利用新开发的参数化区域气候模型 REMO2020-iMOVE 模拟和评估灌溉对欧洲西南部土地-大气相互作用的影响

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Geoscientific Model Development Pub Date : 2023-12-19 DOI:10.5194/gmd-16-7311-2023
Christina Asmus, P. Hoffmann, J. Pietikäinen, J. Böhner, D. Rechid
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引用次数: 1

摘要

摘要灌溉是使农业适应不适宜的气候和土壤条件的重要土地利用方式。为了改善植物的生长,灌溉改变了土壤条件,从而通过土地-大气相互作用对大气产生影响和反馈。这些影响可以通过数值气候模型进行量化,正如各种研究中所做的那样。研究表明,灌溉效应,如降低气温和增加湿度,已得到充分理解,在地方和区域范围内不应被忽视。然而,目前还缺乏对植被在改变的陆地-大气相互作用中的作用的研究。随着数值气候模式分辨率的提高,这些详细过程有机会得到更好的解析和研究。本研究旨在分析灌溉对陆地-大气相互作用的影响,包括植被的影响和反馈。我们开发了一种新的灌溉参数化方法,将其应用于区域气候模拟(REMO2020),并将其与基于MOsaic的交互式植被模块(iMOVE)相结合。采用这种单独灌溉部分的新方法,该参数化适合作为高分辨率研究的子网格参数化,并解决灌溉对土地、大气和植被的影响。此外,该参数化设计了三种不同的施水方案,以分析不同的参数化方法及其对灌溉效应表示的影响。我们以 0.11∘的水平分辨率对欧洲西南部(包括地中海地区)的极端炎热天气进行了灌溉参数化。根据物理过程的一致性对模拟结果进行了评估。我们发现了灌溉的直接影响,如改变地表能量平衡,增加潜热通量,减少显热通量,以及在生长季节平均降低地表温度-4 K 以上。此外,植被对灌溉的反应不仅有直接影响,如减少水分胁迫,还有反馈作用,如近地表温度降低导致生长季节推迟。此外,研究结果还与观测数据进行了比较,结果表明,在使用灌溉参数化时,2 米平均温度的偏差明显减小。
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Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
Abstract. Irrigation is a crucial land use practice to adapt agriculture to unsuitable climate and soil conditions. Aiming to improve the growth of plants, irrigation modifies the soil condition, which causes atmospheric effects and feedbacks through land–atmosphere interaction. These effects can be quantified with numerical climate models, as has been done in various studies. It could be shown that irrigation effects, such as air temperature reduction and humidity increase, are well understood and should not be neglected on local and regional scales. However, there is a lack of studies including the role of vegetation in the altered land–atmosphere interaction. With the increasing resolution of numerical climate models, these detailed processes have a chance to be better resolved and studied. This study aims to analyze the effects of irrigation on land–atmosphere interaction, including the effects and feedbacks of vegetation. We developed a new parameterization for irrigation, implemented it into the REgional climate MOdel (REMO2020), and coupled it with the interactive MOsaic-based VEgetation module (iMOVE). Following this new approach of a separate irrigated fraction, the parameterization is suitable as a subgrid parameterization for high-resolution studies and resolves irrigation effects on land, atmosphere, and vegetation. Further, the parameterization is designed with three different water application schemes in order to analyze different parameterization approaches and their influence on the representation of irrigation effects. We apply the irrigation parameterization for southwestern Europe including the Mediterranean region at a 0.11∘ horizontal resolution for hot extremes. The simulation results are evaluated in terms of the consistency of physical processes. We found direct effects of irrigation, like a changed surface energy balance with increased latent and decreased sensible heat fluxes, and a surface temperature reduction of more than −4 K as a mean during the growing season. Further, vegetation reacts to irrigation with direct effects, such as reduced water stress, but also with feedbacks, such as a delayed growing season caused by the reduction of the near-surface temperature. Furthermore, the results were compared to observational data, showing a significant bias reduction in the 2 m mean temperature when using the irrigation parameterization.
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来源期刊
Geoscientific Model Development
Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
8.60
自引率
9.80%
发文量
352
审稿时长
6-12 weeks
期刊介绍: Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.
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