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  • American Meteorological Society  (7)
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  • 1
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    A Theory for the Seasonal Predictability Barrier: Threshold, Timing, and Intensity (2018)
    American Meteorological Society
    Details
    Publication Date: 2018-12-21
    Description: A theory is developed in a stochastic climate model for understanding the general features of the seasonal predictability barrier (PB), which is characterized by a band of maximum decline in autocorrelation function phase-locked to a particular season. Our theory determines the forcing threshold, timing, and intensity of the seasonal PB as a function of the damping rate and seasonal forcing. A seasonal PB is found to be an intrinsic feature of a stochastic climate system forced by either seasonal growth rate or seasonal noise forcing. A PB is generated when the seasonal forcing, relative to the damping rate, exceeds a modest threshold. Once generated, all the PBs occur in the same calendar month, forming a seasonal PB. The PB season is determined by the decline of the seasonal forcing as well as the delayed response associated with damping. As such, for a realistic weak damping, the PB season is locked close to the minimum SST variance under the seasonal growth-rate forcing, but after the minimum SST variance under the seasonal noise forcing. The intensity of the PB is determined mainly by the amplitude of the seasonal forcing. The theory is able to explain the general features of the seasonal PB of the observed SST variability over the world. In the tropics, a seasonal PB is generated mainly by a strong seasonal growth rate, whereas in the extratropics a seasonal PB is generated mainly by a strong seasonal noise forcing. Our theory provides a general framework for the understanding of the seasonal PB of climate variability.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 2
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    On the formation mechanism of Seasonal Persistence Barrier (2020)
    American Meteorological Society
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    Publication Date: 2020-10-23
    Description: The mechanism of the seasonal persistence barrier (SPB) is studied in the framework of autoregressive (AR) model. In contrast to the seasonal variance, whose minimum is modulated mainly by the minimum growth rate or noise forcing, the SPB is caused primarily by the declining growth rate or increasing noise forcing, instead of the minimum/maximum of the growth rate or noise forcing. In other words, the SPB is caused by the declining signal-to-noise ratio (SNR) rather than the weakest SNR. In a weakly damped system, the phase of SPB is delayed from that of declining SNR by about a season. The mechanism is further applied to explain the observed SST variability in the tropical and North Pacific. For the tropical Pacific, the spring SPB could be caused by the decreasing growth rate from September to March and weak annual mean damping rate, instead of the minimum growth rate in spring. Over the North Pacific, the increasing noise forcing from March to June may lead to the summer SPB. Our mechanism provides a null hypothesis for understanding the SPB of climate variability.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 3
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    Parameter Optimization for Real-World ENSO Forecast in an Intermediate Coupled Model (2019)
    American Meteorological Society
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    Publication Date: 2019-04-10
    Description: We performed parameter estimation in the Zebiak–Cane model for the real-world scenario using the approach of ensemble Kalman filter (EnKF) data assimilation and the observational data of sea surface temperature and wind stress analyses. With real-world data assimilation in the coupled model, our study shows that model parameters converge toward stable values. Furthermore, the new parameters improve the real-world ENSO prediction skill, with the skill improved most by the parameter of the highest climate sensitivity (gam2), which controls the strength of anomalous upwelling advection term in the SST equation. The improved prediction skill is found to be contributed mainly by the improvement in the model dynamics, and second by the improvement in the initial field. Finally, geographic-dependent parameter optimization further improves the prediction skill across all the regions. Our study suggests that parameter optimization using ensemble data assimilation may provide an effective strategy to improve climate models and their real-world climate predictions in the future.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 4
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    A Diurnal Predictability Barrier for Weather Forecasts (2021)
    American Meteorological Society
    Details
    Publication Date: 2021-03-25
