Articles | Volume 22, issue 6
https://doi.org/10.5194/hess-22-3331-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-3331-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jun 2018
Research article |
| 14 Jun 2018
| 14 Jun 2018
Climate change over the high-mountain versus plain areas: Effects on the land surface hydrologic budget in the Alpine area and northern Italy
Claudio Cassardo
Department of Physics and NatRisk Center, University of Torino “Alma Universitas Taurinorum”, Torino, Italy
Department of Climate and Energy Systems Engineering, Ewha Womans University, Seoul, Republic of Korea
Center for Climate/Environment Change Prediction Research and Severe Storm Research Center, Ewha Womans University, Seoul, Republic of Korea
Department of Climate and Energy Systems Engineering, Ewha Womans University, Seoul, Republic of Korea
Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
Center for Climate/Environment Change Prediction Research and Severe Storm Research Center, Ewha Womans University, Seoul, Republic of Korea
Marco Galli
Department of Physics and NatRisk Center, University of Torino “Alma Universitas Taurinorum”, Torino, Italy
now at: Air Force Mountain Centre, Sestola, Modena Province, Italy
Sungmin O
Institute for Geophysics, Astrophysics, and Meteorology, University of Graz, Graz, Austria
now at: Department of Biogechemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
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Sungmin O, Ji Won Yoon, and Seon Ki Park
Atmos. Meas. Tech., 18, 1471–1484, https://doi.org/10.5194/amt-18-1471-2025, https://doi.org/10.5194/amt-18-1471-2025, 2025
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Air pollutants such as particulate matter with diameters of 10 µm and 2.5 µm or less (PM10 and PM2.5) can cause adverse public health and environment effects; therefore their regular monitoring is crucial to keep pollutant concentrations under control. Our study demonstrates the potential of high-resolution aerosol optical depth (AOD) data from the Geostationary Environment Monitoring Spectrometer (GEMS) satellite to estimate ground-level PM concentrations using machine learning models.
Friedrich J. Bohn, Ana Bastos, Romina Martin, Anja Rammig, Niak Sian Koh, Giles B. Sioen, Bram Buscher, Louise Carver, Fabrice DeClerck, Moritz Drupp, Robert Fletcher, Matthew Forrest, Alexandros Gasparatos, Alex Godoy-Faúndez, Gregor Hagedorn, Martin Hänsel, Jessica Hetzer, Thomas Hickler, Cornelia B. Krug, Stasja Koot, Xiuzhen Li, Amy Luers, Shelby Matevich, H. Damon Matthews, Ina C. Meier, Awaz Mohamed, Sungmin O, David Obura, Ben Orlove, Rene Orth, Laura Pereira, Markus Reichstein, Lerato Thakholi, Peter Verburg, and Yuki Yoshida
EGUsphere, https://doi.org/10.5194/egusphere-2024-2551, https://doi.org/10.5194/egusphere-2024-2551, 2024
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An interdisciplinary collaboration of 35 international researchers from 34 institutions highlighting nine recent findings in biosphere research. Within these themes, they discuss issues arising from climate change and other anthropogenic stressors, and highlight the co-benefits of nature-based solutions and ecosystem services. They discuss recent findings in the context of global trade and international policy frameworks, and highlight lessons for local implementation of nature-based solutions.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-114, https://doi.org/10.5194/gmd-2024-114, 2024
Revised manuscript accepted for GMD
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This study evaluates the WRF-Chem model's prediction of a mega Asian Dust Storms (ADSs) over South Korea on March 28–29, 2021. We assessed five dust emission and four land surface schemes for predicting ADSs. Using surface observations and remote sensing data, we examined variables, such as temperature, humidity, wind speed, PM10, and aerosol optical depth. The UoC04 dust emission and CLM4 land surface scheme combination reduced RMSE for PM10 by up to 29.6 %, showing the best performance.
Sujeong Lim, Seon Ki Park, and Claudio Cassardo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-28, https://doi.org/10.5194/gmd-2023-28, 2023
Revised manuscript not accepted
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The ensembles in the numerical weather prediction system are under-dispersed near the land surface; therefore, an inflation method is required to increase it. In this study, we perturbed soil temperature and soil moisture to represent the near-surface uncertainty. Perturbations were obtained by the optimization algorithm taking into account diurnal variations in soil states. Consequently, it indirectly inflated the temperature and water vapor mixing ratio in the planetary boundary layer.
Manal Lam'barki, Wantong Li, Sungmin O, Chunhui Zhan, and Rene Orth
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-404, https://doi.org/10.5194/hess-2022-404, 2022
Manuscript not accepted for further review
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We investigate the main drivers of high river flows in near-natural European catchments. While there are a lot of previous research in this area, the understanding of the relative relevance of high flow drivers other than precipitation is understudied. We find that the secondary drivers of high river flows are very diverse and become more relevant for more extreme events. This illustrates the necessity of flood management by considering a multitude of drivers in the context of climate change.
Sujeong Lim, Hyeon-Ju Gim, Ebony Lee, Seungyeon Lee, Won Young Lee, Yong Hee Lee, Claudio Cassardo, and Seon Ki Park
Geosci. Model Dev., 15, 8541–8559, https://doi.org/10.5194/gmd-15-8541-2022, https://doi.org/10.5194/gmd-15-8541-2022, 2022
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The land surface model (LSM) contains various uncertain parameters, which are obtained by the empirical relations reflecting the specific local region and can be a source of uncertainty. To seek the optimal parameter values in the snow-related processes of the Noah LSM over South Korea, we have implemented an optimization algorithm, a micro-genetic algorithm using the observations. As a result, the optimized snow parameters improve snowfall prediction.
Melissa Ruiz-Vásquez, Sungmin O, Alexander Brenning, Randal D. Koster, Gianpaolo Balsamo, Ulrich Weber, Gabriele Arduini, Ana Bastos, Markus Reichstein, and René Orth
Earth Syst. Dynam., 13, 1451–1471, https://doi.org/10.5194/esd-13-1451-2022, https://doi.org/10.5194/esd-13-1451-2022, 2022
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Subseasonal forecasts facilitate early warning of extreme events; however their predictability sources are not fully explored. We find that global temperature forecast errors in many regions are related to climate variables such as solar radiation and precipitation, as well as land surface variables such as soil moisture and evaporative fraction. A better representation of these variables in the forecasting and data assimilation systems can support the accuracy of temperature forecasts.
Won Young Lee, Hyeon-Ju Gim, and Seon Ki Park
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-319, https://doi.org/10.5194/tc-2021-319, 2021
Manuscript not accepted for further review
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Snow cover or snow albedo plays a vital role in the atmosphere and land surface interaction. Especially, direct observation of snow is difficult and scarce. That's why a reliable Land Surface Model (LSM), including snow physical processes, is significant. In this study, we tried to give meaningful insights for improving the LSM in the future by identifying the main variables or parameters used and examining the different formulas for snow-related processes of the eight LSMs.
Sojung Park and Seon K. Park
Geosci. Model Dev., 14, 6241–6255, https://doi.org/10.5194/gmd-14-6241-2021, https://doi.org/10.5194/gmd-14-6241-2021, 2021
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One of the biggest uncertainties in numerical weather predictions (NWPs) comes from treating subgrid-scale physical processes. Physical processes, such as cumulus, microphysics, and planetary boundary layer processes, are parameterized in NWP models by empirical and theoretical backgrounds. We developed an interface between a micro-genetic algorithm and the WRF model for a combinatorial optimization of physics for heavy rainfall events in Korea. The system improved precipitation forecasts.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
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Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Clara Hohmann, Gottfried Kirchengast, Sungmin O, Wolfgang Rieger, and Ulrich Foelsche
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-453, https://doi.org/10.5194/hess-2020-453, 2020
Manuscript not accepted for further review
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Heavy precipitation events are still feeding with a large uncertainty into hydrological models. Based on the highly dense station network WegenerNet (one station per 2 km2) we analyzed the sensitivity of runoff simulations to different rain network densities and interpolation methods in small catchments. We find, and quantify relevant characteristics, that runoff curves especially from
short-duration convective rainfall events are strongly influenced by gauge station density and distribution.
