Ventilation effects on humidity measurements in thermometer screens

Relative humidity (RH) measurements, as derived from wet-bulb and dry-bulb thermometers operated as a psychrometer within a thermometer screen, have limited accuracy because of natural ventilation variations. Standard RH calculations generally assume a fixed screen psychrometer coefficient, but this is too small during poor ventilation. By comparing a reference humidity probe—exposed within a screen containing a psychrometer—with wind-speed measurements under controlled conditions, a wind-speed correction for the screen psychrometer coefficient has been derived and applicable when 2-metre wind speeds fall below 3 ms–1. Applying this to hourly-averaged data reduced the mean moist RH bias of the psychrometer (over the reference probe) from 1.2% to 0.4%, and reduced the inter-quartile range of the RH differences from 2.0% to 0.8%. This correction is particularly amenable to automatic measurement systems.

Diagnosing eclipse-induced wind changes

Responses in surface winds to solar eclipses have an almost mystical status but are difficult to detect in observations because of their transient nature. High spatial resolution (approx. 1.5 km grid) meteorological models now provide a new technique for their investigation. Measurements from the southern UK meteorological network during the 11 August 1999 total solar eclipse are compared with a high-resolution model ignorant of the lunar shadow’s influence. Differences between the model output and measurements at the eclipse time show transient eclipse zone temperature decreases of up to 3 degrees C, which also depressed the day’s maximum temperature compared with the model prediction. Coherent responses in temperature, and wind speed and direction measurements are detected in the inland cloud-free region (from 51 to 52 degrees N and −2 to 0 degrees E). A mean regional wind speed decrease of 0.7 m s−1 during the maximum eclipse hour is apparent with a mean anticlockwise wind direction change of 17 degrees; no such changes occurred in the model output. Such regional circulation changes are consistent with Clayton’s 1901 cold-cored eclipse cyclone hypothesis, which may be related to the anecdotal ‘eclipse wind’.

Effluent quality and ammonia emissions from out-wintering pads in England, Wales and Ireland

Out-wintering pads offer a reduced cost system for wintering cattle, minimising damage to pasture, providing animal welfare and production benefits, and generate, potentially, a more manageable effluent and lower ammonia emissions. The objectives of the present study were (i) to contribute to improved understanding of the factors impacting on effluent quality, ammonia emissions and animal welfare via observations on four farm-based out-wintering pads (ComOWPs) in England, Wales and Ireland and more detailed studies undertaken on four experimental OWPs (ExpOWPs) constructed at Rothamsted Research North Wyke, Devon, England and (ii) to corroborate the effluent quality data from both the ComOWPs and the ExpOWPs, with findings in the literature. Woodchip size, feeding management and area allowance were the treatment factors applied on the ExpOWPs. These three factors were randomised across the four ExpOWPs, over four 6–7 week periods. Effluent quality from the ExpOWPs was sampled frequently in a flow proportional way and analysed for total N (TN); total P (TP); total solids (TS); ammonium-N (NH4+-N); nitrate-N (NO3−-N). Beef cattle were periodically weighed for determination of live weight gain (LWG). An approximate nitrogen balance was calculated as a means of understanding its partitioning and fate during and after the ExpOWPs use. Effluent quality from the ComOWPs was sampled frequently, also in a flow-proportional way, and analysed for TN, TP, TS, NH4+-N, NO3−-N, total K and COD. Effluent quality data from the ExpOWPs showed no significant differences (P > 0.05) between treatments, with average concentrations of 1095 mg l−1, and 806 mg l−1, for TN and NH4+-N, respectively. Average effluent concentrations from the ComOWPs were 356 mg l−1 TN and 124 mg l−1 NH4+-N. Ammonia emissions from the ExpOWPs showed no significant differences (P > 0.05) between the treatments, with average mean emission rates of 2.5 g m−2 d−1 NH3-N, respectively. A positive correlation was established between NH3-N emission rate and wind speed. Emission rates from the ComOWPs ranged from 0.7 to 1.6 g m−2 d−1 NH3-N. Average daily LWG on the ExpOWPs was 1.33 kg steer−1 d−1. The effluent from both the ComOWPs and ExpOWPs were more similar with dirty water and of consistently lower strength than beef cattle slurry, as supported by findings in the literature, and therefore, it is suggested to be subject to the regulatory requirements of dirty water rather than slurry.

