energiedashboard-ch-energiepreise

title_for_slug: energiedashboard.ch: Energiepreise

de: ogd106-bfe strom gas mineralol treibstoffe

fr: energiedashboard.ch: Prix de l'énergie

de: energiedashboard.ch: Energiepreise

en: energiedashboard.ch: Energy prices

label: European Power Exchange

label: European Energy Exchange - Gas

label: European Energy Exchange - Strom

fr: Indice des prix du Diesel: Consommation finale (indice national des prix à la consommation)

de: Dieselpreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index Diesel final consumption (national consumer price index)

it: Indice dei prezzi del Diesel per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix finaux du diesel selon l'indice des prix à la consommation en Suisse

en: Development of end consumer prices for diesel according to the national consumer price index in Switzerland

de: Entwicklung der Endverbraucherpreise Diesel gemäss Landesindex der Konsumentenpreise in der Schweiz

it: Andamento dei prezzi al consumo finale del diesel in base all'indice nazionale dei prezzi al consumo in Svizzera

fr: Prix du gaz TTF "premier mois" (indexé)

de: Gaspreis TTF «Frontmonat» (indexiert)

en: Gas price TTF "front month" (indexed)

it: Prezzo del gas TTF "mese anteriore" (indicizzato)

fr: Évolution des prix du gaz sur le point d'échange TTF pour le mois suivant, c'est-à-dire les prix du gaz à l'achat pour la livraison du mois suivant. Les prix sont indexés sur le prix moyen 2019-2020

en: Development of gas prices on the TTF trading point for the following month, i.e. the gas prices in the purchase for delivery in the coming month. The prices are indexed to the average price 2019-2020

de: Entwicklung der Gaspreise auf dem TTF Handelspunkt für den Folgemonat, also die Gaspreise im Einkauf für die Lieferung im kommenden Monat. Die Preise sind indexiert auf den Durchschnittspreis 2019-2020.

it: Sviluppo dei prezzi del gas sul punto di negoziazione TTF per il mese successivo, ossia i prezzi del gas nell'acquisto per la consegna nel mese successivo. I prezzi sono indicizzati al prezzo medio del 2019-2020

fr: Indice des prix de la consommation finale de gaz (indice national des prix à la consommation)

de: Gaspreisindex Endverbraucher (Landesindex Konsumentenpreise)

en: Price index gas final consumption (national consumer price index)

it: Indice dei prezzi del gas per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix du gaz à la consommation finale indexés selon l'indice des prix à la consommation en Suisse. La base est le prix en décembre 2020 (=100)

en: Development of end consumer prices for gas indexed according to the national consumer price index in Switzerland. The basis is the prices in December 2020 (=100)

de: Entwicklung der Endverbraucherpreise Gas indexiert gemäss Landesindex der Konsumentenpreise in der Schweiz. Basis sind die Preise im Dezember 2020 (=100)

it: Andamento dei prezzi al consumo finali del gas indicizzati secondo l'indice nazionale dei prezzi al consumo in Svizzera. La base è costituita dai prezzi del dicembre 2020 (=100)

fr: Prix de l'électricité sur le marché spot "Day Ahead" Base Suisse

de: Strompreis Spotmarkt «Day Ahead» Base

en: Electricity Price Spot Market "Day Ahead" Base Switzerland

it: Prezzo dell'elettricità Mercato spot "Day ahead" Base Svizzera

fr: Évolution des prix de détail de l'électricité indexés selon l'indice des prix à la consommation en Suisse. La base est le prix en décembre 2020 (=100)

en: Development of electricity end-user prices indexed according to the national consumer price index in Switzerland. The basis is the prices in December 2020 (=100)

de: Entwicklung der Strompreise auf den Spotmärkten für «day ahead» Preise, also die Strompreise im Einkauf für den Konsum morgen.

it: Andamento dei prezzi dell'elettricità per gli utenti finali, indicizzati secondo l'indice nazionale dei prezzi al consumo in Svizzera. La base è costituita dai prezzi del dicembre 2020 (=100)

fr: Indice des prix du mazout Consommation finale (indice national des prix à la consommation)

de: Heizölpreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index for final heating oil consumption (national consumer price index)

it: Indice dei prezzi per il consumo finale di gasolio da riscaldamento (indice nazionale dei prezzi al consumo)

fr: Évolution des prix du mazout à la consommation finale indexés selon l'indice des prix à la consommation en Suisse. La base est le prix en décembre 2020 (=100)

en: Development of end consumer prices for heating oil indexed according to the national consumer price index in Switzerland. The basis is the prices in December 2020 (=100)

de: Entwicklung der Endverbraucherpreise Heizöl indexiert gemäss Landesindex der Konsumentenpreise in der Schweiz. Basis sind die Preise im Dezember 2020 (=100)

it: Andamento dei prezzi finali al consumo per il gasolio da riscaldamento, indicizzati secondo l'indice nazionale dei prezzi al consumo in Svizzera. La base è costituita dai prezzi del dicembre 2020 (=100)

fr: Indice des prix de l'essence Consommation finale (indice national des prix à la consommation)

de: Benzinpreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index petrol final consumption (national consumer price index)

it: Indice dei prezzi della benzina per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix de détail de l'essence indexés selon l'indice des prix à la consommation en Suisse. La base est le prix en décembre 2020 (=100)

en: Development of end consumer prices for petrol indexed according to the national consumer price index in Switzerland. The basis is the prices in December 2020 (=100)

de: Entwicklung der Endverbraucherpreise Benzin indexiert gemäss Landesindex der Konsumentenpreise in der Schweiz. Basis sind die Preise im Dezember 2020 (=100)

it: Andamento dei prezzi al consumo finali della benzina indicizzati secondo l'indice nazionale dei prezzi al consumo in Svizzera. La base è costituita dai prezzi del dicembre 2020 (=100)

fr: Indice des prix de l'électricité Consommation finale (indice national des prix à la consommation)

de: Strompreisindex Endverbraucher (Landesindex Konsumentenpreise)

en: Price index electricity final consumption (national consumer price index)

it: Indice dei prezzi dei consumi finali di elettricità (indice nazionale dei prezzi al consumo)

de: Entwicklung der Endverbraucherpreise Strom indexiert gemäss Landesindex der Konsumentenpreise in der Schweiz. Basis sind die Preise im Dezember 2020 (=100)

fr: Indice des prix du bois de chauffage: Consommation finale (indice national des prix à la consommation)

de: Brennholzpreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index firewood final consumption (national consumer price index)

it: Indice dei prezzi della legna da ardere per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix finaux du bois de chauffage selon l'indice des prix à la consommation en Suisse

en: Development of end consumer prices for firewood according to the national consumer price index in Switzerland

de: Entwicklung der Endverbraucherpreise Brennholz gemäss Landesindex der Konsumentenpreise in der Schweiz

it: Andamento dei prezzi al consumo finale della legna da ardere in base all'indice nazionale dei prezzi al consumo in Svizzera

fr: Indice des prix du chauffage à distance: Consommation finale (indice national des prix à la consommation)

de: Fernwärmepreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index district heating final consumption (national consumer price index)

it: Indice dei prezzi del teleriscaldamento per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix finaux du chauffage à distance selon l'indice des prix à la consommation en Suisse

en: Development of end consumer prices for district heating according to the national consumer price index in Switzerland

de: Entwicklung der Endverbraucherpreise fernwärme gemäss Landesindex der Konsumentenpreise in der Schweiz

it: Andamento dei prezzi al consumo finale del teleriscaldamento in base all'indice nazionale dei prezzi al consumo in Svizzera

fr:
Les prix de l'énergie sur les marchés sont un indicateur important de la situation actuelle du marché et de l'approvisionnement en Europe et en Suisse. L'offre (production) y est combinée à la demande (consommation) et donne en fin de compte un prix pour un produit énergétique donné. Il existe des marchés pour différents produits. Les marchés spot donnent des signaux à court terme du marché : le marché "day ahead" indique le prix de gros pour le lendemain. Les prix du produit "Base" indiquent la moyenne arithmétique des prix pour une livraison dans les 24 heures suivantes. Le marché intrajournalier consiste à acheter et à vendre de l'énergie qui sera livrée le jour même.

