Profiles Of Ice Water Content Research Articles

An intercomparison of EarthCARE cloud, aerosol, and precipitation retrieval products

Abstract. The objective of the Earth Cloud, Aerosol, and Radiation Explorer (EarthCARE) mission is to infer attributes of cloud, aerosol, precipitation, and radiation from observations made by four complementary instruments. This requires the development of single-instrument and multiple-instrument (i.e. synergistic) retrieval algorithms that employ measurements made by one, or more, of EarthCARE's cloud-profiling radar (CPR), atmospheric lidar (ATLID), and multi-spectral imager (MSI); its broadband radiometer (BBR) places the retrieved quantities in the context of the surface–atmosphere radiation budget. To facilitate the development and evaluation of ESA's EarthCARE production model prior to launch, sophisticated instrument simulators were developed to produce realistic synthetic EarthCARE measurements for simulated conditions provided by cloud-resolving models. While acknowledging that the physical and radiative representations of cloud, aerosol, and precipitation in the test scenes are based on numerical models, the opportunity to perform detailed evaluations wherein the “truth” is known provides insights into the performance of EarthCARE's instruments and retrieval algorithms. This level of omniscience will not be available for the evaluation of in-flight EarthCARE retrieval products, even during validation activities coordinated with ground-based and airborne measurements. In this study, we compare EarthCARE retrieval products both statistically across all simulated scenes and from a specific time series from a single scene. For ice clouds, it is shown that retrieved profiles of ice water content and effective particle size made by the ATLID-CPR-MSI cloud, aerosols, and precipitation (ACM-CAP) synergistic algorithm are consistently more accurate than those from its single-instrument counterparts. While liquid clouds are often difficult to detect from satellite-borne sensors, especially for multi-layered clouds, ACM-CAP benefits from combined constraints from lidar backscatter, solar radiances, and radar-path-integrated attenuation but still exhibits non-trivial random error. For precipitation retrievals, the CPR cloud and precipitation product (C-CLD) and ACM-CAP have a similar performance when well-constrained by CPR measurements. The greatest differences are in coverage, with ACM-CAP reporting retrievals in the melting layer, and in heavy precipitation, where CPR signals are dominated by multiple scattering and attenuation. Aerosol retrievals from ATLID compensate for a high degree of measurement noise in a number of ways, with the ATLID extinction, backscatter, and depolarisation (A-EBD) product and ACM-CAP demonstrating similar performance. The multi-spectral imager (MSI) cloud optical properties (M-COP) product performs very well for unambiguous cloud layers. Similarly, the MSI aerosol optical thickness (M-AOT) product performs well when radiances are unaffected by cloud, but both products provide little information about vertical profiles of properties. Finally, a summary of the performance of all retrieval products and their random errors is provided.

Synergistic Retrievals of Ice in High Clouds from Elastic Backscatter Lidar, Ku-Band Radar, and Submillimeter Wave Radiometer Observations

Abstract In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and submillimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of ice water content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments (frequencies, sensitivities, etc.) are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-means clustering algorithm. In the second step, the IWC profile is estimated using an ensemble Kalman smoother algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.

Demonstration of a Nowcasting Service for High Ice Water Content (HIWC) Conditions

Areas of high ice water content (HIWC) within cloud systems may cause power loss events and engine damage in jet aircraft due to ice crystal icing (ICI). The Algorithm for Prediction of HIWC Areas (ALPHA) was developed to identify these regions and enable provision of guidance to airlines. ALPHA combines numerical weather prediction model data, satellite data, and radar data (where available), and applies fuzzy logic to identify the likely presence of HIWC. In a collaboration between the U.S. National Center for Atmospheric Research, Australian Bureau of Meteorology, U.S. Federal Aviation Administration, and Australian airlines, a trial of ALPHA was conducted for an area across Indonesia, Papua New Guinea (PNG), and northern Australia, a region with frequent deep convection and a relatively high incidence of ICI events. ALPHA was adapted to ingest data from the Australian Community Climate and Earth System Simulator model and the Japanese Himawari-8 geostationary meteorological satellite. Radar data was not used. The HIWC product was made available to stakeholder groups for evaluation. Independent validation of the HIWC product was undertaken by comparing it with retrieved profiles of ice water content (IWC) from the cloud profiling radar on the NASA polar-orbiting CloudSat satellite. Conduct of the ALPHA trial and results from validation of the HIWC product provides confidence in the potential utility for flight planning, maintaining situational awareness, and flight monitoring.

