978 resultados para clouds


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The combination of radar and lidar in space offers the unique potential to retrieve vertical profiles of ice water content and particle size globally, and two algorithms developed recently claim to have overcome the principal difficulty with this approach-that of correcting the lidar signal for extinction. In this paper "blind tests" of these algorithms are carried out, using realistic 94-GHz radar and 355-nm lidar backscatter profiles simulated from aircraft-measured size spectra, and including the effects of molecular scattering, multiple scattering, and instrument noise. Radiation calculations are performed on the true and retrieved microphysical profiles to estimate the accuracy with which radiative flux profiles could be inferred remotely. It is found that the visible extinction profile can be retrieved independent of assumptions on the nature of the size distribution, the habit of the particles, the mean extinction-to-backscatter ratio, or errors in instrument calibration. Local errors in retrieved extinction can occur in proportion to local fluctuations in the extinction-to-backscatter ratio, but down to 400 m above the height of the lowest lidar return, optical depth is typically retrieved to better than 0.2. Retrieval uncertainties are greater at the far end of the profile, and errors in total optical depth can exceed 1, which changes the shortwave radiative effect of the cloud by around 20%. Longwave fluxes are much less sensitive to errors in total optical depth, and may generally be calculated to better than 2 W m(-2) throughout the profile. It is important for retrieval algorithms to account for the effects of lidar multiple scattering, because if this is neglected, then optical depth is underestimated by approximately 35%, resulting in cloud radiative effects being underestimated by around 30% in the shortwave and 15% in the longwave. Unlike the extinction coefficient, the inferred ice water content and particle size can vary by 30%, depending on the assumed mass-size relationship (a problem common to all remote retrieval algorithms). However, radiative fluxes are almost completely determined by the extinction profile, and if this is correct, then errors in these other parameters have only a small effect in the shortwave (around 6%, compared to that of clear sky) and a negligible effect in the longwave.

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Magnetic clouds are a subset of interplanetary coronal mass ejections characterized by a smooth rotation in the magnetic field direction, which is interpreted as a signature of a magnetic flux rope. Suprathermal electron observations indicate that one or both ends of a magnetic cloud typically remain connected to the Sun as it moves out through the heliosphere. With distance from the axis of the flux rope, out toward its edge, the magnetic field winds more tightly about the axis and electrons must traverse longer magnetic field lines to reach the same heliocentric distance. This increased time of flight allows greater pitch-angle scattering to occur, meaning suprathermal electron pitch-angle distributions should be systematically broader at the edges of the flux rope than at the axis. We model this effect with an analytical magnetic flux rope model and a numerical scheme for suprathermal electron pitch-angle scattering and find that the signature of a magnetic flux rope should be observable with the typical pitch-angle resolution of suprathermal electron data provided ACE's SWEPAM instrument. Evidence of this signature in the observations, however, is weak, possibly because reconnection of magnetic fields within the flux rope acts to intermix flux tubes.

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Magnetic clouds are a class of interplanetary coronal mass ejections (CME) predominantly characterised by a smooth rotation in the magnetic field direction, indicative of a magnetic flux rope structure. Many magnetic clouds, however, also contain sharp discontinuities within the smoothly varying magnetic field, suggestive of narrow current sheets. In this study we present observations and modelling of magnetic clouds with strong current sheet signatures close to the centre of the apparent flux rope structure. Using an analytical magnetic flux rope model, we demonstrate how such current sheets can form as a result of a cloud’s kinematic propagation from the Sun to the Earth, without any external forces or influences. This model is shown to match observations of four particular magnetic clouds remarkably well. The model predicts that current sheet intensity increases for increasing CME angular extent and decreasing CME radial expansion speed. Assuming such current sheets facilitate magnetic reconnection, the process of current sheet formation could ultimately lead a single flux rope becoming fragmented into multiple flux ropes. This change in topology has consequences for magnetic clouds as barriers to energetic particle propagation.

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Constant-α force-free magnetic flux rope models have proven to be a valuable first step toward understanding the global context of in situ observations of magnetic clouds. However, cylindrical symmetry is necessarily assumed when using such models, and it is apparent from both observations and modeling that magnetic clouds have highly noncircular cross sections. A number of approaches have been adopted to relax the circular cross section approximation: frequently, the cross-sectional shape is allowed to take an arbitrarily chosen shape (usually elliptical), increasing the number of free parameters that are fit between data and model. While a better “fit” may be achieved in terms of reducing the mean square error between the model and observed magnetic field time series, it is not always clear that this translates to a more accurate reconstruction of the global structure of the magnetic cloud. We develop a new, noncircular cross section flux rope model that is constrained by observations of CMEs/ICMEs and knowledge of the physical processes acting on the magnetic cloud: The magnetic cloud is assumed to initially take the form of a force-free flux rope in the low corona but to be subsequently deformed by a combination of axis-centered self-expansion and heliocentric radial expansion. The resulting analytical solution is validated by fitting to artificial time series produced by numerical MHD simulations of magnetic clouds and shown to accurately reproduce the global structure.

