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  • 1
    Call number: AWI A13-00-0258 ; PIK N 453-01-0477
    In: International geophysics series, 66
    Type of Medium: Monograph available for loan
    Pages: XXXVI, 940 Seiten , Illustrationen, Diagramme, Karten , 24 cm
    ISBN: 0124340687
    Series Statement: International geophysics series 66
    Language: English
    Note: Contents List of Acronyms List of Symbols Foreword Preface Prologue Chapter 1 Introduction to Ocean Dynamics 1.1 Types, Advantages, and Limitations of Ocean Models 1.2 Recent Examples 1.3 Governing Equations 1.4 Vorticity Conservation 1.5 Nondimensional Numbers and Scales of Motion 1.6 Geostrophic Flow and Thermal Wind 1.7 Inertial Motions 1.8 Ekman Layers 1.9 Sverdrup Transport 1.10 Western Boundary Intensification (Stommel Solution) 1.11 Gyre Scale Circulation (Munk Solution) 1.12 Barotropic Currents over Topography 1.13 Baroclinic Transport over Topography 1.14 Coastal Upwelling and Fronts 1.15 Mesoscale Eddies and Variability 1.16 Thermohaline Circulation and Box (Reservoir) Models 1.17 Numerical Models Chapter 2 Introduction to Numerical Solutions 2.1 Introduction 2.1.1 Architecture 2.1.2 Computational Errors 2.2 Ordinary Differential Equations 2.2.1 Runge-Kutta Method 2.3 Partial.Differential Equations 2.3.1 Consistency, Convergence, and Stability 2.3.2 Elliptic, Hyperbolic, and Parabolic Systems 2.4 Elliptic Equations and Steady-State Problems 2.4.1 Direct Solvers 2.4.2 Iterative Solvers and Relaxation Methods 2.4.3 Preconditioned Conjugate Gradient Method 2.4.4 Multigrid Methods 2.4.5 Pseudo-transient Method 2.5 Time Dependent Problems 2.5.1 Advection Equation and Hyperbolic Systems 2.5.2 Diffusion Equation and Parabolic Systems 2.6 Finite-Difference (Grid Point) Methods 2.6.1 Staggered Grids 2.6.2 Time Differencing and Filtering 2.6.3 Computational Grids 2.7 Spectral (Spectral Transform) Methods 2.8 Finite-Element Methods 2.8.1 Spectral Element Approach 2.9 Parameterization of Subgrid Scale Processes 2.10 Lateral Open Boundary Conditions 2.11 Computational Issues 2.12 Examples 2.12.1 Inertial Oscillations 2.12.2 Thermohaline Circulation 2.12.3 Normal Modes 2.12.4 Gyre Scale Circulation 2.12.5 Advection Problems 2.12.6 M.I.T. Nonhydrostatic Global Model Chapter 3 Equatorial Dynamics and Reduced Gravity Models Solutions 3.1 Oceanic Dynamical Response to Forcing 3.2 Governing Equations 3.3 Equatorial Waves 3.3.1 Kelvin Waves 3.3.2 Yanai Waves 3.3.3 Rossby Waves 3.3.4 Inertia-Gravity (Poincare) Waves 3.4 Equatorial Currents 3.5 Reduced Gravity Model of Equatorial Processes Chapter 4 Midlatitude Dynamics and Quasi-Geostrophic Models 4.1 Linear Motions 4.1.1 Inertia-Gravity (Sverdrup/Poincare) Waves 4.1.2 Kelvin Waves 298 4.1.3 Planetary Ross by Waves 4.1.4 Topographic Rossby Waves 4.2 Continuous Stratification 4.3 Geostrophic Adjustment and Instabilities 4.3.1 Geostrophic Adjustment 4.3.2 Instabilities 4.4 Spinup 4.5 Quasi-Geostrophic Models 4.5.1 Governing Equations 4.5.2 Applications Chapter 5 High-Latitude Dynamics and Sea-Ice Models 5.1 Salient Features of Ice Cover 5.2 Momentum Equations for Sea Ice 5.3 Constitutive Law for Sea Ice (Ice Rheology) 5.3.1 Viscous-Plastic Ice Rheology 5.3.2 Elastic-Viscous-Plastic Ice Rheology 5.4 Continuity Equations for Sea Ice 5.5 Response of Sea Ice to Storm Passage 5.6 Numerics 5.6.1 Governing Equations in Orthogonal Curvilinear Coordinates 5.6.2 Solution Technique Chapter 6 Tides and Tidal Modeling 6.1 Description of Tides 6.2 Formulation: Tidal Potential 6.3 Body, Load, Atmospheric, and Radiational Tides 6.3.1 Body (Solid Earth) Tides 6.3.2 Load Tides 6.3.3 Atmospheric Tides 6.3.4 Radiational Tides 6.4 Dynamical Theory of Tides: Laplace Tidal Equations 6.5 Equilibrium Theory of Tides 6.6 Tidal Analysis: Orthotides 6.7 Tidal Currents 6.8 Global Tidal Models 6.9 Regional Tidal Models 6.10 Geophysical Implications 6.10.1 Tidal