Land-atmosphere coupling over North America in CRCM5

Land-atmosphere coupling and its impact on extreme precipitation and temperature events over North America are studied using the fifth generation of the Canadian Regional Climate Model (CRCM5). To this effect, two 30 year long simulations, spanning the 1981–2010 period, with and without land-atmosphere coupling, have been performed with CRCM5, driven by the European Centre for Medium-Range Weather Forecasts reanalysis at the boundaries. In the coupled simulation, the soil moisture interacts freely with the atmosphere at each time step, while in the uncoupled simulation, soil moisture is replaced with its climatological value computed from the coupled simulation, thus suppressing the soil moisture-atmosphere interactions. Analyses of the coupled and uncoupled simulations, for the summer period, show strong soil moisture-temperature coupling over the Great Plains, consistent with previous studies. The maxima of soil moisture-precipitation coupling is more spread out and covers the semiarid regions of the western U.S. and parts of the Great Plains. However, the strength of soil moisture-precipitation coupling is found to be generally weaker than that of soil moisture-temperature coupling. The study clearly indicates that land-atmosphere coupling increases the interannual variability of the seasonal mean daily maximum temperature in the Great Plains. Land-atmosphere coupling is found to significantly modulate selected temperature extremes such as the number of hot days, frequency, and maximum duration of hot spells over the Great Plains. Results also suggest additional hot spots, where soil moisture modulates extreme events. These hot spots are located in the southeast U.S. for the hot days/hot spells and in the semiarid regions of the western U.S. for extreme wet spells. This study thus demonstrates that climatologically wet/dry regions can become hot spots of land-atmosphere coupling when the soil moisture decreases/increases to an intermediate transitional level where evapotranspiration becomes moisture sensitive and large enough to affect the climate.

沙坡头人工植被区陆气耦合模式及生物结皮与植被演变的机理研究

论述了研究陆气相互作用的意义和现状。在以前工作基础上，针对腾格里沙漠人工植被区陆气水热传输过程，提出了一个多层陆气的耦合模式。特别给出了导水率的计算模型和修正后的根系吸水模式，考虑了结皮层对于土壤水分入渗的影响以及植被演变的过程。陆气耦合模式分别对大气、植被、土壤作用多层划分，以助于细致了解沿高度分布的各物理量。同时，介绍了当地气候根况和野外观测情况。利用本模式对中国科学院沙坡头沙漠站人工植被区陆气水热效换过程进行了数值模拟，模拟结果与实测值吻合较好，可为当地合理利用水热资源和治理沙漠提供科学依据。

Observation and modeling for terrestrial processes in alpine meadow

The water-heat transfer process between land and atmosphere in Haibei alpine meadow area has been systematically observed. A multi-layer coupling model for land-atmosphere interaction was presented with special attention paid to the moisture transfer in leaf stomata under unsaturated condition. A profound investigation on the physical process of turbulent transfer inside the vegetation has been performed with a revised formula of water absorption for root system. The present model facilitates the study of vertically distributed physical variables in detail. Numerical simulation was conducted according to the transfer process of Kinesia humility meadow in the area of Haibei Alpine Meadow Ecosystem Station, CAS. The calculated results agree well with observation.

Observation and modeling for terrestrial processes in alpine meadow

The water-heat transfer process between land and atmosphere in Haibei alpine meadow area has been systematically observed. A multi-layer coupling model for land-atmosphere interaction was presented with special attention paid to the moisture transfer in leaf stomata under unsaturated condition. A profound investigation on the physical process of turbulent transfer inside the vegetation has been performed with a revised formula of water absorption for root system. The present model facilitates the study of vertically distributed physical variables in detail. Numerical simulation was conducted according to the transfer process of Kinesia humility meadow in the area of Haibei Alpine Meadow Ecosystem Station, CAS. The calculated results agree well with observation.

