scholarly journals Statistical analysis of contrail to cirrus evolution during the Contrail and Cirrus Experiment (CONCERT)

2018 ◽  
Vol 18 (13) ◽  
pp. 9803-9822 ◽  
Author(s):  
Aurélien Chauvigné ◽  
Olivier Jourdan ◽  
Alfons Schwarzenboeck ◽  
Christophe Gourbeyre ◽  
Jean François Gayet ◽  
...  
Keyword(s):  
Principal Component ◽  
Optical Measurements ◽  
Atmospheric Environment ◽  
Growth Stages ◽  
Atmospheric Conditions ◽  
Scattering Coefficients ◽  
Ice Cloud ◽  
Cloud Properties ◽  
Substantial Progress ◽  
Macrophysical Properties

Abstract. Air traffic affects cloudiness, and thus climate, by emitting exhaust gases and particles. The study of the evolution of contrail properties is very challenging due to the complex interplay of vortex dynamics and the atmospheric environment (e.g. temperature, supersaturation). Despite substantial progress in recent years, the optical, microphysical, and macrophysical properties of contrails and ambient cirrus during contrail formation and subsequent ageing are still subject to large uncertainties due to instrumental and observational limitations and the large number of variables influencing the contrail life cycle. In this study, various contrail cases corresponding to different aircraft types and atmospheric conditions are investigated using a statistical method based on the in situ optical measurements performed during the Contrail and Cirrus Experiments (CONCERT) campaigns 2008 and 2011. The two aircraft campaigns encompass more than 17 aircraft contrail cases. A principal component analysis (PCA) of the angular scattering coefficients measured by the polar nephelometer is implemented. The goal is to classify the sampled ice cloud measurements in several clusters representative of different contrail development stages (primary wake, young contrail, aged contrail, and cirrus). Extinction and asymmetry coefficients, nitrogen oxide concentrations, and relative humidity with respect to ice and particle size distributions are analysed for each cluster to characterize the evolution of ice cloud properties during the contrail to cirrus evolution. The PCA demonstrates that contrail optical properties are well suited to identify and discriminate between the different contrail growth stages and to characterize the evolution of contrail properties.

scholarly journals Statistical Analysis of Contrail to Cirrus Evolution during the Contrail and Cirrus Experiments (CONCERT)

2017 ◽  
Author(s):  
Aurélien Chauvigné ◽  
Olivier Jourdan ◽  
Alfons Schwarzenboeck ◽  
Christophe Gourbeyre ◽  
Christiane Voigt ◽  
...  
Keyword(s):  
Traffic Control ◽  
Principal Component ◽  
Air Traffic ◽  
Optical Measurements ◽  
Atmospheric Environment ◽  
Growth Stages ◽  
Atmospheric Conditions ◽  
Scattering Coefficients ◽  
Ice Cloud

Abstract. Air traffic affects the cloudiness, and thus the climate, by emitting exhaust gases and particles. The study of the evolution of contrail properties is very challenging due to the complex interplay of vortex dynamics and atmospheric environment (e.g. temperature, supersaturation). Despite substantial progress in recent years, the optical, microphysical, and macrophysical properties of contrails and ambient cirrus during contrail formation and subsequent ageing are still subject to large uncertainties due to instrumental and observational limitations and the large number of variables influencing the contrail life cycle. In this study, various contrail cases corresponding to different aircraft types and atmospheric conditions are investigated using a statistical method based on the in situ optical measurements performed during the CONCERT campaigns 2008 and 2011. These two aircraft campaigns encompass more than 17 aircraft contrail cases. A Principal Component Analysis (PCA) of the angular scattering coefficients measured by the Polar Nephelometer has been implemented in order to classify the sampled ice cloud measurements in 6 clusters representative of different development stages of the contrails (primary wake, young contrail, contrail-cirrus and natural cirrus). Based on the information derived from air traffic control, extinction coefficients, asymmetry coefficients, nitrogen oxide concentrations, relative humidity with respect to ice (RHI) and particle size distributions are analyzed for each cluster to provide a characterization of the evolution of ice-cloud properties during the contrail to cirrus evolution. The PCA demonstrates that contrail optical properties are well suited to identify and discriminate the different contrail growth stages and to provide an independent method for the characterization of the evolution of contrail properties.

scholarly journals Growth of nucleation mode particles in the summertime Arctic: a case study