Ce recueil de données fournit des informations sur différentes sources d'énergie. Il s'agit de l'électricité, du gaz, du mazout, du diesel et de l'essence. Différentes données sont utilisées à cet effet. Pour l'électricité et le gaz, ce sont les données des bourses qui sont utilisées. Contrairement aux prix de l'électricité, les données sur les prix du gaz sont référencées sur une année de base, car des questions de licence doivent encore être réglées. D'autres données sur les prix sont obtenues auprès de l'Office fédéral de la statistique.

Les prix de l'électricité et du gaz ne constituent toutefois pas directement le prix de détail que les clients privés et professionnels paient à leur entreprise locale de distribution d'énergie. Ces prix de détail dépendent entre autres de la stratégie d'approvisionnement (achat à long terme ou achat à court terme sur le marché) de l'entreprise locale d'approvisionnement en énergie. Dans le cas de l'électricité, le prix de détail dépend également de la part d'électricité produite dans les centrales électriques de l'entreprise, de la qualité de l'électricité (renouvelable ou non), des coûts de réseau et des taxes.

En ce qui concerne les prix de détail, l'indice des prix à la consommation (IPC) est déterminant. Il mesure l'évolution des prix (renchérissement) des biens et services importants pour les ménages privés (panier-type). Il indique de combien les biens de consommation ont augmenté par rapport au mois précédent, à l'année précédente ou à toute autre date antérieure. L'indice est basé sur le mois de décembre 2020. L'évolution des prix est mesurée à l'aide du panier de biens et services, qui comprend également les principales sources d'énergie - donc aussi l'électricité. La méthode de calcul est gérée par l'Office fédéral de la statistique.

en:
Energy prices on the markets are an important indicator of the current market and supply situation in Europe and Switzerland. Supply (production) is combined here with demand (consumption) and ultimately results in a price for a specific energy product. There are markets for different products. The spot markets give short-term signals from the market: the "Day Ahead" market indicates the wholesale price for the following day. The "Base" product prices indicate the arithmetic mean of the prices for a delivery in the following 24 hours. In intraday trading, energy is bought and sold for delivery on the same day.

This data collection provides information on various energy sources. These include electricity (power), gas, heating oil, diesel and petrol. Different data are used for this purpose. For electricity and gas, data from the stock exchanges are used. In contrast to electricity prices, the data on gas prices are referenced to a base year, as licensing issues still need to be clarified. Other price data is obtained from the Federal Statistical Office.

However, the prices for electricity and gas do not directly result in the end consumer price that private and commercial customers pay to their local energy supply company. These end-customer prices depend, among other things, on the procurement strategy (long-term purchases or short-term purchases on the market) of the local energy supply company. In the case of electricity, the end-user price also depends on the share of electricity produced in the utility's own power plants, the quality of the electricity (renewable or not), the grid costs and levies.

The national consumer price index (CPI) is decisive for end customer prices. It measures the price development (inflation) of goods and services that are important for private households (basket of goods). It shows by how much consumer goods have become more expensive compared to the previous month, the previous year or any other earlier point in time. The index is based on December 2020. The price development is measured on the basis of the basket of goods, which also includes the most important energy sources - i.e. also electricity. The calculation methodology is managed by the Federal Statistical Office.

de:
Die Energiepreise an den Märkten sind ein wichtiger Indikator für die aktuelle Markt- und Versorgungssituation in Europa und der Schweiz. Angebot (Produktion) wird hier mit der Nachfrage (Verbrauch) zusammengeführt und ergibt letztlich einen Preis für ein bestimmtes Energieprodukt. Es gibt Märkte für unterschiedliche Produkte. Die Spotmärkte geben kurzfristige Signale des Marktes wieder: Der «Day Ahead»-Markt gibt den Grosshandelspreis für den Folgetag an. Die Preise des Produktes «Base» geben das arithmetische Mittel der Preise für eine Lieferung in den folgenden 24 Stunden an. Beim Intraday-Handel wird Energie gekauft und verkauft, die noch am gleichen Tag geliefert wird.

Diese Datensammlung stellt Informationen zu verschiedenen Energieträgern bereit. Diese umfassen Elektrizität (Strom), Gas, Heizöl, Diesel und Benzin. Dabei werden unterschiedliche Daten herangezogen. Für Strom und Gas werden Daten der Börsen herangezogen. Die Daten zu den Gaspreisen sind im Gegensatz zu den Strompreise referenziert auf ein Basisjahr, da noch Lizenzfragen zu klären sind. Weitere Preisdaten werden vom Bundesamt für Statistik bezogen.

Die Preise für Strom und Gas ergeben allerdings nicht direkt den Endverbraucherpreis, den die Privat- und Gewerbekunden ihrem lokalen Energieversorgungsunternehmen bezahlen. Diese Endkundenpreise hängen unter anderem von der Beschaffungsstrategie (langfristig eingekauft oder kurzfristig am Markt besorgt) des lokalen Energieversorgungsunternehmen ab. Beim Strom hängt der Endverbrauchpreis auch vom Anteil an in eigenen Kraftwerken produzierten Strom, von der Qualität des Stromes (erneuerbar oder nicht), von den Netzkosten und Abgaben ab.

Hinsichtlich der Endkundenpreise ist der Landesindex der Konsumentenpreise (LIK) massgebend. Er misst die Preisentwicklung (Teuerung) der für die privaten Haushalte bedeutsamen Waren und Dienstleistungen (Warenkorb). Er zeigt, um wie viel die Konsumgüter gegenüber dem Vormonat, dem Vorjahr oder jedem anderen früheren Zeitpunkt teurer geworden sind. Der Index ist auf den Dezember 2020 bezogen. Die Preisentwicklung wird anhand des Warenkorbs gemessen, der auch die wichtigsten Energieträger - also auch Strom - enthält. Die Berechnungsmethodik wird durch das Bundesamt für Statistik verwaltet.

it:
I prezzi dell'energia sui mercati sono un importante indicatore dell'attuale situazione del mercato e dell'offerta in Europa e in Svizzera. L'offerta (produzione) si combina con la domanda (consumo) e alla fine si ottiene il prezzo di uno specifico prodotto energetico. Esistono mercati per prodotti diversi. I mercati spot forniscono segnali a breve termine dal mercato: il mercato "Day Ahead" indica il prezzo all'ingrosso per il giorno successivo. I prezzi dei prodotti "Base" indicano la media aritmetica dei prezzi per una consegna nelle 24 ore successive. Nel trading intraday, l'energia viene acquistata e venduta per la consegna nello stesso giorno.

Questa raccolta dati fornisce informazioni su varie fonti energetiche. Questi includono l'elettricità (corrente), il gas, il gasolio per riscaldamento, il diesel e la benzina. A tal fine vengono utilizzati diversi dati. Per l'elettricità e il gas si utilizzano i dati delle borse valori. A differenza dei prezzi dell'elettricità, i dati sui prezzi del gas sono riferiti a un anno base, poiché le questioni relative alle licenze devono ancora essere chiarite. Altri dati sui prezzi sono stati ottenuti dall'Ufficio federale di statistica.

