LIght Detection And Ranging (LIDAR) systems are complex instruments whose performance is affected by a variety of atmospheric, system design, and geometric factors. To ensure performance parameters, such as maximum range and accuracy, are achieved it is imperative that statistically representative variations in these factors are considered to identify if the system will not meet performance goals under particular corner cases. To this end, a high fidelity, physics-based simulator was developed to aid in the LIDAR design process. This simulator is composed of four major libraries – atmosphere, LIDAR, electronics, and algorithms. The physics-based models in each of these libraries account for environmental, optical, electrical, and mechanical variations in the underlying components which ultimately affect LIDAR signals and data products. The goal of this simulator is to generate realistic LIDAR signals and LIDAR-derived data products to aid in performing trade studies, determine performance envelops, identify parameter tolerances, debug experimental data collections, and provide a testbed to evaluate different algorithms. The simulator has undergone validation and verification against other relevant models, such as NRL-MSISe00, LEEDR, MODTRAN, etc., as well as experimental data. Using this simulator, Monte Carlo techniques were utilized for aerosol (elastic), temperature (inelastic rotational Raman), and water vapor (inelastic vibrational-rotational Raman) LIDARs to determine their performance in a variety of representative atmospheres, and pointing angles. System performance is expressed as a cumulative distribution function of error between LIDAR-retrieved atmospheric quantities (aerosol extinction, temperature, and water vapor) and ‘truth’ atmospheric quantities input into the simulator.

A small form-factor atmospheric lidar demonstrator was developed for high resolution measurements of aerosols. The system is a conventional elastic backscatter lidar with a pulsed laser transmitter operating at a wavelength 1.54 μm coupled with a 2-inch diameter receiver. The intended purpose of the lidar system is to detect various aerosols in the atmosphere at high spatio-temporal resolution and close observational range. The intentionally low Size, Weight and Power (SWaP) of the system design enables use on a variety of fixed and airborne platforms (i.e. unmanned aerial systems). The relative low cost to build and operate the system facilitates proliferation of networks of such systems for increased monitoring coverage. First results from the system that show aerosol transport over a localized urban area will be presented. Future enhancements, such as a depolarization capability, will also be discussed.

We present an unprecedented comparison of temperature measurements from the Rayleigh scatter (RS) and sodium (Na) lidar techniques. The extension of the RS technique into the lower thermosphere that has been achieved by the group at Utah State University (USU), enables simultaneous, common-volume measurements by the two lidar systems hosted in the Atmospheric Lidar Observatory at USU. The two lidars' nightly averaged temperatures from 80-105 km, based on 19 nights of observations, are explored.

The Utah State University (USU) campus (41.7 degrees N, 111.8 degrees W) hosts a unique upper atmospheric observatory that houses both a high-power, large-aperture Rayleigh lidar and a Na lidar. For the first time, we will present 19 nights of coordinated temperature measurements from the two lidars, overlapping in the 80-110km observational range, over one annual cycle (summer 2014 to summer 2015). This overlap has been achieved through upgrades to the existing USU Rayleigh lidar that increased its observational altitude from 45-95 to 70-115km and by relocating the Colorado State Na lidar to the USU campus. Previous climatological comparisons between Rayleigh and Na lidar temperatures have suggested that significant temperature differences exist between the two techniques. This new comparison aims to further these previous studies by using simultaneous, common-volume observations. The present comparison showed the best agreement between 85 and 95km, with a temperature difference, averaged over the whole data set, of about 1.10.5K. Larger differences occurred above and below these altitudes with the Rayleigh temperatures being colder by about 3.50.5K at 82km and warmer by up to 9.13.5K above 95km.

The plots in Fig. 1 illustrate the differences between the two lidars’ temperatures with respect to altitude and time of year: • The best agreement between the two temperature curves occurs from 85 to 95 km • RS temperatures are colder than Na temperatures below 90 km • RS temperatures are warmer than Na temperature from 95 km and above • RS temperatures show stronger vertical wave structure • The worst agreement between the two temperature curves, at all altitudes, occurs in late fall-early winter • The best agreement, at all altitudes, occurs near equinoxes 2. Lidar system descriptions and 2014-2015 observations 3. Results 5. Conclusions and Future Work

..................................................................................................................... iii PUBLIC ABSTRACT ........................................................................................................v DEDICATION .................................................................................................................. vi ACKNOWLEDGMENTS ............................................................................................... vii LIST OF TABLES ............................................................................................................ xi LIST OF FIGURES ......................................................................................................... xii CHAPTER

