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Regional climate is affected by a wide variety of aerosols which modify through their radiative effects the precipitation distribution. In this article, the effects of aerosols, mainly dust aerosols on diurnal cycle of precipitation amount, frequency and intensity are investigated over central Africa by using the latest version of the Abdu Salam ICTP regional climate model coupled with the Community Land Model 4.5 as land surface scheme. Two sets of experiments have been conducted (one with aerosols interaction with dynamics and thermodynamics processes and another without this interaction) for a 10-year study period (2002–2011) and the Fourier transformation is used to study the 24-h cycle. In order to clearly understand spatial differences in RegCM experiments over central Africa, three subregions have been considered according to their land cover and climate characteristics. Our results indicate that the pattern of simulated aerosol optical depth (AOD) is well represented particularly northward of the study region compared to AOD from moderate resolution imaging spectroradiometer (MODIS) even if some differences in terms of magnitude are reported. The aerosols' effects on diurnal cycle are generally not similar to those found in the amplitude and phase. The result pointed out that over the Sahelian region, atmospheric aerosol in general and dust in particular always induced a positive effect on diurnal cycle (increase the magnitude of the cycle) of precipitation intensities and in precipitation amount and precipitation frequency as well. But, the change is opposite in terms of amplitude and peak time over some subregions. It appears that the forcing of aerosols in solar radiation as well as in latent heat flux leads to the changes in the amplitude of the precipitation amount during the DJF and JAS seasons particularly during daytime. The changes in amplitude of the precipitation frequency are not consistent even if the corresponding phase always tends to increase by up to 5 h. [ABSTRACT FROM AUTHOR]

A recently launched project under the auspices of the World Climate Research Program's (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-of-its-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both "weather-like" (WL, initialized just before the event in question) and "climate" (CM, initialized 1 month before the event) modes. Ensembles of 18–21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land–ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes. [ABSTRACT FROM AUTHOR]

Cultivating native lands may alter soil phosphorus (P) distribution and availability. The present study aimed to determine the distribution of P in soil aggregates for different long-term land management practices. The partitioned P in labile (L), Fe/Al-bound, Ca-bound, organic pools, and total P in four aggregate size fractions were determined for five land uses (forest, vineyard after 30 years, wetland, alfalfa, and wheat cultivated soil after 20 years). Both native land uses (forest and wetland) were distinguished by high and low amounts of large macro- and micro-aggregates, respectively, compared with disturbed soils (vineyard, alfalfa, and wheat soils). Labile P in large macro-aggregates were higher in native land use when compared with the other land uses, which led to increasing lability of P and accelerated water pollution. Soils under native conditions sequestered more Ca-bound P in large macro-aggregates than the soils in disturbed conditions. Conversion of native lands to agricultural land caused enhanced organic P storage in aggregates smaller than the 2 mm from 31.0 to 54.3 %. Soils under forest had 30 % total P more than the vineyard for the aggregates >2 mm after 30 years land use change. However, the amount of P in smaller (<2 mm) sized aggregates was increased by 29 % for the vineyard when compared with the forest. The P storage as bound Ca particles for the large macro-aggregates had negative correlation with the micro-aggregates. [ABSTRACT FROM AUTHOR]

The usefulness of two remotely sensed variables, land surface temperature (LST) and cloud cover (CC), as predictors for the gridding of daily maximum and minimum 2 m temperature ( T/ T) was assessed. Four similar gridding methods were compared, each of which applied regression kriging to capture the spatial variation explained by the predictors used; however, both methods differed in the interpolation steps performed and predictor combinations used. The robustness of the gridding methods was tested for daily observations in January and July in the period 2009-2011 and in two different regions: the Central European region (CER) and the Iberian Peninsula (IP). Moreover, the uncertainty estimate provided by each method was evaluated using cross-validation. The regression analyses for both regions demonstrated the high predictive skills of LST for T and T on daily and monthly timescales (and lower predictive skills of CC). The application of LST as a predictor considerably improved the gridding performance over the IP region in July; however, there was only a slight improvement over the CER region. CC reduced the loss of spatial variability in the interpolated daily T/ T values over the IP region. The interpolation skill was mainly controlled by the station density, but also depended on the complexity of the terrain. LST was shown to be of particular value for very low station densities (1 station per 50,000 km). Analyses with artificially decreasing station densities showed that even in the case of very low station densities, LST allows the determination of useful regression functions. [ABSTRACT FROM AUTHOR]

