envi

de: Umwelt

de: erdbebeneinwirkung erdbebensicherheit seismische-baugrundklassen baugrundklassenkarte erdbeben

de: DXF (in Zip): Baugrundklassenkarte

de: GeoPackage (in Zip): Baugrundklassenkarte

de: INTERLIS 2 (in Zip): Baugrundklassenkarte

de: Shapefile (in Zip): Baugrundklassenkarte

de: Die Baugrundklasse ist eine erforderliche Angabe, um die Erdbebeneinwirkung für ein Bauwerk gemäss Norm SIA 261 zu bestimmen. Sie ist als Hinweiskarte zu betrachten und ist nicht parzellenscharf. Methodisch wird bei Unsicherheiten die Baugrundklasse auf der sicheren Seite kartiert. Die Karten sind primär im Rahmen von Voruntersuchungen von Nutzen. Bei der Projektierung von Bauvorhaben ist die Plausibilität der Baugrundklasse aufgrund von lokalen Abklärungen zu verifizieren. Bei begründeten Abweichungen soll die Baugrundklasse basierend auf lokalen Untersuchungen benutzt werden. <br/> Die Karte wurde auf Basis der Norm SIA 261, Ausgabe 2003, erstellt und stammt aus dem Jahr 2006.

de: Baugrundklassenkarte


regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

fr: Environnement

en: Environment

it: Ambiente

de: hohe laserscanning lidar hohenlinien dsm dom ndom

label: geocat.ch permalink

state: active

type: dataset

de: Download über data.geo.so.ch

de: Die Daten liegen in Teilgebiete gegliedert vor. Bezug darum via Gebietsauswahl auf data.geo.so.ch

de: Das normalisierte digitale Oberflächenmodell ist das Resultat aus der Differenzberechnung zwischen dem DOM (Rasterdaten) und DTM (Rasterdaten) aus dem Jahr 2014 (LiDAR). Die Daten haben eine Auflösung von 50 cm.

spatial: Kanton Solothurn (SO)

de: Kanton Solothurn

de: Beginnend mit den Geodaten veröffentlicht der Kanton Solothurn hier nach und nach Datensätze der kantonalen Verwaltung, welche die Anforderungen zur Publikation als Open Government Data erfüllen.

political_level: canton

type: organization

approval_status: approved

value: SO-Kt - Geocat Harvester

de: Normalisiertes digitales Oberflächenmodell (LiDAR 2014)


de: DXF (in Zip): statische Waldgrenze

format: DXF

protocol: WWW:DOWNLOAD:Geopackage (ogc)

de: GeoPackage (in Zip): statische Waldgrenze

format: GPKG

de: INTERLIS 2 (in Zip): statische Waldgrenze

format: INTERLIS

de: Shapefile (in Zip): statische Waldgrenze

format: SHP

de: Statische Waldgrenzen in Bauzonen. Im Rahmen eines Waldfeststellungsverfahrens wird ein Waldfeststellungsplan erstellt. Die dort festgelegten Waldgrenzen sind rechtlich verbindlich, unabhängig von den tatsächlichen Verhältnissen.

de: statische Waldgrenze


envi

de: Umwelt

de: DXF (in Zip): Richtplan

de: GeoPackage (in Zip): Richtplan

de: INTERLIS 2 (in Zip): Richtplan

de: Shapefile (in Zip): Richtplan

de: Der kantonale Richtplan ist das Führungsinstrument des Regierungsrat für die Steuerung und Koordination der langfristigen räumlichen Entwicklung. Der Inhalt wird nach strategischen Überlegungen nach den Themen Siedlung, Landschaft, Verkehr soie Ver- und Entsorgung aufgeteilt. Der Inhalt des Richtplanes ist für kantonale und kommunale Behörden verbindlich. Die Planungs- und Koordinationsabsichten sind im Richtplan auf einen Planungshorizont von 15 bis 25 Jahren ausgelegt. Der Richtplan ist auch ein geeignetes Instrument zur frühzeitigen Information und Mitwirkung der Bevölkerung. Damit können die unterschiedlichen Ansprüche im Hinblick auf einen bestmöglichen Gesamtnutzen für die Öffentlichkeit gegeneinander abgewägt werden.

de: Richtplan


regi

de: Regionen und Städte

de: hohe laserscanning lidar hohenlinien dsm dom ndom

de: Download über data.geo.so.ch

de: Die Daten liegen in Teilgebiete gegliedert vor. Bezug darum via Gebietsauswahl auf data.geo.so.ch

de: Die Ebene Differenz DOM 2014-DOM 2001 ist das Resultat aus der Differenzberechnung zwischen dem DOM (Rasterdaten mit 2m Auflösung) vom Jahr 2001 und dem DOM (Rasterdaten mit 50cm Auflösung) vom Jahr 2014. Die Daten haben eine Auflösung von 50 cm. Achtung: Die Anforderungen aus dem Jahr 2001 und 2014 sind unterschiedlich.

de: Differenz DOM 2014 - DOM 2001


de: GeoTIFF: Klimaanalyse - Kaltluftproduktionsrate Nacht Ist 2020

format: GeoTIFF

de:
Kaltluftproduktionsrate um 4 Uhr in Kubikmeter Kaltluft pro Stunde und Quadratmeter [m3/h/m2] im Zustand Ist 2020.

 Gehört zum Thema Klimaanalyse:
 Der Klimawandel stellt eine neue Herausforderung für die Siedlungsentwicklung dar. Vor diesem Hintergrund wurde die heutige (Ist 2020) und künftige (Zukunft 2060) klimatische Situation flächendeckend für den Kanton Solothurn modelliert (Klimaanalyse). Die Modellergebnisse und die daraus resultierenden Klimaanalyse- und Planungshinweiskarten (zusammen: Klimakarten) geben Aufschluss über die klimatische Situation: Wo befinden sich die Hot-Spots im Siedlungsgebiet? Welche Grün- und Freiräume sind wichtig für die Kaltluftproduktion? Wo verlaufen wichtige Kaltluftleitbahnen, die es freizuhalten gilt?

de: Kanton Solothurn

de: Beginnend mit den Geodaten veröffentlicht der Kanton Solothurn hier nach und nach Datensätze der kantonalen Verwaltung, welche die Anforderungen zur Publikation als Open Government Data erfüllen.


envi

de: Umwelt

de: gesamtmelioration guterregulierung guterzusammenlegung landwirtschaftliche-infrastruktur bodenverbesserung melioration

de: DXF (in Zip): Strukturverbesserungen

de: GeoPackage (in Zip): Strukturverbesserungen

de: INTERLIS 2 (in Zip): Strukturverbesserungen

de: Shapefile (in Zip): Strukturverbesserungen

de: Strukturverbesserungen optimieren die Produktionsbedingungen und fördern eine nachhaltige Entwicklung der Landwirtschaft und des ländlichen Raums. Da mit Strukturverbesserungen auch ökologische Anliegen umgesetzt werden, sind sie ein wichtiges Instrument zur Förderung der Biodiversität.

de: Strukturverbesserungen


regi

de: Regionen und Städte

de: hohe laserscanning lidar dsm dom ndom

de: Auf Basis des DTM (Rasterdaten) wurde die Hangneigung in der Auflösung 25 cm abgeleitet. Die Neigung ist in Grad angegeben.

de: Hangneigung digitales Terrainmodell (LiDAR 2019)


de: GeoTIFF: Klimaanalyse - Windgeschwindigkeit Nacht Ist 2020

de:
Windgeschwindigkeit um 4 Uhr 2 Meter über Grund in Meter pro Sekunde [m/s] für den Zustand Ist 2020.

 Gehört zum Thema Klimaanalyse:
 Der Klimawandel stellt eine neue Herausforderung für die Siedlungsentwicklung dar. Vor diesem Hintergrund wurde die heutige (Ist 2020) und künftige (Zukunft 2060) klimatische Situation flächendeckend für den Kanton Solothurn modelliert (Klimaanalyse). Die Modellergebnisse und die daraus resultierenden Klimaanalyse- und Planungshinweiskarten (zusammen: Klimakarten) geben Aufschluss über die klimatische Situation: Wo befinden sich die Hot-Spots im Siedlungsgebiet? Welche Grün- und Freiräume sind wichtig für die Kaltluftproduktion? Wo verlaufen wichtige Kaltluftleitbahnen, die es freizuhalten gilt?


