Invited perspectives: The ECMWF strategy 2021–2030 Challenges in
the area of natural hazards

Pappenberger, Florian; Rabier, Florence; Venuti, Fabio

doi:10.5194/nhess-2021-33

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…At present, hindcast datasets are available for download and need to be pre‐processed, which can be a time‐consuming process. An open workflow as presented in this paper would benefit from having large volumes of data such as the SEAS5 hindcast accessible on‐demand via a cloud‐based service (Pappenberger et al, 2021; Wagemann et al, 2018). An example of a cloud service for the meteorological and climate community, which in the future may be incorporated in the UNSEEN‐open workflow to obviate retrieval of data, is the European Weather Cloud (Pappenberger & Palkovic, 2020).…”

Section: Discussionmentioning

confidence: 99%

An open workflow to gain insights about low‐likelihood high‐impact weather events from initialized predictions

Kelder

Marjoribanks²,

Slater

et al. 2022

Meteorological Applications

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Low-likelihood weather events can cause dramatic impacts, especially when they are unprecedented. In 2020, amongst other high-impact weather events, UK floods caused more than £300 million damage, prolonged heat over Siberia led to infrastructure failure and permafrost thawing, while wildfires ravaged California. Such rare phenomena cannot be studied well from historical records or reanalysis data. One way to improve our awareness is to exploit ensemble prediction systems, which represent large samples of simulated weather events. This 'UNSEEN' method has been successfully applied in several scientific studies, but uptake is hindered by large data and processing requirements, and by uncertainty regarding the credibility of the simulations.Here, we provide a protocol to apply and ensure credibility of UNSEEN for studying low-likelihood high-impact weather events globally, including an open workflow based on Copernicus Climate Change Services (C3S) seasonal predictions. Demonstrating the workflow using European Centre for Medium-Range Weather Forecasts (ECMWF) SEAS5, we find that the 2020 March-May Siberian heatwave was predicted by one of the ensemble members; and that the record-shattering August 2020 California-Mexico temperatures were part of a strong increasing trend. However, each of the case studies exposes challenges with respect to the credibility of UNSEEN and the sensitivity of the outcomes to user decisions. We conclude that UNSEEN can provide new insights about low-likelihood weather events when the decisions are transparent, and the challenges and sensitivities are acknowledged. Anticipating plausible lowlikelihood extreme events and uncovering unforeseen hazards under a changing climate warrants further research at the science-policy interface to manage high impacts.

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Section: Discussionmentioning

confidence: 99%

An open workflow to gain insights about low‐likelihood high‐impact weather events from initialized predictions

Kelder

Marjoribanks²,

Slater

et al. 2022

Meteorological Applications

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“…(2019; 2020). Coupling with hydrology is of high interest for consistent NWP and environmental forecasts activities, and coupled DA will further enhance capabilities for natural hazards prediction (Pappenberger et al ., 2021).…”

Section: Future Plansmentioning

confidence: 99%

Coupled data assimilation at ECMWF: current status, challenges and future developments

Rosnay

Browne

Boisséson

et al. 2022

Quart J Royal Meteoro Soc

Self Cite

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This article presents coupled data assimilation (DA) activities at the European Centre for Medium‐Range Weather Forecasts (ECMWF). Coupled DA is an essential component of the ECMWF Earth‐system strategy. It aims at providing consistent initial conditions to the coupled atmosphere, land, and ocean forecast model. The article introduces the different DA systems and observing systems for each Earth‐system component. It discusses challenges related to observation consistency, availability, and sustainability across the components. It gives a review of coupling methodologies and presents coupling methods in development at the ECMWF. The current ECMWF system relies on weakly coupled DA approaches between land and atmosphere, between wave and atmosphere, and between ocean and atmosphere. Research on coupled DA has been centred on outer loop coupling developments and evaluation, focused on ocean–atmosphere coupling for reanalysis and for numerical weather prediction. The latest configuration of the ocean–atmosphere outer loop coupling combines weak and outer loop coupling methods. The article discusses the challenges in assimilating surface‐sensitive observations and it presents opportunities that coupled DA offers to enhance the exploitation of interface observations. It presents recent developments on land–atmosphere forward operator coupling and multilayer snow‐emission modelling and shows the potential for coupled radiative transfer modelling at low‐frequency passive microwave. The article discusses ongoing developments of in‐house sea‐surface temperature analysis based on coupled skin temperature assimilation. It presents preliminary results that demonstrate meaningful upper ocean temperature increments when assimilating skin temperature information from four‐dimensional variational assimilation. Coupled assimilation results are illustrated and discussed in the context of several applications related to reanalysis, scatterometer impact on coupled ocean–atmosphere, tropical cyclone, impact of weakly coupled sea‐ice–atmosphere data assimilation as well as land surface coupled DA case studies. These examples illustrate benefits and challenges of coupled DA developments. The article discusses future plans of coupled DA developments in support of ECMWF's Earth‐system 2021–2030 strategy.

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“…At present, hindcast datasets are available for download and need to be pre-processed, which can be a timeconsuming process. An open workflow as presented in this paper would benefit from having large volumes of data such as the SEAS5 hindcast accessible on-demand via a cloud-based service (Pappenberger et al, 2021;Wagemann et al, 2018). An example of a cloud service for the meteorological and climate community, that in the future may be incorporated in the UNSEEN-open workflow to obviate retrieval of data, is the European Weather Cloud (Pappenberger and Palkovic, 2020).…”

Section: Practicalities Of the Unseen-open Workflowmentioning

confidence: 99%

An open workflow for the study of unseen weather extremes

Kelder¹,

Marjoribanks²,

Slater³

et al. 2021

Preprint

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Ensemble members from weather and climate predictions can be used to generate large samples of simulated weather events, allowing the estimation of extreme (hitherto unseen) events. Here, we provide a protocol and open workflow for applying the ‘UNSEEN’ method for hydro-climatic extremes globally, based on Copernicus Climate Change Services (C3S) seasonal predictions but also considering other compatible modelling systems. We discuss common challenges and potential solutions using three examples of extreme events that caused severe damage in 2020 (extreme rainfall, heat, and wildfire danger). These case studies demonstrate the potential of the method to inform decision-making with maximum credible events used for stress-testing adaptation measures and to anticipate unprecedented extremes in a changing climate. As such, this paper may be used to guide the generation of large ensembles that are a credible resource for evaluating otherwise unforeseen hydro-climatic risks.

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Invited perspectives: The ECMWF strategy 2021–2030 Challenges in the area of natural hazards

Cited by 4 publications

References 6 publications

An open workflow to gain insights about low‐likelihood high‐impact weather events from initialized predictions

An open workflow to gain insights about low‐likelihood high‐impact weather events from initialized predictions

Coupled data assimilation at ECMWF: current status, challenges and future developments

An open workflow for the study of unseen weather extremes

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