arbeitslose-anz

title_for_slug: arbeitslose-anz

de: arbeitsmarkt arbeitslosigkeit bezirke arbeitslose kantonzuerich gemeinden

de: Arbeitslose [Anz.]

de: Jahresmittel der beim kantonalen Arbeitsamt eingeschriebenen Arbeitslosen. Aus Datenschutzgründen dürfen Werte von Gemeinden mit weniger als 6 Arbeitslosen (Jahresmittel) nicht ausgewiesen werden.

arbeitslose

display_name: arbeitslose

arbeitslosigkeit

display_name: arbeitslosigkeit

arbeitsmarkt

display_name: arbeitsmarkt

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito


schul-mittelschule-anz

maintainer: Statistisches Amt des Kantons Zürich, Data Shop

title_for_slug: schul-mittelschule-anz

de: mittelschulen schulen schueler schuelerinnen kantonzuerich gemeinden bezirke

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

state: active

type: dataset

de: Schül. Mittelschule [Anz.]

media_type: text/csv

format: CSV

mimetype: text/csv

de: Anzahl MittelschülerInnen inkl. LangzeitgymnasiastInnen und SchülerInnen privater Mittelschulen (nach Wohnort).

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

mittelschulen

display_name: mittelschulen

schueler

display_name: schueler

schuelerinnen

display_name: schuelerinnen

schulen

display_name: schulen

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

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


verkaufe-von-unbebautem-land-anz

title_for_slug: verkaufe-von-unbebautem-land-anz

name: Statistisches Amt des Kantons Zürich, Data Shop

de: gemeinden freihandverkaeufe handaenderungen bauland kantonzuerich bezirke wohnbauland

de: Verkäufe von unbebautem Land [Anz.]

de:
Freihandverkäufe von unbebautem Land der Wohn- und Mischzone (Zentrums-, Kern- und Wohn/Gewerbezonen) inkl. Abbruchliegenschaften. Bis ins Jahr 2011 wurden Verkäufe ab Plan (in der Regel bei Stockwerkeigentum) als unbebaute Liegenschaft erfasst. Die Anzahl Verkäufe ist ab 2011 entsprechend tiefer als zuvor. Die letzten drei Jahre sind provisorisch.
Weitere Infos: www.zh.ch/bodenpreise

bauland

display_name: bauland

freihandverkaeufe

display_name: freihandverkaeufe

handaenderungen

display_name: handaenderungen

wohnbauland

display_name: wohnbauland

prices

fr: Prix

de: Preise

en: Prices

it: Prezzi


zinsbelastungsanteil

title_for_slug: zinsbelastungsanteil

de: kantonzuerich gemeinden gemeindefinanzen oeffentlichefinanzen bezirke

de: Zinsbelastungsanteil [%]

de: Nettozinsaufwand in Prozent vom laufenden Ertrag. Der Zinsbelastungsanteil zeigt den Anteil des laufenden Ertrags, welcher durch den Nettozinsaufwand gebunden ist. Je tiefer der Wert, desto grösser ist der Handlungsspielraum der Gemeinde. 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

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia


de: bezirke bevoelkerung sterbefaelle gemeinden kantonzuerich bevoelkerungsbewegungen

de: Sterberate (5-J.-mittel) [pro 1000 Einw.]

de: Durchschnittliche Zahl von Sterbefällen im Fünfjahresmittel pro 1000 Einw. Beispiel: Die Zahl von 2003 entspricht dem Mittelwert der Sterbefällen von 1999-2003 in Bezug auf die Einwohnerzahl von 1998.

bevoelkerung

display_name: bevoelkerung

bevoelkerungsbewegungen

display_name: bevoelkerungsbewegungen

sterbefaelle

display_name: sterbefaelle

population

fr: Population

de: Bevölkerung

en: Population

it: Popolazione


de: flaeche gemeinden bevoelkerungsdichte bezirke bevoelkerung kantonzuerich

de: 4-Personenhaushalte [Anz.]

bevoelkerungsdichte

display_name: bevoelkerungsdichte

flaeche

display_name: flaeche


bauzonen-uberbaut-ha

title_for_slug: bauzonen-uberbaut-ha

de: bezirke gemeinden kantonzuerich bauzonenverbrauch bodennutzung bauzonen zonenart

de: Bauzonen überbaut [ha]

de: Total überbaute Bauzonenfläche

bauzonen

display_name: bauzonen

bauzonenverbrauch

display_name: bauzonenverbrauch

bezirke

display_name: bezirke

bodennutzung

display_name: bodennutzung

gemeinden

display_name: gemeinden

zonenart

display_name: zonenart

construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione


nrw-wahleranteil-bdp

title_for_slug: nrw-wahleranteil-bdp

de: politik kantonzuerich gemeinden nationalratswahlen parteien bezirke wahlen

de: NRW Wähleranteil BDP [%]

de: Wähleranteil BDP bei Nationalsratswahlen. Hinweis: 2015 werden alle Auslandschweizer zur Stadt Zürich gezählt.

kantonzuerich

display_name: kantonzuerich

nationalratswahlen

display_name: nationalratswahlen

parteien

display_name: parteien

politik

display_name: politik

wahlen

display_name: wahlen

politics

fr: Politique

de: Politik

en: Politics

it: Politica

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 gemeinden bezirke personenwagen motorfahrzeuge fahrzeuge motorfahrzeugbestand privatverkehr

de: Personenwagen pro 1000 Einwohner [Anz.]

de: Der Motorisierungsgrad ist die Anzahl der eingelösten Personenwagen am 30. September, berechnet pro 1000 Einwohnerinnen und Einwohner der zivilrechtlichen Wohnbevölkerung am Ende des Vorjahres. Hinweis: Der Wert für den ganzen Kanton umfasst alle Autos mit einem Zürcher Kennzeichen; diese können auch Personen oder Unternehmen gehören, die ihr Domizil nicht im Kanton Zürich haben.

fahrzeuge

display_name: fahrzeuge

motorfahrzeugbestand

display_name: motorfahrzeugbestand

motorfahrzeuge

display_name: motorfahrzeuge

personenwagen

display_name: personenwagen

privatverkehr

display_name: privatverkehr

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti


name: Fachstelle Open Government Data des Kantons Zürich

de: wirtschaft stiftungen konkurse handelsregister branchen ehra einzelfirmen unternehmen genossenschaften zefix vereine unternehmensdaten shab firmen gmbh

label: Zentraler Firmenindex Zefix (Eidgenössisches Amt für das Handelsregister)

label: Neugründungs- und Konkursstatistik Kanton Zürich

de: Neugründungen nach Branchen im Kanton Zürich und der Schweiz insgesamt, wöchentlich aktualisiert

de: keine

de: Konkurseröffnungen nach Branchen im Kanton Zürich und der Schweiz insgesamt, wöchentlich aktualisiert

de: Anzahl der Eröffnungen von Konkursverfahren gegen Unternehmen und weitere Rechtseinheiten, wie sie im Zentralen Firmenindex (Zefix) mit Mutationstyp "KE Auflösung inf. Konkurs" ausgewiesenen sind. Die Meldungen werden mit den Branchenklassifikationen gemäss der Allgemeinen Systematik der Wirtschaftszweige (NOGA) angereichert und nach Branchen-Abschnitten (Grossbuchstaben) aggregiert. Aufgrund von Unterschieden bei der Datenerhebung kann es zu Abweichungen von anderen Auswertungen (zB. von kantonalen Handelsregisterämtern) kommen. Variabeln: 'br_abschnitt_red' = Auswahl von Branchen-Abschnitten (Grossbuchstaben) gemäss der Allgemeinen Systematik der Wirtschaftszweige (NOGA); 'location' = Kantonskürzel oder 'CH' für die Schweiz insgesamt; 'date' = Datum der Publikation im Schweizerischen Handelsamtsblatt (SHAB), die im Normalfall einige Tage nach der Publikation durch die kantonalen Ämter erfolgt; 'value' = Anzahl erstmaliger Konkursverfahrenseröffnungen per SHAB-Publikationsdatum; 'cumsum_diff' = Differenz der Anzahl Konkursverfahrenseröffnungen am SHAB-Publikationsdatum verglichen mit dem Durchschnitt Konkurseröffnungen der Vergleichsperiode 2017 bis 2019.

