de: Datenstruktur auf Deutsch

en: Data structure in German

de: Migration von Erwerbstätigen nach Jahr, Richtung, Wirtschaftszweig und Geschlecht bei Jahr, Richtung, Wirtschaftszweig und Geschlecht

en: Migration of employed persons by Year, Direction, Economic activity and Sex by Year, Direction, Economic activity and Sex

migration-binnenwanderung

display_name: migration-binnenwanderung

migration-internal-migration

display_name: migration-internal-migration

soci

de: Bevölkerung und Gesellschaft

en: Population and society

intr

de: Internationale Themen

en: International issues

de: Migration von Erwerbstätigen nach Richtung, Wirtschaftszweig und Geschlecht seit 2012

en: Migration of employed persons by direction, economic activity and sex since 2012


state: active

type: dataset

de: Datenwürfel auf Deutsch

en: Data cube in German

media_type: text/html

format: HTML

de: Datenstruktur auf Englisch

en: Data structure in English

media_type: application/json

format: JSON

de: Datenwürfel auf Englisch

en: Data cube in English

de: Vollzeitäquivalente bei Jahr, Wirtschaftszweig, Arbeitsgemeinde und Geschlecht

en: Full-time equivalents by Year, Economic activity, Municipality of work and Sex

beschaftigung

display_name: beschaftigung

employment

display_name: employment

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

political_level: other

liechtenstein

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: DCAT Harvester Amt für Statistik FL

de: Vollzeitäquivalente nach Wirtschaftszweig, Arbeitsgemeinde und Geschlecht seit 2008

en: Full-time equivalents by economic activity, municipality of work and sex since 2008


de: Durchschnittlicher Nettomietpreis nach Stichtag, Wohnungsfläche und Gemeinde

en: Average net rent by Reference date, Useful floor space and Municipality

mietpreise

display_name: mietpreise

rental-prices

display_name: rental-prices

de: Durchschnittlicher Nettomietpreis nach Wohnungsfläche und Gemeinde

en: Average net rent by useful floor space and municipality


de: Erdgaspreise für Haushalte und Kleingewerbe bei Jahr, Tarifgruppe und Jahresbezugsmenge (Brennwert Ho)

en: Natural gas prices for households and small businesses by Year, Tariff group and Annual quantity purchased (gross calorific value GCV)

energiepreise

display_name: energiepreise

energy-prices

display_name: energy-prices

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

de: Erdgaspreise für Haushalte und Kleingewerbe nach Tarifgruppe und Jahresbezugsmenge von 2004 bis 2014

en: Natural gas prices for households and small businesses by tariff group and annual quantity purchased from 2004 to 2014


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Verpackungsabfälle bei Jahr und Materialkategorie

en: Packaging waste by Year and Material category

abfall

display_name: abfall

waste

display_name: waste

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

de: Verpackungsabfälle nach Materialkategorie seit 2006

en: Packaging waste by material category since 2006


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Einbürgerungen im ordentlichen Verfahren bei Jahr, Heimatgemeinde und Geschlecht

en: Naturalisations by ordinary procedure by Year, Home municipality and Sex

einburgerungen

display_name: einburgerungen

naturalisations

display_name: naturalisations

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

intr

fr: Questions internationales

de: Internationale Themen

en: International issues

it: Tematiche internazionali

de: Einbürgerung im ordentlichen Verfahren nach Heimatgemeinde und Geschlecht seit 1970

en: Naturalisations by ordinary procedure by home municipality and sex since 1970


de: Datenstruktur auf Englisch

en: Data structure in English

de: Datenwürfel auf Englisch

en: Data cube in English

de: Erwerbstätige Bevölkerung nach Stichtag, Wirtschaftszweig, Geschlecht und Arbeitsstunden pro Woche

en: Population in gainful employment by Reference date, Branch of economic activity, Sex and Working hours per week

employment-structure

display_name: employment-structure

erwerbsstruktur-berufe

display_name: erwerbsstruktur-berufe

econ

de: Wirtschaft und Finanzen

en: Economy and finance

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Erwerbstätige Bevölkerung nach Wirtschaftszweig, Geschlecht und Arbeitsstunden

en: Population in gainful employment by branch of economic activity, sex and working hours


maintainer: Amt für Statistik

de: Wertstoffe bei Jahr und Wertstoffkategorie

en: Recyclable materials by Year and Recyclable material category

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Wertstoffe nach Wertstoffkategorie seit 1985

en: Recyclable materials by recyclable material category since 1985


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Erstzugelassene Personenwagen bei Jahr, Treibstoff (detailliert) und Importart

en: Passenger cars registered for the first time by Year, Type of fuel (detailed) and Kind of import

fahrzeug-erstzulassungen

display_name: fahrzeug-erstzulassungen

mobility-and-transport

display_name: mobility-and-transport

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

de: Erstzugelassene Personenwagen nach Treibstoff (detailliert) und Importart

en: Passenger cars registered for the first time by type of fuel (detailed) and kind of import


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Interne F+E-Aufwendungen bei Jahr, Finanzierungsart und Sektor

en: Intramural expenditure on R+D by Year, Type of funding and Sector

forschung-und-entwicklung

display_name: forschung-und-entwicklung

research-and-development

display_name: research-and-development

tech

fr: Science et technologie

de: Wissenschaft und Technologie

en: Science and technology

it: Scienza e tecnologia

de: Interne F+E-Aufwendungen nach Finanzierungsart und Sektor seit 2019

en: Intramural expenditure on R+D by type of funding and sector since 2019


de: Datenstruktur auf Englisch

en: Data structure in English

de: Ergebnisse der Landtagswahlen bei Jahr, Kennzahl, Partei und Wahlkreis

en: Results of parliamentary elections by Year, Key figure, Political party and Constituency

elections-referendums

display_name: elections-referendums

wahlen-abstimmungen

display_name: wahlen-abstimmungen

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

de: Ergebnisse der Landtagswahlen nach Wahlkreis und Partei seit 1945

en: Results of parliamentary elections by constituency and political party since 1945


de: Datenwürfel auf Englisch

en: Data cube in English

de: Konsolidiert - Konsolidierte Indikatoren bei Jahr, Indikator und Bereich

en: Consolidated - Consolidated indicators by Year, Indicator and Area

banken

display_name: banken

banking-institutions

display_name: banking-institutions

econ

de: Wirtschaft und Finanzen

en: Economy and finance

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Konsolidiert - Konsolidierte Indikatoren nach Bereich seit 2017

en: Consolidated - Consolidated indicators by area since 2017


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Ständige Bevölkerung bei Jahr, Bewilligungskategorie, Geschlecht und Wohngemeinde

en: Permanent resident population by Year, Residence permit category, Sex and Municipality of residence

bevolkerungsstand

display_name: bevolkerungsstand

population-stock

display_name: population-stock

soci

de: Bevölkerung und Gesellschaft

en: Population and society

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Ständige Bevölkerung nach Bewilligungskategorie, Geschlecht und Wohngemeinde seit 2000

en: Permanent resident population by residence permit category, sex and municipality of residence since 2000


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Privathaushalte bei Jahr, Bruttovermögensklasse und Schuldenklasse

en: Private households by Year, Gross wealth category and Debt category

vermogens--und-einkommensverteilung

display_name: vermogens--und-einkommensverteilung

wealth-and-income-distribution

display_name: wealth-and-income-distribution

de: Privathaushalte nach Bruttovermögens- und Schuldenklasse seit 2020

en: Private households by Gross wealth category and Debt category since 2020


de: Datenstruktur auf Englisch

en: Data structure in English

de: Kennzahlen der Luftqualität bei Jahr, Standort und Kennzahl

en: Key figures on air quality by Year, Location and Key figure

air-climate

display_name: air-climate

luft-klima

display_name: luft-klima

envi

de: Umwelt

en: Environment

de: Kennzahlen der Luftqualität nach Standort und Kennzahl seit 1990

en: Key figures on air quality by location and key figure since 1990


author: Amt für Statistik

de: Datenwürfel auf Englisch

en: Data cube in English

de: Kennzahlen der Vorsteherwahlen nach Jahr, Kennzahl und Gemeinde

en: Key figures on mayorial elections by Year, Key figure and Municipality by Year, Key figure and Municipality

