Articles | Volume 24, issue 1
https://doi.org/10.5194/hess-24-269-2020
© Author(s) 2020. 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-24-269-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Jan 2020
Research article |
| 20 Jan 2020
| 20 Jan 2020
Impact of high-resolution sea surface temperature representation on the forecast of small Mediterranean catchments' hydrological responses to heavy precipitation
Alfonso Senatore
CORRESPONDING AUTHOR
Department of Environmental and Chemical Engineering, Università della Calabria, P.te P. Bucci 42b,
87036 Rende (CS), Italy
Luca Furnari
Department of Environmental and Chemical Engineering, Università della Calabria, P.te P. Bucci 42b,
87036 Rende (CS), Italy
Giuseppe Mendicino
Department of Environmental and Chemical Engineering, Università della Calabria, P.te P. Bucci 42b,
87036 Rende (CS), Italy
Related authors
Alfonso Senatore, Luca Furnari, Gholamreza Nikravesh, Jessica Castagna, and Giuseppe Mendicino
EGUsphere, https://doi.org/10.5194/egusphere-2025-1567, https://doi.org/10.5194/egusphere-2025-1567, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Observations and reanalyses highlight contrasting trends of annual precipitation decline and maximum one-day precipitation increase in Southern Europe. Very high-resolution simulations in a representative Mediterranean sub-region disentangle the role of increasing sea surface temperature so that the projected trend of high precipitation can be summarized as an expected increasing frequency rather than an increasing intensity of impacting overland events.
Vincenzo Carbone, Vincenzo Capparelli, Jessica Castagna, Fabio Lepreti, Alfonso Senatore, and Giuseppe Mendicino
EGUsphere, https://doi.org/10.5194/egusphere-2025-1234, https://doi.org/10.5194/egusphere-2025-1234, 2025
This preprint is open for discussion and under review for Nonlinear Processes in Geophysics (NPG).
Short summary
Short summary
In this work, it is shown that dust storms originating from Sahara and spreading over the Mediterranean Basin are not random events, but rather they are characterized by the presence of time correlations which extend over a timescale range up to about 80 days. The combination of statistical and atmospheric circulation analyses provides a novel and interesting picture of the atmospheric teleconnection between North Africa and the Mediterranean Basin associated with Saharan dust storms.
David J. Peres, Alfonso Senatore, Paola Nanni, Antonino Cancelliere, Giuseppe Mendicino, and Brunella Bonaccorso
Nat. Hazards Earth Syst. Sci., 20, 3057–3082, https://doi.org/10.5194/nhess-20-3057-2020, https://doi.org/10.5194/nhess-20-3057-2020, 2020
Short summary
Short summary
Regional climate models (RCMs) are commonly used for high-resolution assessment of climate change impacts. This research assesses the reliability of several RCMs in a Mediterranean area (southern Italy), comparing historic climate and drought characteristics with
high-density and high-quality ground-based observational datasets. We propose a general methodology and identify the more skilful models able to reproduce precipitation and temperature variability as well as drought characteristics.
Benjamin Fersch, Alfonso Senatore, Bianca Adler, Joël Arnault, Matthias Mauder, Katrin Schneider, Ingo Völksch, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 24, 2457–2481, https://doi.org/10.5194/hess-24-2457-2020, https://doi.org/10.5194/hess-24-2457-2020, 2020
Lu Li, Marie Pontoppidan, Stefan Sobolowski, and Alfonso Senatore
Hydrol. Earth Syst. Sci., 24, 771–791, https://doi.org/10.5194/hess-24-771-2020, https://doi.org/10.5194/hess-24-771-2020, 2020
Short summary
Short summary
We assessed the impact of initial conditions on convection-permitting simulations of a flood event over mountainous terrain. The calibrated convection-permitting model performs better than the simpler conceptual model. Discharge is slightly more sensitive to spin-up time than precipitation due to the influence of soil moisture. A maximum of 0.5 m of snow is converted to runoff irrespective of the initial snow depth, and this snowmelt contributes to discharge mostly during peak flow period.
Elenio Avolio, Ottavio Cavalcanti, Luca Furnari, Alfonso Senatore, and Giuseppe Mendicino
Nat. Hazards Earth Syst. Sci., 19, 1619–1627, https://doi.org/10.5194/nhess-19-1619-2019, https://doi.org/10.5194/nhess-19-1619-2019, 2019
Short summary
Short summary
This is the first scientific report of the flash flood of 20 August 2018 on “Raganello Gorge” (Southern Italy), an extreme event with rather specific features (very localized in space and time), which unfortunately caused 10 victims. The meteo-hydrological dynamics were reasonably reconstructed and the forecasting skills were evaluated using an innovative modelling approach, including fully coupled atmospheric-hydrological modelling and improved representation of Sea Surface Temperature.
Alfonso Senatore, Luca Furnari, Gholamreza Nikravesh, Jessica Castagna, and Giuseppe Mendicino
EGUsphere, https://doi.org/10.5194/egusphere-2025-1567, https://doi.org/10.5194/egusphere-2025-1567, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Observations and reanalyses highlight contrasting trends of annual precipitation decline and maximum one-day precipitation increase in Southern Europe. Very high-resolution simulations in a representative Mediterranean sub-region disentangle the role of increasing sea surface temperature so that the projected trend of high precipitation can be summarized as an expected increasing frequency rather than an increasing intensity of impacting overland events.
