ABSTRACT:Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change impact study. The selection of climate models is not straightforward and can be done by following different methods. Usually, the selection is either based on the entire range of changes in climatic variables as projected by the total ensemble of available climate models or on the skill of climate models to simulate past climate. The present study combines these approaches in a three-step sequential climate model selection procedure: (1) initial selection of climate models based on the range of projected changes in climatic means, (2) refined selection based on the range of projected changes in climatic extremes and (3) final selection based on the climate model skill to simulate past climate. This procedure is illustrated for a study area covering the Indus, Ganges and Brahmaputra river basins. Subsequently, the changes in climate between 1971-2000 and 2071-2100 are analysed, showing that the future climate projections in this area are highly uncertain but that changes are imminent.

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Abstract. Atmospheric CO 2 modeling in interaction with the surface fluxes, at the regional scale is developed within the frame of the European project CarboEurope-IP and its Regional Experiment component. In this context, five mesoscale meteorological models at 2 km resolution participate in an intercomparison exercise. Using a common experimental protocol that imposes a large number of rules, two days of the CarboEurope Regional Experiment Strategy (CERES) campaign are simulated. A systematic evaluation of the models is done in confrontation with the observations, using statistical tools and direct comparisons. Thus, temperature and relative humidity at 2 m, wind direction, surface energy and CO 2 fluxes, vertical profiles of potential temperature as well as in-situ CO 2 concentrations comparisons between observations and simulations are examined. These comparisons reveal a cold bias in the simulated temperature at 2 m, the latent heat flux is often underestimated. Nevertheless, the CO 2 concentrations heterogeneities are well captured by most of the models. This intercomparison exercise shows also the models ability to represent the meteorology and carbon cycling at the synoptic and regional scale in the boundary layer, but also points out some of the major shortcomings of the models.

In 2015, with the signing of the BParis Agreement^, 195 countries committed to limiting the increase in global temperature to less than 2°C with respect to pre-industrial levels and to aim at limiting the increase to 1.5°C by 2100. The regional ramifications of those thresholds remain however largely unknown and variability in the magnitude of change and the associated impacts are yet to be quantified. We provide a regional quantitative assessment of the impacts of a 1.5 versus a 2°C global warming for a major global climate change hotspot: the Indus, Ganges, and Brahmaputra river basins (IGB) in South Asia, by analyzing changes in climate change indicators based on 1.5 and 2°C global warming scenarios. In the analyzed ensemble of general circulation models, a global temperature increase of 1.5°C implies a temperature increase of 1.4-2.6 (μ = 2.1)°C for the IGB. For the 2.0°C scenario, the increase would be 2.0-3.4 (μ = 2.7)°C. We show that climate change impacts are more adverse under 2°C versus 1.5°C warming and that changes in the indicators' values are in general linearly correlated to average temperature increase. We also show that for climate projections following Representative Concentration Pathways 4.5 and 8.5, which may be more realistic, the regional temperature increases and changes in climate change indicators are much stronger than for the 1.5 and 2°C scenarios.

The paper considers local responses to the introduction of an Ebola Treatment Centre in eastern Sierra Leone during the West African epidemic of 2014–15. Our study used qualitative methods consisting of focus groups and interviews, to gather responses from patients, members of the families of survivors and deceased victims of the disease, social liaison workers from the centre, and members of the general public. The data indicate that scepticism and resistance were widespread at the outset, but that misconceptions were replaced, in the minds of those directly affected by the disease, by more positive later assessments. Social workers, and social contacts of families with workers in the centre, helped reshape these perceptions, but a major factor was direct experience of the disease. This is apparent in the positive endorsements by survivors and families who had members taken to the facility. Even relatives of deceased victims agreed that the case-handling centre was valuable. However, we also present evidence of continuing scepticism in the minds of members of the general public, who continue to suspect that Ebola was a crisis manufactured for external benefit. Our conclusions stress the importance of better connectivity between communities and Ebola facilities to facilitate experiential learning. There is also a need to address the wider cognitive shock caused by a well-funded Ebola health initiative arriving in communities with a long history of inadequate health care. Restoring trust in medicine requires Ebola Virus Disease to be re-contextualized within a broader framework of concern for the health of all citizens.

a b s t r a c tAn agricultural experiment is usually associated with a scientific method for testing certain agricultural phenomena. A central point in the work of Paul Richards is that experimentation is at the heart of agricultural practice. The reason why agricultural experiments are something different for farmers and agronomists is not their capacity to experiment as such but the embedding of experiments in a specific ecological, material and institutional environment. Using a historical perspective, changes are examined in the organization of agricultural experiments focusing on the Netherlands and colonial Indonesia during the first half of the 20th century and the international agricultural research institutes for the period thereafter. The results show a gradual shift in the role of experiments in the connection between science and practice. Initially, the link was considered to be established through various forms of experiments, rooted in an integrated social and technical understanding of agronomy. Gradually, this turned into a connection primarily established through various forms of communication. Recent work of Richards incorporates ideas that address key issues emerging from the history of agricultural experiments, dealing with an integrated social and technical understanding of agriculture.

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Abstract. Studies have demonstrated that precipitation onNorthern Hemisphere mid-latitudes has increased in the last decades and that it is likely that this trend will continue. This will have an influence on discharge of the river Meuse. The use of bias correction methods is important when the effect of precipitation change on river discharge is studied. The objective of this paper is to investigate the effect of using two different bias correction methods on output from a Regional Climate Model (RCM) simulation. In this study a Regional Atmospheric Climate Model (RACMO2) run is used, forced by ECHAM5/MPIOM under the condition of the SRES-A1B emission scenario, with a 25 km horizontal resolution. The RACMO2 runs contain a systematic precipitation bias on which two bias correction methods are applied. The first method corrects for the wet day fraction and wet day average (WD bias correction) and the second method corrects for the mean and coefficient of variance (MV bias correction). The WD bias correction initially corrects well for the average, but it appears that too many successive precipitation days were removed with this correction. The second method performed less well on average bias correction, but the temporal precipitation pattern was better. Subsequently, the discharge was calculated by using RACMO2 output as forcing to the HBV-96 hydrological model. A large difference was found between the simulated discharge of the uncorrected RACMO2 run, the WD bias corrected run and the MV bias corrected run. These results show the importance of an appropriate bias correction.