The land–atmosphere feedback observatory: a new observational approach for characterizing land–atmosphere feedback
-
Published:2023-01-25
Issue:1
Volume:12
Page:25-44
-
ISSN:2193-0864
-
Container-title:Geoscientific Instrumentation, Methods and Data Systems
-
language:en
-
Short-container-title:Geosci. Instrum. Method. Data Syst.
Author:
Späth FlorianORCID, Rajtschan VerenaORCID, Weber Tobias K. D.ORCID, Morandage Shehan, Lange DiegoORCID, Abbas Syed Saqlain, Behrendt AndreasORCID, Ingwersen Joachim, Streck ThiloORCID, Wulfmeyer VolkerORCID
Abstract
Abstract. Important topics in land–atmosphere (L–A) feedback research are water and energy balances and heterogeneities of fluxes at the land surface and in the atmospheric boundary layer (ABL). To target these questions, the Land–Atmosphere Feedback Observatory (LAFO) has been installed in southwestern Germany. The instrumentation allows comprehensive and high-resolution measurements from the bedrock to the lower free troposphere. Grouped into three components, atmosphere, soil and land surface, and vegetation, the LAFO observation strategy aims for simultaneous measurements in all three compartments. For this purpose the LAFO sensor synergy contains lidar systems to measure the atmospheric key variables of humidity, temperature and wind. At the land surface, eddy covariance stations are operated to record the energy distribution of radiation, sensible, latent and ground heat fluxes. Together with a water and temperature sensor network, the soil water content and temperature are monitored in the agricultural investigation area. As for vegetation, crop height, leaf area index and phenological growth stage values are registered. The observations in LAFO are organized into operational measurements and
intensive observation periods (IOPs). Operational measurements aim for long
time series datasets to investigate statistics, and we present as an example the correlation between mixing layer height and surface fluxes. The potential of IOPs is demonstrated with a 24 h case study using dynamic and thermodynamic profiles with lidar and a surface layer observation that uses the scanning differential absorption lidar to relate atmospheric humidity patterns to soil water structures. Both IOPs and long-term observations will provide new insight into exchange
processes and their statistics for improving the representation of L–A feedbacks in climate and numerical weather prediction models. The lidar component in particular will support the investigation of coupling to the
atmosphere.
Publisher
Copernicus GmbH
Subject
Atmospheric Science,Geology,Oceanography
Reference90 articles.
1. Adam, S., Behrendt, A., Schwitalla, T., Hammann, E., and Wulfmeyer, V.: First
assimilation of temperature lidar data into a numerical weather prediction
model: Impact on the simulation of the temperature field, inversion strength, and planetary boundary layer depth. Q. J. Roy. Meteorol. Soc., 142, 2882–2896, https://doi.org/10.1002/qj.2875, 2016. 2. Anderegg, W. R. L., Anderegg, L. D. L., Kerr, K. L., and Trugman, A. T.:
Widespread drought-induced tree mortality at dry range edges indicates that
climate stress exceeds species' compensating mechanisms, Global Change Biol., 25, 3793–3802, https://doi.org/10.1111/gcb.14771, 2019. 3. Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S.,
Anthoni, P., Bernhofer, Ch., Davis, K., Evans, R., Fuentes, J., Goldstein,
A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel,
W., Paw U, K. T., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S.,
Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: A New Tool to Study the
Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water
Vapor, and Energy Flux Densities, B. Am. Meteorol. Soc., 82, 2415–2434, https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2, 2001. 4. Behrendt, A., Wulfmeyer, V., Hammann, E., Muppa, S. K., and Pal, S.: Profiles of second- to fourth-order moments of turbulent temperature fluctuations in the convective boundary layer: first measurements with rotational Raman lidar, Atmos. Chem. Phys., 15, 5485–5500, https://doi.org/10.5194/acp-15-5485-2015, 2015. 5. Behrendt, A., Wulfmeyer, V., Senff, C., Muppa, S. K., Späth, F., Lange,
D., Kalthoff, N., and Wieser, A.: Observation of sensible and latent heat
flux profiles with lidar, Atmos. Meas. Tech., 13, 3221–3233,
https://doi.org/10.5194/amt-13-3221-2020, 2020.
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|