Seasonal variation of mesoscale eddy intensity in the global ocean

Mesoscale eddies are a prominent oceanic phenomenon that plays an important role in oceanic mass transport and energy conversion.Characterizing by rotational speed,the eddy intensity is one of the most fundamental properties of an eddy.However,the seasonal spatiotemporal variation in eddy intensity has not been examined from a global ocean perspective.In this study,we unveil the seasonal spatiotemporal characteristics of eddy intensity in the global ocean by using the latest satellite-altimetry-derived eddy trajectory data set.The results suggest that the eddy intensity has a distinct seasonal variation,reaching a peak in spring while attaining a minimum in autumn in the Northern Hemisphere and the opposite in the Southern Hemisphere.The seasonal variation of eddy intensity is more intense in the tropical-subtropical transition zones within latitudinal bands between 15°and 30°in the western Pacific Ocean,the northwestern Atlantic Ocean,and the eastern Indian Ocean because baroclinic instability in these areas changes sharply.Further analysis found that the seasonal variation of baroclinic instability precedes the eddy intensity by a phase of 2–3 months due to the initial perturbations needing time to grow into mesoscale eddies.

Interannual to Interdecadal Variation of East Asian Summer Monsoon and its Association with the Global Atmospheric Circulation and Sea Surface Temperature

The East Asian summer monsoon (EASM) underwent an interdecadal variation with interannual variations during the period from 1958 to 1997, its index tended to decline from a higher stage in the mid-1960,s until it reached a lower stage after 1980/s. Correlation analysis reveals that EASM is closely related with the global atmospheric circulation and sea surface temperature (SST). The differences between the weak and strong stage of EASM shows that, the summer monsoon circulation over East Asia and North Africa is sharply weakened, in the meantime, the westerlies in high latitudes and the trade-wind over the tropical ocean are also changed significantly. Over the most regions south of the northern subtropics, both air temperature in the lower troposphere and SST tended to rise compared with the strong stage of EASM. It is also revealed that the ocean-atmosphere interaction over the western Pacific and Indian Ocean plays a key role in interannual to interdecadal variation of EASM, most probably, the subtropical indian Ocean is more important. On the other hand, the ENSO event is less related to EASM at least during the concerned period.

Spatial and temporal variation of global LAI during 1981-2006

Earth is always changing. Knowledge about where changes happened is the first step for us to understand how these changes affect our lives. In this paper, we use a long-term leaf area index data （LAI） to identify where changes happened and where has experienced the strongest change around the globe during 1981-2006. Results show that, over the past 26 years, LAI has generally increased at a rate of 0.0013 per year around the globe. The strongest increasing trend is around 0.0032 per year in the middle and northern high latitudes （north of 30°N）. LAI has prominently increased in Europe, Siberia, Indian Peninsula, America and south Canada, South region of Sahara, southwest corner of Australia and Kgalagadi Basin; while noticeably decreased in Southeast Asia, southeastern China, central Africa, central and southern South America and arctic areas in North America.

Global and Hemispherical Interannual Variation of Total Column Ozone from TOMS and OMI Data

Daily Total Column Ozone (TCO) measurements compiled from Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instruments (OMI) were used to analyze the global and hemispherical TCO interannual variations. Two periods of TCO measurements were analyzed separately covering full years. For the 1978-1994 period, the TCO showed a global decade decrease rate of 13.45 DU (about -4.3%). For the Northern Hemisphere(NH) the decade decrease rate was of 12.96 DU (-4.0%), while in the Southern Hemisphere (SH) was of 13.57 DU (-4.5%). These decreases in ozone trends, using the totality of TOMS and OMI satellite measurements, are greater than those reported in literature. The 1998-2014 period global TCO decade decrease rate was of 1.56 DU, corresponding 0.94 DU and 0.138 DU for the NH and SH, respectively. The global TCO variations must show a double annual periodicity, the first one with maxima in March due to the Northern Hemisphere (NH) and the second one during September due to the Southern Hemisphere (SH). However, the maxima due to SH TCO interannual variations have gradually vanished. A disturbance in the SH TCO interannual variations has appeared since 1980;graphically the periodicity brakes down and transforms to a double peak from 1985 and on. This effect can be attributed to the hemispheric impact of the ozone hole at the South Pole. Between October 1, 2004 and December 14, 2005 TOMS and OMI have recorded this disturbance unequivocally. We conclude that the disturbance in SH TCO has an irreversible character.

