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Objectives To investigate associations between daily concentrations of air pollution and myocardial infarction (MI), ST-elevation MI (STEMI) and non-ST-elevation MI (NSTEMI). Methods Modelled daily ground-level gaseous, total and speciated particulate pollutant concentrations and ground-level daily mean temperature, all at 5 km×5 km horizontal resolution, were linked to 202 550 STEMI and 322 198 NSTEMI events recorded on the England and Wales Myocardial Ischaemia National Audit Project (MINAP) database. The study period was 2003–2010. A case-crossover design was used, stratified by year, month and day of the week. Data were analysed using conditional logistic regression, with pollutants modelled as unconstrained distributed lags 0–2 days. Results are presented as percentage change in risk per 10 µg/m3 increase in the pollutant relevant metric, having adjusted for daily mean temperature, public holidays, weekly influenza consultation rates and a sine-cosine annual cycle. Results There was no evidence of an association between MI or STEMI and any of O3, NO2, PM2.5, PM10 or selected PM2.5 components (sulfate and elemental carbon). For NSTEMI, there was a positive association with daily maximum 1-hour NO2 (0.27% (95% CI 0.01% to 0.54%)), which persisted following adjustment for O3 and adjustment for PM2.5. The association appeared to be confined to the midland and southern regions of England and Wales. Conclusions The study found no evidence of an association between the modelled pollutants (including components) investigated and STEMI but did find some evidence of a positive association between NO2 and NSTEMI. Confirmation of this association in other studies is required.

A fine resolution numerical model of the Southern Ocean (the Fine Resolution Antarctic Model (FRAM)) has been used to investigate the way in which heat is supplied to the South Atlantic. The heat budget in the model is compared with other estimates and is found to be broadly realistic. The temperature structure in the Atlantic, and therefore the meridional heat transport, depend heavily on the input of heat from the Indian Ocean via the Agulhas Retroflection region. FRAM is compared with three models which do not exhibit a significant input of heat from the Indian Ocean. These models also have a lower equatorward heat transport in the South Atlantic. Horizontal resolution affects the amount of Agulhas transfer with coarser resolution leading to lower heat transport in the Atlantic, a result which has implications for ocean models used in climate simulations.

In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km), and 0.11∘ (∼ 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM–RCM modeling chain.

The storm that disrupted the meeting between President Gorbachev and President Bush in Malta between 2 and 3 December 1989 is analyzed. The meteorological situation that caused the storm was simulated with two European Centre for Medium Range Weather Forecasts (ECMWF) atmospheric numerical models—a global model (resolution T106) and a limited-area model (resolution T333)—and its effect on the sea was simulated with an advanced wave model (WAM). Verification of the wind and wave forecast shows that to obtain a realistic forecast of wave height and distribution it is necessary to increase the horizontal resolution of the model, whose grid size must be no more than 40 km.

The Infrared Atmospheric Sounder Instrument (IASI) allows global coverage with very high spatial resolution and its measurements are promising for long-term ozone monitoring. In this study, Microwave Limb Sounder (MLS) O3 profiles and IASI O3 partial columns (1013.25–345 hPa) are assimilated in a chemistry transport model to produce 6-hourly analyses of tropospheric ozone for 6 years (2008–2013). We have compared and evaluated the IASI-MLS analysis and the MLS analysis to assess the added value of IASI measurements. The global chemical transport model MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) has been used with a linear ozone chemistry scheme and meteorological forcing fields from ERA-Interim (ECMWF global reanalysis) with a horizontal resolution of 2° × 2° and 60 vertical levels. The MLS and IASI O3 retrievals have been assimilated with a 4-D variational algorithm to constrain stratospheric and tropospheric ozone respectively. The ozone analyses are validated against ozone soundings and tropospheric column ozone (TCO) from the OMI-MLS residual method. In addition, an Ozone ENSO Index (OEI) is computed from the analysis to validate the TCO variability during the ENSO events. We show that the assimilation of IASI reproduces the variability of tropospheric ozone well during the period under study. The variability deduced from the IASI-MLS analysis and the OMI-MLS measurements are similar for the period of study. The IASI-MLS analysis can reproduce the extreme oscillation of tropospheric ozone caused by ENSO events over the tropical Pacific Ocean, although a correction is required to reduce a constant bias present in the IASI-MLS analysis.

