Reanalysis products are widely used to study the land-atmosphere exchanges of energy, water, and carbon fluxes, and have been evaluated using in situ data above or below ground. Here measurements for several years at five flux tower sites in the U.S. (with a total of 315,576 hours of data) are used for the coupled evaluation of both below- and above-ground processes from three global reanalysis products and six global land data assimilation products. All products show systematic errors in precipitation, snow depth, and the timing of the melting and onset of snow. Despite the biases in soil moisture, all products show significant correlations with observed daily soil moisture for the periods with unfrozen soil. While errors in 2 meter air temperature are highly correlated with errors in skin temperature for all sites, the correlations between skin and soil temperature errors are weaker, particularly over the sites with seasonal snow. While net shortwave and longwave radiation flux errors have opposite signs across all products, the net radiation and ground heat flux errors are usually smaller in magnitude than turbulent flux errors. On the other hand, the all-product averages usually agree well with the observations on the evaporative fraction, defined as the ratio of latent heat over the sum of latent and sensible heat fluxes. This study identifies the strengths and weaknesses of these widely-used products, and helps understand the connection of their errors in above- versus below-ground quantities.

<p>This study examines whether and how land-atmosphere interactions can have an impact on the nocturnal convection over the Southern Great Plains (SGP) through numerical simulations of an intense nocturnal mesoscale convective system (MCS) on 19-20 June 2007 with the Weather Research and Forecasting (WRF V3.3) model. High-resolution nested simulations were conducted using realistic and idealized land-surfaces and two different planetary boundary layer parameterizations: Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ). All simulations show a persistent dry layer around 2 km during daytime and, despite ample instability in the boundary layer, the lack of a mesoscale lifting mechanism prevents precipitating convection in the daytime and in the evening ahead of the MCS passage after local midnight. Integral differences in timing and amount of MCS precipitation among observations and model results were examined in the light of daytime land-atmosphere interactions, nocturnal pre-storm environment, cold pool strength, squall line morphology and propagation speed, and storm rainfall. At the meso-gamma scale, differences in land-cover and soil type have as much of an effect on the simulated pre-storm environment as the choice of PBL parameterization: MYJ simulations exhibit strong sensitivity to changes in the land-surface in contrast to negligible impact in the case of YSU. A comparison of one-way and two-way nested MYJ results demonstrates that daytime land-atmosphere interactions modify the pre-storm environment remotely through advection of low-level thermodynamic features, which strongly impact the development phases of the MCS. At the end of the afternoon, as the boundary layer collapses, a more homogenous and deeper PBL (and stronger low level shear) is evident in the case of YSU as compared to MYJ when initial land-surface conditions are the same. For different land-surface conditions, propagation speed is generally faster, and organization (bow echo morphology) and cold pool strength enhanced when nocturnal PBL heights are higher and there is stronger low level shear in the pre-storm environment independently of the boundary layer parameterization. To elucidate the distinct roles of mesoscale transport and redistribution of low level instability (daytime remote feedbacks) and low level shear in the downwind pre-storm environment (nighttime local feedbacks), which is to separate the nonlinear land-atmosphere physical processes from PBL parameterization-specific effects on simulated storm dynamics, requires addressing the phase delay in storm development and propagation between the observed and the simulated MCS.</p><p>Another research objective was to examine the contribution of the land surface at short time scales. A second set of experiments was performed in which the land surface properties were homogenized every 5 minutes. The results show that surface effects are most pronounced during periods of insolation and, for the Yonsei University PBL parameterization, effects on the PBL height are most pronounced at the time of PBL collapse. Image processing techniques were found to be a useful measure of the spatial variation within fields. The results of this study show that, for this case, the integrated effect of the land surface can have a noticeable effect on convection, but such effects are not readily discernible at the 5-minute scale. While this study focused on the thermodynamic effects, further work should examine sensitivity to grid spacing and surface roughness.</p> / Thesis