de: satellitenbilder luftbilder

de: Download über data.geo.so.ch

de: Die Daten liegen in Teilgebiete gegliedert vor. Bezug darum via Gebietsauswahl auf data.geo.so.ch

de:
Fabiges Orthofoto der Bezirke Bucheggberg, Lebern, Solothurn und Wasseramt aus dem Jahr 2014.
 Die Pixelgrösse in Natura beträgt 12.5 cm und die Lagegenauigkeit liegt bei 1-2 Pixel. Die digitalen Bilder (Befliegung mit digitaler Luftbildkamera) wurden auf Basis des aktualisierten digitalen Geländemodells des Bundes (DTM-AV) orthorektifiziert.
 Flugdaten: 21. März 2014, 10. April 2014
 Erfassung der Kanäle Rot, Grün, Blau und nahes Infrarot
 verwendete Kanäle: Rot, Grün und Blau

de: Orthofoto 2014 RGB


envi

de: Umwelt

de: erschliessung erschliessungsgute

de: DXF (in Zip): öV-Güteklasse

de: GeoPackage (in Zip): öV-Güteklasse

de: INTERLIS 2 (in Zip): öV-Güteklasse

de: Shapefile (in Zip): öV-Güteklasse

de: Die öV-Güteklassen sind ein Instrument zur Beschreibung der Qualität der öV-Erschliessung. Die öV-Güteklasse eines Standorts ergibt sich aus der Entfernung zu einem öV-Haltepunkt und dem Angebot (Taktdichte) an dieser Haltestelle. Die Berechnung erfolgt auf Grundlage der (mittlerweile nicht mehr gültigen) VSS-Norm SN 640 290. Die Methodik der Norm wurde erweitert, um den spezifischen Gegebenheiten im Kanton Solothurn Rechnung zu tragen. Bei der Berechnung werden Topographie und Hindernisse berücksichtigt.

de: Kanton Solothurn

de: Beginnend mit den Geodaten veröffentlicht der Kanton Solothurn hier nach und nach Datensätze der kantonalen Verwaltung, welche die Anforderungen zur Publikation als Open Government Data erfüllen.

de: öV-Güteklasse


regi

de: Regionen und Städte

de: Farbiges Orthofoto über den ganzen Kanton aus dem Jahr 2002.<br> Für die Erstellung des Orthofotos wurde das 10m Höhenmodell verwendet.

de: Orthofoto 2002 RGB


de: GeoTIFF: Klimaanalyse - Lufttemperatur Tag Ist 2020

de:
Absolute Lufttemperatur [°C] um 14 Uhr 2 Meter über Grund für den Zustand Ist 2020, exemplarisch für eine autochtone Sommernacht.

 Gehört zum Thema Klimaanalyse:
 Der Klimawandel stellt eine neue Herausforderung für die Siedlungsentwicklung dar. Vor diesem Hintergrund wurde die heutige (Ist 2020) und künftige (Zukunft 2060) klimatische Situation flächendeckend für den Kanton Solothurn modelliert (Klimaanalyse). Die Modellergebnisse und die daraus resultierenden Klimaanalyse- und Planungshinweiskarten (zusammen: Klimakarten) geben Aufschluss über die klimatische Situation: Wo befinden sich die Hot-Spots im Siedlungsgebiet? Welche Grün- und Freiräume sind wichtig für die Kaltluftproduktion? Wo verlaufen wichtige Kaltluftleitbahnen, die es freizuhalten gilt?


de: spital klinik analyse erreichbarkeit spitalliste

de: DXF (in Zip): Erreichbarkeitsanalyse Spitäler und Kliniken

de: GeoPackage (in Zip): Erreichbarkeitsanalyse Spitäler und Kliniken

de: INTERLIS 2 (in Zip): Erreichbarkeitsanalyse Spitäler und Kliniken

de: Shapefile (in Zip): Erreichbarkeitsanalyse Spitäler und Kliniken

de:
Im Rahmen der Spitalplanung (Link) gilt es die Erreichbarkeit der verschiedenen Spitälern und Kliniken für die Solothurner Bevölkerung zu berücksichtigen. Für eine Auswahl aller Spitäler und Kliniken der Schweiz ist die Erreichbarkeit für Solothurnerinnen und Solothurner mit dem motorisierten Individualverkehr berechnet worden.

 Datengrundlagen: Standorte basierend auf «Kennzahlen der Schweizer Spitäler» (BAG, 2021).
 Hektarraster der Solothurner Bevölkerung basierend auf STATPOP (BFS, 2022).


waldmassnahmen-und-objekte

envi

de: Umwelt

title_for_slug: waldmassnahmen-und-objekte

de: biotopbaume altholzinsel waldrand feuchtbiotop holzerei jungwaldpflege schutzwald

de: DXF (in Zip): Waldmassnahmen und Objekte

de: GeoPackage (in Zip): Waldmassnahmen und Objekte

de: INTERLIS 2 (in Zip): Waldmassnahmen und Objekte

de: Shapefile (in Zip): Waldmassnahmen und Objekte

de: Massnahmen und Objekte aus dem Waldportal. Mit dem Programm Biodiversität im Wald 2021-2032 führt der Kanton Solothurn die seit 2011 erfolgreiche Förderung der Artenvielfalt im Wald fort. Von den Massnahmen profitieren primär regionstypische einheimische Pflanzen, Tiere und andere Lebewesen; vorab die seltenen und gefährdeten Arten, für welche der Kanton eine besondere Verantwortung trägt.

de: Waldmassnahmen und Objekte


regi

de: Regionen und Städte

de: Download über data.geo.so.ch

de: Die Daten liegen in Teilgebiete gegliedert vor. Bezug darum via Gebietsauswahl auf data.geo.so.ch

de:
Datenbereitstellung gemäss dem kantonalen Datenmodell SO_Nutzungsplanung_20171118 (Modell für die Ersterfassung) .

 Nutzungspläne lokalisieren und dimensionieren gesetzliche zulässige Nutzung des Bodens und des damit verbunden Raumes nach Art und Intensität. Sie trennt das Baugebiet vom Nichtbaugebiet und scheidet Bauzonen von den übrigen Zonen aus. Im Nutzungsplanverfahren werden unter anderem Erschliessungs-, Zonen-, Gesamt-, Gewässerschutzzonenpläne etc. behandelt.

de: Kanton Solothurn

de: Beginnend mit den Geodaten veröffentlicht der Kanton Solothurn hier nach und nach Datensätze der kantonalen Verwaltung, welche die Anforderungen zur Publikation als Open Government Data erfüllen.

de: Nutzungsplanung kommunal (Modell 2017)


de: landesgrenzen kantonsgrenzen gemeindegrenzen bezirksgrenzen schone-steine inventar-hoheitsgrenzsteinen

de: DXF (in Zip): Hoheitsgrenzen

de: GeoPackage (in Zip): Hoheitsgrenzen

de: INTERLIS 2 (in Zip): Hoheitsgrenzen

de: Shapefile (in Zip): Hoheitsgrenzen

de: Als Hoheitsgrenzen werden die Landesgrenzen, Kantonsgrenzen und die Grenzen der politischen Gemeinden bezeichnet. Die Hoheitsgrenzen liegen auf Grundstücksgrenzen. Sie sind Bestandteil der amtlichen Vermessung.

de: Hoheitsgrenzen


envi

de: Umwelt

de: GeoTIFF: Walkerkarte

de:
Die Topographische Karte des Kantons Solothurn von Urs Josef Walker (1800–1855) aus Solothurn.

 Im Jahre 1828 erhielt Walker von der Regierung des Kantons Solothurn den Auftrag, eine Landkarte des Kantons Solothurn zu erstellen. Er konnte sich dabei zum Teil auf vorhandene Triangulationsmessungen von Johann Baptist Altermatt und Antoine-Joseph Buchwalder abstützen.

 Die in den Jahren 1828 bis 1832 aufgenommene Karte wurde von der bekannten Lithographieanstalt Engelmann & Co. in Paris in Stein gestochen. Die grossformatige, 94 x 80 cm messende einfarbige Karte im Massstab 1:60 000 erschien 1832 und diente zum Teil als Grundlage für die Topographische Karte der Schweiz («Dufourkarte») 1:100 000.

 Quelle: Cartographica Helvetica 11 (1995) 11–17

de: Walkerkarte


regi

de: Regionen und Städte

de: DXF (in Zip): Fischerei

de: GeoPackage (in Zip): Fischerei

de: INTERLIS 2 (in Zip): Fischerei

de: Shapefile (in Zip): Fischerei

de: Fischerei Kanton Solothurn

de: Fischerei


de: hohe laserscanning lidar hohenlinien dsm dom ndom

de: Download über data.geo.so.ch

de: Die Daten liegen in Teilgebiete gegliedert vor. Bezug darum via Gebietsauswahl auf data.geo.so.ch

de: Auf Basis des DTM (Rasterdaten) wurde die Hangneigung in der Auflösung 50 cm abgeleitet. Die Neigung ist in Grad angegeben.

de: Kanton Solothurn

de: Beginnend mit den Geodaten veröffentlicht der Kanton Solothurn hier nach und nach Datensätze der kantonalen Verwaltung, welche die Anforderungen zur Publikation als Open Government Data erfüllen.

