archaologisches-inventar

culture

fr: Culture, médias, société de l'information, sport

de: Kultur, Medien, Informationsgesellschaft, Sport

geography

de: Geographie

population

fr: Population

de: Bevölkerung

title_for_slug: archaologisches-inventar

de: archaologie inventar schutzgebiet

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: L'Inventaire archéologique du canton de Berne comprend tous les sites archéologiques connus dans le canton. Un site archéologique peut recouvrir différentes choses ; il peut s'agir de la découverte d'un objet isolé ou de structures aménagées complexes et étendues, enfouies dans le sous-sol. Si des projets d’aménagement du territoire et d’infrastructures ou des projets de construction comprennent un site archéologique ou se trouvent à proximité du périmètre prévu pour le projet, nous recommandons de contacter le Service archéologique au préalable afin de vérifier si de la substance archéologique risque d’être touchée. Le Service archéologique peut être contacté pour ces questions au numéro de téléphone central 031 633 98 98 ou par courriel à adb.bauen@be.ch. Les trouvailles archéologiques sont la propriété du canton de Berne. Les fouilles et l'usage de détecteurs de métaux dans le but de rechercher des objets archéologiques est punissable.

de: Das Archäologische Inventar des Kantons Bern enthält sämtliche bekannten archäologischen Fundstellen des Kantons. Eine Archäologische Fundstelle kann vom einzelnen Fundgegenstand bis zu komplexen und grossflächig im Boden erhaltenen Siedlungs- und Baustrukturen ganz unterschiedliche Dinge umfassen. Sollten bei Projekten der Raumplanung und der Infrastruktur oder bei Bauvorhaben archäologische Fundstellen im oder in der Nähe des geplanten Projektperimeters liegen, so empfehlen wir den vorgängigen Kontakt zum Archäologischen Dienst, damit für das jeweilige Projekt geprüft werden kann, ob die Archäologie betroffen sein wird. Der Archäologische Dienst ist für solche Anfragen erreichbar unter der zentralen Telefonnummer 031 633 98 98 oder per Email an adb.bauen@be.ch. Archäologische Funde sind Eigentum des Kantons Bern. Grabungen und der Einsatz von Metalldetektoren ohne Bewilligung sind strafbar.

name: Amt für Kultur des Kantons Bern - Archäologischer Dienst

fr: Inventaire archéologique

de: Archäologisches Inventar


geography

fr: Géographie

en: Geography

it: Geografia

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

fr: infrastructure-routiere trafic-routier concession route trafic transport-de-marchandises-lourdes transport-maritime

de: verkehrsinfrastruktur strassenverkehr konzession strasse verkehr schwerlastverkehr seeverkehr

label: geocat.ch permalink

state: active

type: dataset

fr: Service de téléchargement (WFS)

de: Downloaddienst (WFS)

format: WFS

fr: Le service représente les données de base du canton de Berne selon la géocatégorie P conforme à eCH-0166. Il comprend les géoproduits suivantes: * Restrictions de circulation sur les routes cantonales * Fichier d'obstacles réseau routier concernant les transports spéciaux * Routes pour les transports exceptionnels * Réseau routier de rang supérieur du canton de Berne * Voies de communication historiques BE * Données relatives au trafic sur les routes cantonales * Bouées et objets de concession navig. de plaisance

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie P gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Verkehrsbeschränkungen auf Kantonstrassen * Hinderniskartei Strassennetz bzgl. Ausnahmetransporte  * Versorgungsrouten für Ausnahmetransporte * Übergeordnetes Strassennetz des Kantons Bern * Historische Verkehrswege des Kantons Bern * Kantonsstrassenverkehrsdaten * Bojen und Konzessionsobjekte Seeverkehr

format: SERVICE

fr: Office de l'information géographique du canton de Berne

de: Amt für Geoinformation des Kantons Bern

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.

political_level: canton

capacity: public

type: organization

approval_status: approved

value: Bern-Kt - Geocat Harvester

fr: Thèmes de transport 02 (WFS)

de: Verkehrsthemen 02 (WFS)


fremdenverkehrsgemeinden

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito

title_for_slug: fremdenverkehrsgemeinden

fr: zone-touristique tourisme habitation commune

de: touristengebiet fremdenverkehr wohnung gemeinde

format: WMS

format: ZIP

fr: L’acquisition d’immeubles par des personnes à l’étranger est subordonnée à une autorisation de l’autorité cantonale compétente. L'achat d'un logement de vacances ou un appartement dans un apparthôtel ne peut être approuvé que si le logement est situé dans un lieu à vocation touristique désigné par le canton. (Acquisition d'immeubles par des personnes à l'étranger (<https://www.weu.be.ch/fr/start/themen/wirtschaft-und-arbeit/aufsicht-pruefen-kontrollieren/marktaufsicht.html>))

de: Personen im Ausland bedürfen für den Erwerb von Grundstücken einer Bewilligung der zuständigen kantonalen Behörde. Der Erwerb einer Ferienwohnung oder einer Wohneinheit in einem Aparthotel kann nur dann bewilligt werden, wenn sich die Wohnung in einem vom Kanton bezeichneten Fremdenverkehrsort befinden. (Grundstückerwerb durch Personen aus dem Ausland (<https://www.weu.be.ch/de/start/themen/wirtschaft-und-arbeit/aufsicht-pruefen-kontrollieren/marktaufsicht.html>))

spatial: Kanton Bern (erweitert)

fr: Communes à vocation touristique

de: Fremdenverkehrsgemeinden


geography

de: Geographie

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

fr: autorite-regionale departement-uk chasse animal-sauvage tribunal route site-historique ingenierie registre-foncier limite-administrative commune planification-regionale bordure bois

de: regionalbehorde landkreis jagd wildtier gericht strasse historischer-standort ingenieurwesen grundbuch verwaltungsgrenze gemeinde regionalplanung grenze wald

fr: Service de consultation (WMS)

de: Darstellungsdienst (WMS)

fr: Le service représente les données de base du canton de Berne selon la géocatégorie D conforme à eCH-0166. Il comprend les géoproduits suivantes: * Des fusions de communes depuis 2000 * Divisions forestières * Inventaires des bornes * Arrondissements du registre foncier généralisés * Cercles électoraux * Arrondissements de l'Office des ponts et chaussées * Tribunaux régionaux des mesures de contrainte * Conférences régionales * Arrondissements du registre foncier * Secteurs de surveillance de l'insp. de la chasse

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie D gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Gemeindefusionen seit 2000 * Waldabteilungen * Steininventare * Grundbuchkreise generalisiert * Wahlkreise * Tiefbauamtkreise * Regionale Zwangsmassnahmengerichte * Regionalkonferenzen * Grundbuchkreise * Wildhüteraufsichtskreise

fr: Limites politiques et administratives 01 (WMS)

de: Politische und administrative Grenzen 01 (WMS)


geography

fr: Géographie

fr: prevention-des-incendies-de-foret service-dincendie incendie-de-foret gestion-forestiere

de: waldbrandverhutung feuerwehr waldbrand forstwirtschaft

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Le géoproduit présente les sites définis pour les panneaux d'interdiction de faire du feu. Ils ont été définis par le service forestier cantonal, en collaboration avec les communes ou d'autres partenaires. Lorsqu'une interdiction de faire du feu a été promulguée dans un ou plusieurs arrondissements administratifs par les préfectures, l'organisme désigné organise l'accrochage des panneaux et leur retrait.

de: Das Geoprodukt zeigt die definierten Standorte für die Feuerverbotsschilder. Die Standorte wurden vom kantonalen Forstdienst in Zusammenarbeit mit Gemeinden oder weiteren Partnern definiert. Wenn in einem oder mehreren Verwaltungskreis(en) von den Regierungsstatthalterämtern ein Feuerverbot erlassen wurde, organisiert die im Geoprodukt bezeichnete Stelle das Auf- und Abhängen.

