Evaluation of the tropical variability from the Beijing Climate Center’s real-time operational global Ocean Data Assimilation System

The second-generation Global Ocean Data Assimilation System of the Beijing Climate Center(BCC_GODAS2.0) has been run daily in a pre-operational mode.It spans the period 1990 to the present day.The goal of this paper is to introduce the main components and to evaluate BCC_GODAS2.0 for the user community.BCC_GODAS2.0 consists of an observational data preprocess,ocean data quality control system,a three-dimensional variational(3DVAR) data assimilation,and global ocean circulation model[Modular Ocean Model 4(MOM4)].MOM4 is driven by six-hourly fluxes from the National Centers for Environmental Prediction.Satellite altimetry data,SST,and in-situ temperature and salinity data are assimilated in real time.The monthly results from the BCC_GODAS2.0 reanalysis are compared and assessed with observations for 1990-2011.The climatology of the mixed layer depth of BCC-GODAS2.0 is generally in agreement with that of World Ocean Atlas 2001.The modeled sea level variations in the tropical Pacific are consistent with observations from satellite altimetry on interannual to decadal time scales.Performances in predicting variations in the SST using BCC_GODAS2.0 are evaluated.The standard deviation of the SST in BCC-GODAS2.0 agrees well with observations in the tropical Pacific.BCC-GODAS2.0 is able to capture the main features of E1 Nino Modoki I and Modoki Ⅱ,which have different impacts on rainfall in southern China.In addition,the relationships between the Indian Ocean and the two types of E1 Nino Modoki are also reproduced.     

Impact of the South China Sea Throughflow on the Pacific Low-Latitude Western Boundary Current: A Numerical Study for Seasonal and Interannual Time Scales

Prior studies have revealed that,as a part of the Pacific tropical gyre,the South China Sea throughflow(SCSTF) is strongly influenced by the Pacific low-latitude western boundary current(LLWBC).In this study,ocean general circulation model(OGCM) experiments with and without connection to the South China Sea(SCS) were performed to investigate the impact of the SCSTF on the Pacific LLWBC.These model experiments show that if the SCS is blocked,seasonal variability of the Kuroshio and Mindanao Current becomes stronger,and the meridional migration of the North Equatorial Current(NEC) bifurcation latitude is enhanced.Both in seasonal and interannual time scales,stronger Luzon Strait transport(LST) induces a stronger Kuroshio transport combined with a southward shift of the NEC bifurcation,which is unfavorable for a further increase of the LST;a weaker LST induces a weaker Kuroshio transport and a northward shifting NEC bifurcation,which is also unfavorable for the continuous decrease of the LST.     

Numerical simulation of the impact of vegetation index on the interannual variation of summer precipitation in the Yellow River Basin

Two sets of numerical experiments using the coupled National Center for Environmental Prediction General Circulation Model （NCEP/GCM T42L18） and the Simplified Simple Biosphere land surface scheme （SSiB） were carried out to investigate the climate impacts of fractional vegetation cover （FVC） and leaf area index （LAI） on East Asia summer precipitation, especially in the Yellow River Basin （YRB）. One set employed prescribed FVC and LAI which have no interannual variations based on the climatology of vegetation distribution; the other with FVC and LAI derived from satellite observations of the International Satellite Land Surface Climate Project （ISLSCP） for 1987 and 1988. The simulations of the two experiments were compared to study the influence of FVC, LAI on summer precipitation interannual variation in the YRB. Compared with observations and the NCEP reanalysis data, the experiment that included both the effects of satellite-derived vegetation indexes and sea surface temperature （SST） produced better seasonal and interannual precipitation variations than the experiment with SST but no interannual variations in FVC and LAI, indicating that better representations of the vegetation index and its interannual variation may be important for climate prediction. The difference between 1987 and 1988 indicated that with the increase of FVC and LAI, especially around the YRB, surface albedo decreased, net surface radiation increased, and consequently local evaporation and precipitation intensified. Further more, surface sensible heat flux, surface temperature and its diurnal variation decreased around the YRB in response to more vegetation. The decrease of surface-emitting longwave radiation due to the cooler surface outweighed the decrease of surface solar radiation income with more cloud coverage, thus maintaining the positive anomaly of net surface radiation. Further study indicated that moisture flux variations associated with changes in the general circulation also contributed to the precipitation interannual variation.     

