An adaptive finite element model for wellbore breakout simulation

A finite element formulation is proposed and implemented for analysing the stability of excavated wells using the DiMaggio-Sandler constitutive elastoplastic model with a typical carbonate reservoir configuration. The quality of the finite element approximation is ensured by applying smooth curved elements adapted to the wellbore geometry, and h − p adaptive finite element meshes in the plastic zone. General purpose procedures are defined to transfer the elastoplastic deformation history to newly created integration points. A breakout damage criterion is proposed based on the second invariant of the deviatoric plastic deformation tensor. This damage criterion is used to apply a mesh movement algorithm to represent material collapse. The automatic successive application of the breakout damage criterion results in elliptical realistically looking geometries obtained in experiments reported in the literature.     

Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches

River water temperature is a key physical variable controlling several chemical, biological and ecological processes. Its reliable prediction is a main issue in many environmental applications, which however is hampered by data scarcity, when using data‐demanding deterministic models, and modelling limitations, when using simpler statistical models. In this work we test a suite of models belonging to air2stream family, which are characterized by a hybrid formulation that combines a physical derivation of the key equation with a stochastic calibration of parameters. The air2stream models rely solely on air temperature and streamflow, and are of similar complexity as standard statistical models. The performances of the different versions of air2stream in predicting river water temperature are compared with those of the most common statistical models typically used in the literature. To this aim, a dataset of 38 Swiss rivers is used, which includes rivers classified into four different categories according to their hydrological characteristics: low‐land natural rivers, lake outlets, snow‐fed rivers and regulated rivers. The results of the analysis provide practical indications regarding the type of model that is most suitable to simulate river water temperature across different time scales (from daily to seasonal) and for different hydrological regimes. A model intercomparison exercise suggests that the family of air2stream hybrid models generally outperforms statistical models, while cross‐validation conducted over a 30‐year period indicates that they can be suitably adopted for long‐term analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Quantitative estimation of submarine groundwater discharge using airborne thermal infrared data acquired at two different tidal heights

Submarine groundwater discharge (SGD) plays an important role in coastal biogeochemical processes and hydrological cycles, particularly off volcanic islands in oligotrophic oceans. However, the spatial and temporal variations of SGD are still poorly understood owing to difficulty in taking rapid SGD measurements over a large scale. In this study, we used four airborne thermal infrared surveys (twice each during high and low tides) to quantify the spatiotemporal variations of SGD over the entire coast of Jeju Island, Korea. On the basis of an analytical model, we found a linear positive correlation between the thermal anomaly and squares of the groundwater discharge velocity and a negative exponential correlation between the anomaly and water depth (including tide height and bathymetry). We then derived a new equation for quantitatively estimating the SGD flow rates from thermal anomalies acquired at two different tide heights. The proposed method was validated with the measured SGD flow rates using a current meter at Gongcheonpo Beach. We believe that the method can be effectively applied for rapid estimation of SGD over coastal areas, where fresh groundwater discharge is significant, using airborne thermal infrared surveys.     

Submarine groundwater discharge revealed by aerial thermal infrared imagery: a case study on Jeju Island,Korea

Submarine groundwater discharge (SGD) is a global phenomenon that carries large volumes of groundwater and dissolved chemical species such as nutrient, metals, and organic compounds to coastal zones. We report the influence of SGD on the coastal waters of Jeju Island, Korea, using high‐resolution aerial thermal infrared (TIR) mapping techniques and field investigations. An aircraft‐based system was implemented using a cost‐effective TIR camera for aerial TIR mapping. Ground‐based calibrations and system integration with GPS/IMU (global positioning system/inertial measurement unit) were performed for the aerial systems. The aerial surveys showed distinct low‐temperature signatures of SGD along the coasts of Jeju Island, revealing large groundwater inputs from the coastal aquifers to the ocean. Multiple aerial surveys over a range of seasons and tidal stages revealed that SGD rates dynamically affect the sea surface temperature (SST) of the coastal zone. The in‐situ measurements supported that SGD has a substantial influence on the coastal water chemistry as well as SST. Our observations highlight the extent to which aerial‐based TIR mapping can serve as a powerful tool for studying SGD and other coastal processes. Copyright © 2016 John Wiley & Sons, Ltd.     

PMODTRAN: a parallel implementation based on MODTRAN for massive remote sensing data processing

MODerate resolution atmospheric TRANsmission (MODTRAN) is a commercial remote sensing (RS) software package that has been widely used to simulate radiative transfer of electromagnetic radiation through the Earth's atmosphere and the radiation observed by a remote sensor. However, when very large RS datasets must be processed in simulation applications at a global scale, it is extremely time-consuming to operate MODTRAN on a modern workstation. Under this circumstance, the use of parallel cluster computing to speed up the process becomes vital to this time-consuming task. This paper presents PMODTRAN, an implementation of a parallel task-scheduling algorithm based on MODTRAN. PMODTRAN was able to reduce the processing time of the test cases used here from over 4.4 months on a workstation to less than a week on a local computer cluster. In addition, PMODTRAN can distribute tasks with different levels of granularity and has some extra features, such as dynamic load balancing and parameter checking.     

