A thermodynamic model of freshwater Antarctic lake ice

Antarctic lakes with simple plankton ecosystems are believed to be sensitive biological indicators of climate change. Models of the physical environment, in particular the ice layer, support understanding of how the ecosystems respond to meteorological variables. This paper describes how data from a previously reported automatic measuring probe and meteorological data from Davis station were used to develop a detailed thermodynamic model of the ice layer on Crooked Lake, one of the largest and deepest freshwater lakes in Antarctica. The general model structure is similar to a previously reported model of sea ice but with modifications specific to the Antarctic freshwater lake case informed by the data. The model inputs are atmospheric variables as well as water temperature, ice albedo and the radiation extinction coefficient for the ice. Heat and radiation fluxes at the ice–air and ice–water boundaries are calculated using equations chosen for their suitability for the Antarctic. In the case of shortwave radiation, equations were fitted to data from the automatic probe. Using the heat fluxes to establish boundary conditions, and incorporating the known thermodynamic properties of ice, the temperature profile within the ice and the resulting growth and melt of the ice can be calculated. The model uses a largely mechanistic approach, with most equations taken from established thermodynamic theories or empirical studies and only one adjustable parameter related to the sensible heat flux from the water, which is not easily calculated from the available data. It was found to accurately reproduce ice temperature and ice thickness data for the year 2003, with r² = 0.89, n = 2005. Finally, the model was simplified to run with air temperature as the only input variable and was shown to perform well—this suggests that freshwater lake ice is affected more by air temperature than any other variable, and is therefore a useful indicator of climate change in its own right.     

A comparative study of prognostic MM5 meteorological modeling with aircraft, wind profiler, lidar, tethered balloon and RASS data over Philadelphia during a 1999 summer episode

This study presents a comparative evaluation of the prognostic meteorological Fifth Generation NCAR Pennsylvania State University Mesoscale Model (MM5) using data from the Northeast Oxidant and Particle Study (NE-OPS) research program collected over Philadelphia, PA during a summer episode in 1999. A set of model simulations utilizing a nested grid of 36 km, 12 km and 4 km horizontal resolutions with 21 layers in the vertical direction was performed for a period of 101 h from July 15, 1999; 12 UTC to July 19, 1999; 17 UTC. The model predictions obtained with 4 km horizontal grid resolution were compared with the NE-OPS observations. Comparisons of model temperature with aircraft data revealed that the model exhibited slight underestimation as noted by previous investigators. Comparisons of model temperature with aircraft and tethered balloon data indicate that the mean absolute error varied up to 1.5 °C. The comparisons of model relative humidity with aircraft and tethered balloon indicate that the mean relative error varied from –11% to –22% for the tethered balloon and from –5% to –30% for the aircraft data. The mean relative error for water vapor mixing ratio with respect to the lidar data exhibited a negative bias consistent with the humidity bias corresponding to aircraft and tethered balloon data. The tendency of MM5 to produce estimates of very low wind speeds, especially in the early-mid afternoon hours, as noted by earlier investigators, is seen in this study also. It is indeed true that the initial fields as well as the fields utilized in the data assimilation also contribute to some of the differences between the model and observations. Studies such as these which compare the grid averaged mean state variables with observations have inherent difficulties. Despite the above limitations, the results of the present study broadly conform to the general traits of MM5 as noted by earlier investigators.     

A Large-Eddy Simulation Study of the Convective Boundary Layer over Philadelphia during the 1999 Summer NE-OPS Campaign