Tuttavia, i prezzi dell'elettricità e del gas non si traducono direttamente nel prezzo al consumo finale che i clienti privati e commerciali pagano alla loro società di fornitura energetica locale. Questi prezzi per i clienti finali dipendono, tra l'altro, dalla strategia di approvvigionamento (acquisti a lungo termine o acquisti a breve termine sul mercato) dell'azienda fornitrice di energia locale. Nel caso dell'elettricità, il prezzo per l'utente finale dipende anche dalla quota di elettricità prodotta nelle centrali elettriche dell'azienda, dalla qualità dell'elettricità (rinnovabile o meno), dai costi di rete e dai prelievi.

L'indice nazionale dei prezzi al consumo (CPI) è determinante per i prezzi al cliente finale. Misura l'andamento dei prezzi (inflazione) di beni e servizi importanti per le famiglie (paniere di beni). Indica di quanto i beni di consumo sono diventati più costosi rispetto al mese precedente, all'anno precedente o a qualsiasi altro momento precedente. L'indice si basa su dicembre 2020. L'andamento dei prezzi è misurato sulla base di un paniere di beni che comprende anche le fonti energetiche più importanti, cioè anche l'elettricità. La metodologia di calcolo è gestita dall'Ufficio federale di statistica.

econ

fr: Économie et finances

it: Economia e finanze

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

it: Ufficio federale dell'energia UFE

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

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


en: sublimation latent-heat snow weissfluhjoch post-depositional-processes stable-water-isotopes natural-tracer paleoclimate

state: active

type: dataset

media_type: application/pdf

en:
Details on the data collected during the different field campaigns and available in this dataset.
Information on the sampling procedure of the snow isotopes samples.

format: PDF

en: Details about the different folders

format: SERVICE

en: Stable water isotopes in snow

media_type: application/zip

en: Stable water isotopes in snow measurements

format: ZIP

en: Stable water isotopes in vapor

en:
Stable water isotopes in vapor measurements. Processed (calibrated) and raw data for February - June 2017. Raw data for January and February 2020.
For the time in between July 2017 and April 2020, raw vapor isotopic measurements are available, but no calibrations were performed during that time. For data delivery, please contact one of the authors.
This folder also contains the post-processing scripts for stable water isotopes in vapor measurements.

en: Weather

en: Meteorological data, snow height measurement, and SNOWPACK simulations covering the different field campaigns.

en:
Notice: Changes to the dataset are still possible. Please do not use this dataset until the final publication with a DOI. Contact the authors if you have questions about this.

This dataset contains measurements of stable water isotopes in snow and vapor on the Weissfluhjoch from different field campaigns (Winter 2017 (Trachsel, 2019), January 2020, December 2020, and March 2021 (Sadowski et al., 2022).
Snow profiles and surface samples are available at different frequencies for each campaign. Please see "Data_description.pdf" for details.

Scripts and SNOWPACK simulations used in (Trachsel, 2019) and (Sadowski et al., 2022) are also provided.

latent-heat

display_name: latent-heat

natural-tracer

display_name: natural-tracer

paleoclimate

display_name: paleoclimate

post-depositional-processes

display_name: post-depositional-processes

snow

display_name: snow

stable-water-isotopes

display_name: stable-water-isotopes

sublimation

display_name: sublimation

weissfluhjoch

display_name: weissfluhjoch

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: Stable Water Isotopes in snow and vapor on the Weissfluhjoch


maintainer: Sebastian Schlögl

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

en: Turbulence data WFJ07

en: lower sensor

mimetype: application/zip

en: Turbulence data PM07

en: SEE

en: Turbulence data AA00

en: sensor in 1 m height

en: Turbulence data WFJ11

en: NWW

en: sensor in 25 m height

en: upper sensor

en: sensor in 0.2 m height

en: Turbulence data GR00

en: sensor in 2 m height

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

stable-boundary-layer

display_name: stable-boundary-layer

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

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


maintainer: Yohann Chauvier

en: range-maps r-package species-observations gbif conservation landsca taxonomy ecoregions large-scale hard-limit accepted-name occurrence-records synonyms flags filtering species-distribution

en: gbif.range R package version 0.2 (deprecated)

en: gbif.range R package version 1.1 (current)

en: GitHub URL

en: wsl.gbif R package version 0.1 (deprecated)

en: Test version, not to be used.

en: Although species range may be obtained using expert maps or modeling methods, expert data is often species-limited and statistical models need more technical expertise as well as many species observations. When unavailable, such information may be extracted from the Global Biodiversity Information facility (GBIF), the largest public data repository inventorying georeferenced species observations worldwide. However, retrieving GBIF records at large scale may be tedious if users are unaware of specific tools and functions that need to be employed. Here we present *gbif.range*, an R library that contains automated methods to generate species range maps from scratch using in-house ecoregions shapefiles and an easy-to-use GBIF download wrapper. Finally, this library also offers a set of additional very useful parameters and functions for large GBIF datasets (generate doi, extract GBIF taxonomy, records filtering...). [gbif.range R project](https://github.com/8Ginette8/gbif.range)

accepted-name

display_name: accepted-name

conservation

display_name: conservation

ecoregions

display_name: ecoregions

filtering

display_name: filtering

flags

display_name: flags

gbif

display_name: gbif

hard-limit

display_name: hard-limit

landsca

display_name: landsca

large-scale

display_name: large-scale

occurrence-records

display_name: occurrence-records

r-package

display_name: r-package

range-maps

display_name: range-maps

species-distribution

display_name: species-distribution

species-observations

display_name: species-observations

synonyms

display_name: synonyms

taxonomy

display_name: taxonomy

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: gbif.range - An R package to generate species range maps based on ecoregions and a user-friendly GBIF wrapper


maintainer: EnviDat Support

en: cmip5 precipitation-amount climate-change air-temperature orographic-precipitation

en: Data Access

en:
Predicting future climatic conditions at high spatial resolution is essential for many applications in science. Here we present data for monthly time series of precipitation and minimum and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation sums at ~5km spatial resolution globally for the years 1850-2100. We validated the performance of the downscaling algorithm by comparing model output with observed climates for the years 1950-2069.

CHELSA_cmip5_ts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

climate-change

display_name: climate-change

orographic-precipitation

display_name: orographic-precipitation

precipitation-amount

display_name: precipitation-amount

en: High resolution monthly precipitation and temperature timeseries for the period 2006-2100


maintainer: Esther Frei

en: long-term-experiment afforestation mountain-forest treeline stillberg

mimetype: application/x-zip-compressed

en:
 Background information

The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Long-term monitoring of the large-scale high-elevation afforestation has generated data about tree growth, survival, and vitality. In addition, detailed characteristics of the microsite conditions of the research were conducted. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone.

 Experiment description

The Stillberg afforestation experiment was established in 1975 by planting 92,000 seedlings of *Larix decidua*, *Pinus cembra* and *Pinus mugo* ssp. *uncinata* in the alpine treeline ecotone. The afforestation site is located on a northeast-facing slope with steep, topographically highly structured terrain and covers elevations from 2075 to 2230 m a.s.l. The afforestation site was divided into 4052 square plots of 3.5 × 3.5 m, arranged in a regular species-alternating pattern over the whole area. Each plot contained 25 trees of one species (1350 plots per species), and the seedlings were systematically planted 70 cm apart. The trees have been monitored since 1975. Specifically, tree mortality was assessed annually from 1975 until 1995 and has been documented every ten years since then, with surveys in 2005 and 2015 (the next survey is due in 2025). Height of the surviving trees was measured in 1975, 1979, 1982, 1985, 1990, 1995, 2005, and 2015. In 1995, 2005, and 2015, drivers of tree vitality were assessed for a subset of trees per plot. Additionally, an extensive set of environmental parameters characterizing microsite conditions of the afforestation area were recorded before and after the planting of the trees.

