scholarly journals Evolution of ice crystal regions on the microscale based on in situ observations

2013 ◽  
Vol 40 (13) ◽  
pp. 3473-3478 ◽  
Author(s):  
Minghui Diao ◽  
Mark A. Zondlo ◽  
Andrew J. Heymsfield ◽  
Stuart P. Beaton ◽  
David C. Rogers
Keyword(s):  
Ice Crystal ◽  
In Situ Observations

Exploring the Diabatic Role of Ice Microphysical Processes in Two North Atlantic Summer Cyclones

2016 ◽  
Vol 144 (4) ◽  
pp. 1249-1272 ◽  
Author(s):  
C. Dearden ◽  
G. Vaughan ◽  
T. Tsai ◽  
J.-P. Chen
Keyword(s):  
Crystal Habit ◽  
Ice Crystal ◽  
Heating And Cooling ◽  
First Case ◽  
Storm Evolution ◽  
In Situ Observations ◽  
Microphysical Processes ◽  
Ice Production ◽  
The Impact

Abstract Numerical simulations are performed with the Weather Research and Forecasting Model to elucidate the diabatic effects of ice phase microphysical processes on the dynamics of two slow-moving summer cyclones that affected the United Kingdom during the summer of 2012. The first case is representative of a typical midlatitude storm for the time of year, while the second case is unusually deep. Sensitivity tests are performed with 5-km horizontal grid spacing and at lead times between 1 and 2 days using three different microphysics schemes, one of which is a new scheme whose development was informed by the latest in situ observations of midlatitude weather systems. The effects of latent heating and cooling associated with deposition growth, sublimation, and melting of ice are assessed in terms of the impact on both the synoptic scale and the frontal scale. The results show that, of these diabatic processes, deposition growth was the most important in both cases, affecting the depth and position of each of the low pressure systems and influencing the spatial distribution of the frontal precipitation. Cooling associated with sublimation and melting also played a role in determining the cyclone depth, but mainly in the more intense cyclone case. The effects of ice crystal habit and secondary ice production are also explored in the simulations, based on insight from in situ observations. However in these two cases, the ability to predict changes in crystal habit did not significantly impact the storm evolution, and the authors found no obvious need to parameterize secondary ice crystal production at the model resolutions considered.

LES of Contrails With Ice Habit Treatment Using the Fickian-Distribution Model

2014 ◽  
Author(s):  
Aniket R. Inamdar ◽  
Sanjiva K. Lele ◽  
Mark Z. Jacobson
Keyword(s):  
Crystal Growth ◽  
Large Eddy Simulation ◽  
Laboratory Data ◽  
Distribution Model ◽  
Ice Crystal ◽  
Ambient Temperatures ◽  
Eddy Simulation ◽  
Large Eddy ◽  
In Situ Observations

This study uses a Fickian-Distribution parameterization [Chen & Lamb, 1994] to model the effects of ice habits on contrail formation within a large eddy simulation (LES). Box model cases were first performed at various ambient temperatures and relative humidities over ice (RHi) and results compared with available laboratory data of ice crystal growth and habit distribution [Bailey & Hallett, 2004]. The model was then used in a full 3-D LES of contrails and results were compared with in-situ observations [Febvre et. al., 2009]. Comparisons are also made with results from simulations that used a probabilistic ice habit model [Inamdar et. al., 2013].

A Comprehensive Habit Diagram for Atmospheric Ice Crystals: Confirmation from the Laboratory, AIRS II, and Other Field Studies

2009 ◽  
Vol 66 (9) ◽  
pp. 2888-2899 ◽  
Author(s):  
Matthew P. Bailey ◽  
John Hallett
Keyword(s):  
Field Studies ◽  
Crystal Habit ◽  
Ice Crystal ◽  
Comprehensive Description ◽  
Cloud Particle ◽  
In Situ Observations ◽  
Ice Crystal Habits ◽  
Habit Modification ◽  
Recent Laboratory

Abstract Recent laboratory experiments and in situ observations have produced results in broad agreement with respect to ice crystal habits in the atmosphere. These studies reveal that the ice crystal habit at −20°C is platelike, extending to −40°C, and not columnar as indicated in many habit diagrams found in atmospheric science journals and texts. These diagrams were typically derived decades ago from laboratory studies, some with inherent habit bias, or from combinations of laboratory and in situ observations at the ground, observations that often did not account for habit modification by precipitation from overlying clouds of varying temperatures. Habit predictions from these diagrams often disagreed with in situ observations at temperatures below −20°C. More recent laboratory and in situ studies have achieved a consensus on atmospheric ice crystal habits that differs from the traditional habit diagrams. These newer results can now be combined to give a comprehensive description of ice crystal habits for the atmosphere as a function of temperature and ice supersaturation for temperatures from 0° to −70°C, a description dominated by irregular and imperfect crystals. Cloud particle imager (CPI) habit observations made during the Second Alliance Icing Research Study (AIRS II) and elsewhere corroborate this comprehensive habit description, and a new habit diagram is derived from these results.

scholarly journals In-situ observations of young contrails – overview and selected results from the CONCERT campaign

