This dissertation examines the variations in the results of a physically-based kinematic routing rainfall-runoff model (KINEROS2) in response to variations in the geometric model definitions caused by grid size and accuracy of Digital Elevation Model (DEM) data sets. A range of independently acquired DEM data resolutions within the 148 km2 USDA-ARS Walnut Gulch Experimental Watershed provided a sound basis for this analysis. Analysis was conducted over a range of watershed scales and DEM effects were studied in relation to other model parameters. Emphasis was placed on identification of dominant processes most influenced by topographic representation. It was evident from the analysis that the topographic algorithms have their limitations and an insufficient resolution of DEM data results in gross misrepresentation of actual drainage network leading to serious modeling errors. It was also observed that geometric representation of the watershed is inherently linked to the other soils and hydrologic parameter definition. As a result, a variation in geometric representation results in variation of other model parameters. This analysis has illustrated that infiltration dynamics have a dominant control on the model results. Further, a change in geometric configuration due to variation of DEM grid size influences the hydrologic model more through their indirect impact on other parameter definitions than the direct effects due to pure geometric changes. A major problem with using fine resolution DEM is the increased storage requirements and enhanced computational burden. On the basis of this research some guidelines are framed for the user to facilitate a choice of DEM data depending on the modeling requirements and the computational resources. There is clear evidence from this research that an extremely fine and accurate DEM does not necessarily add further accuracy to the modeling results. Therefore a moderate resolution and fair accuracy DEM may be chosen safely for a given modeling task given that a few simple checks on the data are performed by the user.

The Atmospheric Remote Sensing Lab at the University of Arizona's Electrical and Computer Engineering Department has been involved with the study and measurement of atmospheric gases and aerosols for many years. The research has been conducted using instruments designed and constructed by the lab. This dissertation presents a system design for the next step in the evolution of spectroradiometers designed by the Atmospheric Remote Sensing Lab. The design draws upon the lessons learned from previous generations of radiometers and from the requirements of ongoing research. The proposed spectroradiometer uses an inexpensive CCD as the detector and takes advantage of modern processors and re-programmable CPLDs. The new design employs an embedded DSP in a novel way; it provides high level control over the CCD detector, receives serial ADC data and communicates with a Host computer. Through the use of one of the serial channels, the DSP identifies when to accumulate charge in the CCD and when to dump it. This controlled sampling allows charge to accumulate from adjacent cells internal to the CCD, improving the SNR in regions of poor spectral transmission. Since the charge accumulate/reset is controlled by the DSP through software, the sequence is programmable using the host computer interface and can be dynamically re-programmed to accommodate changing atmospheric conditions. A re-programmable CPLD isolates the DSP from the detector hardware and provides low level control of the detector assembly. The CPLD accepts high level commands from the DSP and generates the low level clocks and control signals used by the CCD and ADC. This capability permits the CPLD to be re-programmed to accommodate various CCDs and ADCs available today and in the future without altering the Host communication, control or analysis software. The capabilities of the instrument can be altered by downloading new software to the embedded DSP. Provisions have been made to download software or configuration data to the instrument and execute from RAM. Once correct operation of the software has been verified, it can copied to non-voltile memory.

<p> Previous studies investigating the velocity and elevation change records of the Greenland Ice Sheet (GrIS) revealed rapid and complex changes. It is therefore imperative to determine changes with both high spatial and temporal resolutions. By fusing multiple laser altimetry data sets, the Surface Elevation Reconstruction and Change (SERAC) program is capable of reconstructing surface elevation changes with high spatial and temporal resolution over the entire GrIS. The input data include observations from NASA&rsquo;s Ice, Cloud and land Elevation Satellite (ICESat) mission (2003-2009) as well as data collected by NASA&rsquo;s Airborne Topographic Mapper (ATM) (1993-2013) and Land, Vegetation and Ice Sensor (LVIS) (2007-2012) airborne laser altimetry systems. This study extends the record of surface elevation changes over the GrIS by adding 2012 and 2013 laser altimetry data to the previous 1993-2011 record. Extending the record leads to a new, more accurate and detailed altimetry record for 1993-2013. </p><p> Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Models (DEMs) are fused with laser altimetry data over Zachari&aelig; Isstr&oslash;m, northeast Greenland to analyze surface elevation changes and associated thinning rates during 1978-2014. Little to no elevation change occurred over Zachari&aelig; Isstr&oslash;m from 1978-1999, however, from 1999-2014 elevation changes near the calving front became increasingly negative and accelerated. Calving front position showed steady retreat and grounding line position has been retreating towards the interior of the ice sheet at an increasing rate from 2010-2014 when compared to the 1996-2010 period. The measured elevation changes near the calving front have brought a large portion of the glacier close to the height of flotation. If the current thinning trend continues this portion of the glacier will reach flotation within the next 2-5 years allowing for further retreat and increased vulnerability to retreat for sections of the glacier further upstream.</p>

No description available.

