This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The ...This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The developments of associated data products and data applications for use in the fields of ocean, atmosphere, and climate research are discussed, particularly those related to tropical cyclones （typhoons）, ocean circulation, mesoscale eddies, turbulence, oceanic heat/salt storage and transportation, water masses, and operational oceanic/atmospheric/climatic forecasts and predictions. Finaliy, the challenges and opportunities involved in the long-term maintenance and sustained development of the China Argo ocean observation network are outlined. Discussion also focuses on the necessity for increasing the number of floats in the Indian Ocean and for expanding the regional Argo observation network in the South China Sea, together with the importance of promoting the use of Argo data by the maritime countries of Southeast Asia and India.展开更多
Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and...Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and chemical parameters on a global scale.Earth observation data has the 4V features(volume,variety,veracity,and velocity) of big data that are suitable for climate change research.Moreover,the large amount of data available from scientific satellites plays an important role.This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research,such as synchronous satelliteeaerialeground observation experiments,which provide extremely large and abundant datasets; Earth observational sensitive factors(e.g.,glaciers,lakes,vegetation,radiation,and urbanization); and global environmental change information and simulation systems.With the era of global environment change dawning,Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking.Inevitably,Earth observation big data will encounter opportunities and challenges brought about by global climate change.展开更多
Sea surface temperature(SST)data obtained from coastal stations in Jiangsu,China during 20102014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles,including the correlation...Sea surface temperature(SST)data obtained from coastal stations in Jiangsu,China during 20102014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles,including the correlation with the variation of the tide.Quality control of data includes the validation of extreme values and checking of hourly values based on temporally adjacent data points,with 0.15℃/h considered a suitable threshold for detecting abnormal values.The diurnal variation amplitude of the SST data is greater in spring and summer than in autumn and winter.The diurnal variation of SST has bimodal structure on most days,i.e.,SST has a significant semidiurnal cycle.Moreover,the semidiurnal cycle of SST is negatively correlated with the tidal data from March to August,but positively correlated with the tidal data from October to January.Little correlation is detected in the remaining months because of the weak coastal offshore SST gradients.The quality control and understanding of coastal SST data are particularly relevant with regard to the validation of indirect measurements such as satellite-derived data.展开更多
An observation operator is a bridge linking the system state vector and observations in a data assimilation system. Despite its importance, the degree to which an observation operator influences the performance of dat...An observation operator is a bridge linking the system state vector and observations in a data assimilation system. Despite its importance, the degree to which an observation operator influences the performance of data assimilation methods is still poorly understood. This study aimed to analyze the influences of linear and nonlinear observation operators on the sequential data assimilation through soil temperature simulation using the unscented particle filter(UPF) and the common land model. The linear observation operator between unprocessed simulations and observations was first established. To improve the correlation between simulations and observations, both were processed based on a series of equations. This processing essentially resulted in a nonlinear observation operator. The linear and nonlinear observation operators were then used along with the UPF in three assimilation experiments: an hourly in situ soil surface temperature assimilation, a daily in situ soil surface temperature assimilation, and a moderate resolution imaging spectroradiometer(MODIS) land surface temperature(LST) assimilation. The results show that the filter improved the soil temperature simulation significantly with the linear and nonlinear observation operators. The nonlinear observation operator improved the UPF's performance more significantly for the hourly and daily in situ observation assimilations than the linear observation operator did, while the situation was opposite for the MODIS LST assimilation. Because of the high assimilation frequency and data quality, the simulation accuracy was significantly improved in all soil layers for hourly in situ soil surface temperature assimilation, while the significant improvements of the simulation accuracy were limited to the lower soil layers for the assimilation experiments with low assimilation frequency or low data quality.展开更多
To reduce the spatial correlation of representation error in observations and computational complexity, we propose a thinning scheme that can extract typical observations within a certain range. This scheme is applied...To reduce the spatial correlation of representation error in observations and computational complexity, we propose a thinning scheme that can extract typical observations within a certain range. This scheme is applied to the Global/Regional Assimilation and Prediction System(GRAPES) with three-dimensional variation(3 DVAR) to study the effect of the thinning radius on the assimilation results. The assimilation experiments indicate that when the ratio of the model resolution to the observational resolution is 1:3, the simulated results for precipitation are relatively good and have a relatively high equitable threat score(ETS). Moreover, the analysis errors in the temperature and the specific humidity are the smallest, the dependence of the norm gradient vector of the objective function on the number of iterations is slow, gentle, and close to 0, and the minimization results in improved conditions.展开更多