name: Amt für Wald und Naturgefahren - Naturgefahren

fr: Sites définis pour les panneaux d'interdiction de faire du feu


culture

fr: Culture, médias, société de l'information, sport

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

it: Cultura, media, società dell'informazione, sport

energy

fr: Energie

de: Energie

en: Energy

it: Energia

fr: structure-batie alimentation-en-eau eau-substance responsabilite deversement-des-eaux-usees eau-usee

de: bauwerk wasserversorgung wasser zustandigkeit abwasserbeseitigung abwasser

fr: Le géoproduit SOELWA comprend la version numérisée de la GICP, qui a été autorisée par l'OED en qualité d'autorité directrice dans le cadre d'une procédure de droit public. Il s'agit d'une restriction de droit public à la propriété foncière qui sera ensuite traitée par la commune à partir de 2023 et publiée comme géoproduit dans le cadastre RDPPF.

de: Das Geoprodukt SOELWA umfasst die digitale/digitalisierte Version der öffentlich-rechtlichen Sicherungen von öffentlichen Leitungen (SöL), die vom AWA im Rahmen eines UeO-Verfahrens in Funktion der Leitbehörde genehmigt wurden. Dabei handelt es sich um eine öffentlich-rechtliche Eigentumsbeschränkung und wird ab 2023 gemeindeweise aufgearbeitet und als Geoprodukt als auch im ÖREB publiziert.

spatial: Kanton Bern (reduziert)

name: Amt für Wasser und Abfall - Siedlungswasserwirtschaft / Trinkwasser und Abwasser

fr: Office de l'information géographique du canton de Berne

de: Amt für Geoinformation des Kantons Bern

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

fr: Procédure de garantie d’implantation des conduites publiques (GICP)

de: Öffentlich-rechtliche Sicherungen von öffentlichen Leitungen (SöL)


territory

fr: Territoire et environnement

fr: geophysique trou-perce decharge relief traceur gaz-naturel radon roche atmosphere-du-sol decomposition temperature-du-sol transport sciences-naturelles geologie temperature-de-surface-du-sol structure-regionale pergelisol geomorphologie geoelectrique sismologie eaux-souterraines erosion

de: geophysik bohrloch deponie relief tracer erdgas radon fels bodenluft abbau bodentemperatur transport naturwissenschaft geologie bodenoberflachentemperatur raumstruktur permafrost geomorphologie geoelektrik seismik grundwasser erosion

fr: Service de téléchargement (WFS)

de: Downloaddienst (WFS)

fr: Le service représente les données de base du canton de Berne selon la géocatégorie F conforme à eCH-0166. Il comprend les géoproduits suivantes: * Sondages géologiques * Carte du toit du rocher * Concentration de radon à l'intérieur des bâtiments * Typologie des ensembles naturels * Géotopes d'importance régionale * Ligne de connexion du traceur * Pergélisol * Carte des gisements de matières premières EDT

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie F gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Geologische Sondierungen * Felsreliefkarte * Radonkonzentration in Innenräumen * Naturraumgliederung * Geotope von regionaler Bedeutung * Tracer Verbindungslinien * Permafrost * Geologische Rohstoffkarte ADT

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.

fr: Géologie, sols et dangers naturels 02 (WFS)

de: Geologie, Böden und naturbedingte Risiken 02 (WFS)


geography

fr: Géographie

de: Geographie

de: Raum und Umwelt

fr: frontiere-infranationale lac frontiere-nationale limite-administrative commune bordure eaux-interieures administration

de: innerstaatliche-grenze see staatsgrenze verwaltungsgrenze gemeinde grenze binnengewasser verwaltung

fr: Le service représente les données de base du canton de Berne selon la géocatégorie D conforme à eCH-0166. Il comprend les géoproduits suivantes: * Limites politiques généralisées * Limites politiques

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie D gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Politische Grenzen generalisiert * Politische Grenzen

fr: Limites politiques et administratives 02 (WFS)

de: Politische und administrative Grenzen 02 (WFS)


fr: gestion-des-ressources-en-eau reseau-de-mesure analyse-de-leau eau-de-surface source cascade eau-substance surveillance-biologique ecosysteme roche qualite-de-leau ressource-en-eau eau-propre-a-la-consommation surveillance-de-leau fond-de-leau extraction-deau eaux-geographie zonage energie percolation diversite-biologique eaux-interieures environnement eaux-souterraines energie-hydraulique organisme-aquatique

de: wasserbewirtschaftung messstellennetz wasseruntersuchung oberflachengewasser quelle wasserfall wasser biomonitoring okosystem fels wassergute wasserressourcen gebrauchswasser wasseruberwachung gewassersohle wasserentnahme gewasser zoneneinteilung energie versickerung artenvielfalt binnengewasser umwelt grundwasser wasserkraft wasserorganismen

fr: Le service représente les données de base du canton de Berne selon la géocatégorie I conforme à eCH-0166. Il comprend les géoproduits suivantes: * Gisements d'eau souterraine en roches meubles * Qualité des cours d'eau * Zones d'infiltration * Prélèvements d’eau dans les eaux de surface * Habitat des sources * Bases de la planification des revitalisations * Planification stratégique des revitalisations * Stratégie d'utilisation de l'eau

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie I gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Grundwasservorkommen in Lockergestein * Qualität der Oberflächengewässer * Versickerungszonen * Wasserentnahmen aus Oberflächengewässern * Lebensraum Quellen * Revitalisierungsplanung Grundlagen * Strategische Revitalisierungsplanung * Wassernutzungsstrategie

fr: Hydrographie 03 (WFS)

de: Gewässer 03 (WFS)


grundlagenkarte-walderschliessung

agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura

title_for_slug: grundlagenkarte-walderschliessung

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Le produit montre l'état actuel de la desserte des forêts dans une perspective cantonale. À l'aide de modèles, une carte de référence de la qualité de la desserte et une carte de la densité de desserte ont été produites. Ces bases sont complétées par des informations sur la praticabilité des chemins forestiers et sur les unités de desserte. Le produit sert de base pour la planification de projets de desserte forestière avec le soutien de l'OFDN par les propriétaires forestiers.

de: Das Produkt zeigt in einer gesamtkantonalen Sicht den aktuellen Stand der Erschliessung der Wälder auf. Anhand von Modellen wurde eine Hinweiskarte zur Erschliessungsgüte und eine Karte zur Dichte des bestehenden Güterstrassennetzes im Wald erstellt. Ergänzt werden diese Grundlagen mit Angaben zur Befahrbarkeit der Güterstrassen und -wege im Wald, sowie zu den Erschliessungseinheiten. Das Produkt dient als Grundlage für die Planung von Walderschliessungsprojekten mit Unterstützungen des AWN durch die Waldeigentümer.

spatial: Kanton Bern

name: Amt für Wald und Naturgefahren - Fachdienste und Ressourcen

fr: Carte de base de la desserte des forêts

de: Grundlagenkarte Walderschliessung


maintainer: Yves Bühler

en: ramms release avalanche snow hazard-mapping hazard-indication-mapping

en: Potential Release  Area  NHESS

media_type: application/zip

en: This folder contains the output of the different investigated algorithms plus the reference dataset, used for training and validation.

mimetype: application/zip

en: RAMMS simulations NHESS

en: Simulated maximum pressures for the scenarios frequent and extreme taking the forest layer into account

en:
This dataset contains the output and reference data published in the paper "Automated snow avalanche release area delineation - validation of existing algorithms and proposition of a new object-based approach for large scale hazard indication mapping" Yves Bühler, Daniel von Rickenbach, Andreas Stoffel, Stefan Margreth, Lukas Stoffel, Marc Christen (2018) Natural Hazards And Earth System Sciences.

Abstract:
Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche cadastre information, terrain analysis, climatological datasets and numerical modelling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations.