de: Hangneigung digitales Terrainmodell (LiDAR 2014)


envi

de: Umwelt

de: ekat luftverschmutzung stickoxide feinstaub ammoniak nmvoc kohlenstoffmonoxid schwefeldioxid kohlenstoffdioxid methan lachgas emissionen schadstoffausstoss

de: DXF (in Zip): Emissionskataster 2010

de: GeoPackage (in Zip): Emissionskataster 2010

de: INTERLIS 2 (in Zip): Emissionskataster 2010

de: Shapefile (in Zip): Emissionskataster 2010

de: Der Emissionskataster Luft ist eine ortsbezogene, systematische Zusammenstellung der wichtigsten Quellen luftverunreinigender Stoffe und Klimagase. Er enthält Angaben über Art und Menge sowie den Ort der Entstehung der auf dem Gebiet des Kantons Solothurn während eines Jahres abgegebenen Schadstoffe. Die Emissionen werden fünf Quellengruppen zugeordnet: Industrie und Gewerbe, Haushalte, Verkehr, Land- und Forstwirtschaft sowie natürliche Quellen. Die Quantifizierung der Emissionen wird für sechs Luftschadstoffe und drei Treibhausgasen aufgezeigt. Es wird die Gesamtemission sowie die Emissionen der fünf Quellengruppen je Schadstoff bzw. Klimagas angegeben.

de: Emissionskataster 2010


schwarzplan

regi

de: Regionen und Städte

title_for_slug: schwarzplan

de: av grundkarte hintergrundkarte

fr: Map (Preview)

de: Map (Preview) Stadtplan

en: Map (Preview)

it: Map (Preview)

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

format: SERVICE

de: WMS Schwarzplan

de: Web Map Services WMS

format: WMS

de: WMTS Schwarzplan

de: Web Map Tile Services WMTS

format: WMTS

de: Die Gebäudeflächen aus der Bodenbedeckung der Amtlichen Vermessung schwarz eingefärbt bilden eine einfache Grundkarte "Schwarzplan".

spatial: Stadt Bern

geoinformation-der-stadt-bern

fr: L’Office du cadastre de la ville de Berne

de: Geoinformation Stadt Bern

en: The Land Surveying Office of the City of Bern

it: L'ufficio del catasto nella Città di Berna

fr: L’Office du cadastre (Geoinformation Stadt Bern) est l’organisme compétent pour la collecte, l’accès et la diffusion d’informations géographiques dans la ville de Berne.

de: Geoinformation Stadt Bern (ehemals Vermessungsamt) ist die Kompetenzstelle für die Beschaffung, den Zugang und die Verbreitung von Geoinformationen in der Stadt Bern.

en: The Surveying Office (Geoinformation Stadt Bern) is the centre of competence in the City of Bern for the procurement of, access to and dissemination of geographic information.

it: L'ufficio del catasto (Geoinformation Stadt Bern) è il centro di competenza per il reperimento, l'accesso e la diffusione di geoinformazioni nella Città di Berna.

political_level: commune

stadt-bern

capacity: public

value: Geoinformation Stadt Bern - Geocat Harvester

de: Schwarzplan


amtliche-vermessung-darstellung-kontur

envi

de: Umwelt

title_for_slug: amtliche-vermessung-darstellung-kontur

de: WMS Amtliche_Vermessung_Kontur

de: WMTS Amtliche_Vermessung_Kontur

de: WFS Amtliche_Vermessung_Kontur

de: Web Feature Services WFS

format: WFS

de: Daten der amtlichen Vermessung in schwarz und ohne Flächenfüllungen dargestellt. Kann zur Überlagerung mit flächengefüllten Informationen nützlich sein.

de: Amtliche Vermessung (Darstellung Kontur)


stadtplan-darstellung-schwarz-weiss

regi

de: Regionen und Städte

title_for_slug: stadtplan-darstellung-schwarz-weiss

de: av grundkarte hintergrundkarte

de: Map (Preview) Stadtplan

de: WMS Stadtplan_schwarzweiss

de: WMTS Stadtplan_schwarzweiss

de: WFS Stadtplan_schwarzweiss

de: Schwarz/weisse, einfache Darstellung basierend auf den Daten der amtlichen Vermessung.

de: Stadtplan (Darstellung schwarz/weiss)


stadtplan-darstellung-farbig

title_for_slug: stadtplan-darstellung-farbig

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

de: WMS Stadtplan_farbig

de: Web Map Services WMS

de: WMTS Stadtplan_farbig

de: Web Map Tile Services WMTS

de: WFS Stadtplan_farbig

de: Farbige, einfache Darstellung basierend auf den Daten der amtlichen Vermessung.

geoinformation-der-stadt-bern

de: Geoinformation Stadt Bern

de: Geoinformation Stadt Bern (ehemals Vermessungsamt) ist die Kompetenzstelle für die Beschaffung, den Zugang und die Verbreitung von Geoinformationen in der Stadt Bern.

de: Stadtplan (Darstellung farbig)


abfallkubel-geodienst-wfs

title_for_slug: abfallkubel-geodienst-wfs

de: WFS GetCapabilities Abfallkübel

de: Abfallkübel mit Standort und zusätzlichen Informationen.

name: Geoinformationszentrum (GIS) Stadt Luzern

stadt-luzern

de: Stadt Luzern

de:
Die Stadt Luzern veröffentlicht hier schrittweise OGD-Datensätze der städtischen Dienstabteilungen. Mehr über «Open Government Data» bei der Stadt Luzern ist über den Link <www.ogd.stadtluzern.ch> zu erfahren.

Die Geometadaten zu den einzelnen OGD-Daten sind unter "Zusätzliche Informationen" als Link aufgeführt.
Zu beachten sind weitere Bestimmungen zum Datenschutz und Nutzungsbestimmungen gemäss OGD-Internetauftritt der Stadt Luzern.

value: Stadt Luzern - Geocat Harvester

de: Abfallkübel (WFS)


regi

de: Regionen und Städte

envi

de: Umwelt

de: Map (Preview) Stadtplan

de: WMS Amtliche_Vermessung_schwarzweiss

de: WMTS Amtliche_Vermessung_schwarzweiss

de: WFS Amtliche_Vermessung_schwarzweiss

de: Web Feature Services WFS

de: Plan für das Grundbuch der Stadt Bern in Graustufen mit blau eingefärbten Gewässern.

de: Amtliche Vermessung (Darstellung schwarz/weiss)


abfallkubel-geodienst-wms

title_for_slug: abfallkubel-geodienst-wms

de: WMS GetCapabilities Abfallkübel

de: Abfallkübel (WMS)


amtliche-vermessung-darstellung-farbig

title_for_slug: amtliche-vermessung-darstellung-farbig

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

de: WMS Amtliche_Vermessung_farbig

de: Web Map Services WMS

de: WMTS Amtliche_Vermessung_farbig

de: Web Map Tile Services WMTS

de: WFS Amtliche_Vermessung_farbig

de: Plan für das Grundbuch der Stadt Bern - farbig.

geoinformation-der-stadt-bern

de: Geoinformation Stadt Bern

de: Geoinformation Stadt Bern (ehemals Vermessungsamt) ist die Kompetenzstelle für die Beschaffung, den Zugang und die Verbreitung von Geoinformationen in der Stadt Bern.

de: Amtliche Vermessung (Darstellung farbig)


abfallkubel-standort-und-information

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: abfallkubel-standort-und-information

media_type: application/json

de: Abfallkübel als json-Datei

format: JSON

de: Abfallkübel als Geopackage (.gpkg)

de: Abfallkübel als dxf-Datei

de: Abfallkübel mit Standort und zusätzlichen Informationen. Nebst der Lage der Abfallkübel sind Attribute wie Baujahr und Leerungsperiodizität erfasst.

spatial: Stadt Luzern

stadt-luzern

de: Stadt Luzern

de:
Die Stadt Luzern veröffentlicht hier schrittweise OGD-Datensätze der städtischen Dienstabteilungen. Mehr über «Open Government Data» bei der Stadt Luzern ist über den Link <www.ogd.stadtluzern.ch> zu erfahren.

Die Geometadaten zu den einzelnen OGD-Daten sind unter "Zusätzliche Informationen" als Link aufgeführt.
Zu beachten sind weitere Bestimmungen zum Datenschutz und Nutzungsbestimmungen gemäss OGD-Internetauftritt der Stadt Luzern.

de: Abfallkübel - Standort und Information


de: Map (Preview) Stadtplan

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

de: WMS Amtliche_Vermessung_fuer_Orthofoto

de: Web Map Services WMS

de: WMTS Amtliche_Vermessung_fuer_Orthofoto

de: WFS Amtliche_Vermessung_fuer_Orthofoto

de: Web Feature Services WFS

de: Daten der amtlichen Vermessung in weiss/gelb und ohne Flächenfüllungen dargestellt. Kann zur Überlagerung mit Orthofotos nützlich sein.

de: Amtliche Vermessung (Darstellung für Orthofoto)


quellen-und-sondierungen

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: quellen-und-sondierungen

label: Web GIS Client des Kanton Uri. Die Daten können direkt via dem Portal in den unterschiedlichsten Datenformaten heruntergeladen werden.

