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At least 613 records · Page 34

Multifrequency radar observations of clouds and precipitation including the G-band

Abstract. Observations collected during the 25 February 2020 deployment of the Vapor In-Cloud Profiling Radar at the Stony Brook Radar Observatory clearly demonstrate the potential of G-band radars for cloud and precipitation research, something that until now was only discussed in theory. The field experiment, which coordinated an X-, Ka-, W- and G-band radar, revealed that the Ka–G pairing can generate differential reflectivity signal several decibels larger than the traditional Ka–W pairing underpinning an increased sensitivity to smaller amounts of liquid and ice water mass and sizes. The observations also showed that G-band signals experience non-Rayleigh scattering in regions where Ka- and W-band signal do not, thus demonstrating the potential of G-band radars for sizing sub-millimeter ice crystals and droplets. Observed peculiar radar reflectivity patterns also suggest that G-band radars could be used to gain insight into the melting behavior of small ice crystals. G-band signal interpretation is challenging, because attenuation and non-Rayleigh effects are typically intertwined. An ideal liquid-free period allowed us to use triple-frequency Ka–W–G observations to test existing ice scattering libraries, and the results raise questions on their comprehensiveness. Overall, this work reinforces the importance of deploying radars (1) with sensitivity sufficient enough to detect small Rayleigh scatters at cloud top in order to derive estimates of path-integrated hydrometeor attenuation, a key constraint for microphysical retrievals; (2) with sensitivity sufficient enough to overcome liquid attenuation, to reveal the larger differential signals generated from using the G-band as part of a multifrequency deployment; and (3) capable of monitoring atmospheric gases to reduce related uncertainty.

54 ENVIRONMENTAL SCIENCES↗

Tropical Convective Responses to Microphysical and Radiative Processes: A Sensitivity Study With a 2D Cloud Resolving Model

Prognostic cloud schemes are increasingly used in weather and climate models in order to better treat cloud-radiation processes. Simplifications are often made in such schemes for computational efficiency, like the scheme being used in the National Centers for Environment Prediction models that excludes some microphysical processes and precipitation-radiation interaction. In this study, sensitivity tests with a 2D cloud resolving model are carried out to examine effects of the excluded microphysical processes and precipitation-radiation interaction on tropical thermodynamics and cloud properties. The model is integrated for 10 days with the imposed vertical velocity derived from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The experiment excluding the depositional growth of snow from cloud ice shows anomalous growth of cloud ice and more than 20% increase of fractional cloud cover, indicating that the lack of the depositional snow growth causes unrealistically large mixing ratio of cloud ice. The experiment excluding the precipitation-radiation interaction displays a significant cooling and drying bias. The analysis of heat and moisture budgets shows that the simulation without the interaction produces more stable upper troposphere and more unstable mid and lower troposphere than does the simulation with the interaction. Thus, the suppressed growth of ice clouds in upper troposphere and stronger radiative cooling in mid and lower troposphere are responsible for the cooling bias, and less evaporation of rain associated with the large-scale subsidence induces the drying in mid and lower troposphere.

Li, Xiao-Fan↗

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

King, Michael D.↗

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

King, Michael D.↗

Evaluation of Cloud Microphysics Simulated using a Meso-Scale Model Coupled with a Spectral Bin Microphysical Scheme through Comparison with Observation Data by Ship-Borne Doppler and Space-Borne W-Band Radars

Equivalent radar reflectivity factors (Ze) measured by W-band radars are directly compared with the corresponding values calculated from a three-dimensional non-hydrostatic meso-scale model coupled with a spectral-bin-microphysical (SBM) scheme for cloud. Three case studies are the objects of this research: one targets a part of ship-borne observation using 95 GHz Doppler radar over the Pacific Ocean near Japan in May 2001; other two are aimed at two short segments of space-borne observation by the cloud profiling radar on CloudSat in November 2006. The numerical weather prediction (NWP) simulations reproduce general features of vertical structures of Ze and Doppler velocity. A main problem in the reproducibility is an overestimation of Ze in ice cloud layers. A frequency analysis shows a strong correlation between ice water contents (IWC) and Ze in the simulation; this characteristic is similar to those shown in prior on-site studies. From comparing with the empirical correlations by the prior studies, the simulated Ze is overestimated than the corresponding values in the studies at the same IWC. Whereas the comparison of Doppler velocities suggests that large-size snowflakes are necessary for producing large velocities under the freezing level and hence rules out the possibility that an overestimation of snow size causes the overestimation of Ze. Based on the results of several sensitivity tests, we conclude that the source of the overestimation is a bias in the microphysical calculation of Ze or an overestimation of IWC. To identify the source of the problems needs further validation research with other follow-up observations.

