Comparative accuracy of the Albedo, transmission and absorption for selected radiative transfer approximations

Illustrations of both the relative and absolute accuracy of eight different radiative transfer approximations as a function of optical thickness, solar zenith angle and single scattering albedo are given. Computational results for the plane albedo, total transmission and fractional absorption were obtained for plane-parallel atmospheres composed of cloud particles. These computations, which were obtained using the doubling method, are compared with comparable results obtained using selected radiative transfer approximations. Comparisons were made between asymptotic theory for thick layers and the following widely used two stream approximations: Coakley-Chylek's models 1 and 2, Meador-Weaver, Eddington, delta-Eddington, PIFM and delta-discrete ordinates

Windowed and Wavelet Analysis of Marine Stratocumulus Cloud Inhomogeneity

To improve radiative transfer calculations for inhomogeneous clouds, a consistent means of modeling inhomogeneity is needed. One current method of modeling cloud inhomogeneity is through the use of fractal parameters. This method is based on the supposition that cloud inhomogeneity over a large range of scales is related. An analysis technique named wavelet analysis provides a means of studying the multiscale nature of cloud inhomogeneity. In this paper, the authors discuss the analysis and modeling of cloud inhomogeneity through the use of wavelet analysis. Wavelet analysis as well as other windowed analysis techniques are used to study liquid water path (LWP) measurements obtained during the marine stratocumulus phase of the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment. Statistics obtained using analysis windows, which are translated to span the LWP dataset, are used to study the local (small scale) properties of the cloud field as well as their time dependence. The LWP data are transformed onto an orthogonal wavelet basis that represents the data as a number of times series. Each of these time series lies within a frequency band and has a mean frequency that is half the frequency of the previous band. Wavelet analysis combined with translated analysis windows reveals that the local standard deviation of each frequency band is correlated with the local standard deviation of the other frequency bands. The ratio between the standard deviation of adjacent frequency bands is 0.9 and remains constant with respect to time. This ratio defined as the variance coupling parameter is applicable to all of the frequency bands studied and appears to be related to the slope of the data's power spectrum. Similar analyses are performed on two cloud inhomogeneity models, which use fractal-based concepts to introduce inhomogeneity into a uniform cloud field. The bounded cascade model does this by iteratively redistributing LWP at each scale using the value of the local mean. This model is reformulated into a wavelet multiresolution framework, thereby presenting a number of variants of the bounded cascade model. One variant introduced in this paper is the 'variance coupled model,' which redistributes LWP using the local standard deviation and the variance coupling parameter. While the bounded cascade model provides an elegant two- parameter model for generating cloud inhomogeneity, the multiresolution framework provides more flexibility at the expense of model complexity. Comparisons are made with the results from the LWP data analysis to demonstrate both the strengths and weaknesses of these models

Solar Absorption in Cloudy Atmospheres

The theoretical computations used to compute spectral absorption of solar radiation are discussed. Radiative properties relevant to the cloud absorption problem are presented and placed in the context of radiative forcing. Implications for future measuring programs and the effect of horizontal inhomogeneities are discussed

The Use of Satellite-Measured Aerosol Optical Depth to Constrain Biomass Burning Emissions Source Strength in a Global Model GOCART

Small particles in the atmosphere, called "atmospheric aerosol" have a direct effect on Earth climate through scattering and absorbing sunlight, and also an indirect effect by changing the properties of clouds, as they interact with solar radiation as well. Aerosol typically stays in the atmosphere for several days, and can be transported long distances, affecting air quality, visibility, and human health not only near the source, but also far downwind. Smoke from vegetation fires is one of the main sources of atmospheric aerosol; other sources include anthropogenic pollution, dust, and sea salt. Chemistry transport models (CTMs) are among the major tools for studying the atmospheric and climate effects of aerosol. Due to the considerable variation of aerosol concentrations and properties on many temporal and spatial scales, and the complexity of the processes involved, the uncertainties in aerosol effects on climate are large, as is featured in the latest report of Intergovernmental Panel on Climate Change (IPCC) in 2007. Reducing this uncertainty in the models is very important both for predicting future climate scenarios and for regional air quality forecasting and mitigation. During vegetation fires, also called biomass burning (BB) events, complex mixture of gases and particles is emitted. The amount of BB emissions is usually estimated taking into account the intensity and size of the fire and the properties of burning vegetation. These estimates are input into CTMs to simulate BB aerosol. Unfortunately, due to large variability of fire and vegetation properties, the quantity of BB emissions is very difficult to estimate and BB emission inventories provide numbers that can differ by up to the order of magnitude in some regions. Larger uncertainties in data input make uncertainties in model output larger as well. A powerful way to narrow the range of possible model estimates is to compare model output to observations. We use satellite observations of aerosol properties, specifically aerosol optical depth, which is directly proportional to the amount of aerosol in the atmosphere, and compare it to the model output. Assuming the model represents aerosol transport and particle properties correctly, the amount of BB emissions determines the simulated aerosol optical depth. In this study, we explore the regional performance of 13 commonly used emission estimates. These are each input to global Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. We then evaluate how well each emission estimate reproduces the smoke aerosol optical depth measured by the MODIS instrument. We compared GOCART-simulate aerosol optical depth with that measured from the satellite for 124 fire cases around the world during 2006 and 2007. We summarize the regional performance of each emission inventory and discuss reasons for their differences by considering the assumptions made during their development. We also show that because stronger wind disperses smoke plumes more readily, in cases with stronger wind, a larger increase in emission amount is needed to increase aerosol optical depth. In quiet, low-wind-speed environments, BB emissions produce a more significant increase in aerosol optical depth, other things being equal. Using the region-specific, quantitative relationships derived in our paper, together with the wind speed obtained from another source for a given fire case, we can constrain the amount of emission required in the model to reproduce the observations. The results of this paper are useful to the developers of BB emission inventories, as they show the strengths and weaknesses of individual emission inventories in different regions of the globe, and also for modelers who use these inventories and wish to improve their model results

Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity

In the field of neuroimaging, there is a growing interest in developing collaborative frameworks that enable researchers to address challenging questions about the human brain by leveraging data across multiple sites all over the world. Additionally, efforts are also being directed at developing algorithms that enable collaborative analysis and feature learning from multiple sites without requiring the often large data to be centrally located. In this paper, we propose two new decentralized algorithms: (1) A decentralized regression algorithm for performing a voxel-based morphometry analysis on structural magnetic resonance imaging (MRI) data and, (2) A decentralized dynamic functional network connectivity algorithm which includes decentralized group ICA and sliding-window analysis of functional MRI data. We compare results against those obtained from their pooled (or centralized) counterparts on the same data i.e., as if they are at one site. Results produced by the decentralized algorithms are similar to the pooled-case and showcase the potential of performing multi-voxel and multivariate analyses of data located at multiple sites. Such approaches enable many more collaborative and comparative analysis in the context of large-scale neuroimaging studies

Telomere Shortening Impairs Regeneration of the Olfactory Epithelium in Response to Injury but Not Under Homeostatic Conditions

Atrophy of the olfactory epithelium (OE) associated with impaired olfaction and dry nose represents one of the most common phenotypes of human aging. Impairment in regeneration of a functional olfactory epithelium can also occur in response to injury due to infection or nasal surgery. These complications occur more frequently in aged patients. Although age is the most unifying risk factor for atrophic changes and functional decline of the olfactory epithelium, little is known about molecular mechanisms that could influence maintenance and repair of the olfactory epithelium. Here, we analyzed the influence of telomere shortening (a basic mechanism of cellular aging) on homeostasis and regenerative reserve in response to chemical induced injury of the OE in late generation telomere knockout mice (G3 mTerc−/−) with short telomeres compared to wild type mice (mTerc+/+) with long telomeres. The study revealed no significant influence of telomere shortening on homeostatic maintenance of the OE during mouse aging. In contrast, the regenerative response to chemical induced injury of the OE was significantly impaired in G3 mTerc−/− mice compared to mTerc+/+ mice. Seven days after chemical induced damage, G3 mTerc−/− mice exhibited significantly enlarged areas of persisting atrophy compared to mTerc+/+ mice (p = 0.031). Telomere dysfunction was associated with impairments in cell proliferation in the regenerating epithelium. Deletion of the cell cycle inhibitor, Cdkn1a (p21) rescued defects in OE regeneration in telomere dysfunctional mice. Together, these data indicate that telomere shortening impairs the regenerative capacity of the OE by impairing cell cycle progression in a p21-dependent manner. These findings could be relevant for the impairment in OE function in elderly people

Equatorial Atlantic Ocean dynamics in a coupled ocean–atmosphere model simulation

The ocean temperatures and zonal currents at the equatorial Atlantic simulated by an improved version of the Brazilian earth system model (BESM), with changes in the cloud cover scheme and optical properties of the atmospheric component, are analyzed and compared to those obtained from a previous version of BESM and also from other seven selected CMIP5 models. It is shown that this updated version of BESM, despite some persistent biases, more accurately represents the surface temperature variation at the Equator and the equatorial thermocline east–west slope. These improvements are associated to a more realistic seasonal cycle achieved for the Atlantic equatorial undercurrent, as well as sea surface temperatures and zonal wind stress. The better simulation of the equatorial undercurrent is, in its turn, credited to a more realistic representation of the surface wind position and strength at the tropical Atlantic by the coupled model. With many of the systematic errors noticed in the previous version of the model alleviated, this version of BESM can be considered as a useful tool for modelers involved in Atlantic variability studies