scholarly journals Evaluation of <i>seNorge2</i>, a conventional climatological datasets for snow- and hydrological modeling in Norway

2017 ◽  
Author(s):  
Cristian Lussana ◽  
Tuomo Saloranta ◽  
Thomas Skaugen ◽  
Jan Magnussson ◽  
Ole Einar Tveito ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Interpolation ◽  
Hydrological Modeling ◽  
National Level ◽  
Precipitation Amount ◽  
Optimal Interpolation ◽  
Small Scale ◽  
Mean Temperature ◽  
Meteorological Input ◽  
Grid Points

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 &amp;pm;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.

scholarly journals seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day

2018 ◽  
Vol 10 (1) ◽  
pp. 235-249 ◽  
Author(s):  
Cristian Lussana ◽  
Tuomo Saloranta ◽  
Thomas Skaugen ◽  
Jan Magnusson ◽  
Ole Einar Tveito ◽  
...  
Keyword(s):  
High Resolution ◽  
Daily Precipitation ◽  
Spatial Scales ◽  
National Level ◽  
Calibration Procedure ◽  
Geographical Information ◽  
Optimal Interpolation ◽  
Small Scale ◽  
Meteorological Forcing ◽  
Atmospheric Sciences

Abstract. The conventional climate gridded datasets based on observations only are widely used in atmospheric sciences; our focus in this paper is on climate and hydrology. On the Norwegian mainland, seNorge2 provides high-resolution fields of daily total precipitation 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 dataset constitutes a valuable meteorological input for snow and hydrological simulations; it is updated daily and presented on a high-resolution grid (1 km of grid spacing). The climate archive goes back to 1957. The spatial interpolation scheme builds upon classical methods, such as optimal interpolation and successive-correction schemes. An original approach based on (spatial) scale-separation concepts has been implemented which uses geographical coordinates and elevation as complementary information in the interpolation. seNorge2 daily precipitation fields represent local precipitation features at spatial scales of a few kilometers, depending on the station network density. In the surroundings of a station or in dense station areas, the predictions are quite accurate even for intense precipitation. For most of the grid points, the performances are comparable to or better than a state-of-the-art pan-European dataset (E-OBS), because of the higher effective resolution of seNorge2. However, in very data-sparse areas, such as in the mountainous region of southern Norway, seNorge2 underestimates precipitation because it does not make use of enough geographical information to compensate for the lack of observations. The evaluation of seNorge2 as the meteorological forcing for the seNorge snow model and the DDD (Distance Distribution Dynamics) rainfall–runoff model shows that both models have been able to make profitable use of seNorge2, partly because of the automatic calibration procedure they incorporate for precipitation. The seNorge2 dataset 1957–2015 is available at https://doi.org/10.5281/zenodo.845733. Daily updates from 2015 onwards are available at http://thredds.met.no/thredds/catalog/metusers/senorge2/seNorge2/provisional_archive/PREC1d/gridded_dataset/catalog.html.

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
Keyword(s):  
High Resolution ◽  
Input Data ◽  
Hydrologic Modeling ◽  
Small Scale ◽  
Meteorological Input ◽  
New Generation

scholarly journals Evaluation of Gridded Meteorological Datasets for Hydrological Modeling

2017 ◽  
Vol 18 (11) ◽  
pp. 3027-3041 ◽  
Author(s):  
Melanie Raimonet ◽  
Ludovic Oudin ◽  
Vincent Thieu ◽  
Marie Silvestre ◽  
Robert Vautard ◽  
...  
Keyword(s):  
High Resolution ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Climate Model ◽  
Precipitation Amount ◽  
Mountainous Areas ◽  
Elevation Gradients ◽  
Temperature And Precipitation ◽  
The Impact ◽  
Hydrological Applications

Abstract The number and refinement of gridded meteorological datasets are on the rise at the global and regional scales. Although these datasets are now commonly used for hydrological modeling, the representation of precipitation amount and timing is crucial to correctly model streamflow. The Génie Rural à 4 paramètres journalier (GR4J) conceptual hydrological model combined with the CEMANEIGE snow routine was calibrated using four temperature and precipitation datasets [Système d’analyse fournissant des renseignements atmosphériques à la neige (SAFRAN), Mesoscale Analysis (MESAN), E-OBS, and Water and Global Change (WATCH) Forcing Data ERA-Interim (WFDEI)] on 931 French gauged catchments ranging in size from 10 to 10 000 km2. The efficiency of the calibrated hydrological model in simulating streamflow was higher for the models calibrated on high-resolution meteorological datasets (SAFRAN, MESAN) compared to coarse-resolution datasets (E-OBS, WFDEI), as well as for reanalysis (SAFRAN, MESAN, WFDEI) compared to datasets based on interpolation only (E-OBS). The systematic decrease in efficiency associated with precipitation bias or temporality highlights that the use of a hydrological model calibrated on meteorological datasets can assess these datasets, most particularly precipitation. It appears essential that datasets account for high-resolution topography to accurately represent elevation gradients and assimilate dense ground-based observation networks. This is particularly emphasized for hydrological applications in mountainous areas and areas subject to finescale events. For hydrological applications on nonmountainous regions, not subject to finescale events, both regional and global datasets give satisfactory results. It is crucial to continue improving precipitation datasets, especially in mountainous areas, and to assess their sensitivity to eventual corrupted observations. These datasets are essential to correct the bias of climate model outputs and to investigate the impact of climate change on hydrological regimes.

