气候变化领域集成服务门户(CCPortal): Evaluation and bias correction of probabilistic volcanic ash forecasts

CCPortal

DOI	10.5194/acp-22-13967-2022
	Evaluation and bias correction of probabilistic volcanic ash forecasts
	Crawford, Alice; Chai, Tianfeng; Wang, Binyu; Ring, Allison; Stunder, Barbara; Loughner, Christopher P.; Pavolonis, Michael; Sieglaff, Justin
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	13967
结束页码	13996
卷号	22 期号:21 页码:30
英文摘要	Satellite retrievals of column mass loading of volcanic ash are incorporated into the HYSPLIT transport and dispersion modeling system for source determination, bias correction, and forecast verification of probabilistic ash forecasts of a short eruption of Bezymianny in Kamchatka. The probabilistic forecasts are generated with a dispersion model ensemble created by driving HYSPLIT with 31 members of the NOAA global ensemble forecast system (GEFS). An inversion algorithm is used for source determination. A bias correction procedure called cumulative distribution function (CDF) matching is used to very effectively reduce bias. Evaluation is performed with rank histograms, reliability diagrams, fractions skill score, and precision recall curves. Particular attention is paid to forecasting the end of life of the ash cloud when only small areas are still detectable in satellite imagery. We find indications that the simulated dispersion of the ash cloud does not represent the observed dispersion well, resulting in difficulty simulating the observed evolution of the ash cloud area. This can be ameliorated with the bias correction procedure. Individual model runs struggle to capture the exact placement and shape of the small areas of ash left near the end of the clouds lifetime. The ensemble tends to be overconfident but does capture the range of possibilities of ash cloud placement. Probabilistic forecasts such as ensemble-relative frequency of exceedance and agreement in percentile levels are suited to strategies in which areas with certain concentrations or column mass loadings of ash need to be avoided with a chosen amount of confidence.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000877522000001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273810
作者单位	National Oceanic Atmospheric Admin (NOAA) - USA; University System of Maryland; University of Maryland College Park; National Oceanic Atmospheric Admin (NOAA) - USA; University System of Maryland; University of Maryland College Park; National Oceanic Atmospheric Admin (NOAA) - USA; University of Wisconsin System; University of Wisconsin Madison
推荐引用方式 GB/T 7714	Crawford, Alice,Chai, Tianfeng,Wang, Binyu,et al. Evaluation and bias correction of probabilistic volcanic ash forecasts[J],2022,22(21):30.
APA	Crawford, Alice.,Chai, Tianfeng.,Wang, Binyu.,Ring, Allison.,Stunder, Barbara.,...&Sieglaff, Justin.(2022).Evaluation and bias correction of probabilistic volcanic ash forecasts.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(21),30.
MLA	Crawford, Alice,et al."Evaluation and bias correction of probabilistic volcanic ash forecasts".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.21(2022):30.