mobility

de: Mobilität und Verkehr

de: luftfahrt luftraum luftfahrzeug bgdi-bundesgeodaten-infrastruktur

label: Link zu Detailbeschreibung (skyguide)

label: Link zum Fachportal

de: Map (Preview) Vorschau map.geo.admin.ch

de: Vorschau map.geo.admin.ch

fr: Lien vers la distribution des données

de: Link für Datenbezug

en: Link for data download

it: Link per le fonti dei dati

fr: Lien vers le WMS

de: Link zum WMS

en: Link to WMS

it: Link verso WMS

de: RESTful API von geo.admin.ch

fr: Une zone géographique UAS est une partie de l’espace aérien établie par l’autorité compétente qui facilite, restreint ou exclut les exploitations de systèmes d’aéronefs sans occupants (angl. UAS) afin de traiter les risques relatifs à la sécurité, à la sphère privée, à la protection des données à caractère personnel, à la sûreté ou à l’environnement, découlant des exploitations de systèmes d’aéronefs sans occupants. Conformément aux art. 27 et 28 de l'ordonnance du DETEC sur les aéronefs de catégories spéciales (OACS), il est interdit de faire voler des aéronefs sans occupants dans les zones géographiques UAS définies, sauf exception autorisée par les services compétents (art. 29 OACS). De même, l'art. 34 OACS confère aux cantons le pouvoir d'édicter des prescriptions applicables aux aéronefs sans occupants d’un poids allant jusqu’à 25 kg dans le but de réduire les atteintes à l'environnement et le danger auquel les personnes et les biens sont exposés au sol.

de: Ein geografisches UAS-Gebiet ist ein von der zuständigen Behörde festgelegter Teil des Luftraums, der den Betrieb unbemannter Luftfahrzeuge bzw. -systeme (engl. UAS für Unmanned Aircraft System) ermöglicht, einschränkt oder ausschließt, um den mit dem UAS-Betrieb verbundenen Risiken für die Sicherheit, den Schutz der Privatsphäre und personenbezogener Daten, die Sicherheitslage oder die Umwelt Rechnung zu tragen. Gemäss den Art. 27 und 28 der Verordnung des UVEK über Luftfahrzeuge besonderer Kategorien (VLK) ist der Betrieb von unbemannten Luftfahrzeugen in den festgelegten UAS-Gebieten untersagt. Ausnahmen können von den zuständigen Stellen bewilligt werden (Art. 29 VLK). Ebenfalls können die Kantone gestützt auf Art. 34 VLK für unbemannte Luftfahrzeuge mit einem Gewicht von weniger als 25 kg Vorschriften zur Verminderung der Umweltbelastung und der Gefährdung von Personen und Sachen auf der Erde erlassen.

en: A UAS geographical zone is a portion of airspace designated by the competent authority in which the operation of unmanned aircraft systems (UASs) is permitted, restricted or forbidden in order to take account of the risks to safety, privacy and personal data protection, security or the environment that are associated with UAS operations. According to Articles 27 and 28 of the DETEC Ordinance on Special Category Aircraft (OSCA), the operation of unmanned aerial vehicles in the defined UAS areas is prohibited. Exceptions may be granted by the competent authorities (Art. 29 OSCA). Likewise, the cantons may, on the basis of Article 34 OSCA, issue regulations for unmanned aerial vehicles with a weight of less than 25kg to reduce the impact on to the environment and the risk to persons and property on the ground.

it: Una zona geografica unica dell'UAS è una porzione di spazio aereo stabilita dall'autorità competente che agevola, limita o esclude le operazioni di aeromobili o di sistemi senza occupanti (in inglese Unmanned Aircraft System, UAS), al fine di far fronte ai rischi connessi alla sicurezza, alla riservatezza, alla protezione dei dati personali, alla sicurezza o all'ambiente derivanti dalle operazioni UAS. In virtù degli articoli 27 e 28 dell'ordinanza del DATEC sulle categorie speciali di aeromobili (OACS), è proibito l'esercizio di aeromobili senza occupanti nelle zone UAS stabilite. I servizi competenti possono autorizzare eccezioni (art. 29 OACS). Inoltre, in virtù dell'articolo 34 OACS, per gli aeromobili senza occupanti di peso inferiore a 25 kg i Cantoni possono emanare prescrizioni per ridurre l'impatto ambientale e i rischi per persone e cose a terra.

bundesamt-fur-zivilluftfahrt-bazl

fr: Office fédéral de l'aviation civile OFAC

de: Bundesamt für Zivilluftfahrt BAZL

en: Federal Office of Civil Aviation FOCA

it: Ufficio federale dell’aviazione civile UFAC

fr: L’Office fédéral de l’aviation civile (OFAC) est l’organe compétent en matière de politique aéronautique et de surveillance de l'aviation civile suisse. Placé sous l’autorité du Département fédéral de l’environnement, des transports, de l’énergie et de la communication (DETEC), l’OFAC veille à ce que l’aviation civile suisse bénéficie d’un niveau de sécurité élevé et suive un développement durable.

de: Das Bundesamt für Zivilluftfahrt (BAZL) ist für die Luftfahrtentwicklung und die Aufsicht über die zivile Luftfahrt in der Schweiz zuständig. Das BAZL gehört zum Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK) und ist dafür verantwortlich, dass die Zivilluftfahrt in der Schweiz ein hohes Sicherheitsniveau aufweist und eine nachhaltige Entwicklung verfolgt.

en: The Federal Office of Civil Aviation (FOCA) is responsible for aviation development and the supervision of civil aviation activities in Switzerland. The FOCA is part of the Federal Department of the Environment, Transport, Energy and Communications (DETEC) and is charged with ensuring that the high safety standards in civil aviation in Switzerland are maintained, and with pursuing a policy of sustainable development.

it: L’Ufficio federale dell’aviazione civile (UFAC), che fa parte del Dipartimento federale dell’ambiente, dei trasporti, dell’energia e delle comunicazioni (DATEC), è responsabile dell’evoluzione nel settore aeronautico e della sorveglianza sull’aviazione civile in Svizzera. Esso garantisce uno standard di sicurezza elevato e promuove il principio dello sviluppo sostenibile nell’aviazione civile elvetica.

value: BAZL - Geocat Harvester

fr: Zones géographiques UAS en Suisse

de: Geografische UAS-Gebiete der Schweiz

en: Geographical UAS zones of Switzerland

it: Zone geografiche UAS della Svizzera


quartieranalyse

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

title_for_slug: quartieranalyse

de: quartier quartieranalyse siedlungsentwicklung arbeitszone gewerbebauland

label: Geometadaten Kanton Zürich: GeoLion

label: geocat.ch permalink

state: active

spatial: Kanton Zürich

type: dataset

de: Download via GIS-Browser

de: Die Daten zeigen zentrale Merkmale zum Stand der Siedlungsentwicklung auf Quartierebene. Der inhaltliche Schwerpunkt liegt auf Einwohner- und Gebäudeinformationen für Wohn- und Mischzonen. Für Industrie- und Gewerbezonen zeigt die Quartieranalyse reduzierte Inhalte. Weitere Metadaten finden Sie in diesem PDF.

name:
Statistisches Amt  des Kantons Zürich
             -

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

fr:
Le département de géomatique est le centre de compétence du system d'information géographique du canton de Zurich.
Nous coordinons l'aquisition des géodonnées d'intérêt commun sur le territoire cantonal et les mettons à disposition des
secteurs public et privé et des particuliers.

en:
The department of geoinformation is the geospatial competency center of the Canton of Zurich.
We coordinate the acquisition of geodata within the cantonal territory and provide public, private, and government sectors with data of outstanding quality.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

it: La divisione della geoinformazione è il centro d'eccellenza del Cantone di Zurigo per dati georeferenziati. Mettiamo a disposizione dati geografici e informazioni di alta qualità per l'economia, la società e la pubblica amministrazione su tutto il cantone.

political_level: canton

kanton-zuerich

capacity: public

type: organization

approval_status: approved

value: ZH - Geocat Harvester

de: Quartieranalyse


maintainer: OGD-Koordinationsstelle Kanton Thurgau

de: json

media_type: application/json

de: Lotteriefonds Kanton Thurgau: Zugesprochene Beiträge (json)

format: JSON

mimetype: application/json

license: CC BY 4.0

de: csv

media_type: text/csv

de: Lotteriefonds Kanton Thurgau: Zugesprochene Beiträge (csv)

format: CSV

mimetype: text/csv

de: Der Datensatz enthält die zugesprochenen Projektbeiträge aus dem Lotteriefonds des Kantons Thurgau. Zuständig für die Bearbeitung der Gesuche an den Lotteriefonds ist das Kulturamt Kanton Thurgau. Unterstützt werden kulturelle, wissenschaftliche und gemeinnützige Projekte, die einen Bezug haben zum Kanton und von überregionaler Bedeutung sind.Die gesetzlichen Grundlagen und die formalen, inhaltlichen und kulturpolitischen Kriterien für die Beurteilung von Projekten sind online unter www.kulturamt.tg.ch einzusehen.