de: Wöchentlich aktualisierte Informationen zu den im Firmenzentralregister (Zefix) des Eidgenössischen Amts für das Handelsregister (EHRA) eingetragenen Unternehmen und weiteren Rechtseinheiten mit Sitz (Domiziladresse) im Kanton Zürich. Die Daten (Ressourcen) enthalten wöchentlich aktualisierte Konkurseröffnungen und Neugründungen nach Branche. Die Brancheninformation stammt aus dem Betriebs- und Unternehmensregister (BUR), dort sind NOGA-Codes hinterlegt. Das Statistische Amt plant weitere Daten als weitere Ressourcen zu veröffentlichen.

branchen

display_name: branchen

ehra

display_name: ehra

einzelfirmen

display_name: einzelfirmen

firmen

display_name: firmen

genossenschaften

display_name: genossenschaften

gmbh

display_name: gmbh

handelsregister

display_name: handelsregister

konkurse

display_name: konkurse

shab

display_name: shab

stiftungen

display_name: stiftungen

unternehmen

display_name: unternehmen

unternehmensdaten

display_name: unternehmensdaten

vereine

display_name: vereine

wirtschaft

display_name: wirtschaft

zefix

display_name: zefix

national-economy

de: Volkswirtschaft

work

de: Arbeit, Erwerb

de: Tagesregistereinträge zum Kanton Zürich und der Schweiz aus dem Zentralen Firmenindex (Zefix) des Bundes


anteil-gk-f

title_for_slug: anteil-gk-f

de: Anteil GK F [%]

de: Anteil Einwohner pro ÖV-Güteklasse F: Die ÖV-Güteklassen geben lagesscharf Aufschluss über die Erschliessungsqualität einer Gemeinde mit dem ÖV. In einem ersten Schritt werden Haltestellenkategorien definiert, in Abhängigkeit von einem an der Haltestelle verfügbaren ÖV-Verkehrsmittel und dem Kursintervall.  Danach wird in Abhängigkeit von Haltestellenkategorie und Luftliniendistanz die ÖV-Güteklasse ermittelt. Für jede Gemeinde werden die Einwohner pro Güteklasse in Prozent berechnet. (http://www.afv.zh.ch/internet/volkswirtschaftsdirektion/afv/de/verkehrsgrundlagen/verkehrsangebot/erreichbarkeit_und_erschliessung/_jcr_content/contentPar/downloadlist/downloaditems/infoblatt_v_g_teklas.spooler.download.1436273189233.pdf/KTZH_AFV_Broschuere_OeV-Gueteklassen.pdf)

kantonzuerich

display_name: kantonzuerich

oeffentlicherverkehr

display_name: oeffentlicherverkehr

verkehr

display_name: verkehr


de: wohnungsbestand zimmerzahl kantonzuerich gemeinden wohnungen bezirke

de: Anteil 6+ Zi.-Wohnungen [%]

de: Anteil 6+ Zi.-Wohnungen am Wohnungsbestand. Wohnungsbestand gemäss GWS. Wohnungsbestand bis 2009 aus Fortschreibung des Wohnungsbestandes der GWZ aufgrund der WBT.

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

wohnungen

display_name: wohnungen

wohnungsbestand

display_name: wohnungsbestand

zimmerzahl

display_name: zimmerzahl

construction

de: Bau- und Wohnungswesen

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


beschaftigte-im-sekundarsektor-anz

title_for_slug: beschaftigte-im-sekundarsektor-anz

de: bezirke wirtschaftssektor kantonzuerich gemeinden industrie arbeitsmarkt beschaeftigte

de: Beschäftigte im Sekundärsektor [Anz.]

de: Anzahl Beschäftigte des Sekundärsektors (Bergbau, Verarbeitendes Gewerbe/Herstellung von Waren, Energie- und Wasserversorung, Baugewerbe/Bau). Aktuellstes Jahr provisorisch.

arbeitsmarkt

display_name: arbeitsmarkt

beschaeftigte

display_name: beschaeftigte

industrie

display_name: industrie

wirtschaftssektor

display_name: wirtschaftssektor

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.


label: Team "Data" des Kantons Zürich

de: Anfragestatistik des Data Shop im Statistischen Amt des Kantons Zürich - kontrollierte Vokabulare

de: Anfragestatistik des Data Shop im Statistischen Amt des Kantons Zürich ab 2015

de: Spaltenüberschriften: 'id' = Nummer der Anfrage; 'erfassung' = Datum- und Zeitstempel der Anfragenerfassung; 'nutzertyp' = Nutzertyp der Anfrage; 'anfragetyp' = Anfragetyp; 'thema' = Thema der Anfrage; 'kanal' = Eingangskanal der Anfrage; 'zeitaufwand' = Geschätzter Aufwand in Minuten, um die Anfrage zu beantworten (erhoben ab 29.11.2017)

de: Die Abteilung «Data» des Statistischen Amts ist die Anlaufstelle für alle Fragen zu statistischen Informationen. Das Team bewirtschaftet das statistische Grundangebot des Kanton Zürich und bietet Nutzenden kostenlose Auskunft und Beratung zu Anfragen per Telefon oder E-Mail. Seit 2015 werden Anfragen mit Metadaten erfasst und in einer Anfragenstatistik archiviert.


de: kantonzuerich buergerrecht bezirke auslaender bevoelkerung gemeinden auslaenderinnen

de: Erwerb des Schweizer Bürgerrechts [pro 1000 Einw.]

de: in Bezug auf die Einwohnerzahl am Ende des vorhergehenden Jahres (Kantonale Erhebung). 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.

auslaender

display_name: auslaender

auslaenderinnen

display_name: auslaenderinnen

bevoelkerung

display_name: bevoelkerung

buergerrecht

display_name: buergerrecht

population

de: Bevölkerung


neuzulassungen-anderer-antrieb

title_for_slug: neuzulassungen-anderer-antrieb

de: motorfahrzeugbestand personenwagen motorfahrzeuge kantonzuerich gemeinden bezirke fahrzeuge

de: Neuzulassungen anderer Antrieb [%]

de: Anteil der Personenwagen (PW) mit anderem Antrieb an allen Personenwagen, die zwischen dem 1. Oktober des Vorjahrs und dem 30. September erstmals in Verkehr gesetzt wurden. Hinweis: Der Wert für den ganzen Kanton umfasst alle Autos mit einem Zürcher Kennzeichen; diese können auch Personen oder Unternehmen gehören, die ihr Domizil nicht im Kanton Zürich haben.

fahrzeuge

display_name: fahrzeuge

motorfahrzeugbestand

display_name: motorfahrzeugbestand

motorfahrzeuge

display_name: motorfahrzeuge

personenwagen

display_name: personenwagen

mobility

de: Mobilität und Verkehr


geb-vol-landwirtschaft-zunahme

title_for_slug: geb-vol-landwirtschaft-zunahme

de: bautaetigkeit gemeinden gebaeude kantonzuerich landwirtschaft bezirke

de: Geb.Vol. Landwirtschaft: Zunahme [%]

de: Veränderung des Gebäudevolumens gegenüber Vorjahr (1995: jährliche Veränderung im Zeitraum 1990-2000)

bautaetigkeit

display_name: bautaetigkeit

bezirke

display_name: bezirke

gebaeude

display_name: gebaeude

kantonzuerich

display_name: kantonzuerich

landwirtschaft

display_name: landwirtschaft

construction

de: Bau- und Wohnungswesen

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


de: geburten bevoelkerung bezirke bevoelkerungsbewegungen kantonzuerich gemeinden

de: Geburtenrate (5-J.-mittel) [pro 1000 Einw.]

de: Durchschnittliche Zahl von Geburten im Fünfjahresmittel pro 1000 Einw. Beispiel: Die Zahl von 2003 entspricht dem Mittelwert der Geburten von 1999-2003 in Bezug auf die Einwohnerzahl von 1998

bevoelkerungsbewegungen

display_name: bevoelkerungsbewegungen

geburten

display_name: geburten

gemeinden

display_name: gemeinden

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.


bauinvestitionen-fr-einw

title_for_slug: bauinvestitionen-fr-einw

de: bautaetigkeit gemeinden kantonzuerich bezirke bauinvestitionen

de: Bauinvestitionen  [Fr./Einw.]