Iguchi, T.↗

On the Sensitivity of Atmospheric Ensembles to Cloud Microphysics in Long-Term Cloud-Resolving Model Simulations

Month-long large-scale forcing data from two field campaigns are used to drive a cloud-resolving model (CRM) and produce ensemble simulations of clouds and precipitation. Observational data are then used to evaluate the model results. To improve the model results, a new parameterization of the Bergeron process is proposed that incorporates the number concentration of ice nuclei (IN). Numerical simulations reveal that atmospheric ensembles are sensitive to IN concentration and ice crystal multiplication. Two- (2D) and three-dimensional (3D) simulations are carried out to address the sensitivity of atmospheric ensembles to model dimensionality. It is found that the ensembles with high IN concentration are more sensitive to dimensionality than those with low IN concentration. Both the analytic solutions of linear dry models and the CRM output show that there are more convective cores with stronger updrafts in 3D simulations than in 2D, which explains the differing sensitivity of the ensembles to dimensionality at different IN concentrations.

Zeng, Xiping↗

Uncertainties in Ice-Sheet Altimetry from a Spaceborne 1064-nm Single-Channel Lidar Due to Undetected Thin Clouds

In support of the Ice, Cloud, and land Elevation Satellite (ICESat)-II mission, this paper studies the bias in surface-elevation measurements caused by undetected thin clouds. The ICESat-II satellite may only have a 1064-nm single-channel lidar onboard. Less sensitive to clouds than the 532-nm channel, the 1064-nm channel tends to miss thin clouds. Previous studies have demonstrated that scattering by cloud particles increases the photon-path length, thus resulting in biases in ice-sheet-elevation measurements from spaceborne lidars. This effect is referred to as atmospheric path delay. This paper complements previous studies in the following ways: First, atmospheric path delay is estimated over the ice sheets based on cloud statistics from the Geoscience Laser Altimeter System onboard ICESat and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua. Second, the effect of cloud particle size and shape is studied with the state-of-the-art phase functions developed for MODIS cirrus- cloud microphysical model. Third, the contribution of various orders of scattering events to the path delay is studied, and an analytical model of the first-order scattering contribution is developed. This paper focuses on the path delay as a function of telescope field of view (FOV). The results show that reducing telescope FOV can significantly reduce the expected path delay. As an example, the average path delays for FOV = 167 microrad (a 100-m-diameter circle on the surface) caused by thin undetected clouds by the 1064-nm channel over Greenland and East Antarctica are illustrated.

Yang, Yuekui↗

Single-Scattering Properties of Melting Precipitation for GPM Passive Microwave and Radar Remote Sensing Applications

Over the past two decades, detailed computational simulations of the intricate three dimensional structures of ice-phase crystals and aggregates of those crystals have been developed. The microwave single-scattering properties of these simulated ice particles have been computed and used to improve quantitative estimates of snow rates and to better deRne the vertical structure of snow water contents in deep convective systems, as derived from satellite-borne passive microwave and/or radar remote sensing measurements. The same icephase particles have more recently been used as the starting point for simulations of melting precipitation using computational melting methods. In the current study, a heuristic melting method, as well as a physically-based melting procedure based on smoothed-particle hydrodynamics, are applied to ice particle models to describe the full evolution of the particles from dry snow to liquid drops. The discrete dipole approximation is utilized to calculate the single-scattering properties of the mixed-phase particles throughout the melting process. Then, the properties of the particles are “mapped” into simpliRed microphysical simulations of particle size spectra in the melting layers of stratiform, precipitating clouds. The bulk single-scattering properties of the melting layers and the sensitivity of their properties to modeling assumptions are explored, and the implications for combined radar-radiometer precipitation remote sensing from GPM are discussed.

