Earth & Space Science

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https://hdl.handle.net/10315/27626

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Open Access
Deep Convolutional Neural Network Based Single Tree Detection Using Volumetric Module From Airborne Lidar Data
(2023-03-28) Lee, Hyungju; Sohn, Gunho; Ko, Connie
There was an undeniable success of Deep Learning networks for visual data analytics such as object detection and segmentation in recent years, while the adaptation to tree detection has been rare. In this paper, we pursue to achieve individual tree identification, defined as a detection of an individual tree as each object, with deep convolutional neural networks to create and update tree inventories using LiDAR information. The first objective was to provide a suitable dataset that can be used to test such networks and to create a module that attempts to increase the 3D object detection algorithms' detection accuracy. This novel dataset was created by fusing LiDAR data gathered by Teledyne Optech with field data collected by York University. The second was to develop an appropriate accuracy increasing volumetric module. For this module, the learnable weights concept was introduced, which enable to increase detection precision of the object detection algorithm.
Open Access
Development of Advanced Remote Sensing Methods in Quantifying Wildlife Habitat Management
(2023-03-28) Zhang, Wen; Hu, Baoxin; Brown, Glen
Wildlife habitats have been affected by human activities and climate change. Animal diversity is declining at an unprecedented rate. Tools used to obtain a rapid assessment of wildlife habitats at different scales are urgently needed. The habitat management tools that are currently used for conservation and monitoring wildlife are often limited by the availability of mapped habitat information that is tailored to the wildlife of interest and that covers appropriate geographic and temporal extents of interest. Failure to adequately map specific habitat features can limit effective management. Advancements in remote sensing and related technologies have increased the resolution and quantity of landscape data, providing an excellent opportunity to extract various environmental features for examining habitat selection and mapping wildlife habitats to a broad extent. To exploit the potential of the emergent remote sensing data sets, the focus of this study was to develop advanced methodologies to derive information related to the properties of environmental features at different scales and to generate tools to improve the understanding of a wildlife habitat landscape that can benefit from habitat management. Specifically, an advanced algorithm was developed that utilized spatial pattern analysis to classify the forest succession stages from optical imagery and had a classification accuracy of 89%. In addition, a novel method was proposed to extract road features from the road structure knowledge followed by a deep learning VGG 16 classification for a refined output. An overall accuracy of 74% was achieved for the forest road extraction. A robust and operational stepwise automatic thresholding method was developed to accurately map the dynamics of surface water bodies from SAR data, with an overall accuracy of 95%. In addition, an advanced fuzzy AHP model was utilized to accurately map beaver-altered wetlands in the landscape using remote sensing products derived based on the knowledge of beaver activities, where an average of 83.0% of the known beaver dams and 72.5% of the known beaver ponds were correctly identified. In conclusion, this research demonstrated that the advanced methods utilizing multi-source and multi-temporal remote sensing data could effectively characterize and extract environmental features that benefit wildlife habitat management.
Open Access
Active Reinforcement Learning for the Semantic Segmentation of Images Captured by Mobile Sensors
(2023-03-28) Jodeiri Rad, Mahya; Armenakis, Costas
Neural Networks have been employed to attain acceptable performance on semantic segmentation. To perform well, many supervised learning algorithms require a large amount of annotated data. Furthermore, real-world datasets are frequently severely unbalanced, resulting in poor detection of underrepresented classes. The annotation task requires time-consuming human labor. This thesis investigates the use of a reinforced active learning as region selection method to reduce human labor while achieving competitive results. A Deep Query Network (DQN) is utilized to identify the best strategy to label the most informative regions of the image. A Mean Intersection over Union (MIoU) training performance equivalent to 98% of the fully supervised segmentation network was achieved with labeling only 8% of dataset. Another 8% of labelled dataset was used for training the DQN. The performance of all three segmentation networks trained with regions selected by Frequency Weighted Average (FWA) IoU is better in comparison with baseline methods.
