Preprints
https://doi.org/10.5194/gmd-2022-18
https://doi.org/10.5194/gmd-2022-18
Submitted as: model experiment description paper
06 Apr 2022
Submitted as: model experiment description paper | 06 Apr 2022
Status: this preprint was under review for the journal GMD but the revision was not accepted.

Intercomparing radar data assimilation systems for ICE-POP 2018 snowfall cases

Ki-Hong Min1,2, Kao-Shen Chung3, Ji-Won Lee1,2, Cheng-Rong You3, and Gyuwon Lee1,2 Ki-Hong Min et al.
  • 1Department of Atmospheric Sciences, Kyungpook National University, Daegu, 41566, Korea
  • 2Center for Atmospheric Remote Sensing, Kyungpook National University, Daegu, South Korea
  • 3Department of Atmospheric Sciences, National Central University, Jhung-li, 320, Taiwan

Abstract. Gangwon-do (GWD) has complex terrain and surface characteristics due to its location to the East Sea and the Taebaek Mountain range. This coastal location and rugged terrain can amplify snowfall mechanisms, making it challenging to accurately predict the amount and location. This study compares two methods for assimilating radar data and analyzed snowfall prediction results. The two methods compared are local ensemble transform Kalman filter (LETKF) and three-dimensional variational (3DVAR) data assimilation (DA). LETKF improved the water vapor amount and temperature using the covariance of the ensemble members, but 3DVAR improved the water vapor mixing ratio and temperature through an operator that assumed the atmosphere was saturated when reflectivity was above a certain threshold. In 2018, to understand the snowfall in GWD region and support the Pyeongchang Winter Olympic and Paralympic Games, a long-term heavy snow observation campaign was conducted. The International Collaborative Experiments for the 2018 Pyeongchang Olympic Games Projects (ICE-POP 2018) data are used to study and verify the numerical experiments. From the initial field verification using ICE-POP observation data (radiosonde), wind in LETKF was more accurately simulated than 3DVAR, but it underestimated the water vapor amount and temperature in the lower troposphere due to a lack of a water vapor and temperature observation operator. Snowfall in GWD was less simulated in LETKF, whereas snowfall of 10.0 mm or more was simulated in 3DVAR, resulting in an error of 2.62 mm lower than LETKF. The results signify that water vapor assimilation is important in radar DA and significantly impacts precipitation forecasts, regardless of the DA method used. Therefore, it is necessary to apply observation operators for water vapor and temperature in radar DA.

Ki-Hong Min et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • EC1: 'Comment on gmd-2022-18', Yuefei Zeng, 22 Apr 2022
    • AC1: 'Reply on EC1', Ki-Hong Min, 12 May 2022
  • RC1: 'Comment on gmd-2022-18', Anonymous Referee #1, 16 May 2022
    • AC2: 'Reply on RC1', Ki-Hong Min, 20 Jun 2022
    • AC5: 'Reply on RC1', Ki-Hong Min, 20 Jun 2022
  • RC2: 'Comment on gmd-2022-18', Anonymous Referee #2, 21 May 2022
    • AC3: 'Reply on RC2', Ki-Hong Min, 20 Jun 2022
    • AC6: 'Reply on RC2', Ki-Hong Min, 20 Jun 2022
    • AC7: 'Reply on RC2', Ki-Hong Min, 20 Jun 2022
  • RC3: 'Comment on gmd-2022-18', Anonymous Referee #3, 31 May 2022
    • AC4: 'Reply on RC3', Ki-Hong Min, 20 Jun 2022
    • AC8: 'Reply on RC3', Ki-Hong Min, 20 Jun 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • EC1: 'Comment on gmd-2022-18', Yuefei Zeng, 22 Apr 2022
    • AC1: 'Reply on EC1', Ki-Hong Min, 12 May 2022
  • RC1: 'Comment on gmd-2022-18', Anonymous Referee #1, 16 May 2022
    • AC2: 'Reply on RC1', Ki-Hong Min, 20 Jun 2022
    • AC5: 'Reply on RC1', Ki-Hong Min, 20 Jun 2022
  • RC2: 'Comment on gmd-2022-18', Anonymous Referee #2, 21 May 2022
    • AC3: 'Reply on RC2', Ki-Hong Min, 20 Jun 2022
    • AC6: 'Reply on RC2', Ki-Hong Min, 20 Jun 2022
    • AC7: 'Reply on RC2', Ki-Hong Min, 20 Jun 2022
  • RC3: 'Comment on gmd-2022-18', Anonymous Referee #3, 31 May 2022
    • AC4: 'Reply on RC3', Ki-Hong Min, 20 Jun 2022
    • AC8: 'Reply on RC3', Ki-Hong Min, 20 Jun 2022

Ki-Hong Min et al.

Ki-Hong Min et al.

Viewed

Total article views: 636 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
468 139 29 636 6 5
  • HTML: 468
  • PDF: 139
  • XML: 29
  • Total: 636
  • BibTeX: 6
  • EndNote: 5
Views and downloads (calculated since 06 Apr 2022)
Cumulative views and downloads (calculated since 06 Apr 2022)

Viewed (geographical distribution)

Total article views: 584 (including HTML, PDF, and XML) Thereof 584 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 29 Oct 2022
Download
Short summary
LETKF underestimated the water vapor mixing ratio and temperature compared to 3DVAR due to a lack of a water vapor mixing ratio and temperature observation operator. Snowfall in GWD was less simulated in LETKF. The results signify that water vapor assimilation is important in radar DA and significantly impacts precipitation forecasts, regardless of the DA method used. Therefore, it is necessary to apply observation operators for water vapor mixing ratio and temperature in radar DA.