scholarly journals Factors controlling contrail cirrus optical depth

2009 ◽  
Vol 9 (3) ◽  
pp. 11589-11658 ◽  
Author(s):  
B. Kärcher ◽  
U. Burkhardt ◽  
S. Unterstrasser ◽  
P. Minnis
Keyword(s):  
Optical Depth ◽  
Cloud Model ◽  
Climate Impact ◽  
Distribution Functions ◽  
Horizontal Wind ◽  
Mean Values ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Marked Variability ◽  
Shear Factors

Abstract. Aircraft contrails develop into contrail cirrus by depositional growth and sedimentation of ice particles and horizontal spreading due to wind shear. Factors controlling this development include temperature, ice supersaturation, thickness of ice-supersaturated layers, and vertical gradients in the horizontal wind field. An analytical microphysical cloud model is presented and validated that captures these processes. Many individual contrail cirrus are simulated that develop differently owing to the variability in the controlling factors, resulting in large samples of cloud properties that are statistically analyzed. Contrail cirrus development is studied over the first four hours past formation, similar to the ages of contrails that were tracked in satellite imagery on regional scales. On these time scales, contrail cirrus optical depth and microphysical variables exhibit a marked variability, expressed in terms of broad and skewed probability distribution functions. Typical simulated mean optical depths at a wavelength of 0.55 μm are in the range 0.2–0.3. A substantial fraction 20–40% of contrail cirrus stay subvisible (optical depth <0.02). A detailed analysis suggests that previous satellite measurements of line-shaped persistent contrails have missed about 86% (35%) of contrails with optical depth ≤0.05 (0.05–0.1), amounting to almost 50% of contrails of all optical depths. When comparing observations with simulations and when estimating the contrail cirrus climate impact, not only mean values but also the variability in optical depth and microphysical properties need to be considered.

scholarly journals Factors controlling contrail cirrus optical depth

2009 ◽  
Vol 9 (16) ◽  
pp. 6229-6254 ◽  
Author(s):  
B. Kärcher ◽  
U. Burkhardt ◽  
S. Unterstrasser ◽  
P. Minnis
Keyword(s):  
Optical Depth ◽  
Cloud Model ◽  
Climate Impact ◽  
Distribution Functions ◽  
Horizontal Wind ◽  
Mean Values ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Marked Variability ◽  
Shear Factors

Abstract. Aircraft contrails develop into contrail cirrus by depositional growth and sedimentation of ice particles and horizontal spreading due to wind shear. Factors controlling this development include temperature, ice supersaturation, thickness of ice-supersaturated layers, and vertical gradients in the horizontal wind field. An analytical microphysical cloud model is presented and validated that captures these processes. Many individual contrail cirrus are simulated that develop differently owing to the variability in the controlling factors, resulting in large samples of cloud properties that are statistically analyzed. Contrail cirrus development is studied over the first four hours past formation, similar to the ages of line-shaped contrails that were tracked in satellite imagery on regional scales. On these time scales, contrail cirrus optical depth and microphysical variables exhibit a marked variability, expressed in terms of broad and skewed probability distribution functions. Simulated mean optical depths at a wavelength of 0.55 μm range from 0.05-0.5 and a substantial fraction 20-50% of contrail cirrus stay subvisible (optical depth <0.02), depending on meteorological conditions. A detailed analysis based on an observational case study over the continental USA suggests that previous satellite measurements of line-shaped persistent contrails have missed about 89%, 50%, and 11% of contrails with optical depths 0-0.05, 0.05-0.1, and 0.1-0.2, respectively, amounting to 65% of contrail coverage of all optical depths. When comparing observations with simulations and when estimating the contrail cirrus climate impact, not only mean values but also the variability in optical depth and microphysical properties need to be considered.

scholarly journals Ice water content of arctic, midlatitude, and tropical cirrus – Part 2: Extension of the database and new statistical analysis

2012 ◽  
Vol 12 (11) ◽  
pp. 29443-29474 ◽  
Author(s):  
A. E. Luebke ◽  
L. M. Avallone ◽  
C. Schiller ◽  
C. Rolf ◽  
M. Krämer
Keyword(s):  
Water Content ◽  
Radiative Forcing ◽  
Climate Models ◽  
Distribution Functions ◽  
Formation Mechanisms ◽  
Mean Values ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
Ground Based Lidar ◽  
Ice Water

