Dual-Polarization Radar Data Analysis of the Impact of Ground-Based Glaciogenic Seeding on Winter Orographic Clouds. Part I: Mostly Stratiform Clouds

2015 ◽  
Vol 54 (9) ◽  
pp. 1944-1969 ◽  
Author(s):  
Xiaoqin Jing ◽  
Bart Geerts ◽  
Katja Friedrich ◽  
Binod Pokharel
Keyword(s):  
Radar Data ◽  
Control Area ◽  
Target Area ◽  
Dual Polarization ◽  
Stratiform Clouds ◽  
Orographic Clouds ◽  
Close Range ◽  
Glaciogenic Seeding ◽  
Differential Reflectivity ◽  
The Impact

AbstractThe impact of ground-based glaciogenic seeding on wintertime orographic, mostly stratiform clouds is analyzed by means of data from an X-band dual-polarization radar, the Doppler-on-Wheels (DOW) radar, positioned on a mountain pass. This study focuses on six intensive observation periods (IOPs) during the 2012 AgI Seeding Cloud Impact Investigation (ASCII) project in Wyoming. In all six storms, the bulk upstream Froude number below mountaintop exceeded 1 (suggesting unblocked flow), the clouds were relatively shallow (with bases below freezing), some liquid water was present, and orographic flow conditions were mostly steady. To examine the silver iodide (AgI) seeding effect, three study areas are defined (a control area, a target area upwind of the crest, and a lee target area), and comparisons are made between measurements from a treated period and those from an untreated period. Changes in reflectivity and differential reflectivity observed by the DOW at low levels during seeding are consistent with enhanced snow growth, by vapor diffusion and/or aggregation, for a case study and for the composite analysis of all six IOPs, especially at close range upwind of the mountain crest. These low-level changes may have been affected by natural changes aloft, however, as evident from differences in the evolution of the echo-top height in the control and target areas. Even though precipitation in the target region is strongly correlated with that in the control region, the authors cannot definitively attribute the change to seeding because there is a lack of knowledge about natural variability, nor can the outcome be generalized, because the sample size is small.

scholarly journals Dual-Polarization Radar Data Analysis of the Impact of Ground-Based Glaciogenic Seeding on Winter Orographic Clouds. Part II: Convective Clouds

2015 ◽  
Vol 54 (10) ◽  
pp. 2099-2117 ◽  
Author(s):  
Xiaoqin Jing ◽  
Bart Geerts
Keyword(s):  
Cloud Base ◽  
Base Temperature ◽  
Target Area ◽  
Dual Polarization ◽  
Low Level ◽  
Convective Clouds ◽  
Orographic Clouds ◽  
Orographic Convection ◽  
Glaciogenic Seeding ◽  
The Impact

AbstractThis second paper of a two-part series aims to explore the ground-based glaciogenic seeding impact on wintertime orographic clouds using an X-band dual-polarization radar. It focuses on three cases with shallow to moderately deep orographic convection that were observed in January–February of 2012 as part of the AgI Seeding Cloud Impact Investigation (ASCII) project over the Sierra Madre in Wyoming. In each of the storms the bulk upstream Froude number exceeded 1, suggesting unblocked flow. Low-level potential instability was present, explaining orographic convection. The clouds contained little supercooled liquid water on account of the low cloud-base temperature. Ice-crystal photography shows that snow mainly grew by diffusion and aggregation. To examine the seeding effect of silver iodide (AgI), five study areas are defined: two target areas and three control areas. Comparisons are made between the control and target areas as well as between a treated, or seeded, period and an untreated period. Low-level reflectivity tends to increase in the target areas relative to the control. This increase is larger in the lee target area than in the upwind target area, suggesting that precipitation enhancement is delayed in the presence of convection. The echo tops of the convective cells are not higher during seeding, relative to simultaneous changes in the control regions. This result suggests that the dynamic-seeding mechanism does not apply for the cold-base convective clouds that are studied here. An analysis of differential reflectivity and snow photography suggests that static seeding is the more likely snow-enhancement mechanism in these clouds.