Open Access
Energy-saving Trajectory And Control Design For Quadrotors With Slung Payloads
(2023-03-28) Alkomy, Hassan Mohammad Hassan; Shan, Jinjun
Quadrotors have promising applications such as payload transportation, which can change the future of the package delivery industry. However, many challenges block the way of implementing payload transportation in reality. Slung payload vibrations and quadrotor's energy consumption are among the major challenges, which are related to each other because payload vibrations affect energy consumption. In this dissertation, the kinematics, dynamics, and energy models are first developed for both a single quadrotor and a transportation system consisting of a quadrotor with a slung payload. The proposed energy model is novel and introduces the concepts of power and energy quotients that, unlike the existing models, do not depend on quadrotor-related parameters such as motor and propeller parameters. This is the first energy model for such a transportation system. Second, this dissertation focuses on polynomial trajectories, where a generic framework to design feasible polynomial trajectories of arbitrary degree with a large number of waypoints is presented. This allows for extending the capabilities of polynomial trajectories to overcome some kinematic limitations associated with continuous-path trajectories, e.g., arbitrary kinematic constraints. Third, extensive vibration analyses of the transportation system and polynomial trajectories are conducted. As a result, a novel controller-independent payload vibration reduction method is proposed. The proposed method is more generic than the existing methods, e.g., anti-swing controllers. Fourth, the effects of polynomial trajectories, payload mass, and cable length on quadrotor's energy consumption are studied. The comparison with an energy-minimized trajectory shows that polynomial trajectories are not only energy-efficient, but their design is simpler than energy-minimized trajectories and does not require quadrotor-related parameters. Lastly, a robust energy-saving sliding mode controller with input saturation is designed for the transportation system. The experimental results show that the proposed controller is robust and energy-efficient when, qualitatively, compared with an existing energy-saving controller. The proposed controller is the first energy-saving controllers for such a transportation system. This dissertation opens the door for package delivery with quadrotors by providing the first energy analysis, and energy-saving trajectories and controllers for quadrotors with slung payloads.
Open Access
A BIM - GIS Integrated Information Model Using Semantic Web and RDF Graph Databases
(2023-03-28) Hor, Abdelhadi; Sohn, Gunho
In recent years, 3D virtual indoor and outdoor urban modelling has become an essential geospatial information framework for civil and engineering applications such as emergency response, evacuation planning, and facility management. Building multi-sourced and multi-scale 3D urban models are in high demand among architects, engineers, and construction professionals to achieve these tasks and provide relevant information to decision support systems. Spatial modelling technologies such as Building Information Modelling (BIM) and Geographical Information Systems (GIS) are frequently used to meet such high demands. However, sharing data and information between these two domains is still challenging. At the same time, the semantic or syntactic strategies for inter-communication between BIM and GIS do not fully provide rich semantic and geometric information exchange of BIM into GIS or vice-versa. This research study proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graph databases. The suggested solution's originality and novelty come from combining the advantages of integrating BIM and GIS models into a semantically unified data model using a semantic framework and ontology engineering approaches. The new model will be named Integrated Geospatial Information Model (IGIM). It is constructed through three stages. The first stage requires BIMRDF and GISRDF graphs generation from BIM and GIS datasets. Then graph integration from BIM and GIS semantic models creates IGIMRDF. Lastly, the information from IGIMRDF unified graph is filtered using a graph query language and graph data analytics tools. The linkage between BIMRDF and GISRDF is completed through SPARQL endpoints defined by queries using elements and entity classes with similar or complementary information from properties, relationships, and geometries from an ontology-matching process during model construction. The resulting model (or sub-model) can be managed in a graph database system and used in the backend as a data-tier serving web services feeding a front-tier domain-oriented application. A case study was designed, developed, and tested using the semantic integrated information model for validating the newly proposed solution, architecture, and performance.