2016 ◽  
Vol 16 (12) ◽  
pp. 7663-7679 ◽  
Author(s):  
Megan D. Willis ◽  
Julia Burkart ◽  
Jennie L. Thomas ◽  
Franziska Köllner ◽  
Johannes Schneider ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Methanesulfonic Acid ◽  
Lower Troposphere ◽  
Atmospheric Conditions ◽  
Aerosol Formation ◽  
Radiative Balance ◽  
Nucleation Mode ◽  
Cloud Properties ◽  
Marine Influence

Abstract. The summertime Arctic lower troposphere is a relatively pristine background aerosol environment dominated by nucleation and Aitken mode particles. Understanding the mechanisms that control the formation and growth of aerosol is crucial for our ability to predict cloud properties and therefore radiative balance and climate. We present an analysis of an aerosol growth event observed in the Canadian Arctic Archipelago during summer as part of the NETCARE project. Under stable and clean atmospheric conditions, with low inversion heights, carbon monoxide less than 80 ppbv, and black carbon less than 5 ng m−3, we observe growth of small particles,  <  20 nm in diameter, into sizes above 50 nm. Aerosol growth was correlated with the presence of organic species, trimethylamine, and methanesulfonic acid (MSA) in particles ∼ 80 nm and larger, where the organics are similar to those previously observed in marine settings. MSA-to-sulfate ratios as high as 0.15 were observed during aerosol growth, suggesting an important marine influence. The organic-rich aerosol contributes significantly to particles active as cloud condensation nuclei (CCN, supersaturation  =  0.6 %), which are elevated in concentration during aerosol growth above background levels of ∼ 100 to ∼ 220 cm−3. Results from this case study highlight the potential importance of secondary organic aerosol formation and its role in growing nucleation mode aerosol into CCN-active sizes in this remote marine environment.

Simulations of Föhn in Antarctica with WRF for the Antarctic Mesoscale Prediction System AMPS

2021 ◽  
Author(s):  
Amélie Kirchgaessner ◽  
John King ◽  
Alan Gadian ◽  
Phil Anderson
Keyword(s):  
Weather Research And Forecasting ◽  
Mountain Range ◽  
Prediction System ◽  
Atmospheric Conditions ◽  
Ice Shelf ◽  
Cloud Properties ◽  
Surface Melt ◽  
Mixed Phase Clouds ◽  
The Antarctic

&lt;p&gt;We examine the representation of F&amp;#246;hn events across the Antarctic Peninsula Mountains during 2011 as they were observed in measurements by an Automatic Weather Station, and in simulations with the Weather Research and Forecasting Model (WRF) as run for the Antarctic Mesoscale Prediction System (AMPS). On the Larsen Ice Shelf (LIS) in the lee of this mountain range F&amp;#246;hn winds are thought to provide the atmospheric conditions for significant warming over the ice shelf thus leading to the initial firn densification and subsequently providing the melt water for hydrofracturing. This process has led to the dramatic collapse of huge parts of the LIS in 1995 and 2002 respectively.&lt;/p&gt;&lt;p&gt;Measurements obtained at a crest AWS on the Avery Plateau (AV), and the analysis of conditions upstream using the Froude number help to put observations at CP into a wider context. We find that, while the model generally simulates meteorological parameters very well, and shows good skills in capturing the occurrence, frequency and duration of F&amp;#246;hn events realistically, it underestimates the temperature increase and the humidity decrease during the F&amp;#246;hn significantly, and may thus underestimate the contribution of F&amp;#246;hn to driving surface melt on the LIS.&lt;/p&gt;&lt;p&gt;Our results indicate that the misrepresentation of cloud properties and particularly the absence of mixed phase clouds in AMPS, affects the quality of weather simulation under normal conditions to some extent, and to a larger extent the model&amp;#8217;s capability to simulate the strength of F&amp;#246;hn conditions - and thus their contribution to driving surface melt on the LIS - adequately. Most importantly our data show that F&amp;#246;hn conditions can raise the air temperature to above freezing, and thus trigger melt/sublimation even in winter.&lt;/p&gt;

A global record of single-layered ice cloud properties and associated radiative heating rate profiles from an A-Train perspective

2019 ◽  
Vol 53 (5-6) ◽  
pp. 3069-3088 ◽  
Author(s):  
Erica K. Dolinar ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Jonathan H. Jiang ◽  
Norman G. Loeb ◽  
...  
Keyword(s):  
Heating Rate ◽  
Radiative Heating ◽  
Ice Cloud ◽  
Cloud Properties

scholarly journals Synoptic patterns associated with wildfires caused by lightning in Castile and Leon, Spain

