利用Agro浮标估计南大洋混合的时空变化

海洋中的湍流跨等密度面混合(以下简称混合)控制着海洋中淡水、热量以及CO2等溶解物质的输运。南大洋是全球湍流混合最强烈的区域之一。理解南大洋湍流混合的时空分布特征对于模拟和预测全球大洋环流和气候变化起着至关重要的作用。目前,部分投放在南大洋的新型Argo浮标已经采用铱星通讯系统传送数据,可以返回垂向高分辨率的水文剖面,从而为研究南大洋的湍流混合提供了前所未有的机遇。本文作者在国际上首次利用这些新型浮标观测得到的高分辨率剖面对湍流混合进行了研究。结果表明,南大洋的混合存在明显的空间分布不均匀性,并且与地形变化密切相关。此外,在地形平坦处,湍流混合表现出明显的季节变化。这种变化主要是由风输入到海洋中的近惯性能量的季节性变化引起的。     

Genomic and functional adaptation in surface ocean planktonic prokaryotes

The understanding of marine microbial ecology and metabolism has been hampered by the paucity of sequenced reference genomes. To this end, we report the sequencing of 137 diverse marine isolates collected from around the world. We analysed these sequences, along with previously published marine prokaryotic genomes, in the context of marine metagenomic data, to gain insights into the ecology of the surface ocean prokaryotic picoplankton (0.1-3.0?μm size range). The results suggest that the sequenced genomes define two microbial groups: one composed of only a few taxa that are nearly always abundant in picoplanktonic communities, and the other consisting of many microbial taxa that are rarely abundant. The genomic content of the second group suggests that these microbes are capable of slow growth and survival in energy-limited environments, and rapid growth in energy-rich environments. By contrast, the abundant and cosmopolitan picoplanktonic prokaryotes for which there is genomic representation have smaller genomes, are probably capable of only slow growth and seem to be relatively unable to sense or rapidly acclimate to energy-rich conditions. Their genomic features also lead us to propose that one method used to avoid predation by viruses and/or bacterivores is by means of slow growth and the maintenance of low biomass.     

Recent decline in the global land evapotranspiration trend due to limited moisture supply

More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land?a key diagnostic criterion of the effects of climate change and variability?remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1?±?1.0?millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Ni?o event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.     

An assessment of the economic value of non-linear foreign exchange rate forecasts

Recent research suggests that non-linear methods cannot improve the point forecasts of high-frequency exchange rates. These studies have been using standard forecasting criteria such as smallest mean squared error (MSE) and smallest mean absolute error (MAE). It is, however, premature to conclude from this evidence that non-linear forecasts of high-frequency financial returns are economically or statistically insignificant. We prove a proposition which implies that the standard forecasting criteria are not necessarily particularly suited for assessment of the economic value of predictions of non-linear processes where the predicted value and the prediction error may not be independently distributed. Adopting a simple non-linear forecasting procedure to 15 daily exchange rate series we find that although, when compared to simple random walk forecasts, all the non-linear forecasts give a higher MSE and MAE, when applied in a simple trading strategy these forecasts result in a higher mean return. It is also shown that the ranking of portfolio payoffs based on forecasts from a random walk, and linear and non-linear models, is closely related to a non-parametric test of market timing.