The North American Monsoon System (NAMS) is a dominant factor in climate in the southwestern United States and northwestern Mexico. Despite the influence of the NAMS and the intense research efforts it receives, its predictability, its variability, and the details of its influence on the environment are not well understood. This dissertation is comprised of three papers, which collectively address these three aspects of this complex climate phenomenon through an examination of various data and analyses at multiple spatial and temporal scales, while focusing on impacts in southern Arizona. In the first paper, a modified definition of the NAMS is established to delineate dates for monsoon onset, bursts, breaks, and retreat. The results are applied to an atmospheric compositing study in the second paper and to an applied study of monsoon-wildland fire relationships in the third paper. In the second paper, geopotential height patterns that affect moisture advection are identified. Onset, retreat, and break timing and duration are impacted by shifts in the latitude of the mid-level anticyclone and by lower-level gradients and contour orientation. Analyses in the third paper reveal the some of the complex effects of monsoon onset, variations in break timing and duration, and monsoon retreat on fire occurrence. This research contributes to the current knowledge of the NAMS in general and to the specific regional impacts of the monsoon. The results can (1) improve meteorological forecasts through the recognition of synoptic and sub-synoptic patterns related to the NAMS and (2) help fire managers by expanding the current understanding of the regional controls of wildland fire.

abstract: Ecohydrological responses to rainfall in the North American monsoon (NAM) region lead to complex surface-atmosphere interactions. In early summer, it is expected that soil properties and topography act as primary controls in hydrologic processes. Under the presence of strongly dynamic ecosystems, catchment hydrology is expected to vary substantially in comparison to other semiarid areas, affecting our understanding of ecohydrological processes and the parameterization of predictive models. A large impediment toward making progress in this field is the lack of spatially extensive observational data. As a result, it is critical to integrate numerical models, remote sensing observations and ground data to understand and predict ecohydrological dynamics in space and time, including soil moisture, evapotranspiration and runoff generation dynamics. In this thesis, a set of novel ecohydrological simulations that integrate remote sensing and ground observations were conducted at three spatial scales in a semiarid river basin in northern Sonora, Mexico. First, single site simulations spanning several summers were carried out in two contrasting mountain ecosystems to predict evapotranspiration partitioning. Second, a catchment-scale simulation was conducted to evaluate the effects of spatially-variable soil thickness and textural properties on water fluxes and states during one monsoon season. Finally, a river basin modeling effort spanning seven years was applied to understand interannual variability in ecohydrological dynamics. Results indicated that ecohydrological simulations with a dynamic representation of vegetation greening tracked well the seasonal evolution of observed evapotranspiration and soil moisture at two measurement locations. A switch in the dominant component of evapotranspiration from soil evaporation to plant transpiration was observed for each ecosystem, depending on the timing and magnitude of vegetation greening. Furthermore, spatially variable soil thickness affects subsurface flow while soil texture controls patterns of surface soil moisture and evapotranspiration during the transition from dry to wet conditions. Finally, the ratio of transformation of precipitation into evapotranspiration (ET/P) and run off (Q/P) changed in space and time as summer monsoon progresses. The results of this research improve the understanding of the ecohydrology of NAM region, which can be useful for developing sustainable watershed management plans in the face of anticipated land cover and climate changes. / Dissertation/Thesis / Doctoral Dissertation Geological Sciences 2014

Rapid environmental changes linked to human-induced increases in atmospheric greenhouse gas concentrations have been observed on a global scale over recent decades. Given the relative certainty of continued change across many earth systems, the information output from climate models is an essential resource for adaptation planning. But in the face of many known modeling deficiencies, how confident can we be in model projections of future climate? It stands to reason that a realistic simulation of the present climate is at least a necessary (but likely not sufficient) requirement for a model’s ability to realistically simulate the climate of the future. Here, I present the results of three studies that evaluate the 20th century performance of global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The first study examines precipitation, geopotential height, and wind fields from 21 CMIP5 models to determine how well the North American monsoon system (NAMS) is simulated. Models that best capture large-scale circulation patterns at low levels usually have realistic representations of the NAMS, but even the best models poorly represent monsoon retreat. Difficulty in reproducing monsoon retreat results from an inaccurate representation of gradients in low-level geopotential height across the larger region, which causes an unrealistic flux of low-level moisture from the tropics into the NAMS region that extends well into the post-monsoon season. The second study examines the presence and severity of spurious Gibbs-type numerical oscillations across the CMIP5 suite of climate models. The oscillations can appear as unrealistic spatial waves near discontinuities or sharp gradients in global model fields (e.g., orography) and have been a known problem for decades. Multiple methods of oscillation reduction exist; consequently, the oscillations are presumed small in modern climate models and hence are rarely addressed in recent literature. Here we quantify the oscillations in 13 variables from 48 global climate models along a Pacific ocean transect near the Andes. Results show that 48% of nonspectral models and 95% of spectral models have at least one variable with oscillation amplitude as large as, or greater than, atmospheric interannual variability. The third study is an in-depth assessment model simulations of 20th century monthly minimum and maximum surface air temperature over eight US regions, using mean state, trend, and variability bias metrics. Transparent model performance information is provided in the form of model rankings for each bias type. A wide range in model skill is at the regional scale, but no strong relationships are seen between any of the three bias types or between 20th century bias and 21st century projected change. Using our model rankings, two smaller ensembles of models with better performance over the southwestern U.S. are selected, but they result in negligible differences from the all-model ensemble in the average 21st century projected temperature change and model spread. In other words, models of varied quality (and complexity) are projecting very similar changes in temperature, implying that the models are simulating warming for different physical reasons. Despite this result, we suggest that models with smaller 20th century biases have a greater likelihood of being more physically realistic and therefore, more confidence can be placed in their 21st century projections as compared to projections from models that have demonstrably poor skill over the observational period. This type of analysis is essential for responsibly informing climate resilience efforts.