scholarly journals Novel measures for summarizing high-resolution forecast performance

2021 ◽  
Vol 7 (1) ◽  
pp. 13-34
Author(s):  
Eric Gilleland
Keyword(s):  
High Resolution ◽  
Perfect Match ◽  
Small Scale ◽  
Worst Case ◽  
Forecast Performance ◽  
New Methods ◽  
A Value ◽  
Spatial Alignment ◽  
Single User ◽  
Grid Points

Abstract. In ascertaining the performance of a high-resolution gridded forecast against an analysis, called the verification set, on the same grid, care must be taken to account for the over-accumulation of small-scale errors and double penalties. It is also useful to consider both location errors and intensity errors. In the last 2 decades, many new methods have been proposed for analyzing these kinds of verification sets. Many of these new methods involve fairly complicated strategies that do not naturally summarize forecast performance succinctly. This paper presents two new spatial-alignment performance measures, G and Gβ. The former is applied without any requirement for user decisions, while the latter has a single user-chosen parameter, β, that takes on a value from zero to one, where one corresponds to a perfect match and zero corresponds to the user's notion of a worst case. Unlike any previously proposed distance-based measure, both handle the often-encountered case in which all values in one or both of the verification set are zero. Moreover, its value is consistent if only a few grid points are nonzero.

scholarly journals Circum-nuclear molecular disks: Role in AGN fueling and feedback

2019 ◽  
Vol 15 (S359) ◽  
pp. 312-317
Author(s):  
Francoise Combes
Keyword(s):  
Black Hole ◽  
Angular Momentum ◽  
High Resolution ◽  
Large Scale ◽  
Active Galaxy ◽  
Small Scale ◽  
Massive Black Hole ◽  
Molecular Outflows ◽  
Molecular Outflow

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.

scholarly journals High resolution observations of spectral width features associatedwith ULF wave signatures in artificial HF radar backscatter

2004 ◽  
Vol 22 (1) ◽  
pp. 169-182 ◽  
Author(s):  
D. M. Wright ◽  
T. K. Yeoman ◽  
L. J. Baddeley ◽  
J. A. Davies ◽  
R. S. Dhillon ◽  
...  
Keyword(s):  
High Resolution ◽  
Plasma Source ◽  
Spectral Width ◽  
Hf Radar ◽  
Mhd Waves ◽  
Small Scale ◽  
Ulf Waves ◽  
Source Population ◽  
Radar Backscatter ◽  
Field Lines

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)

High resolution observations of small-scale magnetic elements and interpretation

Solar Physics ◽  
1996 ◽  
Vol 164 (1-2) ◽  
pp. 303-310 ◽  
Author(s):  
F. Kneer ◽  
F. Stolpe
Keyword(s):  
High Resolution ◽  
Small Scale ◽  
Magnetic Elements

scholarly journals The definition of an atmospheric database for Aeolus

2011 ◽  
Vol 4 (1) ◽  
pp. 67-88 ◽  
Author(s):  
G. J. Marseille ◽  
K. Houchi ◽  
J. de Kloe ◽  
A. Stoffelen
Keyword(s):  
High Resolution ◽  
Meteorological Data ◽  
Sampling Strategy ◽  
Laser Wavelength ◽  
Geographic Region ◽  
Atmospheric Dynamics ◽  
Specific Humidity ◽  
Small Scale ◽  
Horizontal Line ◽  
Definition Of

Abstract. The definition of an atmospheric database is an important component of simulation studies in preparation of future earth observing remote sensing satellites. The Aeolus mission, formerly denoted Atmospheric Dynamics Mission (ADM) or ADM-Aeolus, is scheduled for launch end of 2013 and aims at measuring profiles of single horizontal line-of-sight (HLOS) wind components from the surface up to about 32 km with a global coverage. The vertical profile resolution is limited but may be changed during in-orbit operation. This provides the opportunity of a targeted sampling strategy, e.g., as a function of geographic region. Optimization of the vertical (and horizontal) sampling strategy requires a characterization of the atmosphere optical and dynamical properties, more in particular the distribution of atmospheric particles and their correlation with the atmospheric dynamics. The Aeolus atmospheric database combines meteorological data from the ECMWF model with atmosphere optical properties data from CALIPSO. An inverse algorithm to retrieve high-resolution particle backscatter from the CALIPSO level-1 attenuated backscatter product is presented. Global weather models tend to underestimate atmospheric wind variability. A procedure is described to ensure compatibility of the characteristics of the database winds with those from high-resolution radiosondes. The result is a high-resolution database of zonal, meridional and vertical wind, temperature, specific humidity and particle and molecular backscatter and extinction at 355 nm laser wavelength. This allows the simulation of small-scale atmospheric processes within the Aeolus observation sampling volume and their impact on the quality of the retrieved HLOS wind profiles. The database extends over four months covering all seasons. This allows a statistical evaluation of the mission components under investigation. The database is currently used for the development of the Aeolus wind processing, the definition of wind calibration strategies and the optimization of the Aeolus sampling strategy.

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