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NASA NTRS2024

A Multi‐Probe Automated Classification of Ice Crystal Habits During the IMPACTS Campaign

Although all ice crystals are unique, many can be grouped together by shape or habit, with members of a habit class sharing similar representations of properties such as fall velocity and growth rate. A decision tree algorithm designed to be adaptable to any particle imaging probe, thus enabling the creation of habit size distributions over a size range larger than that of any probe on its own, is used to classify ice crystals imaged by three airborne cloud probes in mid-latitude winter cyclones during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Crystals are sorted into seven habit classes based on their morphological properties: sphere, column/needle, plate, graupel, dendrite, aggregate, and irregular. Although adaptability was its primary goal, the algorithm was found to be moderately skillful for identifying idealized habit images. Quantitative tests of the algorithm’s adaptability displayed mixed results, as Two-Dimensional Stereo Probe (2DS) classifications showed moderate correlation with Particle Habit Imaging and Polar Scattering Probe (PHIPS) classifications, but only weak correlation with High Volume Precipitation Spectrometer (HVPS) classifications. The algorithm was applied to random sets of images from each probe in a case study of a mesoscale snow band sampled on 7 February 2020. In the case study, qualitative analysis of particle images revealed general agreement on classifications among the probes, supporting the algorithm’s applicability to multiple cloud probes. Most classifications appeared correct upon manual inspection, suggesting that in practical use, the algorithm is reasonably able to classify non-idealized images.

Julian Schima↗

NASA NTRS1993

Three dimensional modeling of cirrus during the 1991 FIRE IFO 2: Detailed process study

A three-dimensional model of cirrus cloud formation and evolution, including microphysical, dynamical, and radiative processes, was used to simulate cirrus observed in the FIRE Phase 2 Cirrus field program (13 Nov. - 7 Dec. 1991). Sulfate aerosols, solution drops, ice crystals, and water vapor are all treated as interactive elements in the model. Ice crystal size distributions are fully resolved based on calculations of homogeneous freezing of solution drops, growth by water vapor deposition, evaporation, aggregation, and vertical transport. Visible and infrared radiative fluxes, and radiative heating rates are calculated using the two-stream algorithm described by Toon et al. Wind velocities, diffusion coefficients, and temperatures were taken from the MAPS analyses and the MM4 mesoscale model simulations. Within the model, moisture is transported and converted to liquid or vapor by the microphysical processes. The simulated cloud bulk and microphysical properties are shown in detail for the Nov. 26 and Dec. 5 case studies. Comparisons with lidar, radar, and in situ data are used to determine how well the simulations reproduced the observed cirrus. The roles played by various processes in the model are described in detail. The potential modes of nucleation are evaluated, and the importance of small-scale variations in temperature and humidity are discussed. The importance of competing ice crystal growth mechanisms (water vapor deposition and aggregation) are evaluated based on model simulations. Finally, the importance of ice crystal shape for crystal growth and vertical transport of ice are discussed.

Jensen, Eric J.↗

NASA NTRS2000

Design and Performance of McRas in SCMs and GEOS I/II GCMs

The design of a prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) for general circulation models (GCMs) will be discussed. McRAS distinguishes three types of clouds: (1) convective, (2) stratiform, and (3) boundary-layer types. The convective clouds transform and merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the auto-conversion equations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, as well as diffuse both horizontally and vertically with a fully interactive cloud-microphysics throughout the life-cycle of the cloud, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III and 5-ARN CART datasets has shown that together with the rest of the model physics, McRAS can simulate the observed temperature, humidity, and precipitation without many systematic errors. The time history and time mean incloud water and ice distribution, fractional cloudiness, cloud optical thickness, origin of precipitation in the convective anvil and towers, and the convective updraft and downdraft velocities and mass fluxes all show a realistic behavior. Performance of McRAS in GEOS 11 GCM shows several satisfactory features but some of the remaining deficiencies suggest need for additional research involving convective triggers and inhibitors, provision for continuously detraining updraft, a realistic scheme for cumulus gravity wave drag, and refinements to physical conditions for ascertaining cloud detrainment level.

Sud, Yogesh C.↗

NASA NTRS2004

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

Tao, Wei-Kuo↗

NASA NTRS2003

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fewer droplets, larger sized develop due to the greater condensational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.

Tao, Wei-Kuo↗

NASA NTRS2003

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fever droplets, larger size develop due to greater condencational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.

