No abstract

During June 2022 surface air temperatures across most of Europe were above the 1991-2020 average and daily maximum temperatures reached over 40 ºC over southern Europe (according to Copernicus.eu). Unusually high temperatures were also reached in Germany, where heat waves took place with over 35 ºC. In the Jülich Observatory for Cloud Evolution (JOYCE), these extreme temperature and humidity conditions were registered. JOYCE combines a rather unique set of ground-based remote sensing instruments that provide information about Boundary Layer thermal structure. The present investigation utilizes some of those measurements to diagnose total mean flux of heat and moisture within the Boundary Layer. In order to analyze the daily evolution of these fluxes during a heat wave, we utilize measurements of temperature and humidity from an Atmospheric Emitted Radiance Interferometer (AERI) and plot them in the mixing diagram approach, i.e.,  in an energy space (Lq versus , where L is the latent heat of vaporization and is the specific heat). Additionally, we quantify, in a 2D vector representation, the contributions of surface, advection and entrainment fluxes to the total mean flux. Estimates of horizontal temperature and humidity advection are obtained from measurements of the 30º elevation scan of a Microwave Radiometer (MWR) and from wind velocities measured by a Doppler Lidar. Additionally, surface flux measurements from the Integrated Carbon Observation System (ICOS) in a near by station in Selhausen are utilized to quantify the contribution of these surface fluxes in the mixing diagram. The total mean flux shows a daytime evolution with both sensible and latent heat components observed in days before the heat wave; whereas a high sensible heat flux dominates during the heat wave and the advective contribution becomes more important when the heat wave ends. We discuss the daily evolution of these fluxes, as well as the implementation of the mixing diagram approach for their study utilizing measured quantities. The present investigation can shed light on the Land-Atmosphere interaction and the closure of the surface energy and water budgets. Furthermore, understanding how the surface conditions can affect the atmospheric variables is valuable for a better characterization, and subsequent prediction, of extreme events such as heat waves in a warming climate.

The Atmospheric Boundary Layer (ABL) height is a key parameter in air quality research as well as for numerical simulations and forecasts. The identification of thermally stable layers, often with radiosondes, has been a common approach for estimating ABL height, though with limited temporal coverage. Remote sensing techniques offer essentially continuous measurements. Nevertheless, ABL height retrievals from different methods can vary greatly when compared, which is particularly notable for topographically complex terrains, such as that surrounding Mexico City. This study, employing one year of data in Mexico City, reveals that the daytime convective boundary layer height (retrieved from Doppler lidar data) is typically lower than the aerosol layer height (retrieved from ceilometer data). Although both estimated heights evolved diurnally, the more elevated aerosol layer decays more slowly, suggesting that the mechanisms that elevate aerosols are not limited to convective motions. Additionally, both diurnal and seasonal variability are investigated, comparing remotely sensed-retrieved heights with thermally stable layers estimated from radiosonde data. Multiple stable layers often develop, those at higher levels have similar values to the ceilometer-retrieved heights, while stable layers at lower heights are similar to Doppler lidar height retrievals. The present research constitutes the first detailed analysis of ceilometer backscatter and Doppler lidar thresholding methods for estimating ABL height over Mexico City, and our results illustrate the complexity of mixing mechanisms on the ABL in this region of complex orography.

Experimental lock-release gravity currents are investigated as they propagate downslope over a synthetic varying topography. We emulate and investigate the dynamics of thermally driven winds that propagate downslope while interacting with the roughness of a topographic surface. The mixing processes between the gravity currents and their surroundings are studied with Particle Image Velocimetry (PIV) and entrainment is quantified. The magnitude of the entrainment coefficient is shown to increase as the roughness of the slope increases. Shadowgraph visualizations qualitatively reproduce this behavior. Finally, pressure fields are estimated from velocity fields and the arrival of gravity currents is shown to be detected in pressure time series. This last result may be useful to detect atmospheric gravity currents using only surface pressure measurements.