Comparison of atmospheric modelling systems simulating the flow,turbulence and dispersion at the microscale within obstacles

Three different modelling techniques to simulate the pollutant dispersion in the atmosphere at the microscale and in presence of obstacles are evaluated and compared. The Eulerian and Lagrangian approaches are discussed, using RAMS6.0 and MicroSpray models respectively. Both prognostic and diagnostic modelling systems are considered for the meteorology as input to the Lagrangian model, their differences and performances are investigated. An experiment from the Mock Urban Setting Test field campaign observed dataset, measured within an idealized urban roughness, is used as reference for the comparison. A case in neutral conditions was chosen among the available ones. The predicted mean flow, turbulence and concentration fields are analysed on the basis of the observed data. The performances of the different modelling approaches are compared and their specific characteristics are addressed. Given the same flow and turbulence input fields, the quality of the Lagrangian particle model is found to be overall comparable to the full-Eulerian approach. The diagnostic approach for the meteorology shows a worse agreement with observations than the prognostic approach but still providing, in a much shorter simulation time, fields that are suitable and reliable for driving the dispersion model.     

Examination of model predictions at different horizontal grid resolutions

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs and data requirements increase significantly with increasing grid resolution. Therefore, it is important to examine, for any given application, whether the expected benefit of increased grid resolution justifies the extra costs. In this study, we examine temperature and ozone observations and model predictions for three high ozone episodes that occurred over the northeastern United States during the summer of 1995. In the first set of simulations, the meteorological model RAMS4a was run with three two-way nested grids of 108/36/12 km grid spacing covering the United States and the photochemical model UAM-V was run with two grids of 36/12 km grid spacing covering the eastern United States. In the second set of simulations, RAMS4a was run with four two-way nested grids of 108/36/12/4 km grid spacing and UAM-V was run with three grids of 36/12/4 km grid spacing with the finest resolution covering the northeastern United States. Our analysis focuses on the comparison of model predictions for the finest grid domain of the simulations, namely, the region overlapping the 12 km and 4 km domains. A comparison of 12 km versus 4 km fields shows that the increased grid resolution leads to finer texture in the model predictions; however, comparisons of model predictions with observations do not reveal the expected improvement in the predictions. While high-resolution modeling has scientific merit and potential uses, the currently available monitoring networks, in conjunction with the scarceness of highly resolved spatial input data and the limitations of model formulation, do not allow confirmation of the expected superiority of the high-resolution model predictions.The U.S. Governments right to retain a non-exclusive royalty-free licence in and to any copyright is acknowledged.     

The performance of RAMS in representing the convective boundary layer structure in a very steep valley

Data from a comprehensive field study in the Riviera Valley of Southern Switzerland are used to investigate convective boundary layer structure in a steep valley and to evaluate wind and temperature fields, convective boundary layer height, and surface sensible heat fluxes as predicted by the mesoscale model RAMS. Current parameterizations of surface and boundary layer processes in RAMS, as well as in other mesoscale models, are based on scaling laws strictly valid only for flat topography and uniform land cover. Model evaluation is required to investigate whether this limits the applicability of RAMS in steep, inhomogeneous terrain. One clear-sky day with light synoptic winds is selected from the field study. Observed temperature structure across and along the valley is nearly homogeneous while wind structure is complex with a wind speed maximum on one side of the valley. Upvalley flows are not purely thermally driven and mechanical effects near the valley entrance also affect the wind structure. RAMS captured many of the observed boundary layer characteristics within the steep valley. The wind field, temperature structure, and convective boundary layer height in the valley are qualitatively simulated by RAMS, but the horizontal temperature structure across and along the valley is less homogeneous in the model than in the observations. The model reproduced the observed net radiation, except around sunset and sunrise when RAMS does not take into account the shadows cast by the surrounding topography. The observed sensible heat fluxes fall within the range of simulated values at grid points surrounding the measurement sites. Some of the scatter between observed and simulated turbulent sensible heat fluxes are due to sub-grid scale effects related to local topography.     

