dataesr/scientific-paragraphs-categorization huggingface dataset:
1 to 35 AU in radius (r), À40°to +40°in latitude (θ), and À180°to 180°in longitude (ϕ). The simulation period of 14 October 2014 to 14 April 2015 included 138 CMEs with speeds above 500 km/s and full angular widths above 50°from the web-accessible Database of Notifications Knowledge Information (https://kauai. ccmc. gsfc. nasa. gov/DONKI/) that is populated by CCMCs Space Weather Research Center team. The ENLIL model extended to 35 AU has not been modified to include the drag effect from pickup ions or the enhancement of the wind mass density due to photoionization of neutral hydrogen entering the heliosphere from the interstellar medium, both of which play a role in ICME propagation at these distances. Figure  3  displays results of the simulation, in particular, the global heliospheric solar wind speed together with the magnetic field polarity and field lines, at the locations of interest for this study.
Comet 67P/Churyumov-Gerasimenko Figure  7  shows the magnetic field, radiation data and solar wind velocity measured by Rosetta at comet 67P at 3. 1 AU from the Sun. Figures  7a  and 7b  show the magnetic field components and magnitude, respectively, as measured by the Rosetta Plasma Consortium (RPC)-magnetometer (MAG)  [Glassmeier et al. , 2007a]  instrument onboard Rosetta. The magnetic field magnitude exhibits a sudden increase from 5 nT to 15 nT on 22 October at 16:30 UT when the ICME-driven interplanetary shock arrived at the comet. At that time, the Rosetta spacecraft was in a terminator orbit at 10 km distance from the comet nucleus mass center, and the coma was relatively weak. Consistent with the arrival of the shock,  Edberg et al. [2016]  noted that a significant disturbance was observed in all the Rosetta plasma instruments, including a sudden signal increase in the ion and electron suprathermal sensor (~10-100 eV) of about 1 order of magnitude together with a general increase in energy of the electrons and also a gradual increase of ~2 orders of magnitude in the ion composition analyzer solar wind fluxes [see  Edberg et al.
Voyager 2 As seen in Figure  1 , if the ICME traveled by Pluto, there is the possibility that the ICME, or a MIR formed by this ICME, could have reached Voyager 2. This spacecraft is currently more than 110 AU from the Sun, within the heliosheath. Figure  10  displays Voyager 2 data from 2014 to mid-2016. Two MIRs are clearly identified, in mid-August 2015 and end-March 2016 (the latter is bracketed by the red vertical bars), from the variations of the dynamic pressure connected with a decrease of GCR. While the first MIR was observed too early to be associated with the ICME studied here, the second event is a plausible association. The arrival time at Voyager 2 is calculated following the same approach as in  Liu et al. [2014]. We start from the possible event at New Horizons at the end of January 2015 and the Voyager 2 position in the range 110-111 AU.
Acknowledgments B. S-. C. , G. P. , S. E. M. , M. L. , M. K. J. , S. W. H. C. , and B. E. S. H acknowledge support through  STFC  grants  ST/K001000/1 ,  ST/N000749/1 , and  ST/K502121/1. M. L. M. and I. G. R. acknowledge the support of  NASA  LWS grants  NNX15AB80G  and  NNG06EO90A , respectively. Simulation results have been provided by the  Community  Coordinated Modeling Center at the  Goddard Space Flight Center  through their public Runs on Request system (http://ccmc. gsfc. nasa. gov;run numbers Leila_Mays_092716_SH_1 and Leila_Mays_100116_SH_1). The WSA model was developed by  N. Arge  at  AFRL , and the ENLIL model was developed by  D. Odstrcil  at  GMU. P. K. 's work has been supported by the  Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica  grant  IA104416.
J. D. R. was supported by  NASA 's  Voyager  project. N. J. T. E. was funded by the  Swedish National Space Board  ( 135/13 ) and  The Swedish Research Council  ( 621-2013-4191 ). The Propagation Tool is designed and developed by the  CDPP and GFI  under CNES funding; it can be accessed from http://propagationtool. cdpp. eu/. All the MAVEN,  MSL ,  Mars Odyssey ,  Cassini , and New Horizons data sets are available at the  NASA PDS. All the scientific data from Mars Express are available at the  ESA PSA  and AMDA (http://amda. cdpp. eu/). The Propagation Tool, 3DView, and AMDA analysis systems are designed and provided by the  Centre de Données de la Physique des Plasmas (CDPP)  supported by  CNRS ,  CNES ,  Observatoire de Paris , and  Université Paul Sabatier, Toulouse. The Propagation Tool is developed by  GFI  and can be accessed from http://propagationtool.