 Data description

The five datasets from the afforestation experiment comprise ecological and environmental data from the main afforestation experiment in five datasets with accompanying metadata (Stillberg_afforestation_all_metadata.xlsx). All data and metadata files are bundled in a ZIP-file (Stillberg_afforestation_v1.zip). In particular, a first dataset contains environmental data characterising microsite conditions of the 4000 plots with regard to soil, topography, vegetation and microclimatic conditions (Stillberg_afforestation_plot_data_v1.csv; Stillberg_afforestation_plot_metadata_v1.csv. In each plot, the natural tree regeneration was assessed by counting seedings of several tree species in 2005 and 2015 (Stillberg_afforestation_regeneration_data_v1.csv; Stillberg_afforestation_regeneration_metadata_v1.csv). Furthermore, specific information about each of the 92’000 planted trees of the tree species is available (Stillberg_afforestation_tree_parameter_data_v1.csv; Stillberg_afforestation_tree_parameter_metadata_v1.csv). Survival data for each of the 92’000 individual trees can be found in a separate dataset (Stillberg_afforestation_tree_survival_data_v1.csv; Stillberg_afforestation_tree_survival_metadata_v1.csv). Tree growth and vitality parameters are available for all trees from 1995, and for subsets of trees for 2005 and 2015 (Stillberg_afforestation_tree_measurements_data_v1.csv; Stillberg_afforestation_tree_measurements_metadata_v1.csv).

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline

en: Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland


en: forest shortwave-radiation fractional-snow shading longwave-radiation

en: Seasonal sub-canopy radiation data

en:
Seasonal, spatially aggregated incoming and outgoing shortwave radiation below an evergreen forest stand collected with a cable car system.

The presented data is used and further described in the following paper: Malle et al. (2019). Shading by Trees and Fractional Snow Cover Control the Subcanopy Radiation Budget. Journal of Geophysical Research Atmospheres. DOI:10.1029/2018JD029908.

format: XLS

en: Radiation Data 25.4.2018

en:
Spatiotemporal incoming/outgoing shortwave and longwave radiation as well as sunlit and shaded-snow view fractions below an evergreen forest stand in the Swiss alps. Data was collected on 25th of April 2018 along a 48m long, heterogeneous forest stand under partial snow cover conditions.

The presented data is used and further described in the following paper: Malle et al. (2019). Shading by Trees and Fractional Snow Cover control the Subcanopy Radiation Budget. Journal of Geophysical Research Atmospheres. DOI:10.1029/2018JD029908.

en: Sky-view fraction along the cablecar transect

media_type: text/plain

en: Data is used and described in the following paper: Malle et al. (2019). Shading by Trees and Fractional Snow Cover control the Subcanopy Radiation Budget. Journal of Geophysical Research. DOI:10.1029/2018JD029908.

format: TXT

mimetype: text/plain

en: Radiation Data 18.04.2019

en:
Spatiotemporal incoming/outgoing shortwave and longwave radiation as well as sunlit and shaded-snow view fractions below an evergreen forest stand in the Swiss alps. Data was collected on 18th of April 2018 along a 48m long, heterogeneous forest stand under full snow cover conditions.

The presented data is used and further described in the following paper: Malle et al. (2019). Shading by Trees and Fractional Snow Cover control the Subcanopy Radiation Budget. Journal of Geophysical Research Atmospheres. DOI:10.1029/2018JD029908.

en: This data set consists of incoming and outgoing short- and longwave radiation as well as sunlit-snow-view-fraction as described in the JGR-Atmospheres paper "Shading by trees and fractional snow cover control the sub-canopy radiation budget", by Malle et al. (2019). Data was collected along a 48m long, heterogeneous forest transect between January and June 2018 close to Davos, Switzerland.

forest

display_name: forest

fractional-snow

display_name: fractional-snow

longwave-radiation

display_name: longwave-radiation

shading

display_name: shading

shortwave-radiation

display_name: shortwave-radiation


maintainer: Geoinformationdienst

title_for_slug: Kennzahlen öffentliche Ladeinfrastruktur Elektromobilität

de: kennzahlen-ladeinfrastruktur-schweiz mobilitat e-mobilitat elektromobilitat energie geoinformation erneuerbare-energie bfe gis geodaten statistiken

author: Geoinformationdienst

label: Documentation

fr: Chiffres-clés concernant l’infrastructure de recharge pour la mobilité électrique

en: Key figures about the charging infrastructure for electrical vehicles

it: Indicatori dell'infrastruttura di ricarica per veicoli elettrici

format: CSV

fr: Frictionless datapackage

de: Frictionless datapackage

fr: Frictionless metadata datapackage. See https://frictionlessdata.io/

format: JSON

fr:
La mobilité électrique est une technologie essentielle pour assurer une mobilité plus durable. Elle contribue à l’atteinte des objectifs énergétiques et de politique climatique dans la mesure où les moteurs électriques sont efficaces sur le plan énergétique et où le recours à l’électricité permet d’utiliser une énergie renouvelable. La disponibilité de bornes de recharge publiques constitue un facteur de réussite déterminant pour la diffusion des voitures électriques. À cet effet, l’application https://je-recharge-mon-auto.ch indique en temps réel les bornes de recharge disponibles pour les véhicules électriques.

En Suisse, l’infrastructure de recharge pour les véhicules électriques ne cesse de s’étoffer. Pour documenter cette évolution, les données en temps réel disponibles sur https://je-recharge-mon-auto.ch sont régulièrement analysées et des chiffres-clés concernant l’infrastructure de recharge sont calculés. Ces derniers sont collectés quotidiennement et publiés chaque mois. La collecte a commencé en novembre 2020 et se poursuit actuellement. Les chiffres-clés sont collectés aussi bien à l’échelle nationale que cantonale. Une documentation détaillée est mise à disposition pour une meilleure compréhension des données.

Visualisation des chiffres clés : http://www.je-recharge-mon-auto.ch/statistiques

en:
Electric mobility is a key technology for more sustainable mobility and is one way of achieving ambitious energy and climate policy goals. Electric engines are efficient, and using electricity means that renewable energies can also be used. The availability of public charging stations is a critical factor in the success of the increasingly widespread use of electric cars, which is why https://www.recharge-my-car.ch displays charging station availability for electric vehicles in real time.

The charging infrastructure for electric vehicles in Switzerland is constantly being developed. We use real-time data from https://www.recharge-my-car.ch to regularly evaluate the ever-increasing number of charging stations, charging points, and types of plug in Switzerland. Since November 2020, this data has been and will continue to be collected on a daily basis for the whole of Switzerland and for the individual cantons, and then averaged each month. This gives an overview of how the charging infrastructure is expanding. Detailed documentation is available for a better understanding of the data.

Visualization of the key figures: http://www.recharge-my-car.ch/keydata

de:
Die Elektromobilität ist eine Schlüsseltechnologie für eine nachhaltigere Mobilität und trägt zur Erreichung ambitionierter energie- und klimapolitischer Ziele bei, da Elektroantriebe effizient sind und der Einsatz von Strom die Nutzung erneuerbarer Energien erlaubt. Ein wichtiger Erfolgsfaktor für die Verbreitung von Elektroautos ist die Verfügbarkeit von öffentlichen Ladestationen. Deshalb zeigt https://ich-tanke-strom.ch die Verfügbarkeit von Ladestationen für Elektrofahrzeuge in Echtzeit an.