With the development of wireless communication technology,cyber physical systems are applied in various fields such as industrial production and infrastructure,where lots of information exchange brings cyber security ...With the development of wireless communication technology,cyber physical systems are applied in various fields such as industrial production and infrastructure,where lots of information exchange brings cyber security threats to the systems.From the perspective of system identification with binary-valued observations,we study the optimal attack problem when the system is subject to both denial of service attacks and data tampering attacks.The packet loss rate and the data tampering rate caused by the attack is given,and the estimation error is derived.Then the optimal attack strategy to maximize the identification error with the least energy is described as a min–max optimization problem with constraints.The explicit expression of the optimal attack strategy is obtained.Simulation examples are presented to verify the effectiveness of the main conclusions.展开更多
Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms tha...Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms that QuikSCAT estimates of wind speed and direction are generally accurate, except for the extremes of high wind speeds (>13.8m/s) and very low wind speeds (<1.5m/s) where direction is poorly predicted. In-situ observations show that the summer monsoon in the northern SCS starts between May 6 and June 1. From March 13, 2010 to August 31, 2010, comparisons of sea surface temperature (SST) and rainfall from AMSR-E with data from a buoy located at Xisha Islands, as well as wind measurements derived from ASCAT and observations from an automatic weather station show that QuikSCAT, ASCAT and AMSR-E data are good enough for research. It is feasible to optimize the usage of remote-sensing data if validated with in-situ measurements. Remarkable changes were observed in wind, barometric pressure, humidity, outgoing longwave radiation (OLR), air temperature, rainfall and SST during the monsoon onset. The eastward shift of western Pacific subtropical high and the southward movement of continental cold front preceded the monsoon onset in SCS. The starting dates of SCS summer monsoon indicated that the southwest monsoon starts in the Indochinese Peninsula and forms an eastward zonal belt, and then the belt bifurcates in the SCS, with one part moving northeastward into the tropical western North Pacific, and another southward into western Kalimantan. This largely determined the pattern of the SCS summer monsoon. Wavelet analysis of zonal wind and OLR at Xisha showed that intra-seasonal variability played an important role in the summer. This work improves the accuracy of the amplitude of intra-seasonal and synoptic variation obtained from remote-sensed data.展开更多
Aircraft Meteorological Data Relay(AMDAR)observations have been widely used in numerical weather prediction(NWP)because of its high spatiotemporal resolution.The observational error of AMDAR is influenced by aircraft ...Aircraft Meteorological Data Relay(AMDAR)observations have been widely used in numerical weather prediction(NWP)because of its high spatiotemporal resolution.The observational error of AMDAR is influenced by aircraft flight altitude and atmospheric condition.In this study,the wind speed and altitude dependent observational error of AMDAR is estimated.The statistical results show that the temperature and the observational error in wind speeds slightly decrease as altitude increases,and the observational error in wind speed increases as wind speed increases.Pseudo single AMDAR observation assimilation tests demonstrate that the wind speed and altitude dependent observational error can provide more reasonable analysis increment.Furthermore,to assess the performance of wind speed and altitude dependent observational error on data assimilation and forecasting,two-month 3-hourly cycling data assimilation and forecast experiments based on the Weather Research and Forecasting Model(WRF)and its Data Assimilation system(WRFDA)are performed for the period during 1 September-31 October,2017.The results of the two-month 3-hourly cycling experiments indicate that new observational error improves analysis and forecast of wind field and geo-potential height,and has slight improvements on temperature.The Fractions Skill Score(FSS)of the 6-h accumulated precipitation shows that new wind speed and altitude dependent observational error leads to better precipitation forecast skill than the default observational error in the WRFDA does.展开更多
Identifying the causal impact of＇ some intervention challenging when one is faced with correlated binary end-points in observational studies is a challenging task, and it is even more The statistical literature on an...Identifying the causal impact of＇ some intervention challenging when one is faced with correlated binary end-points in observational studies is a challenging task, and it is even more The statistical literature on analyzing such data is well documented. Dependence between observations from the same study subject in correlated data renders invalid the usual chi-square tests of independence and inflates the variance ofparameter estimates. Disaggregated approaches such as hierarchical linear models which are able to adjust for individual level covariate：s are favoured in the analysis of such data, thereby gaining power over aggregated and individual-level analyses. In this article the authors, therefore, address the issue of analyzing correlated data with dichotomous end-points by using hierarchical logistic regression, a generalization of the standard logistic regression model for independent outcomes.展开更多
For all-sky infrared radiance assimilation,the heteroscedasticity and non-Gaussian behavior of observation-minusbackground(OMB)departures are two major difficulties.The Geer–Bauer observation error inflation(GBOEI)sc...For all-sky infrared radiance assimilation,the heteroscedasticity and non-Gaussian behavior of observation-minusbackground(OMB)departures are two major difficulties.The Geer–Bauer observation error inflation(GBOEI)scheme is a universal way to handle the issues.However,it fails to take into account the consistency between model and observation,resulting in unreasonably large observation errors where the simulations agree with the observations.Thus,this study modifies the GBOEI scheme to rationalize the observation errors in such areas.With Advanced Himawari Imager water vapor channel data,the test results show that the normalized OMB with the new observation error approach leads to more Gaussian form than the GBOEI method and constant observation errors.Hence,the assimilation experiments with the new scheme produce better brightness temperature analysis than other methods,and also improve temperature and humidity analysis.Furthermore,a real case experiment of Typhoon Lekima(2019)with the new observation error scheme exhibits more accuracy,especially in track prediction,and substantial error reductions in wind,temperature,and humidity forecasts are also obtained.Meanwhile,5-day 6-hour cycling experiments in the real case of Typhoon Lekima(2019)with the new observation error scheme confirm that the new method does not introduce extra imbalance compared to the experiment with constant observation errors;plus,more accurate typhoon forecasts can also be obtained in both the analysis and forecast,especially in track prediction.展开更多
