Improving weather and climate predictions by training of supermodels

Recent studies demonstrate that weather and climate predictions potentially improve by dynamically combining different models into a so-called "supermodel". Here, we focus on the weighted supermodel - the supermodel's time derivative is a weighted superposition of the time derivatives of the imperfect models, referred to as weighted supermodeling. A crucial step is to train the weights of the supermodel on the basis of historical observations. Here, we apply two different training methods to a supermodel of up to four different versions of the global atmosphere-ocean-land model SPEEDO. The standard version is regarded as truth. The first training method is based on an idea called cross pollination in time (CPT), where models exchange states during the training. The second method is a synchronization-based learning rule, originally developed for parameter estimation. We demonstrate that both training methods yield climate simulations and weather predictions of superior quality as compared to the individual model versions. Supermodel predictions also outperform predictions based on the commonly used multi-model ensemble (MME) mean. Furthermore, we find evidence that negative weights can improve predictions in cases where model errors do not cancel (for instance, all models are warm with respect to the truth). In principle, the proposed training schemes are applicable to state-of-the-art models and historical observations. A prime advantage of the proposed training schemes is that in the present context relatively short training periods suffice to find good solutions. Additional work needs to be done to assess the limitations due to incomplete and noisy data, to combine models that are structurally different (different resolution and state representation, for instance) and to evaluate cases for which the truth falls outside of the model class

A study on the forecast quality of the mediterranean cyclones

Comunicación presentada en: 4th Plinius Conference on Mediterranean Storms celebrada del 2 al 4 de octubre de 2002 en Palma de Mallorca.The main general objective of MEDEX is stated to be the improvement of knowledge and forecasting of cyclones that produce high impact weather in the Mediterranean area. So, for this scope one of the intermediate goals of the project concerns the development of an objective method to evaluate the quality of the forecast of the cyclones. The topic of the present study is to investigate the cyclone's forecast errors in that area and to propose an objective methodology to quantify them. An investigation on the performance of the HIRLAM(INM)-0.5 model in the forecast of cyclonic centres has been done. Databases of analysed and forecasted cyclones for the Western Mediterranean have been used in this study. The "distance" between the analysed and forecasted cyclone has been measured calculating the differences in the value of the parameters chosen to describe them at the sea level surface. Results on the characteristics of the errors are shown. An index constructed by means of these differences has been introduced to evaluate the ability of the model forecasting cyclones, and to quantify it. From this index, two others indexes have been derived in order to discriminate if the forecast has overestimated or underestimated some magnitudes in the description of the cyclone. Three different time forecast ranges, H+12,H+24 and H+48, have been considered to investigate temporal trend in their quality. Finally, to check this methodology, it has been applied to some MEDEX cases

LCA assessment related to the evolution of the earthquake performance of a strategic structure

Several buildings and infrastructures, located in urban areas, are identified as strategic in the case of an earthquake event. This is the case of a water treatment plant which is currently built in Genoa, Italy, and which has been assessed for the scope of this research. Since the structure has been designed following the seismic design prescriptions, this work aims to provide a preliminary assessment of how the degradation mechanisms do affect its earthquake response. To this purpose, both chloride attack and carbonation are taken into account as main degradation mechanisms. Moreover, due to the importance of the water treatment plant, to develop a realistic Life Cycle Assessment (LCA) analysis, the earthquake resistance of the structure and its evolution over time as a function of the aforesaid degradation mechanisms, have been accounted as Serviceability Limit State to estimate the frequency of the maintenance activities needed in a timeframe of 100 years

DADA: data assimilation for the detection and attribution of weather and climate-related events

A new nudging method for data assimilation, delay‐coordinate nudging, is presented. Delay‐coordinate nudging makes explicit use of present and past observations in the formulation of the forcing driving the model evolution at each time step. Numerical experiments with a low‐order chaotic system show that the new method systematically outperforms standard nudging in different model and observational scenarios, also when using an unoptimized formulation of the delay‐nudging coefficients. A connection between the optimal delay and the dominant Lyapunov exponent of the dynamics is found based on heuristic arguments and is confirmed by the numerical results, providing a guideline for the practical implementation of the algorithm. Delay‐coordinate nudging preserves the easiness of implementation, the intuitive functioning and the reduced computational cost of the standard nudging, making it a potential alternative especially in the field of seasonal‐to‐decadal predictions with large Earth system models that limit the use of more sophisticated data assimilation procedures

