Cloud Seeding Effects on Precipitation Intensity and Duration of Wintertime Orographic Clouds

1971 ◽  
Vol 10 (5) ◽  
pp. 1006-1010 ◽  
Author(s):  
Charles F. Chappell ◽  
Lewis O. Grant ◽  
Paul W. Mielke
Keyword(s):  
Precipitation Intensity ◽  
Cloud Seeding ◽  
Orographic Clouds ◽  
Seeding Effects

scholarly journals Review of Wintertime Orographic Cloud Seeding

1986 ◽  
Vol 43 ◽  
pp. 87-104 ◽  
Author(s):  
Robert D. Elliott
Keyword(s):  
Scientific Literature ◽  
Doppler Radar ◽  
Cloud Seeding ◽  
Weather Modification ◽  
The Past ◽  
Orographic Clouds ◽  
The 1960S ◽  
Orographic Cloud ◽  
Microwave Radiometers ◽  
Seeding Effects

Abstract This review provides a sketchy background of orographic weather modification activities prior to the 1960s, followed by a more critical review of major orographic projects carried out and reported in the scientific literature during the past 25 years. In the earlier of these major projects, evaluation of results had been based largely upon comparisons of seeded and nonseeded precipitation experimental units stratified by various sounding-derived parameters in an attempt to amplify the physical significance of the seeding effects within various sub-types of orographic clouds. The later major projects are still underway with no final evaluations having been presented. However, a wealth of significant data analyses have been reported that provide important insights into the various natural and seeding precipitation mechanisms. Much of this is attributable to the new observational tools in use, which include airborne and ground microphysical sensors, doppler radar, and microwave radiometers.

Quantifying snowfall from orographic cloud seeding

2020 ◽  
Author(s):  
Katja Friedrich ◽  
Kyoko Ikeda ◽  
Sarah Tessendorf ◽  
Jeffrey French ◽  
Robert Rauber ◽  
...  
Keyword(s):  
Water Management ◽  
Silver Iodide ◽  
Management Strategy ◽  
Radar Reflectivity ◽  
Cloud Seeding ◽  
Straight Line ◽  
Orographic Clouds ◽  
Increasing Demand ◽  
Orographic Cloud ◽  
Water Management Strategy

<p>Cloud seeding has been used as one water management strategy to overcome the increasing demand for water despite decades of inconclusive results on the efficacy of cloud seeding. In this study snowfall accumulation from glaciogenic cloud seeding is quantified based on snow gauge and radar observations from three days in January 2017, when orographic clouds in the absent of natural precipitation were seeded with silver iodide (AgI) in the Payette basin of Idaho during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). On each day, a seeding aircraft equipped with AgI flares flew back and forth on a straight-line flight track producing a zig-zag pattern representing two to eight lines of clouds visible through enhancements in radar reflectivity. As these seeding lines started to form precipitation, they passed over several snow gauges and through the radar observational domain. For the three cases presented here, precipitation gauges measured increases between 0.05-0.3 mm as precipitation generated by cloud seeding pass over the instruments. A variety of relationships between radar reflectivity factor and liquid equivalent snowfall rate were used to quantify snowfall within the radar observation domain. For the three cases, snowfall occurred within the radar observational domain between 25 -160 min producing a total amount of water generated by cloud seeding ranging from 123,220 to 339,540 m3 using the best-match Ze-S relationship. Uncertainties in radar reflectivity estimated snowfall are provided by considering not only the best-match Ze-S relationship but also an ensemble of Ze-S relationships based on the range of coefficients published from previous studies and then examining the percentile of snowfall estimates based on all of the Ze-S relationships within the ensemble. Considering the interquartile range and 5<sup>th</sup>/95<sup>th</sup> percentiles, uncertainties in total amount of water generated by cloud seeding can range between 20-45% compared to the best-math estimates. These results provide new insights towards understanding how cloud seeding impacts precipitation and its distribution across a region.</p>

