993 resultados para Amount of cloud layer 1
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[1] Cloud cover is conventionally estimated from satellite images as the observed fraction of cloudy pixels. Active instruments such as radar and Lidar observe in narrow transects that sample only a small percentage of the area over which the cloud fraction is estimated. As a consequence, the fraction estimate has an associated sampling uncertainty, which usually remains unspecified. This paper extends a Bayesian method of cloud fraction estimation, which also provides an analytical estimate of the sampling error. This method is applied to test the sensitivity of this error to sampling characteristics, such as the number of observed transects and the variability of the underlying cloud field. The dependence of the uncertainty on these characteristics is investigated using synthetic data simulated to have properties closely resembling observations of the spaceborne Lidar NASA-LITE mission. Results suggest that the variance of the cloud fraction is greatest for medium cloud cover and least when conditions are mostly cloudy or clear. However, there is a bias in the estimation, which is greatest around 25% and 75% cloud cover. The sampling uncertainty is also affected by the mean lengths of clouds and of clear intervals; shorter lengths decrease uncertainty, primarily because there are more cloud observations in a transect of a given length. Uncertainty also falls with increasing number of transects. Therefore a sampling strategy aimed at minimizing the uncertainty in transect derived cloud fraction will have to take into account both the cloud and clear sky length distributions as well as the cloud fraction of the observed field. These conclusions have implications for the design of future satellite missions. This paper describes the first integrated methodology for the analytical assessment of sampling uncertainty in cloud fraction observations from forthcoming spaceborne radar and Lidar missions such as NASA's Calipso and CloudSat.
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Eight years of cloud properties retrieved from Television Infrared Observation Satellite-N (TIROS-N) Observational Vertical Sounder (TOVS) observations aboard the NOAA polar orbiting satellites are presented. The relatively high spectral resolution of these instruments in the infrared allows especially reliable cirrus identification day and night. This dataset therefore provides complementary information to the International Satellite Cloud Climatology Project (ISCCP). According to this dataset, cirrus clouds cover about 27% of the earth and 45% of the Tropics, whereas ISCCP reports 19% and 25%, respectively. Both global datasets agree within 5% on the amount of single-layer low clouds, at 30%. From 1987 to 1995, global cloud amounts remained stable to within 2%. The seasonal cycle of cloud amount is in general stronger than its diurnal cycle and it is stronger than the one of effective cloud amount, the latter the relevant variable for radiative transfer. Maximum effective low cloud amount over ocean occurs in winter in SH subtropics in the early morning hours and in NH midlatitudes without diurnal cycle. Over land in winter the maximum is in the early afternoon, accompanied in the midlatitudes by thin cirrus. Over tropical land and in the other regions in summer, the maximum of mesoscale high opaque clouds occurs in the evening. Cirrus also increases during the afternoon and persists during night and early morning. The maximum of thin cirrus is in the early afternoon, then decreases slowly while cirrus and high opaque clouds increase. TOVS extends information of ISCCP during night, indicating that high cloudiness, increasing during the afternoon, persists longer during night in the Tropics and subtropics than in midlatitudes. A comparison of seasonal and diurnal cycle of high cloud amount between South America, Africa, and Indonesia during boreal winter has shown strong similarities between the two land regions, whereas the Indonesian islands show a seasonal and diurnal behavior strongly influenced by the surrounding ocean. Deeper precipitation systems over Africa than over South America do not seem to be directly reflected in the horizontal coverage and mesoscale effective emissivity of high clouds.
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Scalar-flux budgets have been obtained from large-eddy simulations (LESs) of the cumulus-capped boundary layer. Parametrizations of the terms in the budgets are discussed, and two parametrizations for the transport term in the cloud layer are proposed. It is shown that these lead to two models for scalar transports by shallow cumulus convection. One is equivalent to the subsidence detrainment form of convective tendencies obtained from mass-flux parametrizations of cumulus convection. The second is a flux-gradient relationship that is similar in form to the non-local parametrizations of turbulent transports in the dry-convective boundary layer. Using the fluxes of liquid-water potential temperature and total water content from the LES, it is shown that both models are reasonable diagnostic relations between fluxes and the vertical gradients of the mean fields. The LESs used in this study are for steady-state convection and it is possible to treat the fluxes of conserved thermodynamic variables as independent, and ignore the effects of condensation. It is argued that a parametrization of cumulus transports in a model of the cumulus-capped boundary layer should also include an explicit representation of condensation. A simple parametrization of the liquid-water flux in terms of conserved variables is also derived.
