globalchange  > 全球变化的国际研究计划
DOI: 10.5194/gmd-12-3481-2019
WOS记录号: WOS:000479096500002
论文题名:
The road weather model RoadSurf (v6.60b) driven by the regional climate model HCLIM38: evaluation over Finland
作者: Toivonen, Erika1; Hippi, Marjo1; Korhonen, Hannele1; Laaksonen, Ari1,2; Kangas, Markku1; Pietikainen, Joni-Pekka1,3
通讯作者: Toivonen, Erika ; Pietikainen, Joni-Pekka
刊名: GEOSCIENTIFIC MODEL DEVELOPMENT
ISSN: 1991-959X
EISSN: 1991-9603
出版年: 2019
卷: 12, 期:8, 页码:3481-3501
语种: 英语
WOS关键词: CHANGE PROJECTIONS ; EURO-CORDEX ; TRANSPORT ; PARAMETERIZATION ; PRECIPITATION ; IMPACT ; VARIABLES
WOS学科分类: Geosciences, Multidisciplinary
WOS研究方向: Geology
英文摘要:

In this paper, we evaluate the skill of the road weather model RoadSurf to reproduce present-day road weather conditions in Finland. RoadSurf was driven by meteorological input data from cycle 38 of the high-resolution regional climate model (RCM) HARMONIE-Climate (HCLIM38) with ALARO physics (HCLIM38-ALARO) and ERA-Interim forcing in the lateral boundaries. Simulated road surface temperatures and road surface conditions were compared to observations between 2002 and 2014 at 25 road weather stations located in different parts of Finland. The main characteristics of road weather conditions were accurately captured by RoadSurf in the study area. For example, the model simulated road surface temperatures with a mean monthly bias of -0.3 degrees C and mean absolute error of 0.9 degrees C. The RoadSurf's output bias most probably stemmed from the absence of road maintenance operations in the model, such as snow plowing and salting, and the biases in the input meteorological data. The biases in the input data were most evident in northern parts of Finland, where the regional climate model HCLIM38-ALARO overestimated precipitation and had a warm bias in near-surface air temperatures during the winter season. Moreover, the variability in the biases of air temperature was found to explain on average 57% of the variability in the biases of road surface temperature. On the other hand, the absence of road maintenance operations in the model might have affected RoadSurf's ability to simulate road surface conditions: the model tended to overestimate icy and snowy road surfaces and underestimate the occurrence of water on the road. However, the overall good performance of RoadSurf implies that this approach can be used to study the impacts of climate change on road weather conditions in Finland by forcing RoadSurf with future climate projections from RCMs, such as HCLIM.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/145248
Appears in Collections:全球变化的国际研究计划

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作者单位: 1.Finnish Meteorol Inst, Helsinki, Finland
2.Univ Eastern Finland, Dept Appl Phys, Kuopio, Finland
3.Climate Serv Ctr Germany GERICS, Hamburg, Germany

Recommended Citation:
Toivonen, Erika,Hippi, Marjo,Korhonen, Hannele,et al. The road weather model RoadSurf (v6.60b) driven by the regional climate model HCLIM38: evaluation over Finland[J]. GEOSCIENTIFIC MODEL DEVELOPMENT,2019-01-01,12(8):3481-3501
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