en:
This repository contains data related to an interdisciplinary study on playgrounds, looking at both playground vegetation and the well-being of pre-school children using those playgrounds. This project was funded by and initiated at the Institute for Landscape Planning and Ecology (ILPÖ) of the University of Stuttgart, Germany. Data was collected by ILPÖ. The project was finalised in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). The aim of the study was to (1) describe playground vegetation (species richness and diversity at the ground, shrub and tree layers; habitat structure); (2) describe preschool children’s well-being and nature-connectedness; and (3) investigate whether there is a relationship between plant diversity and well-being while exploring potential other predictors of well-being, including children’s and parents’ or carer’s nature-connectedness, greenspace exposure, seasonality, and socio-demographic background.
We sampled ground (-1m height), shrub (1-2m height) and tree (-2m hieght) vegetation of 29 playgrounds of Stuttgart's inner city. Sampling took place between May 25 and July 01, 2021. Ground layer vegetation was sampled in ten one-by-one m2 quadrats per playground, within which we recorded the cover of each species based on the Braun-Blanquet scale. Woody vegetation was exhaustively sampled within the playgrounds and in a surrounding two meters buffer, recording each individual plant. Vegetation cover was visually estimated as a percentage for each vegetation layer, namely the ground, shrub and tree (canopy) layers.
In parallel, we distributed questionnaires to parents and carers to assess the well-being and connectedness-to-nature of preschool children (aged 6 or younger) across the seasons. The questionnaire covered children's (1) use of greenspaces, (2) nature-connectedness, (3) well-being, and (4) socio-demographic variables. Questionnaires were distributed accross all seasons: sampling seasons included autumn (Oct-Nov 2021), winter (Jan-Feb 2022), spring (April-May 2022) and summer (June-July 2022). Ethical approval was granted by the University of Stuttgart Commission on Responsibility in Research (Az. 21-033).

en: biodiversity well-being green-spaces urban seasons

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: Playground biodiversity and preschool children well-being

en:
Resource Title: Spielplatz Fragebogen_Englisch.pdf
    Size: 340244 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/b87bc6b7-9aaa-4c86-adfc-52dcf47bcfb4/download/spielplatz-fragebogen_englisch.pdf
    Description: This document includes the English version of the questionnaire administered to carers of pre-school children. This was the original questionnaire, later translated in the 10 most spoken languages in Baden-Württemberg (DE).

en:
Resource Title: Spielplatz Fragebogen_Ukrainian.pdf
    Size: 1015736 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/1ae17430-7011-40f1-87d5-48f642e997ea/download/spielplatz-fragebogen_ukrainian.pdf
    Description: This document includes the Ukrainian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Arabisch.pdf
    Size: 397855 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/56c767f8-0b3d-45c3-9209-2bce6dac682f/download/spielplatz-fragebogen_arabisch.pdf
    Description: This document includes the Arabic version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Italienisch.pdf
    Size: 322529 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/6971a33d-2b7d-40d4-8d99-d583aed944d2/download/spielplatz-fragebogen_italienisch.pdf
    Description: This document includes the Italian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Französisch.pdf
    Size: 353495 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/872f9d84-d7a4-498d-9f3e-5851bd9bddfd/download/spielplatz-fragebogen_franzosisch.pdf
    Description: This document includes the French version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Plant and playground data.xlsx
    Size: 97321 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/eb12671e-2a17-4acf-b181-a68e40fd1fe5/download/plant-and-playground-data.xlsx
    Description: This file contains the playground and plant diversity data for the manuscript "Playground tree diversity: a driver of well-being in preschool children".
The file is separated in five tabs containing:
(1) the overview of the playgrounds,
(2) the overview of all plant species, with their life-history traits and the diversity indexes per layer,
(3) the tree (canoy) layer abundance of each plant species, measured exhaustively in each playground,
(4) the shrub layer abundance of each plant species, measured exhaustively in each playground, and
(5) the ground layer abundance of each plant species, estimated with the Braun-Blanquet scale in 10 quadrats per playground.

en:
Resource Title: Well-being.xlsx
    Size: 184576 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/8b624832-b01e-4728-95cc-22644320da26/download/well-being.xlsx
    Description: This file contains the anonymised well-being and nature-connectedness data for the manuscript "Playground tree diversity: a driver of well-being in preschool children".

en:
Resource Title: Spielplatz Fragebogen_Türkisch.pdf
    Size: 346481 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/f49040c1-0140-4b98-8b3a-b8b6be4fd565/download/spielplatz-fragebogen_turkisch.pdf
    Description: This document includes the Turkish version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Polnisch.pdf
    Size: 361073 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/024bbf41-00b5-4c84-ba75-28e136050d41/download/spielplatz-fragebogen_polnisch.pdf
    Description: This document includes the Polish version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Deutsch.pdf
    Size: 364554 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/deca6461-d9a1-4cf4-8739-480e13432408/download/spielplatz-fragebogen_deutsch.pdf
    Description: This document includes the German version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Russisch.pdf
    Size: 357530 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/53481be4-b668-48c6-98df-c58961caf97b/download/spielplatz-fragebogen_russisch.pdf
    Description: This document includes the Russian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Rumänisch.pdf
    Size: 349716 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/0ac43c39-4a0d-40c2-a544-e2a4e6109213/download/spielplatz-fragebogen_rumanisch.pdf
    Description: This document includes the Romanian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Spanisch.pdf
    Size: 345221 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/c57948ab-c230-45c0-a9b2-b60eb3460cfd/download/spielplatz-fragebogen_spanisch.pdf
    Description: This document includes the Spanish of the questionnaire administered to carers of pre-school children.

biodiversity

display_name: biodiversity

green-spaces

display_name: green-spaces

seasons

display_name: seasons

urban

display_name: urban

well-being

display_name: well-being


high-resolution-climate-data-for-europe

$oid: OBSOLETE

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present downscaled climate data for the CORDEX EUR11 domain at a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperature lapse rates. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height. The resulting data consist of a daily temperature and precipitation timeseries.
The data is distributed under a: Creative Commons: Attribution 4.0 International (CC BY 4.0) license.

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

envidat

approval_status: approved

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.

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.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: High resolution climate data for Europe

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: CHELSA_EUR11 technical documentation
    Size: 713475 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9e2c4a69-443d-4eb1-b8ab-697fd50bc7d2/resource/bc1df26a-0b8f-4547-872d-f00ed45db554/download/chelsa_eur11_technical_documentation.pdf
    Description: Technical documentation of the data with variable names and methodology.

format: PDF

media_type: application/pdf

en:
Resource Title: Data Access
    Size: 2199023255552 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav2&prefix=EUR11%2F
    Description:

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation


functional-invertebrate-groups-dataset

en: Collected Invertebrate data using pitfall traps at streetlights with different characteristics at three different sites in Switzerland (Birmensdorf, Lägern & Alpthal). LED characteristics are LED color temperature, light level and luminaire shape (K, L_level, Diff). Additionally, we had two pitfall trap positions: Center (C; 100% light intensity)) and  Periphery (P; 10% light intensity). The traps were emptied weekly over a period of two summers (2021 & 2022). The samples were sorted into 40 different taxonomic invertebrate groups. We included weeks where we turned of the light for a different experiement, these weeks were excluded from this dataset.

en: artificial-lighting alan invertebrates light-pollution functional-groups community-composition led

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: Functional Invertebrate Groups - Dataset

title_for_slug: functional-invertebrate-groups-dataset

format: CSV

alan

display_name: alan

artificial-lighting

display_name: artificial-lighting

community-composition

display_name: community-composition

functional-groups

display_name: functional-groups

invertebrates

display_name: invertebrates

led

display_name: led

light-pollution

display_name: light-pollution


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

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

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

en:
Resource Title: Survival_AFT_R_script
    Size: 18015 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/8d9df0cd-f20c-423f-a4ab-71fc213871de/resource/6ff5b7a2-6662-41ab-8c2d-68f688cde189/download/survival_script.r
    Description: The R-script of survival analysis for accelerated failure time model

en:
Resource Title: Mortality of regeneration
    Size: 60209 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8d9df0cd-f20c-423f-a4ab-71fc213871de/resource/37fb69d9-c553-4931-89ba-31857ac15c04/download/imputed.csv
    Description: 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.