Simulation and Analysis of China Climate Using Two-Way Interactive Atmosphere-Vegetation Model （RIEMS-AVIM）

In this paper, an Atmosphere-Vegetation Interaction Model （AVIM） is coupled to the Regional Integrated Environment Model System （RIEMS）, and a 10-year integration for China is performed using the RIEMS-AVIM. The analysis of the results of the 10-year integration shows that the characters of the spatial distributions of temperature and precipitation over China are well simulated. The patterns of simulated surface sensible and latent heat fluxes match well with the spatial climatological atlas： the values of winter surface sensible and latent heat fluxes are both lower than climatological values over the whole country. Summer surface sensible heat flux is higher than climatological values in western China and lower in eastern China, while summer surface latent heat flux is higher than climatological values in the eastern and lower in the western. Seasonal variations of simulated temperature and precipitation of RIMES-AVIM agree with those of the observed. Simulated temperature is lower than the observed in the Tibetan Plateau and Northwest China for the whole year, slightly lower in the remaining regions in winter, but consistent with the observed in summer. The simulated temperature of RIEMS-AVIM is higher in winter and lower in summer than that of RIEMS, which shows that the simulated temperature of RIEMS-AVIM is closer to the observed value. Simulated precipitation is excessive in the first half of the year, but consistent with the observed in the second half of the year. The simulated summer precipitation of RIEMS-AVIM has significant improvement compared to that of RIEMS, which is less and closer to the observed value. The interannual variations of temperature and precipitation are also fairly well simulated, with temperature simulation being superior to precipitation simulation. The interannual variation of simulated temperature is significantly correlated with the observed in Northeast China, the Transition Region, South China, and the Tibetan Plateau, but the correlation between precipitation simu     

An ocean data assimilation system in the Indian Ocean and west Pacific Ocean

The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean(hereafter AIPOcean) constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving,hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles(mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity–temperature–depth, station data), remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993–2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.     

Effects of interannual salinity variability on the barrier layer in the western-central equatorial Pacific: A diagnostic analysis from Argo

ABSTRACT In this paper, interannual variations in the barrier layer thickness （BLT） are analyzed using Argo three-dimensional temperature and salinity data, with a locus on the effects of interannually varying salinity on the evolution of the El Nifio Southern Oscillation （ENSO）. The interannually varying BLT exhibits a zonal seesaw pattern across the equatorial Pacific during ENSO cycles. This phenomenon has been attributed to two different physical processes. During E1 Nifio （La Nifia）, the barrier layer （BL） is anomalously thin （thick） west of about 160°E, and thick （thin） to the east. In the western equatorial Pacific （the western part： 130°-160°E）, interannual variations of the BLT indicate a lead of one year relative to those of the ENSO onset. The interannual variations of the BLT can be largely attributed to the interannual temperature variability, through its dominant effect on the isothermal layer depth （ILD）. However, in the central equatorial Pacific （the eastern part： 160~E- 170~W）, interannual variations of the BL almost synchronously vary with ENSO, with a lead of about two months relative to those of the local SST. In this region, the interannual variations of the BL are significantly affected by the interannually varying salinity, mainly through its modulation effect on the mixed layer depth （MLD）. As evaluated by a onedimensional boundary layer ocean model, the BL around the dateline induced by interannual salinity anomalies can significantly affect the temperature fields in the upper ocean, indicating a positive feedback that acts to enhance ENSO.     

Simulation of Volume and Heat Transport along 26.5°N in the Atlantic

The observed meridional overturning circulation (MOC) and meridional heat transport (MHT) estimated from the Rapid Climate Change/Meridional Circulation and Heat Flux Array (RAPID/MOCHA) at 26.5°N are used to evaluate the volume and heat transport in the eddy-resolving model LASG/IAP Climate system Ocean Model (LICOM). The authors find that the Florida Current transport and upper mid-ocean transport of the model are underestimated against the observations. The simulated variability of MOC and MHT show a high correlation with the observations, exceeding 0.6. Both the simu-lated and observed MOC and MHT show a significant seasonal variability. According to the power spectrum analysis, LICOM can represent the mesoscale eddy characteristic of the MOC similar to the observation. The model shows a high correlation of 0.58 for the internal upper mid-ocean transport (MO) and a density difference between the western and eastern boundaries, as noted in previous studies.     

