Articles | Volume 17, issue 6
https://doi.org/10.5194/hess-17-2107-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-2107-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
05 Jun 2013
Research article |
| 05 Jun 2013
A flood episode in northern Italy: multi-model and single-model mesoscale meteorological ensembles for hydrological predictions
S. Davolio
Institute of Atmospheric Sciences and Climate, National Research Council, Bologna, Italy
M. M. Miglietta
Institute of Atmospheric Sciences and Climate, National Research Council, Lecce, Italy
T. Diomede
HydroMeteoClimate Regional Service of ARPA Emilia Romagna, Bologna, Italy
C. Marsigli
HydroMeteoClimate Regional Service of ARPA Emilia Romagna, Bologna, Italy
A. Montani
HydroMeteoClimate Regional Service of ARPA Emilia Romagna, Bologna, Italy
Related authors
Claudio Sánchez, Suzanne Gray, Ambrogio Volonté, Florian Pantillon, Ségolène Berthou, and Silvio Davolio
Weather Clim. Dynam., 5, 1429–1455, https://doi.org/10.5194/wcd-5-1429-2024, https://doi.org/10.5194/wcd-5-1429-2024, 2024
Short summary
Short summary
Medicane Ianos was a very intense cyclone that led to harmful impacts over Greece. We explore what processes are important for the forecasting of Medicane Ianos, with the use of the Met Office weather model. There was a preceding precipitation event before Ianos’s birth, whose energetics generated a bubble in the tropopause. This bubble created the necessary conditions for Ianos to emerge and strengthen, and the processes are enhanced in simulations with a warmer Mediterranean Sea.
Florian Pantillon, Silvio Davolio, Elenio Avolio, Carlos Calvo-Sancho, Diego Saul Carrió, Stavros Dafis, Emanuele Silvio Gentile, Juan Jesus Gonzalez-Aleman, Suzanne Gray, Mario Marcello Miglietta, Platon Patlakas, Ioannis Pytharoulis, Didier Ricard, Antonio Ricchi, Claudio Sanchez, and Emmanouil Flaounas
Weather Clim. Dynam., 5, 1187–1205, https://doi.org/10.5194/wcd-5-1187-2024, https://doi.org/10.5194/wcd-5-1187-2024, 2024
Short summary
Short summary
Cyclone Ianos of September 2020 was a high-impact but poorly predicted medicane (Mediterranean hurricane). A community effort of numerical modelling provides robust results to improve prediction. It is found that the representation of local thunderstorms controlled the interaction of Ianos with a jet stream at larger scales and its subsequent evolution. The results help us understand the peculiar dynamics of medicanes and provide guidance for the next generation of weather and climate models.
Emmanouil Flaounas, Stavros Dafis, Silvio Davolio, Davide Faranda, Christian Ferrarin, Katharina Hartmuth, Assaf Hochman, Aristeidis Koutroulis, Samira Khodayar, Mario Marcello Miglietta, Florian Pantillon, Platon Patlakas, Michael Sprenger, and Iris Thurnherr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2809, https://doi.org/10.5194/egusphere-2024-2809, 2024
Short summary
Short summary
Storm Daniel (2023) is one of the most catastrophic ones ever documented in the Mediterranean. Our results highlight the different dynamics and therefore the different predictability skill of precipitation, its extremes and impacts that have been produced in Greece and Libya, the two most affected countries. Our approach concerns a holistic analysis of the storm by articulating dynamics, weather prediction, hydrological and oceanographic implications, climate extremes and attribution theory.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
Short summary
Short summary
The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Emmanouil Flaounas, Silvio Davolio, Shira Raveh-Rubin, Florian Pantillon, Mario Marcello Miglietta, Miguel Angel Gaertner, Maria Hatzaki, Victor Homar, Samira Khodayar, Gerasimos Korres, Vassiliki Kotroni, Jonilda Kushta, Marco Reale, and Didier Ricard
Weather Clim. Dynam., 3, 173–208, https://doi.org/10.5194/wcd-3-173-2022, https://doi.org/10.5194/wcd-3-173-2022, 2022
Short summary
Short summary
This is a collective effort to describe the state of the art in Mediterranean cyclone dynamics, climatology, prediction (weather and climate scales) and impacts. More than that, the paper focuses on the future directions of research that would advance the broader field of Mediterranean cyclones as a whole. Thereby, we propose interdisciplinary cooperation and additional modelling and forecasting strategies, and we highlight the need for new impact-oriented approaches to climate prediction.
Mario Marcello Miglietta and Silvio Davolio
Hydrol. Earth Syst. Sci., 26, 627–646, https://doi.org/10.5194/hess-26-627-2022, https://doi.org/10.5194/hess-26-627-2022, 2022
Short summary
Short summary
The main results emerging from the HyMeX SOP1 campaign and in the subsequent research activity in three Italian target areas are highlighted through conceptual models and through the identification of the relevant mesoscale environmental characteristics conducive to heavy rain events.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
Short summary
Short summary
Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
Maria Laura Poletti, Francesco Silvestro, Silvio Davolio, Flavio Pignone, and Nicola Rebora
Hydrol. Earth Syst. Sci., 23, 3823–3841, https://doi.org/10.5194/hess-23-3823-2019, https://doi.org/10.5194/hess-23-3823-2019, 2019
Short summary
Short summary
In this work a probabilistic rainfall nowcasting model, a non-hydrostatic high-resolution numerical weather prediction (NWP) model corrected with data assimilation, and a distributed hydrological model are used together with radar observations to implement a hydrological nowcasting chain. This chain is used to obtain a useful discharge prediction in small catchments with a time horizon of 2–8 h.
P. Stocchi and S. Davolio
Adv. Sci. Res., 13, 7–12, https://doi.org/10.5194/asr-13-7-2016, https://doi.org/10.5194/asr-13-7-2016, 2016
Short summary
Short summary
Three heavy rain events over NE Alps were simulated using a high-resolution model to evaluate the effect of the SST of the Adriatic Sea.
These preliminary results show that SST influences the surface heat fluxes over the sea, but does not necessary affect the vertical integrated water vapour flux across the coast.
The response of heavy precipitation to a SST change is complex: SST affects the PBL characteristics and thus the flow dynamics and its interaction with orography.
R. Ferretti, E. Pichelli, S. Gentile, I. Maiello, D. Cimini, S. Davolio, M. M. Miglietta, G. Panegrossi, L. Baldini, F. Pasi, F. S. Marzano, A. Zinzi, S. Mariani, M. Casaioli, G. Bartolini, N. Loglisci, A. Montani, C. Marsigli, A. Manzato, A. Pucillo, M. E. Ferrario, V. Colaiuda, and R. Rotunno
Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, https://doi.org/10.5194/hess-18-1953-2014, 2014
A. Buzzi, S. Davolio, P. Malguzzi, O. Drofa, and D. Mastrangelo
Nat. Hazards Earth Syst. Sci., 14, 1325–1340, https://doi.org/10.5194/nhess-14-1325-2014, https://doi.org/10.5194/nhess-14-1325-2014, 2014
Kerry Emanuel, Tommaso Alberti, Stella Bourdin, Suzana J. Camargo, Davide Faranda, Manos Flaounas, Juan Jesus Gonzalez-Aleman, Chia-Ying Lee, Mario Marcello Miglietta, Claudia Pasquero, Alice Portal, Hamish Ramsay, and Romualdo Romero
EGUsphere, https://doi.org/10.5194/egusphere-2024-3387, https://doi.org/10.5194/egusphere-2024-3387, 2024
Short summary
Short summary
Storms strongly resembling hurricanes are sometime observed to form well outside the tropics, even in polar latitudes. They behave capriciously, developing very rapidly and then dying just as quickly. We show that strong dynamical processes in the atmosphere can sometimes cause it to become locally much colder than the underlying ocean, creating the conditions for hurricanes to form, but only over small areas and for short times. We call the resulting storms "cyclops".
Claudio Sánchez, Suzanne Gray, Ambrogio Volonté, Florian Pantillon, Ségolène Berthou, and Silvio Davolio
Weather Clim. Dynam., 5, 1429–1455, https://doi.org/10.5194/wcd-5-1429-2024, https://doi.org/10.5194/wcd-5-1429-2024, 2024
Short summary
Short summary
Medicane Ianos was a very intense cyclone that led to harmful impacts over Greece. We explore what processes are important for the forecasting of Medicane Ianos, with the use of the Met Office weather model. There was a preceding precipitation event before Ianos’s birth, whose energetics generated a bubble in the tropopause. This bubble created the necessary conditions for Ianos to emerge and strengthen, and the processes are enhanced in simulations with a warmer Mediterranean Sea.
Florian Pantillon, Silvio Davolio, Elenio Avolio, Carlos Calvo-Sancho, Diego Saul Carrió, Stavros Dafis, Emanuele Silvio Gentile, Juan Jesus Gonzalez-Aleman, Suzanne Gray, Mario Marcello Miglietta, Platon Patlakas, Ioannis Pytharoulis, Didier Ricard, Antonio Ricchi, Claudio Sanchez, and Emmanouil Flaounas
Weather Clim. Dynam., 5, 1187–1205, https://doi.org/10.5194/wcd-5-1187-2024, https://doi.org/10.5194/wcd-5-1187-2024, 2024
Short summary
Short summary
Cyclone Ianos of September 2020 was a high-impact but poorly predicted medicane (Mediterranean hurricane). A community effort of numerical modelling provides robust results to improve prediction. It is found that the representation of local thunderstorms controlled the interaction of Ianos with a jet stream at larger scales and its subsequent evolution. The results help us understand the peculiar dynamics of medicanes and provide guidance for the next generation of weather and climate models.