Ali Fallah, Sungmin O, and Rene Orth
Hydrol. Earth Syst. Sci., 24, 3725–3735, https://doi.org/10.5194/hess-24-3725-2020, https://doi.org/10.5194/hess-24-3725-2020, 2020
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We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs. In contrast, simulated evapotranspiration is generally much less influenced in our comparatively wet study region. We also find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration.
Martin Lasser, Sungmin O, and Ulrich Foelsche
Atmos. Meas. Tech., 12, 5055–5070, https://doi.org/10.5194/amt-12-5055-2019, https://doi.org/10.5194/amt-12-5055-2019, 2019
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This paper evaluates the rain rate estimates from the Global Precipitation Measurement (GPM) mission's radar instrument by comparing them to the data of the WegenerNet, a local-scale high-resolution network of meteorological stations. Our results show that the GPM-DPR estimates basically match with the WegenerNet measurements, but absolute quantities are biased.
Sungmin O and Ulrich Foelsche
Hydrol. Earth Syst. Sci., 23, 2863–2875, https://doi.org/10.5194/hess-23-2863-2019, https://doi.org/10.5194/hess-23-2863-2019, 2019
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We analyze heavy local rainfall to address questions regarding the spatial uncertainty due to the approximation of areal rainfall using point measurements. Ten years of rainfall data from a dense network of 150 rain gauges in southeastern Austria are employed, which permits robust examination of small-scale rainfall at various horizontal resolutions. Quantitative uncertainty information from the study can guide both data users and producers to estimate uncertainty in their own rainfall dataset.
Da-Eun Kim and Seon Ki Park
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-15, https://doi.org/10.5194/tc-2019-15, 2019
Preprint withdrawn
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An accurate prediction of the Eurasian snow is essentially important in predicting the climate and weather phenomena in Asia. Regional climate models are mostly coupled with several land surface models (LSMs) in which the land surface process parameters are calculated under their own physical principles and parameterization schemes. We show that prediction of the Eurasian snow cover is sensitive to the choice of LSMs coupled to regional climate models, and hence the future climate projections.
Sojung Park, Seon Ki Park, Jeung Whan Lee, and Yunho Park
Hydrol. Earth Syst. Sci., 22, 3435–3452, https://doi.org/10.5194/hess-22-3435-2018, https://doi.org/10.5194/hess-22-3435-2018, 2018
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Understanding the precipitation characteristics is essential to design an optimal observation network. We studied the spatial and temporal characteristics of summertime precipitation systems in Korea via geostatistical analyses on the ground-based precipitation and satellite water vapor data. We found that, under a strict standard, an observation network with higher resolution is required in local areas with frequent heavy rainfalls, depending on directional features of precipitation systems.
Sungmin O, Ulrich Foelsche, Gottfried Kirchengast, Juergen Fuchsberger, Jackson Tan, and Walter A. Petersen
Hydrol. Earth Syst. Sci., 21, 6559–6572, https://doi.org/10.5194/hess-21-6559-2017, https://doi.org/10.5194/hess-21-6559-2017, 2017
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We evaluate gridded satellite rainfall estimates, from GPM IMERG, through a direct grid-to-grid comparison with gauge data from the WegenerNet Feldbach (WEGN) network in southeastern Austria. As the WEGN data are independent of the IMERG gauge adjustment process, we could analyze the IMERG estimates across its three different runs. Our results show the effects of additional retrieval processes on the final rainfall estimates, and consequently provide IMERG accuracy information for data users.
Sojung Park and Seon Ki Park
Geosci. Model Dev., 9, 1073–1085, https://doi.org/10.5194/gmd-9-1073-2016, https://doi.org/10.5194/gmd-9-1073-2016, 2016
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Snow albedo varies with snow grain size, snow cover thickness, etc. It also depends on the spatial characteristics of land cover and on the canopy density and structure. The Noah-MP model shows a bias error of albedo in winter due to no proper reflection of the vegetation effect. We developed new parameters, called leaf index and stem index, which reflect the vegetation effect on winter albedo. The Noah-MP's performance in albedo has prominently improved with about 69 % decrease in the RMSE.
J. Kim and S. K. Park
Hydrol. Earth Syst. Sci., 20, 651–658, https://doi.org/10.5194/hess-20-651-2016, https://doi.org/10.5194/hess-20-651-2016, 2016
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This study examined the uncertainty in climatological precipitation in East Asia, calculated from five gridded analysis data sets based on in situ rain gauge observations from 1980 to 2007. It is found that the regions of large uncertainties are typically lightly populated and are characterized by severe terrain and/or very high elevations. Thus, care must be taken in using long-term trends calculated from gridded precipitation analysis data for climate studies over such regions in East Asia.
S. Lim, S. K. Park, and M. Zupanski
Atmos. Chem. Phys., 15, 10019–10031, https://doi.org/10.5194/acp-15-10019-2015, https://doi.org/10.5194/acp-15-10019-2015, 2015
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In this study, the impact of O3 observations on the tropical cyclone (TC) structure is examined using the WRF-Chem with an ensemble-based data assimilation (DA) system. For a TC case that occurred over East Asia, the ensemble forecast is reasonable and the O3 assimilation affects both chemical and atmospheric variables near the TC area. All measures indicate a positive impact of DA on the analysis – the cost function and root mean square error have decreased by 16.9% and 8.87%, respectively.
S. K. Park, S. Lim, and M. Zupanski
Geosci. Model Dev., 8, 1315–1320, https://doi.org/10.5194/gmd-8-1315-2015, https://doi.org/10.5194/gmd-8-1315-2015, 2015
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The structure of an ensemble-based coupled atmosphere-chemistry forecast error covariance is examined using the WRF-Chem, a coupled atmosphere-chemistry model. It is found that the coupled error covariance has important cross-variable components that allow a physically meaningful adjustment of all control variables. Additional benefit of the coupled error covariance is that a cross-component impact is allowed; e.g., atmospheric observations can exert impact on chemistry analysis, and vice versa.
S. Hong, X. Yu, S. K. Park, Y.-S. Choi, and B. Myoung
Geosci. Model Dev., 7, 2517–2529, https://doi.org/10.5194/gmd-7-2517-2014, https://doi.org/10.5194/gmd-7-2517-2014, 2014
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Distribution, trends, and drivers of flash droughts in the United Kingdom
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada
Assessment of seasonal soil moisture forecasts over the Central Mediterranean
Do land models miss key soil hydrological processes controlling soil moisture memory?
