GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Guidelines for the use and interpretation of assays for monitoring autophagy
    Informa UK Limited ; 2012
    In:  Autophagy Vol. 8, No. 4 ( 2012-04), p. 445-544
    Details
    In: Autophagy, Informa UK Limited, Vol. 8, No. 4 ( 2012-04), p. 445-544
    Type of Medium: Online Resource
    ISSN: 1554-8627 , 1554-8635
    URL: Article
    DOI: 10.4161/auto.19496
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2012
    detail.hit.zdb_id: 2262043-6
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    Using Stochastically Perturbed Parameterizations to Represent Model Uncertainty. Part II: Comparison with Existing Techniques in an Operational Ensemble
    American Meteorological Society ; 2022
    In:  Monthly Weather Review Vol. 150, No. 11 ( 2022-11), p. 2859-2882
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 150, No. 11 ( 2022-11), p. 2859-2882
    Abstract: The ability of a stochastically perturbed parameterization (SPP) approach to represent uncertainties in the model component of the Canadian Global Ensemble Prediction System was demonstrated in Part I of this investigation. The goal of this second step in SPP evaluation is to determine whether the scheme represents a viable alternative to the current operational combination of a multiphysics configuration and stochastically perturbed parameterization tendencies (SPPT). An assessment of the impact of each model uncertainty estimate in isolation reveals that, although the multiphysics configuration is highly effective at generating ensemble spread, it is often the result of differing biases rather than a reflection of flow-dependent error growth. Moreover, some of the members of the multiphysics ensemble suffer from large errors on regional scales as a result of suboptimal configurations. The SPP scheme generates a greater diversity of member solutions than the SPPT scheme in isolation, and it has an impact on forecast performance that is similar to that of current operational uncertainty estimates. When the SPP framework is combined with recent upgrades to the model physics suite that are only applicable in the stochastic perturbation context, the quality of global ensemble guidance is significantly improved. Significance Statement The stochastically perturbed parameterization (SPP) technique was introduced in Part I to represent model uncertainties in forecasts generated by an operational global ensemble prediction system. We focus here on the viability of this technique as a replacement for the system’s current uncertainty estimates: multiphysics and stochastic perturbations of physics tendencies. Despite the practical success of this combination, it suffers from physical inconsistencies and poor conservation properties. The adoption of SPP allows the ensemble to benefit from a recent set of model updates that couple with this new representation of model uncertainty to yield significant improvements in the quality of forecasts generated by the system.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    URL: Article
    DOI: 10.1175/MWR-D-21-0316.1
    DOI: 10.1175/MWR-D-21-0316.s1
    RVK:
    RA 1000
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    Reproducible and Irreproducible Components in Ensemble Simulations with a Regional Climate Model
    American Meteorological Society ; 2008
    In:  Monthly Weather Review Vol. 136, No. 12 ( 2008-12-01), p. 4942-4961
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 136, No. 12 ( 2008-12-01), p. 4942-4961
    Abstract: High-resolution limited-area models (LAMs) have been widely employed to downscale coarse-resolution climate simulations or objective analyses. The growing evidence that LAM climate statistics can be sensitive to initial conditions suggests that a deterministic verification of LAM solutions in terms of finescale atmospheric features might be misguided. In this study a 20-member ensemble of LAM integrations with perturbed initial conditions, driven by NCEP–NCAR reanalyses, is conducted for a summer season over a midlatitude domain. Ensemble simulations allow for the separation of the downscaled information in two parts: a unique, reproducible component associated with lateral-boundary and surface forcing, and an irreproducible component associated with internal variability. The partition in the reproducible and irreproducible components and their seasonal statistics is examined as a function of horizontal length scale, geographical position within the domain, height, and weather episodes during the season. The scale analysis of time-dependent model variables shows that, at scales smaller than a few hundred kilometers, the irreproducible component dominates, on average, the model solution, implying that the downscaled information at these scales is mainly in stochastic form. The constraint exerted by the surface forcing on the internal variability is weak. For seasonal averages, the reproducible component dominates at all scales, although for precipitation the reproducible and irreproducible components are of the same order of magnitude at scales smaller than 150 km. These results imply a need for a probabilistic approach to LAM climate simulations and their verification, especially for shorter integration times, from months to seasons.