Instrumental observations, palaeo-proxies, and climate models suggest significant decadal variability within the North Atlantic subpolar gyre (NASPG). However, a poorly sampled observational record and a diversity of model behaviours mean that the precise nature and mechanisms of this variability are unclear. Here, we analyse an exceptionally large multi-model ensemble of 42 present-generation climate models to test whether NASPG mean state biases systematically affect the representation of decadal variability. Temperature and salinity biases in the Labrador Sea co-vary and influence whether density variability is controlled by temperature or salinity variations. Ocean horizontal resolution is a good predictor of the biases and the location of the dominant dynamical feedbacks within the NASPG. However, we find no link to the spectral characteristics of the variability. Our results suggest that the mean state and mechanisms of variability within the NASPG are not independent. This represents an important caveat for decadal predictions using anomaly-assimilation methods.

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions that characterize the former is therefore of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman–Monteith model (sc_PDSI_pm), covering the period 1950–2014, at 2.5∘ horizontal resolution. We find that the land areas affected by extreme wet, dry, and wet–dry events (i.e. geographically remote yet temporally co-occurring wet or dry extremes) are all increasing with time, the trends of which in dry and wet–dry episodes are significant (p value ≪ 0.01). The most geographically widespread wet–dry event was associated with the strong La Niña in 2010. This caused wet–dry anomalies across a land area of 21 million km2 with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid cell scale, we introduce two new metrics: the wet–dry (WD) ratio and the extreme transition (ET) time intervals. The WD ratio measures the relative occurrence of wet or dry extremes, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD ratio shows that the incidence of wet extremes dominates over dry extremes in the USA, northern and southern South America, northern Europe, north Africa, western China, and most of Australia. Conversely, dry extremes are more prominent in most of the remaining regions. The median ET for wet to dry is ∼27 months, while the dry-to-wet median ET is 21 months. We also evaluate correlations between wet–dry hydrological extremes and leading modes of climate variability, namely the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p value < 0.05) a larger area (18.1 % of total sc_PDSI_pm area) compared to the latter (12.0 %), whereas the AMO shows an almost inverse pattern and significantly impacts the largest area overall (18.9 %). ENSO and PDO show the most significant correlations over northern South America, the central and western USA, the Middle East, eastern Russia, and eastern Australia. On the other hand, the AMO shows significant associations over Mexico, Brazil, central Africa, the Arabian Peninsula, China, and eastern Russia. Our analysis brings new insights on hydrological multi-hazards that are of relevance to governments and organizations with globally distributed interests. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.

Large data sets used to study the impact of anthropogenic climate change on the 2013/14 floods in the UK are provided. The data consist of perturbed initial conditions simulations using the Weather@Home regional climate modelling framework. Two different base conditions, Actual, including atmospheric conditions (anthropogenic greenhouse gases and human induced aerosols) as at present and Natural, with these forcings all removed are available. The data set is made up of 13 different ensembles (2 actual and 11 natural) with each having more than 7500 members. The data is available as NetCDF V3 files representing monthly data within the period of interest (1st Dec 2013 to 15th February 2014) for both a specified European region at a 50 km horizontal resolution and globally at N96 resolution. The data is stored within the UK Natural and Environmental Research Council Centre for Environmental Data Analysis repository. Machine-accessible metadata file describing the reported data (ISA-Tab format)

A three-dimensional (3D) wind profiling Lidar, based on the latest high power 1.5 µm fiber laser development at Onera, has been successfully flown on-board a SAFIRE (Service des Avions Français Instrumentés pour la Recherche en Environnement) ATR42 aircraft. The Lidar called LIVE (LIdar VEnt) is designed to measure wind profiles from the aircraft down to ground level, with a horizontal resolution of 3 km, a vertical resolution of 100 m and a designed accuracy on each three wind vector components better than 0.5 m.s−1. To achieve the required performance, LIVE Lidar emits 410 µJ laser pulses repeating at 14 KHz with a duration of 700 ns and uses a conical scanner of 30° total opening angle and a full scan time of 17 s.

