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  • 1
    Publication Date: 2013-04-30
    Print ISSN: 0930-7575
    Electronic ISSN: 1432-0894
    Topics: Geosciences , Physics
    Published by Springer
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  • 2
    Publication Date: 2021-02-11
    Description: 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.
    Print ISSN: 2190-4979
    Electronic ISSN: 2190-4987
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 3
    Publication Date: 2016-10-04
    Description: The Year of Polar Prediction (YOPP) is planned for mid-2017 to mid-2019, centred on 2018. Its goal is to enable a significant improvement in environmental prediction capabilities for the polar regions and beyond, by coordinating a period of intensive observing, modelling, prediction, verification, user-engagement and education activities. With a focus on time scales from hours to a season, YOPP is a major initiative of the World Meteorological Organization’s World Weather Research Programme (WWRP) and a key component of the Polar Prediction Project (PPP). YOPP is being planned and coordinated by the PPP Steering Group together with representatives from partners and other initiatives, including the World Climate Research Programme’s Polar Climate Predictability Initiative (PCPI). The objectives of YOPP are to: 1. Improve the existing polar observing system (enhanced coverage, higher-quality observations). 2. Gather additional observations through field programmes aimed at improving understanding of key polar processes. 3. Develop improved representation of key polar processes in (un)coupled models used for prediction. 4. Develop improved (coupled) data assimilation systems accounting for challenges in the polar regions such as sparseness of observational data. 5. Explore the predictability of the atmosphere-cryosphere-ocean system, with a focus on sea ice, on time scales from hours to a season. 6. Improve understanding of linkages between polar regions and lower latitudes, assess skill of models representing these linkages, and determine the impact of improved polar prediction on forecast skill in lower latitudes. 7. Improve verification of polar weather and environmental predictions to obtain better quantitative knowledge on model performance, and on the skill, especially for user- relevant parameters. 8. Identify various stakeholders and establish their decisionmaking needs with respect to weather, climate, ice, and related environmental services. 9. Assess the costs and benefits of using predictive information for a spectrum of users and services. 10. Provide training opportunities to generate a sound knowledge base (and its transfer across generations) on polar prediction related issues. YOPP is implemented in three distinct phases. During the YOPP Preparation Phase (2013 through to mid-2017) this Implementation Plan was developed, which includes key outcomes of consultations with partners at the YOPP Summit in July 2015. Plans will be further developed and refined through focused international workshops. There will be engagement with stakeholders and arrangement of funding, coordination of observations and modelling activities, and preparatory research. During the YOPP Core Phase (mid-2017 to mid-2019), four elements will be staged: intensive observing periods for both hemispheres, a complementary intensive modelling and prediction period, a period of enhanced monitoring of forecast use in decisionmaking including verification, and a special educational effort. Finally, during the YOPP Consolidation Phase (mid-2019 to 2022) the legacy of data, science and publications will be organized. The WWRP-PPP Steering Group provides endorsement throughout the YOPP phases for projects that contribute to YOPP. This process facilitates coordination and enhances visibility, communication, and networking.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Miscellaneous , notRev
    Format: application/pdf
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