Interannual and Interdecadal Variations in Atmospheric Circulation Factors and Rainfall in China and Their Relationship

Wavelet analysis is used to study the interannual and interdecadal variations of rainfall in China and atmospheric circulation factors, including the key atmospheric oscillations, W, C, E patterns and subtropical high. Regression analysis and correlation analysis are both used to study the relationship of atmospheric circulation factors and China rainfall on different time scale and spatial scale. The results are as follows: (1) The variations of atmospheric circulation and rainfall in China are characterized by interannual and interdecadal scales. The variations of atmospheric circulation and rainfall are composed of interannual and interdecadal variations. It is necessary to separate those two time scales when climate changes and forecast are studied. (2) The variations of China rainfall are due to the interaction of multi-factors rather than single factors. The marked factors which influence the interannual and interdecadal variations are various. Subtropical high is one of the marked factors which influence interannual variations of rainfall, while AO, NAO, and NPO are one of the marked factors which influence interdecadal variations of rainfall. (3) The longer the time scale is, and the larger the spatial scale is, and the more remarkable the relationships between atmospheric circulation and rainfall are.     

IMPACT OF VERTICAL RESOLUTION,MODEL TOP AND DATA ASSIMILATION ON WEATHER FORECASTING——A CASE STUDY

The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top, refining the vertical resolution, and the assimilation of operationally available observations, including conventional and satellite observations, on continental U.S. winter short-range weather forecasting, were investigated in this study. The initial and predicted wind and temperature profiles were analyzed against conventional observations. Generally, the initial wind and temperature bias profiles were better adjusted when a higher model top and refined vertical resolution were used. Negative impacts were also observed in both the initial wind and temperature profiles, over the lower troposphere. Different from the results by only raising the model top, the assimilation of operationally available observations led to significant improvements in both the troposphere and stratosphere initial conditions when a higher top was used. Predictions made with the adjusted stratospheric initial conditions and refined vertical resolutions showed generally better forecasting skill. The major improvements caused by raising the model top with refined vertical resolution, as well as those caused by data assimilation, were in both cases located in the tropopause and lower stratosphere. Negative impacts were also observed, in the predicted near surface wind and lower-tropospheric temperature. These negative impacts were related to the uncertainties caused by more stratospheric information, as well as to some physical processes. A case study shows that when we raise the model top, put more vertical layers in stratosphere and apply data assimilation, the precipitation scores can be slightly improved. However, more analysis are needed due to uncertainties brought by data assimilation.     

A Local Implementation of the POD-Based Ensemble 4DVar with R-Localization简

The purpose of this paper is to provide a robust and flexible implementation of a proper orthogonal decomposition-based ensemble four-dimensional variational assimilation method（PODEn4DVar） through Rlocalization.With R-localization,the implementation of the local PODEn4DVar analysis can be coded for parallelization with enhanced assimilation precision.The feasibility and effectiveness of the PODEn4DVar local implementation with R-localization are demonstrated in a two-dimensional shallow-water equation model with simulated observations（OSSEs） in comparison with the original version of the PODEn4DVar with B-localization and that without localization.The performance of the PODEn4DVar with localization shows a significant improvement over the scheme with no localization,particularly under the imperfect model scenario.Moreover,the R-localization scheme is capable of outperforming the Blocalization case to a certain extent.Further,the assimilation experiments also demonstrate that PODEn4DVar with R-localization is most efficient due to its easy parallel implementation.     

