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CliRSnow SIGNED

Statistically combine climate models with remote sensing to providehigh-resolution snow projections for the near and distant future.

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 CliRSnow project word cloud

Explore the words cloud of the CliRSnow project. It provides you a very rough idea of what is the project "CliRSnow" about.

either    climate    basis    horizonzal    computationally    alpine    15    rcms    series    sufficient    rely    environment    impacts    employ    handling    daily    cryosphere    verge    demand    background    rs    economy    combine    community    data    impossible    consistently    12    warming    infer    cordex    pave    substantially    communities    expertise    researcher    modis    quantity    hydropower    physical    approx    hydrological    seasonality    empirical    host    cover    solution    2000    re    projections    independent    ecosystems    downstream    resolution    feasible    water    5km    discipline    interdisciplinary    countries    technological    region    ready    snow    250m    models    precision    global    computational    fellowship    innovative    statistical    hydrology    space    regional    alps    sensing    correcting    actions    area    career    agriculture    stakeholders    society    local    tourism    forms    skills    rcm    spatial    international    remote    output    intensive    fast    inside    time    bias   

Project "CliRSnow" data sheet

The following table provides information about the project.

Coordinator
ACCADEMIA EUROPEA DI BOLZANO 

Organization address
address: VIALE DRUSO 1
city: BOLZANO
postcode: 39100
website: www.eurac.edu

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Total cost 180˙277 €
 EC max contribution 180˙277 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2017
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2018
 Duration (year-month-day) from 2018-10-01   to  2021-04-01

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ACCADEMIA EUROPEA DI BOLZANO IT (BOLZANO) coordinator 180˙277.00

Map

Leaflet | Map data © OpenStreetMap contributors, CC-BY-SA, Imagery © Mapbox

 Project objective

The cryosphere in the European Alps is expected to change substantially with global warming. Snow in the Alps impacts the local communities but also affects the quantity and seasonality of water downstream, and thus has a wide range of effects on agriculture, ecosystems, hydropower, and tourism. Projections of future snow are required in society and economy. Targeted actions require information at the local community scale, which is not yet consistently available for the whole Alpine region. This is because the existing approaches to infer future snow conditions rely on physical models, either regional climate models (RCMs) or snow-hydrological models, which are both computationally very intensive, making it yet impossible to have a high resolution output for such a large area as the Alps. Here, I shall employ empirical models derived from remote sensing (RS) to provide an innovative and fast solution to increase the precision in future projections of snow cover from RCMs for the whole Alpine area. This will be achieved by correcting the bias in snow cover from RCMs and increasing the spatial resolution with RS snow cover data. Such an approach has now become feasible, because the data that forms its basis is on the verge of being sufficient in time (RS: MODIS time series since 2000) and space (RCM: EURO-CORDEX horizonzal resolution at approx. 12.5km). The host has the necessary data (daily MODIS snow cover at 250m and output from 15 different RCMs with snow cover), the technological environment for the computational demand, and the relevant expertise in each discipline (remote sensing, climate, hydrology) inside the institute and with international partners. I shall bring the statistical background, data handling skills, and interdisciplinary experience to combine these fields. This fellowship shall pave the way for my future career as independent researcher, but also produce output ready for re-use and exploitation by stakeholders in the Alpine countries.

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The information about "CLIRSNOW" are provided by the European Opendata Portal: CORDIS opendata.

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