.csv S4_AmazonPlumeLowSAlgorithmMatchupsX.csv S5_BayOfBengalAlgorithmMatchupsX.csv Datasets S6 to S10 are .csv statistical analyses of the performance of each combination of algorithm and input data - carbonate system variable, algorithm, input datasets used, (MAD, RMSD using all available data, output score, RMSD estimated from output score, output and in situ mean and standard deviation, correlation coefficient), all items in brackets presented both unweighted and weighted, number of matchups, number of potential matchups, matchup coverage, RMSD after subtraction of linear regression, percentage reduction in RMSD due to subtraction of linear regression and weighted score divided by number of matchups). S6_GlobalAlgorithmScoresX.csv S7_GreaterCaribbeanAlgorithmScoresX.csv S8_AmazonPlumeAlgorithmScoresX.csv S9_AmazonPlumeLowSAlgorithmScoresX.csv S10_BayOfBengalAlgorithmScoresX.csv Datasets S11 to S15 are zipped netCDF files containing error analyses of all outputs in each region, including the squared error of each output at each matchup, the weight of each squared error (1/squared uncertainty), weight * squared error, number of matchups available to each output, number of matchups available to each combination of two outputs, (score of each output in a given comparison of two outputs, overall output score and RMSD estimated from output score), all items in the last brackets presented both unweighted and weighted. S11_GlobalSquaredErrorsX.nc S12_GreaterCaribbeanSquaredErrorsX.nc S13_AmazonPlumeSquaredErrorsX.nc S14_AmazonPlumeLowSSquaredErrorsX.nc S15_BayOfBengalSquaredErrorsX.nc Datasets S16 to S20 are zipped netCDF files containing global maps of the mean and standard deviation of each of: in situ data; output data; output data - in situ data and number of matchups. Regional files show the same maps, but only including data within the region. S16_GlobalmapsX.nc S17_GreaterCaribbeanmapsX.nc S18_AmazonPlumemapsX.nc S19_AmazonPlumeLowSmapsX.nc S20_BayOfBengalmapsX.nc Datasets S21 and S22 are .csv files containing the effect on estimated RMSD of excluding various combinations of algorithms and/or inputs for TA and DIC in each region. For a given variable and region, the first line shows the algorithm, input data sources, estimated RMSD and bias of the output with lowest estimated RMSD. Subsequent lines show the effect of excluding combinations of algorithms and/or inputs, ordered first by the number of algorithms/inputs excluded (fewest first), then by effect on lowest estimated RMSD. So the first line(s) consist of the effects of excluding the best algorithm and each of the input sources to that algorithm, most important first. Each line consists of the item excluded, ratio of resulting estimated RMSD to original estimated RMSD, resulting bias and number of items excluded. Some exclusions are equivalent, for instance exclusion of WOA nitrate (the only nitrate source) is equivalent to excluding all algorithms using nitrate. Dataset S21 contains a comprehensive list of all possible exclusions, and so is rather hard to read and interpret. To mitigate this, Dataset S22 contains only those exclusion sets with effect greater than 1% and at least 0.1% greater than any subset of its exclusions. S21_importancesX.csv S22_importances2X.csv Dataset S23 is a .csv file containing like-for-like comparisons of RMSD between TA and DIC in each region. Bear in mind that the RMSD shown here is not the same as the estimated RMSD (RMSDe) shown elsewhere. S23_TA_DICcomparisonX.csv
    Keywords: Aquarius; Carbonate chemistry; CORA; Dissolved inorganic carbon; Earth observation; File content; File format; File name; File size; HadGEM2-ES; Ocean acidification; SMOS; Total alkalinity; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 345 data points
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