Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/joc.5222 |
The VALUE perfect predictor experiment: Evaluation of temporal variability | |
Maraun, Douglas1; Huth, Radan2,3; Gutierrez, Jose M.4; San Martin, Daniel5; Dubrovsky, Martin3; Fischer, Andreas6; Hertig, Elke7; Soares, Pedro M. M.8; Bartholy, Judit9; Pongracz, Rita9; Widmann, Martin10; Casado, Maria J.11; Ramos, Petra12; Bedia, Joaquin5 | |
2019-07-01 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY |
ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2019 |
卷号 | 39期号:9页码:3786-3818 |
文章类型 | Article |
语种 | 英语 |
国家 | Austria; Czech Republic; Spain; Switzerland; Germany; Portugal; Hungary; England |
英文摘要 | Temporal variability is an important feature of climate, comprising systematic variations such as the annual cycle, as well as residual temporal variations such as short-term variations, spells and variability from interannual to long-term trends. The EU-COST Action VALUE developed a comprehensive framework to evaluate downscaling methods. Here we present the evaluation of the perfect predictor experiment for temporal variability. Overall, the behaviour of the different approaches turned out to be as expected from their structure and implementation. The chosen regional climate model adds value to reanalysis data for most considered aspects, for all seasons and for both temperature and precipitation. Bias correction methods do not directly modify temporal variability apart from the annual cycle. However, wet day corrections substantially improve transition probabilities and spell length distributions, whereas interannual variability is in some cases deteriorated by quantile mapping. The performance of perfect prognosis (PP) statistical downscaling methods varies strongly from aspect to aspect and method to method, and depends strongly on the predictor choice. Unconditional weather generators tend to perform well for the aspects they have been calibrated for, but underrepresent long spells and interannual variability. Long-term temperature trends of the driving model are essentially unchanged by bias correction methods. If precipitation trends are not well simulated by the driving model, bias correction further deteriorates these trends. The performance of PP methods to simulate trends depends strongly on the chosen predictors. |
英文关键词 | downscaling evaluation interannual variability long-term trends regional climate spells temporal variability validation |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000474001900007 |
WOS关键词 | STOCHASTIC WEATHER GENERATORS ; REGIONAL CLIMATE MODELS ; BIAS CORRECTION ; DAILY PRECIPITATION ; DOWNSCALING TECHNIQUES ; EXTREME PRECIPITATION ; STATISTICAL-METHODS ; TEMPERATURE TRENDS ; EUROPE ; SIMULATIONS |
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/184662 |
专题 | 气候变化 |
作者单位 | 1.Karl Franzens Univ Graz, Wegener Ctr Climate & Global Change, Brandhofgasse 5, A-8010 Graz, Austria; 2.Charles Univ Prague, Fac Sci, Dept Phys Geog & Geoecol, Prague, Czech Republic; 3.Czech Acad Sci, Inst Atmospher Phys, Prague, Czech Republic; 4.Univ Cantabria, Inst Phys Cantabria IFCA, Santander, Spain; 5.Predictia Intelligent Data Solut SL, Santander, Spain; 6.Fed Off Meteorol & Climatol MeteoSwiss, Zurich, Switzerland; 7.Augsburg Univ, Inst Geog, Augsburg, Germany; 8.Univ Lisbon, Fac Ciencias, Inst Dom Luiz, Lisbon, Portugal; 9.Eotvos Lorand Univ, Dept Meteorol, Budapest, Hungary; 10.Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham, W Midlands, England; 11.Agencia Estatal Meteorol AEMET, Madrid, Spain; 12.Delegac Terr AEMET Andalucia, Seville, Spain |
推荐引用方式 GB/T 7714 | Maraun, Douglas,Huth, Radan,Gutierrez, Jose M.,et al. The VALUE perfect predictor experiment: Evaluation of temporal variability[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2019,39(9):3786-3818. |
APA | Maraun, Douglas.,Huth, Radan.,Gutierrez, Jose M..,San Martin, Daniel.,Dubrovsky, Martin.,...&Bedia, Joaquin.(2019).The VALUE perfect predictor experiment: Evaluation of temporal variability.INTERNATIONAL JOURNAL OF CLIMATOLOGY,39(9),3786-3818. |
MLA | Maraun, Douglas,et al."The VALUE perfect predictor experiment: Evaluation of temporal variability".INTERNATIONAL JOURNAL OF CLIMATOLOGY 39.9(2019):3786-3818. |
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