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  • 1
    In: Climate Dynamics, Springer Science and Business Media LLC, Vol. 53, No. 11 ( 2019-12), p. 6947-6960
    Abstract: Here, we explored in depth the relationship among the deterministic prediction skill, the probabilistic prediction skill and the potential predictability. This was achieved by theoretical analyses and, in particular, by an analysis of long-term ensemble ENSO hindcast over 161 years from 1856 to 2016. First, a nonlinear monotonic relationship between the deterministic prediction skill and the probabilistic prediction skill, derived by theoretical analysis, was examined and validated using the ensemble hindcast. Further, the co-variability between the potential predictability and the deterministic prediction skill was explored in both perfect model assumption and actual model scenario. On these bases, we investigated the relationship between the potential predictability and probabilistic prediction skill from both the practice of ENSO forecast and theoretical perspective. The results of the study indicate that there are nonlinear monotonic relationships among these three kinds of measures. The potential predictability is considered to be a good indicator for the actual prediction skill in terms of both the deterministic measures and the probabilistic framework. The relationships identified here exhibit considerable significant practical sense to conduct predictability researches, which provide an inexpensive and moderate approach for inquiring prediction uncertainties without the requirement of costly ensemble experiments.
    Type of Medium: Online Resource
    ISSN: 0930-7575 , 1432-0894
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 382992-3
    detail.hit.zdb_id: 1471747-5
    SSG: 16,13
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  • 2
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2020
    In:  Climate Dynamics Vol. 54, No. 1-2 ( 2020-01), p. 885-899
    In: Climate Dynamics, Springer Science and Business Media LLC, Vol. 54, No. 1-2 ( 2020-01), p. 885-899
    Abstract: Numerous works have indicated that westerly wind bursts (WWBs) have a significant contribution to the development of El Niño events. However, the simulation of WWBs commonly suffers from large biases in the current generation of coupled general circulation models (CGCMs), limiting our ability to predict El Niño events. In this study, we introduce a WWBs parameterization scheme into the global coupled Community Earth System Model (CESM) to improve the representation of WWBs and to study the impacts of WWBs on El Niño-Southern Oscillation (ENSO) characteristics. It is found that CESM with the WWBs parameterization scheme can generate more realistic characteristics of WWBs, in particular their location and seasonal variation of occurrence. With the parameterized WWBs, the skewness of the Niño 3 index is increased, in better agreement with observation. Eastern Pacific El Niño and central Pacific El Niño events could be successfully reproduced in the model run with WWBs parameterization. Further diagnoses show that the enhanced horizontal advection in the central Pacific and vertical advection in the eastern Pacific, both of which are triggered by WWBs, are crucial factors responsible for the improvements in ENSO simulation. Clearly, WWBs have important effects on ENSO asymmetry and ENSO diversity.
    Type of Medium: Online Resource
    ISSN: 0930-7575 , 1432-0894
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 382992-3
    detail.hit.zdb_id: 1471747-5
    SSG: 16,13
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  • 3
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2018
    In:  Climate Dynamics Vol. 50, No. 3-4 ( 2018-2), p. 1353-1371
    In: Climate Dynamics, Springer Science and Business Media LLC, Vol. 50, No. 3-4 ( 2018-2), p. 1353-1371
    Type of Medium: Online Resource
    ISSN: 0930-7575 , 1432-0894
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2018
    detail.hit.zdb_id: 382992-3
    detail.hit.zdb_id: 1471747-5
    SSG: 16,13
    Location Call Number Limitation Availability
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  • 4
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2022
    In:  Journal of Geophysical Research: Oceans Vol. 127, No. 3 ( 2022-03)
    In: Journal of Geophysical Research: Oceans, American Geophysical Union (AGU), Vol. 127, No. 3 ( 2022-03)
    Abstract: A long‐term ensemble hindcast for 138 years was conducted using the Community Earth System Model The IOD predictability, including the deterministic and probability prediction skills, as well as the potential prediction, is investigated The strength of IOD events plays an important role in the IOD prediction skills, regardless of the measurement metrics
    Type of Medium: Online Resource
    ISSN: 2169-9275 , 2169-9291
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2022
    detail.hit.zdb_id: 2016804-4
