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NASA NTRS1985

LAMPS software and mesoscale prediction studies

The full-physics version of the LAMPS model has been implemented on the Perkin-Elmer computer. In Addition, LAMPS graphics processors have been rewritten to the run on the Perkin-Elmer and they are currently undergoing final testing. Numerical experiments investigating the impact of convective parameterized latent heat release on the evolution of a precipitating storm have been performed and the results are currently being evaluated. Curent efforts include the continued evaluation of the impact of initial conditions on LAMPS model results. This work will help define measurement requirements for future research field projects as well as for observations in support of operational forecasts. Also, the impact of parameterized latent heat on the evolution of precipitating systems is continuing. This research is in support of NASA's proposed Earth Observation Mission (EOM).

Perkey, D. J.↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Molthan, Andrew L.↗
NASA NTRS2021

Measurements of Rainfall Rate, Drop Size Distribution, and Variability at Middle and Higher Latitudes: Application to the Combined DPR-GMI Algorithm

The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth’s global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-precipitation radar and an advanced microwave imager which provide measurements to retrieve the drop size distribution (DSD) and rain rates using a Combined Radar-Radiometer Algorithm (CORRA). Our objective is to validate key assumptions and parameterizations in CORRA and enable improved estimation of precipitation products, especially in the middle-to-higher latitudes in both hemispheres. The DSD parameters and statistical relationships between DSD parameters and radar measurements are a central part of the rainfall retrieval algorithm, which is complicated by regimes where DSD measurements are abysmally sparse (over the open ocean). In view of this, we have assembled optical disdrometer datasets gathered by research vessels, ground stations, and aircrafts to simulate radar observables and validate the scattering lookup tables used in CORRA. The joint use of all DSD datasets spans a large range of drop concentrations and characteristic drop diameters. The scaling normalization of DSDs defines an intercept parameter N(W), which normalizes the concentrations, and a scaling diameter D(m), which compresses or stretches the diameter coordinate axis. A major finding of this study is that a single relationship between N(W) and D(m), on average, unifies all datasets included, from stratocumulus to heavier rainfall regimes. A comparison with the N(W)–D(m) relation used as a constraint in versions 6 and 7 of CORRA highlights the scope for improvement of rainfall retrievals for small drops (D(m) < 1 mm) and large drops (D(m) > 2 mm). The normalized specific attenuation–reflectivity relationships used in the combined algorithm are also found to match well the equivalent relationships derived using DSDs from the three datasets, suggesting that the currently assumed lookup tables are not a major source of uncertainty in the combined algorithm rainfall estimates.

Viswanathan Bringi↗
NASA NTRS2023

Exploring the Predictability of the High-Energy Tail of MEE Precipitation Based on Solar Wind Properties

Medium Energy Electron (MEE) precipitation (≳30 keV) ionizes the mesosphere and initiates chemical reactions, which ultimately can reduce mesospheric and stratospheric ozone. Currently, there are considerable differences in how existing parameterizations represent flux response, timing, and duration of MEE precipitation, especially considering its high-energy tail (≳300 keV). This study compares the nature of ≳300 to ≳30 keV electron fluxes to better understand differences within MEE precipitation. The MEE fluxes are estimated from measurements by the Medium Energy Proton and Electron Detector (MEPED) onboard the Polar Orbiting Environmental Satellite (POES) from 2004 to 2014. The fluxes are explored in the context of solar wind drivers: corotating high-speed solar wind streams (HSSs) and coronal mass ejections (CMEs) alongside their associated solar wind properties. Three key aspects of ≳300 keV electron fluxes are investigated: maximum response, peak timing, and duration. The results reveal a structure-dependent correlation (0.89) between the peak fluxes of ≳30 and ≳300 keV electrons. The epsilon coupling function correlates well (0.84) with the ≳300 keV peak flux, independent of solar wind structure. The ≳300 keV flux peaks 0–3 days after the ≳30 keV flux peaks. The highest probability (∼42%) occurs for a 1-day delay, while predictive capabilities increase when accounting for solar wind speed. The ≳300 keV flux response has the highest probability of lasting 4 days for both CMEs and HSSs. The results form a base for a stochastic MEE parameterization that goes beyond the average picture, enabling realistic flux variability on both daily and decadal scales.

