Swedish e Science Research Center

Stockholm, Sweden

Swedish e Science Research Center

Stockholm, Sweden
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Koenigk T.,Swedish Meteorological and Hydrological Institute | Koenigk T.,University of Stockholm | Koenigk T.,Swedish e Science Research Center | Caian M.,Swedish Meteorological and Hydrological Institute | And 2 more authors.
Climate Dynamics | Year: 2016

Seasonal prediction skill of winter mid and high northern latitudes climate from sea ice variations in eight different Arctic regions is analyzed using detrended ERA-interim data and satellite sea ice data for the period 1980–2013. We find significant correlations between ice areas in both September and November and winter sea level pressure, air temperature and precipitation. The prediction skill is improved when using November sea ice conditions as predictor compared to September. This is particularly true for predicting winter NAO-like patterns and blocking situations in the Euro-Atlantic area. We find that sea ice variations in Barents Sea seem to be most important for the sign of the following winter NAO—negative after low ice—but amplitude and extension of the patterns are modulated by Greenland and Labrador Seas ice areas. November ice variability in the Greenland Sea provides the best prediction skill for central and western European temperature and ice variations in the Laptev/East Siberian Seas have the largest impact on the blocking number in the Euro-Atlantic region. Over North America, prediction skill is largest using September ice areas from the Pacific Arctic sector as predictor. Composite analyses of high and low regional autumn ice conditions reveal that the atmospheric response is not entirely linear suggesting changing predictive skill dependent on sign and amplitude of the anomaly. The results confirm the importance of realistic sea ice initial conditions for seasonal forecasts. However, correlations do seldom exceed 0.6 indicating that Arctic sea ice variations can only explain a part of winter climate variations in northern mid and high latitudes. © 2015, The Author(s).


Canton J.,KTH Royal Institute of Technology | Canton J.,Swedish e Science Research Center | Orlu R.,KTH Royal Institute of Technology | Schlatter P.,KTH Royal Institute of Technology | Schlatter P.,Swedish e Science Research Center
International Journal of Heat and Fluid Flow | Year: 2017

This work is concerned with a detailed investigation of the steady (laminar), incompressible flow inside bent pipes. In particular, a toroidal pipe is considered in an effort to isolate the effect of the curvature, δ, on the flow features, and to compare the present results to available correlations in the literature. More than 110 000 numerical solutions are computed, without any approximation, spanning the entire curvature range, 0 ≤ δ ≤ 1, and for bulk Reynolds numbers Re up to 7 000, where the flow is known to be unsteady. Results show that the Dean number De provides a meaningful non-dimensional group only below very strict limits on the curvature and the Dean number itself. For δ>10−6 and De > 10, in fact, not a single flow feature is found to scale well with the Dean number. These considerations are also valid for quantities, such as the Fanning friction factor, that were previously considered Dean-number dependent only. The flow is therefore studied as a function of two equally important, independent parameters: the curvature of the pipe and the Reynolds number. The analysis shows that by increasing the curvature the flow is fundamentally changed. Moderate to high curvatures are not only quantitatively, but also qualitatively different from low δ cases. A complete description of some of the most relevant flow quantities is provided. Most notably the friction factor f for laminar flow in curved pipes by Ito [J. Basic Eng. 81:123–134 (1959)] is reproduced, the influence of the curvature on f is quantified and the scaling is discussed. A complete database including all the computed solutions is available at www.flow.kth.se. © 2017 Elsevier Inc.


Popovic J.,KTH Royal Institute of Technology | Runborg O.,Swedish e Science Research Center
BIT Numerical Mathematics | Year: 2011

We propose and analyze a fast method for computing the solution of the high frequency Helmholtz equation in a bounded one-dimensional domain with a variable wave speed function. The method is based on wave splitting. The Helmholtz equation is split into one-way wave equations with source functions which are solved iteratively for a given tolerance. The source functions depend on the wave speed function and on the solutions of the one-way wave equations from the previous iteration. The solution of the Helmholtz equation is then approximated by the sum of the one-way solutions at every iteration. To improve the computational cost, the source functions are thresholded and in the domain where they are equal to zero, the one-way wave equations are solved with geometrical optics with a computational cost independent of the frequency. Elsewhere, the equations are fully resolved with a Runge-Kutta method. We have been able to show rigorously in one dimension that the algorithm is convergent and that for fixed accuracy, the computational cost is asymptotically just O(ω 1/p) for a pth order Runge-Kutta method, where ω is the frequency. Numerical experiments indicate that the growth rate of the computational cost is much slower than a direct method and can be close to the asymptotic rate. © 2011 Springer Science + Business Media B.V.


