reingewinn-juristische-personen-mio-fr

title_for_slug: reingewinn-juristische-personen-mio-fr

de: juristischepersonen reingewinn bezirke kantonzuerich gemeinden

de: Reingewinn juristische Personen [Mio.Fr.]

de: Reingewinn (ehem. Ertrag) steuerpflichtiger juristischer Personen. Hinweis: Sehr hohe Beträge einiger weniger Steuerpflichtigen wirken sich entsprechend stark auf den Mittelwert aus.

juristischepersonen

display_name: juristischepersonen

reingewinn

display_name: reingewinn


maintainer: Statistisches Amt des Kantons Zürich, Data Shop

de: bezirke gemeinden kantonzuerich fahrzeuge motorfahrzeuge motorfahrzeugbestand privatverkehr personenwagen

state: active

type: dataset

de: Personenwagen pro 1000 Einwohner [Anz.]

media_type: text/csv

format: CSV

mimetype: text/csv

de: Am 30. September eingelöste Personenwagen, geteilt durch die Bevölkerung in Tausend. Der Wert wird auch Motorisierungsgrad genannt. 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.

bezirke

display_name: bezirke

fahrzeuge

display_name: fahrzeuge

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

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

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


name: Statistisches Amt des Kantons Zürich, Data Shop

de: kantonzuerich beschaeftigte landwirtschaft bezirke arbeitsmarkt beschaeftigungsgrad gemeinden

de: Anteil Vollzeitbeschäftigte Landwirtschaft [%]

de: Vollzeit: >= 75 Prozent

arbeitsmarkt

display_name: arbeitsmarkt

beschaeftigte

display_name: beschaeftigte

beschaeftigungsgrad

display_name: beschaeftigungsgrad

landwirtschaft

display_name: landwirtschaft

agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura


selbstfinanzierung-fr-einw

title_for_slug: selbstfinanzierung-fr-einw

de: gemeinden kantonzuerich bezirke gemeindefinanzen selbstfinanzierung

de: Selbstfinanzierung [Fr./Einw.]

de: Selbstfinanzierung pro Einwohner. Die Selbstfinanzierung entspricht der Summe der selbst erwirtschafteten Mittel (z.B. Ertragsüberschuss, Aufwandüberschuss, Abschreibungen). Sie zeigt die Finanzierung auf, die die Gemeinde durch ihre betriebliche Tätigkeit erzielt und die sie zur Finanzierung ihrer Investitionen benützen kann. 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

selbstfinanzierung

display_name: selbstfinanzierung

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia


de: gemeinden vermoegen steuerbaresvermoegen bezirke natuerlichepersonen kantonzuerich

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


anteil-gk-c

title_for_slug: anteil-gk-c

de: Anteil GK C [%]

de: Anteil Einwohner pro ÖV-Güteklasse C: 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)

oeffentlicherverkehr

display_name: oeffentlicherverkehr

verkehr

display_name: verkehr


de: schueler schulen berufsschule gemeinden kantonzuerich bezirke schuelerinnen

de: Schül. Berufsschule [pro 1000 Einw.]

de: Anzahl BerufsschülerInnen gemessen an der zivilrechtlichen Bevölkerung Ende Vorjahr

berufsschule

display_name: berufsschule

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

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


maintainer: Statistisches Amt des Kantons Zürich, Wahlen & Abstimmungen

de: eidgenoessischevolksabstimmungen kantonalevolksabstimmungen politik abstimmungen regierungsrat kantonsrat

de: Abstimmungsempfehlungen von Kantonsrat und Regierungsrat des Kantons Zürich

de: Abstimmungsempfehlungen des Zürcher Regierungs- und Kantonsrats zu kantonalen Abstimmungen und des Bundes-, des National- und des Ständerates zu eidgenössischen Abstimmungen. Es besteht kein Anspruch auf Vollständigkeit. Bitte senden Sie Ergänzungen zum Datensatz an die unter Kontakt angegebene E-Mail-Adresse.

abstimmungen

display_name: abstimmungen

eidgenoessischevolksabstimmungen

display_name: eidgenoessischevolksabstimmungen

kantonalevolksabstimmungen

display_name: kantonalevolksabstimmungen

kantonsrat

display_name: kantonsrat

politik

display_name: politik

regierungsrat

display_name: regierungsrat

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.


wasserverbrauch-pro-tag-und-kopf-liter

title_for_slug: wasserverbrauch-pro-tag-und-kopf-liter

de: trinkwasser wasserverbrauch kantonzuerich gemeinden bezirke wasser

de: Wasserverbrauch pro Tag und Kopf [Liter]

de: Mittlerer Tagesverbrauch: Die Pro-Kopf-Werte müssen unter Vorbehalt betrachtet werden, da sie auch den Verbrauch von Industrie und Gewerbe mit einschliessen und deshalb nicht als haushaltstypisch angesehen werden können.

kantonzuerich

display_name: kantonzuerich

trinkwasser

display_name: trinkwasser

wasser

display_name: wasser

wasserverbrauch

display_name: wasserverbrauch

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente


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


schul-mittelschule-anz

title_for_slug: schul-mittelschule-anz

de: gemeinden schuelerinnen schueler bezirke mittelschulen schulen kantonzuerich

de: Schül. Mittelschule [Anz.]

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

bezirke

display_name: bezirke

mittelschulen

display_name: mittelschulen


de: gemeindesteuern gemeinden gemeindefinanzen bezirke steuern kantonzuerich natuerlichepersonen

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

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

gemeindefinanzen

display_name: gemeindefinanzen

gemeinden

display_name: gemeinden

gemeindesteuern

display_name: gemeindesteuern

natuerlichepersonen

display_name: natuerlichepersonen

steuern

display_name: steuern

national-economy

de: Volkswirtschaft


name: Statistisches Amt des Kantons Zürich, Wahlen & Abstimmungen

de: kantonsratswahlen kantonsrat regierungsrat regierungsratswahlen

label: Übersicht über die Testdaten

de: Dokumentation eidgenössische und kantonale Echtzeitwahldaten

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

format: XLS

de: Wahlsonntag vom 12.02.2023

media_type: application/json

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

format: JSON

mimetype: application/json

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

kantonsratswahlen

display_name: kantonsratswahlen

regierungsratswahlen

display_name: regierungsratswahlen

politics

de: Politik

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Echtzeitdaten am Wahltag des Kantons Zürich - eidgenössische und kantonale Wahlen


bauzonen-uberbaut

title_for_slug: bauzonen-uberbaut

de: bezirke kantonzuerich nutzungsreserven gemeinden bauzonen

de: Bauzonen überbaut  [%]

de: Anteil überbaute Bauzonenfläche gemessen an der gesamten Bauzonenfläche

bauzonen

display_name: bauzonen

nutzungsreserven

display_name: nutzungsreserven

construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione

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.


bestand-dieselmotor

title_for_slug: bestand-dieselmotor

de: bezirke gemeinden kantonzuerich motorfahrzeuge motorfahrzeugbestand fahrzeuge personenwagen

de: Bestand Dieselmotor [%]

de: Anteil der Personenwagen (PW) mit Dieselmotor an allen am 30. September eingelösten Personenwagen. 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

kantonzuerich

display_name: kantonzuerich

motorfahrzeugbestand

display_name: motorfahrzeugbestand

motorfahrzeuge

display_name: motorfahrzeuge

personenwagen

display_name: personenwagen

mobility

de: Mobilität und Verkehr


de: schuelerinnen bezirke gemeinden sekundarstufe kantonzuerich schueler sekundarschule

de: Schül. Oberstufe [pro 1000 Einw.]