Wind observations above an urban river using a new lidar technique, scintillometry and anemometry

Flow along rivers, an integral part of many cities, might provide a key mechanism for ventilation – which is important for air quality and heat stress. Since the flow varies in space and time around rivers, there is limited utility in point measurements. Ground-based remote sensing offers the opportunity to study 3D flow in locations which are hard to observe. For three months in the winter and spring of 2011, the atmospheric flow above the River Thames in central London was observed using a scanning Doppler lidar, a dual-beam scintillometer and sonic anemometry. First, an inter-comparison showed that lidar-derived mean wind-speed estimates compare almost as well to sonic anemometers (root-mean-square error (rmse) 0.65–0.68 m s–1) as comparisons between sonic anemometers (0.35–0.73 m s–1). Second, the lidar duo-beam scanning strategy provided horizontal transects of wind vectors comparison with scintillometer rmse 1.12–1.63 m s–1) which revealed mean and turbulent flow across the river and surrounds; in particular: chanelling flow along the river and turbulence changes consistent with the roughness changes between built to river environments. The results have important consequences for air quality and dispersion around urban rivers, especially given that many cities have high traffic rates on bankside roads.

Effects of urban ventilation patterns on the carbon monoxide concentration in a high-rise mega city

Carbon monoxide (CO) concentration data from 1999–2006, monitored at 5 different pollution stations in a high-rise mega city (Hong Kong), were collected and investigated. The spatio-temporal characteristics of urban CO concentration profiles were obtained. A new approach was put forward to examine the relationship between urban CO concentration and different wind flow patterns. Rather than relying on the meteorological data from a single weather station, usually adopted in previous studies, four weather stations on the boundary of Hong Kong territory were used in the present study so as to identify 16 different wind flow patterns, among which a typical urban heat island circulation (UHIC) can be distinguished. Higher concentrations were observed to be associated with the flow pattern of an inflow from Lau Fau Shan (LFS) station which is located in the northwest of Hong Kong. This suggests that the ability of dilution for north-to-west wind is relatively weak due to the pollutants carried from outside Hong Kong. The effectiveness of wind speed on the alleviation of urban concentration is dependent on the initial concentration of the approaching wind. The increase of wind speed of north-to-west wind from 0 m/s to 6 m/s has little effect on the reduction of urban CO concentration, especially on the non-roadside stations. By contrast, for the southerly marine wind, pollution concentration decreases sharply with an increase in the wind speed. It was also found that urban heat island circulation (UHIC) is conducive of the accumulation of pollutants, especially at night. There exists a positive correlation between CO concentration and UHI intensity. This correlation is much stronger at night compared to during the day. Keywords: urban pollution monitoring, urban ventilation pattern, urban heat island circulation, mega city

Describing seasonal variability in the distribution of daily effective temperatures for 1985-2009 compared to 1904-1984 for De Bilt, Holland

This paper proposes a method for describing the distribution of observed temperatures on any day of the year such that the distribution and summary statistics of interest derived from the distribution vary smoothly through the year. The method removes the noise inherent in calculating summary statistics directly from the data thus easing comparisons of distributions and summary statistics between different periods. The method is demonstrated using daily effective temperatures (DET) derived from observations of temperature and wind speed at De Bilt, Holland. Distributions and summary statistics are obtained from 1985 to 2009 and compared to the period 1904–1984. A two-stage process first obtains parameters of a theoretical probability distribution, in this case the generalized extreme value (GEV) distribution, which describes the distribution of DET on any day of the year. Second, linear models describe seasonal variation in the parameters. Model predictions provide parameters of the GEV distribution, and therefore summary statistics, that vary smoothly through the year. There is evidence of an increasing mean temperature, a decrease in the variability in temperatures mainly in the winter and more positive skew, more warm days, in the summer. In the winter, the 2% point, the value below which 2% of observations are expected to fall, has risen by 1.2 °C, in the summer the 98% point has risen by 0.8 °C. Medians have risen by 1.1 and 0.9 °C in winter and summer, respectively. The method can be used to describe distributions of future climate projections and other climate variables. Further extensions to the methodology are suggested.