media_type: text/csv

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:
This data set provides estimates of annual fresh water fluxes related to sea-ice formation from ocean freezing and snow-ice formation, sea-ice melting, lateral transport of sea ice in the Southern Ocean over the period 1982 to 2008.It is derived from a mass balance calculation of local sea-ice volume change and divergence from satellite data and sea-ice reconstructions. The mass balance is calculated on a daily basis and fluxes are then integrated over the entire year, where a year is defined from March to February of the next year (i.e. from March 1982 to February 2009). This approach combines multiple products of sea-ice concentration (Cavalieri & Parkinson, 2008;Comiso, 1986; Meier et al., 2013), sea-ice thickness (Kurtz & Markus, 2012; Massonnet et al., 2013; Worby et al., 2008), and sea-ice drift (Fowler et al., 2013; Kwok 2005; Schwegmann et al., 2011). For a detailed description of the method see Haumann et al. (2016). The data set is derived to estimate large-scale (regional to basin-scale) fluxes on an annual basis. Our confidence is reduced on a grid cell basis, such as for single coastal polynyas, where the method and underlying data induce large, unknown uncertainties.
_Disclaimer: This data set is free to use for any non-commercial purpose at the risk of the user and the authors do not take any liability on the use of the data set. The authors assembled the data set carefully and assessed accuracy, errors, and uncertainties. Please contact the authors if you find any issues._
Related publication: http://www.nature.com/nature/journal/v537/n7618/full/nature19101.html (doi:10.1038/nature19101)
Disclaimer: This data set is free to use for any non-commercial purpose at the risk of the user and the authors do not take any liability on the use of the data set. The authors assembled the data set carefully and assessed accuracy, errors, and uncertainties. Please contact the authors if you find any issues.

en: forcing southern-ocean physical-oceanography freshwater-flux sea-ice-divergence mass-balance sea-ice salt cryospheric-science transport freezing salinity melting climate-change satellite polar sea-ice-volume antartic

en: Antarctic sea-ice freshwater fluxes associated with freezing, transport, and melting

en:
Resource Title: AnIceFlux_v01_annual_1982-2008.nc
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    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/b16a0901-3abe-4da0-b61e-cdb80c59ba63/resource/5de37dd3-e6a7-41b4-b97a-21b14734b861/download/aniceflux_v01_annual_1982-2008.nc
    Description: Data in NetCDF4 CF-1.6 format

en:
Resource Title: Explanatory Document
    Size: 379128 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b16a0901-3abe-4da0-b61e-cdb80c59ba63/resource/a2d8430f-dc92-4a03-b3d6-6661b553bdd1/download/aniceflux_v01.pdf
    Description:

en:
Resource Title:  AnIceFlux_v01_clim_mean_1982-2008.nc
    Size: 260945 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/b16a0901-3abe-4da0-b61e-cdb80c59ba63/resource/6a315e6d-4c92-4f85-b131-92fd87853b65/download/aniceflux_v01_clim_mean_1982-2008.nc
    Description: Data in NetCDF4 CF-1.6 format

en:
Resource Title: Link to Related Publication
    Size: 1 bytes
    Format: application/pdf
    URL: http://www.nature.com/articles/nature19101.epdf?author_access_token=dtLqMQ3Ss6p16tymoagae9RgN0jAjWel9jnR3ZoTv0PH2BR1NrVw3zxcEnl7ViU5pKp8iHAlc_ntQx82EiRMqFRuGOR0VueOUVoGWzy8lSzML6YUBUMMZ5f4LYCdK8Ca
    Description:

antartic

display_name: antartic

climate-change

display_name: climate-change

cryospheric-science

display_name: cryospheric-science

forcing

display_name: forcing

freezing

display_name: freezing

freshwater-flux

display_name: freshwater-flux

mass-balance

display_name: mass-balance

melting

display_name: melting

physical-oceanography

display_name: physical-oceanography

polar

display_name: polar

salinity

display_name: salinity

salt

display_name: salt

satellite

display_name: satellite

sea-ice

display_name: sea-ice

sea-ice-divergence

display_name: sea-ice-divergence

sea-ice-volume

display_name: sea-ice-volume

southern-ocean

display_name: southern-ocean

transport

display_name: transport


en:
This repository contains all observational data sets during CALISHTO campaign used for the paper: Gao, K., Vogel, F., Foskinis, R., Vratolis, S., Gini, M. I., Granakis, K., Zografou, O., Fetfatzis, P., Berne, A., Papagiannis, A., Möhler, O., Eleftheridadis, K., and Nenes, A.: On the drivers of ice nucleating particle diurnal variability in Eastern Mediterranean clouds, npj Climate and Atmospheric Science,  Preprint link: https://www.researchsquare.com/article/rs-4378562/v1.
CALISHTO campaign was conducted between 12 October and 27 November 2021 to observe ice nucleating particles and aerosol properties at the Helmos Hellenic Atmospheric Aerosol and Climate Change station in Eastern Mediterranean, to understand cloud-aerosol interactions. To evaluate the spatial-temporal variabilities and characteristics of ice nucleating particles, a high-time resolution ice nucleation spectrometer was employed and different online aerosol  property measurements were conducted in-situ, including particle number concentration, particle size distribution, particle fluorescent properties, and particle chemical composition. In addition, planetary boundary layer conditions at the observation site were determined by remote sensing techniques employed at a lower site.

en: fluorescent-particles biological-particles dust-particles diurnal-variability ice-nucleation aerosol-cloud-interactions

envidat

en: EnviDat: the Environmental Data Portal

en: CALISHTO campaign dataset for the publication On the Drivers of Ice Nucleating Particle Diurnal Variability in Eastern Mediterranean Clouds

envi

en: Environment

en:
Resource Title: Figure 7.xlsx
    Size: 91997 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cf74de68-a026-4c43-abc9-f5cfb4beadb9/resource/63f8b6ff-76a2-4328-a51d-5aaf64705381/download/figure-7.xlsx
    Description: This file contains data presented in Figure 7 in the main text.

format: XLS

en:
Resource Title: Data for figures in the Supplementary.xlsx
    Size: 2644777 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cf74de68-a026-4c43-abc9-f5cfb4beadb9/resource/e3581bf2-16cd-4e3e-9c16-80be733e57fd/download/data-for-figures-in-the-supplementary.xlsx
    Description: This file contains data presented in Figure S2 to S36 in the supplementary.

en:
Resource Title: Figure 3.xlsx
    Size: 41657 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cf74de68-a026-4c43-abc9-f5cfb4beadb9/resource/7d25f431-719b-4e81-9e87-71d6b73cac97/download/figure-3.xlsx
    Description: This file contains data presented in Figure 3 in the main text.

en:
Resource Title: Figure 4.xlsx
    Size: 40769 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cf74de68-a026-4c43-abc9-f5cfb4beadb9/resource/8756a238-ca3d-43e1-8f4b-60877d046731/download/figure-4.xlsx
    Description: This file contains data presented in Figure 4 in the main text.

en:
Resource Title: Figure 1.xlsx
    Size: 19296 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cf74de68-a026-4c43-abc9-f5cfb4beadb9/resource/0459364f-4c2f-4bd2-9825-1a3b527f0550/download/figure-1.xlsx
    Description: This file contains data presented in Figure 1 in the main text.

en:
Resource Title: Figure 5.xlsx
    Size: 39112 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cf74de68-a026-4c43-abc9-f5cfb4beadb9/resource/ed2dec5e-6d02-4835-8c7c-d9054b8bd9da/download/figure-5.xlsx
    Description: This file contains data presented in Figure 5 in the main text.

en:
Resource Title: Figure 2.xlsx
    Size: 41737 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cf74de68-a026-4c43-abc9-f5cfb4beadb9/resource/c95e8863-99bb-4070-8967-9c0c5a767f26/download/figure-2.xlsx
    Description: This file contains data presented in Figure 2 in the main text.

en:
Resource Title: Figure 6.xlsx
    Size: 43273 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cf74de68-a026-4c43-abc9-f5cfb4beadb9/resource/b2d4280e-e366-40e2-9bb1-2480dbb19f6c/download/figure-6.xlsx
    Description: This file contains data presented in Figure 6 in the main text.

aerosol-cloud-interactions

display_name: aerosol-cloud-interactions

biological-particles

display_name: biological-particles

diurnal-variability

display_name: diurnal-variability

dust-particles

display_name: dust-particles

fluorescent-particles

display_name: fluorescent-particles

ice-nucleation

display_name: ice-nucleation


photogrammetric-drone-data-gruenbodeli

en:
We conducted various drone flights at Grüenbödeli near Davos with the Sony RX1R II mounted on a Wingtra drone during 2020/21/22. The data was processed with the Agisoft Metashape Professional Software.
The following products are available for download:
- DSM 10cm resolution
- Orthomosaic 3cm/25mm resolution
- Snow Raster 10cm resolution
- original RGB images