Tree-ring studies have demonstrated that conifer latewood measurements contain information on long-term North American monsoon (NAM) variability, a hydroclimatic feature of great importance to plants, animals, and human society in the US Southwest. This paper explores data-treatment options for developing latewood chronologies aimed at NAM reconstruction. Archived wood samples for five Douglas-fir (Pseudotsuga menziesii, Mirb. Franco) sites in southeastern Arizona are augmented with new collections. The combined dataset is analyzed along with time series of regionally averaged observed precipitation to quantify the strength of regional precipitation signal in latewood time series and to identify ways of increasing the signal strength. Analysis addresses the signal strength influences of including or excluding ‘‘false’’ latewood bands in the nominal ‘‘latewood’’ portion of the ring, the necessary adjustment of latewood width for statistical dependence on antecedent earlywood width, and tree age. Results suggest that adjusted latewood width chronologies from individual sites can explain around 30% of the variance of regional summer (July–August) precipitation—increasing to more than 50% with use of multiple chronologies. This assessment is fairly insensitive to the treatment of false latewood bands (in intra-annual width and 𝛿¹³C variables), and to whether latewood-width is adjusted for dependence on earlywood-width at the core or site level. Considerations for operational chronology development in future studies are (1) large tree-to-tree differences in moisture signal, (2) occasional nonlinearity in EW-LW dependence, and (3) extremely narrow and invariant latewood width in outer portions of some cores. A protocol for chronology development addressing these considerations is suggested.

Climate change is increasing the frequency and extent of high-severity disturbance, with potential to alter vegetation community composition and structure in environments sensitive to tipping points between alternative states. Shrub species display a range of characteristics that promote resistance and resilience to disturbance, and which yield differential post-disturbance outcomes. We investigated differences in shrub patch size and stem density in response to variations in fire severity, vegetation community, and post-disturbance reproductive strategies in Sky Island forested ecosystems in the southwestern United States. Patterns in shrub structure reflect the effects of fire severity as well as differences among species with alternate post-fire reproductive strategies. Increased fire severity correlates with larger patch sizes and greater stem densities; these patterns are observed across multiple fire events, indicating that disturbance legacies can persist for decades. High severity fire produces the largest shrub patches, and variance in shrub patch size increases with severity. High severity fire is likely to promote expansion of shrub species on the landscape, with implications for future community structure. Resprouting species have the greatest variability in patch structure, while seeding species show a strong response to disturbance: resprouting species dominateatlowdisturbanceseverities,andobligateseedersdominatehighseverityareas. Differential post-fire reproductive strategies are likely to generate distinct patterns of vegetation distribution following disturbance, with implications for community composition at various scales. Shrub species demonstrate flexible responses to wildfire disturbance severity that are reflected in shrub patch dynamics at small and intermediate scales.

abstract: Ponderosa pine forests are a dominant land cover type in semiarid montane areas. Water supplies in major rivers of the southwestern United States depend on ponderosa pine forests since these ecosystems: (1) receive a significant amount of rainfall and snowfall, (2) intercept precipitation and transpire water, and (3) indirectly influence runoff by impacting the infiltration rate. However, the hydrologic patterns in these ecosystems with strong seasonality are poorly understood. In this study, we used a distributed hydrologic model evaluated against field observations to improve our understandings on spatial controls of hydrologic patterns, appropriate model resolution to simulate ponderosa pine ecosystems and hydrologic responses in the context of contrasting winter to summer transitions. Our modeling effort is focused on the hydrologic responses during the North American Monsoon (NAM), winter and spring periods. In Chapter 2, we utilized a distributed model explore the spatial controls on simulated soil moisture and temporal evolution of these spatial controls as a function of seasonal wetness. Our findings indicate that vegetation and topographic curvature are spatial controls. Vegetation controlled patterns during dry summer period switch to fine-scale terrain curvature controlled patterns during persistently wet NAM period. Thus, a climatic threshold involving rainfall and weather conditions during the NAM is identified when high rainfall amount (such as 146 mm rain in August, 1997) activates lateral flux of soil moisture and frequent cloudy cover (such as 42% cloud cover during daytime of August, 1997) lowers evapotranspiration. In Chapter 3, we investigate the impacts of model coarsening on simulated soil moisture patterns during the NAM. Results indicate that model aggregation quickly eradicates curvature features and its spatial control on hydrologic patterns. A threshold resolution of ~10% of the original terrain is identified through analyses of homogeneity indices, correlation coefficients and spatial errors beyond which the fidelity of simulated soil moisture is no longer reliable. Based on spatial error analyses, we detected that the concave areas (~28% of hillslope) are very sensitive to model coarsening and root mean square error (RMSE) is higher than residual soil moisture content (~0.07 m3/m3 soil moisture) for concave areas. Thus, concave areas need to be sampled for capturing appropriate hillslope response for this hillslope. In Chapter 4, we investigate the impacts of contrasting winter to summer transitions on hillslope hydrologic responses. We use a distributed hydrologic model to generate a consistent set of high-resolution hydrologic estimates. Our model is evaluated against the snow depth, soil moisture and runoff observations over two water years yielding reliable spatial distributions during the winter to summer transitions. We find that a wet winter followed by a dry summer promotes evapotranspiration losses (spatial averaged ~193 mm spring ET and ~ 600 mm summer ET) that dry the soil and disconnect lateral fluxes in the forested hillslope, leading to soil moisture patterns resembling vegetation patches. Conversely, a dry winter prior to a wet summer results in soil moisture increases due to high rainfall and low ET during the spring (spatially averaged 78 mm ET and 232 mm rainfall) and summer period (spatially averaged 147 mm ET and 247 mm rainfall) which promote lateral connectivity and soil moisture patterns with the signature of terrain curvature. An opposing temporal switch between infiltration and saturation excess runoff is also identified. These contrasting responses indicate that the inverse relation has significant consequences on hillslope water availability and its spatial distribution with implications on other ecohydrological processes including vegetation phenology, groundwater recharge and geomorphic development. Results from this work have implications on the design of hillslope experiments, the resolution of hillslope scale models, and the prediction of hydrologic conditions in ponderosa pine ecosystems. In addition, our findings can be used to select future hillslope sites for detailed ecohydrological investigations. Further, the proposed methodology can be useful for predicting responses to climate and land cover changes that are anticipated for the southwestern United States. / Dissertation/Thesis / Ph.D. Geological Sciences 2012

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

Climate has historically been recognized as an influence on sediment flux and deposition. The North American Monsoon is suggested as the forcing mechanism of deltaic progradational events of the Rio Grande River delta. Interpretations of reflection seismic profiles reveal that eustatic rise in sea-level from the Last Glacial Maximum to present is accompanied by several regressional events of the Rio Grande delta 5.5, 9.5, and 11.5 ka BP. Much of the migration of depositional facies within a delta system is forced by hinterland tectonics and base-level rise and fall. However, we suggest that the movement of facies within the Rio Grande delta system represent climate forcing as the most dominant influence on sediment deposition during this short time period. While dominance of climate influence is possible, the sensitivity of an increase in monsoon precipitation and its effect on sediment flux has not yet been tested. We test monsoonal effects using relationships between sediment flux, river discharge, and precipitation. Heavy water management and withdrawal and complexity of precipitation timing and events within the region make the relationship between precipitation and sediment flux difficult to quantify using modern data sources. Therefore, it is necessary to numerically simulate stream discharge to test potential sensitivities of the system to monsoonal precipitation using a stream discharge model. Precipitation input into the stream discharge model is gathered from a suite of climate model simulation outputs. Suspended sediment flux is derived from the outputs of the flow models using empirically derived sediment rating curves. Results of sediment modeling show that increased precipitation during the monsoon months of July-September, 6 ka BP increased monthly suspended sediment flux by 79 percent. The suite of climate models does not include 9 or 11 ka BP, but we suggest the monsoon may have been stronger during this time based on greater received insolation at these times. This study also shows that duration and intensity of monsoonal precipitation events can more greatly affect stream discharge and sediment flux than increased precipitation with constant storm intensity.