Evaluation of regional climate simulations for air quality modelling purposes

In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional “climate modeling” source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

Wind gust estimation for Mid-European winter storms: towards a probabilistic view

Three wind gust estimation (WGE) methods implemented in the numerical weather prediction (NWP) model COSMO-CLM are evaluated with respect to their forecast quality using skill scores. Two methods estimate gusts locally from mean wind speed and the turbulence state of the atmosphere, while the third one considers the mixing-down of high momentum within the planetary boundary layer (WGE Brasseur). One hundred and fifty-eight windstorms from the last four decades are simulated and results are compared with gust observations at 37 stations in Germany. Skill scores reveal that the local WGE methods show an overall better behaviour, whilst WGE Brasseur performs less well except for mountain regions. The here introduced WGE turbulent kinetic energy (TKE) permits a probabilistic interpretation using statistical characteristics of gusts at observational sites for an assessment of uncertainty. The WGE TKE formulation has the advantage of a ‘native’ interpretation of wind gusts as result of local appearance of TKE. The inclusion of a probabilistic WGE TKE approach in NWP models has, thus, several advantages over other methods, as it has the potential for an estimation of uncertainties of gusts at observational sites.

European storminess and associated circulation weather types: future changes deduced from a multi-model ensemble of GCM simulations

A range of possible changes in the frequency and characteristics of European wind storms under future climate conditions was investigated on the basis of a multi-model ensemble of 9 coupled global climate model (GCM) simulations for the 20th and 21st centuries following the IPCC SRES A1B scenario. A multi-model approach allowed an estimation of the (un)certainties of the climate change signals. General changes in large-scale atmospheric flow were analysed, the occurrence of wind storms was quantified, and atmospheric features associated with wind storm events were considered. Identified storm days were investigated according to atmospheric circulation, associated pressure patterns, cyclone tracks and wind speed patterns. Validation against reanalysis data revealed that the GCMs are in general capable of realistically reproducing characteristics of European circulation weather types (CWTs) and wind storms. Results are given with respect to frequency of occurrence, storm-associated flow conditions, cyclone tracks and specific wind speed patterns. Under anthropogenic climate change conditions (SRES A1B scenario), increased frequency of westerly flow during winter is detected over the central European investigation area. In the ensemble mean, the number of detected wind storm days increases between 19 and 33% for 2 different measures of storminess, only 1 GCM revealed less storm days. The increased number of storm days detected in most models is disproportionately high compared to the related CWT changes. The mean intensity of cyclones associated with storm days in the ensemble mean increases by about 10 (±10)% in the Eastern Atlantic, near the British Isles and in the North Sea. Accordingly, wind speeds associated with storm events increase significantly by about 5 (±5)% over large parts of central Europe, mainly on days with westerly flow. The basic conclusions of this work remain valid if different ensemble contructions are considered, leaving out an outlier model or including multiple runs of one particular model.

Changing European storm loss potentials under modified climate conditions according to ensemble simulations of the ECHAM5/MPI-OM1 GMC

A simple storm loss model is applied to an ensemble of ECHAM5/MPI-OM1 GCM simulations in order to estimate changes of insured loss potentials over Europe in the 21st century. Losses are computed based on the daily maximum wind speed for each grid point. The calibration of the loss model is performed using wind data from the ERA40-Reanalysis and German loss data. The obtained annual losses for the present climate conditions (20C, three realisations) reproduce the statistical features of the historical insurance loss data for Germany. The climate change experiments correspond to the SRES-Scenarios A1B and A2, and for each of them three realisations are considered. On average, insured loss potentials increase for all analysed European regions at the end of the 21st century. Changes are largest for Germany and France, and lowest for Portugal/Spain. Additionally, the spread between the single realisations is large, ranging e.g. for Germany from −4% to +43% in terms of mean annual loss. Moreover, almost all simulations show an increasing interannual variability of storm damage. This assessment is even more pronounced if no adaptation of building structure to climate change is considered. The increased loss potentials are linked with enhanced values for the high percentiles of surface wind maxima over Western and Central Europe, which in turn are associated with an enhanced number and increased intensity of extreme cyclones over the British Isles and the North Sea.

A reprocessing for climate of sea surface temperature from the Along-Track Scanning Radiometers: initial validation, accounting for skin and diurnal variability

An initial validation of the Along Track Scanning Radiometer (ATSR) Reprocessing for Climate (ARC) retrievals of sea surface temperature (SST) is presented. ATSR-2 and Advanced ATSR (AATSR) SST estimates are compared to drifting buoy and moored buoy observations over the period 1995 to 2008. The primary ATSR estimates are of skin SST, whereas buoys measure SST below the surface. Adjustment is therefore made for the skin effect, for diurnal stratification and for differences in buoy–satellite observation time. With such adjustments, satellite-in situ differences are consistent between day and night within ~ 0.01 K. Satellite-in situ differences are correlated with differences in observation time, because of the diurnal warming and cooling of the ocean. The data are used to verify the average behaviour of physical and empirical models of the warming/cooling rates. Systematic differences between adjusted AATSR and in-situ SSTs against latitude, total column water vapour (TCWV), and wind speed are less than 0.1 K, for all except the most extreme cases (TCWV < 5 kg m–2, TCWV > 60 kg m–2). For all types of retrieval except the nadir-only two-channel (N2), regional biases are less than 0.1 K for 80% of the ocean. Global comparison against drifting buoys shows night time dual-view two-channel (D2) SSTs are warm by 0.06 ± 0.23 K and dual-view three-channel (D3) SSTs are warm by 0.06 ± 0.21 K (day-time D2: 0.07 ± 0.23 K). Nadir-only results are N2: 0.03 ± 0.33 K and N3: 0.03 ± 0.19 K showing the improved inter-algorithm consistency to ~ 0.02 K. This represents a marked improvement from the existing operational retrieval algorithms for which inter-algorithm inconsistency is > 0.5 K. Comparison against tropical moored buoys, which are more accurate than drifting buoys, gives lower error estimates (N3: 0.02 ± 0.13 K, D2: 0.03 ± 0.18 K). Comparable results are obtained for ATSR-2, except that the ATSR-2 SSTs are around 0.1 K warm compared to AATSR

Reconstruction and prediction of variations in the open solar magnetic flux and interplanetary conditions

Historic geomagnetic activity observations have been used to reveal centennial variations in the open solar flux and the near-Earth heliospheric conditions (the interplanetary magnetic field and the solar wind speed). The various methods are in very good agreement for the past 135 years when there were sufficient reliable magnetic observatories in operation to eliminate problems due to site-specific errors and calibration drifts. This review underlines the physical principles that allow these reconstructions to be made, as well as the details of the various algorithms employed and the results obtained. Discussion is included of: the importance of the averaging timescale; the key differences between “range” and “interdiurnal variability” geomagnetic data; the need to distinguish source field sector structure from heliospherically-imposed field structure; the importance of ensuring that regressions used are statistically robust; and uncertainty analysis. The reconstructions are exceedingly useful as they provide calibration between the in-situ spacecraft measurements from the past five decades and the millennial records of heliospheric behaviour deduced from measured abundances of cosmogenic radionuclides found in terrestrial reservoirs. Continuity of open solar flux, using sunspot number to quantify the emergence rate, is the basis of a number of models that have been very successful in reproducing the variation derived from geomagnetic activity. These models allow us to extend the reconstructions back to before the development of the magnetometer and to cover the Maunder minimum. Allied to the radionuclide data, the models are revealing much about how the Sun and heliosphere behaved outside of grand solar maxima and are providing a means of predicting how solar activity is likely to evolve now that the recent grand maximum (that had prevailed throughout the space age) has come to an end.