In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche cadastre data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff mapped most avalanches in detail since many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference datasets. Because all tested algorithms do not provide meaningful delineation between individual potential release areas (PRA), we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10 – 30 years return period) and extreme (100 – 300 years return period). This approach opens the door for large scale avalanche hazard indication mapping in all regions where high quality and resolution digital terrain models and snow data are available.

avalanche

display_name: avalanche

hazard-indication-mapping

display_name: hazard-indication-mapping

hazard-mapping

display_name: hazard-mapping

ramms

display_name: ramms

release

display_name: release

snow

display_name: snow

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

political_level: other

key: guid

key: uri

value: Envidat Harvester

en: Automated Avalanche Release Area (PRA) Delineation Davos


geography

en: Geography

fr: Service de consultation (WMS)

de: Darstellungsdienst (WMS)

fr: Le service représente les données de base du canton de Berne selon la géocatégorie S conforme à eCH-0166. Il comprend les géoproduits suivantes: * Les cultures agricoles (provisoires) * Les cultures agricoles

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie S gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Landwirtschaftliche Kulturen (provisorisch) * Landwirtschaftliche Kulturen

fr: Office de l'information géographique du canton de Berne

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.


fr: Géographie

de: Geographie

territory

fr: Territoire et environnement

de: Raum und Umwelt

fr: zone-de-protection-du-paysage zone-construite planification-de-lespace-physique commune eaux-geographie zonage cadastre amenagement-du-territoire planification

de: landschaftsschutzgebiet baugebiet raumplanung gemeinde gewasser zoneneinteilung kataster raumordnung-und--planung planung

fr: La carte synoptique des zones offre une vue d'ensemble simplifiée, tant du point de vue du contenu que des contours géographiques, des plans d'aménagement local approuvés par l'Office des affaires communales et de l'organisation du territoire. Elle indique: · une vue synoptique des origines des plans de zone, · les zones à bâtir (réparties en 28 catégories), · les périmètres des zones à planification obligatoire et des plans de quartier, · les zones de protection du paysage, · les périmètres des plans de protection des rives en vertu de la loi sur les rives des lacs et des rivières.

de: Der Übersichtszonenplan ist eine räumlich und thematisch generalisierte Zusammenfassung der vom Amt für Gemeinden und Raumordnung genehmigten Ortsplanungen der Gemeinden. Er enthält: · eine Übersicht der Herkunft der Zonenpläne; · die Bauzonen in 28 Kategorien; · die Perimeter der Überbauungsordnungen und der Zonen mit Planungspflicht; · die Landschaftsschutzgebiete; · die Perimeter der Uferschutzplanungen nach See- und Flussufergesetz.

de: Amt für Geoinformation des Kantons Bern

fr: Carte synoptique des zones 1:25'000

de: Übersichtszonenplan 1:25'000


mosaic-snow-on-sea-ice-data

title_for_slug: mosaic-snow-on-sea-ice-data

en: surface-mass-balance drifting-and-blowing-snow snow-distribution spatial-variability arctic-sea-ice

en: ALPINE3D setup for MOSAiC

media_type: various

en:
The zip file contains a folder structure that must be kept as it is in order to run the simulation in the current configuration.
The setup contains both input and output data as well as the model configuration as used in the submitted manuscript
"Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

The zip file contains 3 main folders:
* base_setup_files
* a3d_jgr_alpha1
* a3d_jgr_alpha3

The "base_setup_files" contains all input files that are necessary to run the reference (R) simulation ("a3d_jgr_alpha1" folder) and the comparison "C" scenario ("a3d_jgr_alpha3") folder. In the a3d_jgr_alpha1 and a3d_jgr_alpha3 folders you find the corresponding outputs as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each a3d_jgr_alphax/setup/io.ini file. The input data is already linked accordingly in each io.ini file.

a3d_jgr_alpha1 also contains the detailed snow profiles for each point along the transects.

To reproduce the results, download and compile the source code for the adjusted ALPINE3D model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/alpine3d.git under the "alpine3d_mosaic" branch. After installing, you can run the provided model setup uploaded here.

en: SNOWPACK setup for MOSAiC

en:
 The zip file contains both input and output data as well as the model configuration as used in the submitted manuscript "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

The zip file contains 2 main folders:
* SNOWPACK_JGR_ALPHA1
* SNOWPACK_JGR_ALPHA3

In the SNOWPACK_JGR_ALPHA1 (reference "SP_R" simulation) and SNOWPACK_JGR_ALPHA3 (comparison "SP_C" scenario) folders you find the corresponding inputs, outputs and configuration as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each SNOWPACK_JGR_ALPHA/setup/io.ini file. The input data is already linked accordingly in each io.ini file.

To reproduce the results, download and compile the source code for the adjusted SNOWPACK model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/snowpack.git under the "snowpack_mosaic" branch. After installing, you can run the provided model setup uploaded here.

en:
Data accompanying David Wagners' Dissertation.
Covers model results and various input from ALPINE3D and SNOWPACK adjusted for sea ice during MOSAiC.

arctic-sea-ice

display_name: arctic-sea-ice

drifting-and-blowing-snow

display_name: drifting-and-blowing-snow

snow-distribution

display_name: snow-distribution

spatial-variability

display_name: spatial-variability

surface-mass-balance

display_name: surface-mass-balance

en: MOSAIC Snow on Sea Ice Data


mountain-permafrost-hydrology

maintainer: Jeannette Noetzli

title_for_slug: mountain-permafrost-hydrology

en: monitoring-techniques ice-rich-permafrost permafrost-degradation climate-change-impacts mass-movements mountain-permafrost-hydrology

en: DORA Persistent URL

media_type: PDF

format: PDF

en: Synthesis report chapter of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN)

en: This report was prepared as one of the synthesis report chapters of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN). In earlier reports such as the CH2014-IMPACTS report (CH-Impacts 2014), the topic of mountain permafrost hydrology was not addressed. Here, we provide a baseline of the available knowledge of mountain permafrost in the Swiss Alps for future reference. We compile an overview of the current understanding of mountain permafrost in the Swiss Alps, its distribution and characteristics, observed and projected changes, and expected impacts on slope stability, infrastructure and hydrological aspects. We also briefly describe the measurement techniques and modelling approaches applied. The chapter closes with a summary of the most important open research questions. The literature cited mainly includes studies on mountain permafrost published in scientific journals and assessments of long-term observation data. We focus on permafrost hydrology interactions wherever information is available. However, systematic studies on permafrost hydrology in mountain areas are still limited.

climate-change-impacts

display_name: climate-change-impacts

ice-rich-permafrost

display_name: ice-rich-permafrost

mass-movements

display_name: mass-movements

monitoring-techniques

display_name: monitoring-techniques

mountain-permafrost-hydrology

display_name: mountain-permafrost-hydrology

permafrost-degradation

display_name: permafrost-degradation

en: Mountain Permafrost Hydrology


territory

en: Territory and environment

fr: registre-foncier planification-politique droit-de-propriete cadastre amenagement-du-territoire propriete developpement-durable

de: grundbuch politikplanung eigentumsordnung kataster raumordnung-und--planung eigentumsrecht nachhaltige-entwicklung

fr: Le service représente les données de base du canton de Berne selon la géocatégorie E conforme à eCH-0166. Il comprend les géoproduits suivantes: * Catégories des propriétés foncières * Aperçu du cadastre des conduites * État d'une commune dans le cadastre RDPPF * Le développement durable (DD) dans les communes * Portefeuille immobilier de l’Office des immeubles et des constructions

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie E gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Grundeigentumskategorien * Übersicht Leitungskataster * Stand einer Gemeinde im ÖREB-Kataster * Nachhaltige Entwicklung in den Gemeinden * Immobilienportfolio des Amts für Grundstücke und Gebäude

fr: Développement territorial et cadastre foncier 05 (WMS)

de: Raumplanung und Grundstückskataster 05 (WMS)


maintainer: Axel Volkwein

en: rockfall experiment natural-hazards field-test field-data trajectory mass-movements field-tests experiments

en: These data contain the point clouds obtained from laser scanning the test slope and the six test blocks used for the experiments. The coordinates of the slope are given in CH-1903 format. The coordinates of the block point clouds are kept in a lokal x/y/z coordinate system.

en: Jumps and impacts

media_type: ascii, tab separated, also as excel table

en: This table contains data of more than 2200 of each jumps and impacts of the test blocks on a grassy slope. It gives there durations in combination with acting accerlartions and the rotational speed of the blocks. The data were retrieved using the block internal accelerometer and rotation sensors. The combination of these data with the measurement from the local positioning system allows the deduction of jump lengths, slope gradient etc.

en: Block trajectories recorded from local positioning system

media_type: ascii, tab separated, also as Excel table

en: This file contains more than 80 rockfall trajectories projected onto the terrain, i.e. the positions of the single blocks over time during the single tests that were recorded by the local positioning system with about 10Hz. It contains the detected positions as well as a smoothened path (see Volkwein et al., Geosciences, 2018). The table also contains the derived velocities and accelerations along the slope (attention: these accelerations are the once that occur during an impact).

en: Overview of all tests

media_type: ZIP

en:
This table gives an overview on all tests performed including
- block used
- start & end position
- number of jumps
- etc.
-

en:
In summer 2014, 6 rock blocks between 20 and 80kg have been thrown in total 111 times down a slope at the Swiss Oberalppass close to the village Tschamut. The slope was mainly covered by grass and its lower part was flat and large enough to provide natural runouts of the single trajectories.

