Comment on acp-2022-159

Abstract

Lagrangian trajectories are frequently used to trace air parcels from the troposphere to the stratosphere through the tropical tropopause layer (TTL), and the coldest temperatures of these trajectories have been used to reconstruct water vapor variability in the lower stratosphere, where water vapor’s radiative impact on Earth’s surface is strongest. As such, the ability of these trajectories to accurately capture temperatures encountered by parcels in the TTL is crucial to water vapor reconstructions and calculations of water vapor’s radiative forcing. A potential source of error for trajectory calculations is the resolution of the input data. Here, we explore how improving the temporal and spatial resolution of model input data impacts the temperatures measured by Lagrangian trajectories that cross the TTL during boreal winter using ERA5 reanalysis data. We do so by comparing the temperature distribution of trajectories computed with data downsampled in either space or time to those computed with ERA5's maximum resolution. We find that improvements in temporal resolution from 6 hour to 3 or 1 hour lower the cold point temperature distribution, with the mean cold point temperature decreasing from 185.9 K to 185.0 K or 184.5 K for trajectories run during boreal winters of 2010 to 2019, while improvements to vertical resolution from that of MERRA2 data (the GEOS5 model grid) to full ERA5 resolution also lower the distribution but are of secondary importance, and improvements in horizontal resolution from 1° x 1° to 0.5° x 0.5° or 0.25° x 0.25° have negligible impacts. We suggest that this is caused by excess vertical dispersion near the tropopause when temporal resolution is degraded, which allows trajectories to cross the TTL without passing through the coldest regions, and by undersampling of the four--dimensional temperature field when either temporal or vertical resolution is reduced.