2019 journal article
Classifying the nocturnal atmospheric boundary layer into temperature and flow regimes
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 145(721), 1515–1534.
author keywords: classification; distributed temperature sensing; nocturnal near-surface temperatures; radiative forcing; stable boundary layer; topography; Taylor's hypothesis
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(OpenAlex)
11. Sustainable Cities and Communities
(Web of Science)
13. Climate Action
(Web of Science)
Source: Web Of Science
Added: July 22, 2019
We propose a classification scheme for nocturnal atmospheric boundary layers and apply it to investigate the spatio‐temporal structure of air temperature and wind speed in a shallow valley during the Shallow Cold Pool Experiment. This field campaign was the first to collect spatially continuous temperature and wind information at high resolution (1 s, 0.25 m) using the distributed temperature sensing technique across a 220 m long transect at three heights (0.5, 1.0, 2.0 m). The night‐time classification scheme was motivated by a surface energy balance and used a combination of static stability, wind regime and longwave radiative forcing as quantities to determine physically meaningful boundary‐layer regimes. Out of all potential combinations of these three quantities, 14 night‐time classes contained observations, of which we selected three for detailed analysis and comparison.The three classes represent a transition from mechanical to radiative forcing. The first night class represents conditions with strong dynamic forcing caused by locally induced lee turbulence dominating near‐surface temperatures across the shallow valley. The second night class was a concurrence of enhanced dynamic mixing due to significant winds at the valley shoulders and cold‐air pooling at the bottom of the shallow valley as a result of strong radiative cooling. The third night class was characteristic of weak winds eliminating the impact of mechanical mixing but emphasizing the formation and pooling of cold air at the valley bottom.The proposed night‐time classification scheme was found to sort the experimental data into physically meaningful regimes of surface flow and transport. It is suitable to stratify short‐ and long‐term experimental data for ensemble averaging and to identify case studies.