de: Bauinvestitionen von Bautätigkeiten mit Investitionscharakter, die einer behördlichen Bewilligung bedürfen, in Franken pro Einwohner

bauinvestitionen

display_name: bauinvestitionen


name: Statistisches Amt des Kantons Zürich, Analysen & Studien

de: gebaeudeart immobilienmarkt wohnungsbau abbruch wohnbautaetigkeit wohnungsbestand bautaetigkeit neubauten gebaeude

de: GWR-Vorlage: Gebäude- und Wohnungsbestand, Bautätigkeit

media_type: text/html

de: Das HTML-Dokument enthält Skript-Vorlagen in R, wie sie das Statistische Amt für seine Analysen verwendet.

format: HTML

mimetype: text/html

de: Die Vorlage zeigt wie das statistische Amt des Kantons Zürich auf Basis des Gebäude- und Wohnungsregisters (GWR) Subdatensätze erstellt um den Wohnungsbestand sowie Wohnungen in abgebrochenen und neu erstellten Gebäuden zu analysieren. Die Vorlage enthält mehrere R-Skripte, die User:innen kopieren können, um die Resultate des Statistischen Amts zu reproduzieren. Wir bitten ausdrücklich um Hinweise und Feedback.

abbruch

display_name: abbruch

gebaeudeart

display_name: gebaeudeart

immobilienmarkt

display_name: immobilienmarkt

neubauten

display_name: neubauten

wohnbautaetigkeit

display_name: wohnbautaetigkeit

wohnungsbau

display_name: wohnungsbau

wohnungsbestand

display_name: wohnungsbestand

de: Vorlage für die Auswertung des GWR nach Bautätigkeit und Bestand im Kanton Zürich


de: verkehr verkehrsunfaelle kantonzuerich

de: Unfälle [pro 1000 Einw.]

de: Anzahl Unfälle pro 1000 Einwohner Total (mit Personen- und/oder Sachschaden)

verkehr

display_name: verkehr

verkehrsunfaelle

display_name: verkehrsunfaelle

mobility

de: Mobilität und Verkehr


anteil-landwirtschaftsflache

title_for_slug: anteil-landwirtschaftsflache

de: bezirke kantonzuerich gemeinden nutzflaeche flaeche landwirtschaft

de: Anteil Landwirtschaftsfläche [%]

de: Anteil landwirtschaftliche Nutzfläche an der Gesamtfläche.Die Arealstatistiken werden ca. alle 10 Jahre erhoben. Die letzten vier fanden zwischen 1979-1985, 1992-1997, 2004-2009 und 2013-2018 statt.

bezirke

display_name: bezirke

flaeche

display_name: flaeche

nutzflaeche

display_name: nutzflaeche

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


de: bevoelkerungswachstum gemeinden bezirke kantonzuerich bevoelkerung

de: Bevölkerungszunahme 5 Jahre [Pers.]

de: Veränderung der Einwohnerzahl (zivilrechtlicher Wohnsitz) innerhalb von 5 Jahren. Wert für 1970 aus der Volkszählung (wirtschaftl. Wohnsitz), da keine kant. Erhebung stattgefunden hat.

bevoelkerung

display_name: bevoelkerung

bevoelkerungswachstum

display_name: bevoelkerungswachstum

kantonzuerich

display_name: kantonzuerich

population

de: Bevölkerung

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.


arbeitsstatten-im-sekundarsektor-anz

title_for_slug: arbeitsstatten-im-sekundarsektor-anz

de: wirtschaftssektor gemeinden arbeitsstaetten bezirke kantonzuerich industrie

de: Arbeitsstätten im Sekundärsektor [Anz.]

de: Anzahl Arbeitsstätten des Sekundärsektors (Bergbau, Verarbeitendes Gewerbe/Herstellung von Waren, Energie- und Wasserversorung, Baugewerbe/Bau). Aktuellstes Jahr provisorisch.

arbeitsstaetten

display_name: arbeitsstaetten

gemeinden

display_name: gemeinden

industrie

display_name: industrie

wirtschaftssektor

display_name: wirtschaftssektor

work

de: Arbeit, Erwerb


gesamtsteuerfuss-ohne-kirchen

title_for_slug: gesamtsteuerfuss-ohne-kirchen

de: gemeindesteuern bezirke gemeindesteuerfuesse gemeinden

de: Gesamtsteuerfuss (ohne Kirchen) [%]

de: Bezogener Gesamtsteuerfuss ohne Kirchen in Prozent der einfachen Staatssteuer, gewichtet mit der Steuerkraft des jeweiligen Jahres. Zeitreihe ab 2012 (neues Finanzausgleichsgesetz). Details zu angewendeten Steuerfüssen sind direkt bei den jeweiligen Gemeinden einzuholen. Die Daten des aktuellsten Jahr sind provisorisch.

gemeindesteuerfuesse

display_name: gemeindesteuerfuesse

gemeindesteuern

display_name: gemeindesteuern

national-economy

de: Volkswirtschaft


zuzuge-pers

title_for_slug: zuzuge-pers

de: bezirke kantonzuerich gemeinden zuzuege-wegzuege wanderungen bevoelkerung

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.

wanderungen

display_name: wanderungen

zuzuege-wegzuege

display_name: zuzuege-wegzuege


bauzonen-nicht-uberbaut

title_for_slug: bauzonen-nicht-uberbaut

de: kantonzuerich bezirke bauzonen nutzungsreserven gemeinden

de: Bauzonen nicht überbaut  [%]

de: Anteil nicht überbaute Bauzonen gemessen an der gesamten Bauzonenfläche

bauzonen

display_name: bauzonen

nutzungsreserven

display_name: nutzungsreserven

construction

de: Bau- und Wohnungswesen

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


de: gemeinden wohnungen zimmerzahl bezirke kantonzuerich wohnungsbestand

de: Anteil 5 Zi.-Wohnungen [%]

de: Anteil 5 Zi.-Wohnungen am Wohnungsbestand. Wohnungsbestand gemäss GWS. Wohnungsbestand bis 2009 aus Fortschreibung des Wohnungsbestandes der GWZ aufgrund der WBT.

wohnungen

display_name: wohnungen

wohnungsbestand

display_name: wohnungsbestand

zimmerzahl

display_name: zimmerzahl

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.


de: Anteil 1 Zi.-Wohnungen [%]

de: Anteil 1 Zi.-Wohnungen am Wohnungsbestand. Wohnungsbestand gemäss GWS. Wohnungsbestand bis 2009 aus Fortschreibung des Wohnungsbestandes der GWZ aufgrund der WBT.

bezirke

display_name: bezirke


wegzuge

title_for_slug: wegzuge

de: wanderungen zuzuege-wegzuege bezirke bevoelkerung gemeinden kantonzuerich

de: Wegzüge [%]

de: Wegzüge in Bezug auf die Einwohnerzahl (gemäss Kantonaler Erhebung) Ende des vorhergehenden Jahres. Beispiel: Die "Wegzüge [%] 2003" beziehen sich auf die Einwohnerzahl von Ende 2002. 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

population

de: Bevölkerung


nettovermogen-fr-einw

title_for_slug: nettovermogen-fr-einw

de: kantonzuerich bezirke finanzkennzahlen gemeinden finanzvermoegen gemeindefinanzen

de: Nettovermögen [Fr./Einw.]

de: Nettovermögen pro Einwohner. Finanzvermögen minus Fremdkapital. Das Nettovermögen wird als Gradmesser für die Verschuldung verwendet indem sie den Betrag an Finanzvermögen zeigt, welcher die Schulden übersteigt. 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.

finanzkennzahlen

display_name: finanzkennzahlen

finanzvermoegen

display_name: finanzvermoegen

gemeindefinanzen

display_name: gemeindefinanzen

national-economy

de: Volkswirtschaft


de: gemeinden bezirke kantonzuerich gastgewerbe

de: Restaurants pro 1000 Einwohner [Anz.]