Emmanouil Flaounas, Stavros Dafis, Silvio Davolio, Davide Faranda, Christian Ferrarin, Katharina Hartmuth, Assaf Hochman, Aristeidis Koutroulis, Samira Khodayar, Mario Marcello Miglietta, Florian Pantillon, Platon Patlakas, Michael Sprenger, and Iris Thurnherr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2809, https://doi.org/10.5194/egusphere-2024-2809, 2024
Short summary
Short summary
Storm Daniel (2023) is one of the most catastrophic ones ever documented in the Mediterranean. Our results highlight the different dynamics and therefore the different predictability skill of precipitation, its extremes and impacts that have been produced in Greece and Libya, the two most affected countries. Our approach concerns a holistic analysis of the storm by articulating dynamics, weather prediction, hydrological and oceanographic implications, climate extremes and attribution theory.
Emmanouil Flaounas, Leonardo Aragão, Lisa Bernini, Stavros Dafis, Benjamin Doiteau, Helena Flocas, Suzanne L. Gray, Alexia Karwat, John Kouroutzoglou, Piero Lionello, Mario Marcello Miglietta, Florian Pantillon, Claudia Pasquero, Platon Patlakas, María Ángeles Picornell, Federico Porcù, Matthew D. K. Priestley, Marco Reale, Malcolm J. Roberts, Hadas Saaroni, Dor Sandler, Enrico Scoccimarro, Michael Sprenger, and Baruch Ziv
Weather Clim. Dynam., 4, 639–661, https://doi.org/10.5194/wcd-4-639-2023, https://doi.org/10.5194/wcd-4-639-2023, 2023
Short summary
Short summary
Cyclone detection and tracking methods (CDTMs) have different approaches in defining and tracking cyclone centers. This leads to disagreements on extratropical cyclone climatologies. We present a new approach that combines tracks from individual CDTMs to produce new composite tracks. These new tracks are shown to correspond to physically meaningful systems with distinctive life stages.
Roberto Ingrosso, Piero Lionello, Mario Marcello Miglietta, and Gianfausto Salvadori
Nat. Hazards Earth Syst. Sci., 23, 2443–2448, https://doi.org/10.5194/nhess-23-2443-2023, https://doi.org/10.5194/nhess-23-2443-2023, 2023
Short summary
Short summary
Tornadoes represent disruptive and dangerous weather events. The prediction of these small-scale phenomena depends on the resolution of present weather forecast and climatic projections. This work discusses the occurrence of tornadoes in terms of atmospheric variables and provides analytical expressions for their conditional probability. These formulas represent a tool for tornado alert systems and for estimating the future evolution of tornado frequency and intensity in climate projections.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
Short summary
Short summary
The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Michele Salmi, Chiara Marsigli, and Manfred Dorninger
Adv. Sci. Res., 19, 29–38, https://doi.org/10.5194/asr-19-29-2022, https://doi.org/10.5194/asr-19-29-2022, 2022
Short summary
Short summary
High resolution, probabilistic weather prediction systems are increasingly able to model lightning activity with unprecedented accuracy. Is the probabilistic approach skillful when applied to localized, deep convection? This work shows that the ensemble prediction system maintained by the German Weather Service is able to provide a useful forecast of lightning activity at a scale of around 200 km and that the probabilistic approach can anticipate possible lack of accuracy in both time and space.
Emmanouil Flaounas, Silvio Davolio, Shira Raveh-Rubin, Florian Pantillon, Mario Marcello Miglietta, Miguel Angel Gaertner, Maria Hatzaki, Victor Homar, Samira Khodayar, Gerasimos Korres, Vassiliki Kotroni, Jonilda Kushta, Marco Reale, and Didier Ricard
Weather Clim. Dynam., 3, 173–208, https://doi.org/10.5194/wcd-3-173-2022, https://doi.org/10.5194/wcd-3-173-2022, 2022
Short summary
Short summary
This is a collective effort to describe the state of the art in Mediterranean cyclone dynamics, climatology, prediction (weather and climate scales) and impacts. More than that, the paper focuses on the future directions of research that would advance the broader field of Mediterranean cyclones as a whole. Thereby, we propose interdisciplinary cooperation and additional modelling and forecasting strategies, and we highlight the need for new impact-oriented approaches to climate prediction.
