dataesr/scientific-paragraphs-categorization huggingface dataset:
All these methods show grouping significantly different from the metadata approach, and also demonstrate both the value and challenge of representative station classifications. These findings also suggest that trend analyses using the large number of observations available from surface ozone sites benefit from applying objective classification methods (TOAR-Surface ozone database;  Fleming et al. , 2018, hereinafter TOAR-Health). In the free troposphere local effects are less important and representativeness areas are larger. Typical correlation lengths in the free troposphere, for individual measurements, are about 500 km  (Liu et al. , 2009; Nastrom, 1977). However, the distances between ground-based observing sites are usually larger than this  (Figures 8, 15, 16, 21) , and as in the case of surface data, sites are unevenly distributed.
This will be independent of the metric used, as most of the metrics described in TOAR-Metrics are linear transformations of the measured data. The ozone trend found by  Cooper et al. (2010) , based on all available mid-tropospheric ozone measurements over western North America during 1984-2008 (more than 1200 data points per year on a 0. 2° × 0. 2° × 200 m grid), passed a number of statistical tests for robustness. However, in springtime, meteorological variability in ozone over western North America is large and heterogeneous in space and time (e. g. Lin et al. 2015a; Stauffer et al. , 2016). The  Cooper et al. (2010)  dataset was re-examined by  Lin et al. (2015b) , using chemistry-climate model hindcast simulations driven by observed meteorology. The GFDL-AM3 model co-sampled in space and time with observations reproduces the observed ozone trend (0.
Values of ozone absorption coefficients used before 1960 varied, however, and caused ozone to be underestimated by up to 11%. Overall, the 60 available datasets during 1896-1975 indicate an ozone mole fraction in the wellmixed unpolluted boundary layer that lies in the range 22 to 26 nmol mol -1. Comparison with modern measurements from the TOAR database suggests that surface ozone has increased by 32-71%, with large uncertainty, in rural air in the temperate and polar zones of the northern hemisphere, and by much smaller amounts in the southern hemisphere. This estimate depends much more on the modern region chosen for comparison than on   (Hardacre et al. , 2015; Bariteau et al. , 2010; Luhar et al. 2017 Luhar et al. , 2018)).
g. Butchart et al. , 2006; Butchart, 2014). In the lower troposphere increases will be offset by losses due to reaction with water vapour to produce OH  (Stevenson et al. , 2013). At some Arctic sites a long-term increase is observed in surface ODEs  (Tarasick et al. , 2014) , possibly related to changes in snow and sea ice cover  (Simpson et al. , 2007). Oil and gas extraction: Will increased activity in oil and/or gas fracking release NO x and VOCs, leading to high ozone formation? Measurement campaigns with surface monitors, measurements of other species; possibly at multiple sites. Vertical profiling would be useful. Near extraction areas. Sites with multi-year measurement records are of value for background climatology. the historical data, as when some of the historical datasets judged less reliable are omitted the results are quite similar.
Data Accessibility Statement No new measurements were made for this review article. All datasets discussed in the text were obtained from the published scientific literature. Lidar, FTIR, Umkehr and ozonesonde data used in this publication are publicly available, from the World Ozone and UV Data Centre (http://www. woudc. org) and the Network for the Detection of Atmospheric Composition Change (http://www. ndacc. org), and MOZAIC/IAGOS data at (http://www. iagos. org). Satellite data products are available at the URLs listed in Supplemental Material, Text S-12.
Acknowledgements The authors thank the many observers who, over many years, obtained the ozone measurements used in this study. Their careful work has stood the test of time and is gratefully acknowledged. Activity Centre Switzerland (QA/SAC-CH) , which is supported by  MeteoSwiss and Empa. OHP observations are funded by the  NDACC French program. The  Laboratoire Inter-universitaire des Systèmes Atmosphériques (LISA)  acknowledges the support from  CNES (Centre National des Etudes Spatiales)/TOSCA (Terre Océan Surface Continentale Atmosphère) ,  PNTS  ( Programme National de Télédétection Spatiale)  and  ANR (Agence Nationale de la Recherche  -project:  ANR-15-CE04-0005 ) for the development and production of ozone observations from IASI+GOME-2 and IASI. The  MLS, OMI  and  TES  projects are supported by the  National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Aura Program.
