Impact of weather and climate on the incidence of acute coronary syndromes

BACKGROUND: First investigations of the interactions between weather and the incidence of acute myocardial infarctions date back to 1938. The early observation of a higher incidence of myocardial infarctions in the cold season could be confirmed in very different geographical regions and cohorts. While the influence of seasonal variations on the incidence of myocardial infarctions has been extensively documented, the impact of individual meteorological parameters on the disease has so far not been investigated systematically. Hence the present study intended to assess the impact of the essential variables of weather and climate on the incidence of myocardial infarctions. METHODS: The daily incidence of myocardial infarctions was calculated from a national hospitalization survey. The hourly weather and climate data were provided by the database of the national weather forecast. The epidemiological and meteorological data were correlated by multivariate analysis based on a generalized linear model assuming a log-link-function and a Poisson distribution. RESULTS: High ambient pressure, high pressure gradients, and heavy wind activity were associated with an increase in the incidence of the totally 6560 hospitalizations for myocardial infarction irrespective of the geographical region. Snow- and rainfall had inconsistent effects. Temperature, Foehn, and lightning showed no statistically significant impact. CONCLUSIONS: Ambient pressure, pressure gradient, and wind activity had a statistical impact on the incidence of myocardial infarctions in Switzerland from 1990 to 1994. To establish a cause-and-effect relationship more data are needed on the interaction between the pathophysiological mechanisms of the acute coronary syndrome and weather and climate variables.

A history and overview of phenotypic variability in CYP2D6 activity

CYP2D6 is a human cytochrome P450 that is responsible for the metabolism of a large number of drugs and chemicals. Interest in CYP2D6 has largely centered on the wide interindividual variability in its catalytic activity that stems from a common genetic polymorphism in the CYP2D6 gene. Two major phenotypes exist, extensive metabolizer (EM) and poor metabolizer (PM), together with the two less studied phenotypes of ultrarapid metabolizer (UM) and intermediate metabolizer. These phenotypes are the expression of an underlying allelomorphism in CYP2D6 and are also context dependent. Several drugs that are CYP2D6 substrates display polymorphic metabolism, that is, the existence in the population of multiple phenotypes, in particular EM and PM. The most notable drugs in this regard are debrisoquine and sparteine, although there are also data for a few others, in particular, dextromethorphan and metoprolol. Many nongenetic factors can alter the expression of CYP2D6 phenotypes, the most significant of which is the presence of other drugs. In this context, the EM phenotype may not be immutable, with potential conversion into a PM phenocopy, due to significantly impaired CYP2D6 metabolism in the presence of other CYP2D6 substrates and inhibitors. This phenotype interconversion generated great concern and helped drive the movement away from phenotyping based upon drug administration to genotyping of acquired DNA samples. However, ascertaining the presence of CYP2D6 alleles in a DNA sample does not determine the metabolism and pharmacokinetics of CYP2D6 substrates in that subject: it is a forecast, much like the weather forecast and, as we all know regarding the weather, the forecast can be inaccurate at times.

A 49 year hindcast of surface winds over the Iberian Peninsula

The use of hindcast climatic data is quite extended for multiple applications. However, this approach needs the support of a validation process to allow its drawbacks and, therefore, confidence levels to be assessed. In this work, the strategy relies on an hourly wind database resulting from a dynamical downscaling experiment, with a spatial resolution of 10 km, covering the Iberian Peninsula (IP), driven by the ERA40 reanalysis (1959–2001) extended by European Centre for Medium-Range Weather Forecast (ECMWF) analysis (2002–2007) and comprising two main steps. Initially, the skill of the simulation is evaluated comparing the quality-tested observational database (Lorente-Plazas et al., 2014) at local and regional scales. The results show that the model is able to portray the main features of the wind over the IP: annual cycles, wind roses, spatial and temporal variability, as well as the response to different circulation types. In addition, there is a significant added value of the simulation with respect to driving conditions, especially in regions with a complex orography. However, some problems are evident, the major drawback being the systematic overestimation of the wind speed, which is mainly attributed to a missrepresentation of frictional forces. The model skill is also lower along the Mediterranean coast and for the Pyrenees. In a second phase, the high spatio-temporal resolution of the pseudo-real wind database is used to explore the limitations of the observational database. It is shown that missing values do not affect the characterisation of the wind climate over the IP, while the length of the observational period (6 years) is sufficient for most regions, with only a few exceptions. The spatial distribution of the observational sampling schemes should be enhanced to improve the correct assessment of all IP wind regimes, particularly in some mountainous areas.

GROMOS-C, a novel ground-based microwave radiometer for ozone measurement campaigns

Stratospheric ozone is of major interest as it absorbs most harmful UV radiation from the sun, allowing life on Earth. Ground-based microwave remote sensing is the only method that allows for the measurement of ozone profiles up to the mesopause, over 24 hours and under different weather conditions with high time resolution. In this paper a novel ground-based microwave radiometer is presented. It is called GROMOS-C (GRound based Ozone MOnitoring System for Campaigns), and it has been designed to measure the vertical profile of ozone distribution in the middle atmosphere by observing ozone emission spectra at a frequency of 110.836 GHz. The instrument is designed in a compact way which makes it transportable and suitable for outdoor use in campaigns, an advantageous feature that is lacking in present day ozone radiometers. It is operated through remote control. GROMOS-C is a total power radiometer which uses a pre-amplified heterodyne receiver, and a digital fast Fourier transform spectrometer for the spectral analysis. Among its main new features, the incorporation of different calibration loads stands out; this includes a noise diode and a new type of blackbody target specifically designed for this instrument, based on Peltier elements. The calibration scheme does not depend on the use of liquid nitrogen; therefore GROMOS-C can be operated at remote places with no maintenance requirements. In addition, the instrument can be switched in frequency to observe the CO line at 115 GHz. A description of the main characteristics of GROMOS-C is included in this paper, as well as the results of a first campaign at the High Altitude Research Station at Jungfraujoch (HFSJ), Switzerland. The validation is performed by comparison of the retrieved profiles against equivalent profiles from MLS (Microwave Limb Sounding) satellite data, ECMWF (European Centre for Medium-Range Weather Forecast) model data, as well as our nearby NDACC (Network for the Detection of Atmospheric Composition Change) ozone radiometer measuring at Bern.

Comparison of co-located independent ground-based middle atmospheric wind and temperature measurements with numerical weather prediction models

High-resolution, ground-based and independent observations including co-located wind radiometer, lidar stations, and infrasound instruments are used to evaluate the accuracy of general circulation models and data-constrained assimilation systems in the middle atmosphere at northern hemisphere midlatitudes. Systematic comparisons between observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System cycles 38r1 and 38r2, the NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses, and the free-running climate Max Planck Institute–Earth System Model–Low Resolution (MPI-ESM-LR) are carried out in both temporal and spectral dom ains. We find that ECMWF and MERRA are broadly consistent with lidar and wind radiometer measurements up to ~40 km. For both temperature and horizontal wind components, deviations increase with altitude as the assimilated observations become sparser. Between 40 and 60 km altitude, the standard deviation of the mean difference exceeds 5 K for the temperature and 20 m/s for the zonal wind. The largest deviations are observed in winter when the variability from large-scale planetary waves dominates. Between lidar data and MPI-ESM-LR, there is an overall agreement in spectral amplitude down to 15–20 days. At shorter time scales, the variability is lacking in the model by ~10 dB. Infrasound observations indicate a general good agreement with ECWMF wind and temperature products. As such, this study demonstrates the potential of the infrastructure of the Atmospheric Dynamics Research Infrastructure in Europe project that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.