Large biases and inconsistent climate change signals in ENSEMBLES regional projections

Abstract

 

In this paper we analyze some caveats found in the state-of-the-art ENSEMBLES regional projections dataset focusing on precipitation over Spain, and highlight the need of a task-oriented validation of the GCM-driven control runs. In particular, we compare the performance of the GCM-driven control runs (20C3M scenario) with the ERA40-driven ones (“perfect” boundary conditions) in a common period (1961–2000). Large deviations between the results indicate a large uncertainty/bias for the particular RCM-GCM combinations and, hence, a small confidence for the corresponding transient simulations due to the potential nonlinear amplification of biases. Specifically, we found large biases for some RCM-GCM combinations attributable to RCM in-house problems with the particular GCM coupling. These biases are shown to distort the corresponding climate change signal, or “delta”, in the last decades of the 21st century, considering the A1B scenario. Moreover, we analyze how to best combine the available RCMs to obtain more reliable projections.

Authors: Marco Turco, Antonella Sanna, Sixto Herrera, Maria-Carmen Llasat and José Manuel Gutiérrez.

Per llegir l’article sencer fes click AQUÍ

POST-DOCTORAL RESEARCH FELLOWSHIP IN ENSEMBLE PREDICTION FOR HYDRO-METEOROLOGY

Place: National Centre for Meteorological Research – Research group of atmospheric meteorology (CNRM-GAME), Toulouse, France (http://www.cnrm-game.fr/)

Application deadline: 5th May 2013

Starting dates/duration: start between July and November 2013 / 12 months.

Background:

This position is related to the DISTRIBUTED RESEARCH INFRASTRUCTURE FOR HYDRO-METEOROLOGY (DRIHM) project (http://www.drihm.eu/) funded by the European commission. DRIHM intends to develop a prototype e-Science environment to facilitate the collaboration between meteorologists, hydrologists, and Earth science experts and provide end-to-end hydro-meteorological research (HMR) services (models, datasets, and post-processing tools) at the European level, with the ability to expand to global scale. The objectives of DRIHM are to lead the definition of a common long-term strategy, to foster the development of new HMR models and observational archives for the study of severe hydro- meteorological events, to promote the execution and analysis of high-end simulations, and to support the dissemination of predictive models as decision analysis tools.

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.