A quantitative comparison between acoustic sounder returns and the direct measurement of atmospheric temperature fluctuations

1976 ◽  
Vol 10 (2) ◽  
pp. 137-147 ◽  
Author(s):  
D. N. Asimakopoulos ◽  
R. S. Cole ◽  
S. J. Caughey ◽  
B. A. Crease
Keyword(s):  
Direct Measurement ◽  
Temperature Fluctuations ◽  
Atmospheric Temperature ◽  
Quantitative Comparison

scholarly journals Arctic sea-ice variability is primarily driven by atmospheric temperature fluctuations

2019 ◽  
Vol 12 (6) ◽  
pp. 430-434 ◽  
Author(s):  
Dirk Olonscheck ◽  
Thorsten Mauritsen ◽  
Dirk Notz
Keyword(s):  
Sea Ice ◽  
Temperature Fluctuations ◽  
Atmospheric Temperature ◽  
Arctic Sea Ice ◽  
Arctic Sea

scholarly journals Quantitative comparison of electron temperature fluctuations to nonlinear gyrokinetic simulations in C-Mod Ohmic L-mode discharges

2016 ◽  
Vol 23 (4) ◽  
pp. 042303 ◽  
Author(s):  
C. Sung ◽  
A. E. White ◽  
D. R. Mikkelsen ◽  
M. Greenwald ◽  
C. Holland ◽  
...  
Keyword(s):  
Electron Temperature ◽  
Temperature Fluctuations ◽  
Quantitative Comparison ◽  
Gyrokinetic Simulations

scholarly journals Profiles of second- to fourth-order moments of turbulent temperature fluctuations in the convective boundary layer: first measurements with rotational Raman lidar

2015 ◽  
Vol 15 (10) ◽  
pp. 5485-5500 ◽  
Author(s):  
A. Behrendt ◽  
V. Wulfmeyer ◽  
E. Hammann ◽  
S. K. Muppa ◽  
S. Pal
Keyword(s):  
Boundary Layer ◽  
Fourth Order ◽  
Shot Noise ◽  
Temperature Fluctuations ◽  
Atmospheric Temperature ◽  
Order Moment ◽  
Statistical Uncertainty ◽  
Temperature Profiles ◽  
Raman Lidar ◽  
Noise Error

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.

The decay of radar echoes from meteors with particular reference to their use in the determination of temperature fluctuations near the mesopause

1995 ◽  
Vol 13 (10) ◽  
pp. 1104-1106 ◽  
Author(s):  
W. Jones
Keyword(s):  
Diffusion Coefficient ◽  
Kinetic Theory ◽  
Decay Time ◽  
Temperature Fluctuations ◽  
Atmospheric Temperature ◽  
Initial Distribution ◽  
Correct Result ◽  
Radar Echoes ◽  
Decay Times ◽  
Radar Echo

Abstract. The rate of decay of a radar echo from an ionised meteor train will be governed by the diffusion coefficient of the plasma and this in turn will depend on the temperature. Very recently the temperature fluctuations near the mesopause have been monitored by this means, by the recording of the decay times of underdense trains. The usual derivation of the precise expression relating the underdense echo decay time to the temperature contains two important assumptions, (i) that the train is created with a Gaussian ionisation profile, and (ii) that kinetic theory may be applied to calculate the diffusion coefficient. We investigate the effect of these assumptions, showing that the first assumption is unnecessary, an underdense backscatter echo decaying exponentially with a decay time equal to λ2/(32π2D), where λ is the wavelength and D the diffusion coefficient, independently of the initial distribution. However, the second assumption is shown to be incorrect, and whereas according to kinetic theory D∝T1/2/ρ, where T and ρ are the atmospheric temperature and density, the correct result is D∝Tρ. This leads to an appreciable correction to the results for the temperature fluctuations.

scholarly journals Profiles of second- to third-order moments of turbulent temperature fluctuations in the convective boundary layer: first measurements with Rotational Raman Lidar

2014 ◽  
Vol 14 (21) ◽  
pp. 29019-29055 ◽  
Author(s):  
A. Behrendt ◽  
V. Wulfmeyer ◽  
E. Hammann ◽  
S. K. Muppa ◽  
S. Pal
Keyword(s):  
Boundary Layer ◽  
Temperature Measurement ◽  
Convective Boundary Layer ◽  
Temperature Fluctuations ◽  
Atmospheric Temperature ◽  
Order Moment ◽  
Temperature Profiles ◽  
Raman Lidar ◽  
Third Order ◽  
Convective Boundary

Abstract. The rotational Raman lidar of the University of Hohenheim (UHOH) measures atmospheric temperature profiles during daytime 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, we present the first profiling of the second- to forth-order moments of turbulent temperature fluctuations as well as of skewness and kurtosis in the convective boundary layer (CBL) including the interfacial layer (IL). 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.) within one hour around local noon on 24 April 2013 during the Intensive Observations Period (IOP) 6 of the HD(CP)2 Observational Prototype Experiment (HOPE), which is embedded in the German project HD(CP)2 (High-Definition Clouds and Precipitation for advancing Climate Prediction). First, we investigated profiles of the noise variance and compared it with estimates of the statistical temperature measurement uncertainty Δ T based on Poisson statistics. The agreement confirms that photon count numbers obtained from extrapolated analog signal intensities provide a lower estimate of the statistical errors. The total statistical uncertainty of a 20 min temperature measurement is lower than 0.1 K up to 1050 m a.g.l. at noontime; even for single 10 s temperature profiles, it is smaller than 1 K up to 1000 m a.g.l.. Then we confirmed by autocovariance and spectral analyses of the atmospheric temperature fluctuations that a temporal resolution of 10 s was sufficient to resolve the turbulence down to the inertial subrange. This is also indicated by the profile of the integral scale of the temperature fluctuations, which was in the range of 40 to 120 s in the CBL. Analyzing then profiles of the second-, third-, and forth-order moments, we found the largest values of all moments 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 0.40 K2 with 0.06 and 0.08 K2 for the sampling error and noise error, respectively. The third-order moment was not significantly different from zero inside the CBL but showed a negative peak in the IL with a minimum of −0.72 K3 and values of 0.06 and 0.14 K3 for the sampling and noise errors, respectively. The forth-order moment and kurtosis values throughout the CBL were quasi-normal.

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