XX Jornades Eduard Fontserè – Ponències

Podeu veure les ponències de les passades JEF.

http://acam.cat/node/404

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Postdoc vacancies at Oxford in stochastic modelling for weather and climate

The first of these is for up to three posts, each up to four years and funded by the European Research Council. Research topics can include stochastic parametrisation in comprehensive and idealised weather and climate models, stochastic computing, and the development of verification tools including coarse-graining methods. The second is for a 42-month NERC-funded post working with Dr Laure Zanna and me on predicability in coupled models . Part of this post includes the development of stochastic parametrisations in ocean models. It is expected that there will be considerable interaction with scientists at ECMWF, and there is a generous allocation of supercomputing resources at ECMWF for these projects. Leer más de esta entrada

Research Scientist in coupled atmosphere-ocean modelling – Euro Mediterranean Centre for Climate Change – Impact on soil and Coast Division

Company: CMCC

Location: Capua – Italy

Remuneration: Competitive

Position Type: 3 years

Employment type: Full time

CMCC is looking to recruit a motivated and talented researcher for a modelling position in the area of climate numerical simulations. The candidate will be employed in the development of a coupled atmospherical – ocean model including the atmospheric model COSMO-CLM (a regional climate model developed by the COSMO CLM assembly) and the oceanic model NEMO. The goal is to include the effects ofMediterranean sea, using the NEMO code and the OASIS coupler, in the high resolution regional climate model COSMO CLM. The activity will be performed in a European team; therefore some period of training abroad will be required. The cost transfer will be paid by CMCC and the gross salary will be based on qualification and working experience. Leer más de esta entrada

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

Atencia, A., L. Mediero, M. C. Llasat, and L. Garrote, 2011.

Abstract.

The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin.

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Testing MOS precipitation downscaling for ENSEMBLES regional climate models over Spain

Abstract:

Model Output Statistics (MOS) has been recently proposed as an alternative to the standard perfect prognosis statistical downscaling approach for Regional Climate Model (RCM) outputs. In this case, the model output for the variable of interest (e.g. precipitation) is directly downscaled using observations. In this paper we test the performance of a MOS implementation of the popular analog methodology (referred to as MOS analog) applied to downscale daily precipitation outputs over Spain. To this aim, we consider the state‐of‐the‐art ERA40‐driven RCMs provided by the EU‐funded ENSEMBLES project and the Spain02 gridded observations data set, using the common period 1961–2000. The MOS analog method improves the representation of the mean regimes, the annual cycle, the frequency and the extremes of precipitation for all RCMs, regardless of the region and the model reliability (including relatively low‐performing models), while preserving the daily accuracy. The good performance of the method in this complex climatic region suggests its potential transferability to other regions. Furthermore, in order to test the robustness of the method in changing climate conditions, a cross‐validation in driest or wettest years was performed. The method improves the RCM results in both cases, especially in the former.

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