Vincenzo Carbone, Vincenzo Capparelli, Jessica Castagna, Fabio Lepreti, Alfonso Senatore, and Giuseppe Mendicino
EGUsphere, https://doi.org/10.5194/egusphere-2025-1234, https://doi.org/10.5194/egusphere-2025-1234, 2025
This preprint is open for discussion and under review for Nonlinear Processes in Geophysics (NPG).
Short summary
Short summary
In this work, it is shown that dust storms originating from Sahara and spreading over the Mediterranean Basin are not random events, but rather they are characterized by the presence of time correlations which extend over a timescale range up to about 80 days. The combination of statistical and atmospheric circulation analyses provides a novel and interesting picture of the atmospheric teleconnection between North Africa and the Mediterranean Basin associated with Saharan dust storms.
David J. Peres, Alfonso Senatore, Paola Nanni, Antonino Cancelliere, Giuseppe Mendicino, and Brunella Bonaccorso
Nat. Hazards Earth Syst. Sci., 20, 3057–3082, https://doi.org/10.5194/nhess-20-3057-2020, https://doi.org/10.5194/nhess-20-3057-2020, 2020
Short summary
Short summary
Regional climate models (RCMs) are commonly used for high-resolution assessment of climate change impacts. This research assesses the reliability of several RCMs in a Mediterranean area (southern Italy), comparing historic climate and drought characteristics with
high-density and high-quality ground-based observational datasets. We propose a general methodology and identify the more skilful models able to reproduce precipitation and temperature variability as well as drought characteristics.
Benjamin Fersch, Alfonso Senatore, Bianca Adler, Joël Arnault, Matthias Mauder, Katrin Schneider, Ingo Völksch, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 24, 2457–2481, https://doi.org/10.5194/hess-24-2457-2020, https://doi.org/10.5194/hess-24-2457-2020, 2020
Lu Li, Marie Pontoppidan, Stefan Sobolowski, and Alfonso Senatore
Hydrol. Earth Syst. Sci., 24, 771–791, https://doi.org/10.5194/hess-24-771-2020, https://doi.org/10.5194/hess-24-771-2020, 2020
Short summary
Short summary
We assessed the impact of initial conditions on convection-permitting simulations of a flood event over mountainous terrain. The calibrated convection-permitting model performs better than the simpler conceptual model. Discharge is slightly more sensitive to spin-up time than precipitation due to the influence of soil moisture. A maximum of 0.5 m of snow is converted to runoff irrespective of the initial snow depth, and this snowmelt contributes to discharge mostly during peak flow period.
Elenio Avolio, Ottavio Cavalcanti, Luca Furnari, Alfonso Senatore, and Giuseppe Mendicino
Nat. Hazards Earth Syst. Sci., 19, 1619–1627, https://doi.org/10.5194/nhess-19-1619-2019, https://doi.org/10.5194/nhess-19-1619-2019, 2019
Short summary
Short summary
This is the first scientific report of the flash flood of 20 August 2018 on “Raganello Gorge” (Southern Italy), an extreme event with rather specific features (very localized in space and time), which unfortunately caused 10 victims. The meteo-hydrological dynamics were reasonably reconstructed and the forecasting skills were evaluated using an innovative modelling approach, including fully coupled atmospheric-hydrological modelling and improved representation of Sea Surface Temperature.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Allen, M., Frame, D., Kettleborough, J., and Stainforth, D.: Model error in
weather and climate forecasting, in: Palmer, T. and Hagedorn, R.,
Predictability of Weather and Climate (391–427), Cambridge
University Press, Cambridge, https://doi.org/10.1017/CBO9780511617652.016,
2002.
Arnault, J., Wagner, S., Rummler, T., Fersch, B., Bliefernicht, J.,
Andresen, S., and Kunstmann, H.: Role of Runoff–Infiltration Partitioning
and Resolved Overland Flow on Land–Atmosphere Feedbacks: A Case Study with
the WRF-Hydro Coupled Modelling System for West Africa, J. Hydrometeorol., 17,
1489–1516, https://doi.org/10.1175/JHM-D-15-0089.1, 2016.
Avolio, E. and Federico, S.: WRF simulations for a heavy rainfall event in
southern Italy: Verification and sensitivity tests, Atmos. Res.,
209, 14–35, https://doi.org/10.1016/j.atmosres.2018.03.009,
2018.
Avolio, E., Cavalcanti, O., Furnari, L., Senatore, A., and Mendicino, G.: Brief communication: Preliminary hydro-meteorological analysis of the flash flood of 20 August 2018 in Raganello Gorge, southern Italy, Nat. Hazards Earth Syst. Sci., 19, 1619–1627, https://doi.org/10.5194/nhess-19-1619-2019, 2019.