An extensive measurement program has been set up to measure the block trajectories: With surveyor's instruments the slope and the six used rock blocks were scanned and the start and end positions of each test were recorded. During the single events two cameras filmed the trajectories. A special sensor device located within the blocks recorded the acting accelerations and rotational speeds over time. Further, the device emitted a Wifi signal that got detected from eight receivers around the slope. Based on this signal the block position has been recorded over time.

The dataset contains all data that were gathered through above field campaign.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

trajectory

display_name: trajectory

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Repetitive trajectory testing in Tschamut 2014


maintainer: Henning Löwe

en: discrete-element-modelling fast-sintering grain-shape granular-snow angle-of-repose

media_type: text/plain

format: TXT

mimetype: text/plain

en: Angle of repose and 3D CT images

en:
5 Snow types were examined and glass beads as a cohesion-less reference, named as follows:

RG: rounded grains (sieved with 0.7 - 1.4 mm)

FC: faceted grains (1.4 - 2 mm)

FCS: small faceted grains (0.7 - 1.4 mm)

IB: ice beads (4 mm)

IBS: small ice beads (2 - 2.2 mm)

GB: glass beads(2 mm)

en:
Angle of repose experiments were performed with different snow types at temperatures between -2 and -40°C. They were used to examine granular snow dynamics on the grain-scale with focus on the role of grain shape and cohesion. The angle of repose was observed by sieving snow onto a round, freestanding base until a stationary heap was formed.

This dataset consists of 1) the images of the experimental heaps that were taken to determine the angle of repose, 2) one binary 3D micro computed tomography image of each snow type. The CT images were taken with the SLF micro-CT40 to characterize snow properties and grain shape.

The experiments with natural snow types (rounded and faceted grains) and spherical model snow allowed for an examination of the differences in granular properties between natural grain shapes and spherical particles in view of Discrete Element Modelling. With the chosen temperatures, the effect of sintering could be observed that increases the angle of repose with increasing temperature.

angle-of-repose

display_name: angle-of-repose

discrete-element-modelling

display_name: discrete-element-modelling

fast-sintering

display_name: fast-sintering

grain-shape

display_name: grain-shape

granular-snow

display_name: granular-snow

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Angle of repose experiments with natural and spherical snow


en: natural-hazards protective-effect compound-events drought extreme-events forest-fire protection-forest bark-beetles

media_type: application/pdf

en: Factsheet summarising the key results of the study (in German).

mimetype: application/pdf

en: Description of the study site, extreme event (trigger event) and informations about the survey.

en: Conclusions and recommendations of the project (in German).

en: Factsheet summarising the methods used in this project (in German).

media_type: XLSX

en:
This file contains the anonymous answers to the survey for the case study in the protective forest, Val Mesolcina, GR, Switzerland within the BAFU Project "Wenn Risiken kumulieren - Analyse und Umgang mit unerwarteten Ereignissen und kombinierten Risiken".
The survey consists of two parts, based on different concepts: "top-down" and "bottom-up". Answers for both concepts are available in two different worksheets within the Excel file.

format: XLS

en: Factsheet summarising the key results of the study (in French).

en: Case study website

media_type: HTML

en: Page of the case study on the project website. It includes figures fo all questions of the survey and additional synthesis graphs.

format: HTML

en: Factsheet summarising the key results of the study (in Italian).

en:
This dataset contains the results of a case study analysing the potential impacts of a compound meteorological extreme event on the protective forest in the Val Mesolcina. These impacts were assessed in an experts survey. 29 Experts from practice, administration and science estimated the probabilities for a loss of the protective function due to a drought-related compound extreme event based on different hazard scenarios. The experts not only assessed these probabilities but also provided estimates about the reliability of the scenarios, other socio-economic consequences and options for adaptation.
This dataset contains the following information:
- Table with all (anonymised) answers from the survey
- Factsheets summarising the results and methods in German, French and Italian
- A detailed description of the study site and survey instructions
- Link to the project website wit illustrations for each individual question of the survey

bark-beetles

display_name: bark-beetles

compound-events

display_name: compound-events

drought

display_name: drought

extreme-events

display_name: extreme-events

forest-fire

display_name: forest-fire

protection-forest

display_name: protection-forest

protective-effect

display_name: protective-effect

en: Experts survey protective forest and combined extremes in Val Mesolcina


envidat-supports-open-science

maintainer: Ionut Iosifescu Enescu

title_for_slug: envidat-supports-open-science

en: juypter-notebooks open-science research-data-management wsl envidat

en: Article as PDF

en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.

License: This article is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

envidat

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat Supports Open Science


sachplankarte-wanderroutennetz

geography

en: Geography

territory

en: Territory and environment

title_for_slug: sachplankarte-wanderroutennetz

fr: infrastructure-routiere sentier-de-randonnee planification-de-lespace-physique trafic tourisme temps-libre

de: verkehrsinfrastruktur wanderweg raumplanung verkehr fremdenverkehr freizeit

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Le jeu de données comprend les informations représentées dans la partie cartographique du plan sectoriel du réseau des itinéraires de randonnée pédestre du 22 août 2012, mis à jour le 06 février 2019. Ce dernier peut être téléchargé dans sa version complète et bilingue au format PDF. La mise à jour de la carte du plan sectoriel fait l’objet d’un arrêté de la Direction des travaux publics et des transports et les adaptations du plan sectoriel proprement dit d’un arrêté du Conseil-exécutif. Le plan sectoriel du réseau des itinéraires de randonnée pédestre du 22 août 2012 remplace le Plan directeur cantonal du réseau des itinéraires de randonnée pédestre du 1er janvier 2002 (Code: WANDERNK) ainsi que le fichier Réseau des itinéraires de randonnée pédestre (Code: WANDERN) du 18 mars 2010 et toutes les informations qui en découlent.

de: Der Datensatz umfasst die im Kartenteil des Sachplans Wanderroutennetz vom 22.08.2012 (Nachführung: 06.02.2019) dargestellten Informationen. Der vollständige Sachplan Wanderroutennetz mit Textteil in deutscher und französischer Sprache kann als PDF heruntergeladen werden. Die Nachführung der Sachplankarte erfolgt aufgrund eines Beschlusses der Bau- und Verkehrdirektion. Die Anpassungen des Sachplans erfolgt aufgrund eines Beschlusses des Regierungsrates. Der Datensatz Sachplankarte Wanderroutennetz vom 22.08.2012 löst den Datensatz Kantonaler Richtplan des Wanderroutennetzes vom 01.01.2002 (Code: WANDERNK) und den Datensatz Wanderroutennetz (Code: WANDERN) vom 18.03.2010 mit allen in Beziehung stehenden Geoinformationen ab.

fr: Plan sectoriel - itinéraires de randonnée pédestre

de: Sachplankarte Wanderroutennetz


maintainer: Matthias Haeni

en: par precipitation relative-humidity meteo long-term swiss-forest-lab meteorology climate-change temperature wind-speed

en: Forest station data (CIB)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Data plot of the field station (CIF)

en: Data plot of the forest station (CIB)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Site photo of the forest station (CIB)

media_type: image/jpeg

en: Site photo of the forest station from below (viewing upwards the slope).

mimetype: image/jpeg

en: Site photo of the field station (CIF)

en: Site photo of the field station from the side.

en: Site aerial photo (Chironico)

en: Site aerial photo from both Chironico stations. Source: Google. 2016. Site aerial photo from both Chironico stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Chironico in Switzerland where one station is located within a natural coniferous forest stand (CIB) with Norway spruce (_Picea abies_; 160-180 yrs) and European silver fir (_Abies alba_; 140-160 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CIF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Chironico is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

education

fr: Education, science

de: Bildung, Wissenschaft

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

en: Chironico, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 2000 onwards


automatic-classification-of-avalanches

maintainer: Alec van Herwijnen

title_for_slug: automatic-classification-of-avalanches

en: localization seismic avalanche machine-learning monitoring

media_type: application/x-tar

en:
This tar file contains classification results for two seismic geophone arrays deployed above Davos, Switzerland. The of the first array located at the Dischma Valley was used to automatically identify all seismic events produced by avalanches, whereas the classification perfomed at the second array located at the Wannengrat field site was used to identify airplanes and earthquakes.
Furthermore, this tar file also contains the median back-azimuth of all classified events at the Dischma field site.

