maintainer: Giulia Mazzotti

en: snow-energy-balance forest-snow forest-structure snow-distribution snow-modelling

en: Canopy data

en: Includes all canopy structure metrics computed at all surveyed locations

en: Snow depth data forest sites

en: Contains all snow depth data acquired at all forest sites during winters 2012/13, 2013714 and 2014/15.

en: Meteo data to drive FSM2 model

en: Includes meteorological driving data used to run the forest snow model FSM2, processed and parsed in text files that match the format required by FSM2. Separate files are available for each field area (Laret, Drusatscha and Ischlag) and season (2012/13, 2013/14, 2014/15). Each file includes data for the period from October 1st to May 31st at hourly resolution.

en: Coordinates data

en: Includes coordinate information of each surveyed point (7 x 276 = 1932 forest points, 2 open areas)

en: Snow depth data open sites

en: Contains all snow detph data accquired at open sites nearby the forest stands during the same period.

en: Grid point nomenclature

en: The grid structure of each forest site and the respective nomenclature applied to label individual points within each grid are outlined here.  Each point marks the location of snow depth measurements and co-located canopy structure parameters.

en:
This dataset contains all snow, canopy and meteorological data presented and used in the publication: Mazzotti, G., Essery, R., Moeser, D. & Jonas T. (2020) 'Resolving spatial variability of forest snow using an energy-balance model with a 1-layer canopy'. Water Resources Research, https://doi.org/10.1029/2019WR026129.
This publication must be cited when using this dataset.

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

snow-distribution

display_name: snow-distribution

snow-energy-balance

display_name: snow-energy-balance

snow-modelling

display_name: snow-modelling

en: Snow depth, canopy structure and meterorological datasets from the Davos area, Switzerland, Winters 2012/13-2014/15, used for high-resolution forest snow modelling


high-resolution-climate-data-for-europe

maintainer: EnviDat Support

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

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

state: active

type: dataset

en: Data Access

format: SERVICE

en: CHELSA_EUR11 technical documentation

media_type: application/pdf

en: Technical documentation of the data with variable names and methodology.

format: PDF

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

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

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: High resolution climate data for Europe


maintainer: Matthias Haeni

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

en: Data plot of the forest station (VSB)

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

mimetype: application/pdf

en: Site photo of the forest station (VSB)

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

mimetype: image/jpeg

en: Forest station data (VSB)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Field station data (VSF)

en: Data plot of the field station (VSF)

en: Site aerial photo (Visp)

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

en: Site photo of the field station (VSF)

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

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

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


en: anthophila urban-ecosystems sads wildbees cities urban-beekeeping dominance honeybees

en: Dataset proportion honeybees and wild bees

en:
The dataset provide the main features for each included dataset from published and unpublished research works. Each row represents a dataset, which provides bee community data in one city / urban aggregation. Overall, it contains 68 datasets from 46 cities in 15 countries and five continents. The data is organised in the following columns:
- Article_ID: id used in the study
- DOI: doi of the publication, when available
- Authors
- Year: of publication
- Duration sampling (years)
- Start_sampling: month of the year
- End_sampling: month of the year
- Continent
- Country
- N. cities: number of cities included in the publication
- City
- Sampling type: active, passive or both
- Sampling methodology: within each sampling type.
- Habitats: list of sampling habitats
- N_habitats: number of sampling habitats
- Parks_similar: binnary (1 = yes; 0 = no)
- Agriculture: binnary (1 = yes; 0 = no)
- Private_gardens: binnary (1 = yes; 0 = no)
- Green_roofs: binnary (1 = yes; 0 = no)
- seminatural_natural_wasteland: binnary (1 = yes; 0 = no)
- other_unspecified: binnary (1 = yes; 0 = no)
- Number sites
- Abundance honeybees
- Abundance wild bees
- Total bees
- Proportion honeybees
- Proportion wildbees
- Area:. of the studied city/urban aggregation

en: R script for analyses and plots

format: OCTET

en: Dataset species abundance

en:
This data resource provides the individual species abundance per city / urban aggregation. It contains data from 41 datasets from 37 studies collected in 33 cities / urban aggregations. It contains the following columns:
 - Article_ID
- DOI
- Authors
- Year
- Continent
- Country
- City
- Bee genus
- Bee species
- Bee merged
- Bee full
- Abundance
- Bee_ID_per_study: ID for the study

en: Dataset coordinates study cities

en:
The data contains the latitude and longitude of the studied cities / urban aggregations. It contains the following columns:
- Continent
-Country
- City
- Lat: Latitude
- Lon: Longitude

en:
The following repository contains the data and code to reproduce the figures analyses of the paper "Examining honeybee (Apis mellifera) dominance patterns within urban bee communities worldwide". It contains three datasets and one .R file

---

The data results from a literature review on abundance distribution of urban bee communities worldwide, aiming at obtaining studies reporting total abundances of honeybees and wildbees in a given city, and species abundances of wildbees and honeybees in a given city.

---

1. **Data**:
- *20240308_cities_coords.csv*: the data contains the latitude and longitude of the included cities in the study. It is used for making the world map with the cities.
- *20241201_proportion_HB_WB.csv*: the data contains the total wild bee and honeybee abundances per city/urban aggregation, and the proportions.
- *20241201_rad_bees.csv*: the data contains the species abundances per city/urban aggregation

2. **Script**:
- *HoneybeeDominance_Analyses_Figures.R*: the script to run the analyses and make the plots. Analyses were done in R version 4.2.1, using the packages ggplot2, glmmTMB, multcomp, wesanderson, terra.

anthophila

display_name: anthophila

cities

display_name: cities

dominance

display_name: dominance

honeybees

display_name: honeybees

sads

display_name: sads

urban-beekeeping

display_name: urban-beekeeping

urban-ecosystems

display_name: urban-ecosystems

wildbees

display_name: wildbees

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Data supporting ‘Examining honeybee (Apis mellifera) dominance patterns within urban bee communities worldwide’


en: soil-texture lwc matric-potential soil alpine measurements glide-snow-avalanche soil-classification

en: Daily averaged values used for the direct fitting

media_type: application/zip

en: Hydrus files used for the inverse fitting

format: ZIP

en: Complete list of the van Genuchten parameter values for each soil and method

media_type: text/plain

en: Detailed information of each file in the dataset

format: TXT

en: Coordinates of each soil location, location of the snow profiles, and location of the snow liquid water content measurements

en: Texture data of the soil locations

en: The dataset contains measured values of soil liquid water content, matric potential, and soil texture of 40 soil samples in Davos, Switzerland. The measurements were used for determining van Genuchten parameter values through fitting of water retention curves, pedotransfer functions, and inverse fitting with Hydrus-1D.

alpine

display_name: alpine

glide-snow-avalanche

display_name: glide-snow-avalanche

lwc

display_name: lwc

matric-potential

display_name: matric-potential

measurements

display_name: measurements

soil

display_name: soil

soil-classification

display_name: soil-classification

soil-texture

display_name: soil-texture

en: Soil measurements of Seewer Berg and Davos


forest-canopy-layer-code

title_for_slug: forest-canopy-layer-code

en: itd forest protective-forest lidar forest-management mountain-forest vhm

en:
R script for large-scale mapping of forest canopy layering. The approach combines tree-based and area-based methods, using airborne laser scanning point clouds together with individual tree detection (ITD) information (tree height and position) to distinguish between single- and multi-layered forests. The output is a raster layer at 10m x 10m resolution, encoded as follows:
1: single-layered (class 1): Both point cloud and ITD approaches classify the forest as single-layered.
2: probably single-layered (class 2): ITD classifies the forest as single-layered, while the point cloud suggests multi-layered.
3: probably multi-layered (class 3): ITD classifies the forest as multi-layered, while the point cloud suggests single-layered.
4: multi-layered (class 4): Both point cloud and ITD approaches classify the forest as multi-layered.
Next to the R script, we also provide an example data set. The LAZ files in the example dataset are from the nationwide ALS data and are provided by the Federal Office of Topography swisstopo in accordance with its open data policy (swisstopo, 2022a, 2019). The detected individual trees were identified using Dalponte and Coomes' (2016) algorithm on a spike-free vegetation height model (cell size 0.5m). The provided forest mask corresponds to the NFI forest layer definition by Waser et al. (2015). For details and mentioned references, we refer to the related publication by Bast et al. (under revision; JAG).