Observation-driven model for calculating water-harvesting potential from advective fog in (semi-)arid coastal regions
Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets
Downscaling the probability of heavy rainfall over the Nordic countries
Modelling convective cell life cycles with a copula-based approach
Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5
Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model
Assessing rainfall radar errors with an inverse stochastic modelling framework
Towards a Robust Hydrologic Data Assimilation System for Hurricane-induced River Flow Forecasting
Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau
Skilful probabilistic predictions of UK floods months ahead using machine learning models trained on multimodel ensemble climate forecasts
FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America
On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy
An increase in the spatial extent of European floods over the last 70 years
140-year daily ensemble streamflow reconstructions over 661 catchments in France
Deep learning based sub-seasonal precipitation and streamflow forecasting over the source region of the Yangtze River
The agricultural expansion in South America's Dry Chaco: regional hydroclimate effects
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Improving runoff simulation in the Western United States with Noah-MP and VIC models
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Assessing downscaling methods to simulate hydrologically relevant weather scenarios from a global atmospheric reanalysis: case study of the upper Rhône River (1902–2009)
Global total precipitable water variations and trends over the period 1958–2021
Assessing decadal- to centennial-scale nonstationary variability in meteorological drought trends
Identification of compound drought and heatwave events on a daily scale and across four seasons
Implementation of global soil databases in NOAH-MP model and the effects on simulated mean and extreme soil hydrothermal changes
Potential for historically unprecedented Australian droughts from natural variability and climate change
Enhanced Evaluation of Sub-daily and Daily Extreme Precipitation in Norway from Convection-Permitting Models at Regional and Local Scales
Flood risk assessment for Indian sub-continental river basins
Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities
Divergent future drought projections in UK river flows and groundwater levels
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model
Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework
Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
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We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
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Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
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The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
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Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
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Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
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This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
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Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
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Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
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We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
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We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
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This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
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This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
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Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
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Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Peyman Abbaszadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-209, https://doi.org/10.5194/hess-2024-209, 2024
Revised manuscript accepted for HESS
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The Hybrid Ensemble and Variational Data Assimilation framework for Environmental System (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three Southeastern U.S. watersheds during hurricanes, HEAVEN assimilates real-time USGS streamflow data, boosting forecast accuracy.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
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To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
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We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Simon Moulds, Louise Slater, Louise Arnal, and Andrew Wood
EGUsphere, https://doi.org/10.31223/X5X405, https://doi.org/10.31223/X5X405, 2024
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Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to four months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to four months ahead in many locations, although in general the skill declines with increasing lead time.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-212, https://doi.org/10.5194/hess-2024-212, 2024
Revised manuscript accepted for HESS
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Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather impacts, yet current long-term forecast products are often embedded with uncertainties. We develop a deep learning based modelling framework to improve 30-day rainfall and streamflow forecasts by combining advanced neural networks and outputs from physical models. With the forecast error reduced by up to 32%, the framework has the potential to enhance water management and disaster preparedness.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Kazeem Ishola, Gerald Mills, Ankur Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-304, https://doi.org/10.5194/hess-2023-304, 2024
Revised manuscript accepted for HESS
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The global soil information contributes to uncertainty in many models that monitor soil hydrothermal changes. Using the NOAH-MP model with two different global soil information, we show under-represented soil properties in wet loam soil, leading to dry bias in soil moisture. The dry bias is higher and drought categories are more severe in SOILGRIDS. We conclude that models should consider using detailed regionally-derived soil information, to reduce model uncertainties.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Gokturk
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-68, https://doi.org/10.5194/hess-2024-68, 2024
Revised manuscript accepted for HESS
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We compared extreme precipitations in Norway from convection-permitting models at 3 km resolution (HCLIM3) and regional climate model at 12 km (HCLIM12) and show that the HCLIM3 is more accurate than HCLIM12 in predicting the intense rainfalls that can lead to floods, especially at local scales. This is more clear in hourly extremes than daily. Our research suggests using more detailed climate models could improve forecasts, helping the local society brace for the impacts of extreme weather.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Cited articles
Abiodun, B. J., Pal, J. S., Afiesimama, E. A., Gutowski, W. J., and Adedoyin,
A.: Simulation of West African Monsoon using RegCM3. Part II: Impact of
desertification and deforestation, Theor. Appl. Climatol., 93, 245–261,
2007. a
Adam, J. C., Hamlet, A. F., and Lettenmaier, D. P.: Implications of global
climate change for snowmelt hydrology in the twenty-first century, Hydrol.
Process., 23, 962–972, 2009. a
Addor, N., Rössler, O., Köplin, N., Huss, M., Weingartner, R., and
Seibert, J.: Robust changes and sources of uncertainty in the projected
hydrological regimes of Swiss catchments, Water Resour. Res., 50, 7541–7562,
https://doi.org/10.1002/2014WR015549, 2014. a, b
Alo, C. A. and Anagnostou, E. N.: A sensitivity study of the impact of
dynamic vegetation on simulated future climate change over Southern Europe
and the Mediterranean, Int. J. Climatol., 37, 2037–2050, https://doi.org/10.1002/joc.4833, 2017. a
Anthes, R.: A cumulus parametrization scheme utilizing a one-dimensional
cloud model, Mon. Weather Rev., 105, 270–286, 1977. a
Araújo, M. B., Nogués-Bravo, D., Reginster, I., Rounsevell, M., and
Whittaker, R. J.: Exposure of European biodiversity to changes in
human-induced pressures, Environ. Sci. Policy, 11, 38–45, https://doi.org/10.1016/j.envsci.2007.07.002, 2008. a
Ayers, M. A., Wolock, D. M., McCabe, G. J., and Hay, L. E.: Hydrologic
effects of climatic change in the Delaware River basin, in: US Geological
Survey Yearbook, Fiscal Year 1989, US Government Printing Office,
Washington, DC, USA, 31–33, 1990. a
Baker, N. C. and Huang, H.-P.: A comparative study of precipitation and
evaporation between CMIP3 and CMIP5 climate model ensembles in semiarid
regions, J. Climate, 27, 3731–3749, https://doi.org/10.1175/JCLI-D-13-00398.1, 2014.
a, b
Ballester, J., Rodó, X., and Giorgi, F.: Future changes in Central Europe
heat waves expected to mostly follow summer mean warming, Clim. Dynam., 35,
1191–1205, https://doi.org/10.1007/s00382-009-0641-5, 2010. a
Barange, M., Merino, G., Blanchard, J. L., Scholtens, J., Harle, J., Allison,
E. H., Allen, J. I., Holt, J., and Jennings, S.: Impacts of climate change on
marine ecosystem production in societies dependent on fisheries, Nature Clim.
Change, 4, 211–216, https://doi.org/10.1038/nclimate2119, 2014. a
Belda, M., Skalák, P., Farda, A., Halenka, T., Déqué, M., Csima,
G., Bartholy, J., Torma, C., Boroneant, C., Caian, M., and Spiridonov, V.:
CECILIA regional climate simulations for future climate: Analysis of climate
change signal, Adv. Meteorol., 2015, 354727, https://doi.org/10.1155/2015/354727, 2015. a
Beniston, M.: Mountain weather and climate: A general overview and a focus on
climatic change in the Alps, Hydrobiologia, 562, 3–16,
https://doi.org/10.1007/s10750-005-1802-0, 2006. a, b
Beniston, M.: Trends in joint quantiles of temperature and precipitation in
Europe since 1901 and projected for 2100, Geophys. Res. Lett., 36, L07707,
https://doi.org/10.1029/2008GL037119, 2009. a
Beniston, M., Stephenson, D. B., Christensen, O. B., Ferro, C. A. T., Frei,
C., Goyette, S., Halsnaes, K., Holt, T., Jylhü, K., Koffi, B.,
Palutikoff, J., Schöll, R., Semmler, T., and Woth, K.: Future extreme
events in European climate: an exploration of regional climate model
projections, Clim. Change, 81, 71–95, https://doi.org/10.1007/s10584-006-9226-z, 2007. a
Berg, P., Moseley, C., and Haerter, J. O.: Strong increase in convective
precipitation in response to higher temperatures, Nat. Geosci., 6, 181–185,
https://doi.org/10.1038/ngeo1731, 2013. a
Bhaskaran, B., Ramachandran, A., Jones, R., and Moufouma-Okia, W.: Regional
climate model applications on sub-regional scales over the Indian monsoon
region: The role of domain size on downscaling uncertainty, J. Geophys. Res.,
117, D10113, https://doi.org/10.1029/2012JD017956, 2012. a
Blenkinsop, S. and Fowler, H. J.: Changes in European drought characteristics
projected by the PRUDENCE regional climate models, Int. J. Climatol., 27,
1595–1610, https://doi.org/10.1002/joc.1538, 2007. a
Boberg, F., Berg, P., Thejll, P., Gutowski, W. J., and Christensen, J. H.:
Improved confidence in climate change projections of precipitation evaluated
using daily statistics from the PRUDENCE ensemble, Clim. Dynam., 32,
1097–1106, https://doi.org/10.1007/s00382-008-0446-y, 2009. a
Bonanno, R., Loglisci, N., Cavalletto, S., and Cassardo, C.: Analysis of
different freezing/thawing parameterizations using the UTOPIA model, Water,
2, 468–483, 2010. a
Bultot, F., Coppens, A., Dupriez, G. L., Gellens, D., and Meulenberghs, F.:
Repercussions of a CO2 doubling on the water cycle and on the water
balance – a case study for Belgium, J. Hydrol., 99, 319–347, 1988. a
Buonomo, E., Jones, R., Huntingford, C., and Hannaford, J.: On the robustness
of changes in extreme precipitation over Europe from two high resolution
climate change simulations, Q. J. R. Meteor. Soc., 133, 65–81,
https://doi.org/10.1002/qj.13, 2007. a
Burden, R. L. and Faires, J. D.: Numerical Analysis, Brooks/Cole, Boston, MA,
USA, 2004. a
Buytaert, W., Celleri, R., and Timbe, L.: Predicting climate change impacts
on water resources in the tropical Andes: Effects of GCM uncertainty,
Geophys. Res. Lett., 36, L07406, https://doi.org/10.1029/2008GL037048, 2009. a
Cabré, M. F., Solman, S. A., and Nunez, M. N.: Regional climate change
scenarios over southern South America for future climate (2080–2099) using
the MM5 model. Mean, interannual variability and uncertainties,
Atmósfera, 29, 35–60, https://doi.org/10.20937/ATM.2016.29.01.04, 2016. a
Calzadilla, A., Rehdanz, K., Betts, R., Falloon, P., Wiltshire, A., and Tol,
R. S. J.: Climate change impacts on global agriculture, Clim. Change, 120,
357–374, https://doi.org/10.1007/s10584-013-0822-4, 2013. a
Carvalho, A., Monteiro, A., Solman, S., Miranda, A. I., and Borrego, C.:
Climate-driven changes in air quality over Europe by the end of the 21st
century, with special reference to Portugal, Environ. Sci. Policy, 13,
445–458, https://doi.org/10.1016/j.envsci.2010.05.001, 2010. a
Casajus, N., Périé, C., Logan, T., Lambert, M.-C., de Blois, S., and
Berteaux, D.: An objective approach to select climate scenarios when
projecting species distribution under climate change, PLoS ONE,
11, e0152495,
https://doi.org/10.1371/journal.pone.0152495, 2016. a, b
Cassardo, C.: The land surface process model (LSPM) version 2006, Tech. Rep.
