A potential lag between the open solar magnetic source flux and solar EUV and X-ray emissions as measured by the Earth's ionosphere during total solar eclipses

Measurements of the ionospheric E-region during total solar eclipses have been used to provide information about the evolution of the solar magnetic field and EUV and X-ray emissions from the solar corona and chromosphere. By measuring levels of ionisation during an eclipse and comparing these measurements with an estimate of the unperturbed ionisation levels (such as those made during a control day, where available) it is possible to estimate the percentage of ionising radiation being emitted by the solar corona and chromosphere. Previously unpublished data from the two eclipses presented here are particularly valuable as they provide information that supplements the data published to date. The eclipse of 23 October 1976 over Australia provides information in a data gap that would otherwise have spanned the years 1966 to 1991. The eclipse of 4 December 2002 over Southern Africa is important as it extends the published sequence of measurements. Comparing measurements from eclipses between 1932 and 2002 with the solar magnetic source flux reveals that changes in the solar EUV and X-ray flux lag the open source flux measurements by approximately 1.5 years. We suggest that this unexpected result comes about from changes to the relative size of the limb corona between eclipses, with the lag representing the time taken to populate the coronal field with plasma hot enough to emit the EUV and X-rays ionising our atmosphere.

Atmospheric blocking and mean biases in climate models

Models often underestimate blocking in the Atlantic and Pacific basins and this can lead to errors in both weather and climate predictions. Horizontal resolution is often cited as the main culprit for blocking errors due to poorly resolved small-scale variability, the upscale effects of which help to maintain blocks. Although these processes are important for blocking, the authors show that much of the blocking error diagnosed using common methods of analysis and current climate models is directly attributable to the climatological bias of the model. This explains a large proportion of diagnosed blocking error in models used in the recent Intergovernmental Panel for Climate Change report. Furthermore, greatly improved statistics are obtained by diagnosing blocking using climate model data corrected to account for mean model biases. To the extent that mean biases may be corrected in low-resolution models, this suggests that such models may be able to generate greatly improved levels of atmospheric blocking.

The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: a case study over the UK

Over recent years there has been an increasing deployment of renewable energy generation technologies, particularly large-scale wind farms. As wind farm deployment increases, it is vital to gain a good understanding of how the energy produced is affected by climate variations, over a wide range of time-scales, from short (hours to weeks) to long (months to decades) periods. By relating wind speed at specific sites in the UK to a large-scale climate pattern (the North Atlantic Oscillation or "NAO"), the power generated by a modelled wind turbine under three different NAO states is calculated. It was found that the wind conditions under these NAO states may yield a difference in the mean wind power output of up to 10%. A simple model is used to demonstrate that forecasts of future NAO states can potentially be used to improve month-ahead statistical forecasts of monthly-mean wind power generation. The results confirm that the NAO has a significant impact on the hourly-, daily- and monthly-mean power output distributions from the turbine with important implications for (a) the use of meteorological data (e.g. their relationship to large scale climate patterns) in wind farm site assessment and, (b) the utilisation of seasonal-to-decadal climate forecasts to estimate future wind farm power output. This suggests that further research into the links between large-scale climate variability and wind power generation is both necessary and valuable.

Boundary layer dynamics over London, UK, as observed using Doppler lidar during REPARTEE-II

Urban boundary layers (UBLs) can be highly complex due to the heterogeneous roughness and heating of the surface, particularly at night. Due to a general lack of observations, it is not clear whether canonical models of boundary layer mixing are appropriate in modelling air quality in urban areas. This paper reports Doppler lidar observations of turbulence profiles in the centre of London, UK, as part of the second REPARTEE campaign in autumn 2007. Lidar-measured standard deviation of vertical velocity averaged over 30 min intervals generally compared well with in situ sonic anemometer measurements at 190 m on the BT telecommunications Tower. During calm, nocturnal periods, the lidar underestimated turbulent mixing due mainly to limited sampling rate. Mixing height derived from the turbulence, and aerosol layer height from the backscatter profiles, showed similar diurnal cycles ranging from c. 300 to 800 m, increasing to c. 200 to 850 m under clear skies. The aerosol layer height was sometimes significantly different to the mixing height, particularly at night under clear skies. For convective and neutral cases, the scaled turbulence profiles resembled canonical results; this was less clear for the stable case. Lidar observations clearly showed enhanced mixing beneath stratocumulus clouds reaching down on occasion to approximately half daytime boundary layer depth. On one occasion the nocturnal turbulent structure was consistent with a nocturnal jet, suggesting a stable layer. Given the general agreement between observations and canonical turbulence profiles, mixing timescales were calculated for passive scalars released at street level to reach the BT Tower using existing models of turbulent mixing. It was estimated to take c. 10 min to diffuse up to 190 m, rising to between 20 and 50 min at night, depending on stability. Determination of mixing timescales is important when comparing to physico-chemical processes acting on pollutant species measured simultaneously at both the ground and at the BT Tower during the campaign. From the 3 week autumnal data-set there is evidence for occasional stable layers in central London, effectively decoupling surface emissions from air aloft.

