122,834 research outputs found
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Linking the anomaly initialization approach to the mapping paradigm: a proof-of-concept study
No full textSeasonal-to-decadal predictions are initialized using observations of the present climatic state in full field initialization (FFI). Such model integrations undergo a drift toward the model attractor due to model deficiencies that incur a bias in the model. The anomaly initialization (AI) approach reduces the drift by adding an estimate of the bias onto the observations at the expense of a larger initial error.
In this study FFI is associated with the fidelity paradigm, and AI is associated with an instance of the mapping paradigm, in which the initial conditions are mapped onto the imperfect model attractor by adding a fixed error term; the mapped state on the model attractor should correspond to the nature state. Two diagnosis tools assess how well AI conforms to its own paradigm under various circumstances of model error: the degree of approximation of the model attractor is measured by calculating the overlap of the AI initial conditions PDF with the model PDF; and the sensitivity to random error in the initial conditions reveals how well the selected initial conditions on the model attractor correspond to the nature states. As a useful reference, the initial conditions of FFI are subjected to the same analysis.
Conducting hindcast experiments using a hierarchy of low-order coupled climate models, it is shown that the initial conditions generated using AI approximate the model attractor only under certain conditions: differences in higher-than-first-order moments between the model and nature PDFs must be negligible. Where such conditions fail, FFI is likely to perform better
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Reliability of regional climate model trends
No full textA necessary condition for a good probabilistic forecast is that the forecast system is shown to be reliable: forecast probabilities should equal observed probabilities verified over a large number of cases. As climate change trends are now emerging from the natural variability, we can apply this concept to climate predictions and compute the reliability of simulated local and regional temperature and precipitation trends (1950–2011) in a recent multi-model ensemble of climate model simulations prepared for the Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5). With only a single verification time, the verification is over the spatial dimension. The local temperature trends appear to be reliable. However, when the global mean climate response is factored out, the ensemble is overconfident: the observed trend is outside the range of modelled trends in many more regions than would be expected by the model estimate of natural variability and model spread. Precipitation trends are overconfident for all trend definitions. This implies that for near-term local climate forecasts the CMIP5 ensemble cannot simply be used as a reliable probabilistic forecast
Full-field and anomaly initialization using a low-order climate model: A comparison and proposals for advanced formulations
No full textInitialization techniques for seasonal-to-decadal climate predictions fall into two main categories; namely full-field initialization (FFI) and anomaly initialization (AI). In the FFI case the initial model state is replaced by the best possible available estimate of the real state. By doing so the initial error is efficiently reduced but, due to the unavoidable presence of model deficiencies, once the model is let free to run a prediction, its trajectory drifts away from the observations no matter how small the initial error is. This problem is partly overcome with AI where the aim is to forecast future anomalies by assimilating observed anomalies on an estimate of the model climate. The large variety of experimental setups, models and observational networks adopted worldwide make it difficult to draw firm conclusions on the respective advantages and drawbacks of FFI and AI, or to identify distinctive lines for improvement. The lack of a unified mathematical framework adds an additional difficulty toward the design of adequate initialization strategies that fit the desired forecast horizon, observational network and model at hand. Here we compare FFI and AI using a low-order climate model of nine ordinary differential equations and use the notation and concepts of data assimilation theory to highlight their error scaling properties. This analysis suggests better performances using FFI when a good observational network is available and reveals the direct relation of its skill with the observational accuracy. The skill of AI appears, however, mostly related to the model quality and clear increases of skill can only be expected in coincidence with model upgrades. We have compared FFI and AI in experiments in which either the full system or the atmosphere and ocean were independently initialized. In the former case FFI shows better and longer-lasting improvements, with skillful predictions until month 30. In the initialization of single compartments, the best performance is obtained when the stabler component of the model (the ocean) is initialized, but with FFI it is possible to have some predictive skill even when the most unstable compartment (the extratropical atmosphere) is observed. Two advanced formulations, least-square initialization (LSI) and exploring parameter uncertainty (EPU), are introduced. Using LSI the initialization makes use of model statistics to propagate information from observation locations to the entire model domain. Numerical results show that LSI improves the performance of FFI in all the situations when only a portion of the system's state is observed. EPU is an online drift correction method in which the drift caused by the parametric error is estimated using a short-time evolution law and is then removed during the forecast run. Its implementation in conjunction with FFI allows us to improve the prediction skill within the first forecast year. Finally, the application of these results in the context of realistic climate models is discussed. © Author(s) 2014. CC Attribution 3.0 License
