H2020Индивидуална стипендия2018–2021

CliRSnow · Statistically combine climate models with remote sensing to provide high-resolution snow projections for the near and distant future.

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2018-10-01 → 2021-09-12
Финансиране от ЕС: 180 277 €
Участници: 1
Схема: MSCA-IF-EF-ST

Линиите свързват координатора с партньорите.

Накратко на български

Снежното покритие в европейските Алпи се анализира чрез комбиниране на климатични модели и сателитни данни за бъдещи прогнози. Това помага да се разберат промените в разпределението на водата, които влияят на земеделието, енергетиката и зимния туризъм.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

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

Seasonal snow cover plays a key role in mountain socio-ecosystems but it is threatened by climate change. Snow accumulates in winter and subsequently melts in spring and summer, thus releasing significant water amounts downstream. The water availability from snow impacts hydro-power generation and agriculture far beyond the mountain ranges, while the snow cover directly affects vegetation phenology and species distribution. Moreover, snow plays an important role in defining mountain people’s identities and is a major influence on mountain economy via winter tourism. With increasing temperatures and potentially changing precipitation patterns, the timing and abundance of snow will change. In order to determine the impacts of changing snow patterns, climate information is crucial, which can identify the impact of different emission scenarios as well as temporal and spatial patterns of change. The main challenge in determining future snow cover lies in the interaction between the large-scale weather forcing and small-scale topographical control on snow. The overall objective of CliRSnow is to produce climatological information on snow cover in the European Alps for the past and the future. This is achieved by combining in-situ data, regional climate models and remote sensing to provide high-resolution projections of snow cover fraction for different scenarios of greenhouse gas concentrations, and putting these in context to past changes.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

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.

Оригинален текст от CORDIS (на английски).

Участници

ACCADEMIA EUROPEA DI BOLZANO · BolzanoКоординаторИталия