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  • 1
    Call number: AWI A3-20-93592
    Type of Medium: Monograph available for loan
    Pages: xxxiii, 613 Seiten , Illustrationen , 42 mm x 170 mm
    Edition: Second edition
    ISBN: 978-3-642-13918-0
    Series Statement: Springer praxis books environmental sciences
    Language: English
    Note: Contents Preface Preface to the First Edition List of figures Abbreviations 1 Historical perspective (Roland A. Madden and Paul R. Julian) 1.1 Introduction 1.2 The intraseasonal, tropospheric oscillation 1.3 The elementary 4-D structure 1.4 Other early studies of the oscillation 1.5 The oscillation in 1979 1.6 Complexity of cloud movement and structure 1.7 Seasonal variations in the oscillation 1.8 The oscillation in the zonal average 1.9 Other effects of the oscillation 1.10 Summary 1.11 References 2 South Asian monsoon (B. N. Goswami) 2.1 Introduction 2.1.1 South Asian summer monsoon and active/break cycles 2.1.2 Amplitude and temporal and spatial scales 2.1.3 Regional propagation characteristics 2.1.4 Relationship between poleward-propagating ISOs and monsoon onset 2.1.5 Relationship with the MJO 2.2 Mechanism for temporal-scale selection and propagation 2.2.1 30 to 60-day mode 2.2.2 10 to 20-day mode 2.3 Air-sea interactions 2.4 Clustering of synoptic events by ISOs 2.5 Monsoon ISOs and predictability of the seasonal mean 2.6 Aerosols and monsoon ISOs 2.7 Predictability and prediction of monsoon ISOs 2.8 Summary and discussion 2.9 Acknowledgments 2.10 Appendix 2.11 References 3 Intraseasonal variability of the atmosphere-ocean-climate system: East Asian monsoon (Huang-Hsiung Hsu) 3.1 Introduction 3.2 General characteristics of EA/WNP monsoon flow 3.3 Periodicity, seasonality, and regionality 3.4 Intraseasonal oscillation propagation tendency 3.5 Relationship with monsoon onsets and breaks 3.6 The 10 to 30-day and 30 to 60-day boreal summer ISO 3.6.1 The 30 to 60-day northward/northwestward-propagating pattern 3.6.2 The 10 to 30-day westward-propagating pattern 3.7 Relationship with tropical cyclone activity 3.8 Upscale effect of TC and synoptic systems 3.9 Final remarks 3.9.1 Close association with the EA/WNP monsoon 3.9.2 The CISO vs. interannual variability 3.9.3 Multiperiodicities and multiscale interaction 3.9.4 Others 3.10 References 4 Pan America (Kingtse C. Mo, Charles Jones, and Julia Nogues Paegle) 4.1 Introduction 4.2 Variations in the IS band 4.3 IS variability in December-March 4.3.1 EOF modes 4.3.2 The Madden Julian Oscillation 4.3.3 The submonthly oscillation 4.4 IS variability in June-September 4.4.1 EOF modes 4.4.2 Madden-Julian Oscillation 4.4.3 Submonthly oscillation 4.5 Intraseasonal modulation of hurricanes 4.6 Summary 4.7 References 5 Australasian monsoon (M. C. Wheeler and J. L. McBride) 5.1 Introduction 5.2 Seasonal cycle of background flow 5.3 Broadband intraseasonal behavior: Bursts and breaks 5.4 Broadband intraseasonal behavior: Spectral analysis 5.5 Meteorology of the bursts and breaks 5.6 Characteristics and influence of the MJO 5.7 1983/1984 and 1987/1988 case studies 5.8 MJO influence on monsoon onset 5.9 Other modes and sources of ISV 5.10 Modulation of tropical cyclones 5.11 Extratropical-tropical interaction 5.12 Prediction 5.13 Conclusions 5.14 References 6 The oceans (William S. Kessler) 6.1 Introduction 6.2 Heat fluxes 6.2.1 Salinity and the barrier layer 6.2.2 A 1-D heat balance? 6.2.3 The role of advection 6.3 Vertical structure under westerly winds 6.4 Remote signatures of wind-forced Kelvin waves 6.5 El Nino and rectification of ISV 6.6 ISV in the Indian Ocean 6.6.1 Differences between the Indian and Pacific Ocean warm pools and their consequences 6.6.2 Oscillations lasting about 60 days in the western equatorial Indian Ocean 6.6.3 Recent models of wind-forced ISV in the Indian Ocean 6.7 Other intrinsic oceanic ISV 6.7.1 Global ISV 6.7.2 Non-TISO-forced ISV in the tropical Indo-Pacific 6.7.3 ISV outside the equatorial Indo-Pacific 6.8 Conclusion 6.9 References 7 Air-sea interaction (Harry Hendori) 7.1 Introduction 7.2 Air-sea fluxes for the eastward MJO 7.3 Air-sea fluxes associated with northward propagation in the Indian summer monsoon 7.4 SST variability 7.5 Mechanisms