Despite the strong societal impact of natural hazards, their documentation remains incomplete, with only a few inventories exceeding the past two centuries. Surprisingly enough, this also applies to Europe, a densely populated territory, and to floods, which along with storms are the most common and damage-causing natural hazard in Europe. In addition, existing inventories have often been compiled by scientists and technicians and are used for risk management in a top-down manner, although the participation of all parties concerned has been recognized as a key factor for disaster reduction. To address this double paradox, the present article presents the regional flood risk observatory ORRION for the Alsatian region, north-eastern France, and its very rich data content. Stemming from two successive interdisciplinary and transnational French-German research projects, ORRION was designed as a participative online platform on which information is shared between individuals, stakeholders, engineers, and scientists.
e. temporal distribution of past events) and understand the dynamics of the potentially damagecausing phenomena over several centuries. In practice, however, spatially and temporally comprehensive databases dedi-Published by Copernicus Publications on behalf of the European Geosciences Union. F. Giacona et al. :  Improving the understanding of flood risk cated to natural hazards are relatively rare (e. g. Giacona et al. , 2017) , even in the case of hydrological risks (e. g. Guzzetti and Tonelli, 2004; Brázdil et al. , 2006; Hilker et al. , 2009; Martin, 2010; Wetter et al. , 2011; Lang et al. , 2012; Kjeldsen et al. , 2014; Veale et al. , 2017). From a different perspective, the information on natural hazards that is available to the public is generally summed up by researchers and/or managers.
Furthermore, it more often than not remains limited to the mapping of hazard-prone areas (e. g. InfoTerre, 2017, Internet portal managed by the French Geological Survey) and to mentions of remarkable and/or severe phenomena (e. g. French historical flood database, BDHI, 2017, http://bdhi. fr/; French avalanche database,  Bourova et al. , 2016). More rarely, comprehensive records in a given territory are offered (e. g. a historical database of floods in the lower Rhône River catchment, France, HISTRHONE database, 2017, https:// histrhone. cerege. fr/; French National Observatory for Natural Risks, Observatoire National des Risques Naturels, http://www. onrn. fr (last access: 20 June 2018) 2015; the British Hydrological Events database, 2019, http://www. cbhe. hydrology. org. uk/index. php).
All these databases only partially contribute to detailed knowledge based on the memory of the past. Instead, information is transferred in a one-way top-down manner, from experts to the public, to which "expert knowledge"  (Höppner et al. , 2012)  is exposed without a clear logic of dialogue  (Martin, 2006). Very few databases and platforms have been created to date as tools for sharing knowledge with mutual benefit between citizens, stakeholders, technicians, and scientists (e. g. Sangster et al. , 2018). Yet, the importance of public involvement and participation in environmental decision-making is now widely acknowledged and promoted, especially regarding risk management and/or knowledge capitalization  (Scarwell and Laganier, 2004; Kenyon, 2007; Koehler and Koontz, 2008; Fournier, 2010; Collombat, 2012; When et al.
Specifically, it is considered essential that the different actors, including the public, work together  (European Union, 2007; Challies et al. , 2016; Evers et al. , 2016). Fulfilling the wish of the European Floods Directive to establish closer cooperation between the European Union countries on this question, the French-German research programmes ANR-DFG TRANSRISK  (2008) (2009) (2010) (2011)  and TRANSRISK 2 (2014-2017) involved researchers from both the University of Haute-Alsace, Mulhouse (France), and the University of Freiburg im Breisgau (Germany). The interdisciplinary project team included hydrologists, climatologists, geographers, and historians. The TRANSRISK project thus made it possible to create a transnational database of historical floods in the south of the Rhine basin from the end of the 15th century to the present day.
, 2015a, b; 2017). Despite this broad outlook, however, a detailed analysis of floods that have affected all major rivers in this territory is still lacking. The TRANSRISK 2 project expanded the study area. It also defined as a specific goal the strengthening of the collaboration between local authorities and relevant administrations in terms of flood risk management. More broadly, it aimed at involving all the stakeholders concerned. During the project, the information required to implement the Flood Risk Prevention Plan (PPRI), the Flood Prevention Action Programme (PAPI), and local flood risk management strategies (Directive 2007/60/EC) was provided to the services in charge of these programmes. In return, the latter contributed to the database by providing feedback from their archives or from local populations.
It is in this context that the participative database OR-RION (Regional Observatory of Flood Risks) was launched. As a first step, currently, it only considers the French part of the study area (e. g. the Alsace region within its 2015 administrative boundaries). This original initiative was elaborated with the dual objective of (a) making the information collected by the research programmes available to everyone and (b) gathering information from all those involved in the local risk area. Indeed, it is believed that by collecting the different types of knowledge  (expert, layperson, administrative, and scientific) , one can hope to achieve a global, integrated approach to the risk problem  (Decrop, 1997). The TRANSRISK 2 research programme aims, in particular, at establishing the risk in its territory through the enhancement and sharing of local knowledge.
, 2017). The current article presents this original approach, involving both the creation of a database within the framework of a basic research project and the process by which it has been made available to the wider public who can enrich it in return. To address the need for developing long territorialized hazard and risk chronologies, the proposed analysis uses the information gathered, making it possible to highlight the main characteristics of the floods that have affected the Alsace, mostly since the end of the 15th century but even before that period for a few rivers and over more than one millennium for the Rhine River. After providing a brief overview of the territorial context of the study area, special attention is paid to presenting the data entered in ORRION as well as to the structure of the sharing platform.