Estimating the potential yield of small wind turbines in urban areas: a case study for Greater London, UK

To optimise the placement of small wind turbines in urban areas a detailed understanding of the spatial variability of the wind resource is required. At present, due to a lack of observations, the NOABL wind speed database is frequently used to estimate the wind resource at a potential site. However, recent work has shown that this tends to overestimate the wind speed in urban areas. This paper suggests a method for adjusting the predictions of the NOABL in urban areas by considering the impact of the underlying surface on a neighbourhood scale. In which, the nature of the surface is characterised on a 1 km2 resolution using an urban morphology database. The model was then used to estimate the variability of the annual mean wind speed across Greater London at a height typical of current small wind turbine installations. Initial validation of the results suggests that the predicted wind speeds are considerably more accurate than the NOABL values. The derived wind map therefore currently provides the best opportunity to identify the neighbourhoods in Greater London at which small wind turbines yield their highest energy production. The model does not consider street scale processes, however previously derived scaling factors can be applied to relate the neighbourhood wind speed to a value at a specific rooftop site. The results showed that the wind speed predicted across London is relatively low, exceeding 4 ms-1 at only 27% of the neighbourhoods in the city. Of these sites less than 10% are within 10 km of the city centre, with the majority over 20 km from the city centre. Consequently, it is predicted that small wind turbines tend to perform better towards the outskirts of the city, therefore for cities which fit the Burgess concentric ring model, such as Greater London, ‘distance from city centre’ is a useful parameter for siting small wind turbines. However, there are a number of neighbourhoods close to the city centre at which the wind speed is relatively high and these sites can only been identified with a detailed representation of the urban surface, such as that developed in this study.

Implications of the recent low solar minimum for the solar wind during the Maunder minimum

The behavior of the Sun and near-Earth space during grand solar minima is not understood; however, the recent long and low minimum of the decadal-scale solar cycle gives some important clues, with implications for understanding the solar dynamo and predicting space weather conditions. The speed of the near-Earth solar wind and the strength of the interplanetary magnetic field (IMF) embedded within it can be reliably reconstructed for before the advent of spacecraft monitoring using observations of geomagnetic activity that extend back to the mid-19th century. We show that during the solar cycle minima around 1879 and 1901 the average solar wind speed was exceptionally low, implying the Earth remained within the streamer belt of slow solar wind flow for extended periods. This is consistent with a broader streamer belt, which was also a feature of the recent low minimum (2009), and yields a prediction that the low near-Earth IMF during the Maunder minimum (1640-1700), as derived from models and deduced from cosmogenic isotopes, was accompanied by a persistent and relatively constant solar wind of speed roughly half the average for the modern era.

DIRTMAP: the geological record of dust.

Atmospheric dust is an important feedback in the climate system, potentially affecting the radiative balance and chemical composition of the atmosphere and providing nutrients to terrestrial and marine ecosystems. Yet the potential impact of dust on the climate system, both in the anthropogenically disturbed future and the naturally varying past, remains to be quantified. The geologic record of dust provides the opportunity to test earth system models designed to simulate dust. Records of dust can be obtained from ice cores, marine sediments, and terrestrial (loess) deposits. Although rarely unequivocal, these records document a variety of processes (source, transport and deposition) in the dust cycle, stored in each archive as changes in clay mineralogy, isotopes, grain size, and concentration of terrigenous materials. Although the extraction of information from each type of archive is slightly different, the basic controls on these dust indicators are the same. Changes in the dust flux and particle size might be controlled by a combination of (a) source area extent, (b) dust emission efficiency (wind speed) and atmospheric transport, (c) atmospheric residence time of dust, and/or (d) relative contributions of dry settling and rainout of dust. Similarly, changes in mineralogy reflect (a) source area mineralogy and weathering and (b) shifts in atmospheric transport. The combination of these geological data with process-based, forward-modelling schemes in global earth system models provides an excellent means of achieving a comprehensive picture of the global pattern of dust accumulation rates, their controlling mechanisms, and how those mechanisms may vary regionally. The Dust Indicators and Records of Terrestrial and MArine Palaeoenvironments (DIRTMAP) data base has been established to provide a global palaeoenvironmental data set that can be used to validate earth system model simulations of the dust cycle over the past 150,000 years.