1,923 research outputs found
ENSEMBLES: a new multi-model ensemble for seasonal-to-annual predictions: Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs
No full textA new 46-year hindcast dataset for seasonal-to-annual ensemble predictions has been created using a multi-model ensemble of 5 state-of-the-art coupled atmosphere-ocean circulation models. The multi-model outperforms any of the single-models in forecasting tropical Pacific SSTs because of reduced RMS errors and enhanced ensemble dispersion at all lead-times. Systematic errors are considerably reduced over the previous generation (DEMETER). Probabilistic skill scores show higher skill for the new multi-model ensemble than for DEMETER in the 4–6 month forecast range. However, substantially improved models would be required to achieve strongly statistical significant skill increases. The combination of ENSEMBLES and DEMETER into a grand multi-model ensemble does not improve the forecast skill further. Annual-range hindcasts show anomaly correlation skill of ∼0.5 up to 14 months ahead. A wide range of output from the multi-model simulations is becoming publicly available and the international community is invited to explore the full scientific potential of these data
How to create an operational multi-model of seasonal forecasts?
No full textSeasonal forecasts of variables like near-surface temperature or precipitation are becoming increasingly important for a wide range of stakeholders. Due to the many possibilities of recalibrating, combining, and verifying ensemble forecasts, there are ambiguities of which methods are most suitable. To address this we compare approaches how to process and verify multi-model seasonal forecasts based on a scientific assessment performed within the framework of the EU Copernicus Climate Change Service (C3S) Quality Assurance for Multi-model Seasonal Forecast Products (QA4Seas) contract C3S 51 lot 3. Our results underpin the importance of processing raw ensemble forecasts differently depending on the final forecast product needed. While ensemble forecasts benefit a lot from bias correction using climate conserving recalibration, this is not the case for the intrinsically bias adjusted multi-category probability forecasts. The same applies for multi-model combination. In this paper, we apply simple, but effective, approaches for multi-model combination of both forecast formats. Further, based on existing literature we recommend to use proper scoring rules like a sample version of the continuous ranked probability score and the ranked probability score for the verification of ensemble forecasts and multi-category probability forecasts, respectively. For a detailed global visualization of calibration as well as bias and dispersion errors, using the Chi-square decomposition of rank histograms proved to be appropriate for the analysis performed within QA4Seas.The research leading to these results is part of the Copernicus Climate Change Service (C3S) (Framework Agreement number C3S_51_Lot3_BSC), a program being implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission. Francisco Doblas-Reyes acknowledges the support by the H2020 EUCP project (GA 776613) and the MINECO-funded CLINSA project (CGL2017-85791-R). Further, the authors thank Nicolau Manubens and Alasdair Hunter for the valuable technical support, Eduardo Penabad for the support on data supply, as well as all other QA4Seas colleagues. Last but not least, we are grateful to the two anonymous reviewers for their helpful comments.Peer Reviewe
Influence of climate variability on European agriculture-analysis of winter wheat production
No full textInternational audienceEuropean agricultural production is influenced by the space-time distribution of regional climate. Because regional distributions of temperature and precipitation in Europe are affected by changes in the wintertime atmospheric circulation, this paper aims at identifying the relationships between the wintertime Euro-Atlantic variability and wheat yield for the Member States ofthe European Union. An empirical orthogonal function (EOF) decomposition of the 500 hPa geopotential height fields is used to describe the wintertime climate variability, associating the leading 4 components of the EOF decomposition into known climatic patterns (such as North Atlantic Oscillation or Eastern Atlantic patterns). Using statistical methods such as ANOVA, linear regression and ‘leave-one-out’ cross-validation, those patterns are related to time series of wheat yield anomalies. It is shown that, depending on the country, there is a link between wheat yield and modes of winter climate variability, and this link differs from the relationship between temperature and precipitation with the modes. Looking ahead to the improvement of seasonal climate forecasts, it is expected that such meteorological patterns may be predicted with some accuracy, which in turn could improve cropyield forecasts
