| Since 2000,the speed of global warming has a decrease characteristic, which is called "Global Warming Hiatus" by part of researchers. Meanwhile, the frequent occurrence of cold event in Era-Asia also attracts the attention of research on extreme low temperature event. Therefore, this paper mainly focus on the identification of regional low temperature(RLTE), the characters of RLTE, the relationship between RLTE and both climate indices and geopotential height anomalies of block high in key areas, the winter-winter reoccurrence mechanism of temperature change in Northern of East Asia and the prediction method of RLTE. Some meaningful conclusions are as followings,(1) An objective identification technique for regional low temperature extreme events(OITRLTE) is developed. This technique consists of four parts, 1) defining the threshold value of extreme low temperature for single station; 2) partition daily natural abnormality belts; 3) distinguishing event’s temporal continuity; 4) an index system for regional events was specially developed, which includes five single indices and an integrated index. The integrated index is also defined by consider the co-affections of single index. Applied studies then show that OITRLTE is skillful capability in identifying regional low temperature extreme events. It can objectively and automatically capture daily impacted areas of a regional event for its duration, and reasonably putting them in a “string” to shape an entire regional event. OITRLTE is also used in the extreme event real time monitoring system of National Climate Center. The database, platform of retrieve for RLTE is also developed respectively, in order to supply technique support for producing real time operational products. The spatial and temporal continuity of RLTE is analyzed from time maintain and space synchronization.We calculate nonlinear correlation between different grid points by event synchronization(ES) method, and construct extreme event network over eastern Asia. The occurrence, development, and demise of extreme event are shown similar to cellular automata. And we construct nonlinear dynamics prediction model using extreme event network which is suitable for RLTE, regional high temperature event and regional strong precipitation event. Furthermore, 6 typical extreme rainfall cases are simulated and the mean prediction accuracy is 31.3%, the prediction accuracy of some process can reach 40%. The comparison between modeling and observation reveals that the extreme rainfall region can be substantially loaded by this model, which has potential valuable application on prediction extreme rainfall over eastern Asia.(2)The spatial distribution and temporal changes of RLTEs is also investigated. Results show that probability distribution of indexes lowest temperature and latitude of geometrical center of RLTEs both obeys the two peak distribution, which means that the center of RLTEs mainly located at two belts of 32°N and 42°N. Besides, the annual accumulative value of the frequency, intensity and max covering area of RLTEs is decreased, and there is obvious phase shift during the end of 1980 s and the trend becomes stationary after 1990 s. Considering the spatial distribution of RLTE, those 60 RLTEs with highest integrated index value were classified into 6 types, such as nationwide type(20 events), east China type(15 events), northeast-north China type(5 events), north-south China type(7 events), south China type(3 events) and northwest-south China style(10 events). The circulation backgrounds of different types of RLTE were also analyzed to indentify the possibility of classification.(3) The regional low temperature event(RLTE) from December 30, 2010 to February 2, 2011 was the very rare and protracted cold event with the largest integrated index(Z) since 1979. Two meteorological factors could be responsible for this extreme event. First, a persistent blocking pattern existed in the mid-latitudes. This not only allowed cold air to persist in southern China, but also enabled each perturbation from the west propagating around the blocking high to trigger downstream cold-air intrusions from the north. Second, the consistently downward negative Arctic Oscillation(AO) was favorable for the eastward moving of Rossby waves in middle latitudes, which made the upper reaches positive center in SLP and negative center in Z500 move to East Asia. This stable and consistent situation favored the polar area cold air invasion to the mid-latitude region. Of these two factors, the blocking pattern was likely to be the direct cause, the co-effects of consistently strong downward negative AO from the stratosphere and the corresponding eastward moving wave train in Z500 and SLP might be the leading tele-connection. The corresponding relationships between different type of events and anomalies of climatic indices were further studied, and the mainly influencing indices related well to different types of events were obtained. On the whole, the small of the NINO3.4, PDO, AO and strong of winter wind indices have good corresponding relationships with RLTE; among the years that the winter average values of four indices reach 15% extreme threshold, the percentage of occurrence of RLTE run up to 80.0%,77.8%,60.0% and 62.5%, respectively.