hotelbetten-anz

title_for_slug: hotelbetten-anz

de: gemeinden gastgewerbe kantonzuerich hotelbetriebe bezirke hotellerie betten

de: Hotelbetten [Anz.]

de: Anzahl Hotelbetten im Juni des Erhebungsjahres. Daten des aktuellsten Jahres sind provisorisch!

betten

display_name: betten

gastgewerbe

display_name: gastgewerbe

gemeinden

display_name: gemeinden

hotelbetriebe

display_name: hotelbetriebe

hotellerie

display_name: hotellerie

econ

de: Wirtschaft und Finanzen


krw-wahleranteil-edu

maintainer: Statistisches Amt des Kantons Zürich, Data Shop

title_for_slug: krw-wahleranteil-edu

de: kantonzuerich gemeinden politik kantonsratswahlen bezirke wahlen parteien

label: Übersicht über alle Listen der Kantonsratswahlen

label: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

state: active

type: dataset

de: Kantonsratswahlen: Wähleranteil EDU [%]

media_type: text/csv

format: CSV

mimetype: text/csv

de: Wähleranteil aller Listen der Partei EDU bei den Kantonsratswahlen

bezirke

display_name: bezirke

kantonsratswahlen

display_name: kantonsratswahlen

kantonzuerich

display_name: kantonzuerich

parteien

display_name: parteien

politik

display_name: politik

wahlen

display_name: wahlen

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.

political_level: canton

kanton-zuerich

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: ZH-Kt Statistisches Amt - DCAT Harvester


maintainer: Statistisches Amt des Kantons Zürich, Wahlen & Abstimmungen

de: politik gemeinden abstimmungsergebnisse abstimmungen

label: Webservices für Echtzeit-Ergebnisse am Abstimmungssonntag (Bundesamt für Statistik)

label: Wahlen & Abstimmungen: Aktuelle Vorlagen

de: Abstimmungssonntag vom 19.11.2023

media_type: application/json

format: JSON

mimetype: application/json

de: Abstimmungssonntag vom 12.02.2023

de: Um die Stabilität unserer Server nicht zu gefährden, bitten wir die Konsumenten auf eine Direktverlinkung zu verzichten und stattdessen das File in regelmässigen Abständen auf den eigenen Server herunterzuladen.

de: Abstimmungssonntag vom 22.10.2023

de: Abstimmungssonntag vom 28.01.2024

de: Abstimmungssonntag vom 09.07.2023

de: Abstimmungssonntag vom 12.03.2023

de: Abstimmungssonntag vom 26.09.2021

de: Abstimmungssonntag vom 13.02.2022

de: Abstimmungssonntag vom 25.09.2022

de: Abstimmungssonntag vom 18.06.2023

de: Abstimmungssonntag vom 15.05.2022

de: Abstimmungssonntag vom 26.11.2023

de: Abstimmungssonntag vom 16.04.2023

de: Abstimmungssonntag vom 27.11.2022

de: Abstimmungssonntag vom 28.11.2021

de:
Echtzeitdaten zu in den Gemeinden der Kantone Zürich, Aargau und Graubünden stattfindenden kommunalen und regionalen Volksabstimmungen. Es werden nur diejenigen Geschäfte angezeigt, die von den verantwortlichen Gemeinden erfasst werden.
Die aktuelle Ressource wird ca. sechs bis vier Wochen vor dem Urnengang publiziert und dann täglich aktualisiert. Am Abstimmungstag erfolgt die Aktualisierung in der Regel alle zehn Minuten.

de: Echtzeitdaten am Abstimmungstag – kommunale und regionale Vorlagen


kapitaldienstanteil

title_for_slug: kapitaldienstanteil

name: Statistisches Amt des Kantons Zürich, Data Shop

de: gemeinden bezirke kantonzuerich gemeindefinanzen oeffentlichefinanzen

de: Kapitaldienstanteil [%]

de: Kapitaldienst in Prozent vom laufenden Ertrag. Der Kapitaldienstanteil gibt Auskunft, in welchem Ausmass der laufende Ertrag durch den Zinsendienst und die Abschreibungen belastet ist. Ein hoher Kapitaldienstanteil weist auf einen enger werdenden finanziellen Spielraum hin. Grundlage ist die Konsolidierte Gemeinde. Der Haushalt der Schulgemeinde wird dabei anteilsmässig in den Haushalt der poltischen Gemeinden umgelegt. Umstellung des Rechnungsmodells von HRM1 auf HRM2 ab Rechnungsjahr 2019.

gemeindefinanzen

display_name: gemeindefinanzen

oeffentlichefinanzen

display_name: oeffentlichefinanzen

gove

de: Regierung und öffentlicher Sektor

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


de: kantonzuerich bezirke bevoelkerung haushaltsgroesse haushalt-typ haushalte gemeinden

de: Anteil 6 und mehr Personenhaushalte [%]

de: Anteil Haushalte mit 6 und mehr Personen an allen Privathaushalten

bevoelkerung

display_name: bevoelkerung

haushalt-typ

display_name: haushalt-typ

haushalte

display_name: haushalte

haushaltsgroesse

display_name: haushaltsgroesse

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società


de: bezirke kantonzuerich steuerbareseinkommen gemeinden natuerlichepersonen einkommensstufen

de: Steuerb. Einkommen natürl. Pers. Durchschn. [Fr.]

de: Steuerbares Einkommen Schweiz steuerpflichtiger natürlicher Personen aus der Bundessteuerstatistik. (Durchschnitt).

einkommensstufen

display_name: einkommensstufen

natuerlichepersonen

display_name: natuerlichepersonen

steuerbareseinkommen

display_name: steuerbareseinkommen


de: bevoelkerung bezirke kantonzuerich gemeinden geburten bevoelkerungsbewegungen

de: Geburtenrate [pro 1000 Einw.]

de: Geburtenzahl in Bezug auf die Einwohnerzahl (gemäss Kantonaler Erhebung) Ende des vorhergehenden Jahres pro 1000 Einw. Beispiel: Die Geburten 2003 beziehen sich auf die Einwohnerzahl von Ende 2002.

bevoelkerungsbewegungen

display_name: bevoelkerungsbewegungen

geburten

display_name: geburten

gemeinden

display_name: gemeinden


vza-im-primarsektor-anz

title_for_slug: vza-im-primarsektor-anz

de: wirtschaftssektor kantonzuerich gemeinden beschaeftigte bezirke landwirtschaft arbeitsmarkt

de: VZÄ im Primärsektor [Anz.]

de: Beschäftigung des Primärsektors (Land- und Forstwirtschaft) in Vollzeitäquivalenten. Aktuellstes Jahr provisorisch. Ab 2015 Berechnung mit neuem Modell, was in Bezug auf die VZÄ zu einem Bruch in der Zeitreihe zwischen 2014 und 2015 führt. Werte < 4 werden nicht ausgewiesen.

arbeitsmarkt

display_name: arbeitsmarkt

beschaeftigte

display_name: beschaeftigte

bezirke

display_name: bezirke

landwirtschaft

display_name: landwirtschaft

wirtschaftssektor

display_name: wirtschaftssektor


name: Statistisches Amt des Kantons Zürich, Wahlen & Abstimmungen

de: nationalrat kantonsrat regierungsrat staenderat regierungsratswahlen kantonsratswahlen staenderatswahlen nationalratswahlen

label: Übersicht über die Testdatenstände 22.10.2023

label: Übersicht über die Testdatenstände 19.11.2023

de: Wahlsonntag vom 12.02.2023

de:
Kantons- und Regierungsratswahl
Um die Stabilität unserer Server nicht zu gefährden, bitten wir die Konsumentinnen und Konsumenten auf eine Direktverlinkung zu verzichten und stattdessen das File in regelmässigen Abständen auf den eigenen Server herunterzuladen.