Barker, D., Huang, X.-Y, Liu, Z., Auligné, T., Zhang, X., Rugg, S.,
Ajjaji, R., Bourgeois, A., Bray, J., Chen, Y., Demirtas, M., Guo, Y.-R,
Henderson, T., Huang, W., Lin, H.-C., Michalakes, J., Rizvi, S., and Zhang,
X.: The Weather Research and Forecasting Model's Community
Variational/Ensemble Data Assimilation System: WRFDA, B. Am. Meteorol.
Soc., 93, 831–843, https://doi.org/10.1175/BAMS-D-11-00167.1,
2012.
Barker, D. M., Huang, W., Guo, Y. R., Bourgeois, A. J., and Xiao, Q. N.: A
Three-Dimensional (3DVAR) Data Assimilation System For Use With MM5:
Implementation and Initial Results, Mon. Weather Rev., 132, 897–914, https://doi.org/10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2, 2004.
Berthou, S., Mailler, S., Drobinski, P., Arsouze, T., Bastin, S.,
Béranger, K., and Lebeaupin-Brossier, C.: Prior history of Mistral and
Tramontane winds modulates heavy precipitation events in southern France,
Tellus A, 66, 24064,
https://doi.org/10.3402/tellusa.v66.24064, 2014.
Berthou, S., Mailler, S., Drobinski, P., Arsouze, T., Bastin, S.,
Béranger, K., and Lebeaupin-Brossier, C.: Sensitivity of an intense rain
event between atmosphere-only and atmosphere–ocean regional coupled models:
19 September 1996, Q. J. Roy. Meteor. Soc., 141,
258–271, https://doi.org/10.1002/qj.2355, 2015.
Berthou, S., Mailler, S., Drobinski, P., Arsouze, T., Bastin, S.,
Béranger, K., Flaounas, E., Lebeaupin Brossier, C., Somot, S., and
Stéfanon, M.: Influence of submonthly air–sea coupling on heavy
precipitation events in the Western Mediterranean basin, Q. J. Roy. Meteor.
Soc., 142, 453–471, https://doi.org/10.1002/qj.2717, 2016.
Buizza, R.: Chapter 2 – Ensemble Forecasting and the Need for Calibration,
in: Statistical Postprocessing of Ensemble Forecasts, edited by: Vannitsem, S., Wilks, D. S., and Messner, J. W., Elsevier, 15–48,
ISBN 9780128123720,
https://doi.org/10.1016/B978-0-12-812372-0.00002-9, 2018.
Cabanes, C., Grouazel, A., von Schuckmann, K., Hamon, M., Turpin, V., Coatanoan, C., Paris, F., Guinehut, S., Boone, C., Ferry, N., de Boyer Montégut, C., Carval, T., Reverdin, G., Pouliquen, S., and Le Traon, P.-Y.: The CORA dataset: validation and diagnostics of in-situ ocean temperature and salinity measurements, Ocean Sci., 9, 1–18, https://doi.org/10.5194/os-9-1-2013, 2013.
Cassola, F., Ferrari, F., Mazzino, A., and Miglietta, M. M.: The role of the
sea on the flash floods events over Liguria (northwestern Italy), Geophys.
Res. Lett., 43, 3534–3542,
https://doi.org/10.1002/2016GL068265, 2016.
Centro Funzionale Centrale Rischio Meteo-idrogeologico e Idraulico – Italian Government, Home page: available at:
http://www.protezionecivile.gov.it/home, last access: 5 December 2019.
Centro Funzionale Multirischi – ARPACAL: Historical dataset, available at:
http://www.cfd.calabria.it/index.php/dati-stazioni/dati-storici, last access: 5 December 2019.
CFM (Centro Funzionale Multirischi della Calabria): Technical report,
Rapporto speditivo di evento metopluviometrico del 12 agosto 2015, available at: http://www.cfd.calabria.it/DatiVari/Pubblicazioni/rapporto di evento 12 agosto.pdf
(last access: 4 November 2019), 2015a (in
Italian).
CFM (Centro Funzionale Multirischi della Calabria): Technical report,
Rapporto di evento metopluviometrico del 30 ottobre 2 novembre 2015, available at: http://www.cfd.calabria.it/DatiVari/Pubblicazioni/rapporto di evento 30 ottobre-2 novembre2015.pdf
(last access: 4 November 2019), 2015b (in
Italian).
Chen, S. H. and Sun, W.-Y.: A One-dimensional Time Dependent Cloud Model,
J. Meteorol. Soc. Jpn., 80, 99–118,
https://doi.org/10.2151/jmsj.80.99, 2002.
Chiaravalloti, F. and Gabriele, S.: Vibo Valentia flood and MSG rainfall
evaluation, Atmos. Res., 93, 286–294, https://doi.org/10.1016/j.atmosres.2008.10.027, 2009.
Cohen, S., Praskievicz, S., and Maidment, D. R.: Featured Collection
Introduction: National Water Model, J. Am. Water Resour.
As., 54, 767–769, https://doi.org/10.1111/1752-1688.12664, 2018.
Cuo, L., Pagano, T. C., and Wang, Q. J.: A Review of Quantitative
Precipitation Forecasts and Their Use in Short- to Medium-Range Streamflow
Forecasting, J. Hydrometeorol., 12, 713–728,
https://doi.org/10.1175/2011JHM1347.1, 2011.
