The Inter-Annual Variability of Rainfall Onset and Its Implication on Crop Planting in Selected East Africa Countries

The inter-annual variability of rainfall onset and crop replanting in East Africa (EA) was assessed using daily estimated rainfall data from climate hazard group infrared precipitation (CHIRPS Ver2.0) and monthly Sea Surface Temperature (SST) indices [Indian Ocean Dipole (IOD) and El-Ni?o Southern Oscillation (ENSO) at NINO3.4 region] from the National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). The data covered a period of 40 years from1981 to 2020. The methods of cumulative of daily mean rainfall, percentage of onset date departure (PODD), Mann-Kendall (MK) trend test, student t-test, and correlation were applied in the analysis. The results showed that early onset with dry spell (WDS) consideration frequently occurs in Uganda between the first and second dekads of September, while late rainfall onset WDS occurs in the first and second dekads of December over central and Northern Kenya as well as in the Northeastern highlands, parts of the northern coast and unimodal regions in Tanzania. Rainfall onset with no dry spell (WnDS) portrayed an average of 10 days before the occurrence of true onset WDS, with maximum onset departure days (ODD) above 30 days across the Rift Valley area in Kenya and the Northeastern highlands in Tanzania. The high chance of minimum ODD is seen over entire Uganda and the area around Lake Victoria. However, few regions, such as Nakuru (Kenya) Gulu and Kibale (Uganda), and Gitega (Burundi), revealed a slight positive linear trend while others showed negative trend. Significant positive patterns for correlation between onset WDS and SST indices (IOD and NINO 3.4) were discovered in Northern and Northeastern Kenya, as well as areas along the Indian Ocean (over Tanzania’s Northern Coast). Inter-annual relationship between onset dates WDS and IOD (NINO3.4) indices exhibits a high correlation coefficient r = 0.23 (r = 0.48) in Uganda and r = 0.44 (r = 0.36) in Kenya. On the other hand, a negative correlation was revealed over Burundi and Tanzania (over a unimodal region). A high percentage of PODD was observed, ranging from 40% to 70% over the Rift Valley in Kenya and at the Northeastern highlands in Tanzania. However, a strong PODD above 70% was observed over Tanga and the Northern Pwani Region in Tanzania. These findings will help farmers to understand the appropriate time for crop planting, as well as help other socio-economic activities that strongly depend on rainfall.

On Multi-Timescale Variability of Temperature in China in Modulated Annual Cycle Reference Frame

The traditional anomaly （TA） reference frame and its corresponding anomaly for a given data span changes with the extension of data length. In this study, the modulated annual cycle （MAC）, instead of the widely used climatological mean annual cycle, is used as an alternative reference frame for computing climate anomalies to study the multi-timescale variability of surface air temperature （SAT） in China based on homogenized daily data from 1952 to 2004. The Ensemble Empirical Mode Decomposition （EEMD） method is used to separate daily SAT into a high frequency component, a MAC component, an interannual component, and a decadal-to-trend component. The results show that the EEMD method can reflect historical events reasonably well, indicating its adaptive and temporally local characteristics. It is shown that MAC is a temporally local reference frame and will not be altered over a particular time span by an exten-sion of data length, thereby making it easier for physical interpretation. In the MAC reference frame, the low frequency component is found more suitable for studying the interannual to longer timescale variability （ILV） than a 13-month window running mean, which does not exclude the annual cycle. It is also better than other traditional versions （annual or summer or winter mean） of ILV, which contains a portion of the annual cycle. The analysis reveals that the variability of the annual cycle could be as large as the magnitude of interannual variability. The possible physical causes of different timescale variability of SAT in China are further discussed.

