Evaluation of simulations of near-surface variables using the regional climate model CCLM for the MOSAiC winter period

IF 4.7 3区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Elementa-Science of the Anthropocene Pub Date : 2022-01-01 DOI:10.1525/elementa.2022.00033

G. Heinemann, Lukas Schefczyk, S. Willmes, M. Shupe

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引用次数: 3

Abstract

The ship-based experiment MOSAiC 2019/2020 was carried out during a full year in the Arctic and yielded an excellent data set to test the parameterizations of ocean/sea-ice/atmosphere interaction processes in regional climate models (RCMs). In the present paper, near-surface data during MOSAiC are used for the verification of the RCM COnsortium for Small-scale MOdel–Climate Limited area Mode (COSMO-CLM or CCLM). CCLM is used in a forecast mode (nested in ERA5) for the whole Arctic with 15 km resolution and is run with different configurations of sea ice data. These include the standard sea ice concentration taken from passive microwave data with around 6 km resolution, sea ice concentration from Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data and MODIS sea ice lead fraction data for the winter period. CCLM simulations show a good agreement with the measurements. Relatively large negative biases for temperature occur for November and December, which are likely associated with a too large ice thickness used by CCLM. The consideration of sea ice leads in the sub-grid parameterization in CCLM yields improved results for the near-surface temperature. ERA5 data show a large warm bias of about 2.5°C and an underestimation of the temperature variability.

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区域气候模式CCLM对MOSAiC冬季近地表变量模拟的评价

基于船舶的MOSAiC 2019/2020实验在北极进行了整整一年的时间，获得了一组优秀的数据集，用于测试区域气候模式(RCMs)中海洋/海冰/大气相互作用过程的参数化。本文利用MOSAiC期间的近地表数据对RCM联盟的小尺度模式-气候有限区域模式(cosmos - clm或CCLM)进行了验证。CCLM在整个北极地区以15公里分辨率的预报模式(嵌套在ERA5中)使用，并使用不同配置的海冰数据运行。这些数据包括从6公里分辨率的被动微波数据中获取的标准海冰浓度，从中分辨率成像光谱仪(MODIS)热红外数据中获取的海冰浓度，以及MODIS冬季海冰铅分数数据。CCLM仿真结果与实测结果吻合较好。11月和12月的温度出现了相对较大的负偏差，这可能与CCLM使用的冰厚过大有关。在CCLM的亚网格参数化中，考虑海冰的影响，可以提高近地表温度的参数化结果。ERA5数据显示约2.5°C的较大暖偏和对温度变率的低估。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Elementa-Science of the Anthropocene Earth and Planetary Sciences-Atmospheric Science

CiteScore

6.90

自引率

5.10%

发文量

审稿时长

16 weeks

期刊介绍： A new open-access scientific journal, Elementa: Science of the Anthropocene publishes original research reporting on new knowledge of the Earth’s physical, chemical, and biological systems; interactions between human and natural systems; and steps that can be taken to mitigate and adapt to global change. Elementa reports on fundamental advancements in research organized initially into six knowledge domains, embracing the concept that basic knowledge can foster sustainable solutions for society. Elementa is published on an open-access, public-good basis—available freely and immediately to the world.