12 results on '"Charles N. Helms"'
Search Results
2. Retrieval of Normalized Gamma Size Distribution Parameters Using Precipitation Imaging Package (Pip) Snowfall Observations During Ice-Pop 2018
- Author
-
Ali Tokay, Liang Liao, Robert Meneghini, Charles N. Helms, S. Joseph Munchak, David B. Wolff, and Patrick N. Gatlin
- Subjects
Meteorology and Climatology - Abstract
Parameters of the normalized gamma particle size distribution (PSD) have been retrieved from the Precipitation Image Package (PIP) snowfall observations collected during the International Collaborative Experiment - PyeongChang Olympics and Paralympic (ICE-POP 2018). Two of the gamma PSD parameters, the mass weighted particle diameter (Dmass) and the normalized intercept parameter NW, have median values of 1.15-1.31 mm and 2.84-3.04 log(mm-1 m-3), respectively. This range arises from the choice of the relationship between the maximum versus equivalent diameter, Dmx-Deq, and the relationship between the Reynolds and Best numbers, Re-X. Normalization of snow water equivalent rate (SWER) and ice water content (W) by NW reduces the range in NW resulting in well fitted power law relationship, between SWER/NW and Dmass and between W/NW and Dmass. The bulk descriptors of snowfall are calculated from PIP observations and from the gamma PSD with values of the shape parameter (μ) ranging from -2 to 10. NASA’s Global Precipitation Measurement (GPM) mission, which adopted the normalized gamma PSD, assumes μ = 2 and μ = 3 in its two separate algorithms. The mean fractional bias (MFB) of the snowfall parameters changes with μ, where the functional dependence on μ depends on the specific snowfall parameter of interest. The MFB of the total concentration was underestimated by 0.23-0.34 when μ = 2 and by 0.29-0.40 when μ = 3, while the MFB of SWER had a much narrower range (-0.03 to 0.04) for the same μ values.
- Published
- 2023
- Full Text
- View/download PDF
3. Evaluation of SWER(Ze) Relationships by Precipitation Imaging Package (PIP) during ICE-POP 2018
- Author
-
Ali Tokay, Charles N. Helms, Kwonil Kim, Patrick N. Gatlin, and David B. Wolff
- Subjects
Meteorology and Climatology - Abstract
Improving estimation of snow water equivalent rate (SWER) from radar reflectivity (Ze), known as a SWER(Ze) relationship, is a priority for NASA’s Global Precipitation Measurement (GPM) mission ground validation program as it is needed to comprehensively validate spaceborne precipitation retrievals. This study investigates the performance of eight operational and four research-based SWER(Ze) relationships utilizing Precipitation Imaging Probe (PIP) observations from the International Collaborative Experiment for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field campaign. During ICE-POP 2018, there were 10 snow events that are classified by synoptic conditions as either cold low or warm low, and a SWER(Ze) relationship is derived for each event. Additionally, a SWER(Ze) relationship is derived for each synoptic classification by merging all events within each class. Two new types of SWER(Ze) relationships are derived from PIP measurements of bulk density and habit classification. These two physically based SWER(Ze) relationships provided superior estimates of SWER when compared to the operational, event-specific, and synoptic SWER(Ze) relationships. For estimates of the event snow water equivalent total, the event-specific, synoptic, and best-performing operational SWER(Ze) relationships outperformed the physically based SWER(Ze) relationship, although the physically based relationships still performed well. This study recommends using the density or habit-based SWER(Ze) relationships for microphysical studies, whereas the other SWER(Ze) relationships are better suited toward hydrologic application.