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

kanton-thurgau

fr: Canton de Thurgovie

de: Kanton Thurgau

en: Canton of Thurgau

it: Cantone di Turgovia

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

key: guid

key: uri

value: TG-Kt DCAT Harvester


maintainer: Sektion energieeffizienter Verkehr

title_for_slug: Kennzahlen alternativ angetriebene LNF

de: ogd93-bfe elektromobilitat leichte-nutzfahrzeuge alternative-antriebe lieferwagen elektrische-fahrzeuge hybridfahrzeuge co2

fr: Chiffres clés des véhicules utilitaires légers neufs à propulsion alternative (VUL)

de: Kennzahlen alternativ angetriebene LNF

en: Key figures for alternatively powered LCVs

it: Indicatori VCL a propulsione alternativa

label: Storymap

fr: Modèles de VUL entièrement électriques (modèles BEV) les plus prisés

de: Beliebteste vollelektrische LNF-Modelle (BEV)

en: Most popular all-electric LCV models (BEV)

it: VCL completamente elettrici più diffusi (modelli BEV)

fr:
L’Office fédéral de l’énergie évalue depuis 2020 les modèles de VUL entièrement électriques (modèles BEV) les plus prisés. Pour l’année 2020, des chiffres trimestriels sont disponibles; à partir de 2021, les valeurs sont disponibles à un rythme mensuel.

La numérotation des cantons est celle de l’OFS.

en:
The Swiss Federal Office of Energy has since 2020 ranked the most popular all-electric LCV models (BEV). Quarterly figures are provided for 2020; from 2021 on, the values are available on a monthly basis.

Numbering of cantons according to FSO

de:
Das Bundesamt für Energie wertet seit 2020 bei den LNF die beliebtesten, vollelektrischen Modellen (BEV) aus. Für das Jahr 2020 sind Quartalszahlen bereitgestellt, ab 2021 sind die Werte in monatlicher Auflösung verfügbar.

Nummerierung der Kantone gemäss BFS

it:
Dal 2020 l'Ufficio federale dell'energia analizza i modelli di VCL completamente elettrici più diffusi. Per il 2020 vengono forniti dati trimestrali, mentre dal 2021 in poi i valori sono disponibili con risoluzione mensile.

Numerazione dei Cantoni secondo UST.

fr: Chiffres clés des VUL à propulsion alternative

fr:
Sur la base des données anonymisées des nouvelles immatriculations publiées par l’OFROU, l’Office fédéral de l’énergie évalue depuis 2020 des chiffres clés importants concernant les voitures de livraison et tracteurs à sellette légers à propulsion alternative (véhicules utilitaires légers, VUL). Sont réputés véhicules à propulsion alternative les véhicules ne disposant pas exclusivement d’un moteur à combustion à essence ou à diesel. Ce jeu de données comprend, outre les statistiques annuelles agrégées, les chiffres trimestriels et mensuels des parts de marché ainsi que des indications sur les différents cantons.

Légende: t1 = émissions moyennes de CO2, t2 = part BEV, t3 = part PHEV essence, t4 = part PHEV diesel, t5 = part hybride essence, t6 = part hybride diesel, t7 = part gaz naturel, t8 = part nouvelles immatriculations, t10 = part hydrogène

La numérotation des cantons est celle de l’OFS.

en:
On the basis of the anonymised data for new registrations published by FEDRO, the Swiss Federal Office of Energy has evaluated since 2020 the key figures for alternatively powered vans and light articulated vehicles (collectively: light commercial vehicles, LCVs). Vehicles are considered to be alternatively powered if they do not have an exclusively petrol or diesel-driven internal combustion engine. In addition to aggregated annual key figures, this data set also contains quarterly and monthly market share figures as well as information regarding the individual cantons.

Key: t1 = CO2 average, t2 = Share of BEVs, t3 = Share of petrol PHEVs, t4 = Share of diesel PHEVs, t5 = Share of hybrid petrol, t6 = Share of hybrid diesel, t7 = Share of natural gas, t8 = Number of new registrations, t10 = Share of hydrogen

Numbering of cantons according to FSO

de:
Auf Basis der vom ASTRA publizierten, anonymisierten Neuzulassungsdaten wertet das Bundesamt für Energie ab 2020 wichtige Kennzahlen zu den alternativ angetriebenen Lieferwagen und leichten Sattelschlepper (Sammelbegriff: leichte Nutzfahrzeuge, LNF) aus. Als alternativ angetrieben gelten Fahrzeuge, bei denen nicht ausschliesslich ein Benzin- oder Diesel-Verbrennungsmotor eingebaut ist. Dieser Datensatz enthält neben aggregierten jährlichen Kennzahlen auch Quartals- und Monatszahlen der Marktanteile sowie Angaben zu den einzelnen Kantonen.

Legende: t1 = CO2 Durchschnitt, t2 = Anteil BEV, t3 = Anteil Benzin PHEV, t4 = Anteil Diesel PHEV, t5 = Anteil Hybrid Benzin, t6 = Anteil Hybrid Diesel, t7 = Anteil Erdgas, t8 = Anzahl Neuzulassungen, t10 = Anteil Wasserstoff

Nummerierung der Kantone gemäss BFS

it:
Sulla base dei dati anonimizzati sulle nuove immatricolazioni pubblicati dall'USTRA, dal 2020 l'Ufficio federale dell'energia analizza importanti indicatori relativi agli autofurgoni e ai trattori a sella leggeri (iperonimo: veicoli commerciali leggeri VCL) a propulsione alternativa. Per veicoli a propulsione alternativa si intendono veicoli sui quali non è installato esclusivamente un motore a combustione a benzina o diesel. Oltre a indicatori annuali aggregati, questo set di dati contiene anche dati trimestrali e mensili relativi alle quote di mercato e indicazioni sui singoli Cantoni.

Legenda: t1 = Emissioni medie di CO2, t2 = Percentuale BEV, t3 = Percentuale PHEV benzina, t4 = Percentuale PHEV diesel, t5 = Percentuale ibride benzina, t6 = Percentuale ibride diesel, t7 = Percentuale gas naturale, t8 = Numero nuove immatricolazioni, t10 = Percentuale idrogeno

Numerazione dei Cantoni secondo UST.

fr:
Sur la base des données anonymisées des nouvelles immatriculations publiées par l’OFROU, l’Office fédéral de l’énergie évalue depuis 2020 des chiffres clés importants portant sur les voitures de livraison et tracteurs à sellette légers à propulsion alternative (véhicules utilitaires légers, VUL). Sont réputés véhicules à propulsion alternative les véhicules dont la propulsion ne se fait pas exclusivement avec un moteur à combustion à essence ou à diesel. Ce jeu de données comprend, outre les statistiques annuelles agrégées, les chiffres trimestriels et mensuels des parts de marché ainsi que des indications sur les différents cantons. L’OFEN évalue en outre les modèles de VUL entièrement électriques les plus prisés.

Base légale: art. 11 de l’ordonnance sur les exigences relatives à l’efficacité énergétique (OEEE)

en:
On the basis of the anonymised data for new registrations published by FEDRO, the Swiss Federal Office of Energy has since 2020 evaluated key figures for alternatively powered vans and light articulated vehicles (collectively: light commercial vehicles, LCVs). Alternatively powered vehicles are vehicles that are not solely powered by a petrol or diesel internal combustion engine. In addition to aggregated annual key figures, this data set also contains quarterly and monthly market share figures as well as information regarding the individual cantons. Also, the Swiss Federal Office of Energy ranks the most popular all-electric LCV models.

Legal basis: Energy Efficiency Ordinance (EnEO), Art. 11

de:
Auf Basis der vom ASTRA publizierten, anonymisierten Neuzulassungsdaten wertet das Bundesamt für Energie seit 2020 die wichtigsten Kennzahlen zu den alternativ angetriebenen Lieferwagen und leichten Sattelschlepper (Sammelbegriff: leichte Nutzfahrzeuge, LNF) aus. Als alternativ angetrieben gelten Fahrzeuge, die nicht ausschliesslich über einen Benzin- oder Diesel-Verbrennungsmotor angetrieben werden. Dieser Datensatz enthält neben aggregierten jährlichen Kennzahlen auch Quartal- und Monatszahlen der Marktanteile sowie Angaben zu den einzelnen Kantonen. Zudem wertet das Bundesamt für Energie bei den LNF die beliebtesten, vollelektrischen Modellen aus.