de: Anzahl OberstufenschülerInnen (exklusiv LangzeitgymnasiastInnen) gemessen an der zivilrechtlichen Bevölkerung Ende Vorjahr

schueler

display_name: schueler

schuelerinnen

display_name: schuelerinnen

sekundarschule

display_name: sekundarschule

sekundarstufe

display_name: sekundarstufe

education

de: Bildung, Wissenschaft


de: bezirke bevoelkerungswachstum bevoelkerung gemeinden kantonzuerich

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

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

population

fr: Population

de: Bevölkerung

en: Population

it: Popolazione


wahlarchiv-standeratswahlen

title_for_slug: wahlarchiv-standeratswahlen

de: politischeparteien kantonzuerich politik staenderat wahlergebnisse wahlen staenderatswahlen

de: Resultate 2. Wahlgang Erneuerungswahl Ständerat 2019

de: Kandidierende 1. Wahlgang Erneuerungswahl Ständerat 2011

de: Kandidierende 1. Wahlgang Erneuerungswahl Ständerat 2015

de: Resultate 1. Wahlgang Erneuerungswahl Ständerat 2019

de: Resultate 1. Wahlgang Erneuerungswahl Ständerat 2015

de: Kandidierende 2. Wahlgang Erneuerungswahl Ständerat 2015

de: Kandidierende 1. Wahlgang Erneuerungswahl Ständerat 2019

de: Resultate 1. Wahlgang Erneuerungswahl Ständerat 2003

de: Kandidierende 2. Wahlgang Erneuerungswahl Ständerat 2011

de: Dokumentation Ständeratswahl

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

de: Resultate 2. Wahlgang Erneuerungswahl Ständerat 2007

de: Resultate 1. Wahlgang Erneuerungswahl Ständerat 2011

de: Kandidierende 1. Wahlgang Erneuerungswahl Ständerat 2007

de: Resultate 2. Wahlgang Erneuerungswahl Ständerat 2015

de: Kandidierende 1. Wahlgang Erneuerungswahl Ständerat 2003

de: Kandidierende 2. Wahlgang Erneuerungswahl Ständerat 2019

de: Resultate 2. Wahlgang Erneuerungswahl Ständerat 2011

de: Kandidierende 2. Wahlgang Erneuerungswahl Ständerat 2007

de: Resultate 1. Wahlgang Erneuerungswahl Ständerat 2007

de: Ergebnisse der Erneuerungswahlen der zürcherischen Mitglieder des Ständerates

politik

display_name: politik

politischeparteien

display_name: politischeparteien

staenderat

display_name: staenderat

staenderatswahlen

display_name: staenderatswahlen

wahlen

display_name: wahlen

wahlergebnisse

display_name: wahlergebnisse

politics

de: Politik


wahlbeteiligung-kantonsrat

title_for_slug: wahlbeteiligung-kantonsrat

de: politik gemeinden kantonsratswahlen wahlen bezirke kantonzuerich wahlbeteiligung

de: Wahlbeteiligung Kantonsrat [%]

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

kantonsratswahlen

display_name: kantonsratswahlen

kantonzuerich

display_name: kantonzuerich

wahlbeteiligung

display_name: wahlbeteiligung

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

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


krw-wahleranteil-evp

title_for_slug: krw-wahleranteil-evp

de: kantonsratswahlen gemeinden bezirke parteien wahlen kantonzuerich politik

de: KRW Wähleranteil EVP [%]

de: Wähleranteil EVP bei Kantonsratswahlen

parteien

display_name: parteien


de: unternehmen bezirke kantonzuerich gemeinden

de: Total geschaffene Stellen, Beschäftigte [Anz.]

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

unternehmen

display_name: unternehmen

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito


de: gemeinden politik kantonzuerich wahlergebnisse wahlen gemeindewahlen politischeparteien politischegemeinden

label: Gemeindewahlen

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

de: Dokumentation Gemeindeparlamentswahlen

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

de: Ergebnisse der kommunalen Parlamentswahlen 2022 auf Ebene Kandidierende

de: Ergebnisse der kommunalen Parlamentswahlen 2022 auf Ebene Listen

gemeindewahlen

display_name: gemeindewahlen

politischegemeinden

display_name: politischegemeinden

de: Archiv Wahlresultate Gemeindeparlamentswahlen im Kanton Zürich


bauinvestitionen-fr-einw

title_for_slug: bauinvestitionen-fr-einw

de: bautaetigkeit bezirke gemeinden kantonzuerich bauinvestitionen

de: Bauinvestitionen  [Fr./Einw.]

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

bauinvestitionen

display_name: bauinvestitionen

bautaetigkeit

display_name: bautaetigkeit

construction

de: Bau- und Wohnungswesen


de: bezirke ehescheidung bevoelkerung ehe kantonzuerich gemeinden scheidung

de: Scheidungen [pro 1000 Einw.]

de: Anzahl Scheidungen pro 1000 Einwohner (Rohe Scheidungsziffer). Hinweise: Am 1.Januar 2000 trat das neue Scheidungsrecht in Kraft. Ab 2011 Wechsel der Datenquelle: Es werden nicht mehr alle Scheidungen von zwei ausländischen Personen ausgewiesen.

bevoelkerung

display_name: bevoelkerung

bezirke

display_name: bezirke

ehe

display_name: ehe

ehescheidung

display_name: ehescheidung

scheidung

display_name: scheidung

population

de: Bevölkerung

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.


geb-vol-wohnen-anteil

title_for_slug: geb-vol-wohnen-anteil

de: gebaeude bautaetigkeit bezirke gebaeudeart kantonzuerich gemeinden

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

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

gebaeude

display_name: gebaeude

gebaeudeart

display_name: gebaeudeart

gemeinden

display_name: gemeinden


de: betriebe unternehmensstruktur bezirke kantonzuerich gemeinden

de: Mikrobetriebe (0-9 VZÄ) [Anz.]

de: Anzahl Mikrobetriebe mit einer Beschäftigung von weniger als 10 Vollzeitäquivalenten. Aktuellstes Jahr provisorisch.

betriebe

display_name: betriebe

unternehmensstruktur

display_name: unternehmensstruktur

work

de: Arbeit, Erwerb


arbeitsstatten-im-sekundarsektor-anz

title_for_slug: arbeitsstatten-im-sekundarsektor-anz

de: gemeinden arbeitsstaetten bezirke wirtschaftssektor 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

industrie

display_name: industrie

kantonzuerich

display_name: kantonzuerich

wirtschaftssektor

display_name: wirtschaftssektor


anteil-verkehrsflache

title_for_slug: anteil-verkehrsflache

de: kantonzuerich verkehrsinfrastruktur bezirke gemeinden flaeche strassen

de: Anteil Verkehrsfläche [%]

de: Anteil Verkehrsfläche 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.

flaeche

display_name: flaeche

strassen

display_name: strassen

verkehrsinfrastruktur

display_name: verkehrsinfrastruktur

territory

de: Raum und Umwelt


krw-wahleranteil-al

title_for_slug: krw-wahleranteil-al

de: parteien wahlen kantonzuerich kantonsratswahlen gemeinden politik bezirke

de: KRW Wähleranteil AL [%]

de: Wähleranteil AL bei Kantonsratswahlen

kantonsratswahlen

display_name: kantonsratswahlen

parteien

display_name: parteien

politik

display_name: politik

wahlen

display_name: wahlen

politics

de: Politik


bauinv-wohnen-fr-einw

title_for_slug: bauinv-wohnen-fr-einw

de: kantonzuerich bezirke gemeinden bautaetigkeit bauinvestitionen wohnbautaetigkeit

de: Bauinv. Wohnen  [Fr./Einw.]

de: Durchschnittliche Bauinvestitionen im Bereich Wohnen (Bauinv. für EFH, MFH, andere Wohngebäude und übriges Wohnen), in Franken pro Einwohner.

bauinvestitionen

display_name: bauinvestitionen

bautaetigkeit

display_name: bautaetigkeit

bezirke

display_name: bezirke

wohnbautaetigkeit

display_name: wohnbautaetigkeit

construction

de: Bau- und Wohnungswesen

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: gemeinden bezirke bautaetigkeit landwirtschaft bauinvestitionen gebaeudeart kantonzuerich

de: Bauinv. Landwirtschaft 5 Jahre [Fr./Einw.]

de: Durchschnittliche Bauinvestitionen der letzten 5 Jahre im Bereich Landwirtschaft (Bauinv. für landwirtschaftliche Ökonomiebauten inkl. Gartenbau), in Franken pro Einwohner.

gebaeudeart

display_name: gebaeudeart

gemeinden

display_name: gemeinden

landwirtschaft

display_name: landwirtschaft


zuzuge-pers

title_for_slug: zuzuge-pers

de: kantonzuerich zuzuege-wegzuege wanderungen bezirke bevoelkerung gemeinden

de: Zuzüge [Pers.]