Rayleigh-scatter lidar observations were made at the Atmospheric Lidar Observatory (ALO) at Utah State University (USU) from 1993–2004 from 45–90 km. The lidar operated at 532 nm with a power-aperture-product (PAP) of ~3.1 Wm2. The sensitivity of the lidar has since been increased by a factor of 66 to 205 Wm2, extending the maximum altitude into new territory, the lower thermosphere. Observations have been extended up to 115 km, almost to the 120 km goal. Early temperatures from four ~4-week periods starting in June 2014 are presented and discussed. They are compared to each other, to the ALO climatology from the original lidar [1], and to temperatures from the NRLMSISe00 empirical model [2].

A Rayleigh lidar was operated from 1993 to 2004, at the Atmospheric Lidar Observatory (ALO; 41.7°N, 111.8°W) at the Center for Atmospheric and Space Sciences (CASS) on the campus of Utah State University (USU). Observations were carried out on over 900 nights, 729 of which had good data starting at 45 km and going upward toward 90 km. They were reduced for absolute temperatures and relative neutral number densities. The latter at 45 km can be put on an absolute basis by using atmospheric models that go up to at least 45 km. The models’ absolute number densities at 45 km are used to normalize the lidar observations, thereby providing absolute densities from 45 to 90 km. We examine these absolute density profiles for differences from the overall mean density profile to show altitudinal structure and seasonal variations.

The Rayleigh-scatter lidar at the Atmospheric Lidar Observatory at Utah State University (ALO-USU; 41.74° N, 111.81° W) started observations in 1993. In 2012 the original lidar system was upgraded with an array of larger mirrors and two lasers to enable observations of the upper mesosphere and lower thermosphere from 70 km to about 115 km in altitude. (Continued refinement should provide data to above 120 km.) Recently, the original system was reconfigured [Elliott et al., 2016] to again observe the lower mesosphere between 40 km and 90 km. Initial data collected by these two parts of the Rayleigh system have been “stitched” together to obtain a full temperature profile from 40 km to about 115 km. These extended profiles have been used to obtain relative neutral densities and temperatures through the entire mesosphere and well into the lower thermosphere. This extends the CEDAR goal of studying coupling between atmospheric regions. Furthermore, by normalizing the relative neutral densities between ~35 and 45 km to an advanced reanalysis model, absolute neutral densities become available from a ground-based, remote-sensing instrument all the way into the lower thermosphere. This opens that region to detailed studies for many research topics. Merging High and Low Altitudes Because of weather and equipment challenges after the small Rayleigh lidar was completed, few nights of good data have been collected so far with the combined system. To illustrate what will be done, we will work with one night of lower altitude data from April 2016 and with one night of higher altitude data from a year earlier, from April 2015. The temperatures from these two nights are shown in Figure 2. Three ways of merging the data are as follows: a.Merge the signals from the two lidars in the overlap region. b.Reduce the big lidar data to temperatures. Use one or more of the lowest altitude temperatures as seed temperatures to reduction the data from the small lidar. c. Reduce the big and small lidar data to temperatures. Average temperatures from the lowest altitudes from the big lidar with temperatures from the same altitudes from the small lidar. Given that we are only illustrating the process, we will use the last method, which is the simplest. Taking into account that the two sets of temperatures will have very different uncertainties, the average temperature is given by T = T# σ# + ⁄ T% σ% ⁄ 1 σ# + ⁄ 1 σ% ⁄ ⁄ and its uncertainty by σ% = 1 1 σ# + ⁄ 1 σ% ⁄ ⁄ . The merged temperature profile is given in Figure 3. This figure emphasizes that the ALO-USU Rayleigh lidar system can provide continuous coverage from the upper stratosphere into the lower thermosphere. Using the first method will provide a continuous signal profile from which the relative density profile can be determined. This can then be used to derive a continuous temperature profile. In addition, the relative density profile can be normalized below 45 km against one of the reanalysis models (e.g., NCEP, MERRA, ERA-Interim) to obtain absolute densities all the way from the stratosphere, through the mesosphere, into the thermosphere. Having ground based observations of the neutral densities at 120 km would be a significant first. Acknowledgements We gratefully acknowledge the support of the USU Physics Department, Space Dynamics Lab, USU Office of Research and Graduate Studies, and personal contributions. The observatory, telescope and laser laboratory were built with funds from NSF, AFOSR, USU, and SDL. Figure 1: Large telescope system. The four 1.25 m mirrors are mounted in the cage where the two laser beams pass through the center of the cage. Figure 2: An all night averaged high altitude profile from 04/14/15 was merged with that of lower data observed on 04/07/16 to show proof of concept of the technique. Future Research With these new observational possibilities come both new and improved research opportunities. We now have neutral densities, in addition to neutral temperatures, extending from the stratosphere well into the lower thermosphere. This is the first time that neutral densities can be obtained all the way to 120 km from ground-based observations. These capabilities suggest numerous projects, a few of most interest to us are given below: o Compare densities and temperatures at 120 km to the bottom boundary conditions for thermospheric models • Important input for satellite orbital-decay predictions. • Significant for examining ionosphere-thermosphere interactions o Examine the significant differences that have been found between Rayleigh and Na lidar temperatures above 95 km at ALO-USU [Sox et al., 2016a]. o Help to understand the Rayleigh-Na differences by comparing Rayleigh temperatures to those from TIMED-SABER (as in Fig. 3) and, later, to those from the OPAL CubeSat. o Extend the search for effects from sudden stratospheric warmings, which have been seen at ALOUSU up to 90 km [Sox et al., 2016b], to the thermosphere and to densities. Figure 3: Illustrative profile of merged temperature data from the USU-ALO big and small lidars. This is compared with SABER data and the MSIS00 model. Background Between 1993 and 2004 the ALO-USU Rayleigh-scatter lidar used a single 44 cm diameter mirror with a GCR series Spectra-Physics Nd:YAG laser operating at 30 Hz and 532 nm (with a PAP = 6.4 Wm%) to make observations from which relative densities and absolute temperatures of the mesosphere could be derived between 40 and 90 km. The ALO-USU lidar system was later upgraded, adding another GCR series laser and four 1.25 m diameter mirrors (increased PAP = 706 Wm%), Figure 1. It came into full operation in 2014. This big Rayleigh lidar opened up Rayleigh observations from the upper mesosphere well into the lower thermosphere, from 70 to 115 km [e.g., Sox et al., 2016; Wickwar et al., 2016]. In the spring of 2016, the 44 cm mirror was repurposed using a Dobsonian telescope design, a new photomultiplier tube, a chopper, and optics to make a small Rayleigh lidar to again observe the lower mesosphere from 40 to 90 km [Elliott, et al., 2016]. The small and big lidars share the same lasers. The ALO-USU Rayleigh lidar system now has the capability of observing from 40 to about 115 km. The intent is to extend this range from 30 to about 120 km. The data from the big and small lidars then need to be combined to produce full profiles over this very extended altitude range. These, in turn, lead to full profiles of relative density, which can be reduced to full profiles of absolute neutral temperatures and absolute neutral densities.