Mario Marcello Miglietta and Silvio Davolio
Hydrol. Earth Syst. Sci., 26, 627–646, https://doi.org/10.5194/hess-26-627-2022, https://doi.org/10.5194/hess-26-627-2022, 2022
Short summary
Short summary
The main results emerging from the HyMeX SOP1 campaign and in the subsequent research activity in three Italian target areas are highlighted through conceptual models and through the identification of the relevant mesoscale environmental characteristics conducive to heavy rain events.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
Short summary
Short summary
Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
Chiara Marsigli, Elizabeth Ebert, Raghavendra Ashrit, Barbara Casati, Jing Chen, Caio A. S. Coelho, Manfred Dorninger, Eric Gilleland, Thomas Haiden, Stephanie Landman, and Marion Mittermaier
Nat. Hazards Earth Syst. Sci., 21, 1297–1312, https://doi.org/10.5194/nhess-21-1297-2021, https://doi.org/10.5194/nhess-21-1297-2021, 2021
Short summary
Short summary
This paper reviews new observations for the verification of high-impact weather and provides advice for their usage in objective verification. New observations include remote sensing datasets, products developed for nowcasting, datasets derived from telecommunication systems, data collected from citizens, reports of impacts and reports from insurance companies. This work has been performed in the framework of the Joint Working Group on Forecast Verification Research (JWGFVR) of the WMO.
Enzo Papandrea, Stefano Casadio, Elisa Castelli, Bianca Maria Dinelli, and Mario Marcello Miglietta
Atmos. Meas. Tech., 12, 6683–6693, https://doi.org/10.5194/amt-12-6683-2019, https://doi.org/10.5194/amt-12-6683-2019, 2019
Short summary
Short summary
Lee waves have been detected in clear-sky conditions over the Mediterranean Sea using the total column water vapour (TCWV) fields. The products were generated applying the Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) retrieval algorithm to the thermal infrared measurements of the Along Track Scanning Radiometer (ATSR) instrument series. A subset of the occurrences has been compared with both independent observations and model simulations.
Maria Laura Poletti, Francesco Silvestro, Silvio Davolio, Flavio Pignone, and Nicola Rebora
Hydrol. Earth Syst. Sci., 23, 3823–3841, https://doi.org/10.5194/hess-23-3823-2019, https://doi.org/10.5194/hess-23-3823-2019, 2019
Short summary
Short summary
In this work a probabilistic rainfall nowcasting model, a non-hydrostatic high-resolution numerical weather prediction (NWP) model corrected with data assimilation, and a distributed hydrological model are used together with radar observations to implement a hydrological nowcasting chain. This chain is used to obtain a useful discharge prediction in small catchments with a time horizon of 2–8 h.
Thomas Gastaldo, Virginia Poli, Chiara Marsigli, Pier Paolo Alberoni, and Tiziana Paccagnella
Nonlin. Processes Geophys., 25, 747–764, https://doi.org/10.5194/npg-25-747-2018, https://doi.org/10.5194/npg-25-747-2018, 2018
Short summary
Short summary
Accuracy of numerical weather prediction forecasts is strongly related to the quality of initial conditions employed. To improve them, it seems advantageous to use radar reflectivity observations because of their high spatial and temporal resolution. This is tested in a high-resolution model whose domain covers Italy. Results show that the employment of reflectivity observations improves precipitation forecast accuracy, but the positive impact is lost after a few hours of forecast.
Matteo Vasconi, Andrea Montani, and Tiziana Paccagnella
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npg-2018-21, https://doi.org/10.5194/npg-2018-21, 2018
Revised manuscript has not been submitted
Andrea Tateo, Mario Marcello Miglietta, Francesca Fedele, Micaela Menegotto, Alfonso Monaco, and Roberto Bellotti
Adv. Sci. Res., 14, 95–102, https://doi.org/10.5194/asr-14-95-2017, https://doi.org/10.5194/asr-14-95-2017, 2017
Lidia Bressan, Andrea Valentini, Tiziana Paccagnella, Andrea Montani, Chiara Marsigli, and Maria Stefania Tesini
Adv. Sci. Res., 14, 77–84, https://doi.org/10.5194/asr-14-77-2017, https://doi.org/10.5194/asr-14-77-2017, 2017
Short summary
Short summary
This study presents the sensitivity of an oceanic model of the Adriatic Sea to the horizontal resolution and to the meteorological forcing. The model is run with two different configurations and with two horizontal grids at 1 and 2 km resolution. To study the influence of the meteorological forcing, the two storms have been reproduced by running ROMS in ensemble mode. Possible optimizations of the model set-up are deduced by the comparison of the different run outputs.
