Impact of Assimilating Thermodynamic and Kinematic Profiles on a Convection Initiation Forecast

Details

• Journal Title:
  Monthly Weather Review
• Personal Author:
  Kay, Junkyung ; Weckwerth, Tammy M. ; Turner, David D. ; Romine, Glen ; Ying, Yue
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; GSL (Global Systems Laboratory)
• Description:
  The first field campaign of a network of water vapor lidars, called the micropulse differential absorption lidar (MPD) network demonstration project, combined the observational capabilities of the water vapor MPD, the Atmospheric Emitted Radiance Interferometer (AERI), and the Doppler wind lidar (DWL) at five sites at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) field observatory from 22 April to 19 July 2019. During the field campaign, water vapor profiles from the MPD were collected to complement the ARM/SGP temperature and water vapor profiles from the AERI, wind profiles from the DWL, and supplemental radiosondes, along with operational weather radar and surface station data. The impacts of assimilating AERI, MPD, and DWL are evaluated for a mesoscale convection initiation (CI) and precipitation event on 14 June 2019. Short-term forecasts of CI and precipitation are improved by assimilating all MPD and AERI profiling data in comparison to assimilating conventional observations and DWL. While AERI shows marginal impact on the forecasts of CI near the sites, assimilating the MPD water vapor profiles contributes the most to improving forecast skill over almost all forecast times and reflectivity thresholds. The data assimilation (DA) experiments show the development of moist absolutely unstable layers near the observing sites and MPD DA improved the vertical moisture profile, leading to an improvement of the southern CI forecasts for the MPD DA experiment. Furthermore, MPD DA additionally leads to improved CI forecasts north of the sites due to enhanced thermodynamic instability and modified wind field leading to convergence in the lower atmosphere.
• Keywords:
  Numerical weather forecasting Atmospheric Profilers Data Assimilation; Numerical Weather Prediction/Forecasting Lidar Observations Mesoscale Forecasting
• Source:
  Mon. Wea. Rev., 153, 1793–1813
• DOI:
  https://doi.org/10.1175/MWR-D-24-0233.1
• Format:
  PDF
• Document Type:
  Journal Article
• Funding:
  Grant no. NA19OAR4590320 ; Grant no. NA23OAR4590399
• Rights Information:
  Other
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:b7e3330ca573d9dee5878aaf5c259e15aa8615672633306dbb8f1fd5946bde46087801b406a159840d6d55a4542d58da1bb8b6f0d1efd1c814c5093de25f06a6
• File Type: