A Data-Adaptive Filter of the Tahiti-Darwin Southern Oscillation Index and the Associate Scheme of Filling Data Gaps

The Tahiti-Darwin Southern Oscillation index provided by Climate Analysis Center of USA has been used in numerous studies. But, it has some deficiency. It contains noise mainly due to high month-to-month variability. In order to reduce the level of noise in the SO index, this paper introduces a fully data-adaptive filter based on singular spectrum analysis. Another interesting aspect of the filter is that it can be used to fill data gaps of the SO index by an iterative process. Eventually, a noiseless long-period data series without any gaps is obtained.

A New North Atlantic Oscillation Index and Its Variability

A new North Atlantic Oscillation (NAO) index, the NAOI, is defined as the differences of normalized sea level pressures regionally zonal-averaged over a broad range of longitudes 80°W-30°E. A comprehensive comparison of six NAO indices indicates that the new NAOI provides a more faithful representation of the spatial-temporal variability associated with the NAO on all timescales. A very high signal-to-noise ratio for the NAOI exists for all seasons, and the life cycle represented by the NAOI describes well the seasonal migration for action centers of the NAO. The NAOI captures a larger fraction of the variance of sea level pressure over the North Atlantic sector (20°-90°N, 80°W-30°E), on average 10% more than any other NAO index. There are quite different relationships between the NAOI and surface air temperature during winter and summer. A novel feature, however, is that the NAOI is significantly negative correlated with surface air temperature over the North Atlantic Ocean between 10°-25°N and 70°-30°W, whether in winter or summer. From 1873, the NAOI exhibits strong interannual and decadal variability. Its interannual variability of the twelve calendar months is obviously phase-locked with the seasonal cycle. Moreover, the annual NAOI exhibits a clearer decadal variability in amplitude than the winter NAOI. An upward trend is found in the annual NAOI between the 1870s and 1910s, while the other winter NAO indices fail to show this tendency. The annual NAOI exhibits a strongly positive epoch of 50 years between 1896 and 1950. After 1950, the variability of the annual NAOI is very similar to that of the winter NAO indices.

Antarctica Sea-ice Oscillation and Its Possible Impact on Monsoon of South Sea

Antarctic sea-ice oscillation index with a seesaw pattern is defined using NCEP/NCAR reanalysis girds data of monthly Antarctica sea-ice concentration from 1979 to 2002.The relationships between the index of winter and the summer precipitations in China as well as the onset date of the summer East Asia monsoon are presented.The study result shows that the grids of correlation coefficients passed 5% confidence level between Antarctic sea-ice oscillation index and Antarctic sea-ice concentration are more than 1/3 of all grids of Antarctica sea-ice,that means the index can represent 1/3 sea-ice area.The winter index has a significant correlation with abnormal summer（June-August） precipitation in China.The area of positive correlation lies in the Yangtze River basin and its south,and that of negative correlation lies mainly in the north of Yangtze River basin.While the winter index is positive（negative）,the onset date of South China Sea monsoon is earlier（later）,with a probability of 79%（80%）.Consequently, a conceptual model is given in term of discussing the possible process between the winter Antarctic sea ice and the monsoon precipitation in China.

Pre-summer Persistent Heavy Rain over Southern China and Its Relationship with Intra-seasonal Oscillation of Tropical Atmosphere

Based on daily precipitation data supplied by the Chinese meteorological administration,hourly reanalysis datasets provided by the ECMWF and daily outgoing long wave radiation supplied by the NOAA,the evolution regularity of continuous heavy precipitation over Southern China(SC)from April to June in 1979-2020 was systematically analyzed.The interaction between specific humidity and circulation field at the background-scale,the intra-seasonal-scale and the synoptic-scale,and its influence on persistent heavy precipitation over the SC during the April-June rainy season were quantitatively diagnosed and analyzed.The results are as follows.Persistent heavy rainfall events(PHREs)over the SC during the April-June rainy season occur frequently from mid-May to mid-and late-June,exhibiting significant intra-seasonal oscillation(10-30-day)features.Vertically integrated moisture flux convergence(VIMFC)can well represent the variation of the PHREs.A multiscale quantitative diagnosis of the VIMFC shows that the pre-summer PHREs over the SC are mainly affected by the background water vapor(greater than 30 days),intraseasonal circulation disturbance(10-30-day)and background circulation(greater than 30 days),and water vapor convergences are the main factor.The SC is under the control of a warm and humid background and a strong intraseasonal cyclonic circulation,with strong convergence and ascending movements and abundant water vapor conditions during the period of the PHREs.Meanwhile,the westward inter-seasonal oscillation of tropical atmosphere keeps the precipitation system over the SC for several consecutive days,eventually leading to the occurrence,development and persistence of heavy precipitation.

