<p> Water vapor, clouds and aerosols are three major components in the atmosphere that largely influence the Earth's climate and weather systems. However, there is still a lack of understanding on the distribution and interaction of these components. Large uncertainties still remain in estimating the magnitude and direction of the aerosol indirect effect on cloud radiative forcing, which potentially can either double or cancel out all anthropogenic greenhouse gas effect. In particular, a small variation in water vapor mixing ratio and cloud distribution in the upper troposphere and lower stratosphere (UT/LS) can generate large impacts on the Earth's surface temperature. Yet the understanding of water vapor and clouds in the UT/LS is still limited due to difficulties in observations. To improve our understanding of these components, observations are needed from the microscale (~100 m) to the global scale. The first part of my PhD work is to provide quality-controlled, high resolution (~200 m), in situ water vapor observations using an open-path, aircraft-based laser hygrometer. The laboratory calibrations of the laser hygrometer were conducted using complementary experimental systems. The second part is to compare the NASA AIRS/AMSU-A water vapor and temperature retrievals with aircraft-based observations from the surface to the UT/LS at 87&deg;N-67&deg;S in order to understand the accuracy and uncertainties in remote sensing measurements. The third part of my research analyzes the spatial characteristics and formation condition of ice supersaturation (ISS), the birthplace of cirrus clouds, and shows that water vapor horizontal heterogeneities play a key role in determining the spatial distribution of ISS. The fourth part is to understand the formation and evolution of ice crystal regions (ICRs) in a quasi-Lagrangian view. Finally, to help estimate the hemispheric differences in ice nucleation, the ISS distribution and ICR evolution are compared between the two hemispheres. Overall, these analyses provided a microphysical scale yet global perspective of the formation of ISS and cirrus clouds. Ultimately, these efforts will help to improve the understanding of human activities' influences on clouds, water vapor and relative humidity in the UT/LS and provide more accurate representations of these components in future climate prediction.</p>

<p> I present the development of instrumentation and methods for the measurement of coastal processes, ocean surface phenomena, and air-sea interaction in two parts. In the first, I discuss the development of a portable scanning lidar (light detection and ranging) system for manned aircraft and demonstrate its functionality for oceanographic and coastal measurements. Measurements of the Southern California coastline and nearshore surface wave fields from seventeen research flights between August 2007 and December 2008 are analyzed and discussed. The October 2007 landslide on Mt. Soledad in La Jolla, California was documented by two of the flights. The topography, lagoon, reef, and surrounding wave field of Lady Elliot Island in Australia's Great Barrier Reef were measured with the airborne scanning lidar system on eight research flights in April 2008. Applications of the system, including coastal topographic surveys, wave measurements, ship wake studies, and coral reef research, are presented and discussed. </p><p> In the second part, I detail the development of instrumentation packages for small (18 &ndash; 28 kg) unmanned aerial vehicles (UAVs) to measure momentum fluxes and latent, sensible, and radiative heat fluxes in the atmospheric boundary layer (ABL), and the surface topography. Fast-response turbulence, hygrometer, and temperature probes permit turbulent momentum and heat flux measurements, and short- and long-wave radiometers allow the determination of net radiation, surface temperature, and albedo. Careful design and testing of an accurate turbulence probe, as demonstrated in this thesis, are essential for the ability to measure momentum and scalar fluxes. The low altitude required for accurate flux measurements (typically assumed to be 30 m) is below the typical safety limit of manned research aircraft; however, it is now within the capability of small UAV platforms. Flight tests of two instrumented BAE Manta UAVs over land were conducted in January 2011 at McMillan Airfield (Camp Roberts, CA), and flight tests of similarly instrumented Boeing-Insitu ScanEagle UAVs were conducted in April 2012 at the Naval Surface Warfare Center, Dahlgren Division (Dahlgren, VA), where the first known direct flux measurements were made from low-altitude (down to 30 m) UAV flights over water (Potomac River). During the October 2012 Equatorial Mixing Experiment in the central Pacific aboard the R/V <i>Roger Revelle</i>, ship-launched and recovered ScanEagles were deployed in an effort to characterize the marine atmospheric boundary layer structure and dynamics. I present a description of the instrumentation, summarize results from flight tests, present preliminary analysis from UAV flights off of the <i>Revelle</i>, and discuss potential applications of these UAVs for marine atmospheric boundary layer studies.</p>

