475 research outputs found
An Observational and Modeling Study of the Winter-to-Spring Transition in East Asia—Onset of the South China Spring Rain
No full textWinter-to-Spring Transition in East Asia: A Planetary-Scale Perspective of the South China Spring Rain Onset
No full textHuang-Group-UMICH/LW-scattering-polar-climate: Softwares for the LW scattering polar climate study
No full textThis accompanies our LW scattering paper accepted by Geophysical Research Letters
Utilizing Distributed Acoustic Sensing for Applications in Observational Seismology
No full textObservational seismology plays a crucial role in advancing our understanding of the Earth's dynamic processes and internal structure. It relies heavily on the availability and quality of data from a wide range of sources. Distributed Acoustic Sensing (DAS) is an emerging technology with the potential to greatly expand seismic data coverage by converting fiber-optic cables into dense arrays of seismic sensors. Compared to conventional instruments, DAS offers unique advantages in spatial density and convenient deployment, particularly in challenging or previously inaccessible environments. However, DAS also presents several limitations, including lower signal-to-noise ratios for individual channels, indirect measurements of ground motion, and directional sensitivity to axial fiber orientation. Therefore, data processing procedures for routine seismic monitoring need to accommodate these features. This thesis contributes to developing modified processing techniques and evaluating their performance across three key applications: event detection, source imaging, and shallow subsurface characterization. The findings of these case studies aim to provide implications for assessing the potential for integrating DAS into modern seismic networks.
In Chapter 2, we focused on assessing the recording capability of an Ocean-Bottom DAS (OBDAS) array in the Sanriku region, Japan. We introduced two array-based detection methods that utilize the dense spatial sampling of OBDAS to detect coherent earthquake signals over subsections of the array. These techniques detected thousands of cataloged and previously uncataloged earthquakes. By analyzing the detection statistics, we found that the recording capability of the OBDAS array varies substantially across channels, and the array is well capable of recording regional earthquakes within a 100 km radius region. The array also recorded local repeating earthquakes across different subregions. These results highlight the feasibility of using OBDAS for long-term seismic monitoring and its potential to address the scarcity of offshore instrumentation.
In Chapter 3, we investigated the potential of DAS on earthquake rupture imaging. We utilized both synthetic data and realistic recordings to identify the significant challenges of applying the Back-projection method (BP) to DAS data: the unstable solvability caused by highly asymmetric array geometry and limited azimuth coverage. Considering these constraints, we also proposed several data processing procedures to better adapt DAS data for BP analysis. We demonstrated the effectiveness of BP with the 2022 Michoacán earthquake recorded by a DAS array in Mexico City. Our analysis demonstrated that, despite some limitations, DAS-based BP could successfully capture key rupture features. Meanwhile, we analyzed several sources of uncertainty and proposed practical guidelines for improving DAS-based BP performance. We also proposed an initial assessment scheme to understand the feasibility of BP analysis, which is transferable to other similar studies. Our work highlights the potential of DAS to enhance earthquake source imaging on a regional-to-local scale, offering alternative yet valuable insights into regions underserved by conventional seismic networks.
In Chapter 4, we used ambient seismic fields recorded by an OBDAS array to image the shallow subsurface beneath the Florence region. Leveraging the long-duration recordings of DAS, we retrieved coherent surface waves and applied a double-beamforming approach to stably measure multimode dispersions. We performed a perturbational-based inversion method to invert for S-wave velocities over the first 2000-meter sediments underlying the fiber-optic cable. While the high cost and limited availability of conventional underwater instruments hinder progress in imaging shallow structures in marine settings, this work demonstrates the potential of OBDAS arrays for high-resolution passive imaging.PhDEarth and Environmental SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/199443/1/yaolinm_1.pd
Hybrid Method for Full-wave Simulations of Vegetation
No full textIn this dissertation, a hybrid method combing both the analytical and the numerical solutions is developed for full-wave simulations of vegetation. A realistic field setup is introduced to consider the plant structures and gaps within the vegetation canopy. The scattering of the whole vegetation field is then decomposed and solved in the following two steps.