    Type of Medium: Online Resource
    ISSN: 1520-0493 , 0027-0644
    URL: Article
    DOI: 10.1175/2008MWR2393.1
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2008
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    A Convection Parameterization for Low-CAPE Environments
    American Meteorological Society ; 2020
    In:  Monthly Weather Review Vol. 148, No. 12 ( 2020-12), p. 4917-4941
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 148, No. 12 ( 2020-12), p. 4917-4941
    Abstract: Numerical models that are unable to resolve moist convection in the atmosphere employ physical parameterizations to represent the effects of the associated processes on the resolved-scale state. Most of these schemes are designed to represent the dominant class of cumulus convection that is driven by latent heat release in a conditionally unstable profile with a surplus of convective available potential energy (CAPE). However, an important subset of events occurs in low-CAPE environments in which potential and symmetric instabilities can sustain moist convective motions. Convection schemes that are dependent on the presence of CAPE are unable to depict accurately the effects of cumulus convection in these cases. A mass-flux parameterization is developed to represent such events, with triggering and closure components that are specifically designed to depict subgrid-scale convection in low-CAPE profiles. Case studies show that the scheme eliminates the “bull’s-eyes” in precipitation guidance that develop in the absence of parameterized convection, and that it can represent the initiation of elevated convection that organizes squall-line structure. The introduction of the parameterization leads to significant improvements in the quality of quantitative precipitation forecasts, including a large reduction in the frequency of spurious heavy-precipitation events predicted by the model. An evaluation of surface and upper-air guidance shows that the scheme systematically improves the model solution in the warm season, a result that suggests that the parameterization is capable of accurately representing the effects of moist convection in a range of low-CAPE environments.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/MWR-D-20-0020.1
    RVK:
    RA 1000
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 5
    Online Resource
    Online Resource
    Reducing a Tropical Cyclone Weak-Intensity Bias in a Global Numerical Weather Prediction System
    American Meteorological Society ; 2024
    In:  Monthly Weather Review Vol. 152, No. 3 ( 2024-03), p. 837-863
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 152, No. 3 ( 2024-03), p. 837-863
    Abstract: The operational Canadian Global Deterministic Prediction System suffers from a weak-intensity bias for simulated tropical cyclones. The presence of this bias is confirmed in progressively simplified experiments using a hierarchical system development technique. Within a semi-idealized, simplified-physics framework, an unexpected insensitivity to the representation of relevant physical processes leads to investigation of the model’s semi-Lagrangian dynamical core. The root cause of the weak-intensity bias is identified as excessive numerical dissipation caused by substantial off-centering in the two time-level time integration scheme used to solve the governing equations. Any (semi)implicit semi-Lagrangian model that employs such off-centering to enhance numerical stability will be afflicted by a misalignment of the pressure gradient force in strong vortices. Although the associated drag is maximized in the tropical cyclone eyewall, the impact on storm intensity can be mitigated through an intercomparison-constrained adjustment of the model’s temporal discretization. The revised configuration is more sensitive to changes in physical parameterizations and simulated tropical cyclone intensities are improved at each step of increasing experimental complexity. Although some rebalancing of the operational system may be required to adapt to the increased effective resolution, significant reduction of the weak-intensity bias will improve the quality of Canadian guidance for global tropical cyclone forecasting. Significance Statement Global numerical weather prediction systems provide important guidance to forecasters about tropical cyclone development, motion, and intensity. Despite recent improvements in the Canadian operational model’s ability to predict tropical cyclone formation, the system systematically underpredicts the intensity of these storms. In this study, we use a set of increasingly simplified experiments to identify the source of this error, which lies in the numerical time-stepping scheme used to solve the model equations. By decreasing numerical drag on the tropical cyclone circulation, intensity predictions that resemble those of other global modeling systems are achieved. This will improve the quality of Canadian tropical cyclone guidance for forecasters around the world.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    URL: Article
    DOI: 10.1175/MWR-D-23-0193.1
    DOI: 10.1175/MWR-D-23-0193.s1
    RVK:
    RA 1000
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2024
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 6
    Online Resource
    Online Resource
    Present climate and climate change over North America as simulated by the fifth-generation Canadian regional climate model
    Springer Science and Business Media LLC ; 2013
    In:  Climate Dynamics Vol. 41, No. 11-12 ( 2013-12), p. 3167-3201
    Details
    In: Climate Dynamics, Springer Science and Business Media LLC, Vol. 41, No. 11-12 ( 2013-12), p. 3167-3201
    Type of Medium: Online Resource
    ISSN: 0930-7575 , 1432-0894
    URL: Article
    DOI: 10.1007/s00382-013-1737-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2013
    detail.hit.zdb_id: 382992-3
    detail.hit.zdb_id: 1471747-5
    SSG: 16,13
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 7
    Online Resource
    Online Resource
    Climate projections over CORDEX Africa domain using the fifth-generation Canadian Regional Climate Model (CRCM5)
    Springer Science and Business Media LLC ; 2013
    In:  Climate Dynamics Vol. 41, No. 11-12 ( 2013-12), p. 3219-3246
    Details
    In: Climate Dynamics, Springer Science and Business Media LLC, Vol. 41, No. 11-12 ( 2013-12), p. 3219-3246
    Type of Medium: Online Resource
    ISSN: 0930-7575 , 1432-0894
    URL: Article
    DOI: 10.1007/s00382-012-1651-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2013
