404 research outputs found

    The COSMO-CLM preprocessor PEP

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    Characterization of the rainy season in Burkina Faso and it's representation by regional climate models

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    International audienceWest African monsoon is one of the most challenging climate components to model. Five regional climate models (RCMs) were run over the West African region with two lateral boundary conditions, ERA-Interim re-analysis and simulations from two general circulation models (GCMs). Two sets of daily rainfall data were generated from these boundary conditions. These simulated rainfall data are analyzed here in comparison to daily rainfall data collected over a network of ten synoptic stations in Burkina Faso from 1990 to 2004. The analyses are based on a description of the rainy season throughout a number of it's characteristics. It was found that the two sets of rainfall data produced with the two driving data present significant biases. The RCMs generally produce too frequent low rainfall values (between 0. 1 and 5 mm/day) and too high extreme rainfalls (more than twice the observed values). The high frequency of low rainfall events in the RCMs induces shorter dry spells at the rainfall thresholds of 0. 1-1 mm/day. Altogether, there are large disagreements between the models on the simulate season duration and the annual rainfall amounts but most striking are their differences in representing the distribution of rainfall intensity. It is remarkable that these conclusions are valid whether the RCMs are driven by re-analysis or GCMs. In none of the analyzed rainy season characteristics, a significant improvement of their representation can be found when the RCM is forced by the re-analysis, indicating that these deficiencies are intrinsic to the models. © 2011 The Author(s)

    On the role of soil moisture in the generation of heavy rainfall during the Oder flood event in July 1997

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    Soil moisture-atmosphere feedbacks play an important role in the regional climate over many regions worldwide, not only for the mean climate but also for extreme events. Several studies have shown that the extent and severity of droughts and heat waves can be significantly impacted by dry or wet soil moisture conditions. To date, the impact of soil moisture on heavy rainfall events has been less frequently investigated. Thus, we consider the role of soil moisture in the formation of heavy rainfall using the Oder flood event in July 1997 as an example. Here, we used the regional climate model CCLM as an uncoupled stand alone model and the coupled COSTRICE system, where CCLM is coupled with an ocean and a sea ice model over the Baltic and North Sea regions. The results from climate simulations over Europe show that the coupled model can capture the second phase (18-20 July) of heavy rainfall that led to the Oder flood, while the uncoupled model does not. Sensitivity experiments demonstrate that the better performance of the coupled model can be attributed to the simulated soil moisture conditions in July 1997 in Central Europe, which were wetter for the coupled model than for the uncoupled model. This finding indicates that the soil moisture preceding the event significantly impacted the generation of heavy rainfall in this second phase. The better simulation in the coupled model also implies the added value that the atmosphere-ocean coupling has on the simulation of this specific extreme event. As none of the model versions captured the first phase (4-8 July), despite the differences in soil moisture, it can be concluded that the importance of soil moisture for the generation of heavy rainfall events strongly depends on the event and the general circulation pattern associated with it

    Soil control on runoff response to climate change in regional climate model simulations

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    Simulations with seven regional climate models driven by a common control climate simulation of a GCM carried out for Europe in the context of the (European Union) EU-funded Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project were analyzed with respect to land surface hydrology in the Rhine basin. In particular, the annual cycle of the terrestrial water storage was compared to analyses based on the 40-yr ECMWF Re-Analysis (ERA-40) atmospheric convergence and observed Rhine discharge data. In addition, an analysis was made of the partitioning of convergence anomalies over anomalies in runoff and storage. This analysis revealed that most models underestimate the size of the water storage and consequently overestimated the response of runoff to anomalies in net convergence. The partitioning of these anomalies over runoff and storage was indicative for the response of the simulated runoff to a projected climate change consistent with the greenhouse gas A2 Synthesis Report on Emission Scenarios (SRES). In particular, the annual cycle of runoff is affected largely by the terrestrial storage reservoir. Larger storage capacity leads to smaller changes in both wintertime and summertime monthly mean runoff. The sustained summertime evaporation resulting from larger storage reservoirs may have a noticeable impact on the summertime surface temperature projections

    Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

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    Acknowledgments We thank Reik V. Donner for inspiring suggestions that initialized the work presented herein. Jan H. Feldhoff is credited for providing us with the STARS simulation data and for his contributions to fruitful discussions. Comments by the anonymous reviewers are gratefully acknowledged as they led to substantial improvements of the manuscript.Peer reviewedPublisher PD

    Effects of external nutrient sources and extreme weather events on the nutrient budget of a Southern European coastal lagoon

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    The seasonal and annual nitrogen (N), phosphorus (P), and carbon (C) budgets of the mesotidal Ria Formosa lagoon, southern Portugal, were estimated to reveal the main inputs and outputs, the seasonal patterns, and how they may influence the ecological functioning of the system. The effects of extreme weather events such as long-lasting strong winds causing upwelling and strong rainfall were assessed. External nutrient inputs were quantified; ocean exchange was assessed in 24-h sampling campaigns, and final calculations were made using a hydrodynamic model of the lagoon. Rain and stream inputs were the main freshwater sources to the lagoon. However, wastewater treatment plant and groundwater discharges dominated nutrient input, together accounting for 98, 96, and 88 % of total C, N, and P input, respectively. Organic matter and nutrients were continuously exported to the ocean. This pattern was reversed following extreme events, such as strong winds in early summer that caused upwelling and after a period of heavy rainfall in late autumn. A principal component analysis (PCA) revealed that ammonium and organic N and C exchange were positively associated with temperature as opposed to pH and nitrate. These variables reflected mostly the benthic lagoon metabolism, whereas particulate P exchange was correlated to Chl a, indicating that this was more related to phytoplankton dynamics. The increase of stochastic events, as expected in climate change scenarios, may have strong effects on the ecological functioning of coastal lagoons, altering the C and nutrient budgets.Portuguese Science and Technology Foundation (FCT) [POCI/MAR/58427/2004, PPCDT/MAR/58427/2004]; Portuguese Science and Technology Foundation (FCT

    The RACE Project: Robustness by Autonomous Competence Enhancement

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    This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system
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