In the first step, the numerical solver is utilized to perform full-wave simulations of one single plant, from which the corresponding T-matrix is extracted based on the near-field using the Huygens principle and vector cylindrical wave (VCW) expansions. The full-wave based T-matrix characterizes the scattering of one single plant and captures the multiple scattering effects caused by the plant structure. In the second step, the T-matrix is combined with Foldy-Lax (FL) multiple scattering equations to consider the interactions among different plants within the vegetation field. The resulting closed-form equations are solved analytically using the VCW expansions and the translational addition theorem.
The convergence and the accuracy of the hybrid method are verified with the High Frequency Structure Simulator (HFSS) by comparing the solutions of scatterings from four wheat plants. After that, the hybrid method is applied to investigate the frequency dependence of the vegetation effects by performing full-wave simulations of wheat fields at L-, S-, and C-band. A physical-iterative approach is implemented together with Message Passing Interface (MPI) parallel computing to facilitate the Monte Carlo simulations. The results obtained from the hybrid method are compared with those of the classical radiative transfer equation (RTE) model to illustrate the importance of full-wave simulations.
In the second part, the full-wave simulation of forest is realized using the hybrid method after two critical issues are successfully resolved. To overcome the challenge in calculating the tree T-matrix, the general relation between the T-matrix and the scattered field coefficient is first revealed and a far-field based T-matrix extraction method applicable for plants of arbitrary size and structure is thus developed. Second, the memory challenge of hybrid method is eliminated by adopting the iterative solutions for solving the FL equations. The proposed methods are validated with FEKO by comparing the field solutions of scattering from three eight meters tall trees. The full-wave Monte Carlo simulations of forest are performed to investigate the tree effects on microwave propagation and the potential of using L-band signal to retrieve soil moisture over the forested area.PhDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/175703/1/whgu_1.pd
Climate Change Analysis from the TOA Spectrally Resolved IR Radiation
Full text linkRadiation plays a central role in the global energy budget. It is closely intertwined with atmospheric dynamics and cloud microphysics that lie at the heart of global climate change studies. On the other hand, radiation is not merely a type of energy flux. It is spectrally dependent, and such spectrally resolved radiation contains detailed information about geophysical variables. Recently more and more high-quality measurements of top-of-atmosphere (TOA) longwave radiation at very high spectral resolution (~1cm-1 or higher; a.k.a. hyperspectral measurements) have become available. Motivated by such measurements, in particular by their perspectives for climate studies, this thesis explores which new insights into the climate change and variability we could draw from the spectral dimension of such measurements and their counterparts based on model simulation and reanalysis data.
First the spectrally resolved radiances in stratospheric channels observed by AIRS (Atmospheric infrared Sounder) over the last decade have been examined. Their secular trends are estimated and compared with counterparts of two sets of synthetic AIRS radiances. One set was generated using atmospheric profiles from the free-running GFDL AM3 forced by the observed sea surface temperature and the other using ECMWF ERA-interim reanalysis. AIRS lower-stratospheric channels exhibit a cooling trend of brightness temperature no more than 0.23 K decade-1 while its middle- and upper-stratospheric channels consistently show a statistically significant cooling trend of brightness temperature as large as 0.58 K decade-1. Neither of the synthetic radiances is capable of capturing these trends.
Optimal fingerprinting technique is further applied to the trends of radiances in AIRS stratospheric channels and in AMSU stratospheric channels to derive global-mean temporal changes of stratospheric temperature and CO2 due to anthropogenic activities (so-called average-then-retrieve approach). The retrievals are not only consistent with trend estimates using other data sets such as layer-mean stratospheric temperature observations by SSU but also improve the vertical resolution of such temperature trend estimates. Furthermore, synergistic use of microwave radiances effectively helps to disentangle covariance of the temperature and CO2 changes.
Traditionally, radiative feedbacks have been considered regarding the perturbation to broadband flux. Because of the compensating biases among spectral bands, it is possible that global climate models (GCMs) produce similar broadband feedback but the spectral decomposition of such broadband feedback can be considerably different, implying various changes of geophysical variables leading to such seemingly agreement in the broadband feedback. Spectral relative humidity (RH) longwave feedbacks of CMIP5 GCMs are calculated and then are analyzed utilizing the spectral RH radiative kernels. The spectral and spatial compensations lead to a consistent and nearly zero RH broadband feedback among models, usually referred to as “constant RH” concerning global warming. Further analysis reveals that spectral details in RH feedbacks can provide more information about the changes of geophysical variables than the broadband RH feedback does.
