174 resultados para AXISYMMETRICAL CLOUD CORES


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Increases in cloud optical depth and liquid water path (LWP) are robust features of global warming model simulations in high latitudes, yielding a negative shortwave cloud feedback, but the mechanisms are still uncertain. We assess the importance of microphysical processes for the negative optical depth feedback by perturbing temperature in the microphysics schemes of two aquaplanet models, both of which have separate prognostic equations for liquid water and ice. We find that most of the LWP increase with warming is caused by a suppression of ice microphysical processes in mixed-phase clouds, resulting in reduced conversion efficiencies of liquid water to ice and precipitation. Perturbing the temperature-dependent phase partitioning of convective condensate also yields a small LWP increase. Together, the perturbations in large-scale microphysics and convective condensate partitioning explain more than two-thirds of the LWP response relative to a reference case with increased SSTs, and capture all of the vertical structure of the liquid water response. In support of these findings, we show the existence of a very robust positive relationship between monthly-mean LWP and temperature in CMIP5 models and observations in mixed-phase cloud regions only. In models, the historical LWP sensitivity to temperature is a good predictor of the forced global warming response poleward of about 45°, although models appear to overestimate the LWP response to warming compared to observations. We conclude that in climate models, the suppression of ice-phase microphysical processes that deplete cloud liquid water is a key driver of the LWP increase with warming and of the associated negative shortwave cloud feedback.

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Substantial biases in shortwave cloud forcing (SWCF) of up to ±30 W m−2are found in the midlatitudes of the Southern Hemisphere in the historical simulations of 34 CMIP5 coupled general circulation models. The SWCF biases are shown to induce surface temperature anomalies localized in the midlatitudes, and are significantly correlated with the mean latitude of the eddy-driven jet, with a negative SWCF bias corresponding to an equatorward jet latitude bias. Aquaplanet model experiments are performed to demonstrate that the jet latitude biases are primarily induced by the midlatitude SWCF anomalies, such that the jet moves toward (away from) regions of enhanced (reduced) temperature gradients. The results underline the necessity of accurately representing cloud radiative forcings in state-of-the-art coupled models.

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Increasing optical depth poleward of 45° is a robust response to warming in global climate models. Much of this cloud optical depth increase has been hypothesized to be due to transitions from ice-dominated to liquid-dominated mixed-phase cloud. In this study, the importance of liquid-ice partitioning for the optical depth feedback is quantified for 19 Coupled Model Intercomparison Project Phase 5 models. All models show a monotonic partitioning of ice and liquid as a function of temperature, but the temperature at which ice and liquid are equally mixed (the glaciation temperature) varies by as much as 40 K across models. Models that have a higher glaciation temperature are found to have a smaller climatological liquid water path (LWP) and condensed water path and experience a larger increase in LWP as the climate warms. The ice-liquid partitioning curve of each model may be used to calculate the response of LWP to warming. It is found that the repartitioning between ice and liquid in a warming climate contributes at least 20% to 80% of the increase in LWP as the climate warms, depending on model. Intermodel differences in the climatological partitioning between ice and liquid are estimated to contribute at least 20% to the intermodel spread in the high-latitude LWP response in the mixed-phase region poleward of 45°S. It is hypothesized that a more thorough evaluation and constraint of global climate model mixed-phase cloud parameterizations and validation of the total condensate and ice-liquid apportionment against observations will yield a substantial reduction in model uncertainty in the high-latitude cloud response to warming.

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The simulated annealing approach to crystal structure determination from powder diffraction data, as implemented in the DASH program, is readily amenable to parallelization at the individual run level. Very large scale increases in speed of execution can be achieved by distributing individual DASH runs over a network of computers. The CDASH program delivers this by using scalable on-demand computing clusters built on the Amazon Elastic Compute Cloud service. By way of example, a 360 vCPU cluster returned the crystal structure of racemic ornidazole (Z0 = 3, 30 degrees of freedom) ca 40 times faster than a typical modern quad-core desktop CPU. Whilst used here specifically for DASH, this approach is of general applicability to other packages that are amenable to coarse-grained parallelism strategies.

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A data insertion method, where a dispersion model is initialized from ash properties derived from a series of satellite observations, is used to model the 8 May 2010 Eyjafjallajökull volcanic ash cloud which extended from Iceland to northern Spain. We also briefly discuss the application of this method to the April 2010 phase of the Eyjafjallajökull eruption and the May 2011 Grímsvötn eruption. An advantage of this method is that very little knowledge about the eruption itself is required because some of the usual eruption source parameters are not used. The method may therefore be useful for remote volcanoes where good satellite observations of the erupted material are available, but little is known about the properties of the actual eruption. It does, however, have a number of limitations related to the quality and availability of the observations. We demonstrate that, using certain configurations, the data insertion method is able to capture the structure of a thin filament of ash extending over northern Spain that is not fully captured by other modeling methods. It also verifies well against the satellite observations according to the quantitative object-based quality metric, SAL—structure, amplitude, location, and the spatial coverage metric, Figure of Merit in Space.