Umberto Rizza, Francesca Barnaba, Mario Marcello Miglietta, Cristina Mangia, Luca Di Liberto, Davide Dionisi, Francesca Costabile, Fabio Grasso, and Gian Paolo Gobbi
Atmos. Chem. Phys., 17, 93–115, https://doi.org/10.5194/acp-17-93-2017, https://doi.org/10.5194/acp-17-93-2017, 2017
P. Stocchi and S. Davolio
Adv. Sci. Res., 13, 7–12, https://doi.org/10.5194/asr-13-7-2016, https://doi.org/10.5194/asr-13-7-2016, 2016
Short summary
Short summary
Three heavy rain events over NE Alps were simulated using a high-resolution model to evaluate the effect of the SST of the Adriatic Sea.
These preliminary results show that SST influences the surface heat fluxes over the sea, but does not necessary affect the vertical integrated water vapour flux across the coast.
The response of heavy precipitation to a SST change is complex: SST affects the PBL characteristics and thus the flow dynamics and its interaction with orography.
R. Ferretti, E. Pichelli, S. Gentile, I. Maiello, D. Cimini, S. Davolio, M. M. Miglietta, G. Panegrossi, L. Baldini, F. Pasi, F. S. Marzano, A. Zinzi, S. Mariani, M. Casaioli, G. Bartolini, N. Loglisci, A. Montani, C. Marsigli, A. Manzato, A. Pucillo, M. E. Ferrario, V. Colaiuda, and R. Rotunno
Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, https://doi.org/10.5194/hess-18-1953-2014, 2014
A. Buzzi, S. Davolio, P. Malguzzi, O. Drofa, and D. Mastrangelo
Nat. Hazards Earth Syst. Sci., 14, 1325–1340, https://doi.org/10.5194/nhess-14-1325-2014, https://doi.org/10.5194/nhess-14-1325-2014, 2014
F. De Biasio, M. M. Miglietta, S. Zecchetto, and A. della Valle
Adv. Sci. Res., 11, 41–48, https://doi.org/10.5194/asr-11-41-2014, https://doi.org/10.5194/asr-11-41-2014, 2014
I. M. Mazzitelli, M. Cassol, M. M. Miglietta, U. Rizza, A. M. Sempreviva, and A. S. Lanotte
Nonlin. Processes Geophys., 21, 489–501, https://doi.org/10.5194/npg-21-489-2014, https://doi.org/10.5194/npg-21-489-2014, 2014
C. Marsigli, A. Montani, and T. Paccagnella
Nonlin. Processes Geophys., 21, 393–403, https://doi.org/10.5194/npg-21-393-2014, https://doi.org/10.5194/npg-21-393-2014, 2014
A. Ceppi, G. Ravazzani, A. Salandin, D. Rabuffetti, A. Montani, E. Borgonovo, and M. Mancini
Nat. Hazards Earth Syst. Sci., 13, 1051–1062, https://doi.org/10.5194/nhess-13-1051-2013, https://doi.org/10.5194/nhess-13-1051-2013, 2013
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
Probabilistic precipitation downscaling for ungauged mountain sites: a pilot study for the Hindu Kush Karakoram Himalaya
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
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.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2805, https://doi.org/10.5194/egusphere-2024-2805, 2024
Short summary
Short summary
We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Karakoram Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical / machine learning techniques. Our results show this approach outperforms traditional methods, especially in remote, ungauged areas, suggesting it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
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.
Cited articles
Adams, T. and Ostrowski, J.: Short lead-time hydrologic ensemble forecasts from numerical weather prediction model ensembles. Proc. World Environment and Water Resources Congress, Providence, RI, American Society of Civil Engineers, 16–20 May 2010, 2294–2304, 2010.
Addor, N., Jaun, S., Fundel, F., and Zappa, M.: An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios, Hydrol. Earth Syst. Sci., 15, 2327–2347, https://doi.org/10.5194/hess-15-2327-2011, 2011.
Bauer, H.-S., Weusthoff, T., Dorninger, M., Wulfmeyer, V., Schwitalla, T., Gorgas, T., Arpagaus, M., and Warrach-Sagi, K.: Predictive skill of a subset of the D-PHASE multi-model ensemble in the COPS region, Q. J. Roy. Meteor. Soc., 137, 287–305, 2011.
Bogner, K., Cloke, H. L., Pappenberger, F., de Roo, A., and Thielen, J.: Improving the evaluation of hydrological multi-model forecast performance in the upper Danube catchment, Int. J. River Basin Manag., 10, 1–12, 2011.
