An Approach for the Aggregation of Aerodynamic Surface Parameters in Calculating the Turbulent Fluxes over Heterogeneous Surfaces in Atmospheric Models

Experimental evidence indicates that there is a significant departure of the wind profile above the underlying surface consisting of patches of solid and liquid parts, and plant communities with different morphological from that predicted by the logarithmic relationship, which gives the values larger than those observed. This situation can seriously affect the transfer of momentum, heat and water vapor from the surface fluxes into the atmosphere.The object of this paper is to generalize the calculation of the exchange of momentum between the atmosphere and a very heterogeneous surface, find a general equation for the wind speed profile in a roughness sublayer under neutral conditions, and, then, derive aggregated roughness length and displacement height over the grid cell. The suggested expression for the wind profile is compared with some earlier approaches, using a common parameterization of aerodynamic parameters over the grid cell, and the observations obtained at an experimental site in Philadelphia, PA.     

Dynamics of surface albedo of a boreal forest and its simulation

Surface albedo determines the distribution of solar radiation between the earth's surface and the atmosphere. It affects the global climate directly by altering surface energy balance, and indirectly by controlling ecosystem processes and greenhouse gas exchange. In this study, a land surface albedo model was constructed based on the gap probability approach for ray tracing and the basic optical parameters of ecosystem elements. The model was applied to a boreal deciduous forest and results were compared with field measurements. Results show that seasonal and diurnal albedo dynamics were well simulated by the model. The standard deviation between the simulated and measured reflected radiation was 2.5–5.0 W m⁻² in different seasons. The model also provided an insight into the relationships between surface albedo and radiation components (direct versus diffuse), solar zenith angle, and different wave bands. Model sensitivity analyses show that the surface albedo in winter is very sensitive to the forest wood area index for this boreal aspen forest, suggesting that accurate estimates of wood area index are necessary to improve the accuracy of surface albedo simulation in leafless seasons.     

Space-time estimation of grid-cell hourly ozone levels for assessment of a deterministic model

We present an approach to estimate hourly grid-cell surface ozone concentrations based on observations from point monitoring sites in space, for comparison with grid-based results from the SARMAP photochemical air-quality model for a region of northern California. Statistical estimation is carried out on a transformed (square root) scale, followed by back-transforming to the original scale of ozone in parts per billion, adjusting for bias and variance. We estimate a spatially-varying diurnal mean structure and a non-separable space-time correlation structure on the transformed scale. Temporal pre-whitening is followed by modelling of a spatially non-stationary, diurnally-varying spatial correlation structure using a spatial deformation approach. Comparisons of SARMAP model results with the estimated grid-cell ozone levels are presented.     

A Fine-Scale <Emphasis Type="Italic">k</Emphasis>−ε Model for Atmospheric Flow over Heterogeneous Landscapes

A multi-purpose model for small-scale atmospheric flows over heterogeneous landscapes is being developed. The aim of this research is to build a tool able to predict the dynamical (wind, turbulence) and diffusive (gases, particles) fields over landscapes characterised by heterogeneous plant cover. In its present stage of development the model is based on the numerical integration of neutral atmospheric flow equations, using an energy-dissipation closure scheme and over a domain that may include vegetation layers. Three validation cases of the model are presented: (i) response of the airflow to a change in surface roughness; (ii) airflow within and above a horizontally homogeneous plant canopy; (iii) airflow over two complex forest-to-clearing and clearing-to-forest transitions. All simulations provide results in good agreement with the experimental data, except for turbulent kinetic energy just after a clearing-to-forest transition. This result is not surprising for a statistical k– model in a flow region characterised by strong distorsion and intermittent turbulence. However the overall good performance of the model is promising for environmental research at fine scales over heterogeneous landscapes.     

Modeling and inference of forest coverage ratio using zero-one inflated distributions with spatial dependence

This paper explores statistical modeling of forest area with two covariates. The forest coverage ratio of grid-cell data was modeled by taking human population density and relief energy into account. The likelihood of the forest ratios was decomposed into the product of two likelihoods. The first likelihood was due to trinomial logistic distributions on three categories: the forest ratios take zero, or one, or values between zero and one. The second one was due to a logistic-normal regression model for the ratios between zero and one. This model was applied to real grid-cell data and it fit better than zero-inflated beta regression models.     

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.     

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.     

