Multi-year prediction of European summer drought conditions for the agricultural sector

Solaraju-Murali, Balakrishnan; Caron, Louis-Philippe; González-Reviriego, Nube; Doblas‐Reyes, Francisco J.

doi:10.1088/1748-9326/ab5043

Cited by 36 publications

(24 citation statements)

References 71 publications

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“…Prediction of climate up to ten years into the future, so-called decadal climate prediction, has received considerable scientific attention due to its potentially high impact on society (Yeager & Robson 2017, Solaraju-Murali et al 2019, Meehl et al 2021. On this time scale, the influence of chaotic internal climate variability and the response to external forcing strongly overlap (Lehner et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Skillful decadal prediction of unforced southern European summer temperature variations

Borchert¹,

Koul²,

Menary³

et al. 2022

Preprint

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We assess the capability of decadal prediction simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) archive to predict European summer temperature during the period 1970-2014. Using a multi-model ensemble average from 8 decadal prediction systems, we show that European summer temperatures are highly predictable for up to 10 years in CMIP6. Much of this predictive capability, or skill, is related to the externally forced response. Prediction skill for the unforced signal of European summer temperature is low. A link between unforced Southern European summer temperature and preceding spring Eastern North Atlantic - Mediterranean sea surface temperature (SST) observed during the period 1900-1969 motivates the application of a dynamical-statistical model to overcome the low summer temperature skill over Europe. This dynamical-statistical model uses dynamical spring SST predictions to predict European summer temperature. Our model significantly increases decadal prediction skill of unforced European summer temperature variations: Unlike purely dynamical predictions, the dynamical-statistical model shows significant prediction skill for unforced Southern European summer temperature 2-9 years ahead. Our results highlight that dynamical-statistical models can serve to benefit the decadal prediction of variables with initially limited skill beyond the forcing, such as summer temperature over Europe.

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Section: Introductionmentioning

confidence: 99%

Skillful decadal prediction of unforced southern European summer temperature variations

Borchert¹,

Koul²,

Menary³

et al. 2022

Preprint

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show abstract

“…Interest in seasonal to decadal climate predictions has grown in recent years due to their potential to provide relevant climate information for decision-making in different socio-economic sectors (e.g. Suckling, 2018;Solaraju-Murali et al, 2019;Merryfield et al, 2020). Scientifically, climate predictions have provided novel ways of evaluating and comparing climate simulations with observations and improve our understanding of the intrinsic predictability of the climate system, including the key mechanisms operating at interannual to decadal timescales.…”

Section: Introductionmentioning

confidence: 99%

Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth

et al. 2021

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Abstract. In this paper, we present and evaluate the skill of an EC-Earth3.3 decadal prediction system contributing to the Decadal Climate Prediction Project – Component A (DCPP-A). This prediction system is capable of skilfully simulating past global mean surface temperature variations at interannual and decadal forecast times as well as the local surface temperature in regions such as the tropical Atlantic, the Indian Ocean and most of the continental areas, although most of the skill comes from the representation of the external radiative forcings. A benefit of initialization in the predictive skill is evident in some areas of the tropical Pacific and North Atlantic oceans in the first forecast years, an added value that is mostly confined to the south-east tropical Pacific and the eastern subpolar North Atlantic at the longest forecast times (6–10 years). The central subpolar North Atlantic shows poor predictive skill and a detrimental effect of initialization that leads to a quick collapse in Labrador Sea convection, followed by a weakening of the Atlantic Meridional Overturning Circulation (AMOC) and excessive local sea ice growth. The shutdown in Labrador Sea convection responds to a gradual increase in the local density stratification in the first years of the forecast, ultimately related to the different paces at which surface and subsurface temperature and salinity drift towards their preferred mean state. This transition happens rapidly at the surface and more slowly in the subsurface, where, by the 10th forecast year, the model is still far from the typical mean states in the corresponding ensemble of historical simulations with EC-Earth3. Thus, our study highlights the Labrador Sea as a region that can be sensitive to full-field initialization and hamper the final prediction skill, a problem that can be alleviated by improving the regional model biases through model development and by identifying more optimal initialization strategies.

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“…Simulations with EC-Earth2 contributed to the CMIP5 archive, and numerous studies performed with the EC-Earth model appeared in peer-reviewed literature and contributed to the Fifth Assessment Report (AR5) of the IPCC (Intergovernmental Panel on Climate Change) (IPCC, 2013). EC-Earth is used in a wide range of studies from paleo-research to climate projections, including also seasonal (Bellprat et al, 2016;Prodhomme et al, 2016;Haarsma et al, 2019) and decadal forecasts (Guemas et al, 2013(Guemas et al, , 2015Doblas-Reyes et al, 2013;Caron et al, 2014;Solaraju Murali et al, 2019;Koenigk et al, 2013;Koenigk and Brodeau, 2014;Brodeau and Koenigk, 2016).…”

Section: Introductionmentioning

confidence: 99%

HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR – description, model computational performance and basic validation

et al. 2020

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Abstract. A new global high-resolution coupled climate model, EC-Earth3P-HR has been developed by the EC-Earth consortium, with a resolution of approximately 40 km for the atmosphere and 0.25∘ for the ocean, alongside with a standard-resolution version of the model, EC-Earth3P (80 km atmosphere, 1.0∘ ocean). The model forcing and simulations follow the High Resolution Model Intercomparison Project (HighResMIP) protocol. According to this protocol, all simulations are made with both high and standard resolutions. The model has been optimized with respect to scalability, performance, data storage and post-processing. In accordance with the HighResMIP protocol, no specific tuning for the high-resolution version has been applied. Increasing horizontal resolution does not result in a general reduction of biases and overall improvement of the variability, and deteriorating impacts can be detected for specific regions and phenomena such as some Euro-Atlantic weather regimes, whereas others such as the El Niño–Southern Oscillation show a clear improvement in their spatial structure. The omission of specific tuning might be responsible for this. The shortness of the spin-up, as prescribed by the HighResMIP protocol, prevented the model from reaching equilibrium. The trend in the control and historical simulations, however, appeared to be similar, resulting in a warming trend, obtained by subtracting the control from the historical simulation, close to the observational one.

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Multi-year prediction of European summer drought conditions for the agricultural sector

Cited by 36 publications

References 71 publications

Skillful decadal prediction of unforced southern European summer temperature variations

Skillful decadal prediction of unforced southern European summer temperature variations

Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth

HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR – description, model computational performance and basic validation

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