This study presents a large-eddy simulation (LES) study of the convective boundary layer on August 1, 1999 over Philadelphia, PA during a summer ozone episode. The study is an evaluation of the Colorado State University's Regional Atmospheric Modeling System Version 4.3 (RAMS4.3) with the LES option using Northeast Oxidant and Particulate Study (NE-OPS) data. Simulations were performed with different imposed sensible heat fluxes at the ground surface. The model was initialized with the atmospheric sounding data collected at Philadelphia at 1230 UTC and model integrations continued till 2130 UTC. The resulting mean profiles of temperature and humidity obtained from the LES model were compared with atmospheric soundings, tethered balloon and aircraft data collected during the NE-OPS 1999 field campaign. Also the model-derived vertical profiles of virtual temperature were compared with NE-OPS Radio Acoustic Sounder System (RASS) data while the humidity profiles were compared with NE-OPS lidar data. The comparison of the radiosonde data with the LES model predictions suggests that the growth of the mixing layer is reasonably well simulated by the model. Overall, the agreement of temperature predictions of the LES model with the radiosonde observations is good. The model appears to underestimate humidity values for the case of higher imposed sensible heat flux. However, the humidity values in the mixing layer agree quite well with radiosonde observations for the case of lower imposed sensible heat flux. The model-predicted temperature and humidity profiles are in reasonable agreement with the tethered balloon data except for some small overestimation of temperature at lower layers and some underestimation of humidity values. However, the humidity profiles as simulated by the model agree quite well with the tethered balloon data for the case of lower imposed sensible heat flux. The model-predicted virtual temperature profile is also in better agreement with RASS data for the case of lower imposed sensible heat flux. The model-predicted temperature profile further agrees quite well with aircraft data for the case of lower imposed heat flux. However, the relative humidity values predicted by the model are lower compared with the aircraft data. The model-predicted humidity profiles are only in partial agreement with the lidar data. The results of this study suggest that the explicitly resolved energetic eddies seem to provide the correct forcing necessary to produce good agreement with observations for the case of an imposed sensible heat flux of 0.1 K m s^–1 at the surface.     

Sensitivity of atmospheric dispersion simulations by HYSPLIT to the meteorological predictions from a meso-scale model

Mesoscale transport and dispersion of air pollutants from a few major point sources in the Mississippi Gulf coastal region is calculated using a coupled modeling system consisting of the atmospheric dynamical model WRF and the lagrangian particle model HYSPLIT. The sensitivity of the dispersion model results to the meteorological fields is studied by conducting an ensemble of simulations using the WRF model for the same dispersion case. Several parameterization schemes for the physical processes of boundary layer turbulence and land surface temperature/moisture prediction in WRF are used in various combinations to produce different meteorological members which are then used for dispersion simulation. The uncertainty in the simulated concentration probabilities to the meteorological model configurations and the ensemble mean are presented. The parameters used for determining the uncertainties include the wind fields, temperature, area of concentration and the levels of concentration. The results indicate that dispersion model results are influenced by the choices made in respect of the planetary boundary layer and land surface schemes in the mesoscale model to produce the meteorological forecast thereby leading to certain amount of uncertainty in the resultant concentrations. Results show that the specific choices made about the atmospheric model configuration can significantly after the simulated concentrations.     

Abundance and variability of microorganisms and transparent exopolymer particles across the ice–water interface of melting first-year sea ice in the Laptev Sea (Arctic)

The distribution and abundance of transparent exopolymer particles (TEP) was determined in and below pack ice of the Laptev Sea from July to September 1995. Samples were collected from the lowermost 10 cm of ice floes and at 10 cm below the ice–water interface. Abundance of bacteria, protists and TEP was determined, and the sea ice–water boundary layer was characterized using temperature, salinity and molecular viscous shear stress. TEP, with a distinct size distribution signal, were found in highest concentrations inside the sea ice, ranging from not detectable to 16 cm² l⁻¹ (median: 2.9 cm² l⁻¹). In the water, concentrations were one order of magnitude lower, ranged from below detection to 2.7 cm² l⁻¹ (median: 0.2 cm² l⁻¹) and decreased after the middle of August, whereas abundances of autotrophic flagellates (AF), diatoms, heterotrophic flagellates (HF) and ciliates increased. The abundance of TEP decreased with its size in all samples following a power law relationship. The relation of TEP to the microbial community differed between the sea ice and water, being positively correlated with bacteria and diatoms in the ice and negatively correlated with HF in the sea water. The presence of a pycnocline significantly influenced the abundance of organisms, diatom composition and TEP concentrations. Pennate diatoms dominated by Nitzschia frigida were most abundant inside the ice. Though bacteria have the potential to produce exopolymeric substances (EPS), the results of this study indicate that the majority of TEP at the ice–water interface in first-year Arctic summer pack ice are produced by diatoms. Received: 19 August 1999 / Accepted: 4 July 2000     