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Dieser Layer liefert Informationen über die Lage und den Status der öffentlichen und privaten Quellen, sowie die Sondierungen im Kanton Uri. Dies dient als Planungsgrundlage u.a. für die Wasserversorgung, Stellungnahmen, etc.

spatial: Canton of Uri (UR)

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

value: Uri-Kt - Geocat Harvester

fr: Quellen und Sondierungen

de: Quellen und Sondierungen

en: Quellen und Sondierungen

it: Quellen und Sondierungen


gestaltungsplane-perimeter

title_for_slug: gestaltungsplane-perimeter

de: eigentumsbeschrankungoreb nutzungsplanung raumplanung sondernutzungsplanung

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Perimeter der Gestaltungspläne

spatial: Kanton Luzern

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

fr: La géoinformation du canton de Lucerne est responsable de la collecte, du traitement et de la gestion des données à référence spatiale. Elle dirige, coordonne et surveille les travaux de la géoinformation et de la mensuration officielle.

en: Geoinformation of the Canton of Lucerne is responsible for the collection, processing and management of spatial data. It manages, coordinates and monitors the work of geoinformation and of the cadastral surveying.

de: Die Geoinformation des Kantons Luzern ist für die Erhebung, Verarbeitung und Verwaltung von raumbezogenen Daten zuständig. Sie leitet, koordiniert und überwacht die Arbeiten der Geoinformation und der amtlichen Vermessung.

it: La Geoinformation del Cantone di Lucerna è responsabile della raccolta, dell'elaborazione e della gestione dei dati territoriali. Gestisce, coordina e monitora il lavoro della geoinformazione e della misurazione ufficiale.

value: LU-Kt - Geocat Harvester

de: Gestaltungspläne: Perimeter


gewasserschutzbereiche-ur

title_for_slug: gewasserschutzbereiche-ur

fr: Die Kantone bezeichnen zum Schutz des Grundwassers und als Grundlage für die zu treffenden Schutzmassnahmen die besonders gefährdeten und die übrigen Bereiche. Die besonders gefährdeten Bereiche umfassen den Gewässerschutzbereich Au, den Gewässerschutzbereich Ao, den Zuströmbereich Zu und den Zuströmbereich Zo. Die Gewässerschutzbereiche Au und Zu dienen dem planerischen Schutz der unterirdischen Gewässer. Die Bereiche Ao und Zo bezwecken den Schutz von Oberflächengewässern. Die übrigen Bereiche (üB) umfassen den Rest des Kantons.

fr: Gewässerschutzbereiche (UR)

de: Gewässerschutzbereiche (UR)

en: Gewässerschutzbereiche (UR)

it: Gewässerschutzbereiche (UR)


soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

de: eigentumsbeschrankungoreb gebaude-und-anlagen kulturdenkmal kulturguterschutz nutzungsplanung ortsbildschutz zonenplan

de: Zeigt im Kantonalen Denkmalverzeichnis (KDV) und Bauinventar eingetragene Bauten und Schutzobjekte.

name: Denkmalpflege und Archäologie des Kantons Luzern, Denkmalpflege

de: Kantonales Denkmalverzeichnis und Bauinventar


nutzungsplanung-planungszonen

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: nutzungsplanung-planungszonen

de: bewilligungen eigentumsbeschrankungoreb nutzungsplanung raumplanung zonenplan

de: Die Planungszone bezeichnet ein Gebiet, in dem Nutzungspläne erlassen oder geändert werden müssen.

de: Nutzungsplanung: Planungszonen


waldflachen

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

title_for_slug: waldflachen

de: forstwirtschaft nutzungsplanung vegetation wald

de: Datenshop

de: Wald nach Waldrecht, dieser umfasst unter anderem auch Waldstrassen, Gewässer und Gebäude innerhalb des Waldes.

name: Dienststelle Landwirtschaft und Wald (lawa)

de: Waldflächen


maintainer: EnviDat Support

en: switzerland environmental--policy ecology wetlands environmental---history historical-carthography

en: Wetlands 1850 - 2010 (shapefiles)

media_type: application/zip

en:
 History of wetlands - GIS-Layers
 Location of wetlands based on signatures in topographic maps
* Basis 1850: original measuring table sheets Dufour created between the years 1834 and 1863.
* Basis 1900/ Basis 1950: The Siegfried maps were updated and published at regular intervals between 1870 and 1949. This long period of time made it possible to reconstruct wetlands for two periods based on the Siegfried Maps: the first edition (hereinafter referred to as "1900") and the last edition ("1950").
* Basis 2010: Map sheets from the National Map from 2006 to 2011 were used for the most recent time period of the reconstruction.
 Location of wetlands due to reconstructions
The reconstruction **must not** be interpreted in the sense of a surface-accurate separation, but shows without claim to location accuracy the approximate extent of the areas that would have corresponded to the mapping criteria for wetlands used in today's topographic maps around 1850, 1900 and 1950. The basics can be found in Stuber & Bürgi 2019, chapter 5.4.

format: ZIP

mimetype: application/zip

en:
Naturally, large parts of the Swiss Plateau are characterised by wetlands
and meandering rivers. That this is no longer the case today is the result
of centuries of efforts to obtain dry land. But how did this process take
place? What were the relevant actors and what were their motivations? And
what can be said about the ecological consequences of this development?

In a research project on the history of wetlands in Switzerland since 1700,
we conducted (a) a historical analysis of the development of land use in
wetlands and the actors involved, (b) a historical-cartographic
reconstruction of wetland extent since 1850 and (c) an evaluation of
ecological effects of changes in wetlands on various organisms groups.

The series of GIS layers on wetland history stem from the second part of
the project. The area reconstruction is based on digitized and homogenized
signatures from national map series, as they have been available since
about 1850. Details about the digitalization process and the homogenization
procedures applied ("Rekonstruktionen") are included in Stuber & Bürgi
2019.

Book Citation:
 > Stuber M, Bürgi M (2019) Vom «eroberten Land» zum Renaturierungsprojekt. Geschichte der Feuchtgebiete in der Schweiz seit 1700. "Bristol Schriftenreihe", Band 59. Haupt Verlag, Bern, Stuttgart, Wien. 262 Seiten.

ecology

display_name: ecology

environmental---history

display_name: environmental---history

environmental--policy

display_name: environmental--policy

historical-carthography

display_name: historical-carthography

switzerland

display_name: switzerland

wetlands

display_name: wetlands

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: History of wetlands in Switzerland since 1850


en: orography air-temperature precipitation paleo-climate last-glacial-maximum glaciers

en: Technical documentation

media_type: application/pdf

en: Technical documentation containing file metadata and variable descriptions.

format: PDF

mimetype: application/pdf

en: Data Access via S3

en:
High resolution, downscaled climate model data are used in a wide variety of applications in environmental sciences. Here we present the CHELSA-TraCE21k downscaling algorithm to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100 year time steps for the last 21,000 years. Paleo orography at high spatial resolution and at each timestep is created by combining high resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases with the interpolation of a dynamic ice sheet model (ICE6G) and a coupling to mean annual temperatures from CCSM3-TraCE21k. Based on the reconstructed paleo orography, mean annual temperature and precipitation was downscaled using the CHELSA V1.2 algorithm.

The data is published under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

glaciers

display_name: glaciers

last-glacial-maximum

display_name: last-glacial-maximum

orography

display_name: orography

paleo-climate

display_name: paleo-climate

precipitation

display_name: precipitation

en: CHELSA-TraCE21k: Downscaled transient temperature and precipitation data since the last glacial maximum


en: population-evolution biological-control dryocosmus-kuriphilus southern-switzerland pest-invasion torymus-sinensis castanea-sativa

media_type: text/csv

en:
Data has been collected from summer 2011 to 2016.

Main reasons for NA values:

-	D. kuriphilus still not arrived in the site.
-	No galls were found during the field sampling.
-	Site has not been sampled in the correspondent year because of time, weather or money constrains.
-    T. sinensis not found in the galls

Variable description:

Year = sampling year.

Coordinate, elevation, slope, aspect = average site characteristics.

ts_arrival = T. sinensis arrival year.

dk_arrival = D. kuriphilus arrival year.

dk_parasitism_by_ts = D. kuriphilus parasitism rate by T. sinensis. Formula: (no. of T. sinensis/ no. of D. kuriphilus chambers) * 100 at gall level.

dk_infestation = Percentage of attacked buds. Formula: no. of attacked buds / no. of total developed buds*100 (as presented in Kotobuki et al. 1985) at shoot level.

ts_per_bud = number of alive T. sinensis individual calculated at bud level.

dk_per_bud = number of alive D. kuriphilus individual calculated at bud level.

dk_pot_per_bud = overall number (dead and alive) D. kuriphilus individual calculated at bud level.

total_gall_nr_per_bud = average gall number per bud.

chamber_per_galls = average D. kuriphilus chamber number per gall.

For details see the submitted publication with the same name

References
Kotobuki, K., Mori, K. and Sato, Y. (1985) ‘2 methods to estimate the tree damage by chestnut gall wasp Dryocosmus-kuriphilus’, Bulletin of the fruit tree research station A (Yatabe), 2(12), pp. 29–36.

format: CSV

mimetype: text/csv

en:
This dataset contains the population evolution of a pest and its biocontrol agent in terms of presence proportion at gall level and absolute number of insects.

