The gravity wave momentum flux in hydrostatic flow with directional shear over elliptical mountains

Semi-analytical expressions for the momentum flux associated with orographic internal gravity waves, and closed analytical expressions for its divergence, are derived for inviscid, stationary, hydrostatic, directionally-sheared flow over mountains with an elliptical horizontal cross-section. These calculations, obtained using linear theory conjugated with a third-order WKB approximation, are valid for relatively slowly-varying, but otherwise generic wind profiles, and given in a form that is straightforward to implement in drag parametrization schemes. When normalized by the surface drag in the absence of shear, a quantity that is calculated routinely in existing drag parametrizations, the momentum flux becomes independent of the detailed shape of the orography. Unlike linear theory in the Ri → ∞ limit, the present calculations account for shear-induced amplification or reduction of the surface drag, and partial absorption of the wave momentum flux at critical levels. Profiles of the normalized momentum fluxes obtained using this model and a linear numerical model without the WKB approximation are evaluated and compared for two idealized wind profiles with directional shear, for different Richardson numbers (Ri). Agreement is found to be excellent for the first wind profile (where one of the wind components varies linearly) down to Ri = 0.5, while not so satisfactory, but still showing a large improvement relative to the Ri → ∞ limit, for the second wind profile (where the wind turns with height at a constant rate keeping a constant magnitude). These results are complementary, in the Ri > O(1) parameter range, to Broad’s generalization of the Eliassen–Palm theorem to 3D flow. They should contribute to improve drag parametrizations used in global weather and climate prediction models.

Stochastic climate theory and modeling

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models.

Observing wind, aerosol particles, clouds and precipitation: Finland's new ground-based remote-sensing network

The Finnish Meteorological Institute, in collaboration with the University of Helsinki, has established a new ground-based remote-sensing network in Finland. The network consists of five topographically, ecologically and climatically different sites distributed from southern to northern Finland. The main goal of the network is to monitor air pollution and boundary layer properties in near real time, with a Doppler lidar and ceilometer at each site. In addition to these operational tasks, two sites are members of the Aerosols, Clouds and Trace gases Research InfraStructure Network (ACTRIS); a Ka band cloud radar at Sodankylä will provide cloud retrievals within CloudNet, and a multi-wavelength Raman lidar, PollyXT (POrtabLe Lidar sYstem eXTended), in Kuopio provides optical and microphysical aerosol properties through EARLINET (the European Aerosol Research Lidar Network). Three C-band weather radars are located in the Helsinki metropolitan area and are deployed for operational and research applications. We performed two inter-comparison campaigns to investigate the Doppler lidar performance, compare the backscatter signal and wind profiles, and to optimize the lidar sensitivity through adjusting the telescope focus length and data-integration time to ensure sufficient signal-to-noise ratio (SNR) in low-aerosol-content environments. In terms of statistical characterization, the wind-profile comparison showed good agreement between different lidars. Initially, there was a discrepancy in the SNR and attenuated backscatter coefficient profiles which arose from an incorrectly reported telescope focus setting from one instrument, together with the need to calibrate. After diagnosing the true telescope focus length, calculating a new attenuated backscatter coefficient profile with the new telescope function and taking into account calibration, the resulting attenuated backscatter profiles all showed good agreement with each other. It was thought that harsh Finnish winters could pose problems, but, due to the built-in heating systems, low ambient temperatures had no, or only a minor, impact on the lidar operation – including scanning-head motion. However, accumulation of snow and ice on the lens has been observed, which can lead to the formation of a water/ice layer thus attenuating the signal inconsistently. Thus, care must be taken to ensure continuous snow removal.

The effects of springtime mid-latitude storms on trace gas composition determined from the MACC reanalysis