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

gastgewerbe

display_name: gastgewerbe

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

industry

fr: Industrie, services

de: Industrie, Dienstleistungen

en: Industry and services

it: Industria, servizi


hohe-m-u-m

title_for_slug: hohe-m-u-m

de: kantonzuerich bezirke geographie gemeinden

de: Höhe [m.ü.M.]

de: Höhe des Hauptsiedlungsgebietes, erhoben bei den Gemeinden 1995 (i.d.R. die Höhe des Dorfzentrums, der reformierten Kirche oder des Gemeindehauses)

geographie

display_name: geographie

territory

de: Raum und Umwelt

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


verpackungsglasmengen-tonnen

title_for_slug: verpackungsglasmengen-tonnen

de: kantonzuerich altglas recycling gemeinden bezirke

de: Verpackungsglasmengen [Tonnen]

de: Verpackungsglasmengen aus kommunaler Sammlung von Industrie und Privathaushalten.

altglas

display_name: altglas

recycling

display_name: recycling

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.


gebaudevolumen-zunahme

title_for_slug: gebaudevolumen-zunahme

de: bezirke kantonzuerich gemeinden bautaetigkeit gebaeude

de: Gebäudevolumen: Zunahme [%]

de: Veränderung des Gebäudevolumens gegenüber Vorjahr (1995: jährliche Veränderung im Zeitraum 1990-2000)

bautaetigkeit

display_name: bautaetigkeit

gebaeude

display_name: gebaeude

construction

de: Bau- und Wohnungswesen


de: kantonzuerich bezirke bevoelkerung haushalte gemeinden haushaltsgroesse haushalt-typ

de: Anteil 5-Personenhaushalte [%]

de: Anteil Fünfpersonenhaushalte an allen Privathaushalten

haushalt-typ

display_name: haushalt-typ

haushalte

display_name: haushalte

haushaltsgroesse

display_name: haushaltsgroesse

population

de: Bevölkerung


de: industrie bautaetigkeit gebaeudeart gemeinden bauinvestitionen bezirke kantonzuerich

de: Bauinv. Industr./Lager 5 Jahre [Fr./Einw.]

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

bauinvestitionen

display_name: bauinvestitionen

gebaeudeart

display_name: gebaeudeart

industrie

display_name: industrie


leerwohnungsquote

title_for_slug: leerwohnungsquote

de: gemeinden kantonzuerich bezirke wohnungsbestand wohnungen leerwohnungen

de: Leerwohnungsquote [%]

de: Leerstehende Wohnungen am 1. Juni des Erhebungsjahres, gemessen am Wohnungsbestand

bezirke

display_name: bezirke

leerwohnungen

display_name: leerwohnungen

wohnungen

display_name: wohnungen

wohnungsbestand

display_name: wohnungsbestand


de: oeffentlichefinanzen kantonzuerich bezirke nettoaufwendungen gemeinden gemeindefinanzen

de: Nettoaufwand Umweltschutz und Raumordnung [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

gemeinden

display_name: gemeinden

nettoaufwendungen

display_name: nettoaufwendungen

oeffentlichefinanzen

display_name: oeffentlichefinanzen

national-economy

de: Volkswirtschaft

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


anteil-unproduktive-flache

title_for_slug: anteil-unproduktive-flache

de: bezirke flaeche geographie kantonzuerich gemeinden

de: Anteil unproduktive Fläche [%]

de: Anteil unproduktiver Fläche (ohne Gewässerfläche). Die Arealstatistiken werden ca. alle 10 Jahre erhoben. Die letzten vier fanden zwischen 1979-1985, 1992-1997, 2004-2009 und 2013-2018 statt.

flaeche

display_name: flaeche

geographie

display_name: geographie

kantonzuerich

display_name: kantonzuerich

territory

de: Raum und Umwelt

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 gemeinden bevoelkerungswachstum bezirke bevoelkerung

de: Bevölkerungszunahme 5 Jahre [%]

de: Veränderung der Einwohnerzahl (zivilrechtlicher Wohnsitz) innerhalb von 5 Jahren in Prozent. Wert für 1970 aus der Volkszählung (wirtschaftl. Wohnsitz), da keine kant. Erhebung stattgefunden hat.

bevoelkerung

display_name: bevoelkerung

bevoelkerungswachstum

display_name: bevoelkerungswachstum

population

de: Bevölkerung


wahlbeteiligung-kantonsrat

title_for_slug: wahlbeteiligung-kantonsrat

de: wahlen kantonzuerich bezirke wahlbeteiligung kantonsratswahlen politik gemeinden

de: Wahlbeteiligung Kantonsrat [%]

de: Gültig eingelegte Listen (Wahlzettel) dividiert durch Anzahl Wahlberechtigte

kantonsratswahlen

display_name: kantonsratswahlen

politik

display_name: politik

wahlbeteiligung

display_name: wahlbeteiligung

wahlen

display_name: wahlen

politics

de: Politik


nrw-wahleranteil-al

title_for_slug: nrw-wahleranteil-al

de: kantonzuerich bezirke nationalratswahlen parteien wahlen politik gemeinden

de: NRW Wähleranteil AL [%]

de: Wähleranteil AL bei Nationalratswahlen. Hinweis: 2015 werden alle Auslandschweizer zur Stadt Zürich gezählt.

bezirke

display_name: bezirke

nationalratswahlen

display_name: nationalratswahlen

parteien

display_name: parteien


reformierte-kirchensteuerpflichtige-anz

title_for_slug: reformierte-kirchensteuerpflichtige-anz

de: kirchensteuer gemeinden kantonzuerich oeffentlichefinanzen steuerpflichtige bezirke

de: Reformierte Kirchensteuerpflichtige

kirchensteuer

display_name: kirchensteuer

steuerpflichtige

display_name: steuerpflichtige

national-economy

de: Volkswirtschaft

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


geb-vol-dienstleistungen-zunahme

title_for_slug: geb-vol-dienstleistungen-zunahme

de: gebaeudeart gemeinden bautaetigkeit gebaeude kantonzuerich bezirke

de: Geb.Vol. Dienstleistungen: Zunahme [%]

de: Veränderung des Gebäudevolumens gegenüber Vorjahr (1995: jährliche Veränderung im Zeitraum 1990-2000)

bautaetigkeit

display_name: bautaetigkeit

gebaeude

display_name: gebaeude

gebaeudeart

display_name: gebaeudeart

gemeinden

display_name: gemeinden

construction

de: Bau- und Wohnungswesen


de: gemeinden natuerlichepersonen vermoegen bezirke kantonzuerich steuerbaresvermoegen

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

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.


maintainer: Statistisches Amt des Kantons Zürich, Wahlen & Abstimmungen

de: abstimmungsergebnisse gemeinden politik politischegemeinden kantonalevolksabstimmungen eidgenoessischevolksabstimmungen abstimmungen

label: Abstimmungsarchiv

de: Abstimmungsarchiv des Kantons Zürich, Ergebnisse pro Gemeinde

de: Abstimmungsarchiv des Kantons Zürich, Ergebnisse Kanton Zürich

de: Alle Ergebnisse der kantonalen und eidgenössischen Abstimmungen des Kantons Zürich seit 1831.

abstimmungen

display_name: abstimmungen

abstimmungsergebnisse

display_name: abstimmungsergebnisse

eidgenoessischevolksabstimmungen

display_name: eidgenoessischevolksabstimmungen

kantonalevolksabstimmungen

display_name: kantonalevolksabstimmungen

politischegemeinden

display_name: politischegemeinden

de: Abstimmungsarchiv des Kantons Zürich ab 1831


de: kantonzuerich bevoelkerungswachstum bevoelkerung bezirke gemeinden

de: Bevölkerungszunahme 1 Jahr [%]

de: Veränderung der Einwohnerzahl (zivilrechtlicher Wohnsitz) gegenüber dem Vorjahr in Prozent. Wert für 1970 aus der Volkszählung (wirtschaftl. Wohnsitz), da keine kant. Erhebung stattgefunden hat.