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

de: Kennzahlen der Vorsteherwahlen nach Gemeinde seit 1975

en: Key figures on mayoral elections by municipality and political party since 1975


de: Alle Beherbergungsarten bei Jahr, Kennzahl, Monat und Beherbergungsart

en: All types of accommodation by Year, Key figure, Month and Type of accommodation

tourism

display_name: tourism

tourismus

display_name: tourismus

econ

de: Wirtschaft und Finanzen

en: Economy and finance

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Alle Beherbergungsarten - Gästeankünfte, Logiernächte und Aufenthaltsdauer nach Monat und Beherbergungsart seit 2012

en: All types of accommodation - Arrivals, nights spent and length of stay by month and type of accommodation since 2012


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Hotellerie bei Jahr, Kennzahl und Monat

en: Hotels and similar accommodation by Year, Key figure and Month

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Hotellerie - Kennzahlen nach Monat seit 2008

en: Hotels and similar accommodation - Key data by month since 2008


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Gesundheitsausgaben in Tausend CHF bei Jahr, Funktion der Gesundheitsversorgung, Ort der Leistung und Finanzierungssystem

en: Health accounts in thousand CHF by Year, Function, Place of activity and Financing scheme

gesundheitsausgaben

display_name: gesundheitsausgaben

health-accounts

display_name: health-accounts

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

de: Gesundheitsausgaben in Tausend CHF nach Funktion der Gesundheitsversorgung, Ort der Leistung und Finanzierungssystem seit 2013

en: Health accounts in thousand CHF by function, place of activity and financing schemes since 2013


de: Datenstruktur auf Englisch

en: Data structure in English

de: Wohnbevölkerung bei Jahr, Heimat, Geschlecht und Wohngemeinde

en: Resident population by Year, Citizenship, Sex and Municipality of residence

soci

de: Bevölkerung und Gesellschaft

en: Population and society

de: Wohnbevölkerung nach Heimat, Geschlecht und Wohngemeinde seit 1960

en: Resident population by citizenship, sex and municipality of residence since 1960


de: Datenwürfel auf Englisch

en: Data cube in English

de: Privathaushalte bei Jahr, Haushaltsgrösse, Vermögen und Vermögensklasse

en: Private households by Year, Household size, Wealth and Wealth category

de: Privathaushalte nach Vermögensklasse und Haushaltsgrösse seit 2020

en: Private households by wealth category and household size since 2020


de: Erstzugelassene Personenwagen bei Jahr, Treibstoffart, Gesamtgewichtsklasse und Leistungsklasse

en: Passenger cars registered for the first time by Year, Type of fuel, Maximum gross weight class and Engine power class

fahrzeug-erstzulassungen

display_name: fahrzeug-erstzulassungen

mobility-and-transport

display_name: mobility-and-transport

tran

de: Verkehr

en: Transport

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Erstzugelassene Personenwagen nach Treibstoffart, Gesamtgewichtsklasse und Leistungsklasse

en: Passenger cars registered for the first time by type of fuel, maximum gross weight class and engine power class


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Erstzugelassene Personenwagen bei Jahr, Leergewichtsklasse, Leistungsklasse und Monat

en: Passenger cars registered for the first time by Year, Unladen weight class, Engine power class and Month

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Erstzugelassene Personenwagen nach Leergewichtsklasse, Leistungsklasse und Monat

en: Passenger cars registered for the first time by unladen weight class, engine power class and month


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Erstzugelassene Sachentransportfahrzeuge bei Jahr, Nutzfahrzeugart und Mittlere Kennzahlen

en: Goods vehicles registered for the first time by Year, Type of utility vehicle and Average key figures

de: Erstzugelassene Sachentransportfahrzeuge nach Nutzfahrzeugart sowie mittlere Kennzahlen (Nutzlast, Hubraum, Leistung, CO2-Emission)

en: Goods vehicles registered for the first time by type of utility vehicle  as well as average key figures (load weight, engine capacity, engine power, CO2 emission)


de: Datenstruktur auf Englisch

en: Data structure in English

de: Einnahmen aus umweltbezogenen Abgaben bei Jahr und Abgabenkategorie

en: Revenue from environmental related levies by Jahr and Levies category

environmental-levies

display_name: environmental-levies

umweltabgaben

display_name: umweltabgaben

envi

de: Umwelt

en: Environment

de: Einnahmen aus umweltbezogenen Abgaben nach Abgabenkategorie seit 1997

en: Revenue from environmental related levies by levies category since 1997


de: Datenwürfel auf Englisch

en: Data cube in English

de: Einzelbasis - Nachrangige Bilanzpositionen bei Jahr, Nachrangige Bilanzposition und Domizil

en: Individual basis - Subordinated balance sheet items by Year, Subordinated balance sheet item and Domicile

econ

de: Wirtschaft und Finanzen

en: Economy and finance

de: Einzelbasis - Nachrangige Bilanzpositionen nach Domizil seit 2017

en: Individual basis - Subordinated balance sheet items by domicile since 2017


de: Prämienverbilligungen nach Jahr, Altersgruppe, Geschlecht und Einheit bei Jahr, Altersgruppe, Geschlecht und Einheit

en: Premium reductions by Year, Age group, Sex and Unit

social-benefits

display_name: social-benefits

sozialleistungen

display_name: sozialleistungen

soci

de: Bevölkerung und Gesellschaft

en: Population and society

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Prämienverbilligungen nach Altersgruppe und Geschlecht seit 2001

en: Premium reductions by age group and sex since 2001


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Ständige Bevölkerung ab 15 Jahren nach Stichtag, Anzahl Kinder, Heimat, Geschlecht und Fünfjahresklassen

en: Permanent resident population aged 15 years and over by Reference date, Number of children, Citizenship, Sex and Age group

bevolkerungsstruktur

display_name: bevolkerungsstruktur

population-structure

display_name: population-structure

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Ständige Bevölkerung ab 15 Jahren nach Anzahl Kindern, Heimat, Geschlecht und Fünfjahresklassen

en: Permanent resident population aged 15 years and over by number of children, citizenship, sex and age group


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Monatlicher Bruttolohn nach Jahr, Vollzeit/Teilzeit, Alter, Geschlecht und Kennzahl

en: Gross monthly wage by Year, Full-time/Part-time, Age, Sex and Key figure

lohne

display_name: lohne

wages

display_name: wages

de: Monatlicher Bruttolohn nach Voll-/Teilzeit, Alter (5-Jahres-Klassen) und Geschlecht

en: Gross monthly wage by full-/part-time, age (5-year groups) and sex


de: Datenstruktur auf Englisch

en: Data structure in English

de: Lernende in Liechtenstein bei Jahr, Bildungsfeld, Geschlecht und Wohnland

en: Apprentices in Liechtenstein by Year, Field of education, Sex and Country of residence

duale-ausbildung

display_name: duale-ausbildung

vocational-education-and-training

display_name: vocational-education-and-training

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

de: Lernende in Liechtenstein nach Bildungsfeld, Wohnland und Geschlecht seit 2014/15

en: Apprentices in Liechtenstein by field of education, country of resindence and sex since 2014/15


de: Datenwürfel auf Englisch

en: Data cube in English

de: Warenhandel nach Jahr, Verwendungszweck, Richtung und Einheit

en: Trade in goods by Year, Broad economic categories, Traffic direction and Unit

foreign-trade-in-goods

display_name: foreign-trade-in-goods

warenhandel

display_name: warenhandel

de: Warenhandel nach Verwendungszweck und Richtung 1995 bis 2019

en: Trade in goods by broad economic categories and traffic direction 1995 to 2019


de: Bevölkerung nach Szenario, Heimat, Geschlecht, Fünfjahresklasse und Jahr

en: Population by Scenario, Citizenship, Sex, five-year age group and Year

bevolkerungsszenarien

display_name: bevolkerungsszenarien

population-scenarios

display_name: population-scenarios

soci

de: Bevölkerung und Gesellschaft

en: Population and society

de: Bevölkerung nach Szenario, Heimat, Geschlecht und Fünfjahresklasse von 2023 bis 2060

en: Population by Scenario, Citizenship, Sex and five-year age group from 2023 to 2060


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Studierende an Hochschulen in Liechtenstein nach Jahr, Fächergruppe, Geschlecht, Ausbildungsstätte und Studienstufe

en: Students at institutions of higher education in Liechtenstein by Year, Field of study, Sex, Institution and Academic degree

hochschulen

display_name: hochschulen

tertiary-education

display_name: tertiary-education

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Studierende an Hochschulen in Liechtenstein nach Fächergruppe, Geschlecht, Ausbildungsstätte und Studienstufe seit 2005/06

en: Students at institutions of higher education in Liechtenstein by field of study, sex, institution and academic degree since 2005/06


