de: Tagesaktuelle Baustellen auf dem Kantonsstrassennetz. Die vier Unterhaltregionen des Tiefbauamtes aktualisieren laufend die Informationen über bestehende und zukünftige Baustellen. Die Kommunikationsabteilung der Baudirektion des Kantons Zürich ist Ansprechpartner bei Fragen zu den Baustellen (http://www.bd.zh.ch/internet/baudirektion/de/service/nav/service/medien.html).

de: WFS Baustellen Kantonsstrassen


label: Geometadaten Kanton Zürich: GeoLion

label: geocat.ch permalink

state: active

type: dataset

media_type: WMS

de: Das Strassenenetz visualisiert nach Strassentypisierung Richtplan: Hochleistungsstrassen, Hauptverkehrsstrassen und Regionale Verbindungsstrassen und die wichtigsten geplanten Strassen.

format: WMS

name:
Tiefbauamt
               - Stab

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: WMS Strassennetz: Strassentypisierung nach Richtplan:


wms-zustandigkeiten-abteilung-wasserbau

title_for_slug: wms-zustandigkeiten-abteilung-wasserbau

de: Zuständigkeiten der Abteilung Wasserbau, Sektionen 'Gewässerunterhalt', 'Beratung und Bewilligung' (Wasserbauanliegen, Erstberatung und Baugesuche), Planung' (Gewässerraumfestlegung und raumplanerische Geschäfte) und 'Gewässernutzung' (Bewilligungen Stehgewässer).

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Wasserbau

de: WMS Zuständigkeiten Abteilung Wasserbau


gewasser-okomorphologie

title_for_slug: gewasser-okomorphologie

de: Mit dem Bau von Siedlungen und Verkehrswegen sowie der Intensivierung der Landwirtschaft wurde der Raum der Fliessgewässer in den vergangenen Jahrzehnten zunehmend eingeengt. Umfangreiche bauliche Massnahmen veränderten den natürlichen Lauf der Bäche, um Infrastruktur und landwirtschaftliche Kulturen vor Schäden durch Hochwasser zu schützen. Diese Verbauungen beeinträchtigen vielerorts die ökologische Funktionsfähigkeit der Gewässer. Damit ein Gewässer seine Funktion als Lebensraum erfüllen kann, braucht es nicht nur eine gute Wasserqualität, sondern auch naturnahe morphologische und hydrologische Bedingungen. Die flächendeckende Ersterhebung der Daten fand zwischen 1997 und 1999 statt. 2005 wurde eine Teilrevision von rund 500 km gemacht. Zwischen 2009 und 2012 wurde für rund 1500 km eine Neuerhebung im Feld durchgeführt. Für die übrigen rund 2200 km wurden die Daten der Ersterhebung auf das aktuelle Gewässernetz übertragen. Im Zuge der Umstellung des Gewässernetzes auf Daten der amtlichen Vermessung wurden 2014 auch die Ökomorphologiedaten auf die amtlichen Vermessungsdaten übertragen. Ab 2015 werden die Daten laufend nachgeführt. Im Jahr 2019 wurden zusätzlich zu den Fliessgewässern auch die Seeufer bzgl. der Ökomorphologie erhoben und beurteilt.

de: Gewässer-Ökomorphologie (OGD)


media_type: WCS

de: Klimaanalysekarten aus der Anwendung des Klimamodells FITNAH für das Gebiet des Kantons ZH. Rasterdaten mit 25m x 25m räumlicher Auflösung.

format: WCS

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Luft, Klima und Strahlung

de: WCS Klimamodell ZH: Analysekarten (Raster)


media_type: WFS

de: Dieser Datensatz enthält die durch die KaPo verfügten Tempo30- und Begegnungszonen im Kanton Zürich, ausgenommen die Städte Zürich und Winterthur. Die Karte sagt nichts darüber aus, wann und ob die Verkehrsanordnung umgesetzt wurde.

format: WFS

name:
Amt für Mobilität
               - Mobilitätsentwicklung und -steuerung

de: WFS Tempo30- und Begegnungszonen


wms-jagdreviere

title_for_slug: wms-jagdreviere

de: Jagdreviere Kanton Zürich.

name:
Amt für Landschaft und Natur
               - Fischerei- und Jagdverwaltung

de: WMS Jagdreviere


wms-offentliche-oberflachengewasser

title_for_slug: wms-offentliche-oberflachengewasser

de: Öffentliche Oberflächengewässer, Gewässerraum, Wasserrechte

de: WMS Öffentliche Oberflächengewässer


de: Web Map Service Strassenlärm-Emissionen zur Darstellung der Lärmquellen.

de: WMS Strassenlärm


de: WMS der Teilobjektperimeter Lichte Wälder gemäss Aktionsplan

name:
Amt für Landschaft und Natur
               - Fachstelle Naturschutz

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS der Objekte Lichte Wälder


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.

de: WMS Tempo30- und Begegnungszonen


de: Hinweiskarte für anthropogene Böden

name:
Amt für Landschaft und Natur
               - Fachstelle Bodenschutz

de: WMS Hinweiskarte für anthropogene Böden (OGD)


de: Waldareal im Kanton Zürich

name:
Amt für Landschaft und Natur
               - Abteilung Wald

de: WFS Waldareal


de: Gewässerschutzkarte

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Gewässerschutz

de: WFS Gewässerschutzkarte


wfs-klimamodell-zh-planhinweiskarten

title_for_slug: wfs-klimamodell-zh-planhinweiskarten

de: Die Planhinweiskarten (PHK) stellen die planerische Inwertsetzung der im Projekt erzeugten Modelldaten/Klimaanalysekarten dar. Sie sind die zentrale Basis für Entscheidungsprozesse rund um die klimagerechte räumliche Entwicklung.

de: WFS Klimamodell ZH: Planhinweiskarten


de: Gemeindegrenzen in Übersichtsplangenauigkeit. Es stehen drei Datensätze zur Verfügung: Gemeinden: Offizieller Verlauf der Gemeindegrenzen, d.h. die Grenze der Stadt Zürich verläuft durch den Zürichsee, die Grenzen der übrigen Zürichsee- und der Greifenseegemeinden verlaufen entlang der Seeufer. Gemeinde-, Bezirks- und Kantonsgrenzen: Anhand dieser Linienversion können für kartografische Zwecke Gemeinde-, Bezirks- und Kantonsgrenzen sowie Grenzen auf Seeflächen unterschieden werden. Gemeinden mit Berücksichtigung von Seen: In dieser Variante sind Zürich-, Greifen-, Pfäffiker-, Chatzen- und Türlersee voll ausgespart.