Hypotheses for the Climax Wintertime Orographic Cloud Seeding Experiments

1986 ◽  
Vol 43 ◽  
pp. 105-108 ◽  
Author(s):  
Lewis O. Grant
Keyword(s):  
Hypothesis Testing ◽  
Remotely Sensed ◽  
Cloud Seeding ◽  
Statistical Experiments ◽  
Orographic Clouds ◽  
Orographic Cloud

Abstract The hypothesis used for the initial Climax wintertime cloud seeding experiment and for subsequent Climax replication-type experiments are described and briefly discussed. More recent physical studies of Colorado orographic clouds and seeding hypotheses are briefly summarized. These later tests and studies of orographic cloud seeding hypotheses emphasized direct and remotely sensed cloud and precipitation measurements utilizing instrumentation and modeling capabilities not available during the Climax statistical experiments. The conclusions suggested from the hypothesis testing, considering both the statistical experiments and the later physical studies, are summarized.

Numerical study of the cloud seeding effects

1990 ◽  
Vol 42 (2) ◽  
pp. 145-164 ◽  
Author(s):  
M. Ćurić ◽  
D. Janc
Keyword(s):  
Numerical Study ◽  
Cloud Seeding ◽  
Seeding Effects

Implementation of a Silver Iodide Cloud-Seeding Parameterization in WRF. Part II: 3D Simulations of Actual Seeding Events and Sensitivity Tests

2013 ◽  
Vol 52 (6) ◽  
pp. 1458-1476 ◽  
Author(s):  
Lulin Xue ◽  
Sarah A. Tessendorf ◽  
Eric Nelson ◽  
Roy Rasmussen ◽  
Daniel Breed ◽  
...  
Keyword(s):  
Silver Iodide ◽  
Winter Season ◽  
Wrf Model ◽  
Reanalysis Data ◽  
Atmospheric Conditions ◽  
Cloud Seeding ◽  
The North ◽  
Cloud Properties ◽  
Regional Reanalysis ◽  
Seeding Effects

AbstractFour cloud-seeding cases over southern Idaho during the 2010/11 winter season have been simulated by the Weather Research and Forecasting (WRF) model using the coupled silver iodide (AgI) cloud-seeding scheme that was described in Part I. The seeding effects of both ground-based and airborne seeding as well as the impacts of model physics, seeding rates, location, timing, and cloud properties on seeding effects have been investigated. The results were compared with those from Part I and showed the following: 1) For the four cases tested in this study, control simulations driven by the Real-Time Four Dimensional Data Assimilation (RTFDDA) WRF forecast data generated more realistic atmospheric conditions and precipitation patterns than those driven by the North America Regional Reanalysis data. Sensitivity experiments therefore used the RTFDDA data. 2) Glaciogenic cloud seeding increased orographic precipitation by less than 1% over the simulation domain, including the Snake River basin, and by up to 5% over the target areas. The local values of the relative precipitation enhancement by seeding were ~20%. Most of the enhancement came from vapor depletion. 3) The seeding effect was inversely related to the natural precipitation efficiency but was positively related to seeding rates. 4) Airborne seeding is generally more efficient than ground-based seeding in terms of targeting, but its efficiency depends on local meteorological conditions. 5) The normalized seeding effects ranged from 0.4 to 1.6 under various conditions for a certain seeding event.

A Transformational Approach to Winter Orographic Weather Modification Research: The SNOWIE Project

2019 ◽  
Vol 100 (1) ◽  
pp. 71-92 ◽  
Author(s):  
Sarah A. Tessendorf ◽  
Jeffrey R. French ◽  
Katja Friedrich ◽  
Bart Geerts ◽  
Robert M. Rauber ◽  
...  
Keyword(s):  
Silver Iodide ◽  
Supercooled Liquid ◽  
Cloud Seeding ◽  
Remotely Sensed Data ◽  
Weather Modification ◽  
Before And After ◽  
Orographic Clouds ◽  
Seeding Material ◽  
Airborne Sensors