Open Access
Technology for Low Resolution Space Based RSO Detection and Characterisation
(2023-03-28) Clark, Ryan William; Lee, Regina
Space Situational Awareness (SSA) refers to all activities to detect, identify and track objects in Earth orbit. SSA is critical to all current and future space activities and protect space assets by providing access control, conjunction warnings, and monitoring status of active satellites. Currently SSA methods and infrastructure are not sufficient to account for the proliferations of space debris. In response to the need for better SSA there has been many different areas of research looking to improve SSA most of the requiring dedicated ground or space-based infrastructure. In this thesis, a novel approach for the characterisation of RSO’s (Resident Space Objects) from passive low-resolution space-based sensors is presented with all the background work performed to enable this novel method. Low resolution space-based sensors are common on current satellites, with many of these sensors being in space using them passively to detect RSO’s can greatly augment SSA with out expensive infrastructure or long lead times. One of the largest hurtles to overcome with research in the area has to do with the lack of publicly available labelled data to test and confirm results with. To overcome this hurtle a simulation software, ORBITALS, was created. To verify and validate the ORBITALS simulator it was compared with the Fast Auroral Imager images, which is one of the only publicly available low-resolution space-based images found with auxiliary data. During the development of the ORBITALS simulator it was found that the generation of these simulated images are computationally intensive when propagating the entire space catalog. To overcome this an upgrade of the currently used propagation method, Specialised General Perturbation Method 4th order (SGP4), was performed to allow the algorithm to run in parallel reducing the computational time required to propagate entire catalogs of RSO’s. From the results it was found that the standard facet model with a particle swarm optimisation performed the best estimating an RSO’s attitude with a 0.66 degree RMSE accuracy across a sequence, and ~1% MAPE accuracy for the optical properties. This accomplished this thesis goal of demonstrating the feasibility of low-resolution passive RSO characterisation from space-based platforms in a simulated environment.
Open Access
Thermal Control Design for a Space-Borne On-Chip Optical Phased Array
(2022-12-14) Zonta, Nicholas Sebastian; Lee, Regina
The thermal control and model-based analysis is an integral part of developing an optical photonics device such as the proposed Optical Phased Array (OPA). This research is to model and implement the thermal control hardware and algorithm to keep the OPA at a stable temperature during operation. Detailed COMSOL models of the OPA and supporting hardware demonstrated that a constant setpoint results in consistent and proportional low levels of thermal crosstalk. A thermal feedback controller and supporting hardware was designed and tested to improve the overshoot and settling time. The system for the OPA includes both a solid state thermo-electric cooler (TEC), and the custom PCB interface between them. The controller was tuned experimentally and simulation analysis. The results indicate that a combination of the heuristic Zeigler-Nichols classic method and simulated input dependent experimental transfer function method yields the fastest settling times at 18.5 and 27.5 seconds.
Open Access
Design of a Shape Memory Alloy Coil Actuated Robotic Finger with Compliant Joint Antagonists
(2022-12-14) Tangestanian, Arvin; Orszulik, Ryan
This thesis investigates the development of a 3D-printable finger with compliant joints actuated by shape memory alloy (SMA) coils. This work presents the design, manufacturing, and characterization of the compliant finger mechanism, the SMA coil actuators, and an integrated prototype from analytical and experimental methods. The compliant finger mechanism is 3D-printed using thermoplastic polyurethane. Characterization of the mechanism exhibits a hysteresis profile in the force-displacement domain. The SMA coils are designed using a static two-state model, based on the required actuation stroke at discrete force-displacement coordinates. SMA coils are manufactured and characterized to obtain the actuator profiles for the SMA. The experimental profiles for the actuator and structure are used to predict equilibrium points between the two hysteresis curves. The final assembly with an SMA coil actuating the compliant mechanism is tested, and the experimental results show the actuation stroke and bias distance match the predictions from the hysteresis analysis.