Linking 3D spatial models of fuels and fire: Effects of spatial heterogeneity on fire behavior

Crown fire endangers fire fighters and can have severe ecological consequences. Prediction of fire behavior in tree crowns is essential to informed decisions in fire management. Current methods used in fire management do not address variability in crown fuels. New mechanistic physics-based fire models address convective heat transfer with computational fluid dynamics (CFD) and can be used to model fire in heterogeneous crown fuels. However, the potential impacts of variability in crown fuels on fire behavior have not yet been explored. In this study we describe a new model, FUEL3D, which incorporates the pipe model theory (PMT) and a simple 3D recursive branching approach to model the distribution of fuel within individual tree crowns. FUEL3D uses forest inventory data as inputs, and stochastically retains geometric variability observed in field data. We investigate the effects of crown fuel heterogeneity on fire behavior with a CFD fire model by simulating fire under a homogeneous tree crown and a heterogeneous tree crown modeled with FUEL3D, using two different levels of surface fire intensity. Model output is used to estimate the probability of tree mortality, linking fire behavior and fire effects at the scale of an individual tree. We discovered that variability within a tree crown altered the timing, magnitude and dynamics of how fire burned through the crown; effects varied with surface fire intensity. In the lower surface fire intensity case, the heterogeneous tree crown barely ignited and would likely survive, while the homogeneous tree had nearly 80% fuel consumption and an order of magnitude difference in total net radiative heat transfer. In the higher surface fire intensity case, both cases burned readily. Differences for the homogeneous tree between the two surface fire intensity cases were minimal but were dramatic for the heterogeneous tree. These results suggest that heterogeneity within the crown causes more conditional, threshold-like interactions with fire. We conclude with discussion of implications for fire behavior modeling and fire ecology.     

Wave hydrodynamics around a multi-functional artificial reef at Leirosa

This paper describes an application of the Boussinesq-type COULWAVE model to study the wave hydrodynamics in the vicinity of a multi-functional artificial reef (MFAR). This reef is under investigation and consists of a supplementary protection solution for the Leirosa sand dune system located at South of Figueira da Foz, on the Portuguese West coast. Such installation near the coastline is expected to contribute to enhance the surfing conditions in the area, protect the sand dune system in the surroundings of Leirosa beach, and increase its environmental value. Numerical calculations with the COULWAVE model were performed for four test cases, considering two reef geometries (differing in the reef angle) and two incident wave conditions (storm condition and a common wave condition). Comparisons between the results obtained, in terms of wave heights and breaking line positions allow us to assess the influence of the reef on the hydrodynamics near the beach and around the reef. Moreover, the reef performance was analysed in terms of surfability and coastal protection. The surfability parameters (breaker height, Iribarren number and peel angle) were calculated for each test case using the numerical wave heights, wave directions and wave breaking positions. Comparisons of parameters allow characterizing the most appropriate configuration of the reef to improve the surfing conditions in the study area. A methodology based on numerical free surface elevations and horizontal velocity components was developed to calculate wave directions, since this is not a direct output of the COULWAVE model. Concerning coastal protection, analyses of the mean currents around the reef were used together with observations of the velocity cells near the shoreline as an indication of the sediment transport.     

Oviposition height increases parasitism success by the robber fly Mallophora ruficauda (Diptera: Asilidae)

For parasitoids, host finding is a central problem that has been solved through a variety of behavioural mechanisms. Among species in which females do not make direct contact with hosts, as is the case for many dipteran parasitoids, eggs must be laid in an appropriate part of the host habitat. The asilid fly Mallophora ruficauda lays eggs in clusters on tall vegetation. Upon eclosion, pollen-sized larvae fall and parasitize soil-dwelling scarab beetle larvae. We hypothesized that wind dissemination of M. ruficauda larvae is important in the host-finding process and that females lay eggs at heights that maximize parasitism of its concealed host. Through numerical and analytical models resembling those used to describe seed and pollen wind dispersal, we estimated an optimal oviposition height in the 1.25- to 1.50-m range above the ground. Our models take into account host distribution, plant availability and the range over which parasitic larvae search for hosts. Supporting our findings, we found that the results of the models match heights at which egg clusters of M. ruficauda are found in the field. Generally, work on facilitation of host finding using plants focuses on plants as indicators of host presence. We present a case where plants are used in a different way, as a means of offspring dispersal. For parasitoids that carry out host searching at immature stages rather than as adults, plants are part of a dissemination mechanism of larvae that, as with minute seeds, uses wind and a set of simple rules of physics to increase offspring success.     