基于奇异谱分析的南方涛动指数短期气候预测试验(英文)

The Southern Oscillation Index (SOI) time series is analyzed by means of the singular spectrum analysis (SSA) method with 60-month window length. Two major oscillatory pairs are found in the series whose periods are quasi-four and quasi-two years respectively. The auto-regressive model, which is developed on the basis of the Maximum Entropy Spectrum Analysis, is fitted to each of the 9 leading components including the oscillatory pairs. The prediction of SOI with the 36-month lead is obtained from the reconstruction of these extrapolated series. Correlation coefficient between predicted series and 5 months running mean of observed series is up to 0.8. The model can successfully predict the peak and duration of the strong ENSO event from 1997 to 1998. It's also shown that the proper choice of reconstructed components is the key to improve the model prediction.

Establishment of Statistical Model for Precipitation Prediction in the Flood Season in China

[Objective] The research aimed to establish the regression model which was used to predict the precipitation in the flood season in China.[Method] Based on statistical model,North Atlantic oscillation index and the sea surface temperature index in development and declining stages of ENSO were used to predict East Asian summer monsoon index.After the stations were divided into 16 zones,the same factors were used to establish the regression model predicting the station precipitation in the flood season in China.Moreover,it was compared with the model that predicted firstly the monsoon index and estimated the precipitation.[Result] The prediction results of summer precipitation during 2005-2009 by every model were contrasted.It was found that the model that the factor predicted indirectly the regional precipitation was better than that predicted indirectly the station precipitation.Meanwhile,the model that the factor predicted directly the regional precipitation was better than that predicted indirectly the regional precipitation.The prediction score P of optimum model that three factors predicted directly the regional precipitation reached averagely 74.2,and the anomaly correlation coefficient ACC was averagely 0.219.Seen from the comparison situation of positive and negative zone distribution of precipitation anomaly percentage between the predicted and observed values in 5 years,the prediction effects in the south and east of Northeast China,some areas in the south of Yangtze River,the coast of South China and most areas of Xinjiang were good.The predicted positive/negative distribution of precipitation anomaly percentage tallied with that of observation.[Conclusion] The model could predict well summer precipitation in China.

Dengue Climate Variability in Rio de Janeiro City with Cross-Wavelet Transform

Dengue is one of the most prominent tropical epidemic diseases present in the Rio de Janeiro city and Southeast part of Brazil, due to the widespread conditions of occurrence of the dengue vector, the mosquito Aedesaegypti, such as high-temperature days interlaced with afternoon or nocturnal rainstorms in summer. This work has the objective of investigating the relationships between variabilities of the El Ni?o-South Oscillation (ENSO) and greater epidemics of dengue in Rio de Janeiro city. To accomplish this goal, the analysis and signal decomposition by cross-wavelet transform (WT) was applied to obtain the cross variability associated with variations of power and phase of both signals by characteristic periods and along with the time series. Data considered in the analysis are (the decimal logarithm of normalized value) of the monthly available notifications of dengue worsening, provided by the public health system of Brazil, and the Southern Oscillation Index (SOI) Ni?o 3.4 data, provided by the National Oceanic and Atmospheric Administration (NOAA), in the period 2000-2017. A maximum cross-wavelet power close to 0.45 was obtained for the representative period of 1 year and also to periods between 3 and 4 years, associated with the positive phase of the SOI index (i.e. , La Ni?a) or with a transition to the positive phase. The evolution of the combined variability of SOI and dengue can be expressed by progressive differences in phase along the time, eventually resulting in yielding phases (i.e., La Niña-Dengue epidemic).