name:
Amt für Raumentwicklung
               - Geoinformation

de: WFS Gemeindegrenzen 1:5000


de: Höhendaten, abgeleitet von LiDAR-Daten (2017 Bund, 2014 ZH): Digitales Terrainmodell (DTM) Relief (Terrainschummerung/Hillshade) des Digitalen Terrainmodells (DTM Relief) Digitales Oberflächenmodell (DOM) Relief (Oberflächenschummerung/Hillshade) des Digitalen Oberflächenmodells (DOM Relief) Isohypsen 1m Isohypsen 5m Isohypsen 10m Für die aktuellste Version der genannten Layer bleibt der Layer-Name konstant: dom, dtm, dtm_relief, dom_relief, hoehenlinien1, hoehenlinien5, hoehenlinien10 Zusätzlich zur aktuellsten Version sind für DOM, DTM, DOM Relief und DTM Relief die älteren Versionen als Layer verfügbar. Im Moment ist die aktuellste Version aus dem Jahr 2017/2018 (Befliegung Bund), die ältere Version aus dem Jahr 2014 (Befliegung Kanton Zürich).

de: WMS Höhendaten, abgeleitet von LiDAR-Daten (OGD)


de: Naturgefahrenkarte - Wassertiefenkarten - Wassrtiefenflächen

de: WMS Naturgefahrenkarte - Wassertiefenflächen


de: Orthofoto 1981

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS Orthofoto 1981 (OGD)


de: Im WMS werden die Ausnahmetransportrouten des Kantons Zürich dargestellt. Es werden die Routen, die Werke und allfällige Einschränkungen dargestellt. Das TBA pflegt im Auftrag des AFV die Daten der kantonalen Ausnahmetransportrouten. Es wird zwischen Typ 1 und Typ 2 unterschieden. Kennzahlen Ausnahmetransportrouten Typ 1: - Lichte Höhe min. 5.20 m - Lichte Breite min. 7.50 m - Totalgew. max. 480 t - Achslast max. 30 t Kennzahlen Ausnahmetransportrouten Typ 2: - Lichte Höhe min. 4.80 m - Lichte Breite min 6.50 m - Totalgew. max. 240 t - Achslast max. 20 t Die Attribute der Ausnahmetransportrouten werden auf dem Datensatz des Strassennetzes gepflegt.

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.

de: WMS Ausnahmetransportrouten


de: Tagesaktuelle Baustellen auf dem Kantonsstrassennetz. Die vier Unterhaltregionen des Tiefbauamtes aktualisieren laufend die Informationen über bestehende und zukünftige Baustellen. Die Kommunikationsabteilung der Baudirektion des Kantons Zürich ist Ansprechpartner bei Fragen zu den Baustellen (http://www.bd.zh.ch/internet/baudirektion/de/service/nav/service/medien.html).

de: WMS Baustellen Kantonsstrassen


de: NO2-, PM10-, PM2.5- und Russ (BC)-Immissionen im Kanton Zürich für die Zeitstände 2015, 2020 und 2030. Es handelt sich dabei um Jahresmittelwerte in 20m x 20m räumlicher Auflösung.

de: WMS Immissionen (Luftqualität)


de: Entwicklung der mittleren Anzahl Anzahl Sommertage, Hitzetage, PET und Tropennächte pro Jahr für vier verschiedene Zeiträume.

de: WCS Klimamodell ZH: Szenarienkarten


de: Die Verkehrtechnische Abteilung der Kantonspolizei ist zuständig für die Verkehrsanordnungen im Kantonsgebiet (ohne Städte Zürich und Winterthur) und stellt die Verfügungen sämtlicher Strassensignalisationen/Markierungen aus. Diese Verfügungen bilden die Grundlage zur Nachführung der Höchstgeschwindigkeitssignale in der Strassendatenbank LOGO durch das TBA. Aus diesen Daten werden Abschnitte generiert. Halbjährlich werden die Daten ins SDE und in den GIS-Browser (inkl. WMS/WFS) exportiert. Die Datengrundlage ist das Geodatenelement GIS-ZH Nr. 54.3 (aus Geodatensatz GIS-ZH Nr. 54).

de: WMS Signalisierte Geschwindigkeit Kantonsstrassen


de: Wild-Karte oder Topographische Karte des Kantons Zürich 1:25000

de: WMS Historische Karte J. Wild (~1850)


de: Die archäologischen Zonenpläne stellen einen Verdachtsflächen-Kataster dar.

name:
Amt für Raumentwicklung
               - Kantonsarchäologie

de: WMS Archäologische Zonen


de: Dieser WFS beinhaltet die Streckenaufteilung auf Kantonsstrassen nach den Innerorts- und Ausserortsbereichen. Diese sind durch die Signale Ortsein- und Ortsausfahrt (Sig. 4.28 bis 4.30) definiert. Die zugrundeliegende Geometrie bildet der Geodatensatz Strassennetz Kanton Zürich GDS 102. Publiziert wird ein Auszug aus den Attributen des Geodatenelementes 54.4.

de: Geoinformation Kanton Zürich

de: WFS Inner-/Ausserorts auf Kantonsstrasse


de: Fischereireviere

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.

de: WMS Fischereireviere (OGD)


wms-abflussprozesskarte-ogd

title_for_slug: wms-abflussprozesskarte-ogd

de: Die Abflussprozesskarte zeigt die Flächen der dominanten Abflussprozesse, hortonscher Oberflächenabfluss, Sättigungsoberflächenabfluss, laterale unterirdische Entwässerung, Drainagen und Tiefenversickerung. In einem zweiten Layer sind Flächen dargestellt, die bei intensiven Starkniederschlägen zu schnellem Oberflächenabfluss neigen (potentielle HOF-Flächen).

de: WMS Abflussprozesskarte (OGD)


de: Die Haltestellen des öffentlichen Verkehrs wurden im Laufe des Jahres 1997 in Zusammenarbeit mit dem ZVV, dem Tiefbauamt, den regionalen Verkehrsbetrieben, der Post und dem GIS-Zentrum erfasst. Die laufende Aktualisierung geschieht durch die VBZ.

