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By interacting with radiation, aerosols perturb the Earth’s energy budget and thus the global precipitation amount. It was previously shown that aerosols lead to a reduction in the global-mean precipitation amount. We have further demonstrated in aqua-planet simulations that the local response to absorbing aerosols differs between the tropics and the extra-tropics. In this study we incorporate an energy budget perspective to further examine the latitudinal dependence of the effect of aerosol-radiation interaction on precipitation in idealized global simulations. We demonstrate that the transition between a positive local precipitation response in the tropics and a negative local precipitation response in the extra-tropics occurs at relatively low latitudes (~10), indicating a transition between the deep-tropics (in which the Coriolis force is low, hence direct thermally-driven circulation, and associated divergence/convergence of energy/moisture, can form as a result of the diabatic-heating) and their surroundings. In addition, we gradually increase the level of complexity of the simulations and demonstrate that, in the case of absorbing aerosols, the effect of land is to counteract some of the response both inside and outside the deep-tropics due to the reduction in surface latent-heat flux that opposes the diabatic-heating. The effect of scattering aerosols is also examined and demonstrate a decrease in precipitation over land in both the tropics and extra-tropics and no effect over the ocean. Finally, we examine these results in a more realistic set-up and demonstrate that although the physical mechanisms still operate, they are unlikely to be significant enough to be discerned from natural-variability.

Our goal is to equip a dialogue agent that asks questions about a visual scene with object detection skills. We take the first steps in this direction within the GuessWhat?! game. We use Mask R-CNN object features as a replacement for ground-truth annotations in the Guesser module, achieving an accuracy of 57.92%. This proves that our system is a viable alternative to the original Guesser, which achieves an accuracy of 62.77% using ground-truth annotations, and thus should be considered an upper bound for our automated system. Crucially, we show that our system exploits the Mask R-CNN object features, in contrast to the original Guesser augmented with global, VGG features. Furthermore, by automating the object detection in GuessWhat?!, we open up a spectrum of opportunities, such as playing the game with new, non-annotated images and using the more granular visual features to condition the other modules of the game architecture.

Cloud‐aerosol interactions are considered as one of the largest sources of uncertainties in the study of climate change. Here another possible cloud‐aerosol effect on climate is proposed. A series of large eddy simulations (LES) with bin microphysics reveal a sensitivity of the total atmospheric water vapor amount to aerosol concentration. Under polluted conditions the rain is suppressed and the total amount of water vapor in the atmosphere increases with time compared to clean precipitating conditions. Theoretical examination of this aerosol effect on water vapor transport from the subtropics to the tropics, and hence on the equatorial rain and Hadley circulation, is conducted using an idealized general circulation model (GCM). It is shown that a reduction in the subtropical rain amount results in increased water vapor advection to the tropics and enhanced equatorial rain and Hadley circulation. This joins previously proposed mechanisms on the radiative aerosol effect on the general circulation.

In Part I of this work a 3-D cloud tracking algorithm and phase space of center of gravity altitude versus cloud liquid water mass (CvM space) were introduced and described in detail. We showed how new physical insight can be gained by following cloud trajectories in the CvM space. Here this approach is used to investigate aerosol effects on cloud fields of warm cumuli. We show a clear effect of the aerosol loading on the shape and size of CvM clusters. We also find fundamental differences in the CvM space between simulations using bin versus bulk microphysical schemes, with the bin scheme precipitation expressing much higher sensitivity to changes in aerosol concentrations. Using the bin microphysical scheme, we find that the increase in cloud center of gravity altitude with increase in aerosol concentrations occurs for a wide range of cloud sizes. This is attributed to reduced sedimentation, increased buoyancy and vertical velocities, and increased environmental instability, all of which are tightly coupled to inhibition of precipitation processes and subsequent feedbacks of clouds on their environment. Many of the physical processes shown here are consistent with processes typically associated with cloud invigoration.

Solute transport takes place in heterogeneous porous formations, with the log conductivity, Y = ln K, modeled as a stationary random space function of given univariate normal probability density function (pdf) with mean 〈Y〉, variance σY2, and integral scale IY. For weak heterogeneity, the above mentioned quantities completely define the first-order approximation of the longitudinal macrodispersivity αL = σY2 IY. However, in highly heterogeneous formations, nonlinear effects which depend on the multipoint joint pdf of Y, impact αL. Most of the past numerical simulations assumed a multivariate normal distribution (MVN) of Y values. The main aim of this study is to investigate the impact of deviations from the MVN structure upon αL. This is achieved by using the concept of spatial correlations of different Y classes, the latter being defined as the space domain where Y falls in the generic interval [Y,Y + DY]. The latter is characterized by a length scale γ(Y), reflecting the degree of connectivity of the domain (the concept is similar to the indicator variograms). We consider both "symmetrical" and "non-symmetrical" structures, for which γ(Y′) = γ(-Y′) (similar to the MVN), and γ(Y′) ≠ γ(-Y′), respectively, where Y′ = Y - 〈Y〉. For example, large Y zones may have high spatial correlation, while low Y zones are poorly correlated, or vice versa. The impact of γ(Y) on αL is investigated by adopting a structure model which has been used in the past in order to investigate flow and transport in highly heterogeneous media. It is found that the increased correlation in the low conductive zones with respect to the high ones generally leads to a significant increase in aL, for the same global IY. The finding is explained by the solute retention occurring in low Y zones, which has a larger effect on solute spreading than hi h Y zones. Conversely, αL decreases when the high conductivity zones are more correlated than the low Y ones. Dispersivity is less affected by the shape of γ(Y) for symmetrical distributions. It is found that the range of validity of the first-order dispersivity, i.e., αL = IYσY2, narrows down for non-symmetrical structures. © 2010 by the American Geophysical Union.