Rechtsgrundlage: Energieeffizienzverordnung (EnEV) Art. 11

it:
Sulla base dei dati anonimizzati sulle nuove immatricolazioni pubblicati dall'USTRA, dal 2020 l'Ufficio federale dell'energia analizza importanti indicatori relativi agli autofurgoni e ai trattori a sella leggeri (iperonimo: veicoli commerciali leggeri VCL) a propulsione alternativa. Per veicoli a propulsione alternativa si intendono veicoli che non sono mossi esclusivamente da un motore a combustione a benzina o diesel. Oltre a indicatori annuali aggregati, questo set di dati contiene anche dati trimestrali e mensili relativi alle quote di mercato e indicazioni sui singoli Cantoni. Inoltre l'Ufficio federale dell'energia analizza i modelli di VCL completamente elettrici più diffusi.

Base legale: ordinanza sull’efficienza energetica (OEEne), nello specifico l'articolo 11

alternative-antriebe

display_name: alternative-antriebe

elektrische-fahrzeuge

display_name: elektrische-fahrzeuge

elektromobilitat

display_name: elektromobilitat

hybridfahrzeuge

display_name: hybridfahrzeuge

leichte-nutzfahrzeuge

display_name: leichte-nutzfahrzeuge

lieferwagen

display_name: lieferwagen

energy

fr: Energie

de: Energie

en: Energy

it: Energia

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).

political_level: confederation


title_for_slug: Kennzahlen alternativ angetriebene PW

de: alternative-antriebe elektromobilitat hybridfahrzeuge co2 ogd92-bfe personenwagen elektrische-fahrzeuge

fr: Chiffres clés des voitures de tourisme neuves à propulsion alternative

de: Kennzahlen alternativ angetriebene PW

en: Key figures for alternatively powered passenger cars

it: Indicatori relativi alle automobili a propulsione alternativa

fr: Modèles de voitures de tourisme hybrides rechargeables les plus prisés

de: Beliebteste Plug-In PW-Modelle (PHEV)

en: Most popular plug-in models (cars)

it: Automobili plug-in più diffuse (modelli PHEV)

fr: Depuis 2015, l’Office fédéral de l’énergie recense chaque trimestre les modèles de voitures de tourisme hybrides rechargeables (PHEV) les plus prisés; depuis 2021, les données sont disponibles à un rythme mensuel. Tous les modèles hybrides rechargeables disponibles en Suisse sont pris en compte.

en: Since 2015, the Swiss Federal Office of Energy has reported the most popular plug-in models (PHEVs) among passenger cars on a quarterly basis; since 2021, the data has been available on a monthly basis. All plug-in models from Switzerland are counted together.

de: Ab 2015 weist das Bundesamt für Energie quartalsweise die beliebtesten Plug-In Modelle (PHEV) bei den Personenwagen aus, ab 2021 sind die Daten in monatlicher Auflösung verfügbar. Dabei werden alle Plug-In Modelle aus der Schweiz zusammengezählt.

it: Dal 2015 l'Ufficio federale dell'energia indica su base trimestrale i modelli più diffusi di automobili plug-in (PHEV); dal 2021 i dati sono disponibili con risoluzione mensile. Vengono conteggiati tutti i modelli plug-in presenti in Svizzera.

fr: Statistiques des motorisations alternatives des voitures de tourisme

fr:
Sur la base des données anonymisées des nouvelles immatriculations publiées par l’OFROU, l’Office fédéral de l’énergie évalue depuis 2015 les statistiques des motorisations alternatives des voitures de tourisme. Sont réputés véhicules à propulsion alternative les véhicules dont la propulsion ne se fait pas exclusivement avec un moteur à combustion à essence ou à diesel. Ce jeu de données comprend, outre les statistiques annuelles agrégées, les chiffres trimestriels et mensuels des parts de marché ainsi que des indications sur les différents cantons.

Légende: t1 = émissions moyennes de CO2, t2 = part BEV, t3 = part PHEV essence, t4 = part PHEV diesel, t5 = part hybride essence, t6 = part hybride diesel, t7 = part gaz naturel, t8 = part nouvelles immatriculations, t10 = part hydrogène

La numérotation des cantons est celle de l’OFS.

en:
On the basis of the anonymised data for new registrations published by FEDRO, the Swiss Federal Office of Energy has evaluated key figures on alternatively powered passenger cars since 2015. Alternatively powered vehicles are vehicles that are not solely powered by a petrol or diesel internal combustion engine. In addition to aggregated annual key figures, this data set also contains quarterly and monthly market share figures as well as information regarding the individual cantons.

Key: t1 = Average CO2 emissions, t2 = Share of BEVs, t3 = Share of petrol PHEVs, t4 = Share of diesel PHEVs, t5 = Share of hybrid petrol, t6 = Share of hybrid diesel, t7 = Share of natural gas, t8 = Number of new registrations, t10 = Share of hydrogen

Numbering of cantons according to FSO

de:
Auf Basis der vom ASTRA publizierten, anonymisierten Neuzulassungsdaten wertet das Bundesamt für Energie seit 2015 wichtige Kennzahlen zu den alternativ angetriebenen Personenwagen aus. Als alternativ angetriebenen Fahrzeuge gelten Fahrzeuge, die nicht ausschliesslich über einen Benzin- oder Diesel-Verbrennungsmotor angetrieben werden. Dieser Datensatz enthält neben aggregierten jährlichen Kennzahlen auch Quartals- und Monatszahlen der Marktanteile sowie Angaben zu den einzelnen Kantonen.

Legende: t1 = Durchschnittliche CO2-Emissionen, t2 = Anteil BEV, t3 = Anteil Benzin PHEV, t4 = Anteil Diesel PHEV, t5 = Anteil Hybrid Benzin, t6 = Anteil Hybrid Diesel, t7 = Anteil Erdgas, t8 = Anzahl Neuzulassungen, t10 = Anteil Wasserstoff

Nummerierung der Kantone gemäss BFS

it:
Sulla base dei dati anonimizzati sulle nuove immatricolazioni pubblicati dall'USTRA, dal 2015 l'Ufficio federale dell'energia analizza importanti indicatori relativi alle automobili a propulsione alternativa. Per veicoli a propulsione alternativa si intendono veicoli che non sono mossi esclusivamente da un motore a combustione a benzina o diesel. Oltre a indicatori annuali aggregati, questo set di dati contiene anche dati trimestrali e mensili relativi alle quote di mercato e indicazioni sui singoli Cantoni.

Legenda: t1 = Emissioni medie di CO2, t2 = Percentuale BEV, t3 = Percentuale PHEV benzina, t4 = Percentuale PHEV diesel, t5 = Percentuale ibride benzina, t6 = Percentuale ibride diesel, t7 = Percentuale gas naturale, t8 = Numero nuove immatricolazioni, t10 = Percentuale idrogeno

Numerazione dei Cantoni secondo UST.

fr: Modèles de voitures de tourisme entièrement électriques les plus prisés

de: Beliebteste vollelektrische PW-Modelle (BEV)

en: Most popular all-electric models (cars)

it: Modelli più diffusi di automobili completamente elettriche

fr: Depuis 2015, l’Office fédéral de l’énergie recense chaque trimestre les modèles de voitures de tourisme entièrement électriques (BEV) les plus prisés; depuis 2021, les données sont disponibles à un rythme mensuel. Tous les modèles entièrement électriques disponibles en Suisse sont pris en compte.

en: Since 2015, the Swiss Federal Office of Energy has reported the most popular all-electric models (BEVs) among passenger cars on a quarterly basis; since 2021, the data has been available on a monthly basis. All fully electric models from Switzerland are counted together.

de: Ab 2015 weist das Bundesamt für Energie quartalsweise die beliebtesten vollelektrische Modelle (BEV) bei den Personenwagen aus, ab 2021 sind die Daten in monatlicher Auflösung verfügbar. Dabei werden alle vollelektrischen Modelle aus der Schweiz zusammengezählt.

it: Dal 2015 l'Ufficio federale dell'energia indica su base trimestrale i modelli più diffusi di automobili completamente elettriche (BEV); dal 2021 i dati sono disponibili con risoluzione mensile. Vengono conteggiati tutti i modelli completamente elettrici presenti in Svizzera.

fr:
Sur la base des données anonymisées des nouvelles immatriculations publiées par l’OFROU, l’Office fédéral de l’énergie évalue depuis 2015 des chiffres clés importants concernant les voitures de tourisme à propulsion alternative. Sont réputés véhicules à propulsion alternative les véhicules dont la propulsion ne se fait pas exclusivement avec un moteur à combustion à essence ou à diesel. Ce jeu de données comprend, outre les statistiques annuelles agrégées, les chiffres trimestriels et mensuels des parts de marché ainsi que des indications sur les différents cantons. L’Office fédéral de l’énergie évalue par ailleurs les modèles entièrement électriques et hybrides rechargeables les plus prisés.