The relationship between springtime air pollution transport of ozone (O3) and carbon monoxide (CO) and mid-latitude cyclones is explored for the first time using the Monitoring Atmospheric Composition and Climate (MACC) reanalysis for the period 2003–2012. In this study, the most intense spring storms (95th percentile) are selected for two regions, the North Pacific (NP) and the North Atlantic (NA). These storms (∼60 storms over each region) often track over the major emission sources of East Asia and eastern North America. By compositing the storms, the distributions of O3 and CO within a "typical" intense storm are examined. We compare the storm-centered composite to background composites of "average conditions" created by sampling the reanalysis data of the previous year to the storm locations. Mid-latitude storms are found to redistribute concentrations of O3 and CO horizontally and vertically throughout the storm. This is clearly shown to occur through two main mechanisms: (1) vertical lifting of CO-rich and O3-poor air isentropically, from near the surface to the mid- to upper-troposphere in the region of the warm conveyor belt; and (2) descent of O3-rich and CO-poor air isentropically in the vicinity of the dry intrusion, from the stratosphere toward the mid-troposphere. This can be seen in the composite storm's life cycle as the storm intensifies, with area-averaged O3 (CO) increasing (decreasing) between 200 and 500 hPa. The influence of the storm dynamics compared to the background environment on the composition within an area around the storm center at the time of maximum intensity is as follows. Area-averaged O3 at 300 hPa is enhanced by 50 and 36% and by 11 and 7.6% at 500 hPa for the NP and NA regions, respectively. In contrast, area-averaged CO at 300 hPa decreases by 12% for NP and 5.5% for NA, and area-averaged CO at 500 hPa decreases by 2.4% for NP while there is little change over the NA region. From the mid-troposphere, O3-rich air is clearly seen to be transported toward the surface, but the downward transport of CO-poor air is not discernible due to the high levels of CO in the lower troposphere. Area-averaged O3 is slightly higher at 1000 hPa (3.5 and 1.8% for the NP and NA regions, respectively). There is an increase of CO at 1000 hPa for the NP region (3.3%) relative to the background composite and a~slight decrease in area-averaged CO for the NA region at 1000 hPa (-2.7%).

JOYCE: Jülich Observatory for cloud evolution

The Jülich Observatory for Cloud Evolution (JOYCE), located at Forschungszentrum Jülich in the most western part of Germany, is a recently established platform for cloud research. The main objective of JOYCE is to provide observations, which improve our understanding of the cloudy boundary layer in a midlatitude environment. Continuous and temporally highly resolved measurements that are specifically suited to characterize the diurnal cycle of water vapor, stability, and turbulence in the lower troposphere are performed with a special focus on atmosphere–surface interaction. In addition, instruments are set up to measure the micro- and macrophysical properties of clouds in detail and how they interact with different boundary layer processes and the large-scale synoptic situation. For this, JOYCE is equipped with an array of state-of-the-art active and passive remote sensing and in situ instruments, which are briefly described in this scientific overview. As an example, a 24-h time series of the evolution of a typical cumulus cloud-topped boundary layer is analyzed with respect to stability, turbulence, and cloud properties. Additionally, we present longer-term statistics, which can be used to elucidate the diurnal cycle of water vapor, drizzle formation through autoconversion, and warm versus cold rain precipitation formation. Both case studies and long-term observations are important for improving the representation of clouds in climate and numerical weather prediction models.

Equations to predict methane emissions from cows fed at maintenance energy level in pasture-based systems

Ruminant production is a vital part of food industry but it raises environmental concerns, partly due to the associated methane outputs. Efficient methane mitigation and estimation of emissions from ruminants requires accurate prediction tools. Equations recommended by international organizations or scientific studies have been developed with animals fed conserved forages and concentrates and may be used with caution for grazing cattle. The aim of the current study was to develop prediction equations with animals fed fresh grass in order to be more suitable to pasture-based systems and for animals at lower feeding levels. A study with 25 nonpregnant nonlactating cows fed solely fresh-cut grass at maintenance energy level was performed over two consecutive grazing seasons. Grass of broad feeding quality, due to contrasting harvest dates, maturity, fertilisation and grass varieties, from eight swards was offered. Cows were offered the experimental diets for at least 2 weeks before housed in calorimetric chambers over 3 consecutive days with feed intake measurements and total urine and faeces collections performed daily. Methane emissions were measured over the last 2 days. Prediction models were developed from 100 3-day averaged records. Internal validation of these equations, and those recommended in literature, was performed. The existing in greenhouse gas inventories models under-estimated methane emissions from animals fed fresh-cut grass at maintenance while the new models, using the same predictors, improved prediction accuracy. Error in methane outputs prediction was decreased when grass nutrient, metabolisable energy and digestible organic matter concentrations were added as predictors to equations already containing dry matter or energy intakes, possibly because they explain feed digestibility and the type of energy-supplying nutrients more efficiently. Predictions based on readily available farm-level data, such as liveweight and grass nutrient concentrations were also generated and performed satisfactorily. New models may be recommended for predictions of methane emissions from grazing cattle at maintenance or low feeding levels.