Flow and transport are solved for a heterogeneous medium modeled as an ensemble of spherical inclusions of uniform radius R and of conductivities K, drawn from a pdff(K) (Fig. 1). This can be regarded as a particular discretization scheme, allowing for accurate numerical and semi-analytical solutions, for any given univariate f (Y) (Y = In K) and integral scale I(y). The transport is quantified by the longitudinal equivalent macrodispersivity alpha(Leq), for uniform mean flow of velocity U and for a large (ergodic) plume of a conservative solute injected in a vertical plane (x = 0) and moving past a control plane at x >> I(y). In the past we have solved transport for advection solely for highly heterogeneous media of sigma(2)(Y) > 1. (C) 2008 Elsevier Ltd. All rights reserved.

The effective conductivity Kef of porous formations of spatially variable permeability K is determined for media of random two-dimensional and isotropic structures. The medium is modeled as an ensemble of multiphase circular inclusions of different Y = ln K, characterized by a pdf f(Y), and of different radii R (polydisperse medium), of pdf f(R vertical bar Y), which are implanted in a matrix of K = K(0). A large number of inclusions are embedded in a large circle, to allow for exchange of space and ensemble averaging. For symmetrical pdf f(Y) = f(-Y) and symmetrical f(R vertical bar Y), the Matheron exact relationship K(ef) = KG (the geometric mean) applies. The main aim of the article is to determine the deviation of K(ef) from K(G) for symmetrical f(Y) but nonsymmetrical f(R vertical bar Y). This is related to recent studies on the effect on Kef of connectivity of spatial domains of different K classes. The problem is solved numerically by an accurate and efficient iterative procedure and by a novel, approximate, analytical method. The two procedures are illustrated and compared for the configuration of two phases of conductivities K(1), K(2), of equal volume fractions, of different radii R(1) and R(2), respectively, within a matrix of K(0) = K(G) = (K(1) K(2))(1/2). Even for very high heterogeneity (K(1)/K(2) = 1000) it is found that the effect of variable R is relatively modest and it manifests mainly at the largest attainable volume fraction. The simple analytical approximation, valid for moderate volume fractions, is applied to investigation of K(ef) for normal f(Y), and for two values of R, for Y 0 and Y > 0, respectively. The results are of interest for similar heterogeneous media and for other physical processes governed by linear relationships between the flux and the driving potential gradient.

At regional scale, it is common to model groundwater flow as 2-D in the x, y, horizontal plane, by integrating the full 3-D equations over the vertical. Furthermore, adopting the Dupuit assumption results in the local transmissivity T as a formation property, equal to the vertically integrated hydraulic conductivity K. In practice, the related block transmissivity T(b), defined for a volume of area omega (square of side L) in the horizontal plane and height D, is the property of interest. However, most aquifers are of a heterogeneous 3-D structure, and Y = lnK is commonly modeled as a normal and stationary random function which is characterized by the variance sigma(2)(Y), the horizontal I, and vertical I(v) integral scales. The Dupuit assumption is generally not obeyed for formations of 3-D spatially variable Y, and transmissivity is no more a meaningful property, independent of flow conditions. Useful generalizations of local and block transmissivity are possible for steady mean uniform flow in the horizontal direction and formations of constant thickness. In that case T and T(b) become random stationary variables characterized by their mean, variance, and integral scales. These moments are determined for the first time in an analytical form or by a few quadratures, by adopting a first-order approximation in sigma(2)(Y), and they depend on the ratio D/I(v), e = I(v)/I and L/I. The block conductivity expected values are compared with the numerical solutions of Dykaar and Kitanidis (1993), and the agreement is very good for sigma(2)(Y)