forest

display_name: forest

forest-management

display_name: forest-management

itd

display_name: itd

lidar

display_name: lidar

mountain-forest

display_name: mountain-forest

protective-forest

display_name: protective-forest

vhm

display_name: vhm

en: Forest Canopy Layer Code


maintainer: Merin Reji Chacko

en: biodiversity-assessment spatial-ecology environmental-dna biomonitoring dna-metabarcoding

en: Genomic data

en: Fastq files, primer descriptions and the final output dataset.

en: Analysis and Figures

en: This zipped file includes R scripts and the datasets required to run the analyses. A README describes the columns in each dataset.

en: Field Metadata

en: Information concerning the locations and times of sampling, as well as the identity of the samplers and relevant comments.

en: This dataset contains the results of a five-day field excursion which the extent to which eDNA sampling can capture the diversity of a region with highly heterogeneous habitat patches across a wide elevation gradient through multiple hydrological catchments of the Swiss Alps. Using peristaltic pumps, we filtered 60 L of water at five sites per catchment for a total volume of 1 800 L. Using an eDNA metabarcoding approach focusing on vertebrates and plants, we detected 86 vertebrate taxa spanning 41 families and 263 plant taxa spanning 79 families across ten catchments. This dataset includes two sets of data. The first (Genomic data) includes all the necessary data for the bioinformatic pipeline, whereas the second (Analysis Figures) contains tidied data and scripts for the reproduction of all figures/analyses in the article describing this study.

biodiversity-assessment

display_name: biodiversity-assessment

biomonitoring

display_name: biomonitoring

dna-metabarcoding

display_name: dna-metabarcoding

environmental-dna

display_name: environmental-dna

spatial-ecology

display_name: spatial-ecology

en: Vertebrate and plant taxa recovered from 10 catchments in Vaud using an eDNA-metabarcoding approach


maintainer: Anita C. Risch

en: grassland mineralization soil-chemistry global nutrient-network soil-biology soil worldwide

en:
site.code: Site code

Continent: Continent

sampleID: Sample ID

nn.latitude: Lattitude

nn.longitude: Longitude

bioclim.T.ann: Mean annual temperature (°C)

bioclim.T.var: Temperature variability (°C)

bioclim.T.q.wet: Temperature of the wettest quarter (°C)

bioclim.T.q.dry: Temperature of the driest quarter (°C)

bioclim.T.q.warm: Temperature of the warmest quarter (°C)

bioclim.P.ann: Mean annual preciptiation (mm)

bioclim.P.q.wet: Precipitation of the wettest quarter (mm)

ch.pH: pH

ch.WSK.vol: Water holding capacity (vol%)

ch.bulkdensity.gcm3: Bulk density (g cm-3)

ch.porespace: Pore space (vol%)

ch.sand.perc: Soil texture: sand (%)

ch.silt.perc: Soil texture: silt (%)

ch.clay.perc: Soil texture: clay (%)

ch.NO3start.mgg: NO3 at the beginning of the incubation (mgkg)

ch.Ntot.perc: Total soil N (%)

ch.Ctot.perc: Total soil C (%)

ch.Corg.perc: Soil organic C (%)

ch.netNminfield.mgkgd: Realised soil net N mineralisation (mg kg-1 d-1)

ch.netNminlab.mgkgd: Potential soil ne N mineralisation (mg kg-1 d-1)

archaea.cpg.log: Ammonia oxidising archaea (archaeal amoA gene copies g-1 soil)

bacteria.cpg.log: Ammonia oxidising bacteria (bacterial amoA gene copies g-1 soil)

micr.biom: Microbial biomass (ug g-1 soil)

ch.CtoN: C to N ratio

ch.netNnitriffield.mgkgd.sqrt: Realised soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniffield.mgkgd.sqrt: Realised soil net ammonification, transformed (mg kg-1 d-1)

ch.netNnitriflab.mgkgd.sqrt: Potential soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniflab.mgkgd.sqrt: Potential soil net ammonifiation, transformed (mg kg-1 d-1)

format: XLS

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

Paper Citation:

Risch, A. C.; Zimmermann, S.; Ochoa-Hueso, R.; Schütz, M.; Frey, B.; Firn, J. L.; Fay, P. A.; Hagedorn, F.; Borer, E. T.; Seabloom, E. W.; et al. Soil net nitrogen mineralisation across global grasslands. Nat. Commun. 2019, 10 (1), 4981 (10 pp.). doi.org/10.1038/s41467-019-12948-2

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

We conducted coordinated measurements of realised and potential soil net Nmin, and assessed water holding capacity, bulk density, C and N content, texture, pH, pore space, microbial biomass, and archaeal (AOA) and bacterial (AOB) ammonia oxidiser abundance using identical materials and methods across 30 grasslands on six continents. The sites covered a globally relevant range of climatic and edaphic conditions. Climate data was obtained from worldclim - Global climate data https://www.worldclim.org/

global

display_name: global

grassland

display_name: grassland

mineralization

display_name: mineralization

nutrient-network

display_name: nutrient-network

soil-biology

display_name: soil-biology

soil-chemistry

display_name: soil-chemistry

worldwide

display_name: worldwide

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


en: meteo-station snow-height longwave-radiation gemstock shortwave-radiation

en: DATA ACCESS

en:
Meteo data at Gemsstock [Level 2 dataset](http://models.slf.ch/p/dataset-processing/).

fields      = timestamp TSS HS VW DW VW_MAX OSWR ISWR ILWR RECORD AUX_VOLTAGE LOGGER_VOLTAGE LW_SENSOR_TEMP VENTILATION_FLAG OLWR

en:
Meteorological station at Gemstock (3021 m asl) in Canton Uri. The station includes in/out LW/SW and a snow height sensor.

Data from this station is managed by the permos.ch project. More information: https://www.permos.ch/permafrost-monitoring/field-sites

gemstock

display_name: gemstock

longwave-radiation

display_name: longwave-radiation

meteo-station

display_name: meteo-station

shortwave-radiation

display_name: shortwave-radiation

snow-height

display_name: snow-height

en: GEM2: Meteorological and snow station at Gemsstock (3021 m asl), Canton Uri, Switzerland


en: antarctica uav drone irra sea-ice snow-temperature snow-roughness snow

en:
This dataset accompanies the publication "How Flat is Flat? Investigating the spatial variability of snow surface temperature and roughness on landfast sea ice using UAVs in McMurdo Sound, Antarctica".
The dataset consists of 1) processed orthomosaic of RGB values, snow topography (digital elevation model), and surface temperature, 2) topography-dependent irradiance map, and 3) point data of measured radiation and atmospheric parameters in the McMurdo Sound, October-December 2022. The data was collected as part of the New Zealand Marsden Fund Research Grant 21-VUW-103 "Can Snow Change the Fate of Antarctic Sea Ice?". Unprocessed data associated with this field campaign are published in 10.16904/envidat.633.
For the airborne measurements, we used a DJI Matrice 30T, a multi-rotor (quadcopter) UAV with self-heating batteries, suitable for operations in polar conditions (temperature range from -20 to +50 °C). The UAV has a wide-angle camera (12 megapixels) for RGB images and a thermal camera (Uncooled Vox Microbolometer, long-wave infrared spectrum 8-14 µm, 1.31 megapixels) for TIR images with an accuracy of ±2 °C or ± 2 %.
GNSS data includes high-precision location information (latitude, longitude, ellipsoidal height, receiver clock offset, and timestamps formatted in decimal hours and day-of-year notation).
WE calculated the distribution of received solar irradiance over the sea-ice surface using a terrain-corrected radiative transfer model and measured shortwave radiation components, accounting for surface roughness, aspect, slope, and solar position during the flight, while applying terrain shading and measured diffuse radiation.
The broadband radiation station data consists of shortwave (Sw) and longwave (Lw) radiation measurements (Kipp & Zonen CMP22 pyranometers and CGR4 pyrgeometers).
Surface temperature readings from cold, sediment, and hot targets were recorded using Apogee SI-121-SS sensors.
This dataset also contains automated weather station (AWS) data (air and snow surface temperatures, relative humidity, wind direction, and wind speed).
For detailed information, please use the README file.

antarctica

display_name: antarctica

drone

display_name: drone

irra

display_name: irra

sea-ice

display_name: sea-ice

snow

display_name: snow

snow-roughness

display_name: snow-roughness

snow-temperature

display_name: snow-temperature

uav

display_name: uav

en: Snow On Antarctic Sea Ice - McMurdoSound 2022 - UAV Retrievals of Snow Topography and Snow Surface Temperature


en: soil-water-matrix-potential soil-temperature soil-moisture landslide-early-warning soil-water-content

en: In-situ soil moisture measurements, Langnau i E, since 2021

en:
Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each. Meteorological variables, such as air temperature or precipitation can be received from MeteoSwiss.
Time intervall: 1 hour. Measurement period: since June 2021.
Location: flat terrain, meadow (measurement site of MeteoSwiss)
For a detailed description of site, soil and vegetation: see attached document.

