干旱区生态环境知识资源中心(Arid): An Automated Detection Methodology for Dry Well-Mixed Layers

Arid

DOI	10.1175/JTECH-D-18-0149.1
	An Automated Detection Methodology for Dry Well-Mixed Layers
	Nicholls, Stephen D.1,2; Mohr, Karen I.3
通讯作者	Nicholls, Stephen D.
来源期刊	JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY
ISSN	0739-0572
EISSN	1520-0426
出版年	2019
卷号	36 期号:5 页码:761-779
英文摘要	The intense surface heating over arid land surfaces produces dry well-mixed layers (WML) via dry convection. These layers are characterized by nearly constant potential temperature and low, nearly constant water vapor mixing ratio. To further the study of dry WMLs, we created a detection methodology and supporting software to automate the identification and characterization of dry WMLs from multiple data sources including rawinsondes, remote sensing platforms, and model products. The software is a modular code written in Python, an open-source language. Radiosondes from a network of synoptic stations in North Africa were used to develop and test the WML detection process. The detection involves an iterative decision tree that ingests a vertical profile from an input data file, performs a quality check for sufficient data density, and then searches upward through the column for successive points where the simultaneous changes in water vapor mixing ratio and potential temperature are less than the specified maxima. If points in the vertical profile meet the dry WML identification criteria, statistics are generated detailing the characteristics of each layer in the profile. At the end of the vertical profile analysis, there is an option to plot analyzed profiles in a variety of file formats. Initial results show that the detection methodology can be successfully applied across a wide variety of input data and North African environments and for all seasons. It is sensitive enough to identify dry WMLs from other types of isentropic phenomena such as subsidence layers and distinguish the current day's dry WML from previous days.
英文关键词	Atmosphere Africa Algorithms Profilers atmospheric Radiosonde observations
类型	Article
语种	英语
国家	USA
开放获取类型	Bronze, Green Submitted
收录类别	SCI-E
WOS记录号	WOS:000465566800001
WOS关键词	SEVERE-STORM ENVIRONMENT ; ATMOSPHERIC BOUNDARY-LAYER ; AFRICAN MONSOON ONSET ; CONVECTIVE COLD POOL ; RETRIEVAL ALGORITHM ; EXTREME CONVECTION ; DATA ASSIMILATION ; AIR OUTBREAKS ; ERA-INTERIM ; WEST-AFRICA
WOS类目	Engineering, Ocean ; Meteorology & Atmospheric Sciences
WOS研究方向	Engineering ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/216810
作者单位	1.Univ Maryland Baltimore Cty, Joint Ctr Earth Syst Technol, Baltimore, MD 21228 USA; 2.NASA, Mesoscale Atmospher Proc Lab, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA; 3.NASA, Lab Atmospheres, Earth Sci Div, Goddard Space Flight Ctr, Greenbelt, MD USA
推荐引用方式 GB/T 7714	Nicholls, Stephen D.,Mohr, Karen I.. An Automated Detection Methodology for Dry Well-Mixed Layers[J],2019,36(5):761-779.
APA	Nicholls, Stephen D.,&Mohr, Karen I..(2019).An Automated Detection Methodology for Dry Well-Mixed Layers.JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY,36(5),761-779.
MLA	Nicholls, Stephen D.,et al."An Automated Detection Methodology for Dry Well-Mixed Layers".JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY 36.5(2019):761-779.