bluuebunny/crossref_metadata_2025 huggingface dataset:
TCV-like event induced by positive-negative pulse pair of solar wind dynamic pressure
Authors: Tian Anmin , Degeling Alexander , Shi Quanqi , Xing Zanyang
Published: March 2020

Both simulations and observations had shown that step function-like increase/decrease of solar wind dynamic pressure pulse would excite flow vortex pairs in the dawn and dusk high latitude ionosphere simultaneously. However, some plasma structures, hot flow anomaly, sheath jets etc. existing in the solar wind or magnetosheath are often accompanied with spike-like changes of the dynamic pressure. Whether they can drive the ionospheric vortices or not is still unclear. In this work we report a traveling convection vortex like (TCV-like) event that was induced by a positive-negative pulse pair of dynamic pressure(△p/p~1) accompanying a large scale (~9min) magnetic hole in the solar wind. It is found that following the magnetic hole, two traveling convection vortices first in anticlockwise then in clockwise rotation were detected by geomagnetic stations located along the 10:30MLT meridian. Meanwhile, another pair of ionospheric vortices azimuthally seen up to 3 MLT first in clockwise then in anticlockwise rotation were appeared in the afternoon sector (~14MLT) centered at ~75MLAT with a trend of poleward moving. The duskside vortices were also confirmed by SuperDARN radar data. The processes following magnetosphere struck by a positive-negative pulse pair were simulated and it found that two pairs of flow vortices in the dawn and dusk magnetosphere may provide the field-aligned currents(FACs) required for the flow/current vortices observed in ionosphere. This work provides a way to understand how the momentum and energy injects to the ionosphere under spike-like dynamic pressures imposing on the magnetosphere.
Quantification and Reduction of Uncertainties in 3D Stress Models
Authors: Ziegler Moritz , Heidbach Oliver
Published: March 2020

The undisturbed stress state of a potential site for nuclear waste disposal is of key importance for the assessment of long-term stability of the geotechnical installations and for seismic hazard assessment. In particular, the stability of pre-existing faults within and near a repository can only be evaluated with the knowledge of the initial stress state. Information on stress magnitudes is rare and unevenly distributed. Thus, 3D geomechanical-numerical modelling is used to estimate the stress state in an area of interest. However, due to the limitation of available data, the modelled stress state has a large uncertainty which has not been rigorously quantified yet. We present an approach to quantify the uncertainties in a 3D geomechanical-numerical modelled stress field. We combine the available SHmax and Shmin data records to pairs. For each pair we compute an individual model scenario. At each location in the model each scenario contains the full stress tensor. Then, from all model scenarios we compute an average value and a standard deviation for each component of the full stress tensor at each location within the model. This provides a comprehensive assessment of the stress state and its uncertainties.

Furthermore, we present an approach to reduce the previously quantified uncertainties in the model results: We use additional borehole observables (Formation Integrity Tests) and observed seismicity and - if available - its focal mechanisms. These observables cannot provide any data records on the stress state. Yet, the information that can be extracted is valuable as it contains upper boundaries for the magnitudes of the minimum principal stress (Formation Integrity Tests) and the maximum principal stress/differential stress (seismicity), respectively. These boundaries are compared to the stress states in the individual model scenarios. Then, each scenario is assigned a weight based on its agreement with the additional data. This allows computing a weighted average and a standard deviation. The resulting standard deviation is clearly smaller compared to the unweighted approach and small changes in the average stress state are observed. Thus, even with only limited data record availability, a quantification and even a significant reduction of uncertainties in the modelling results is possible which increases the significance and value of the model.
The Response of the QBO to Increases in CO2 Using Three Atmospheric Chemistry Configurations
Authors: DallaSanta Kevin , Orbe Clara , Polvani Lorenzo
Published: March 2020

Long-term projections of the Quasi-Biennial Oscillation (QBO) remain highly uncertain. This is partly due to the paucity of models which are able to properly simulate that phenomenon. Only 5 of the 47 CMIP5 models are capable of spontaneously generating a realistic QBO (Butchart et al., 2018), and even those models exhibit large biases in key QBO characteristics (e.g. amplitude, period, vertical extent) when compared with observations. Furthermore, only 1 of these 5 employed interactive atmospheric chemistry, which is known to modulate QBO dynamics.

We here investigate the QBO response to increased greenhouse gases using the NASA Goddard Institute for Space Studies Middle Atmosphere Model E2.2. Compared to lower vertical resolution versions of Model E, version 2.2 has a higher model top (0.002 hPa), and additional interactive non-orographic gravity wave drag sources from convection and shear, which produce a sufficiently realistic QBO, thus rendering it suitable for use in climate change studies. Steady-state responses to doubled and quadrupled CO2 from a pre-industrial control are analyzed, as well as the transient response to a 1% per year CO2 increase. In addition, we systematically explore the impact of interactive chemistry in modulating the QBO response to increased CO2 by contrasting interactive, prescribed, and linearized ozone chemistry configurations of the model. Overall, in response to increase CO2 concentrations the QBO is seen to increase in frequency and weaken in amplitude, consistent with previous results, but the memory of the tropical stratosphere may complicate assessments of trends in chemistry and surface impacts. We also discuss implications for the trade-off between ensemble size and the complexity of the chemistry scheme in the model.
Improving Total Electron Content (TEC) Models for Geodetic Applications
Authors: Kosary Mona , Farzaneh Saeed , Schumacher Maike , Forootan Ehsan
Published: March 2020

