A Raman lidar to measure water vapor in the atmospheric boundary layer

Froidevaux, M.; Higgins, C. W.; Simeonov, V.; Ristori, P.; Pardyjak, Eric R.; Serikov, Ilya; Calhoun, Ronald; Bergh, Hubert van den; Parlange, Marc B.

doi:10.1016/j.advwatres.2012.04.008

Cited by 43 publications

(33 citation statements)

References 63 publications

(90 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The horizontal variations of the moisture fields can be detected with scanning lidar. Scanning WVRL measurements were used, for example, to observe the WV structures in the ABL (Goldsmith et al, 1998;Eichinger et al, 1999;Whiteman et al, 2006;Froidevaux et al, 2013;Matsuda, 2013) or to estimate latent heat fluxes at the surface (Eichinger et al, 2000). However, the SNR is still limited during daytime (Turner at al., 2002), making high-resolution scans under daylight conditions more difficult than with WVDIAL; and 3-D measurements of WVRL have not been demonstrated yet.…”

Section: F Späth Et Al: 3-d Water Vapor Field In the Atmospheric Bomentioning

confidence: 99%

3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar

et al. 2016

View full text Add to dashboard Cite

Abstract. High-resolution three-dimensional (3-D) water vapor data of the atmospheric boundary layer (ABL) are required to improve our understanding of land-atmosphere exchange processes. For this purpose, the scanning differential absorption lidar (DIAL) of the University of Hohenheim (UHOH) was developed as well as new analysis tools and visualization methods. The instrument determines 3-D fields of the atmospheric water vapor number density with a temporal resolution of a few seconds and a spatial resolution of up to a few tens of meters. We present three case studies from two field campaigns. In spring 2013, the UHOH DIAL was operated within the scope of the HD(CP) 2 Observational Prototype Experiment (HOPE) in western Germany. HD(CP) 2 stands for High Definition of Clouds and Precipitation for advancing Climate Prediction and is a German research initiative. Range-height indicator (RHI) scans of the UHOH DIAL show the water vapor heterogeneity within a range of a few kilometers up to an altitude of 2 km and its impact on the formation of clouds at the top of the ABL. The uncertainty of the measured data was assessed for the first time by extending a technique to scanning data, which was formerly applied to vertical time series. Typically, the accuracy of the DIAL measurements is between 0.5 and 0.8 g m −3 (or < 6 %) within the ABL even during daytime. This allows for performing a RHI scan from the surface to an elevation angle of 90 • within 10 min. In summer 2014, the UHOH DIAL participated in the Surface Atmosphere Boundary Layer Exchange (SABLE) campaign in southwestern Germany. Conical volume scans were made which reveal multiple water vapor layers in three dimensions. Differences in their heights in different directions can be attributed to different surface elevation. With low-elevation scans in the surface layer, the humidity profiles and gradients can be related to different land cover such as maize, grassland, and forest as well as different surface layer stabilities.

show abstract

Section: F Späth Et Al: 3-d Water Vapor Field In the Atmospheric Bomentioning

confidence: 99%

3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Crucial parts of these budgets are the advection terms 584 which are very difficult to measure. Higgins et al (2013) demonstrated the potential of scan-585 ning lidar systems for improving the estimation of advection. The LAFE design will enable us 586 to estimate this component with improved accuracy.…”

mentioning

confidence: 99%

A New Research Approach for Observing and Characterizing Land–Atmosphere Feedback

Wulfmeyer

Turner

Baker

et al. 2018

Bulletin of the American Meteorological Society

View full text Add to dashboard Cite

38Forecast errors with respect to wind, temperature, moisture, clouds, and precipitation largely 39 correspond to the limited capability of current earth system models to capture and simulate 40 land-atmosphere feedback. To facilitate its realistic simulation in next generation models, an 41 improved process understanding of the related complex interactions is essential. To this end, 42 accurate 3D observations of key variables in the land-atmosphere (L-A) system with high 43 vertical and temporal resolution from the surface to the free troposphere are indispensable. 44Recently, we developed a synergy of innovative ground-based, scanning active remote sens-45 ing systems for 2D to 3D measurements of wind, temperature, and water vapor from the sur-46 face to the lower troposphere that is able to provide comprehensive data sets for characteriz-47 Motivation 71The land-atmosphere (L-A) system includes the soil, the land cover such as vegetation, and 72 the overlying atmosphere. The interaction of variables, e.g. related to the water and energy 73 budgets, results in characteristic natural variabilities and regimes as well as their changes due 74 to anthropogenic influences. The planetary boundary layer (PBL) is part of the L-A system 75 and represents the interface between the land surface and the free troposphere. Through an 76 exchange of momentum, energy and water, the dynamics, the thermodynamic structure, and 77 the evolution of the PBL affect the formation of shallow and deep clouds, convection initia-78 tion, and thus precipitation (Sherwood et al. 2010, Behrendt et al. 2011, Santanello et al. 79 2011, van den Hurk et al. 2011. One of the most complex feedback 80 loops is between soil moisture and precipitation (Seneviratne et al. 2010, Guillod et al. 2015, 81 Santanello et al. 2017). Precipitation can be influenced directly by the surface fluxes (Ek and 82Holtslag 2004), and indirectly via PBL dynamics and mesoscale circulations (Taylor et al. 83 2012). 84The PBL state and its evolution are strongly influenced by non-linear feedbacks in the L-A 85 system. These are due to two-way interactions between radiation, soil, vegetation, and atmos-86 pheric variables, which result in the diurnal cycles of surface fluxes. The feedbacks are rele-87 vant from local to global scales (Mahmood et al. 2013, Stéfanon et al. 2014, and their 88 strength varies both regionally and seasonally in dependence of soil moisture, advection, and 89 climate regimes. In locations where these feedbacks play an important role, it is likely that 90 they will become even more important due to anthropogenic climate change (Dirmeyer et al. 91 2012). Thus, to improve our understanding of the state and the evolution of the L-A system as 92 well as the dynamics and thermodynamics of the PBL, it is critical that feedbacks and fluxes 93 between the different components, including entrainment at the top of the PBL, are well char-94 4 acterized and appropriately represented in weather, climate, and earth system models (e.g., 95 Se...

show abstract

“…In the summer of 2008, four eddy covariance towers were installed near a small lake in northwestern Switzerland (Froidevaux et al 2013). On each tower, a Campbell Scientific CSAT3 sonic anemometer was coupled to a LI-COR LI-7500 open path gas analyzer and sampled at 20 Hz.…”

Section: Field Experimentsmentioning

confidence: 99%

“…While each of these studies provided unique insights, each study also indicated that the advection of water vapor and heat, due to underlying land surface variability, could be a potential energy pathway that is not typically measured. Interpreting advective effects on evaporation measurements becomes paramount in reservoirs and irrigated fields and has been the focus of several studies (Alfieri et al 2012;Figuerola and Berliner 2005;Hanks et al 1971;Prueger et al 1996;Tanny et al 2008;Zermeño-Gonzalez and Hipps 1997).…”

Section: Introductionmentioning

confidence: 99%

Measured and Estimated Water Vapor Advection in the Atmospheric Surface Layer

Higgins

Pardyjak

Froidevaux

et al. 2013

Journal of Hydrometeorology

Self Cite

View full text Add to dashboard Cite

The flux of water vapor due to advection is measured using high-resolution Raman lidar that was orientated horizontally across a land-lake transition. At the same time, a full surface energy balance is performed to assess the impact of scalar advection on energy budget closure. The flux of water vapor due to advection is then estimated with analytical solutions to the humidity transport equation that show excellent agreement with the field measurements. Although the magnitude of the advection was not sufficient to account for the total energy deficit for this field site, the analytical approach is used to explore situations where advection would be the dominant transport mechanism. The authors find that advection is at maximum when the measurement height is 0.036 times the distance to a land surface transition. The framework proposed in this paper can be used to predict the potential impact of advection on surface flux measurements prior to field deployment and can be used as a data analysis algorithm to calculate the flux of water vapor due to advection from field measurements.

show abstract

A Raman lidar to measure water vapor in the atmospheric boundary layer

Cited by 43 publications

References 63 publications

3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar

3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar

A New Research Approach for Observing and Characterizing Land–Atmosphere Feedback

Measured and Estimated Water Vapor Advection in the Atmospheric Surface Layer

Contact Info

Product

Resources

About