Machine learning for earth system observation and prediction

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Supermodeling Improving Predictions with an Ensemble of Interacting Models

The modeling of weather and climate has been a success story. The skill of forecasts continues to improve and model biases continue to decrease. Combining the output of multiple models has further improved forecast skill and reduced biases. But are we exploiting the full capacity of state-of-the-art models in making forecasts and projections? Supermodeling is a recent step forward in the multimodel ensemble approach. Instead of combining model output after the simulations are completed, in a supermodel individual models exchange state information as they run, influencing each other's behavior. By learning the optimal parameters that determine how models influence each other based on past observations, model errors are reduced at an early stage before they propagate into larger scales and affect other regions and variables. The models synchronize on a common solution that through learning remains closer to the observed evolution. Effectively a new dynamical system has been created, a supermodel, that optimally combines the strengths of the constituent models. The supermodel approach has the potential to rapidly improve current state-of-the-art weather forecasts and climate predictions. In this paper we introduce supermodeling, demonstrate its potential in examples of various complexity, and discuss learning strategies. We conclude with a discussion of remaining challenges for a successful application of supermodeling in the context of state-of-the-art models. The supermodeling approach is not limited to the modeling of weather and climate, but can be applied to improve the prediction capabilities of any complex system, for which a set of different models exists

Recent progress in understanding and predicting Atlantic decadal climate variability

Recent Atlantic climate prediction studies are an exciting new contribution to an extensive body of research on Atlantic decadal variability and predictability that has long emphasized the unique role of the Atlantic Ocean in modulating the surface climate. We present a survey of the foundations and frontiers in our understanding of Atlantic variability mechanisms, the role of the Atlantic Meridional Overturning Circulation (AMOC), and our present capacity for putting that understanding into practice in actual climate prediction systems

Consensus Report : 2nd European Workshop on Tobacco Use Prevention and Cessation for Oral Health Professionals

Tobacco use has been identified as a major risk factor for oral disorders such as cancer and periodontal disease. Tobacco use cessation (TUC) is associated with the potential for reversal of precancer, enhanced outcomes following periodontal treatment, and better periodontal status compared to patients who continue to smoke. Consequently, helping tobacco users to quit has become a part of both the responsibility of oral health professionals and the general practice of dentistry. TUC should consist of behavioural support, and if accompanied by pharmacotherapy, is more likely to be successful. It is widely accepted that appropriate compensation of TUC counselling would give oral health professionals greater incentives to provide these measures. Therefore, TUC-related compensation should be made accessible to all dental professionals and be in appropriate relation to other therapeutic interventions. International and national associations for oral health professionals are urged to act as advocates to promote population, community and individual initiatives in support of tobacco use prevention and cessation (TUPAC) counselling, including integration in undergraduate and graduate dental curricula. In order to facilitate the adoption of TUPAC strategies by oral health professionals, we propose a level of care model which includes 1) basic care: brief interventions for all patients in the dental practice to identify tobacco users, assess readiness to quit, and request permission to re-address at a subsequent visit, 2) intermediate care: interventions consisting of (brief) motivational interviewing sessions to build on readiness to quit, enlist resources to support change, and to include cessation medications, and 3) advanced care: intensive interventions to develop a detailed quit plan including the use of suitable pharmacotherapy. To ensure that the delivery of effective TUC becomes part of standard care, continuing education courses and updates should be implemented and offered to all oral health professionals on a regular basis

Electron Polarization Operators

Two types of electron polarization operators are surveyed. A three- vector operator is described that is appropriate for calculations involving plane- wave states. A four-vector operator is described that can be used for taking account of external electromagnetic fields. (T.F.H.

Introduction to the special issue on the statistical mechanics of climate

We introduce the special issue on the Statistical Mechanics of Climate by presenting an informal discussion of some theoretical aspects of climate dynamics that make it a topic of great interest for mathematicians and theoretical physicists. In particular, we briefly discuss its nonequilibrium and multiscale properties, the relationship between natural climate variability and climate change, the different regimes of climate response to perturbations, and critical transitions