Declined trends of chlorophyll a in the South China Sea over 2005–2019 from remote sensing reconstruction

Chlorophyll a concentration(CHL)is an important proxy of the marine ecological environment and phytoplankton production.Long-term trends in CHL of the South China Sea(SCS)reflect the changes in the ecosystem’s productivity and functionality in the regional carbon cycle.In this study,we applied a previously reconstructed 15-a(2005–2019)CHL product,which has a complete coverage at 4 km and daily resolutions,to analyze the long-term trends of CHL in the SCS.Quantile regression was used to elaborate on the long-term trends of high,median,and low CHL values,as an extended method of conventional linear regression.The results showed downward trends of the SCS CHL for the 75th,50th,and 25th quantile in the past 15 a,which were−0.0040 mg/(m^(3)·a)(−1.62%per year),−0.0023 mg/(m^(3)·a)(−1.10%per year),and−0.0019 mg/(m^(3)·a)(−1.01%per year).The negative trends in winter(November to March)were more prominent than those in summer(May to September).In terms of spatial distribution,the downward trend was more significant in regions with higher CHL.These led to a reduced standard deviation of CHL over time and space.We further explored the influence of various dynamic factors on CHL trends for the entire SCS and two typical systems(winter Luzon Strait(LZ)and summer Vietnam Upwelling System(SV))with single-variate linear regression and multivariate Random Forest analysis.The multivariate analysis suggested the CHL trend pattern can be best explained by the trends of wind speed and mixed-layer depth.The divergent importance of controlling factors for LZ and SV can explain the different CHL trends for the two systems.This study expanded our understanding of the long-term changes of CHL in the SCS and provided a reference for investigating changes in the marine ecosystem.

Decadal variation and trend of the upper layer salinity in the South China Sea from 1960 to 2010

Ocean salinity is an essential measurable indicator of water cycle and plays a crucial role in regulating ocean and climate change.Using Simple Ocean Data Assimilation(SODA)reanalysis product,substantial decadal variability of the salinity in the upper layer of the South China Sea(SCS)from 1960 to 2010 was examined.Results show that a decadal variation of the upper layer salinity is clear.The upper layer(100 m)waters are found to freshen from 1960,become saltier during 1975 to 1995,and freshen again from 1995 to 2010.The strongest anomalies appear in the northeastern,northern,and northwestern regions in the three periods,respectively.The salinity variation trends become weaker below the upper layer,except the salinifi cation trend in the northern SCS extends to at least 300 m during the salinifi cation period.Diagnosis of the salinity budget over the top 100 m shows that during the fi rst freshening period horizontal advection,vertical advection,and surface freshwater forcing all contribute to salinity freshening,and horizontal advection is relatively larger.The contribution of horizontal advection and surface freshwater forcing to the positive salinity anomaly is comparable,while the vertical advection is the secondary factor in the salinifi cation period.Horizontal advection,especially zonal advection,plays a crucial role during the second freshening period.Moreover,horizontal advection is more important than that in the fi rst freshening period.In addition,the contribution of horizontal advection is mainly in zonal direction controlled by Kuroshio intrusion.Further analysis shows the upper-layer salinity variations have a Pacifi c Decadal Oscillation(PDO)-like signal,with freshening during the negative PDO years,and salinifi cation during the positive PDO years.PDO mainly infl uences the upper-layer salinity changes through both atmospheric bridge and oceanic bridge.

Trends of sea surface temperature and sea surface temperature fronts in the South China Sea during 2003–2017

The trends of the sea surface temperature(SST) and SST fronts in the South China Sea(SCS) are analyzed during2003–2017 using high-resolution satellite data. The linear trend of the basin averaged SST is 0.31°C per decade,with the strongest warming identified in southeastern Vietnam. Although the rate of warming is comparable in summer and winter for the entire basin, the corresponding spatial patterns of the linear trend are substantially different between them. The SST trend to the west of the Luzon Strait is characterized by rapid warming in summer, exceeding approximately 0.6°C per decade, but the trend is insignificant in winter. The strongest warming trend occurs in the southeast of Vietnam in winter, with much less pronounced warming in summer. A positive trend of SST fronts is identified for the coast of China and is associated with increasing wind stress. The increasing trend of SST fronts is also found in the east of Vietnam. Large-scale circulation, such as El Ni?o, can influence the trends of the SST and SST fronts. A significant correlation is found between the SST anomaly and Ni?o3.4 index, and the ENSO signal leads by eight months. The basin averaged SST linear trends increase after the El Ni?o event(2009–2010), which is, at least, due to the rapid warming rate causing by the enhanced northeasterly wind. Peaks of positive anomalous SST and negatively anomalous SST fronts are found to co-occur with the strong El Ni?o events.