- Published
- 2023
- Full Text
- View/download PDF
4. A Comparative Evaluation of Snowflake Particle Shape Estimation Techniques Used By the Precipitation Imaging Package (PIP), Multi-Angle Snowflake Camera (MASC), and Two-Dimensional Video Disdrometer (2DVD)
- Author
-
Charles N Helms, S Joseph Munchak, Ali Tokay, and Claire Pettersen
- Subjects
Earth Resources and Remote Sensing ,Instrumentation and Photography ,Meteorology and Climatology - Abstract
Measurements of snowflake particle shape are important for studying snow microphysics. While a number of instruments exist that are capable of measuring particle shape, this study focuses on the measurement techniques of three digital video disdrometers: the Precipitation Imaging Package (PIP), the Multi-Angle Snowflake Camera (MASC), and the Two-Dimensional Video Disdrometer (2DVD). To gain a better understanding of the relative strengths and weaknesses of these instruments and to provide a foundation upon which comparisons can be made between studies using data from different instruments, we perform a comparative analysis of the shape measurement algorithms employed by each of the three instruments by applying the algorithms to snowflake images captured by PIP during the ICE-POP 2018 field campaign. Our analysis primarily focuses on the measurement of the aspect ratio of either the particle itself, in the case of PIP and MASC, or of the particle bounding box, in the case of PIP and 2DVD. Both PIP and MASC use shape-fitting algorithms to measure aspect ratio. While our analysis of the MASC aspect ratio suggests that the measurements are reliable, our findings indicate that both the ellipse and rectangle aspect ratios produced by PIP underperformed considerably due to the shortcomings of the PIP shape-fitting techniques. We also demonstrate that reliable measurements of aspect ratio can be retrieved from PIP by reprocessing the raw PIP images using either the MASC ellipse-fitting algorithm or a tensor-based ellipse-fitting algorithm. Because of differences in instrument design, 2DVD produces measurements of particle horizontal and vertical extent rather than length and width. Furthermore, the 2DVD measurements of particle horizontal extent can be contaminated by horizontal particle motion. Our findings indicate that, although the correction technique used to remove the horizontal motion contamination performs remarkably well with snowflakes despite being designed for use with raindrops, the 2DVD measurements of particle horizontal extent are less reliable than those measured by PIP.
- Published
- 2022
- Full Text
- View/download PDF
5. Snow Microphysical Retrieval from the NASA D3R Radar During ICE-POP 2018
- Author
-
S Joseph Munchak, Robert S Schrom, Charles N Helms, and Ali Tokay
- Subjects
Earth Resources And Remote Sensing ,Meteorology And Climatology - Abstract
A method is developed to use both polarimetric and dual-frequency radar measurements to retrieve microphysical properties of falling snow. It is applied to the Ku- and Ka-band measurements of the NASA dual-polarization, dual-frequency Doppler radar (D3R) obtained during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018) field campaign and incorporates the Atmospheric Radiative Transfer Simulator (ARTS) microwave singles cattering property database for oriented particles. The retrieval uses optimal estimation to solve for several parameters that describe the particle size distribution (PSD), relative contribution of pristine, aggregate, and rimed ice species, and the orientation distribution along an entire radial simultaneously. Examination of Jacobian matrices and averaging kernels shows that the dual-wavelength ratio (DWR) measurements provide information regarding the characteristic particle size, and to a lesser extent, the rime fraction and shape parameter of the size distribution, whereas the polarimetric measurements provide information regarding the mass fraction of pristine particles and their characteristic size and orientation distribution. Thus, by combining the dual-frequency and polarimetric measurements, some ambiguities can be resolved that should allow a better determination of the PSD and bulk microphysical properties (e.g., snowfall rate) than can be retrieved from single-frequency polarimetric measurements or dual-frequency, single-polarization measurements. The D3R ICE-POP retrievals were validated using Precipitation Imaging Package (PIP) and Pluvio weighing gauge measurements taken nearby at the May Hills ground site. The PIP measures the snow PSD directly, and its measurements can be used to derived the snowfall rate (volumetric and water equivalent), mean volume-weighted particle size, and effective density, as well as particle aspect ratio and orientation. Four retrieval experiments were performed to evaluate the utility of different measurement combinations: Kuonly, DWR-only, Ku-pol, and All-obs. In terms of correlation, the volumetric snowfall rate (r D 0:95) and snow water equivalent rate (r D 0:92) were best retrieved by the Ku-pol method, while the DWR-only method had the lowest magnitude bias for these parameters (-31% and -8 %, respectively). The methods that incorporated DWR also had the best correlation to particle size (r D 0:74 and r D 0:71 for DWR-only and All-obs, respectively), although none of the methods retrieved density particularly well (r D 0:43 for Allobs). The ability of the measurements to retrieve mean aspect ratio was also inconclusive, although the polarimetric methods (Ku-pol and All-obs) had reduced biases and mean absolute error (MAE) relative to the Ku-only and DWR-only methods. The significant biases in particle size and snowfall rate appeared to be related to biases in the measured DWR, emphasizing the need for accurate DWR measurements and frequent calibration in future D3R deployments.