de: Wahlsonntag vom 22.10.2023

de:
National- und Ständeratswahl
Um die Stabilität unserer Server nicht zu gefährden, bitten wir die Konsumentinnen und Konsumenten auf eine Direktverlinkung zu verzichten und stattdessen das File in regelmässigen Abständen auf den eigenen Server herunterzuladen.

de: Wahlsonntag vom 19.11.2023

de: Echtzeitdaten zu den im Kanton Zürich stattfindenden Wahlen. Am Wahlsonntag, ab der Schliessung der letzten Urnen um 12 Uhr, erfolgt die Aktualisierung ca. alle 15 Minuten.

kantonsrat

display_name: kantonsrat

kantonsratswahlen

display_name: kantonsratswahlen

nationalrat

display_name: nationalrat

nationalratswahlen

display_name: nationalratswahlen

regierungsrat

display_name: regierungsrat

regierungsratswahlen

display_name: regierungsratswahlen

staenderat

display_name: staenderat

staenderatswahlen

display_name: staenderatswahlen

gove

de: Regierung und öffentlicher Sektor

de: Echtzeitdaten am Wahltag des Kantons Zürich


geb-vol-wohnen-anteil

title_for_slug: geb-vol-wohnen-anteil

de: gebaeude bautaetigkeit bezirke kantonzuerich gebaeudeart gemeinden

de: Geb.Vol. Wohnen: Anteil [%]

de: Approximatives Gebäudevolumen von Wohnbauten (exkl. Anteil Fremdnutzungen in Wohnbauten)

bautaetigkeit

display_name: bautaetigkeit

gebaeude

display_name: gebaeude

gebaeudeart

display_name: gebaeudeart

kantonzuerich

display_name: kantonzuerich

soci

de: Bevölkerung und Gesellschaft

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


de: bauland bezirke kantonzuerich gemeinden bodenpreise

label: Infoseite zu Bodenpreise inkl. interaktivem Rechner

de: Baulandpreis Modell (Median) [Fr./m2]

de: Bodenpreismodell: Median der Modellpreise von unbebautem Land der Wohn- und Mischzone inkl. Abbruchliegenschaften. Die Modellpreise werden jährlich für den gesamten ausgewiesenen Zeitraum neu berechnet und aktualisiert.

bauland

display_name: bauland

bodenpreise

display_name: bodenpreise

gemeinden

display_name: gemeinden

econ

de: Wirtschaft und Finanzen


leerwohnungen-total-anz

title_for_slug: leerwohnungen-total-anz

de: bezirke kantonzuerich zimmerzahl wohnungen wohnungsbestand gemeinden

de: Leerwohnungen Total [Anz.]

de: Leerstehende Wohnungen am 1. Juni des Erhebungsjahres

bezirke

display_name: bezirke

wohnungen

display_name: wohnungen

wohnungsbestand

display_name: wohnungsbestand

zimmerzahl

display_name: zimmerzahl


de: gemeinden altersstruktur kantonzuerich bezirke bevoelkerung alter

de: Bevölkerung: Anteil 0-14-Jährige [%]

de: Anteil 0-14-Jähriger an der Gesamtbevölkerung nach zivilrechtlichem Wohnsitz (ab 2010 inkl. vorläufig Aufgenommene, die seit mehr als einem Jahr in der Gemeinde leben, aber ohne Wochenaufenthalter und Asylbewerber).

alter

display_name: alter

altersstruktur

display_name: altersstruktur

bevoelkerung

display_name: bevoelkerung


total-beschaftigte-anz

title_for_slug: total-beschaftigte-anz

de: gemeinden kantonzuerich arbeitsmarkt bezirke beschaeftigte

de: Total Beschäftigte [Anz.]

de: Anzahl Beschäftigte des Primär-, des Sekundär- und des Tertiärsektors. Aktuellstes Jahr provisorisch.

arbeitsmarkt

display_name: arbeitsmarkt

beschaeftigte

display_name: beschaeftigte


de: bevoelkerung haushaltsgroesse haushalt-typ gemeinden haushalte kantonzuerich bezirke

de: Anteil 5-Personenhaushalte [%]

de: Anteil Fünfpersonenhaushalte an allen Privathaushalten

haushalt-typ

display_name: haushalt-typ

haushalte

display_name: haushalte

haushaltsgroesse

display_name: haushaltsgroesse


de: schulen gemeinden berufsschule kantonzuerich schuelerinnen schueler bezirke

de: Schül. Berufsschule [pro 1000 Einw.]

de: Anzahl BerufsschülerInnen gemessen an der zivilrechtlichen Bevölkerung Ende Vorjahr

berufsschule

display_name: berufsschule

schueler

display_name: schueler

schuelerinnen

display_name: schuelerinnen

schulen

display_name: schulen

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


krw-wahleranteil-svp

title_for_slug: krw-wahleranteil-svp

de: bezirke wahlen nationalratswahlen parteien kantonzuerich politik gemeinden

de: Kantonsratswahlen: Wähleranteil SVP [%]

de: Wähleranteil aller Listen der Partei SVP bei den Kantonsratswahlen

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

nationalratswahlen

display_name: nationalratswahlen

parteien

display_name: parteien

politik

display_name: politik

wahlen

display_name: wahlen

gove

de: Regierung und öffentlicher Sektor


nrw-wahleranteil-svp

title_for_slug: nrw-wahleranteil-svp

de: politik gemeinden wahlen nationalratswahlen bezirke parteien kantonzuerich

label: Übersicht über alle Listen der Nationalratswahlen

de: Nationalratswahlen: Wähleranteil SVP [%]

de: Wähleranteil aller Listen der Partei SVP bei den Nationalratswahlen

bezirke

display_name: bezirke


de: gemeinden nettoaufwendungen gemeindeverwaltung gemeindefinanzen oeffentlichefinanzen bezirke kantonzuerich

de: Nettoaufwand allgemeine Verwaltung [Fr./Einw.]

de: Bruttoaufwand - Bruttoertrag (der Laufenden Rechnung). Aussage: Durch Steuern zu finanzierender Anteil des betreffenden Hauptaufgabenbereichs. Grundlage ist die Konsolidierte Gemeinde. Der Haushalt der Schulgemeinde wird dabei anteilsmässig in den Haushalt der poltischen Gemeinden umgelegt. Umstellung des Rechnungsmodells von HRM1 auf HRM2 ab Rechnungsjahr 2019.

gemeindefinanzen

display_name: gemeindefinanzen

gemeindeverwaltung

display_name: gemeindeverwaltung

nettoaufwendungen

display_name: nettoaufwendungen

oeffentlichefinanzen

display_name: oeffentlichefinanzen

econ

de: Wirtschaft und Finanzen


de: kantonzuerich gemeindefinanzen oeffentlichefinanzen bezirke nettoaufwendungen gemeinden

de: Nettoaufwand Umweltschutz und Raumordnung [Fr./Einw.]


de: bauinvestitionen bautaetigkeit bezirke entsorgung gemeinden kantonzuerich

de: Bauinv. Ver-/Entsorg. 5 Jahre [Fr./Einw.]

de: Durchschnittliche Bauinvestitionen der letzten 5 Jahre im Bereich Ver- und Entsorgung (Bauinv. für Ver- und Entsorgung), in Franken pro Einwohner.

bauinvestitionen

display_name: bauinvestitionen

bautaetigkeit

display_name: bautaetigkeit

entsorgung

display_name: entsorgung

soci

de: Bevölkerung und Gesellschaft


krw-wahleranteil-al

title_for_slug: krw-wahleranteil-al

de: gemeinden parteien kantonzuerich bezirke kantonsratswahlen politik wahlen

de: Kantonsratswahlen: Wähleranteil FGA/AL/PDA [%]

de: Wähleranteil aller Listen der Parteien FGA/AL/PDA bei den Kantonsratswahlen

kantonsratswahlen

display_name: kantonsratswahlen

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


scheidungen-anz

title_for_slug: scheidungen-anz

de: bevoelkerung ehe scheidung bezirke kantonzuerich ehescheidung gemeinden

de: Scheidungen [Anz.]