Davolio, S., Silvestro, F., and Malguzzi, P.: Effects of Increasing
Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting:
The 2011 Dramatic Events in Liguria, Italy, J. Hydrometeorol., 16, 1843–1856, https://doi.org/10.1175/JHM-D-14-0094.1, 2015.
Davolio, S., Silvestro, F., and Gastaldo, T.: Impact of Rainfall
Assimilation on High-Resolution Hydrometeorological Forecasts over Liguria,
Italy, J. Hydrometeorol., 18, 2659–2680,
https://doi.org/10.1175/JHM-D-17-0073.1, 2017.
Donlon, C., Robinson, I., Casey, K. S., Vazquez-Cuervo, J., Armstrong, E.,
Arino, O., Gentemann, C., May, D., LeBorgne, P., Piollé, J., Barton, I.,
Beggs, H., Poulter, D. J., Merchant, C. J., Bingham, A., Heinz, S., Harris,
A., Wick, G., Emery, B., Minnett, P., Evans, R., Llewellyn-Jones, D.,
Mutlow, C., Reynolds, R. W., Kawamura, H., and Rayner, N.: The Global Ocean
Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot
Project, B. Am. Meteorol. Soc., 88, 1197–1214,
https://doi.org/10.1175/BAMS-88-8-1197, 2007.
Drobinski, P., Silva, N.D., Panthou, G., Bastin, S., Muller, C., Ahrens, B.,
Borga, B., Conte, D., Fosser, G., Giorgi, F., Güttler, I., Kotroni, V.,
Li, L., Morin, E., Önol, B., Quintana-Segui, P., Romera, R., and Torma,
C. S.: Scaling precipitation extremes with temperature in the Mediterranean:
past climate assessment and projection in anthropogenic scenarios, Clim.
Dynam., 51, 1237–1257, https://doi.org/10.1007/s00382-016-3083-x,
2018.
Dudhia, J.: Numerical Study of Convection Observed during the Winter Monsoon
Experiment Using a Mesoscale Two-Dimensional Model, J. Atmos. Sci., 46,
3077–3107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2, 1989.
Evans, C., Dyke, D., and Lericos, T.: How Do Forecasters Utilize Output from
a Convection-Permitting Ensemble Forecast System? Case Study of a
High-Impact Precipitation Event, Weather Forecast., 29, 466–486,
https://doi.org/10.1175/WAF-D-13-00064.1, 2014.
Federico, S., Bellecci, C., and Colacino, M.: Numerical simulation of
Crotone flood: storm evolution, Il Nuovo Cimento C., 26, 357–371, 2003a.
Federico, S., Bellecci, C., and Colacino, M.: Quantitative precipitation of
the Soverato flood: the role of orography and surface fluxes, Il Nuovo
Cimento C., 26, 7–22, 2003b.
Federico, S., Avolio, E., Bellecci, C., Lavagnini, A., Colacino, M., and Walko, R. L.: Numerical analysis of an intense rainstorm occurred in southern Italy, Nat. Hazards Earth Syst. Sci., 8, 19–35, https://doi.org/10.5194/nhess-8-19-2008, 2008.
Federico, S., Pasqualoni, L., Avolio, E., and Bellecci, C.: Brief communication “Calabria daily rainfall from 1970 to 2006”, Nat. Hazards Earth Syst. Sci., 10, 717–722, https://doi.org/10.5194/nhess-10-717-2010, 2010.
Gascón, E., Laviola, S., Merino, A., and Miglietta, M. M.: Analysis of a
localized flash-flood event over the central Mediterranean, Atmos.
Res., 182, 256–268, https://doi.org/10.1016/j.atmosres.2016.08.007, 2016.
Gochis, D. J., Yu, W., and Yates, D.: The WRF-Hydro model technical
description and user's guide, version 3.0, NCAR Tech. Doc. 120,
https://doi.org/10.5065/D6DN43TQ, 2015.
Gronewold, A. D., Clites, A. H., Hunter, T. S., and Stow, C. G.: An appraisal of
the Great Lakes advanced hydrologic prediction system, J. Great
Lakes Res., 37, 577–583, https://doi.org/10.1016/j.jglr.2011.06.010, 2011.
Gustafsson, N., Nyberg, L., and Omstedt, A.: Coupling of a High-Resolution
Atmospheric Model and an Ocean Model for the Baltic Sea, Mon. Weather
Rev., 126, 2822–2846,
https://doi.org/10.1175/1520-0493(1998)126<2822:COAHRA>2.0.CO;2, 1998.
Gustafsson, N, Janjić, T, Schraff, C, Leuenberger, D., Weissmann, M.,
Reich, H., Brousseau, P., Montmerle, T., Wattrelot, E., Bučánek, A.,
Mile, M., Hamdi, R., Lindskog, M., Barkmeijer, J., Dahlbom, M., Macpherson,
B., Ballard, S., Inverarity, G., Carley, J., Alexander, C., Dowell, D., Liu,
S., Ikuta, Y., and Fujita, T.: Survey of data assimilation methods for
convective-scale numerical weather prediction at operational centres, Q. J. Roy. Meteor. Soc., 144, 1218–1256,
https://doi.org/10.1002/qj.3179, 2018.