    detail.hit.zdb_id: 382992-3
    detail.hit.zdb_id: 1471747-5
    SSG: 16,13
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 8
    Online Resource
    Online Resource
    Using Stochastically Perturbed Parameterizations to Represent Model Uncertainty. Part I: Implementation and Parameter Sensitivity
    American Meteorological Society ; 2022
    In:  Monthly Weather Review Vol. 150, No. 11 ( 2022-11), p. 2829-2858
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 150, No. 11 ( 2022-11), p. 2829-2858
    Abstract: Accurately representing model-based sources of uncertainty is essential for the development of reliable ensemble prediction systems for NWP applications. Uncertainties in discretizations, algorithmic approximations, and diabatic and unresolved processes combine to influence forecast skill in a flow-dependent way. An emerging approach designed to provide a process-level representation of these potential error sources, stochastically perturbed parameterizations (SPP), is introduced into the Canadian operational Global Ensemble Prediction System. This implementation extends the SPP technique beyond its typical application to free parameters in the physics suite by sampling uncertainty both within the dynamical core and at the formulation level using “error models” when multiple physical closures are available. Because SPP perturbs components within the model, internal consistency is ensured and conservation properties are not affected. The full SPP scheme is shown to increase ensemble spread to keep pace with error growth on a global scale. The sensitivity of the ensemble to each independently perturbed “element” is then assessed, with those responsible for the bulk of the response analyzed in more detail. Perturbations to surface exchange coefficients and the turbulent mixing length have a leading impact on near-surface statistics. Aloft, a tropically focused error model representing uncertainty in the advection scheme is found to initiate growing perturbations on the subtropical jet that lead to forecast improvements at higher latitudes. The results of Part I suggest that SPP has the potential to serve as a reliable representation of model uncertainty for ensemble NWP applications. Significance Statement Ensemble systems account for the negative impact that uncertainties in prediction models have on forecasts. Here, uncertain model parameters and algorithms are subjected to perturbations representing impact on forecast errors. By initiating error growth within the model calculations, the equally skillful members of the ensemble remain physically realistic and self-consistent, which is not guaranteed by other depictions of model error. This “stochastically perturbed parameterization” technique (SPP) comprises many small error sources, each analyzed in isolation. Each source is related to a limited set of processes, making it possible to determine how the individual perturbations affect the forecast. We conclude that SPP in the Canadian Global Ensemble Forecasting System produces realistic estimates of the impact of model uncertainties on forecast skill.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/MWR-D-21-0315.1
    RVK:
    RA 1000
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 9
    Online Resource
    Online Resource
    Is Institutional Democracy a Good Proxy for Model Independence?
    American Meteorological Society ; 2016
    In:  Journal of Climate Vol. 29, No. 23 ( 2016-12-01), p. 8301-8316
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 29, No. 23 ( 2016-12-01), p. 8301-8316
    Abstract: Climate models developed within a given research group or institution are prone to share structural similarities, which may induce resembling features in their simulations of the earth’s climate. This assertion, known as the “same-center hypothesis,” is investigated here using a subsample of CMIP3 climate projections constructed by retaining only the models originating from institutions that provided more than one model (or model version). The contributions of individual modeling centers to this ensemble are first presented in terms of climate change projections. A metric for climate change disagreement is then defined to analyze the impact of typical structural differences (such as resolution, parameterizations, or even entire atmosphere and ocean components) on regional climate projections. This metric is compared to a present climate performance metric (correlation of error patterns) within a cross-model comparison framework in terms of their abilities to identify the same-center models. Overall, structural differences between the pairs of same-center models have a stronger impact on climate change projections than on how models reproduce the observed climate. The same-center criterion is used to detect agreements that might be attributable to model similarities and thus that should not be interpreted as implying greater confidence in a given result. It is proposed that such noninformative agreements should be discarded from the ensemble, unless evidence shows that these models can be assumed to be independent. Since this burden of proof is not generally met by the centers participating in a multimodel ensemble, the authors propose an ensemble-weighting scheme based on the assumption of institutional democracy to prevent overconfidence in climate change projections.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    DOI: 10.1175/JCLI-D-15-0761.1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2016
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 10
    Online Resource
    Online Resource
    Internal variability of fine‐scale components of meteorological fields in extended‐range limited‐area model simulations with atmospheric and surface nudging
    American Geophysical Union (AGU) ; 2015
    In:  Journal of Geophysical Research: Atmospheres Vol. 120, No. 17 ( 2015-09-16), p. 8621-8641
    Details
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 120, No. 17 ( 2015-09-16), p. 8621-8641
    Abstract: Dynamical downscaling Initial condition ensembles Spectral analysis of reproducibility
    Type of Medium: Online Resource
    ISSN: 2169-897X , 2169-8996
    URL: Issue
    URL: Article
    DOI: 10.1002/jgrd.v120.17
    DOI: 10.1002/2015JD023350
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2015
    detail.hit.zdb_id: 710256-2
    detail.hit.zdb_id: 2016800-7
    detail.hit.zdb_id: 2969341-X
    SSG: 16,13
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...