Development of super-ensemble techniques for ocean analyses:  the Mediterranean Sea case

Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Κορρές, Γεράσιμος; Drillet, Yann

doi:10.5194/nhess-16-1807-2016

Cited by 3 publications

(2 citation statements)

References 37 publications

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“…In oceanography, the multimodel superensemble concept was applied for the Mediterranean Sea SST forecasting by Pistoia et al (2016) using a multiple linear regression technique applied to a multiphysics and multimodel dataset. The Mediterranean Sea was the subject of early ensemble systems for the determination of the ocean response to surface wind uncertainty (Pinardi et al 2008(Pinardi et al , 2011Milliff et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Storm Surge Ensemble Prediction System for Lagoons and Transitional Environments

Alessandri

Pinardi

Federico

et al. 2023

Weather and Forecasting

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We developed a storm surge Ensemble Prediction System (EPS) for lagoons and transitional environments. Lagoons are often threatened by storm surge events with consequent risks for human life and economic losses. The uncertainties connected with a classic deterministic forecast are many, thus an ensemble forecast system is required to properly consider them and inform the end-user community accordingly. The technological resources now available allow to investigate the possibility of operational ensemble forecasting systems that will become increasingly essential for coastal management. We show the advantages and limitations of an EPS applied to a Lagoon, using a very high-resolution unstructured grid finite element model and 45 EPS members. For five recent storm surge events, the EPS generally improves the forecast skill on the third forecast day compared to just one deterministic forecast, while they are similar in the first two days. A weighting system is implemented to compute an improved ensemble mean. The uncertainties regarding sea level due to meteorological forcing, river runoff, initial and lateral boundaries are evaluated for a special case in the northern Adriatic Sea, and the different forecasts are used to compose the EPS members. We conclude that the largest uncertainty is in the initial and lateral boundary fields at different time and space scales, including the tidal components.

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Section: Introductionmentioning

confidence: 99%

Storm Surge Ensemble Prediction System for Lagoons and Transitional Environments

Alessandri

Pinardi

Federico

et al. 2023

Weather and Forecasting

View full text Add to dashboard Cite

show abstract

“…In oceanography, the multimodel super-ensemble concept was applied for the Mediterranean Sea SST forecasting by Pistoia et al, (2016) using a multiple linear regression technique applied to a multiphysics and multi-model dataset. The Mediterranean Sea was the subject of early ensemble systems for the determination of the ocean response to surface wind uncertainty (Pinardi et al 2008(Pinardi et al , 2011Milliff et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Ensemble Storm Surge Modelling of the Goro Lagoon (Adriatic Sea, Northern Italy)

Alessandri

Pinardi

Federico

et al. 2022

Preprint

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We developed a storm surge Ensemble Prediction System (EPS) for the Goro lagoon (GOLFEM-EPS) in the Northern Adriatic Sea. The lagoon is threatened every year by storm surge events with consequent risks for human life and economic losses. We show the advantages and limitations of an EPS with 45 members, using a very high-resolution unstructured grid finite element model. For five recent storm surge events, the EPS generally improves the forecast skill on the third forecast day compared to just one deterministic forecast, while they are similar in the first two days. A weighting system is implemented to compute an improved ensemble mean. The uncertainties regarding sea level due to meteorological forcing, river run-off, initial and lateral boundaries are evaluated, and the different forecasts are used to compose the EPS members. We conclude that the largest uncertainty is in the initial and lateral boundary fields at different time and space scales, including the tidal components.

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A Statistical Parameter Correction Technique for WRF Medium-Range Prediction of Near-Surface Temperature and Wind Speed Using Generalized Linear Model

Jeong¹,

Lee²

2018

Atmosphere

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Abstract:A statistical post-processing method was developed to increase the accuracy of numerical weather prediction (NWP) and simulation by matching the daily distribution of predicted temperatures and wind speeds using the generalized linear model (GLM) and parameter correction, considering an increase in model bias when the range of the prediction time lengthens. The Land Atmosphere Modeling Package Weather Research and Forecasting model, which provides 12-day agrometeorological predictions for East Asia, was employed from May 2017 to April 2018. Training periods occurred one month prior to and after the test period (12 days). A probabilistic consideration accounts for the relatively short training period. Based on the total and monthly root mean square error values for each test site, the results show an improvement in the NWP accuracy after bias correction. The spatial distributions in July and January were compared in detail. It was also shown that the physical consistency between temperature and wind speed was retained in the correction procedure, and that the GLM exhibited better performance than the quantile matching method based on monthly Pearson correlation comparison. The characteristics of coastal and mountainous sites are different from inland automatic weather stations, indicating that supplements to cover these distinctive topographic locations are necessary.

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Development of super-ensemble techniques for ocean analyses: the Mediterranean Sea case

Cited by 3 publications

References 37 publications

Storm Surge Ensemble Prediction System for Lagoons and Transitional Environments

Storm Surge Ensemble Prediction System for Lagoons and Transitional Environments

Ensemble Storm Surge Modelling of the Goro Lagoon (Adriatic Sea, Northern Italy)

A Statistical Parameter Correction Technique for WRF Medium-Range Prediction of Near-Surface Temperature and Wind Speed Using Generalized Linear Model

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