de: WFS Haltestellen des öffentlichen Verkehrs


de: WMS Orthofotos Kanton Zürich in Echtfarben und als Falschfarbeninfrarot

de: WMS Orthofotos


wms-seebautenkataster

title_for_slug: wms-seebautenkataster

de: Seebautenkataster

de: WMS Seebautenkataster


wfs-naturgefahrenkarte

title_for_slug: wfs-naturgefahrenkarte

de: WFS Naturgefahrenkarte


de: Wild-Karte oder Topographische Karte des Kantons Zürich 1:25000.

de: WMS Historische Karte J. Wild (~1850) (OGD)


de: Mit dem Bau von Siedlungen und Verkehrswegen sowie der Intensivierung der Landwirtschaft wurde der Raum der Fliessgewässer in den vergangenen Jahrzehnten zunehmend eingeengt. Umfangreiche bauliche Massnahmen veränderten den natürlichen Lauf der Bäche, um Infrastruktur und landwirtschaftliche Kulturen vor Schäden durch Hochwasser zu schützen. Diese Verbauungen beeinträchtigen vielerorts die ökologische Funktionsfähigkeit der Gewässer. Damit ein Gewässer seine Funktion als Lebensraum erfüllen kann, braucht es nicht nur eine gute Wasserqualität, sondern auch naturnahe morphologische und hydrologische Bedingungen. Die flächendeckende Ersterhebung der Daten fand zwischen 1997 und 1999 statt. 2005 wurde eine Teilrevision von rund 500 km gemacht. Zwischen 2009 und 2012 wurde für rund 1500 km eine Neuerhebung im Feld durchgeführt. Für die übrigen rund 2200 km wurden die Daten der Ersterhebung auf das aktuelle Gewässernetz übertragen. Im Zuge der Umstellung des Gewässernetzes auf Daten der amtlichen Vermessung wurden 2014 auch die Ökomorphologiedaten auf die amtlichen Vermessungsdaten übertragen. Ab 2015 werden die Daten laufend nachgeführt.

de: WFS Gewässer-Ökomorphologie


name:
Amt für Raumentwicklung
               - Kantonale Denkmalpflege

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS Archäologische Zonen und Denkmalschutzobjekte (OGD)


de: Gewässerschutzkarte

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.

de: WMS Gewässerschutzkarte


de: Entwicklung der mittleren Anzahl Anzahl Sommertage, Hitzetage, PET und Tropennächte pro Jahr für vier verschiedene Zeiträume.

de: WMS Klimamodell ZH: Szenarienkarten


wms-energieplan

title_for_slug: wms-energieplan

de: Der Energieplan des Kantons Zürich beruht auf den nachstehend aufgeführten und einzeln dokumentierten Daten, die das GIS-Zentrum in Zusammenarbeit mit der Abteilung Energie des AWEL erarbeitet, erfasst und kartiert hat. Aufgrund der Fülle von Informationen auf kleinem Raum mit gegenseitiger Überdeckung muss bei der Gesamtdarstellung auf die geeignete Reihenfolge geachtet werden (Punkte über Linien, Linien über Flächen sowie kleinere über grösseren Elementen).

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Energie

de: WMS Energieplan


de: WMS Landwirtschaftliche Nutzungseignungskarte (OGD)


de: WMS Öffentliche Oberflächengewässer, Gewässerraum und Wasserrechte (OGD)


de: Waldentwicklungsplan Kanton Zürich: Waldfunktionen

de: WMS Waldentwicklungsplan: Waldfunktionen (OGD)


de: Der WCS Vegetationshöhe beschreibt die Höhe der Vegetation (Bäume, Büsche, etc.) im Kanton Zürich. Symbology: Stretched, 3-50, Color Ramp, Apply Gamma Stretch 3-50

de: WCS Vegetationshöhe


wfs-grundwasserkarte-mittelwasserstand

title_for_slug: wfs-grundwasserkarte-mittelwasserstand

de: Grundwasserkarte Mittelwasserstand

de: WFS Grundwasserkarte Mittelwasserstand


de: Web Coverage Service (WCS) Modellierte Potenziale für naturnahe Lebensräume

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WCS Modellierte Potenziale für naturnahe Lebensräume (OGD)


wms-klimamodell-zh-analysekarten-vektor

title_for_slug: wms-klimamodell-zh-analysekarten-vektor

de: Klimaanalysekarten aus der Anwendung des Klimamodells FITNAH für das Gebiet des Kantons ZH. Punktdaten des Windfeldes (Windrichtung und -geschwindigkeit) über den ganzen Kanton. Räumliche Genauigkeit: 25m.

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.

de: WMS Klimamodell ZH: Analysekarten (Vektor)


de: Der Kanton Zürich hat 2011 die öffentlich zugänglichen Veloparkieranlagen im Kanton Zürich ohne Einbezug der Stadt Zürich erhoben. Dazu gehören Anlagen mit mindestens 5 Veloplätzen (ersichtlich durch Markierungen, Signalisationstafeln oder Überdachung) oder wildes Parkieren (im Minimum 10 Velos). Folgende Gebiete wurden ausgeschlossen: reine Wohngebiete gemäss Zonenplan, Weiler mit weniger als 30 Gebäuden, abgelegene sowie private Sportstätten, Strassen mit allg. Fahrverbot, Naturstrassen und als solche bezeichnete Privatstrassen. Velostationen wurden nicht erfasst. Diese sind in der "Koordination Velostation Schweiz" (www.velostationen.ch) zusammengeschlossen.

de: WFS Veloparkieranlagen


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

spatial: Kanton Zürich

de: Download via GIS-Browser

de: Der Seebautenkataster ist ein Übersichtsplan der zürcherischen Seen. Er enthält die Bauten und Anlagen der gültigen Konzessionen und Bewilligungen wie auch die Dimensionen der konzedierten Landanlagen. Zusätzlich werden Flächen dargestellt, bei denen feststeht oder mit grosser Wahrscheinlichkeit angenommen werden darf, dass darauf öffentlich-rechtliche Eigentumsbeschränkungen bestehen.