Abstract. Ice clouds are known to be major contributors to radiative forcing in the Earth's atmosphere, yet describing their microphysical properties in climate models remains challenging. Among these properties, the ice water content (IWC) of cirrus clouds is of particular interest both because it is measurable and because it can be directly related to a number of other radiatively important variables such as extinction and effective radius. This study expands upon the work of Schiller et al. (2008), extending a climatology of IWC by combining datasets from several European and US airborne campaigns and ground-based lidar measurements over Jülich, Germany. The relationship between IWC and temperature is further investigated using the new merged dataset and probability distribution functions (PDFs). A PDF-based formulation allows for representation of not only the mean values of IWC, but also the variability of IWC within a temperature band. The IWC-PDFs are found to be bimodal over the whole cirrus temperature range, which might be attributed to different cirrus formation mechanisms such as heterogeneous and homogeneous freezing. The PDFs of IWC are further compared to distributions of cirrus ice crystal number and mass mean radius, which show that the general relationship between IWC and temperature appears to be influenced much more by particle number than by particle size.

scholarly journals Exponential Size Distributions for Snow

2008 ◽  
Vol 65 (12) ◽  
pp. 4017-4031 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Paul Field ◽  
Aaron Bansemer
Keyword(s):  
Cloud Model ◽  
Size Distributions ◽  
Airborne Measurements ◽  
Ice Cloud ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Small Crystals ◽  
Before And After ◽  
Ice Water Content ◽  
Ice Water

Abstract Using airborne data from several recent field projects, the authors have taken another look at the properties of exponential ice particle size distributions (PSDs) when the PSDs are broad. Two primary questions are addressed: for what ranges of ice water content (IWC) and equivalent radar reflectivity (Ze) do exponentials produce accurate estimates of these higher moments of the PSD, and why is there a lower limit to the value to the slope of exponential fits to PSD, λ, as has been found from airborne measurements? Earlier studies at temperatures primarily above −10°C have found that λ measured in snow during spiral descents through deep ice cloud layers decreases to about 9 cm−1 and then remains there. Several physical processes have been advanced to explain these observations. If reliable, the data could be used to improve retrieval of ice cloud properties through remote sensing and for cloud model representations of ice cloud microphysical properties. For data acquired from 2D probes, recent evidence indicates shattering of large ice particles ahead of, but attributable to, the probe’s sensing area, generating small crystals that the probe then senses. Shattered artifacts have been objectively removed from the data. Comparisons of size distributions before and after removal of suspected shattered particles suggest that the reported minimum may have been due to shattering and/or other instrument errors. The revised PSDs indicate that for λ &lt; 40 cm−1, 0.1 g m−1 &lt; IWC, and 5 dB &lt; Ze, moments two (IWC) through four (Ze) of the PSD are dominated by particles larger than a few hundred microns. Analytical representations with more variables than exponentials (e.g., gamma PSD) are not required to accurately derive these moments from the PSD. In these situations, the intercept parameter of the exponential PSD, N0 ≈ 1 cm−4, is 5 to 30 times larger than assumed earlier.

scholarly journals Ice water content of Arctic, midlatitude, and tropical cirrus – Part 2: Extension of the database and new statistical analysis

2013 ◽  
Vol 13 (13) ◽  
pp. 6447-6459 ◽  
Author(s):  
A. E. Luebke ◽  
L. M. Avallone ◽  
C. Schiller ◽  
J. Meyer ◽  
C. Rolf ◽  
...  
Keyword(s):  
Water Content ◽  
Radiative Forcing ◽  
Climate Models ◽  
Distribution Functions ◽  
Formation Mechanisms ◽  
Mean Values ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
Ground Based Lidar ◽  
Ice Water

Abstract. Ice clouds are known to be major contributors to radiative forcing in the Earth's atmosphere, yet describing their microphysical properties in climate models remains challenging. Among these properties, the ice water content (IWC) of cirrus clouds is of particular interest both because it is measurable and because it can be directly related to a number of other radiatively important variables such as extinction and effective radius. This study expands upon the work of Schiller et al. (2008), extending a climatology of IWC by combining datasets from several European and US airborne campaigns and ground-based lidar measurements over Jülich, Germany. The relationship between IWC and temperature is further investigated using the new merged dataset and probability distribution functions (PDFs). A PDF-based formulation allows for representation of not only the mean values of IWC, but also the variability of IWC within a temperature band. The IWC-PDFs are observed to be bimodal over the whole cirrus temperature range. This bimodality is also found in ice crystal number PDFs and might be attributed to different cirrus formation mechanisms such as heterogeneous and homogeneous freezing.

