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The Bloomberg Carbon Clock is a web-based and real-time estimate of the global average atmospheric CO₂ level. The work was conceived to help non-scientists understand the seasonal nature of atmospheric composition, and offers a click-through explanation of the CO₂ data’s meaning, history, and implications. The Carbon Clock was designed to satisfy both scientific rigor and aesthetic appeal.

The Detrended Fluctuation Analysis (DFA) and its extensions (MF-DFA) have been proposed as robust techniques to determine possible long-range correlations in self-affine signals. However, many studies have reported the susceptibility of DFA to trends which give rise to spurious crossovers and prevent reliable estimations of the scaling exponents. Lately, several modifications of the DFA method have been reported with many different techniques for eliminating the monotonous and periodic trends. In this study, a smoothing algorithm based on the Orthogonal V-system (OVS) is proposed to minimize the effect of power-law trends, periodic trends, assembled trends and piecewise function trends. The effectiveness of the new method is demonstrated on monofractal data and multifractal data corrupted with different trends.

Indonesia, a tropical maritime continent between the Pacific Ocean and the Indian Ocean, frequently experiences extreme rainfall (ER) that lead to a major disaster such as floods and landslides. These disasters are effect economic activity and impact human daily life, and the future change projection, therefore, is important to reduce the impact of extreme rainfall in Indonesia. In this study, we examined the linking of the annual maximum (AM) of daily rainfall series with climate variability including El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Madden-Julian Oscillation (MJO) by optimizing statistical extreme value analysis based on daily rainfall data (1985– 2014) observed at ten meteorological stations around the Java and Makassar Islands. Using the trend-free pre-whitening (TFPW) Mann-Kendall test, the AM had significantly increased by 0.983 mm/year (p < 0.001), probably due to intensified sea surface temperature (SST) anomaly by global warming. Furthermore, based on the best selected non-stationary generalized extreme value distribution model, Waingapu and Luwuk covariate significantly with ENSO, while Perak and Jakarta station covariate insignificantly to IOD. The intensified AM during La Nina and negative IOD tend to increase Indonesia SST and then corresponding with the low-level wind convergence that produces upward moisture flux motion, increasing cloud cover that enriches the convection activity. On the contrary, the Madden-Julian Oscillation signal in AM was less prominent in all stations possibly due to weakened mesoscale circulation. During active MJO over Indonesia region, increasing in cloud cover will reduce the solar radiation. This condition is unfavorable for convection activity and therefore, ER is reduced. Finally, analyses of Indonesia ER variability reveal some sensitivity to climate variability in adjacent parts of Indian and Pacific Ocean and trough extreme value analysis, this study highlights the interaction between ER variability and sea-air phenomena around Indonesia.

A key element in the design of a repeated sample survey is the rotation pattern, which affects the variability of the time series of survey estimates and the seasonally adjusted and trend estimates produced from them. This paper considers the choice of rotation pattern for seasonally adjusted and trend estimates obtained from a repeated survey, using X11 based methods.

In order to provide data reference in protecting Beihai Silver Beach this article used the moving average method spearman rank correlation analysis method and R/S rescaled range method to analyze the typhoon tendency in Beihai Silver Beach and predicted the future tendency from the typhoon frequency intensity and extremes. The results show that: In the past 60 years there is a downward trend in the typhoon frequency in Beihai Silver Beach with a growing trend in the intensity and extremes though those three trends aren't very obvious; the typhoon frequency in Beihai Silver Beach will rise in the future so do the intensity and extremes. For ensuring Silver Beach is not affected by the change of typhoon in the future we must make some targeted and reasonable responses.