en: Detailed description of soil moisture measurment sites, soil properties and sensor installations (in German)

en: In-situ soil moisture measurements, Wasen i.E., flat location, 2019-2023

en:
Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, and two additional soil temperature measurements (oC), air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: April 2019-Dec 2023.
Location: flat terrain, meadow
For a detailed description of site, soil and vegetation: see attached document.

en: In-situ soil moisture measurements, Trub, since 2021

en:
Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, as well as air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: since April 2021.
Location: slope, meadow
For a detailed description of site, soil and vegetation: see attached document.

en: In-situ soil moisture measurements, Wasen i.E., flat location, since 2019

en:
Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, and two additional soil temperature measurements (oC), air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: since April 2019.
Location: flat terrain, meadow
For a detailed description of site, soil and vegetation: see attached document.
Updates 2025:
The “precipitation” column was set to not available (NA) for periods when the pluviometer was identified as clogged. These periods were assigned (i) based on regular maintenance of the measurement station and (ii) irregular behavior of the measurement series compared to the precipitation signal from the other nearby measurement stations.
Column “VWC_0.7m_right” and “ST_5TE_0.7m_right” were set to not available (NA) for the period after the 2023-06-19T14:00:00Z due to irregular behavior of the ECH2O - 5TE sensor.

en: In-situ soil moisture measurements, Wasen i.E., steep slope, since 2019

en:
Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, and two additional soil temperature measurements (oC), air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: since April 2019.
Location: steep hillslope, meadow
For a detailed description of site, soil and vegetation: see attached document.

en: In-situ soil moisture measurements, Ranflüh, since 2021

en:
Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, as well as air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: since April 2021.
Location: hillslope, meadow
For a detailed description of site, soil and vegetation: see attached document.
Update 2025:
The “precipitation” column was set to not available (NA) for periods when the pluviometer was identified as clogged. These periods were assigned (i) based on regular maintenance of the measurement station and (ii) irregular behavior of the measurement series compared to the precipitation signal from the other nearby measurement stations.

en: In-situ soil moisture measurements, Napf, since 2021

en:
Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each. Meteorological variables such as air temperature or precipitation can be received from MeteoSwiss.
Time intervall: 1 hour.
Measurement period: since June 2021
Location: flat terrain, meadow (official MeteoSwiss station)
For a detailed description of site, soil and vegetation: see attached document.

en: In-situ soil moisture measurements, Ranflüh, 2021-2023

en:
Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, as well as air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: April 2021-Dec 2023.
Location: hillslope, meadow
For a detailed description of site, soil and vegetation: see attached document.

en: In the context of landslide early warning research, soil moisture (e.g. volumetric soil water content and soil water potential) has been measured at six locations in the Napf-region (Emmental, central Switzerland) since April 2019. Here, we provide the hourly mean values of all sensors from all 6 locations after a comprehensive data control, filtering and aggregation (from 10-min to 1-hour values). A sub-set of these data (for the locations Wasen i.E.) has previously been published in envidat.ch at https://www.doi.org/10.16904/envidat.369 applying the same data post-processing method. The dataset is complemented with meteorological data (locally measured air temperature and precipitation) as well as soil temperature. A detailed description of the sites and measurement installations can be found in a separate report (attached with the data).

landslide-early-warning

display_name: landslide-early-warning

soil-moisture

display_name: soil-moisture

soil-temperature

display_name: soil-temperature

soil-water-content

display_name: soil-water-content

soil-water-matrix-potential

display_name: soil-water-matrix-potential

en: In-situ soil moisture measurements Napf-region


en: snow-modelling avalanche snowdrift snowpack source-code

en:
This dataset includes the FORTRAN code of the FSM2trans model version used in the paper: Quéno et al., Snow redistribution in an intermediate-complexity snow hydrology modelling framework, The Cryosphere, 2024.
The FSM2trans code is derived from the FSM2 model (Essery et al., 2015) and its variant FSM2oshd (Mott et al., 2023). In this model, we implemented and adapted the snowdrift model SnowTran-3D (Liston et al., 2007) and the avalanching model SnowSlide (Bernhardt and Schulz, 2010).
This dataset does not include the processing scripts to prepare meteorological input data for the model, provided as bin files.

avalanche

display_name: avalanche

snow-modelling

display_name: snow-modelling

snowdrift

display_name: snowdrift

snowpack

display_name: snowpack

source-code

display_name: source-code

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: FSM2trans code


maintainer: Camille Albouy

en: bay-biscay actinopterygii atlantic-region teleo edna dna-metabarcoding fish-composition chondrichthyes

en: Data access

en:
Environmental DNA complements scientific trawling in surveys of marine fish biodiversity (Dataset 2020)

In October 2020 we chose 16 sites from the 2020 EVHOE survey for eDNA sampling. The French international EVHOE bottom trawl survey is carried out annually during autumn in the BoB to monitor demersal fish resources. All sites were located on the continental shelf (26–170 m depth), except one on the upper slope with a depth of 1045 m. To perform eDNA sampling, we collected water samples at 15 sites (Figure 1a). At each site, we sampled seawater using Niskin bottles deployed with a circular rosette. There were nine bottles on the rosette, each of them able to hold ∼5 l of water. At each site, we first cleaned the circular rosette and bottles with freshwater, then lowered the rosette (with bottles open) to 5 m above the sea bottom, and finally closed the bottles remotely from the boat. The 45 l of sampled water was transferred to four disposable and sterilized plastic bags of 11.25 l each to perform the filtration on-board in a laboratory dedicated to the processing of eDNA samples. To speed up the filtration process, we used two identical filtration devices, each composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 l min–1 ), a VigiDNA 0.20 μm filtration capsule (SPYGEN, le Bourget du Lac, France), and disposable sterile tubing. Each filtration device filtered the water contained in two plastic bags (22.5 l), which represent two replicates per sampling site. We followed a rigorous protocol to avoid contamination during fieldwork, using disposable gloves and single-use filtration equipment and plastic bags to process each water sample. At the end of each filtration, we emptied the water inside the capsule that we replaced by 80 ml of CL1 conservation buffer and stored the samples at room temperature following the specifications of the manufacturer (SPYGEN, Le Bourget du Lac, France). We processed the eDNA capsules at SPYGEN, following the protocol proposed by Polanco-Fernández et al., (2020). We performed library preparation and sequencing at Fasteris (Geneva, Switzerland). Specifically, we prepared four libraries using the MetaFast protocol (a ligation-based method) and sequenced them separately. We carried out paired-end sequencing using a MiSeq sequencer (2 × 125 bp, Illumina, San Diego, CA, USA) on two MiSeq Flow Cell Kits (v3; Illumina), following the manufacturer’s instructions. We analysed the sequence reads using the OBITools package (http:
//metabarcoding.org/obitools; Boyer et al., 2016), following the protocol described by Valentini et al. (2016).

Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

actinopterygii

display_name: actinopterygii

atlantic-region

display_name: atlantic-region

bay-biscay

display_name: bay-biscay

chondrichthyes

display_name: chondrichthyes

dna-metabarcoding

display_name: dna-metabarcoding

edna

display_name: edna

fish-composition

display_name: fish-composition

teleo

display_name: teleo

en: Environmental DNA Marine France Evhoe 2020


maintainer: Dirk Nikolaus Karger

en: interannual-climate-variability reptiles chelsa amphibians niche-models range-maps species-distribution-models sdm random-forests mammals generalized-additive-models iucn generalized-linear-models climate-variablity

en: Readme file containing the file naming convention, file dimensions, and variable names

en: File containing the climate predictors as SAGA grid files (.sgrd)

en: File containing the record dimension, genus, and species of the respective netcdf files

en: Amphibians

en: Species distribution models based on different climate predictor groups

en: Reptiles

en: Mammals

en: We modelled the global distribution of 730 amphibian, 1276 reptile, and 1961 mammal species globally as a function of current climate at a 0.5° spatial resolution using four different predictor groups composed of different combinations of input variables: mean climatic conditions, spatial climatic variability, and temporal (interannual) climatic variability.

