modeling-snow-failure-with-dem

title_for_slug: modeling-snow-failure-with-dem

en: snow-micro-mechanics snow-failure snow-avalanche discrete-element-modelling snow

en: Python file

media_type: text/x-python

en: Python file to reproduce the figures in Bobillier et al. (2019)

mimetype: text/x-python

en: Read-me

en: The read-me file contains a description of all the data provided in the zip file.

en: Dataset

en: The zip file contains the data underlying the figures presented in Bobillier et al. (2019). The figures can be reproduced with the python file, which is also provided.

en: This data set includes the modeling results described in the research article by Bobiller et al. (2020). All the figures in the article can be reproduced with the data provided.

discrete-element-modelling

display_name: discrete-element-modelling

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-micro-mechanics

display_name: snow-micro-mechanics

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Modeling snow failure with DEM


maintainer: EnviDat Support

en: snow-ice-temperature snow-water-equivalent weisfluhjoch snow-stratigraphy snow-density

state: active

type: dataset

en: README

media_type: TXT

en: README file giving use metadata.

format: TXT

en: WFJ Snow Profiles 1999-2014

media_type: application/zip

en:
Biweekly manual snow profiles from Weissfluhjoch, Davos, Switzerland.
Version: 2015-09-14T16:25

format: ZIP

mimetype: application/zip

en: Dataset of manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland. Typical snow profile measurements and observations are included (temperature, density, grain size, grain type, hardness, wetness), following the guidelines of the The International Classification for Seasonal Snow on the Ground (ICSSG) [Fierz, C., Armstrong, R.L., Durand, Y., Etchevers, P., Greene, E., McClung, D.M., Nishimura, K., Satyawali, P.K. and Sokratov, S.A. 2009. The International Classification for Seasonal Snow on the Ground. IHP-VII Technical Documents in Hydrology N°83, IACS Contribution N°1, UNESCO-IHP, Paris].

snow-density

display_name: snow-density

snow-ice-temperature

display_name: snow-ice-temperature

snow-stratigraphy

display_name: snow-stratigraphy

snow-water-equivalent

display_name: snow-water-equivalent

weisfluhjoch

display_name: weisfluhjoch

education

fr: Education, science

de: Bildung, Wissenschaft

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland


en: conservation landscape amphibians occupancy-models wetlands

en: Covariate data 1

media_type: CSV

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

format: CSV

en: Model code

media_type: Rmd

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

format: SERVICE

en: Model code, description

media_type: HTML

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

format: HTML

en: Original raw data

media_type: XLSX

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

format: XLS

en: Readme

media_type: PDF

en: Description of methods and datasets.

format: PDF

en: Covariate data 2

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

en: Observation data

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

en:
In the canton of Aargau, hundreds of new ponds have been constructed since the 1990s to benefit declining amphibian populations. This dataset consists of monitoring data for all 12 pond-breeding amphibian species in the canton of Aargau from 1999 to 2019 in 856 ponds, and environmental variables that describe the ponds and the landscape surrounding the ponds. Species observation data is detection/non-detection data from repeat visits during survey years, during which all potentially suitable ponds in an area were surveyed. Environmental variables describing the ponds are whether the pond has been newly constructed since 1991 or not, pond age (if constructed), elevation a.s.l., the water surface area, and whether the water table fluctuates or not. Environmental variables describing the surroundings of the ponds are the percent area of forest within a circular buffer of radius 100m around the pond, the area of large (width ≥6m) roads within a circular buffer of radius 1km around the pond, and structural connectivity.

The canton of Aargau is the owner of the monitoring data; the original datafile is only disclosed upon request and in consultation with the canton of Aargau.

The edited dataset contains cleaned observation data for the 12 amphibian species, as well as compiled and edited covariate data and code to fit dynamic occupancy models.

amphibians

display_name: amphibians

conservation

display_name: conservation

landscape

display_name: landscape

occupancy-models

display_name: occupancy-models

wetlands

display_name: wetlands

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


backward-trajectories

maintainer: Michael Sprenger

title_for_slug: backward-trajectories

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

en: Backward Trajectories

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

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

alps

display_name: alps

atmospheric-dynamics

display_name: atmospheric-dynamics

backward-trajectories

display_name: backward-trajectories

complex-topopgraphy

display_name: complex-topopgraphy

cosmo

display_name: cosmo

lagrangian-analysis

display_name: lagrangian-analysis

raclets

display_name: raclets

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Backward  Trajectories


data-set-on-snow-instability

title_for_slug: data-set-on-snow-instability

en: weak-layer rutschblock crack-propagation slab-tensile-support snow-stability-evaluation failure-initiation snow-avalanche avalanche-forcasting slab propgatoin-saw-test

en: Read-me file on snow instability data

media_type: application/pdf

mimetype: application/pdf

en: data set on snow instability

media_type: text/csv

mimetype: text/csv

en:
These data on snow instability include three data subsets that were analyzed and the results published by Reuter and Schweizer (2018) who suggest a novel framework on how to describe snow instability by failure initiation, crack propagation and slab tensile support.

Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Reuter, B. and Schweizer, J., 2018. Describing snow instability by failure initiation, crack propagation and slab tensile support. Geophys. Res. Lett., 45, doi: 10.1029/2018GL078069.

avalanche-forcasting

display_name: avalanche-forcasting

crack-propagation

display_name: crack-propagation

failure-initiation

display_name: failure-initiation

propgatoin-saw-test

display_name: propgatoin-saw-test

rutschblock

display_name: rutschblock

slab

display_name: slab

slab-tensile-support

display_name: slab-tensile-support

snow-avalanche

display_name: snow-avalanche

snow-stability-evaluation

display_name: snow-stability-evaluation

weak-layer

display_name: weak-layer

en: Data set on snow instability


maintainer: Michael Lehning

en: Description

en: Full Data Description

en: Data Source

media_type: R

en: Coordinates of Grid Points

en: Hourly Gridded Wind Power Time Series

en:
This dataset consist of simulated hourly power production from an Enercon E82 Turbine at 100 m hub-height. It describes the hourly power output a 1MW turbine would produce in each 0.01° grid cell for the years 2016 and 2017.

100 m wind speed data was taken from the COSMO-1 model (Consortium for Small-scale Modeling 2017), which has a 0.01° horizontal resolution. The domain covered is the whole of Switzerland, with the exclusion of lakes. As such, the number of 0.01◦ pixels within Switzerland amounts to 48657.
Conversion to power output was done based on the power curve of the Enercon E82 Turbine. As power output is lower at altitude due to lower air density, we corrected for this effect as described in (Kruyt et al. 2017).