Hodur, R. M.: The Naval Research Laboratory's Coupled Ocean/Atmosphere
Mesoscale Prediction System (COAMPS), Mon. Weather Rev., 125, 1414–1430,
https://doi.org/10.1175/1520-0493(1997)125<1414:TNRLSC>2.0.CO;2, 1997.
Huang, X. Y., Xiao, Q., Barker, D. M., Zhang, X., Michalakes, J., Huang, W.,
Henderson, T., Bray, J., Chen, Y., Ma, Z., Dudhia, J., Guo, Y., Zhang, X.,
Won, D. J., Lin, H. C., and Kuo, Y. H.: Four-Dimensional Variational Data
Assimilation for WRF: Formulation and Preliminary Results, Mon. Weather Rev.,
137, 299–314, https://doi.org/10.1175/2008MWR2577.1, 2009.
Hydrologic Engineering Center: HEC-RAS, River Analysis System, Hydraulic
Reference Manual, Version 5.0, U.S. Army Corps of Engineers, Davis,
California, 2016.
Ivatek-Šahdan, Stanešić, S. A., Tudor, M., Plenković, I. O.,
and Janeković, I.: Impact of SST on heavy rainfall events on eastern
Adriatic during SOP1 of HyMeX, Atmos. Res., 200, 36–59, https://doi.org/10.1016/j.atmosres.2017.09.019, 2018.
Janjić, Z. I.: The Step-Mountain Eta Coordinate Model: Further
Developments of the Convection, Viscous Sublayer, and Turbulence Closure
Schemes, Mon. Weather Rev., 122, 927–945,
https://doi.org/10.1175/1520-0493(1994)122< 0927:TSMECM>2.0.CO;2, 1994.
Jansa, A., Alpert, P., Arbogast, P., Buzzi, A., Ivancan-Picek, B., Kotroni, V., Llasat, M. C., Ramis, C., Richard, E., Romero, R., and Speranza, A.: MEDEX: a general overview, Nat. Hazards Earth Syst. Sci., 14, 1965–1984, https://doi.org/10.5194/nhess-14-1965-2014, 2014.
Kain, J. S.: The Kain–Fritsch Convective Parameterization: An Update, J.
Appl. Meteorol., 43, 170–181,
https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
Katsafados, P., Mavromatidis, E., Papadopoulos, A., and Pytharoulis, I.: Numerical simulation of a deep Mediterranean storm and its sensitivity on sea surface temperature, Nat. Hazards Earth Syst. Sci., 11, 1233–1246, https://doi.org/10.5194/nhess-11-1233-2011, 2011.
Keresturi, E., Wang, Y., Meier, F., Weidle, F., and Wittman, C.: Improving
initial condition perturbations in a convection-permitting ensemble
prediction system, Q. J. Roy. Meteor. Soc.,
145, 993–1012, https://doi.org/10.1002/qj.3473, 2019.
Lahmers, T. M., Gupta, H., Castro, C. L., Gochis, D. J., Yates, D., Dugger, A.,
Goodrich, D., and Hazenberg, P.: Enhancing the Structure of the WRF-Hydro
Hydrologic Model for Semiarid Environments, J. Hydrometeorol., 20, 691–714,
https://doi.org/10.1175/JHM-D-18-0064.1, 2019.
Lebeaupin, C., Ducrocq, V., and Giordani, H.: Sensitivity of torrential rain
events to the sea surface temperature based on high-resolution numerical
forecasts, J. Geophys. Res., 111, D12110,
https://doi.org/10.1029/2005JD006541, 2006.
Lewis, H. W., Castillo Sanchez, J. M., Arnold, A., Fallmann, J., Saulter, A., Graham, J., Bush, M., Siddorn, J., Palmer, T., Lock, A., Edwards, J., Bricheno, L., Martínez-de la Torre, A., and Clark, J.: The UKC3 regional coupled environmental prediction system, Geosci. Model Dev., 12, 2357–2400, https://doi.org/10.5194/gmd-12-2357-2019, 2019a.
Lewis, H. W., Siddorn, J., Castillo Sanchez, J. M., Petch, J., Edwards, J. M., and Smyth, T.: Evaluating the impact of atmospheric forcing and air–sea coupling on near-coastal regional ocean prediction, Ocean Sci., 15, 761–778, https://doi.org/10.5194/os-15-761-2019, 2019b.
Li, J., Chen, Y., Wang, H., Qin, J., Li, J., and Chiao, S.: Extending flood forecasting lead time in a large watershed by coupling WRF QPF with a distributed hydrological model, Hydrol. Earth Syst. Sci., 21, 1279–1294, https://doi.org/10.5194/hess-21-1279-2017, 2017.