<p> The formation of mineralized tissue was critical to the evolution and diversification of metazoans and remains functionally significant in most animal lineages. Of special importance is the protein found occluded within the mineral matrix, which facilitates the process of biomineralization and modulates the final mineral structure. These skeletal matrix proteins have well been described in several species, including the sea urchin <i> Stronglyocentrotus purpuratus,</i> an important model organism. Biomineralization research is limited in other echinoderm classes. This research encompasses the first description of mineral matrix proteins in a member of the echinoderm class Ophiuroidea. This work describes the skeletal matrix proteins of the brittle star <i>Ophiocoma wendtii</i> using bioinformatic and proteomic techniques. General characteristics of matrix protein are described and a number of candidate biomineralization related genes have been identified, cloned, and sequenced. The unique evolutionary and biochemical properties of brittle star skeletal matrix proteins are also described.</p>

<p>A large multi-aperture telescope has the potential to reach the diffraction limit corresponding to its baseline. To do so, Adaptive Optics (AO) and beam combination are critical to good performance. Operation as an interferometer is a complicated mode for the telescope. The system now has much tighter tolerances and is difficult to align. The alignment process needs to be planned in multiple steps, and tolerance and sensitivity analysis needs to be performed for each step. Alignment tools can be prepared based on the resolution found in the sensitivity analysis in each step. </p><p> Random fluctuation is another critical factor that reduces system performance. If noise sources near the telescope are characterized and identified, image quality can be improved by post-image processing. </p><p> Measuring the outer scale of atmosphere is also helpful for understanding the system performance. The fringe tracking method in the Large Binocular Telescope Interferometer (LBTI) system provides optical path difference (OPD) variation, and the power spectral density of the OPD variation is used to estimate the size of the outer scale. However, this method is limited by the baseline of the LBTI by 5[special characters omitted] B, where B is the baseline, and by this equation the outer scale size which is able to be estimated should be more than 125 m. </p><p> AO simulation can provide an understanding of new AO system concepts and parameter variations before they are applied to the real system. In this dissertation study, we simulated an LBTI system with structural vibration of 10 Hz and 20 Hz and with various amplitudes. From the simulation, we learned that the slower bandwidth of piston-correcting systems allows stars as faint as ~13^the magnitude to be observed. If there is significant vibration on the structure, the increased bandwidth will limit the phasing stars to 10~11^th magnitudes. This demonstrates the limits of the LBTI system regarding structural vibration. </p><p> An alternative phasing sensor for the LBTI system, the pseudo phasing sensor, can be used for more than 1000 m of outer scale of atmosphere. If the direct phasing sensor embedded in the LBTI system cannot be used for a very faint star, the pseudo phasing sensor, which approximately estimates the phase difference by AO wavefront sensor, can be useful for atmospheric conditions with estimated outer scale of about 1000 m. </p><p> The analyses in this dissertation provide a partial guide for developing large-scale telescopes and astronomical instruments.</p>

<p>Earth and Mars have nearly the same axial tilt, so seasons on these two bodies progress in a similar manner. During fall and winter on Mars, the primarily CO₂ atmosphere (~95% by volume) condenses out onto the poles as ice. Approximately 25% of the entire Martian atmosphere condenses, and then sublimes in the spring, making this cycle a dominant driver in the global climate. Because the water and dust cycles are coupled to this CO₂ cycle, we must examine seasonal CO₂ processes to understand the global (seasonal) distribution of H₂O on Mars. The density of the ice may indicate whether it condensed in the atmosphere and precipitated as &ldquo;snow&rdquo; or condensed directly onto the surface as &ldquo;slab&rdquo;. Variations in density may be controlled by geographic location and surface morphology. The distribution and variations in densities of seasonal deposits on the Martian poles gives us insight to the planet&rsquo;s volatile inventories. Here we analyze density variations over time on Mars&rsquo; Northern Polar Seasonal Cap (NPSC) using observational data and energy balance techniques. </p><p> We calculate the bulk density of surface CO₂ ice by dividing the column mass abundance (the mass of CO₂ per unit area) by the depth of the ice cap at a given location. We use seasonal rock shadow measurements from High Resolution Imaging Science Experiment (HiRISE) images to estimate ice depth. The length of a rock&rsquo;s shadow is related to its height through the solar incidence angle and the slope of the ground. </p><p> From differences in the height of a rock measured in icy vs. ice-free images, we estimate the depth of surface ice at the time of the icy observation. Averaging over many rocks in a region yields the ice depth for that region. This technique yields minimums for ice depth and therefore maximums for density. </p><p> Thermal properties of rocks may play an important role in observed ice depths. Crowns of ice may form on the tops of rocks with insufficient heat capacity to inhibit ice condensation, and may cause an artificial increase in shadow length. This increases the apparent height of a rock and thus decreases the apparent surface ice depth. Additionally, moats may form around rocks with sufficient heat capacity to sublime ice as it is deposited. Moating will also artificially increase the shadow lengths (decreasing apparent surface ice depth). We correct for these effects in our depth-estimation technique. </p><p> We balance incoming solar flux with outgoing thermal radiation from Thermal Emission Spectrometer (TES) observations to calculate the column mass abundance. TES thermal bolometer atmospheric albedo and temperature observations are a good proxy to the surface bond albedo and effective surface temperature. These parameters are needed to balance the incoming and outgoing flux. </p><p> Mars&rsquo; atmosphere is tenuous so we assume homogeneous radiance from the surface to the top of the atmosphere, no lateral diffusion of heat, and that any excess heat goes into subliming surface ice in our flux balance. Using a Monte Carlo model, we integrate the net flux until reaching the time where Cap Recession Observations indicate CO₂ has Ultimately Sublimed (the CROCUS date) to obtain the column mass abundance. </p><p> We study seasonal ice at three distinct geomorphic units: plains, dune fields, and craters. Two plains regions, four dunes regions, and two crater regions are analyzed over springtime sublimation. Data for these regions spanned three Mars Years. </p><p> Our results indicate that the evolution of seasonally deposited CO₂ ice on the Northern Polar Cap of Mars is highly dependent on complex relationships between various processes. The grain size, dust contamination, water doping, and density vary dramatically over time. The initially deposited material varies according to local geomorphic features and topography, as well as latitude and longitude. The inter-annual variability of ice may play a role in its evolution over sublimation, but likely plays a smaller role than anticipated. Low normalized initial and time-averaged densities suggest that NPSC deposits are initially low and remain relatively low throughout spring. These densities are very similar to estimates made by previous studies. Thus, we conclude that the NPSC is indeed pervaded by low density deposits. These deposits densify over time, but rarely reach typical characteristics for pure slab ice. </p>