name:
Amt für Abfall, Wasser, Energie und Luft
             - Abteilung Wasserbau

de: Seebautenkataster


de: Mit der Festlegung des Gewässerraums an den oberirdischen Gewässern soll der Raum gesichert werden, welcher nötig ist zur Gewährleistung der natürlichen Funktionen der Gewässer, des Hochwasserschutzes und der Gewässernutzung. Die Gewässerschutzverordnung des Bundes (GSchV) legt dazu konkrete Masse fest, wie gross der Gewässerraum mindestens sein muss (Art. 41a und 41b GSchV). Der Gewässerraum muss dort erhöht werden, wo dies zur Gewährleistung für den Hochwasserschutz, der Revitalisierung, sowie bei überwiegenden Interessen des Natur- und Landschaftsschutzes und der Gewässernutzung erforderlich ist. Im Gewässerraum dürfen nur standortgebundene, im öffentlichen Interesse liegende Bauten und Anlagen erstellt werden. In dicht überbauten Gebieten kann der Gewässerraum den baulichen Gegebenheiten angepasst werden, soweit der Schutz vor Hochwasser gewährleistet ist, bzw. kann die Behörde für zonenkonforme Bauten und Anlagen Ausnahmen bewilligen, sofern keine überwiegenden Interessen entgegenstehen. Rechtmässig erstellte und bestimmungsgemäss nutzbare Bauten und Anlagen im Gewässerraum sind in ihrem Bestand grundsätzlich geschützt. Der Gewässerraum darf nur extensiv gestaltet und bewirtschaftet werden (Art. 41 c GschV) Solange der Gewässerraum nicht festgelegt ist, regeln die Übergangsbestimmungen der GSchV direkt und grundeigentümerverbindlich die Bemessung der von Bauten und Anlagen freizuhaltenden Uferstreifen. Der Gewässerabstand von 5 Meter gemäss § 21 des kantonalen Wasserwirtschaftsgesetzes (WWG), behält bis zu einer allfälligen Anpassung des WWG auch mit der Festlegung des Gewässerraums weiterhin Gültigkeit. Nach der Ersterfassung werden die Daten in den ÖREB-Kataster überführt.

de: Gewässerraum


de: Revitalisierungsplanung, Haupteinzugsgebiete, Seebautenkataster, Gewässerraum, Wasserrechte, Seen, öffentliche Oberflächengewässer

de: WFS Wasserbauthemen


maintainer: EnviDat Support

en: snow-density snow-water-equivalent snow-ice-temperature weisfluhjoch snow-stratigraphy

en: README

media_type: TXT

en: README file giving use metadata.

format: TXT

en: WFJ Snow Profiles 1999-2014

media_type: application/zip

en:
Biweekly manual snow profiles from Weissfluhjoch, Davos, Switzerland.
Version: 2015-09-14T16:25

format: ZIP

mimetype: application/zip

en: Dataset of manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland. Typical snow profile measurements and observations are included (temperature, density, grain size, grain type, hardness, wetness), following the guidelines of the The International Classification for Seasonal Snow on the Ground (ICSSG) [Fierz, C., Armstrong, R.L., Durand, Y., Etchevers, P., Greene, E., McClung, D.M., Nishimura, K., Satyawali, P.K. and Sokratov, S.A. 2009. The International Classification for Seasonal Snow on the Ground. IHP-VII Technical Documents in Hydrology N°83, IACS Contribution N°1, UNESCO-IHP, Paris].

snow-density

display_name: snow-density

snow-ice-temperature

display_name: snow-ice-temperature

snow-stratigraphy

display_name: snow-stratigraphy

snow-water-equivalent

display_name: snow-water-equivalent

weisfluhjoch

display_name: weisfluhjoch

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

key: guid

key: uri

value: Envidat Harvester

en: Manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland


en: forest-management soil-impacts pairwise-stand-comparisons biodiversity biogeography

en: headers

media_type: ascii, tab separated, also as excel table

en: Description of headers for data_wohlgemuth_etal_Neobiota_2022

format: SERVICE

en: references

media_type: XLS

en: Bibliography of all references cited in data_wohlgemuth_etal_Neobiota_2022.

format: XLS

media_type: CSV

en: Baseline data

format: CSV

en: Compiled data on the impacts of seven important NNTs (Acacia dealbata, Ailanthus altissima, Eucalyptus globulus, Prunus serotina, Pseudotsuga menziesii, Quercus rubra, Robinia pseudoacacia) on physical and chemical soil and biodiversity in Europe, and summarise commonalities and differences. A total of 107 publications considered, studies referred to biodiversity attributes and soil properties: 2804 lines and 30 rows.

biodiversity

display_name: biodiversity

biogeography

display_name: biogeography

forest-management

display_name: forest-management

pairwise-stand-comparisons

display_name: pairwise-stand-comparisons

soil-impacts

display_name: soil-impacts

en: Impact of non-native tree species in Europe on soil properties and biodiversity: a review


maintainer: Marcia Phillips

en: permos borehole permafrost ritigraben meteo-station

en: DATA ACCESS

media_type: SMET

en: Meterological station at the [Ritigraben permafrost borehole](http://www.envidat.ch/dataset/rit1) (RIT_0102) in canton Valais, Switzerland. The station is located at 2690 m asl on a flat site.

borehole

display_name: borehole

meteo-station

display_name: meteo-station

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

en: RIT2: Meteorological station at Ritigraben borehole site


mimetype: text/csv

en:
This dataset contains the statistics on the number of avalanche fatalities per **calendar year** in Switzerland. The data collection commences with the beginning of the year 1937. After the completion of a hydrological year, which is the standard way avalanche fatalities are summarized in Switzerland and ends on the 30th of September, the new data is appended to the existing dataset.
If you require annual statistics per hydrological year, please download the data from here: [https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936]

The following information is contained (by column and column title):
 - year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste, away from open and secured ski runs)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)

The definitions for these four categories, as described in the guidelines to the avalanche accident database are:

tour:
activities include back-country ski, snowboard or snow-shoe touring

offpiste:
access from ski area, generally from the top of a skilift with short hiking distances

transportation.corridors (Techel et al., 2016):
people travelling or recreating on open or temporarily closed transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)

buildings (Techel et al., 2016):
people inside or just outside buildings, and workers on high alpine building sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

en: Number of avalanche fatalities per calendar year in Switzerland since 1937


en: avalanche danger-level avalanche-danger avalanche-forecasting snow snow-instability

en: Read-me file

media_type: PDF

en: This read-me file contains the descriptions of the variables.

format: PDF

en: Field observations of snow instabilities

en:
This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019.

These data were analyzed and results published by Schweizer et al. (2021). They characterized the avalanche danger levels based on signs of instability (whumpfs, shooting cracks, recent avalanches), snow stability class and new snow height.

The data are provided in a csv file (589 records); the variables are described in the corresponding read-me file.

These data are the basis of the following publication: Schweizer, J., Mitterer, C., Reuter, B., and Techel, F.: Avalanche danger level characteristics from field observations of snow instability, Cryosphere, 15, in review, 2021.