mimetype: application/x-tar

en: This dataset contains the classification and localization results obtained during the automatic classification of avalanches during the winter season 2017.

avalanche

display_name: avalanche

localization

display_name: localization

machine-learning

display_name: machine-learning

monitoring

display_name: monitoring

seismic

display_name: seismic

education

en: Education and science

en: EnviDat: the Environmental Data Portal

en: Automatic Classification of Avalanches


maintainer: Robert Pazúr

en: habitat agriculture vegetation-indices phenology machine-learning grassland cropland switzerland remote-sensing sentinel-2

en: Cropland and grassland map of Switzerland  (v.1.0)

media_type: TIFF

en: !!! Please check out the newer version in this repository !!! (1) cropland; (2) grassland; other LC classes are masked out from the map

format: TIFF

en: GEE (Google Earth Engine) script (JavaScript) to derived the output map  (v1.0)

media_type: JS

en: !!! Please check out the newer version in the repository !!! The code used in Google Earth Engine to derive the cropland, grassland and shrubland map of Switzerland

en: Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.6  (v1.0)

en:
!!! Please check out the newer version in the repository !!!
Mask of unsealed surfaces of Switzerland based on 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.6

en: (current version) Cropland, grassland, and shrubland map of Switzerland (v.1.5)

media_type: geotiff

format: GeoTIFF

en: Cropland, grassland, and shrubland map of Switzerland (v1.0)

en: !!! Please check out the newer version in this repository !!! (1) cropland; (2) grassland; (3) shrubland; other LC classes are masked out from the map

en: GEE (Google Earth Engine) script (JavaScript) to derived the output map  (v1.5)

en: The code used in Google Earth Engine to derive the cropland, grassland and shrubland map of Switzerland. Compare to the previous version the newer version includes the shadow masking procedure which might be important in the mountainous areas.

en: (current version) Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.6 (v1.5)

en: Assuming that sealed surfaces have little or no phenological response we calculated a mask of unsealed surfaces based on the 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.6.

en: Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.7 (v1.0)

en: !!! Please check out the newer version in this repository !!! Assuming that sealed surfaces have little or no phenological response we calculated a mask of unsealed surfaces based on the 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.7.

en: (current version) Cropland and grassland map of Switzerland (v.1.5)

en: (current version) Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.7 (v1.5)

en: We developed a map of cropland and grassland allocation for Switzerland based on several indices dominantly derived from Sentinel-2 satellite imagery captured over multiple growing seasons. The classification model was trained based on parcel-based data derived from landholder reporting. The mapping was conducted on Google Earth Engine platform using random forest classifier. Areas of high vegetation, shrubland, sealed surface and non-vegetated areas were masked out from the country-wide map. The resulting map has high accuracy in lowlands as well as mountainous areas.

agriculture

display_name: agriculture

cropland

display_name: cropland

grassland

display_name: grassland

habitat

display_name: habitat

phenology

display_name: phenology

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

vegetation-indices

display_name: vegetation-indices

en: Cropland and grassland map of Switzerland based on Sentinel-2 data


maintainer: Athanasios Nenes

en: ccn sigma-w cloud-droplets cloud-modeling weissfluhjoch supersaturation dmt-ccn-chamber hygroscopicity raclets

en: Hygroscopicity parameter Weissfluhjoch

en:
The aerosol hygroscopicity parameter is derived combining the CCN and SMPS size distribution data collected between February 24 and March 8 2019 at Weissfluhjoch. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The instrument supersaturation (SS%)
* The calculated hygroscopicity parameter (kappa)
* The calculated critical dry diameter of the particles (Dcr) in nm.

Missing values are indicated by "-999".

en: Predicted cloud droplet number concentrations Weissfluhjoch

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Weissfluhjoch station between February 24 and March 8 2019. For this, a hygroscopicity parameter of 0.25 is assumed, according to the CCN-derived values. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

en: CCN data Weissfluhjoch

en:
In-situ CCN measurements were conducted between February 24 and March 8 2019 at Weissfluhjoch. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* Filtered CCN number concentrations (in cmˉ³) measured at 6 discrete supersaturations (SS) ranging from 0.09% to 0.74%. The name of each CCN column is indicative of the SS developed within the instrument.
* Instrument characteristics such as sample temperature (in °C) and pressure (in mbar)
* A code that refers to the reason of filtering.

Missing or filtered CCN values are indicated by "-999", while a declaration of each "Error_code" can be found in the following list:

_Error_code_:

0000: Measurements without error

1000: Period of transient operation after a supersaturation change

2000: Sharp change (decrease) in the room temperature housing the instrument, which induces a reset in column temperature

3000: Irregular values in the room temperature housing the instrument

9999: Missing data

en:
Cloud Condensation Nuclei (CCN) data: A Droplet Measurement Technologies (DMT) single-column continuous-flow streamwise thermal gradient chamber (CFSTGC; Roberts and Nenes, 2005) was deployed at the measurement site Weissfluhjoch (2700 m a.s.l., LON: 9.806475, LAT: 46.832964) to record the in-situ CCN number concentrations between February 24 and March 8 2019 for different supersaturations (SS). To account for the difference between the ambient (~735 mbar) and the calibration pressure (~800 mbar), the SS reported by the instrument is adjusted by a factor of 0.92. The CFSTGC was cycled between 6 discrete SS values ranging from 0.09% to 0.74%, producing a full CCN spectrum every hour. The raw CCN measurements are filtered to discount periods of transient operation and whenever the room temperature housing the instrument changed sufficiently to induce a reset in column temperature. Additional information can be found in Section 2.1.2 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

Hygroscopicity data: The CCN number concentration measurements were directly related to the size distribution and total aerosol concentration data measured by the Scanning Mobility Particle Size Spectrometer (SMPS) instrument at the same station (https://www.envidat.ch/dataset/aerosol-data-weissfluhjoch) to infer the particles hygroscopicity parameter (kappa). For each SMPS scan, the particles critical dry diameter (Dcr) is estimated by integrating backward the SMPS size distribution, until the aerosol number matches the CCN concentration observed for the same time period as the SMPS scan. Assuming the particle chemical composition is internally mixed, the kappa is determined from Dcr and SS, applying Köhler theory. Additional information can be found in Section 2.2 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

Predicted cloud droplet numbers: Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from the SMPS instrument deployed at Weissfluhjoch. The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at Davos Wolfgang and are extracted for the altitude of interest, being 1100 m above ground level for Weissfluhjoch. Additional information can be found in Section 2.3 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

ccn

display_name: ccn

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

dmt-ccn-chamber

display_name: dmt-ccn-chamber

hygroscopicity

display_name: hygroscopicity

raclets

display_name: raclets

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

weissfluhjoch

display_name: weissfluhjoch

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: CCN, hygroscopicity, predicted cloud droplet numbers Weissfluhjoch


sensitivity-of-modeled-snow-instability

maintainer: Bettina Richter

title_for_slug: sensitivity-of-modeled-snow-instability

en: numerical-avalanche-forecasting snow-cover-modeling snow-instability global-sensitivity-analysis snowpack

en: Case WL

en: Extracted output data for case ALL. Here biases were introduced to meteorological input data during the period of weak layer formation. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

en: Case ALL

en: Extracted output data for case ALL. Here biases were introduced to meteorological input data during the whole simulation period. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

en: Reference run

en: Reference run for the sensitivity analysis at Weissfluhjoch field site for winter season 2016-2017. Meteorological data from the automatic weather stations are used. No biases were introduced to the input data.

en: Manually observed snow profiles

en: Manually observed snow profiles at Weissfluhjoch field site for winter season 2016-2017, including layer depth, hand hardness, grain size and grain shape for each layer.

en: Case SL

en: Extracted output data for case SL. Here biases were introduced to meteorological input data during the period of slab formation. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

en: We investigated the sensitivity of modeled snow instability to meteorological input data using SNOWPACK. We therefore used input data from the automatic weather station at the Weissfluhjoch field site for the year 2016-2017. We investigated three scenarios and performed 14'000 simulations for each scenario. The dataset contains extracted output data from modeled SNOWPACK simulations, including setup files to reproduce the simulations. For further information read the README file.

global-sensitivity-analysis

display_name: global-sensitivity-analysis

numerical-avalanche-forecasting

display_name: numerical-avalanche-forecasting

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability

snowpack

display_name: snowpack

en: Sensitivity of modeled snow instability


maintainer: EnviDat Support

en: longwave-radiation fractional-snow forest shortwave-radiation shading

en: Sky-view fraction along the cablecar transect

en: Data is used and described in the following paper: Malle et al. (2019). Shading by Trees and Fractional Snow Cover control the Subcanopy Radiation Budget. Journal of Geophysical Research. DOI:10.1029/2018JD029908.

en: Radiation Data 25.4.2018

en:
Spatiotemporal incoming/outgoing shortwave and longwave radiation as well as sunlit and shaded-snow view fractions below an evergreen forest stand in the Swiss alps. Data was collected on 25th of April 2018 along a 48m long, heterogeneous forest stand under partial snow cover conditions.