About 600 ozone sonde profiles and in situ ozone observations on 2300 aircraft flights were compared with several three-dimensional global chemistry-transport models, in the midlatitude lowermost stratosphere during 1996. The models use the same top boundary conditions and parameterized ozone chemistry. The comparisons show that the models using general circulation model (GCM) winds do not capture the seasonal ozone accumulation in the lowermost stratosphere. The models using winds from the European Centre for Medium-Range Weather Forecasts (ECWMF) overestimate ozone above this maximum, especially during spring. This overestimation increases with increasing latitude. Close to the tropopause, the best agreement between models and observations is found during winter and the worst occurs during summer, where most models underestimate the mean ozone concentration. This underestimation is partly caused by inaccurate description of the relatively small-scale transport processes, mainly associated with convective activity, and partly by incomplete ozone chemistry in the parameterized scheme. The models that use assimilated winds show significant differences in calculated ozone, despite their common source (ECWMF) to calculate the transport. We illustrate that the model performance significantly depends on the ECWMF processing method and that interpolation of wind data should be avoided. In addition, the results seem relatively insensitive to vertical resolution. To improve the model performance further in this region, the horizontal resolution should be higher than 2.5°.

Global climate models (GCMs) are the primary tools for predicting the evolution of the climate system. Through decades of development, GCMs have demonstrated useful skill in simulating climate at continental to global scales. However, large uncertainties remain in projecting climate change at regional scales, which limit our ability to inform decisions on climate change adaptation and mitigation. To bridge this gap, different modeling approaches including nested regional climate models (RCMs), global stretch-grid models, and global high-resolution atmospheric models have been used to provide regional climate simulations (Leung et al. 2003). In previous efforts to evaluate these approaches, isolating their relative merits was not possible because factors such as dynamical frameworks, physics parameterizations, and model resolutions were not systematically constrained. With advances in high performance computing, it is now feasible to run coupled atmosphere-ocean GCMs at horizontal resolution comparable to what RCMs use today. Global models with local refinement using unstructured grids have become available for modeling regional climate (e.g., Rauscher et al. 2012; Ringler et al. 2013). While they offer opportunities to improve climate simulations, significant efforts are needed to test their veracity for regional-scale climate simulations.

The ability of the High-Resolution Global Environmental Monitoring (HiGEM) climate model to represent high-impact, regional precipitation events is investigated in two ways. The first focuses on a case study of extreme regional accumulation of precipitation during the passage of a summer extratropical cyclone across southern England on 20 July 2007 that resulted in a national flooding emergency. The climate model is compared with a global numerical weather prediction (NWP) model and higher-resolution, nested limited-area models. While the climate model does not simulate the timing and location of the cyclone and associated precipitation as accurately as the NWP simulations, the total accumulated precipitation in all models is similar to the rain-gauge estimate across England and Wales. The regional accumulation over the event is insensitive to horizontal resolution for grid spacings ranging from 90–4 km. Secondly, the free-running climate model reproduces the statistical distribution of daily precipitation accumulations observed in the England–Wales precipitation record. The model distribution diverges increasingly from the record for longer accumulation periods, with a consistent under-representation of more intense multiday accumulations. This may indicate a lack of low-frequency variability associated with weather regime persistence. Despite this, the overall seasonal and annual precipitation totals from the model are still comparable to those from ERA-Interim.

