Jan H. Schween

Monitoring and Modeling the Terrestrial System from Pores to Catchments: The Transregional Collaborative Research Center on Patterns in the Soil–Vegetation–Atmosphere System

AbstractMost activities of humankind take place in the transition zone between four compartments of the terrestrial system: the unconfined aquifer, including the unsaturated zone; surface water; vegetation; and atmosphere. The mass, momentum, and heat energy fluxes between these compartments drive their mutual state evolution. Improved understanding of the processes that drive these fluxes is important for climate projections, weather prediction, flood forecasting, water and soil resources management, agriculture, and water quality control. The different transport mechanisms and flow rates within the compartments result in complex patterns on different temporal and spatial scales that make predictions of the terrestrial system challenging for scientists and policy makers. The Transregional Collaborative Research Centre 32 (TR32) was formed in 2007 to integrate monitoring with modeling and data assimilation in order to develop a holistic view of the terrestrial system. TR32 is a long-term research program ...

JOYCE: Jülich Observatory for Cloud Evolution

AbstractThe Julich Observatory for Cloud Evolution (JOYCE), located at Forschungszentrum Julich in the most western part of Germany, is a recently established platform for cloud research. The main objective of JOYCE is to provide observations, which improve our understanding of the cloudy boundary layer in a midlatitude environment. Continuous and temporally highly resolved measurements that are specifically suited to characterize the diurnal cycle of water vapor, stability, and turbulence in the lower troposphere are performed with a special focus on atmosphere–surface interaction. In addition, instruments are set up to measure the micro- and macrophysical properties of clouds in detail and how they interact with different boundary layer processes and the large-scale synoptic situation. For this, JOYCE is equipped with an array of state-of-the-art active and passive remote sensing and in situ instruments, which are briefly described in this scientific overview. As an example, a 24-h time series of the ev...

Large-Eddy Atmosphere–Land-Surface Modelling over Heterogeneous Surfaces: Model Development and Comparison with Measurements

A model is developed for the large-eddy simulation (LES) of heterogeneous atmosphere and land-surface processes. This couples a LES model with a land-surface scheme. New developments are made to the land-surface scheme to ensure the adequate representation of atmosphere–land-surface transfers on the large-eddy scale. These include, (1) a multi-layer canopy scheme; (2) a method for flux estimates consistent with the large-eddy subgrid closure; and (3) an appropriate soil-layer configuration. The model is then applied to a heterogeneous region with 60-m horizontal resolution and the results are compared with ground-based and airborne measurements. The simulated sensible and latent heat fluxes are found to agree well with the eddy-correlation measurements. Good agreement is also found in the modelled and observed net radiation, ground heat flux, soil temperature and moisture. Based on the model results, we study the patterns of the sensible and latent heat fluxes, how such patterns come into existence, and how large eddies propagate and destroy land-surface signals in the atmosphere. Near the surface, the flux and land-use patterns are found to be closely correlated. In the lower boundary layer, small eddies bearing land-surface signals organize and develop into larger eddies, which carry the signals to considerably higher levels. As a result, the instantaneous flux patterns appear to be unrelated to the land-use patterns, but on average, the correlation between them is significant and persistent up to about 650 m. For a given land-surface type, the scatter of the fluxes amounts to several hundred W

Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity

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Investigating Water Vapor Variability by Ground-Based Microwave Radiometry: Evaluation Using Airborne Observations

, due to (1) large-eddy randomness; (2) rapid large-eddy and surface feedback; and (3) local advection related to surface heterogeneity.

Heat and moisture budgets from airborne measurements and high-resolution model simulations

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) programs Raman lidar at the ARM Southern Great Plains site in north central Oklahoma has collected water vapor mixing ratio (q) profile data more than 90% of the time since October 2004. Three hundred (300) cases were identified where the convective boundary layer was quasi-stationary and well mixed for a 2 h period, and q mean, variance, third-order moment, and skewness profiles were derived from the 10 s, 75 m resolution data. These cases span the entire calendar year, and demonstrate that the q variance profiles at the mixed layer (ML) top changes seasonally and is strongly related to the gradient of q across the interfacial layer. The q variance at the top of the ML shows only weak correlations (r < 0.3) with sensible heat flux, Deardorff convective velocity scale, and turbulence kinetic energy measured at the surface. The median q skewness profile is most negative at 0.85 zi, zero at approximately zi, and positive above zi, where zi is the depth of the convective ML. The spread in the q skewness profiles is smallest between 0.95 zi and zi. The q skewness at altitudes between 0.6 zi and 1.2 zi is correlated with the magnitude of the q variance at zi, with increasingly negative values of skewness observed lower down in the ML as the variance at zi increases, suggesting that in cases with larger variance at zi there is deeper penetration of the warm, dry free tropospheric air into the ML.

AWARDS: Advanced microwave radiometers for deep space stations

Sun-induced chlorophyll fluorescence (F) is a novel remote sensing parameter providing an estimate of actual photosynthetic rates. A combination of this new observable and Monteith’s light use efficiency (LUE) concept was suggested for an advanced modeling of gross primary productivity (GPP). In this demonstration study, we evaluate the potential of both F and the more commonly used photochemical reflectance index (PRI) to approximate the LUE term in Monteith’s equation and eventually improve the forward modeling of GPP diurnals. Both F and the PRI were derived from ground and airborne based spectrometer measurements over two different crops. We demonstrate that approximating dynamic changes of LUE using F and PRI significantly improves the forward modeling of GPP diurnals. Especially in sugar beet, a changing photosynthetic efficiency during the day was traceable with F and incorporating F in the forward modeling significantly improved the estimation of GPP. Airborne data were projected to produce F and PRI maps for winter wheat and sugar beet fields over the course of one day. We detected a significant variability of both, F and the PRI within one field and particularly between fields. The variability of F and PRI was higher in sugar beet, which also showed a physiological down-regulation of leaf photosynthesis. Our results underline the potential of F to serve as a superior indicator for the actual efficiency of the photosynthetic machinery, which is linked to physiological responses of vegetation.

Diurnal Dynamics of Wheat Evapotranspiration Derived from Ground-Based Thermal Imagery

We present a method for deriving horizontal-humidity variability from a single-scanning passive microwave radiometer (MWR). The MWR used has full scanning capabilities in azimuth and elevation and is sensitive to the path of integrated water vapor as well as cloud liquid water. Applying a simple linear-gradient model together with an assumed vertical profile derived from the closest radiosonde ascent, the strength and direction of the horizontal-humidity gradient can be determined with a temporal resolution on the order of 15-20 min. For the case of an approaching frontal system, the derived humidity field can explain up to 88% of the measured humidity variance-the missing variance can most probably be attributed to convective activity.