Numerical modeling of the 26th December 2004 India Ocean tsunami at Andaman and Nicobar Islands

A numerical simulation of the 26th December 2004 Indian Ocean tsunami for the Andaman and Nicobar Islands case study is presented. The simulation approach is based on a fully nonlinear Boussinesq tsunami propagation model and included an accurate computational domain and a robust coseismic source. The simulation is first confronted to available tide gauge and run-up observations. The agreement between observations and the predicted wave heights allowed a reasonable validation of the simulation. As a result a full picture of the tsunami impact is provided over the entire coastal zone of Andaman and Nicobar Islands. The processes responsible for coastal vulnerability are discussed.     

Surface modelling of human population distribution in China

On the basis of introducing major data layers corresponding to net primary productivity (NPP), elevation, city distribution and transport infrastructure distribution of China, surface modelling of population distribution (SMPD) is conducted by means of grid generation method. A search radius of 200 km is defined in the process of generating each grid cell. SMPD not only pays attention to the situation of relative elements at the site of generating grid cell itself but also calculates contributions of other grid cells by searching the surrounding environment of the generating grid cell. Human population distribution trend since 1930 in China is analysed. The results show that human population distribution in China has a slanting trend from the eastern region to the western and middle regions of China during the period from 1930 to 2000. Two scenarios in 2015 are developed under two kinds of assumptions. Both scenarios show that the trends of population floating from the western and middle regions to the eastern region of China are very outstanding with urbanization and transport development.     

Simulating wildfire patterns using a small-world network model

This paper presents the development and validation results of a weighted small-world network model designed to simulate fire patterns in real heterogeneous landscapes. Fire spread is simulated on a gridded landscape, a mosaic in which each cell represents an area of the land surface. In this model, the interaction between burning and non-burning cells (here, due to flame radiation) may extend well beyond nearest neighbors, and depends on local conditions of wind, topography, and vegetation. An approach based on the coupling of the solid flame model with the Monte Carlo method is used to predict the radiative heat flux from the flame generated by the burning of each combustible cell to its neighbors. The weighting procedure takes into account latency (a combustible cell will only ignite when it has accumulated enough energy along time) and flaming persistence of burning cells. The model is applied to very different fire scenarios: a historical Mediterranean fire that occurred in southeastern France in 2005 and experimental fires conducted in arid savanna fuels in South Africa in 1992. Model results are found to be in agreement with real fire patterns, in terms both of rate of spread, and of the area and shape of the burn. This work also shows that the fractal properties of fire patterns predicted by the model are similar to those observed from satellite images of three other Mediterranean fire scars.     

Wind- and tide-induced currents in the Stagnone lagoon (Sicily)

The hydrodynamic circulation is analyzed in the coastal lagoon of Stagnone di Marsala, a natural reserve located in the north-western part of Sicily, using both experimental measurements and numerical simulations. Field measurements of velocities and water levels, carried out using an ultrasound sensor (3D), are used to validate the numerical model. A 3D finite-volume model is used to solve the Reynolds-averaged momentum and mass balance differential equations on a curvilinear structured grid, employing the k–e{\varepsilon} turbulence model for the Reynolds stresses. The numerical analysis allows to identify the relative contribution of the forces affecting the hydrodynamic circulation inside the lagoon. In the simulations only wind and tide forces are considered, neglecting the effects of water density changes. Two different conditions are considered. In the first both the wind stress over the free-surface and the tidal motion are imposed. In the second the wind action is neglected, to separately analyze the tide-induced circulation. The comparison between the two test cases highlights the fundamental role of the wind on the hydrodynamics of the Stagnone lagoon, producing a strong vertical recirculation pattern that is not observed when the flow is driven by tides only.     

Modeling the interaction between tides and storm surges for the Taiwan coast

An unstructured grid, two-dimensional hydrodynamic model was established and applied to the coast of Taiwan to investigate the tide-surge interaction. Tidal elevations at the open boundaries coupled with a global ocean tidal model and the meteorological conditions using a cyclone model are used to drive the model. The model was calibrated and verified with the observed tidal levels at six tidal stations for seven typhoon events to ascertain the capability and feasibility of the model. The results show reasonable agreement between the simulated and observed tidal levels. The validated model was then applied to probe the influence of tide-surge interaction on phase, water levels, and storm surge height. We found that the tide-surge interaction influenced both the magnitude and timing of the surge, which depended on the typhoon path. The storm surge heights at different tidal stations were significantly influenced by wind stresses and directions. The water level rise due to the storm surge during high tide was greater at neap tide than at spring tide. Changing tidal ranges altered the prediction of the surge enough to induce the changes in peak water levels.     