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

bevoelkerung

display_name: bevoelkerung

wanderungen

display_name: wanderungen

zuzuege-wegzuege

display_name: zuzuege-wegzuege

population

de: Bevölkerung


anteil-siedlungsflache

title_for_slug: anteil-siedlungsflache

de: kantonzuerich flaeche gemeinden geographie bezirke

de: Anteil Siedlungsfläche [%]

de: Anteil Siedlungsfläche (ohne Verkehrsfläche) an der Gesamtfläche. Die Arealstatistiken werden ca. alle 10 Jahre erhoben. 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


krw-wahleranteil-sd

title_for_slug: krw-wahleranteil-sd

de: kantonzuerich kantonsratswahlen politik bezirke wahlen parteien gemeinden

de: KRW Wähleranteil SD [%]

de: Wähleranteil SD bei Kantonsratswahlen

kantonsratswahlen

display_name: kantonsratswahlen

politics

de: Politik


de: bezirke oeffentlicherverkehr kantonzuerich gemeinden infrastruktur bauinvestitionen

de: Bauinv. ÖV, Kommunik. 5 Jahre [Fr./Einw.]

de: Durchschnittliche Bauinvestitionen der letzten 5 Jahre im Bereich ÖV und Kommunikation (Bauinv. für Bahn, Bus, Tram, Flugverkehr und Schifffahrt sowie für Kommunikation), in Franken pro Einwohner.

infrastruktur

display_name: infrastruktur

oeffentlicherverkehr

display_name: oeffentlicherverkehr

construction

de: Bau- und Wohnungswesen

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


de: schueler schulen gemeinden kantonzuerich primarschule bezirke schuelerinnen

de: Schül. Primarschule [pro 1000 Einw.]

de: Anzahl PrimarschülerInnen gemessen an der zivilrechtlichen Bevölkerung Ende Vorjahr

primarschule

display_name: primarschule

schueler

display_name: schueler

schuelerinnen

display_name: schuelerinnen

schulen

display_name: schulen

education

de: Bildung, Wissenschaft

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.


bruttoinvestitionen-fr-einw

title_for_slug: bruttoinvestitionen-fr-einw

de: finanzkennzahlen gemeindefinanzen bezirke kantonzuerich gemeinden

de: Bruttoinvestitionen [Fr./Einw.]

de: Bruttoinvestitionen pro Einwohner. Aussage: Massgrösse für den Infrastrukturausbau ohne Berücksichtigung der Finanzierungsträger. Grundlage ist die Konsolidierte Gemeinde. Der Haushalt der Schulgemeinde wird dabei anteilsmässig in den Haushalt der poltischen Gemeinden umgelegt.

bezirke

display_name: bezirke

finanzkennzahlen

display_name: finanzkennzahlen

gemeindefinanzen

display_name: gemeindefinanzen

national-economy

de: Volkswirtschaft


durchschnittliche-haushaltsgrosse-pers

title_for_slug: durchschnittliche-haushaltsgrosse-pers

de: haushalt-typ kantonzuerich bevoelkerung haushaltsgroesse bezirke haushalte gemeinden

de: Durchschnittliche Haushaltsgrösse von Privathaushalten der ständigen Wohnbevölkerung.

gemeinden

display_name: gemeinden

haushalt-typ

display_name: haushalt-typ

haushalte

display_name: haushalte

haushaltsgroesse

display_name: haushaltsgroesse

population

de: Bevölkerung


de: gemeinden zahnaerztinnen gesundheit kantonzuerich zahnaerzte bezirke

de: Zahnärzte [pro 1000 Einw.]

de: Definition: Zahnärzte, welche eine Bewilligung zur selbständigen Berufsübung haben, jeweils am Ende eines Kalenderjahres. Für 1993 und 2003 keine Zahlen vorhanden. Aktuellstes Jahr provisorisch.

gesundheit

display_name: gesundheit

zahnaerzte

display_name: zahnaerzte

zahnaerztinnen

display_name: zahnaerztinnen

health

fr: Santé

de: Gesundheit

en: Health

it: Sanità


bauinvestitionen-mio-fr

title_for_slug: bauinvestitionen-mio-fr

de: bezirke kantonzuerich bauinvestitionen bautaetigkeit gemeinden

de: Bauinvestitionen [Mio.Fr.]

de: Bauinvestitionen von Bautätigkeiten mit Investitionscharakter, die einer behördlichen Bewilligung bedürfen

bauinvestitionen

display_name: bauinvestitionen

bautaetigkeit

display_name: bautaetigkeit

kantonzuerich

display_name: kantonzuerich

construction

de: Bau- und Wohnungswesen

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


anteil-landwirtschaftsflache

title_for_slug: anteil-landwirtschaftsflache

de: kantonzuerich bezirke landwirtschaft nutzflaeche flaeche gemeinden

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.

flaeche

display_name: flaeche

landwirtschaft

display_name: landwirtschaft

nutzflaeche

display_name: nutzflaeche

territory

de: Raum und Umwelt

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: haushalt-typ kantonzuerich bevoelkerung haushaltsgroesse haushalte bezirke gemeinden

de: Anteil 4-Personenhaushalte [%]

de: Anteil Vierpersonenhaushalte an allen Privathaushalten

bevoelkerung

display_name: bevoelkerung


en: soil ecological-indicator-values grain-size phylogenetic-diversity functional-diversity climate taxonomic-diversity

en: Data access

media_type: ZIP

format: ZIP

en:
This dataset comprises a large array of ecological data for the European Alps:

  (1) Current soil and climate predictors at various resolutions.
  (2) GBIF observations of the European Alps Flora (~4,000 species).
  (3) Species habitat suitability maps (1,109 species; based on species observations filtered at 40x40-km)
  at various resolutions used in the study to generate (4); except 'expert'...
  (4) Expert, Taxonomic, phylogenetic and functional diversity of the study region at various resolutions
  (from 100-m to 40-km --> 100-m aggregated & mean to km + non-aggregated/predicted) for CLIM,
  SOIL and CLIM-SOIL models.
  (5) Ecological and altitudinal preferences of the European Alps Flora.
  (6) Data outputs of the related published article.
  (7) All scripts used for analyses.
  (8) Additional files used for analyses.
  (9) Improved set of species habitat suitability maps (~2,600 species; based on species observations
  filtered at 1x1-km) and related taxonomic diversity at 100-m resolution (aggregated to km +
  non-aggregated/predicted) for CLIM, SOIL and CLIM-SOIL models ---> not incorporated in the study.