Bougeault, P., Toth, Z., Bishop, C., Brown, B., Burridge, D., Chen, D. H., Ebert, B., Fuentes, M., Hamill, T. M., Mylne, K., Nicolau, J., Paccagnella, T., Park, Y. Y., Parsons, D., Raoult, B., Schuster, D., Dias, P. S., Swinbank, R., Takeuchi, Y., Tennant, W., Wilson, L., and Worley, S.: The THORPEX Interactive Grand Global Ensemble, B. Am. Meteorol. Soc., 91, 1059–1072, 2010.
Bowler, N. E., Arribas, A., and Mylne, K. R.: The benefits of multianalysis and poor man's ensembles, Mon. Weather Rev., 136, 4113–4129, 2008.
Buizza, R.: The value of probabilistic prediction, Atmos. Sci. Lett., 9, 36–42, 2008.
Cloke, H. L. and Pappenberger, F.: Ensemble flood forecasting: a review, J. Hydrol., 375, 613–626, 2009.
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, 2011.
Davolio, S., Miglietta, M. M., Diomede, T., Marsigli, C., Morgillo, A., and Moscatello, A.: A meteo-hydrological prediction system based on a multi-model approach for precipitation forecasting, Nat. Hazards Earth Syst. Sci., 8, 143–159, https://doi.org/10.5194/nhess-8-143-2008, 2008.
Diomede, T., Davolio, S., Marsigli, C., Miglietta, M. M., Moscatello, A., Papetti, P., Paccagnella, T., Buzzi, A., and Malguzzi, P.: Discharge prediction based on multi-model precipitation forecasts, Meteorol. Atmos. Phys., 101, 245–265, 2008a.
Diomede, T., Marsigli, C., Montani, A., and Paccagnella, T.: A limited-area ensemble prediction system to drive a flood forecasting chain, Proc. of HydroPredict'2008, International Interdisciplinary Conference on Predictions for Hydrology, Ecology, and Water Resources Management – Using Data and Models to Benefit Society, Prague, edited by: Bruthans, J., Kovar, K., and Hrkal, Z., Czech Republic, 15–18 September 2008, 211–214, ISBN 978-80-903635-3-3 publication of the Czech Association of Hydrogeologists, available at: http://web.natur.cuni.cz/hydropredict2008, 2008b.
Diomede T., Marsigli, C., Montani, A., and Paccagnella, T.: Streamflow ensemble forecast driven by COSMO-LEPS for small-size catchments in northern Italy. Proc. HEPEX Workshop on Post-Processing and Downscaling Atmospheric Forecasts for Hydrologic Applications, Toulouse, France, 15–18 June 2009, p. 6, available at: http://hepex.nmpi.net/files/download/workshops/post-processing/Book_Abstracts.pdf), 2009.
Dudhia, J.: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46, 3077–3107, 1989.
Garcia-Moya, J. A., Callado, A., Escribà, P., Santos, C., Santos-Muñoz, D., and Simarro, J.: Predictability of short-range forecasting: a multimodel approach, Tellus A, 63, 550–563, 2011.
Gebhardt, C., Theis, S. E., Paulat, M., and Ben Bouallègue, Z.: Uncertainties in COSMO-DE precipitation forecasts introduced by model perturbations and variation of lateral boundaries, Atmos. Res., 100, 168–177, 2011.
Gouweleeuw, B. T., Thielen, J., Franchello, G., De Roo, A. P. J., and Buizza, R.: Flood forecasting using medium-range probabilistic weather prediction, Hydrol. Earth Syst. Sci., 9, 365–380, https://doi.org/10.5194/hess-9-365-2005, 2005.
Hamill, T., Clark, M., Schaake, J., and Buizza, R.: Second HEPEX Workshop Summary Report, Boulder, Colorado, available at: http://hepex.nmpi.net/files/download/workshops/2nd/HEPEX05-Summary.pdf (last access: 30 May 2013), 2005.
Hapuarachchi, H. A. P., Wang, Q. J., and Pagano, T. C.: A review of advances in flash flood forecasting, Hydrol. Process., 25, 2771–2784, 2011.
Hou, D., Mitchell, K., Toth, Z., Lohmann, D., and Wei, H.: Ensemble streamflow forecasting with the coupled GFS-NOAH modelling system, 3rd HEPEX workshop, Book of Abstracts, edited by: Thielen, J., Bartholmes, J., and Schaake, J., European Commission EUR22861EN, 65–68, 2007.
Houtekamer, P. L., Derome, J., Ritchie, H., and Mitchell, H. L: A system simulation approach to ensemble prediction, Mon. Weather Rev., 124, 1225–1242, 1996.
Iversen, T., Deckmyn, A., Santos, A., Sattler, K., Bremnes, J. B., Feddersen, H., and Frogner, L. L.: Evaluation of GLAMEPS – A proposed multimodel EPS for short range forecasting, Tellus A, 63, 513–530, 2011.
