skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Multisensor Agile Adaptive Sampling (MAAS): A Methodology to Collect Radar Observations of Convective Cell Life Cycle
Abstract Multisensor Agile Adaptive Sampling (MAAS), a smart sensing framework, was adapted to increase the likelihood of observing the vertical structure (with little to no gaps), spatial variability (at subkilometer scale), and temporal evolution (at ∼2-min resolution) of convective cells. This adaptation of MAAS guided two mechanically scanning C-band radars (CSAPR2 and CHIVO) by automatically analyzing the latest NEXRAD data to identify, characterize, track, and nowcast the location of all convective cells forming in the Houston domain. MAAS used either a list of predetermined rules or real-time user input to select a convective cell to be tracked and sampled by the C-band radars. The CSAPR2 tracking radar was first tasked to collect three sector plan position indicator (PPI) scans toward the selected cell. Edge computer processing of the PPI scans was used to identify additional targets within the selected cell. In less than 2 min, both the CSAPR2 and CHIVO radars were able to collect bundles of three to six range–height indicator (RHI) scans toward different targets of interest within the selected cell. Bundles were successively collected along the path of cell advection for as long as the cell met a predetermined set of criteria. Between 1 June and 30 September 2022 over 315 000 vertical cross-section observations were collected by the C-band radars through ∼1300 unique isolated convective cells, most of which were observed for over 15 min of their life cycle. To the best of our knowledge, this dataset, collected primarily through automatic means, constitutes the largest dataset of its kind.  more » « less
Award ID(s):
2019932
PAR ID:
10475396
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  
Publisher / Repository:
American Meteorological Society
Date Published:
Journal Name:
Journal of Atmospheric and Oceanic Technology
Volume:
40
Issue:
11
ISSN:
0739-0572
Format(s):
Medium: X Size: p. 1509-1522
Size(s):
p. 1509-1522
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; (, Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States))
    One of the challenges of analyzing convective cell properties is quick evolution of the individual convective cells.  While the operational radar data provide great a data set to analyze the evolution of radar observables of convective precipitation clouds statistically, previous studies also suggested that, because of the quick evolution of cell life cycle, conventional radar volume scan strategies taking ~5-7 minutes might not capture the detailed evolution. The TRACER campaign deployed CSAPR2, which performed frequent update of RHI and sector PPI scans to track convective cells every < 2 minutes guided by a new cell-tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. The submitted data files are CSAPR2 data in CfRadial format collected during the TRACER field campaign from June to September 2020. The data files include processed radar variables including: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification.   
    more » « less
  2. (, UCAR/NCAR - Earth Observing Laboratory)
    The dataset consists of vertical profiles of horizontal winds derived from radar Plan Position Indicator (PPI) scans conducted at a 17° elevation angle. In cases where 17° data were unavailable, the highest available elevation angle was utilized. The wind profiles were obtained using the Vertical Azimuth Display (VAD) technique, which involves measuring the radial velocity of targets at various azimuth angles and applying a least square fitting procedure to extract the horizontal wind speed and direction as a function of altitude. This method assumes that the wind field is horizontally homogeneous over the radar sampling volume. For more details on the VAD technique, refer to Browning and Wexler (1968). 
    more » « less
  3. (, UCAR/NCAR - Earth Observing Laboratory)
    The dataset consists of vertical profiles of horizontal winds derived from radar Plan Position Indicator (PPI) scans conducted at a 17° elevation angle. In cases where 17° data were unavailable, the highest available elevation angle was utilized. The wind profiles were obtained using the Vertical Azimuth Display (VAD) technique, which involves measuring the radial velocity of targets at various azimuth angles and applying a least square fitting procedure to extract the horizontal wind speed and direction as a function of altitude. This method assumes that the wind field is horizontally homogeneous over the radar sampling volume. For more details on the VAD technique, refer to Browning and Wexler (1968). 
    more » « less
  4. (, UCAR/NCAR - Earth Observing Laboratory)
    The dataset consists of vertical profiles of horizontal winds derived from radar Plan Position Indicator (PPI) scans conducted at a 18° elevation angle. The wind profiles were obtained using the Vertical Azimuth Display (VAD) technique, which involves measuring the radial velocity of targets at various azimuth angles and applying a least square fitting procedure to extract the horizontal wind speed and direction as a function of altitude. This method assumes that the wind field is horizontally homogeneous over the radar sampling volume. For more details on the VAD technique, refer to Browning and Wexler (1968). The data format is readable ASCII. 
    more » « less
  5. (, UCAR/NCAR - Earth Observing Laboratory)
    The dataset consists of vertical profiles of horizontal winds derived from radar Plan Position Indicator (PPI) scans conducted at a 18° elevation angle. The wind profiles were obtained using the Vertical Azimuth Display (VAD) technique, which involves measuring the radial velocity of targets at various azimuth angles and applying a least square fitting procedure to extract the horizontal wind speed and direction as a function of altitude. This method assumes that the wind field is horizontally homogeneous over the radar sampling volume. For more details on the VAD technique, refer to Browning and Wexler (1968). The data are readable ASCII. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email