An Empirical Parameterization of the Subgrid-Scale Distribution of Water Vapor in the UTLS for Atmospheric General Circulation Models

IF 3.8 2区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Geophysical Research: Atmospheres Pub Date : 2024-10-10 DOI:10.1029/2024JD040981
Audran Borella, Étienne Vignon, Olivier Boucher, Susanne Rohs
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Abstract

Temperature and water vapor are known to fluctuate on multiple scales. In this study 27 years of airborne measurements of temperature and relative humidity from In-service Aircraft for a Global Observing System (IAGOS) are used to parameterize the distribution of water vapor in the upper troposphere and lower stratosphere. The parameterization is designed to simulate water vapor fluctuations within gridboxes of atmospheric general circulation models (AGCMs) with typical size of a few tens to a few hundred kilometers. The distributions currently used in such models are often not supported by observations at high altitude. More sophisticated distributions are key to represent ice supersaturation, a physical phenomenon that plays a major role in the formation of natural cirrus and contrail cirrus. Here the observed distributions are fitted with a beta law whose parameters are adjusted from the gridbox mean variables. More specifically the standard deviation and skewness of the distributions are expressed as empirical functions of the average temperature and specific humidity, two typical prognostic variables of AGCMs. Thus, the distribution of water vapor is fully parameterized for a use in these models. The new parameterization reproduces the observed distributions with a determination coefficient always greater than 0.917 and with a mean value of 0.997. The parameterization is robust to a selection of various geographical subsets of data and to gridbox sizes varying between 25 and 300 km.

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UTLS中水汽亚网格尺度分布的经验参数化,用于大气环流模式
众所周知,温度和水汽会在多个尺度上波动。在这项研究中,利用全球观测系统在役飞机(IAGOS)27 年的温度和相对湿度机载测量数据,对对流层上部和平流层下部的水汽分布进行了参数化。参数设置的目的是模拟大气环流模式(AGCM)网格框内的水汽波动,网格框的典型大小为几十公里到几百公里。这些模型中目前使用的分布通常得不到高空观测数据的支持。更复杂的分布是表示冰过饱和的关键,冰过饱和是一种物理现象,在自然卷云和忌雾卷云的形成中起着重要作用。在这里,观测到的分布用贝塔定律拟合,其参数根据网格框平均变量进行调整。更具体地说,水汽分布的标准偏差和倾斜度是以平均温度和比湿度(AGCMs 的两个典型预报变量)的经验函数来表示的。因此,水汽的分布被完全参数化,可用于这些模式。新的参数化重现了观测到的分布,确定系数始终大于 0.917,平均值为 0.997。参数化对选择各种地理数据子集以及 25 至 300 千米之间的网格框大小都是稳健的。
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来源期刊
Journal of Geophysical Research: Atmospheres
Journal of Geophysical Research: Atmospheres Earth and Planetary Sciences-Geophysics
CiteScore
7.30
自引率
11.40%
发文量
684
期刊介绍: JGR: Atmospheres publishes articles that advance and improve understanding of atmospheric properties and processes, including the interaction of the atmosphere with other components of the Earth system.
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