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

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: Photogrammetric Drone Data Grüenbödeli

title_for_slug: photogrammetric-drone-data-gruenbodeli

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow-depth-mapping

display_name: snow-depth-mapping

uav

display_name: uav

wingtra

display_name: wingtra


en:
The data was generated during a landscape experiment performed on 69 plots in Sihlwald forest between 2016 and 2019. Branch bundles of different sizes consisting of beech branches were exposed in the forest for one year to be colonized by saproxylic beetles and later reared for one year in emergence traps. All beetles emerging from the branches were collected. Overall 244 branch bundles are included and we found 66 beetles species (23511 individuals) of which 43 were classified as saproxylic (20873 individuals).
 Species data (2 tables)
Two community matrices (including abundance): one for saproxylic beetles and one for all beetles. Beetles were classfied as saproxylic following an extended list of the list reported in Schmidl & Bussler (2004).
 Model data (1 table)
*Response variables*
Species richness and abundance of (saproxylic) beetles.
*Branch bundles*
Branch bundles consisted of 1, 3, 6 or 12 branches and each bundle size was installed at each of the 69 plots. The bundles consisted of standardized freshly cut beech branches (Fagus sylvatica) with a length of 80 cm and a diameter between 3 and 6 cm. Total surface and volume of each bundle is reported.
*Tree on which the bundle was installed*
Information on the tree to which the bundles were attached (tree species, dbh, distance and azimut from the plot center).
*Temperature and light availability*
Temperature (plot level) and light availability (bundle level) were calculated.
*Deadwood availability in the landscape*
Based on a map of lying dead wood, dead wood amount and isolation were calculated for concentric circles with a radius ranging from 20 to 200 m (in 10 m steps) around each branch bundle.
 Variable descriptions (1 table)

en: saproxylic-beetles dead-wood habitat-availability conservation forest-management colonisation sloss biodiversity habitat-heterogeneity

en: Beetle communities reared from beech branches and associated forest and environmental variables

en:
Resource Title: Variable description
    Size: 3005 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/8113973a-149d-4514-8b03-11201870881c/download/variable_description.csv
    Description: Detailed description of the forest and environmental variables

en:
Resource Title: Community matrix (saproxylic beetles)
    Size: 23120 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/1873211d-631c-493e-a998-103395d5de43/download/abundance_saproxylics.csv
    Description: Abundances of saproxylic beetle species for each branch bundle

en:
Resource Title: Forest and environmental variables
    Size: 158262 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/66dbaff5-2b06-4e82-9f92-9e40d298f938/download/data_branch_bundles.csv
    Description: Data on the branch bundle, forest and environmental variables

en:
Resource Title: Community matrix (all beetles)
    Size: 34872 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/30938085-43a4-43f0-bdde-2f57dd557064/download/abundance_all_beetles.csv
    Description: Abundances of all beetle species for each branch bundle

biodiversity

display_name: biodiversity

colonisation

display_name: colonisation

conservation

display_name: conservation

dead-wood

display_name: dead-wood

forest-management

display_name: forest-management

habitat-availability

display_name: habitat-availability

habitat-heterogeneity

display_name: habitat-heterogeneity

saproxylic-beetles

display_name: saproxylic-beetles

sloss

display_name: sloss


en:
This repository contains the data necessary to reproduce Fig. 5 of the publication: L. Mewes, H. Löwe, M. Schneebeli & B. Walter, *Optical determination of snow density via sub-surface scattering*, Commun Phys, doi: [10.1038/s42005-026-02490-1](https://doi.org/10.1038/s42005-026-02490-1).
The source code generating Fig. 5 for the above mentioned publication is available at [10.16904/envidat.726](https://doi.org/10.16904/envidat.726).
 Files
`SI01_Reflectance_Coldlab.h5`: Reflectance and partial reflectance data of a snow profile using the [SnowImager](https://www.snowimager.ch/).
`uCT_reference_data.csv`: Reference data extracted from a micro-computed tomography measurement.
Please refer to the `README` of the analysis code at [10.16904/envidat.726](https://doi.org/10.16904/envidat.726) for further information.

en: laboratory-study reflection snow-microstructure snow-stratigraphy snowimager snow-profile snow-density

envidat

en: EnviDat: the Environmental Data Portal

en: Data for the publication Optical determination of snow density via sub-surface scattering

envi

en: Environment

format: ZIP

laboratory-study

display_name: laboratory-study

reflection

display_name: reflection

snow-density

display_name: snow-density

snow-microstructure

display_name: snow-microstructure

snow-profile

display_name: snow-profile

snow-stratigraphy

display_name: snow-stratigraphy

snowimager

display_name: snowimager


en:
To assess the possible consequences of potential changes in snow accumulation and temperature and their impact on avalanche hazard, we introduce a comprehensive multi-step framework. It includes the analysis of climate change scenarios as well as the modeling of future snow covers and the simulation of avalanches in a case study region in central Switzerland.
Using a downscaling and a quantile mapping approach, we considered the high emission RCP8.5 from the CH2018 Swiss climate change scenarios and simulated a potential snow cover of more than 100 future winters with the snow cover model SNOWPACK. Changing snow accumulation and snow cover temperature was taken into account for two future time frames. The changed parameters were used in the RAMMS::EXTENDED avalanche simulation software on large scale.

en: hazard avalanche-mapping new-snow avalanche climate-change ramms

en: A novel approach for bridging the gap between climate change scenarios and avalanche hazard indication mapping

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

climate-change

display_name: climate-change

hazard

display_name: hazard

new-snow

display_name: new-snow

ramms

display_name: ramms


en: This repository presents the basis data of both the Energyscape 1 (2018) and the Energyscape 2 (2022) survey about renewable energy infrastructure related landscape preferences in Switzerland. Both  datasets are based on Swiss-national representatative online panel surveys (BILENDI). Information about the choice design and landscape visualizations can be derived from https://www.sciencedirect.com/science/article/pii/S2352340921003097fig0001

en: energy-transition landscape-perception survey renewable-energy discrete-choice

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: Energyscape 2 - Comparing stated preferences of renewable energy landscapes in Switzerland in 2018 and 2022

en:
Resource Title: Energyscape2 basis data with original Respondent ID
    Size: 70331 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e3451afd-f9d8-41ce-a7dc-d3f9fad95e67/resource/4ad511f8-f29a-4b71-bd2c-8b2e9e541ee6/download/energyscape2_n1006_basis_ce1_swth_sel.csv
    Description: This is solely the Energyscape 2 basis data including the original respondents ID "sys_RespNum" to be merged with the covariated data set.

en:
Resource Title: Energyscape1 & Energyscape2 basis data
    Size: 136853 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e3451afd-f9d8-41ce-a7dc-d3f9fad95e67/resource/9081e5b8-6f16-4873-84f3-f8ab6d030cf2/download/energyscape12_basis_ce1_swth_sel.csv
    Description: This is the already cleaned and ready to use basis dataset for the comparison of stated choice preferences across the 2018 (Energyscape 1, n=844) and the 2022 (Energyscape 2, n=1006) surveys. The first four numbers in the first column "sys_RespNum" of the dataset refer to the year of the surveys, followed by the original Respondent ID. The date can be uploaded as is to analysis software (like Sawtooth) and can be filtered by survey with the help of the very last column "surveytime".

en:
Resource Title: Energyscape2 Covariates
    Size: 12192 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e3451afd-f9d8-41ce-a7dc-d3f9fad95e67/resource/9d6902f1-784f-4a0a-be6a-aa800b430beb/download/energyscape2_n1006_basis_cov_items_recoded.csv
    Description: This data includes the recoded covariates used in the publication (Cov_1, Cov_2, Cov_3). They can be merged with the column "sys_RespNum" to the basis dataset of the Energyscape 2 survey.

discrete-choice

display_name: discrete-choice

energy-transition

display_name: energy-transition

landscape-perception

display_name: landscape-perception

renewable-energy

display_name: renewable-energy

survey

display_name: survey


en: The reaction of ozone with bromide in polar regions results in the formation of reactive bromide species with impacts on ozone budget and the oxidative capacity of the lower atmosphere. Here, we present a data investigating the temperature dependence of bromide oxidation by ozone using a coated wall flow tube reactor coated with an aqueous mixture of citric acid and sodium bromide, a proxy for sea salt aerosol in snow or the free troposphere. Thus study shows the effect of of organic species at relatively mild temperatures between the freezing point and eutectic temperature as typical for Earth's cryosphere.

en: polar sea-salt-aerosol cryosphere laboratory-study snow arctic antartic

en: Kinetic experiments on the oxidation of bromide by ozone from 289-245 K.

en:
Resource Title: Experimental Results: Uptake coefficients vs. temperature and ozone concentration
    Size: 1422 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8c77d71e-155b-40ab-a446-ae2dccac9740/resource/af7e17ca-b08b-48d2-8198-621ec0814252/download/dataenivdat.csv
    Description: * Final Data to Figure 3: Uptake coefficients as a function of temperature at 5E12 molecules per cm3 ozone concentration.
* Final Data to Figure 6: Uptake coefficients at different temperatures as a function of gas- phase ozone concentration.