No description available.

Substantial impacts of aerosols on climate and public health underscore the need for accurate characterization of atmospheric aerosol distributions and microphysical properties. The Multiangle SpectroPolarimetric Imager (MSPI) combines accurate multispectral, multiangle, and polarimetric technologies in a single instrument that images a wide swath on the Earth's surface to advance aerosol remote sensing capabilities. MSPI is required to have 3% radiometric uncertainty and 0.005 degree of linear polarization (DoLP) uncertainty. These are difficult requirements that push the limits of available technologies needed to perform space-based polarimetric imaging. This work examines three topics related to MSPI fabrication and calibration: polarization errors and their correction, achromatic, athermal, quarter wave retarder fabrication, and analysis of a polarization state generator (PSG) for MSPI polarization calibration confirmation.MSPI polarization errors may arise from surface geometry of the optical components, coatings, and quarter wave plates (QWPs). Static polarization errors can be calibrated out, but result in decreased SNR. Polarization errors that drift following calibration cannot be corrected, so a sensitivity analysis is used to set time-varying diattenuation and retardance magnitude tolerances. QWPs are required to work in concert with the PEMs to modulate the linear component of the Stokes vector. A three-material achromatic, athermalized QWP was designed, fabricated and its performance validated. Analysis indicated that the compound QWP was unlikely to meet the requirements if plates were specified by thickness. To address this, a method for QWP fabrication was developed that involves monitoring retardance during polishing. To verify MSPI performance, a PSG was built and calibrated which outputs weakly linearly polarized light with DoLPs varying from 0.0005 to 0.4 with 0.0005 uncertainty by passing nearly unpolarized light through a tilted plane parallel plate. The PSG was intended to act as a calibration standard based on calculated DoLP, but proved difficult to model. Therefore, the DoLP was instead measured to repeatability of 0.0005. Finally, example spectropolarimetric image data taken with MSPI was presented. Work on a follow-on prototype continues that will advance the technologies needed to realize the space-based, fully capable MSPI.

Cirrus clouds are known to play a key role in the earth's radiation budget, yet are one of the most uncertain components of the earth-atmosphere system. With the development of instruments such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Moderate-resolution Infrared Spectroradiometer (MODIS), scientists now have an unprecedented ability to study cirrus clouds. To aid in the understanding of such clouds, a significant study of cirrus radiative properties has been undertaken. This research is composed of three parts: 1) the retrieval of tropical cirrus optical thickness using MODIS level-1b calibrated radiance data, 2) a survey of tropical cirrus cloud cover, including seasonal variations, using MODIS level-3 global daily gridded data, and 3) the simultaneous retrieval of cirrus optical thickness and ice crystal effective diameter using AVIRIS reflectance measurements.

The plane parallel homogeneous (PPH) bias is defined as the difference between the plane parallel cloud albedo, calculated for homogeneous cloud optical depth distributions, and the independent pixel (IP) albedo, which allows for optical depth variability, but assumes that individual cloudy columns transfer solar radiation as plane parallel slabs (horizontal photon transport is neglected). Estimates of the PPH bias from extensive Advanced Very High Resolution Radiometer (AVHRR) observations are provided for areas similar in size to weather and climate model gridboxes. The goal is to investigate conditions and assumptions influencing the PPH bias, and to suggest methods to correct for it. / Visible PPH biases vary from about 0.02 to 0.30, depending on area size, view/sun geometry, and other factors influencing optical depth retrievals and albedo calculations. Broadband PPH biases are slightly smaller than visible biases; broadband absorptance biases are about an order of magnitude smaller. Approximate estimates of the bias in broadband reflected flux at cloud top often exceed 30 Wm$ sp{-2}$ for near-nadir measurements, suggesting that the assumption of cloud homogeneity produces errors that cannot be ignored in climate studies. / Solar geometry affects the PPH bias not only through the direct dependence of albedo on solar zenith angle, but also through systematic changes in the apparent mean and variance of optical depth arising from the neglect of 3-d effects in satellite radiance inversions. PPH biases decrease with data resolution, increase when atmospheric radiative effects are accounted for in optical depth retrievals, and are only slightly affected by water cloud microphysics. PPH biases are also shown to differ substantially between the forward and backward scattering directions, and between large-scale models with and without provision for fractional cloudiness. / A large fraction of the PPH bias is removable by: (1) adjusting regionally averaged optical depths with the reduction factor of Cahalan et al. (1994a), and (2) fitting observed optical depth distributions with lognormal and (to a lesser degree) gamma distributions. These methods require the logarithmic mean and variance of optical depth, which are parameterized as a function of regional mean optical depth and cloud fraction, quantities routinely available in climate models.