Die öffentliche Ladeinfrastruktur für Elektrofahrzeuge in der Schweiz wird stetig ausgebaut. Um diese Entwicklung zu dokumentieren, werden die Echtzeit-Daten von https://ich-tanke-strom.ch regelmässig ausgewertet und Kennzahlen zur Ladeinfrastruktur abgeleitet. Die Kennzahlen werden täglich erhoben und anschliessend pro Monat gemittelt. Die Erhebung startete im November 2020 und wird laufend weitergeführt. Die Kennzahlen werden für die ganze Schweiz sowie für die einzelnen Kantone erhoben. Für das bessere Verständnis der Daten steht eine detaillierte Dokumentation bereit.

Visualisierung der Kennzahlen: http://www.ich-tanke-strom.ch/kennzahlen

it:
La mobilità elettrica è una tecnologia chiave per una mobilità più sostenibile e contribuisce al raggiungimento di ambiziosi obiettivi di politica energetica e climatica: infatti, i veicoli a propulsione elettrica sono efficienti e l'impiego dell'elettricità permette l'utilizzo di energie rinnovabili. Un importante fattore di successo per la diffusione delle auto elettriche è la disponibilità di stazioni di ricarica pubbliche. Per questo motivo, la piattaforma https://pieno-di-elettricita.ch mostra in tempo reale la disponibilità delle stazioni di ricarica per veicoli elettrici.

L'infrastruttura di ricarica per veicoli elettrici in Svizzera viene costantemente ampliata. Per documentare questo sviluppo, i dati in tempo reale di https://pieno-di-elettricita.ch vengono valutati regolarmente e da essi vengono ricavati gli indicatori dell'infrastruttura di ricarica. Tali indicatori sono rilevati quotidianamente per l'intera Svizzera e per i singoli Cantoni, e se ne calcola la media mensile. Il rilevamento ha avuto inizio nel novembre 2020 ed è ancora in corso. Per una migliore comprensione dei dati, è disponibile una documentazione dettagliata.

Visualizzazione degli indici: http://www.pieno-di-elettricita.ch/indici

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

econ

de: Wirtschaft und Finanzen

en: Economy and finance

bundesamt-fur-energie-bfe

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

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

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

political_level: confederation


maintainer: Roksolana Petrovska

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

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

en: Mortality of regeneration

media_type: text/csv

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

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

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

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

acer

display_name: acer

dominance

display_name: dominance

fagus

display_name: fagus

lar

display_name: lar

mortality-rate

display_name: mortality-rate

regeneration

display_name: regeneration

shade-tolerance

display_name: shade-tolerance

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: Mortality of regeneration: Acer spp. and Fagus sylvatica


maintainer: Digital Innovation Office

de: ogd104-bfe versorgungssicherheit strom kernkraft erneuerbare-energien wasserkraft

fr: energiedashboard.ch: Producion d'électricité Swissgrid

en: energiedashboard.ch: Electricity production Swissgrid

it: energiedashboard.ch: Produzione di elettricità Swissgrid

fr:
En Suisse, il existe un grand nombre de centrales électriques qui produisent de l'énergie électrique (électricité). En ce qui concerne la production, on distingue les catégories suivantes : centrales nucléaires, centrales thermiques, centrales hydroélectriques fluviales, centrales hydroélectriques à accumulation, centrales éoliennes et centrales photovoltaïques. La production de ces centrales est entraînée par différents facteurs. Alors que les centrales à accumulation et à pompage-turbinage, par exemple, sont fortement guidées par le marché (en fonction des signaux de prix), les centrales nucléaires produisent de l'énergie en bande. En revanche, le photovoltaïque et l'éolien dépendent du soleil et du vent.

La production en Suisse, ajoutée aux importations et aux exportations, donne la consommation nationale, y compris la consommation des centrales de pompage-turbinage.

La tendance indique l'évolution de la production totale suisse par rapport à la moyenne des 10 derniers jours.

Disclaimer Données

Les données relatives aux mesures de la production suisse ne sont pas satisfaisantes. Alors que des données de mesure avec une résolution horaire sont disponibles pour les moyennes et grandes centrales, de telles données ne sont pas disponibles pour les plus petites installations ou ne concernent que l'injection dans le réseau au lieu de la production. De plus, toutes les données de mesure des installations décentralisées ne sont mises à disposition par les gestionnaires de réseau pour un enregistrement central dans différentes résolutions qu'avec plusieurs semaines de retard, conformément aux exigences légales en matière de promotion ou d'obligation de garantie d'origine. Il faut donc travailler avec des modèles qui prennent en compte les données météorologiques telles que la température, le rayonnement solaire et les précipitations. En outre, le comportement historique des catégories de production d'électricité est pris en compte. La production affichée dans la résolution journalière comprend à la fois des données mesurées et des données modélisées. Il peut y avoir des différences avec les statistiques fédérales de l'électricité en raison des données et des modélisations.

en:
In Switzerland, there are a large number of power plants that produce electrical energy (electricity). In terms of production, a distinction is made between the categories of nuclear power plants, thermal power plants, river hydropower, storage hydropower, wind power and photovoltaics. The production of these power plants is driven by different factors. For example, while storage and pumped storage power plants are strongly market-driven (based on price signals), nuclear power plants produce band energy. Photovoltaics and wind, on the other hand, are dependent on the sun and wind.

The production in Switzerland together with import and export results in the country's consumption including the consumption of pumped storage.

The trend indicates the development of the total Swiss production compared to the average of the last 10 days.

Disclaimer Data

The data situation regarding measurements of Swiss production is not satisfactory. While measurement data in hourly resolution are available for medium and large power plants, such data are not available for the smaller plants or only feed-in to the grid instead of production. In addition, all the measurement data from the decentralised plants are only made available by the grid operators for central recording in different resolutions with a delay of several weeks, in accordance with the legal requirements for subsidies or the guarantee of origin obligation. Thus, models have to be used which take into account meteorological data such as temperature, solar radiation and precipitation. In addition, the historical behaviour of the electricity generation categories is used. The production shown in the daily resolution includes both measured and modelled data. Due to the data situation and the modelling, there may be deviations from the electricity statistics of the federal government.

de:
In der Schweiz gibt es eine Vielzahl an Kraftwerken, die elektrische Energie (Strom) produzieren. Bei der Produktion werden die Kategorien Kernkraftwerke, thermische Kraftwerke, Flusswasserkraft, Speicherwasserkraft, Windkraft und Photovoltaik unterschieden. Die Produktion dieser Kraftwerke ist getrieben durch unterschiedliche Faktoren. Während beispielsweise Speicher- und Pumpspeicherkraftwerke stark marktgetrieben (anhand von Preissignalen) eingesetzt werden, produzieren die Kernkraftwerke Bandenergie. Photovoltaik und Wind sind hingegen abhängig von Sonne und Wind.

Die Produktion in der Schweiz zusammen mit Import und Export ergibt den Landesverbrauch inklusive des Verbrauchs der Pumpspeicher.

Der Trend gibt die Entwicklung der Schweizer Gesamtproduktion im Vergleich zum Durchschnitt der letzten 10 Tage an.