 Acknowlegements
Many of the data were recorded by SLF observers and staff members, among those Roland Meister, Stephan Harvey, Lukas Dürr, Marcia Phillips, Christine Pielmeier and Thomas Stucki. Their contribution is gratefully acknowledged.

avalanche

display_name: avalanche

avalanche-danger

display_name: avalanche-danger

avalanche-forecasting

display_name: avalanche-forecasting

danger-level

display_name: danger-level

snow

display_name: snow

snow-instability

display_name: snow-instability

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal


en: bioenergy switzerland review biogas manure

en: Production de biogaz à partir d’engrais de ferme en Suisse

en: L'objectif de ce livre blanc est de fournir aux décideurs, aux administrations et aux parties prenantes les résultats de recherche les plus récents afin de promouvoir l'utilisation optimale de la bioénergie issue des engrais de ferme dans la transition énergétique suisse. A cette fin, les résultats du centre de compétence suisse pour la recherche en bioénergie - SCCER BIOSWEET - sont résumés et présentés dans un contexte plus large. Si rien d'autre n'est mentionné, les résultats se réfèrent à la Suisse et, dans le cas de la matière première, aux potentiels nationaux de biomasse.

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland

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.


disdrometer-data-gotschnagrat

title_for_slug: disdrometer-data-gotschnagrat

en: hydrometeors disdrometer raclets precipitation visibility

en: Disdrometer Data Gotschnagrat

en: The zip folder contains one netCDF file per day for Gotschnagrat from February 11 to March 27 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Gotschna_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

en: A laser optical disdrometer (Parsivel² , OTT Hydromet) was deployed at Gotschnagrat (LON: 9.849, LAT: 46.859) to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms. The dataset contains information on precipitation amount and type for the period of February 11 to March 27 2019 at Gotschnagrat.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility


en: buffer geospatial roads gis jupyter density

en: Road Density Calculation (Python Notebook) online

media_type: url

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

en: Plots

en: Random plot locations

media_type: ipynb

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

buffer

display_name: buffer

density

display_name: density

geospatial

display_name: geospatial

gis

display_name: gis

jupyter

display_name: jupyter

roads

display_name: roads

en: Dataset for OGRS 2018 publication


en: alptal first-order-catchment meteorological-data runoff snow subalpine

en: Daily meteorological and snow data (1968-2019) Alptal

media_type: XLSX

en:
Air temperature, dew point temperature, relative humidity, wind speed, precipitation and global radiation have been measured (since 1981) on a meadow (Erlenhöhe) in the Erlenbach catchment. It is located at 1'220 m a.s.l. with an exposure towards west. In order to assess the spatial variability of precipiation, two additional rain gauges have been running in the Vogelbach and Lümpenenbach catchment, respectively.
For the period before 1981, meteorological variables have been extrapolated from the nearby MeteoSwiss station Einsiedeln (ca. 15 km north) to the WSL station Erlenhöhe using a linear correction factor for air temperature, wind speed and precipitation.
Snow depth has been recorded automatically since 2003.

en: Manual snow measurements Alptal (1968-2020)

en:
Snow depth, snow density and snow water equivalent have been measured since winter 1968/69 along more than 15 transects distributed across the Alptal valley representing different altitudes, aspects and land use (closed forest and open meadows). Length of the snow courses: 20 to 30 m. The measurement interval has been weekly to monthly.
More details about the locations and methods can be found in Stähli, M.; Gustafsson, D., (2006). Long-term investigations of the snow cover in a subalpine semi-forested catchment. Hydrological Processes, 20, 411-428. doi: 10.1002/hyp.6058.

en: Daily runoff data from three steep torrents in the Alptal (1968-2019)

en: Runoff, water temperature and electrical conductivity have been measured since 1968 at the outlet of three torrential catchments (with an area of approximately 1 km2 each) located in the Alptal valley: Erlenbach, Lümpenenbach and Vogelbach. This data set provides daily mean values; data at 10-min resolution can be provided on request for the period 1984-2020 (contact: alptal@wsl.ch).

en:
This data set includes 52 years of hydrometeorological measurements from small (first-order) catchments in the pre-alpine valley Alptal. Here we provide daily mean values; values in sub-daily resolution can be provided on demand.
Runoff has been measured at the outlet of three small (first-order) catchments of approximately 1 km2 area: Erlenbach (two independent runoff measurements), Vogelbach and Lümpenenbach. The catchments are similar with regard to geology (Flysch) and soil conditions (clay soils), but differ in forest coverage (20 to 60%). A detailed description of the catchments can be found at https://www.wsl.ch/alptal .
Runoff in these small catchments is typically very dynamic and can temporally carry large amounts of sediment and large wood. Thus, the accuracy of the measurements at very large flow is limited.
Meteorological variables have been measured on a meadow (Erlenhöhe) located in the Erlenbach catchment at 1220 m a.s.l. using a standard meteorological station (incl. ventilated air temperature and heated rain gauges). In addition, precipitation has also been recorded at two other locations (in the Vogelbach and Lümpenenbach catchments).
Snow measurements have been conducted weekly to monthly since 1968 at more than 15 locations (30-m transects) representing different altitudes, aspects and land uses (meadow, forest). In addition, snow depth has been recorded continuously since 2003 at Erlenhöhe, and for this location we also include a simulation of snow depth and SWE (using the numerical model COUP) that assimilates the manual weekly snow-course measurements. Details on these snow measurements can be found in Stähli, M. and Gustafsson, D. 2006. Hydrol. Proc., 20, 411-428. doi: 10.1002/hyp.6058.

Further information on the methods and sensors can be found at https://www.wsl.ch/alptal .

