Atmospheric Radiation Measurement Climate Research Facility US Department of Energy

csapr > CSAPR2 cell-tracking data collected during TRACERData Source Type(s) > PI

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. 



CSAPR2 performed frequent update of range-height indicator (RHI) and sector plan position indicator (PPI) scans targeting convective cell lifecycles during the TRACER field campaign. The radar scans were guided by the Multisensor Agile Adaptive Sampling (MAAS, Kollias et al. 2020) using eternal sources of measurements (i.e. satellite). 

The data can be used to analyze fast-evolved radar observables (e.g., reflectivity, Doppler velocity, specific differential phase, and differential reflectivity) of individual deep convective clouds observed in Houston in the summer 2022. The analysis using the dataset can help to improve understanding convective cell structure and lifecycle.


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Data Details

Developed By Mariko Oue | Bernat Puigdoménech-Treserras | Edward Luke | Pavlos Kollias
Contact Mariko Oue
Resource(s) Data Directory
Data format NetCDF4, CfRadial
Site HOU
Content time range 4 June 2022 - 20 September 2022
Attribute accuracy No formal uncertainty assessments were conducted and no estimates of uncertainty are reported.
Positional accuracy No formal positional accuracy tests were conducted.
Data Consistency and Completeness Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
Access Restriction No access constraints are associated with this data.
Use Restriction No use constraints are associated with this data.
File naming convention Generally the filename has “” The first three characters “hou” represent the Houston site. The following characters “csapr2” represent the name of the radar “CSAPR2”. The following characters “ppirhi” represent that the data file includes PPI and RHI scans. This part sometimes has “ppi” or “rhi” only if the file includes data from PPI or RHI only. “lv2” means “Level2” product including processed data.
Directory Organization The data files are stored in the subdirectory named the date (yyyymmdd).
Citations Helmus, J.J. and Collis, S.M., (2016), The Python ARM Radar Toolkit (Py-ART), a Library for Working with Weather Radar Data in the Python Programming Language. Journal of Open Research Software. 4(1), p.e25. DOI:

Kollias, P., Luke, E., Oue, M., and Lamer, K. (2020), Agile adaptive radar sampling of fast-evolving atmospheric phenomena guided by satellite imagery and surface cameras. Geophysical Research Letters, 45, e2020GL088440.

Bell, M. M., Dixon, M., Lee, W.-C., Javornik, B., DeHart, J., Cha, T.-Y., and DesRosiers, A. (2022). nsf-lrose/lrose-topaz: lrose-topaz stable final release 20220222 (lrose-topaz-2022022). Zenodo.