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Einzelbasis - Indikatoren bei Jahr, Indikator und Bereich

en: Individual basis - Indicators by Year, Indicator and Area

banken

display_name: banken

banking-institutions

display_name: banking-institutions

econ

de: Wirtschaft und Finanzen

en: Economy and finance

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Einzelbasis - Indikatoren nach Bereich seit 2017

en: Individual basis - Indicators by area since 2017


de: Datenstruktur auf Englisch

en: Data structure in English

de: Eintragungen und Auflösungen von Partnerschaften bei Jahr, Geschlecht, Partnerschaften und Kennzahl

en: Registrations and dissolutions of partnerships by Year, Sex, Partnerships and Indicator

ehen-partnerschaften

display_name: ehen-partnerschaften

marriages-partnerships

display_name: marriages-partnerships

de: Eintragungen und Auflösungen von Partnerschaften seit 2011

en: Registrations and dissolutions of partnerships since 2011


de: Datenwürfel auf Englisch

en: Data cube in English

de: Einkommensverteilungskonto zu laufenden Preisen 2013 - 2016 bei Jahr, Transaktion und Wirtschaftsbereich

en: Allocation of primary income account at current prices 2013 - 2016 by Year, Transaction and Economic activity

national-accounts

display_name: national-accounts

volkswirtschaftliche-gesamtrechnungen

display_name: volkswirtschaftliche-gesamtrechnungen

de: Einkommensverteilungskonto zu laufenden Preisen 2013 - 2016 nach Wirtschaftsbereich

en: Allocation of primary income account at current prices 2013 - 2016 by economic activity


de: Einzelbasis - Bilanz (Passiven) bei Jahr, Passiven, Währungsgebiet und Währung

en: Individual basis - Balance sheet (liabilities) by Year, Liabilities, Currency area and Currency

de: Einzelbasis - Bilanz (Passiven) nach Währungsgebiet und Währung seit 2017

en: Individual basis - Balance sheet (liabilities) by currency area and currency since 2017


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Einkommensentstehungskonto zu laufenden Preisen 1998 - 2013 by Jahr, Transaktion and Wirtschaftsbereich

en: Generation of income account at current prices 1998 - 2013 by Year, Transaction and Economic activity

de: Einkommensentstehungskonto zu laufenden Preisen 1998 - 2013 nach Wirtschaftsbereich

en: Generation of income account at current prices 1998 - 2013 by economic activity


de: Nichtständige Bevölkerung bei Jahr, Staatsbürgerschaft, Geschlecht und Bewilligungskategorie

en: Non-permanent resident population by Year, Citizenship, Sex and Municipality of residence

bevolkerungsstand

display_name: bevolkerungsstand

population-stock

display_name: population-stock

soci

de: Bevölkerung und Gesellschaft

en: Population and society

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Nichtständige Bevölkerung nach Staatsbürgerschaft, Geschlecht und Bewilligungskategorie seit 2000

en: Non-permanent resident population in gainful employment by citizenship, sex and residence permit category since 2000


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Ständige Bevölkerung ab 15 Jahren nach Stichtag, Sozioprofessionelle Kategorie, Heimat, Geschlecht und Wohngemeinde

employment-structure

display_name: employment-structure

erwerbsstruktur-berufe

display_name: erwerbsstruktur-berufe

econ

de: Wirtschaft und Finanzen

en: Economy and finance

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Ständige Bevölkerung ab 15 Jahren nach sozioprofessioneller Kategorie, Heimat, Geschlecht und Wohngemeinde


de: Datenwürfel auf Englisch

de: Datenstruktur auf Englisch

en: Data structure in English

de: Einzelbasis - Bilanz (Passiven) bei Jahr, Passiven und Fälligkeit

en: Individual basis - Balance sheet (liabilities) by Year, Liabilities and Maturity

de: Einzelbasis - Bilanz (Passiven) nach Fälligkeit seit 2017

en: Individual basis - Balance sheet (liabilities) by maturity since 2017


en: Data cube in English

de: Nutztierbestand bei Jahr, Tierkategorie und Grössenklasse | Zone | Region

en: Livestock by Year, Animal category and Size class | zone | region

agriculture

display_name: agriculture

landwirtschaft

display_name: landwirtschaft

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

de: Nutztierbestand nach Tierkategorie (detailliert), Grössenklasse, Zone und Region seit 2005

en: Livestock by animal category (detailed), size class, zone and region since 2005


maintainer: EnviDat Support

en: occupancy-models wetlands landscape amphibians conservation connectivity

en: Structural connectivity data

media_type: text/csv

en: This file contains structural connectivity data (three different metrics), calculated based on all existing ponds in each year, in long format. See Readme v2.0 for details. Required to run Model code 2.

format: CSV

en: Potential population connectivity data

en: This file contains potential population connectivity data (three different metrics), calculated based on all existing and occupied ponds in each year, for each species, in long format. See Readme v2.0 for details. Required to run Model code 2.

en: Model code, description

en: This is the output of the R markdown file that provides JAGS model code and describes how to format the provided data and fit the dynamic occupancy models described in the associated publication, for a quick overview.

en: Original raw data

en: This file contains the original raw monitoring data as provided by the canton of Aargau. Access is restricted and only considered upon request and in consultation with the canton of Aargau.

format: XLS

en: Covariate data 2

en: This file contains covariate data that changes over time for 856 ponds in 21 years (long format): whether or not a pond exists in year _t_, the age of constructed ponds in year _t_, structural connectivity of the pond in year _t_.

en: Covariate data 1

en: This file contains covariate data that does not change over time for 856 ponds: the region the pond is in, whether the pond is old or new (constructed since 1991), elevation, water surface area, fluctuations of the water table (yes, no), the percent forest cover in 100m radius around the pond, the area or large (>6m wide) roads in 1km radius around the pond.

en: Observation data

en: This file contains detection/non-detection data for the 12 amphibian species between 1999 and 2019 for 3 annual visits. Detectable denotes whether or not a visit j was made to pond i in year t. ObservedID gives a unique ID for the observer collecting the data during visit j to pond i in year t.

en: Model code 2, description

en: This is the output of the R markdown file Model code 2 that provides JAGS model code and describes how to format the provided data and fit the dynamic occupancy models described in the second associated publication, for a quick overview.

en: Model code

en: This R markdown file contains all code and descriptions necessary to load and format the provided data and to fit the dynamic occupancy models described in the associated publication, including JAGS code for the fitted models.

format: SERVICE

en: Model code 2

en: This R markdown file contains all code and descriptions necessary to load and format the provided data and to fit the dynamic occupancy models described in the second associated publication, including JAGS code for the fitted models.

format: OCTET

en: Readme

media_type: application/pdf

en: Description of methods and datasets. Version 1.

format: PDF

en: Readme, v 2.0

en: Description of methods and datasets. Version 2.0, including new datasets fro structural and potential population connectivity.

en:
In the canton of Aargau, hundreds of new ponds have been constructed since the 1990s to benefit declining amphibian populations. This dataset consists of monitoring data for all 12 pond-breeding amphibian species in the canton of Aargau from 1999 to 2019 in 856 ponds, and environmental variables that describe the ponds and the landscape surrounding the ponds. Species observation data is detection/non-detection data from repeat visits during survey years, during which all potentially suitable ponds in an area were surveyed. Environmental variables describing the ponds are whether the pond has been newly constructed since 1991 or not, pond age (if constructed), elevation a.s.l., the water surface area, and whether the water table fluctuates or not. Environmental variables describing the surroundings of the ponds are the percent area of forest within a circular buffer of radius 100m around the pond, the area of large (width ≥6m) roads within a circular buffer of radius 1km around the pond, as well as structural and potential population connectivity, quantified by three different metrics each.
The canton of Aargau is the owner of the monitoring data; the original datafile is only disclosed upon request and in consultation with the canton of Aargau.
The edited dataset contains cleaned observation data for the 12 amphibian species, as well as compiled and edited covariate data and code to fit dynamic occupancy models.