Wavelet transform method is applied to measure time-frequency distribution characteristics of digital deformation data and noise. Based on the characteristics of primary modulus and stochastic white noise discriminati...Wavelet transform method is applied to measure time-frequency distribution characteristics of digital deformation data and noise. Based on the characteristics of primary modulus and stochastic white noise discrimination factor of wavelet decomposition, we analyze the variation rule of normal background and noise data from Shandong digital deformation observation data. The research results indicate that: a) 1/4 daily wave, semi-diurnal tide wave, daily wave and half lunar wave and so on quasi-periodic signal exist in the detail decomposing signal of wavelet when scale are equal to 2, 3 and 4; b) The amplitude of detail decomposing signal is the biggest when scale is equal to 3; c) The detail decomposing signal contains mainly noise corresponding to scale 1 and 5, respectively; d) We may trace the abnormal precursory which is related to earthquake by analyzing non-earthquake wavelet decomposing signal whose scale is specified from digital deformation observation data.展开更多
A superconducting gravimeter (SG, model TT70#016, GWR Instruments) was deployed for the first time in Antarctica in 1992 at Syowa Station. Observations began in April 1993. Although the SG was equipped with a 10 K cry...A superconducting gravimeter (SG, model TT70#016, GWR Instruments) was deployed for the first time in Antarctica in 1992 at Syowa Station. Observations began in April 1993. Although the SG was equipped with a 10 K cryocooler, its liquid helium (LHe) required refilling twice a year to maintain its superconducting state. The LHe was produced by a separate helium liquefier. After continuous gravity measurement with the SG for 11 years, it was replaced by a second SG (CT#043) with a 4 K cryocooler in December 2003 in order to reduce loads of person in charge for LHe production. Because the manufacturer could not supply a replacement 4 K cryocooler, this SG ceased measurement in November 2009. In January 2010, a new superconducting gravimeter (OSG#058) was installed and had recorded high-quality gravity time series with data acquired every second for more than five years without interruption. Because the personal computer (PC) controlling the observation and data acquisition is connected with PCs in Japan through an Intelsat satellite communication link, we can check the status of observations in real time. It is also possible to fix remotely certain problems with the gravimeter. The observed gravity data are transferred daily to a data server in Japan. Also included in the upload are diagnostic data of the gravimeter such as the temperature of the coldhead and environmental data such as atmospheric pressure. Plots of the daily data are publicly available. The raw data with a 1 s sampling interval are also released to registered researchers. The released gravity time series along with the environmental data are greatly useful for investigating solid earth dynamics especially in the long period bands. We provide necessary information to use these long-range data sets.展开更多
With the development of meteorological services, there are more and more types of real-time observation data, and the timeliness requirements are getting higher and higher. The monitoring methods of existing meteorolo...With the development of meteorological services, there are more and more types of real-time observation data, and the timeliness requirements are getting higher and higher. The monitoring methods of existing meteorological observation data transmission can no longer meet the needs. This paper proposes a new monitoring model, namely the “integrated monitoring model” for provincial meteorological observation data transmission. The model can complete the whole network monitoring of meteorological observation data transmission process. Based on this model, the integrated monitoring system for meteorological observation data transmission in Guangdong Province is developed. The system uses Java as the programming language, and integrates J2EE, Hibernate, Quartz, Snmp4j and Slf4j frameworks, and uses Oracle database as the data storage carrier, following the MVC specification and agile development concept. The system development uses four key technologies, including simple network management protocol, network connectivity detection technology, remote host management technology and thread pool technology. The integrated monitoring system has been put into business application. As a highlight of Guangdong’s meteorological modernization, it has played an active role in many major meteorological services.展开更多
Due to the limitation of data sources, the application of Distributed Hydrological Models (DHMs) using earth observation data to research water resources is necessary. In this study, the BTOPMC (Block-wise use of TOPM...Due to the limitation of data sources, the application of Distributed Hydrological Models (DHMs) using earth observation data to research water resources is necessary. In this study, the BTOPMC (Block-wise use of TOPMODEL) model was applied for 2 basins in the tropical monsoon region. This is the first time that the land cover map of the CCI (Climate Change Initiative Land Cover Team) was prepared for input data instead of IGBP (International Geosphere-Biosphere Programme) land cover map as proposed in the demo version of the BTOPMC model. The calibration and validation results showed that the Nash-Sutcliffe coefficients for daily stream discharge were 77.5% and 68.7% at Cung Son station (Ba basin). The Nash-Sutcliffe coefficients for daily stream discharge were 79.4% and 69.0% at Binh Tuong station (Kone basin), respectively. Because of a stop in measuring the discharge at Binh Tuong station in 2007, this model was applied to simulate discharge during the period of 2008-2015. Furthermore, the effect of land cover on discharge at Cung Son station was considered. The annual discharge in 2010 at Cung Son decreased 8 m3/s in the comparison between two scenarios (land cover of 2000 and 2010). According to this result, it is possible to propose a wide application range of the DHMs model to the tropical monsoon river basins using earth observation data.展开更多
