The European Centre for Medium-Range Weather Forecasts (ECMWF) recently released its most advanced reanalysis product, the ERA5 dataset. It was designed and generated with methods giving it multiple ...advantages over the previous release, the ERA-Interim reanalysis product. Notably, it has a finer spatial resolution, is archived at the hourly time step, uses a more advanced assimilation system and includes more sources of data. This paper aims to evaluate the ERA5 reanalysis as a potential reference dataset for hydrological modelling by considering the ERA5 precipitation and temperatures as proxies for observations in the hydrological modelling process, using two lumped hydrological models over 3138 North American catchments. This study shows that ERA5-based hydrological modelling performance is equivalent to using observations over most of North America, with the exception of the eastern half of the US, where observations lead to consistently better performance. ERA5 temperature and precipitation biases are consistently reduced compared to ERA-Interim and systematically more accurate for hydrological modelling. Differences between ERA5, ERA-Interim and observation datasets are mostly linked to precipitation, as temperature only marginally influences the hydrological simulation outcomes.
This work compares the performance of six bias correction methods for hydrological modeling over 10 North American river basins. Four regional climate model (RCM) simulations driven by reanalysis ...data taken from the North American Regional Climate Change Assessment Program intercomparison project are used to evaluate the sensitivity of bias correction methods to climate models. The hydrological impacts of bias correction methods are assessed through the comparison of streamflows simulated by a lumped empirical hydrology model (HSAMI) using raw RCM‐simulated and bias‐corrected precipitation time series. The results show that RCMs are biased in the simulation of precipitation, which results in biased simulated streamflows. All six bias correction methods are capable of improving the RCM‐simulated precipitation in the representation of watershed streamflows to a certain degree. However, the performance of hydrological modeling depends on the choice of a bias correction method and the location of a watershed. Moreover, distribution‐based methods are consistently better than mean‐based methods. A low coherence between the temporal sequences of observed and RCM‐simulated (driven by reanalysis data) precipitation was observed over 5 of the 10 watersheds studied. All bias corrections methods fail over these basins due to their inability to specifically correct the temporal structure of daily precipitation occurrence, which is critical for hydrology modeling. In this study, this failure occurred on basins that were distant from the RCM model boundaries and where topography exerted little control over precipitation. These results indicate that bias correction performance is location dependent and that a careful validation should always be performed, especially on studies over new regions.
Key Points
Bias correction methods were evaluated with respect to hydrological modeling.
Distribution‐based bias correction methods are better than mean‐based methods.
The performance of bias correction is location‐dependent.
► Uncertainty of six downscaling techniques. ► Hydrological impacts of climate change. ► The uncertainty linked to the choice of a downscaling method should not be ignored. ► The choice of ...downscaling approach should be evaluated on a case by case basis.
Uncertainty estimation of climate change impacts has been given a lot of attention in the recent literature. It is generally assumed that the major sources of uncertainty are linked to General Circulation Models (GCMs) and Greenhouse Gases Emissions Scenarios (GGES). However, other sources of uncertainty such as the choice of a downscaling method have been given less attention. This paper focuses on this issue by comparing six downscaling methods to investigate the uncertainties in quantifying the impacts of climate change on the hydrology of a Canadian (Quebec province) river basin. The downscaling methods regroup dynamical and statistical approaches, including the change factor method and a weather generator-based approach. Future (2070–2099, 2085 horizon) hydrological regimes simulated with a hydrological model are compared to the reference period (1970–1999) using the average hydrograph, annual mean discharge, peak discharge and time to peak discharge as criteria. The results show that all downscaling methods suggest temperature increases over the basin for the 2085 horizon. The regression-based statistical methods predict a larger increase in autumn and winter temperatures. Predicted changes in precipitation are not as unequivocal as those of temperatures, they vary depending on the downscaling methods and seasons. There is a general increase in winter discharge (November–April) while decreases in summer discharge are predicted by most methods. Consistently with the large predicted increases in autumn and winter temperature, regression-based statistical methods show severe increases in winter flows and considerable reductions in peak discharge. Across all variables, a large uncertainty envelope was found to be associated with the choice of a downscaling method. This envelope was compared to the envelope originating from the choice of 28 climate change projections from a combination of seven GCMs and three GGES. Both uncertainty envelopes were similar, although the latter was slightly larger. The regression-based statistical downscaling methods contributed significantly to the uncertainty envelope. Overall, results indicate that climate change impact studies based on only one downscaling method should be interpreted with caution.