The presented data is used and further described in the following paper: Malle et al. (2019). Shading by Trees and Fractional Snow Cover control the Subcanopy Radiation Budget. Journal of Geophysical Research Atmospheres. DOI:10.1029/2018JD029908.

en: Seasonal sub-canopy radiation data

en:
Seasonal, spatially aggregated incoming and outgoing shortwave radiation below an evergreen forest stand collected with a cable car system.

The presented data is used and further described in the following paper: Malle et al. (2019). Shading by Trees and Fractional Snow Cover Control the Subcanopy Radiation Budget. Journal of Geophysical Research Atmospheres. DOI:10.1029/2018JD029908.

en: Radiation Data 18.04.2019

en:
Spatiotemporal incoming/outgoing shortwave and longwave radiation as well as sunlit and shaded-snow view fractions below an evergreen forest stand in the Swiss alps. Data was collected on 18th of April 2018 along a 48m long, heterogeneous forest stand under full snow cover conditions.

The presented data is used and further described in the following paper: Malle et al. (2019). Shading by Trees and Fractional Snow Cover control the Subcanopy Radiation Budget. Journal of Geophysical Research Atmospheres. DOI:10.1029/2018JD029908.

en: This data set consists of incoming and outgoing short- and longwave radiation as well as sunlit-snow-view-fraction as described in the JGR-Atmospheres paper "Shading by trees and fractional snow cover control the sub-canopy radiation budget", by Malle et al. (2019). Data was collected along a 48m long, heterogeneous forest transect between January and June 2018 close to Davos, Switzerland.

forest

display_name: forest

fractional-snow

display_name: fractional-snow

longwave-radiation

display_name: longwave-radiation

shading

display_name: shading

shortwave-radiation

display_name: shortwave-radiation

education

en: Education and science


en: stillberg snow-depth shortwave-radiation soil-temperature treeline dew-point-temperature precipitation-sum relative-humidity air-pressure wind-direction air-temperature wind-speed

en: The Davos Stillberg meteorological data (Stillberg_meteo_v1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

en: The Davos Stillberg meteorological data (Stillberg_meteo_v1.1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

en:
 Background information
The Stillberg ecological treeline research site is located in the transition zone between the relatively humid climate of the Northern Alps and the continental climate of the Central Alps. In 1975, 92,000 seedlings of the high-elevation conifer species *Larix decidua* Mill. (European larch), *Pinus cembra* L. (Cembran pine), and *Pinus mugo* ssp. *uncinata* (DC.) Domin (mountain pine) were systematically planted across an area of 5 hectares along an elevation gradient of about 150 metres, with the aim to develop ecologically, technically, and economically sustainable afforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Alongside the ecological long-term monitoring of the afforestation, several meteorological stations have recorded local meteorological conditions at the Stillberg research site. Here, we provide the Davos Stillberg meteorological timeseries of five stations from 1975 (01-01-1975), the year of the afforestation establishment, until the end of the year 2022 (31-12-2022).

 Station description
The five meteorological stations were all installed at the same location (46°46′25.015″N 9°52′01.792″E) at 2090 m a.s.l., in the lower part of the afforestation area. In general, the five stations were operated sequentially (Stillberg_meteo_metadata_stations_v1.csv). However, there are some overlapping time periods when more than one station was operated in parallel. The stations have recorded environmental parameters, such as air and soil temperature, dew point temperature, air pressure, relative humidity, wind direction and velocity, radiation, precipitation, and snow depth (Stillberg_meteo_metadata_parameters_v1.csv). The meteorological measurements were recorded hourly from 1975 until 1996 and have been recorded in 10-minute intervals since 1997.

 Data description
We processed the Davos Stillberg meteorological timeseries with the MeteoIO meteorological data pre-processing library (Bavay & Egger, 2014). Data files are provided for each station and quality level separately and named according to the station (see ‘Stillberg_meteo_metadata_stations_v1.csv’). From the raw data in their original formats, we generated three data quality levels: raw standardized (folder ‘raw_standardized’), edited (folder ‘raw_edited’) and filtered (folder ‘filtered’). The processing level is indicated in the headers of the data files. The whole processing protocol is described in a set of human-readable configuration files that are used by MeteoIO to generate the required data quality levels. This improves long-term reproducibility (Bavay et al., 2022), as the data could be regenerated in the future, even using a completely different software, to account for additional data points or to introduce new data corrections. The first quality level (raw standardized) is generated by parsing the original data files and interpreting them in order to convert all data points to a common format and meteorological parameter naming scheme, while excluding unreadable or duplicated data lines. The generated data files are derivatives of CSV files, with a standardised header that contains the metadata that are necessary to interpret and use the data (use metadata) and to populate a data index (search metadata). The latter is a textual implementation of the Attribute Convention for Data Discovery (ACDD) metadata standard (Attribute Convention for Data Discovery 1-3, 2022). The second quality level (edited) builds on the raw data by performing low-level data editing, such as removing some data periods that are known to be unusable (often based on maintenance records or anecdotal evidence) or applying undocumented calibration factors (for example, when there seems to be an obvious offset on a measured parameter for a period between two documented maintenance operations). The third quality level is generated by applying statistical filters on the data (per station and per meteorological parameter) to exclude presumably wrong values. We did not perform gap filling, as no single strategy could be relied upon that would work best for all possible data usage scenarios.

air-pressure

display_name: air-pressure

air-temperature

display_name: air-temperature

dew-point-temperature

display_name: dew-point-temperature

precipitation-sum

display_name: precipitation-sum

relative-humidity

display_name: relative-humidity

snow-depth

display_name: snow-depth

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

treeline

display_name: treeline

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Long-term meteorological station Stillberg, Davos, Switzerland at 2090 m a.s.l.


maintainer: Jürg Schweizer

en: danger-level snow-avalanche avalanche-activity avalanche-forcasting avalanche-size

en: Avalanche activity data

en: This data file includes data on the avalanche activity per day aggregated from the avalanche data.

en: Readme

en: The Readme file contains the description of the two data files.

en: Snow avalanche data

en: This data file includes data on the avalanches mapped in the region of Davos.

en:
These data include all avalanches that were mapped in the region of Davos, Switzerland during the winters 1998-1999 to 2018-2019 (21 years), in total 13,918 avalanches, and the corresponding forecast danger level valid on the day of avalanche occurrence, 3533 days and danger ratings in total.

This avalanche activity data set was analysed and results published by Schweizer et al. (2020). They found that the
number of avalanches per day strongly increased with increasing danger level, but avalanche size was poorly related to avalanche danger level.

The data are provided in two files: the first includes the avalanche data (13,918 records); the second includes the avalanche activity per day (3533 records).
Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Schweizer, J., Mitterer, C., Techel, F., Stoffel, A. and Reuter, B., 2020. On the relation between avalanche occurrence and avalanche danger level. The Cryosphere, 14, 737-750, https://doi.org/10.5194/tc-14-737-2020.

avalanche-activity

display_name: avalanche-activity

avalanche-forcasting

display_name: avalanche-forcasting

avalanche-size

display_name: avalanche-size

danger-level

display_name: danger-level

snow-avalanche

display_name: snow-avalanche

en: Snow avalanche data Davos, Switzerland, 1999-2019


en: mixing-models tracers eemma emma stable-isotopes end-member-mixing-analysis

en: vignette data

en: A simple data set for the vignette script

en: eemma vignette script

media_type: application/octet-stream

en: An R script for the vignettes (simple data analysis demonstrations) shown in the user's guide

mimetype: application/octet-stream

media_type: r script (flat-ascii text)

en: An R script that performs ensemble end-member mixing analysis

en: eemma user's guide

en: A brief user's guide to EEMMA, with illustrations using a simple data set

en:
The R script eemma.R, which implements Ensemble End-Member Mixing Analysis (EEMMA) to estimate source fractions in mixtures, exploiting information contained in time-series correlations among tracer time series.