cdpp. eu/. Rosetta  scientific data sets are available at the ESA PSA and Rosetta SREM data at http://spitfire. estec. esa. int/sedat/dplot_odi. html. All the solar data are available at https://sohodata. nascom. nasa. gov/cgi-bin/data_query,http:// sdo. gsfc. nasa. gov/data/aiahmi/,https:// stereo-ssc. nascom. nasa. gov/beacon/beacon_secchi. shtml, and http:// proba2. sidc. be/data/LYRA. Voyager 2 data are available at http://web. mit. edu/space/www/voyager/voyager. html and http://voyager. gsfc. nasa. gov/heliopause/data. html. The  Bartol Research Institute neutron monitor program  is supported by the  National Science Foundation  under grants  PLR-1245939  and  PLR-1341562 , and by the  University of Delaware Department of Physics and Astronomy and Bartol Research Institute , and can be downloaded from http://neutronm.
EU countries report outbreaks of WNV encephalomyelitis in horses to the European Commission (EC) via the Animal Disease Notification System (ADNS)  [24]  and regular summaries are posted online. The data from WNV monitoring in animals is reported annually by EU countries under Directive 2003/99/EC [25] and presented in the annual EFSA/ECDC EU Summary Report on Trends and Sources of Zoonoses, Zoonotic Agents and Food-borne Outbreaks  [6]. Animal WNF outbreak data reported to the OIE are publically available on the World Animal Health Information Database (WAHIS) interface  [26]. Through the Pan-European VectorNet project  [27] , presence/absence distribution maps of Culex species are under development. Current Culex pipiens maps are incomplete  [28].
At the same time, passive surveillance of human WNND cases is undertaken in the whole region in which the affected area is located, requesting physicians to report all probable and confirmed WNND cases using a modified EU case definition, which includes neurological symptoms. Probable and confirmed human cases are notified by regional authorities to the Ministry of Health and to the Istituto Superiore di Sanità using a password-protected web-based system gathering epidemiological and laboratory information about cases. The database is also accessible by the National Blood Centre and the National Transplant Network in order to implement measures on blood and transplants safety in a timely manner. Since 2013 all asymptomatic confirmed cases of WNV infection in blood donors have also been notified through the web-based system.
The surveillance activities for wild birds and vectors have been strengthened since 2013. Bird surveillance focuses on three aspects: WNV detection in resident target species such as magpies and crows; immunological response among poultry of rural farms, sentinel chickens and migratory birds; and bird mortality. Entomological surveillance includes WNV detection in mosquito pools from affected areas. There is passive surveillance in equidae with random serological tests in non-endemic areas and monitoring of sentinel horses. However, many horses in Italy are vaccinated against WNV. A web-based national animal disease notification system allows the notification of animal diseases. The system allows the integration of data from veterinary field services and laboratories into a national database.
Acknowledgements ECDC: We would like to thank  Hervé Zeller  for his valuable comments on the manuscript. France: We would like to thank  Gregory L'Ambert from EID Méditerranée  and  Isabelle Leparc Goffart  from the  National Reference  Centre for Arbovirus. Greece: We would like to thank  Associate Professor Constantina Politis  from the  Hellenic Coordinating Haemovigilance Centre  and all hospital physicians, laboratory experts and staff, staff at the national and local public health authorities, the private veterinarians, staff at the local veterinary authorities, staff at the  Department of Virology of the Athens Center of Veterinary Institutes , the  Universities  and the  MALWEST  project, who contributed to the surveillance of WNV infections in humans, animals and mosquitoes in Greece.
Long-term, high-resolution data about hydrologic fluxes and states are needed for many hydrological applications. Because continuous large-scale observations of such variables are not feasible, hydrologic or land surface models are applied to derive them. This study aims to analyze and provide a consistent high-resolution dataset of land surface variables over Germany, accounting for uncertainties caused by equifinal model parameters. The mesoscale Hydrological Model (mHM) is employed to derive an ensemble (100 members) of evapotranspiration, groundwater recharge, soil moisture, and runoff generated at high spatial and temporal resolutions (4 km and daily, respectively) for the period 1951-2010. The model is cross-evaluated against the observed daily streamflow in 222 basins, which are not used for model calibration.
