Unmitigated tropospheric delay is one of the major error sources in precise point positioning(PPP).Precise Slant Tropospheric Delay(STD)estimation could help to provide cleaner observables for PPP,and improve its conv...Unmitigated tropospheric delay is one of the major error sources in precise point positioning(PPP).Precise Slant Tropospheric Delay(STD)estimation could help to provide cleaner observables for PPP,and improve its convergence,accuracy,and stability.STD is difficult to model accurately due to the rapid spatial and temporal variation of the water vapor in the troposphere.In the traditional approach,the STD is mapped from the zenith direction,which assumes a spherically symmetric local tropospheric profile and has limitations.In this paper,a new approach of directly estimating the STD from high resolution numerical weather modeling(NWM)products is introduced.This approach benefits from the best available meteorological information to improve real time STD estimation,with the RMS residual lower than 3.5 cm above 15°elevation,and 2 cm above 30°.Therefore,the new method can provide sufficient accuracy to improve PPP convergence time.To improve the performance of the new method in highly variable tropospheric conditions,a correction scheme is proposed which combines NWM information with multi-GNSS observations from a network of local continuously operating reference stations.It is demonstrated through a case study that this correction scheme is quite effective in reducing the STD estimation residuals and PPP convergence time.展开更多
The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Lium...The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly-used microphysics scheme(WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme,it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.展开更多
Model error is one of the key factors restricting the accuracy of numerical weather prediction （NWP）. Considering the continuous evolution of the atmosphere, the observed data （ignoring the measurement error） can ...Model error is one of the key factors restricting the accuracy of numerical weather prediction （NWP）. Considering the continuous evolution of the atmosphere, the observed data （ignoring the measurement error） can be viewed as a series of solutions of an accurate model governing the actual atmosphere. Model error is represented as an unknown term in the accurate model, thus NWP can be considered as an inverse problem to uncover the unknown error term. The inverse problem models can absorb long periods of observed data to generate model error correction procedures. They thus resolve the deficiency and faultiness of the NWP schemes employing only the initial-time data. In this study we construct two inverse problem models to estimate and extrapolate the time-varying and spatial-varying model errors in both the historical and forecast periods by using recent observations and analogue phenomena of the atmosphere. Numerical experiment on Burgers＇ equation has illustrated the substantial forecast improvement using inverse problem algorithms. The proposed inverse problem methods of suppressing NWP errors will be useful in future high accuracy applications of NWP.展开更多
A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale ...A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.展开更多
Through the analysis of core descriptions, well-logs, seismic data, geochemical data and structural settings of the volcanic rock of the Yingcheng Formation in the Xujiaweizi fault depression, Songliao Basin, and the ...Through the analysis of core descriptions, well-logs, seismic data, geochemical data and structural settings of the volcanic rock of the Yingcheng Formation in the Xujiaweizi fault depression, Songliao Basin, and the geological section of the Yingcheng Formation in the southeast uplift area, this work determined the existence of volcanic weathering crust exists in the study area. The identification marks on the volcanic weathering crust can be recognized on the scale of core, logging, seismic, geochemistry, etc. In the study area, the structure of this crust is divided into clay layer, leached zone, fracture zone and host rocks, which are 5-118 m thick （averaging 27.5 m）. The lithology of the weathering crust includes basalt, andesite, rhyolite and volcanic breccia, and the lithofacies are igneous effusive and extrusive facies. The volcanic weathering crusts are clustered together in the Dashen zone and the middle of the Xuzhong zone, whereas in the Shengshen zone and other parts of the Xuzhong zone, they have a relatively scattered distribution. It is a major volcanic reservoir bed, which covers an area of 2104.16 km2. According to the geotectonic setting of the Songliao Basin, the formation process of the weathering crust is complete. Combining the macroscopic and microscopic features of the weathering crust of the Yingcheng Formation in Xujiaweizi with the logging and three-dimensional seismic sections, we established a developmental model of the paleo uplift and a developmental model of the slope belt that coexists with the sag on the Xujiaweizi volcanic weathering crust. In addition, the relationship between the volcanic weathering crust and the formation and distribution of the oil/gas reservoir is discussed.展开更多