amphibians

display_name: amphibians

connectivity

display_name: connectivity

conservation

display_name: conservation

landscape

display_name: landscape

occupancy-models

display_name: occupancy-models

wetlands

display_name: wetlands

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

en: Amphibian observation and pond data (Aargau, Switzerland)


en: snow spatial-variability antarctica drone-data sea-ice polar

media_type: application/zip

format: ZIP

en:
Data of snow and sea ice in the McMurdo Sound, October-December 2022. The data was collected as part of the New Zealand Marsden Fund Research Grant 21-VUW-103 "Can Snow Change the Fate of Antarctic Sea Ice?"
The dataset includes raw data of the manual snow and sea ice measurements from snow pits and ice cores (temperature, density, salinity, dO18), measurements of snow water equivalent (SWE), spatial information of snow height (MagnaProbe) and sea ice thickness (EM-31), AWS (air temperature, wind speed, wind direction, relative humidity, pressure), radiations stations (shortwave, longwave, thermal IR, spectral shortwave), differential GPS data (3 fixed stations on different sea ice thicknesses, + 1 rover station for georeferencing UAV measurements), SIMBA buoy temperature (+heated temperature) data (3 buoys during November, 1 buoy for 15 months), UAV data: RGB, thermal IR, broadband albedo, spectral albedo, Chlorophyll-a from ice cores (bottom 10 cm), NIR reflectivity data of snow at 850 nm, and 940 nm (snow surface, profile, ice surface), photographs (1. overview of field sites, 2. for Structure from Motion for surface roughness, 3. macrophotos of snow) surface impurity concentrations, microCT data of snow microstructure, Denoth probe (density) and InfraSnow (specific surface area - SSA).
See the README file in each dataset for detailed information.

antarctica

display_name: antarctica

drone-data

display_name: drone-data

polar

display_name: polar

sea-ice

display_name: sea-ice

snow

display_name: snow

spatial-variability

display_name: spatial-variability

value: Envidat Harvester

en: Snow on Antarctic Sea Ice - McMurdo Sound 2022


en: snow weissfluhjoch wfj-research-site microstructure snow-density weisfluhjoch snow-ssa snow-stratigraphy snowmicropen snow-measurements

en: WFJ_DailySMP data access

en: A huge thanks goes to the countless PhD students, without whom collecting this dataset would not be possible.

en:
The WFJ_DailySMP dataset contains daily SnowMicroPen (SMP) measurements conducted throughout the winter seasons 2015-2025 (ongoing) at the Weissfluhjoch research site, Davos, Switzerland. The measurement program DailySMP started in winter 2015/2016 during which the measurement protocol was established as part of the RHOSSA campaign, described in the related publication.
Since then, measurements have been repeated every winter as part of the standard snow monitoring program by the PhD students at SLF. All published SMP files have undergone manual quality control by an expert, including a supervised detection of the snow surface, which is included in the dataset.
In addition to the raw data, we provide a rudimentary post-processing workflow in which the derived SSA and density profiles are adjusted by the total snow height obtained from the adjacent IMIS snow station (https://www.slf.ch/en/avalanche-bulletin-and-snow-situation/measured-values/description-of-automated-stations/) and their evolution is plotted over time. Please refer to the README for detailed information on how to get started.

microstructure

display_name: microstructure

snow-density

display_name: snow-density

snow-measurements

display_name: snow-measurements

snow-ssa

display_name: snow-ssa

snow-stratigraphy

display_name: snow-stratigraphy

snowmicropen

display_name: snowmicropen

weisfluhjoch

display_name: weisfluhjoch

weissfluhjoch

display_name: weissfluhjoch

wfj-research-site

display_name: wfj-research-site

en: WFJ_DailySMP - High-Resolution Snow Stratigraphy at Weissfluhjoch -- Davos 2015-ongoing


maintainer: Johanna T. Malle

en: snow land-cover land-use high-resolution evapotranspiration oshd forest-productivity clm5 snow-simulation

en: Point-scale CLM5 simulation output of snow depth and snow water equivalent for 9 different simulation scenarios, each performed at 36 snow station locations across Switzerland. Please have a look at table A1 in the appendix of the linked publication for coordinates of the stations. Additional information on the setup, and the differences between simulation setups can also be found in the linked publication.

en: Forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution. For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR) are provided.

en:
12 gridded CLM5 simulations over the spatial extent of Switzerland:
- 1km, 0.25deg, 0.5deg
- 3 different meteorological forcings (Clim_CRU, CLIM_CRU*, CLIM_OSHD)
- 2 different land use forcings
each with the following outputs:
- daily snow depth (file SNOW_DEPTH.nc)
- monthly summed gross primary production (file FPSN_MONTH_SUM.nc)
- monthly summed evapotranspiration (file QFLX_EVAP_TOT_MONTH_SUM.nc).
Temporal extent of all simulations: 01/01/2015 - 31/12/2020.

en:
This dataset contains Community Land Model 5 (CLM5) simulation output over the spatial extent of Switzerland at different resolutions and based on a range of input datasets. It further contains land-use surface data used for the CLM5-simulations.

**Detailed description of the CLM5 simulation setup and the various input datasets can be found in the accompanying publication: https://doi.org/10.5194/egusphere-2023-1832.**

 CLM5 simulation output

This dataset includes gridded CLM5 simulations of snow depth, gross primary productivity (GPP) and evapotranspiration at different resolutions ( 1km, 0.25° and 0.5°) and based on a range of input datasets over the spatial extent of Switzerland (see folder *gridded_CLM5_simulations*). Additionally, point-scale CLM5 simulations of snow depth and snow-water-equivalent at 36 snow-station locations (see folder *point_scale_CLM5_simulations*) are included. Latitude, longitude and elevation for these station locations can be found in table A1 of the above-mentioned publication. All simulation output spans from 01/01/2015 - 31/12/2019.

Included CLM5 simulation results are based on 3 different meteorological forcing datasets:
* Clim_CRU: standard global dataset, we used the recent state-of-the-art standrd global dataset CRU-JRA (https://catalogue.ceda.ac.uk/uuid/aed8e269513f446fb1b5d2512bb387ad)

* Clim_CRU*: ClimCRU upraded by downscaling temperature data using a temperature lapse rate of -6.5K/1000m and a high-resolution DEM

* Clim_OSHD: highest level of detail, meteorological forcing generated according to methods developed by the Operational Snow Hydrological Service (OSHD), at 1km spatial and 1hour temporal resolution</li>

 Land-use surface data

This dataset further includes forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution (see folder *surface_landuse_datasets*). For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR), which includes a higher level of detail and is based on a more up-to-date land use datase, are provided. More details on these two datasets can be found in the above-mentioned publication.

evapotranspiration

display_name: evapotranspiration

forest-productivity

display_name: forest-productivity

high-resolution

display_name: high-resolution

land-cover

display_name: land-cover

land-use

display_name: land-use

oshd

display_name: oshd

snow-simulation

display_name: snow-simulation

en: Multi-resolution CLM5 simulations across Switzerland


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

en: Sonic temperature

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

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 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 v

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 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: 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

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Snow Drift Station - 3D Ultrasonic


maintainer: Athanasios Nenes

en: raclets cloud-droplets supersaturation sigma-w cloud-modeling wolfgangpass

en: Predicted cloud droplet numbers (kappa=0.1) Davos Wolfgang

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.1 is assumed, which is the lower limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

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

mimetype: text/csv

en: Predicted cloud droplet numbers (kappa=0.25) Weissfluhjoch

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.25 is assumed, which is the upper limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

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

en: Cloud droplet properties were predicted between February 24 and March 8 2019 for the measurement site Davos Wolfgang (1630 m a.s.l., LON: 9.853594, LAT: 46.835577). Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from a Scanning Mobility Particle Size Spectrometer (SMPS) instrument deployed at Davos Wolfgang (https://www.envidat.ch/dataset/aerosol-data-davos-wolfgang). The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at the same station and are extracted from the first bin of the instrument, being 200 m above ground level. The hygroscopic properties of the particles measured at Davos Wolfgang could not be estimated, owing to a lack of concurrent CCN measurements. As a sensitivity test, droplet calculations are performed assuming two different values of the aerosol hygroscopicity parameter, 0.1 and 0.25, based on the analysis carried out for Weissfluhjoch. Additional information can be found in Section 2.3 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

wolfgangpass

display_name: wolfgangpass

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: Predicted cloud droplet numbers Davos Wolfgang


carabid-beetles-in-forests

maintainer: Martin K. Obrist

title_for_slug: carabid-beetles-in-forests

en: running-beetles insects carabidae trapping coleoptera arthropoda forest

en: Data query used on Fauna Database to retrieve the submitted data.

en: SQL query used to extract the data from fauna database.

media_type: text/plain

en: Tab-delimited data of the according sql query.

format: TXT

en: Data extract in TAB-delimted format. First row is header, first column is counter.

en:
Carabidae data from all historic up to the recent projects (21.10.2019) of WSL, collected with various methods in forests of different types.

