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<p>While very important from an economical and societal point of view, estimating precipitation in the western United States remains an unsolved and challenging problem. This is due to difficulties in observing and modeling precipitation in complex terrain. This research examines this issue by (i) providing a systematic evaluation of precipitation observations to quantify data uncertainty and (ii) investigating the ability of the Ocean-Land-Atmosphere Model (OLAM) to simulate the winter hydroclimate in this region. This state-of-the-art, non-hydrostatic model has the capability of simulating simultaneously all scales of motions at various resolutions.</p><p>This research intercompares nine precipitation datasets commonly used in hydrometeorological research in two ways. First, using principal component analysis, a precipitation climatology is conducted for the western U.S. from which five unique precipitation climates are identified. From this analysis, data uncertainty is shown to be primarily due to differences in (i) precipitation over the Rocky Mountains, (ii) the eastward wet-to-dry precipitation gradient during the cold season, (iii) the North American Monsoon signal, and (iv) precipitation in the desert southwest during spring and summer. The second intercomparison uses these five precipitation regions to provide location-specific assessments of uncertainty, which is shown to be dependent on season and location.</p><p>Long-range weather forecasts on the order of a season are important for water-scarce regions such as the western U.S. The modeling component of this research looks at the ability of the OLAM to simulate the hydroclimate in the western U.S. during the winter of 1999. Six global simulations are run, each with a different spatial resolution over the western U.S. (360 km down to 11 km). For this study, OLAM is configured as for a long-range seasonal hindcast but with observed sea surface temperatures. OLAM precipitation compares well against observations, and is generally within the range of data uncertainty. Observed and simulated synoptic meteorological conditions are examined during the wettest and driest events. OLAM is shown to reproduce the appropriate anomaly fields, which is encouraging since it demonstrates the capability of a global climate model, driven only by SSTs and initial conditions, to represent meteorological features associated with daily precipitation variability.</p> / Dissertation

Atmospheric aerosols and trace gases are a highly relevant component of the climate system affecting atmospheric radiative transfer and the hydrologic cycle. In arid and semi-arid regions, where cloud cover is often low and precipitation is generally scarce and sporadic, the driving processes accounting for the production, loss and transport of atmospheric constituents are often distinctly different from other climates. In arid regions, the same circulation dynamics that suppress cloud formation can be responsible for creating strong subsidence inversions, which cap atmospheric mixing and trap pollutants close to the surface, often placing populated arid regions high on global rankings of air pollution concerns. In addition, low soil moisture can encourage wind-blown dust emissions, which can be a significant fraction of the total aerosol loading in both coarse and fine modes on a mass basis. Three distinct focus regions are investigated over varying time scales, using a diverse set of techniques, and with wide-ranging primary goals. 1) the Tehran metropolitan area in Iran over a ten-year period from 2000-2009, 2) Tucson, Arizona over 2012-2014 with three intensive monitoring periods during summer 2014 and winter 2015 and 3) the San Joaquin Valley in California during the NASA DISCOVER-AQ campaign during Jan-Feb 2013. However, in all cases, local and regional scale meteorology play a significant role in controlling the spatiotemporal variability in trace gas and aerosol concentrations. Particular emphasis is placed on understanding transport pathways due to the local wind patterns and the importance of key meteorological parameters such as temperature, humidity and solar radiation on controlling production and loss mechanisms. While low in magnitude, the precipitation pattern is still an important sink mechanism that modulates gas phase and particle abundances in all three regions, either through scavenging or by promoting vertical mixing. The reported measurements and data analysis serve to improve the characterization of trace gases and aerosols in populated arid regions and offer process level understanding of dominant mechanisms for model validations and improvements.