amphibians

display_name: amphibians

chelsa

display_name: chelsa

climate-variablity

display_name: climate-variablity

generalized-additive-models

display_name: generalized-additive-models

generalized-linear-models

display_name: generalized-linear-models

interannual-climate-variability

display_name: interannual-climate-variability

iucn

display_name: iucn

mammals

display_name: mammals

niche-models

display_name: niche-models

random-forests

display_name: random-forests

range-maps

display_name: range-maps

reptiles

display_name: reptiles

sdm

display_name: sdm

species-distribution-models

display_name: species-distribution-models

en: Global species distributions for mammals, reptiles, and amphibians


maintainer: Roman Zweifel

en: forest icos carbon-storage sap-flow forest-dynamics forest-ecosystems ecosystem-functioning carbon-cycle water-relations ecophysiology picea-abies eddy-covariance-measurements dbh seehornwald forest-biomass carbon-sequestration forest-function icp-forests flux open-data climate-growth co2 forest-canopy carbon-dioxide ilter tree-stem stem-growth subalpine dendrometer metadata eddy-covariance forest-monitoring forest-area climate-change treenet davos twd lwf forest-characteristics biomass automated-monitoring atmospheric-conditions

en: Readme

en: Collection of files with information about the research site Seehornwald Davos CH-DAV

en: Site description of the Seehornwald Davos (CH-DAV) research site. The material provided offers information on the biomass and growth of trees in CH-DAV, including supporting materials such as maps, geolocations and analyses. CH-DAV is part of networks such as ICOS, LWF, TreeNet, ICPForests and is dedicated to forest monitoring and research.

atmospheric-conditions

display_name: atmospheric-conditions

automated-monitoring

display_name: automated-monitoring

biomass

display_name: biomass

carbon-cycle

display_name: carbon-cycle

carbon-dioxide

display_name: carbon-dioxide

carbon-sequestration

display_name: carbon-sequestration

carbon-storage

display_name: carbon-storage

climate-change

display_name: climate-change

climate-growth

display_name: climate-growth

davos

display_name: davos

dbh

display_name: dbh

dendrometer

display_name: dendrometer

ecophysiology

display_name: ecophysiology

ecosystem-functioning

display_name: ecosystem-functioning

eddy-covariance

display_name: eddy-covariance

eddy-covariance-measurements

display_name: eddy-covariance-measurements

flux

display_name: flux

forest

display_name: forest

forest-area

display_name: forest-area

forest-biomass

display_name: forest-biomass

forest-canopy

display_name: forest-canopy

forest-characteristics

display_name: forest-characteristics

forest-dynamics

display_name: forest-dynamics

forest-ecosystems

display_name: forest-ecosystems

forest-function

display_name: forest-function

forest-monitoring

display_name: forest-monitoring

icos

display_name: icos

icp-forests

display_name: icp-forests

ilter

display_name: ilter

lwf

display_name: lwf

metadata

display_name: metadata

open-data

display_name: open-data

picea-abies

display_name: picea-abies

sap-flow

display_name: sap-flow

seehornwald

display_name: seehornwald

stem-growth

display_name: stem-growth

subalpine

display_name: subalpine

tree-stem

display_name: tree-stem

treenet

display_name: treenet

twd

display_name: twd

water-relations

display_name: water-relations

educ

en: Education, culture and sport

en: Site description Davos Seehornwald CH-DAV


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

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

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

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

en: 06_Studyprotocol_GPS tracks of the walking routes.zip

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

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

en: 07_Studyprotocol_Test site pictures.zip

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

en: 03b_Studyprotocol_Script_Analysis stationary noise evaluation.sps.sps

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

en: 11_P4_S1_Instructions for individual mindful walking.pdf

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

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

en: 13_P4_Data mindful walking.sav

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

en: 09_P2_Fotos Noise ROS paper.zip

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

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

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

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

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

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

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

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

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

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

en:
This repository contains data related to the field experiments of the RESTORE project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and the Swiss Federal Laboratories for Materials Science & Technology (EMPA). It has received funding from the Swiss National Science Foundation. The overall objective of the RESTORE project was to assess the effects of green spaces as facilitators and noise as impediment to recover from stress in people's daily environments across Switzerland.
We conducted a randomized, controlled field study to compare the psychophysiological benefits of exposure to forests and urban built environments with different levels of road traffic noise in healthy adults during 30-minute walks in Zürich, Switzerland to explore:
1) The psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure
2) The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world
3) The effects of a mindful walking intervention in urban forests for healthy adults

Accordingly, this repository includes data and documentation for the 3 scientific articles:

Scientific article 1. “Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: study protocol of a randomized controlled trial", BMC Psychology, 2024. https://doi.org/10.1186/s40359-024-01720-x

Scientific article 2. "Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“. Journal of Environmental Psychology, 2025.

Scientific article 3. “The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial". To be submitted to PLOS One, 2025.

Scientific article 4: "Effects of a mindful walking intervention in urban forests for healthy adults". To be submitted to Current Psychology, 2025.

field-data

display_name: field-data

forest

display_name: forest

restoration

display_name: restoration

traffic-noise

display_name: traffic-noise

urban-landscape

display_name: urban-landscape

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: pmcamx-uf nucleation total-number modeling cloud-droplets

en: data_JRL_New particle formation events can reduce cloud droplets in boundary layer clouds at the continental scale.Paper_2023GL106182.zip

en: This repository contains PMCMx-UF model outputs used for the paper: D. Patoulias K. Florou S. N. Pandis and A. Nenes: New particle formation events can reduce cloud droplets in boundary layer clouds at the continental scale, Geophysical Research Letters, in review, 2023.

cloud-droplets

display_name: cloud-droplets

modeling

display_name: modeling

nucleation

display_name: nucleation

pmcamx-uf

display_name: pmcamx-uf

total-number

display_name: total-number

educ

en: Education, culture and sport

en: Dataset for the publication New particle formation events can reduce cloud droplets in boundary layer clouds at the continental scale


maintainer: Marco Moretti

en: resource-availability bettergardens urban-ecosystems pollinator-experiment urban-biodiversity urbanization zurich city4bees beekeeping gardens wild-bees honeybees

en: Response and predictors used for the SEMs

en:
The data contains the following columns:

  SiteID: numeric, the identity of the garden where the bee was sampled.
  Taxonname: character, species name
  Lecty: numeric discreet, a mesure of specialisation degree. Levels: 1 = monolectic; 2=oliolectic; 3=polilectic
  Pheno.start= numeric discreet, the starting week of the flying activity.
  Pheno.end= numeric discreet, the ending week of the flying activity.
  Pheno.duration=numeric discreet, Pheno.end - Pheno.start
  Daytime.activity = numeric continuous, individual-level measure of the day hour when the bee was sampled
  ITD = numeric continuous, individual-level measure of the InterTegular Distance, a metric of mobility in mm.
  Rel.tongue.length =numeric continuous, individual-level measure of the relative tongue length (Tongue length / ITD), a metric of specilaisation degree, in mm.

en: Metadata for the predictor and response dataset

en:
Mean, standard deviation , minimum and maximum values of six functional traits. The data has the following structure:
- Bee_species: bee scientific name
- mean_trait: mean value
- sd_trait: standard deviation
_min_trait: minimum value
- max_trait: maximum value
- trait: the six traits used. ITD = Intertegular distance (mm); Pheno.duration = duration of the phenology; Pheno.start = start of the phenology; Pheno.end = end of the phenology; Rel.tongue.length= relative tongue length (mm); Daytime.activity = daily activity (h)
DistNichePart: functional dissimilarity in a multidimentional trait space defined by five traits between wild bee individuals of a wild bee species and the honeybee individuals. Values are at the species level.

en: Metadata for the predictors and response dataset

en:
Cities are socio-ecological systems that filter and select species, thus establishing unique species assemblages and biotic interactions. Urban ecosystems can host richer wild bee communities than highly intensified agricultural areas, specifically in resource-rich urban green spaces such as allotment and family gardens. At the same time, urban beekeeping has boomed in many European cities, raising concerns that the fast addition of a large number of managed bees could deplete the existing floral resources, triggering competition between wild bees and honeybees. The data has been used to investigated the interplay between resource availability and the number of honeybees at local and landscape scales and how this relationship influences wild bee diversity.

This dataset contains the raw and processed data supporting the findings from the paper: "Low resource availability drives feeding niche partitioning between wild bees and honeybees in a European city".