2011 ◽  
Vol 11 (3) ◽  
pp. 851-863 ◽  
Author(s):  
E. García-Ortega ◽  
M. T. Trobajo ◽  
L. López ◽  
J. L. Sánchez
Keyword(s):  
Principal Component ◽  
Horizontal Wind ◽  
Complex Task ◽  
Atmospheric Conditions ◽  
Natural Risk ◽  
Convective Storms ◽  
Local Character ◽  
Weather Events ◽  
Nw Of Spain

Abstract. The Iberian Peninsula presents the highest number of wildfires in Europe. In the NW of Spain in particular, wildfires are the natural risk with the greatest economic impact in this region. Wildfires caused by lightning are closely related to the triggering of convective phenomena. The prediction of thunderstorms is a very complex task because these weather events have a local character and are highly dependent on mesoscale atmospheric conditions. The development of convective storms is directly linked to the existence of a synoptic environment favoring convection. The aim of this study is to classify the atmospheric patterns that provide favorable environments for the occurrence of wildfires caused by lightning in the region of Castile and Leon, Spain. The database used for the study contains 376 wildfire days from the period 1987–2006. NCEP data reanalysis has been used. The atmospheric fields used to characterise each day were: geopotential heights and temperatures at 500 hPa and 850 hPa, relative humidity and the horizontal wind at 850 hPa. A Principal Component Analysis in T-mode followed by a Cluster Analysis resulted in a classification of wildfire days into five clusters. The characteristics of these clusters were analysed and described, focusing particularly on the study of those wildfire days in which more than one wildfire was detected. In these cases the main feature observed was the intensification of the disturbance typical of the cluster to which the wildfire belongs.

scholarly journals Effect of Aerosols on the Ice Cloud Properties Over the Tibetan Plateau

2019 ◽  
Vol 124 (16) ◽  
pp. 9594-9608 ◽  
Author(s):  
Yuzhi Liu ◽  
Shan Hua ◽  
Rui Jia ◽  
Jianping Huang
Keyword(s):  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Ice Cloud ◽  
Cloud Properties

scholarly journals Weather During Key Growth Stages Explains Grain Quality and Yield of Maize

Agronomy ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 16 ◽  
Author(s):  
Carrie J. Butts-Wilmsmeyer ◽  
Juliann R. Seebauer ◽  
Lee Singleton ◽  
Frederick E. Below
Keyword(s):  
Environmental Factors ◽  
Grain Yield ◽  
Grain Quality ◽  
Principal Component ◽  
The United States ◽  
Soil Water Storage ◽  
Growth Stages ◽  
Linear Regression Models ◽  
Compositional Quality ◽  
Large Geographical Region

Maize (Zea mays L.) grain yield and compositional quality are interrelated and are highly influenced by environmental factors such as temperature, total precipitation, and soil water storage. Our aim was to develop a regression model to account for this relationship among grain yield and compositional quality traits across a large geographical region. Three key growth periods were used to develop algorithms based on the week of emergence, the week of 50% silking, and the week of maturity that enabled collection and modeling of the effect of weather and climatic variables across the major maize growing region of the United States. Principal component analysis (PCA), stepwise linear regression models, and hierarchical clustering analyses were used to evaluate the multivariate relationship between weather, grain quality, and yield. Two PCAs were found that could identify superior grain compositional quality as a result of ideal environmental factors as opposed to low-yielding conditions. Above-average grain protein and oil levels were favored by less nitrogen leaching during early vegetative growth and higher temperatures at flowering, while greater oil than protein concentrations resulted from lower temperatures during flowering and grain fill. Water availability during flowering and grain fill was highly explanatory of grain yield and compositional quality.

scholarly journals Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission

2016 ◽  
Vol 16 (18) ◽  
pp. 12287-12303 ◽  
Author(s):  
Husi Letu ◽  
Hiroshi Ishimoto ◽  
Jerome Riedi ◽  
Takashi Y. Nakajima ◽  
Laurent C.-Labonnote ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Asymmetry Factor ◽  
Size Parameter ◽  
Geometric Optics ◽  
Ice Clouds ◽  
Extinction Efficiency ◽  
Ice Cloud ◽  
Cloud Properties