A first version of this data set (for the period 1968-2017) was uploaded in June 2018 at the occasion of the 50-year anniversary. This original data set was updated in February 2021 (with data from 2018 and 2019), and this data set was used for a longterm trend analysis, submitted for publication in a special issue of Hydrological Processes.

alptal

display_name: alptal

first-order-catchment

display_name: first-order-catchment

meteorological-data

display_name: meteorological-data

runoff

display_name: runoff

snow

display_name: snow

subalpine

display_name: subalpine

education

en: Education and science

en: Longterm hydrological observatory Alptal (central Switzerland)


vegetation-height-model-nfi

maintainer: Christian Ginzler

title_for_slug: vegetation-height-model-nfi

en: point-cloud photogrammety vegetation-height-model 3d forest

en: 2012 Vegetation Height Model NFI

media_type: geotiff

en:
Data 'Vegetation Height Model NFI 2012' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2007 to 2012.

format: GeoTIFF

en: 2015 Vegetation Height Model NFI

en:
Data 'Vegetation Height Model NFI 2015' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2010 to 2015.

en: 2016 Vegetation Height Model NFI

en:
Data 'Vegetation Height Model NFI 2016' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2011 to 2016.

en: Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory

en: Thumbnail

media_type: image/jpeg

mimetype: image/jpeg

en: 2019 Vegetation Height Model NFI (current)

en:
Data 'Vegetation Height Model NFI 2019' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2013 to 2019.

en:
A national vegetation height model was calculated for Switzerland using digital aerial images.
We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution
(1 × 1 m and 0.5 x 0.5 m). The DSM was then normalized to obtain the actual
vegetation heights using a digital terrain model (DTM)
based on laser data with the buildings masked out, and to
produce a vegetation height model (VHM). Such a model
will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very
high level of detail. For covering the whole of Switzerland,
we use summer aerial images from six years.

Latest version is from 2019.

forest

display_name: forest

photogrammety

display_name: photogrammety

point-cloud

display_name: point-cloud

vegetation-height-model

display_name: vegetation-height-model

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: Vegetation Height Model NFI


en: water-temperature model hydrology discharge climate-change-impact

en: Data access

media_type: .zip

en:
This work presents the first extensive study of climate change impacts on rivers temperature in Switzerland. Results show that even for low emissions scenarios, water temperature increase will lead to adverse effect for both ecosystems and socioeconomic sectors (such as nuclear plant cooling) throughout the 21st century. For high emissions scenarios, the effect will be worsen. This study also shows that water warming in summer will be more important in Alpine regions than in lowlands.
This material is distributed under CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/legalcode).

climate-change-impact

display_name: climate-change-impact

discharge

display_name: discharge

hydrology

display_name: hydrology

model

display_name: model

water-temperature

display_name: water-temperature

education

en: Education and science

en: Dataset for: Future water temperature of rivers in Switzerland under climate change investigated with physics-based models


en: maximum-temperature precipitation timeseries climate-layers minimum-temperature climate air-temperature free-climate-data century

en: Data Access

en: CHELSA Technical Documentation

media_type: application/pdf

en: As the CHELSA project is continuously expanded, certain new parameters, time scales etc. are not included anymore in the original publication (Karger et al. 2017). We are therefore provide this document as a guideline of the current climatic parameters available and will expand it as new parameters or time periods will become available. Please refer to the version history for changes made in the document.

mimetype: application/pdf

en:
CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum. Here we use the delta change method by B-spline interpolation of anomalies (deltas) of the CRU TS 4.01 dataset. Anomalies were interpolated between all CRU TS grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2 (Karger et al. 2017, Scientific Data). This method has the assumption that climate only varies on the scale of the coarser (CRU TS) dataset, and the spatial pattern (from CHELSA) is consistent over time. This is certainly a rather crude assumption, and for time periods for which more accurate data is available CHELSAcruts should be avoided if possible (e.g. use CHELSA V1.2 for 1979-2015). Different to CHELSA V1.2, CHELSAcruts does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages.

CHELSAcruts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

century

display_name: century

climate

display_name: climate

climate-layers

display_name: climate-layers

free-climate-data

display_name: free-climate-data

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation

timeseries

display_name: timeseries

en: CHELSAcruts -  High resolution temperature and precipitation timeseries for the 20th century and beyond


en: snow-temperature ice-layers water-front weissfluhjoch snowmicropen snow-stratigraphy

en: README

media_type: text/plain

mimetype: text/plain

en: WFJ_ICE_LAYERS dataset

en: The WFJ_ICE_LAYERS dataset contains multi-instrument snowpack measurements at high temporal resolution, which enable to monitor the formation of deep ice layers due to preferential water flow, at the Weissfluhjoch research site, Davos, Switzerland. It covers the winter 2016/2017, with a focus on the early melting season. This dataset includes traditional snowpack profiles (weekly resolution, 15/11/2016-29/05/2017), SnowMicroPen penetration resistance profiles (daily resolution, 01/02/2017-19/04/2017), snow temperatures measured at different heights in the snowpack (half-hourly resolution, 01/03/2017-15/04/2017) and the water front height derived from an upward-looking ground penetrating radar (3-hour resolution, 04/03/2017-08/04/2017). The measurements are complemented by initialization files for SNOWPACK model simulations with the ice reservoir parameterization at Weissfluhjoch for the winter 2016/2017.

ice-layers

display_name: ice-layers

snow-stratigraphy

display_name: snow-stratigraphy

snow-temperature

display_name: snow-temperature

snowmicropen

display_name: snowmicropen

water-front

display_name: water-front

weissfluhjoch

display_name: weissfluhjoch

en: WFJ_ICE_LAYERS: Multi-instrument data for monitoring deep ice layer formation in an alpine snowpack


ceilometer-klosters

title_for_slug: ceilometer-klosters

en: cloud-base-height klosters raclets ceilometer vertical-visibility

en: Ceilometer data Klosters

media_type: mat

en: Ceilometer installed at Klosters measuring cloud base height, cloud cover and backscatter profile. The time resolution is 30 seconds, with time given in number of days from January 0, 0000, UTC. More information on the variables in the manufacturer manual.

en: Cloud base height (m) and vertical visibility (m) were measured with the VAISALA Ceilometer CL31 in Klosters (LON: 9.880413, LAT: 46.869019). The CL31 is an instrument with constant reliability for all weather conditions and simultaneous detection of three cloud layers in heights up to 7.6 km.

ceilometer

display_name: ceilometer

cloud-base-height

display_name: cloud-base-height

klosters

display_name: klosters

raclets

display_name: raclets

vertical-visibility

display_name: vertical-visibility

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: Ceilometer Klosters


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

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: 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: 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: 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 version 2 (corrected version)

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

en: Hydro-CH2018 reservoirs


en: stillberg davos treeline-ecosystems mountain-forest afforestation foresty

en: Documentation

media_type: application/msword

mimetype: application/msword

en: Site photo

media_type: JPEG

en: Dataset V1

media_type: GDB

en: This dataset has been depricated in favour of an updated version.

format: GDB

en:
#Background Information

A history of many centuries of seasonal livestock grazing of alpine pastures has significantly depressed the treeline in many European mountain ranges. Therefore, observations of treeline patterns are more likely to be obscured by historical land use than in regions with less human influence and might not provide relevant information about environmental factors that influence mortality and growth patterns at the natural high-elevation limit of tree existence. To overcome this, we used a large afforestation experiment in the Swiss Alps, "Stillberg", to address the following questions:

Can trees survive above the current treeline in the European Alps? Are environmental factors that influence spatial patterns of mortality the same as those that influence height growth? Does the relative importance of these environmental variables change over the first 40 years after planting as seedlings?

