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A major source of uncertainty in regional climate model simulations arises from the convection parameterisation. Increasing spatial resolution to the so-called convection-permitting scale allows switching off most of the convective parameterisations. Several studies prove the benefits of this spatial scale, but none of them is based on climatological time-scale (i.e. 30 years) as this research.

regional climate model --- convection --- Regionale Klimamodelle --- Konvektion --- atmosphärische Prozesse --- convection-permitting scale --- atmospheric processes --- climate change signal --- Klimawandel-Signal

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- Water resources management should be assessed under climate change conditions, as historic data cannot replicate future climatic conditions. - Climate change impacts on water resources are bound to affect all water uses, i.e., irrigated agriculture, domestic and industrial water supply, hydropower generation, and environmental flow (of streams and rivers) and water level (of lakes). - Bottom-up approaches, i.e., the forcing of hydrologic simulation models with climate change models’ outputs, are the most common engineering practices and considered as climate-resilient water management approaches. - Hydrologic simulations forced by climate change scenarios derived from regional climate models (RCMs) can provide accurate assessments of the future water regime at basin scales. - Irrigated agriculture requires special attention as it is the principal water consumer and alterations of both precipitation and temperature patterns will directly affect agriculture yields and incomes. - Integrated water resources management (IWRM) requires multidisciplinary and interdisciplinary approaches, with climate change to be an emerging cornerstone in the IWRM concept.

California --- hydrologic regions --- warming --- drought --- regional climate modeling --- hydrological modeling --- bias correction --- multivariate --- pseudo reality --- rainfall --- trend analysis --- Mann–Kendall --- kriging interpolation --- multiple climate models --- standardized precipitation index (SPI) --- droughts --- weights --- Vu Gia-Thu Bon --- climate change --- optimal control --- geoengineering --- climate manipulation --- GCM --- RCM --- CMIP5 --- CORDEX --- climate model selection --- upper Indus basin --- NDVI --- ENSO --- wavelet --- time series analysis --- Hluhluwe-iMfolozi Park --- Google Earth Engine --- Mediterranean climate --- cluster analysis --- objective classification --- ERA5 --- mega-fires --- Bayesian-model averaging --- model uncertainty --- climate-fire models --- Mono River watershed --- climate --- temperature --- heat wave --- excess heat factor --- acclimatization --- Greece --- precipitations --- Hurst exponent --- persistence --- spatial correlation --- Caucasian region --- Regional Climate Model --- climate classification --- bias correction methods --- precipitation --- terrestrial ecosystems --- GPP --- LAI --- CO2 fertilization effect --- feedback --- sassandra watershed --- Côte d’Ivoire --- boreal region --- extreme wind speed --- wind climate --- soil frost --- wind damage risk management --- wind multiplier --- downscaling --- topography --- surface roughness --- VIIRS --- MODIS --- OLCI --- RSB --- SNPP --- Terra --- Aqua --- Sentinel-3A --- reflective solar bands --- intersensor comparison --- intercalibration --- SNO --- climate indices --- climate change and Conakry