- Published
- 2022
- Full Text
- View/download PDF
6. Reducing Errors in Velocity–Azimuth Display (VAD) Wind and Deformation Retrievals from Airborne Doppler Radars in Convective Environments
- Author
-
Charles N Helms, Matthew L W Mclinden, Gerald M Heymsfield, and Stephen R Guimond
- Subjects
Communications And Radar - Abstract
The present study describes methods to reduce the uncertainty of velocity–azimuth display (VAD) wind and deformation retrievals from downward-pointing, conically scanning, airborne Doppler radars. These retrievals have important applications in data assimilation and real-time data processing. Several error sources for VAD retrievals are considered here, including violations to the underlying wind field assumptions, Doppler velocity noise, data gaps, temporal variability, and the spatial weighting function of the VAD retrieval. Specific to airborne VAD retrievals, we also consider errors produced due to the radar scans occurring while the instrument platform is in motion. While VAD retrievals are typically performed using data from a single antenna revolution, other strategies for selecting data can be used to reduce retrieval errors. Four such data selection strategies for airborne VAD retrievals are evaluated here with respect to their effects on the errors. These methods are evaluated using the second hurricane nature run numerical simulation, analytic wind fields, and observed Doppler radar radial velocities. The proposed methods are shown to reduce the median absolute error of the VAD wind retrievals, especially in the vicinity of deep convection embedded in stratiform precipitation. The median absolute error due to wind field assumption violations for the along-track and for the across-track wind is reduced from 0.36 to 0.08 m s−1 and from 0.35 to 0.24 m s−1, respectively. Although the study focuses on Doppler radars, the results are equally applicable to conically scanning Doppler lidars as well.
- Published
- 2020
- Full Text
- View/download PDF
7. The Impact of a Midlevel Dry Airflow Layer on Deep Convection in the Pre-Gabrielle (2013) Tropical Disturbance on 4–5 September
- Author
-
Lance F. Bosart and Charles N. Helms
- Subjects
Atmospheric Science ,Deep convection ,Disturbance (geology) ,Flow (psychology) ,Atmospheric sciences ,Layer (electronics) ,Geology - Abstract
On 4–5 September 2013, a relatively shallow layer of northerly dry airflow was observed just west of the core deep convection associated with the low-level center of the pre-Gabrielle (2013) tropical disturbance. Shortly thereafter, the core deep convection of the disturbance collapsed after having persisted for well over 24 h. The present study provides an in-depth analysis of the interaction between this dry airflow layer and the pre-Gabrielle disturbance core deep convection using a combination of observations, reanalysis fields, and idealized simulations. Based on the analysis, we conclude that the dry airflow layer played an important role in the collapse of the core deep convection in the pre-Gabrielle disturbance. Furthermore, we found that the presence of storm-relative flow was critical to the inhibitive effects of the dry airflow layer on deep convection. The mechanism by which the dry airflow layer inhibited deep convection was found to be enhanced dry air entrainment.