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The International System of Units, the SI, is built upon seven base quantities and seven base units, as summarized in the table below. Although most of these are familiar to all scientists, the quantity “amount of substance” and its unit “mole” are less familiar and are mainly used by chemists.1 In the chemistry community, the unit “mole” is familiar, but the name of the corresponding quantity “amount of substance” is not so familiar, and the concept is still a source of difficulty for many students. This article reviews and clarifies these two concepts2 and discusses the definition of the unit “mole” and its possible revision.
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Vitamin E absorption requires the presence of fat; however, limited information exists on the influence of fat quantity on optimal absorption. In the present study we compared the absorption of stable-isotope-labelled vitamin E following meals of varying fat content and source. In a randomised four-way cross-over study, eight healthy individuals consumed a capsule containing 150 mg H-2-labelled RRR-alpha-tocopheryl acetate with a test meal of toast with butter (17.5 g fat), cereal with full-fat milk (17.5 g fat), cereal with semi-skimmed milk (2.7 g fat) and water (0g fat). Blood was taken at 0, 0.5, 1, 1.5, 2, 3, 6 and 9 h following ingestion, chylomicrons were isolated, and H-2-labelled alpha-tocopherol was analysed in the chylomicron and plasma samples. There was a significant time (P<0.001) and treatment effect (P<0.001) in H-2-labelled alpha-tocopherol concentration in both chylomicrons and plasma between the test meals. H-2-labelled alpha-tocopherol concentration was significantly greater with the higher-fat toast and butter meal compared with the low-fat cereal meal or water (P< 0.001), and a trend towards greater concentration compared with the high-fat cereal meal (P= 0.065). There was significantly greater H-2-labelled α-tocopherol concentration with the high-fat cereal meal compared with the low-fat cereal meal (P< 0.05). The H-2-labelled alpha-tocopherol concentration following either the low-fat cereal meal or water was low. These results demonstrate that both the amount of fat and the food matrix influence vitamin E absorption. These factors should be considered by consumers and for future vitamin E intervention studies.
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Cloud radar and lidar can be used to evaluate the skill of numerical weather prediction models in forecasting the timing and placement of clouds, but care must be taken in choosing the appropriate metric of skill to use due to the non- Gaussian nature of cloud-fraction distributions. We compare the properties of a number of different verification measures and conclude that of existing measures the Log of Odds Ratio is the most suitable for cloud fraction. We also propose a new measure, the Symmetric Extreme Dependency Score, which has very attractive properties, being equitable (for large samples), difficult to hedge and independent of the frequency of occurrence of the quantity being verified. We then use data from five European ground-based sites and seven forecast models, processed using the ‘Cloudnet’ analysis system, to investigate the dependence of forecast skill on cloud fraction threshold (for binary skill scores), height, horizontal scale and (for the Met Office and German Weather Service models) forecast lead time. The models are found to be least skillful at predicting the timing and placement of boundary-layer clouds and most skilful at predicting mid-level clouds, although in the latter case they tend to underestimate mean cloud fraction when cloud is present. It is found that skill decreases approximately inverse-exponentially with forecast lead time, enabling a forecast ‘half-life’ to be estimated. When considering the skill of instantaneous model snapshots, we find typical values ranging between 2.5 and 4.5 days. Copyright c 2009 Royal Meteorological Society
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We have conducted the first extensive field test of two new methods to retrieve optical properties for overhead clouds that range from patchy to overcast. The methods use measurements of zenith radiance at 673 and 870 nm wavelengths and require the presence of green vegetation in the surrounding area. The test was conducted at the Atmospheric Radiation Measurement Program Oklahoma site during September–November 2004. These methods work because at 673 nm (red) and 870 nm (near infrared (NIR)), clouds have nearly identical optical properties, while vegetated surfaces reflect quite differently. The first method, dubbed REDvsNIR, retrieves not only cloud optical depth τ but also radiative cloud fraction. Because of the 1-s time resolution of our radiance measurements, we are able for the first time to capture changes in cloud optical properties at the natural timescale of cloud evolution. We compared values of τ retrieved by REDvsNIR to those retrieved from downward shortwave fluxes and from microwave brightness temperatures. The flux method generally underestimates τ relative to the REDvsNIR method. Even for overcast but inhomogeneous clouds, differences between REDvsNIR and the flux method can be as large as 50%. In addition, REDvsNIR agreed to better than 15% with the microwave method for both overcast and broken clouds. The second method, dubbed COUPLED, retrieves τ by combining zenith radiances with fluxes. While extra information from fluxes was expected to improve retrievals, this is not always the case. In general, however, the COUPLED and REDvsNIR methods retrieve τ to within 15% of each other.