The distinct element method（DEM） incorporated with a novel bond contact model was applied in this paper to shed light on the microscopic physical origin of macroscopic behaviors of weathered rock, and to achieve the...The distinct element method（DEM） incorporated with a novel bond contact model was applied in this paper to shed light on the microscopic physical origin of macroscopic behaviors of weathered rock, and to achieve the changing laws of microscopic parameters from observed decaying properties of rocks during weathering. The changing laws of macroscopic mechanical properties of typical rocks were summarized based on the existing research achievements. Parametric simulations were then conducted to analyze the relationships between macroscopic and microscopic parameters, and to derive the changing laws of microscopic parameters for the DEM model. Equipped with the microscopic weathering laws, a series of DEM simulations of basic laboratory tests on weathered rock samples was performed in comparison with analytical solutions. The results reveal that the relationships between macroscopic and microscopic parameters of rocks against the weathering period can be successfully attained by parametric simulations. In addition, weathering has a significant impact on both stressestrain relationship and failure pattern of rocks.展开更多
In this report, we summarize the needs of space weather models, and recommend that developing operational prediction models, rather than transitioning from research to operation, is a more feasible and critical way fo...In this report, we summarize the needs of space weather models, and recommend that developing operational prediction models, rather than transitioning from research to operation, is a more feasible and critical way for space weather services in the near future. Operational models for solar wind speed, geomagnetic indices, magnetopause, plasma sheet energetic electrons, inner boundary of ion plasma sheet, energetic electrons in outer radiation belt, and thermospheric density at low Earth orbit, have been developed and will be introduced briefly here. Their applications made a big progress in space weather services during the past two years in China.展开更多
We used a Lake Shira numerical model to estimate the response of the ecosystem of a saline meromictic lake to variations in weather parameters during the growing season. The sensitivity analysis of the model suggests ...We used a Lake Shira numerical model to estimate the response of the ecosystem of a saline meromictic lake to variations in weather parameters during the growing season. The sensitivity analysis of the model suggests that compared to other external(nutrient inflows) and internal(spring biomasses of food-web components) factors, weather parameters are among the most influential for both mixolimnetic(phyto-and zooplankton) and monimolimnetic(purple sulfur bacteria, sulfur reducing bacteria and hydrogen sulfide) food-web components. Calculations with different weather scenarios shows how changes in the water temperature and mixing depth af fect mixolimnetic and monimolimnetic food-web components and the depth of the oxic-anoxic interface in a meromictic lake. When weather forcing stimulates an increase in the biomass of food-web components in the mixolimnion, it produces cascading effects that lead to three results: 1) a higher content of detritus in the water column; 2) a higher content of hydrogen sulfide in the monimolimnion; 3) raising of the oxic-anoxic interface closer to the water-air surface. This cascading effect is complicated by the negative correlation between two light dependent primary producers located at diff erent depths—phytoplankton in the mixolimnion and purple sulfur bacteria at the oxic-anoxic interface. Thus, weather conditions that stimulate higher phytoplankton biomass are associated with a higher detritus content and lower biomass of purple sulfur bacteria, a higher content of hydrogen sulfide and a shallower oxic-anoxic interface. The same weather conditions(higher wind, lower cloud cover, and lower air temperature) promote a scenario of less stable thermal stratification. Thus, our calculations suggest that weather parameters during the summer season strongly control the mixing depth, water temperature and the mixolimnetic food web. An effect of biogeochemical and physical interactions on the depth of the oxicanoxic interface is also detectable. However, intra-and interannual climate and weather effects will be more important for the control of meromixis stability.展开更多
The aim of this work is to investigate the influence of rainy weather on traffic accidents of a freeway. The micro-scale driving behaviors in rainy weather and possible vehicle rear-end and sideslip accidents are anal...The aim of this work is to investigate the influence of rainy weather on traffic accidents of a freeway. The micro-scale driving behaviors in rainy weather and possible vehicle rear-end and sideslip accidents are analyzed. An improved CA model of two lanes one-way freeway is presented, where some vehicle accidents will occur when the necessary conditions are simultaneously satisfied. The characteristics of traffic flow under different rainfall intensities are discussed and the accident probabilities are analyzed via the simulation experiments by using variable speed limit （VSL） and incoming flow control. The results indicate that the measures are effective especially during heavy rainstorms or short-time heavy rainfall. According to different rainfall intensities, an appropriate strategy should be adopted in order to reduce the probability of vehicle accidents and enhance traffic flux as well.展开更多