A brief user's guide, a demonstration script, and a demonstration data set are also provided, to accompany Kirchner, J.W., Mixing models with multiple, overlapping, or incomplete end-members, quantified using time series of a single tracer, Geophysical Research Letters, 2023.

The user's guide is available for public use under Creative Commons CC-BY-SA. Public use of the scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

eemma

display_name: eemma

emma

display_name: emma

end-member-mixing-analysis

display_name: end-member-mixing-analysis

mixing-models

display_name: mixing-models

stable-isotopes

display_name: stable-isotopes

tracers

display_name: tracers

education

en: Education and science

en: eemma.R, an R script for Ensemble End-Member Mixing Analysis


weissfluhjoch-dataset-for-esm-snowmip

maintainer: Nander Wever

title_for_slug: weissfluhjoch-dataset-for-esm-snowmip

en: esm-snowmip snow-models snow-depth snow weissfluhjoch

media_type: application/zip

en: ini file

en: This ini file is required by data-converter from MeteoIO version 1887 (http://models.slf.ch/p/meteoio/)

en: Conversion script

media_type: text/x-sh

en:
Use this script to convert WFJ_optimaldataset_v6.smet to wfj.smet, the file that is used for the ESM-SnowMIP project. It also requires the file: WFJ_AirPressure_Data.zip

Use: bash create_wfj_dataset.sh > input/wfj.smet

mimetype: text/x-sh

en: Dataset Weissfluhjoch for ESM-SnowMIP

en: This Weissfluhjoch dataset is a processed version of the Weissfluhjoch dataset version 6 from https://doi.org/10.16904/6. This dataset was specially created for the ESM-SnowMIP project. Here it is documented how this dataset has been created.

esm-snowmip

display_name: esm-snowmip

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-models

display_name: snow-models

weissfluhjoch

display_name: weissfluhjoch

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Weissfluhjoch dataset for ESM-SnowMIP


maintainer: James W. Kirchner

en: sap-flow snowmelt diel-cycle streamflow groundwater ecohydrology evapotranspiration diurnal-cycle

en: Daily time series

en: Daily hydrometeorological and ecohydrological time series

en: Subcatchment polygons

en: Subcatchment polygons for use in the Google Earth Engine scripts.

en: 30-minute time series

en: 30-minute hydrometeorological and ecohydrological time series.

en: MODIS EVI2 script

en: Google Earth Engine script for computing MODIS two-band enhanced vegetation index (EVI2) values and averaging them over subcatchments.

en: MODIS NDSI script

en: Google Earth Engine script for computing MODIS normalized difference snow index (NDSI) values and averaging them over subcatchment areas.

en: Metadata

en: Column descriptions for both data files, and map coordinates for all measurement locations.

en:
Hydrometerological and ecohydrological time series from Sagehen Creek and Independence Creek, Sierra Nevada, USA, illustrating hydrological responses to daily cycles in snowmelt and evapotranspiration forcing.

Data include 30-minute time series of

- weather variables,

- sap flow fluxes,

- groundwater levels (in two riparian transects of shallow groundwater wells),

- and stream stages (at 12 sites spanning a 500-meter elevation gradient),

and daily time series of

- temperature, precipitation, and snow water equivalent at three nearby snow telemetry stations

- diel cycle index values for groundwater levels and stream stages,

- and MODIS normalized difference snow index (NDSI) and enhanced vegetation index (EVI2) values averaged over selected subcatchments.

Google Earth Engine scripts for extracting the MODIS data are also provided.

diel-cycle

display_name: diel-cycle

diurnal-cycle

display_name: diurnal-cycle

ecohydrology

display_name: ecohydrology

evapotranspiration

display_name: evapotranspiration

groundwater

display_name: groundwater

sap-flow

display_name: sap-flow

snowmelt

display_name: snowmelt

streamflow

display_name: streamflow

en: Daily cycles in solar flux, snowmelt, transpiration, groundwater, and streamflow at Sagehen and Independence Creeks, Sierra Nevada, USA


en: buffer jupyter density gis roads geospatial

en: Plots

en: Random plot locations

en: Road data from OSM for the surroundings of Menzberg, Switzerland

media_type: ipynb

en: Road Density Calculation (Python Notebook) online

media_type: url

en:
This dataset contains the road and plot data used for the geospatial analysis example showcased in "Fostering Open Science at WSL with the EnviDat Environmental Data Portal", a contribution to the 5th Open Source Geospatial Research and Education Symposium (OGRS), 2018.
The example uses Jupyter Notebook to calculate road densities in the neighbourhood of sample plot locations with Python. Road data were extracted from OpenStreetMap, while the point data (sample plots) were generated manually.

buffer

display_name: buffer

density

display_name: density

geospatial

display_name: geospatial

gis

display_name: gis

jupyter

display_name: jupyter

roads

display_name: roads

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Dataset for OGRS 2018 publication


maintainer: Marco Moretti

en: beekeeping urban-ecosystems urban-biodiversity pollinator-experiment resource-availability wild-bees zurich urbanization gardens bettergardens city4bees honeybees

media_type: .csv

en: Metadata for the predictor and response dataset

media_type: CSV

en:
Mean, standard deviation , minimum and maximum values of six functional traits. The data has the following structure:
- Bee_species: bee scientific name
- mean_trait: mean value
- sd_trait: standard deviation
_min_trait: minimum value
- max_trait: maximum value
- trait: the six traits used. ITD = Intertegular distance (mm); Pheno.duration = duration of the phenology; Pheno.start = start of the phenology; Pheno.end = end of the phenology; Rel.tongue.length= relative tongue length (mm); Daytime.activity = daily activity (h)
DistNichePart: functional dissimilarity in a multidimentional trait space defined by five traits between wild bee individuals of a wild bee species and the honeybee individuals. Values are at the species level.

en:
The data contains the following columns:

  SiteID: numeric, the identity of the garden where the bee was sampled.
  Taxonname: character, species name
  Lecty: numeric discreet, a mesure of specialisation degree. Levels: 1 = monolectic; 2=oliolectic; 3=polilectic
  Pheno.start= numeric discreet, the starting week of the flying activity.
  Pheno.end= numeric discreet, the ending week of the flying activity.
  Pheno.duration=numeric discreet, Pheno.end - Pheno.start
  Daytime.activity = numeric continuous, individual-level measure of the day hour when the bee was sampled
  ITD = numeric continuous, individual-level measure of the InterTegular Distance, a metric of mobility in mm.
  Rel.tongue.length =numeric continuous, individual-level measure of the relative tongue length (Tongue length / ITD), a metric of specilaisation degree, in mm.

en: Response and predictors used for the SEMs

en: Metadata for the predictors and response dataset

en:
Cities are socio-ecological systems that filter and select species, thus establishing unique species assemblages and biotic interactions. Urban ecosystems can host richer wild bee communities than highly intensified agricultural areas, specifically in resource-rich urban green spaces such as allotment and family gardens. At the same time, urban beekeeping has boomed in many European cities, raising concerns that the fast addition of a large number of managed bees could deplete the existing floral resources, triggering competition between wild bees and honeybees. The data has been used to investigated the interplay between resource availability and the number of honeybees at local and landscape scales and how this relationship influences wild bee diversity.

This dataset contains the raw and processed data supporting the findings from the paper: "Low resource availability drives feeding niche partitioning between wild bees and honeybees in a European city".