scholarly journals Remote sensing of aerosol in the terrestrial atmosphere from space: new missions

2015 ◽  
Vol 5 (1) ◽  
pp. 11-16 ◽  
Author(s):  
G. Milinevsky ◽  
Ya. Yatskiv ◽  
O. Degtyaryov ◽  
I. Syniavskyi ◽  
Yu. Ivanov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosols ◽  
Climate Models ◽  
Global Scale ◽  
Climate Impact ◽  
Quality Of Data ◽  
Anthropogenic Aerosol ◽  
Terrestrial Atmosphere ◽  
Microphysical Properties ◽  
Cloud Properties

The distribution and properties of atmospheric aerosols on a global scale are not well known in terms of determination of their effects on climate. This mostly is due to extreme variability of aerosol concentrations, properties, sources, and types. Aerosol climate impact is comparable to the effect of greenhouse gases, but its influence is more difficult to measure, especially with respect to aerosol microphysical properties and the evaluation of anthropogenic aerosol effect. There are many satellite missions studying aerosol distribution in the terrestrial atmosphere, such as MISR/Terra, OMI/Aura, AVHHR, MODIS/Terra and Aqua, CALIOP/CALIPSO. To improve the quality of data and climate models, and to reduce aerosol climate forcing uncertainties, several new missions are planned. The gap in orbital instruments for studying aerosol microphysics has arisen after the Glory mission failed during launch in 2011. In this review paper, we describe several planned aerosol space missions, including the Ukrainian project Aerosol-UA that obtains data using a multi-channel scanning polarimeter and wide-angle polarimetric camera. The project is designed for remote sensing of the aerosol microphysics and cloud properties on a global scale.

Global dust climatology based on MODIS C6.1 and OMI-OMAERUV satellite data for the period 2005 to 2019

2020 ◽  
Author(s):  
Maria Gavrouzou ◽  
Nikos Hatzianastassiou ◽  
Antonis Gkikas ◽  
Nikos Mihalopoulos
Keyword(s):  
Optical Depth ◽  
Radiative Forcing ◽  
Cloud Condensation Nuclei ◽  
Temporal Distribution ◽  
Daily Basis ◽  
Radiative Properties ◽  
Spatiotemporal Variability ◽  
Radiation Budget ◽  
Mean Values ◽  
Cloud Properties

&lt;p&gt;Aerosol particles influence the Earth&amp;#8217;s radiation budget, and thus weather and climate, through their interaction primarily with solar, but also with terrestrial radiation. Moreover, aerosol-cloud interactions are essential, since aerosols act as Cloud Condensation Nuclei (CCN) and/or Ice Nuclei (IN), and thus crucially affect cloud properties. Dust is a major aerosol type, accounting for a great fraction of the global aerosol mass, mostly originating from the global deserts). Dust aerosols exert a strong radiative forcing, while acting as CCN and/or IN, thus modifying the cloud physical optical and radiative properties as well as also cloud lifetime and precipitation. However, the direct and indirect effects of dust are strongly dependent on their spatial and temporal distribution, which still has a considerable degree of uncertainty. This uncertainty is due to limitations of our knowledge about the dust spatiotemporal variability, which is due to the strong variability both of the dust sources and emissions as well as their transport and removal processes. However, in the last two decades, significant steps have been made towards improving the ability to observe dust from satellites. Advanced retrieval algorithms enable to effectively derive key aerosol optical properties which are characteristic of their physical properties such as size and absorptivity. The availability of such aerosol data since the early 2000s offers nowadays the possibility to build satellite-based dust climatologies.&lt;/p&gt;&lt;p&gt;In the present study a global dust climatology is constructed using a satellite based algorithm. The algorithm is initialized with the latest editions of Collection 6.1 MODIS-Aqua and OMAER-UV OMI-Aura data spanning the 14-year period from 2005 to 2018. The raw data of the algorithm are: (1) spectrally resolved MODIS Aerosol Optical Depth-AOD and (2) OMI Aerosol Index-AI), both available on a daily basis and at 1&amp;#176;x1&amp;#176; latitude-longitude spatial resolution. The algorithm computes, using the spectral AOD values, the aerosol Angstrom Exponent (AE), which is finally used along with AI as the main algorithm input data that are characteristic of aerosol size (AE) and absorptivity (AI). By applying appropriate thresholds that ensure the coarse size and significant absorptivity of dust, the algorithm identifies presence of dust in the atmospheric column on a daily and 1&amp;#176;x1&amp;#176; basis over the entire globe and the period 2005-2018. The algorithm estimates the frequency of presence and the associated loading (in terms of dust optical depth, DOD) of dust on a monthly and annual basis. The 14-year study period enables the computation of climatological mean values, as well as the intra-annual and inter-annual variability and trends of dust. Specific emphasis is given to the world&amp;#8217;s great deserts, as well as to regions undergoing important transport of dust.&lt;/p&gt;