Modelo OLAM (ocean-land-atmosphere-model): descrição, aplicações, e perspectivas

O modelo OLAM foi desenvolvido com objetivo de estender a capacidade de representar os fenômenos de escala global e regional simultaneamente. Este modelo apresenta inovações quanto aos processos dinâmicos, configuração de grade, estrutura de memória e técnicas de solução numérica das equações prognósticas. As equações de Navier-Stokes são resolvidas através da técnica de volumes finitos que conservam massa, momento e energia. No presente trabalho, apresenta-se uma descrição sucinta do OLAM e alguns resultados de sua aplicação em simulações climáticas da precipitação mensal para a região norte da América do Sul, bem como em rodadas para previsão numérica de tempo regional. Os resultados mostram que o modelo consegue representar bem os aspectos meteorológicos de grande escala. Em geral, seu desempenho melhora quando são adotadas grades de maior resolução espacial, nas quais se verificam melhorias significativas tanto na estimativa da precipitação mensal regional, quanto na previsão numérica de tempo.

A coupling model for terrestrial processes in arid areas and its application

In this paper, the importance of investigation on terrestrical processes in arid areas for mankind's living environment protection and local economy development as well as its present state of the art are elucidated. A coupling model, which evaluates heat, mass, momentum and radiative fluxes in the SPAC system, is developed for simulating microclimate over plant and bare soil. Especially, it is focussed on the details of turbulence transfer. For illustration, numerical simulation of the water-heat exchange processes at Shapotou Observatory, GAS, Ninxia Province are conducted, and the computational results show that the laws of land-surface processes are rather typical in the arid areas.

The land-atmosphere water flux in the tropics

Tropical vegetation is a major source of global land surface evapotranspiration, and can thus play a major role in global hydrological cycles and global atmospheric circulation. Accurate prediction of tropical evapotranspiration is critical to our understanding of these processes under changing climate. We examined the controls on evapotranspiration in tropical vegetation at 21 pan-tropical eddy covariance sites, conducted a comprehensive and systematic evaluation of 13 evapotranspiration models at these sites, and assessed the ability to scale up model estimates of evapotranspiration for the test region of Amazonia. Net radiation was the strongest determinant of evapotranspiration (mean evaporative fraction was 0.72) and explained 87% of the variance in monthly evapotranspiration across the sites. Vapor pressure deficit was the strongest residual predictor (14%), followed by normalized difference vegetation index (9%), precipitation (6%) and wind speed (4%). The radiation-based evapotranspiration models performed best overall for three reasons: (1) the vegetation was largely decoupled from atmospheric turbulent transfer (calculated from X decoupling factor), especially at the wetter sites; (2) the resistance-based models were hindered by difficulty in consistently characterizing canopy (and stomatal) resistance in the highly diverse vegetation; (3) the temperature-based models inadequately captured the variability in tropical evapotranspiration. We evaluated the potential to predict regional evapotranspiration for one test region: Amazonia. We estimated an Amazonia-wide evapotranspiration of 1370 mm yr(-1), but this value is dependent on assumptions about energy balance closure for the tropical eddy covariance sites; a lower value (1096 mm yr(-1)) is considered in discussion on the use of flux data to validate and interpolate models.

Holocene experiment with coupled atmosphere-ocean-model ECHAM5/MPI-OM

Changes in the Earth's orbit lead to changes in the seasonal and meridional distribution of insolation. We quantify the influence of orbitally induced changes on the seasonal temperature cycle in a transient simulation of the last 6000 years - from the mid-Holocene to today - using a coupled atmosphere-ocean general circulation model (ECHAM5/MPI-OM) including a land surface model (JSBACH). The seasonal temperature cycle responds directly to the insolation changes almost everywhere. In the Northern Hemisphere, its amplitude decreases according to an increase in winter insolation and a decrease in summer insolation. In the Southern Hemisphere, the opposite is true. Over the Arctic Ocean, decreasing summer insolation leads to an increase in sea-ice cover. The insulating effect of sea ice between the ocean and the atmosphere leads to decreasing heat flux and favors more "continental" conditions over the Arctic Ocean in winter, resulting in strongly decreasing temperatures. Consequently, there are two competing effects: the direct response to insolation changes and a sea-ice insulation effect. The sea-ice insulation effect is stronger, and thus an increase in the amplitude of the seasonal temperature cycle over the Arctic Ocean occurs. This increase is strongest over the Barents Shelf and influences the temperature response over northern Europe. We compare our modeled seasonal temperatures over Europe to paleo reconstructions. We find better agreements in winter temperatures than in summer temperatures and better agreements in northern Europe than in southern Europe, since the model does not reproduce the southern European Holocene summer cooling inferred from the paleo reconstructions. The temperature reconstructions for northern Europe support the notion of the influence of the sea-ice insulation effect on the evolution of the seasonal temperature cycle.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