Disclaimer Daten

Die Datenlage in Bezug auf Messungen zur Schweizer Produktion ist nicht zufriedenstellend. Während für mittlere und grosse Kraftwerke Messdaten in stündlicher Auflösung verfügbar sind, sind solche Daten für die kleineren Anlagen nicht verfügbar oder nur die Einspeisung in das Netz anstelle der Produktion. Zudem werden alle Messdaten der dezentralen Anlagen nur mit mehreren Wochen Verzögerung durch die Netzbetreiber für eine zentrale Erfassung in unterschiedlichen Auflösungen bereitgestellt entsprechend den rechtlichen Anforderungen zu Förderung oder zur Herkunftsnachweispflicht. So muss mit Modellen gearbeitet werden, welche meteorologische Daten wie Temperatur, Sonneneinstrahlung, Niederschlag berücksichtigen. Zusätzlich wird das historische Verhalten der Stromerzeugungskategorien herbeigezogen. Die in der Tagesauflösung angezeigte Produktion umfasst sowohl gemessene als auch modellierte Daten. Es kann aufgrund der Datenlagen und den Modellierungen Abweichungen zur Elektrizitätsstatistik des Bundes geben.

it:
In Svizzera, ci sono un gran numero di centrali elettriche che producono energia elettrica (elettricità). In termini di produzione, si distingue tra le categorie di centrali nucleari, centrali termiche, energia idroelettrica fluviale, energia idroelettrica di accumulo, energia eolica e fotovoltaica. La produzione di queste centrali elettriche è guidata da diversi fattori. Per esempio, mentre le centrali di accumulo e di pompaggio sono fortemente orientate al mercato (basandosi sui segnali di prezzo), le centrali nucleari producono energia di banda. Il fotovoltaico e l'eolico, invece, dipendono dal sole e dal vento.

La produzione in Svizzera, insieme all'importazione e all'esportazione, si traduce nel consumo del Paese, compreso il consumo dell'accumulo con pompaggio.

Il trend indica l'andamento della produzione totale svizzera rispetto alla media degli ultimi 10 giorni.

Disclaimer Dati

La situazione dei dati relativi alle misurazioni della produzione svizzera non è soddisfacente. Mentre i dati di misurazione con risoluzione oraria sono disponibili per le centrali elettriche di medie e grandi dimensioni, tali dati non sono disponibili per le centrali più piccole o che si limitano all'immissione in rete invece che alla produzione. Inoltre, tutti i dati di misurazione degli impianti decentralizzati vengono resi disponibili dai gestori di rete solo per la registrazione centrale in diverse risoluzioni con un ritardo di diverse settimane, in conformità con i requisiti legali per le sovvenzioni o l'obbligo di garanzia di origine. Pertanto, è necessario utilizzare modelli che tengano conto dei dati meteorologici come la temperatura, la radiazione solare e le precipitazioni. Inoltre, viene utilizzato il comportamento storico delle categorie di generazione elettrica. La produzione mostrata nella risoluzione giornaliera comprende sia i dati misurati che quelli modellati. A causa della situazione dei dati e della modellazione, potrebbero esserci delle deviazioni rispetto alle statistiche sull'elettricità del governo federale.

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico


maintainer: Christoph Marty

en: Aare input

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

mimetype: application/x-tar

en: Dataset

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

en: CH2014 REPORT

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

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

en: Graubunden input

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

en:
 Overview

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

 Experimental Setup

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

 Data

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

climate-change

display_name: climate-change

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

en: Alpine3D simulations of future climate scenarios CH2014


en: land-cover landscape landscape-change land-use machine-learning modelling

en:
Code used to produce the Land-use/land-cover forecasts for Switzerland across the 21st century at 100-m resolution.
The script is based on input data which are not included as they are not freely available, therefore it will not run as it is. These input data are described in the accompanying publication on Data Science access to them can be requested to their owners. Alternatively the code can be modified to run on other data.

en: Compressed (.zip) file containing six georeferenced raster files in the GeoTIFF format with embedded coordinate reference system, and a table (comma separated values, .csv) encoding a colour palette for plotting (HEX colour codes for each class). GeoTIFF file names include the time-step and the RCP (e.g. “LULC_2020_2049_RCP45.tiff”). Each raster file has 3484x2207 square pixels (i.e. 7.7 megapixels) and is projected in the Swiss coordinate system CH1903+/LV95 (EPSG:2056).

en: We present forecasts of land-use/land-cover (LULC) change for Switzerland for three time-steps in the 21st century under the representative concentration pathways 4.5 and 8.5, and at 100-m spatial and 14-class thematic resolution. We modelled the spatial suitability for each LULC class with a neural network (NN) using >200 predictors and accounting for climate and policy changes. We used data augmentation to increase performance for underrepresented classes, resulting in an overall quantity disagreement of 0.053 and allocation disagreement of 0.15, which indicate good model performance. These class-specific spatial suitability maps outputted by the NN were then merged in a single LULC map per time-step using the CLUE-S algorithm, accounting for LULC demand for the future and a set of LULC transition rules. As the first LULC forecast for Switzerland at a thematic resolution comparable to available LULC maps for the past, this product lends itself to applications in land-use planning, resource management, ecological and hydraulic modelling, habitat restoration and conservation.

land-cover

display_name: land-cover

land-use

display_name: land-use

landscape

display_name: landscape

landscape-change

display_name: landscape-change

machine-learning

display_name: machine-learning

modelling

display_name: modelling

educ

en: Education, culture and sport

en: High resolution land use forecasts for Switzerland in the 21st century


title_for_slug: energiedashboard.ch: Tägliche Flüsse in die und aus der Schweiz (Strom)

de: ogd107-bfe stromimport stromexport versorgungssicherheit internationale-vernetzung

fr: energiedashboard.ch: Flux quotidiens d'importation et exportation (Électricité)

en: energiedashboard.ch: Daily import and export flows (Electricity)

it: energiedashboard.ch: Flussi giornalieri di import ed export (Elettricità)

fr:
Les réseaux électriques, en tant que lien entre la production et la consommation, sont d'une importance capitale pour garantir la sécurité de l'approvisionnement en électricité. Le réseau électrique de la Suisse ne s'arrête pas simplement à la frontière avec les autres pays européens, mais est étroitement relié aux réseaux électriques voisins. Cela est essentiel pour la sécurité de l'approvisionnement : Si la Suisse a besoin d'électricité supplémentaire, elle peut l'importer.

Le flux physique d'électricité ou échange d'interconnexion désigne la quantité d'énergie en gigawattheures par heure (GWh/h) qui circule sur les lignes électriques transfrontalières entre l'étranger et la Suisse.

Le chiffre relatif à l'importation / exportation est la somme des quantités d'électricité importées et exportées pendant une journée. Une valeur négative signifie que la Suisse exporte en somme de l'électricité.  La flèche de tendance indique la tendance des importations & exportations de la Suisse. Il faut distinguer 4 cas : 1. Si la Suisse importe plus d'électricité que la moyenne des 10 derniers jours, la flèche est orientée à la hausse. 2. si la Suisse importe moins que la moyenne des 10 derniers jours, elle est orientée à la baisse. 3) Dans le cas des exportations, si la Suisse exporte plus que la moyenne des 10 derniers jours, la flèche pointe vers le bas. 4. si la Suisse exporte moins que la moyenne des 10 derniers jours, la flèche pointe vers le haut.

Disclaimer Données

Les données proviennent de l'ENTSO-E. Elles sont disponibles par heure, mais pour des raisons de simplicité, elles sont totalisées sur la journée pour le tableau de bord de l'OFEN et mises à jour quotidiennement.

en:
Electricity grids are of central importance as a link between production and consumption to ensure the security of electricity supply. Switzerland's electricity grid does not simply stop at the border with the rest of Europe, but is closely connected to neighbouring electricity grids. This is central to security of supply: If Switzerland needs additional electricity, it can be imported.

The physical flow of electricity or interconnection exchange is the amount of energy in gigawatt hours per hour (GWh/h) that flows between foreign countries and Switzerland via the cross-border power lines.

The import/export figure is the sum of the imported and exported electricity quantities during one day. A negative value means that Switzerland is exporting electricity in total.  The trend arrow indicates the trend of Switzerland's import & export. A distinction is made between 4 cases: 1. if Switzerland imports more electricity overall than on average over the last 10 days, the arrow points upwards. 2. if Switzerland imports less electricity than on average over the last 10 days, the arrow points downwards. 2. if Switzerland imports less than the average over the last 10 days, the arrow points downwards. 3. in the case of exports, the arrow points downwards if Switzerland exports more than the average over the last 10 days. 4. if Switzerland exports less than average in the last 10 days, the arrow points upwards.