scholarly journals Aerosol Characterization during the Summer 2017 Huge Fire Event on Mount Vesuvius (Italy) by Remote Sensing and In Situ Observations

2021 ◽  
Vol 13 (10) ◽  
pp. 2001
Author(s):  
Antonella Boselli ◽  
Alessia Sannino ◽  
Mariagrazia D’Emilio ◽  
Xuan Wang ◽  
Salvatore Amoruso
Keyword(s):  
Remote Sensing ◽  
Biomass Burning ◽  
Ground Level ◽  
Large Area ◽  
Fire Event ◽  
Near Surface ◽  
Mean Values ◽  
Microphysical Properties ◽  
Observational Site ◽  
Biomass Burning Aerosol

During the summer of 2017, multiple huge fires occurred on Mount Vesuvius (Italy), dispersing a large quantity of ash in the surrounding area ensuing the burning of tens of hectares of Mediterranean scrub. The fires affected a very large area of the Vesuvius National Park and the smoke was driven by winds towards the city of Naples, causing daily peak values of particulate matter (PM) concentrations at ground level higher than the limit of the EU air quality directive. The smoke plume spreading over the area of Naples in this period was characterized by active (lidar) and passive (sun photometer) remote sensing as well as near-surface (optical particle counter) observational techniques. The measurements allowed us to follow both the PM variation at ground level and the vertical profile of fresh biomass burning aerosol as well as to analyze the optical and microphysical properties. The results evidenced the presence of a layer of fine mode aerosol with large mean values of optical depth (AOD > 0.25) and Ångstrom exponent (γ > 1.5) above the observational site. Moreover, the lidar ratio and aerosol linear depolarization obtained from the lidar observations were about 40 sr and 4%, respectively, consistent with the presence of biomass burning aerosol in the atmosphere.

scholarly journals Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations

2021 ◽  
Vol 13 (6) ◽  
pp. 1096
Author(s):  
Soi Ahn ◽  
Sung-Rae Chung ◽  
Hyun-Jong Oh ◽  
Chu-Yong Chung
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Northeast Asia ◽  
Low Earth Orbit ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Radiometric Calibration ◽  
Climate Data ◽  
Error Statistics ◽  
Spatiotemporal Resolution

This study aimed to generate a near real time composite of aerosol optical depth (AOD) to improve predictive model ability and provide current conditions of aerosol spatial distribution and transportation across Northeast Asia. AOD, a proxy for aerosol loading, is estimated remotely by various spaceborne imaging sensors capturing visible and infrared spectra. Nevertheless, differences in satellite-based retrieval algorithms, spatiotemporal resolution, sampling, radiometric calibration, and cloud-screening procedures create significant variability among AOD products. Satellite products, however, can be complementary in terms of their accuracy and spatiotemporal comprehensiveness. Thus, composite AOD products were derived for Northeast Asia based on data from four sensors: Advanced Himawari Imager (AHI), Geostationary Ocean Color Imager (GOCI), Moderate Infrared Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Cumulative distribution functions were employed to estimate error statistics using measurements from the Aerosol Robotic Network (AERONET). In order to apply the AERONET point-specific error, coefficients of each satellite were calculated using inverse distance weighting. Finally, the root mean square error (RMSE) for each satellite AOD product was calculated based on the inverse composite weighting (ICW). Hourly AOD composites were generated (00:00–09:00 UTC, 2017) using the regression equation derived from the comparison of the composite AOD error statistics to AERONET measurements, and the results showed that the correlation coefficient and RMSE values of composite were close to those of the low earth orbit satellite products (MODIS and VIIRS). The methodology and the resulting dataset derived here are relevant for the demonstrated successful merging of multi-sensor retrievals to produce long-term satellite-based climate data records.