of SST variability 7.6 SST-atmosphere feedback 7.7 Impact of slow SST variations on MJO activity 7.8 Concluding remarks 7.9 Acknowledgments 7.10 References 8 Mass, momentum, and geodynamics (Benjamin F. Chao and David A. Salstein) 8.1 Introduction 8.2 Angular momentum variations and Earth rotation 8.2.1 Length-of-day variation and axial angular momentum 8.2.2 Polar motion excitation and equatorial angular momentum 8.2.3 Angular momentum and torques 8.3 Time-variable gravity 8.4 Geocenter motion 8.5 Conclusions 8.6 Acknowledgments 8.7 References 9 El Nino Southern Oscillation connection (William K. M. Lau) 9.1 Introduction 9.2 A historical perspective 9.3 Phase 1: The embryonic stage 9.3.1 OLR time-longitude sections 9.3.2 Seasonality 9.3.3 Supercloud clusters 9.3.4 Early modeling framework 9.4 Phase 2: The exploratory stage 9.4.1 MJO and ENSO interactions 9.4.2 WWEs 9.5 Phase 3: ENSO case studies 9.5.1 El Nino of 1997/1998 9.5.2 Stochastic forcings 9.6 Phase-4: Recent development 9.6.1 A new ISO index 9.6.2 Composite events 9.6.3 The ISV-ENSO biennial rhythm 9.7 TISV and predictability 9.8 Acknowledgments 9.9 References 10 Theories (Bin Wang) 10.1 Introduction 10.2 Review of ISO theories 10.2.1 Wave CISK 10.2.2 Wind-evaporation feedback or WISHE 10.2.3 Frictional convergence instability (FCI) 10.2.4 Cloud-radiation feedback 10.2.5 Convection-water vapor feedback and the moisture mode 10.2.6 Multiscale interaction theory 10.2.7 Mechanisms of the boreal summer intraseasonal oscillation 10.2.8 Atmosphere-ocean interaction 10.3 A general theoretical framework 10.3.1 Fundamental physical processes 10.3.2 Governing equations 10.3.3 Boundary layer dynamics near the equator 10.3.4 The 1.5-layer model for the MJO 10.3.5 The 2.5-layer model including the effects of basic flows 10.4 Dynamics of the MJO 10.4.1 Low-frequency equatorial waves and the associated Ekman pumping 10.4.2 Frictional convergence instability (FCI) 10.4.3 FCI mode under nonlinear heating 10.4.4 The role of multiscale interaction (MSI) in MJO dynamics 10.5 Dynamics of boreal summer ISO 10.5.1 Effects of mean flows on the ISO 10.5.2 Mechanism of northward propagation 10.6 Role played by atmospheric-ocean interaction 10.7 Summary and discussion 10.7.1 Understanding gained from the FCI theory 10.7.2 Model limitations 10.7.3 Outstanding issues 10.8 Acknowledgments 10.9 References 11 Modeling intraseasonal variability (K. R. Sperber, J. M. Slingo, and P. M. Inness) 11.1 Introduction 11.2 Modeling the MJO in boreal winter 11.2.1 Interannual and decadal variability of the MJO 11.2.2 Sensitivity to formulation of the atmospheric model 11.2.3 Modeling the MJO as a coupled ocean-atmosphere phenomenon 11.3 Boreal summer intraseasonal variability 11.3.1 GCM simulations 11.3.2 Air-sea interaction and boreal summer intraseasonal variability 11.3.3 Modeling studies of the links between boreal summer intraseasonal and interannual variability 11.4 The impact of vertical resolution in the upper ocean 11.5 Concluding remarks 11.6 Acknowledgments 11.7 References 12 Predictability and forecasting (Duane Waliser) 12.1 Introduction 12.2 Empirical models 12.3 Dynamical forecast models 12.4 Predictability 12.5 Real time forecasts 12.6 Discussion 12.7 Appendix 12.8 Acknowledgments 12.9 References 13 Africa and West Asia (Mathew Barlow) 13.1 Overview 13.2 Summary of Africa research 13.2.1 West Africa 13.2.2 Eastern Africa 13.2.3 Southern Africa 13.3 Summary of West Asia research 13.4 Station data analysis 13.4.1 Methodology and data 13.4.2 Nairobi 13.4.3 Riyadh 13.5 Relevance of Gill-Matsuno dynamics and the role of mean wind 13.6 Summary and discussion 13.7 References 14 Tropical-extratropical interactions (Paul E. Roundy) 14.1 Introduction 14.2 A boreal winter composite of the global flow associated with the MJO 14.3 Response of the global atmosphere to heating in tropical convection 14.4 Influence of extratropical waves on tropical convection 14.5 Two-way interactions between the tropics and extratropics 14.6 MJO inf
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  • 2
    Publication Date: 2020-07-07