Research and application of big data mining,at present,is a hot issue. This paper briefly introduces the basic ideas of big data research, analyses the necessity of big data application in earthquake precursor observa...Research and application of big data mining,at present,is a hot issue. This paper briefly introduces the basic ideas of big data research, analyses the necessity of big data application in earthquake precursor observation,and probes certain issues and solutions when applying this technology to work in the seismic-related domain. By doing so,we hope it can promote the innovative use of big data in earthquake precursor observation data analysis.展开更多
Aiming at improving the observation uncertainty caused by limited accuracy of sensors,and the uncertainty of observation source in clutters,through the dynamic combination of ensemble Kalman filter(EnKF) and probabili...Aiming at improving the observation uncertainty caused by limited accuracy of sensors,and the uncertainty of observation source in clutters,through the dynamic combination of ensemble Kalman filter(EnKF) and probabilistic data association(PDA),a novel probabilistic data association algorithm based on ensemble Kalman filter with observation iterated update is proposed.Firstly,combining with the advantages of data assimilation handling observation uncertainty in EnKF,an observation iterated update strategy is used to realize optimization of EnKF in structure.And the object is to further improve state estimation precision of nonlinear system.Secondly,the above algorithm is introduced to the framework of PDA,and the object is to increase reliability and stability of candidate echo acknowledgement.In addition,in order to decrease computation complexity in the combination of improved EnKF and PDA,the maximum observation iterated update mechanism is applied to the iteration of PDA.Finally,simulation results verify the feasibility and effectiveness of the proposed algorithm by a typical target tracking scene in clutters.展开更多
Based on the diurnal consecutively observed data in the offshore area of Jiaonan in 2005, the paper tries to make a preliminary analysis of the specificity of ocean currents, tidal current property and residual curren...Based on the diurnal consecutively observed data in the offshore area of Jiaonan in 2005, the paper tries to make a preliminary analysis of the specificity of ocean currents, tidal current property and residual current property in the area in observing dates. Then on the basis of observed data analysis and by employing the split-step method, the paper conducts a numerical simulation of the tidal current field, which can show the M2 tidal constituent tidal wave system, current ellipse distribution, maximum current velocity distribution and time-dependent current field. The calculated results agree well with the observed data, which can on the one hand reflect the basic specificities of temporal and spatial distribution of the M2 tidal constituent current field to some extent, and, on the other hand, offer more information about the hydrodynamic condition. So the paper would provide a scientific basis for the making of sea environment protection plans in the offshore area of Jiaonan under certain conditions.展开更多
Cloud microphysical property retrievals from the active microwave instrument on a satellite require the cloud droplet size distribution obtained from aircraft observations as a priori data in the iteration procedure.T...Cloud microphysical property retrievals from the active microwave instrument on a satellite require the cloud droplet size distribution obtained from aircraft observations as a priori data in the iteration procedure.The cloud lognormal size distributions derived from 12 flights over Beijing,China,in 2008-09 were characterized to evaluate and improve regional CloudSat cloud water content retrievals.We present the distribution parameters of stratiform cloud droplet （diameter ＜500 tm and ＜1500 μm） and discuss the effect of large particles on distribution parameter fitting.Based on three retrieval schemes with different lognormal size distribution parameters,the vertical distribution of cloud liquid and ice water content were derived and then compared with the aircraft observations.The results showed that the liquid water content （LWC） retrievals from large particle size distributions were more consistent with the vertical distribution of cloud water content profiles derived from in situ data on 25 September 2006.We then applied two schemes with different a priori data derived from flight data to CloudSat overpasses in northern China during April-October in 2008 and 2009.The CloudSat cloud water path （CWP） retrievals were compared with Moderate Resolution Imaging Spectroradiometer （MODIS） liquid water path （LWP） data.The results indicated that considering a priori data including large particle size information can significantly improve the consistency between the CloudSat CWP and MODIS CWP.These results strongly suggest that it is necessary to consider particles with diameters greater than 50 tm in CloudSat LWC retrievals.展开更多
Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolu...Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.展开更多
基金The National Natural Science Foundation under contract No.41621064the Science and Technology Basic Work of the Ministry of Science and Technology of China under contract No.2012FY112300the Public Science and Technology Research Funds Projects of Ocean under contract No.201005033
文摘This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The developments of associated data products and data applications for use in the fields of ocean, atmosphere, and climate research are discussed, particularly those related to tropical cyclones （typhoons）, ocean circulation, mesoscale eddies, turbulence, oceanic heat/salt storage and transportation, water masses, and operational oceanic/atmospheric/climatic forecasts and predictions. Finaliy, the challenges and opportunities involved in the long-term maintenance and sustained development of the China Argo ocean observation network are outlined. Discussion also focuses on the necessity for increasing the number of floats in the Indian Ocean and for expanding the regional Argo observation network in the South China Sea, together with the importance of promoting the use of Argo data by the maritime countries of Southeast Asia and India.
