Covariance Of Fluctuations Research Articles

Modulation of Phytoplankton Uptake by Mesoscale and Submesoscale Eddies in the California Current System

AbstractEddies play a crucial role in shaping ocean dynamics by affecting material transport, and generating spatio‐temporal heterogeneity. However, how eddies at different scales modulate biogeochemical transformation rates remains an open question. Applying a multi‐scale decomposition to a numerical simulation, we investigate the respective impact of mesoscale and submesoscale eddies on nutrient transport and biogeochemical cycling in the California Current System. First, the non‐linear nature of nutrient uptake by phytoplankton results in a 50% reduction in primary production in the presence of eddies. Second, eddies shape the vertical transport of nutrients with a strong compensation between mesoscale and submesoscale. Third, the eddy effect on nutrient uptake is controlled by the covariance of temperature, nutrient and phytoplankton fluctuations caused by eddies. Our results shed new light on the tight interaction between non‐linear fluid dynamics and ecosystem processes in realistic eddy regimes, which remain largely under‐resolved by global Earth system models.

Financial Intermediation and Economic Growth: From Idiosyncratic Shocks to Aggregate Fluctuations

The objective of this paper is to explore the transmission of non-capital shocks through banking networks. We develop a methodology to construct non-capital (real) shocks, idiosyncratic shocks, using labor productivity shocks to large firms. We document a change in the relationship between (foreign) idiosyncratic shocks in state j and (domestic) economic growth in state i between 1978 and 2000 wherein the relation changes from positive to negative over this period. We show that the contemporaneous changes in banking integration across states is a key driver of this phenomenon. This is driven by geographically diversified banks diverting funds away from economies experiencing negative shocks towards other unaffected economies. This result operates through changes in bank loan supply. Our instrumental variable estimates suggest that a 1% increase in the bank loan supply is associated with a 0.05-0.26 pp increase in economic growth. Lastly, we argue that this mechanism can explain the decrease in covariance of state-level fluctuations, potentially explaining the Great Moderation, the period of relatively low aggregate volatility.

A computational model for controlling conformational cooperativity and function in proteins.

We present a computational model that allows for rapid prediction of correlations among a set of residue pairs when the fluctuations of another set of residues are perturbed. The simple theory presented here is based on the knowledge of the fluctuation covariance matrix only. In this sense, the theory is model independent and therefore universal. Perturbation of any set of fluctuations and the resulting response of the remaining set are calculated using conditional probabilities of a multivariate normal distribution. The model is expected to rapidly and accurately map the consequences of mutations in proteins, as well as allosteric activity and ligand binding. Knowledge of triple correlations of fluctuations of residues i, j, and k, emerges as the necessary source of information for controlling residue pairs by perturbing a distant residue. Triple correlations have not received wide attention in literature. Perturbation-response-function relations for ubiquitin (UBQ) are discussed as an example. Covariance matrix for UBQ obtained from the Gaussian Network Model combined with the present computational algorithm is able to reflect the millisecond molecular dynamics correlations and observed NMR results. © 2018 Wiley Periodicals, Inc.

Instantaneous transport of a passive scalar in a turbulent separated flow

The results of large-eddy simulations of flow and transient solute transport over a backward facing step and through a 180° bend are presented. The simulations are validated successfully in terms of hydrodynamics and tracer transport with experimental velocity data and measured residence time distribution curves confirming the accuracy of the method. The hydrodynamics are characterised by flow separation and subsequent recirculation in vertical and horizontal directions and the solute dispersion process is a direct response to the significant unsteadiness and turbulence in the flow. The turbulence in the system is analysed and quantified in terms of power density spectra and covariance of velocity fluctuations. The injection of an instantaneous passive tracer and its dispersion through the system is simulated. Large-eddy simulations enable the resolution of the instantaneous flow field and it is demonstrated that the instabilities of intermittent large-scale structures play a distinguished role in the solute transport. The advection and diffusion of the scalar is governed by the severe unsteadiness of the flow and this is visualised and quantified. The analysis of the scalar mass transport budget quantifies the mechanisms controlling the turbulent mixing and reveals that the mass flux is dominated by advection.

