scholarly journals Ground-Based Remote Retrievals of Cumulus Entrainment Rates

2013 ◽  
Vol 30 (7) ◽  
pp. 1460-1471 ◽  
Author(s):  
Timothy J. Wagner ◽  
David D. Turner ◽  
Larry K. Berg ◽  
Steven K. Krueger

Abstract While fractional entrainment rates for cumulus clouds have typically been derived from airborne observations, this limits the size and scope of available datasets. To increase the number of continental cumulus entrainment rate observations available for study, an algorithm for retrieving them from ground-based remote sensing observations has been developed. This algorithm, called the Entrainment Rate In Cumulus Algorithm (ERICA), uses the suite of instruments at the Southern Great Plains (SGP) site of the U.S. Department of Energy's Atmospheric Radiation Measurement Program (ARM) Climate Research Facility as inputs into a Gauss–Newton optimal estimation scheme, in which an assumed guess of the entrainment rate is iteratively adjusted through intercomparison of modeled cloud attributes to their observed counterparts. The forward model in this algorithm is the explicit mixing parcel model (EMPM), a cloud parcel model that treats entrainment as a series of discrete entrainment events. A quantified value for the uncertainty in the retrieved entrainment rate is also returned as part of the retrieval. Sensitivity testing and information content analysis demonstrate the robust nature of this method for retrieving accurate observations of the entrainment rate without the drawbacks of airborne sampling. Results from a test of ERICA on 3 months of shallow cumulus cloud events show significant variability of the entrainment rate of clouds in a single day and from one day to the next. The mean value of 1.06 km−1 for the entrainment rate in this dataset corresponds well with prior observations and simulations of the entrainment rate in cumulus clouds.

2021 ◽  
Vol 14 (4) ◽  
pp. 3033-3048
Author(s):  
David D. Turner ◽  
Ulrich Löhnert

Abstract. Thermodynamic profiles in the planetary boundary layer (PBL) are important observations for a range of atmospheric research and operational needs. These profiles can be retrieved from passively sensed spectral infrared (IR) or microwave (MW) radiance observations or can be more directly measured by active remote sensors such as water vapor differential absorption lidars (DIALs). This paper explores the synergy of combining ground-based IR, MW, and DIAL observations using an optimal-estimation retrieval framework, quantifying the reduction in the uncertainty in the retrieved profiles and the increase in information content as additional observations are added to IR-only and MW-only retrievals. This study uses ground-based observations collected during the Perdigão field campaign in central Portugal in 2017 and during the DIAL demonstration campaign at the Atmospheric Radiation Measurement Southern Great Plains site in 2017. The results show that the information content in both temperature and water vapor is higher for the IR instrument relative to the MW instrument (thereby resulting in smaller uncertainties) and that the combined IR + MW retrieval is very similar to the IR-only retrieval below 1.5 km. However, including the partial profile of water vapor observed by the DIAL increases the information content in the combined IR + DIAL and MW + DIAL water vapor retrievals substantially, with the exact impact vertically depending on the characteristics of the DIAL instrument itself. Furthermore, there is a slight increase in the information content in the retrieved temperature profile using the IR + DIAL relative to the IR-only; this was not observed in the MW + DIAL retrieval.


2020 ◽  
Author(s):  
David D. Turner ◽  
Ulrich Löhnert

Abstract. Thermodynamic profiles in the planetary boundary layer (PBL) are important observations for a range of atmospheric research and operational needs. These profiles can be retrieved from passively sensed spectral infrared (IR) or microwave (MW) radiance observations, or can be more directly measured by active remote sensors such as water vapor differential absorption lidars (DIALs). This paper explores the synergy of combining ground-based IR, MW, and DIAL observations using an optimal estimation retrieval framework, quantifying the reduction in the uncertainty in the retrieved profiles and the increase in information content as additional observations are added to IR-only and MW-only retrievals. This study uses ground-based observations collected during the Perdigao field campaign in central Portugal in 2017 and during the DIAL demonstration campaign at the Atmospheric Radiation Measurement Southern Great Plains site in 2017. The results show that the information content in both temperature and water vapor is higher for IR instrument relative to the MW instrument (thereby resulting in smaller uncertainties), and that the combined IR+MW retrieval is very similar to the IR-only retrieval below 1.5 km. However, including the partial profile of water vapor observed by the DIAL increases the information content in the combined IR+DIAL and MW+DIAL water vapor retrievals substantially, with the exact impact vertically depending on the characteristics of the DIAL instrument itself. Furthermore, there is slight increase in the information content in the retrieved temperature profile using the IR+DIAL relative to the IR-only; this was not observed in the MW+DIAL retrieval.


