TY - JOUR
T1 - The impact of temperature vertical structure on trajectory modeling of stratospheric water vapor
AU - Wang, T.
AU - Dessler, A. E.
AU - Schoeberl, M. R.
AU - Randel, W. J.
AU - Kim, J. E.
N1 - Publisher Copyright:
© 2015 Author(s). CC Attribution 3.0 License.
PY - 2015/3/31
Y1 - 2015/3/31
N2 - Lagrangian trajectories driven by reanalysis meteorological fields are frequently used to study water vapor (H2O) in the stratosphere, in which the tropical cold-point temperatures regulate the amount of H2O entering the stratosphere. Therefore, the accuracy of temperatures in the tropical tropopause layer (TTL) is of great importance for understanding stratospheric H2O abundances. Currently, most reanalyses, such as the NASA MERRA (Modern Era Retrospective - analysis for Research and Applications), only provide temperatures with ∼1.2 km vertical resolution in the TTL, which has been argued to miss finer vertical structure in the tropopause and therefore introduce uncertainties in our understanding of stratospheric H2O. In this paper, we quantify this uncertainty by comparing the Lagrangian trajectory prediction of H2O using MERRA temperatures on standard model levels (traj.MER-T) to those using GPS temperatures at finer vertical resolution (traj.GPS-T), and those using adjusted MERRA temperatures with finer vertical structures induced by waves (traj.MER-Twave). It turns out that by using temperatures with finer vertical structure in the tropopause, the trajectory model more realistically simulates the dehydration of air entering the stratosphere. But the effect on H2O abundances is relatively minor: compared with traj.MER-T, traj.GPS-T tends to dry air by ∼0.1 ppmv, while traj.MERTwave tends to dry air by 0.2-0.3 ppmv. Despite these differences in absolute values of predicted H2O and vertical dehydration patterns, there is virtually no difference in the interannual ariability in different runs. Overall, we find that a tropopause temperature with finer vertical structure has limited impact on predicted stratospheric H2O.
AB - Lagrangian trajectories driven by reanalysis meteorological fields are frequently used to study water vapor (H2O) in the stratosphere, in which the tropical cold-point temperatures regulate the amount of H2O entering the stratosphere. Therefore, the accuracy of temperatures in the tropical tropopause layer (TTL) is of great importance for understanding stratospheric H2O abundances. Currently, most reanalyses, such as the NASA MERRA (Modern Era Retrospective - analysis for Research and Applications), only provide temperatures with ∼1.2 km vertical resolution in the TTL, which has been argued to miss finer vertical structure in the tropopause and therefore introduce uncertainties in our understanding of stratospheric H2O. In this paper, we quantify this uncertainty by comparing the Lagrangian trajectory prediction of H2O using MERRA temperatures on standard model levels (traj.MER-T) to those using GPS temperatures at finer vertical resolution (traj.GPS-T), and those using adjusted MERRA temperatures with finer vertical structures induced by waves (traj.MER-Twave). It turns out that by using temperatures with finer vertical structure in the tropopause, the trajectory model more realistically simulates the dehydration of air entering the stratosphere. But the effect on H2O abundances is relatively minor: compared with traj.MER-T, traj.GPS-T tends to dry air by ∼0.1 ppmv, while traj.MERTwave tends to dry air by 0.2-0.3 ppmv. Despite these differences in absolute values of predicted H2O and vertical dehydration patterns, there is virtually no difference in the interannual ariability in different runs. Overall, we find that a tropopause temperature with finer vertical structure has limited impact on predicted stratospheric H2O.
UR - https://www.scopus.com/pages/publications/84926058960
U2 - 10.5194/acp-15-3517-2015
DO - 10.5194/acp-15-3517-2015
M3 - Article
AN - SCOPUS:84926058960
SN - 1680-7316
VL - 15
SP - 3517
EP - 3526
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
IS - 6
ER -