Abstract
In this paper, by using forecasts of the highest and lowest daily surface air temperatures from the Coupled Forecast System version 2 (CFSv2) over a period of 9 months, NCEP/DOE reanalysis data from the National Centers for Environmental Prediction (NCEP), and data from the U.S. NOAA Climate Prediction Center (CPC), three cold waves are identified during 2015–2016 in China, and the CFSv2 forecasts of these cold waves are evaluated. The results show that the high-resolution CPC data and the low-resolution NCEP/DOE data both very clearly show the temperature drops and temperature anomalies of these cold waves. The earlier the forecast lead time is, the greater the errors in the beginning and ending dates of the cold waves between the CFSv2 forecasts and the observations; there are errors of 1–2 days in the durations of the cold waves between the CFSv2 forecasts and the observations. CFSv2 exhibits certain abilities to forecast the overall temperature drops and temperature anomalies of cold waves at forecast lead times of 0, 5, 10, and 15 days, but the CFSv2 prediction ability is poor at forecast lead times exceeding 20 days. CFSv2 can predict the spatial distribution of temperature drops better than it can predict that of temperature anomalies, but the absolute errors in the observed temperature drops are greater than those in the observed temperature anomalies. The temperature drops from the CFSv2 forecasts are obviously underestimated in North China, South China, and their nearby areas but overestimated in Mongolia and Northeast China. The temperature anomalies from the CFSv2 forecasts are obviously underestimated in the inland areas of China but overestimated in the surrounding oceans and adjacent coastal areas. The difference fields at forecast lead times of 0 and 30 days are basically the same, but the absolute values of the differences increase with increases in the forecast lead time (with a few exceptions).
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References
Becker E, Dool H (2016) Probabilistic seasonal forecasts in the North American multimodel ensemble: a baseline skill assessment. J Clim 29:3015–3026. https://doi.org/10.1175/JCLI-D-14-00862.1
Cellitti MP, Walsh DE, Rauber RM, Portis DH (2006) Extreme cold air outbreaks over the United States, the polar vortex, and the large-scale circulation. J Geophys Res 111:D02114. https://doi.org/10.1029/2005JD006273
He Q, Zuo ZY, Zhang RH et al (2016) Prediction skill and predictability of Eurasian snow cover fraction in the NCEP Climate Forecast System version 2 reforecasts. Int J Climatol 36:4071–4084. https://doi.org/10.1002/joc.4618
Jiang ZH, Ma TT, Wu ZW (2012) China cold wave duration in a warming winter: change of the leading mode. Theor Appl Climatol 110(1/2):65–75. https://doi.org/10.1007/s00704-012-0613-2
Kalnay E, Kanamitsu M, Kistler R et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–470
Kang ZM, Jin RH, Bao YY (2010) Characteristic analysis of cold wave in China during the period of 1951-2006. Plateau Meteor (in Chinese) 29(2):420–428
Kim HM, Webster PJ, Curry JA (2012) Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter. Clim Dyn 39:2957–2973. https://doi.org/10.1007/s00382-012-1364-6
Li QP, Ding YH, Dong WJ et al (2007) A numerical study on the winter monsoon and cold surge over East Asia[J]. Adv Atmos Sci 24(4):664–678. https://doi.org/10.1007/s00376-007-0664-y
Lin AL, Wu SS (1998) The characteristics of cold wave action in Guangdong province during recently 44 years. J Trop Meteorol 14(4):337–343
Luo YL (2012) Changes in weather and climate extremes. Adv Climate Change Res (in Chinese) 8(2):90–98
Ma TT, Wu ZW, Jiang ZH (2012) How does cold wave frequency in China respond to a warming climate. Clim Dyn 39:2487–2496. https://doi.org/10.1007/s00382-012-1354-8