The average ozone uptake coefficients of the three cycles between the bypass and the flow tube per repeat is taken as the mean uptake coefficient for each experiment. Gamma was corrected for gas phase diffusion limitation following the Cooney–Kim– Davis (CKD) method52 (see supporting material of publication for details).

en:
Resource Title: Experimental results of uptake coefficient vs. temperature and ozone concentration
    Size: 1279 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8c77d71e-155b-40ab-a446-ae2dccac9740/resource/fd675417-23be-47bb-bcf3-44c3bb2eb572/download/dataenivdat.csv
    Description: Data to Figure 3: Measured uptake coefficients as a function of temperature at 5E12 molecules per cm3 ozone concentration.

Data to Figure 6: Measured  uptake coefficients at different temperatures as a function of gas- phase ozone concentration.

antartic

display_name: antartic

arctic

display_name: arctic

cryosphere

display_name: cryosphere

laboratory-study

display_name: laboratory-study

polar

display_name: polar

sea-salt-aerosol

display_name: sea-salt-aerosol

snow

display_name: snow


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 Othmarsingen in Switzerland where one station is located within a natural deciduous forest stand (OTB) with European beech (_Fagus sylvatica_; 120-140 yrs) and lime trees (_Tilia sp._; 120-140 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, OTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Othmarsingen is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

envidat

en: EnviDat: the Environmental Data Portal

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

en:
Resource Title: Field station data (OTF)
    Size: 11582801 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/5b4e810a-ce77-47dc-9e23-ba691ade9192/download/otffield.csv
    Description: Data file.

en:
Resource Title: Data plot of the forest station (OTB)
    Size: 255873 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/f01faaab-8cee-4b07-b95c-1498f5b09285/download/otbplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site photo of the forest station (OTB)
    Size: 319164 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/b1937555-6a89-4452-93f9-3cf418382fb6/download/otb.jpg
    Description: Site photo of the forest station from above (viewing downwards the slope).

format: jpeg

en:
Resource Title: Data plot of the field station (OTF)
    Size: 302026 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/663df714-b0fb-45d3-b83f-3e80755a0a1a/download/otfplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Forest station data (OTB)
    Size: 10501901 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/f5f71a78-9574-4bcc-a326-4d455b6821a4/download/otbforest.csv
    Description: Data file.

en:
Resource Title: Site aerial photo (Othmarsingen)
    Size: 7687492 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/d74e4b24-bd75-4ce2-8bb5-4c04b77d8099/download/otfront.jpg
    Description: Site aerial photo from both Othmarsingen stations. Source: Google. 2016. Site aerial photo from both Othmarsingen stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en:
Resource Title: Site photo of the field station (OTF)
    Size: 11868194 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/74f4dcb2-e18d-40bb-bb18-8383f907a285/download/otf.jpg
    Description: Site photo of the field station from below (viewing upwards the slope).

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:
The dataset consists of the standardized precipitation (SPI) and the standardized precipitation evapotranspiration index (SPEI) index with a 30 arcsec (~1km) horizontal resolution.
Data for precipitation rates (pr) and potential evapotranspiration (pet) are taken from CHELSA V2.1 (https://doi.org/10.16904/envidat.228.v2.1). Both data sets are monthly time series from 1980 to 2018 at 30 arcsec. and have the unit of kg m-2 month-1. SPEI is a more reliable measure of drought than SPI as it additionally considers the effect of potential evapotranspiration. Potential evapotranspiration (pet) is the amount of water per area per time that can evaporate at the soil surface or be transpired by plants in absence of water supply limitations. SPEI effectively estimates for a given location how the climatic water balance, i.e., the difference between precipitation rate (pr) and potential evapotranspiration (pet), relates to the long-term mean. Here, pet was calculated with the Penman-Montheith approach, assuming surface conductance of a reference crop of 12 cm height following the definition of the Food and Agriculture Organization of the United Nations (FAO), originating from CHELSA-BIOCLIM+ database (https://www.doi.org/10.16904/envidat.332). To obtain global time series of SPEI, in each pixel the frequency distribution of water balance estimates (pr-pet) is approximated with a log-logistic probability distribution function. We calculate monthly SPEI using a 12-month memory and approximate the parameters of the log-logistic probability distribution based on the time series from 1980-2018. Such a 12-month time window is suitable to capture long-term drought events that are long enough to impose substantial impacts on agriculture, hydrology, and ecosystems while ones at shorter time scales would be more appropriate to detect short-term drought. For each month, SPEI is calculated considering the respective water-balance value and the values of the eleven preceding months. Here we use SPEI-12 in December to represent the overall water-balance condition of the respective year. The resulting SPEI data has a horizontal resolution of 130 arcsec (~1km). The calculation of SPI and SPEI is done in R with the package SPEI (https://www.doi.org/10.32614/CRAN.package.SPEI).

en: multi-year-drought potential-evapotranspiration chelsa extreme-events drought megadrought precipitation

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: High resolution global standardized drought indices

envi

en: Environment

en:
Resource Title: Multiyear meteorological droughts (MYMD10) statistics - Description
    Size: 1384 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/c1c0dbc9-ec96-462e-bf62-bc90b6aad3ab/download/mymd10_stats_description.csv
    Description: Description of column names, and units of the fields contained in the dataset "Multiyear meteorological droughts (MYMD10) statistics".

en:
Resource Title: Multiyear meteorological droughts (MYMD)
    Size: 368640 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fmymd%2F
    Description: Global annual layers of the multiyear meteorological droughts (MYMD) at a 1/24° (~5km) spatial resolution

en:
Resource Title: Multiyear meteorological droughts (MYMD10) statistics
    Size: 928956 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/fa3d92e1-1eb0-478c-900d-dca818e3b4ff/download/mymd10_stats.csv
    Description: Multiyear meteorological droughts (MYMD10) statistics

Statistics of the multiyear meteorological droughts, containing the ID, duration, area, and empirical ranking of the droughts, and the anomalies in kNDVI

en:
Resource Title: CHELSA-drought-indices Technical Documentation
    Size: 257611 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/3149a573-b55c-499c-9efa-2cbe920bc483/download/chelsa_file_specification_drought_indicies.pdf
    Description: Technical documentation document including the variable names, units, scaling, offset, and background.

en:
Resource Title: Multiyear meteorological droughts (MYMD10)
    Size: 107930 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fmymd10%2F
    Description: Global annual layers of the multiyear meteorological droughts (MYMD) at a 1/12° (~10km) spatial resolution

en:
Resource Title: Multiyear meteorological droughts (MYMD) statistics
    Size: 785961 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/21046cb1-0a1c-4890-8025-aefb5d9f3f1d/download/mymd_stats.csv
    Description: Statistics of the multiyear meteorological droughts, containing the ID, duration, area, and empirical ranking of the droughts.

en:
Resource Title: Kernel Normalized Difference Vegetation Index Anomaly (QKNDVI)
    Size: 6710886 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fqkndvi%2F
    Description: Global annual layers of the the kernel normalized difference vegetation index anomaly (qkndvi) at a 1/12° (~10km) spatial resolution.

en:
Resource Title: Standardised Precipitation Evapotranspiration Index (SPEI)
    Size: 209715200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fmonthly%2Fspei12%2F
    Description: Global monthly layers of the Standardized Precipitation Evapotranspiration Index (SPEI) a 30 arcsec (~1km) spatial resolution

en:
Resource Title: Multiyear meteorological droughts (MYMD) statistics - Description
    Size: 1114 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/a32ef5b4-fab9-4d15-b6da-c8244029027d/download/mymd_stats_description.csv
    Description: Description of column names, and units of the fields contained in the dataset "Multiyear meteorological droughts (MYMD) statistics".