Version 2 ('FIDO_global_extract 2019-11-22_18-11-24 WSL-Forest-Carabidae') contains additional data field PROJ_FALLENBEZEICHNUNG.

Data are provided on request to contact person against bilateral agreement.

arthropoda

display_name: arthropoda

carabidae

display_name: carabidae

coleoptera

display_name: coleoptera

forest

display_name: forest

insects

display_name: insects

running-beetles

display_name: running-beetles

trapping

display_name: trapping

en: Carabid beetles in forests


maintainer: Ionuț Iosifescu Enescu

en: map preview 0.5MB

mimetype: image/jpeg

en: Bulk Data Access

en: Link to the S3 bucket where all the data resources can be downloaded in bulk

format: GeoTIFF

en:
The attached data are some large GIS raster files (GeoTIFFs) made with Natural Earth data. Natural Earth is a free vector and raster map data @ naturalearthdata.com. The data used for creating these large files was the "Cross Blended Hypso with Shaded Relief and Water". Data was concatenated to achieve larger and larger files. Internal pyramids were created, in order that the files can be opened easily in a GIS software such as QGIS or by a (future) GIS data visualisation module integrated in EnviDat.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Large GIS raster data derived from Natural Earth Data (Cross Blended Hypso with Shaded Relief and Water)


lwf-tea-bag-sites

maintainer: Marcus Schaub

title_for_slug: lwf-tea-bag-sites

en: litter roiboos decomposition carbon green-tea tea-bag modeling verification forest

en: Site Information

en: Descriptive information on sites

en:
Decomposition of plant litter is a key process for the transfer of carbon and nutrients in ecosystems. Carbon contained in the decaying biomass is released to the atmosphere as respired CO2, and may contribute to global warming. Litterbag studies have been used to improve our knowledge of the drivers of litter decomposition, but they lack comparability because litter quality is plant species-specific. The use of commercial tea bags as a standard substrate was suggested in order to harmonize studies, where green tea and rooibos represent more labile and more recalcitrant C compounds as surrogates of local litter.
The tea bag approach was implemented on eight sites of the Swiss long-term Forest Ecosystem Research (LWF) network (https://www.wsl.ch/LWF). This allowed us to take advantage from the existing infrastructure and data from a previous litterbag study with local litter. In Beatenberg and Schaenis, additional elevation transects were established (1200-1800 m and 540-1150 m, respectively) to examine particularly the effect of temperature on decomposition. In Pfynwald (https://www.wsl.ch/de/ueber-die-wsl/versuchsanlagen-und-labors/flaechen-im-wald/pfynwald.html) and Salgesch, infrastructure of running projects was used to examine the effect of drought and understory removal, respectively. In Novaggio, tea bags were incubated in summer and winter to study the effect of seasonality particularly precipitation. Tea bags are collected after 3, 12, 24, and 36 months; for the two time-shifted experiments additionally after 6 and 9 months.
The study has two primary objectives. Firstly, it contributes to TeaComposition initiative (http://teacomposition.org/) which aims at investigating long-term litter decomposition and its key drivers at present as well as under different future climate scenarios using a common protocol and standard litter (tea) across nine terrestrial biomes. Secondly, the data are used to further develop decomposition models such as Yasso (http://en.ilmatieteenlaitos.fi/yasso) which is used by several countries, including Switzerland to estimate the annual carbon fluxes in dead wood, litter, and soil for reporting in National Greenhouse Gas Inventories under the United Nations Framework Convention on Climate Change and the Kyoto Protocol.

carbon

display_name: carbon

decomposition

display_name: decomposition

green-tea

display_name: green-tea

litter

display_name: litter

modeling

display_name: modeling

roiboos

display_name: roiboos

tea-bag

display_name: tea-bag

verification

display_name: verification

en: LWF-Tea bag sites


maintainer: Frank Techel

en: avalanche-forecast snow danger-level european-alps warning-regions

en: Forecast avalanche danger level

en: contains the highest forecast danger level (dangerLevelMax) for each day and warning region

en: shape file warning regions Alps

mimetype: application/zip

en:
This dataset contains the data used in the publication by Techel et al., 2018 _Spatial consistency and bias in avalanche forecasts - a case study in the European Alps_ (Nat Haz Earth Syst Sci).
For details on the data please refer to this publication.
The dataset contains the following:
- shape files for the warning regions in the Alps
- highest forecast danger level for each warning region and day

avalanche-forecast

display_name: avalanche-forecast

danger-level

display_name: danger-level

european-alps

display_name: european-alps

snow

display_name: snow

warning-regions

display_name: warning-regions

envidat

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

en: Forecast avalanche danger level European Alps 2011 - 2015


radar-wind-profiler-davos-wolfgang

maintainer: Maxim Hervo

title_for_slug: radar-wind-profiler-davos-wolfgang

en: wolfgangpass wind-speed radar wind-direction raclets

en: Radar Wind Profiler Data

en: A Vaisala Lap3000 was installed at Davos Wolfgang to record wind profiles. The time format is number of days fom January 0, 0000 in UTC with a 10 minute resolution.

en: The RADAR wind profiler from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 2171 m above sea level to 11079 m, with a temporal resolution of 10 minutes.

raclets

display_name: raclets

radar

display_name: radar

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

wolfgangpass

display_name: wolfgangpass

en: RADAR Wind profiler Davos Wolfgang


maintainer: Anna Braun

en: microstructure fem snow numerical-simulations metamorphism

author: EnviDat

en: Simulation parameters and outputs for "Towards a physically and microstructure-based equation for the evolution of the specific surface area in snow"

format: ODS

en:
In the associated study [1], evolution of randomly generated bi-continuous microstructures that resemble real snow microstructures has been investigated. The control of the ambient conditions (temperature and temperature gradient) and of the physical processes at play on the rate of change of the specific surface area have been evaluated. Based on the evaluation, a new physically-informed governing law for the coarsening of microstructures has been proposed. This law accurately predicts the simulation outputs under various conditions. Furthermore, a potential parametrization of newly introduced material properties has been proposed and evaluated on snow coarsening data.
This dataset contains the parameters used for the mesh generation and the finite-element simulations. The output parameters of simulations, such as the ice fraction, surface of the ice-air interface per total volume, mean curvature and growth rate are provided.
[1]: A.Braun, K. Fourteau, S. Frei, M. Lehning, H. Löwe: Towards a physically and microstructure-based equation for the evolution of the specific surface area in snow, Journal of Glaciology, accepted for publication in 2024

fem

display_name: fem

metamorphism

display_name: metamorphism

microstructure

display_name: microstructure

numerical-simulations

display_name: numerical-simulations

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Simulation parameters and outputs for towards a physically and microstructure-based equation for the evolution of the specific surface area in snow


en: snow-saltation splash drifting-snow saltation-parameterizations large-eddy-simulation aerodynamic-entrainment

en: Code and input files to reproduce the simulations in Melo et al. (2024), as well as the post-processing scripts used in the analysis.

en:
This dataset includes the necessary files to reproduce the results presented in Melo et al. (2024):
- code version used in the simulations (also available at the institutional [GitLab repository](https://gitlabext.wsl.ch/atmospheric-models/les-lsm) - tag 'r2024')
- input files to run the simulations
- post-processing scripts (MATLAB and FORTRAN)
- selected raw output files
- post-processed results (MATLAB data files).
 	**Note:** Direct model outputs are not provided because of their size, but they can be shared upon request. They can be reproduced by running the code. The post-processed results allow you to reproduce all figures in Melo et al. (2024).

aerodynamic-entrainment

display_name: aerodynamic-entrainment

drifting-snow

display_name: drifting-snow

large-eddy-simulation

display_name: large-eddy-simulation

saltation-parameterizations

display_name: saltation-parameterizations

snow-saltation

display_name: snow-saltation

splash

display_name: splash

en: Understanding snow saltation parameterizations - Reproducibility


en: teleo marine fish-composition coral-reefs fish caribbean-region edna environmental-dna curacao

en: Data access

en:
Fish taxonomic, functional and phylogenetic composition variations recovered from eDNA metabarcoding along the coast of Curacao