de: Anzahl Scheidungen. Hinweise: Am 1.Januar 2000 trat das neue Scheidungsrecht in Kraft. Ab 2011 Wechsel der Datenquelle: Es werden nicht mehr alle Scheidungen von zwei ausländischen Personen ausgewiesen.

bevoelkerung

display_name: bevoelkerung

ehe

display_name: ehe

ehescheidung

display_name: ehescheidung

scheidung

display_name: scheidung


de: politischegemeinden wahlen politischeparteien wahlergebnisse kantonzuerich gemeindewahlen politik gemeinden

label: Gemeindewahlen

de: Ergebnisse der Erneuerungswahlen der Zürcher Gemeindeparlamente. Abgebildet sind sämtliche über die den Gemeinden vom Kanton Zürich zur Verfügung gestellte Wahl- und Abstimmungssoftware abgewickelten Gemeindeparlamentswahlen 2022. Gemeinden sind nicht verpflichtet, die Wahlen mit besagter Software abzuwickeln. Ausserdem ist es möglich, dass gewählte Personen die Wahl ablehnen. Der rechtskräftig gewordene Ausgang einer Wahl wird lediglich von der entsprechenden Gemeinde publiziert.

format: XLS

de: Ergebnisse der kommunalen Parlamentswahlen 2022 auf Ebene Kandidierende

de: Ergebnisse der kommunalen Parlamentswahlen 2022 auf Ebene Listen

de: Dokumentation Gemeindeparlamentswahlen

de: Erklärungen und Definitionen der einzelnen Variablen für die Ressourcen dieses Datensatzes

gemeinden

display_name: gemeinden

gemeindewahlen

display_name: gemeindewahlen

kantonzuerich

display_name: kantonzuerich

politischegemeinden

display_name: politischegemeinden

politischeparteien

display_name: politischeparteien

wahlergebnisse

display_name: wahlergebnisse

gove

de: Regierung und öffentlicher Sektor

de: Archiv Wahlresultate Gemeindeparlamentswahlen im Kanton Zürich


anteil-jur-pers-an-allg-gemeindesteuern

title_for_slug: anteil-jur-pers-an-allg-gemeindesteuern

de: juristischepersonen kantonzuerich gemeinden gemeindesteuern bezirke gemeindefinanzen steuern

de: Anteil jur. Pers. an allg. Gemeindesteuern [%]

de: Anteil der juristischen Personen an den allg. Gemeindesteuern (Nettoertrag Rechnungsjahr).

bezirke

display_name: bezirke

gemeindefinanzen

display_name: gemeindefinanzen

gemeindesteuern

display_name: gemeindesteuern

juristischepersonen

display_name: juristischepersonen

steuern

display_name: steuern

econ

de: Wirtschaft und Finanzen


schweine-anz

title_for_slug: schweine-anz

de: nutztiere kantonzuerich gemeinden viehbestand bezirke landwirtschaft

de: Schweine [Anz.]

de: Anzahl Schweine

landwirtschaft

display_name: landwirtschaft

nutztiere

display_name: nutztiere

viehbestand

display_name: viehbestand

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

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


nrw-wahleranteil-sp

title_for_slug: nrw-wahleranteil-sp

de: parteien gemeinden nationalratswahlen kantonzuerich bezirke politik wahlen

de: Nationalratswahlen: Wähleranteil SP [%]

de: Wähleranteil aller Listen der Partei SP bei den Nationalratswahlen

nationalratswahlen

display_name: nationalratswahlen

parteien

display_name: parteien

politik

display_name: politik

wahlen

display_name: wahlen

statistisches-amt-kanton-zuerich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


restaurants-anz

title_for_slug: restaurants-anz

de: kantonzuerich gemeinden gastgewerbe betriebe bezirke

de: Restaurants [Anz.]

de: Anzahl Restaurants, Imbissstuben, Tea-Rooms und Gelaterias inkl. Restaurants mit begrenzten Übernachtungsmöglichkeiten (2008: NOGA2008 561001 und 561002; bis 2005: NOGA2002 HA 553). Bruch in der Reihe zwischen 2008 und 2011 aufgrund des Übergangs von der alten BZ-Methodik auf STATENT. Daten des aktuellsten Jahres provisorisch.

betriebe

display_name: betriebe

gastgewerbe

display_name: gastgewerbe

gemeinden

display_name: gemeinden


beschaftigte-im-tertiarsektor-anz

title_for_slug: beschaftigte-im-tertiarsektor-anz

de: dienstleistungssektor bezirke kantonzuerich arbeitsmarkt gemeinden beschaeftigte wirtschaftssektor

de: Beschäftigte im Tertiärsektor [Anz.]

de: Anzahl Beschäftigte des Tertiärsektors (Handel, Instandhaltung/Reparatur, Verkehr/Lagerei, Gastgewerbe/Gastronomie, Information/Kommunikation, Finanz-/Versicherungs-DL, Grundstücks-/Wohnungswesen, weitere DL, öffentliche Verwaltung, Erziehung/Unterrricht, Gesundheit, Kunst). Aktuellstes Jahr provisorisch.

arbeitsmarkt

display_name: arbeitsmarkt

beschaeftigte

display_name: beschaeftigte

dienstleistungssektor

display_name: dienstleistungssektor

kantonzuerich

display_name: kantonzuerich

wirtschaftssektor

display_name: wirtschaftssektor


zuzuge-pers

title_for_slug: zuzuge-pers

de: bezirke zuzuege-wegzuege bevoelkerung kantonzuerich wanderungen gemeinden

de: Zuzüge [Pers.]

de: Anzahl zugezogene Personen. Hinweis: Ab 2011 Wechsel des Produktionsverfahrens und neue Definition der ständigen Wohnbevölkerung, die zusätzlich Personen im Asylprozess mit einer Gesamtaufenthaltsdauer von mindestens 12 Monaten umfasst. Inkl. innerkantonaler Wanderungen.

bevoelkerung

display_name: bevoelkerung

bezirke

display_name: bezirke

wanderungen

display_name: wanderungen

zuzuege-wegzuege

display_name: zuzuege-wegzuege

soci

de: Bevölkerung und Gesellschaft


bauzonen-ha

title_for_slug: bauzonen-ha

de: kantonzuerich zonenart bodennutzung bauzonen gemeinden bezirke

de: Bauzonen [ha]

de: Total Bauzonenfläche

bauzonen

display_name: bauzonen

bodennutzung

display_name: bodennutzung

zonenart

display_name: zonenart


neu-gegrundete-unternehmen-total-anz

title_for_slug: neu-gegrundete-unternehmen-total-anz

de: kantonzuerich gemeinden bezirke unternehmensstruktur unternehmen

de: Neu gegründete Unternehmen Total [Anz.]

de: Neu gegründete Unternehmen (2. und 3. Sektor). Die Statistik der Neugründungen erfasst nur tatsächlich - also «ex nihilo» - neu entstandene Unternehmen mit marktwirtschaftlicher Tätigkeit. Aus Fusionen, Übernahmen, Spaltungen oder Restrukturierungen hervorgegangene Unternehmen werden folglich nicht berücksichtigt. Werte < 4 werden nicht ausgewiesen.

unternehmen

display_name: unternehmen

unternehmensstruktur

display_name: unternehmensstruktur

econ

de: Wirtschaft und Finanzen

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


bevolkerung-durchschnittsalter-jahre

title_for_slug: bevolkerung-durchschnittsalter-jahre

de: bezirke bevoelkerungsstatistik bevoelkerung kantonzuerich altersstruktur alter gemeinden

de: Bevölkerung: Durchschnittsalter [Jahre]

de: Durchschnittsalter Ende Jahr (zivilrechtlicher Wohnsitz; ab 2010 inkl. vorläufig Aufgenommene, die seit mehr als einem Jahr in der Gemeinde leben, aber ohne Wochenaufenthalter und Asylbewerber).