<p> Mapping forest resources is useful for identifying threat patterns and monitoring changes associated with landscapes. Remote Sensing and Geographic Information Science techniques are effective tools used to identify and forecast forest resource threats such as exotic plant invasion, vulnerability to climate change, and land-use/cover change. This research focused on mapping abundance and distribution of Russian-olive using soil and land-use/cover data, evaluating historic land-use/cover change using mappable water-related indices addressing the primary loss of riparian arboreal ecosystems, and detecting year-to-year land-cover changes on forest conversion processes. Digital image processing techniques were used to detect the changes of arboreal ecosystems using ArcGIS ArcInfo&reg; 9.3, ENVI&reg;, and ENVI&reg; EX platforms.</p><p> Research results showed that Russian-olive at the inundated habitats of the Missouri River is abundant compared to terrestrial habitats in the Bismarck-Mandan Wildland Urban Interface. This could be a consequence of habitat quality of the floodplain, such as its silt loam and silty clay soil type, which favors Russian-olive regeneration. Russian-olive has close assemblage with cottonwood (<i>Populus deltoides</i>) and buffaloberry (<i>Shepherdia argentea</i>) trees at the lower elevations. In addition, the Russian-olive-cottonwood association correlated with low nitrogen, low pH, and high Fe, while Russian-olive- buffaloberry association occurred in highly eroded areas.</p><p> The Devils Lake sub-watershed was selected to demonstrate how both land-use/cover modification and climatic variability have caused the vulnerability of arboreal ecosystems on the fringe to such changes. Land-cover change showed that the forest acreage declined from 9% to 1%, water extent increased from 13% to 25%, and cropland extent increased from 34% to 39% between 1992 and 2006. In addition, stochastic modeling was adapted to simulate how land-use/cover change influenced forest conversion to non-forested lands at the urban-wildland fringes in Cass County. The analysis yielded two distinct statistical groups of transition probabilities for forest to non-forest, with high transition probability of unchanged forest (0.54&le; Pff &le; 0.68) from 2006 to 2011. Generally, the land-uses, such as row crops, showed an increasing trend, while grains, hay, seeds, and other crops showed a declining trend. This information is vital to forest managers for implementing restoration and conservation practices in arboreal ecosystems.</p>

The problem of creating synoptic maps from asynoptically gathered data has prompted the development of a number of schemes. Most notable among these schemes are the Kalman filter, the Salby-Fourier technique, and constituent reconstruction. This thesis presents a new technique, called trajectory mapping. Trajectory mapping employs a simple model of air parcel motion to create synoptic maps from asynoptically gathered data. To assess the applicability of the technique, four sources of trajectory mapping errors were analyzed. The analysis revealed that (1) the computational error is negligible; (2) measurement uncertainties can result in errors which grow with time scales on the order of a week; (3) isentropic approximations lead to errors characterized by time scales of a week; and (4) wind field inaccuracies can cause significant errors in individual parcel trajectories in a matter of hours. All the studies, however, indicated that while individual trajectory errors can grow rapidly, constituent distributions, such as those depicted in trajectory maps, are much more robust, maintaining a high level of accuracy for periods on the order of several weeks. The trajectory mapping technique has been successfully applied to a variety of problems. First, trajectory mapping was employed in the study of dynamical wave-breaking events. Second, trajectory mapping was applied in satellite data validation studies, both for the determination of instrument accuracy and precision. Third, trajectory mapping was used to assess the accuracy of the meteorological wind fields. Such demonstrations imply that trajectory mapping will become an important tool in answering questions of global change, particularly the issue of ozone depletion.