Abstract. In this study, various ice particle habits are investigated in conjunction with inferring the optical properties of ice clouds for use in the Global Change Observation Mission-Climate (GCOM-C) satellite programme. We develop a database of the single-scattering properties of five ice habit models: plates, columns, droxtals, bullet rosettes, and Voronoi. The database is based on the specification of the Second Generation Global Imager (SGLI) sensor on board the GCOM-C satellite, which is scheduled to be launched in 2017 by the Japan Aerospace Exploration Agency. A combination of the finite-difference time-domain method, the geometric optics integral equation technique, and the geometric optics method is applied to compute the single-scattering properties of the selected ice particle habits at 36 wavelengths, from the visible to the infrared spectral regions. This covers the SGLI channels for the size parameter, which is defined as a single-particle radius of an equivalent volume sphere, ranging between 6 and 9000 µm. The database includes the extinction efficiency, absorption efficiency, average geometrical cross section, single-scattering albedo, asymmetry factor, size parameter of a volume-equivalent sphere, maximum distance from the centre of mass, particle volume, and six nonzero elements of the scattering phase matrix. The characteristics of calculated extinction efficiency, single-scattering albedo, and asymmetry factor of the five ice particle habits are compared. Furthermore, size-integrated bulk scattering properties for the five ice particle habit models are calculated from the single-scattering database and microphysical data. Using the five ice particle habit models, the optical thickness and spherical albedo of ice clouds are retrieved from the Polarization and Directionality of the Earth's Reflectances-3 (POLDER-3) measurements, recorded on board the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The optimal ice particle habit for retrieving the SGLI ice cloud properties is investigated by adopting the spherical albedo difference (SAD) method. It is found that the SAD is distributed stably due to the scattering angle increases for bullet rosettes with an effective diameter (Deff) of 10 µm and Voronoi particles with Deff values of 10, 60, and 100 µm. It is confirmed that the SAD of small bullet-rosette particles and all sizes of Voronoi particles has a low angular dependence, indicating that a combination of the bullet-rosette and Voronoi models is sufficient for retrieval of the ice cloud's spherical albedo and optical thickness as effective habit models for the SGLI sensor. Finally, SAD analysis based on the Voronoi habit model with moderate particle size (Deff = 60 µm) is compared with the conventional general habit mixture model, inhomogeneous hexagonal monocrystal model, five-plate aggregate model, and ensemble ice particle model. The Voronoi habit model is found to have an effect similar to that found in some conventional models for the retrieval of ice cloud properties from space-borne radiometric observations.

Compositional changes over four years for binary mixtures of grass species grown with white clover

2005 ◽  
Vol 85 (2) ◽  
pp. 351-360 ◽  
Author(s):  
D. B. McKenzie ◽  
Y. A. Papadopoulos ◽  
K. B. McRae ◽  
E. Butt
Keyword(s):  
White Clover ◽  
Tall Fescue ◽  
Principal Component ◽  
Growing Season ◽  
Kentucky Bluegrass ◽  
Repeated Measurements ◽  
Grass Species ◽  
Growth Stages ◽  
Meadow Fescue ◽  
Reed Canarygrass

Kentucky bluegrass, meadow fescue, orchardgrass, tall fescue, timothy, and reed canarygrass were seeded in all possible two-grass combinations with white clover in conventional and underseeded barley treatments using a split-plot design at the Western Agriculture Centre near Pynn’s Brook, NL. The objectives were: (1) to assess dry matter yield (DMY) of two binary grass species when sown with white clover in mixtures under a system with cuttings at similar crop growth stages as rotational grazing and to assess the effect of underseeding to barley on this system; (2) to identify mixtures that enhance herbage distribution throughout the grazing season; and (3) to assess the sward dynamics over successive cropping seasons. The composition of the binary grass mixtures with white clover affected seasonal DMY, seasonal herbage distribution, and sward dynamics over the production years. Orchardgrass in mixtures decreased DMY, shifted the herbage distribution toward early season, and competed with other species. Timothy composition of the stand showed the largest decline over the 3 production years, whereas white clover declined in mixtures with bluegrass, orchardgrass, or tall fescue. Meadow fescue and reed canarygrass with white clover was the most productive mixture with excellent persistence and good yield distribution over the growing season. Orchardgrass was the least compatible species in the mixtures; it dominated first growth and contributed the least to biomass production in later years. Both bluegrass and reed canarygrass performed well in mixtures over the 3 production years; bluegrass appeared to enhance the performance of the other species during summer regrowth whereas reed canarygrass was superior in the later part of the growing season. Underseeding with barley did not affect white clover yield in any production year but detrimentally affected the yield of orchardgrass and meadow fescue in mixtures, and their seasonal distribution. Key words: Bluegrass, orchardgrass, meadow fescue, tall fescue, timothy, reed canarygrass, repeated measurements, principal component analysis, herbage DM distribution, species competition

Sign in / Sign up

Export Citation Format

Share Document