Please cite the following paper in connection with the dataset:

Paper Citation:
 > _Bert Kruyt, Jérôme Dujardin, and Michael Lehning: Improvement of wind power assessment in complex terrain: The case of COSMO-1 in the Swiss Alps, Front. Energy Res., [doi:10.3389/fenrg.2018.00102] (https://doi.org/10.3389/fenrg.2018.00102)_

mountain-wind-potential

display_name: mountain-wind-potential

topography

display_name: topography

wind-energy

display_name: wind-energy

en: Dataset on Cosmo-1 based Energy Potential in Swiss Alps


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

en: CHELSA-BIOCLIM+

media_type: geotiff

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

format: GeoTIFF

en: CHELSA-BIOCLIM+ Technical Documentation

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

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

growing-degree-days

display_name: growing-degree-days

growing-season-length

display_name: growing-season-length

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

soil-water-balance

display_name: soil-water-balance

solar-radiation

display_name: solar-radiation

temperature

display_name: temperature

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


wind-crust-formation-snowmicropen-data

title_for_slug: wind-crust-formation-snowmicropen-data

en: wind-packing wind-crust snow snowmicropen smp

en: SMP data

media_type: Link

en: Links to the dataset

en: Processing scripts

en: Contains the R-scripts used to process the SMPs

en: README

media_type: text/plain

en: Describes the dataset in detail

mimetype: text/plain

en:
This dataset contains the SnowMicroPen (SMP) data from 38 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winters 2015/16 and 2016/17 and include more than 1000 SMP measurements.

The SMPs are organized per experiment. Each experiment subfolder contains the processed SMP profiles and some additional files.

Please refer to the README for more details on the data. The processing scripts are available for download as well. The scripts are mainly provided as documentation and would need to be adjusted to be used.

This dataset is the basis of the following publication:

Sommer C.G., Lehning M., & Fierz C. (2017). Wind tunnel experiments: Saltation is necessary for wind-packing. Journal of Glaciology, 63(242), 950-958. doi:10.1017/jog.2017.53

smp

display_name: smp

snow

display_name: snow

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Wind crust formation: SnowMicroPen data


maintainer: Jana von Freyberg

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

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

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

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

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

ecohydrology

display_name: ecohydrology

endmember-mixing-models

display_name: endmember-mixing-models

plant-water-uptake

display_name: plant-water-uptake

review

display_name: review

root-zone

display_name: root-zone

stable-water-isotopes

display_name: stable-water-isotopes

uncertainties

display_name: uncertainties

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


maintainer: Matthias Haeni

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

en: Field station data (VSF)

en: Data file.

en: Site photo of the field station (VSF)

media_type: image/jpeg

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

mimetype: image/jpeg

en: Site photo of the forest station (VSB)

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

en: Forest station data (VSB)

en: Data plot of the field station (VSF)

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

en: Data plot of the forest station (VSB)

en: Site aerial photo (Visp)

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

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

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

swiss-forest-lab

display_name: swiss-forest-lab

wind-speed

display_name: wind-speed

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


weissfluhjoch-dataset-for-esm-snowmip

maintainer: Nander Wever

title_for_slug: weissfluhjoch-dataset-for-esm-snowmip

en: esm-snowmip snow-models snow-depth snow weissfluhjoch

en: Conversion script

media_type: text/x-sh

en:
Use this script to convert WFJ_optimaldataset_v6.smet to wfj.smet, the file that is used for the ESM-SnowMIP project. It also requires the file: WFJ_AirPressure_Data.zip

Use: bash create_wfj_dataset.sh > input/wfj.smet

mimetype: text/x-sh

en: ini file

en: This ini file is required by data-converter from MeteoIO version 1887 (http://models.slf.ch/p/meteoio/)

en: Dataset Weissfluhjoch for ESM-SnowMIP

en: This Weissfluhjoch dataset is a processed version of the Weissfluhjoch dataset version 6 from https://doi.org/10.16904/6. This dataset was specially created for the ESM-SnowMIP project. Here it is documented how this dataset has been created.

esm-snowmip

display_name: esm-snowmip

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-models

display_name: snow-models

weissfluhjoch

display_name: weissfluhjoch

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Weissfluhjoch dataset for ESM-SnowMIP


weather-station-davos-wolfgang

maintainer: Jörg Wieder

title_for_slug: weather-station-davos-wolfgang

en: relative-humidity raclets weather pressure temperature

en: Weather Station Davos Wolfgang

en: The data file contains date and time (YYYY-MM-DD hh:mm:ss) in UTC, temperature (°C), relative humidity (%), pressure (hPa) at 10 m above ground and above sea level. The data was averaged over 10 minutes.

en: The dataset contains weather parameters measured at Davos Wolfgang (LON: 9.853594, LAT: 46.835577).

pressure

display_name: pressure

raclets

display_name: raclets

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

weather

display_name: weather


en: python cryowrf antarctica aws consistent

media_type: .zip

en: Scripts to preprocess (and download for some databases) atmospheric weather station data. Furthermore, a list of stations and a map can be created to have an overview.

en:
There are many sources providing atmospheric weather station data for the Antarctic continent. However, variable naming, timestamps and data types are highly variable between the different sources. The published python code intends to make processing of different AWS sources from Antarctica easier. For all datasets that are taken into account variables are renamed in a consistent way. Data from different sources can then be handled in one consistent python dictionary.

The following data sources are taken into account:

* AAD: Australian Antarctic Division (https://data.aad.gov.au/aws)
* ACECRC: Antarctic Climate and Ecosystems Cooperative Research Centre by the Australian Antarctic Division
* AMRC: Antarctic Meteorological Research Center (ftp://amrc.ssec.wisc.edu/pub/aws/q1h/)
* BAS: British Antarctic Survey (ftp://ftp.bas.ac.uk/src/ANTARCTIC_METEOROLOGICAL_DATA/AWS/; https://legacy.bas.ac.uk/met/READER/ANTARCTIC_METEOROLOGICAL_DATA/)
* CLIMANTARTIDE: Antarctic Meteo-Climatological Observatory by the italian National Programme of Antarctic Research (https://www.climantartide.it/dataaccess/index.php?lang=en)
* IMAU: Institute for Marine and Atmospheric research Utrecht (Lazzara et al., 2012), https://www.projects.science.uu.nl/iceclimate/aws/antarctica.ph
* JMA: Japan Meteorological Agency (https://www.data.jma.go.jp/antarctic/datareport/index-e.html)
* NOAA: National Oceanic and Atmospheric Administration (https://gml.noaa.gov/aftp/data/meteorology/in-situ/spo/)
* Other/AWS_PE: Princess Elisabeth (PE), KU Leuven, Prof. N. van Lipzig, personal communication
* Other/DDU_transect: Stations D-17 and D-47 (in transect between Dumont d’Urville and Dome C, Amory, 2020)
* PANGAEA: World Data Center (e.g. König-Langlo, 2012)

Important notes

* Information about data sources is available. Some downloading scripts are included in the provided code. However, users should make sure to comply with the data providers terms and conditions.
* Given changing download options of the differnent institutions the above links may not permanently work and data has to be retrieved by the user of this dataset.
* No quality control is applied in the provided preprocessing software - quality control is up to the user of the datasets. Some dataset are quality controlled by the owner.

