Evaluation of Three Reanalysis Soil Temperature Datasets with Observation Data over China

IF 1.6 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY
Cailing Zhao, C. Gong, H. Duan, P. Yan, Yuanpu Liu, G. Zhou
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Abstract

Soil temperature is a crucial parameter in surface emissions of carbon, water, and energy exchanges. This study utilized the soil temperature of 836 national basic meteorological observing stations over China to evaluate three soil temperature products. Soil temperature data from the China Meteorology Administration Land Data Assimilation System (CLDAS), European Centre for Medium-Range Weather Forecasts (ERA-Interim), and Global Land Data Assimilation System (GLDAS) during 2017 are evaluated. The results showed that soil temperature reanalysis datasets display a significant north-to-south difference over eastern China with generally underestimated magnitudes. CLDAS data perform soil temperature assessment best at different depths and can be reproduced well in most areas of China. CLDAS slightly overestimates soil temperature in summer. The most significant deviation of ERA-Interim (GLDAS) appears in summer (summer and autumn). As soil depth increases, the soil temperature errors of all three datasets increase. The CLDAS represents the soil temperature over China but owns a more considerable bias in barren or sparsely vegetated croplands. ERA-Interim performs poorest in urban and built-up and barren or sparsely vegetated areas. GLDAS overall owns an enormous bias at the mixed forest, grassland, and croplands areas, which should be improved, especially in summer. However, it performs better in open shrublands and barren or sparsely vegetated areas. The ST of mixed forests shows better results in the south region than the north region. For grasslands, smaller MEs are located in the north and northwest regions. The ST of croplands shows the poorest performance over the northwest region.
中国3个再分析土壤温度观测资料的评价
土壤温度是地表碳排放、水和能量交换的关键参数。本研究利用全国836个国家基础气象观测站的土壤温度,对3种土壤温度产品进行了评价。对中国气象局土地资料同化系统(CLDAS)、欧洲中期天气预报中心(ERA-Interim)和全球土地资料同化系统(GLDAS) 2017年的土壤温度数据进行了评估。结果表明,中国东部地区土壤温度再分析数据呈现出显著的南北差异,但差异幅度普遍被低估。CLDAS数据在不同深度下的土壤温度评价效果最好,在中国大部分地区都能很好地再现。CLDAS略微高估了夏季的土壤温度。ERA-Interim (GLDAS)的偏差在夏季(夏秋两季)最为显著。随着土壤深度的增加,三个数据集的土壤温度误差都增加。CLDAS代表了中国的土壤温度,但在贫瘠或植被稀疏的农田中具有更大的偏差。ERA-Interim在城市和建成区以及贫瘠或植被稀少的地区表现最差。GLDAS总体上对混交林、草地和农田存在较大的偏倚,需要改进,特别是在夏季。但在开阔的灌丛和贫瘠或植被稀疏的地区表现较好。混交林的ST在南方地区优于北方地区。对于草原而言,较小的MEs位于北部和西北部地区。农田温度表现最差的地区为西北地区。
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
Earth Interactions
Earth Interactions 地学-地球科学综合
CiteScore
2.70
自引率
5.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: Publishes research on the interactions among the atmosphere, hydrosphere, biosphere, cryosphere, and lithosphere, including, but not limited to, research on human impacts, such as land cover change, irrigation, dams/reservoirs, urbanization, pollution, and landslides. Earth Interactions is a joint publication of the American Meteorological Society, American Geophysical Union, and American Association of Geographers.
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