For detailed analyses, two specific classifications are proposed to further distinguish the floods based on the rivers that were affected and the damage reported. Simple statistical methods are then systematically applied to infer the main patterns in flood causes, consequences, spatial extent, temporal distribution, and seasonality, etc. Further analyses at the scale of selected rivers and municipalities are also presented. All these illustrate the potential of ORRION, both for providing useful data to risk managers and for further improving our geophysical and socio-economical understanding of flood risk in the target area. Finally, the main outcomes, advantages, and limits of the work are discussed, and further perspectives are suggested.
From the TRANSRISK database to ORRION online A large part of the information currently stored in ORRION comes from the database built during the TRANSRISK project using geohistorical methods. The latter compiles information derived mainly from the analysis of archives (departmental and communal) as well as from scientific publications, local non-scientific literature, and a few newspapers. The research focused on the main rivers of the Alsace in France (Largue, Ill, Doller, Thur, Fecht, and Lauch) and of the Baden region in Germany (Wiese, Klemmbach, Kander, Neumagen/Möhlin, Dreisam, Elz, Schutter, and Kinzig), as well as on the Rhine River. The database contains more than 3000 entries (for each watercourse, each flood counts as one entry) of varied magnitude and extent. Most of these floods occurred between 1480 and 2015, although a few entries refer to even older floods.
Details about the data, the sources, and the historical methodology can be found in  Himmelsbach et al. (2015). The tambora. org database provides the data for the German part  (Riemann et al. , 2015; Glaser et al. , 2016). The TRANSRISK database was designed by researchers for academic purposes. In order to facilitate data sharing, it was decided to build a regional observatory for flood risk (ORRION). The ORRION website was launched in 2015 after its conceptual phase and its construction during 2014. The design of ORRION was guided by a SWOT analysis of flood risk databases already existing at that time: the French National Observatory for Natural Risks, the French database on historical floods (BDHI), the database of the French Restauration des Terrains en Montagne services (2017), and the regional risk observatory in the Provence-Alpes-Côte d'Azur region (south-eastern France).
The last one, like our study case, is based not on the French national scale but a regional scale. However, all these databases have a complex or unattractive interface and do not meet the essential requirement of our objectives. Indeed, in these examples, the collaborative aspect concerns government services only, de facto excluding citizens. Conversely, the objective of the OR-RION database was not only to make raw data on historical floods in Alsace region available to all stakeholders but also to provide a tool allowing all types of actors to actively take part in the compilations of flood risk knowledge in a collective approach. Quality control of the data collected with this participative approach is a crucial part of the database management work. The team of database administrators verifies possible redundancy with pre-existing information, directly interacts with the information providers, checks by itself the provided sources (e.
Structure of the ORRION website and presentation of the data The website ORRION was designed in this sense in partnership with the company CYSTEME. To minimize management difficulties, it is not structured along the lines of a "classic" online database but is built on a CMS structure (WordPress type). It is composed of four main parts (Fig. 2 ). The home page reflects the territorial establishment of OR-RION and provides information regarding local flood risk management procedures. A second page, called "overview," presents the research programme TRANSRISK (objectives and administrators of the website) and the main characteristics of floods that took place in the Alsace. The third section leads to the database itself. A general map localizes all the floods recorded in the area and gives access to detailed information.
A contact form is accessible both on the "database" page and directly on the home page. It allows anyone to contribute to ORRION's comprehensiveness by sharing their information and knowledge about floods in the target area. Of course, information provided this way by online contributors is cross-checked by administrators before it is integrated in the database. As the website is intended to inform and to share information in the particular context of a cross-border territory, it has a bilingual presentation (French and German). With the same perspective of sharing, communicating, and informing, ORRION benefits from a link to a Facebook page intended to increase the visibility and the attractiveness of the website, via, for example, the regular publication of photos (especially public contributions) or former postcards illustrating old floods.
Finally, as confirmation of its territorial establishment, since 2017, ORRION has provided information on its home page regarding various ongoing local procedures related to flood risk management, information, and prevention. In addition to the participatory nature of the database, three other important factors differentiate the ORRION and TRANSRISK databases. First, the latter deals with the whole Upper Rhine Valley (French and German sides), whereas ORRION focuses only on the French side. Second, supplementary research was carried out for ORRION in the departmental archives of the Bas-Rhin and of the Haut-Rhin, enriching the information on floods that occurred in particular during the 19th and 20th centuries. Third, data are structured by "event" in ORRION: each event on the website corresponds, at the scale of the entire study area, to a set of local floods that likely resulted from the same meteorological drivers (same synoptic situation, similar soil saturation state, etc.