DFG Report – 01/2006, Dipartimento di Fisica Generale Amedeo Avogadro,
University of Torino, Torino, Italy, 2006. a
Cassardo, C., Ji, J. J., and Longhetto, A.: A study of the performances of a
land surface process model (LSPM), Bound.-Lay. Meteorol., 72, 87–121, 1995. a
Cassardo, C., Ruti, P. M., Cacciamani, C., Longhetto, A., Paccagnella, T.,
and Bargagli, A.: CLIPS experiment. First step: model intercomparison and
validation against experimental data, MAP Newsletters, 7, 74–75, 1997. a
Cassardo, C., Carena, E., and Longhetto, A.: Validation and sensitivity tests
on improved parametrizations of a land surface process model (LSPM) in the Po
Valley, Il Nuovo Cimento, 21, 189–213, 1998. a
Cassardo, C., Loglisci, N., Gandini, D., Qian, M. W., Niu, Y. P., Ramieri,
P., Pelosini, R., and Longhetto, A.: The flood of November 1994 in Piedmont,
Italy: A quantitative simulation, Hydrol. Process., 16, 1275–1299,
2002. a
Cassardo, C., Loglisci, N., and Romani, M.: Preliminary results of an attempt
to provide soil moisture datasets in order to verify numerical weather
prediction models, Il Nuovo Cimento, 28, 159–171, 2005. a
Cassardo, C., Loglisci, N., Paesano, G., Rabuffetti, D., and Qian, M. W.: The
hydrological balance of the October 2000 flood in Piedmont, Italy:
Quantitative analysis and simulation, Phys. Geogr., 27, 411–434, 2006. a
Cassardo, C., Mercalli, L., and Cat Berro, D.: Characteristics of the summer
2003 heat wave in Piedmont, Italy, and its effects on water resources, J.
Korean Meteor. Soc., 43, 195–221, 2007. a
Christensen, J. H. and Christensen, O. B.: A summary of the PRUDENCE model
projections of changes in European climate by the end of this century, Clim.
Change, 81, 7–30, https://doi.org/10.1007/s10584-006-9210-7, 2007. a
Christensen, J. H., Carter, T. R., Rummukainen, M., and Amanatidis, G.:
Evaluating the performance and utility of regional climate models: the
PRUDENCE project, Clim. Change, 81, 1–6, https://doi.org/10.1007/s10584-006-9211-6,
2007. a, b
Ciscar, J.-C., Iglesias, A., Feyen, L., Szabó, L., Van Regemorter, D.,
Amelung, B., Nicholls, R., Watkiss, P., Christensen, O. B., Dankers, R.,
Garrote, L., Goodess, C. M., Hunt, A., Moreno, A., Richards, J., and Soria,
A.: Physical and economic consequences of climate change in Europe, P. Natl.
Acad. Sci. USA, 108, 2678–2683, https://doi.org/10.1073/pnas.1011612108, 2011. a
Coppola, E. and Giorgi, F.: An assessment of temperature and precipitation
change projections over Italy from recent global and regional climate model
simulations, Int. J. Climatol., 30, 11–32, https://doi.org/10.1002/joc.1867, 2010. a, b, c, d
Coppola, E., Verdecchia, M., Giorgi, F., Colaiuda, V., Tomassetti, B., and
Lombardi, A.: Changing hydrological conditions in the Po basin under global
warming, Sci. Total Environ., 493, 1183–1196,
https://doi.org/10.1016/j.scitotenv.2014.03.003, 2014. a, b, c, d
Crosbie, R. S., Binning, P., and Kalma, J. D.: A time series approach to
inferring groundwater recharge using the water table fluctuation method,
Water Resour. Res., 41, W01008, https://doi.org/10.1029/2004WR003077, 2005. a
Dankers, R. and Feyen, L.: Climate change impact on flood hazard in Europe:
An assessment based on high-resolution climate simulations, J. Geophys. Res.,
113, D19105, https://doi.org/10.1029/2007JD009719, 2008. a
da Silva, R. S., Kumar, L., Shabani, F., and Picanço, M. C.: Potential
risk levels of invasive Neoleucinodes elegantalis (small tomato
borer) in areas optimal for open-field Solanum lycopersicum (tomato)
cultivation in the present and under predicted climate change, Pest. Manag.
Sci., 73, 616–627, https://doi.org/10.1002/ps.4344, 2017. a
Déqué, M.: Frequency of precipitation and temperature extremes over
France in an anthropogenic scenario: Model results and statistical correction
according to observed values, Global Planet. Change, 57, 16–26,
https://doi.org/10.1016/j.gloplacha.2006.11.030, 2007. a
Déqué, M., Jones, R. G., Wild, M., Giorgi, F., Christensen, J. H.,
Hassell, D. C., Vidale, P. L., Rockel, B., Jacob, D., Kjellström, E., de
Castro, M., Kucharski, F., and van den Hurk, B.: Global high resolution
versus limited area model climate change projections over Europe: quantifying
confidence level from PRUDENCE results, Clim. Dynam., 25, 653–670,
https://doi.org/10.1007/s00382-005-0052-1, 2005. a
Déqué, M., Rowell, D.P., Lüthi, D., Giorgi, F., Christensen, J.