The study area extends from the Cuneo region (Piedmont, Italy) to southern Switzerland. In order to provide a complete range of data covering the entire process from the pest arrival to complete biological control by its natural enemy T. sinensis, a space-for-time substitution approach has been adopted so as to create a temporal gradient of the epidemic stages over the whole study area.

The southernmost Swiss sites roughly represent the arrival and establishment of the pest without the presence of the natural enemy, the central ones the early epidemic stage and the epidemic peak, whereas the northern ones the end of the epidemic with the beginning of the biocontrol. The Italian ones represent the beginning of the equilibrium between the two population as well as the situation with stable T. sinensis populations on the long term.

These data are used in the paper entitled: Torymus sinensis local and regional early population dynamics in the Insubrian and Piedmont regions

biological-control

display_name: biological-control

castanea-sativa

display_name: castanea-sativa

dryocosmus-kuriphilus

display_name: dryocosmus-kuriphilus

pest-invasion

display_name: pest-invasion

population-evolution

display_name: population-evolution

southern-switzerland

display_name: southern-switzerland

torymus-sinensis

display_name: torymus-sinensis


disdrometer-data-gotschnagrat

title_for_slug: disdrometer-data-gotschnagrat

en: visibility disdrometer raclets hydrometeors precipitation

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

raclets

display_name: raclets

visibility

display_name: visibility

educ

en: Education, culture and sport


photogrammetric-drone-data-schurlialp

maintainer: Yves Bühler

title_for_slug: photogrammetric-drone-data-schurlialp

en: wingtra uav drone-data orthophoto photogrammetry dsm

en: Data Access

en:
- 10 cm DSM
- 10 cm HS
- 3 cm orthophoto
- original RGB images
- Agisoft Metashape Processing Report

All of the products are also available as a cloud optimized geotiff.

en: The data was collected on 16.04.2021 and on 28.05.2021 with a Wingtra Gen II and a Sony RX1 II RGB sensor to obtain snow depth and distribution data. Following the data collection, the data was processed with Agisoft Metashape. A 10cm DSM, a 10cm snow depth raster, a 3mm orthophoto and the original drone images are available for download.

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

envidat

en: EnviDat: the Environmental Data Portal

en: Photogrammetric Drone Data Schürlialp


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

en: Site aerial photo (Vordemwald)

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

mimetype: image/jpeg

en: Forest station data (VOB)

en: Data file.

en: Field station data (VOF)

en: Site photo of the field station (VOF)

en: Site photo of the field stationfrom the side.

en: Data plot of the forest station (VOB)

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

en: Site photo of the forest station (VOB)

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

en: Data plot of the field station (VOF)

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 Vordemwald in Switzerland where one station is located within a natural mixed forest stand (VOB) with European silver fir (_Abies alba_; 110 yrs) and oak trees (_Quercus sp._; 190-210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, VOF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Vordemwald 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 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: Vordemwald, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards


maintainer: Sebastian Schlögl

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

en: Turbulence data AA00

en: sensor in 1 m height

en: Turbulence data PM07

en: NWW

en: SEE

en: Turbulence data WFJ11

en: sensor in 25 m height

en: sensor in 0.2 m height

en: Turbulence data WFJ07

en: upper sensor

en: lower sensor

en: Turbulence data GR00

en: sensor in 2 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

educ

en: Education, culture and sport

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


maintainer: Anita C Risch

en: soil-properties herbivore-exclusion nutrient-addition climate microbial-biomass-carbon microbial-respiration anthropogenic-management

en: Risch et al. GEB_data.xlsx

en:
Study sites and experimental design
We collected data from 23 sites that are part of the Nutrient Network Global Research Cooperative (NutNet, https://nutnet.umn.edu/). The mean annual air temperature (MAT) across these sites ranged from -4 to 22°C, mean annual precipitation (MAP) from 252 to 1592 mm, and elevations from 6 to 4261 m above sea level (Fig 1a, Supplementary Table S1), hence cover a wide range of climatic conditions under which grasslands occur (Fig 1b). Soil organic C concentrations ranged between 0.8 to 7.8%, soil total N concentrations between 0.1 and 0.6%, and the soil C:N ratio between 9.1 and 21.5. Soil clay content spanned from 3.0 to 35%, and soil pH from 3.4 to 7.6 (Supplementary Table S2).
At each site, the effects of nutrient addition and herbivore exclusion were tested via a randomized-block design (Borer et al., 2014). Three blocks with 10 treatment plots each were established at each site, except for the site at bldr.us (only two blocks). Each of these 10 plots was randomly assigned to a nutrient or fencing treatment. An individual plot was 5 x 5 m, divided into four 2.5 x 2.5 m subplots. Each subplot was further divided into four 1 x 1 m square sampling plots, one of which was set aside for soil sampling (Borer et al., 2014). Plots were separated by at least 1 m wide walkways. We collected soil samples from four different treatments for this study: (i) untreated control plots (Control), (ii) herbivore exclusion plots (Fence), (iii) plots fertilized with N, P, K, plus nine essential macro and micronutrients (NPK), and (iv) plots with simultaneous fertilizer addition and herbivore exclusion (NPK+Fence). The experiments were established at different times in the past, with years of treatment different among sites (2 – 9 years since start of treatment; Supplementary Table S1). For the nutrient additions, all sites applied 10 g N m-2 each year as time-release urea; 10 g P m-2 yr-1 as triple-super phosphate; 10 g K m-2 yr-1 as potassium sulfate. A micro-nutrient mix (Fe, S, Mg, Mn, Cu, Zn, B, Mo, Ca) was applied at 100 g m-2 together with K in the first year of treatments but not thereafter.
We excluded large vertebrate herbivores (Fence) by fencing two plots, one with and one without NPK additions, within each block. The fences excluded all aboveground mammalian herbivores with a body mass of over 50 g (Borer et al., 2014). At most sites, the fences were 180 cm high, and the fence contained a wire mesh (1 cm holes) for the bottom 90 cm with a 30 cm outward-facing flange stapled to the ground to exclude burrowing animals. Climbing and subterranean animals may potentially still access these plots (Borer et al., 2014). For slight modifications in fence design at a few sites see Supplementary Table S3. Most sites only had wild herbivores, although four sites were also grazed by domestic animals (Supplementary Table S1).

