A highly modular and scale-consistent Terrestrial Systems Modeling Platform (TerrSysMP) is presented. The modeling platform consists of an atmospheric model (Consortium for Small-Scale Modeling; COSMO), a land surface model (the NCAR Community Land Model, version 3.5; CLM3.5), and a 3D variably saturated groundwater flow model (ParFlow). An external coupler (Ocean Atmosphere Sea Ice Soil, version 3.0; OASIS3) with multiple executable approaches is employed to couple the three independently developed component models, which intrinsically allows for a separation of temporal–spatial modeling scales and the coupling frequencies between the component models.Idealized TerrSysMP simulations are presented, which focus on the interaction of key hydrologic processes, like runoff production (excess rainfall and saturation) at different hydrological modeling scales and the drawdown of the water table through groundwater pumping, with processes in the atmospheric boundary layer. The results show a strong linkage between integrated surface–groundwater dynamics, biogeophysical processes, and boundary layer evolution. The use of the mosaic approach for the hydrological component model (to resolve subgrid-scale topography) impacts simulated runoff production, soil moisture redistribution, and boundary layer evolution, which demonstrates the importance of hydrological modeling scales and thus the advantages of the coupling approach used in this study.Real data simulations were carried out with TerrSysMP over the Rur catchment in Germany. The inclusion of the integrated surface–groundwater flow model results in systematic patterns in the root zone soil moisture, which influence exchange flux distributions and the ensuing atmospheric boundary layer development. In a first comparison to observations, the 3D model compared to the 1D model shows slightly improved predictions of surface fluxes and a strong sensitivity to the initial soil moisture content.

Continental-scale hyper-resolution simulations constitute a grand challenge in characterizing nonlinear feedbacks of states and fluxes of the coupled water, energy, and biogeochemical cycles of terrestrial systems. Tackling this challenge requires advanced coupling and supercomputing technologies for earth system models that are discussed in this study, utilizing the example of the implementation of the newly developed Terrestrial Systems Modeling Platform (TerrSysMP v1.0) on JUQUEEN (IBM Blue Gene/Q) of the Jülich Supercomputing Centre, Germany. The applied coupling strategies rely on the Multiple Program Multiple Data (MPMD) paradigm using the OASIS suite of external couplers, and require memory and load balancing considerations in the exchange of the coupling fields between different component models and the allocation of computational resources, respectively. Using the advanced profiling and tracing tool Scalasca to determine an optimum load balancing leads to a 19% speedup. In massively parallel supercomputer environments, the coupler OASIS-MCT is recommended, which resolves memory limitations that may be significant in case of very large computational domains and exchange fields as they occur in these specific test cases and in many applications in terrestrial research. However, model I/O and initialization in the petascale range still require major attention, as they constitute true big data challenges in light of future exascale computing resources. Based on a factor-two speedup due to compiler optimizations, a refactored coupling interface using OASIS-MCT and an optimum load balancing, the problem size in a weak scaling study can be increased by a factor of 64 from 512 to 32 768 processes while maintaining parallel efficiencies above 80% for the component models.

Most 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 funded by the German national science foundation Deutsche Forschungsgemeinschaft (DFG), in order to focus and integrate research activities of several universities on an emerging scientific topic of high societal relevance. Aiming to bridge the gap between microscale soil pores and catchment-scale atmospheric variables, TR32 unites research groups from the German universities of Aachen, Bonn, and Cologne, and from the environmental and geoscience departments of Forschungszentrum Jülich GmbH. Here, we report about recent achievements in monitoring and modeling of the terrestrial system, including the development of new observation techniques for the subsurface, the establishment of cross-scale, multicompartment modeling platforms from the pore to the catchment scale, and their use to investigate the propagation of patterns in the state and structure of the subsurface to the atmospheric boundary layer.

Cloud and precipitation processes are still a main source of uncertainties in numerical weather prediction and climate change projections. The Priority Programme “Polarimetric Radar Observations meet Atmospheric Modelling (PROM)”, funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), is guided by the hypothesis that many uncertainties relate to the lack of observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Such observations can, however, at present be provided by the recently installed dual-polarization C-band weather radar network of the German national meteorological service in synergy with cloud radars and other instruments at German supersites and similar national networks increasingly available worldwide. While polarimetric radars potentially provide valuable in-cloud information on hydrometeor type, quantity, and microphysical cloud and precipitation processes, and atmospheric models employ increasingly complex microphysical modules, considerable knowledge gaps still exist in the interpretation of the observations and in the optimal microphysics model process formulations. PROM is a coordinated interdisciplinary effort to increase the use of polarimetric radar observations in data assimilation, which requires a thorough evaluation and improvement of parameterizations of moist processes in atmospheric models. As an overview article of the inter-journal special issue “Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes”, this article outlines the knowledge achieved in PROM during the past 2 years and gives perspectives for the next 4 years.

Aerosol particle number size distribution and chemical composition were measured at two low altitude sites, one urban and one relatively pristine valley, in Central Nepal during the 2009 pre-monsoon season (May–June). This is the first time that aerosol size distribution and chemical composition were measured simultaneously at lower elevations in the middle Himalayan region in Nepal. The aerosol size distribution was measured using a Scanning Mobility Particle Sizer (SMPS, 14–340 nm), and the chemical composition of the filter samples collected during the field campaign was analyzed in the laboratory. Teflon membrane filters were used for ion chromatography (IC) and water-soluble organic carbon and nitrogen analysis. Quartz fiber filters were used for organic carbon and elemental carbon analysis. Multi-lognormal fits to the measured aerosol size distribution indicated a consistent larger mode around 100 nm which is usually the oldest, most processed background aerosol. The smaller mode was located around 20 nm, which is indicative of fresh but not necessarily local aerosol. The diurnal cycle of the aerosol number concentration showed the presence of two peaks (early morning and evening), during the transitional periods of boundary layer growth and collapse. The increase in number concentration during the peak periods was observed for the entire size distribution. Although the possible contribution of local emissions in size ranges similar to the larger mode cannot be completely ruled out, another plausible explanation is the mixing of aged elevated aerosol in the residual layer during the morning period as suggested by previous studies. Similarly, the evening time concentration peaks when the boundary layer becomes shallow concurrent with increase in local activity. A decrease in aerosol number concentration was observed during the nighttime with the development of cold (downslope) mountain winds that force the low level warmer air in the valley to rise. The mountain valley wind mechanisms induced by the topography along with the valley geometry appear to have a strong control in the diurnal cycle of the aerosol size distribution. During the sampling period, the chemical composition of PM_2.5 was dominated by organic matter at both sites. Organic carbon (OC) comprised the major fraction (64–68%) of the aerosol concentration followed by ionic species (24–26%, mainly SO₄²⁻ and NH₄⁺). Elemental Carbon (EC) compromised 7–10% of the total composition and 27% of OC was found to be water soluble at both sites. The day-to-day variability observed in the time series of aerosol composition could be explained by the synoptic scale haze that extended to the sampling region from the Indian Gangetic Plain (IGP), and rainfall occurrence. In the presence of regional scale haze during dry periods, the mean volume aerosol concentration was found to increase and so did the aerosol mass concentrations.