Statistical analysis of electroconvection near an ion-selective membrane in the highly chaotic regime

We investigate electroconvection and its impact on ion transport in a model system comprised of an ion-selective membrane, an aqueous electrolyte, and an external electric field applied normal to the membrane. We develop a direct numerical simulation code to solve the governing Poisson-Nernst-Planck and Navier-Stokes equations in three dimensions using a specialized parallel numerical algorithm and sufficient resolution to capture the high frequency and high wavenumber physics. We show a comprehensive statistical analysis of the transport phenomena in the highly chaotic regime. Qualitative and quantitative comparisons of two-dimensional (2D) and 3D simulations include prediction of the mean concentration fields as well as the spectra of concentration, charge density, and velocity signals. Our analyses reveal a significant quantitative difference between 2D and 3D electroconvection. Furthermore, we show that high-intensity yet short-lived current density hot spots appear randomly on the membrane surface, contributing significantly to the mean current density. By examining cross correlations between current density on the membrane and other field quantities we explore the physical mechanisms leading to current hot spots. We also present analysis of transport fluxes in the context of ensemble-averaged equations. Our analysis reveals that in the highly chaotic regime the mixing layer (ML), which spans the majority of the domain extent, is governed by advective fluctuations. Furthermore, we show that in the ML the mean electromigration fluxes cancel out for positive and negative ions, indicating that the mean transport of total salt content within the ML can be represented via the electroneutral approximation. Finally, we present an assessment of the importance of different length scales in enhancing transport by computing the cross covariance of concentration and velocity fluctuations in the wavenumber space. Our analysis indicates that in the majority of the domain the large scales contribute most significantly to transport, while the effects of small scales become more appreciable in regions very near the membrane.7 MoreReceived 14 June 2016DOI:https://doi.org/10.1103/PhysRevFluids.1.073601©2016 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasElectrokinetic flowsNanofluidicsFluid Dynamics

Observations of the Transfer of Energy and Momentum to the Oceanic Surface Boundary Layer beneath Breaking Waves

AbstractMeasurements just beneath the ocean surface demonstrate that the primary mechanism by which energy from breaking waves is transmitted into the water column is through the work done by the covariance of turbulent pressure and velocity fluctuations. The convergence in the vertical transport of turbulent kinetic energy (TKE) balances the dissipation rate of TKE at first order and is nearly an order of magnitude greater than the sum of the integrated Eulerian and Stokes shear production. The measured TKE transport is consistent with a simple conceptual model that assumes roughly half of the surface flux of TKE by wave breaking is transmitted to depths greater than the significant wave height. During conditions when breaking waves are inferred, the direction of momentum flux is more aligned with the direction of wave propagation than with the wind direction. Both the energy and momentum fluxes occur at frequencies much lower than the wave band, consistent with the time scales associated with wave breaking. The largest instantaneous values of momentum flux are associated with strong downward vertical velocity perturbations, in contrast to the pressure work, which is associated with strong drops in pressure and upward vertical velocity perturbations.

