CLAMPS Realtime Data

Collaborative Lower Atmospheric Mobile Profiling System

CLAMPS (or the Collaborative Lower Atmospheric Mobile Profiling System) was originally envisioned as a deployable boundary layer profiling system that is able to measure profiles of temperature, water vapor, and wind in the lowest several kilometers of the atmosphere at high temporal resolution using a particular combination of instruments. This instrument suite, and more specifically, the dataset derived from these observations, allows the users to identify and quantify significant changes in the atmospheric thermodynamic or dynamic structure. The real-time and continuous observation of these atmospheric properties is useful for characterizing the pre-convection environment for research on convective systems, mesoscale dynamic studies, research on nowcasting and forecasting local weather, technique development for remote sensing, urban meteorology, air quality and chemical weather analyses, research on boundary layer evolution, and other applications. In other words, the system allows for a unique breadth of research topics and applications. At the time of CLAMPS’s inception, no comparable capability existed within the university community or NOAA/OAR, and the CLAMPS system was the first to combine two thermodynamic profiling capabilities. While the three remote sensors that make up the CLAMPS mobile facility have a significant history, integration of the three together is what makes CLAMPS unique and powerful. The CLAMPS platform is made up of three main instruments: a Doppler lidar, a microwave radiometer (MWR), and an atmospheric emitted radiance interferometer (AERI). In addition to these three, CLAMPS also supports surface meteorological observations and a balloon radiosonde system.

CLAMPS is a collaborative effort between the NOAA National Severe Storms Laboratory (NSSL) and the University of Oklahoma (OU) School of Meteorology (SoM). Two CLAMPS facilities are operated by the collaborative team. CLAMPS-1 was funded by the NSF, NSSL, and OU, and was constructed in 2015. CLAMPS-2 was built in early 2016 with funding from NSSL. The CLAMPS facilities are trailer-based systems with their own generators and thus are easily transported to different locations; they can also be operated from shore power.

References

These references provide examples of CLAMPS data applications in published science and/or information about CLAMPS instrumentation and retreivals.

  • Degelia, S. K., X. Wang, and D. J. Stensrud, 2019: An Evaluation of the Impact of Assimilating AERI Retrievals, Kinematic Profilers, Rawinsondes, and Surface Observations on a Forecast of a Nocturnal Convection Initiation Event during the PECAN Field Campaign. Mon. Wea. Rev., 147, 2739–2764, https://doi.org/10.1175/MWR-D-18-0423.1.
  • Smith, E. N., J. G. Gebauer, P. M. Klein, E. Fedorovich, and J. A. Gibbs, 2019: The Great Plains Low-Level Jet during PECAN: Observed and Simulated Characteristics. Mon. Wea. Rev., 147, 1845–1869, https://doi.org/10.1175/MWR-D-18-0293.1.
  • Wagner, T. J., P. M. Klein, and D. D. Turner, 2019: A New Generation of Ground-Based Mobile Platforms for Active and Passive Profiling of the Boundary Layer. Bull. Amer. Meteor. Soc., 100, 137–153, https://doi.org/10.1175/BAMS-D-17-0165.1.
  • Geerts, B., and coauthors, 2017: The 2015 Plains Elevated Convection at Night (PECAN) field project. Bull. Amer. Meteor. Soc., 98, 767–786, https://doi.org/10.1175/BAMS-D-15-00257.1.
  • Blumberg, W.G., D.D. Turner, U. Loehnert, and S. Castleberry, 2015: Ground-based temperature and humidity profiling using spectral infrared and microwave observations. Part 2: Actual retrieval performance in clear sky and cloudy conditions. J. Appl. Meteor. Clim., 54, 2305-2319, doi:10.1175/JAMC-D-15-0005.1.
  • Klein, P., T.A. Bonin, J.F. Newman, D.D. Turner, P.B. Chilson, C.E. Wainwright, W.G. Blumberg, S. Mishra, M. Carney, E.P. Jacobsen, S. Wharton, and R.K. Newsom, 2015: LABLE: A multi-institutional, student-led, atmospheric boundary layer experiment. Bull. Amer. Meteo Soc., 96, 1743-1764. doi:10.1175/BAMS-D-13-00267.1.