Increasing the quality of ionosphere modeling is crucial and remains a challenge for many geodetic applications such as GNSS Precise Point Positioning (PPP) and navigation. Ionosphere models are the main tool to provide an estimation of Total Electron Content (TEC) to be corrected from GNSS career phase and pseudorange measurements. Skills of these models are however limited due to the simplifications in model equations and the imperfect knowledge of model parameters. In this study, an ionosphere reconstruction approach is presented, where global estimations of geodetic-based TEC measurements are combined with an ionospheric background model. This is achieved here through a novel simultaneous Calibration and Data Assimilation (C/DA) technique that works based on the sequential Ensemble Kalman Filter (EnKF). The C/DA method ingests the actual ionospheric measurements (derived from global GNSS measurements) into the IRI (International Reference Ionosphere) model. It also calibrates those parameters that control the F2 layer’s characteristics such as selected important CCIR (Comité Consultatif International des Radiocommunicationsand) URSI (International Union of Radio Science) coefficients.  The calibrated parameters derived from the C/DA are then replaced in the IRI to simulate TEC values in locations, where less GNSS ground-station infrastructure exists, as well as to enhance the prediction of TEC when the observations are not available or their usage is cautious due to low quality. Our numerical assessments indicate the advantage of the C/DA to improve the IRI’s performance. Values of the TEC-Root Mean Square of Error (RMSE) are found to be decreased by up to 30% globally, compared to the original IRI simulations. The importance of the new TEC estimations is demonstrated for PPP applications, whose results show improvements in navigation applications.

Keywords: Ionosphere, Calibration and Data Assimilation (C/DA), IRI, Total Electron Content (TEC), Precise Point Positioning (PPP), GNSS
Planning method and application case of debris-flow check dams in water and soil conservation
Authors: Chen Jiangang , Chen Huayong , Chen Xiaoqing
Published: March 2020

Check dams are transverse structures build across gullies and they are very important engineering measure in soil restoration hazard mitigation. After three successive earthquakes in China, a considerable number of solid material was deposited in gullies. With the extreme rainfall, a numerous of flood and debris flow events were trigged, some of them caused serious secondary disasters. In the past 12 years after the Wenchuan earthquake, based on the debris-flow prevention method by controlling debris-flow magnitude and avoiding blocking river, a series of check dams were constructed to regulate the water and soil erosion. The operation status of check dams needs to be investigated and summarize the engineering practice experience. Based on the results of field investigation, the shape and size characteristics of the dam opening were analyzed, and then established a classification system of the opening clogging types. Moreover, in August 20, 2019, Flash floods and mudslides occurred in Wenchuan County, causing more than 30 people dead, buried the G213 highway, and damaged a bridge. These disasters bring new thinking for future hazard mitigation. Geotechnical measures can quickly reduce the disaster risk of flash flood and debris flow, and now it has formed a set of perfect design standards. However, the disaster mitigation effect of the vegetation measures are not fully studied. Thus, the integrated disaster mitigation effect of the above two methods will be investigated in the future work.
The Ocean's Alkalinity: Connecting geological and metabolic processes and time-scales
Authors: Thomas Helmuth , Norbisrath Mona , Treblin Nele , van Dam Bryce , Pätsch Johannes , Emeis Kay-Christian
Published: March 2020

The Earth system has entered a new geological epoch, the Anthropocene. The oceans’ capacity to regulate atmospheric carbon dioxide (CO 2 ) at various
timescales is amongst the most crucial players to maintain climate on Earth in a habitable range. The biogeochemical property exerting this regulatory mechanism is alkalinity, the oceans’ CO 2 and pH buffer capacity. The proposed project will investigate how the oceans’ alkalinity is impacted firstly by human measures, required by the Paris agreement (COP 21) to mitigate climate change via bioenergy production and its downstream effects on shallow oceans, and secondly by climate change, in particular by increased weathering in the Arctic because of ice retreat.
Source mechanism of recent seismic events and microzonation studies along Sagaing Fault near Nay Pyi Taw, capital of Myanmar
Authors: Milkereit Claus , Tun Pa Pa , Than Oo , Oo Kyawmoe , Naing Kyaw Zayar , Aung Myat Min , Htwe Yin Myo Min , Heimann Sebastian
Published: March 2020

In 2005, the capital of Myanmar was moved to the newly designed city of Nay Pyi Taw, some 300 km north of Yangon. Both Yangon as well as the capital Nay Pyi Taw are situated along the 1200 km long north-south trending Sagaing Fault, an active strike-slip fault which showed large and disastrous earthquakes in the past. Almost nothing is known about details of the Sagaing Fault in the area of Nay Pyi Taw, neither the precise location of different branches of the Sagaing Fault, nor the precise location of recent seismic events along different branches of the fault, nor the distribution and depth of the sedimentary layers in and around Nay Pyi Taw.