Tao, Wei-Kuo↗

NASA NTRS2004

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

Tao, Wei-Kuo↗

NASA NTRS2004

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.

Tao, Wei-Kuo↗

NASA NTRS2008

Formation of Large (Approximately 100 micrometers) Ice Crystals Near the Tropical Tropopause

Recent high-altitude aircraft measurements with in situ imaging instruments indicated the presence of relatively large (approx.100 microns length), thin (aspect ratios of approx.6:1 or larger) hexagonal plate ice crystals near the tropical tropopause in very low concentrations (<0.01/L). These crystals were not produced by deep convection or aggregation. We use simple growth-sedimentation calculations as well as detailed cloud simulations to evaluate the conditions required to grow the large crystals. Uncertainties in crystal aspect ratio leave a range of possibilities, which could be constrained by knowledge of the water vapor concentration in the air where the crystal growth occurred. Unfortunately, water vapor measurements made in the cloud formation region near the tropopause with different instruments ranged from <2 ppmv to approx.3.5 ppmv. The higher water vapor concentrations correspond to very large ice supersaturations (relative humidities with respect to ice of about 200%). If the aspect ratios of the hexagonal plate crystals are as small as the image analysis suggests (6:1, see companion paper (Lawson et al., 2008)) then growth of the large crystals before they sediment out of the supersaturated layer would only be possible if the water vapor concentration were on the high end of the range indicated by the different measurements (>3 ppmv). On the other hand, if the crystal aspect ratios are quite a bit larger (approx.10:1), then H2O concentrations toward the low end of the measurement range (approx.2-2.5 ppmv) would suffice to grow the large crystals. Gravity-wave driven temperature and vertical wind perturbations only slightly modify the H2O concentrations needed to grow the crystals. We find that it would not be possible to grow the large crystals with water concentrations less than 2 ppmv, even with assumptions of a very high aspect ratio of 15 and steady upward motion of 2 cm/s to loft the crystals in the tropopause region. These calculations would seem to imply that the measurements indicating water vapor concentrations less than 2ppmv are implausible, but we cannot rule out the possibility that higher humidity prevailed upstream of the aircraft measurements and the air was dehydrated by the cloud formation. Simulations of the cloud formation with a detailed model indicate that homogeneous freezing should generate ice concentrations larger than the observed concentrations (20/L), and even concentrations as low as 20/L should have depleted the vapor in excess of saturation and prevented growth of large crystals. It seems likely that the large crystals resulted from ice nucleation on effective heterogeneous nuclei at low ice supersaturations. Improvements in our understanding of detailed cloud microphysical processes require resolution of the water vapor measurement discrepancies in these very cold, dry regions of the atmosphere.

Jensen, E. J.↗

NASA NTRS2012

Climate Impacts of Ice Nucleation

Several different ice nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of ice nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of ice microphysical states that are consistent with the spread of observations, but many simulations have higher present-day ice crystal number concentrations than in-situ observations. These different states result from different parameterizations of ice cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (0.06 Wm(exp-2) and not statistically significant AIE when included as ice nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting ice AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous ice nucleation. Regional effects can reach several Wm2. Indirect effects are slightly larger for those states with less homogeneous nucleation and lower ice number concentration in the base state. The total ice AIE is estimated at 0.27 +/- 0.10 Wm(exp-2) (1 sigma uncertainty). This represents a 20% offset of the simulated total shortwave AIE for ice and liquid clouds of 1.6 Wm(sup-2).

Gettelman, Andrew↗

NASA NTRS2021

Operational Detection of Sun Glints in DSCOVR EPIC Images

Satellite images often feature sun glints caused by the specular reflection of sunlight from water surfaces or from horizontally oriented ice crystals occurring in clouds. Such glints can prevent accurate retrievals of atmospheric and surface properties using existing algorithms, but the glints can also be used to infer more about the glint-causing objects—for example about the microphysical properties and radiative effects of ice clouds. This paper introduces the recently released operational glint product of the Earth Polychromatic Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft. Most importantly, the paper describes the algorithm used for generating the key component of the new product: a glint mask indicating the presence of sun glint caused by the specular reflection of sunlight from ice clouds and smooth water surfaces. After describing the glint detection algorithm and glint product, the paper shows some examples of the detected glints and discusses some basic statistics of the glint population in a yearlong dataset of EPIC images. These statistics provide insights into the performance of glint detection and point toward possibilities for using the glint product to gain scientific insights about ice clouds and water surfaces.

