Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

Wang, Bin; Lee, June‐Yi; Kang, Iksung; Shukla, J.; Park, C. K.; Kumar, Arun; Schemm, Jae-Kyung E.; Cocke, S.; Kug, Jong‐Seong; Luo, Jing–Jia; Zhou, Tianjun; Wang, B.; Fu, Xiouhua; Yun, Won-Tae; Alves, Oscar; Jin, Emilia Kyung; Kinter, James L.; Kirtman, Ben P.; Krishnamurti, T. N.; Lau, Ngar‐Cheung; Lau, William K. M.; Liu, P.; Pegion, Philip; Rosati, T.; Schubert, Siegfried D.; Stern, William F.; Suárez, Max J.; Yamagata, Toshio

doi:10.1007/s00382-008-0460-0

Cited by 381 publications

(309 citation statements)

References 69 publications

Supporting

Mentioning

288

Contrasting

Unclassified

Order By: Relevance

“…However, predicting the summer mean precipitation over the Asian summer monsoon region, even with a 1 month lead, remains challenging for climate models [Wang et al, 2007[Wang et al, , 2008a[Wang et al, , 2008b[Wang et al, , 2009Kug et al, 2008;Lee et al, 2010Lee et al, , 2011. This study evaluates the potential of using one-tier multimodel ensemble (MME) products for long-lead drought predictions.…”

Section: Introductionmentioning

confidence: 99%

Six month–lead downscaling prediction of winter to spring drought in South Korea based on a multimodel ensemble

Sohn

Ahn

Tam

2013

Geophysical Research Letters

View full text Add to dashboard Cite

[1] The potential of using a dynamical-statistical method for long-lead drought prediction was investigated. In particular, the APEC Climate Center one-tier multimodel ensemble (MME) was downscaled for predicting the standardized precipitation evapotranspiration index (SPEI) over 60 stations in South Korea. SPEI depends on both precipitation and temperature, and can incorporate the effect of global warming on the balance between precipitation and evapotranspiration. It was found that the one-tier MME has difficulty in capturing the local temperature and rainfall variations over extratropical land areas, and has no skill in predicting SPEI during boreal winter and spring. On the other hand, temperature and precipitation predictions were substantially improved in the downscaled MME. In conjunction with variance inflation, downscaled MME can give reasonably skillful 6 month-lead forecasts of SPEI for the winter to spring period. Our results could lead to more reliable hydrological extreme predictions for policymakers and stakeholders in the water management sector, and for better mitigation and climate adaptations. Citation: Sohn, S.-J., J.-B.Ahn, and C.-Y. Tam (2013), Six month-lead downscaling prediction of winter to spring drought in South Korea based on a multimodel ensemble, Geophys. Res. Lett., 40,[579][580][581][582][583]

show abstract

Section: Introductionmentioning

confidence: 99%

Six month–lead downscaling prediction of winter to spring drought in South Korea based on a multimodel ensemble

Sohn

Ahn

Tam

2013

Geophysical Research Letters

View full text Add to dashboard Cite

show abstract

“…The boreal summer CGT pattern has been the topic of subsequent investigations focusing on meteorological aspects [Ding and Wang, 2007] and climatic aspects [Lin, 2009;Yasui and Watanabe, 2010]. Although the boreal summer teleconnection is weaker than its winter counterpart, it is intimately coupled to surface air temperature and precipitation variability in the NH extratropics [Ding et al, 2011] and may act as a significant source of climate predictability over the extratropical region of interest [Wang et al, 2008b;Lee et al, 2010Lee et al, , 2011.…”

Section: Introductionmentioning

confidence: 99%

Interdecadal change of the boreal summer circumglobal teleconnection (1958–2010)

Wang

Huang

et al. 2012

Geophysical Research Letters

Self Cite

View full text Add to dashboard Cite

[1] The tropical-extratropical teleconnection during boreal summer is characterized by a circumglobal teleconnection (CGT) pattern in the northern hemisphere (NH). Around the late 1970s, there was an abrupt change in the coupled atmosphere-ocean system over the NH and global tropics. This study found that the CGT has experienced a significant change since late 1970s. During the recent epoch , the major CGT centers weakened with pronounced changes over the North Atlantic and Europe. Partial correlation analysis of 200-hPa geopotential height and the NH summer monsoon heat sources indicates that the change of Indian summer monsoon (ISM) rainfall has a global impact on the CGT, whereas other NH summer monsoons (West African, western North Pacific, and North American) have only a regional modification to the CGT. The weakening of the CGT pattern in the recent epoch is a consequence of weakened coupling between ISM rainfall and midlatitude circulation, which results from the reduced interannual variability of ISM rainfall due to changes in El Niño-Southern Oscillation properties. The large change of the CGT over the North Atlantic and Europe is attributed to a southward shift of upper-level westerlies and enhanced coupling to West African monsoon rainfall.

show abstract

“…Furthermore, considering that the sample used is relatively small, the whole assessment is based on a thorough treatment of statistical inference to determine which features are statistically significant and might be interpreted as being robust. This approach to forecast quality assessment is necessary because long-range forecasts typically have low skill and because seasonal forecast systems show small differences in skill (Wang et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Addressing model uncertainty in seasonal and annual dynamical ensemble forecasts

Doblas‐Reyes

Weisheimer

Déqué

et al. 2009

Quart J Royal Meteoro Soc

123

View full text Add to dashboard Cite

ABSTRACT:The relative merits of three forecast systems addressing the impact of model uncertainty on seasonal/annual forecasts are described. One system consists of a multi-model, whereas two other systems sample uncertainties by perturbing the parametrization of reference models through perturbed parameter and stochastic physics techniques. Ensemble reforecasts over 1991 to 2001 were performed with coupled climate models started from realistic initial conditions. Forecast quality varies due to the different strategies for sampling uncertainties, but also to differences in initialisation methods and in the reference forecast system. Both the stochastic-physics and perturbed-parameter ensembles improve the reliability with respect to their reference forecast systems, but not the discrimination ability. Although the multi-model experiment has an ensemble size larger than the other two experiments, most of the assessment was done using equally-sized ensembles. The three ensembles show similar levels of skill: significant differences in performance typically range between 5 and 20%. However, a nine-member multi-model shows better results for seasonal predictions with lead times shorter than five months, followed by the stochastic-physics and perturbed-parameter ensembles. Conversely, for seasonal predictions with lead times longer than four months, the perturbed-parameter ensemble gives more often better results. All systems suggest that spread cannot be considered a useful predictor of skill. Annual-mean predictions showed lower forecast quality than seasonal predictions. Only small differences between the systems were found. The full multi-model ensemble has improved quality with respect to all other systems, mainly from the larger ensemble size for lead times longer than four months and annual predictions.

show abstract

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

Cited by 381 publications

References 69 publications

Six month–lead downscaling prediction of winter to spring drought in South Korea based on a multimodel ensemble

Six month–lead downscaling prediction of winter to spring drought in South Korea based on a multimodel ensemble

Interdecadal change of the boreal summer circumglobal teleconnection (1958–2010)

Addressing model uncertainty in seasonal and annual dynamical ensemble forecasts

Contact Info

Product

Resources

About