William S Olson↗

Cirrus Clouds Optical, Microphysical and Radiative Properties Observed During Crystal-Face Experiment: I. A Radar-Lidar Retrieval System

A method of retrieving cloud microphysical properties using combined observations from both cloud radar and lidar is introduced. This retrieval makes use of an improvement to the traditional optimal estimation retrieval method, whereby a series of corrections are applied to the state vector during the search for an iterative solution. This allows faster convergence to a solution and is less processor intensive. The method is first applied to a synthetic cloud t o demonstrate its validity, and it is shown that the retrieval reliably reproduces vertical profiles of ice water content. The retrieval method is then applied to radar and lidar observations from the CRYSTAL-FACE experiment, and vertical profiles of ice crystal diameter, number concentration, and ice water content are retrieved for a cirrus cloud layers observed one day of that experiment. The validity of the relationship between visible extinction coefficient and radar reflectivity was examined. While synthetic tests showed such a functional relationship, the measured data only partially supported such a conclusion. This is due to errors in the forward model (as explained above) as well as errors in the data sets, including possible mismatch between lidar and radar profiles or errors in the optical depth. Empirical relationships between number concentrations and mean particle diameter were also examined. The results indicate that a distinct and robust relationship exists between these retrieved quantities and it is argued that such a relationship is more than an artifact of the retrieval process offering insight into the nature of the microphysical processes taking place in cirrus.

Mitrescu, C.↗

Updates on Modeling the Water Cycle with the NASA Ames Mars Global Climate Model

Global Circulation Models (GCMs) have made steady progress in simulating the current Mars water cycle. It is now widely recognized that clouds are a critical component that can significantly affect the nature of the simulated water cycle. Two processes in particular are key to implementing clouds in a GCM: the microphysical processes of formation and dissipation, and their radiative effects on heating/ cooling rates. Together, these processes alter the thermal structure, change the dynamics, and regulate inter-hemispheric transport. We have made considerable progress representing these processes in the NASA Ames GCM, particularly in the presence of radiatively active water ice clouds. We present the current state of our group's water cycle modeling efforts, show results from selected simulations, highlight some of the issues, and discuss avenues for further investigation.­

Global Circulation Models (GCMs)↗

Millimeter wave radiative transfer studies for precipitation measurements

Scattering calculations using the discrete dipole approximation and vector radiative transfer calculations were performed to model multiparameter radar return and passive microwave emission for a simple model of a winter storm. The issue of dendrite riming was addressed by computing scattering properties of thin ice disks with varying bulk density. It was shown that C-band multiparameter radar contains information about particle density and the number concentration of the ice particles. The radiative transfer modeling indicated that polarized multifrequency passive microwave emission may be used to infer some properties of ice hydrometers. Detailed radar modeling and vector radiative transfer modeling is in progress to enhance the understanding of simultaneous radar and radiometer measurements, as in the case of the proposed TRMM field program. A one-dimensional cloud model will be used to simulate the storm structure in detail and study the microphysics, such as size and density. Multifrequency polarized radiometer measurements from the SSMI satellite instrument will be analyzed in relation to dual-frequency and dual-polarization radar measurements.

Vivekanandan, J.↗

Response of marine post-frontal clouds to Gulf Stream variability

Understanding how Gulf Stream variation influences cloud morphology is critical for evaluating cloud feedback in the western North Atlantic Ocean and beyond, where mesoscale air-sea interactions dominate. This study investigates the impact of altered mean sea surface temperature (SST) and SST gradients on post-frontal cloud characteristics during cold-air outbreaks, using the Weather Research and Forecasting (WRF) model. Three sensitivity experiments are conducted: a control simulation (default SST), Plus4 (uniform SST increase of 4 K), and Gradplus (SST gradient enhanced by 25 %, centered around mean SST). Results reveal distinctly different responses in boundary layer dynamics and cloud macro-physics. In Plus4, a warmer and moister boundary layer reduces total cloud cover but promotes larger cloud sizes and elongated cloud streets, with diminished liquid water and enhanced ice-phase hydrometeors. Conversely, Gradplus amplifies impacts in the upwind colder SST regions, yielding a drier, colder boundary layer, weaker energy transport, and higher liquid water path but reduced ice water content and cloud lines. Tracer analysis highlights that SST modifications alter airmass sources near cloud tops due to the entrainment of ambient air, with Plus4 amplifying boundary layer contributions to cloud-top regions. These findings underscore the spatially varying effects of SST gradients and mean SST on cloud organization and microphysics, emphasizing the need to resolve ocean-atmosphere coupling in global models to improve the prediction of marine cloud feedback under warming scenarios.