Similar to the trend-detections studies for the stratospheric temperatures and CO2, the hyperspectral measurements also have the potential for providing constraints on the changes of temperature, humidity, and cloud properties in the troposphere using the average-then-retrieve approach. Meanwhile, more than a decade of hyperspectral data also provides a new opportunity to test climate models more rigorously by comparing the spectrally resolved radiances. Discrepancies in such comparison can be more attributable to the causes than those in broadband comparison, thus bridging the model assessments in the radiation field and in the geophysical field.PhDAtmospheric, Oceanic & Space ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138477/1/fangpan_1.pd
Common-Aperture Dual-Polarized Transceiver Antenna Systems for Millimeter-Wave Polarimetric Radar
No full textThe millimeter-wave radar is one of the key sensor technologies utilized in the automotive industry for advanced driver assistance systems and autonomous vehicles. Its ability to leverage phenomena such as the Doppler effect and the polarization of electromagnetic waves make it an extremely versatile sensor, capable of detecting position and velocity of potential roadway obstacles, as well as distinguishing between obstacles of different types (pedestrians, other vehicles, etc.) based on their polarization responses. Additionally, its relative insensitivity to precipitation and fog allows for all-weather operation, even in conditions that severely inhibit visibility. However, radar is not a perfect all-encompassing sensing solution; in particular, its most significant drawback is imaging resolution inferior to that of optical sensors like cameras and lidar.
A radar’s resolution is closely linked to its antenna system. Angular resolution is improved with a narrow antenna beam, which translates to a large effective aperture. Similarly, fine range resolution is achieved using the frequency-modulated continuous-wave technique, which requires high transmit-to-receive antenna isolation. Typically, this isolation is accomplished with spatial separation between elements. Limited available mounting space on most vehicles prohibits the large antenna system size mandated by these requirements.
The focus of this dissertation is the development of an antenna system architecture which provides a very narrow beam and high isolation, while supporting dual-polarized transmit and receive capability for polarimetry applications. The use of a common transmit/receive aperture makes the antenna system relatively compact while eliminating parallax. The shared aperture is a single dielectric lens, which focuses at both the transmit and receive feeds by means of a novel polarization-independent spatial power divider. This device was designed using concepts from the flourishing field of electromagnetic metamaterials and metasurfaces, and can be constructed using standard semiconductor fabrication techniques.
While modern automotive radars operate at the 79 GHz band, there is a strong interest in exploring higher millimeter-wave frequencies (particularly the 230 GHz band) for future systems. The shift to a shorter wavelength will result in improved angular and range resolution while reducing antenna size. Therefore, separate versions of the common-aperture dual-polarized transceiver antenna system have been designed for operation at the two bands. One of the challenges of moving to higher frequency is the availability and performance of millimeter-wave electronics and waveguide components. In support of high frequency dual-polarized radar antennas, an orthomode transducer with a simple structure has been designed for reduced fabrication complexity at the 230 GHz band.
Additionally, there is currently a lack of data on the backscattering properties of many target classes at 230 GHz. The antenna and orthomode transducer designs of this work have been incorporated as part of the front ends of radar systems operating at this band. As a demonstration of the utility of 230 GHz radar, as well as the antenna system itself, a set of polarimetric backscattering measurements of several road surfaces is presented. Such data can be used to inform algorithms for discrimination between different surfaces, and assessment of road conditions.
Another topic in this dissertation is the design of a low-profile passive reflector, which can enable radar sensors to detect and identify road markings, a task currently handled only by cameras. As an appendix, a planar antenna system with high isolation for wireless communication and radar applications at 6 GHz is presented.PhDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/174394/1/tjdoug_1.pd
Linear and Nonlinear Kelvin Waves/Tropical Instability Waves in the Shallow-Water System.