The mean (standard deviation) of the ensemble median Nash-Sutcliffe efficiency estimated for these basins is 0. 68 (0. 09) for daily streamflow simulations. The modeled evapotranspiration and soil moisture reasonably represent the observations from eddy covariance stations. Our analysis indicates the lowest parametric uncertainty for evapotranspiration, and the largest is observed for groundwater recharge. The uncertainty of the hydrologic variables varies over the course of a year, with the exception of evapotranspiration, which remains almost constant. This study emphasizes the role of accounting for the parametric uncertainty in modelderived hydrological datasets.
Introduction Consistent, long-term data of meteorological and hydrological variables at a high spatial resolution are needed for many applications, including (i) impact assessment studies, such as for drought, flood, or climate change analysis  (Sheffield and Wood, 2007; Huang et al. , 2010; Samaniego et al. , 2013; Kumar et al. , 2016; Zink et al. , 2016) , and (ii) studies that need spatially and temporally continuous, observation-based datasets, e. g. , for downscaling or disaggregating climate model outputs  (Wood et al. , 2004; Thober et al. , 2014)  or for establishing Ensemble Streamflow Prediction  (Day, 1985)  and reverse Ensemble Streamflow Prediction approaches  (Wood and Lettenmaier, 2008). Continuous observations of hydrologic fluxes and states are economically and logistically not feasible on regional to national scales  (Vereecken et al.
, 2012). Reanalysis products, in Published by Copernicus Publications on behalf of the European Geosciences Union. contrast, provide continuous data but they have coarse spatial resolutions of at most 1/4 •  (Dee et al. , 2016) , which is not suitable for regional-scale applications. Hydrologic models driven by ground-based meteorological observations are the prime alternative to derive spatially and temporally consistent water fluxes and states at large spatial domains. For example,  Maurer et al. (2002) ;  Zhu and Lettenmaier (2007) ;  Livneh et al. (2013) ; and  Zhang et al. (2014)  provided model-based datasets on a national scale. These data are based on the Variable Infiltration Capacity (VIC) model  (Liang et al. , 1994)  and have, at most, a spatial resolution of 1/16 • and cover the contiguous United States, Mexico, China, and parts of Canada.
Livneh et al. (2015) ;  Newman et al. (2015a) ; and  Newman et al. (2015b)  provide data on the same domain with a focus on meteorological data. A set of four models was used in the NLDAS project to assess the water balance components over the contiguous United States  (Mitchell, 2004; Xia et al. , 2012a, b). Studies by  Nijssen et al. (2001) ;  Fan and van den Dool (2004) ;  Berg et al. (2005) ; and  Sheffield et al. (2006)  focus on the global domain. The spatial resolution of these global datasets is at most 1/2 • , and many of these studies focus on meteorological forcings rather than hydrologic variables. The resolution of the abovementioned model-derived datasets are coarse according to  Wood et al. (2011) , who stated a need for higher-resolution data and models for purpose of, e. g.
Furthermore, hydrological models are subject to different sources of uncertainty, i. e. , input, model structural, and parametric uncertainty  (Beven, 1993). All of the aforementioned uncertainties propagate to the model results and can superpose each other  (Zappa et al. , 2011). The overall uncertainty of hydrological models is therefore summarized as predictive uncertainty. Uncertainties are often not considered when deriving hydrological or hydro-meteorological datasets (e. g. ,  Huang et al. , 2010; Livneh et al. , 2013; Zhang et al. , 2014). As a result, predictive uncertainties are often not addressed but may have substantial implications on subsequent studies, as shown by  Samaniego et al. (2013). Herein, we will focus on the predictive uncertainties caused by equifinal parameter sets.
Such an approach combines all of the aforementioned strategies. The aim of this study is to derive a model based, consistent set of national-scale hydrological data for Germany within the period 1951-2010. We address the need for highly resolved data by conducting observation-driven hydrological simulations at a spatial resolution of 4 km × 4 km (1/25 • ). Daily fields of evapotranspiration, soil moisture, groundwater recharge, and grid-cell-generated runoff as well as precipitation, temperatures, and potential evapotranspiration are made freely available. To our knowledge, such a consistent and long-term dataset for Germany has not been freely available until now. The dataset accounts for predictive uncertainties by considering a set of equifinal parameters. An parameter estimation approach for deriving a set of 100 parameters on the national scale is developed.