A shift in the upper-ocean temperature trends in the South China Sea since the late 1990s

In this paper, the interdecadal variability of upper-ocean temperature in the South China Sea（SCS） is investigated based on several objectively analyzed data sets and two reanalysis data sets. The trends of the SCS sea surface temperature（SST） have changed from warming to cooling since the late 1990 s. A heat budget analysis suggests that the warming of the surface mixed layer during 1984-1999 is primarily attributed to the horizontal heat advection and the decrease of upward long wave radiation, with the net surface heat flux playing a damping role due to the increase of upward latent and sensible heat fluxes. On the other hand, the cooling of the surface mixed layer during 2000-2009 is broadly controlled by net surface heat flux, with the radiation flux playing the dominant role. A possible mechanism is explored that the variation of a sea level pressure（SLP） over the North Pacific Ocean may change the prevailing winds over the SCS, which contributes to the change of the SST in the SCS through the horizontal heat advection and heat fluxes.

Homogeneity and Trend Analysis of Hydrometeorological Data of the Eastern Black Sea Region, Turkey

Eastern Black Sea Region in northeastern part of Turkey has the highest precipitation total in the country, approaching 2500 mm per a year. It is therefore an important region as it frequently encounters with flash floods due to heavy rains. For future planning of water resources, environment and urbanization, it is important to know the expected behavior of hydrometeorological processes, mainly precipitation and flow. Due to these facts, in this study, homogeneity of long-term annual precipitation and streamflow series of the Eastern Black Sea Region, Turkey is checked using double mass curve method and trends are determined by means of the Mann-Kendall test. The data network consists of 38 precipitation gauging stations and 40 flow gauging stations across the Eastern Black Sea Region. It is found that 27 precipitation stations out of 38 are homogeneous and no trend is available. Out of the remaining stations, nine are found non-homogeneous and four with trend. For annual flow data, it is found that 22 stations out of 40 are homogeneous and no trend is available. The remaining 18 stations are found non-homogeneous, among which 5 stations have trend at the same time.

Global Distribution of Thermosteric Contribution to Sea Level Rising Trend

The sea level derived from TOPEX/Poseidon （T/P） altimetry data shows prominent long term trend and inter-annual variability. The global mean sea level rising rate during 1993-2003 was 2.9mm a^-1. The T/P sea level trend maps the geographical variability. In the Northern Hemisphere （15°-64°N）, the sea level rise is very fast at the mid-latitude （20°-40°N） but much slower at the high-latitude, for example, only 0.5 mm a^-1 in the latitude band 40°-50°N. In the Southern Hemisphere, the sea level shows high rising rate both in mid-latitude and high-latitude areas, for example, 5.1 mm a^-1 in the band 40°- 50°S. The global thermosteric sea level （TSL） derived from Ishii temperature data was rising during 1993-2003 at a rate of 1.2 mm a^-1 and accounted for more than 40% of the global T/P sea level rise. The contributions of the TSL distribution are not spatially uniform; for instance, the percentage is 67% for the Northern Hemisphere and only 29% for the Southern Hemisphere （15°-64°S） and the maximum thermosteric contribution appears in the Pacific Ocean, which contributes more than 60% of the global TSL. The sea level change trend in tropical ocean is mainly caused by the thermosteric effect, which is different from the case of seasonal variability in this area. The TSL variability dominates the T/P sea level rise in the North Atlantic, but it is small in other areas, and shows negative trend at the high-latitude area （40°-60°N, and 50°-60°S）. The global TSL during 1945-2003 showed obvious rising trend with the rate of about 0.3 mm a-l and striking inter-annual and decadal variability with period of 20 years. In the past 60 years, the Atlantic TSL was rising continuously and remarkably, contributing 38% to the global TSL rising. The TSL in the Pacific and Indian Ocean rose with significant in- ter-annual and decadal variability. The first EOF mode of the global TSL from Ishii temperature data was the ENSO mode in which the time series of the first mode showed steady rising trend. Among the three oceans, the first mode of the Pacific TSL presented the ENSO mode; there was relatively steady rising trend in the Atlantic Ocean, and no dominant mode in the Indian Ocean.