基金funded by the International Cooperation and Exchanges National Natural Science Foundation of China (41120114001)
文摘Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and chemical parameters on a global scale.Earth observation data has the 4V features(volume,variety,veracity,and velocity) of big data that are suitable for climate change research.Moreover,the large amount of data available from scientific satellites plays an important role.This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research,such as synchronous satelliteeaerialeground observation experiments,which provide extremely large and abundant datasets; Earth observational sensitive factors(e.g.,glaciers,lakes,vegetation,radiation,and urbanization); and global environmental change information and simulation systems.With the era of global environment change dawning,Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking.Inevitably,Earth observation big data will encounter opportunities and challenges brought about by global climate change.
基金The Open Fund of State Key Laboratory of Satellite Ocean Environment Dynamics under contract No.SOED1402the Youth Science and Technology Foundation of East China Sea Branch,SOA under contract No.201624
文摘Sea surface temperature(SST)data obtained from coastal stations in Jiangsu,China during 20102014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles,including the correlation with the variation of the tide.Quality control of data includes the validation of extreme values and checking of hourly values based on temporally adjacent data points,with 0.15℃/h considered a suitable threshold for detecting abnormal values.The diurnal variation amplitude of the SST data is greater in spring and summer than in autumn and winter.The diurnal variation of SST has bimodal structure on most days,i.e.,SST has a significant semidiurnal cycle.Moreover,the semidiurnal cycle of SST is negatively correlated with the tidal data from March to August,but positively correlated with the tidal data from October to January.Little correlation is detected in the remaining months because of the weak coastal offshore SST gradients.The quality control and understanding of coastal SST data are particularly relevant with regard to the validation of indirect measurements such as satellite-derived data.
基金supported by the National Key Research and Development Program of China(Grants No.2016YFC0402706 and 2016YFC0402710)the National Natural Science Foundation of China(Grants No.51709046 and41323001)the Open Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University(Grant No.2015490311)
文摘An observation operator is a bridge linking the system state vector and observations in a data assimilation system. Despite its importance, the degree to which an observation operator influences the performance of data assimilation methods is still poorly understood. This study aimed to analyze the influences of linear and nonlinear observation operators on the sequential data assimilation through soil temperature simulation using the unscented particle filter(UPF) and the common land model. The linear observation operator between unprocessed simulations and observations was first established. To improve the correlation between simulations and observations, both were processed based on a series of equations. This processing essentially resulted in a nonlinear observation operator. The linear and nonlinear observation operators were then used along with the UPF in three assimilation experiments: an hourly in situ soil surface temperature assimilation, a daily in situ soil surface temperature assimilation, and a moderate resolution imaging spectroradiometer(MODIS) land surface temperature(LST) assimilation. The results show that the filter improved the soil temperature simulation significantly with the linear and nonlinear observation operators. The nonlinear observation operator improved the UPF's performance more significantly for the hourly and daily in situ observation assimilations than the linear observation operator did, while the situation was opposite for the MODIS LST assimilation. Because of the high assimilation frequency and data quality, the simulation accuracy was significantly improved in all soil layers for hourly in situ soil surface temperature assimilation, while the significant improvements of the simulation accuracy were limited to the lower soil layers for the assimilation experiments with low assimilation frequency or low data quality.
基金Young Meteorological Research of Jiangsu Provincial Meteorological Bureau(Q201611)Key Scientific Research Projects of Jiangsu Provincial Meteorological Bureau(KZ201605)+1 种基金Natural Science Foundation of Jiangsu Province(BK20161074)Beijige Fund of Jiangsu Institute of Meteorological Sciences(BJG201512)
文摘To reduce the spatial correlation of representation error in observations and computational complexity, we propose a thinning scheme that can extract typical observations within a certain range. This scheme is applied to the Global/Regional Assimilation and Prediction System(GRAPES) with three-dimensional variation(3 DVAR) to study the effect of the thinning radius on the assimilation results. The assimilation experiments indicate that when the ratio of the model resolution to the observational resolution is 1:3, the simulated results for precipitation are relatively good and have a relatively high equitable threat score(ETS). Moreover, the analysis errors in the temperature and the specific humidity are the smallest, the dependence of the norm gradient vector of the objective function on the number of iterations is slow, gentle, and close to 0, and the minimization results in improved conditions.
文摘With the development of wireless communication technology,cyber physical systems are applied in various fields such as industrial production and infrastructure,where lots of information exchange brings cyber security threats to the systems.From the perspective of system identification with binary-valued observations,we study the optimal attack problem when the system is subject to both denial of service attacks and data tampering attacks.The packet loss rate and the data tampering rate caused by the attack is given,and the estimation error is derived.Then the optimal attack strategy to maximize the identification error with the least energy is described as a min–max optimization problem with constraints.The explicit expression of the optimal attack strategy is obtained.Simulation examples are presented to verify the effectiveness of the main conclusions.