#Dataset
The 5 ha Stillberg long-term afforestation research area is located near Davos (Central Alps, Switzerland). The bottom of the afforestation is approximately at the current treeline and it covers an altitudinal gradient of more than 150 m (2075 to 2230 m a.s.l.; see picture above). Approximately 92'000 seedlings of three treeline species (Larix decidua, Pinus mugo ssp. uncinata and Pinus cembra) were systematically planted in 1975, and mortality and height growth were closely monitored during the following 40 years.

Publications
Barbeito, I., Dawes, M. A., Rixen, C., Senn, J. and Bebi, P. (2012), Factors driving mortality and growth at treeline: a 30-year experiment of 92 000 conifers. Ecology, 93: 389–401. http://dx.doi.org/10.1890/11-0384.1

afforestation

display_name: afforestation

davos

display_name: davos

foresty

display_name: foresty

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline-ecosystems

display_name: treeline-ecosystems

en: Long-term treeline research dataset at Stillberg, Davos


en: rain-on-snow uncertainty snow-water-equivalent climate-change-impact cryosphere natural-climate-variability

en: climate realizations

en: The dataset contains for three variables (snow water equivalent, surface water input and liquid precipitation) 50 realizations of current and future climate periods for two time horizons (mid end end of century), two emission senarions (RCP 4.5 and 8.5) and 10 climate model chains (all EUR11 chains within CH2018). To quantify natural climate variability for projections of snow conditions and resulting rain-on-snow (ROS) flood events, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12 x 12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The data was extracted in 2021 from original model output.

climate-change-impact

display_name: climate-change-impact

cryosphere

display_name: cryosphere

natural-climate-variability

display_name: natural-climate-variability

rain-on-snow

display_name: rain-on-snow

snow-water-equivalent

display_name: snow-water-equivalent

uncertainty

display_name: uncertainty

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: Multiple realizations of daily snow water equivalent, surface water input and liquid precipitation projections for mid- and late-century


aerosol-data-weissfluhjoch

title_for_slug: aerosol-data-weissfluhjoch

en: inp aerosol linda ice-nucleation raclets particles

en: SMPS Dataset Weissfluhjoch

media_type: application/x-netcdf

en: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity) in a temporal resolution of 2 minutes, with time in UTC, measured at Weissfluhjoch.

mimetype: application/x-netcdf

en: OPC-GT526S Dataset Weissfluhjoch

media_type: text/csv

en: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

en: LINDA Dataset Weissfluhjoch

en: The LINDA file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

en: OPC-N3 Dataset Weissfluhjoch

en: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

en: APS Dataset Weissfluhjoch

en: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Weissfluhjoch.

en:
Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.

Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0).

Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³).

Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³).

Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

aerosol

display_name: aerosol

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

linda

display_name: linda

particles

display_name: particles

raclets

display_name: raclets

en: Aerosol Data Weissfluhjoch


root-traits

maintainer: Ivano Brunner

title_for_slug: root-traits

en: soil-coring belowground-biomass fine-root-traits ingrowth-cores drought

en: Root-traits

media_type: application/zip

en:
Fine-root traits of Scots pine in response to enhanced soil water availability deriving from long-term irrigation in the Pfynwald

Data_Fig.1.xlsx
Fine-root biomass of the topsoil (0-10 cm) in the dry and irrigated treatment of the Scots pine forest of the years 2003 to 2016 recorded by soil coring

Data_Tab1+2_2005.xlsx
Fine-root traits from roots of ingrowth cores from 2005 after two years of growth in the dry and irrigated treatment of the Scots pine forest

Data_Tab1+2_2016.xlsx
Fine-root traits from roots of ingrowth cores from 2016 after two years of growth, and from roots of the soil-coring sampling from 2016 in the dry and irrigated treatment of the Scots pine forest

belowground-biomass

display_name: belowground-biomass

drought

display_name: drought

fine-root-traits

display_name: fine-root-traits

ingrowth-cores

display_name: ingrowth-cores

soil-coring

display_name: soil-coring

education

en: Education and science


maintainer: Matthias Haeni

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

en: Site photo of the forest station (VSB)

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

en: Site aerial photo (Visp)

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

en: Data plot of the field station (VSF)

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

en: Forest station data (VSB)

en: Data file.

en: Field station data (VSF)

en: Site photo of the field station (VSF)

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

en: Data plot of the forest station (VSB)

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 Visp in Switzerland where one station is located within a natural mixed forest stand (VSB) with Scots pine (_Pinus sylvestris_; 40-80 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, VSF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Visp 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

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


en: co2 soil picea-abies forest face nitrogen

en: Gross N mineralisation and nitrification

en: Gross rates of N mineralisation and nitrification (15N dilution)

en: Collection of soil solution

en: Soil solution collected by suction cups

en: Collection points

en: Collection points under the trees

en: Soil C and N

en: Analyses of C, N and their stable isotopes in the soil, and soil pH

en: Water analyses

en: Analyses of water, especially soil solution

en: Resin bags

en: Ammonium, nitrate and their 15N in resin bags

en: Data obtained in the free-air CO2 enrichment (FACE) experiment at Hofstetten, NW Switzerland, between 2009 and 2016. This dataset contains analyses of the soil solution throughout the experiment, especially for nitrate, as well as different analyses done at the end of the experiment: ammonium and nitrate captured by ion-exchange resin bags and extracted from soil cores, gross N mineralisation and nitrification measured by isotope dilution.

