An ensemble approach to assess hydrological models’ contribution to uncertainties in the analysis of climate change impact on water resources

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 5 project (Que´bec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in 10 Southern Que´bec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs’ members over a reference (1971–2000) and a future (2041–2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows

On the need for bias correction in regional climate scenarios to assess climate change impacts on river runoff

In climate change impact research, the assessment of future river runoff as well as the catchment scale water balance is impeded by different sources of modeling uncertainty. Some research has already been done in order to quantify the uncertainty of climate 5 projections originating from the climate models and the downscaling techniques as well as from the internal variability evaluated from climate model member ensembles. Yet, the use of hydrological models adds another layer of incertitude. Within the QBic3 project (Qu´ebec-Bavaria International Collaboration on Climate Change) the relative contributions to the overall uncertainty from the whole model chain (from global climate 10 models to water management models) are investigated using an ensemble of multiple climate and hydrological models. Although there are many options to downscale global climate projections to the regional scale, recent impact studies tend to use Regional Climate Models (RCMs). One reason for that is that the physical coherence between atmospheric and land-surface 15 variables is preserved. The coherence between temperature and precipitation is of particular interest in hydrology. However, the regional climate model outputs often are biased compared to the observed climatology of a given region. Therefore, biases in those outputs are often corrected to reproduce historic runoff conditions from hydrological models using them, even if those corrections alter the relationship between temperature and precipitation. So, as bias correction may affect the consistency between RCM output variables, the use of correction techniques and even the use of (biased) climate model data itself is sometimes disputed among scientists. For those reasons, the effect of bias correction on simulated runoff regimes and the relative change in selected runoff indicators is explored. If it affects the conclusion of climate change analysis in 25 hydrology, we should consider it as a source of uncertainty. If not, the application of bias correction methods is either unnecessary in hydro-climatic projections, or safe to use as it does not alter the change signal of river runoff. The results of the present paper highlight the analysis of daily runoff simulated with four different hydrological models in two natural-flow catchments, driven by different regional climate models for a reference and a future period. As expected, bias correction of climate model outputs is important for the reproduction of the runoff regime of the 5 past regardless of the hydrological model used. Then again, its impact on the relative change of flow indicators between reference and future period is weak for most indicators with the exception of the timing of the spring flood peak. Still, our results indicate that the impact of bias correction on runoff indicators increases with bias in the climate simulations

Reduced-symmetry two-dimensional solitons in photonic lattices

We demonstrate theoretically and experimentally a novel type of localized beams supported by the combined effects of total internal and Bragg reflection in nonlinear two-dimensional square periodic structures. Such localized states exhibit strong anisotropy in their mobility properties, being highly mobile in one direction and trapped in the other, making them promising candidates for optical routing in nonlinear lattices.Comment: 5 pages, 4 figure

Adapting SAM for CDF

The CDF and D0 experiments probe the high-energy frontier and as they do so have accumulated hundreds of Terabytes of data on the way to petabytes of data over the next two years. The experiments have made a commitment to use the developing Grid based on the SAM system to handle these data. The D0 SAM has been extended for use in CDF as common patterns of design emerged to meet the similar requirements of these experiments. The process by which the merger was achieved is explained with particular emphasis on lessons learned concerning the database design patterns plus realization of the use cases.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 4 pages, pdf format, TUAT00

Heavy Flavours in Collider Experiments

Current issues in the studies of Heavy Flavours in colliders are described with particular emphasis on experiments in which the UK is involved. Results on charm production at HERA are examined and compared to those at the Tevatron. B production rates at the Tevatron as well as the status of B lifetimes and mixing in the LEP collaborations and at the Tevatron are highlighted. The measurement of sin2beta from CDF is described as well as the most recent results on top physics at the Tevatron

Examination of the rumen bacteria and methanogenic archaea of wild impalas (Aepyceros melampus melampus) from Pongola, South Africa