Three-dimensional advective transport of passive solutes through isotropic porous formations of stationary non- Gaussian log conductivity distributions is investigated by using an approximate semianalytical model, which is compared with accurate numerical simulations. The study is a continuation of our previous works in which formation heterogeneity is modeled using spherical nonoverlapping inclusions and an approximate analytical model was developed. Flow is solved for average uniform velocity, and transport of an ergodic plume is quantified by mass flux ( traveltime distribution) at a control plane. The analytical model uses a self- consistent argument, and it is based on the solution for an isolated inclusion submerged in homogeneous background matrix of effective conductivity. As demonstrated in the past, this analytical model accurately predicted the entire distributions of traveltimes in formations of Gaussian log conductivity distributions, as validated by numerical simulations. The present study ( 1) extends the results to formations of non- Gaussian log conductivity structures ( the subordination model), ( 2) extends the approximate analytical model to cubical blocks that tessellate the entire domain, ( 3) identifies a condition in conductivity distribution, at the tail of low values, that renders transport anomalous with macrodispersivity growing without bounds, and ( 4) provides links of our work to continuous time random walk ( CTRW) methodology, as applied to subsurface transport. It is found that a class of CTRW solutions proposed in the past cannot be based on solution of flow in formations with conductivity distribution of finite integral scale.

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Determination of hydraulic head, H, as a function of spatial coordinates and time, in ground water flow is the basis for aquifer management and for prediction of contaminant transport. Several computer codes are available for this purpose. Spatial distribution of the transmissivity, T( x, y), is a required input to these codes. In most aquifers, T varies in an erratic manner, and it can be characterized statistically in terms of a few moments: the expected value, the variance, and the variogram. Knowledge of these moments, combined with a few measurements, permits one to estimate T at any point using geostatistical methods. In a review of transmissivity data from 19 unconsolidated aquifers, Hoeksema and Kitanidis ( 1985) identified two types of the logtransmissivity Y = In( T) variations: correlated variations with variance sigma(Yc)(2) and correlation scale, I-Y, on the order of kilometers, and uncorrelated variations with variance sigma(Yn)(2). Direct identification of the logtransmissivity variogram, Gamma(Y), from measurements is difficult because T data are generally scarce. However, many head measurements are commonly available. The aim of the paper is to introduce a methodology to identify the transmissivity variogram parameters (sigma(Yc)(2), I-Y, and sigma(Yn])(2)) using head data in formations characterized by large logtransmissivity variance. The identification methodology uses a combination of precise numerical simulations ( carried out using analytic element method) and a theoretical model. The main objective is to demonstrate the application of the methodology to a regional ground water flow in Eagle Valley basin in west- central Nevada for which abundant transmissivity and head measurements are available.

Uniform flow of mean velocity U takes place in a highly heterogeneous, isotropic, aquifer of lognormal conductivity distribution (variance sigma(2)(Y), integral scale I). A conservative solute is injected instantaneously over an area A(0) at x = 0, normal to the mean flow, in a flux-proportional mode. Longitudinal spreading is caused by advection by the fluid velocity and is quantified with the aid of the mass flux mu(t, x) through fixed control planes at x. An equivalent macrodispersivity is defined in terms of the traveltime variance. The flow and transport are solved numerically in three realizations of the conductivity field with sigma(2)(Y) = 2, 4, 8, respectively. The medium is modeled by a collection of a large number N = 100,000 of spherical inclusions whose conductivities are drawn at random. Transport is simulated by tracking 40,000 particles originating at a large injection area (A(0) similar or equal to 2000 I-2) and for travel distance x

Flow and transport take place in a heterogeneous medium of lognormal distribution of the conductivity K. Flow is uniform in the mean, and the system is defined by U (mean velocity), sigma(2)(Y) (log conductivity variance), and integral scale I. Transport is analyzed in terms of the breakthrough curve of the solute, identical to the traveltime distribution, at control planes at distance x from the source. The "self-consistent'' approximation is used, where the traveltime tau is approximated by the sum of t pertinent to the different separate inclusions, and the neglected interaction between inclusions is accounted for by using the effective conductivity. The pdf f(tau, x), where x is the control plane distance, is derived by a simple convolution. It is found that f(tau, x) has an early arrival time portion that captures most of the mass and a long tail, which is related to the slow solute particles that are trapped in blocks of low K. The macrodispersivity is very large and is independent of x. The tail f(tau, x) is highly skewed, and only for extremely large x/I, depending on sigma(2)(Y), the plume becomes Gaussian. Comparison with numerical simulations shows very good agreement in spite of the absence of parameter fitting. It is found that finite plumes are not ergodic, and a cutoff of f(tau, x) is needed in order to fit the mass flux of a finite plume, depending on sigma(2)(Y) and x/I. The bulk of f(tau, x) can be approximated by a Gaussian shape, with fitted equivalent parameters. The issue of anomalous behavior is examined with the aid of the model.

Determining the effective conductivity of heterogeneous media is a central problem in different fields of physics. The medium considered here contains cylinders (inclusions) of random conductivities that are distributed at random in an embedding matrix. For random systems, widely encountered in applications, we derive an approximative analytical solution that applies to significantly denser configurations than Maxwell first-order approximations. The analytic solution is tested against accurate numerical simulations. The widely used effective medium approach is shown to be exact for symmetric conductivity distributions and quite accurate for asymmetrical cases.