Towards a new generation of high-resolution meteorological input data for small-scale hydrologic modeling

2011 ◽  
Vol 402 (3-4) ◽  
pp. 317-332 ◽  
Author(s):  
Sophia Leimer ◽  
Thorsten Pohlert ◽  
Stephan Pfahl ◽  
Wolfgang Wilcke
Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1717 ◽  
Author(s):  
Antonio Annis ◽  
Fernando Nardi ◽  
Andrea Petroselli ◽  
Ciro Apollonio ◽  
Ettore Arcangeletti ◽  
...  

Devastating floods are observed every year globally from upstream mountainous to coastal regions. Increasing flood frequency and impacts affect both major rivers and their tributaries. Nonetheless, at the small-scale, the lack of distributed topographic and hydrologic data determines tributaries to be often missing in inundation modeling and mapping studies. Advances in Unmanned Aerial Vehicle (UAV) technologies and Digital Elevation Models (DEM)-based hydrologic modeling can address this crucial knowledge gap. UAVs provide very high resolution and accurate DEMs with low surveying cost and time, as compared to DEMs obtained by Light Detection and Ranging (LiDAR), satellite, or GPS field campaigns. In this work, we selected a LiDAR DEM as a benchmark for comparing the performances of a UAV and a nation-scale high-resolution DEM (TINITALY) in representing floodplain topography for flood simulations. The different DEMs were processed to provide inputs to a hydrologic-hydraulic modeling chain, including the DEM-based EBA4SUB (Event-Based Approach for Small and Ungauged Basins) hydrologic modeling framework for design hydrograph estimation in ungauged basins; the 2D hydraulic model FLO-2D for flood wave routing and hazard mapping. The results of this research provided quantitative analyses, demonstrating the consistent performances of the UAV-derived DEM in supporting affordable distributed flood extension and depth simulations.


2019 ◽  
Vol 12 (12) ◽  
pp. 4955-4997 ◽  
Author(s):  
Ignacio Pisso ◽  
Espen Sollum ◽  
Henrik Grythe ◽  
Nina I. Kristiansen ◽  
Massimo Cassiani ◽  
...  

Abstract. The Lagrangian particle dispersion model FLEXPART in its original version in the mid-1990s was designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as those released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modeling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g., greenhouse gases, short-lived climate forcers like black carbon and volcanic ash, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to global. In particular, inverse modeling based on source–receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.4, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) and data from the United States National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physicochemical parameterizations, input/output formats, and available preprocessing and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes in runs with very large numbers of particles. The deviation from 100 % efficiency is almost entirely due to the remaining nonparallelized parts of the code, suggesting large potential for further speedup. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g., to quantify dispersion in the vicinity of a point source. The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option of running backward in time from atmospheric concentrations at receptor locations for many years, but this has now been extended to also work for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEXPART is the only model with that capability. Furthermore, the temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing for more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane. Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART's customary binary format. In this paper, we describe these new developments. Moreover, we present some tools for the preparation of the meteorological input data and for processing FLEXPART output data, and we briefly report on alternative FLEXPART versions.


2020 ◽  
Author(s):  
Ignacio Pisso ◽  

<p>Following its release and corresponding publication in GMD, we present the Lagrangian model FLEXPART 10.4, which simulates the transport, diffusion, dry and wet deposition, radioactive decay and first order chemical reactions of atmospheric tracers. The model has been recently updated, both technical and in the representation of physico-chemical processes.<span> </span></p><p>FLEXPART was in its original version in the mid-1990s designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as released after an accident in a nuclear power plant. Given suitable meteorological input data, it can be used for scales from dozens of meters to the global scale. In particular, inverse modelling based on source-receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.4, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts’ (ECMWF) Integrated Forecast System (IFS), and data from the United States’ National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physico-chemical parametrizations, input/output formats and available pre- and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75% for up to 64 processes on multiple nodes in runs with very large numbers of particles. The deviation from 100% efficiency is almost entirely due to remaining non-parallelized parts of the code, suggesting large potential for further speed-up. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g. to quantify dispersion in the vicinity of a point source. The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option for running backward in time from atmospheric concentrations at receptor locations for many years, but this has now been extended to work also for deposition values . To our knowledge, to date FLEXPART is the only model with that capability. Furthermore, temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane. Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART’s customary binary format. In this paper, we describe these new developments. Moreover, we present some<span> </span> tools for the preparation of the meteorological input data and for processing of FLEXPART output data and briefly report on alternative FLEXPART versions.<span> </span></p>