In February 2020, we collected a total of 20 water samples, from 10 stations, with two filtration replicates per station, in the two investigated coastal areas. Each station consisted of a transect of 2 km at an overall constant distance from the coast. We recorded the GPS coordinates at the start and end of the transect, which we used to map the transect positions. We conducted eDNA sampling by using a filtration device composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 L/min), a VigiDNA® 0.20 μM cross-flow filtration capsule (SPYGEN, le Bourget du Lac, France) and disposable sterile tubing for each filtration capsule. We performed two filtration replicates in parallel on each side of a boat, at each station, for 30 min corresponding to a volume of ~30 L of water filtered by each capsule. At the end of each filtration, the water inside the capsules was emptied, and we filled the capsules with 80 ml of CL1 Conservation buffer (SPYGEN, le Bourget du Lac, France) and stored at room temperature. We followed a strict contamination control protocol in both field and laboratory stages (Valentini et al., 2016). Each water sample processing included the use of disposable gloves and single-use filtration equipment to avoid any risk of contamination. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).

caribbean-region

display_name: caribbean-region

coral-reefs

display_name: coral-reefs

curacao

display_name: curacao

edna

display_name: edna

environmental-dna

display_name: environmental-dna

fish

display_name: fish

fish-composition

display_name: fish-composition

marine

display_name: marine

teleo

display_name: teleo

envidat

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

en: Environmental DNA Marine Curacao 2020


maintainer: Dominique Weber

en: sentinel-2 landsat use-intensity mowing grassland land-use remote-sensing management

en: Webcam-based reference data

en: Webcam-based reference data from 2020 and 2021 (see readme).

en: Grassland-use intensity map 2018

en: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2018. See readme file for more details.

en: Grassland-use intensity map 2019

en: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2019. See readme file for more details.

en: Grassland-use intensity map 2021

en: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2021. See readme file for more details.

en: Preview number of grassland management events 2020

media_type: image/png

en: Spatial distribution of the number of management events for Switzerland and for three zoomed-in regions (a, b, c). The three zoomed-in regions show different grassland-use intensities, which are reflected in the distribution of management frequency (Weber et al., 2023; IN REVIEW)

format: PNG

en: Readme

en: Metadata and description of the maps and webcam-based reference data.

en: Preview time of 1st grassland management event 2020

en: Spatial distribution of the timing (day of year; DOY) of the first management event for Switzerland and for three zoomed-in regions (a, b, c). The three zoomed-in regions show different grassland-use intensities, which are reflected in the timing of the first event of the year (Weber et al., 2023; IN REVIEW)

en: Grassland-use intensity map 2020

en: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2020. See readme file for more details.

en:
A rule-based algorithm [(Schwieder et al., 2022)](https://doi.org/10.1016/j.rse.2021.112795) was used to produce annual maps for 2018–2021 of grassland-management events, i.e. mowing and/or grazing, for Switzerland using Sentinel-2 and Landsat 8 satellite time series. All satellite images were processed with the [FORCE](https://force-eo.readthedocs.io) framework.

The resulting maps provide information on the number and timing of grassland-management events at a spatial resolution of 10 m × 10 m for the whole of Switzerland. For the final maps, permanent grasslands were masked using a variety of land-use layers, according to [Huber et al. (2022)](https://doi.org/10.1002/rse2.298) but replacing the crop mask with the agricultural-use data from the cantons.

We assessed the detection of management events based on independent reference data, which we acquired from daily time series of publicly available webcams that are widely distributed across Switzerland. We further tested the ecological relevance of the generated intensity measures in relation to nationwide biodiversity data (see [Weber et al., 2023](https://doi.org/10.1002/rse2.372)).

The webcam-based reference data used for verification was subsequently added on 14.02.2024.

grassland

display_name: grassland

land-use

display_name: land-use

landsat

display_name: landsat

management

display_name: management

mowing

display_name: mowing

remote-sensing

display_name: remote-sensing

use-intensity

display_name: use-intensity

en: Grassland-use intensity maps for Switzerland


en: field-data restoration urban-landscape forest traffic-noise

en: This SPSS data file includes the data used for analysis in paper 2 (Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial) and paper 3 ("The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial").

en: 02_Studyprotocol_Data on Laeq from noise recordings of walking routes_Studyprotocol.sav

en: This data file contains information on the LAeq levels recorded along the final walking routes between September 2021 and March 2022, prior to the commencement of data collection.

en: 12_P4_S2_Description of mindful walking intervention on site.pdf

en: This file includes the guided mindful walking instructions provided to participants in the mindfulness condition during the on-site walks.

en: 07_Studyprotocol_Test site pictures.zip

en: This folder includes two pictures of each test site. The locations for the two pictures on each route were chosen to be as characteristic as possible in terms of the visual and acoustical impressions of the walk.

en: 03b_Studyprotocol_Script_Analysis stationary noise evaluation.sps.sps

en: This SPSS syntax file contains a script for analyzing data related to the stationary evaluation of the acoustic impressions at the test sites, which is numbered 03a in this repository.

en: This document includes the questionnaire for Papers 2 and 3, administered at the second measurement time point (after the walk).

en: This file contains the informed consent document that participants signed to participate in the study.

en: This file includes the information sheet provided to participants before they consented to take part in the study.

en: 06_Studyprotocol_GPS tracks of the walking routes.zip

en: This folder contains the GPS tracks of the walking routes in the test sites.

en: 09_P2_Fotos Noise ROS paper.zip

en: This folder included the example pictures of the conditions included in paper 2 ("Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“).

en: This document includes the questionnaire for Papers 2 and 3, administered at the third measurement time point (10 days after participation on site).

en: 11_P4_S1_Instructions for individual mindful walking.pdf

en: This document contains the booklet with instructions for mindful walking, which participants in the mindfulness condition were encouraged to take with them and use during their individual walks over the 10 days following on-site participation.

en: 01_Studyprotocol_Locations of the starting points of the walking routes in the test settings.pdf

en: This document includes GPS coordinates of the starting points of the walking routes in the test sites.

en: 13_P4_Data mindful walking.sav

en: This file contains data for the manuscript "Effects of a mindful walking intervention in urban forests for healthy adults".

en: This document includes the questionnaire for Papers 2 and 3, administered at the first measurement time point (before the walk began).

en: 03a_Studyprotocol_Data on evaluation of acoustic impression of the test settings_Studyprotocol.sav

en: This data file includes information for an additional post hoc classification of the sound environment of the test sites. This evaluation was conducted in the afternoons of the same week in 2023 at two locations within each test site by a civil servant who was not familiar with the study's research questions.

en:
This repository contains data related to the field experiments of the RESTORE project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and the Swiss Federal Laboratories for Materials Science & Technology (EMPA). It has received funding from the Swiss National Science Foundation. The overall objective of the RESTORE project was to assess the effects of green spaces as facilitators and noise as impediment to recover from stress in people's daily environments across Switzerland.
We conducted a randomized, controlled field study to compare the psychophysiological benefits of exposure to forests and urban built environments with different levels of road traffic noise in healthy adults during 30-minute walks in Zürich, Switzerland to explore:
1) The psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure
2) The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world
3) The effects of a mindful walking intervention in urban forests for healthy adults
Accordingly, this repository includes data and documentation for the 3 scientific articles:
Scientific article 1. “Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: study protocol of a randomized controlled trial", BMC Psychology, 2024. https://doi.org/10.1186/s40359-024-01720-x
Scientific article 2. "Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“. Journal of Environmental Psychology, 2025.
Scientific article 3. “The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial". To be submitted to PLOS One, 2025.
Scientific article 4: "Effects of a mindful walking intervention in urban forests for healthy adults". To be submitted to Current Psychology, 2025.

field-data

display_name: field-data

forest

display_name: forest

restoration

display_name: restoration

traffic-noise

display_name: traffic-noise

urban-landscape

display_name: urban-landscape

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


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

en: WFJ_ICE_LAYERS dataset

en: README

mimetype: text/plain

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

ice-layers

display_name: ice-layers

snow-stratigraphy

display_name: snow-stratigraphy

snow-temperature

display_name: snow-temperature

snowmicropen

display_name: snowmicropen

water-front

display_name: water-front

weissfluhjoch

display_name: weissfluhjoch

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


digitizing-historical-plague

maintainer: Christian Ginzler

title_for_slug: digitizing-historical-plague

en: black-death plague-outbreaks bubonic-plague palaeo-epidemiology yersinia-pestis plague-inventory historical-plague plague-mapping

en: We present newly digitized data on 6,929 plague outbreaks that occurred between 1347 and 1900 AD across Europe. The data base on an inventory initially published 1976. For georeferencing the information of Tele Atlas 2009 was used. The coordinates are in the reference systems ETRS89 and WGS84.