DSCOVR↗

NASA NTRS1991

A numerical study of thunderstorm electrification - Model development and case study

A numerical model was developed for examining the thunderstorm electrification process in which it is assumed that the electrification is entirely due to noninductive charge transfer between colliding ice crystals and hail. Since this ice-hail charge mechanism is very dependent on particle sizes and distributions, an explicit microphysical framework is used. To maintain simplicity, the electrification model is kinematic; thus the temperature and velocity fields are input into the electrification model. The cloud model of Taylor (1989) was used to generate the temperature and velocity fields to examine the July 19, 1981, Cooperative Convective Precipitation Experiment thundercloud. Using these fields, the electrification model produced time-dependent ice particle concentrations, radar reflectivities, charge, and vertical electric field distributions in good general agreement with those observed. The model produced a maximum electric field strength of 1.27 kV/cm, which is on the order of that needed for lightning initiation, and this maximum occurred very close to the time of the observed discharge. Thus, the ice-hail charge mechanism appears to have played an important role in the electrical development of the July 19 cloud.

Norville, K.↗

NASA NTRS2010

Exploring a Physically Based Tool for Lightning Cessation: A Preliminary Study

The University of Alabama in Huntsville (UA Huntsville) and NASA's Marshall Space Flight Center are collaborating with the 45th Weather Squadron (45WS) at Cape Canaveral Air Force Station (CCAFS) to enable improved nowcasting of lightning cessation. The project centers on use of dual-polarimetric radar capabilities, and in particular, the new C-band dual-polarimetric weather radar acquired by the 45WS. Special emphasis is placed on the development of a physically based operational algorithm to predict lightning cessation. While previous studies have developed statistically based lightning cessation algorithms, we believe that dual-polarimetric radar variables offer the possibility to improve existing algorithms through the inclusion of physically meaningful trends reflecting interactions between in-cloud electric fields and microphysics. Specifically, decades of polarimetric radar research using propagation differential phase has demonstrated the presence of distinct phase and ice crystal alignment signatures in the presence of strong electric fields associated with lightning. One question yet to be addressed is: To what extent can these ice-crystal alignment signatures be used to nowcast the cessation of lightning activity in a given storm? Accordingly, data from the UA Huntsville Advanced Radar for Meteorological and Operational Research (ARMOR) along with the North Alabama Lightning Mapping Array are used in this study to investigate the radar signatures present before and after lightning cessation. A summary of preliminary results will be presented.

Schultz, Elise V.↗

NASA NTRS2010

Exploring a Physically Based Tool for Lightning Cessation: Preliminary Results

The University of Alabama in Huntsville (UAHuntsville) and NASA s Marshall Space Flight Center are collaborating with the 45th Weather Squadron (45WS) at Cape Canaveral Air Force Station (CCAFS) to enable improved nowcasting of lightning cessation. The project centers on use of dual-polarimetric radar capabilities, and in particular, the new C-band dual-polarimetric weather radar acquired by the 45WS. Special emphasis is placed on the development of a physically based operational algorithm to predict lightning cessation. While previous studies have developed statistically based lightning cessation algorithms, we believe that dual-polarimetric radar variables offer the possibility to improve existing algorithms through the inclusion of physically meaningful trends reflecting interactions between in-cloud electric fields and microphysics. Specifically, decades of polarimetric radar research using propagation differential phase has demonstrated the presence of distinct phase and ice crystal alignment signatures in the presence of strong electric fields associated with lightning. One question yet to be addressed is: To what extent can these ice-crystal alignment signatures be used to nowcast the cessation of lightning activity in a given storm? Accordingly, data from the UAHuntsville Advanced Radar for Meteorological and Operational Research (ARMOR) along with the North Alabama Lightning Mapping Array are used in this study to investigate the radar signatures present before and after lightning cessation. A summary of preliminary results will be presented.