climate

display_name: climate

ecological-indicator-values

display_name: ecological-indicator-values

functional-diversity

display_name: functional-diversity

grain-size

display_name: grain-size

phylogenetic-diversity

display_name: phylogenetic-diversity

soil

display_name: soil

taxonomic-diversity

display_name: taxonomic-diversity

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: Resolution in species distribution models shapes spatial patterns of plant multifaceted diversity


wohnungsbestand-whg

title_for_slug: wohnungsbestand-whg

de: wohnungsbestand kantonzuerich immobilien wohnungen bezirke gemeinden

de: Wohnungsbestand [Whg.]

de: Wohnungsbestand gemäss GWS. Wohnungsbestand bis 2009 aus Fortschreibung des Wohnungsbestandes der GWZ aufgrund der WBT. Hinweis zu GWS: Die Jahresdifferenz 2009/2010 und 2010/2011 des Wohnungsbestandes entspricht nicht dem Wohnungszugang aufgrund Registerbereinigungen (s. http://www.bfs.admin.ch/bfs/portal/de/index/infothek/erhebungen__quellen/blank/blank/gws/02.html)

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

immobilien

display_name: immobilien

wohnungen

display_name: wohnungen

wohnungsbestand

display_name: wohnungsbestand


maintainer: EnviDat Support

en: aerosol backward-trajectories ice-nucleation raclets clouds

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

backward-trajectories

display_name: backward-trajectories

clouds

display_name: clouds

ice-nucleation

display_name: ice-nucleation

raclets

display_name: raclets

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


maintainer: Ueli Reber

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

en: Replication files

format: SERVICE

en:
 Introduction

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

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

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

 Data folder

The data folder contains the following files.

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

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

 Text corpus

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

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

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

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

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

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

 Code folder

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

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

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

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

 Contact

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

bgb

display_name: bgb

biodiversity

display_name: biodiversity

environmental--policy

display_name: environmental--policy

policy-analysis

display_name: policy-analysis

policy-documents

display_name: policy-documents

switzerland

display_name: switzerland

text-corpus

display_name: text-corpus

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


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

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

media_type: application/zip

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

mimetype: application/zip

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

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

acoustic-emissions

display_name: acoustic-emissions

fiber-bundle-model

display_name: fiber-bundle-model

sintering

display_name: sintering

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-mechanics

display_name: snow-mechanics

viscous-deformation

display_name: viscous-deformation

education

en: Education and science

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


en: snow-instability failure-layer snow-stratigraphy snowpack-simulation snowpack rutschblock snow-profiles

en: DAV data set: Properties of observed snow profiles and simulated failure layers

media_type: CSV

en:
For each profile pair from the DAV data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. The content of the columns is explained in Table 1 of the ReadMe file. Only those profile pairs which fulfilled predefined similarity criteria (column
"similarity_obs_sim" = 1) and which belonged to the stability classes "stable" and "unstable" (column "stability_class"
= 0 or 1) were used to train the RF model. Please note that for each of the two snow profiles with RB score 7 (profile
IDs 7228 and 9526), three additional layers were included in this data set to obtain a balanced set of training data (73
unstable and 73 stable profiles).

en: ReadMe

en: ReadMe file explaining data structure and content

en: Observed snow profiles

media_type: .csv

en: Observed snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding simulated profile in the "simulated_profiles" folder. One row corresponds to one observed snow layer. The content of the columns is described in Table 2 of the ReadMe file.

en: SWISS data set: Properties of observed snow profiles and simulated failure layers

en: For each profile pair from the SWISS data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. Please note that only those profile pairs which fulfilled the similarity criteria (column similarity_obs_sim = 1, 121 profiles) were used to validate the RF model. The content of the columns is explained in Table 1 of the ReadMe file.

en: Simulated snow profiles

en: Simulated snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding observed profile in the "observed_profiles" folder. One row corresponds to one simulated snow layer. The content of the columns 1-7 is described in Table 3 of the ReadMe file. The remaining columns (8-31) contain all features that were used in the development of the RF model and are described in Table 1 of the ReadMe file.

en:
This data set includes information on all observed and simulated snow profiles that were used to train and validate the
random forest model described in Mayer et al. (2022). The RF model was trained to assess snow instability from simulated snow stratigraphy. The data set contains observed snow profiles from the region of Davos (DAV subset, 512 profiles) and from all over Switzerland (SWISS subset, 230 profiles). For each observed snow profile, there is a corresponding simulated profile which was obtained using meteorological input data for the numerical snow cover model SNOWPACK. The information on the observed snow profile contains a Rutschblock test result including the depth of the failure interface. As part of the study described in Mayer et al. (2022), each observed snow profile was manually compared to its simulated counterpart and the simulated layer corresponding to the Rutschblock failure layer was identified.

The data are provided in the following form: one file each per observed and simulated snow profile (2x512 files DAV, 2x230 files SWISS), two files (1 file DAV, 1 file SWISS) containing the observed information on snow instability, the allocation between observed and simulated failure layer, and all features extracted from the simulated weak layers that were used to develop the RF model.

failure-layer

display_name: failure-layer

rutschblock

display_name: rutschblock

snow-instability

display_name: snow-instability

snow-profiles

display_name: snow-profiles

snow-stratigraphy

display_name: snow-stratigraphy

snowpack

display_name: snowpack

snowpack-simulation

display_name: snowpack-simulation

en: Observed and simulated snow profile data


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

en: Data Forward Scattering

media_type: .zip

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

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

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

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

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

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

albedo

display_name: albedo

photovoltaic

display_name: photovoltaic

shortwave-radiation

display_name: shortwave-radiation

winter-energy-production

display_name: winter-energy-production

envidat

en: EnviDat: the Environmental Data Portal

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

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


en: anemometer wind-speed wind-direction raclets wind wind-velocity

en: Sonic wind component v

media_type: npy

en:
The data contains values for v direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

1. Define moving window uₓ = u(i-3:i+3)
2. If u(i)-mean(uₓ) > 2*std(uₓ):u(i) = NaN

Frozen detectors resulted in continuous zero values (not filtered).
The wind speed and direction were calculated as follows:

wind speed = sqrt(u² + v²)
wind direction = 180° + (180° / PI)* arctan2 (-u, -v)

en: Sonic time

en: The data set contains the time in YYYY-mm-dd HH:MM:SS.sss for the anemometer data. The time is given in UTC+1.

en: Sonic wind component w

en:
The data contains values for w direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

1. Define moving window uₓ = u(i-3:i+3)
2. If u(i)-mean(uₓ) > 2*std(uₓ):u(i) = NaN

Frozen detectors resulted in continuous zero values (not filtered).
The wind speed and direction were calculated as follows:

wind speed = sqrt(u² + v²)
wind direction = 180° + (180° / PI)* arctan2 (-u, -v)

en: Sonic wind component u

en:
The data contains values for u direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

1. Define moving window uₓ = u(i-3:i+3)
2. If u(i)-mean(uₓ) > 2*std(uₓ):u(i) = NaN

Frozen detectors resulted in continuous zero values (not filtered).
The wind speed and direction were calculated as follows:

wind speed = sqrt(u² + v²)
wind direction = 180° + (180° / PI)* arctan2 (-u, -v)

en: Sonic temperature

en: The data set contains values of temperature (°C) measured with the anemometer at a sampling frequency of 20 Hz.

en: A Young 81000 sonic anemomenter was deployed at Gotschnagrat (LON: 46.859 LAT: 9.849) to record three components of the wind velocity (u, v, w in [m s‾ ¹]) and air temperature (Ts in [°C]). The anemomenter was mounted in direction North at a height of 1.5 m above snow surface at the beginning. The time within each data set is given in UTC+1. Instrument specifications can be found [here](http://www.youngusa.com/Manuals/81000-90(I).pdf) .