Collection of soil samples, soil microbial respiration, microbial biomass, and other soil properties
Each of the 23 sites received a package containing identical material from the Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Switzerland to be used for sampling (Risch et al., 2015; Risch et al., 2019). We collected two soil cores of 5 cm diameter and 12 cm depth in each sampling plot and composited them to measure MR, MBC, and soil chemical properties (see below). An additional sample (5 x 12 cm) was collected to assess soil physical properties. This sample remained within a steel sampling core after collection and both ends were tightly closed with plastic caps to avoid disturbance. All soils were shipped cooled to the laboratory at (Location will be disclosed after manuscript acceptance) within a few days after collection. Soils were sampled roughly 6 weeks prior to peak biomass at each site during 2015 and 2016.
To assess MR (CO2 production) in a laboratory incubation experiment we weighed duplicate soil samples (8 g dry soil equivalent) into 50-ml Falcon tubes. No additional substrate (glucose, sugar) was added to these samples. We adjusted the soil moisture of each sample to 60% field capacity. We then placed a 15 ml plastic test tube (Semadeni 1701A) containing 7.25 ml 0.05 M NaOH over each soil sample. The test tube was fixed with a plastic rod so that it was not in contact with the soil sample. The Falcon tubes were then sealed with a screw cap and placed in an incubator under completely dark conditions at 20°C. The CO2 produced by microbial respiration was absorbed by the 0.05 M NaOH. For five weeks we measured the decrease in conductivity within the 0.05 M NaOH solution on a weekly basis with a Multimeter WTW Multi 3410 (WTW GmbH, Germany) and replaced the 0.05 M NaOH with fresh solution. We included Falcon tubes without soil samples in each incubation run as blanks to test if tubes were tight and no CO2 could enter or escape. We calibrated the relationship between conductivity reduction and NaOH absorbed as follows: 400 ml 0.05 M NaOH was placed in a beaker and its conductivity was measured with the multimeter. While stirring, air containing CO2 was blown into the solution for approximately one minute, which reacts with NaOH to form Na2CO3. After this process, conductivity was measured again. We then transferred 7.25 ml of the solution into a smaller beaker and added 1 ml of 0.1 M BaCl2 to precipitate Na2CO3 and then titrated the solution with 0.05 M HCl to determine the remaining NaOH. We then repeated these steps with the remaining solution a total of nine times and plotted the conductivities (y-axis) against the NaOH consumed (x-axis, Supplementary Fig S1). This regression line was used to infer the consumption of NaOH from the conductivity reduction in the incubation experiments and to calculate CO2 evolution during incubation. In addition, we determined the optimum concentration for the NaOH solution in series of preliminary experiments, so that the concentration was not too high to become insensitive, but also not too low so that not all NaOH reacts during incubation. We then calculated MR (mg CO2-C kg dry soil-1 h-1) as total amount of CO2 released over the 5 weeks divided by the duration of the entire incubation in hrs.
Soil microbial biomass carbon (MBC; mg C kg soil-1 ) was measured at the beginning of the experiment by measuring the maximal respiratory response to the addition of glucose solution (4 mg glucose per g soil dry weight dissolved in distilled water; substrate-induced respiration method) on approximately 5.5 g of soil (J. P. E. Anderson & Domsch, 1978; Nico Eisenhauer et al., 2018; Scheu, 1992). For this purpose we used an O2-micro-compensation apparatus (Scheu, 1992). More specifically, substrate-induced respiration was calculated from the respiratory response to D-glucose for 10 hr at 20°C. Glucose was added according to preliminary studies to saturate the catabolic enzymes of microorganisms (4 mg g soil-1 dissolved in 400 ml deionized water). The mean of the lowest three readings within the first 10 hrs (between the initial peak caused by disturbing the soil and the peak caused by microbial growth) was taken as maximum initial respiratory response (MIRR; ml O2 kg soil-1 h-1) and microbial biomass (mg C kg soil-1) was calculated as 38 x MIRR (Beck et al., 1997; Cesarz et al., 2022; Thakur et al., 2015).
The rest of the composited sample was dried at 65°C for 48 h, ground and sieved (2 mm mesh) to assess the soil pH, mineral soil total C and N and C:N ratio, and mineral soil organic C (Risch et al., 2019). The undisturbed sample was used to assess water holding capacity (WHC), bulk density (BD), and soil texture [sand, silt, clay; methods in (Risch et al., 2019)]. We used the percentage of sand and clay as an indicator of soil texture in this study. MAT (°C), MAP (mm) and temperature of the wettest quarter (°C) were obtained from www.worldclim.com (Fick & Hijmans, 2017; Hijmans, Cameron, Parra, Jones, & Jarvis, 2005). These variables were selected as they were found to be drivers of soil nutrient processes across these sites in earlier studies (Risch et al., 2020; Risch et al., 2019). Mean annual soil temperatures (MAST; °C) for the 0 to 5 cm soil layer were obtained for each site from the SoilTemp maps (J. Lembrechts et al., 2021; J. J. Lembrechts et al., 2022), global gridded modelled products of soil bioclimatic variables for the 1979-2013 period at a 1-km² resolution, based on CHELSA, ERA5 and in-situ soil temperature measurements.
Numerical calculations and statistical analyses
We calculated MMQ as MR/MBC. We corrected this measure using the average soil temperature of each site (MMQsoil). This temperature correction is necessary as incubation temperatures are usually much higher than site mean annual soil temperatures (see Xu et al. 2017). MMQsoil = MMQ x Q10(MAST – 20)/10, where Q10 was assumed to be 2 (Xu et al. 2017). See Supplementary Fig S2 for comparison of air and soil temperatures across the 23 sites as well as the incubation temperature.
Some of the explanatory variables (clay, soil organic C, C:N ratio) were skewed and were thus log-transformed prior to analyses. All continuous explanatory variables were centred and scaled to have a mean of zero and variance of one. To avoid collinearity between them we filtered them using correlation analysis (Supplementary Fig S3). From the variables that were strongly correlated (Pearson’s |r| > 0.70) (Dormann et al., 2013), we selected the ones that allowed us to minimize the number of variables (Supplementary Fig S3). Specifically, soil total N concentration, soil total C concentration, soil sand content and soil bulk density were dropped from the dataset. We then assessed how these edaphoclimatic variables are related to MMQ across our global grasslands.
For this, we used linear mixed effects models (LMMs) fitted by maximum likelihood with the lme function in the nlme package (version 3.1-153) (Pinheiro, Bates, DebRoy, & Sarkar, 2021) in R version 3.6.3. (R Core Team, 2019). We used treatment as a fixed effect and plot nested in site as random effects to assess treatment differences in MMQsoil, as well as MR, and MBC. The number of years since the treatment started was included as a fixed effect in all the initial models but was not significant and therefore not retained in the models. To assess how differences in MMQsoil were affected by environmental factors (soil, climatic properties) we again used LMMs. Soil and climatic properties were included as fixed effects and plot nested in site as random effects. We did not include interactions between environmental variables. We then used the MuMin package (Barton, 2018) (version 1.42.1) to select the best models that explained the most variation based on Akaike’s information criterion (AIC; model.avg function). We used the corrected AIC (AICc) to account for our small sample size and selected the top models that fell within 4 AICc units (delta AICc < 4) (Burnham & Anderson, 2002; Johnson & Omland, 2004). We present all our top models rather than model averages. Conditional averages are provided in the Supplementary material.
Based on findings from analyses described above and the literature, we developed a conceptual model of direct and indirect relationships between both edaphoclimatic variables and experimental treatments (Supplement Figure S4) to obtain a more holistic approach in understanding how these properties affect MMQsoil. We had data from 23 sites with 272 observations. We tested this model using structural equation modelling based on a d-sep approach (Lefcheck, 2016; Shipley, 2009). We considered those environmental drivers that were included in our top LMMs, namely temperature of the wettest quarter (T.q.wet), soil pH, water holding capacity (WHC) and soil organic C (organic C; Supplementary Figure S4). These factors were allowed to directly affect MMQsoil, and via their interactions with treatments. In addition, treatments were allowed to directly affect MMQsoil. Treatments were included as dummy variables in the model. We tested our conceptual model (Supplementary Fig S4) using the piecewiseSEM package (version 2.0.2; Lefcheck, 2016) in R 3.4.0, in which a structured set of linear models are fitted individually. This approach allowed us to account for the nested experimental design, and overcome some of the limitations of standard structural equation models, such as small sample sizes (Lefcheck, 2016; Shipley, 2009). We used the lme function of the nlme package to model response variables, including site as a random factor. Good fit of the SEM was assumed when Fisher’s C values were non-significant (p > 0.05). For all significant interactions between soil or climate variables and treatments detected in the SEMs, we calculated treatment effect sizes, i.e., the differences in MMQsoil between Control and treatments as log response ratios (LRR) and plotted these values against the climate or soil factors. The LRR were defined as log(Control/Treatment), where treatment was either Fence, NPK or NPK+Fence. To assess which of the LRR-climate or soil property relationships were significant we again used LMMs, in which soil and climatic properties were included as fixed effects and plot nested in site as random effects.

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

Paper Citation:

Risch Anita C., Zimmermann, Stefan, Schütz, Martin, Borer, Elizabeth T., Broadbent, Arthur A.D., Caldeira, Maria C., Davies, Kendi F., Eisenhauer, Nico, Eskelinen, Anu, Fay, Philip A., Hagedorn, Frank, Knops, Johannes M.H., Lembrechts, Jonas, J., MacDougall, Andrew S., McCulley, Rebecca L., Melbourne, Brett A., Moore, Joslin L., Power, Sally A., Seabloom, Eric W., Silveira, Maria L., Virtanen, Risto, Yahdjian, Laura, Ochoa-Hueso, Raul (accepted). Drivers of the microbial metabolic quotient across global grasslands. Global Ecology and Biogeography

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

The microbial metabolic quotient (MMQ; mg CO2-C mg MBC-1 h-1), defined as the amount of microbial CO2 respired (MR; mg CO2-C kg soil-1 h-1) per unit of microbial biomass C (MBC; mg C kg soil-1), is a key parameter for understanding the microbial regulation of the carbon (C) cycle, including soil C sequestration. Here, we experimentally tested hypotheses about the individual and interactive effects of multiple nutrient addition (NPK+micronutrients) and herbivore exclusion on MR, MBC, and MMQ across 23 sites (5 continents). Our sites encompassed a wide range of edaphoclimatic conditions, thus we assessed which edaphoclimatic variables affected MMQ the most and how they interacted with our treatments. Soils were collected in plots with established experimental treatments. MR was assessed in a five-week laboratory incubation without glucose addition, MBC via substrate-induced respiration. MMQ was calculated as MR/MBC and corrected for soil temperatures (MMQsoil). Using LMMs and SEMs, we analysed how edaphoclimatic characteristics and treatments interactively affected MMQsoil. MMQsoil was higher in locations with higher mean annual temperature, lower water holding capacity, and soil organic C concentration, but did not respond to our treatments across sites as neither MR nor MBC changed. We attributed this relative homeostasis to our treatments to the modulating influence of edaphoclimatic variables. For example, herbivore exclusion, regardless of fertilization, led to greater MMQsoil only at sites with lower soil organic C (<1.7%). Our results pinpoint the main variables related to MMQsoil across grasslands and emphasize the importance of the local edaphoclimatic conditions in controlling the response of the C cycle to anthropogenic stressors. By testing hypotheses about MMQsoil across global edaphoclimatic gradients, this work also helps to align the conflicting results of prior studies.

anthropogenic-management

display_name: anthropogenic-management

climate

display_name: climate

herbivore-exclusion

display_name: herbivore-exclusion

microbial-biomass-carbon

display_name: microbial-biomass-carbon

microbial-respiration

display_name: microbial-respiration

nutrient-addition

display_name: nutrient-addition

soil-properties

display_name: soil-properties

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.


maintainer: Frank Techel

en: avalanche-accident avalanche-accident-statistics avalanche-statistics long-term-trends avalanche-fatalities

en: Data avalanche fatalities 1969/1970 - 2014/2015

media_type: text/plain

en: The data comprises avalanche fatality data from the Alpine regions in the seven countries Austria, France, Germany, Italy, Liechtenstein, Slovenia, and Switzerland.

format: TXT

mimetype: text/plain

en:
During the last 45 years, about 100 people lost their lives in avalanches in the European Alps each year. Avalanche fatalities in settlements and on transportation corridors have considerably decreased since the 1970s. In contrast, the number of avalanche fatalities during recreational activities away from avalanche-secured terrain doubled between the 1960s and 1980s and has remained relatively stable since, despite a continuing strong increase in winter backcountry recreational activities.