北京城郊地区二氧化碳通量特征研究

PDF HTML阅读 XML下载 导出引用 引用提醒 北京城郊地区二氧化碳通量特征 DOI: 10.5846/stxb201309012181 作者: 作者单位: 中国气象局北京城市气象研究所,中国气象局北京城市气象研究所,中国气象局北京城市气象研究所,中国气象局北京城市气象研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(41175015); 北京市自然科学基金(8122022); 中央级公益性科研院所基本科研费专项基金(IUMKY2014 (LH)02) Carbon dioxide fluxes in a suburban area of Beijing Author: Affiliation: Institute of Urban Meteorology, CMA,Institute of Urban Meteorology, CMA,Institute of Urban Meteorology, CMA,Institute of Urban Meteorology, CMA Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:利用位于北京市顺义气象局45 m气象塔上36 m高度的湍流观测资料,对该区域2008年11月1日至2009年10月31日共365d的二氧化碳通量(CO2)的时间变化和各方位的分布特征进行了分析研究,并计算了CO2年排放量。结果表明,CO2受交通因素和居民日常生活排放的影响较小,冬季耗能取暖会显著增加CO2的排放量;受供暖排放和植物生长季节光合作用的影响,冬季的CO2通量值在全天绝大多数时刻均高于其他季节,其日平均值为15.6 μmol m-2 s-1,显著高于春、夏、秋季的日平均值5.6、5.7和8.8 μmol m-2 s-1(t-test, P<0.001)。各方向CO2通量值的大小与其源区内土地利用/覆盖方式以及建筑物的使用功能和使用性质密切相关,住宅楼、饭店、工厂、旅馆等人工建筑面积占比例越大,CO2排放量越大;而植被覆盖比例较高的方向CO2值较小。观测点周边区域是CO2的排放源,且年平均排放量达到13.6 kg m-2 a-1,但低于同一时期北京市内高密度住宅区域的CO2年排放量。 Abstract:Over the last two decades, the eddy covariance (EC) technique has been applied to measure the flux of CO2 in various ecosystems. Among terrestrial ecosystems, urban areas play an important role because most of the anthropogenic emissions of CO2 originate in these areas. A better understanding of CO2 exchange between urban ecosystems and the atmosphere is important for quantifying urban contributions to the global carbon cycle as well as for evaluating the urban climate impact on and response to global climate changes. In the past two decades, studies of CO2 levels in urban environment mainly focused on the concentration in the ambient and emission inventory based on energy consumption data in China. To date, CO2 monitoring in Chinese cities using EC techniques is rare because it is difficult to find a representative urban surface and install EC instruments on the available tower. We investigated CO2 fluxes over a suburban, low-density residential area (Shunyi) in the north east Beijing. Suburban areas are growing rapidly in China and are potentially an important land-use category for anthropogenic CO2 emissions. We collected the EC measurements from the meteorological tower of Shunyi Meteorology Center from November 1, 2008 to October 31, 2009. The half-hourly CO2 fluxes were calculated by computing the mean covariance of CO2 fluctuations with the fluctuating vertical velocity observed by the EC system. Turbulence Knight2 (TK2) software package was employed for quality assurance and quality control of the EC data. TK2 provides a quality flag for each half-hourly flux data, and the highest quality data when the quality flag was less than 3 were used to analyze the daily variation and spatial distribution characteristics of CO2 flux during different seasons, the summer daytime CO2 flux as a function of photosynthetically active radiation (PAR), and the nighttime CO2 flux as a function of soil temperature at 10 cm depth during the measurement period. The data gaps were filled using the back propagation neural network to calculate the annual total CO2 emissions. Our results indicate that CO2 emissions were less affected by road vehicles and household activities at the Shunyi measurement area. Fuel consumption for heating during winter significantly increased CO2 emissions; and because of the carbon uptake by plants for photosynthesis during the growing season, the average daily flux measured in winter was significantly higher than that in other seasons. Patterns of spatial variation of CO2 flux showed that areas with a high proportion of man-made surfaces had higher CO2 values, while vegetation covered areas had lower CO2 values. The consistently positive CO2 flux throughout the year indicates that the analyzed suburban surface is a net source of CO2 to the atmosphere. The total annual CO2 emission from our study area was 13.6 kg m-2 a-1; this value is higher than the emissions from suburban residential areas in foreign cities. We infer that this high value is because of the low vegetation coverage and higher number of commercial and industrial buildings in our study area. Our data will be added to the global database of CO2 fluxes and it can be used for future planning of urban development with regard to reducing the CO2 emission. 参考文献 相似文献 引证文献

Smoothed particle hydrodynamics model for Landau-Lifshitz-Navier-Stokes and advection-diffusion equations.