Jasper, K. and Kaufmann, P.: Coupled runoff simulations as validation tools for atmospheric models at the regional scale, Q. J. Roy. Meteor. Soc., 129, 673–692, 2003.
Kain, J. S.: The Kain–Fritsch convective parameterization: An update, J. Appl. Meteorol., 43, 170–181, 2004.
Krishnamurti, T. N., Kistawal, C. M., LaRow, T. E., Bachiochi, D. R., Zhang, Z., Williford, C. E., Gadgil, S., and Surendran, S: Improved weather and seasonal climate forecasts from multimodel superensemble, Science, 285, 1548–1550, 1999.
Krzysztofowicz, R.: Bayesian theory of probabilistic forecasting via deterministic hydrologic model, Water Resour. Res., 35, 2739–2750, 1999.
Liu, Z. and Todini, E.: Towards a comprehensive physically-based rainfall-runoff model, Hydrol. Earth Syst. Sci., 6, 859–881, https://doi.org/10.5194/hess-6-859-2002, 2002.
Marsigli, C.: COSMO-SREPS Priority Project "Short Range Ensemble Prediction System (SREPS): final report, COSMO Technical report, 13, available at: http://www.cosmo-model.org/content/model/documentation/techReports/default.htm (last access: 30 May 2013), 2009.
Marsigli, C., Montani, A., and Paccagnella, T.: A spatial verification method applied to the evaluation of high-resolution ensemble forecasts, Meteorol. Appl., 15, 125–143, 2008.
Marsigli, C., Montani, A., and Paccagnella, T.: Perturbation of initial and boundary conditions for limited-area ensemble: multi-model versus single-model approach, Q. J. Roy. Meteor. Soc., https://doi.org/10.1002/qj.2128, online first, 2013.
Melone, F., Barbetta, S., Diomede, T., Perucacci, S., Rossi, M., Tessarollo, A., and Verdecchia, M.: Review and selection of hydrological models – Integration of hydrological models and meteorological inputs, Resulting from WP1, Action 13, RISK AWARE – INTERREG III B – CADSES, 34 pp., 2005.
Montani, A., Cesari, D., Marsigli, C., and Paccagnella, T.: Seven years of activity in the field of mesoscale ensemble forecasting by the COSMO-LEPS system: main achievements and open challenges, Tellus A, 63, 605–624, 2011.
Mylne, K. R., Evans, R. E., and Clark, R. T.: Multi-model multi-analysis ensemble in quesi-operational medium-range forecasting, Q. J. Roy. Meteor. Soc., 128, 361–384, 2002.
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E. , Chen, F., Ek, M. B., Barlage, M., L. Longuevergne, L., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res., 116, D12109, https://doi.org/10.1029/2010JD015139, 2011.
Palmer, T. N., Barkmeijer, J., Buizza, R., and Petroliagis, T.: The ECMWF ensemble prediction system, Meteorol. Appl., 4, 301–304, 1997.
Pappenberger, F., Beven, K. J., Hunter, N. M., Bates, P. D., Gouweleeuw, B. T., Thielen, J., and de Roo, A. P. J.: Cascading model uncertainty from medium range weather forecasts (10 days) through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS), Hydrol. Earth Syst. Sci., 9, 381–393, https://doi.org/10.5194/hess-9-381-2005, 2005.
Park, Y. Y., Buizza, R., and Leutbecher, M.: TIGGE: preliminary results on comparing and combining ensembles, Q. J. Roy. Meteor. Soc., 134, 2029–2050, 2008.
Randrianosolo, A., Ramos, M. H., Thirel, G., Andréassian, V., and Martin, E.: Comparing the scores of hydrological ensemble forecasts issued by two different hydrological models, Atmos. Sci. Lett., 11, 100–107, 2010.
Ranzi, R., Bacchi, B., Ceppi, A., Cislaghi, M., Ehret, U., Jaun, S., Marx, A., Hegg, C., and Zappa, M.: Real-time demonstration of hydrological ensemble forecasts in MAP D-PHASE, La-Huille-Blanche, 5, 95–103, https://doi.org/10.1051/lhb/2009061, 2009.
Ritter, B. and Geleyn, J. F.: A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations, Mon. Weather Rev., 120, 303–325, 1992.
Rotach, M. W., Ambrosetti, P., Ament, F., Appenzeller, C., Arpagaus, M., Bauer, M. S., Behrendt, A., Bouttier, F., Buzzi, A., Corazza, M., Davolio, S., Denhard, M., Dorninger, M., Fontannaz, L., Frick, J., Fundel, F., Germann, U., Gorgas, T., Hegg, C., Hering, A., Keil, C., Liniger, M. A., Marsigli, C., McTaggart-Cowan, R., Montani, A., Mylne, K., Ranzi, R., Richard, E., Rossa, A., Santos-Muñoz, D., Schär, C., Seity, Y., Staudinger, M., Stoll, M., Volkert, H., Walser, A., Wang, Y., Werhahn, J., Wulfmeyer, V., and Zappa, M.: MAP D-PHASE: Real-time Demonstration of Weather Forecast Quality in the Alpine Region, B. Am. Meteorol. Soc., 90, 1321–1336, 2009.