Data complementing Figure 2 in:
_"Avalanche fatalities in the European Alps: long-term trends and statistics"_, by Techel, F., Jarry, F., Kronthaler, G., Mitterer, S., Nairz, P., Pavšek, M., Valt, M., and Darms, G.

Data description:
please refer to section 2 (Data and Methods) in the mentioned publication

avalanche-accident

display_name: avalanche-accident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

avalanche-statistics

display_name: avalanche-statistics

long-term-trends

display_name: long-term-trends

en: Avalanche fatalities in the European Alps (1969/1970 - 2014/2015)


tree-ring-laser-ablation-data

maintainer: Paula Ballikaya

title_for_slug: tree-ring-laser-ablation-data

en: tree-rings air-pollution dendrochemistry laser-ablation dendrochronology

en: Laser ablation data

en:
This dataset contains the values of several chemical elements (Mg, Al, Si, S, K, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Tl, Pb, Bi) measured in the latewood of tree rings of Mongolian oak from Harbin, China, at a 5-year resolution. Due to the lack of a suitable reference material for wood, absolute concentration was not calculated, and the ratio between the chemical element and 13C was taken as proxy for the element signal.

In Harbin, one of the largest cities and most important industrial centers in northeastern China, air quality monitoring systems were built only by the end of 2015 to meet the national requirements. Thus, dendrochemical analyses could be used as a tool to complement for the lack of air quality data over longer periods of time, allowing for the reconstruction of the temporal trend of trace metals. Our main scopes were to: (a) assess the chemical composition of Quercus mongolica Fisch. ex Ledeb. tree rings from Harbin using a recently developed system of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), (b) identify the main chemical elements which
derived from air pollution and may be used as indicators over the period 1965–2020 in Harbin, while excluding those that were controlled by physiological processes in the tree, and (c) reconstruct the history of pollution in Harbin by comparing the tree-ring chemical composition of recent decades with that of previous decades, in trees growing in the highly polluted city of Harbin and in trees growing in a control site 90 km away from major pollution sources.

Briefly, the temporal trend of some elements was influenced by physiological factors, by environmental factors such as pollution, or influenced by both. Mg, K, Zn, Cu, Ni, Pb, As, Sr and Tl showed changes in pollution levels over time.

air-pollution

display_name: air-pollution

dendrochemistry

display_name: dendrochemistry

dendrochronology

display_name: dendrochronology

laser-ablation

display_name: laser-ablation

tree-rings

display_name: tree-rings

en: Tree-ring laser ablation data


en: perialpine-lakes climate-change lake-level-regulation hydrologic-and-hydrodynamic-modelling switzerland

en: Lake water level scenarios CH2018

en: Lake water level scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

format: XLS

en: Lake characteristics

en: Lake characteristics: stage-area relation for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun, stage-discharge relations for the unregulated Lake Walen and semi-regulated Lake Brienz and, lake level management rules for the two regulated lakes Zurich and Thun.

en: Lake outflow scenarios CH2018

en: Lake outflow scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en:
The dataset "Lake_climate_change_scenarios_CH2018" provides simulation-based climate change impact scenarios for perialpine lakes in Switzerland. These transient future scenarios were produced by combining the hydrologic model PREVAH with the hydrodynamic model MIKE11 to simulate daily lake water level (Lake_water_level_scenarios_CH2018.xls) and outflow scenarios (Lake_outflow_scenarios_CH2018.xls) from 1981 to 2099, using the Swiss Climate Change Scenarios CH2018. The future scenarios contain a total of 39 model members for three Representative Concentration Pathways, RCP2.6 (concerted mitigation efforts), RCP4.5 (limited climate mitigation) and RCP8.5 (no climate mitigation measures). These scenarios result from the study titled "Lower summer lake levels in regulated perialpine lakes, caused by climate change," authored by Wechsler et al. in 2023.

The dataset emphasizes four specific Swiss lakes, each subject to different degrees of lake level management: an unregulated lake (Lake Walen), a semi-regulated lake (Lake Brienz), and two regulated lakes (Lake Zurich and Lake Thun).

In addition, the file (Lake_characteristics.xlsx) includes data used in the modeling process, encompassing the stage-area relation for the four lakes, stage-discharge relations for the unregulated and semi-regulated lakes, and lake level management rules for the two regulated lakes.

climate-change

display_name: climate-change

hydrologic-and-hydrodynamic-modelling

display_name: hydrologic-and-hydrodynamic-modelling

lake-level-regulation

display_name: lake-level-regulation

perialpine-lakes

display_name: perialpine-lakes

switzerland

display_name: switzerland

educ

en: Education, culture and sport


maintainer: Elisabeth Hafner

en: validation avalanche-hazard-mapping snow satellite avalanche

en: Satellite Avalanche Mapping Validation data and data description

en: 14 shapefiles to be used only together with the data description also provided as a pdf.

en:
Validation points, validation area, ground truth coverage, SPOT 6 avalanche outlines, Sentinel-1 avalanche outlines, Sentinel-2 avalanche outlines, Davos avalanche mapping (DAvalMap) avalanche outlines as shapefiles and a detailed attribute description (DataDescription_EvalSatMappingMethods.pdf).

Coordinate system: CH1903+_LV95

The generation of this dataset is described in detail in:

Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, https://doi.org/10.5194/tc-2020-272, 2021.

avalanche

display_name: avalanche

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

satellite

display_name: satellite

snow

display_name: snow

validation

display_name: validation

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: Satellite avalanche mapping validation data


aerosol-data-davos-wolfgang

title_for_slug: aerosol-data-davos-wolfgang

en: raclets particles drincz aerosol inp ice-nucleation

en: SMPS Dataset Davos Wolfgang

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 Davos Wolfgang.

mimetype: application/x-netcdf

en: OPC-N3 Dataset Davos Wolfgang

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 Davos Wolfgang

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 Davos Wolfgang.

en: OPC GT-526S Dataset Davos Wolfgang

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: DRINCZ Dataset Davos Wolfgang

en: The DRINCZ 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:
Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). 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 (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 (3788 , 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 DRINCZ: 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 minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

aerosol

display_name: aerosol

drincz

display_name: drincz

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

particles

display_name: particles

raclets

display_name: raclets

en: Aerosol Data Davos Wolfgang


maintainer: Mountain Hydrology and Mass Movements

en: windstorm-fatalities lightning-fatalities rockfall-fatalities ice-avalanche-fatalities flood-fatalities debris-flow-fatalities natural-hazard-fatalities landslide-fatalities earthquake-fatalities

en: Natural hazard fatalities per year in Swizterland since 1946.

en:
This dataset contains the number of fatalities due to flood, debris flow, landslide, rockfall, windstorm, lightning, ice avalanche, earthquake and other processes like roof avalanche or lacustrine tsunami for each year since 1946.
The following information is contained (by column and column title):

* year
* total number of hazard fatalities
* number of fatalities by flood (German: Hochwasser, Überschwemmung). Flood includes people drowned in flooded or inundated areas or carried away in streams under high-water conditions.
* number of fatalities by debris flow (German: Murgang).
* number of fatalities by landslide (German: Erdrutsch). Landslide includes people killed by landslides and hillslope debris flows (German: Hangmure).
* number of fatalities by rockfall (German: Steinschlag, Fels- und Bergsturz).
* number of fatalities by windstorm (German: Sturm). Windstorm includes people killed by falling objects or trees during very strong wind conditions and people who drowned in lakes because their boat capsized during such conditions.
* number of fatalities by lightning (German: Blitz).
* number of fatalities by ice avalanche (German: Eislawine).
* number of fatalities by earthquake (German: Erdbeben).
* number of fatalities by other processes like roof avalanche, lacustrine tsunami (German: andere Prozesse wie Dachlawine, Tsunami im See).

The data was collected based on newspaper research. For more information please refer to

_Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747-2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016._

The data collection is financed by the FOEN (with exception of the collection of the avalanche fatalities). The data contains the official statistics of the FOEN on fatalities due to flood, debris flow, landslide, rock fall and avalanche.

