Cloud liquid and ice water content estimation from satellite: a regression approach based on neural networks

2021 ◽  
Author(s):  
Pietro Mastro ◽  
Guido Masiello ◽  
Domenico Cimini ◽  
Filomena Romano ◽  
Elisabetta Ricciardelli ◽  
...  
Keyword(s):  
Neural Networks ◽  
Water Content ◽  
Regression Approach ◽  
Ice Water Content ◽  
Ice Water

Ice water content assessment in the single-, dual-, and triple-frequency radar scenarios

2021 ◽  
Vol 254 ◽  
pp. 112242
Author(s):  
Eugenio Gorgucci ◽  
Luca Baldini ◽  
Elisa Adirosi ◽  
Mario Montopoli
Keyword(s):  
Water Content ◽  
Content Assessment ◽  
Triple Frequency ◽  
Ice Water Content ◽  
Ice Water

scholarly journals Measuring ice- and liquid-water properties in mixed-phase cloud layers at the Leipzig Cloudnet station

2016 ◽  
Vol 16 (16) ◽  
pp. 10609-10620 ◽  
Author(s):  
Johannes Bühl ◽  
Patric Seifert ◽  
Alexander Myagkov ◽  
Albert Ansmann
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Mass Flux ◽  
Mixed Phase ◽  
Cloud Base ◽  
Doppler Velocity ◽  
Special Focus ◽  
Data Set ◽  
Ice Water Content ◽  
Ice Water

Abstract. An analysis of the Cloudnet data set collected at Leipzig, Germany, with special focus on mixed-phase layered clouds is presented. We derive liquid- and ice-water content together with vertical motions of ice particles falling through cloud base. The ice mass flux is calculated by combining measurements of ice-water content and particle Doppler velocity. The efficiency of heterogeneous ice formation and its impact on cloud lifetime is estimated for different cloud-top temperatures by relating the ice mass flux and the liquid-water content at cloud top. Cloud radar measurements of polarization and Doppler velocity indicate that ice crystals formed in mixed-phase cloud layers with a geometrical thickness of less than 350 m are mostly pristine when they fall out of the cloud.

Simultaneous Ice Water Content Measurements at Multiple Locations on the NASA DC-8 Aircraft During the 2018 HIWC RADAR Flight Campaign

2021 ◽  
Author(s):  
Lyle E. Lilie ◽  
Dan Bouley ◽  
Christopher P. Sivo ◽  
John W. Strapp ◽  
Thomas P. Ratvasky
Keyword(s):  
Water Content ◽  
Ice Water Content ◽  
Ice Water

scholarly journals A Prototype Method for Diagnosing High Ice Water Content Probability Using Satellite Imager Data

2017 ◽  
Author(s):  
Christopher R. Yost ◽  
Kristopher M. Bedka ◽  
Patrick Minnis ◽  
Louis Nguyen ◽  
J. Walter Strapp ◽  
...  
Keyword(s):  
Water Content ◽  
Deep Convection ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Radar Data ◽  
High Mass ◽  
Cloud Optical Depth ◽  
Geo Satellite ◽  
Ice Water Content ◽  
Ice Water

Abstract. Recent studies have found that flight through deep convective storms and ingestion of high mass concentrations of ice crystals, also known as high ice water content (HIWC), into aircraft engines can adversely impact aircraft engine performance. These aircraft engine icing events caused by HIWC have been documented during flight in weak reflectivity regions near convective updraft regions that do not appear threatening in onboard weather radar data. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in-situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: 1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, 2) tropopause-relative infrared brightness temperature, and 3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite-aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC ≥ 0.5 g m−3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.

scholarly journals Summary of the High Ice Water Content (HIWC) RADAR Flight Campaigns

2019 ◽  
Author(s):  
Thomas Ratvasky ◽  
Steven Harrah ◽  
J. Walter Strapp ◽  
Lyle Lilie ◽  
Fred Proctor ◽  
...  
Keyword(s):  
Water Content ◽  
Ice Water Content ◽  
Ice Water

scholarly journals An algorithm to retrieve ice water content profiles in cirrus clouds from the synergy of ground-based lidar and thermal infrared radiometer measurements