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The properties of planar ice crystals settling horizontally have been investigated using a vertically pointing Doppler lidar. Strong specular reflections were observed from their oriented basal facets, identified by comparison with a second lidar pointing 4° from zenith. Analysis of 17 months of continuous high-resolution observations reveals that these pristine crystals are frequently observed in ice falling from mid-level mixed-phase layer clouds (85% of the time for layers at −15 °C). Detailed analysis of a case study indicates that the crystals are nucleated and grow rapidly within the supercooled layer, then fall out, forming well-defined layers of specular reflection. From the lidar alone the fraction of oriented crystals cannot be quantified, but polarimetric radar measurements confirmed that a substantial fraction of the crystal population was well oriented. As the crystals fall into subsaturated air, specular reflection is observed to switch off as the crystal faces become rounded and lose their faceted structure. Specular reflection in ice falling from supercooled layers colder than −22 °C was also observed, but this was much less pronounced than at warmer temperatures: we suggest that in cold clouds it is the small droplets in the distribution that freeze into plates and produce specular reflection, whilst larger droplets freeze into complex polycrystals. The lidar Doppler measurements show that typical fall speeds for the oriented crystals are ≈ 0.3 m s−1, with a weak temperature correlation; the corresponding Reynolds number is Re ∼ 10, in agreement with light-pillar measurements. Coincident Doppler radar observations show no correlation between the specular enhancement and the eddy dissipation rate, indicating that turbulence does not control crystal orientation in these clouds. Copyright © 2010 Royal Meteorological Society

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The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

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In this paper, data from spaceborne radar, lidar and infrared radiometers on the “A-Train” of satellites are combined in a variational algorithm to retrieve ice cloud properties. The method allows a seamless retrieval between regions where both radar and lidar are sensitive to the regions where one detects the cloud. We first implement a cloud phase identification method, including identification of supercooled water layers using the lidar signal and temperature to discriminate ice from liquid. We also include rigorous calculation of errors assigned in the variational scheme. We estimate the impact of the microphysical assumptions on the algorithm when radiances are not assimilated by evaluating the impact of the change in the area-diameter and the density-diameter relationships in the retrieval of cloud properties. We show that changes to these assumptions affect the radar-only and lidar-only retrieval more than the radar-lidar retrieval, although the lidar-only extinction retrieval is only weakly affected. We also show that making use of the molecular lidar signal beyond the cloud as a constraint on optical depth, when ice clouds are sufficiently thin to allow the lidar signal to penetrate them entirely, improves the retrieved extinction. When infrared radiances are available, they provide an extra constraint and allow the extinction-to-backscatter ratio to vary linearly with height instead of being constant, which improves the vertical distribution of retrieved cloud properties.

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It has been proposed that Earth's climate could be affected by changes in cloudiness caused by variations in the intensity of galactic cosmic rays in the atmosphere. This proposal stems from an observed correlation between cosmic ray intensity and Earth's average cloud cover over the course of one solar cycle. Some scientists question the reliability of the observations, whereas others, who accept them as reliable, suggest that the correlation may be caused by other physical phenomena with decadal periods or by a response to volcanic activity or El Niño. Nevertheless, the observation has raised the intriguing possibility that a cosmic ray–cloud interaction may help explain how a relatively small change in solar output can produce much larger changes in Earth's climate. Physical mechanisms have been proposed to explain how cosmic rays could affect clouds, but they need to be investigated further if the observation is to become more than just another correlation among geophysical variables.