Base légale: art. 11 de l’ordonnance sur les exigences relatives à l’efficacité énergétique (OEEE)

en:
On the basis of the anonymised data for new registrations published by FEDRO, the Swiss Federal Office of Energy has evaluated key figures for alternatively powered passenger cars since 2015. Alternatively powered vehicles are vehicles that are not solely powered by a petrol or diesel internal combustion engine. In addition to aggregated annual key figures, this data set also contains quarterly and monthly market share figures as well as information regarding the individual cantons. Also, the Swiss Federal Office of Energy ranks the most popular all-electric and plug-in car models.

Legal basis: Energy Efficiency Ordinance (EnEO), Art. 11

de:
Auf Basis der vom ASTRA publizierten, anonymisierten Neuzulassungsdaten wertet das Bundesamt für Energie seit 2015 wichtige Kennzahlen zu den alternativ angetriebenen Personenwagen (PW) aus. Als alternativ angetriebenen Fahrzeuge gelten Fahrzeuge, die nicht ausschliesslich über einen Benzin- oder Diesel-Verbrennungsmotor angetrieben werden. Dieser Datensatz enthält neben aggregierten jährlichen Kennzahlen auch Quartals- und Monatszahlen der Marktanteile sowie Angaben zu den einzelnen Kantonen. Zudem wertet das Bundesamt für Energie bei den PW die beliebtesten vollelektrischen und Plug-In Modellen aus.

Rechtsgrundlage: Energieeffizienzverordnung (EnEV) Art. 11

it:
Sulla base dei dati anonimizzati sulle nuove immatricolazioni pubblicati dall'Ufficio federale delle strade (USTRA), dal 2015 l'Ufficio federale dell'energia analizza importanti indicatori relativi alle automobili a propulsione alternativa. Per veicoli a propulsione alternativa si intendono veicoli che non sono mossi esclusivamente da un motore a combustione a benzina o diesel. Oltre a indicatori annuali aggregati, questo set di dati contiene anche dati trimestrali e mensili relativi alle quote di mercato e indicazioni sui singoli Cantoni. Inoltre l'Ufficio federale dell'energia analizza i modelli di automobili completamente elettriche e plug-in più diffusi.

Base legale: ordinanza sull’efficienza energetica (OEEne), nello specifico l'articolo 11

personenwagen

display_name: personenwagen

territory

de: Raum und Umwelt


radiosondes

maintainer: Jörg Wieder

title_for_slug: radiosondes

en: wind-direction relative-humidity wind radiosonde temperature holoballoon raclets pressure

en: Radiosond Sounding Files

media_type: application/zip

en:
The "soundings" radiosond data contains information on ambient pressure (mbar), temperature (C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), and are ordered with respect to the height above ground (m AGL) with a step size of 20 m. The first line of each file idicates the geographic location and the start time (in UTC) of the ascent. If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

format: ZIP

mimetype: application/zip

en: Radiosond Template Files

en:
The "template" files contain standard parameters, i.e. ambient pressure (mbar and Pa), temperature (°C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), as well as additional information, e.g. time (UTC and local time), dew point (°C), mixing ration (g/kg), density (kg m³), altitude (m MSL), height above ground (ft and m AGL), and geographic coordinates (longitude, latitude). If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosondes (Windsond, Sparv Embedded AB) were started in Davos Wolfgang (LON: 9.853594, LAT: 46.835577) to report height profiles of pressure, relative humidity and temperature at specific days. In addition to regular launches of radiosondes, sondes were attached to [HoloBalloon](https://www.envidat.ch/group/clouds-in-situ-raclets) to report the ambient conditions of the in-situ measurements. Further profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/clouds-in-situ-raclets) which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.

holoballoon

display_name: holoballoon

pressure

display_name: pressure

raclets

display_name: raclets

radiosonde

display_name: radiosonde

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind

display_name: wind

wind-direction

display_name: wind-direction

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

value: Envidat Harvester

en: Radiosondes


en: community-energy energy-cooperatives cooperatives renewable-energy switzerland

en: Questionnaire with variable names

media_type: PDF

en: Modified questionnaire with variable names for each item. Should be used together with the data files (.csv or .sav) to reconstruct the data and variable structures.

format: PDF

mimetype: application/pdf

en: Codebook

en: Description of variable attributes and valid n

en: Raw data (.csv)

media_type: CSV

en: Raw data in csv. format. For comprehension of the data and variable structure, please consult the codebook and the modified questionnaire with variable names.

en: Raw date (SPSS)

media_type: SAV

en: Raw data in sav. format (SPSS). For comprehension of the data and variable structure, please consult the modified questionnaire with variable names.

format: SERVICE

en:
 Topic of Survey
The data at hand on energy cooperatives in Switzerland were collected in 2016 as part of the project "Collective financing of renewable energy projects in Switzerland and Germany" of the National Research Programme 71 "Managing Energy Consumption". The cooperatives were surveyed on their organizational structure, their activities in electricity and heat generation, their finances, the political context and their assessments of the future.

 Survey Method
The survey was targeted at all energy cooperatives in Switzerland (this is the basic population). The Swiss Commercial Register was searched for cooperatives and specific keywords in order to determine this basic population and collect addresses. This search in May 2016 resulted in a total of 304 energy cooperatives, to which a questionnaire was sent in July 2016. A pre-test with 8 persons had been carried out before the questionnaire was sent out. The questionnaire was provided in German and French. It was sent by mail and an attached letter referred to a link for the digital version if preferred. The online version was designed with the software "Sawtooth". After three weeks, a first, and after six weeks a second reminder letter was sent to those cooperatives that had not yet completed the questionnaire. The returned hardcopy questionnaires were manually entered into the database and then combined with the electronic data from the online survey. In the course of the survey, the total population was reduced from 304 to 289: in 4 cases the survey was not deliverable, 4 cooperatives had dissolved, 6 were not actually energy cooperatives, 1 case had recently changed its legal form. With a response rate of 47%, the final data set comprises 136 responses (from 77 digital and 59 hardcopy questionnaires). However, not all 136 of the returned questionnaires were filled out completely. We checked for answers that seemed contradictory or incomprehensible. If an error could be clearly identified and the correct answer derived, the answer was adjusted, otherwise the answer was replaced by "missing data".

 Anonymization
Participating cooperatives have been assured that their information will be kept confidential and will only be made public anonymously. For this reason, the data have been anonymized in in order to prevent any identification of individual cooperatives.

 How to Use the Data
* The data are available in CSV and SPSS (sav.) format.
* A codebook and a modified version of the used questionnaire are provided to illustrate the data and variable structure. In the questionnaire, the variable names are assigned to the corresponding questions. In the codebook, further information on these variables (valid n, answer categories) can be found. This information (of the codebook) is already integrated in the SPSS file.

 Current Embargo on Data
These data are currently under embargo and will only be released when the project is completed (not before 2020).

#Additional Information
* The used questionnaire is provided in German and French.
* Descriptive results of the survey were published in a WSL report: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:18943

community-energy

display_name: community-energy

cooperatives

display_name: cooperatives

energy-cooperatives

display_name: energy-cooperatives

renewable-energy

display_name: renewable-energy

switzerland

display_name: switzerland

en: Energy Cooperatives in Switzerland: Survey Results // Energiegenossenschaften in der Schweiz: Befragungsergebnisse


weather-station-davos-wolfgang

title_for_slug: weather-station-davos-wolfgang

en: relative-humidity temperature pressure weather raclets

en: Weather Station Davos Wolfgang

en: The data file contains date and time (YYYY-MM-DD hh:mm:ss) in UTC, temperature (°C), relative humidity (%), pressure (hPa) at 10 m above ground and above sea level. The data was averaged over 10 minutes.

en: The dataset contains weather parameters measured at Davos Wolfgang (LON: 9.853594, LAT: 46.835577).

weather

display_name: weather


maintainer: EnviDat Support

en: snow-depth vertical-wind-motion snow-cover boundary-layer-winds saltation

en: Data Compilation

media_type: ZIP

en: Compressed TXT files

en:
The data correspond to the experiments presented and discussed in a paper regarding the interaction between turbulent wind fluctuations and snow saltation mass-fluxes (Paterna, 2016). Each of the nine data files corresponds to a different experiment presented in the paper and conducted in the winter 2014/2015 in the WSL/SLF cold wind tunnel in Davos. For each file the five columns indicate the time from the beginning of the experiment, the streamwise (u’) and the vertical (w’) wind velocity fluctuations, the streamwise (qx) and the vertical (qz) snow mass-flux components. From these time-series the scales of the snow saltation and of the turbulent flow are obtained with respect to the eddy-cycles and snow saltation cycles. From spectral analysis of the time-series a decoupling of the snow saltation from the turbulence forcing reveals two regimes of interaction: a turbulence-dependent regime occurring with weak saltation, and a turbulence-independent regime with strong saltation. Further details can be found at the link below.