Study domain and datasets The study is conducted on the territory of Germany, which covers an area of approximately 357 000 km 2 (Fig. 1 ). The region, located in central Europe, is mainly characterized by a humid climate but nonetheless has north-to-south and east-to-west climatic gradients. The topography varies from low-altitude, flat areas in the north (North German Plain) over mid-altitude mountains in central Germany (Central Uplands) to the high-altitude Alpine foothills and the Alps in the south. Whereas the northwestern part of Germany is still under maritime influence, the eastern part has a more continental climate that is characterized by colder winters and less precipitation. The assessment of water fluxes and states is restricted to the national borders of Germany because meteorological data and land-surface characteristics are available in this domain.
Based on the DEM, additional information, such as the slope, aspect, flow direction, and flow accumulation, are inferred. Land cover information is derived from CORINE land cover scenes of the years  1990 , 2000 , and 2006 (European Environmental Agency , EEA). The period prior to 1990 is assumed to be static and is represented by the scene of 1990. All datasets are remapped to a common spatial resolution of 100 m × 100 m using a nearest neighbor approach. The location and shape of the major basins (Fig. 1 ) are derived via an automated delineation, which is based on gauging station and terrain information (flow accumulation and flow direction). Streamflow data are provided by the European Water Archive (EWA) and the Global Runoff Data Centre (GRDC). The results of the delineation are approved via comparison with the CCM River and Catchment Database (European Commission -Joint Research center , JRC;  Vogt et al.
The interpolation of the precipitation is evaluated with gridded precipitation data (REGNIE) provided by the German Meteorological Service (Deutscher Wetterdienst, DWD;  Rauthe et al. , 2013). The REGNIE data are based on the same observations and have a spatial resolution of 1 km. They are derived by applying a multiple linear regression approach, which accounts for daily atmospheric conditions and terrain properties, such as elevation, slope, and aspect  (Rauthe et al. , 2013). After remapping the REGNIE data to the aforementioned 4 km × 4 km grid by bilinear interpolation, a satisfactory correspondence between the interpolation and the REG-NIE precipitation data is found (see  Samaniego et al. , 2013). The spatially averaged bias of the daily fields is 0 with a standard deviation of 0. 11 mm d -1 within the period 1951-2010.
Validation data In addition to streamflow in the seven major German river basins, the model performance is evaluated against streamflow in 222 additional basins and complementary datasets including evapotranspiration, soil moisture, and groundwater recharge. The cross-validation of ensemble parameter sets in basins that have not been used for parameter inference should prove the ability of the model to satisfactorily estimate streamflow in various regions of Germany with differing hydrologic characteristics. The basins for cross-validation are distributed all over Germany and range in size from 100 to 8500 km 2. A detailed characterization of these basins is given in Table  S3  in the Supplement. A subset of these basins contains subbasins of seven major basins. The simulation time period is adopted for the available streamflow observations but is at least 10 years.
Rather than downscaling the model results, the hydrologic processes are modeled at the resolution of the observations. The transferability of mHM across scales is presented in  Samaniego et al. (2010)  and  Kumar et al. (2013b). The model is evaluated with spatially distributed data, i. e. , evapotranspiration and groundwater recharge, additionally to the evaluation of the model at the point or local scale. A remote-sensing-based dataset is used for evaluating the monthly modeled evapotranspiration between 2001 and 2010. For this purpose we used the gridded evapotranspiration (E a ) dataset based on the Moderate Resolution Imaging Spectroradiometer (MODIS), which was acquired from the Numerical Terradynamic Simulation Group at the University of Montana  (Mu et al. , 2007 (Mu et al. , , 2011)).
The spatial resolution is approximately 5 km × 5 km (0. 05 • ), which is close to the model resolution of 4 km × 4 km. The evapotranspiration estimates are based on the Penman-Monteith energy balance equation using global daily temperature, actual vapor deficit, incoming solar radiation as well as remotely sensed leaf area index, fraction of photosynthetic active radiation, albedo, and land cover characteristics. The meteorological variables are based on the reanalysis product from the Global Modeling and Assimilation Office, whereas vegetation products are derived from MODIS. Interested readers may refer to  Mu et al. (2007 Mu et al. ( , 2011) )  for a detailed description of the MODIS E a product. As a second spatial dataset, we utilize a long-term estimate of annual recharge over Germany.