Groundwater yield in the Kenya Rift is highly unsustainable owing to geological variability.In this study,field hydraulic characterization was performed by using geoelectric approaches.The relations between electrical...Groundwater yield in the Kenya Rift is highly unsustainable owing to geological variability.In this study,field hydraulic characterization was performed by using geoelectric approaches.The relations between electrical-hydraulic(eh)conductivities were modeled hypothetically and calibrated empirically.Correlations were based on the stochastic models and field-scale hydraulic parameters were contingent on pore-level parameters.By considering variation in pore-size distributions over eh conduction interval,the relations were scaled-up for use at aquifer-level.Material-level electrical conductivities were determined by using Vertical Electrical Survey and hydraulic conductivities by analyzing aquifer tests of eight boreholes in the Olbanita aquifer located in Kenya rift.VES datasets were inverted by using the computer code IP2Win.The main result is that ln T=0.537(ln Fa)+3.695;the positive gradient indicating eh conduction through pore-surface networks and a proxy of weathered and clayey materials.An inverse(1/F-K)correlation is observed.Hydraulic parameters determined using such approaches may possibly contribute significantly towards sustainable yield management and planning of groundwater resources.展开更多
A traffic model based on the road surface conditions during adverse weather is presented. The surface of a road is affected by snow, compacted snow, and ice, which affects the traffic behavior. In this paper, a new ma...A traffic model based on the road surface conditions during adverse weather is presented. The surface of a road is affected by snow, compacted snow, and ice, which affects the traffic behavior. In this paper, a new macroscopic traffic flow model based on the transition velocity distribution is proposed which characterizes traffic alignment under adverse weather conditions. Two examples are considered to illustrate the effect of the transition velocity behavior on traffic velocity and density. Simulation results are presented which show that this model provides a more accurate characterization of traffic flow behavior than the well known Payne-Whitham model. The proposed model can be used to reduce accidents and improve road safety during adverse weather conditions.展开更多
Weather models are essential tools for checking of the effect of the weather elements in terms of their effect on the production of the crop. This research is an attempt to see the effect of only two variables i.e., t...Weather models are essential tools for checking of the effect of the weather elements in terms of their effect on the production of the crop. This research is an attempt to see the effect of only two variables i.e., temperature and rainfall for the division Faisalabad (semitropical region of Pakistan).The model fitted is of the linear form:the values of a,b, c have been found. The expected yield has been calculated by using the aridity indices (X1 and X2 ) and the result in the form of coefficient of determination R2 has been found equal to 0.166. The significance of the regression coefficient has been tested, which shows that the contribution to the yield from aridity index at germination and that at ripening is significant.The wheat yields are the results of a wide variety of variables, most of which show varying degree of relationship with one another, some positive and some negative in terms of output. These variables may be technology, fertilizers, pesticides, epidemics, kinds of seeds used, market price of crop and the area under cultivation etc, which can be the source of variation in the wheat yield. Since rainfall during germination and temperature at the ripening periods are the necessary factors for the yield of wheat, for this purpose these parameters have been studied in order to their contribution.展开更多
Identifying risk factors for road traffic injuries can be considered one of the main priorities of transportation agencies. More than 12,000 fatal work zone crashes were reported between 2000 and 2013. Despite recent ...Identifying risk factors for road traffic injuries can be considered one of the main priorities of transportation agencies. More than 12,000 fatal work zone crashes were reported between 2000 and 2013. Despite recent efforts to improve work zone safety, the frequency and severity of work zone crashes are still a big concern for transportation agencies. Although many studies have been conducted on different work zone safety-related issues, there is a lack of studies that investigate the effect of adverse weather conditions on work zone crash severity. This paper utilizes probit–classification tree, a relatively recent and promising combination of machine learning technique and conventional parametric model, to identify factors affecting work zone crash severity in adverse weather conditions using 8 years of work zone weatherrelated crashes (2006–2013) in Washington State. The key strength of this technique lies in its capability to alleviate the shortcomings of both parametric and nonparametric models. The results showed that both presence of traffic control device and lighting conditions are significant interacting variables in the developed complementary crash severity model for work zone weather-related crashes. Therefore, transportation agencies and contractors need to invest more in lighting equipment and better traffic control strategies at work zones, specifically during adverse weather conditions.展开更多