Disclaimer data

The data come from ENTSO-E. They are available per hour, but for simplicity they are summed up over the day for the BFE Dashboard and updated daily.

de:
Stromnetze sind als Bindeglied zwischen Produktion und Verbrauch von zentraler Bedeutung, um die Stromversorgungssicherheit zu gewährleisten. Das Stromnetz der Schweiz hört nicht einfach an der Grenze zum europäischen Ausland auf, sondern ist eng mit den benachbarten Stromnetzen verbunden. Dies ist für die Versorgungssicherheit zentral: Benötigt die Schweiz zusätzlichen Strom, kann dieser importiert werden.

Als physikalischer Stromfluss oder Verbundaustausch wird die Energiemenge in Gigawattstunden pro Stunde (GWh/h) bezeichnet, die über die grenzüberschreitenden Stromleitungen zwischen dem Ausland und der Schweiz fliesst.

Die Zahl zum Import / Export ist die Summe der importierten und exportierten Strommengen während eines Tages. Ein negativer Wert bedeutet, dass die Schweiz in der Summe Strom exportiert.  Der Trendpfeil gibt die Tendenz von Import & Export der Schweiz an. Dabei sind 4 Fälle zu unterscheiden: 1. Importiert die Schweiz insgesamt mehr Strom als durchschnittlich in den letzten 10 Tagen zeigt er nach oben. 2. Importiert die Schweiz weniger als durchschnittlich in den letzten 10 Tagen, zeigt er nach unten. 3. Für den Fall des Exportes gilt, dass der Pfeil nach unten zeigt, wenn die Schweiz mehr exportiert als durchschnittlich in den letzten 10 Tagen. 4. Wenn die Schweiz weniger exportiert als durchschnittlich in den letzten 10 Tagen, dann zeigt der Pfeil nach oben.

Disclaimer Daten

Die Daten stammen von der ENTSO-E. Sie sind pro Stunde verfügbar, werden aber der Einfachheit halber für das BFE Dashboard über den Tag aufsummiert und täglich aktualisiert.

it:
Le reti elettriche sono di importanza centrale come collegamento tra produzione e consumo, per garantire la sicurezza dell'approvvigionamento elettrico. La rete elettrica della Svizzera non si ferma semplicemente al confine con il resto dell'Europa, ma è strettamente collegata alle reti elettriche vicine. Questo è fondamentale per la sicurezza dell'approvvigionamento: Se la Svizzera ha bisogno di energia elettrica aggiuntiva, può importarla.

Il flusso fisico di energia elettrica o scambio di interconnessione è la quantità di energia in gigawattora all'ora (GWh/h) che scorre tra l'estero e la Svizzera attraverso le linee elettriche transfrontaliere.

La cifra di import/export è la somma delle quantità di energia elettrica importate ed esportate durante un giorno. Un valore negativo significa che la Svizzera sta esportando elettricità in totale.  La freccia di tendenza indica l'andamento dell'import-export della Svizzera. Si distingue tra 4 casi: 1. se la Svizzera importa complessivamente più elettricità rispetto alla media degli ultimi 10 giorni, la freccia punta verso l'alto. 2. se la Svizzera importa meno elettricità rispetto alla media degli ultimi 10 giorni, la freccia punta verso il basso. 2. Se la Svizzera importa meno della media degli ultimi 10 giorni, la freccia punta verso il basso. 3. Nel caso delle esportazioni, la freccia punta verso il basso se la Svizzera esporta più della media degli ultimi 10 giorni. 4. Se la Svizzera esporta meno della media negli ultimi 10 giorni, la freccia punta verso l'alto.

Disclaimer Dati

I dati provengono da ENTSO-E. Sono disponibili per ora, ma per semplicità vengono sommati nell'arco della giornata per il cruscotto BFE e aggiornati giornalmente.

ener

en: Energy

gove

en: Government and public sector

econ

en: Economy and finance

bundesamt-fur-energie-bfe

en: Swiss Federal Office of Energy SFOE

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


en: compound-events drought natural-hazards forest-fire protection-forest extreme-events bark-beetles protective-effect

en: Case study website

media_type: text/html

en: Page of the case study on the project website. It includes figures fo all questions of the survey and additional synthesis graphs.

format: HTML

en: Conclusions and recommendations of the project (in German).

mimetype: application/pdf

en: Description of the study site, extreme event (trigger event) and informations about the survey.

en: Factsheet summarising the methods used in this project (in German).

en: Factsheet summarising the key results of the study (in German).

en:
This file contains the anonymous answers to the survey for the case study in the protective forest, Val Mesolcina, GR, Switzerland within the BAFU Project "Wenn Risiken kumulieren - Analyse und Umgang mit unerwarteten Ereignissen und kombinierten Risiken".
The survey consists of two parts, based on different concepts: "top-down" and "bottom-up". Answers for both concepts are available in two different worksheets within the Excel file.

en: Factsheet summarising the key results of the study (in Italian).

en: Factsheet summarising the key results of the study (in French).

en:
This dataset contains the results of a case study analysing the potential impacts of a compound meteorological extreme event on the protective forest in the Val Mesolcina. These impacts were assessed in an experts survey. 29 Experts from practice, administration and science estimated the probabilities for a loss of the protective function due to a drought-related compound extreme event based on different hazard scenarios. The experts not only assessed these probabilities but also provided estimates about the reliability of the scenarios, other socio-economic consequences and options for adaptation.
This dataset contains the following information:
- Table with all (anonymised) answers from the survey
- Factsheets summarising the results and methods in German, French and Italian
- A detailed description of the study site and survey instructions
- Link to the project website wit illustrations for each individual question of the survey

bark-beetles

display_name: bark-beetles

compound-events

display_name: compound-events

drought

display_name: drought

extreme-events

display_name: extreme-events

forest-fire

display_name: forest-fire

natural-hazards

display_name: natural-hazards

protection-forest

display_name: protection-forest

protective-effect

display_name: protective-effect

educ

de: Bildung, Kultur und 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: Experts survey protective forest and combined extremes in Val Mesolcina


wind-crust-formation-snowmicropen-data

title_for_slug: wind-crust-formation-snowmicropen-data

en: wind-packing snowmicropen snow wind-crust smp

en: README

en: Describes the dataset in detail

en: SMP data

en: Links to the dataset

en: Processing scripts

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

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

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

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

This dataset is the basis of the following publication:

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

smp

display_name: smp

snow

display_name: snow

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

educ

en: Education, culture and sport

de: EnviDat: das Umwelt-Datenportal

en: Wind crust formation: SnowMicroPen data


maintainer: Mountain Hydrology and Mass Movements

en: debris-flow-fatalities earthquake-fatalities ice-avalanche-fatalities windstorm-fatalities natural-hazard-fatalities flood-fatalities lightning-fatalities landslide-fatalities rockfall-fatalities

en: Natural hazard fatalities per year in Swizterland since 1946.

mimetype: text/csv

en:
This dataset contains the number of fatalities due to flood, debris flow, landslide, rockfall, windstorm, lightning, ice avalanche, earthquake and other processes like roof avalanche or lacustrine tsunami for each year since 1946.
The following information is contained (by column and column title):

* year
* total number of hazard fatalities
* number of fatalities by flood (German: Hochwasser, Überschwemmung). Flood includes people drowned in flooded or inundated areas or carried away in streams under high-water conditions.
* number of fatalities by debris flow (German: Murgang).
* number of fatalities by landslide (German: Erdrutsch). Landslide includes people killed by landslides and hillslope debris flows (German: Hangmure).
* number of fatalities by rockfall (German: Steinschlag, Fels- und Bergsturz).
* number of fatalities by windstorm (German: Sturm). Windstorm includes people killed by falling objects or trees during very strong wind conditions and people who drowned in lakes because their boat capsized during such conditions.
* number of fatalities by lightning (German: Blitz).
* number of fatalities by ice avalanche (German: Eislawine).
* number of fatalities by earthquake (German: Erdbeben).
* number of fatalities by other processes like roof avalanche, lacustrine tsunami (German: andere Prozesse wie Dachlawine, Tsunami im See).

