71 research outputs found

    Interactions between downslope flows and a developing cold-air pool

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    A numerical model has been used to characterize the development of a region of enhanced cooling in an alpine valley with a width of order (Formula presented.) km, under decoupled stable conditions. The region of enhanced cooling develops largely as a region of relatively dry air which partitions the valley atmosphere dynamics into two volumes, with airflow partially trapped within the valley by a developing elevated inversion. Complex interactions between the region of enhanced cooling and the downslope flows are quantified. The cooling within the region of enhanced cooling and the elevated inversion is almost equally partitioned between radiative and dynamic effects. By the end of the simulation, the different valley atmospheric regions approach a state of thermal equilibrium with one another, though this cannot be said of the valley atmosphere and its external environment.Peer reviewe

    Pollutant dispersion in a developing valley cold-air pool

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    Pollutants are trapped and accumulate within cold-air pools, thereby affecting air quality. A numerical model is used to quantify the role of cold-air-pooling processes in the dispersion of air pollution in a developing cold-air pool within an alpine valley under decoupled stable conditions. Results indicate that the negatively buoyant downslope flows transport and mix pollutants into the valley to depths that depend on the temperature deficit of the flow and the ambient temperature structure inside the valley. Along the slopes, pollutants are generally entrained above the cold-air pool and detrained within the cold-air pool, largely above the ground-based inversion layer. The ability of the cold-air pool to dilute pollutants is quantified. The analysis shows that the downslope flows fill the valley with air from above, which is then largely trapped within the cold-air pool, and that dilution depends on where the pollutants are emitted with respect to the positions of the top of the ground-based inversion layer and cold-air pool, and on the slope wind speeds. Over the lower part of the slopes, the cold-air-pool-averaged concentrations are proportional to the slope wind speeds where the pollutants are emitted, and diminish as the cold-air pool deepens. Pollutants emitted within the ground-based inversion layer are largely trapped there. Pollutants emitted farther up the slopes detrain within the cold-air pool above the ground-based inversion layer, although some fraction, increasing with distance from the top of the slopes, penetrates into the ground-based inversion layer.Peer reviewe

    Evaluation of the performance of different atmospheric chemical transport models and inter-comparison of nitrogen and sulphur deposition estimates for the UK

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    An evaluation has been made of a number of contrasting atmospheric chemical transport models, of varying complexity, applied to estimate sulphur and nitrogen deposition in the UK. The models were evaluated by comparison with annually averaged measurements of gas, aerosol and precipitation concentrations from the national monitoring networks. The models were evaluated in relation to performance criteria. They were generally able to satisfy a criterion of ‘fitness for purpose’ that at least 50% of modelled concentrations should be within a factor of two of measured values. The second criterion, that the magnitude of the normalised mean bias should be less than 20%, was not always satisfied. Considering known uncertainties in measurement techniques, this criterion may be too strict. Overall, simpler models were able to give a good representation of measured gas concentrations whilst the use of dynamic meteorology, and complex photo-chemical reactions resulted in a generally better representation of measured aerosol and precipitation concentrations by more complex models. The models were compared graphically by plotting maps and cross-country transects of wet and dry deposition as well as calculating budgets of total wet and dry deposition to the UK for sulphur, oxidised nitrogen and reduced nitrogen. The total deposition to the UK varied by ±22–36% amongst the different models depending on the deposition component. At a local scale estimates of both dry and wet deposition for individual 5 km × 5 km model grid squares were found to vary between the different models by up to a factor of 4.This work was funded by the Department for the Environment, Food and Rural Affairs. Additional support was provided by the Joint Environmental Program, the Natural Environment Research Council and the Environment Agency.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.atmosenv.2015.08.00

    Interactions between the night time valley-wind system and a developing cold-air pool