bevoelkerung

display_name: bevoelkerung

bevoelkerungswachstum

display_name: bevoelkerungswachstum

bezirke

display_name: bezirke

kantonzuerich

display_name: kantonzuerich

population

de: Bevölkerung


maintainer: Marcia Phillips

en: borehole ritigraben permafrost permos meteo-station

en: DATA ACCESS

media_type: SMET

format: SERVICE

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

borehole

display_name: borehole

meteo-station

display_name: meteo-station

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

education

de: Bildung, Wissenschaft

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: RIT2: Meteorological station at Ritigraben borehole site


krw-wahleranteil-glp

title_for_slug: krw-wahleranteil-glp

de: kantonsratswahlen wahlen bezirke parteien kantonzuerich gemeinden politik

de: KRW Wähleranteil GLP [%]

de: Wähleranteil GLP bei Kantonsratswahlen

gemeinden

display_name: gemeinden

kantonsratswahlen

display_name: kantonsratswahlen

parteien

display_name: parteien

politik

display_name: politik

wahlen

display_name: wahlen

politics

de: Politik

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


en: metabarcoding monitoring edna spore-dispersal air-sampling

en: Data files and analysis scripts (Version 1)

media_type: application/zip

en: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of fungi". Please refer to README.pdf inside the archive for more information.

format: ZIP

mimetype: application/zip

en:
Resources associated with the manuscript *A case study on the application of spore sampling for the monitoring of fungi* (Schlegel et al. 2023, submitted).
Airborne environmental DNA (eDNA) monitoring of fungi was evaluated on a species-rich grassland site. Extensive fruiting body surveys yielded 29 waxcap and clavarioid species, 19 of which were also detectable in air eDNA. The analysis indicates that spores of locally occurring fruiting bodies were detected, in addition to a large diversity of common fungal species, while rare and threatened species were underrepresented in the air.
The contents of the dataset (ZIP archive):
* All analysis scripts in [R-Markdown](https://rmarkdown.rstudio.com) format, including the rendered PDF output with figures and tables (*analysis* directory)
* eDNA sample metadata (*amplicon_meta*) and results of the amplicon clustering (*amplicon_data*) and the source code of the pipeline (*amplicon_pipeline*)
* positions of all fruiting body groups found in the surveys (3838 GPS points) (*surveys*)
* positions of the spore traps, taxonomy of studied grassland fungi and red-list species, and many more resources
Please refer to `README.pdf` inside the archive for a complete description of the file structure and information on how to reproduce the analyses.

air-sampling

display_name: air-sampling

edna

display_name: edna

metabarcoding

display_name: metabarcoding

monitoring

display_name: monitoring

spore-dispersal

display_name: spore-dispersal

en: Supporting information for case study on the application of spore sampling for the monitoring of fungi


maintainer: Varun Sharma

en: mesoscale-modelling blowing-snow alps snow-atmosphere-interaction antarctica

media_type: ZIP

en:
REPRODUCIBILITY_POSTPROCESSING.zip contains data and scripts used to produce all figures from for the associated manuscript submitted for peer review ( see section on Citations below )

The folders stand for the three case studies presented in the manuscript. Two case studies (case Ia and case Ib) are on simulations in Antarctica and one case study
case II is for simulations in the Alps.

The associated data in the form of netcdf files or text files were produced using CRYOWRF v1.0

Apart from reproducibility, the intention of sharing these scripts is also to make it easy for new users to adopt CRYOWRF and be efficient, in particular in processing snowpack outputs.

The scripts were tested on multiple machines (different OSes) with the attached YAML file (wrf_analysis.yml) to setup the conda environment. All scripts were run using spyder as the IDE.

en: REPRODUCIBILITY_SIMULATION.zip contains all the extraneous files required to perform the simulations in associated manuscript (see Citations 3 in README.txt). The purpose of sharing these files apart from purposes of reproducibility is to also serve as templates for users to learn the workflow of CRYOWRF and perform simulations for their own purposes.

en:
This repository contains data required for reproducibility of the results to be published in the associated manuscript.

Apart from reproducibility, the attached datasets also serve as templates for new users to adopt CRYOWRF in their research.

The datasets consist of two folders organized in zip format:

1. REPRODUCIBILITY_SIMULATION:
  Consists of namelists for WPS, WRF and SNOWPACK to reproduce simulations published in the manuscript
  Additional files include datasets (from IMAU-FDM / RACMO, see "credits" below ) as well as helper python scripts to
  produce *.sno files
  which are used as initial conditions for SNOWPACK in CRYOWRF.

2. REPRODUCIBILITY_POSTPROCESSING:
   Includes outputs of CRYOWRF and python scripts used to prepare figures in the manuscript.

Each of the folders have their own readme files for more details.

 Code
citation: Varun Sharma. (2021, July 2). vsharma-next/CRYOWRF: CRYOWRF v1.0 (Version v1.0). Zenodo. http://doi.org/10.5281/zenodo.5060165

location: https://gitlabext.wsl.ch/atmospheric-models/CRYOWRF   (stable releases / institutional repo)
        https://github.com/vsharma-next/CRYOWRF            (dev branches / developer repo)

 Publication
**Introducing CRYOWRF v1.0: Multiscale atmospheric flow simulations with advanced snow cover modelling.**
Varun Sharma, Fraziska Gerber and Michael Lehning, Submitted to Geoscientific Model Development

 Acknowledgements
We thank Peter Kuipers Munneke (P.KuipersMunneke@uu.nl) for preparing and sharing outputs of IMAU-FDM and RACMO used for initial conditions for case Ia. The relevant citations for the methods through which these datasets were generated are:

* Kuipers Munneke, P., S. R. M. Ligtenberg, B. P. Y. Noël, I. M. Howat, J. E. Box, E. Mosley-Thompson, J. R. McConnell, K. Steffen, J. T. Harper, S. B. Das and M. R. van den Broeke. 2015. Elevation change of the Greenland ice sheet due to surface mass balance and firn processes, 1960-2014. The Cryosphere, 9, 2009-2025. doi:10.5194/tc-9-2009-2015

 * Ligtenberg, S. R. M., P. Kuipers Munneke, B. P. Y. Noël, and M. R. van den Broeke. 2018. Brief communication: Improved simulation of the present-day Greenland firn layer (1960-2016). The Cryosphere, 12, doi:10.5194/tc-12-1643-2018

alps

display_name: alps

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

mesoscale-modelling

display_name: mesoscale-modelling

snow-atmosphere-interaction

display_name: snow-atmosphere-interaction

education

en: Education and science

en: Reproducibility Dataset for CRYOWRF v1.0


bryophytes-of-europe-traits-bet-dataset

title_for_slug: bryophytes-of-europe-traits-bet-dataset

en: life-history-traits red-list mosses bioclimatic-variables indicator-values liverworts hornworts iucn

media_type: PDF

en: PDF including the (trait) explanations.

format: PDF

media_type: TXT

en: Text file including the BET dataset.

format: TXT

media_type: XLSX

en: Excel file including the BET dataset and (trait) explanations.

format: XLS

en: The Bryophytes of Europe Traits (BET) dataset includes values for 65 biological and ecological traits and 25 bioclimatic variables for all 1816 bryophytes included in the European Red List (Hodgetts et al. 2019). The traits are compiled from several regional trait datasets and manually complemented using Floras, species-specific literature and expert knowledge. The bioclimatic variables are calculated using the European range of each species. Details regarding the trait compilation and extraction of bioclimatic variables can be found in the corresponding data paper (Van Zuijlen et al. 2023).

bioclimatic-variables

display_name: bioclimatic-variables

hornworts

display_name: hornworts

indicator-values

display_name: indicator-values

iucn

display_name: iucn

life-history-traits

display_name: life-history-traits

liverworts

display_name: liverworts

mosses

display_name: mosses

red-list

display_name: red-list


maintainer: Adam Winstral

en: snow-simulation jim jules-investigation-model snow-depth snow

en: HS and SWE observations

en: Automated (HS) and manual (SWE) data used to evaluate model simulations

en: DEM

media_type: text/plain

en: 1-km resolution DEM used for downscaling gridded NWP data to stations and for distributing BDE evaluations at HS-stations to SWE-stations

mimetype: text/plain

en: File/data descriptor

en: Station forcing data

en: All forcing data need to run JIM at HS and SWE stations. These are data downscaled directly from COSMO NWP data (WY14, WY15) and further enhanced by additional station observations of snow depth (HS) and air temperature (Ta) in WY17. Further information can be found in README file. Note that in WY14 and WY15, shortwave radiation was not split into direct and diffuse (not necessary for JIM) and that the default method in JIM for splitting precipitation phase was used. In WY 17, direct and diffuse were combined as input to JIM and JIM was forced with pre-processed liquid and solid precipitation phases.