Major PM10 source location by a spatial multivariate receptor model

We present a multivariate receptor model for identifying the spatial location of major PM₁₀ pollution sources through the concentrations at multiple monitoring stations. We build on a mixed multiplicative log-normal factor model adjusting the source contributions for meteorological covariates and for temporal correlation and considering source profiles as compositional Gaussian random fields, to account for the variability induced by the spatial distribution of the monitoring sites. Taking a Bayesian approach to estimation, the proposed hierarchical model is implemented and used to analyze average daily PM₁₀ concentration measurements from 13 monitoring sites in Taranto, Italy, for the period April–December 2005. Three major sources of pollution are identified and characterized in terms of their spatial and temporal behavior and in relation to meteorological data.     

呼伦湖冰封期污染特征分析及对水处理的意义

以内蒙古呼伦湖为研究对象,对其在冰封过程中总氮、总磷和有机物在冰体和水体中的浓度及分布特征及其在呼伦湖的空间变异性进行分析。结果表明,冰封条件下,呼伦湖水体中总氮、总磷和有机物的含量均大于其在对应冰体中的含量,其含量均值分别是其对应冰体中的3.144倍、2.200倍和3.042倍,即低温冷冻过程对水体中的污染物有一定的浓缩效应;水体中各营养盐和有机物的空间变异性明显小于其在冰体中的;从固-液相平衡理论、结晶学理论和热力学理论三个方面对冷冻浓缩效应做出了合理的解释。研究认为,可以将冷冻浓缩效应运用到给水处理和污水处理领域,这样既可以进行大规模的处理,也可以节约资源、保护环境。     

Vertical fine structure of the biomass and composition of algal communities in Arctic pack ice

The biomass and composition of algal communities in sea ice were studied during two summer expeditions to the central Arctic Ocean and the Greenland Sea. Based on algal pigment determination and cell counts, high biomass accumulations were found at the surface, in the interior and in the bottom layer of the ice floes. Pennate diatoms dominated in the bottom layer, while phototrophic flagellates and cysts of unknown origin were the most abundant taxa in the upper parts. The lowermost 20 to 40 cm contained between 4 and 62% of the entire algal biomass. Consequently, ice biological studies, which deal only with the bottom few centimetres of the ice floes, will underestimate algal biomass and production by factors of up to 25. Differences between the results of this study and published data from coastal locations point towards different biological regimes in Arctic sea ice. The algal biomass in coastal ice is about two orders of magnitude higher and composed mainly of diatoms, probably supported by nutrient influx from the water column. In the pack ice of the central Arctic, nutrient supply is probably reduced, and flagellates contribute substantially to total algal biomass. However, methodological problems might partially be responsible for the observed differences. Received: 12 June 1998 / Accepted: 11 December 1998     

A Multimedia Chemical Fate Model with Time-Dependent Air-Water Transfer Rates

A multimedia model for the temporal evolution of the concentration of chemical species in a water basin and its bottom sediment layer has been tested with time-dependent air-water transfer rates varying with the meteorological conditions over the basin. The multimedia model uses the chemical fugacity approach in a system of two ordinary differential equations for the chemical species partition in the two mentioned media, with transfer through the sediment-water and the air-water interfaces. The air-water transfer rates are estimated by a micrometeorological preprocessor. A scenario in which known concentrations in air of a soluble pollutant (benzene) induce water and sediment pollution is tested on both synthetic (MonteCarlo-simulated) and real series of meteorological data. It is found that the use of time-dependent transfer coefficients affects not only the relaxation time, but also the long term concentration of the pollutant in water and sediment, that differs between 10 and 40% in the examined cases when compared with the same multimedia model using average constant transfer rates as usual. This is shown to be due to the statistical correlations between meteorological parameters and air pollutant concentrations, which stresses the advantages of a time-dependent estimation of the transfer coefficients. Correction terms are proposed to take into account the correlation effects when a constant parameters multimedia model is used.     