Schultz, Elsie V.↗

NASA NTRS2011

Exploring the Use of Radar for Physically-Based Nowcasting of Lightning Cessation

NASA's Marshall Space Flight Center and the University of Alabama in Huntsville (UAHuntsville) are collaborating with the 45th Weather Squadron (45WS) at Cape Canaveral Air Force Station (CCAFS) to enable improved nowcasting of lightning cessation. This project centers on use of dual-polarimetric radar capabilities, and in particular, the new C-band dual polarimetric weather radar acquired by the 45WS. Special emphasis is placed on the development of a physically-based operational algorithm to predict lightning cessation. While previous studies have developed statistically based lightning cessation algorithms driven primarily by trending in the actual total lightning flash rate, we believe that dual polarimetric radar variables offer the possibility to improve existing algorithms through the inclusion of physically meaningful trends reflecting interactions between in-cloud electric fields and ice-microphysics. Specifically, decades of polarimetric radar research using propagation differential phase has demonstrated the presence of distinct phase and ice crystal alignment signatures in the presence of strong electric fields associated with lightning. One question yet to be addressed is: To what extent can propagation phase-based ice-crystal alignment signatures be used to nowcast the cessation of lightning activity in a given storm? Accordingly, data from the UAHuntsville Advanced Radar for Meteorological and Operational Research (ARMOR) along with the NASA-MSFC North Alabama Lightning Mapping Array are used in this study to investigate the radar signatures present before and after lightning cessation. Thus far our case study results suggest that the negative differential phase shift signature weakens and disappears after the analyzed storms ceased lightning production (i.e., after the last lightning flash occurred). This is a key observation because it suggests that while strong electric fields may still have been present, the lightning cessation signature was encompassed in the period of the polarimetric negative phase shift signature. To the extent this behavior is repeatable in other cases, even if only in a substantial fraction of those cases, the analysis suggests that differential propagation phase may prove to be a useful parameter for future lightning cessation algorithms. Indeed, a preliminary analysis of 15+ cases has shown additional indications of the weakening and disappearance of this ice alignment signature with lightning cessation. A summary of these case-study results is presented.

Schultz, Elise V.↗

NASA NTRS2026

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗

NASA NTRS1990

Interpretation of satellite-measured bidirectional reflectance from Cirrus cloudy atmospheres

The interpretation of the observed bidirectional reflectance from cirrus cloudy atmospheres is presented. A theoretical model was developed for the computation of the transfer of solar radiation in an anisotropic medium with particular applications to oriented ice crystals in cirrus clouds. In this model, the adding principle for radiative transfer was used with modifications to account for the anisotropy of scattering particles and the associated scattering phase matrix. The single-scattering properties, including the phase function, single-scattering albedo, and extinction cross sections, were used for randomly and horizontally oriented hexagonal ice crystals in radiative transfer computations. The radiative transfer model developed for the cirrus clouds was modified to account for the scattering contributions from the atmosphere and the surface. In order to test the relevance and significance of the ice crystal model for the interpretation of observed bidirectional reflectance from satellites, visible radiances collected on the half hour by the GOES series were selected. The data are calibrated and corrected with the proper filter functions, then navigated to match selected landmark data. A number of clear and cloudy cases during the cirrus IFO of the Fire experiment were chosen for theoretical analyses. The cloud particle shape and size distributions that were taken during satellite overpasses are used in radiative transfer calculations. The sensitivities of the shape, orientation, and size distribution of ice crystals on the reflected intensities at the top of the atmosphere are investigated. Finally, the relative importance of these cloud microphysical properties in the interpretation of satellite bidirectional reflectance are assessed and presented.

Takano, Y.↗

NASA NTRS2002

Cloud Microphysics and Absorption Validation

Vertical distributions of particle size and habit were developed from in-situ data collected from three midlatitude cirrus field campaigns (FIRE-1, FIRE-2, and ARM IOP). These new midlatitude microphysical models were used to develop new cirrus scattering models at a number of wavelengths appropriate for use with the MODIS imager (Nasiri et al. 2002). This was the first successful collaborative effort between all the investigators on this proposal. Recent efforts have extended the midlatitude cirrus cloud analyses to tropical cirrus, using in-situ data collected during the Tropical Rainfall Measurement Mission (TRMM) Kwajalein field campaign in 1999. We note that there are critical aspects to the work: a) Improvement in computing the scattering and radiative properties of ice crystals; b) Requirement for copious amounts of cirrus in-situ data, presented in terms of both particle size and habit distributions; c) Development of cirrus microphysical and optical models for various satellite, aircraft, and ground-based instruments based on the theoretical calculations and in-situ measurements; d) Application to satellite data.

Ackerman, Steven↗