Acknowledgements
--------------------------
We thank all the data providers for making the data publicly available or providing them upon request. Full acknowledgements can be found in Gerber et al., submitted.

References
---------------
Amory, C. (2020). “Drifting-snow statistics from multiple-year autonomous measurements in Adélie Land, East
Antarctica”. The Cryosphere, 1713–1725. doi: 10.5194/tc-14-1713-2020

Gerber, F., Sharma, V. and Lehning, M.: CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB, JGR - Atmospheres, submitted.

König-Langlo, G. (2012). “Continuous meteorological observations at Neumayer station (2011-01)”. Alfred Wegener
Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, doi: 10.1594/PANGAEA.
775173

antarctica

display_name: antarctica

aws

display_name: aws

consistent

display_name: consistent

cryowrf

display_name: cryowrf

python

display_name: python

en: Preprocessing Antarctic Weather Station (AWS) data in python


maintainer: Jonas Stillhard

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

en: Data description

en: Available online on publishers website

en: Dataset

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

carpathian-biosphere-reserve

display_name: carpathian-biosphere-reserve

dem

display_name: dem

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-structure

display_name: forest-structure

long-term-data-sets

display_name: long-term-data-sets

permanent-forest-plot-data

display_name: permanent-forest-plot-data

primeval-beech-forest

display_name: primeval-beech-forest

stand-inventory-data

display_name: stand-inventory-data

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


en: treeline-ecosystems stillberg mountain-ecology literature-review long-term-experiment

en: The Stillberg bibliography (Stillberg_bibliography_v1.zip) comprises a comprehensive list of 276 scientific publications, 91 of them published in peer-reviewed ISI journals (Stillberg_bibliography_data_v1.csv) along with the metadata file (Stillberg_bibliography_metadata_v1.csv). Currently the bibliography comprises literature about the main afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, and the G-TREE experiment, as well as further publications related to the Stillberg research site that have been published until August 2023. The bibliography can be filtered for different categories, e.g., experiment, peer-review, source repository or database, and source title.

en:
 Background information

The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Over almost fifty years, research at the Stillberg site combined long-term monitoring of the large-scale high-elevation afforestation with experimental manipulations simulating global change impacts. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone across different compartments and scales, from individual trees, non-tree vegetation and soils to whole ecosystems, in the context of global change resulting in more than 150 publications.

 Dataset generation

We compiled a comprehensive list of scientific publications covering research at the Stillberg research site by conducting searches in the literature databases Web of Science and Google Scholar, as well as in the Digital Object Repository of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL (DORA). We compiled all publications about the afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, the G-TREE experiment, as well as other studies related to the Stillberg research site.

 Data description

The Stillberg bibliography (Stillberg_bibliography_data_v1.csv) comprises a comprehensive list of 276 scientific publications, 91 of them published in peer-reviewed ISI journals. Currently the bibliography comprises literature about the main afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, and the G-TREE experiment, as well as further publications related to the Stillberg research site that have been published until August 2023. The bibliography can be filtered for different categories, e.g., experiment, peer-review, source repository or database, and source title. The bibliography is described in a metadata file (Stillberg_bibliography_metadata_v1.csv). The bibliography along with the metadata file are provided in a ZIP-folder (Stillberg_bibliography_v1.zip).

literature-review

display_name: literature-review

long-term-experiment

display_name: long-term-experiment

mountain-ecology

display_name: mountain-ecology

stillberg

display_name: stillberg

treeline-ecosystems

display_name: treeline-ecosystems

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Bibliography of the long-term treeline research site Stillberg, Switzerland


en: precipitation temperature-profiles radiation atmospheric-conditions wind

en: DATA ACCESS

media_type: smet

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

en: Overview plot

media_type: PNG

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

format: PNG

en: Site photo 3

media_type: JPEG

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

en: Site photo 1

en: STB2 CSV

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

en: README

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

en: Site photo 2

en: Latest data from Stillberg climate station

en:
 Important

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

atmospheric-conditions

display_name: atmospheric-conditions

precipitation

display_name: precipitation

radiation

display_name: radiation

temperature-profiles

display_name: temperature-profiles

wind

display_name: wind

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


maintainer: Anita C. Risch

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

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

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

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

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

Paper Citation:

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

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

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

ammonification

display_name: ammonification

climate

display_name: climate

fertilization

display_name: fertilization

global-change

display_name: global-change

grassland

display_name: grassland

herbivore

display_name: herbivore

mineralization

display_name: mineralization

nitrification

display_name: nitrification

nitrogen

display_name: nitrogen

nutrient-network

display_name: nutrient-network

soil

display_name: soil

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Anthropogenic change and soil net N mineralization


envidat-supports-open-science

maintainer: Ionut Iosifescu Enescu

title_for_slug: envidat-supports-open-science

en: research-data-management juypter-notebooks envidat wsl open-science

en: Article as PDF

en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.

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

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl

en: EnviDat Supports Open Science


label: geocat.ch permalink

fr: Grundwasserschutzareal

de: Grundwasserschutzareal

en: Grundwasserschutzareal

it: Grundwasserschutzareal

format: WMS

fr: WFS-Dienst des Kantons Schwyz

de: WFS-Dienst des Kantons Schwyz

en: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

format: WFS

fr: Grundwasserschutzareale sind Teil des planerischen Gewässerschutzes. Sie dienen der Sicherstellung des Grundwassers bezüglich einer künftigen Grundwasserbewirtschaftung (Anreicherung oder Nutzung).

spatial: Kanton Schwyz (SZ)

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.

political_level: canton

value: SZ-Kt Geoinformation - Geocat Harvester

fr: Grundwasserschutzareale

de: Grundwasserschutzareale

en: Grundwasserschutzareale

it: Grundwasserschutzareale


fernwarme-jahrlich-abonnierte-leistung

maintainer: Open Data Zürich

title_for_slug: fernwarme-jahrlich-abonnierte-leistung

de: Summe der gemäss den Wärmelieferungsverträgen abonnierten Leistung in MW pro Jahr

fernwarme-leistung

display_name: fernwarme-leistung

energy

fr: Energie

de: Energie

en: Energy

it: Energia

name: Fernwärme, Entsorgung + Recycling Zürich, Tiefbau- und Entsorgungsdepartement

stadt-zurich

fr: Ville de Zurich

de: Stadt Zürich

en: City of Zurich

it: Cità di Zurigo

fr: Vous trouverez ici les données de la ville de Zürich. En parallèle, Open Data Zürich a son propre portail Open Data où vous pouvez trouver également des manuels et des documents sur le traitement des données. À de rares exceptions près, toutes les données publiées par Open Data Zürich sont sous une licence «Creative Commons Zero».