Estimating trends of the Mediterranean Sea level changes from tide gauge and satellite altimetry data (1993-2015)

The impact of climate change on sea level has received a great deal of attention by scientists worldwide. In this context, the problem of sea levels on global and regional scales have been analyzed in a number of studies based on tide gauges observations and satellite altimetry measurements. This study focuses on trend estimates from 18 high-quality tide gauge stations along the Mediterranean Sea coast. The seasonal Mann-Kendall test was run at a 5% significance level for each of the 18 stations for the period of 1993-2015 (satellite altimetry era). The results of this test indicate that the trends for 17 stations were statistically significant and showed an increase (no significant trend was observed only at one station). The rates of sea level change for the 17 stations that exhibit significant trends, estimated using seasonal Sen's approach, range after correction for Vertical Land Motion (VLM) from 1.48 to 8.72 mm/a for the period 1993-2015. Furthermore, the magnitude of change at the location of each tide gauge station was estimated using the satellite altimetry measurements. Thus, the results obtained agree with those from the tide-gauge data analysis.

Trend analysis of relative sea level rise or fall of the tide gauge stations in the Pacific

On the basis of the analytical results of the period components of monthly mean sea level of 236 stationsin the Pacific, the period components plus linear trend are ed to fit the monthly mean sea level series. The statisticalresults of linear trend Coefficients of these stations indicate that, if the abnormal values of sea-level rise and fall are neglected, the average rise rate of relative sea level in the Pacific is 1. 16 mm/a. Affected by nonuniformity Of land subsidence and other factors, the regional change of relative sea level rise or fall in the Pacific is greater. In the light of thepositive or negative values of linear trend coefficients as well as the geographical position of the sea area, zoning is madeof the sea level rise or fall in the Pacific including the coastal areas of China and Southeast Asia to obtain the averagerate of rise or fall in each sea area. The rise or fall trends of relative sea level obtained for the entire Pacific Ocean,west coast of North America, the northern and central South America, the greater part of the tropical Pacific and thecoastal Islands of Japan are basically in keeping with the other relevant results. The regional average estimated result ofthe relative sea level in the coast of East Asia is on the rise while the estimated results provided by Barnett tend todrop; the main cause of this nonuniformity is the number of stations selected and the distributional density.

Long-term trend analysis of wave characteristics in the Bohai Sea based on interpolated ERA5 wave reanalysis from 1950 to 2020

Reasonably understanding of the long-term wave characteristics is very crucial for the ocean engineering.A feedforward neural network is operated for interpolating ERA5 wave reanalysis in this study,which embodies a detailed record from 1950 onwards.The spatiotemporal variability of wave parameters in the Bohai Sea,especially the significant wave height(SWH),is presented in terms of combined wave,wind wave and swell by employing the 71 years(1950–2020)of interpolated ERA5 reanalysis.Annual mean SWH decreases at−0.12 cm/a estimated by Theil-Sen estimator and 95th percentile SWH reflecting serve sea states decreases at−0.20 cm/a.Inter-seasonal analysis shows SWH of wind wave has steeper decreasing trend with higher slopes than that of swell,especially in summer and winter,showing the major decrease may attribute to the weakening of monsoon.The inner Bohai Sea reveals a general decreasing trend while the intersection connecting with the Yellow Sea has the lower significance derived by Mann-Kendall test.Meanwhile,95th percentile SWH decreases at a higher rate while with a lower significance in comparison with the mean state.The frequencies of mean wave directions in sub-sector are statistically calculated to find the seasonal prevailing directions.Generally,the dominant directions in summer and winter are south and north.A similar variation concerning to SWH,the trend of the mean wave period is provided,which also shows a decrease for decades.

Upper-ocean temperature trends in the Eastern China Seas during 1976–1996

Temperature in the Eastern China Seas(ECS), including the Bohai, Yellow, and East China seas, is crucially important with regard to weather forecasting and fishery activities of adjacent countries. Although sea surface temperature(SST) in the ECS has demonstrated a dramatically accelerated trend of warming after a regime shift(1976–1996), trends beneath the surface remain poorly understood because of the sparsity of observations. This study used in situ hydrographic data from 1976 to 1996 to examine upperocean temperature trends in the ECS. It was found that the multilevel trends show consistency with that of the surface water; i.e., warming is faster in winter than summer. However, the magnitudes of the trends weaken with increasing depth. Furthermore, the seasonal dif ference in the upper ocean is mainly associated with the warm currents in the ECS, which implies an essential contribution from horizontal advection. These phenomena could also be detected from data acquired from the routinely observed PN and 34°N sections. The spatiotemporal patterns of temperature trends in the upper ECS extend our understanding beyond the SST, especially highlighting the role of ocean dynamics in forming temperature patterns beneath the surface in comparison with atmospheric ef fects.