H., Rockel, B., Jacob, D., Kjellström, E., de Castro, M., and van den
Hurk, B.: An intercomparison of regional climate simulations for Europe:
assessing uncertainties in model projections, Clim. Change, 81, 53–70,
https://doi.org/10.1007/s10584-006-9228-x, 2007. a
Dickinson, R. E., Errico, R. M., Giorgi, F., and Bates, G. T.: A regional
climate model for the western United States, Clim. Change, 15, 383–442,
1989. a
Dickinson, R. E., Henderson-Sellers, A., and Kennedy, P.:
Biosphere-atmosphere transfer scheme (BATS) version 1e as coupled to the NCAR
community climate model, Tech. Rep., National Center for Atmospheric
Research, Boulder, CO, USA, 1993. a
Diffenbaugh, N. S. and Giorgi, F.: Climate change hotspots in the CMIP5
global climate model ensemble, Clim. Change, 114, 813–822,
https://doi.org/10.1007/s10584-012-0570-x, 2012. a, b
Diffenbaugh, N. S., Pal, J. S., Trapp, R. J., and Giorgi, F.: Fine-scale
processes regulate the response of extreme events to global climate change,
P. Natl. Acad. Sci. USA, 102, 15774–15778, 2005. a
Dobler, C., Hagemann, S., Wilby, R. L., and Stötter, J.: Quantifying
different sources of uncertainty in hydrological projections in an Alpine
watershed, Hydrol. Earth Syst. Sci., 16, 4343–4360,
https://doi.org/10.5194/hess-16-4343-2012, 2012. a, b
Dunford, R. W., Smith, A. C., Harrison, P. A., and Hanganu, D.: Ecosystem
service provision in a changing Europe: adapting to the impacts of combined
climate and socio-economic change, Landscape Ecol., 30, 443–461,
https://doi.org/10.1007/s10980-014-0148-2, 2015. a, b
EEA: Regional Climate Change and Adaptation, The Alps Facing the Challenge of
Changing Water Resources, European Environment Agency, Copenhagen, Denmark,
2009. a
Elguindi, N., Bi, X., Giorgi, F., Nagarajan, B., Pal, J., Solmon, F.,
Rauscher, S., and Zakey, A.: RegCM version 3.1 user's guide, Tech. Rep.,
ICTP, Trieste, Italy, 2007. a
Emanuel, K. A.: A scheme for representing cumulus convection in large-scale
models, J. Atmos. Sci., 48, 2313–2329, 1991. a
Emanuel, K. A. and Živković-Rothman, M.: Development and evaluation
of a convection scheme for use in climate models, J. Atmos. Sci., 56,
1766–1782, 1999. a
Faggian, P.: Climate change projections for Mediterranean region with focus
over Alpine region and Italy, J. Environ. Sci. Eng. B, 4, 482–500,
https://doi.org/10.17265/2162-5263/2015.09.004, 2015. a, b
Feehan, J., Harley, M., and van Minnen, J.: Climate change in Europe. 1.
Impact on terrestrial ecosystems and biodiversity. A review, Agron. Sustain.
Dev., 29, 409–421, https://doi.org/10.1051/agro:2008066, 2009. a
Feng, J., Liu, X., Cassardo, C., and Longhetto, A.: A model of plant
transpiration and stomatal regulation under the condition of water stress, J.
Desert Res., 17, 59–66, 1997. a
Flaschka, I. M., Stockton, C. W., and Boggess, W. R.: Climatic variation and
surface water resources in the Great Basin region, Water Resour. Bull., 23,
47–57, 1987. a
Francone, C., Cassardo, C., Spanna, F., Alemanno, L., Bertoni, D.,
Richiardone, R., and Vercellino, I.: Preliminary results on the evaluation of
factors influencing evapotranspiration processes in vineyards, Water, 2,
916–937, 2010. a
Francone, C., Cassardo, C., Richiardone, R., and Confalonieri, R.:
Sensitivity analysis and investigation of the behaviour of the UTOPIA
land-surface process model: A case study for vineyards in northern Italy,
Bound.-Lay. Meteorol., 144, 419–430, 2012a. a
Francone, C., Katul, G. G., Cassardo, C., and Richiardone, R.: Turbulent
transport efficiency and the ejection-sweep motion for momentum and heat on
sloping terrain covered with vineyards, Agr. Forest Meteorol., 162–163,
98–107, 2012b. a
Frei, C., Schöll, R., Fukutome, S., Schmidli, J., and Vidale, P. L.:
Future change of precipitation extremes in Europe: Intercomparison of
scenarios from regional climate models, J. Geophys. Res., 111, D06105,
https://doi.org/10.1029/2005JD005965, 2006. a
Frei, P., Kotlarski, S., Liniger, M. A., and Schär, C.: Future snowfall
in the Alps: projections based on the EURO-CORDEX regional climate models,
The Cryosphere, 12, 1–24, https://doi.org/10.5194/tc-12-1-2018, 2018. a, b
Fronzek, S., Carter, T. R., and Jylhä, K.: Representing two centuries of
past and future climate for assessing risks to biodiversity in Europe, Global
Ecol. Biogeogr., 21, 19–35, https://doi.org/10.1111/j.1466-8238.2011.00695.x, 2012. a
Gang, C., Zhang, Y., Wang, Z., Chen, Y., Yang, Y., Li, J., Cheng, J., Qi, J.,
and Odeh, I.: Modeling the dynamics of distribution, extent, and NPP of
global terrestrial ecosystems in response to future climate change, Global
Planet. Change, 148, 153–165, 2017. a
Gim, H.-J., Park, S. K., Kang, M., Thakuri, B. M., Kim, J., and Ho, C.-H.: An
improved parameterization of the allocation of assimilated carbon to plant
parts in vegetation dynamics for Noah-MP, J. Adv. Model. Earth
Sy., 9, 1776–1794,
https://doi.org/10.1002/2016MS000890, 2017. a
Giorgi, F.: Simulation of regional climate using a limited area model nested
in a general circulation model, J. Climate, 3, 941–963, 1990. a
Giorgi, F.: Sensitivity of simulated summertime precipitation over the
western United States to different physics parametrization, Mon. Weather
Rev., 119, 2870–2888, 1991. a
Giorgi, F.: Climate change hot-spots, Geophys. Res. Lett., 33, L08707,
https://doi.org/10.1029/2006GL025734, 2006. a, b
Giorgi, F. and Diffenbaugh, N.: Developing regional climate change scenarios
for use in assessment of effects on human health and disease, Clim. Res., 36,
141–151, https://doi.org/10.3354/cr00728, 2008. a
Giorgi, F. and Shields, C.: Tests of precipitation parametrizations available
in latest version of NCAR regional climate model (RegCM) over continental
United States, J. Geophys. Res., 104, 6353–6375, 1999. a
Giorgi, F., Bates, G. T., and Nieman, S. J.: The multi-year surface
climatology of a regional atmospheric model over the western United States,
J. Climate, 6, 75–95, 1993. a
Giorgi, F., Hurrell, J. W., Marinucci, M. R., and Beniston, M.: Elevation
signal in surface climate change: a model study, J. Climate, 10, 288–296,
https://doi.org/10.1175/1520-0442(1997)010<0288:EDOTSC>2.0.CO;2, 1997. a, b
Giorgi, F., Bi, X., and Qian, Y.: Indirect vs. direct effects of
anthropogenic sulfate on the climate of East Asia as simulated with a
regional coupled climate-chemistry/aerosol model, Clim. Change, 58, 345–376,
2003a. a
Giorgi, F., Francisco, R., and Pal, J. S.: Effects of a subgrid-scale
topography and land use scheme on the simulation of surface climate and
hydrology. Part I: Effects of temperature and water vapour disaggregation, J.
Hydrometeorol., 4, 317–333, 2003b. a
Gleick, P. H.: Methods for evaluating the regional hydrologic impacts of
global climatic changes, J. Hydrol., 88, 97–116, 1986. a
Gleick, P. H.: The development and testing of a water balance model for
climate impact assessment: modelling the Sacramento basin, Water Resour.
