Stochastic ensemble climate forecast with an analogue model

Yiou, Pascal; Déandreis, Céline

doi:10.5194/gmd-12-723-2019

Cited by 20 publications

(43 citation statements)

References 35 publications

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“…The first step is to build a database of analogs of the atmospheric circulation. We outline the procedure of Yiou and Déandréis (2019), summarized in Figure 1a. For a given day t, we determine the similarity of Z500 for all days t that are in a year different from t, but within 30 calendar days of t. This similarity is quantified by a Euclidean distance (or root mean square) between the daily Z500 maps.…”

Section: Analogsmentioning

confidence: 99%

“…As a refinement over the study of Yiou and Déandréis (2019), a time embedding of 4 days was used for the search of analogs dates. This means that the field X(t) for which we compute analogs is X(t) = (Z500(t), Z500(t + 1), .…”

Section: Analogsmentioning

confidence: 99%

“…simulation of European precipitations. We then analyse the performance of this SWG for lead times of 5 to 20 days, with the forecast skill scores used by Yiou and Déandréis (2019).…”

mentioning

confidence: 99%

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Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation

Krouma

Yiou

Déandreis³

et al. 2021

Preprint

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Abstract. In this study, we aim to assess the skill of a stochastic weather generator (SWG) to forecast precipitation in several cities of Western Europe. The SWG is based on random sampling of analogs of the geopotential height at 500 hPa. The SWG is evaluated for two reanalyses (NCEP and ERA5). We simulate 100-member ensemble forecasts on a daily time increment. We evaluate the performance of SWG with forecast skill scores and we compare it to ECMWF forecasts. Results show significant positive skill scores (continuous rank probability skill score and correlation) for lead times of 5 and 10 days for different areas in Europe. We found that the low predictability of our model is related to specific weather regimes, depending on the European region. Comparing SWG forecasts to ECMWF forecasts, we found that the SWG shows a good performance for 5 days. This performance varies from one region to another. This paper is a proof of concept for a stochastic regional ensemble precipitation forecast. Its parameters (e.g. region for analogs) must be tuned for each region in order to optimize its performance.

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Section: Analogsmentioning

confidence: 99%

Section: Analogsmentioning

confidence: 99%

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Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation

Krouma

Yiou

Déandreis³

et al. 2021

Preprint

Self Cite

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“…For each day between 1 January 1948 and 31 December 2018, the best 20 analogues (with respect to a Euclidean distance) in a different year and within 30 cal-endar days are searched. This follows the procedure of Yiou et al (2013).…”

Section: Circulation Analoguesmentioning

confidence: 99%

“…This shows how the dynamic simulations differ from each other and depend on the initial conditions. The sensitivity to initial conditions was exploited by Yiou and Déandréis (2019) for ensemble forecasts with analogues.…”

Section: Atmospheric Patternsmentioning

confidence: 99%

Simulation of extreme heat waves with empirical importance sampling

Yiou

Jézéquel²

2020

Geosci. Model Dev.

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Abstract. Simulating ensembles of extreme events is a necessary task to evaluate their probability distribution and analyze their meteorological properties. Algorithms of importance sampling have provided a way to simulate trajectories of dynamical systems (like climate models) that yield extreme behavior, like heat waves. Such algorithms also give access to the return periods of such events. We present an adaptation based on circulation analogues of importance sampling to provide a data-based algorithm that simulates extreme events like heat waves in a realistic way. This algorithm is a modification of a stochastic weather generator, which gives more weight to trajectories with higher temperatures. This presentation outlines the methodology using European heat waves and illustrates the spatial and temporal properties of simulations.

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What do large‐scale patterns teach us about extreme precipitation over the Mediterranean at medium‐ and extended‐range forecasts?

Mastrantonas

Magnusson

Pappenberger

et al. 2022

Quart J Royal Meteoro Soc

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Extreme precipitation events (EPEs) can have devastating consequences, such as floods and landslides, posing a great threat to society and economy. Predicting such events long in advance can support the mitigation of negative impacts. Here, we focus on EPEs over the Mediterranean, a region that is frequently affected by such hazards. Previous work identified strong connections between localized EPEs and large‐scale atmospheric flow patterns, affecting weather over the entire Mediterranean. We analyse the predictive skill of these patterns in the European Centre for Medium‐Range Weather Forecasts (ECMWF) extended range forecasts and assess if and where these patterns can be used for indirect predictions of EPEs, using the Brier skill score. The results show that the ECMWF model provides skilful predictions of the Mediterranean patterns up to 2 weeks in advance. Moreover, using the forecasted patterns for indirect predictability of EPEs outperforms the reference score up to ∼10 days lead time for many locations. For high orography locations or coastal areas in particular, like parts of western Turkey, western Balkans, Iberian Peninsula, and Morocco, this limit extends to 11–14 days lead time. This study demonstrates that the connections between localized EPEs and large‐scale patterns over the Mediterranean extend the forecasting horizon of the model by over 3 days in many locations, in comparison with forecasting based on the predicted precipitation. Thus, it is beneficial to use the predicted patterns rather than the predicted precipitation at longer lead times for EPE forecasting. The model's performance is also assessed from a user perspective, showing that the EPE forecasting based on the patterns increases the economic benefits at medium/extended range lead times. Such information could support higher confidence in the decision‐making of various users; for example, the agricultural sector and (re)insurance companies.

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Stochastic ensemble climate forecast with an analogue model

Cited by 20 publications

References 35 publications

Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation

Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation

Simulation of extreme heat waves with empirical importance sampling

What do large‐scale patterns teach us about extreme precipitation over the Mediterranean at medium‐ and extended‐range forecasts?

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