基金Supported by the National Basic Research Program of China (973 Program)(No. 2011CB403504)the Knowledge Innovation Program of Chinese Academy of Sciences (Nos. KZCX2-YW-Q11-02, KZCX2-YW-Y202)the National Natural Science Foundation of China (Nos. 40830851, 41006011)
文摘Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms that QuikSCAT estimates of wind speed and direction are generally accurate, except for the extremes of high wind speeds (>13.8m/s) and very low wind speeds (<1.5m/s) where direction is poorly predicted. In-situ observations show that the summer monsoon in the northern SCS starts between May 6 and June 1. From March 13, 2010 to August 31, 2010, comparisons of sea surface temperature (SST) and rainfall from AMSR-E with data from a buoy located at Xisha Islands, as well as wind measurements derived from ASCAT and observations from an automatic weather station show that QuikSCAT, ASCAT and AMSR-E data are good enough for research. It is feasible to optimize the usage of remote-sensing data if validated with in-situ measurements. Remarkable changes were observed in wind, barometric pressure, humidity, outgoing longwave radiation (OLR), air temperature, rainfall and SST during the monsoon onset. The eastward shift of western Pacific subtropical high and the southward movement of continental cold front preceded the monsoon onset in SCS. The starting dates of SCS summer monsoon indicated that the southwest monsoon starts in the Indochinese Peninsula and forms an eastward zonal belt, and then the belt bifurcates in the SCS, with one part moving northeastward into the tropical western North Pacific, and another southward into western Kalimantan. This largely determined the pattern of the SCS summer monsoon. Wavelet analysis of zonal wind and OLR at Xisha showed that intra-seasonal variability played an important role in the summer. This work improves the accuracy of the amplitude of intra-seasonal and synoptic variation obtained from remote-sensed data.
基金National Key R&D Program of China(2017YFC1502102,2018YFC1506802)National Natural Science Foundation of China(41675102)。
文摘Aircraft Meteorological Data Relay(AMDAR)observations have been widely used in numerical weather prediction(NWP)because of its high spatiotemporal resolution.The observational error of AMDAR is influenced by aircraft flight altitude and atmospheric condition.In this study,the wind speed and altitude dependent observational error of AMDAR is estimated.The statistical results show that the temperature and the observational error in wind speeds slightly decrease as altitude increases,and the observational error in wind speed increases as wind speed increases.Pseudo single AMDAR observation assimilation tests demonstrate that the wind speed and altitude dependent observational error can provide more reasonable analysis increment.Furthermore,to assess the performance of wind speed and altitude dependent observational error on data assimilation and forecasting,two-month 3-hourly cycling data assimilation and forecast experiments based on the Weather Research and Forecasting Model(WRF)and its Data Assimilation system(WRFDA)are performed for the period during 1 September-31 October,2017.The results of the two-month 3-hourly cycling experiments indicate that new observational error improves analysis and forecast of wind field and geo-potential height,and has slight improvements on temperature.The Fractions Skill Score(FSS)of the 6-h accumulated precipitation shows that new wind speed and altitude dependent observational error leads to better precipitation forecast skill than the default observational error in the WRFDA does.
文摘Identifying the causal impact of＇ some intervention challenging when one is faced with correlated binary end-points in observational studies is a challenging task, and it is even more The statistical literature on analyzing such data is well documented. Dependence between observations from the same study subject in correlated data renders invalid the usual chi-square tests of independence and inflates the variance ofparameter estimates. Disaggregated approaches such as hierarchical linear models which are able to adjust for individual level covariate：s are favoured in the analysis of such data, thereby gaining power over aggregated and individual-level analyses. In this article the authors, therefore, address the issue of analyzing correlated data with dichotomous end-points by using hierarchical logistic regression, a generalization of the standard logistic regression model for independent outcomes.
基金funded by the National Natural Science Foundation of China(Grant Nos.42192553 and 41805071)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX24_1413)the High Performance Computing Center of Nanjing University of Information Science&Technology for their support of this work。
文摘For all-sky infrared radiance assimilation,the heteroscedasticity and non-Gaussian behavior of observation-minusbackground(OMB)departures are two major difficulties.The Geer–Bauer observation error inflation(GBOEI)scheme is a universal way to handle the issues.However,it fails to take into account the consistency between model and observation,resulting in unreasonably large observation errors where the simulations agree with the observations.Thus,this study modifies the GBOEI scheme to rationalize the observation errors in such areas.With Advanced Himawari Imager water vapor channel data,the test results show that the normalized OMB with the new observation error approach leads to more Gaussian form than the GBOEI method and constant observation errors.Hence,the assimilation experiments with the new scheme produce better brightness temperature analysis than other methods,and also improve temperature and humidity analysis.Furthermore,a real case experiment of Typhoon Lekima(2019)with the new observation error scheme exhibits more accuracy,especially in track prediction,and substantial error reductions in wind,temperature,and humidity forecasts are also obtained.Meanwhile,5-day 6-hour cycling experiments in the real case of Typhoon Lekima(2019)with the new observation error scheme confirm that the new method does not introduce extra imbalance compared to the experiment with constant observation errors;plus,more accurate typhoon forecasts can also be obtained in both the analysis and forecast,especially in track prediction.