The data contains:
1. Bee trait measurements at the species and individual-level of five functional traits.
2. The values of the feeding niche partitioning (functional dissimilarity to honeybees)
3. The predictors of resource availability and beekeeping intensity at local and landscape scales used in the modelling of the paper for the 23 experimental sites.

beekeeping

display_name: beekeeping

bettergardens

display_name: bettergardens

gardens

display_name: gardens

honeybees

display_name: honeybees

pollinator-experiment

display_name: pollinator-experiment

resource-availability

display_name: resource-availability

urban-biodiversity

display_name: urban-biodiversity

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wild-bees

display_name: wild-bees

zurich

display_name: zurich

en: Niche partitioning between wild bees and honeybees


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

en: WFJ_DailySMP data access

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

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

microstructure

display_name: microstructure

snow

display_name: snow

snow-density

display_name: snow-density

snow-measurements

display_name: snow-measurements

snow-ssa

display_name: snow-ssa

snow-stratigraphy

display_name: snow-stratigraphy

snowmicropen

display_name: snowmicropen

weisfluhjoch

display_name: weisfluhjoch

weissfluhjoch

display_name: weissfluhjoch

wfj-research-site

display_name: wfj-research-site

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


functional-invertebrate-groups-dataset

title_for_slug: functional-invertebrate-groups-dataset

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

en: Raw data of invertebrate sampling at different streetlight characteristics (light temperature (K), light level (L_level), luminaire shape (Diff)) over two summers (2021 & 2022). Included are two pitfall trap positions (Center C (100% light intensity) and Periphery P (10% light intensity).

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

alan

display_name: alan

artificial-lighting

display_name: artificial-lighting

community-composition

display_name: community-composition

functional-groups

display_name: functional-groups

invertebrates

display_name: invertebrates

led

display_name: led

light-pollution

display_name: light-pollution

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: Functional Invertebrate Groups - Dataset


maintainer: Rebecca Mott

en: tls terrestrial-laser-scanning patchy-snow-covers riegl-vz6000 snow-ablation-rates

en: Snowmask 2016

mimetype: application/zip

en: Digital Elevation Modell 2016

en: Digital Elevation Modell 2014

en: Snowmask 2015

en: Snowmask 2014

en: Digital Elevation Modell 2015

en: Gletschboden test site

en: We recorded snow ablation maps with a terrestrial laser scanner (TLS, Riegl-VZ6000) at the Gletschboden area. The TLS position is located approximately 30 vertical meters above the Gletschboden area at a northerly exposed slope. In total 44 TLS measurement sets have been conducted in three consecutive years 2014-2016 (2014: 13 measurements; 2015: 17 measurements; 2016: 14 measurements). The TLS system has a single-point measurement frequency of 300 kHz and a beam divergence of 0.007°. This set-up allows a horizontal resolution of approximately 0.01 m in 100 m distance to the TLS position. One scan of the Gletschboden area lasts approximately 15 minutes. The travel time from the laser scanner towards the surface is recorded and afterwards converted into a point cloud of distances. 5 reflectors located at the Gletschboden area and in the closer surroundings were additionally scanned during each measurement to transform the point cloud from the scanner own coordinate system into Swiss coordinates. Additionally, orthophotos have been created by using pictures recorded from the TLS in order to provide snow mask maps. Snow and bare ground can be distinguished by the RGB color information of the orthophoto. Cells with blue band information greater than 175 were categorized as snow and all cells with values smaller or equal 175 were categorized as bare ground.

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls

educ

en: Education, culture and sport

en: DISCHMEX - High-resolution daily snow ablation rates in an Alpine environment


en: runoff land alptal topsoil-interflow overland-flow plot studibach time-series rainfall

en:
Time series of overland flow and topsoil interflow discharge at 14 runoff plot locations in the Studibach catchment over 27 rain events in 2022.
Format: NEAD
Metadata included in the file: latitude, longitude, data units, timezone.
Source for reading and writing NEAD format: https://www.doi.org/10.16904/envidat.187.

en:
The dataset comprises the time series of overland flow (OF) and topsoil interflow (TIF) discharges from 14 small runoff plots (1 x 3 m) over 27 rainfall events in 2022 across the Studibach in the Alptal, a typical pre-Alpine catchment in Switzerland.
The runoff plots were installed on different topographic indices and vegetation covers in order to study the spatio-temporal variability of OF and TIF.
The runoff was collected into self-made "Upwelling Bernoulli Tubes" and the water level inside these tubes was measured by pressure sensors (DCX-22-CTD, Keller Druck, Switzerland) at a 5-min resolution. The discharge was derived from the water level.
The precipitation was measured with a tipping bucket at the Erlenhöhe meteorological station and has a 10-min resolution.

alptal

display_name: alptal

land

display_name: land

overland-flow

display_name: overland-flow

plot

display_name: plot

rainfall

display_name: rainfall

runoff

display_name: runoff

studibach

display_name: studibach

time-series

display_name: time-series

topsoil-interflow

display_name: topsoil-interflow

en: Overland and topsoil interflow time series from the Studibach - summer 2022


en: climate imis grassland phenology monitoring long-term snow alpine snowmelt ultrasonic

en: Contains custom functions required for the scripts; this file must be sourced before running other scripts.

en: Generates the methods-related figures used in the publication.

en: Contains IMIS station location data

en: Temporary data. Contains annual unfiltered output of phenofit (i.e. the variable names are in line with the phenofit documentation), including all curve parametrization variables for plotting and additional variables, which are not necessarily used in the analysis.

media_type: image/png

en: Snow3.png and grass.png are needed for plotting the methods plot in 5_methods_plots.Rmd

format: PNG

en: Contains daily climate station data including daily median temperatures, snow depth, plant height, and annual melt-out timings.

en: implements the phenofit method. Note: This script is computationally intensive and may take a while to run. We recommend using the temporary data created from it (i.e. starting from 2_temperature.R). For a better description of the phenofit R package and the different methods to determine the SOG, see Kong et al. (2022): https://doi.org/10.1111/2041-210X.13870

en: Contains unfiltered annual phenological, temperature and snow-climatic data for all IMIS stations.

en: Contains filtered annual phenological data from 40 IMIS stations suitable and used for phenological analysis

en: Is the readme that documents all data and code in this repository

en: Contains annual phenological variables and phenofit outputs, sorted, ordered and renamed according with the readme in this repository

en: Documents and reproduces the statistical models used in the analysis.

en:
Long-term phenological data in alpine regions are often limited to a few locations and thus, little is known about climate-change induced plant phenological shifts above the treeline. Because plant growth initiation in seasonally snow-covered regions is largely driven by snowmelt timing and local temperature, it is essential to simultaneously track phenological shifts, snowmelt, and near-ground temperatures. In this study, we make use of ultrasonic snow height sensors installed at climate stations in the Swiss Alps to reveal phenological advance of grassland ecosystems and relate them to climatic changes over 25 years (1998 – 2023). When snow is absent, these snow height sensors additionally provide information on plant growth at a uniquely fine temporal scale. Daily temperatures and snow- / plant height values, annual phenological- and melt-out dates were derived from IMIS climate station data (doi.org/10.16904/envidat.406). We observed an advance of green-up by -2.4 days/decade coinciding with strong warming of up to +0.8°C/decade. Although the timing of melt-out has not changed significantly over the study period in this focal region, phenological responses to early melt-out years varied due to differing influences of photoperiodic and thermal constraints, which were not equally important across elevations and communities. Phenological shifts of alpine grasslands are thus likely to become even more pronounced if melt-out timing advances in the future as predicted.
This repository relates to the publication Zehnder et al. (2025). Snow height sensors reveal phenological advance in alpine grasslands. Global Change Biology. accepted. The model data and code that support our findings are deposited in this repository.

alpine

display_name: alpine

climate

display_name: climate

grassland

display_name: grassland

imis

display_name: imis

long-term

display_name: long-term

monitoring

display_name: monitoring

phenology

display_name: phenology

snow

display_name: snow

snowmelt

display_name: snowmelt

ultrasonic

display_name: ultrasonic

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: IMIS Phenology Data Since 1998


maintainer: Anna Braun

en: snow metamorphism microstructure numerical-simulations fem

author: EnviDat

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

format: ODS

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

fem

display_name: fem

metamorphism

display_name: metamorphism

microstructure

display_name: microstructure

numerical-simulations

display_name: numerical-simulations

educ

en: Education, culture and sport

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


maintainer: Elisabeth Hafner

en: natural-hazard avalanche hazard-mapping satellite snow

en: SPOT6 Avalanche Outlines 16 January 2019

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

format: SHP

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

The generation of the data is described in:

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

The data was comprehensivly validated in a subset area in

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

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

en: SPOT6 Avalanche outlines 16 January 2019


en: core gridded-data time-series raster video-encoding sentinel-2 research-data-management geodata

en: Disclaimer: provided for the Geomatics peer review in 2021 and left as additional information for the dataset. Software dependencies and libraries, as well as cloud storage paths, may change over time (after 2021).

en: View publication in the Digital Object Repository at WSL (DORA)

media_type: text/html

format: HTML

en: CORE Dataset (80 GB)

en:
Acknowledgements: The CORE format was proudly inspired by the Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) format, by considering how to leverage the ability of clients issuing HTTP GET range requests for a time-series of remote sensing and aerial imagery (instead of just one image).