The data was collected based on newspaper research. For more information please refer to

_Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747-2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016._

The data collection is financed by the FOEN (with exception of the collection of the avalanche fatalities). The data contains the official statistics of the FOEN on fatalities due to flood, debris flow, landslide, rock fall and avalanche.

Restrictions: The data set is not complete. Only fatalities in or around settlements and on open transportation routes are included. More precisely, fatalities were not collected, when persons exposed themselves to a great danger on purpose. Or fatalities during leisure activities which are connected to a higher risk were not included (this includes e.g. canoeing or river surfing during flood, canyoning, mountaineering, climbing, walking or driving on a closed road).

Fatalities by avalanches are collected at the WSL Institute for Snow and Avalanche Research SLF. You can download the avalanche fatalities per hydrological year [here](https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936) and per calendar year [here](https://www.envidat.ch/dataset/avalanche-fatalities-per-calendar-year-since-1936). For a direct comparison with the fatalities presented here, please download the data set with the calendar years and do not consider fatalities in the backcountry (tour) or in terrain close to ski areas (offpiste).

debris-flow-fatalities

display_name: debris-flow-fatalities

earthquake-fatalities

display_name: earthquake-fatalities

flood-fatalities

display_name: flood-fatalities

ice-avalanche-fatalities

display_name: ice-avalanche-fatalities

landslide-fatalities

display_name: landslide-fatalities

lightning-fatalities

display_name: lightning-fatalities

natural-hazard-fatalities

display_name: natural-hazard-fatalities

rockfall-fatalities

display_name: rockfall-fatalities

windstorm-fatalities

display_name: windstorm-fatalities

envidat

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.

en: Number of natural hazard fatalities per year in Switzerland since 1946


maintainer: Leo Gallus Bont

en: openstreetmap geoprocessing forest seilaplan qgis accessible-forest

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

en: Juypter Notebook for Data Preparation

en: Railways vector data (close to the sample forest range)

en: Forest vector data (for sample forest range)

en: Digitised sample perimeter

en: DEM (for the area of the sample forest range)

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Juypter Notebook for Data Preparation (online)

en: Power lines vector data (close to the area of the sample forest range)

en:
This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).
The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.
The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019.

Additional notes for vector data:
Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API - https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any perimeter or area can be digitised freely using the QGIS editing toolbar.

The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:

- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)
- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif

This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.

Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.

This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan

en: EnviDat: the Environmental Data Portal

en: Sample Geodata and Software for Demonstrating Geospatial Preprocessing for Forest Accessibility and Wood Harvesting at FOSS4G2019


snow-drift-station-micro-rain-radar

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

en: precipitation radar mountain snow raclets rain

en: MRR data Period 2

en: The dataset contains measurements between March 5 and March 8, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en: Parameter MRR

en: The PDF contains additional information on parameters which were set for the certain time periods (time in UTC).

en: MRR data of period 4

en: The dataset contains measurements between March 13 and March 22, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en: MRR data of period 3

en: The dataset contains measurements between March 8 and March 13, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

en: MMR Data Period 1

en: The dataset contains measurements between March 1 and March 5, 2019, with time in UTC. The parameters and specifications are given in MRR_parameters.pdf. The zip folder contains hourly data files in netCDF format and a log file, reporting the instrument status.

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

mountain

display_name: mountain

precipitation

display_name: precipitation

raclets

display_name: raclets

radar

display_name: radar

rain

display_name: rain

snow

display_name: snow

educ

en: Education, culture and sport

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: Snow Drift Station - Micro Rain Radar


en: biodiversity bryophyte moss endemic-species endemic climate-change-impact functional-taxonomic-groups photobiont disturbance elevational-gradient lichen-growth-form lichen liverwort functional-taxonomic-group lichen-growthform climate-change madeira-island bryophyte-life-strategy

en: MadCrypto – Bryophyte and macrolichen diversity in laurel forests of Madeira

en:
This dataset includes species lists of bryophytes and macrolichens (presence/absence) sampled on the forest floor and on trees in disturbed and undisturbed plots along elevation gradients in the laurel forests of Madeira island. It also contains species specific information (bryophytes: red list status, endemic status, taxonomic group, life strategy; macrolichens: photobiont type, growth form) as well as plot information (Plot_ID, sampling date, coordinates, elevation a.s.l. (m), disturbance type, sampled host tree species).

The dataset was used for the paper
Boch S, Martins A, Ruas S, Fontinha S, Carvalho P, Reis F, Bergamini A, Sim-Sim M (2019) Bryophyte and macrolichen diversity show contrasting elevation relationships and are negatively affected by disturbances in laurel forests of Madeira island. Journal of Vegetation Science.

en:
This dataset includes species lists of bryophytes and macrolichens (presence/absence) sampled on the forest floor and on trees in disturbed and undisturbed plots along elevation gradients in the laurel forests of Madeira island. It also contains species specific information (bryophytes: red list status, endemic status, taxonomic group, life strategy; macrolichens: photobiont type, growth form) as well as plot information (Plot_ID, sampling date, coordinates, elevation a.s.l. (m), disturbance type, sampled host tree species).

The dataset was used for the paper
Boch S, Martins A, Ruas S, Fontinha S, Carvalho P, Reis F, Bergamini A, Sim-Sim M (2019) Bryophyte and macrolichen diversity show contrasting elevation relationships and are negatively affected by disturbances in laurel forests of Madeira island. Journal of Vegetation Science 30: 1122–1133.

The excel file contains 5 sheets:
1) Plot information
2) Bryophyte data with species specific information, separated per substrate
3) Macrolichen data with species specific information, separated per substrate
4) Bryophyte data with species specific information (plot level data). Species lists of the two substrates were merged; if one substrate in a plot hosted a species identified only to genus level (genus spec.) but the second investigated substrate hosted an identified species of the same genus, we removed the genus spec. entry in the particular plot. The species list of sheet 2 and 4 might therefore differ slightly.
5) Macrolichen data with species specific information (plot level data). Species lists of the two substrates were merged; if one substrate in a plot hosted a species identified only to genus level (genus spec.) but the second investigated substrate hosted an identified species of the same genus, we removed the genus spec. entry in the particular plot. The species list of sheet 3 and 5 might therefore differ slightly.

biodiversity

display_name: biodiversity

bryophyte

display_name: bryophyte

bryophyte-life-strategy

display_name: bryophyte-life-strategy

climate-change

display_name: climate-change

climate-change-impact

display_name: climate-change-impact

disturbance

display_name: disturbance

elevational-gradient

display_name: elevational-gradient

endemic

display_name: endemic

endemic-species

display_name: endemic-species

functional-taxonomic-group

display_name: functional-taxonomic-group

functional-taxonomic-groups

display_name: functional-taxonomic-groups

lichen

display_name: lichen

lichen-growth-form

display_name: lichen-growth-form

lichen-growthform

display_name: lichen-growthform

liverwort

display_name: liverwort

madeira-island

display_name: madeira-island

moss

display_name: moss

photobiont

display_name: photobiont

envidat

en: EnviDat: the Environmental Data Portal