INTERANNUAL VARIABILITY OF WINTER AND SPRING PRECIPITATION IN SOUTH CHINA AND ITS RELATION TO MOISTURE TRANSPORT

The interannual variability of winter and spring precipitation in South China(SC)and its relation to moisture transport are investigated by using the monthly precipitation data of NMIC,NCEP reanalysis datasets and NOAA ERSST analysis datasets from 1960 to 2008.The results show that winter and spring precipitation in SC is less than normal from the 1960s to the start of the 1970s and from the end of the 1990s to the present.Most of rainfall anomalies on the whole regional scale of SC is well in phase during winter and spring,and the frequency of persistent drought is higher than that of persistent flood.Seasonal variations of moisture transport differences of SC between persistent drought and flood events are observed:the differences in winter are characterized by moisture transport from Bay of Bangle(BOB)and South China Sea(SCS),while differences in spring are characterized by that from SCS and North China(NC).There are two types of Ni o3.4 sea surface temperature anomaly(SSTA)related to persistent winter and spring drought(flood)events in SC,which are positive SSTA next to Ni o4(Ni o3)and negative SSTA next to Ni o3(Ni o4).Moreover,the variations of moisture transport from BOB and SC have important effects on persistent drought/flood in SC when the Ni o3.4 index is in the positive phase,while those from western North Pacific(WNP)-SC in winter and those from Philippine Sea(PHS)-SC and NC in spring primarily contribute to persistent drought/flood events in SC when the Ni o3.4 index is in the negative phase,and these stronger(weaker)moisture transports are observed in persistent flood(drought)during winter and spring regardless of the Ni o3.4 index.In conclusion,with the correlation between variations and distributions of Ni o3.4 SSTA and persistent drought/flood events in SC,moisture transport is responsible for the formation of precipitation anomalies.In addition,the moisture transport from SCS is most significantly correlated with persistent drought/flood events during winter and spring.     

EVOLUTION LAW OF DRYNESS AND WETNESS IN KUNMING IN RECENT 300 YEARS

Using indexes of dryness and wetness in historical record over the recent recent years and rainfall data over the tatest century, the work involves itself with the study of climatological evolution of dryness and wetness. periodic variations of climate and interannual laws of variation. The discussion also covers the subjects of effects of El Nino. sunspot, predictors of general circulation on climatic variation of dryness and wetness. There arc main conclusions as follows: (1) The main cyclic variations of climate are 40 and 11 years in Kunming. the former being subject to that of El Nino and the latter to that of sunspots. They are two principal factors for periodic variations of dryness and wetness in Kunming. (2) A close relationship exists between interannual variations and general circulation factors for Kunming. The comprehensive influence as imposed by ENSO and allocations of W.C.E. patterns of circulation in the westerly are ma.tor weather and climate causes for the interannual variations of precipitation in Kunming.     

Variational Assimilation of GPS Precipitable Water Vapor and Hourly Rainfall Observations for a Meso-β Scale Heavy Precipitation Event During the 2002 Mei-Yu Season

Recent advances in Global Positioning System （GPS） remote sensing technology allow for a direct estimation of the precipitable water vapor （PWV） from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational （4DVAR） data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems （MCS） along the mei-yu front in China. The experiments with GPS-PWV assimilation cluster and also eliminated the erroneous rainfall successfully simulated the evolution of the observed MCS systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.     

Simulation of Tropospheric Ozone with MOZART-2： An Evaluation Study over East Asia

Climate changes induced by human activities have attracted a great amount of attention. With this, a coupling system of an atmospheric chemistry model and a climate model is greatly needed in China for better understanding the interaction between atmospheric chemical components and the climate. As the first step to realize this coupling goal, the three-dimensional global atmospheric chemistry transport model MOZART-2 (the global Model of Ozone and Related Chemical Tracers, version 2) coupled with CAM2 (the Community Atmosphere Model, version 2) is set up and the model results are compared against observations obtained in East Asia in order to evaluate the model performance. Comparison of simulated ozone mixing ratios with ground level observations at Minamitorishima and Ryori and with ozonesonde data at Naha and Tateno in Japan shows that the observed ozone concentrations can be reproduced reasonably well at Minamitorishima but they tend to be slightly overestimated in winter and autumn while underestimated a little in summer at Ryori. The model also captures the general features of surface CO seasonal variations quite well, while it underestimates CO levels at both Minamitorishima and Ryori. The underestimation is primarily associated with the emission inventory adopted in this study. Compared with the ozonesonde data, the simulated vertical gradient and magnitude of ozone can be reasonably well simulated with a little overestimation in winter, especially in the upper troposphere. The model also generally captures the seasonal, latitudinal and altitudinal variations in ozone concentration. Analysis indicates that the underestimation of tropopause height in February contributes to the overestimation of winter ozone in the upper and middle troposphere at Tateno.     