Since 2014, 4 shallow earthquakes with magnitudes larger than ML=4 are reported near Nay Pyi Taw. Some were clearly felt in the capital. The different location solutions reported by local and international agencies indicate a location accuracy not better accurate than 5 km. We derived re-locations and moment tensor analyses as well as meaningful model uncertainties for these events. The results show that the Sagaing Fault near Nay Pyi Taw may follow different active branches. While geological mapping indicates an active branch west of Nay Pyi Taw, the event locations and source mechanisms of the recent seismic activity indicate an active branch under and east of Nay Pyi Taw. Here, a geological mapping is complicated as sediments of unknown thickness cover the basement. Therefore, a microzonation study has been started with the aim to determine the fundamental resonant frequencies of the sedimentary layers, their spatial variability, and the amplification factors. First results of this ongoing project with more than 50 noise recordings in and around Nay Pyi Taw indicate amplification of ground motion with a factor up to 10 in distinct frequency ranges from 0.3 – 10 Hz.

 
The clogging and outbreak processes of debris flow with large wood in Jiuzhaigou Valley, China
Authors: Chen Xiaoqing , Chen Jiangang , Zhao Wanyu
Published: March 2020

UNESCO designated 1121 properties with outstanding universal value, including 869 cultural sites, 213 natural sites and 39 mixed sites, from 167 states parties as world heritage sites at the end of 2019. Some of them are threatened by geological disasters, especially, the landslides and debris flows become the most frequent hazard type at world heritage sites. Until 2019, China has 55 world heritage sites and ranks first in the world, with 24 places under threat from different types of geological disasters and these disasters directly or indirectly threaten the security of heritage points. The forest coverage rate in Jiuzhaigou valley is more than 80%, and the collapse, rock fall, landslide and other disasters induced by the Jiuzhaigou earthquake on August 8, 2017 have caused extensive forest destruction. We found that there are a lot of large wood (LW) in Jiuzhaigou valley that can be transported. According to previous study results, the process of blocking-outburst in gullies will appear with a large number of LW when transported along with debris flows. Compared with the discharge amplification effect of the debris flow in natural gully, the blocking-outburst effect of LW also intensifies the damage. The process of blockage and outburst with LW movement causes the discharge amplification of debris flow, while the discharge amplification coefficient determines the accuracy of discharge calculation, in further it affects the accuracy of engineering design parameters. Moreover, the LW carried in the debris flow may cause strong impact damage to check dams and other engineering measures. Therefore, we take the debris flow occurred in the Jiuzhaigou valley as an example to investigate the characteristics of the magnitude amplification ratio.
Measuring stress and strain in rocks by spectroscopy
Authors: Angel Ross , Murri Mara , Campomenosi Nicola , Mihailova Boriana , Prencipe Mauro , Alvaro Matteo
Published: March 2020

Microstructures and the different thermoelastic properties of minerals ensure that no rock is ever under perfect hydrostatic stress at the grain level. If deviatoric stresses and strains significantly modify thermodynamic properties of minerals so that the equilibrium assemblage and compositions are different from that predicted from hydrostatic conditions, it is crucial to be able to measure the stress state of minerals in-situ in rocks. Forty years ago it was considered that ‘Analysis of residual stresses at the scale of mineral grains within a polycrystalline aggregate such as a rock is virtually intractable’ [1]. This is no longer true.

Confocal Raman spectroscopy allows spectra to be collected from small volumes of mineral grains within a section. The positions of Raman peaks depends on the elastic strains in the minerals through the phonon-mode Grüneisen tensors [2]. The development of precise DFT simulations of crystal structures and their Raman spectra now allows the components of the phonon-mode Grüneisen tensors to be calculated [3]. With these tensors it is possible to determine the strains from measured Raman peak positions, to thereby map the strain, and hence the stress state, of individual mineral grains. We have now extended the DFT simulations to show that the Raman shifts of crystals subject to symmetry-breaking stresses (e.g. around inclusions) are, as expected, not solely determined by the phonon-mode Grüneisen tensors of the ideal crystal. We have also recently developed the measurement of the change in peak intensities in cross-polarised Raman spectra to determine the stress [4] in these cases. For minerals such as garnets, this effect is stronger and therefore more sensitive to stress than the shifts in peak positions and offers at the moment the possibility to quickly visualise stress and strain fields in minerals in-situ in rocks. Quantitative stress values from this method await the determination of the piezo-phonon tensors for garnets, but comparison of peak positions and intensities show that the two methods return consistent results.

This work was supported by ERC-StG TRUE DEPTHS grant (number 714936) to M. Alvaro. N. Campomenosi was also supported by the University of Genova.

 

[1] Holzhausen & Johnson (1979) Tectonophysics 58, 237.

[2] Angel et al. (2019) Zeitschrift für Kristallographie, 234, 129.

[3] Murri et al. (2018) American Mineralogist, 103, 1869.