Publication http://onlinelibrary.wiley.com/doi/10.1002/2016GL068171/abstract

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

vertical-wind-motion

display_name: vertical-wind-motion

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: Wind tunnel measurement data of drifting snow and turbulent wind fluctuations


maintainer: Bundesamt für Energie BFE

fr: rpc prix-de-reference commercialisation-directe ogd60bfe retribution-de-l-injection

de: direktvermarktung referenz-marktpreis kev einspeiseverguetung ogd60bfe

fr: Prix de marché de référence selon l'art. 15, OEneR

de: Referenz-Marktpreise gemäss Art. 15, EnFV

author: Bundesamt für Energie BFE

media_type: SERVICE

mimetype: SERVICE

fr: Prix de marché de référence (art. 15, OEneR) - prix trimestriel

de: Referenz-Marktpreise (Art. 15, EnFV) - Quartalspreise

fr: Prix de marché de référence (art. 15, OEneR) - prix annuel

de: Referenz-Marktpreise (Art. 15, EnFV) – Jahrespreise

fr: Prix de marché de référence (art. 15, OEneR) - prix mensuel

de: Referenz-Marktpreise (Art. 15, EnFV) – Monatspreise

media_type: XML

format: XML

fr:
Le prix de marché de référence est déterminant pour la fixation de la prime d’injection pour les installations de production bénéficiant de la rétribution de l’injection. Le prix de marché de référence des __installations photovoltaïques__ correspond à la moyenne des prix fixés sur la bourse de l’électricité Swissix pour le jour suivant (day-ahead) sur un trimestre, pondérés par l’injection effective au quart d’heure des installations photovoltaïques avec mesure de la courbe de charge.
Pour les __autres technologies__, le prix de marché de référence pour les installations avec mesure de la courbe de charge correspond à la moyenne mensuelle des prix day-ahead qui sont fixés sur la bourse de l’électricité Suisse. Pour les installations sans mesure de la courbe de charge le prix de marché de référence correspond à la moyenne trimestrielle.

Les prix s'entendent hors TVA.

de:
Der Referenz-Marktpreis ist für die Festlegung der Einspeiseprämie für Erzeugungsanlagen mit Einspeisevergütung massgebend. Der Referenz-Marktpreis für __Photovoltaikanlagen__ entspricht dem Durchschnitt der Preise, die an der Strombörse (Swissix) in einem Vierteljahr jeweils für den Folgetag (day-ahead) festgesetzt werden, gewichtet nach der tatsächlichen viertelstündlichen Einspeisung der lastganggemessenen Anlagen. Bei den __übrigen Technologien__ entspricht der Referenz-Marktpreis dem Durchschnitt der Preise, die für lastganggemessene Anlagen in einem Monat und für nicht lastganggemessene Anlagen in einem Vierteljahr an der Strombörse für den Folgetag für das Marktgebiet Schweiz festgesetzt werden.

Die Preise verstehen sich exklusive Mehrwertsteuer.

commercialisation-directe

display_name: commercialisation-directe

direktvermarktung

display_name: direktvermarktung

einspeiseverguetung

display_name: einspeiseverguetung

kev

display_name: kev

prix-de-reference

display_name: prix-de-reference

referenz-marktpreis

display_name: referenz-marktpreis

retribution-de-l-injection

display_name: retribution-de-l-injection

rpc

display_name: rpc

energy

en: Energy

politics

fr: Politique

de: Politik

en: Politics

it: Politica

prices

fr: Prix

de: Preise

en: Prices

it: Prezzi

bundesamt-fur-energie-bfe

en: Swiss Federal Office of Energy SFOE

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).


maintainer: James W. Kirchner

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

en: Subcatchment polygons

media_type: text/plain

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

format: TXT

mimetype: text/plain

en: Metadata

media_type: application/pdf

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

en: Daily time series

en: Daily hydrometeorological and ecohydrological time series

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: MODIS EVI2 script

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

en: 30-minute time series

en: 30-minute hydrometeorological and ecohydrological time series.

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


maintainer: Thorsten Bartels-Rausch

en: laboratory-study cryosphere snow arctic sea-salt-aerosol antartic polar

en: Experimental Results: Uptake coefficients vs. temperature and ozone concentration

en:
* Final Data to Figure 3: Uptake coefficients as a function of temperature at 5E12 molecules per cm3 ozone concentration.
* Final Data to Figure 6: Uptake coefficients at different temperatures as a function of gas- phase ozone concentration.

The average ozone uptake coefficients of the three cycles between the bypass and the flow tube per repeat is taken as the mean uptake coefficient for each experiment. Gamma was corrected for gas phase diffusion limitation following the Cooney–Kim– Davis (CKD) method52 (see supporting material of publication for details).

en: Experimental results of uptake coefficient vs. temperature and ozone concentration

en:
Data to Figure 3: Measured uptake coefficients as a function of temperature at 5E12 molecules per cm3 ozone concentration.

Data to Figure 6: Measured uptake coefficients at different temperatures as a function of gas- phase ozone concentration.

en: The reaction of ozone with bromide in polar regions results in the formation of reactive bromide species with impacts on ozone budget and the oxidative capacity of the lower atmosphere. Here, we present a data investigating the temperature dependence of bromide oxidation by ozone using a coated wall flow tube reactor coated with an aqueous mixture of citric acid and sodium bromide, a proxy for sea salt aerosol in snow or the free troposphere. Thus study shows the effect of of organic species at relatively mild temperatures between the freezing point and eutectic temperature as typical for Earth's cryosphere.

antartic

display_name: antartic

arctic

display_name: arctic

cryosphere

display_name: cryosphere

laboratory-study

display_name: laboratory-study

polar

display_name: polar

sea-salt-aerosol

display_name: sea-salt-aerosol

snow

display_name: snow

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: Kinetic experiments on the oxidation of bromide by ozone from 289-245 K.


en: cryowrf antarctica topography wrf landuse

en: Scripts

en: Scripts to run the preprocessing to produce WRF binary tiles from REMA and AntarcticaLC2000 for topography and landuse (see Documentation for procedure).

en: Documentation

en: Documentation about how the provided dataset was produced including details to reproduce the dataset.

en: WPSinput

en: Input files to run the Weather Research and Forecasting model (WRF) preprocessing system WPS with REMA topography and AntarcticaLC2000 landuse data (see Documentation for details).

en:
Reference Elevation Model of Antarctica (REMA) topography and AntarcticaLC2000 landuse data
are now available as static data input for the Weather Research and Forecasting model (WRF). Topography
and landuse are made available at a spatial resolution of 1 km. This documentation describes the methods
applied to convert REMA and AntarcticaLC2000 to WRF readable format and shows how this improves
the representation of the Antarctic topography and landuse categories over coastal Antarctic regions.

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

en: REMA topography and AntarcticaLC2000 for WRF


mountain-permafrost-hydrology

maintainer: Jeannette Noetzli

title_for_slug: mountain-permafrost-hydrology

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

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

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). 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


maintainer: Matthias Haeni

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

en: Data plot of the forest station (BTB)

en: Data file.

en: Site photo of the field station (BTF)

media_type: image/jpeg

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

mimetype: image/jpeg

en: Data plot of the field station (BTF)

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

en: Field station data (BTF)

en: Site aerial photo (Bettlachstock)

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

en: Site photo of the forest station (BTB)

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

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 Bettlachstock in Switzerland where one station is located within a natural mixed forest stand (BTB) with European beech (_Fagus sylvatica_; 170-190 yrs), European silver fir (_Abies alba_; 190 yrs) and Norway spruce (_Picea abies_; 200 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Bettlachstock 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

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Bettlachstock, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Henning Löwe

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

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


maintainer: Frank Techel

en: avalanche-danger avalanche-observations norway rutschblock-test switzerland extended-column-test

en: avalanche occurrence data (Norway, Sitzerland) - avalanche sizes per day and warning region

en: ECT data (Norway, Switzerland)

en: avalanche occurrence data (Norway, Sitzerland) - largest avalanche size per day and warning region

en: Rutschblock data (Switzerland)

en:
Observational data used to quantitatively describe the key elements describing avalanche danger: snowpack stability, the frequency distribution of snowpack stability, and avalanche size.
The data set consists of
- Rutschblock test results (Switzerland)
- Extended Column Test results (Switzerland, Norway)
- Avalanche occurrence data (Switzerland, Norway).
The data were extracted from the respective operational databases of the national avalanche warning services in Switzerland (WSL Institute for Snow and Avalanche Research SLF Davos, Switzerland) and Norway (The Norwegian Water Resources and Energy Directorate NVE).
For further information regarding the data, please refer to the publication or contact the author.

