An empirical parameterization of subsurface entrainment temperature for improved SST anomaly simulations in an intermediate ocean model

An empirical model for the temperature of subsurface water entrained into the ocean mixed layer (Te) is presented and evaluated to improve sea surface temperature anomaly (SSTA) simulations in an intermediate ocean model (IOM) of the tropical Pacific. An inverse modeling approach is adopted to estimate Te from an SSTA equation using observed SST and simulated upper-ocean currents. A relationship between Te and sea surface height (SSH) anomalies is then obtained by utilizing a singular value decomposition (SVD) of their covariance. This empirical scheme is able to better parameterize Te anomalies than other local schemes and quite realistically depicts interannual variability of Te, including a nonlocal phase lag relation of Te variations relative to SSH anomalies over the central equatorial Pacific. An improved Te parameterization naturally leads to better depiction of the subsurface effect on SST variability by the mean upwelling of subsurface temperature anomalies. As a result, SSTA simulations are significantly improved in the equatorial Pacific; a comparison with other schemes indicates that systematic errors of the simulated SSTAs are significantly small—apparently due to the optimized empirical Teparameterization. Cross validation and comparisons with other model simulations are made to illustrate the robustness and effectiveness of the scheme. In particular it is demonstrated that the empirical Te model constructed from one historical period can be successfully used to improve SSTA simulations in another

Retrospective El Niño hindcasts/forecasts using an improved intermediate coupled model

A new intermediate coupled model (ICM) is presented and employed to make retrospective predictions of tropical Pacific sea surface temperature (SST) anomalies. The ocean dynamics is an extension of the McCreary baroclinic modal model to include varying stratification and certain nonlinear effects. A standard configuration is chosen with 10 baroclinic modes plus two surface layers, which are governed by Ekman dynamics and simulate the combined effects of the higher baroclinic modes from 11 to 30. A nonlinear correction associated with vertical advection of zonal momentum is incorporated and applied (diagnostically) only within the two surface layers, forced by the linear part through nonlinear advection terms. As a result of these improvements, the model realistically simulates the mean equatorial circulation and its variability. The ocean thermodynamics include an SST anomaly model with an empirical parameterization for the temperature of subsurface water entrained into the mixed layer (Te), which is optimally calculated in terms of sea surface height (SSH) anomalies using an empirical orthogonal function (EOF) analysis technique from historical data. The ocean model is then coupled to a statistical atmospheric model that estimates wind stress (τ) anomalies based on a singular value decomposition (SVD) analysis between SST anomalies observed and τ anomalies simulated from ECHAM4.5 (24-member ensemble mean). The coupled system exhibits realistic interannual variability associated with El Niño, including a predominant standing pattern of SST anomalies along the equator and coherent phase relationships among different atmosphere–ocean anomaly fields with a dominant 3-yr oscillation period. Twelve-month hindcasts/forecasts are made during the period 1963–2002, starting each month. Only observed SST anomalies are used to initialize the coupled predictions. As compared to other prediction systems, this coupled model has relatively small systematic errors in the predicted SST anomalies, and its SST prediction skill is apparently competitive with that of most advanced coupled systems incorporating sophisticated ocean data assimilation. One striking feature is that the model skill surpasses that of persistence at all lead times over the central equatorial Pacific. Prediction skill is strongly dependent on the season, with the correlations attaining a minimum in spring and a maximum in fall. Cross-validation experiments are performed to examine the sensitivity of the prediction skill to the data periods selected for training the empirical Te model. It is demonstrated that the artificial skill introduced by using a dependently constructed Te model is not significant. Independent forecasts are made for the period 1997–2002 when no dependent data are included in constructing the two empirical models (Te and τ). The coupled model has reasonable success in predicting transition to warm phase and to cold phase in the spring of 1997 and 1998, respectively. Potential problems and further improvements are discussed with the new intermediate prediction system

Measures of observation impact in non-Gaussian data assimilation

ABSTRACT Non-Gaussian/non-linear data assimilation is becoming an increasingly important area of research in the Geosciences as the resolution and non-linearity of models are increased and more and more non-linear observation operators are being used. In this study, we look at the effect of relaxing the assumption of a Gaussian prior on the impact of observations within the data assimilation system. Three different measures of observation impact are studied: the sensitivity of the posterior mean to the observations, mutual information and relative entropy. The sensitivity of the posterior mean is derived analytically when the prior is modelled by a simplified Gaussian mixture and the observation errors are Gaussian. It is found that the sensitivity is a strong function of the value of the observation and proportional to the posterior variance. Similarly, relative entropy is found to be a strong function of the value of the observation. However, the errors in estimating these two measures using a Gaussian approximation to the prior can differ significantly. This hampers conclusions about the effect of the non-Gaussian prior on observation impact. Mutual information does not depend on the value of the observation and is seen to be close to its Gaussian approximation. These findings are illustrated with the particle filter applied to the Lorenz ’63 system. This article is concluded with a discussion of the appropriateness of these measures of observation impact for different situations