Towards reliable extreme weather and climate event attribution
No full textClimate change is shaping extreme heat and rain. To what degree human activity has increased the risk of high impact events is of high public concern and still heavily debated. Recent studies attributed single extreme events to climate change by comparing climate model experiments where the influence of an external driver can be included or artificially suppressed. Many of these results however did not properly account for model errors in simulating the probabilities of extreme event occurrences. Here we show, exploiting advanced correction techniques from the weather forecasting field, that correcting properly for model probabilities alters the attributable risk of extreme events to climate change. This study illustrates the need to correct for this type of model error in order to provide trustworthy assessments of climate change impacts.This work has been supported by the EUropean CLimate and weather Events: Interpretation and Attribution (EUCLEIA) project, funded by the European Union’s Seventh Framework Programme [FP7/2007–2013] under Grant agreement no. 607085 as well as the Horizon 2020 EUCP EUropean Climate Prediction system under Grant agreement no. 776613 and by the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 grant reference RYC-2017-22964. We thank Antje Weisheimer and Tim Palmer from the University of Oxford for their support to conduct this research. We are further indepted to Fraser Lott, Jonas Bhend, Stefan Siegert, Karsten Haustein, and Myles Allen for their help on the analysis and interpretation. O. Bellprat is the corresponding author ([email protected]) and carried out the core analysis and writing of the paper. V. Guemas, F. Doblas-Reyes, and M. Donat have all either contributed in the study design or the interpretation of the analysis as well as the writing of the paperPeer Reviewe
Towards reliable extreme weather and climate event attribution
No full textClimate change is shaping extreme heat and rain. To what degree human activity has increased the risk of high impact events is of high public concern and still heavily debated. Recent studies attributed single extreme events to climate change by comparing climate model experiments where the influence of an external driver can be included or artificially suppressed. Many of these results however did not properly account for model errors in simulating the probabilities of extreme event occurrences. Here we show, exploiting advanced correction techniques from the weather forecasting field, that correcting properly for model probabilities alters the attributable risk of extreme events to climate change. This study illustrates the need to correct for this type of model error in order to provide trustworthy assessments of climate change impacts.This work has been supported by the EUropean CLimate and weather Events: Interpretation and Attribution (EUCLEIA) project, funded by the European Union’s Seventh Framework Programme [FP7/2007–2013] under Grant agreement no. 607085 as well as the Horizon 2020 EUCP EUropean Climate Prediction system under Grant agreement no. 776613 and by the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 grant reference RYC-2017-22964. We thank Antje Weisheimer and Tim Palmer from the University of Oxford for their support to conduct this research. We are further indepted to Fraser Lott, Jonas Bhend, Stefan Siegert, Karsten Haustein, and Myles Allen for their help on the analysis and interpretation. O. Bellprat is the corresponding author ([email protected]) and carried out the core analysis and writing of the paper. V. Guemas, F. Doblas-Reyes, and M. Donat have all either contributed in the study design or the interpretation of the analysis as well as the writing of the paperPeer ReviewedPostprint (published version
The match between climate services demands and Earth System Models supplies
No full textEarth System Models (ESM) are key ingredients of many of the climate services that are currently being developed and delivered. However, ESMs have more applications than the provision of climate services, and similarly many climate services use more sources of information than ESMs. This discussion paper elaborates on dilemmas that are evident at the interface between ESMs and climate services, in particular: (a) purposes of the models versus service development, (b) gap between the spatial and temporal scales of the models versus the scales needed in applications, and (c) Tailoring climate model results to real-world applications. A continued and broad-minded dialogue between the ESM developers and climate services providers’ communities is needed to improve both the optimal use and direction of ESM development and climate service development. We put forward considerations to improve this dialogue between the communities developing ESMs and climate services, in order to increase the mutual benefit that enhanced understanding of prospects and limitations of ESMs and climate services will bring.This work and its contributors (B. van den Hurk, C. Hewitt, J. Bessembinder, F. Doblas-Reyes, R. Döscher) were funded by the
Horizon 2020 Framework Programme of the European Union: Project ref. 689029 (Climateurope project). The co-author and editor of the journal states that she was not involved in the review process of the
paper.Peer Reviewe
The match between climate services demands and Earth System Models supplies