Ocean atmosphere coupling over monsoon regions

In monsoon regions, the seasonal migration of the intertropical convergence zone (ITCZ) is manifested as a seasonal reversal of winds. Most of the summer monsoon rainfall over India occurs owing to synoptic and large-scale convection associated with the continental ITCZ (Fig. 1). We have investigated the interaction between these large-scale convective systems and the ocean over which they are generated1â3, concentrating on the relationship between organized convection over the Indian Ocean and sea surface temperature (SST). We report here that on a monthly basis the degree of cloudiness correlates well with SST for the relatively colder oceans, but when SST is maintained above 28 °C it ceases to be an important factor in determining the variability of cloudiness. Over the major regions of convection east of 70°E, which are warm year after year, the observed cloudiness cannot be correlated with variations in SST.

Land use regression model (LUR) for ultrafine particles in Brisbane

Traffic-related air pollution has been associated with a wide range of adverse health effects. One component of traffic emissions that has been receiving increasing attention is ultrafine particles(UFP, < 100 nm), which are of concern to human health due to their small diameters. Vehicles are the dominant source of UFP in urban environments. Small-scale variation in ultrafine particle number concentration (PNC) can be attributed to local changes in land use and road abundance. UFPs are also formed as a result of particle formation events. Modelling the spatial patterns in PNC is integral to understanding human UFP exposure and also provides insight into particle formation mechanisms that contribute to air pollution in urban environments. Land-use regression (LUR) is a technique that can use to improve the prediction of air pollution.

Two-way coupling model for shock-induced laminar boundary-layer flows of a dusty gas

The present paper describes a numerical two-way coupling model for shock-induced laminar boundary-layer flows of a dust-laden gas and studies the transverse migration of fine particles under the action of Saffman lift force. The governing equations are formulated in the dilute two-phase continuum framework with consideration of the finiteness of the particle Reynolds and Knudsen numbers. The full Lagrangian method is explored for calculating the dispersed-phase flow fields (including the number density of particles) in the regions of intersecting particle trajectories. The computation results show a significant reaction of the particles on the two-phase boundary-layer structure when the mass loading ratio of particles takes finite values.

A dynamic coupling model for hybrid atomistic-continuum computations

A dynamic coupling model is developed for a hybrid atomistic-continuum computation in micro- and nano-fluidics. In the hybrid atomistic-continuum computation, a molecular dynamics (MD) simulation is utilized in one region where the continuum assumption breaks down and the Navier-Stokes (NS) equations are used in another region where the continuum assumption holds. In the overlapping part of these two regions, a constrained particle dynamics is needed to couple the MD simulation and the NS equations. The currently existing coupling models for the constrained particle dynamics have a coupling parameter, which has to be empirically determined. In the present work, a novel dynamic coupling model is introduced where the coupling parameter can be calculated as the computation progresses rather than inputing a priori. The dynamic coupling model is based on the momentum constraint and exhibits a correct relaxation rate. The results from the hybrid simulation on the Couette flow and the Stokes flow are in good agreement with the data from the full MD simulation and the solutions of the NS equations, respectively. (c) 2007 Elsevier Ltd. All rights reserved.

Coupling model uncertainty for coupled rainfall/runoff and surface water quality models in river problems

Coupled hydrology and water quality models are an important tool today, used in the understanding and management of surface water and watershed areas. Such problems are generally subject to substantial uncertainty in parameters, process understanding, and data. Component models, drawing on different data, concepts, and structures, are affected differently by each of these uncertain elements. This paper proposes a framework wherein the response of component models to their respective uncertain elements can be quantified and assessed, using a hydrological model and water quality model as two exemplars. The resulting assessments can be used to identify model coupling strategies that permit more appropriate use and calibration of individual models, and a better overall coupled model response. One key finding was that an approximate balance of water quality and hydrological model responses can be obtained using both the QUAL2E and Mike11 water quality models. The balance point, however, does not support a particularly narrow surface response (or stringent calibration criteria) with respect to the water quality calibration data, at least in the case examined here. Additionally, it is clear from the results presented that the structural source of uncertainty is at least as significant as parameter-based uncertainties in areal models. © 2012 John Wiley & Sons, Ltd.