Multiple perspectives on the attribution of the extreme European summer of 2012 to climate change

Summer 2012 was very wet in northern Europe, and unusually dry and hot in southern Europe. We use multiple approaches to determine whether anthropogenic forcing made the extreme European summer of 2012 more likely. Using a number of observation- and model-based methods, we find that there was an anthropogenic contribution to the extremes in southern Europe, with a qualitative consensus across all methodologies. There was a consensus across the methodologies that there has been a significant increase in the risk of hot summers in southern Europe with climate change. Most approaches also suggested a slight drying, but none of the results were statistically significant. The unusually wet summer in northern Europe was made more likely by the observed atmospheric circulation pattern in 2012, but no evidence was found for a long-term trend in circulation

Action anticipation based on an agent's epistemic state in toddlers and adults

Do toddlers and adults engage in spontaneous Theory of Mind (ToM)? Evidence from anticipatory looking (AL) studies suggests that they do. But a growing body of failed replication studies raised questions about the paradigm’s suitability. In this multi-lab collaboration, we test the robustness of spontaneous ToM measures. We examine whether 18- to 27-month-olds’ and adults’ anticipatory looks distinguish between two basic forms of an agent’s epistemic states: knowledge and ignorance. In toddlers [ANTICIPATED n = 520 50% FEMALE] and adults [ANTICIPATED n = 408, 50% FEMALE] from diverse ethnic backgrounds, we found [SUPPORT/NO SUPPORT] for epistemic state-based action anticipation. Future research can probe whether this conclusion extends to more complex kinds of epistemic states, such as true and false beliefs

Improved representation of the diurnal variation of warm season precipitation by an atmospheric general circulation model at a 10 km horizontal resolution

This study investigates the diurnal variation of the warm season precipitation simulated by the Goddard Earth Observing System version 5 atmospheric general circulation model for 2??years (2005???2006) at a horizontal resolution of 10??km. The simulation was validated with the satellite-derived Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation data and the Modern-Era Retrospective analysis for Research and Applications atmospheric reanalysis for atmospheric winds and moisture. The simulation is compared with the coarse-resolution run in 50??km to examine the impacts driven by resolution change. Overall, the 10??km model tends to reproduce the important features of the observed diurnal variation, such as the amplitude and phase at which precipitation peaks in the evening on land and in the morning over the ocean, despite an excessive amplitude bias over land. The model also reproduces the realistic propagation patterns of precipitation in the vicinity of ocean coasts and major mountains. The regional characteristics of the diurnal precipitation over two regions, the Bay of Bengal and the Great Plains in North America, are examined in detail, where the observed diurnal cycle exhibits a systematic transition in the peak phase due to the development and propagation of regional-scale convective systems. The model is able to reproduce this pattern as well as the diurnal variation of low-level wind and moisture convergence; however, it is less effective at representing the nocturnal peak of precipitation over the Great Plains. The model results suggest that increasing the horizontal resolution of the model to 10??km substantially improves the representation of the diurnal precipitation cycle. However, intrinsic model deficiencies in topographical precipitation and the accurate representation of mesoscale convective systems remain a challenge

Proportions of Convective and Stratiform Precipitation Revealed in Water Isotope Ratios

Tropical and midlatitude precipitation is fundamentally of two types, spatially-limited and high-intensity convective or widespread and lower-intensity stratiform, owing to differences in vertical air motions and microphysical processes governing rain formation. These processes are difficult to observe or model and precipitation partitioning into rain types is critical for understanding how the water cycle responds to climate changes. Here, we combine two independent data sets – convective and stratiform precipitation fractions, derived from the Tropical Rainfall Measuring Mission satellite or synoptic cloud observations, and stable isotope and tritium compositions of surface precipitation, derived from a global network – to show that isotope ratios reflect rain type proportions and are negatively correlated with stratiform fractions. Condensation and riming associated with boundary layer moisture produces higher isotope ratios in convective rain, along with higher tritium when riming in deep convection occurs with entrained air at higher altitudes. Based on our data, stable isotope ratios can be used to monitor changes in the character of precipitation in response to periodic variability or changes in climate. Our results also provide observational constraints for an improved simulation of convection in climate models and a better understanding of isotope variations in proxy archives, such as speleothems and tropical ice

Daily precipitation statistics in a EURO-CORDEX RCM ensemble: added value of raw and bias-corrected high-resolution simulations