Correlation analysis between the Aral Sea shrinkage and the Amu Darya River

The shrinkage of the Aral Sea,which is closely related to the Amu Darya River,strongly affects the sustainability of the local natural ecosystem,agricultural production,and human well-being.In this study,we used the Bayesian Estimator of Abrupt change,Seasonal change,and Trend(BEAST)model to detect the historical change points in the variation of the Aral Sea and the Amu Darya River and analyse the causes of the Aral Sea shrinkage during the 1950–2016 period.Further,we applied multifractal detrend cross-correlation analysis(MF-DCCA)and quantitative analysis to investigate the responses of the Aral Sea to the runoff in the Amu Darya River,which is the main source of recharge to the Aral Sea.Our results showed that two significant trend change points in the water volume change of the Aral Sea occurred,in 1961 and 1974.Before 1961,the water volume in the Aral Sea was stable,after which it began to shrink,with a shrinkage rate fluctuating around 15.21 km3/a.After 1974,the water volume of the Aral Sea decreased substantially at a rate of up to 48.97 km3/a,which was the highest value recorded in this study.In addition,although the response of the Aral Sea's water volume to its recharge runoff demonstrated a complex non-linear relationship,the replenishment of the Aral Sea by the runoff in the lower reaches of the Amu Darya River was identified as the dominant factor affecting the Aral Sea shrinkage.Based on the scenario analyses,we concluded that it is possible to slow down the retreat of the Aral Sea and restore its ecosystem by increasing the efficiency of agricultural water use,decreasing agricultural water use in the middle and lower reaches,reducing ineffective evaporation from reservoirs and wetlands,and increasing the water coming from the lower reaches of the Amu Darya River to the 1961–1973 level.These measures would maintain and stabilise the water area and water volume of the Aral Sea in a state of ecological restoration.Therefore,this study focuses on how human consumption of recharge runoff affects the Aral Sea and provides scientific perspective on its ecological conservation and sustainable development.

Analysis on Long-Term Change of Sea Surface Temperature in the China Seas

Long-term change of sea surface temperature （SST） in the China Seas from 1900 to 2006 is examined based on two different observation datasets （HadlSSTI and HadSST3）. Similar to the Atlantic, SST in the China Seas has been well observed during the past 107 years. A comparison between the reconstructed （HadISSTI） and un-interpolated （HadSST3） datasets shows that the SST wanning trends from both datasets are consistent with each other in most of the China Seas. The warming trends are stronger in winter than in summer, with a maximum rate of SST increase exceeding 2.7℃ （100year）-I in the East China Sea and the Taiwan Strait during winter based on HadISSTI. However, the SST from both datasets experienced a sudden decrease after 1999 in the China Seas. The estimated trend from HadlSSTI is stronger than that fi＇om HadSST3 in the East China Sea and the east of Taiwan Island, where the difference in the linear SST warming trends are as large as about 1℃ （100year）-I when using respectively HadISST1 and HadSST3 datasets. When compared to the linear winter warnling trend of the land surface air temperature （1.6℃ （100 year）-1）, HadSST3 shows a more reasonable trend of less than 2.1℃（ 100 year）-1 than HadISST 1 ＇s trend of larger than 2.7℃ （ 100 year）-1 at the mouth of the Yangtze River. The restllts also indicate large uncertainties in the estimate of SST warming patterns.

Evaluation on monthly sea surface wind speed of four reanalysis data sets over the China seas after 1988

This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set(CCMP), NCEP climate forecast system reanalysis data set(CFSR),ERA-interim reanalysis data set(ERA-int) and Japanese 55-year reanalysis data set(JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the longterm and homogeneous observation wind speeds data recorded at ten stations. The results reveal that(1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively.The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s,respectively;(2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea;(3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.

