scholarly journals Evaluation of Several A-Train Ice Cloud Retrieval Products with In Situ Measurements Collected during the SPARTICUS Campaign

2013 ◽  
Vol 52 (4) ◽  
pp. 1014-1030 ◽  
Author(s):  
Min Deng ◽  
Gerald G. Mace ◽  
Zhien Wang ◽  
R. Paul Lawson
Keyword(s):  
Water Content ◽  
Detection Threshold ◽  
In Situ Measurements ◽  
Subtle Difference ◽  
Ice Cloud ◽  
In Situ Data ◽  
Cloud Water Content ◽  
Mass Size ◽  
Ice Water

AbstractIn this study several ice cloud retrieval products that utilize active and passive A-Train measurements are evaluated using in situ data collected during the Small Particles in Cirrus (SPARTICUS) field campaign. The retrieval datasets include ice water content (IWC), effective radius re, and visible extinction σ from CloudSat level-2C ice cloud property product (2C-ICE), CloudSat level-2B radar-visible optical depth cloud water content product (2B-CWC-RVOD), radar–lidar (DARDAR), and σ from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). When the discrepancies between the radar reflectivity Ze derived from 2D stereo probe (2D-S) in situ measurements and Ze measured by the CloudSat radar are less than 10 dBZe, the flight mean ratios of the retrieved IWC to the IWC estimated from in situ data are 1.12, 1.59, and 1.02, respectively for 2C-ICE, DARDAR, and 2B-CWC-RVOD. For re, the flight mean ratios are 1.05, 1.18, and 1.61, respectively. For σ, the flight mean ratios for 2C-ICE, DARDAR, and CALIPSO are 1.03, 1.42, and 0.97, respectively. The CloudSat 2C-ICE and DARDAR retrieval products are typically in close agreement. However, the use of parameterized radar signals in ice cloud volumes that are below the detection threshold of the CloudSat radar in the 2C-ICE algorithm provides an extra constraint that leads to slightly better agreement with in situ data. The differences in assumed mass–size and area–size relations between CloudSat 2C-ICE and DARDAR also contribute to some subtle difference between the datasets: re from the 2B-CWC-RVOD dataset is biased more than the other retrieval products and in situ measurements by about 40%. A slight low (negative) bias in CALIPSO σ may be due to 5-km averaging in situations in which the cirrus layers have significant horizontal gradients in σ.

scholarly journals Dependence of the Ice Water Content and Snowfall Rate on Temperature, Globally: Comparison of in Situ Observations, Satellite Active Remote Sensing Retrievals, and Global Climate Model Simulations

2017 ◽  
Vol 56 (1) ◽  
pp. 189-215 ◽  
Author(s):  
Andrew Heymsfield ◽  
Martina Krämer ◽  
Norman B. Wood ◽  
Andrew Gettelman ◽  
Paul R. Field ◽  
...  
Keyword(s):  
Water Content ◽  
Global Climate ◽  
Global Climate Model ◽  
Ice Cloud ◽  
In Situ Data ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
In Situ Observations ◽  
Ice Water

AbstractCloud ice microphysical properties measured or estimated from in situ aircraft observations are compared with global climate models and satellite active remote sensor retrievals. Two large datasets, with direct measurements of the ice water content (IWC) and encompassing data from polar to tropical regions, are combined to yield a large database of in situ measurements. The intention of this study is to identify strengths and weaknesses of the various methods used to derive ice cloud microphysical properties. The in situ data are measured with total water hygrometers, condensed water probes, and particle spectrometers. Data from polar, midlatitude, and tropical locations are included. The satellite data are retrieved from CloudSat/CALIPSO [the CloudSat Ice Cloud Property Product (2C-ICE) and 2C-SNOW-PROFILE] and Global Precipitation Measurement (GPM) Level2A. Although the 2C-ICE retrieval is for IWC, a method to use the IWC to get snowfall rates S is developed. The GPM retrievals are for snowfall rate only. Model results are derived using the Community Atmosphere Model (CAM5) and the Met Office Unified Model [Global Atmosphere 7 (GA7)]. The retrievals and model results are related to the in situ observations using temperature and are partitioned by geographical region. Specific variables compared between the in situ observations, models, and retrievals are the IWC and S. Satellite-retrieved IWCs are reasonably close in value to the in situ observations, whereas the models’ values are relatively low by comparison. Differences between the in situ IWCs and those from the other methods are compounded when S is considered, leading to model snowfall rates that are considerably lower than those derived from the in situ data. Anomalous trends with temperature are noted in some instances.

