Evaluation of turbulent dissipation rate retrievals from Doppler Cloud Radar

Abstract

Abstract. Turbulent dissipation rate retrievals from cloud radar Doppler velocity measurements are evaluated using independent, in situ observations in Arctic stratocumulus clouds. In situ validation data sets of dissipation rate are derived using sonic anemometer measurements from a tethered balloon and high frequency pressure variation observations from a research aircraft, both flown in proximity to stationary, ground-based radars. Modest biases are found among the data sets in particularly low-or high-turbulence regimes, but in general the radar-retrieved values correspond well with the in situ measurements. Root mean square differences are typically a factor of 4-6 relative to any given magnitude of dissipation rate. These differences are no larger than those found when comparing dissipation rates computed from tetheredballoon and meteorological tower-mounted sonic anemometer measurements made at spatial distances of a few hundred meters. Temporal lag analyses suggest that approximately half of the observed differences are due to spatial sampling considerations, such that the anticipated radar-based retrieval uncertainty is on the order of a factor of 2-3. Moreover, radar retrievals are clearly able to capture the vertical dissipation rate structure observed by the in situ sensors, while offering substantially more information on the time variability of turbulence profiles. Together these evaluations indicate that radar-based retrievals can, at a minimum, be used to determine the vertical structure of turbulence in Arctic stratocumulus clouds.

Characteristic nature of vertical motions observed in Arctic mixed-phase stratocumulus

“…Profiles of ε are estimated using temporal variance of the first Doppler moment, namely the mean Doppler velocity; details of the estimation method are given in Shupe et al (2012). The ε retrieval can be applied (contours, [dBZ]) observed from the vertically pointing MMCR radar at ASCOS over the week 25-30 August 2008.…”

“…Relatively recent studies on AMPS in-cloud vertical velocity (w) have identified characteristic cloud overturning timescales on the order of 10 min (Pinto, 1998;Shupe et al, 2008aShupe et al, , 2012. These characteristic motions have been linked to the persistent nature of AMPS through the nearly continuous generation of cloud condensate, regulated in magnitude by ice crystal formation and precipitation processes (Shupe et al, 2008a).…”

“…This campaign was conceived to address the knowledge gap of, among many others, surface-atmosphere-cloud processes and interactions that may be critical in the development and persistence of Arctic stratocumulus. Contributing to the community's understanding of low-level (< 2.5 km above the surface) cloud processes over the Arctic, a number of ASCOS process-oriented studies relating to such interactions have recently been conducted (e.g., Sedlar et al, 2011;Mauritsen et al, 2011;Birch et al, 2012;Shupe et al, 2012;Tjernström et al, 2012;Kuzpiewski et al, 2013;Sotiropoulou et al, 2014). The entire timeline of ASCOS is meticulously detailed in Tjernström et al (2014), including extensive descriptions of the instrumentation and measurements, and so only the necessary details are provided below.…”

Turbulent structure and scaling of the inertial subrange in a stratocumulus-topped boundary layer observed by a Doppler lidar

“…Kouznetsov et al, 2007), Doppler cloud radars (e.g. Shupe et al, 2012) and combinations of these (e.g. Norton, 2006).…”

A new model for retrieving information about turbulence intensity from radar signal

“…There are a lot of works on estimation of EDR based on radar remote sensing data. Many of radar methods and signal processing algorithms are based on estimating Doppler spectrum width (DSW) [1][2][3][4][5]. It is known that the DSW provides an overestimate of the turbulence EDR because not only turbulence contributes to the width of the spectrum.…”