[4] Campomenosi et al. (2020) Contributions to Mineralogy and Petrology, accepted.
River flow prediction of Hunza River by LSSVR, fuzzy genetic and M5 model tree using nearby station’s meteorological data
Authors: Ikram Rana Muhammad Adnan , Liang Zhongmin , Kisi Ozgur , Adnan Muhammad , Li Binquan , Sathishkumar Kuppusamy
Published: March 2020

River runoff prediction plays a very vital role in water resources planning, hydropower designing and agricultural water management. In the current study, the prediction capability of three machine learning models, least square support vector regression (LSSVR), fuzzy genetic (FG) and M5 model tree (M5Tree), in modeling daily and monthly runoffs of Hunza River catchment (HRC) using own and nearby Gilgit climatic station data is examined. The prediction performances of three machine learning models are compared using three statistical indexes, namely, root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). Firstly, four previous time lagged values of runoff, rainfall and atmospheric temperature are used as inputs on basis of correlation analysis to validate and test the accuracy of three machine learning models. After analyzing the performance of various input combinations, optimal one is selected for each variable and then these optimal inputs are employed together to see the forecasting performance. In the first part of study, monthly runoff of HRC are predicted using inputs consisting of local previous monthly runoff values and monthly meteorological values of Gilgit station. The test results show that LSSVR provides more accurate prediction results than the other two machine learning models. In the second part, daily runoffs of HRC are predicted using own previous daily runoff and Gilgit station’s climatic values. In the test results, a better accuracy is obtained from LSSVR models in relative to the FG and M5Tree models. In the last part of study, daily runoffs of HRC are predicted using own runoff and climatic data of HRC. In the results, it is found that local climatic data slightly improved the all model’s prediction accuracy in comparison of other scenario which also uses nearby station’s climatic data. The LSSVR models again are found to be better than the FGA and M5Tree models. LSSVM generally performs superior to the FGA and M5Tree in forecasting daily stream flow of Hunza River using local stream flow and climatic inputs. Based on the results of study, LSSVR model is recommended for monthly and daily runoff prediction of HRC with or without local climatic data.
Thermal imaging of a shattering freezing water droplet
Authors: Kleinheins Judith , Kiselev Alexei , Keinert Alice , Leisner Thomas
Published: March 2020

The freezing of a supercooled water drop freely falling through a mixed-phase cloud is an ubiquitous natural process fundamental for the formation of precipitation in clouds. The freezing is known to proceed in two stages: first, a network of ice dendrites spreads across the volume of a supercooled droplet resulting in ultrafast release of latent heat and warming of the droplet up to the melting point of ice; during the second stage a solid ice shell grows from the outside into the droplet, leading to a pressure increase inside the liquid core. Once the pressure gets too high, either the shell cracks open or the droplet explodes. The resulting secondary ice fragments start growing in the water-saturated environment or cause the freezing of neighbouring droplets. This secondary ice production mechanism is important for the rapid glaciation of mixed-phase clouds, however, the details of the underlying mechanisms are poorly understood. To quantify this process of ice multiplication, the evolution of the droplet’s surface temperature during the second freezing stage was investigated with a high-resolution infrared thermography system (INFRATEC). Drops of about 300 µm diameter were levitated in an electrodynamic trap under controlled conditions with respect to temperature, humidity and ventilation. The surface temperature of the droplet was measured with the IR system while the freezing process and shattering of the freezing droplet was recorded by a high-speed video camera. Combining experimental results and comprehensive process modelling, we explore the thermodynamic conditions beneficial for secondary ice production upon freezing of freely falling drizzle droplets.
Characterizing the vertical concentration profiles of ship plumes with a microscale model - is it all Gaussian?
Authors: Badeke Ronny , Matthias Volker , Grawe David , Schlünzen Heinke
Published: March 2020

Accurate modeling of ship emissions is a topic of increasing interest due to the ever-growing global fleet and its emission of air pollutants. With the increasing calculation power of modern computers, numerical grid models can nowadays be used to analyze effects of shipping emissions from global to local scales. However, modeling entire ports and larger domains still requires a good representation for the vertical concentration profile of single ship plumes. As the shape of the plume strongly varies depending on parameters like plume temperature, ship-induced turbulence and meteorological conditions, the plume dilution does not always appear to be represented by a simple Gaussian distribution. In this work, the microscale model MITRAS is used to calculate vertical concentration profiles of ship plumes under varying technical and meteorological scenarios. The resulting curves are fitted with different mathematical curves (e.g. Gaussian, Polynomial and Gamma distribution) by a least square minimization approach and the best representations for individual scenarios are discussed.
Removal of range uncertainty of CW Wind Lidar by frequency modulation.
Authors: Peters Gerhard , Markmann Piet
Published: March 2020

