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Observations of profiles of winds, aerosol, clouds, winds, temperature and humidity in the lowest few km of the atmosphere from networks of ceilometers, Doppler wind lidars and microwave radiometers are starting to flow in real time to forecasting centers in Europe.\ud \ud To realise the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few km are hardly accessible by satellite, especially in dynamically-active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real-time to forecast centers. The three classes of instruments are: (i) Automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog and volcanic ash, the last two being especially important for air traffic control; (ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind-gusts and low-level jets; and (iii) Microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. Twenty-two European countries and fifteen European National Weather Services are collaborating in the project, that involves the implementation of common operating procedures, instrument calibrations, data formats and retrieval algorithms. Currently, data from 220 ceilometers in 17 countries are being distributed in near real-time to national weather forecast centers; this should soon rise to many hundreds. The wind lidars should start delivering real time data in late 2018, and the plan is to incorporate the microwave radiometers in 2019. Initial data assimilation tests indicate a positive impact of the new data.

The ClearfLo project provides integrated measurements of the meteorology, composition and particulate loading of London's urban atmosphere to improve predictive capability for air quality.Air quality and heat are strong health drivers and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants such as ozone, nitrogen dioxide, and fine and coarse particulate matter in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the ClearfLo project's interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures.Within ClearfLo (www.clearflo.ac.uk), a large multi-institutional project funded by the UK Natural Environment Research Council (NERC), integrated measurements of meteorology, gaseous and particulate composition/loading within London's atmosphere were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, kerbside and rural locations were complemented with high-resolution numerical atmospheric simulations . Combining these (measurement/modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and summer Olympics 2012) focus upon the vertical structure and evolution of the urban boundary layer, chemical controls on nitrogen dioxide and ozone production, in particular the role of volatile organic compounds, and processes controlling the evolution, size, distribution and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.

For years, various indices of seasonal West African precipitation have served as useful predictors of the overall tropical cyclone activity in the Atlantic Ocean. Since the mid-1990s, the correlation unexpectedly deteriorated. In the present study, statistical techniques are developed to describe the nonstationary nature of the correlations between annual measures of Atlantic tropical cyclone activity and three selected West African precipitation indices (namely, western Sahelian precipitation in June–September, central Sahelian precipitation in June–September, and Guinean coastal precipitation in the preceding year’s August–November period). The correlations between these parameters are found to vary over the period from 1921 to 2007 on a range of time scales. Additionally, considerable year-to-year variability in the strength of these correlations is documented by selecting subsamples of years with respect to various meteorological factors. Broadly, in years when the environment in the main development region is generally favorable for enhanced tropical cyclogenesis (e.g., when sea surface temperatures are high, when there is relatively little wind shear through the depth of the troposphere, or when the relative vorticity in the midtroposphere is anomalously high), the correlations between indices of West African monsoon precipitation and Atlantic tropical cyclone activity are considerably weaker than in years when the overall conditions in the region are less conducive. Other more remote climate parameters, such as the phase of the Southern Oscillation, are less effective at modulating the nature of these interactions.