Multiscale Plume Transport from the Collapse of the World Trade Center on September 11, 2001

The collapse of the world trade center (WTC) produced enhanced levels of airborne contaminants in New York City and nearby areas on September 11, 2001 through December, 2001. This catastrophic event revealed the vulnerability of the urban environment, and the inability of many existing air monitoring systems to operate efficiently in a crisis. The contaminants released circulated within the street canyons, but were also lifted above the urban canopy and transported over large distances, reflecting the fact that pollutant transport affects multiple scales, from single buildings through city blocks to mesoscales. In this study, ground-and space-based observations were combined with numerical weather forecast fields to initialize fine-scale numerical simulations. The effort is aimed at reconstructing pollutant dispersion from the WTC in New York City to surrounding areas, to provide means for eventually evaluating its effect on population and environment. Atmospheric dynamics were calculated with the multi-grid Regional Atmospheric Modeling System (RAMS), covering scales from 250 m to 300 km and contaminant transport was studied using the Hybrid Particle and Concentration Transport (HYPACT) model that accepts RAMS meteorological output. The RAMS/HYPACT results were tested against PM2.5 observations from the roofs of public schools in New York City (NYC), Landsat images, and Multi-angle Imaging SpectroRadiometer (MISR) retrievals. Calculations accurately reproduced locations and timing of PM2.5 peak aerosol concentrations, as well as plume directionality. By comparing calculated and observed concentrations, the effective magnitude of the aerosol source was estimated. The simulated pollutant distributions are being used to characterize levels of human exposure and associated environmental health impacts.     

Sensitivity of ecological models to their climate drivers: statistical ensembles for forcing.

Global and regional numerical models for terrestrial ecosystem dynamics require fine spatial resolution and temporally complete historical climate fields as input variables. However, because climate observations are unevenly spaced and have incomplete records, such fields need to be estimated. In addition, uncertainty in these fields associated with their estimation are rarely assessed. Ecological models are usually driven with a geostatistical model's mean estimate (kriging) of these fields without accounting for this uncertainty, much less evaluating such errors in terms of their propagation in ecological simulations. We introduce a Bayesian statistical framework to model climate observations to create spatially uniform and temporally complete fields, taking into account correlation in time and space, spatial heterogeneity, lack of normality, and uncertainty about all these factors. A key benefit of the Bayesian model is that it generates uncertainty measures for the generated fields. To demonstrate this method, we reconstruct historical monthly precipitation fields (a driver for ecological models) on a fine resolution grid for a climatically heterogeneous region in the western United States. The main goal of this work is to evaluate the sensitivity of ecological models to the uncertainty associated with prediction of their climate drivers. To assess their numerical sensitivity to predicted input variables, we generate a set of ecological model simulations run using an ensemble of different versions of the reconstructed fields. We construct such an ensemble by sampling from the posterior predictive distribution of the climate field. We demonstrate that the estimated prediction error of the climate field can be very high. We evaluate the importance of such errors in ecological model experiments using an ensemble of historical precipitation time series in simulations of grassland biogeochemical dynamics with an ecological numerical model, Century. We show how uncertainty in predicted precipitation fields is propagated into ecological model results and that this propagation had different modes. Depending on output variable, the response of model dynamics to uncertainty in inputs ranged from uncertainty in outputs that matched that of inputs to those that were muted or that were biased, as well as uncertainty that was persistent in time after input errors dropped.     

Mass conservation and atmospheric dynamics in the Regional Atmospheric Modeling System (RAMS)

This paper examines the spatio-temporal patterns of atmospheric carbon dioxide transport predicted by the Regional Atmospheric Modeling System (RAMS). Forty-eight hour simulations over northern New England incorporating a simple representation of the diurnal summertime surface carbon dioxide forcing arising from biological activity indicate that, in its native formulation, RAMS exhibits a significant degree of mass non-conservation. Domain-wide rates of non-physical mass gain and mass loss are as large as three percent per day which translates into approximately eleven parts per million per day for carbon dioxide — enough to rapidly dilute the signature of carbon dioxide fluxes arising from biological activity. Analysis shows that this is due to the approximation used by RAMS to compute the Exner function. Substitution of the exact, physically complete equation improves mass conservation by two orders of magnitude. In addition to greatly improving mass conservation, use of the complete Exner function equation has a substantial impact on the spatial pattern of carbon dioxide predicted by the model, yielding predictions differing from a conventional RAMS simulation by as much as forty parts per million. Such differences have important implications both for comparisons of modeled atmospheric carbon dioxide concentrations to observations and for carbon dioxide inversion studies, which use estimates of atmospheric transport of carbon dioxide in conjunction with measurements of atmospheric carbon dioxide concentrations to infer the spatio-temporal distribution of surface carbon dioxide fluxes. Furthermore, use of the complete Exner function equation affects the vertical velocity and water mixing ratio fields, causing significant changes in accumulated precipitation over the region.     

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.     

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.     