基金Natural Science Foundation of Shandong Province (Y2000E08) the bargain item of China Earthquake Administration in the year 2002.
文摘Wavelet transform method is applied to measure time-frequency distribution characteristics of digital deformation data and noise. Based on the characteristics of primary modulus and stochastic white noise discrimination factor of wavelet decomposition, we analyze the variation rule of normal background and noise data from Shandong digital deformation observation data. The research results indicate that: a) 1/4 daily wave, semi-diurnal tide wave, daily wave and half lunar wave and so on quasi-periodic signal exist in the detail decomposing signal of wavelet when scale are equal to 2, 3 and 4; b) The amplitude of detail decomposing signal is the biggest when scale is equal to 3; c) The detail decomposing signal contains mainly noise corresponding to scale 1 and 5, respectively; d) We may trace the abnormal precursory which is related to earthquake by analyzing non-earthquake wavelet decomposing signal whose scale is specified from digital deformation observation data.
文摘A superconducting gravimeter (SG, model TT70#016, GWR Instruments) was deployed for the first time in Antarctica in 1992 at Syowa Station. Observations began in April 1993. Although the SG was equipped with a 10 K cryocooler, its liquid helium (LHe) required refilling twice a year to maintain its superconducting state. The LHe was produced by a separate helium liquefier. After continuous gravity measurement with the SG for 11 years, it was replaced by a second SG (CT#043) with a 4 K cryocooler in December 2003 in order to reduce loads of person in charge for LHe production. Because the manufacturer could not supply a replacement 4 K cryocooler, this SG ceased measurement in November 2009. In January 2010, a new superconducting gravimeter (OSG#058) was installed and had recorded high-quality gravity time series with data acquired every second for more than five years without interruption. Because the personal computer (PC) controlling the observation and data acquisition is connected with PCs in Japan through an Intelsat satellite communication link, we can check the status of observations in real time. It is also possible to fix remotely certain problems with the gravimeter. The observed gravity data are transferred daily to a data server in Japan. Also included in the upload are diagnostic data of the gravimeter such as the temperature of the coldhead and environmental data such as atmospheric pressure. Plots of the daily data are publicly available. The raw data with a 1 s sampling interval are also released to registered researchers. The released gravity time series along with the environmental data are greatly useful for investigating solid earth dynamics especially in the long period bands. We provide necessary information to use these long-range data sets.
文摘With the development of meteorological services, there are more and more types of real-time observation data, and the timeliness requirements are getting higher and higher. The monitoring methods of existing meteorological observation data transmission can no longer meet the needs. This paper proposes a new monitoring model, namely the “integrated monitoring model” for provincial meteorological observation data transmission. The model can complete the whole network monitoring of meteorological observation data transmission process. Based on this model, the integrated monitoring system for meteorological observation data transmission in Guangdong Province is developed. The system uses Java as the programming language, and integrates J2EE, Hibernate, Quartz, Snmp4j and Slf4j frameworks, and uses Oracle database as the data storage carrier, following the MVC specification and agile development concept. The system development uses four key technologies, including simple network management protocol, network connectivity detection technology, remote host management technology and thread pool technology. The integrated monitoring system has been put into business application. As a highlight of Guangdong’s meteorological modernization, it has played an active role in many major meteorological services.
文摘Due to the limitation of data sources, the application of Distributed Hydrological Models (DHMs) using earth observation data to research water resources is necessary. In this study, the BTOPMC (Block-wise use of TOPMODEL) model was applied for 2 basins in the tropical monsoon region. This is the first time that the land cover map of the CCI (Climate Change Initiative Land Cover Team) was prepared for input data instead of IGBP (International Geosphere-Biosphere Programme) land cover map as proposed in the demo version of the BTOPMC model. The calibration and validation results showed that the Nash-Sutcliffe coefficients for daily stream discharge were 77.5% and 68.7% at Cung Son station (Ba basin). The Nash-Sutcliffe coefficients for daily stream discharge were 79.4% and 69.0% at Binh Tuong station (Kone basin), respectively. Because of a stop in measuring the discharge at Binh Tuong station in 2007, this model was applied to simulate discharge during the period of 2008-2015. Furthermore, the effect of land cover on discharge at Cung Son station was considered. The annual discharge in 2010 at Cung Son decreased 8 m3/s in the comparison between two scenarios (land cover of 2000 and 2010). According to this result, it is possible to propose a wide application range of the DHMs model to the tropical monsoon river basins using earth observation data.