en:
Resource Title: Standardized Precipitation Index (SPI)
    Size: 209715200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fmonthly%2Fspi12%2F
    Description: Global monthly layers of the Standardized Precipitation Index (SPI) a 30 arcsec (~1km) spatial resolution

en:
Resource Title: CHELSA-drought-indices Technical Documentation
    Size: 335096 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/a4ec699c-1e4a-45ab-8b7c-ccdf09c6e828/download/chelsa_file_specification_drought_indicies.pdf
    Description: Technical documentation document including the variable names, units, scaling, offset, and background.

chelsa

display_name: chelsa

drought

display_name: drought

extreme-events

display_name: extreme-events

megadrought

display_name: megadrought

multi-year-drought

display_name: multi-year-drought

potential-evapotranspiration

display_name: potential-evapotranspiration


en:
On this repository you can find the monitoring data of the 3 PV power-plants analysed in the article _"Confirmation of the power gain for solar photovoltaic systems in alpine areas"_ (doi: 10.3389/fenrg.2024.1372680) . Each folder contains the following two elements:
1.  **README.txt**  : describes the content of the folder. Especially it describes the plant's monitoring system's architecture and relates it to the various files included in the data sub-folder.  It also provides a detailed description of all processing steps leading to the data sets as available in the data sub-folder and used in the pre-cited article.
3. **data/** : sub-folder containing the file(s) used in the referenced article.

en: alps bifaciality snow photovoltaic winter-electricity

envidat

en: EnviDat: the Environmental Data Portal

en: Monitoring data sets of alpine photovoltaic power-plants

en:
Resource Title: A2.zip
    Size: 27177550 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/40024d58-c912-499e-8f4f-8a9b9189955a/resource/e68bb1d0-915a-49a5-a108-c607356b1889/download/a2.zip
    Description: Title: Monitoring data set at A2 (utility-scale power-plant Muttsee), months 10.2022-09.2023
Provider: AXPO - IWB Industrielle Werke Basel
Last edition: 17.01.2024
Editor: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL

File name structure:
The power-plant is made of 23 string boxes (GAK) and inverters (WR) named after their given number. One file per device is provided in the data/ subfolder, following the same naming convention  (e.g. for the string box number 1, the file name is: “A2_GAK01.csv” and for the corresponding inverter, the file name is “A2_WR01.csv”). Refer to the publication for further details on the setup of the power plant.

File format:
All files are provided in the CSV format.

Column headings:
	String boxes and inverters (GAK & WR):
	⁃	device_name (string): name of the device (same as file name)
	⁃	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC

	String boxes (GAK):
	⁃	I_# (double): input current from the substring number # (W)
	⁃	I_SUM (double): output current of string box (A)
	⁃	U_DC (double): output voltage of string box (V)
	⁃	P_DC_# (double):  input DC power from the substring number # (W)
	⁃	P_DC (double): output DC power of string box (W)
	⁃	$S$_T#_$T$ (double): temperature from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S)  of table T. Two types of temperature measurements (#) are available: 1=standard cell temperature (°C) , 2=module temperature on the rear side (°C) .
	⁃	$S$_SRAD_T (double): poa irradiation (W/m**2) from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S)  of table T.

		Inverters (WR):
	⁃	I_DC (double): input DC current(A)
	⁃	U_DC(double): input DC voltage(V)
	⁃	P_DC (double): input DC power (W)
	⁃	P_AC (double): output AC power (W)

Preprocessing:
	1. Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.

	2. Missing data:
	⁃	Data holes of less or equal to 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).

	3. Wiring losses:
	⁃	To be consistent with A1, wiring losses are corrected at A2. The wiring loss between the string boxes and the inverters is removed by multiplying the value of input P_DC at the inverter level (P_DC,inv) by the mean ratio P_DC,inv / P_DC,arr.
	⁃	The computed mean wiring loss is 2.3\%. It is computed from 2023-02-01 to 2023-09-30, after the long data hole in the data sets of the string boxes.

Mean uptime:
	Raw:
	⁃	WR: 98.2%
	⁃	GAK*: 38.5%
	Processed:
	⁃	WR: 99.6%
	⁃	GAK*: 56.4%

	*The uptime at the string box level (GAK) is low because PMUs at this level shut down during steady and low signal leading to unavailable data at night. In addition, the 23 days downtime of 	January 2023 could not be interpolated nor replaced.

media_type: application/zip

en:
Resource Title: A1.zip
    Size: 5999205 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/40024d58-c912-499e-8f4f-8a9b9189955a/resource/1a7597fd-203a-427f-851a-009673c29374/download/a1.zip
    Description: Title: Monitoring data set at A1 (test-site of Totalp), years 2018-2022
Provider: ZHAW - EKZ

Edition: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL
Last edition: 17.01.2024

File name structure:
The test site contains 6 segments named from A to F. The six files provided in the data/ subfolder follow the same naming convention (e.g. for segment A, the file name is: “A1_A.csv”). Refer to the publication for further details on the setups of the segments.

File format:
All files are provided in the CSV format.

Column headings:
	•	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC
	•	poa_front (double): front plane-of-array irradiation (W/m**2)
	•	poa_back (double): rear plane-of-array irradiation (W/m**2)
	•	mod_temp (double): module’s temperature (°C)
	•	P_AC (double): output AC power (W)

Preprocessing:
	Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.

	Missing data:
	⁃	Data holes of less than 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).

	Wiring losses :
	⁃	As described in [1] , the test-site setup caused abnormally large wiring losses,  mainly due to the distance to optimisers and to the low installed power per DC-wire.
	⁃	The wiring losses comprised between 10% and 15%, are averaged hourly and added to the measured DC power.

	Misc.:
	⁃	P_AC is computed for each segment based on the measured DC power and the average inverter’s efficiency (96.1%).
	⁃	As described in [1],  the peak power of the installed module, used to compute the final yield is slightly different from the values announced by the manufacturer.

Mean uptime:
	Raw:
	⁃	95.2%
	Processed:
	⁃	100%

References:
[1] 	D. Anderegg, S. Strebel, and J. Rohrer, “Alpine Photovoltaik Versuchsanlage Davos Totalp : Erkenntnisse aus 5 Jahren Betrieb,” de, Sep. 	2023, Accepted: 2023-09-29T09:13:16Z Publisher: ZHAW Zürcher Hochschule für Angewandte Wissenschaften.DOI: 10.21256/	zhaw-2524. [Online]. Available: https://digitalcollection.zhaw.ch/handle/11475/28797 (visited on 12/15/2023).

alps

display_name: alps

bifaciality

display_name: bifaciality

photovoltaic

display_name: photovoltaic

winter-electricity

display_name: winter-electricity


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 Neunkirch in Switzerland where one station is located within a natural deciduous forest stand (NEB) with European beech (_Fagus sylvatica_; 160 yrs), sycamore maple (_Acer pseudoplatanus_; 160 yrs) and lime trees (_Tilia sp._; 110 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NEF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Neunkirch is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

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

envi

en: Environment

en:
Resource Title: Data plot of the field station (NEF)
    Size: 313178 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/084cafd7-038f-4922-a36c-af54c00399cb/download/nefplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Forest station data (NEB)
    Size: 10603940 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/0dc8b0c2-02f7-4052-bdfc-ac967a916888/download/nebforest.csv
    Description: Data file.

en:
Resource Title: Field station data (NEF)
    Size: 10713187 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/f7dc0cd8-8dd9-49f6-bfee-47d2945a23df/download/neffield.csv
    Description: Data file.

en:
Resource Title: Data plot of the forest station (NEB)
    Size: 229180 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/64f63815-a1df-4f25-92d3-75e2c19b2abd/download/nebplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site photo of the forest station (NEB)
    Size: 5116944 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/49887857-0fad-44d6-a56c-58e8851a65a8/download/neb.jpg
    Description: Site photo of the forest station from below (viewing upwards the slope).

en:
Resource Title: Site photo of the field station (NEF)
    Size: 1877748 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/f8bb24e8-a6a2-4cf5-bf88-f688b7a4e488/download/nef.jpg
    Description: Site photo of the field station from the side.

en:
Resource Title: Site aerial photo (Neunkirch)
    Size: 8951072 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/68f3a7a3-21b6-45cd-8578-6232edf6d1ef/download/nefront.jpg
    Description: Site aerial photo from both Neunkirch stations. Source: Google. 2016. Site aerial photo from both Neunkirch stations. Retrieved November 11, 2016, from https://www.google.ch/maps