Simulations of the flow in the Mahakam river–lake–delta system,Indonesia

Large rivers often present a river–lake–delta system, with a wide range of temporal and spatial scales of the flow due to the combined effects of human activities and various natural factors, e.g., river discharge, tides, climatic variability, droughts, floods. Numerical models that allow for simulating the flow in these river–lake–delta systems are essential to study them and predict their evolution under the impact of various forcings. This is because they provide information that cannot be easily measured with sufficient temporal and spatial detail. In this study, we combine one-dimensional sectional-averaged (1D) and two-dimensional depth-averaged (2D) models, in the framework of the finite element model SLIM, to simulate the flow in the Mahakam river–lake–delta system (Indonesia). The 1D model representing the Mahakam River and four tributaries is coupled to the 2D unstructured mesh model implemented on the Mahakam Delta, the adjacent Makassar Strait, and three lakes in the central part of the river catchment. Using observations of water elevation at five stations, the bottom friction for river and tributaries, lakes, delta, and adjacent coastal zone is calibrated. Next, the model is validated using another period of observations of water elevation, flow velocity, and water discharge at various stations. Several criteria are implemented to assess the quality of the simulations, and a good agreement between simulations and observations is achieved in both calibration and validation stages. Different aspects of the flow, i.e., the division of water at two bifurcations in the delta, the effects of the lakes on the flow in the lower part of the system, the area of tidal propagation, are also quantified and discussed.     

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.     

Towards carrying capacity assessment for aquaculture in the Bolinao Bay, Philippines: A numerical study of tidal circulation

The increase in intensive aquaculture production in the Bolinao Bay, Philippines reached the point of harmful influence to production stock. Up to the present, there has been no estimation of aquaculture carrying capacity which is based on quantification of processes responsible for (a) water quality inside the units, (b) impact to the seabed and (c) water quality in the whole Bolinao Bay. The numerical estimation of tidal circulation, which is the most dominant part of the hydrodynamical regime in the Bolinao Bay, represents an unavoidable step in the carrying capacity determination considering points (a), (b) and (c). The hydrodynamical model we apply is a free surface, 3D finite element tidal model, forced with sea elevation dynamics at three open boundaries. It incorporates an increase in bottom stress drag coefficients in the coral areas and advanced transport corrected advection scheme. The model simulations of water flow show good agreement with measured currents in the central part of the Bolinao Bay, southern and northeastern channel, while agreement in the areas in vicinity of northern channel is not as tight. In order to provide an insight into the water exchange in aquaculture units, to support local water quality models and seabed deposition models (points (a) and (b)), the area is mapped with neap tide mean, spring tide mean and 14-day mean current velocity contours. The highest 14-day mean velocities are attained in the southern channel (>17 cm s⁻¹), while the mean velocities characteristic for northern part (<6 cm s⁻¹) and shallow areas of coral reefs (<2 cm s⁻¹) are much lower. Area-mean difference between spring tide and 14-day mean velocities is estimated to be 18.32% (std=7.31%), while difference between neap tide and 14-day mean velocities is 17.62 % (std=11.19%). To support global basin-wide water quality models (point (c)), retention of water in the bay is estimated by Lagrangian and Eulerian calculation procedure of mean residence time field. Both calculations estimate the highest (no-wind) residence times (Lan: 25.4 days, Eul: 21.03 days) in the central northern part, but most of the area (Lan: 73.11%, Eul: 79.31%) is characterized by residence time values significantly lower than 15 days. The results are readily applicable for upcoming implementation in the models of local (aquaculture units, seabed) and basin-wide (Bolinao Bay) nutrient dynamics, primary and secondary production, organic matter decomposition and oxygen dynamics.     

LES validation of urban flow,part II: eddy statistics and flow structures

Time-dependent three-dimensional numerical simulations such as large-eddy simulation (LES) play an important role in fundamental research and practical applications in meteorology and wind engineering. Whether these simulations provide a sufficiently accurate picture of the time-dependent structure of the flow, however, is often not determined in enough detail. We propose an application-specific validation procedure for LES that focuses on the time dependent nature of mechanically induced shear-layer turbulence to derive information about strengths and limitations of the model. The validation procedure is tested for LES of turbulent flow in a complex city, for which reference data from wind-tunnel experiments are available. An initial comparison of mean flow statistics and frequency distributions was presented in part I. Part II focuses on comparing eddy statistics and flow structures. Analyses of integral time scales and auto-spectral energy densities show that the tested LES reproduces the temporal characteristics of energy-dominant and flux-carrying eddies accurately. Quadrant analysis of the vertical turbulent momentum flux reveals strong similarities between instantaneous ejection-sweep patterns in the LES and the laboratory flow, also showing comparable occurrence statistics of rare but strong flux events. A further comparison of wavelet-coefficient frequency distributions and associated high-order statistics reveals a strong agreement of location-dependent intermittency patterns induced by resolved eddies in the energy-production range. The validation concept enables wide-ranging conclusions to be drawn about the skill of turbulence-resolving simulations than the traditional approach of comparing only mean flow and turbulence statistics. Based on the accuracy levels determined, it can be stated that the tested LES is sufficiently accurate for its purpose of generating realistic urban wind fields that can be used to drive simpler dispersion models.     