Preaching to different choirs: How to motivate dismissive,uncommitted, and alarmed audiences to adapt to climate change?

People vary considerably in terms of their knowledge, beliefs, and concern about climate change. Thus, an important challenge for climate change communicators is how to most effectively engage different types of audiences. This study aimed to identify distinct audience segments that vary in terms of their values, beliefs, and responses to climate change and determine for each segment which specific message attributes increased motivation to engage in climate adaptation. A sample of 1031 Australian residents (aged 18–66 years) completed an online survey assessing their values, beliefs, and behaviors related to climate change, and recording their responses to a broad range of climate change adaptation messages. Latent profile analysis identified three distinct audience segments: alarmed (34.4%), uncommitted (45.2%), and dismissive (20.3%). Sixty climate change adaptation messages were coded in terms of the presence/absence of six attributes: explicit reference to climate change, providing specific adaptation advice, strong negative emotive content, emphasis on collective responsibility, highlighting local impacts, and underscoring financial impacts. Participants viewed a random sample of six messages and rated the extent to which each message motivated them to seek out more information and immediately respond to the climate change threat portrayed in the message. Multilevel modeling indicated messages that included strong negative emotive content or provided specific adaptation advice increased adaptation intentions in all three audience segments. Omitting any mention of climate change and emphasizing local impacts increased adaptation intentions in dismissive audiences. Implications for tailoring and targeting climate change adaptation messages are discussed.     

适应气候变化的国际行动和农业措施研究进展

针对气候变暖采取稳健的适应措施已成为国际社会共识。该文综合了当前适应气候变化的国际谈判进展及已有的农业适应气候变化措施,指出适应资金严重不足,技术研发、应用与转让难以实施,以及适应气候变化行动实施能力的不足严重制约着适应气候变化行动的有效实施;关于农业适应气候变化的技术措施仍缺乏系统的理论研究与应用示范。在此基础上,提出了未来中国农业适应气候变化需要重点开展的研究任务,即农业气象灾变过程的新特点及其风险管理, 农业适应气候变化的大数据决策管理系统研发及适应气候变化的农业气候区划与减灾保产技术研究,以切实推进农业适应气候变化,为确保国家粮食安全与农业可持续发展提供支撑。     

北京和广州地区云闪初始击穿电场变化特征

对比分析了北京和广州地区各100例云闪初始阶段前30 ms快电场变化波形上初始击穿脉冲的特征。依据脉冲的结构特征,两地区的云闪初始击穿脉冲可分为单极性单峰型、单极性多峰型、双极性单峰型和双极性多峰型脉冲,两地区均以单极性和单峰型脉冲为主。对脉冲参量特征的统计发现,脉冲的10%-90%上升时间、半峰值宽度地区差异性小于脉冲类型差异性;双极性单峰型脉冲的半峰值宽是单极性单峰型的1.2倍。不同类型脉冲过零时间的中值、平均值在10μs左右量级,且广州地区较北京地区的大;云闪初始击穿脉冲宽度平均值显著小于相同地区正地闪的,而脉冲间隔显著大于正地闪的。初始击穿脉冲最为集中的出现在云闪最初的1~2 ms,其比例随时间以显著的负指数分布下降。研究发现,双极性脉冲的过零时间与脉冲宽度之间、起始半周期峰值幅度与过冲幅度之间均存在较好的线性关系。     

气候变化情景下黄淮海区域热量资源及夏玉米温度适宜度

利用黄淮海区域90个站点1971—2000年逐日气象资料以及国家气候中心发布的未来气候变化情景(A1B)下区域气候模式(Reg CM3)模拟的黄淮海区域1951—2070年0.25°×0.25°格点气象资料,结合夏玉米主要生育期对温度的需求,构建了黄淮海区域的温度适宜度和变异系数模型,并对1951—2070年黄淮海区域热量资源、夏玉米主要生育期的温度适宜度及其变异系数的时空变化特征进行分析。结果表明:1)黄淮海区域≥10℃积温和80%保证率下日平均温度≥10℃的初日均呈现由北向南依次增加的趋势,且随时间推移,分别呈增加和提前趋势。2)黄淮海区域夏玉米播种—出苗期的温度适宜度随时间整体呈逐渐上升的变化趋势、其变异系数随时间呈降—升—降的变化趋势;出苗—抽雄期的温度适宜度随时间呈先降后升的变化趋势、其变异系数呈降—升—降—升的变化趋势;抽雄—成熟期的温度适宜度空间上呈现2010年前北低南高、未来情景下中部低四周高的分布趋势,时间上呈2010年前稳定、未来情景下先降后升的变化趋势,其变异系数呈相反变化趋势;3)黄淮海区域夏玉米温度适宜度及其变异系数从播种—出苗期—出苗—抽雄期—抽雄—成熟期均呈反相位的变化关系。