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,includ...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 is needed due to uncertainties brought by data assimilation.展开更多
Recently, as the oceanic activities are more and more frequently carried out, marine oil spill accidents bring to enormous harm to the economy and society in China, especially in the Offshore China. Marine oil spill i...Recently, as the oceanic activities are more and more frequently carried out, marine oil spill accidents bring to enormous harm to the economy and society in China, especially in the Offshore China. Marine oil spill is one kind of serious disasters which severely damages the marine environment. Aiming at the improvement of the emergency response system and response ability for the oil spill, the relative technologies on oil spill response are developed. This paper briefly introduces the developments and achievements of the oil spill numerical models, including the oil spill spreading model, the oil spill transport model, the oil particle model as well as the oil spill weathering model, which provide the theoretic criterions for the future work on the oil spill predicting and response.展开更多
The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared...The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared and analyzed in this paper. The satellite products, including CPC MORPHing technique（CMORPH）, TMPA-RT, and PERSIANN are all near-real-time retrieved with high temporal and spatial resolutions. The numerical weather model used in this paper for precipitation forecasting is WRF. The results show that all three satellite products can basically reproduce the rainfall pattern, distribution, timing, scale, and extreme values of the event, compared with gauge data. Their temporal and spatial correlation coefficients with gauge data are as high as about 0.6, which is statistically significant at 0.01 level. The performance of the forecasted results modeled with different spatial resolutions are not as good as the satellite-estimated results, although their correlation coefficients are still statistically significant at 0.05 level. From the total rainfall and extreme value time series for the domain, it is clear that, from the grid-to-grid perspective, the passive microwave-based CMORPH and TRMM products are more accurate than the infrared-based PERSIANN, while PERSIANN performs very well from the general point of view, especially when considering the whole domain or the whole convective precipitation system. The forecasted data — especially the highest resolution model domain data — are able to represent the total or mean precipitation very well in the research domain, while for extreme values the errors are large. This study suggests that satellite-retrieved and model-forecasted rainfall data are a useful complement to gauge data, especially for areas without gauge stations and areas not covered by weather radars.展开更多
Numerical weather simulation data usually comprises various meteorological variables, such as precipitation, temperature and pressure. In practical applications, data generated with several different numerical simulat...Numerical weather simulation data usually comprises various meteorological variables, such as precipitation, temperature and pressure. In practical applications, data generated with several different numerical simulation models are usually used together by forecasters to generate the final forecast. However, it is difficult for forecasters to obtain a clear view of all the data due to its complexity. This has been a great limitation for domain experts to take advantage of all the data in their routine work. In order to help explore the multi-variate and multi-model data, we propose a stamp based exploration framework to assist domain experts in analyzing the data. The framework is used to assist domain experts in detecting the bias patterns between numerical simulation data and observation data. The exploration pipeline originates from a single meteorological variable and extends to multiple variables under the guidance of a designed stamp board. Regional data patterns can be detected by analyzing distinctive stamps on the board or generating extending stamps using the Boolean set operations. Experiment results show that some meteorological phenomena and regional data patterns can be easily detected through the exploration. These can help domain experts conduct the data analysis efficiently and further guide forecasters in producing reliable weather forecast.展开更多
基金This study is carried out as part of the project Innovative Navigation using new GNSS Signals with Hybridized Technologies(iNsight),which is funded by the UK Engineering and Physical Sciences Research Council(EPSRC).