A Climatology of Heavy Rain and Major Flood Events in Victoria 1876-2019 and the Effect of the 1976 Climate Shift

An extensive search has been carried out to find all major flood and very heavy rainfall events in Victoria since 1876 when Southern Oscillation(SOI)data became available.The synoptic weather patterns were analysed and of the 319 events studied,121 events were found to be East Coast Lows(ECLs)and 82 were other types of low-pressure systems.Tropical influences also played a large role with 105 events being associated with tropical air advecting down to Victoria into weather systems.Examples are presented of all the major synoptic patterns identified.The SOI was found to be an important climate driver with positive SOIs being associated with many events over the 144 years studied.The 1976 Climate Shift and its influence on significant Victorian rainfall events is studied and negative SOI monthly values were shown to dominate following the Shift.However,one of the most active periods in 144 years of Victorian heavy rain occurred after the shift with a sustained period of positive SOI events from 2007 to 2014.Therefore,it is critical for forecasting future Victorian heavy rainfall is to understand if sequences of these positive SOI events continue like those preceding the Shift.Possible relationships between the Shift and Global Temperature rises are also explored.Upper wind data available from some of the heaviest rainfall events showed the presence of anticyclonic turning of the winds between 850hPa and 500hPa levels which has been found to be linked with extreme rainfall around the Globe.

Evaluation of Chaotic Demodulator for EBPSK Signals

Based on the theory of Duffing oscillator weak signal detection and the technology of extended binary phase shift keying （EBPSK） modulation, the chaotic demodulator using the Duffing oscillator for EBPSK signals was proposed. The proposed demodulator could avoid the problem of demodulation filters design, and shows the excellent anti-noise capability of chaotic oscillator detection. Numerical and experimental tests were taken to investigate the impact of modulation parameters T and 0 on bit error performance of the proposed method, and the performance limits were gotten. The results show that the proposed chaotic demodulator works well under a very low signal-to-noise ratio （SNR） conditions, and gets SNR gains about 20 dB to 30 dB from the impulse filter.

DISCONTINUOUS OSCILLATION IN THE ATMOSPHERIC CIRCULATION AND INDEX CYCLE

By using a low-order,two-layer baroclinic quasi-geostrophic model,a nonlinear system including the interaction between a thermal forced wave,a transient wave and zonal flow is studied. Under the conditions of near-resonance and weak baroclinic instability,the features of solution in phase space are discussed with the analytical methods of multiple scale and discontinuous oscillation.The results show that the dynamic coupling between forced wave and transient wave is responsible for the physical mechanism of the non-uniform index cycle of the atmospheric circulation.

Relationship between increase rate of human plague in China and global climate index as revealed by cross-spectral and cross-wavelet analyses

Plague has caused the death of hundreds of millions of people throughout the human history.Today this disease is again re-emerging and hence is again becoming an increasing threat to human health in several parts of the world.However,impacts of global climate variation(e.g.El Nino and Southern Oscillation[ENSO])and global warming on plagues are largely unknown.Using cross-spectral analysis and cross-wavelet analysis,we have analyzed the relationship between increase rate of human plague in China during 1871–2003 and the following climate factors(as measured by the Southern Oscillation Index[SOI],Sea Surface Temperature of east Pacific equator[SST]and air Temperature of the Northern Hemisphere[NHT]).We found in the frequency domain that increase rate of human plague was closely associated with SOI and SST.Cross-spectral analysis reveals that significant coherencies between increase rate of human plague and ENSO were found over short periods(2–3 years),medium periods(6–7 years)and long periods(11–12 years,30–40 years).Cross-wavelet analysis reveals that increase rate of human plague oscillates in phase with SOI,but in anti-phase with SST over periods of 2–4 years and approximately 8 years(6–10 years).These results indicate that ENSO-driven climate variation may be important for occurrences of human plague in China.However,there is a need for a further analysis of the underlying mechanism between human plague in China and ENSO.

A New Prediction Model for Grain Yield in Northeast China Based on Spring North Atlantic Oscillation and Late-Winter Bering Sea Ice Cover

Accurate estimations of grain output in the agriculturally important region of Northeast China are of great strategic significance for guaranteeing food security.New prediction models for maize and rice yields are built in this paper based on the spring North Atlantic Oscillation index and the Bering Sea ice cover index.The year-to-year increment is first forecasted and then the original yield value is obtained by adding the historical yield of the previous year.The multivariate linear prediction model of maize shows good predictive ability,with a low normalized root-mean-square error（NRMSE）of 13.9%,and the simulated yield accounts for 81%of the total variance of the observation.To improve the performance of the multivariate linear model,a combined forecasting model of rice is built by considering the weight of the predictors.The NRMSE of the model is 12.9%and the predicted rice yield explains 71%of the total variance.The corresponding cross-validation test and independent samples test further demonstrate the efficiency of the models.It is inferred that the statistical models established here by applying year-to-year increment approach could make rational prediction for the maize and rice yield in Northeast China before harvest.The present study may shed new light on yield prediction in advance by use of antecedent large-scale climate signals adequately.