Open Access
Modeling and Observing Atmospheres of Terrestrial Exoplanets
(2022-12-14) Nguyen, Tue Giang; Moores, John
The recent launch of the James Webb Space Telescope (JWST) allows us to observe more exoplanets and in greater detail. Now that we can characterize terrestrial planets and their atmospheres, this dissertation features several theoretical works that study atmospheric dynamics and infer observability. First, we explore the processes of non-collisional atmospheres to determine the tendency of exospheric volatile transport. We use a Monte Carlo simulation to infer water cold-trapping efficiency for different planetary configurations and find that there are optimal conditions for planetoids to accumulate water on the surface. Planetoids outside these conditions are either too small and thus lose water to thermal escape, or too large and lose water to photodissociation. Bodies similar in size to the moon are ideal for cold-trapping water, which gives great insight into the solar system and its history. Planetoids that build large reservoirs of water, or other volatiles, can evolve to form observable transient collisional atmospheres. While only relatively small planetoids are subjected to exospheric dynamics and therefore not ideal for observations outside the solar system, the dynamics of a half collisional, half non-collisional atmosphere are present in lava planets. Because of the relative ease in observing these planets, they are currently the best target for detecting a rocky exoplanet atmosphere. We modelled the flow of lava planet K2-141b’s silicate atmosphere and inferred atmospheric pressure, temperature, and wind speed. We found that SiO should be the dominant gas species and that winds reach supersonic speed, typical for lava planets. However, our analysis where we coupled radiative transfer to the hydrodynamics suggests that the large wind speed induced from a large negative lapse rate cools down the atmosphere much more than previously thought. Therefore, the simulated eclipse spectrum shows absorptive SiO spectral features, as opposed to emission features, that are prominent enough to be observed with JWST. However, the atmosphere is still too thin and the transit depth too small, making observing K2-141b’s atmosphere via transmission spectroscopy too difficult with the current technology.
Open Access
An Investigation of Turbulence and Diffusion within Vehicle Wakes and On-Road Measurements using an Instrumented Mobile Car and a Stationary Roadside Monitoring System
(2022-12-14) Miller, Stefan John; Gordon, Mark
Moving motor vehicles emit pollutants that negatively impact human health. Stationary roadside measurements alone are not sufficient to quantify the pollutant–flow interactions that occur behind moving vehicles. The instrumented mobile car however is well–suited for on–road measurements, but has been underutilized for this purpose since limited studies have investigated its accuracy at high vehicle speeds. Thus, this work details two on–road measurement campaigns using an instrumented car, with three main objectives: (1) study the vehicle momentum wake and vehicle–induced turbulence (VIT), (2) investigate the accuracy of the mobile system for measuring atmospheric means, variances and covariances, and (3) quantify the emission of aerosols and CO2 by on–road vehicles and their subsequent diffusion. Measurements behind on–road vehicles demonstrate that VIT decays with increasing distance following a power law relationship. Comparison of measurements with prior on–road studies suggests a height dependence of VIT in vehicle wakes, and an extended parameterization is outlined that describes the total on–road turbulent kinetic energy (TKE) enhancement due to a composition of vehicles, including a vertical dependence on the magnitude of TKE. Next, a wavelet–based approach to remove the effects of sporadic passing traffic is developed and applied to a measurement period during which a heavy–duty truck passes in the opposite highway lane; removing the times with traffic in this measurement period gives a 10% reduction in the TKE. When sampling uncertainties are considered, the vertical momentum flux measured on the car is found to be not different from roadside measurements in the 95% confidence interval. The first on–road and in–traffic measurements of the vertical turbulent particle number flux and the vertical turbulent CO2 flux are presented and the results suggest this technique could be further developed to measure individual vehicle emission rates while driving. The lateral width of the wake generated by each passing vehicle is estimated using the stationary roadside measurements, and is determined to be a factor of 5 times greater for heavy–duty trucks relative to sport utility vehicles and passenger cars at a distance of 150 m behind the vehicle.