不同结构形状的街道峡谷内污染物扩散

针对不同的城市街道峡谷结构形状,通过求解二维不可压缩N-S方程和K-ε湍流模型方程及污染物对流扩散方程,数值模拟了街道峡谷内的流场及机动车排放污染物浓度场,从而说明了街道峡谷的结构是影响街道峡谷内污染气体扩散的主要因素之一。     

Effects of source size,monitoring distance and aquifer heterogeneity on contaminant mass discharge and plume spread uncertainty

Estimating the movement of dissolved contaminants in heterogeneous aquifers is very important for the monitoring design, risk assessment, and remediation of contaminated aquifers. This work explored the influence of source size, monitoring distance, and aquifer heterogeneity on the accuracy of contaminant mass discharge (CMD) estimation using leaching surface approach as well as on the plume spread uncertainty in a 2-D heterogeneous aquifer. The interaction among source size, monitoring distance, and aquifer heterogeneity regarding the accuracy of CMD estimation and the plume spread uncertainty at downstream of the contaminated aquifer was extensively investigated. The transient leaking of a contaminated aquifer in a saturated heterogeneous aquifer under steady-state flow conditions was simulated. The effect of aquifer heterogeneity on the CMD uncertainty was evaluated through the expected values and variance. The results showed that the CMD estimation error varied from underestimation in the mildly heterogeneous aquifer, over accurate estimation in the medium heterogeneous aquifer to overestimation in the highly heterogeneous aquifer. Additionally, the results illustrated that the mean and variance of the transverse spatial extent of the peak concentrations for the plume at the control plane were very sensitive to the aquifer heterogeneity and detectable concentrations of contaminants.     

The role of periodic boundary forcing in plankton pattern formation

We consider one and two-dimensional minimal models in plankton dynamics. The influence of oscillating boundary forcing functions as agents for triggering pattern formation is discussed. In particular it is found that in these conditions population waves arise for one dimensional models, while for two dimensional models, different amplitudes and frequencies in the boundary forcing generate definite patterns, mimicking the boundary term. This happens even though the model we investigate is very simple. The emergence of these features is an interesting metaphor for the fundamental biological problem of how pattern formation processes may be inevitable in natural heterogeneous ecosystems.     

Integration of a fish bioenergetics model into a spatially explicit water quality model: Application to menhaden in Chesapeake Bay

Although fish are usually thought of as victims of water quality degradation, it has been proposed that some planktivorous species may improve water quality through consumption of algae and sequestering of nutrients via growth. Within most numerical water quality models, the highest trophic level modeled explicitly is zooplankton, prohibiting an investigation of the effect a fish species may be having on its environment. Conversely, numerical models of fish consumption do not typically include feedback mechanisms to capture the effects of fish on primary production and nutrient recycling. In the present study, a fish bioenergetics model is incorporated into CE-QUAL-ICM, a spatially explicit eutrophication model. In addition to fish consumption of algae, zooplankton, and detritus, fish biomass accumulation and nutrient recycling to the water column are explicitly accounted for. These developments advance prior modeling efforts of the impact of fish on water quality, many of which are based on integrated estimates over an entire system and which omit the feedback the fish have through nutrient recycling and excretion. To validate the developments, a pilot application was undertaken for Atlantic menhaden (Brevoortia tyrannus) in Chesapeake Bay. The model indicates menhaden may reduce the algal biomass while simultaneously increasing primary productivity.     

Flexible hierarchical mark-recapture modeling for open populations using WinBUGS

Hierarchical mark-recapture models offer three advantages over classical mark-recapture models: (i) they allow expression of complicated models in terms of simple components; (ii) they provide a convenient way of modeling missing data and latent variables in a way that allows expression of relationships involving latent variables in the model; (iii) they provide a convenient way of introducing parsimony into models involving many nuisance parameters. Expressing models using the complete data likelihood we show how many of the standard mark-recapture models for open populations can be readily fitted using the software WinBUGS. We include examples that illustrate fitting the Cormack–Jolly–Seber model, multi-state and multi-event models, models including auxiliary data, and models including density dependence.