scholarly journals Particle properties and water content of noctilucent clouds and their interannual variation

2008 ◽  
Vol 113 (D6) ◽  
Author(s):  
G. Baumgarten ◽  
J. Fiedler ◽  
F.-J. Lübken ◽  
G. von Cossart
Keyword(s):  
Water Content ◽  
Interannual Variation ◽  
Noctilucent Clouds ◽  
Particle Properties

scholarly journals On microphysical processes of noctilucent clouds (NLC): observations and modeling of mean and width of the particle size-distribution

2010 ◽  
Vol 10 (2) ◽  
pp. 3605-3625
Author(s):  
G. Baumgarten ◽  
J. Fiedler ◽  
M. Rapp
Keyword(s):  
Particle Size ◽  
Linear Relationship ◽  
Size Distribution ◽  
Eddy Diffusion ◽  
Particle Sizes ◽  
Noctilucent Clouds ◽  
Atmospheric Variability ◽  
Distribution Width ◽  
Particle Properties ◽  
Microphysical Processes

Abstract. Noctilucent clouds (NLC) in the polar summer mesopause region have been observed in Norway (69° N, 16° E) between 1998 and 2009 by 3-color lidar technique. Assuming a mono-modal Gaussian size distribution we deduce mean and width of the particle sizes throughout the clouds. We observe a quasi linear relationship between distribution width and mean of the particle size at the top of the clouds and a deviation from this behavior for particle sizes larger than 40 nm, most often in the lower part of the layer. The vertically integrated particle properties show that 65% of the data follows the linear relationship with a slope of 0.42±0.02. For the vertically resolved particle properties (Δz=0.15 km) the slope is smaller and only 0.39±0.03. We compare our observations to microphysical modeling of noctilucent clouds and find that the distribution width depends on turbulence, the time that turbulence can act (cloud age), and the sampling volume/time (atmospheric variability). The model results nicely reproduce the measurements and show that the observed slope can be explained by eddy diffusion profiles as observed from rocket measurements.

scholarly journals A ubiquitous ice size bias in simulations of tropical deep convection

2017 ◽  
Author(s):  
McKenna W. Stanford ◽  
Adam Varble ◽  
Ed Zipser ◽  
J. Walter Strapp ◽  
Delphine Leroy ◽  
...  
Keyword(s):  
Water Content ◽  
Deep Convection ◽  
Particle Sizes ◽  
Size Distributions ◽  
Particle Properties ◽  
Ice Water Content ◽  
High Bias ◽  
Microphysical Processes ◽  
Bin Microphysics ◽  
Ice Water

Abstract. The High Altitude Ice Crystals – High Ice Water Content (HAIC-HIWC) joint field campaign produced aircraft retrievals of total condensed water content (TWC), hydrometeor particle size distributions (PSDs), and vertical velocity (w) in high ice water content regions of mature and decaying tropical mesoscale convective systems (MCSs). The resulting dataset is used here to explore causes of the commonly documented high bias in radar reflectivity within cloud-resolving simulations of deep convection. This bias has been linked to overly strong simulated convective updrafts lofting excessive condensate mass but is also modulated by parameterizations of hydrometeor size distributions, single particle properties, species separation, and microphysical processes. Observations are compared with three Weather Research and Forecasting model simulations of an observed MCS using differing microphysics while controlling for w, TWC, and temperature. Two bulk microphysics schemes (Thompson and Morrison) and one bin microphysics scheme (Fast Spectral Bin Microphysics) are compared. For temperatures between −10 °C and −40 °C and TWC > 1 g m−3 inside updrafts, all microphysics schemes produce median mass diameters (MMDs) that are generally larger than observed, and the precipitating ice species that controls this size bias varies by scheme, temperature, and w. Despite a much greater number of samples, all simulations fail to reproduce observed high TWC conditions (> 2 g m−3) between −20 °C and −40 °C in which only a small fraction of condensate mass is found in relatively large particle sizes greater than 1 mm in diameter. Although more mass is distributed to relatively large particle sizes relative to observed across all schemes when controlling for temperature, w, and TWC, differences with observations for a given particle size vary greatly between schemes. As a result, this bias is hypothesized to partly result from errors in parameterized hydrometeor PSD and single particle properties, but because it is present in all schemes, it may also partly result from errors in parameterized microphysical processes present in all schemes. Because of these ubiquitous ice size biases, microphysical parameterizations inherently produce a high bias in convective reflectivity for a wide range of temperatures, vertical velocities, and TWCs.