呼伦湖冰封期污染特征分析及对水处理的意义

以内蒙古呼伦湖为研究对象,对其在冰封过程中总氮、总磷和有机物在冰体和水体中的浓度及分布特征及其在呼伦湖的空间变异性进行分析。结果表明,冰封条件下,呼伦湖水体中总氮、总磷和有机物的含量均大于其在对应冰体中的含量,其含量均值分别是其对应冰体中的3.144倍、2.200倍和3.042倍,即低温冷冻过程对水体中的污染物有一定的浓缩效应;水体中各营养盐和有机物的空间变异性明显小于其在冰体中的;从固-液相平衡理论、结晶学理论和热力学理论三个方面对冷冻浓缩效应做出了合理的解释。研究认为,可以将冷冻浓缩效应运用到给水处理和污水处理领域,这样既可以进行大规模的处理,也可以节约资源、保护环境。     

Airborne hydrophilic microplastics in cloud water at high altitudes and their role in cloud formation

Microplastic pollution is occurring in most ecosystem, yet their presence in high altitude clouds and their influence on cloud formation and climate change are poorly known. Here we analyzed microplastics in cloud water sampled at the summits of Japan mountains at 1300–3776 m altitude by attenuated total reflection imaging and micro-Fourier transform infrared spectroscopy. We observed nine microplastics including polyethylene, polypropylene, polyethylene terephthalate, polymethyl methacrylate, polyamide 6, polycarbonate, ethylene–propylene copolymer or polyethylene–polypropylene alloy, polyurethane, and epoxy resin. Microplastic were fragmented, with mean concentrations ranging from 6.7 to 13.9 pieces per liter, and with Feret diameters ranging from 7.1 to 94.6 μm. Microplastics bearing hydrophilic groups such as carbonyl and/or hydroxyl groups were abundant, suggesting that they might have acted as condensation nuclei of cloud ice and water. Overall, our finding suggest that high-altitude microplastics cloud influence cloud formation and, in turn, might modify the climate.

     

Estimation of urban sensible heat flux using a dense wireless network of observations

The determination of the sensible heat flux over urban terrain is challenging due to irregular surface geometry and surface types. To address this, in 2006–07, a major field campaign (LUCE) took place at the école Polytechnique Fédérale de Lausanne campus, a moderately occupied urban site. A distributed network of 92 wireless weather stations was combined with routine atmospheric profiling, offering high temporal and spatial resolution meteorological measurements. The objective of this study is to estimate the sensible heat flux over the built environment under convective conditions. Calculations were based on Monin–Obukhov similarity for temperature in the surface layer. The results illustrate a good agreement between the sensible heat flux inferred from the thermal roughness length approach and independent calibrated measurements from a scintillometer located inside the urban canopy. It also shows that using only one well-selected station can provide a good estimate of the sensible heat flux over the campus for convective conditions. Overall, this study illustrates how an extensive network of meteorological measurements can be a useful tool to estimate the sensible heat flux in complex urban environments.     

Determination of the optimum MM5 configuration for long term CMAQ simulations of aerosol bound pollutants in Europe

Realistic meteorological fields are a prerequisite for the determination of pollutant concentrations and depositions by means of a chemistry transport model. Different configurations of the 5th generation NCAR/Penn State University mesoscale meteorological model MM5 were tested to determine the optimum set up for long term hindcasts that cover several months up to years. Four dimensional data assimilation (FDDA) significantly enhances the spatio temporal representation of temperature, humidity and wind. Best agreement with radiosonde observations could be achieved when temperature, humidity and wind were grid nudged every 6 h. The quality of the resulting meteorological fields showed no significant systematic temporal or spatial variation over Europe in a model run of the year 2000. It was found that the hydrological cycle was not correctly reproduced by the model when no nudging was applied. The relevant model run showed too high relative humidity and too high rainfall when compared to observations. This led to considerably lower aerosol concentrations close to ground and a shift in the deposition patterns of particle bound pollutants like the carcinogenic benzo(a)pyrene (B(a)P). Guest Editor: Dr. S. T. Rao.     