black-death

display_name: black-death

bubonic-plague

display_name: bubonic-plague

historical-plague

display_name: historical-plague

palaeo-epidemiology

display_name: palaeo-epidemiology

plague-inventory

display_name: plague-inventory

plague-mapping

display_name: plague-mapping

plague-outbreaks

display_name: plague-outbreaks

yersinia-pestis

display_name: yersinia-pestis

en: Digitizing historical plague


en: COST European Snow Booklet (ESB)

en: Please find here the web version of the COST European Snow Booklet (ESB).

mimetype: application/pdf

en: European Snow Booklet public metadata

en:
The core of the European Snow Booklet (ESB), the country reports of 38 European countries, are based on information and metadata on snow measurements collected through a comprehensive survey, the ESB Questionnaire, between August 2017 and March 2018. The station metadata (for example location, elevation, measurement start date) from each country was provided by one or several institutions responsible for snow observations. By answering the questionnaire the contacts agreed that the information and metadata provided could be presented in the ESB. For cases where institutions indicated that information on station locations could be made publicly available, the metadata for the variables snow depth (HS), depth of snowfall (HN) and water equivalent of the snow cover (SWE), is additionally provided here for download (METADATA.xlsx).
Please note that not all institutions gave permission to publish their station metadata. This metadata has to be requested from the non-personal institution contacts provided in the METADATA.xlsx file. In some cases, however, no institutional contact is available and thus the contact of the country representative who filled in the questionnaire is used.
For current, updated station metadata we refer to the (non-personal) institutional contacts provided in METADATA.xlsx and/or the institution webpages. Note, however, that we cannot guarantee for completeness of the dataset for all countries because operational networks are prone to changes.

en: List of authors and list of the editorial board of the European Snow Booklet

en:
Here you can find the list of all lead authors of the different chapters of the European Snow Booklet (ESB).
In addition a list of the editorial board that reviewed the ESB is given.

en: COST European Snow Booklet (ESB) - DORA Link

en: DORA Link of the COST European Snow Booklet (ESB).

en:
The European Snow Booklet (ESB) is a book of reference for snow measurements that has been produced through collaboration with many European snow practitioners and snow scientists in the framework of the European Cooperation in Science and Technology (COST) Action ES1404 “A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction (HarmoSnow)”. The ESB provides a unique collection of information about operational snow observations in the European countries and the methods used to perform basic measurements of snow on the ground: snow depth (HS), depth of snowfall (HN), water equivalent of the snow cover (SWE) and presence of snow on the ground (PSG). Information and station metadata (for example location, elevation) for these basic snow variables were collected through a comprehensive survey, the ESB questionnaire between August 2017 and March 2018. Numerous institutions of 38 European countries provided detailed information describing the status of the operational snow observations and the methods used at the time of the survey. Based on the information provided, a country report was written for each European country. Similarities and differences among the countries, that is, the choice of snow variables to be measured, the measurement principles applied, the number of stations, or the spatial and elevational station distribution are pointed out. Thus the collection of country reports demonstrates the relevance of snow measurements for each country. Thus, the intention of the ESB is to foster better knowledge transfer regarding snow measurements between the snow science and operational communities and to improve the communication of information to the general public.

For detailed information on the European countries, we refer to the ESB, which can be downloaded here (envidat.ch). Please note that the ESB is not a living document and information and station metadata are from August 2017 till March 2018, except for Latvia (metadata updated in December 2018).

depth-of-snowfall

display_name: depth-of-snowfall

harmonisation-of-snow-measurements

display_name: harmonisation-of-snow-measurements

snow-depth

display_name: snow-depth

snow-measurement-methods

display_name: snow-measurement-methods

water-equivalent-of-the-snow-cover

display_name: water-equivalent-of-the-snow-cover

en: European Snow Booklet – an Inventory of Snow Measurements in Europe


disdrometer-data-laret

maintainer: Daniel Wolfensberger

title_for_slug: disdrometer-data-laret

en: raclets precipitation hydrometeors disdrometer visibility

en: Disdrometer Data Laret

en: The zip folder contains one netCDF file per day for Laret from February 7 to March 29 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Laret_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

en:
A laser optical disdrometer (Parsivel² , OTT Hydromet) was used to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms.
The dataset contains information on precipitation amount and type for the period of February 7 to March 29 2019 in Laret.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: Armin Sigmund

en: antarctica atmospheric-turbulence meteorological-measurements blowing-snow drifting-snow

en: (h) Sonic data 5

en: Ultrasonic anemometer data in the period from 6 to 13 November 2000.

en: (a) Metadata

en: General and specific metadata for all files.

en: (b) SPC time series

en: Data from the snow particle counters with 1-s intervals.

en: (k) Wind speed profiles

en: Average vertical profiles of horizontal wind speed based on the ultrasonic anemometer data.

en: (c) SPC average profiles

en: Average vertical profiles of the horizontal snow mass flux, particle number size distribution, and mean and standard deviation of the particle diameter.

en: (e) Sonic data 2

en: Ultrasonic anemometer data in the period from 11 to 21 October 2000.

en: (g) Sonic data 4

en: Ultrasonic anemometer data in the period from 30 October to 6 November 2000.

en: (i) Sonic data 6

en: Ultrasonic anemometer data in the period from 13 to 18 November 2000.

en: (m) Weather observations

en: Weather elements and phenomena observed by the Japanese Meteorological Agency.

en: (j) Spike percentage

en: Percentage of spikes removed from the ultrasonic anemometer data per 5-min interval.

en: (d) Sonic data 1

en: Ultrasonic anemometer data in the period from 30 September to 11 October 2000.

en: (f) Sonic data 3

en: Ultrasonic anemometer data in the period from 21 to 30 October 2000.

en: (l) AWS data

en: Automatic weather station data with 10-min intervals.

en:
This data was collected at Mizuho Station (44.315°E, 70.71°S, 2230 m a.s.l.), East Antarctica, from **30 September to 22 November 2000** during the 41st Japanese Antarctic research expedition. Vertical profiles of the horizontal mass flux and particle number size distribution of drifting and blowing snow were measured in the lowest 10 m of the atmosphere using four **snow particle counters** (SPCs). Three 3-dimensional **ultrasonic anemometers** were deployed in the lowest 25 m of the atmosphere to record the wind velocity components and sonic temperature at a high frequency of 100 Hz. Additionally, an **automatic weather station** provided air temperature, relative humidity, air pressure, shortwave and longwave downward and upward radiation fluxes, surface temperature, snow temperatures at depths of 0.1 and 0.4 m below the surface, wind speed, and wind direction. The data is complemented by **weather observations** performed twice to eleven times per day by the Japanese Meteorological Agency.
Most of the time, the lowest SPC was situated at a height of 0.05 or 0.1 m above the snow surface. During certain periods called profile runs, the height of the lowest SPC was systematically varied between 0.02 and 0.2 m to increase the vertical resolution of the measured profiles. The other SPC's were installed at fixed heights of 1.1, 3.1, and 9.6 m. During each profile run, the lowest SPC was kept at a specific height for approximately 10 min before changing the height. If the wind speed remained approximately constant throughout a profile run, the data was used to compute the average snow-transport profile in that period. In total, 24 of such average profiles were obtained. A part of these SPC measurements are discussed in Nishimura and Nemoto (2005).
The ultrasonic anemometers were placed at heights of 0.3, 1, and 25 m. However, the height of the lowest ultrasonic anemometer was changed several times in the measurement period and ranged from 0.05 to 0.32 m. On top of that, 19 short periods (each lasting 15 to 160 min) were used to systematically vary the height of the lowest ultrasonic anemometer and thus increase the vertical resolution of the measured wind speed profile. Occasionally, drifting and blowing snow particles perturbed the ultrasonic measurement signal and electrically-charged particles caused an electric charge of the anemometers, leading to artifacts such as spikes and dropouts in the measured time series. These artifacts were largely removed and replaced by NaN, using the statistical spike removal algorithm of Mauder et al. (2013). However, the artifact removal was sometimes incomplete for the lowest anemometer because of very intense snow transport close to the surface. While temporal averages are barely affected by the artifacts, the high-frequency data of the lowest anemometer should be used carefully when computing turbulent fluxes using the eddy-covariance method. Further important explanations are provided in the file Readme.pdf in data resource '(a) Metadata'.
References
- Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H.P., Schmidt, M., Steinbrecher, R. (2013). A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements. Agric For Meteorol 169:122–135. https://doi.org/10.1016/j.agrformet.2012.09.006
- Nishimura, K., Nemoto M. (2005). Blowing snow at Mizuho station, Antarctica. Phil. Trans. R. Soc. A. 363: 1647–1662. https://doi.org/10.1098/rsta.2005.1599

antarctica

display_name: antarctica

atmospheric-turbulence

display_name: atmospheric-turbulence

blowing-snow

display_name: blowing-snow

drifting-snow

display_name: drifting-snow

meteorological-measurements

display_name: meteorological-measurements

en: Profile measurements of snow transport and micrometeorology at Mizuho Station in Antarctica


en: air-temperature climate-change time-series shortwave-radiation precipitation speed2zero meteo-station relative-humidity wind-speed

en: Data link

en:
This dataset provides 50 years of seasonal synthetic hourly time series for five meteorological variables: incoming shortwave radiation, total precipitation, relative humidity, 2-meter air temperature and wind speed.