Investigating the radiative effect of Arctic cirrus measured in situ during the winter 2015–2016

Abstract. The radiative energy budget in the Arctic undergoes a rapid transformation compared with global mean changes. Understanding the role of cirrus clouds in this system is vital, as they interact with short- and long-wave radiation, and the presence of cirrus can be decisive as to a net gain or loss of radiative energy in the polar atmosphere. In an effort to derive the radiative properties of cirrus in a real scenario in this sensitive region, we use in situ measurements of the ice water content (IWC) performed during the Polar Stratosphere in a Changing Climate (POLSTRACC) aircraft campaign in the boreal winter and spring 2015–2016 employing the German High Altitude and Long Range Research Aircraft (HALO). A large dataset of IWC measurements of mostly thin cirrus at high northern latitudes was collected in the upper troposphere and also frequently in the lowermost stratosphere. From this dataset, we select vertical profiles that sampled the complete vertical extent of cirrus cloud layers. These profiles exhibit a vertical IWC structure that will be shown to control the instantaneous radiative effect in both the long and short wavelength regimes in the polar winter. We perform radiative transfer calculations with the uvspec model from the libRadtran software package in a one-dimensional column between the surface and the top of the atmosphere (TOA), using the IWC profiles as well as the state of the atmospheric column at the time of measurement, as given by weather forecast products, as input. In parameter studies, we vary the surface albedo and solar zenith angle in ranges typical of the Arctic region. We find the strongest (positive) radiative forcing up to about 48 W m−2 for cirrus over bright snow, whereas the forcing is mostly weaker and even ambiguous, with a rather symmetric range of values down to -35Wm-2, over the open ocean in winter and spring. The IWC structure over several kilometres in the vertical affects the irradiance at the TOA via the distribution of optical thickness. We show the extent to which IWC profiles with a coarser vertical resolution can reflect this effect. Further, a highly variable heating rate profile within the cloud is found which drives dynamical processes and contributes to the thermal stratification at the tropopause. Our case studies highlight the importance of a detailed resolution of cirrus clouds and the consideration of surface albedo for estimations of the radiative energy budget in the Arctic.

Climatology of the Vertical Profiles of Polarimetric Radar Variables and Retrieved Microphysical Parameters in Continental/Tropical MCSs and Landfalling Hurricanes

AbstractMost existing cloud models tend to overestimate the size of cloud ice particles and underestimate their concentration. This emphasizes the need to provide a reliable observational reference to optimize cloud model performance, particularly in areas of high concentration of ice at high altitudes. The dual‐polarization radars give the community a unique opportunity to quantify cloud ice with a good accuracy using polarimetric radar retrievals. In this study, we utilize the network of operational WSR‐88D radars to build a climatology of the vertical profiles of radar variables, such as radar reflectivity Z, differential reflectivity ZDR, and specific differential phase KDP as well as the radar‐retrieved vertical profiles of ice water content (IWC) above the melting layer and liquid water content below it, mean volume diameter Dm, and total number concentration Nt of ice and liquid particles. Such climatology was created for continental/marine mesoscale convective systems (MCSs) and tropical cyclones including hurricanes. The dataset includes 13 continental MCSs, 10 marine MCSs, and 11 tropical cyclones. Separate statistics of the “background” vertical profiles and the ones associated with high IWC aloft have been obtained in the course of this study. It is shown that continental MCSs exhibit larger size of ice in lower concentration aloft compared to the marine MCSs and especially tropical cyclones/hurricanes. A combination of high KDP and low Z aloft signifies lower Dm, higher Nt, and often substantial IWC.