The long-term variability of sea surface temperature in the seas east of China in the past 40 a

The global surface temperature change since the mid-19th century has caused general concern and intensive study. However, long-term changes in the marginal seas, including the seas east of China, are not well understood because long-term observations are sparse and, even when they exist, they are over limited areas. Preliminary results on the long-term variability of sea surface temperature （SST） in summer and winter in the seas east of China during the period of 1957-2001 are reported using the Ocean Science Database of Institute of Oceanology, Chinese Academy of Sciences, the coastal hydrological station in situ and satellite data. The results show well-defined warming trends in the study area. However warming and cooling trends vary from decade to decade, with steady and rapid warming trends after the 1980s and complicated spatial patterns. The distribution of SST variation is intricate and more blurred in the areas far away from the Kuroshio system. Both historical and satellite data sets show significant warming trends after 1985. The warming trends are larger and spread to wider areas in winter than in summer, which means decrease in the seasonal cycle of SST probably linked with recently observed increase of the tropical zooplankton species in the region. Spatial structures of the SST trends are roughly consistent with the circulation pattern especially in winter when the meridional SST gradients are larger, suggesting that a horizontal advection may play an important role in the long-term SST variability in winter.

Psychological stress and long-term blood pressure variability of military young males:The cardiorespiratory fitness and hospitalization events in armed forces study

BACKGROUND Acute stress might increase short-term heart rate variability and blood pressure variability(BPV);however,chronic stress would not alter short-term BPV in animal models.AIM To examine the association of psychological stress with long-term BPV in young male humans.METHODS We prospectively examined the association of chronic psychological stress with long-term BPV in 1112 healthy military males,averaged 32.2 years from the cardiorespiratory fitness and hospitalization events in armed forces study in Taiwan.Psychological stress was quantitatively evaluated with the Brief Symptom Rating Scale(BSRS-5),from the least symptom of 0 to the most severe of 20,and the five components of anxiety,insomnia,depression,interpersonal sensitivity,and hostility(the severity score in each component from 0 to 4).Longterm BPV was assessed by standard deviation(SD)for systolic and diastolic blood pressure(SBP and DBP),and average real variability(ARV),defined as the average absolute difference between successive measurements of SBP or DBP,across four visits in the study period from 2012 to 2018(2012-14,2014-15,2015-16,and 2016-18).RESULTS The results of multivariable linear regressions showed that there were no correlations of the BSRS-5 score with SDSBP,SDDBP,ARVSBP,and ARVDBP after adjusting for all the covariates[β(SE):-0.022(0.024),-0.023(0.026),-0.001(0.018),and 0.001(0.020),respectively;P>0.05 for all].In addition,there were also no correlations between each component of the BSRS score and the long-term BPV indexes.CONCLUSION Our findings suggest that chronic psychological stress might not be associated with long-term BPV in military young male humans.

The inter-annual variability of the Yellow Sea Warm Current surface axis and its influencing factors

Based on the Pathfinder sea surface temperature(PFSST),the surface axis and its pattern of the Yellow Sea Warm Current(YSWC) are discussed.A structure of double-warm-tongue is found in February and it varies in different years.Two indexes are calculated to represent the westward shift(WSI) and northward extension(NEI) of the warm water in the Yellow Sea(YS).Wavelet analysis illustrates that the WSI and NEI have prominent periods of 3-6 years and 3-4 years,respectively.The Empirical Orthogonal Function(EOF) decomposition is applied to the winter wind stress curl and the Kuroshio Current(KC) transport,which are believed to play important roles in forcing the variability of the YSWC surface axis.Statistics shows that the WSI is significantly related with the second EOF mode of the wind stress curl in February,which may force the YSWC surface axis moving westward and maintaining the double warm tongues because of its opposite curl in the YSWC domain.The first EOF mode of wind stress curl in January is propitious for inducing the warm tongue in the YS to advance more northward.Hence,the wind stress curls both in January and in February could force variations of the YSWC surface axis;however,the effect of the January wind stress curl is relatively weaker than that of the February.The relationship between the NEI and the KC transport is remarkable,and it seems that the stronger KC supplies more power to push the YSWC northward against the southward wind.