Rotach, M. W., Arpagaus, M., Dorninger, M., Hegg, C., Montani, A., and Ranzi, R.: Uncertainty propagation for flood forecasting in the Alps: different views and impacts from MAP D-PHASE, Nat. Hazards Earth Syst. Sci., 12, 2439–2448, https://doi.org/10.5194/nhess-12-2439-2012, 2012.
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 Technical note NCAR/TN-475+STR, 2008.
Steppeler, J., Doms, G., Schättler, U., Bitzer, H. W., Gassmann, A., Damrath, U., and Gregoric, G.: Meso-gamma scale forecasts using the nonhydrostatic model LM, Meteorol. Atmos. Phys., 82, 75–96, 2003.
Thielen, J., Bartholmes, J., Ramos, M.-H., and de Roo, A.: The European Flood Alert System – Part 1: Concept and development, Hydrol. Earth Syst. Sci., 13, 125–140, https://doi.org/10.5194/hess-13-125-2009, 2009.
Thirel, G., Rousset-Regimbeau, F., Martin, E., and Habets, F.: On the impact of short-range meteorological forecasts for ensemble streamflow predictions, J. Hydrometeorol., 9, 1301–1317, 2008.
Thompson, G., Rasmussen, R. M., and Manning, K.: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis, Mon. Weather Rev., 132, 519–542, 2004.
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in large-scale models, Mon. Weather Rev., 117, 1779–1800, 1989.
Todini, E. , and Ciarapica, L.: The TOPKAPI model, in: Mathematical models of large watershed hydrology, edited by: Singh, V. P. and Frevert, D. K., Littleton, Colorado, USA, Water Resources Publications, 914 pp., 2002.
Toth, Z., and Kalnay, E.: Ensemble forecasting at NCEP and the breeding method, Mon. Weather Rev., 125, 3297–3319, 1997.
Velázquez, J. A., Anctil, F., Ramos, M. H., and Perrin, C.: Can a multi-model approach improve hydrological ensemble forecasting? A study on 29 French catchments using 16 hydrological model structures, Adv. Geosci., 29, 33–42, https://doi.org/10.5194/adgeo-29-33-2011, 2011.
Vié, B., Molinié, G., Nuissier, O., Vincendon, B., Ducrocq, V., Bouttier, F., and Richard, E.: Hydro-meteorological evaluation of a convection-permitting ensemble prediction system for Mediterranean heavy precipitating events, Nat. Hazards Earth Syst. Sci., 12, 2631–2645, https://doi.org/10.5194/nhess-12-2631-2012, 2012.
Wei, M. Z., Toth, Z., Wobus, R., Zhu, Y. J., Bishop, C. H., and Wang, X. G.: Ensemble transform Kalman filter-based ensemble perturbations in an operational global prediction system at NCEP, Tellus A, 58, 28–44, 2006.
Weisman, M. L., Davies, C., Wang, W., Manning, K. W., and Klemp, J. B.: Experiences with 0-36-h explicit convective forecasts with the WRF-ARW model, Weather Forecast., 23, 407–437, 2008.
Weusthoff, T., Ament, F., Arpagaus, M., and Rotach, M. W.: Assessing the benefits of convection permitting models by Neighborhood Verification – examples from MAP D-PHASE, Mon. Weather Rev., 138, 3418–3433, 2010.
Zampieri, M., Malguzzi, P., and Buzzi, A.: Sensitivity of quantitative precipitation forecasts to boundary layer parameterization: a flash flood case study in the Western Mediterranean, Nat. Hazards Earth Syst. Sci., 5, 603–612, https://doi.org/10.5194/nhess-5-603-2005, 2005.
Zappa, M., Beven, K. J., Bruen, M., Cofino, A. S., Kok, K., Martin, E., Nurmi, P., Orfila, B., Roulin, E., Schröter, K., Seed, A., Szturc, J., Vehviläinen, B., Germann, U., and Rossa, A.: Propagation of uncertainty from observing systems and NWP into hydrological models: COST-731 Working Group 2, Atmos. Sci. Lett., 11, 83–91, 2010.
Zappa, M., Jaun, S., Germann, U., Walser, A., and Fundel, F.: Superposition of three sources of uncertainties in operational flood forecasting chains, Atmos. Res., 100, 246–262, 2011.