AIR-SEA INTERACTION↗

Microphysical properties of the Shuttle exhaust cloud

A data base describing the properties of the exhaust cloud produced by the launch of the STS has been developed based on data from a series of ground and aircraft based measurements made during the launches of STS 2, 3, and 4. Aircraft observations were performed during the STS-3 launch with a NOAA WP-3D Orion hurricane research aircraft which contained instrumentation for cloud condensation nucleus and ice nucleus counting, Aitken particle counting, and pH determination. Ground observations were conducted at 50 different sites, as well as in the direct exhaust from the solid rocket booster flame trench at all three launches. The data is analyzed in order to determine any possible adverse impacts of the exhaust products on human health and/or the environment. Analyses of the exhaust cloud measurements indicate that in the case of the ground cloud where plenty of large water drops are present and considerable scavenging and fallout of aerosol takes place, possible adverse impacts of the remaining aerosols (CCN and IN) on natural precipitation processes which may occur in the launch area hours after the launch are remote. However, it is determined that under certain atmospheric conditions there could be short term adverse effects on visibility.

Keller, V. W.↗

Observed and Simulated Variability of Droplet Spectral Dispersion in Convective Clouds Over the Amazon

Abstract In this study, the variability of the spectral dispersion of droplet size distributions (DSDs) in convective clouds is investigated. Analyses are based on aircraft measurements of growing cumuli near the Amazon basin, and on numerical simulations of an idealized ice‐free cumulus. In cleaner clouds, the relative dispersion , defined as the ratio of the standard deviation to the mean value of the droplet diameter, is negatively correlated with the ratio of the cloud water content ( ) to the adiabatic liquid water content ( ), while no strong correlation between and is seen in polluted clouds. Bin microphysics numerical simulations suggest that these contrasting behaviors are associated with the effect of collision‐coalescence in cleaner clouds, and secondary droplet activation in polluted clouds, in addition to the turbulent mixing of parcels that experienced different paths within the cloud. Collision‐coalescence simultaneously broadens the DSDs and decreases , explaining the inverse relationship between and in cleaner clouds. Secondary droplet activation broadens the DSDs but has little direct impact on . The combination of a rather modest DSD broadening due to weak collision‐coalescence with enhanced droplet activation in both diluted and highly undiluted cloud regions may contribute to maintain a relatively uniform within polluted clouds. These findings can be useful for parameterizing the shape parameter ( ) of gamma DSDs in bulk microphysics cloud‐resolving models. It is shown that emulating the observed relationship improves the estimation of the collision‐coalescence rate in bulk microphysics simulations compared to the bin simulations.

54 ENVIRONMENTAL SCIENCES↗

Texas A&M University Mobile Facility Measurements during TRACER (Field Campaign Report)

One of the main goals of the U.S Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) near Houston, Texas is to improve understanding of how meteorology and aerosols impact storm dynamical and microphysical processes in deep convection to better constrain and improve their model representation. The Houston area is strongly influenced by sea- and bay-breeze circulations that generate convergence and help to initiate and organize deep convection. To properly isolate and understand the roles of varied meteorological conditions and cloud condensation nuclei (CCN) and ice nucleation particles (INP) distributions in different air masses, co-located thermodynamic, kinematic, and aerosol vertical profile observations are needed. The focus of this campaign was to provide key measurements in air masses both in front of and behind sea/bay breeze fronts moving through the greater Houston area to sample the airmass heterogeneity. The overarching scientific goal of this campaign is to understand how the vertical distributions of both CCN and INP correspond to the inflow layer of deep convection in maritime, background continental, and polluted continental air masses, and how these variations influence deep convection. To fully sample the heterogeneity in both meteorological conditions and aerosols across the sea-breeze front (SBF), Texas A&M University (TAMU) deployed a InterMet 3050A 403 MHz mobile unit launching iMet-4 radiosondes and the new Rapid Onsite Atmospheric Measurement Van (ROAM-V) for aerosol sampling during the TRACER intensive operational period (IOP) from June to September 2022. The suite of instruments deployed on ROAM-V included a condensation particle counter (CPC; GRIMM Model 5.403 CPC), scanning mobility particle sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A differential mobility analyzer), cloud condensation nuclei counter (Droplet Measurement Technologies CCN counter), micropulse lidar (Droplet Measurement Technologies micropulse lidar [miniMPL]), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the Global Positioning System (GPS) on the phone application “My Altitude”. The DRUM data were collected as part of a closely related ARM field campaign and also supported by DOE Atmospheric System Research grant DE-SC0021047. The TAMU team sampled these airmass heterogeneities by strategically choosing deployment sites in a different airmass than the ARM fixed sites in La Porte and Guy, Texas. On days when the sea/bay breeze boundary was pushing inland, the TAMU team would usually sample the airmass on the maritime side of the SBF at a coastal site in Galveston, Texas in the early afternoon (1730-1900 UTC) and then move inland ahead of the SBF to sample the airmass on the continental side during late afternoon (2030-2230). Figure 1 shows the Galveston maritime site and the array of sites for the late afternoon continental measurements.