Full text linkThe Kelvin wave is the slowest eastward propagating eigenmode of Laplace's Tidal Equation. It is widely observed in both the ocean and the atmosphere. On the sphere, in the absence of mean currents, the Kelvin wave depends on two parameters: the zonal wavenumber s and Lamb's parameter epsilon. First, we derive an asymptotic approximation for the linear Kelvin wave valid in the limit sqrt{s^{2}+epsilon}>>1, which generalizes the usual ''equatorial wave'' limit that epsilon goes to infinity for fixed s. Then for the weakly nonlinear Kelvin wave we derive the analytic solution of the traveling Kelvin wave for small epsilon and amplitude with a perturbation method. For the strongly nonlinear Kelvin wave, through numerical computations, we show that for sufficiently small amplitude, there are Kelvin traveling waves (cnoidal waves); as the amplitude increases, the branch of traveling waves terminates in a so-called ''corner wave'' with a discontinuous first derivative. All waves larger than the corner wave evolve to fronts and break.
On the equatorial beta-plane, Kelvin waves are nondispersive without a background mean. To obtain the traveling wave solution, we include a jet symmetric about the equator. We show that the linear Kelvin waves have much more complicated structures and phase speeds than the Kelvin wave with a resting background. In longitude, the nonlinear traveling waves also terminate in a ''corner wave''. In latitude, as the wave amplitude increases, the waves narrow for a westward jet but widen for an eastward jet. Phase speeds are largely determined by the linear Kelvin waves' dynamics; nonlinearity only increases the phase speeds by a few percent.
Tropical Instability Waves (TIWs) are prominent westward intraseasonal oscillations observed in both equatorial Pacific and Atlantic oceans. How the nonlinearity of the TIWs affects the development of the instabilities is studied through solving the linear stability problem and high resolution time dependent numerical simulation. We show that neutral Yanai waves with periods about 15-22 days emerge near the equator when the unstable TIWs centered near 5 degree north grow into fully nonlinear vortices which explains the coexistence of two different types of TIWs observed during the TIW season.PhDAtmospheric and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75867/1/zhouc_1.pd
Exploring the Variability of Seismic b-Values Using a Relative Amplitude Method for Earthquake Magnitude Reassessment
No full textProbabilistic seismic hazard assessment (PSHA) is a widely used statistical approach to estimate where and when earthquakes are likely to occur based on the statistics of past seismicity patterns. A critical component of PSHA is the estimation of magnitude recurrence intervals based on the Gutenberg-Richter Law which characterizes the frequency of earthquakes magnitudes and defines the b-value which expresses the relative proportion of small to large events in the magnitude-frequency distribution (MFD). However, the MFD and the b-value are heavily influenced by the accuracy of earthquake magnitude estimates. This research addresses the critical need for high-quality magnitude measurements for small earthquakes by using relative amplitude methods. These improved magnitude estimates are used to examine spatiotemporal variations in b-value for multiple earthquake sequences to improve our understanding of short-term seismic hazard forecasting. Chapters 1 and 2 introduce a generalized methodology to determine relative magnitudes for earthquake sequences which is only dependent on relative amplitude differences between interlinked pairs of waveforms, as well as methods for determining the b-value from the distribution of magnitude differences between successive events. Chapter 3, examines the uncertainty of magnitude results produced from the relative magnitude method through a parameter study on critical variables including thresholds for signal-to-noise ratio and cross-correlation, frequency content filtering, and seismic station selection. We show that signal-to-noise and cross-correlation thresholds limit the number of magnitudes that can be recalculated while bandpass filtering has the largest effect on the variability of magnitude results. Chapter 4, presents a set of coda-envelope moment magnitudes (MW) as a benchmark data set for the relative magnitude method, allowing us to align our relative magnitude measurements to an absolute moment magnitude scale for small earthquakes. We produce moment magnitudes for approximately 80% of the events in the Delaware Basin and demonstrate the capabilities of this method to provide moment magnitude for small earthquakes in regional earthquake catalogs. In Chapter 5, we use an uncalibrated relative magnitude method to reevaluate magnitude estimates for the 2011 Prague, Oklahoma earthquake sequence and calculate the temporal and spatial variations of b-value. We show that b-values during the aftershock sequence are consistently low which demonstrate that the