Rodriguez D.,Science for Life Laboratory | Rodriguez D.,Swedish e Science Research Center | Rodriguez D.,University of Stockholm | Ranganathan A.,Science for Life Laboratory | And 5 more authors.
Current Topics in Medicinal Chemistry | Year: 2015

G protein-coupled receptors (GPCRs) constitute the largest group of human membrane proteins and have received significant attention in drug discovery for their important roles in physiological processes. Drug development for GPCRs has been remarkably successful and several of the most profitable pharmaceuticals on the market target members of this superfamily. Breakthroughs in structural biology for GPCRs have revealed how their binding sites recognize extracellular molecules at the atomic level. High-resolution crystal structures of GPCR-drug complexes capturing different receptor conformations are now available, which have provided insights into how ligands stabilize different functional states. Recently, the basis for subtype selectivity and novel allosteric binding sites has also been revealed by crystal structures. These accomplishments provide exciting opportunities to identify novel GPCR ligands using in silico structure-based methods such as molecular docking. Increased computational power now enables docking screens of large chemical libraries to identify molecules that complement GPCR binding sites, which may provide possibilities to identify ligands with tailored pharmacological properties. This review focuses on prospective docking screens against GPCRs and how this technique can be used to identify lead candidates with specific signaling or selectivity profiles. The current state of this field suggests that molecular docking, in combination with further understanding of GPCR signaling, will play an important role in future drug discovery. © 2015 Bentham Science Publishers.


Uziela K.,University of Stockholm | Wallner B.,Linköping University | Wallner B.,Swedish e Science Research Center
Bioinformatics | Year: 2016

Motivation: Model quality assessment programs are used to predict the quality of modeled protein structures. They can be divided into two groups depending on the information they are using: ensemble methods using consensus of many alternative models and methods only using a single model to do its prediction. The consensus methods excel in achieving high correlations between prediction and true quality measures. However, they frequently fail to pick out the best possible model, nor can they be used to generate and score new structures. Single-model methods on the other hand do not have these inherent shortcomings and can be used both to sample new structures and to improve existing consensus methods. Results: Here, we present an implementation of the ProQ2 program to estimate both local and global model accuracy as part of the Rosetta modeling suite. The current implementation does not only make it possible to run large batch runs locally, but it also opens up a whole new arena for conformational sampling using machine learned scoring functions and to incorporate model accuracy estimation in to various existing modeling schemes. ProQ2 participated in CASP11 and results from CASP11 are used to benchmark the current implementation. Based on results from CASP11 and CAMEO-QE, a continuous benchmark of quality estimation methods, it is clear that ProQ2 is the single-model method that performs best in both local and global model accuracy. © The Author 2016. Published by Oxford University Press.


Wallner B.,Linköping University | Wallner B.,Swedish e Science Research Center
Bioinformatics | Year: 2014

Summary: Model Quality Assessment Programs (MQAPs) are used to predict the quality of modeled protein structures. These usually use two approaches: methods using consensus of many alternative models and methods requiring only a single model to do its prediction. The consensus methods are useful to improve overall accuracy; however, they frequently fail to pick out the best possible model and cannot be used to generate and score new structures. Single-model methods, on the other hand, do not have these inherent shortcomings and can be used to both sample new structures and improve existing consensus methods. Here, we present ProQM-resample, a membrane protein-specific single-model MQAP, that couples side-chain resampling with MQAP rescoring by ProQM to improve model selection. The side-chain resampling is able to improve side-chain packing for 96% of all models, and improve model selection by 24% as measured by the sum of the Z-score for the first-ranked model (from 25.0 to 31.1), even better than the state-of-the-art consensus method Pcons. The improved model selection can be attributed to the improved side-chain quality, which enables the MQAP to rescue good backbone models with poor side-chain packing. Availability and implementation: http://proqm.wallnerlab.org/download/. © The Author 2014.


Engstrom A.,University of Stockholm | Engstrom A.,Swedish e Science Research Center | Karlsson J.,University of Stockholm | Svensson G.,University of Stockholm | Svensson G.,Swedish e Science Research Center
Journal of Climate | Year: 2014

