Distribution Of Ice Water Content Research Articles

Using Satellite Observations to Evaluate the Relationships between Ice Condensate, Latent Heat Release, and Tropical Cyclone Intensification in a Mesoscale Model

AbstractThis study examines the relationship between frozen hydrometeors and latent heating in model simulations and evaluates the capability of the Weather Research and Forecasting (WRF) Model to reproduce the observed frozen hydrometeors and their relationship to tropical cyclone (TC) intensification. Previous modeling studies have emphasized the importance of both the amount and location of latent heating in modulating the evolution of TC intensity. However, the lack of observations limits a full understanding of its importance in the real atmosphere. Idealized simulations using WRF indicate that latent heating is strongly correlated to the amount of ice water content, suggesting that ice water content can serve as an observable proxy for latent heat release in the mid- to upper troposphere. Based on this result, satellite observations are used to create storm-centered composites of ice water path as a function of TC intensity. The model reasonably captures the vertical and horizontal distribution of ice water content and its dependence upon TC intensity, with differences typically less than 20%. The model also captures the signature of increased ice water content for intensifying TCs, suggesting that observations of ice water content provide a useful diagnostic for understanding and evaluating model simulations of TC intensification.

Combining In Situ and Satellite Observations to Understand the Vertical Structure of Tropical Anvil Cloud Microphysical Properties During the TC4 Experiment.

Tropical anvil clouds have a profound impact on Earth's weather and climate. Their role in Earth's energy balance and hydrologic cycle is heavily modulated by the vertical structure of the microphysical properties for various hydrometeors in these clouds and their dependence on the ambient environmental conditions. Accurate representations of the variability and covariability of such vertical structures are key to both the satellite remote sensing of cloud and precipitation and numerical modeling of weather and climate, which remain a challenge. This study presents a new method to combine vertically resolved observations from CloudSat radar reflectivity and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud masks with probability distributions of cloud microphysical properties and the ambient atmospheric conditions from detailed in situ measurements on tropical anvils sampled during the National Aeronautics and Space Administration TC4 (Tropical Composition, Cloud and Climate Coupling) mission. We focus on the microphysical properties of the vertical distribution of ice water content, particle size distributions, and effective sizes for different hydrometeors, including ice particles and supercooled liquid droplets. Results from this method are compared with those from in situ data alone and various CloudSat/Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud retrievals. The sampling limitation of the field experiment and algorithm limitations in the current retrievals is highlighted, especially for the liquid cloud particles, while a generally good agreement with ice cloud microphysical properties is seen from different methods. While the method presented in this study is applied to tropical anvil clouds observed during TC4, it can be readily employed to study a broad range of ice clouds sampled by various field campaigns.

Testing ice microphysics parameterizations in the NCAR Community Atmospheric Model Version 3 using Tropical Warm Pool–International Cloud Experiment data

Cloud properties have been simulated with a new double‐moment microphysics scheme under the framework of the single‐column version of NCAR Community Atmospheric Model version 3 (CAM3). For comparison, the same simulation was made with the standard single‐moment microphysics scheme of CAM3. Results from both simulations compared favorably with observations during the Tropical Warm Pool–International Cloud Experiment by the U.S. Department of Energy Atmospheric Radiation Measurement Program in terms of the temporal variation and vertical distribution of cloud fraction and cloud condensate. Major differences between the two simulations are in the magnitude and distribution of ice water content within the mixed‐phase cloud during the monsoon period, though the total frozen water (snow plus ice) contents are similar. The ice mass content in the mixed‐phase cloud from the new scheme is larger than that from the standard scheme, and ice water content extends 2 km further downward, which is in better agreement with observations. The dependence of the frozen water mass fraction on temperature from the new scheme is also in better agreement with available observations. Outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from the simulation with the new scheme is, in general, larger than that with the standard scheme, while the surface downward longwave radiation is similar. Sensitivity tests suggest that different treatments of the ice crystal effective radius contribute significantly to the difference in the calculations of TOA OLR, in addition to cloud water path. Numerical experiments show that cloud properties in the new scheme can respond reasonably to changes in the concentration of aerosols and emphasize the importance of correctly simulating aerosol effects in climate models for aerosol‐cloud interactions. Further evaluation, especially for ice cloud properties based on in situ data, is needed.

Determination of 3D Cloud Ice Water Contents by Combining Multiple Data Sources from Satellite, Ground Radar, and a Numerical Model

Abstract This study aims at determining the three-dimensional distribution of ice water content over a broad area near the Atmospheric Radiation Measurement Program Southern Great Plains site, where cloud radar and meteorological observations have been routinely conducted. Together with wind fields from other measurements, the ice water content retrievals can be used to derive the cloud ice water advective tendency terms needed for single-column model simulations. In this study, a Bayesian retrieval algorithm has been developed that combines multiple data sources from satellite high-frequency microwave radiometry, ground cloud radar observations, and mesoscale numerical model analysis. The cloud radar observations allow the characteristics of vertical ice water content structures to be inferred. The numerical model data are used to locate the cloud height. The satellite data provide information on the integrated ice water path, its horizontal distribution over a broad area, and, to a lesser extent, the vertical structure of ice water content. The approach herein is to retrieve the three-dimensional cloud ice water content in a 10° × 10° area surrounding the cloud radar site by combining all the information contained in the above datasets through a Bayesian framework. Validation of the algorithm has been done by comparing the retrievals with measurements from two ground radars. The comparison shows that the mean ice water content profiles and the two-dimensional (height–ice water content) probability density functions retrieved for 19 coincident cases agree fairly well with the validation data. However, the retrieved ice water contents generally lack detailed vertical structures because of the low sensitivity of satellite data to the vertical variation of cloud ice.