scholarly journals On microphysical processes of noctilucent clouds (NLC): observations and modeling of mean and width of the particle size-distribution

2010 ◽  
Vol 10 (14) ◽  
pp. 6661-6668 ◽  
Author(s):  
G. Baumgarten ◽  
J. Fiedler ◽  
M. Rapp
Keyword(s):  
Particle Size ◽  
Linear Relationship ◽  
Size Distribution ◽  
Eddy Diffusion ◽  
Particle Sizes ◽  
Noctilucent Clouds ◽  
Atmospheric Variability ◽  
Distribution Width ◽  
Particle Properties ◽  
Microphysical Processes

Abstract. Noctilucent clouds (NLC) in the polar summer mesopause region have been observed in Norway (69° N, 16° E) between 1998 and 2009 by 3-color lidar technique. Assuming a mono-modal Gaussian size distribution we deduce mean and width of the particle sizes throughout the clouds. We observe a quasi linear relationship between distribution width and mean of the particle size at the top of the clouds and a deviation from this behavior for particle sizes larger than 40 nm, most often in the lower part of the layer. The vertically integrated particle properties show that 65% of the data follows the linear relationship with a slope of 0.42±0.02 for mean particle sizes up to 40 nm. For the vertically resolved particle properties (Δz = 0.15 km) the slope is comparable and about 0.39±0.03. For particles larger than 40 nm the distribution width becomes nearly independent of particle size and even decreases in the lower part of the layer. We compare our observations to microphysical modeling of noctilucent clouds and find that the distribution width depends on turbulence, the time that turbulence can act (cloud age), and the sampling volume/time (atmospheric variability). The model results nicely reproduce the measurements and show that the observed slope can be explained by eddy diffusion profiles as observed from rocket measurements.

scholarly journals A ubiquitous ice size bias in simulations of tropical deep convection

2017 ◽  
Vol 17 (15) ◽  
pp. 9599-9621 ◽  
Author(s):  
McKenna W. Stanford ◽  
Adam Varble ◽  
Ed Zipser ◽  
J. Walter Strapp ◽  
Delphine Leroy ◽  
...  
Keyword(s):  
Water Content ◽  
Deep Convection ◽  
Particle Sizes ◽  
Size Distributions ◽  
Particle Properties ◽  
Ice Water Content ◽  
High Bias ◽  
Microphysical Processes ◽  
Bin Microphysics ◽  
Ice Water

Abstract. The High Altitude Ice Crystals – High Ice Water Content (HAIC-HIWC) joint field campaign produced aircraft retrievals of total condensed water content (TWC), hydrometeor particle size distributions (PSDs), and vertical velocity (w) in high ice water content regions of mature and decaying tropical mesoscale convective systems (MCSs). The resulting dataset is used here to explore causes of the commonly documented high bias in radar reflectivity within cloud-resolving simulations of deep convection. This bias has been linked to overly strong simulated convective updrafts lofting excessive condensate mass but is also modulated by parameterizations of hydrometeor size distributions, single particle properties, species separation, and microphysical processes. Observations are compared with three Weather Research and Forecasting model simulations of an observed MCS using different microphysics parameterizations while controlling for w, TWC, and temperature. Two popular bulk microphysics schemes (Thompson and Morrison) and one bin microphysics scheme (fast spectral bin microphysics) are compared. For temperatures between −10 and −40 °C and TWC  >  1 g m−3, all microphysics schemes produce median mass diameters (MMDs) that are generally larger than observed, and the precipitating ice species that controls this size bias varies by scheme, temperature, and w. Despite a much greater number of samples, all simulations fail to reproduce observed high-TWC conditions ( >  2 g m−3) between −20 and −40 °C in which only a small fraction of condensate mass is found in relatively large particle sizes greater than 1 mm in diameter. Although more mass is distributed to large particle sizes relative to those observed across all schemes when controlling for temperature, w, and TWC, differences with observations are significantly variable between the schemes tested. As a result, this bias is hypothesized to partly result from errors in parameterized hydrometeor PSD and single particle properties, but because it is present in all schemes, it may also partly result from errors in parameterized microphysical processes present in all schemes. Because of these ubiquitous ice size biases, the frequently used microphysical parameterizations evaluated in this study inherently produce a high bias in convective reflectivity for a wide range of temperatures, vertical velocities, and TWCs.