Soil biota influence plant performance through plant-soil feedback, but it is unclear whether the strength of such feedback depends on plant traits and whether plant-soil feedback drives local plant ...diversity. We grew 16 co-occurring plant species with contrasting nutrient-acquisition strategies from hyperdiverse Australian shrublands and exposed them to soil biota from under their own or other plant species. Plant responses to soil biota varied according to their nutrient-acquisition strategy, including positive feedback for ectomycorrhizal plants and negative feedback for nitrogen-fixing and nonmycorrhizal plants. Simulations revealed that such strategy-dependent feedback is sufficient to maintain the high taxonomic and functional diversity characterizing these Mediterranean-climate shrublands. Our study identifies nutrient-acquisition strategy as a key trait explaining how different plant responses to soil biota promote local plant diversity.
► This work assesses the uncertainty of empirical downscaling methods on hydrology. ► A large uncertainty was linked to the choice of an empirical downscaling method. ► Empirical downscaling ...uncertainty was more significant in projecting extreme flow. ► The uncertainty linked to using change factor and bias correction methods was larger than within each type.
Statistical and dynamical downscaling techniques have been proposed to bridge the gaps between coarse-scale and generally biased climate model outputs and the point-scale requirements of impact model inputs. Amongst the various statistical approaches, empirical downscaling methods are the most commonly used due to their ease of implementation. Several empirical downscaling approaches have been proposed and need to be assessed as to which method contributes (or not) to the overall climate change uncertainty. Accordingly, this work aims at assessing the uncertainty of six empirical downscaling methods in quantifying the hydrological impact of climate change over two North American river basins under different climate conditions. The six empirical downscaling methods are grouped into change factor (two methods) and bias correction (four methods) approaches. The uncertainty related to the choice of an empirical downscaling method is compared to that associated with the choice of climate simulation, through the use of two Regional Climate Models (RCMs) driven by three different General Circulation Models (GCMs), totaling four RCM simulations, taken from the NARCCAP inter-comparison project. The future (2041–2065) hydrological regimes simulated with an empirical lumped hydrology model (HSAMI) are compared to the reference period (1971–1995) using a set of hydrology criteria which includes statistics of both mean and extreme values. The results show a large uncertainty envelope associated with the choice of a given empirical downscaling method, as well as for the choice of an RCM simulation. The uncertainty due to empirical downscaling and RCM simulation was more significant in projecting extreme streamflow than in projecting mean flows. Comparing the uncertainty envelope of empirical downscaling methods to the envelope resulting from four RCM simulations indicates that both are similar, even though the latter was slightly larger for some statistics. Finally, the uncertainty linked to the choice of an empirical downscaling approach (change factor vs. bias correction) was much larger than within each type. Overall, this work emphasizes the importance of using several climate projections and empirical downscaling approaches to delineate uncertainty when assessing the climate change impacts on hydrology.
In motor neocortex, preparatory activity predictive of specific movements is maintained by a positive feedback loop with the thalamus. Motor thalamus receives excitatory input from the cerebellum, ...which learns to generate predictive signals for motor control. The contribution of this pathway to neocortical preparatory signals remains poorly understood. Here, we show that, in a virtual reality conditioning task, cerebellar output neurons in the dentate nucleus exhibit preparatory activity similar to that in anterolateral motor cortex prior to reward acquisition. Silencing activity in dentate nucleus by photoactivating inhibitory Purkinje cells in the cerebellar cortex caused robust, short-latency suppression of preparatory activity in anterolateral motor cortex. Our results suggest that preparatory activity is controlled by a learned decrease of Purkinje cell firing in advance of reward under supervision of climbing fiber inputs signaling reward delivery. Thus, cerebellar computations exert a powerful influence on preparatory activity in motor neocortex.
•Similar activity in dentate nucleus (DN) and ALM cortex prior to reward acquisition•Silencing DN activity selectively suppresses preparatory activity in ALM•Preparatory activity likely controlled by learned decrease in Purkinje cell firing•Dynamics of preparatory activity imply reward time prediction from external cues
Chabrol et al. show that the cerebellum is directly involved in maintaining preparatory activity in the premotor neocortex during learned, goal-directed behavior. Their results suggest the cerebellum provides a learned timing signal required for motor preparation in the neocortex.