文摘Unmitigated tropospheric delay is one of the major error sources in precise point positioning(PPP).Precise Slant Tropospheric Delay(STD)estimation could help to provide cleaner observables for PPP,and improve its convergence,accuracy,and stability.STD is difficult to model accurately due to the rapid spatial and temporal variation of the water vapor in the troposphere.In the traditional approach,the STD is mapped from the zenith direction,which assumes a spherically symmetric local tropospheric profile and has limitations.In this paper,a new approach of directly estimating the STD from high resolution numerical weather modeling(NWM)products is introduced.This approach benefits from the best available meteorological information to improve real time STD estimation,with the RMS residual lower than 3.5 cm above 15°elevation,and 2 cm above 30°.Therefore,the new method can provide sufficient accuracy to improve PPP convergence time.To improve the performance of the new method in highly variable tropospheric conditions,a correction scheme is proposed which combines NWM information with multi-GNSS observations from a network of local continuously operating reference stations.It is demonstrated through a case study that this correction scheme is quite effective in reducing the STD estimation residuals and PPP convergence time.
基金Ministry of Science and Technology of China(2017YFC1501406)National Key Research and Development Plan Program of China(2017YFA0604500)CMA Youth Founding Program(Q201706&NWPC-QNJJ-201702)
文摘The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly-used microphysics scheme(WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme,it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.
基金Project supported by the Special Scientific Research Project for Public Interest(Grant No.GYHY201206009)the Fundamental Research Funds for the Central Universities,China(Grant Nos.lzujbky-2012-13 and lzujbky-2013-11)the National Basic Research Program of China(Grant Nos.2012CB955902 and 2013CB430204)
文摘Model error is one of the key factors restricting the accuracy of numerical weather prediction （NWP）. Considering the continuous evolution of the atmosphere, the observed data （ignoring the measurement error） can be viewed as a series of solutions of an accurate model governing the actual atmosphere. Model error is represented as an unknown term in the accurate model, thus NWP can be considered as an inverse problem to uncover the unknown error term. The inverse problem models can absorb long periods of observed data to generate model error correction procedures. They thus resolve the deficiency and faultiness of the NWP schemes employing only the initial-time data. In this study we construct two inverse problem models to estimate and extrapolate the time-varying and spatial-varying model errors in both the historical and forecast periods by using recent observations and analogue phenomena of the atmosphere. Numerical experiment on Burgers＇ equation has illustrated the substantial forecast improvement using inverse problem algorithms. The proposed inverse problem methods of suppressing NWP errors will be useful in future high accuracy applications of NWP.
基金jointly supported by the Main Direction Program of Knowledge Innovation of the Chinese Academy of Sciences(Grant No.KZCX2EW203)the National Key Basic Research Program of China(Grant No.2013CB430105)the National Department of Public Benefit Research Foundation(Grant No.GYHY201006031)
文摘A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.
基金supported by the National Natural Science Fund Project(grant No.41430322)the National Basic Research Program of China(grant No.2009CB219306)the Open Fund of the State Key Laboratory Base of Unconventional Oil and Gas Accumulation and Exploitation,Northeast Petroleum University(grant No.2010DS670083-201301)
文摘Through the analysis of core descriptions, well-logs, seismic data, geochemical data and structural settings of the volcanic rock of the Yingcheng Formation in the Xujiaweizi fault depression, Songliao Basin, and the geological section of the Yingcheng Formation in the southeast uplift area, this work determined the existence of volcanic weathering crust exists in the study area. The identification marks on the volcanic weathering crust can be recognized on the scale of core, logging, seismic, geochemistry, etc. In the study area, the structure of this crust is divided into clay layer, leached zone, fracture zone and host rocks, which are 5-118 m thick （averaging 27.5 m）. The lithology of the weathering crust includes basalt, andesite, rhyolite and volcanic breccia, and the lithofacies are igneous effusive and extrusive facies. The volcanic weathering crusts are clustered together in the Dashen zone and the middle of the Xuzhong zone, whereas in the Shengshen zone and other parts of the Xuzhong zone, they have a relatively scattered distribution. It is a major volcanic reservoir bed, which covers an area of 2104.16 km2. According to the geotectonic setting of the Songliao Basin, the formation process of the weathering crust is complete. Combining the macroscopic and microscopic features of the weathering crust of the Yingcheng Formation in Xujiaweizi with the logging and three-dimensional seismic sections, we established a developmental model of the paleo uplift and a developmental model of the slope belt that coexists with the sag on the Xujiaweizi volcanic weathering crust. In addition, the relationship between the volcanic weathering crust and the formation and distribution of the oil/gas reservoir is discussed.