Open Access
How Does Coupled Tropospheric Chemistry Affect Climate? An Investigation Using the Community Earth System Model Version 2
(2022-12-14) Stanton, Noah Alexander; Tandon, Neil
The depiction of tropospheric chemistry in climate models has greatly improved in recent years. The Community Earth System Model version 2 with Whole Atmosphere Community Climate Model version 6 (CESM2-WACCM6) has implemented fully-coupled tropospheric chemistry with 231 chemical species, an updated aerosol scheme, as well as a fully-coupled ocean. To examine the impacts of these improvements, 100-year preindustrial control simulations were run using the following two configurations 1) a “simplified” CESM2-WACCM6 configuration in which coupled chemistry is confined to the middle atmosphere, and 2) the standard CESM2-WACCM6 configuration with fully-coupled chemistry over all atmospheric levels. Regional differences in surface temperature and the CRE range between -5 K and 5 K and -10 W m-2 to 10 W m-2, respectively. Dynamical changes include an equatorward shift of the mid-latitude jets and weakening of the Southern Hemisphere stratospheric polar vortex. The equatorward shifts of the jets are due to widespread tropospheric cooling.
Open Access
A Deep Learning Approach to the Detection and Tracking of Moving Objects in 2D Point Clouds
(2022-12-14) Schofield, Hunter Liam; Shan, Jinjun
The detection and tracking of moving objects (DATMO) are crucial tasks that any autonomous vehicle must perform. Autonomous vehicles must detect and track all obstacles to ensure safety within the environment while also completing their tasks efficiently. In autonomous driving research, LiDAR is becoming increasingly popular due to its high resolution and accuracy. There are many state-of-the-art DATMO methods using LiDAR, however, most methods are designed for 3D LiDAR sensors. Methods that work for 2D LiDAR sensors are not as robust as their 3D counterparts or require too many computational resources to run efficiently on less powerful robots. This research presents two robust solutions to the DATMO problem based on deep learning techniques that can scale to meet a variety of hardware constraints. The first solution, detect while track (DWT), combines a convolutional neural network (CNN) with a multiple hypothesis tracking (MHT) approach and Kalman filter. The second solution, pixel predictions for future-oriented bounding boxes (PIXFOR), combines a CNN with a recurrent network architecture to solve both detection and tracking problems in a single forward pass. Both methods are experimentally validated on an unmanned ground vehicle (UGV) operating on an intersection scenario and a highway scenario using 2D point clouds collected from simulation and hardware environments. The run-time performance of both methods is also validated different hardware platforms to show that the methods can scale to meet different hardware constraints. When compared to state-of-the-art DATMO methods, the newly proposed methods outperform in the object detection and tracking tasks, while operating at a faster run time on equivalent hardware.
Open Access
Dynamics & Mammatus Clouds in the Anvil Outflow of Deep Convection Over the Tiwi Islands
(2022-12-14) Howard, Shaya George; Whiteway, James A.
The research that is presented in this thesis is based on data that comes from the EMERALD-2 research campaign. EMERALD-2 focused on “Hector” which is a convective system that occurs regularly over the Tiwi Islands, just off the coast of northern Australia. On December 2nd, 2002 mammatus clouds developed on the base of the anvil outflow cirrus clouds produced by Hector. During the experiment, the Egrett & King Air research aircraft carried instruments that measured temperature, pressure, wind velocity, moisture & cloud structure in the anvil outflow of Hector. The main objective was to analyze the data and identify a possible formation mechanism for the mammatus clouds. Atmospheric conditions were favourable for cloud base detrainment instability and a density overhang to cause the formation of mammatus clouds. It was found that the gradients of liquid water static energy and potential temperature were negative at the base of the Mammatus clouds.
Open Access
Fusion Approaches to Individual Tree Species Classification Using Multi-Source Remotely Sensed Data
(2022-12-14) Li, Qian; Hu, Baoxin
Tree species information plays essential roles in urban ecological management and sustainable development, and thus tree species classification has been an active research topic over the years. This study investigated fusion approaches deployed with Support Vector Machine (SVM) and Random Forest (RF) algorithms to incorporating multispectral imagery (MSI), a very high spatial resolution panchromatic image (PAN), and Light Detection and Ranging (LiDAR) data for five object-based tree species classification in an urban environment. The results demonstrated that 3D structural features contributed more to tree species with broad crowns, such as honey locust and Austrian pine, whereas textural features were more effective in differentiating trees in narrow crowns, such as spruce. Among all the possible classification schemes based on multi-source features in combinations, decision fusion achieved the best overall accuracies (0.86 for SVM and 0.84 for RF), slightly outperforming the feature fusion approach (0.85 for SVM and 0.83 for RF). Both fusion approaches significantly improved tree species classifications produced by MSI (0.7), PAN (0.74), and LiDAR (0.8) individually.