Ensemble Square Root Filter Assimilation of Near-Surface Soil Moisture and Reference-Level Observations into a Coupled Land Surface-Boundary Layer Model

The potential for using the ensemble square root filter data assimilation technique to estimate soil moisture profiles, surface heat fluxes, and the state of the planetary boundary layer （PBL） is explored. An observing system simulation experiment is designed to mimic the assimilation of near-surface soil moisture observations （θo ） and in-situ measurements of 2-m temperature （To ）, 2-m specific humidity （Qo ）, and 10-m horizontal winds [Vo =（Uo , Vo ）]. The background forecasts are generated by a one-dimensional coupled land surface-boundary layer model （CLS-BLM） with soil, surface-layer and PBL parameterization schemes similar to those used in the Weather Research and Forecasting （WRF） model. Soil moisture, surface heat fluxes, and the state of the PBL evolve on different characteristic timescales, so the minimum assimilation time intervals required for skillful estimates of each target component are different. Correct estimates of the soil moisture profile are obtained effectively when a 6-h update time interval is used, while skillful estimates of surface fluxes and the PBL state require more frequent updates. The CLS-BLM requires a shorter assimilation time interval to correctly estimate the soil moisture profile than previously indicated by experiments using an off-line land surface model （LSM）. Results from assimilating different subsets of observations show that θo makes a larger contribution to soil moisture estimates, while To , θo , and Vo are more important for estimates of surface heat fluxes and the PBL state. It is therefore necessary to combine these variables to accurately estimate the states of both the land surface and the PBL. Experimentation with different prescribed observational errors shows that the assimilation system is more sensitive to increases in observational errors than to reductions in observational errors.     

Impacts of XBT, TAO, Altimetry and ARGO Observations on the Tropical Pacific Ocean Data Assimilation

This study aims at assessing the relative impacts of four major components of the tropical Pacific Ocean observing system on assimilation of temperature and salinity fields. Observations were collected over a period between January 2001 through June 2003 including temperature data from the expendable bathythermographs （XBT）, thermistor data from the Tropical Ocean Global Atmosphere Tropical Atmosphere-Ocean （TOGA-TAO） mooring array, sea level anomalies from the Topex/Poseidon and Jason-1 altimetry （T/P-J）, and temperature and salinity profiles from the Array for Real-time Geostrophic Oceanography （ARGO） floats. An efficient three-dimensional variational analysis-based method was introduced to assimilate the above data into the tropical-Pacific circulation model. To evaluate the impact of the individual component of the observing system, four observation system experiments were carried out. The experiment that assimilated all four components of the observing system was taken as the reference. The other three experiments were implemented by withholding one of the four components. Results show that the spatial distribution of the data influences its relative contribution. XBT observations produce the most distinguished effects on temperature analyses in the off-equatorial region due to the large amount of measurements and high quality. Similarly, the impact of TAO is dominant in the equatorial region due to the focus of the spatial distribution. The Topex/Poseidon-Jason-1 can be highly complementary where the XBT and TAO observations are sparse. The contribution of XBT or TAO on the assimilated salinity is made by the model dynamics because no salinity observations from them are assimilated. Therefore, T/P-J, as a main source for providing salinity data, has been shown to have greater impacts than either XBT or TAO on the salinity analysis. Although ARGO includes the subsurface observations, the relatively smaller number of observation makes it have the smallest contribution to the assimilation syst     

Assimilating surface observations in a four-dimensional variational Doppler radar data assimilation system to improve the analysis and forecast of a squall line case

This paper examines how assimilating surface observations can improve the analysis and forecast ability of a fourdimensional Variational Doppler Radar Analysis System(VDRAS).Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational(4DVAR) data assimilation system.A squall-line case observed during a field campaign is selected to investigate the performance of the technique.A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions.The surface-based cold pool,divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation.Three experiments—assimilating radar data only,assimilating radar data with surface data blended in a mesoscale background,and assimilating both radar and surface observations with a 4DVAR cost function—are conducted to examine the impact of the surface data assimilation.Independent surface and wind profiler observations are used for verification.The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations.It is also shown that the additional surface data can help improve the analysis and forecast at low levels.Surface and low-level features of the squall line—including the surface warm inflow,cold pool,gust front,and low-level wind—are much closer to the observations after assimilating the surface data in VDRAS.     

