Cumulative CO2 emissions are a robust predictor of mean temperature increase. However, many societal impacts are driven by exposure to extreme weather conditions. Here, we show that cumulative emissions can be robustly linked to regional changes of a heat exposure indicator, as well as the resulting socioeconomic impacts associated with labour productivity loss in vulnerable economic sectors. We estimate historical and future increases in heat exposure using simulations from eight Earth System Models. Both the global intensity and spatial pattern of heat exposure evolve linearly with cumulative emissions across scenarios (1% CO2, RCP4.5 and RCP8.5). The pattern of heat exposure at a given level of global temperature increase is strongly affected by non-CO2 forcing. Global non-CO2 greenhouse gas emissions amplify heat exposure, while high local emissions of aerosols could moderate exposure. Considering CO2 forcing only, we commit ourselves to an additional annual loss of labour productivity of about 2% of total GDP per unit of trillion tonne of carbon emitted. This loss doubles when adding non-CO2 forcing of the RCP8.5 scenario. This represents an additional economic loss of about 4,400 G$ every year (i.e. 0.59 $/tCO2), varying across countries with generally higher impact in lower-income countries.

This paper presents the SELENDIA code designed for the simulation of marine diesel engines. Various measured and simulated results are compared for the performance of a sequentially turbocharged marine diesel engine during a switch from one to two turbochargers. The results show a good agreement between measured and simulated data. Surge loops that are experimentally observed in case of an anomaly are analyzed using simulated results. Finally, the predictive capabilities of the simulation code are utilized to investigate the influence of the inlet manifold volume on the engine and air charging system performance with a special focus on compressor surge. [S0742-4795(00)01104-2]

Climate conditions for Québec's viticultural potential (VP) during upcoming decades are estimated through high-resolution probabilistic climate scenarios (PCS) based on a large ensemble of simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). VP is investigated through four temperature-related indices identified as current limiting factors for cold, northern latitudes: length of frost-free season (CNFD), growing degree-days (DDB10), annual winter minimum temperature (AWMT), and annual number of very cold days (ANVCD). Results show that by 2040-2050, most of southern Québec can reasonably expect favorable climatic conditions, with enough consecutive frost-free days and growing degree-days for growing current hybrid-grape varieties, as well as some Vitis vinifera grape varieties. Regions with new VP are identified, for example southern Outaouais and along the St-Lawrence River. Cold winter temperatures remain problematic, but technical solutions to this limiting factor exist.

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ABSTRACT:The present study focuses on the evaluation and comparison of the ability of two versions of the Canadian Regional Climate Model (CRCM) driven by re-analyses (NCEP-NCAR) to reproduce the observed extremes and climate variability in summer . The analysed variables are daily precipitation, minimum and maximum temperatures over three regions located in north-eastern North America that are characterized by different topography and observation density. The validation has been performed with multiple climate extreme indices characterizing the frequency, intensity and duration of precipitation and temperature events. The assessment of the ability of the CRCM is done through an in-depth analysis of the statistical distribution, performance scores and interannual variability of extreme indices. The reference database has been constructed by kriging the daily observed data from local meteorological stations onto the CRCM 45-km grid. The vast majority of results over the three regions show that, with respect to the previous (i.e. 3.7.1) CRCM version, the latest version (4.1.1) improves in general the simulated extreme events. In particular, the intensity of extreme hot summer temperature, diurnal temperature range, wet days occurrence, seasonal dry spell, and to a lesser extent extreme cold summer temperature and heavy rainfall. The study suggests that improvements in the simulated extremes in the latest version are due mainly to the introduction of the new land surface scheme (CLASS 2.7), with a more sophisticated representation of the soil moisture content. This suggests the importance of surface processes parameterization as a potential cause of errors in simulated extremes.