An OSSE Study of the Impact of Micropulse Differential Absorption Lidar (MPD) Water Vapor Profiles on Convective Weather Forecasting
| العنوان: | An OSSE Study of the Impact of Micropulse Differential Absorption Lidar (MPD) Water Vapor Profiles on Convective Weather Forecasting |
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| المؤلفون: | Junkyung Kay, Tammy M. Weckwerth, Wen-Chau Lee, Jenny Sun, Glen Romine |
| المصدر: | Monthly Weather Review. 150:2787-2811 |
| بيانات النشر: | American Meteorological Society, 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Atmospheric Science |
| الوصف: | The National Center for Atmospheric Research (NCAR) and Montana State University jointly developed water vapor micropulse differential absorption lidars (MPDs) that are a significant advance in eye-safe, unattended, lidar-based water vapor remote sensing. MPD is designed to provide continuous vertical water vapor profiles with high vertical (150 m) and temporal resolution (5 min) in the lower troposphere. This study aims to investigate MPD observation impacts and the scientific significance of MPDs for convective weather analyses and predictions using observation system simulation experiments (OSSEs). In this study, the Data Assimilation Research Testbed (DART) and the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model are used to conduct OSSEs for a case study of a mesoscale convective system (MCS) observed during the Plains Elevated Convection At Night (PECAN) experiment. A poor-performing control simulation that was drawn from a 40-member ensemble at 3-km resolution is markedly improved by assimilation of simulated observations drawn from a more skillful simulation that served as the nature run at 1-km resolution. In particular, assimilating surface observations corrected surface warm front structure errors, while MPD observations remedied errors in low- to midlevel moisture ahead of the MCS. Collectively, these analyses changes led to markedly improved short-term predictions of convection initiation, evolution, and precipitation of the MCS in the simulations on 15 July 2015. For this case study, the OSSE results indicate that a more dense MPD network results in better prediction performance for convective precipitation while degrading light precipitation prediction performance due to an imbalance of the analysis at large scales. |
| تدمد: | 1520-0493 0027-0644 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::b5d8c2011ebf081e73ea3ddbb2eab5b4 https://doi.org/10.1175/mwr-d-21-0284.1 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........b5d8c2011ebf081e73ea3ddbb2eab5b4 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15200493 00270644 |
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