Res., 23, 1049–1061, 1987. a
Gobiet, A., Kotlarski, S., Beniston, M., Heinrich, G., Rajczak, J., and
Stoffel, M.: 21st century climate change in the European Alps – A review,
Sci. Total Environ., 493, 1138–1151, https://doi.org/10.1016/j.scitotenv.2013.07.050,
2014. a, b, c, d
Grell, G.: Prognostic evaluation of assumptions used by cumulus
parametrizations, Mon. Weather Rev., 121, 764–787, 1993. a
Harrison, P. A., Dunford, R. W., Holman, I. P., and Rounsevell, M. D. A.:
Climate change impact modelling needs to include cross-sectoral interactions,
Nature Clim. Change, 6, 885–890, https://doi.org/10.1038/nclimate3039, 2016. a, b
Hassan, I., Ghumman, A. R., Ghazaw, Y., Abdel-Maguid, R. H., and Samreen, B.:
Climate change impact on precipitation in arid areas of Pakistan, Int. J.
Water Resour. Arid Environ., 6, 80–88, 2017. a
Heinrich, G., Gobiet, A., and Mendlik, T.: Extended regional climate model
projections for Europe until the mid-twentyfirst century: combining ENSEMBLES
and CMIP3, Clim. Dynam., 42, 521–535, https://doi.org/10.1007/s00382-013-1840-7, 2014. a, b
Herrera, S., Fita, L., Fernández, J., and Gutiérrez, J. M.:
Evaluation of the mean and extreme precipitation regimes from the ENSEMBLES
regional climate multimodel simulations over Spain, J. Geophys. Res., 115,
D21117, https://doi.org/10.1029/2010JD013936, 2010. a
Hong, S., Yu, X., Park, S. K., Choi, Y.-S., and Myoung, B.: Assessing optimal
set of implemented physical parameterization schemes in a multi-physics land
surface model using genetic algorithm, Geosci. Model Dev., 7, 2517–2529,
https://doi.org/10.5194/gmd-7-2517-2014, 2014. a
Hong, S., Park, S. K., and Yu, X.: Scheme-based optimization of land surface
model using a micro-genetic algorithm: Assessment of its performance and
usability for regional applications, Sci. Online Lett. Atmos., 11, 129–133,
2015. a
Hoogwijk, M., Faaij, A., Eickhout, B., de Vries, B., and Turkenburg, W.:
Potential of biomass energy out to 2100, for four IPCC SRES land-use
scenarios, Biomass Bioenerg., 29, 225–257,
https://doi.org/10.1016/j.biombioe.2005.05.002, 2005. a
Hostetler, S. W. and Bartlein, P. J.: Simulation of lake evaporation with
application to modelling lake level variations of Harney-Malheur Lake,
Oregon, Water Resour. Res., 26, 2603–2612, 1990. a
Im, E.-S., Coppola, E., Giorgi, F., and Bi, X.: Local effects of climate
change over the Alpine region: A study with a high resolution regional
climate model with a surrogate climate change scenario, Geophys. Res. Lett.,
37, L05704, https://doi.org/10.1029/2009GL041801, 2010. a, b, c, d
IPCC: Climate Change 2007: The Physical Science Basis. Contribution of
Working Group I to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen,
Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge
University Press, Cambridge, UK, 2007. a, b, c
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of
Working Group I to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K.,
Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and
Midgley, P. M., Cambridge University Press, Cambridge, UK, 2013. a, b
Jacob, D. J. and Winner, D. A.: Effect of climate change on air quality,
Atmos. Environ., 43, 51–63, https://doi.org/10.1016/j.atmosenv.2008.09.051, 2009. a
Jacob, D., Bärring, L., Christensen, O. B., Christensen, J. H., de
Castro, M., Déqué, M., Giorgi, F., Hagemann, S., Hirschi, M., Jones,
R., Kjellström, E., Lenderink, G., Rockel, B., Sánchez, E.,
Schär, C., Seneviratne, S. I., Somot, S., van Ulden, A., and van den
Hurk, B.: An inter-comparison of regional climate models for Europe: model
performance in present-day climate, Clim. Change, 81, 31–52,
https://doi.org/10.1007/s10584-006-9213-4, 2007. a
Jacob, D., Göttel, H., Kotlarski, S., and Lorenz, P.: Mögliche
Klimaänderungen im Alpenraum, in: Klimawandel in den Alpen: Fakten –
Folgen – Anpassung, Bundesministerium für Umwelt, Naturschutz und
Reaktorsicherheit, Berlin, Germany, 22–27, 2007. a
Jaczewski, A., Brzoska, B., and Wibig, J.: Comparison of temperature indices
for three IPCC SRES scenarios based on RegCM simulations for Poland in
2011–2030 period, Meteorol. Z., 24, 99–106, https://doi.org/10.1127/metz/2014/0457,
2015. a
Jiang, Z., Song, J., Li, L., Chen, W., Wang, Z., and Wang, J.: Extreme
climate events in China: IPCC-AR4 model evaluation and projection, Clim.
Change, 110, 385–401, https://doi.org/10.1007/s10584-011-0090-0, 2012. a
Jones, C., Lowe, J., Liddicoat, S., and Betts, R.: Committed terrestrial
ecosystem changes due to climate change, Nat. Geosci., 2, 484–487,
https://doi.org/10.1038/ngeo555, 2009. a
Jury, M. W., Prein, A. F., Truhetz, H., and Gobiet, A.: Evaluation of CMIP5
models in the context of dynamical downscaling over Europe, J. Climate, 28,
5575–5582, https://doi.org/10.1175/JCLI-D-14-00430.1, 2015. a
Kiguchi, M., Shen, Y., Kanae, S., and Oki, T.: Re-evaluation of future water
stress due to socio-economic and climate factors under a warming climate,
Hydrolog. Sci. J., 60, 14–29, https://doi.org/10.1080/02626667.2014.888067, 2015. a
Kim, S. B., Shin, H. J., Park, M., and Kim, S. J.: Assessment of future
climate change impacts on snowmelt and stream water quality for a mountainous
high-elevation watershed using SWAT, Paddy Water Environ., 13, 557–569,
https://doi.org/10.1007/s10333-014-0471-x, 2015. a
Klausmeyer, K.: Effects of climate change on the hydrology of upper Alameda
Creek, UC Berkeley: Water Resources Center Archives, available at:
http://escholarship.org/uc/item/3tz1153d (last access: 15 September 2017), 2005. a
Kotlarski, S., Lüthi, D., and Schär, C.: The elevation dependency of
21st century European climate change: an RCM ensemble perspective, Int. J.
Climatol., 35, 3902–3920, https://doi.org/10.1002/joc.4254, 2015. a
Krüger, L. F., da Rocha, R. P., Reboita, M. S., and Ambrizzi, T.: RegCM3
nested in HadAM3 scenarios A2 and B2: projected changes in extratropical
cyclogenesis, temperature and precipitation over the South Atlantic Ocean,
Clim. Change, 113, 599–621, https://doi.org/10.1007/s10584-011-0374-4, 2012. a
Kyselý, J., Gaál, L., Beranová, R., and Plavcová, E.: Climate
change scenarios of precipitation extremes in Central Europe from ENSEMBLES
regional climate models, Theor. Appl. Climatol., 104, 529–542,
https://doi.org/10.1007/s00704-010-0362-z, 2011. a, b
Lam, V. W. Y., Cheung, W. W. L., and Sumaila, U. R.: Marine capture fisheries
in the Arctic: winners or losers under climate change and ocean
acidification?, Fish Fish., 17, 335–357. https://doi.org/10.1111/faf.12106, 2016. a
Lautenschlager, M., Keuler, K., Wunram, C., Keup-Thiel, E., Schubert, M.,
Will, A., Rockel, B., and Boehm, U.: Climate simulation with CLM, climate of
the 20th century, data stream 3: European region MPI-M/MaD, World Data Center
for Climate, 2008. a
Lavalle, C., Micale, F., Houston, T. D., Camia, A., Hiederer, R., Lazar, C.,
Conte, C., Amatulli, G., and Genovese, G.: Climate change in Europe. 3.
Impact on agriculture and forestry. A review, Agron. Sustain. Dev., 29,
433–446, https://doi.org/10.1051/agro/2008068, 2009. a
Lee, Y. H., Park, S. K., and Chang, D.-E.: Parameter estimation using the
genetic algorithm and its impact on quantitative precipitation forecast, Ann.
