气候变化领域集成服务门户(CCPortal): Statistical adjustment; calibration and downscaling of seasonal forecasts: a case-study for Southeast Asia

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DOI	10.1007/s00382-020-05145-1
	Statistical adjustment; calibration and downscaling of seasonal forecasts: a case-study for Southeast Asia
	Manzanas R.; Gutiérrez J.M.; Bhend J.; Hemri S.; Doblas-Reyes F.J.; Penabad E.; Brookshaw A.
发表日期	2020
ISSN	0930-7575
起始页码	2869
结束页码	2882
卷号	54
英文摘要	The present paper is a follow-on of the work presented in Manzanas et al. (Clim Dyn 53(3–4):1287–1305, 2019) which provides a comprehensive intercomparison of alternatives for the post-processing (statistical adjustment, calibration and downscaling) of seasonal forecasts for a particularly interesting region, Southeast Asia. To answer the questions that were raised in the preceding work, apart from Bias Adjustment (BA) and ensemble Re-Calibration (RC) methods—which transform directly the variable of interest,—we include here more complex Perfect Prognosis (PP) and Model Outputs Statistics (MOS) downscaling techniques—which operate on a selection of large-scale model circulation variables linked to the local observed variable of interest. Moreover, we test the suitability of BA and PP methods for the post-processing of daily—not only seasonal—time-series, which are often needed in a variety of sectoral applications (crop, hydrology, etc.) or to compute specific climate indices (heat waves, fire weather index, etc.). In addition, we also undertake an assessment of the effect that observational uncertainty may have for statistical post-processing. Our results indicate that PP methods (and to a lesser extent MOS) are highly case-dependent and their application must be carefully analyzed for the region/season/application of interest, since they can either improve or degrade the raw model outputs. Therefore, for those cases for which the use of these methods cannot be carefully tested by experts, our overall recommendation would be the use of BA methods, which seem to be a safe, easy to implement alternative that provide competitive results in most situations. Nevertheless, all methods (including BA ones) seem to be sensitive to observational uncertainty, especially regarding the reproduction of extremes and spells. For MOS and PP methods, this issue can even lead to important regional differences in interannual skill. The lessons learnt from this work can substantially benefit a wide range of end-users in different socio-economic sectors, and can also have important implications for the development of high-quality climate services. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
语种	英语
scopus关键词	atmospheric circulation; calibration; climate prediction; downscaling; ensemble forecasting; seasonal variation; time series analysis; Southeast Asia
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/145547
作者单位	Meteorology Group, Dpto. de Matemática Aplicada y Ciencias de la Computación, Universidad de Cantabria, Santander, Spain; Meteorology Group, Institute of Physics of Cantabria (IFCA), CSIC-University of Cantabria, Santander, Spain; Federal Office of Meteorology and Climatology, MeteoSwiss, Zurich, Switzerland; Barcelona Supercomputing Center (BSC), Barcelona, Spain; ICREA, Pg. Lluís Companys 23 08010, Barcelona, Spain; European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom
推荐引用方式 GB/T 7714	Manzanas R.,Gutiérrez J.M.,Bhend J.,et al. Statistical adjustment; calibration and downscaling of seasonal forecasts: a case-study for Southeast Asia[J],2020,54.
APA	Manzanas R..,Gutiérrez J.M..,Bhend J..,Hemri S..,Doblas-Reyes F.J..,...&Brookshaw A..(2020).Statistical adjustment; calibration and downscaling of seasonal forecasts: a case-study for Southeast Asia.Climate Dynamics,54.
MLA	Manzanas R.,et al."Statistical adjustment; calibration and downscaling of seasonal forecasts: a case-study for Southeast Asia".Climate Dynamics 54(2020).