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Airborne Lidar Observations of Water Vapor Variability in Tropical Shallow Convective Environment

Kiemle, Christoph and Groß, Silke and Wirth, Martin and Bugliaro Goggia, Luca (2017) Airborne Lidar Observations of Water Vapor Variability in Tropical Shallow Convective Environment. Surveys in Geophysics, 38, pp. 1425-1433. Springer. doi: 10.1007/s10712-017-9431-5. ISSN 0169-3298.

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Official URL: https://link.springer.com/article/10.1007/s10712-017-9431-5

Abstract

An airborne downward-pointing water vapor lidar provides two-dimensional, simultaneous curtains of atmospheric backscatter and humidity along the flight track with high accuracy and spatial resolution. In order to improve the knowledge on the coupling between clouds, circulation and climate in the trade wind region, the DLR (Deutsches Zentrum für Luft- und Raumfahrt) water vapor lidar was operated on board the German research aircraft HALO during the NARVAL (Next Generation Aircraft Remote Sensing for Validation Studies) field experiment in December 2013. Out of the wealth of about 30 flight hours or 25,000 km of data over the Tropical Atlantic Ocean east of Barbados, three 2-h-long, representative segments from different flights were selected. Analyses of Meteosat Second Generation images and dropsondes complement this case study. All observations indicate a high heterogeneity of the humidity in the lowest 4 km of the tropical troposphere, as well as of the depth of the cloud (1–2 km thick) and sub-cloud layer (1 km thick). At the winter trade inversion with its strong humidity jump of up to 9 g/kg in water vapor mixing ratio, the mixing ratio variance can attain 9 (g/kg)2, while below it typically ranges between 1 and 3 (g/kg)2. Layer depths and partial water vapor columns within the layers vary by up to a factor of 2. This affects the total tropospheric water vapor column, amounting on average to 28 kg/m2, by up to 10 kg/m2 or 36%. The dominant scale of the variability is given by the extent of regions with higher-than-average humidity and lies between 300 and 600 km. The variability mainly stems from the alternation between dry regions and moisture lifted by convection. Occasionally, up to 100-km large dry regions are observed. In between, convection pushes the trade inversion upward, sharpening the vertical moisture gradient that is colocated with the trade inversion. In most of the water vapor profiles, this gradient is stronger than the one located at the top of the sub-cloud layer. Lidar observations in concert with models accurately reproducing the observed variability are expected to help evaluate the role these findings play for climate.

Item URL in elib:https://elib.dlr.de/116529/
Document Type:Article
Additional Information:Vgl. auch spätere Veröffentlichung in einem Fachbuch, https://elib.dlr.de/120798/
Title:Airborne Lidar Observations of Water Vapor Variability in Tropical Shallow Convective Environment
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Kiemle, ChristophDLR, IPAhttps://orcid.org/0000-0003-1231-2813UNSPECIFIED
Groß, SilkeDLR, IPAUNSPECIFIEDUNSPECIFIED
Wirth, MartinDLR, IPAUNSPECIFIEDUNSPECIFIED
Bugliaro Goggia, LucaDLR, IPAhttps://orcid.org/0000-0003-4793-0101UNSPECIFIED
Date:October 2017
Journal or Publication Title:Surveys in Geophysics
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:38
DOI:10.1007/s10712-017-9431-5
Page Range:pp. 1425-1433
Publisher:Springer
ISSN:0169-3298
Status:Published
Keywords:Airborne lidar, Water vapor lidar, Shallow convection, Trade wind region, Cloud layer
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - LIDAR research and development
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Lidar
Institute of Atmospheric Physics > Atmospheric Remote Sensing
Deposited By: Kiemle, Dr.rer.nat. Christoph
Deposited On:04 Dec 2017 11:58
Last Modified:02 Nov 2023 13:14

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