Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1007/s00382-017-3532-1 |
Decadal temperature predictions over the continental United States: Analysis and Enhancement | |
Salvi, Kaustubh1; Villarini, Gabriele1; Vecchi, Gabriel A.2; Ghosh, Subimal3 | |
2017-11-01 | |
发表期刊 | CLIMATE DYNAMICS |
ISSN | 0930-7575 |
EISSN | 1432-0894 |
出版年 | 2017 |
卷号 | 49 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; India |
英文摘要 | Increases in global temperature over recent decades and the projected acceleration in warming trends over the 21 century have resulted in a strong need to obtain information about future temperature conditions. Hence, skillful decadal temperature predictions (DTPs) can have profound societal and economic benefits through informed planning and response. However, skillful and actionable DTPs are extremely challenging to achieve. Even though general circulation models (GCMs) provide decadal predictions of different climate variables, the direct use of GCM data for regional-scale impacts assessment is not encouraged because of the limited skill they possibly exhibit and their coarse spatial resolution. Here, we focus on 14 GCMs and evaluate seasonally and regionally averaged skills in DTPs over the continental United States. Moreover, we address the limitations in skill and spatial resolution in the GCM outputs using two data-driven approaches: (1) quantile-based bias correction and (2) linear regression-based statistical downscaling. For both the approaches, statistical parameters/relationships, established over the calibration period (1961-1990) are applied to retrospective and near future decadal predictions by GCMs to obtain DTPs at '4 km' resolution. Predictions are assessed using different evaluation metrics, long-term statistical properties, and uncertainty in terms of the range of predictions. Both the approaches adopted here show improvements with respect to the raw GCM data, particularly in terms of the long-term statistical properties and uncertainty, irrespective of lead time. The outcome of the study is monthly DTPs from 14 GCMs with a spatial resolution of 4 km, which can be used as a key input for impacts assessments. |
英文关键词 | Decadal temperature predictions Continental United States Bias correction Statistical downscaling |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000414153800037 |
WOS关键词 | PRINCIPAL COMPONENTS ; CLIMATE MODEL ; REANALYSIS ; NUMBER ; RECONSTRUCTION ; PRECIPITATION ; FORECASTS ; SKILLFUL ; ENSEMBLE |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/35219 |
专题 | 气候变化 |
作者单位 | 1.Univ Iowa, C Maxwell Stanley Hydraul Lab 100, IIHR Hydrosci & Engn, Iowa City, IA 52242 USA; 2.NOAA, Geophys Fluid Dynam Lab, Princeton, NJ USA; 3.Indian Inst Technol, Dept Civil Engn, Bombay, Maharashtra, India |
推荐引用方式 GB/T 7714 | Salvi, Kaustubh,Villarini, Gabriele,Vecchi, Gabriel A.,et al. Decadal temperature predictions over the continental United States: Analysis and Enhancement[J]. CLIMATE DYNAMICS,2017,49. |
APA | Salvi, Kaustubh,Villarini, Gabriele,Vecchi, Gabriel A.,&Ghosh, Subimal.(2017).Decadal temperature predictions over the continental United States: Analysis and Enhancement.CLIMATE DYNAMICS,49. |
MLA | Salvi, Kaustubh,et al."Decadal temperature predictions over the continental United States: Analysis and Enhancement".CLIMATE DYNAMICS 49(2017). |
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