Cooking organic aerosol (COA) is currently not included in European emission inventories. However, recent positive matrix factorization (PMF) analyses of aerosol mass spectrometer (AMS) measurements have suggested important contributions of COA in several European cities. In this study, emissions of COA were estimated for the UK, based on hourly AMS measurements of COA made at two sites in London (a kerbside site in central London and an urban background site in a residential area close to central London) for the full calendar year of 2012 during the Clean Air for London (ClearfLo) campaign. Iteration of COA emissions estimates and subsequent evaluation and sensitivity experiments were conducted with the EMEP4UK atmospheric chemistry transport modelling system with a horizontal resolution of 5 km × 5 km. The spatial distribution of these emissions was based on workday population density derived from the 2011 census data. The estimated UK annual COA emission was 7.4 Gg per year, which is an almost 10 % addition to the officially reported UK national total anthropogenic emissions of PM2.5 (82 Gg in 2012), corresponding to 320 mg person−1 day−1 on average. Weekday and weekend diurnal variation in COA emissions were also based on the AMS measurements. Modelled concentrations of COA were then independently evaluated against AMS-derived COA measurements from another city and time period (Manchester, January–February 2007), as well as with COA estimated by a chemical mass balance model of measurements for a 2-week period at the Harwell rural site (∼ 80 km west of central London). The modelled annual average contribution of COA to ambient particulate matter (PM) in central London was between 1 and 2 µg m−3 (∼ 20 % of total measured OA1) and between 0.5 and 0.7 µg m−3 in other major cities in England (Manchester, Birmingham, Leeds). It was also shown that cities smaller than London can have a central hotspot of population density of smaller area than the computational grid cell, in which case higher localized COA concentrations than modelled here may be expected. Modelled COA concentrations dropped rapidly outside of major urban areas (annual average of 0.12 µg m−3 for the Harwell location), indicating that although COA can be a notable component in urban air, it does not have a significant effect on PM concentrations on rural areas. The possibility that the AMS-PMF apportionment measurements overestimate COA concentrations by up to a factor of 2 is discussed. Since COA is a primary emission, any downward adjustments in COA emissions would lead to a proportional linear downward scaling in the absolute magnitudes of COA concentrations simulated in the model.

Extreme rainfall events continue to be one of the largest natural hazards in the UK. In winter, heavy precipitation and floods have been linked with intense moisture transport events associated with atmospheric rivers (ARs), yet no large-scale atmospheric precursors have been linked to summer flooding in the UK. This study investigates the link between ARs and extreme rainfall from two perspectives: (1) Given an extreme rainfall event, is there an associated AR? (2) Given an AR, is there an associated extreme rainfall event? We identify extreme rainfall events using the UK Met Office daily rain gauge data set and link these to ARs using two different horizontal resolution atmospheric data sets (ERA-Interim and Twentieth Century Reanalysis). The results show that less than 35% of winter ARs and less than 15% of summer ARs are associated with an extreme rainfall event. Consistent with previous studies, at least 50% of extreme winter rainfall events are associated with an AR. However, less than 20% of the identified summer extreme rainfall events are associated with an AR. The dependence of the water vapor transport intensity threshold used to define an AR on the years included in the study, and on the length of the season, is also examined. Including a longer period (1900–2012) compared to previous studies (1979–2005) reduces the water vapor transport intensity threshold used to define an AR.

The traditional picture of the earth used for developing seismic reflection theory is one-dimensional, 'layer-cake' geology, where the physical properties of the earth vary only with depth, and the horizontal direction exists only for the purpose of considering an offset between source and receiver.

An inverse frequency modulation method was developed to record color moving pictures on Magneto-optical disks. An improved S/N of reproduced pictures as high as 45 dB with a horizontal resolution of 400 lines was obtained at the inner area of the disk.

Color moving pitures were recorded on the magneto-optical disk by a frequency modulation method. Two types of FM modems whose bandwidths were 6 MHz and 9.3 MHz were developed. In the latter modem, the quality of reproduced pictures was as good as that of the Video Disc. It was confirmed that the horizontal resolution through the ITE test patterns was over 400 lines and the signal-to-noise ratio measured by video noise meter was 40 dB or more.