scholarly journals An Inverse Problem Approach for the Retrieval of Ice Particle Mass from In Situ Measurements

2017 ◽  
Vol 34 (11) ◽  
pp. 2457-2473 ◽  
Author(s):  
Pierre Coutris ◽  
Delphine Leroy ◽  
Emmanuel Fontaine ◽  
Alfons Schwarzenboeck
Keyword(s):  
Inverse Problem ◽  
Particle Size ◽  
Power Law ◽  
In Situ Measurements ◽  
Ice Cloud ◽  
Size Dependent ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
Ice Water

AbstractMass–dimensional relationships have been published for decades to characterize the microphysical properties of ice cloud particles. Classical retrieval methods employ a simplifying assumption that restricts the form of the mass–dimensional relationship to a power law, an assumption that was proved inaccurate in recent studies. In this paper, a nonstandard approach that leverages optimal use of in situ measurements to remove the power-law constraint is presented. A model formulated as a linear system of equations relating ice particle mass to particle size distribution (PSD) and ice water content (IWC) is established, and the mass retrieval process consists of solving the inverse problem with numerical optimization algorithms. First, the method is applied to a synthetic crystal dataset in order to validate the selected algorithms and to tune the regularization strategy. Subsequently, the method is applied to in situ measurements collected during the High Altitude Ice Crystal–High Ice Water Content field campaigns. Preliminary results confirm the method is efficient at retrieving size-dependent masses from real data despite a significant amount of noise: the IWC values calculated from the retrieved masses are in good agreement with reference IWC measurements (errors on the order of 10%–15%). The possibility to retrieve ice particle size–dependent masses combined with the flexibility left for sorting datasets as a function of parameters such as cloud temperature, cloud type, or convective index makes this approach well suited for studying ice cloud microphysical properties.

scholarly journals Evaluation of the Lidar–Radar Cloud Ice Water Content Retrievals Using Collocated in Situ Measurements

2015 ◽  
Vol 54 (10) ◽  
pp. 2087-2097 ◽  
Author(s):  
Sujan Khanal ◽  
Zhien Wang
Keyword(s):  
Remote Sensing ◽  
Water Content ◽  
Cloud Microphysics ◽  
In Situ Measurements ◽  
Ice Water Content ◽  
Flight Level ◽  
The Mean ◽  
Cloud Ice ◽  
Ice Water

AbstractRemote sensing and in situ measurements made during the Colorado Airborne Multiphase Cloud Study, 2010–2011 (CAMPS) with instruments aboard the University of Wyoming King Air aircraft are used to evaluate lidar–radar-retrieved cloud ice water content (IWC). The collocated remote sensing and in situ measurements provide a unique dataset for evaluation studies. Near-flight-level IWC retrieval is compared with an in situ probe: the Colorado closed-path tunable diode laser hygrometer (CLH). Statistical analysis showed that the mean radar–lidar IWC is within 26% of the mean in situ measurements for pure ice clouds and within 9% for liquid-topped mixed-phase clouds. Considering their different measurement techniques and different sample volumes, the comparison shows a statistically good agreement and is close to the measurement uncertainty of the CLH, which is around 20%. It is shown that ice cloud microphysics including ice crystal shape and orientation has a significant impact on IWC retrievals. These results indicate that the vertical profile of the retrieved lidar–radar IWC can be reliably combined with the flight-level measurements made by the in situ probes to provide a more complete picture of the cloud microphysics.

scholarly journals In-situ measurements of tropical cloud properties in the West African monsoon: upper tropospheric ice clouds, mesoscale convective system outflow, and subvisual cirrus