The REMO Ocean Data Assimilation System into HYCOM （RODAS_H）： General Description and Preliminary Results

The first version of the Brazilian Oceano- graphic Modeling and Observation Network （REMO） ocean data assimilation system into the Hybrid Coordi- nate Ocean Model （HYCOM） （RODAS H） has recently been constructed for research and operational purposes. The system is based on a multivariate Ensemble Optimal Interpolation （EnOI） scheme and considers the high fre- quency variability of the model error co-variance matrix. The EnOl can assimilate sea surface temperature （SST）, satellite along-track and gridded sea level anomalies （SLA）, and vertical profiles of temperature （T） and salinity （S） from Argo. The first observing system experiment was carried out over the Atlantic Ocean （78°S-50°N, 100°W-20°E） with HYCOM forced with atmospheric reanalysis from 1 January to 30 June 2010. Five integra- tions were performed, including the control run without assimilation. In the other four, different observations were assimilated： SST only （A SST）; Argo T-S profiles only （AArgo）; along-track SLA only （A_SLA）; and all data employed in the previous runs （A_All）. The A_SST, A_Argo, and A_SLA runs were very effective in improv- ing the representation of the assimilated variables, but they had relatively little impact on the variables that were not assimilated. In particular, only the assimilation of S was able to reduce the deviation of S with respect to ob- servations. Overall, the A_All run produced a good analy- sis by reducing the deviation of SST, T, and S with respect to the control run by 39%, 18%, and 30%, respectively, and by increasing the correlation of SLA by 81%.     

Climatology and variability of the Indonesian Throughflow in an eddy-permitting oceanic GCM

A quasi-global eddy permitting oceanic GCM, LICOM1.0, is run with the forcing of ERA40 daily wind stress from 1958 to 2001. The modelled Indonesian Throughflow (ITF) is reasonable in the aspects of both its water source and major pathways. Compared with the observation, the simulated annual mean and seasonal cycle of the ITF transport are fairly realistic. The interannual variation of the tropical Pacific Ocean plays a more important role in the interannual variability of the ITF transport. The relationshipbetween the ITF and the Indian Ocean Dipole (IOD) also reflects the influence of ENSO. However, the relationship between the ITF transport and the interannual anomalies in the Pacific and Indian Oceans vary with time. During some years, (e.g., 1994), the effect of a strong IOD on the ITF transport is more than that from ENSO.     

Characteristics of Gaseous Pollutants at a Regional Background Station in Southern China

Measurements of gaseous pollutants （03, NOx, SO2, and CO） were conducted at Dinghushan background station in southern China from January to December 2013. The levels and variations of O3, NOx, SO2, and CO were analyzed and their possible causes discussed. The annual average concentrations of 03, NOx, SO2, and CO were 24.6 ± 23.9, 12.8 ± 10.2, 4.0 ± 4.8, and 348 ± 185 ppbv, respectively. The observed levels of the gaseous pollutants are comparable to those at other background sites in China. The most obvious diurnal variation of 03 was observed in autumn, with minima in the early morning and maxima in the afternoon. The diurnal variations of SO2 showed high values during the day. The diurnal cycles of NOx showed higher values in the morning and lower values during the night. Higher CO concentrations were observed in spring followed by winter, autumn, and summer. Biomass burning, in combination with the transport of regional pollution, is an important source of CO, SO2, and NOx in spring and winter. Backward trajectories were calculated and analyzed together with corresponding pollutant concentrations. The results indicate that air masses passing over polluted areas are responsible for the high concentrations of gaseous pollutants at the Dinghushan background station.