Javascript must be enabled to continue!
Assessment of variability in continental low stratiform clouds based on observations of radar reflectivity
View through CrossRef
The variability of overcast low stratiform clouds observed over the ARM Climate Research Facility Southern Great Plains (ACRF SGP) site is analyzed, and an approach to characterizing subgrid variability based on assumed statistical distributions is evaluated. The analysis is based on a vast (>1000 hours) radar reflectivity database collected by the Millimeter‐Wave Cloud Radar at ACRF SGP site. The radar data are classified into two low cloud categories and stratified by scale and the presence of precipitation. Cloud variability is analyzed by studying statistical distributions for the first two moments of the probability distribution functions (PDF) of radar reflectivity. Results indicate that variability for a broadly defined low‐altitude stratiform cloud type exhibits on average 40% greater standard deviation than canonical boundary layer clouds topped by an inversion. Cloud variability also dramatically depends on microphysical processes (as manifested in radar reflectivity) and increases by 2–5 times within a typical reflectivity range. Finally, variability is a strong function of scale and almost doubles in the 20–100 min temporal scale range. Formulations of subgrid variability, based on PDFs of reflectivity, are evaluated for the two cloud types and two scales of 10 and 30 km, taken to be representative of mesoscale and NWP model grid sizes. The results show that for these cloud types and scales the PDF of reflectivity can be reasonably well approximated by a truncated Gaussian function, specified by mean and standard deviation with the latter parameterized as a linear function of the mean.
American Geophysical Union (AGU)
Title: Assessment of variability in continental low stratiform clouds based on observations of radar reflectivity
Description:
The variability of overcast low stratiform clouds observed over the ARM Climate Research Facility Southern Great Plains (ACRF SGP) site is analyzed, and an approach to characterizing subgrid variability based on assumed statistical distributions is evaluated.
The analysis is based on a vast (>1000 hours) radar reflectivity database collected by the Millimeter‐Wave Cloud Radar at ACRF SGP site.
The radar data are classified into two low cloud categories and stratified by scale and the presence of precipitation.
Cloud variability is analyzed by studying statistical distributions for the first two moments of the probability distribution functions (PDF) of radar reflectivity.
Results indicate that variability for a broadly defined low‐altitude stratiform cloud type exhibits on average 40% greater standard deviation than canonical boundary layer clouds topped by an inversion.
Cloud variability also dramatically depends on microphysical processes (as manifested in radar reflectivity) and increases by 2–5 times within a typical reflectivity range.
Finally, variability is a strong function of scale and almost doubles in the 20–100 min temporal scale range.
Formulations of subgrid variability, based on PDFs of reflectivity, are evaluated for the two cloud types and two scales of 10 and 30 km, taken to be representative of mesoscale and NWP model grid sizes.
The results show that for these cloud types and scales the PDF of reflectivity can be reasonably well approximated by a truncated Gaussian function, specified by mean and standard deviation with the latter parameterized as a linear function of the mean.
Related Results
Development of a weather radar simulator for the characterisation of radar reflectivity of tropical rainfall
Development of a weather radar simulator for the characterisation of radar reflectivity of tropical rainfall
Weather radar systems are important tools for rainfall monitoring, atmospheric research, and the design of microwave communication systems. However, the high cost and limited avail...
Mid-level clouds are frequent above the southeast Atlantic stratocumulus clouds
Mid-level clouds are frequent above the southeast Atlantic stratocumulus clouds
Abstract. Shortwave-absorbing aerosols seasonally overlay extensive low-level stratocumulus clouds over the southeast Atlantic. While a lot of attention has been focused on the int...
Vertical profiles of precipitating clouds in Monsoon Regions using the GPM satellite
Vertical profiles of precipitating clouds in Monsoon Regions using the GPM satellite
The vertical structure of precipitating clouds plays a vital role in shaping the rainfall characteristics of the surrounding region. Based on the dual-frequency space-borne precipi...
Physical processes in polar stratospheric ice clouds
Physical processes in polar stratospheric ice clouds
A one‐dimensional model of cloud microphysics has been used to simulate the formation and evolution of polar stratospheric ice clouds. The model results are in general agreement wi...
Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event
Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event
Operational Doppler radar observations have potential advantages over other above-surface observations when it comes to assimilation for mesoscale model simulations with high spati...
Damage Analysis and Close-Range Radar Observations of the 13 April 2019 Greenwood Springs, Mississippi, Tornado during VORTEX-SE Meso18-19
Damage Analysis and Close-Range Radar Observations of the 13 April 2019 Greenwood Springs, Mississippi, Tornado during VORTEX-SE Meso18-19
Abstract
A tornado outbreak occurred across the Southeast United States on 13–14 April 2019, during the Verification of the Origins of Rotation in Tornadoes Experiment–Southeast (V...
Radar Data Assimination in WRF Model to Forecast Heavy Rainfall at Ho Chi Minh City
Radar Data Assimination in WRF Model to Forecast Heavy Rainfall at Ho Chi Minh City
Abstract: This article using high resolution WRF model simulation on a heavy rainfall in summer at Hochiminh city by using radar data to assimilation initial conditions with 3DVAR ...
MST radar and polarization lidar observations of tropical cirrus
MST radar and polarization lidar observations of tropical cirrus
Abstract. Significant gaps in our understanding of global cirrus effects on the climate system involve the role of frequently occurring tropical cirrus. Much of the cirrus in the a...