Restrictions: The data set is not complete. Only fatalities in or around settlements and on open transportation routes are included. More precisely, fatalities were not collected, when persons exposed themselves to a great danger on purpose. Or fatalities during leisure activities which are connected to a higher risk were not included (this includes e.g. canoeing or river surfing during flood, canyoning, mountaineering, climbing, walking or driving on a closed road).

Fatalities by avalanches are collected at the WSL Institute for Snow and Avalanche Research SLF. You can download the avalanche fatalities per hydrological year [here](https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936) and per calendar year [here](https://www.envidat.ch/dataset/avalanche-fatalities-per-calendar-year-since-1936). For a direct comparison with the fatalities presented here, please download the data set with the calendar years and do not consider fatalities in the backcountry (tour) or in terrain close to ski areas (offpiste).

debris-flow-fatalities

display_name: debris-flow-fatalities

earthquake-fatalities

display_name: earthquake-fatalities

flood-fatalities

display_name: flood-fatalities

ice-avalanche-fatalities

display_name: ice-avalanche-fatalities

landslide-fatalities

display_name: landslide-fatalities

lightning-fatalities

display_name: lightning-fatalities

natural-hazard-fatalities

display_name: natural-hazard-fatalities

rockfall-fatalities

display_name: rockfall-fatalities

windstorm-fatalities

display_name: windstorm-fatalities

educ

en: Education, culture and sport

en: Number of natural hazard fatalities per year in Switzerland since 1946


en: snow alpine3d-simulations switzerland graubunden climate-change

en: Configuration file

en: Simulation data

en: Reference data as well as the 2050 and 2099 scenarios for ARPEGE and ETHZ other RCMs available on demand)

en:
This is the simulation dataset from _"Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland"_, M. Bavay, T. Grünewald, M. Lehning, Advances in Water Resources 55, 4-16, 2013

A model study on the impact of climate change on snow cover and runoff has been conducted for the Swiss Canton of Graubünden. The model Alpine3D has been forced with the data from 35 Automatic Weather Stations in order to investigate snow and runoff dynamics for the current climate. The data set has then been modified to reflect climate change as predicted for the 2021-2050 and 2070-2095 periods from an ensemble of regional climate models.

The predicted changes in snow cover will be moderate for 2021-2050 and become drastic in the second half of the century. Towards the end of the century the snow cover changes will roughly be equivalent to an elevation shift of 800 m. Seasonal snow water equivalents will decrease by one to two thirds and snow seasons will be shortened by five to nine weeks in 2095.

Small, higher elevation catchments will show more winter runoff, earlier spring melt peaks and reduced summer runoff. Where glacierized areas exist, the transitional increase in glacier melt will initially offset losses from snow melt. Larger catchments, which reach lower elevations will show much smaller changes since they are already dominated by summer precipitation.

climate-change

display_name: climate-change

graubunden

display_name: graubunden

snow

display_name: snow

switzerland

display_name: switzerland

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: Alpine3D simulations of future climate scenarios for Graubunden


maintainer: Nander Wever

en: humidity wind-speed wind-direction snow-ice-temperature precipitation-amount snow-depth longwave-radiation shortwave-radiation air-temperature

en: SNOWPACK ini file (old syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: Version 2

en:
Deprecated version. Release notes:

Bug fix: in v1, incoming radiation components were taken from WFJ_Gipfel station, instead of WFJ Versuchsfeld.

en: SNOWPACK ini file (new syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using the new MeteoIO Filter, Generator and Interpolation syntax.

en: Version 4

en:
Deprecated version. Release notes:

Update: dataset extended to 2016-09-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 1

en:
Deprecated version. Release notes:

First release of dataset.

en: All versions

en: Version 5

en:
Deprecated version. Release notes:

Update: using the incoming and outgoing short- and longwave radiation data from the new processing chain from 2010 onwards, filling also data gaps in pre-2010 data.

Update: dataset extended to 2016-10-04T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 3

en:
Deprecated version. Release notes:

Bug fix: in version 2, the undercatch correction was not applied correctly

Bug fix: in version 2, snow lysimeter data was missing for extended periods of time

Update: dataset extended to 2016-01-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Undercatch correction

en: This document describes how the undercatch correction for the Weissfluhjoch measurement site was determined.

en: SNOWPACK sno file

en: This sno-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: Version 6

en:
Deprecated version.

Release notes:

- Missing ISWR for 2009-09-30 and 2010-04-30 has been replaced by data from WFJ Gipfel

This dataset is the basis for the Weissfluhjoch dataset in ESM-SnowMIP (doi: http://dx.doi.org/10.16904/16).

en: Version 7 (current)

en:
Release notes:

Bug fix: in previous versions, snow lysimeter data from September 2010 onwards was erroneously reported for UTC+2, instead of UTC+1 (i.e., reported one hour later than should have been).

Update: dataset extended to 2017-07-11T00:30.

en:
Dataset of meteorological and snowpack measurements from the automatic weather station at Weissfluhjoch, Davos, Switzerland, suitable for driving snowpack models. The dataset contains standard meteorological measurements, and additionally snowpack runoff data from a snow lysimeter. Where possible, data is quality checked and missing data are replaced from backup sensors from the measurement site itself, or (in only a few cases) from the MeteoSwiss weather station at 470 m distance and 150 m above the measurement site.

Publication
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M. Verification of the multi-layer SNOWPACK model with different water transport schemes. 2015. The Cryosphere. Volume 9. 2271-2293. http://dx.doi.org/10.5194/tc-9-2271-2015.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

precipitation-amount

display_name: precipitation-amount

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

snow-ice-temperature

display_name: snow-ice-temperature

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

en: WFJ_MOD: Meteorological and snowpack measurements from Weissfluhjoch, Davos, Switzerland


mosaic-snow-on-sea-ice-data

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

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

en: ALPINE3D setup for MOSAiC

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

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

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

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

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

en: SNOWPACK setup for MOSAiC

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

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

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

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

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

arctic-sea-ice

display_name: arctic-sea-ice

drifting-and-blowing-snow

display_name: drifting-and-blowing-snow

snow-distribution

display_name: snow-distribution

spatial-variability

display_name: spatial-variability

surface-mass-balance

display_name: surface-mass-balance

educ

en: Education, culture and sport

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: MOSAIC Snow on Sea Ice Data


rorcc

maintainer: Tobias Wechsler

title_for_slug: rorcc

en: environmental-flow design-discharge hydropower climate-change run-of-river-power-plants

en: RoRCC

en:
The dataset “RoRCC” consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
-	metadata on the RoR power plants under consideration
-	annual and seasonal production scenarios differentiated into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)
-	annual and seasonal production loss due to environmental flow requirements
-	annual and seasonal the technical increase potential (via design discharge optimisation)
-	annual and seasonal changes in the hydrological cycle for the three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)

en:
The dataset "RoRCC" consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
1) metadata on the RoR power plants under consideration, 2) annual and seasonal production potential scenarios under into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099), 3) annual and seasonal streamflow scenarios, 4) annual and seasonal production loss due to environmental flow requirements, 5) annual and seasonal the technical increase potential (via design discharge optimisation) and 6) annual and seasonal changes in the hydrological cycle.

climate-change

display_name: climate-change

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants


maintainer: Athanasios Nenes

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

en: Predicted cloud droplet number concentrations Weissfluhjoch

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

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

en: CCN data Weissfluhjoch

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

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

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

_Error_code_:

0000: Measurements without error

1000: Period of transient operation after a supersaturation change

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

3000: Irregular values in the room temperature housing the instrument

9999: Missing data

en: Hygroscopicity parameter Weissfluhjoch

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

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

Missing values are indicated by "-999".

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

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

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

ccn

display_name: ccn

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

dmt-ccn-chamber

display_name: dmt-ccn-chamber

hygroscopicity

display_name: hygroscopicity

raclets

display_name: raclets

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

weissfluhjoch

display_name: weissfluhjoch

en: CCN, hygroscopicity, predicted cloud droplet numbers Weissfluhjoch


photogrammetric-drone-data-dorfberg

title_for_slug: photogrammetric-drone-data-dorfberg

en: snow-distribution dsm snow photogrammetry uav drone-data snow-depth-mapping orthophoto

en: Data Access

en:
- 3cm-resolution Orthophoto
- 10cm-resolution DSM
- 10cm-resolution snow depth raster
- original RGB images
- Agisoft Metashape Report

All products are also available as a cloud optimized geotiff.

en: The data was collected with a Wingtra Gen II drone and a Sony RX1R II sensor. In total, 10 flights were conducted at different dates, both in summer and winter. A DSM, an orthophoto, a snow depth raster and the original drone images from every flight are available at a high resolution (10cm and 3cm, respectively).

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow

display_name: snow

snow-depth-mapping

display_name: snow-depth-mapping

snow-distribution

display_name: snow-distribution

uav

display_name: uav

educ

en: Education, culture and sport

en: Photogrammetric Drone Data Dorfberg


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

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