Summer Monsoon Impacts on Chlorophyll-a Concentration in the Middle of the South China Sea:Climatological Mean and Annual Variability

Climatological mean and annual variations of Chlorophyll-a(Chl-a) distribution,sea surface wind(SSW),and sea surface temperature(SST) from 1998 to 2008 were analyzed in the middle of the South China Sea(SCS),focusing on the typical region off the east coast of Vietnam(8.5-14°N,109.5-114°E).Based on remote sensing data and SCS summer monsoon index(SCSSMI) data,high Chl-a concentrations in the middle of the SCS in the southwest summer monsoon season(June-September) may be related to strong Ekman pumping and strong wind stress.The maximum of the monthly averaged climatological Chl-a in the summer appeared in August.According to the annual variation,there was a significant negative correlation(r =-0.42) between the SCSSMI and SST,a strongly positive correlation(r=0.61) between the SCSSMI and Chl-a,and a strongly negative correlation(r =-0.74) between the SST and Chl-a in the typical region off the east coast of Vietnam during 1998-2008.Due to the El Ni?o event specifically,the phenomena of a low Chl-a concentration,high SST and weak SCSSMI were extremely predominant in the summer of 1998.These relationships imply that the SCSSMI associated with the SST could be used to predict the annual variability of summer Chl-a in the SCS.

Annual and Interannual Variability of Scatterometer Ocean Surface Wind over the South China Sea

To investigate the annual and interannual variability of ocean surface wind over the South China Sea(SCS), the vector empirical orthogonal function(VEOF) method and the Hilbert-Huang transform(HHT) method were employed to analyze a set of combined satellite scatterometer wind data during the period from December 1992 to October 2009. The merged wind data were generated from European Remote Sensing Satellite(ERS)-1/2 Scatterometer, NASA Scatterometer(NSCAT) and NASA's Quick Scatterometer(QuikSCAT) wind products. The first VEOF mode corresponds to a winter-summer mode which accounts for 87.3% of the total variance and represents the East Asian monsoon features. The second mode of VEOF corresponds to a spring-autumn oscillation which accounts for 8.3% of the total variance. To analyze the interannual variability, the annual signal was removed from the wind data set and the VEOFs of the residuals were calculated. The temporal mode of the first interannual VEOF is correlated with the Southern Oscillation Index(SOI) with a four-month lag. The second temporal interannual VEOF mode is correlated with the SOI with no time lag. The time series of the two interannual VEOFs were decomposed using the HHT method and the results also show a correlation between the interannual variability and El Ni?o-Southern Oscillation(ENSO) events.

SEASONAL AND INTER-ANNUAL VARIABILITY OF THE SOUTH CHINA SEA WARM POOL AND ITS RELATION TO THE SOUTH CHINA SEA MONSOON ONSET

The South China Sea warm pool interacts vigorously with the summer monsoon which is active in the region. However, there has not been a definition concerning the former warm pool which is as specific as that for the latter. The seasonal and inter-annual variability of the South China Sea warm pool and its relations to the South China Sea monsoon onset were analyzed using Levitus and NCEP/NCAR OISST data. The results show that, the seasonal variability of the South China Sea warm pool is obvious, which is weak in winter, develops rapidly in spring, becomes strong and extensive in summer and early autumn, and quickly decays from mid-autumn. The South China Sea warm pool is 55 m in thickness in the strongest period and its axis is oriented from southwest to northeast with the main section locating along the western offshore steep slope of northern Kalimantan-Palawan Island. For the warm pools in the South China Sea, west Pacific and Indian Ocean, the oscillation, which is within the same large scale air-sea coupling system, is periodic around 5 years. There are additional oscillations of about 2.5 years and simultaneous inter-annual variations for the latter two warm pools. The intensity of the South China Sea warm pool varies by a lag of about 5 months as compared to the west Pacific one. The result also indicates that the inter-annual variation of the intensity index is closely related with the onset time of the South China Sea monsoon. When the former is persistently warmer (colder) in preceding winter and spring, the monsoon in the South China Sea usually sets in on a later (earlier) date in early summer. The relation is associated with the activity of the high pressure over the sea in early summer. An oceanic background is given for the prediction of the South China Sea summer monsoon, though the mechanism through which the warm pool and eventually the monsoon are affected remains unclear.