Assessing synergistic radar and radiometer capability in retrieving ice cloud microphysics based on hybrid Bayesian algorithms

Abstract. The 2017 National Academy of Sciences Decadal Survey highlighted several high-priority objectives to be pursued in the decadal timeframe, and the next-generation Cloud, Convection and Precipitation (CCP) observing system is thereby contemplated. In this study, we develop a suite of hybrid Bayesian algorithms to evaluate two CCP remote sensor candidates including a W-band cloud radar and a (sub)millimeter-wave radiometer with channels in the 118–880 GHz frequency range for capability in constraining ice cloud microphysical quantities. The algorithms address active-only, passive-only, and synergistic active–passive retrievals. The hybrid Bayesian algorithms combine the Bayesian Monte Carlo integration and optimization process to retrieve quantities with uncertainty estimates. The radar-only retrievals employ the optimal estimation methodology, while the radiometer-involved retrievals employ ensemble approaches to maximize the posterior probability density function. A priori information is obtained from the Tropical Composition, Cloud and Climate Coupling (TC4) in situ data and CloudSat radar observations. End-to-end simulation experiments are conducted to evaluate the retrieval accuracies by comparing the retrieved parameters with known values. The experiment results suggest that the radiometer measurements possess high sensitivity to ice cloud particles with large water content. The radar-only retrievals demonstrate capability in reproducing ice water content profiles, but the performance in retrieving number concentration is poor. The synergistic observations enable improved pixel-level retrieval accuracies, and the improvements in ice water path retrievals are significant. The proposed retrieval algorithms could serve as alternative methods for exploring the synergistic active and passive concept, and the algorithm framework could be extended to the inclusion of other remote sensors to further assess the CCP observing system in future studies.

Sensing Horizontally Oriented Frozen Particles With Polarimetric Radio Occultations Aboard PAZ: Validation Using GMI Coincident Observations and Cloudsat a Priori Information

The sensitivity of PAZ’s Polarimetric Radio Occultation (PRO) observations to horizontally oriented frozen particles is assessed using coincident measurements from the Global Precipitation Measurement (GPM) core satellite’s radiometer GPM Microwave Imager (GMI) and ancillary information from Cloudsat. The difference between the horizontal and vertical polarizations of the GMI observed radiances at 166 GHz, indicative of horizontally oriented particles, is compared with the PAZ differential phase shift observations. A clear positive trend is observed, exhibiting a good correlation between the two observations. The radiometer absolute observations and polarization differences (PD) are then used to build a lookup table of ice water content (IWC) vertical profiles, using coincident observations between GPM and Cloudsat. The vertical profiles of IWC, along with the information of the radiometric PDs and some simple assumptions, are used to simulate the expected PAZ differential phase shift observations. The validation with the PAZ and GPM coincident measurements shows a high correlation between the simulated and observed differential phase shift, therefore proving the sensitivity of polarimetric radio occultations to horizontally oriented frozen particles. These results demonstrate that PRO can not only sense the precipitation near the surface (the original goal of the mission) but also the frozen particles near and well above the freezing level, providing additional detail of the cloud vertical structure.

Properties of Arctic liquid and mixed-phase clouds from shipborne Cloudnet observations during ACSE 2014