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology


snow-drift-station-micro-rain-radar

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

en: rain raclets precipitation radar mountain snow

en: Snow Drift Station - Micro Rain Radar

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

en:
Resource Title: MRR data of period 4
    Size: 517071441 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.113/raclets/Period4.zip
    Description: The dataset contains measurements between March 13 and March 22, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en:
Resource Title: MRR data of period 3
    Size: 340845550 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.113/raclets/Period3.zip
    Description: The dataset contains measurements between March 8 and March 13, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en:
Resource Title: MRR data Period 2
    Size: 720723546 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.113/raclets/Period2.zip
    Description: The dataset contains measurements between March 5 and March 8, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en:
Resource Title: Parameter MRR
    Size: 93093 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/898d94a9-7a48-4fdc-9eda-43f536e39285/resource/cc39db24-81eb-4110-8a71-d7b04d5f56e6/download/mrr_parameters.pdf
    Description: The PDF contains additional information on parameters which were set for the certain time periods (time in UTC).

en:
Resource Title: MMR Data Period 1
    Size: 2576980378 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.113/raclets/Period1.zip
    Description: The dataset contains measurements between March 1 and March 5, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

mountain

display_name: mountain

precipitation

display_name: precipitation

raclets

display_name: raclets

radar

display_name: radar

rain

display_name: rain

snow

display_name: snow


en: Data obtained in the free-air CO2 enrichment (FACE) experiment at Hofstetten, NW Switzerland, between 2009 and 2016. This dataset contains analyses of the soil solution throughout the experiment, especially for nitrate, as well as different analyses done at the end of the experiment: ammonium and nitrate captured by ion-exchange resin bags and extracted from soil cores, gross N mineralisation and nitrification measured by isotope dilution.

en: picea-abies co2 nitrogen face forest soil

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: EnviDat: the Environmental Data Portal

en: Nitrogen availability under trees exposed to CO2 enrichment (FACE)

en:
Resource Title: Collection points
    Size: 453 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/1e7dfaf0-d504-4bab-ae3b-8f96181b4e84/download/points.csv
    Description: Collection points under the trees

en:
Resource Title: Water analyses
    Size: 65553 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/50749920-cf85-4140-8802-54beffcf490e/download/water-analyses.csv
    Description: Analyses of water, especially soil solution

en:
Resource Title: Resin bags
    Size: 1237 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/594288d3-95ff-4ad6-914e-d3e9c1d0ea42/download/resin-bags.csv
    Description: Ammonium, nitrate and their 15N in resin bags

en:
Resource Title: Soil C and N
    Size: 1298 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/dc99385c-0ab8-4c7f-88cd-cf53ba0aea41/download/soil-c-n.csv
    Description: Analyses of C, N and their stable isotopes in the soil, and soil pH

en:
Resource Title: Gross N mineralisation and nitrification
    Size: 1183 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/f6a9e85f-187b-4a55-9f57-e243d14906ab/download/mineralisation-nitrification.csv
    Description: Gross rates of N mineralisation and nitrification (15N dilution)

en:
Resource Title: Collection of soil solution
    Size: 33840 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/3cfe06e1-c280-4b18-903a-321ceef6044a/download/soil-solution.csv
    Description: Soil solution collected by suction cups

face

display_name: face

forest

display_name: forest

nitrogen

display_name: nitrogen

picea-abies

display_name: picea-abies

soil

display_name: soil


en:
This dataset contains the data acquired during the expedition to Princess Elisabeth Antarctica Station in December 2016 and January 2017. The dataset consits of meterorological data, drifting snow mass flux data, SnowMicroPen data and Terrestrial Laser Scanning data.
Please refer to the README for more information about the data.
This dataset is the basis of the following publication:
Sommer, C. G., Wever, N., Fierz, C., and Lehning, M.: Wind-packing of snow in Antarctica, The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-36, in review, 2018.

en: antarctica drifting-snow mass-flux snowmicropen meteorological-data terrestrial-laser-scanning

en: Expedition to Princess Elisabeth Antarctica Station, 2016/2017

envi

en: Environment

en:
Resource Title: README
    Size: 3534 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/b5c9438a-83c3-4afb-8f37-b3ec18d3db6e/resource/f5b4224d-6a68-4090-b0d6-24234f698bb5/download/readme.txt
    Description: Describes the dataset in detail

format: TXT

media_type: text/plain

en:
Resource Title: Dataset
    Size: 697932186 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.30/princessElisabethStation_2016_2017/
    Description:

antarctica

display_name: antarctica

drifting-snow

display_name: drifting-snow

mass-flux

display_name: mass-flux

meteorological-data

display_name: meteorological-data

snowmicropen

display_name: snowmicropen

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning


litterfall-lwf

en:
Litterfall is a key parameter in the biogeochemical cycle of forest ecosystems, linking the tree part to the soil compartment. Litterfall has been collected on 15 LWF plots using 10 traps that are emptied every 4 to 8 weeks since 1996 or later. Both the biomass of the litter and its chemical content (including heavy metals) are measured, in order to quantify the annual return of nutrients and organic matter to the soil. Furthermore, the analysis of the temporal pattern of litterfall production gives insight into possible effects of anthropogenic and natural factors (e.g. severe drought) on the ecosystem and the vitality of the forest stand, provides information on the phenological development of the stand, and, in particular, allows mast years to be identified. At 7 broadleaved sites, litterfall was also used to estimate the leaf area index (LAI) of the forest stand.
 Purpose:
To quantify the annual return of nutrients and organic matter to the soil.
 Manual Citation:
 * Thimonier, A., Brang, P., Ottiger, A., 1997. Kapitel C5. Streufall, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-18.
 *  Ukonmaanaho  L.,  Pitman  R,  Bastrup-Birk  A,  Breda  N,  Rautio  P,  2016:  Part  XIII:  Sampling  and  Analysis  of  Litterfall.  In:  UNECE  ICP  Forests  Programme  Co-ordinating  Centre  (ed.):  Manual  on  methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute for Forests Ecosystems, Eberswalde, Germany, 14 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Thimonier A, Sedivy I, Schleppi P (2010) Estimating leaf area index in different types of mature forest stands in Switzerland: a comparison of methods. European Journal of Forest Research, 129 (4): 543-562. [doi: 10.1007/s10342-009-0353-8](http://doi.org/10.1007/s10342-009-0353-8 )

en: litterfall nutrient-content foliage-production fruit-production branches icp-forests long-term-forest-ecosystem-research swiss-forest-lab

en: Litterfall LWF

title_for_slug: litterfall-lwf

format: HTML

branches

display_name: branches

foliage-production

display_name: foliage-production

fruit-production

display_name: fruit-production

icp-forests

display_name: icp-forests

litterfall

display_name: litterfall

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

nutrient-content

display_name: nutrient-content

swiss-forest-lab

display_name: swiss-forest-lab


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).

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: EnviDat: the Environmental Data Portal

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

en:
Resource Title: European Snow Booklet public metadata
    Size: 1536715 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/492dfd3d-99d4-4cfb-b129-77e98344a237/resource/d05304f6-6862-4f6c-b4b9-3601201cc824/download/metadata.xlsx
    Description: 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:
Resource Title: COST European Snow Booklet (ESB)
    Size: 136492575 bytes
    Format: application/pdf
    URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A20198/datastream/PDF/Haberkorn-2019-European_Snow_Booklet-%28published_version%29.pdf
    Description: Please find here the web version of the COST European Snow Booklet (ESB).

en:
Resource Title: COST European Snow Booklet (ESB) - DORA Link
    Size: 1 bytes
    Format: No Info
    URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:20198
    Description: DORA Link of the COST European Snow Booklet (ESB).

en:
Resource Title: List of authors and list of the editorial board of the European Snow Booklet
    Size: 14675 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/492dfd3d-99d4-4cfb-b129-77e98344a237/resource/1e7628d8-50b7-45cc-8974-b50907b365fc/download/list_of_authors_and_editorial_board.xlsx
    Description: 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.