en: These data were used to drive and evaluate Jules Investigation Model (JIM) snow simulations. The data provided are the forcing data used for the "deterministic" runs as described in Winstral et al., 2019. The bias-detecting ensemble (Winstral et al., 2019) used observed snow depths (HS) to detect biases in these deterministic simulations related to precipitation and energy inputs to JIM. Simulations that included the BDE evaluations substantially improved JIM simulations.

jim

display_name: jim

jules-investigation-model

display_name: jules-investigation-model

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation

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: Meteorological data used to develop and validate the bias-detecting ensemble (BDE)


en: remote-sensing avalanche-mapping avalanche-size-estimation avalanche reliability

en: AvalancheReliabilityData

media_type: application/x-zip-compressed

en: The .zip contains all data used to conduct the reliability study as well as the results, a detailed description of the included files is contained in the included pdf. All geospatial data is provided in the Swiss Coordinate System: CH1903+ / LV95 (EPSG 2056). For any use of the data the proper citation provided is obligatory!

mimetype: application/x-zip-compressed

en:
This dataset contains the data used and collected to investigate the reliability of avalanche size estimates and avalanche outlines (see related publications). Namely this is

 Avalanche size estimates

* the 10 pictures depicting avalanches
* the survey results from the 170 participants

 Avalanche outlines mapped from oblique photographs
* the pictures of the six avalanches
* the avalanche outlines mapped by the 10 participants
* the reference mapped from the georeferenced photographs

 Avalanche outlines from remotely-sensed imagery
* the orthophotos in the four different resolutions (2m, 1m, 50cm, 25cm)
* the area of interest (AoI) delimiting the research area
* the avalanche mappings in each resolution for all five participants
* the shade masks used to separate illuminated and shaded areas

The acquisition of the orthophotos has been partially supported by the Swiss National Science Foundation (SNF; Grant N°200021_172800).

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing

education

en: Education and science

en: Data reliability study: avalanche size estimates and outlines


en: extreme-values return-periods low-flow alpine-precipitation reservoir-inflow

en: R codes for Extreme Values Analysis

media_type: zip-compresses folder of R scripts

en: Zip file containing R codes for running extreme value analyses for high precipitation and inflow events as well as code for determining return levels of low inflow and low precipitation events

en: Daily Luzzone Reservoir Inflow 01-01-2000 to 31-12-2019

media_type: .csv

en: Daily total water inflow to Luzzone reservoir. Natural inflow (LUZ_inflow_raw) is back-calculated based on daily water level in reservoir (removing hydropower inputs and spills). Linear interpolation between daily values is used to bring all inflow values into positive space (LUZ_inflow_intrp).

en:
 Summary

* Dataset of daily inflow to Luzzone reservoir in Ticino, Switzerland

* R scripts used to generate return levels for low reservoir inflow, low precipitation, high inflow, and extreme high precipitation based on various methods from extreme value analysis

 Data
The dataset included here is the "natural" reservoir inflow for the Luzzone reservoir.
Additional analyses were conducted on daily total precipitation of 6 meteorological stations (abbreviations: TIOLI, TIOLV, COM, VRN, VLS, ZEV). These precipitation data are freely available for teaching and research from the MeteoSwiss IDAweb portal (https://www.meteoswiss.admin.ch/services-and-publications/service/weather-and-climate-products/data-portal-for-teaching-and-research.html).

 Codes
R scripts used to determine return levels of the data set are included for both extreme high events and low events. The scripts include the following methods for calculating return levels:

* GEV (Generalized Extreme Value)

* GPD and GPDd (Generalized Pareto Distribution including declustered version)

* eGPD (extended Generalized Pareto Distribution)

* MEV (Metastatistical Extreme Value)

alpine-precipitation

display_name: alpine-precipitation

extreme-values

display_name: extreme-values

low-flow

display_name: low-flow

reservoir-inflow

display_name: reservoir-inflow

return-periods

display_name: return-periods

en: Data and Code on Extreme Inflow and Lowflow Analysis for Alpine Reservoirs


maintainer: Yohann Chauvier

en: random-stratified-sampling cluster background-data independent-dataset point-process-model survey-effort target-group covariate-correction environmental-stratification plant-species

en: Non-copyright data, scripts, diversity outputs

en:
Aim: While species distribution models (SDMs) are standard tools to predict species distributions, they can suffer from observation and sampling biases, particularly presence-only SDMs that often rely on species observations from non-standardized sampling efforts. To address this issue, sampling background points with a target-group strategy is commonly used, although more robust strategies and refinements could be implemented. Here, we exploited a dataset of plant species from the European Alps to propose and demonstrate efficient ways to correct for observer and sampling bias in presence-only models.

Innovation: Recent methods correct for observer bias by using covariates related to accessibility in model calibrations (classic bias covariate correction, Classic-BCC). However, depending on how species are sampled, accessibility covariates may not sufficiently capture observer bias. Here, we introduced BCCs more directly related to sampling effort, as well as a novel corrective method based on stratified resampling of the observational dataset before model calibration (environmental bias correction, EBC). We compared, individually and jointly, the effect of EBC and different BCC strategies, when modelling the distributions of 1’900 plant species. We evaluated model performance with spatial block split-sampling and independent test data, and assessed the accuracy of plant diversity predictions across the European Alps.

Main conclusions: Implementing EBC with BCC showed best results for every evaluation method. Particularly, adding the observation density of a target group as bias covariate (Target-BCC) displayed most realistic modelled species distributions, with a clear positive correlation (r≃0.5) found between predicted and expert-based species richness. Although EBC must be carefully implemented in a species-specific manner, such limitations may be addressed via automated diagnostics included in a provided R function. Implementing EBC and bias covariate correction together may allow future studies to address efficiently observer bias in presence-only models, and overcome the standard need of an independent test dataset for model evaluation.

background-data

display_name: background-data

cluster

display_name: cluster

covariate-correction

display_name: covariate-correction

environmental-stratification

display_name: environmental-stratification

independent-dataset

display_name: independent-dataset

plant-species

display_name: plant-species

point-process-model

display_name: point-process-model

random-stratified-sampling

display_name: random-stratified-sampling

survey-effort

display_name: survey-effort

target-group

display_name: target-group

en: Novel methods to correct for observer and sampling bias in presence-only species distribution models


maintainer: Leo Gallus Bont

en: seilaplan forest qgis geoprocessing openstreetmap accessible-forest

en: Juypter Notebook for Data Preparation

media_type: ipynb

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

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

en: Digitised sample perimeter

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

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Forest vector data (for sample forest range)

en: Juypter Notebook for Data Preparation (online)

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

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

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

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

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

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

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

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

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan

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


maintainer: Elisabeth Hafner

en: avalanche hazard-mapping snow satellite natural-hazard

en: SPOT6 Avalanche Outlines 16 January 2019

media_type: SHP

en: Shapefile of the manually mapped avalanche outlines. Please only use this data together with the example key document provided with this dataset and within the limitations of the dataset described in the publications.

format: SHP

en:
Outlines of 6'041 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 16 January 2019. The dataset was acquired following a period with very high avalanche danger. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping16012019.pdf)

The generation of the data is described in:

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

The data was comprehensivly validated in a subset area in

Hafner, E.D.; Techel, F.; Leinss, S.; Bühler, Y., 2021: Mapping avalanches with satellites - evaluation of performance and completeness. Cryosphere, 15, 2: 983-1004. doi: 10.5194/tc-15-983-2021

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow

education

en: Education and science

en: SPOT6 Avalanche outlines 16 January 2019


en: model-residuals hypervolume habitat-heterogeneity hengduan-mountains phytodiversity

en: Eurasia plant family richness map

en: This is the plant family level richness map at the Eurasia scale calculated from https://www.nature.com/articles/s41597-021-00997-6

en: Hengduan plant family richness map

en: This is the family level plant richness map in the Hengduan mountain scale at 1km resoution

en: Eurasia SR and heteorgeneity

en: This table is used for the Eurasia scale analyses, including both family level species richness map and different heterogeneity predictors

en: Plant range map at Hengduan scale

en: This is the plant range map at the Hengduan mountain scale based on species distribution model, elevation, and county level distribution information

en: HDM heterogeneity scales

en: The Heterogeneity matrics in the Hengduan mountain scale

en: This research data is used to re includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions. This research data includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions.

habitat-heterogeneity

display_name: habitat-heterogeneity

hengduan-mountains

display_name: hengduan-mountains

hypervolume

display_name: hypervolume

model-residuals

display_name: model-residuals

phytodiversity

display_name: phytodiversity

en: Phytodiversity is associated with habitat heterogeneity from Eurasia to Hengduan


high-resolution-climate-data-for-europe

maintainer: EnviDat Support

title_for_slug: high-resolution-climate-data-for-europe

en: minimum-temperature daily-climate precipitation air-temperature maximum-temperature cordex eur11 europe

en: CHELSA EUR11 Technical Documentation

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

en: Data Access

media_type: NetCDF

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present downscaled climate data for the CORDEX EUR11 domain at a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperature lapse rates. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height. The resulting data consist of a daily temperature and precipitation timeseries.