Lin, P., Yang, Z.-L. Gochis, D. J., Yu, W., Maidment, D. R., Somos-Valenzuela,
M. A., and David, C. H.: Implementation of a vector-based river network
routing scheme in the community WRF-Hydro modelling framework for flood
discharge simulation, Environ. Modell. Softw., 107, 1–11,
https://doi.org/10.1016/j.envsoft.2018.05.018, 2018.
Liu, J., Bray, M., and Han, D.: Exploring the effect of data assimilation by
WRF-3DVar for numerical rainfall prediction with different types of storm
events, Hydrol. Process., 27, 3627–3640,
https://doi.org/10.1002/hyp.9488, 2013.
Liu, J., Tian, J., Yan, D., Li, C., Yu, F., and Shen, F.: Evaluation of Doppler radar and GTS data assimilation for NWP rainfall prediction of an extreme summer storm in northern China: from the hydrological perspective, Hydrol. Earth Syst. Sci., 22, 4329–4348, https://doi.org/10.5194/hess-22-4329-2018, 2018.
Liu, Y., Weerts, A. H., Clark, M., Hendricks Franssen, H.-J., Kumar, S., Moradkhani, H., Seo, D.-J., Schwanenberg, D., Smith, P., van Dijk, A. I. J. M., van Velzen, N., He, M., Lee, H., Noh, S. J., Rakovec, O., and Restrepo, P.: Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities, Hydrol. Earth Syst. Sci., 16, 3863–3887, https://doi.org/10.5194/hess-16-3863-2012, 2012.
Llasat, M. C., Llasat-Botija, M., Petrucci, O., Pasqua, A. A., Rosselló, J., Vinet, F., and Boissier, L.: Towards a database on societal impact of Mediterranean floods within the framework of the HYMEX project, Nat. Hazards Earth Syst. Sci., 13, 1337–1350, https://doi.org/10.5194/nhess-13-1337-2013, 2013.
Loglisci, N., Qian, M. W., Rachev, N., Cassardo, C., Longhetto, A., Purini,
R., Trivero, P., Ferrarese, S., and Giraud, C.: Development of an
atmosphere-ocean coupled model and its application over the Adriatic Sea
during a severe weather event of Bora wind, J. Geophys. Res., 109, D01102,
https://doi.org/10.1029/2003JD003956, 2004.
Manzato, A., Davolio, S., Miglietta, M. M., Pucillo, A., and Setvák, M.:
12 September 2012: A supercell outbreak in NE Italy?, Atmos. Res.,
153, 98–118, https://doi.org/10.1016/j.atmosres.2014.07.019,
2015.
Matte, D., Laprise, R., Thériault, J. M., and Lucs-Picher, P.: Spatial
spin-up of fine scales in a regional climate model simulation driven by
low-resolution boundary conditions, Clim. Dynam., 49, 563–574,
https://doi.org/10.1007/s00382-016-3358-2, 2017.
Medspiration Service: Access to data and services
available at:
http://cersat.ifremer.fr/thematic-portals/projects/medspiration/access-to-data-and-services, last access: 5 December 2019.
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for
geophysical fluid problems, Rev. Geophys., 20, 851–875,
https://doi.org/10.1029/RG020i004p00851, 1982.
Merchant, C. J., Filipiak, M. J., Le Borgne, P., Roquet, H., Autret, E.,
Piolle, J. F., and Lavender, S.: Diurnal warm-layer events in the western
Mediterranean and European shelf seas, Geophys. Res. Lett.,
35, L04601, https://doi.org/10.1029/2007GL033071, 2008.
Meredith, E. P., Maraun, D., Semenov, V. A., and Park, W.: Evidence for added
value of convection-permitting models for studying changes in extreme
precipitation, J. Geophys. Res.-Atmos., 120, 12500–12513,
https://doi.org/10.1002/2015JD024238, 2015.
Miglietta, M. M., Moscatello, A., Conte, D., Mannarini, G., Lacorata, G., and
Rotunno R.: Numerical analysis of a Mediterranean “hurricane” over
south-eastern Italy: Sensitivity experiments to sea surface temperature,
Atmos. Res., 101, 412–426, https://doi.org/10.1016/j.atmosres.2011.04.006, 2011.
Miglietta, M. M., Bueso, J., Motola, V., and Pasini, A.: Effect of a positive
Sea Surface Temperature anomaly on a Mediterranean tornadic supercell,
Sci. Rep.-UK, 7, 12828, https://doi.org/10.1038/s41598-017-13170-0, 2017.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S.
A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated
correlated-k model for the longwave, J. Geophys. Res., 102, 16663–16682, https://doi.org/10.1029/97JD00237, 1997.
NCEP: NCEP ADP Global Upper Air Observational Weather Data, October 1999–continuing, https://doi.org/10.5065/39C5-Z211, 2004.
Pagano, T. C., Wood, A. W., Ramos, M. H., Cloke, H. L., Pappenberger, F.,
Clark, M. P., Cranston, M., Kavetski, D., Mathevet, T., Sorooshian, S., and
Verkade, J. S.: Challenges of operational river forecasting, J.
Hydrometeorol., 15, 1692–1707,
https://doi.org/10.1175/JHM-D-13-0188.1, 2014.