We propose a novel smoothed particle hydrodynamics (SPH) discretization of the fully coupled Landau-Lifshitz-Navier-Stokes (LLNS) and stochastic advection-diffusion equations. The accuracy of the SPH solution of the LLNS equations is demonstrated by comparing the scaling of velocity variance and the self-diffusion coefficient with kinetic temperature and particle mass obtained from the SPH simulations and analytical solutions. The spatial covariance of pressure and velocity fluctuations is found to be in a good agreement with theoretical models. To validate the accuracy of the SPH method for coupled LLNS and advection-diffusion equations, we simulate the interface between two miscible fluids. We study formation of the so-called "giant fluctuations" of the front between light and heavy fluids with and without gravity, where the light fluid lies on the top of the heavy fluid. We find that the power spectra of the simulated concentration field are in good agreement with the experiments and analytical solutions. In the absence of gravity, the power spectra decay as the power -4 of the wavenumber-except for small wavenumbers that diverge from this power law behavior due to the effect of finite domain size. Gravity suppresses the fluctuations, resulting in much weaker dependence of the power spectra on the wavenumber. Finally, the model is used to study the effect of thermal fluctuation on the Rayleigh-Taylor instability, an unstable dynamics of the front between a heavy fluid overlaying a light fluid. The front dynamics is shown to agree well with the analytical solutions.

Fluctuations of cell population in a colonic crypt.

The number of stem cells in a colonic crypt is often very small, which leads to large intrinsic fluctuations in the cell population. Based on the model of cell population dynamics with linear feedback in a colonic crypt, we present a stochastic dynamics of the cell population [including stem cells (SCs), transit amplifying cells (TACs), and fully differentiated cells (FDCs)]. The Fano factor, covariance, and susceptibility formulas of the cell population around the steady state are derived by using the Langevin theory. In the range of physiologically reasonable parameter values, it is found that the stationary populations of TACs and FDCs exhibit an approximately threshold behavior as a function of the net growth rate of TACs, and the reproductions of TACs and FDCs can be classified into three regimens: controlled, crossover, and uncontrolled. With the increasing of the net growth rate of TACs, there is a maximum of the relative intrinsic fluctuations (i.e., the Fano factors) of TACs and FDCs in the crossover region. For a fixed differentiation rate and the net growth rate of SCs, the covariance of fluctuations between SCs and TACs has a maximum in the crossover region. However, the susceptibilities of both TACs and FDCs to the net growth rate of TACs have a minimum in the crossover region.

On the Convergence to the Continuum of Finite Range Lattice Covariances

In (J. Stat. Phys. 115:415–449, 2004) Brydges, Guadagni and Mitter proved the existence of multiscale expansions of a class of lattice Green’s functions as sums of positive definite finite range functions (called fluctuation covariances). The lattice Green’s functions in the class considered are integral kernels of inverses of second order positive self-adjoint elliptic operators with constant coefficients and fractional powers thereof. The rescaled fluctuation covariance in the nth term of the expansion lives on a lattice with spacing L −n and satisfies uniform bounds. Our main result in this note is that the sequence of these terms converges in appropriate norms at a rate L −n/2 to a smooth, positive definite, finite range continuum function.

