建立瑞士空间积雪气候学:现有数据集的比较与验证

IF 1.2 4区 地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES
Simon C. Scherrer, Monika Göldi, Stefanie Gubler, Christian R. Steger, Sven Kotlarski
{"title":"建立瑞士空间积雪气候学:现有数据集的比较与验证","authors":"Simon C. Scherrer, Monika Göldi, Stefanie Gubler, Christian R. Steger, Sven Kotlarski","doi":"10.1127/metz/2023/1210","DOIUrl":null,"url":null,"abstract":"In the European Alps, surface snow cover is of high relevance and a major factor for environmental, ecological and economical systems. The provision of accurate and timely climatological information on the spatio-temporal distribution of Alpine snow cover is hence an important yet challenging task of modern climate services. To assess the quality and the reliability of existing snow cover products in this region, we here compare daily snow cover datasets over Switzerland from the low-resolution ERA5 reanalysis, two intermediate resolution reanalyses (ERA5-Land and COSMO-REA6) and a high-resolution AVHRR-derived remote sensing product with three high-resolution 1 km offline snow models for the past 30 to 60 years. We focus on the parameters snow water equivalent (SWE) and daily snow coverage (snow/no snow). In the challenging Alpine terrain, all datasets are able to broadly represent the mean and the seasonal cycle of SWE and the number of snow days. They also agree on the direction of the trends. Decreasing mean SWE and snow day trends are found for the whole of Switzerland and all subregions in the period 1982–2019. Regarding interannual variability and trends, ERA5, ERA5-Land and COSMO-REA6 seem to perform reasonably well in most regions although the absolute and relative biases can be considerable. Especially ERA5-Land strongly overestimates SWE at high elevations. The biases are often larger in the southern Alps than in and north of the Alps. Most datasets, including the high-resolution ones, have problems correctly representing small SWE values at low elevations. The results indicate that in order to estimate absolute SWE or snow days with a reasonable accuracy, or to conduct a detailed study of the elevation dependence of snow, a km‑scale model that assimilates snow measurements is highly preferable. MeteoSwiss and the WSL Institute for Snow and Avalanche Research SLF are currently setting up a 1 km daily operational climatological product covering the period from 1961 to today.","PeriodicalId":49824,"journal":{"name":"Meteorologische Zeitschrift","volume":"43 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards a spatial snow climatology for Switzerland: Comparison and validation of existing datasets\",\"authors\":\"Simon C. Scherrer, Monika Göldi, Stefanie Gubler, Christian R. Steger, Sven Kotlarski\",\"doi\":\"10.1127/metz/2023/1210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the European Alps, surface snow cover is of high relevance and a major factor for environmental, ecological and economical systems. The provision of accurate and timely climatological information on the spatio-temporal distribution of Alpine snow cover is hence an important yet challenging task of modern climate services. To assess the quality and the reliability of existing snow cover products in this region, we here compare daily snow cover datasets over Switzerland from the low-resolution ERA5 reanalysis, two intermediate resolution reanalyses (ERA5-Land and COSMO-REA6) and a high-resolution AVHRR-derived remote sensing product with three high-resolution 1 km offline snow models for the past 30 to 60 years. We focus on the parameters snow water equivalent (SWE) and daily snow coverage (snow/no snow). In the challenging Alpine terrain, all datasets are able to broadly represent the mean and the seasonal cycle of SWE and the number of snow days. They also agree on the direction of the trends. Decreasing mean SWE and snow day trends are found for the whole of Switzerland and all subregions in the period 1982–2019. Regarding interannual variability and trends, ERA5, ERA5-Land and COSMO-REA6 seem to perform reasonably well in most regions although the absolute and relative biases can be considerable. Especially ERA5-Land strongly overestimates SWE at high elevations. The biases are often larger in the southern Alps than in and north of the Alps. Most datasets, including the high-resolution ones, have problems correctly representing small SWE values at low elevations. The results indicate that in order to estimate absolute SWE or snow days with a reasonable accuracy, or to conduct a detailed study of the elevation dependence of snow, a km‑scale model that assimilates snow measurements is highly preferable. MeteoSwiss and the WSL Institute for Snow and Avalanche Research SLF are currently setting up a 1 km daily operational climatological product covering the period from 1961 to today.