alter

display_name: alter

altersstruktur

display_name: altersstruktur

bevoelkerungsstatistik

display_name: bevoelkerungsstatistik

statistisches-amt-kanton-zuerich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


jugendquotient

title_for_slug: jugendquotient

de: alter gemeinden kantonzuerich bezirke altersstruktur bevoelkerung

de: Jugendquotient [%]

de: Quantitatives Verhältnis zwischen den 0- bis 19-Jährigen und den 20- bis 64-Jährigen.

gemeinden

display_name: gemeinden


de: vermoegen natuerlichepersonen gemeinden steuerbaresvermoegen kantonzuerich bezirke

de: Steuerb. Vermögen natürl. Pers. 75%-Quantil [Fr.]

de: Steuerbares Vermögen natürlicher Personen des Kantonalen Steueramts. Das 75%-Quantil ist ein Schwellenwert: Drei Viertel der Bevölkerung liegt unter, das andere Viertel über diesem Wert.

natuerlichepersonen

display_name: natuerlichepersonen

steuerbaresvermoegen

display_name: steuerbaresvermoegen

vermoegen

display_name: vermoegen

gove

de: Regierung und öffentlicher Sektor


de: Steuererträge nach Vermögensklassen

de: Steuererträge nach Einkommensklassen

de: Die Basis für die Berechnung der approximativen Steuererträge bildet das steuerbare Einkommen gemäss Bundessteuer. Das steuerbare Einkommen gemäss Bundesteuer kann aufgrund unterschiedlicher Abzüge von dem für die Staats- und Gemeindesteuer massgebenden Einkommen abweichen. Für die unterschiedlich hohen Kinderabzüge wurde eine Korrektur vorgenommen. Für andere Positionen werden keine Korrekturen vorgenommen (z.B. Berufsauslagen).

de: Steuerertrag nach Einkommens- und Vermögensklassen auf Basis der Bundessteuerdaten des kantonalen Steueramts.

einkommensverteilung

display_name: einkommensverteilung

steuerbareseinkommen

display_name: steuerbareseinkommen

steuerertrag

display_name: steuerertrag

de: Steuererträge nach Einkommens- und Vermögensklassen


maintainer: EnviDat Support

en: incoming davos longwave-radiation outgoing shortwave-radiation

en: Metadata

media_type: application/pdf

format: PDF

mimetype: application/pdf

en: Parameter file

media_type: text/plain

format: TXT

mimetype: text/plain

en: Processing doc

en: DATA ACCESS

format: SERVICE

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

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

davos

display_name: davos

incoming

display_name: incoming

longwave-radiation

display_name: longwave-radiation

outgoing

display_name: outgoing

shortwave-radiation

display_name: shortwave-radiation

educ

de: Bildung, Kultur und Sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

value: Envidat Harvester

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


en: research-data-management raster gridded-data sentinel-2 time-series video-encoding geodata core

en:
Shell script to extract data from the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en: View publication in the Digital Object Repository at WSL (DORA)

media_type: text/html

format: HTML

en: CORE Dataset (80 GB)

en:
Shell script to reproduce the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software for working with CORE will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en:
DISCLAIMER: CORE is still in development. Interested parties are warmly invited to join common development, to comment, discuss, find bugs, etc.

Acknowledgement: The CORE format was proudly inspired by the Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) format, by considering how to leverage the ability of clients issuing HTTP GET range requests for a time-series of remote sensing and aerial imagery (instead of just one image).

License: The Cloud Optimized Raster Encoding (CORE) specifications are released to the public domain under a Creative Commons 1.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

-----------------------

Summary:
The Cloud Optimized Raster Encoding (CORE) format is being developed for the efficient storage and management of gridded data by applying video encoding algorithms. It is mainly designed for the exchange and preservation of large time series data in environmental data repositories, while in the same time enabling more efficient workflows on the cloud. It can be applied to any large number of similar (in pixel size and image dimensions) raster data layers. CORE is not designed to replace COG but to work together with COG for a collection of many layers (e.g. by offering a fast preview of layers when switching between layers of a time series).

WARNING: Currently only applicable to RGB/Byte imagery. The final CORE specifications may probably be very different from what is written herein or CORE may not ever become productive due to a myriad of reasons (see also 'Major issues to be solved').

With this early public sharing of the format we explicitly support the Open Science agenda, which implies "shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process" (quote from: European Commission, Directorate General for Research and Innovation, 2016. Open innovation, open science, open to the world).

CORE Specifications:

1) a MP4 or WebM video digital multimedia container format (or any future video container playable as HTML video in major browsers)

2) a free to use or open video compression codec such as H.264, VP9, or AV1 (or any future video codec that is open sourced or free to use for end users)

Note: H.264 is currently recommended because of the wide usage with support in all major browsers, fast encoding due to acceleration in hardware (which is currently not the case for AV1 or VP9) and the fact that MPEG LA has allowed the free use for streaming video that is free to the end users. However, please note that H.264 is restricted by patents and its use in proprietary or commercial software requires the payment of royalties to [MPEG LA](https://www.mpegla.com/programs/avc-h-264/). However, when AV1 matures and accelerated hardware encoding becomes available, AV1 is expected to offer 30% to 50% smaller file size in comparison with H.264, while retaining the [same quality](https://trac.ffmpeg.org/wiki/Encode/AV1).

3) the encoding frame rate should be of one frame per second (fps) with each layer segmented in internal tiles, similar to COG, ordered by the main use case when accessing the data: either layer contiguous or tile contiguous;

Note: The internal tile arrangement should support an easy navigation inside the CORE video format, depending on the use case.

4) a CORE file is optimised for streaming with the moov atom at the beginning of the file (e.g. with -movflags faststart) and optional additional optimisations depending on the codec used (e.g. -tune fastdecode -tune zerolatency for H.264)

5) metadata tags inside the moov atom for describing and using geographic image data (that are preferably compatible with the [OGC GeoTIFF standard](https://www.ogc.org/standards/geotiff) or any future standard accepted by the geospatial community) as well as list of original file names corresponding to each CORE layer

6) it needs to encode similar source rasters (such as time series of rasters with the same extent and resolution, or different tiles of the same product; each input raster should be having the same image and pixel size)

7) it provides a mechanism for addressing and requesting overviews (lower resolution data) for a fast display in web browser depending on the map scale (currently external overviews)

Major issues to be solved:

- Internal overviews (similar to COG), by chaining lower resolution videos in the same MP4 container for fast access to overviews first); Currently, overviews are kept as separate files, as external overviews.

- Metadata encoding (how to best encode spatial extent, layer names, and so on, for each of the layer inside the series, which may have a different geographical extent, etc...; Known issues: adding too many tags with FFmpeg which are not part of the standard MP4 moov atom; metadata tags have a limited string length.

- Applicability beyond RGB/Byte datasets; defining a standard way of converting cell values from Int16/UInt16/UInt32/Int32/Float32/Float64/ data types into multi-band Byte values (and reconstructing them back to the original data type within acceptable thresholds)

Example

Notice: The provided CORE (.mp4) examples contain modified Copernicus Sentinel data [2018-2021].

For generating the CORE examples provided, 50 original Sentinel 2 (S-2) TCI data images from an area located inside Switzerland were downloaded from www.copernicus.eu, and then transformed into CORE format using ffmpeg with H.264 encoding using the [x264 library](https://www.videolan.org/developers/x264.html).

For full reproducibility, we provide the original data set and results, as well scripts for data encoding and extraction (see resources).