While mesospheric temperature anomalies associated with Sudden Stratospheric Warmings (SSWs) have been observed extensively in the polar regions, observations of these anomalies at midlatitudes are sparse. The original Rayleigh-scatter lidar that operated at the Atmospheric Lidar Observatory (ALO; 41.7°N, 111.8°W) in the Center for Atmospheric and Space Sciences (CASS) on the campus of Utah State University (USU) collected an extensive set of temperature data for 11 years in the 45–90 km altitude range. This work focuses on the extensive Rayleigh lidar observations made during six major SSW events that occurred between 1993 and 2004, providing a climatological study of the midlatitude mesospheric temperatures during these SSW events. An overall disturbance pattern was observed in the mesospheric temperatures during these SSWs. It included coolings in the upper mesosphere, comparable to those seen in the polar regions during SSW events, and warmings in the lower mesosphere.

While the mesospheric temperature anomalies associated with Sudden Stratospheric Warmings (SSWs) have been observed extensively in the polar regions, observations of these anomalies at midlatitudes are much more sparse. The Rayleigh‐scatter lidar system, which operated at the Center for Atmospheric and Space Sciences on the campus of Utah State University (41.7°N, 111.8°W), collected a very dense set of observations, from 1993 to 2004, over a 45–90 km altitude range. This paper focuses on Rayleigh lidar temperatures derived during the six major SSW events that occurred during the 11 year period when the lidar was operating and aims to characterize the local response to these midlatitude SSW events. In order to determine the characteristics of these mesospheric temperature anomalies, comparisons were made between the temperatures from individual nights during a SSW event and a climatological temperature profile. An overall disturbance pattern was observed in the mesospheric temperatures associated with SSW events, including coolings in the upper mesosphere and warmings in the upper stratosphere and lower mesosphere, both comparable to those seen at polar latitudes.