Application of polarization lidars to study the orientation of crystalline particles in ice clouds

2021 ◽  
Author(s):  
Grigorii P. Kokhanenko ◽  
Yurii S. Balin ◽  
Anatoli G. Borovoi ◽  
Marina G. Klemasheva ◽  
Sergei V. Nasonov ◽  
...  
Keyword(s):  
Ice Clouds

scholarly journals Mars: Mariner 9 Spectroscopic Evidence for H2O Ice Clouds

Science ◽  
1973 ◽  
Vol 182 (4110) ◽  
pp. 381-383 ◽  
Author(s):  
R. J. Curran ◽  
B. J. Conrath ◽  
R. A. Hanel ◽  
V. G. Kunde ◽  
J. C. Pearl
Keyword(s):  
Ice Clouds ◽  
Spectroscopic Evidence ◽  
Mariner 9

scholarly journals A model sensitivity study of the impact of clouds on satellite detection and retrieval of volcanic ash

2015 ◽  
Vol 8 (5) ◽  
pp. 1935-1949 ◽  
Author(s):  
A. Kylling ◽  
N. Kristiansen ◽  
A. Stohl ◽  
R. Buras-Schnell ◽  
C. Emde ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Liquid Water ◽  
Volcanic Ash ◽  
Spectral Band ◽  
Sensitivity Study ◽  
Transfer Model ◽  
Mass Loading ◽  
Ice Clouds ◽  
Medium Range Weather Forecast ◽  
The Impact

Abstract. Volcanic ash is commonly observed by infrared detectors on board Earth-orbiting satellites. In the presence of ice and/or liquid-water clouds, the detected volcanic ash signature may be altered. In this paper the sensitivity of detection and retrieval of volcanic ash to the presence of ice and liquid-water clouds was quantified by simulating synthetic equivalents to satellite infrared images with a 3-D radiative transfer model. The sensitivity study was made for the two recent eruptions of Eyjafjallajökull (2010) and Grímsvötn (2011) using realistic water and ice clouds and volcanic ash clouds. The water and ice clouds were taken from European Centre for Medium-Range Weather Forecast (ECMWF) analysis data and the volcanic ash cloud fields from simulations by the Lagrangian particle dispersion model FLEXPART. The radiative transfer simulations were made both with and without ice and liquid-water clouds for the geometry and channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The synthetic SEVIRI images were used as input to standard reverse absorption ash detection and retrieval methods. Ice and liquid-water clouds were on average found to reduce the number of detected ash-affected pixels by 6–12%. However, the effect was highly variable and for individual scenes up to 40% of pixels with mass loading >0.2 g m−2 could not be detected due to the presence of water and ice clouds. For coincident pixels, i.e. pixels where ash was both present in the FLEXPART (hereafter referred to as "Flexpart") simulation and detected by the algorithm, the presence of clouds overall increased the retrieved mean mass loading for the Eyjafjallajökull (2010) eruption by about 13%, while for the Grímsvötn (2011) eruption ash-mass loadings the effect was a 4% decrease of the retrieved ash-mass loading. However, larger differences were seen between scenes (standard deviations of ±30 and ±20% for Eyjafjallajökull and Grímsvötn, respectively) and even larger ones within scenes. The impact of ice and liquid-water clouds on the detection and retrieval of volcanic ash, implies that to fully appreciate the location and amount of ash, hyperspectral and spectral band measurements by satellite instruments should be combined with ash dispersion modelling.

scholarly journals Effects of ice particle size vertical inhomogeneity on the passive remote sensing of ice clouds

2010 ◽  
Vol 115 (D17) ◽  
Author(s):  
Zhibo Zhang ◽  
Steven Platnick ◽  
Ping Yang ◽  
Andrew K. Heidinger ◽  
Jennifer M. Comstock
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Ice Clouds ◽  
Passive Remote Sensing ◽  
Vertical Inhomogeneity

Impacts of mineral dust on ice clouds in tropical deep convection systems

2014 ◽  
Vol 143 ◽  
pp. 64-72 ◽  
Author(s):  
Q.-L. Min ◽  
R. Li ◽  
B. Lin ◽  
E. Joseph ◽  
V. Morris ◽  
...  
Keyword(s):  
Mineral Dust ◽  
Deep Convection ◽  
Ice Clouds ◽  
Tropical Deep Convection

Effects of water and ice clouds on cloud microphysical budget: An equilibrium modeling study