GNSS spoofing detection for single antenna receivers via CNR variation monitoring

In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in the signals across different incident directions,resulting in distinct CNR variations for each signal.A model is developed to calculate the variation value of the signal CNR based on the antenna gain pattern.This model enables the differentiation of the variation values of the CNR for authentic satellite signals and spoofing signals,thereby facilitating spoofing detection.The proposed method is capable of detecting spoofing signals with power and CNR similar to those of authentic satellite signals.The accuracy of the signal CNR variation value calculation model and the effectiveness of the spoofing detection method are verified through a series of experiments.In addition,the proposed spoofing detection method works not only for a single spoofing source but also for distributed spoofing sources.

Discovery of an abnormally high-δ^(34)S barite deposit and a new understanding of global sulfur isotope variation during geological history

The evolution of the global sulfur isotope curve was plotted based on the δ34S values of evaporates resultant from oceanic evaporation. In the long period of geological history the δ34S values showed obvious peaks for three times during the process of ancient oceans' sulfur isotope evolution, namely the Early Cambrian (+30‰), the Late Devonian (+25‰) and the Permian-Triassic transition interval (+17‰), but the causes of the abnormal rise of sulfur isotopic values during the geological period are still in question. In this paper, 18 samples collected from a large Devonian barite deposit from Zhenning County were analyzed to determine their δ34S values, revealing that the 18 samples have very high δ34S values (δ34S=41.88‰-+68.39‰), with an average close to 56.30‰, which are higher than the isotopic values of contemporary sulfates (+17‰- +25‰). A comparative analysis was conducted of the emerging of high δ34S barite deposits (from Cambrian and Devonian) and the δ34S variation curves of the ancient oceans. The results indicate that the time when the obvious peaks of δ34S values appeared and the time of massive sedimentation of high δ34S barite deposits are very close to each other, which, in our opinion, is not a coincidence. There may exist some correlations between the sulfur isotope evolution of ancient oceans during the diverse periods of geological history and the massive sedimentation of high δ34S barite deposits. Therefore, it is inferred that perhaps it was the massive sedimentation of high δ34S barites that caused the sharp rise of δ34S values in a short period of time.

Managing Variation and Resolving the Trade-off Implications of Global Supply

The reduction of wasteful variation within the supp ly chain is naturally suited to high and stable volumes, as epitomised in the lean practices of the automotive industry. However, with the growth of innovative pr oducts, typically characterised by lower volumes and uncertain demand, it is als o important to develop strategies to effectively manage the externally imposed v ariation resulting from volatile market demand. Such strategies often come under the banner of quick response or agile supply. System variation is the common denominator, for whereas lean strategies emphasis e the need for stability and the reduction of wasteful supply chain variation, a gile emphasises the need to respond to externally imposed demand variation. Simi larly, lean supply is closely associated with level scheduling and investing in inventory to decouple demand variation from the supply chain, whereas, agile sup ply is associated with investing in responsive capacity as inventory requirement s cannot be effectively predicted. This distinction between lean and agile supply, highlights a trade-off between investing in responsive capacity and decoupling inventory, which is closely related to the conflicting manufacturing tasks of fast response and low cost. The implications of this conflict have been more widely felt in recent years, as companies have opted to outsource manufacture to low cost overseas suppliers. T he rationale is to reduce manufacturing costs, but the trade-off is a dramatic loss of responsive capacity with higher dependency on decoupling inventory. As with lean and agile supply, the trade-off implications of such choices need to be acknowledged, conceptually understood and then separate out or otherwise r esolved. This paper introduces the business need before exploring the significance of var iation and the concept of managing variation in a delivery system using responsi ve capacity and decoupling inventory. These concepts will then be used to unpack the lean and agile paradigms before applying the thinking to a more detailed in dustrial case concerning offshore supply decisions. The paper concludes with som e reflections.

A VARIATIONAL IMAGE SMOOTHING MODEL WITH GLOBAL CONVERGENCE

A new smoothing method is proposed. The smoothing process adapts to image characteristics and is good at preserving local image structures. More importantly, in the theory under the conditions weaker than those in the original Kaanov method an approximal sequence of solutions to the variational problems can be constructed and the global convergence can be proved. And the conditions in the papers of Schno¨rr(1994) and Heers, et al (2001) are discussed. Numerical solutions of the model are given.