2013 ◽  
Vol 26 (24) ◽  
pp. 10031-10050 ◽  
Author(s):  
Arunchandra S. Chandra ◽  
Pavlos Kollias ◽  
Bruce A. Albrecht

Abstract A long data record (14 yr) of ground-based observations at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site is analyzed to document the macroscopic and dynamical properties of daytime fair-weather cumulus clouds during summer months. First, a fuzzy logic–based algorithm is developed to eliminate insect radar echoes in the boundary layer that hinder the ability to develop representative cloud statistics. The refined dataset is used to document the daytime composites of fair-weather cumulus clouds properties. Doppler velocities are processed for lower reflectivity thresholds that contain small cloud droplets having insignificant terminal velocities; thus, Doppler velocities are used as tracers of air motion. The algorithm is implemented to process the entire 14-yr dataset of cloud radar vertical velocity data. Composite diurnal variations of the cloud vertical velocity statistics, surface parameters, and profiles of updraft and downdraft fractions, bulk velocity of updrafts and downdrafts, and updraft and downdraft mass flux are calculated. Statistics on the cloud geometrical properties such as cloud thickness, cloud chord length, cloud spacing, and aspect ratios are calculated on the cloud scale. The present dataset provides a unique insight into the daytime evolution and statistical description of the turbulent structure inside fair-weather cumuli over land.


2011 ◽  
Vol 4 (1) ◽  
pp. 715-735 ◽  
Author(s):  
E. Kassianov ◽  
J. Barnard ◽  
L. K. Berg ◽  
C. Flynn ◽  
C. N. Long

Abstract. The diffuse all-sky surface irradiances measured at two nearby wavelengths in the visible spectral range and their model clear-sky counterparts are two main components of a new method for estimating the fractional sky cover of different cloud types, including cumulus clouds. The performance of this method is illustrated using 1-min resolution data from ground-based Multi-Filter Rotating Shadowband Radiometer (MFRSR). The MFRSR data are collected at the US Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site during the summer of 2007 and represent 13 days with cumulus clouds. Good agreement is obtained between estimated values of the fractional sky cover and those provided by a well-established independent method based on broadband observations.


2005 ◽  
Vol 22 (6) ◽  
pp. 605-627 ◽  
Author(s):  
Robert F. Cahalan ◽  
Matthew McGill ◽  
John Kolasinski ◽  
Tamás Várnai ◽  
Ken Yetzer

Abstract Conventional wisdom is that lidar pulses do not significantly penetrate clouds having an optical thickness exceeding about τ = 2, and that no returns are detectible from more than a shallow skin depth. Yet optically thicker clouds of τ ≫ 2 reflect a larger fraction of visible photons and account for much of the earth’s global average albedo. As cloud-layer thickness grows, an increasing fraction of reflected photons are scattered multiple times within the cloud and return from a diffuse concentric halo that grows around the incident pulse, increasing in horizontal area with layer physical thickness. The reflected halo is largely undetected by narrow field-of-view (FOV) receivers commonly used in lidar applications. Cloud Thickness from Offbeam Returns (THOR) is an airborne wide-angle detection system with multiple FOVs, capable of observing the diffuse halo as a wide-angle signal, from which the physical thickness of optically thick clouds can be retrieved. This paper describes the THOR system, demonstrates that the halo signal is stronger for thicker clouds, and presents a validation of physical thickness retrievals for clouds having τ > 20, from NASA’s P-3B flights over the Department of Energy’s Atmospheric Radiation Measurement Southern Great Plains site, using the lidar, radar, and other ancillary ground-based data.


2020 ◽  
Vol 20 (6) ◽  
pp. 3483-3501 ◽  
Author(s):  
Xiaojian Zheng ◽  
Baike Xi ◽  
Xiquan Dong ◽  
Timothy Logan ◽  
Yuan Wang ◽  
...  

Abstract. The aerosol indirect effect on cloud microphysical and radiative properties is one of the largest uncertainties in climate simulations. In order to investigate the aerosol–cloud interactions, a total of 16 low-level stratus cloud cases under daytime coupled boundary-layer conditions are selected over the southern Great Plains (SGP) region of the United States. The physicochemical properties of aerosols and their impacts on cloud microphysical properties are examined using data collected from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the SGP site. The aerosol–cloud interaction index (ACIr) is used to quantify the aerosol impacts with respect to cloud-droplet effective radius. The mean value of ACIr calculated from all selected samples is 0.145±0.05 and ranges from 0.09 to 0.24 at a range of cloud liquid water paths (LWPs; LWP=20–300 g m−2). The magnitude of ACIr decreases with an increasing LWP, which suggests a diminished cloud microphysical response to aerosol loading, presumably due to enhanced condensational growth processes and enlarged particle sizes. The impact of aerosols with different light-absorbing abilities on the sensitivity of cloud microphysical responses is also investigated. In the presence of weak light-absorbing aerosols, the low-level clouds feature a higher number concentration of cloud condensation nuclei (NCCN) and smaller effective radii (re), while the opposite is true for strong light-absorbing aerosols. Furthermore, the mean activation ratio of aerosols to CCN (NCCN∕Na) for weakly (strongly) absorbing aerosols is 0.54 (0.45), owing to the aerosol microphysical effects, particularly the different aerosol compositions inferred by their absorptive properties. In terms of the sensitivity of cloud-droplet number concentration (Nd) to NCCN, the fraction of CCN that converted to cloud droplets (Nd∕NCCN) for the weakly (strongly) absorptive regime is 0.69 (0.54). The measured ACIr values in the weakly absorptive regime are relatively higher, indicating that clouds have greater microphysical responses to aerosols, owing to the favorable thermodynamic condition. The reduced ACIr values in the strongly absorptive regime are due to the cloud-layer heating effect induced by strong light-absorbing aerosols. Consequently, we expect larger shortwave radiative cooling effects from clouds in the weakly absorptive regime than those in the strongly absorptive regime.


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