天气条件对福州近地层臭氧分布的影响

利用2009—2010年福州市近地层臭氧连续观测资料,并结合气象资料分析不同天气型对臭氧浓度变化的影响,以及臭氧浓度与气象要素的相关性。结果表明：在高压后部、地面倒槽等6种天气型影响下,福州市臭氧浓度值较高;在低涡锋面、台风（热带辐合带）等4种天气型影响下,臭氧浓度值较低。导致福州市臭氧平均浓度值最高的天气型是台风（热带辐合带）外围,最低的是低涡锋面系统。高压后部、地面倒槽和锋前暖区等强暖性、且非常不利于污染物扩散的天气型易造成臭氧浓度超标。臭氧浓度与气象要素关系密切,与温度、日照、太阳辐射显著正相关,与云量、相对湿度、降水量显著负相关,受偏南和偏东风影响,平均风速较大时,臭氧浓度较高,在SSE方位上臭氧小时浓度超标率最高。     

Mass Transport in Vegetated Shear Flows

Submerged aquatic vegetation has the potential to greatly improve water quality through the removal of nutrients, particulates and trace metals. The efficiency of this removal depends heavily upon the rate of vertical mixing, which dictates the timescale over which these constituents remain in the canopy. Continuous dye injection experiments were conducted in a flume with model vegetation to characterize vertical mass transport in vegetated shear flows. Through the absorbance–concentration relationship of the Beer–Lambert Law, digital imaging was used to provide high-resolution concentration profiles of the dye plumes. Vertical mass transport is dominated by the coherent vortices of the vegetated shear layers. This is highlighted by the strong periodicity of the transport and its simple characterization based on properties of the shear layer. For example, the vertical turbulent diffusivity is directly proportional to the shear and thickness of the layer. The turbulent diffusivity depends upon the size of the plume, such that the rate of plume growth is lower near the source. In the far-field, mass is mixed more than twice as rapidly as momentum. Finally, plume size is dictated predominantly by X, a dimensionless distance that scales upon the number of vortex rotations experienced by the plume.     

Stability and Mixing of a Vertical Axisymmetric Buoyant Jet in Shallow Water

The stability, mixing and effect of downstream control on axisymmetric turbulent buoyant jets discharging vertically into shallow stagnant water is studied using 3D Reynolds-averaged Navier–Stokes equations (RANS) combined with a buoyancy-extended k –ε model. The steady axisymmetric turbulent flow, temperature (or tracer concentration) and turbulence fields are computed using the finite volume method on a high resolution grid. The numerical predictions demonstrate two generic flow patterns for different turbulent heated jet discharges and environmental parameters (i) a stable buoyant discharge with the mixed fluid leaving the vertical jet region in a surface warm water layer; and (ii) an unstable buoyant discharge with flow recirculation and re-entrainment of heated water. A stratified counterflow region always appears in the far-field for both stable and unstable buoyant discharges. Provided that the domain radius L exceeds about 6H, the near field interaction and hence discharge stability is governed chiefly by the jet momentum length scale to depth ratio l_M/H, regardless of downstream control. The near field jet stability criterion is determined to be l_M/H = 3.5. A radial internal hydraulic jump always exists beyond the surface impingement region, with a 3- to 6-fold increase in dilution across the jump compared with vertical buoyant jet mixing. The predicted stability category, velocity and temperature/concentration fields are well-supported by experiments of all previous investigators.     