N-ftaloil-glicin-hidroksamska kiselina kao kelator željeza u serumu štakora

The aim of this study was to investigate the activity of N-phthaloyl-glycine-hydroxamic acid (Phth-Gly-HA) as a new iron chelator in vivo to be used in iron overload diseases. After intraperitoneal application of Phth-Gly-HA to male rats (1 mg kg1 body mass) once a day for seven days, iron serum level decreased by 21%, whereas the iron value dropped by 32% in female rats (1.5 mg kg1 body mass). The results indicate that the tested substance has the ability to bind serum iron by complexation. Besides transferrin iron release, mobilization of ferritin iron is also possibleU cilju pronalaženja novog efikasnog kelatora koji bi mogao poslužiti u liječenju bolesti izazvanih viškom željeza, u ovom je radu ispitano djelovanje N-ftaloil-glicin-hidroksamske kiseline (Phth-Gly-HA) in vivo. Istraživan je utjecaj kelatora na razinu željeza u serumu štakora nakon intraperitonealne primjene vodene otopine Phth-Gly-HA (0,1 mg mL1) jednom dnevno tijekom 7 dana. Kontrolne su životinje primale fiziološku otopinu. Kod mužjaka injektiranje test supstancije (1 mg kg1) uzrokovalo je pad serumskog željeza za 21%. Kod ženki je nakon tretmana (1,5 mg kg1) izmjereno sniženje razine željeza za 35%. Rezultati pokazuju da ispitivana supstanca ima sposobnost kompleksiranja serumskog željeza, pretežno transferinskog, ali da postoji mogućnost mobilizacije željeza i iz feritinskih zaliha

Early Neutrophilia Marked by Aerobic Glycolysis Sustains Host Metabolism and Delays Cancer Cachexia

An elevated neutrophil–lymphocyte ratio negatively predicts the outcome of patients with cancer and is associated with cachexia, the terminal wasting syndrome. Here, using murine model systems of colorectal and pancreatic cancer we show that neutrophilia in the circulation and multiple organs, accompanied by extramedullary hematopoiesis, is an early event during cancer progression. Transcriptomic and metabolic assessment reveals that neutrophils in tumor-bearing animals utilize aerobic glycolysis, similar to cancer cells. Although pharmacological inhibition of aerobic glycolysis slows down tumor growth in C26 tumor-bearing mice, it precipitates cachexia, thereby shortening the overall survival. This negative effect may be explained by our observation that acute depletion of neutrophils in pre-cachectic mice impairs systemic glucose homeostasis secondary to altered hepatic lipid processing. Thus, changes in neutrophil number, distribution, and metabolism play an adaptive role in host metabolic homeostasis during cancer progression. Our findings provide insight into early events during cancer progression to cachexia, with implications for therapy

Children and Virtual Reality: Emerging Possibilities and Challenges

Virtual Reality is fast becoming a reality, with estimates that over 200m headsets will have been sold by 2020, and the market value for VR hardware and software reaching well over $20bn by then. Key players in the market currently include PlayStation with PSVR, Facebook with Oculus Rift, Google Cardboard and Daydream, Mattel with Viewmaster, and many other brands investing in content production for various audiences. One of those audiences is young people and children. “Children and Virtual Reality” is a collaboration between Dubit, Turner, WEARVR and the COST (European Cooperation in Science and Technology) Action DigiLitEY. Dubit, Turner and WEARVR are companies that specialise in digital, TV and VR content, with an interest in developing best practices around VR and children. DigiLitEY is a five year (2013-2017) academic network that focuses on existing and emerging communicative technologies for young children. This includes wearable technologies, 3D printers, robots, augmented reality, toys and games and relevant aspects of the Internet of Things. This report brings together industry research into the effects of VR on 8 to 12 year olds, and ideas that arose from a COST funded Think Tank to explore what the research findings might mean for the use of VR by under 8s

Anterior colporrhaphy does not induce bladder outlet obstruction

We aimed to evaluate if anterior colporrhaphy causes incomplete voiding due to bladder outlet obstruction. Women scheduled for anterior colporrhaphy were asked to undergo multichannel urodynamic investigation before surgery and the first postoperative day. Bladder outlet obstruction was assessed using the Blaivas-Groutz voiding nomogram. Maximum flow rate, detrusor pressure and residual volume were compared between pre- and postoperative measurements and between women with and without an abnormal post-void residual volume (PVR; volume exceeding 150 ml). Seventeen women participated. One woman who was unobstructed before surgery was obstructed after surgery. Overall, detrusor pressure and maximum flow rate before and after surgery did not differ. After surgery, six women had an abnormal PVR, one was unable to void, four were mildly obstructed and one moderately obstructed. Urodynamic investigation the first day after anterior colporrhaphy did not show that anterior colporrhaphy induces bladder outlet obstruction. The explanation for postoperative urinary retention can therefore also lie in non-anatomical causes such as postoperative pain and psychological factor

A review of the predictability and prediction of ENSO

A hierarchy of El Niño-Southern Oscillation (ENSO) prediction schemes has been developed during the Tropical Ocean-Global Atmosphere (TOGA) program which includes statistical schemes and physical models. The statistical models are, in general, based on linear statistical techniques and can be classified into models which use atmospheric (sea level pressure or surface wind) or oceanic (sea surface temperature or a measure of upper ocean heat content) quantities or a combination of oceanic and atmospheric quantities as predictors. The physical models consist of coupled ocean-atmosphere models of varying degrees of complexity, ranging from simplified coupled models of the “shallow water” type to coupled general circulation models. All models, statistical and physical, perform considerably better than the persistence forecast in predicting typical indices of ENSO on lead times of 6 to 12 months. The TOGA program can be regarded as a success from this perspective. However, despite the demonstrated predictability, little is known about ENSO predictability limits and the predictability of phenomena outside the tropical Pacific. Furthermore, the predictability of anomalous features known to be associated with ENSO (e.g., Indian monsoon and Sahel rainfall, southern African drought, and off-equatorial sea surface temperature) needs to be addressed in more detail. As well, the relative importance of different physical mechanisms (in the ocean or atmosphere) has yet to be established. A seasonal dependence in predictability is seen in many models, but the processes responsible for it are not fully understood, and its meaning is still a matter of scientific discussion. Likewise, a marked decadal variation in skill is observed, and the reasons for this are still under investigation. Finally, the different prediction models yield similar skills, although they are initialized quite differently. The reasons for these differences are also unclear