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

en: Here you find all publicly available data published by Open Data Zürich. In addition, the city of Zurich runs its own Open Data Portal, where you find manuals and documentation about the handling of datasets. With only a few exceptions, all datasets from Open Data Zürich are licensed under «Creative Commons Zero».

it:
Open Data Zürich propone qui dati pubblici della città di Zurigo, pronti alla libera utilizzazione.
La città di Zurigo dispone parallelamente di un proprio portale Open Data, sul quale sono disponibili anche istruzioni e documentazioni per contestualizzare i datasets.
A parte poche eccezioni tutte le datasets della città di Zurigo hanno una licenza «Creative Commons Zero».

political_level: commune

value: ZH - DCAT Harvester

de: Fernwärme: Jährlich abonnierte Leistung


en: energy irradiance mountain reflection photovoltaic albedo snow

en: PV Data

media_type: application/zip

en: Windows users use the 7-zip app to extract the zip-file.

en:
 Overview
The SUNWELL Modelling Environment is a combination of data and code that models electricity production from satellite-derived irradiance data and other spatial data sets for all of Switzerland. This ensemble accompanies the publication "The bright side of PV production in snow-covered mountains", published in the Proceedings of the National Academy of Science and reproduces all results and figures of. Code and resources are in their original form (with documentation). A new version with a more generalized application to PV modelling and with more flexibility in terms of input and output formats will be released in the coming months.

 Format
All code is written and has to be executed in Matlab. The input and output data sets are also in the Matlab-specific .mat format. Whenever publicly available, the original data is provided as geotif, .xlsx or other common format.
This is the case for:

- Digital Elevation Model (InputsFromMatlab/MSG/OriginalData/ASTERDEM),
- Landsurface cover type (InputsFromMatlab/MSG/OriginalData/CORINE),
- Population Density (InputsFromMatlab/MSG/OriginalData/popdensRaster,
- Electricity production from three of our validation sites (/Validation/WSL),
- Measured irradiance for two validation sites (/Validation/ASRB)
The ‘Metadata’ documents in the respective folders provide further information about the data sources and processing. Figures are produced either in .pdf or .png format.

 Structure
The central level of the SUNWELL environment holds the 5 Mains, which run the different modelling aspects of the paper; each code is documented separately. Additional code is located in the ‘DataProcessing’ and the ‘functions’ folder. Functions are called in the different Mains.

‘InputsFromMatlab’ contains the radiation and albedo input data sets in separate subfolders (SIS/SISDIR/ALB). The original data is not publicly available, but can be requested for research purposes free of charge. We provide a processed subset of the data set that was used to run the SUNWELL simulations. The MSG subfolder contains additional spatial input data sets.

‘Outputs’ contains the output files from the different mains (matching names, Main_CHallpixels.m  Prod_CHallpixels)

‘Publication_figures’ contains all individual figures from the PNAS publication, as well as the generating code (/code_plot) and the power point figures (/ppts) that provide the combined final figures.

‘Validation’ contains the data sets used in the model validation:

- Electricity production from three of our validation sites (/WSL),
- Measured irradiance for two validation sites (/ASRB)

Electricity production from a validation site at Lac des Toules in Wallis (/LDT), this data set was provided under an NDA and cannot be made publicly available.

Paper Citation:
 > _Annelen Kahl; Jérôme Dujardin; Michael Lehning (2018). Dataset on PV Production in Snow Covered Mountains. PNAS - Proceedings of the National Academy of Sciences. (in press)_

albedo

display_name: albedo

energy

display_name: energy

irradiance

display_name: irradiance

mountain

display_name: mountain

photovoltaic

display_name: photovoltaic

reflection

display_name: reflection

snow

display_name: snow

envidat

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


de: Entlastung von CO2-Äquivalente durch den Einsatz von Fernwärme anstelle von Öl in Tonnen

fernwarme

display_name: fernwarme

de: Fernwärme: CO2-Entlastung


maintainer: Loïc Pellissier Pellissier

en: alps elevation community-indices environmental-gradients plant-herbivore-interactions herbivores-communities functional-traits

en: Nematode surveys

en: Surveys of soil nematode along elevation

en: Orthoptera surveys

en: Species inventories of Orthoptera

en: Vegetion surveys

en: Species inventories of plants

en: Study sites

en: Coordinates and elevation of the study sites

en: Plant traits

en: Plant functional traits (SLA, LDMC, carbon and nitrogen content, punch strenght; averaged by species)

en: Orthoptera traits

en: Orthoptera functional traits (incisive mandibular strength averaged by species)

en: Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017.

alps

display_name: alps

community-indices

display_name: community-indices

elevation

display_name: elevation

environmental-gradients

display_name: environmental-gradients

functional-traits

display_name: functional-traits

herbivores-communities

display_name: herbivores-communities

plant-herbivore-interactions

display_name: plant-herbivore-interactions

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Above- and below-ground herbivore communities along elevation


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

en: Field station data (NOF)

en: Data file.

en: Data plot of the forest station (NOB)

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

en: Site aerial photo (Novaggio)

en: Site aerial photo from both Novaggio stations. Source: Google. 2016. Site aerial photo from both Novaggio stations. Retrieved November 15, 2016, from https://www.google.ch/maps

en: Site photo of the field station (NOF)

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

en: Site photo of the forest station (NOB)

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

en: Data plot of the field station (NOF)

en: Forest station data (NOB)

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 Novaggio in Switzerland where one station is located within a natural deciduous forest stand (NOB) with Turkey oak (_Quercus cerris_; 70 yrs), sweet chestnut (_Castanea sativa_; 90 yrs) and silver birch (_Betula pendula_; 70 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NOF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Novaggio is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


fr: Annuaire statistique de la Suisse 1892

media_type: text/html

mimetype: text/html

de: Statistisches Jahrbuch der Schweiz 1892

basas-statisticas-e-survistas

display_name: basas-statisticas-e-survistas

bases-statistiques-et-generalites

display_name: bases-statistiques-et-generalites

grundlagen-und-ubersichten

display_name: grundlagen-und-ubersichten

statistical-basis-and-overviews

display_name: statistical-basis-and-overviews

spatial: Schweiz

statistical-basis

fr: Bases statistiques

de: Statistische Grundlagen

en: Statistical basis

it: Basi statistiche

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS

de: Bundesamt für Statistik BFS

en: Federal Statistical Office FSO

it: Ufficio federale di statistica UST

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.

en: The FSO is Switzerland's national competence centre for official statistics. It produces and publishes statistical information on the status and development of the population, economy, society, education, research, territory and the environment. This information is used for opinion building among the population and for the planning and management of key policy areas. They make an important contribution to a modern, democratic state.

it: L’UST è il centro di competenza nazionale per la statistica pubblica della Svizzera. Produce e pubblica informazioni statistiche sullo stato e sull'evoluzione della popolazione, dell'economia, della società, della formazione, della ricerca, del territorio e dell'ambiente. Queste informazioni servono alla formazione dell'opinione pubblica nonché alla pianificazione e alla gestione in ambiti politici di centrale importanza. Forniscono un importante contributo per uno Stato moderno e democratico.