scholarly journals Evaluating CloudSat ice water content retrievals using a cloud-resolving model: Sensitivities to frozen particle properties

2008 ◽  
Vol 113 ◽  
Author(s):  
Christopher P. Woods ◽  
Duane E. Waliser ◽  
Jui-Lin Li ◽  
Richard T. Austin ◽  
Graeme L. Stephens ◽  
...  
Keyword(s):  
Water Content ◽  
Particle Properties ◽  
Cloud Resolving Model ◽  
Ice Water Content ◽  
Ice Water

Characterization of frozen hydrated biological specimens by low-loss EELS

1992 ◽  
Vol 50 (2) ◽  
pp. 1572-1573
Author(s):  
Songquan Sun ◽  
Richard D. Leapman
Keyword(s):  
Water Content ◽  
Direct Method ◽  
Internal Standard ◽  
Dry Weight ◽  
Dark Field ◽  
Protein Solutions ◽  
Subcellular Compartment ◽  
Differential Shrinkage ◽  
Electron Energy Loss

Analyses of ultrathin cryosections are generally performed after freeze-drying because the presence of water renders the specimens highly susceptible to radiation damage. The water content of a subcellular compartment is an important quantity that must be known, for example, to convert the dry weight concentrations of ions to the physiologically more relevant molar concentrations. Water content can be determined indirectly from dark-field mass measurements provided that there is no differential shrinkage between compartments and that there exists a suitable internal standard. The potential advantage of a more direct method for measuring water has led us to explore the use of electron energy loss spectroscopy (EELS) for characterizing biological specimens in their frozen hydrated state.We have obtained preliminary EELS measurements from pure amorphous ice and from cryosectioned frozen protein solutions. The specimens were cryotransfered into a VG-HB501 field-emission STEM equipped with a 666 Gatan parallel-detection spectrometer and analyzed at approximately −160 C.

STEM measurement of subcellular water distributions

1993 ◽  
Vol 51 ◽  
pp. 568-569
Author(s):  
R.D. Leapman ◽  
S.Q. Sun ◽  
S-L. Shi ◽  
R.A. Buchanan ◽  
S.B. Andrews
Keyword(s):  
Water Content ◽  
Internal Standard ◽  
Dry Weight ◽  
Dry Mass ◽  
Scanning Transmission Electron Microscope ◽  
Dark Field ◽  
Bulk Water ◽  
Inelastic Electron ◽  
Scanning Transmission ◽  
Annular Dark Field

Recent advances in rapid-freezing and cryosectioning techniques coupled with use of the quantitative signals available in the scanning transmission electron microscope (STEM) can provide us with new methods for determining the water distributions of subcellular compartments. The water content is an important physiological quantity that reflects how fluid and electrolytes are regulated in the cell; it is also required to convert dry weight concentrations of ions obtained from x-ray microanalysis into the more relevant molar ionic concentrations. Here we compare the information about water concentrations from both elastic (annular dark-field) and inelastic (electron energy loss) scattering measurements.In order to utilize the elastic signal it is first necessary to increase contrast by removing the water from the cryosection. After dehydration the tissue can be digitally imaged under low-dose conditions, in the same way that STEM mass mapping of macromolecules is performed. The resulting pixel intensities are then converted into dry mass fractions by using an internal standard, e.g., the mean intensity of the whole image may be taken as representative of the bulk water content of the tissue.

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