J A Salice↗
NASA NTRS2010

Genesis of Pre-Hurricane Felix (2007): Warm Core Formation, Precipitation Evolution, and Predictability - Part 2

This is the second of a two-part study examining the simulated formation of Atlantic Hurricane Felix (2007) in a cloud-representing framework. Here several open issues are addressed concerning the formation of the storm's warm core, the evolution and respective contribution of stratiform versus convective precipitation within the parent wave's pouch, and the sensitivity of the development pathway reported in Part I to different model physics options and initial conditions. All but one of the experiments include ice microphysics as represented by one of several parameterizations, and the partition of convective versus stratiform precipitation is accomplished using a standard numerical technique based on the high-resolution control experiment. The transition to a warm-core tropical cyclone from an initially cold-core, lower tropospheric wave disturbance is analyzed first. As part of this transformation process, it is shown that deep moist convection is sustained near the pouch center. Both convective and stratiform precipitation rates increase with time. While stratiform precipitation occupies a larger area even at the tropical storm stage, deep moist convection makes a comparable contribution to the total rain rate at the pregenesis stage, and a larger contribution than stratiform processes at the storm stage. The convergence profile averaged near the pouch center is found to become dominantly convective with increasing deep moist convective activity there. Low-level convergence forced by interior diabatic heating plays a key role in forming and intensifying the near-surface closed circulation, while the midlevel convergence associated with stratiform precipitation helps to increase the midlevel circulation and thereby contributes to the formation and upward extension of a tropospheric-deep cyclonic vortex. Sensitivity tests with different model physics options and initial conditions demonstrate a similar pregenesis evolution. These tests suggest that the genesis location of a tropical storm is largely controlled by the parent wave's critical layer, whereas the genesis time and intensity of the protovortex depend on the details of the mesoscale organization, which is less predictable. Some implications of the findings are discussed.

Wang, zhuo↗
NASA NTRS2008

The Super Tuesday Outbreak: Forecast Sensitivities to Single-Moment Microphysics Schemes

Forecast precipitation and radar characteristics are used by operational centers to guide the issuance of advisory products. As operational numerical weather prediction is performed at increasingly finer spatial resolution, convective precipitation traditionally represented by sub-grid scale parameterization schemes is now being determined explicitly through single- or multi-moment bulk water microphysics routines. Gains in forecasting skill are expected through improved simulation of clouds and their microphysical processes. High resolution model grids and advanced parameterizations are now available through steady increases in computer resources. As with any parameterization, their reliability must be measured through performance metrics, with errors noted and targeted for improvement. Furthermore, the use of these schemes within an operational framework requires an understanding of limitations and an estimate of biases so that forecasters and model development teams can be aware of potential errors. The National Severe Storms Laboratory (NSSL) Spring Experiments have produced daily, high resolution forecasts used to evaluate forecast skill among an ensemble with varied physical parameterizations and data assimilation techniques. In this research, high resolution forecasts of the 5-6 February 2008 Super Tuesday Outbreak are replicated using the NSSL configuration in order to evaluate two components of simulated convection on a large domain: sensitivities of quantitative precipitation forecasts to assumptions within a single-moment bulk water microphysics scheme, and to determine if these schemes accurately depict the reflectivity characteristics of well-simulated, organized, cold frontal convection. As radar returns are sensitive to the amount of hydrometeor mass and the distribution of mass among variably sized targets, radar comparisons may guide potential improvements to a single-moment scheme. In addition, object-based verification metrics are evaluated for their utility in gauging model performance and QPF variability.