Pastor, F., Valiente, J. A., and Estrela, M. J.: Sea surface temperature and torrential rains in the Valencia region: modelling the role of recharge areas, Nat. Hazards Earth Syst. Sci., 15, 1677–1693, https://doi.org/10.5194/nhess-15-1677-2015, 2015.
Petrucci, O., Salvati, P., Aceto, L., Bianchi, C., Pasqua, A. A., Rossi, M.,
and Guzzetti, F.: The Vulnerability of People to Damaging Hydrogeological
Events in the Calabria Region (Southern Italy), Int. J. Environ. Res. Pu., 15, 48, https://doi.org/10.3390/ijerph15010048,
2018.
Pullen, J., Doyle, J. D., Hodur, R., Ogston, A., Book, J. W., Perkins, H.,
and Signell, R.: Coupled ocean-atmosphere nested modelling of the Adriatic
Sea during winter and spring 2001, J. Geophys. Res., 108, 3320,
https://doi.org/10.1029/2003JC001780, 2003.
Pytharoulis, I.: Analysis of a Mediterranean tropical-like cyclone and its
sensitivity to the sea surface temperatures, Atmos. Res., 208,
167–179, https://doi.org/10.1016/j.atmosres.2017.08.009, 2018.
Rainaud, R., Lebeaupin Brossier, C., Ducrocq, V., Giordani, H., Nuret, M.,
Fourrié, N., Bouin, M., Taupier-Letage, I., and Legain, D.:
Characterization of air–sea exchanges over the Western Mediterranean Sea
during HyMeX SOP1 using the AROME–WMED model, Q. J. Roy. Meteor. Soc., 142,
173–187, https://doi.org/10.1002/qj.2480, 2016.
Ren, X., Perrie, W., Long, Z., and Gyakum, J.: Atmosphere–Ocean Coupled
Dynamics of Cyclones in the Midlatitudes, Mon. Weather Rev., 132, 2432–2451, https://doi.org/10.1175/1520-0493(2004)132<2432:ACDOCI>2.0.CO;2, 2004.
Renard, B., Kavetski, D., Kuczera, G., Thyer, M., and Franks, S. W.:
Understanding predictive uncertainty in hydrologic modelling: The challenge
of identifying input and structural errors, Water Resour. Res., 46, W05521,
https://doi.org/10.1029/2009WR008328, 2010.
Ricchi, A., Miglietta, M. M., Bonaldo, D., Cioni, G., Rizza, U., and Carniel,
S.: Multi-Physics Ensemble versus Atmosphere–Ocean Coupled Model
Simulations for a Tropical-Like Cyclone in the Mediterranean Sea,
Atmosphere, 10, 202, https://doi.org/10.3390/atmos10040202,
2019.
Robinson, I., Piolle, J. F., Leborgne, P., Poulter, D., Donlon, C., and
Arino, O.: Widening the application of AATSR SST data to operational tasks
through the Medspiration Service, Remote Sens. Environ., 116,
126–139, https://doi.org/10.1016/j.rse.2010.12.019, 2012.
Romaniello, V., Oddo, P., Tonani, M., Torrisi, L., Grandi, A., and Pinardi,
N.: Impact of Sea Surface Temperature on COSMO Forecasts of a Medicane over
the Western Mediterranean Sea, Journal of earth science and engineering, 5,
338–348, https://doi.org/10.17265/2159-581X/2015.06.002, 2015.
Ruti, P. M., Somot, S., Giorgi, F., Dubois, C., Flaounas, E., Obermann, A.,
Dell'Aquila, A., Pisacane, G., Harzallah, A., Lombardi, E., Ahrens, B.,
Akhtar, N., Alias, A., Arsouze, T., Aznar, R., Bastin, S., Bartholy, J.,
Béranger, K., Beuvier, J., Bouffies-Cloché, S., Brauch, J., Cabos,
W., Calmanti, S., Calvet, J., Carillo, A., Conte, D., Coppola, E.,
Djurdjevic, V., Drobinski, P., Elizalde-Arellano, A., Gaertner, M.,
Galàn, P., Gallardo, C., Gualdi, S., Goncalves, M., Jorba, O.,
Jordà, G., L'Heveder, B., Lebeaupin-Brossier, C., Li, L., Liguori, G.,
Lionello, P., Maciàs, D., Nabat, P., Önol, B., Raikovic, B., Ramage,
K., Sevault, F., Sannino, G., Struglia, M. V., Sanna, A., Torma, C., and
Vervatis, V.: Med-CORDEX Initiative for Mediterranean Climate Studies, B.
Am. Meteorol. Soc., 97, 1187–1208,
https://doi.org/10.1175/BAMS-D-14-00176.1, 2016.
Salas, F. R., Somos-Valenzuela, M. A., Dugger, A., Maidment, D. R., Gochis,
D. J., David, C. H., Yu, W., Ding, D., Clark, E. P., and Noman, N.: Towards
Real-Time Continental Scale Streamflow Simulation in Continuous and Discrete
Space, J. Am. Water Resour. As., 54, 7–27, https://doi.org/10.1111/1752-1688.12586, 2018.