Continental and global scale flood forecasting systems

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction.

The EarthCARE satellite: the next step forward in global measurements of clouds, aerosols, precipitation, and radiation

The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

Emission of polycyclic aromatic hydrocarbons from gasohol and ethanol vehicles

The exhaust emission of the polycyclic aromatic hydrocarbons (PAHs) considered toxic to human health were investigated on two spark ignition light duty vehicles, one being gasohol (Gasohol, in Brazil, is the generic denomination for mixtures of pure gasoline plus 20-25% of anhydrous ethyl alcohol fuel (AEAF).)-fuelled and the other a flexible-fuel vehicle fuelled with hydrated ethanol. The influence of fuel type and quality, aged lubricant oil type and use of fuel additives on the formation of these compounds was tested using standardized tests identical to US FTP-75 cycle. PAH sampling and chemical analysis followed the basic recommendations of method TO-13 (United States. Environmental Protection Agency, 1999. Compendium Method TO-13A - Determination of polycyclic Aromatic hydrocarbons (PAH) in Ambient Air Using Gas Chromatography/Mass Spectrometry (CG/MS). Center for environmental research information, Cincinnati, p. 78), with the necessary modification for this particular application. Results showed that the total PAH emission factor varied from 41.9 mu g km(-1) to 612 mu g km(-1) in the gasohol vehicle, and from 11.7 mu g km(-1) to 27.4 mu g km(-1) in the ethanol-fuelled vehicle, a significant difference in favor of the ethanol vehicle. Generally, emission of light molecular weight PAHs was predominant, while high molecular weights PAHs were not detected. In terms of benzo(a)pyrene toxicity equivalence, emission factors varied from 0.00984 mu g TEQ km(-1) to 4.61 mu g TEQ km(-1) for the gasohol vehicle and from 0.0117 mu g TEQ km(-1) to 0.0218 mu g TEQ km(-1) in the ethanol vehicle. For the gasohol vehicle, results showed that the use of fuel additive causes a significant increase in the emission of naphthalene and phenanthrene at a confidence level of 90% or higher; the use of rubber solvent on gasohol showed a reduction in the emission of naphthalene and phenanthrene at the same confidence level; the use of synthetic oil instead of mineral oil also contributed significantly to a decrease in the emission of naphthalene and fluorene. In relation to the ethanol vehicle, the same factors were tested and showed no statistically significant influence on PAH emission. (c) 2008 Elsevier Ltd. All rights reserved.

Characterization of Metal and Trace Element Contents of Particulate Matter (PM10) Emitted by Vehicles Running on Brazilian FuelsHydrated Ethanol and Gasoline with 22% of Anhydrous Ethanol

Emission of fine particles by mobile sources has been a matter of great concern due to its potential risk both to human health and the environment. Although there is no evidence that one sole component may be responsible for the adverse health outcomes, it is postulated that the metal particle content is one of the most important factors, mainly in relation to oxidative stress. Data concerning the amount and type of metal particles emitted by automotive vehicles using Brazilian fuels are limited. The aim of this study was to identify inhalable particles (PM10) and their trace metal content in two light-duty vehicles where one was fueled with ethanol while the other was fueled with gasoline mixed with 22% of anhydrous ethanol (gasohol); these engines were tested on a chassis dynamometer. The elementary composition of the samples was evaluated by the particle-induced x-ray emission technique. The experiment showed that total emission factors ranged from 2.5 to 11.8 mg/km in the gasohol vehicle, and from 1.2 to 3 mg/km in the ethanol vehicle. The majority of particles emitted were in the fine fraction (PM2.5), in which Al, Si, Ca, and Fe corresponded to 80% of the total weight. PM10 emissions from the ethanol vehicle were about threefold lower than those of gasohol. The elevated amount of fine particulate matter is an aggravating factor, considering that these particles, and consequently associated metals, readily penetrate deeply into the respiratory tract, producing damage to lungs and other tissues.