81 fJ/bit energy-to-data ratio of 850 nm vertical-cavity surface-emitting lasers for optical interconnects
No full textThis article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Appl. Phys. Lett. 98, 231106 (2011) and may be found at https://doi.org/10.1063/1.3597799.Extremely energy-efficient oxide-confined high-speed 850 nm vertical-cavity surface-emitting lasers for optical interconnects are presented. Error-free performance at 17 and 25 Gb/s via a 100 m multimode fiber link is demonstrated at record high dissipation-power-efficiencies of up to 69 fJ/bit (<0.1mW/Gbps) and 99 fJ/bit, respectively. These are the most power efficient high-speed directly modulated light sources reported to date. The total energy-to-data ratio is 83 fJ/bit at 25°C and reduces to 81 fJ/bit at 55°C. These results were obtained without adjustment of driving conditions. A high -factor of 12.0GHz/(mA)0.5 and a -factor of 0.41 ns are measured.EC/FP7/224211/EU/VISIT - Vertically Integrated Systems for Information Transfer/VISITDFG, 43659573, SFB 787: Halbleiter - Nanophotonik: Materialien, Modelle, Bauelement
Single-drive high-speed lumped depletion-type modulators toward 10 fJ/bit energy consumption
No full textReduction of modulator energy consumption to 10 fJ/bit is essential for the sustainable development of communication systems. Lumped modulators might be a viable solution if instructed by a complete theory system. Here, we present a complete analytical electro-optic response theory, energy consumption analysis, and eye diagrams on absolute scales for lumped modulators. Consequently the speed limitation is understood and alleviated by single-drive configuration, and comprehensive knowledge into the energy dependence on structural parameters significantly reduces energy consumption. The results show that silicon modulation energy as low as 80.8 and 21.5 fJ/bit can be achieved at 28 Gbd under 50 and 10 Omega impedance drivers, respectively. A 50 Gbd modulation is also shown to be possible. The analytical models can be extended to lumped modulators on other material platforms and offer a promising solution to the current challenges of modulation energy reduction. (C) 2017 Chinese Laser PressNational Natural Science Foundation of China (NSFC) [61120106012]SCI(E)ARTICLE2134-142
The rationale behind the success of multi-model ensembles in seasonal forecasting - I. Basic concept
No full textProbabilistic prediction of climate using multi-model ensembles: from basics to applications.
No full textThe development of multi-model ensembles for reliable predictions of inter-annual climate fluctuations and climate change, and their application to health, agronomy and water management, are discussed
The rationale behind the success of multi-model ensembles in seasonal forecasting - II. Calibration and combination
No full textPeroxisome proliferator-activated receptor-gamma2-Pro12Ala and endothelial nitric oxide synthase-4a/b gene polymorphisms are associated with essential hypertension
No full textObjective Peroxisome proliferator-activated receptor-gamma2 (PPARgamma2) belongs to the family of the nuclear hormone receptors and has been recently implicated in vascular biology. PPARgamma2(Pro12Ala) gene polymorphism is associated with obesity, body mass index and diabetes mellitus. The endothelial nitric oxide synthase (eNOS) (4a/b) gene polymorphism contributes to coronary heart disease and hypertension risk. We tested whether both polymorphic variants were associated with hypertension risk, and their inter-relationship with plasma homocysteine.Design A case-control study was conducted selecting 235 subjects with arterial hypertension and 223 normotensive matched controls.Methods Genotyping for the PPARgamma2(Pro12Ala) and the eNOS(4a/b) were performed by mutagenically separated polymerase chain reaction and by polymerase chain reaction. Glucose, lipid profile, plasma creatinine, homocysteine and microalbuminuria were measured.Results We found a significant contribution of the PPARgamma2(Pro12Ala) and eNOS(4a/b) gene polymorphisms to hypertensive risk in our population (odds ratio, 1.9 and 1.6, respectively), confirmed by multiple logistic regression analysis. Those subjects with normal plasma homocysteine values had an increased hypertensive risk with an odds ratio of 2.6 for the PP genotype of the PPARgamma2 gene and an odds ratio of 1.8 for the a allele of the eNOS gene.Conclusions Both analyzed polymorphisms were associated in a synergistic manner with hypertension. This effect manifested only in those subjects with normal homocysteine plasma values. Our findings suggest complex genotype-environmental interactions on hypertensive risk.1655164973,572Q1SCI
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