2011 ◽  
Vol 11 (1) ◽  
pp. 745-812 ◽  
Author(s):  
W. Frey ◽  
S. Borrmann ◽  
D. Kunkel ◽  
R. Weigel ◽  
M. de Reus ◽  
...  
Keyword(s):  
Water Content ◽  
Potential Temperature ◽  
In Situ Measurements ◽  
Size Distributions ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Ice Particles ◽  
Ice Water Content ◽  
Ice Water

Abstract. In-situ measurements of ice crystal size distributions in tropical upper troposphere/lower stratosphere (UT/LS) clouds were performed during the SCOUT-AMMA campaign over West Africa in August 2006. The cloud properties were measured with a Forward Scattering Spectrometer Probe (FSSP-100) and a Cloud Imaging Probe (CIP) operated aboard the Russian high altitude research aircraft M-55 ''Geophysica'' with the mission base in Ouagadougou, Burkina Faso. A total of 117 ice particle size distributions were obtained from the measurements in the vicinity of Mesoscale Convective Systems (MCS). Two or three modal lognormal size distributions were fitted to the average size distributions for different potential temperature bins. The measurements showed proportionate more large ice particles compared to former measurements above maritime regions. With the help of trace gas measurements of NO, NOy, CO2, CO, and O3, and satellite images clouds in young and aged MCS outflow were identified. These events were observed at altitudes of 11.0 km to 14.2 km corresponding to potential temperature levels of 346 K to 356 K. In a young outflow (developing MCS) ice crystal number concentrations of up to 8.3 cm−3 and rimed ice particles with maximum dimensions exceeding 1.5 mm were found. A maximum ice water content of 0.05 g m−3 was observed and an effective radius of about 90 μm. In contrast the aged outflow events were more diluted and showed a maximum number concentration of 0.03 cm−3, an ice water content of 2.3 × 10−4 g m−3, an effective radius of about 18 μm, while the largest particles had a maximum dimension of 61 μm. Close to the tropopause subvisual cirrus were encountered four times at altitudes of 15 km to 16.4 km. The mean ice particle number concentration of these encounters was 0.01 cm−3 with maximum particle sizes of 130 μm, and the mean ice water content was about 1.4 × 10−4 g m−3. All known in-situ measurements of subvisual tropopause cirrus are compared and an exponential fit on the size distributions is established in order to give a parameterisation for modelling. A comparison of aerosol to ice crystal number concentrations, in order to obtain an estimate on how many ice particles result from activation of the present aerosol, yielded low activation ratios for the subvisual cirrus cases of roughly one cloud particle per 30 000 aerosol particles, while for the MCS outflow cases this resulted in a high ratio of one cloud particle per 300 aerosol particles.

scholarly journals Development of a Method to Detect High Ice Water Content Environments Using Machine Learning

2020 ◽  
Vol 37 (4) ◽  
pp. 641-663
Author(s):  
Julie A. Haggerty ◽  
Allyson Rugg ◽  
Rodney Potts ◽  
Alain Protat ◽  
J. Walter Strapp ◽  
...  
Keyword(s):  
Machine Learning ◽  
False Alarm ◽  
Water Content ◽  
Field Experiments ◽  
Weather Prediction ◽  
In Situ Measurements ◽  
Probability Of Detection ◽  
Ice Water Content ◽  
Ice Water

AbstractThis paper describes development of a method for discriminating high ice water content (HIWC) conditions that can disrupt jet-engine performance in commuter and large transport aircraft. Using input data from satellites, numerical weather prediction models, and ground-based radar, this effort employs machine learning to determine optimal combinations of available information using fuzzy logic. Airborne in situ measurements of ice water content (IWC) from a series of field experiments that sampled HIWC conditions serve as training data in the machine-learning process. The resulting method, known as the Algorithm for Prediction of HIWC Areas (ALPHA), estimates the likelihood of HIWC conditions over a three-dimensional domain. Performance statistics calculated from an independent subset of data reserved for verification indicate that the ALPHA has skill for detecting HIWC conditions, albeit with significant false alarm rates. Probability of detection (POD), probability of false detection (POFD), and false alarm ratio (FAR) are 86%, 29% (60% when IWC below 0.1 g m−3 are omitted), and 51%, respectively, for one set of detection thresholds using in situ measurements. Corresponding receiver operating characteristic (ROC) curves give an area under the curve of 0.85 when considering all data and 0.69 for only points with IWC of at least 0.1 g m−3. Monte Carlo simulations suggest that aircraft sampling biases resulted in a positive POD bias and the actual probability of detection is between 78.5% and 83.1% (95% confidence interval). Analysis of individual case studies shows that the ALPHA output product generally tracks variation in the measured IWC.

