Numerical weather modeling-based slant tropospheric delay estimation and its enhancement by GNSS data

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.

A STUDY OF THE INFLUENCE OF MICROPHYSICAL PROCESSES ON TYPHOON NIDA(2016) USING A NEW DOUBLE-MOMENT MICROPHYSICS SCHEME IN THE WEATHER RESEARCH AND FORECASTING MODEL

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.

An approach to estimating and extrapolating model error based on inverse problem methods:towards accurate numerical weather prediction

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.

A Methodological Study on Using Weather Research and Forecasting(WRF) Model Outputs to Drive a One-Dimensional Cloud Model

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.

The Identification and Modeling of the Volcanic Weathering Crust in the Yingcheng Formation of the Xujiaweizi Fault Depression, Songliao Basin

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.

Development of Operational Space Weather Prediction Models

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.

DEM investigation of weathered rocks using a novel bond contact model

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.

A model study of the effect of weather forcing on the ecology of a meromictic Siberian lake

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.

Effects of rainy weather on traffic accidents of a freeway using cellular automata model

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.

Electrical-hydraulic conductivity model for a weatheredfractured aquifer system of Olbanita, Lower Baringo Basin, Kenya Rift

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.

A macroscopic traffic model based on weather conditions

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.

Weather Yield Model for the Semi Tropical Region (Pakistan)

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.

数值预报AI气象大模型国际发展动态研究

数值预报是研究地球系统的重要工具,有助于加深科学家对大气、海洋、气候和环境等复杂系统之间相互作用和变化过程的理解,在防灾减灾、气候变化和环境治理等方面发挥着不可或缺的作用。随着模式复杂度和分辨率的提高,传统数值模式在气候变化研究和气候预测方面取得了迅速的进展,但也面临一些挑战,需要得到数据同化、集合耦合、高性能计算和不确定性分析等多方面的支持。而近年来,“AI+气象”的交叉研究在气象领域引起了广泛关注。基于多种深度学习架构的人工智能大模型,依托强大的计算资源和海量的数据进行训练,能够以新的科学范式进行高效数值预报。气象大模型不断涌现,一些科技公司如华为、英伟达、DeepMind、谷歌、微软等,以及国内外高校如清华大学、复旦大学、密歇根大学、莱斯大学等发布了多个涵盖临近预报、短时预报、中期预报和延伸期预报等不同领域的气象大模型。这标志着人工智能与气象领域的交叉融合已经达到新的高度。尽管气象大模型在现阶段取得了较大突破,但其发展仍然面临弱可解释性、泛化能力不足、极端事件预报强度偏低、智能预报结果过平滑、深度学习框架能力需要拓展等诸多挑战。

Complementary parametric probit regression and nonparametric classi?cation tree modeling approaches to analyze factors affecting severity of work zone weather-related crashes

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.

基于陆气耦合模式的降雨径流模拟研究进展

基于陆气耦合模式的降雨径流模拟是变化环境下水文循环过程研究的重要内容之一。围绕陆气耦合降雨径流模拟,分析基于陆气耦合模式的降雨径流模拟框架,对比基础输入资料、天气模式和陆面水文模型各方面的优缺点,回顾基于该框架的发展历程,从集合预报、数据驱动、陆面水文模型与天气模式3个方面介绍了陆气耦合降雨径流模拟技术的发展,提出多尺度转换、双向耦合、不确定性问题及误差修正4个热点关键技术问题,并对未来研究进行展望,以期为推进基于陆气耦合模式的降雨径流模拟研究提供参考。

