Regional climate modeling using convection‐permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large‐scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

Interactions between surface and ground water are a key component of the hydrologic budget on the watershed scale. Models that honor these interactions are commonly based on the conductance concept that presumes a distinct interface at the land surface, separating the surface from the subsurface domain. These types of models link the subsurface and surface domains via an exchange flux that depends upon the magnitude and direction of the hydraulic gradient across the interface and a proportionality constant (a measure of the hydraulic connectivity). Because experimental evidence of such a distinct interface is often lacking in field systems, there is a need for a more general coupled modeling approach.A more general coupled model is presented that incorporates a new two-dimensional overland flow simulator into the parallel three-dimensional variable saturated subsurface flow code ParFlow. In ParFlow, the overland flow simulator takes the form of an upper boundary condition and is, thus, fully integrated without relying on the conductance concept. Another important advantage of this approach is the efficient parallelism incorporated into ParFlow, which is efficiently exploited by the overland flow simulator.Several verification and simulation examples are presented that focus on the two main processes of runoff production : excess infiltration and saturation. The model is shown to reproduce an analytical solution for overland flow and compares favorably to other commonly used hydrologic models. The influence of heterogeneity of the shallow subsurface on overland flow is also examined. The results show the uncertainty in overland flow predictions due to subsurface heterogeneity and demonstrate the usefulness of our approach. Both the overland flow component and the coupled model are evaluated in a parallel scaling study and show to be efficient.

[1] The influence of groundwater dynamics on the energy balance at the land surface is studied using an integrated, distributed watershed modeling platform. This model includes the mass and energy balance at the land surface; three-dimensional variably saturated subsurface flow; explicit representation of the water table; and overland flow. The model is applied to the Little Washita watershed in Central Oklahoma, USA and compared to runoff, soil moisture and energy flux observations. The connection between groundwater dynamics and the land surface energy balance is studied using a variety of conventional and spatial statistical measures. For a number of energy variables a strong interconnection is demonstrated with water table depth. This connection varies seasonally and spatially depending on the spatial composition of water table depth. A theoretical critical water table depth range is presented where a strong sensitivity between groundwater and land-surface processes may be observed. For this particular watershed, a critical depth range is established between 1 and 5 m in which the land surface energy budget is most sensitive to groundwater storage. Finally, concrete recommendations are put forth to characterize this interconnection in the field.Citation: Kollet, S. J., and R. M. Maxwell (2008), Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model, Water Resour. Res., 44, W02402,

The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.