2010 ◽  
Vol 10 (5) ◽  
pp. 12713-12763 ◽  
Author(s):  
C. Voigt ◽  
U. Schumann ◽  
T. Jurkat ◽  
D. Schäuble ◽  
H. Schlager ◽  
...  
Keyword(s):  
Western Europe ◽  
Trace Gas ◽  
Ice Crystal ◽  
Particle Properties ◽  
Mixing Ratios ◽  
Distribution Shape ◽  
Research Aircraft ◽  
In Situ Observations ◽  
Halogen Species

Abstract. Lineshaped contrails were detected with the research aircraft Falcon during the CONCERT – CONtrail and Cirrus ExpeRimenT – campaign in October/November 2008. Thereby the Falcon was equipped with a set of instruments to measure particle properties such as the particle size distribution, shape, extinction, chemical composition as well as trace gas concentrations of sulfur dioxide (SO2), reactive nitrogen and halogen species (NO, NOy, HNO3, HONO, HCl), ozone (O3) and carbon monoxide (CO). During 12 mission flights over Western Europe numerous contrails and cirrus clouds were probed at altitudes between 8.5 and 11.6 km and temperatures above 213 K. 22 contrails from 11 different aircraft were observed near and below ice saturation. The observed NO mixing ratios, ice crystal and soot number densities are compared to a process based contrail model. Further we investigate in detail the contrail from a CRJ-2 aircraft detected on 19 November 2008 in 10.1 km altitude. The contrail with an age of 1 to 2 min had average ice crystal concentrations of 128 cm−3 in the size range 0.4

In situ observations of electromigration induced void behavior

1995 ◽  
Vol 53 ◽  
pp. 244-245
Author(s):  
T. Marieb ◽  
J. C. Bravman ◽  
P. Flinn ◽  
D. Gardner ◽  
M. Madden
Keyword(s):  
Electron Microscopy ◽  
Void Nucleation ◽  
Plan View ◽  
Transmission Electron ◽  
Nucleation Sites ◽  
Microelectronics Industry ◽  
In Situ Observations ◽  
Backscatter Electron Detector ◽  
Voltage Scanning

Electromigration and stress voiding have been active areas of research in the microelectronics industry for many years. While accelerated testing of these phenomena has been performed for the last 25 years[1-2], only recently has the introduction of high voltage scanning electron microscopy (HVSEM) made possible in situ testing of realistic, passivated, full thickness samples at high resolution.With a combination of in situ HVSEM and post-testing transmission electron microscopy (TEM) , electromigration void nucleation sites in both normal polycrystalline and near-bamboo pure Al were investigated. The effect of the microstructure of the lines on the void motion was also studied.The HVSEM used was a slightly modified JEOL 1200 EX II scanning TEM with a backscatter electron detector placed above the sample[3]. To observe electromigration in situ the sample was heated and the line had current supplied to it to accelerate the voiding process. After testing lines were prepared for TEM by employing the plan-view wedge technique [6].

scholarly journals In situ observations of coral spawning and spawn slick at Lankayan Island, Sabah, Malaysia

2021 ◽  
Vol 51 (1) ◽  
Author(s):  
Sze Hoon Gan ◽  
Zarinah Waheed ◽  
Fung Chen Chung ◽  
Davies Austin Spiji ◽  
Leony Sikim ◽  
...  
Keyword(s):  
Coral Spawning ◽  
In Situ Observations

scholarly journals Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere

2021 ◽  
Vol 13 (7) ◽  
pp. 1250
Author(s):  
Yanxing Hu ◽  
Tao Che ◽  
Liyun Dai ◽  
Lin Xiao
Keyword(s):  
Machine Learning ◽  
Northern Hemisphere ◽  
Snow Depth ◽  
Learning Algorithm ◽  
Random Forest Regression ◽  
Machine Learning Methods ◽  
Long Time ◽  
In Situ Observations ◽  
Input Variables

In this study, a machine learning algorithm was introduced to fuse gridded snow depth datasets. The input variables of the machine learning method included geolocation (latitude and longitude), topographic data (elevation), gridded snow depth datasets and in situ observations. A total of 29,565 in situ observations were used to train and optimize the machine learning algorithm. A total of five gridded snow depth datasets—Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth, Global Snow Monitoring for Climate Research (GlobSnow) snow depth, Long time series of daily snow depth over the Northern Hemisphere (NHSD) snow depth, ERA-Interim snow depth and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) snow depth—were used as input variables. The first three snow depth datasets are retrieved from passive microwave brightness temperature or assimilation with in situ observations, while the last two are snow depth datasets obtained from meteorological reanalysis data with a land surface model and data assimilation system. Then, three machine learning methods, i.e., Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Random Forest Regression (RFR), were used to produce a fused snow depth dataset from 2002 to 2004. The RFR model performed best and was thus used to produce a new snow depth product from the fusion of the five snow depth datasets and auxiliary data over the Northern Hemisphere from 2002 to 2011. The fused snow-depth product was verified at five well-known snow observation sites. The R2 of Sodankylä, Old Aspen, and Reynolds Mountains East were 0.88, 0.69, and 0.63, respectively. At the Swamp Angel Study Plot and Weissfluhjoch observation sites, which have an average snow depth exceeding 200 cm, the fused snow depth did not perform well. The spatial patterns of the average snow depth were analyzed seasonally, and the average snow depths of autumn, winter, and spring were 5.7, 25.8, and 21.5 cm, respectively. In the future, random forest regression will be used to produce a long time series of a fused snow depth dataset over the Northern Hemisphere or other specific regions.

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