scholarly journals Comparison of Airborne In Situ, Airborne Radar–Lidar, and Spaceborne Radar–Lidar Retrievals of Polar Ice Cloud Properties Sampled during the POLARCAT Campaign

2013 ◽  
Vol 30 (1) ◽  
pp. 57-73 ◽  
Author(s):  
Julien Delanoë ◽  
Alain Protat ◽  
Olivier Jourdan ◽  
Jacques Pelon ◽  
Mathieu Papazzoni ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Process Analysis ◽  
Airborne Radar ◽  
Ice Cloud ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Surface Measurements ◽  
Ice Water ◽  
Spaceborne Radar

Abstract This study illustrates the high potential of RALI, the French airborne radar–lidar instrument, for studying cloud processes and evaluating satellite products when satellite overpasses are available. For an Arctic nimbostratus ice cloud collected on 1 April 2008 during the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport (POLARCAT) campaign, the capability of this synergistic instrument to retrieve cloud properties and to characterize the cloud phase at scales smaller than a kilometer, which is crucial for cloud process analysis, is demonstrated. A variational approach, which combines radar and lidar, is used to retrieve the ice-water content (IWC), extinction, and effective radius. The combination of radar and lidar is shown to provide better retrievals than do stand-alone methods and, in general, the radar overestimates and the lidar underestimates IWC. As the sampled ice cloud was simultaneously observed by CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellites, a new way to assess satellite cloud products by combining in situ and active remote sensing measurements is identified. It was then possible to compare RALI to three satellite ice cloud products: CloudSat, CALIPSO, and the Cloud-Aerosol-Water-Radiation Interactions (ICARE) center’s radar–lidar project (DARDAR).

Simulation of remote sensing of clouds and humidity from space using a combined platform of radar and multi-frequency microwave radiometers

2020 ◽  
Author(s):  
Jonathan Jiang ◽  
Hui Su ◽  
Qing Yue ◽  
Pekka Kangaslahti
Keyword(s):  
Remote Sensing ◽  
Effective Diameter ◽  
Cloud Particle ◽  
Ice Cloud ◽  
Cloud Properties ◽  
Thermodynamic Conditions ◽  
Ice Water Content ◽  
Microwave Radiometers ◽  
Cloud Ice ◽  
Ice Water

<p>We present a simulated simultaneous retrieval of mass mean cloud ice particle effective diameter, ice water content, water vapor, and temperature profiles using a combination of a 94-GHz cloud radar and multi-frequency (118, 183, 240, 310, 380, 664, and 850 GHz) millimeter- and submillimeter-wave radiometers from a space platform. The retrieval capabilities and uncertainties of the combined radar and microwave radiometers are quantified. We show that this combined active and passive remote sensing approach with SmallSat technologies addresses a gap in the current state-of-the-art remote sensing measurements of ice cloud properties, especially deriving vertical profiles of ice cloud particle sizes in the atmosphere together with the ambient thermodynamic conditions. Therefore, this new approach can serve as a plausible candidate for future missions that target cloud and precipitation processes to improve weather forecasts and climate predictions.  </p>

scholarly journals The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

2011 ◽  
Vol 11 (16) ◽  
pp. 8363-8384 ◽  
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
P. T. May ◽  
J. Haynes ◽  
C. Jakob ◽  
...  
Keyword(s):  
Large Scale ◽  
Effective Radius ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Mean Differences ◽  
Ice Water ◽  
Lidar Observations

Abstract. The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

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 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 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 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 < 40 cm−1, 0.1 g m−1 < IWC, and 5 dB < 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 The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

2010 ◽  
Vol 10 (8) ◽  
pp. 20069-20124
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
P. T. May ◽  
J. Haynes ◽  
C. Jakob ◽  
...  
Keyword(s):  
Large Scale ◽  
Cloud Fraction ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Mean Differences ◽  
Ice Water ◽  
Lidar Observations

Abstract. The statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness, cloud fraction as derived considering a typical large-scale model grid box), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, terminal fall speed, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden–Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The rationale for characterizing this variability is to provide an observational basis to which model outputs can be compared for the different regimes or large-scale characteristics and from which new parameterizations accounting for the large-scale context can be derived. The mean vertical variability of ice cloud occurrence and microphysical properties is large (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98% of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). Our results also indicate that, at least in the northern Australian region, the upper part of the troposphere can be split into three distinct layers characterized by different statistically-dominant microphysical processes. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is found to be large, producing mean differences of up to a factor of 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes, a factor of 3 to 4 for the ISCCP regimes and the MJO phases, and mean differences of a factor of 2 typically in all microphysical properties analysed in the present paper between large-scale atmospheric regimes or MJO phases. Large differences in occurrence (up to 60–80%) are also found in the main patterns of the cloud fraction distribution of ice clouds (fractions smaller than 0.3 and larger than 0.9). Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (almost no detectable diurnal cycle) to values in excess of 2.0 (very large diurnal amplitude).

scholarly journals The Characterization of Ice Cloud Properties from Doppler Radar Measurements

2007 ◽  
Vol 46 (10) ◽  
pp. 1682-1698 ◽  
Author(s):  
Julien Delanoë ◽  
A. Protat ◽  
D. Bouniol ◽  
Andrew Heymsfield ◽  
Aaron Bansemer ◽  
...  
Keyword(s):  
Water Content ◽  
Weather Prediction ◽  
Doppler Velocity ◽  
Fall Velocity ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Radar Measurements ◽  
Ice Water

