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 ◽  
...  

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.

2010 ◽  
Vol 10 (8) ◽  
pp. 20069-20124
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
P. T. May ◽  
J. Haynes ◽  
C. Jakob ◽  
...  

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).


2008 ◽  
Vol 65 (12) ◽  
pp. 4017-4031 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Paul Field ◽  
Aaron Bansemer

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.


2011 ◽  
Vol 50 (9) ◽  
pp. 1952-1969 ◽  
Author(s):  
Thorwald H. M. Stein ◽  
Julien Delanoë ◽  
Robin J. Hogan

AbstractThe A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud (penetrated only by the radar). In this paper, several versions of the VarCloud retrieval are compared with the CloudSat standard ice-only retrieval of ice water content, two empirical formulas that derive ice water content from radar reflectivity and temperature, and retrievals of vertically integrated properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) radiometer. The retrieved variables typically agree to within a factor of 2, on average, and most of the differences can be explained by the different microphysical assumptions. For example, the ice water content comparison illustrates the sensitivity of the retrievals to assumed ice particle shape. If ice particles are modeled as oblate spheroids rather than spheres for radar scattering then the retrieved ice water content is reduced by on average 50% in clouds with a reflectivity factor larger than 0 dBZ. VarCloud retrieves optical depths that are on average a factor-of-2 lower than those from MODIS, which can be explained by the different assumptions on particle mass and area; if VarCloud mimics the MODIS assumptions then better agreement is found in effective radius and optical depth is overestimated. MODIS predicts the mean vertically integrated ice water content to be around a factor-of-3 lower than that from VarCloud for the same retrievals, however, because the MODIS algorithm assumes that its retrieved effective radius (which is mostly representative of cloud top) is constant throughout the depth of the cloud. These comparisons highlight the need to refine microphysical assumptions in all retrieval algorithms and also for future studies to compare not only the mean values but also the full probability density function.


2015 ◽  
Vol 28 (9) ◽  
pp. 3880-3901 ◽  
Author(s):  
Yulan Hong ◽  
Guosheng Liu

Abstract The characteristics of ice clouds with a wide range of optical depths are studied based on satellite retrievals and radiative transfer modeling. Results show that the global-mean ice cloud optical depth, ice water path, and effective radius are approximately 2, 109 g m−2, and 48 , respectively. Ice cloud occurrence frequency varies depending not only on regions and seasons, but also on the types of ice clouds as defined by optical depth values. Ice clouds with different values show differently preferential locations on the planet; optically thinner ones ( < 3) are most frequently observed in the tropics around 15 km and in midlatitudes below 5 km, while thicker ones ( > 3) occur frequently in tropical convective areas and along midlatitude storm tracks. It is also found that ice water content and effective radius show different temperature dependence among the tropics, midlatitudes, and high latitudes. Based on analyzed ice cloud frequencies and microphysical properties, cloud radiative forcing is evaluated using a radiative transfer model. The results show that globally radiative forcing due to ice clouds introduces a net warming of the earth–atmosphere system. Those with < 4.0 all have a positive (warming) net forcing with the largest contribution by ice clouds with ~ 1.2. Regionally, ice clouds in high latitudes show a warming effect throughout the year, while they cause cooling during warm seasons but warming during cold seasons in midlatitudes. Ice cloud properties revealed in this study enhance the understanding of ice cloud climatology and can be used for validating climate models.


2018 ◽  
Author(s):  
Quitterie Cazenave ◽  
Marie Ceccaldi ◽  
Julien Delanoë ◽  
Jacques Pelon ◽  
Silke Groß ◽  
...  

Abstract. In this paper we present the latest refinements brought to the DARDAR-CLOUD product, which contains ice cloud microphysical properties retrieved from the cloud radar and lidar measurements from the A-Train mission. Based on a large dataset of in-situ ice cloud measurements collected during several campaigns performed between 2000 and 2007 in different regions of the globe, the parameterizations used in the microphysical model of the algorithm were assessed and refined to 5 better fit the measurements, keeping the same formalism as proposed in DARDAR basis papers. It is shown that these changes can affect the ice water content retrievals by up to 50 %, with, globally, a reduction of the ice water content and ice water path. In parallel, the retrieved effective radii increase between 5 % and 40 %. The largest differences are found for the warmest temperatures (between −20 °C and 0 °C) in regions where the cloud microphysical processes are more complex and where the retrieval is almost exclusively based on radar-only measurements. In regions where lidar measurements are available, the lidar 10 ratio retrieved for ice clouds is shown to be well constrained by lidar-radar combination or molecular signal detected below thin semi-transparent cirrus. Using this information, the parameterization of the lidar ratio was refined and the new retrieval equals on average 35 sr ± 10 sr in the temperature range between −60 °C and −20 °C.


2017 ◽  
Vol 34 (11) ◽  
pp. 2457-2473 ◽  
Author(s):  
Pierre Coutris ◽  
Delphine Leroy ◽  
Emmanuel Fontaine ◽  
Alfons Schwarzenboeck

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.


2017 ◽  
Vol 17 (7) ◽  
pp. 4731-4749 ◽  
Author(s):  
Chenglai Wu ◽  
Xiaohong Liu ◽  
Minghui Diao ◽  
Kai Zhang ◽  
Andrew Gettelman ◽  
...  