Molthan, Andrew L.↗
NASA NTRS2004

Rain Reevaporation, Boundary Layer Convection Interactions, and Pacific Rainfall Patterns in an AGCM

Sensitivity experiments with an atmospheric general circulation model (AGCM) show that parameterized rain re-evaporation has a large impact on simulated precipitation patterns in the tropical Pacific, especially on the configuration of the model s intertropical convergence zone (ITCZ). Weak re-evaporation leads t o the formation of a "double ITCZ" during the northern warm season. The double ITCZ is accompanied by strong coupling between precipitation and high-frequency vertical motion in the planetary boundary layer (PBL). Strong reevaporation leads to a better overall agreement of simulated precipitation with observations. The model s double ITCZ bias is reduced. At the same time, correlation between high-frequency vertical motion in the PBL and precipitation is reduced. Experiments with modified physics suggest that evaporative cooling by rain near the PBL top weakens the coupling between precipitation and vertical motion. This may reduce the model s tendency to form double ITCZs. The strength of high-frequency vertical motions in the PBL was also reduced directly through the introduction of a diffusive cumulus momentum transport (DCMT) parameterization. The DCMT had a visible impact on simulated precipitation in the tropics, but did not reduce the model s double bias in all cases.

Bacmeister, Julio T.↗
NASA NTRS2006

A Mission to Observe Ice in Clouds from Space

To date there have been multiple satellite missions to observe and retrieve cloud top properties and the liquid in, and precipitation from, clouds. There are currently a few missions that attempt to measure cloud ice properties as a byproduct of other observations. However, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in clouds either melts into rain or is detrained, and persists, as cirrus clouds affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various cloud properties at the temporal and spatial scales of cloud processes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice clouds and ice processes. This presentation will describe the Submillimeter-wave InfraRed Ice Cloud Experiment (SIRICE) concept, a satellite mission designed to acquire global Earth radiance measurements in the infrared and submillimeter-wave region (183-874 GHz). If successful, this mission will bridge the measurement gap between microwave sounders and shorter-wavelength infrared and visible sensors. The brightness temperatures at submillimeter-wave frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the cloud layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of clouds, thus requiring only one term of the radiative transfer equation (ice scattering) to relate brightness temperatures to ice. Scientific justification and the SIRICE approach to measuring ice water path and particle size that span a range encompassing both the hydrologically active and radiatively active components of cloud systems will be presented.

Ackerman, S.↗
NASA NTRS2006

Observing Ice in Clouds from Space

There are many satellite observations of cloud top properties and the liquid and rain content of clouds, however, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in clouds in the upper troposphere either melts into rain or is detrained, and persists, as cirrus clouds affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various cloud properties at the temporal and spatial scales of cloud processes. These properties include cloud horizontal and vertical structure, cloud water content and some measure of particle sizes and shapes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice clouds and ice processes. One barrier to achieving accurate global ice cloud properties is the lack of adequate observations at millimeter and submillimeter wavelengths (183-874 GHz). Recent advances in instrumentation have allowed for the development and implementation of an airborne submillimeter-wave radiometer. The brightness temperatures at these frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the cloud layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of clouds, thus requiring only one term of the radiative transfer equation (ice scattering) to relate brightness temperatures to ice. The next step is a satellite mission designed to acquire global Earth radiance measurements in the submillimeter-wave region, thus bridging the measurement gap between microwave sounders and shorter-wavelength infrared and visible sensors. This presentation provides scientific justification and an approach to measuring ice water path and particle size from a satellite platform that spans a range encompassing both the hydrologically active and radiatively active components of cloud systems.

Ackerman, S.↗
NASA NTRS2009

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Molthan, Andrew↗
NASA NTRS2012

Correction of Excessive Precipitation over Steep Mountains in a General Circulation Model (GCM)

