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The flux Richardson number R, (also known as the mixing efficiency) for the stably stratified atmospheric boundary layer is investigated as a function of the gradient Richardson number Ri(g), using data taken during two field studies: the Vertical Transport and Mixing Experiment (VTMX) in Salt Lake City, Utah (October 2000), and a long-term rural field data set from Technical Area 6 (TA-6) at Los Alamos National Laboratory, New Mexico. The results show the existence of a maximum R(f) (0.4-0.5) at a gradient Richardson number of approximately unity. These large-Reynolds-number results agree well with recent laboratory stratified shear layer measurements, but are at odds with some commonly used R(f) parameterizations, particularly under high-Ri(g) conditions. The observed variations in buoyancy flux and turbulent kinetic energy production are consistent with the concept of global intermittency of the atmospheric stable boundary layer

All over the world, the rapid urbanization process is challenging the sustainable development of our cities. In 2015, the United Nation highlighted in Goal 11 of the SDGs (Sustainable Development Goals) the importance to "Make cities inclusive, safe, resilient and sustainable". In order to monitor progress regarding SDG 11, there is a need for proper indicators, representing different aspects of city conditions, obviously including the Land Cover (LC) changes and the urban climate with its most distinct feature, the Urban Heat Island (UHI). One of the aspects of UHI is the Surface Urban Heat Island (SUHI), which has been investigated through airborne and satellite remote sensing over many years. The purpose of this work is to show the present potential of Google Earth Engine (GEE) to process the huge and continuously increasing free satellite Earth Observation (EO) Big Data for long-term and wide spatio-temporal monitoring of SUHI and its connection with LC changes. A large-scale spatio-temporal procedure was implemented under GEE, also benefiting from the already established Climate Engine (CE) tool to extract the Land Surface Temperature (LST) from Landsat imagery and the simple indicator Detrended Rate Matrix was introduced to globally represent the net effect of LC changes on SUHI. The implemented procedure was successfully applied to six metropolitan areas in the U.S., and a general increasing of SUHI due to urban growth was clearly highlighted. As a matter of fact, GEE indeed allowed us to process more than 6000 Landsat images acquired over the period 1992-2011, performing a long-term and wide spatio-temporal study on SUHI vs. LC change monitoring. The present feasibility of the proposed procedure and the encouraging obtained results, although preliminary and requiring further investigations (calibration problems related to LST determination from Landsat imagery were evidenced), pave the way for a possible global service on SUHI monitoring, able to supply valuable indications to address an increasingly sustainable urban planning of our cities.

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The representation of spatial wind distribution is recognized as a serious difficulty when modeling the hydrodynamics of lakes surrounded by a complex topography. To address this issue, we propose to force a 3‐D lake model with the wind field simulated by a high‐resolution atmospheric model, considering as a case study a 61 km2 prealpine lake surrounded by mountain ranges that reach 1800 m above the lake's surface, where a comprehensive data set was available in the stratified season. The improved distributed description of the wind stress over the lake surface led to a significant enhancement in the representation of the main basin‐scale internal wave motions, and hence provided a reference solution to test the use of simplified approaches. Moreover, the analysis of the power exerted by the computed wind field enabled us to identify measuring stations that provide suitable wind data to be applied uniformly on the lake surface in long‐term simulations. Accordingly, the proposed methodology can contribute to reducing the uncertainties associated with the definition of wind forcing for modeling purposes and can provide a rational criterion for installing representative measurement locations in prealpine lakes.