The Effect of Regional Ocean-Atmosphere Coupling on the Long-term Variability in the Pacific Ocean

A fully coupled ocean-atmosphere model is applied to highlight the mechanism of the long-term variability （including decadal and longer time scales） in the Pacific Ocean. We are interested in the effect of ocean-atmosphere coupling of different regions during these processes. The control run successfully simulates the Pacific long-term variability, whose leading modes are the Pacific （inter） Decadal Oscillation （PDO） and the North Pacific mode （NPM）. Furthermore, three numerical experiments are conducted, shutting down the ocean-atmosphere coupling in the North Pacific, the tropical Pacific, and the South Pacific, respectively. The results show that regional ocean-atmosphere coupling is not only important to the strength of local long-term SST variability but also has an influence on the variability further afield. In both the tropical Pacific and North Pacific, this local effect is the main control, which is much more obvious in the tropical regions. The existence of the PDO is extremely dependent on the coupling in the tropical Pacific. However, extratropical coupling, in particular that in the North Pacific, is also important to form its spatial pattern and strengthen the variability in some tropical areas. For the NPM, its existence is primarily determined by the coupling in the North Pacific.

A Recent Study on the Relationship between Global Radiative Forcing and Global Annual Climatic Variability

The present paper investigates the relationship between the global radiative forcing (GRF) and global annual climatic variability. The relation between the GRF and global annual changes in the operational weather and climatic parameters is uncovered. There are several datasets which have been used to challenge this goal. The NCEP/NCAR Reanalysis dataset of several meteorological elements, such as air temperature, wind, surface pressure, outgoing long wave radiation, precipitation rate and geopotential height at level 500 hPa, etc. for the globe for the period (1948-2012), has been used. Furthermore, the GRF data for greenhouse gases through the period (1979-2010) has been used. Also, datasets of climatic indices NAO, SOI, El Nino 3.4 and SST during the period (1948-2012) have been used through this study. Time series analysis, anomaly and correlation coefficient technique methods have been used to analyze the datasets. The results reveal that there is an outstanding positive correlation coefficient (more than +0.80) between GRF and the global annual weather elements of surface air temperature, temperature and geopotential height at level 500 hPa, precipitation rate and sea surface temperature. CO2 has a significant correlation coefficient (+0.89) with the outcomes longwave radiation and sea surface temperature. There is a significant relationship between the global annual variability of weather and climatic elements and GHGs, global warming and climatic indices, NAO, SOI, El Nino 3.4 and SST.

Crops Responses to Inter-Annual Climate Variability in Agroclimatic Zone of Sub-Saharan Africa

Climate variability has become a decisive factor for the crop yields in Sub-Saharan African countries. Inter-annual variability in rainfall has been the key climatic element that determines the success of agriculture in this region.From an analysis of recent rainfall conditions in West Africa,FAO(2001) concluded that a long-term change in rainfall has occurred in the semi-arid and sub-humid zones of West Africa.Thus,this study aims at assessing the vulnerability of crop yields to inter-annual variability in rainfall in sub-Saharan African countries taking Nigeria as a case study.A time series of the averaged value of the 12-Month Weighted Anomaly Standardized Precipita-