Geophys., 24, 3185–3189, https://doi.org/10.5194/angeo-24-3185-2006, 2006. a
Lettenmaier, D. P. and Gan, T. Y.: Hydrologic sensitivities of the
Sacramento-San Joaquin River Basin, California, to global warming, Water
Resour. Res., 26, 69–86, 1990. a
Liu, Y., Stanturf, J., and Goodrick, S.: Trends in global wildfire potential
in a changing climate, Forest Ecol. Manag., 259, 685–697, 2010. a
Loglisci, N., Qian, M. W., Cassardo, C., Longhetto, A., and Giraud, C.:
Energy and water balance at soil-air interface in a Sahelian region, Adv.
Atmos. Sci., 18, 897–909, 2001. a
Luo, Y., Ficklin, D. L., Liu, X., and Zhang, M.: Assessment of climate change
impacts on hydrology and water quality with a watershed modeling approach,
Sci. Total Environ., 450–451, 72–82, https://doi.org/10.1016/j.scitotenv.2013.02.004,
2013. a
Mamoon, A. A., Joergensen, N. E., Rahman, A., and Qasem, H.: Design rainfall
in Qatar: sensitivity to climate change scenarios, Nat. Hazards, 81,
1797–1810, https://doi.org/10.1007/s11069-016-2156-9, 2016. a
Marengo, J. A., Jones, R., Alves, L. M., and Valverde, M. C.: Future change
of temperature and precipitation extremes in South America as derived from
the PRECIS regional climate modeling system, Int. J. Climatol., 29,
2241–2255, https://doi.org/10.1002/joc.1863, 2009. a
Masson, V., Champeaux, J. L., Chauvin, F., Meriguet, C., and Lacaze, R.: A
global database of land surface parameters at 1 km resolution in
meteorological and climate models, J. Climate, 16, 1261–1282, 2003 (data available at:
https://opensource.umr-cnrm.fr/projects/ecoclimap/files, last access: 15 September 2017). a
Matthews, H. D. and Solomon, S.: Irreversible does not mean unavoidable,
Science, 340, 438–439, https://doi.org/10.1126/science.1236372, 2013. a, b
Meng, L. and Quiring, S.: A comparison of soil moisture models using soil
climate analysis network observations, J. Hydrometeorol., 9, 641–659, 2008. a
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van
Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A.,
Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R.
J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next generation
of scenarios for climate change research and assessment, Nature, 463,
747–756, https://doi.org/10.1038/nature08823, 2010. a
Nadeem, I. and Formayer, H.: Sensitivity studies of high-resolution RegCM3
simulations of precipitation over the European Alps: The effect of lateral
boundary conditions and domain size, Theor. Appl. Climatol., 126, 617–630,
https://doi.org/10.1007/s00704-015-1586-8, 2016. a
Nemec, J. and Schaake, J.: Sensitivity of water resources to climate
variations, J. Hydrol. Sci., 27, 327–343, 1982. a
Nolan, P., O'Sullivan, J., and McGrath, R.: Impacts of climate change on
mid-twenty-first-century rainfall in Ireland: a high-resolution regional
climate model ensemble approach, Int. J. Climatol., 37, 4347–4363,
https://doi.org/10.1002/joc.5091, 2017. a, b, c
Ogden, N. H., Radojević, M., Wu, X., Duvvuri, V. R., Leighton, P. A., and
Wu, J.: Estimated effects of projected climate change on the basic reproductive number of the Lyme disease vector Ixodes scapularis,
Environ. Health Persp., 122, 631–638, https://doi.org/10.1289/ehp.1307799, 2014. a
O'Sullivan, J., Sweeney, C., Nolan, P., and Gleeson, E.: A high-resolution,
multi-model analysis of Irish temperatures for the mid-21st century, Int. J.
Climatol., 36, 1256–1267, https://doi.org/10.1002/joc.4419, 2016. a, b, c
Pal, J. S., Small, E. E., and Eltahir, E. A. B.: Simulation of regional-scale
water and energy budgets: Representation of subgrid cloud and precipitation
processes within RegCM, J. Geophys. Res., 105, 29579–29594, 2000. a
Pal, J. S. and Eltahir, E. A. B.: Teleconnections of soil moisture and
rainfall during the 1993 Midwest summer flood, Geophys. Res. Lett., 29, 1865,
https://doi.org/10.1029/2002GL014815, 2002. a
Pal, J. S. and Eltahir, E. A. B.: A feedback mechanism between soil moisture
distribution and storm tracks, Q. J. Roy. Meteor. Soc., 129, 2279–2297,
2003. a
Pal, J. S., Giorgi, F., and Bi, X.: Consistency of recent European summer
precipitation trends and extremes with future regional climate projections,
Geophys. Res. Lett., 31, L13202, https://doi.org/10.1029/2004GL019836, 2004. a
Park, S. K.: Nonlinearity and predictability of convective rainfall
associated with water vapor perturbations in a numerically-simulated storm,
J. Geophys. Res., 104, 31575–31588, 1999. a
Park, S. and Park, S. K.: Parameterization of the snow-covered surface albedo
in the Noah-MP Version 1.0 by implementing vegetation effects, Geosci. Model
Dev., 9, 1073–1085, https://doi.org/10.5194/gmd-9-1073-2016, 2016. a
Park, S. K., O, S., and Cassardo, C.: Soil temperature response in Korea to a
changing climate using a land surface model, Asia-Pac. J. Atmos. Sci.,
53, 457–470,
https://doi.org/10.1007/s13143-017-0048-x, 2017. a, b, c
Patz, J. A., Campbell-Lendrum, D., Holloway, T., and Foley, J. A.: Impact of
regional climate change on human health, Nature, 438, 310–317,
https://doi.org/10.1038/nature04188, 2005. a
Perez, J., Menendez, M., Mendez, F. J., and Losada, I. J.: Evaluating the
performance of CMIP3 and CMIP5 global climate models over the north-east
Atlantic region, Clim. Dynam., 43, 2663–2680, https://doi.org/10.1007/s00382-014-2078-8,
2014. a
Peters, G. P., Andrew, R. M., Boden, T., Canadell, J. G., Ciais, P., Le
Quéré, C., Marland, G., Raupach, M. R., and Wilson, C.: The challenge
to keep global warming below 2 ∘C, Nature Clim. Change, 3, 4–6,
https://doi.org/10.1038/nclimate1783, 2013. a, b
Qian, Y., Giorgi, F., Huang, Y., Chameides, W. L., and Luo, C.: Simulation of
anthropogenic sulfur over East Asia with a regional coupled chemistry-climate
model, Tellus B, 53, 171–191, 2001. a
Rauscher, S. A., Coppola, E., Piani, C., and Giorgi, F.: Resolution effects
on regional climate model simulations of seasonal precipitation over Europe,
Clim. Dynam., 35, 685–711, https://doi.org/10.1007/s00382-009-0607-7, 2010. a
Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., Kindermann,
G., Nakicenovic, N., and Rafaj, P.: RCP 8.5 – A scenario of comparatively
high greenhouse gas emissions, Clim. Change, 109, 33–57,
https://doi.org/10.1007/s10584-011-0149-y, 2011. a, b
Rind, D., Rosenzweig, C., and Goldberg, R.: Modelling the hydrological cycle
in assessments of climate change, Nature, 358, 119–123, 1992. a
Rogelj, J., Meinshausen, M., and Knutti, R.: Global warming under old and new
scenarios using IPCC climate sensitivity range estimates, Nature Clim.