Frequency Modulation (FM) is a well-known technology but was never used in Continuous Wave (CW) Wind Lidars. The reason is because range and velocity can only be resolved for single hard targets like vehicles but not for dispersed targets like atmospheric aerosol. Here we present a FMCW system that uses the established focusing method for ranging and in addition a frequency modulated transmit signal. The origin of the scattered radiation is localized by focusing in a limited measuring volume. Because of this – by applying FM – the unavoidable range-velocity ambiguity of CW Wind Lidars can be resolved similarly as for hard targets. This is particularly important in conditions with fog or low hanging clouds (coastal or mountainous areas) or distant moving obstacles behind the measuring volume, or generally spoken in cases with strong gradients of the backscatter cross section. While out-of-focus contributions is a well-known concern of CW Lidar, we will show examples from FMCW field measurements first time revealing quantitatively the range uncertainty based on focus distance. Not surprisingly this uncertainty increases with height range, where the focus becomes less well-defined. Furthermore, the FMCW Wind Lidar allows also to correct uncertainties of mechanical focus distance setting. This is also mainly important at larger ranges where the focus distance becomes very sensitive to mechanical tolerances. Moreover, auxiliary measurements of wind direction, that are needed by CW systems for removing the sign-ambiguity of velocity, are obsolete, and there is no lower threshold of measurable windspeed. As a consequence wind measurements are feasible in street canyons, forest clearings and any other environment with strong vertical gradients.
Spider webbing the land-atmosphere interface
Authors: Coenders-Gerrits Miriam , Schilperoort Bart
Published: March 2020

Worldwide 55-80% of the rainfall evaporates from the surface, making it a major water drain for the earth's water resources and a major supply of moisture to the atmosphere. Evaporation is relevant for crop growth and has a high impact on the severity of drought and floods. Nonetheless, this key process is still a highly uncertain, insufficiently quantified process. Also effecting weather forecasts as the available water is used as their boundary condition in atmospheric models. The persistent problem herein is our restricted understanding of the key processes of the land-atmosphere interface, as well as their interplay with hydrological and atmospheric processes. The major bottleneck is the difficulty to properly measure the land-atmosphere interface at the right spatial and temporal scale.

In this talk I will propose an experimental approach that enables data collection for the full surface energy balance at the land-atmosphere interface. This will be achieved by developing and exploiting a 'spider web' - like measurement approach with temperature measuring fibre optic cables (Distributed Temperature Sensing). This will enable simultaneously and continuously measurements of high-resolution temperature, humidity, wind, and soil moisture gradients. Which allows derivaiton of the sensible, latent, and ground heat flux and storage. The spider web offers a better representation of the land-atmosphere interface for the purpose to provide a knowledge base for improving flood and drought predictions and weather forecasts.
Luminescence dating challenges: about hiati and methodological considerations in the Urluia and Vlasca loess-paleosol sequences, Romania
Authors: Bösken Janina , Klasen Nicole , Constantin Daniela , Hambach Ulrich , Veres Daniel , Schmidt Christoph , Pötter Stephan , Zeeden Christian , Lehmkuhl Frank , Timar-Gabor Alida
Published: March 2020

Loess-paleosol sequences are in the focus of paleoenvironmental research because they offer potentially quasi-continuous terrestrial records of environmental change. For the research on paleoenvironments, paleoclimates, and human evolution studies reliable dating approaches are essential. Age models can be based on different methods, e.g. proxy data correlation and chronometric dating approaches. For the Urluia loess-paleosol sequence, which provides a high-resolution record covering the Last Glacial Cycle in the Lower Danube-Black Sea area (Romania), correlative and luminescence age models do not agree with each other (Bösken et al., 2018). While the results of internal quality checks of the luminescence data speaks for a reliable chronology, the radiometric ages of samples assigned to the MIS 4-5 interval based on stratigraphic evidence are significantly overestimated. As ages in the lower half of the section do not increase with depth, field saturation has been suggested, while new measurements indicate that laboratory saturation has not been reached. This contribution presents a detailed luminescence dating approach using OSL and pIRIR protocols for fine-grain quartz and polymineral samples. Furthermore, the geochronology of the Vlasca loess-paleosol sequence that is located at the bank of the Danube ~40 km north of Urluia is presented. The section was chosen because it contains a vast accumulation of loess with one prominent paleosol at the bottom (total height ~27 m), presumably covering a similar time-interval as the Urluia sequence. The dating approach includes fine-grain quartz, coarse-grain quartz, polymineral pIRIR225, and portable OSL measurements. The question whether the observed discrepancy between the dating results and the stratigraphy at Urluia represents a regional pattern and/or possibly intrinsic luminescence properties are responsible will be discussed.

References

Bösken, J., Zeeden, C., Hambach, U., Veres, D., Klasen, N., Brill, D., Burow, C., Obreht, I. and Lehmkuhl, F. (2018). Consistency challenges between correlative and luminescence age models for the last ~150 ka in the Lower Danube Basin loess-paleosol sequences. Geophysical Research Abstracts 20, EGU2018-7986, EGU General Assembly 2018.
Night-Time Cooling of Surface Water: Laboratory experiment and numerical simulation
Authors: van de Giesen Nick , Selker John , Hilgersom Koen , Solcerova Anna
Published: March 2020

In the framework of the Small Reservoirs Project (www.smallreservoirs.org), evaporation in semi-arid areas from open water has been measured through water balances, floating evaporation pans, and eddy covariance measurements. Each method showed that the actual evaporation was 30%-50% less than the evaporation from open water as predicted by Penman. During daytime, this reduced evaporation may be due to the formation of a stable internal boundary layer over the reservoirs. One would expect that this evaporation reducing effect would at least partially be offset during the night when the warm water would induce strong turbulent transport through an unstable local boundary layer. Through detailed Distributed Temperature Sensing observation in ponds, lakes, and reservoirs in different parts of the world, it was observed that during cloudless nights with low wind speeds or no wind, the top layer (1cm-2cm) of the water was one to two degrees colder than the air immediately above it. Such a temperature difference would again set up a stable layer, hindering turbulent transport of heat and water vapor into the atmosphere. 