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

research-data-management

display_name: research-data-management

time-series

display_name: time-series

video-encoding

display_name: video-encoding


maintainer: Avalanche Warning Service SLF

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

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

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

educ

en: Education, culture and sport

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


en: growing-season-length temperature soil-water-balance solar-radiation relative-humidity growing-degree-days precipitation

en: CHELSA-BIOCLIM+ Technical Documentation

en: Technical documentation document including the variable names, units, scaling, offset, and background.

en: CHELSA-BIOCLIM+

en: Global extented set of bioclimatic variables at different temporal (e.g. monthly, annual, long term normals) resolution in Geotiff format.

format: GeoTIFF

en: A multitude of physical and biological processes on which ecosystems and human societies depend are governed by climatic conditions. Understanding how these processes are altered by climate change is central to mitigation efforts. Based on mechanistically downscaled climate data, we developed a set of climate-related variables at yet unprecedented spatiotemporal detail as a basis for environmental and ecological analyses. We created gridded data for near-surface relative humidity (hurs), cloud area fraction (clt), near-surface wind speed (sfcWind), vapour pressure deficit (vpd), surface downwelling shortwave radiation (rsds), potential evapotranspiration (pet), climate moisture index (cmi), and site water balance (swb), at a monthly temporal and 30 arcsec spatial resolution globally starting 1980 until 2018. At the same spatial resolution, we further estimated climatological normals of frost change frequency (fcf), snow cover days (scd), potential net primary productivity (npp), growing degree days (gdd), and growing season characteristics for the periods 1981-2010, 2011-2040, 2041-2070, and 2071-2100, considering three shared socioeconomic pathways (SSP126, SSP370, SSP585) and five Earth system models. Time-series variables showed high accuracy when validated against observations from meteorological stations. Climatological normals were also highly correlated to observations although some variables showed notable biases, e.g., snow cover days (scd). Together, the data sets presented here allow improving our understanding of patterns and processes that are governed by climate, including the impact of recent and future climate changes on the world’s ecosystems and associated services to societies.

growing-degree-days

display_name: growing-degree-days

growing-season-length

display_name: growing-season-length

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

soil-water-balance

display_name: soil-water-balance

solar-radiation

display_name: solar-radiation

temperature

display_name: temperature

en: CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution


en: compression-experiments snow x-ray-tomography snow-mechanics microstructure

en: Snowmicroquakes Data

en: Compression experiments, X-ray images and simulation data with supplemented README file

en: README

en: README file explaining the organization of the data

en:
When snow is compressed with a certain speed, micro-snowquakes are triggered in the porous structure of bonded crystals. The present dataset covers uniaxial compression experiments of snow at different strain rates and concurrent X-ray tomography imaging documenting this feature.

The experiments were conducted in a micro-compression stage operated in the X-ray tomography scanner in the SLF cold laboratory. The dataset comprises the compression force data of 17 compression experiments, the 3D image data from 4 X-ray tomography scans and the results of numerical simulations.

compression-experiments

display_name: compression-experiments

microstructure

display_name: microstructure

snow

display_name: snow

snow-mechanics

display_name: snow-mechanics

x-ray-tomography

display_name: x-ray-tomography

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: Compressive stick slip and snow-micro-quakes


snow-drift-station-micro-rain-radar

title_for_slug: snow-drift-station-micro-rain-radar

en: raclets radar snow rain mountain precipitation

en: Parameter MRR

en: The PDF contains additional information on parameters which were set for the certain time periods (time in UTC).

en: MRR data of period 4

media_type: application/zip

en: The dataset contains measurements between March 13 and March 22, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

format: ZIP

mimetype: application/zip

en: MRR data of period 3

en: The dataset contains measurements between March 8 and March 13, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en: MMR Data Period 1

en: The dataset contains measurements between March 1 and March 5, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en: MRR data Period 2

en: The dataset contains measurements between March 5 and March 8, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en: The instrument (MRR, Metek) was mounted at Gotschnagrat (LON: 46.859 LAT: 9.849) at a height of 1 m above snow surface (at the beginning of the campaign) with an orientation of 22° with respect to North and a horizontal viewing direction. The sampling time was either 5 s or 10 s, depending on the settings at the specific period. The MRR produces standard outputs like radar reflectivity, doppler velocity, etc., and additional information can be found [here](https://metek.de/de/product/mrr-2/).

mountain

display_name: mountain

raclets

display_name: raclets

radar

display_name: radar

rain

display_name: rain

educ

en: Education, culture and sport

en: Snow Drift Station - Micro Rain Radar


maintainer: Ionut Iosifescu Enescu

en: hpc open-source reproducibility open-science jupyter-notebooks research-data-management open-data

en: Open Science Support @ WSL (Poster)

en:
This poster was originally created for the swissuniversities Open Science Action Plan: Kick-Off Forum, and showed to the audience on 17.10.2019. It illustrates how the environmental data portal EnviDat provides the tools for fostering Open Science and Reproducibility of scientific research at WSL.

Supporting open science is a highly relevant user requirement for EnviDat and for implementing FAIR (Findability, Accessibility, Interoperability and Reusability) principles at dataset level.
EnviDat encourages WSL scientists to complement data publication with a complete description of research methods and the inclusion of the open source software, code or scripts used for processing the dataset or for obtaining the published results. By openly publishing open software (e.g. as Jupyter notebooks) alongside research data sets, researchers can contribute to mitigate reproducibility issues.

EnviDat also promotes and supports, where possible and practical, the publication of software as Jupyter notebooks. Jupyter notebooks provide a solution for improved documentation and interactive execution of open code in a wide range of programming languages (Python, R, Octave/Matlab, Java or Scala). These programming languages are widely used in environmental research at WSL and well supported by the Jupyter-compatible kernels. We have sucessfully interfaced EnviDat-hosted notebooks with the WSL High-Performance Computing (HPC) Linux Cluster through a JupyterHub/JuypterLab beta installation on the HPC cluster implemented in close collaboration with the WSL IT-Services.
For existing software that cannot be easily migrated to Jupyter Notebooks, the Open Science and Reproducibility is assisted by containerisation. We have proven that several Singularity containers can successfully run on WSL's HPC cluster.

Finally, the researchers can upload the data/results complemented by code (e.g. as Jupyter Notebooks, or Singularity containers) and any additional documentation in EnviDat. Consequently, they will receive a DOI for the entire dataset, which they can reference in their science paper in order to publish a more reproducible research.

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

hpc

display_name: hpc

jupyter-notebooks

display_name: jupyter-notebooks

open-data

display_name: open-data

open-science

display_name: open-science

open-source

display_name: open-source

reproducibility

display_name: reproducibility

research-data-management

display_name: research-data-management

envidat

en: EnviDat: the Environmental Data Portal

en: Open Science Support at the Swiss Federal Research Institute WSL. The EnviDat Concept


maintainer: Dirk Nikolaus Karger

en: free-climate-data climatology bioclim temperature climate-layers precipitation climate climate-change

en: CHELSA V1.2 (deprecated)

en: CHELSA Version 1.2 based on ERA-Interim forcings and CMIP5

en: CHELSA Technical Documentation

en: Technical documentation document including the variable names, units, scaling, offset, and background.

en: CHELSA V2.1 (current)

en: CHELSA Version 2.1 based on ERA5 forcings and CMIP6

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled temperature and precipitation to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction.

CHELSA data published in EnviDat includes the deprecated version 1.2 (originally published under 10.5061/dryad.kd1d4). Please use the current 2.1 version.