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:
Data and scripts of publication:
Madleina Gerecke, Oskar Hagen, Janine Bolliger, Anna M. Hersperger, Felix Kienast, Bronwyn Price, Loïc Pellissier (2019) Assessing potential landscape service trade-offs driven by urbanization in Switzerland. Palgrave communications.
Contains land use projections for Switzerland and scripts and data for these projections as well as the calculation of landscape services.
Data Folder:
Contains sub-folder with the data necessary for this study (provided were no copyright issues, otherwise placeholders with descriptions), and folders where produced data may be stored
Scripts Folder:
Contains scripts organized into subfolders depending on their purpose
Note: Some abbreviations within the scripts and data are derived from German words and not English.

en: modeling landscape-services land-use statistical-model urbanization switzerland land-use-change

en: Land use projections and services for Switzerland

en:
Resource Title: Data for Assessing potential landscape service trade-offs driven by urbanization in Switzerland
    Size: 4119284 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c259ac71-37ea-477e-94b0-c463cc195304/resource/3f13ea3a-3dd2-48a3-98a1-284b565b2c2d/download/data.zip
    Description: The provided folder structure follows the set up of the scripts.
Data is only provided when it has been fully produced by us, otherwise dummies are given.
For data that will be produced by one of the scripts, no dummies are given.
The folders may contain sub-folders, which would be filled if the scripts were all run

## 00_Analysis_Data
Data produced throughout the process of the calibration and projection that is later needed for analysis

## 01_Raw_Data
Primary data from external sources that were used to compile the rasters and numbers used during the calibration and projection of landscape transitions as well as service calculation

## 02_Prepared_Data
Data that will be prepared for further use by scripts are put in here
Additionally it contains the parameter sheets for the transition predictors that we compiled

## 03_Model_Data
# Model outputs
Folder were the projection models statistics will be saved
# Models
Folder into which the actual transition models will be saved
# Residuals
Folder into which data on models residuals will be saved for future use

## 04_Projected_Data
The output of the projections will be saved into this folder

## 05_Service_Data
Any service calculations will be saved in here

## 06_Results_Analysis
Any Analysis plots and tables as well as intermediate data will be saved here in the respective sub-folder

en:
Resource Title: Scripts for Assessing potential landscape service trade-offs driven by urbanization in Switzerland
    Size: 72256 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c259ac71-37ea-477e-94b0-c463cc195304/resource/062e679c-5d1b-4733-8d91-4caca049816f/download/scripts.zip
    Description: Scripts ordered by their main purpose within sequential folders in this ReadMe marked with ##

Within the folders the capital letters refer to the parallel or sequential use of the scripts; scripts here in ReadMe are marked with #

## 00_Function Scripts ##
# Functions.r
Script containing several functions for analyzing statistical models: cohen.kappa, meva.table, D2, max-Tss, plot-TSS

# Service_functions.R
Script containing functions for calculating all services and returning sums (and median for bd and rec) as well as rasters

## 01_Data Preparation ##
# A_AS_raster_preparation.R
Preparation of the land use rasters for the years 1985, 1997, and 2009 based on the original Arealstatistik (AS/ASCH); Assigning our categories and assining new values to all "construction sites" for calibrating the models
For model projection starting point (2009) and for service calculations (all ASCH years) the "other" categories were assigned to the land use categories based on dominant neighbor, so that there were no empty cells
Creation of water & mountainous area raster that stayed stable throughout the projections
Creation of MFH raster (2009), to have as base for all new projection years, as this category never becames any other

# B_Factors_preparation.R
Preparation of the factor rasters that were used to calculate service values per cell (see Table 2): LWfactor, Transportation, Vol, Rivers, Lakes, slope, TWW, Hazard_risk

# B_Predictors_preparation.R
Preparation of the raster of the predictors used for calibrating (ASCH years) and projecting (stable) the transition models that do not depend on the land use categories: Temperature (ASCH years), solar radiation (stable), Public transportation access (stable), Elevation (stable), Workers density (ASCH years), Population change (ASCH transitions)

# B_Regions_preparation.R
Preparation of bioregions as raster to be used to mask asxxxx later to calculated services and land use area just for one region

# C_Pred_proj.R
Projecting the dynamic predictors into the future for projecting the land use transitions with the model: Linear extrapolations for workers densities and population; more detailed extrapolation of temperature (based on data for all stations that matched between the temp table we used for the calibration period and the projections from CS2M, and then making a spatial interpolation for all years based on the interpolation of temperature for all years per station)

## 02_Model calibration ##
# A_Bioreg_pred_corr.R
Calculating correlation between the predictors for each bioregion and land use category, Output are those with too high correlation so that one predictor can be removed from transitions were both predictors occur

# A_trans_numbers_bioreg.R
Calculate transition numbers for each bioregion to decide which transitions to primarily consider

# B_Bioreg_ext_eval.R
Calculating TSS based on the external evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 85-97, evaluation data: 97-09)

# B_Bioreg_int_eval.R
Calculating TSS based on the internal evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 70%, evaluation data: 30%)

# C_Bioreg_TSS_analysis.R
Extracting TSS numbers from internal and external evaluation, calculating mean and median for each transition for each region for each evaluation method and saving as csv per region to be able to select only the transitions with high enough model performance

# D_Bioreg_Models_for_prediction.R
Calibration of the models that were then used to project land use transitions into the future; calibrated separately for each bioregion

# E_Residuals_trans_models.R
Calculation of Moran's I statistics to analyze the residuals of the land use transition models

## 03_Projections ##
# A_Bioreg_Projections_run.R
Master script for: Extrapolaitng into the future with the regional models and then assembling for each time step to calculate new AS predictors; Several Outputs: txt file to test for NAs in Predictors, txt file with random seed number for sampling, txt file with times for calculation steps (check progress of script while running), csv sheet with projected transition frequencies, tif-rasters for every region and time step, pdf with raster plot for every region and time step

## 04_Service calculation ##
# A_Bioreg_as_services.R
Calculate services per bioregion for years 1985, 1997, 2009

# A_Service_calculation_bioregions.R
Extracting service numbers(sums) per bioregions for all projection runs and storing them in a list of matrixes to be available for further plotting; can be run for swiss wide projections or regional ones

## 05_Analysis ##
# A_Bioreg_ASCH_development.R
Extracting the occurrence of each category per region for all runs (first part), then for ASCH years, and then plotting them nicely; only works for regional projections

# A_Bioreg_Predictors_importanceD2.R
Calculating D2 for each transition and each considered predictor from bivariate models to get value of importance

# B_Bioreg_Pred_imp_analysis.R
Using calculated D2 to sort Predictors according to their importance for each transition

# A_Bioreg_Spatial_results_analysis.R
Plotting randomly sampled runs for ASCH and services to analyses their spatial development

# A_Bioreg_Transition_numbers_check_v1.R
Analyzing the frequency for all transitions for all regions and producing the point plots for each transition separately

# A_Bioreg_Transition_numbers_check_v2.R
Analyzing percentage and numbers of all transitions but plotting them per region and originating ASCH category

# B_Transition_Analysis.R
Further Analysis of transition numbers

# A_Service_analysis.R
Plotting of the service development for bioregions in several ways for analyzing

land-use

display_name: land-use

land-use-change

display_name: land-use-change

landscape-services

display_name: landscape-services

modeling

display_name: modeling

statistical-model

display_name: statistical-model

switzerland

display_name: switzerland

urbanization

display_name: urbanization


en: The dataset contains several snow models in the Standard Tesselated Geometry File Format (stl) for 3D visualization, printing and additive manufacturing. Different snow types are available (new snow, rounded snow, depth hoar, buried surface hoar, graupel).

en: snow weak-layer 3d-model snow-cast 3d-print new-snow depth-hoar rounded-snow

envi

en: Environment

en:
Resource Title: Description of snowtypes, filenames and other metadata
    Size: 2170683 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/f5163bdf-657d-43f8-a907-5a87e440f06a/resource/2092babe-4033-4cd3-bacc-857bce65cbb1/download/3d_snow_models_metadata.xlsx
    Description: This file contains information about the stl-files of the different snow models. Snowtype (Schneeart), International Snow Classification, preview picture, notes about the origin of the snow, filename of the stl-data, and physical size of the model are given.

en:
Resource Title: Snow models in STL-format
    Size: 382570967 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f5163bdf-657d-43f8-a907-5a87e440f06a/resource/59fbf858-ae63-4067-9c51-4cd21817e22c/download/3d_snow_stl.zip
    Description: The zipped file contains all data described in the file 3d_snow_models_metadata. The stl-files should be ready for additive manufacturing.

