Gong Zhi-Qiang

Objective identification research on cold vortex and mid-summer rainy periods in Northeast China

Considering the differences between the Northeast China Cold Vortex (CV) and the Mid-Summer (MS) rainy period and their corresponding atmospheric circulations are comprehensively analyzed, and the objective identification methods of defining the annual beginning and ending dates of Northeast China CV and MS rainy periods are developed respectively. The annual beginning date of the CV (MS) rainy period is as follows. In a period from April to August, if daily regional mean precipitation ryi is larger than yearly regional mean precipitation R (or 2R) on a certain day, the station precipitation rs is larger than the station yearly mean precipitation 〈r〉 (or 2〈r〉) in at least 50% of stations in Northeast China, and this condition is satisfied in the following 2 (7) days, then this date is defined as the beginning date of the CV (MS) rainy period. While the definition of the ending date of the MS rainy period shows the opposite process to its beginning date. With this objective identification method, the multi-year average (1981–2010) beginning date of the CV rainy period is May 3, the beginning date of the MS rainy period is June 27, the ending day of the CV rainy period is defined as the day before the beginning date of the MS rainy period, and the ending date of the MS rainy period is August 29. Meanwhile, corresponding anomaly analysis at a 500-hPa geopotential height, 850-hPa wind, Omega and relative humidity fields all show that the definitions of the average beginning and ending dates of the CV and MS rainy periods have a certain circulation meaning. Furthermore, the daily evolution of the CV index, meridional and zonal wind index, etc. all show that these objectively defined beginning and ending dates of the CV and MS rainy periods have climate significance.

Spatial-Temporal Characteristics of Regional Extreme Low Temperature Events in China during 1960-2009

An objective identification technique is used to detect regional extreme low temperature events(RELTE) in China during 1960-2009.Their spatial-temporal characteristics are analyzed.The results indicate that the lowest temperatures of RELTE,together with the frequency distribution of the geometric latitude center,exhibit a double-peak feature.The RELTE frequently happen near the geometric area of 30 N and 42 N before the mid-1980s,but shifted afterwards to 30 N.During 1960-2009,the frequency,intensity,and the maximum impacted area of RELTE show overall decreasing trends.Due to the contribution of RELTE,with long duration and large spatial range,which account for 10% of the total RELTE,there is a significant turning point in the late 1980s.A change to a much more steady state after the late 1990s is identified.In addition,the integrated indices of RELTE are classified and analyzed.

Spatiotemporal distribution characteristics and attribution of extreme regional low temperature event

Based on an objective identification technique for regional low temperature event (OITRLTE), the daily minimum temperature in China has been detected from 1960 to 2013. During this period, there were 60 regional extreme low temperature events (ERLTEs), which are included in the 690 regional low temperature events (RLTEs). The 60 ERLTEs are analyzed in this paper. The results show that in the last 50 years, the intensity of the ERLTEs has become weak; the number of lasted days has decreased; and, the affected area has become small. However, that situation has changed in this century. In terms of spatial distribution, the high intensity regions are mainly in Northern China while the high frequency regions concentrate in Central and Eastern China. According to the affected area of each event, the 60 ERLTEs are classified into six types. The atmospheric circulation background fields which correspond to these types are also analyzed. The results show that, influenced by stronger blocking highs of Ural and Lake Baikal, as well as stronger southward polar vortex and East Asia major trough at 500-hPa geopotential height, cold air from high latitudes is guided to move southward and abnormal northerly winds at 850 hPa makes the cold air blow into China along diverse paths, thereby forming different types of regional extreme low temperatures in winter.

Vertical structure of predictability and information transport over the Northern Hemisphere

Based on nonlinear prediction and information theory, vertical heterogeneity of predictability and information loss rate in geopotential height field are obtained over the Northern Hemisphere. On a seasonal-to-interannual time scale, the predictability is low in the lower troposphere and high in the mid-upper troposphere. However, within mid-upper troposphere over the subtropics ocean area, there is a relatively poor predictability. These conclusions also fit the seasonal time scale. Moving to the interannual time scale, the predictability becomes high in the lower troposphere and low in the mid-upper troposphere, contrary to the former case. On the whole the interannual trend is more predictable than the seasonal trend. The average information loss rate is low over the mid-east Pacific, west of North America, Atlantic and Eurasia, and the atmosphere over other places has a relatively high information loss rate on all-time scales. Two channels are found steadily over the Pacific Ocean and Atlantic Ocean in subtropics. There are also unstable channels. The four-season influence on predictability and information communication are studied. The predictability is low, no matter which season data are removed and each season plays an important role in the existence of the channels, except for the winter. The predictability and teleconnections are paramount issues in atmospheric science, and the teleconnections may be established by communication channels. So, this work is interesting since it reveals the vertical structure of predictability distribution, channel locations, and the contributions of different time scales to them and their variations under different seasons.