 

It was hypothesized that outward longwave radiation, which during cloudless nights can quickly reach 200 W/m2, would cause a thin layer of cold water on top of the warmer water body. Through conduction, this cold layer would grow until it would become unstable, at which point the surface would be (partially) refreshed through downward finger flow. Detailed numerical simulations of the heat transport in the water body were undertaken to test this hypothesis. The numerical results indeed showed the cooling of the top layer and formation of instabilities with characteristic length and time scales. To test these results and the general concept, a MacGyver-worthy laboratory set-up was built consisting of an insulated 20 liter bucket, covered by a double hemispheric dome of perspex. On the inside of the dome, a thermal camera was attached at the apex. The space between the inner and outer dome was filled with dry ice to create an inside surface temperature of about 230K. After the dry ice was added, surface cooling was observed, followed by the formation of zones with upwelling warm water and downwelling cold water. These circulation cells were comparable in size to the simulated ones. A detailed analysis of spatial and temporal scales of the laboratory and simulation results will be presented.
Stochastic Local Interaction Models for Processing Spatiotemporal Datasets
Authors: Hristopulos Dionissios , Agou Vasiliki , Pavlides Andreas , Gkafa Panagiota
Published: March 2020

We present recent advances related to Stochastic Local Interaction (SLI) models. These probabilistic models capture local correlations by means of suitably constructed precision matrices which are inferred from the available data. SLI models share features with Gaussian Markov random fields, and they can be used to complete spatial and spatiotemporal datasets with missing data.  SLI models are applicable to data sampled on both regular and irregular space-time grids.  The SLI models can also incorporate space-time trend functions. The degree of localization provided by SLI models is determined by means of kernel functions and appropriate bandwidths that adaptively determine local neighborhoods around each point of interest (including points in the sampling set and the map grid). The local neighborhoods lead to sparse precision (inverse covariance) matrices and also to explicit, semi-analytical relations for predictions, which are based on the conditional mean and the conditional variance.

We focus on a simple SLI model whose parameter set involves amplitude and rigidity coefficients as well as a characteristic length scale. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. The parameter estimation is based on the method of maximum likelihood estimation (MLE). However, covariance matrix inversion is not required, since the precision matrix is known conditionally on the model parameters. In addition, the calculation of the precision matrix determinant can be efficiently performed computationally given the sparsity of the precision matrix.  Typical values of the sparsity index obtained by analyzing various environmental datasets are less than 1%. 

We discuss the results of SLI predictive performance with both real and simulated data sets. We find that in terms of cross validation measures the performance of the method is similar to ordinary kriging while the computations are faster.  Overall, the SLI model takes advantage of sparse precision matrix structure to reduce the computational memory and time required for the processing of large spatiotemporal datasets.  

 

References

D. T. Hristopulos. Stochastic local interaction (SLI) model: Bridging machine learning and geostatistics. Computers and Geosciences, 85(Part B):26–37, December 2015. doi:10.1016/j.cageo.2015.05.018.

D. T. Hristopulos and V. D. Agou. Stochastic local interaction model for space-time data. Spatial Statistics, page 100403, 2019. doi:10.1016/j.spasta.2019.100403.

D. T. Hristopulos, A. Pavlides, V. D. Agou, P. Gkafa. Stochastic local interaction model for geostatistical analysis of big spatial datasets, 2019. arXiv:2001.02246
Comparison of Quantitative Precipitation Estimation Using Spatial Interpolation methods in Bukhan River Basin
Authors: Yoon Sanghoo , Kim Junseok , Kwon Taeyong
Published: March 2020

Quantitative precipitation estimation is needed to reduce damages from weather disasters such as torrential rain. This study is dealt with estimates of the quantitative precipitation using multiple spatial interpolation methods and compares the results. Inverse distance weight method and k-nearest neighborhood algorithm were considered as a deterministic approach and the general additive model and kriging methods were used as a stochastic approach. To evaluate the prediction performance, leave-one-out cross-validation was performed with the root mean squared error (RMSE), mean absolute error (MAE), bias, and correlation coefficient. The research data were rain gauged and radar data in the Bukhan river, which were collected from May 2018 to August 2019. The results showed that the inverse distance weight method reflected the spatial rainfall characteristics well. However, caution is needed because the best models vary depending on the pattern of rainfall in the sense of RMSE.