2017 ◽  
Author(s):  
Cristian Lussana ◽  
Tuomo Saloranta ◽  
Thomas Skaugen ◽  
Jan Magnussson ◽  
Ole Einar Tveito ◽  
...  

Abstract. The conventional climate datasets based on observations only are a widely used source of information for climate and hydrology. On the Norwegian mainland, the seNorge datasets of daily mean temperature and total precipitation amount constitute a valuable meteorological input for snow- and hydrological simulations which are routinely conducted over such a complex and heterogeneous terrain. A new seNorge version (seNorge2) has been released recently and to support operational applications for civil protection purposes, it must be updated daily and presented on a high-resolution grid (1 km of grid spacing). The archive goes back to 1957. The seNorge2 statistical interpolation schemes can provide high-resolution fields for applications requiring long-term datasets at regional or national level, where the challenge is to simulate small-scale processes often taking place in complex terrain. The statistical schemes build upon classical spatial interpolation methods, such as Optimal Interpolation and successive-correction schemes, and introduce original approaches. For both temperature and precipitation, the spatial interpolation exploits the concept of (spatial) scale-separation and the first-guess field is derived from the observed data. Furthermore, the geographical coordinates and the elevation are used as complementary information. The evaluation of the seNorge2 products is presented both from a general point of view, through systematic cross-validations, and specifically as the meteorological input in the operational model chains used for snow- and hydrological simulations. The seNorge snow model is used for simulation of snow fields and the DDD (Distance Distribution Dynamics) rainfall-runoff model is the hydrological model used. The evaluation points out important information for the future seNorge2 developments: the daily mean temperature fields constitute an accurate and precise dataset, on average the predicted temperature is an unbiased estimate of the actual temperature and its precision (at grid points) varies between 0.8 °C and 2.4 °C; the daily precipitation fields provide a reasonable estimate of the actual precipitation, the cross-validation shows that on average the precision of the estimates (at grid points) is about ±20 %, though a systematic underestimation of precipitation occurs in data-sparse areas and for intense precipitation. Both the seNorge snow and the DDD models have been able to make profitable use of seNorge2, partly because of the automatic calibration procedure they incorporate for precipitation. The dataset described in this article is available for public download at http://doi.org/10.5281/zenodo.845733.


2019 ◽  
Author(s):  
Ignacio Pisso ◽  
Espen Sollum ◽  
Henrik Grythe ◽  
Nina Kristiansen ◽  
Massimo Cassiani ◽  
...  

Abstract. The Lagrangian particle dispersion model FLEXPART was in its original version in the mid-1990s designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modelling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g. greenhouse gases, short-lived climate forcers like black carbon, or volcanic emissions, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to the global scale. In particular, inverse modelling based on source-receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.3, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts' (ECMWF) Integrated Forecast System (IFS), and data from the United States' National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physico-chemical parametrizations, input/output formats and available pre- and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes. The deviation from 100 % efficiency is almost entirely due to remaining non-parallelized parts of the code, suggesting large potential for further speed-up. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g. to quantify dispersion in the vicinity of a point source. The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option for running backward in time from atmospheric concentrations at receptor locations since many years, but this has now been extended to work also for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEXPART is the only model with that capability. Furthermore, temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane. Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART's customary binary format. In this paper, we describe these new developments. Moreover, we present some tools for the preparation of the meteorological input data and for processing of FLEXPART output data and briefly report on alternative FLEXPART versions.