avalanche-danger

display_name: avalanche-danger

avalanche-observations

display_name: avalanche-observations

extended-column-test

display_name: extended-column-test

norway

display_name: norway

rutschblock-test

display_name: rutschblock-test

switzerland

display_name: switzerland

en: Stability tests, avalanche observations, Switzerland, Norway


maintainer: Sebastian Schlögl

en: snow stable-boundary-layer atmospheric-turbulence turbulent-sensible-heat-fluxes atmosphere

en: Turbulence data WFJ07

en: upper sensor

en: Turbulence data AA00

en: sensor in 0.2 m height

en: Turbulence data PM07

en: SEE

en: Turbulence data WFJ11

en: lower sensor

en: Turbulence data GR00

en: sensor in 2 m height

en: NWW

en: sensor in 1 m height

en: sensor in 25 m height

en:
We used five different atmospheric turbulence datasets from four test sites, with these sites showing differences in their topographical characteristics. We chose one typical alpine test site with high topographical complexity (Weissfluhjoch, Davos, Switzerland) and three test sites consisting of one glacier site (Plaine Morte, Crans-Montana, Switzerland) and two polar sites (Greenland and Antarctica) representing a quasi-ideal site with homogeneous surface and quasi infinite fetch in all directions.
The turbulent sensible heat flux was calculated using the eddy-covariance method. Note that the sonic temperature fluctuations have been converted into virtual temperature fluctuations.
Three-dimensional wind velocity and air temperature were processed using a linear detrending (Rannik and Vesala, 1999) and a planar fit approach (Massmann and Lee, 2002) to rotate the coordinate system. Air temperature, relative humidity and air pressure from weather stations were used to calculate air properties, which are required for the data processing. The weather stations are located in the immediate vicinity of the turbulence tower and are affected by the same air masses. Turbulence data were averaged to 30-min intervals, whilst changing to a 15-min time interval marginally affects the heat fluxes at the Weissfluhjoch test site (Mott et al., 2011). Note that we define a negative sensible heat flux as being directed towards the snow surface and a positive sensible heat flux as being directed upwards.
The selected datasets and corresponding test sites are briefly introduced below:

Weissfluhjoch 2007 (WFJ07): A vertical set-up of two three-dimensional ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) was used at the traditional field site Weissfluhjoch (2540 m asl.) to measure three-dimensional wind velocity and air temperature at a frequency of 20 Hz. The sensors were mounted 3 m and 5 m above the ground and provided reliable data for 50 days between 11 February 2007 and 24 April 2007. Further information on the field campaign can be found in Stössel et al. (2010) and Mott et al. (2011).

Weissfluhjoch 2011-13 (WFJ11): Three-dimensional wind velocity and air temperature were recorded at 5 m above the ground at a frequency of 10 Hz with a three-dimensional ultrasonic anemometer (CSAT3). The analysis was conducted for data obtained between February and March in the years 2011-13.

Plaine Morte 2007 (PM07): Two three-dimensional ultrasonic anemometers (CSAT3) were installed on a horizontal boom facing opposite directions (west-north-west vs. east-south-east) at 3.75 m above the ground to measure air temperature and three-dimensional wind velocity at 20 Hz. The data were collected at the almost flat field site on the Plaine Morte glacier (2750 m asl.) near Crans-Montana, Switzerland from February to April 2007. High quality meteorological data were additionally recorded and used to force the model. A detailed description about the set-up at the Plaine Morte glacier can be found in Huwald et al. (2009) and Bou-Zeid et al. (2010).

Greenland 2000 (GR00): High-frequency three-dimensional ultrasonic anemometer measurements (CSAT3) were recorded at 50 Hz at the Summit Camp (72.3 °N, 38.8 °W, 3208 m asl.) located on the northern dome of the Greenland ice sheet. Data were collected at 1 m and 2 m above the snow surface during summer in 2000 and 2001. Additionally, meteorological measurements were obtained for the post processing and used to force the model. More information about the field campaign can be found in Cullen et al. (2007, 2014).

Antarctica 2000 (AA00): A set-up of three vertical three-dimensional ultrasonic anemometers (DA-600, Kaijo Denki) were installed at Mizuho Station (70°42' S, 44°20' E, 2230 m asl.) in Eastern Antarctica at 0.2, 1 and 25 m and recorded turbulence data at a frequency of 100 Hz from October to November 2000. Longwave and shortwave radiation, relative humidity, air and snow surface temperature were additionally measured and used to force the model. More information about the field campaign can be found in Nishimura and Nemoto (2005).

atmosphere

display_name: atmosphere

atmospheric-turbulence

display_name: atmospheric-turbulence

snow

display_name: snow

stable-boundary-layer

display_name: stable-boundary-layer

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

en: How do stability corrections perform in the stable boundary layer over snow?


en: snow shortwave-radiation photovoltaic winter-energy-production albedo

en: Data Forward Scattering

media_type: .zip

en: GROUNDEYE model for multiple forward scattering in snow-covered terrain. Meteorological and topographical input data set for the Meierhofertäli near Davos, Switzerland, September 2017 - August 2018. Output data for September 2017 - August 2018 at hourly resolution and every pixel. Post-processing scripts for plotting and analysis.

en:
 Overview
We present GROUNDEYE, a new model of radiative transfer over mountainous terrain, which considers for the first time the forward scattering properties of snow.
Embedded in the surface process model Alpine3D, the new terrain radiation model GROUNDEYE receives interpolated real weather data with diffuse and direct broadband shortwave radiation for each pixel as well as a spatially variable plane albedo from the module SNOWPACK.

 Format
The GROUNDEYE model is written in c++, as is the entire environment of Alpine3d. The input and output data sets are .xlsx or .txt format, pre- and postprocessing including the generation of all figures is in .R format.

 Structure
In Data_Forward_Scattering.zip you will find all necessary data and model details to
reproduce the results of the JGR publication "How forward-scattering snow and terrain change the Alpine radiation balance with application to solar panels"

 - 	Model Input Data contains the meteorological and topographic input data sets, the BRDF, and preprocessing scripts.
 - Model Code contains the full model Alpine3d including the radiative transfer module GROUNDEYE.
 - Model Output Data contains the results of the simulation of terrain irradiance and irradiance of solar panels; hourly resolution, 1. Sptember 2017 - 31. August 2018.
 - Measurements Solar Testsite contains information and measurements of the solar testsite at the Totalp near Davos, Switzerland.
 - Postprocessing contains all R-Scripts used for the analysis and
plotting of the corresponding data.

In each of these folders you will find detailed information in
the file 'About this Folder.txt'.

albedo

display_name: albedo

photovoltaic

display_name: photovoltaic

shortwave-radiation

display_name: shortwave-radiation

winter-energy-production

display_name: winter-energy-production

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: Data, Code Link and Metadata on Forward Scattering of Snow at Totalp


en: borehole ritigraben permos ground-temperature permafrost

en: DATA ACCESS

media_type: URL

en: Map of PERMOS borehole network

en: PERMOS DATA POLICY

en:
_ENVIDAT NOTE: Data currently unvailable and measures are being taken to recover and restore the data files._

Processed ground temperature measurements at the Ritigraben permafrost borehole (RIT_0102) in canton Valais, Switzerland. The borehole is located at 2690 m asl on a flat site. The surface material is coarse blocks and borehole depth is 30 m. Thermistors used YSI 44006. Year of drilling 2002. This borehole is part of the Swiss Permafrost network, PERMOS (www.permos.ch). Contact phillips@slf.ch for details of processing applied.

borehole

display_name: borehole

ground-temperature

display_name: ground-temperature

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

en: RIT1: Processed permafrost borehole data (2690  m asl), Ritigraben, Switzerland


en: hazard-mapping satellite avalanche natural-hazard snow

en: SPOT6 Avalanche outlines 24 January 2018

media_type: SHP

en: Shapefile of the manually mapped avalanche outlines. Please only use this data together with the example key document provided with this dataset.

format: SHP

en:
Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)

The generation of the data is described in:

Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.

Abstract.
Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2).

We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.

This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.

Koordinate System: CH1903+ LV95 LN02

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite


en: cryowrf surface-mass-balance antarctica reproducibility blowing-snow

en: Processed CRYOWRF output used for the analysis and the figures in the paper.

en: Static input data from the WRF simulations (used in the python scripts in Scripts_Reproducibility).

en: Python scripts to reproduces figures in Gerber et al., 2022, submitted.

en: Processed WRF output (run with Noah-MP land surface model) used for the analysis and the figures in the paper.

en: Namelist and input files and information to run the WRF and CRYOWRF simulations used in the paper.

en:
This dataset contains data and scripts for "CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB" (Gerber et al., submitted).

* Simulation_setup: Namelists and input information to run the simulation. Some input files need to be downloaded from Sharma et a., 2021.
* Static_input: Static topography input file of WRF (geo_em.d01).
* WRF_27km_NoahMP: Preprocessed WRF output of the simulation run with the WRF using the surface parameterization Noah-MP to reproduce the figures and results in the paper.
* WRF_27km_CRYOWRF: Preprocessed WRF output of the simulation run with CRYOWRF to reproduce the figures and results in the paper.
* Scripts_Reproducibility: Python scripts to reproduce the figures and results in the paper.