Ma S, Zhu C (2019) Extreme cold wave over East Asia in January 2016: a possible response to the larger internal atmospheric variability induced by Arctic warming. J Clim 32(4):1203–1216. https://doi.org/10.1175/JCLI-D-18-0234.1
Ma XQ, Ding YH, Xu HM, He JH (2008) The relation between strong cold waves and low-frequency waves during the winter of 2004/2005. Chin J Atmos Sci 32(2):380–394
Peterson TC, Hoerling MP, Stott PA, Herring HE (2013) Explaining extreme events of 2012 from a climate perspective. Bull Am Meteorol Soc 94(9):S1–S74
Qian WH, Zhang WW (2007) Changes in cold wave events and warm winter in China during the last 46 years. Chin J Atmos Sci 31(6):1266–1278
Qu W, Wang J, Zhang X, Yang Z, Gao S (2015) Effect of cold wave on winter visibility over eastern China. J Geophys Res Atmos 120:2394–2406. https://doi.org/10.1002/2014JD021958
Radinović D, Ćurić M (2014) Measuring scales for daily temperature extremes, precipitation and wind velocity. Meteorol Appl 21:461–465. https://doi.org/10.1002/met.1356
Ren FM, Gao H, Liu LL et al (2014) Research progresses on extreme weather and climate events and their operational applications in climate monitoring and prediction. Meteor Mon 40(7):860–874
Riddle E, Amy H, Butler J et al (2013) CFSv2 ensemble prediction of the wintertime Arctic Oscillation. Clim Dyn 41:1099–1116. https://doi.org/10.1007/s00382-013-1850-5
Saha S, Moorthi S, Wu X et al (2014) The NCEP climate forecast system version 2. J Clim 27(6):2185–2208
Sillmann J, Thorarinsdottir T, Keenlyside N et al (2017) Understanding, modeling and predicting weather and climate extremes: challenges and opportunities. Weather Clim Extremes 18:65–74. https://doi.org/10.1016/j.wace.2017.10.003
Smith ET, Sheridan SC (2018) The characteristics of extreme cold events and cold air outbreaks in the eastern United States. Int J Climatol 38(Suppl.1):e807–e820. https://doi.org/10.1002/joc.5408
Tao YW, Dai K, Dong Q et al (2017) Extreme analysis and ensemble prediction verification on cold wave process in January 2016. Meteor Mon 43(10):1176–1185
Wang ZY, Ding YH (2006) Climate change of the cold wave frequency of China in the last 53 years and the possible reasons. Chin J Atmos Sci 30(6):1068–1076
Wei FY (2008) Variation characteristics of cold waves in China under the background of climate warming. Prog Nat Sci 18(3):289–295
Wheeler DD, Harvey VL, Atkinson DE, Collins RL, Mills MJ (2011) A climatology of cold air outbreaks over North America: WACCM and ERA-40 comparison and analysis. J Geophys Res Atmos 116(D12):D12107
Wu HY, Du YD (2010) Climatic characteristics of cold waves in South China in the Period 1961–2008. Adv Clim Chang Res 6(3):192–197
Yu YY, Cai M, Shi CH, Yan RK, Rao J (2019) Sub-seasonal prediction skill for the stratospheric meridional mass circulation variability in CFSv2. Clim Dyn 53:631–650. https://doi.org/10.1007/s00382-018-04609-9
Acknowledgements
The CPC global temperature data and NCEP/DOE reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, were acquired from their website at https://www.esrl.noaa.gov/psd/. The CFSv2 highest and lowest daily surface air temperature data were acquired from https://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.ncdc:C00877. The authors are grateful to the United States National Centers for Environmental Prediction (NCEP) for making these data available.
Funding
This work was jointly funded by the National Key R&D Program of China (2017YFC1502301) and the National Natural Science Foundation of China (41875089).
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Wei, Z., Dong, W. Evaluation on the CFSv2 forecasts of three cold waves during 2015–2016 in China. Theor Appl Climatol 141, 509–524 (2020). https://doi.org/10.1007/s00704-020-03220-5
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DOI: https://doi.org/10.1007/s00704-020-03220-5