    detail.hit.zdb_id: 161667-5
    detail.hit.zdb_id: 3094219-6
    SSG: 16,13
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  • 5
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2016
    In:  Journal of Advances in Modeling Earth Systems Vol. 8, No. 4 ( 2016-12), p. 1932-1952
    In: Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), Vol. 8, No. 4 ( 2016-12), p. 1932-1952
    Abstract: We comprehensively examine the possible impacts of coupling processes on simulations of the Indian Ocean Dipole The IOD intensity is attributable to wind‐thermocline depth feedback and thermocline depth‐subsurface temperature feedback We analyze the relationships of IOD‐monsoon, ENSO‐monsoon, and IOD‐ENSO
    Type of Medium: Online Resource
    ISSN: 1942-2466 , 1942-2466
    URL: Issue
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2016
    detail.hit.zdb_id: 2462132-8
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  • 6
    Online Resource
    Online Resource
    Wiley ; 2017
    In:  Quarterly Journal of the Royal Meteorological Society Vol. 143, No. 709 ( 2017-10), p. 3269-3278
    In: Quarterly Journal of the Royal Meteorological Society, Wiley, Vol. 143, No. 709 ( 2017-10), p. 3269-3278
    Abstract: Particle filters (PFs) constitute a sequential data assimilation method based on the Monte Carlo approximation of Bayesian estimation theory. Standard PFs use scalar weights derived from the likelihood of the approximate posterior probability density functions (PDFs) of observations and use resampling schemes to generate posterior particles. However, the scalar weights approach interferes with the localization algorithm and often results in filter degeneracy. Recently, a localized particle filter (LPF) was developed by extending the scalar weights of PFs to vector weights, which produces various (local) posterior PDFs for different model grids and variables. With a sampling and merging approach in the resampling, a LPF can effectively solve the filter degeneracy problem and offer a practical, efficient algorithm for localization. However, this algorithm assumes the variations in the weights of a state variable of neighbouring grids to be continuous and uses a spatially linear interpolation of PF weights to determine the local weights. In this paper, we first analyse the possible concerns associated with the linear continuity of PF weights. This assumption is found to challenge the theoretical properties of nonlinear and non‐Gaussian variations in weights and alleviate the intrinsic spatial variations of PF weights. On this basis, we propose a new algorithm to produce vector weights for PFs for neighbouring grids. Numerical experiments using the Lorenz 96 model show that our new LPF performs better than the existing LPF algorithm, indicating the advantages and potential applications of this new algorithm of vector weights in the field of data assimilation.
    Type of Medium: Online Resource
    ISSN: 0035-9009 , 1477-870X
    URL: Issue
    RVK:
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 3142-2
    detail.hit.zdb_id: 2089168-4
    SSG: 14
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  • 7
    Online Resource
    Online Resource
    American Meteorological Society ; 2022
    In:  Journal of Climate ( 2022-04-28), p. 1-21
    In: Journal of Climate, American Meteorological Society, ( 2022-04-28), p. 1-21
    Abstract: Maritime continent (MC) rainfall plays an important role in global climate variability, but its prediction remains extremely challenging. Based on a long-term state-of-the-art hindcast product recently completed by the authors’ group, this work investigates the decadal variation of the MC rainfall predictability in the wet season for the first time. The prediction skills were relatively high before 1940 and after 1980, but relatively low between these years. In a diagnostic analysis of the controlling factors of the decadal variation, the signal strength represented by the variance of the rainfall variability was identified as the dominant factor. Further analysis concluded that the El Niño Southern Oscillation (ENSO) phases are the key controlling sources. The MC rainfall was more predictable during periods dominated by El Niño events than during periods dominated by La Niña events because El Niño elicits stronger ocean–atmosphere interactions in the tropics, providing a stronger signal of MC rainfall than La Niña events.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 8
    Online Resource
    Online Resource
    American Meteorological Society ; 2022
    In:  Journal of Climate Vol. 35, No. 17 ( 2022-09-01), p. 5759-5771
    In: Journal of Climate, American Meteorological Society, Vol. 35, No. 17 ( 2022-09-01), p. 5759-5771