<p> A PM_2.5 monitoring network was established around Lake Tahoe during fall 2011, which, in conjunction with measurements at prescribed burns and smoke dispersion modeling based on the Fire Emission Production Simulator and the Hybrid Single Particle Lagrangian Integrated Trajectory (FEPS-HYSPLIT) Model, served to evaluate the prescribed burning impacts on air quality. Emissions from pile and understory prescribed burns were characterized using a mobile air monitoring system. In field PM_2.5 emission factors showed ranges consistent with laboratory combustion of wet and dry fuels. Measurements in the smoke plume showed progression from flaming to smoldering phase consistent with FEPS and PM_2.5 emission factors generally increased with decreasing combustion efficiency. Model predicted smoke contributions are consistent with elevated ambient PM_2.5 concentrations in three case studies, and high meteorological model resolution (2km &times; 2 km) seems to produce accurate smoke arriving times. In other cases, the model performance is difficult to evaluate due to low predicted smoke contributions relative to the typical ambient PM_2.5 level. Synergistic assessment of modeling and measurement can be used to determine basin air quality impact. The findings from this study will help land management agencies better understand the implications of managing fire at the wildland-urban interface.</p>

<p> Using the Hampton University (HU) Mie and Raman lidar, tropospheric temperature profiles were inferred from lidar measurements of anti-Stokes rotational Raman (RR) backscattered laser light from atmospheric nitrogen and oxygen molecules. The molecules were excited by 354.7 nanometer (nm) laser light emitted by the HU lidar. Averaged over 60-minute intervals, RR backscattered signals were detected in narrow 353.35 nm and 354.20 nm spectral bands with full-widths-at-half-maxima (FWHM) of 0.3 nm. During the special April 19-30, 2012, Ground-Based Remote Atmospheric Sounding Program (GRASP) campaign, the lidar temperature calibration coefficients were empirically derived using linear least squares and second order polynomial analyses of the lidar backscattered RR signals and of reference temperature profiles, obtained from radiosondes. The GRASP radiosondes were launched within 400 meters of the HU lidar site. Lidar derived temperature profiles were obtained at altitudes from the surface to over 18 kilometers (km) at night, and up to 5 km during the day. Using coefficients generated from least squares analyses, nighttime profiles were found to agree with profiles from reference radiosonde measurements within 3 K, at altitudes between 4 km and 9 km. Coefficients generated from the second order analyses yielded profiles which agreed with the reference profiles within 1 K uncertainty level in the 4 km to 10 km altitude region. Using profiles from GRASP radiosondes, the spatial and temporal homogeneities of the atmosphere, over HU, were estimated at the 1.5 K level within a 10 km radius of HU, and for observational periods approaching 3 hours. Theoretical calibration coefficients were derived from the optical and physical properties of the HU RR lidar and from the spectroscopic properties of atmospheric molecular nitrogen and oxygen. The theoretical coefficients along with lidar measurements of sky background radiances were used to evaluate the temporal stability of the empirically derived temperature profiles from the RR lidar measurements. The evaluations revealed systematic drifts in the coefficients. Frequent reference radiosonde temperature profiles should be used to correct for the drifts in the coefficients. </p><p> For the first time, the cause of the coefficient drifts has been identified as the differences in the aging of the spectral responses of the HU lidar detector pairs. For the first time, the use of lidar sky background measurements was demonstrated as a useful technique to correct for the coefficient drift. This research should advance the derivations of lidar temperature calibration coefficients which can be used for long observational periods of temperature fields without the need for frequent lidar calibrations using radiosondes. </p>