This thesis develops several unique different precipitation statistics and verification measures that are applicable to scales relevant to global climate models, regional models and hydrological runoff models, through a series of three papers.The first section of the dissertation is motivated by the fact that climate models are unable to account for the variability of precipitation within a grid box, and that other hydrologically critical precipitation characteristics, such as intensity and frequency, are often times overlooked in the literature. Several issues related to spatial averaging of these two measures are investigated. Rain gauge reports and radar precipitation analyses are used here to address three issues related to the areal estimation of intensity and frequency of precipitation. Differences between the order of spatial and temporal averaging methods are proven to be significant; therefore quantifying these differences is critical for both climate model diagnostics and downscaling applications.The second section documents spatio-temporal statistics of hourly fine-scale precipitation analyses for the continental U.S. The spatio-temporal coherence of precipitation fields, quantified under the assumption of isotropy, reveals significant seasonal and geographical variations. Anisotropic factors are then considered to obtain estimates of the mean movement and orientation of the precipitating storm systems.The dissertation provides new methodology to quantify the spatio-temporal variability of observed and modeled precipitation that offers new insight into how to correct erroneous model simulations.The methodologies are used to evaluate the performance of two mesoscale atmospheric forecast models, one with explicit treatment of convection and the other with a convective parameterization scheme. Designed to account for the transient and intermittent character of precipitation, these new verification techniques show that explicit formulation of convection yields spatio-temporal covariance structures that agree closely with observations. The explicit scheme shows however, a systematic tendency to propagate summertime precipitating storm systems to the right of observations, suggesting that the model's convection is too dependent on the source of low-level moisture.

Limited Time Period (LTP) running trends are used to evaluate Microwave Sounding Unit (MSU) derived tropospheric temperature trend methods in an attempt to alleviate documented considerable disagreements between tropospheric datasets so investigation into the atmospheric variability is able to move forward.Regression derived coefficients were used to combine lower stratosphere (LS) and mid-troposphere to lower stratosphere (MT) simulated MSU channels from RATPAC radiosonde data. This protocol is used to estimate tropospheric temperature trends and compared to actual RATPAC derived tropospheric temperature trends. It is found that the statistical LS/MT combination results in greater than 50% error over some LTP. These errors are found to exist when strong cooling in the stratosphere is coincident with periods when the level separating cooling from warming is above the tropopause.LTP trends are also created from various MSU difference time series between the University of Alabama in Huntsville (UAH) and Remote Sensing System (RSS) group's lower troposphere (LT) and MT channels. Results suggest the greatest discrepancies over time periods where NOAA-11 through NOAA-15 adjustments was applied to the raw LT data over land. Discrepancies are shown to be dominated by differences in diurnal correction methods due to orbital drift. Comparison of MSU data with radiosonde data indicate that RSS's method of determining diurnal effects is overestimating the correction in the LT channel. Diurnal correction signatures still exist in the RSS LT time series and are likely affecting the long term trend with a warm bias.These findings suggest atmospheric amplification is not happening in the atmosphere using globally averaged data over the MSU era. There is evidence however from the radiosonde data that shows greater warming in the ~300-500 hPa layer than at the surface during some LTP in the complete radiosonde database. This temporal change in temperature trends warrants further studies on this subject.This research suggests overall that the temporal changes in temperature trend profiles and their causes are extremely important in our understanding of atmospheric changes and are themselves, not well characterized.