Retrievals of cloud ice water path by combining ground cloud radar and satellite high‐frequency microwave measurements near the ARM SGP site

A framework to retrieve ice water paths over a broad area by combining observations of surface cloud radar and satellite high‐frequency microwave measurements in a physically consistent way is presented. The surface cloud radar provides the statistics of vertical distribution of ice water content, while the satellite retrievals use those statistics to broaden a point measurement to an areal measurement. This study seeks to improve retrievals by adopting newly available ice microphysical properties from recent in situ observations, and by treating single scattering properties based on discrete dipole approximation simulations of realistic nonspherical ice particles. First, a new radar reflectivity‐ice water content relation is derived using backscattering cross sections calculated from six types of nonspherical ice particles. Ice water content profiles derived from radar reflectivity profiles are then used to calculate brightness temperatures at satellite observing frequencies by a radiative transfer model, which forms an a priori database for a Bayesian ice water path retrieval algorithm. Comparison between the satellite and surface radar retrievals shows that the two agree better for cases with ice water paths greater than 100 g m−2. For lower ice water paths, the difference between satellite and surface radar retrievals becomes large, presumably because of the insensitivity of the microwave scattering to optically thin ice clouds.

Multichannel Satellite Retrieval of Cloud Parameter Probability Distribution Functions

Abstract A retrieval method has been developed to directly retrieve statistics of cloud parameters from Geostationary Operational Environmental Satellite (GOES) visible and infrared imager data. This method retrieves cloud parameter probability density functions (PDFs) directly from distributions of multichannel satellite-observed radiances. For example, the joint probability distribution of ice water content and effective radius can be retrieved from a four-dimensional histogram of GOES radiances. A forward radiative transfer model creates a mapping from cloud parameter space to satellite radiance space. The cloud parameter space is described by vertically inhomogeneous liquid and ice cloud layers with variable liquid water path, effective radius, height, and thickness. A Monte Carlo procedure uses the mapping to transform probability density from the observed satellite radiance histogram, or radiance PDF, to a two-dimensional cloud property PDF. An estimate of the uncertainty in the retrieved PDF is cal...

Variability of Microphysical Parameters in High-Altitude Ice Clouds: Results of the Remote Sensing Method

Abstract The remote sensing method for retrieving vertical profiles of microphysical parameters in ice clouds from ground-based measurements taken by the Doppler radar and IR radiometer was applied to several cloud cases observed during different field experiments including FIRE-II, ASTEX, and the Arizona Program. The measurements were performed with the NOAA Environmental Technology Laboratory instrumentation. The observed ice clouds were mostly cirrus clouds located in the upper troposphere above 5.6 km. Their geometrical thicknesses varied from a few hundred meters to 3 km. Characteristic cloud particle sizes expressed in median mass diameters of equal-volume spheres varied from about 25 μm to more than 400 μm. Typically, characteristic particle sizes were increasing toward the cloud base, with the exception of the lowest range gates where particles were quickly sublimating. Highest particle concentrations were usually observed near the cloud tops. The vertical variability of particle sizes inside an individual cloud could reach one order of magnitude. The standard deviation of the mean profile for a typical cloud is usually factor of 2 or 3 smaller than mean values of particle characteristic size. Typical values of retrieved cloud ice water content varied from 1 to 100 mg m−3; however, individual variations were as high as four orders of magnitude. There was no consistent pattern in the vertical distribution of ice water content except for the rapid decrease in the vicinity of the cloud base. The relationships between retrieved cloud parameters and measured radar reflectivities were considered. The uncertainty of estimating cloud parameters from the power-law regressions is discussed. The parameters of these regressions varied from cloud to cloud and were comparable to the parameters in corresponding regressions obtained from direct particle sampling in other experiments. Relationships between cloud microphysical parameters and reflectivity can vary even for the same observational case. The variability diminishes if stronger reflectivities are considered. A procedure of “tuning” cloud microphysics–reflectivity regressions for individual profiles is suggested. Such a procedure can simplify the radar–radiometer method and make it applicable for a broader range of clouds.

Heating Rates in Tropical Anvils

The interaction of infrared and solar radiation with tropical cirrus anvils is addressed. Optical properties of the anvils are inferred from satellite observations and from high-altitude aircraft measurements. An infrared multiple-scattering model is used to compute heating rates in tropical anvils. Layer-average heating rates in 2 km thick anvils were found to be on the order of 20 to 30 K/day. The difference between heating rates at cloud bottom and cloud top ranges from 30 to 200 K/day, leading to convective instability in the anvil. The calculations are most sensitive to the assumed ice water content, but also are affected by the vertical distribution of ice water content and by the anvil thickness. Solar heating in anvils is shown to be less important than infrared heating but not negligible. The dynamical implications of the computed heating rates are also explored and it is concluded that the heating may have important consequences for upward mass transport in the tropics. The potential impact of tropical cirrus on the tropical energy balance and cloud forcing are discussed.

Determination of Cloud Ice Water Content and Geometrical Thickness Using Microwave and Infrared Radiometric Measurements

Cloud ice water content and cloud geometrical thickness have been determined using a combination of near-infrared, thermal infrared and thermal microwave radiometric measurements. The radiometric measurements are from a Multispectral Cloud Radiometer, which has seven channels ranging from visible to thermal infrared, and an Advanced Microwave Moisture Sounder, which has four channels ranging from 90 to 183 GHz. Studies indicate that the microwave brightness temperatures depend not only on the amount of ice water content but also on the vertical distribution of ice water content. Studies also show that the low brightness temperature at 92 GHz for large ice water content is due to cloud reflection which reflects most of the irradiance incident at the cloud base downward. Therefore the 92 GHz channel detects a low brightness temperature at the cloud top.