High-Latitude Atmospheric Motion Vectors from Composite Satellite Data

Author:

Lazzara Matthew A.1,Dworak Richard2,Santek David A.2,Hoover Brett T.2,Velden Christopher S.2,Key Jeffrey R.3

Affiliation:

1. Antarctic Meteorological Research Center, and Cooperative Institute for Meteorological Satellite Studies, Space Science and Engineering Center, University of Wisconsin—Madison, Madison, Wisconsin

2. Cooperative Institute for Meteorological Satellite Studies, Space Science and Engineering Center, University of Wisconsin—Madison, Madison, Wisconsin

3. NOAA/NESDIS/Center for Satellite Applications and Research, Madison, Wisconsin

Abstract

AbstractAtmospheric motion vectors (AMVs) are derived from satellite-observed motions of clouds and water vapor features. They provide crucial information in regions void of conventional observations and contribute to forecaster diagnostics of meteorological conditions, as well as numerical weather prediction. AMVs derived from geostationary (GEO) satellite observations over the middle latitudes and tropics have been utilized operationally since the 1980s; AMVs over the polar regions derived from low‐earth (polar)‐orbiting (LEO) satellites have been utilized since the early 2000s. There still exists a gap in AMV coverage between these two sources in the latitude band poleward of 60° and equatorward of 70° (both hemispheres). To address this AMV gap, the use of a novel approach to create image sequences that consist of composites derived from a combination of LEO and GEO observations that extend into the deep middle latitudes is explored. Experiments are performed to determine whether the satellite composite images can be employed to generate AMVs over the gap regions. The derived AMVs are validated over both the Southern Ocean/Antarctic and the Arctic gap regions over a multiyear period using rawinsonde wind observations. In addition, a two-season numerical model impact study using the Global Forecast System indicates that the assimilation of these AMVs can improve upon the control (operational) forecasts, particularly during lower-skill (dropout) events.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The JRA-3Q Reanalysis;Journal of the Meteorological Society of Japan. Ser. II;2024

2. Pre-Processing, Quality Assurance, and Use of Global Atmospheric Motion Vector Observations in CRA;Journal of Meteorological Research;2022-12

3. Assimilation of satellite data in numerical weather prediction. Part II : Recent years;Quarterly Journal of the Royal Meteorological Society;2022-01-11

4. Two-Stage Artificial Intelligence Algorithm for Calculating Moisture-Tracking Atmospheric Motion Vectors;Journal of Applied Meteorology and Climatology;2021-12

5. Assimilation of Observations from Meteorological Satellites in the Hydrometcenter of Russia;Russian Meteorology and Hydrology;2021-12

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3