Evaluation with spatially distributed data In this section, we present results of the model skill in representing gridded fluxes over the entire German domain. The first comparison is conducted for the assessment of reproducing the monthly fields of modeled E a against the remotely sensed MODIS product. The results are summarized in Fig. 7  in terms of three key metrics: relative bias, correlation, and RMSE. The analysis is conducted using the ensemble mean of E a from the 100 model simulations. The modeled E a is able to adequately capture the spatiotemporal features of the MODIS derived product with the majority of grid cells (74 %) having a relative absolute bias of less than 10 %. Notable differences among these two evapotranspiration datasets are appearing in lowland areas along the Danube River basin in southern Germany, where the modeled E a exhibited a dry bias compared to MODIS.
An opposite trend of positive bias in modeled E a is observed for grid cells lying www. hydrol-earth-syst-sci. net/21/1769/2017/ Hydrol. Earth Syst. Sci. , 21, 1769-1790, 2017  along the coastal region in northern Germany. The temporal correspondence between both evapotranspiration datasets is also remarkably high with an average Pearson correlation coefficient of 0. 96 (standard deviation 0. 02). Notably, both evaporation datasets exhibit pronounced seasonal variability leading to a high temporal correspondence between them. The second assessment evaluates the modeled groundwater recharge with long-term annual values from the Hydrologic Atlas of Germany (HAD) (Federal Ministry for the Environment Nature Conservation Building and Nuclear Safety, 2003). mHM's long-term recharge estimate implicitly represents the baseflow component of the total runoff based on the assumption that the underground basin is closed and that there are no external losses (e.
Summary and conclusion In this study, we present the derivation and evaluation of a high-resolution (4 km × 4 km) dataset of hydrologic and meteorological fluxes and states for Germany covering the period 1951-2010, which is freely available. The dataset incorporates 100 spatially consistent ensemble simulations, which are analyzed regarding their uncertainty caused by the parameter estimation. The parameter sets of the ensemble simulations are determined by a two-step parameter selection method. The model is calibrated in seven basins, and the parameter sets are filtered based on the cross-validation results in all of the basins. Thus, the uncertainty is composed of the uncertainty in parameter estimation and the uncertainty stemming from transferring these parameters to remote locations.
The ensemble simulations are evaluated with streamflow, evapotranspiration and soil moisture observations, and recharge data. A comparable study by  Newman et al. (2015a)  focuses on the provision of a 100 member ensemble dataset, which is focusing on meteorological variables for major parts of North America. Similar to the study presented herein they evaluate the data in a large sample of basins, i. e. , 671. We, however, conclude that 100 realizations is an appropriate sample size for an uncertainty assessment study. The evaluation regarding streamflow at 222 additional basins revealed a median NSE of 0. 68. Thus, the 100 ensemble parameter sets are considered to be representative for Germany. The evaluation with evapotranspiration from eddy covariance stations showed deficiencies in mHM.
Data availability. The dataset consists of daily values of precipitation and minimum, maximum, and average temperature, potential evapotranspiration, evapotranspiration, soil moisture, groundwater recharge, and generated runoff, whereas the latter four are provided as ensemble of 100 simulations. The data format is the Net Common Data Format (NetCDF version 3) and is based on the CF conventions (www. cfconventions. org). Additionally, the ensemble means and standard deviations are provided for download. The dataset is freely accessible under Creative Commons license at http://www. ufz. de/index. php?en=41160.
| Strain identification by MALDI-TOF MS and 16S rRNA gene sequencing The MALDI-TOF MS protein analysis consisted of picking an isolated colony and then depositing twelve distinct deposits on a MTP 96 MALDI-TOF target plate (Bruker Daltonics, Leipzig, Germany) to be analyzed. 2 μl of a matrix solution (saturated solution of α-cyano-4-hydroxycinnamic acid diluted in 50% acetonitrile and 2. 5% of tri-fluoro-acetic acid) was added on each spot. Measurements and proteomic analysis of the isolate were carried out with a Microflex spectrometer (Bruker) as previously described  (Seng et al. , 2009). Protein spectra were imported into the MALDI BioTyper software (version 2. 0, Bruker) and analyzed by standard pattern matching (with default parameter settings) against the spectra of the Bruker database (constantly incremented with our new spectra).