anemometer

display_name: anemometer

raclets

display_name: raclets

wind

display_name: wind

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

wind-velocity

display_name: wind-velocity

education

en: Education and science

en: Snow Drift Station - 3D Ultrasonic


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

en: Wetlands 1850 - 2010 (shapefiles)

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

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

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

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

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

ecology

display_name: ecology

environmental---history

display_name: environmental---history

environmental--policy

display_name: environmental--policy

historical-carthography

display_name: historical-carthography

switzerland

display_name: switzerland

wetlands

display_name: wetlands

envidat

en: EnviDat: the Environmental Data Portal

en: History of wetlands in Switzerland since 1850


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

en: Data Compilation

en: Compressed TXT files

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

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

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

vertical-wind-motion

display_name: vertical-wind-motion

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

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


maintainer: Thorsten Bartels-Rausch

en: antarctica brine arctic metamorphism reaction ozone snow heterogeneous alpine solution laboratory-study interface chemistry

en: Matlab Script to view and plot data

media_type: .m

en: Readme file

media_type: application/pdf

en: This file shows data, code, and plots.

format: PDF

mimetype: application/pdf

en: Acetone data

media_type: dat

en:
intensity of the acetone-water-cluster and water-cluster (as derived by a chemical ionisation mass spectrometer) with time in the carrier gas downstream of packed bed flow tube holding the snow sample or the by-pass, respectively. Time "0" denotes the time when the mass spectrometer data acquisition was started. When the carrier
gas with acetone was passed via the packed bed flow tube, that is switched from by-pass to pass the snow, acetone concentration in the carrier gas rapidly dropped due to surface adsorption and slowly recovered as the adsorption sites saturate. From this, the surface area can be obtained.

en: Ozone data

en: Trend of ozone mixing ratio ( _O3mixingRatio_ppb_ with time ( _time_s_ ) as measured downstream of the snow sample during the experiments. Time "0" denotes the time when data acquisition with ozone analyser was started. And, ozone (_nOzone_molec_per_s_ ) loss for each experiment with duration of ozone exposure ( _duration_s_ ) of ozone exposure, as derived from the ozone trends shown above. Time "0" denotes the time when the carrier gas with ozone was passed via the snow sample.

en: data list

en: Lists file names, snow sample properties, and flow settings for each data-set.

en: Data Figure 1

en: Data of published Figure

en: Matlab Data

media_type: mat

en: All data as Matlab mat file

en: Earth’s snow cover is very dynamic on diurnal time scales. The changes to the snow structure during this metamorphism have wide ranging impacts such as on avalanche formation and on the capacity of surface snow to exchange trace gases with the atmosphere. Here, we investigate the influence of dry metamorphism, which involves fluxes of water vapor, on the chemical reactivity of bromide in the snow. For this, the heterogeneous reactive loss of ozone at a concentration of 5-6E12 molecules cm-3 is investigated in artificial, shock-frozen snow samples doped with 6.2 uM sodium bromide and with varying metamorphism history. The oxidation of bromide in snow is one reaction initiating polar bromine releases and ozone depletions.

alpine

display_name: alpine

antarctica

display_name: antarctica

arctic

display_name: arctic

brine

display_name: brine

chemistry

display_name: chemistry

heterogeneous

display_name: heterogeneous

interface

display_name: interface

laboratory-study

display_name: laboratory-study

metamorphism

display_name: metamorphism

ozone

display_name: ozone

reaction

display_name: reaction

snow

display_name: snow

solution

display_name: solution

en: Data set on bromide oxidation by ozone in snow during metamorphism from laboratory study


vegetation-height-model-nfi

maintainer: Christian Ginzler

title_for_slug: vegetation-height-model-nfi

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

en: Thumbnail

media_type: image/jpeg

mimetype: image/jpeg

en: 2019 Vegetation Height Model NFI (current)

media_type: geotiff

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

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

format: GeoTIFF

en: 2015 Vegetation Height Model NFI

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

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

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

media_type: PDF

en: 2016 Vegetation Height Model NFI

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

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

en: 2012 Vegetation Height Model NFI

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

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

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

Latest version is from 2019.

forest

display_name: forest

photogrammety

display_name: photogrammety

point-cloud

display_name: point-cloud

vegetation-height-model

display_name: vegetation-height-model

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Vegetation Height Model NFI


maintainer: Frank Techel

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

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

media_type: text/plain

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

format: TXT

mimetype: text/plain

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

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

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

avalanche-accident

display_name: avalanche-accident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

avalanche-statistics

display_name: avalanche-statistics

long-term-trends

display_name: long-term-trends

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


maintainer: Tessa Hegetschweiler

en: childhood teenagers recreational-activities forest adolescents

en: Dataset survey at schools

en: The dataset of the questionnaire survey at schools in excel format.

en: Survey at schools 2017

en: The dataset of the questionnaire survey at schools in SPSS-format.

en: Questionnaire school survey

en: The questionnaire used in the survey at 8 schools aimed at teenagers in German.

en: Dataset comments

en: The codebook to the dataset

en: The data results from a questionnaire survey conducted at 8 schools in the cantons Zurich, Aargau and St. Gallen. Respondents aged 13-22 years. The aim of the survey was to gain insight into teenagers' relationship to the forest, reasons for visiting or not visiting the forest and activities in the forest.

adolescents

display_name: adolescents

childhood

display_name: childhood

recreational-activities

display_name: recreational-activities

teenagers

display_name: teenagers

en: Factors influencing teenagers' forest visit frequency


irkis-soil-moisture-measurements-davos

maintainer: Nander Wever

title_for_slug: irkis-soil-moisture-measurements-davos

en: meteo-station soil-moisture meteorological-measurements dischma-catchment davos

en: IRKIS soil moisture data (zip file)

en: Compressed archive (zip) containing soil moisture measurements, as well as meteorological measurements and interpolated meteorological time series.

en:
Meteorological and soil moisture measurements from soil moisture stations installed from October 2010 - October 2013 in the area surrounding Davos, in particular in the Dischma catchment.

There are in total 7 stations: 1202, 1203, 1204, 1205, 222, 333 and SLF2. For each of the stations, there is a:

* vwc_[stn].smet: containing the soil moisture measurements

* station_[stn].smet: in-situ measured meteorlogical parameters. Note, the quality of these measurements for stations 1202, 1203, 1204 and 1205 is very low, with data gaps. Use this data with care. For stations 222, 333 and SLF2, data quality is high and only the default cautiousness should be applied.

* interpolatedmeteo_[stn].smet contains per stations a dataset derived by interpolating from several stations in the Davos area to the stations location. This dataset was generated from the output of the Alpine3D model, of which simulations are presented in the Wever et al. (2017) manuscript.

At the soil moisture measurement sites, Decagon 10HS sensors were installed, at 10, 30, 50, 80 and 120 cm depth. Per depth 2 sensors were installed, labelled A and B in the datafiles. Note that at stations 1203, 1204 and 1205, sensors were only installed at 10, 30 and 50 cm depth.

The files follow the SMET format: https://models.slf.ch/docserver/meteoio/SMET_specifications.pdf and metadata for the stations can be found in the header of the smet files.

Please cite the Wever et al. (2017) reference when using this data in publications.