<p> Mineral dust aerosols can impact air quality, climate change, biological cycles, tropical cyclone development and flight operations due to reduced visibility. Dust emissions are primarily limited to the extensive arid regions of the world, yet can negatively impact local to global scales, and are extremely complex to model accurately. Within this dissertation, the Dust Entrainment And Deposition (DEAD) model was adapted to run, for the first known time, using high temporal (hourly) and spatial (0.3&deg;x0.3&deg;) resolution data to methodically interrogate the key parameters and factors influencing global dust emissions. The dependence of dust emissions on key parameters under various conditions has been quantified and it has been shown that dust emissions within DEAD are largely determined by wind speeds, vegetation extent, soil moisture and topographic depressions. Important findings were that grid degradation from 0.3&ordm;x0.3&ordm; to 1&ordm;x1&ordm;, 2&ordm;x2.5&ordm;, and 4&deg;x5&deg; of key meteorological, soil, and surface input parameters greatly reduced emissions approximately 13% and 29% and 64% respectively, as a result of the loss of sub grid detail within these key parameters at coarse grids. After running high resolution DEAD emissions globally for 2 years, two severe dust emission cases were chosen for an in-depth investigation of the root causes of the events and evaluation of the 2&deg;x2.5&deg; Goddard Earth Observing System (GEOS)-Chem and 0.3&deg;x0.3&deg; DEAD model capabilities to simulate the events: one over South West Asia (SWA) in June 2008 and the other over the Middle East in July 2009. The 2 year lack of rain over SWA preceding June 2008 with a 43% decrease in mean rainfall, yielded less than normal plant growth, a 28% increase in Aerosol Optical Depth (AOD), and a 24% decrease in Meteorological Aerodrome Report (METAR) observed visibility (VSBY) compared to average years. GEOS-Chem captured the observed higher AOD over SWA in June 2008. More detailed comparisons of GEOS-Chem predicted AOD and visibility over SWA with those observed at surface stations and from satellites revealed overall success of the model, although substantial regional differences exist. Within the extended drought, the study area was zoomed into the Middle East (ME) for July 2009 where multi-grid DEAD dust emissions using hourly CFSR meteorological input were compared with observations. The high resolution input yielded the best spatial and temporal dust patterns compared with Defense Meteorological Satellite Program (DMSP), Moderate Resolution Imaging Spectroradiometer (MODIS) and METAR VSBY observations and definitively revealed Syria as a major dust source for the region. The coarse resolution dust emissions degraded or missed daily dust emissions entirely. This readily showed that the spatial scale degradation of the input data can significantly impair DEAD dust emissions and offers a strong argument for adapting higher resolution dust emission schemes into future global models for improvements of dust simulations.</p>

<p> Smoke plumes associated with wildland fires are difficult to characterize due to the non-linear behavior of the variables involved. Plume chemistry is largely modeled using emission factors to represent the relative trace gas and aerosol species emitted. Plume dynamics are modeled based on assumptions of plume vertical distribution and atmospheric dispersion. In the studies presented here, near and in-source measurements of emissions from prescribed burns are used to characterize the variability of emission factors from low-intensity fires. Emissions factors were found to be in the same range as those from other, similar studies in the literature and it appears that the emission factors may be sensitive to small differences in surface conditions such as fuel moisture, surface wind speed, and the ratio of live to dead fuels. We also used two coupled fire atmosphere models, which utilize the Weather Research and Forecasting (WRF) model called WRF-Fire and WRF-Sfire, to investigate the role that atmospheric stability plays in influencing plume rise as well as developing a technique for assessing plume rise and the vertical distribution of pollutants in regional air quality models. Plume heights, as well as rate of growth of the fire, were found to be sensitive to atmospheric stability while fire rate of spread was not. The plume center-of-mass technique was demonstrated to work well but has slightly low estimates compared to observations. </p>

Considerable research has been performed on persistent-anomaly structures for the Northern Hemisphere winter. However, atmospheric blocking structures during the warm season also have a considerable impact on weather and climate, as manifested through heat waves, floods, and droughts. In particular, atmospheric blocked flow has a profound impact on anomalously-dry regimes over the central North American continent. In order to provide a better understanding of the life cycle of the atmospheric blocking events and their relation to fast-climate phenomena, we analyse persistent height-anomaly structures derived from the National Centers for Environmental Prediction (NCEP) global reanalyses. We devise an objective criterion for the characterization of blocked flow by relating it to persistent positive height anomalies. Individual warm-season events over the North American continent are then identified and examined in case studies. This reveals a type of blocking regime, differing in structure from the Rex and Omega type blocks described in the literature, as being important in the region during summer. Moreover, changes in the statistical distribution of the event frequencies are analysed in order to detect climatic trends. We find a pronounced westward displacement of the North American anomaly event frequency maximum to be associated with the 1999-2004 drought in the Canadian Prairies.