Paper Citation:
 > _Karger DN. et al. Climatologies at high resolution for the earth’s land surface areas, Scientific Data, 4, 170122 (2017) [doi: 10.1038/sdata.2017.122](https://doi.org/10.1038/sdata.2017.122)._

bioclim

display_name: bioclim

climate

display_name: climate

climate-change

display_name: climate-change

climate-layers

display_name: climate-layers

climatology

display_name: climatology

free-climate-data

display_name: free-climate-data

precipitation

display_name: precipitation

temperature

display_name: temperature

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: Marco Moretti

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

en: Metadata for the predictor and response dataset

en: Response and predictors used for the SEMs

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

en:
The data contains the following columns:

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

en: Metadata for the predictors and response dataset

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

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

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

beekeeping

display_name: beekeeping

bettergardens

display_name: bettergardens

gardens

display_name: gardens

honeybees

display_name: honeybees

pollinator-experiment

display_name: pollinator-experiment

resource-availability

display_name: resource-availability

urban-biodiversity

display_name: urban-biodiversity

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wild-bees

display_name: wild-bees

zurich

display_name: zurich

en: Niche partitioning between wild bees and honeybees


snow-depth-mapping

maintainer: Mauro Marty

title_for_slug: snow-depth-mapping

en: avalanche snow-hydrology aerial-imagery snow-depth snow-water-equivalent dsm image-matching

en: Snow depth map 20160420

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Snow depth map 20160126

en:
Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m
Because of very diffuse light conditions at time of image acquisition the quality of the resulting snow depth values are in some regions quite poor.

en: Snow depth map 20100416

en: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en: Snow depth map 20150415

en: Snow depth map 20120320

en: Snow depth map 20140417

en: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.18 m

en: Snow depth map 20130415

en: Snow depth map 20160309

en:
The available datasets are snow depth maps with a spatial resolution of 2m generated from image matching of ADS 80/100 data. Image acquisition took place at peak of winter (time when the thickest snowpack is expected). The snow depth maps are the difference of a summer DSM from the winter DSM of the corresponding date . The summer DSM used is a product of image matching of ADS 80 data from summer 2013. In the available products buildings, vegetation and outliers were masked (set to NoData).
For the elimination of buildings the TLM layer (swisstopo) was used, because this layer might not represent exactly the
state of infrastructure at time of image acquisition, it is possible that mainly in dense settlement some buildings were not successfully masked. For the relevant area above treeline the masking of buildings showed good results. Vegetation got masked for a height above ground > 1m and was detected in a combination of summer and winter data sets. As Outliers were considered unrealistic snow depths caused by a failure of the image matching algorithm. Snow depths > 15m and smaller than < -15m were classified as outliers. Negative snow depth were kept, because of an uncertainty in image orientation accuracy. It is expected that in regions with negative snow depth also positive snow depth are underestimated by the same amount, which means that an estimation of snow volume should be carried out summing up the absolute values of snow depth (also the negative ones). For volume estimation in small regions the user has to take into account, that orientation accuracy of the images is roughly around 1-2 GSD (30cm), which propagates directly to the snow depth product. Areas which are not covered by snow got assigned a value of 0 as snow depth.

The work is published in:

Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C., (2015). Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9 (1), 229-243. doi: 10.5194/tc-9-229-2015

aerial-imagery

display_name: aerial-imagery

avalanche

display_name: avalanche

dsm

display_name: dsm

image-matching

display_name: image-matching

snow-depth

display_name: snow-depth

snow-hydrology

display_name: snow-hydrology

snow-water-equivalent

display_name: snow-water-equivalent

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal


en: mars sediment-transport snow erosion model

en: Datasets of Figure 2

en: Datasets of Figure 4a

en: Datasets of Figure 4b

en: Datasets of Figure 3b

en: Datasets of Figure 3a

en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).

 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow

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: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation


en: wind radiation temperature-profiles precipitation atmospheric-conditions

en: Site photo 2

en: This site photo is outdated and has been replaced with an updated version (see description).

en: Site photo 1

en: README

en: This description is outdated and has been replaced with an updated version (see description).

en: Latest data from Stillberg climate station

en: This dataset is outdated and has been replaced with an updated version (see description).

en: DATA ACCESS

en: This data access is outdated and has been replaced with an updated version (see description).

en: Overview plot

media_type: image/png

en: This overview plot is outdated and has been replaced with an updated version (see description).

format: PNG

en: STB2 CSV

en: Site photo 3

en:
 Important

This EnviDat entry is outdated. The most recent, usable version of the data can be found under the new EnviDat entry "Long-term meteorological station Stillberg, Davos, Switzerland at 2090 m a.s.l.." The entry can be found under this link <https://www.envidat.ch/dataset/meteo-stillberg> and with this DOI https://doi.org/10.16904/envidat.396.

atmospheric-conditions

display_name: atmospheric-conditions

precipitation

display_name: precipitation

radiation

display_name: radiation

temperature-profiles

display_name: temperature-profiles

wind

display_name: wind

en: Long-term meteorological and snow station at 2090 m a.s.l., Stillberg, Davos, Switzerland (1975 - present)


maintainer: Yohann Chauvier

en: ecoregions large-scale accepted-name taxonomy r-package flags conservation gbif landsca species-distribution range-maps occurrence-records filtering hard-limit synonyms species-observations

en: gbif.range R package version 0.2 (deprecated)

en: gbif.range R package version 1.1 (current)

en: wsl.gbif R package version 0.1 (deprecated)

en: Test version, not to be used.

en: GitHub URL

en: Although species range may be obtained using expert maps or modeling methods, expert data is often species-limited and statistical models need more technical expertise as well as many species observations. When unavailable, such information may be extracted from the Global Biodiversity Information facility (GBIF), the largest public data repository inventorying georeferenced species observations worldwide. However, retrieving GBIF records at large scale may be tedious if users are unaware of specific tools and functions that need to be employed. Here we present *gbif.range*, an R library that contains automated methods to generate species range maps from scratch using in-house ecoregions shapefiles and an easy-to-use GBIF download wrapper. Finally, this library also offers a set of additional very useful parameters and functions for large GBIF datasets (generate doi, extract GBIF taxonomy, records filtering...). [gbif.range R project](https://github.com/8Ginette8/gbif.range)

accepted-name

display_name: accepted-name

conservation

display_name: conservation

ecoregions

display_name: ecoregions

filtering

display_name: filtering

flags

display_name: flags

gbif

display_name: gbif

hard-limit

display_name: hard-limit

landsca

display_name: landsca

large-scale

display_name: large-scale

occurrence-records

display_name: occurrence-records

r-package

display_name: r-package

range-maps

display_name: range-maps

species-distribution

display_name: species-distribution

species-observations

display_name: species-observations

synonyms

display_name: synonyms

taxonomy

display_name: taxonomy

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: gbif.range - An R package to generate species range maps based on ecoregions and a user-friendly GBIF wrapper


en: topography cryowrf landuse wrf antarctica

en: Scripts

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

en: WPSinput

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

en: Documentation

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

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

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

en: REMA topography and AntarcticaLC2000 for WRF


snow-drift-station-snow-and-air-data

maintainer: Benjamin Walter

title_for_slug: snow-drift-station-snow-and-air-data

en: raclets snow temperature snow-temperature snow-depth snow-height

en: Snow Depth

en: The snow depth (cm) was measured with a Lufft SHM-31 which was mounted at 1.7 m above ground. The time is given in UTC+1.

en: Snow Surface Temperature

en: The snow surface temperature (°C) was measured with a Campbell SI-111 at 0.7 m above ground. The time is given in UTC+1.

en: Air Temperature

en: The air temperature (°C) was measured with a Campbell CS-215 which was mounted at a height of 2.2 m above ground. The time is given in UTC+1.

en: Relative Humidity

en: The relative humidity (%) was measured with a Campbell CS-215 at a height of 2.2 m above ground. The time is given in UTC+1.

en: Snow and air data was monitored at Gotschnagrat (LON: 46.859 LAT: 9.849) by an infrarot radiometer (Campbell SI-111) for snow temperature (°C), a snow height sensor (Lufft SHM-31) for snow height change (cm) and a temperature and humidity sensor (Campbell CS-215) for air temperature (°C) and relative humidity (%). No filter was applied to the sensors and the smapling frequency was 1 Hz.