The data is distributed under a: Creative Commons: Attribution 4.0 International (CC BY 4.0) license.

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation

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: High resolution climate data for Europe


maintainer: Jana von Freyberg

en: snowmelt-rate stable-water-isotopes solutes snowmelt-lysimeter snowpack-outflow

en: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution. 10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

en:
This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland. The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.
The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

stable-water-isotopes

display_name: stable-water-isotopes

education

en: Education and science

en: Daily data of the volumes, solutes and isotopes in snowpack outflow measured at three locations in the southern Alp catchment


photogrammetric-drone-data-schurlialp

title_for_slug: photogrammetric-drone-data-schurlialp

en: photogrammetry orthophoto wingtra uav drone-data dsm

media_type: TIF

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

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

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

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

en: Photogrammetric Drone Data Schürlialp


radiosondes

maintainer: Jörg Wieder

title_for_slug: radiosondes

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

en: Radiosond Template Files

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

en: Radiosond Sounding Files

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

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

holoballoon

display_name: holoballoon

pressure

display_name: pressure

raclets

display_name: raclets

radiosonde

display_name: radiosonde

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind

display_name: wind

wind-direction

display_name: wind-direction

en: Radiosondes


en: snow turbulence dust particles hill atmosphere deposition

en: preferential deposition patterns of all simulations performed

en: The data consist of matlab files. Each files contains a 2D array with the values of deposition at the surface nodes. Each array has Nx x Ny values. Please refer to the original paper for additional information on the spatial resolution and grid size.

en:
Preferential deposition of snow and dust over complex terrain is responsible for a wide range of environmental processes, and accounts for a significant source of uncertainty in surface mass balances of cold and arid regions. Despite the growing body of literature on the subject, previous studies reported contradictory results on the location and magnitude of deposition maxima and minima. This study aims at unraveling the governing processes of preferential deposition in neutrally stable atmosphere and to reconcile seemingly inconsistent results of previous works. For this purpose, a comprehensive modeling approach is developed, based on large eddy simulations of the turbulent airflow, Lagrangian stochastic model of particle trajectories, and immersed-boundary method to represent the underlying topography. The model performance is tested against wind tunnel measurements of dust deposition around isolated and sequential hills. A scale analysis is then performed to investigate the dependence of snowfall deposition on the particle Froude and Stokes numbers, which fully account for the governing processes of inertia, flow advection, and gravity. Additional simulations are performed, to test whether the often used assumption of inertialess particles yields accurate deposition patterns. We finally show that our scale analysis provides qualitatively similar results for hills with different aspect ratios.

This dataset contains the results of the LES-LSM model. Each Matlab file contains a 2D array of deposition values (in kg/m2) in each surface node (ix, iy) of the Cartesian grid. The file names are consistent with the simulation numbers listed in the original paper. For additional information, please refer to "Preferential deposition of snow and dust over hills: governing processes and relevant scales" by F. Comola, M. G. Giometto, S. T. Salesky, M. B. Parlange, and M. Lehning, Journal of Geophysical Research: Atmospheres, 2019.

atmosphere

display_name: atmosphere

deposition

display_name: deposition

dust

display_name: dust

hill

display_name: hill

particles

display_name: particles

snow

display_name: snow

turbulence

display_name: turbulence

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.


media_type: CSV

en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per **calendar year** in Switzerland. The data collection commences with the beginning of the year 1937. After the completion of a hydrological year, which is the standard way avalanche fatalities are summarized in Switzerland and ends on the 30th of September, the new data is appended to the existing dataset.
If you require annual statistics per hydrological year, please download the data from here: [https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936]
The following information is contained (by column and column title):
 - year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste, away from open and secured ski runs)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)
The definitions for these four categories, as described in the guidelines to the avalanche accident database are:
tour:
activities include back-country ski, snowboard or snow-shoe touring
offpiste:
access from ski area, generally from the top of a skilift with short hiking distances
transportation.corridors (Techel et al., 2016):
people travelling or recreating on open or temporarily closed transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)
buildings (Techel et al., 2016):
people inside or just outside buildings, and workers on high alpine building sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

education

en: Education and science

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


maintainer: Matthias Haeni

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

en: Site photo of the field station (CLF)

media_type: image/jpeg

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

mimetype: image/jpeg

en: Data plot of the forest station (CLB)

media_type: text/csv

en: Data file.

media_type: application/pdf

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

mimetype: application/pdf

en: Data plot of the field station (CLF)

en: Site photo of the forest station (CLB)

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

en: Site aerial photo (Celerina)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Celerina in Switzerland where one station is located within a natural coniferous forest stand (CLB) with Swiss pine (_Pinus cembra_; 210-250 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CLF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Celerina 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: Celerina, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Henning Löwe

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

en: Angle of repose and 3D CT images

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

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

FC: faceted grains (1.4 - 2 mm)

FCS: small faceted grains (0.7 - 1.4 mm)

IB: ice beads (4 mm)

IBS: small ice beads (2 - 2.2 mm)

GB: glass beads(2 mm)

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

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

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

angle-of-repose

display_name: angle-of-repose

discrete-element-modelling

display_name: discrete-element-modelling

fast-sintering

display_name: fast-sintering

grain-shape

display_name: grain-shape

granular-snow

display_name: granular-snow

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: Angle of repose experiments with natural and spherical snow


en: 3d-ct-images discrete-element-modelling snow-mechanics unconfined-compression-experiments spherical-model-snow microstructure

en: Data Access

media_type: HTTPS

en: Data Structure (Python Notebook - view online)

en: Data Structure (Python Notebook)

en:
For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles.
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).

microstructure

display_name: microstructure

snow-mechanics

display_name: snow-mechanics

spherical-model-snow

display_name: spherical-model-snow

unconfined-compression-experiments

display_name: unconfined-compression-experiments

education

en: Education and science

en: Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples


maintainer: Frank Techel

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

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

en: ECT data (Norway, Switzerland)

en: Rutschblock data (Switzerland)

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

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

avalanche-danger

display_name: avalanche-danger

avalanche-observations

display_name: avalanche-observations

extended-column-test

display_name: extended-column-test

norway

display_name: norway

rutschblock-test

display_name: rutschblock-test

switzerland

display_name: switzerland

en: Stability tests, avalanche observations, Switzerland, Norway


mountain-permafrost-hydrology

maintainer: Jeannette Noetzli

title_for_slug: mountain-permafrost-hydrology

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

en: DORA Persistent URL

media_type: PDF

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

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

climate-change-impacts

display_name: climate-change-impacts

ice-rich-permafrost

display_name: ice-rich-permafrost

mass-movements

display_name: mass-movements

monitoring-techniques

display_name: monitoring-techniques

mountain-permafrost-hydrology

display_name: mountain-permafrost-hydrology

permafrost-degradation

display_name: permafrost-degradation

envidat

en: EnviDat: the Environmental Data Portal

en: Mountain Permafrost Hydrology


swiss-fluxnet-site-lageren

title_for_slug: swiss-fluxnet-site-lageren

en: swiss-forest-lab greenhouse-gas flux forest swiss-fluxnet meteorological-measurements eddy-covariance

en: Site description

media_type: .pdf

en: Fluxnet2015 dataset

en: The flux and meteo data of the Swiss FluxNet site Lägeren are also part of the Fluxnet2015 dataset.

en: Data access

en: The flux and meteo data of the Swiss FluxNet site Lägeren are openly available from the European Fluxes Database Cluster.

en:
The Swiss FluxNet Site Lägeren is a managed mixed deciduous mountain forest located on the steep Lägeren mountain (NW of Zurich, Swiss Plateau). The forest is highly diverse, dominated by beech, but also including ash, maple, spruce and fir trees. Eddy covariance flux measurements were started in April 2004. The site was part of the international CarboEurope IP network and the National Air Pollution Monitoring Network (NABEL). In addition to Swiss FluxNet, the site is part of the Long-term Forest Ecosystem Research (LWF) of WSL and the biological drought and growth indicator network (TreeNet) of WSL.