Abstract. This study presents Cloudnet retrievals of Arctic clouds from measurements conducted during a 3-month research expedition along the Siberian shelf during summer and autumn 2014. During autumn, we find a strong reduction in the occurrence of liquid clouds and an increase for both mixed-phase and ice clouds at low levels compared to summer. About 80 % of all liquid clouds observed during the research cruise show a liquid water path below the infrared black body limit of approximately 50 g m−2. The majority of mixed-phase and ice clouds had an ice water path below 20 g m−2. Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. Changes in these parameters have little effect on the geometric thickness of liquid clouds while mixed-phase clouds during warm-air advection events are generally thinner than when such events were absent. Cloud-top temperatures are very similar for all mixed-phase clouds. However, more cases of lower cloud-top temperature were observed in the absence of warm-air advection. Profiles of liquid and ice water content are normalized with respect to cloud base and height. For liquid water clouds, the liquid water content profile reveals a strong increase with height with a maximum within the upper quarter of the clouds followed by a sharp decrease towards cloud top. Liquid water content is lowest for clouds observed below an inversion during warm-air advection events. Most mixed-phase clouds show a liquid water content profile with a very similar shape to that of liquid clouds but with lower maximum values during events with warm air above the planetary boundary layer. The normalized ice water content profiles in mixed-phase clouds look different from those of liquid water content. They show a wider range in maximum values with the lowest ice water content for clouds below an inversion and the highest values for clouds above or extending through an inversion. The ice water content profile generally peaks at a height below the peak in the liquid water content profile – usually in the centre of the cloud, sometimes closer to cloud base, likely due to particle sublimation as the crystals fall through the cloud.

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

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.

Vertical Profiles of Ice Cloud Microphysical Properties and Their Impacts on Cloud Retrieval Using Thermal Infrared Measurements

AbstractDespite the vertically inhomogeneous (VIH) structure of ice clouds, current passive remote sensing methods assume plane‐parallel homogeneous (PPH) layers, which can lead to retrieval errors. An adequate VIH cloud model is required to improve retrieval performance. In this study, CloudSat and CALIPSO satellite measurements in a 1‐year period were analyzed to model cloud vertical inhomogeneity, and its impacts on cloud retrieval were assessed using thermal infrared (TIR) measurements. The satellite measurements revealed that the peak ice water content (IWC) located around the cloud vertical midpoint moved toward the cloud base as the ice water path (IWP) increased in clouds with small IWP values; thicker clouds exhibited a gradual shift in IWC peak location toward the cloud top as IWP increased. The vertical profiles of both the cloud‐particle effective radius (CER) and a proxy of cloud‐particle number concentration showed close associations with the vertical IWC profile. An empirical model linking cloud geometrical thickness to columnar optical properties (IWP and column‐mean CER) as a function of cloud‐top temperature was also proposed. Compared with a model assuming PPH clouds, the VIH cloud model improved retrieval performance by reducing the retrieval error of the TIR‐based passive remote sensing algorithm. Further, by increasing the retrieved values of cloud‐top height noticeably for high‐level clouds and column‐mean CER considerably, with minimal effects on cloud optical thickness retrieval, the VIH cloud model yielded results that were in better agreement with radar/lidar ice cloud products than those obtained under the assumption of PPH cloud layers.

Lapse rate characteristics in ice clouds inferred from GPS RO and CloudSat observations

GPS Radio Occultation (RO) cloudy profiles during a seven-year period from 2007 to 2013 over the globe are firstly selected and grouped into four types of ice clouds (e.g., nimbostratus, deep convective, cirrus, altostratus) based on collocated CloudSat data. Vertical temperature profiles within ice clouds below −20°C are then retrieved from GPS RO refractivity observations, in which the vertical profiles of ice water content required by the forward model of refractivity are obtained from CloudSat retrievals of ice water content. Vertical distributions of relative humidity and lapse rate within clouds are finally examined in terms of their occurrences, mean values and standard deviations. It is found that ice clouds have preferred values of relative humidity and lapse rate depending on cloud types and altitudes. Most altostratus ice clouds are located between 4 and 8km with relative humidity between 55 and 75%. The cirrus clouds have a relative humidity around 60% and are located mostly above 6km to as high as 13km. Difference from cirrus and altostratus ice clouds, nimbostratus ice clouds that occur mostly in polar regions are found at all altitudes below 10km with a relative humidity decreasing linearly from about 90% near the surface to about 60% around 6km. Within deep convective ice clouds, the relative humidity also decreases linearly from about 100% around 2.5km to about 60% around 9km. The lapse rate slightly increases with altitude and its value ranges between 5 and 8°Ckm−1 within nimbostratus, deep convective and altostratus ice clouds. The lapse rate within cirrus clouds varies from 6°Ckm−1 to 9°Ckm−1. Vertical variations of the lapse rate derived from GPS RO cloudy retrievals compared favorably to those derived from radiosonde profiles. Both showed that the mean lapse rate increases with altitude from about 5°Ckm−1 around 3km to about 7°Ckm−1 around 7km, and the standard deviations are much smaller than the mean lapse rate.

