Abstract

Abstract. The mixing layer height (MLH) is a key parameter for boundary layer studies, including meteorology, air quality, and climate. MLH estimates are inferred from in situ radiosonde measurements or remote sensing observations from instruments like lidar, wind profiling radar, or sodar. Methods used to estimate MLH from radiosonde profiles are also used with atmospheric temperature and humidity profiles retrieved by microwave radiometers (MWR). This paper proposes an alternative approach to estimate MLH from MWR data, based on direct observations (brightness temperatures, Tb) instead of retrieved profiles. To our knowledge, MLH estimates directly from Tb observations have never been attempted before. The method consists of a multivariate linear regression trained with an a priori set of collocated MWR Tb observations (multifrequency and multi-angle) and MLH estimates from a state-of-the-art lidar system. The proposed method was applied to a 7-month data set collected at a typical midlatitude site. Results show that the method is able to follow both the diurnal cycle and the day-to-day variability as suggested by the lidar measurements, and also it can detect low MLH values that are below the full overlap limit (~200 m) of the lidar system used. Statistics of the comparison between MWR- and reference lidar-based MLH retrievals show mean difference within 10 m, root mean square within 340 m, and correlation coefficient higher than 0.77. Monthly mean analysis for daytime MLH from MWR, lidar, and radiosonde shows consistent seasonal variability, peaking at ~1200–1400 m in June and decreasing down to ~600 m in October. Conversely, nighttime monthly mean MLH from all methods are within 300–500 m without any significant seasonal variability. The proposed method provides results that are more consistent with radiosonde estimates than MLH estimates from MWR-retrieved profiles. MLH monthly mean values agree well within 1 standard deviation with the bulk Richardson number method applied at radiosonde profiles at 11:00 and 23:00 UTC. The method described herewith operates continuously and is expected to work with analogous performances for the entire diurnal cycle, except during considerable precipitation, demonstrating new potential for atmospheric observation by ground-based microwave radiometry.

Highlights

  • The atmosphere boundary layer is characterized by turbulent fluctuations that induce mixing of aerosol particles and other trace gases and govern vertical distribution of thermodynamic variables

  • It is important to keep in mind that lidar and microwave radiometers (MWR) rely on different aspec2t6s of the boundary layer to estimate mixing layer height (MLH), the first being based on aerosol distribution while the second on thermodynamical properties

  • Discrepancies are evident, especially at low MLH values, where the MWR-based estimates go often lower than the corresponding lidar-based estimate. This behavior is consistent with the results in Wang et al (2012), which conclude that lidar data under weak convection conditions reveal higher MLH values than those estimated from MWR profiles

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Summary

Introduction

The atmosphere boundary layer is characterized by turbulent fluctuations that induce mixing of aerosol particles and other trace gases and govern vertical distribution of thermodynamic variables. We adopt the MLH definition of Seibert et al (2000), as “the height of the layer adjacent to the ground over which pollutants emitted within this layer or entrained into it become vertically dispersed by convection or mechanical turbulence”. This definition applies both for daytime, where the MLH is the top of a well-mixed layer, and for nighttime, where the MLH is the top of the stable layer in which surface-emitted pollutants are mixed through intermittent turbulence

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