Abstract The paper describes an original method that is complementary to the radar–lidar algorithm method to characterize ice cloud properties. The method makes use of two measurements from a Doppler cloud radar (35 or 95 GHz), namely, the radar reflectivity and the Doppler velocity, to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction from which the optical depth can be estimated. This radar method relies on the concept of scaling the ice particle size distribution. An error analysis using an extensive in situ airborne microphysical database shows that the expected errors on ice water content and extinction are around 30%–40% and 60%, respectively, including both a calibration error and a bias on the terminal fall velocity of the particles, which all translate into errors in the retrieval of the density–diameter and area–diameter relationships. Comparisons with the radar–lidar method in areas sampled by the two instruments also demonstrate the accuracy of this new method for retrieval of the cloud properties, with a roughly unbiased estimate of all cloud properties with respect to the radar–lidar method. This method is being systematically applied to the cloud radar measurements collected over the three-instrumented sites of the European Cloudnet project to validate the representation of ice clouds in numerical weather prediction models and to build a cloud climatology.

Ice cloud retrieval from high spectral resolution measurements in the thermal infrared : Application to IASI and IASI-NG

2021 ◽  
Author(s):  
Lucie Leonarski ◽  
Laurent C.-Labonnote ◽  
Mathieu Compiègne ◽  
Jérôme Vidot ◽  
Anthony J. Baran ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
Weather Forecast ◽  
Thermal Infrared ◽  
High Spectral Resolution ◽  
Ice Cloud ◽  
Clear Sky ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Passive Measurements ◽  
Ice Water

<p>Besides their strong contribution to weather forecast improvement through data assimilation in clear-sky conditions, thermal infrared sounders on board polar orbiting platforms are now playing a key role in monitoring changes in atmospheric composition. However, it is known that clear sky observations are only a small part of the entire set of measurements, the remaining part <span><span data-language-to-translate-into="fr" data-phrase-index="0">is only slightly</span></span> used as they are contaminated by either aerosols and/or clouds. Moreover, ice or liquid cloud retrieval of column and profile properties from passive and active measurements respectively help us in reaching a better understanding of climate processes. If the information provided by the latter has allowed a significant advance in our knowledge of the vertical distribution of condensed water, it suffers from spatial coverage compared to passive measurements. It is therefore fundamental to better characterize cloud properties from passive measurements by using, for example, high spectral resolution instruments such as IASI and the future IASI-NG.</p><p>An information content analysis based on Shannon's formalism has been used to determine the level and the spectral repartition of the information about the ice cloud properties in the IASI and IASI-NG spectra. Based on this analysis, we have developped and tested an algorithm which allows to retrieve from an optimal estimation approach the cloud integrated ice water content together with the cloud layer altitude. We have taken into account the Signal-to-Noise ratio of each specific instrument and the uncertainties due to the non-retrieved atmospheric and surface parameters. The forward model is the fast radiative transfer model RTTOV which has been developped for satellite data assimilation in Numerical Weather Prediction (NWP) models. The ice cloud microphysical model is based on the ensemble model of Baran and Labonnote (2007), where the bulk ice optical properties have been parametrized as a function of the ice water content (expressed in g/m³) and in cloud temperature.</p><p>The present study aims to quantify the potential and limits of thermal infrared sounders such as IASI or IASI-NG to retrieve ice cloud properties by using a representative dataset from the global operational short range forecast of the european center of medium-range weather forecast.</p>

Refinements to Ice Particle Mass Dimensional and Terminal Velocity Relationships for Ice Clouds. Part II: Evaluation and Parameterizations of Ensemble Ice Particle Sedimentation Velocities

2007 ◽  
Vol 64 (4) ◽  
pp. 1068-1088 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Gerd-Jan van Zadelhoff ◽  
David P. Donovan ◽  
Frederic Fabry ◽  
Robin J. Hogan ◽  
...  
Keyword(s):  
Climate Models ◽  
Doppler Radar ◽  
Terminal Velocity ◽  
Fall Velocity ◽  
Particle Sedimentation ◽  
Cloud Properties ◽  
Wide Range ◽  
Single Moment ◽  
Ice Water Content ◽  
Ice Water

Abstract This two-part study addresses the development of reliable estimates of the mass and fall speed of single ice particles and ensembles. Part I of the study reports temperature-dependent coefficients for the mass-dimensional relationship, m = aDb, where D is particle maximum dimension. The fall velocity relationship, Vt = ADB, is developed from observations in synoptic and low-latitude, convectively generated, ice cloud layers, sampled over a wide range of temperatures using an assumed range for the exponent b. Values for a, A, and B were found that were consistent with the measured particle size distributions (PSD) and the ice water content (IWC). To refine the estimates of coefficients a and b to fit both lower and higher moments of the PSD and the associated values for A and B, Part II uses the PSD from Part I plus coincident, vertically pointing Doppler radar returns. The observations and derived coefficients are used to evaluate earlier, single-moment, bulk ice microphysical parameterization schemes as well as to develop improved, statistically based, microphysical relationships. They may be used in cloud and climate models, and to retrieve cloud properties from ground-based Doppler radar and spaceborne, conventional radar returns.

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