Changes in the shape of cloud ice water content vertical structure due to aerosol variations

Abstract. Changes in the shape of cloud ice water content (IWC) vertical structure due to variations in Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depths (AODs), Ozone Monitoring Instrument (OMI) absorptive aerosol optical depths (AAODs), and Microwave Limb Sounder (MLS) CO (an absorptive aerosol proxy) at 215 hPa are calculated in the Tropics during 2007–2010 based upon an analysis of DARDAR IWC profiles for deep convective clouds. DARDAR profiles are a joint retrieval of CloudSat-CALIPSO data. Analysis is performed for 12 separate regions over land and ocean, and carried out applying MODIS AOD fields that attempt to correct for 3-D cloud adjacency effects. The 3-D cloud adjacency effects have a small impact upon our particular calculations of aerosol–cloud indirect effects. IWC profiles are averaged for three AOD bins individually for the 12 regions. The IWC average profiles are also normalized to unity at 5 km altitude in order to study changes in the shape of the average IWC profiles as AOD increases. Derivatives of the IWC average profiles, and derivatives of the IWC shape profiles, in percent change per 0.1 change in MODIS AOD units, are calculated separately for each region. Means of altitude-specific probability distribution functions, which include both ocean and land IWC shape regional derivatives, are modest, near 5 %, and positive to the 2σ level between 11 and 15 km altitude. Similar analyses are carried out for three AAOD and three CO bins. On average, the vertical profiles of the means of the derivatives based upon the profile shapes over land and ocean are smaller for the profiles binned according to AAOD and CO values, than for the MODIS AODs, which include both scattering and absorptive aerosol. This difference in character supports the assertion that absorptive aerosol can inhibit cloud development.

Ice water content vertical profiles of high-level clouds: classification and impact on radiative fluxes

Abstract. In this article, we discuss the shape of ice water content (IWC) vertical profiles in high ice clouds and its effect on their radiative properties, both in short- and in long-wave bands (SW and LW). Based on the analysis of collocated satellite data, we propose a minimal set of primitive shapes (rectangular, isosceles trapezoid, lower and upper triangle), which represents the IWC profiles sufficiently well. About 75 % of all high-level ice clouds (P < 440 hPa) have an ice water path (IWP) smaller than 100 g m−2, with a 10 % smaller contribution from single layer clouds. Most IWC profiles (80 %) can be represented by a rectangular or isosceles trapezoid shape. However, with increasing IWP, the number of lower triangle profiles (IWC rises towards cloud base) increases, reaching up to 40 % for IWP values greater than 300 g m−2. The number of upper triangle profiles (IWC rises towards cloud top) is in general small and decreases with IWP, with the maximum occurrence of 15 % in cases of IWP less than 10 g m−2. We propose a statistical classification of the IWC shapes using IWP as a single parameter. We have estimated the radiative effects of clouds with the same IWP and with different IWC profile shapes for five typical atmospheric scenarios and over a broad range of IWP, cloud height, cloud vertical extent, and effective ice crystal diameter (De). We explain changes in outgoing LW fluxes at the top of the atmosphere (TOA) by the cloud thermal radiance while differences in TOA SW fluxes relate to the De vertical profile within the cloud. Absolute differences in net TOA and surface fluxes associated with these parameterized IWC profiles instead of assuming constant IWC profiles are in general of the order of 1–2 W m−2: they are negligible for clouds with IWP < 30 g m−2, but may reach 2 W m−2 for clouds with IWP > 300 W m−2.