Monitoring the transport of biomass burning emissions in South America

The atmospheric transport of biomass burning emissions in the South American and African continents is being monitored annually using a numerical simulation of air mass motions; we use a tracer transport capability developed within RAMS (Regional Atmospheric Modeling System) coupled to an emission model. Mass conservation equations are solved for carbon monoxide (CO) and particulate material (PM2.5). Source emissions of trace gases and particles associated with biomass burning activities in tropical forest, savanna and pasture have been parameterized and introduced into the model. The sources are distributed spatially and temporally and assimilated daily using the biomass burning locations detected by remote sensing. Advection effects (at grid scale) and turbulent transport (at sub-grid scale) are provided by the RAMS parameterizations. A sub-grid transport parameterization associated with moist deep and shallow convection, not explicitly resolved by the model due to its low spatial resolution, has also been introduced. Sinks associated with the process of wet and dry removal of aerosol particles and chemical transformation of gases are parameterized and introduced in the mass conservation equation. An operational system has been implemented which produces daily 48-h numerical simulations (including 24-h forecasts) of CO and PM2.5, in addition to traditional meteorological fields. The good prediction skills of the model are demonstrated by comparisons with time series of PM2.5 measured at the surface.     

Modeling linkages between sediment resuspension and water quality in a shallow,eutrophic, wind-exposed lake

The interactions between bed sediments and the water column in shallow, eutrophic lakes have tremendous implications for the fate and transport of nutrients in those water bodies. This has resulted in the development of water quality models for lakes incorporating the processes of sediment resuspension. Reliable resuspension models are thus needed to accurately represent this phenomenon. In this paper, three different sediment-resuspension models are combined with a hydrodynamic and water quality model, dynamic lake model-water quality (DLM-WQ), and the resulting models are used to simulate nutrient distributions in the highly eutrophic Salton Sea, California, USA. One of the resuspension formulas is based upon sediment characteristics as well as the bed shear stress exerted by wind-induced waves and currents, while the other two are standard, power-law-type formulas for cohesive sediments with two different exponents. The outputs for water quality variables, such as temperature, chlorophyll a, dissolved oxygen and nutrients, obtained from the three resulting models and from an earlier DLM-WQ run with a simple empirical sediment-resuspension model are compared with measured data. The level of agreement between the simulations and the measured data is assessed by using both statistical and graphical model evaluation methods, including measures of residual errors, sample autocorrelations, t-tests, and box plots. Based on these assessments, DLM-WQ with an extended version of the García and Parker [García, M.H., Parker, G., 1993. Experiments on the entrainment of sediment into suspension by a dense bottom current. J. Geophys. Res.-Oceans 98, 4793–4807] relationship gave the best results for water quality in the Salton Sea, confirming that the use of formulas with more information on the sediment characteristics yields more accurate results. To the best of our knowledge, this is the first effort to combine water quality models for lakes and reservoirs with a sediment-resuspension model which was originally intended for open-channel flows. The simulations confirm that sediment resuspension is the most dominant process in the Salton Sea's nutrient cycling. The effect of proposed physical changes to the Salton Sea on water quality characteristics is also addressed.     

Mass conservation above slopes in the Regional Atmospheric Modelling System (RAMS)

This paper examines the mass balance in calculations with the Regional Atmospheric Modelling System (RAMS). An error is pointed out that concerns the calculation of the surface fluxes on slopes. This error affects all the prognostic variables in RAMS when sloping terrain is involved. Here we explain how the error can be corrected. To study the impact of the error, we compared simulations with the uncorrected and corrected model. The model contains CO₂ transport, and online mass balance calculations were performed for this tracer. Without correction, effective surface CO₂-fluxes on mountain slopes were found to be enhanced under certain common conditions to several times the parameterized fluxes. Neglecting this error may cause substantial deviations in both forward and inverse model calculations. After the correction a very good closure of the mass balance is obtained. The correction also modifies the meteorological parameters, although the consequences were limited compared to the CO₂-fluxes.     