scholarly journals Impact of the Dual-Polarization Doppler Radar Data on Two Convective Storms with a Warm-Rain Radar Forward Operator

2012 ◽  
Vol 140 (7) ◽  
pp. 2147-2167 ◽  
Author(s):  
Xuanli Li ◽  
John R. Mecikalski
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Radar Data ◽  
Dual Polarization ◽  
Convective Storms ◽  
Warm Rain ◽  
Mesoscale Convective ◽  
Differential Reflectivity ◽  
The Impact

Abstract The dual-polarization (dual pol) Doppler radar can transmit/receive both horizontally and vertically polarized power returns. The dual-pol radar measurements have been shown to provide a more accurate precipitation estimate compared to traditional radars. In this study, the horizontal reflectivity ZH, differential reflectivity ZDR, specific differential phase KDP, and radial velocity VR collected by the C-band Advanced Radar for Meteorological and Operational Research (ARMOR) are assimilated for two convective storms. A warm-rain scheme is constructed to assimilate ZH, ZDR, and KDP data using the three-dimensional variational data assimilation (3DVAR) system with the Advanced Research Weather Research and Forecasting Model (ARW-WRF). The main goals of this study are first to demonstrate and compare the impact of various dual-pol variables in initialization of real case convective storms and second to test how the dual-pol fields may be better used with a 3DVAR system. The results show that the ZH, ZDR, KDP, and VR data substantially improve the initial condition for two mesoscale convective storms. Significant positive impacts on short-term forecast are obtained for both storms. Additionally, KDP and ZDR data assimilation is shown to be superior to ZH and ZDR and ZH-only data assimilation when the warm-rain microphysics is adopted. With the ongoing upgrade of the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network to include dual-pol capabilities (started in early 2011), the findings from this study can be a helpful reference for utilizing the dual-pol radar data in numerical simulations of severe weather and related quantitative precipitation forecasts.

scholarly journals The Extra-Area Effect of Orographic Cloud Seeding: Observational Evidence of Precipitation Enhancement Downwind of the Target Mountain

2016 ◽  
Vol 55 (6) ◽  
pp. 1409-1424 ◽  
Author(s):  
Xiaoqin Jing ◽  
Bart Geerts ◽  
Bruce Boe
Keyword(s):  
Vertical Mixing ◽  
Radar Data ◽  
Control Area ◽  
Radar Reflectivity ◽  
Target Range ◽  
Target Area ◽  
Mountain Ranges ◽  
Ice Nuclei ◽  
Orographic Cloud ◽  
Glaciogenic Seeding

AbstractThis study uses scanning X-band Doppler on Wheels (DOW) radar data to examine whether ground-based glaciogenic seeding influences orographic precipitation, inadvertently, over the foothills of a mountain ~50 km downwind of the target mountain. The data were collected during seven storms during the 2012 AgI Seeding Cloud Impact Investigation (ASCII-12) campaign in Wyoming. The DOW was located on the Sierra Madre (the target range), with excellent low-level coverage toward the Medicine Bow (the downwind range). To examine the seeding impact, two study areas are designated, both over the foothills of the downwind range: one is directly downwind of the remote silver iodide (AgI) generators (target area), and the other is offset sideways (control area). Comparisons are made between radar reflectivity measurements from a treated period and those from an untreated period. The total treated (untreated) period over seven storms is 14.3 h (21.2 h). Independent measurements of ice nuclei concentrations indicate that ground-released AgI nuclei can disperse across two mountain ranges over a distance of ~80 km. Analyses of DOW transects, DOW echo-height maps, and Doppler velocities from an airborne profiling radar suggest three different mechanisms for the vertical mixing of AgI nuclei: in all cases boundary layer mixing is active, and in some cases convection, or a lee hydraulic jump, or both are present. In all cases the radar reflectivity is higher during seeding in the target region when compared with the trend over the same period in the control region. Note that the results are not definitive proof of a downwind seeding impact since natural variability of precipitation is large and the sample size examined is small.