License: The Cloud Optimized Raster Encoding (CORE) specifications are released to the public domain under a Creative Commons 1.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

-----------------------

Summary:
The Cloud Optimized Raster Encoding (CORE) format is being developed for the efficient storage and management of gridded data by applying video encoding algorithms. It is mainly designed for the exchange and preservation of large time series data in environmental data repositories, while in the same time enabling more efficient workflows on the cloud. It can be applied to any large number of similar (in pixel size and image dimensions) raster data layers. CORE is not designed to replace COG but to work together with COG for a collection of many layers (e.g. by offering a fast preview of layers when switching between layers of a time series).

WARNING: Currently only applicable to RGB/Byte imagery. The final CORE specifications may probably be very different from what is written herein or CORE may not ever become productive due to a myriad of reasons (see also 'Major issues to be solved').

With this early public sharing of the format we explicitly support the Open Science agenda, which implies "shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process" (quote from: European Commission, Directorate General for Research and Innovation, 2016. Open innovation, open science, open to the world).

CORE Specifications:

1) a MP4 or WebM video digital multimedia container format (or any future video container playable as HTML video in major browsers)

2) a free to use or open video compression codec such as H.264, VP9, or AV1 (or any future video codec that is open sourced or free to use for end users)

Note: H.264 is currently recommended because of the wide usage with support in all major browsers, fast encoding due to acceleration in hardware (which is currently not the case for AV1 or VP9) and the fact that MPEG LA has allowed the free use for streaming video that is free to the end users. However, please note that H.264 is restricted by patents and its use in proprietary or commercial software requires the payment of royalties to [MPEG LA](https://www.mpegla.com/programs/avc-h-264/). However, when AV1 matures and accelerated hardware encoding becomes available, AV1 is expected to offer 30% to 50% smaller file size in comparison with H.264, while retaining the [same quality](https://trac.ffmpeg.org/wiki/Encode/AV1).

3) the encoding frame rate should be of one frame per second (fps) with each layer segmented in internal tiles, similar to COG, ordered by the main use case when accessing the data: either layer contiguous or tile contiguous;

Note: The internal tile arrangement should support an easy navigation inside the CORE video format, depending on the use case.

4) a CORE file is optimised for streaming with the moov atom at the beginning of the file (e.g. with -movflags faststart) and optional additional optimisations depending on the codec used (e.g. -tune fastdecode -tune zerolatency for H.264)

5) metadata tags inside the moov atom for describing and using geographic image data (that are preferably compatible with the [OGC GeoTIFF standard](https://www.ogc.org/standards/geotiff) or any future standard accepted by the geospatial community) as well as list of original file names corresponding to each CORE layer

6) it needs to encode similar source rasters (such as time series of rasters with the same extent and resolution, or different tiles of the same product; each input raster should be having the same image and pixel size)

7) it provides a mechanism for addressing and requesting overviews (lower resolution data) for a fast display in web browser depending on the map scale (currently external overviews)

Major issues to be solved:

- Internal overviews (similar to COG), by chaining lower resolution videos in the same MP4 container for fast access to overviews first); Currently, overviews are kept as separate files, as external overviews.

- Metadata encoding (how to best encode spatial extent, layer names, and so on, for each of the layer inside the series, which may have a different geographical extent, etc...; Known issues: adding too many tags with FFmpeg which are not part of the standard MP4 moov atom; metadata tags have a limited string length.

- Applicability beyond RGB/Byte datasets; defining a standard way of converting cell values from Int16/UInt16/UInt32/Int32/Float32/Float64/ data types into multi-band Byte values (and reconstructing them back to the original data type within acceptable thresholds)

Example

Notice: The provided CORE (.mp4) examples contain modified Copernicus Sentinel data [2018-2021].

For generating the CORE examples provided, 50 original Sentinel 2 (S-2) TCI data images from an area located inside Switzerland were downloaded from www.copernicus.eu, and then transformed into CORE format using ffmpeg with H.264 encoding using the [x264 library](https://www.videolan.org/developers/x264.html).

DISCLAIMER: Basic scripts are provided for the Geomatics peer review (in 2021) and kept as additional information for the dataset. Nevertheless, please note that software dependencies and libraries, as well as cloud storage paths, may quickly become deprecated over time (after 2021). For compatibility, stable dependencies and libraries released around 2020 should be used.

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

research-data-management

display_name: research-data-management

time-series

display_name: time-series

video-encoding

display_name: video-encoding


en: zurich cavity-nesting wasps management-intensity bees trap-nest urban-ecology urbanization food-webs urban-ecosystems hymenoptera host-enemy-interactions

en: Raw data nests

en: Host-enemy interaction data, used to compute the interaction diversity metrics

en: Data of the study

en: The csv. file contains the response variable "interaction diversity" (idiv), and the values of the predictors used in the paper. The "id" column indicates the garden ID, each row in the dataset correspond to a garden and each column to the response (idiv), an explanatory variable or a descriptor (name, Lat, Long). See the thesaurus and the readme file for extended information on the variables.

en: Read me file

en: Script for the analyses v2.0

en: Cleaned script to reproduce the analyses

en: Not used: data of the study

en: Script for the analyses v1.0

en: Not used: raw questionnaires

en: Thesaurus

en: Variable names and their description.

en: Not used: readme

en: Questionnaires management intensity anonymised

en: Results from the management intensity questionnaires anonymised. IDs are randomized and don't match those in the study data csv

en:
The data supports the paper "Local and landscape factors shape alpha and beta trophic interaction diversity in urban gardens". It provides:
(1) the host-natural enemy interaction networks and network metrics between cavity-nesting bees and wasps and their natural enemies,
 (2) the explanatory variables reflecting urban intensity, temperature, habitat amount and management intensity.
(3) the questionnaires for assessing management intensity.
(4) a thesaurus for the variable names.
(5) a readme file.
(6) the R script used for the analyses.
The data is part of the BetterGardens project. It was sampled in 85 allotment and home gardens in the ctiy of Zurich in 2015 using standardized trapnests.

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

food-webs

display_name: food-webs

host-enemy-interactions

display_name: host-enemy-interactions

hymenoptera

display_name: hymenoptera

management-intensity

display_name: management-intensity

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wasps

display_name: wasps

zurich

display_name: zurich

envidat

en: EnviDat: the Environmental Data Portal

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

en: Data on interaction diversity in urban gardens


maintainer: Benjamin Reuter

en: avalanche-problem-type avalanche-danger snow snowpack snow-cover-modeling snow-instability weissfluhjoch avalanche-activity crocus avalanche

en: 2015-2016 Avalanche problem types from SNOWPACK

en:
Avalanche problem types were derived from a snow cover simulation with the model SNOWAPCK for the winter season 2015-2016 at the Weissfluhjoch study plot, Davos, CH.
The data cover the period 01.01.2016-30.04.2016. The binary indicator (0,1) tells whether an avalanche problem type was identified in the snow cover simulation (1) or not (0).
The data are presented in Figure 7 in Reuter et al. (2021).

en: 2015-2016 Seismic avalanche acitivity catalogue

en:
Avalanches were indentified in seismic data recorded by two seismic arrays, one deployed at Wannengrat (2,500 m) and another one deployed in the Dischma valley (2,000 m).
The data cover the period from 01.01.2016 - 30.04.2016 and are presented in Figure 7 in Reuter et al. (2021).

en: 2015-2016 Avalanche problem types from Crocus

en:
Avalanche problem types were derived from a snow cover simulation with the model Crocus for the winter season 2015-2016 at the Weissfluhjoch study plot, Davos, CH.
The data cover the period 01.01.2016-30.04.2016. The binary indicator (0,1) tells whether an avalanche problem type was identified in the snow cover simulation (1) or not (0).
The data are presented in Figure 7 in Reuter et al. (2021).

en: 1999-2017 Avalanche problem types from Crocus

en:
Avalanche problem types were derived from snow cover simulations with the model Crocus at the Weissfluhjoch study plot, Davos, CH.
The data cover the winter seasons between 1999-2017 and include the simulated annual frequencies of new snow, wind slab, persistent weak layer, aging-persistent weak layer and wet snow problem types.
The data are presented in Figure 8 in Reuter et al. (2021).

en: 1999-2017 Avalanche problem types from SNOWPACK

en:
Avalanche problem types were derived from snow cover simulations with the model SNOWPACK at the Weissfluhjoch study plot, Davos, CH.
The data cover the winter seasons between 1999-2017 and include the simulated annual frequencies of new snow, wind slab, persistent weak layer, aging-persistent weak layer and wet snow problem types.
The data are shown in Figure 8 in Reuter et al. (2021).

en:
Avalanche problem types were derived from snow cover simulations with the models Crocus and SNOWPACK at the Weissfluhjoch study plot, Davos, CH. The data include annual frequencies of avalanche problem types for the seasons 1999-2017 and daily presence of avalanche problem types for the period 01.01.2016 - 30.04.2016.
Avalanche activity was derived from two seismic sensor arrays deployed no further than 15 km from Weissfluhjoch, Davos, CH. The data cover the period 01.01.2016 - 30.04.2016.