Daily precipitation statistics as simulated by the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble are evaluated over two distinct regions of the European continent, namely the European Alps and Spain. The potential added value of the high-resolution 12 km experiments with respect to their 50 km resolution counterparts is investigated. The statistics considered consist of wet-day intensity and precipitation frequency as a measure of mean precipitation, and three precipitation-derived indicators (90th percentile on wet days?90pWET, contribution of the very wet days to total precipitation?R95pTOT and number of consecutive dry days?CDD). As reference for model evaluation high resolution gridded observational data over continental Spain (Spain011/044) and the Alpine region (EURO4M-APGD) are used. The assessment and comparison of the two resolutions is accomplished not only on their original horizontal grids (approximately 12 and 50 km), but the high-resolution RCMs are additionally regridded onto the coarse 50 km grid by grid cell aggregation for the direct comparison with the low resolution simulations. The direct application of RCMs e.g. in many impact modelling studies is hampered by model biases. Therefore bias correction (BC) techniques are needed at both resolutions to ensure a better agreement between models and observations. In this work, the added value of the high resolution (before and after the bias correction) is assessed and the suitability of these BC methods is also discussed. Three basic BC methods are applied to isolate the effect of biases in mean precipitation, wet-day intensity and wet-day frequency on the derived indicators. Daily precipitation percentiles are strongly affected by biases in the wet-day intensity, whereas the dry spells are better represented when the simulated precipitation frequency is adjusted to the observed one. This confirms that there is no single optimal way to correct for RCM biases, since correcting some distributional features typically leads to an improvement of some aspects but to a deterioration of others. Regarding mean seasonal biases before the BC, we find only limited evidence for an added value of the higher resolution in the precipitation intensity and frequency or in the derived indicators. Thereby, evaluation results considerably depend on the RCM, season and indicator considered. High resolution simulations better reproduce the indicators? spatial patterns, especially in terms of spatial correlation. However, this improvement is not statistically significant after applying specific BC methods.The authors are grateful to Prof. C. Schär for his helpful comments and E. van Meijgaard for making available the RACMO model data. We acknowledge the observational data providers. Calculations for WRF311F were made using the TGCC super computers under the GENCI time allocation GEN6877. The WRF331A from CRP-GL (now LIST) was funded by the Luxembourg National Research Fund (FNR) through grant FNR C09/SR/16 (CLIMPACT). The KNMI-RACMO2 simulations were supported by the Dutch Ministry of Infrastructure and the Environment. The CCLM and REMO simulations were supported by the Federal Ministry of Education and Research (BMBF) and performed under the Konsortial share at the German Climate Computing Centre (DKRZ). The CCLM simulations were furthermore supported by the Swiss National Supercomputing Centre (CSCS) under project ID s78. Part of the SMHI contribution was carried out in the Swedish Mistra-SWECIA programme founded by Mistra (the Foundation for Strategic Environmental Research). This work is supported by CORWES (CGL2010-22158-C02) and EXTREMBLES (CGL2010-21869) projects funded by the Spanish R&D programme and the European COST ACTION VALUE (ES1102). A. C. thanks the Spanish Ministry of Economy and Competitiveness for the funding provided within the FPI programme (BES-2011-047612 and EEBB-I-13-06354). We also thank two anonymous referees for their useful comments that helped to improve the original manuscript

Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a ‘storyline’ approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a conditioned manner and (iv) exploring the boundaries of plausibility, thereby guarding against false precision and surprise. Storylines also offer a powerful way of linking physical with human aspects of climate change

Lateral terrestrial water flow contribution to summer precipitation at continental scale – A comparison between Europe and West Africa with WRF‐Hydro‐tag ensembles

It is well accepted that summer precipitation can be altered by soil moisture condition. Coupled land surface – atmospheric models have been routinely used to quantify soil moisture – precipitation feedback processes. However, most of the land surface models (LSMs) assume a vertical soil water transport and neglect lateral terrestrial water flow at the surface and in the subsurface, which potentially reduces the realism of the simulated soil moisture – precipitation feedback. In this study, the contribution of lateral terrestrial water flow to summer precipitation is assessed in two different climatic regions, Europe and West Africa, for the period June–September 2008. A version of the coupled atmospheric-hydrological model WRF-Hydro with an option to tag and trace land surface evaporation in the modelled atmosphere, named WRF-Hydro-tag, is employed. An ensemble of 30 simulations with terrestrial routing and 30 simulations without terrestrial routing is generated with random realizations of turbulent energy with the stochastic kinetic energy backscatter scheme, for both Europe and West Africa. The ensemble size allows to extract random noise from continental-scale averaged modelled precipitation. It is found that lateral terrestrial water flow increases the relative contribution of land surface evaporation to precipitation by 3.6% in Europe and 5.6% in West Africa, which enhances a positive soil moisture – precipitation feedback and generates more uncertainty in modelled precipitation, as diagnosed by a slight increase in normalized ensemble spread. This study demonstrates the small but non-negligible contribution of lateral terrestrial water flow to precipitation at continental scale

Enhanced future changes in wet and dry extremes over Africa at convection-permitting scale

African society is particularly vulnerable to climate change. The representation of convection in climate models has so far restricted our ability to accurately simulate African weather extremes, limiting climate change predictions. Here we show results from climate change experiments with a convection-permitting (4.5 km grid-spacing) model, for the first time over an Africa-wide domain (CP4A). The model realistically captures hourly rainfall characteristics, unlike coarser resolution models. CP4A shows greater future increases in extreme 3-hourly precipitation compared to a convection-parameterised 25 km model (R25). CP4A also shows future increases in dry spell length during the wet season over western and central Africa, weaker or not apparent in R25. These differences relate to the more realistic representation of convection in CP4A, and its response to increasing atmospheric moisture and stability. We conclude that, with the more accurate representation of convection, projected changes in both wet and dry extremes over Africa may be more severe

Northward shift of the agricultural climate zone under 21st-century global climate change

As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21st-century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions