| Autor: |
Späth, Florian, Rajtschan, Verena, Weber, Tobias K. D., Morandage, Shehan, Lange, Diego, Abbas, Syed Saqlain, Behrendt, Andreas, Ingwersen, Joachim, Streck, Thilo, Wulfmeyer, Volker |
| Předmět: |
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| Zdroj: |
Geoscientific Instrumentation, Methods & Data Systems (GI); 2023, Vol. 12 Issue 1, p25-44, 20p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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