Synergistic multi-sensor and multi-frequency retrieval of cloud ice water path constrained by CloudSat collocations

The cloud ice water path (IWP) is one of the major parameters that have a strong influence on earth׳s radiation budget. Onboard satellite sensors are recognized as valuable tools to measure the IWP in a global scale. Albeit, active sensors such as the Cloud Profiling Radar (CPR) onboard the CloudSat satellite has better capability to measure the ice water content profile, thus, its vertical integral, IWP, than any passive microwave (MW) or infrared (IR) sensors. In this study, we investigate the retrieval of IWP from MW and IR sensors, including AMSU-A, MHS, and HIRS instruments on-board the N19 satellite, such that the retrieval is consistent with the CloudSat IWP estimates. This is achieved through the collocations between the passive satellite measurements and CloudSat scenes. Potential benefit of synergistic multi-sensor multi-frequency retrieval is investigated. Two modeling approaches are explored for the IWP retrieval – generalized linear model (GLM) and neural network (NN). The investigation has been carried out over both ocean and land surface types. The MW/IR synergy is found to be retrieved more accurate IWP than the individual AMSU-A, MHS, or HIRS measurements. Both GLM and NN approaches have been able to exploit the synergistic retrievals.

Vertical structure of ice cloud layers from CloudSat and CALIPSO measurements and comparison to NICAM simulations

AbstractThe shape of the vertical profile of ice cloud layers is examined using 4 months of CloudSat and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) global measurements taken on January, April, July, and October 2007. Ice clouds are selected using temperature profiles when the cloud base is located above the 253 K temperature level. The obtained ice water content (IWC), effective radius, or extinction coefficient profiles are normalized by their layer mean values and are expressed in the normalized vertical coordinate, which is defined as 0 and 1 at the cloud base and top heights, respectively. Both CloudSat and CALIPSO observations show that the maximum in the IWC and extinction profiles shifts toward the cloud bottom, as the cloud depth increases. In addition, clouds with a base reaching the surface in a high‐latitude region show that the maximum peak of the IWC and extinction profiles occurs near the surface, which is presumably due to snow precipitation. CloudSat measurements show that the seasonal difference in normalized cloud vertical profiles is not significant, whereas the normalized cloud vertical profile significantly varies depending on the cloud type and the presence of precipitation. It is further examined if the 7 day Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulation results from 25 December 2006 to 1 January 2007 generate similar cloud profile shapes. NICAM IWC profiles also show maximum peaks near the cloud bottom for thick cloud layers and maximum peaks at the cloud bottom for low‐level clouds near the surface. It is inferred that oversized snow particles in the NICAM cloud scheme produce a more vertically inhomogeneous IWC profile than observations due to quick sedimentation.

Impacts of Ice Clouds on GPS Radio Occultation Measurements

Abstract Mathematical solutions accounting for the effects of liquid and ice clouds on the propagation of the GPS radio signals are first derived. The percentage contribution of ice water content (IWC) to the total refractivity increases linearly with the amount of IWC at a rate of 0.6 (g m−3)−1. Measurements of coincident profiles of IWC from CloudSat in deep convection during 2007–10 are then used for estimating the ice-scattering effects on GPS radio occultation (RO) measurements from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC). The percentage contribution of IWC to the total refractivity from CloudSat measurements is consistent with the theoretical model, reaching about 0.6% at 1 g m−3 IWC. The GPS RO refractivity observations in deep convective clouds are found to be systematically greater than the refractivity calculated from the ECMWF analysis. The fractional N bias (GPS minus ECMWF) can be as high as 1.8% within deep convective clouds. Compared with ECMWF analysis, the GPS RO retrievals have a negative temperature bias and a positive water vapor bias, which is consistent with a positive bias in refractivity. The relative humidity calculated from GPS retrievals is usually as high as 80%–90% right above the 0°C temperature level in deep convection and is about 15%–30% higher than the ECMWF analysis. The majority of the data points in deep convection are located on the negative side of temperature differences and the positive side of relative humidity differences between GPS RO retrievals and ECMWF analysis.

Ice hydrometeor profile retrieval algorithm for high-frequency microwave radiometers: application to the CoSSIR instrument during TC4

Abstract. A Bayesian algorithm to retrieve profiles of cloud ice water content (IWC), ice particle size (Dme), and relative humidity from millimeter-wave/submillimeter-wave radiometers is presented. The first part of the algorithm prepares an a priori file with cumulative distribution functions (CDFs) and empirical orthogonal functions (EOFs) of profiles of temperature, relative humidity, three ice particle parameters (IWC, Dme, distribution width), and two liquid cloud parameters. The a priori CDFs and EOFs are derived from CloudSat radar reflectivity profiles and associated ECMWF temperature and relative humidity profiles combined with three cloud microphysical probability distributions obtained from in situ cloud probes. The second part of the algorithm uses the CDF/EOF file to perform a Bayesian retrieval with a hybrid technique that uses Monte Carlo integration (MCI) or, when too few MCI cases match the observations, uses optimization to maximize the posterior probability function. The very computationally intensive Markov chain Monte Carlo (MCMC) method also may be chosen as a solution method. The radiative transfer model assumes mixtures of several shapes of randomly oriented ice particles, and here random aggregates of spheres, dendrites, and hexagonal plates are used for tropical convection. A new physical model of stochastic dendritic snowflake aggregation is developed. The retrieval algorithm is applied to data from the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) flown on the ER-2 aircraft during the Tropical Composition, Cloud and Climate Coupling (TC4) experiment in 2007. Example retrievals with error bars are shown for nadir profiles of IWC, Dme, and relative humidity, and nadir and conical scan swath retrievals of ice water path and average Dme. The ice cloud retrievals are evaluated by retrieving integrated 94 GHz backscattering from CoSSIR for comparison with the Cloud Radar System (CRS) flown on the same aircraft. The rms difference in integrated backscattering is around 3 dB over a 30 dB range. A comparison of CoSSIR retrieved and CRS measured reflectivity shows that CoSSIR has the ability to retrieve low-resolution ice cloud profiles in the upper troposphere.

Simulating the equivalent radar reflectivity of cirrus at 94 GHz using an ensemble model of cirrus ice crystals: a test of the Met Office global numerical weather prediction model

AbstractIn this paper an ensemble model of ice crystals previously used to simulate the short‐wave scattering properties of cirrus is now applied to simulate its equivalent radar reflectivity (Ze) at 94 GHz. It is shown that the ensemble model conserves the mass of aggregating ice crystals when compared against in situ derived mass‐dimensional (m‐D) relationships. The ensemble model derived m‐D relationship is applied to the Rayleigh–Gans approximation to obtain a new parametrized radar reflectivity forward model for general circulation models (GCMs). The derived forward model is parametrized as a function of ice mixing ratio and in‐cloud temperature, and it is shown that the forward model error is generally well within ±2 dBZe using a linear fit; this new parametrization negates the need for an ‘effective diameter’.The Met Office Unified global Model (MetUM) predictions of ice water content (IWC) and Ze are compared against profiled in situ microphysical probe estimates of IWC and Ze, based on in situ estimates. The in situ IWC profiles were obtained from a midlatitude cirrus case during an airborne campaign around the UK. The paper demonstrates that towards cloud‐bottom and cloud‐top the MetUM prediction of IWC is generally within and outside the experimental uncertainty, respectively. The MetUM forward simulation of Ze assumes two particle size distributions (PSDs) of differing shapes and it is shown that the broader PSD simulates Ze better when compared against Ze based on in situ estimates for all altitudes. For the same case the PSD assumed in the CloudSat retrieval of IWC is also investigated and it is speculated that it could be too narrow towards cloud‐bottom. The paper demonstrates the need for consistent PSDs when forward modelling Ze at 94 GHz, and the forward radar model error in the MetUM should be better characterized. Copyright © 2011 British Crown copyright, the Met Office. Published by John Wiley & Sons Ltd.

