Lidar observations of a mesoscale moisture transport event impacting convection and comparison to Rapid Refresh model analysis

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  • 1 Department of Physics, University of Maryland Baltimore County, Baltimore, Maryland, USA, and Joint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, Maryland, USA
  • 2 Global Systems Laboratory, National Oceanic and Atmospheric Administration, Boulder, Colorado, USA
  • 3 Joint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, Maryland, USA
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Abstract

The 2015 Plains Elevated Convection at Night (PECAN) field campaign provided a wealth of intensive observations for improving understanding of interplay between the Great Plains low-level jet (LLJ), mesoscale convective systems (MCSs), and other phenomena in the nocturnal boundary layer. This case study utilizes PECAN ground-based Doppler and water vapor lidar and airborne water vapor lidar observations for a detailed examination of water vapor transport in the Great Plains. The chosen case, 11 July 2015, featured a strong LLJ that helped sustain an MCS overnight. The lidars resolved boundary layer moisture being transported northward, leading to a large increase in water vapor in the lowest several hundred meters above the surface in northern Kansas. A branch of nocturnal convection initiated coincident with the observed maximum water vapor flux. Radiosondes confirmed an increase in convective potential within the LLJ layer. Moist static energy (MSE) growth was generated by increasing moisture in spite of a temperature decrease in the LLJ layer. This unique dataset is also used to evaluate the Rapid Refresh (RAP) analysis model performance, comparing model output against the continuous lidar profiles of water vapor and wind. While the RAP analysis captured the large-scale trends, errors in water vapor mixing ratio were found ranging 0 to 2 g/kg at the ground-based lidar sites. Comparison with the airborne lidar throughout the PECAN domain yielded a RMSE of 1.14 g/kg in the planetary boundary layer. These errors mostly manifested as contiguous dry or wet regions spanning spatial scales of O(10s-100s km).

This article is included in the Plains Elevated Convection At Night (PECAN) Special Collection.

Corresponding author: Brian J. Carroll, brian.carroll@umbc.edu

Abstract

The 2015 Plains Elevated Convection at Night (PECAN) field campaign provided a wealth of intensive observations for improving understanding of interplay between the Great Plains low-level jet (LLJ), mesoscale convective systems (MCSs), and other phenomena in the nocturnal boundary layer. This case study utilizes PECAN ground-based Doppler and water vapor lidar and airborne water vapor lidar observations for a detailed examination of water vapor transport in the Great Plains. The chosen case, 11 July 2015, featured a strong LLJ that helped sustain an MCS overnight. The lidars resolved boundary layer moisture being transported northward, leading to a large increase in water vapor in the lowest several hundred meters above the surface in northern Kansas. A branch of nocturnal convection initiated coincident with the observed maximum water vapor flux. Radiosondes confirmed an increase in convective potential within the LLJ layer. Moist static energy (MSE) growth was generated by increasing moisture in spite of a temperature decrease in the LLJ layer. This unique dataset is also used to evaluate the Rapid Refresh (RAP) analysis model performance, comparing model output against the continuous lidar profiles of water vapor and wind. While the RAP analysis captured the large-scale trends, errors in water vapor mixing ratio were found ranging 0 to 2 g/kg at the ground-based lidar sites. Comparison with the airborne lidar throughout the PECAN domain yielded a RMSE of 1.14 g/kg in the planetary boundary layer. These errors mostly manifested as contiguous dry or wet regions spanning spatial scales of O(10s-100s km).

This article is included in the Plains Elevated Convection At Night (PECAN) Special Collection.

Corresponding author: Brian J. Carroll, brian.carroll@umbc.edu
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