political_level: confederation

value: BFS – DCAT Harvester


geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

de: fahrrad verkehrsnetz mobilitat langsamverkehr bgdi-bundesgeodaten-infrastruktur ressourcen-ressourcennutzung soziale-aspekte-bevolkerung verkehr energie tourismus-und-freizeit handel-dienstleistungen allgemeine-angelegenheiten geographie

de: GBFS 2.0

media_type: JSON

format: JSON

de: REST API

format: API

de: GBFS 2.3

fr: Map (Preview)

de: Map (Preview)

en: Map (Preview)

it: Map (Preview)

de: Fachportal - map.geo.admin.ch

fr: La mobilité partagée désigne l'utilisation commune et partagée de moyens de transport tels que la voiture, le taxi, le vélo, le vélo électrique, le cargobike, le scooter/la trottinette électrique, etc. Ces moyens de déplacement ne sont plus considérés comme des biens individuels mais comme des biens communs, accessibles en cas de besoin. La mobilité se conçoit dès lors en tant que service (Mobility as a Service [MaaS]). La mobilité partagée permet de se déplacer de façon adaptée aux besoins, et ce de manière économique, efficace en énergie et économe en ressources. En Suisse, divers prestataires proposent une offre complète de mobilité partagée. Vous pouvez réserver ou utiliser un véhicule rapidement et en toute simplicité grâce aux applications ou aux plateformes de réservation des prestataires. En alliant différents moyens de transport, on obtient des solutions pour l'ensemble de la chaîne de mobilité, ce qui contribue à la numérisation et à la durabilité de la mobilité. Ce jeu de données présente la géolocalisation et la disponibilité en temps réel d'offres de mobilité partagée. Pour de plus amples informations concernant le téléchargement des données et les prestataires partenaires de mobilité partagée, veuillez vous rendre sur: www.sharedmobility.ch/info

de: Unter Shared Mobility versteht man die gemeinsame, geteilte Nutzung von Verkehrsmitteln wie Autos, Taxis, Velos, E-Bikes, Cargobikes, Scooter/E-Trottis etc. Diese werden dabei nicht mehr als individuelle sondern als gemeinschaftliche Besitzgüter verstanden, auf welche je nach Bedarf zugegriffen werden kann. So wird Mobilität zur Dienstleistung (Mobility as a Service, MaaS). Shared Mobility ermöglicht eine bedarfsgerechte, kostengünstige sowie ressourcenschonende und energieeffizente Fortbewegung. In der Schweiz stellen diverse Anbietende umfangreiche Shared Mobility Angebote bereit. Über Apps oder Buchungsplattformen der Anbietenden kann ein Fahrzeug schnell und einfach gebucht und verwendet werden. Durch die geschickte Kombination von verschiedenen Verkehrsmitteln entstehen Lösungen für die gesamte Mobilitätskette, wodurch eine digitalisierte und nachhaltige Mobilität entsteht. Dieser Datensatz zeigt die Standorte und Verfügbarkeit von Shared Mobility-Angeboten in Echtzeit. Weitere Informationen zum Download der Daten sowie den angeschlossenen Shared Mobility-Anbietenden findet man unter: www.sharedmobility.ch/info

en: Shared mobility is the shared use of means of transport such as cars, taxis, bikes, scooters, etc. These are then no longer considered private property, but shared property that can be accessed as required. Mobility is thus seen as a service (Mobility as a Service, MaaS). Shared Mobility is a needs-based, economical and energy-saving means of transport. Shared mobility services run by various providers are already widespread in Switzerland. Customers can quickly and easily book a vehicle via an app or booking platform. By cleverly combining different means of transport, door-to-door solutions can be found. Mobility becomes digitalised and sustainable. This dataset shows the location and availability of shared mobility services in real time. Further information on downloading the data and about affiliated shared mobility providers can be found at: www.sharedmobility.ch/info

it: Con il termine shared mobility si intende l'utilizzo comune e condiviso di mezzi di trasporto quali automobili, taxi, biciclette, biciclette elettriche, biciclette da carico, scooter, monopattini elettrici ecc. Tali mezzi non sono più intesi come proprietà individuale, ma come proprietà collettiva alla quale si può accedere in base alle necessità. In questo modo la mobilità diventa un servizio (Mobility-as-a-Service, MaaS). La shared mobility consente di spostarsi in maniera orientata alle necessità, economica nonché efficiente in materia di utilizzo di risorse e di energia. In Svizzera esistono diversi fornitori che mettono a disposizione ampie offerte di shared mobility. Grazie all'utilizzo di app e di piattaforme per la prenotazione è possibile prenotare in modo semplice e veloce un veicolo e averlo a propria disposizione in tempi brevi. Il sistema invia all'utente una combinazione di mezzi di trasporto diversi creando soluzioni che attingono all'intera catena della mobilità, garantendo una mobilità digitalizzata e sostenibile. Questa base dati mostra in tempo reale i luoghi e la disponibilità delle offerte di shared mobility. Ulteriori informazioni riguardo al download di dati e ai fornitori della shared mobility sono disponibili sul sito: www.sharedmobility.ch/info

name: Shared Mobility Anbieter und Bundesamt für Energie

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).

value: BFE - Geocat Harvester

fr: Géolocalisation et disponibilité en temps réel d'offres de mobilité partagée

de: Standorte und Verfügbarkeit von Shared Mobility Angeboten

en: Locations and availability of shared mobility services in real time

it: Dove trovare offerte disponibili di shared mobility in tempo reale


verwaltungsgrenzen-der-schweiz-inspire

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

title_for_slug: verwaltungsgrenzen-der-schweiz-inspire

fr: geodonnees-de-base inspire unites-administratives nationales limite-administrative

de: geobasisdaten inspire verwaltungseinheiten national verwaltungsgrenze

en: official-geodata inspire administrative-units national administrative-boundary

it: geodati-di-base inspire unita-amministrative nazionali confine-amministrativo

en: Administrative units Switzerland - INSPIRE - reference system CH1903+ / LV95

en: Administrative units Switzerland - INSPIRE - reference system ETRS89 / UTM zone 32N

en: Administrative units Switzerland - INSPIRE - reference system ETRS89 / ETRS-LAEA

en: Administrative units Switzerland - INSPIRE - reference system WGS84 Web Mercator

en: Administrative units Switzerland - INSPIRE - reference system WGS 84

fr: "Limites administratives" est une sous-couche des unités administratives et est basée sur le jeu de données swissBOUNDARIES3D de swisstopo. Ce jeu de données contient toutes les unités administratives et les frontières nationales de la Suisse et de la Principauté du Liechtenstein sous forme vectorielle. Le produit est basé sur un modèle de données optimisé pour la Suisse et est conforme aux données de l'Office fédéral de la statistique. swissBOUNDARIES3D remplace le jeu de données GG25 à partir de 2010.