The Houston Lightning Mapping Array (LMA) is a lightning detection network providing total lightning mapping for the Houston metropolitan area and southeast Texas. The network is comprised of twelve Very High Frequency (VHF) time-of-arrival total lightning mapping sensors built by New Mexico Institute of Mining and Technology and purchased by Texas A&M University. The sensors, installed in April 2012, are of the latest, modular design and built to be independent stations that utilize a solar panel for electricity and cellular data modems for communication. Each sensor detects the time of arrival of a VHF impulse emitted as part of the electrical breakdown and lightning propagation process. Data from each sensor are processed on a central LMA server to provide three-dimensional mapping of these impulses, also called LMA sources. This processing facilitates the analysis of variations in thunderstorm structure and the associated changes in both space and time. The primary objectives for the installation of the Houston LMA network are twofold: first, to provide a dataset enabling research into thunderstorm electrification in the context of a coastal, urban, polluted environment; and second, to enable improvements in operational forecasting and public safety by providing total lightning data to partners including the National Weather Service (NWS). A workflow was established to create and share real-time data to these partners, while simultaneously maintaining a full, research-quality dataset. Data are retrieved from the field sensors and backed up to a central LMA server for processing and storage. Archived network data are available from July 2012 through the present. The network measures 150 km from north to south, with stations in College Station and Galveston complementing the ten sites surrounding downtown Houston. This extends the region constrained by the network beyond the immediate metropolitan Houston area, resulting in increased accuracy in locating sources further from the network center. Based on initial analyses, the effective range of the Houston LMA is 75 km for three-dimensional mapping and approximately 250 km for two-dimension mapping.

<p> This study primarily focuses on sea ice variability in the Bering Sea, and its thermodynamic and dynamic controls. </p><p> First, the seasonal cycle of sea ice variability in the Bering Sea is studied using a global fine-resolution (1/10-degree) fully-coupled ocean and sea ice model forced with reanalysis atmospheric forcing for 1980-1989. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The modeled seasonal mean sea ice concentration strongly resembles satellite-derived observations. During winter, which dominates the annual mean, model sea ice is mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast, due to cold air from northerly winds and ice motion away from the coast. South of St. Lawrence Island, winds drive sea ice to drift southwestward from the north to the southwestern ice covered region. Along the ice edge in the western Bering, ice is melted by warm ocean water, which is carried by the Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric pattern seen in the ice edge. </p><p> Second, the year-to-year variability of sea ice in the Bering Sea for 1980-1989 is addressed. While thermodynamic processes dominate the variations in ice volume change in the Bering Sea on the large scale, dynamic processes are important locally near ice margins (both oceanic and land), where local dynamic and thermodynamic ice volume changes have opposite signs with large and similar amplitudes. The thermodynamic ice volume change is dominated by ice-air surface heat flux, which in turn is dominated by sensible heat flux, except near the southern ice edge where it is largely controlled by ocean-ice heat flux. This indicates that surface air temperature, which is specified from observations, strongly controls the ice volume tendency. Ice motion is generally consistent with winds driving the flow, except near certain straits in the north where ice motion largely follows ocean currents. </p><p> This study also addresses Greenland supraglacial lakes on top of ice and ice-dammed lakes adjacent to glaciers. Those surface lakes have been observed to fill and drain periodically, affecting the ice motion over land. This study provides observational constraints on the volume of water contained in and drained from the lakes, based on the repeat laser altimetry. </p>

<p>Well known dynamic models for air and stormwater quality typically involve the application of deterministic differential equations (DDEs) or random differential equations (RDEs) that apply Monte Carlo simulation. An alternative to RDEs are stochastic differential equations (SDEs), which are DDEs that incorporate random noise. In this thesis, we develop air and stormwater quality models that employ DDEs, RDEs and SDEs numerically solved by finite difference methods. The numerical results of the model variants are compared to each other and empirical data. The outcome demonstrates the utility of the SDE approach. The stormwater model is based on a one-dimensional advection-diffusion partial differential equation (PDE) that simulates the stream transport of copper in a small area within Los Angeles. Two air models are implemented, an ordinary differential equation model based on the continuity equation and a two-dimensional advection-diffusion PDE. The models approximate carbon monoxide levels in Costa Mesa and the Coachella Valley in California. The numerical PDEs are solved with the Strang splitting method, where the Lax-Wendroff and Crank-Nicolson methods are employed for the advection and diffusion subproblems respectively. For the SDE case the Euler-Maruyama method is applied to the source term subproblem. </p>