For a more detailed description, please refer to: Wever, N., Comola, F., Bavay, M., and Lehning, M.: Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment, Hydrol. Earth Syst. Sci., 21, 4053-4071, https://doi.org/10.5194/hess-21-4053-2017, 2017.

davos

display_name: davos

dischma-catchment

display_name: dischma-catchment

meteo-station

display_name: meteo-station

meteorological-measurements

display_name: meteorological-measurements

soil-moisture

display_name: soil-moisture

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: IRKIS Soil moisture measurements Davos


backward-trajectories

maintainer: Michael Sprenger

title_for_slug: backward-trajectories

en: atmospheric-dynamics complex-topopgraphy cosmo raclets lagrangian-analysis backward-trajectories alps

en: Backward Trajectories

en: The trajectories are started from surface up to 5000 m altitude, with an equidistant vertical spacing of 200 m, and calculated 120 h backward in time. As long as the trajectories stay in the COSMO1 domain (essentially the Alpine region), as run operationally at MeteoSwiss, the COSMO analysis wind fields are used. When the trajectories leave this domain, they are extended further backward in time based on ECMWF analysis data. The following fields are traced along the trajectories: longitude, latitude, geopotential height, pressure, specific humidity, temperature and surface topography. Furthermore, it is indicated for each trajectory time instance on which model data, COSMO or ECMWF, the trajectory time is based. Finally, the trajectories are started every hour in the specified time period, and positions and fields are available every 10 min. Each day is saved as a separate file. The last 8 digits of the file names indicate the starting date of the trajectories.

en: Backward trajectories were calculated from two positions: Davos Wolfgang (LON: 9.85361, LAT: 46.83551) and Weissfluhjoch (LON: 9.80646 LAT: 46.83304) for the time period February 2 until March 27 2019 using COSMO or ECMWF, respectively.

alps

display_name: alps

atmospheric-dynamics

display_name: atmospheric-dynamics

backward-trajectories

display_name: backward-trajectories

complex-topopgraphy

display_name: complex-topopgraphy

cosmo

display_name: cosmo

lagrangian-analysis

display_name: lagrangian-analysis

raclets

display_name: raclets

en: Backward  Trajectories


maintainer: Henning Löwe

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

en: Angle of repose and 3D CT images

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

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

FC: faceted grains (1.4 - 2 mm)

FCS: small faceted grains (0.7 - 1.4 mm)

IB: ice beads (4 mm)

IBS: small ice beads (2 - 2.2 mm)

GB: glass beads(2 mm)

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

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

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

angle-of-repose

display_name: angle-of-repose

discrete-element-modelling

display_name: discrete-element-modelling

fast-sintering

display_name: fast-sintering

grain-shape

display_name: grain-shape

granular-snow

display_name: granular-snow

en: Angle of repose experiments with natural and spherical snow


maintainer: Lisa Hülsmann

en: tree-growth empirical-mortality-models forest-reserves inventory-data tree-mortality

en: Calibration data

en:
A set of three consecutive inventories was used to generate records for the calibration of mortality models based on trees that were alive in the first and second inventory and either dead or alive in the third inventory.

 Meta data
Reserve: Name of the forest reserve

Plot: Permanent plot number

 Tree data
Species: Latin species name (or species group, cf. _Quercus_ spp.)

y: Status of the tree with 0 = alive and 1 = dead

dt: Length of the mortality period (years)

DBH: Diameter at breast height (mm) of the second inventory

relBAI: Annual relative basal area increment (-) calculated based on the first and the second DBH measurement as the compound annual growth rate of the trees basal area

 Stand data
_All stand variables were calculated for the second inventory._

mDBH: Mean diameter at breast height (mm)

iqrDBH: Interquartile range of diameter at breast height (mm)

BA: Basal area per hectare (m2 ha-1)

N: Number of trees per hectare (ha-1)

 Climate data
_Both climate variables were calculated for the period between the second and the third inventory._

P: Mean annual precipitation sum (mm)

mT: Mean annual air temperature (°C)

en:
The dataset comprises > 90 000 records from inventories in 54 strict forest reserves in [Switzerland](https://www.wsl.ch/de/wald/biodiversitaet-naturschutz-urwald/naturwaldreservate.html) and [Lower Saxony / Germany](http://naturwaelder.de/) along a considerable environmental gradient. It was used to develop parsimonious, species-specific mortality models for 18 European tree species based on tree size and growth as well as additional covariates on stand structure and climate.

 Inventory data
Measurements had been conducted repeatedly on up to 14 permanent plots per reserve for up to 60 years with re-measurement intervals of 4 - 27 years. The permanent plots vary in size between 0.03 and 3.47 ha. The inventories provide diameter measurements at breast height (DBH) and information on the species and status (alive or dead) of trees with DBH ≥ 4 cm for Switzerland and ≥ 7 cm for Germany.

 Data selection
We excluded three permanent plots where at least 80 % of the trees died during an interval of 10 years, and mortality could be clearly assigned to a disturbance agent. Mortality in the remaining stands was rather low, with a mean annual mortality rate of 1.5 % and strong variation between plots from 0 to 6.5 % (assessed for trees of all species with DBH ≥ 7 cm).
We only used data from permanent plots with at least 20 trees per species to obtain reliable plot-level mortality rates even for species with low mortality rates (about 5 % during 10 years), and selected tree species occurring on at least 10 plots to cover sufficient ecological gradients. This led to a dataset of 197 permanent plots and 18 tree or shrub species: _Abies alba_ Mill., _Acer campestre_ L., _Acer pseudoplatanus_ L., _Alnus incana_ Moench., _Betula pendula_ Roth, _Carpinus betulus_ L., _Cornus mas_ L., _Corylus avellana_ L., _Fagus sylvatica_ L., _Fraxinus excelsior_ L., _Picea abies_ (L.) Karst, _Pinus mugo_ Turra, _Pinus sylvestris_ L., _Quercus pubescens_ Willd., _Quercus_ spp. (_Q. petraea_ Liebl. and _Q. robur_ L.; not properly differentiated in the Swiss inventories), _Sorbus aria_ Crantz, _Tilia cordata_ Mill. and _Ulmus glabra_ Huds..

 Predictors of tree mortality
We considered tree size and growth as key indicators for mortality risk. Radial stem growth between the first and second inventory and DBH at the second inventory were used to predict tree status (alive or dead) at the third inventory. To this end, the annual relative basal area increment (relBAI) was calculated as the compound annual growth rate of the trees basal area. Additional covariates on stand structure and climate comprise mean annual precipitation sum (P), mean annual air temperature (mT), the mean and the interquartile range of DBH (mDBH, iqrDBH), basal area (BA) and the number of trees (N) per hectare.

 Further information
For further information, refer to Hülsmann _et al_. (in press) How to kill a tree – Empirical mortality models for eighteen species and their performance in a dynamic forest model. _Ecological Applications_.

empirical-mortality-models

display_name: empirical-mortality-models

forest-reserves

display_name: forest-reserves

inventory-data

display_name: inventory-data

tree-growth

display_name: tree-growth

tree-mortality

display_name: tree-mortality

en: Calibration data for empirical mortality models of 18 European tree species


en: 18o advection snow metamorphism stable-water-isotope

en: Data files and read-me

en: raw data and micro-CT data available from contacts

en: Read-me

en: A short description of the data contained in the zipped-file. Recommended for reading before downloading the dataset.

en:
Stable water isotopes (δ18O) obtained from snow and ice samples of polar regions are used to reconstruct past climate variability, but heat and mass transport processes can affect the isotopic composition. Here we present an experimental study on the effect on the snow isotopic composition by airflow through a snow pack in controlled laboratory conditions. The influence of isothermal and controlled temperature gradient conditions on the δ18O content in the snow and interstitial water vapor is elucidated. The observed disequilibrium between snow and vapor isotopes led to exchange of isotopes between snow and vapor under non-equilibrium processes, significantly changing the δ18O content of the snow. The type of metamorphism of the snow had a significant influence on this process.
Ebner, P. P., Steen-Larsen, H. C., Stenni, B., Schneebeli, M., and Steinfeld, A.: Experimental observation of transient δ18O interaction between snow and advective airflow under various temperature gradient conditions, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-16, accepted, 2017.

advection

display_name: advection

metamorphism

display_name: metamorphism

snow

display_name: snow

stable-water-isotope

display_name: stable-water-isotope

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Experiments on stable water isotopes,  snow metamorphism, and advection


maintainer: Christoph Marty

en: CH2014 REPORT

en:
CH2014-Impacts: Toward Quantitative Scenarios of Climate Change Impacts in Switzerland

The CH2014-Impacts report presents the results of a concerted effort of 15 Swiss research institutions to describe impacts of climate change in Switzerland quantitatively. This dataset contributes to the Crosphere/Snowcover section.

en: Aare input

media_type: application/x-tar

en: Grid input data for the 'Aare' CH2014 simulation.

mimetype: application/x-tar

en: Graubunden input

en: Grid input data for the 'Graubunden' CH2014 simulation.

en: Dataset

en: Datasets are grouped under experiment "Aare" and "Graubunden".Data is also made available in netCDF format. A range of tools are available to [read netCDF](http://www.unidata.ucar.edu/software/netcdf/software.html).

en:
 Overview

The CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change.