    Abstract: In this study, we investigate both the decadal variation of the Indian Ocean dipole (IOD) prediction skill and possible sources of this decadal variation. We use an ensemble long-term retrospective forecast experiment covering 1880–2017 that utilizes the Community Earth System Model (CESM). We find that the decadal variation of the IOD prediction skill is significant and that it varies with the lead time. We also find that the decadal variation of the IOD prediction skill for the target season of boreal autumn determines that for all initial conditions, regardless of the lead months. For short lead times, the decadal variations of the IOD strength and of the IOD precursor in the initial month of July are the major factors influencing the IOD prediction skill. This occurs because the IOD events are in the developmental phase, and the stronger IOD signal in the initial conditions leads to better predictions. For long lead times, the decadal variation of remote forcing by El Niño–Southern Oscillation (ENSO) and the ENSO precursor signal in the IOD influence the IOD prediction skill more significantly than do the strengths of the ENSO or the IOD. In addition, the analysis also indicated that the period with a low ENSO–IOD relationship has low predictability, not only because the ENSO little influence on IOD but also because the model biasedly overestimates the ENSO–IOD relationship. Significance Statement The Indian Ocean dipole (IOD) has strong climatic effects, both around the Indian Ocean and globally, which have strong impacts on human life and economic development. It is important to be able to predict IOD events accurately to mitigate those impacts. Here, we conducted a 138-yr prediction experiment using a state-of-the-art climate model to confirm the existence of a decadal variation in IOD predictability and to identify factors that influence the IOD prediction skill. The most important factors that influence the decadal variation of IOD prediction skill differ for 3-month and 6-month lead times, and additional studies will be necessary to clarify the specific factors responsible for these differences.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 9
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Journal of Climate Vol. 34, No. 9 ( 2021-05), p. 3355-3366
    In: Journal of Climate, American Meteorological Society, Vol. 34, No. 9 ( 2021-05), p. 3355-3366
    Abstract: This work uses a 19-yr ensemble hindcast of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the average predictable time (APT) method to detect the most predictable tropical intraseasonal variability (ISV) mode. The first and most predictable mode (APT1) of tropical ISV is similar to a joint merger of the two Madden–Julian oscillation (MJO) modes with more weight on the second mode and is characterized by a tripole pattern with two positive centers in the equatorial western Indian Ocean and central Pacific Ocean and a negative center over the Maritime Continent. The APT1 doubles the skillful prediction period made by the MJO defined by a correlation skill of 0.5 (approximately 25 days in the ECMWF model), demonstrating its potential to become a skillful prediction target and to offer powerful subseasonal prediction sources. The underlying physical process and predictability source of the APT1 are further analyzed. The APT1 is very similar to the pattern triggered by the most predictable tropical intraseasonal sea surface temperature (SST) anomalies mode, suggesting its oceanic origin. Tropical ocean–atmosphere interaction plays a critical role in the APT1 by enhancing the evolution of tropical convection cells under WES (wind–evaporation–SST) and Bjerknes feedbacks. The internal atmospheric processes also have an important impact on the formation and maintenance of the APT1.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 10
    In: National Science Review, Oxford University Press (OUP)
    Abstract: Ensemble Kalman filter-based targeted observation is one of the best methods for determining the optimal observational array for oceanic buoy deployment. This study proposes a new algorithm suitable for a ‘cross-region and cross-variable’ approach by introducing a projection operator into the optimization process. A targeted observational analysis was conducted for El Niño–Southern Oscillation (ENSO) events in the tropical western Pacific for the Tropical Pacific Observation System (TPOS) 2020. The prediction target was at the Niño 3.4 region, and the first 10 optimal observational sites detected reduced initial uncertainties by 70%, with the best observational array located where the Rossby wave signal dominates. At the vertical level, the most significant contribution was derived from observations near the thermocline. This study provides insights into understanding ENSO-related variability and offers a practical approach to designing an optimal mooring array. It serves as a scientific guidance for designing a TPOS observation network.
    Type of Medium: Online Resource
    ISSN: 2095-5138 , 2053-714X
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 2745465-4
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