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We present new inferences about cloud vertical structures from multidirectionnal measurements in the oxygen A-band. The analysis of collocated data provided by instruments onboard satellite platforms within the A-Train, as well as simulations have shown that for monolayered clouds, the cloud oxygen pressure PO2PO2 derived from the POLDER3 instrument was sensitive to the cloud vertical structure in two ways: First, PO2PO2 is actually close to the pressure of the geometrical middle of cloud and we propose a method to correct it to get the cloud top pressure (CTP), and then to obtain the cloud geometrical extent. Second, for the liquid water clouds, the angular standard deviation σPO2σPO2 of PO2PO2 is correlated with the geometrical extent of cloud layers, which makes possible a second estimation of the cloud geometrical thickness. The determination of the vertical location of cloud layers from passive measurements, eventually completed from other observations, would be useful in many applications for which cloud macrophysical properties are needed

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The vertical distribution of cloud cover has a significant impact on a large number of meteorological and climatic processes. Cloud top altitude and cloud geometrical thickness are then essential. Previous studies established the possibility of retrieving those parameters from multi-angular oxygen A-band measurements. Here we perform a study and comparison of the performances of future instruments. The 3MI (Multi-angle, Multi-channel and Multi-polarization Imager) instrument developed by EUMETSAT, which is an extension of the POLDER/PARASOL instrument, and MSPI (Multi-angles Spectro-Polarimetric Imager) develoloped by NASA's Jet Propulsion Laboratory will measure total and polarized light reflected by the Earth's atmosphere–surface system in several spectral bands (from UV to SWIR) and several viewing geometries. Those instruments should provide opportunities to observe the links between the cloud structures and the anisotropy of the reflected solar radiation into space. Specific algorithms will need be developed in order to take advantage of the new capabilities of this instrument. However, prior to this effort, we need to understand, through a theoretical Shannon information content analysis, the limits and advantages of these new instruments for retrieving liquid and ice cloud properties, and especially, in this study, the amount of information coming from the A-Band channel on the cloud top altitude (CTOP) and geometrical thickness (CGT). We compare the information content of 3MI A-Band in two configurations and that of MSPI. Quantitative information content estimates show that the retrieval of CTOP with a high accuracy is possible in almost all cases investigated. The retrieval of CGT seems less easy but possible for optically thick clouds above a black surface, at least when CGT > 1–2 km.

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Aerosol-cloud interactions have the potential to modify many different cloud properties. There is significant uncertainty in the strength of these aerosol-cloud interactions in analyses of observational data, partly due to the difficulty in separating aerosol effects on clouds from correlations generated by local meteorology. The relationship between aerosol and cloud fraction (CF) is particularly important to determine, due to the strong correlation of CF to other cloud properties and its large impact on radiation. It has also been one of the hardest to quantify from satellites due to the strong meteorological covariations involved. This work presents a new method to analyze the relationship between aerosol optical depth (AOD) and CF. By including information about the cloud droplet number concentration (CDNC), the impact of the meteorological covariations is significantly reduced. This method shows that much of the AOD-CF correlation is explained by relationships other than that mediated by CDNC. By accounting for these, the strength of the global mean AOD-CF relationship is reduced by around 80%. This suggests that the majority of the AOD-CF relationship is due to meteorological covariations, especially in the shallow cumulus regime. Requiring CDNC to mediate the AOD-CF relationship implies an effective anthropogenic radiative forcing from an aerosol influence on liquid CF of −0.48 W m−2 (−0.1 to −0.64 W m−2), although some uncertainty remains due to possible biases in the CDNC retrievals in broken cloud scenes.

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Exploiting the observed robust relationships between temperature and optical depth in extratropical clouds, we calculate the shortwave cloud feedback from historical data, by regressing observed and modeled cloud property histograms onto local temperature in middle to high southern latitudes. In this region, all CMIP5 models and observational data sets predict a negative cloud feedback, mainly driven by optical thickening. Between 45° and 60°S, the mean observed shortwave feedback (−0.91 ± 0.82 W m−2 K−1, relative to local rather than global mean warming) is very close to the multimodel mean feedback in RCP8.5 (−0.98 W m−2 K−1), despite differences in the meridional structure. In models, historical temperature-cloud property relationships reliably predict the forced RCP8.5 response. Because simple theory predicts this optical thickening with warming, and cloud amount changes are relatively small, we conclude that the shortwave cloud feedback is very likely negative in the real world at middle to high latitudes.