基于第十三代国际地磁参考场模型在中国区域特征分析与研究

根据最新的第十三代国际地磁参考场模型(IGRF13),计算了2015—2020年中国区域地磁场模型七要素长期变化速率,并在此基础上分析我国区域地磁场长期变化特征。通过分析计算我国28个地磁台的IGRF13模型值与实际地磁场的长期变化速率、差值及均方误差,结果显示:IGRF13模型所显示的地磁场长期变化与我国区域地磁场实际观测变化基本一致,但在局部区域也存在差异,IGRF13模型能够体现中国区域地磁场的特征。应用IGRF13模型数据时需要考虑局部区域与台站实际观测数据的误差。

近60年福建“龙舟水”期间降水的时空分布及影响因素

每年5月中旬左右,南海夏季风爆发后“龙舟水”给福建地区带来大量的降雨,短时强降雨易引起积涝的风险,对人民生产生活造成巨大的影响,但其背后的影响机制仍不清楚。本研究基于福建省60个气象站1962-2021年降水监测资料,采用主成分分析、合成分析、小波分析等方法重建了近60年来福建“龙舟水”期间降水的时空变化特征。结果显示,在年际尺度上福建“龙舟水”整体呈现出先下降后增加的趋势,其中在1981-1995年明显趋于偏少,而空间上自东南向西北呈增加趋势。“龙舟水”的长期趋势与副热带高压活动(以下简称副高)存在着反相关关系,即副高弱时其位置偏东,“龙舟水”偏多;而副高强时,位置偏西,“龙舟水”则偏少。此外,在El Nino年时,季风爆发相对较晚,“龙舟水”偏少;而在La Nina年,夏季风爆发相对较早,“龙舟水”较多。“龙舟水”从20世纪70年代中后期开始到21世纪初期与ENSO存在5~7 a的共同周期,进一步说明在年代际尺度上ENSO对龙舟水起着重要的调控作用。

Analysis of Temperature Trends and Variations in the Arabian Peninsula’s Upper Atmosphere

In this study, the trends of upper-air temperatures are analysed by utilising radiosonde observations for the barometric levels at 700, 500, 300, 200, 150, 100 and 50 hPa from five meteorological stations within the Arabian Peninsula from January 1986 to August 2015. The mean monthly variations of the temperatures at these levels are characterised and established. The magnitudes of the annual trends of the mean temperatures for each site for the selected barometric levels are studied and statistically tested using Mann-Kendall rank statistics at different significance levels. The temperature trends at different pressure levels show that the upper troposphere and lower stratosphere are warming, while the middle troposphere is cooling which is consistent with the findings of other studies. The variations in upper air temperature observed in this study can be attributed to a range of factors, including increasing greenhouse gas concentrations, changes in atmospheric circulation patterns, variations in solar activity, aerosols and volcanic eruptions, and land use and land cover change.

The variability of eddy ki/netic energy in the South China Sea deduced from satellite altimeter data

We used fifteen years (1993-2007) of altimetric data,combined from different missions (ERS-1/2,TOPEX/Poseidon,Jason-1,and Envisat),to analyze the variability of the eddy kinetic energy (EKE) in the South China Sea (SCS).We found that the EKE ranged from 64 cm2/s2 to 1 390 cm2/s2 with a mean value of 314 cm2/s2.The highest EKE center was observed to the east of Vietnam (with a mean value of 509 cm2/s2) and the second highest EKE region was located to the southwest of Taiwan Island (with a mean value of 319 cm2/s2).We also found that the EKE structure is the consequence of the superposition of different variability components.First,interannual variability is important in the SCS.Spectral analysis of the EKE interannual signal (IA-EKE) shows that the main periodicities of the IA-EKE to the east of Vietnam,to the southwest of Taiwan Island,and in the SCS are 3.75,1.87,and 3.75 years,respectively.It is to the south of Taiwan Island that the IA-EKE signal has the most obvious impact on EKE variability.In addition,the IA-EKE exhibit different trends in different regions.An obvious positive trend is observed along the east coast of Vietnam,while a negative trend is found to the southwest of Taiwan Island and in the east basin of Vietnam.Correlation analysis shows that the IA-EKE has an obvious negative correlation with the SSTA in Nio3 (5°S-5°N,90°W-150°W).El Nio-Southern Oscillation (ENSO) affects the IA-EKE variability in the SCS through an atmospheric bridge-wind stress curl over the SCS.Second,the seasonal cycle is the most obvious timescale affecting EKE variability.The locations of the most remarkable EKE seasonal variabilities in the SCS are to the east of Vietnam,to the southwest of Taiwan,and to the west of Philippines.To the east of Vietnam,the seasonal cycle is the dominant mechanism controlling EKE variability,which is attributed primarily to the annual cycle there of wind stress curl.In this area,the maximum EKE is observed in autumn.To the southwest of Taiwan Island,the EKE is enlarged by the stronger SCS circulation,which is caused by the intrusion branch from the Kuroshio in winter.Finally,intra-annual and mesoscale variability,although less important than the former,cannot be neglected.The most obvious intra-annual and mesoscale variability,which may be the result of baroclinic instability of the background flow,are observed to the southwest of Taiwan Island.Sporadic events can have an important effect on EKE variability.