Excessive precipitation over steep and high mountains (EPSM) is a well-known problem in GCMs and regional climate models even at a resolution as high as 19km. The affected regions include the Andes, the Himalayas, Sierra Madre, New Guinea and others. This problem also shows up in some data assimilation products. Among the possible causes investigated in this study, we found that the most important one, by far, is a missing upward transport of heat out of the boundary layer due to the vertical circulations forced by the daytime subgrid-scale upslope winds, which in turn is forced by heated boundary layer on the slopes. These upslope winds are associated with large subgrid-scale topographic variance, which is found over steep mountains. Without such subgrid-scale heat ventilation, the resolvable-scale upslope flow in the boundary layer generated by surface sensible heat flux along the mountain slopes is excessive. Such an excessive resolvable-scale upslope flow in the boundary layer combined with the high moisture content in the boundary layer results in excessive moisture transport toward mountaintops, which in turn gives rise to excessive precipitation over the affected regions. We have parameterized the effects of subgrid-scale heated-slope-induced vertical circulation (SHVC) by removing heat from the boundary layer and depositing it in the layers higher up when topographic variance exceeds a critical value. Test results using NASA/Goddard's GEOS-5 GCM have shown that the EPSM problem is largely solved.

Chao, Winston C.↗
NASA NTRS1990

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 2: Retrieval method and applications (report version)

A physical retrieval method for estimating precipitating water distributions and other geophysical parameters based upon measurements from the DMSP-F8 SSM/I is developed. Three unique features of the retrieval method are (1) sensor antenna patterns are explicitly included to accommodate varying channel resolution; (2) precipitation-brightness temperature relationships are quantified using the cloud ensemble/radiative parameterization; and (3) spatial constraints are imposed for certain background parameters, such as humidity, which vary more slowly in the horizontal than the cloud and precipitation water contents. The general framework of the method will facilitate the incorporation of measurements from the SSMJT, SSM/T-2 and geostationary infrared measurements, as well as information from conventional sources (e.g., radiosondes) or numerical forecast model fields.

Olson, William S.↗
NASA NTRS1974

The GISS model of the global atmosphere

A description and numerical results are presented for a global atmospheric circulation model developed at the Goddard Institute for Space Studies (GISS). The model version described is a 9-level primitive-equation model in sigma coordinates. It includes a realistic distribution of continents, oceans and topography. Detailed calculations of energy transfer by solar and terrestrial radiation make use of cloud and water vapor fields calculated by the model. The model hydrologic cycle includes two precipitation mechanisms: large-scale supersaturation and a parameterization of subgrid-scale cumulus convection. Results are presented both from a comparison of the 13th to the 43rd days (January) of one integration with climatological statistics, and from five short-range forecasting experiments. In the extended integration, the near-equilibrium January-mean model atmosphere exhibits an energy cycle in good agreement with observational estimates, together with generally realistic zonal mean fields of winds, temperature, humidity, transports, diabatic heating, evaporation, precipitation, and cloud cover.

Somerville, R. C. J.↗
NASA NTRS2013

Using Field and Satellite Measurements to Improve Snow and Riming Processes in Cloud Resolving Models

The representation of clouds in climate and weather models is a driver in forecast uncertainty. Cloud microphysics parameterizations are challenged by having to represent a diverse range of ice species. Key characteristics of predicted ice species include habit and fall speed, and complex interactions that result from mixed-phased processes like riming. Our proposed activity leverages Global Precipitation Measurement (GPM) Mission ground validation studies to improve parameterizations

Colle, Brian A.↗
NASA NTRS2007

New, Improved Bulk-microphysical Schemes for Studying Precipitation Processes in WRF: Comparisons with Other Schemes - Part 1

Advances in computing power allow atmospheric prediction models to be mn at progressively finer scales of resolution, using increasingly more sophisticated physical parameterizations and numerical methods. The representation of cloud microphysical processes is a key component of these models, over the past decade both research and operational numerical weather prediction models have started using more complex microphysical schemes that were originally developed for high-resolution cloud-resolving models (CRMs). A recent report to the United States Weather Research Program (USWRP) Science Steering Committee specifically calls for the replacement of implicit cumulus parameterization schemes with explicit bulk schemes in numerical weather prediction (NWP) as part of a community effort to improve quantitative precipitation forecasts (QPF). An improved Goddard bulk microphysical parameterization is implemented into a state-of the-art of next generation of Weather Research and Forecasting (WRF) model. High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atllan"ic hurricane). The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The 31CE scheme with a cloud ice-snow-hail configuration led to a better agreement with observation in terms of simulated narrow convective line and rainfall intensity. This is because the 3ICE-hail scheme includes dense ice precipitating (hail) particle with very fast fall speed (over 10 m/s). For an Atlantic hurricane case, varying the microphysical schemes had no significant impact on the track forecast but did affect the intensity (important for air-sea interaction)