We developed an operationally applicable land-only daily high-resolution (5 km × 5 km) gridding method for station observations of minimum and maximum 2 m temperature ( T/ T) for Europe (WMO region VI). The method involves two major steps: (1) the generation of climatological T/ T maps for each month of the year using block regression kriging, which considers the spatial variation explained by applied predictors; and (2) interpolation of transformed daily anomalies using block kriging, and combination of the resulting anomaly maps with climatological maps. To account for heterogeneous climatic conditions in the estimation of the statistical parameters, these steps were applied independently in overlapping climatic subregions, followed by an additional spatial merging step. Uncertainties in the gridded maps and the derived error maps were quantified: (a) by cross-validation; and (b) comparison with the T/ T maps estimated in two regions having very dense temperature observation networks. The main advantages of the method are the high quality of the daily maps of T/ T, the calculation of daily error maps and computational efficiency. [ABSTRACT FROM AUTHOR]

The long- and short-wave components of the radiation budget are among the most important quantities in climate modelling. In this study, we evaluated the radiation budget at the earth's surface and at the top of atmosphere over Europe as simulated by the regional climate model CLM. This was done by comparisons with radiation budgets as computed by the GEWEX/SRB satellite-based product and as realised in the ECMWF re-analysis ERA40. Our comparisons show that CLM has a tendency to underestimate solar radiation at the surface and the energy loss by thermal emission. We found a clear statistical dependence of radiation budget imprecision on cloud cover and surface albedo uncertainties in the solar spectrum. In contrast to cloud fraction errors, surface temperature errors have a minor impact on radiation budget uncertainties in the long-wave spectrum. We also evaluated the impact of the number of atmospheric layers used in CLM simulations. CLM simulations with 32 layers perform better than do those with 20 layers in terms of the surface radiation budget components but not in terms of the outgoing long-wave radiation and of radiation divergence. Application of the evaluation approach to similar simulations with two additional regional climate models confirmed the results and showed the usefulness of the approach. [ABSTRACT FROM AUTHOR]

One of the main objectives of numerical weather prediction models is reliable forecasting of heavy rain events. This paper discusses problems and strategies of evaluation of daily rain forecasting with operationally available rain station data. The focus is on spatial upscaling of rain station data to the grid of the direct model output. We show limitations of regression – or smoothing – based upscaling like as done, for example, by Kriging analysis and promote probabilistic upscaling by ensembles of stochastic simulations conditioned to the available observations. These ensembles easily provide uncertainties of daily evaluation and unbiased estimates for second moment comparison statistics. As an evaluation exercise we assess the quality of daily forecasts for Austria (total area: 84,000 km2) with the limited-area model ALADIN (horizontal grid-spacing 10 km). A quasi–operational set-up is compared to a physically enhanced but less well tested and tuned set-up. It is shown that the evaluation uncertainty is large, but with a full year of forecasts available it is possible to conclude that the physically enhanced set-up simulates too much rain and significantly more than the operational version with only small differences in simulated patterns and variability. [ABSTRACT FROM AUTHOR]