Evaluating CloudSat ice water content retrievals using a cloud‐resolving model: Sensitivities to frozen particle properties

The A‐Train satellite constellation has dramatically increased the temporal and spatial coverage of atmospheric ice water content estimates. The new data are derived by retrieval algorithms designed to estimate atmospheric cloud ice water content from remotely sensed measurements. Such retrieval algorithms rely on simplifying assumptions regarding the characteristics of ice particles in the atmosphere. In this study, the sensitivities of CloudSat ice water content retrievals to frozen particle characteristics are tested by generating CloudSat‐like retrievals from profiles of known ice water content. CloudSat actively measures vertical profiles of radar reflectivity in clouds with a 94‐GHz cloud‐profiling radar. Ice water content is retrieved in each cloudy profile at temperatures below 0°C. To assess the CloudSat radar‐only ice water content retrieval algorithm (version 5.0 in Release 3 [R03] and version 5.1 in Release 4 [R04] of 2B‐CWC‐RO), we apply a 94‐GHz reflectivity simulator to profiles of ice water content generated by a cloud‐resolving numerical model and comprising various frozen particle species (ice, snow, and graupel). The CloudSat ice water content retrieval algorithm is applied to the profiles of simulated reflectivity, and the results are compared to the modeled profiles of known frozen water mass. The results from each version of the algorithm are shown to be sensitive to the characteristics of the frozen particle size distributions and particle densities. Tests of version 5.0 indicate that height varying information could improve retrievals. Despite the addition of a height varying component implemented in version 5.1, similar positive biases are indicated in the tests of each algorithm.

Testing IWC Retrieval Methods Using Radar and Ancillary Measurements with In Situ Data

Abstract Vertical profiles of ice water content (IWC) can now be derived globally from spaceborne cloud satellite radar (CloudSat) data. Integrating these data with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data may further increase accuracy. Evaluations of the accuracy of IWC retrieved from radar alone and together with other measurements are now essential. A forward model employing aircraft Lagrangian spiral descents through mid- and low-latitude ice clouds is used to estimate profiles of what a lidar and conventional and Doppler radar would sense. Radar reflectivity Ze and Doppler fall speed at multiple wavelengths and extinction in visible wavelengths were derived from particle size distributions and shape data, constrained by IWC that were measured directly in most instances. These data were provided to eight teams that together cover 10 retrieval methods. Almost 3400 vertically distributed points from 19 clouds were used. Approximate cloud optical depths ranged from below 1 to more than 50. The teams returned retrieval IWC profiles that were evaluated in seven different ways to identify the amount and sources of errors. The mean (median) ratio of the retrieved-to-measured IWC was 1.15 (1.03) ± 0.66 for all teams, 1.08 (1.00) ± 0.60 for those employing a lidar–radar approach, and 1.27 (1.12) ± 0.78 for the standard CloudSat radar–visible optical depth algorithm for Ze > −28 dBZe. The ratios for the groups employing the lidar–radar approach and the radar–visible optical depth algorithm may be lower by as much as 25% because of uncertainties in the extinction in small ice particles provided to the groups. Retrievals from future spaceborne radar using reflectivity–Doppler fall speeds show considerable promise. A lidar–radar approach, as applied to measurements from CALIPSO and CloudSat, is useful only in a narrow range of ice water paths (IWP) (40 < IWP < 100 g m−2). Because of the use of the Rayleigh approximation at high reflectivities in some of the algorithms and differences in the way nonspherical particles and Mie effects are considered, IWC retrievals in regions of radar reflectivity at 94 GHz exceeding about 5 dBZe are subject to uncertainties of ±50%.