Ocean current observation and spectrum analysis in central Chukchi Sea during the summer of 2008

During the summer of 2008, the third CHINARE Arctic Expedition was carried out on board of Xuelong Icebreaker in the central Chukchi Sea. A submersible mooring system was deployed and recovered at Station CN-01 （71.40.024＇N, 167.58.910＇W） with 33 days of the current profile records, and continuous observation of temperature and salinity data were collected. This mooring station locates in the blank of similar observation area and it is the first time for our Chinese to finish this kind of long-term mooring work in this area. This mooring system finished integrated hydrological observations with long-term continuous record of the whole profile velocity for the first time. Based on time series analysis of temperature, salinity, velocity and flow direction, we get the following main results. （1） During the observation period, the mean surface current velocity is 70.2 cm/s eastward, and velocity reaches its maximum in average at 3 m level with magnitude 90.0 cm/s, direction 206.. （2） In 9-30 m layers, the semidiurnal period variation is the most obvious, the flow direction is quite stable, and the flow is synchronous and consistent vertically. （3） Besides the semidiurnal period variation, the main variation in the upper layer is in 11-d period, with variations in period 5.5, 5.5, and 3.7 d, which reflect the influences of sea surface wind change and maintenance. （4） Near the bottom the temperature change is correlated and synchronized with the conductivity.

A possible interrelation between Earth rotation and climatic variability at decadal time-scale

Using multichannel singular spectrum analysis （MSSA） we decomposed climatic time se- ries into principal components, and compared them with Earth rotation parameters. The global warming trends were initially subtracted. Similar quasi 60 and 20 year periodic os- cillations have been found in the global mean Earth temperature anomaly （HadCRUT4） and global mean sea level （GMSL）. Similar cycles were also found in Earth rotation variation. Over the last 160 years multi-decadal change of Earth＇s rotation velocity is correlated with the 60-year temperature anomaly, and Chandler wobble envelope reproduces the form of the 60-year oscillation noticed in GMSL. The quasi 20-year oscillation observed in GMSL is correlated with the Chandler wobble excitation. So, we assume that Earth＇s rotation and climate indexes are connected. Despite of all the clues hinting this connection, no sound conclusion can be done as far as ocean circulation modelling is not able to correctly catch angular momentum of the oscillatory modes.

Smoothing Non-Stationary Time Series Using the Discrete Cosine Transform

This paper considers the problem of smoothing a non-stationary time series(having either deterministic and/or stochastic trends) using the discrete cosine transform(DCT).The DCT is a powerful tool which has found fruitful applications in filtering and smoothing as it can closely approximate the optimal Karhunen-Loeve transform(KLT).In fact,it is known that it almost corresponds to the KLT for first-order autoregressive processes with a root close to unity:This is the case with most economic and financial time series.A number of new results are derived in the paper:(a) The explicit form of the linear smoother based on the DCT,which is found to have time-varying weights and that uses all observations;(b) the extrapolation of the DCT-smoothed series;(c) the form of the average frequency response function,which is shown to approximate the frequency response of the ideal low pass filter;(d) the asymptotic distribution of the DCT coefficients under the assumptions of deterministic or stochastic trends;(e) two news method for selecting an appropriate degree of smoothing,in general and under the assumptions in(d).These findings are applied and illustrated using several real world economic and financial time series.The results indicate that the DCT-based smoother that is proposed can find many useful applications in economic and financial time series.