Convective processes play an important role in Earth's energy balance by distributing heat and moisture throughout the atmosphere. In particular, vertical air motions associated with these processes are inherently linked to the life cycle of these convective systems and are therefore directly tied to their energy budget. However, direct measurements of vertical air motions (e.g., in situ aircraft observations) are sparse, making it difficult to compare them with numerical model output, which relies on convective parameterization schemes that have yet to be extensively validated with direct or indirect measurements. A Doppler weather radar, though unable to directly measure vertical velocity, is able to observe mesoscale storm structure. Using data assimilation techniques, observations from a single or multiple Doppler weather radars can be combined with other observations (e.g., a radiosonde profile) to produce a best estimate of the mesoscale atmospheric kinematics. The Convective Vertical Velocity (CONVV) VAP is the product of an algorithm based on these ideas.
CONVV
convv > Convective Vertical VelocityData Source Type(s) > PI
Purpose
Convective processes play an important role in Earth's energy balance by distributing heat and moisture throughout the atmosphere. In particular, vertical air motions associated with these processes are inherently linked to the life cycle of these convective systems and are therefore directly tied to their energy budget. However, direct measurements of vertical air motions (e.g. in situ aircraft observations) are sparse, making it difficult to compare with numerical model output, which rely on convective parameterization schemes that have yet to be extensively validated with direct or indirect measurements. A Doppler weather radar, though unable to directly measure vertical velocity, is able to observe mesoscale storm structure. Using data assimilation techniques, observations from a single or multiple Doppler weather radars can be combined with other observations (e.g. a radiosonde profile) to produce a best estimate of the mesoscale atmospheric kinematics. ConVVAP is the product of an algorithm based on these ideas.
Primary Measurements
Locations
- Fixed
- Mobile
Data Details
Developed By | Kirk North | Scott Collis |
Contact | Hannah Collier |
Resource(s) |
Data Directory ReadMe |
Data format | netcdf, png |
Site | SGP |
Content time range | 25 April 2011 - 23 May 2011 |
Attribute accuracy | No formal attribute accuracy tests were conducted |
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. |
Citations |
Collis, S., A. Protat, and K.-S. Chung, 2010: The effect of radial velocity gridding artifacts on variationally retrieved vertical velocities. J. Atmos. Oceanic Technol., 27, 1239-1246.
Collis, S., A. Protat, P. May, and C. Williams, 2012: Statistics of storm updraft velocities from TWP-ICE including verification with profiling measurements. J. Appl. Meteor. Climatol. Gao, J., M. Xue, A. Shapiro, and K. K. Droegemeier, 1999: A variational method for the analysis of three-dimensional wind fields from two Doppler radars. Mon. Wea. Rev., 127, 2128-2142. Laroche, S., and I. Zawadzki, 1994: A variational analysis method for retrieval of three-dimensional wind field from single-Doppler radar data. J. Atmos. Sci., 51, 2664-2682. Protat, A., and I. Zawadzki, 1999: A variational method for real-time retrieval of three-dimensional wind field from multiple-Doppler bistatic radar network data. J. Atmos. Oceanic Technol., 16, 432-449. Ray, P. S., C. L. Ziegler, W. Bumgarner, and R. J. Serafin, 1980: Single and multiple Doppler radar observations of tornadic storms. Mon. Wea. Rev., 108, 1607-1625. Steiner, M., R. A. Houze Jr., and S. E. Yuter, 1995: Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data. J. Appl. Meteor., 34, 1978-2006. |