). This is why there are far fewer ORRION events than entries in the TRANSRISK database, where each river flood is a single entry. Specifically, each ORRION event includes all rivers where a flood occurred within the same time win-dow of 10 d (the downstream travel time of the flood wave may take several days). As a consequence, an ORRION event may correspond to one river that overflowed in one specific location (or to a more generalized extent) or to a situation in which water overflow has been reported for almost all major Alsatian rivers at the same time and often at several locations along the rivers. Note that, in addition to a variety of river flood types, ORRION also reports on some mass movements due to local storms and on floods by surface runoff or by rising groundwater. Here, however, we focus only on river floods, and thus the latter types of events have not been taken into account.
In ORRION, events were characterized as precisely as possible, taking into account the fact that descriptions in the historical sources are largely heterogeneous, which makes it difficult to produce homogeneous data. Thus, for each event, different fields are filled in when the information is available (Fig. 2d ): date of occurrence, i. e. day/month/year, month/year, or year; affected rivers; impacted municipalities; causes, of which one or several causes (if any) can be documented for each event; damage types, which can be human (i. e. with at least one person killed), material, functional, environmental, or unknown and of which zero to four damage types can be documented for each event; number of sources reporting the event; the complete quotes accompanied by their sources. Moreover, the database structure allows one to include tables and photos via hypertext links (Fig.
Further filtering and additional event typologies For this specific work, four additional filters were applied for all the ORRION data. First, this article does not consider low-magnitude events during which no river overflowed its banks. Such events were discarded. By contrast, every event during which water overflow occurred for at least one river was retained, as we wanted the most exhaustive overview  possible of each event. Hence, for each event, we distinguished between rivers for which flooding without water overflow was described (i. e. simply an "abnormally high" runoff) and rivers with water overflow. Second, this study deals only with floods from overflowing rivers and does not include surface runoff or rising groundwater. As a consequence, from the whole set of flood causes documented in the ORRION database, we retained only heavy rainfall, long-lasting precipitation, snow melting/thaw, ice jams, ice break-up, thunderstorms, and soil saturation.
Himmelsbach et al. (2015)  proposed a classification of flood severity for TRANSRISK events, taking into account the same criteria, plus secondary and tertiary parameters such as the duration of the flood or the mitigation strategies that were implemented. The scale of  Himmelsbach et al. (2015)  has three levels ranging from "small flood" to "extreme/supra-regional flood. " However, this scale could not be used. For our events, the sources do not often allow the necessary secondary and tertiary criteria to be identified. Indeed, since our study covers a multisecular period, the available data are disparate, both qualitatively and quantitatively. The corpus of events is thus affected by different major types of heterogeneity  (Martin et al. , 2015a, b) : the nature of the sources evolves in time and space, and the mass of documentation tends to increase with time.
Most of the events have occurred since the end of the 15th century, but a few of them occurred earlier for distinct rivers, especially the Rhine, for which the time frame covered extends over more than one millennium. This article has shown that information accumulated this way and its organization by event is sufficiently rich and convenient to significantly update what was known to date about floods in the greater Alsatian region  (Himmelsbach et al. , 2015; Martin et al. , 2017, and previous work). Specifically, it allows us to complement the results already obtained at the much larger scale of major European rivers  (Glaser et al. , 2010)  and for specific events in the database  (Martin et al. , 2010). For instance, comprehensive flood occurrence data are now available for many rivers and municipalities with a careful distinction of floods with and without overflow and according to specific typologies regarding the hydrological configuration, causes, and severity of each event.
Changes related to sources and documentation of past events The way the search is conducted through the archives (systematic or not, etc. ) influences the results. Thus, it is not relevant to look at trends before the end of the 15th century. The TRANSRISK research programme began its study at that time. Older records are periodic and generally attributed to indirect sources that have rarely been verified. It should also be noted that the systematic search in the archives focused on the 19th and 20th centuries only, a period that enjoyed certain homogeneity in terms of production and conservation of archives  (Lang et al. , 2003; Giacona et al. , 2017). However, some recent events are missing or incomplete in the ORRION database because documents related to them were not already available in the departmental archives.
The floods of April and May 1983 were major floods indeed, but they appear in our chronology as Class III events only (10 impacted municipalities for both floods) because departmental archives are still incomplete for this recent period. Additional searches were conducted in the local press within the framework of TRANSRISK 2 , generating a huge number of new data currently not integrated into the ORRION database. This is certainly the most important factor explaining flood nonstationarity in our chronologies. For instance, the slight (and counterintuitive) increase in the number of Class III events over time is certainly partly due to the more systematic research conducted over the last two centuries. Moreover, as already mentioned, the appearance of Class IV events at the end of the 17th century constitutes an artefact linked to our typology and to more incomplete and/or less detailed sources for the earlier periods.