*This work was supported by KOREA HYDRO & NUCLEAR POWER CO., LTD(No. 2018-Tech-20)
Tipping Points in the Climate System and the Economics of Climate Change
Authors: Rising James , Dietz Simon , Stoerk Thomas , Wagner Gernot
Published: March 2020

Tipping points in the climate system are a key determinant of future impacts from climate change. Current consensus estimates for the economic impact of greenhouse gas emissions, however, do not yet incorporate tipping points. The last decade has, at the same time, seen publication of over 50 individual research papers on how tipping points affect the economic impacts of climate change. These papers have typically incorporated an individual tipping point into an integrated climate-economy assessment model (IAM) such as DICE to study how the the tipping point affects economic impacts of climate change such as the social cost of carbon (SC-CO2). This literature, has, however, not yet been synthesized to study the joint effect of the large number of tipping points on the SC-CO2. SC-CO2 estimates currently used in climate policy are therefore too low, and they fail to reflect the latest research.

This paper brings together this large and active literature and proposes a way to jointly estimate the impact of tipping points. In doing so, we bridge an important gap between climate science and climate economics. To do so, we develop a new integrated assessment model with frontier characteristics: a tractable geophysical module for each tipping point, damage functions based on recent climate econometric advances, and disaggregated climate change impacts at the national level, including from sea-level rise. In this model, we consider the following tipping points: the permafrost carbon feedback, the dissociation of ocean methane hydrates, Amazon forest dieback, the disintegration of the Greenland ice sheet, the disintegration of the West Antarctic ice sheet, the slowdown of the Atlantic Meridional Overturning Circulation, changed patterns of the India summer monsoon, and changes in surface albedo feedback (also referred to as Arctic sea-ice loss).

 

Our preliminary findings show that the geophysical tipping points tend to increase the economic impact of climate change, with a combined effect of increasing the social cost of carbon (SC-CO2) by 14%-43%. The largest contributions to this increase come from methane-related tipping points.
Comprehensive evaluation of the effects of climate change and land use and land cover change variables on runoff and sediment discharge
Authors: Zhang Huilan
Published: March 2020

Climate change and various human activities have resulted in noticeable changes in watershed hydrological and soil erosion regimes. In this study, a comprehensive investigation was conducted to distinguish between the effects of climate variables and those of land use and land cover change (LUCC) variables on runoff and sediment discharge in a watershed located at upper reaches of the Yangtze River. Statistical analysis results revealed significant and slight increasing trends in runoff and sediment discharge, respectively. Abrupt changes occurred in 1974 and 1995, which divided the entire time series into a decrease–increase–decrease tendency pattern; this pattern was the response to climate changes and the Reforestation and Returning Farmland to Forest project in China. In addition, redundancy analysis was used for partition statistical analyses, and the contributions of climate change and LUCC to runoff and sediment discharge were at the ratio of 4:1. Since 1990, the effect of LUCC has increased notably and its relationship with hydrological variables changed from positive to negative in approximately 1995. Finally, simulations performed using the distributed Basic Pollution Calculation Center (BPCC) model confirmed that climate and LUCC variables reduced the runoff depth and sediment load between 1980 and 2003. The contributions of climate fluctuation and LUCC to runoff depth were at the ratio of 5:1, and those to sediment load were at the ratio of 3:1, which exhibited the dominant role of climate change and the high sensitivity of sediment load to human interference. Overall, the results of distributed hydrological modeling were consistent with those of statistical analyses. The results provided detailed information and explained the mechanics underlying hydrological processes and soil erosion.

 
A 25-kyr record of East African monsoon variability: Insights from grain-size distributions and end-member modeling of siliciclastic sediments from Lake Chala
Authors: Meyer Inka , Van Daele Maarten , Thange Niels , Verschuren Dirk , De Batist Marc
Published: March 2020

Terrigenous particles deposited in all kinds of sedimentary records (terrestrial, marine and lacustrine) have proven to yield valuable information for reconstruction of paleo-climate and paleo-environments. Natural sediments typically represent a mixture of deposits of diverse provenance, potentially supplied by different transport processes, expressed in a bi-or poly-modal grain-size distribution. Recently, complex mathematical-statistical end-member models have been developed to disentangle the different sub-populations within one grain-size distribution, which are then assumed to represent a distinct sediment fraction that has a single provenance and/or was transported by the same process to the site of deposition.

Here we present end-member modeling results of the terrigenous sediment fraction in a 25-kyr sediment sequence from Lake Chala (Kenya/Tanzania), revealing valuable information on climate and environmental change in equatorial East Africa since the Last Glacial Maximum (LGM). Calculated end members could be related to distinct source areas and transport processes, namely to fine aeolian dust, fine-grained soil runoff, coarser aeolian dust from proximal sources and coarse erosive material originating from the crater rim surrounding the lake. Variations in the occurrence of distal versus proximal dust is suggested to be a reliable indicator for changes in East African monsoon circulation. During Northern Hemisphere cold periods, such as the LGM and Younger Dryas (YD), wind systems associated with the Intertropical Convergence Zone (ITCZ) were pushed southward, causing a more intense influence of the NE monsoon at Lake Chala. This resulted in high amounts of fine dust originating from the Horn of Africa region. At the same time, SE monsoon circulation was diminished due to a reduced atmospheric pressure gradient between the Asian/Indian continent and the Indian Ocean. Influx of coarse dust from proximal sources, which are mostly located east of Lake Chala, was impossible due to the weaker SE monsoon circulation. After termination of the YD, rapid reestablishment of the SE monsoon in the Early Holocene is recorded by an abrupt increase in the influx of coarse dust.

