CLAMPS-EOL Collaboration

Science Lead (2021)

My Role

  • Collaborated to design a month-long CLAMPS-1 facility deployment to the Marshal field site in Boulder, CO.
  • Deployment supported EOL’s progress toward LOTOS and built new collaborations between EOL and BLISS communities.

OU BLISS – NCAR EOL Collaborative Deployment Summer 2021

Background

The University of Oklahoma’s Boundary Layer Integrated Sensing and Simulation (BLISS) Group collaborated with the the NCAR Earth Observing Laboratory (EOL) by deploying the Collaborative Lower Atmospheric Mobile Profiling System (CLAMPS) to the NCAR Marshall Field Site for approximately one month in the summer of 2021.

Assets

BLISS is providing the CLAMPS platform which provides the following instruments and assets:

  • Halo Streamline (upgraded) Doppler wind lidar
  • RPG HATPRO microwave radiometer
  • ABB atmospheric emitted radiance interferometer (aka AERI)
  • Trailer-mounted meteorology mast
  • Internal automated data system capable of remote monitoring

EOL is providing the following instruments and assets:

  • 3-panel 449 wind profiling radar
  • 915 wind profiling radar
  • Radio acoustic sounding spectrometer
  • 32-m telescoping tower with flux stations
  • Micropulse differential absorption lidar
  • Windcube wind scanning Doppler lidar
  • Ceilometer
  • 30-40 radiosondes (plus quality assurance)

Objectives

A series of mutually beneficial objectives were identified by BLISS and EOL staff. They are listed below with a short descriptions. Note that these are the planned objectives, but interesting and relevant targets of opportunity such as, but not limited to, convection initiation processes, slope wind events, periods with interesting and high quality turbulence observation, cold pool passage, shallow stable layers, and near- or pre-storm environmental observation were also considered an objectivd.

  1. Optimal estimation of boundary layer winds:
    BLISS and EOL both benefit from the development of a method by which wind profiles (u-, v-, w-components) can be retrieved via an optimal estimation approach. This method is adaptable to apply to radar wind profilers, Doppler wind lidars, in-situ observations, and various time scales. This method development resulted in a multi-institution publication, and to be deployed both in CLAMPS and LOTOS frameworks (see WINDoe, Gebauer et al.)
  2. Multi-instrument boundary layer height retrievals:
    There is a pre-developed fuzzy logic algorithm to retrieve boundary layer height from CLAMPS instrumentation. This algorithm can be adapted to include different and/or additional inputs. This provided an opportunity to apply existing fuzzy logic methods to radar wind profiler data and employ radiosonde, ceilometer, Doppler weather radar, and other datasets. These data enable various algorithm comparisons, validation, and improvement.
  3. Instrument deployment and operation methods:
    The deployment explore various methods of operating and integrating the combination of instruments deployed on site. For example, how water vapor observations from the MPDial can be applied in thermodynamic retrieval frameworks, and how to design various virtual tower scans.
  4. Data workflows and visualization:
    The CLAMPS platform has a robust and fairly mature data system which ingests multiple datastreams to provide initial quality checks and provide some value-added products and near-real time data visualization. There are always some areas where this could be improved and tested. In this deployment, tested deployment of new open source tools, implemented new algorithms, and moved toward JSON web plotting instead of static images.