Modeling of Arctic Sea Ice Variability During 1948–2009: Validation of Two Versions of the Los Alamos Sea Ice Model(CICE)

The Los Alamos sea ice model(CICE) is used to simulate the Arctic sea ice variability from 1948 to 2009. Two versions of CICE are validated through comparison with Hadley Centre Global Sea Ice and Sea Surface Temperature(Had ISST) observations. Version 5.0 of CICE with elastic-viscous-plastic(EVP) dynamics simulates a September Arctic sea ice concentration(SASIC) trend of –0.619 × 1012 m2 per decade from 1969 to 2009, which is very close to the observed trend(-0.585 × 1012 m2 per decade). Version 4.0 of CICE with EVP dynamics underestimates the SASIC trend(-0.470 × 1012 m2 per decade). Version 5.0 has a higher correlation(0.742) with observation than version 4.0(0.653). Both versions of CICE simulate the seasonal cycle of the Arctic sea ice, but version 5.0 outperforms version 4.0 in both phase and amplitude. The timing of the minimum and maximum sea ice coverage occurs a little earlier(phase advancing) in both versions. Simulations also show that the September Arctic sea ice volume(SASIV) has a faster decreasing trend than SASIC.

Interannual salinity variability of the Northern Yellow Sea Cold Water Mass

This paper discusses the interannual variability of the Northern Yellow Sea Cold Water Mass(NYSCWM) and the factors that influence it,based on survey data from the 1976–2006 national standard section and the Korea Oceanographic Data Center,monthly E-P flux data from the European Centre for Medium-Range Weather Forecasts,and meridional wind speed data from the International Comprehensive Ocean-Atmosphere Data Set. The results show that:1) the mean salinity of the NYSCWM center has a slightly decreasing trend,which is not consistent with the high salinity center; 2) both the southern salinity front and the halocline of the NYSCWM display a weakening trend,which indicates that the difference between the NYSCWM and coastal water decreases; 3) the Yellow Sea Warm Current intrusion,the E-P flux of the northern Yellow Sea,and the strength of the winter monsoon will affect the NYSCWM salinity during the following summer.

A COMPARISON AND EVALUATION OF TWO CENTENNIAL-SCALE SEA SURFACE TEMPERATURE DATASETS IN THE CHINA SEAS AND THEIR ADJACENT SEA AREAS

Two reconstructed sea surface temperature(SST) datasets(HadISST1 and COBE SST2) with centennial-scale are compared on the SST climate change over the China Seas and their adjacent sea areas. Two independent datasets show consistency in statistically significant trends, with a warming trend of 0.07—0.08 ℃ per decade from 1890 to2013. However, in shorter epochs(such as 1961—2013 and 1981—2013), HadISST1 exhibits stronger warming rates than those of COBE SST2. Both datasets experienced a sudden decrease in the global hiatus period(1998—2013), but the cooling rate of HadISST1 is lower than that of COBE SST2. These differences are possibly caused by the different observations sources which are incorporated to fill with data-sparse regions since 1982. Different data sources may lead to higher values in HadISST1 from 1981 to 2013 than that in COBE SST2. Meanwhile, the different data sources and bias adjustment before the World War II may also cause the large divergence between COBE SST2 and HadISST1,leading to lower SST from 1891 to 1930. These findings illustrate that the long-term linear trends are broadly similar in the centennial-scale in the China Seas using different datasets. However, there are large uncertainties in the estimate of warming or cooling tendency in the shorter epochs, because there are different data sources, different bias adjustment and interpolation method in different datasets.

Reduction of global natural gas hydrate(NGH)resource estimation and implications for the NGH development in the South China Sea

There have been at least 29 groups of estimates on the global natural gas hydrate(NGH)resource since1973,varying greatly with up to 10,000 times and showing a decreasing trend with time.For the South China Sea(SCS),35 groups of estimations were conducted on NGH resource potential since 2000,while these estimates kept almost the same with time,varying between 60 and 90 billion tons of oil equivalent(toe).What are the key factors controlling the variation trend?What are the implications of these variations for the NGH development in the world and the SCS?By analyzing the investigation characteristics of NGH resources in the world,this study divided the evaluation process into six stages and confirmed four essential factors for controlling the variations of estimates.Results indicated that the reduction trend reflects an improved understanding of the NGH formation mechanism and advancement in the resource evaluation methods,and promoted more objective evaluation results.Furthermore,the analysis process and improved evaluation method was applied to evaluate the NGH resources in the SCS,showing the similar decreasing trend of NGH resources with time.By utilizing the decreasing trend model,the predicted recoverable resources in the world and the SCS are(205-500)×10^(12)m^(3)and(0.8-6.5)×10^(12)m^(3),respectively,accounting for 20%of the total conventional oil and gas resources.Recoverable NGH resource in the SCS is only about 4%-6%of the previous estimates of 60-90 billion toe.If extracted completely,it only can support the sustainable development of China for 7 years at the current annual consumption level of oil and gas.NGH cannot be the main energy resource in future due to its low resource potential and lack of advantages in recovery.