face

display_name: face

forest

display_name: forest

nitrogen

display_name: nitrogen

picea-abies

display_name: picea-abies

soil

display_name: soil

education

en: Education and science

en: Nitrogen availability under trees exposed to CO2 enrichment (FACE)


maintainer: Anita C. Risch

en: soil soil-chemistry global nutrient-network mineralization soil-biology grassland worldwide

en:
site.code: Site code

Continent: Continent

sampleID: Sample ID

nn.latitude: Lattitude

nn.longitude: Longitude

bioclim.T.ann: Mean annual temperature (°C)

bioclim.T.var: Temperature variability (°C)

bioclim.T.q.wet: Temperature of the wettest quarter (°C)

bioclim.T.q.dry: Temperature of the driest quarter (°C)

bioclim.T.q.warm: Temperature of the warmest quarter (°C)

bioclim.P.ann: Mean annual preciptiation (mm)

bioclim.P.q.wet: Precipitation of the wettest quarter (mm)

ch.pH: pH

ch.WSK.vol: Water holding capacity (vol%)

ch.bulkdensity.gcm3: Bulk density (g cm-3)

ch.porespace: Pore space (vol%)

ch.sand.perc: Soil texture: sand (%)

ch.silt.perc: Soil texture: silt (%)

ch.clay.perc: Soil texture: clay (%)

ch.NO3start.mgg: NO3 at the beginning of the incubation (mgkg)

ch.Ntot.perc: Total soil N (%)

ch.Ctot.perc: Total soil C (%)

ch.Corg.perc: Soil organic C (%)

ch.netNminfield.mgkgd: Realised soil net N mineralisation (mg kg-1 d-1)

ch.netNminlab.mgkgd: Potential soil ne N mineralisation (mg kg-1 d-1)

archaea.cpg.log: Ammonia oxidising archaea (archaeal amoA gene copies g-1 soil)

bacteria.cpg.log: Ammonia oxidising bacteria (bacterial amoA gene copies g-1 soil)

micr.biom: Microbial biomass (ug g-1 soil)

ch.CtoN: C to N ratio

ch.netNnitriffield.mgkgd.sqrt: Realised soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniffield.mgkgd.sqrt: Realised soil net ammonification, transformed (mg kg-1 d-1)

ch.netNnitriflab.mgkgd.sqrt: Potential soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniflab.mgkgd.sqrt: Potential soil net ammonifiation, transformed (mg kg-1 d-1)

en:
This dataset contains all data on which the following publication below is based.

Paper Citation:

Risch, A. C.; Zimmermann, S.; Ochoa-Hueso, R.; Schütz, M.; Frey, B.; Firn, J. L.; Fay, P. A.; Hagedorn, F.; Borer, E. T.; Seabloom, E. W.; et al. Soil net nitrogen mineralisation across global grasslands. Nat. Commun. 2019, 10 (1), 4981 (10 pp.). doi.org/10.1038/s41467-019-12948-2

Please cite this paper together with the citation for the datafile.

We conducted coordinated measurements of realised and potential soil net Nmin, and assessed water holding capacity, bulk density, C and N content, texture, pH, pore space, microbial biomass, and archaeal (AOA) and bacterial (AOB) ammonia oxidiser abundance using identical materials and methods across 30 grasslands on six continents. The sites covered a globally relevant range of climatic and edaphic conditions. Climate data was obtained from worldclim - Global climate data https://www.worldclim.org/

global

display_name: global

grassland

display_name: grassland

mineralization

display_name: mineralization

nutrient-network

display_name: nutrient-network

soil-biology

display_name: soil-biology

soil-chemistry

display_name: soil-chemistry

worldwide

display_name: worldwide

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: incoming davos shortwave-radiation longwave-radiation outgoing

en: Parameter file

en: Metadata

en: DATA ACCESS

media_type: SMET

en: Processing doc

en:
Incoming and outgoing shortwave and longwave 2 min radiation measurements in Davos Dorf, CH.

 References
1. Marty, C., Philipona, R., Frohlich, C., Ohmura, A.. Altitude dependence of surface radiation fluxes and cloud forcing in the alps: results from the alpine surface radiation budget network. 2002. Theoretical and Applied Climatology. Volume 72. Issue 3-4. 137-155. http://dx.doi.org/10.1007/s007040200019. 10.1007/s007040200019.
2. Christoph Marty. Surface Radiation, Cloud Forcing and Greenhouse Effect in the Alps. 2000. Institute fuer Klimaforschung ETH. Zuercher Klima-Schriften. Volume 79. http://e-collection.library.ethz.ch/eserv/eth:23491/eth-23491-01.pdf.

davos

display_name: davos

incoming

display_name: incoming

longwave-radiation

display_name: longwave-radiation

outgoing

display_name: outgoing

shortwave-radiation

display_name: shortwave-radiation

en: ASRB_DAV: Shortwave and longwave radiation measurements (2 min) in Davos Dorf


maintainer: Sebastian Schlögl

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

en: Turbulence data WFJ07

en: lower sensor

en: Turbulence data PM07

en: NWW

en: Turbulence data GR00

en: sensor in 2 m height

en: Turbulence data AA00

en: sensor in 25 m height

en: sensor in 0.2 m height

en: Turbulence data WFJ11

en: SEE

en: sensor in 1 m height

en: upper sensor

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

en: Data plot of the field station (BAF)

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

en: Site photo of the field station (BAF)

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

en: Site aerial photo (Beatenberg)

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

en: Forest station data (BAB)

en: Data file.

en: Field station data (BAF)

en: Data plot of the forest station (BAB)

en: Site photo of the forest station (BAB)

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

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 Beatenberg in Switzerland where one station is located within a natural coniferous forest (BAB) with Norway spruce (_Picea abies_; 190-210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Beatenberg 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: 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: Beatenberg, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Jonas Stillhard

en: dem fagus-sylvatica stand-inventory-data carpathian-biosphere-reserve forest primeval-beech-forest long-term-data-sets forest-dynamics forest-structure permanent-forest-plot-data

en: Dataset

en: Data description

en: Available online on publishers website

en:
In 2000, a permanent forest plot of 10 ha has been established in the core zone of the primeval beech forest of Uholka.
 All living and dead trees with a diameter at breast height (DBH) ≥ 60 mm were identified to species, DBH measured, stems tagged and mapped.
Since then, the plot has been remeasured in 2005, 2010, and 2015. In total, 4,820 individual trees were measured with 14,116 individual measurements throughout all four inventories.
In spring 2018, an Airborne Laser Scan was carried out, covering the Uholka‐Shyrokyi Luh forest. This data set allows us to derive a high‐resolution digital elevation model (DEM) of the plot area.
The data set allows for important insights into the development and the spatial and temporal dynamics of primeval beech forests.

carpathian-biosphere-reserve

display_name: carpathian-biosphere-reserve

dem

display_name: dem

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-structure

display_name: forest-structure

long-term-data-sets

display_name: long-term-data-sets

permanent-forest-plot-data

display_name: permanent-forest-plot-data

primeval-beech-forest

display_name: primeval-beech-forest

stand-inventory-data

display_name: stand-inventory-data

en: Stand inventory data from the 10‐ha forest research plot in Uholka, Ukraine