27 Sep 2023
 | 27 Sep 2023

Influence of radiosonde observations on the sharpness and altitude of the midlatitude tropopause in the ECMWF IFS

Konstantin Krüger, Andreas Schäfler, Martin Weissmann, and George C. Craig

Abstract. Initial conditions of current numerical weather prediction systems insufficiently represent the sharp vertical gradients across the midlatitude tropopause. Data assimilation may provide a means to improve the tropopause structure by correcting the erroneous background forecast towards the observations. In this paper, the influence of assimilating radiosonde observations on the tropopause structure, i.e., the sharpness and altitude, is investigated in the ECMWF IFS. We evaluate 9729 midlatitude radiosondes launched during one month in autumn 2016. About 500 of these radiosondes, launched on request during the North Atlantic Waveguide Downstream impact Experiment (NAWDEX) field campaign, were used to set up an observing system experiment (OSE). The OSE comprises two cycled assimilation forecast experiments, one with and one without the non-operational soundings. The influence on the tropopause is assessed in a statistical, tropopause–relative evaluation of observation departures of temperature, static stability (N2), wind speed and wind shear from the background forecast and the analysis. The background temperature is overestimated at the tropopause (warm bias, ~1 K) and underestimated in the lower stratosphere (cold bias, −0.3 K) leading to an underestimation of the abrupt vertical increase of N2 at the tropopause. We show that the increments (differences of analysis and background) reduce background biases and improve the tropopause sharpness. Profiles with sharper tropopause exhibit stronger background biases and, in turn, an increased positive influence of the observations on temperature and N2 in the analysis. Wind speed is underestimated in the background, especially in the upper troposphere (~1 m s−1), but the assimilation improves the wind profile. For the strongest winds the background bias is roughly halved. The positive influence on the analysis wind distribution is associated with an increase of vertical wind speed shear, which is underestimated above the tropopause. In addition to the tropopause sharpening, we detect a shift of the analysis tropopause altitude towards the observations. The comparison of the OSE runs highlights that the main contribution to the tropopause sharpening can be attributed to the radiosondes. This study shows that data assimilation improves wind and temperature gradients across the tropopause, but the sharpening is small compared to the model biases. Hence, the analysis still systematically underestimates the tropopause sharpness which may negatively impact weather and climate forecasts.

Konstantin Krüger et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2094', Anonymous Referee #1, 13 Nov 2023
  • RC2: 'Comment on egusphere-2023-2094', Anonymous Referee #2, 20 Nov 2023

Konstantin Krüger et al.

Konstantin Krüger et al.


Total article views: 261 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
196 57 8 261 3 4
  • HTML: 196
  • PDF: 57
  • XML: 8
  • Total: 261
  • BibTeX: 3
  • EndNote: 4
Views and downloads (calculated since 27 Sep 2023)
Cumulative views and downloads (calculated since 27 Sep 2023)

Viewed (geographical distribution)

Total article views: 248 (including HTML, PDF, and XML) Thereof 248 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 29 Nov 2023
Short summary
Initial conditions of current numerical weather prediction models insufficiently represent the sharp vertical gradients across the midlatitude tropopause. Observation-space data assimilation output is used to study the influence of assimilated radiosondes on the tropopause. The radiosondes reduce systematic biases of the model background and sharpen temperature and wind gradients in the analysis. Tropopause sharpness is still underestimated in the analysis, which may impact weather forecasts.