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

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

恶劣天气下机场离场航班运行韧性评估及恢复

为保障恶劣天气下机场整体性能,科学评估机场离场航班运行韧性,提高航班恢复能力,从而有效缓解天气的影响。给出机场离场航班运行定义,从机场离场航班运行系统性能出发,分析航班离场延误时间、离场总延误时间、离场航班正常率和机场离场航班运行系统综合韧性指数4个指标,对系统在恶劣天气条件下的韧性变化进行评估;提出机场离场航班运行系统性能恢复策略,利用遗传算法对离场延误航班进行优化排序;以2012年北京首都国际机场“721”特大暴雨事件为实例进行数据分析,得到暴雨影响下首都机场的性能指标和韧性指数,对比分析机场离场航班运行系统性能及韧性水平变化。研究结果表明:受暴雨影响,机场离场航班运行系统综合韧性指数由0.457 3下降到0.062 8,暴雨减小后上升到0.222 3;在进行航班优化排序后,离场航班总延误时间减少了24.85%,优化后机场性能恢复速度提升了13.89%,优化后的机场离场航班运行系统最小韧性指数提升了13.38%,系统性能优先恢复至初始状态,表明所提恢复策略有效。

动水头作用下花岗岩风化土的内部侵蚀机理

[目的]揭示动水头作用下花岗岩风化土侵蚀演化的动态过程,研究动态水力条件对土体内部侵蚀发展的影响,探明颗粒迁移规律与内部侵蚀机理,为深入研究花岗岩边坡的破坏模式与促滑机理提供理论依据。[方法]设计竖向土柱渗流装置,开展上升水头与正弦水头条件下花岗岩风化土柱的渗流试验,基于渗流土柱顶面与侧面的试验现象,从渗流速度变化、颗粒流失量变化和渗流前后颗粒级配、质量变化等方面,分析动水头作用下花岗岩风化土内部侵蚀的发育特征。[结果]①花岗岩风化土粒径差异较大,在骨架间存在微小孔隙,渗流冲刷作用使得土颗粒通过土体骨架间的孔隙运移流失。在内部侵蚀过程中,细颗粒流失量相对较多,粗颗粒流失量较少。②土体内部侵蚀作用是渐进发展的过程,在土体薄弱区域的结构最先产生变形与破坏。试验中渗流泉眼由土柱边界开始发展到土柱中部区域,渗流通道沿着渗流方向自下而上发育,水力条件短时间内发生显著变化会造成渗流通道快速贯通。③土体内部侵蚀作用将随渗流时间推进而趋于稳定,但正弦水头将“激活”土颗粒运动,加剧土体的内部侵蚀作用。加大水头变化幅度或减小水头变化周期,能够加剧土体内部侵蚀作用,导致水流运移速度加快以及颗粒迁移流失量增多。[结论]水力条件变化对土体内部侵蚀作用存在显著影响,正弦水头更能加剧颗粒迁移流失。

天气雷达站电磁环境影响监测研究

天气雷达站产生的超标电磁辐射会对人体造成严重的损伤。为此,提出天气雷达站电磁环境影响监测与分析。分析天气雷达站电磁影响因素,结合发射天线的方向函数,构建雷达功率密度模型。测试结果表明,对于S波、C波段、X波段,真实值与计算值呈现随距离增加而降低的趋势。对于三个波的频段,当接近天线的远场区时,计算值与真实值逐渐接近,相对误差均较小,说明模型在远场区的适用性更强;研究算法与实测值的拟合程度较高;在模型的应用中,真实反映了某市区的电磁辐射情况。

面向多天气退化图像恢复的自注意力扩散模型

复杂天气下的图像恢复对后续高级计算机视觉任务具有重要意义.然而,多数现有图像恢复算法仅能去除单一天气退化,鲜有针对多天气退化图像恢复的同一模型.对此,结合去噪扩散概率模型和视觉Transformer,提出一种用于多天气退化图像恢复的自注意力扩散模型.首先,利用天气退化图像作为条件来引导扩散模型反向采样生成去除退化的干净背景图像.其次,提出次空间转置自注意力噪声估计网络,利用退化图像和噪化状态来估计噪声分布,包括次空间转置自注意力机制(STSA)和双分组门控前馈网络(DGGFFN).STSA利用次空间变换系数实现有效学习特征全局性长距离依赖的同时,可显著降低计算负担;DGGFFN利用双分组门控机制来增强前馈网络的非线性表征能力.实验结果表明,在5个天气退化图像数据集上,相比近来同类算法All-in-One和TransWeather,本文算法所得恢复图像的平均峰值信噪比分别提高3.68和3.08 dB,平均结构相似性分别提高2.93%和3.13%.