Note:

* To run some of the scripts Atmospheric Weather station data needs to be prepared using Gerber and Lehning, 2022.
* AWS data is not provided and needs to be downloaded from the corresponding databases. Please make sure to comply with the respective terms and conditions.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance

en: Reproducibility dataset for CRYOWRF validation


maintainer: Franziska Koch

en: gps snow-depth snow-cover liquid-water-content snow

en: Read-me

en: The read-me file contains the description of the data provided.

en: Dataset with GPS-derived snow cover properties and validation data

en: This file includes the data as described in the Read-me file.

en:
This data set includes GPS-derived snow water equivalent (SWE), snow depth (HS) and liquid water content (LWC) data for three entire snow-covered seasons (2015-2016, 2016-2017, 2017-2018) at the study plot Weissfluhjoch 2540 m a.s.l. (Davos, Switzerland). The procedure to derive these snow properties is described in Koch et al. (2019). The novel approach is based on a combination of GPS signal attenuation and time delay.

The dataset also includes corresponding validation data for SWE and HS measured at Weissfluhjoch, and some additional meteorological data used for interpretation of the snow cover evolution.

Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
> Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., Prasch, M., Schweizer, J., and Mauser, W., 2019. Retrieval of snow water equivalent, liquid water content and snow height of dry and wet snow by combining GPS signal attenuation and time delay. Water Resources Research, 55(5), 4465-4487. https://doi.org/10.1029/2018WR024431

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

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: GPS-derived data of SWE, HS and LWC and corresponding validation data


maintainer: Leo Gallus Bont

en: accessible-forest openstreetmap seilaplan geoprocessing forest qgis

en: Forest vector data (for sample forest range)

en: Juypter Notebook for Data Preparation (online)

media_type: ipynb

en: Digitised sample perimeter

en: Power lines vector data (close to the area of the sample forest range)

en: Juypter Notebook for Data Preparation

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

en: DEM (for the area of the sample forest range)

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Railways vector data (close to the sample forest range)

en:
This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).
The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.
The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019.

Additional notes for vector data:
Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API - https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any perimeter or area can be digitised freely using the QGIS editing toolbar.

The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:

- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)
- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif

This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.

Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.

This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan

en: Sample Geodata and Software for Demonstrating Geospatial Preprocessing for Forest Accessibility and Wood Harvesting at FOSS4G2019


en: meteodat-gmbh wagital snow-water-equivalent snow gcos

media_type: TXT

en:
Total water reserves of the snow cover [mio m3] for Wägital catchment, Switzerland, for reference date April 1. Data is separated in 2 elevation zones 900m-1500m asl and 1500m-2300m asl. Time period 1943-2022, status 2022-04-20.

Funded currently or in the past by:

- Federal Office of Meteorology and Climatology MeteoSwiss in the context of GCOS Switzerland
- Meteodat GmbH
- Institute of Geography, University of Zurich
- WSL Institute for Snow and Avalanche Research SLF
- Institute of Geography, ETH Zurich (IAC ETH Zurich)
- AG Kraftwerk Wägital (AXPO and EWZ)

See also https://www.meteodat.ch/waegital.html

gcos

display_name: gcos

meteodat-gmbh

display_name: meteodat-gmbh

snow-water-equivalent

display_name: snow-water-equivalent

wagital

display_name: wagital

en: Snow water equivalent for reference date April 1 for Wägital catchment, starting 1943


en: snow acoustic-emissions fiber-bundle-model sintering snow-avalanche snow-failure viscous-deformation snow-mechanics

en: fiber-bundle-model-for-snow-failure

media_type: application/zip

en: Data underlying Figures in publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted to "Geophysical Research Letters"

en:
This dataset contains modeled and experimental results for laboratory snow failure experiments and the concurrent acoustic emissions signatures for different loading rates. For modelling the snow failure we used a fiber bundle model that includes sintering and viscous deformation.

The data underlay the figures in the publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted for publication to "Geophysical Research Letters".

acoustic-emissions

display_name: acoustic-emissions

fiber-bundle-model

display_name: fiber-bundle-model

sintering

display_name: sintering

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-mechanics

display_name: snow-mechanics

viscous-deformation

display_name: viscous-deformation

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Fiber Bundle Model for snow failure and concurrent Acoustic Emissions


en: strategic-plans development-priorities spatial-information urban-region europe

en: Planning intentios

en:
The present dataset is part of the report titled Gradinaru S.R., Hersperger A.M., Schmid F. (2021). Deriving Planning Intentions from written planning documents. Report on CONCUR Project- From plans to land change: how strategic spatial planning contributes to the development of urban regions.
The data corresponds to the data collected as part of the DPI Method for deriving all PIs contained in a plan (open coding) as detailed in section 4 of the report. The method involved reading the plans to break down of information in meaningful discrete “incidents” or planning intentions. To identify the planning intentions, the starting points were represented by a) the structuring of the plans in chapters and sub chapters and b) the themes that the plans addressed. Thus, the collected information was not grouped according to pre-defined categories of planning intentions, but rather put together as a list of intentions as revealed by each plan. As a result, we provide, for each case study, a document (named [Urban region name] PI as defined in the plan) which contains:
	Date when the information was filled in.
	Name of the urban region and analysed strategic spatial plan .
	A list of all planning intentions contained in a plan, with each PI being addresses as follows:
	Name of PI as it appears in the plan
	Translated name of the PI (i.e. short name for easy understanding of the meaning)
	Explanation regarding the meaning of the PI
	Why the PI is considered a priority for the urban region
	Spatial information on the PI (text and cartographic representations).
In total, 14 documents are available, one for each case study. Documents contain up to 20 pages of information extracted from the plans together with explanations and notes taken during plan reading.

development-priorities

display_name: development-priorities

europe

display_name: europe

spatial-information

display_name: spatial-information

strategic-plans

display_name: strategic-plans

urban-region

display_name: urban-region

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: Planning intentions in strategic plans of European urban regions


maintainer: Ionuț Iosifescu Enescu

en: map preview 0.5MB

en: large map 10GB

en: huge map 100GB

en: map 2GB

en: Bulk Data Access

en: Link to the S3 bucket where all the data resources can be downloaded in bulk

en: map 0.2GB

en: map 0.5GB

en: map 1GB

en:
The attached data are some large GIS raster files (GeoTIFFs) made with Natural Earth data. Natural Earth is a free vector and raster map data @ naturalearthdata.com. The data used for creating these large files was the "Cross Blended Hypso with Shaded Relief and Water". Data was concatenated to achieve larger and larger files. Internal pyramids were created, in order that the files can be opened easily in a GIS software such as QGIS or by a (future) GIS data visualisation module integrated in EnviDat.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis

en: Large GIS raster data derived from Natural Earth Data (Cross Blended Hypso with Shaded Relief and Water)


en: water-supply water-scarcity reservoirs water-demand climate-change

en: Water supply

en: Simulated discharge series for a reference period 1981-2010 and till the end of the century. Data are provided for 39 climate model chains and a control run based on the observed meteorology. Data are provided at daily resolution (mm/d).

en: Water demand (deprecated)

en:
Warning: please use the corrected version 2, since this file contains errors for certain categories such as Livestock, Industry or Houshold.

Water demand estimates for the 307 medium-sized catchments for different categories for current and future conditions. One text file is provided per demand category. One column corresponds to one catchment (IDs compare to shapefile), The data are provided at monthly resolution in mm/d and can be converted to volumes by using the catchment area. E.g.
Q[mm/d] * catchment area [m²] /1000 = Q[m³/d]
or to obtain discharge in m³/s
Q[mm/d] * catchment area [m²]/1000/24/3600 = Q [m³/s].
Future irrigation and hydropower water demand are provided per climate model chain.

en: Water demand version 2 (corrected version)

en: Reservoir volumes

en: Reservoir volume for the 307 medium-sized catchments for different storage categories: natural lakes, artificial reservoirs, reservoirs for artificial snow production, drinking water reservoirs, and usable volumes of natural lakes. Unit: Mio m³. One column per catchment (see shapefile).

en: Shapefile of 307 catchments in Switzerland

en: Shapefile of 307 catchments for which estimates of water supply, demand, and reservoir volumes are provided. The OBJECTID entry corresponds to the catchment ID which is used as a reference in the other datasets provided.

en:
The dataset Hydro-CH2018 reservoirs provides estimates of current and future water supply, water demand, and storage volumes for 307 medium-sized catchments in Switzerland.
Water supply for current (1981-2010) and future (2070-2099) climate conditions was simulated using the hydrological model PREVAH. For modeling current water supply, observed meteorological time series were used as input, while simulated meteorological time series derived from 39 model chains of the CH2018 initiative were used as an input for simulating future climate conditions.