Abstract. In this study we evaluate cloud properties simulated by the Community Atmosphere Model version 5 (CAM5) using in situ measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign for the period of 2009 to 2011. The modeled wind and temperature are nudged towards reanalysis. Model results collocated with HIPPO flight tracks are directly compared with the observations, and model sensitivities to the representations of ice nucleation and growth are also examined. Generally, CAM5 is able to capture specific cloud systems in terms of vertical configuration and horizontal extension. In total, the model reproduces 79.8 % of observed cloud occurrences inside model grid boxes and even higher (94.3 %) for ice clouds (T ≤ −40 °C). The missing cloud occurrences in the model are primarily ascribed to the fact that the model cannot account for the high spatial variability of observed relative humidity (RH). Furthermore, model RH biases are mostly attributed to the discrepancies in water vapor, rather than temperature. At the micro-scale of ice clouds, the model captures the observed increase of ice crystal mean sizes with temperature, albeit with smaller sizes than the observations. The model underestimates the observed ice number concentration (Ni) and ice water content (IWC) for ice crystals larger than 75 µm in diameter. Modeled IWC and Ni are more sensitive to the threshold diameter for autoconversion of cloud ice to snow (Dcs), while simulated ice crystal mean size is more sensitive to ice nucleation parameterizations than to Dcs. Our results highlight the need for further improvements to the sub-grid RH variability and ice nucleation and growth in the model.


2007 ◽  
Vol 46 (3) ◽  
pp. 249-272 ◽  
Author(s):  
M. Chiriaco ◽  
H. Chepfer ◽  
P. Minnis ◽  
M. Haeffelin ◽  
S. Platnick ◽  
...  

Abstract This study compares cirrus-cloud properties and, in particular, particle effective radius retrieved by a Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-like method with two similar methods using Moderate-Resolution Imaging Spectroradiometer (MODIS), MODIS Airborne Simulator (MAS), and Geostationary Operational Environmental Satellite imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands to infer the microphysical properties of cirrus clouds. The two other methods, using passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (using 20 spectral bands from visible to infrared, referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the Clouds and the Earth’s Radiant Energy System (CERES) team at Langley Research Center (LaRC) in support of CERES algorithms (using 0.65-, 3.75-, 10.8-, and 12.05-μm bands); the two algorithms will be referred to as the MOD06 and LaRC methods, respectively. The three techniques are compared at two different latitudes. The midlatitude ice-clouds study uses 16 days of observations at the Palaiseau ground-based site in France [Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA)], including a ground-based 532-nm lidar and the MODIS overpasses on the Terra platform. The tropical ice-clouds study uses 14 different flight legs of observations collected in Florida during the intensive field experiment known as the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE), including the airborne cloud-physics lidar and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote sensing method (CALIPSO like) for the study of subvisible ice clouds, in both the midlatitudes and Tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds, because of their particular microphysical properties.


2013 ◽  
Vol 30 (11) ◽  
pp. 2527-2553 ◽  
Author(s):  
A. V. Korolev ◽  
E. F. Emery ◽  
J. W. Strapp ◽  
S. G. Cober ◽  
G. A. Isaac

Abstract Ice particle shattering poses a serious problem to the airborne characterization of ice cloud microstructure. Shattered ice fragments may contaminate particle measurements, resulting in artificially high concentrations of small ice. The ubiquitous observation of small ice particles has been debated over the last three decades. The present work is focused on the study of the effect of shattering based on the results of the Airborne Icing Instrumentation Evaluation (AIIE) experiment flight campaign. Quantitative characterization of the shattering effect was studied by comparing measurements from pairs of identical probes, one modified to mitigate shattering using tips designed for this study (K-tips) and the other in the standard manufacturer’s configuration. The study focused on three probes: the forward scattering spectrometer probe (FSSP), the optical array probe (OAP-2DC), and the cloud imaging probe (CIP). It has been shown that the overestimation errors of the number concentration in size distributions measured by 2D probes increase with decreasing size, mainly affecting particles smaller than approximately 500 μm. It was found that shattering artifacts may increase measured particle number concentration by 1 to 2 orders of magnitude. However, the associated increase of the extinction coefficient and ice water content derived from 2D data is estimated at only 20%–30%. Existing antishattering algorithms alone are incapable of filtering out all shattering artifacts from OAP-2DC and CIP measurements. FSSP measurements can be completely dominated by shattering artifacts, and it is not recommended to use this instrument for measurements in ice clouds, except in special circumstances. Because of the large impact of shattering on ice measurements, the historical data collected by FSSP and OAP-2DC should be reexamined by the cloud physics community.


2010 ◽  
Vol 10 (10) ◽  
pp. 23091-23108 ◽  
Author(s):  
J. H. Jiang ◽  
H. Su ◽  
C. Zhai ◽  
S. T. Massie ◽  
M. R. Schoeberl ◽  
...  

Abstract. Satellite observations show that ice cloud effective radius (re) increases with ice water content (IWC) but decreases with aerosol optical thickness (AOT). Using least-squares fitting to the observed data, we obtain an analytical formula to describe the variations of re with IWC and AOT for several regions with distinct characteristics of re-IWC-AOT relationships. As IWC directly relates to convective strength and AOT represents aerosol loading, our empirical formula provides a means to quantify the relative roles of dynamics and aerosols in controlling re in different geographical regions, and to establish a framework for parameterization of aerosol effects on re in climate models.


Sign in / Sign up

Export Citation Format

Share Document