54 ENVIRONMENTAL SCIENCES↗

Statistics of Cirrus Horizontal Inhomogeneity in the Southern Great Plains

Variability of cloud properties on scales smaller than that of a GCM grid is potentially important both for realistic parameterizations of microphysical processes and for the prediction of the large-scale radiative effects of clouds, have suggested that a simple model of marine stratocumulus variability, based on the assumption of Gaussian variation statistics of cloud depth, can explain the liquid water path histogram shapes observed in Landsat data. In advance of ARM SGP MMCR ice water path climatologies, we have examined aircraft ice water content statistics for cirrus clouds observed over Coffeyville, Kansas during FIRE 2. We find similar associations of histogram shape and cloud cover for these clouds, and we show that a simple modification of the model for cirrus combined with observed mean cloud depths, their standard deviations, and ambient thermodynamic conditions predicts both the histogram shape and cirrus cloud cover fairly well. This suggests that subgrid variability of cloud properties may be similar for vastly different cloud types, and that a universal parameterization of the effects of subgrid variability in GCMs as a function of only a few parameters may be a realistic goal.

Smith, S. A.↗

New Challenges of Cloud Remote Sensing from Space

Clouds are recognized as a major source of uncertainties in predicting climate change. Lack of observational constraints on cloud processes has hindered the development of more reliable climate and weather models. With the advanced NASA EOS and A-Train sensors, we now have better knowledge about vertical distribution, water content, and occurrence frequency of global cloudiness. New ice water content (IWC) measurements from CloudSat and MLS have led to several improvements in model physics and parameterization schemes. MISR and GPS high-resolution data start to reveal deep insights on cloud processes and dynamicS in the planetary boundary layer (PBL). However, Earth sciences are still facing urgent needs to measure cloud microphysical properties, interactions between clouds and aerosol/precipitation, and processes that are coupled in 3-D space but not adequately sampled by the A-Train curtains or by the 2-D imageries. Submillimeter- wave, multi-angle imaging, and GPS radio occultation have emerged as promising remote sensing techniques to meet the challenges and enable new sciences for mid-tropospheric and PBL clouds.

Wu, Dong L.↗

Bulk cloud microphysical properties as seen from numerical simulation and remote sensing products: case study of a hailstorm event over the La Plata Basin

Hailstorms develop over the La Plata Basin, in south-eastern South America, more often during later winter and early austral spring, between September and October. These systems have significant socioeconomic impacts over the region. Thus, a better understanding of how atmospheric drivers modulate the formation of hailstorms is important to improve the forecast of such phenomena. In this study, we selected a hailstorm event observed over the eastern La Plata Basin during 14–15 July 2016 to evaluate the performance of the Brazilian developments on the Regional Atmospheric Modelling System (BRAMS) model. The ability of the model in simulating cloud microphysical properties was evaluated by comparing simulations driven by different global forcings against in situ and remote sensing observations. The model results showed good skill in capturing the basic characteristics of the thunderstorm, particularly in terms of the spatial distribution of hydrometeors. The simulated spatial distribution of hail covers locations where hail fall was reported. The BRAMS simulations suggest that, despite relatively low values of the convective available potential energy (CAPE) (700–1000 J kg -1 ), environments with strong 0–8-km bulk shear (60–70 kt, ~30.9–36.0 m s –1 ) can promote the formation of ice clouds and hail fall over the eastern La Plata Basin. To be more conclusive, however, further research is needed to understand how different combinations of CAPE and shear affect hail formation over the region.

54 ENVIRONMENTAL SCIENCES↗