Although the rumen microbiome of domesticated ruminants has been evaluated, few studies have explored the rumen microbiome of wild ruminants, and no studies have identified the rumen microbiome in the impala (Aepyceros melampus melampus). In the present study, next-generation sequencing and real-time polymerase chain reaction were used to investigate the diversity and density of the bacteria and methanogenic archaea residing in the rumen of five adult male impalas, culled during the winter dry season in Pongola, South Africa. A total of 15,323 bacterial 16S rRNA gene sequences (from five impala), representing 3,892 different phylotypes, were assigned to 1,902 operational taxonomic units (OTUs). A total of 20,124 methanogen 16S rRNA gene sequence reads (from four impala), of which 5,028 were unique, were assigned to 344 OTUs. From the total sequence reads, Bacteroidetes, Proteobacteria, and Firmicutes were the most abundant bacterial phyla. While the majority of the bacterial genera found were unclassified, Prevotella and Cupriavidus were the most abundant classified genera. For methanogens, the genera Methanobrevibacter and Methanosphaera represented 94.3 % and 4.0 % of the classified sequences, respectively. Most notable was the identification of Methanobrevibacter thaueri-like 16S rRNA gene sequence reads in all four impala samples, representing greater than 30 % of each individual’s total sequences. Both data sets are accessible through NCBI’s Sequence Read Archive (SRA), under study accession number SRP [048619]. The densities of bacteria (1.26×1010–3.82×1010 cells/ml whole rumen contents) and methanogens (4.48×108–7.2×109 cells/ml of whole rumen contents) from five individual impala were similar to those typically observed in domesticated ruminants.http://link.springer.com/journal/2482016-04-30hb201

Rationally designed immunogens enable immune focusing following SARS-CoV-2 spike imprinting

Eliciting antibodies to surface-exposed viral glycoproteins can generate protective responses that control and prevent future infections. Targeting conserved sites may reduce the likelihood of viral escape and limit the spread of related viruses with pandemic potential. Here we leverage rational immunogen design to focus humoral responses on conserved epitopes. Using glycan engineering and epitope scaffolding in boosting immunogens, we focus murine serum antibody responses to conserved receptor binding motif (RBM) and receptor binding domain (RBD) epitopes following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike imprinting. Although all engineered immunogens elicit a robust SARS-CoV-2-neutralizing serum response, RBM-focusing immunogens exhibit increased potency against related sarbecoviruses, SARS-CoV, WIV1-CoV, RaTG13-CoV, and SHC014-CoV; structural characterization of representative antibodies defines a conserved epitope. RBM-focused sera confer protection against SARS-CoV-2 challenge. Thus, RBM focusing is a promising strategy to elicit breadth across emerging sarbecoviruses without compromising SARS-CoV-2 protection. These engineering strategies are adaptable to other viral glycoproteins for targeting conserved epitopes

Autonomous multi-platform observations during the Salinity Processes in the Upper-ocean Regional Study

Author Posting. © The Oceanography Society, 2017. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 30, no. 2 (2017): 38–48, doi:10.5670/oceanog.2017.218.The Salinity Processes in the Upper-ocean Regional Study (SPURS) aims to understand the patterns and variability of sea surface salinity. In order to capture the wide range of spatial and temporal scales associated with processes controlling salinity in the upper ocean, research vessels delivered autonomous instruments to remote sites, one in the North Atlantic and one in the Eastern Pacific. Instruments sampled for one complete annual cycle at each of these two sites, which are subject to contrasting atmospheric forcing. The SPURS field programs coordinated sampling from many different platforms, using a mix of Lagrangian and Eulerian approaches. This article discusses the motivations, implementation, and first results of the SPURS-1 and SPURS-2 programs.SPURS is supported by multiple NASA grants, with important additional contributions from the US National Science Foundation, NOAA, and the Office of Naval Research, as well as international agencies. SVP drifters are deployed with support from NASA and the NOAA funded Global Drifter Program at the Lagrangian Drifter Laboratory of the Scripps Institution of Oceanography. SVP-S2 drifters are provided by NOAA-AOML and NASA. PRAWLER mooring development is supported by NOAA’s Office of Oceanic and Atmospheric Research, Ocean Observing and Monitoring Division, and by NOAA/PMEL

An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic<sup>3</sup> project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e., lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by global climate models over a reference (1971–2000) and a future (2041–2070) period. The results show that, for our hydrological model ensemble, the choice of model strongly affects the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model