Dissipation and LOD 6.10.2 Tidal Energetics 6.11 Changes in Earth's Rotation 6.12 Baroclinic (Internal) Tides 6.13 Long-Period Tides 6.14 Shallow Water Tides and Residual Currents 6.15 Summary Chapter 7 Coastal Dynamics and Barotropic Models 7.1 Wind- and Buoyancy-Driven Currents 7.2 Tidal Motions 7.3 Continental Shelf Waves 7.4 Modeling Shelf Circulation 7.5 Barotropic Models 7.5.1 Coastal Ocean Response to Wind Forcing 7.5.2 Storm Surges and Storm Surge Modeling 7.5.3 Response to Pressure Forcing Chapter 8 Data and Data Processing 8.1 In Situ Observational Data 8.1.1 XBT, CTD, CM, ADCP, and Drifter Data 8.1.2 Historical Hydrographic Data 8.1.3 Historical Marine Surface Data 8.2 Remotely Sensed Data 8.2.1 Sea Surface Temperature from IR Sensors 8.2.2 Sea Surface Winds from Microwave Sensors 8.2.3 Chlorophyll and Optical Clarity from Color Sensors 8.2.4 Sea Surface Height from Satellite Altimetry 8.3 NWP Products 8.4 Preprocessing of Observational Data and Postprocessing of Model Output 8.4.1 Graphics and Visualization of Model Output 8.4.2 Analyses Chapter 9 Sigma-Coordinate Regional and Coastal Models 9.1 Introduction 9.2 Governing Equations 9.3 Vertical Mixing 9.4 Boundary Conditions 9.5 Mode Splitting 9.6 Numerics 9.6.1 Vertical Direction 9.6.2 Horizontal Direction 9.7 Numerical Problems 9.8 Applications 9.9 Code Structure Chapter 10 Multilevel Basin Scale and Global Models 10.1 Introduction 10.2 Governing Equations 10.3 Isopycnal Diffusion 10.4 Architecture and Other Model Features 10.5 Applications 10.6 Hybrid s-Coordinate Models 10.7 Regional z-Level Models Chapter 11 Layered and Isopycnal Models 11.1 Layered Models 11.2 Isopycnal Models Chapter 12 Ice-Ocean Coupled Models 12.1 Sea-Ice Models 12.2 Coupled Ice-Ocean Models Chapter 13 Ocean-Atmosphere Coupled Models 13.1 Coupling between the Ocean and the Atmosphere 13.2 Coupled Ocean-Atmosphere General Circulation Models 13.3 Regional Coupled Ocean-Atmosphere Models Chapter 14 Data Assimilation and Nowcasts/ Forecasts 14.1 Introduction 14.2 Direct Insertion 14.3 Nudging 14.4 Statistical Assimilation Schemes 14.4.1 Kalman Filter 14.4.2 Reduced State Space Kalman Filters 14.4.3 Optimal Interpolation (OI) Scheme 14.5 Variational Methods 14.5.1 Adjoint Models 14.6 Predictability of Nonlinear Systems-Low Order Paradigms 14.7 Nowcasts/Forecasts in the Gulf of Mexico Appendix A Equations of State A.1 Equation of State for the Ocean A.2 Equation of State for the Atmosphere Appendix B Wavelet Transforms B.1 Introduction B.1.1 Theory B.1.2 Continuous Wavelet Transforms (CWT) B.1.3 Discrete Wavelet Transforms (DWT) B.2 Examples B.3 Wavelet Transforms and Stochastic Processes B.4 Two-Dimensional Wavelet Transforms B.5 Cross Wavelet Transforms (CrWT) B.6 Error Analysis Appendix C Empirical Orthogonal Functions and Empirical Normal Modes C.1 Empirical Orthogonal Functions C.1.1 Complex EOFs C.1.2 Singular Spectrum Analysis C.1.3 Extended EOFs C.1.4 Coupled Pattern Analysis C.2 Empirical Normal Modes Appendix D Units and Constants D.1 Useful Quantities D.1.1 SI (International System of Units) Units and Conventions D.1.2 Useful Conversion Factors D.1.3 Useful Universal Constants D.1.4 Useful Geodetic Constants D.1.5 Useful Physical Constants D.1.6 Useful Dynamical Quantities D.2 Important Scales and Quantities D.2.1 Length Scales D.2.2 Timescales D.2.3 Velocity Scales D.2.4 Nondimensional Quantities D.3 Useful Websites References Biographies Index
    Location: AWI Reading room
    Location: A 18 - must be ordered
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    Branch Library: PIK Library
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  • 2
    Monograph available for loan
    Monograph available for loan
    San Diego [u.a.] : Acad. Press
    Associated volumes
    Call number: AWI A6-00-0268
    In: International geophysics series
    Type of Medium: Monograph available for loan
    Pages: XXVIII, 888 S.