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In numerical weather prediction (NWP) data assimilation (DA) methods are used to combine available observations with numerical model estimates. This is done by minimising measures of error on both observations and model estimates with more weight given to data that can be more trusted. For any DA method an estimate of the initial forecast error covariance matrix is required. For convective scale data assimilation, however, the properties of the error covariances are not well understood. An effective way to investigate covariance properties in the presence of convection is to use an ensemble-based method for which an estimate of the error covariance is readily available at each time step. In this work, we investigate the performance of the ensemble square root filter (EnSRF) in the presence of cloud growth applied to an idealised 1D convective column model of the atmosphere. We show that the EnSRF performs well in capturing cloud growth, but the ensemble does not cope well with discontinuities introduced into the system by parameterised rain. The state estimates lose accuracy, and more importantly the ensemble is unable to capture the spread (variance) of the estimates correctly. We also find, counter-intuitively, that by reducing the spatial frequency of observations and/or the accuracy of the observations, the ensemble is able to capture the states and their variability successfully across all regimes.
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The assimilation of observations with a forecast is often heavily influenced by the description of the error covariances associated with the forecast. When a temperature inversion is present at the top of the boundary layer (BL), a significant part of the forecast error may be described as a vertical positional error (as opposed to amplitude error normally dealt with in data assimilation). In these cases, failing to account for positional error explicitly is shown t o r esult in an analysis for which the inversion structure is erroneously weakened and degraded. In this article, a new assimilation scheme is proposed to explicitly include the positional error associated with an inversion. This is done through the introduction of an extra control variable to allow position errors in the a priori to be treated simultaneously with the usual amplitude errors. This new scheme, referred to as the ‘floating BL scheme’, is applied to the one-dimensional (vertical) variational assimilation of temperature. The floating BL scheme is tested with a series of idealised experiments a nd with real data from radiosondes. For each idealised experiment, the floating BL scheme gives an analysis which has the inversion structure and position in agreement with the truth, and outperforms the a ssimilation which accounts only for forecast a mplitude error. When the floating BL scheme is used to assimilate a l arge sample of radiosonde data, its ability to give an analysis with an inversion height in better agreement with that observed is confirmed. However, it is found that the use of Gaussian statistics is an inappropriate description o f t he error statistics o f t he extra c ontrol variable. This problem is alleviated by incorporating a non-Gaussian description of the new control variable in the new scheme. Anticipated challenges in implementing the scheme operationally are discussed towards the end of the article.
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This paper evaluates the relationship between the cloud modification factor (CMF) in the ultraviolet erythe- mal range and the cloud optical depth (COD) retrieved from the Aerosol Robotic Network (AERONET) "cloud mode" algorithm under overcast cloudy conditions (confirmed with sky images) at Granada, Spain, mainly for non-precipitating, overcast and relatively homogenous water clouds. Empirical CMF showed a clear exponential dependence on experimental COD values, decreasing approximately from 0.7 for COD=10 to 0.25 for COD=50. In addition, these COD measurements were used as input in the LibRadtran radia tive transfer code allowing the simulation of CMF values for the selected overcast cases. The modeled CMF exhibited a dependence on COD similar to the empirical CMF, but modeled values present a strong underestimation with respect to the empirical factors (mean bias of 22 %). To explain this high bias, an exhaustive comparison between modeled and experimental UV erythemal irradiance (UVER) data was performed. The comparison revealed that the radiative transfer simulations were 8 % higher than the observations for clear-sky conditions. The rest of the bias (~14 %) may be attributed to the substantial underestimation of modeled UVER with respect to experimental UVER under overcast conditions, although the correlation between both dataset was high (R2 ~ 0.93). A sensitive test showed that the main reason responsible for that underestimation is the experimental AERONET COD used as input in the simulations, which has been retrieved from zenith radiances in the visible range. In this sense, effective COD in the erythemal interval were derived from an iteration procedure based on searching the best match between modeled and experimental UVER values for each selected overcast case. These effective COD values were smaller than AERONET COD data in about 80 % of the overcast cases with a mean relative difference of 22 %.
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A disposable backscatter instrument is described for optical detection of cloud in the atmosphere from a balloon-carried platform. It uses an ultra-bright light emitting diode (LED) illumination source with a photodiode detector. Scattering of the LED light by cloud droplets generates a small optical signal which is separated from background light fluctuations using a lock-in technique. The signal to noise obtained permits cloud detection using the scattered LED light, even in daytime. The response is interpreted in terms of the equivalent visual range within the cloud. The device is lightweight (150 g) and low power (∼30 mA), for use alongside a conventional meteorological radiosonde.
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The extensive use of cloud computing in educational institutes around the world brings unique challenges for universities. Some of these challenges are due to clear differences between Europe and Middle East universities. These differences stem from the natural variation between people. Cloud computing has created a new concept to deal with software services and hardware infrastructure. Some benefits are immediately gained, for instance, to allow students to share their information easily and to discover new experiences of the education system. However, this introduces more challenges, such as security and configuration of resources in shared environments. Educational institutes cannot escape from these challenges. Yet some differences occur between universities which use cloud computing as an educational tool or a form of social connection. This paper discusses some benefits and limitations of using cloud computing and major differences in using cloud computing at universities in Europe and the Middle East, based on the social perspective, security and economics concepts, and personal responsibility.
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The calcium-mediated interaction of DNA with monolayers of the non-toxic, zwitterionic phospholipid, 1,2-distearoyl-sn-glycero-3-phosphocholine when mixed with 50 mol% of a second lipid, either the zwitteronic 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine or neutral cholesterol was investigated using a combination of surface pressure-area isotherms, Brewster angle microscopy, external reflectance Fourier transform infrared spectroscopy and specular neutron reflectivity in combination with contrast variation. When calcium and DNA were both present in the aqueous subphase, changes were observed in the compression isotherms as well as the surface morphologies of the mixed lipid monolayers. In the presence of calcium and DNA, specular neutron reflectivity showed that directly underneath the head groups of the lipids comprising the monolayers, DNA occupied a layer comprising approximately 13 and 18% v/v DNA for the 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine and cholesterol-containing monolayers, respectively. The volume of the corresponding layer for 1,2-distearoyl-sn-glycero-3-phosphocholine only containing monolayers was ∼15% v/v DNA. Furthermore regardless of the presence and nature of the second lipid and the surface pressure of the monolayer, the specular neutron reflectivity experiments showed that the DNA-containing layer was 20–27 Å thick, suggesting the presence of a well-hydrated layer of double-stranded DNA. External reflectance Fourier transform infrared studies confirmed the presence of double stranded DNA, and indicated that the strands are in the B-form conformation. The results shed light on the interaction between lipids and nucleic acid cargo as well as the role of a second lipid in lipid-based carriers for drug delivery.