de: Verwaltungsgrenzen ist ein Sub Layer von Verwaltungseinheiten und basiert auf dem Datensatz swissBOUNDARIES3D von swisstopo. Dieser Datensatz enthält alle Verwaltungseinheiten und Landesgrenzen der Schweiz und des Fürstentums Liechtenstein in Vektorform. Das Produkt basiert auf einem optimierten Datenmodell für die Schweiz und ist konform mit den Daten des Bundesamtes für Statistik. swissBOUNDARIES3D ersetzt ab 2010 den Datensatz GG25.

en: Administrative boundary is a sub layer of Administrative units and is based on the data set swissBOUNDARIES3D by swisstopo. It contains all administrative units and national boundaries of Switzerland and the Principality of Liechtenstein in vector form. The product is based on an optimized data model for Switzerland and conforms to the data of the Swiss Federal Statistical Office. swissBOUNDARIES3D replaces the GG25 dataset from 2010 onwards.

spatial: Switzerland

fr: Office fédéral de topographie swisstopo

de: Bundesamt für Landestopografie swisstopo

en: Federal Office of Topography swisstopo

it: Ufficio federale di topografia swisstopo

fr: Le centre de compétence de la Confédération suisse pour les informations géographiques, c'est-à-dire pour la description, la représentation et l’archivage de données à référence spatiale.

de: Das Kompetenzzentrum der Schweizerischen Eidgenossenschaft für Geoinformation, d.h. für die Beschreibung, Darstellung und Archivierung von raumbezogenen Geodaten.

en: The centre of competence for the Swiss Confederation responsible for geographical reference data, for instance the description, representation and archiving of geographic spatial data.

it: Il centro d’eccellenza della Confederazione Elvetica per geoinformazione, cioè per la descrizione, rappresentazione e archiviazione dei dati georeferenziati (geodati).

value: Swisstopo - Geocat Harvester

fr: Limites administratives de la Suisse – INSPIRE

de: Verwaltungsgrenzen der Schweiz – INSPIRE

en: Administrative boundary Switzerland - INSPIRE


de: Statistisches Jahrbuch der Schweiz 1912

fr: Annuaire statistique de la Suisse 1912

statistical-basis

de: Statistische Grundlagen

en: Statistical basis

bundesamt-fur-statistik-bfs

de: Bundesamt für Statistik BFS

en: Federal Statistical Office FSO

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.

en: The FSO is Switzerland's national competence centre for official statistics. It produces and publishes statistical information on the status and development of the population, economy, society, education, research, territory and the environment. This information is used for opinion building among the population and for the planning and management of key policy areas. They make an important contribution to a modern, democratic state.


fr: Annuaire statistique de la Suisse 1914

de: Statistisches Jahrbuch der Schweiz 1914

statistical-basis

fr: Bases statistiques


fr: Annuaire statistique de la Suisse 1910

de: Statistisches Jahrbuch der Schweiz 1910

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.


fr: Annuaire statistique de la Suisse 1906

de: Statistisches Jahrbuch der Schweiz 1906


culture

fr: Culture, médias, société de l'information, sport

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

it: Cultura, media, società dell'informazione, sport

energy

fr: Energie

de: Energie

en: Energy

it: Energia

geography

fr: Géographie

de: Geographie

en: Geography

protocol: WWW:DOWNLOAD:Geopackage (ogc)

de: Geopackage

media_type: Geopackage (ogc)

format: GPKG

de: Interlis

media_type: INTERLIS

format: INTERLIS

de: WFS

de: WMS

protocol: WWW:DOWNLOAD:ESRI Shapefile

de: Shapefile

media_type: ESRI Shapefile

format: SHP

fr: Service WMS-IFDG, couche "Installations électriques"

de: WMS-BGDI Dienst, Layer "Elektrische Anlagen"

en: WMS-FSDI service, layer "Electrical installations"

it: Servizio WMS-IFDG, strato "Impianti elettrici"

fr: Map (Preview) Géoportail thématique - map.energie.admin.ch

de: Map (Preview) Fachportal - map.energie.admin.ch

en: Map (Preview) Thematic geoportal - map.energie.admin.ch

it: Map (Preview) Geoportale tematico - map.energie.admin.ch

de: Fachportal - map.energie.admin.ch

de: swisstopo REST API

fr: Le réseau électrique établit la liaison entre producteurs et consommateurs d’énergie électrique. Il permet de transporter l’électricité, de la transformer (augmenter ou diminuer la tension) et de la distribuer. Le maillon que le réseau électrique constitue entre la production et la consommation est d’une importance majeure pour garantir la sécurité de l’approvisionnement en électricité. On entend par «installation électrique» tous les composants d’un réseau d’électricité servant à transporter le courant électrique, par exemple les lignes, les sous-stations et les stations de transformation. Le jeu de géodonnées de base «Installations électriques d’une tension nominale supérieure à 36 kV» comprend une vue d’ensemble géographique des installations électriques du réseau suisse à haute et à très haute tension. Certaines exploitants n'ont pas encore fourni de données, c'est pourquoi l'aperçu n'est pas encore complet.

de: Das Stromnetz ist die Verbindung zwischen Produzenten und Verbrauchern von elektrischer Energie. Via Netz wird der Strom transportiert, transformiert (von höherer zu tieferer Spannung und umgekehrt) und verteilt. Als Bindeglied zwischen Produktion und Verbrauch ist das Stromnetz von zentraler Bedeutung für die Gewährleistung der Stromversorgungssicherheit. Unter elektrischen Anlagen versteht man alle Komponenten eines Elektrizitätsnetzes, die der Übertragung von elektrischem Strom dienen wie beispielsweise Leitungen, Unterwerke und Transformatorenstationen. Der Geobasisdatensatz «Elektrische Anlagen mit einer Nennspannung von über 36 kV» beinhaltet eine geografische Gesamtsicht der elektrischen Anlagen des Höchst- und Hochspannungsnetzes der Schweiz. Nicht alle Werke haben bereits Daten geliefert, daher ist die Übersicht noch nicht vollständig.

en: The electricity grid is the point of connection between producers and consumers of electrical energy. Via the grid, electricity is transported, transformed (from a higher to lower voltage and vice versa) and distributed. As the link between production and consumption, the electricity grid is a key element in ensuring the security of electricity supply. The term electrical installations refers to all components of an electricity network that serve to transmit electrical current, such as lines, substations and transformer stations. The geodatabase dataset 'Electrical installations with a nominal voltage exceeding 36kV' contains a geographical overview of the electrical installations of the extra-high and high-voltage grid in Switzerland. Some plant operators have not yet provided data, so the overview is not yet complete.