Winter sea ice albedo variations in the Bohai Sea of China

Sea ice conditions in the Bohai Sea of China are sensitive to large-scale climatic variations. On the basis of CLARA-A1-SAL data, the albedo variations are examined in space and time in the winter（December, January and February） from 1992 to 2008 in the Bohai Sea sea ice region. Time series data of the sea ice concentration（SIC）, the sea ice extent（SIE） and the sea surface temperature（SST） are used to analyze their relationship with the albedo. The sea ice albedo changed in volatility appears along with time, the trend is not obvious and increases very slightly during the study period at a rate of 0.388% per decade over the Bohai Sea sea ice region.The interannual variation is between 9.93% and 14.50%, and the average albedo is 11.79%. The sea ice albedo in years with heavy sea ice coverage, 1999, 2000 and 2005, is significantly higher than that in other years; in years with light sea ice coverage, 1994, 1998, 2001 and 2006, has low values. For the monthly albedo, the increasing trend（at a rate of 0.988% per decade） in December is distinctly higher than that in January and February. The mean albedo in January（12.90%） is also distinctly higher than that in the other two months. The albedo is significantly positively correlated with the SIC and is significantly negatively correlated with the SST（significance level 90%）.

Sea Surface Temperature Extremes of Different Intensity in the China Seas During the Global Warming Acceleration and Hiatus Periods

Based on the daily OISST V2 with 0.25ohorizontal resolutions, the present study looks into the variations of sea surface temperature (SST) extremes in the China Seas for different segments of the period 1982-2013. The two segments include the warming acceleration period from 1982 to 1997 and the hiatus period from 1998 to 2013 when the global mean surface temperature (GMST) did not significantly increase as expected, or even decreased in some areas.First, we construct the regional average time series over the entire China Seas (15°-45°N, 105°-130°E) for these SST extremes. During the hiatus period, the regionally averaged 10th, 1th and 0.1th percentile of SSTs in each year decreased significantly by 0.40℃, 0.56℃ and 0.58℃ per decade, respectively. The regionally averaged 90th, 99th and 99.9th percentile of SSTs in each year decreased slightly or insignificantly. Our work confirm that the regional hiatus was primarily reflected by wintertime cold extremes. Spatially, the trends of cold extremes in different intensity were nonuniformly distributed. Cold extremes in the near-shore areas were much more sensitive to the global warming hiatus. Hot extremes exhibited non-significant trend in the China Seas during the hiatus period. In short, the variations of the SST extremes in the two periods were non-uniform spatially and asymmetric seasonally. It is unexpected that the hot and cold extremes of each year during 1998-2013 were still higher than those extremes during 1982-1997. It is obvious that compared with the warming acceleration period, hot extremes were far more likely to occur in the recent hiatus as a result of a 0.3℃ warmer shift in the mean temperature distribution. Moreover, hot extremes in the China Seas will be sustained or amplified with the end of warming hiatus and the continuous anthropogenic warming.

Research on the spectral analysis and testmethod of period signals in monthly mean sea level

This paper summarizes the general methods,existing problems and their causes of the period analysis for the monthly mean sea level and points out that it is the key to the analysing period signals and forecasting the change trend of the monthly mean sea level that the periods of the signals are selected reasonably. As there are often many period signals in these series, nonlinear effects exist between pairs of period signals. In order to avoid the false periods that may be introduced due to the effects of side lobes and the periods with statistical phase significance coherence that may be introduced due to the effects of nonlinear effects and their restraint to other period signals, the maximum entropy spectral analysis and the corresponding significance period test may be performed repeatedly on the basis of the bispectrum analysis and meanwhile the most significant period component is filtered out by the least square filtering method, i. e., the method of the significance period analysis with mixed spectra modeled by a nonlinear system is adopted and the signal periods approaching the reality are selected one by one. The examples of the bispectrum analysis, the signal period analysis by mixed spectra and the fitting parameters for combined period components with linear trend in the time series of monthly mean sea level are given in this paper.