Risk spreading, connectivity, and optimal reserve spacing

Two important processes determining the dynamics of spatially structured populations are dispersal and the spatial covariance of demographic fluctuations. Spatially explicit approaches to conservation, such as reserve networks, must consider the tension between these two processes and reach a balance between distances near enough to maintain connectivity, but far enough to benefit from risk spreading. Here, we model this trade-off. We show how two measures of metapopulation persistence depend on the shape of the dispersal kernel and the shape of the distance decay in demographic covariance, and we consider the implications of this trade-off for reserve spacing. The relative rates of distance decay in dispersal and demographic covariance determine whether the long-run metapopulation growth rate, and quasi-extinction risk, peak for adjacent patches or intermediately spaced patches; two local maxima in metapopulation persistence are also possible. When dispersal itself fluctuates over time, the trade-off changes. Temporal variation in mean distance that propagules are dispersed (i.e., propagule advection) decreases metapopulation persistence and decreases the likelihood that persistence will peak for adjacent patches. Conversely, variation in diffusion (the extent of random spread around mean dispersal) increases metapopulation persistence overall and causes it to peak at shorter inter-patch distances. Thus, failure to consider temporal variation in dispersal processes increases the risk that reserve spacings will fail to meet the objective of ensuring metapopulation persistence. This study identifies two phenomena that receive relatively little attention in empirical work on reserve spacing, but that can qualitatively change the effectiveness of reserve spacing strategies: (1) the functional form of the distance decay in covariance among patch-specific demographic rates and (2) temporal variation in the shape of the dispersal kernel. The sensitivity of metapopulation recovery and persistence to how covariance of vital rates decreases with distance suggests that estimating the shape of this function is likely to be as important for effective reserve design as estimating connectivity. Similarly, because temporal variation in dispersal dynamics influences the effect of reserve spacing, approaches to reserve design that ignore such variation, and rely instead on long-term average dispersal patterns, are likely to lead to lower metapopulation viability than is actually achievable.

Dynamical Allosterism in the Mechanism of Action of DNA Mismatch Repair Protein MutS

The multidomain protein Thermus aquaticus MutS and its prokaryotic and eukaryotic homologs recognize DNA replication errors and initiate mismatch repair. MutS actions are fueled by ATP binding and hydrolysis, which modulate its interactions with DNA and other proteins in the mismatch-repair pathway. The DNA binding and ATPase activities are allosterically coupled over a distance of ∼70 Å, and the molecular mechanism of coupling has not been clarified. To address this problem, all-atom molecular dynamics simulations of ∼150 ns including explicit solvent were performed on two key complexes—ATP-bound and ATP-free MutS⋅DNA(+T bulge). We used principal component analysis in fluctuation space to assess ATP ligand-induced changes in MutS structure and dynamics. The molecular dynamics-calculated ensembles of thermally accessible structures showed markedly small differences between the two complexes. However, analysis of the covariance of dynamical fluctuations revealed a number of potentially significant interresidue and interdomain couplings. Moreover, principal component analysis revealed clusters of correlated atomic fluctuations linking the DNA and nucleotide binding sites, especially in the ATP-bound MutS⋅DNA(+T) complex. These results support the idea that allosterism between the nucleotide and DNA binding sites in MutS can occur via ligand-induced changes in motion, i.e., dynamical allosterism.

Budget study of the internal variability in ensemble simulations of the Canadian Regional Climate Model at the seasonal scale

Previous investigations with nested regional climate models have revealed that simulations are sensitive to the initial conditions (IC). This results in internal variability (IV) in ensembles of simulations initialized with small differences in IC. In a previous study, a quantitative budget calculation has documented the physical processes responsible for the rapid growth of IV in simulations with the Canadian Regional Climate Model (CRCM). By using an ensemble of 20 simulations performed for the 1993 summer season, we extend the previous study to further our understanding about the physical processes responsible for the maintenance and fluctuations of IV in a seasonal simulation with CRCM. We have identified and quantified various terms in the prognostic budget equations of IV for the potential temperature and the absolute vorticity. For these studied variables, the covariance of fluctuations acting on the gradient of the ensemble mean of variables generally contributes to increasing the IV, indicating that the transport of heat and vorticity is down the gradient of ensemble mean potential temperature and absolute vorticity. The horizontal transport of IV by ensemble mean flow acts as a sink term, the IV transport out of the study domain contributing to reduce the IV. On average in the troposphere and at the seasonal scale, results confirm that there is no trend in IV although it greatly fluctuates in time. Our results also show that IV is a natural phenomenon arising from the chaotic nature of the atmosphere. In a time-averaged sense, the IV budget reduces to a balance between generation and destruction terms.

