Water Vapor Variability in the Tropics Observed by Airborne Lidar and Modelling

Thanks to the capability of profiling simultaneously atmospheric backscatter and water vapor in regions of particular interest, an airborne water vapor lidar can help elucidate the key role of water vapor in the tropics, where its distribution is closely connected to the appearance of shallow and de...

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Bibliographic Details
Main Author: Kiemle, Christoph
Format: Conference Object
Language:unknown
Published: 2019
Subjects:
Online Access:https://elib.dlr.de/135009/
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Summary:Thanks to the capability of profiling simultaneously atmospheric backscatter and water vapor in regions of particular interest, an airborne water vapor lidar can help elucidate the key role of water vapor in the tropics, where its distribution is closely connected to the appearance of shallow and deep convection, interacts with the circulation through radiation, and affects the intensity of cloud feedbacks. The DLR water vapor differential absorption lidar WALES was operated on board the German research aircraft HALO during the NARVAL campaigns in December 2013 and in August 2016 in the Northern Tropical Atlantic east of Barbados. High horizontal and vertical water vapor variability is omnipresent and poses challenges to climate and weather models. It is caused by water vapor updrafts in both shallow and deep convective clouds with subsequent horizontal outflow at elevated levels. Out of the wealth of about 30 winter and 60 summer flight hours totaling 75,000 km of NARVAL lidar data, several lidar curtains from different flights are presented together with satellite cloud imagery and dropsonde profiles. With a vertical resolution of 300 m the lidar is able to detect small-scale vertical water vapor gradients and thin dry layers. It has the capability to obtain profiles within cloud gaps of 3 km minimum size. These characteristics allow unprecedented insights into water vapor distributions in the vicinity of shallow (trade clouds) and deep convection (ITCZ). The lidar data are compared with results from ICON model runs that are available at several grid spacings down to 300 m and include the area and period of the flight domains. For optimum interpretation, the comparisons are undertaken in the “moisture space” where all lidar and model water vapor profiles are sorted from the driest water vapor path to the moistest, and where cloud cover can be represented as an additional parameter. Across model grid spacing from 300 m to 2.5 km, ICON shows a good skill in reproducing lidar measurements of water vapor ...