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An assessment of aerosol-cloud interactions (ACI) from ground-based remote sensing under coastal stratiform clouds is presented. The assessment utilizes a long-term, high temporal resolution data set from the Atmospheric Radiation Measurement (ARM) Program deployment at Pt. Reyes, California, United States, in 2005 to provide statistically robust measures of ACI and to characterize the variability of the measures based on variability in environmental conditions and observational approaches. The average ACIN (= dlnNd/dlna, the change in cloud drop number concentration with aerosol concentration) is 0.48, within a physically plausible range of 0–1.0. Values vary between 0.18 and 0.69 with dependence on (1) the assumption of constant cloud liquid water path (LWP), (2) the relative value of cloud LWP, (3) methods for retrieving Nd, (4) aerosol size distribution, (5) updraft velocity, and (6) the scale and resolution of observations. The sensitivity of the local, diurnally averaged radiative forcing to this variability in ACIN values, assuming an aerosol perturbation of 500 c-3 relative to a background concentration of 100 cm-3, ranges betwee-4 and -9 W -2. Further characterization of ACI and its variability is required to reduce uncertainties in global radiative forcing estimates.

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Many clouds important to the Earth’s energy balance contain small amounts of liquid water, yet despite many improvements, large differences in retrievals of their liquid water amount and particle size still must be resolved.

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We outline a method to determine the direction of solar open flux transport that results from the opening of magnetic clouds (MCs) by interchange reconnection at the Sun based solely on in-situ observations. This method uses established findings about i) the locations and magnetic polarities of emerging MC footpoints, ii) the hemispheric dependence of the helicity of MCs, and iii) the occurrence of interchange reconnection at the Sun being signaled by uni-directional suprathermal electrons inside MCs. Combining those observational facts in a statistical analysis of MCs during solar cycle 23 (period 1995 – 2007), we show that the time of disappearance of the northern polar coronal hole (1998 – 1999), permeated by an outward-pointing magnetic field, is associated with a peak in the number of MCs originating from the northern hemisphere and connected to the Sun by outward-pointing magnetic field lines. A similar peak is observed in the number of MCs originating from the southern hemisphere and connected to the Sun by inward-pointing magnetic field lines. This pattern is interpreted as the result of interchange reconnection occurring between MCs and the open field lines of nearby polar coronal holes. This reconnection process closes down polar coronal hole open field lines and transports these open field lines equatorward, thus contributing to the global coronal magnetic field reversal process. These results will be further constrainable with the rising phase of solar cycle 24.

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Using 4 years of radar and lidar observations of layer clouds from the Chilbolton Observatory in the UK, we show that almost all (95%) ice particles formed at temperatures >-20°C appear to originate from supercooled liquid clouds. At colder temperatures, there is a monotonic decline in the fraction of liquid-topped ice clouds: 50% at -27°C, falling to zero at -37°C (where homogeneous freezing of water droplets occurs). This strongly suggests that deposition nucleation plays a relatively minor role in the initiation of ice in mid-level clouds. It also means that the initial growth of the ice particles occurs predominantly within a liquid cloud, a situation which promotes rapid production of precipitation via the Bergeron-Findeison mechanism.

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During April-May 2010 volcanic ash clouds from the Icelandic Eyjafjallajökull volcano reached Europe causing an unprecedented disruption of the EUR/NAT region airspace. Civil aviation authorities banned all flight operations because of the threat posed by volcanic ash to modern turbine aircraft. New quantitative airborne ash mass concentration thresholds, still under discussion, were adopted for discerning regions contaminated by ash. This has implications for ash dispersal models routinely used to forecast the evolution of ash clouds. In this new context, quantitative model validation and assessment of the accuracies of current state-of-the-art models is of paramount importance. The passage of volcanic ash clouds over central Europe, a territory hosting a dense network of meteorological and air quality observatories, generated a quantity of observations unusual for volcanic clouds. From the ground, the cloud was observed by aerosol lidars, lidar ceilometers, sun photometers, other remote-sensing instru- ments and in-situ collectors. From the air, sondes and multiple aircraft measurements also took extremely valuable in-situ and remote-sensing measurements. These measurements constitute an excellent database for model validation. Here we validate the FALL3D ash dispersal model by comparing model results with ground and airplane-based measurements obtained during the initial 14e23 April 2010 Eyjafjallajökull explosive phase. We run the model at high spatial resolution using as input hourly- averaged observed heights of the eruption column and the total grain size distribution reconstructed from field observations. Model results are then compared against remote ground-based and in-situ aircraft-based measurements, including lidar ceilometers from the German Meteorological Service, aerosol lidars and sun photometers from EARLINET and AERONET networks, and flight missions of the German DLR Falcon aircraft. We find good quantitative agreement, with an error similar to the spread in the observations (however depending on the method used to estimate mass eruption rate) for both airborne and ground mass concentration. Such verification results help us understand and constrain the accuracy and reliability of ash transport models and it is of enormous relevance for designing future operational mitigation strategies at Volcanic Ash Advisory Centers.