Open Access
Extraplanetary Exploration Using Electric Solar Wind Sail
(2022-12-14) Du, Chonggang; Zhu, George Z.H.
This doctoral research investigates the problems in the dynamics and control of extraplanetary exploration using an electric solar wind sail (E-sail). The E-sail is a novel propellantless propulsion technology that harvests energy by repelling the charged particles in solar wind. It consists of a spinning central spacecraft connected by kilometer-long and thin positively charged tethers with remote units at their tips. Three dynamic models of E-sail are developed: the high-fidelity tether dynamic model, the generalized E-sail model, and the reduced-order analytical E-sail model. The coupling effects of orbital and self-spinning motions of the E-sail, the elastic deformation of tethers, the rigid-flexible coupling effect on the attitude dynamics and spin control of E-sail, and the stability control of the flexible E-sail are thoroughly investigated based on these models. Meanwhile, the controllability of E-sail spin rate and the attitude of the E-sail are demonstrated, and the trajectory tracking problems in extraplanetary exploration missions are studied. Finally, the main contributions of this dissertation are introduced.
Open Access
The effects of pollution on CO2 exchange in a Boreal Forest
(2022-08-08) Chen, Yichu; Gordon, Mark D.
Boreal forests are the largest biological community on earth, with an area of about 14.7×10^6 km2. Canada has about 270 Mha of boreal forests. The purpose of this project is to study CO2 exchange at the York Athabasca Jack Pine (YAJP) site near the oil sands facilities by analyzing temperature, H2O, CO2 concentration, and CO2 flux. The results show both temperature and water vapour affected the CO2 concentration and flux. When the wind direction was from the direction of upgrading facilities, a higher concentration of pollutants was measured at YAJP site. The CO2 concentration during pollution episodes was 17.3 (1.6) mmol/m3 and the flux was -5.5 (1.4) μmol/m2/s. These values are compared to 16.8 (0.6) mmol/m3 and -3.4 (0.2) μmol/m2/s when winds were not from this range (numbers in brackets are standard deviations). These results suggest that pollution at Alberta's oil sands facilities affects the CO2 exchange in boreal forests.
Open Access
Simulation of Small Satellite Performance Using Improved Attitude Determination and Control Hardware
(2022-08-08) Keum, Ki Hwan; Lee, Regina
In this research, the attitude determination and control system (ADCS) of a small satellite is examined through a series of simulation analysis using MATLAB and Simulink. The attitude determination component involves a sub-pixel interpolated digital sun sensor that is examined through day-in-the-life analysis while the attitude control component involves a single gimbal control moment gyroscope (SGCMG) pyramid cluster examined using torque profiles of two coastline observation scenarios. Results show that the digital sun sensor improves determination capabilities up to sensor accuracy of 0.027 degrees with diminishing returns thereafter. The SGCMG pyramid cluster meets the requested torque profiles with less than 0.3 degrees of pointing error throughout the sweep. The impact of sensors on attitude determination and viability of the SGCMG cluster over reaction wheels provide a promising alternative for ACS design for small satellites where control accuracy and agility have been limited by existing attitude sensors and actuators.