No full textEarth System Models (ESM) are key ingredients of many of the climate services that are currently being developed and delivered. However, ESMs have more applications than the provision of climate services, and similarly many climate services use more sources of information than ESMs. This discussion paper elaborates on dilemmas that are evident at the interface between ESMs and climate services, in particular: (a) purposes of the models versus service development, (b) gap between the spatial and temporal scales of the models versus the scales needed in applications, and (c) Tailoring climate model results to real-world applications. A continued and broad-minded dialogue between the ESM developers and climate services providers’ communities is needed to improve both the optimal use and direction of ESM development and climate service development. We put forward considerations to improve this dialogue between the communities developing ESMs and climate services, in order to increase the mutual benefit that enhanced understanding of prospects and limitations of ESMs and climate services will bring.This work and its contributors (B. van den Hurk, C. Hewitt, J. Bessembinder, F. Doblas-Reyes, R. Döscher) were funded by the
Horizon 2020 Framework Programme of the European Union: Project ref. 689029 (Climateurope project). The co-author and editor of the journal states that she was not involved in the review process of the
paper.Peer ReviewedPostprint (published version
Sources of skill in near-term climate prediction: generating initial conditions
No full textThis study investigates the role of different areas of the ocean in driving the climate variability. The impact of both global and regional ocean nudging on the climate reconstruction obtained with the climate model EC-Earth v2.3 is studied over the period 1960–2012. Ocean temperature and salinity below the mixed layer are relaxed toward the monthly averages from the ORAS4 ocean reanalysis. Three coupled ocean–atmosphere simulations are considered: (1) global ocean nudging, (2) nudging in the global upper ocean (above 2000 m) and (3) nudging in the mid-latitude ocean and at full ocean depth. The experimental setup allows for identifying local and remote effects of nudging on different geographical areas. The validation is based on the correlation coefficients and the root mean square error skill score and concerns the following variables: ocean heat content, ocean barotropic streamfunction, intensity of the ocean gyres and indexes of convection, sea ice extension, near-surface air and sea surface temperature, and El Niño–Southern Oscillation 3.4 index. The results can be summarized as follows: (1) the positive impact on the reconstruction of the ocean state is found almost everywhere and for most of the analyzed variables, including unconstrained variables and/or regions, (2) deep-ocean nudging shows low impact on sea-surface temperature but a significant impact on the ocean circulation, (3) mid-latitude ocean nudging shows systematically the worst performance pointing at the importance of the poles and tropics in reconstructing the global ocean
Geografía elemental astronómica, física, política y descriptiva
No full textDatos del impresor: F. de los Reyes, traballou en Granada entre os anos 1884 e 189
Deforrnational processes in sorne dikes of the Tardi -Hercynian dike-cornplex of the Southwestern Montnegre batholith (<<Cordillera Litoral Costero-Catalana»)
No full textEn este trabajo, estudiamos las deformaciones de algunos diques del Complejo filoniano Tardi-Hercínico de la zona SW del batolito del Montnegre (Cordillera Litoral Costero-Catalana). Estos diques pre-Triásicos, presentan diferentes composiciones y directrices (dominando la NE-SW), y se hallan emplazados en un batolito granítico calco-alcalino postectónico con respecto al ciclo Hercínico (ENRIQUE, P., 1978; ENRIQUE, P., 1983; ]UUVERT, M. y MARTINEZ, F. J, 1983; ENRIQUE, P. Y DEBON, F., 1987; ENRIQUE, P. el al., 1987; SERRA, A. y ENRIQUE, P., 1987). En estos diques se observan deformaciones de origen inttusivo en los bordes de los mismos, similares a las que venimos describiendo desde hace algún tiempo en el Sistema Central Español (UBANELL, A. G. Y DOBLAS, M., 1987a; DOBLAS, M. el al., 1987; DOBLAS, M. et al., en prensa) Parece obvio que para tiempos Tardi-Hercínicos se produjo en esta zona un régimen extensional, originando un complejo filoniano esencialmente lineal (NE-SW). Finalmente, trataremos de enmarcar este episodio extensional Tardi-Hercínico, dentro de un marco global, comparando las caracterlSticas de esta zona con el Sistema Central Español, y los Pirineos.In this paper, we study the deformation of sorne dikes within the Tardi-Hercynian dike-complex of the southwestern Montnegre batholith ("Cordillera Litoral Costero Catalana»). These dikes, which are mainly pre-Triasic in age, display different compositions and trends (dominantly NE-SW), and they were emplaced in a calc-alkaline granitic batholith, post-tectonic (with respect to the Hercynian cycle)(ENRIQUE, P., 1978; ENRIQUE, P., 1983; ]ULlVERT, M. & MARTINEZ, F.]., 1983; ENRIQUE, p. &DEBON, F. 1987; ENRIQUE, P. el al., 1987;
SERRA, A. & ENRIQUE, P. 1987)
In the borders of the dikes, we may observe intrusion-related deformational features,
similar ro the ones described in the dike-complex of the Spanish Central
System (UBANELL, A. G. & DOBLAS, M. 1987a; DOBLAS, M. el al., 1987;
DOBLAS M. el al., in press).
During Tardi-Hercynian times the area underwent extensional tectonics resulting
in the emplacement of this linear-shaped dike-complex (NE-SW). Finally,
we will include this Tardi-Hercynian extensional event within a generalized model,
comparing the characteristics of the Catalonian province, with the Spanish
Central System and the PyreneesDepto. de Geodinámica, Estratigrafía y PaleontologíaFac. de Ciencias GeológicasFALSEpu
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