CO_2 seasonal variation and global change: Test global warming from another point of view

CO2 and temperature records at Mauna Loa, Hawaii, and other observation stations show that the correlation between CO2 and temperature is not significant. These stations are located away from big cities, and in various latitudes and hemi-spheres. But the correlation is significant in global mean data. Over the last five decades, CO2 has grown at an accelerating rate with no corresponding rise in temperature in the stations. This discrepancy indicates that CO2 probably is not the driving force of temperature change globally but only locally （mainly in big cities）. We suggest that the Earth＇s atmospheric concentration of CO2 is too low to drive global temperature change. Our empirical perception of the global warming record is due to the urban heat island effect： temperature rises in areas with rising population density and rising industrial activity. This effect mainly occurs in the areas with high population and intense human activities, and is not representative of global warming. Regions far from cities, such as the Mauna Loa highland, show no evident warming trend. The global monthly mean temperature calculated by record data, widely used by academic researchers, shows R2=0.765, a high degree of correlation with CO2 . However, the R2 shows much less significance （mean R2=0.024） if calculated by each record for 188 selected stations over the world. This test suggests that the inflated high correlation between CO2 and temperature （mean R2=0.765-0.024=0.741） used in reports from the Intergovernmental Panel on Climate Change （IPCC） was very likely produced during data correction and processing. This untrue global monthly mean temperature has created a picture： human emission drives global warming.

MERIT FUNCTION AND GLOBAL ALGORITHMFOR BOX CONSTRAINED VARIATIONALINEQUALITIES

The authors consider optimization methods for box constrained variational inequalities. First, the authors study the KKT-conditions problem based on the original problem. A merit function for the KKT-conditions problem is proposed, and some desirable properties of the merit function are obtained. Through the merit function, the original problem is reformulated as minimization with simple constraints. Then, the authors show that any stationary point of the optimization problem is a solution of the original problem. Finally, a descent algorithm is presented for the optimization problem, and global convergence is shown.

Annual variation rate of global sea－level rise and the prediction for the 21st century

An analytics method of predicting the annual variation rate (AVR) of global sea-level (GSL) is developed.Through the calculation by using the mean sea-level data collected from the tidal gauge stations over the world, a GSL rise of 0. 15～0. 16 cm/a is obtained. The predicted values of AVR of GSL for the 21st century are presented. The authors' results have been compared to those reported by other scientists at home and abroad. The method proposedhere is more convenient and precise.

NEW SIMPLE SMOOTH MERIT FUNCTION FOR BOX CONSTRAINED VARIATIONAL INEQUALITIES AND DAMPED NEWTON TYPE METHOD

By introducing a smooth merit function for the median function, a new smooth merit function for box constrained variational inequalities (BVIs) was constructed. The function is simple and has some good differential properties. A damped Newton type method was presented based on it.Global and local superlinear/quadratic convergence results were obtained under mild conditions, and the finite termination property was also shown for the linear BVIs. Numerical results suggest that the method is efficient and promising.

Spatial-temporal dynamics of desert vegetation and its responses to climatic variations over the last three decades:a case study of Hexi region in Northwest China

Analysis of spatial-temporal variations of desert vegetation under the background of climate changes can provide references for ecological restoration in arid and semi-arid areas. In this study, we used the Global Inventory Modeling and Mapping Studies （GIMMS） NDVI data from 1982 to 2006 and Moderate Resolution Imaging Spectroradiometer （MODIS） NDVI data from 2000 to 2013 to reveal the dynamics of desert vegetation in Hexi region of Northwest China over the past three decades. We also used the annual temperature and precipitation data acquired from the Chinese meteorological stations to analyze the response of desert vegetation to climatic variations. The average value of NDVImax （the maximum NDVI during the growing season） for desert vegetation in Hexi region increased at the rate of 0.65x10-3/a （P〈0.05） from 1982 to 2013, and the significant increases of NDVImax mainly appeared in the typical desert vegetation areas. Vegetation was significantly improved in the lower reaches of Shule and Shiyang river basins, and the weighted mean center of desert vegetation mainly shifted toward the lower reaches of the two basins. Almost 95.32% of the total desert vegetation area showed positive correlation between NDVImax and annual precipitation, indicating that precipitation is the key factor for desert vegetation growth in the entire study area. Moreover, the areas with non-significant positive correlation between NDVImax and annual precipitation mainly located in the lower reaches of Shiyang and Shule river basins, this may be due to human activities. Only 7.64% of the desert vegetation showed significant positive correlation between NDVImax and annual precipitation in the Shule River Basin （an extremely arid area）, indicating that precipitation is not the most important factor for vegetation growth in this basin, and further studies are needed to investigate the mechanism for this phenomenon.

