Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2016.11.004 |
Assimilating synthetic hyperspectral sounder temperature and humidity retrievals to improve severe weather forecasts | |
Jones, Thomas A.1,2; Koch, Steven2; Li, Zhenglong3 | |
2017-04-01 | |
发表期刊 | ATMOSPHERIC RESEARCH |
ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2017 |
卷号 | 186页码:43733 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Assimilation of hyperspectral sounder data into numerical weather prediction (NWP) models has provenvital to generating accurate model analyses of tropospheric temperature and humidity where few conventional observations exist. Applications to storm-scale models are limited since the low temporal resolution provided by polar orbiting sensors cannot adequately sample rapidly changing environments associated with high impact weather events. To address this limitation, hyperspectral sounders have been proposed for geostationary orbiting satellites, but these have yet to be built and launched in part due to much higher engineering costs and a lack of a definite requirement for the data. This study uses an Observation System Simulation Experiment (OSSE) approach to simulate temperature and humidity profiles from a hypothetical geostationary-based sounder from a nature run of a high impact weather event on 20 May 2013. The simulated observations are then assimilated using an ensemble adjustment Kalman filter approach, testing both hourly and 15 minute cycling to determine their relative effectiveness at improving the near storm environment Results indicate that assimilating both temperature and humidity profiles reduced mid-tropospheric both mean and standard deviation of analysis and forecast errors compared to assimilating conventional observations alone. The 15 minute cycling generally produced the lowest errors while also generating the best 2-4 hour updraft helicity forecasts of ongoing convection. This study indicates the potential for significant improvement in short-term forecasting of severe storms from the assimilation of hyperspectral geostationary satellite data. However, more studies are required using improved OSSE designs encompassing multiple storm environments and additional observation types such as radar reflectivity to fully define the effectiveness of assimilating geostationary hyperspectral observations for high impact weather forecasting applications. (C) 2016 Elsevier B.V. All rights reserved. |
英文关键词 | Hyperspectral sounders Ensemble data assimilation Storm-scale data assimilation OSSE |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000392557700002 |
WOS关键词 | ENSEMBLE KALMAN FILTER ; SYSTEM SIMULATION EXPERIMENTS ; EXPLICIT FORECASTS ; PART I ; IMPACT ; RADIANCE ; RADAR ; IMPLEMENTATION ; MODEL ; AIRS/AMSU/HSB |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/38382 |
专题 | 地球科学 |
作者单位 | 1.Univ Oklahoma, Cooperat Inst Mesoscale Meteorol Studies, Norman, OK 73019 USA; 2.NOAA, Natl Severe Storms Lab, Norman, OK 73069 USA; 3.Univ Wisconsin, Cooperat Inst Meteorol Satellite Studies, Madison, WI USA |
推荐引用方式 GB/T 7714 | Jones, Thomas A.,Koch, Steven,Li, Zhenglong. Assimilating synthetic hyperspectral sounder temperature and humidity retrievals to improve severe weather forecasts[J]. ATMOSPHERIC RESEARCH,2017,186:43733. |
APA | Jones, Thomas A.,Koch, Steven,&Li, Zhenglong.(2017).Assimilating synthetic hyperspectral sounder temperature and humidity retrievals to improve severe weather forecasts.ATMOSPHERIC RESEARCH,186,43733. |
MLA | Jones, Thomas A.,et al."Assimilating synthetic hyperspectral sounder temperature and humidity retrievals to improve severe weather forecasts".ATMOSPHERIC RESEARCH 186(2017):43733. |
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