Background. A robust association between “suicidality” and deficits of the serotoninergic neurotransmission has been claimed in the past. However, many studies having investigated the relationship between suicidality and peripheral indicators of serotoninergic neurotransmission suffer from considering only one or a very small number of potentially useful serotoninergic parameters, whereas a synoptic multidimensional approach appears to be more appropriate. Furthermore, the psychiatric context within which suicidal behaviour occurs should be considered when interpreting biochemical findings of patients with suicidal ideation and suicide attempts. Methods. In the present study 5 peripheral serotonergic markers, (platelet 5HT concentration, 5HT uptake activity, 5HT2A receptor binding characteristics, MAO-B activity and tryptophan concentration in plasma) were assessed simultaneously. Of the 60 acutely suicidal inpatients (ICD-10: F43.xx, n = 52; F31/32/33, n = 8), 45 were suicide attempters. Data of 28 nonsuicidal patients with major depression (F31, n = 4; F32, n = 14; F33, n = 10) and 123 healthy volunteers represented the control groups. Results. Mean platelet 5HT concentration was significantly lower in suicidal inpatients when compared to nonsuicidal depressed patients, but did not differ from the figure in healthy subjects. Nonsuicidal depressed patients showed significantly higher mean platelet-5HT concentration than healthy controls. Mean Vmax of 5HT uptake in washed platelets, but not in platelet-rich plasma, was significantly higher in suicidal patients than in healthy controls, not, however, when compared to nonsuicidal depressed patients. Mean KD for the platelet 5HT2A receptor and MAO-B activity were significantly lower in suicidal patients as compared to nonsuicidal depressed patients and healthy controls. The observed differences in peripheral serotonergic markers between groups are partially due to a significant gender effect. A lower MAO-B activity was observed only in suicidal females, while the higher Vmax of 5HT uptake in washed platelets of suicidal patients was due to suicidal males. Conclusions. In view of conflicting observations made by other authors and the present findings on suicidal patients with adjustment disorder it remains doubtful whether and if so to which extent platelet studies can provide valid information on serotonergic mechanisms related to suicidal behaviour. [ABSTRACT FROM AUTHOR]

Deals with a study that assesses the dimensional and categorical aspects of depression. Background on the Association for Methodology and Documentation in Psychiatry-Depression Scale (AMDP-DS); Development of the scale; Methods applied in the study; Result of the study; Conclusion.

Diagnostic time-mean budgets of energy and water are evaluated in many atmospheric process studies. The errors of budget-derived quantities like sub-gridscale fluxes or diabatic heating are governed by the errors of the budgets. Here we consider 3D-budgets on the meso-β scale over Europe. They are compiled from analyses of state quantities available from forecast centres. In the present study we found that the mandatory 6 hours sampling interval between synoptic observations is the main error source for routine time-mean budgets. The errors have been quantified (i) by first sampling forecast data of the German Europamodell every 5 minutes and averaging them over 12 hours ( reference budget), and (ii) by sampling the same data only every 6 hours and averaging these also over 12 hours ( routine budget). With this method we find that routine budgets in single atmospheric meso-β scale columns show relative random errors of typically 200% and systematic errors of up to 20%, exclusively due to undersampling. Thus routine budgets, if applied to specific days at individual locations, cannot be expected to yield useful results, except perhaps for cases with extremely strong signal. Compositing over several hundreds of columns with similar weather reduces the random budget error down to about 50%; this seems to be the best one can achieve for routine budgets. The systematic error of some budget quantities is caused by a correlation between the time of occurence of certain processes (mainly convection) and the sampling times. While this error cannot be reduced through compositing, we find that it can be crudely estimated by using different time averaging methods. As application for this method we determine sub-gridscale budget quantities over the BALTEX catchment (August-September 1995) for an ensemble of convectively active and an ensemble of rain-active columns. For the ensemble mean profiles we find, in terms of the diagnosed sub-gridscale test quantities diabatic heating and vertical moist enthalpy flux divergence, that their accuracy is sufficient to detect statistically significant differences between both ensembles. The diabatic heating is about the same for both ensembles, while the flux divergence in the convective ensemble is about three times as large as in the rain ensemble. [ABSTRACT FROM AUTHOR]