2019 ◽  
Vol 12 (3) ◽  
pp. 1545-1568
Author(s):  
Friederike Hemmer ◽  
Laurent C.-Labonnote ◽  
Frédéric Parol ◽  
Gérard Brogniez ◽  
Bahaiddin Damiri ◽  
...  
Keyword(s):  
Water Content ◽  
Correction Factor ◽  
Phase Function ◽  
Extinction Ratio ◽  
Optimal Estimation ◽  
Thermal Infrared ◽  
Cirrus Clouds ◽  
Ice Crystals ◽  
Ice Water Content ◽  
Ice Water

Abstract. The algorithm presented in this paper was developed to retrieve ice water content (IWC) profiles in cirrus clouds. It is based on optimal estimation theory and combines ground-based visible lidar and thermal infrared (TIR) radiometer measurements in a common retrieval framework in order to retrieve profiles of IWC together with a correction factor for the backscatter intensity of cirrus cloud particles. As a first step, we introduce a method to retrieve extinction and IWC profiles in cirrus clouds from the lidar measurements alone and demonstrate the shortcomings of this approach due to the backscatter-to-extinction ambiguity. As a second step, we show that TIR radiances constrain the backscattering of the ice crystals at the visible lidar wavelength by constraining the ice water path (IWP) and hence the IWC, which is linked to the optical properties of the ice crystals via a realistic bulk ice microphysical model. The scattering phase function obtained from the microphysical model is flat around the backscatter direction (i.e., there is no backscatter peak). We show that using this flat backscattering phase function to define the backscatter-to-extinction ratio of the ice crystals in the retrievals with the lidar-only algorithm results in an overestimation of the IWC, which is inconsistent with the TIR radiometer measurements. Hence, a synergy algorithm was developed that combines the attenuated backscatter profiles measured by the lidar and the measurements of TIR radiances in a common optimal estimation framework to retrieve the IWC profile together with a correction factor for the phase function of the bulk ice crystals in the backscattering direction. We show that this approach yields consistent lidar and TIR results. The resulting lidar ratios for cirrus clouds are found to be consistent with previous independent studies.

scholarly journals Radar Scattering from Ice Aggregates Using the Horizontally Aligned Oblate Spheroid Approximation

2012 ◽  
Vol 51 (3) ◽  
pp. 655-671 ◽  
Author(s):  
Robin J. Hogan ◽  
Lin Tian ◽  
Philip R. A. Brown ◽  
Christopher D. Westbrook ◽  
Andrew J. Heymsfield ◽  
...  
Keyword(s):  
Water Content ◽  
Millimeter Wave ◽  
Mie Scattering ◽  
Ice Particles ◽  
Size Relationship ◽  
Wave Radar ◽  
Mass Size ◽  
Ice Water Content ◽  
Ice Water ◽  
Reflectivity Factor

AbstractThe assumed relationship between ice particle mass and size is profoundly important in radar retrievals of ice clouds, but, for millimeter-wave radars, shape and preferred orientation are important as well. In this paper the authors first examine the consequences of the fact that the widely used “Brown and Francis” mass–size relationship has often been applied to maximum particle dimension observed by aircraft Dmax rather than to the mean of the particle dimensions in two orthogonal directions Dmean, which was originally used by Brown and Francis. Analysis of particle images reveals that Dmax ≃ 1.25Dmean, and therefore, for clouds for which this mass–size relationship holds, the consequences are overestimates of ice water content by around 53% and of Rayleigh-scattering radar reflectivity factor by 3.7 dB. Simultaneous radar and aircraft measurements demonstrate that much better agreement in reflectivity factor is provided by using this mass–size relationship with Dmean. The authors then examine the importance of particle shape and fall orientation for millimeter-wave radars. Simultaneous radar measurements and aircraft calculations of differential reflectivity and dual-wavelength ratio are presented to demonstrate that ice particles may usually be treated as horizontally aligned oblate spheroids with an axial ratio of 0.6, consistent with them being aggregates. An accurate formula is presented for the backscatter cross section apparent to a vertically pointing millimeter-wave radar on the basis of a modified version of Rayleigh–Gans theory. It is then shown that the consequence of treating ice particles as Mie-scattering spheres is to substantially underestimate millimeter-wave reflectivity factor when millimeter-sized particles are present, which can lead to retrieved ice water content being overestimated by a factor of 4.

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