Temperature and Precipitation Variations at Two Meteorological Stations on Eastern Slope of Gongga Mountain,SW China in the Past Two Decades

Gongga Mountain, locates on the eastern edge of Tibetan Plateau of China, is the highest mountain in China except summits in Tibet. Only limited meteorological data on Gongga Mountain have been published so far. Here we present the meteorological records from two stations, Moxi Station （at 1,621.7 m above sea level （a.s.1.）, 1992- 2010） and Hailuogou Station （at 2,947.8 m a.s.l., 1988-2010）, on the eastern slope of Gongga Mountain. In the past two decades, the annual precipitation decreased while the annual mean temperature increased at Hailuogou Station. Both precipitation and temperature increased at Moxi Station. The precipitation variation on the eastern slope of Gongga Mountain is influenced by both East Asian Monsoon and Indian Monsoon, so that the precipitation concentrated between May and October. The temperature variation on the eastern slope of Gongga Mountain in the past two decades showed similar trends as that of the northern hemispheric and global. In the past two decades, the temperature increased o.35℃ and o.3℃/decade at Hailuogou Station and Moxi Station respectively, which was higher than the increase extents of northern hemispheric and global temperature. The most intense warming occurred at the first decade of 21St century. The winter temperature increased more at Hailuogou Station than at Moxi Station. A remarkable increase of temperature in March was observed with only a little precipitation at both high and low altitude stations.

NEW SIMPLE SMOOTH MERIT FUNCTION FOR BOX CONSTRAINED VARIATIONAL INEQUALITIES AND DAMPED NEWTON TYPE METHOD

By introducing a smooth merit function for the median function, a new smooth merit function for box constrained variational inequalities （BVIs） was constructed. The function is simple and has some good differential properties. A damped Newton type method was presented based on it. Global and local superlinear/ quadratic convergence results were obtained under mild conditions, and the finite termination property was also shown for the linear BVIs. Numerical results suggest that the method is efficient and promising.

Spatio-temporal Variation of Soil Respiration and Its Driving Factors in Semi-arid Regions of North China

Soil respiration （SR） is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate estimation of CO2 emissions via SR. However, studies on spatio-temporal variation of SR are still scarce for semi-arid regions of North China. In this study, we conducted 12-month SR measurements in six land-use types, including two secondary forests （Populus tomentosa （PT） and Robinia pseudoacacia （RP））, three artificial plantations （Armeniaca sibirica （AS）, Punica granatum （PG） and Ziziphusjujuba （Z J）） and one natural grassland （GR）, to quantify spatio-temporal variation of SR and distinguish its controlling factors. Results indicated that SR exhibited distinct sea- sonal patterns for the six sites. Soil respiration peaked in August 2012 and bottomed in April 2013. The temporal coefficient of variation （CI0 of SR for the six sites ranged from 76.98% to 94.08%, while the spatial CV of SR ranged from 20.28% to 72.97% across the 12-month measurement. Soil temperature and soil moisture were the major controlling factors of temporal variation of SR in the six sites, while spatial variation in SR was mainly caused by the differences in soil total nitrogen （STN）, soil organic carbon （SOC）, net photosynthesis rate, and fine root biomass. Our results show that the annual average SR and Q10 （temperature sensitivity of soil respira- tion） values tended to decrease from secondary forests and grassland to plantations, indicating that the conversion of natural ecosystems to man-made ecosystems may reduce CO2 emissions and SR temperature sensitivity. Due to the high spatio-temporal variation of SR in our study area, care should be taken when converting secondary forests and grassland to plantations from the point view of accurately quantifying C02 emissions via SR at regional scales.

A Smoothing Newton Method for the Box Constrained Variational Inequality Problems

The box constrained variational inequality problem can be reformulated as a nonsmooth equation by using median operator.In this paper,we present a smoothing Newton method for solving the box constrained variational inequality problem based on a new smoothing approximation function.The proposed algorithm is proved to be well defined and convergent globally under weaker conditions.

