The growth rings of eastern redcedar (Juniperus virginiana L.) often contain a high frequency of false intra-annual growth bands, which complicates the dendrochronology of this species. However, exactly dated false rings replicated among many trees can reflect major weather changes during the growing season. Sixty-one trees from two sites (Oklahoma and Kansas) were dated and used to compile replicated chronologies of false rings at both locations extending from AD 1700–2000. False-ring events during the modern instrumental era were compared with the daily weather data from nearby stations. Significant false-ring events occurred at both locations during years that experienced a dramatic late-growing season weather reversal, when an extended period of high temperatures and drought was followed by prolonged cool and wet conditions. Synoptic weather maps for these events indicate that all ten replicated false-ring events in the instrumental era occurred during the highly unseasonable penetration of a cold front into the region. However, none of the significant false-ring events occurred in the same year at both sites. These separate false-ring chronologies indicate that there may be phenological differences in the timing of radial growth in redcedar between Kansas and Oklahoma, and that the weather conditions responsible for false-ring formation often occur at the mesoscale and do not often impact central Kansas and northcentral Oklahoma simultaneously.

This work introduces diagnostic methods for land surface model (LSM) evaluation that enable developers to identify structural shortcomings in model parameterizations by evaluating model 'signatures' (characteristic temporal and spatial patterns of behavior) in feature, cost-function, and parameter spaces. The ensemble-based methods allow researchers to draw conclusions about hypotheses and model realism that are independent of parameter choice. I compare the performance and physical realism of three versions of Noah LSM (a benchmark standard version [STD], a dynamic-vegetation enhanced version [DV], and a groundwater-enabled one [GW]) in simulating high-frequency near-surface states and land-to-atmosphere fluxes in-situ and over a catchment at high-resolution in the U.S. Southern Great Plains, a transition zone between humid and arid climates. Only at more humid sites do the more conceptually realistic, hydrologically enhanced LSMs (DV and GW) ameliorate biases in the estimation of root-zone moisture change and evaporative fraction. Although the improved simulations support the hypothesis that groundwater and vegetation processes shape fluxes in transition zones, further assessment of the timing and partitioning of the energy and water cycles indicates improvements to the movement of water within the soil column are needed. Distributed STD and GW underestimate the contribution of baseflow and simulate too-flashy streamflow. This work challenges common practices and assumptions in LSM development and offers researchers more stringent model evaluation methods. I show that, because of equifinality, ad-hoc evaluation using single parameter sets provides insufficient information for choosing among competing parameterizations, for addressing hypotheses under uncertainty, or for guiding model development. Posterior distributions of physically meaningful parameters differ between models and sites, and relationships between parameters themselves change. 'Plug and play' of modules and partial calibration likely introduce error and should be re-examined. Even though LSMs are 'physically based,' model parameters are effective and scale-, site- and model-dependent. Parameters are not functions of soil or vegetation type alone: they likely depend in part on climate and cannot be assumed to be transferable between sites with similar physical characteristics. By helping bridge the gap between the model identification and model development, this research contributes to the continued improvement of our understanding and modeling of environmental processes. / text