Importance of Using Observations of Mixing Depths in order to Avoid Large Prediction Errors by a Transport and Dispersion Model

Author:

White J. M.1,Bowers J. F.1,Hanna S. R.2,Lundquist J. K.3

Affiliation:

1. Dugway Proving Ground, Dugway, Utah

2. Hanna Consultants, Inc., Kennebunkport, Maine

3. Lawrence Livermore National Laboratory, Livermore, California

Abstract

Abstract The mixing depth of the boundary layer is an input to most atmospheric transport and dispersion (ATD) models, which obtain mixing depths in one of four ways: 1) observations by radiosondes, sodars, or other devices; 2) simulations by regional or mesoscale meteorological models; 3) parameterizations based on boundary layer similarity theory; or 4) climatological averages. This paper describes a situation during a field experiment when exceptionally low mixing depths persisted in the morning and led to relatively high observed tracer concentrations. The low mixing depths were caused by synoptic effects associated with a nearby stationary front and the outflow from a mesoscale thunderstorm complex located 20–50 km away. For the same time period, the ATD model-parameterized mixing depth was a factor of 5–10 higher, leading to predicted concentrations that were less than the observations by a factor of 5–10. The synoptic situation is described and local radiosonde and radar observations of mixing depth are presented, including comparisons with other more typical days. Time series of local observations of near-surface sensible heat fluxes are also plotted to demonstrate the suppression of turbulence by negative sensible heat fluxes during the period in question.

Publisher

American Meteorological Society

Subject

Atmospheric Science,Ocean Engineering

Reference18 articles.

1. Overview of Joint Urban 2003—An atmospheric dispersion study in Oklahoma City.;Allwine,2004

2. Evaluation of the NCEP mesoscale Eta Model convective boundary layer for air quality applications.;Angevine;Mon. Wea. Rev.,2001

3. Boundary-layer depth and entrainment zone characterization with a boundary-layer profiler.;Angevine;Bound.-Layer Meteor.,1994

4. Air Pollution Meteorology and Dispersion.;Arya,1999

5. Convective boundary layer depth: Improved measurement by Doppler radar wind profiler using fuzzy logic methods.;Bianco;J. Atmos. Oceanic Technol.,2002

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