Tao, W.-K.↗
NASA NTRS2018

Impact of a Cold Pool Parameterization on the Diurnal Cycle and Intraseasonal Variability in the GEOS AGCM

A gradual transition from shallow to deep convection may be important both to the continental diurnal cycle of precipitation and to the tropical Madden-Julian Oscillation. However, many existing convection parameterizations transition too readily, with corresponding diurnal and intraseasonal biases. High entrainment rates can be used to delay deep convection, but typically produce mean state biases; this is the "entrainment dilemma." Cold pools and sub-grid organization offer a potential solution to this dilemma, and recent work shows parameterized cold pools can effectively modulate deep convection, with improvements to the diurnal cycle and intraseasonal variability. Here we investigate the effects of a simple prognostic cold pool scheme coupled to the Grell-Freitas convection parameterization, in a set of global simulations with the NASA GEOS model. Air detrained from parameterized downdrafts is maintained in vertically resolved cold pools, which evolve with simplified dynamics. We test several options for cold pool feedbacks on convection, including modifications to deep convective entrainment rates, convective source air properties, and thermodynamic profiles, based on the level of cold pool activity. Cold pool impacts on the diurnal cycle are evaluated against TRMM, and moisture and moist static energy budgets are used to understand changes in tropical intraseasonal variability. Preliminary results show delays in the diurnal cycle of precipitation.

Arnold, Nathan↗
NASA NTRS2020

Cascading toward a Kilometer‐scale GCM: Impacts of a Scale‐aware Convection Parameterization in the Goddard Earth Observing System GCM.

The NASA Goddard Earth Observing System global model is evaluated through a cascade of simulations with increasing horizontal resolution. This model employs a non-hydrostatic dynamical core and includes a scale-aware, deep convection parameterization (DPCP). 40-daysimulations at six resolutions (100km to 3km) with unvarying model formulation were produced. At the highest resolution, extreme experiments were carried out; one with no DPCP, and one with its scale-awareness eliminated. Simulated precipitation, radiative balance, and atmospheric thermodynamic and dynamical variables are well reproduced with respect to both observational and reanalysis data. As model resolution increases, the convective precipitation smoothly transitions from being mostly produced by the convection parameterization to the cloud microphysics parameterization. However, contrary to current thought, these extreme cases argue for maintaining, to some extent, the scale-aware deep convection parameterization even at 3kmscale, as the run relying solely on explicit grid-scale production of rainfall performs more poorly at this resolution.

Saulo Freitas↗
NASA NTRS2007

Nonspherical and Spherical Characterization of Ice in Hurricane Erin for Wideband Passive Microwave Comparisons

In order to better understand the characteristics of frozen cloud particles in hurricane systems, computed brightness temperatures were compared with radiometric observations of Hurricane Erin (2001) from the NASA ER-2 aircraft. The focus was oil the frozen particle microphysics and the high frequencies (2 85 GHz) that are particularly sensitive to frozen particles. Frozen particles in hurricanes are an indicator of increasing hurricane intensity. In fact "hot towers" associated with increasing hurricane intensity are composed of frozen ice cloud particles. (They are called hot towers because their column of air is warmer than the surrounding air temperature, but above about 5-7 km to the tops of the towers at 15-19 km, the cloud particles are frozen.) This work showed that indeed, one can model information about cloud ice particle characteristics and indicated that nonspherical ice shapes, instead of spherical particles, provided the best match to the observations. Overall, this work shows that while non-spherical particles show promise, selecting and modeling a proper ice particle parameterization can be difficult and additional in situ measurements are needed to define and validate appropriate parameterizations. This work is important for developing Global Precipitation Measurement (GPM) mission satellite algorithms for the retrieval of ice characteristics both above the melting layer, as in Hurricane Erin, and for ice particles that reach the surface as falling snow.

Skofronick-Jackson, Gail↗