raclets

display_name: raclets

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-height

display_name: snow-height

snow-temperature

display_name: snow-temperature

temperature

display_name: temperature

en: Snow Drift Station - Snow and Air Data


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

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

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


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

en: Data plot of the forest station (LEB)

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

en: Forest station data (LEB)

en: Data file.

en: Site photo of the forest station (LEB)

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

mimetype: image/jpeg

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 one meteorological station in Lens in Switzerland which is located within a natural coniferous forest with Scots pine (_Pinus sylvestris_; 150-170 yrs)) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lens 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

wind-speed

display_name: wind-speed

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


maintainer: Jana von Freyberg

en: uncertainties root-zone review plant-water-uptake ecohydrology endmember-mixing-models stable-water-isotopes

en: Data set of MEE-20-04-264 (CSV)

en: Data set of MEE-20-04-264

en: The following two tables contain information about the data sources of the values reported in Table 1 and 2 in the paper “Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources” published in the journal ‘Methods in Ecology and Evolution’.

en: The following two tables contain information about the data sources of the values reported in Table 1 and 2 in the paper “Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources” published in the journal 'Methods in Ecology and Evolution'.

ecohydrology

display_name: ecohydrology

endmember-mixing-models

display_name: endmember-mixing-models

plant-water-uptake

display_name: plant-water-uptake

review

display_name: review

root-zone

display_name: root-zone

stable-water-isotopes

display_name: stable-water-isotopes

uncertainties

display_name: uncertainties

en: Data set of: Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources


en: hydrology climate-change snowmelt discharge precipitation soil-moisture

en: Shapefile of 307 catchments in Switzerland

en: Shapefile of the 307 medium-sized catchments in Switzerland. The "gridcode" provides the ID of the catchment used in the datafiles.

en: Daily simulated data for the reference period

en: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the reference period 1981-2017 in mm.

en: Daily simulated data for the future period

en: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the period 1981-2100 in mm for the 307 catchments.

en:
Daily discharge and the related hydro-meteorological variables precipitation, snowmelt, and soil moisture are provided for current (1981-2017) and for future climate conditions (1981-2100) for 307 medium-sized catchments in Switzerland. The catchments have a median catchment area of 117 km². The 307 catchments together form a set representative of the climatological conditions and runoff characteristics in Switzerland. The four variables were simulated at a daily resolution using the hydrological model PREVAH. PREVAH is a conceptual process-based model that was run in this study in its fully distributed version on a 500 m grid (Viviroli et al. 2009a). For the calibration, runoff time series from 140 mesoscale catchments covering the different runoff regimes were used. The model calibration was conducted over the period 1993-1997. Verification was performed on the period 1983-2005 using (i) volumetric deviation (Viviroli et al. 2007) and (ii) benchmark efficiency (Schäfli et al 2007) as objective functions. The calibration and validation procedures are described in detail in Köplin et al. (2010). The parameters for each model grid cell were derived by regionalizing the parameters obtained for the 140 catchments with a procedure based on ordinary kriging (Viviroli et al. 2009b, Köplin et al. 2010).
The calibrated and validated model was then driven with transient meteorological data (precipitation, temperature, radiation, and wind) representing both reference (1981-2017) and future climate conditions (2018-2099). The data were derived from the CH2018 climate scenarios (NCCS 2018) provided by the Swiss National Centre for Climate Services (NCCS). They were obtained from climate experiments produced with different climate modeling chains, consisting of a global and a regional circulation model each, within EUROCORDEX for three representative concentration pathways (RCP) emission scenarios. Downscaled output of ten climate model chains derived by quantile mapping were considered. The focus was on the chains of the EUR-11 domain with a horizontal resolution of 0.11 degrees (roughly 12.5 km). The climate model chains (GCM, RCM, RCP, and grid resolution) used are listed below:

- ICHEC-EC-EARTH	DMI-HIRHAM5	2.6	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	4.5	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	8.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	2.6	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	4.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	8.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	4.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	8.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	4.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	8.5	EUR-11

*References*:

-	Köplin, N., D. Viviroli, B. Schädler, and R. Weingartner (2010), _How does climate change affect mesoscale catchments in Switzerland? - A framework for a comprehensive assessment_, Advances in Geosciences, 27, 111-119, doi:10.5194/adgeo-27-111-2010.
-	National Centre for Climate Services (2018), CH2018 - _Climate Scenarios for Switzerland_, Tech. rep., NCCS, Zurich.
-	Schäfli, B., and H. V. Gupta (2007), _Do Nash values have value?_, Hydrological Processes, 21, 2075-2080, doi:10.1002/hyp.6825.
-	Viviroli, D., J. Gurtz, and M. Zappa (2007), _The hydrological modelling system PREVAH. Part II - Physical model description_, Geographica Bernensia, 40, 1-89.
-	Viviroli, D., M. Zappa, J. Gurtz, and R. Weingartner (2009a), _An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools_, Environmental Modelling & Software, 24, 1209-1222, doi:10.1016/j.envsoft.2009.04.001.
-	Viviroli, D., H. Mittelbach, J. Gurtz, and R. Weingartner (2009b), _Continuous simulation for flood estimation in ungauged mesoscale catchments of Switzerland-Part II: Parameter regionalisation and flood estimation results_, Journal of Hydrology, 377 (1), 208-225, doi:10.1016/j.jhydrol.2009.08.022.

discharge

display_name: discharge

hydrology

display_name: hydrology

snowmelt

display_name: snowmelt

soil-moisture

display_name: soil-moisture

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: Simulated future discharge and climatological variables for medium-sized catchments in Switzerland


maintainer: Nander Wever

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

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: 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: All versions

en: Undercatch correction

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

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 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 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: 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 1

en:
Deprecated version. Release notes:

First release of dataset.

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: 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: Version 4

en:
Deprecated version. Release notes:

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

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

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

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


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

en: Data Forward Scattering

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

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

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

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

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

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

albedo

display_name: albedo

photovoltaic

display_name: photovoltaic

snow

display_name: snow

winter-energy-production

display_name: winter-energy-production

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


en: outgoing weissfluhjoch longwave-radiation shortwave-radiation incoming

en: Processing doc

en: Parameter file

en: Metadata

en: DATA ACCESS

en:
Corrected incoming and outgoing shortwave and longwave 2 min radiation measurements at the Weissfluhjoch summit, Davos, CH.

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

incoming

display_name: incoming

outgoing

display_name: outgoing

weissfluhjoch

display_name: weissfluhjoch

en: ASRB_WFJ: Shortwave and longwave radiation measurements (2 min) at the Weissfluhjoch research site, Davos


maintainer: Maria Elvira Murazzi

en: polystyrene nanoplastic forest-trees uptake 13c-labelling

en: Nanoplastic in forests experiment

en:
Data embargoed until August 2022, and it will be provided upon request

-  excel file containing: two working sheets (leaf supply and root supply experiment) with a table with the values 13C-nanopolystyrene in the different tissues of the two forest tree species; graph showing the differences between controls and treatments of 13C-nanopolystyrene enrichment for each tissue of each forest tree species; ANOVA table showing significant values after having exposed the tree species to 13C-nanopolystyrene

en:
The fate of plastic in the environment is of global concern, because its production recently has
increased strongly and it accumulates in terrestrial and aquatic ecosystems. Although some knowledge on
its role in aquatic and terrestrial ecosystems was gained in the recent decade, hitherto very little is known
about the impact of micro and nanoplastics in forest ecosystems.

The aim of this pioneering project was to explore if nanoplastics are taken up by forest trees species
through leaves or roots. In greenhouse experiments, we exposed leaves or roots of seedling of two forest
trees species to solutions with highly 13C-labelled polystyrene nanoparticles (13C-nPS, 99 atom%) and
examined if they were incorporated in different above- and belowground tissues.