基金sponsored by the Earthquake Monitoring Special Project of "Precursor Observation Data Mining",Key Laboratory of Crustal Dynamics,Institute of Crustal Dynamics,China Earthquake Administration
文摘Research and application of big data mining,at present,is a hot issue. This paper briefly introduces the basic ideas of big data research, analyses the necessity of big data application in earthquake precursor observation,and probes certain issues and solutions when applying this technology to work in the seismic-related domain. By doing so,we hope it can promote the innovative use of big data in earthquake precursor observation data analysis.
基金Supported by the National Nature Science Foundation of China(No.61300214)the Science and Technology Innovation Team Support Plan of Education Department of Henan Province(No.13IRTSTHN021)+5 种基金the National Natural Science Foundation of Henan Province(No.132300410148)the Science and Technology Research Key Project of Education Department of Henan Province(No.13A413066)the Postdoctoral Science Foundation of China(No.2014M551999)the Funding Scheme of Young Key Teacher of Henan Province Universities(No.2013GGJS-026)the Postdoctoral Fund of Henan Province(No.2013029)the Outstanding Young Cultivation Foundation of Henan University(No.0000A40366)
文摘Aiming at improving the observation uncertainty caused by limited accuracy of sensors,and the uncertainty of observation source in clutters,through the dynamic combination of ensemble Kalman filter(EnKF) and probabilistic data association(PDA),a novel probabilistic data association algorithm based on ensemble Kalman filter with observation iterated update is proposed.Firstly,combining with the advantages of data assimilation handling observation uncertainty in EnKF,an observation iterated update strategy is used to realize optimization of EnKF in structure.And the object is to further improve state estimation precision of nonlinear system.Secondly,the above algorithm is introduced to the framework of PDA,and the object is to increase reliability and stability of candidate echo acknowledgement.In addition,in order to decrease computation complexity in the combination of improved EnKF and PDA,the maximum observation iterated update mechanism is applied to the iteration of PDA.Finally,simulation results verify the feasibility and effectiveness of the proposed algorithm by a typical target tracking scene in clutters.
文摘Based on the diurnal consecutively observed data in the offshore area of Jiaonan in 2005, the paper tries to make a preliminary analysis of the specificity of ocean currents, tidal current property and residual current property in the area in observing dates. Then on the basis of observed data analysis and by employing the split-step method, the paper conducts a numerical simulation of the tidal current field, which can show the M2 tidal constituent tidal wave system, current ellipse distribution, maximum current velocity distribution and time-dependent current field. The calculated results agree well with the observed data, which can on the one hand reflect the basic specificities of temporal and spatial distribution of the M2 tidal constituent current field to some extent, and, on the other hand, offer more information about the hydrodynamic condition. So the paper would provide a scientific basis for the making of sea environment protection plans in the offshore area of Jiaonan under certain conditions.
基金supported by China public science and technology research funds projects of meteorology (Grant No. GYHY201406015)the Chinese Academy of Sciences (Grant No. XDA05040000)+3 种基金the National High-Tech R&D Program of China (Grant No. SQ2010AA1221583001)National Science Foundation program (Grant Nos. 41375024, 40775002, 41175020, and 41375008)the basic research program (Grant No. 2010CB950802)the NASA CloudSat project for making CloudSat data available to the scientific community
文摘Cloud microphysical property retrievals from the active microwave instrument on a satellite require the cloud droplet size distribution obtained from aircraft observations as a priori data in the iteration procedure.The cloud lognormal size distributions derived from 12 flights over Beijing,China,in 2008-09 were characterized to evaluate and improve regional CloudSat cloud water content retrievals.We present the distribution parameters of stratiform cloud droplet （diameter ＜500 tm and ＜1500 μm） and discuss the effect of large particles on distribution parameter fitting.Based on three retrieval schemes with different lognormal size distribution parameters,the vertical distribution of cloud liquid and ice water content were derived and then compared with the aircraft observations.The results showed that the liquid water content （LWC） retrievals from large particle size distributions were more consistent with the vertical distribution of cloud water content profiles derived from in situ data on 25 September 2006.We then applied two schemes with different a priori data derived from flight data to CloudSat overpasses in northern China during April-October in 2008 and 2009.The CloudSat cloud water path （CWP） retrievals were compared with Moderate Resolution Imaging Spectroradiometer （MODIS） liquid water path （LWP） data.The results indicated that considering a priori data including large particle size information can significantly improve the consistency between the CloudSat CWP and MODIS CWP.These results strongly suggest that it is necessary to consider particles with diameters greater than 50 tm in CloudSat LWC retrievals.
基金This work is supported by the National Key Research and Development Program of China[grant number 2018YFB2100501]the Key Research and Development Program of Yunnan province in China[grant number 2018IB023]+2 种基金the Research Project from the Ministry of Natural Resources of China[grant number 4201⁃⁃240100123]the National Natural Science Foundation of China[grant numbers 41771452,41771454,41890820,and 41901340]the Natural Science Fund of Hubei Province in China[grant number 2018CFA007].
文摘Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.