Observations from the Surface Heat Budget of the Arctic Ocean experiment (SHEBA) suggest that the Arctic Basin is characterized by two distinctly different preferred atmospheric states during wintertime. These states appear as two peaks in the frequency distribution of surface downwelling longwave radiation (LWD), representing radiatively clear and opaque conditions. Here, the authors have investigated the occurrence and representation of these states in the widely used ECMWF Interim Re-Analysis (ERA-Interim) dataset. An interannually recurring bimodal distribution of LWDvalues is not a clearly observable feature in the reanalysis data. However, large differences in the simulated liquid water content of clouds in ERA-Interim compared to observations are identified and these are linked to the lack of a radiatively opaque peak in the reanalysis. Using a single-column model, dynamically controlled by data fromERA-Interim, the authors show that, by tuning the glaciation speed of supercooled liquid clouds, it is possible to reach a very good agreement between the model and observations from the SHEBA campaign in terms of LWD. The results suggest that the presence of two preferred Arctic states, as observed during SHEBA, is a recurring feature of the Arctic climate system during winter [December-March (DJFM)]. The mean increase in LWD during the Arctic winter compared to ERAInterim is 15Wm-2. This has a substantial bearing on climate model evaluation in the Arctic as it indicates the importance of representing Arctic states in climate models and reanalysis data and that doing so could have a significant impact on winter ice thickness and surface temperatures in the Arctic. © 2014 American Meteorological Society.


Lindvall J.,University of Stockholm | Lindvall J.,Swedish e Science Research Center | Svensson G.,University of Stockholm | Svensson G.,Swedish e Science Research Center | And 2 more authors.
Climate Dynamics | Year: 2016

Simulations with the Community Atmosphere Model version 5 (CAM5) are used to analyze the sensitivity of the large-scale circulation to changes in parameterizations of orographic surface drag and vertical diffusion. Many GCMs and NWP models use enhanced turbulent mixing in stable conditions to improve simulations, while CAM5 cuts off all turbulence at high stabilities and instead employs a strong orographic surface stress parameterization, known as turbulent mountain stress (TMS). TMS completely dominates the surface stress over land and reduces the near-surface wind speeds compared to simulations without TMS. It is found that TMS is generally beneficial for the large-scale circulation as it improves zonal wind speeds, Arctic sea level pressure and zonal anomalies of the 500-hPa stream function, compared to ERA-Interim. It also alleviates atmospheric blocking frequency biases in the Northern Hemisphere. Using a scheme that instead allows for a modest increase of turbulent diffusion at higher stabilities only in the planetary boundary layer (PBL) appears to in some aspects have a similar, although much smaller, beneficial effect as TMS. Enhanced mixing throughout the atmospheric column, however, degrades the CAM5 simulation. Evaluating the simulations in comparison with detailed measurements at two locations reveals that TMS is detrimental for the PBL at the flat grassland ARM Southern Great Plains site, giving too strong wind turning and too deep PBLs. At the Sodankylä forest site, the effect of TMS is smaller due to the larger local vegetation roughness. At both sites, all simulations substantially overestimate the boundary layer ageostrophic flow. © 2016 The Author(s)


Light S.,University of Stockholm | Basile W.,University of Stockholm | Elofsson A.,University of Stockholm | Elofsson A.,Swedish e Science Research Center
Current Opinion in Structural Biology | Year: 2014

The frequency of de novo creation of proteins has been debated. Early it was assumed that de novo creation should be extremely rare and that the vast majority of all protein coding genes were created in early history of life. However, the early genomics era lead to the insight that protein coding genes do appear to be lineage-specific. Today, with thousands of completely sequenced genomes, this impression remains. It has even been proposed that the creation of novel genes, a continuous process where most de novo genes are short-lived, is as frequent as gene duplications. There exist reports with strongly indicative evidence for de novo gene emergence in many organisms ranging from Bacteria, sometimes generated through bacteriophages, to humans, where orphans appear to be overexpressed in brain and testis. In contrast, research on protein evolution indicates that many very distantly related proteins appear to share partial homology. Here, we discuss recent results on de novo gene emergence, as well as important technical challenges limiting our ability to get a definite answer to the extent of de novo protein creation. © 2014 Elsevier Ltd.


Light S.,University of Stockholm | Elofsson A.,University of Stockholm | Elofsson A.,Swedish e Science Research Center
Current Opinion in Structural Biology | Year: 2013

Many proteins are composed of protein domains, functional units of common descent. Multidomain forms are common in all eukaryotes making up more than half of the proteome and the evolution of novel domain architecture has been accelerated in metazoans. It is also becoming increasingly clear that alternative splicing is prevalent among vertebrates. Given that protein domains are defined as structurally, functionally and evolutionarily distinct units, one may speculate that some alternative splicing events may lead to clean excisions of protein domains, thus generating a number of different domain architectures from one gene template. However, recent findings indicate that smaller alternative splicing events, in particular in disordered regions, might be more prominent than domain architectural changes.The problem of identifying protein isoforms is, however, still not resolved. Clearly, many splice forms identified through detection of mRNA sequences appear to produce 'nonfunctional' proteins, such as proteins with missing internal secondary structure elements. Here, we review the state of the art methods for identification of functional isoforms and present a summary of what is known, thus far, about alternative splicing with regard to protein domain architectures. © 2013 Elsevier Ltd.

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