Author(s):  
John L. Hutchison

Over the past five years or so the development of a new generation of high resolution electron microscopes operating routinely in the 300-400 kilovolt range has produced a dramatic increase in resolution, to around 1.6 Å for “structure resolution” and approaching 1.2 Å for information limits. With a large number of such instruments now in operation it is timely to assess their impact in the various areas of materials science where they are now being used. Are they falling short of the early expectations? Generally, the manufacturers’ claims regarding resolution are being met, but one unexpected factor which has emerged is the extreme sensitivity of these instruments to both floor-borne and acoustic vibrations. Successful measures to counteract these disturbances may require the use of special anti-vibration blocks, or even simple oil-filled dampers together with springs, with heavy curtaining around the microscope room to reduce noise levels. In assessing performance levels, optical diffraction analysis is becoming the accepted method, with rotational averaging useful for obtaining a good measure of information limits. It is worth noting here that microscope alignment becomes very critical for the highest resolution.In attempting an appraisal of the contributions of intermediate voltage HREMs to materials science we will outline a few of the areas where they are most widely used. These include semiconductors, oxides, and small metal particles, in addition to metals and minerals.


2020 ◽  
Vol 32 (52) ◽  
pp. 2070388
Author(s):  
Simone Gervasoni ◽  
Anastasia Terzopoulou ◽  
Carlos Franco ◽  
Andrea Veciana ◽  
Norman Pedrini ◽  
...  

2019 ◽  
Vol 15 (S359) ◽  
pp. 312-317
Author(s):  
Francoise Combes

AbstractGas fueling AGN (Active Galaxy Nuclei) is now traceable at high-resolution with ALMA (Atacama Large Millimeter Array) and NOEMA (NOrthern Extended Millimeter Array). Dynamical mechanisms are essential to exchange angular momentum and drive the gas to the super-massive black hole. While at 100pc scale, the gas is sometimes stalled in nuclear rings, recent observations reaching 10pc scale (50mas), may bring smoking gun evidence of fueling, within a randomly oriented nuclear gas disk. AGN feedback is also observed, in the form of narrow and collimated molecular outflows, which point towards the radio mode, or entrainment by a radio jet. Precession has been observed in a molecular outflow, indicating the precession of the radio jet. One of the best candidates for precession is the Bardeen-Petterson effect at small scale, which exerts a torque on the accreting material, and produces an extended disk warp. The misalignment between the inner and large-scale disk, enhances the coupling of the AGN feedback, since the jet sweeps a large part of the molecular disk.


2004 ◽  
Vol 22 (1) ◽  
pp. 169-182 ◽  
Author(s):  
D. M. Wright ◽  
T. K. Yeoman ◽  
L. J. Baddeley ◽  
J. A. Davies ◽  
R. S. Dhillon ◽  
...  

Abstract. The EISCAT high power heating facility at Tromsø, northern Norway, has been utilised to generate artificial radar backscatter in the fields of view of the CUTLASS HF radars. It has been demonstrated that this technique offers a means of making very accurate and high resolution observations of naturally occurring ULF waves. During such experiments, the usually narrow radar spectral widths associated with artificial irregularities increase at times when small scale-sized (high m-number) ULF waves are observed. Possible mechanisms by which these particle-driven high-m waves may modify the observed spectral widths have been investigated. The results are found to be consistent with Pc1 (ion-cyclotron) wave activity, causing aliasing of the radar spectra, in agreement with previous modelling work. The observations also support recent suggestions that Pc1 waves may be modulated by the action of longer period ULF standing waves, which are simultaneously detected on the magnetospheric field lines. Drifting ring current protons with energies of ∼ 10keV are indicated as a common plasma source population for both wave types. Key words. Magnetospheric physics (MHD waves and instabilities) – Space plasma physics (wave-particle interactions) – Ionosphere (active experiments)


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