Performance analysis of WRF and LES in describing the evolution and structure of the planetary boundary layer

We implemented the Weather Research and Forecast (WRF) model and WRF Large-Eddy Simulation (WRF–LES), focusing on calculations for the planetary boundary layer (PBL), and compared the results against a data set of a well-documented campaign, in the Houston–Galveston area, Texas, in summer 2006. A methodology using WRF in a mesoscale and LES was implemented to assess the performance of the model in simulating the evolution and structure of the PBL over Houston during the Vertical Mixing Experiment. Also, the WRF model in a real case mode was examined to explore potential differences between the results of each simulation approach. We analyzed both WRF results for key meteorological parameters like wind speed, wind direction and potential temperature, and compared the model results against the observations. The reasonably good agreement of LES results forced with observed surface fluxes provides confidence that LES describes turbulence quantities such as turbulent kinetic energy correctly and warrants further turbulence structure analysis. The LES results indicate a weak but noticeable nighttime turbulent kinetic energy which was produced by wind shear in Houston’s planetary boundary layer and which may likely be related to intermittent turbulence. This is supported by observations made at the University of Houston Moody Tower air quality station when intermittent peaks of carbon monoxide occurred in the evening, although the variability in wind conditions was very little.     

Intercomparison of Two Models,ETA and RAMS,with TRACT Field Campaign Data

In this work a model intercomparison between RAMS and ETA models is carried out, with the aim of evaluating the quality and accuracy of these mesoscale models in reproducing the time evolution of the meteorology in real complex terrain. This is of great importance not only for meteorological forecast but also for air quality assessment. Numerical simulations are performed to reproduce the mean variables' fields and to compare them with measurements collected during the field campaign TRACT. The domain covers the Rhine valley and surrounding mountainous region and we consider a time period of two days. Results from simulations are compared to observations relative to ground stations and radiosoundings. A qualitative analysis is joined to a quantitative estimation of some reference statistical indexes. Both RAMS and ETA models performances are satisfactory when compared to the measured data and also their relative agreement is good. The mean variable fields are reproduced with a satisfactory degree of reliability, even if the simulated profiles are not able to describe the largest fluctuations of the variables. At the surface stations, the best agreement between predictions and observations is obtained for the wind velocity, while the quality of the results is lower for temperature and humidity.     

Numerical Investigation of the Effects of Boundary-Layer Evolution on the Predictions of Ozone and the Efficacy of Emission Control Options in the Northeastern United States

This paper examines the effects of two different planetary boundary-layer (PBL) parameterization schemes – Blackadar and Gayno–Seaman – on the predicted ozone (O₃) concentration fields using the MM5 (Version 3.3) meteorological model and the MODELS-3 photochemical model. The meteorological fields obtained from the two boundary-layer schemes have been used to drive the photochemical model to simulate O₃ concentrations in the northeastern United States for a three-day O₃ episodic period. In addition to large differences in the predicted O₃ levels at individual grid cells, the simulated daily maximum 1-h O₃ concentrations appear at different regions of the modeling domain in these simulations, due to the differences in the vertical exchange formulations in these two PBL schemes. Using process analysis, we compared the differences between the different simulations in terms of the relative importance of chemical and physical processes to O₃ formation and destruction over the diurnal cycle. Finally, examination of the photochemical model's response to reductions in emissions reveals that the choice of equally valid boundary-layer parameterizations can significantly influence the efficacy of emission control strategies.     

Prediction of sulphur removal with Acidithiobacillus sp. using artificial neural networks

Artificial neural network (ANN) model was used to predict the extent of sulphur removal from three types of coal using native cultures of Acidithiobacillus ferrooxidans. The type of coal, initial pH, pulp density, particle size, residence time, media composition and initial sulphur content of coal were fed as input to the network. The output of the model was sulphur removal. The resulting ANN showed satisfactory prediction of sulphur removal percentages with mean absolute deviations varying from 0.003 to 0.5. A three layer feed forward neural network model consisting of an input layer, one hidden layer and an output layer was found to give satisfactory results. Although the number of data sets were limited, the parity plot shows that the model estimations for the test set was good.