Human influence on the record-breaking cold event in January of 2016 in Eastern China

Transcription

1 Human influence on the record-breaking cold event in January of 2016 in Eastern China Cheng Qian 1, Jun Wang 1, Siyan Dong 2, Hong Yin 2, Claire Burke 3, Andrew Ciavarella 3, Buwen Dong 4, Nicolas Freychet 5, Fraser C Lott 3, and Simon F. B. Tett 5 * 1. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China 2.National Climate Center, China Meteorological Administration, Beijing, China 3. Met Office Hadley Centre, Exeter, UK 4. Department of Meteorology, University of Reading, UK 5. School of Geosciences, University of Edinburgh, Edinburgh, UK

2 Background WMO: global mean temperature 2014 record-breaking 2015 record-breaking 2016 record-breaking CO 2 concentration in 2015: exceeded 400ppm (record-breaking)

3 Background

4 Background Arctic warming: more cold extremes in mid-latitude Eurasia? Yes: Mori et al. 2014; Francis and Vavrus, 2015;Kug et al No: McCusker et al. 2016; Sun et al Huang et al., 2017, Clim. Dynamics

5 Background Changes in extreme cold days 二十四节气 (Twenty-four Solar Terms) ( 이십사 ) 절기 Great Cold China averaged occurrences decreasing Qian et al. 2012, CSB ( にじゅうし ) せっき 立春りっしゅん雨水うすい啓蟄けいちつ春分しゅんぶん清明せいめい谷雨こくう立夏りっか小満しょうまん芒种ぼうしゅ夏至げし小暑しょうしょ大暑たいしょ立秋りっしゅう処暑しょしょ白露はくろ秋分しゅうぶん寒露かんろ霜降そうこう立冬りっとう小雪しょうせつ大雪たいせつ冬至とうじ小寒しょうかん大寒だいかん

6 A strong cold surge occurred during 21st 25th January 2016 affecting most areas of China, especially E China Boss 级寒潮, 入选 2016 年国内十大天气气候事件 Qian et al. 2017, BAMS T max on 23 Jan in Beijing On 24 th January, the snowline even reached Guangzhou and the Pearl River Delta in southern China. This was the first time recorded since 1951.

7 The area averaged anomaly of T min over the region (20-44 o N, o E) 2016: -4 o C ( 2.2 standard deviations) relative to the normal. record-breaking cold 2015/2016 warmest winter Qian et al. 2017, BAMS

8 Media Is it contradict that extreme cold event occurred under global warming? Was the extreme event in January caused by global warming? Aim of this study How much anthropogenic forcing agents have affected the probability of cold events with an intensity equal to or larger than the January 2016 extreme event?

9 Data 744 station observations: homogenized, (Li et al. 2015) HadGEM3-A-N216 model simulations: the Met Office Hadley Centre system for Attribution of extreme weather and Climate Events (ACE; Christidis et al. 2013; Burke and Stott, 2017) 525 histall (historical anthropogenic and natural forcings) 525 histnat (natural forcings only)

10 Data process procedures make observations and simulations comparable: histclim runs average 2. anomaly ( : 15 runs average) 3. mask HadGEM-A ocean grids 4. regridded to 2 o x2 o and mask by Obs 5. gridded Obs masked by simulation 6. area-weighted average of Obs and simulation HistALL & histnat anomalies: both relative to the climatology of histclim.

11 Testing of goodness-of-fit for distribution Qian et al. 2017, BAMS The GEV fit was found to be the most appropriate

12 Qian et al. 2017, BAMS Threshold: 4 o C based on the observed regional T min for 2016 Conclusions: human influences reduced the probability of such a cold event by approximately 2/3 The risk ratio (P1/P0) is approximately 34% (31% and 38%) The return period extended by about 28 years

13 Concluding Remarks Our results are in line with McCusker et al. (2016) and Sun et al. (2016) and agree with Trenary et al. (2015) that despite severe cold surges and record-breaking extreme cold-day occurrences during 2016, winters have become warmer.

14 Why is the long-term warming trend in winter? warmest winter Qian et al. 2017, BAMS

15 Observed and CMIP5 model simulated trends similar Qian and Zhang, 2015, J.Climate

16 Human influences on JJA/DJF temperature D&A using optimal fingerprinting 最优指纹检测冬夏气温中的人为影响 weaker weaker Human influences are robustly detected in East Asia, although it is weaker than the observed changes in winter. 人为影响在东亚区域可以清楚检测出, 虽然比观测到的变化小 Qian and Zhang, 2015, J.Climate

17 Trends in temperature extremes in association with weather-intraseasonal fluctuations in eastern China 与天气 - 季内波动有关的中国东部气温极值趋势 Raw 逐日气温 = Intra-annual 天气 - 季内波动 +annual cycle 年循环 + longer-term 年际年代际 Raw data Intra-annual 天气 - 季内 Annual cycle 年循环 Longer-term 年际年代际 Qian et al. 2011,AAS

18 Trends in temperature extremes in association with weather-intraseasonal fluctuations in eastern China 与天气 - 季内波动有关的中国东部气温极值趋势 ( ) Warm days 暖日 (Tx90p) Cold days 冷日 (Tx10p) Warm nights 暖夜 (Tn90p) Cold nights 冷夜 (Tn10p) DJF Weakened weather-intraseasonal fluctuations in almost all regions in winter 冬季天气 - 季内波动全区减弱, 相应的气温极值全减少 JJA Dipole pattern of changes in summer: weakened in the north, strengthened in the south 夏季天气 - 季内波动 ( 相应的气温极值 ) 是南北偶极子型 : 北方减弱 ( 减少 ) 南方增强( 增多 ) Qian et al. 2011,AAS

19 References Qian C., J. Wang, S. Dong, H. Yin, C. Burke, A. Ciavarella, B. Dong, N. Freychet, F. C Lott, and S. F. B. Tett, 2017: Human influence on the record-breaking cold event in January of 2016 in Eastern China. Bull. Amer. Meteor. Soc., DOI: /BAMS-D Qian, C., and X. Zhang, 2015: Human influences on changes in the temperature seasonality in mid- to high-latitude land areas. J. Climate, 28(15), Qian, C., Z. W. Yan, and C. B. Fu, 2012: Climatic changes in the Twenty-four Solar Terms during , Chinese Sci. Bull., 57(2), Qian, C., Z.W. Yan, Z. Wu, C. B. Fu, and K. Tu, 2011: Trends in temperature extremes in association with weatherintraseasonal fluctuations in eastern China. Adv. Atmos. Sci., 28(2),

20 Thank you for your attention!