Abstract

Abstract. The rotational Raman lidar (RRL) of the University of Hohenheim (UHOH) measures atmospheric temperature profiles with high resolution (10 s, 109 m). The data contain low-noise errors even in daytime due to the use of strong UV laser light (355 nm, 10 W, 50 Hz) and a very efficient interference-filter-based polychromator. In this paper, the first profiling of the second- to fourth-order moments of turbulent temperature fluctuations is presented. Furthermore, skewness profiles and kurtosis profiles in the convective planetary boundary layer (CBL) including the interfacial layer (IL) are discussed. The results demonstrate that the UHOH RRL resolves the vertical structure of these moments. The data set which is used for this case study was collected in western Germany (50°53'50.56'' N, 6°27'50.39'' E; 110 m a.s.l.) on 24 April 2013 during the Intensive Observations Period (IOP) 6 of the HD(CP)2 (High-Definition Clouds and Precipitation for advancing Climate Prediction) Observational Prototype Experiment (HOPE). We used the data between 11:00 and 12:00 UTC corresponding to 1 h around local noon (the highest position of the Sun was at 11:33 UTC). First, we investigated profiles of the total noise error of the temperature measurements and compared them with estimates of the temperature measurement uncertainty due to shot noise derived with Poisson statistics. The comparison confirms that the major contribution to the total statistical uncertainty of the temperature measurements originates from shot noise. The total statistical uncertainty of a 20 min temperature measurement is lower than 0.1 K up to 1050 m a.g.l. (above ground level) at noontime; even for single 10 s temperature profiles, it is smaller than 1 K up to 1020 m a.g.l. Autocovariance and spectral analyses of the atmospheric temperature fluctuations confirm that a temporal resolution of 10 s was sufficient to resolve the turbulence down to the inertial subrange. This is also indicated by the integral scale of the temperature fluctuations which had a mean value of about 80 s in the CBL with a tendency to decrease to smaller values towards the CBL top. Analyses of profiles of the second-, third-, and fourth-order moments show that all moments had peak values in the IL around the mean top of the CBL which was located at 1230 m a.g.l. The maximum of the variance profile in the IL was 0.39 K2 with 0.07 and 0.11 K2 for the sampling error and noise error, respectively. The third-order moment (TOM) was not significantly different from zero in the CBL but showed a negative peak in the IL with a minimum of −0.93 K3 and values of 0.05 and 0.16 K3 for the sampling and noise errors, respectively. The fourth-order moment (FOM) and kurtosis values throughout the CBL were not significantly different to those of a Gaussian distribution. Both showed also maxima in the IL but these were not statistically significant taking the measurement uncertainties into account. We conclude that these measurements permit the validation of large eddy simulation results and the direct investigation of turbulence parameterizations with respect to temperature.

Highlights

  • Temperature fluctuations and their vertical organization inherently govern the energy budget in the convective planetary boundary layer (CBL) by determining the vertical heat fluxPublished by Copernicus Publications on behalf of the European Geosciences Union.A

  • We found that we can interrupt the iteration procedure in the first step because all resulting profiles are within the range of the noise error bars in this case regardless of whether we use 10, 15, or 20 fit lags

  • To the best of our knowledge, the first profile of the temperature variance of the atmosphere Ta (z) 2 measured with a lidar system is shown in Fig. 9; the profile starts at about 0.3 zi and covers the whole CBL

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Summary

Introduction

Temperature fluctuations and their vertical organization inherently govern the energy budget in the convective planetary boundary layer (CBL) by determining the vertical heat flux. To the best of our knowledge, there are no previous observations based on a remote-sensing technique suitable for this important task, i.e., resolving temperature fluctuations in high resolution and covering simultaneously the CBL up to the interfacial layer (IL). Kadygrov et al (2003) published a study on turbulent temperature fluctuations based on passive remote-sensing techniques. New insights in CBL turbulence were provided by studies based on active remote sensing with different types of radar and lidar systems. A. Behrendt et al.: Profiles of second- to fourth-order moments of turbulent temperature fluctuations tioned during this study at 50◦53 50.56 N, 6◦27 50.39 E, 110 m a.s.l. near the village of Hambach in western Germany where it performed measurements between 1 April and 31 May 2013.

Setup of the UHOH RRL
Data set
Turbulent temperature fluctuations
Noise errors
Integral scale
Temperature variance
Third-order moment and skewness
Fourth-order moment and kurtosis
Conclusions
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