---
OA_place: publisher
OA_type: hybrid
_id: '22529'
abstract:
- lang: eng
text: Mountainous catchments cover a broad range of elevations and their response
to a warming climate is expected to vary significantly in space. Nevertheless,
studies on climate change impacts typically examine the changes in flow statistics
only at the catchment outlet. In this study, we instead demonstrate the high variability
of the hydrological response to climate change at the sub-catchment scale, investigating
in detail the contribution of all components of the hydrological cycle in two
mountainous catchments (Thur and Kleine Emme) in the Swiss Alps. The analysis
was conducted with a two-dimensional weather generator model that simulated gridded
climate variables at an hourly and 2-km resolution until the end of the 21st century
for the RCP8.5 emission scenario. The climate ensemble was used as input into
a distributed hydrological model to estimate the changes in hydrological processes
at 100-m and hourly resolutions. Climate models show that precipitation intensifies
during winter but weakens during summer in the order of ± 5–10% toward the end
of the century. Temperature will rise by up to 4°C, leading to a 50% reduction
in snowmelt, 10% increase in evapotranspiration, and shift in precipitation type
from snowfall to rainfall. As a result, streamflow is projected to increase by
40% in winter but decrease by 20% to 40% during summer, with winter floods becoming
more frequent. The changes to streamflow (mean and extreme low and high flows)
at the sub-catchments show a strong dependency with elevation. In contrast to
the small changes projected at the outlet of the catchments, streamflow shows
a reduction at higher elevations (up to −20% change in mean streamflow for sub-catchments
at elevations exceeding 1400 m) and an increase at lower elevations (up to +5%
for Kleine Emme and +20% for the Thur at elevations below 600 m). These impacts
are tied to the changes in precipitation, as well as changes in snowmelt (at high
elevation) and evapotranspiration (at low elevation). The results reveal the causes
and diversity of hydrological response to climate change, emphasizing the importance
of investigating the distributed impacts of climate change in mountainous environments.
article_number: '126806'
article_processing_charge: No
article_type: original
author:
- first_name: Jorge Sebastián
full_name: Moraga, Jorge Sebastián
last_name: Moraga
- first_name: Nadav
full_name: Peleg, Nadav
last_name: Peleg
- first_name: Simone
full_name: Fatichi, Simone
id: cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6
last_name: Fatichi
- first_name: Peter
full_name: Molnar, Peter
last_name: Molnar
- first_name: Paolo
full_name: Burlando, Paolo
last_name: Burlando
citation:
ama: Moraga JS, Peleg N, Fatichi S, Molnar P, Burlando P. Revealing the impacts
of climate change on mountainous catchments through high-resolution modelling.
Journal of Hydrology. 2021;603. doi:10.1016/j.jhydrol.2021.126806
apa: Moraga, J. S., Peleg, N., Fatichi, S., Molnar, P., & Burlando, P. (2021).
Revealing the impacts of climate change on mountainous catchments through high-resolution
modelling. Journal of Hydrology. Elsevier. https://doi.org/10.1016/j.jhydrol.2021.126806
chicago: Moraga, Jorge Sebastián, Nadav Peleg, Simone Fatichi, Peter Molnar, and
Paolo Burlando. “Revealing the Impacts of Climate Change on Mountainous Catchments
through High-Resolution Modelling.” Journal of Hydrology. Elsevier, 2021.
https://doi.org/10.1016/j.jhydrol.2021.126806.
ieee: J. S. Moraga, N. Peleg, S. Fatichi, P. Molnar, and P. Burlando, “Revealing
the impacts of climate change on mountainous catchments through high-resolution
modelling,” Journal of Hydrology, vol. 603. Elsevier, 2021.
ista: Moraga JS, Peleg N, Fatichi S, Molnar P, Burlando P. 2021. Revealing the impacts
of climate change on mountainous catchments through high-resolution modelling.
Journal of Hydrology. 603, 126806.
mla: Moraga, Jorge Sebastián, et al. “Revealing the Impacts of Climate Change on
Mountainous Catchments through High-Resolution Modelling.” Journal of Hydrology,
vol. 603, 126806, Elsevier, 2021, doi:10.1016/j.jhydrol.2021.126806.
short: J.S. Moraga, N. Peleg, S. Fatichi, P. Molnar, P. Burlando, Journal of Hydrology
603 (2021).
das_tickbox: '1'
date_created: 2026-07-27T12:30:24Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2026-08-06T14:31:25Z
day: '01'
doi: 10.1016/j.jhydrol.2021.126806
extern: '1'
intvolume: ' 603'
keyword:
- Catchment modelling
- Climate change impacts
- Weather generator
- Distributed hydrological model
- Streamflow extremes
- Hydrological response
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1016/j.jhydrol.2021.126806
month: '12'
oa: 1
oa_version: Published Version
publication: Journal of Hydrology
publication_identifier:
eissn:
- 1879-2707
issn:
- 0022-1694
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Revealing the impacts of climate change on mountainous catchments through high-resolution
modelling
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 603
year: '2021'
...