Lake Chala sediments contain one of the few continuous and high-resolution climate records in East Africa spanning the past 25 kyr, providing detailed information on long-term climate variation in an area highly sensitive to hydrological variations. Subdividing the clastic sediment fraction into statistically robust end members produces multiple quantitative and independent proxies to help reconstruct this region’s climate and environmental history.
Coating material-dependent differences in modelled lidar-measurable quantities for heavily coated soot particles
Authors: Kanngiesser Franz , Kahnert Michael
Published: March 2020

The depolarisation ratio of heavily coated soot particles was previously found to be sensitive to the chemical composition of the coating material, which is reflected by the refractive index. Employing the Discrete Dipole Approximation code ADDA optical calculations were performed with a set of heavily coating soot aggregates with two different coating materials at 355 nm, 532 nm, and 1064 nm. As coating materials sulphate and a toluene-based material were assumed. The soot aggregates were modelled based on results reported from in-situ field measurements and using a coating model, which allows for a tunable transition between film coating and spherical shell coating. The aggregates’ size was varied by increasing the number of soot monomers inside each aggregate from 26 to 1508 in linearly equidistant steps.

Size-averaged lidar-measureable quantities for the coated aggregates, such as the linear depolarisation ratio, the extinction-to-backscatter ratio (lidar ratio), and the Ångström exponents of the extinction coefficient, the backscatter coefficient, and the extinction-to-backscatter ratio were calculated, and the error of the simulations was estimated. With the exception of the linear depolarisation ratio at 1064 nm these observables do not overlap within the estimated error bounds. As the coating materials result in clearly distinguishable lidar observables, information on the chemical composition of coated soot aerosol can potentially be inferred from lidar measurements.

 

 
Combined numerical and experimental study of microstructure and permeability in porous granular media
Authors: Eichheimer Philipp , Thielmann Marcel , Fujita Wakana , Golabek Gregor J. , Nakamura Michihiko , Okumura Satoshi , Nakatani Takayuki , Kottwitz Maximilian O.
Published: March 2020

Fluid flow on different scales is of interest for several Earth science disciplines like petrophysics, hydrogeology and volcanology. To parameterize fluid flow in large-scale numerical simulations (e.g. groundwater and volcanic systems), flow properties on the microscale need to be considered. For this purpose experimental and numerical investigations of flow through porous media over a wide range of porosities are necessary. In the present study we sinter glass bead media with various porosities, representing shallow depth crustal sediments. The microstructure, namely effective porosity and effective specific surface, is investigated using image processing. We furthermore determine flow properties like hydraulic tortuosity and permeability using both experimental measurements and numerical simulations. By fitting microstructural and flow properties to porosity, we obtain a modified Kozeny-Carman equation for isotropic low-porosity media, that can be used to simulate permeability in large-scale numerical models. To verify the modified Kozeny-Carman equation we compare it to the numerically computed and experimentally measured permeability values.
Airborne Measurements of Formaldehyde In Biomass Burning and Urban Plumes In Central Africa Using Laser Induced Fluorescence
Authors: Ronnie Grace , Whalley Lisa , Heard Dwayne , Ingham Trevor , Lee James , Pasternak Dominka , Bauguitte Stéphane , Carling Rebecca , Bannan Thomas , Wu Huihui , Archibald Alexander
Published: March 2020

Formaldehyde is a key intermediate in photochemical oxidation of volatile organic compounds in the troposphere and is also directly emitted by a range of sources, including biomass burning and fuel combustion. Airborne measurements of formaldehyde have therefore been used to investigate oxidation in biomass burning (BB) plumes intercepted during the Methane Observations and Yearly Assessments (MOYA) campaign. The MOYA campaign took place January/February 2019 in Uganda and Zambia and mixing ratios of formaldehyde were obtained using the University of Leeds formaldehyde Laser Induced Fluorescence (LIF) instrument. A range of air masses were intercepted including multiple near-field biomass burning (BB) plumes, with up to 140 ppb of formaldehyde observed, and urban emission plumes from the capital city of Kampala in Uganda, where up to 7 ppb of formaldehyde was measured. Formaldehyde emission factors have been calculated for Ugandan BB (1.20 ± 0.23 g kg-1) which agree well with literature (1.23 ± 0.65 g kg-1) for Savannah combustion. Production of formaldehyde as a function of plume age has also been investigated in order to discriminate direct emission from photochemical formation in BB plumes. BB plumes were also intercepted during other aircraft campaigns several days downwind of emission such as a plume transported from Canadian wildfires observed in the North Atlantic during ACSIS-5/ARNA-1 where levels of up to 18.30 ppb were detected, indicative of sustained photochemical oxidation within the plume. Comparison of urban, near-field BB and far-field BB plumes provides a variety of environments and photochemical ages to test our understanding of combustion oxidation processes.