Diagnostic budget study of the internal variability in ensemble simulations of the Canadian RCM

Due to the chaotic and nonlinear nature of the atmospheric dynamics, it is known that small differences in the initial conditions (IC) of models can grow and affect the simulation evolution. In this study, we perform a quantitative diagnostic budget calculation of the various diabatic and dynamical contributions to the time evolution and spatial distribution of internal variability (IV) in simulations with the nested Canadian Regional Climate Model. We establish prognostic budget equations of the IV for the potential temperature and the relative vorticity fields. For both of these variables, the IV equations present similar terms, notably terms relating to the transport of IV by ensemble-mean flow and to the covariance of fluctuations acting on the gradient of the ensemble-mean state. We show the skill of these equations to diagnose the IV that took place in an ensemble of 20 3-month (summer season) simulations that differed only in their IC. Our study suggests that the dominant terms responsible for the large increase of IV are either the covariance term involving the potential temperature fluctuations and diabatic heating fluctuations, or the covariance of inter-member fluctuations acting upon ensemble-mean gradients. Our results also show that, on average, the third-order terms are negligible, but they can become important when the IV is large.

All-Atom Molecular Dynamics Simulations of the K+ Channel Chimera Kv1.2/Kv2.1

Voltage-gated K+ channels (Kv) are composed of four subunits, each of which contains six trans-membrane domains (TMs), S1 through S6. The S1-S4 segments comprise the voltage-sensing domain (VS), which senses membrane potential and controls the gating of the pore domain (PD). Although still controversial, the voltage-sensing domain undergoes conformational changes within the membrane electric field, upon membrane depolarization, that is mechanically transferred via the S4-S5 linker to the intracellular gate of the channel. MD simulations of portions of PD and VS regions highlighted the importance of their flexibility for proper channel function. Nevertheless, a comprehensive description of the dynamics of both domains at atomic level has not been provided yet. Here we report the analysis of all-atom multiple molecular dynamics simulations (∼200 ns) of the entire Kv1.2/2.1 chimera, consisting of the α and β chain embedded in a 549 monomer POPC bilayer, and immersed in a box of 135K explicit SPC water molecules at 300 K. We used principal components analysis (PCA) of the Cα atomic fluctuations covariance matrix to analyze the essential subspace that characterizes the channel internal dynamics. Briefly, we observed an up to 4.5 A conformational drift of VS from its starting position. The average RMSF of the S3b-S4 domain was between 1.6 and 3.0 A. Relative to the pore region, i) the second principal component shows that all four VS domains fluctuate in a concerted manner and affect the flexibility of the intracellular gates; ii) the first principal component reveals that T1 domain moves approximately 3.5 A downwards, influencing the local structure and dynamics of the neighboring intracellular gate. Protein-lipids interactions are crucial for channel structure/function. Thus, the contributions of H-bonds and salt-bridges between channel atoms and lipid head-groups on global channel dynamics will be illustrated.

Linear Response of Biomolecules To External Perturbations: Revisit Induce-fit

Atoms in proteins, viewed as interlinked hubs, communicate with each other in complying with governed physical forces. The deviations of their positions from the mean, known as fluctuations, are essential in mediating functionally relevant biological processes maintaining one's daily life. The coupled fluctuations between pairs of atoms, the fluctuation covariance, can be determined analytically by Normal Mode Analysis, or numerically by MD simulations. Our study considers how this network of atoms reacts in response to external perturbations. Effects of such perturbations are exemplified by ligand- or (another) protein-induced conformational changes as well as the appreciated structural distortion of crystalline structures from its solution conformers. We assume the response of the system has linear departure from the mean under small perturbations on the Hamiltonian at equilibrium state. The formulated linear response theories, either time-dependent or -independent [1], says that the positional change of a given atom i is the accumulative sum of fluctuation covariance ij, at unperturbed state, multiplied by the force exerted on atom j. The time-dependent response function determined from MD simulation of carbonmonoxy myoglobin is used to track time-dependent conformational changes upon photo-dissociation of CO. The consequently obtained understanding of perturbation propagation is compared with experimental results. Also, the structural distortion of X-ray-characterized ubiquitin from its solution conformer can be well explained by the induce-fit theory, in a wider sense, while population-shift does not account for such a deviation.[1] Ikeguchi M, Ueno J, Sato M, and Kidera A. (2005) Phys Rev Lett, 94, 078102.