2014 ◽  
Vol 23 (2) ◽  
pp. 024204 ◽  
Author(s):  
Shou-Ting Gao ◽  
Xiao-Fan Li ◽  
Yu-Shu Zhou
Keyword(s):  
Ice Clouds ◽  
Equilibrium Modeling ◽  
Modeling Study

scholarly journals Accuracy and precision of polar lower stratospheric temperatures from reanalyses evaluated from A-Train CALIOP and MLS, COSMIC GPS RO, and the equilibrium thermodynamics of supercooled ternary solutions and ice clouds

2018 ◽  
Vol 18 (3) ◽  
pp. 1945-1975 ◽  
Author(s):  
Alyn Lambert ◽  
Michelle L. Santee
Keyword(s):  
Pressure Range ◽  
Equilibrium Thermodynamics ◽  
Polar Stratospheric Clouds ◽  
Ice Clouds ◽  
Warm Bias ◽  
Frost Point ◽  
Ternary Solutions ◽  
Accuracy And Precision ◽  
Temperature Reference ◽  
Stratospheric Clouds

Abstract. We investigate the accuracy and precision of polar lower stratospheric temperatures (100–10 hPa during 2008–2013) reported in several contemporary reanalysis datasets comprising two versions of the Modern-Era Retrospective analysis for Research and Applications (MERRA and MERRA-2), the Japanese 55-year Reanalysis (JRA-55), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-I), and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (NCEP-CFSR). We also include the Goddard Earth Observing System model version 5.9.1 near-real-time analysis (GEOS-5.9.1). Comparisons of these datasets are made with respect to retrieved temperatures from the Aura Microwave Limb Sounder (MLS), Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) Global Positioning System (GPS) radio occultation (RO) temperatures, and independent absolute temperature references defined by the equilibrium thermodynamics of supercooled ternary solutions (STSs) and ice clouds. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations of polar stratospheric clouds are used to determine the cloud particle types within the Aura MLS geometric field of view. The thermodynamic calculations for STS and the ice frost point use the colocated MLS gas-phase measurements of HNO3 and H2O. The estimated bias and precision for the STS temperature reference, over the 68 to 21 hPa pressure range, are 0.6–1.5 and 0.3–0.6 K, respectively; for the ice temperature reference, they are 0.4 and 0.3 K, respectively. These uncertainties are smaller than those estimated for the retrieved MLS temperatures and also comparable to GPS RO uncertainties (bias  <  0.2 K, precision  >  0.7 K) in the same pressure range. We examine a case study of the time-varying temperature structure associated with layered ice clouds formed by orographic gravity waves forced by flow over the Palmer Peninsula and compare how the wave amplitudes are reproduced by each reanalysis dataset. We find that the spatial and temporal distribution of temperatures below the ice frost point, and hence the potential to form ice polar stratospheric clouds (PSCs) in model studies driven by the reanalyses, varies significantly because of the underlying differences in the representation of mountain wave activity. High-accuracy COSMIC temperatures are used as a common reference to intercompare the reanalysis temperatures. Over the 68–21 hPa pressure range, the biases of the reanalyses with respect to COSMIC temperatures for both polar regions fall within the narrow range of −0.6 K to +0.5 K. GEOS-5.9.1, MERRA, MERRA-2, and JRA-55 have predominantly cold biases, whereas ERA-I has a predominantly warm bias. NCEP-CFSR has a warm bias in the Arctic but becomes substantially colder in the Antarctic. Reanalysis temperatures are also compared with the PSC reference temperatures. Over the 68–21 hPa pressure range, the reanalysis temperature biases are in the range −1.6 to −0.3 K with standard deviations  ∼  0.6 K for the CALIOP STS reference, and in the range −0.9 to +0.1 K with standard deviations  ∼  0.7 K for the CALIOP ice reference. Comparisons of MLS temperatures with the PSC reference temperatures reveal vertical oscillations in the MLS temperatures and a significant low bias in MLS temperatures of up to 3 K.

scholarly journals Influence of water ice clouds on Martian tropical atmospheric temperatures

2008 ◽  
Vol 35 (7) ◽  
pp. n/a-n/a ◽  
Author(s):  
R. John Wilson ◽  
Stephen R. Lewis ◽  
Luca Montabone ◽  
Michael D. Smith
Keyword(s):  
Ice Clouds ◽  
Water Ice ◽  
Influence Of Water
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