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    This is a pre-copyedited, author-produced PDF of an article accepted for publication in Boundary-Layer Meteorology following peer review. The version of record [Arduini, G., Staquet, C & Chemel, C., ‘Interactions between the night time valley-wind system and a developing cold-air pool’, Boundary-Layer Meteorol (2016) 161:1 (49-72), first published online June 2, 2016, is available at Springer online at doi: 10.1007/s10546-016-0155-8The Weather Research and Forecast (WRF) numerical model is used to characterize the influence of a thermally-driven down-valley flow on a developing cold-air pool in an idealized alpine valley decoupled from the atmosphere above. Results for a three-dimensional (3D) valley, which allows for the formation of a down-valley flow, and for a two-dimensional (2D) valley, where the formation of a down-valley flow is inhibited, are analyzed and compared. A key result is that advection leads to a net cooling in the 2D valley and to a warming in the 3D valley, once the down-valley flow is fully developed. This difference stems from the suppression of the slope-flow induced upward motions over the valley centre in the 3D valley. As a result, the downslope flows develop a cross-valley circulation within the cold-air pool, the growth of the cold-air pool is reduced and the valley atmosphere is generally warmer than in the 2D valley. A quasi-steady state is reached for which the divergence of the down-valley flow along the valley is balanced by the convergence of the downslope flows at the top of the cold-air pool, with no net contribution of subsiding motions far from the slope layer. More precisely, the inflow of air at the top of the cold-air pool is found to be driven by an interplay between the return flow from the plain region and subsidence over the plateaux. Finally, the mechanisms that control the structure of the cold-air pool and its evolution are found to be independent of the valley length as soon as the quasi-steady state is reached and the down-valley flow is fully developed.Peer reviewedFinal Accepted Versio

    Evaluating the capability of regional-scale air quality models to cature the vertical distribution of pollutants

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    This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and European (EU) continents for 2006. The modelled concentrations of ozone and CO, along with the meteorological fields of wind speed (WS) and direction (WD), temperature (T), and relative humidity (RH), are compared against high-quality in-flight measurements collected by instrumented commercial aircraft as part of the Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out for five model domains positioned around four major airports in NA (Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt), from the surface to 8.5 km. We compare mean vertical profiles of modelled and measured variables for all airports to compute error and variability statistics, perform analysis of altitudinal error correlation, and examine the seasonal error distribution for ozone, including an estimation of the bias introduced by the lateral boundary conditions (BCs). The results indicate that model performance is highly dependent on the variable, location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being analysed. While model performance for T is satisfactory at all sites (correlation coefficient in excess of 0.90 and fractional bias ≀ 0.01 K), WS is not replicated as well within the PBL (exhibiting a positive bias in the first 100 m and also underestimating observed variability), while above 1000 m, the model performance improves (correlation coefficient often above 0.9). The WD at NA airports is found to be biased in the PBL, primarily due to an overestimation of westerly winds. RH is modelled well within the PBL, but in the free troposphere large discrepancies among models are observed, especially in EU. CO mixing ratios show the largest range of modelled-to-observed standard deviations of all the examined species at all heights and for all airports. Correlation coefficients for CO are typically below 0.6 for all sites and heights, and large errors are present at all heights, particularly in the first 250 m. Model performance for ozone in the PBL is generally good, with both bias and error within 20%. Profiles of ozone mixing ratios depend strongly on surface processes, revealed by the sharp gradient in the first 2 km (10 to 20 ppb km−1). Modelled ozone in winter is biased low at all locations in the NA, primarily due to an underestimation of ozone from the BCs. Most of the model error in the PBL is due to surface processes (emissions, transport, photochemistry), while errors originating aloft appear to have relatively limited impact on model performance at the surface. Suggestions for future work include interpretation of the model-to-model variability and common sources of model bias, and linking CO and ozone bias to the bias in the meteorological fields. Based on the results from this study, we suggest possible in-depth, process-oriented and diagnostic investigations to be carried out next

    Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

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    © 2016. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. Ioannis Kioutsioukis, et al, ‘Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data’, Atmospheric Chemistry and Physics, Vol 16(24): 15629-15652, published 20 December 2016, the version of record is available at doi:10.5194/acp-16-15629-2016 Published by Copernicus Publications on behalf of the European Geosciences Union.Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.Peer reviewedFinal Published versio
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