Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/joc.4706 |
Impacts of uncertainties in European gridded precipitation observations on regional climate analysis | |
Prein, Andreas F.1,2,3; Gobiet, Andreas3,4 | |
2017 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY |
ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2017 |
卷号 | 37期号:1 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Austria |
英文摘要 | Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution station-based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post-processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small-scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate-mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments. |
英文关键词 | observation uncertainties precipitation undercatch correction climate models high resolution EURO-CORDEX extremes |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000392415700023 |
WOS关键词 | MASS FLUX FRAMEWORK ; PART I ; SPATIAL INTERPOLATION ; DAILY RAINFALL ; MODEL ; PARAMETERIZATION ; RESOLUTION ; MESOSCALE ; SCALE ; PERFORMANCE |
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/36931 |
专题 | 气候变化 |
作者单位 | 1.NCAR, MMM Mesoscale & Microscale Meteorol Lab, 3090 Ctr Green Dr, Boulder, CO 80301 USA; 2.NCAR, Res Applicat Lab, 3090 Ctr Green Dr, Boulder, CO 80301 USA; 3.Graz Univ, Wegener Ctr Climate & Global Change, Graz, Austria; 4.Cent Inst Meteorol & Geodynam ZAMG, Avalanche Warning Serv, Graz, Austria |
推荐引用方式 GB/T 7714 | Prein, Andreas F.,Gobiet, Andreas. Impacts of uncertainties in European gridded precipitation observations on regional climate analysis[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2017,37(1). |
APA | Prein, Andreas F.,&Gobiet, Andreas.(2017).Impacts of uncertainties in European gridded precipitation observations on regional climate analysis.INTERNATIONAL JOURNAL OF CLIMATOLOGY,37(1). |
MLA | Prein, Andreas F.,et al."Impacts of uncertainties in European gridded precipitation observations on regional climate analysis".INTERNATIONAL JOURNAL OF CLIMATOLOGY 37.1(2017). |
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