    Description: The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs (1) targets observed variables that can be compared to CMIP model variables; (2) utilizes dataset formatting specifications and metadata requirements closely aligned with CMIP model output; (3) provides brief technical documentation for each dataset, designed for nonexperts and tailored towards relevance for model evaluation, including information on uncertainty, dataset merits, and limitations; and (4) disseminates the data through the Earth System Grid Federation (ESGF) platforms, making the observations searchable and accessible via the same portals as the model output. Taken together, these characteristics of the organization and structure of obs4MIPs should entice a more diverse community of researchers to engage in the comparison of model output with observations and to contribute to a more comprehensive evaluation of the climate models. At present, the number of obs4MIPs datasets has grown to about 80; many are undergoing updates, with another 20 or so in preparation, and more than 100 are proposed and under consideration. A partial list of current global satellite-based datasets includes humidity and temperature profiles; a wide range of cloud and aerosol observations; ocean surface wind, temperature, height, and sea ice fraction; surface and top-of-atmosphere longwave and shortwave radiation; and ozone (O3), methane (CH4), and carbon dioxide (CO2) products. A partial list of proposed products expected to be useful in analyzing CMIP6 results includes the following: alternative products for the above quantities, additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g., FAPAR, LAI, burned area fraction), ice sheet mass and height, carbon monoxide (CO), and nitrogen dioxide (NO2). While most existing obs4MIPs datasets consist of monthly-mean gridded data over the global domain, products with higher time resolution (e.g., daily) and/or regional products are now receiving more attention. Along with an increasing number of datasets, obs4MIPs has implemented a number of capability upgrades including (1) an updated obs4MIPs data specifications document that provides additional search facets and generally improves congruence with CMIP6 specifications for model datasets, (2) a set of six easily understood indicators that help guide users as to a dataset's maturity and suitability for application, and (3) an option to supply supplemental information about a dataset beyond what can be found in the standard metadata. With the maturation of the obs4MIPs framework, the dataset inclusion process, and the dataset formatting guidelines and resources, the scope of the observations being considered is expected to grow to include gridded in situ datasets as well as datasets with a regional focus, and the ultimate intent is to judiciously expand this scope to any observation dataset that has applicability for evaluation of the types of Earth system models used in CMIP.
    Print ISSN: 1991-959X
    Electronic ISSN: 1991-9603
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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    Publication Date: 2018-05-07
    Description: A uniform, global approach is used to quantify how atmospheric rivers (ARs) change between Coupled Model Intercomparison Project Phase 5 historical simulations and future projections under the Representative Concentration Pathway (RCP) 4.5 and RCP8.5 warming scenarios. The projections indicate that while there will be ~10% fewer ARs in the future, the ARs will be ~25% longer, ~25% wider, and exhibit stronger integrated water vapor transports (IVTs) under RCP8.5. These changes result in pronounced increases in the frequency (IVT strength) of AR conditions under RCP8.5: ~50% (25%) globally, ~50% (20%) in the northern midlatitudes, and ~60% (20%) in the southern midlatitudes. The models exhibit systematic low biases across the midlatitudes in replicating historical AR frequency (~10%), zonal IVT (~15%), and meridional IVT (~25%), with sizable intermodel differences. A more detailed examination of six regions strongly impacted by ARs suggests that the western United States, northwestern Europe, and southwestern South America exhibit considerable intermodel differences in projected changes in ARs. ©2018. American Geophysical Union. All Rights Reserved.