The data are generated from observational records (1990–present) from nine MeteoSwiss stations (ABO, BAS, BER, LUG, PUY, SCU, SIO, STG, WFJ). We use a sampling approach that preserves both the temporal structure and inter-variable dependencies. Specifically, the time series are constructed by drawing 7-day blocks from historical observations, ensuring realistic short-term variability and maintaining the physical coherence between variables.

The synthetic sequences are constrained to follow daily temperature change trajectories corresponding to three future climate scenarios for the period 2040–2070: RCP2.6, RCP8.5 and RCP0: a counterfactual scenario with no long-term warming trend, but with temperature variability consistent with the RCP2.6 one.
The temperature constraints are derived from projections downscaled at the staiton level, available at: https://www.envidat.ch/#/metadata/climate-change-scenarios-at-hourly-resolution

air-temperature

display_name: air-temperature

climate-change

display_name: climate-change

meteo-station

display_name: meteo-station

relative-humidity

display_name: relative-humidity

shortwave-radiation

display_name: shortwave-radiation

time-series

display_name: time-series

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Meteorological Time Series Aligned with Projected Temperature Changes


en: alptal tracers studibach celerity runoff-plot preferential-flow velocity rainfall-simulation topsoil-interflow overland-flow

en:
Description:
This dataset comprises the time series of overland flow (OF) and topsoil interflow (TIF) discharge, and tracer concentrations during artificial rainfall simulation experiments at two large (>80 m2) trenched runoff plots in the Studibach catchment in the Alptal, a typical pre-Alpine headwater catchment in Switzerland.
One plot is located in a natural clearing in an open mixed forest and the other in a grassland. Together, they represent the dominant land cover types in the region.
We applied streamwater to the surface of the plots using sprinklers and added tracers after OF and TIF had reached steady state. Deuterium enriched water was applied to the surface of the plots via the sprinklers, while Uranine and NaCl were applied as a line tracer at multiple distances from the trench. NaBr was injected into the topsoil at ~20 cm depth. Samples of overland flow and topsoil interflow were collected for several hours after tracer application, while the sprinklers continued to apply water to the surface. The runoff was collected into self-made "Upwelling Bernoulli Tubes" and the water level inside these tubes was measured using pressure sensors (DCX-22-CTD, Keller Druck, Switzerland) at a 1-min resolution during the day and 5-min resolution during the night. Uranine concentrations and electrical conductivity (EC) were recorded at a 1-minute interval. Samples for deuterium and Bromide were analysed in the lab.
The celerity of overland flow and topsoil interflow was determined during another experiment by temporarily adding more water to the surface of the plots at different distances from the trench after steady state conditions had been reached. The overland flow and topsoil interflow discharge were again measured using the Upwelling Bernoulli Tubes and pressure transducers.

alptal

display_name: alptal

celerity

display_name: celerity

overland-flow

display_name: overland-flow

preferential-flow

display_name: preferential-flow

rainfall-simulation

display_name: rainfall-simulation

runoff-plot

display_name: runoff-plot

studibach

display_name: studibach

topsoil-interflow

display_name: topsoil-interflow

tracers

display_name: tracers

velocity

display_name: velocity

en: Flow and tracer data for overland flow and topsoil interflow during rainfall simulation experiments in the Studibach catchment - Alptal - Switzerland


maintainer: Roksolana Petrovska

en: fagus regeneration acer dominance shade-tolerance lar mortality-rate

en: The R-script of survival analysis for accelerated failure time model

en: Mortality of regeneration

en: Acer platanoides, Acer pseudoplatanus and Fagus sylvatica living and dead juveniles (0-500 cm in height) grown in the deep shade of a prime beech-dominated forest.

en:
 One individual per species, vitality class (low and high) and height class (eight classes: 0–10, 11–20, 21–35, 36–60, 61–90, 91–130, 131–200 and 201–500 cm) was randomly selected and harvested in each of the six plots. This resulted in a sample of 82, 80 and 89 living individuals of A. platanoides, A. pseudoplatanus and F. sylvatica, respectively.

 Additionally stems of dead Acer spp. and F. sylvatica trees that had died within the last three years (2015–2018) were randomly harvested, matching the height classes of the harvested living trees wherever possible. In total, 179 dead young trees (60 A. platanoides, 72 A. pseudoplatanus and 47 F. sylvatica) were collected.

 Variables:
* species_code: a_pla - Acer platanoides, a_pse - Acer pseudoplatanus, f_syl - Fagus sylvatica
* species: as above
* dummy: 0 - living individual, 1 - dead individual
* LAR_cm2_g: leaf area ratio or ratio of leaf area to total plant biomass, [cm2/g]
* tree_age: in years
* avg_ring_micron: average width of the last 5 rings in tree life excluding the last ring
* dry_mass_g: aboveground and belowground biomass
* DLI: direct light index (measured only under living individuals)
* BLI: diffuse light index (measured only under living individuals)
* GLI: global light index

acer

display_name: acer

dominance

display_name: dominance

fagus

display_name: fagus

lar

display_name: lar

mortality-rate

display_name: mortality-rate

regeneration

display_name: regeneration

shade-tolerance

display_name: shade-tolerance

en: Mortality of regeneration: Acer spp. and Fagus sylvatica


maintainer: Matthias Haeni

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

en: Site photo of the forest station (VSB)

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

en: Site photo of the field station (VSF)

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

en: Forest station data (VSB)

en: Data file.

en: Data plot of the forest station (VSB)

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

en: Site aerial photo (Visp)

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

en: Field station data (VSF)

en: Data plot of the field station (VSF)

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

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


maintainer: Jonas Stillhard

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

en: Dataset

en: Data description

en: Available online on publishers website

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

carpathian-biosphere-reserve

display_name: carpathian-biosphere-reserve

dem

display_name: dem

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-structure

display_name: forest-structure

long-term-data-sets

display_name: long-term-data-sets

permanent-forest-plot-data

display_name: permanent-forest-plot-data

primeval-beech-forest

display_name: primeval-beech-forest

stand-inventory-data

display_name: stand-inventory-data

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

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


en: arthropods diversity snails species-richness-models species-abundance-distributions birds spiders urbanization urban-ecology insects sdms

en: contains the raw data to perform the species richness models of the hypercommon species

en: contains the raw data to perform the species richness models of all species

en: contains the raw data to perform the species richness models of the rare species

en: contains the raw data to perform species distribution models, only for common species

en: abundance and occurrence data of the 1446 species studied, used to investigate species-abundance distributions and species-occurrence distributions

en:
Richness, site occurrence and abundance data of bees, beetles, birds, hoverflies, net-wingeds, true bugs, snails, spiders, milipides, wasps collected in the city of Zurich using different sampling techniques, and the environmental variables for each sampling site.
Data are provided on request to contact person against bilateral agreement.

arthropods

display_name: arthropods

birds

display_name: birds

diversity

display_name: diversity

insects

display_name: insects

sdms

display_name: sdms

snails

display_name: snails

species-abundance-distributions

display_name: species-abundance-distributions

species-richness-models

display_name: species-richness-models

spiders

display_name: spiders

urban-ecology

display_name: urban-ecology

urbanization

display_name: urbanization

en: Ecological properties of urban ecosystems. Biodiversity dataset of Zurich