A Modelling Study of Inter-Annual Variation of Kuroshio Intrusion on the Shelf of East China Sea

Inter-annual variability of the Kuroshio water intrusion on the shelf of East China Sea (ECS) was simulated with a nested global and Northwest Pacific ocean circulation model.The model analysis reveals the influence of the variability of Kuroshio transport east of Taiwan on the intrusion to the northeast of Taiwan:high correlation (r=0.92) with the on-shore volume flux in the lower layer (50 200 m) ;low correlation (r=0.50) with the on-shore flux in the upper layer (0 50 m) .Spatial distribution of correlations between volume fluxes and sea surface height suggests that inter-annual variability of the Kuroshio flux east of Taiwan and its subsurface water intruding to the shelf lag behind the sea surface height anomalies in the central Pacific at 162 E by about 14 months,and could be related to wind-forced variation in the interior North Pacific that propagates westward as Rossby waves.The intrusion of Kuroshio surface water is also influenced by local winds.The intruding Kuroshio subsurface water causes variations of temperature and salinity of bottom waters on the southern ECS shelf.The influence of the intruding Kuroshio subsurface water extends widely from the shelf slope northeast of Taiwan northward to the central ECS near the 60 m isobath,and northeastward to the region near the 90 m isobath.

Variability in Road Runoff Pollution by Polycyclic Aromatic Hydrocarbons (PAHs) in the Urbanized Area Adjacent to Biscayne Bay, Florida

Polycyclic aromatic hydrocarbons (PAHs) were consistently documented in the sediments of the canals draining into Biscayne Bay. The study examines the contribution of urban runoff to PAHs discharges. Subtropical climatic conditions associated with prolonged dry seasons often exacerbate the problem of PAHs pollution as the initial storms of the wet season wash off pollutants accumulated over time. Road runoff samples were collected at two sites with different levels of traffic at the end and at the beginning of the wet season. Storm-event mass first flush was found to occur inconsistently. Higher levels of PAH pollution were found at both sites after an extended dry season. The Kendall’s tau test used to measure the association between antecedent dry days and flow-weighted PAH concentrations was found to be statistically significant. The correlation between traffic intensity and PAHs levels in road runoff was found not to be statistically significant. High-molecular-weight PAHs originating in vehicle exhaust emissions appeared to dominate PAH concentrations in road runoff. The Friedman’s test showed overall similarity in PAHs composition profiles between seasons with the exception of low-molecular weight PAHs.