A Case Study of Radar Observations and WRF LES Simulations of the Impact of Ground-Based Glaciogenic Seeding on Orographic Clouds and Precipitation. Part I: Observations and Model Validations

2014 ◽  
Vol 53 (10) ◽  
pp. 2264-2286 ◽  
Author(s):  
Xia Chu ◽  
Lulin Xue ◽  
Bart Geerts ◽  
Roy Rasmussen ◽  
Daniel Breed
Keyword(s):  
Vertical Plane ◽  
Vertical Motion ◽  
Radar Data ◽  
Mountain Range ◽  
Motion Field ◽  
Microphysics Scheme ◽  
Seeding Effect ◽  
Orographic Clouds ◽  
Glaciogenic Seeding ◽  
The Impact

AbstractProfiling airborne radar data and accompanying large-eddy-simulation (LES) modeling are used to examine the impact of ground-based glaciogenic seeding on cloud and precipitation in a shallow stratiform orographic winter storm. This storm occurred on 18 February 2009 over a mountain in Wyoming. The numerical simulations use the Weather Research and Forecasting (WRF) Model in LES mode with horizontal grid spacings of 300 and 100 m in a domain covering the entire mountain range, and a glaciogenic seeding parameterization coupled with the Thompson microphysics scheme. A series of non-LES simulations at 900-m resolution, each with different initial/boundary conditions, is validated against sounding, cloud, and precipitation data. The LES runs then are driven by the most representative 900-m non-LES simulation. The 100-m LES results compare reasonably well to the vertical-plane radar data. The modeled vertical-motion field reveals a turbulent boundary layer and gravity waves above this layer, as observed. The storm structure also validates well, but the model storm thins and weakens more rapidly than is observed. Radar reflectivity frequency-by-altitude diagrams suggest a positive seeding effect, but time- and space-matched model reflectivity diagrams only confirm this in a relative sense, in comparison with the trend in the control region upwind of seeding generators, and not in an absolute sense. A model sensitivity run shows that in this case natural storm weakening dwarfs the seeding effect, which does enhance snow mass and snowfall. Since the kinematic and microphysical structure of the storm is simulated well, future Part II of this study will examine how glaciogenic seeding impacts clouds and precipitation processes within the LES.

scholarly journals A Case Study of Cloud Radar Observations and Large-Eddy Simulations of a Shallow Stratiform Orographic Cloud, and the Impact of Glaciogenic Seeding

2017 ◽  
Vol 56 (5) ◽  
pp. 1285-1304 ◽  
Author(s):  
Xia Chu ◽  
Bart Geerts ◽  
Lulin Xue ◽  
Binod Pokharel
Keyword(s):  
Liquid Water ◽  
Supercooled Liquid ◽  
Cold Season ◽  
Cloud Base ◽  
Target Area ◽  
Blowing Snow ◽  
Large Eddy ◽  
Orographic Clouds ◽  
Glaciogenic Seeding ◽  
The Impact

AbstractThe impact of glaciogenic seeding on precipitation remains uncertain, mainly because of the noisy nature of precipitation. Operational seeding programs often target cold-season orographic clouds because of their abundance of supercooled liquid water. Such clouds are complicated because of common natural seeding from above (seeder–feeder effect) or from below (blowing snow). Here, observations, mainly from a profiling airborne Doppler radar, and numerical simulations are used to examine the impact of glaciogenic seeding on a very shallow (<1 km), largely blocked cloud that is not naturally seeded from aloft or from below. This cloud has limited but persistent supercooled liquid water, a cloud-base (top) temperature of −12°C (−16°C), and produces only very light snowfall naturally. A Weather Research and Forecasting Model large-eddy simulation at 100-m resolution captures the observed upstream stability and wind profiles and reproduces the essential characteristics of the orographic flow, cloud, and precipitation. Both observations and simulations indicate that seeding locally increases radar (or computed) reflectivity in the target area, even after removal of the natural trend between these two periods in a nearby control region. A model sensitivity run suggests that seeding effectively glaciates the mostly liquid cloud and substantially increases snowfall within the seeding plume. This is due to a dramatic increase in the number of ice particles and not to their size. The increased ice particle concentration facilitates snow growth by vapor deposition in a cloud the temperature range of which is conducive to the Bergeron process.

A Case Study on the Impact of Ground-based Glaciogenic Seeding on Winter Orographic Clouds at Daegwallyeong

2015 ◽  
Vol 36 (4) ◽  
pp. 301-314 ◽  
Author(s):  
Ha-Young Yang ◽  
◽  
Sanghee Chae ◽  
Jin-Yim Jeong ◽  
Seong-Kyu Seo ◽  
...  
Keyword(s):  
Orographic Clouds ◽  
Glaciogenic Seeding ◽  
The Impact

An Automated Python Algorithm to Quantify ZDR Arc and KDP-ZDR Separation Signatures in Supercells

2020 ◽  
Author(s):  
Matthew B. Wilson ◽  
Matthew S. Van Den Broeke
Keyword(s):  
Time Series ◽  
Recent Work ◽  
Radar Data ◽  
Dual Polarization ◽  
Low Level ◽  
Supercell Storms ◽  
Size Sorting ◽  
Supercell Thunderstorms ◽  
Differential Reflectivity

AbstractSupercell thunderstorms often have pronounced signatures of hydrometeor size sorting within their forward flank regions, including an arc-shaped region of high differential reflectivity (ZDR) along the inflow edge of the forward flank known as the ZDR arc and a clear horizontal separation between this area of high ZDP values and and an area of enhanced KDP values deeper into the storm core. Recent work has indicated that ZDR arc and KDP-ZDR separation signatures in supercell storms may be related to environmental storm-relative helicity and low-level shear. Thus, characteristics of these signatures may be helpful to indicate whether a given storm is likely to produce a tornado. Although ZDR arc and KDP-ZDR separation signatures are typically easy to qualitatively identify in dual-polarization radar fields, quantifying their characteristics can be time-consuming and makes research into these signatures and their potential operational applications challenging. To address this problem, this paper introduces an automated Python algorithm to objectively identify and track these signatures in Weather Surveillance Radar-1988 Doppler (WSR-88D) radar data and quantify their characteristics. This paper will discuss the development of the algorithm, demonstrate its performance through comparisons with manually-generated time series of ZDR arc and KDP-ZDR separation signature characteristics, and briefly explore potential uses of this algorithm in research and operations.

An Airborne Profiling Radar Study of the Impact of Glaciogenic Cloud Seeding on Snowfall from Winter Orographic Clouds

2010 ◽  
Vol 67 (10) ◽  
pp. 3286-3302 ◽  
Author(s):  
Bart Geerts ◽  
Qun Miao ◽  
Yang Yang ◽  
Roy Rasmussen ◽  
Daniel Breed
Keyword(s):  
Doppler Radar ◽  
Weather Conditions ◽  
Cold Season ◽  
Near Surface ◽  
Medicine Bow Mountains ◽  
Orographic Clouds ◽  
Surface Reflectivity ◽  
Glaciogenic Seeding ◽  
The Impact ◽  
Composite Data

Abstract Data from an airborne vertically pointing millimeter-wave Doppler radar are used to study the cloud microphysical effect of glaciogenic seeding of cold-season orographic clouds. Fixed flight tracks were flown downstream of ground-based silver iodide (AgI) generators in the Medicine Bow Mountains of Wyoming. Composite data from seven flights, each with a no-seeding period followed by a seeding period, indicate that radar reflectivity was higher near the ground during the seeding periods. Several physical considerations argue in favor of the hypothesis that the increase in near-surface reflectivity is attributed to AgI seeding. While the increase in near-surface reflectivity and thus snowfall rate are statistically significant, caution is warranted in view of the large natural variability of weather conditions and the small size of the dataset.

scholarly journals Differential Reflectivity Calibration and Antenna Temperature

2017 ◽  
Vol 34 (9) ◽  
pp. 1885-1906 ◽  
Author(s):  
J. C. Hubbert
Keyword(s):  
Thermal Expansion ◽  
Doppler Radar ◽  
Radar Data ◽  
The Sun ◽  
Dual Polarization ◽  
Calibration Technique ◽  
Atmospheric Research ◽  
Using Data ◽  
Power Measurements ◽  
Differential Reflectivity

AbstractTemporal differential reflectivity bias variations are investigated using the National Center for Atmospheric Research (NCAR) S-band dual-polarization Doppler radar (S-Pol). Using data from the Multi-Angle Snowflake Camera-Ready (MASCRAD) Experiment, S-Pol measurements over extended periods reveal a significant correlation between the ambient temperature at the radar site and the bias. Using radar scans of the sun and the ratio of cross-polar powers, the components of the radar that cause the variation of the bias are identified. It is postulated that the thermal expansion of the antenna is likely the primary cause of the observed bias variation. The cross-polar power (CP) calibration technique, which is based on the solar and cross-polar power measurements, is applied to data from the Plains Elevated Convection at Night (PECAN) field project. The bias from the CP technique is compared to vertical-pointing bias measurements, and the uncertainty of the bias estimates is given. An algorithm is derived to correct the radar data for the time- and temperature-varying bias. Bragg scatter measurements are used to corroborate the CP technique bias measurements.

scholarly journals A Case Study of Radar Observations and WRF LES Simulations of the Impact of Ground-Based Glaciogenic Seeding on Orographic Clouds and Precipitation. Part II: AgI Dispersion and Seeding Signals Simulated by WRF

2016 ◽  
Vol 55 (2) ◽  
pp. 445-464 ◽  
Author(s):  
Lulin Xue ◽  
Xia Chu ◽  
Roy Rasmussen ◽  
Daniel Breed ◽  
Bart Geerts
Keyword(s):  
Nucleation Rate ◽  
Wrf Model ◽  
Grid Spacing ◽  
Medicine Bow Mountains ◽  
Eddy Simulation ◽  
Cloud Dynamics ◽  
Vertical Dispersion ◽  
Orographic Clouds ◽  
Glaciogenic Seeding ◽  
The Impact

AbstractSeveral Weather Research and Forecasting (WRF) Model simulations of natural and seeded clouds have been conducted in non-LES and LES (large-eddy simulation) modes to investigate the seeding impact on wintertime orographic clouds for an actual seeding case on 18 February 2009 in the Medicine Bow Mountains of Wyoming. Part I of this two-part series has shown the capability of WRF LES with 100-m grid spacing to capture the essential environmental conditions by comparing the model results with measurements from a variety of instruments. In this paper, the silver iodide (AgI) dispersion features, the AgI impacts on the turbulent kinetic energy (TKE), the microphysics, and the precipitation are examined in detail using the model data, which leads to five main results. 1) The vertical dispersion of AgI particles is more efficient in cloudy conditions than in clear conditions. 2) The wind shear and the buoyancy are both important TKE production mechanisms in the wintertime PBL over complex terrain in cloudy conditions. The buoyancy-induced eddies are more responsible for the AgI vertical dispersion than the shear-induced eddies are. 3) Seeding has insignificant effects on the cloud dynamics. 4) AgI particles released from the ground-based generators affect the cloud within the boundary layer below 1 km AGL through nucleating extra ice crystals, converting liquid water into ice, depleting more vapor, and generating more precipitation on the ground. The AgI nucleation rate is inversely related to the natural ice nucleation rate. 5) The seeding effects on the ground precipitation are confined within narrow areas. The relative seeding effect ranges between 5% and 20% for the simulations with different grid spacing.

Sign in / Sign up

Export Citation Format

Share Document