Sisi Chen, L. Xue, S. Tessendorf, Thomas H. Chubb, Andrew Peace, Luis Ackermann, Artur Gevorgyan, Yi Huang, S. Siems, Roy Rasmussen, Suzanne Kenyon, Johanna Speirs
{"title":"澳大利亚雪山上空冬季地形云播种模拟","authors":"Sisi Chen, L. Xue, S. Tessendorf, Thomas H. Chubb, Andrew Peace, Luis Ackermann, Artur Gevorgyan, Yi Huang, S. Siems, Roy Rasmussen, Suzanne Kenyon, Johanna Speirs","doi":"10.1175/jamc-d-23-0012.1","DOIUrl":null,"url":null,"abstract":"\nThis study presents the first numerical simulations of seeded clouds over the Snowy Mountains of Australia. WRF-WxMod®, a novel glaciogenic cloud seeding model, was utilized to simulate the cloud response to winter orographic seeding under various meteorological conditions. Three cases during the 2018 seeding periods were selected for model evaluation, coinciding with an intensive ground-based measurement campaign. The campaign data were used for model validation and evaluation.\nComparisons between simulations and observations demonstrate that the model realistically represents cloud structures, liquid water path, and precipitation. Sensitivity tests were performed to pinpoint key uncertainties in simulating natural and seeded clouds and precipitation processes. They also shed light on the complex interplay between various physical parameters/processes and their interaction with large-scale meteorology.\nOur study found that in unseeded scenarios, the warm and cold biases in different initialization datasets can heavily influence the intensity and phase of natural precipitation. Secondary ice production via Hallett-Mossop processes exerts a secondary influence. On the other hand, the seeding impacts are primarily sensitive to aerosol conditions and the natural ice nucleation process. Both factors alter the supercooled liquid water availability and the precipitation phase, consequently impacting the AgI nucleation rate. Furthermore, model sensitivities were inconsistent across cases, indicating no single model configuration optimally represents all three cases. This highlights the necessity of employing an ensemble approach for a more comprehensive and accurate assessment of the seeding impact.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simulating Wintertime Orographic Cloud Seeding over the Snowy Mountains of Australia\",\"authors\":\"Sisi Chen, L. Xue, S. Tessendorf, Thomas H. Chubb, Andrew Peace, Luis Ackermann, Artur Gevorgyan, Yi Huang, S. Siems, Roy Rasmussen, Suzanne Kenyon, Johanna Speirs\",\"doi\":\"10.1175/jamc-d-23-0012.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nThis study presents the first numerical simulations of seeded clouds over the Snowy Mountains of Australia. WRF-WxMod®, a novel glaciogenic cloud seeding model, was utilized to simulate the cloud response to winter orographic seeding under various meteorological conditions. Three cases during the 2018 seeding periods were selected for model evaluation, coinciding with an intensive ground-based measurement campaign. The campaign data were used for model validation and evaluation.\\nComparisons between simulations and observations demonstrate that the model realistically represents cloud structures, liquid water path, and precipitation. Sensitivity tests were performed to pinpoint key uncertainties in simulating natural and seeded clouds and precipitation processes. They also shed light on the complex interplay between various physical parameters/processes and their interaction with large-scale meteorology.\\nOur study found that in unseeded scenarios, the warm and cold biases in different initialization datasets can heavily influence the intensity and phase of natural precipitation. Secondary ice production via Hallett-Mossop processes exerts a secondary influence. On the other hand, the seeding impacts are primarily sensitive to aerosol conditions and the natural ice nucleation process. Both factors alter the supercooled liquid water availability and the precipitation phase, consequently impacting the AgI nucleation rate. Furthermore, model sensitivities were inconsistent across cases, indicating no single model configuration optimally represents all three cases. 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Simulating Wintertime Orographic Cloud Seeding over the Snowy Mountains of Australia
This study presents the first numerical simulations of seeded clouds over the Snowy Mountains of Australia. WRF-WxMod®, a novel glaciogenic cloud seeding model, was utilized to simulate the cloud response to winter orographic seeding under various meteorological conditions. Three cases during the 2018 seeding periods were selected for model evaluation, coinciding with an intensive ground-based measurement campaign. The campaign data were used for model validation and evaluation.
Comparisons between simulations and observations demonstrate that the model realistically represents cloud structures, liquid water path, and precipitation. Sensitivity tests were performed to pinpoint key uncertainties in simulating natural and seeded clouds and precipitation processes. They also shed light on the complex interplay between various physical parameters/processes and their interaction with large-scale meteorology.
Our study found that in unseeded scenarios, the warm and cold biases in different initialization datasets can heavily influence the intensity and phase of natural precipitation. Secondary ice production via Hallett-Mossop processes exerts a secondary influence. On the other hand, the seeding impacts are primarily sensitive to aerosol conditions and the natural ice nucleation process. Both factors alter the supercooled liquid water availability and the precipitation phase, consequently impacting the AgI nucleation rate. Furthermore, model sensitivities were inconsistent across cases, indicating no single model configuration optimally represents all three cases. This highlights the necessity of employing an ensemble approach for a more comprehensive and accurate assessment of the seeding impact.
期刊介绍:
The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.