aftershock distribution is skewed towards producing earthquakes of higher magnitude for at least 5 months following the mainshock. Additionally, we show a trend of decreasing b-value along the Meeker-Prague fault as distance from the mainshock increases suggesting that tectonic stress may still exist in areas of low b-value. Finally, in Chapter 6, we apply the relative magnitude method to 6 foreshock sequences in southern California and focus on an in-depth exploration of the spatial and temporal variations in b-value and their sensitivity to parameters such as spatial binning and window length. We show that approximately half of the sequences exhibit a drop in b-value in the months or days prior to a mainshock. We also show that mainshocks frequently occur in areas of low foreshock b-value for single-fault or dense seismicity. This research demonstrates the importance of reliable and transportable magnitude estimation for small earthquakes. With these improved magnitude estimates, we also gain valuable insights into the behavior of seismic sequences through analysis of the spatiotemporal variability of the MFD and b-value.PhDEarth and Environmental SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/199110/1/gablesyd_1.pd
The Application of Infrared Spectral Radiances and Fluxes for Arctic Climate Monitoring and Cloud Phase Determination from Space
No full textThe Arctic climate is strongly influenced by infrared (IR) radiation emitted and absorbed by greenhouse gases, clouds, and the surface. As the Arctic continues to rapidly change, it is crucial to further understand how changes in such geophysical variables influence changes in IR flux at the Arctic surface and the top-of-atmosphere. Cloud phase (i.e., ice, liquid, and mixed) can affect the clouds’ overall contributions to the IR fluxes. However, the spatial and temporal occurrences of Arctic cloud phase are not well characterized.
Satellite observations of spectrally resolved IR fluxes can be used to connect changes in the atmosphere and surface to broadband IR flux changes, however, such studies have not been performed in the Arctic. Spectral IR radiances can be used for satellite-based cloud phase retrievals, but conventional methods using the mid-IR window region (~800-1250 cm-1) have limitations in polar regions, especially for mixed phase clouds. It may be possible to improve Arctic mid-IR cloud phase retrievals with far-IR (<~600 cm-1) measurements. However, few studies have investigated far-IR cloud phase retrievals from space.
Overall, this dissertation studies the potential and limitations of spectral mid-IR and far-IR radiances and fluxes for monitoring Arctic IR radiation and identifying cloud phase from space. It contains four studies. The first study examines the trends of zonal mean spectral outgoing longwave radiation (OLR) and greenhouse efficiencies (GHE) in the Arctic from 2003 to 2016 using spectral flux derived from collocated Atmospheric IR Sounder (AIRS) and the Clouds and the Earth's Radiant Energy System observations in conjunction with AIRS retrievals. Positive and negative trends in Arctic OLR and GHE are observed across the far-IR and mid-IR spectral regions, depending on the season, and the largest positive OLR and GHE trends occur in spring. Sensitivity studies reveal that surface temperature increases contribute most to the OLR and GHE trends, but the effects of atmospheric humidity and temperature are discernable.
In the second study, AIRS cloud phase retrievals, which were never evaluated over the Arctic, are evaluated against four years of combined CloudSat and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation measurements over the Arctic Ocean. AIRS classification skill for single-layer ice- and liquid-phase clouds ranges from 85%–95% and 22%–32%, respectively. Most unknown and liquid AIRS phase classifications correspond to mixed-phase clouds.
The third study explores the synergy between the far- and mid-IR for polar ice cloud detection. A far-IR brightness temperature difference (BTD) test is developed and applied to simulated IR radiances and the results are compared to those from a mid-IR BTD test. Scattering leads to the far-IR being most sensitive to small ice particles, and the increase of cloud optical depth contributing to stronger far-IR BTD signals. Synergy between the mid-IR and far-IR is most useful for identifying cloud ice particles with an effective diameter around 40 µm.
The final study examines the sensitivity of simulated 11 µm brightness temperature (BT11) to cloud ice changes within Arctic liquid-topped mixed phase clouds (LTMs). It was determined that BT11 can be sensitive to cloud ice for a range of commonly observed Arctic LTMs. By utilizing channels in the mid- and far-IR, it may be possible to use BTD tests together with a machine learning approach to detect Arctic LTMs from space.PhDAtmospheric, Oceanic & Space ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/174592/1/coltenp_1.pd
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