The present work focuses on the sources and transport of water vapor to the La Plata Basin (LPB), and the role of groundwater dynamics on the simulation of hydrometeorological conditions over the basin. In the first part of the study an extension to the Dynamic Recycling Model (DRM) is developed to estimate the water vapor transported to the LPB from different regions in South America and the nearby oceans, and the corresponding contribution to precipitation over the LPB. It is found that more than 23% of the precipitation over the LPB is from local origin, while nearly 20% originates from evapotranspiration from the southern Amazon. Most of the moisture comes from terrestrial sources, with the South American continent contributing more than 62% of the moisture for precipitation over the LPB. The Amazonian contribution increases during the positive phase of El Niño and the negative phase of the Antarctic Oscillation. In the second part of the study the effect of a groundwater scheme on the simulation of terrestrial water storage, soil moisture and evapotranspiration (ET) over the LPB is investigated. It is found that the groundwater scheme improves the simulation of fluctuations in the terrestrial water storage over parts of the southern Amazon. There is also an increase in the soil moisture in the root zone over those regions where the water table is closer to the surface, including parts of the western and southern Amazon, and of the central and southern LPB. ET increases in the central and southern LPB, where it is water limited. Over parts of the southeastern Amazon the effects of the groundwater scheme are only observed at higher resolution, when the convergence of lateral groundwater flow in local topographical depressions is resolved by the model. Finally, the effects of the groundwater scheme on near surface conditions and precipitation are explored. It is found that the increase in ET induced by the groundwater scheme over parts of the LPB induces an increase in near surface specific humidity, accompanied by a decrease in near surface temperature. During the dry season, downstream of the regions where ET increases, there is also a slight increase in precipitation, over a region where the model has a dry bias compared with observations. During the early rainy season, there is also an increase in the local convective available potential energy. Over the southern LPB, groundwater induces an increase in ET and precipitation of 13 and 10%, respectively. Over the LPB, the groundwater scheme tends to improve the warm and dry biases of the model. It is suggested that a more realistic simulation of the water table depth could further increase the simulated precipitation during the early rainy season.

Land surface areas, which represent approximately 30% of the Earth’s surface, contribute largely to the complexity of the climate system by exchanging water, energy, momentum, and chemical materials with the overlying atmosphere. Because of the highly heterogeneous nature of the land surface and its rapid transformation due to human activities, future climate projections are less certain on regional scales than for the globe as a whole. The work presented in this dissertation is focused on a better understanding of regional-scale land–atmosphere interactions and their impacts on climate and air quality. Specifically, I concentrate my research on three typical regions in the United States (U.S.): 1) the Central U.S. (representing transition zones between arid and wet climates); 2) the Houston metropolitan region (representing a major urban area); and 3) the eastern U.S. (representing temperate forested regions). These regions are also chosen owing to the consideration of data availability. The first study concerns the roles of vegetation phenology and groundwater dynamics in regulating evapotranspiration and precipitation over the transition zones in summer months. It is found that the warm-season precipitation in the Central U.S. is sensitive to latent heat fluxes controlled by vegetation dynamics. Groundwater enhances the persistence of soil moisture memory from rainy periods to dry periods by transferring water to upper soil layers through capillary forces. Enhancement in soil moisture facilitates vegetation persistence in dry periods, producing more evaporation to the atmosphere and resulting in enhanced precipitation, which then increases soil moisture. The second study compares the impacts of future urbanization and climate change on regional air quality. The results show that the effect of land use change on surface ozone (O3) is comparable to that of climate change, but the details differ across the domain. The third study deals with the formation and distributions of secondary organic aerosols (SOA) — a largely overlooked but potentially important component in the climate system. Under future different climate scenarios, I found that biogenic emissions — an important precursor of SOA — are expected to increase everywhere over the U.S., with the largest increase found in the southeastern U.S. and the northwestern U.S., while changes in SOA do not necessarily follow those in biogenic emissions. Other factors such as partitioning coefficients, atmospheric oxidative capability, primary organic carbon, and anthropogenic emissions also play a role in SOA formation. Direct and indirect impacts from climate change complicate the future SOA formation. / text

Hydraulic conductivity of variably-saturated soils is critical to understanding processes at the land surface. Yet measuring it over an area comparable to the resolution of land-surface models is fraught because of its strong spatial and temporal variations, which render point measurements nearly useless. We derived unsaturated hydraulic conductivity at the horizontal scale of hectometers and the vertical scale of decimeters by analyzing trends in soil moisture measured using the cosmic-ray neutron method. The resulting effective hydraulic conductivity remains close to its value at saturation over approximately half of the saturation range and then plummets. It agrees with the aggregate of 36 point measurements near saturation, but becomes progressively higher at lower water contents; the difference is potentially reconcilable by upscaling of point measurements. This study shows the feasibility of the cosmic-ray method, highlights the importance of measurement scale, and provides a route toward better understanding of land-surface processes.