 Experimental Setup

Future snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graubünden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m × 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999–2012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085).

 Data

Snow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5–9 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400–800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average.

climate-change

display_name: climate-change

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

en: Alpine3D simulations of future climate scenarios CH2014


maintainer: Anita C. Risch

en: climate fertilization ammonification grassland nitrogen mineralization herbivore nutrient-network soil nitrification global-change

en: Risch et al. 2020 - Raw data for publication "Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties"

en:
we assessed how the removal of mammalian herbivores (Fence) and fertilization with growth-limiting nutrients (N, P, K, plus nine essential macro- and micronutrients; NPK) individually, and in combination (NPK+Fence), affected potential and realized soil net Nmin across 22 natural and semi-natural grasslands on five continents. Our sites spanned a comprehensive range of climatic and edaphic conditions found across the grassland biome. We focused on grasslands, because they cover 40-50% of the ice-free land surface and provide vital ecosystem functions and services. They are particularly important for forage production and C sequestration. Worldwide, grasslands store approximately 20-30% of the Earth’s terrestrial C, most of it in the soil (Schimel, 1995; White et al., 2000).

Study sites and experimental design
The 22 sites contributing to this project are part of the Nutrient Network Global Research Cooperative (NutNet, https://nutnet.umn.edu/). Mean annual temperature across our 22 sites ranged from -4 to 22°C, mean annual precipitation from 252 to 1,592 mm, and elevations from 6 to 4,261 m above sea level (Fig. 1, Supplementary Table S1). Soil organic C varied from 0.8 to 7.8%, soil total N from 0.1 to 0.6%, and the soil C:N ratio from 9.1 to 21.5. Soil clay content spanned from 3.0 to 35%, and soil pH from 3.4 to 7.6 (Supplementary Table S2). Thus, the sites covered a wide range of environments in which grasslands occur (Fig. 1, Supplementary Table S1 & S2).
At each site, the effects of nutrient addition and herbivore removal were tested via a randomized-block design (Borer et al., 2014; Supplementary Fig. S1a). Three replicate blocks with 10 treatment plots each were established at each site, with the exception of the site at bldr.us, where only two blocks were established (Supplementary Fig. S1a). The 10 plots were randomly assigned to a nutrient or fencing treatment, but only a subset of four plots was used in the current study, each with a different treatment (see below; Supplementary Fig. S1a). All plots were 5 x 5 m and divided into four 2.5 x 2.5 m subplots (Supplementary Fig. S1b). Each subplot was further divided into four 1 x 1 m square sampling plots, one of which was set aside for soil sampling (Borer et al., 2014; Supplementary Fig. S1b). Plots were separated by at least 1 m wide walkways.
In this study, we collected data from the following four treatments: (i) untreated control plots (Control), (ii) herbivore removal plots (Fence), (iii) plots fertilized with N, P, K, plus nine essential macro and micronutrients (NPK), and (iv) plots with simultaneous fertilizer addition and herbivore removal (NPK+Fence; Supplementary Fig. S1a). The number of years of treatment differed among sites (2 – 9 years since start of treatment; Supplementary Table S1). For the nutrient additions, all sites applied 10 g N m-2 yr-1 as time-release urea; 10 g P m-2 yr-1 as triple-super phosphate; 10 g K m-2 yr-1 as potassium sulfate. A micro-nutrient mix (Fe, S, Mg, Mn, Cu, Zn, B, Mo, Ca) was applied at 100 g m-2 together with K in the first year of treatments but not thereafter.
The vertebrate herbivore removal treatment (Fence) was established by fencing two plots, one control and one NPK plot, within each of the blocks (Supplementary Fig. S1a). We designed the fences so that they would effectively exclude aboveground mammalian herbivores with a body mass of over 50 g (Borer et al., 2014). At the majority of sites, the height of the fences was 180 cm, and the fence design included wire mesh (1 cm holes) on the first 90 cm along with a 30 cm outward-facing flange stapled to the ground to exclude burrowing animals; climbing and subterranean animals may potentially still access these plots (Borer et al., 2014). For slight modifications in fence design at a few sites see Supplementary Table S3. While most sites only had native herbivores, a few sites (4) were also grazed by domestic animals (Supplementary Table S1).
Potential and realized soil net N mineralization, ammonification, nitrification and other soil properties
Each site participating in the study received a package containing identical material from the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) to be used for sampling and on-site N incubations. For the field incubation, we followed the protocol by Risch et al. (2015, 2019). Briefly, we drove a 5 x 15 cm (diameter x depth) steel cylinder 13.5 cm deep into the soil after clipping the vegetation at randomized locations in each plot. The top 1.5 cm of the cylinder remained empty to capture incoming N from run-off or deposition with a polyester mesh bag (mesh-size 250 µm) filled with 13.2 ± 0.9 g of acidic and alkaline exchanger resin (1:1 mixture; ion-exchanger I KA/ion-exchanger III AA, Merck AG, Darmstadt). The bag was fixed in place with a metal Seeger ring (Bruetsch-Rüegger Holding, Urdorf, Switzerland). We then removed 1.5 cm soil at the bottom of the cylinder and placed another resin bag to capture N leached from the soil column. The exchange resin was saturated with H+ and Cl- prior to filling the bags by stirring the mixture in 1.2M HCl for 1 h and then rinsing it with demineralized water until the electrical conductivity of the water reached 5 μS/cm. The cylinders were then re-inserted into the cored hole, level with the soil surface, and incubated for an average of 42 days (range 40 to 57days). The individual site coordinators chose the timing of incubation to start approximately six weeks prior to peak plant biomass production. All incubations were completed between February 2015 and January 2016 accounting for differences in growing season between northern and southern hemispheres. At the end of the incubation, the cylinders were re-collected and immediately shipped to WSL in an insulated box together with cold packs to halt further mineralization. Gloves were worn at all times to avoid contamination of the samples. Upon arrival at WSL, we extracted the resin bags and a 20 g subsample of sieved soil (4 mm) separately in a 100 ml PE-bottle with 80 ml 1 M KCl for 1.5 h on an end-over-end shaker and filtered through ashless folded filter paper (DF 5895 150, ALBET LabScience). We measured NO3- (colorimetrically; Norman & Stucki, 1981) and NH4+concentrations (flow injection analysis; FIAS 300, Perkin Elmer) on these filtrates.
At the start of the field incubation, we additionally collected two soil cores of 5 x 12 cm (diameter x depth) in each sampling plot and composited them to measure potential soil net Nmin, soil chemical and biological properties (see below). We also collected an additional sample (5 x 12 cm) to assess soil physical properties, which remained within the steel cylinder. Both ends were tightly closed with plastic caps. Cores were carefully packed to avoid further disturbance, and together with the composited soil samples, were shipped to the laboratory at WSL within a few days after collection.
From the composited samples, we extracted an equivalent of 20 g dry soil with KCl, as described above, and measured NO3- and NH4+concentrations. Realized soil net Nmin was then calculated as the difference between the inorganic N content of samples collected at the end of the incubation (plus N extracted from the bottom resin bag) and the N content at the beginning of the incubation; values were scaled to represent daily mineralization rates (mg N kg-1soil d-1; Risch et al., 2015). Realized soil net Nmin values represent an average period of 42 days prior to peak biomass, typically the highest period of biological activity, and not the entire year (Risch et al., 2019).