基金funded by the National Basic Research Programs of China(Grant Nos.2011CB013504 and 2014CB046901)the National Funds for Distinguished Young Scientists of China(Grant No.51025932)the National Nature Science Foundation of China(Grant No.41372272)
文摘The distinct element method（DEM） incorporated with a novel bond contact model was applied in this paper to shed light on the microscopic physical origin of macroscopic behaviors of weathered rock, and to achieve the changing laws of microscopic parameters from observed decaying properties of rocks during weathering. The changing laws of macroscopic mechanical properties of typical rocks were summarized based on the existing research achievements. Parametric simulations were then conducted to analyze the relationships between macroscopic and microscopic parameters, and to derive the changing laws of microscopic parameters for the DEM model. Equipped with the microscopic weathering laws, a series of DEM simulations of basic laboratory tests on weathered rock samples was performed in comparison with analytical solutions. The results reveal that the relationships between macroscopic and microscopic parameters of rocks against the weathering period can be successfully attained by parametric simulations. In addition, weathering has a significant impact on both stressestrain relationship and failure pattern of rocks.
文摘In this report, we summarize the needs of space weather models, and recommend that developing operational prediction models, rather than transitioning from research to operation, is a more feasible and critical way for space weather services in the near future. Operational models for solar wind speed, geomagnetic indices, magnetopause, plasma sheet energetic electrons, inner boundary of ion plasma sheet, energetic electrons in outer radiation belt, and thermospheric density at low Earth orbit, have been developed and will be introduced briefly here. Their applications made a big progress in space weather services during the past two years in China.
文摘We used a Lake Shira numerical model to estimate the response of the ecosystem of a saline meromictic lake to variations in weather parameters during the growing season. The sensitivity analysis of the model suggests that compared to other external(nutrient inflows) and internal(spring biomasses of food-web components) factors, weather parameters are among the most influential for both mixolimnetic(phyto-and zooplankton) and monimolimnetic(purple sulfur bacteria, sulfur reducing bacteria and hydrogen sulfide) food-web components. Calculations with different weather scenarios shows how changes in the water temperature and mixing depth af fect mixolimnetic and monimolimnetic food-web components and the depth of the oxic-anoxic interface in a meromictic lake. When weather forcing stimulates an increase in the biomass of food-web components in the mixolimnion, it produces cascading effects that lead to three results: 1) a higher content of detritus in the water column; 2) a higher content of hydrogen sulfide in the monimolimnion; 3) raising of the oxic-anoxic interface closer to the water-air surface. This cascading effect is complicated by the negative correlation between two light dependent primary producers located at diff erent depths—phytoplankton in the mixolimnion and purple sulfur bacteria at the oxic-anoxic interface. Thus, weather conditions that stimulate higher phytoplankton biomass are associated with a higher detritus content and lower biomass of purple sulfur bacteria, a higher content of hydrogen sulfide and a shallower oxic-anoxic interface. The same weather conditions(higher wind, lower cloud cover, and lower air temperature) promote a scenario of less stable thermal stratification. Thus, our calculations suggest that weather parameters during the summer season strongly control the mixing depth, water temperature and the mixolimnetic food web. An effect of biogeochemical and physical interactions on the depth of the oxicanoxic interface is also detectable. However, intra-and interannual climate and weather effects will be more important for the control of meromixis stability.
基金supported by the National Natural Science Foundation of China(Grant No.50478088)the Natural Science Foundation of Hebei Province,China(Grant No.E2015202266)
文摘The aim of this work is to investigate the influence of rainy weather on traffic accidents of a freeway. The micro-scale driving behaviors in rainy weather and possible vehicle rear-end and sideslip accidents are analyzed. An improved CA model of two lanes one-way freeway is presented, where some vehicle accidents will occur when the necessary conditions are simultaneously satisfied. The characteristics of traffic flow under different rainfall intensities are discussed and the accident probabilities are analyzed via the simulation experiments by using variable speed limit （VSL） and incoming flow control. The results indicate that the measures are effective especially during heavy rainstorms or short-time heavy rainfall. According to different rainfall intensities, an appropriate strategy should be adopted in order to reduce the probability of vehicle accidents and enhance traffic flux as well.
基金funded by the Kenya Government through the National Research Fund
文摘Groundwater yield in the Kenya Rift is highly unsustainable owing to geological variability.In this study,field hydraulic characterization was performed by using geoelectric approaches.The relations between electrical-hydraulic(eh)conductivities were modeled hypothetically and calibrated empirically.Correlations were based on the stochastic models and field-scale hydraulic parameters were contingent on pore-level parameters.By considering variation in pore-size distributions over eh conduction interval,the relations were scaled-up for use at aquifer-level.Material-level electrical conductivities were determined by using Vertical Electrical Survey and hydraulic conductivities by analyzing aquifer tests of eight boreholes in the Olbanita aquifer located in Kenya rift.VES datasets were inverted by using the computer code IP2Win.The main result is that ln T=0.537(ln Fa)+3.695;the positive gradient indicating eh conduction through pore-surface networks and a proxy of weathered and clayey materials.An inverse(1/F-K)correlation is observed.Hydraulic parameters determined using such approaches may possibly contribute significantly towards sustainable yield management and planning of groundwater resources.
基金Project supported by Higher Education Commission,Pakistan/National Center of Big Data and Cloud Computing
文摘A traffic model based on the road surface conditions during adverse weather is presented. The surface of a road is affected by snow, compacted snow, and ice, which affects the traffic behavior. In this paper, a new macroscopic traffic flow model based on the transition velocity distribution is proposed which characterizes traffic alignment under adverse weather conditions. Two examples are considered to illustrate the effect of the transition velocity behavior on traffic velocity and density. Simulation results are presented which show that this model provides a more accurate characterization of traffic flow behavior than the well known Payne-Whitham model. The proposed model can be used to reduce accidents and improve road safety during adverse weather conditions.
文摘Weather models are essential tools for checking of the effect of the weather elements in terms of their effect on the production of the crop. This research is an attempt to see the effect of only two variables i.e., temperature and rainfall for the division Faisalabad (semitropical region of Pakistan).The model fitted is of the linear form:the values of a,b, c have been found. The expected yield has been calculated by using the aridity indices (X1 and X2 ) and the result in the form of coefficient of determination R2 has been found equal to 0.166. The significance of the regression coefficient has been tested, which shows that the contribution to the yield from aridity index at germination and that at ripening is significant.The wheat yields are the results of a wide variety of variables, most of which show varying degree of relationship with one another, some positive and some negative in terms of output. These variables may be technology, fertilizers, pesticides, epidemics, kinds of seeds used, market price of crop and the area under cultivation etc, which can be the source of variation in the wheat yield. Since rainfall during germination and temperature at the ripening periods are the necessary factors for the yield of wheat, for this purpose these parameters have been studied in order to their contribution.
基金sponsored by the Federal Highway Administration(FHWA)in cooperation with the American Association of State Highway and Transportation Officials(AASHTO)
文摘Identifying risk factors for road traffic injuries can be considered one of the main priorities of transportation agencies. More than 12,000 fatal work zone crashes were reported between 2000 and 2013. Despite recent efforts to improve work zone safety, the frequency and severity of work zone crashes are still a big concern for transportation agencies. Although many studies have been conducted on different work zone safety-related issues, there is a lack of studies that investigate the effect of adverse weather conditions on work zone crash severity. This paper utilizes probit–classification tree, a relatively recent and promising combination of machine learning technique and conventional parametric model, to identify factors affecting work zone crash severity in adverse weather conditions using 8 years of work zone weatherrelated crashes (2006–2013) in Washington State. The key strength of this technique lies in its capability to alleviate the shortcomings of both parametric and nonparametric models. The results showed that both presence of traffic control device and lighting conditions are significant interacting variables in the developed complementary crash severity model for work zone weather-related crashes. Therefore, transportation agencies and contractors need to invest more in lighting equipment and better traffic control strategies at work zones, specifically during adverse weather conditions.