    Description: In this study, we investigate a diurnal predictability barrier (DPB) for weather predictions using an idealized model and observations. This DPB is referred to a maximum drop of predictability (e.g., autocorrelation) at a particular time of the day, regardless of the initial time. Previous studies demonstrated that a strong seasonal cycle of El Niño-Southern Oscillation (ENSO) growth rate is responsible for the seasonal predictability barrier of the ENSO in spring. This led us to investigate whether or not a strong diurnal cycle may generate a DPB. We study the DPB using an idealized model, the Lorenz 1963 model (Lorenz63), with the addition of a diurnal cycle. We find that diurnal growth rate can generate a DPB in this chaotic system, regardless of the initial error. Finally, by calculating the autocorrelation function using the hourly data of surface temperature, we explore the DPB at two stations in Wisconsin, USA and Beijing, China. A clear DPB feature is found at both stations. The dramatic drop of predictability at a specific time of the day is likely due to the diurnal variation of the system. This is a new feature that needs further study for short-term weather predictions.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 5
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    A theory of Spring Persistence Barrier on ENSO. Part II: Persistence Barriers in SST and ocean heat content (2021)
    American Meteorological Society
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    Publication Date: 2021-04-09
    Description: In this paper, we investigate the potential factors that control the relationship between the El Niño-Southern Oscillation (ENSO) persistence barriers (PB) in sea surface temperature (SST) and ocean heat content (OHC) and apply it to explain observational ENSO PBs. With the addition of seasonal growth rate in SST in the neutral recharge oscillator (NRO) model, approximate analytical solutions of autocorrelation functions for SST and OHC suggest strictly that the timing of PB for OHC leads that of SST by half a year and the strength of the two PBs are the same. The numerical solutions of the NRO model also show a similar relationship. The role of ENSO growth rate to PBs in SST and OHC is then identified in the damped and unstable ENSO regime. Therefore, it is suggested that for the observational ENSO, the seasonally varying ENSO growth rate in SST controls PBs in SST and OHC simultaneously.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 6
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    A theory of Spring Persistence Barrier on ENSO. Part I: The role of ENSO period (2020)
    American Meteorological Society
    Details
    Publication Date: 2020-12-23
    Description: In this paper, we investigate the role of El Niño-Southern Oscillation (ENSO) period in the spring persistence barrier (SPB) mainly using the neutral recharge oscillator (NRO) model both analytically and numerically. It is suggested that a shorter ENSO period strengthens the SPB. Moreover, in contrast to the strict phase locking of the SPB in the Langevin equation, the phase of a SPB is no longer locked exactly to a particular time of the calendar year in the NRO model. Instead, the phases of the SPB for different initial months shift earlier with the maximum persistence decline lag months. In particular, the phase of a SPB will be shifted from the early summer to early spring, corresponding to the initial months of the early half year and later half year. This feature demonstrates that for later half year, ENSO predictability decreases as the presence of ENSO period. For realistic parameters, the range of the phase change is modest, smaller than 2-3 months. Similar phase shift is also identified for the SPB in the damped ENSO regime, unstable ENSO regime and observation. Our theory provides a null hypothesis for the role of ENSO period in SPB.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 7
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    A Theory of the Spring Persistence Barrier on ENSO. Part III: The role of Tropical Pacific Ocean Heat Content (2021)
    American Meteorological Society
    Details
    Publication Date: 2021-08-24
    Description: In this paper, we investigate the relationship between upper ocean heat content (OHC) and El Niño-Southern Oscillation (ENSO) sea surface temperature (SST) anomalies mainly using the neutral recharge oscillator (NRO) model both analytically and numerically. Previous studies showed that spring OHC, which leads SST by 6-12 months, represents a major source of predictability for ENSO. It is suggested that this seasonality is caused by the seasonally varying growth rate in SST anomalies. Moreover, a shortened ENSO period will lead to a reduced SST predictability from OHC, with the most significant decrease occurring in the latter half of the calendar year. The cross-correlation relationship between OHC and ENSO SST anomalies is further identified in damped and self-excited version of the recharge oscillator model. Finally, we suggest that the seasonal growth rate of ENSO anomalies is the cause of the seasonality in the effectiveness of OHC as a predictor in ENSO forecasting. We also explain the shorter lead time between spring OHC and ENSO SST anomalies after the turn of the 21st century in terms of the apparent higher frequency of the ENSO period.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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