abstract: Land-atmosphere interactions of semiarid shrublands have garnered significant scientific interest. One of the main tools used for this research is the eddy covariance (EC) method, which measures fluxes of energy, water vapor, and carbon dioxide. EC fluxes can be difficult to interpret due to complexities within the EC footprint (i.e. the surface conditions that contribute to the flux measurements). Most EC studies use a small number of soil probes to estimate the land surface states underlying the measured fluxes, which likely undersamples the footprint-scale conditions, especially in semiarid shrublands which are characterized by high spatial and temporal variability. In this study, I installed a dense network of soil moisture and temperature probe profiles in the footprint region of an EC tower at two semiarid sites: a woody savanna in southern Arizona and a mixed shrubland in southern New Mexico. For data from May to September 2013, I link land surface states to EC fluxes through daily footprints estimated using an analytical model. Novel approaches are utilized to partition evapotranspiration, estimate EC footprint soil states, connect differences in fluxes to footprint composition, and assess key drivers behind soil state variability. I verify the hypothesis that a small number of soil probes poorly estimates the footprint conditions for soil moisture, due to its high spatial variability. Soil temperature, however, behaves more consistently in time and space. As such, distributed surface measurements within the EC footprint allow for stronger ties between evapotranspiration and moisture, but demonstrate no significant improvement in connecting sensible heat flux and temperature. I also find that in these systems vegetation cover appears to have stronger controls on soil moisture and temperature than does soil texture. Further, I explore the influence of footprint vegetation composition on the measured fluxes, which reveals that during the monsoon season evaporative fraction tends to increase with footprint bare soil coverage for the New Mexico site and that the ratio of daily transpiration to evapotranspiration increases with grass coverage at the Arizona site. The thesis results are useful for understanding the land-atmosphere interactions of these ecosystems and for guiding future EC studies in heterogeneous landscapes. / Dissertation/Thesis / M.S. Civil and Environmental Engineering 2013

Soil moisture influences the water and energy cycles of terrestrial environments, and thus plays an important climatic role. However, the behavior of soil moisture at large scales, including its impact on atmospheric processes such as precipitation, is not well characterized. Satellite remote sensing allows for indirect observation of large-scale soil moisture, but validation of these data is complicated by the difference in scales between remote sensing footprints and direct ground-based measurements. To address this problem, a method, based on information theory (specifically, mutual information), was developed to determine the useful information content of satellite soil moisture records using precipitation observations. This method was applied to three soil moisture datasets derived from Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements over the contiguous U.S., allowing for spatial identification of the algorithm with the least inferred error. Ancillary measures of biomass and topography revealed a strong dependence between algorithm performance and confounding surface properties. Next, statistical causal identification methods (i.e. Granger causality) were used to examine the link between AMSR-E soil moisture and the occurrence of next day precipitation, accounting for long term variability and autocorrelation in precipitation. The probability of precipitation occurrence was modeled using a probit regression framework, and soil moisture was added to the model in order to test for statistical significance and sign. A contrasting pattern of positive feedback in the western U.S. and negative feedback in the east was found, implying a possible amplification of drought and flood conditions in the west and damping in the east. Finally, observations and simulations were used to demonstrate the pitfalls of determining causality between soil moisture and precipitation. It is shown that ignoring long term variability and precipitation autocorrelation can result in artificial positive correlation between soil moisture and precipitation, unless explicitly accounted for in the analysis. In total, this dissertation evaluates large-scale soil moisture measurements, outlines important factors that can cloud the determination of land surface-atmosphere hydrologic feedback, and examines the causal linkage between soil moisture and precipitation at large scales.