Treated part of the trees for both species showed significant 13C-enrichment, indicating that trees take up nanoparticles. However, the overall 13C signal strength in tissues that were not exposed to the 13C label remained low (Δδ13C<1‰) and was confined to a few seedlings, leaving it ambiguous whether nanoplastic transport occurs or not.

We acknowledge that the new method developed might be not sensitive enough to unequivocally detect
mechanisms of nanoplastic uptake and transport at environmentally realistic concentrations.

forest-trees

display_name: forest-trees

nanoplastic

display_name: nanoplastic

polystyrene

display_name: polystyrene

uptake

display_name: uptake

en: Nanoplastics in forests: Exploring the effects of nanoplastics on forest soils and tree physiology (NanoPlast)


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

en: Data plot of the forest station (LAB)

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

en: Forest station data (LAB)

en: Data file.

en: Data plot of the field station (LAF)

en: Site photo of the field station (LAF)

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

en: Site aerial photo (Lausanne)

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

en: Site photo of the forest station (LAB)

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

en: Field station data (LAF)

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 Lausanne in Switzerland where one station is located within a natural mixed forest stand (LAB) with European beech (_Fagus sylvatica_; 160-170 yrs), European silver fir (_Abies alba_; 160-170 yrs) and Norway spruce (_Picea abies_; 160-170 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, LAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lausanne is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


maintainer: James W. Kirchner

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

en: 30-minute time series

en: 30-minute hydrometeorological and ecohydrological time series.

en: Subcatchment polygons

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

en: Daily time series

en: Daily hydrometeorological and ecohydrological time series

en: Metadata

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

en: MODIS NDSI script

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

en: MODIS EVI2 script

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

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

Data include 30-minute time series of

- weather variables,

- sap flow fluxes,

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

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

and daily time series of

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

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

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

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

diel-cycle

display_name: diel-cycle

diurnal-cycle

display_name: diurnal-cycle

ecohydrology

display_name: ecohydrology

evapotranspiration

display_name: evapotranspiration

groundwater

display_name: groundwater

sap-flow

display_name: sap-flow

snowmelt

display_name: snowmelt

streamflow

display_name: streamflow

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


maintainer: Paraskevi Georgakaki

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

en: Observational data

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

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

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

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

en: WRF outputs

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

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

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

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

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

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf

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


maintainer: Ueli Reber

en: environmental--policy switzerland policy-documents policy-analysis text-corpus biodiversity bgb

en: Replication files

en:
 Introduction

The ZIP file contains all data and code to replicate the analyses reported in the following paper.

Reber, U., Fischer, M., Ingold, K., Kienast, F., Hersperger, A. M., Grütter, R., & Benz, R. (2022). Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics. *Policy Sciences*. [https://doi.org/10.1007/s11077-022-09456-4](https://doi.org/10.1007/s11077-022-09456-4)

If you use any of the material included in this repository, please refer to the paper. If you use (parts of) the text corpus, please also refer to the sources used for its compilation listed below. The content of the texts may not be changed.

 Data folder

The data folder contains the following files.

* _corpus.parquet_: Text corpus of Swiss policy documents
* _dict_de.csv_: Biodiversity dictionary (German)
* _dict_fr.csv_: Biodiversity dictionary (French)
* _dict_it.csv_: Biodiversity dictionary (Italian)
* _topic_labels.csv_: labels/codes for policy sectors
* _topics.csv_: labels/codes for policy sectors

The corpus and the dictionary were compiled by the authors specifically for this project. The labels/codes for policy sectors are based on the [coding scheme](http://ws-old.parlament.ch/affairs/topics) of the Swiss Parliament.

 Text corpus

The text corpus consists of 439,984 Swiss policy documents in German, French, and Italian from 1999 to 2018. The corpus was compiled from the following source between 2020-10-01 and 2021-01-31.

* Transcripts and parliamentary businesses (e.g. questions, motions, parliamentary initiatives) via the [Web Services (WS)](https://www.parlament.ch/de/%C3%BCber-das-parlament/fakten-und-zahlen/open-data-web-services) provided by the Swiss Parliament
* The official compilation of federal legislation ("Amtliche Sammlung", AS) via [opendata.swiss](https://opendata.swiss/de/dataset/official-compilation-of-federal-legislation-bs-as-1947-2018) provided by the Swiss Federal Archives (SFA)
* The federal gazette ("Bundesblatt") via [fedlex.admin.ch](https://www.fedlex.admin.ch/de/fga/index)
* Decisions of federal courts via [entscheidsuche.ch (ES)](https://entscheidsuche.ch/)

The corpus is stored in a single data frame to use with R saved as [PARQUET](https://parquet.apache.org/) file (corpus.parquet). The data frame has the following structure.

* _text_id_: Unique identifier for each text (source information as prefix, e.g. "t_")
* _doc_type_: Document type (see coding scheme below)
* _branch_: Government branche (1 legislative, 2 executive, 3 judicative)
* _stage_: Stage of policy process (1 drafting, 2 introduction, 3 interpretation)
* _year_: Year of publication
* _topic_: Policy sector (coding scheme in separate file in data folder)
* _lang_: Language (de, fr, it)
* _text_: Text

The following list contains the coding scheme for the doc_type variable.

* 101: Federal gazette // Draft for public consultation ("Vernehmlassungsverfahren")
* 102: Federal gazette // Explanation of draft for parliament ("Botschaft")
* 103: Federal gazette // Strategy, action plan
* 104: Federal gazette // Federal council decree ("Bundesratsbeschluss")
* 105: Federal gazette // (Simple) Federal decree ("(Einfacher) Bundesbeschluss")
* 106: Federal gazette // General decree ("Allgemeinverfügung")
* 107: Federal gazette // Treaty ("Übereinkommen")
* 108: Federal gazette // Treaty ("Abkommen")
* 109: Federal gazette // Draft for parliament ("Entwurf")
* 110: Federal gazette // Report ("Bericht")
* 111: Federal gazette // Report of parliamentary comission ("Bericht")
* 112: Federal gazette // Report of federal council ("Bericht")
* 201: Parl. businesses // Submitted text
* 202: Parl. businesses // Reason text
* 203: Parl. businesses // Federal council response
* 204: Parl. businesses // Initial situation
* 205: Parl. businesses // Proceedings
* 301: Parl. transcripts // Speech of MP
* 302: Parl. transcripts // Speech of federal council
* 401: Federal legislation // Legal text of the official compilation (law, ordinances, etc.)
* 501: Court decisions // Federal Supreme Court
* 502: Court decisions // Federal Criminal Court
* 503: Court decisions // Federal Administrative Court

 Code folder

The code folder contains all R code for the analyses. The files are numbered chronologically.

* _1_classifier_training.R_: Training of classifiers for classification of policy sectors
* _2_classifier_application.R_: Classification of documents in corpus
* _3_dictionary_application.R_: Biodiversity indexing of documents in corpus
* _4_stm_truncation.R_: Truncation of indexed documents to keep only relevant parts
* _5_stm_translation.R_: Translation of FR and IT documents to DE
* _6_stm_model.R_: Preprocesssing and structural topic model
* _7_plots.R_: Plots and numbers as included in the paper

The code/functions folder contains custom functions used in the scripts, e.g. to support topic model interpretation.

Package versions and setup details are noted in the code files.

 Contact

Please direct any questions to Ueli Reber (ueli.reber@eawag.ch).

bgb

display_name: bgb

biodiversity

display_name: biodiversity

environmental--policy

display_name: environmental--policy

policy-analysis

display_name: policy-analysis

policy-documents

display_name: policy-documents

switzerland

display_name: switzerland

text-corpus

display_name: text-corpus

en: Replication files for "Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics"