Assessing Soil and Potential Air Temperature Coupling Using PALM-4U: Implications for Idealized Scenarios

Underground heat extremes amplified by e.g., underground infrastructure or badly adjusted geothermal systems have long been discussed in geosciences. However, there is little emphasis on the exchange between these subsurface heat extremes and the atmosphere. To address the issue, this study investigates the impact of varying soil temperatures on potential air temperatures in an idealized domain using the turbulence and building resolving large eddy simulation urban micro-climate model PALM-4U. This involves two steps: first we test if and how idealized domains can be simulated, second the coupling between surface and subsurface energy fluxes or rather temperatures in air and soil are in focus. We develop several scenarios, distinguishing between cyclic or Dirichlet/radiation boundary conditions along the x-axis, between summer and winter, as well as between various land cover types. Our results demonstrate that cyclic boundary conditions induce modifications of the potential air temperatures due to changes in the soil temperature. The magnitude of the impact varies with respect to the tested land covers, which primarily affect absolute temperatures. Daytime and season have a larger influence on the magnitude of the modifications. A 5 K increase in subsurface temperatures at 2 m depth results in a maximum of a 0.38 K increase for near surface potential air temperatures in winter between 09:00 and 10:00 local time after three days of simulation. When soil temperatures are decreased, we find predominantly inverse patterns. The least influence is found during summer at 09:00 local time where the elevated soil temperatures increase potential air temperatures by only 0.02 K over short- and tall grass, and 0.18 K over bare soil. When using Dirichlet/radiation boundary conditions, the atmosphere cannot develop freely and changing soil temperatures do not impact potential air temperatures. These results help to enhance our understanding of the coupling between soil- and atmospheric temperatures and also provide recommendations for the simulability of idealized but reality-oriented scenarios in PALM-4U. It is one of the first studies that demonstrates that heat and cold sources in the soil can affect atmospheric parameters

Urban Atmospheric Boundary-Layer Structure in Complex Topography: An Empirical 3D Case Study for Stuttgart, Germany

Investigation of the atmospheric boundary-layer structure in urban areas can be challenged by landscape complexity and the heterogenous conditions this instills. Stuttgart, Germany, is a city situated in a bowl-shaped basin and troubled by the accumulation of pollutants during weak-wind conditions. The center of Stuttgart is surrounded by steep slopes up to 250m above the basin floor, except for an opening to the northeast that allows runoff towards the Neckar river. Urban planning and regulation of air quality require advanced monitoring and forecasting skills, which in turn require knowledge about the structure of the atmospheric boundary layer (ABL), down to the surface. Three dimensional observations of the ABL were collected in the City Centre of Stuttgart in 2017. A laser ceilometer and a concerted network of Doppler lidar systems were deployed on roof-tops, providing continuous observations of the cloud base, the mixing-layer height and the three-dimensional wind field. The impact of weak-wind conditions, the presence of shear layers, properties of convective cells and the impact of nocturnal low-levels jets were studied for representative days in winter and summer. The observations revealed the development of distinctive layers with high directional deviation from the flow aloft, reoccurring as a dominant diurnal pattern. Our findings highlight the influence of topography and surface heterogeneity on the structure of the ABL and development of flow regimes near the surface that are relevant for the transport of heat and pollutants

The Validation and Assessment of Machine Learning: A Game of Prediction from High-Dimensional Data

In applied statistics, tools from machine learning are popular for analyzing complex and high-dimensional data. However, few theoretical results are available that could guide to the appropriate machine learning tool in a new application. Initial development of an overall strategy thus often implies that multiple methods are tested and compared on the same set of data. This is particularly difficult in situations that are prone to over-fitting where the number of subjects is low compared to the number of potential predictors. The article presents a game which provides some grounds for conducting a fair model comparison. Each player selects a modeling strategy for predicting individual response from potential predictors. A strictly proper scoring rule, bootstrap cross-validation, and a set of rules are used to make the results obtained with different strategies comparable. To illustrate the ideas, the game is applied to data from the Nugenob Study where the aim is to predict the fat oxidation capacity based on conventional factors and high-dimensional metabolomics data. Three players have chosen to use support vector machines, LASSO, and random forests, respectively

Urban atmospheric boundary-layer structure in complex topography: an empirical 3D case study for Stuttgart, Germany

Investigation of the atmospheric boundary-layer structure in urban areas can be challenged by landscape complexity and the heterogenous conditions this instills. Stuttgart, Germany, is a city situated in a bowl-shaped basin and troubled by the accumulation of pollutants during weak-wind conditions. The center of Stuttgart is surrounded by steep slopes up to 250 m above the basin floor, except for an opening to the northeast that allows runoff towards the Neckar river. Urban planning and regulation of air quality require advanced monitoring and forecasting skills, which in turn require knowledge about the structure of the atmospheric boundary layer (ABL), down to the surface. Three-dimensional observations of the ABL were collected in the City Centre of Stuttgart in 2017. A laser ceilometer and a concerted network of Doppler lidar systems were deployed on roof-tops, providing continuous observations of the cloud base, the mixing-layer height and the three-dimensional wind field. The impact of weak-wind conditions, the presence of shear layers, properties of convective cells and the impact of nocturnal low-levels jets were studied for representative days in winter and summer. The observations revealed the development of distinctive layers with high directional deviation from the flow aloft, reoccurring as a dominant diurnal pattern. Our findings highlight the influence of topography and surface heterogeneity on the structure of the ABL and development of flow regimes near the surface that are relevant for the transport of heat and pollutants