scholarly journals Triple frequency radar retrieval of microphysical properties of snow

2021 ◽  
Author(s):  
Kamil Mroz ◽  
Alessandro Battaglia ◽  
Cuong Nguyen ◽  
Andrew Heymsfield ◽  
Alain Protat ◽  
...  
Keyword(s):  
Water Content ◽  
Radar Data ◽  
Characteristic Size ◽  
In Situ Data ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
Radar Measurements ◽  
Highly Correlated ◽  
Ice Water

Abstract. An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterized by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment. During this campaign in-situ microphysical probes were mounted on the same airplane as the radars. This nearly perfectly collocated dataset of the remote and in-situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content and mean-mass-weighted diameters obtaining root-mean-square-error of 0.13 and 0.15, respectively for log10 IWC and log10 Dm. The retrieval of the degree of riming is more challenging and only the algorithm that uses Doppler information obtains results that are highly correlated with the in-situ data.

scholarly journals In situ measurements of tropical cloud properties in the West African Monsoon: upper tropospheric ice clouds, Mesoscale Convective System outflow, and subvisual cirrus

2011 ◽  
Vol 11 (12) ◽  
pp. 5569-5590 ◽  
Author(s):  
W. Frey ◽  
S. Borrmann ◽  
D. Kunkel ◽  
R. Weigel ◽  
M. de Reus ◽  
...  
Keyword(s):  
Water Content ◽  
Potential Temperature ◽  
In Situ Measurements ◽  
Size Distributions ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Ice Particles ◽  
Ice Water Content ◽  
Ice Water

Abstract. In situ measurements of ice crystal size distributions in tropical upper troposphere/lower stratosphere (UT/LS) clouds were performed during the SCOUT-AMMA campaign over West Africa in August 2006. The cloud properties were measured with a Forward Scattering Spectrometer Probe (FSSP-100) and a Cloud Imaging Probe (CIP) operated aboard the Russian high altitude research aircraft M-55 Geophysica with the mission base in Ouagadougou, Burkina Faso. A total of 117 ice particle size distributions were obtained from the measurements in the vicinity of Mesoscale Convective Systems (MCS). Two to four modal lognormal size distributions were fitted to the average size distributions for different potential temperature bins. The measurements showed proportionately more large ice particles compared to former measurements above maritime regions. With the help of trace gas measurements of NO, NOy, CO2, CO, and O3 and satellite images, clouds in young and aged MCS outflow were identified. These events were observed at altitudes of 11.0 km to 14.2 km corresponding to potential temperature levels of 346 K to 356 K. In a young outflow from a developing MCS ice crystal number concentrations of up to (8.3 ± 1.6) cm−3 and rimed ice particles with maximum dimensions exceeding 1.5 mm were found. A maximum ice water content of 0.05 g m−3 was observed and an effective radius of about 90 μm. In contrast the aged outflow events were more diluted and showed a maximum number concentration of 0.03 cm−3, an ice water content of 2.3 × 10−4 g m−3, an effective radius of about 18 μm, while the largest particles had a maximum dimension of 61 μm. Close to the tropopause subvisual cirrus were encountered four times at altitudes of 15 km to 16.4 km. The mean ice particle number concentration of these encounters was 0.01 cm−3 with maximum particle sizes of 130 μm, and the mean ice water content was about 1.4 × 10−4 g m−3. All known in situ measurements of subvisual tropopause cirrus are compared and an exponential fit on the size distributions is established for modelling purposes. A comparison of aerosol to ice crystal number concentrations, in order to obtain an estimate on how many ice particles may result from activation of the present aerosol, yielded low ratios for the subvisual cirrus cases of roughly one cloud particle per 30 000 aerosol particles, while for the MCS outflow cases this resulted in a high ratio of one cloud particle per 300 aerosol particles.