Water demand was estimated for six categories:

- 1) Drinking water (households and tourism),
- 2) industry (second and third sector),
- 3) artificial snow production,
- 4) agriculture (irrigation and livestock feeding),
- 5) ecology (residual flows), and
- 6) hydropower.

Future estimates consider changes in demand related to population growth and changes in the hydrological conditions.
Storage volumes are provided for natural lakes (storage capacities and usable volumes), artificial reservoirs, reservoirs for artificial snow production, and drinking reservoirs.

A detailed description of the simulation and estimation procedures can be found in

*  Brunner, M.I., Björnsen Gurung, A., Zappa, M., Zekollari, H., Farinotti, D., Stähli, M., 2019. Present and future water scarcity in Switzerland: Potential for alleviation through reservoirs and lakes. Sci. Total Environ. 666, 1033–1047. https://doi.org/10.1016/j.scitotenv.2019.02.169.

This dataset contains the following information:

1.	Shapefile with the 307 medium-sized Swiss catchments.
2.   Textfiles with the water supply simulations for the control run and the 39 climate model chains (one file per chain) at daily resolution for the 307 catchments.
3.	Textfiles with the current and future demand estimates per category at monthly resolution for the 307 catchments.
4.	Textfiles with the storage volumes per category and catchment.

climate-change

display_name: climate-change

reservoirs

display_name: reservoirs

water-demand

display_name: water-demand

water-scarcity

display_name: water-scarcity

water-supply

display_name: water-supply

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Hydro-CH2018 reservoirs


wind-lidar-davos-wolfgang

title_for_slug: wind-lidar-davos-wolfgang

en: wind wolfgangpass raclets profiles lidar

en: Wind LIDAR data Wolfgang

en: A Leosphere WidCube 100S was deployed at Davos Wolfang, measuring wind profiles as well as performing PPI and RHI scans. Time format is in UTC with highest time resolution of 5 seconds.

en: Scanning wind Lidar from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 200 m above ground to 8100 m. The time resolution is up to 5 seconds. The Lidar was measuring wind profiles but also performed plan position indicator (PPI) and range height indicator (RHI) scans.

lidar

display_name: lidar

profiles

display_name: profiles

raclets

display_name: raclets

wind

display_name: wind

wolfgangpass

display_name: wolfgangpass

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: Wind LIDAR Davos Wolfgang


maintainer: Paraskevi Georgakaki

en: blowing-snow ice-water-content jungfraujoch liquid-water-content ice-crystal-number-concentration secondary-ice-production swiss-alps wrf

en: WRF outputs

media_type: zip-compressed folder of NetCDF files

en:
The .zip file contains all the NetCDF outputs produced by the mesoscale Weather Research and Forecasting (WRF) model (version: 4.0.1). Two case studies were simulated in this study, between 25-28 January 2014 (00:00 UTC) and 29 January - 1 February 2014 (00:00 UTC), respectively. The former is denoted as "NW" and the latter as "SE", owing to the prevailing wind conditions at the Jungfraujoch (JFJ) station.

The outputs come from the innermost domain of the simulations with a spatial resolution of 1 km and are extracted from the nearest to JFJ model grid point (46.55°N 7.98°E). The dimensions of each model variable is [145,100], which corresponds to time and height, respectively. The frequency of the outputs is 30 min. Note that the first 24 hours of each simulation (i.e., the first 48 outputs) were considered spin up time.

The following sets of sensitivity simulations were presented in this study:

* CNTRL_NW.nc, CNTRL_SE.nc : Sensitivity simulations performed with the default version of WRF
* DS_PHILL_NW.nc, DS_PHILL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Phillips et al. (2018)
* DS_SULL_NW.nc, DS_SULL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Sullivan et al. (2018)
* PHILL_NW.nc, PHILL_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Phillips et al. (2017)
* TAKAH_NW.nc, TAKAH_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Sullivan et al. (2018) based on Takahashi et al. (1995)
* TAKAHrim_NW.nc, TAKAHrim_SE.nc : Same set-up as before but applied only to collisions between rimed ice particles
* BIPS_Xk0_DY_NW.nc, BIPS_Xk0_DY_SE.nc : Sensitivity simulations including a source of Xk0 (either 10.0 or 100.0 L⁻¹) ice crystals with sizes of DY (either 10 or 100 μm) in the first atmospheric level of the model
* BIPS100_PHILL_NW.nc, BIPS100_PHILL_SE.nc : Sensitivity simulations where the combined effect of blowing snow and ice-ice collisional break-up is examined

en: Observational data

media_type: zip-compressed folder of csv

en:
The .zip file contains 6 .csv files including all microphysical measurements taken at the Jungfraujoch station during the two periods of interest:

* 25-28 January 2014 : northwesterly-winds (NW)
* 29 January - 1 February 2014 : southeasterly-winds (SE)

The total Ice Crystal Number Concentration (ICNC; reported in L⁻¹) is measured by the two-dimensional stereo hydrometeor spectrometer (2D-S; Lawson et al., 2006) over the size range 10-1280 μm. The total ice water content (IWC; reported in gm⁻³) is also derived by the 2D-S data using the Brown and Francis (1995) mass-diameter relationship. Finally, the quantification of the liquid water content (LWC; reported in gm⁻³) is based on the liquid droplet size distribution data derived from a DMT cloud droplet probe (CDP; Lance et al., 2010) over the size range 2-50 μm. The frequency of the measurements in the .csv files is 30 min, to match the output frequency of the model. Datetime is also reported in the files (DD/MM/YYYY h:mm) in UTC.

Acknowledgment: Collection and pre-processing of the microphysical measurements has been performed by Gary Lloyd (gary.lloyd@manchester.ac.uk). More details about the instrumentation during the CLACE2014 campaign can be found in Lloyd et al. (2015).

en:
This repository contains all WRF model outputs and observational data sets used for the paper:
Georgakaki, P., Sotiropoulou, G., Vignon, É., Billault-Roux, A.-C., Berne, A., and Nenes, A.: Secondary ice production processes in wintertime alpine mixed-phase clouds, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-760, in review, 2021.

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf

en: Data for the publication "Secondary ice production processes in wintertime alpine mixed-phase clouds"


en: wms-data swiss-geodata qgis-plugin geoinformation-system digital-planning cable-yarding digital-elevation-model seilaplan open-source

en: View video on youtube!

en: WMS-Layer als Hintergrundkarten laden

en:
In order to digitally plan a cable line using the QGIS plugin ‘Seilaplan’, maps with various background information are helpful. In this tutorial we show you how to obtain maps that are helpful for cable line planning, for example a national map of Switzerland at different scales, the NFI vegetation height model or the NFI forest mix rate. For this we explain what WMS datasets are and how to integrate them into QGIS. No download of large data is needed for this, only a good internet connection. Please note that the tutorial language is German!

Link for the integration of WMS data: https://wms.geo.admin.ch/

Link to the description on the Swisstopo website:
https://www.geo.admin.ch/en/geo-services/geo-services/portrayal-services-web-mapping/web-map-services-wms.html

Link to the Seilaplan website: https://seilaplan.wsl.ch

**************************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung sind verschiedene Hintergrundkarten hilfreich. In diesem Tutorialvideo zeigen wir, was WMS Daten sind und wie man diese in QGIS einbinden kann. Dafür müssen die Daten nicht heruntergeladen werden. Es braucht lediglich eine gute Internetverbindung. Für die Seillinienplanung hilfreiche Karten sind bspw. die Landeskarte der Schweiz in verschiedenen Massstäben, das Vegetationshöhenmodell LFI oder der Waldmischungsgrad LFI.

Link zur Einbindung der WMS Daten: https://wms.geo.admin.ch/

Link zur Beschreibung auf der Swisstopo Webseite: https://www.geo.admin.ch/de/geo-dienstleistungen/geodienste/darstellungsdienste-webmapping-webgis-anwendungen/web-map-services-wms.html

Link zur Seilaplan-Website: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

wms-data

display_name: wms-data

en: Seilaplan Tutorial: Load WMS layers as background maps


lidar-davos-wolfgang

maintainer: Patric Seifert

title_for_slug: lidar-davos-wolfgang

en: tropos clouds raclets lidar polly

en: Raman Lidar Davos

en: A portable Raman lidar system (Polly) from Leibnitz Institute for Tropospheric Research (Tropos) was deployed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Please use this [link](http://polly.tropos.de/?p=lidarzeit&Ort=39), to be directly forwarded to the Davos location and select the date of interest from the calendar (bold numbers). The data can be requested directly at the Polly team.

clouds

display_name: clouds

lidar

display_name: lidar

polly

display_name: polly

raclets

display_name: raclets

tropos

display_name: tropos

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: LIDAR Davos Wolfgang