    ISBN: 0124340709
    Series Statement: International geophysics series 67
    Branch Library: AWI Library
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  • 3
    Publication Date: 2009-08-13
    Print ISSN: 0177-7971
    Electronic ISSN: 1436-5065
    Topics: Geography , Physics
    Published by Springer
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  • 4
    Publication Date: 2020-06-03
    Description: Recent results using wind and sea surface temperature data from satellites and high-resolution coupled models suggest that mesoscale ocean–atmosphere interactions affect the locations and evolution of storms and seasonal precipitation over continental regions such as the western US and Europe. The processes responsible for this coupling are difficult to verify due to the paucity of accurate air–sea turbulent heat and moisture flux data. These fluxes are currently derived by combining satellite measurements that are not coincident and have differing and relatively low spatial resolutions, introducing sampling errors that are largest in regions with high spatial and temporal variability. Observational errors related to sensor design also contribute to increased uncertainty. Leveraging recent advances in sensor technology, we here describe a satellite mission concept, FluxSat, that aims to simultaneously measure all variables necessary for accurate estimation of ocean–atmosphere turbulent heat and moisture fluxes and capture the effect of oceanic mesoscale forcing. Sensor design is expected to reduce observational errors of the latent and sensible heat fluxes by almost 50%. FluxSat will improve the accuracy of the fluxes at spatial scales critical to understanding the coupled ocean–atmosphere boundary layer system, providing measurements needed to improve weather forecasts and climate model simulations.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
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  • 5
    Publication Date: 2020-08-31
    Description: Four state-of-the-art satellite-based estimates of ocean surface latent heat fluxes (LHFs) extending over three decades are analyzed, focusing on the interannual variability and trends of near-global averages and regional patterns. Detailed intercomparisons are made with other datasets including 1) reduced observation reanalyses (RedObs) whose exclusion of satellite data renders them an important independent diagnostic tool; 2) a moisture budget residual LHF estimate using reanalysis moisture transport, atmospheric storage, and satellite precipitation; 3) the ECMWF Reanalysis 5 (ERA5); 4) Remote Sensing Systems (RSS) single-sensor passive microwave and scatterometer wind speed retrievals; and 5) several sea surface temperature (SST) datasets. Large disparities remain in near-global satellite LHF trends and their regional expression over the 1990–2010 period, during which time the interdecadal Pacific oscillation changed sign. The budget residual diagnostics support the smaller RedObs LHF trends. The satellites, ERA5, and RedObs are reasonably consistent in identifying contributions by the 10-m wind speed variations to the LHF trend patterns. However, contributions by the near-surface vertical humidity gradient from satellites and ERA5 trend upward in time with respect to the RedObs ensemble and show less agreement in trend patterns. Problems with wind speed retrievals from Special Sensor Microwave Imager/Sounder satellite sensors, excessive upward trends in trends in Optimal Interpolation Sea Surface Temperature (OISST AVHRR-Only) data used in most satellite LHF estimates, and uncertainties associated with poor satellite coverage before the mid-1990s are noted. Possibly erroneous trends are also identified in ERA5 LHF associated with the onset of scatterometer wind data assimilation in the early 1990s.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 6
    Publication Date: 2015-03-01
    Print ISSN: 0034-4257
    Electronic ISSN: 1879-0704
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by Elsevier
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  • 7
    Publication Date: 2007-01-15
    Description: A dataset consisting of daily diurnal warming values from 1996 through 2000 covering the global Tropics (30°N through 30°S) at 0.25° × 0.25° resolution has been created using a parameterization for the diurnal warming developed previously. The inputs to the parameterization are the peak shortwave solar radiation [determined from International Satellite Cloud Climatology Project (ISCCP) data] and daily averaged wind speed [determined from Special Sensor Microwave Imager (SSM/I) data]. Comparisons with Tropical Ocean Global Atmosphere (TOGA) Tropical Atmosphere Ocean (TAO) and Pilot Research Moored Array in the Tropical Atlantic (PIRATA) buoys show that the biases are small (mean bias is 0.0012°C; the standard