---
OA_type: closed access
_id: '22551'
abstract:
- lang: eng
text: Exploring the effects of climate change on the hydrological response at the
local scale requires climate data at high spatial and temporal resolutions. This
is best achieved by generating downscaled ensembles of future climate variables
derived from climate models. For this purpose we present a methodology to re-parameterize
the AWE-GEN-2d model (Advanced WEather GENerator for a two-dimensional grid).
The model simulates key meteorological variables needed by hydrological models
and is particularly suitable to explore the effects of stochastic (natural) climatic
uncertainty, which is fundamental for hydrological applications, especially at
sub-kilometer and hourly scales. Factors of change for different climate statistics
are calculated from climate model simulations of present and future climates and
subsequently applied to the statistics derived from observations to re-parameterize
AWE-GEN-2d. The model abilities in generating an ensemble of future climate variables
for the transient period 2020–2089 is presented with examples of precipitation
and near-surface air temperature fields from hourly to multi-annual scales for
a small mountainous region in the Swiss Alps. The stochastic uncertainty is examined
for present and future periods and for spatial scales from the RCM scale (12-km,
daily) to 2-km demonstrating the potential use of AWE-GEN-2d outputs. At the RCM
scale, model results yield a small increase in annual precipitation (4%) which
is within the stochastic uncertainty range for present and future periods (7%).
At the fine scale of 2-km, the increase in annual precipitation can exceed the
stochastic uncertainty, but for less than 10% of the domain area. On the contrary,
changes in annual near-surface air temperature exceed stochastic uncertainty both
at the RCM and finer scales. Stochastic climate uncertainty was concluded to be
very similar when comparing present and future periods and 12-km and 2-km scales.
The benefits of using AWE-GEN-2d in hydrological climate change impact assessments
are finally discussed.
article_processing_charge: No
article_type: original
author:
- first_name: Nadav
full_name: Peleg, Nadav
last_name: Peleg
- first_name: Peter
full_name: Molnar, Peter
last_name: Molnar
- first_name: Paolo
full_name: Burlando, Paolo
last_name: Burlando
- first_name: Simone
full_name: Fatichi, Simone
id: cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6
last_name: Fatichi
citation:
ama: Peleg N, Molnar P, Burlando P, Fatichi S. Exploring stochastic climate uncertainty
in space and time using a gridded hourly weather generator. Journal of Hydrology.
2019;571:627-641. doi:10.1016/j.jhydrol.2019.02.010
apa: Peleg, N., Molnar, P., Burlando, P., & Fatichi, S. (2019). Exploring stochastic
climate uncertainty in space and time using a gridded hourly weather generator.
Journal of Hydrology. Elsevier. https://doi.org/10.1016/j.jhydrol.2019.02.010
chicago: Peleg, Nadav, Peter Molnar, Paolo Burlando, and Simone Fatichi. “Exploring
Stochastic Climate Uncertainty in Space and Time Using a Gridded Hourly Weather
Generator.” Journal of Hydrology. Elsevier, 2019. https://doi.org/10.1016/j.jhydrol.2019.02.010.
ieee: N. Peleg, P. Molnar, P. Burlando, and S. Fatichi, “Exploring stochastic climate
uncertainty in space and time using a gridded hourly weather generator,” Journal
of Hydrology, vol. 571. Elsevier, pp. 627–641, 2019.
ista: Peleg N, Molnar P, Burlando P, Fatichi S. 2019. Exploring stochastic climate
uncertainty in space and time using a gridded hourly weather generator. Journal
of Hydrology. 571, 627–641.
mla: Peleg, Nadav, et al. “Exploring Stochastic Climate Uncertainty in Space and
Time Using a Gridded Hourly Weather Generator.” Journal of Hydrology, vol.
571, Elsevier, 2019, pp. 627–41, doi:10.1016/j.jhydrol.2019.02.010.
short: N. Peleg, P. Molnar, P. Burlando, S. Fatichi, Journal of Hydrology 571 (2019)
627–641.
das_tickbox: '1'
date_created: 2026-07-27T12:30:24Z
date_published: 2019-04-01T00:00:00Z
date_updated: 2026-08-06T08:45:41Z
day: '01'
doi: 10.1016/j.jhydrol.2019.02.010
extern: '1'
intvolume: ' 571'
keyword:
- Weather generator
- Stochastic downscaling
- Climate change
- Internal climate variability
- Climate uncertainty
- High-resolution rainfall model
language:
- iso: eng
month: '04'
oa_version: None
page: 627-641
publication: Journal of Hydrology
publication_identifier:
eissn:
- 1879-2707
issn:
- 0022-1694
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Exploring stochastic climate uncertainty in space and time using a gridded
hourly weather generator
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 571
year: '2019'
...