Measurements

- Ecosystem flux measurements of CO2, H2O vapour are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.
- Sub-canopy eddy fluxes (CO2, H2O), soil respiration campaigns
- Continuous CO2 profile measurements.
- Auxiliary micrometeorology and soil climate measurements.

Data availability

All data are available from the European Fluxes Database Cluster, but are also part of Fluxnet2015 dataset.

Data policy

ICOS data license:
[https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)

Detailed site info:
[https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae//](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae/)

eddy-covariance

display_name: eddy-covariance

flux

display_name: flux

forest

display_name: forest

greenhouse-gas

display_name: greenhouse-gas

meteorological-measurements

display_name: meteorological-measurements

swiss-fluxnet

display_name: swiss-fluxnet

swiss-forest-lab

display_name: swiss-forest-lab

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: Swiss FluxNet Site Lägeren


en: backward-trajectories snow-sublimation lagrangian-analysis antarctica isotopic-distillation evaporation stable-water-isotopes

en: Readme

media_type: TXT

en: Meta data

en: Python scripts for data visualization

media_type: ZIP

en: Scripts for generating the figures of the related research article and generating the data files (csv) from the model output

en: Model code

en: Model Sublimation and Model Air Parcel (python scripts)

en: Data

media_type: zip-compressed folder of csv

en: Modeled data including the data shown in the figures of the related research article

en:
 Summary

This data set contains Python programming code and modeled data discussed in a related research article. We developed a simple isotope model to study the drivers of the particularly depleted vapour isotopic composition measured on the ship of the Antarctic Circumnavigation Expedition close to the outlet of the Mertz glacier, East Antarctica, in the 6-day period from 27 January 2017 to 1 February 2017. The model considers the stable water isotopologues H2(16O), H2(18O), and HD(16O). It uses data from the ERA5 reanalysis product with a spatial resolution of 0.25° x 0.25° (Hersbach et al., 2018) and 10-day backward trajectories for the location of the ship, published by Thurnherr et al. (2020a). Our data set includes the model code, Python scripts for visualizing the results, and data produced by the model including the results shown in the figures of the related research article. Here, we summarize the most important model characteristics while further details can be found in the readme.txt file and the related research article including its supporting information.

 Main model characteristics

The modeling approach consists of two steps called *Model Sublimation* and *Model Air Parcel*. The former estimates the isotopic compositions of the snow and sublimation flux across the Antarctic Ice Sheet using an Eulerian frame of reference while the latter models the vapour isotopic composition and specific humidity along air parcel trajectories using a Lagrangian frame of reference. The isotope effects of most phase changes are represented by equilibrium fractionation. Only for ocean evaporation, kinetic fractionation is additionally taken into account (original Craig-Gordon formula). For snow sublimation, two assumptions are tested: *Run E* assumes that sublimation is associated with equilibrium fractionation while *Run N* assumes that sublimation occurs without isotopic fractionation.

 Model Sublimation
Model Sublimation uses a simple one-dimensional mass-balance approach in each grid cell, considering snow accumulation due to snowfall and vapour deposition and snow ablation due to sublimation. The snowpack is represented by 100 layers of equal thickness (e.g., 1 cm) and density (350 kg m-3). The isotopic composition of snowfall is parameterized by generalizing a site-specific, empirical relationship between the daily mean air temperature and snowfall isotopic composition. In the case of vapour deposition, Model Sublimation assumes equilibrium fractionation and estimates the isotopic composition of the atmospheric vapour as the average value for two idealized situations: (i) locally sourced vapour which has the same isotopic composition as the sublimation flux; (ii) non-locally sourced vapour in isotopic equilibrium with snowfall. Model Sublimation is run with a time step of 1 h, independently of Model Air Parcel.

 Model Air Parcel
Every hour, an ensemble of trajectories arrives at different heights in the ABL above the ship. For each of these trajectories, we consider an air parcel with a constant volume of 1 x 1 x 1 m3. The air parcels are initialized at the first suitable time when the trajectories are located in the ABL, either over the ice-free ocean in conditions of evaporation or over snow (Antarctic Ice Sheet or sea ice). Subsequently, the masses of the water isotopologues in the air parcels are simulated with a time step of 3 h, considering vapour uptake or removal due to the moisture flux at the snow or liquid ocean surface (only if the parcel is in the ABL) and cloud/precipitation formation (if the saturation specific humidity is reached). Sea ice is taken into account in a very simplified way. We represent the sea ice by grid cells with a sea-ice cover of more than 90% and assume the isotopic composition of the sublimation flux to be identical to that in the nearest grid cell of the Antarctic Ice Sheet. The isotopic composition of the sublimation flux is taken from Model Sublimation whereas the isotopic composition of the vapour deposition flux (over snow) and condensation flux (over ice-free ocean) is simulated assuming an isotopic equilibrium with the air parcel. Isotope effects of cloud/precipitation formation are represented using the classic Rayleigh distillation model with equilibrium fractionation, where the cloud water is assumed to precipitate immediately after formation.

 References

Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horanyi, A., Munoz Sabater, J.,... others (2018). *ERA5 hourly data on single levels from 1979 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS)*. doi: 10.24381/cds.bd0915c6

Thurnherr, I., Wernli, H., & Aemisegger, F. (2020a). *10-day backward trajectories from ECMWF analysis data along the ship track of the Antarctic Circumnavigation Expedition in austral summer 2016/2017*. Zenodo. doi: 10.5281/zenodo.4031705

antarctica

display_name: antarctica

backward-trajectories

display_name: backward-trajectories

evaporation

display_name: evaporation

isotopic-distillation

display_name: isotopic-distillation

lagrangian-analysis

display_name: lagrangian-analysis

snow-sublimation

display_name: snow-sublimation

stable-water-isotopes

display_name: stable-water-isotopes

education

en: Education and science

en: Modeled Isotopic Composition of Water Vapour Along Air Parcel Trajectories in the Antarctic


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

en: Forest station data (VSB)

en: Data file.

en: Data plot of the forest station (VSB)

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

en: Site photo of the forest station (VSB)

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

en: Field station data (VSF)

en: Site aerial photo (Visp)

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

en: Data plot of the field station (VSF)

en: Site photo of the field station (VSF)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Visp in Switzerland where one station is located within a natural mixed forest stand (VSB) with Scots pine (_Pinus sylvestris_; 40-80 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, VSF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Visp is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind-speed

display_name: wind-speed

envidat

en: EnviDat: the Environmental Data Portal

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


en: aerosol clouds ice-nucleation raclets backward-trajectories

en: This dataset contains number concentrations of ice-nucleating particles active at -15 °C observed at Weissfluhjoch during February and March 2019, as well as complementary data (measured aerosol number concentrations and modelled total precipitation along air mass trajectories). This data formed the basis of our paper with the title “Towards parameterising atmospheric concentrations of ice-nucleating particles active at moderate supercooling”.

aerosol

display_name: aerosol

clouds

display_name: clouds

ice-nucleation

display_name: ice-nucleation

raclets

display_name: raclets

education

en: Education and science

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: Ice nucleating particle concentrations active at -15 °C at Weissfluhjoch


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

en: Data Access via S3

media_type: geotiff

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

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

format: GeoTIFF

en: Technical documentation

en: Technical documentation containing file metadata and variable descriptions.

air-temperature

display_name: air-temperature

glaciers

display_name: glaciers

last-glacial-maximum

display_name: last-glacial-maximum

orography

display_name: orography

paleo-climate

display_name: paleo-climate

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