AbstractThe Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) project aims to study the impacts of cloud seeding on winter orographic clouds. The field campaign took place in Idaho between 7 January and 17 March 2017 and employed a comprehensive suite of instrumentation, including ground-based radars and airborne sensors, to collect in situ and remotely sensed data in and around clouds containing supercooled liquid water before and after seeding with silver iodide aerosol particles. The seeding material was released primarily by an aircraft. It was hypothesized that the dispersal of the seeding material from aircraft would produce zigzag lines of silver iodide as it dispersed downwind. In several cases, unambiguous zigzag lines of reflectivity were detected by radar, and in situ measurements within these lines have been examined to determine the microphysical response of the cloud to seeding. The measurements from SNOWIE aim to address long-standing questions about the efficacy of cloud seeding, starting with documenting the physical chain of events following seeding. The data will also be used to evaluate and improve computer modeling parameterizations, including a new cloud-seeding parameterization designed to further evaluate and quantify the impacts of cloud seeding.

Microphysical characteristics and evolution of seeded orographic clouds

2021 ◽  
Author(s):  
Katja Friedrich ◽  
Jeffrey R. French ◽  
Sarah A. Tessendorf ◽  
Melinda Hatt ◽  
Courtney Weeks ◽  
...  
Keyword(s):  
Silver Iodide ◽  
Particle Growth ◽  
Liquid Water Content ◽  
Atmospheric Conditions ◽  
Cloud Seeding ◽  
Spatiotemporal Evolution ◽  
Widespread Occurrence ◽  
Orographic Clouds ◽  
Microphysical Processes

AbstractThe spatial distribution and magnitude of snowfall resulting from cloud seeding with silver iodide (AgI) is closely linked to atmospheric conditions, seeding operations, and dynamical, thermodynamical, and microphysical processes. Here, microphysical processes leading to ice and snow production are analyzed in orographic clouds for three cloud seeding events, each with light or no natural precipitation and well-defined, traceable seeding lines. Airborne and ground-based radar observations are linked to in-situ cloud and precipitation measurements to determine the spatiotemporal evolution of ice initiation, particle growth, and snow fallout in seeded clouds. These processes and surface snow amounts are explored as particle plumes evolve from varying amounts of AgI released, and within changing environmental conditions, including changes in liquid water content (LWC) along and downwind of the seeding track, wind speed, and shear. More AgI did not necessarily produce more liquid equivalent snowfall (LESnow). The greatest amount of LESnow, largest area covered by snowfall, and highest peak snowfall produced through seeding occurred on the day with the largest and most widespread occurrence of supercooled drizzle, highest wind shear, and greater LWC along and downwind of the seeding track. The day with the least supercooled drizzle and the lowest LWC downwind of the seeding track produced the smallest amount of LESnow through seeding. The stronger the wind, the farther away the snowfall occurred from the seeding track.

An Assessment of Winter Orographic Precipitation and Cloud-Seeding Potential in Wyoming

2020 ◽  
Vol 59 (7) ◽  
pp. 1217-1238 ◽  
Author(s):  
Sarah A. Tessendorf ◽  
Kyoko Ikeda ◽  
Courtney Weeks ◽  
Roy Rasmussen ◽  
Jamie Wolff ◽  
...  
Keyword(s):  
High Resolution ◽  
Model Simulation ◽  
Orographic Precipitation ◽  
Atmospheric Conditions ◽  
Cloud Seeding ◽  
Mountain Ranges ◽  
Precipitation Patterns ◽  
Resolution Model ◽  
Orographic Clouds ◽  
High Resolution Model

AbstractThis paper presents an evaluation of the precipitation patterns and seedability of orographic clouds in Wyoming using SNOTEL precipitation data and a high-resolution multiyear model simulation over an 8-yr period. A key part of assessing the potential for cloud seeding is to understand the natural precipitation patterns and how often atmospheric conditions and clouds meet cloud-seeding criteria. The analysis shows that high-resolution model simulations are useful tools for studying patterns of orographic precipitation and establishing the seedability of clouds by providing information that is either missed by or not available from current observational networks. This study indicates that the ground-based seeding potential in some mountain ranges in Wyoming is limited by flow blocking and/or prevailing winds that were not normal to the barrier to produce upslope flow. Airborne seeding generally had the most potential for all of the mountain ranges that were studied.

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