Vehicular particulate matter emissions in road tunnels in Sao Paulo, Brazil

In the metropolitan area of Sao Paulo, Brazil, ozone and particulate matter ( PM) are the air pollutants that pose the greatest threat to air quality, since the PM and the ozone precursors ( nitrogen oxides and volatile organic compounds) are the main source of air pollution from vehicular emissions. Vehicular emissions can be measured inside road tunnels, and those measurements can provide information about emission factors of in-use vehicles. Emission factors are used to estimate vehicular emissions and are described as the amount of species emitted per vehicle distance driven or per volume of fuel consumed. This study presents emission factor data for fine particles, coarse particles, inhalable particulate matter and black carbon, as well as size distribution data for inhalable particulate matter, as measured in March and May of 2004, respectively, in the Janio Quadros and Maria Maluf road tunnels, both located in Sao Paulo. The Janio Quadros tunnel carries mainly light-duty vehicles, whereas the Maria Maluf tunnel carries light-duty and heavy-duty vehicles. In the Janio Quadros tunnel, the estimated light-duty vehicle emission factors for the trace elements copper and bromine were 261 and 220 mu g km(-1), respectively, and 16, 197, 127 and 92 mg km(-1), respectively, for black carbon, inhalable particulate matter, coarse particles and fine particles. The mean contribution of heavy-duty vehicles to the emissions of black carbon, inhalable particulate matter, coarse particles and fine particles was, respectively 29, 4, 6 and 6 times higher than that of light-duty vehicles. The inhalable particulate matter emission factor for heavy-duty vehicles was 1.2 times higher than that found during dynamometer testing. In general, the particle emissions in Sao Paulo tunnels are higher than those found in other cities of the world.

Tibouchina pulchra (Cham.) Cogn., a native Atlantic Forest species, as a bio-indicator of ozone: Visible injury

Tibouchina pulchra saplings were exposed to carbon filtered air (CF), ambient non-filtered air (NF) and ambient non-filtered air + 40 ppb ozone (NF + O-3) 8 h per day during two months. The AOT40 values at the end of the experiment were 48, 910 and 12,895 ppb h(-1), respectively, for the three treatments. After 25 days of exposure (AOT40=3871 ppb h(-1)), interveinal red stippling appeared in plants in the NF + O-3 chamber. In the NF chamber, symptoms were observed only after 60 days of exposure (AOT40 = 910 ppb h(-1)). After 60 days, injured leaves per plant corresponded to 19% in NF + O-3 and 1% in the NF treatment; and the average leaf area injured was 7% within the NF + O-3 and 0.2% within the NF treatment. The extent of leaf area injured (leaf injury index) was mostly explained by the accumulated exposure of ozone (r(2) = 0.89; p < 0.05). (C) 2007 Elsevier Ltd. All rights reserved.

Leaf antioxidant fluctuations and growth responses in saplings of Caesalpinia echinata Lam. (brazilwood) under an urban stressing environment

We intended to establish how efficient the leaf antioxidant responses of C. echinata are against oxidative environmental conditions observed in an urban environment and their relations to growth and biomass parameters. Plants were grown for 15 months in four sites: Congonhas and Pinheiros, affected by pollutants from vehicular emissions; Ibirapuera, affected by high O(3) concentrations; and a greenhouse with filtered air. Fifteen plants were quarterly removed from each site for analysis of antioxidants, growth and biomass. Plants growing in polluted sites showed alterations in their antioxidants. They were shorter, had thicker stems and produced less leaf biomass than plants maintained under filtered air. The fluctuations in the levels of antioxidants were significantly influenced by combined effects of climatic and pollution variables. The higher were the antioxidant responses and the concentrations of pollutant markers of air contamination in each site the slower were the growth and biomass production. (C) 2009 Elsevier Inc. All rights reserved.

Sub-tropical urban environment affecting content and composition of non-structural carbohydrates of Lolium multiflorum ssp italicum cv. Lema

This study analyzed the relationship between environmental factors, especially air pollution and climatic conditions, and non-structural carbohydrates (NSC) in plants of Lolium multiflorum exposed during 10 consecutive periods of 28 days at a polluted site (Congonhas) and at a reference site in Sao Paulo city (Brazil). After exposure, NSC composition and leaf concentrations of Al, Fe. Cu, Zn, Pb and Cd were measured. The seasonal pattern of NSC accumulation was quite similar in both sites, but plants at Congonhas showed higher concentrations of these compounds, especially fructans of low and medium degree of polymerization. Regression analysis showed that NSC in plants growing at the polluted site were explained by variations on temperature and leaf concentration of Fe (positive effect), as well as relative humidity and particulate material (negative effect). NSC in the standardized grass culture, in addition to heavy metal accumulation, may indicate stressing conditions in a sub-tropical polluted environment. (C) 2008 Elsevier Ltd. All rights reserved.