Effect of Aspect on Climate Variation in Mountain Ranges of Shennongjia Massif, Central China

The aim of this study was to better understand the mechanisms of regional climate variation in mountain ranges with contrasting aspects as mediated by changes in global climate. It may help predict trends of vegetation variations in native ecosystems in natural reserves. As measures of climate response, temperature and precipitation data from the north, east, and south-facing mountain ranges of Shennongjia Massif in the coldest and hottest months(January and July), different seasons(spring, summer, autumn, and winter) and each year were analyzed from a long-term dataset(1960 to 2003) to tested variations characteristics, temporal and spatial quantitative relationships of climates. The results showed that the average seasonal temperatures and precipitation in the north, east, and south aspects of the mountain ranges changed at different rates. The average seasonal temperatures change rate ranges in the north, east, and south-facing mountain ranges were from –0.0210℃/yr to 0.0143℃/yr, –0.0166℃/yr to 0.0311℃/yr, and –0.0290 ℃/yr to 0.0084℃/yr, respectively, and seasonal precipitation variation magnitude were from –1.4940 mm/yr to 0.6217 mm/yr, –1.6833 mm/yr to 2.6182 mm/yr, and –0.8567 mm/yr to 1.4077 mm/yr, respectively. The climates variation trend among the three mountain ranges were different in magnitude and direction, showing a complicated change of the climates in mountain ranges and some inconsistency with general trends in global climate change. The climate variations were significantly different and positively correlated cross mountain ranges, revealing that aspects significantly affected on climate variations and these variations resulted from a larger air circulation system, which were sensitive to global climate change. We conclude that location and terrain of aspect are the main factors affecting differences in climate variation among the mountain ranges with contrasting aspects.

Removal of Ocular Artifacts from Electroencephalo-Graph by Improving Variational Mode Decomposition

Ocular artifacts in Electroencephalography(EEG)recordings lead to inaccurate results in signal analysis and process.Variational Mode Decomposition(VMD)is an adaptive and completely nonrecursive signal processing method.There are two parameters in VMD that have a great influence on the result of signal decomposition.Thus,this paper studies a signal decomposition by improving VMD based on squirrel search algorithm(SSA).It’s improved with abilities of global optimal guidance and opposition based learning.The original seasonal monitoring condition in SSA is modified.The feedback of whether the optimal solution is successfully updated is used to establish new seasonal monitoring conditions.Opposition-based learning is introduced to reposition the position of the population in this stage.It is applied to optimize the important parameters of VMD.GOSSA-VMD model is established to remove ocular artifacts from EEG recording.We have verified the effectiveness of our proposal in a public dataset compared with other methods.The proposed method improves the SNR of the dataset from-2.03 to 2.30.

Study of Initial Vorticity Forcing for Block Onset by a 4-Dimensional Variational Approach

With the aid of a global barotropic model, the role of the interaction of the synoptic-scale disturbance and the planetary flow in block onset is examined by a 4-dimensional variational approach. A cost function is defined to measure the squared errors of the forecasted stream functions during block onset period (day 4 and day 5 in this study) over a selected blocking domain. The sensitivity of block onset with respect to the initial synoptic-scale disturbance is studied by examining the gradient of the defined cost function with respect to the initial (during the first 24 hours) vorticity forcing, which is evaluated by the adjoint integration. Furthermore, the calculated cost function and gradient are connected with the limited-memory quasi-Newton optimization algorithm for solving the optimal initial vorticity forcing for block onset. For two studied cases of block onset (northern Atlantic and northern Pacific) introducing the optimal initial vorticity forcing, the nonlinear barotropic advection process mostly reconstructs these blocking onset processes. The results show that the formation of blocking can be correctly described by a barotropic nonlinear advection process, in which the wave- (synoptic-scale) flow (planetary-scale) interaction plays a very important role. On an appropriate planetary-scale flow, a certain synoptic-scale disturbance can cause the blocking onset by the interaction between the synoptic scale perturbations and the planetary scale basic flows. The extended forecasts show that the introduction of the optimal initial vorticity forcing can predict the blocking process up to the 7th or 8th day in this simple model case. The experimental results in this study show that the 4-dimensional variational approach has a good potential to be applied to study the dynamics of the medium-range weather processes. This simple model case study is only an initial trial. Applying the framework in this study to a complex model will further our understanding of the mechanism of the atmospheric/oceanic processes and improve their prediction.