Parameterizing,evaluating and comparing metapopulation models with data from individual-based simulations

Due to the lack of sufficient data and appropriate ecological information parameterizing predictive population dynamical models usually is a difficult task. The approach proposed in this study is meant to overcome this problem by using detailed individual-based simulations to generate artificial data. With short-term data samples, the models to be investigated can be parameterized and their predictions be compared. The flexibility of individual-based simulations as experimental tools also facilitates the evaluation and comparison of different (aggregated) model types. The presented approach is a step towards unifying models of different complexity. As an example we applied it to two metapopulation models of insect species in a highly fragmented landscape: the well-known incidence function model with a patch-based representation of space and a grid-based analogue. The models are tested with respect to their data requirement and recommendations for a better data sampling are derived.     

Revisiting Kappa to account for change in the accuracy assessment of land-use change models

Land-use change models are typically calibrated to reproduce known historic changes. Calibration results can then be assessed by comparing two datasets: the simulated land-use map and the actual land-use map at the same time. A common method for this is the Kappa statistic, which expresses the agreement between two categorical datasets corrected for the expected agreement. This expected agreement is based on a stochastic model of random allocation given the distribution of class sizes. However, when a model starts from an initial land-use map and makes changes to it, that stochastic model does not pose a meaningful reference level. This paper introduces K_Simulation, a statistic that is identical in form to the Kappa statistic but instead applies a more appropriate stochastic model of random allocation of class transitions relative to the initial map. The new method is illustrated on a simple example and then the results of the Kappa statistic and K_Simulation are compared using the results of a land-use model. It is found that only K_Simulation truly tests models in their capacity to explain land-use changes over time, and unlike Kappa it does not inflate results for simulations where little change takes place over time.     

Development and application of “U.S.E.D.”: A hydroclimate lake stratification model

Two model types are currently in use to model the thermal stratification cycle in lakes and reservoirs: the eddy diffusion and the mixed layer (or integral energy) approaches. Here the former is analysed and developments are proposed to remove the empiricisms previously implicit in these models. These discussions permit the reformulation of K_H0 independently of current shear, together with an expression for R_i. The deduced formulae are in good agreement with observations. The newly formulated model (the University of Salford eddy diffusion model, U.S.E.D.) is subsequently used in simulations of lakes and reservoirs at different latitudes which are found to be in good agreement with observations without requiring inter-site calibration.     

北京城市热岛的定量监测及规划模拟研究

为定量地评估北京城市热岛现状并预测未来北京城市热岛发展趋势,分别采用气温资料、遥感资料和城市规划资料进行了研究分析。对北京20个气象台站按照台站距离城市中心的距离划分为远郊、近郊和城市三类,分别计算三种类型站点经过海拔订正后的年平均气温,利用1971-2012年城市站和远郊站的年平均气温差值估算北京气温热岛的时间变化;利用1987-2012年的NOAA/AVHRR和Landsat-TM两种不同分辨率的卫星资料,采用定量化的指标--地表热岛强度和热岛比例指数分别估算了不同时期北京地区和城六区热岛强度和范围,并对北京平原地区的城市热岛状况进行了评估;利用2020年的北京城市规划土地利用资料,结合2008年的城市热岛现状监测结果对2020年的北京热岛状况进行了模拟分析。研究结果表明,北京城市的气温热岛与遥感监测地表热岛在时间变化趋势上具有一致性,不同分辨率卫星资料监测地表热岛在时空分布上也具有一致性。其中1971-2012年,以年平均气温计算的北京城市热岛强度增温率为0.33℃·（10 a）-1,近5年（2008-2012）平均热岛为1.12℃。遥感监测结果显示1987-2001年北京地区的热岛持续增强,2001年之后由于北京申奥的成功进行了大面积的旧城改造和绿化,使得城市热岛强度和范围在2004年和2008年有所降低,2008年之后城市热岛继续向东、南和北方向扩展,并出现了中心城区热岛与通州、顺义、大兴、昌平热岛连成片的趋势,到2012年城六区热岛面积百分比已从1990年的31%增加到77%。由热岛比例指数确定的北京各区县热岛强度排名前三分别是城区、海淀和丰台,延庆县最低。对2020年城市规划图热岛模拟结果显示北京热岛已由“摊大饼”演变为“中心＋周边分散”模式,中心城区热岛强度和范围明显减弱,周边广大远郊区将出现分散?