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Several studies have indicated that patients with bipolar disorder (BD) who respond well to lithium prophylaxis constitute a biologically distinct subgroup. Lithium is thought to stablize mood by acting at the phosphoinositide cycle. We have investigated a polymorphism located in the gene (PLCG1) that codes for a γ-1 isozyme of phospholipase (PLC), an enzyme that plays an important role in the phosphoinositide second messenger system. A population-based association study and a family-based linkage study were carried out on patients who were considered excellent responders to lithium prophylaxis. Response to lithium was evaluated prospectively with an average follow-up of 14.4 ± 6.8 years. The PLCG1 polymorphism was investigated in 136 excellent lithium responders and 163 controls. In addition, the segregation of this marker was studied in 32 families ascertained through lithium-responsive bipolar probands. The allele distributions between lithium-responsive bipolar patients and controls were different, with a higher frequency of one of the PLCG1 polymorphisms in patients (χ² = 8.09; empirical P=0.033). This polymorphism, however, confers only a small risk (OR = 1.88, CI 1.19-3.00). Linkage studies with the same marker yielded modest support for the involvement of this gene in the pathogenesis of BD when unilineal families were considered (Max LOD=1.45; empirical P=0.004), but not in the whole sample. Our results provide preliminary evidence that a PLC isozyme may confer susceptibility to bipolar disorder, probably accounting for a fraction of the total genetic variance. Whether this polymorphism is impli- cated in the pathogenesis of BD or in the mechanism of lithium response remains to be determined. [ABSTRACT FROM AUTHOR]

Data assimilation in meteorology and oceanography for strongly nonlinear dynamical systems is challenging. The dynamical system studied here is the classical three-variable Lorenz model. In this context data assimilation with weak-constraint variational methods performs better than other methods like strong-constraint variational methods or Kalman filters. The difficulty in tracking the chaotic Lorenz orbit by assimilation of noisy observations results from the inherent instability in the system. In variational methods a cost function has to be minimized. It is known, that in the Lorenz case the structure of the cost function becomes more and more complex with increasing length of the assimilation time interval and with reduction of the observational data quality. This paper proposes a non-standard implementation of a genetic algorithm for searching the global minimum in case of a weak-constraint formulation. The good performance of this non-local search is shown, but the algorithm is computationally demanding due to a very large number of control parameters within the weak-constraint formulation and, thus, the algorithm is applicable for simple systems only. [ABSTRACT FROM AUTHOR]

The regional atmospheric model REMO is used to study the energy and water exchange between surface and atmosphere over the Baltic Sea and its catchment area. As a prerequisite for such studies, the model has to be validated. A major part of such a validation is the comparison of simulation results with observational data. In this study the DX product of the International Cloud Climatology Project (ISCCP) and precipitation measurements from 7775 rain gauge stations within the model domain are used for comparisons with the simulated cloud cover and precipitation fields, respectively. The observations are available in this high spatiotemporal resolution for June 1993. To quantify the comparisons of means, variability, and patterns of the data fields simple statistics are used and the significance of the results is determined with resampling methods (Pool Permutation Procedure and Bootstrap-t). The conclusion is that simulated and observed means of the fields are not different at the 5% significance level. The determined variability of the fields is also in good agreement except the space variability in cloud cover. Time mean and anomaly patterns are in good coincidence in case of the comparisons of cloud cover fields, but in reduced coincidence in case of precipitation. [ABSTRACT FROM AUTHOR]

Focuses on the role of polyglutamine in bipolar disorder. Response to lithium; Use of the repeat expansion detection technique.

HPTLC (High Performance Thin Layer Chromatography) is a well known and versatile separation method which shows many advantages when compared to other separation techniques. The method is fast and inexpensive and does not need time-consuming pretreatments. For visualisation of the sample distribution on a HPTLC-plate we developed a new and sturdy HPTLC-scanner. The scanner allows simultaneous registrations of spectra in a range from 198 nm to 612 nm with a spectral resolution of better than 0.8 nm. The on-plate spatial resolution is better than 160 μm. The measurement of 450 spectra in one separation track does not need more than two minutes. The new diode-array scanner offers a fast survey over a TLC-separation and makes various chemometric applications possible. For compound identification a cross-correlation function is described to compare UV sample spectra with appropriate library data. The cross-correlation function herein described can also be used for purity testing. Unresolved peaks can be virtually separated by use of a least squares fit algorithm. In summary, the diode arry system delivers much more information than the commonly used TLC-scanner. [ABSTRACT FROM AUTHOR]