Change, 2, 248–253, https://doi.org/10.1038/nclimate1385, 2012. a, b, c
Rummukainen, M.: Changes in climate and weather extremes in the 21st century,
WIREs Clim. Change, 3, 115–129, https://doi.org/10.1002/wcc.160, 2012. a
Shaltout, M. and Omstedt, A.: Recent precipitation trends and future
scenarios over the Mediterranean Sea, Geofizika, 31, 127–150,
https://doi.org/10.15233/gfz.2014.31.7, 2014. a, b
Shen, Y., Oki, T., Utsumi, N., Kanae, S., and Hanasaki, N.: Projection of
future world water resources under SRES scenarios: water withdrawal,
Hydrolog. Sci. J., 53, 11–33, https://doi.org/10.1623/hysj.53.1.11, 2008. a
Shen, Y., Oki, T., Kanae, S., Hanasaki, N., Utsumi, N., and Kiguchi, M.:
Projection of future world water resources under SRES scenarios: an
integrated assessment, Hydrolog. Sci. J., 59, 1775–1793,
https://doi.org/10.1080/02626667.2013.862338, 2014. a
Skalák, P., Déqué, M., Belda, M., Farda, A., Halenka, T., Csima,
G., Bartholy, J., Caian, M., and Spiridonov, V.: CECILIA regional climate
simulations for the present climate: validation and inter-comparison, Clim.
Res., 60, 1–12, https://doi.org/10.3354/cr01207, 2014. a, b
Smiatek, G., Kunstmann, H., Knoche, R., and Marx, A.: Precipitation and
temperature statistics in high-resolution regional climate models: Evaluation
for the European Alps, J. Geophys. Res., 114, D19107,
https://doi.org/10.1029/2008JD011353, 2009. a, b
Stevanović, M., Popp, A., Lotze-Campen, H., Dietrich, J. P., Müller,
C., Bonsch, M., Schmitz, C., Bodirsky, B. L., Humpenöder, F., and Weindl,
I.: The impact of high-end climate change on agricultural welfare, Sci. Adv.,
2, e1501452,
https://doi.org/10.1126/sciadv.1501452, 2016. a, b
Tainio, M., Juda-Rezler, K., Reizer, M., Warchalowski, A., Trapp, W., and
Skotak, K.: Future climate and adverse health effects caused by fine
particulate matter air pollution: case study for Poland, Reg. Environ.
Change, 13, 705–715, https://doi.org/10.1007/s10113-012-0366-6, 2013. a
Torma, C., Coppola, E., Giorgi, F., Bartholy, J., and Pongrácz, R.:
Validation of a high-resolution version of the regional climate model RegCM3
over the Carpathian basin, J. Hydrometeorol., 12, 84–100,
https://doi.org/10.1175/2010JHM1234.1, 2011. a, b
Torma, C., Giorgi, F., and Coppola, E.: Added value of regional climate
modeling over areas characterized by complex terrain – Precipitation over
the Alps, J. Geophys. Res.-Atmos., 120, 3957–3972, https://doi.org/10.1002/2014JD022781,
2015. a, b, c
Tukimat, N. N. A. and Alias, N. A.: Assessment the potential of SRES scenario
for Kuala Sala, Malaysia, IOSR J. Mech. Civil Eng., 13, 6–12,
2016. a
van Vliet, M. T. H., Yearsley, J. R., Ludwig, F., Vögele, S.,
Lettenmaier, D. P., and Kabat, P.: Vulnerability of US and European
electricity supply to climate change, Nature Clim. Change, 2, 676–681,
https://doi.org/10.1038/nclimate1546, 2012. a
Vautard, R., Gobiet, A., Sobolowski, S., Kjellström, E., Stegehuis, A.,
Watkiss, P., Mendlik, T., Landgren, O., Nikulin, G., Teichmann, C., and
Jacob, D.: The European climate under a 2 ∘C global warming,
Environ. Res. Lett., 9, 034006, https://doi.org/10.1088/1748-9326/9/3/034006, 2014. a, b
Walz, A., Braendle, J. M., Lang, D. J., Brand, F., Briner, S., Elkin, C.,
Hirschi, C., Huber, R., Lischke, H., and Schmatz, D. R.: Experience from
downscaling IPCC-SRES scenarios to specific national-level focus scenarios
for ecosystem service management, Technol. Forecasting Social Change, 86,
21–32, https://doi.org/10.1016/j.techfore.2013.08.014, 2014. a
Ward, J. D., Werner, A. D., Nel, W. P., and Beecham, S.: The influence of
constrained fossil fuel emissions scenarios on climate and water resource
projections, Hydrol. Earth Syst. Sci., 15, 1879–1893,
https://doi.org/10.5194/hess-15-1879-2011, 2011. a, b
Westerling, A. L., Bryant, B. P., Preisler, H. K., Holmes, T. P., Hidalgo, H.
G., Das, T., and Shrestha, S. R.: Climate change and growth scenarios for
California wildfire, Clim. Change, 109, 445–463,
https://doi.org/10.1007/s10584-011-0329-9, 2011. a
White, M., Diffenbaugh, N., Jones, G., Pal, J. S., and Giorgi, F.: Increased
heat stress in the 21st century reduces and shifts premium wine production in
the United States, P. Natl. Acad. Sci. USA, 103, 11217–11222, 2006. a
Wilby, R. L. and Wigley, T. M. L.: Downscaling general circulation model
output: a review of methods and limitations, Prog. Phys. Geog., 21, 530–548,
https://doi.org/10.1177/030913339702100403, 1997. a
Wilby, R. L., Whitehead, P. G., Wade, A. J., Butterfield, D., Davis, R. J.,
and Watts, G.: Integrated modelling of climate change impacts on water
resources and quality in a lowland catchment: River Kennet, UK, J. Hydrol.,
330, 204–220, https://doi.org/10.1016/j.jhydrol.2006.04.033, 2006. a
Xu, C.-Y. and Singh, V. P.: A review on monthly water balance models for
water resources investigation and climatic impact assessment, Water Resour.
Manag., 12, 31–50, 1998. a
Yu, X., Park, S. K., Lee, Y. H., and Choi, Y.-S.: Quantitative precipitation
forecast of a tropical cyclone through optimal parameter estimation in a
convective parameterization, Sci. Online Lett. Atmos., 9, 36–39, 2013. a
Zanis, P., Ntogras, C., Zakey, A., Pytharoulis, I., and Karacostas, T.:
Regional climate feedback of anthropogenic aerosols over Europe using RegCM3,
Clim. Res., 52, 267–278, https://doi.org/10.3354/cr01070, 2012. a
Zhang, Y., Cassardo, C., Ye, C., and Galli, M.: A landfall typhoon simulation
in a coupled land surface process model with WRF, in: Preprints, Conf. on
MCSs and High-Impact Weather/Climate in East Asia (ICMCS-VII), 11–13
November 2009, Seoul, Korea, 114–121, 2009. a
Zhang, Y., Cassardo, C., Ye, C., Galli, M., and Vela, N.: The role of the
land surface processes in the rainfall generated by a landfall typhoon: A
simulation of the Typhoon Sepat (2007), Asia-Pac. J. Atmos. Sci., 47, 63–77,
2011. a
Zheng, X., Wang, C., Cai, W., Kummu, M., and Varis, O.: The vulnerability of
thermoelectric power generation to water scarcity in China: Current status
and future scenarios for power planning and climate change, Appl. Energ.,
171, 444–455, https://doi.org/10.1016/j.apenergy.2016.03.040, 2016. a
Zubizarreta-Gerendiain, A., Pukkala, T., and Peltola, H.: Effects of wood
harvesting and utilisation policies on the carbon balance of forestry under
changing climate: a Finnish case study, Forest Policy Economics, 62,
168–176, https://doi.org/10.1016/j.forpol.2015.08.007, 2016. a
Short summary
Temperature and precipitation can have abnormal states due to climate change and exert a significant impact on the regional hydrologic cycle. We assess the hydrologic component changes in the Alps and northern Italy, on the basis of regional future climate (FC) conditions, using the UTOPIA land surface model. The annual mean number of dry (wet) days increase remarkably (slightly) in FCs, thus increasing the risk of severe droughts and slightly increasing the risk of floods coincidently.
Temperature and precipitation can have abnormal states due to climate change and exert a...