depth-hoar

display_name: depth-hoar

new-snow

display_name: new-snow

rounded-snow

display_name: rounded-snow

snow

display_name: snow

snow-cast

display_name: snow-cast

weak-layer

display_name: weak-layer


en:
Nuclear microsatellite markers and genotype data for _Trichopria ddrosophilae_
This data set comprises (i) the characteristics of a set of 21 species-specific nuclear microsatellites for PCR amplification in _Trichopria drosophilae_ (ii) and genotype data for samples collected in southern Switzerland (Canton of Ticino), with few reference samples from Canton of Vaud, southern Germany, and northern Italy (lab-reared population).
Markers were developed by Ecogenics GmbH, Balgach (Switzerland), using MiSeq Nano 2x250 v2 format (on a mix of 10 individuals). Multiplex PCR assays for multilocus genotyping were established by Ecological Genetics (WSL Birmensdorf), and population genetic analyses are found in Gugerli et al., Agrarforschung Schweiz 2019.

en: drosophila-suzukii simple-sequence-repeats switzerland biological-control nuclear-microsatellite-markers multilocus-genotypes trichopria-drosophilae population-genetics

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: Nuclear microsatellite markers for Trichopria drosophilae, parasitoid wasp on Drosophila suzukii

en:
Resource Title: Trichopria-drosophilae_nuclear-microsatellite-markers_characteristics
    Size: 6134 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a69b5f91-0e30-45ba-9d42-06db76b549c4/resource/9bd01ee4-8334-4d38-b64e-806fc839fa8c/download/trichopriadrosophilae_nucmicrosat_seqinfo.csv
    Description: Table comprising all pertinent information for multiplex PCRs of species-specific nuclear microsatellite makers for Trichopria drosophilae, comprising all 21 newly developed markers, details on full sequences with GenBank accession numbers, primer sequences (including labeling and pig-tails), and repeat motives. PCRs with respective annealing temperatures (AnnealingTemp) refer to Type-It Multiplex PCR Kit (Qiagen, Hilden, Germany).

en:
Resource Title: Trichopria-drosophilae_nuclear-microsatellite-multilocus-genotype_dataset
    Size: 100131 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a69b5f91-0e30-45ba-9d42-06db76b549c4/resource/9998d313-6c9a-4abc-b83b-a5b0c31c07cb/download/trichopriadrosophilae_nucmicrosat_genotypes.csv
    Description: Multilocus genotypes (biallelic coding for 21 nuclear microsatellites) of Trichopria drosophilae described in Gugerli et al. Agrarforschung Schweiz 2019. Missing data denoted as '999'. Population codes (PopNo) are the following: 1, Vezia; 3, Contone ; 5, Davesco; 6, Corteglia; 7, Mezzana; 8, Stabio; 9, Gordola; 10, Sementina; 12, Brusata di Novazzano; 14, Monteggio; 16, Giubiasco; 17, ComoBP; 18, VD; 19, Weil_D; 20, Dossenheim; 21, BioPlanet_Como. Coordinates (CoordCH_E, CoordCH_N) refer to the Swiss coordinates system CH1903.

biological-control

display_name: biological-control

drosophila-suzukii

display_name: drosophila-suzukii

multilocus-genotypes

display_name: multilocus-genotypes

nuclear-microsatellite-markers

display_name: nuclear-microsatellite-markers

population-genetics

display_name: population-genetics

simple-sequence-repeats

display_name: simple-sequence-repeats

trichopria-drosophilae

display_name: trichopria-drosophilae


de: Alle Waldflächen im Kanton Aargau sind einem Forstrevier angeschlossen. Ein Forstrevier kann sich über mehrere Gemeinden erstrecken und wird durch einen Revierförster vertreten. Forstreviere erstrecken sich nie über die Kantonsgrenze hinaus.

de: Das AGIS Service Center unterstützt als kantonale Koordinationsstelle die Bereitstellung von Geoinformationen und Metadaten der kantonalen Verwaltung. Die zuständigen kantonalen Fachstellen stellen die öffentlichen Geodaten des Kantons Aargau mittels der Infrastruktur des AGIS Service Center in der Informatik Aargau als Webservices und zum Download bereit.

de: AGIS Service Center Kanton Aargau

political_level: canton

de: Abteilung Wald

de: geocat.ch Permalink

fr: geocat.ch permalien

it: geocat.ch link permanente

en: geocat.ch permalink

de: Forstreviere

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

fr: Agriculture, pêche, sylviculture et alimentation

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

regi

de: Regionen und Städte

en: Regions and cities

fr: Régions et villes

it: Regioni e città

de: AGIS Direktdownload

format: WMS

value: Aargau-Kt - Geocat Harvester


de: Besitzverhältnisse des Waldes (Staat, Gemeinde, privat etc.), Basis bilden die Waldausscheidung, die Parzellengrenzen der amtlichen Vermessung und die Forstorganisation.

de: Waldeigentum


bienenseuchen-sperrkreise

de: Infizierte Bienenstände und temporäre Magazine

de: Amt für Verbraucherschutz

de: Bienenseuchen Sperrkreise

title_for_slug: bienenseuchen-sperrkreise


de:
Kommunale
Siedlungsabfallstatistik Nur von den Gemeinden gesammelte Abfälle exkl. regionale Entsorgungszentren. Nur ein Teil der separat gesammelten Kunststoffe wird wiederverwertet. Ein grosser Teil der gesammelten Kunststoffe wird nach wie vor verbrannt.

de: glas grungut hauskehricht sperrgut ol papier karton metall blech aluminium statistikdaten

kanton-basel-landschaft

en:
The Canton of Basel-Country publishes open datasets of cantonal offices and agencies.
Further information at https://ogd.bl.ch/

de:
Der Kanton Basel-Landschaft veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.
Weitere Informationen unter https://ogd.bl.ch/

de: Kanton Basel-Landschaft

en: Canton of Basel-Country

fr: Canton de Bâle-Campagne

it: Cantone di Basilea-Campagna

de: kanton-basel-landschaft

value: BL - DCAT

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (csv)

de: csv

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (json)

de: json

format: JSON

media_type: application/json

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (jsonl)

de: jsonl

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (parquet)

de: parquet

format: PARQUET

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (rdfxml)

de: rdfxml

format: RDF XML

media_type: application/rdf+xml

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (jsonld)

de: jsonld

format: JSON-LD

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (turtle)

de: turtle

format: RDF Turtle

media_type: text/turtle

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (n3)

de: Abfallmengen nach Kategorie, Gemeinde und Jahr (seit 2017) (xls)

de: xls

aluminium

display_name: aluminium

blech

display_name: blech

glas

display_name: glas

grungut

display_name: grungut

hauskehricht

display_name: hauskehricht

karton

display_name: karton

metall

display_name: metall

ol

display_name: ol

papier

display_name: papier

sperrgut

display_name: sperrgut

statistikdaten

display_name: statistikdaten


adressen-gis-zh

de: Die Adressen stammen aus der Amtlichen Vermessung (AV) (GIS-ZH-Datensatz 406). Im GIS-Browser sind "provisorisch platzierte Adressen" projektierte Adressen der AV-Daten. Falls Sie auf fehlerhafte Daten treffen sollten, sind wir froh um ein Mail an kataster@bd.zh.ch.

geoinformation-kanton-zuerich

fr:
Le département de géomatique est le centre de compétence du system d'information géographique du canton de Zurich.
Nous coordinons l'aquisition des géodonnées d'intérêt commun sur le territoire cantonal et les mettons à disposition des
secteurs public et privé et des particuliers.

en:
The department of geoinformation is the geospatial competency center of the Canton of Zurich.
We coordinate the acquisition of geodata within the cantonal territory and provide public, private, and government sectors with data of outstanding quality.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

it: La divisione della geoinformazione è il centro d'eccellenza del Cantone di Zurigo per dati georeferenziati. Mettiamo a disposizione dati geografici e informazioni di alta qualità per l'economia, la società e la pubblica amministrazione su tutto il cantone.

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

fr: Département de Géoinformation du Canton de Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

de: Kanton Zürich

de: geocat.ch Permalink

spatial: Kanton Zürich

de: Adressen GIS-ZH

title_for_slug: adressen-gis-zh

regi

de: Regionen und Städte

envi

de: Umwelt

de: Administrative Einteilungen

de: Map (Preview) Vorschau GIS-Browser ZH

fr: Map (Preview)

it: Map (Preview)

en: Map (Preview)

format: SERVICE

de: Allgemeiner WFS für Open-Government-Data des Kantons Zürich (OGD ZH WFS)

format: WFS

de: WMS Administrative Einteilungen (OGD)

de: Grundstücks - Lageklassen der einzelnen Gemeinden im Kanton Zürich: http://web.wms.zh.ch/LageklassenZHWMS (http://wms.zh.ch/LageklassenZHWMS)

de: WMS Grundstücks-Lageklassen

value: ZH - Geocat Harvester