it: La rete elettrica è il risultato del collegamento tra produttori e consumatori di energia elettrica. La rete permette di trasportare, trasformare (da una tensione più alta a una tensione più bassa e viceversa) e distribuire l'energia elettrica. In quanto anello di congiunzione tra produzione e consumo, la rete elettrica è di fondamentale importanza per la sicurezza dell'approvvigionamento elettrico. Sono impianti elettrici tutti i componenti di una rete elettrica necessari ai fini del trasporto di energia elettrica, come ad esempio linee, sottostazioni e stazioni di trasformazione. Il set di geodati di base «Impianti elettrici con una tensione nominale superiore a 36 kV» contiene un quadro geografico generale degli impianti elettrici delle reti ad altissima e ad alta tensione della Svizzera. Alcuni exercente non hanno ancora fornito i dati, quindi la panoramica non è ancora completa.

name: Werksbetreiber und Bundesamt für Energie

bundesamt-fur-energie-bfe

en: Swiss Federal Office of Energy SFOE


de: Statistisches Jahrbuch der Schweiz 1915

fr: Annuaire statistique de la Suisse 1915

media_type: application/pdf

statistical-basis

de: Statistische Grundlagen

it: Basi statistiche

bundesamt-fur-statistik-bfs

de: Bundesamt für Statistik BFS

it: Ufficio federale di statistica UST

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.

it: L’UST è il centro di competenza nazionale per la statistica pubblica della Svizzera. Produce e pubblica informazioni statistiche sullo stato e sull'evoluzione della popolazione, dell'economia, della società, della formazione, della ricerca, del territorio e dell'ambiente. Queste informazioni servono alla formazione dell'opinione pubblica nonché alla pianificazione e alla gestione in ambiti politici di centrale importanza. Forniscono un importante contributo per uno Stato moderno e democratico.


fr: Annuaire statistique de la Suisse 1907

de: Statistisches Jahrbuch der Schweiz 1907


fr: Annuaire statistique de la Suisse 1902

de: Statistisches Jahrbuch der Schweiz 1902


fr: Annuaire statistique de la Suisse 1903

de: Statistisches Jahrbuch der Schweiz 1903


fr: Annuaire statistique de la Suisse 1916

de: Statistisches Jahrbuch der Schweiz 1916


de: Statistisches Jahrbuch der Schweiz 1904

fr: Annuaire statistique de la Suisse 1904


de: Statistisches Jahrbuch der Schweiz 1900

fr: Annuaire statistique de la Suisse 1900

statistical-basis

fr: Bases statistiques


de: Statistisches Jahrbuch der Schweiz 1911

fr: Annuaire statistique de la Suisse 1911

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


fr: Annuaire statistique de la Suisse 1896

de: Statistisches Jahrbuch der Schweiz 1896

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.


de: Statistisches Jahrbuch der Schweiz 1894

fr: Annuaire statistique de la Suisse 1894


fr: Annuaire statistique de la Suisse 1908

de: Statistisches Jahrbuch der Schweiz 1908


de: Statistisches Jahrbuch der Schweiz 1901

fr: Annuaire statistique de la Suisse 1901


de: Statistisches Jahrbuch der Schweiz 1899

fr: Annuaire statistique de la Suisse 1899


fr: Annuaire statistique de la Suisse 1905

de: Statistisches Jahrbuch der Schweiz 1905


fr: Annuaire statistique de la Suisse 1893

de: Statistisches Jahrbuch der Schweiz 1893


de: Statistisches Jahrbuch der Schweiz 1909

fr: Annuaire statistique de la Suisse 1909

statistical-basis

de: Statistische Grundlagen


de: Statistisches Jahrbuch der Schweiz 1898

fr: Annuaire statistique de la Suisse 1898

bundesamt-fur-statistik-bfs

de: Bundesamt für Statistik BFS

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.


de: Alphabetisches Inhaltsverzeichnis der Jahrgänge I-X (1891-1901) des Statistischen Jahrbuches der Schweiz und des graphisch-statistischen Atlasses vom Jahre 1897

fr: Index alphabétique de l'Annuaire statistique de la Suisse, tomes I à X (1891 à 1901) et de l'Atlas graphique et statistique, année 1897


fr: Annuaire statistique de la Suisse 1940

de: Statistisches Jahrbuch der Schweiz 1940


fr: Annuaire statistique de la Suisse 1942

de: Statistisches Jahrbuch der Schweiz 1942


fr: Annuaire statistique de la Suisse 1957

de: Statistisches Jahrbuch der Schweiz 1957


fr: Annuaire statistique de la Suisse 1949

de: Statistisches Jahrbuch der Schweiz 1949

statistical-basis

fr: Bases statistiques


fr: Annuaire statistique de la Suisse 1917

de: Statistisches Jahrbuch der Schweiz 1917

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


fr: Annuaire statistique de la Suisse 1941

de: Statistisches Jahrbuch der Schweiz 1941

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.


fr: Annuaire statistique de la Suisse 1944

de: Statistisches Jahrbuch der Schweiz 1944


fr: Annuaire statistique de la Suisse 1943

de: Statistisches Jahrbuch der Schweiz 1943


fr: Annuaire statistique de la Suisse 1950

de: Statistisches Jahrbuch der Schweiz 1950


fr: Annuaire statistique de la Suisse 1922

de: Statistisches Jahrbuch der Schweiz 1922


fr: Annuaire statistique de la Suisse 1935

de: Statistisches Jahrbuch der Schweiz 1935


de: Statistisches Jahrbuch der Schweiz 1928

fr: Annuaire statistique de la Suisse 1928


de: Statistisches Jahrbuch der Schweiz 1923

fr: Annuaire statistique de la Suisse 1923

statistical-basis

de: Statistische Grundlagen


fr: Annuaire statistique de la Suisse 1953

de: Statistisches Jahrbuch der Schweiz 1953

bundesamt-fur-statistik-bfs

de: Bundesamt für Statistik BFS


fr: Annuaire statistique de la Suisse 1936

de: Statistisches Jahrbuch der Schweiz 1936

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.


de: Statistisches Jahrbuch der Schweiz 1926

fr: Annuaire statistique de la Suisse 1926


de: Statistisches Jahrbuch der Schweiz 1920

fr: Annuaire statistique de la Suisse 1920


fr: Annuaire statistique de la Suisse 1961

de: Statistisches Jahrbuch der Schweiz 1961


fr: Annuaire statistique de la Suisse 1945

de: Statistisches Jahrbuch der Schweiz 1945

statistical-basis

fr: Bases statistiques


de: Statistisches Jahrbuch der Schweiz 1948

fr: Annuaire statistique de la Suisse 1948

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


de: Statistisches Jahrbuch der Schweiz 1925

fr: Annuaire statistique de la Suisse 1925

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.