scholarly journals A two-habit model for the microphysical and optical properties of ice clouds

2014 ◽  
Vol 14 (24) ◽  
pp. 13719-13737 ◽  
Author(s):  
C. Liu ◽  
P. Yang ◽  
P. Minnis ◽  
N. Loeb ◽  
S. Kato ◽  
...  
Keyword(s):  
Optical Properties ◽  
Near Infrared ◽  
Cloud Model ◽  
In Situ Measurements ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Sensing Applications ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Water

Abstract. To provide a better representation of natural ice clouds, a novel ice cloud model is developed by assuming an ice cloud to consist of an ensemble of hexagonal columns and 20-element aggregates with specific habit fractions at each particle size bin. The microphysical and optical properties of this two-habit model (THM) are compared with both laboratory and in situ measurements, and its performance in downstream satellite remote sensing applications is assessed. The ice water contents and median mass diameters calculated based on the THM closely agree with in situ measurements made during 11 field campaigns. In this study, the scattering, absorption, and polarization properties of ice crystals are calculated with a combination of the invariant imbedding T matrix, pseudo-spectral time domain, and improved geometric-optics methods over an entire practical range of particle sizes. The phase functions, calculated based on the THM, show close agreement with counterparts from laboratory and in situ measurements and from satellite-based retrievals. When the THM is applied to the retrievals of cloud microphysical and optical properties from MODIS (the Moderate Resolution Imaging Spectroradiometer) observations, excellent spectral consistency is achieved; specifically, the retrieved cloud optical thicknesses based on the visible/near infrared bands and the thermal infrared bands agree quite well. Furthermore, a comparison between the polarized reflectivities observed by the PARASOL satellite and from theoretical simulations illustrates that the THM can be used to represent ice cloud polarization properties.

scholarly journals Comparisons of in situ measurements of cirrus cloud ice water content

2007 ◽  
Vol 112 (D10) ◽  
Author(s):  
Sean M. Davis ◽  
Linnea M. Avallone ◽  
Elliot M. Weinstock ◽  
Cynthia H. Twohy ◽  
Jessica B. Smith ◽  
...  
Keyword(s):  
Water Content ◽  
In Situ Measurements ◽  
Cirrus Cloud ◽  
Ice Water Content ◽  
Cloud Ice ◽  
Ice Water

scholarly journals A two-habit model for the microphysical and optical properties of ice clouds

2014 ◽  
Vol 14 (13) ◽  
pp. 19545-19586 ◽  
Author(s):  
C. Liu ◽  
P. Yang ◽  
P. Minnis ◽  
N. Loeb ◽  
S. Kato ◽  
...  
Keyword(s):  
Optical Properties ◽  
Near Infrared ◽  
Cloud Model ◽  
In Situ Measurements ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Sensing Applications ◽  
Phase Functions ◽  
Ice Water

Abstract. To provide a better representation of natural ice clouds, a novel ice cloud model containing two particle habits is developed. The microphysical and optical properties of the two-habit model (THM) are compared with both laboratory and in situ measurements, and its performance in downstream satellite remote sensing applications is tested. The THM assumes an ice cloud to be an ensemble of hexagonal columns and twenty-element aggregates, and to have specific habit fractions at each particle size. The ice water contents and median mass diameters calculated based on the THM closely agree with in situ measurements made during 11 field campaigns. In this study, the scattering, absorption, and polarization properties of ice crystals are calculated with a combination of the invariant imbedding T-matrix, pseudo-spectral time domain, and improved geometric-optics methods over an entire range of particle sizes. The phase functions, calculated based on the THM, show excellent agreement with counterparts from laboratory and in situ measurements and from satellite retrievals. For downstream applications in the retrieval of cloud microphysical and optical properties from MODIS observations, the THM presents excellent spectral consistency; specifically, the retrieved cloud optical thicknesses based on the visible/near infrared bands and the thermal infrared bands agree quite well. Furthermore, a comparison between the polarized reflectivities observed by the PARASOL satellite and from theoretical simulations illustrates that the THM can be used to represent ice cloud polarization properties.

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