Combined vertical-velocity observations with Doppler lidar, cloud radar and wind profiler

Bühl, Johannes; Leinweber, Ronny; Görsdorf, Ulrich; Radenz, Martin; Ansmann, Albert; Lehmann, Volker

doi:10.5194/amt-8-3527-2015

Cited by 24 publications

(22 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As mentioned, measurements of vertical movements (updrafts, downdrafts, gravity waves) must be an essential part of field observations because vertical motions control all cloud processes (Twomey, 1959;Ghan et al, 1993Ghan et al, , 1997Ghan et al, , 2011Morales and Nenes, 2010). New techniques as well as new combinations of existing techniques and tools such as presented by Bühl et al (2015) need to be introduced to improve our ability to study ACI in the necessary detail and to provide in this way fundamental, reliable information for the improvement of cloud microphysics parameterization schemes in cloud-resolving models.…”

Section: Introductionmentioning

confidence: 99%

Strong aerosol–cloud interaction in altocumulus during updraft periods: lidar observations over central Europe

et al. 2015

Self Cite

View full text Add to dashboard Cite

Abstract. For the first time, a liquid-water cloud study of the aerosol-cloud-dynamics relationship, solely based on lidar, was conducted. Twenty-nine cases of pure liquid-water altocumulus layers were observed with a novel dual-field-ofview Raman lidar over the polluted central European site of Leipzig, Germany, between September 2010 and September 2012. By means of the novel Raman lidar technique, cloud properties such as the droplet effective radius and cloud droplet number concentration (CDNC) in the lower part of altocumulus layers are obtained. The conventional aerosol Raman lidar technique provides the aerosol extinction coefficient (used as aerosol proxy) below cloud base. A collocated Doppler lidar measures the vertical velocity at cloud base and thus updraft and downdraft occurrence. Here, we present the key results of our statistical analysis of the 2010-2012 observations. Besides a clear aerosol effect on cloud droplet number concentration in the lower part of the altocumulus layers during updraft periods, turbulent mixing and entrainment of dry air is assumed to be the main reason for the found weak correlation between aerosol proxy and CDNC higher up in the cloud. The corresponding aerosol-cloud interaction parameter based on changes in cloud droplet number concentration with aerosol loading was found to be close to 0.8 at 30-70 m above cloud base during updraft periods and below 0.4 when ignoring vertical-wind information in the analysis. Our findings are extensively compared with literature values and agree well with airborne observations.

show abstract

Section: Introductionmentioning

confidence: 99%

Strong aerosol–cloud interaction in altocumulus during updraft periods: lidar observations over central Europe

et al. 2015

Self Cite

View full text Add to dashboard Cite

show abstract

“…Our multivariate GRF formulation provides a consistent formulation of the covariance structure for both the potential and the horizontal wind components. A stochastic formulation of the potentials may also be relevant for the assimilation of measurements of the vertical velocity (Bühl et al 2015), which provide proxies for the horizontal divergence of the field. Our covariance function represents the divergence within a stochastic model, which is needed to assimilate the observations.…”

Section: Discussionmentioning

confidence: 99%

A Matérn-Based Multivariate Gaussian Random Process for a Consistent Model of the Horizontal Wind Components and Related Variables

Hewer

Friederichs

Hense

et al. 2017

Journal of the Atmospheric Sciences

View full text Add to dashboard Cite

The integration of physical relationships into stochastic models is of major interest, for example, in data assimilation. Here, a multivariate Gaussian random field formulation is introduced that represents the differential relations of the two-dimensional wind field and related variables such as the streamfunction, velocity potential, vorticity, and divergence. The covariance model is based on a flexible bivariate Matérn covariance function for the streamfunction and velocity potential. It allows for different variances in the potentials, nonzero correlations between them, anisotropy, and a flexible smoothness parameter. The joint covariance function of the related variables is derived analytically. Further, it is shown that a consistent model with nonzero correlations between the potentials and positive definite covariance function is possible. The statistical model is fitted to forecasts of the horizontal wind fields of a mesoscale numerical weather prediction system. Parameter uncertainty is assessed by a parametric bootstrap method. The estimates reveal only physically negligible correlations between the potentials.

show abstract

“…The technical parameters of cloud radar and RWP are given in Table 1. The measurements were performed between June and September 2015 in the framework of the COL-RAWI campaign (combined observations with lidar, radar and wind profiler; Bühl et al, 2015). Figure 3 shows the measurements of both systems for an example case (17 June 2015; covered in detail in Sect.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Configuration settings of the major instruments used in the COLRAWI campaigns (based onBühl et al, 2015). The second number indicates the setting used for the RWP during IOPs.…”

mentioning

confidence: 99%

Combining cloud radar and radar wind profiler for a value added estimate of vertical air motion and particle terminal velocity within clouds

et al. 2018

View full text Add to dashboard Cite

Abstract. Vertical-stare observations from a 482 MHz radar wind profiler and a 35 GHz cloud radar are combined on the level of individual Doppler spectra to measure vertical air motions in clear air, clouds and precipitation. For this purpose, a separation algorithm is proposed to remove the influence of falling particles from the wind profiler Doppler spectra and to calculate the terminal fall velocity of hydrometeors. The remaining error of both vertical air motion and terminal fall velocity is estimated to be better than 0.1 m s−1 using numerical simulations. This combination of instruments allows direct measurements of in-cloud vertical air velocity and particle terminal fall velocity by means of ground-based remote sensing. The possibility of providing a profile every 10 s with a height resolution of <100 m allows further insight into the process scale of in-cloud dynamics. The results of the separation algorithm are illustrated by two case studies, the first covering a deep frontal cloud and the second featuring a shallow mixed-phase cloud.

show abstract

Combined vertical-velocity observations with Doppler lidar, cloud radar and wind profiler

Cited by 24 publications

References 26 publications

Strong aerosol–cloud interaction in altocumulus during updraft periods: lidar observations over central Europe

Strong aerosol–cloud interaction in altocumulus during updraft periods: lidar observations over central Europe

A Matérn-Based Multivariate Gaussian Random Process for a Consistent Model of the Horizontal Wind Components and Related Variables

Combining cloud radar and radar wind profiler for a value added estimate of vertical air motion and particle terminal velocity within clouds

Contact Info

Product

Resources

About