Open Access
General Circulation Model Regional Predictions Using MOS techniques: Seasonal Forecasting
(2022-08-08) Thapa, Anuj Dhoj; Taylor, Peter
Ocean and atmospheric Coupled Global Climate Models (CGCMs) have been widely used to provide more accurate and coherent seasonal forecasts. However, they still show some limitations. Model Output Statistics (MOS) approaches may improve performance if observed and forecast values are available for a long record. This study investigates the skills of a MOS approach on ECHAM4p5 in simulating rainfall and temperature on a seasonal time scale over the South West (SW) Ontario region. ECHAM4p5 model has 20 ensemble members and those 20 members along with their mean are compared with real time observational data collected locally by Environment and Climate Change Canada (ECCC) weather stations. Presently, the ECHAM4p5 model is run by the Foundation Cearense for Meteorology and Water Management (FUNCEME), Brazil. The model is run at the beginning of every month based on persisted Sea Surface Temperature (SST) from 0000 of 1st day of that month. An ensemble average of 20 realizations is used for the forecasts. The model uses for eight-month weather predictions ahead of the start date. Historical model data were available from International Research Institute for Climate and Society (IRI), Columbia University and used together with Global Precipitation Climatology Centre (GPCC) rainfall data and average daily temperature obtained from the Climatic Research Unit (CRU) at University of East Anglia. Ten years of daily forecasts for SW Ontario from the ECHAM4p5 model are used to develop Regional Correction Factors (RCF) to help in improving the model seasonal forecast confidence level. The basic (bias correction based) MOS technique is applied for seasonal and regional bias corrections. Our focus has been on the first three months of the forecast and comparisons are made against Meteorological Terminal Air Report (METAR) and other data for SW Ontario. The comparison of tuned data and observations has been made over SW Ontario. The motivation of taking this domain is that our industrial partner is mainly working with the farmers in SW Ontario. The approach used had given encouraging results (based on personal communication) in larger geographic areas and improved seasonal predictions in Pakistan. The results so far in the much smaller SW Ontario domain, with a somewhat different climatology, have not been as successful but have provided ideas for future research. We have worked on both monthly and daily precipitation and temperature, but in particular we have focused to investigate day to day differences between different ensemble members to see what information might be gained from them. Our results show that there is huge variation among 20 ensemble members and those variations are canceled out while taking their mean for ensemble mean forecasting technique. Furthermore, while comparing individual ensemble members with observation data, we also get the idea that few ensemble members are following observation data closely. We also compare the same method for larger domain to improve our forecasting results.
Open Access
Aphelion Cloud Formation and Swiss Cheese Sublimation: Martian Atmospheric Water Vapour Processes
(2022-03-03) Innanen, Alex Cummings; Moores, John
This thesis studies the behaviour of atmospheric water vapour at two points in the Martian water cycle: the formation of the Aphelion Cloud Belt (ACB) in Northern spring and summer and the sublimation of the south polar cap in Northern autumn and winter. Firstly, comparing the phase functions of ACB clouds before and after the global dust storm (GDS) of Mars year 34 finds little difference between the two, indicating the dominant ice crystal habit was not impacted by the GDS. The exact nature of this geometry is still not known. Secondly, we mapped the current extent of Swiss cheese features and determined a range of temperatures of exposed water ice within them. From this we estimated a current sublimation rate and found the water vapour contribution from them is negligible. We also determined the area of exposed water ice needed to sublimate 30 precipitable microns of water vapour.
Open Access
Constraining the Hydration State of the Phyllosilicate Deposits of Eastern Valles Marineris Mars
(2021-11-15) Rezza, Craig Anthony; Smith, Isaac B.
A study has found that the bound water of clay deposits on Mars render radar observations ineffective, as the water presence absorbs the radar signal beyond detection (Stillman & Grimm 2011). However, at Aurorae Planum, basal reflections are still observed, despite the presence of widespread clay deposits in the region. We conduct dielectric laboratory experiments on a terrestrial analog clay sample to constrain dielectric properties sufficient enough to allow transmission of SHARAD radar. In addition, we utilize HiRISE and CRISM data to draw correlations between the clays and the radar observations. Our study finds that a catastrophic flooding event is a sufficient and plausible explanation for this contradiction. Leftover pooled water from the flood was left to alter shallow sediment deposits, and upon evaporating, provided the necessary mechanism for desiccation due to water table retreat to occur, minimizing the influence of bound water on the incident radar waves.