<p> The upper troposphere lower stratosphere (UTLS) is a region of minimum temperatures that contains the tropopause. As a transition region between the troposphere and the stratosphere, the UTLS contains various processes that facilitate stratosphere-troposphere exchange (STE) which can redistribute radiatively important species such as water vapor or ozone. One potential marker for STE is the double tropopause (DT). Therefore this study seeks to further understand how DTs form and how they could enhance the current understanding of some STE processes in the UTLS. </p><p> Using data from the High Resolution Dynamic Limb Sounder (HIRDLS), a data set with high vertical and horizontal resolution, newly discovered DT structures are found over the Pacific and Atlantic oceans that suggest a relationship between the DT and both storm tracks and Rossby waves. The association between DTs and storm tracks is examined by further analyzing the recently discovered and unexpected relationship between the DT and the tropopause inversion layer (TIL) in a developing baroclinic disturbance. Results show an increase in the number of DTs when the lapse rate of the extratropical TIL is less than -2&deg;C/km, i.e. when the TIL is stronger and the local stability is higher. Composites of ERA-Interim DT profiles for three different TIL strengths shows that the vertical motion and relative vorticity both decrease as the TIL increases, which suggests the warm conveyor belt as a mechanism. This is investigated further with a case study analysis of a developing extratropical cyclone in the Pacific Ocean. Additionally, an analysis of DTs in relation to the large scale flow responsible for storm development shows a strong correlation between monthly Rossby wave activity, ozone laminae and DT variability. Further examination shows that if these waves break a DT will be found with a wave breaking event about 30% of the time in the eastern Pacific and eastern Atlantic oceans, both regions of poleward wave breaking. </p><p> These results highlight a new and more complicated DT structure that is a product of both large scale dynamics and small scale vertical motions, thus adding new information to the current understanding of the UTLS.</p>

<p> Downdrafts are an integral part of the convective cycle, and have been observed and documented for more than a hundred years. But many questions still surround convective downdrafts and their most difficult to observe properties. These questions have made the parameterization of convective downdrafts in global climate models (GCMs) very difficult. Designers of parameterizations have resorted to a wide range of assumptions and unverified hypotheses in their models of convective downdrafts. </p><p> In the last ten years, computing resources have advanced to a point where large domain, high resolution cloud resolving models (CRMs) can easily be run for long simulations. This study uses several simulations with 1 km horizontal resolution from the System for Atmospheric Modeling (SAM) v6.8.2 to examine convective downdrafts. We look at Radiative-Convective Equilibrium (RCE), a 21 day case from TOGA-COARE, Weak Temperature Gradient (WTG) simulations with varied shear profiles, and Lagrangian Parcel data to consider many difficult to observe properties of downdrafts. </p><p> We consider a variety of assumptions and questions that arise in the development of convective parameterizations. Our results show that downdrafts are an important mass flux in all simulations, and that cold pools organize convective systems and enhance updraft Convective Available Potential Energy (CAPE). We examine the ability for downdrafts to help couple deep convection to high relative-humidity regions in the tropics, and find that entrainment is likely a more important process in this relationship. We discuss the impact of downdrafts in maintaining boundary layer quasi-equilibrium, and find that, in our simulations, environmental entrainment has a larger impact on low-level most static energy. Finally, we show results from Lagrangian parcel data that illuminate our downdrafts as existing in an unsaturated state, with increasing buoyancy as they descend. We show that many of our downdrafts have positive buoyancy perturbations, suggesting the presence of warm downdrafts and under-shooting bottoms in heavily precipitating tropical systems.</p>