Dew amount and its long-term variation in the Kunes River Valley,Northwest China

Dew is an essential water resource for the survival and reproduction of organisms in arid and semi-arid regions.Yet estimating the dew amount and quantifying its long-term variation are challenging.In this study,we elucidate the dew amount and its long-term variation in the Kunes River Valley,Northwest China,based on the measured daily dew amount and reconstructed values(using meteorological data from 1980 to 2021),respectively.Four key results were found:(1)the daily mean dew amount was 0.05 mm during the observation period(4 July-12 August and 13 September-7 October of 2021).In 35 d of the observation period(i.e.,73%of the observation period),the daily dew amount exceeded the threshold(>0.03 mm/d)for microorganisms;(2)air temperature,relative humidity,and wind speed had significant impacts on the daily dew amount based on the relationships between the measured dew amount and meteorological variables;(3)for estimating the daily dew amount,random forest(RF)model outperformed multiple linear regression(MLR)model given its larger R^(2) and lower MAE and RMSE;and(4)the dew amount during June-October and in each month did not vary significantly from 1980 to the beginning of the 21^(st) century.It then significantly decreased for about a decade,after it increased slightly from 2013 to 2021.For the whole meteorological period of 1980-2021,the dew amount decreased significantly during June-October and in July and September,and there was no significant variation in June,August,and October.Variation in the dew amount in the Kunes River Valley was mainly driven by relative humidity.This study illustrates that RF model can be used to reconstruct long-term variation in the dew amount,which provides valuable information for us to better understand the dew amount and its relationship with climate change.

Estimation and Long-term Trend Analysis of Surface Solar Radiation in Antarctica: A Case Study of Zhongshan Station

Long-term,ground-based daily global solar radiation (DGSR) at Zhongshan Station in Antarctica can quantitatively reveal the basic characteristics of Earth’s surface radiation balance and validate satellite data for the Antarctic region.The fixed station was established in 1989,and conventional radiation observations started much later in 2008.In this study,a random forest (RF) model for estimating DGSR is developed using ground meteorological observation data,and a highprecision,long-term DGSR dataset is constructed.Then,the trend of DGSR from 1990 to 2019 at Zhongshan Station,Antarctica is analyzed.The RF model,which performs better than other models,shows a desirable performance of DGSR hindcast estimation with an R^2 of 0.984,root-mean-square error of 1.377 MJ m^(-2),and mean absolute error of 0.828 MJ m^(-2).The trend of DGSR annual anomalies increases during 1990–2004 and then begins to decrease after 2004.Note that the maximum value of annual anomalies occurs during approximately 2004/05 and is mainly related to the days with precipitation (especially those related to good weather during the polar day period) at this station.In addition to clouds and water vapor,bad weather conditions (such as snowfall,which can result in low visibility and then decreased sunshine duration and solar radiation) are the other major factors affecting solar radiation at this station.The high-precision,longterm estimated DGSR dataset enables further study and understanding of the role of Antarctica in global climate change and the interactions between snow,ice,and atmosphere.

Under-ice ambient noise in the Arctic Ocean: observations at the long-term ice station

Under-ice ambient noise in the Arctic Ocean is studied using the data recorded by autonomous hydrophones at the long-term ice station during the 9th Chinese National Arctic Research Expedition.Time-frequency analysis of two 7-s-long ice-induced noise samples shows that both ice collision and ice breaking noise have many outliers in the time-domain(impulsive characteristic)and abundant frequency components in the frequency-domain.Ice collision noise lasts for several seconds while the duration of ice breaking noise is much shorter(i.e.,less than tens of milliseconds).Gaussian distribution and symmetric alpha stable(sαs)distribution are used in this paper to fit the impulsive under-ice noise.The sαs distribution can achieve better performance as it can track the heavy tails of impulsive noise while Gaussian distribution fails.This paper also analyzes the meteorological variables during the under-ice noise observation experiment and deduces that the impulsive ambient noise was caused by the combined force of high wind speed and increasing atmosphere temperature on the ice canopy.The Pearson correlation coefficients between long-term power spectral density variations of under-ice ambient noise and meteorological variables are also studied in this paper.