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

avalanche-danger

display_name: avalanche-danger

avalanche-problem-type

display_name: avalanche-problem-type

crocus

display_name: crocus

snow

display_name: snow

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability

snowpack

display_name: snowpack

weissfluhjoch

display_name: weissfluhjoch

educ

en: Education, culture and sport

en: Simulated avalanche problem types and seismic avalanche activity around Weissfluhjoch


disdrometer-data-davos-wolfgang

title_for_slug: disdrometer-data-davos-wolfgang

en: precipitation disdrometer raclets davos fall-velocity

en: Disdrometer Data Davos Wolfgang

en:
The zip folder contains one netCDF file per day for Davos Wolfgang from February 8 to March 19 2019 with a temporal resolution of 30 seconds (time in UTC) and includes:

- characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...)
- precipitation rate
- radar reflectivity
- visibility range
- weather codes
- instrument performance

en: The dataset contains information on precipitation amount and type for Davos Wolfgang (LON: 9.853594, LAT: 46.835577) from February 8 to March 19 2019. It includes: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

davos

display_name: davos

disdrometer

display_name: disdrometer

fall-velocity

display_name: fall-velocity

precipitation

display_name: precipitation

raclets

display_name: raclets

envidat

en: EnviDat: the Environmental Data Portal


maintainer: Océane Hames

en: openfoam antarctica snow-deposition mosaic arctic-sea-ice snow-transport

en: MOSAiC Met City preliminary (Level 2) wind data

en:
Extract from the preliminary MOSAiC atmospheric data (Level 2) for the time period 6th to 13th of November, 2019.
This data was used to set up the fluid forcing parameters in the snowBedFoam simulations on MOSAiC sea ice. It is being published in this repository with the kind permission from Matthew Shupe and his team.
The final processed and quality controlled version of this dataset (Level 3) has not been published yet. A complete reference will be added in this description once it is released.

en: Snowdrift measurements around Neumayer Station III

en: Files containing the topographical data barometrically measured in June 2009 around the German Antarctic Research station Neumayer III. Those measurements are compared to the snowBedFoam simulations to assess the ability of the model to reproduce real snow distribution observations.

en:
OpenFOAM-2.3.0. scripts containing the implemented Eulerian-Lagrangian snow transport model.

The code file provided here is not updated. The most recent version of the script can be found on the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/atmospheric-models/snowbedfoam-v1-0.git

en: Neumayer III simulations

en:
Snow distribution results around Neumayer Station III obtained for the sensitivity analysis and comparison to measurements. The file contains several sub-folders, namely:
-COMP: simulation output for the comparison to measurements;
-FLOW: simulation output for the study of wind forcing impact;
-simulation_exampleCase: example case of a snowBedFoam simulation with the reference Neumayer Station mesh;
-SNOW: simulation output for the study of snow properties impact;
-STRUCT: simulation output for the study of structure properties impact.

en:
OpenFOAM-5.0 scripts containing the implemented Eulerian-Lagrangian snow transport model.
The code file provided here is not updated. The most recent version of the script can be found on the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/atmospheric-models/snowbedfoam-v1-0.git

en: Paper Draft

en: This is the initial draft of the paper where the snowBedFoam 1.0. results are tested against Terrestrial Laser Scan (TLS) measurements of snow dynamics on Arctic sea ice (MOSAiC expedition). It highlights the numerical limitations of our model as well as the measurement uncertainties, which may occur in such extreme environments.

en:
snowBedFoam 1.0. is a snow transport solver implemented in the computational fluid dynamics software OpenFOAM. It is adapted from the standard multi-phase flow solver DPMFoam for application in snow-influenced environments.
To simulate aeolian snow transport, snowBedFoam 1.0. handles coupled Eulerian–Lagrangian phases, which involve a finite number of particles (snow) spread in a continuous phase (air). The snow erosion and deposition are modelled through physics-based equations similar to the ones employed in the well-established LES-Lagrangian Stochastic Model (Comola and Lehning, 2017 ; Sharma et al., 2018 ; Melo et al., 2022). This modelling approach is computationally intensive and thus adapted to simulate snow movement and distribution on small scale terrain.
First, snowBedFoam 1.0. was applied to topographical data collected on Arctic sea ice during the MOSAiC expedition (Clemens-Sewall, 2021). Together with atmospheric data from the MOSAiC Met City (Shupe et al., 2021) used for the fluid forcing, the model was able to accurately simulate the zones of erosion and deposition of snow along a complex ice ridge structure (Hames et al., 2022).
Second, snowBedFoam 1.0. was used to simulate the snow distribution around the German Antarctic research station Neumayer Station III. The effect of snow properties, fluid forcing and aerodynamic structures on the snow accumulation were assessed.
snowBedFoam 1.0 was implemented in 2 different OpenFOAM versions, namely OpenFOAM-2.3.0 and OpenFOAM-5.0. The latter offers more options for turbulence models and boundary conditions. The fundamental model equations were not changed from one implementation to the other, thus both still correspond to snowBedFoam 1.0. The two branches are called snowBedFoam-v1-2.3.0 (OpenFOAM-2.3.0) and snowBedFoam-v1-5.0 (OpenFOAM-5.0). The core codes of snowBedFoam 1.0. are directly accessible on the WSL/SLF GitLab repository (more details in the Resources section).

antarctica

display_name: antarctica

arctic-sea-ice

display_name: arctic-sea-ice

mosaic

display_name: mosaic

openfoam

display_name: openfoam

snow-deposition

display_name: snow-deposition

snow-transport

display_name: snow-transport

envidat

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

en: snowBedFoam: an OpenFOAM Eulerian-Lagrangian solver for modelling snow transport


en: spatially-distributed-sampling geochemical-solutes stable-water-isotopes precipitation stream-water

en: The dataset contains daily measurements of volumes, isotopes and solutes of stream water as well as precipitation measured several locations; meteorological variables are added. Date: 18.07.2019

en:
This dataset contain measurements of solute and stable water isotopes in stream water and precipitation in the Alp catchment and two of its tributaries (between 2015 -2018) . The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l. The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (precipitation rates, discharge) at daily intervals from several sampling locations.
An updated version of the isotope dataset is available here: https://www.doi.org/10.16904/envidat.242

geochemical-solutes

display_name: geochemical-solutes

spatially-distributed-sampling

display_name: spatially-distributed-sampling

stable-water-isotopes

display_name: stable-water-isotopes

stream-water

display_name: stream-water

educ

en: Education, culture and sport

en: Daily data of solute and stable water isotopes in stream water and precipitation in the Alp catchment, Central Switzerland


en: rainfall illgraben surge-waves debris-flow radar

en: Radar-based flow height measurement of debris flow at CD28 at Illgraben. Flow height is derived relative to pre-event channel-bed elevation. Sensor location: 46.309677N, 7.633304E

en: Cumulative rainfall measured at CD1 in the Illgraben catchment. Sensor location: 46.283287N / 7.619689E

en:
This dataset contains measurements from two debris flows recorded in 2024 at the Illgraben debris-flow observatory in Switzerland. The first debris flow was recorded on 15 June 2024 and the second debris flow was recorden on 21 June 2024.

This dataset contains the following reseach data for both:
a) Cummulative rainfall measured at CD1 in the catchment.
b) Radar-based flow height of debris flows measured at CD28.