\",\"PeriodicalId\":49824,\"journal\":{\"name\":\"Meteorologische Zeitschrift\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Meteorologische Zeitschrift\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1127/metz/2023/1210\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meteorologische Zeitschrift","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1127/metz/2023/1210","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

在欧洲阿尔卑斯山,地表积雪与环境、生态和经济系统密切相关,是一个重要因素。因此,提供有关阿尔卑斯山积雪时空分布的准确及时的气候学信息是现代气候服务的一项重要而又具有挑战性的任务。为了评估该地区现有积雪覆盖产品的质量和可靠性,我们在此比较了过去 30-60 年间低分辨率 ERA5 再分析、两个中分辨率再分析(ERA5-Land 和 COSMO-REA6)和高分辨率 AVHRR 衍生遥感产品与三个高分辨率 1 公里离线积雪模型在瑞士上空的日积雪覆盖数据集。我们重点研究了雪水当量(SWE)和日积雪覆盖率(积雪/无雪)参数。在极具挑战性的阿尔卑斯山地形中,所有数据集都能大致反映出雪水当量的平均值和季节周期以及积雪天数。它们在趋势方向上也是一致的。在 1982-2019 年期间,整个瑞士和所有分区的平均 SWE 和积雪日数都呈下降趋势。在年际变化和趋势方面,ERA5、ERA5-Land 和 COSMO-REA6 在大多数地区的表现都相当不错,但绝对和相对偏差可能相当大。特别是ERA5-陆地模式严重高估了高海拔地区的SWE。阿尔卑斯山南部的偏差往往大于阿尔卑斯山及其以北地区。大多数数据集,包括高分辨率数据集,在正确表示低海拔地区较小的 SWE 值方面都存在问题。研究结果表明,为了以合理的精度估算绝对西南降水量或积雪日数,或对积雪的海拔依赖性进行详细研究,最好使用同化了积雪测量数据的千米尺度模型。目前,MeteoSwiss 和 WSL 雪与雪崩研究所 SLF 正在建立一个覆盖 1961 年至今的 1 公里日运行气候学产品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a spatial snow climatology for Switzerland: Comparison and validation of existing datasets
In the European Alps, surface snow cover is of high relevance and a major factor for environmental, ecological and economical systems. The provision of accurate and timely climatological information on the spatio-temporal distribution of Alpine snow cover is hence an important yet challenging task of modern climate services. To assess the quality and the reliability of existing snow cover products in this region, we here compare daily snow cover datasets over Switzerland from the low-resolution ERA5 reanalysis, two intermediate resolution reanalyses (ERA5-Land and COSMO-REA6) and a high-resolution AVHRR-derived remote sensing product with three high-resolution 1 km offline snow models for the past 30 to 60 years. We focus on the parameters snow water equivalent (SWE) and daily snow coverage (snow/no snow). In the challenging Alpine terrain, all datasets are able to broadly represent the mean and the seasonal cycle of SWE and the number of snow days. They also agree on the direction of the trends. Decreasing mean SWE and snow day trends are found for the whole of Switzerland and all subregions in the period 1982–2019. Regarding interannual variability and trends, ERA5, ERA5-Land and COSMO-REA6 seem to perform reasonably well in most regions although the absolute and relative biases can be considerable. Especially ERA5-Land strongly overestimates SWE at high elevations. The biases are often larger in the southern Alps than in and north of the Alps. Most datasets, including the high-resolution ones, have problems correctly representing small SWE values at low elevations. The results indicate that in order to estimate absolute SWE or snow days with a reasonable accuracy, or to conduct a detailed study of the elevation dependence of snow, a km‑scale model that assimilates snow measurements is highly preferable. MeteoSwiss and the WSL Institute for Snow and Avalanche Research SLF are currently setting up a 1 km daily operational climatological product covering the period from 1961 to today.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Meteorologische Zeitschrift
Meteorologische Zeitschrift 地学-气象与大气科学
CiteScore
2.80
自引率
8.30%
发文量
19
审稿时长
6-12 weeks
期刊介绍: Meteorologische Zeitschrift (Contributions to Atmospheric Sciences) accepts high-quality, English language, double peer-reviewed manuscripts on all aspects of observational, theoretical and computational research on the entire field of meteorology and atmospheric physics, including climatology. Manuscripts from applied sectors such as, e.g., Environmental Meteorology or Energy Meteorology are particularly welcome. Meteorologische Zeitschrift (Contributions to Atmospheric Sciences) represents a natural forum for the meteorological community of Central Europe and worldwide.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信