Beyond surface fluxes: Observational and computational needs of multilayer canopy models – A walnut orchard test case

IF 6.6 1区 农林科学 Q1 AGRONOMY
Agricultural and Forest Meteorology Pub Date : 2026-03-01 Epub Date: 2025-12-02 DOI:10.1016/j.agrformet.2025.110960
Gordon B. Bonan , Sean P. Burns , Edward G. Patton
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引用次数: 0

Abstract

Land surface models simulate fluxes exchanged between the land and atmosphere in weather and climate models. The prevailing modeling paradigm uses a big-leaf canopy parameterization that is not vertically-resolved. Multilayer canopy models have received interest over the past several years as a means to improve surface fluxes and enable new science. We present results from a comparison of the Community Land Model (CLM) multilayer canopy model (CLM-ml v2) and observations of air temperature, specific humidity, wind speed, and fluxes (net radiation, sensible heat, latent heat, momentum) at multiple heights in and above a walnut orchard during the Canopy Horizontal Array Turbulence Study (CHATS). The dataset provides a benchmark with which to test multilayer models. Above-canopy sensible heat, latent heat, and momentum fluxes are well simulated under a range of atmospheric regimes spanning strongly unstable, weakly unstable, near-neutral, weakly stable, and strongly stable, as are vertical profiles of fluxes within the canopy. Vertical profiles of wind speed closely match the observations under all stability regimes. Vertical profiles of air temperature and specific humidity are well simulated except for strongly stable conditions, when the first-order turbulence closure cannot represent within-canopy non-local vertical mixing that would otherwise transport the cool air produced by radiative cooling of the upper canopy downward to the lower canopy. Our model–data comparison highlights the potential of multilayer models to simulate the surface air space. The multilayer canopy model is simpler and more consistent with theory than is the CLM big-leaf canopy model, and it modernizes the canopy physics for theoretical and computational advances compared with CLM’s outdated ad-hoc parameterizations. Nonetheless, our analysis points to further modeling needs and identifies observations central to model testing. Measurements of within-canopy micrometeorology and leaf gas exchange are needed in addition to above-canopy fluxes.
超越地表通量:多层冠层模型的观测和计算需求——一个核桃园试验案例
在天气和气候模式中,陆地表面模式模拟陆地和大气之间交换的通量。流行的建模范例使用不是垂直解析的大叶冠参数化。多层冠层模型作为一种改善地表通量和促进新科学发展的手段,在过去几年中引起了人们的兴趣。我们将社区陆地模型(CLM)多层冠层模型(CLM-ml v2)与冠层水平阵列湍流研究(CHATS)期间核桃园内外多个高度的气温、比湿、风速和通量(净辐射、感热、潜热、动量)的观测结果进行了比较。该数据集为测试多层模型提供了一个基准。在强不稳定、弱不稳定、接近中性、弱稳定和强稳定的一系列大气状态下,很好地模拟了冠层上感热、潜热和动量通量,以及冠层内通量的垂直剖面。风速的垂直剖面与所有稳定状态下的观测结果非常吻合。空气温度和比湿度的垂直剖面得到了很好的模拟,但在强稳定条件下,一阶湍流闭合不能代表冠层内部的非局部垂直混合,否则会将上层冠层辐射冷却产生的冷空气向下输送到下层冠层。我们的模型与数据对比突出了多层模型模拟地表空气空间的潜力。多层冠层模型比CLM大叶冠层模型更简单,更符合理论,与CLM过时的自组织参数化相比,它在理论和计算方面实现了冠层物理的现代化。尽管如此,我们的分析指出了进一步的建模需求,并确定了模型测试的核心观察结果。除了冠层上通量外,还需要测量冠层内微气象学和叶片气体交换。
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来源期刊
CiteScore
10.30
自引率
9.70%
发文量
415
审稿时长
69 days
期刊介绍: Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published. Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.
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