This paper focuses on evaluating the uncertainty of three common regionalization methods for predicting continuous streamflow in ungauged basins. A set of 268 basins covering 1.6 million km2 in the ...province of Quebec was used to test the regionalization strategies. The multiple linear regression, spatial proximity, and physical similarity approaches were evaluated on the catchments using a leave‐one‐out cross‐validation scheme. The lumped conceptual HSAMI hydrological model was used throughout the study. A bootstrapping method was chosen to further estimate uncertainty due to parameter set selection for each of the parameter set/regionalization method pairs. Results show that parameter set selection can play an important role in regionalization method performance depending on the regionalization methods (and their variants) used and that equifinality does not contribute significantly to the overall uncertainty witnessed throughout the regionalization methods applications. Regression methods fail to consistently assign behavioral parameter sets to the pseudoungauged basins (i.e., the ones left out). Spatial proximity and physical similarity score better, the latter being the best. It is also shown that combining either physical similarity or spatial proximity with the multiple linear regression method can lead to an even more successful prediction rate. However, even the best methods were shown to be unreliable to an extent, as successful prediction rates never surpass 75%. Finally, this paper shows that the selection of catchment descriptors is crucial to the regionalization strategies' performance and that for the HSAMI model, the optimal number of donor catchments for transferred parameter sets lies between four and seven.
Key Points
Uncertainty can be limited in regionalization
Physical similarity method is best, followed by spatial proximity
Regression‐augmented methods can yield better performance
We used incentivized experimental games to manipulate leader power — the number of followers and the discretion leaders had to enforce their will. Leaders had complete autonomy in deciding payouts to ...themselves and their followers. Although leaders could make prosocial decisions to benefit the public good they could also abuse their power by invoking antisocial decisions, which reduced the total payouts to the group but increased the leaders' earnings. In Study 1 (N=478), we found that both amount of followers and discretionary choices independently predicted leader corruption. In Study 2 (N=240), we examined how power and individual differences (e.g., personality, hormones) affected leader corruption over time; power interacted with endogenous testosterone in predicting corruption, which was highest when leader power and baseline testosterone were both high. Honesty predicted initial level of leader antisocial decisions; however, honesty did not shield leaders from the corruptive effect of power.
The development of group 15 Lewis acids is an area of active investigation that has led to numerous advances in anion sensing and catalysis. While phosphorus has drawn considerable attention, ...emerging research shows that organoantimony(III) reagents may also act as potent Lewis acids. Comparison of the properties of SbPh3, Sb(C6F5)3, and SbArF3 with those of their tetrachlorocatecholate analogues SbPh3Cat, Sb(C6F5)3Cat, and SbArF3Cat (Cat=o‐O2C6Cl4, ArF=3,5‐(CF3)2C6H3) demonstrates that the Lewis acidity of electron deficient organoantimony(III) reagents can be readily enhanced by oxidation to the +V state—as verified by binding studies, organic reaction catalysis, and computational studies. The results are rationalized by explaining that oxidation of the antimony center leads to a lowering of the accepting σ* orbital and a deeper carving of the associated σ‐hole.
Taking a dig at the σ‐hole! Oxidation of organoantimony derivatives from the +III to the +V state leads to a more pronounced σ‐hole on antimony, thereby making these main‐group compounds better pnictogen bond donors or better Lewis acids. These results, which can be rationalized using orbital‐based arguments, offer a new strategy for tuning the magnitude of pnictogen bonding and have applications in catalysis.
In search of a molecular receptor that could bind fluoride ions in water below the maximum contaminant level of 4 ppm set by the Environmental Protection Agency (EPA), we have investigated the water ...stability and fluoride binding properties of a series of phosphonium boranes of general formula p-(Mes2B)C6H4(PPh2R)+ with R = Me (1+), Et (2+), n-Pr (3+), and Ph (4+). These phosphonium boranes are water stable and react reversibly with water to form the corresponding zwitterionic hydroxide complexes of general formula p-(Mes2(HO)B)C6H4(PPh2R). They also react with fluoride ions to form the corresponding zwitterionic fluoride complexes of general formula p-(Mes2(F)B)C6H4(PPh2R). Spectrophotometric acid−base titrations carried out in H2O/MeOH (9:1 vol.) afford pK R+ values of 7.3(±0.07) for 1+, 6.92(±0.1) for 2+, 6.59(±0.08) for 3+, and 6.08(±0.09) for 4+, thereby indicating that the Lewis acidity of the cationic boranes increases in following order: 1+ < 2+ < 3+ < 4+. In agreement with this observation, fluoride titration experiments in H2O/MeOH (9:1 vol.) show that the fluoride binding constants (K = 840(±50) M−1 for 1+, 2500(±200) M−1 for 2+, 4000(±300) M−1 for 3+, and 10 500(±1000) M−1 for 4+) increase in the same order. These results show that the Lewis acidity of the cationic boranes increases with their hydrophobicity. The resulting Lewis acidity increase is substantial and exceeds 1 order of magnitude on going from 1+ to 4+. In turn, 4+ is sufficiently fluorophilic to bind fluoride ions below the EPA contaminant level in pure water. These results indicate that phosphonium boranes related to 4+ could be used as molecular recognition units in chemosensors for drinking water analysis.
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