A second subsample of the composited sample was used to determine potential soil net Nmin in the laboratory (Risch et al., 2019). Briefly, we weighed duplicate samples (8 g dry soil) into 50-ml Falcon tubes. Soil moisture was brought to 60% of the field capacity of each plot, the Falcon tubes tightly closed and then incubated at 20°C for 42 days in a dark room. Every week the Falcon tubes were opened and ventilated. At the end of the incubation, the soil samples were extracted the same way as described above and NO3- and NH4+ was determined. Potential soil net Nmin was calculated as the difference between the N content before and after the incubation and scaled to represent daily values (mg N kg-1soil d-1). Using our NO3- and NH4+ measures we also calculated potential and realized soil net nitrification and soil net ammonification to be able to better understand the drivers of fertilization and herbivore removal effects on potential and realized soil net Nmin.
A third subsample of the composite soil sample was sieved (2 mm mesh) and microbial biomass (μg Cmic g-1 soil dry weight) was estimated by measuring the maximal respiratory response to the addition of glucose solution (4 mg glucose per g soil dry weight dissolved in distilled water; substrate-induced respiration method) on approximately 5.5 g of soil (Anderson & Domsch, 1978). The rest of the composited sample was dried at 65°C for 48 h, ground and sieved (2 mm mesh) to assess a series of soil chemical properties (Risch et al., 2019). We measured the percentage of clay as an indicator of soil texture (Gee & Bauder, 1986; Risch et al., 2019).
Statistical analyses
Potential and realized soil net Nmin were square root transformed to account for a highly skewed data distribution (yt = sign(y)*sqrt|y|; negative values in the data set impeded log transformation). To assess treatment effects on potential and realized soil net Nmin, we used linear mixed effects models (LMMs) fitted by maximum likelihood using the lme function from the nlme package (version 3.131.1; Pinheiro et al., 2016), R version 3.6.1; R Foundation for Statistical Computing. Treatment (Control, Fence, NPK, NPK+Fence) was a fixed factor, with site and block as random factors, where block was nested within site. We also tested for effects of time since start of treatments in preliminary analyses by adding total treatment years as an additional fixed factor. We did not find a significant effect of years of treatment, and thus dropped this variable from the models. The LMMs were corrected using varIdent if the homogeneity of variance criterion was not met (Pinheiro et al., 2016). To visualize our results, we calculated treatment effects using Cohens’ d statistic (Cohen, 1977; Koricheva et al., 2013). Note that calculating response ratios (or log response ratios) was not possible with our data, as we have both negative and positive values. We also fitted LMMs for potential and realized soil net ammonification and nitrification to gain more insight into how global change affects the processes underpinning potential and realized soil net Nmin. We also sqrt-transformed (see above) these dependent variables. Treatment was included as a fixed factor with random factors as described above. In addition, we assessed how potential and realized soil net Nmin were related to potential and realized soil net ammonification and nitrification, respectively. For this, we calculated site averages for each treatment separately. We then ran LMMs, with potential and realized soil net Nmin as the dependent variable, potential and realized soil net ammonification/nitrification as the independent ones. Site was included as a random factor.
Based on our previous work (Risch et al., 2019) and the existing literature (Schimel & Bennett, 2004; Liu et al., 2017), we developed a priori causal conceptual models of relationships among treatments, environmental drivers, and potential and realized soil net Nmin (Supplementary Fig. S2) to test with structural equation modelling (SEM) using a d-sep approach (Shipley, 2009; Lefcheck, 2016). The variables included in the model were long-term climatic conditions, specifically, site-level mean annual precipitation (MAP) and temperature of the wettest quarter (T.q.wet), plot-level soil texture (clay content) and soil microbial biomass. Mean annual precipitation and T.q.wet were obtained from WorldClim (Hijmans et al., 2005) (http://www.worldclim.org/) and together with the experimental treatments were predicted to directly affect soil properties and soil net Nmin (Supplementary Fig. S2). Soil clay content was, in turn, predicted to affect microbial biomass and soil net Nmin. Because we determined microbial biomass prior to incubating the samples in the laboratory or field, we assumed that the abundance of these microbes would be responsible for N process rates and not vice versa (Supplementary Fig. S2). We tested our conceptual model (Supplementary Fig. S2) using the piecewiseSEM package (version 2.0.2; Lefcheck, 2016) in R 3.4.0, in which a structured set of linear models are fitted individually. This approach allowed us to account for the nested experimental design, and overcome some of the limitations of standard structural equation models, such as small sample sizes (Shipley, 2009; Lefcheck, 2016). We used the lme function of the nlme package to model response variables, including site as a random factor. Good fit of the SEM was assumed when Fisher’s C values were non-significant (p > 0.05). For all significant interactions between covariates and experimental treatments detected in the SEMs, we calculated treatment effect sizes, i.e. the differences in potential or realized soil net Nmin between Control and treatments (Fence, NPK, NPK+Fence) and plotted these values against the climate or soil covariates. Finally, we fitted LMMs for the soil variables included in our SEMs, with treatment as the fixed factor, and with site and block as random factors, where block was nested within site.

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

Paper Citation:

Risch Anita C., Zimmermann, Stefan, Moser, Barbara, Schütz, Martin, Hagedorn, Frank, Firn, Jennifer, Fay, Philip A., Adler, Peter B., Biederman, Lori A., Blair, John M., Borer, Elizabeth T., Broadbent, Arthur A.D., Brown, Cynthia S., Cadotte, Marc W., Caldeira, Maria C., Davies, Kendi F., di Virgilio, Augustina, Eisenhauer, Nico, Eskelinen, Anu, Knops, Johannes M.H., MacDougall, Andrew S., McCulley, Rebecca L., Melbourne, Brett A., Moore, Joslin L., Power, Sally A., Prober, Suzanne M., Seabloom, Eric W., Siebert, Julia, Silveira, Maria L. , Speziale, Karina L., Stevens, Carly J., Tognetti, Pedro M., Virtanen, Risto, Yahdjian, Laura, Ochoa-Hueso, Raul (accepted). Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties. Global Change Biology

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

We assessed how the removal of mammalian herbivores (Fence) and fertilization with growth-limiting nutrients (N, P, K, plus nine essential macro- and micronutrients; NPK) individually, and in combination (NPK+Fence), affected potential and realized soil net Nmin across 22 natural and semi-natural grasslands on five continents. Our sites spanned a comprehensive range of climatic and edaphic conditions found across the grassland biome. We focused on grasslands, because they cover 40-50% of the ice-free land surface and provide vital ecosystem functions and services. They are particularly important for forage production and C sequestration. Worldwide, grasslands store approximately 20-30% of the Earth’s terrestrial C, most of it in the soil (Schimel, 1995; White et al., 2000).

ammonification

display_name: ammonification

climate

display_name: climate

fertilization

display_name: fertilization

global-change

display_name: global-change

grassland

display_name: grassland

herbivore

display_name: herbivore

mineralization

display_name: mineralization

nitrification

display_name: nitrification

nitrogen

display_name: nitrogen

nutrient-network

display_name: nutrient-network

soil

display_name: soil

en: Anthropogenic change and soil net N mineralization