de: Statistisches Jahrbuch der Schweiz 1963

fr: Annuaire statistique de la Suisse 1963


fr: Annuaire statistique de la Suisse 1927

de: Statistisches Jahrbuch der Schweiz 1927


fr: Annuaire statistique de la Suisse 1952

de: Statistisches Jahrbuch der Schweiz 1952


fr: Annuaire statistique de la Suisse 1954

de: Statistisches Jahrbuch der Schweiz 1954


de: Statistisches Jahrbuch der Schweiz 1937

fr: Annuaire statistique de la Suisse 1937


fr: Annuaire statistique de la Suisse 1929

de: Statistisches Jahrbuch der Schweiz 1929


fr: Annuaire statistique de la Suisse 1931

de: Statistisches Jahrbuch der Schweiz 1931

statistical-basis

de: Statistische Grundlagen


fr: Annuaire statistique de la Suisse 1934

de: Statistisches Jahrbuch der Schweiz 1934

bundesamt-fur-statistik-bfs

de: Bundesamt für Statistik BFS


de: Statistisches Jahrbuch der Schweiz 1921

fr: Annuaire statistique de la Suisse 1921

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.


fr: Annuaire statistique de la Suisse 1932

de: Statistisches Jahrbuch der Schweiz 1932


de: Statistisches Jahrbuch der Schweiz 1956

fr: Annuaire statistique de la Suisse 1956


fr: Annuaire statistique de la Suisse 1959-60

de: Statistisches Jahrbuch der Schweiz 1959-60


de: Statistisches Jahrbuch der Schweiz 1967

fr: Annuaire statistique de la Suisse 1967

statistical-basis

fr: Bases statistiques


fr: Annuaire statistique de la Suisse 1951

de: Statistisches Jahrbuch der Schweiz 1951

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


fr: Annuaire statistique de la Suisse 1924

de: Statistisches Jahrbuch der Schweiz 1924

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.


de: Statistisches Jahrbuch der Schweiz 1939

fr: Annuaire statistique de la Suisse 1939


fr: Annuaire statistique de la Suisse 1966

de: Statistisches Jahrbuch der Schweiz 1966


fr: Annuaire statistique de la Suisse 1965

de: Statistisches Jahrbuch der Schweiz 1965


fr: Annuaire statistique de la Suisse 1962

de: Statistisches Jahrbuch der Schweiz 1962


fr: Annuaire statistique de la Suisse 1947

de: Statistisches Jahrbuch der Schweiz 1947


de: Statistisches Jahrbuch der Schweiz 1918

fr: Annuaire statistique de la Suisse 1918


de: Statistisches Jahrbuch der Schweiz 1919

fr: Annuaire statistique de la Suisse 1919

statistical-basis

de: Statistische Grundlagen


de: Statistisches Jahrbuch der Schweiz 1930

fr: Annuaire statistique de la Suisse 1930

bundesamt-fur-statistik-bfs

de: Bundesamt für Statistik BFS


fr: Annuaire statistique de la Suisse 1955

de: Statistisches Jahrbuch der Schweiz 1955

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.


fr: Annuaire statistique de la Suisse 1946

de: Statistisches Jahrbuch der Schweiz 1946


de: Statistisches Jahrbuch der Schweiz 1964

fr: Annuaire statistique de la Suisse 1964


de: Statistisches Jahrbuch der Schweiz 1977

fr: Annuaire statistique de la Suisse 1977


de: Statistisches Jahrbuch der Schweiz 2004

de: Diese elektronische Datei enthält nur die Texte des Jahrbuchs.

fr: Annuaire statistique de la Suisse 2004

fr: Ce fichier électronique ne comprend que les textes de l‘Annuaire.

statistical-basis

fr: Bases statistiques


fr: Annuaire statistique de la Suisse 1968

de: Statistisches Jahrbuch der Schweiz 1968

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


de: Bewohnte Wohnungen nach Kanton, Anzahl Zimmer, Bauperiode, 1970, 1980, 1990, 2000

de: Dieses Dataset präsentiert die Anzahl der bewohnten Wohnungen nach Kanton, Anzahl Zimmer und Bauperiode, 1970, 1980, 1990 und 2000.

fr: Logements occupés selon les cantons, le nombre de pièces, l'époque de construction, 1970, 1980, 1990, 2000

de: JSON-Struktur

fr: Ce dataset présente le nombre de logements occupés selon le canton, le nombre de pièces et l'époque de construction, en 1970, 1980,1990 et 2000.

fr: Structure JSON

bau--und-wohnungswesen

display_name: bau--und-wohnungswesen

construction-and-housing

display_name: construction-and-housing

construction-et-logement

display_name: construction-et-logement

construcziuns-ed-abitaziuns

display_name: construcziuns-ed-abitaziuns

costruzioni-e-abitazioni

display_name: costruzioni-e-abitazioni

construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.


fr: Annuaire statistique de la Suisse 1971

de: Statistisches Jahrbuch der Schweiz 1971


de: Bewohnte Wohnungen nach Gemeinde, Anzahl Zimmer und Mietklassen, 1970, 1980, 1990, 2000

fr: Logements occupés selon les communes, le nombre de pièces et le loyer (classes),  1970, 1980, 1990, 2000

fr: Ce dataset présente le nombre de logements occupés selon la commune, le nombre de pièces et le loyer mensuel net, en 1970, 1980, 1990 et 2000.

de: Dieses Dataset präsentiert die Anzahl der bewohnten Wohnungen nach Gemeinde, Anzahl Zimmer und Mietpreisklasse, 1970, 1980, 1990 und 2000.

spatial: Gemeinden


fr: Annuaire statistique de la Suisse 1970

de: Statistisches Jahrbuch der Schweiz 1970

statistical-basis

de: Statistische Grundlagen


fr: Annuaire statistique de la Suisse 1974

de: Statistisches Jahrbuch der Schweiz 1974

bundesamt-fur-statistik-bfs

de: Bundesamt für Statistik BFS


fr: Annuaire statistique de la Suisse 1976

de: Statistisches Jahrbuch der Schweiz 1976

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.


de: Statistisches Jahrbuch der Schweiz 1995

fr: Annuaire statistique de la Suisse 1995


de: Statistisches Jahrbuch der Schweiz 1996

fr: Annuaire statistique de la Suisse 1996


fr: Annuaire statistique de la Suisse 1997

de: Statistisches Jahrbuch der Schweiz 1997


fr: Annuaire statistique de la Suisse 1986

de: Statistisches Jahrbuch der Schweiz 1986

statistical-basis

fr: Bases statistiques


fr: Annuaire statistique de la Suisse 1994

de: Statistisches Jahrbuch der Schweiz 1994

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


fr: Annuaire statistique de la Suisse 2003

fr: Ce fichier électronique ne comprend que les textes de l"Annuaire - les tableaux se trouvent dans la version imprimée du livre.

de: Statistisches Jahrbuch der Schweiz 2003

de: Diese elektronische Datei enthält nur die Texte des Jahrbuchs - die Tabellen finden Sie im gedruckten Buch.