The data contains:
1. Bee trait measurements at the species and individual-level of five functional traits.
2. The values of the feeding niche partitioning (functional dissimilarity to honeybees)
3. The predictors of resource availability and beekeeping intensity at local and landscape scales used in the modelling of the paper for the 23 experimental sites.

beekeeping

display_name: beekeeping

bettergardens

display_name: bettergardens

gardens

display_name: gardens

honeybees

display_name: honeybees

pollinator-experiment

display_name: pollinator-experiment

resource-availability

display_name: resource-availability

urban-biodiversity

display_name: urban-biodiversity

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wild-bees

display_name: wild-bees

zurich

display_name: zurich

en: Niche partitioning between wild bees and honeybees


present-weather-sensor-klosters

maintainer: Maxime Hervo

title_for_slug: present-weather-sensor-klosters

en: raclets weather sensor visibility precipitation

en: Present Weather Sensor Klosters

media_type: mat

en: Present Weather sensor measuring visibility and weather type installed at Klosters.

en: A present weather sensor (Vaisala PWD22) was deployed in Klosters (LON: 9.880413, LAT: 46.869019) for weather observation, combining the functions of a forwardscatter visibility meter and a present weather sensor. Besides measuring ambient light, it detects the intensity as well as the amount of both liquid and solid precipitation. More information can be found in the [User's Manual](ftp://ftp.cmdl.noaa.gov/aerosol/doc/manuals/PWD22_Manual.pdf).

precipitation

display_name: precipitation

raclets

display_name: raclets

sensor

display_name: sensor

visibility

display_name: visibility

weather

display_name: weather


maintainer: Achille Capelli

en: liquid-water-content snow-water-equivalent swe snow lwc gnss gps

en: Profile data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Webcam images

media_type: ZIP

en: Webcam images showing some typical differences in the snow conditions at the four sites (Küblis, Klosters, Laret and Weissfluhjoch) for two time periods (14-18.3.2019 and 27.1-11.2.2020). Both time periods included a precipitation event with partial rain-on–snow occurring at the lower locations.

en: Daily data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Manual profiles

media_type: .zip

en: Data of the traditional manual profiles for the locations Weissfluhjoch, Klosters and Küblis. For the location of Küblis there are no traditional manual profile data. We provided the data as both PDF and .CAAML format (See https://niviz.org/ or http://caaml.org/Schemas/V5.0/Profiles/SnowProfileIACS/CAAMLv5_SnowProfileIACS.pdf). Moreover, we added LWC and density profiles when available (all locations).

en: Snow profiles data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: Snow and meteo data from automatic sensors for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Daily observer data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: GNSS derived data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Daily data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Snow and meteo data from automatic sensors for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Snow profiles data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Daily data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Snow and meteo data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Snow and meteo data from automatic sensors from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: Snow profiles data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Daily data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Daily observer data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: GNSS derived SWE, LWC and HS from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-20

en: GNSS derived SWE, LWC and HS from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-20

en: GNSS derived SWE, HS, and LWC for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Daily observer data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: This database contains GNSS derived snow water equivalent (SWE), liquid water content (LWC), and snow height (HS) and reference data collected during the two winter 2018-2020 at 4 sites Weissfluhjoch (2540 m asl, 46°49’47’’ N, 9°48’34’’E), Laret (1515 m asl, . 46°50’2’’N, 9°52’17’’E), Klosters (1200 m asl, 46°51’49’’N, 9°53’17’’E), and Küblis (815 m asl, 46°54’48’’N, 9°46’54’’E).

gnss

display_name: gnss

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

lwc

display_name: lwc

snow

display_name: snow

en: Snow water equivalent measurements with low-cost GNSS receivers along a steep elevation gradient in the East-ern Swiss Alps


en: frost-change-velocity aridity sdms ground-temperature precipitation soil

media_type: tif

en: Precipitation seasonality from CHELSA

en: Soil organic carbon content modified from SoilGrids

en: Mean diurnal range modified from CHELSA

en: Frost change frequency modified from CHELSA

en: Soil pH modified from SoilGrids

en: Soil clay content modified from SoilGrids

en: Precipitation of driest quarter modified from CHELSA

en: Mean annual temperature modified from CHELSA

en: The dataset contains seven environmental layers (average annual temperature, aridity [annual precipitation divided by annual potential evapotranspiration], frost change frequency, precipitation in the driest quarter, mean diurnal temperature range, and precipitation seasonality) modified from CHELSA (https://chelsa-climate.org/) and three soil layers (soil organic matter content, pH water, and clay content) modified from SoilGrids (https://soilgrids.org/).

aridity

display_name: aridity

frost-change-velocity

display_name: frost-change-velocity

ground-temperature

display_name: ground-temperature

sdms

display_name: sdms

soil

display_name: soil

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Environmental layers for SDM simulations (GDPlants)


maintainer: Avalanche Warning Service SLF

en: Avalanche fatalities per year in Switzerland since 1936/1937

en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per hydrological year in Switzerland. The data set commences with the beginning of the hydrological year 1936/37 on 01/10/1936. After the completion of a hydrological year, the new data is appended to the existing dataset.
The following information is contained (by column and column title):
 - hydrological year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)
The definition for these four categories as described in the guidelines to the avalanche accident database:
**tour**:
activities include back-country ski, snowboard or snow-shoe touring
**offpiste**:
access from ski area, generally from the top of a skilift with short hiking distances
**transportation.corridors** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people travelling or recreating on open or temporarily closed
transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)
**buildings** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people inside or just outside buildings, and workers on high alpine building
sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

en: Number of avalanche fatalities per hydrological year in Switzerland since 1936-1937


en: par long-term meteo wind-speed precipitation relative-humidity climate-change swiss-forest-lab temperature meteorology

en: Data plot of the forest station (NOB)

media_type: application/pdf

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Site photo of the field station (NOF)

media_type: image/jpeg

en: Site photo of the field station from the side.

en: Forest station data (NOB)

media_type: text/csv

en: Data file.

en: Site photo of the forest station (NOB)

en: Site photo of the forest station from the side.

en: Data plot of the field station (NOF)

en: Field station data (NOF)

en: Site aerial photo (Novaggio)

en: Site aerial photo from both Novaggio stations. Source: Google. 2016. Site aerial photo from both Novaggio stations. Retrieved November 15, 2016, from https://www.google.ch/maps

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Novaggio in Switzerland where one station is located within a natural deciduous forest stand (NOB) with Turkey oak (_Quercus cerris_; 70 yrs), sweet chestnut (_Castanea sativa_; 90 yrs) and silver birch (_Betula pendula_; 70 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NOF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Novaggio is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

en: Novaggio, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards


maintainer: Christoph Marty

en: snowfall hydrology snow climate-change-impacts water-cycle

en: Synthesis report chapter

en: DORA Persistent URL

en:
This report was prepared as one of the synthesis report chapters of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN). An important feature of snow cover is the fact that its volume and duration is subject to large year-to-year fluctuations. As frozen precipitation, snow cover is nothing other than a natural water reservoir that delays precipitation to runoff and is thus of outstanding importance for the seasonal water balance in Switzerland. Over a whole year, approximately 40% (22 km3) of the annual runoff currently comes from snow melting and only 1% from glacier melting. Typically, the snow cover in the Alpine region builds up over the autumn and winter months, reaches its maximum between February and May, depending on the altitude, and dominates the runoff processes during melting in the following spring and summer months.
Due to the great dependence on minus temperatures and precipitation, the snow cover reacts sensitively to temperatures above 0° Celsius and more or less precipitation. Due to climate change and the associated warming, the proportion of precipitation that falls as snow decreases measurably. In addition to this reduction in snowfall, the warmer temperatures also cause the snow cover to melt more quickly. The decline in snowfall has so far mainly affected lower altitudes, where winter temperatures often reach positive levels.
As climate change progresses, this trend is likely to continue and above all affect higher zones. Even at higher altitudes, the snow cover will then start later, melt away earlier and is increasingly no longer permanently present. This development will also have an effect on the water bodies. Today nival regimes, i.e. regimes shaped by snow, are shifting towards pluvial regimes, i.e. regimes dominated by rain. Overall, winter runoff increases, summer runoff decreases. By the end of the century, the proportion of runoff from snowmelt will decrease throughout Switzerland, albeit to a lesser extent than the proportion from glacier melt.

climate-change-impacts

display_name: climate-change-impacts

hydrology

display_name: hydrology

snow

display_name: snow

snowfall

display_name: snowfall

water-cycle

display_name: water-cycle

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Snow and the water cycle in a changing climate