    Print ISSN: 0094-8276
    Electronic ISSN: 1944-8007
    Topics: Geosciences , Physics
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  • 7
    Publication Date: 2018-02-01
    Description: A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ~5 × 108 kg s−1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on 21 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERA-Interim (MERRA-2), which indicates a mean error of −2% (−8%) in AR width and +3% (−1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and ~6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean difference of 5% (20%) in AR width and 5% (14%) in TIVT and suggests the limited number of dropsonde observations is a highly (reasonably) representative sampling of ARs in the northeastern Pacific. Sensitivities of the comparison to seasonal and geographical variations in AR width/TIVT are also examined. The results provide a case where dedicated observational efforts in specific regions corroborate with global reanalyses in better characterizing the geometry and strength of ARs regionally and globally. The results also illustrate that the reanalysis depiction of ARs can help inform the selection of locations for future observational and modeling efforts.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 8
    Publication Date: 2018-02-01
    Description: Atmospheric rivers (ARs) are global phenomena that transport water vapor horizontally and are associated with hydrological extremes. In this study, the Atmospheric River Skill (ATRISK) algorithm is introduced, which quantifies AR prediction skill in an object-based framework using Subseasonal to Seasonal (S2S) Project global hindcast data from the European Centre for Medium-Range Weather Forecasts (ECMWF) model. The dependence of AR forecast skill is globally characterized by season, lead time, and distance between observed and forecasted ARs. Mean values of daily AR prediction skill saturate around 7–10 days, and seasonal variations are highest over the Northern Hemispheric ocean basins, where AR prediction skill increases by 15%–20% at a 7-day lead during boreal winter relative to boreal summer. AR hit and false alarm rates are explicitly considered using relative operating characteristic (ROC) curves. This analysis reveals that AR forecast utility increases at 10-day lead over the North Pacific/western U.S. region during positive El Niño–Southern Oscillation (ENSO) conditions and at 7- and 10-day leads over the North Atlantic/U.K. region during negative Arctic Oscillation (AO) conditions and decreases at a 10-day lead over the North Pacific/western U.S. region during negative Pacific–North America (PNA) teleconnection conditions. Exceptionally large increases in AR forecast utility are found over the North Pacific/western United States at a 10-day lead during El Niño + positive PNA conditions and over the North Atlantic/United Kingdom at a 7-day lead during La Niña + negative PNA conditions. These results represent the first global assessment of AR prediction skill and highlight climate variability conditions that modulate regional AR forecast skill.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 9
    Publication Date: 2018-01-16
    Description: Realistic simulations of the Madden–Julian oscillation (MJO) by global climate models (GCMs) remain a great challenge. To evaluate GCM simulations of the MJO, the U.S. CLIVAR MJO Working Group developed a standardized set of diagnostics, providing a comprehensive assessment of statistical properties of the MJO. Here, a suite of complementary diagnostics has been developed that provides discrimination and assessment of MJO simulations based on the perception that the MJO propagation has characteristic dynamic and thermodynamic structures. The new dynamics-oriented diagnostics help to evaluate whether a model produces eastward-propagating MJOs for the right reasons. The diagnostics include 1) the horizontal structure of boundary layer moisture convergence (BLMC) that moistens the lower troposphere to the east of a convection center, 2) the preluding eastward propagation of BLMC that leads the propagation of MJO precipitation by about 5 days, 3) the horizontal structure of 850-hPa zonal wind and its equatorial asymmetry (Kelvin easterly versus Rossby westerly intensity), 4) the equatorial vertical–longitudinal structure of the equivalent potential temperature and convective instability index that reflects the premoistening and predestabilization processes, 5) the equatorial vertical–longitudinal distribution of diabatic heating that reflects the multicloud structure of the MJO, 6) the upper-level divergence that reflects the influence of stratiform cloud heating, and 7) the MJO available potential energy generation that reflects the amplification and propagation of an MJO. The models that simulate better three-dimensional dynamic and thermodynamic structures of MJOs generally reproduce better eastward propagations. This evaluation identifies a number of shortcomings in representing dynamical and heating processes relevant to the MJO simulation and reveals potential sources of the shortcomings.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 10
    Publication Date: 2018-06-19
    Description: Atmospheric rivers (ARs) are narrow, long, transient, water vapor-rich corridors of the atmosphere that are responsible for over 90% of the poleward water vapor transport in and across midlatitudes. However, the role of ARs in modulating extratropical and polar hydroclimate features (e.g., water vapor content and precipitation) has not been fully studied, even though moistening of the polar atmosphere is both a key result and amplifier of Arctic warming and sea ice melt, and precipitation is key to the surface mass balance of polar sea ice and ice sheets. This study uses the Modern-Era Retrospective analysis for Research and Applications, Version 2 reanalysis to characterize the roles of AR water vapor transport on the column-integrated atmospheric water vapor budget in the extratropical and polar regions of both hemispheres. Meridional water vapor transport by ARs across a given latitude (examined for 40°, 50°, 60°, and 70°) is strongly related to variations in area-averaged (i.e., over the cap poleward of the given latitude) total water vapor storage and precipitation poleward of that latitude. For the climatological annual cycle, both AR transport (i.e., nonlocal sources) and total evaporation (i.e., local sources) are most correlated with total precipitation, although with slightly different phases. However, for monthly anomalies, the water budget at higher latitudes is largely dominated by the relationship between AR transport and precipitation. For pentad and daily anomalies, AR transport is related to both precipitation and water vapor storage variations. These results demonstrate the important role of episodic, extreme water vapor transports by ARs in modulating extratropical and polar hydroclimate. ©2018. American Geophysical Union. All Rights Reserved.
    Print ISSN: 2169-897X
    Electronic ISSN: 2169-8996
    Topics: Geosciences , Physics
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