Thermal Submesoscale Motions in the Nocturnal Stable Boundary Layer. Part 1: Detection and Mean Statistics

Abstract

Submesoscale motions within the stable boundary layer were detected during the Shallow Cold Pool Experiment conducted in the Colorado plains, Colorado, U.S.A. in 2012. The submesoscale motion consisted of two air layers creating a well-defined front with a sharp temperature gradient, and further-on referred to as a thermal submesofront (TSF). The semi-stationary TSFs and their advective velocities are detected and determined by the fibre-optic distributed-sensing (FODS) technique. An objective detection algorithm utilizing FODS measurements is able to detect the TSF boundary, which enables a detailed investigation of its spatio–temporal statistics. The novel approach in data processing is to conditionally average any parameter depending on the distance between a TSF boundary and the measurement location. By doing this, a spatially-distributed feature like TSFs can be characterized by point observations and processes at the TSF boundary can be investigated. At the TSF boundary, the air layers converge, creating an updraft, strong static stability, and vigorous mixing. Further, the TSF advective velocity of TSFs is an order of magnitude lower than the mean wind speed. Despite being gentle, the topography plays an important role in TSF formation. Details on generating mechanisms and implications of TSFs on the stable boundary layer are discussed in Part 2.

Distributed sensing of wind direction using fiber-optic cables

“…After calibrating the fiber temperatures, the artifact-free regions of the fiber cross are identified while regions potentially contaminated by artifacts from fiber holders (Pfister et al 2019) are discarded. This results in an 8-m-long test section that is not influenced by any edge effects for each of the branches (Fig.…”

“…These exchange processes typically are statistically parameterized using similarity theories (Holtslag and De Bruin 1988). Many of the fundamental assumptions made by similarity theories, however, e.g., spatial homogeneity and Taylor's hypothesis of frozen turbulence (Taylor 1938), are not fulfilled in the surface layer, particularly during nocturnal weak-wind situations and during the occurrence of submesoscale processes (Mahrt et al 2009;Thomas 2011;Sun et al 2012Sun et al , 2015Sun et al , 2020Pfister et al 2021b). The inapplicability of these assumptions hampers climate and weather models since it leads to incorrect predictions of turbulent fluxes at the land surface (Holtslag and De Bruin 1988;Holtslag et al 2013;Davy and Esau 2014;Lapo et al 2019).…”

“…The inapplicability of these assumptions hampers climate and weather models since it leads to incorrect predictions of turbulent fluxes at the land surface (Holtslag and De Bruin 1988;Holtslag et al 2013;Davy and Esau 2014;Lapo et al 2019). Due to the invalidity of Taylor's hypothesis and the local character of turbulent quantities, spatially and temporally explicit measurements are needed in order to understand the nature of submesoscale processes, building toward the goal of improving model parameterizations (Mahrt et al 2009;Acevedo et al 2014;Thomas 2011;Pfister et al 2021a;Mahrt 2020). Spatially explicit measurements are also useful in other conditions than during a stable weakwind boundary layer, since internal boundary layers and heterogeneous turbulence can occur during strong wind conditions and in the convective boundary layer in the presence of surface heterogeneities (Mahrt and Vickers 2005;Mott et al 2017;Fritz et al 2021).…”

“…For the observation of wind speeds through FODS, an active approach is used and the fiber is utilized as a spatially resolved hotwire anemometer (van Ramshorst et al 2020;Sayde et al 2015). With this approach, temperature and wind speed observations can be obtained at temporal resolutions down to seconds and on spatial scales from tens of centimeters up to kilometers (Pfister et al 2019). As such, FODS is capable of monitoring turbulent and submesoscale events.…”

Toward quantifying turbulent vertical airflow and sensible heat flux in tall forest canopies using fiber-optic distributed temperature sensing

“…This technique measures the temperature and its location along a fiber-optic cable at a time resolution of a few seconds and spatial resolution of tens of centimeters up to 20 kilometers in total length. It is capable of observing atmospheric flows under physically poorly understood sub-meso motions (Pfister et al, 2021;C. K. Thomas et al, 2012).…”