基金National Key Research and Development Project(2018YFC1505706)Fund of Southern Marine Science and Engineering Guangdong Laboratory(Zhanjiang)(ZJW-2019-08)+3 种基金Program for Scientific Research Start-up Funds of GDOU(R17061)Project of Enhancing School with Innovation of GDOU(230419053)Projects(Platforms)for Construction of Top-ranking Disciplines of GDOU(231419022)Special Funds of Central Finance to Support the Development of Local Colleges and Universities(000041)
文摘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 is needed due to uncertainties brought by data assimilation.
文摘Recently, as the oceanic activities are more and more frequently carried out, marine oil spill accidents bring to enormous harm to the economy and society in China, especially in the Offshore China. Marine oil spill is one kind of serious disasters which severely damages the marine environment. Aiming at the improvement of the emergency response system and response ability for the oil spill, the relative technologies on oil spill response are developed. This paper briefly introduces the developments and achievements of the oil spill numerical models, including the oil spill spreading model, the oil spill transport model, the oil particle model as well as the oil spill weathering model, which provide the theoretic criterions for the future work on the oil spill predicting and response.
基金supported by the National Natural Science Foundation of China[grant numbers 41421004 and 41210007]the International Innovation Team project of the Chinese Academy of Sciences entitled ‘High Resolution Numerical Simulation of Regional Environment’
文摘The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared and analyzed in this paper. The satellite products, including CPC MORPHing technique（CMORPH）, TMPA-RT, and PERSIANN are all near-real-time retrieved with high temporal and spatial resolutions. The numerical weather model used in this paper for precipitation forecasting is WRF. The results show that all three satellite products can basically reproduce the rainfall pattern, distribution, timing, scale, and extreme values of the event, compared with gauge data. Their temporal and spatial correlation coefficients with gauge data are as high as about 0.6, which is statistically significant at 0.01 level. The performance of the forecasted results modeled with different spatial resolutions are not as good as the satellite-estimated results, although their correlation coefficients are still statistically significant at 0.05 level. From the total rainfall and extreme value time series for the domain, it is clear that, from the grid-to-grid perspective, the passive microwave-based CMORPH and TRMM products are more accurate than the infrared-based PERSIANN, while PERSIANN performs very well from the general point of view, especially when considering the whole domain or the whole convective precipitation system. The forecasted data — especially the highest resolution model domain data — are able to represent the total or mean precipitation very well in the research domain, while for extreme values the errors are large. This study suggests that satellite-retrieved and model-forecasted rainfall data are a useful complement to gauge data, especially for areas without gauge stations and areas not covered by weather radars.
基金Supported by National Natural Science Foundation of China(61572274,61672307,61272225,51261120376)the National Key Technologies R&D Program of China(2015BAF23B03)
文摘Numerical weather simulation data usually comprises various meteorological variables, such as precipitation, temperature and pressure. In practical applications, data generated with several different numerical simulation models are usually used together by forecasters to generate the final forecast. However, it is difficult for forecasters to obtain a clear view of all the data due to its complexity. This has been a great limitation for domain experts to take advantage of all the data in their routine work. In order to help explore the multi-variate and multi-model data, we propose a stamp based exploration framework to assist domain experts in analyzing the data. The framework is used to assist domain experts in detecting the bias patterns between numerical simulation data and observation data. The exploration pipeline originates from a single meteorological variable and extends to multiple variables under the guidance of a designed stamp board. Regional data patterns can be detected by analyzing distinctive stamps on the board or generating extending stamps using the Boolean set operations. Experiment results show that some meteorological phenomena and regional data patterns can be easily detected through the exploration. These can help domain experts conduct the data analysis efficiently and further guide forecasters in producing reliable weather forecast.
