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The Towards an Optimal estimation based Snow Characterization Algorithm (TOSCA) project addresses possible novel measurement synergies for deriving snowfall microphysical parameters from the ground by combining the unique information obtained from a suite of ground-based sensors: microwave radiometers (22–150 GHz), 24- and 36-GHz radar, lidar, and in situ optical disdrometer methods. During the winter of 2008/09, such instruments were deployed at the Environmental Research Station Schneefernerhaus (UFS; at 2650 m MSL) at the Zugspitze Mountain in Germany for deriving microphysical properties of snowfall. This contribution gives an overview of the measurements carried out and discusses the potential for the developments of synergetic retrieval algorithms for deriving snow water content within the vertical column. The identification of potentially valuable ground-based instrument synergy for the retrieval of snowfall parameters from the surface will also be of importance for the development of new space-borne observational techniques. Microwave radiometer measurements show that brightness temperature enhancements at 90 and 150 GHz are correlated with the radar-derived snow water path, which is supported by radiative transfer simulations. The synergy of these measurements toward an improved snow mass content, however, needs to be augmented by knowledge on water vapor, supercooled liquid water, particle size distribution, and shape, thus making clear the necessity of synergetic remote sensing and in situ measurements. The radiometric measurements also reveal the very frequent presence of supercooled water within snow clouds and its importance to microphysical diffusion and aggregation growth of snow crystals. Analysis of the disdrometer measurements shows a “secondary aggregation peak” around −12° to −15°C, a temperature range where the Wegener–Bergeron–Findeisen process is most effective and typically dendrite snow crystals forms dominate.
The Towards an Optimal estimation based Snow Characterization Algorithm (TOSCA) project addresses possible novel measurement synergies for deriving snowfall microphysical parameters from the ground by combining the unique information obtained from a suite of ground-based sensors: microwave radiometers (22–150 GHz), 24- and 36-GHz radar, lidar, and in situ optical disdrometer methods. During the winter of 2008/09, such instruments were deployed at the Environmental Research Station Schneefernerhaus (UFS; at 2650 m MSL) at the Zugspitze Mountain in Germany for deriving microphysical properties of snowfall. This contribution gives an overview of the measurements carried out and discusses the potential for the developments of synergetic retrieval algorithms for deriving snow water content within the vertical column. The identification of potentially valuable ground-based instrument synergy for the retrieval of snowfall parameters from the surface will also be of importance for the development of new space-borne observational techniques. Microwave radiometer measurements show that brightness temperature enhancements at 90 and 150 GHz are correlated with the radar-derived snow water path, which is supported by radiative transfer simulations. The synergy of these measurements toward an improved snow mass content, however, needs to be augmented by knowledge on water vapor, supercooled liquid water, particle size distribution, and shape, thus making clear the necessity of synergetic remote sensing and in situ measurements. The radiometric measurements also reveal the very frequent presence of supercooled water within snow clouds and its importance to microphysical diffusion and aggregation growth of snow crystals. Analysis of the disdrometer measurements shows a “secondary aggregation peak” around −12° to −15°C, a temperature range where the Wegener–Bergeron–Findeisen process is most effective and typically dendrite snow crystals forms dominate.
Clouds cause uncertainties in the determination of climate sensitivity to either natural or anthropogenic changes. Furthermore, clouds dominate our perception of the weather, and the relatively poor forecast of cloud and precipitation parameters in numerical weather prediction (NWP) models is striking. In order to improve modeling and forecasting of clouds in climate and NWP models the BALTEX BRIDGE Campaign (BBC) was conducted in the Netherlands in August/September 2001 as a contribution to the main field experiment of the Baltic Sea Experiment (BALTEX) from April 1999 to March 2001 (BRIDGE). The complex cloud processes, which involve spatial scales from less than 1 mm (condensation nuclei) to 1000 km (frontal systems) require an integrated measurement approach. Advanced remote sensing instruments were operated at the central facility in Cabauw, Netherlands, to derive the vertical cloud structure. A regional network of stations was operated within a 100 km × 100 km domain to observe solar radiation, cloud liquid water path, cloud-base temperature, and height. Aircraft and tethered balloon measurements were used to measure cloud microphysical parameters and solar radiation below, in, and above the cloud. Satellite measurements complemented the cloud observations by providing the spatial structure from above. In order to better understand the effect of cloud inhomogeneities on the radiation field, three-dimensional radiative transfer modeling was closely linked to the measurement activities. To evaluate the performance of dynamic atmospheric models for the cloudy atmosphere four operational climate and NWP models were compared to the observations. As a first outcome of BBC we demonstrate that increased vertical resolution can improve the representation of clouds in these models.
Clouds cause uncertainties in the determination of climate sensitivity to either natural or anthropogenic changes. Furthermore, clouds dominate our perception of the weather, and the relatively poor forecast of cloud and precipitation parameters in numerical weather prediction (NWP) models is striking. In order to improve modeling and forecasting of clouds in climate and NWP models the BALTEX BRIDGE Campaign (BBC) was conducted in the Netherlands in August/September 2001 as a contribution to the main field experiment of the Baltic Sea Experiment (BALTEX) from April 1999 to March 2001 (BRIDGE). The complex cloud processes, which involve spatial scales from less than 1 mm (condensation nuclei) to 1000 km (frontal systems) require an integrated measurement approach. Advanced remote sensing instruments were operated at the central facility in Cabauw, Netherlands, to derive the vertical cloud structure. A regional network of stations was operated within a 100 km × 100 km domain to observe solar radiation, cloud liquid water path, cloud-base temperature, and height. Aircraft and tethered balloon measurements were used to measure cloud microphysical parameters and solar radiation below, in, and above the cloud. Satellite measurements complemented the cloud observations by providing the spatial structure from above. In order to better understand the effect of cloud inhomogeneities on the radiation field, three-dimensional radiative transfer modeling was closely linked to the measurement activities. To evaluate the performance of dynamic atmospheric models for the cloudy atmosphere four operational climate and NWP models were compared to the observations. As a first outcome of BBC we demonstrate that increased vertical resolution can improve the representation of clouds in these models.
Abstract
The Jülich Observatory for Cloud Evolution (JOYCE), located at Forschungszentrum Jülich 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 evolution of a typical cumulus cloud-topped boundary layer is analyzed with respect to stability, turbulence, and cloud properties. Additionally, we present longer-term statistics, which can be used to elucidate the diurnal cycle of water vapor, drizzle formation through autoconversion, and warm versus cold rain precipitation formation. Both case studies and long-term observations are important for improving the representation of clouds in climate and numerical weather prediction models.
Abstract
The Jülich Observatory for Cloud Evolution (JOYCE), located at Forschungszentrum Jülich 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 evolution of a typical cumulus cloud-topped boundary layer is analyzed with respect to stability, turbulence, and cloud properties. Additionally, we present longer-term statistics, which can be used to elucidate the diurnal cycle of water vapor, drizzle formation through autoconversion, and warm versus cold rain precipitation formation. Both case studies and long-term observations are important for improving the representation of clouds in climate and numerical weather prediction models.
Abstract
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.
Abstract
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.
Abstract
Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.
Abstract
Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.