deviation and correlation are 0.26°C and 0.74) and show no discernable geographic bias. The 5-yr average shows that throughout most regions the values are small, with higher values (approaching 1°C) in the northern Indian Ocean, the western equatorial Pacific, the equatorial eastern Pacific, and several coastal regions. An EOF analysis of the variability indicates that seasonal variability is the most dominant form for each of the basins; in the Atlantic and Pacific basins it is north–south following the solar cycle. In the Indian Ocean the seasonal cycle is dominated by monsoonal variability; both the northern and southern portions of the basin have above-mean or below-mean values at the same times. Seasonal shortwave variability is responsible for the second mode in the Indian Ocean. East–west dipole weight structures appear in the spatial patterns for mode 2 in the Pacific and mode 3 for the Atlantic and Indian Oceans. These modes also display seasonally varying characteristics, with late 1997 and early 1998 being somewhat anomalous in the Pacific and Indian Oceans.
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    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 8
    Publication Date: 2013-04-15
    Description: Diurnal sea surface warming affects the fluxes of latent heat, sensible heat, and upwelling longwave radiation. Diurnal warming most typically reaches maximum values of 3°C, although very localized events may reach 7°–8°C. An analysis of multiple years of diurnal warming over the global ice-free oceans indicates that heat fluxes determined by using the predawn sea surface temperature can differ by more than 100% in localized regions over those in which the sea surface temperature is allowed to fluctuate on a diurnal basis. A comparison of flux climatologies produced by these two analyses demonstrates that significant portions of the tropical oceans experience differences on a yearly average of up to 10 W m−2. Regions with the highest climatological differences include the Arabian Sea and the Bay of Bengal, as well as the equatorial western and eastern Pacific Ocean, the Gulf of Mexico, and the western coasts of Central America and North Africa. Globally the difference is on average 4.45 W m−2. The difference in the evaporation rate globally is on the order of 4% of the total ocean–atmosphere evaporation. Although the instantaneous, year-to-year, and seasonal fluctuations in various locations can be substantial, the global average differs by less than 0.1 W m−2 throughout the entire 10-yr time period. A global heat budget that uses atmospheric datasets containing diurnal variability but a sea surface temperature that has removed this signal may be underestimating the flux to the atmosphere by a fairly constant value.
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    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 9
    Publication Date: 2002-07-01
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 10
    Publication Date: 2006-12-01
    Description: Improved seasonal prediction of sea surface temperature (SST) anomalies over the global oceans is the theme of this paper. Using 13 state-of-the-art coupled global atmosphere–ocean models and 13 yr of seasonal forecasts, the performance of individual models, the ensemble mean, the bias-removed ensemble mean, and the Florida State University (FSU) superensemble are compared. A total of 23 400 seasonal forecasts based on 1-month lead times were available for this study. Evaluation metrics include both deterministic and probabilistic skill measures, such as verification of anomalies based on model and observed climatology, time series of specific climate indices, standard deterministic ensemble mean scores including anomaly correlations, root-mean-square (RMS) errors, and probabilistic skill measures such as equitable threat scores for seasonal SST forecasts. This study also illustrates the Niño-3.4 SST forecast skill for the equatorial Pacific Ocean and for the dipole index for the Indian Ocean. The relative skills of total SST fields and of the SST anomalies from the 13 coupled atmosphere–ocean models are presented. Comparisons of superensemble-based seasonal forecasts with recent studies on SST anomaly forecasts are also shown. Overall it is found that the multimodel superensemble forecasts are characterized by considerable RMS error reductions and increased accuracy in the spatial distribution of SST. Superensemble SST skill also persists for El Niño and La Niña forecasts since the large comparative skill of the superensemble is retained across such years. Real-time forecasts of seasonal sea surface temperature anomalies appear to be possible.
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    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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