Abstract
In recent years, the destructive impact of debris flows in alpine regions has become increasingly evident. Surge waves within debris flows increase peak discharge and magnify the hazard potential. Hence, understanding the dynamic complexity of debris flows is crucial to mitigate their risk. In order to capture the dynamic processes involved in the formation and interaction of surge waves, it is necessary to obtain distributed observations in the spatiotemporal domain. In this study, we present near-torrent distributed seismic measurements to monitor the Illgraben channel located in the Swiss Alps. With 33 nodal sensors, we detected and tracked surge waves along a 2-kilometer torrent section across the Illgraben fan, which allowed us to gain valuable new insights into the spatial scales relevant for surge wave formation and their long-distance propagation characteristics. We observed erosion-deposition waves that emerged out of the muddy flow tail and propagated with constant velocity along the torrent, reaching meter-scale flow heights within only 100s of meters of flow distance which significantly impact the hazard potential of debris flows. Our results provide valuable observations of surge waves from their formation to their annihilation. We can differentiate flow regimes based on their seismic signature and track them along the torrent, thus mapping the debris-flow evolution in time and space. The observations elucidate large-scale debris flow dynamics thus improving our understanding of hazard potential and the effectiveness of structural countermeasures.

debris-flow

display_name: debris-flow

illgraben

display_name: illgraben

radar

display_name: radar

rainfall

display_name: rainfall

surge-waves

display_name: surge-waves

envidat

en: EnviDat: the Environmental Data Portal

en: Debris flow observation at Illgraben 2024: Event Data 15 June / 21 June


en: digital-elevation-model geoinformation-system open-source digital-planning swiss-geodata seilaplan qgis-plugin cable-yarding wms-data

en: WMS-Layer als Hintergrundkarten laden

en: View video on youtube!

en:
In order to digitally plan a cable line using the QGIS plugin ‘Seilaplan’, maps with various background information are helpful. In this tutorial we show you how to obtain maps that are helpful for cable line planning, for example a national map of Switzerland at different scales, the NFI vegetation height model or the NFI forest mix rate. For this we explain what WMS datasets are and how to integrate them into QGIS. No download of large data is needed for this, only a good internet connection. Please note that the tutorial language is German!

Link for the integration of WMS data: https://wms.geo.admin.ch/

Link to the description on the Swisstopo website:
https://www.geo.admin.ch/en/geo-services/geo-services/portrayal-services-web-mapping/web-map-services-wms.html

Link to the Seilaplan website: https://seilaplan.wsl.ch

**************************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung sind verschiedene Hintergrundkarten hilfreich. In diesem Tutorialvideo zeigen wir, was WMS Daten sind und wie man diese in QGIS einbinden kann. Dafür müssen die Daten nicht heruntergeladen werden. Es braucht lediglich eine gute Internetverbindung. Für die Seillinienplanung hilfreiche Karten sind bspw. die Landeskarte der Schweiz in verschiedenen Massstäben, das Vegetationshöhenmodell LFI oder der Waldmischungsgrad LFI.

Link zur Einbindung der WMS Daten: https://wms.geo.admin.ch/

Link zur Beschreibung auf der Swisstopo Webseite: https://www.geo.admin.ch/de/geo-dienstleistungen/geodienste/darstellungsdienste-webmapping-webgis-anwendungen/web-map-services-wms.html

Link zur Seilaplan-Website: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

wms-data

display_name: wms-data

en: Seilaplan Tutorial: Load WMS layers as background maps


maintainer: Sebastian Schlögl

en: stable-boundary-layer atmospheric-turbulence snow atmosphere turbulent-sensible-heat-fluxes

en: Turbulence data GR00

en: sensor in 2 m height

en: Turbulence data AA00

en: sensor in 25 m height

en: Turbulence data WFJ07

en: lower sensor

en: upper sensor

en: sensor in 1 m height

en: Turbulence data PM07

en: SEE

en: NWW

en: sensor in 0.2 m height

en: Turbulence data WFJ11

en:
We used five different atmospheric turbulence datasets from four test sites, with these sites showing differences in their topographical characteristics. We chose one typical alpine test site with high topographical complexity (Weissfluhjoch, Davos, Switzerland) and three test sites consisting of one glacier site (Plaine Morte, Crans-Montana, Switzerland) and two polar sites (Greenland and Antarctica) representing a quasi-ideal site with homogeneous surface and quasi infinite fetch in all directions.
The turbulent sensible heat flux was calculated using the eddy-covariance method. Note that the sonic temperature fluctuations have been converted into virtual temperature fluctuations.
Three-dimensional wind velocity and air temperature were processed using a linear detrending (Rannik and Vesala, 1999) and a planar fit approach (Massmann and Lee, 2002) to rotate the coordinate system. Air temperature, relative humidity and air pressure from weather stations were used to calculate air properties, which are required for the data processing. The weather stations are located in the immediate vicinity of the turbulence tower and are affected by the same air masses. Turbulence data were averaged to 30-min intervals, whilst changing to a 15-min time interval marginally affects the heat fluxes at the Weissfluhjoch test site (Mott et al., 2011). Note that we define a negative sensible heat flux as being directed towards the snow surface and a positive sensible heat flux as being directed upwards.
The selected datasets and corresponding test sites are briefly introduced below:

Weissfluhjoch 2007 (WFJ07): A vertical set-up of two three-dimensional ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) was used at the traditional field site Weissfluhjoch (2540 m asl.) to measure three-dimensional wind velocity and air temperature at a frequency of 20 Hz. The sensors were mounted 3 m and 5 m above the ground and provided reliable data for 50 days between 11 February 2007 and 24 April 2007. Further information on the field campaign can be found in Stössel et al. (2010) and Mott et al. (2011).

Weissfluhjoch 2011-13 (WFJ11): Three-dimensional wind velocity and air temperature were recorded at 5 m above the ground at a frequency of 10 Hz with a three-dimensional ultrasonic anemometer (CSAT3). The analysis was conducted for data obtained between February and March in the years 2011-13.

Plaine Morte 2007 (PM07): Two three-dimensional ultrasonic anemometers (CSAT3) were installed on a horizontal boom facing opposite directions (west-north-west vs. east-south-east) at 3.75 m above the ground to measure air temperature and three-dimensional wind velocity at 20 Hz. The data were collected at the almost flat field site on the Plaine Morte glacier (2750 m asl.) near Crans-Montana, Switzerland from February to April 2007. High quality meteorological data were additionally recorded and used to force the model. A detailed description about the set-up at the Plaine Morte glacier can be found in Huwald et al. (2009) and Bou-Zeid et al. (2010).

Greenland 2000 (GR00): High-frequency three-dimensional ultrasonic anemometer measurements (CSAT3) were recorded at 50 Hz at the Summit Camp (72.3 °N, 38.8 °W, 3208 m asl.) located on the northern dome of the Greenland ice sheet. Data were collected at 1 m and 2 m above the snow surface during summer in 2000 and 2001. Additionally, meteorological measurements were obtained for the post processing and used to force the model. More information about the field campaign can be found in Cullen et al. (2007, 2014).

Antarctica 2000 (AA00): A set-up of three vertical three-dimensional ultrasonic anemometers (DA-600, Kaijo Denki) were installed at Mizuho Station (70°42' S, 44°20' E, 2230 m asl.) in Eastern Antarctica at 0.2, 1 and 25 m and recorded turbulence data at a frequency of 100 Hz from October to November 2000. Longwave and shortwave radiation, relative humidity, air and snow surface temperature were additionally measured and used to force the model. More information about the field campaign can be found in Nishimura and Nemoto (2005).

atmosphere

display_name: atmosphere

atmospheric-turbulence

display_name: atmospheric-turbulence

snow

display_name: snow

stable-boundary-layer

display_name: stable-boundary-layer

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

envidat

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

en: How do stability corrections perform in the stable boundary layer over snow?


defoliation-growth-data

title_for_slug: defoliation-growth-data

en: literature-review forest-health relative-growth tree-growth defoliation

en:
Using a literature review extracted data from 26 published papers which had data on individual tree defoliation and growth relationships In Europe.
This data set includes 415 defoliation-growth data points from 16 different tree species covering 15+ countries in Europe. Growth metrics used in individual papers were different, and included increments in terms of volume, tree rings width, radial growth, basal area and biomass. All growth metrics were converted into relative growth (presented in this dataset), expressed as a percentage of the growth of progressively defoliated trees in relation to the growth of those trees adopted as reference (control) defoliation level (i.e. the growth of the lowest defoliation level in each study was used as the reference growth point).

defoliation

display_name: defoliation

forest-health

display_name: forest-health

literature-review

display_name: literature-review

relative-growth

display_name: relative-growth

tree-growth

display_name: tree-growth

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal

en: Defoliation-Growth data