The changing atmospheric water cycle in polar regions in a warmer climate

We have examined the atmospheric water cycle of both Polar Regions, pole wards of 60°N and 60°S, using the ERA-Interim re-analysis and high-resolution simulations with the ECHAM5 model for both the present and future climate based on the IPCC, A1B scenario, representative of the last three decades of the 21st century. The annual precipitation in ERA-Interim amounts to ~17000 km3 and is more or less the same in the Arctic and the Antarctic, but it is composed differently. In the Arctic the annual evaporation is some 8000 km3 but some 3000 km3 less in the Antarctica where the net horizontal transport is correspondingly larger. The net water transport of the model is more intense than in ERA-Interim, in the Arctic the difference is 2.5% and in the Antarctic it is 6.2%. Precipitation and net horizontal transport in the Arctic has a maximum in August and September. Evaporation peaks in June and July. The seasonal cycle is similar in Antarctica with the highest precipitation in the austral autumn. The largest net transport occurs at the end of the major extra-tropical storm tracks in the Northern Hemisphere such as the eastern Pacific and eastern north Atlantic. The variability of the model is virtually identical to that of the re-analysis and there are no changes in variability between the present climate and the climate at the end of the 21st century when normalized with the higher level of moisture. The changes from year to year are substantial with the 20 and 30-year records being generally too short to identify robust trends in the hydrological cycle. In the A1B climate scenario the strength of the water cycle increases by some 25% in the Arctic and by 19% in the Antarctica, as measured by annual precipitation. The increase in the net horizontal transport is 29% and 22% respectively, and the increase in evaporation correspondingly less. The net transport follows closely the Clausius-Clapeyron relation. There is 2 a minor change in the annual cycle of the Arctic atmospheric water cycle with the maximum transport and precipitation occurring later in the year. There is a small imbalance of some 4-6% between the net transport and precipitation minus evaporation. We suggest that this is mainly due to the fact the transport is calculated from instantaneous 6-hourly data while precipitation and evaporation is accumulated over a 6 hour period. The residual difference is proportionally similar for all experiments and hardly varies from year to year.

Fair weather atmospheric electricity

Abstract. Not long after Franklin’s iconic studies, an atmospheric electric field was discovered in “fair weather” regions, well away from thunderstorms. The origin of the fair weather field was sought by Lord Kelvin, through development of electrostatic instrumentation and early data logging techniques, but was ultimately explained through the global circuit model of C.T.R. Wilson. In Wilson’s model, charge exchanged by disturbed weather electrifies the ionosphere, and returns via a small vertical current density in fair weather regions. New insights into the relevance of fair weather atmospheric electricity to terrestrial and planetary atmospheres are now emerging. For example, there is a possible role of the global circuit current density in atmospheric processes, such as cloud formation. Beyond natural atmospheric processes, a novel practical application is the use of early atmospheric electrostatic investigations to provide quantitative information on past urban air pollution.

Radicals from the atmospheric pressure pyrolysis and oxidative pyrolysis of hydroquinone, catechol, and phenol

The burning of tobacco creates various types of free radicals that have been reported to be biologically active. Some radicals are transient but can initiate catalytic cycles that generate other free radicals. Other radicals are environmentally persistent and can exist in total particulate matter (TPM) for extended periods. In spite of their importance, little is known concerning the precursors of these radicals or under what pyrolysis/combustion conditions they are formed. We performed studies of the formation of radicals from the gas-phase pyrolysis and oxidative pyrolysis of hydroquinone (HQ) and catechol (CT) between 750 and 1000 °C and phenol from 500 to 1000 °C. The initial electron paramagnetic resonance (EPR) spectra were complex, indicating the presence of multiple radicals. Using matrix annealing and microwave power saturation techniques, phenoxyl, cyclopentadienyl, and peroxyl radicals were identifiable, but only cyclopentadienyl radicals were stable above 750 °C.

Evaluating the structure and magnitude of the ash plume during the initial phase of the 2010 Eyjafjallajökull eruption using lidar observations and NAME simulations

The Eyjafjallajökull volcano in Iceland erupted explosively on 14 April 2010, emitting a plume of ash into the atmosphere. The ash was transported from Iceland toward Europe where mostly cloud-free skies allowed ground-based lidars at Chilbolton in England and Leipzig in Germany to estimate the mass concentration in the ash cloud as it passed overhead. The UK Met Office's Numerical Atmospheric-dispersion Modeling Environment (NAME) has been used to simulate the evolution of the ash cloud from the Eyjafjallajökull volcano during the initial phase of the ash emissions, 14–16 April 2010. NAME captures the timing and sloped structure of the ash layer observed over Leipzig, close to the central axis of the ash cloud. Relatively small errors in the ash cloud position, probably caused by the cumulative effect of errors in the driving meteorology en route, result in a timing error at distances far from the central axis of the ash cloud. Taking the timing error into account, NAME is able to capture the sloped ash layer over the UK. Comparison of the lidar observations and NAME simulations has allowed an estimation of the plume height time series to be made. It is necessary to include in the model input the large variations in plume height in order to accurately predict the ash cloud structure at long range. Quantitative comparison with the mass concentrations at Leipzig and Chilbolton suggest that around 3% of the total emitted mass is transported as far as these sites by small (<100 μm diameter) ash particles.

Cloud-base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

The statistics of cloud-base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in Central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that, as expected, AROME significantly underestimates the variability of vertical velocity at cloud-base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4-6 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70-80% of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 4 times the physically-defined grid spacing. The results illustrate the need for special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.