---
OA_type: closed access
_id: '22556'
abstract:
- lang: eng
text: Numerous studies across multiple disciplines search for insights on the effects
of climate change at local spatial scales and at fine time resolutions. This study
presents an overall methodology of using a weather generator for downscaling an
ensemble of climate model outputs. The downscaled predictions can explicitly include
climate model uncertainty, which offers valuable information for making probabilistic
inferences about climate impacts. The hourly weather generator that serves as
the downscaling tool is briefly presented. The generator is designed to reproduce
a set of meteorological variables that can serve as input to hydrological, ecological,
geomorphological, and agricultural models. The generator is capable of reproducing
a wide set of climate statistics over a range of temporal scales, from extremes,
to low-frequency interannual variability; its performance for many climate variables
and their statistics over different aggregation periods is highly satisfactory.
The use of the weather generator in simulations of future climate scenarios, as
inferred from climate models, is described in detail. Using a previously developed
methodology based on a Bayesian approach, the stochastic downscaling procedure
derives the frequency distribution functions of factors of change for several
climate statistics from a multi-model ensemble of outputs of General Circulation
Models. The factors of change are subsequently applied to the statistics derived
from observations to re-evaluate the parameters of the weather generator. Using
embedded causal and statistical relationships, the generator simulates future
realizations of climate for a specific point location at the hourly scale. Uncertainties
present in the climate model realizations and the multi-model ensemble predictions
are discussed. An application of the weather generator in reproducing present
(1961–2000) and forecasting future (2081–2100) climate conditions is illustrated
for the location of Tucson (AZ). The stochastic downscaling is carried out using
simulations of eight General Circulation Models adopted in the IPCC 4AR, A1B emission
scenario.
article_processing_charge: No
article_type: original
author:
- first_name: Simone
full_name: Fatichi, Simone
id: cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6
last_name: Fatichi
- first_name: Valeriy Y.
full_name: Ivanov, Valeriy Y.
last_name: Ivanov
- first_name: Enrica
full_name: Caporali, Enrica
last_name: Caporali
citation:
ama: Fatichi S, Ivanov VY, Caporali E. Simulation of future climate scenarios with
a weather generator. Advances in Water Resources. 2011;34(4):448-467. doi:10.1016/j.advwatres.2010.12.013
apa: Fatichi, S., Ivanov, V. Y., & Caporali, E. (2011). Simulation of future
climate scenarios with a weather generator. Advances in Water Resources.
Elsevier. https://doi.org/10.1016/j.advwatres.2010.12.013
chicago: Fatichi, Simone, Valeriy Y. Ivanov, and Enrica Caporali. “Simulation of
Future Climate Scenarios with a Weather Generator.” Advances in Water Resources.
Elsevier, 2011. https://doi.org/10.1016/j.advwatres.2010.12.013.
ieee: S. Fatichi, V. Y. Ivanov, and E. Caporali, “Simulation of future climate scenarios
with a weather generator,” Advances in Water Resources, vol. 34, no. 4.
Elsevier, pp. 448–467, 2011.
ista: Fatichi S, Ivanov VY, Caporali E. 2011. Simulation of future climate scenarios
with a weather generator. Advances in Water Resources. 34(4), 448–467.
mla: Fatichi, Simone, et al. “Simulation of Future Climate Scenarios with a Weather
Generator.” Advances in Water Resources, vol. 34, no. 4, Elsevier, 2011,
pp. 448–67, doi:10.1016/j.advwatres.2010.12.013.
short: S. Fatichi, V.Y. Ivanov, E. Caporali, Advances in Water Resources 34 (2011)
448–467.
das_tickbox: '1'
date_created: 2026-07-27T12:30:24Z
date_published: 2011-04-01T00:00:00Z
date_updated: 2026-08-06T10:13:12Z
day: '01'
doi: 10.1016/j.advwatres.2010.12.013
extern: '1'
intvolume: ' 34'
issue: '4'
keyword:
- Weather generator
- Stochastic downscaling
- Climate change
- Hydro-meteorology
- Rainfall model
language:
- iso: eng
month: '04'
oa_version: None
page: 448-467
publication: Advances in Water Resources
publication_identifier:
issn:
- 0309-1708
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Simulation of future climate scenarios with a weather generator
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 34
year: '2011'
...