Spectral analysis of forecast error investigated with an observing system
                        simulation experiment

Privé, Nikki C.; Errico, Ronald M.

doi:10.3402/tellusa.v67.25977

Cited by 9 publications

(11 citation statements)

References 47 publications

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“…The forecast error will then relate to the total variance in the predicted phenomenon. The saturation of forecast error occurs most quickly at the finest scales, whereas at larger scales of motion variations are observed that have the potential for predictability at longer lead times (Hoskins, 2013;Privé and Errico, 2015;Ying and Zhang, 2017;Toth and Buizza, 2019).…”

mentioning

confidence: 99%

The influence of aggregation and statistical post‐processing on the subseasonal predictability of European temperatures

Straaten

Whan

Coumou

et al. 2020

Quart J Royal Meteoro Soc

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The succession of European surface weather patterns has limited predictability because disturbances quickly transfer to the large‐scale flow. Some aggregated statistics, however, such as the average temperature exceeding a threshold, can have extended predictability when adequate spatial scales, temporal scales and thresholds are chosen. This study benchmarks how the forecast skill horizon of probabilistic 2‐m temperature forecasts from the subseasonal forecast system of the European Centre for Medium‐Range Weather Forecasts (ECMWF) evolves with varying scales and thresholds. We apply temporal aggregation by rolling‐window averaging and spatial aggregation by hierarchical clustering. We verify 20 years of re‐forecasts against the E‐OBS dataset and find that European predictability extends at maximum into the fourth week. Simple aggregation and standard statistical post‐processing extend the forecast skill horizon with two and three skilful days on average, respectively. The intuitive notion that higher levels of aggregation capture large‐scale and low‐frequency variability and can therefore tap into extended predictability holds in many cases. However, we show that the effect can be saturated and that there exist regional optimums beyond which extra aggregation reduces the forecast skill horizon. We expect such windows of predictability to result from specific physical mechanisms that only modulate and extend predictability locally. To optimize subseasonal forecasts for Europe, aggregation should thus be limited in certain cases.

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mentioning

confidence: 99%

The influence of aggregation and statistical post‐processing on the subseasonal predictability of European temperatures

Straaten

Whan

Coumou

et al. 2020

Quart J Royal Meteoro Soc

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show abstract

“…The above remarks concerning the challenges of calibrating AMSEAS motivate the methodology used to assess the forecast error of non-phase-locked tides in AMSEAS. In the nomenclature of numerical weather forecasting, the approach taken is a self-analysis verification or self-verification (e.g., Privé and Errico, 2015). The forecast error is measured by comparing the nowcast valid at date, T n , with a forecast previously computed on the date, T f = T n − τ , with a given lead time, τ , i.e., T f + τ = T n .…”

Section: The Amseas Ocean Forecasting Systemmentioning

confidence: 99%

“…In fact, it is only possible to separate the baroclinic tide from the barotropic tide in altimetry data because of the large separation in spatial scales between these classes of waves (Zaron, 2019). However, there is another component of sea level variability associated with the tidal frequencies that represents non-phaselocked baroclinic tides, which are created by temporal modulations of the propagation medium (Munk and Cartwright, 1966;Rainville and Pinkel, 2006;Colosi and Munk, 2006;Zilberman et al, 2011;Ray and Zaron, 2011). Because modulations of the propagation medium -caused by mesoscale eddies and other processes -are, in part, represented within operational ocean forecasting systems, it ought to be possible to predict some component of the non-phase-locked tide with such a forecasting system.…”

Section: Introductionmentioning

confidence: 99%

Predictability of non-phase-locked baroclinic tides in the Caribbean Sea

Zaron

2019

Ocean Sci.

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Abstract. The predictability of the sea surface height expression of baroclinic tides is examined with 96 h forecasts produced by the AMSEAS operational forecast model during 2013–2014. The phase-locked tide, both barotropic and baroclinic, is identified by harmonic analysis of the 2-year record and found to agree well with observations from tide gauges and satellite altimetry within the Caribbean Sea. The non-phase-locked baroclinic tide, which is created by time-variable mesoscale stratification and currents, may be identified from residual sea level anomalies (SLAs) near the tidal frequencies. The predictability of the non-phase-locked tide is assessed by measuring the difference between a forecast – centered at T+36, T+60, or T+84 h – and the model's later verifying analysis for the same time. Within the Caribbean Sea, where a baroclinic tidal sea level range of ±5 cm is typical, the forecast error for the non-phase-locked tidal SLA is correlated with the forecast error for the subtidal (mesoscale) SLA. Root mean square values of the former range from 0.5 to 2 cm, while the latter ranges from 1 to 6 cm, for a typical 84 h forecast. The spatial and temporal variability of the forecast error is related to the dynamical origins of the non-phase-locked tide and is briefly surveyed within the model.

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“…The above remarks concerning the difficulty with mapping the baroclinic tides motivate the methodology used to assess the forecast error of non-phase-locked tides in AMSEAS. In the nomenclature of numerical weather forecasting, the approach taken is a self-analysis verification, or self-verification (e.g., Privé and Errico, 2015). The forecast error is measured by comparing the nowcast valid at date, T n , with a forecast previously computed on the date, T f = T n − τ , with a given lead-time, τ , i.e., T f + τ = T n .…”

Section: Phase-locked Tides In Amseasmentioning

confidence: 99%

Predictability of Non-Phase-Locked Baroclinic Tides in the Caribbean Sea

Zaron¹

2019

Preprint

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Abstract. The predictability of the sea surface height expression of baroclinic tides is examined with 96 hr forecasts produced by the AMSEAS operational forecast model during 2013–2014. The phase-locked tide, both barotropic and baroclinic, is identified by harmonic analysis of the 2 year record and found to agree well with observations from tide gauges and satellite altimetry within the Caribbean Sea. The non-phase-locked baroclinic tide, which is created by the time-variable mesoscale stratification and currents, may be identified from residual sea level anomaly (SLA) near the tidal frequencies. The predictability of the non-phase-locked tide is assessed by measuring the difference between a forecast – centered at T+36 hr, T+60 hr, or T+84 hr – and the model's later verifying analysis for the same time. Within the Caribbean Sea, where a baroclinic tidal sea level range of ±5 cm is typical, the forecast error for the non-phase-locked tidal SLA is correlated with the forecast error for the sub-tidal (mesoscale) SLA. Root-mean-square values of the former range from 0.5 cm to 2 cm, while the latter ranges from 1 cm to 6 cm, for a typical 84 hr forecast. The spatial and temporal variability of the forecast error is related to the dynamical origins of the non-phase-locked tide and is briefly surveyed within the model.

show abstract

Spectral analysis of forecast error investigated with an observing system simulation experiment

Cited by 9 publications

References 47 publications

The influence of aggregation and statistical post‐processing on the subseasonal predictability of European temperatures

The influence of aggregation and statistical post‐processing on the subseasonal predictability of European temperatures

Predictability of non-phase-locked baroclinic tides in the Caribbean Sea

Predictability of Non-Phase-Locked Baroclinic Tides in the Caribbean Sea

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