scholarly journals Investigation of Regional and Seasonal Variations in Marine Boundary Layer Cloud Properties from MODIS Observations

2008 ◽  
Vol 21 (19) ◽  
pp. 4955-4973 ◽  
Author(s):  
Michael P. Jensen ◽  
Andrew M. Vogelmann ◽  
William D. Collins ◽  
Guang J. Zhang ◽  
Edward P. Luke
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
General Circulation Models ◽  
Test Bed ◽  
Liquid Water Path ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Peak Versus

Abstract To aid in understanding the role that marine boundary layer (MBL) clouds play in climate and assist in improving their representations in general circulation models (GCMs), their long-term microphysical and macroscale characteristics are quantified using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the National Aeronautics and Space Administration’s (NASA’s) Terra satellite. Six years of MODIS pixel-level cloud products are used from oceanic study regions off the west coasts of California, Peru, the Canary Islands, Angola, and Australia where these cloud types are common. Characterizations are given for their organization (macroscale structure), the associated microphysical properties, and the seasonal dependencies of their variations for scales consistent with the size of a GCM grid box (300 km × 300 km). MBL mesoscale structure is quantified using effective cloud diameter CD, which is introduced here as a simplified measure of bulk cloud organization; it is straightforward to compute and provides descriptive information beyond that offered by cloud fraction. The interrelationships of these characteristics are explored while considering the influences of the MBL state, such as the occurrence of drizzle. Several commonalities emerge for the five study regions. MBL clouds contain the best natural examples of plane-parallel clouds, but overcast clouds occur in only about 25% of the scenes, which emphasizes the importance of representing broken MBL cloud fields in climate models (that are subgrid scale). During the peak months of cloud occurrence, mesoscale organization (larger CD) increases such that the fractions of scenes characterized as “overcast” and “clumped” increase at the expense of the “scattered” scenes. Cloud liquid water path and visible optical depth usually trend strongly with CD, with the largest values occurring for scenes that are drizzling. However, considerable interregional differences exist in these trends, suggesting that different regression functionalities exist for each region. For peak versus off-peak months, the fraction of drizzling scenes (as a function of CD) are similar for California and Angola, which suggests that a single probability distribution function might be used for their drizzle occurrence in climate models. The patterns are strikingly opposite for Peru and Australia; thus, the contrasts among regions may offer a test bed for model simulations of MBL drizzle occurrence.

Comparison of Ice-Phase Microphysical Parameterization Schemes Using Numerical Simulations of Tropical Convection

1991 ◽  
Vol 30 (7) ◽  
pp. 985-1004 ◽  
Author(s):  
Michale McCumber ◽  
Wei-Kuo Tao ◽  
Joanne Simpson ◽  
Richard Penc ◽  
Su-Tzai Soong
Keyword(s):  
Cloud Model ◽  
Type Systems ◽  
Two Dimensions ◽  
Tropical Convection ◽  
Three Dimensions ◽  
Microphysical Properties ◽  
Cloud Models ◽  
Optimal Mix ◽  
Cloud Ice ◽  
Microphysical Parameterization

Abstract A numerical cloud model is used to evaluate the performance of several ice parameterizations. Results from simulations using these schemes are contrasted with each other, with an ice-free control simulation, and with observations to determine to what extent ice physics affect the realism of these results. Two different types of tropical convection are simulated. Tropical squall-type systems are simulated in two dimensions so that a large domain can be used to incorporate a complete anvil. Nonsquall-type convective lines are simulated in three dimensions owing to their smaller horizontal scale. The inclusion of ice processes enhances the agreement of the simulated convection with some features of observed convection, including the proportion of surface rainfall in the anvil region, and the intensity and structure of the radar brightband near the melting level in the anvil. In the context of our experimental design, the use of three ice classes produces better results than two ice classes or ice-free conditions, and for the tropical cumuli, the optimal mix of the bulk ice hydrometeors is cloud ice-snow-graupel. We infer from our modeling results that application of bulk ice microphysics in cloud models might be case specific, which is a significant limitation. This can have serious ramifications for microwave interpretation of cloud microphysical properties. Generalization of ice processes may require a larger number of ice categories than we have evaluated and/or the prediction of hydrometeor concentrations or particle-size spectra.

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