Predicting extreme rainfall over eastern Asia by using complex networks

A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971?2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization (ES). Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay (1 ? n ? 10). The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay (2 ? n ? 10). The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon (EASM) or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years.

The Relationship Between North Pacific Oscillation and Summer Floods/Drougts over North China

The NCEP/NCAR reanalysis data for the period 1948-2011 is used to calculate North Pacific Oscillation Index (NPOI), and then the positive correlation between NPO and summer floods/drougts over North China was discovered through studying the relationship between NPOI and Palmer Drought Severity Index (PDSI). When in positive NPOI years, summer PDSI is higher than normal, and North China has more summer floods; otherwise, summer PDSI is lower than normal, and North China has more summer drougts. Possible mechanism analysis shows that, when in positive(negative) NPOI years, in 850hPa wind anomaly, the common action of anti-cyclonic(cyclonic) in Ural Mountains, the cyclone(anti-cyclonic) of Lake Baikal, and the anti-cyclonic(cyclonic) anomaly circulation in West Pacific, have strengthened(weakened) the convergence of south-west warm and humid air flows of low layer in North China region. And also, when in positive(negative) NPOI years, 500hPa geopotential height anomaly shows’+ - +’(‘- + -‘)wave train, and West Pacific subtropical high is stronger(weaker)/shifting northwest(southeast)than normal years, cold and warm air activities make more (less) rainfall over North China.

Preliminary research on the relationship between long-range correlations and predictability

By establishing the Markov model for a long-range correlated time series (LRCS) and analysing its evolutionary characteristics, this paper defines a physical effective correlation length (ECL) τ, which reflects the predictability of the LRCS. It also finds that the ECL has a better power law relation with the long-range correlated exponent γ of the LRCS: τ = K exp(−γ/0.3) + Y, (0 < γ < 1) — the predictability of the LRCS decays exponentially with the increase of γ. It is then applied to a daily maximum temperature series (DMTS) recorded at 740 stations in China between the years 1960–2005 and calculates the ECL of the DMTS. The results show the remarkable regional distributive feature that the ECL is about 10–14 days in west, northwest and northern China, and about 5–10 days in east, southeast and southern China. Namely, the predictability of the DMTS is higher in central-west China than in east and southeast China. In addition, the ECL is reduced by 1–8 days in most areas of China after subtracting the seasonal oscillation signal of the DMTS from its original DMTS; however, it is only slightly altered when the decadal linear trend is removed from the original DMTS. Therefore, it is shown that seasonal oscillation is a significant component of daily maximum temperature evolution and may provide a basis for predicting daily maximum temperatures. Seasonal oscillation is also significant for guiding general weather predictions, as well as seasonal weather predictions.

Scale and phase characteristics of temperature series in China

The scaling behavior and phase probability distribution of temperature return series of Beijing station is investigated using Hilbert Huang transform (HHT) method. Results show that return series have nice scaling behavior, characterized by an exponent α (2<α< 4), well outside the stable Lévy regime 0<α<2. Besides, the phase probability distribution of temperature return series shows that abruptly changing behaviors indicate non-predictable and stochastic features on long scales, while gradually it is convergent to a spike value at the point Ф=0 indicating a comparatively better prediction on short scales.

The prediction theory of record breaking daily temperature events

The daily maximum/minimum temperature data at 740 stations in China from 1960 to 2005 were analyzed to reveal the statistical characteristics of record-breaking (RB) daily extreme temperature events in the past 46 years. The results indicate that the change amplitudes of future extreme temperatures differ evidently from place to place, showing a remarkable regional feature: future extreme high temperature events will be in a stronger rising period of intensity in Southwest China, and in a relatively weaker rising period in western China; while the largest decreasing amplitude of future extreme low temperature events will appear in Northeast China and the north of Northwest China, and its intensity will be in a relatively stable period in central China and Southwest China.