- Published
- 2021
8. Reply on RC2
- Author
-
Charles N. Helms
- Published
- 2022
9. Snow Microphysical Retrieval from the NASA D3R Radar During ICE-POP 2018
- Author
-
S. Joseph Munchak, Robert S. Schrom, Charles N. Helms, and Ali Tokay
- Subjects
Atmospheric Science - Abstract
A method is developed to use both polarimetric and dual-frequency radar measurements to retrieve microphysical properties of falling snow. It is applied to the Ku- and Ka-band measurements of the NASA dual-polarization, dual-frequency Doppler radar (D3R) obtained during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018) field campaign and incorporates the Atmospheric Radiative Transfer Simulator (ARTS) microwave single-scattering property database for oriented particles. The retrieval uses optimal estimation to solve for several parameters that describe the particle size distribution (PSD), relative contribution of pristine, aggregate, and rimed ice species, and the orientation distribution along an entire radial simultaneously. Examination of Jacobian matrices and averaging kernels shows that the dual-wavelength ratio (DWR) measurements provide information regarding the characteristic particle size, and to a lesser extent, the rime fraction and shape parameter of the size distribution, whereas the polarimetric measurements provide information regarding the mass fraction of pristine particles and their characteristic size and orientation distribution. Thus, by combining the dual-frequency and polarimetric measurements, some ambiguities can be resolved that should allow a better determination of the PSD and bulk microphysical properties (e.g., snowfall rate) than can be retrieved from single-frequency polarimetric measurements or dual-frequency, single-polarization measurements. The D3R ICE-POP retrievals were validated using Precipitation Imaging Package (PIP) and Pluvio weighing gauge measurements taken nearby at the May Hills ground site. The PIP measures the snow PSD directly, and its measurements can be used to derived the snowfall rate (volumetric and water equivalent), mean volume-weighted particle size, and effective density, as well as particle aspect ratio and orientation. Four retrieval experiments were performed to evaluate the utility of different measurement combinations: Ku-only, DWR-only, Ku-pol, and All-obs. In terms of correlation, the volumetric snowfall rate (r=0.95) and snow water equivalent rate (r=0.92) were best retrieved by the Ku-pol method, while the DWR-only method had the lowest magnitude bias for these parameters (−31 % and −8 %, respectively). The methods that incorporated DWR also had the best correlation to particle size (r=0.74 and r=0.71 for DWR-only and All-obs, respectively), although none of the methods retrieved density particularly well (r=0.43 for All-obs). The ability of the measurements to retrieve mean aspect ratio was also inconclusive, although the polarimetric methods (Ku-pol and All-obs) had reduced biases and mean absolute error (MAE) relative to the Ku-only and DWR-only methods. The significant biases in particle size and snowfall rate appeared to be related to biases in the measured DWR, emphasizing the need for accurate DWR measurements and frequent calibration in future D3R deployments.
- Published
- 2021
10. The Evolution of Dropsonde-Derived Kinematic and Thermodynamic Structures in Developing and Nondeveloping Atlantic Tropical Convective Systems
- Author
-
Robert E. Hart and Charles N. Helms
- Subjects
Convection ,Atmospheric Science ,Mesoscale convective system ,Tropical cyclogenesis ,Meteorology ,Climatology ,Cyclone ,Kinematics ,Tropical cyclone ,Dropsonde ,Geology - Abstract
The processes by which tropical cyclones evolve from loosely organized convective clusters are still poorly understood. Because of the data-sparse regions in which tropical cyclones form, observational studies of tropical cyclogenesis are often more difficult than studies of land-based convective phenomena. As a result, many studies of tropical cyclogenesis are limited to either a few case studies or rely on simulations. The 2010 PREDICT and GRIP field experiments have provided a new opportunity to gain insight into these processes using unusually dense observations in both time and space. The present study aims at using these recent datasets to perform a detailed analysis of the three-dimensional evolution of both kinematic and thermodynamic fields in both developing and nondeveloping tropical convective systems in the western Atlantic. Five tropical convective systems are analyzed in this study: two nondeveloping, two developing, and one dissipating system. Although the analysis necessarily includes only a very limited number of cases, the results suggest that the convectively active nondeveloping systems and developing systems examined here have similar kinematic structures. The most notable difference is the distribution of humidity and the impacts this distribution has on the thermodynamics of the system. Displacements between the upper-level warm anomaly, responsible for midlevel vorticity generation, and the midlevel vorticity maximum are observed in both developing and nondeveloping cases. In the nondeveloping case the displacement appears to be caused by mid- and upper-level dry air. Further work is needed to fully understand the cause of these displacements and their relation to tropical cyclogenesis.
- Published
- 2015
11. A Polygon-Based Line-Integral Method for Calculating Vorticity, Divergence, and Deformation from Nonuniform Observations
- Author
-
Robert E. Hart and Charles N. Helms
- Subjects
Atmospheric Science ,Tessellation ,Mathematical analysis ,Polygon ,Line integral ,Regular polygon ,Divergence (statistics) ,Grid ,Regular grid ,Mathematics ,Interpolation - Abstract
Traditional observational analysis of derivative-based variables (e.g., vorticity) usually relies on interpolating observations and evaluating spatial derivatives either on a Cartesian grid or on a spherical grid. Great care must be taken in selecting the domain and the interpolation scheme to properly represent the features. There exist a number of alternative methods of calculating such variables by evaluating line integrals on triangular regions according to Green’s theorem. Since these methods rely on only three observations to perform calculations, they are overly sensitive to observations dominated by local phenomena as well as instrument noise. A few studies have attempted to minimize the impact of nonrepresentative or noisy observations by using higher-order polygons, but they have been limited to fitting regular polygons to near-regularly gridded data. The current study describes a new approach to calculating these fields by constructing higher-order polygons from a triangle tessellation and then applying Green’s theorem. Since the polygons are constructed using an automated triangle tessellation, the polygon construction process can proceed without the need for uniformly spaced data. The triangle tessellation employed here is unique for a given set of points, generating easily reproducible results. In addition, this method reduces the impact of noise associated with individual observations with only a minor loss in the length of the resolvable scale. An error analysis of the proposed method shows a large decrease in errors in comparison with purely triangle-based calculations. These improvements are present with a variety of data distributions (random and along research aircraft flight paths) and kinematic variables (vorticity, divergence, and deformation).
- Published
- 2013
12. An Objective Algorithm for Detecting and Tracking Tropical Cloud Clusters: Implications for Tropical Cyclogenesis Prediction
- Author
-
Charles N. Helms, Kenneth R. Knapp, Christopher C. Hennon, and Amanda R. Bowen
- Subjects
NetCDF ,Atmospheric Science ,geography ,geography.geographical_feature_category ,Meteorology ,Ocean Engineering ,computer.file_format ,Tropical cyclogenesis ,Climatology ,Latent heat ,Environmental science ,Satellite ,Tropical cyclone forecast model ,Tropical cyclone ,Oceanic basin ,computer ,Algorithm ,Central dense overcast - Abstract
An algorithm to detect and track global tropical cloud clusters (TCCs) is presented. TCCs are organized large areas of convection that form over warm tropical waters. TCCs are important because they are the “seedlings” that can evolve into tropical cyclones. A TCC satisfies the necessary condition of a “preexisting disturbance,” which provides the required latent heat release to drive the development of tropical cyclone circulations. The operational prediction of tropical cyclogenesis is poor because of weaknesses in the observational network and numerical models; thus, past studies have focused on identifying differences between “developing” (evolving into a tropical cyclone) and “nondeveloping” (failing to do so) TCCs in the global analysis fields to produce statistical forecasts of these events. The algorithm presented here has been used to create a global dataset of all TCCs that formed from 1980 to 2008. Capitalizing on a global, Gridded Satellite (GridSat) infrared (IR) dataset, areas of persistent, intense convection are identified by analyzing characteristics of the IR brightness temperature (Tb) fields. Identified TCCs are tracked as they move around their ocean basin (or cross into others); variables such as TCC size, location, convective intensity, cloud-top height, development status (i.e., developing or nondeveloping), and a movement vector are recorded in Network Common Data Form (NetCDF). The algorithm can be adapted to near-real-time tracking of TCCs, which could be of great benefit to the tropical cyclone forecast community.
- Published
- 2011
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.