abstract: Land surface fluxes of energy and mass developed over heterogeneous mountain landscapes are fundamental to atmospheric processes. However, due to their high complexity and the lack of spatial observations, land surface processes and land-atmosphere interactions are not fully understood in mountain regions. This thesis investigates land surface processes and their impact on convective precipitation by conducting numerical modeling experiments at multiple scales over the North American Monsoon (NAM) region. Specifically, the following scientific questions are addressed: (1) how do land surface conditions evolve during the monsoon season, and what are their main controls?, (2) how do the diurnal cycles of surface energy fluxes vary during the monsoon season for the major ecosystems?, and (3) what are the impacts of surface soil moisture and vegetation condition on convective precipitation? Hydrologic simulation using the TIN-based Real-time Integrated Basin Simulator (tRIBS) is firstly carried out to examine the seasonal evolution of land surface conditions. Results reveal that the spatial heterogeneity of land surface temperature and soil moisture increases dramatically with the onset of monsoon, which is related to seasonal changes in topographic and vegetation controls. Similar results are found at regional basin scale using the uncoupled WRF-Hydro model. Meanwhile, the diurnal cycles of surface energy fluxes show large variation between the major ecosystems. Differences in both the peak magnitude and peak timing of plant transpiration induce mesoscale heterogeneity in land surface conditions. Lastly, this dissertation examines the upscale effect of land surface heterogeneity on atmospheric condition through fully-coupled WRF-Hydro simulations. A series of process-based experiments were conducted to identify the pathways of soil moisture-rainfall feedback mechanism over the NAM region. While modeling experiments confirm the existence of positive soil moisture/vegetation-rainfall feedback, their exact pathways are slightly different. Interactions between soil moisture, vegetation cover, and rainfall through a series of land surface and atmospheric boundary layer processes highlight the strong land-atmosphere coupling in the NAM region, and have important implications on convective rainfall prediction. Overall, this dissertation advances the study of complex land surface processes over the NAM region, and made important contributions in linking complex hydrologic, ecologic and atmospheric processes through numerical modeling. / Dissertation/Thesis / Doctoral Dissertation Civil and Environmental Engineering 2016

abstract: Rapid urban expansion and the associated landscape modifications have led to significant changes of surface processes in built environments. These changes further interact with the overlying atmospheric boundary layer and strongly modulate urban microclimate. To capture the impacts of urban land surface processes on urban boundary layer dynamics, a coupled urban land-atmospheric modeling framework has been developed. The urban land surface is parameterized by an advanced single-layer urban canopy model (SLUCM) with realistic representations of urban green infrastructures such as lawn, tree, and green roof, etc. The urban atmospheric boundary layer is simulated by a single column model (SCM) with both convective and stable schemes. This coupled SLUCM-SCM framework can simulate the time evolution and vertical profile of different meteorological variables such as virtual potential temperature, specific humidity and carbon dioxide concentration. The coupled framework has been calibrated and validated in the metropolitan Phoenix area, Arizona. To quantify the model sensitivity, an advanced stochastic approach based on Markov-Chain Monte Carlo procedure has been applied. It is found that the development of urban boundary layer is highly sensitive to surface characteristics of built terrains, including urban land use, geometry, roughness of momentum, and vegetation fraction. In particular, different types of urban vegetation (mesic/xeric) affect the boundary layer dynamics through different mechanisms. Furthermore, this framework can be implanted into large-scale models such as Weather Research and Forecasting model to assess the impact of urbanization on regional climate. / Dissertation/Thesis / Doctoral Dissertation Civil and Environmental Engineering 2016

abstract: The world has been continuously urbanized and is currently accommodating more than half of the human population. Despite that cities cover only less than 3% of the Earth’s land surface area, they emerged as hotspots of anthropogenic activities. The drastic land use changes, complex three-dimensional urban terrain, and anthropogenic heat emissions alter the transport of mass, heat, and momentum, especially within the urban canopy layer. As a result, cities are confronting numerous environmental challenges such as exacerbated heat stress, frequent air pollution episodes, degraded water quality, increased energy consumption and water use, etc. Green infrastructure, in particular, the use of trees, has been proved as an effective means to improve urban environmental quality in existing research. However, quantitative evaluations of the efficacy of urban trees in regulating air quality and thermal environment are impeded by the limited temporal and spatial scales in field measurements and the deficiency in numerical models. This dissertation aims to advance the simulation of realistic functions of urban trees in both microscale and mesoscale numerical models, and to systematically evaluate the cooling capacity of urban trees under thermal extremes. A coupled large-eddy simulation–Lagrangian stochastic modeling framework is developed for the complex urban environment and is used to evaluate the impact of urban trees on traffic-emitted pollutants. Results show that the model is robust for capturing the dispersion of urban air pollutants and how strategically implemented urban trees can reduce vehicle-emitted pollution. To evaluate the impact of urban trees on the thermal environment, the radiative shading effect of trees are incorporated into the integrated Weather Research and Forecasting model. The mesoscale model is used to simulate shade trees over the contiguous United States, suggesting how the efficacy of urban trees depends on geographical and climatic conditions. The cooling capacity of urban trees and its response to thermal extremes are then quantified for major metropolitans in the United States based on remotely sensed data. It is found the nonlinear temperature dependence of the cooling capacity remarkably resembles the thermodynamic liquid-water–vapor equilibrium. The findings in this dissertation are informative to evaluating and implementing urban trees, and green infrastructure in large, as an important urban planning strategy to cope with emergent global environmental changes. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2019