(4) The nature of RLTE has good correlation with block high anomalies in north hemisphere midlatitude. The research on relationship between the geopotential height anomalies mode in Euro-Asia block high areas RLTE shows that the probability of positive anomalies happened in one area of Ural, Baikal or Okhotsk is 0.83 for RLTEs longer than 12 days, while it is 0.92 for RLTEs longer than 15 days. Therefore, geopotential height anomalies mode in Euro-Asia block high areas might be the direct reasons for the RLTE. Then the mode with positive height anomalies is divided into 7 types, i.e. positive anomalies in area of Ural, Baikal, Okhotsk, Ural-Baikal, UralBaikal-Okhotsk, Ural-Okhotsk, and Baikal-Okhotsk, respectively. Besides, different anomaly modes corresponded RLTEs have quite different spatial distribution, duration and density. i.e. the Ural-Baikal-Okhotsk mode is always corresponding to strong event with spatial distribution is North-South China type, with average duration is 15.3 days, and with average integrated index is 2.0. While, the Ural-Okhotsk mode is always corresponding to weak event with spatial distribution is the North-South China type, with average duration is 9 days. Furthermore, each type of positive height anomalies has prior signals for the RLTE and the averages lead-time is up to 5-10 days. Spatial distribution of leading days also show that the prior signal often happens at area of Ural and Okhotsk.(5) 5 typical frequent low-temperature periods(the middle of 1960 s, the middle of 1970 s, the beginning of 1990 s, the beginning of 2000 s and 2008-2011) were selected in order to analyze their scale character. The atmospheric circulation and sea surface temperature(SST) external forcing is also compared among these 5 different periods. Results indicate that the current period of frequent has the similar characters as that of 1960 s, i.e. surface temperature is lower than normal from Europe to South Asia, anomalies of 500 h Pa field in mid-latitude of Europe- Asia show the north-positive and south-negative character, north and south gradient of U300 at west wind flow area is quite obvious, the Siberia high is quite stronger than normal, and the PDO show the typical cold phase character with SST in north pacific is warmer than normal. Meanwhile, the difference of winter atmosphere anomalies between cold period(1960s-1970s) and warm period(2008-2011) is also analyzed. The Temperature is cold in northern Era-Asia and Arctic area and AO shows weak negative phase in cold period, while the temperature is warm in northern Era-Asia and Arctic area and AO shows strong negative phase in cold period.(6) The atmospheric temperature in the northern area of East Asia(40-50°N, 100-130°E)had a typical characteristic of cold winter-warm summer-the following cold winter for two consecutive years in the periods 1950 s, 1960 s and 2000 s. While, the opposite variation characteristic of warm winter-cold summer-the following warm winter was happened in 1990 s. This typical seasonal evolution of atmospheric temperature was defined as a new variation mechanism: winter-to-winter recurrence(WWR). There were 23 WWR years and the probability of occurrence was close to 40%. This WWR characteristic was independent of the variation of the ENSO index which has significant research meaning. The attribution of WWR is also analyzed by the research of the possible influence caused by the atmosphere internal factors and external forces. Main research results indicate that 1) there is the same winter-winter reoccurrence phenomenon in the AO abnormal index which has a significant correlation with the WWR index of temperature change in Northern East Asia with correlation coefficient is 0.45. It is indicates that seasonal abnormal might be an important influence factor to the WWR of temperature change in Northern East Asia. 2) In negative WWR years, PDO mainly shows the negative phases in different seasons while it is occupied by positive phases in positive WWR years. As negative(positive) PDO is good for continuous cold(warm) winter in Northern East Asia, PDO might be the external force factor of WWR of temperature change in Northern East Asia. 3) With the binary regression based on the indexes of PDO and AO, the regression index series Therefore, the WWR of temperature change in Northern East Asia might be the result of co-action between PDO and AO. |
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