Testing of ambient noise forecasting algorithms with LADC noise data

Long-term, omnidirectional underwater acoustic noise was measured by three buoys in the northern Gulf of Mexico over a 36-day period during the summer of 2001 as part of the Littoral Acoustic Demonstration Center project, phase I. This extensive data set is used to develop and evaluate algorithms for near-term temporal prediction of noise, based on immediate in situ data. Noise time series data in one-third-octave bands from 10 to 5000 Hz are processed to extract characterizing parameters such as mean level, variance, and temporal coherence across all frequency bands. The fluctuation spectrum is analyzed to determine how the noise variability is distributed with temporal period, and eigenvectors based on the fluctuation covariance matrix are used to identify underlying basic properties of noise variation. These tools are then used to predict future values of noise based on measurements at preceding times. [Research supported by ONR.]

Atmospheric optical communication with a Gaussian Schell beam.

We consider a wireless optical communication link in which the laser source is a Gaussian Schell beam. The effects of atmospheric turbulence strength and degree of source spatial coherence on aperture averaging and average bit error rate are examined. To accomplish this, we have derived analytic expressions for the spatial covariance of irradiance fluctuations and log-intensity variance for a Gaussian beam of any degree of coherence in the weak fluctuation regime. When spatial coherence of the transmitted source beam is reduced, intensity fluctuations (scintillations) decrease, leading to a significant reduction in the bit error rate of the optical communication link. We have also identified an enhanced aperture-averaging effect that occurs in tightly focused coherent Gaussian beams and in collimated and slightly divergent partially coherent beams. The expressions derived provide a useful design tool for selecting the optimal transmitter beam size, receiver aperture size, beam spatial coherence, transmitter focusing, etc., for the anticipated atmospheric channel conditions.

Bank Integration and Business Volatility in the U.S.

We investigate how bank migration across state lines over the last quarter century has affected the size and covariance of business fluctuations within states. Starting with a two-state version of the unit banking model in Holmstrom and Tirole(1997), we conclude that the theoretical affect of integration on business cycle size is ambiguous, as some shocks are dampened by integration, but others are amplified. Empirically, we find that integration diminishes employment growth fluctuations within states, and decreases the deviations in employment growth across states. Business cycles within states become smaller with integration, in other words, but more alike. Our results for the United States bear on the financial convergence underway in Europe, where banks remain highly fragmented across nations.

Multiple Scattering in Clouds: Insights from Three-Dimensional Diffusion/P1 Theory

In the atmosphere, multiple scattering matters nowhere more than in clouds, and being a product of its turbulence, clouds are highly variable environments. This challenges three-dimensional (3D) radiative transfer theory in a way that easily swamps any available computational resources. Fortunately, the far simpler diffusion (or P1) theory becomes more accurate as the scattering intensifies, and allows for some analytical progress as well as computational efficiency. After surveying current approaches to 3D solar cloud-radiation problems from the diffusion standpoint, a general 3D result in steady-state diffusive transport is derived relating the variability-induced change in domain-average flux (i.e., diffuse transmittance) to the one-point covariance of internal fluctuations in particle density and in radiative flux. These flux variations follow specific spatial patterns in deliberately hydrodynamical language: radiative channeling. The P1 theory proves even more powerful when the photon diffusion process unfolds in time as well as space. For slab geometry, characteristic times and lengths that describe normal and transverse transport phenomena are derived. This phenomenology is used to (a) explain persistent features in satellite images of dense stratocumulus as radiative channeling, (b) set limits on current cloud remote-sensing techniques, and (c) propose new ones both active and passive.