Senatore, A., Mendicino, G., Knoche, H. R., and Kunstmann, H.: Sensitivity of
Modelled Precipitation to Sea Surface Temperature in Regions with Complex
Topography and Coastlines: A Case Study for the Mediterranean, J. Hydrometeorol., 15, 2370–2396,
https://doi.org/10.1175/JHM-D-13-089.1, 2014.
Senatore, A., Mendicino, G., Gochis, D. J., Yu, W., Yates, D. N., and
Kunstmann, H.: Fully coupled atmosphere-hydrology simulations for the
central Mediterranean: Impact of enhanced hydrological parameterization for
short and long time scales, J. Adv. Model. Earth Sy., 7, 1693–1715,
https://doi.org/10.1002/2015MS000510, 2015.
Silvestro, F., Rebora, N., Cummings, G., and Ferraris, L.: Dealing with flash
floods using a hydrological nowcasting chain, J. Flood Risk Manag., 10,
446–462, https://doi.org/10.1111/jfr3.12161, 2017.
Sinclair, S. and Pegram, G.: Combining radar and rain gauge rainfall
estimates using conditional merging, Atmos. Sci. Lett., 6, 19–22,
https://doi.org/10.1002/asl.85, 2005.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda,
M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A Description of the
Advanced Research WRF Version 3, NCAR Tech. Note NCAR/TN-475+STR, 113 pp.,
https://doi.org/10.5065/D68S4MVH, 2008.
Somot, S., Ruti, P., Ahrens, B. Coppola, E., Jordà G., Sannino, G., and
Solmon F.: Editorial for the Med-CORDEX special issue, Clim. Dynam., 51,
771–777, https://doi.org/10.1007/s00382-018-4325-x, 2018.
Stocchi, P. and Davolio, S.: Intense air-sea exchanges and heavy orographic
precipitation over Italy: The role of Adriatic sea surface temperature
uncertainty, Atmos. Res., 196, 62–82,
https://doi.org/10.1016/j.atmosres.2017.06.004, 2017.
Sun, J., Wang, H., Tong, W., Zhang, Y., Lin, C., and Xu, D.: Comparison of
the Impacts of Momentum Control Variables on High-Resolution Variational
Data Assimilation and Precipitation Forecasting, Mon. Weather Rev., 144,
149–169, https://doi.org/10.1175/MWR-D-14-00205.1, 2016.
Tao, J., Wu, D., Gourley, J., Zhang, S. Q., Crow, W., Peters-Lidard, C., and
Barros, A. P.: Operational hydrological forecasting during the IPHEx-IOP
campaign – Meet the challenge, J. Hydrol., 541,
434–456, https://doi.org/10.1016/j.jhydrol.2016.02.019, 2016.
Termonia, P., Deckmyn, A., and Hamdi, R.: Study of the lateral boundary
condition temporal resolution problem and a proposed solution by means of
boundary error restarts, Mon. Weather Rev., 137, 3551–3566, https://doi.org/10.1175/2009MWR2964.1, 2009.
Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M. A., Mitchell, K., Ek,
M., Gayno, G., Wegiel, J., and Cuenca, R. H.: Implementation and verification
of the unified NOAH land surface model in the WRF model. 20th conference on
weather analysis and forecasting/16th conference on numerical weather
prediction, 11–15, 2004.
Thiruvengadam, P., Indu, J., and Ghosh, S.: Assimilation of Doppler Weather
Radar data with a regional WRF-3DVAR system: Impact of control variables on
forecasts of a heavy rainfall case, Adv. Water Resour., 126, 24–39,
https://doi.org/10.1016/j.advwatres.2019.02.004, 2019.
Verri, G., Pinardi, N., Gochis, D., Tribbia, J., Navarra, A., Coppini, G., and Vukicevic, T.: A meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment, Nat. Hazards Earth Syst. Sci., 17, 1741–1761, https://doi.org/10.5194/nhess-17-1741-2017, 2017.
Wilks, S. D.: Statistical Methods in the Atmospheric Sciences, International
Geophysics Series, 59, chap. XI,
https://doi.org/10.1016/S0074-6142(06)80036-7, 2006.
Yucel, I., Onen, A., Yilmaz, K., and Gochis, D. J.: Calibration and
Evaluation of a Flood Forecasting System: Utility of Numerical Weather
Prediction Model, Data Assimilation and Satellite-Based Rainfall, J.
Hydrol., 523, 49–66,
https://doi.org/10.1016/j.jhydrol.2015.01.042, 2015.
Zeng, X. and Beljaars, A.: A prognostic scheme of sea surface skin
temperature for modelling and data assimilation, Geophys. Res. Lett., 32, L14605, https://doi.org/10.1029/2005GL023030, 2005.
Short summary
This paper addresses the question of how different resolutions of sea surface temperature (SST) representation affect regional operational hydro-meteorological forecasting chains over coastal Mediterranean catchments by analysing two different severe events that affected southern Italy in 2015. Even if the benefits of high-resolution SST representation are hidden by other sources of uncertainty, the experiments highlight that the impact is non-negligible in most cases.
This paper addresses the question of how different resolutions of sea surface temperature (SST)...
